diff --git a/spaces/0x876/Yotta_Mix/app.py b/spaces/0x876/Yotta_Mix/app.py
deleted file mode 100644
index b60a087620a806fea130bedcd6940bef75fa3337..0000000000000000000000000000000000000000
--- a/spaces/0x876/Yotta_Mix/app.py
+++ /dev/null
@@ -1,3 +0,0 @@
-import gradio as gr
-
-gr.Interface.load("models/CompVis/stable-diffusion-v1-4").launch()
diff --git a/spaces/0x90e/ESRGAN-MANGA/process_image.py b/spaces/0x90e/ESRGAN-MANGA/process_image.py
deleted file mode 100644
index ca687c0329f171f83db2bf9c4a3bb2d6ffadfda9..0000000000000000000000000000000000000000
--- a/spaces/0x90e/ESRGAN-MANGA/process_image.py
+++ /dev/null
@@ -1,31 +0,0 @@
-import os
-import gradio as gr
-from run_cmd import run_cmd
-from PIL import Image
-import tempfile
-import uuid
-import numpy as np
-
-temp_path = tempfile.gettempdir()
-
-def inference(img, size, type):
-    if not img:
-        raise Exception("No image!")
-
-    OUTPUT_PATH = os.path.join(temp_path, f"{str(uuid.uuid4())[0:12]}_{size}.png")
-    
-    img.save(OUTPUT_PATH)
-
-    if type == "Manga":
-        run_cmd(f"python inference_manga_v2.py {OUTPUT_PATH}")
-    else:
-        run_cmd(f"python inference.py {OUTPUT_PATH} {type}")
-
-    img_out = Image.open(OUTPUT_PATH)
-
-    if size == "x2":
-        img_out = img_out.resize((img_out.width // 2, img_out.height // 2), resample=Image.BICUBIC)
-
-    img_out = np.array(img_out)
-
-    return img_out, gr.File.update(value=OUTPUT_PATH)
\ No newline at end of file
diff --git a/spaces/1acneusushi/gradio-2dmoleculeeditor/Skyrim-Simpackdll.md b/spaces/1acneusushi/gradio-2dmoleculeeditor/Skyrim-Simpackdll.md
deleted file mode 100644
index e03bcb747aeca5fb2139d3b4c835094772e29991..0000000000000000000000000000000000000000
--- a/spaces/1acneusushi/gradio-2dmoleculeeditor/Skyrim-Simpackdll.md
+++ /dev/null
@@ -1,88 +0,0 @@
-## Skyrim Simpackdll
-
-
-
- 
-
- ![Skyrim Simpackdll](https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcR3PTHDbn7juqcw8p6GQesIZvxzdiwnWWuAEkPfULQhrCJKwHINNl6rc5c)
-
- 
-
- 
-
-**LINK ===> [https://jinyurl.com/2tA0aO](https://jinyurl.com/2tA0aO)**
-
-
-
- 
-
- 
-
- 
-
- 
-
- 
-
-# How to Fix Skyrim Simpackdll Error
-
- 
-
-If you are trying to play Skyrim on your PC, you may encounter an error message that says "simpack.dll is missing" or "simpack.dll not found". This error means that your system does not have the simpack.dll file, which is a dynamic link library (DLL) file that is required by the Skyrim game. The simpack.dll file contains various functions and routines that are used by the game to perform simulations of mechanical systems, such as vehicle dynamics, suspension systems, and powertrain systems.
-
- 
-
-The simpack.dll error can be caused by various reasons, such as a corrupt or missing DLL file, conflicts with other software, or malware infections. In this article, we will show you how to fix the Skyrim simpackdll error by following these steps:
-
- 
-
-1. Reinstall the Skyrim game. The easiest way to fix the simpack.dll error is to reinstall the Skyrim game on your PC. This will ensure that you have all the necessary files and components for the game to run properly. To reinstall the game, you need to uninstall it first from your Control Panel or Settings app, and then install it again from your original source, such as a CD/DVD or a digital download.
-
-2. Download and restore the simpack.dll file. If reinstalling the game does not work, you can try to download and restore the simpack.dll file manually. You can get the file from a reliable source, such as [DLLme.com](https://www.dllme.com/dll/files/simpack), which offers free DLL downloads for various software applications. To download and restore the simpack.dll file, follow these steps:
-
-    - Go to [DLLme.com](https://www.dllme.com/dll/files/simpack) and search for "simpack.dll".
-
-    - Click on the "Download" button and save the file to your computer.
-
-    - Copy and paste the file to the folder where Skyrim is installed. The default location is C:\Program Files (x86)\Steam\steamapps\common\Skyrim.
-
-    - Restart your computer and launch Skyrim.
-
-3. Scan your PC for malware. Sometimes, the simpack.dll error can be caused by malware infections that may damage or delete the DLL file. To scan your PC for malware, you need to use a reputable antivirus or anti-malware software, such as [Malwarebytes](https://www.malwarebytes.com/), which can detect and remove various types of malware threats from your system. To scan your PC for malware, follow these steps:
-
-    - Download and install Malwarebytes from [Malwarebytes.com](https://www.malwarebytes.com/).
-
-    - Launch Malwarebytes and click on the "Scan" button.
-
-    - Wait for the scan to complete and review the results.
-
-    - If any malware is detected, click on the "Quarantine" button to remove them.
-
-    - Restart your computer and launch Skyrim.
-
-4. Update your drivers and Windows. Another possible cause of the simpack.dll error is outdated or incompatible drivers or Windows updates. Drivers are software components that allow your hardware devices to communicate with your operating system. Windows updates are software patches that fix bugs and improve security and performance of your system. To update your drivers and Windows, follow these steps:
-
-    - Go to Device Manager by pressing Windows + X keys and selecting Device Manager from the menu.
-
-    - Expand each category of devices and look for any yellow exclamation marks or red crosses.
-
-    - If you find any, right-click on them and select Update driver.
-
-    - Follow the on-screen instructions to install the latest drivers for your devices.
-
-    - Go to Settings by pressing Windows + I keys and selecting Settings from the menu.
-
-    - Click on Update & Security and then on Windows Update.
-
-    - Click on Check for updates and install any available updates for your system.
-
-<145887f19f
-
-
-
-
-
-
-
-
-
diff --git a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Cle De Licence Malwarebytes Anti Malware Gratuit Tlchargez Et Installez Le Logiciel En Quelques Minutes.md b/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Cle De Licence Malwarebytes Anti Malware Gratuit Tlchargez Et Installez Le Logiciel En Quelques Minutes.md
deleted file mode 100644
index a5cf50a7d374403dad94e4e51f1d92dce47bcae3..0000000000000000000000000000000000000000
--- a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Cle De Licence Malwarebytes Anti Malware Gratuit Tlchargez Et Installez Le Logiciel En Quelques Minutes.md	
+++ /dev/null
@@ -1,113 +0,0 @@
-<br />
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- <h2>Introduction</h2>
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-<p>Malwarebytes Anti Malware is a cyber security software that protects your device from malware, viruses, ransomware, spyware, adware, trojans, and other online threats. It uses multiple layers of malware-crushing technology, including real-time protection, artificial intelligence, behavior analysis, and web filtering. It can detect and remove threats that other antivirus programs may miss or overlook. It can also work alongside your existing antivirus software to provide an extra layer of security.</p>
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- <h3>How to get a free license key for Malwarebytes Anti Malalare?</h3>
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-</ul>
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-<h3>Download and install Malwarebytes Anti Malalare</h3>
-<p>To download and install Malwarebytes Anti Malalare on your device, follow these steps:</p>
-<ol>
-```html lare.</li>
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-</ol>
- <h3>Enter the free license key</h3>
-<p>To activate the premium features of Malwarebytes Anti Malalare with a free license key, follow these steps:</p>
-<ol>
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-<li>You will see a confirmation message that your license key has been activated and your premium features have been unlocked.</li>
-</ol>
- <h3>Enjoy the full features of Malwarebytes Anti Malalare</h3>
-<p>Now that you have activated the premium features of Malwarebytes Anti Malalare with a free license key, you can enjoy the full benefits of this powerful and reliable cyber security software. You can scan and remove malware from your device in seconds, protect your device from ransomware attacks, block malicious websites and downloads, and secure your online privacy with VPN and anti-tracking features. You can also customize your settings, manage your devices, and access support and updates from Malwarebytes.</p>
- <h2>Conclusion</h2>
-<h3>Summary of the main points</h3>
-<p>In this article, we have shown you how to get a free license key for Malwarebytes Anti Malalare, a cyber security software that protects your device from malware, viruses, ransomware, spyware, adware, trojans, and other online threats. We have also explained what Malwarebytes Anti Malalare is, why you need a license key for it, and what features it offers. We have also provided a step-by-step guide on how to download, install, and activate Malwarebytes Anti Malalare with a free license key.</p>
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-```html lare?</b></li>
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-</ul>
- </p> 0a6ba089eb<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/DVDIdle Pro v5.9.8.3 (precracked) free download The ultimate tool for DVD playback enhancement.md b/spaces/1acneusushi/gradio-2dmoleculeeditor/data/DVDIdle Pro v5.9.8.3 (precracked) free download The ultimate tool for DVD playback enhancement.md
deleted file mode 100644
index 01d280ab3b08a95486656437b2670329b8bfdd23..0000000000000000000000000000000000000000
--- a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/DVDIdle Pro v5.9.8.3 (precracked) free download The ultimate tool for DVD playback enhancement.md	
+++ /dev/null
@@ -1,90 +0,0 @@
-<br />
-<h1>DVDIdle Pro v5.9.8.3 (precracked) free download</h1>
-<p>Do you love watching DVD movies on your PC but hate the annoying region codes and copy protections that prevent you from enjoying them fully? Do you want to extend the lifetime of your DVD drive by reducing its wear and tear? If you answered yes to any of these questions, then you need DVDIdle Pro, a powerful software that combines the functionality of DVD Region-Free and DVDIdle into one efficient program.</p>
-<h2>DVDIdle Pro v5.9.8.3 (precracked) free download</h2><br /><p><b><b>Download File</b> &#9734; <a href="https://byltly.com/2uKzKG">https://byltly.com/2uKzKG</a></b></p><br /><br />
-<h2>What is DVDIdle Pro and why do you need it?</h2>
-<p>DVDIdle Pro is a software that helps you to watch and copy any DVD movie on any DVD drive, regardless of the region code or the copy protection. It works in the background to provide a smart read-ahead cache for your DVD player, saving the DVD data that will be played soon onto your hard disk or RAM cache, and feeding it to your DVD player when needed. This way, your DVD drive can take a rest and work less, extending its lifetime by up to 800 percent.</p>
-<h3>DVDIdle Pro features</h3>
-<p>DVDIdle Pro has many features that make it a must-have software for any DVD lover. Some of these features are:</p>
-<ul>
-<li>It supports region-protected (RPC2) DVD drives, and does not require any firmware modifications.</li>
-<li>It works with all software DVD players, such as PowerDVD, WinDVD, etc.</li>
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-</ul>
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-</ul>
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-<p>Now that you have downloaded and installed DVDIdle Pro on your PC, you might be wondering how to use it effectively. Well, it's very easy and simple as well. Just follow these steps:</p>
-<h3>Step 1: Launch DVDIdle Pro</h3>
-<p>The first thing you need to do is launch DVDIdle Pro from your desktop or start menu. You will see a small icon in your system tray that indicates that the program is running in the background.</p>
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diff --git a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Download Spiderman Friend Or Foe Iso Pc [REPACK].md b/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Download Spiderman Friend Or Foe Iso Pc [REPACK].md
deleted file mode 100644
index 06ce0fc851b446a68dd8f25694c5a119772a7bd1..0000000000000000000000000000000000000000
--- a/spaces/1acneusushi/gradio-2dmoleculeeditor/data/Download Spiderman Friend Or Foe Iso Pc [REPACK].md	
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diff --git a/spaces/1gistliPinn/ChatGPT4/Examples/Alertpay-Paypal Money Hack V4 - [full UPDATED Version].md b/spaces/1gistliPinn/ChatGPT4/Examples/Alertpay-Paypal Money Hack V4 - [full UPDATED Version].md
deleted file mode 100644
index fe3132d67111f75a138e8edbf3ee5f87ad46356b..0000000000000000000000000000000000000000
--- a/spaces/1gistliPinn/ChatGPT4/Examples/Alertpay-Paypal Money Hack V4 - [full UPDATED Version].md	
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deleted file mode 100644
index f802e8388c61eeaf75c732ccf19076b72aff684c..0000000000000000000000000000000000000000
--- a/spaces/1gistliPinn/ChatGPT4/Examples/Descarga wifislax 4.3 torrent todo lo que necesitas saber sobre esta versin de Wifislax.md	
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-<p>Para comenzar a usar el cliente, lo primero que tenemos que hacer es proceder con su <strong>descarga e instalación</strong> en nuestro ordenador. Por suerte qBittorrent es un software multiplataforma de código abierto y gratuito que podemos descargar desde su página web oficial. Por lo tanto, lo único que tenemos que hacer para descargar la herramienta es seguir el enlace anterior y elegir la versión del programa que se adapte a nuestro equipo en cuanto a sistema operativo y arquitectura utilizada.</p>
-<p>Una vez hecho esto, se nos descargará en nuestro disco duro un archivo .exe, por lo que, lo único que tendremos que hacer para su instalación es doble clic sobre él. El proceso es muy muy sencillo, ya que únicamente tendremos que elegir el idioma de instalación y la ruta donde queremos instalarlo y en tan solo unos instantes veremos cómo la herramienta está lista para empezar a usarla.</p>
-<p>Lanzamos qBittorrent en nuestro equipo y veremos cómo cuenta con una interfaz muy limpia y con casi todas las opciones más importantes a mano. Y decimos «casi», porque lo cierto es que, aunque el cliente incluye su propio <strong>motor de búsqueda</strong>, éste no viene activado por defecto. Por lo tanto, lo primero que debemos hacer es activarlo.</p>
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-<p>Desde las opciones de configuración de la herramienta también podemos encontrar otros ajustes interesantes para configurar qBittorrent a nuestro gusto. Para ello, únicamente tenemos que hacer clic sobre el icono del engranaje que encontramos en la parte superior. Esto nos abrirá una ventana en la que tendremos un panel izquierdo donde aparecen las opciones del menú.</p>
-<p>Entre ellas cabe destacar la opción <strong>Descargas</strong>, donde podremos configurar, entre otras cosas, la carpeta donde queremos que se nos guarden todos los archivos descargados desde qBittorrent.</p>
-<p>Dentro de la opción <strong>BitTorrent</strong> podemos configurar las descargas y las subidas activas, es decir, el número de descargas y subidas de archivos que queremos que estén activas como máximo al mismo tiempo.</p>
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-<p>Además de la búsqueda y descarga de archivos desde el propio motor de búsqueda de qBittorrent, la herramienta nos ofrece la posibilidad de <strong>utilizar archivos torrent</strong> y <strong>enlaces magnet</strong>. Lo cierto es que el proceso es similar, pero en este caso, lo primero que tendremos que hacer es buscar en una página de archivos torrent el fichero que queremos descargar.</p>
-<p>Una vez encontrado y siempre asegurándonos que es un sitio y archivo de confianza, descargamos el archivo .torrent en nuestro ordenador. Ahora, lo siguiente que debemos hacer es asociar la apertura de archivos de este tipo con qBittorrent, ya que, de esta manera, lo único que tendremos que hacer para que comience a descargarse es hacer doble clic sobre el archivo .torrent.</p>
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-<p>Y si lo que queremos es descargar archivos a través de un enlace magnet, qBittorrent también nos da esa opción. Lo único que tenemos que hacer es ir a la opción <strong>Archivo > Añadir enlace torrent</strong> y copiar el enlace magnet en el cuadro de texto de la ventana que se nos abre a continuación. Por último, pulsamos en Descargar y el proceso de descarga comenzará automáticamente.</p>
-<p>Aunque la aplicación funcione correctamente, lo cierto es que en un momento determinado nos podemos encontrar con que los archivos no se descargan o lo hacen a una velocidad muy lenta. En este caso, hay varias cosas que debemos revisar para tratar de encontrar la causa del problema y la solución.</p>
-<p>Una de las causas de que no se realicen las descargas es que el <strong>firewall</strong> de Windows o de cualquier otra herramienta de seguridad, esté bloqueando las descargas a través de qBittorrent. Por lo tanto, podemos probar a desactivar de manera temporal la herramienta de seguridad y comprobar si de esta manera las descargas se realizan con normalidad.</p>
-<p>Otro aspecto para revisar son los <strong>puertos de nuestro router</strong>, para verificar que todos los necesarios para las conexiones de qBittorrent está abiertos y correctamente redirigidos al cliente. Es importante también revisar que el protocolo <strong>UPnP</strong> de nuestro router esté correctamente activado, puesto que nos ayudará a resolver ciertos problemas de conexión.</p>
-<p>También es recomendable hacer un análisis en busca de cualquier tipo de <strong>virus y malware</strong> a nuestro equipo, para evitar que cualquier tipo de amenaza esté usando la red para otros menesteres o simplemente esté usando los recursos de nuestro equipo y no deje que se dediquen a las descargas a través de qBittorrent.</p>
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diff --git a/spaces/1gistliPinn/ChatGPT4/Examples/Free Netflix Download Premium 9.2 Code File [WORK].md b/spaces/1gistliPinn/ChatGPT4/Examples/Free Netflix Download Premium 9.2 Code File [WORK].md
deleted file mode 100644
index 02f3193ec1e6e11e3cc29f2579aec91a9654e50f..0000000000000000000000000000000000000000
--- a/spaces/1gistliPinn/ChatGPT4/Examples/Free Netflix Download Premium 9.2 Code File [WORK].md	
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diff --git a/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/12 Locks II A Puzzle Game with 3 Different Rooms and 12 Locks Each - APK Download.md b/spaces/1pelhydcardo/ChatGPT-prompt-generator/assets/12 Locks II A Puzzle Game with 3 Different Rooms and 12 Locks Each - APK Download.md
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-<h1>12 Locks II: A Fun and Challenging Puzzle Game for Android</h1>
-<p>If you are looking for a puzzle game that will test your logic, creativity and patience, you might want to try 12 Locks II. This is a sequel to the popular 12 Locks game by RUD Present, a developer that specializes in creating unique and colorful games with plasticine graphics. In this article, we will tell you everything you need to know about 12 Locks II, including what it is, how to play it, why you should download it and how to download it.</p>
- <h2>What is 12 Locks II?</h2>
-<p>12 Locks II is a puzzle game that challenges you to find all the keys to unlock 12 doors in different rooms. Each room has its own theme and style, such as a kitchen, a bathroom, a spaceship, a pirate ship and more. You will have to explore the rooms, interact with various objects, solve mini-puzzles and collect clues to find the keys.</p>
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- <h3>The premise of the game</h3>
-<p>The game follows the adventures of a plasticine man who has a bad habit of locking all doors to 12 locks. As a result, he finds himself in different awkward situations all the time. For example, he might get stuck in a toilet, a fridge or a washing machine. Your task is to help him escape from these predicaments by unlocking the doors.</p>
- <h3>The features of the game</h3>
-<p>Some of the features that make 12 Locks II stand out are:</p>
-<ul>
-<li>The game has colorful and detailed graphics made with plasticine. The rooms are full of funny and quirky details that add to the charm and humor of the game.</li>
-<li>The game has cheerful and catchy music that matches the mood of each room. The sound effects are also realistic and amusing.</li>
-<li>The game has simple and intuitive controls. You just need to tap on the screen to interact with objects and drag items to use them.</li>
-<li>The game has challenging and varied puzzles that require logic, creativity and attention to detail. Some puzzles are easy and straightforward, while others are more complex and tricky. You will have to use your brain and your imagination to solve them.</li>
-<li>The game has no time limit or penalties. You can play at your own pace and enjoy the process of finding solutions. You can also use hints if you get stuck.</li>
-</ul>
- <h2>How to play 12 Locks II?</h2>
-<p>Playing 12 Locks II is easy and fun. Here are some tips on how to play it:</p>
- <h3>The controls of the game</h3>
-<p>To play 12 Locks II, you just need to tap on the screen to interact with objects and drag items to use them. You can also zoom in or out by pinching the screen. To move between rooms, you can swipe left or right on the screen. To access the inventory or the menu, you can tap on the icons at the bottom of the screen.</p>
- <h3>The tips and tricks of the game</h3>
-<p>To solve the puzzles in 12 Locks II, you need to pay attention to everything in the rooms. Here are some tips and tricks that might help you:</p>
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-<ul>
-<li>Look for clues and hints in the environment. For example, you might find codes, symbols, colors, shapes, patterns, directions, numbers or words that can help you unlock the locks.</li>
-<li>Use logic and common sense to figure out the connections between the clues and the locks. For example, you might have to match colors, shapes, numbers or words to the corresponding locks.</li>
-<li>Use trial and error to test your hypotheses. For example, you might have to try different combinations of codes, symbols or directions to find the right one.</li>
-<li>Use creativity and imagination to think outside the box. For example, you might have to use unconventional methods or items to solve some puzzles.</li>
-<li>Don't be afraid to experiment and explore. For example, you might have to tap on everything, move objects around, combine items or use items in unexpected ways.</li>
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-<p>12 Locks II is a game that will keep you entertained and challenged for hours. Here are some reasons why you should download it:</p>
- <h3>The benefits of playing 12 Locks II</h3>
-<p>Playing 12 Locks II can have many benefits for your brain and your mood. Some of them are:</p>
-<ul>
-<li>It can improve your cognitive skills, such as memory, attention, concentration, logic, problem-solving and creativity.</li>
-<li>It can stimulate your curiosity and imagination, as you discover new rooms and puzzles.</li>
-<li>It can provide you with a sense of achievement and satisfaction, as you unlock the doors and progress in the game.</li>
-<li>It can reduce your stress and anxiety, as you focus on the game and forget about your worries.</li>
-<li>It can make you laugh and smile, as you enjoy the humor and fun of the game.</li>
-</ul>
- <h3>The reviews and ratings of the game</h3>
-<p>12 Locks II is a game that has received positive reviews and ratings from players and critics alike. Some of them are:</p>
-<table>
-<tr><th>Name</th><th>Rating</th><th>Review</th></tr>
-<tr><td>Google Play Store</td><td>4.5/5 stars</td><td>"This game is awesome! It's challenging but not frustrating. The graphics are cute and funny. The music is catchy. I love it!"</td></tr>
-<tr><td>App Store</td><td>4.7/5 stars</td><td>"This game is amazing! It's so creative and original. The puzzles are clever and fun. The rooms are colorful and detailed. I recommend it!"</td></tr>
-<tr><td>New Scientist</td><td>8/10 points</td><td>"This game is a delight! It's a perfect blend of logic, creativity and humor. The plasticine graphics are charming and quirky. The puzzles are varied and engaging."</td></tr>
-<tr><td>The Sun</td><td>9/10 points</td><td>"This game is a blast! It's a great way to kill time and exercise your brain. The rooms are full of surprises and jokes. The puzzles are challenging but fair."</td></tr>
-</table>
- <h2>How to download 12 Locks II?</h2>
-<p>If you are interested in playing 12 Locks II, you can download it easily from your preferred app store. Here are some steps on how to do it:</p>
- <h3>The requirements of the game</h3>
-<p>To play 12 Locks II, you need to have an Android or iOS device that meets the following requirements:</p>
-<ul>
-<li>Android: version 4.4 or higher; 40 MB of free space; internet connection (optional)</li>
-<li>iOS: version 10.0 or higher; 64 MB of free space; internet connection (optional)</li>
-</ul>
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-<p>To download 12 Locks II from your app store, you need to follow these steps:</p>
-<ol>
-<li>Open your app store (Google Play Store or App Store) on your device.</li>
-<li>Type "12 Locks II" in the search bar and tap on the game icon.</li>
-<li>Tap on the "Install" or "Get" button and wait for the download to finish.</li>
-<li>Tap on the "Open" or "Play" button and enjoy the game!</li>
-</ol>
- <h2>Conclusion</h2>
-<p>In conclusion, 12 Locks II is a fun and challenging puzzle game that will test your logic, creativity and patience. You will have to find all the keys to unlock 12 doors in different rooms with different themes and styles. You will have to explore the rooms, interact with objects, solve mini-puzzles and collect clues to find the keys. The game has colorful and detailed graphics made with plasticine, cheerful and catchy music, simple and intuitive controls, challenging and varied puzzles, no time limit or penalties, and hints if you get stuck. Playing 12 Locks II can improve your cognitive skills, stimulate your curiosity and imagination, provide you with a sense of achievement and satisfaction, reduce your stress and anxiety, and make you laugh and smile. You can download 12 Locks II from your preferred app store by following some simple steps. If you are looking for a puzzle game that will keep you entertained and challenged for hours, you should give 12 Locks II a try!</p>
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-<p>Here are some frequently asked questions about 12 Locks II:</p>
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-<li><b>Q: How many levels are there in 12 Locks II?</b></li>
-<li>A: There are 12 levels in 12 Locks II, each with a different room and theme.</li>
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-<li>A: It depends on your skill and speed, but it can take anywhere from a few hours to a few days to finish the game.</li>
-<li><b>Q: Is the game suitable for children?</b></li>
-<li>A: Yes, the game is suitable for children of all ages. The game has no violence, gore or inappropriate content. The game is also educational and fun.</li>
-<li><b>Q: Is the game free to play?</b></li>
-<li>A: Yes, the game is free to play. However, the game contains ads that can be removed by purchasing the premium version of the game.</li>
-<li><b>Q: Can I play the game offline?</b></li>
-<li>A: Yes, you can play the game offline. However, you will need an internet connection to download the game and access some features such as hints or updates.</li>
-</ul></p> 197e85843d<br />
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diff --git a/spaces/1phancelerku/anime-remove-background/Cricket League Full Mod APK Everything You Need to Know.md b/spaces/1phancelerku/anime-remove-background/Cricket League Full Mod APK Everything You Need to Know.md
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+++ /dev/null
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-<ol>
-<li>What is Cricket League?</li>
-<p>Cricket League is a realistic and immersive cricket simulation game developed by Miniclip. It lets you play as your favorite teams and players in various modes and tournaments. You can customize your team, choose your batting and bowling style, and compete with other players online.</p>
-<li>What is Cricket League Full Mod APK?</li>
-<p>Cricket League Full Mod APK is a hacked version of Cricket League that gives you unlimited coins and gems, which are the in-game currencies. You can use these coins and gems to unlock all the players, modes, stadiums, and equipment in the game. You can also customize your players' appearance, skills, and attributes to suit your preferences.</p>
-<li>How to download Cricket League Full Mod APK?</li>
-<p>To download Cricket League Full Mod APK, you need to enable unknown sources on your device, download the mod apk file from a trusted source , locate and install the mod apk file on your device, and launch the game.</p>
-<li>What are the pros and cons of Cricket League Full Mod APK?</li>
-<p>The pros of Cricket League Full Mod APK are more fun, more options, more customization. The cons of Cricket League Full Mod APK are risk of malware, ban from official servers, compatibility issues.</p>
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-<p>Cricket League Full Mod APK is not completely safe to use as it can expose your device to malware and viruses that can harm your device or steal your personal information. It can also violate the terms and conditions of the original app and result in a ban from the official servers. It can also cause crashes, glitches, or errors on your device. You should always scan the mod apk file before installing it and use a reliable antivirus app on your device. You should also backup your data before using mod apk files and uninstall them if you encounter any problems.</p>
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diff --git a/spaces/1phancelerku/anime-remove-background/Download Airtel Payment Bank App and Enjoy Online Banking Services.md b/spaces/1phancelerku/anime-remove-background/Download Airtel Payment Bank App and Enjoy Online Banking Services.md
deleted file mode 100644
index b470f5ef2a9abd1df090df23b49cbff4bf5608a0..0000000000000000000000000000000000000000
--- a/spaces/1phancelerku/anime-remove-background/Download Airtel Payment Bank App and Enjoy Online Banking Services.md	
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-<ol>
-<li>Log in to your Airtel Payment Bank account and select the service that you want to recharge or pay.</li>
-<li>Enter the amount and the details of the service provider.</li>
-<li>Choose your payment method (wallet balance, online debit card, UPI, etc.) and confirm the transaction.</li>
-<li>You will receive a confirmation message and a receipt on your phone and email.</li>
-</ol>
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-<p>You can shop online from various websites and apps that accept Airtel Payment Bank as a payment option. You can also make online payments for various services such as food delivery, cab booking, movie tickets, etc. using Airtel Payment Bank. You can get cashback and discounts on some of these transactions. To shop or pay online, you need to:</p>
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-<li>Enter your mobile number and OTP to verify your identity.</li>
-<li>Choose your payment method (wallet balance, online debit card, UPI, etc.) and confirm the transaction.</li>
-<li>You will receive a confirmation message and a receipt on your phone and email.</li>
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-<p>You can transfer money to any bank account or mobile number using Airtel Payment Bank. You can also withdraw cash from any of the over 5 lakh banking points across India using your mobile number and PIN. You can get cashback and discounts on some of these transactions. To transfer money or withdraw cash, you need to:</p>
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-<li>Log in to your Airtel Payment Bank account and select the option of money transfer or cash withdrawal.</li>
-<li>Enter the amount and the details of the recipient (bank account number, IFSC code, mobile number, etc.) or the banking point (name, location, etc.).</li>
-<li>Choose your payment method (wallet balance, online debit card, UPI, etc.) and confirm the transaction.</li>
-<li>You will receive a confirmation message and a receipt on your phone and email.</li>
-</ol>
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-<p>Airtel Payment Bank is a great way to manage your money digitally and enjoy various benefits and features. It is easy to download Airtel Payment Bank app and online debit card, and use them for various transactions. You can also save money by getting cashback and discounts on some of these transactions. So what are you waiting for? Download Airtel Payment Bank today and experience the convenience of digital banking!</p>
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-<h4>Q1: What are the charges for using Airtel Payment Bank?</h4>
-<p>A1: There are no charges for opening an account, maintaining a zero balance, or getting an online debit card with Airtel Payment Bank. However, there may be some charges for certain transactions such as money transfer, cash withdrawal, ATM usage, etc. depending on the amount and frequency of the transaction. You can check the latest charges on the website or app of Airtel Payment Bank.</p>
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diff --git a/spaces/1phancelerku/anime-remove-background/Download Nubank Fake APK for Android 2023 Explore the Features of the Famous App.md b/spaces/1phancelerku/anime-remove-background/Download Nubank Fake APK for Android 2023 Explore the Features of the Famous App.md
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--- a/spaces/1phancelerku/anime-remove-background/Download Nubank Fake APK for Android 2023 Explore the Features of the Famous App.md	
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-<p>Nubank is a digital bank that helps customers in Brazil, Mexico, and Colombia manage their money with freedom. Nubank is just one digital banking option in the Latin American world. It offers a variety of services for its customers, such as credit card applications, loans, life insurance, and business accounts. Nubank wants to improve the banking experience for customers across Latin America by using proprietary technology to create streamlined, uncomplicated, and completely digital banking options for its customers.</p>
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-<p>If you want to enjoy the benefits of Nubank without risking your device or data, you need to download and install the genuine Nubank app safely. Here are the steps to do so:</p>
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-<p>The official Nubank app is available on Google Play Store for Android devices and Apple App Store for iOS devices. To find and verify the official Nubank app, you can:</p>
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-<li>Tap on the "Install" button on the app store. Wait for the app to download and install on your device.</li>
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-<p>Nubank is a digital bank that offers a convenient, secure, and transparent way to manage your money with freedom. However, you need to be careful of fake apps that can imitate Nubank and harm your device or data. To avoid fake apps, you need to check the app's name, developer, description, reviews, permissions, and settings before downloading it. You also need to use only trusted and verified app stores to download apps. To download and install the genuine Nubank app safely, you need to find and verify the official Nubank app on Google Play Store or Apple App Store, then follow the steps to install and set up the app on your device.</p>
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- <p><b>Disclaimer:</b> This article is for informational purposes only and does not constitute financial or legal advice. Please consult a professional before making any decisions regarding your money or data.</p>
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-<p>Here are some frequently asked questions about Nubank and fake apps:</p>
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diff --git a/spaces/1phancelerku/anime-remove-background/Download Onmyoji Arena APK for Android - Play Offline Strategy Game.md b/spaces/1phancelerku/anime-remove-background/Download Onmyoji Arena APK for Android - Play Offline Strategy Game.md
deleted file mode 100644
index 2eb756dab507a4c5003f5b19114be770ba232c88..0000000000000000000000000000000000000000
--- a/spaces/1phancelerku/anime-remove-background/Download Onmyoji Arena APK for Android - Play Offline Strategy Game.md	
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-<p>If you want to play Onmyoji Arena offline, you will need to download and install the APK file of the game on your Android device. Here are the steps to do so:</p>
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-<p>Before you install Onmyoji Arena APK offline on your device, you should take some precautions to ensure your safety and security. Here are some tips to follow:</p>
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-<p>Once you have installed Onmyoji Arena APK offline on your device, you can play the game without internet connection. However, you will only be able to access some modes and options in the offline mode. Here are some of them:</p>
-<ul>
-<li>You can play the tutorial mode, where you can learn the basics of the game and practice with different shikigami.</li>
-<li>You can play the practice mode, where you can choose any shikigami and any map, and play against AI opponents or bots.</li>
-<li>You can play the custom mode, where you can create your own match settings, such as the number of players, the difficulty level, and the map.</li>
-<li>You can play the story mode, where you can follow the plot of the game and unlock new shikigami and skins.</li>
-<li>You can access the shikigami gallery, where you can view the details and stats of each shikigami, as well as their skins, accessories, and emotes.</li>
-</ul>
- <h3>The tips and tricks to enjoy the game offline</h3>
-<p>Playing Onmyoji Arena offline can be fun and rewarding, if you know how to make the most of it. Here are some tips and tricks to enjoy the game offline:</p>
-<ul>
-<li>Try different shikigami and find out which ones suit your playstyle and preferences.</li>
-<li>Experiment with different builds and items for each shikigami, and see how they affect their performance.</li>
-<li>Learn the strengths and weaknesses of each shikigami, and how to counter them effectively.</li>
-<li>Master the mechanics and strategies of each map, such as the objectives, the lanes, the jungle, and the bosses.</li>
-<li>Challenge yourself by increasing the difficulty level or changing the match settings in the custom mode.</li>
-</ul>
- <h2>Conclusion</h2>
-<p>Onmyoji Arena is a great game that you can play online or offline. If you want to play it offline, you will need to download and install Onmyoji Arena APK offline on your Android device. You will be able to access some modes and options in the offline mode, such as tutorial, practice, custom, and story. You will also be able to enjoy the game offline by trying different shikigami, builds, items, maps, and settings. However, you will not be able to access some features or modes that require internet connection, such as ranked matches, casual matches, or special events. You will also not be able to update your game or download new content that might be released by the developers. You will also not be able to interact with other players or join a guild. You will also not be able to earn rewards or achievements that are based on online activities. Therefore, playing Onmyoji Arena offline has its pros and cons, and you should decide which mode suits you better. If you are interested in playing Onmyoji Arena offline, you can follow the steps and tips we have provided in this article. We hope you have fun playing Onmyoji Arena offline!</p>
- <h2>FAQs</h2>
-<h3>Q: Is Onmyoji Arena APK offline safe to download and install?</h3>
-<p>A: Yes, as long as you download it from a trusted website that offers Onmyoji Arena APK offline download, such as [APKCombo] or [Google Play Store]. You should also scan it for viruses or malware before installing it on your device.</p>
- <h3>Q: Can I play Onmyoji Arena offline on iOS devices?</h3>
-<p>A: No, Onmyoji Arena APK offline is only compatible with Android devices. If you want to play Onmyoji Arena on iOS devices, you will need an internet connection.</p>
- <h3>Q: Can I switch between online and offline mode in Onmyoji Arena?</h3>
-<p>A: Yes, you can switch between online and offline mode in Onmyoji Arena, as long as you have an internet connection. You can do so by tapping on the settings icon on the top right corner of the main screen, and then choosing the online or offline option. However, you should note that some of your data or progress might not be synced or saved when you switch modes.</p>
- <h3>Q: What are the best shikigami to play offline in Onmyoji Arena?</h3>
-<p>A: The best shikigami to play offline in Onmyoji Arena depends on your personal preference and playstyle. However, some of the shikigami that are generally considered to be good for offline mode are:</p>
-<ul>
-<li>Yoto Hime: A powerful samurai who can deal massive damage and execute enemies with her ultimate skill.</li>
-<li>Yamakaze: A swift ninja who can dash and blink around the map, and assassinate enemies with his stealth and burst.</li>
-<li>Shuten Doji: A tanky ogre who can absorb damage and heal himself, and stun enemies with his drunken rage.</li>
-<li>Hana: A graceful healer who can support her allies and herself with her healing and shielding skills.</li>
-<li>Ootengu: A versatile mage who can cast spells from a distance, and unleash a devastating storm with his ultimate skill.</li>
-</ul>
- <h3>Q: How can I get more skins, accessories, and emotes for my shikigami in offline mode?</h3>
-<p>A: Unfortunately, you cannot get more skins, accessories, or emotes for your shikigami in offline mode. You will need to play online mode to earn rewards or purchase items that can unlock more customization options for your shikigami.</p> 197e85843d<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/20four60/Auto-GPT/README.md b/spaces/20four60/Auto-GPT/README.md
deleted file mode 100644
index 9f8b3e2d2ea8a43988518fdc8e56935675f89e30..0000000000000000000000000000000000000000
--- a/spaces/20four60/Auto-GPT/README.md
+++ /dev/null
@@ -1,11 +0,0 @@
----
-title: Zenml Server
-emoji: 🧘
-colorFrom: purple
-colorTo: green
-sdk: docker
-pinned: false
-app_port: 8080
-license: wtfpl
-duplicated_from: zenml/zenml
----
diff --git a/spaces/4Taps/SadTalker/src/face3d/models/arcface_torch/eval/verification.py b/spaces/4Taps/SadTalker/src/face3d/models/arcface_torch/eval/verification.py
deleted file mode 100644
index 253343b83dbf9d1bd154d14ec068e098bf0968db..0000000000000000000000000000000000000000
--- a/spaces/4Taps/SadTalker/src/face3d/models/arcface_torch/eval/verification.py
+++ /dev/null
@@ -1,407 +0,0 @@
-"""Helper for evaluation on the Labeled Faces in the Wild dataset 
-"""
-
-# MIT License
-#
-# Copyright (c) 2016 David Sandberg
-#
-# Permission is hereby granted, free of charge, to any person obtaining a copy
-# of this software and associated documentation files (the "Software"), to deal
-# in the Software without restriction, including without limitation the rights
-# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-# copies of the Software, and to permit persons to whom the Software is
-# furnished to do so, subject to the following conditions:
-#
-# The above copyright notice and this permission notice shall be included in all
-# copies or substantial portions of the Software.
-#
-# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-# SOFTWARE.
-
-
-import datetime
-import os
-import pickle
-
-import mxnet as mx
-import numpy as np
-import sklearn
-import torch
-from mxnet import ndarray as nd
-from scipy import interpolate
-from sklearn.decomposition import PCA
-from sklearn.model_selection import KFold
-
-
-class LFold:
-    def __init__(self, n_splits=2, shuffle=False):
-        self.n_splits = n_splits
-        if self.n_splits > 1:
-            self.k_fold = KFold(n_splits=n_splits, shuffle=shuffle)
-
-    def split(self, indices):
-        if self.n_splits > 1:
-            return self.k_fold.split(indices)
-        else:
-            return [(indices, indices)]
-
-
-def calculate_roc(thresholds,
-                  embeddings1,
-                  embeddings2,
-                  actual_issame,
-                  nrof_folds=10,
-                  pca=0):
-    assert (embeddings1.shape[0] == embeddings2.shape[0])
-    assert (embeddings1.shape[1] == embeddings2.shape[1])
-    nrof_pairs = min(len(actual_issame), embeddings1.shape[0])
-    nrof_thresholds = len(thresholds)
-    k_fold = LFold(n_splits=nrof_folds, shuffle=False)
-
-    tprs = np.zeros((nrof_folds, nrof_thresholds))
-    fprs = np.zeros((nrof_folds, nrof_thresholds))
-    accuracy = np.zeros((nrof_folds))
-    indices = np.arange(nrof_pairs)
-
-    if pca == 0:
-        diff = np.subtract(embeddings1, embeddings2)
-        dist = np.sum(np.square(diff), 1)
-
-    for fold_idx, (train_set, test_set) in enumerate(k_fold.split(indices)):
-        if pca > 0:
-            print('doing pca on', fold_idx)
-            embed1_train = embeddings1[train_set]
-            embed2_train = embeddings2[train_set]
-            _embed_train = np.concatenate((embed1_train, embed2_train), axis=0)
-            pca_model = PCA(n_components=pca)
-            pca_model.fit(_embed_train)
-            embed1 = pca_model.transform(embeddings1)
-            embed2 = pca_model.transform(embeddings2)
-            embed1 = sklearn.preprocessing.normalize(embed1)
-            embed2 = sklearn.preprocessing.normalize(embed2)
-            diff = np.subtract(embed1, embed2)
-            dist = np.sum(np.square(diff), 1)
-
-        # Find the best threshold for the fold
-        acc_train = np.zeros((nrof_thresholds))
-        for threshold_idx, threshold in enumerate(thresholds):
-            _, _, acc_train[threshold_idx] = calculate_accuracy(
-                threshold, dist[train_set], actual_issame[train_set])
-        best_threshold_index = np.argmax(acc_train)
-        for threshold_idx, threshold in enumerate(thresholds):
-            tprs[fold_idx, threshold_idx], fprs[fold_idx, threshold_idx], _ = calculate_accuracy(
-                threshold, dist[test_set],
-                actual_issame[test_set])
-        _, _, accuracy[fold_idx] = calculate_accuracy(
-            thresholds[best_threshold_index], dist[test_set],
-            actual_issame[test_set])
-
-    tpr = np.mean(tprs, 0)
-    fpr = np.mean(fprs, 0)
-    return tpr, fpr, accuracy
-
-
-def calculate_accuracy(threshold, dist, actual_issame):
-    predict_issame = np.less(dist, threshold)
-    tp = np.sum(np.logical_and(predict_issame, actual_issame))
-    fp = np.sum(np.logical_and(predict_issame, np.logical_not(actual_issame)))
-    tn = np.sum(
-        np.logical_and(np.logical_not(predict_issame),
-                       np.logical_not(actual_issame)))
-    fn = np.sum(np.logical_and(np.logical_not(predict_issame), actual_issame))
-
-    tpr = 0 if (tp + fn == 0) else float(tp) / float(tp + fn)
-    fpr = 0 if (fp + tn == 0) else float(fp) / float(fp + tn)
-    acc = float(tp + tn) / dist.size
-    return tpr, fpr, acc
-
-
-def calculate_val(thresholds,
-                  embeddings1,
-                  embeddings2,
-                  actual_issame,
-                  far_target,
-                  nrof_folds=10):
-    assert (embeddings1.shape[0] == embeddings2.shape[0])
-    assert (embeddings1.shape[1] == embeddings2.shape[1])
-    nrof_pairs = min(len(actual_issame), embeddings1.shape[0])
-    nrof_thresholds = len(thresholds)
-    k_fold = LFold(n_splits=nrof_folds, shuffle=False)
-
-    val = np.zeros(nrof_folds)
-    far = np.zeros(nrof_folds)
-
-    diff = np.subtract(embeddings1, embeddings2)
-    dist = np.sum(np.square(diff), 1)
-    indices = np.arange(nrof_pairs)
-
-    for fold_idx, (train_set, test_set) in enumerate(k_fold.split(indices)):
-
-        # Find the threshold that gives FAR = far_target
-        far_train = np.zeros(nrof_thresholds)
-        for threshold_idx, threshold in enumerate(thresholds):
-            _, far_train[threshold_idx] = calculate_val_far(
-                threshold, dist[train_set], actual_issame[train_set])
-        if np.max(far_train) >= far_target:
-            f = interpolate.interp1d(far_train, thresholds, kind='slinear')
-            threshold = f(far_target)
-        else:
-            threshold = 0.0
-
-        val[fold_idx], far[fold_idx] = calculate_val_far(
-            threshold, dist[test_set], actual_issame[test_set])
-
-    val_mean = np.mean(val)
-    far_mean = np.mean(far)
-    val_std = np.std(val)
-    return val_mean, val_std, far_mean
-
-
-def calculate_val_far(threshold, dist, actual_issame):
-    predict_issame = np.less(dist, threshold)
-    true_accept = np.sum(np.logical_and(predict_issame, actual_issame))
-    false_accept = np.sum(
-        np.logical_and(predict_issame, np.logical_not(actual_issame)))
-    n_same = np.sum(actual_issame)
-    n_diff = np.sum(np.logical_not(actual_issame))
-    # print(true_accept, false_accept)
-    # print(n_same, n_diff)
-    val = float(true_accept) / float(n_same)
-    far = float(false_accept) / float(n_diff)
-    return val, far
-
-
-def evaluate(embeddings, actual_issame, nrof_folds=10, pca=0):
-    # Calculate evaluation metrics
-    thresholds = np.arange(0, 4, 0.01)
-    embeddings1 = embeddings[0::2]
-    embeddings2 = embeddings[1::2]
-    tpr, fpr, accuracy = calculate_roc(thresholds,
-                                       embeddings1,
-                                       embeddings2,
-                                       np.asarray(actual_issame),
-                                       nrof_folds=nrof_folds,
-                                       pca=pca)
-    thresholds = np.arange(0, 4, 0.001)
-    val, val_std, far = calculate_val(thresholds,
-                                      embeddings1,
-                                      embeddings2,
-                                      np.asarray(actual_issame),
-                                      1e-3,
-                                      nrof_folds=nrof_folds)
-    return tpr, fpr, accuracy, val, val_std, far
-
-@torch.no_grad()
-def load_bin(path, image_size):
-    try:
-        with open(path, 'rb') as f:
-            bins, issame_list = pickle.load(f)  # py2
-    except UnicodeDecodeError as e:
-        with open(path, 'rb') as f:
-            bins, issame_list = pickle.load(f, encoding='bytes')  # py3
-    data_list = []
-    for flip in [0, 1]:
-        data = torch.empty((len(issame_list) * 2, 3, image_size[0], image_size[1]))
-        data_list.append(data)
-    for idx in range(len(issame_list) * 2):
-        _bin = bins[idx]
-        img = mx.image.imdecode(_bin)
-        if img.shape[1] != image_size[0]:
-            img = mx.image.resize_short(img, image_size[0])
-        img = nd.transpose(img, axes=(2, 0, 1))
-        for flip in [0, 1]:
-            if flip == 1:
-                img = mx.ndarray.flip(data=img, axis=2)
-            data_list[flip][idx][:] = torch.from_numpy(img.asnumpy())
-        if idx % 1000 == 0:
-            print('loading bin', idx)
-    print(data_list[0].shape)
-    return data_list, issame_list
-
-@torch.no_grad()
-def test(data_set, backbone, batch_size, nfolds=10):
-    print('testing verification..')
-    data_list = data_set[0]
-    issame_list = data_set[1]
-    embeddings_list = []
-    time_consumed = 0.0
-    for i in range(len(data_list)):
-        data = data_list[i]
-        embeddings = None
-        ba = 0
-        while ba < data.shape[0]:
-            bb = min(ba + batch_size, data.shape[0])
-            count = bb - ba
-            _data = data[bb - batch_size: bb]
-            time0 = datetime.datetime.now()
-            img = ((_data / 255) - 0.5) / 0.5
-            net_out: torch.Tensor = backbone(img)
-            _embeddings = net_out.detach().cpu().numpy()
-            time_now = datetime.datetime.now()
-            diff = time_now - time0
-            time_consumed += diff.total_seconds()
-            if embeddings is None:
-                embeddings = np.zeros((data.shape[0], _embeddings.shape[1]))
-            embeddings[ba:bb, :] = _embeddings[(batch_size - count):, :]
-            ba = bb
-        embeddings_list.append(embeddings)
-
-    _xnorm = 0.0
-    _xnorm_cnt = 0
-    for embed in embeddings_list:
-        for i in range(embed.shape[0]):
-            _em = embed[i]
-            _norm = np.linalg.norm(_em)
-            _xnorm += _norm
-            _xnorm_cnt += 1
-    _xnorm /= _xnorm_cnt
-
-    acc1 = 0.0
-    std1 = 0.0
-    embeddings = embeddings_list[0] + embeddings_list[1]
-    embeddings = sklearn.preprocessing.normalize(embeddings)
-    print(embeddings.shape)
-    print('infer time', time_consumed)
-    _, _, accuracy, val, val_std, far = evaluate(embeddings, issame_list, nrof_folds=nfolds)
-    acc2, std2 = np.mean(accuracy), np.std(accuracy)
-    return acc1, std1, acc2, std2, _xnorm, embeddings_list
-
-
-def dumpR(data_set,
-          backbone,
-          batch_size,
-          name='',
-          data_extra=None,
-          label_shape=None):
-    print('dump verification embedding..')
-    data_list = data_set[0]
-    issame_list = data_set[1]
-    embeddings_list = []
-    time_consumed = 0.0
-    for i in range(len(data_list)):
-        data = data_list[i]
-        embeddings = None
-        ba = 0
-        while ba < data.shape[0]:
-            bb = min(ba + batch_size, data.shape[0])
-            count = bb - ba
-
-            _data = nd.slice_axis(data, axis=0, begin=bb - batch_size, end=bb)
-            time0 = datetime.datetime.now()
-            if data_extra is None:
-                db = mx.io.DataBatch(data=(_data,), label=(_label,))
-            else:
-                db = mx.io.DataBatch(data=(_data, _data_extra),
-                                     label=(_label,))
-            model.forward(db, is_train=False)
-            net_out = model.get_outputs()
-            _embeddings = net_out[0].asnumpy()
-            time_now = datetime.datetime.now()
-            diff = time_now - time0
-            time_consumed += diff.total_seconds()
-            if embeddings is None:
-                embeddings = np.zeros((data.shape[0], _embeddings.shape[1]))
-            embeddings[ba:bb, :] = _embeddings[(batch_size - count):, :]
-            ba = bb
-        embeddings_list.append(embeddings)
-    embeddings = embeddings_list[0] + embeddings_list[1]
-    embeddings = sklearn.preprocessing.normalize(embeddings)
-    actual_issame = np.asarray(issame_list)
-    outname = os.path.join('temp.bin')
-    with open(outname, 'wb') as f:
-        pickle.dump((embeddings, issame_list),
-                    f,
-                    protocol=pickle.HIGHEST_PROTOCOL)
-
-
-# if __name__ == '__main__':
-#
-#     parser = argparse.ArgumentParser(description='do verification')
-#     # general
-#     parser.add_argument('--data-dir', default='', help='')
-#     parser.add_argument('--model',
-#                         default='../model/softmax,50',
-#                         help='path to load model.')
-#     parser.add_argument('--target',
-#                         default='lfw,cfp_ff,cfp_fp,agedb_30',
-#                         help='test targets.')
-#     parser.add_argument('--gpu', default=0, type=int, help='gpu id')
-#     parser.add_argument('--batch-size', default=32, type=int, help='')
-#     parser.add_argument('--max', default='', type=str, help='')
-#     parser.add_argument('--mode', default=0, type=int, help='')
-#     parser.add_argument('--nfolds', default=10, type=int, help='')
-#     args = parser.parse_args()
-#     image_size = [112, 112]
-#     print('image_size', image_size)
-#     ctx = mx.gpu(args.gpu)
-#     nets = []
-#     vec = args.model.split(',')
-#     prefix = args.model.split(',')[0]
-#     epochs = []
-#     if len(vec) == 1:
-#         pdir = os.path.dirname(prefix)
-#         for fname in os.listdir(pdir):
-#             if not fname.endswith('.params'):
-#                 continue
-#             _file = os.path.join(pdir, fname)
-#             if _file.startswith(prefix):
-#                 epoch = int(fname.split('.')[0].split('-')[1])
-#                 epochs.append(epoch)
-#         epochs = sorted(epochs, reverse=True)
-#         if len(args.max) > 0:
-#             _max = [int(x) for x in args.max.split(',')]
-#             assert len(_max) == 2
-#             if len(epochs) > _max[1]:
-#                 epochs = epochs[_max[0]:_max[1]]
-#
-#     else:
-#         epochs = [int(x) for x in vec[1].split('|')]
-#     print('model number', len(epochs))
-#     time0 = datetime.datetime.now()
-#     for epoch in epochs:
-#         print('loading', prefix, epoch)
-#         sym, arg_params, aux_params = mx.model.load_checkpoint(prefix, epoch)
-#         # arg_params, aux_params = ch_dev(arg_params, aux_params, ctx)
-#         all_layers = sym.get_internals()
-#         sym = all_layers['fc1_output']
-#         model = mx.mod.Module(symbol=sym, context=ctx, label_names=None)
-#         # model.bind(data_shapes=[('data', (args.batch_size, 3, image_size[0], image_size[1]))], label_shapes=[('softmax_label', (args.batch_size,))])
-#         model.bind(data_shapes=[('data', (args.batch_size, 3, image_size[0],
-#                                           image_size[1]))])
-#         model.set_params(arg_params, aux_params)
-#         nets.append(model)
-#     time_now = datetime.datetime.now()
-#     diff = time_now - time0
-#     print('model loading time', diff.total_seconds())
-#
-#     ver_list = []
-#     ver_name_list = []
-#     for name in args.target.split(','):
-#         path = os.path.join(args.data_dir, name + ".bin")
-#         if os.path.exists(path):
-#             print('loading.. ', name)
-#             data_set = load_bin(path, image_size)
-#             ver_list.append(data_set)
-#             ver_name_list.append(name)
-#
-#     if args.mode == 0:
-#         for i in range(len(ver_list)):
-#             results = []
-#             for model in nets:
-#                 acc1, std1, acc2, std2, xnorm, embeddings_list = test(
-#                     ver_list[i], model, args.batch_size, args.nfolds)
-#                 print('[%s]XNorm: %f' % (ver_name_list[i], xnorm))
-#                 print('[%s]Accuracy: %1.5f+-%1.5f' % (ver_name_list[i], acc1, std1))
-#                 print('[%s]Accuracy-Flip: %1.5f+-%1.5f' % (ver_name_list[i], acc2, std2))
-#                 results.append(acc2)
-#             print('Max of [%s] is %1.5f' % (ver_name_list[i], np.max(results)))
-#     elif args.mode == 1:
-#         raise ValueError
-#     else:
-#         model = nets[0]
-#         dumpR(ver_list[0], model, args.batch_size, args.target)
diff --git a/spaces/AI-Hobbyist/Hoyo-RVC/Changelog_KO.md b/spaces/AI-Hobbyist/Hoyo-RVC/Changelog_KO.md
deleted file mode 100644
index 37e0891a5c5d22288b525f8bdab4d9c041601122..0000000000000000000000000000000000000000
--- a/spaces/AI-Hobbyist/Hoyo-RVC/Changelog_KO.md
+++ /dev/null
@@ -1,91 +0,0 @@
-### 2023년 6월 18일 업데이트
-
-- v2 버전에서 새로운 32k와 48k 사전 학습 모델을 추가.
-- non-f0 모델들의 추론 오류 수정.
-- 학습 세트가 1시간을 넘어가는 경우, 인덱스 생성 단계에서 minibatch-kmeans을 사용해, 학습속도 가속화.
-- [huggingface](https://huggingface.co/spaces/lj1995/vocal2guitar)에서 vocal2guitar 제공.
-- 데이터 처리 단계에서 이상 값 자동으로 제거.
-- ONNX로 내보내는(export) 옵션 탭 추가.
-
-업데이트에 적용되지 않았지만 시도한 것들 :
-
-- 시계열 차원을 추가하여 특징 검색을 진행했지만, 유의미한 효과는 없었습니다.
-- PCA 차원 축소를 추가하여 특징 검색을 진행했지만, 유의미한 효과는 없었습니다.
-- ONNX 추론을 지원하는 것에 실패했습니다. nsf 생성시, Pytorch가 필요하기 때문입니다.
-- 훈련 중에 입력에 대한 음고, 성별, 이퀄라이저, 노이즈 등 무작위로 강화하는 것에, 유의미한 효과는 없었습니다.
-
-추후 업데이트 목록:
-
-- Vocos-RVC (소형 보코더) 통합 예정.
-- 학습 단계에 음고 인식을 위한 Crepe 지원 예정.
-- Crepe의 정밀도를 REC-config와 동기화하여 지원 예정.
-- FO 에디터 지원 예정.
-
-### 2023년 5월 28일 업데이트
-
-- v2 jupyter notebook 추가, 한국어 업데이트 로그 추가, 의존성 모듈 일부 수정.
-- 무성음 및 숨소리 보호 모드 추가.
-- crepe-full pitch 감지 지원.
-- UVR5 보컬 분리: 디버브 및 디-에코 모델 지원.
-- index 이름에 experiment 이름과 버전 추가.
-- 배치 음성 변환 처리 및 UVR5 보컬 분리 시, 사용자가 수동으로 출력 오디오의 내보내기(export) 형식을 선택할 수 있도록 지원.
-- 32k 훈련 모델 지원 종료.
-
-### 2023년 5월 13일 업데이트
-
-- 원클릭 패키지의 이전 버전 런타임 내, 불필요한 코드(infer_pack 및 uvr5_pack) 제거.
-- 훈련 세트 전처리의 유사 다중 처리 버그 수정.
-- Harvest 피치 인식 알고리즘에 대한 중위수 필터링 반경 조정 추가.
-- 오디오 내보낼 때, 후처리 리샘플링 지원.
-- 훈련에 대한 다중 처리 "n_cpu" 설정이 "f0 추출"에서 "데이터 전처리 및 f0 추출"로 변경.
-- logs 폴더 하의 인덱스 경로를 자동으로 감지 및 드롭다운 목록 기능 제공.
-- 탭 페이지에 "자주 묻는 질문과 답변" 추가. (github RVC wiki 참조 가능)
-- 동일한 입력 오디오 경로를 사용할 때 추론, Harvest 피치를 캐시.
-  (주의: Harvest 피치 추출을 사용하면 전체 파이프라인은 길고 반복적인 피치 추출 과정을 거치게됩니다. 캐싱을 하지 않는다면, 첫 inference 이후의 단계에서 timbre, 인덱스, 피치 중위수 필터링 반경 설정 등 대기시간이 엄청나게 길어집니다!)
-
-### 2023년 5월 14일 업데이트
-
-- 입력의 볼륨 캡슐을 사용하여 출력의 볼륨 캡슐을 혼합하거나 대체. (입력이 무음이거나 출력의 노이즈 문제를 최소화 할 수 있습니다. 입력 오디오의 배경 노이즈(소음)가 큰 경우 해당 기능을 사용하지 않는 것이 좋습니다. 기본적으로 비활성화 되어있는 옵션입니다. (1: 비활성화 상태))
-- 추출된 소형 모델을 지정된 빈도로 저장하는 기능을 지원. (다양한 에폭 하에서의 성능을 보려고 하지만 모든 대형 체크포인트를 저장하고 매번 ckpt 처리를 통해 소형 모델을 수동으로 추출하고 싶지 않은 경우 이 기능은 매우 유용합니다)
-- 환경 변수를 설정하여 서버의 전역 프록시로 인한 "연결 오류" 문제 해결.
-- 사전 훈련된 v2 모델 지원. (현재 40k 버전만 테스트를 위해 공개적으로 사용 가능하며, 다른 두 개의 샘플링 비율은 아직 완전히 훈련되지 않아 보류되었습니다.)
-- 추론 전, 1을 초과하는 과도한 볼륨 제한.
-- 데이터 전처리 매개변수 미세 조정.
-
-### 2023년 4월 9일 업데이트
-
-- GPU 이용률 향상을 위해 훈련 파라미터 수정: A100은 25%에서 약 90%로 증가, V100: 50%에서 약 90%로 증가, 2060S: 60%에서 약 85%로 증가, P40: 25%에서 약 95%로 증가.
-  훈련 속도가 크게 향상.
-- 매개변수 기준 변경: total batch_size는 GPU당 batch_size를 의미.
-- total_epoch 변경: 최대 한도가 100에서 1000으로 증가. 기본값이 10에서 20으로 증가.
-- ckpt 추출이 피치를 잘못 인식하여 비정상적인 추론을 유발하는 문제 수정.
-- 분산 훈련 과정에서 각 랭크마다 ckpt를 저장하는 문제 수정.
-- 특성 추출 과정에 나노 특성 필터링 적용.
-- 무음 입력/출력이 랜덤하게 소음을 생성하는 문제 수정. (이전 모델은 새 데이터셋으로 다시 훈련해야 합니다)
-
-### 2023년 4월 16일 업데이트
-
-- 로컬 실시간 음성 변경 미니-GUI 추가, go-realtime-gui.bat를 더블 클릭하여 시작.
-- 훈련 및 추론 중 50Hz 이하의 주파수 대역에 대해 필터링 적용.
-- 훈련 및 추론의 pyworld 최소 피치 추출을 기본 80에서 50으로 낮춤. 이로 인해, 50-80Hz 사이의 남성 저음이 무음화되지 않습니다.
-- 시스템 지역에 따른 WebUI 언어 변경 지원. (현재 en_US, ja_JP, zh_CN, zh_HK, zh_SG, zh_TW를 지원하며, 지원되지 않는 경우 기본값은 en_US)
-- 일부 GPU의 인식 수정. (예: V100-16G 인식 실패, P4 인식 실패)
-
-### 2023년 4월 28일 업데이트
-
-- Faiss 인덱스 설정 업그레이드로 속도가 더 빨라지고 품질이 향상.
-- total_npy에 대한 의존성 제거. 추후의 모델 공유는 total_npy 입력을 필요로 하지 않습니다.
-- 16 시리즈 GPU에 대한 제한 해제, 4GB VRAM GPU에 대한 4GB 추론 설정 제공.
-- 일부 오디오 형식에 대한 UVR5 보컬 동반 분리에서의 버그 수정.
-- 실시간 음성 변경 미니-GUI는 이제 non-40k 및 non-lazy 피치 모델을 지원합니다.
-
-### 추후 계획
-
-Features:
-
-- 다중 사용자 훈련 탭 지원.(최대 4명)
-
-Base model:
-
-- 훈련 데이터셋에 숨소리 wav 파일을 추가하여, 보컬의 호흡이 노이즈로 변환되는 문제 수정.
-- 보컬 훈련 세트의 기본 모델을 추가하기 위한 작업을 진행중이며, 이는 향후에 발표될 예정.
diff --git a/spaces/AIConsultant/MusicGen/audiocraft/grids/__init__.py b/spaces/AIConsultant/MusicGen/audiocraft/grids/__init__.py
deleted file mode 100644
index 70643517cd1a8b4e712eca90e23411ae89937795..0000000000000000000000000000000000000000
--- a/spaces/AIConsultant/MusicGen/audiocraft/grids/__init__.py
+++ /dev/null
@@ -1,6 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-"""Dora Grids."""
diff --git a/spaces/AIConsultant/MusicGen/docs/AUDIOGEN.md b/spaces/AIConsultant/MusicGen/docs/AUDIOGEN.md
deleted file mode 100644
index a0ff481190fb52fe865aa66aaaa10176f7cf995c..0000000000000000000000000000000000000000
--- a/spaces/AIConsultant/MusicGen/docs/AUDIOGEN.md
+++ /dev/null
@@ -1,158 +0,0 @@
-# AudioGen: Textually-guided audio generation
-
-AudioCraft provides the code and a model re-implementing AudioGen, a [textually-guided audio generation][audiogen_arxiv]
-model that performs text-to-sound generation.
-
-The provided AudioGen reimplementation follows the LM model architecture introduced in [MusicGen][musicgen_arxiv]
-and is a single stage auto-regressive Transformer model trained over a 16kHz
-<a href="https://github.com/facebookresearch/encodec">EnCodec tokenizer</a> with 4 codebooks sampled at 50 Hz.
-This model variant reaches similar audio quality than the original implementation introduced in the AudioGen publication
-while providing faster generation speed given the smaller frame rate.
-
-**Important note:** The provided models are NOT the original models used to report numbers in the
-[AudioGen publication][audiogen_arxiv]. Refer to the model card to learn more about architectural changes.
-
-Listen to samples from the **original AudioGen implementation** in our [sample page][audiogen_samples].
-
-
-## Model Card
-
-See [the model card](../model_cards/AUDIOGEN_MODEL_CARD.md).
-
-
-## Installation
-
-Please follow the AudioCraft installation instructions from the [README](../README.md).
-
-AudioCraft requires a GPU with at least 16 GB of memory for running inference with the medium-sized models (~1.5B parameters).
-
-## API and usage
-
-We provide a simple API and 1 pre-trained models for AudioGen:
-
-`facebook/audiogen-medium`: 1.5B model, text to sound - [🤗 Hub](https://huggingface.co/facebook/audiogen-medium)
-
-You can play with AudioGen by running the jupyter notebook at [`demos/audiogen_demo.ipynb`](../demos/audiogen_demo.ipynb) locally (if you have a GPU).
-
-See after a quick example for using the API.
-
-```python
-import torchaudio
-from audiocraft.models import AudioGen
-from audiocraft.data.audio import audio_write
-
-model = AudioGen.get_pretrained('facebook/audiogen-medium')
-model.set_generation_params(duration=5)  # generate 5 seconds.
-descriptions = ['dog barking', 'sirene of an emergency vehicle', 'footsteps in a corridor']
-wav = model.generate(descriptions)  # generates 3 samples.
-
-for idx, one_wav in enumerate(wav):
-    # Will save under {idx}.wav, with loudness normalization at -14 db LUFS.
-    audio_write(f'{idx}', one_wav.cpu(), model.sample_rate, strategy="loudness", loudness_compressor=True)
-```
-
-## Training
-
-The [AudioGenSolver](../audiocraft/solvers/audiogen.py) implements the AudioGen's training pipeline
-used to develop the released model. Note that this may not fully reproduce the results presented in the paper.
-Similarly to MusicGen, it defines an autoregressive language modeling task over multiple streams of
-discrete tokens extracted from a pre-trained EnCodec model (see [EnCodec documentation](./ENCODEC.md)
-for more details on how to train such model) with dataset-specific changes for environmental sound
-processing.
-
-Note that **we do NOT provide any of the datasets** used for training AudioGen.
-
-### Example configurations and grids
-
-We provide configurations to reproduce the released models and our research.
-AudioGen solvers configuration are available in [config/solver/audiogen](../config/solver/audiogen).
-The base training configuration used for the released models is the following:
-[`solver=audiogen/audiogen_base_16khz`](../config/solver/audiogen/audiogen_base_16khz.yaml)
-
-Please find some example grids to train AudioGen at
-[audiocraft/grids/audiogen](../audiocraft/grids/audiogen/).
-
-```shell
-# text-to-sound
-dora grid audiogen.audiogen_base_16khz
-```
-
-### Sound dataset and metadata
-
-AudioGen's underlying dataset is an AudioDataset augmented with description metadata.
-The AudioGen dataset implementation expects the metadata to be available as `.json` files
-at the same location as the audio files or through specified external folder.
-Learn more in the [datasets section](./DATASETS.md).
-
-### Evaluation stage
-
-By default, evaluation stage is also computing the cross-entropy and the perplexity over the
-evaluation dataset. Indeed the objective metrics used for evaluation can be costly to run
-or require some extra dependencies. Please refer to the [metrics documentation](./METRICS.md)
-for more details on the requirements for each metric.
-
-We provide an off-the-shelf configuration to enable running the objective metrics
-for audio generation in
-[config/solver/audiogen/evaluation/objective_eval](../config/solver/audiogen/evaluation/objective_eval.yaml).
-
-One can then activate evaluation the following way:
-```shell
-# using the configuration
-dora run solver=audiogen/debug solver/audiogen/evaluation=objective_eval
-# specifying each of the fields, e.g. to activate KL computation
-dora run solver=audiogen/debug evaluate.metrics.kld=true
-```
-
-See [an example evaluation grid](../audiocraft/grids/audiogen/audiogen_pretrained_16khz_eval.py).
-
-### Generation stage
-
-The generation stage allows to generate samples conditionally and/or unconditionally and to perform
-audio continuation (from a prompt). We currently support greedy sampling (argmax), sampling
-from softmax with a given temperature, top-K and top-P (nucleus) sampling. The number of samples
-generated and the batch size used are controlled by the `dataset.generate` configuration
-while the other generation parameters are defined in `generate.lm`.
-
-```shell
-# control sampling parameters
-dora run solver=audiogen/debug generate.lm.gen_duration=5 generate.lm.use_sampling=true generate.lm.top_k=15
-```
-
-## More information
-
-Refer to [MusicGen's instructions](./MUSICGEN.md).
-
-### Learn more
-
-Learn more about AudioCraft training pipelines in the [dedicated section](./TRAINING.md).
-
-
-## Citation
-
-AudioGen
-```
-@article{kreuk2022audiogen,
-    title={Audiogen: Textually guided audio generation},
-    author={Kreuk, Felix and Synnaeve, Gabriel and Polyak, Adam and Singer, Uriel and D{\'e}fossez, Alexandre and Copet, Jade and Parikh, Devi and Taigman, Yaniv and Adi, Yossi},
-    journal={arXiv preprint arXiv:2209.15352},
-    year={2022}
-}
-```
-
-MusicGen
-```
-@article{copet2023simple,
-    title={Simple and Controllable Music Generation},
-    author={Jade Copet and Felix Kreuk and Itai Gat and Tal Remez and David Kant and Gabriel Synnaeve and Yossi Adi and Alexandre Défossez},
-    year={2023},
-    journal={arXiv preprint arXiv:2306.05284},
-}
-```
-
-## License
-
-See license information in the [model card](../model_cards/AUDIOGEN_MODEL_CARD.md).
-
-[audiogen_arxiv]: https://arxiv.org/abs/2209.15352
-[musicgen_arxiv]: https://arxiv.org/abs/2306.05284
-[audiogen_samples]: https://felixkreuk.github.io/audiogen/
diff --git a/spaces/AIGC-Audio/Make_An_Audio_inpaint/ldm/models/diffusion/ddpm_audio_inpaint.py b/spaces/AIGC-Audio/Make_An_Audio_inpaint/ldm/models/diffusion/ddpm_audio_inpaint.py
deleted file mode 100644
index 1541a74cd3082d8b44ba7a7988aeb65c2dd84a24..0000000000000000000000000000000000000000
--- a/spaces/AIGC-Audio/Make_An_Audio_inpaint/ldm/models/diffusion/ddpm_audio_inpaint.py
+++ /dev/null
@@ -1,1081 +0,0 @@
-"""
-wild mixture of
-https://github.com/lucidrains/denoising-diffusion-pytorch/blob/7706bdfc6f527f58d33f84b7b522e61e6e3164b3/denoising_diffusion_pytorch/denoising_diffusion_pytorch.py
-https://github.com/openai/improved-diffusion/blob/e94489283bb876ac1477d5dd7709bbbd2d9902ce/improved_diffusion/gaussian_diffusion.py
-https://github.com/CompVis/taming-transformers
--- merci
-"""
-import os
-import torch
-import torch.nn as nn
-import numpy as np
-import pytorch_lightning as pl
-from torch.optim.lr_scheduler import LambdaLR
-from einops import rearrange, repeat
-from contextlib import contextmanager
-from functools import partial
-from tqdm import tqdm
-from torchvision.utils import make_grid
-from pytorch_lightning.utilities.distributed import rank_zero_only
-
-from ldm.util import log_txt_as_img, exists, default, ismap, isimage, mean_flat, count_params, instantiate_from_config
-from ldm.modules.ema import LitEma
-from ldm.modules.distributions.distributions import normal_kl, DiagonalGaussianDistribution
-from ldm.models.autoencoder import VQModelInterface, IdentityFirstStage, AutoencoderKL
-from ldm.modules.diffusionmodules.util import make_beta_schedule, extract_into_tensor, noise_like
-from ldm.models.diffusion.ddim import DDIMSampler
-from ldm.models.diffusion.ddpm import DDPM, disabled_train
-
-__conditioning_keys__ = {'concat': 'c_concat',
-                         'crossattn': 'c_crossattn',
-                         'adm': 'y'}
-
-# add mel_dim and mel_length params to ensure correct shape
-class LatentDiffusion_audioinpaint(DDPM):
-    """main class"""
-    def __init__(self,
-                 first_stage_config,
-                 cond_stage_config,
-                 num_timesteps_cond=None,
-                 mel_dim=80,
-                 mel_length=848,
-                 cond_stage_key="image",
-                 cond_stage_trainable=False,
-                 concat_mode=True,
-                 cond_stage_forward=None,
-                 conditioning_key=None,
-                 scale_factor=1.0,
-                 scale_by_std=False,
-                 test_repeat=1,
-                 test_numsteps = None,
-                 *args, **kwargs):
-        self.num_timesteps_cond = default(num_timesteps_cond, 1)
-        self.scale_by_std = scale_by_std
-        assert self.num_timesteps_cond <= kwargs['timesteps']
-        # for backwards compatibility after implementation of DiffusionWrapper
-        if conditioning_key is None:
-            conditioning_key = 'concat' if concat_mode else 'crossattn'
-        if cond_stage_config == '__is_unconditional__':
-            conditioning_key = None
-        ckpt_path = kwargs.pop("ckpt_path", None)
-        ignore_keys = kwargs.pop("ignore_keys", [])
-        super().__init__(conditioning_key=conditioning_key, *args, **kwargs)
-        self.test_repeat = test_repeat
-        if test_numsteps == None:
-            self.test_numsteps = self.num_timesteps
-        self.concat_mode = concat_mode
-        self.mel_dim = mel_dim
-        self.mel_length = mel_length
-        self.cond_stage_trainable = cond_stage_trainable
-        self.cond_stage_key = cond_stage_key
-        try:
-            self.num_downs = len(first_stage_config.params.ddconfig.ch_mult) - 1
-        except:
-            self.num_downs = 0
-        if not scale_by_std:
-            self.scale_factor = scale_factor
-        else:
-            self.register_buffer('scale_factor', torch.tensor(scale_factor))
-        self.instantiate_first_stage(first_stage_config)
-        self.instantiate_cond_stage(cond_stage_config)
-        self.cond_stage_forward = cond_stage_forward
-        self.clip_denoised = False
-        self.bbox_tokenizer = None  
-
-        self.restarted_from_ckpt = False
-        if ckpt_path is not None:
-            self.init_from_ckpt(ckpt_path, ignore_keys)
-            self.restarted_from_ckpt = True
-
-    def make_cond_schedule(self, ):
-        self.cond_ids = torch.full(size=(self.num_timesteps,), fill_value=self.num_timesteps - 1, dtype=torch.long)
-        ids = torch.round(torch.linspace(0, self.num_timesteps - 1, self.num_timesteps_cond)).long()
-        self.cond_ids[:self.num_timesteps_cond] = ids
-
-    @rank_zero_only
-    @torch.no_grad()
-    def on_train_batch_start(self, batch, batch_idx, dataloader_idx):
-        # only for very first batch
-        if self.scale_by_std and self.current_epoch == 0 and self.global_step == 0 and batch_idx == 0 and not self.restarted_from_ckpt:
-            assert self.scale_factor == 1., 'rather not use custom rescaling and std-rescaling simultaneously'
-            # set rescale weight to 1./std of encodings
-            print("### USING STD-RESCALING ###")
-            x = super().get_input(batch, self.first_stage_key)
-            x = x.to(self.device)
-            encoder_posterior = self.encode_first_stage(x)
-            z = self.get_first_stage_encoding(encoder_posterior).detach()
-            del self.scale_factor
-            self.register_buffer('scale_factor', 1. / z.flatten().std())
-            print(f"setting self.scale_factor to {self.scale_factor}")
-            print("### USING STD-RESCALING ###")
-
-    def register_schedule(self,
-                          given_betas=None, beta_schedule="linear", timesteps=1000,
-                          linear_start=1e-4, linear_end=2e-2, cosine_s=8e-3):
-        super().register_schedule(given_betas, beta_schedule, timesteps, linear_start, linear_end, cosine_s)
-
-        self.shorten_cond_schedule = self.num_timesteps_cond > 1
-        if self.shorten_cond_schedule:
-            self.make_cond_schedule()
-
-    def instantiate_first_stage(self, config):
-        model = instantiate_from_config(config)
-        self.first_stage_model = model.eval()
-        self.first_stage_model.train = disabled_train
-        for param in self.first_stage_model.parameters():
-            param.requires_grad = False
-
-    def instantiate_cond_stage(self, config):
-        if not self.cond_stage_trainable:
-            if config == "__is_first_stage__":# for no_text inpainting task
-                print("Using first stage also as cond stage.")
-                self.cond_stage_model = self.first_stage_model
-            elif config == "__is_unconditional__":# for unconditional image generation such as human face、ImageNet
-                print(f"Training {self.__class__.__name__} as an unconditional model.")
-                self.cond_stage_model = None
-                # self.be_unconditional = True
-            else:
-                model = instantiate_from_config(config)
-                self.cond_stage_model = model.eval()
-                self.cond_stage_model.train = disabled_train
-                for param in self.cond_stage_model.parameters():
-                    param.requires_grad = False
-        else:
-            assert config != '__is_first_stage__'
-            assert config != '__is_unconditional__'
-            model = instantiate_from_config(config)
-            self.cond_stage_model = model
-
-    def _get_denoise_row_from_list(self, samples, desc='', force_no_decoder_quantization=False):
-        denoise_row = []
-        for zd in tqdm(samples, desc=desc):
-            denoise_row.append(self.decode_first_stage(zd.to(self.device),
-                                                            force_not_quantize=force_no_decoder_quantization))
-        n_imgs_per_row = len(denoise_row)
-        denoise_row = torch.stack(denoise_row)  # n_log_step, n_row, C, H, W
-        denoise_grid = rearrange(denoise_row, 'n b c h w -> b n c h w')
-        denoise_grid = rearrange(denoise_grid, 'b n c h w -> (b n) c h w')
-        denoise_grid = make_grid(denoise_grid, nrow=n_imgs_per_row)
-        return denoise_grid
-
-    def get_first_stage_encoding(self, encoder_posterior):# encode_emb from autoencoder
-        if isinstance(encoder_posterior, DiagonalGaussianDistribution):
-            z = encoder_posterior.sample()
-        elif isinstance(encoder_posterior, torch.Tensor):
-            z = encoder_posterior
-        else:
-            raise NotImplementedError(f"encoder_posterior of type '{type(encoder_posterior)}' not yet implemented")
-        return self.scale_factor * z
-
-    def get_learned_conditioning(self, c):
-        if self.cond_stage_forward is None:
-            if hasattr(self.cond_stage_model, 'encode') and callable(self.cond_stage_model.encode):
-                c = self.cond_stage_model.encode(c)
-                if isinstance(c, DiagonalGaussianDistribution):
-                    c = c.mode()
-            else:
-                c = self.cond_stage_model(c)
-        else:
-            assert hasattr(self.cond_stage_model, self.cond_stage_forward)
-            c = getattr(self.cond_stage_model, self.cond_stage_forward)(c)
-        return c
-
-    def meshgrid(self, h, w):
-        y = torch.arange(0, h).view(h, 1, 1).repeat(1, w, 1)
-        x = torch.arange(0, w).view(1, w, 1).repeat(h, 1, 1)
-
-        arr = torch.cat([y, x], dim=-1)
-        return arr
-
-    def delta_border(self, h, w):
-        """
-        :param h: height
-        :param w: width
-        :return: normalized distance to image border,
-         wtith min distance = 0 at border and max dist = 0.5 at image center
-        """
-        lower_right_corner = torch.tensor([h - 1, w - 1]).view(1, 1, 2)
-        arr = self.meshgrid(h, w) / lower_right_corner
-        dist_left_up = torch.min(arr, dim=-1, keepdims=True)[0]
-        dist_right_down = torch.min(1 - arr, dim=-1, keepdims=True)[0]
-        edge_dist = torch.min(torch.cat([dist_left_up, dist_right_down], dim=-1), dim=-1)[0]
-        return edge_dist
-
-    def get_weighting(self, h, w, Ly, Lx, device):
-        weighting = self.delta_border(h, w)
-        weighting = torch.clip(weighting, self.split_input_params["clip_min_weight"],
-                               self.split_input_params["clip_max_weight"], )
-        weighting = weighting.view(1, h * w, 1).repeat(1, 1, Ly * Lx).to(device)
-
-        if self.split_input_params["tie_braker"]:
-            L_weighting = self.delta_border(Ly, Lx)
-            L_weighting = torch.clip(L_weighting,
-                                     self.split_input_params["clip_min_tie_weight"],
-                                     self.split_input_params["clip_max_tie_weight"])
-
-            L_weighting = L_weighting.view(1, 1, Ly * Lx).to(device)
-            weighting = weighting * L_weighting
-        return weighting
-
-    def get_fold_unfold(self, x, kernel_size, stride, uf=1, df=1):  # todo load once not every time, shorten code
-        """
-        :param x: img of size (bs, c, h, w)
-        :return: n img crops of size (n, bs, c, kernel_size[0], kernel_size[1])
-        """
-        bs, nc, h, w = x.shape
-
-        # number of crops in image
-        Ly = (h - kernel_size[0]) // stride[0] + 1
-        Lx = (w - kernel_size[1]) // stride[1] + 1
-
-        if uf == 1 and df == 1:
-            fold_params = dict(kernel_size=kernel_size, dilation=1, padding=0, stride=stride)
-            unfold = torch.nn.Unfold(**fold_params)
-
-            fold = torch.nn.Fold(output_size=x.shape[2:], **fold_params)
-
-            weighting = self.get_weighting(kernel_size[0], kernel_size[1], Ly, Lx, x.device).to(x.dtype)
-            normalization = fold(weighting).view(1, 1, h, w)  # normalizes the overlap
-            weighting = weighting.view((1, 1, kernel_size[0], kernel_size[1], Ly * Lx))
-
-        elif uf > 1 and df == 1:
-            fold_params = dict(kernel_size=kernel_size, dilation=1, padding=0, stride=stride)
-            unfold = torch.nn.Unfold(**fold_params)
-
-            fold_params2 = dict(kernel_size=(kernel_size[0] * uf, kernel_size[0] * uf),
-                                dilation=1, padding=0,
-                                stride=(stride[0] * uf, stride[1] * uf))
-            fold = torch.nn.Fold(output_size=(x.shape[2] * uf, x.shape[3] * uf), **fold_params2)
-
-            weighting = self.get_weighting(kernel_size[0] * uf, kernel_size[1] * uf, Ly, Lx, x.device).to(x.dtype)
-            normalization = fold(weighting).view(1, 1, h * uf, w * uf)  # normalizes the overlap
-            weighting = weighting.view((1, 1, kernel_size[0] * uf, kernel_size[1] * uf, Ly * Lx))
-
-        elif df > 1 and uf == 1:
-            fold_params = dict(kernel_size=kernel_size, dilation=1, padding=0, stride=stride)
-            unfold = torch.nn.Unfold(**fold_params)
-
-            fold_params2 = dict(kernel_size=(kernel_size[0] // df, kernel_size[0] // df),
-                                dilation=1, padding=0,
-                                stride=(stride[0] // df, stride[1] // df))
-            fold = torch.nn.Fold(output_size=(x.shape[2] // df, x.shape[3] // df), **fold_params2)
-
-            weighting = self.get_weighting(kernel_size[0] // df, kernel_size[1] // df, Ly, Lx, x.device).to(x.dtype)
-            normalization = fold(weighting).view(1, 1, h // df, w // df)  # normalizes the overlap
-            weighting = weighting.view((1, 1, kernel_size[0] // df, kernel_size[1] // df, Ly * Lx))
-
-        else:
-            raise NotImplementedError
-
-        return fold, unfold, normalization, weighting
-
-    @torch.no_grad()
-    def get_input(self, batch, k, return_first_stage_outputs=False, force_c_encode=False,
-                  cond_key=None, return_original_cond=False, bs=None):
-        x = super().get_input(batch, k)
-        if bs is not None:
-            x = x[:bs]
-        x = x.to(self.device)
-        encoder_posterior = self.encode_first_stage(x)
-        z = self.get_first_stage_encoding(encoder_posterior).detach()
-
-        if self.model.conditioning_key is not None:# 'crossattn' for txt2image, 'hybird' for txt_inpaint
-            if cond_key is None:
-                cond_key = self.cond_stage_key # 'caption' for txt_inpaint
-            if self.model.conditioning_key == 'hybrid':
-                xc = {}
-                assert cond_key == 'caption' # only txt_inpaint is implemented now
-                assert 'masked_image' in batch.keys() 
-                assert 'mask' in batch.keys()
-                masked_image = super().get_input(batch,'masked_image')
-                mask = super().get_input(batch,'mask')
-                if bs is not None:
-                    masked_image,mask = masked_image[:bs],mask[:bs]
-                masked_image,mask = masked_image.to(self.device),mask.to(self.device)
-                masked_image = self.get_first_stage_encoding(self.encode_first_stage(masked_image)).detach()
-                resized_mask = torch.nn.functional.interpolate(mask,size=masked_image.shape[-2:])
-                xc['c_concat'] = torch.cat((masked_image,resized_mask),dim = 1)
-                xc[cond_key] = batch[cond_key]
-            else:
-                if cond_key != self.first_stage_key:
-                    if cond_key in ['caption', 'coordinates_bbox']:
-                        xc = batch[cond_key]
-                    elif cond_key == 'class_label':
-                        xc = batch
-                    else:
-                        xc = super().get_input(batch, cond_key).to(self.device)
-                else:# cond_key == 'image'
-                    xc = x
-            if not self.cond_stage_trainable or force_c_encode:# cond_stage_trainable is true for txt2img，force_c_encoder = True，when called in log_images
-                if isinstance(xc, list):
-                    # import pudb; pudb.set_trace()
-                    c = self.get_learned_conditioning(xc)# 因为log_images内接下来要调用sample_log,所以需要预先得到处理好的c
-                if isinstance(xc, dict):
-                    c = {}
-                    c['c_concat'] = xc['c_concat']
-                    c['c_crossattn'] = self.get_learned_conditioning(xc[cond_key])
-                else:
-                    c = self.get_learned_conditioning(xc.to(self.device))
-            else:
-                c = xc
-            if bs is not None:
-                if isinstance(c,dict):
-                    for k in c.keys():
-                        c[k] = c[k][:bs]
-                else:
-                    c = c[:bs]
-
-            if self.use_positional_encodings:
-                pos_x, pos_y = self.compute_latent_shifts(batch)
-                ckey = __conditioning_keys__[self.model.conditioning_key]
-                c = {ckey: c, 'pos_x': pos_x, 'pos_y': pos_y}
-
-        else:
-            c = None
-            xc = None
-            if self.use_positional_encodings:
-                pos_x, pos_y = self.compute_latent_shifts(batch)
-                c = {'pos_x': pos_x, 'pos_y': pos_y}
-        out = [z, c]
-        if return_first_stage_outputs:
-            xrec = self.decode_first_stage(z)
-            out.extend([x, xrec])
-        if return_original_cond:
-            out.append(xc)
-        return out
-
-    @torch.no_grad()
-    def decode_first_stage(self, z, predict_cids=False, force_not_quantize=False):
-        if predict_cids:
-            if z.dim() == 4:
-                z = torch.argmax(z.exp(), dim=1).long()
-            z = self.first_stage_model.quantize.get_codebook_entry(z, shape=None)
-            z = rearrange(z, 'b h w c -> b c h w').contiguous()
-
-        z = 1. / self.scale_factor * z
-
-        if hasattr(self, "split_input_params"):
-            if self.split_input_params["patch_distributed_vq"]:
-                ks = self.split_input_params["ks"]  # eg. (128, 128)
-                stride = self.split_input_params["stride"]  # eg. (64, 64)
-                uf = self.split_input_params["vqf"]
-                bs, nc, h, w = z.shape
-                if ks[0] > h or ks[1] > w:
-                    ks = (min(ks[0], h), min(ks[1], w))
-                    print("reducing Kernel")
-
-                if stride[0] > h or stride[1] > w:
-                    stride = (min(stride[0], h), min(stride[1], w))
-                    print("reducing stride")
-
-                fold, unfold, normalization, weighting = self.get_fold_unfold(z, ks, stride, uf=uf)
-
-                z = unfold(z)  # (bn, nc * prod(**ks), L)
-                # 1. Reshape to img shape
-                z = z.view((z.shape[0], -1, ks[0], ks[1], z.shape[-1]))  # (bn, nc, ks[0], ks[1], L )
-
-                # 2. apply model loop over last dim
-                if isinstance(self.first_stage_model, VQModelInterface):
-                    output_list = [self.first_stage_model.decode(z[:, :, :, :, i],
-                                                                 force_not_quantize=predict_cids or force_not_quantize)
-                                   for i in range(z.shape[-1])]
-                else:
-
-                    output_list = [self.first_stage_model.decode(z[:, :, :, :, i])
-                                   for i in range(z.shape[-1])]
-
-                o = torch.stack(output_list, axis=-1)  # # (bn, nc, ks[0], ks[1], L)
-                o = o * weighting
-                # Reverse 1. reshape to img shape
-                o = o.view((o.shape[0], -1, o.shape[-1]))  # (bn, nc * ks[0] * ks[1], L)
-                # stitch crops together
-                decoded = fold(o)
-                decoded = decoded / normalization  # norm is shape (1, 1, h, w)
-                return decoded
-            else:
-                if isinstance(self.first_stage_model, VQModelInterface):
-                    return self.first_stage_model.decode(z, force_not_quantize=predict_cids or force_not_quantize)
-                else:
-                    return self.first_stage_model.decode(z)
-
-        else:
-            if isinstance(self.first_stage_model, VQModelInterface):
-                return self.first_stage_model.decode(z, force_not_quantize=predict_cids or force_not_quantize)
-            else:
-                return self.first_stage_model.decode(z)
-
-    # same as above but without decorator
-    def differentiable_decode_first_stage(self, z, predict_cids=False, force_not_quantize=False):
-        if predict_cids:
-            if z.dim() == 4:
-                z = torch.argmax(z.exp(), dim=1).long()
-            z = self.first_stage_model.quantize.get_codebook_entry(z, shape=None)
-            z = rearrange(z, 'b h w c -> b c h w').contiguous()
-
-        z = 1. / self.scale_factor * z
-
-        if hasattr(self, "split_input_params"):
-            if self.split_input_params["patch_distributed_vq"]:
-                ks = self.split_input_params["ks"]  # eg. (128, 128)
-                stride = self.split_input_params["stride"]  # eg. (64, 64)
-                uf = self.split_input_params["vqf"]
-                bs, nc, h, w = z.shape
-                if ks[0] > h or ks[1] > w:
-                    ks = (min(ks[0], h), min(ks[1], w))
-                    print("reducing Kernel")
-
-                if stride[0] > h or stride[1] > w:
-                    stride = (min(stride[0], h), min(stride[1], w))
-                    print("reducing stride")
-
-                fold, unfold, normalization, weighting = self.get_fold_unfold(z, ks, stride, uf=uf)
-
-                z = unfold(z)  # (bn, nc * prod(**ks), L)
-                # 1. Reshape to img shape
-                z = z.view((z.shape[0], -1, ks[0], ks[1], z.shape[-1]))  # (bn, nc, ks[0], ks[1], L )
-
-                # 2. apply model loop over last dim
-                if isinstance(self.first_stage_model, VQModelInterface):  
-                    output_list = [self.first_stage_model.decode(z[:, :, :, :, i],
-                                                                 force_not_quantize=predict_cids or force_not_quantize)
-                                   for i in range(z.shape[-1])]
-                else:
-
-                    output_list = [self.first_stage_model.decode(z[:, :, :, :, i])
-                                   for i in range(z.shape[-1])]
-
-                o = torch.stack(output_list, axis=-1)  # # (bn, nc, ks[0], ks[1], L)
-                o = o * weighting
-                # Reverse 1. reshape to img shape
-                o = o.view((o.shape[0], -1, o.shape[-1]))  # (bn, nc * ks[0] * ks[1], L)
-                # stitch crops together
-                decoded = fold(o)
-                decoded = decoded / normalization  # norm is shape (1, 1, h, w)
-                return decoded
-            else:
-                if isinstance(self.first_stage_model, VQModelInterface):
-                    return self.first_stage_model.decode(z, force_not_quantize=predict_cids or force_not_quantize)
-                else:
-                    return self.first_stage_model.decode(z)
-
-        else:
-            if isinstance(self.first_stage_model, VQModelInterface):
-                return self.first_stage_model.decode(z, force_not_quantize=predict_cids or force_not_quantize)
-            else:
-                return self.first_stage_model.decode(z)
-
-    @torch.no_grad()
-    def encode_first_stage(self, x):
-        if hasattr(self, "split_input_params"):
-            if self.split_input_params["patch_distributed_vq"]:
-                ks = self.split_input_params["ks"]  # eg. (128, 128)
-                stride = self.split_input_params["stride"]  # eg. (64, 64)
-                df = self.split_input_params["vqf"]
-                self.split_input_params['original_image_size'] = x.shape[-2:]
-                bs, nc, h, w = x.shape
-                if ks[0] > h or ks[1] > w:
-                    ks = (min(ks[0], h), min(ks[1], w))
-                    print("reducing Kernel")
-
-                if stride[0] > h or stride[1] > w:
-                    stride = (min(stride[0], h), min(stride[1], w))
-                    print("reducing stride")
-
-                fold, unfold, normalization, weighting = self.get_fold_unfold(x, ks, stride, df=df)
-                z = unfold(x)  # (bn, nc * prod(**ks), L)
-                # Reshape to img shape
-                z = z.view((z.shape[0], -1, ks[0], ks[1], z.shape[-1]))  # (bn, nc, ks[0], ks[1], L )
-
-                output_list = [self.first_stage_model.encode(z[:, :, :, :, i])
-                               for i in range(z.shape[-1])]
-
-                o = torch.stack(output_list, axis=-1)
-                o = o * weighting
-
-                # Reverse reshape to img shape
-                o = o.view((o.shape[0], -1, o.shape[-1]))  # (bn, nc * ks[0] * ks[1], L)
-                # stitch crops together
-                decoded = fold(o)
-                decoded = decoded / normalization
-                return decoded
-
-            else:
-                return self.first_stage_model.encode(x)
-        else:
-            return self.first_stage_model.encode(x)
-
-    def shared_step(self, batch, **kwargs):
-        x, c = self.get_input(batch, self.first_stage_key)# get latent and condition
-        loss = self(x, c)
-        return loss
-
-    def test_step(self,batch,batch_idx):
-        # TODO make self.test_repeat work
-        cond = {}
-        cond[self.cond_stage_key] = batch[self.cond_stage_key]
-        cond[self.cond_stage_key] = self.get_learned_conditioning(cond[self.cond_stage_key]) # c: string -> [B, T, Context_dim]
-        cond['c_crossattn'] = cond.pop(self.cond_stage_key)
-        masked_image = super().get_input(batch,'masked_image')
-        mask = super().get_input(batch,'mask')
-        masked_image,mask = masked_image.to(self.device),mask.to(self.device)
-        masked_image = self.get_first_stage_encoding(self.encode_first_stage(masked_image)).detach()
-        resized_mask = torch.nn.functional.interpolate(mask,size=masked_image.shape[-2:])
-        cond['c_concat'] = torch.cat((masked_image,resized_mask),dim = 1)
-        batch_size = len(batch[self.cond_stage_key])
-        # shape = [batch_size,self.channels,self.mel_dim,self.mel_length]
-        enc_emb = self.sample(cond,batch_size,timesteps=self.test_numsteps)
-        xrec = self.decode_first_stage(enc_emb)
-        reconstructions = (xrec + 1)/2 # to mel scale
-        test_ckpt_path = os.path.basename(self.trainer.tested_ckpt_path)
-        savedir = os.path.join(self.trainer.log_dir,f'output_imgs_{test_ckpt_path}','fake_class')
-        if not os.path.exists(savedir):
-            os.makedirs(savedir)
-
-        file_names = batch['f_name']
-        nfiles = len(file_names)
-        reconstructions = reconstructions.cpu().numpy().squeeze(1) # squuze channel dim
-        for k in range(reconstructions.shape[0]):
-            b,repeat = k % nfiles, k // nfiles
-            vname_num_split_index = file_names[b].rfind('_')# file_names[b]:video_name+'_'+num
-            v_n,num = file_names[b][:vname_num_split_index],file_names[b][vname_num_split_index+1:]
-            save_img_path = os.path.join(savedir,f'{v_n}_sample_{num}_{repeat}.npy')# the num_th caption, the repeat_th repitition
-            np.save(save_img_path,reconstructions[b])
-        
-        return None
-
-    def forward(self, x, c, *args, **kwargs):
-        t = torch.randint(0, self.num_timesteps, (x.shape[0],), device=self.device).long()
-        if self.model.conditioning_key is not None:
-            assert c is not None
-            if self.cond_stage_trainable:
-                if isinstance(c,dict):
-                    c[self.cond_stage_key] = self.get_learned_conditioning(c[self.cond_stage_key])
-                    c['c_crossattn'] = c.pop(self.cond_stage_key)
-                else:
-                    c = self.get_learned_conditioning(c) # c: string -> [B, T, Context_dim]
-            if self.shorten_cond_schedule:  # TODO: drop this option
-                tc = self.cond_ids[t].to(self.device)
-                c = self.q_sample(x_start=c, t=tc, noise=torch.randn_like(c.float()))
-        return self.p_losses(x, c, t, *args, **kwargs)
-
-    def _rescale_annotations(self, bboxes, crop_coordinates):  # TODO: move to dataset
-        def rescale_bbox(bbox):
-            x0 = torch.clamp((bbox[0] - crop_coordinates[0]) / crop_coordinates[2])
-            y0 = torch.clamp((bbox[1] - crop_coordinates[1]) / crop_coordinates[3])
-            w = min(bbox[2] / crop_coordinates[2], 1 - x0)
-            h = min(bbox[3] / crop_coordinates[3], 1 - y0)
-            return x0, y0, w, h
-
-        return [rescale_bbox(b) for b in bboxes]
-
-    def apply_model(self, x_noisy, t, cond, return_ids=False):
-        # make values to list to enable concat operation in 
-        if isinstance(cond, dict):
-            # hybrid case, cond is exptected to be a dict. (txt2inpaint)
-            cond_tmp = {}# use cond_tmp to avoid inplace edit
-            for k,v in cond.items():
-                if not isinstance(v, list):
-                    cond_tmp[k] = [cond[k]]
-                else:
-                    cond_tmp[k] = cond[k]
-            cond = cond_tmp
-        else:
-            if not isinstance(cond, list):
-                cond = [cond]
-            key = 'c_concat' if self.model.conditioning_key == 'concat' else 'c_crossattn'
-            cond = {key: cond}
-
-        if hasattr(self, "split_input_params"):
-            assert len(cond) == 1  # todo can only deal with one conditioning atm
-            assert not return_ids  
-            ks = self.split_input_params["ks"]  # eg. (128, 128)
-            stride = self.split_input_params["stride"]  # eg. (64, 64)
-
-            h, w = x_noisy.shape[-2:]
-
-            fold, unfold, normalization, weighting = self.get_fold_unfold(x_noisy, ks, stride)
-
-            z = unfold(x_noisy)  # (bn, nc * prod(**ks), L)
-            # Reshape to img shape
-            z = z.view((z.shape[0], -1, ks[0], ks[1], z.shape[-1]))  # (bn, nc, ks[0], ks[1], L )
-            z_list = [z[:, :, :, :, i] for i in range(z.shape[-1])]
-
-            if self.cond_stage_key in ["image", "LR_image", "segmentation",
-                                       'bbox_img'] and self.model.conditioning_key:  # todo check for completeness
-                c_key = next(iter(cond.keys()))  # get key
-                c = next(iter(cond.values()))  # get value
-                assert (len(c) == 1)  # todo extend to list with more than one elem
-                c = c[0]  # get element
-
-                c = unfold(c)
-                c = c.view((c.shape[0], -1, ks[0], ks[1], c.shape[-1]))  # (bn, nc, ks[0], ks[1], L )
-
-                cond_list = [{c_key: [c[:, :, :, :, i]]} for i in range(c.shape[-1])]
-
-            elif self.cond_stage_key == 'coordinates_bbox':
-                assert 'original_image_size' in self.split_input_params, 'BoudingBoxRescaling is missing original_image_size'
-
-                # assuming padding of unfold is always 0 and its dilation is always 1
-                n_patches_per_row = int((w - ks[0]) / stride[0] + 1)
-                full_img_h, full_img_w = self.split_input_params['original_image_size']
-                # as we are operating on latents, we need the factor from the original image size to the
-                # spatial latent size to properly rescale the crops for regenerating the bbox annotations
-                num_downs = self.first_stage_model.encoder.num_resolutions - 1
-                rescale_latent = 2 ** (num_downs)
-
-                # get top left postions of patches as conforming for the bbbox tokenizer, therefore we
-                # need to rescale the tl patch coordinates to be in between (0,1)
-                tl_patch_coordinates = [(rescale_latent * stride[0] * (patch_nr % n_patches_per_row) / full_img_w,
-                                         rescale_latent * stride[1] * (patch_nr // n_patches_per_row) / full_img_h)
-                                        for patch_nr in range(z.shape[-1])]
-
-                # patch_limits are tl_coord, width and height coordinates as (x_tl, y_tl, h, w)
-                patch_limits = [(x_tl, y_tl,
-                                 rescale_latent * ks[0] / full_img_w,
-                                 rescale_latent * ks[1] / full_img_h) for x_tl, y_tl in tl_patch_coordinates]
-                # patch_values = [(np.arange(x_tl,min(x_tl+ks, 1.)),np.arange(y_tl,min(y_tl+ks, 1.))) for x_tl, y_tl in tl_patch_coordinates]
-
-                # tokenize crop coordinates for the bounding boxes of the respective patches
-                patch_limits_tknzd = [torch.LongTensor(self.bbox_tokenizer._crop_encoder(bbox))[None].to(self.device)
-                                      for bbox in patch_limits]  # list of length l with tensors of shape (1, 2)
-                print(patch_limits_tknzd[0].shape)
-                # cut tknzd crop position from conditioning
-                assert isinstance(cond, dict), 'cond must be dict to be fed into model'
-                cut_cond = cond['c_crossattn'][0][..., :-2].to(self.device)
-                print(cut_cond.shape)
-
-                adapted_cond = torch.stack([torch.cat([cut_cond, p], dim=1) for p in patch_limits_tknzd])
-                adapted_cond = rearrange(adapted_cond, 'l b n -> (l b) n')
-                print(adapted_cond.shape)
-                adapted_cond = self.get_learned_conditioning(adapted_cond)
-                print(adapted_cond.shape)
-                adapted_cond = rearrange(adapted_cond, '(l b) n d -> l b n d', l=z.shape[-1])
-                print(adapted_cond.shape)
-
-                cond_list = [{'c_crossattn': [e]} for e in adapted_cond]
-
-            else:
-                cond_list = [cond for i in range(z.shape[-1])]  # Todo make this more efficient
-
-            # apply model by loop over crops
-            output_list = [self.model(z_list[i], t, **cond_list[i]) for i in range(z.shape[-1])]
-            assert not isinstance(output_list[0],
-                                  tuple)  # todo cant deal with multiple model outputs check this never happens
-
-            o = torch.stack(output_list, axis=-1)
-            o = o * weighting
-            # Reverse reshape to img shape
-            o = o.view((o.shape[0], -1, o.shape[-1]))  # (bn, nc * ks[0] * ks[1], L)
-            # stitch crops together
-            x_recon = fold(o) / normalization
-
-        else:
-            # x_noisy is tensor with shape [b,c,mel_len,T]
-            # if condition is caption ,cond['c_crossattn'] is a list, each item shape is [1, 77, 1280]
-            x_recon = self.model(x_noisy, t, **cond)# tensor with shape [b,c,mel_len,T]
-
-        if isinstance(x_recon, tuple) and not return_ids:
-            return x_recon[0]
-        else:
-            return x_recon
-
-    def _predict_eps_from_xstart(self, x_t, t, pred_xstart):
-        return (extract_into_tensor(self.sqrt_recip_alphas_cumprod, t, x_t.shape) * x_t - pred_xstart) / \
-               extract_into_tensor(self.sqrt_recipm1_alphas_cumprod, t, x_t.shape)
-
-    def _prior_bpd(self, x_start):
-        """
-        Get the prior KL term for the variational lower-bound, measured in
-        bits-per-dim.
-        This term can't be optimized, as it only depends on the encoder.
-        :param x_start: the [N x C x ...] tensor of inputs.
-        :return: a batch of [N] KL values (in bits), one per batch element.
-        """
-        batch_size = x_start.shape[0]
-        t = torch.tensor([self.num_timesteps - 1] * batch_size, device=x_start.device)
-        qt_mean, _, qt_log_variance = self.q_mean_variance(x_start, t)
-        kl_prior = normal_kl(mean1=qt_mean, logvar1=qt_log_variance, mean2=0.0, logvar2=0.0)
-        return mean_flat(kl_prior) / np.log(2.0)
-
-    def p_losses(self, x_start, cond, t, noise=None):
-        noise = default(noise, lambda: torch.randn_like(x_start))
-        x_noisy = self.q_sample(x_start=x_start, t=t, noise=noise)
-        model_output = self.apply_model(x_noisy, t, cond)
-
-        loss_dict = {}
-        prefix = 'train' if self.training else 'val'
-
-        if self.parameterization == "x0":
-            target = x_start
-        elif self.parameterization == "eps":
-            target = noise
-        else:
-            raise NotImplementedError()
-
-        loss_simple = self.get_loss(model_output, target, mean=False).mean([1, 2, 3])
-        loss_dict.update({f'{prefix}/loss_simple': loss_simple.mean()})
-
-        logvar_t = self.logvar[t].to(self.device)
-        loss = loss_simple / torch.exp(logvar_t) + logvar_t
-        # loss = loss_simple / torch.exp(self.logvar) + self.logvar
-        if self.learn_logvar:
-            loss_dict.update({f'{prefix}/loss_gamma': loss.mean()})
-            loss_dict.update({'logvar': self.logvar.data.mean()})
-
-        loss = self.l_simple_weight * loss.mean()
-
-        loss_vlb = self.get_loss(model_output, target, mean=False).mean(dim=(1, 2, 3))
-        loss_vlb = (self.lvlb_weights[t] * loss_vlb).mean()
-        loss_dict.update({f'{prefix}/loss_vlb': loss_vlb})
-        loss += (self.original_elbo_weight * loss_vlb)
-        loss_dict.update({f'{prefix}/loss': loss})
-
-        return loss, loss_dict
-
-    def p_mean_variance(self, x, c, t, clip_denoised: bool, return_codebook_ids=False, quantize_denoised=False,
-                        return_x0=False, score_corrector=None, corrector_kwargs=None):
-        t_in = t
-        model_out = self.apply_model(x, t_in, c, return_ids=return_codebook_ids)
-
-        if score_corrector is not None:
-            assert self.parameterization == "eps"
-            model_out = score_corrector.modify_score(self, model_out, x, t, c, **corrector_kwargs)
-
-        if return_codebook_ids:
-            model_out, logits = model_out
-
-        if self.parameterization == "eps":
-            x_recon = self.predict_start_from_noise(x, t=t, noise=model_out)
-        elif self.parameterization == "x0":
-            x_recon = model_out
-        else:
-            raise NotImplementedError()
-
-        if clip_denoised:
-            x_recon.clamp_(-1., 1.)
-        if quantize_denoised:
-            x_recon, _, [_, _, indices] = self.first_stage_model.quantize(x_recon)
-        model_mean, posterior_variance, posterior_log_variance = self.q_posterior(x_start=x_recon, x_t=x, t=t)
-        if return_codebook_ids:
-            return model_mean, posterior_variance, posterior_log_variance, logits
-        elif return_x0:
-            return model_mean, posterior_variance, posterior_log_variance, x_recon
-        else:
-            return model_mean, posterior_variance, posterior_log_variance
-
-    @torch.no_grad()
-    def p_sample(self, x, c, t, clip_denoised=False, repeat_noise=False,
-                 return_codebook_ids=False, quantize_denoised=False, return_x0=False,
-                 temperature=1., noise_dropout=0., score_corrector=None, corrector_kwargs=None):
-        b, *_, device = *x.shape, x.device
-        outputs = self.p_mean_variance(x=x, c=c, t=t, clip_denoised=clip_denoised,
-                                       return_codebook_ids=return_codebook_ids,
-                                       quantize_denoised=quantize_denoised,
-                                       return_x0=return_x0,
-                                       score_corrector=score_corrector, corrector_kwargs=corrector_kwargs)
-        if return_codebook_ids:
-            raise DeprecationWarning("Support dropped.")
-            model_mean, _, model_log_variance, logits = outputs
-        elif return_x0:
-            model_mean, _, model_log_variance, x0 = outputs
-        else:
-            model_mean, _, model_log_variance = outputs
-
-        noise = noise_like(x.shape, device, repeat_noise) * temperature
-        if noise_dropout > 0.:
-            noise = torch.nn.functional.dropout(noise, p=noise_dropout)
-        # no noise when t == 0
-        nonzero_mask = (1 - (t == 0).float()).reshape(b, *((1,) * (len(x.shape) - 1)))
-
-        if return_codebook_ids:
-            return model_mean + nonzero_mask * (0.5 * model_log_variance).exp() * noise, logits.argmax(dim=1)
-        if return_x0:
-            return model_mean + nonzero_mask * (0.5 * model_log_variance).exp() * noise, x0
-        else:
-            return model_mean + nonzero_mask * (0.5 * model_log_variance).exp() * noise
-
-    @torch.no_grad()
-    def progressive_denoising(self, cond, shape, verbose=True, callback=None, quantize_denoised=False,
-                              img_callback=None, mask=None, x0=None, temperature=1., noise_dropout=0.,
-                              score_corrector=None, corrector_kwargs=None, batch_size=None, x_T=None, start_T=None,
-                              log_every_t=None):
-        if not log_every_t:
-            log_every_t = self.log_every_t
-        timesteps = self.num_timesteps
-        if batch_size is not None:
-            b = batch_size if batch_size is not None else shape[0]
-            shape = [batch_size] + list(shape)
-        else:
-            b = batch_size = shape[0]
-        if x_T is None:
-            img = torch.randn(shape, device=self.device)
-        else:
-            img = x_T
-        intermediates = []
-        if cond is not None:
-            if isinstance(cond, dict):
-                cond = {key: cond[key][:batch_size] if not isinstance(cond[key], list) else
-                list(map(lambda x: x[:batch_size], cond[key])) for key in cond}
-            else:
-                cond = [c[:batch_size] for c in cond] if isinstance(cond, list) else cond[:batch_size]
-
-        if start_T is not None:
-            timesteps = min(timesteps, start_T)
-        iterator = tqdm(reversed(range(0, timesteps)), desc='Progressive Generation',
-                        total=timesteps) if verbose else reversed(
-            range(0, timesteps))
-        if type(temperature) == float:
-            temperature = [temperature] * timesteps
-
-        for i in iterator:
-            ts = torch.full((b,), i, device=self.device, dtype=torch.long)
-            if self.shorten_cond_schedule:
-                assert self.model.conditioning_key != 'hybrid'
-                tc = self.cond_ids[ts].to(cond.device)
-                cond = self.q_sample(x_start=cond, t=tc, noise=torch.randn_like(cond))
-
-            img, x0_partial = self.p_sample(img, cond, ts,
-                                            clip_denoised=self.clip_denoised,
-                                            quantize_denoised=quantize_denoised, return_x0=True,
-                                            temperature=temperature[i], noise_dropout=noise_dropout,
-                                            score_corrector=score_corrector, corrector_kwargs=corrector_kwargs)
-            if mask is not None:
-                assert x0 is not None
-                img_orig = self.q_sample(x0, ts)
-                img = img_orig * mask + (1. - mask) * img
-
-            if i % log_every_t == 0 or i == timesteps - 1:
-                intermediates.append(x0_partial)
-            if callback: callback(i)
-            if img_callback: img_callback(img, i)
-        return img, intermediates
-
-    @torch.no_grad()
-    def p_sample_loop(self, cond, shape, return_intermediates=False,
-                      x_T=None, verbose=True, callback=None, timesteps=None, quantize_denoised=False,
-                      mask=None, x0=None, img_callback=None, start_T=None,
-                      log_every_t=None):
-
-        if not log_every_t:
-            log_every_t = self.log_every_t
-        device = self.betas.device
-        b = shape[0]
-        if x_T is None:
-            img = torch.randn(shape, device=device)
-        else:
-            img = x_T
-
-        intermediates = [img]
-        if timesteps is None:
-            timesteps = self.num_timesteps
-
-        if start_T is not None:
-            timesteps = min(timesteps, start_T)
-        iterator = tqdm(reversed(range(0, timesteps)), desc='Sampling t', total=timesteps) if verbose else reversed(
-            range(0, timesteps))
-
-        if mask is not None:
-            assert x0 is not None
-            assert x0.shape[2:3] == mask.shape[2:3]  # spatial size has to match
-
-        for i in iterator:
-            ts = torch.full((b,), i, device=device, dtype=torch.long)
-            if self.shorten_cond_schedule:
-                assert self.model.conditioning_key != 'hybrid'
-                tc = self.cond_ids[ts].to(cond.device)
-                cond = self.q_sample(x_start=cond, t=tc, noise=torch.randn_like(cond))
-
-            img = self.p_sample(img, cond, ts,
-                                clip_denoised=self.clip_denoised,
-                                quantize_denoised=quantize_denoised)
-            if mask is not None:
-                img_orig = self.q_sample(x0, ts)
-                img = img_orig * mask + (1. - mask) * img
-
-            if i % log_every_t == 0 or i == timesteps - 1:
-                intermediates.append(img)
-            if callback: callback(i)
-            if img_callback: img_callback(img, i)
-
-        if return_intermediates:
-            return img, intermediates
-        return img
-
-    @torch.no_grad()
-    def sample(self, cond, batch_size=16, return_intermediates=False, x_T=None,
-               verbose=True, timesteps=None, quantize_denoised=False,
-               mask=None, x0=None, shape=None,**kwargs):
-        if shape is None:
-            shape = (batch_size, self.channels, self.mel_dim, self.mel_length)
-        if cond is not None:
-            if isinstance(cond, dict):
-                cond = {key: cond[key][:batch_size] if not isinstance(cond[key], list) else
-                list(map(lambda x: x[:batch_size], cond[key])) for key in cond}
-            else:
-                cond = [c[:batch_size] for c in cond] if isinstance(cond, list) else cond[:batch_size]
-        return self.p_sample_loop(cond,
-                                  shape,
-                                  return_intermediates=return_intermediates, x_T=x_T,
-                                  verbose=verbose, timesteps=timesteps, quantize_denoised=quantize_denoised,
-                                  mask=mask, x0=x0)
-
-    @torch.no_grad()
-    def sample_log(self,cond,batch_size,ddim, ddim_steps,**kwargs):
-        if ddim:
-            ddim_sampler = DDIMSampler(self)
-            shape = (self.channels, self.mel_dim, self.mel_length)
-            samples, intermediates =ddim_sampler.sample(ddim_steps,batch_size,
-                                                        shape,cond,verbose=False,**kwargs)
-
-        else:
-            samples, intermediates = self.sample(cond=cond, batch_size=batch_size,
-                                                 return_intermediates=True,**kwargs)
-
-        return samples, intermediates
-
-    @torch.no_grad()
-    def log_images(self, batch, N=8, n_row=4, sample=True, ddim_steps=200, ddim_eta=1., return_keys=None,
-                   quantize_denoised=True, inpaint=True, plot_denoise_rows=False, plot_progressive_rows=True,
-                   plot_diffusion_rows=True, **kwargs):
-
-        use_ddim = ddim_steps is not None
-
-        log = dict()
-        z, c, x, xrec, xc = self.get_input(batch, self.first_stage_key,
-                                           return_first_stage_outputs=True,
-                                           force_c_encode=True,
-                                           return_original_cond=True,
-                                           bs=N)
-
-        N = min(x.shape[0], N)
-        n_row = min(x.shape[0], n_row)
-        log["inputs"] = x # 原始输入图像
-        log["reconstruction"] = xrec # 重建得到的图像
-        if self.model.conditioning_key is not None:
-            if hasattr(self.cond_stage_model, "decode"):# when cond_stage is first_stage. (bert embedder doesnot have decode)
-                xc = self.cond_stage_model.decode(c)# decoded masked image
-                log["conditioning"] = xc # 重建后的图像
-            elif self.cond_stage_key in ["caption"]:
-                xc = log_txt_as_img((x.shape[2], x.shape[3]), batch["caption"])
-                log["conditioning"] = xc # 含有文本的图像 
-                if self.model.conditioning_key == 'hybrid':
-                    log["decoded_maskedimg"] = self.first_stage_model.decode(c['c_concat'][:,:self.first_stage_model.embed_dim])# c_concat is the concat result of masked_img latent and resized mask. get latent here to decode
-            elif self.cond_stage_key == 'class_label':
-                xc = log_txt_as_img((x.shape[2], x.shape[3]), batch["human_label"])
-                log['conditioning'] = xc # 文本为类标签的图像
-            elif isimage(xc):
-                log["conditioning"] = xc
-            if ismap(xc):
-                log["original_conditioning"] = self.to_rgb(xc)
-
-        if plot_diffusion_rows:# diffusion每一步的图像
-            # get diffusion row
-            diffusion_row = list()
-            z_start = z[:n_row]
-            for t in range(self.num_timesteps):
-                if t % self.log_every_t == 0 or t == self.num_timesteps - 1:
-                    t = repeat(torch.tensor([t]), '1 -> b', b=n_row)
-                    t = t.to(self.device).long()
-                    noise = torch.randn_like(z_start)
-                    z_noisy = self.q_sample(x_start=z_start, t=t, noise=noise)
-                    diffusion_row.append(self.decode_first_stage(z_noisy))
-
-            diffusion_row = torch.stack(diffusion_row)  # n_log_step, n_row, C, H, W
-            diffusion_grid = rearrange(diffusion_row, 'n b c h w -> b n c h w')
-            diffusion_grid = rearrange(diffusion_grid, 'b n c h w -> (b n) c h w')
-            diffusion_grid = make_grid(diffusion_grid, nrow=diffusion_row.shape[0])
-            log["diffusion_row"] = diffusion_grid
-
-        if sample:# 
-            # get denoise row
-            with self.ema_scope("Plotting"):
-                samples, z_denoise_row = self.sample_log(cond=c,batch_size=N,ddim=use_ddim,
-                                                         ddim_steps=ddim_steps,eta=ddim_eta)
-                # samples, z_denoise_row = self.sample(cond=c, batch_size=N, return_intermediates=True)
-            x_samples = self.decode_first_stage(samples)
-            log["samples"] = x_samples
-            if plot_denoise_rows:
-                denoise_grid = self._get_denoise_row_from_list(z_denoise_row)
-                log["denoise_row"] = denoise_grid
-
-            if quantize_denoised and not isinstance(self.first_stage_model, AutoencoderKL) and not isinstance(
-                    self.first_stage_model, IdentityFirstStage):
-                # also display when quantizing x0 while sampling
-                with self.ema_scope("Plotting Quantized Denoised"):
-                    samples, z_denoise_row = self.sample_log(cond=c,batch_size=N,ddim=use_ddim,
-                                                             ddim_steps=ddim_steps,eta=ddim_eta,
-                                                             quantize_denoised=True)
-                    # samples, z_denoise_row = self.sample(cond=c, batch_size=N, return_intermediates=True,
-                    #                                      quantize_denoised=True)
-                x_samples = self.decode_first_stage(samples.to(self.device))
-                log["samples_x0_quantized"] = x_samples
-
-            if inpaint:
-                # make a simple center square
-                b, h, w = z.shape[0], z.shape[2], z.shape[3]
-                mask = torch.ones(N, h, w).to(self.device)
-                # zeros will be filled in
-                mask[:, h // 4:3 * h // 4, w // 4:3 * w // 4] = 0.
-                mask = mask[:, None, ...]# N,1,H,W
-                with self.ema_scope("Plotting Inpaint"):
-                    samples, _ = self.sample_log(cond=c,batch_size=N,ddim=use_ddim, eta=ddim_eta,
-                                                ddim_steps=ddim_steps, x0=z[:N], mask=mask)
-                x_samples = self.decode_first_stage(samples.to(self.device))
-                log["samples_inpainting"] = x_samples
-                log["mask"] = mask
-
-                # outpaint
-                with self.ema_scope("Plotting Outpaint"):
-                    samples, _ = self.sample_log(cond=c, batch_size=N, ddim=use_ddim,eta=ddim_eta,
-                                                ddim_steps=ddim_steps, x0=z[:N], mask=mask)
-                x_samples = self.decode_first_stage(samples.to(self.device))
-                log["samples_outpainting"] = x_samples
-
-        if plot_progressive_rows:
-            with self.ema_scope("Plotting Progressives"):
-                img, progressives = self.progressive_denoising(c,
-                                                               shape=(self.channels, self.mel_dim, self.mel_length),
-                                                               batch_size=N)
-            prog_row = self._get_denoise_row_from_list(progressives, desc="Progressive Generation")
-            log["progressive_row"] = prog_row
-
-        if return_keys:
-            if np.intersect1d(list(log.keys()), return_keys).shape[0] == 0:
-                return log
-            else:
-                return {key: log[key] for key in return_keys}
-        return log
-
-    def configure_optimizers(self):
-        lr = self.learning_rate
-        params = list(self.model.parameters())
-        if self.cond_stage_trainable:
-            print(f"{self.__class__.__name__}: Also optimizing conditioner params!")
-            params = params + list(self.cond_stage_model.parameters())
-        if self.learn_logvar:
-            print('Diffusion model optimizing logvar')
-            params.append(self.logvar)
-        opt = torch.optim.AdamW(params, lr=lr)
-        if self.use_scheduler:
-            assert 'target' in self.scheduler_config
-            scheduler = instantiate_from_config(self.scheduler_config)
-
-            print("Setting up LambdaLR scheduler...")
-            scheduler = [
-                {
-                    'scheduler': LambdaLR(opt, lr_lambda=scheduler.schedule),
-                    'interval': 'step',
-                    'frequency': 1
-                }]
-            return [opt], scheduler
-        return opt
-
-    @torch.no_grad()
-    def to_rgb(self, x):
-        x = x.float()
-        if not hasattr(self, "colorize"):
-            self.colorize = torch.randn(3, x.shape[1], 1, 1).to(x)
-        x = nn.functional.conv2d(x, weight=self.colorize)
-        x = 2. * (x - x.min()) / (x.max() - x.min()) - 1.
-        return x
-
diff --git a/spaces/AchyuthGamer/OpenGPT-Chat-UI/src/routes/logout/+page.server.ts b/spaces/AchyuthGamer/OpenGPT-Chat-UI/src/routes/logout/+page.server.ts
deleted file mode 100644
index 1d60b6c5d8df28981da4d06d5ea58eeeaf838b47..0000000000000000000000000000000000000000
--- a/spaces/AchyuthGamer/OpenGPT-Chat-UI/src/routes/logout/+page.server.ts
+++ /dev/null
@@ -1,17 +0,0 @@
-import { dev } from "$app/environment";
-import { base } from "$app/paths";
-import { COOKIE_NAME } from "$env/static/private";
-import { redirect } from "@sveltejs/kit";
-
-export const actions = {
-	default: async function ({ cookies }) {
-		cookies.delete(COOKIE_NAME, {
-			path: "/",
-			// So that it works inside the space's iframe
-			sameSite: dev ? "lax" : "none",
-			secure: !dev,
-			httpOnly: true,
-		});
-		throw redirect(303, `${base}/`);
-	},
-};
diff --git a/spaces/Adr740/Hadith_AI_Explorer/data.py b/spaces/Adr740/Hadith_AI_Explorer/data.py
deleted file mode 100644
index 136bd1e5e925c8936cb792ae2bce1dc830308dff..0000000000000000000000000000000000000000
--- a/spaces/Adr740/Hadith_AI_Explorer/data.py
+++ /dev/null
@@ -1,2 +0,0 @@
-import pandas as pd
-data = pd.read_pickle("pickle_ebd.pkl")
diff --git a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/basesizer/PreLayout.js b/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/basesizer/PreLayout.js
deleted file mode 100644
index 6869558720041323d5bc41a1ac7e90f51c10468f..0000000000000000000000000000000000000000
--- a/spaces/AgentVerse/agentVerse/ui/src/phaser3-rex-plugins/templates/ui/basesizer/PreLayout.js
+++ /dev/null
@@ -1,15 +0,0 @@
-var PreLayout = function () {
-    this._childrenWidth = undefined;
-    this._childrenHeight = undefined;
-
-    var children = this.getChildrenSizers(),
-        child;
-    for (var i = 0, cnt = children.length; i < cnt; i++) {
-        child = children[i];
-        if (child.ignoreLayout) {
-            continue;
-        }
-        child.preLayout();
-    }
-}
-export default PreLayout;
\ No newline at end of file
diff --git a/spaces/Ailexcoder/GPT4ALL1/app.py b/spaces/Ailexcoder/GPT4ALL1/app.py
deleted file mode 100644
index 30287cab6d0c1aa31c6361afa856f9b231210488..0000000000000000000000000000000000000000
--- a/spaces/Ailexcoder/GPT4ALL1/app.py
+++ /dev/null
@@ -1,143 +0,0 @@
-from __future__ import annotations
-from typing import Iterable
-import gradio as gr
-from gradio.themes.base import Base
-from gradio.themes.utils import colors, fonts, sizes
-
-from llama_cpp import Llama
-from huggingface_hub import hf_hub_download
-
-hf_hub_download(repo_id="LLukas22/gpt4all-lora-quantized-ggjt", filename="ggjt-model.bin", local_dir=".")
-llm = Llama(model_path="./ggjt-model.bin", n_threads=2)
-
-
-ins = '''### Instruction:
-{}
-### Response:
-'''
-
-theme = gr.themes.Monochrome(
-    primary_hue="indigo",
-    secondary_hue="blue",
-    neutral_hue="slate",
-    radius_size=gr.themes.sizes.radius_sm,
-    font=[gr.themes.GoogleFont("Open Sans"), "ui-sans-serif", "system-ui", "sans-serif"],
-)
-
-
-
-
-# def generate(instruction): 
-#     response = llm(ins.format(instruction))
-#     response = response['choices'][0]['text']
-#     result = ""
-#     for word in response.split(" "):
-#         result += word + " "
-#         yield result
-
-def generate(instruction): 
-    result = ""
-    for x in llm(ins.format(instruction), stop=['### Instruction:', '### End'], stream=True):
-        result += x['choices'][0]['text']
-        yield result
-
-
-examples = [
-    "Instead of making a peanut butter and jelly sandwich, what else could I combine peanut butter with in a sandwich? Give five ideas",
-    "How do I make a campfire?",
-    "Explain to me the difference between nuclear fission and fusion.",
-    "I'm selling my Nikon D-750, write a short blurb for my ad."
-]
-
-def process_example(args):
-    for x in generate(args):
-        pass
-    return x
-    
-css = ".generating {visibility: hidden}"
-
-# Based on the gradio theming guide and borrowed from https://huggingface.co/spaces/shivi/dolly-v2-demo
-class SeafoamCustom(Base):
-    def __init__(
-        self,
-        *,
-        primary_hue: colors.Color | str = colors.emerald,
-        secondary_hue: colors.Color | str = colors.blue,
-        neutral_hue: colors.Color | str = colors.blue,
-        spacing_size: sizes.Size | str = sizes.spacing_md,
-        radius_size: sizes.Size | str = sizes.radius_md,
-        font: fonts.Font
-        | str
-        | Iterable[fonts.Font | str] = (
-            fonts.GoogleFont("Quicksand"),
-            "ui-sans-serif",
-            "sans-serif",
-        ),
-        font_mono: fonts.Font
-        | str
-        | Iterable[fonts.Font | str] = (
-            fonts.GoogleFont("IBM Plex Mono"),
-            "ui-monospace",
-            "monospace",
-        ),
-    ):
-        super().__init__(
-            primary_hue=primary_hue,
-            secondary_hue=secondary_hue,
-            neutral_hue=neutral_hue,
-            spacing_size=spacing_size,
-            radius_size=radius_size,
-            font=font,
-            font_mono=font_mono,
-        )
-        super().set(
-            button_primary_background_fill="linear-gradient(90deg, *primary_300, *secondary_400)",
-            button_primary_background_fill_hover="linear-gradient(90deg, *primary_200, *secondary_300)",
-            button_primary_text_color="white",
-            button_primary_background_fill_dark="linear-gradient(90deg, *primary_600, *secondary_800)",
-            block_shadow="*shadow_drop_lg",
-            button_shadow="*shadow_drop_lg",
-            input_background_fill="zinc",
-            input_border_color="*secondary_300",
-            input_shadow="*shadow_drop",
-            input_shadow_focus="*shadow_drop_lg",
-        )
-
-
-seafoam = SeafoamCustom()
-
-
-with gr.Blocks(theme=seafoam, analytics_enabled=False, css=css) as demo:
-    with gr.Column():
-        gr.Markdown(
-            """ ## GPT4ALL
-            
-            An ecosystem of open-source chatbots trained on a massive collections of clean assistant data including code, stories and dialogue
-            
-            Type in the box below and click the button to generate answers to your most pressing questions!
-            
-      """
-        )
-
-        with gr.Row():
-            with gr.Column(scale=3):
-                instruction = gr.Textbox(placeholder="Enter your question here", label="Question", elem_id="q-input")
-
-                with gr.Box():
-                    gr.Markdown("**Answer**")
-                    output = gr.Markdown(elem_id="q-output")
-                submit = gr.Button("Generate", variant="primary")
-                gr.Examples(
-                    examples=examples,
-                    inputs=[instruction],
-                    cache_examples=True,
-                    fn=process_example,
-                    outputs=[output],
-                )
-        
-
-
-    submit.click(generate, inputs=[instruction], outputs=[output])
-    instruction.submit(generate, inputs=[instruction], outputs=[output])
-
-demo.queue(concurrency_count=1).launch(debug=True)
\ No newline at end of file
diff --git a/spaces/AlexWang/lama/saicinpainting/training/data/__init__.py b/spaces/AlexWang/lama/saicinpainting/training/data/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/examples/community/sd_text2img_k_diffusion.py b/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/examples/community/sd_text2img_k_diffusion.py
deleted file mode 100644
index b7fbc46b67cbe88cd82f2f88b4fbcdeb1fac51e0..0000000000000000000000000000000000000000
--- a/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/examples/community/sd_text2img_k_diffusion.py
+++ /dev/null
@@ -1,475 +0,0 @@
-# Copyright 2023 The HuggingFace Team. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import importlib
-import warnings
-from typing import Callable, List, Optional, Union
-
-import torch
-from k_diffusion.external import CompVisDenoiser, CompVisVDenoiser
-
-from diffusers import DiffusionPipeline, LMSDiscreteScheduler
-from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
-from diffusers.utils import is_accelerate_available, logging
-
-
-logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
-
-
-class ModelWrapper:
-    def __init__(self, model, alphas_cumprod):
-        self.model = model
-        self.alphas_cumprod = alphas_cumprod
-
-    def apply_model(self, *args, **kwargs):
-        if len(args) == 3:
-            encoder_hidden_states = args[-1]
-            args = args[:2]
-        if kwargs.get("cond", None) is not None:
-            encoder_hidden_states = kwargs.pop("cond")
-        return self.model(*args, encoder_hidden_states=encoder_hidden_states, **kwargs).sample
-
-
-class StableDiffusionPipeline(DiffusionPipeline):
-    r"""
-    Pipeline for text-to-image generation using Stable Diffusion.
-
-    This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods the
-    library implements for all the pipelines (such as downloading or saving, running on a particular device, etc.)
-
-    Args:
-        vae ([`AutoencoderKL`]):
-            Variational Auto-Encoder (VAE) Model to encode and decode images to and from latent representations.
-        text_encoder ([`CLIPTextModel`]):
-            Frozen text-encoder. Stable Diffusion uses the text portion of
-            [CLIP](https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPTextModel), specifically
-            the [clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14) variant.
-        tokenizer (`CLIPTokenizer`):
-            Tokenizer of class
-            [CLIPTokenizer](https://huggingface.co/docs/transformers/v4.21.0/en/model_doc/clip#transformers.CLIPTokenizer).
-        unet ([`UNet2DConditionModel`]): Conditional U-Net architecture to denoise the encoded image latents.
-        scheduler ([`SchedulerMixin`]):
-            A scheduler to be used in combination with `unet` to denoise the encoded image latents. Can be one of
-            [`DDIMScheduler`], [`LMSDiscreteScheduler`], or [`PNDMScheduler`].
-        safety_checker ([`StableDiffusionSafetyChecker`]):
-            Classification module that estimates whether generated images could be considered offensive or harmful.
-            Please, refer to the [model card](https://huggingface.co/runwayml/stable-diffusion-v1-5) for details.
-        feature_extractor ([`CLIPImageProcessor`]):
-            Model that extracts features from generated images to be used as inputs for the `safety_checker`.
-    """
-    _optional_components = ["safety_checker", "feature_extractor"]
-
-    def __init__(
-        self,
-        vae,
-        text_encoder,
-        tokenizer,
-        unet,
-        scheduler,
-        safety_checker,
-        feature_extractor,
-    ):
-        super().__init__()
-
-        if safety_checker is None:
-            logger.warning(
-                f"You have disabled the safety checker for {self.__class__} by passing `safety_checker=None`. Ensure"
-                " that you abide to the conditions of the Stable Diffusion license and do not expose unfiltered"
-                " results in services or applications open to the public. Both the diffusers team and Hugging Face"
-                " strongly recommend to keep the safety filter enabled in all public facing circumstances, disabling"
-                " it only for use-cases that involve analyzing network behavior or auditing its results. For more"
-                " information, please have a look at https://github.com/huggingface/diffusers/pull/254 ."
-            )
-
-        # get correct sigmas from LMS
-        scheduler = LMSDiscreteScheduler.from_config(scheduler.config)
-        self.register_modules(
-            vae=vae,
-            text_encoder=text_encoder,
-            tokenizer=tokenizer,
-            unet=unet,
-            scheduler=scheduler,
-            safety_checker=safety_checker,
-            feature_extractor=feature_extractor,
-        )
-
-        model = ModelWrapper(unet, scheduler.alphas_cumprod)
-        if scheduler.config.prediction_type == "v_prediction":
-            self.k_diffusion_model = CompVisVDenoiser(model)
-        else:
-            self.k_diffusion_model = CompVisDenoiser(model)
-
-    def set_sampler(self, scheduler_type: str):
-        warnings.warn("The `set_sampler` method is deprecated, please use `set_scheduler` instead.")
-        return self.set_scheduler(scheduler_type)
-
-    def set_scheduler(self, scheduler_type: str):
-        library = importlib.import_module("k_diffusion")
-        sampling = getattr(library, "sampling")
-        self.sampler = getattr(sampling, scheduler_type)
-
-    def enable_attention_slicing(self, slice_size: Optional[Union[str, int]] = "auto"):
-        r"""
-        Enable sliced attention computation.
-
-        When this option is enabled, the attention module will split the input tensor in slices, to compute attention
-        in several steps. This is useful to save some memory in exchange for a small speed decrease.
-
-        Args:
-            slice_size (`str` or `int`, *optional*, defaults to `"auto"`):
-                When `"auto"`, halves the input to the attention heads, so attention will be computed in two steps. If
-                a number is provided, uses as many slices as `attention_head_dim // slice_size`. In this case,
-                `attention_head_dim` must be a multiple of `slice_size`.
-        """
-        if slice_size == "auto":
-            # half the attention head size is usually a good trade-off between
-            # speed and memory
-            slice_size = self.unet.config.attention_head_dim // 2
-        self.unet.set_attention_slice(slice_size)
-
-    def disable_attention_slicing(self):
-        r"""
-        Disable sliced attention computation. If `enable_attention_slicing` was previously invoked, this method will go
-        back to computing attention in one step.
-        """
-        # set slice_size = `None` to disable `attention slicing`
-        self.enable_attention_slicing(None)
-
-    def enable_sequential_cpu_offload(self, gpu_id=0):
-        r"""
-        Offloads all models to CPU using accelerate, significantly reducing memory usage. When called, unet,
-        text_encoder, vae and safety checker have their state dicts saved to CPU and then are moved to a
-        `torch.device('meta') and loaded to GPU only when their specific submodule has its `forward` method called.
-        """
-        if is_accelerate_available():
-            from accelerate import cpu_offload
-        else:
-            raise ImportError("Please install accelerate via `pip install accelerate`")
-
-        device = torch.device(f"cuda:{gpu_id}")
-
-        for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae, self.safety_checker]:
-            if cpu_offloaded_model is not None:
-                cpu_offload(cpu_offloaded_model, device)
-
-    @property
-    def _execution_device(self):
-        r"""
-        Returns the device on which the pipeline's models will be executed. After calling
-        `pipeline.enable_sequential_cpu_offload()` the execution device can only be inferred from Accelerate's module
-        hooks.
-        """
-        if self.device != torch.device("meta") or not hasattr(self.unet, "_hf_hook"):
-            return self.device
-        for module in self.unet.modules():
-            if (
-                hasattr(module, "_hf_hook")
-                and hasattr(module._hf_hook, "execution_device")
-                and module._hf_hook.execution_device is not None
-            ):
-                return torch.device(module._hf_hook.execution_device)
-        return self.device
-
-    def _encode_prompt(self, prompt, device, num_images_per_prompt, do_classifier_free_guidance, negative_prompt):
-        r"""
-        Encodes the prompt into text encoder hidden states.
-
-        Args:
-            prompt (`str` or `list(int)`):
-                prompt to be encoded
-            device: (`torch.device`):
-                torch device
-            num_images_per_prompt (`int`):
-                number of images that should be generated per prompt
-            do_classifier_free_guidance (`bool`):
-                whether to use classifier free guidance or not
-            negative_prompt (`str` or `List[str]`):
-                The prompt or prompts not to guide the image generation. Ignored when not using guidance (i.e., ignored
-                if `guidance_scale` is less than `1`).
-        """
-        batch_size = len(prompt) if isinstance(prompt, list) else 1
-
-        text_inputs = self.tokenizer(
-            prompt,
-            padding="max_length",
-            max_length=self.tokenizer.model_max_length,
-            truncation=True,
-            return_tensors="pt",
-        )
-        text_input_ids = text_inputs.input_ids
-        untruncated_ids = self.tokenizer(prompt, padding="max_length", return_tensors="pt").input_ids
-
-        if not torch.equal(text_input_ids, untruncated_ids):
-            removed_text = self.tokenizer.batch_decode(untruncated_ids[:, self.tokenizer.model_max_length - 1 : -1])
-            logger.warning(
-                "The following part of your input was truncated because CLIP can only handle sequences up to"
-                f" {self.tokenizer.model_max_length} tokens: {removed_text}"
-            )
-
-        if hasattr(self.text_encoder.config, "use_attention_mask") and self.text_encoder.config.use_attention_mask:
-            attention_mask = text_inputs.attention_mask.to(device)
-        else:
-            attention_mask = None
-
-        text_embeddings = self.text_encoder(
-            text_input_ids.to(device),
-            attention_mask=attention_mask,
-        )
-        text_embeddings = text_embeddings[0]
-
-        # duplicate text embeddings for each generation per prompt, using mps friendly method
-        bs_embed, seq_len, _ = text_embeddings.shape
-        text_embeddings = text_embeddings.repeat(1, num_images_per_prompt, 1)
-        text_embeddings = text_embeddings.view(bs_embed * num_images_per_prompt, seq_len, -1)
-
-        # get unconditional embeddings for classifier free guidance
-        if do_classifier_free_guidance:
-            uncond_tokens: List[str]
-            if negative_prompt is None:
-                uncond_tokens = [""] * batch_size
-            elif type(prompt) is not type(negative_prompt):
-                raise TypeError(
-                    f"`negative_prompt` should be the same type to `prompt`, but got {type(negative_prompt)} !="
-                    f" {type(prompt)}."
-                )
-            elif isinstance(negative_prompt, str):
-                uncond_tokens = [negative_prompt]
-            elif batch_size != len(negative_prompt):
-                raise ValueError(
-                    f"`negative_prompt`: {negative_prompt} has batch size {len(negative_prompt)}, but `prompt`:"
-                    f" {prompt} has batch size {batch_size}. Please make sure that passed `negative_prompt` matches"
-                    " the batch size of `prompt`."
-                )
-            else:
-                uncond_tokens = negative_prompt
-
-            max_length = text_input_ids.shape[-1]
-            uncond_input = self.tokenizer(
-                uncond_tokens,
-                padding="max_length",
-                max_length=max_length,
-                truncation=True,
-                return_tensors="pt",
-            )
-
-            if hasattr(self.text_encoder.config, "use_attention_mask") and self.text_encoder.config.use_attention_mask:
-                attention_mask = uncond_input.attention_mask.to(device)
-            else:
-                attention_mask = None
-
-            uncond_embeddings = self.text_encoder(
-                uncond_input.input_ids.to(device),
-                attention_mask=attention_mask,
-            )
-            uncond_embeddings = uncond_embeddings[0]
-
-            # duplicate unconditional embeddings for each generation per prompt, using mps friendly method
-            seq_len = uncond_embeddings.shape[1]
-            uncond_embeddings = uncond_embeddings.repeat(1, num_images_per_prompt, 1)
-            uncond_embeddings = uncond_embeddings.view(batch_size * num_images_per_prompt, seq_len, -1)
-
-            # For classifier free guidance, we need to do two forward passes.
-            # Here we concatenate the unconditional and text embeddings into a single batch
-            # to avoid doing two forward passes
-            text_embeddings = torch.cat([uncond_embeddings, text_embeddings])
-
-        return text_embeddings
-
-    def run_safety_checker(self, image, device, dtype):
-        if self.safety_checker is not None:
-            safety_checker_input = self.feature_extractor(self.numpy_to_pil(image), return_tensors="pt").to(device)
-            image, has_nsfw_concept = self.safety_checker(
-                images=image, clip_input=safety_checker_input.pixel_values.to(dtype)
-            )
-        else:
-            has_nsfw_concept = None
-        return image, has_nsfw_concept
-
-    def decode_latents(self, latents):
-        latents = 1 / 0.18215 * latents
-        image = self.vae.decode(latents).sample
-        image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
-        image = image.cpu().permute(0, 2, 3, 1).float().numpy()
-        return image
-
-    def check_inputs(self, prompt, height, width, callback_steps):
-        if not isinstance(prompt, str) and not isinstance(prompt, list):
-            raise ValueError(f"`prompt` has to be of type `str` or `list` but is {type(prompt)}")
-
-        if height % 8 != 0 or width % 8 != 0:
-            raise ValueError(f"`height` and `width` have to be divisible by 8 but are {height} and {width}.")
-
-        if (callback_steps is None) or (
-            callback_steps is not None and (not isinstance(callback_steps, int) or callback_steps <= 0)
-        ):
-            raise ValueError(
-                f"`callback_steps` has to be a positive integer but is {callback_steps} of type"
-                f" {type(callback_steps)}."
-            )
-
-    def prepare_latents(self, batch_size, num_channels_latents, height, width, dtype, device, generator, latents=None):
-        shape = (batch_size, num_channels_latents, height // 8, width // 8)
-        if latents is None:
-            if device.type == "mps":
-                # randn does not work reproducibly on mps
-                latents = torch.randn(shape, generator=generator, device="cpu", dtype=dtype).to(device)
-            else:
-                latents = torch.randn(shape, generator=generator, device=device, dtype=dtype)
-        else:
-            if latents.shape != shape:
-                raise ValueError(f"Unexpected latents shape, got {latents.shape}, expected {shape}")
-            latents = latents.to(device)
-
-        # scale the initial noise by the standard deviation required by the scheduler
-        return latents
-
-    @torch.no_grad()
-    def __call__(
-        self,
-        prompt: Union[str, List[str]],
-        height: int = 512,
-        width: int = 512,
-        num_inference_steps: int = 50,
-        guidance_scale: float = 7.5,
-        negative_prompt: Optional[Union[str, List[str]]] = None,
-        num_images_per_prompt: Optional[int] = 1,
-        eta: float = 0.0,
-        generator: Optional[torch.Generator] = None,
-        latents: Optional[torch.FloatTensor] = None,
-        output_type: Optional[str] = "pil",
-        return_dict: bool = True,
-        callback: Optional[Callable[[int, int, torch.FloatTensor], None]] = None,
-        callback_steps: int = 1,
-        **kwargs,
-    ):
-        r"""
-        Function invoked when calling the pipeline for generation.
-
-        Args:
-            prompt (`str` or `List[str]`):
-                The prompt or prompts to guide the image generation.
-            height (`int`, *optional*, defaults to 512):
-                The height in pixels of the generated image.
-            width (`int`, *optional*, defaults to 512):
-                The width in pixels of the generated image.
-            num_inference_steps (`int`, *optional*, defaults to 50):
-                The number of denoising steps. More denoising steps usually lead to a higher quality image at the
-                expense of slower inference.
-            guidance_scale (`float`, *optional*, defaults to 7.5):
-                Guidance scale as defined in [Classifier-Free Diffusion Guidance](https://arxiv.org/abs/2207.12598).
-                `guidance_scale` is defined as `w` of equation 2. of [Imagen
-                Paper](https://arxiv.org/pdf/2205.11487.pdf). Guidance scale is enabled by setting `guidance_scale >
-                1`. Higher guidance scale encourages to generate images that are closely linked to the text `prompt`,
-                usually at the expense of lower image quality.
-            negative_prompt (`str` or `List[str]`, *optional*):
-                The prompt or prompts not to guide the image generation. Ignored when not using guidance (i.e., ignored
-                if `guidance_scale` is less than `1`).
-            num_images_per_prompt (`int`, *optional*, defaults to 1):
-                The number of images to generate per prompt.
-            eta (`float`, *optional*, defaults to 0.0):
-                Corresponds to parameter eta (η) in the DDIM paper: https://arxiv.org/abs/2010.02502. Only applies to
-                [`schedulers.DDIMScheduler`], will be ignored for others.
-            generator (`torch.Generator`, *optional*):
-                A [torch generator](https://pytorch.org/docs/stable/generated/torch.Generator.html) to make generation
-                deterministic.
-            latents (`torch.FloatTensor`, *optional*):
-                Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
-                generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
-            output_type (`str`, *optional*, defaults to `"pil"`):
-                The output format of the generate image. Choose between
-                [PIL](https://pillow.readthedocs.io/en/stable/): `PIL.Image.Image` or `np.array`.
-            return_dict (`bool`, *optional*, defaults to `True`):
-                Whether or not to return a [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] instead of a
-                plain tuple.
-            callback (`Callable`, *optional*):
-                A function that will be called every `callback_steps` steps during inference. The function will be
-                called with the following arguments: `callback(step: int, timestep: int, latents: torch.FloatTensor)`.
-            callback_steps (`int`, *optional*, defaults to 1):
-                The frequency at which the `callback` function will be called. If not specified, the callback will be
-                called at every step.
-
-        Returns:
-            [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] or `tuple`:
-            [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] if `return_dict` is True, otherwise a `tuple.
-            When returning a tuple, the first element is a list with the generated images, and the second element is a
-            list of `bool`s denoting whether the corresponding generated image likely represents "not-safe-for-work"
-            (nsfw) content, according to the `safety_checker`.
-        """
-
-        # 1. Check inputs. Raise error if not correct
-        self.check_inputs(prompt, height, width, callback_steps)
-
-        # 2. Define call parameters
-        batch_size = 1 if isinstance(prompt, str) else len(prompt)
-        device = self._execution_device
-        # here `guidance_scale` is defined analog to the guidance weight `w` of equation (2)
-        # of the Imagen paper: https://arxiv.org/pdf/2205.11487.pdf . `guidance_scale = 1`
-        # corresponds to doing no classifier free guidance.
-        do_classifier_free_guidance = True
-        if guidance_scale <= 1.0:
-            raise ValueError("has to use guidance_scale")
-
-        # 3. Encode input prompt
-        text_embeddings = self._encode_prompt(
-            prompt, device, num_images_per_prompt, do_classifier_free_guidance, negative_prompt
-        )
-
-        # 4. Prepare timesteps
-        self.scheduler.set_timesteps(num_inference_steps, device=text_embeddings.device)
-        sigmas = self.scheduler.sigmas
-        sigmas = sigmas.to(text_embeddings.dtype)
-
-        # 5. Prepare latent variables
-        num_channels_latents = self.unet.config.in_channels
-        latents = self.prepare_latents(
-            batch_size * num_images_per_prompt,
-            num_channels_latents,
-            height,
-            width,
-            text_embeddings.dtype,
-            device,
-            generator,
-            latents,
-        )
-        latents = latents * sigmas[0]
-        self.k_diffusion_model.sigmas = self.k_diffusion_model.sigmas.to(latents.device)
-        self.k_diffusion_model.log_sigmas = self.k_diffusion_model.log_sigmas.to(latents.device)
-
-        def model_fn(x, t):
-            latent_model_input = torch.cat([x] * 2)
-
-            noise_pred = self.k_diffusion_model(latent_model_input, t, cond=text_embeddings)
-
-            noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)
-            noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond)
-            return noise_pred
-
-        latents = self.sampler(model_fn, latents, sigmas)
-
-        # 8. Post-processing
-        image = self.decode_latents(latents)
-
-        # 9. Run safety checker
-        image, has_nsfw_concept = self.run_safety_checker(image, device, text_embeddings.dtype)
-
-        # 10. Convert to PIL
-        if output_type == "pil":
-            image = self.numpy_to_pil(image)
-
-        if not return_dict:
-            return (image, has_nsfw_concept)
-
-        return StableDiffusionPipelineOutput(images=image, nsfw_content_detected=has_nsfw_concept)
diff --git a/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/examples/community/text_inpainting.py b/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/examples/community/text_inpainting.py
deleted file mode 100644
index 99a488788a0de6db78ae7c2c89038565efd29551..0000000000000000000000000000000000000000
--- a/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/examples/community/text_inpainting.py
+++ /dev/null
@@ -1,302 +0,0 @@
-from typing import Callable, List, Optional, Union
-
-import PIL
-import torch
-from transformers import (
-    CLIPImageProcessor,
-    CLIPSegForImageSegmentation,
-    CLIPSegProcessor,
-    CLIPTextModel,
-    CLIPTokenizer,
-)
-
-from diffusers import DiffusionPipeline
-from diffusers.configuration_utils import FrozenDict
-from diffusers.models import AutoencoderKL, UNet2DConditionModel
-from diffusers.pipelines.stable_diffusion import StableDiffusionInpaintPipeline
-from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
-from diffusers.schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler
-from diffusers.utils import deprecate, is_accelerate_available, logging
-
-
-logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
-
-
-class TextInpainting(DiffusionPipeline):
-    r"""
-    Pipeline for text based inpainting using Stable Diffusion.
-    Uses CLIPSeg to get a mask from the given text, then calls the Inpainting pipeline with the generated mask
-
-    This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods the
-    library implements for all the pipelines (such as downloading or saving, running on a particular device, etc.)
-
-    Args:
-        segmentation_model ([`CLIPSegForImageSegmentation`]):
-            CLIPSeg Model to generate mask from the given text. Please refer to the [model card]() for details.
-        segmentation_processor ([`CLIPSegProcessor`]):
-            CLIPSeg processor to get image, text features to translate prompt to English, if necessary. Please refer to the
-            [model card](https://huggingface.co/docs/transformers/model_doc/clipseg) for details.
-        vae ([`AutoencoderKL`]):
-            Variational Auto-Encoder (VAE) Model to encode and decode images to and from latent representations.
-        text_encoder ([`CLIPTextModel`]):
-            Frozen text-encoder. Stable Diffusion uses the text portion of
-            [CLIP](https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPTextModel), specifically
-            the [clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14) variant.
-        tokenizer (`CLIPTokenizer`):
-            Tokenizer of class
-            [CLIPTokenizer](https://huggingface.co/docs/transformers/v4.21.0/en/model_doc/clip#transformers.CLIPTokenizer).
-        unet ([`UNet2DConditionModel`]): Conditional U-Net architecture to denoise the encoded image latents.
-        scheduler ([`SchedulerMixin`]):
-            A scheduler to be used in combination with `unet` to denoise the encoded image latens. Can be one of
-            [`DDIMScheduler`], [`LMSDiscreteScheduler`], or [`PNDMScheduler`].
-        safety_checker ([`StableDiffusionSafetyChecker`]):
-            Classification module that estimates whether generated images could be considered offensive or harmful.
-            Please, refer to the [model card](https://huggingface.co/runwayml/stable-diffusion-v1-5) for details.
-        feature_extractor ([`CLIPImageProcessor`]):
-            Model that extracts features from generated images to be used as inputs for the `safety_checker`.
-    """
-
-    def __init__(
-        self,
-        segmentation_model: CLIPSegForImageSegmentation,
-        segmentation_processor: CLIPSegProcessor,
-        vae: AutoencoderKL,
-        text_encoder: CLIPTextModel,
-        tokenizer: CLIPTokenizer,
-        unet: UNet2DConditionModel,
-        scheduler: Union[DDIMScheduler, PNDMScheduler, LMSDiscreteScheduler],
-        safety_checker: StableDiffusionSafetyChecker,
-        feature_extractor: CLIPImageProcessor,
-    ):
-        super().__init__()
-
-        if hasattr(scheduler.config, "steps_offset") and scheduler.config.steps_offset != 1:
-            deprecation_message = (
-                f"The configuration file of this scheduler: {scheduler} is outdated. `steps_offset`"
-                f" should be set to 1 instead of {scheduler.config.steps_offset}. Please make sure "
-                "to update the config accordingly as leaving `steps_offset` might led to incorrect results"
-                " in future versions. If you have downloaded this checkpoint from the Hugging Face Hub,"
-                " it would be very nice if you could open a Pull request for the `scheduler/scheduler_config.json`"
-                " file"
-            )
-            deprecate("steps_offset!=1", "1.0.0", deprecation_message, standard_warn=False)
-            new_config = dict(scheduler.config)
-            new_config["steps_offset"] = 1
-            scheduler._internal_dict = FrozenDict(new_config)
-
-        if hasattr(scheduler.config, "skip_prk_steps") and scheduler.config.skip_prk_steps is False:
-            deprecation_message = (
-                f"The configuration file of this scheduler: {scheduler} has not set the configuration"
-                " `skip_prk_steps`. `skip_prk_steps` should be set to True in the configuration file. Please make"
-                " sure to update the config accordingly as not setting `skip_prk_steps` in the config might lead to"
-                " incorrect results in future versions. If you have downloaded this checkpoint from the Hugging Face"
-                " Hub, it would be very nice if you could open a Pull request for the"
-                " `scheduler/scheduler_config.json` file"
-            )
-            deprecate("skip_prk_steps not set", "1.0.0", deprecation_message, standard_warn=False)
-            new_config = dict(scheduler.config)
-            new_config["skip_prk_steps"] = True
-            scheduler._internal_dict = FrozenDict(new_config)
-
-        if safety_checker is None:
-            logger.warning(
-                f"You have disabled the safety checker for {self.__class__} by passing `safety_checker=None`. Ensure"
-                " that you abide to the conditions of the Stable Diffusion license and do not expose unfiltered"
-                " results in services or applications open to the public. Both the diffusers team and Hugging Face"
-                " strongly recommend to keep the safety filter enabled in all public facing circumstances, disabling"
-                " it only for use-cases that involve analyzing network behavior or auditing its results. For more"
-                " information, please have a look at https://github.com/huggingface/diffusers/pull/254 ."
-            )
-
-        self.register_modules(
-            segmentation_model=segmentation_model,
-            segmentation_processor=segmentation_processor,
-            vae=vae,
-            text_encoder=text_encoder,
-            tokenizer=tokenizer,
-            unet=unet,
-            scheduler=scheduler,
-            safety_checker=safety_checker,
-            feature_extractor=feature_extractor,
-        )
-
-    def enable_attention_slicing(self, slice_size: Optional[Union[str, int]] = "auto"):
-        r"""
-        Enable sliced attention computation.
-
-        When this option is enabled, the attention module will split the input tensor in slices, to compute attention
-        in several steps. This is useful to save some memory in exchange for a small speed decrease.
-
-        Args:
-            slice_size (`str` or `int`, *optional*, defaults to `"auto"`):
-                When `"auto"`, halves the input to the attention heads, so attention will be computed in two steps. If
-                a number is provided, uses as many slices as `attention_head_dim // slice_size`. In this case,
-                `attention_head_dim` must be a multiple of `slice_size`.
-        """
-        if slice_size == "auto":
-            # half the attention head size is usually a good trade-off between
-            # speed and memory
-            slice_size = self.unet.config.attention_head_dim // 2
-        self.unet.set_attention_slice(slice_size)
-
-    def disable_attention_slicing(self):
-        r"""
-        Disable sliced attention computation. If `enable_attention_slicing` was previously invoked, this method will go
-        back to computing attention in one step.
-        """
-        # set slice_size = `None` to disable `attention slicing`
-        self.enable_attention_slicing(None)
-
-    def enable_sequential_cpu_offload(self):
-        r"""
-        Offloads all models to CPU using accelerate, significantly reducing memory usage. When called, unet,
-        text_encoder, vae and safety checker have their state dicts saved to CPU and then are moved to a
-        `torch.device('meta') and loaded to GPU only when their specific submodule has its `forward` method called.
-        """
-        if is_accelerate_available():
-            from accelerate import cpu_offload
-        else:
-            raise ImportError("Please install accelerate via `pip install accelerate`")
-
-        device = torch.device("cuda")
-
-        for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae, self.safety_checker]:
-            if cpu_offloaded_model is not None:
-                cpu_offload(cpu_offloaded_model, device)
-
-    @property
-    # Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline._execution_device
-    def _execution_device(self):
-        r"""
-        Returns the device on which the pipeline's models will be executed. After calling
-        `pipeline.enable_sequential_cpu_offload()` the execution device can only be inferred from Accelerate's module
-        hooks.
-        """
-        if self.device != torch.device("meta") or not hasattr(self.unet, "_hf_hook"):
-            return self.device
-        for module in self.unet.modules():
-            if (
-                hasattr(module, "_hf_hook")
-                and hasattr(module._hf_hook, "execution_device")
-                and module._hf_hook.execution_device is not None
-            ):
-                return torch.device(module._hf_hook.execution_device)
-        return self.device
-
-    @torch.no_grad()
-    def __call__(
-        self,
-        prompt: Union[str, List[str]],
-        image: Union[torch.FloatTensor, PIL.Image.Image],
-        text: str,
-        height: int = 512,
-        width: int = 512,
-        num_inference_steps: int = 50,
-        guidance_scale: float = 7.5,
-        negative_prompt: Optional[Union[str, List[str]]] = None,
-        num_images_per_prompt: Optional[int] = 1,
-        eta: float = 0.0,
-        generator: Optional[torch.Generator] = None,
-        latents: Optional[torch.FloatTensor] = None,
-        output_type: Optional[str] = "pil",
-        return_dict: bool = True,
-        callback: Optional[Callable[[int, int, torch.FloatTensor], None]] = None,
-        callback_steps: int = 1,
-        **kwargs,
-    ):
-        r"""
-        Function invoked when calling the pipeline for generation.
-
-        Args:
-            prompt (`str` or `List[str]`):
-                The prompt or prompts to guide the image generation.
-            image (`PIL.Image.Image`):
-                `Image`, or tensor representing an image batch which will be inpainted, *i.e.* parts of the image will
-                be masked out with `mask_image` and repainted according to `prompt`.
-            text (`str``):
-                The text to use to generate the mask.
-            height (`int`, *optional*, defaults to 512):
-                The height in pixels of the generated image.
-            width (`int`, *optional*, defaults to 512):
-                The width in pixels of the generated image.
-            num_inference_steps (`int`, *optional*, defaults to 50):
-                The number of denoising steps. More denoising steps usually lead to a higher quality image at the
-                expense of slower inference.
-            guidance_scale (`float`, *optional*, defaults to 7.5):
-                Guidance scale as defined in [Classifier-Free Diffusion Guidance](https://arxiv.org/abs/2207.12598).
-                `guidance_scale` is defined as `w` of equation 2. of [Imagen
-                Paper](https://arxiv.org/pdf/2205.11487.pdf). Guidance scale is enabled by setting `guidance_scale >
-                1`. Higher guidance scale encourages to generate images that are closely linked to the text `prompt`,
-                usually at the expense of lower image quality.
-            negative_prompt (`str` or `List[str]`, *optional*):
-                The prompt or prompts not to guide the image generation. Ignored when not using guidance (i.e., ignored
-                if `guidance_scale` is less than `1`).
-            num_images_per_prompt (`int`, *optional*, defaults to 1):
-                The number of images to generate per prompt.
-            eta (`float`, *optional*, defaults to 0.0):
-                Corresponds to parameter eta (η) in the DDIM paper: https://arxiv.org/abs/2010.02502. Only applies to
-                [`schedulers.DDIMScheduler`], will be ignored for others.
-            generator (`torch.Generator`, *optional*):
-                A [torch generator](https://pytorch.org/docs/stable/generated/torch.Generator.html) to make generation
-                deterministic.
-            latents (`torch.FloatTensor`, *optional*):
-                Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
-                generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
-            output_type (`str`, *optional*, defaults to `"pil"`):
-                The output format of the generate image. Choose between
-                [PIL](https://pillow.readthedocs.io/en/stable/): `PIL.Image.Image` or `np.array`.
-            return_dict (`bool`, *optional*, defaults to `True`):
-                Whether or not to return a [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] instead of a
-                plain tuple.
-            callback (`Callable`, *optional*):
-                A function that will be called every `callback_steps` steps during inference. The function will be
-                called with the following arguments: `callback(step: int, timestep: int, latents: torch.FloatTensor)`.
-            callback_steps (`int`, *optional*, defaults to 1):
-                The frequency at which the `callback` function will be called. If not specified, the callback will be
-                called at every step.
-
-        Returns:
-            [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] or `tuple`:
-            [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] if `return_dict` is True, otherwise a `tuple.
-            When returning a tuple, the first element is a list with the generated images, and the second element is a
-            list of `bool`s denoting whether the corresponding generated image likely represents "not-safe-for-work"
-            (nsfw) content, according to the `safety_checker`.
-        """
-
-        # We use the input text to generate the mask
-        inputs = self.segmentation_processor(
-            text=[text], images=[image], padding="max_length", return_tensors="pt"
-        ).to(self.device)
-        outputs = self.segmentation_model(**inputs)
-        mask = torch.sigmoid(outputs.logits).cpu().detach().unsqueeze(-1).numpy()
-        mask_pil = self.numpy_to_pil(mask)[0].resize(image.size)
-
-        # Run inpainting pipeline with the generated mask
-        inpainting_pipeline = StableDiffusionInpaintPipeline(
-            vae=self.vae,
-            text_encoder=self.text_encoder,
-            tokenizer=self.tokenizer,
-            unet=self.unet,
-            scheduler=self.scheduler,
-            safety_checker=self.safety_checker,
-            feature_extractor=self.feature_extractor,
-        )
-        return inpainting_pipeline(
-            prompt=prompt,
-            image=image,
-            mask_image=mask_pil,
-            height=height,
-            width=width,
-            num_inference_steps=num_inference_steps,
-            guidance_scale=guidance_scale,
-            negative_prompt=negative_prompt,
-            num_images_per_prompt=num_images_per_prompt,
-            eta=eta,
-            generator=generator,
-            latents=latents,
-            output_type=output_type,
-            return_dict=return_dict,
-            callback=callback,
-            callback_steps=callback_steps,
-        )
diff --git a/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/tests/pipelines/kandinsky/test_kandinsky_combined.py b/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/tests/pipelines/kandinsky/test_kandinsky_combined.py
deleted file mode 100644
index 21c8e78cfade2b7b55a91c4badb0a701c311b2e9..0000000000000000000000000000000000000000
--- a/spaces/Androidonnxfork/CivitAi-to-Diffusers/diffusers/tests/pipelines/kandinsky/test_kandinsky_combined.py
+++ /dev/null
@@ -1,335 +0,0 @@
-# coding=utf-8
-# Copyright 2023 HuggingFace Inc.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import unittest
-
-import numpy as np
-
-from diffusers import KandinskyCombinedPipeline, KandinskyImg2ImgCombinedPipeline, KandinskyInpaintCombinedPipeline
-from diffusers.utils import torch_device
-from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
-
-from ..test_pipelines_common import PipelineTesterMixin
-from .test_kandinsky import Dummies
-from .test_kandinsky_img2img import Dummies as Img2ImgDummies
-from .test_kandinsky_inpaint import Dummies as InpaintDummies
-from .test_kandinsky_prior import Dummies as PriorDummies
-
-
-enable_full_determinism()
-
-
-class KandinskyPipelineCombinedFastTests(PipelineTesterMixin, unittest.TestCase):
-    pipeline_class = KandinskyCombinedPipeline
-    params = [
-        "prompt",
-    ]
-    batch_params = ["prompt", "negative_prompt"]
-    required_optional_params = [
-        "generator",
-        "height",
-        "width",
-        "latents",
-        "guidance_scale",
-        "negative_prompt",
-        "num_inference_steps",
-        "return_dict",
-        "guidance_scale",
-        "num_images_per_prompt",
-        "output_type",
-        "return_dict",
-    ]
-    test_xformers_attention = False
-
-    def get_dummy_components(self):
-        dummy = Dummies()
-        prior_dummy = PriorDummies()
-        components = dummy.get_dummy_components()
-
-        components.update({f"prior_{k}": v for k, v in prior_dummy.get_dummy_components().items()})
-        return components
-
-    def get_dummy_inputs(self, device, seed=0):
-        prior_dummy = PriorDummies()
-        inputs = prior_dummy.get_dummy_inputs(device=device, seed=seed)
-        inputs.update(
-            {
-                "height": 64,
-                "width": 64,
-            }
-        )
-        return inputs
-
-    def test_kandinsky(self):
-        device = "cpu"
-
-        components = self.get_dummy_components()
-
-        pipe = self.pipeline_class(**components)
-        pipe = pipe.to(device)
-
-        pipe.set_progress_bar_config(disable=None)
-
-        output = pipe(**self.get_dummy_inputs(device))
-        image = output.images
-
-        image_from_tuple = pipe(
-            **self.get_dummy_inputs(device),
-            return_dict=False,
-        )[0]
-
-        image_slice = image[0, -3:, -3:, -1]
-        image_from_tuple_slice = image_from_tuple[0, -3:, -3:, -1]
-
-        assert image.shape == (1, 64, 64, 3)
-
-        expected_slice = np.array([0.0000, 0.0000, 0.6777, 0.1363, 0.3624, 0.7868, 0.3869, 0.3395, 0.5068])
-
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
-        ), f" expected_slice {expected_slice}, but got {image_slice.flatten()}"
-        assert (
-            np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1e-2
-        ), f" expected_slice {expected_slice}, but got {image_from_tuple_slice.flatten()}"
-
-    @require_torch_gpu
-    def test_offloads(self):
-        pipes = []
-        components = self.get_dummy_components()
-        sd_pipe = self.pipeline_class(**components).to(torch_device)
-        pipes.append(sd_pipe)
-
-        components = self.get_dummy_components()
-        sd_pipe = self.pipeline_class(**components)
-        sd_pipe.enable_model_cpu_offload()
-        pipes.append(sd_pipe)
-
-        components = self.get_dummy_components()
-        sd_pipe = self.pipeline_class(**components)
-        sd_pipe.enable_sequential_cpu_offload()
-        pipes.append(sd_pipe)
-
-        image_slices = []
-        for pipe in pipes:
-            inputs = self.get_dummy_inputs(torch_device)
-            image = pipe(**inputs).images
-
-            image_slices.append(image[0, -3:, -3:, -1].flatten())
-
-        assert np.abs(image_slices[0] - image_slices[1]).max() < 1e-3
-        assert np.abs(image_slices[0] - image_slices[2]).max() < 1e-3
-
-    def test_inference_batch_single_identical(self):
-        super().test_inference_batch_single_identical(expected_max_diff=1e-2)
-
-
-class KandinskyPipelineImg2ImgCombinedFastTests(PipelineTesterMixin, unittest.TestCase):
-    pipeline_class = KandinskyImg2ImgCombinedPipeline
-    params = ["prompt", "image"]
-    batch_params = ["prompt", "negative_prompt", "image"]
-    required_optional_params = [
-        "generator",
-        "height",
-        "width",
-        "latents",
-        "guidance_scale",
-        "negative_prompt",
-        "num_inference_steps",
-        "return_dict",
-        "guidance_scale",
-        "num_images_per_prompt",
-        "output_type",
-        "return_dict",
-    ]
-    test_xformers_attention = False
-
-    def get_dummy_components(self):
-        dummy = Img2ImgDummies()
-        prior_dummy = PriorDummies()
-        components = dummy.get_dummy_components()
-
-        components.update({f"prior_{k}": v for k, v in prior_dummy.get_dummy_components().items()})
-        return components
-
-    def get_dummy_inputs(self, device, seed=0):
-        prior_dummy = PriorDummies()
-        dummy = Img2ImgDummies()
-        inputs = prior_dummy.get_dummy_inputs(device=device, seed=seed)
-        inputs.update(dummy.get_dummy_inputs(device=device, seed=seed))
-        inputs.pop("image_embeds")
-        inputs.pop("negative_image_embeds")
-        return inputs
-
-    def test_kandinsky(self):
-        device = "cpu"
-
-        components = self.get_dummy_components()
-
-        pipe = self.pipeline_class(**components)
-        pipe = pipe.to(device)
-
-        pipe.set_progress_bar_config(disable=None)
-
-        output = pipe(**self.get_dummy_inputs(device))
-        image = output.images
-
-        image_from_tuple = pipe(
-            **self.get_dummy_inputs(device),
-            return_dict=False,
-        )[0]
-
-        image_slice = image[0, -3:, -3:, -1]
-        image_from_tuple_slice = image_from_tuple[0, -3:, -3:, -1]
-
-        assert image.shape == (1, 64, 64, 3)
-
-        expected_slice = np.array([0.4260, 0.3596, 0.4571, 0.3890, 0.4087, 0.5137, 0.4819, 0.4116, 0.5053])
-
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
-        ), f" expected_slice {expected_slice}, but got {image_slice.flatten()}"
-        assert (
-            np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1e-2
-        ), f" expected_slice {expected_slice}, but got {image_from_tuple_slice.flatten()}"
-
-    @require_torch_gpu
-    def test_offloads(self):
-        pipes = []
-        components = self.get_dummy_components()
-        sd_pipe = self.pipeline_class(**components).to(torch_device)
-        pipes.append(sd_pipe)
-
-        components = self.get_dummy_components()
-        sd_pipe = self.pipeline_class(**components)
-        sd_pipe.enable_model_cpu_offload()
-        pipes.append(sd_pipe)
-
-        components = self.get_dummy_components()
-        sd_pipe = self.pipeline_class(**components)
-        sd_pipe.enable_sequential_cpu_offload()
-        pipes.append(sd_pipe)
-
-        image_slices = []
-        for pipe in pipes:
-            inputs = self.get_dummy_inputs(torch_device)
-            image = pipe(**inputs).images
-
-            image_slices.append(image[0, -3:, -3:, -1].flatten())
-
-        assert np.abs(image_slices[0] - image_slices[1]).max() < 1e-3
-        assert np.abs(image_slices[0] - image_slices[2]).max() < 1e-3
-
-    def test_inference_batch_single_identical(self):
-        super().test_inference_batch_single_identical(expected_max_diff=1e-2)
-
-
-class KandinskyPipelineInpaintCombinedFastTests(PipelineTesterMixin, unittest.TestCase):
-    pipeline_class = KandinskyInpaintCombinedPipeline
-    params = ["prompt", "image", "mask_image"]
-    batch_params = ["prompt", "negative_prompt", "image", "mask_image"]
-    required_optional_params = [
-        "generator",
-        "height",
-        "width",
-        "latents",
-        "guidance_scale",
-        "negative_prompt",
-        "num_inference_steps",
-        "return_dict",
-        "guidance_scale",
-        "num_images_per_prompt",
-        "output_type",
-        "return_dict",
-    ]
-    test_xformers_attention = False
-
-    def get_dummy_components(self):
-        dummy = InpaintDummies()
-        prior_dummy = PriorDummies()
-        components = dummy.get_dummy_components()
-
-        components.update({f"prior_{k}": v for k, v in prior_dummy.get_dummy_components().items()})
-        return components
-
-    def get_dummy_inputs(self, device, seed=0):
-        prior_dummy = PriorDummies()
-        dummy = InpaintDummies()
-        inputs = prior_dummy.get_dummy_inputs(device=device, seed=seed)
-        inputs.update(dummy.get_dummy_inputs(device=device, seed=seed))
-        inputs.pop("image_embeds")
-        inputs.pop("negative_image_embeds")
-        return inputs
-
-    def test_kandinsky(self):
-        device = "cpu"
-
-        components = self.get_dummy_components()
-
-        pipe = self.pipeline_class(**components)
-        pipe = pipe.to(device)
-
-        pipe.set_progress_bar_config(disable=None)
-
-        output = pipe(**self.get_dummy_inputs(device))
-        image = output.images
-
-        image_from_tuple = pipe(
-            **self.get_dummy_inputs(device),
-            return_dict=False,
-        )[0]
-
-        image_slice = image[0, -3:, -3:, -1]
-        image_from_tuple_slice = image_from_tuple[0, -3:, -3:, -1]
-
-        assert image.shape == (1, 64, 64, 3)
-
-        expected_slice = np.array([0.0477, 0.0808, 0.2972, 0.2705, 0.3620, 0.6247, 0.4464, 0.2870, 0.3530])
-
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
-        ), f" expected_slice {expected_slice}, but got {image_slice.flatten()}"
-        assert (
-            np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1e-2
-        ), f" expected_slice {expected_slice}, but got {image_from_tuple_slice.flatten()}"
-
-    @require_torch_gpu
-    def test_offloads(self):
-        pipes = []
-        components = self.get_dummy_components()
-        sd_pipe = self.pipeline_class(**components).to(torch_device)
-        pipes.append(sd_pipe)
-
-        components = self.get_dummy_components()
-        sd_pipe = self.pipeline_class(**components)
-        sd_pipe.enable_model_cpu_offload()
-        pipes.append(sd_pipe)
-
-        components = self.get_dummy_components()
-        sd_pipe = self.pipeline_class(**components)
-        sd_pipe.enable_sequential_cpu_offload()
-        pipes.append(sd_pipe)
-
-        image_slices = []
-        for pipe in pipes:
-            inputs = self.get_dummy_inputs(torch_device)
-            image = pipe(**inputs).images
-
-            image_slices.append(image[0, -3:, -3:, -1].flatten())
-
-        assert np.abs(image_slices[0] - image_slices[1]).max() < 1e-3
-        assert np.abs(image_slices[0] - image_slices[2]).max() < 1e-3
-
-    def test_inference_batch_single_identical(self):
-        super().test_inference_batch_single_identical(expected_max_diff=1e-2)
diff --git a/spaces/Andy1621/uniformer_image_detection/mmdet/models/dense_heads/ga_rpn_head.py b/spaces/Andy1621/uniformer_image_detection/mmdet/models/dense_heads/ga_rpn_head.py
deleted file mode 100644
index 2ec0d4fdd3475bfbd2e541a6e8130b1df9ad861a..0000000000000000000000000000000000000000
--- a/spaces/Andy1621/uniformer_image_detection/mmdet/models/dense_heads/ga_rpn_head.py
+++ /dev/null
@@ -1,171 +0,0 @@
-import copy
-import warnings
-
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-from mmcv import ConfigDict
-from mmcv.cnn import normal_init
-from mmcv.ops import nms
-
-from ..builder import HEADS
-from .guided_anchor_head import GuidedAnchorHead
-from .rpn_test_mixin import RPNTestMixin
-
-
-@HEADS.register_module()
-class GARPNHead(RPNTestMixin, GuidedAnchorHead):
-    """Guided-Anchor-based RPN head."""
-
-    def __init__(self, in_channels, **kwargs):
-        super(GARPNHead, self).__init__(1, in_channels, **kwargs)
-
-    def _init_layers(self):
-        """Initialize layers of the head."""
-        self.rpn_conv = nn.Conv2d(
-            self.in_channels, self.feat_channels, 3, padding=1)
-        super(GARPNHead, self)._init_layers()
-
-    def init_weights(self):
-        """Initialize weights of the head."""
-        normal_init(self.rpn_conv, std=0.01)
-        super(GARPNHead, self).init_weights()
-
-    def forward_single(self, x):
-        """Forward feature of a single scale level."""
-
-        x = self.rpn_conv(x)
-        x = F.relu(x, inplace=True)
-        (cls_score, bbox_pred, shape_pred,
-         loc_pred) = super(GARPNHead, self).forward_single(x)
-        return cls_score, bbox_pred, shape_pred, loc_pred
-
-    def loss(self,
-             cls_scores,
-             bbox_preds,
-             shape_preds,
-             loc_preds,
-             gt_bboxes,
-             img_metas,
-             gt_bboxes_ignore=None):
-        losses = super(GARPNHead, self).loss(
-            cls_scores,
-            bbox_preds,
-            shape_preds,
-            loc_preds,
-            gt_bboxes,
-            None,
-            img_metas,
-            gt_bboxes_ignore=gt_bboxes_ignore)
-        return dict(
-            loss_rpn_cls=losses['loss_cls'],
-            loss_rpn_bbox=losses['loss_bbox'],
-            loss_anchor_shape=losses['loss_shape'],
-            loss_anchor_loc=losses['loss_loc'])
-
-    def _get_bboxes_single(self,
-                           cls_scores,
-                           bbox_preds,
-                           mlvl_anchors,
-                           mlvl_masks,
-                           img_shape,
-                           scale_factor,
-                           cfg,
-                           rescale=False):
-        cfg = self.test_cfg if cfg is None else cfg
-
-        cfg = copy.deepcopy(cfg)
-
-        # deprecate arguments warning
-        if 'nms' not in cfg or 'max_num' in cfg or 'nms_thr' in cfg:
-            warnings.warn(
-                'In rpn_proposal or test_cfg, '
-                'nms_thr has been moved to a dict named nms as '
-                'iou_threshold, max_num has been renamed as max_per_img, '
-                'name of original arguments and the way to specify '
-                'iou_threshold of NMS will be deprecated.')
-        if 'nms' not in cfg:
-            cfg.nms = ConfigDict(dict(type='nms', iou_threshold=cfg.nms_thr))
-        if 'max_num' in cfg:
-            if 'max_per_img' in cfg:
-                assert cfg.max_num == cfg.max_per_img, f'You ' \
-                    f'set max_num and max_per_img at the same time, ' \
-                    f'but get {cfg.max_num} ' \
-                    f'and {cfg.max_per_img} respectively' \
-                    'Please delete max_num which will be deprecated.'
-            else:
-                cfg.max_per_img = cfg.max_num
-        if 'nms_thr' in cfg:
-            assert cfg.nms.iou_threshold == cfg.nms_thr, f'You set ' \
-                f'iou_threshold in nms and ' \
-                f'nms_thr at the same time, but get ' \
-                f'{cfg.nms.iou_threshold} and {cfg.nms_thr}' \
-                f' respectively. Please delete the ' \
-                f'nms_thr which will be deprecated.'
-
-        assert cfg.nms.get('type', 'nms') == 'nms', 'GARPNHead only support ' \
-            'naive nms.'
-
-        mlvl_proposals = []
-        for idx in range(len(cls_scores)):
-            rpn_cls_score = cls_scores[idx]
-            rpn_bbox_pred = bbox_preds[idx]
-            anchors = mlvl_anchors[idx]
-            mask = mlvl_masks[idx]
-            assert rpn_cls_score.size()[-2:] == rpn_bbox_pred.size()[-2:]
-            # if no location is kept, end.
-            if mask.sum() == 0:
-                continue
-            rpn_cls_score = rpn_cls_score.permute(1, 2, 0)
-            if self.use_sigmoid_cls:
-                rpn_cls_score = rpn_cls_score.reshape(-1)
-                scores = rpn_cls_score.sigmoid()
-            else:
-                rpn_cls_score = rpn_cls_score.reshape(-1, 2)
-                # remind that we set FG labels to [0, num_class-1]
-                # since mmdet v2.0
-                # BG cat_id: num_class
-                scores = rpn_cls_score.softmax(dim=1)[:, :-1]
-            # filter scores, bbox_pred w.r.t. mask.
-            # anchors are filtered in get_anchors() beforehand.
-            scores = scores[mask]
-            rpn_bbox_pred = rpn_bbox_pred.permute(1, 2, 0).reshape(-1,
-                                                                   4)[mask, :]
-            if scores.dim() == 0:
-                rpn_bbox_pred = rpn_bbox_pred.unsqueeze(0)
-                anchors = anchors.unsqueeze(0)
-                scores = scores.unsqueeze(0)
-            # filter anchors, bbox_pred, scores w.r.t. scores
-            if cfg.nms_pre > 0 and scores.shape[0] > cfg.nms_pre:
-                _, topk_inds = scores.topk(cfg.nms_pre)
-                rpn_bbox_pred = rpn_bbox_pred[topk_inds, :]
-                anchors = anchors[topk_inds, :]
-                scores = scores[topk_inds]
-            # get proposals w.r.t. anchors and rpn_bbox_pred
-            proposals = self.bbox_coder.decode(
-                anchors, rpn_bbox_pred, max_shape=img_shape)
-            # filter out too small bboxes
-            if cfg.min_bbox_size > 0:
-                w = proposals[:, 2] - proposals[:, 0]
-                h = proposals[:, 3] - proposals[:, 1]
-                valid_inds = torch.nonzero(
-                    (w >= cfg.min_bbox_size) & (h >= cfg.min_bbox_size),
-                    as_tuple=False).squeeze()
-                proposals = proposals[valid_inds, :]
-                scores = scores[valid_inds]
-            # NMS in current level
-            proposals, _ = nms(proposals, scores, cfg.nms.iou_threshold)
-            proposals = proposals[:cfg.nms_post, :]
-            mlvl_proposals.append(proposals)
-        proposals = torch.cat(mlvl_proposals, 0)
-        if cfg.get('nms_across_levels', False):
-            # NMS across multi levels
-            proposals, _ = nms(proposals[:, :4], proposals[:, -1],
-                               cfg.nms.iou_threshold)
-            proposals = proposals[:cfg.max_per_img, :]
-        else:
-            scores = proposals[:, 4]
-            num = min(cfg.max_per_img, proposals.shape[0])
-            _, topk_inds = scores.topk(num)
-            proposals = proposals[topk_inds, :]
-        return proposals
diff --git a/spaces/Anonymous-sub/Rerender/ControlNet/annotator/uniformer/mmcv/runner/default_constructor.py b/spaces/Anonymous-sub/Rerender/ControlNet/annotator/uniformer/mmcv/runner/default_constructor.py
deleted file mode 100644
index 3f1f5b44168768dfda3947393a63a6cf9cf50b41..0000000000000000000000000000000000000000
--- a/spaces/Anonymous-sub/Rerender/ControlNet/annotator/uniformer/mmcv/runner/default_constructor.py
+++ /dev/null
@@ -1,44 +0,0 @@
-from .builder import RUNNER_BUILDERS, RUNNERS
-
-
-@RUNNER_BUILDERS.register_module()
-class DefaultRunnerConstructor:
-    """Default constructor for runners.
-
-    Custom existing `Runner` like `EpocBasedRunner` though `RunnerConstructor`.
-    For example, We can inject some new properties and functions for `Runner`.
-
-    Example:
-        >>> from annotator.uniformer.mmcv.runner import RUNNER_BUILDERS, build_runner
-        >>> # Define a new RunnerReconstructor
-        >>> @RUNNER_BUILDERS.register_module()
-        >>> class MyRunnerConstructor:
-        ...     def __init__(self, runner_cfg, default_args=None):
-        ...         if not isinstance(runner_cfg, dict):
-        ...             raise TypeError('runner_cfg should be a dict',
-        ...                             f'but got {type(runner_cfg)}')
-        ...         self.runner_cfg = runner_cfg
-        ...         self.default_args = default_args
-        ...
-        ...     def __call__(self):
-        ...         runner = RUNNERS.build(self.runner_cfg,
-        ...                                default_args=self.default_args)
-        ...         # Add new properties for existing runner
-        ...         runner.my_name = 'my_runner'
-        ...         runner.my_function = lambda self: print(self.my_name)
-        ...         ...
-        >>> # build your runner
-        >>> runner_cfg = dict(type='EpochBasedRunner', max_epochs=40,
-        ...                   constructor='MyRunnerConstructor')
-        >>> runner = build_runner(runner_cfg)
-    """
-
-    def __init__(self, runner_cfg, default_args=None):
-        if not isinstance(runner_cfg, dict):
-            raise TypeError('runner_cfg should be a dict',
-                            f'but got {type(runner_cfg)}')
-        self.runner_cfg = runner_cfg
-        self.default_args = default_args
-
-    def __call__(self):
-        return RUNNERS.build(self.runner_cfg, default_args=self.default_args)
diff --git a/spaces/Artificio/AdversarialArt/README.md b/spaces/Artificio/AdversarialArt/README.md
deleted file mode 100644
index 450f7e62b14fd833017a0c0c6838b93c643322f5..0000000000000000000000000000000000000000
--- a/spaces/Artificio/AdversarialArt/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: AdversarialArt
-emoji: 🏢
-colorFrom: blue
-colorTo: green
-sdk: gradio
-sdk_version: 3.1.6
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Artrajz/vits-simple-api/bert_vits2/text/tone_sandhi.py b/spaces/Artrajz/vits-simple-api/bert_vits2/text/tone_sandhi.py
deleted file mode 100644
index 6a6e4c3e64f1a9e8b9da73fc6fbebf8a33e5602d..0000000000000000000000000000000000000000
--- a/spaces/Artrajz/vits-simple-api/bert_vits2/text/tone_sandhi.py
+++ /dev/null
@@ -1,769 +0,0 @@
-# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-from typing import List
-from typing import Tuple
-
-import jieba
-from pypinyin import lazy_pinyin
-from pypinyin import Style
-
-
-class ToneSandhi:
-    def __init__(self):
-        self.must_neural_tone_words = {
-            "麻烦",
-            "麻利",
-            "鸳鸯",
-            "高粱",
-            "骨头",
-            "骆驼",
-            "马虎",
-            "首饰",
-            "馒头",
-            "馄饨",
-            "风筝",
-            "难为",
-            "队伍",
-            "阔气",
-            "闺女",
-            "门道",
-            "锄头",
-            "铺盖",
-            "铃铛",
-            "铁匠",
-            "钥匙",
-            "里脊",
-            "里头",
-            "部分",
-            "那么",
-            "道士",
-            "造化",
-            "迷糊",
-            "连累",
-            "这么",
-            "这个",
-            "运气",
-            "过去",
-            "软和",
-            "转悠",
-            "踏实",
-            "跳蚤",
-            "跟头",
-            "趔趄",
-            "财主",
-            "豆腐",
-            "讲究",
-            "记性",
-            "记号",
-            "认识",
-            "规矩",
-            "见识",
-            "裁缝",
-            "补丁",
-            "衣裳",
-            "衣服",
-            "衙门",
-            "街坊",
-            "行李",
-            "行当",
-            "蛤蟆",
-            "蘑菇",
-            "薄荷",
-            "葫芦",
-            "葡萄",
-            "萝卜",
-            "荸荠",
-            "苗条",
-            "苗头",
-            "苍蝇",
-            "芝麻",
-            "舒服",
-            "舒坦",
-            "舌头",
-            "自在",
-            "膏药",
-            "脾气",
-            "脑袋",
-            "脊梁",
-            "能耐",
-            "胳膊",
-            "胭脂",
-            "胡萝",
-            "胡琴",
-            "胡同",
-            "聪明",
-            "耽误",
-            "耽搁",
-            "耷拉",
-            "耳朵",
-            "老爷",
-            "老实",
-            "老婆",
-            "老头",
-            "老太",
-            "翻腾",
-            "罗嗦",
-            "罐头",
-            "编辑",
-            "结实",
-            "红火",
-            "累赘",
-            "糨糊",
-            "糊涂",
-            "精神",
-            "粮食",
-            "簸箕",
-            "篱笆",
-            "算计",
-            "算盘",
-            "答应",
-            "笤帚",
-            "笑语",
-            "笑话",
-            "窟窿",
-            "窝囊",
-            "窗户",
-            "稳当",
-            "稀罕",
-            "称呼",
-            "秧歌",
-            "秀气",
-            "秀才",
-            "福气",
-            "祖宗",
-            "砚台",
-            "码头",
-            "石榴",
-            "石头",
-            "石匠",
-            "知识",
-            "眼睛",
-            "眯缝",
-            "眨巴",
-            "眉毛",
-            "相声",
-            "盘算",
-            "白净",
-            "痢疾",
-            "痛快",
-            "疟疾",
-            "疙瘩",
-            "疏忽",
-            "畜生",
-            "生意",
-            "甘蔗",
-            "琵琶",
-            "琢磨",
-            "琉璃",
-            "玻璃",
-            "玫瑰",
-            "玄乎",
-            "狐狸",
-            "状元",
-            "特务",
-            "牲口",
-            "牙碜",
-            "牌楼",
-            "爽快",
-            "爱人",
-            "热闹",
-            "烧饼",
-            "烟筒",
-            "烂糊",
-            "点心",
-            "炊帚",
-            "灯笼",
-            "火候",
-            "漂亮",
-            "滑溜",
-            "溜达",
-            "温和",
-            "清楚",
-            "消息",
-            "浪头",
-            "活泼",
-            "比方",
-            "正经",
-            "欺负",
-            "模糊",
-            "槟榔",
-            "棺材",
-            "棒槌",
-            "棉花",
-            "核桃",
-            "栅栏",
-            "柴火",
-            "架势",
-            "枕头",
-            "枇杷",
-            "机灵",
-            "本事",
-            "木头",
-            "木匠",
-            "朋友",
-            "月饼",
-            "月亮",
-            "暖和",
-            "明白",
-            "时候",
-            "新鲜",
-            "故事",
-            "收拾",
-            "收成",
-            "提防",
-            "挖苦",
-            "挑剔",
-            "指甲",
-            "指头",
-            "拾掇",
-            "拳头",
-            "拨弄",
-            "招牌",
-            "招呼",
-            "抬举",
-            "护士",
-            "折腾",
-            "扫帚",
-            "打量",
-            "打算",
-            "打点",
-            "打扮",
-            "打听",
-            "打发",
-            "扎实",
-            "扁担",
-            "戒指",
-            "懒得",
-            "意识",
-            "意思",
-            "情形",
-            "悟性",
-            "怪物",
-            "思量",
-            "怎么",
-            "念头",
-            "念叨",
-            "快活",
-            "忙活",
-            "志气",
-            "心思",
-            "得罪",
-            "张罗",
-            "弟兄",
-            "开通",
-            "应酬",
-            "庄稼",
-            "干事",
-            "帮手",
-            "帐篷",
-            "希罕",
-            "师父",
-            "师傅",
-            "巴结",
-            "巴掌",
-            "差事",
-            "工夫",
-            "岁数",
-            "屁股",
-            "尾巴",
-            "少爷",
-            "小气",
-            "小伙",
-            "将就",
-            "对头",
-            "对付",
-            "寡妇",
-            "家伙",
-            "客气",
-            "实在",
-            "官司",
-            "学问",
-            "学生",
-            "字号",
-            "嫁妆",
-            "媳妇",
-            "媒人",
-            "婆家",
-            "娘家",
-            "委屈",
-            "姑娘",
-            "姐夫",
-            "妯娌",
-            "妥当",
-            "妖精",
-            "奴才",
-            "女婿",
-            "头发",
-            "太阳",
-            "大爷",
-            "大方",
-            "大意",
-            "大夫",
-            "多少",
-            "多么",
-            "外甥",
-            "壮实",
-            "地道",
-            "地方",
-            "在乎",
-            "困难",
-            "嘴巴",
-            "嘱咐",
-            "嘟囔",
-            "嘀咕",
-            "喜欢",
-            "喇嘛",
-            "喇叭",
-            "商量",
-            "唾沫",
-            "哑巴",
-            "哈欠",
-            "哆嗦",
-            "咳嗽",
-            "和尚",
-            "告诉",
-            "告示",
-            "含糊",
-            "吓唬",
-            "后头",
-            "名字",
-            "名堂",
-            "合同",
-            "吆喝",
-            "叫唤",
-            "口袋",
-            "厚道",
-            "厉害",
-            "千斤",
-            "包袱",
-            "包涵",
-            "匀称",
-            "勤快",
-            "动静",
-            "动弹",
-            "功夫",
-            "力气",
-            "前头",
-            "刺猬",
-            "刺激",
-            "别扭",
-            "利落",
-            "利索",
-            "利害",
-            "分析",
-            "出息",
-            "凑合",
-            "凉快",
-            "冷战",
-            "冤枉",
-            "冒失",
-            "养活",
-            "关系",
-            "先生",
-            "兄弟",
-            "便宜",
-            "使唤",
-            "佩服",
-            "作坊",
-            "体面",
-            "位置",
-            "似的",
-            "伙计",
-            "休息",
-            "什么",
-            "人家",
-            "亲戚",
-            "亲家",
-            "交情",
-            "云彩",
-            "事情",
-            "买卖",
-            "主意",
-            "丫头",
-            "丧气",
-            "两口",
-            "东西",
-            "东家",
-            "世故",
-            "不由",
-            "不在",
-            "下水",
-            "下巴",
-            "上头",
-            "上司",
-            "丈夫",
-            "丈人",
-            "一辈",
-            "那个",
-            "菩萨",
-            "父亲",
-            "母亲",
-            "咕噜",
-            "邋遢",
-            "费用",
-            "冤家",
-            "甜头",
-            "介绍",
-            "荒唐",
-            "大人",
-            "泥鳅",
-            "幸福",
-            "熟悉",
-            "计划",
-            "扑腾",
-            "蜡烛",
-            "姥爷",
-            "照顾",
-            "喉咙",
-            "吉他",
-            "弄堂",
-            "蚂蚱",
-            "凤凰",
-            "拖沓",
-            "寒碜",
-            "糟蹋",
-            "倒腾",
-            "报复",
-            "逻辑",
-            "盘缠",
-            "喽啰",
-            "牢骚",
-            "咖喱",
-            "扫把",
-            "惦记",
-        }
-        self.must_not_neural_tone_words = {
-            "男子",
-            "女子",
-            "分子",
-            "原子",
-            "量子",
-            "莲子",
-            "石子",
-            "瓜子",
-            "电子",
-            "人人",
-            "虎虎",
-        }
-        self.punc = "：，；。？！“”‘’':,;.?!"
-
-    # the meaning of jieba pos tag: https://blog.csdn.net/weixin_44174352/article/details/113731041
-    # e.g.
-    # word: "家里"
-    # pos: "s"
-    # finals: ['ia1', 'i3']
-    def _neural_sandhi(self, word: str, pos: str, finals: List[str]) -> List[str]:
-        # reduplication words for n. and v. e.g. 奶奶, 试试, 旺旺
-        for j, item in enumerate(word):
-            if (
-                j - 1 >= 0
-                and item == word[j - 1]
-                and pos[0] in {"n", "v", "a"}
-                and word not in self.must_not_neural_tone_words
-            ):
-                finals[j] = finals[j][:-1] + "5"
-        ge_idx = word.find("个")
-        if len(word) >= 1 and word[-1] in "吧呢啊呐噻嘛吖嗨呐哦哒额滴哩哟喽啰耶喔诶":
-            finals[-1] = finals[-1][:-1] + "5"
-        elif len(word) >= 1 and word[-1] in "的地得":
-            finals[-1] = finals[-1][:-1] + "5"
-        # e.g. 走了, 看着, 去过
-        # elif len(word) == 1 and word in "了着过" and pos in {"ul", "uz", "ug"}:
-        #     finals[-1] = finals[-1][:-1] + "5"
-        elif (
-            len(word) > 1
-            and word[-1] in "们子"
-            and pos in {"r", "n"}
-            and word not in self.must_not_neural_tone_words
-        ):
-            finals[-1] = finals[-1][:-1] + "5"
-        # e.g. 桌上, 地下, 家里
-        elif len(word) > 1 and word[-1] in "上下里" and pos in {"s", "l", "f"}:
-            finals[-1] = finals[-1][:-1] + "5"
-        # e.g. 上来, 下去
-        elif len(word) > 1 and word[-1] in "来去" and word[-2] in "上下进出回过起开":
-            finals[-1] = finals[-1][:-1] + "5"
-        # 个做量词
-        elif (
-            ge_idx >= 1
-            and (word[ge_idx - 1].isnumeric() or word[ge_idx - 1] in "几有两半多各整每做是")
-        ) or word == "个":
-            finals[ge_idx] = finals[ge_idx][:-1] + "5"
-        else:
-            if (
-                word in self.must_neural_tone_words
-                or word[-2:] in self.must_neural_tone_words
-            ):
-                finals[-1] = finals[-1][:-1] + "5"
-
-        word_list = self._split_word(word)
-        finals_list = [finals[: len(word_list[0])], finals[len(word_list[0]) :]]
-        for i, word in enumerate(word_list):
-            # conventional neural in Chinese
-            if (
-                word in self.must_neural_tone_words
-                or word[-2:] in self.must_neural_tone_words
-            ):
-                finals_list[i][-1] = finals_list[i][-1][:-1] + "5"
-        finals = sum(finals_list, [])
-        return finals
-
-    def _bu_sandhi(self, word: str, finals: List[str]) -> List[str]:
-        # e.g. 看不懂
-        if len(word) == 3 and word[1] == "不":
-            finals[1] = finals[1][:-1] + "5"
-        else:
-            for i, char in enumerate(word):
-                # "不" before tone4 should be bu2, e.g. 不怕
-                if char == "不" and i + 1 < len(word) and finals[i + 1][-1] == "4":
-                    finals[i] = finals[i][:-1] + "2"
-        return finals
-
-    def _yi_sandhi(self, word: str, finals: List[str]) -> List[str]:
-        # "一" in number sequences, e.g. 一零零, 二一零
-        if word.find("一") != -1 and all(
-            [item.isnumeric() for item in word if item != "一"]
-        ):
-            return finals
-        # "一" between reduplication words should be yi5, e.g. 看一看
-        elif len(word) == 3 and word[1] == "一" and word[0] == word[-1]:
-            finals[1] = finals[1][:-1] + "5"
-        # when "一" is ordinal word, it should be yi1
-        elif word.startswith("第一"):
-            finals[1] = finals[1][:-1] + "1"
-        else:
-            for i, char in enumerate(word):
-                if char == "一" and i + 1 < len(word):
-                    # "一" before tone4 should be yi2, e.g. 一段
-                    if finals[i + 1][-1] == "4":
-                        finals[i] = finals[i][:-1] + "2"
-                    # "一" before non-tone4 should be yi4, e.g. 一天
-                    else:
-                        # "一" 后面如果是标点，还读一声
-                        if word[i + 1] not in self.punc:
-                            finals[i] = finals[i][:-1] + "4"
-        return finals
-
-    def _split_word(self, word: str) -> List[str]:
-        word_list = jieba.cut_for_search(word)
-        word_list = sorted(word_list, key=lambda i: len(i), reverse=False)
-        first_subword = word_list[0]
-        first_begin_idx = word.find(first_subword)
-        if first_begin_idx == 0:
-            second_subword = word[len(first_subword) :]
-            new_word_list = [first_subword, second_subword]
-        else:
-            second_subword = word[: -len(first_subword)]
-            new_word_list = [second_subword, first_subword]
-        return new_word_list
-
-    def _three_sandhi(self, word: str, finals: List[str]) -> List[str]:
-        if len(word) == 2 and self._all_tone_three(finals):
-            finals[0] = finals[0][:-1] + "2"
-        elif len(word) == 3:
-            word_list = self._split_word(word)
-            if self._all_tone_three(finals):
-                #  disyllabic + monosyllabic, e.g. 蒙古/包
-                if len(word_list[0]) == 2:
-                    finals[0] = finals[0][:-1] + "2"
-                    finals[1] = finals[1][:-1] + "2"
-                #  monosyllabic + disyllabic, e.g. 纸/老虎
-                elif len(word_list[0]) == 1:
-                    finals[1] = finals[1][:-1] + "2"
-            else:
-                finals_list = [finals[: len(word_list[0])], finals[len(word_list[0]) :]]
-                if len(finals_list) == 2:
-                    for i, sub in enumerate(finals_list):
-                        # e.g. 所有/人
-                        if self._all_tone_three(sub) and len(sub) == 2:
-                            finals_list[i][0] = finals_list[i][0][:-1] + "2"
-                        # e.g. 好/喜欢
-                        elif (
-                            i == 1
-                            and not self._all_tone_three(sub)
-                            and finals_list[i][0][-1] == "3"
-                            and finals_list[0][-1][-1] == "3"
-                        ):
-                            finals_list[0][-1] = finals_list[0][-1][:-1] + "2"
-                        finals = sum(finals_list, [])
-        # split idiom into two words who's length is 2
-        elif len(word) == 4:
-            finals_list = [finals[:2], finals[2:]]
-            finals = []
-            for sub in finals_list:
-                if self._all_tone_three(sub):
-                    sub[0] = sub[0][:-1] + "2"
-                finals += sub
-
-        return finals
-
-    def _all_tone_three(self, finals: List[str]) -> bool:
-        return all(x[-1] == "3" for x in finals)
-
-    # merge "不" and the word behind it
-    # if don't merge, "不" sometimes appears alone according to jieba, which may occur sandhi error
-    def _merge_bu(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
-        new_seg = []
-        last_word = ""
-        for word, pos in seg:
-            if last_word == "不":
-                word = last_word + word
-            if word != "不":
-                new_seg.append((word, pos))
-            last_word = word[:]
-        if last_word == "不":
-            new_seg.append((last_word, "d"))
-            last_word = ""
-        return new_seg
-
-    # function 1: merge "一" and reduplication words in it's left and right, e.g. "听","一","听" ->"听一听"
-    # function 2: merge single  "一" and the word behind it
-    # if don't merge, "一" sometimes appears alone according to jieba, which may occur sandhi error
-    # e.g.
-    # input seg: [('听', 'v'), ('一', 'm'), ('听', 'v')]
-    # output seg: [['听一听', 'v']]
-    def _merge_yi(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
-        new_seg = []
-        # function 1
-        for i, (word, pos) in enumerate(seg):
-            if (
-                i - 1 >= 0
-                and word == "一"
-                and i + 1 < len(seg)
-                and seg[i - 1][0] == seg[i + 1][0]
-                and seg[i - 1][1] == "v"
-            ):
-                new_seg[i - 1][0] = new_seg[i - 1][0] + "一" + new_seg[i - 1][0]
-            else:
-                if (
-                    i - 2 >= 0
-                    and seg[i - 1][0] == "一"
-                    and seg[i - 2][0] == word
-                    and pos == "v"
-                ):
-                    continue
-                else:
-                    new_seg.append([word, pos])
-        seg = new_seg
-        new_seg = []
-        # function 2
-        for i, (word, pos) in enumerate(seg):
-            if new_seg and new_seg[-1][0] == "一":
-                new_seg[-1][0] = new_seg[-1][0] + word
-            else:
-                new_seg.append([word, pos])
-        return new_seg
-
-    # the first and the second words are all_tone_three
-    def _merge_continuous_three_tones(
-        self, seg: List[Tuple[str, str]]
-    ) -> List[Tuple[str, str]]:
-        new_seg = []
-        sub_finals_list = [
-            lazy_pinyin(word, neutral_tone_with_five=True, style=Style.FINALS_TONE3)
-            for (word, pos) in seg
-        ]
-        assert len(sub_finals_list) == len(seg)
-        merge_last = [False] * len(seg)
-        for i, (word, pos) in enumerate(seg):
-            if (
-                i - 1 >= 0
-                and self._all_tone_three(sub_finals_list[i - 1])
-                and self._all_tone_three(sub_finals_list[i])
-                and not merge_last[i - 1]
-            ):
-                # if the last word is reduplication, not merge, because reduplication need to be _neural_sandhi
-                if (
-                    not self._is_reduplication(seg[i - 1][0])
-                    and len(seg[i - 1][0]) + len(seg[i][0]) <= 3
-                ):
-                    new_seg[-1][0] = new_seg[-1][0] + seg[i][0]
-                    merge_last[i] = True
-                else:
-                    new_seg.append([word, pos])
-            else:
-                new_seg.append([word, pos])
-
-        return new_seg
-
-    def _is_reduplication(self, word: str) -> bool:
-        return len(word) == 2 and word[0] == word[1]
-
-    # the last char of first word and the first char of second word is tone_three
-    def _merge_continuous_three_tones_2(
-        self, seg: List[Tuple[str, str]]
-    ) -> List[Tuple[str, str]]:
-        new_seg = []
-        sub_finals_list = [
-            lazy_pinyin(word, neutral_tone_with_five=True, style=Style.FINALS_TONE3)
-            for (word, pos) in seg
-        ]
-        assert len(sub_finals_list) == len(seg)
-        merge_last = [False] * len(seg)
-        for i, (word, pos) in enumerate(seg):
-            if (
-                i - 1 >= 0
-                and sub_finals_list[i - 1][-1][-1] == "3"
-                and sub_finals_list[i][0][-1] == "3"
-                and not merge_last[i - 1]
-            ):
-                # if the last word is reduplication, not merge, because reduplication need to be _neural_sandhi
-                if (
-                    not self._is_reduplication(seg[i - 1][0])
-                    and len(seg[i - 1][0]) + len(seg[i][0]) <= 3
-                ):
-                    new_seg[-1][0] = new_seg[-1][0] + seg[i][0]
-                    merge_last[i] = True
-                else:
-                    new_seg.append([word, pos])
-            else:
-                new_seg.append([word, pos])
-        return new_seg
-
-    def _merge_er(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
-        new_seg = []
-        for i, (word, pos) in enumerate(seg):
-            if i - 1 >= 0 and word == "儿" and seg[i - 1][0] != "#":
-                new_seg[-1][0] = new_seg[-1][0] + seg[i][0]
-            else:
-                new_seg.append([word, pos])
-        return new_seg
-
-    def _merge_reduplication(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
-        new_seg = []
-        for i, (word, pos) in enumerate(seg):
-            if new_seg and word == new_seg[-1][0]:
-                new_seg[-1][0] = new_seg[-1][0] + seg[i][0]
-            else:
-                new_seg.append([word, pos])
-        return new_seg
-
-    def pre_merge_for_modify(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
-        seg = self._merge_bu(seg)
-        try:
-            seg = self._merge_yi(seg)
-        except:
-            print("_merge_yi failed")
-        seg = self._merge_reduplication(seg)
-        seg = self._merge_continuous_three_tones(seg)
-        seg = self._merge_continuous_three_tones_2(seg)
-        seg = self._merge_er(seg)
-        return seg
-
-    def modified_tone(self, word: str, pos: str, finals: List[str]) -> List[str]:
-        finals = self._bu_sandhi(word, finals)
-        finals = self._yi_sandhi(word, finals)
-        finals = self._neural_sandhi(word, pos, finals)
-        finals = self._three_sandhi(word, finals)
-        return finals
diff --git a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/rich/filesize.py b/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/rich/filesize.py
deleted file mode 100644
index 99f118e20103174993b865cfb43ac6b6e00296a4..0000000000000000000000000000000000000000
--- a/spaces/Ataturk-Chatbot/HuggingFaceChat/venv/lib/python3.11/site-packages/pip/_vendor/rich/filesize.py
+++ /dev/null
@@ -1,89 +0,0 @@
-# coding: utf-8
-"""Functions for reporting filesizes. Borrowed from https://github.com/PyFilesystem/pyfilesystem2
-
-The functions declared in this module should cover the different
-use cases needed to generate a string representation of a file size
-using several different units. Since there are many standards regarding
-file size units, three different functions have been implemented.
-
-See Also:
-    * `Wikipedia: Binary prefix <https://en.wikipedia.org/wiki/Binary_prefix>`_
-
-"""
-
-__all__ = ["decimal"]
-
-from typing import Iterable, List, Optional, Tuple
-
-
-def _to_str(
-    size: int,
-    suffixes: Iterable[str],
-    base: int,
-    *,
-    precision: Optional[int] = 1,
-    separator: Optional[str] = " ",
-) -> str:
-    if size == 1:
-        return "1 byte"
-    elif size < base:
-        return "{:,} bytes".format(size)
-
-    for i, suffix in enumerate(suffixes, 2):  # noqa: B007
-        unit = base**i
-        if size < unit:
-            break
-    return "{:,.{precision}f}{separator}{}".format(
-        (base * size / unit),
-        suffix,
-        precision=precision,
-        separator=separator,
-    )
-
-
-def pick_unit_and_suffix(size: int, suffixes: List[str], base: int) -> Tuple[int, str]:
-    """Pick a suffix and base for the given size."""
-    for i, suffix in enumerate(suffixes):
-        unit = base**i
-        if size < unit * base:
-            break
-    return unit, suffix
-
-
-def decimal(
-    size: int,
-    *,
-    precision: Optional[int] = 1,
-    separator: Optional[str] = " ",
-) -> str:
-    """Convert a filesize in to a string (powers of 1000, SI prefixes).
-
-    In this convention, ``1000 B = 1 kB``.
-
-    This is typically the format used to advertise the storage
-    capacity of USB flash drives and the like (*256 MB* meaning
-    actually a storage capacity of more than *256 000 000 B*),
-    or used by **Mac OS X** since v10.6 to report file sizes.
-
-    Arguments:
-        int (size): A file size.
-        int (precision): The number of decimal places to include (default = 1).
-        str (separator): The string to separate the value from the units (default = " ").
-
-    Returns:
-        `str`: A string containing a abbreviated file size and units.
-
-    Example:
-        >>> filesize.decimal(30000)
-        '30.0 kB'
-        >>> filesize.decimal(30000, precision=2, separator="")
-        '30.00kB'
-
-    """
-    return _to_str(
-        size,
-        ("kB", "MB", "GB", "TB", "PB", "EB", "ZB", "YB"),
-        1000,
-        precision=precision,
-        separator=separator,
-    )
diff --git a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_1x.py b/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_1x.py
deleted file mode 100644
index 40844ddeb8d47ff58a6af49ab35bad84e14f5721..0000000000000000000000000000000000000000
--- a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_1x.py
+++ /dev/null
@@ -1,8 +0,0 @@
-from ..common.optim import SGD as optimizer
-from ..common.coco_schedule import lr_multiplier_1x as lr_multiplier
-from ..common.data.coco import dataloader
-from ..common.models.mask_rcnn_fpn import model
-from ..common.train import train
-
-model.backbone.bottom_up.freeze_at = 2
-train.init_checkpoint = "detectron2://ImageNetPretrained/MSRA/R-50.pkl"
diff --git a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/detectron2/export/torchscript_patch.py b/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/detectron2/export/torchscript_patch.py
deleted file mode 100644
index da9b324f1582e31d1a16d2fe462ac2989bea56ea..0000000000000000000000000000000000000000
--- a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/detectron2/export/torchscript_patch.py
+++ /dev/null
@@ -1,406 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import os
-import sys
-import tempfile
-from contextlib import ExitStack, contextmanager
-from copy import deepcopy
-from unittest import mock
-import torch
-from torch import nn
-
-# need some explicit imports due to https://github.com/pytorch/pytorch/issues/38964
-import detectron2  # noqa F401
-from detectron2.structures import Boxes, Instances
-from detectron2.utils.env import _import_file
-
-_counter = 0
-
-
-def _clear_jit_cache():
-    from torch.jit._recursive import concrete_type_store
-    from torch.jit._state import _jit_caching_layer
-
-    concrete_type_store.type_store.clear()  # for modules
-    _jit_caching_layer.clear()  # for free functions
-
-
-def _add_instances_conversion_methods(newInstances):
-    """
-    Add from_instances methods to the scripted Instances class.
-    """
-    cls_name = newInstances.__name__
-
-    @torch.jit.unused
-    def from_instances(instances: Instances):
-        """
-        Create scripted Instances from original Instances
-        """
-        fields = instances.get_fields()
-        image_size = instances.image_size
-        ret = newInstances(image_size)
-        for name, val in fields.items():
-            assert hasattr(ret, f"_{name}"), f"No attribute named {name} in {cls_name}"
-            setattr(ret, name, deepcopy(val))
-        return ret
-
-    newInstances.from_instances = from_instances
-
-
-@contextmanager
-def patch_instances(fields):
-    """
-    A contextmanager, under which the Instances class in detectron2 is replaced
-    by a statically-typed scriptable class, defined by `fields`.
-    See more in `scripting_with_instances`.
-    """
-
-    with tempfile.TemporaryDirectory(prefix="detectron2") as dir, tempfile.NamedTemporaryFile(
-        mode="w", encoding="utf-8", suffix=".py", dir=dir, delete=False
-    ) as f:
-        try:
-            # Objects that use Instances should not reuse previously-compiled
-            # results in cache, because `Instances` could be a new class each time.
-            _clear_jit_cache()
-
-            cls_name, s = _gen_instance_module(fields)
-            f.write(s)
-            f.flush()
-            f.close()
-
-            module = _import(f.name)
-            new_instances = getattr(module, cls_name)
-            _ = torch.jit.script(new_instances)
-            # let torchscript think Instances was scripted already
-            Instances.__torch_script_class__ = True
-            # let torchscript find new_instances when looking for the jit type of Instances
-            Instances._jit_override_qualname = torch._jit_internal._qualified_name(new_instances)
-
-            _add_instances_conversion_methods(new_instances)
-            yield new_instances
-        finally:
-            try:
-                del Instances.__torch_script_class__
-                del Instances._jit_override_qualname
-            except AttributeError:
-                pass
-            sys.modules.pop(module.__name__)
-
-
-def _gen_instance_class(fields):
-    """
-    Args:
-        fields (dict[name: type])
-    """
-
-    class _FieldType:
-        def __init__(self, name, type_):
-            assert isinstance(name, str), f"Field name must be str, got {name}"
-            self.name = name
-            self.type_ = type_
-            self.annotation = f"{type_.__module__}.{type_.__name__}"
-
-    fields = [_FieldType(k, v) for k, v in fields.items()]
-
-    def indent(level, s):
-        return " " * 4 * level + s
-
-    lines = []
-
-    global _counter
-    _counter += 1
-
-    cls_name = "ScriptedInstances{}".format(_counter)
-
-    field_names = tuple(x.name for x in fields)
-    extra_args = ", ".join([f"{f.name}: Optional[{f.annotation}] = None" for f in fields])
-    lines.append(
-        f"""
-class {cls_name}:
-    def __init__(self, image_size: Tuple[int, int], {extra_args}):
-        self.image_size = image_size
-        self._field_names = {field_names}
-"""
-    )
-
-    for f in fields:
-        lines.append(
-            indent(2, f"self._{f.name} = torch.jit.annotate(Optional[{f.annotation}], {f.name})")
-        )
-
-    for f in fields:
-        lines.append(
-            f"""
-    @property
-    def {f.name}(self) -> {f.annotation}:
-        # has to use a local for type refinement
-        # https://pytorch.org/docs/stable/jit_language_reference.html#optional-type-refinement
-        t = self._{f.name}
-        assert t is not None, "{f.name} is None and cannot be accessed!"
-        return t
-
-    @{f.name}.setter
-    def {f.name}(self, value: {f.annotation}) -> None:
-        self._{f.name} = value
-"""
-        )
-
-    # support method `__len__`
-    lines.append(
-        """
-    def __len__(self) -> int:
-"""
-    )
-    for f in fields:
-        lines.append(
-            f"""
-        t = self._{f.name}
-        if t is not None:
-            return len(t)
-"""
-        )
-    lines.append(
-        """
-        raise NotImplementedError("Empty Instances does not support __len__!")
-"""
-    )
-
-    # support method `has`
-    lines.append(
-        """
-    def has(self, name: str) -> bool:
-"""
-    )
-    for f in fields:
-        lines.append(
-            f"""
-        if name == "{f.name}":
-            return self._{f.name} is not None
-"""
-        )
-    lines.append(
-        """
-        return False
-"""
-    )
-
-    # support method `to`
-    none_args = ", None" * len(fields)
-    lines.append(
-        f"""
-    def to(self, device: torch.device) -> "{cls_name}":
-        ret = {cls_name}(self.image_size{none_args})
-"""
-    )
-    for f in fields:
-        if hasattr(f.type_, "to"):
-            lines.append(
-                f"""
-        t = self._{f.name}
-        if t is not None:
-            ret._{f.name} = t.to(device)
-"""
-            )
-        else:
-            # For now, ignore fields that cannot be moved to devices.
-            # Maybe can support other tensor-like classes (e.g. __torch_function__)
-            pass
-    lines.append(
-        """
-        return ret
-"""
-    )
-
-    # support method `getitem`
-    none_args = ", None" * len(fields)
-    lines.append(
-        f"""
-    def __getitem__(self, item) -> "{cls_name}":
-        ret = {cls_name}(self.image_size{none_args})
-"""
-    )
-    for f in fields:
-        lines.append(
-            f"""
-        t = self._{f.name}
-        if t is not None:
-            ret._{f.name} = t[item]
-"""
-        )
-    lines.append(
-        """
-        return ret
-"""
-    )
-
-    # support method `cat`
-    # this version does not contain checks that all instances have same size and fields
-    none_args = ", None" * len(fields)
-    lines.append(
-        f"""
-    def cat(self, instances: List["{cls_name}"]) -> "{cls_name}":
-        ret = {cls_name}(self.image_size{none_args})
-"""
-    )
-    for f in fields:
-        lines.append(
-            f"""
-        t = self._{f.name}
-        if t is not None:
-            values: List[{f.annotation}] = [x.{f.name} for x in instances]
-            if torch.jit.isinstance(t, torch.Tensor):
-                ret._{f.name} = torch.cat(values, dim=0)
-            else:
-                ret._{f.name} = t.cat(values)
-"""
-        )
-    lines.append(
-        """
-        return ret"""
-    )
-
-    # support method `get_fields()`
-    lines.append(
-        """
-    def get_fields(self) -> Dict[str, Tensor]:
-        ret = {}
-    """
-    )
-    for f in fields:
-        if f.type_ == Boxes:
-            stmt = "t.tensor"
-        elif f.type_ == torch.Tensor:
-            stmt = "t"
-        else:
-            stmt = f'assert False, "unsupported type {str(f.type_)}"'
-        lines.append(
-            f"""
-        t = self._{f.name}
-        if t is not None:
-            ret["{f.name}"] = {stmt}
-        """
-        )
-    lines.append(
-        """
-        return ret"""
-    )
-    return cls_name, os.linesep.join(lines)
-
-
-def _gen_instance_module(fields):
-    # TODO: find a more automatic way to enable import of other classes
-    s = """
-from copy import deepcopy
-import torch
-from torch import Tensor
-import typing
-from typing import *
-
-import detectron2
-from detectron2.structures import Boxes, Instances
-
-"""
-
-    cls_name, cls_def = _gen_instance_class(fields)
-    s += cls_def
-    return cls_name, s
-
-
-def _import(path):
-    return _import_file(
-        "{}{}".format(sys.modules[__name__].__name__, _counter), path, make_importable=True
-    )
-
-
-@contextmanager
-def patch_builtin_len(modules=()):
-    """
-    Patch the builtin len() function of a few detectron2 modules
-    to use __len__ instead, because __len__ does not convert values to
-    integers and therefore is friendly to tracing.
-
-    Args:
-        modules (list[stsr]): names of extra modules to patch len(), in
-            addition to those in detectron2.
-    """
-
-    def _new_len(obj):
-        return obj.__len__()
-
-    with ExitStack() as stack:
-        MODULES = [
-            "detectron2.modeling.roi_heads.fast_rcnn",
-            "detectron2.modeling.roi_heads.mask_head",
-            "detectron2.modeling.roi_heads.keypoint_head",
-        ] + list(modules)
-        ctxs = [stack.enter_context(mock.patch(mod + ".len")) for mod in MODULES]
-        for m in ctxs:
-            m.side_effect = _new_len
-        yield
-
-
-def patch_nonscriptable_classes():
-    """
-    Apply patches on a few nonscriptable detectron2 classes.
-    Should not have side-effects on eager usage.
-    """
-    # __prepare_scriptable__ can also be added to models for easier maintenance.
-    # But it complicates the clean model code.
-
-    from detectron2.modeling.backbone import ResNet, FPN
-
-    # Due to https://github.com/pytorch/pytorch/issues/36061,
-    # we change backbone to use ModuleList for scripting.
-    # (note: this changes param names in state_dict)
-
-    def prepare_resnet(self):
-        ret = deepcopy(self)
-        ret.stages = nn.ModuleList(ret.stages)
-        for k in self.stage_names:
-            delattr(ret, k)
-        return ret
-
-    ResNet.__prepare_scriptable__ = prepare_resnet
-
-    def prepare_fpn(self):
-        ret = deepcopy(self)
-        ret.lateral_convs = nn.ModuleList(ret.lateral_convs)
-        ret.output_convs = nn.ModuleList(ret.output_convs)
-        for name, _ in self.named_children():
-            if name.startswith("fpn_"):
-                delattr(ret, name)
-        return ret
-
-    FPN.__prepare_scriptable__ = prepare_fpn
-
-    # Annotate some attributes to be constants for the purpose of scripting,
-    # even though they are not constants in eager mode.
-    from detectron2.modeling.roi_heads import StandardROIHeads
-
-    if hasattr(StandardROIHeads, "__annotations__"):
-        # copy first to avoid editing annotations of base class
-        StandardROIHeads.__annotations__ = deepcopy(StandardROIHeads.__annotations__)
-        StandardROIHeads.__annotations__["mask_on"] = torch.jit.Final[bool]
-        StandardROIHeads.__annotations__["keypoint_on"] = torch.jit.Final[bool]
-
-
-# These patches are not supposed to have side-effects.
-patch_nonscriptable_classes()
-
-
-@contextmanager
-def freeze_training_mode(model):
-    """
-    A context manager that annotates the "training" attribute of every submodule
-    to constant, so that the training codepath in these modules can be
-    meta-compiled away. Upon exiting, the annotations are reverted.
-    """
-    classes = {type(x) for x in model.modules()}
-    # __constants__ is the old way to annotate constants and not compatible
-    # with __annotations__ .
-    classes = {x for x in classes if not hasattr(x, "__constants__")}
-    for cls in classes:
-        cls.__annotations__["training"] = torch.jit.Final[bool]
-    yield
-    for cls in classes:
-        cls.__annotations__["training"] = bool
diff --git a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/tests/layers/test_nms_rotated.py b/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/tests/layers/test_nms_rotated.py
deleted file mode 100644
index 4b45384892ab2a7cb20871cf19374f1bd08907ce..0000000000000000000000000000000000000000
--- a/spaces/Awiny/Image2Paragraph/models/grit_src/third_party/CenterNet2/tests/layers/test_nms_rotated.py
+++ /dev/null
@@ -1,172 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-from __future__ import absolute_import, division, print_function, unicode_literals
-import numpy as np
-import unittest
-from copy import deepcopy
-import torch
-from torchvision import ops
-
-from detectron2.layers import batched_nms, batched_nms_rotated, nms_rotated
-from detectron2.utils.testing import random_boxes
-
-
-def nms_edit_distance(keep1, keep2):
-    """
-    Compare the "keep" result of two nms call.
-    They are allowed to be different in terms of edit distance
-    due to floating point precision issues, e.g.,
-    if a box happen to have an IoU of 0.5 with another box,
-    one implentation may choose to keep it while another may discard it.
-    """
-    keep1, keep2 = keep1.cpu(), keep2.cpu()
-    if torch.equal(keep1, keep2):
-        # they should be equal most of the time
-        return 0
-    keep1, keep2 = tuple(keep1), tuple(keep2)
-    m, n = len(keep1), len(keep2)
-
-    # edit distance with DP
-    f = [np.arange(n + 1), np.arange(n + 1)]
-    for i in range(m):
-        cur_row = i % 2
-        other_row = (i + 1) % 2
-        f[other_row][0] = i + 1
-        for j in range(n):
-            f[other_row][j + 1] = (
-                f[cur_row][j]
-                if keep1[i] == keep2[j]
-                else min(min(f[cur_row][j], f[cur_row][j + 1]), f[other_row][j]) + 1
-            )
-    return f[m % 2][n]
-
-
-class TestNMSRotated(unittest.TestCase):
-    def reference_horizontal_nms(self, boxes, scores, iou_threshold):
-        """
-        Args:
-            box_scores (N, 5): boxes in corner-form and probabilities.
-                (Note here 5 == 4 + 1, i.e., 4-dim horizontal box + 1-dim prob)
-            iou_threshold: intersection over union threshold.
-        Returns:
-             picked: a list of indexes of the kept boxes
-        """
-        picked = []
-        _, indexes = scores.sort(descending=True)
-        while len(indexes) > 0:
-            current = indexes[0]
-            picked.append(current.item())
-            if len(indexes) == 1:
-                break
-            current_box = boxes[current, :]
-            indexes = indexes[1:]
-            rest_boxes = boxes[indexes, :]
-            iou = ops.box_iou(rest_boxes, current_box.unsqueeze(0)).squeeze(1)
-            indexes = indexes[iou <= iou_threshold]
-
-        return torch.as_tensor(picked)
-
-    def _create_tensors(self, N, device="cpu"):
-        boxes = random_boxes(N, 200, device=device)
-        scores = torch.rand(N, device=device)
-        return boxes, scores
-
-    def test_batched_nms_rotated_0_degree_cpu(self, device="cpu"):
-        N = 2000
-        num_classes = 50
-        boxes, scores = self._create_tensors(N, device=device)
-        idxs = torch.randint(0, num_classes, (N,))
-        rotated_boxes = torch.zeros(N, 5, device=device)
-        rotated_boxes[:, 0] = (boxes[:, 0] + boxes[:, 2]) / 2.0
-        rotated_boxes[:, 1] = (boxes[:, 1] + boxes[:, 3]) / 2.0
-        rotated_boxes[:, 2] = boxes[:, 2] - boxes[:, 0]
-        rotated_boxes[:, 3] = boxes[:, 3] - boxes[:, 1]
-        err_msg = "Rotated NMS with 0 degree is incompatible with horizontal NMS for IoU={}"
-        for iou in [0.2, 0.5, 0.8]:
-            backup = boxes.clone()
-            keep_ref = batched_nms(boxes, scores, idxs, iou)
-            assert torch.allclose(boxes, backup), "boxes modified by batched_nms"
-            backup = rotated_boxes.clone()
-            keep = batched_nms_rotated(rotated_boxes, scores, idxs, iou)
-            assert torch.allclose(
-                rotated_boxes, backup
-            ), "rotated_boxes modified by batched_nms_rotated"
-            # Occasionally the gap can be large if there are many IOU on the threshold boundary
-            self.assertLessEqual(nms_edit_distance(keep, keep_ref), 5, err_msg.format(iou))
-
-    @unittest.skipIf(not torch.cuda.is_available(), "CUDA not available")
-    def test_batched_nms_rotated_0_degree_cuda(self):
-        self.test_batched_nms_rotated_0_degree_cpu(device="cuda")
-
-    def test_nms_rotated_0_degree_cpu(self, device="cpu"):
-        N = 1000
-        boxes, scores = self._create_tensors(N, device=device)
-        rotated_boxes = torch.zeros(N, 5, device=device)
-        rotated_boxes[:, 0] = (boxes[:, 0] + boxes[:, 2]) / 2.0
-        rotated_boxes[:, 1] = (boxes[:, 1] + boxes[:, 3]) / 2.0
-        rotated_boxes[:, 2] = boxes[:, 2] - boxes[:, 0]
-        rotated_boxes[:, 3] = boxes[:, 3] - boxes[:, 1]
-        err_msg = "Rotated NMS incompatible between CPU and reference implementation for IoU={}"
-        for iou in [0.2, 0.5, 0.8]:
-            keep_ref = self.reference_horizontal_nms(boxes, scores, iou)
-            keep = nms_rotated(rotated_boxes, scores, iou)
-            self.assertLessEqual(nms_edit_distance(keep, keep_ref), 1, err_msg.format(iou))
-
-    @unittest.skipIf(not torch.cuda.is_available(), "CUDA not available")
-    def test_nms_rotated_0_degree_cuda(self):
-        self.test_nms_rotated_0_degree_cpu(device="cuda")
-
-    def test_nms_rotated_90_degrees_cpu(self):
-        N = 1000
-        boxes, scores = self._create_tensors(N)
-        rotated_boxes = torch.zeros(N, 5)
-        rotated_boxes[:, 0] = (boxes[:, 0] + boxes[:, 2]) / 2.0
-        rotated_boxes[:, 1] = (boxes[:, 1] + boxes[:, 3]) / 2.0
-        # Note for rotated_boxes[:, 2] and rotated_boxes[:, 3]:
-        # widths and heights are intentionally swapped here for 90 degrees case
-        # so that the reference horizontal nms could be used
-        rotated_boxes[:, 2] = boxes[:, 3] - boxes[:, 1]
-        rotated_boxes[:, 3] = boxes[:, 2] - boxes[:, 0]
-
-        rotated_boxes[:, 4] = torch.ones(N) * 90
-        err_msg = "Rotated NMS incompatible between CPU and reference implementation for IoU={}"
-        for iou in [0.2, 0.5, 0.8]:
-            keep_ref = self.reference_horizontal_nms(boxes, scores, iou)
-            keep = nms_rotated(rotated_boxes, scores, iou)
-            self.assertLessEqual(nms_edit_distance(keep, keep_ref), 1, err_msg.format(iou))
-
-    def test_nms_rotated_180_degrees_cpu(self):
-        N = 1000
-        boxes, scores = self._create_tensors(N)
-        rotated_boxes = torch.zeros(N, 5)
-        rotated_boxes[:, 0] = (boxes[:, 0] + boxes[:, 2]) / 2.0
-        rotated_boxes[:, 1] = (boxes[:, 1] + boxes[:, 3]) / 2.0
-        rotated_boxes[:, 2] = boxes[:, 2] - boxes[:, 0]
-        rotated_boxes[:, 3] = boxes[:, 3] - boxes[:, 1]
-        rotated_boxes[:, 4] = torch.ones(N) * 180
-        err_msg = "Rotated NMS incompatible between CPU and reference implementation for IoU={}"
-        for iou in [0.2, 0.5, 0.8]:
-            keep_ref = self.reference_horizontal_nms(boxes, scores, iou)
-            keep = nms_rotated(rotated_boxes, scores, iou)
-            self.assertLessEqual(nms_edit_distance(keep, keep_ref), 1, err_msg.format(iou))
-
-
-class TestScriptable(unittest.TestCase):
-    def setUp(self):
-        class TestingModule(torch.nn.Module):
-            def forward(self, boxes, scores, threshold):
-                return nms_rotated(boxes, scores, threshold)
-
-        self.module = TestingModule()
-
-    def test_scriptable_cpu(self):
-        m = deepcopy(self.module).cpu()
-        _ = torch.jit.script(m)
-
-    @unittest.skipIf(not torch.cuda.is_available(), "CUDA not available")
-    def test_scriptable_cuda(self):
-        m = deepcopy(self.module).cuda()
-        _ = torch.jit.script(m)
-
-
-if __name__ == "__main__":
-    unittest.main()
diff --git a/spaces/Benson/text-generation/Examples/Com.p1.chomp Sms Pro Apk.md b/spaces/Benson/text-generation/Examples/Com.p1.chomp Sms Pro Apk.md
deleted file mode 100644
index ebc6e2370e89788c8ee7a9811f646090e177db95..0000000000000000000000000000000000000000
--- a/spaces/Benson/text-generation/Examples/Com.p1.chomp Sms Pro Apk.md	
+++ /dev/null
@@ -1,104 +0,0 @@
-<br />
-<h1>¿Qué es com.p1.chomp sms pro apk? </h1>
-<p>Si usted está buscando una forma rápida, fácil y divertida de enviar y recibir mensajes de texto, entonces es posible que desee probar com.p1.chomp sms pro apk. Esta es una aplicación de mensajería popular que le permite personalizar sus mensajes con varios temas, fuentes, colores, emojis, pegatinas, GIF y más. También puede programar mensajes, hacer copias de seguridad y restaurar sus mensajes, bloquear spam y mensajes no deseados, y disfrutar de muchas otras características que hacen que los mensajes de texto sean más agradables. </p>
-<h2>¿Por qué usar com.p1.chomp sms pro apk? </h2>
-<p>Hay muchas razones por las que es posible que desee utilizar com.p1.chomp sms pro apk sobre otras aplicaciones de mensajería. Estos son algunos de ellos:</p>
-<h2>com.p1.chomp sms pro apk</h2><br /><p><b><b>Download File</b> &#10145; <a href="https://bltlly.com/2v6Ja1">https://bltlly.com/2v6Ja1</a></b></p><br /><br />
-<ul>
-<li>Es gratis y sin publicidad. No tienes que pagar nada ni lidiar con anuncios molestos para usar la aplicación. </li>
-<li>Es compatible con la mayoría de los dispositivos Android. Puede usar la aplicación en cualquier dispositivo que ejecute Android 4.1 o superior. </li>
-<li> Es fácil de usar. Puede configurar la aplicación en minutos y empezar a enviar mensajes de texto de inmediato. </li>
-<li>Es personalizable. Puede elegir entre cientos de temas, fuentes, colores y notificaciones para hacer que sus mensajes se vean únicos. </li>
-<li>Es divertido. Puedes expresarte con emojis, pegatinas, GIF y otros medios a los que puedes acceder desde el teclado de la aplicación. </li>
-<li> Es inteligente. Puede programar mensajes, hacer copias de seguridad y restaurar sus mensajes, bloquear el spam y los mensajes no deseados, y usar otras funciones que hacen que los mensajes de texto sean más convenientes. </li>
-</ul>
-<h3>Cómo descargar e instalar com.p1.chomp sms pro apk? </h3>
-<p>Para descargar e instalar com.p1.chomp sms pro apk en su dispositivo, debe seguir estos pasos:</p>
-<ol>
-<li>Vaya a <a href="( 1 )">https://apkdone.com/chomp-sms/</a> y haga clic en el botón "Descargar APK". </li>
-<li>Espera a que termine la descarga y luego abre el archivo. </li>
-<li>Si ves un mensaje de advertencia que dice "Instalar bloqueado", ve a la configuración de tu dispositivo y habilita "Fuentes desconocidas". </li>
-<li>Toque en "Instalar" y espere a que la instalación se complete. </li>
-
-</ol>
-<h4>Cómo personalizar sus mensajes con com.p1.chomp sms pro apk? </h4>
-<p>Para personalizar sus mensajes con com.p1.chomp sms pro apk, es necesario hacer lo siguiente:</p>
-<ul>
-<li>Abra la aplicación y toque en el icono del menú (tres líneas horizontales) en la esquina superior izquierda. </ <li>Seleccione "Configuración" y luego "Personalizar apariencia". </li>
-<li>Aquí puede elegir entre varias opciones para cambiar la apariencia de sus mensajes, como tema, fuente, color, estilo de burbuja, icono de notificación y más. </li>
-<li>Toque en la opción que desea cambiar y seleccione su opción preferida. </li>
-<li>Toque en "Guardar" y luego en "Aceptar" para aplicar los cambios. </li>
-</ul>
-<h4>Cómo utilizar emojis, pegatinas y GIF con com.p1.chomp sms pro apk? </h4>
-<p>Para usar emojis, pegatinas y GIF con com.p1.chomp sms pro apk, debe hacer lo siguiente:</p>
-<ul>
-<li> Abra la aplicación y toque en el icono "+" en la esquina inferior izquierda del teclado. </li>
-<li>Verá un menú con diferentes opciones para agregar medios a sus mensajes, como emojis, pegatinas, GIF, fotos, videos, notas de voz y más. </li>
-<li>Toque en la opción que desea utilizar y navegue a través de las opciones disponibles. </li>
-<li>Toque en el medio que desea enviar y se añadirá a su mensaje. </li>
-<li>Toque en el botón "Enviar" para enviar su mensaje con los medios de comunicación. </li>
-</ul>
-<h4>Cómo programar mensajes con com.p1.chomp sms pro apk? </h4>
-<p>Para programar mensajes con com.p1.chomp sms pro apk, debe hacer lo siguiente:</p>
-<ul>
-<li> Abra la aplicación y toque en el "Nuevo mensaje" botón en la esquina inferior derecha. </li>
-<li>Escribe el número o nombre del destinatario y escribe tu mensaje. </li>
-<li>Toque en el icono del reloj en la esquina superior derecha del teclado. </li>
-<li>Verá un menú con diferentes opciones para programar su mensaje, como más tarde hoy, mañana, la próxima semana o la fecha y hora personalizadas. </li>
-<li>Toque en la opción que desea utilizar y confirme su elección. </li>
-
-</ul> <h3>Cómo hacer copias de seguridad y restaurar sus mensajes con com.p1.chomp sms pro apk? </h3>
-<p>Para respaldar y restaurar sus mensajes con com.p1.chomp sms pro apk, debe hacer lo siguiente:</p>
-<ul>
-<li> Abra la aplicación y toque en el icono del menú (tres líneas horizontales) en la esquina superior izquierda. </li>
-<li>Seleccione "Configuración" y luego "Copia de seguridad & Restaurar". </li>
-<li>Aquí puede elegir hacer copias de seguridad de sus mensajes en la nube o en su dispositivo, así como restaurar sus mensajes desde la nube o desde su dispositivo. </li>
-<li>Toque en la opción que desea utilizar y siga las instrucciones en la pantalla. </li>
-<li>Necesitará iniciar sesión con su cuenta de Google para usar el servicio en la nube. </li>
-<li>Tus mensajes serán respaldados o restaurados según tu elección. </li>
-</ul>
-<h3>Cómo bloquear spam y mensajes no deseados con com.p1.chomp sms pro apk? </h3>
-<p>Para bloquear spam y mensajes no deseados con com.p1.chomp sms pro apk, debe hacer lo siguiente:</p>
-<p></p>
-<ul>
-<li> Abra la aplicación y toque en el mensaje que desea bloquear. </li>
-<li>Toque en el icono del menú (tres puntos verticales) en la esquina superior derecha del mensaje. </li>
-<li>Seleccione "Bloquear" y luego "OK". </li>
-<li> El mensaje se moverá a la carpeta "Bloqueado" y no recibirá más mensajes de ese número o contacto. </li>
-<li>También puede agregar números o contactos a su lista negra manualmente yendo a "Configuración" y luego "Lista negra". </li>
-<li>También puede habilitar el modo de privacidad yendo a "Configuración" y luego "Privacidad". Esto ocultará sus notificaciones y mensajes de miradas indiscretas. </li>
-</ul>
-<h2>¿Cuáles son los pros y los contras de com.p1.chomp sms pro apk? </h2>
-<p>Como cualquier otra aplicación, com.p1.chomp sms pro apk tiene sus pros y contras. Aquí están algunos de ellos:</p>
- <tabla>
-<tr><th>Pros</th><th>Contras</th></tr>
-<tr><td>Libre y sin anuncios</td><td>Requiere conexión a Internet</td></tr>
-<tr><td>Compatible con la mayoría de dispositivos Android</td><td>No disponible para dispositivos iOS</td></tr>
-
-<tr><td>Personalizable</td><td>Puede consumir más batería o memoria</td></tr>
-<tr><td>Diversión</td><td>Puede que no soporte algunos formatos de medios</td></tr>
-<tr><td>Smart</td><td>Puede que no funcione con algunos operadores o redes</td></tr>
-</tabla>
- <p>Si usted está buscando algunas alternativas a com.p1.chomp sms pro apk, puede probar estas aplicaciones:</p>
- <ul>
-<li>Textra SMS: Una aplicación de mensajería simple y rápida que también te permite personalizar tus mensajes con temas, emojis, GIF y más. </li>
-<li>Pulse SMS: Una aplicación de mensajería potente y segura que también te permite sincronizar tus mensajes en todos tus dispositivos, incluido tu ordenador. </li>
-<li>Mood Messenger: Una aplicación de mensajería elegante e inteligente que también le permite enviar emojis animados, mensajes de voz, ubicación y más. </li>
-</ul>
- <h2>Conclusión</h2>
- <p>En conclusión, com.p1.chomp sms pro apk es una gran aplicación de mensajería que ofrece muchas características y opciones para hacer mensajes de texto más divertido y conveniente. Puede descargar e instalar la aplicación de forma gratuita y disfrutar de la personalización de sus mensajes con temas, fuentes, colores, emojis, pegatinas, GIF, y más. También puede programar mensajes, hacer copias de seguridad y restaurar sus mensajes, bloquear el spam y los mensajes no deseados, y usar otras funciones que hacen que los mensajes de texto sean más inteligentes. Sin embargo, también debe ser consciente de los contras y limitaciones de la aplicación, tales como requerir conexión a Internet, no estar disponible para dispositivos iOS, tener algunos errores o problemas técnicos, consumir más batería o memoria, no es compatible con algunos formatos de medios, y no trabajar con algunos operadores o redes. También puede probar algunas alternativas a com.p1.chomp sms pro apk si desea explorar otras aplicaciones de mensajería. Esperamos que este artículo le ha ayudado a aprender más acerca de com.p1.chomp sms pro apk y cómo usarlo. Feliz mensajes de texto! </p>
- <h2>Preguntas frecuentes (preguntas frecuentes)</h2>
- <ol>
-<li><b>Lo que es com.p1.chomp sms pro apk? </b></li>
-
- <li><b>Cómo puedo descargar e instalar com.p1.chomp sms pro apk? </b></li <p>A: Para descargar e instalar com.p1.chomp sms pro apk en su dispositivo, debe ir a <a href="">https://apkdone.com/chomp-sms/</a> y hacer clic en el botón "Descargar APK". Luego, debe abrir el archivo y tocar en "Instalar". Es posible que deba habilitar "Fuentes desconocidas" en la configuración de su dispositivo para instalar la aplicación. Una vez completada la instalación, puedes tocar en "Abrir" y disfrutar usando la aplicación. </p>
- <li><b>¿Cómo puedo personalizar mis mensajes con com.p1.chomp sms pro apk? </b></li>
-<p>A: Para personalizar sus mensajes con com.p1.chomp sms pro apk, es necesario abrir la aplicación y toque en el icono del menú (tres líneas horizontales) en la esquina superior izquierda. Luego, debe seleccionar "Configuración" y luego "Personalizar apariencia". Aquí, puede elegir entre varias opciones para cambiar la apariencia de sus mensajes, como tema, fuente, color, estilo de burbuja, icono de notificación y más. Puede pulsar en la opción que desea cambiar y seleccionar su opción preferida. Puede pulsar en "Guardar" y luego "Aceptar" para aplicar los cambios. </p>
- <li><b>¿Cómo puedo usar emojis, pegatinas y GIF con com.p1.chomp sms pro apk? </b></li>
-<p>A: Para utilizar emojis, pegatinas y GIF con com.p1.chomp sms pro apk, es necesario abrir la aplicación y toque en el "+" icono en la esquina inferior izquierda del teclado. Verá un menú con diferentes opciones para agregar medios a sus mensajes, como emojis, pegatinas, GIF, fotos, videos, notas de voz y más. Puede tocar en la opción que desea utilizar y navegar a través de las opciones disponibles. Puede pulsar en el medio que desea enviar y se añadirá a su mensaje. Puede pulsar en el botón "Enviar" para enviar su mensaje con el medio. </p>
- <li><b>¿Cómo puedo programar mensajes con com.p1.chomp sms pro apk? </b></li>
-
- <li><b>¿Cómo hago copia de seguridad y restaurar mis mensajes con com.p1.chomp sms pro apk? </b></li>
-<p>A: Para copia de seguridad y restaurar sus mensajes con com.p1.chomp sms pro apk, es necesario abrir la aplicación y toque en el icono del menú (tres líneas horizontales) en la esquina superior izquierda. Luego, debe seleccionar "Configuración" y luego "Copia de seguridad y restauración". Aquí, puede elegir hacer una copia de seguridad de sus mensajes en la nube o en su dispositivo, así como restaurar sus mensajes desde la nube o desde su dispositivo. Puede tocar en la opción que desea utilizar y siga las instrucciones en la pantalla. Deberá iniciar sesión con su cuenta de Google para utilizar el servicio en la nube. Se realizará una copia de seguridad de sus mensajes o se restaurarán según su elección. </p> 64aa2da5cf<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/Benson/text-generation/Examples/Descargar Canciones De M Kumaran Hijo De Mahalakshmi.md b/spaces/Benson/text-generation/Examples/Descargar Canciones De M Kumaran Hijo De Mahalakshmi.md
deleted file mode 100644
index 0172791547006b1315f6acf2b38f8a815de1dd97..0000000000000000000000000000000000000000
--- a/spaces/Benson/text-generation/Examples/Descargar Canciones De M Kumaran Hijo De Mahalakshmi.md	
+++ /dev/null
@@ -1,102 +0,0 @@
-
-<h1>Cómo descargar canciones de M. Kumaran Son of Mahalakshmi</h1>
-<p>M. Kumaran Son of Mahalakshmi es una película tamil de 2004 dirigida por M. Raja y protagonizada por Jayam Ravi, Asin, Nadhiya y Prakash Raj. La película es un remake de la película telugu Amma Nanna O Tamila Ammayi y cuenta la historia de Kumaran, un kickboxer que va a Malasia para encontrarse con su padre después de la muerte de su madre. La película fue un éxito de taquilla y una de las películas más rentables de 2004. </p>
-<p>Una de las razones del éxito de la película fue su banda sonora, compuesta por Srikanth Deva, hijo del veterano director musical Deva. La banda sonora consta de seis canciones que van desde el rock, folk, melodía, y géneros de rap. Las canciones cuentan con varios cantantes como Shankar Mahadevan, Karthik, Sadhana Sargam, Tippu, Anuradha Sriram, Ranjith, Premji Amaren y el propio Srikanth Deva. Las canciones son pegadizas, emocionales y motivacionales, y se adaptan perfectamente al tema de la película. </p>
-<h2>descargar canciones de m kumaran hijo de mahalakshmi</h2><br /><p><b><b>Download</b> &#10038; <a href="https://bltlly.com/2v6LVR">https://bltlly.com/2v6LVR</a></b></p><br /><br />
-<p>Si eres un fan de las canciones de M. Kumaran Son of Mahalakshmi y quieres descargarlas en tu dispositivo, tienes dos opciones: puedes descargarlas gratis o por una tarifa. En este artículo, te mostraremos cómo hacer ambas cosas. </p>
- <h2>Por qué deberías escuchar canciones de M. Kumaran hijo de Mahalakshmi</h2>
-<h3>Las canciones están compuestas por Srikanth Deva, un director de música popular en el cine tamil</h3>
-<p>Srikanth Deva es uno de los directores de música más prolíficos en el cine tamil, habiendo compuesto música para más de 100 películas desde su debut en 2002. Es conocido por su versatilidad y capacidad para crear canciones que atraen a diferentes audiencias. Ha trabajado con muchos actores y directores principales en el cine tamil, como Vij <h3>Las canciones cuentan con varios cantantes y géneros, como rock, folk, melodía y rap</h3>
-
-<p>Estas canciones no solo son agradables de escuchar, sino también significativas y relevantes para la historia y los personajes. Mejoran el estado de ánimo y la emoción de la película y la hacen más atractiva y memorable. </p>
- <h3>Las canciones son pegadizas, emocionales y motivadoras, y se adaptan al tema de la película</h3>
-<p>Las canciones de M. Kumaran Son of Mahalakshmi no son solo canciones aleatorias o de relleno. Son pegadizos, emocionales y motivadores, y se adaptan al tema de la película. La película trata sobre el viaje de Kumaran para encontrar su identidad y su lugar en el mundo, así como su relación con su padre, su madre, su novia y sus amigos. Las canciones reflejan estos aspectos y transmiten el mensaje de la película. </p>
-<p>Por ejemplo, la canción "Amma Nee Sumandha" es un homenaje a la madre de Kumaran, quien lo crió sin ayuda y le enseñó a ser fuerte e independiente. La canción "Rakkamma" es una canción motivacional que anima a Kumaran a superar sus miedos y desafíos y lograr sus sueños. La canción "Aethiree" es una canción pegadiza que muestra la amistad y la diversión entre Kumaran y sus amigos. La canción "Unnai Ninaithu" es una canción emocional que revela los sentimientos de Kumaran por su padre, quien lo abandonó cuando era joven. </p>
-<p>Estas canciones no solo son pegadizas, emocionales y motivadoras, sino que también se adaptan al tema de la película. Transmiten el mensaje de la película y la hacen más impactante e inspiradora. </p>
- <h2>Cómo descargar canciones de M. Kumaran Son of Mahalakshmi gratis</h2>
-<h3>Utilice un sitio web o aplicación confiable y legal que ofrece descargas gratuitas de canciones tamiles</h3>
-
-<p>Algunos de los sitios web o aplicaciones confiables y legales que ofrecen descargas gratuitas de canciones tamiles son:</p>
-<ul>
-<li><a href="">Gaana.com</a>: Esta es una de las plataformas de streaming de música online más grandes de la India, con más de 200 millones de usuarios mensuales. Ofrece descargas gratuitas de canciones tamiles, así como de otros idiomas y géneros. Puedes buscar canciones de M. Kumaran Son of Mahalakshmi escribiendo el nombre de la película o el nombre de la canción en la barra de búsqueda. También puede navegar a través de las categorías y listas de reproducción para encontrar las canciones que desea. Puede descargar las canciones haciendo clic en el icono de descarga junto al título de la canción. Puede elegir el formato y la calidad que prefiera, como MP3, AAC o HD. También puede escuchar las canciones en línea o sin conexión en su dispositivo. </li>
-<li><a href="">Hungama.com</a>: Esta es otra popular plataforma de streaming de música en línea en la India, con más de 150 millones de usuarios mensuales. También ofrece descargas gratuitas de canciones tamiles, así como de otros idiomas y géneros. Puedes buscar canciones de M. Kumaran Son of Mahalakshmi escribiendo el nombre de la película o el nombre de la canción en la barra de búsqueda. También puede navegar a través de las categorías y listas de reproducción para encontrar las canciones que desea. Puede descargar las canciones haciendo clic en el icono de descarga junto al título de la canción. Puede elegir el formato y la calidad que prefiera, como MP3, AAC o HD. También puede escuchar las canciones en línea o sin conexión en su dispositivo. </li>
-
-</ul>
-<p>Estos son algunos de los sitios web o aplicaciones confiables y legales que ofrecen descargas gratuitas de canciones tamiles. Sin embargo, siempre debe comprobar los términos y condiciones de cada sitio web o aplicación antes de descargar cualquier canción, y asegúrese de no violar ninguna ley o política. </p>
-<p></p>
- <h2>Cómo descargar canciones de M. Kumaran Son of Mahalakshmi por una tarifa</h2>
-<h3>Utilice un servicio de streaming de pago o tienda en línea que ofrece descargas de alta calidad de canciones Tamil</h3>
-<p>Si desea descargar canciones de M. Kumaran Son of Mahalakshmi por una tarifa, debe usar un servicio de transmisión pagado o una tienda en línea que ofrece descargas de alta calidad de canciones tamiles. Hay muchos servicios de streaming de pago y tiendas en línea que ofrecen descargas de alta calidad de canciones tamiles, pero no todos ellos valen su dinero o tiempo. Algunos de ellos pueden cobrarle demasiado o muy poco, algunos de ellos pueden tener un mal servicio al cliente o soporte técnico, algunos de ellos pueden tener opciones o características limitadas, y algunos de ellos pueden tener productos de baja calidad o falsos. Por lo tanto, debe tener cuidado y elegir un servicio o tienda que vale la pena su dinero y tiempo, y que proporciona productos y servicios de alta calidad. </p>
-<p>Algunos de los servicios de streaming de pago y tiendas en línea que ofrecen descargas de alta calidad de canciones tamiles son:</p>
-<ul>
-
-<li><a href="">iTunes</a>: Esta es una de las tiendas de música en línea más populares y ampliamente utilizadas del mundo, con más de 60 millones de canciones disponibles para comprar y descargar. Ofrece descargas de alta calidad de canciones tamiles, así como otros idiomas y géneros. Puedes buscar canciones de M. Kumaran Son of Mahalakshmi escribiendo el nombre de la película o el nombre de la canción en la barra de búsqueda. También puede navegar a través de las categorías y listas de reproducción para encontrar las canciones que desea. Puede descargar las canciones haciendo clic en el botón comprar junto al título de la canción. Puede elegir el formato y la calidad que prefiera, como MP3, AAC o HD. También puede escuchar las canciones en línea o sin conexión en su dispositivo. Sin embargo, necesitas registrarte para una cuenta y pagar por cada canción que quieras descargar. El precio de cada canción varía de $0.69 a $1.29, dependiendo de la popularidad y la demanda de la canción. </li>
-<li><a href="">Saavn</a>: Esta es una de las plataformas de streaming de música más populares y ampliamente utilizadas en la India, con más de 100 millones de usuarios mensuales. Ofrece descargas de alta calidad de canciones tamiles, así como otros idiomas y géneros. Puedes buscar canciones de M. Kumaran Son of Mahalakshmi escribiendo el nombre de la película o el nombre de la canción en la barra de búsqueda. También puede navegar a través de las categorías y listas de reproducción para encontrar las canciones que desea. Puede descargar las canciones haciendo clic en el icono de descarga junto al título de la canción. Puede elegir el formato y la calidad que prefiera, como MP3, AAC o HD. También puede escuchar las canciones en línea o sin conexión en su dispositivo. Sin embargo, debe registrarse para obtener una cuenta y pagar una suscripción para acceder a la función de descarga. Los planes de suscripción varían de $1.99 a $9.99 por mes, dependiendo de las características y beneficios que desee. </li>
-</ul>
-
- <h2>Cómo disfrutar de las canciones de M. Kumaran hijo de Mahalakshmi después de descargarlas</h2>
-<h3>Transfiera las canciones a su reproductor de música o dispositivo preferido</h3>
-<p>Después de descargar canciones de M. Kumaran Son of Mahalakshmi, necesitas transferirlas a tu reproductor de música o dispositivo preferido, para que puedas disfrutarlas en cualquier momento y en cualquier lugar que desees. Hay diferentes formas de transferir las canciones, dependiendo de la fuente y el destino de la transferencia. </p>
-<p>Por ejemplo, si has descargado las canciones de Gaana.com o Hungama.com, puedes transferirlas a tu smartphone o tablet mediante un cable USB o una conexión inalámbrica. Si los has descargado de iTunes, puedes transferirlos a tu iPhone, iPad, iPod o Mac usando iTunes Sync o iCloud Music Library. Si los ha descargado desde Saavn, puede transferirlos a su smartphone o tableta mediante un cable USB o una conexión inalámbrica. </p>
-<p>Siempre debe seguir las instrucciones y directrices de cada sitio web o aplicación al transferir las canciones, y asegúrese de no perder ni dañar ningún archivo durante el proceso. </p>
- <h3>Crear una lista de reproducción de sus canciones favoritas de la película</h3>
-<p>Después de transferir canciones de M. Kumaran Son of Mahalakshmi a su reproductor de música o dispositivo preferido, puede crear una lista de reproducción de sus canciones favoritas de la película. Una lista de reproducción es una colección de canciones que puedes reproducir en modo secuencial o aleatorio. Crear una lista de reproducción de tus canciones favoritas de la película puede ayudarte a disfrutarlas más y organizarlas mejor. También puede compartir su lista de reproducción con sus amigos o familiares, o escuchar las listas de reproducción de otras personas de la misma película. </p>
-
-<p>Siempre debe seguir las instrucciones y directrices de cada reproductor de música o dispositivo al crear una lista de reproducción, y asegúrese de guardar y actualizar su lista de reproducción con regularidad. </p>
- <h3>Escuchar las canciones en cualquier momento y en cualquier lugar que desee</h3>
-<p>Después de crear una lista de reproducción de tus canciones favoritas de M. Kumaran Son of Mahalakshmi, puedes escuchar las canciones en cualquier momento y en cualquier lugar que quieras. Puede escuchar las canciones en línea o fuera de línea, dependiendo de su conexión a Internet y plan de datos. También puede ajustar el volumen, saltar, repetir o barajar las canciones, dependiendo de su preferencia y estado de ánimo. También puedes cantar, bailar o simplemente relajarte y disfrutar de las canciones. </p>
-<p>Escuchar canciones de M. Kumaran Son of Mahalakshmi puede hacerte sentir feliz, triste, emocionado, nostálgico o inspirado, dependiendo de la canción y la situación. Las canciones también pueden recordarte la película y sus personajes, y hacerte apreciar más la historia y el mensaje. Las canciones también pueden ayudarle a aprender más sobre la cultura y el idioma tamil, y enriquecer su conocimiento y experiencia. </p>
- <h1>Conclusión</h1>
-<p>M. Kumaran Son of Mahalakshmi es una película tamil de 2004 que tiene una gran banda sonora compuesta por Srikanth Deva. La banda sonora consta de seis canciones que cuentan con varios cantantes y géneros, como rock, folk, melodía y rap. Las canciones son pegadizas, emocionales y motivacionales, y se adaptan perfectamente al tema de la película. </p>
-
-<p>Después de descargar canciones de M. Kumaran Son of Mahalakshmi a tu dispositivo, puedes disfrutarlas en cualquier momento y en cualquier lugar que quieras. Puede transferir las canciones a su reproductor de música o dispositivo preferido, crear una lista de reproducción de sus canciones favoritas de la película y escuchar las canciones en línea o fuera de línea. También puede compartir su lista de reproducción con sus amigos o familiares, o escuchar las listas de reproducción de otras personas de la misma película. </p>
-<p>Escuchar canciones de M. Kumaran Son of Mahalakshmi puede hacerte sentir feliz, triste, emocionado, nostálgico o inspirado, dependiendo de la canción y la situación. Las canciones también pueden recordarte la película y sus personajes, y hacerte apreciar más la historia y el mensaje. Las canciones también pueden ayudarle a aprender más sobre la cultura y el idioma tamil, y enriquecer su conocimiento y experiencia. </p>
-<p>Entonces, ¿qué estás esperando? Descarga las canciones de M. Kumaran Son of Mahalakshmi hoy y disfrútalas al máximo! </p>
- <h2>Preguntas frecuentes</h2>
-<h3>P: ¿Cuáles son los nombres de las seis canciones de M. Kumaran Hijo de Mahalakshmi? </h3>
-<p>A: Los nombres de las seis canciones de M. Kumaran Son:</p>
-<ol>
-<li>Ayyo Ayyo</li>
-<li>Yaaru Yaaru</li>
-<li>Neeye Neeye</li>
-<li>Chennai Senthamizh</li>
-<li>Amma Nee Sumandha</li>
-<li>Rakkamma</li>
-</ol>
- <h3>P: ¿Quiénes son los cantantes de las seis canciones de M. Kumaran Hijo de Mahalakshmi? </h3>
-<p>A: Los cantantes de las seis canciones de M. Kumaran Son:</p>
-<ul>
-<li>Ayyo Ayyo: Shankar Mahadevan y Karthik</li>
-<li>Yaaru Yaaru: Tippu y Anuradha Sriram</li>
-<li>Neeye Neeye: Karthik y Sadhana Sargam</li>
-<li>Chennai Senthamizh: Ranjith, Premji Amaren y Srikanth Deva</li>
-<li>Amma Nee Sumandha: Srikanth Deva</li>
-<li>Rakkamma: Tippu y Anuradha Sriram</li>
-</ul>
- <h3>P: ¿Dónde puedo ver la película en línea de M. Kumaran Son of Mahalakshmi? </h3>
-<p>A: Puedes ver la película en línea de M. Kumaran Son of Mahalakshmi en varias plataformas de streaming, como:</p>
-<ul>
-
-<li><a href=">YouTube</a>: Esta es una popular plataforma para compartir videos que ofrece una variedad de videos en diferentes categorías y temas. Puedes ver M. Kumaran Son of Mahalakshmi película en línea en YouTube de forma gratuita con anuncios, o por una tarifa sin anuncios. También puede descargar la película en su dispositivo para ver sin conexión. </li>
-<li><a href="">Amazon Prime Video</a>: Esta es una popular plataforma de streaming que ofrece una variedad de películas y programas en diferentes idiomas y géneros. Puedes ver la película en línea de M. Kumaran Son of Mahalakshmi en Amazon Prime Video por una tarifa con o sin anuncios. También puede descargar la película en su dispositivo para ver sin conexión. </li>
-</ul>
- <h3>Q: ¿Cómo puedo aprender más sobre la cultura y el idioma tamil? </h3>
-<p>A: Hay muchas maneras de aprender más sobre la cultura y el idioma tamil, como:</p>
-<ul>
-<li>Leer libros, revistas, periódicos, blogs o sitios web que están escritos en tamil o sobre temas tamiles. </li>
-<li>Ver películas, programas, documentales o videos que se hacen en tamil o sobre temas tamiles. </li>
-<li>Escuchar podcasts, estaciones de radio, álbumes de música o canciones que se hablan en tamil o sobre temas tamiles. </li>
-<li>Tomar cursos, clases, lecciones o tutoriales que enseñan el idioma o la cultura tamil. </li>
-<li>Unirse a clubes, grupos, comunidades o foros que hablan de la lengua o cultura tamil. </li>
-<li>Visitar lugares, eventos, festivales o atracciones que muestran el idioma o la cultura tamil. </li>
-<li <li>Conocer gente, amigos, familiares o vecinos que hablan tamil o conocen la cultura tamil. </li>
-</ul>
- <h3>Q: ¿Cuáles son algunas otras películas que tienen buenas canciones tamiles? </h3>
-<p>A: Hay muchas películas que tienen buenas canciones tamiles, pero algunas de las más populares y aclamadas son:</p>
-<ul>
-
-<li>Roja: Esta es una película romántica de 1992 dirigida por Mani Ratnam y protagonizada por Arvind Swamy y Madhoo. La película trata sobre una mujer que intenta rescatar a su marido que es secuestrado por terroristas en Cachemira. La película tiene una hermosa banda sonora compuesta por A.R. Rahman, con canciones como "Kadhal Rojave", "Chinna Chinna Aasai", "Pudhu Vellai Mazhai" y "Rukkumani Rukkumani". </li>
-<li>3: Esta es una película romántica de 2012 dirigida por Aishwarya R. Dhanush y protagonizada por Dhanush y Shruti Haasan. La película trata sobre una pareja que enfrenta varios desafíos en su relación debido al trastorno bipolar y la muerte. La película tiene una banda sonora pegadiza compuesta por Anirudh Ravichander, con canciones como "Why This Kolaveri Di", "Idhazhin Oram", "Nee Paartha Vizhigal" y "Po Nee Po". </li>
-</ul></p> 64aa2da5cf<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/BetterAPI/BetterChat/src/lib/utils/randomUuid.ts b/spaces/BetterAPI/BetterChat/src/lib/utils/randomUuid.ts
deleted file mode 100644
index 9d536365c57659305ad28d6fc06b89d77ab337ab..0000000000000000000000000000000000000000
--- a/spaces/BetterAPI/BetterChat/src/lib/utils/randomUuid.ts
+++ /dev/null
@@ -1,14 +0,0 @@
-type UUID = ReturnType<typeof crypto.randomUUID>;
-
-export function randomUUID(): UUID {
-	// Only on old safari / ios
-	if (!("randomUUID" in crypto)) {
-		return "10000000-1000-4000-8000-100000000000".replace(/[018]/g, (c) =>
-			(
-				Number(c) ^
-				(crypto.getRandomValues(new Uint8Array(1))[0] & (15 >> (Number(c) / 4)))
-			).toString(16)
-		) as UUID;
-	}
-	return crypto.randomUUID();
-}
diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_internal/metadata/importlib/_dists.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_internal/metadata/importlib/_dists.py
deleted file mode 100644
index 65c043c87eff27e9405316fdbc0c695f2b347441..0000000000000000000000000000000000000000
--- a/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_internal/metadata/importlib/_dists.py
+++ /dev/null
@@ -1,224 +0,0 @@
-import email.message
-import importlib.metadata
-import os
-import pathlib
-import zipfile
-from typing import (
-    Collection,
-    Dict,
-    Iterable,
-    Iterator,
-    Mapping,
-    Optional,
-    Sequence,
-    cast,
-)
-
-from pip._vendor.packaging.requirements import Requirement
-from pip._vendor.packaging.utils import NormalizedName, canonicalize_name
-from pip._vendor.packaging.version import parse as parse_version
-
-from pip._internal.exceptions import InvalidWheel, UnsupportedWheel
-from pip._internal.metadata.base import (
-    BaseDistribution,
-    BaseEntryPoint,
-    DistributionVersion,
-    InfoPath,
-    Wheel,
-)
-from pip._internal.utils.misc import normalize_path
-from pip._internal.utils.packaging import safe_extra
-from pip._internal.utils.temp_dir import TempDirectory
-from pip._internal.utils.wheel import parse_wheel, read_wheel_metadata_file
-
-from ._compat import BasePath, get_dist_name
-
-
-class WheelDistribution(importlib.metadata.Distribution):
-    """An ``importlib.metadata.Distribution`` read from a wheel.
-
-    Although ``importlib.metadata.PathDistribution`` accepts ``zipfile.Path``,
-    its implementation is too "lazy" for pip's needs (we can't keep the ZipFile
-    handle open for the entire lifetime of the distribution object).
-
-    This implementation eagerly reads the entire metadata directory into the
-    memory instead, and operates from that.
-    """
-
-    def __init__(
-        self,
-        files: Mapping[pathlib.PurePosixPath, bytes],
-        info_location: pathlib.PurePosixPath,
-    ) -> None:
-        self._files = files
-        self.info_location = info_location
-
-    @classmethod
-    def from_zipfile(
-        cls,
-        zf: zipfile.ZipFile,
-        name: str,
-        location: str,
-    ) -> "WheelDistribution":
-        info_dir, _ = parse_wheel(zf, name)
-        paths = (
-            (name, pathlib.PurePosixPath(name.split("/", 1)[-1]))
-            for name in zf.namelist()
-            if name.startswith(f"{info_dir}/")
-        )
-        files = {
-            relpath: read_wheel_metadata_file(zf, fullpath)
-            for fullpath, relpath in paths
-        }
-        info_location = pathlib.PurePosixPath(location, info_dir)
-        return cls(files, info_location)
-
-    def iterdir(self, path: InfoPath) -> Iterator[pathlib.PurePosixPath]:
-        # Only allow iterating through the metadata directory.
-        if pathlib.PurePosixPath(str(path)) in self._files:
-            return iter(self._files)
-        raise FileNotFoundError(path)
-
-    def read_text(self, filename: str) -> Optional[str]:
-        try:
-            data = self._files[pathlib.PurePosixPath(filename)]
-        except KeyError:
-            return None
-        try:
-            text = data.decode("utf-8")
-        except UnicodeDecodeError as e:
-            wheel = self.info_location.parent
-            error = f"Error decoding metadata for {wheel}: {e} in {filename} file"
-            raise UnsupportedWheel(error)
-        return text
-
-
-class Distribution(BaseDistribution):
-    def __init__(
-        self,
-        dist: importlib.metadata.Distribution,
-        info_location: Optional[BasePath],
-        installed_location: Optional[BasePath],
-    ) -> None:
-        self._dist = dist
-        self._info_location = info_location
-        self._installed_location = installed_location
-
-    @classmethod
-    def from_directory(cls, directory: str) -> BaseDistribution:
-        info_location = pathlib.Path(directory)
-        dist = importlib.metadata.Distribution.at(info_location)
-        return cls(dist, info_location, info_location.parent)
-
-    @classmethod
-    def from_metadata_file_contents(
-        cls,
-        metadata_contents: bytes,
-        filename: str,
-        project_name: str,
-    ) -> BaseDistribution:
-        # Generate temp dir to contain the metadata file, and write the file contents.
-        temp_dir = pathlib.Path(
-            TempDirectory(kind="metadata", globally_managed=True).path
-        )
-        metadata_path = temp_dir / "METADATA"
-        metadata_path.write_bytes(metadata_contents)
-        # Construct dist pointing to the newly created directory.
-        dist = importlib.metadata.Distribution.at(metadata_path.parent)
-        return cls(dist, metadata_path.parent, None)
-
-    @classmethod
-    def from_wheel(cls, wheel: Wheel, name: str) -> BaseDistribution:
-        try:
-            with wheel.as_zipfile() as zf:
-                dist = WheelDistribution.from_zipfile(zf, name, wheel.location)
-        except zipfile.BadZipFile as e:
-            raise InvalidWheel(wheel.location, name) from e
-        except UnsupportedWheel as e:
-            raise UnsupportedWheel(f"{name} has an invalid wheel, {e}")
-        return cls(dist, dist.info_location, pathlib.PurePosixPath(wheel.location))
-
-    @property
-    def location(self) -> Optional[str]:
-        if self._info_location is None:
-            return None
-        return str(self._info_location.parent)
-
-    @property
-    def info_location(self) -> Optional[str]:
-        if self._info_location is None:
-            return None
-        return str(self._info_location)
-
-    @property
-    def installed_location(self) -> Optional[str]:
-        if self._installed_location is None:
-            return None
-        return normalize_path(str(self._installed_location))
-
-    def _get_dist_name_from_location(self) -> Optional[str]:
-        """Try to get the name from the metadata directory name.
-
-        This is much faster than reading metadata.
-        """
-        if self._info_location is None:
-            return None
-        stem, suffix = os.path.splitext(self._info_location.name)
-        if suffix not in (".dist-info", ".egg-info"):
-            return None
-        return stem.split("-", 1)[0]
-
-    @property
-    def canonical_name(self) -> NormalizedName:
-        name = self._get_dist_name_from_location() or get_dist_name(self._dist)
-        return canonicalize_name(name)
-
-    @property
-    def version(self) -> DistributionVersion:
-        return parse_version(self._dist.version)
-
-    def is_file(self, path: InfoPath) -> bool:
-        return self._dist.read_text(str(path)) is not None
-
-    def iter_distutils_script_names(self) -> Iterator[str]:
-        # A distutils installation is always "flat" (not in e.g. egg form), so
-        # if this distribution's info location is NOT a pathlib.Path (but e.g.
-        # zipfile.Path), it can never contain any distutils scripts.
-        if not isinstance(self._info_location, pathlib.Path):
-            return
-        for child in self._info_location.joinpath("scripts").iterdir():
-            yield child.name
-
-    def read_text(self, path: InfoPath) -> str:
-        content = self._dist.read_text(str(path))
-        if content is None:
-            raise FileNotFoundError(path)
-        return content
-
-    def iter_entry_points(self) -> Iterable[BaseEntryPoint]:
-        # importlib.metadata's EntryPoint structure sasitfies BaseEntryPoint.
-        return self._dist.entry_points
-
-    def _metadata_impl(self) -> email.message.Message:
-        # From Python 3.10+, importlib.metadata declares PackageMetadata as the
-        # return type. This protocol is unfortunately a disaster now and misses
-        # a ton of fields that we need, including get() and get_payload(). We
-        # rely on the implementation that the object is actually a Message now,
-        # until upstream can improve the protocol. (python/cpython#94952)
-        return cast(email.message.Message, self._dist.metadata)
-
-    def iter_provided_extras(self) -> Iterable[str]:
-        return (
-            safe_extra(extra) for extra in self.metadata.get_all("Provides-Extra", [])
-        )
-
-    def iter_dependencies(self, extras: Collection[str] = ()) -> Iterable[Requirement]:
-        contexts: Sequence[Dict[str, str]] = [{"extra": safe_extra(e)} for e in extras]
-        for req_string in self.metadata.get_all("Requires-Dist", []):
-            req = Requirement(req_string)
-            if not req.marker:
-                yield req
-            elif not extras and req.marker.evaluate({"extra": ""}):
-                yield req
-            elif any(req.marker.evaluate(context) for context in contexts):
-                yield req
diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_vendor/distlib/scripts.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_vendor/distlib/scripts.py
deleted file mode 100644
index d2706242b8aac125a66450d5ce8dcd3395336182..0000000000000000000000000000000000000000
--- a/spaces/Big-Web/MMSD/env/Lib/site-packages/pip/_vendor/distlib/scripts.py
+++ /dev/null
@@ -1,437 +0,0 @@
-# -*- coding: utf-8 -*-
-#
-# Copyright (C) 2013-2015 Vinay Sajip.
-# Licensed to the Python Software Foundation under a contributor agreement.
-# See LICENSE.txt and CONTRIBUTORS.txt.
-#
-from io import BytesIO
-import logging
-import os
-import re
-import struct
-import sys
-import time
-from zipfile import ZipInfo
-
-from .compat import sysconfig, detect_encoding, ZipFile
-from .resources import finder
-from .util import (FileOperator, get_export_entry, convert_path,
-                   get_executable, get_platform, in_venv)
-
-logger = logging.getLogger(__name__)
-
-_DEFAULT_MANIFEST = '''
-<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
-<assembly xmlns="urn:schemas-microsoft-com:asm.v1" manifestVersion="1.0">
- <assemblyIdentity version="1.0.0.0"
- processorArchitecture="X86"
- name="%s"
- type="win32"/>
-
- <!-- Identify the application security requirements. -->
- <trustInfo xmlns="urn:schemas-microsoft-com:asm.v3">
- <security>
- <requestedPrivileges>
- <requestedExecutionLevel level="asInvoker" uiAccess="false"/>
- </requestedPrivileges>
- </security>
- </trustInfo>
-</assembly>'''.strip()
-
-# check if Python is called on the first line with this expression
-FIRST_LINE_RE = re.compile(b'^#!.*pythonw?[0-9.]*([ \t].*)?$')
-SCRIPT_TEMPLATE = r'''# -*- coding: utf-8 -*-
-import re
-import sys
-from %(module)s import %(import_name)s
-if __name__ == '__main__':
-    sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0])
-    sys.exit(%(func)s())
-'''
-
-
-def enquote_executable(executable):
-    if ' ' in executable:
-        # make sure we quote only the executable in case of env
-        # for example /usr/bin/env "/dir with spaces/bin/jython"
-        # instead of "/usr/bin/env /dir with spaces/bin/jython"
-        # otherwise whole
-        if executable.startswith('/usr/bin/env '):
-            env, _executable = executable.split(' ', 1)
-            if ' ' in _executable and not _executable.startswith('"'):
-                executable = '%s "%s"' % (env, _executable)
-        else:
-            if not executable.startswith('"'):
-                executable = '"%s"' % executable
-    return executable
-
-# Keep the old name around (for now), as there is at least one project using it!
-_enquote_executable = enquote_executable
-
-class ScriptMaker(object):
-    """
-    A class to copy or create scripts from source scripts or callable
-    specifications.
-    """
-    script_template = SCRIPT_TEMPLATE
-
-    executable = None  # for shebangs
-
-    def __init__(self, source_dir, target_dir, add_launchers=True,
-                 dry_run=False, fileop=None):
-        self.source_dir = source_dir
-        self.target_dir = target_dir
-        self.add_launchers = add_launchers
-        self.force = False
-        self.clobber = False
-        # It only makes sense to set mode bits on POSIX.
-        self.set_mode = (os.name == 'posix') or (os.name == 'java' and
-                                                 os._name == 'posix')
-        self.variants = set(('', 'X.Y'))
-        self._fileop = fileop or FileOperator(dry_run)
-
-        self._is_nt = os.name == 'nt' or (
-            os.name == 'java' and os._name == 'nt')
-        self.version_info = sys.version_info
-
-    def _get_alternate_executable(self, executable, options):
-        if options.get('gui', False) and self._is_nt:  # pragma: no cover
-            dn, fn = os.path.split(executable)
-            fn = fn.replace('python', 'pythonw')
-            executable = os.path.join(dn, fn)
-        return executable
-
-    if sys.platform.startswith('java'):  # pragma: no cover
-        def _is_shell(self, executable):
-            """
-            Determine if the specified executable is a script
-            (contains a #! line)
-            """
-            try:
-                with open(executable) as fp:
-                    return fp.read(2) == '#!'
-            except (OSError, IOError):
-                logger.warning('Failed to open %s', executable)
-                return False
-
-        def _fix_jython_executable(self, executable):
-            if self._is_shell(executable):
-                # Workaround for Jython is not needed on Linux systems.
-                import java
-
-                if java.lang.System.getProperty('os.name') == 'Linux':
-                    return executable
-            elif executable.lower().endswith('jython.exe'):
-                # Use wrapper exe for Jython on Windows
-                return executable
-            return '/usr/bin/env %s' % executable
-
-    def _build_shebang(self, executable, post_interp):
-        """
-        Build a shebang line. In the simple case (on Windows, or a shebang line
-        which is not too long or contains spaces) use a simple formulation for
-        the shebang. Otherwise, use /bin/sh as the executable, with a contrived
-        shebang which allows the script to run either under Python or sh, using
-        suitable quoting. Thanks to Harald Nordgren for his input.
-
-        See also: http://www.in-ulm.de/~mascheck/various/shebang/#length
-                  https://hg.mozilla.org/mozilla-central/file/tip/mach
-        """
-        if os.name != 'posix':
-            simple_shebang = True
-        else:
-            # Add 3 for '#!' prefix and newline suffix.
-            shebang_length = len(executable) + len(post_interp) + 3
-            if sys.platform == 'darwin':
-                max_shebang_length = 512
-            else:
-                max_shebang_length = 127
-            simple_shebang = ((b' ' not in executable) and
-                              (shebang_length <= max_shebang_length))
-
-        if simple_shebang:
-            result = b'#!' + executable + post_interp + b'\n'
-        else:
-            result = b'#!/bin/sh\n'
-            result += b"'''exec' " + executable + post_interp + b' "$0" "$@"\n'
-            result += b"' '''"
-        return result
-
-    def _get_shebang(self, encoding, post_interp=b'', options=None):
-        enquote = True
-        if self.executable:
-            executable = self.executable
-            enquote = False     # assume this will be taken care of
-        elif not sysconfig.is_python_build():
-            executable = get_executable()
-        elif in_venv():  # pragma: no cover
-            executable = os.path.join(sysconfig.get_path('scripts'),
-                            'python%s' % sysconfig.get_config_var('EXE'))
-        else:  # pragma: no cover
-            executable = os.path.join(
-                sysconfig.get_config_var('BINDIR'),
-               'python%s%s' % (sysconfig.get_config_var('VERSION'),
-                               sysconfig.get_config_var('EXE')))
-            if not os.path.isfile(executable):
-                # for Python builds from source on Windows, no Python executables with
-                # a version suffix are created, so we use python.exe
-                executable = os.path.join(sysconfig.get_config_var('BINDIR'),
-                                'python%s' % (sysconfig.get_config_var('EXE')))
-        if options:
-            executable = self._get_alternate_executable(executable, options)
-
-        if sys.platform.startswith('java'):  # pragma: no cover
-            executable = self._fix_jython_executable(executable)
-
-        # Normalise case for Windows - COMMENTED OUT
-        # executable = os.path.normcase(executable)
-        # N.B. The normalising operation above has been commented out: See
-        # issue #124. Although paths in Windows are generally case-insensitive,
-        # they aren't always. For example, a path containing a ẞ (which is a
-        # LATIN CAPITAL LETTER SHARP S - U+1E9E) is normcased to ß (which is a
-        # LATIN SMALL LETTER SHARP S' - U+00DF). The two are not considered by
-        # Windows as equivalent in path names.
-
-        # If the user didn't specify an executable, it may be necessary to
-        # cater for executable paths with spaces (not uncommon on Windows)
-        if enquote:
-            executable = enquote_executable(executable)
-        # Issue #51: don't use fsencode, since we later try to
-        # check that the shebang is decodable using utf-8.
-        executable = executable.encode('utf-8')
-        # in case of IronPython, play safe and enable frames support
-        if (sys.platform == 'cli' and '-X:Frames' not in post_interp
-            and '-X:FullFrames' not in post_interp):  # pragma: no cover
-            post_interp += b' -X:Frames'
-        shebang = self._build_shebang(executable, post_interp)
-        # Python parser starts to read a script using UTF-8 until
-        # it gets a #coding:xxx cookie. The shebang has to be the
-        # first line of a file, the #coding:xxx cookie cannot be
-        # written before. So the shebang has to be decodable from
-        # UTF-8.
-        try:
-            shebang.decode('utf-8')
-        except UnicodeDecodeError:  # pragma: no cover
-            raise ValueError(
-                'The shebang (%r) is not decodable from utf-8' % shebang)
-        # If the script is encoded to a custom encoding (use a
-        # #coding:xxx cookie), the shebang has to be decodable from
-        # the script encoding too.
-        if encoding != 'utf-8':
-            try:
-                shebang.decode(encoding)
-            except UnicodeDecodeError:  # pragma: no cover
-                raise ValueError(
-                    'The shebang (%r) is not decodable '
-                    'from the script encoding (%r)' % (shebang, encoding))
-        return shebang
-
-    def _get_script_text(self, entry):
-        return self.script_template % dict(module=entry.prefix,
-                                           import_name=entry.suffix.split('.')[0],
-                                           func=entry.suffix)
-
-    manifest = _DEFAULT_MANIFEST
-
-    def get_manifest(self, exename):
-        base = os.path.basename(exename)
-        return self.manifest % base
-
-    def _write_script(self, names, shebang, script_bytes, filenames, ext):
-        use_launcher = self.add_launchers and self._is_nt
-        linesep = os.linesep.encode('utf-8')
-        if not shebang.endswith(linesep):
-            shebang += linesep
-        if not use_launcher:
-            script_bytes = shebang + script_bytes
-        else:  # pragma: no cover
-            if ext == 'py':
-                launcher = self._get_launcher('t')
-            else:
-                launcher = self._get_launcher('w')
-            stream = BytesIO()
-            with ZipFile(stream, 'w') as zf:
-                source_date_epoch = os.environ.get('SOURCE_DATE_EPOCH')
-                if source_date_epoch:
-                    date_time = time.gmtime(int(source_date_epoch))[:6]
-                    zinfo = ZipInfo(filename='__main__.py', date_time=date_time)
-                    zf.writestr(zinfo, script_bytes)
-                else:
-                    zf.writestr('__main__.py', script_bytes)
-            zip_data = stream.getvalue()
-            script_bytes = launcher + shebang + zip_data
-        for name in names:
-            outname = os.path.join(self.target_dir, name)
-            if use_launcher:  # pragma: no cover
-                n, e = os.path.splitext(outname)
-                if e.startswith('.py'):
-                    outname = n
-                outname = '%s.exe' % outname
-                try:
-                    self._fileop.write_binary_file(outname, script_bytes)
-                except Exception:
-                    # Failed writing an executable - it might be in use.
-                    logger.warning('Failed to write executable - trying to '
-                                   'use .deleteme logic')
-                    dfname = '%s.deleteme' % outname
-                    if os.path.exists(dfname):
-                        os.remove(dfname)       # Not allowed to fail here
-                    os.rename(outname, dfname)  # nor here
-                    self._fileop.write_binary_file(outname, script_bytes)
-                    logger.debug('Able to replace executable using '
-                                 '.deleteme logic')
-                    try:
-                        os.remove(dfname)
-                    except Exception:
-                        pass    # still in use - ignore error
-            else:
-                if self._is_nt and not outname.endswith('.' + ext):  # pragma: no cover
-                    outname = '%s.%s' % (outname, ext)
-                if os.path.exists(outname) and not self.clobber:
-                    logger.warning('Skipping existing file %s', outname)
-                    continue
-                self._fileop.write_binary_file(outname, script_bytes)
-                if self.set_mode:
-                    self._fileop.set_executable_mode([outname])
-            filenames.append(outname)
-
-    variant_separator = '-'
-
-    def get_script_filenames(self, name):
-        result = set()
-        if '' in self.variants:
-            result.add(name)
-        if 'X' in self.variants:
-            result.add('%s%s' % (name, self.version_info[0]))
-        if 'X.Y' in self.variants:
-            result.add('%s%s%s.%s' % (name, self.variant_separator,
-                                      self.version_info[0], self.version_info[1]))
-        return result
-
-    def _make_script(self, entry, filenames, options=None):
-        post_interp = b''
-        if options:
-            args = options.get('interpreter_args', [])
-            if args:
-                args = ' %s' % ' '.join(args)
-                post_interp = args.encode('utf-8')
-        shebang = self._get_shebang('utf-8', post_interp, options=options)
-        script = self._get_script_text(entry).encode('utf-8')
-        scriptnames = self.get_script_filenames(entry.name)
-        if options and options.get('gui', False):
-            ext = 'pyw'
-        else:
-            ext = 'py'
-        self._write_script(scriptnames, shebang, script, filenames, ext)
-
-    def _copy_script(self, script, filenames):
-        adjust = False
-        script = os.path.join(self.source_dir, convert_path(script))
-        outname = os.path.join(self.target_dir, os.path.basename(script))
-        if not self.force and not self._fileop.newer(script, outname):
-            logger.debug('not copying %s (up-to-date)', script)
-            return
-
-        # Always open the file, but ignore failures in dry-run mode --
-        # that way, we'll get accurate feedback if we can read the
-        # script.
-        try:
-            f = open(script, 'rb')
-        except IOError:  # pragma: no cover
-            if not self.dry_run:
-                raise
-            f = None
-        else:
-            first_line = f.readline()
-            if not first_line:  # pragma: no cover
-                logger.warning('%s is an empty file (skipping)', script)
-                return
-
-            match = FIRST_LINE_RE.match(first_line.replace(b'\r\n', b'\n'))
-            if match:
-                adjust = True
-                post_interp = match.group(1) or b''
-
-        if not adjust:
-            if f:
-                f.close()
-            self._fileop.copy_file(script, outname)
-            if self.set_mode:
-                self._fileop.set_executable_mode([outname])
-            filenames.append(outname)
-        else:
-            logger.info('copying and adjusting %s -> %s', script,
-                        self.target_dir)
-            if not self._fileop.dry_run:
-                encoding, lines = detect_encoding(f.readline)
-                f.seek(0)
-                shebang = self._get_shebang(encoding, post_interp)
-                if b'pythonw' in first_line:  # pragma: no cover
-                    ext = 'pyw'
-                else:
-                    ext = 'py'
-                n = os.path.basename(outname)
-                self._write_script([n], shebang, f.read(), filenames, ext)
-            if f:
-                f.close()
-
-    @property
-    def dry_run(self):
-        return self._fileop.dry_run
-
-    @dry_run.setter
-    def dry_run(self, value):
-        self._fileop.dry_run = value
-
-    if os.name == 'nt' or (os.name == 'java' and os._name == 'nt'):  # pragma: no cover
-        # Executable launcher support.
-        # Launchers are from https://bitbucket.org/vinay.sajip/simple_launcher/
-
-        def _get_launcher(self, kind):
-            if struct.calcsize('P') == 8:   # 64-bit
-                bits = '64'
-            else:
-                bits = '32'
-            platform_suffix = '-arm' if get_platform() == 'win-arm64' else ''
-            name = '%s%s%s.exe' % (kind, bits, platform_suffix)
-            # Issue 31: don't hardcode an absolute package name, but
-            # determine it relative to the current package
-            distlib_package = __name__.rsplit('.', 1)[0]
-            resource = finder(distlib_package).find(name)
-            if not resource:
-                msg = ('Unable to find resource %s in package %s' % (name,
-                       distlib_package))
-                raise ValueError(msg)
-            return resource.bytes
-
-    # Public API follows
-
-    def make(self, specification, options=None):
-        """
-        Make a script.
-
-        :param specification: The specification, which is either a valid export
-                              entry specification (to make a script from a
-                              callable) or a filename (to make a script by
-                              copying from a source location).
-        :param options: A dictionary of options controlling script generation.
-        :return: A list of all absolute pathnames written to.
-        """
-        filenames = []
-        entry = get_export_entry(specification)
-        if entry is None:
-            self._copy_script(specification, filenames)
-        else:
-            self._make_script(entry, filenames, options=options)
-        return filenames
-
-    def make_multiple(self, specifications, options=None):
-        """
-        Take a list of specifications and make scripts from them,
-        :param specifications: A list of specifications.
-        :return: A list of all absolute pathnames written to,
-        """
-        filenames = []
-        for specification in specifications:
-            filenames.extend(self.make(specification, options))
-        return filenames
diff --git a/spaces/Big-Web/MMSD/env/Lib/site-packages/setuptools/wheel.py b/spaces/Big-Web/MMSD/env/Lib/site-packages/setuptools/wheel.py
deleted file mode 100644
index 527ed3b23306a3822388520115bafaf3eabb5024..0000000000000000000000000000000000000000
--- a/spaces/Big-Web/MMSD/env/Lib/site-packages/setuptools/wheel.py
+++ /dev/null
@@ -1,222 +0,0 @@
-"""Wheels support."""
-
-import email
-import itertools
-import os
-import posixpath
-import re
-import zipfile
-import contextlib
-
-from distutils.util import get_platform
-
-import pkg_resources
-import setuptools
-from pkg_resources import parse_version
-from setuptools.extern.packaging.tags import sys_tags
-from setuptools.extern.packaging.utils import canonicalize_name
-from setuptools.command.egg_info import write_requirements
-from setuptools.archive_util import _unpack_zipfile_obj
-
-
-WHEEL_NAME = re.compile(
-    r"""^(?P<project_name>.+?)-(?P<version>\d.*?)
-    ((-(?P<build>\d.*?))?-(?P<py_version>.+?)-(?P<abi>.+?)-(?P<platform>.+?)
-    )\.whl$""",
-    re.VERBOSE).match
-
-NAMESPACE_PACKAGE_INIT = \
-    "__import__('pkg_resources').declare_namespace(__name__)\n"
-
-
-def unpack(src_dir, dst_dir):
-    '''Move everything under `src_dir` to `dst_dir`, and delete the former.'''
-    for dirpath, dirnames, filenames in os.walk(src_dir):
-        subdir = os.path.relpath(dirpath, src_dir)
-        for f in filenames:
-            src = os.path.join(dirpath, f)
-            dst = os.path.join(dst_dir, subdir, f)
-            os.renames(src, dst)
-        for n, d in reversed(list(enumerate(dirnames))):
-            src = os.path.join(dirpath, d)
-            dst = os.path.join(dst_dir, subdir, d)
-            if not os.path.exists(dst):
-                # Directory does not exist in destination,
-                # rename it and prune it from os.walk list.
-                os.renames(src, dst)
-                del dirnames[n]
-    # Cleanup.
-    for dirpath, dirnames, filenames in os.walk(src_dir, topdown=True):
-        assert not filenames
-        os.rmdir(dirpath)
-
-
-@contextlib.contextmanager
-def disable_info_traces():
-    """
-    Temporarily disable info traces.
-    """
-    from distutils import log
-    saved = log.set_threshold(log.WARN)
-    try:
-        yield
-    finally:
-        log.set_threshold(saved)
-
-
-class Wheel:
-
-    def __init__(self, filename):
-        match = WHEEL_NAME(os.path.basename(filename))
-        if match is None:
-            raise ValueError('invalid wheel name: %r' % filename)
-        self.filename = filename
-        for k, v in match.groupdict().items():
-            setattr(self, k, v)
-
-    def tags(self):
-        '''List tags (py_version, abi, platform) supported by this wheel.'''
-        return itertools.product(
-            self.py_version.split('.'),
-            self.abi.split('.'),
-            self.platform.split('.'),
-        )
-
-    def is_compatible(self):
-        '''Is the wheel is compatible with the current platform?'''
-        supported_tags = set(
-            (t.interpreter, t.abi, t.platform) for t in sys_tags())
-        return next((True for t in self.tags() if t in supported_tags), False)
-
-    def egg_name(self):
-        return pkg_resources.Distribution(
-            project_name=self.project_name, version=self.version,
-            platform=(None if self.platform == 'any' else get_platform()),
-        ).egg_name() + '.egg'
-
-    def get_dist_info(self, zf):
-        # find the correct name of the .dist-info dir in the wheel file
-        for member in zf.namelist():
-            dirname = posixpath.dirname(member)
-            if (dirname.endswith('.dist-info') and
-                    canonicalize_name(dirname).startswith(
-                        canonicalize_name(self.project_name))):
-                return dirname
-        raise ValueError("unsupported wheel format. .dist-info not found")
-
-    def install_as_egg(self, destination_eggdir):
-        '''Install wheel as an egg directory.'''
-        with zipfile.ZipFile(self.filename) as zf:
-            self._install_as_egg(destination_eggdir, zf)
-
-    def _install_as_egg(self, destination_eggdir, zf):
-        dist_basename = '%s-%s' % (self.project_name, self.version)
-        dist_info = self.get_dist_info(zf)
-        dist_data = '%s.data' % dist_basename
-        egg_info = os.path.join(destination_eggdir, 'EGG-INFO')
-
-        self._convert_metadata(zf, destination_eggdir, dist_info, egg_info)
-        self._move_data_entries(destination_eggdir, dist_data)
-        self._fix_namespace_packages(egg_info, destination_eggdir)
-
-    @staticmethod
-    def _convert_metadata(zf, destination_eggdir, dist_info, egg_info):
-        def get_metadata(name):
-            with zf.open(posixpath.join(dist_info, name)) as fp:
-                value = fp.read().decode('utf-8')
-                return email.parser.Parser().parsestr(value)
-
-        wheel_metadata = get_metadata('WHEEL')
-        # Check wheel format version is supported.
-        wheel_version = parse_version(wheel_metadata.get('Wheel-Version'))
-        wheel_v1 = (
-            parse_version('1.0') <= wheel_version < parse_version('2.0dev0')
-        )
-        if not wheel_v1:
-            raise ValueError(
-                'unsupported wheel format version: %s' % wheel_version)
-        # Extract to target directory.
-        _unpack_zipfile_obj(zf, destination_eggdir)
-        # Convert metadata.
-        dist_info = os.path.join(destination_eggdir, dist_info)
-        dist = pkg_resources.Distribution.from_location(
-            destination_eggdir, dist_info,
-            metadata=pkg_resources.PathMetadata(destination_eggdir, dist_info),
-        )
-
-        # Note: Evaluate and strip markers now,
-        # as it's difficult to convert back from the syntax:
-        # foobar; "linux" in sys_platform and extra == 'test'
-        def raw_req(req):
-            req.marker = None
-            return str(req)
-        install_requires = list(map(raw_req, dist.requires()))
-        extras_require = {
-            extra: [
-                req
-                for req in map(raw_req, dist.requires((extra,)))
-                if req not in install_requires
-            ]
-            for extra in dist.extras
-        }
-        os.rename(dist_info, egg_info)
-        os.rename(
-            os.path.join(egg_info, 'METADATA'),
-            os.path.join(egg_info, 'PKG-INFO'),
-        )
-        setup_dist = setuptools.Distribution(
-            attrs=dict(
-                install_requires=install_requires,
-                extras_require=extras_require,
-            ),
-        )
-        with disable_info_traces():
-            write_requirements(
-                setup_dist.get_command_obj('egg_info'),
-                None,
-                os.path.join(egg_info, 'requires.txt'),
-            )
-
-    @staticmethod
-    def _move_data_entries(destination_eggdir, dist_data):
-        """Move data entries to their correct location."""
-        dist_data = os.path.join(destination_eggdir, dist_data)
-        dist_data_scripts = os.path.join(dist_data, 'scripts')
-        if os.path.exists(dist_data_scripts):
-            egg_info_scripts = os.path.join(
-                destination_eggdir, 'EGG-INFO', 'scripts')
-            os.mkdir(egg_info_scripts)
-            for entry in os.listdir(dist_data_scripts):
-                # Remove bytecode, as it's not properly handled
-                # during easy_install scripts install phase.
-                if entry.endswith('.pyc'):
-                    os.unlink(os.path.join(dist_data_scripts, entry))
-                else:
-                    os.rename(
-                        os.path.join(dist_data_scripts, entry),
-                        os.path.join(egg_info_scripts, entry),
-                    )
-            os.rmdir(dist_data_scripts)
-        for subdir in filter(os.path.exists, (
-            os.path.join(dist_data, d)
-            for d in ('data', 'headers', 'purelib', 'platlib')
-        )):
-            unpack(subdir, destination_eggdir)
-        if os.path.exists(dist_data):
-            os.rmdir(dist_data)
-
-    @staticmethod
-    def _fix_namespace_packages(egg_info, destination_eggdir):
-        namespace_packages = os.path.join(
-            egg_info, 'namespace_packages.txt')
-        if os.path.exists(namespace_packages):
-            with open(namespace_packages) as fp:
-                namespace_packages = fp.read().split()
-            for mod in namespace_packages:
-                mod_dir = os.path.join(destination_eggdir, *mod.split('.'))
-                mod_init = os.path.join(mod_dir, '__init__.py')
-                if not os.path.exists(mod_dir):
-                    os.mkdir(mod_dir)
-                if not os.path.exists(mod_init):
-                    with open(mod_init, 'w') as fp:
-                        fp.write(NAMESPACE_PACKAGE_INIT)
diff --git a/spaces/BramVanroy/text-to-amr/README.md b/spaces/BramVanroy/text-to-amr/README.md
deleted file mode 100644
index cbb58b9fd48f161517fda5b04e5c413aec044477..0000000000000000000000000000000000000000
--- a/spaces/BramVanroy/text-to-amr/README.md
+++ /dev/null
@@ -1,16 +0,0 @@
----
-title: Text To AMR
-emoji: 👩‍💻
-colorFrom: yellow
-colorTo: gray
-sdk: docker
-app_port: 8501
-app_file: app.py
-pinned: true
-license: gpl-3.0
-tags:
-    - natural language processing
-    - semantic parsing
-    - abstract meaning representation
-    - amr
----
diff --git a/spaces/C6AI/HDRL/README.md b/spaces/C6AI/HDRL/README.md
deleted file mode 100644
index 6412f3386f0294d7fc0c0696b331c672c0379cc3..0000000000000000000000000000000000000000
--- a/spaces/C6AI/HDRL/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Livebook
-emoji: 📓
-colorFrom: pink
-colorTo: purple
-sdk: docker
-fullWidth: true
-duplicated_from: livebook-dev/livebook
-license: mit
----
-
-You can install and run [Livebook](https://livebook.dev/) inside a Hugging Face Space. Here's [a tutorial](https://huggingface.co/docs/hub/spaces-sdks-docker-livebook) on how to do that.
\ No newline at end of file
diff --git a/spaces/CCaniggia/GPT/Dockerfile b/spaces/CCaniggia/GPT/Dockerfile
deleted file mode 100644
index ad25254725cfd7305edf205272a35c9f781d1081..0000000000000000000000000000000000000000
--- a/spaces/CCaniggia/GPT/Dockerfile
+++ /dev/null
@@ -1,11 +0,0 @@
-from golang:alpine as builder
-run apk --no-cache add git
-run git clone https://github.com/Harry-zklcdc/go-proxy-bingai.git /workspace/app
-workdir /workspace/app
-run go build -ldflags="-s -w" -tags netgo -trimpath -o go-proxy-bingai main.go
-from alpine
-workdir /workspace/app
-copy --from=builder /workspace/app/go-proxy-bingai .
-env Go_Proxy_BingAI_USER_TOKEN_1="kJs8hD92ncMzLaoQWYtx5rG6bE3fZ4iO"
-expose 8080
-cmd ["/workspace/app/go-proxy-bingai"]
\ No newline at end of file
diff --git a/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/detectron2/utils/visualizer.py b/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/detectron2/utils/visualizer.py
deleted file mode 100644
index a8aa4f4682d1db3195f5104da6686258cfa6fd3d..0000000000000000000000000000000000000000
--- a/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/detectron2/utils/visualizer.py
+++ /dev/null
@@ -1,1133 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
-import colorsys
-import logging
-import math
-import numpy as np
-from enum import Enum, unique
-import cv2
-import matplotlib as mpl
-import matplotlib.colors as mplc
-import matplotlib.figure as mplfigure
-import pycocotools.mask as mask_util
-import torch
-from matplotlib.backends.backend_agg import FigureCanvasAgg
-
-from detectron2.structures import BitMasks, Boxes, BoxMode, Keypoints, PolygonMasks, RotatedBoxes
-
-from .colormap import random_color
-
-logger = logging.getLogger(__name__)
-
-__all__ = ["ColorMode", "VisImage", "Visualizer"]
-
-
-_SMALL_OBJECT_AREA_THRESH = 1000
-_LARGE_MASK_AREA_THRESH = 120000
-_OFF_WHITE = (1.0, 1.0, 240.0 / 255)
-_BLACK = (0, 0, 0)
-_RED = (1.0, 0, 0)
-
-_KEYPOINT_THRESHOLD = 0.05
-
-
-@unique
-class ColorMode(Enum):
-    """
-    Enum of different color modes to use for instance visualizations.
-
-    Attributes:
-        IMAGE: Picks a random color for every instance and overlay segmentations with low opacity.
-        SEGMENTATION: Let instances of the same category have similar colors
-            (from metadata.thing_colors), and overlay them with
-            high opacity. This provides more attention on the quality of segmentation.
-        IMAGE_BW: same as IMAGE, but convert all areas without masks to gray-scale.
-            Only available for drawing per-instance mask predictions.
-    """
-
-    IMAGE = 0
-    SEGMENTATION = 1
-    IMAGE_BW = 2
-
-
-class GenericMask:
-    """
-    Attribute:
-        polygons (list[ndarray]): list[ndarray]: polygons for this mask.
-            Each ndarray has format [x, y, x, y, ...]
-        mask (ndarray): a binary mask
-    """
-
-    def __init__(self, mask_or_polygons, height, width):
-        self._mask = self._polygons = self._has_holes = None
-        self.height = height
-        self.width = width
-
-        m = mask_or_polygons
-        if isinstance(m, dict):
-            # RLEs
-            assert "counts" in m and "size" in m
-            if isinstance(m["counts"], list):  # uncompressed RLEs
-                h, w = m["size"]
-                assert h == height and w == width
-                m = mask_util.frPyObjects(m, h, w)
-            self._mask = mask_util.decode(m)[:, :]
-            return
-
-        if isinstance(m, list):  # list[ndarray]
-            self._polygons = [np.asarray(x).reshape(-1) for x in m]
-            return
-
-        if isinstance(m, np.ndarray):  # assumed to be a binary mask
-            assert m.shape[1] != 2, m.shape
-            assert m.shape == (height, width), m.shape
-            self._mask = m.astype("uint8")
-            return
-
-        raise ValueError("GenericMask cannot handle object {} of type '{}'".format(m, type(m)))
-
-    @property
-    def mask(self):
-        if self._mask is None:
-            self._mask = self.polygons_to_mask(self._polygons)
-        return self._mask
-
-    @property
-    def polygons(self):
-        if self._polygons is None:
-            self._polygons, self._has_holes = self.mask_to_polygons(self._mask)
-        return self._polygons
-
-    @property
-    def has_holes(self):
-        if self._has_holes is None:
-            if self._mask is not None:
-                self._polygons, self._has_holes = self.mask_to_polygons(self._mask)
-            else:
-                self._has_holes = False  # if original format is polygon, does not have holes
-        return self._has_holes
-
-    def mask_to_polygons(self, mask):
-        # cv2.RETR_CCOMP flag retrieves all the contours and arranges them to a 2-level
-        # hierarchy. External contours (boundary) of the object are placed in hierarchy-1.
-        # Internal contours (holes) are placed in hierarchy-2.
-        # cv2.CHAIN_APPROX_NONE flag gets vertices of polygons from contours.
-        mask = np.ascontiguousarray(mask)  # some versions of cv2 does not support incontiguous arr
-        res = cv2.findContours(mask.astype("uint8"), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
-        hierarchy = res[-1]
-        if hierarchy is None:  # empty mask
-            return [], False
-        has_holes = (hierarchy.reshape(-1, 4)[:, 3] >= 0).sum() > 0
-        res = res[-2]
-        res = [x.flatten() for x in res]
-        res = [x for x in res if len(x) >= 6]
-        return res, has_holes
-
-    def polygons_to_mask(self, polygons):
-        rle = mask_util.frPyObjects(polygons, self.height, self.width)
-        rle = mask_util.merge(rle)
-        return mask_util.decode(rle)[:, :]
-
-    def area(self):
-        return self.mask.sum()
-
-    def bbox(self):
-        p = mask_util.frPyObjects(self.polygons, self.height, self.width)
-        p = mask_util.merge(p)
-        bbox = mask_util.toBbox(p)
-        bbox[2] += bbox[0]
-        bbox[3] += bbox[1]
-        return bbox
-
-
-class _PanopticPrediction:
-    def __init__(self, panoptic_seg, segments_info):
-        self._seg = panoptic_seg
-
-        self._sinfo = {s["id"]: s for s in segments_info}  # seg id -> seg info
-        segment_ids, areas = torch.unique(panoptic_seg, sorted=True, return_counts=True)
-        areas = areas.numpy()
-        sorted_idxs = np.argsort(-areas)
-        self._seg_ids, self._seg_areas = segment_ids[sorted_idxs], areas[sorted_idxs]
-        self._seg_ids = self._seg_ids.tolist()
-        for sid, area in zip(self._seg_ids, self._seg_areas):
-            if sid in self._sinfo:
-                self._sinfo[sid]["area"] = float(area)
-
-    def non_empty_mask(self):
-        """
-        Returns:
-            (H, W) array, a mask for all pixels that have a prediction
-        """
-        empty_ids = []
-        for id in self._seg_ids:
-            if id not in self._sinfo:
-                empty_ids.append(id)
-        if len(empty_ids) == 0:
-            return np.zeros(self._seg.shape, dtype=np.uint8)
-        assert (
-            len(empty_ids) == 1
-        ), ">1 ids corresponds to no labels. This is currently not supported"
-        return (self._seg != empty_ids[0]).numpy().astype(np.bool)
-
-    def semantic_masks(self):
-        for sid in self._seg_ids:
-            sinfo = self._sinfo.get(sid)
-            if sinfo is None or sinfo["isthing"]:
-                # Some pixels (e.g. id 0 in PanopticFPN) have no instance or semantic predictions.
-                continue
-            yield (self._seg == sid).numpy().astype(np.bool), sinfo
-
-    def instance_masks(self):
-        for sid in self._seg_ids:
-            sinfo = self._sinfo.get(sid)
-            if sinfo is None or not sinfo["isthing"]:
-                continue
-            mask = (self._seg == sid).numpy().astype(np.bool)
-            if mask.sum() > 0:
-                yield mask, sinfo
-
-
-def _create_text_labels(classes, scores, class_names):
-    """
-    Args:
-        classes (list[int] or None):
-        scores (list[float] or None):
-        class_names (list[str] or None):
-
-    Returns:
-        list[str] or None
-    """
-    labels = None
-    if classes is not None and class_names is not None and len(class_names) > 1:
-        labels = [class_names[i] for i in classes]
-    if scores is not None:
-        if labels is None:
-            labels = ["{:.0f}%".format(s * 100) for s in scores]
-        else:
-            labels = ["{} {:.0f}%".format(l, s * 100) for l, s in zip(labels, scores)]
-    return labels
-
-
-class VisImage:
-    def __init__(self, img, scale=1.0):
-        """
-        Args:
-            img (ndarray): an RGB image of shape (H, W, 3).
-            scale (float): scale the input image
-        """
-        self.img = img
-        self.scale = scale
-        self.width, self.height = img.shape[1], img.shape[0]
-        self._setup_figure(img)
-
-    def _setup_figure(self, img):
-        """
-        Args:
-            Same as in :meth:`__init__()`.
-
-        Returns:
-            fig (matplotlib.pyplot.figure): top level container for all the image plot elements.
-            ax (matplotlib.pyplot.Axes): contains figure elements and sets the coordinate system.
-        """
-        fig = mplfigure.Figure(frameon=False)
-        self.dpi = fig.get_dpi()
-        # add a small 1e-2 to avoid precision lost due to matplotlib's truncation
-        # (https://github.com/matplotlib/matplotlib/issues/15363)
-        fig.set_size_inches(
-            (self.width * self.scale + 1e-2) / self.dpi,
-            (self.height * self.scale + 1e-2) / self.dpi,
-        )
-        self.canvas = FigureCanvasAgg(fig)
-        # self.canvas = mpl.backends.backend_cairo.FigureCanvasCairo(fig)
-        ax = fig.add_axes([0.0, 0.0, 1.0, 1.0])
-        ax.axis("off")
-        ax.set_xlim(0.0, self.width)
-        ax.set_ylim(self.height)
-
-        self.fig = fig
-        self.ax = ax
-
-    def save(self, filepath):
-        """
-        Args:
-            filepath (str): a string that contains the absolute path, including the file name, where
-                the visualized image will be saved.
-        """
-        if filepath.lower().endswith(".jpg") or filepath.lower().endswith(".png"):
-            # faster than matplotlib's imshow
-            cv2.imwrite(filepath, self.get_image()[:, :, ::-1])
-        else:
-            # support general formats (e.g. pdf)
-            self.ax.imshow(self.img, interpolation="nearest")
-            self.fig.savefig(filepath)
-
-    def get_image(self):
-        """
-        Returns:
-            ndarray: the visualized image of shape (H, W, 3) (RGB) in uint8 type.
-              The shape is scaled w.r.t the input image using the given `scale` argument.
-        """
-        canvas = self.canvas
-        s, (width, height) = canvas.print_to_buffer()
-        if (self.width, self.height) != (width, height):
-            img = cv2.resize(self.img, (width, height))
-        else:
-            img = self.img
-
-        # buf = io.BytesIO()  # works for cairo backend
-        # canvas.print_rgba(buf)
-        # width, height = self.width, self.height
-        # s = buf.getvalue()
-
-        buffer = np.frombuffer(s, dtype="uint8")
-
-        # imshow is slow. blend manually (still quite slow)
-        img_rgba = buffer.reshape(height, width, 4)
-        rgb, alpha = np.split(img_rgba, [3], axis=2)
-
-        try:
-            import numexpr as ne  # fuse them with numexpr
-
-            visualized_image = ne.evaluate("img * (1 - alpha / 255.0) + rgb * (alpha / 255.0)")
-        except ImportError:
-            alpha = alpha.astype("float32") / 255.0
-            visualized_image = img * (1 - alpha) + rgb * alpha
-
-        visualized_image = visualized_image.astype("uint8")
-
-        return visualized_image
-
-
-class Visualizer:
-    def __init__(self, img_rgb, metadata, scale=1.0, instance_mode=ColorMode.IMAGE):
-        """
-        Args:
-            img_rgb: a numpy array of shape (H, W, C), where H and W correspond to
-                the height and width of the image respectively. C is the number of
-                color channels. The image is required to be in RGB format since that
-                is a requirement of the Matplotlib library. The image is also expected
-                to be in the range [0, 255].
-            metadata (MetadataCatalog): image metadata.
-        """
-        self.img = np.asarray(img_rgb).clip(0, 255).astype(np.uint8)
-        self.metadata = metadata
-        self.output = VisImage(self.img, scale=scale)
-        self.cpu_device = torch.device("cpu")
-
-        # too small texts are useless, therefore clamp to 9
-        self._default_font_size = max(
-            np.sqrt(self.output.height * self.output.width) // 90, 10 // scale
-        )
-        self._instance_mode = instance_mode
-
-    def draw_instance_predictions(self, predictions):
-        """
-        Draw instance-level prediction results on an image.
-
-        Args:
-            predictions (Instances): the output of an instance detection/segmentation
-                model. Following fields will be used to draw:
-                "pred_boxes", "pred_classes", "scores", "pred_masks" (or "pred_masks_rle").
-
-        Returns:
-            output (VisImage): image object with visualizations.
-        """
-        boxes = predictions.pred_boxes if predictions.has("pred_boxes") else None
-        scores = predictions.scores if predictions.has("scores") else None
-        classes = predictions.pred_classes if predictions.has("pred_classes") else None
-        labels = _create_text_labels(classes, scores, self.metadata.get("thing_classes", None))
-        keypoints = predictions.pred_keypoints if predictions.has("pred_keypoints") else None
-
-        if predictions.has("pred_masks"):
-            masks = np.asarray(predictions.pred_masks)
-            masks = [GenericMask(x, self.output.height, self.output.width) for x in masks]
-        else:
-            masks = None
-
-        if self._instance_mode == ColorMode.SEGMENTATION and self.metadata.get("thing_colors"):
-            colors = [
-                self._jitter([x / 255 for x in self.metadata.thing_colors[c]]) for c in classes
-            ]
-            alpha = 0.8
-        else:
-            colors = None
-            alpha = 0.5
-
-        if self._instance_mode == ColorMode.IMAGE_BW:
-            assert predictions.has("pred_masks"), "ColorMode.IMAGE_BW requires segmentations"
-            self.output.img = self._create_grayscale_image(
-                (predictions.pred_masks.any(dim=0) > 0).numpy()
-            )
-            alpha = 0.3
-
-        self.overlay_instances(
-            masks=masks,
-            boxes=boxes,
-            labels=labels,
-            keypoints=keypoints,
-            assigned_colors=colors,
-            alpha=alpha,
-        )
-        return self.output
-
-    def draw_sem_seg(self, sem_seg, area_threshold=None, alpha=0.8):
-        """
-        Draw semantic segmentation predictions/labels.
-
-        Args:
-            sem_seg (Tensor or ndarray): the segmentation of shape (H, W).
-            area_threshold (int): segments with less than `area_threshold` are not drawn.
-            alpha (float): the larger it is, the more opaque the segmentations are.
-
-        Returns:
-            output (VisImage): image object with visualizations.
-        """
-        if isinstance(sem_seg, torch.Tensor):
-            sem_seg = sem_seg.numpy()
-        labels, areas = np.unique(sem_seg, return_counts=True)
-        sorted_idxs = np.argsort(-areas).tolist()
-        labels = labels[sorted_idxs]
-        for label in filter(lambda l: l < len(self.metadata.stuff_classes), labels):
-            try:
-                mask_color = [x / 255 for x in self.metadata.stuff_colors[label]]
-            except (AttributeError, IndexError):
-                mask_color = None
-
-            binary_mask = (sem_seg == label).astype(np.uint8)
-            text = self.metadata.stuff_classes[label]
-            self.draw_binary_mask(
-                binary_mask,
-                color=mask_color,
-                edge_color=_OFF_WHITE,
-                text=text,
-                alpha=alpha,
-                area_threshold=area_threshold,
-            )
-        return self.output
-
-    def draw_panoptic_seg_predictions(
-        self, panoptic_seg, segments_info, area_threshold=None, alpha=0.7
-    ):
-        """
-        Draw panoptic prediction results on an image.
-
-        Args:
-            panoptic_seg (Tensor): of shape (height, width) where the values are ids for each
-                segment.
-            segments_info (list[dict]): Describe each segment in `panoptic_seg`.
-                Each dict contains keys "id", "category_id", "isthing".
-            area_threshold (int): stuff segments with less than `area_threshold` are not drawn.
-
-        Returns:
-            output (VisImage): image object with visualizations.
-        """
-        pred = _PanopticPrediction(panoptic_seg, segments_info)
-
-        if self._instance_mode == ColorMode.IMAGE_BW:
-            self.output.img = self._create_grayscale_image(pred.non_empty_mask())
-
-        # draw mask for all semantic segments first i.e. "stuff"
-        for mask, sinfo in pred.semantic_masks():
-            category_idx = sinfo["category_id"]
-            try:
-                mask_color = [x / 255 for x in self.metadata.stuff_colors[category_idx]]
-            except AttributeError:
-                mask_color = None
-
-            text = self.metadata.stuff_classes[category_idx]
-            self.draw_binary_mask(
-                mask,
-                color=mask_color,
-                edge_color=_OFF_WHITE,
-                text=text,
-                alpha=alpha,
-                area_threshold=area_threshold,
-            )
-
-        # draw mask for all instances second
-        all_instances = list(pred.instance_masks())
-        if len(all_instances) == 0:
-            return self.output
-        masks, sinfo = list(zip(*all_instances))
-        category_ids = [x["category_id"] for x in sinfo]
-
-        try:
-            scores = [x["score"] for x in sinfo]
-        except KeyError:
-            scores = None
-        labels = _create_text_labels(category_ids, scores, self.metadata.thing_classes)
-
-        try:
-            colors = [random_color(rgb=True, maximum=1) for k in category_ids]
-        except AttributeError:
-            colors = None
-        self.overlay_instances(masks=masks, labels=labels, assigned_colors=colors, alpha=alpha)
-
-        return self.output
-
-    def draw_dataset_dict(self, dic):
-        """
-        Draw annotations/segmentaions in Detectron2 Dataset format.
-
-        Args:
-            dic (dict): annotation/segmentation data of one image, in Detectron2 Dataset format.
-
-        Returns:
-            output (VisImage): image object with visualizations.
-        """
-        annos = dic.get("annotations", None)
-        if annos:
-            if "segmentation" in annos[0]:
-                masks = [x["segmentation"] for x in annos]
-            else:
-                masks = None
-            if "keypoints" in annos[0]:
-                keypts = [x["keypoints"] for x in annos]
-                keypts = np.array(keypts).reshape(len(annos), -1, 3)
-            else:
-                keypts = None
-
-            boxes = [BoxMode.convert(x["bbox"], x["bbox_mode"], BoxMode.XYXY_ABS) for x in annos]
-
-            labels = [x["category_id"] for x in annos]
-            colors = None
-            if self._instance_mode == ColorMode.SEGMENTATION and self.metadata.get("thing_colors"):
-                colors = [
-                    self._jitter([x / 255 for x in self.metadata.thing_colors[c]]) for c in labels
-                ]
-            names = self.metadata.get("thing_classes", None)
-            if names:
-                labels = [names[i] for i in labels]
-            labels = [
-                "{}".format(i) + ("|crowd" if a.get("iscrowd", 0) else "")
-                for i, a in zip(labels, annos)
-            ]
-            self.overlay_instances(
-                labels=labels, boxes=boxes, masks=masks, keypoints=keypts, assigned_colors=colors
-            )
-
-        sem_seg = dic.get("sem_seg", None)
-        if sem_seg is None and "sem_seg_file_name" in dic:
-            sem_seg = cv2.imread(dic["sem_seg_file_name"], cv2.IMREAD_GRAYSCALE)
-        if sem_seg is not None:
-            self.draw_sem_seg(sem_seg, area_threshold=0, alpha=0.5)
-        return self.output
-
-    def overlay_instances(
-        self,
-        *,
-        boxes=None,
-        labels=None,
-        masks=None,
-        keypoints=None,
-        assigned_colors=None,
-        alpha=0.5
-    ):
-        """
-        Args:
-            boxes (Boxes, RotatedBoxes or ndarray): either a :class:`Boxes`,
-                or an Nx4 numpy array of XYXY_ABS format for the N objects in a single image,
-                or a :class:`RotatedBoxes`,
-                or an Nx5 numpy array of (x_center, y_center, width, height, angle_degrees) format
-                for the N objects in a single image,
-            labels (list[str]): the text to be displayed for each instance.
-            masks (masks-like object): Supported types are:
-
-                * `structures.masks.PolygonMasks`, `structures.masks.BitMasks`.
-                * list[list[ndarray]]: contains the segmentation masks for all objects in one image.
-                    The first level of the list corresponds to individual instances. The second
-                    level to all the polygon that compose the instance, and the third level
-                    to the polygon coordinates. The third level should have the format of
-                    [x0, y0, x1, y1, ..., xn, yn] (n >= 3).
-                * list[ndarray]: each ndarray is a binary mask of shape (H, W).
-                * list[dict]: each dict is a COCO-style RLE.
-            keypoints (Keypoint or array like): an array-like object of shape (N, K, 3),
-                where the N is the number of instances and K is the number of keypoints.
-                The last dimension corresponds to (x, y, visibility or score).
-            assigned_colors (list[matplotlib.colors]): a list of colors, where each color
-                corresponds to each mask or box in the image. Refer to 'matplotlib.colors'
-                for full list of formats that the colors are accepted in.
-
-        Returns:
-            output (VisImage): image object with visualizations.
-        """
-        num_instances = None
-        if boxes is not None:
-            boxes = self._convert_boxes(boxes)
-            num_instances = len(boxes)
-        if masks is not None:
-            masks = self._convert_masks(masks)
-            if num_instances:
-                assert len(masks) == num_instances
-            else:
-                num_instances = len(masks)
-        if keypoints is not None:
-            if num_instances:
-                assert len(keypoints) == num_instances
-            else:
-                num_instances = len(keypoints)
-            keypoints = self._convert_keypoints(keypoints)
-        if labels is not None:
-            assert len(labels) == num_instances
-        if assigned_colors is None:
-            assigned_colors = [random_color(rgb=True, maximum=1) for _ in range(num_instances)]
-        if num_instances == 0:
-            return self.output
-        if boxes is not None and boxes.shape[1] == 5:
-            return self.overlay_rotated_instances(
-                boxes=boxes, labels=labels, assigned_colors=assigned_colors
-            )
-
-        # Display in largest to smallest order to reduce occlusion.
-        areas = None
-        if boxes is not None:
-            areas = np.prod(boxes[:, 2:] - boxes[:, :2], axis=1)
-        elif masks is not None:
-            areas = np.asarray([x.area() for x in masks])
-
-        if areas is not None:
-            sorted_idxs = np.argsort(-areas).tolist()
-            # Re-order overlapped instances in descending order.
-            boxes = boxes[sorted_idxs] if boxes is not None else None
-            labels = [labels[k] for k in sorted_idxs] if labels is not None else None
-            masks = [masks[idx] for idx in sorted_idxs] if masks is not None else None
-            assigned_colors = [assigned_colors[idx] for idx in sorted_idxs]
-            keypoints = keypoints[sorted_idxs] if keypoints is not None else None
-
-        for i in range(num_instances):
-            color = assigned_colors[i]
-            if boxes is not None:
-                self.draw_box(boxes[i], edge_color=color)
-
-            if masks is not None:
-                for segment in masks[i].polygons:
-                    self.draw_polygon(segment.reshape(-1, 2), color, alpha=alpha)
-
-            if labels is not None:
-                # first get a box
-                if boxes is not None:
-                    x0, y0, x1, y1 = boxes[i]
-                    text_pos = (x0, y0)  # if drawing boxes, put text on the box corner.
-                    horiz_align = "left"
-                elif masks is not None:
-                    x0, y0, x1, y1 = masks[i].bbox()
-
-                    # draw text in the center (defined by median) when box is not drawn
-                    # median is less sensitive to outliers.
-                    text_pos = np.median(masks[i].mask.nonzero(), axis=1)[::-1]
-                    horiz_align = "center"
-                else:
-                    continue  # drawing the box confidence for keypoints isn't very useful.
-                # for small objects, draw text at the side to avoid occlusion
-                instance_area = (y1 - y0) * (x1 - x0)
-                if (
-                    instance_area < _SMALL_OBJECT_AREA_THRESH * self.output.scale
-                    or y1 - y0 < 40 * self.output.scale
-                ):
-                    if y1 >= self.output.height - 5:
-                        text_pos = (x1, y0)
-                    else:
-                        text_pos = (x0, y1)
-
-                height_ratio = (y1 - y0) / np.sqrt(self.output.height * self.output.width)
-                lighter_color = self._change_color_brightness(color, brightness_factor=0.7)
-                font_size = (
-                    np.clip((height_ratio - 0.02) / 0.08 + 1, 1.2, 2)
-                    * 0.5
-                    * self._default_font_size
-                )
-                self.draw_text(
-                    labels[i],
-                    text_pos,
-                    color=lighter_color,
-                    horizontal_alignment=horiz_align,
-                    font_size=font_size,
-                )
-
-        # draw keypoints
-        if keypoints is not None:
-            for keypoints_per_instance in keypoints:
-                self.draw_and_connect_keypoints(keypoints_per_instance)
-
-        return self.output
-
-    def overlay_rotated_instances(self, boxes=None, labels=None, assigned_colors=None):
-        """
-        Args:
-            boxes (ndarray): an Nx5 numpy array of
-                (x_center, y_center, width, height, angle_degrees) format
-                for the N objects in a single image.
-            labels (list[str]): the text to be displayed for each instance.
-            assigned_colors (list[matplotlib.colors]): a list of colors, where each color
-                corresponds to each mask or box in the image. Refer to 'matplotlib.colors'
-                for full list of formats that the colors are accepted in.
-
-        Returns:
-            output (VisImage): image object with visualizations.
-        """
-
-        num_instances = len(boxes)
-
-        if assigned_colors is None:
-            assigned_colors = [random_color(rgb=True, maximum=1) for _ in range(num_instances)]
-        if num_instances == 0:
-            return self.output
-
-        # Display in largest to smallest order to reduce occlusion.
-        if boxes is not None:
-            areas = boxes[:, 2] * boxes[:, 3]
-
-        sorted_idxs = np.argsort(-areas).tolist()
-        # Re-order overlapped instances in descending order.
-        boxes = boxes[sorted_idxs]
-        labels = [labels[k] for k in sorted_idxs] if labels is not None else None
-        colors = [assigned_colors[idx] for idx in sorted_idxs]
-
-        for i in range(num_instances):
-            self.draw_rotated_box_with_label(
-                boxes[i], edge_color=colors[i], label=labels[i] if labels is not None else None
-            )
-
-        return self.output
-
-    def draw_and_connect_keypoints(self, keypoints):
-        """
-        Draws keypoints of an instance and follows the rules for keypoint connections
-        to draw lines between appropriate keypoints. This follows color heuristics for
-        line color.
-
-        Args:
-            keypoints (Tensor): a tensor of shape (K, 3), where K is the number of keypoints
-                and the last dimension corresponds to (x, y, probability).
-
-        Returns:
-            output (VisImage): image object with visualizations.
-        """
-        visible = {}
-        keypoint_names = self.metadata.get("keypoint_names")
-        for idx, keypoint in enumerate(keypoints):
-            # draw keypoint
-            x, y, prob = keypoint
-            if prob > _KEYPOINT_THRESHOLD:
-                self.draw_circle((x, y), color=_RED)
-                if keypoint_names:
-                    keypoint_name = keypoint_names[idx]
-                    visible[keypoint_name] = (x, y)
-
-        if self.metadata.get("keypoint_connection_rules"):
-            for kp0, kp1, color in self.metadata.keypoint_connection_rules:
-                if kp0 in visible and kp1 in visible:
-                    x0, y0 = visible[kp0]
-                    x1, y1 = visible[kp1]
-                    color = tuple(x / 255.0 for x in color)
-                    self.draw_line([x0, x1], [y0, y1], color=color)
-
-        # draw lines from nose to mid-shoulder and mid-shoulder to mid-hip
-        # Note that this strategy is specific to person keypoints.
-        # For other keypoints, it should just do nothing
-        try:
-            ls_x, ls_y = visible["left_shoulder"]
-            rs_x, rs_y = visible["right_shoulder"]
-            mid_shoulder_x, mid_shoulder_y = (ls_x + rs_x) / 2, (ls_y + rs_y) / 2
-        except KeyError:
-            pass
-        else:
-            # draw line from nose to mid-shoulder
-            nose_x, nose_y = visible.get("nose", (None, None))
-            if nose_x is not None:
-                self.draw_line([nose_x, mid_shoulder_x], [nose_y, mid_shoulder_y], color=_RED)
-
-            try:
-                # draw line from mid-shoulder to mid-hip
-                lh_x, lh_y = visible["left_hip"]
-                rh_x, rh_y = visible["right_hip"]
-            except KeyError:
-                pass
-            else:
-                mid_hip_x, mid_hip_y = (lh_x + rh_x) / 2, (lh_y + rh_y) / 2
-                self.draw_line([mid_hip_x, mid_shoulder_x], [mid_hip_y, mid_shoulder_y], color=_RED)
-        return self.output
-
-    """
-    Primitive drawing functions:
-    """
-
-    def draw_text(
-        self,
-        text,
-        position,
-        *,
-        font_size=None,
-        color="g",
-        horizontal_alignment="center",
-        rotation=0
-    ):
-        """
-        Args:
-            text (str): class label
-            position (tuple): a tuple of the x and y coordinates to place text on image.
-            font_size (int, optional): font of the text. If not provided, a font size
-                proportional to the image width is calculated and used.
-            color: color of the text. Refer to `matplotlib.colors` for full list
-                of formats that are accepted.
-            horizontal_alignment (str): see `matplotlib.text.Text`
-            rotation: rotation angle in degrees CCW
-
-        Returns:
-            output (VisImage): image object with text drawn.
-        """
-        if not font_size:
-            font_size = self._default_font_size
-
-        # since the text background is dark, we don't want the text to be dark
-        color = np.maximum(list(mplc.to_rgb(color)), 0.2)
-        color[np.argmax(color)] = max(0.8, np.max(color))
-
-        x, y = position
-        self.output.ax.text(
-            x,
-            y,
-            text,
-            size=font_size * self.output.scale,
-            family="sans-serif",
-            bbox={"facecolor": "black", "alpha": 0.8, "pad": 0.7, "edgecolor": "none"},
-            verticalalignment="top",
-            horizontalalignment=horizontal_alignment,
-            color=color,
-            zorder=10,
-            rotation=rotation,
-        )
-        return self.output
-
-    def draw_box(self, box_coord, alpha=0.5, edge_color="g", line_style="-"):
-        """
-        Args:
-            box_coord (tuple): a tuple containing x0, y0, x1, y1 coordinates, where x0 and y0
-                are the coordinates of the image's top left corner. x1 and y1 are the
-                coordinates of the image's bottom right corner.
-            alpha (float): blending efficient. Smaller values lead to more transparent masks.
-            edge_color: color of the outline of the box. Refer to `matplotlib.colors`
-                for full list of formats that are accepted.
-            line_style (string): the string to use to create the outline of the boxes.
-
-        Returns:
-            output (VisImage): image object with box drawn.
-        """
-        x0, y0, x1, y1 = box_coord
-        width = x1 - x0
-        height = y1 - y0
-
-        linewidth = max(self._default_font_size / 4, 1)
-
-        self.output.ax.add_patch(
-            mpl.patches.Rectangle(
-                (x0, y0),
-                width,
-                height,
-                fill=False,
-                edgecolor=edge_color,
-                linewidth=linewidth * self.output.scale,
-                alpha=alpha,
-                linestyle=line_style,
-            )
-        )
-        return self.output
-
-    def draw_rotated_box_with_label(
-        self, rotated_box, alpha=0.5, edge_color="g", line_style="-", label=None
-    ):
-        """
-        Args:
-            rotated_box (tuple): a tuple containing (cnt_x, cnt_y, w, h, angle),
-                where cnt_x and cnt_y are the center coordinates of the box.
-                w and h are the width and height of the box. angle represents how
-                many degrees the box is rotated CCW with regard to the 0-degree box.
-            alpha (float): blending efficient. Smaller values lead to more transparent masks.
-            edge_color: color of the outline of the box. Refer to `matplotlib.colors`
-                for full list of formats that are accepted.
-            line_style (string): the string to use to create the outline of the boxes.
-            label (string): label for rotated box. It will not be rendered when set to None.
-
-        Returns:
-            output (VisImage): image object with box drawn.
-        """
-        cnt_x, cnt_y, w, h, angle = rotated_box
-        area = w * h
-        # use thinner lines when the box is small
-        linewidth = self._default_font_size / (
-            6 if area < _SMALL_OBJECT_AREA_THRESH * self.output.scale else 3
-        )
-
-        theta = angle * math.pi / 180.0
-        c = math.cos(theta)
-        s = math.sin(theta)
-        rect = [(-w / 2, h / 2), (-w / 2, -h / 2), (w / 2, -h / 2), (w / 2, h / 2)]
-        # x: left->right ; y: top->down
-        rotated_rect = [(s * yy + c * xx + cnt_x, c * yy - s * xx + cnt_y) for (xx, yy) in rect]
-        for k in range(4):
-            j = (k + 1) % 4
-            self.draw_line(
-                [rotated_rect[k][0], rotated_rect[j][0]],
-                [rotated_rect[k][1], rotated_rect[j][1]],
-                color=edge_color,
-                linestyle="--" if k == 1 else line_style,
-                linewidth=linewidth,
-            )
-
-        if label is not None:
-            text_pos = rotated_rect[1]  # topleft corner
-
-            height_ratio = h / np.sqrt(self.output.height * self.output.width)
-            label_color = self._change_color_brightness(edge_color, brightness_factor=0.7)
-            font_size = (
-                np.clip((height_ratio - 0.02) / 0.08 + 1, 1.2, 2) * 0.5 * self._default_font_size
-            )
-            self.draw_text(label, text_pos, color=label_color, font_size=font_size, rotation=angle)
-
-        return self.output
-
-    def draw_circle(self, circle_coord, color, radius=3):
-        """
-        Args:
-            circle_coord (list(int) or tuple(int)): contains the x and y coordinates
-                of the center of the circle.
-            color: color of the polygon. Refer to `matplotlib.colors` for a full list of
-                formats that are accepted.
-            radius (int): radius of the circle.
-
-        Returns:
-            output (VisImage): image object with box drawn.
-        """
-        x, y = circle_coord
-        self.output.ax.add_patch(
-            mpl.patches.Circle(circle_coord, radius=radius, fill=True, color=color)
-        )
-        return self.output
-
-    def draw_line(self, x_data, y_data, color, linestyle="-", linewidth=None):
-        """
-        Args:
-            x_data (list[int]): a list containing x values of all the points being drawn.
-                Length of list should match the length of y_data.
-            y_data (list[int]): a list containing y values of all the points being drawn.
-                Length of list should match the length of x_data.
-            color: color of the line. Refer to `matplotlib.colors` for a full list of
-                formats that are accepted.
-            linestyle: style of the line. Refer to `matplotlib.lines.Line2D`
-                for a full list of formats that are accepted.
-            linewidth (float or None): width of the line. When it's None,
-                a default value will be computed and used.
-
-        Returns:
-            output (VisImage): image object with line drawn.
-        """
-        if linewidth is None:
-            linewidth = self._default_font_size / 3
-        linewidth = max(linewidth, 1)
-        self.output.ax.add_line(
-            mpl.lines.Line2D(
-                x_data,
-                y_data,
-                linewidth=linewidth * self.output.scale,
-                color=color,
-                linestyle=linestyle,
-            )
-        )
-        return self.output
-
-    def draw_binary_mask(
-        self, binary_mask, color=None, *, edge_color=None, text=None, alpha=0.5, area_threshold=4096
-    ):
-        """
-        Args:
-            binary_mask (ndarray): numpy array of shape (H, W), where H is the image height and
-                W is the image width. Each value in the array is either a 0 or 1 value of uint8
-                type.
-            color: color of the mask. Refer to `matplotlib.colors` for a full list of
-                formats that are accepted. If None, will pick a random color.
-            edge_color: color of the polygon edges. Refer to `matplotlib.colors` for a
-                full list of formats that are accepted.
-            text (str): if None, will be drawn in the object's center of mass.
-            alpha (float): blending efficient. Smaller values lead to more transparent masks.
-            area_threshold (float): a connected component small than this will not be shown.
-
-        Returns:
-            output (VisImage): image object with mask drawn.
-        """
-        if color is None:
-            color = random_color(rgb=True, maximum=1)
-        if area_threshold is None:
-            area_threshold = 4096
-
-        has_valid_segment = False
-        binary_mask = binary_mask.astype("uint8")  # opencv needs uint8
-        mask = GenericMask(binary_mask, self.output.height, self.output.width)
-        shape2d = (binary_mask.shape[0], binary_mask.shape[1])
-
-        if not mask.has_holes:
-            # draw polygons for regular masks
-            for segment in mask.polygons:
-                area = mask_util.area(mask_util.frPyObjects([segment], shape2d[0], shape2d[1]))
-                if area < area_threshold:
-                    continue
-                has_valid_segment = True
-                segment = segment.reshape(-1, 2)
-                self.draw_polygon(segment, color=color, edge_color=edge_color, alpha=alpha)
-        else:
-            rgba = np.zeros(shape2d + (4,), dtype="float32")
-            rgba[:, :, :3] = color
-            rgba[:, :, 3] = (mask.mask == 1).astype("float32") * alpha
-            has_valid_segment = True
-            self.output.ax.imshow(rgba)
-
-        if text is not None and has_valid_segment:
-            # TODO sometimes drawn on wrong objects. the heuristics here can improve.
-            lighter_color = self._change_color_brightness(color, brightness_factor=0.7)
-            _num_cc, cc_labels, stats, centroids = cv2.connectedComponentsWithStats(binary_mask, 8)
-            largest_component_id = np.argmax(stats[1:, -1]) + 1
-
-            # draw text on the largest component, as well as other very large components.
-            for cid in range(1, _num_cc):
-                if cid == largest_component_id or stats[cid, -1] > _LARGE_MASK_AREA_THRESH:
-                    # median is more stable than centroid
-                    # center = centroids[largest_component_id]
-                    center = np.median((cc_labels == cid).nonzero(), axis=1)[::-1]
-                    self.draw_text(text, center, color=lighter_color)
-        return self.output
-
-    def draw_polygon(self, segment, color, edge_color=None, alpha=0.5):
-        """
-        Args:
-            segment: numpy array of shape Nx2, containing all the points in the polygon.
-            color: color of the polygon. Refer to `matplotlib.colors` for a full list of
-                formats that are accepted.
-            edge_color: color of the polygon edges. Refer to `matplotlib.colors` for a
-                full list of formats that are accepted. If not provided, a darker shade
-                of the polygon color will be used instead.
-            alpha (float): blending efficient. Smaller values lead to more transparent masks.
-
-        Returns:
-            output (VisImage): image object with polygon drawn.
-        """
-        if edge_color is None:
-            # make edge color darker than the polygon color
-            if alpha > 0.8:
-                edge_color = self._change_color_brightness(color, brightness_factor=-0.7)
-            else:
-                edge_color = color
-        edge_color = mplc.to_rgb(edge_color) + (1,)
-
-        polygon = mpl.patches.Polygon(
-            segment,
-            fill=True,
-            facecolor=mplc.to_rgb(color) + (alpha,),
-            edgecolor=edge_color,
-            linewidth=max(self._default_font_size // 15 * self.output.scale, 1),
-        )
-        self.output.ax.add_patch(polygon)
-        return self.output
-
-    """
-    Internal methods:
-    """
-
-    def _jitter(self, color):
-        """
-        Randomly modifies given color to produce a slightly different color than the color given.
-
-        Args:
-            color (tuple[double]): a tuple of 3 elements, containing the RGB values of the color
-                picked. The values in the list are in the [0.0, 1.0] range.
-
-        Returns:
-            jittered_color (tuple[double]): a tuple of 3 elements, containing the RGB values of the
-                color after being jittered. The values in the list are in the [0.0, 1.0] range.
-        """
-        color = mplc.to_rgb(color)
-        vec = np.random.rand(3)
-        # better to do it in another color space
-        vec = vec / np.linalg.norm(vec) * 0.5
-        res = np.clip(vec + color, 0, 1)
-        return tuple(res)
-
-    def _create_grayscale_image(self, mask=None):
-        """
-        Create a grayscale version of the original image.
-        The colors in masked area, if given, will be kept.
-        """
-        img_bw = self.img.astype("f4").mean(axis=2)
-        img_bw = np.stack([img_bw] * 3, axis=2)
-        if mask is not None:
-            img_bw[mask] = self.img[mask]
-        return img_bw
-
-    def _change_color_brightness(self, color, brightness_factor):
-        """
-        Depending on the brightness_factor, gives a lighter or darker color i.e. a color with
-        less or more saturation than the original color.
-
-        Args:
-            color: color of the polygon. Refer to `matplotlib.colors` for a full list of
-                formats that are accepted.
-            brightness_factor (float): a value in [-1.0, 1.0] range. A lightness factor of
-                0 will correspond to no change, a factor in [-1.0, 0) range will result in
-                a darker color and a factor in (0, 1.0] range will result in a lighter color.
-
-        Returns:
-            modified_color (tuple[double]): a tuple containing the RGB values of the
-                modified color. Each value in the tuple is in the [0.0, 1.0] range.
-        """
-        assert brightness_factor >= -1.0 and brightness_factor <= 1.0
-        color = mplc.to_rgb(color)
-        polygon_color = colorsys.rgb_to_hls(*mplc.to_rgb(color))
-        modified_lightness = polygon_color[1] + (brightness_factor * polygon_color[1])
-        modified_lightness = 0.0 if modified_lightness < 0.0 else modified_lightness
-        modified_lightness = 1.0 if modified_lightness > 1.0 else modified_lightness
-        modified_color = colorsys.hls_to_rgb(polygon_color[0], modified_lightness, polygon_color[2])
-        return modified_color
-
-    def _convert_boxes(self, boxes):
-        """
-        Convert different format of boxes to an NxB array, where B = 4 or 5 is the box dimension.
-        """
-        if isinstance(boxes, Boxes) or isinstance(boxes, RotatedBoxes):
-            return boxes.tensor.numpy()
-        else:
-            return np.asarray(boxes)
-
-    def _convert_masks(self, masks_or_polygons):
-        """
-        Convert different format of masks or polygons to a tuple of masks and polygons.
-
-        Returns:
-            list[GenericMask]:
-        """
-
-        m = masks_or_polygons
-        if isinstance(m, PolygonMasks):
-            m = m.polygons
-        if isinstance(m, BitMasks):
-            m = m.tensor.numpy()
-        if isinstance(m, torch.Tensor):
-            m = m.numpy()
-        ret = []
-        for x in m:
-            if isinstance(x, GenericMask):
-                ret.append(x)
-            else:
-                ret.append(GenericMask(x, self.output.height, self.output.width))
-        return ret
-
-    def _convert_keypoints(self, keypoints):
-        if isinstance(keypoints, Keypoints):
-            keypoints = keypoints.tensor
-        keypoints = np.asarray(keypoints)
-        return keypoints
-
-    def get_output(self):
-        """
-        Returns:
-            output (VisImage): the image output containing the visualizations added
-            to the image.
-        """
-        return self.output
diff --git a/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/tools/plain_train_net.py b/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/tools/plain_train_net.py
deleted file mode 100644
index e3fe1db98d097423fc42243e8ef0b505d06505ee..0000000000000000000000000000000000000000
--- a/spaces/CVPR/Dual-Key_Backdoor_Attacks/datagen/detectron2/tools/plain_train_net.py
+++ /dev/null
@@ -1,231 +0,0 @@
-#!/usr/bin/env python
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
-"""
-Detectron2 training script with a plain training loop.
-
-This scripts reads a given config file and runs the training or evaluation.
-It is an entry point that is able to train standard models in detectron2.
-
-In order to let one script support training of many models,
-this script contains logic that are specific to these built-in models and therefore
-may not be suitable for your own project.
-For example, your research project perhaps only needs a single "evaluator".
-
-Therefore, we recommend you to use detectron2 as an library and take
-this file as an example of how to use the library.
-You may want to write your own script with your datasets and other customizations.
-
-Compared to "train_net.py", this script supports fewer default features.
-It also includes fewer abstraction, therefore is easier to add custom logic.
-"""
-
-import logging
-import os
-from collections import OrderedDict
-import torch
-from torch.nn.parallel import DistributedDataParallel
-
-import detectron2.utils.comm as comm
-from detectron2.checkpoint import DetectionCheckpointer, PeriodicCheckpointer
-from detectron2.config import get_cfg
-from detectron2.data import (
-    MetadataCatalog,
-    build_detection_test_loader,
-    build_detection_train_loader,
-)
-from detectron2.engine import default_argument_parser, default_setup, launch
-from detectron2.evaluation import (
-    CityscapesEvaluator,
-    COCOEvaluator,
-    COCOPanopticEvaluator,
-    DatasetEvaluators,
-    LVISEvaluator,
-    PascalVOCDetectionEvaluator,
-    SemSegEvaluator,
-    inference_on_dataset,
-    print_csv_format,
-)
-from detectron2.modeling import build_model
-from detectron2.solver import build_lr_scheduler, build_optimizer
-from detectron2.utils.events import (
-    CommonMetricPrinter,
-    EventStorage,
-    JSONWriter,
-    TensorboardXWriter,
-)
-
-logger = logging.getLogger("detectron2")
-
-
-def get_evaluator(cfg, dataset_name, output_folder=None):
-    """
-    Create evaluator(s) for a given dataset.
-    This uses the special metadata "evaluator_type" associated with each builtin dataset.
-    For your own dataset, you can simply create an evaluator manually in your
-    script and do not have to worry about the hacky if-else logic here.
-    """
-    if output_folder is None:
-        output_folder = os.path.join(cfg.OUTPUT_DIR, "inference")
-    evaluator_list = []
-    evaluator_type = MetadataCatalog.get(dataset_name).evaluator_type
-    if evaluator_type in ["sem_seg", "coco_panoptic_seg"]:
-        evaluator_list.append(
-            SemSegEvaluator(
-                dataset_name,
-                distributed=True,
-                num_classes=cfg.MODEL.SEM_SEG_HEAD.NUM_CLASSES,
-                ignore_label=cfg.MODEL.SEM_SEG_HEAD.IGNORE_VALUE,
-                output_dir=output_folder,
-            )
-        )
-    if evaluator_type in ["coco", "coco_panoptic_seg"]:
-        evaluator_list.append(COCOEvaluator(dataset_name, cfg, True, output_folder))
-    if evaluator_type == "coco_panoptic_seg":
-        evaluator_list.append(COCOPanopticEvaluator(dataset_name, output_folder))
-    if evaluator_type == "cityscapes":
-        assert (
-            torch.cuda.device_count() >= comm.get_rank()
-        ), "CityscapesEvaluator currently do not work with multiple machines."
-        return CityscapesEvaluator(dataset_name)
-    if evaluator_type == "pascal_voc":
-        return PascalVOCDetectionEvaluator(dataset_name)
-    if evaluator_type == "lvis":
-        return LVISEvaluator(dataset_name, cfg, True, output_folder)
-    if len(evaluator_list) == 0:
-        raise NotImplementedError(
-            "no Evaluator for the dataset {} with the type {}".format(dataset_name, evaluator_type)
-        )
-    if len(evaluator_list) == 1:
-        return evaluator_list[0]
-    return DatasetEvaluators(evaluator_list)
-
-
-def do_test(cfg, model):
-    results = OrderedDict()
-    for dataset_name in cfg.DATASETS.TEST:
-        data_loader = build_detection_test_loader(cfg, dataset_name)
-        evaluator = get_evaluator(
-            cfg, dataset_name, os.path.join(cfg.OUTPUT_DIR, "inference", dataset_name)
-        )
-        results_i = inference_on_dataset(model, data_loader, evaluator)
-        results[dataset_name] = results_i
-        if comm.is_main_process():
-            logger.info("Evaluation results for {} in csv format:".format(dataset_name))
-            print_csv_format(results_i)
-    if len(results) == 1:
-        results = list(results.values())[0]
-    return results
-
-
-def do_train(cfg, model, resume=False):
-    model.train()
-    optimizer = build_optimizer(cfg, model)
-    scheduler = build_lr_scheduler(cfg, optimizer)
-
-    checkpointer = DetectionCheckpointer(
-        model, cfg.OUTPUT_DIR, optimizer=optimizer, scheduler=scheduler
-    )
-    start_iter = (
-        checkpointer.resume_or_load(cfg.MODEL.WEIGHTS, resume=resume).get("iteration", -1) + 1
-    )
-    max_iter = cfg.SOLVER.MAX_ITER
-
-    periodic_checkpointer = PeriodicCheckpointer(
-        checkpointer, cfg.SOLVER.CHECKPOINT_PERIOD, max_iter=max_iter
-    )
-
-    writers = (
-        [
-            CommonMetricPrinter(max_iter),
-            JSONWriter(os.path.join(cfg.OUTPUT_DIR, "metrics.json")),
-            TensorboardXWriter(cfg.OUTPUT_DIR),
-        ]
-        if comm.is_main_process()
-        else []
-    )
-
-    # compared to "train_net.py", we do not support accurate timing and
-    # precise BN here, because they are not trivial to implement
-    data_loader = build_detection_train_loader(cfg)
-    logger.info("Starting training from iteration {}".format(start_iter))
-    with EventStorage(start_iter) as storage:
-        for data, iteration in zip(data_loader, range(start_iter, max_iter)):
-            iteration = iteration + 1
-            storage.step()
-
-            loss_dict = model(data)
-            losses = sum(loss_dict.values())
-            assert torch.isfinite(losses).all(), loss_dict
-
-            loss_dict_reduced = {k: v.item() for k, v in comm.reduce_dict(loss_dict).items()}
-            losses_reduced = sum(loss for loss in loss_dict_reduced.values())
-            if comm.is_main_process():
-                storage.put_scalars(total_loss=losses_reduced, **loss_dict_reduced)
-
-            optimizer.zero_grad()
-            losses.backward()
-            optimizer.step()
-            storage.put_scalar("lr", optimizer.param_groups[0]["lr"], smoothing_hint=False)
-            scheduler.step()
-
-            if (
-                cfg.TEST.EVAL_PERIOD > 0
-                and iteration % cfg.TEST.EVAL_PERIOD == 0
-                and iteration != max_iter
-            ):
-                do_test(cfg, model)
-                # Compared to "train_net.py", the test results are not dumped to EventStorage
-                comm.synchronize()
-
-            if iteration - start_iter > 5 and (iteration % 20 == 0 or iteration == max_iter):
-                for writer in writers:
-                    writer.write()
-            periodic_checkpointer.step(iteration)
-
-
-def setup(args):
-    """
-    Create configs and perform basic setups.
-    """
-    cfg = get_cfg()
-    cfg.merge_from_file(args.config_file)
-    cfg.merge_from_list(args.opts)
-    cfg.freeze()
-    default_setup(
-        cfg, args
-    )  # if you don't like any of the default setup, write your own setup code
-    return cfg
-
-
-def main(args):
-    cfg = setup(args)
-
-    model = build_model(cfg)
-    logger.info("Model:\n{}".format(model))
-    if args.eval_only:
-        DetectionCheckpointer(model, save_dir=cfg.OUTPUT_DIR).resume_or_load(
-            cfg.MODEL.WEIGHTS, resume=args.resume
-        )
-        return do_test(cfg, model)
-
-    distributed = comm.get_world_size() > 1
-    if distributed:
-        model = DistributedDataParallel(
-            model, device_ids=[comm.get_local_rank()], broadcast_buffers=False
-        )
-
-    do_train(cfg, model)
-    return do_test(cfg, model)
-
-
-if __name__ == "__main__":
-    args = default_argument_parser().parse_args()
-    print("Command Line Args:", args)
-    launch(
-        main,
-        args.num_gpus,
-        num_machines=args.num_machines,
-        machine_rank=args.machine_rank,
-        dist_url=args.dist_url,
-        args=(args,),
-    )
diff --git a/spaces/CVPR/LIVE/thrust/thrust/async/sort.h b/spaces/CVPR/LIVE/thrust/thrust/async/sort.h
deleted file mode 100644
index c665c6467e372929efbb586a8ffa19b761601c39..0000000000000000000000000000000000000000
--- a/spaces/CVPR/LIVE/thrust/thrust/async/sort.h
+++ /dev/null
@@ -1,275 +0,0 @@
-/*
- *  Copyright 2008-2018 NVIDIA Corporation
- *
- *  Licensed under the Apache License, Version 2.0 (the "License");
- *  you may not use this file except in compliance with the License.
- *  You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- *  Unless required by applicable law or agreed to in writing, software
- *  distributed under the License is distributed on an "AS IS" BASIS,
- *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- *  See the License for the specific language governing permissions and
- *  limitations under the License.
- */
-
-/*! \file async/sort.h
- *  \brief Functions for asynchronously sorting a range.
- */
-
-#pragma once
-
-#include <thrust/detail/config.h>
-#include <thrust/detail/cpp14_required.h>
-
-#if THRUST_CPP_DIALECT >= 2014
-
-#include <thrust/detail/static_assert.h>
-#include <thrust/detail/select_system.h>
-#include <thrust/type_traits/logical_metafunctions.h>
-#include <thrust/type_traits/remove_cvref.h>
-#include <thrust/type_traits/is_execution_policy.h>
-#include <thrust/system/detail/adl/async/sort.h>
-
-#include <thrust/event.h>
-
-namespace thrust
-{
-
-namespace async
-{
-
-namespace unimplemented
-{
-
-template <
-  typename DerivedPolicy
-, typename ForwardIt, typename Sentinel, typename StrictWeakOrdering
->
-__host__ 
-event<DerivedPolicy>
-async_stable_sort(
-  thrust::execution_policy<DerivedPolicy>& 
-, ForwardIt, Sentinel, StrictWeakOrdering
-)
-{
-  THRUST_STATIC_ASSERT_MSG(
-    (thrust::detail::depend_on_instantiation<ForwardIt, false>::value)
-  , "this algorithm is not implemented for the specified system"
-  );
-  return {};
-} 
-
-} // namespace unimplemented
-
-namespace stable_sort_detail
-{
-
-using thrust::async::unimplemented::async_stable_sort;
-
-struct stable_sort_fn final
-{
-  template <
-    typename DerivedPolicy
-  , typename ForwardIt, typename Sentinel, typename StrictWeakOrdering
-  >
-  __host__ 
-  static auto call(
-    thrust::detail::execution_policy_base<DerivedPolicy> const& exec
-  , ForwardIt&& first, Sentinel&& last
-  , StrictWeakOrdering&& comp
-  )
-  // ADL dispatch.
-  THRUST_RETURNS(
-    async_stable_sort(
-      thrust::detail::derived_cast(thrust::detail::strip_const(exec))
-    , THRUST_FWD(first), THRUST_FWD(last)
-    , THRUST_FWD(comp)
-    )
-  )
-
-  template <
-    typename DerivedPolicy
-  , typename ForwardIt, typename Sentinel
-  >
-  __host__ 
-  static auto call(
-    thrust::detail::execution_policy_base<DerivedPolicy> const& exec
-  , ForwardIt&& first, Sentinel&& last
-  )
-  // ADL dispatch.
-  THRUST_RETURNS(
-    async_stable_sort(
-      thrust::detail::derived_cast(thrust::detail::strip_const(exec))
-    , THRUST_FWD(first), THRUST_FWD(last)
-    , thrust::less<
-        typename iterator_traits<remove_cvref_t<ForwardIt>>::value_type
-      >{}
-    )
-  )
-
-  template <typename ForwardIt, typename Sentinel, typename StrictWeakOrdering>
-  __host__ 
-  static auto call(ForwardIt&& first, Sentinel&& last, StrictWeakOrdering&& comp) 
-  THRUST_RETURNS(
-    stable_sort_fn::call(
-      thrust::detail::select_system(
-        typename iterator_system<remove_cvref_t<ForwardIt>>::type{}
-      )
-    , THRUST_FWD(first), THRUST_FWD(last)
-    , THRUST_FWD(comp)
-    )
-  )
-
-  template <typename ForwardIt, typename Sentinel>
-  __host__ 
-  static auto call(ForwardIt&& first, Sentinel&& last) 
-  THRUST_RETURNS(
-    stable_sort_fn::call(
-      THRUST_FWD(first), THRUST_FWD(last)
-    , thrust::less<
-        typename iterator_traits<remove_cvref_t<ForwardIt>>::value_type
-      >{}
-    )
-  )
-
-  template <typename... Args>
-  THRUST_NODISCARD __host__ 
-  auto operator()(Args&&... args) const
-  THRUST_RETURNS(
-    call(THRUST_FWD(args)...)
-  )
-};
-
-} // namespace stable_sort_detail
-
-THRUST_INLINE_CONSTANT stable_sort_detail::stable_sort_fn stable_sort{};
-
-namespace fallback
-{
-
-template <
-  typename DerivedPolicy
-, typename ForwardIt, typename Sentinel, typename StrictWeakOrdering
->
-__host__ 
-event<DerivedPolicy>
-async_sort(
-  thrust::execution_policy<DerivedPolicy>& exec
-, ForwardIt&& first, Sentinel&& last, StrictWeakOrdering&& comp
-)
-{
-  return async_stable_sort(
-    thrust::detail::derived_cast(exec)
-  , THRUST_FWD(first), THRUST_FWD(last), THRUST_FWD(comp)
-  );
-} 
-
-} // namespace fallback
-
-namespace sort_detail
-{
-
-using thrust::async::fallback::async_sort;
-
-struct sort_fn final
-{
-  template <
-    typename DerivedPolicy
-  , typename ForwardIt, typename Sentinel, typename StrictWeakOrdering
-  >
-  __host__ 
-  static auto call(
-    thrust::detail::execution_policy_base<DerivedPolicy> const& exec
-  , ForwardIt&& first, Sentinel&& last
-  , StrictWeakOrdering&& comp
-  )
-  // ADL dispatch.
-  THRUST_RETURNS(
-    async_sort(
-      thrust::detail::derived_cast(thrust::detail::strip_const(exec))
-    , THRUST_FWD(first), THRUST_FWD(last)
-    , THRUST_FWD(comp)
-    )
-  )
-
-  template <
-    typename DerivedPolicy
-  , typename ForwardIt, typename Sentinel
-  >
-  __host__ 
-  static auto call3(
-    thrust::detail::execution_policy_base<DerivedPolicy> const& exec
-  , ForwardIt&& first, Sentinel&& last
-  , thrust::true_type
-  )
-  THRUST_RETURNS(
-    sort_fn::call(
-      exec
-    , THRUST_FWD(first), THRUST_FWD(last)
-    , thrust::less<
-        typename iterator_traits<remove_cvref_t<ForwardIt>>::value_type
-      >{}
-    )
-  )
-
-  template <typename ForwardIt, typename Sentinel, typename StrictWeakOrdering>
-  __host__ 
-  static auto call3(ForwardIt&& first, Sentinel&& last,
-                    StrictWeakOrdering&& comp,
-                    thrust::false_type)
-  THRUST_RETURNS(
-    sort_fn::call(
-      thrust::detail::select_system(
-        typename iterator_system<remove_cvref_t<ForwardIt>>::type{}
-      )
-    , THRUST_FWD(first), THRUST_FWD(last)
-    , THRUST_FWD(comp)
-    )
-  )
-
-  // MSVC WAR: MSVC gets angsty and eats all available RAM when we try to detect
-  // if T1 is an execution_policy by using SFINAE. Switching to a static
-  // dispatch pattern to prevent this.
-  template <typename T1, typename T2, typename T3>
-  __host__
-  static auto call(T1&& t1, T2&& t2, T3&& t3)
-  THRUST_RETURNS(
-    sort_fn::call3(THRUST_FWD(t1), THRUST_FWD(t2), THRUST_FWD(t3),
-                   thrust::is_execution_policy<thrust::remove_cvref_t<T1>>{})
-  )
-
-  template <typename ForwardIt, typename Sentinel>
-  __host__ 
-  static auto call(ForwardIt&& first, Sentinel&& last) 
-  THRUST_RETURNS(
-    sort_fn::call(
-      thrust::detail::select_system(
-        typename iterator_system<remove_cvref_t<ForwardIt>>::type{}
-      )
-    , THRUST_FWD(first), THRUST_FWD(last)
-    , thrust::less<
-        typename iterator_traits<remove_cvref_t<ForwardIt>>::value_type
-      >{}
-    )
-  )
-
-  template <typename... Args>
-  THRUST_NODISCARD __host__ 
-  auto operator()(Args&&... args) const
-  THRUST_RETURNS(
-    call(THRUST_FWD(args)...)
-  )
-};
-
-} // namespace sort_detail
-
-THRUST_INLINE_CONSTANT sort_detail::sort_fn sort{};
-
-} // namespace async
-
-} // end namespace thrust
-
-#endif
-
diff --git a/spaces/CVPR/LIVE/thrust/thrust/system/detail/adl/tabulate.h b/spaces/CVPR/LIVE/thrust/thrust/system/detail/adl/tabulate.h
deleted file mode 100644
index 6ae2b22a5cbd3d2705cf4b13757c050b7c6161cc..0000000000000000000000000000000000000000
--- a/spaces/CVPR/LIVE/thrust/thrust/system/detail/adl/tabulate.h
+++ /dev/null
@@ -1,44 +0,0 @@
-/*
- *  Copyright 2008-2013 NVIDIA Corporation
- *
- *  Licensed under the Apache License, Version 2.0 (the "License");
- *  you may not use this file except in compliance with the License.
- *  You may obtain a fill of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- *  Unless required by applicable law or agreed to in writing, software
- *  distributed under the License is distributed on an "AS IS" BASIS,
- *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- *  See the License for the specific language governing permissions and
- *  limitations under the License.
- */
-
-#pragma once
-
-#include <thrust/detail/config.h>
-
-// the purpose of this header is to #include the tabulate.h header
-// of the sequential, host, and device systems. It should be #included in any
-// code which uses adl to dispatch tabulate
-
-#include <thrust/system/detail/sequential/tabulate.h>
-
-// SCons can't see through the #defines below to figure out what this header
-// includes, so we fake it out by specifying all possible files we might end up
-// including inside an #if 0.
-#if 0
-#include <thrust/system/cpp/detail/tabulate.h>
-#include <thrust/system/cuda/detail/tabulate.h>
-#include <thrust/system/omp/detail/tabulate.h>
-#include <thrust/system/tbb/detail/tabulate.h>
-#endif
-
-#define __THRUST_HOST_SYSTEM_TABULATE_HEADER <__THRUST_HOST_SYSTEM_ROOT/detail/tabulate.h>
-#include __THRUST_HOST_SYSTEM_TABULATE_HEADER
-#undef __THRUST_HOST_SYSTEM_TABULATE_HEADER
-
-#define __THRUST_DEVICE_SYSTEM_TABULATE_HEADER <__THRUST_DEVICE_SYSTEM_ROOT/detail/tabulate.h>
-#include __THRUST_DEVICE_SYSTEM_TABULATE_HEADER
-#undef __THRUST_DEVICE_SYSTEM_TABULATE_HEADER
-
diff --git a/spaces/CVPR/LIVE/thrust/thrust/system/tbb/detail/extrema.h b/spaces/CVPR/LIVE/thrust/thrust/system/tbb/detail/extrema.h
deleted file mode 100644
index e0dd4c042b38bafb42d683e2f4f19bab3678a4b4..0000000000000000000000000000000000000000
--- a/spaces/CVPR/LIVE/thrust/thrust/system/tbb/detail/extrema.h
+++ /dev/null
@@ -1,67 +0,0 @@
-/*
- *  Copyright 2008-2013 NVIDIA Corporation
- *
- *  Licensed under the Apache License, Version 2.0 (the "License");
- *  you may not use this file except in compliance with the License.
- *  You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- *  Unless required by applicable law or agreed to in writing, software
- *  distributed under the License is distributed on an "AS IS" BASIS,
- *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- *  See the License for the specific language governing permissions and
- *  limitations under the License.
- */
-
-#pragma once
-
-#include <thrust/detail/config.h>
-#include <thrust/system/tbb/detail/execution_policy.h>
-#include <thrust/system/detail/generic/extrema.h>
-
-namespace thrust
-{
-namespace system
-{
-namespace tbb
-{
-namespace detail
-{
-
-template <typename DerivedPolicy, typename ForwardIterator, typename BinaryPredicate>
-ForwardIterator max_element(execution_policy<DerivedPolicy> &exec,
-                            ForwardIterator first, 
-                            ForwardIterator last,
-                            BinaryPredicate comp)
-{
-  // tbb prefers generic::max_element to cpp::max_element
-  return thrust::system::detail::generic::max_element(exec, first, last, comp);
-} // end max_element()
-
-template <typename DerivedPolicy, typename ForwardIterator, typename BinaryPredicate>
-ForwardIterator min_element(execution_policy<DerivedPolicy> &exec,
-                            ForwardIterator first, 
-                            ForwardIterator last,
-                            BinaryPredicate comp)
-{
-  // tbb prefers generic::min_element to cpp::min_element
-  return thrust::system::detail::generic::min_element(exec, first, last, comp);
-} // end min_element()
-
-template <typename DerivedPolicy, typename ForwardIterator, typename BinaryPredicate>
-thrust::pair<ForwardIterator,ForwardIterator> minmax_element(execution_policy<DerivedPolicy> &exec,
-                                                             ForwardIterator first, 
-                                                             ForwardIterator last,
-                                                             BinaryPredicate comp)
-{
-  // tbb prefers generic::minmax_element to cpp::minmax_element
-  return thrust::system::detail::generic::minmax_element(exec, first, last, comp);
-} // end minmax_element()
-
-} // end detail
-} // end tbb
-} // end system
-} // end thrust
-
-
diff --git a/spaces/CVPR/v-doc_abstractive_mac/ops.py b/spaces/CVPR/v-doc_abstractive_mac/ops.py
deleted file mode 100644
index 52c6b54c94592e1ef27b0d28ba3bc8bffcd952a8..0000000000000000000000000000000000000000
--- a/spaces/CVPR/v-doc_abstractive_mac/ops.py
+++ /dev/null
@@ -1,1067 +0,0 @@
-from __future__ import division
-import math
-import tensorflow as tf
-
-from mi_gru_cell import MiGRUCell
-from mi_lstm_cell import MiLSTMCell
-from config import config
-
-eps = 1e-20
-inf = 1e30
-
-####################################### variables ########################################
-
-'''
-Initializes a weight matrix variable given a shape and a name. 
-Uses random_normal initialization if 1d, otherwise uses xavier. 
-'''
-def getWeight(shape, name = ""):
-    with tf.variable_scope("weights"):               
-        initializer = tf.contrib.layers.xavier_initializer()
-        # if len(shape) == 1: # good?
-        #     initializer = tf.random_normal_initializer()        
-        W = tf.get_variable("weight" + name, shape = shape, initializer = initializer)
-    return W
-
-'''
-Initializes a weight matrix variable given a shape and a name. Uses xavier
-'''
-def getKernel(shape, name = ""):
-    with tf.variable_scope("kernels"):               
-        initializer = tf.contrib.layers.xavier_initializer()
-        W = tf.get_variable("kernel" + name, shape = shape, initializer = initializer)
-    return W
-
-'''
-Initializes a bias variable given a shape and a name.
-'''
-def getBias(shape, name = ""):
-    with tf.variable_scope("biases"):              
-        initializer = tf.zeros_initializer()
-        b = tf.get_variable("bias" + name, shape = shape, initializer = initializer)
-    return b
-
-######################################### basics #########################################
-
-'''
-Multiplies input inp of any depth by a 2d weight matrix.  
-'''
-# switch with conv 1?
-def multiply(inp, W):
-    inDim = tf.shape(W)[0]
-    outDim = tf.shape(W)[1] 
-    newDims = tf.concat([tf.shape(inp)[:-1], tf.fill((1,), outDim)], axis = 0)
-    
-    inp = tf.reshape(inp, (-1, inDim))
-    output = tf.matmul(inp, W)
-    output = tf.reshape(output, newDims)
-
-    return output
-
-'''
-Concatenates x and y. Support broadcasting. 
-Optionally concatenate multiplication of x * y
-'''
-def concat(x, y, dim, mul = False, extendY = False):
-    if extendY:
-        y = tf.expand_dims(y, axis = -2)
-        # broadcasting to have the same shape
-        y = tf.zeros_like(x) + y
-
-    if mul:
-        out = tf.concat([x, y, x * y], axis = -1)
-        dim *= 3
-    else:
-        out = tf.concat([x, y], axis = -1)
-        dim *= 2
-    
-    return out, dim
-
-'''
-Adds L2 regularization for weight and kernel variables.
-'''
-# add l2 in the tf way
-def L2RegularizationOp(l2 = None):
-    if l2 is None:
-        l2 = config.l2
-    l2Loss = 0
-    names = ["weight", "kernel"]
-    for var in tf.trainable_variables():
-        if any((name in var.name.lower()) for name in names):
-            l2Loss += tf.nn.l2_loss(var)
-    return l2 * l2Loss
-
-######################################### attention #########################################
-
-'''
-Transform vectors to scalar logits.
-
-Args:
-    interactions: input vectors
-    [batchSize, N, dim]
-
-    dim: dimension of input vectors
-
-    sumMod: LIN for linear transformation to scalars.
-            SUM to sum up vectors entries to get scalar logit.
-
-    dropout: dropout value over inputs (for linear case)
-
-Return matching scalar for each interaction.
-[batchSize, N]
-'''
-sumMod = ["LIN", "SUM"]
-def inter2logits(interactions, dim, sumMod = "LIN", dropout = 1.0, name = "", reuse = None):
-    with tf.variable_scope("inter2logits" + name, reuse = reuse): 
-        if sumMod == "SUM":
-            logits = tf.reduce_sum(interactions, axis = -1)
-        else: # "LIN"
-            logits = linear(interactions, dim, 1, dropout = dropout, name = "logits")
-    return logits
-
-'''
-Transforms vectors to probability distribution. 
-Calls inter2logits and then softmax over these.
-
-Args:
-    interactions: input vectors
-    [batchSize, N, dim]
-
-    dim: dimension of input vectors
-
-    sumMod: LIN for linear transformation to scalars.
-            SUM to sum up vectors entries to get scalar logit.
-
-    dropout: dropout value over inputs (for linear case)
-
-Return attention distribution over interactions.
-[batchSize, N]
-'''
-def inter2att(interactions, dim, dropout = 1.0, name = "", reuse = None):
-    with tf.variable_scope("inter2att" + name, reuse = reuse): 
-        logits = inter2logits(interactions, dim, dropout = dropout)
-        attention = tf.nn.softmax(logits)    
-    return attention
-
-'''
-Sums up features using attention distribution to get a weighted average over them. 
-'''
-def att2Smry(attention, features):
-    return tf.reduce_sum(tf.expand_dims(attention, axis = -1) * features, axis = -2)
-
-####################################### activations ########################################
-
-'''
-Performs a variant of ReLU based on config.relu
-    PRM for PReLU
-    ELU for ELU
-    LKY for Leaky ReLU
-    otherwise, standard ReLU
-'''
-def relu(inp):                  
-    if config.relu == "PRM":
-        with tf.variable_scope(None, default_name = "prelu"):
-            alpha = tf.get_variable("alpha", shape = inp.get_shape()[-1], 
-                initializer = tf.constant_initializer(0.25))
-            pos = tf.nn.relu(inp)
-            neg = - (alpha * tf.nn.relu(-inp))
-            output = pos + neg
-    elif config.relu == "ELU":
-        output = tf.nn.elu(inp)
-    # elif config.relu == "SELU":
-    #     output = tf.nn.selu(inp) 
-    elif config.relu == "LKY":
-        # output = tf.nn.leaky_relu(inp, config.reluAlpha)
-        output = tf.maximum(inp, config.reluAlpha * inp)
-    elif config.relu == "STD": # STD
-        output = tf.nn.relu(inp)
-    
-    return output
-
-activations = {
-    "NON":      tf.identity, # lambda inp: inp    
-    "TANH":     tf.tanh,
-    "SIGMOID":  tf.sigmoid,
-    "RELU":     relu,
-    "ELU":      tf.nn.elu
-}    
-
-# Sample from Gumbel(0, 1)
-def sampleGumbel(shape): 
-    U = tf.random_uniform(shape, minval = 0, maxval = 1)
-    return -tf.log(-tf.log(U + eps) + eps)
-
-# Draw a clevr_sample from the Gumbel-Softmax distribution
-def gumbelSoftmaxSample(logits, temperature): 
-    y = logits + sampleGumbel(tf.shape(logits))
-    return tf.nn.softmax(y / temperature)
-
-def gumbelSoftmax(logits, temperature, train): # hard = False
-    # Sample from the Gumbel-Softmax distribution and optionally discretize.
-    # Args:
-    #    logits: [batch_size, n_class] unnormalized log-probs
-    #    temperature: non-negative scalar
-    #    hard: if True, take argmax, but differentiate w.r.t. soft clevr_sample y
-    # Returns:
-    #    [batch_size, n_class] clevr_sample from the Gumbel-Softmax distribution.
-    #    If hard=True, then the returned clevr_sample will be one-hot, otherwise it will
-    #    be a probabilitiy distribution that sums to 1 across classes
-
-    y = gumbelSoftmaxSample(logits, temperature)
-
-    # k = tf.shape(logits)[-1]
-    # yHard = tf.cast(tf.one_hot(tf.argmax(y,1),k), y.dtype)
-    yHard = tf.cast(tf.equal(y, tf.reduce_max(y, 1, keep_dims = True)), y.dtype)
-    yNew = tf.stop_gradient(yHard - y) + y
-
-    if config.gumbelSoftmaxBoth:
-        return y
-    if config.gumbelArgmaxBoth:
-        return yNew
-    ret = tf.cond(train, lambda: y, lambda: yNew)
-    
-    return ret 
-
-def softmaxDiscrete(logits, temperature, train):
-    if config.gumbelSoftmax:
-        return gumbelSoftmax(logits, temperature = temperature, train = train)
-    else:
-        return tf.nn.softmax(logits)
-
-def parametricDropout(name, train):
-    var = tf.get_variable("varDp" + name, shape = (), initializer = tf.constant_initializer(2), 
-        dtype = tf.float32)
-    dropout = tf.cond(train, lambda: tf.sigmoid(var), lambda: 1.0)
-    return dropout
-
-###################################### sequence helpers ######################################
-
-'''
-Casts exponential mask over a sequence with sequence length.
-Used to prepare logits before softmax.
-'''
-def expMask(seq, seqLength):
-    maxLength = tf.shape(seq)[-1]
-    mask = (1 - tf.cast(tf.sequence_mask(seqLength, maxLength), tf.float32)) * (-inf)
-    masked = seq + mask
-    return masked
-
-'''
-Computes seq2seq loss between logits and target sequences, with given lengths.
-'''
-def seq2SeqLoss(logits, targets, lengths):
-    mask = tf.sequence_mask(lengths, maxlen = tf.shape(targets)[1])
-    loss = tf.contrib.seq2seq.sequence_loss(logits, targets, tf.to_float(mask))
-    return loss
-
-'''
-Computes seq2seq loss between logits and target sequences, with given lengths.
-    acc1: accuracy per symbol 
-    acc2: accuracy per sequence
-'''
-def seq2seqAcc(preds, targets, lengths):
-    mask = tf.sequence_mask(lengths, maxlen = tf.shape(targets)[1])
-    corrects = tf.logical_and(tf.equal(preds, targets), mask)
-    numCorrects = tf.reduce_sum(tf.to_int32(corrects), axis = 1)
-    
-    acc1 = tf.to_float(numCorrects) / (tf.to_float(lengths) + eps) # add small eps instead?
-    acc1 = tf.reduce_mean(acc1)  
-    
-    acc2 = tf.to_float(tf.equal(numCorrects, lengths))
-    acc2 = tf.reduce_mean(acc2)      
-
-    return acc1, acc2
-
-########################################### linear ###########################################
-
-'''
-linear transformation.
-
-Args:
-    inp: input to transform
-    inDim: input dimension
-    outDim: output dimension
-    dropout: dropout over input
-    batchNorm: if not None, applies batch normalization to inputs
-    addBias: True to add bias
-    bias: initial bias value
-    act: if not None, activation to use after linear transformation
-    actLayer: if True and act is not None, applies another linear transformation on top of previous
-    actDropout: dropout to apply in the optional second linear transformation
-    retVars: if True, return parameters (weight and bias) 
-
-Returns linear transformation result.
-'''
-# batchNorm = {"decay": float, "train": Tensor}
-# actLayer: if activation is not non, stack another linear layer
-# maybe change naming scheme such that if name = "" than use it as default_name (-->unique?)
-def linear(inp, inDim, outDim, dropout = 1.0, 
-    batchNorm = None, addBias = True, bias = 0.0,
-    act = "NON", actLayer = True, actDropout = 1.0, 
-    retVars = False, name = "", reuse = None):
-    
-    with tf.variable_scope("linearLayer" + name, reuse = reuse):        
-        W = getWeight((inDim, outDim) if outDim > 1 else (inDim, ))
-        b = getBias((outDim, ) if outDim > 1 else ()) + bias
-        
-        if batchNorm is not None:
-            inp = tf.contrib.layers.batch_norm(inp, decay = batchNorm["decay"], 
-                center = True, scale = True, is_training = batchNorm["train"], updates_collections = None)
-            # tf.layers.batch_normalization, axis -1 ?
-
-        inp = tf.nn.dropout(inp, dropout)                
-        
-        if outDim > 1:
-            output = multiply(inp, W)
-        else:
-            output = tf.reduce_sum(inp * W, axis = -1)
-        
-        if addBias:
-            output += b
-
-        output = activations[act](output)
-
-        # good?
-        if act != "NON" and actLayer:
-            output = linear(output, outDim, outDim, dropout = actDropout, batchNorm = batchNorm,  
-                addBias = addBias, act = "NON", actLayer = False, 
-                name = name + "_2", reuse = reuse)
-
-    if retVars:
-        return (output, (W, b))
-
-    return output
-
-'''
-Computes Multi-layer feed-forward network.
-
-Args:
-    features: input features
-    dims: list with dimensions of network. 
-          First dimension is of the inputs, final is of the outputs.
-    batchNorm: if not None, applies batchNorm
-    dropout: dropout value to apply for each layer
-    act: activation to apply between layers.
-    NON, TANH, SIGMOID, RELU, ELU
-'''
-# no activation after last layer
-# batchNorm = {"decay": float, "train": Tensor}
-def FCLayer(features, dims, batchNorm = None, dropout = 1.0, act = "RELU"):
-    layersNum = len(dims) - 1
-    
-    for i in range(layersNum):
-        features = linear(features, dims[i], dims[i+1], name = "fc_%d" % i, 
-            batchNorm = batchNorm, dropout = dropout)
-        # not the last layer
-        if i < layersNum - 1: 
-            features = activations[act](features)
-    
-    return features   
-
-###################################### cnns ######################################
-
-'''
-Computes convolution.
-
-Args:
-    inp: input features
-    inDim: input dimension
-    outDim: output dimension
-    batchNorm: if not None, applies batchNorm on inputs
-    dropout: dropout value to apply on inputs
-    addBias: True to add bias
-    kernelSize: kernel size
-    stride: stride size
-    act: activation to apply on outputs
-    NON, TANH, SIGMOID, RELU, ELU
-'''
-# batchNorm = {"decay": float, "train": Tensor, "center": bool, "scale": bool}
-# collections.namedtuple("batchNorm", ("decay", "train"))
-def cnn(inp, inDim, outDim, batchNorm = None, dropout = 1.0, addBias = True, 
-    kernelSize = None, stride = 1, act = "NON", name = "", reuse = None):
-    
-    with tf.variable_scope("cnnLayer" + name, reuse = reuse):
-        
-        if kernelSize is None:
-            kernelSize = config.stemKernelSize            
-        kernelH = kernelW = kernelSize
-        
-        kernel = getKernel((kernelH, kernelW, inDim, outDim))
-        b = getBias((outDim, ))
-        
-        if batchNorm is not None:
-            inp = tf.contrib.layers.batch_norm(inp, decay = batchNorm["decay"], center = batchNorm["center"], 
-                scale = batchNorm["scale"], is_training = batchNorm["train"], updates_collections = None)   
-
-        inp = tf.nn.dropout(inp, dropout)                
-        
-        output = tf.nn.conv2d(inp, filter = kernel, strides = [1, stride, stride, 1], padding = "SAME")
-        
-        if addBias:
-            output += b
-
-        output = activations[act](output)
-
-    return output
-
-'''
-Computes Multi-layer convolutional network.
-
-Args:
-    features: input features
-    dims: list with dimensions of network. 
-          First dimension is of the inputs. Final is of the outputs.
-    batchNorm: if not None, applies batchNorm
-    dropout: dropout value to apply for each layer
-    kernelSizes: list of kernel sizes for each layer. Default to config.stemKernelSize
-    strides: list of strides for each layer. Default to 1.
-    act: activation to apply between layers.
-    NON, TANH, SIGMOID, RELU, ELU
-'''
-# batchNorm = {"decay": float, "train": Tensor, "center": bool, "scale": bool}
-# activation after last layer
-def CNNLayer(features, dims, batchNorm = None, dropout = 1.0, 
-    kernelSizes = None, strides = None, act = "RELU"):
-    
-    layersNum = len(dims) - 1
-    
-    if kernelSizes is None:
-        kernelSizes = [config.stemKernelSize for i in range(layersNum)]
-    
-    if strides is None:
-        strides = [1 for i in range(layersNum)]
-    
-    for i in range(layersNum):
-        features = cnn(features, dims[i], dims[i+1], name = "cnn_%d" % i, batchNorm = batchNorm, 
-            dropout = dropout, kernelSize = kernelSizes[i], stride = strides[i], act = act)
-
-    return features
-
-######################################## location ########################################
-
-'''
-Computes linear positional encoding for h x w grid. 
-If outDim positive, casts positions to that dimension.
-'''
-# ignores dim
-# h,w can be tensor scalars
-def locationL(h, w, dim, outDim = -1, addBias = True):
-    dim = 2
-    grid = tf.stack(tf.meshgrid(tf.linspace(-config.locationBias, config.locationBias, w), 
-                                tf.linspace(-config.locationBias, config.locationBias, h)), axis = -1)
-
-    if outDim > 0:
-        grid = linear(grid, dim, outDim, addBias = addBias, name = "locationL")
-        dim = outDim
-
-    return grid, dim
-
-'''
-Computes sin/cos positional encoding for h x w x (4*dim). 
-If outDim positive, casts positions to that dimension.
-Based on positional encoding presented in "Attention is all you need"
-'''
-# dim % 4 = 0
-# h,w can be tensor scalars
-def locationPE(h, w, dim, outDim = -1, addBias = True):    
-    x = tf.expand_dims(tf.to_float(tf.linspace(-config.locationBias, config.locationBias, w)), axis = -1)
-    y = tf.expand_dims(tf.to_float(tf.linspace(-config.locationBias, config.locationBias, h)), axis = -1)
-    i = tf.expand_dims(tf.to_float(tf.range(dim)), axis = 0)
-
-    peSinX = tf.sin(x / (tf.pow(10000.0, i / dim)))
-    peCosX = tf.cos(x / (tf.pow(10000.0, i / dim)))
-    peSinY = tf.sin(y / (tf.pow(10000.0, i / dim)))
-    peCosY = tf.cos(y / (tf.pow(10000.0, i / dim)))
-
-    peSinX = tf.tile(tf.expand_dims(peSinX, axis = 0), [h, 1, 1])
-    peCosX = tf.tile(tf.expand_dims(peCosX, axis = 0), [h, 1, 1])
-    peSinY = tf.tile(tf.expand_dims(peSinY, axis = 1), [1, w, 1])
-    peCosY = tf.tile(tf.expand_dims(peCosY, axis = 1), [1, w, 1]) 
-
-    grid = tf.concat([peSinX, peCosX, peSinY, peCosY], axis = -1)
-    dim *= 4
-    
-    if outDim > 0:
-        grid = linear(grid, dim, outDim, addBias = addBias, name = "locationPE")
-        dim = outDim
-
-    return grid, dim
-
-locations = {
-    "L": locationL,
-    "PE": locationPE
-}
-
-'''
-Adds positional encoding to features. May ease spatial reasoning.
-(although not used in the default model). 
-
-Args:
-    features: features to add position encoding to.
-    [batchSize, h, w, c]
-
-    inDim: number of features' channels
-    lDim: dimension for positional encodings
-    outDim: if positive, cast enhanced features (with positions) to that dimension
-    h: features' height
-    w: features' width
-    locType: L for linear encoding, PE for cos/sin based positional encoding
-    mod: way to add positional encoding: concatenation (CNCT), addition (ADD), 
-            multiplication (MUL), linear transformation (LIN).
-'''
-mods = ["CNCT", "ADD", "LIN", "MUL"]
-# if outDim = -1, then will be set based on inDim, lDim
-def addLocation(features, inDim, lDim, outDim = -1, h = None, w = None, 
-    locType = "L", mod = "CNCT", name = "", reuse = None): # h,w not needed
-    
-    with tf.variable_scope("addLocation" + name, reuse = reuse):
-        batchSize = tf.shape(features)[0]
-        if h is None:
-            h = tf.shape(features)[1]
-        if w is None:
-            w = tf.shape(features)[2]
-        dim = inDim
-
-        if mod == "LIN":
-            if outDim < 0:
-                outDim = dim
-
-            grid, _ = locations[locType](h, w, lDim, outDim = outDim, addBias = False)
-            features = linear(features, dim, outDim, name = "LIN")
-            features += grid  
-            return features, outDim
-
-        if mod == "CNCT":
-            grid, lDim = locations[locType](h, w, lDim)
-            # grid = tf.zeros_like(features) + grid
-            grid = tf.tile(tf.expand_dims(grid, axis = 0), [batchSize, 1, 1, 1])
-            features = tf.concat([features, grid], axis = -1)
-            dim += lDim
-
-        elif mod == "ADD":
-            grid, _ = locations[locType](h, w, lDim, outDim = dim)
-            features += grid    
-        
-        elif mod == "MUL": # MUL
-            grid, _ = locations[locType](h, w, lDim, outDim = dim)
-
-            if outDim < 0:
-                outDim = dim
-
-            grid = tf.tile(tf.expand_dims(grid, axis = 0), [batchSize, 1, 1, 1])
-            features = tf.concat([features, grid, features * grid], axis = -1)
-            dim *= 3                
-
-        if outDim > 0:
-            features = linear(features, dim, outDim)
-            dim = outDim 
-
-    return features, dim
-
-# config.locationAwareEnd
-# H, W, _ = config.imageDims
-# projDim = config.stemProjDim
-# k = config.stemProjPooling
-# projDim on inDim or on out
-# inDim = tf.shape(features)[3]
-
-'''
-Linearize 2d image to linear vector.
-
-Args:
-    features: batch of 2d images. 
-    [batchSize, h, w, inDim]
-
-    h: image height
-
-    w: image width
-
-    inDim: number of channels
-
-    projDim: if not None, project image to that dimension before linearization
-
-    outDim: if not None, project image to that dimension after linearization
-
-    loc: if not None, add positional encoding:
-        locType: L for linear encoding, PE for cos/sin based positional encoding
-        mod: way to add positional encoding: concatenation (CNCT), addition (ADD), 
-            multiplication (MUL), linear transformation (LIN).
-        pooling: number to pool image with before linearization.
-
-Returns linearized image:
-[batchSize, outDim] (or [batchSize, (h / pooling) * (w /pooling) * projDim] if outDim not supported) 
-'''
-# loc = {"locType": str, "mod": str}
-def linearizeFeatures(features, h, w, inDim, projDim = None, outDim = None, 
-    loc = None, pooling = None):
-    
-    if pooling is None:
-        pooling = config.imageLinPool
-    
-    if loc is not None:
-        features = addLocation(features, inDim, lDim = inDim, outDim = inDim, 
-            locType = loc["locType"], mod = loc["mod"])
-
-    if projDim is not None:
-        features = linear(features, dim, projDim)
-        features = relu(features)
-        dim = projDim
-
-    if pooling > 1:
-        poolingDims = [1, pooling, pooling, 1]
-        features = tf.nn.max_pool(features, ksize = poolingDims, strides = poolingDims, 
-            padding = "SAME")
-        h /= pooling
-        w /= pooling
-  
-    dim = h * w * dim  
-    features = tf.reshape(features, (-1, dim))
-    
-    if outDim is not None:
-        features = linear(features, dim, outDim)
-        dim = outDim
-
-    return features, dim
-
-################################### multiplication ###################################
-# specific dim / proj for x / y
-'''
-"Enhanced" hadamard product between x and y:
-1. Supports optional projection of x, and y prior to multiplication.
-2. Computes simple multiplication, or a parametrized one, using diagonal of complete matrix (bi-linear) 
-3. Optionally concatenate x or y or their projection to the multiplication result.
-
-Support broadcasting
-
-Args:
-    x: left-hand side argument
-    [batchSize, dim]
-
-    y: right-hand side argument
-    [batchSize, dim]
-
-    dim: input dimension of x and y
-    
-    dropout: dropout value to apply on x and y
-
-    proj: if not None, project x and y:
-        dim: projection dimension
-        shared: use same projection for x and y
-        dropout: dropout to apply to x and y if projected
-
-    interMod: multiplication type:
-        "MUL": x * y
-        "DIAG": x * W * y for a learned diagonal parameter W
-        "BL": x' W y for a learned matrix W
-
-    concat: if not None, concatenate x or y or their projection. 
-    
-    mulBias: optional bias to stabilize multiplication (x * bias) (y * bias)
-
-Returns the multiplication result
-[batchSize, outDim] when outDim depends on the use of proj and cocnat arguments.
-'''
-# proj = {"dim": int, "shared": bool, "dropout": float} # "act": str, "actDropout": float
-## interMod = ["direct", "scalarW", "bilinear"] # "additive"
-# interMod = ["MUL", "DIAG", "BL", "ADD"]
-# concat = {"x": bool, "y": bool, "proj": bool}
-def mul(x, y, dim, dropout = 1.0, proj = None, interMod = "MUL", concat = None, mulBias = None,
-    extendY = True, name = "", reuse = None):
-    
-    with tf.variable_scope("mul" + name, reuse = reuse):                
-        origVals = {"x": x, "y": y, "dim": dim}
-
-        x = tf.nn.dropout(x, dropout)
-        y = tf.nn.dropout(y, dropout)
-        # projection
-        if proj is not None:
-            x = tf.nn.dropout(x, proj.get("dropout", 1.0))
-            y = tf.nn.dropout(y, proj.get("dropout", 1.0))
-
-            if proj["shared"]:
-                xName, xReuse = "proj", None
-                yName, yReuse = "proj", True
-            else:
-                xName, xReuse = "projX", None
-                yName, yReuse = "projY", None
-
-            x = linear(x, dim, proj["dim"], name = xName, reuse = xReuse)
-            y = linear(y, dim, proj["dim"], name = yName, reuse = yReuse)
-            dim = proj["dim"]
-            projVals = {"x": x, "y": y, "dim": dim}
-            proj["x"], proj["y"] = x, y
-
-        if extendY:
-            y = tf.expand_dims(y, axis = -2)
-            # broadcasting to have the same shape
-            y = tf.zeros_like(x) + y
-
-        # multiplication
-        if interMod == "MUL":
-            if mulBias is None:
-                mulBias = config.mulBias             
-            output = (x + mulBias) * (y + mulBias)
-        elif interMod == "DIAG":
-            W = getWeight((dim, )) # change initialization?
-            b = getBias((dim, ))
-            activations = x * W * y + b
-        elif interMod == "BL":
-            W = getWeight((dim, dim))
-            b = getBias((dim, ))            
-            output = multiply(x, W) * y + b
-        else: # "ADD"
-            output = tf.tanh(x + y)
-        # concatenation
-        if concat is not None:
-            concatVals = projVals if concat.get("proj", False) else origVals
-            if concat.get("x", False):
-                output = tf.concat([output, concatVals["x"]], axis = -1)
-                dim += concatVals["dim"]
-
-            if concat.get("y", False):
-                output = ops.concat(output, concatVals["y"], extendY = extendY)
-                dim += concatVals["dim"]
-
-    return output, dim
-
-######################################## rnns ########################################
-
-'''
-Creates an RNN cell.
-
-Args:
-    hdim: the hidden dimension of the RNN cell.
-    
-    reuse: whether the cell should reuse parameters or create new ones.
-    
-    cellType: the cell type 
-    RNN, GRU, LSTM, MiGRU, MiLSTM, ProjLSTM
-
-    act: the cell activation
-    NON, TANH, SIGMOID, RELU, ELU
-
-    projDim: if ProjLSTM, the dimension for the states projection
-
-Returns the cell.
-'''
-# tf.nn.rnn_cell.MultiRNNCell([cell(hDim, reuse = reuse) for _ in config.encNumLayers])
-# note that config.enc params not general 
-def createCell(hDim, reuse, cellType = None, act = None, projDim = None):
-    if cellType is None:
-        cellType = config.encType
-
-    activation = activations.get(act, None) 
-
-    if cellType == "ProjLSTM":
-        cell = tf.nn.rnn_cell.LSTMCell
-        if projDim is None:
-            projDim = config.cellDim
-        cell = cell(hDim, num_proj = projDim, reuse = reuse, activation = activation)
-        return cell        
-
-    cells = {
-        "RNN": tf.nn.rnn_cell.BasicRNNCell,
-        "GRU": tf.nn.rnn_cell.GRUCell,
-        "LSTM": tf.nn.rnn_cell.BasicLSTMCell,
-        "MiGRU": MiGRUCell,
-        "MiLSTM": MiLSTMCell
-    }
-
-    cell = cells[cellType](hDim, reuse = reuse, activation = activation)
-
-    return cell
-
-'''
-Runs an forward RNN layer.
-
-Args:
-    inSeq: the input sequence to run the RNN over.
-    [batchSize, sequenceLength, inDim]
-    
-    seqL: the sequence matching lengths.
-    [batchSize, 1]
-
-    hDim: hidden dimension of the RNN.
-
-    cellType: the cell type 
-    RNN, GRU, LSTM, MiGRU, MiLSTM, ProjLSTM
-
-    dropout: value for dropout over input sequence
-
-    varDp: if not None, state and input variational dropouts to apply.
-    dimension of input has to be supported (inputSize). 
-
-Returns the outputs sequence and final RNN state.  
-'''
-# varDp = {"stateDp": float, "inputDp": float, "inputSize": int}
-# proj = {"output": bool, "state": bool, "dim": int, "dropout": float, "act": str}
-def fwRNNLayer(inSeq, seqL, hDim, cellType = None, dropout = 1.0, varDp = None, 
-    name = "", reuse = None): # proj = None
-    
-    with tf.variable_scope("rnnLayer" + name, reuse = reuse):
-        batchSize = tf.shape(inSeq)[0]
-
-        cell = createCell(hDim, reuse, cellType) # passing reuse isn't mandatory
-
-        if varDp is not None:
-            cell = tf.contrib.rnn.DropoutWrapper(cell, 
-                state_keep_prob = varDp["stateDp"],
-                input_keep_prob = varDp["inputDp"],
-                variational_recurrent = True, input_size = varDp["inputSize"], dtype = tf.float32)
-        else:           
-            inSeq = tf.nn.dropout(inSeq, dropout)
-        
-        initialState = cell.zero_state(batchSize, tf.float32)
-
-        outSeq, lastState = tf.nn.dynamic_rnn(cell, inSeq, 
-            sequence_length = seqL, 
-            initial_state = initialState,
-            swap_memory = True)
-            
-        if isinstance(lastState, tf.nn.rnn_cell.LSTMStateTuple):
-            lastState = lastState.h
-
-        # if proj is not None:
-        #     if proj["output"]:
-        #         outSeq = linear(outSeq, cell.output_size, proj["dim"], act = proj["act"],  
-        #             dropout = proj["dropout"], name = "projOutput")
-
-        #     if proj["state"]:
-        #         lastState = linear(lastState, cell.state_size, proj["dim"], act = proj["act"],  
-        #             dropout = proj["dropout"], name = "projState")
-
-    return outSeq, lastState
-
-'''
-Runs an bidirectional RNN layer.
-
-Args:
-    inSeq: the input sequence to run the RNN over.
-    [batchSize, sequenceLength, inDim]
-    
-    seqL: the sequence matching lengths.
-    [batchSize, 1]
-
-    hDim: hidden dimension of the RNN.
-
-    cellType: the cell type 
-    RNN, GRU, LSTM, MiGRU, MiLSTM
-
-    dropout: value for dropout over input sequence
-
-    varDp: if not None, state and input variational dropouts to apply.
-    dimension of input has to be supported (inputSize).   
-
-Returns the outputs sequence and final RNN state.     
-'''
-# varDp = {"stateDp": float, "inputDp": float, "inputSize": int}
-# proj = {"output": bool, "state": bool, "dim": int, "dropout": float, "act": str}
-def biRNNLayer(inSeq, seqL, hDim, cellType = None, dropout = 1.0, varDp = None, 
-    name = "", reuse = None): # proj = None, 
-
-    with tf.variable_scope("birnnLayer" + name, reuse = reuse):
-        batchSize = tf.shape(inSeq)[0]
-
-        with tf.variable_scope("fw"):
-            cellFw = createCell(hDim, reuse, cellType)
-        with tf.variable_scope("bw"):
-            cellBw = createCell(hDim, reuse, cellType)
-        
-        if varDp is not None:
-            cellFw = tf.contrib.rnn.DropoutWrapper(cellFw, 
-                state_keep_prob = varDp["stateDp"],
-                input_keep_prob = varDp["inputDp"],
-                variational_recurrent = True, input_size = varDp["inputSize"], dtype = tf.float32)
-            
-            cellBw = tf.contrib.rnn.DropoutWrapper(cellBw, 
-                state_keep_prob = varDp["stateDp"],
-                input_keep_prob = varDp["inputDp"],
-                variational_recurrent = True, input_size = varDp["inputSize"], dtype = tf.float32)            
-        else:
-            inSeq = tf.nn.dropout(inSeq, dropout)
-
-        initialStateFw = cellFw.zero_state(batchSize, tf.float32)
-        initialStateBw = cellBw.zero_state(batchSize, tf.float32)
-
-        (outSeqFw, outSeqBw), (lastStateFw, lastStateBw) = tf.nn.bidirectional_dynamic_rnn(
-            cellFw, cellBw, inSeq, 
-            sequence_length = seqL, 
-            initial_state_fw = initialStateFw, 
-            initial_state_bw = initialStateBw,
-            swap_memory = True)
-
-        if isinstance(lastStateFw, tf.nn.rnn_cell.LSTMStateTuple):
-            lastStateFw = lastStateFw.h # take c? 
-            lastStateBw = lastStateBw.h  
-
-        outSeq = tf.concat([outSeqFw, outSeqBw], axis = -1)
-        lastState = tf.concat([lastStateFw, lastStateBw], axis = -1)
-
-        # if proj is not None:
-        #     if proj["output"]:
-        #         outSeq = linear(outSeq, cellFw.output_size + cellFw.output_size, 
-        #             proj["dim"], act = proj["act"], dropout = proj["dropout"], 
-        #             name = "projOutput")
-
-        #     if proj["state"]:
-        #         lastState = linear(lastState, cellFw.state_size + cellFw.state_size, 
-        #             proj["dim"], act = proj["act"], dropout = proj["dropout"], 
-        #             name = "projState")
-
-    return outSeq, lastState
-
-# int(hDim / 2) for biRNN?
-'''
-Runs an RNN layer by calling biRNN or fwRNN.
-
-Args:
-    inSeq: the input sequence to run the RNN over.
-    [batchSize, sequenceLength, inDim]
-    
-    seqL: the sequence matching lengths.
-    [batchSize, 1]
-
-    hDim: hidden dimension of the RNN.
-
-    bi: true to run bidirectional rnn.
-
-    cellType: the cell type 
-    RNN, GRU, LSTM, MiGRU, MiLSTM
-
-    dropout: value for dropout over input sequence
-
-    varDp: if not None, state and input variational dropouts to apply.
-    dimension of input has to be supported (inputSize).   
-
-Returns the outputs sequence and final RNN state.     
-'''
-# proj = {"output": bool, "state": bool, "dim": int, "dropout": float, "act": str}
-# varDp = {"stateDp": float, "inputDp": float, "inputSize": int}
-def RNNLayer(inSeq, seqL, hDim, bi = None, cellType = None, dropout = 1.0, varDp = None, 
-    name = "", reuse = None): # proj = None
-    
-    with tf.variable_scope("rnnLayer" + name, reuse = reuse):
-        if bi is None:
-            bi = config.encBi
-        
-        rnn = biRNNLayer if bi else fwRNNLayer
-        
-        if bi:
-            hDim = int(hDim / 2)
-
-    return rnn(inSeq, seqL, hDim, cellType = cellType, dropout = dropout, varDp = varDp) # , proj = proj
-
-# tf counterpart?
-# hDim = config.moduleDim
-def multigridRNNLayer(featrues, h, w, dim, name = "", reuse = None):
-    with tf.variable_scope("multigridRNNLayer" + name, reuse = reuse):
-        featrues = linear(featrues, dim, dim / 2, name = "i")
-
-        output0 = gridRNNLayer(featrues, h, w, dim, right = True, down = True, name = "rd")
-        output1 = gridRNNLayer(featrues, h, w, dim, right = True, down = False, name = "r")
-        output2 = gridRNNLayer(featrues, h, w, dim, right = False, down = True, name = "d")
-        output3 = gridRNNLayer(featrues, h, w, dim, right = False, down = False, name = "NON")
-
-        output = tf.concat([output0, output1, output2, output3], axis = -1)
-        output = linear(output, 2 * dim, dim, name = "o")
-
-    return outputs
-
-# h,w should be constants
-def gridRNNLayer(features, h, w, dim, right, down, name = "", reuse = None):
-    with tf.variable_scope("gridRNNLayer" + name):
-        batchSize = tf.shape(features)[0]
-
-        cell = createCell(dim, reuse = reuse, cellType = config.stemGridRnnMod, 
-            act = config.stemGridAct)
-        
-        initialState = cell.zero_state(batchSize, tf.float32)
-        
-        inputs = [tf.unstack(row, w, axis = 1) for row in tf.unstack(features, h, axis = 1)]
-        states = [[None for _ in range(w)] for _ in range(h)]
-
-        iAxis = range(h) if down else (range(h)[::-1])
-        jAxis = range(w) if right else (range(w)[::-1])
-
-        iPrev = -1 if down else 1
-        jPrev = -1 if right else 1
-
-        prevState = lambda i,j: states[i][j] if (i >= 0 and i < h and j >= 0 and j < w) else initialState
-        
-        for i in iAxis:
-            for j in jAxis:
-                prevs = tf.concat((prevState(i + iPrev, j), prevState(i, j + jPrev)), axis = -1)
-                curr = inputs[i][j]
-                _, states[i][j] = cell(prevs, curr)
-
-        outputs = [tf.stack(row, axis = 1) for row in states]
-        outputs = tf.stack(outputs, axis = 1)
-
-    return outputs
-
-# tf seq2seq?
-# def projRNNLayer(inSeq, seqL, hDim, labels, labelsNum, labelsDim, labelsEmb, name = "", reuse = None):
-#     with tf.variable_scope("projRNNLayer" + name):
-#         batchSize = tf.shape(features)[0]
-
-#         cell = createCell(hDim, reuse = reuse)
-
-#         projCell = ProjWrapper(cell, labelsNum, labelsDim, labelsEmb, # config.wrdEmbDim
-#             feedPrev = True, dropout = 1.0, config,
-#             temperature = 1.0, clevr_sample = False, reuse)
-        
-#         initialState = projCell.zero_state(batchSize, tf.float32)
-        
-#         if config.soft:
-#             inSeq = inSeq
-
-#             # outputs, _ = tf.nn.static_rnn(projCell, inputs, 
-#             #     sequence_length = seqL, 
-#             #     initial_state = initialState)
-
-#             inSeq = tf.unstack(inSeq, axis = 1)                        
-#             state = initialState
-#             logitsList = []
-#             chosenList = []
-
-#             for inp in inSeq:
-#                 (logits, chosen), state = projCell(inp, state)
-#                 logitsList.append(logits)
-#                 chosenList.append(chosen)
-#                 projCell.reuse = True
-
-#             logitsOut = tf.stack(logitsList, axis = 1)
-#             chosenOut = tf.stack(chosenList, axis = 1)
-#             outputs = (logitsOut, chosenOut)
-#         else:
-#             labels = tf.to_float(labels)
-#             labels = tf.concat([tf.zeros((batchSize, 1)), labels], axis = 1)[:, :-1] # ,newaxis
-#             inSeq = tf.concat([inSeq, tf.expand_dims(labels, axis = -1)], axis = -1)
-
-#             outputs, _ = tf.nn.dynamic_rnn(projCell, inSeq, 
-#                 sequence_length = seqL, 
-#                 initial_state = initialState,
-#                 swap_memory = True)
-
-#     return outputs #, labelsEmb
-
-############################### variational dropout ###############################
-
-'''
-Generates a variational dropout mask for a given shape and a dropout 
-probability value.
-'''
-def generateVarDpMask(shape, keepProb):
-    randomTensor = tf.to_float(keepProb)
-    randomTensor += tf.random_uniform(shape, minval = 0, maxval = 1)
-    binaryTensor = tf.floor(randomTensor)
-    mask = tf.to_float(binaryTensor)
-    return mask
-
-'''
-Applies the a variational dropout over an input, given dropout mask 
-and a dropout probability value. 
-'''
-def applyVarDpMask(inp, mask, keepProb):
-    ret = (tf.div(inp, tf.to_float(keepProb))) * mask
-    return ret   
diff --git a/spaces/ChandraMohanNayal/AutoGPT/autogpt/config/ai_config.py b/spaces/ChandraMohanNayal/AutoGPT/autogpt/config/ai_config.py
deleted file mode 100644
index d50c30beee9dc8009f63415378ae1c6a399f0037..0000000000000000000000000000000000000000
--- a/spaces/ChandraMohanNayal/AutoGPT/autogpt/config/ai_config.py
+++ /dev/null
@@ -1,121 +0,0 @@
-# sourcery skip: do-not-use-staticmethod
-"""
-A module that contains the AIConfig class object that contains the configuration
-"""
-from __future__ import annotations
-
-import os
-from typing import Type
-
-import yaml
-
-
-class AIConfig:
-    """
-    A class object that contains the configuration information for the AI
-
-    Attributes:
-        ai_name (str): The name of the AI.
-        ai_role (str): The description of the AI's role.
-        ai_goals (list): The list of objectives the AI is supposed to complete.
-    """
-
-    def __init__(
-        self, ai_name: str = "", ai_role: str = "", ai_goals: list | None = None
-    ) -> None:
-        """
-        Initialize a class instance
-
-        Parameters:
-            ai_name (str): The name of the AI.
-            ai_role (str): The description of the AI's role.
-            ai_goals (list): The list of objectives the AI is supposed to complete.
-        Returns:
-            None
-        """
-        if ai_goals is None:
-            ai_goals = []
-        self.ai_name = ai_name
-        self.ai_role = ai_role
-        self.ai_goals = ai_goals
-
-    # Soon this will go in a folder where it remembers more stuff about the run(s)
-    SAVE_FILE = os.path.join(os.path.dirname(__file__), "..", "ai_settings.yaml")
-
-    @staticmethod
-    def load(config_file: str = SAVE_FILE) -> "AIConfig":
-        """
-        Returns class object with parameters (ai_name, ai_role, ai_goals) loaded from
-          yaml file if yaml file exists,
-        else returns class with no parameters.
-
-        Parameters:
-           config_file (int): The path to the config yaml file.
-             DEFAULT: "../ai_settings.yaml"
-
-        Returns:
-            cls (object): An instance of given cls object
-        """
-
-        try:
-            with open(config_file, encoding="utf-8") as file:
-                config_params = yaml.load(file, Loader=yaml.FullLoader)
-        except FileNotFoundError:
-            config_params = {}
-
-        ai_name = config_params.get("ai_name", "")
-        ai_role = config_params.get("ai_role", "")
-        ai_goals = config_params.get("ai_goals", [])
-        # type: Type[AIConfig]
-        return AIConfig(ai_name, ai_role, ai_goals)
-
-    def save(self, config_file: str = SAVE_FILE) -> None:
-        """
-        Saves the class parameters to the specified file yaml file path as a yaml file.
-
-        Parameters:
-            config_file(str): The path to the config yaml file.
-              DEFAULT: "../ai_settings.yaml"
-
-        Returns:
-            None
-        """
-
-        config = {
-            "ai_name": self.ai_name,
-            "ai_role": self.ai_role,
-            "ai_goals": self.ai_goals,
-        }
-        with open(config_file, "w", encoding="utf-8") as file:
-            yaml.dump(config, file, allow_unicode=True)
-
-    def construct_full_prompt(self) -> str:
-        """
-        Returns a prompt to the user with the class information in an organized fashion.
-
-        Parameters:
-            None
-
-        Returns:
-            full_prompt (str): A string containing the initial prompt for the user
-              including the ai_name, ai_role and ai_goals.
-        """
-
-        prompt_start = (
-            "Your decisions must always be made independently without"
-            " seeking user assistance. Play to your strengths as an LLM and pursue"
-            " simple strategies with no legal complications."
-            ""
-        )
-
-        from autogpt.prompt import get_prompt
-
-        # Construct full prompt
-        full_prompt = (
-            f"You are {self.ai_name}, {self.ai_role}\n{prompt_start}\n\nGOALS:\n\n"
-        )
-        for i, goal in enumerate(self.ai_goals):
-            full_prompt += f"{i+1}. {goal}\n"
-
-        full_prompt += f"\n\n{get_prompt()}"
-        return full_prompt
diff --git a/spaces/ChandraMohanNayal/AutoGPT/tests/unit/test_commands.py b/spaces/ChandraMohanNayal/AutoGPT/tests/unit/test_commands.py
deleted file mode 100644
index ecbac9b73bd9ad872931d77e144dd853b3d8ef64..0000000000000000000000000000000000000000
--- a/spaces/ChandraMohanNayal/AutoGPT/tests/unit/test_commands.py
+++ /dev/null
@@ -1,22 +0,0 @@
-"""Unit tests for the commands module"""
-from unittest.mock import MagicMock, patch
-
-import pytest
-
-import autogpt.agent.agent_manager as agent_manager
-from autogpt.app import execute_command, list_agents, start_agent
-
-
-@pytest.mark.integration_test
-def test_make_agent() -> None:
-    """Test the make_agent command"""
-    with patch("openai.ChatCompletion.create") as mock:
-        obj = MagicMock()
-        obj.response.choices[0].messages[0].content = "Test message"
-        mock.return_value = obj
-        start_agent("Test Agent", "chat", "Hello, how are you?", "gpt2")
-        agents = list_agents()
-        assert "List of agents:\n0: chat" == agents
-        start_agent("Test Agent 2", "write", "Hello, how are you?", "gpt2")
-        agents = list_agents()
-        assert "List of agents:\n0: chat\n1: write" == agents
diff --git a/spaces/Chintan-Donda/KKMS-KSSW-HF/src/weather.py b/spaces/Chintan-Donda/KKMS-KSSW-HF/src/weather.py
deleted file mode 100644
index 266413b4427232a0ac3a1d5a21378f80689f55c2..0000000000000000000000000000000000000000
--- a/spaces/Chintan-Donda/KKMS-KSSW-HF/src/weather.py
+++ /dev/null
@@ -1,87 +0,0 @@
-import requests
-from bs4 import BeautifulSoup as bs
-import src.constants as constants_utils
-
-
-class WEATHER:
-    def __init__(self):
-        self.base_url = 'https://nwp.imd.gov.in/blf/blf_temp'
-        self.headers = {
-            'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7',
-        }
-
-        self.state_names_codes = {}
-        self.districts = []
-
-
-    def get_state_names_codes(
-        self
-    ):
-        response = requests.get(
-            self.base_url,
-            headers=self.headers,
-        )
-
-        soup = bs(response.text, 'html.parser')
-        for option in soup.find_all('option'):
-            if option.text.strip() == 'Select':
-                continue
-            self.state_names_codes[option.text.strip()] = str(option['value'].split('=')[-1][:2])
-        
-        return self.state_names_codes
-
-
-    def get_district_names(
-        self,
-        state_name
-    ):
-        url = f"{self.base_url}/dis.php?value={constants_utils.WEATHER_FORECAST_STATE_CODES.get(state_name, '') + state_name}"
-        response = requests.get(
-            url,
-            headers=self.headers,
-        )
-
-        soup = bs(response.text, 'html.parser')
-        self.districts = soup.findAll('select', {'name': 'dis'}, limit=None)
-        self.districts = [district.strip() for district in self.districts[0].text.split('\n') if district and district != 'Select']
-        return self.districts
-
-
-    # Weather forecast from Govt. website
-    def get_weather_forecast(
-        self,
-        state,
-        district,
-        is_block_level=False
-    ):
-        self.district_url = f"{self.base_url}/block.php?dis={constants_utils.WEATHER_FORECAST_STATE_CODES.get(state, '') + district}"
-        self.block_url = f'{self.base_url}/table2.php'
-
-        response = requests.get(self.district_url if not is_block_level else self.block_url)
-        soup = bs(response.text, 'html.parser')
-        scripts = soup.findAll('font')[0]
-        return scripts.text
-
-
-    # Weather using Google weather API
-    def get_weather(
-        self,
-        city
-    ):
-        city = city + " weather"
-        city = city.replace(" ", "+")
-
-        headers = {
-            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3'
-        }
-        response = requests.get(
-            f'https://www.google.com/search?q={city}&oq={city}&aqs=chrome.0.35i39l2j0l4j46j69i60.6128j1j7&sourceid=chrome&ie=UTF-8', headers=headers)
-
-        soup = bs(response.text, 'html.parser')
-        location = soup.select('#wob_loc')[0].getText().strip()
-        time = soup.select('#wob_dts')[0].getText().strip()
-        info = soup.select('#wob_dc')[0].getText().strip()
-        temperature = soup.select('#wob_tm')[0].getText().strip()
-        temperature = temperature + "°C"
-
-        return time, info, temperature
diff --git a/spaces/Cran-May/BetaSEA-Streamlit/README.md b/spaces/Cran-May/BetaSEA-Streamlit/README.md
deleted file mode 100644
index 75ed1444abb880d9f3cf663983fad0bf2b4278e8..0000000000000000000000000000000000000000
--- a/spaces/Cran-May/BetaSEA-Streamlit/README.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-title: 兮辞·析辞-常明
-emoji: 💻
-colorFrom: indigo
-colorTo: pink
-sdk: streamlit
-sdk_version: 1.27.2
-app_file: app.py
-pinned: true
-models:
-- Cran-May/SLIDE
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
\ No newline at end of file
diff --git a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/altair/vegalite/display.py b/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/altair/vegalite/display.py
deleted file mode 100644
index 91c5f33e093b32cf81accd6fdeeb8a18292c28c0..0000000000000000000000000000000000000000
--- a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/altair/vegalite/display.py
+++ /dev/null
@@ -1,11 +0,0 @@
-from ..utils.display import Displayable, default_renderer_base, json_renderer_base
-from ..utils.display import RendererRegistry, HTMLRenderer
-
-
-__all__ = (
-    "Displayable",
-    "default_renderer_base",
-    "json_renderer_base",
-    "RendererRegistry",
-    "HTMLRenderer",
-)
diff --git a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/ttLib/tables/J_S_T_F_.py b/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/ttLib/tables/J_S_T_F_.py
deleted file mode 100644
index 111c700710e56f1f92703b212b530267313293ba..0000000000000000000000000000000000000000
--- a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/fontTools/ttLib/tables/J_S_T_F_.py
+++ /dev/null
@@ -1,5 +0,0 @@
-from .otBase import BaseTTXConverter
-
-
-class table_J_S_T_F_(BaseTTXConverter):
-    pass
diff --git a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/gradio/components/label.py b/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/gradio/components/label.py
deleted file mode 100644
index 5a2c40fd387b7250cd75d3dfd7ade49ab5343b51..0000000000000000000000000000000000000000
--- a/spaces/DQChoi/gpt-demo/venv/lib/python3.11/site-packages/gradio/components/label.py
+++ /dev/null
@@ -1,182 +0,0 @@
-"""gr.Label() component."""
-
-from __future__ import annotations
-
-import operator
-from pathlib import Path
-from typing import Callable, Literal
-
-from gradio_client.documentation import document, set_documentation_group
-from gradio_client.serializing import (
-    JSONSerializable,
-)
-
-from gradio.components.base import IOComponent, _Keywords
-from gradio.deprecation import warn_style_method_deprecation
-from gradio.events import (
-    Changeable,
-    EventListenerMethod,
-    Selectable,
-)
-
-set_documentation_group("component")
-
-
-@document()
-class Label(Changeable, Selectable, IOComponent, JSONSerializable):
-    """
-    Displays a classification label, along with confidence scores of top categories, if provided.
-    Preprocessing: this component does *not* accept input.
-    Postprocessing: expects a {Dict[str, float]} of classes and confidences, or {str} with just the class or an {int}/{float} for regression outputs, or a {str} path to a .json file containing a json dictionary in the structure produced by Label.postprocess().
-
-    Demos: main_note, titanic_survival
-    Guides: image-classification-in-pytorch, image-classification-in-tensorflow, image-classification-with-vision-transformers, building-a-pictionary-app
-    """
-
-    CONFIDENCES_KEY = "confidences"
-
-    def __init__(
-        self,
-        value: dict[str, float] | str | float | Callable | None = None,
-        *,
-        num_top_classes: int | None = None,
-        label: str | None = None,
-        every: float | None = None,
-        show_label: bool | None = None,
-        container: bool = True,
-        scale: int | None = None,
-        min_width: int = 160,
-        visible: bool = True,
-        elem_id: str | None = None,
-        elem_classes: list[str] | str | None = None,
-        color: str | None = None,
-        **kwargs,
-    ):
-        """
-        Parameters:
-            value: Default value to show in the component. If a str or number is provided, simply displays the string or number. If a {Dict[str, float]} of classes and confidences is provided, displays the top class on top and the `num_top_classes` below, along with their confidence bars. If callable, the function will be called whenever the app loads to set the initial value of the component.
-            num_top_classes: number of most confident classes to show.
-            label: component name in interface.
-            every: If `value` is a callable, run the function 'every' number of seconds while the client connection is open. Has no effect otherwise. Queue must be enabled. The event can be accessed (e.g. to cancel it) via this component's .load_event attribute.
-            show_label: if True, will display label.
-            container: If True, will place the component in a container - providing some extra padding around the border.
-            scale: relative width compared to adjacent Components in a Row. For example, if Component A has scale=2, and Component B has scale=1, A will be twice as wide as B. Should be an integer.
-            min_width: minimum pixel width, will wrap if not sufficient screen space to satisfy this value. If a certain scale value results in this Component being narrower than min_width, the min_width parameter will be respected first.
-            visible: If False, component will be hidden.
-            elem_id: An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.
-            elem_classes: An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.
-            color: The background color of the label (either a valid css color name or hexadecimal string).
-        """
-        self.num_top_classes = num_top_classes
-        self.color = color
-        self.select: EventListenerMethod
-        """
-        Event listener for when the user selects a category from Label.
-        Uses event data gradio.SelectData to carry `value` referring to name of selected category, and `index` to refer to index.
-        See EventData documentation on how to use this event data.
-        """
-        IOComponent.__init__(
-            self,
-            label=label,
-            every=every,
-            show_label=show_label,
-            container=container,
-            scale=scale,
-            min_width=min_width,
-            visible=visible,
-            elem_id=elem_id,
-            elem_classes=elem_classes,
-            value=value,
-            **kwargs,
-        )
-
-    def get_config(self):
-        return {
-            "num_top_classes": self.num_top_classes,
-            "value": self.value,
-            "color": self.color,
-            "selectable": self.selectable,
-            **IOComponent.get_config(self),
-        }
-
-    def postprocess(self, y: dict[str, float] | str | float | None) -> dict | None:
-        """
-        Parameters:
-            y: a dictionary mapping labels to confidence value, or just a string/numerical label by itself
-        Returns:
-            Object with key 'label' representing primary label, and key 'confidences' representing a list of label-confidence pairs
-        """
-        if y is None or y == {}:
-            return {}
-        if isinstance(y, str) and y.endswith(".json") and Path(y).exists():
-            return self.serialize(y)
-        if isinstance(y, (str, float, int)):
-            return {"label": str(y)}
-        if isinstance(y, dict):
-            if "confidences" in y and isinstance(y["confidences"], dict):
-                y = y["confidences"]
-                y = {c["label"]: c["confidence"] for c in y}
-            sorted_pred = sorted(y.items(), key=operator.itemgetter(1), reverse=True)
-            if self.num_top_classes is not None:
-                sorted_pred = sorted_pred[: self.num_top_classes]
-            return {
-                "label": sorted_pred[0][0],
-                "confidences": [
-                    {"label": pred[0], "confidence": pred[1]} for pred in sorted_pred
-                ],
-            }
-        raise ValueError(
-            "The `Label` output interface expects one of: a string label, or an int label, a "
-            "float label, or a dictionary whose keys are labels and values are confidences. "
-            f"Instead, got a {type(y)}"
-        )
-
-    @staticmethod
-    def update(
-        value: dict[str, float]
-        | str
-        | float
-        | Literal[_Keywords.NO_VALUE]
-        | None = _Keywords.NO_VALUE,
-        label: str | None = None,
-        show_label: bool | None = None,
-        container: bool | None = None,
-        scale: int | None = None,
-        min_width: int | None = None,
-        visible: bool | None = None,
-        color: str | Literal[_Keywords.NO_VALUE] | None = _Keywords.NO_VALUE,
-    ):
-        # If color is not specified (NO_VALUE) map it to None so that
-        # it gets filtered out in postprocess. This will mean the color
-        # will not be updated in the front-end
-        if color is _Keywords.NO_VALUE:
-            color = None
-        # If the color was specified by the developer as None
-        # Map is so that the color is updated to be transparent,
-        # e.g. no background default state.
-        elif color is None:
-            color = "transparent"
-        return {
-            "label": label,
-            "show_label": show_label,
-            "container": container,
-            "scale": scale,
-            "min_width": min_width,
-            "visible": visible,
-            "value": value,
-            "color": color,
-            "__type__": "update",
-        }
-
-    def style(
-        self,
-        *,
-        container: bool | None = None,
-    ):
-        """
-        This method is deprecated. Please set these arguments in the constructor instead.
-        """
-        warn_style_method_deprecation()
-        if container is not None:
-            self.container = container
-        return self
diff --git a/spaces/DaFujaTyping/hf-Chat-ui/src/routes/conversation/[id]/summarize/+server.ts b/spaces/DaFujaTyping/hf-Chat-ui/src/routes/conversation/[id]/summarize/+server.ts
deleted file mode 100644
index fcb4800aedbd249f49acbbecdfa10ae65405e7bd..0000000000000000000000000000000000000000
--- a/spaces/DaFujaTyping/hf-Chat-ui/src/routes/conversation/[id]/summarize/+server.ts
+++ /dev/null
@@ -1,77 +0,0 @@
-import { buildPrompt } from "$lib/buildPrompt";
-import { PUBLIC_SEP_TOKEN } from "$lib/constants/publicSepToken.js";
-import { collections } from "$lib/server/database.js";
-import { modelEndpoint } from "$lib/server/modelEndpoint.js";
-import { defaultModel } from "$lib/server/models.js";
-import { trimPrefix } from "$lib/utils/trimPrefix.js";
-import { trimSuffix } from "$lib/utils/trimSuffix.js";
-import { textGeneration } from "@huggingface/inference";
-import { error } from "@sveltejs/kit";
-import { ObjectId } from "mongodb";
-
-export async function POST({ params, locals, fetch }) {
-	const convId = new ObjectId(params.id);
-
-	const conversation = await collections.conversations.findOne({
-		_id: convId,
-		sessionId: locals.sessionId,
-	});
-
-	if (!conversation) {
-		throw error(404, "Conversation not found");
-	}
-
-	const firstMessage = conversation.messages.find((m) => m.from === "user");
-
-	const userPrompt =
-		`Please summarize the following message as a single sentence of less than 5 words:\n` +
-		firstMessage?.content;
-
-	const prompt = buildPrompt([{ from: "user", content: userPrompt }], defaultModel);
-
-	const parameters = {
-		...defaultModel.parameters,
-		return_full_text: false,
-	};
-
-	const endpoint = modelEndpoint(defaultModel);
-	let { generated_text } = await textGeneration(
-		{
-			model: endpoint.url,
-			inputs: prompt,
-			parameters,
-		},
-		{
-			fetch: (url, options) =>
-				fetch(url, {
-					...options,
-					headers: { ...options?.headers, Authorization: endpoint.authorization },
-				}),
-		}
-	);
-
-	generated_text = trimSuffix(trimPrefix(generated_text, "<|startoftext|>"), PUBLIC_SEP_TOKEN);
-
-	if (generated_text) {
-		await collections.conversations.updateOne(
-			{
-				_id: convId,
-				sessionId: locals.sessionId,
-			},
-			{
-				$set: { title: generated_text },
-			}
-		);
-	}
-
-	return new Response(
-		JSON.stringify(
-			generated_text
-				? {
-						title: generated_text,
-				  }
-				: {}
-		),
-		{ headers: { "Content-Type": "application/json" } }
-	);
-}
diff --git a/spaces/Dagfinn1962/prodia2/app.py b/spaces/Dagfinn1962/prodia2/app.py
deleted file mode 100644
index cd6da72e6c2522d67142ec6d970ca1d58a7db678..0000000000000000000000000000000000000000
--- a/spaces/Dagfinn1962/prodia2/app.py
+++ /dev/null
@@ -1,336 +0,0 @@
-import numpy as np
-import gradio as gr
-import ast
-import requests
-
-import logging
-from rembg import new_session
-from cutter import remove, make_label
-from utils import *
-
-API_URL_INITIAL = "https://ysharma-playground-ai-exploration.hf.space/run/initial_dataframe"
-API_URL_NEXT10 = "https://ysharma-playground-ai-exploration.hf.space/run/next_10_rows"
-
-#from theme_dropdown import create_theme_dropdown  # noqa: F401
-
-from theme_dropdown import create_theme_dropdown  # noqa: F401
-
-dropdown, js = create_theme_dropdown()
-
-models = [
-    {"name": "❤ STABLE DIFFUSION MODELS ==========", "url": "stabilityai/stable-diffusion-2-1"},
-     {"name": "SD ComVis 1.2","url": "CompVis/stable-diffusion-v1-2"},
-    {"name": "SD Comvis 1.4","url": "CompVis/stable-diffusion-v1-4"},
-    {"name": "SD runawayml 1.5","url": "runwayml/stable-diffusion-v1-5"},
-    {"name": "SD stable-diffusion xl base 1.0","url": "timothymhowe/stable-diffusion-xl-base-1.0"},
-     {"name": "SD NSFW","url": "digiplay/CamelliaMix_NSFW_diffusers_v1.1"},
-    
-     {"name": "SD Dreamshaper-Anime","url": "Lykon/DreamShaper"},
-     {"name": "Dreamlike Anime","url": "dreamlike-art/dreamlike-photoreal-2.0"},
-    {"name": "❤ REALISTIC PHOTO MODELS ==========", "url": "dreamlike-art/dreamlike-photoreal-2.0"},
-    {"name": "AmiIReal", "url": "stablediffusionapi/amireal"},
-    {"name": "Analog Diffusion", "url": "wavymulder/Analog-Diffusion"},
-    {"name": "Circulus 2.8", "url": "circulus/sd-photoreal-v2.8"},
-    {"name": "UltraSkin", "url": "VegaKH/Ultraskin"},
-    {"name": "Wavyfusion", "url": "wavymulder/wavyfusion"},
-    {"name": "❤ SEMI-REALISTIC MODELS ==========", "url": "stablediffusionapi/all-526"},    
-    {"name": "All 526", "url": "stablediffusionapi/all-526"},
-    {"name": "All 526 animated", "url": "stablediffusionapi/all-526-animated"},
-    {"name": "Circulus Semi Real 2", "url": "circulus/sd-photoreal-semi-v2"},
-    {"name": "Semi Real Mix", "url": "robotjung/SemiRealMix"},
-    {"name": "SpyBG", "url": "stablediffusionapi/spybg"},
-    {"name": "Stable Diffusion 2", "url": "stabilityai/stable-diffusion-2-1"},
-    {"name": "stability AI", "url": "stabilityai/stable-diffusion-2-1-base"},
-    {"name": "Compressed-S-D", "url": "nota-ai/bk-sdm-small"},
-    {"name": "Future Diffusion", "url": "nitrosocke/Future-Diffusion"},
-    {"name": "JWST Deep Space Diffusion", "url": "dallinmackay/JWST-Deep-Space-diffusion"},
-    {"name": "Robo Diffusion 3 Base", "url": "nousr/robo-diffusion-2-base"},
-    {"name": "Robo Diffusion", "url": "nousr/robo-diffusion"},
-    {"name": "Tron Legacy Diffusion", "url": "dallinmackay/Tron-Legacy-diffusion"},
-    {"name": "❤ 3D ART MODELS ==========", "url": "DucHaiten/DucHaitenAIart"},
-    {"name": "DucHaiten Art", "url": "DucHaiten/DucHaitenAIart"},
-    {"name": "DucHaiten ClassicAnime", "url": "DucHaiten/DH_ClassicAnime"},
-    {"name": "DucHaiten DreamWorld", "url": "DucHaiten/DucHaitenDreamWorld"},
-    {"name": "DucHaiten Journey", "url": "DucHaiten/DucHaitenJourney"},
-    {"name": "DucHaiten StyleLikeMe", "url": "DucHaiten/DucHaiten-StyleLikeMe"},
-    {"name": "DucHaiten SuperCute", "url": "DucHaiten/DucHaitenSuperCute"},
-    {"name": "Redshift Diffusion 768", "url": "nitrosocke/redshift-diffusion-768"},
-    {"name": "Redshift Diffusion", "url": "nitrosocke/redshift-diffusion"},
-]   
-
-
-####  REM-BG
-
-remove_bg_models = {
-    "TracerUniversalB7": "TracerUniversalB7",
-    "U2NET": "u2net",
-    "U2NET Human Seg": "u2net_human_seg",
-    "U2NET Cloth Seg": "u2net_cloth_seg"
-}
-
-model_choices = keys(remove_bg_models)
-
-
-def predict(image, session, smoot, matting, bg_color):
-
-    session = new_session(remove_bg_models[session])
-
-    try:
-        return remove(session, image, smoot, matting, bg_color)
-    except ValueError as err:
-        logging.error(err)
-        return make_label(str(err)), None
-
-
-def change_show_mask(chk_state):
-    return gr.Image.update(visible=chk_state)
-
-
-def change_include_matting(chk_state):
-    return gr.Box.update(visible=chk_state), (0, 0, 0), 0, 0, 0
-
-
-def change_foreground_threshold(fg_value, value):
-    fg, bg, erode = value
-    return fg_value, bg, erode
-
-
-def change_background_threshold(bg_value, value):
-    fg, bg, erode = value
-    return fg, bg_value, erode
-
-
-def change_erode_size(erode_value, value):
-    fg, bg, erode = value
-    return fg, bg, erode_value
-
-
-def set_dominant_color(chk_state):
-    return chk_state, gr.ColorPicker.update(value=False, visible=not chk_state)
-
-
-def change_picker_color(picker, dominant):
-    if not dominant:
-        return picker
-    return dominant
-
-
-def change_background_mode(chk_state):
-    return gr.ColorPicker.update(value=False, visible=chk_state), \
-        gr.Checkbox.update(value=False, visible=chk_state)
-
-
-
-###########
-
-text_gen = gr.Interface.load("spaces/daspartho/prompt-extend")
-
-current_model = models[0]
-
-models2 = []
-for model in models:
-    model_url = f"models/{model['url']}"
-    loaded_model = gr.Interface.load(model_url, live=True, preprocess=True)
-    models2.append(loaded_model)
-
-def text_it(inputs, text_gen=text_gen):
-    return text_gen(inputs)
-
-def flip_text(x):
-    return x[::-1]
-
-def send_it(inputs, model_choice):
-    proc = models2[model_choice]
-    return proc(inputs)
-
-
-def flip_image(x):
-    return np.fliplr(x)
-
-
-def set_model(current_model_index):
-    global current_model
-    current_model = models[current_model_index]
-    return gr.update(value=f"{current_model['name']}")
-
-#define inference function
-#First: Get initial images for the grid display 
-def get_initial_images():
-  response = requests.post(API_URL_INITIAL, json={
-            "data": []
-            }).json()
-  #data = response["data"][0]['data'][0][0][:-1]
-  response_dict = response['data'][0]
-  return response_dict  #, [resp[0][:-1] for resp in response["data"][0]["data"]]
-
-#Second: Process response dictionary to get imges as hyperlinked image tags
-def process_response(response_dict):
-  return [resp[0][:-1] for resp in response_dict["data"]]
-
-response_dict = get_initial_images()
-initial = process_response(response_dict)
-initial_imgs  = '<div style="display: grid; grid-template-columns: repeat(3, 1fr); grid-template-rows: repeat(3, 1fr); grid-gap: 0; background-color: #fff; padding: 20px; box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);">\n' + "\n".join(initial[:-1])
-
-#Third: Load more images for the grid
-def get_next10_images(response_dict, row_count):
-    row_count = int(row_count)
-    #print("(1)",type(response_dict))
-    #Convert the string to a dictionary
-    if isinstance(response_dict, dict) == False :
-        response_dict = ast.literal_eval(response_dict)
-    response = requests.post(API_URL_NEXT10, json={
-              "data": [response_dict, row_count ] #len(initial)-1
-               }).json()
-    row_count+=10
-    response_dict = response['data'][0]
-    #print("(2)",type(response))
-    #print("(3)",type(response['data'][0]))
-    next_set  = [resp[0][:-1] for resp in response_dict["data"]]
-    next_set_images = '<div style="display: grid; grid-template-columns: repeat(3, 1fr); grid-template-rows: repeat(3, 1fr); grid-gap: 0; background-color: #fff; padding: 20px; box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2); ">\n' + "\n".join(next_set[:-1])
-    return response_dict, row_count, next_set_images  #response['data'][0]
-
-
-with gr.Blocks(css ='main.css') as pan:
-    gr.Markdown("MENU")
-                    
-    with gr.Tab("TEXT TO IMAGE"):
-        
-    ##model = ("stabilityai/stable-diffusion-2-1")
-         model_name1 = gr.Dropdown(
-                label="Choose Model",
-                choices=[m["name"] for m in models],
-                type="index",
-                value=current_model["name"],
-                interactive=True,
-         )
-         input_text = gr.Textbox(label="Prompt idea",)
-
-        ##  run = gr.Button("Generate Images")
-         with gr.Row():
-             see_prompts = gr.Button("Generate Prompts")
-             run = gr.Button("Generate Images", variant="primary")
-        
-         with gr.Row():
-             magic1 = gr.Textbox(label="Generated Prompt", lines=2)
-             output1 = gr.Image(label="")
-          
-             
-         with gr.Row():    
-             magic2 = gr.Textbox(label="Generated Prompt", lines=2)
-             output2 = gr.Image(label="")
-
-            
-         run.click(send_it, inputs=[magic1, model_name1], outputs=[output1])
-         run.click(send_it, inputs=[magic2, model_name1], outputs=[output2])
-         see_prompts.click(text_it, inputs=[input_text], outputs=[magic1])
-         see_prompts.click(text_it, inputs=[input_text], outputs=[magic2])
-        
-    model_name1.change(set_model, inputs=model_name1, outputs=[output1, output2,])
-        
-    with gr.Tab("AI Library"):
-         #Using Gradio Demos as API - This is Hot!
-#get_next10_images(response_dict=response_dict, row_count=9)
-#position: fixed; top: 0; left: 0; width: 100%; padding: 20px; box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
-
-#Defining the Blocks layout
-   # with gr.Blocks(css = """#img_search img {width: 100%; height: 100%; object-fit: cover;}""") as demo:
-         gr.HTML(value="top of page", elem_id="top",visible=False)
-         gr.HTML("""<div style="text-align: center; max-width: 700px; margin: 0 auto;">
-            <div
-            style="
-            display: inline-flex;
-            align-items: center;
-            gap: 0.8rem;
-            font-size: 1.75rem;
-            "
-            >
-            <h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;">
-            Using Gradio API - 2 </h1><br></div>
-            <div><h4 style="font-weight: 500; margin-bottom: 7px; margin-top: 5px;">
-            Stream < href="https://huggingface.co/collections/Dagfinn1962/images-64fc02ca304b8cb412ccda28" target="_blank">Collection Images</a> ina beautiful grid</h4><br>
-            </div>""")
-    with gr.Tab("Gallery"):
-    #with gr.Tab(): #(elem_id = "col-container"):
-          #gr.Column(): #(elem_id = "col-container"):
-             b1 = gr.Button("Load More Images").style(full_width=False)
-             df = gr.Textbox(visible=False,elem_id='dataframe', value=response_dict)
-             row_count = gr.Number(visible=False, value=19 )
-             img_search = gr.HTML(label = 'Images from PlaygroundAI dataset', elem_id="img_search", 
-                                 value=initial_imgs ) #initial[:-1] )
-      
-
-    b1.click(get_next10_images, [df, row_count], [df, row_count, img_search], api_name = "load_playgroundai_images" ) 
-            
-##########################  REM-BG
-    with gr.Tab("Remove Background"):
-        
-        color_state = gr.State(value=False)
-        matting_state = gr.State(value=(0, 0, 0))
-        gr.HTML("<center><h1>Remove Background Tool</h1></center>")
-        
-        with gr.Row(equal_height=False):
-            with gr.Column():
-                input_img = gr.Image(type="pil", label="Input image")
-                drp_models = gr.Dropdown(choices=model_choices, label="Model Segment", value="TracerUniversalB7")
-
-            with gr.Row():
-                chk_include_matting = gr.Checkbox(label="Matting", value=False)
-                chk_smoot_mask = gr.Checkbox(label="Smoot Mask", value=False)
-                chk_show_mask = gr.Checkbox(label="Show Mask", value=False)
-            with gr.Box(visible=False) as slider_matting:
-                slr_fg_threshold = gr.Slider(0, 300, value=270, step=1, label="Alpha matting foreground threshold")
-                slr_bg_threshold = gr.Slider(0, 50, value=20, step=1, label="Alpha matting background threshold")
-                slr_erode_size = gr.Slider(0, 20, value=11, step=1, label="Alpha matting erode size")
-            with gr.Box():
-                with gr.Row():
-                    chk_change_color = gr.Checkbox(label="Change background color", value=False)
-                    pkr_color = gr.ColorPicker(label="Pick a new color", visible=False)
-                    chk_dominant = gr.Checkbox(label="Use dominant color", value=False, visible=False)
-
-                #######################
-                    ############################
-                    #############################
-                run_btn = gr.Button(value="Remove background", variant="primary")        
-
-            with gr.Column():
-                output_img = gr.Image(type="pil", label="Image Result")
-                mask_img = gr.Image(type="pil", label="Image Mask", visible=False)
-                gr.ClearButton(components=[input_img, output_img, mask_img])
-
-        chk_include_matting.change(change_include_matting, inputs=[chk_include_matting],
-                               outputs=[slider_matting, matting_state,
-                                        slr_fg_threshold, slr_bg_threshold, slr_erode_size])
-        
-        slr_bg_threshold.change(change_background_threshold, inputs=[slr_bg_threshold, matting_state],
-                            outputs=[matting_state])
-
-        slr_fg_threshold.change(change_foreground_threshold, inputs=[slr_fg_threshold, matting_state],
-                            outputs=[matting_state])
-
-        slr_erode_size.change(change_erode_size, inputs=[slr_erode_size, matting_state],
-                          outputs=[matting_state])
-
-        chk_show_mask.change(change_show_mask, inputs=[chk_show_mask], outputs=[mask_img])
-
-        chk_change_color.change(change_background_mode, inputs=[chk_change_color],
-                            outputs=[pkr_color, chk_dominant])
-
-        pkr_color.change(change_picker_color, inputs=[pkr_color, chk_dominant], outputs=[color_state])
-
-        chk_dominant.change(set_dominant_color, inputs=[chk_dominant], outputs=[color_state, pkr_color])
-
-        run_btn.click(predict, inputs=[input_img, drp_models, chk_smoot_mask, matting_state, color_state],
-                  outputs=[output_img, mask_img])
-
-
-                
-#            text_input = gr.Textbox()                      ##   Diffuser
-#            image_output = gr.Image()
-#        image_button = gr.Button("Flip")
-
-
-
-   # text_button.click(flip_text, inputs=text_input, outputs=text_output)
-   # image_button.click(flip_image, inputs=image_input, outputs=image_output)
-pan.queue(concurrency_count=200)
-pan.launch(inline=True, show_api=True,  max_threads=400 )
diff --git a/spaces/DaleChen/AutoGPT/run.bat b/spaces/DaleChen/AutoGPT/run.bat
deleted file mode 100644
index afbab57a0603a126b04845ec754d1ecf3fdea18d..0000000000000000000000000000000000000000
--- a/spaces/DaleChen/AutoGPT/run.bat
+++ /dev/null
@@ -1,8 +0,0 @@
-@echo off
-python scripts/check_requirements.py requirements.txt
-if errorlevel 1 (
-    echo Installing missing packages...
-    pip install -r requirements.txt
-)
-python -m autogpt %*
-pause
diff --git a/spaces/Daniton/superjourney/app.py b/spaces/Daniton/superjourney/app.py
deleted file mode 100644
index 2193905172b6fb6d868bff88cc8311f491ec13b3..0000000000000000000000000000000000000000
--- a/spaces/Daniton/superjourney/app.py
+++ /dev/null
@@ -1,3 +0,0 @@
-import gradio as gr
-
-gr.Interface.load("models/prompthero/openjourney").launch()
\ No newline at end of file
diff --git a/spaces/Dantra1/CeliaSensei/text/__init__.py b/spaces/Dantra1/CeliaSensei/text/__init__.py
deleted file mode 100644
index 663c4b6416affb53c9dc56dddbc8b2b65d4bf518..0000000000000000000000000000000000000000
--- a/spaces/Dantra1/CeliaSensei/text/__init__.py
+++ /dev/null
@@ -1,57 +0,0 @@
-""" from https://github.com/keithito/tacotron """
-from text import cleaners
-from text.symbols import symbols
-
-
-# Mappings from symbol to numeric ID and vice versa:
-_symbol_to_id = {s: i for i, s in enumerate(symbols)}
-_id_to_symbol = {i: s for i, s in enumerate(symbols)}
-
-
-def text_to_sequence(text, symbols, cleaner_names):
-  '''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
-    Args:
-      text: string to convert to a sequence
-      cleaner_names: names of the cleaner functions to run the text through
-    Returns:
-      List of integers corresponding to the symbols in the text
-  '''
-  _symbol_to_id = {s: i for i, s in enumerate(symbols)}
-  sequence = []
-
-  clean_text = _clean_text(text, cleaner_names)
-  for symbol in clean_text:
-    if symbol not in _symbol_to_id.keys():
-      continue
-    symbol_id = _symbol_to_id[symbol]
-    sequence += [symbol_id]
-  return sequence, clean_text
-
-
-def cleaned_text_to_sequence(cleaned_text):
-  '''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
-    Args:
-      text: string to convert to a sequence
-    Returns:
-      List of integers corresponding to the symbols in the text
-  '''
-  sequence = [_symbol_to_id[symbol] for symbol in cleaned_text if symbol in _symbol_to_id.keys()]
-  return sequence
-
-
-def sequence_to_text(sequence):
-  '''Converts a sequence of IDs back to a string'''
-  result = ''
-  for symbol_id in sequence:
-    s = _id_to_symbol[symbol_id]
-    result += s
-  return result
-
-
-def _clean_text(text, cleaner_names):
-  for name in cleaner_names:
-    cleaner = getattr(cleaners, name)
-    if not cleaner:
-      raise Exception('Unknown cleaner: %s' % name)
-    text = cleaner(text)
-  return text
diff --git a/spaces/Dao3/DreamlikeArt-Diffusion-1.0/README.md b/spaces/Dao3/DreamlikeArt-Diffusion-1.0/README.md
deleted file mode 100644
index 43bb4c92438a78f83eca8f7f06051c81b01bb4ce..0000000000000000000000000000000000000000
--- a/spaces/Dao3/DreamlikeArt-Diffusion-1.0/README.md
+++ /dev/null
@@ -1,19 +0,0 @@
----
-title: DreamlikeArt-Diffusion 1.0
-emoji: 🧘🏻‍♂️
-colorFrom: blue
-colorTo: yellow
-sdk: gradio
-sdk_version: 3.16.1
-app_file: app.py
-pinned: false
-duplicated_from: phenomenon1981/DreamlikeArt-Diffusion-1.0
----
----
-title: DreamlikeArt-Diffusion .0
-emoji: 🧘🏻‍♂️
-colorFrom: blue
-colorTo: yellow
-sdk: gradio
-sdk_version: 3.16.1
-app_file: app.py
\ No newline at end of file
diff --git a/spaces/Dragonnext/Drago-Proxy/greeting.md b/spaces/Dragonnext/Drago-Proxy/greeting.md
deleted file mode 100644
index 56bf37f8d86ab390933477c5cb1741c78393b180..0000000000000000000000000000000000000000
--- a/spaces/Dragonnext/Drago-Proxy/greeting.md
+++ /dev/null
@@ -1,11 +0,0 @@
-**THIS PROXY IS PRIVATE USED ONLY BY ME TO TEST KEYS OR COOM MYSELF, USE UNICORN (TURBO) ONE (*THIS ONE WILL NEVER BE PUBLIC*)**
-
-    https://huggingface.co/spaces/Dragonnext/Unicorn-proxy
-
-Contact with me:
-contactdrago@proton.me
-
-My private bots not promising good results (Feel free to share rentry):
-https://rentry.co/dragobots
-
-![cute](https://files.catbox.moe/nuxjp4.png)
diff --git a/spaces/ECCV2022/bytetrack/tutorials/centertrack/README.md b/spaces/ECCV2022/bytetrack/tutorials/centertrack/README.md
deleted file mode 100644
index b46bb2f0412c260c53d90bb5f8e5f2c387f748a5..0000000000000000000000000000000000000000
--- a/spaces/ECCV2022/bytetrack/tutorials/centertrack/README.md
+++ /dev/null
@@ -1,42 +0,0 @@
-# CenterTrack
-
-Step1.  git clone https://github.com/xingyizhou/CenterTrack.git
-
-
-Step2. 
-
-replace https://github.com/xingyizhou/CenterTrack/blob/master/src/lib/utils/tracker.py
-
-replace https://github.com/xingyizhou/CenterTrack/blob/master/src/lib/opts.py
-
-
-Step3. run
-```
-python3 test.py tracking --exp_id mot17_half --dataset mot --dataset_version 17halfval --pre_hm --ltrb_amodal  --load_model ../models/mot17_half.pth --track_thresh 0.4 --new_thresh 0.5 --out_thresh 0.2 --pre_thresh 0.5
-```
-
-
-# CenterTrack_BYTE
-
-Step1.  git clone https://github.com/xingyizhou/CenterTrack.git
-
-
-Step2. 
-
-replace https://github.com/xingyizhou/CenterTrack/blob/master/src/lib/utils/tracker.py by byte_tracker.py
-
-replace https://github.com/xingyizhou/CenterTrack/blob/master/src/lib/opts.py
-
-add mot_online to https://github.com/xingyizhou/CenterTrack/blob/master/src/lib/utils
-
-Step3. run
-```
-python3 test.py tracking --exp_id mot17_half --dataset mot --dataset_version 17halfval --pre_hm --ltrb_amodal  --load_model ../models/mot17_half.pth --track_thresh 0.4 --new_thresh 0.5 --out_thresh 0.2 --pre_thresh 0.5
-```
-
-
-## Notes
-tracker.py: only motion
-
-byte_tracker.py: motion with kalman filter
-
diff --git a/spaces/EPFL-VILAB/MultiMAE/utils/layers/helpers.py b/spaces/EPFL-VILAB/MultiMAE/utils/layers/helpers.py
deleted file mode 100644
index e28234052d6b3c36845bd51e33de9b5855776877..0000000000000000000000000000000000000000
--- a/spaces/EPFL-VILAB/MultiMAE/utils/layers/helpers.py
+++ /dev/null
@@ -1,38 +0,0 @@
-# --------------------------------------------------------
-# Based on timm and MAE-priv code bases
-# https://github.com/rwightman/pytorch-image-models/tree/master/timm
-# https://github.com/BUPT-PRIV/MAE-priv
-# --------------------------------------------------------
-
-""" Layer/Module Helpers
-
-Hacked together by / Copyright 2020 Ross Wightman
-"""
-import collections.abc
-from itertools import repeat
-
-
-# From PyTorch internals
-def _ntuple(n):
-    def parse(x):
-        if isinstance(x, collections.abc.Iterable):
-            return x
-        return tuple(repeat(x, n))
-
-    return parse
-
-
-to_1tuple = _ntuple(1)
-to_2tuple = _ntuple(2)
-to_3tuple = _ntuple(3)
-to_4tuple = _ntuple(4)
-to_ntuple = _ntuple
-
-
-def make_divisible(v, divisor=8, min_value=None, round_limit=.9):
-    min_value = min_value or divisor
-    new_v = max(min_value, int(v + divisor / 2) // divisor * divisor)
-    # Make sure that round down does not go down by more than 10%.
-    if new_v < round_limit * v:
-        new_v += divisor
-    return new_v
diff --git a/spaces/Eunice0120/text_generator/README.md b/spaces/Eunice0120/text_generator/README.md
deleted file mode 100644
index 99d8c0b984f1a2cb66e08623dd9c3fd0a847375c..0000000000000000000000000000000000000000
--- a/spaces/Eunice0120/text_generator/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Text Generator
-emoji: 🏃
-colorFrom: blue
-colorTo: yellow
-sdk: gradio
-sdk_version: 3.18.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/EuroPython2022/Warehouse_Apparel_Detection/templates/index.html b/spaces/EuroPython2022/Warehouse_Apparel_Detection/templates/index.html
deleted file mode 100644
index 9d60b551ef40b9b33e45c9e0c10dc32f005d41e0..0000000000000000000000000000000000000000
--- a/spaces/EuroPython2022/Warehouse_Apparel_Detection/templates/index.html
+++ /dev/null
@@ -1,351 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-
-<head>
-	<meta charset="UTF-8">
-	<meta name="viewport" content="width=device-width, initial-scale=1.0">
-	<meta http-equiv="X-UA-Compatible" content="ie=edge">
-	<title>iNeuron</title>
-	<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/css/bootstrap.min.css"
-		integrity="sha384-Gn5384xqQ1aoWXA+058RXPxPg6fy4IWvTNh0E263XmFcJlSAwiGgFAW/dAiS6JXm" crossorigin="anonymous">
-	<style>
-
-		.iupload h3 {
-			color: #1b2d6b;
-			font-size: 30px;
-			font-weight: 700;
-		}
-
-		.img-part-1 {
-			height: 300px;
-			width: 300px;
-			margin: 0px auto;
-		}
-
-		.image-part {
-			height: 300px;
-			width: 300px;
-			border: 1px solid #1b2d6b;
-		}
-
-		.image-part img {
-			/* position: absolute; */
-			height: 300px;
-			width: 300px;
-			display: none;
-			padding: 5px;
-		}
-
-		.image-part #video {
-			/* display: block; */
-			height: 300px;
-			width: 300px;
-			padding: 5px;
-		}
-
-		.res-part {
-			/* margin-left: 20px; */
-			height: 400px;
-			width: 100%;
-			padding: 5px;
-			margin: 0px auto;
-			overflow: auto;
-		}
-
-		.upload-image {
-			/* margin-left: 20px; */
-			height: 400px;
-			width: auto;;
-			padding: 5px;
-			margin: 0px auto;
-			overflow: auto;
-		}
-
-		.resp-img {
-			height: 400px;
-			width: auto;
-			margin: 0px auto;
-		}
-
-		.jsonRes {
-			margin-left: 30px;
-		}
-
-		#send {
-			cursor: pointer;
-		}
-
-		.btn-part {
-			width: 325px;
-		}
-
-		textarea,
-		select,
-		.form-control,
-		.custom-select,
-		button.btn,
-		.btn-primary,
-		input[type="text"],
-		input[type="url"],
-		.uneditable-input {
-			border: 1px solid #363e75;
-			outline: 0 !important;
-			border-radius: 0px;
-			box-shadow: none;
-			-webkit-box-shadow: none;
-			-moz-box-shadow: none;
-			-moz-transition: none;
-			-webkit-transition: none;
-		}
-
-		textarea:focus,
-		select:focus,
-		.form-control:focus,
-		.btn:focus,
-		.btn-primary:focus,
-		.custom-select:focus,
-		input[type="text"]:focus,
-		.uneditable-input:focus {
-			border: 1px solid #007bff;
-			outline: 0 !important;
-			border-radius: 0px;
-			box-shadow: none;
-			-webkit-box-shadow: none;
-			-moz-box-shadow: none;
-			-moz-transition: none;
-			-webkit-transition: none;
-		}
-
-		#loading {
-			position: fixed;
-			left: 0px;
-			top: 0px;
-			width: 100%;
-			height: 100%;
-			z-index: 9999999999;
-			overflow: hidden;
-			background: rgba(255, 255, 255, 0.7);
-		}
-
-		.loader {
-			border: 8px solid #f3f3f3;
-			border-top: 8px solid #363e75;
-			border-radius: 50%;
-			width: 60px;
-			height: 60px;
-			left: 50%;
-			margin-left: -4em;
-			display: block;
-			animation: spin 2s linear infinite;
-		}
-
-		.loader,
-		.loader:after {
-			display: block;
-			position: absolute;
-			top: 50%;
-			margin-top: -4.05em;
-		}
-
-		@keyframes spin {
-			0% {
-				transform: rotate(0deg);
-			}
-
-			100% {
-				transform: rotate(360deg);
-			}
-		}
-
-		.logo {
-			position: absolute;
-			right: 0px;
-			bottom: 0px;
-			margin-right: 30px;
-			margin-bottom: 30px;
-		}
-	</style>
-</head>
-
-<body>
-	<!-- <div class="main container">
-		<section class="iupload">
-			<h3 class="text-center py-4">Object Detection Using TFOD</h3>
-			<div class="row">
-				<div class="img-part col-md-6">
-					<div class="image-part">
-						<video autoplay id="video"
-							poster="https://img.freepik.com/free-vector/group-young-people-posing-photo_52683-18824.jpg?size=338&ext=jpg"></video>
-						<img src="" id="photo">
-						<canvas style="display:none;" id="canvas"></canvas>
-					</div>
-				</div>
-				<div class="col-md-6 col-xs-12 right-part">
-					<h5 class="mb-2">
-						Prediction Results
-					</h5>
-					<div class="row">
-						<div class="res-part2 col-md-2 col-xs-12"></div>
-					</div>
-				</div>
-			</div>
-		</section>
-
-		
-	</div> -->
-
-	<!-- Header -->
-<header class="bg-primary text-center py-5 mb-4">
-	<div class="container">
-	  <h1 class="font-weight-light text-white">Warehouse Apparel Detection using YOLOv5</h1>
-	</div>
-  </header>
-  
-  <!-- Page Content -->
-  <div class="container">
-
-	  
-	<form class="input-group upload-data row">	
-		<div class="col-xl-6 col-md-6 col-sm-6">
-		<button type="button" class="btn btn-primary col-12" id="uload">Upload</button>
-		</div>
-		<div class="col-xl-6 col-md-6 col-sm-6">
-			<button id="send" type="button" class="btn btn-success col-12">Predict</button>
-		</div>
-
-		<!-- change url value  -->
-
-		<input type="hidden" class="form-control mr-2" id="url" placeholder="Enter REST Api url..." value="../predict" />
-		<input name="upload" type="file" id="fileinput" style="position:absolute;top:-500px; display: none;" /><br />
-	</form>
-
-	<div class="row">
-	  <!-- Team Member 1 -->
-	  <div class="col-xl-6 col-md-6 col-sm-6 mb-6">
-		<div class="card border-0 shadow upload-image ">
-		  <!-- <img src="https://source.unsplash.com/TMgQMXoglsM/500x350" class="card-img-top" alt="..."> -->
-		  	<video autoplay id="video" poster="https://img.freepik.com/free-vector/group-young-people-posing-photo_52683-18824.jpg?size=338&ext=jpg"></video>
-			<img src="" class="" id="photo">
-			<canvas style="display:none;" id="canvas"></canvas>
-		  <!-- <div class="card-body text-center">
-			<h5 class="card-title mb-0">Team Member</h5>
-		  </div> -->
-		</div>
-	  </div>
-	  <!-- Team Member 2 -->
-	  <div class="col-xl-6 col-md-6 col-sm-6 mb-6">
-		<div class="card border-0 shadow res-part2">
-		  <div class="card-body text-center">
-			<h5 class="card-title mb-0">Prediction Results</h5>
-		  </div>
-		</div>
-	  </div>
-	</div>
-	<!-- /.row -->
-
-  
-  </div>
-  <!-- /.container -->
-
-	<img class="logo"
-		src="https://apparel.ineuronvision.com/static/logo.png" />
-
-
-	<div id="loading">
-		<div class="loader"></div>
-	</div>
-	<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.4.1/jquery.min.js"></script>
-	<script src="https://cdnjs.cloudflare.com/ajax/libs/popper.js/1.12.9/umd/popper.min.js"
-		integrity="sha384-ApNbgh9B+Y1QKtv3Rn7W3mgPxhU9K/ScQsAP7hUibX39j7fakFPskvXusvfa0b4Q" crossorigin="anonymous">
-	</script>
-	<script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/js/bootstrap.min.js"
-		integrity="sha384-JZR6Spejh4U02d8jOt6vLEHfe/JQGiRRSQQxSfFWpi1MquVdAyjUar5+76PVCmYl" crossorigin="anonymous">
-	</script>
-
-	<script>
-		var mybtn = document.getElementById('startbtn');
-		var myvideo = document.getElementById('video');
-		var mycanvas = document.getElementById('canvas');
-		var myphoto = document.getElementById('photo');
-		var base_data = "";
-
-		function sendRequest(base64Data) {
-			var type = "json";
-			if (base64Data != "" || base64Data != null) {
-				if (type == "imgtobase") {
-					$(".res-part").html("");
-					$(".res-part").html(base64Data);
-				} else if (type == "basetoimg") {
-					var imageData = $("#imgstring").val();
-					$(".res-part").html("");
-					$(".res-part").append("<img src='data:image/jpeg;base64," + imageData + "' alt='' />");
-				} else {
-					var url = $("#url").val();
-					$("#loading").show();
-					$.ajax({
-						url: url,
-						type: "post",
-						cache: false,
-						async: true,
-						crossDomain: true,
-						headers: {
-							'Content-Type': 'application/json',
-							'Access-Control-Allow-Origin': '*'
-						},
-						data: JSON.stringify({
-							image: base64Data
-						}),
-						success: function (res) {
-							$(".res-part").html("");
-							$(".res-part2").html("");
-							var imageData = res.image;
-							$(".res-part2").append("<img class='resp-img' src='data:image/jpeg;base64," +
-								imageData + "' alt='' />");
-							// $(".res-part").html("<pre>" + JSON.stringify(res[0], undefined, 2) + "</pre>");
-							$("#loading").hide();
-						}
-					});
-				}
-			}
-		}
-
-		$(document).ready(function () {
-			$("#loading").hide();
-
-			$('#send').click(function (evt) {
-				sendRequest(base_data);
-			});
-
-			$('#uload').click(function (evt) {
-				$('#fileinput').focus().trigger('click');
-			});
-			$("#fileinput").change(function () {
-				if (this.files && this.files[0]) {
-					var reader = new FileReader();
-					reader.onload = function (e) {
-						var url = e.target.result;
-						var img = new Image();
-						img.crossOrigin = 'Anonymous';
-						img.onload = function () {
-							var canvas = document.createElement('CANVAS');
-							var ctx = canvas.getContext('2d');
-							canvas.height = this.height;
-							canvas.width = this.width;
-							ctx.drawImage(this, 0, 0);
-							base_data = canvas.toDataURL('image/jpeg', 1.0).replace(
-								/^data:image.+;base64,/, '');
-							canvas = null;
-						};
-						img.src = url;
-						$('#photo').attr('src', url);
-						$('#photo').show();
-						$('#video').hide();
-					}
-					reader.readAsDataURL(this.files[0]);
-				}
-			});
-		});
-	</script>
-</body>
-
-</html>
\ No newline at end of file
diff --git a/spaces/EuroPython2022/mmocr-demo/configs/textrecog/crnn/README.md b/spaces/EuroPython2022/mmocr-demo/configs/textrecog/crnn/README.md
deleted file mode 100644
index 52232587e512eb53f16e652e3f3afd0a53686faf..0000000000000000000000000000000000000000
--- a/spaces/EuroPython2022/mmocr-demo/configs/textrecog/crnn/README.md
+++ /dev/null
@@ -1,50 +0,0 @@
-# CRNN
-
-> [An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition](https://arxiv.org/abs/1507.05717)
-
-<!-- [ALGORITHM] -->
-
-## Abstract
-
-Image-based sequence recognition has been a long-standing research topic in computer vision. In this paper, we investigate the problem of scene text recognition, which is among the most important and challenging tasks in image-based sequence recognition. A novel neural network architecture, which integrates feature extraction, sequence modeling and transcription into a unified framework, is proposed. Compared with previous systems for scene text recognition, the proposed architecture possesses four distinctive properties: (1) It is end-to-end trainable, in contrast to most of the existing algorithms whose components are separately trained and tuned. (2) It naturally handles sequences in arbitrary lengths, involving no character segmentation or horizontal scale normalization. (3) It is not confined to any predefined lexicon and achieves remarkable performances in both lexicon-free and lexicon-based scene text recognition tasks. (4) It generates an effective yet much smaller model, which is more practical for real-world application scenarios. The experiments on standard benchmarks, including the IIIT-5K, Street View Text and ICDAR datasets, demonstrate the superiority of the proposed algorithm over the prior arts. Moreover, the proposed algorithm performs well in the task of image-based music score recognition, which evidently verifies the generality of it.
-
-<div align=center>
-<img src="https://user-images.githubusercontent.com/22607038/142797788-6b1cd78d-1dd6-4e02-be32-3dbd257c4992.png"/>
-</div>
-
-## Dataset
-
-### Train Dataset
-
-| trainset | instance_num | repeat_num | note  |
-| :------: | :----------: | :--------: | :---: |
-|  Syn90k  |   8919273    |     1      | synth |
-
-### Test Dataset
-
-| testset | instance_num |   note    |
-| :-----: | :----------: | :-------: |
-| IIIT5K  |     3000     |  regular  |
-|   SVT   |     647      |  regular  |
-|  IC13   |     1015     |  regular  |
-|  IC15   |     2077     | irregular |
-|  SVTP   |     645      | irregular |
-|  CT80   |     288      | irregular |
-
-## Results and models
-
-|                         methods                          |        | Regular Text |      |     |      | Irregular Text |      |                                             download                                              |
-| :------------------------------------------------------: | :----: | :----------: | :--: | :-: | :--: | :------------: | :--: | :-----------------------------------------------------------------------------------------------: |
-|                         methods                          | IIIT5K |     SVT      | IC13 |     | IC15 |      SVTP      | CT80 |                                                                                                   |
-| [CRNN](/configs/textrecog/crnn/crnn_academic_dataset.py) |  80.5  |     81.5     | 86.5 |     | 54.1 |      59.1      | 55.6 | [model](https://download.openmmlab.com/mmocr/textrecog/crnn/crnn_academic-a723a1c5.pth) \| [log](https://download.openmmlab.com/mmocr/textrecog/crnn/20210326_111035.log.json) |
-
-## Citation
-
-```bibtex
-@article{shi2016end,
-  title={An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition},
-  author={Shi, Baoguang and Bai, Xiang and Yao, Cong},
-  journal={IEEE transactions on pattern analysis and machine intelligence},
-  year={2016}
-}
-```
diff --git a/spaces/FFusion/FFXL-SDXL-Convert-diffusers/convert.py b/spaces/FFusion/FFXL-SDXL-Convert-diffusers/convert.py
deleted file mode 100644
index 6f4877ae1204be1ad3142bf583ff0e24eac88b7e..0000000000000000000000000000000000000000
--- a/spaces/FFusion/FFXL-SDXL-Convert-diffusers/convert.py
+++ /dev/null
@@ -1,69 +0,0 @@
-import gradio as gr
-import requests
-import os
-import shutil
-from pathlib import Path
-from typing import Any
-from tempfile import TemporaryDirectory
-from typing import Optional
-
-import torch
-from io import BytesIO
-
-from huggingface_hub import CommitInfo, Discussion, HfApi, hf_hub_download
-from huggingface_hub.file_download import repo_folder_name
-from diffusers import StableDiffusionXLPipeline
-from transformers import CONFIG_MAPPING
-
-
-COMMIT_MESSAGE = " This PR adds fp32 and fp16 weights in safetensors format to {}"
-
-
-def convert_single(model_id: str, filename: str, folder: str, progress: Any, token: str):
-    progress(0, desc="Downloading model")
-    local_file = os.path.join(model_id, filename)
-    ckpt_file = local_file if os.path.isfile(local_file) else hf_hub_download(repo_id=model_id, filename=filename, token=token)
-
-    pipeline = StableDiffusionXLPipeline.from_single_file(ckpt_file)
-
-    pipeline.save_pretrained(folder, safe_serialization=True)
-    pipeline = pipeline.to(torch_dtype=torch.float16)
-    pipeline.save_pretrained(folder, safe_serialization=True, variant="fp16")
-
-    return folder
-
-
-def previous_pr(api: "HfApi", model_id: str, pr_title: str) -> Optional["Discussion"]:
-    try:
-        discussions = api.get_repo_discussions(repo_id=model_id)
-    except Exception:
-        return None
-    for discussion in discussions:
-        if discussion.status == "open" and discussion.is_pull_request and discussion.title == pr_title:
-            details = api.get_discussion_details(repo_id=model_id, discussion_num=discussion.num)
-            if details.target_branch == "refs/heads/main":
-                return discussion
-
-
-def convert(token: str, model_id: str, filename: str, progress=gr.Progress()):
-    api = HfApi()
-
-    pr_title = "Adding `diffusers` weights of this model"
-
-    with TemporaryDirectory() as d:
-        folder = os.path.join(d, repo_folder_name(repo_id=model_id, repo_type="models"))
-        os.makedirs(folder)
-        new_pr = None
-        try:
-            folder = convert_single(model_id, filename, folder, progress, token)
-            progress(0.7, desc="Uploading to Hub")
-            new_pr  = api.upload_folder(folder_path=folder, path_in_repo="./", repo_id=model_id, repo_type="model", token=token, commit_message=pr_title, commit_description=COMMIT_MESSAGE.format(model_id), create_pr=True)
-            pr_number = new_pr.split("%2F")[-1].split("/")[0]
-            link = f"Pr created at: {'https://huggingface.co/' + os.path.join(model_id, 'discussions', pr_number)}"
-            progress(1, desc="Done")
-        except Exception as e:
-            raise gr.exceptions.Error(str(e))
-        finally:
-            shutil.rmtree(folder)
-
-        return link
diff --git a/spaces/FelixLuoX/codeformer/CodeFormer/basicsr/archs/vqgan_arch.py b/spaces/FelixLuoX/codeformer/CodeFormer/basicsr/archs/vqgan_arch.py
deleted file mode 100644
index f6dfcf4c9983b431f0a978701e5ddd9598faf381..0000000000000000000000000000000000000000
--- a/spaces/FelixLuoX/codeformer/CodeFormer/basicsr/archs/vqgan_arch.py
+++ /dev/null
@@ -1,435 +0,0 @@
-'''
-VQGAN code, adapted from the original created by the Unleashing Transformers authors:
-https://github.com/samb-t/unleashing-transformers/blob/master/models/vqgan.py
-
-'''
-import numpy as np
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-import copy
-from basicsr.utils import get_root_logger
-from basicsr.utils.registry import ARCH_REGISTRY
-
-def normalize(in_channels):
-    return torch.nn.GroupNorm(num_groups=32, num_channels=in_channels, eps=1e-6, affine=True)
-    
-
-@torch.jit.script
-def swish(x):
-    return x*torch.sigmoid(x)
-
-
-#  Define VQVAE classes
-class VectorQuantizer(nn.Module):
-    def __init__(self, codebook_size, emb_dim, beta):
-        super(VectorQuantizer, self).__init__()
-        self.codebook_size = codebook_size  # number of embeddings
-        self.emb_dim = emb_dim  # dimension of embedding
-        self.beta = beta  # commitment cost used in loss term, beta * ||z_e(x)-sg[e]||^2
-        self.embedding = nn.Embedding(self.codebook_size, self.emb_dim)
-        self.embedding.weight.data.uniform_(-1.0 / self.codebook_size, 1.0 / self.codebook_size)
-
-    def forward(self, z):
-        # reshape z -> (batch, height, width, channel) and flatten
-        z = z.permute(0, 2, 3, 1).contiguous()
-        z_flattened = z.view(-1, self.emb_dim)
-
-        # distances from z to embeddings e_j (z - e)^2 = z^2 + e^2 - 2 e * z
-        d = (z_flattened ** 2).sum(dim=1, keepdim=True) + (self.embedding.weight**2).sum(1) - \
-            2 * torch.matmul(z_flattened, self.embedding.weight.t())
-
-        mean_distance = torch.mean(d)
-        # find closest encodings
-        # min_encoding_indices = torch.argmin(d, dim=1).unsqueeze(1)
-        min_encoding_scores, min_encoding_indices = torch.topk(d, 1, dim=1, largest=False)
-        # [0-1], higher score, higher confidence
-        min_encoding_scores = torch.exp(-min_encoding_scores/10)
-
-        min_encodings = torch.zeros(min_encoding_indices.shape[0], self.codebook_size).to(z)
-        min_encodings.scatter_(1, min_encoding_indices, 1)
-
-        # get quantized latent vectors
-        z_q = torch.matmul(min_encodings, self.embedding.weight).view(z.shape)
-        # compute loss for embedding
-        loss = torch.mean((z_q.detach()-z)**2) + self.beta * torch.mean((z_q - z.detach()) ** 2)
-        # preserve gradients
-        z_q = z + (z_q - z).detach()
-
-        # perplexity
-        e_mean = torch.mean(min_encodings, dim=0)
-        perplexity = torch.exp(-torch.sum(e_mean * torch.log(e_mean + 1e-10)))
-        # reshape back to match original input shape
-        z_q = z_q.permute(0, 3, 1, 2).contiguous()
-
-        return z_q, loss, {
-            "perplexity": perplexity,
-            "min_encodings": min_encodings,
-            "min_encoding_indices": min_encoding_indices,
-            "min_encoding_scores": min_encoding_scores,
-            "mean_distance": mean_distance
-            }
-
-    def get_codebook_feat(self, indices, shape):
-        # input indices: batch*token_num -> (batch*token_num)*1
-        # shape: batch, height, width, channel
-        indices = indices.view(-1,1)
-        min_encodings = torch.zeros(indices.shape[0], self.codebook_size).to(indices)
-        min_encodings.scatter_(1, indices, 1)
-        # get quantized latent vectors
-        z_q = torch.matmul(min_encodings.float(), self.embedding.weight)
-
-        if shape is not None:  # reshape back to match original input shape
-            z_q = z_q.view(shape).permute(0, 3, 1, 2).contiguous()
-
-        return z_q
-
-
-class GumbelQuantizer(nn.Module):
-    def __init__(self, codebook_size, emb_dim, num_hiddens, straight_through=False, kl_weight=5e-4, temp_init=1.0):
-        super().__init__()
-        self.codebook_size = codebook_size  # number of embeddings
-        self.emb_dim = emb_dim  # dimension of embedding
-        self.straight_through = straight_through
-        self.temperature = temp_init
-        self.kl_weight = kl_weight
-        self.proj = nn.Conv2d(num_hiddens, codebook_size, 1)  # projects last encoder layer to quantized logits
-        self.embed = nn.Embedding(codebook_size, emb_dim)
-
-    def forward(self, z):
-        hard = self.straight_through if self.training else True
-
-        logits = self.proj(z)
-
-        soft_one_hot = F.gumbel_softmax(logits, tau=self.temperature, dim=1, hard=hard)
-
-        z_q = torch.einsum("b n h w, n d -> b d h w", soft_one_hot, self.embed.weight)
-
-        # + kl divergence to the prior loss
-        qy = F.softmax(logits, dim=1)
-        diff = self.kl_weight * torch.sum(qy * torch.log(qy * self.codebook_size + 1e-10), dim=1).mean()
-        min_encoding_indices = soft_one_hot.argmax(dim=1)
-
-        return z_q, diff, {
-            "min_encoding_indices": min_encoding_indices
-        }
-
-
-class Downsample(nn.Module):
-    def __init__(self, in_channels):
-        super().__init__()
-        self.conv = torch.nn.Conv2d(in_channels, in_channels, kernel_size=3, stride=2, padding=0)
-
-    def forward(self, x):
-        pad = (0, 1, 0, 1)
-        x = torch.nn.functional.pad(x, pad, mode="constant", value=0)
-        x = self.conv(x)
-        return x
-
-
-class Upsample(nn.Module):
-    def __init__(self, in_channels):
-        super().__init__()
-        self.conv = nn.Conv2d(in_channels, in_channels, kernel_size=3, stride=1, padding=1)
-
-    def forward(self, x):
-        x = F.interpolate(x, scale_factor=2.0, mode="nearest")
-        x = self.conv(x)
-
-        return x
-
-
-class ResBlock(nn.Module):
-    def __init__(self, in_channels, out_channels=None):
-        super(ResBlock, self).__init__()
-        self.in_channels = in_channels
-        self.out_channels = in_channels if out_channels is None else out_channels
-        self.norm1 = normalize(in_channels)
-        self.conv1 = nn.Conv2d(in_channels, out_channels, kernel_size=3, stride=1, padding=1)
-        self.norm2 = normalize(out_channels)
-        self.conv2 = nn.Conv2d(out_channels, out_channels, kernel_size=3, stride=1, padding=1)
-        if self.in_channels != self.out_channels:
-            self.conv_out = nn.Conv2d(in_channels, out_channels, kernel_size=1, stride=1, padding=0)
-
-    def forward(self, x_in):
-        x = x_in
-        x = self.norm1(x)
-        x = swish(x)
-        x = self.conv1(x)
-        x = self.norm2(x)
-        x = swish(x)
-        x = self.conv2(x)
-        if self.in_channels != self.out_channels:
-            x_in = self.conv_out(x_in)
-
-        return x + x_in
-
-
-class AttnBlock(nn.Module):
-    def __init__(self, in_channels):
-        super().__init__()
-        self.in_channels = in_channels
-
-        self.norm = normalize(in_channels)
-        self.q = torch.nn.Conv2d(
-            in_channels,
-            in_channels,
-            kernel_size=1,
-            stride=1,
-            padding=0
-        )
-        self.k = torch.nn.Conv2d(
-            in_channels,
-            in_channels,
-            kernel_size=1,
-            stride=1,
-            padding=0
-        )
-        self.v = torch.nn.Conv2d(
-            in_channels,
-            in_channels,
-            kernel_size=1,
-            stride=1,
-            padding=0
-        )
-        self.proj_out = torch.nn.Conv2d(
-            in_channels,
-            in_channels,
-            kernel_size=1,
-            stride=1,
-            padding=0
-        )
-
-    def forward(self, x):
-        h_ = x
-        h_ = self.norm(h_)
-        q = self.q(h_)
-        k = self.k(h_)
-        v = self.v(h_)
-
-        # compute attention
-        b, c, h, w = q.shape
-        q = q.reshape(b, c, h*w)
-        q = q.permute(0, 2, 1)   
-        k = k.reshape(b, c, h*w)
-        w_ = torch.bmm(q, k) 
-        w_ = w_ * (int(c)**(-0.5))
-        w_ = F.softmax(w_, dim=2)
-
-        # attend to values
-        v = v.reshape(b, c, h*w)
-        w_ = w_.permute(0, 2, 1) 
-        h_ = torch.bmm(v, w_)
-        h_ = h_.reshape(b, c, h, w)
-
-        h_ = self.proj_out(h_)
-
-        return x+h_
-
-
-class Encoder(nn.Module):
-    def __init__(self, in_channels, nf, emb_dim, ch_mult, num_res_blocks, resolution, attn_resolutions):
-        super().__init__()
-        self.nf = nf
-        self.num_resolutions = len(ch_mult)
-        self.num_res_blocks = num_res_blocks
-        self.resolution = resolution
-        self.attn_resolutions = attn_resolutions
-
-        curr_res = self.resolution
-        in_ch_mult = (1,)+tuple(ch_mult)
-
-        blocks = []
-        # initial convultion
-        blocks.append(nn.Conv2d(in_channels, nf, kernel_size=3, stride=1, padding=1))
-
-        # residual and downsampling blocks, with attention on smaller res (16x16)
-        for i in range(self.num_resolutions):
-            block_in_ch = nf * in_ch_mult[i]
-            block_out_ch = nf * ch_mult[i]
-            for _ in range(self.num_res_blocks):
-                blocks.append(ResBlock(block_in_ch, block_out_ch))
-                block_in_ch = block_out_ch
-                if curr_res in attn_resolutions:
-                    blocks.append(AttnBlock(block_in_ch))
-
-            if i != self.num_resolutions - 1:
-                blocks.append(Downsample(block_in_ch))
-                curr_res = curr_res // 2
-
-        # non-local attention block
-        blocks.append(ResBlock(block_in_ch, block_in_ch))
-        blocks.append(AttnBlock(block_in_ch))
-        blocks.append(ResBlock(block_in_ch, block_in_ch))
-
-        # normalise and convert to latent size
-        blocks.append(normalize(block_in_ch))
-        blocks.append(nn.Conv2d(block_in_ch, emb_dim, kernel_size=3, stride=1, padding=1))
-        self.blocks = nn.ModuleList(blocks)
-
-    def forward(self, x):
-        for block in self.blocks:
-            x = block(x)
-            
-        return x
-
-
-class Generator(nn.Module):
-    def __init__(self, nf, emb_dim, ch_mult, res_blocks, img_size, attn_resolutions):
-        super().__init__()
-        self.nf = nf 
-        self.ch_mult = ch_mult 
-        self.num_resolutions = len(self.ch_mult)
-        self.num_res_blocks = res_blocks
-        self.resolution = img_size 
-        self.attn_resolutions = attn_resolutions
-        self.in_channels = emb_dim
-        self.out_channels = 3
-        block_in_ch = self.nf * self.ch_mult[-1]
-        curr_res = self.resolution // 2 ** (self.num_resolutions-1)
-
-        blocks = []
-        # initial conv
-        blocks.append(nn.Conv2d(self.in_channels, block_in_ch, kernel_size=3, stride=1, padding=1))
-
-        # non-local attention block
-        blocks.append(ResBlock(block_in_ch, block_in_ch))
-        blocks.append(AttnBlock(block_in_ch))
-        blocks.append(ResBlock(block_in_ch, block_in_ch))
-
-        for i in reversed(range(self.num_resolutions)):
-            block_out_ch = self.nf * self.ch_mult[i]
-
-            for _ in range(self.num_res_blocks):
-                blocks.append(ResBlock(block_in_ch, block_out_ch))
-                block_in_ch = block_out_ch
-
-                if curr_res in self.attn_resolutions:
-                    blocks.append(AttnBlock(block_in_ch))
-
-            if i != 0:
-                blocks.append(Upsample(block_in_ch))
-                curr_res = curr_res * 2
-
-        blocks.append(normalize(block_in_ch))
-        blocks.append(nn.Conv2d(block_in_ch, self.out_channels, kernel_size=3, stride=1, padding=1))
-
-        self.blocks = nn.ModuleList(blocks)
-   
-
-    def forward(self, x):
-        for block in self.blocks:
-            x = block(x)
-            
-        return x
-
-  
-@ARCH_REGISTRY.register()
-class VQAutoEncoder(nn.Module):
-    def __init__(self, img_size, nf, ch_mult, quantizer="nearest", res_blocks=2, attn_resolutions=[16], codebook_size=1024, emb_dim=256,
-                beta=0.25, gumbel_straight_through=False, gumbel_kl_weight=1e-8, model_path=None):
-        super().__init__()
-        logger = get_root_logger()
-        self.in_channels = 3 
-        self.nf = nf 
-        self.n_blocks = res_blocks 
-        self.codebook_size = codebook_size
-        self.embed_dim = emb_dim
-        self.ch_mult = ch_mult
-        self.resolution = img_size
-        self.attn_resolutions = attn_resolutions
-        self.quantizer_type = quantizer
-        self.encoder = Encoder(
-            self.in_channels,
-            self.nf,
-            self.embed_dim,
-            self.ch_mult,
-            self.n_blocks,
-            self.resolution,
-            self.attn_resolutions
-        )
-        if self.quantizer_type == "nearest":
-            self.beta = beta #0.25
-            self.quantize = VectorQuantizer(self.codebook_size, self.embed_dim, self.beta)
-        elif self.quantizer_type == "gumbel":
-            self.gumbel_num_hiddens = emb_dim
-            self.straight_through = gumbel_straight_through
-            self.kl_weight = gumbel_kl_weight
-            self.quantize = GumbelQuantizer(
-                self.codebook_size,
-                self.embed_dim,
-                self.gumbel_num_hiddens,
-                self.straight_through,
-                self.kl_weight
-            )
-        self.generator = Generator(
-            self.nf, 
-            self.embed_dim,
-            self.ch_mult, 
-            self.n_blocks, 
-            self.resolution, 
-            self.attn_resolutions
-        )
-
-        if model_path is not None:
-            chkpt = torch.load(model_path, map_location='cpu')
-            if 'params_ema' in chkpt:
-                self.load_state_dict(torch.load(model_path, map_location='cpu')['params_ema'])
-                logger.info(f'vqgan is loaded from: {model_path} [params_ema]')
-            elif 'params' in chkpt:
-                self.load_state_dict(torch.load(model_path, map_location='cpu')['params'])
-                logger.info(f'vqgan is loaded from: {model_path} [params]')
-            else:
-                raise ValueError(f'Wrong params!')
-
-
-    def forward(self, x):
-        x = self.encoder(x)
-        quant, codebook_loss, quant_stats = self.quantize(x)
-        x = self.generator(quant)
-        return x, codebook_loss, quant_stats
-
-
-
-# patch based discriminator
-@ARCH_REGISTRY.register()
-class VQGANDiscriminator(nn.Module):
-    def __init__(self, nc=3, ndf=64, n_layers=4, model_path=None):
-        super().__init__()
-
-        layers = [nn.Conv2d(nc, ndf, kernel_size=4, stride=2, padding=1), nn.LeakyReLU(0.2, True)]
-        ndf_mult = 1
-        ndf_mult_prev = 1
-        for n in range(1, n_layers):  # gradually increase the number of filters
-            ndf_mult_prev = ndf_mult
-            ndf_mult = min(2 ** n, 8)
-            layers += [
-                nn.Conv2d(ndf * ndf_mult_prev, ndf * ndf_mult, kernel_size=4, stride=2, padding=1, bias=False),
-                nn.BatchNorm2d(ndf * ndf_mult),
-                nn.LeakyReLU(0.2, True)
-            ]
-
-        ndf_mult_prev = ndf_mult
-        ndf_mult = min(2 ** n_layers, 8)
-
-        layers += [
-            nn.Conv2d(ndf * ndf_mult_prev, ndf * ndf_mult, kernel_size=4, stride=1, padding=1, bias=False),
-            nn.BatchNorm2d(ndf * ndf_mult),
-            nn.LeakyReLU(0.2, True)
-        ]
-
-        layers += [
-            nn.Conv2d(ndf * ndf_mult, 1, kernel_size=4, stride=1, padding=1)]  # output 1 channel prediction map
-        self.main = nn.Sequential(*layers)
-
-        if model_path is not None:
-            chkpt = torch.load(model_path, map_location='cpu')
-            if 'params_d' in chkpt:
-                self.load_state_dict(torch.load(model_path, map_location='cpu')['params_d'])
-            elif 'params' in chkpt:
-                self.load_state_dict(torch.load(model_path, map_location='cpu')['params'])
-            else:
-                raise ValueError(f'Wrong params!')
-
-    def forward(self, x):
-        return self.main(x)
\ No newline at end of file
diff --git a/spaces/Felladrin/Web-LLM-Mistral-7B-OpenOrca/dist/index.9744ff88.css b/spaces/Felladrin/Web-LLM-Mistral-7B-OpenOrca/dist/index.9744ff88.css
deleted file mode 100644
index 7f27ffbb5e0ba8eded3d8e1429eb083ae4551df1..0000000000000000000000000000000000000000
--- a/spaces/Felladrin/Web-LLM-Mistral-7B-OpenOrca/dist/index.9744ff88.css
+++ /dev/null
@@ -1 +0,0 @@
-.chatui{border:2px solid #ddd;border-radius:5px;flex-flow:column wrap;justify-content:space-between;width:100%;max-width:867px;height:600px;margin:25px 10px;display:flex;box-shadow:0 15px 15px -5px #0003}s .chatui-header{color:#666;background:#eee;border-bottom:2px solid #ddd;justify-content:space-between;padding:10px;display:flex}.chatui-chat{flex:1;padding:10px;overflow-y:auto}.chatui-chat::-webkit-scrollbar{width:6px}.chatui-chat::-webkit-scrollbar-track{background:#ddd}.chatui-chat::-webkit-scrollbar-thumb{background:#bdbdbd}.msg{align-items:flex-end;margin-bottom:10px;display:flex}.msg:last-of-type{margin:0}.msg-bubble{background:#ececec;border-radius:15px;max-width:450px;padding:15px}.left-msg .msg-bubble{border-bottom-left-radius:0}.error-msg .msg-bubble{color:#f15959;border-bottom-left-radius:0}.init-msg .msg-bubble{border-bottom-left-radius:0}.right-msg{flex-direction:row-reverse}.right-msg .msg-bubble{color:#fff;background:#579ffb;border-bottom-right-radius:0}.chatui-inputarea{background:#eee;border-top:2px solid #ddd;padding:10px;display:flex}.chatui-inputarea *{border:none;border-radius:3px;padding:10px;font-size:1em}.chatui-input{background:#ddd;flex:1}.chatui-reset-btn{cursor:pointer;background:#ececec;border-radius:8px;width:200px;margin-left:10px;font-weight:700}.chatui-reset-btn:hover{background:#dcdada}.chatui-send-btn{color:#fff;cursor:pointer;background:#579ffb;margin-left:10px;font-weight:700}.chatui-send-btn:hover{background:#577bfb}.chatui-chat{background-color:#fcfcfe}
\ No newline at end of file
diff --git a/spaces/FrankZxShen/so-vits-svc-models-pcr/pretrain/meta.py b/spaces/FrankZxShen/so-vits-svc-models-pcr/pretrain/meta.py
deleted file mode 100644
index cc35dd3c0dfe8436e7d635f2db507cedca75ed49..0000000000000000000000000000000000000000
--- a/spaces/FrankZxShen/so-vits-svc-models-pcr/pretrain/meta.py
+++ /dev/null
@@ -1,31 +0,0 @@
-def download_dict():
-    return {
-        "vec768l12": {
-            "url": "https://ibm.ent.box.com/shared/static/z1wgl1stco8ffooyatzdwsqn2psd9lrr",
-            "output": "./pretrain/checkpoint_best_legacy_500.pt"
-        },
-        "vec256l9": {
-            "url": "https://ibm.ent.box.com/shared/static/z1wgl1stco8ffooyatzdwsqn2psd9lrr",
-            "output": "./pretrain/checkpoint_best_legacy_500.pt"
-        },
-        "hubertsoft": {
-            "url": "https://github.com/bshall/hubert/releases/download/v0.1/hubert-soft-0d54a1f4.pt",
-            "output": "./pretrain/hubert-soft-0d54a1f4.pt"
-        },
-        "whisper-ppg": {
-            "url": "https://openaipublic.azureedge.net/main/whisper/models/345ae4da62f9b3d59415adc60127b97c714f32e89e936602e85993674d08dcb1/medium.pt",
-            "output": "./pretrain/medium.pt"
-        }
-    }
-
-
-def get_speech_encoder(config_path="configs/config.json"):
-    import json
-
-    with open(config_path, "r") as f:
-        data = f.read()
-        config = json.loads(data)
-        speech_encoder = config["model"]["speech_encoder"]
-        dict = download_dict()
-
-        return dict[speech_encoder]["url"], dict[speech_encoder]["output"]
diff --git a/spaces/GipAdonimus/Real-Time-Voice-Cloning/synthesizer/utils/numbers.py b/spaces/GipAdonimus/Real-Time-Voice-Cloning/synthesizer/utils/numbers.py
deleted file mode 100644
index 75020a0bd732830f603d7c7d250c9e087033cc24..0000000000000000000000000000000000000000
--- a/spaces/GipAdonimus/Real-Time-Voice-Cloning/synthesizer/utils/numbers.py
+++ /dev/null
@@ -1,68 +0,0 @@
-import re
-import inflect
-
-_inflect = inflect.engine()
-_comma_number_re = re.compile(r"([0-9][0-9\,]+[0-9])")
-_decimal_number_re = re.compile(r"([0-9]+\.[0-9]+)")
-_pounds_re = re.compile(r"£([0-9\,]*[0-9]+)")
-_dollars_re = re.compile(r"\$([0-9\.\,]*[0-9]+)")
-_ordinal_re = re.compile(r"[0-9]+(st|nd|rd|th)")
-_number_re = re.compile(r"[0-9]+")
-
-
-def _remove_commas(m):
-  return m.group(1).replace(",", "")
-
-
-def _expand_decimal_point(m):
-  return m.group(1).replace(".", " point ")
-
-
-def _expand_dollars(m):
-  match = m.group(1)
-  parts = match.split(".")
-  if len(parts) > 2:
-    return match + " dollars"  # Unexpected format
-  dollars = int(parts[0]) if parts[0] else 0
-  cents = int(parts[1]) if len(parts) > 1 and parts[1] else 0
-  if dollars and cents:
-    dollar_unit = "dollar" if dollars == 1 else "dollars"
-    cent_unit = "cent" if cents == 1 else "cents"
-    return "%s %s, %s %s" % (dollars, dollar_unit, cents, cent_unit)
-  elif dollars:
-    dollar_unit = "dollar" if dollars == 1 else "dollars"
-    return "%s %s" % (dollars, dollar_unit)
-  elif cents:
-    cent_unit = "cent" if cents == 1 else "cents"
-    return "%s %s" % (cents, cent_unit)
-  else:
-    return "zero dollars"
-
-
-def _expand_ordinal(m):
-  return _inflect.number_to_words(m.group(0))
-
-
-def _expand_number(m):
-  num = int(m.group(0))
-  if num > 1000 and num < 3000:
-    if num == 2000:
-      return "two thousand"
-    elif num > 2000 and num < 2010:
-      return "two thousand " + _inflect.number_to_words(num % 100)
-    elif num % 100 == 0:
-      return _inflect.number_to_words(num // 100) + " hundred"
-    else:
-      return _inflect.number_to_words(num, andword="", zero="oh", group=2).replace(", ", " ")
-  else:
-    return _inflect.number_to_words(num, andword="")
-
-
-def normalize_numbers(text):
-  text = re.sub(_comma_number_re, _remove_commas, text)
-  text = re.sub(_pounds_re, r"\1 pounds", text)
-  text = re.sub(_dollars_re, _expand_dollars, text)
-  text = re.sub(_decimal_number_re, _expand_decimal_point, text)
-  text = re.sub(_ordinal_re, _expand_ordinal, text)
-  text = re.sub(_number_re, _expand_number, text)
-  return text
diff --git a/spaces/Gmq-x/gpt-academic/crazy_functions/test_project/python/dqn/dqn.py b/spaces/Gmq-x/gpt-academic/crazy_functions/test_project/python/dqn/dqn.py
deleted file mode 100644
index 6cea64d39baa7ff4c1e549869aaa4b0ae17779a9..0000000000000000000000000000000000000000
--- a/spaces/Gmq-x/gpt-academic/crazy_functions/test_project/python/dqn/dqn.py
+++ /dev/null
@@ -1,245 +0,0 @@
-from typing import Any, Dict, List, Optional, Tuple, Type, Union
-
-import gym
-import numpy as np
-import torch as th
-from torch.nn import functional as F
-
-from stable_baselines3.common import logger
-from stable_baselines3.common.off_policy_algorithm import OffPolicyAlgorithm
-from stable_baselines3.common.preprocessing import maybe_transpose
-from stable_baselines3.common.type_aliases import GymEnv, MaybeCallback, Schedule
-from stable_baselines3.common.utils import get_linear_fn, is_vectorized_observation, polyak_update
-from stable_baselines3.dqn.policies import DQNPolicy
-
-
-class DQN(OffPolicyAlgorithm):
-    """
-    Deep Q-Network (DQN)
-
-    Paper: https://arxiv.org/abs/1312.5602, https://www.nature.com/articles/nature14236
-    Default hyperparameters are taken from the nature paper,
-    except for the optimizer and learning rate that were taken from Stable Baselines defaults.
-
-    :param policy: The policy model to use (MlpPolicy, CnnPolicy, ...)
-    :param env: The environment to learn from (if registered in Gym, can be str)
-    :param learning_rate: The learning rate, it can be a function
-        of the current progress remaining (from 1 to 0)
-    :param buffer_size: size of the replay buffer
-    :param learning_starts: how many steps of the model to collect transitions for before learning starts
-    :param batch_size: Minibatch size for each gradient update
-    :param tau: the soft update coefficient ("Polyak update", between 0 and 1) default 1 for hard update
-    :param gamma: the discount factor
-    :param train_freq: Update the model every ``train_freq`` steps. Alternatively pass a tuple of frequency and unit
-        like ``(5, "step")`` or ``(2, "episode")``.
-    :param gradient_steps: How many gradient steps to do after each rollout (see ``train_freq``)
-        Set to ``-1`` means to do as many gradient steps as steps done in the environment
-        during the rollout.
-    :param optimize_memory_usage: Enable a memory efficient variant of the replay buffer
-        at a cost of more complexity.
-        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195
-    :param target_update_interval: update the target network every ``target_update_interval``
-        environment steps.
-    :param exploration_fraction: fraction of entire training period over which the exploration rate is reduced
-    :param exploration_initial_eps: initial value of random action probability
-    :param exploration_final_eps: final value of random action probability
-    :param max_grad_norm: The maximum value for the gradient clipping
-    :param tensorboard_log: the log location for tensorboard (if None, no logging)
-    :param create_eval_env: Whether to create a second environment that will be
-        used for evaluating the agent periodically. (Only available when passing string for the environment)
-    :param policy_kwargs: additional arguments to be passed to the policy on creation
-    :param verbose: the verbosity level: 0 no output, 1 info, 2 debug
-    :param seed: Seed for the pseudo random generators
-    :param device: Device (cpu, cuda, ...) on which the code should be run.
-        Setting it to auto, the code will be run on the GPU if possible.
-    :param _init_setup_model: Whether or not to build the network at the creation of the instance
-    """
-
-    def __init__(
-        self,
-        policy: Union[str, Type[DQNPolicy]],
-        env: Union[GymEnv, str],
-        learning_rate: Union[float, Schedule] = 1e-4,
-        buffer_size: int = 1000000,
-        learning_starts: int = 50000,
-        batch_size: Optional[int] = 32,
-        tau: float = 1.0,
-        gamma: float = 0.99,
-        train_freq: Union[int, Tuple[int, str]] = 4,
-        gradient_steps: int = 1,
-        optimize_memory_usage: bool = False,
-        target_update_interval: int = 10000,
-        exploration_fraction: float = 0.1,
-        exploration_initial_eps: float = 1.0,
-        exploration_final_eps: float = 0.05,
-        max_grad_norm: float = 10,
-        tensorboard_log: Optional[str] = None,
-        create_eval_env: bool = False,
-        policy_kwargs: Optional[Dict[str, Any]] = None,
-        verbose: int = 0,
-        seed: Optional[int] = None,
-        device: Union[th.device, str] = "auto",
-        _init_setup_model: bool = True,
-    ):
-
-        super(DQN, self).__init__(
-            policy,
-            env,
-            DQNPolicy,
-            learning_rate,
-            buffer_size,
-            learning_starts,
-            batch_size,
-            tau,
-            gamma,
-            train_freq,
-            gradient_steps,
-            action_noise=None,  # No action noise
-            policy_kwargs=policy_kwargs,
-            tensorboard_log=tensorboard_log,
-            verbose=verbose,
-            device=device,
-            create_eval_env=create_eval_env,
-            seed=seed,
-            sde_support=False,
-            optimize_memory_usage=optimize_memory_usage,
-            supported_action_spaces=(gym.spaces.Discrete,),
-        )
-
-        self.exploration_initial_eps = exploration_initial_eps
-        self.exploration_final_eps = exploration_final_eps
-        self.exploration_fraction = exploration_fraction
-        self.target_update_interval = target_update_interval
-        self.max_grad_norm = max_grad_norm
-        # "epsilon" for the epsilon-greedy exploration
-        self.exploration_rate = 0.0
-        # Linear schedule will be defined in `_setup_model()`
-        self.exploration_schedule = None
-        self.q_net, self.q_net_target = None, None
-
-        if _init_setup_model:
-            self._setup_model()
-
-    def _setup_model(self) -> None:
-        super(DQN, self)._setup_model()
-        self._create_aliases()
-        self.exploration_schedule = get_linear_fn(
-            self.exploration_initial_eps, self.exploration_final_eps, self.exploration_fraction
-        )
-
-    def _create_aliases(self) -> None:
-        self.q_net = self.policy.q_net
-        self.q_net_target = self.policy.q_net_target
-
-    def _on_step(self) -> None:
-        """
-        Update the exploration rate and target network if needed.
-        This method is called in ``collect_rollouts()`` after each step in the environment.
-        """
-        if self.num_timesteps % self.target_update_interval == 0:
-            polyak_update(self.q_net.parameters(), self.q_net_target.parameters(), self.tau)
-
-        self.exploration_rate = self.exploration_schedule(self._current_progress_remaining)
-        logger.record("rollout/exploration rate", self.exploration_rate)
-
-    def train(self, gradient_steps: int, batch_size: int = 100) -> None:
-        # Update learning rate according to schedule
-        self._update_learning_rate(self.policy.optimizer)
-
-        losses = []
-        for _ in range(gradient_steps):
-            # Sample replay buffer
-            replay_data = self.replay_buffer.sample(batch_size, env=self._vec_normalize_env)
-
-            with th.no_grad():
-                # Compute the next Q-values using the target network
-                next_q_values = self.q_net_target(replay_data.next_observations)
-                # Follow greedy policy: use the one with the highest value
-                next_q_values, _ = next_q_values.max(dim=1)
-                # Avoid potential broadcast issue
-                next_q_values = next_q_values.reshape(-1, 1)
-                # 1-step TD target
-                target_q_values = replay_data.rewards + (1 - replay_data.dones) * self.gamma * next_q_values
-
-            # Get current Q-values estimates
-            current_q_values = self.q_net(replay_data.observations)
-
-            # Retrieve the q-values for the actions from the replay buffer
-            current_q_values = th.gather(current_q_values, dim=1, index=replay_data.actions.long())
-
-            # Compute Huber loss (less sensitive to outliers)
-            loss = F.smooth_l1_loss(current_q_values, target_q_values)
-            losses.append(loss.item())
-
-            # Optimize the policy
-            self.policy.optimizer.zero_grad()
-            loss.backward()
-            # Clip gradient norm
-            th.nn.utils.clip_grad_norm_(self.policy.parameters(), self.max_grad_norm)
-            self.policy.optimizer.step()
-
-        # Increase update counter
-        self._n_updates += gradient_steps
-
-        logger.record("train/n_updates", self._n_updates, exclude="tensorboard")
-        logger.record("train/loss", np.mean(losses))
-
-    def predict(
-        self,
-        observation: np.ndarray,
-        state: Optional[np.ndarray] = None,
-        mask: Optional[np.ndarray] = None,
-        deterministic: bool = False,
-    ) -> Tuple[np.ndarray, Optional[np.ndarray]]:
-        """
-        Overrides the base_class predict function to include epsilon-greedy exploration.
-
-        :param observation: the input observation
-        :param state: The last states (can be None, used in recurrent policies)
-        :param mask: The last masks (can be None, used in recurrent policies)
-        :param deterministic: Whether or not to return deterministic actions.
-        :return: the model's action and the next state
-            (used in recurrent policies)
-        """
-        if not deterministic and np.random.rand() < self.exploration_rate:
-            if is_vectorized_observation(maybe_transpose(observation, self.observation_space), self.observation_space):
-                n_batch = observation.shape[0]
-                action = np.array([self.action_space.sample() for _ in range(n_batch)])
-            else:
-                action = np.array(self.action_space.sample())
-        else:
-            action, state = self.policy.predict(observation, state, mask, deterministic)
-        return action, state
-
-    def learn(
-        self,
-        total_timesteps: int,
-        callback: MaybeCallback = None,
-        log_interval: int = 4,
-        eval_env: Optional[GymEnv] = None,
-        eval_freq: int = -1,
-        n_eval_episodes: int = 5,
-        tb_log_name: str = "DQN",
-        eval_log_path: Optional[str] = None,
-        reset_num_timesteps: bool = True,
-    ) -> OffPolicyAlgorithm:
-
-        return super(DQN, self).learn(
-            total_timesteps=total_timesteps,
-            callback=callback,
-            log_interval=log_interval,
-            eval_env=eval_env,
-            eval_freq=eval_freq,
-            n_eval_episodes=n_eval_episodes,
-            tb_log_name=tb_log_name,
-            eval_log_path=eval_log_path,
-            reset_num_timesteps=reset_num_timesteps,
-        )
-
-    def _excluded_save_params(self) -> List[str]:
-        return super(DQN, self)._excluded_save_params() + ["q_net", "q_net_target"]
-
-    def _get_torch_save_params(self) -> Tuple[List[str], List[str]]:
-        state_dicts = ["policy", "policy.optimizer"]
-
-        return state_dicts, []
diff --git a/spaces/GodParticle69/minor_demo/mrcnn/visualize.py b/spaces/GodParticle69/minor_demo/mrcnn/visualize.py
deleted file mode 100644
index ebddf729b364657e304af0b66c5d3a44eedd404f..0000000000000000000000000000000000000000
--- a/spaces/GodParticle69/minor_demo/mrcnn/visualize.py
+++ /dev/null
@@ -1,452 +0,0 @@
-"""
-Mask R-CNN
-Display and Visualization Functions.
-
-Copyright (c) 2017 Matterport, Inc.
-Licensed under the MIT License (see LICENSE for details)
-Written by Waleed Abdulla
-"""
-
-import os
-import sys
-import logging
-import random
-import itertools
-import colorsys
-
-import numpy as np
-from skimage.measure import find_contours
-import matplotlib.pyplot as plt
-from matplotlib import patches,  lines
-from matplotlib.patches import Polygon
-import IPython.display
-
-# Root directory of the project
-ROOT_DIR = os.path.abspath("../")
-
-# Import Mask RCNN
-sys.path.append(ROOT_DIR)  # To find local version of the library
-from mrcnn import utils
-
-
-############################################################
-#  Visualization
-############################################################
-
-def display_images(images, titles=None, cols=4, cmap=None, norm=None,
-                   interpolation=None):
-    """Display the given set of images, optionally with titles.
-    images: list or array of image tensors in HWC format.
-    titles: optional. A list of titles to display with each image.
-    cols: number of images per row
-    cmap: Optional. Color map to use. For example, "Blues".
-    norm: Optional. A Normalize instance to map values to colors.
-    interpolation: Optional. Image interporlation to use for display.
-    """
-    # titles = titles if titles is not None else [""] * len(images)
-    # rows = len(images) // cols + 1
-    # plt.figure(figsize=(14, 14 * rows // cols))
-    # i = 1
-    # for image, title in zip(images, titles):
-    #     plt.subplot(rows, cols, i)
-    #     plt.title(title, fontsize=9)
-    #     plt.axis('off')
-    #     plt.imshow(image.astype(np.uint8), cmap=cmap,
-    #                norm=norm, interpolation=interpolation)
-    #     i += 1
-    # plt.show()
-    pass
-
-
-def random_colors(N, bright=True):
-    """
-    Generate random colors.
-    To get visually distinct colors, generate them in HSV space then
-    convert to RGB.
-    """
-    brightness = 1.0 if bright else 0.7
-    hsv = [(i / N, 1, brightness) for i in range(N)]
-    colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv))
-    random.shuffle(colors)
-    return colors
-
-
-def apply_mask(image, mask, color, alpha=0.5):
-    """Apply the given mask to the image.
-    """
-    for c in range(3):
-        image[:, :, c] = np.where(mask == 1,
-                                  image[:, :, c] *
-                                  (1 - alpha) + alpha * color[c] * 255,
-                                  image[:, :, c])
-    return image
-
-
-def display_instances(image, boxes, masks, class_ids, class_names,
-                      scores=None, title="",
-                      figsize=(16, 16), ax=None):
-    """
-    boxes: [num_instance, (y1, x1, y2, x2, class_id)] in image coordinates.
-    masks: [height, width, num_instances]
-    class_ids: [num_instances]
-    class_names: list of class names of the dataset
-    scores: (optional) confidence scores for each box
-    figsize: (optional) the size of the image.
-    """
-    # Number of instances
-    N = boxes.shape[0]
-    if not N:
-        print("\n*** No instances to display *** \n")
-    else:
-        assert boxes.shape[0] == masks.shape[-1] == class_ids.shape[0]
-
-    # if not ax:
-    #     _, ax = plt.subplots(1, figsize=figsize)
-
-    # Generate random colors
-    colors = random_colors(N)
-
-    # Show area outside image boundaries.
-    height, width = image.shape[:2]
-#     ax.set_ylim(height + 10, -10)
-#     ax.set_xlim(-10, width + 10)
-#     ax.axis('off')
-#     ax.set_title(title)
-
-    masked_image = image.astype(np.uint32).copy()
-    for i in range(N):
-        color = colors[i]
-
-        # Bounding box
-        if not np.any(boxes[i]):
-            # Skip this instance. Has no bbox. Likely lost in image cropping.
-            continue
-        y1, x1, y2, x2 = boxes[i]
-        p = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=2,
-                              alpha=0.7, linestyle="dashed",
-                              edgecolor=color, facecolor='none')
-        #ax.add_patch(p)
-
-        # Label
-        class_id = class_ids[i]
-        score = scores[i] if scores is not None else None
-        label = class_names[class_id]
-        x = random.randint(x1, (x1 + x2) // 2)
-        caption = "{} {:.3f}".format(label, score) if score else label
-#         ax.text(x1, y1 + 8, caption,
-#                 color='w', size=11, backgroundcolor="none")
-
-        # Mask
-        mask = masks[:, :, i]
-        masked_image = apply_mask(masked_image, mask, color)
-
-        # Mask Polygon
-        # Pad to ensure proper polygons for masks that touch image edges.
-        padded_mask = np.zeros(
-            (mask.shape[0] + 2, mask.shape[1] + 2), dtype=np.uint8)
-        padded_mask[1:-1, 1:-1] = mask
-        contours = find_contours(padded_mask, 0.5)
-        for verts in contours:
-            # Subtract the padding and flip (y, x) to (x, y)
-            verts = np.fliplr(verts) - 1
-            p = Polygon(verts, facecolor="none", edgecolor=color)
-            #ax.add_patch(p)
-    #ax.imshow(masked_image.astype(np.uint8))
-    #plt.show()
-    return masked_image.astype(np.uint8)
-    
-
-def draw_rois(image, rois, refined_rois, mask, class_ids, class_names, limit=10):
-    """
-    anchors: [n, (y1, x1, y2, x2)] list of anchors in image coordinates.
-    proposals: [n, 4] the same anchors but refined to fit objects better.
-    """
-    masked_image = image.copy()
-
-    # Pick random anchors in case there are too many.
-    ids = np.arange(rois.shape[0], dtype=np.int32)
-    ids = np.random.choice(
-        ids, limit, replace=False) if ids.shape[0] > limit else ids
-
-    fig, ax = plt.subplots(1, figsize=(12, 12))
-    if rois.shape[0] > limit:
-        plt.title("Showing {} random ROIs out of {}".format(
-            len(ids), rois.shape[0]))
-    else:
-        plt.title("{} ROIs".format(len(ids)))
-
-    # Show area outside image boundaries.
-    ax.set_ylim(image.shape[0] + 20, -20)
-    ax.set_xlim(-50, image.shape[1] + 20)
-    ax.axis('off')
-
-    for i, id in enumerate(ids):
-        color = np.random.rand(3)
-        class_id = class_ids[id]
-        # ROI
-        y1, x1, y2, x2 = rois[id]
-        p = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=2,
-                              edgecolor=color if class_id else "gray",
-                              facecolor='none', linestyle="dashed")
-        ax.add_patch(p)
-        # Refined ROI
-        if class_id:
-            ry1, rx1, ry2, rx2 = refined_rois[id]
-            p = patches.Rectangle((rx1, ry1), rx2 - rx1, ry2 - ry1, linewidth=2,
-                                  edgecolor=color, facecolor='none')
-            ax.add_patch(p)
-            # Connect the top-left corners of the anchor and proposal for easy visualization
-            ax.add_line(lines.Line2D([x1, rx1], [y1, ry1], color=color))
-
-            # Label
-            label = class_names[class_id]
-            ax.text(rx1, ry1 + 8, "{}".format(label),
-                    color='w', size=11, backgroundcolor="none")
-
-            # Mask
-            m = utils.unmold_mask(mask[id], rois[id]
-                                  [:4].astype(np.int32), image.shape)
-            masked_image = apply_mask(masked_image, m, color)
-
-    #ax.imshow(masked_image)
-
-    # Print stats
-    print("Positive ROIs: ", class_ids[class_ids > 0].shape[0])
-    print("Negative ROIs: ", class_ids[class_ids == 0].shape[0])
-    print("Positive Ratio: {:.2f}".format(
-        class_ids[class_ids > 0].shape[0] / class_ids.shape[0]))
-
-
-# TODO: Replace with matplotlib equivalent?
-def draw_box(image, box, color):
-    """Draw 3-pixel width bounding boxes on the given image array.
-    color: list of 3 int values for RGB.
-    """
-    y1, x1, y2, x2 = box
-    image[y1:y1 + 2, x1:x2] = color
-    image[y2:y2 + 2, x1:x2] = color
-    image[y1:y2, x1:x1 + 2] = color
-    image[y1:y2, x2:x2 + 2] = color
-    return image
-
-
-def display_top_masks(image, mask, class_ids, class_names, limit=4):
-    """Display the given image and the top few class masks."""
-    to_display = []
-    titles = []
-    to_display.append(image)
-    titles.append("H x W={}x{}".format(image.shape[0], image.shape[1]))
-    # Pick top prominent classes in this image
-    unique_class_ids = np.unique(class_ids)
-    mask_area = [np.sum(mask[:, :, np.where(class_ids == i)[0]])
-                 for i in unique_class_ids]
-    top_ids = [v[0] for v in sorted(zip(unique_class_ids, mask_area),
-                                    key=lambda r: r[1], reverse=True) if v[1] > 0]
-    # Generate images and titles
-    for i in range(limit):
-        class_id = top_ids[i] if i < len(top_ids) else -1
-        # Pull masks of instances belonging to the same class.
-        m = mask[:, :, np.where(class_ids == class_id)[0]]
-        m = np.sum(m * np.arange(1, m.shape[-1] + 1), -1)
-        to_display.append(m)
-        titles.append(class_names[class_id] if class_id != -1 else "-")
-    display_images(to_display, titles=titles, cols=limit + 1, cmap="Blues_r")
-
-
-def plot_precision_recall(AP, precisions, recalls):
-    """Draw the precision-recall curve.
-
-    AP: Average precision at IoU >= 0.5
-    precisions: list of precision values
-    recalls: list of recall values
-    """
-    # Plot the Precision-Recall curve
-    _, ax = plt.subplots(1)
-    ax.set_title("Precision-Recall Curve. AP@50 = {:.3f}".format(AP))
-    ax.set_ylim(0, 1.1)
-    ax.set_xlim(0, 1.1)
-    _ = ax.plot(recalls, precisions)
-
-
-def plot_overlaps(gt_class_ids, pred_class_ids, pred_scores,
-                  overlaps, class_names, threshold=0.5):
-    """Draw a grid showing how ground truth objects are classified.
-    gt_class_ids: [N] int. Ground truth class IDs
-    pred_class_id: [N] int. Predicted class IDs
-    pred_scores: [N] float. The probability scores of predicted classes
-    overlaps: [pred_boxes, gt_boxes] IoU overlaps of predictins and GT boxes.
-    class_names: list of all class names in the dataset
-    threshold: Float. The prediction probability required to predict a class
-    """
-    gt_class_ids = gt_class_ids[gt_class_ids != 0]
-    pred_class_ids = pred_class_ids[pred_class_ids != 0]
-
-    plt.figure(figsize=(12, 10))
-    plt.imshow(overlaps, interpolation='nearest', cmap=plt.cm.Blues)
-    plt.yticks(np.arange(len(pred_class_ids)),
-               ["{} ({:.2f})".format(class_names[int(id)], pred_scores[i])
-                for i, id in enumerate(pred_class_ids)])
-    plt.xticks(np.arange(len(gt_class_ids)),
-               [class_names[int(id)] for id in gt_class_ids], rotation=90)
-
-    thresh = overlaps.max() / 2.
-    for i, j in itertools.product(range(overlaps.shape[0]),
-                                  range(overlaps.shape[1])):
-        text = ""
-        if overlaps[i, j] > threshold:
-            text = "match" if gt_class_ids[j] == pred_class_ids[i] else "wrong"
-        color = ("white" if overlaps[i, j] > thresh
-                 else "black" if overlaps[i, j] > 0
-                 else "grey")
-        plt.text(j, i, "{:.3f}\n{}".format(overlaps[i, j], text),
-                 horizontalalignment="center", verticalalignment="center",
-                 fontsize=9, color=color)
-
-    plt.tight_layout()
-    plt.xlabel("Ground Truth")
-    plt.ylabel("Predictions")
-
-
-def draw_boxes(image, boxes=None, refined_boxes=None,
-               masks=None, captions=None, visibilities=None,
-               title="", ax=None):
-    """Draw bounding boxes and segmentation masks with differnt
-    customizations.
-
-    boxes: [N, (y1, x1, y2, x2, class_id)] in image coordinates.
-    refined_boxes: Like boxes, but draw with solid lines to show
-        that they're the result of refining 'boxes'.
-    masks: [N, height, width]
-    captions: List of N titles to display on each box
-    visibilities: (optional) List of values of 0, 1, or 2. Determine how
-        prominant each bounding box should be.
-    title: An optional title to show over the image
-    ax: (optional) Matplotlib axis to draw on.
-    """
-    # Number of boxes
-    assert boxes is not None or refined_boxes is not None
-    N = boxes.shape[0] if boxes is not None else refined_boxes.shape[0]
-
-    # Matplotlib Axis
-    if not ax:
-        _, ax = plt.subplots(1, figsize=(12, 12))
-
-    # Generate random colors
-    colors = random_colors(N)
-
-    # Show area outside image boundaries.
-    margin = image.shape[0] // 10
-    ax.set_ylim(image.shape[0] + margin, -margin)
-    ax.set_xlim(-margin, image.shape[1] + margin)
-    ax.axis('off')
-
-    ax.set_title(title)
-
-    masked_image = image.astype(np.uint32).copy()
-    for i in range(N):
-        # Box visibility
-        visibility = visibilities[i] if visibilities is not None else 1
-        if visibility == 0:
-            color = "gray"
-            style = "dotted"
-            alpha = 0.5
-        elif visibility == 1:
-            color = colors[i]
-            style = "dotted"
-            alpha = 1
-        elif visibility == 2:
-            color = colors[i]
-            style = "solid"
-            alpha = 1
-
-        # Boxes
-        if boxes is not None:
-            if not np.any(boxes[i]):
-                # Skip this instance. Has no bbox. Likely lost in cropping.
-                continue
-            y1, x1, y2, x2 = boxes[i]
-            p = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=2,
-                                  alpha=alpha, linestyle=style,
-                                  edgecolor=color, facecolor='none')
-            ax.add_patch(p)
-
-        # Refined boxes
-        if refined_boxes is not None and visibility > 0:
-            ry1, rx1, ry2, rx2 = refined_boxes[i].astype(np.int32)
-            p = patches.Rectangle((rx1, ry1), rx2 - rx1, ry2 - ry1, linewidth=2,
-                                  edgecolor=color, facecolor='none')
-            ax.add_patch(p)
-            # Connect the top-left corners of the anchor and proposal
-            if boxes is not None:
-                ax.add_line(lines.Line2D([x1, rx1], [y1, ry1], color=color))
-
-        # Captions
-        if captions is not None:
-            caption = captions[i]
-            # If there are refined boxes, display captions on them
-            if refined_boxes is not None:
-                y1, x1, y2, x2 = ry1, rx1, ry2, rx2
-            x = random.randint(x1, (x1 + x2) // 2)
-            ax.text(x1, y1, caption, size=11, verticalalignment='top',
-                    color='w', backgroundcolor="none",
-                    bbox={'facecolor': color, 'alpha': 0.5,
-                          'pad': 2, 'edgecolor': 'none'})
-
-        # Masks
-        if masks is not None:
-            mask = masks[:, :, i]
-            masked_image = apply_mask(masked_image, mask, color)
-            # Mask Polygon
-            # Pad to ensure proper polygons for masks that touch image edges.
-            padded_mask = np.zeros(
-                (mask.shape[0] + 2, mask.shape[1] + 2), dtype=np.uint8)
-            padded_mask[1:-1, 1:-1] = mask
-            contours = find_contours(padded_mask, 0.5)
-            for verts in contours:
-                # Subtract the padding and flip (y, x) to (x, y)
-                verts = np.fliplr(verts) - 1
-                p = Polygon(verts, facecolor="none", edgecolor=color)
-                ax.add_patch(p)
-    ax.imshow(masked_image.astype(np.uint8))
-
-
-def display_table(table):
-    """Display values in a table format.
-    table: an iterable of rows, and each row is an iterable of values.
-    """
-    html = ""
-    for row in table:
-        row_html = ""
-        for col in row:
-            row_html += "<td>{:40}</td>".format(str(col))
-        html += "<tr>" + row_html + "</tr>"
-    html = "<table>" + html + "</table>"
-    #IPython.display.display(IPython.display.HTML(html))
-
-
-def display_weight_stats(model):
-    """Scans all the weights in the model and returns a list of tuples
-    that contain stats about each weight.
-    """
-    layers = model.get_trainable_layers()
-    table = [["WEIGHT NAME", "SHAPE", "MIN", "MAX", "STD"]]
-    for l in layers:
-        weight_values = l.get_weights()  # list of Numpy arrays
-        weight_tensors = l.weights  # list of TF tensors
-        for i, w in enumerate(weight_values):
-            weight_name = weight_tensors[i].name
-            # Detect problematic layers. Exclude biases of conv layers.
-            alert = ""
-            if w.min() == w.max() and not (l.__class__.__name__ == "Conv2D" and i == 1):
-                alert += "<span style='color:red'>*** dead?</span>"
-            if np.abs(w.min()) > 1000 or np.abs(w.max()) > 1000:
-                alert += "<span style='color:red'>*** Overflow?</span>"
-            # Add row
-            table.append([
-                weight_name + alert,
-                str(w.shape),
-                "{:+9.4f}".format(w.min()),
-                "{:+10.4f}".format(w.max()),
-                "{:+9.4f}".format(w.std()),
-            ])
-    #display_table(table)
diff --git a/spaces/Goya11/zimu/README.md b/spaces/Goya11/zimu/README.md
deleted file mode 100644
index 5cc3da0bc0fb1033ffef1178324d5440a3373d09..0000000000000000000000000000000000000000
--- a/spaces/Goya11/zimu/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Zimu
-emoji: 🏆
-colorFrom: yellow
-colorTo: green
-sdk: gradio
-sdk_version: 3.28.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Gradio-Blocks/EmojiGAN/torch_utils/ops/grid_sample_gradfix.py b/spaces/Gradio-Blocks/EmojiGAN/torch_utils/ops/grid_sample_gradfix.py
deleted file mode 100644
index ca6b3413ea72a734703c34382c023b84523601fd..0000000000000000000000000000000000000000
--- a/spaces/Gradio-Blocks/EmojiGAN/torch_utils/ops/grid_sample_gradfix.py
+++ /dev/null
@@ -1,83 +0,0 @@
-# Copyright (c) 2021, NVIDIA CORPORATION.  All rights reserved.
-#
-# NVIDIA CORPORATION and its licensors retain all intellectual property
-# and proprietary rights in and to this software, related documentation
-# and any modifications thereto.  Any use, reproduction, disclosure or
-# distribution of this software and related documentation without an express
-# license agreement from NVIDIA CORPORATION is strictly prohibited.
-
-"""Custom replacement for `torch.nn.functional.grid_sample` that
-supports arbitrarily high order gradients between the input and output.
-Only works on 2D images and assumes
-`mode='bilinear'`, `padding_mode='zeros'`, `align_corners=False`."""
-
-import warnings
-import torch
-
-# pylint: disable=redefined-builtin
-# pylint: disable=arguments-differ
-# pylint: disable=protected-access
-
-#----------------------------------------------------------------------------
-
-enabled = False  # Enable the custom op by setting this to true.
-
-#----------------------------------------------------------------------------
-
-def grid_sample(input, grid):
-    if _should_use_custom_op():
-        return _GridSample2dForward.apply(input, grid)
-    return torch.nn.functional.grid_sample(input=input, grid=grid, mode='bilinear', padding_mode='zeros', align_corners=False)
-
-#----------------------------------------------------------------------------
-
-def _should_use_custom_op():
-    if not enabled:
-        return False
-    if any(torch.__version__.startswith(x) for x in ['1.7.', '1.8.', '1.9']):
-        return True
-    warnings.warn(f'grid_sample_gradfix not supported on PyTorch {torch.__version__}. Falling back to torch.nn.functional.grid_sample().')
-    return False
-
-#----------------------------------------------------------------------------
-
-class _GridSample2dForward(torch.autograd.Function):
-    @staticmethod
-    def forward(ctx, input, grid):
-        assert input.ndim == 4
-        assert grid.ndim == 4
-        output = torch.nn.functional.grid_sample(input=input, grid=grid, mode='bilinear', padding_mode='zeros', align_corners=False)
-        ctx.save_for_backward(input, grid)
-        return output
-
-    @staticmethod
-    def backward(ctx, grad_output):
-        input, grid = ctx.saved_tensors
-        grad_input, grad_grid = _GridSample2dBackward.apply(grad_output, input, grid)
-        return grad_input, grad_grid
-
-#----------------------------------------------------------------------------
-
-class _GridSample2dBackward(torch.autograd.Function):
-    @staticmethod
-    def forward(ctx, grad_output, input, grid):
-        op = torch._C._jit_get_operation('aten::grid_sampler_2d_backward')
-        grad_input, grad_grid = op(grad_output, input, grid, 0, 0, False)
-        ctx.save_for_backward(grid)
-        return grad_input, grad_grid
-
-    @staticmethod
-    def backward(ctx, grad2_grad_input, grad2_grad_grid):
-        _ = grad2_grad_grid # unused
-        grid, = ctx.saved_tensors
-        grad2_grad_output = None
-        grad2_input = None
-        grad2_grid = None
-
-        if ctx.needs_input_grad[0]:
-            grad2_grad_output = _GridSample2dForward.apply(grad2_grad_input, grid)
-
-        assert not ctx.needs_input_grad[2]
-        return grad2_grad_output, grad2_input, grad2_grid
-
-#----------------------------------------------------------------------------
diff --git a/spaces/Gradio-Blocks/pokemon-move-generator-app/README.md b/spaces/Gradio-Blocks/pokemon-move-generator-app/README.md
deleted file mode 100644
index a16cbf994f996fe17dc7a81878744648348e88d6..0000000000000000000000000000000000000000
--- a/spaces/Gradio-Blocks/pokemon-move-generator-app/README.md
+++ /dev/null
@@ -1,10 +0,0 @@
----
-title: Pokémon Move Generator
-emoji: 🎮
-colorFrom: red
-colorTo: grey
-sdk: gradio
-sdk_version: 3.0.2
-app_file: app.py
-pinned: True
----
diff --git a/spaces/Gradio-Blocks/uniformer_image_detection/configs/cascade_rcnn/cascade_rcnn_r101_caffe_fpn_1x_coco.py b/spaces/Gradio-Blocks/uniformer_image_detection/configs/cascade_rcnn/cascade_rcnn_r101_caffe_fpn_1x_coco.py
deleted file mode 100644
index 8e8b830fd544b73d2da7a359ea208178a37fc324..0000000000000000000000000000000000000000
--- a/spaces/Gradio-Blocks/uniformer_image_detection/configs/cascade_rcnn/cascade_rcnn_r101_caffe_fpn_1x_coco.py
+++ /dev/null
@@ -1,4 +0,0 @@
-_base_ = './cascade_rcnn_r50_caffe_fpn_1x_coco.py'
-model = dict(
-    pretrained='open-mmlab://detectron2/resnet101_caffe',
-    backbone=dict(depth=101))
diff --git a/spaces/Gradio-Blocks/uniformer_image_detection/configs/fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py b/spaces/Gradio-Blocks/uniformer_image_detection/configs/fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py
deleted file mode 100644
index 2816b16f64dbcbfecd779650aaae0ca6cee0d810..0000000000000000000000000000000000000000
--- a/spaces/Gradio-Blocks/uniformer_image_detection/configs/fcos/fcos_r50_caffe_fpn_gn-head_4x4_1x_coco.py
+++ /dev/null
@@ -1,4 +0,0 @@
-# TODO: Remove this config after benchmarking all related configs
-_base_ = 'fcos_r50_caffe_fpn_gn-head_1x_coco.py'
-
-data = dict(samples_per_gpu=4, workers_per_gpu=4)
diff --git a/spaces/Gradio-Blocks/uniformer_image_detection/configs/gn+ws/faster_rcnn_r101_fpn_gn_ws-all_1x_coco.py b/spaces/Gradio-Blocks/uniformer_image_detection/configs/gn+ws/faster_rcnn_r101_fpn_gn_ws-all_1x_coco.py
deleted file mode 100644
index a5f6bd2292f4c1dfbd59de968e0dc3acf7579424..0000000000000000000000000000000000000000
--- a/spaces/Gradio-Blocks/uniformer_image_detection/configs/gn+ws/faster_rcnn_r101_fpn_gn_ws-all_1x_coco.py
+++ /dev/null
@@ -1,3 +0,0 @@
-_base_ = './faster_rcnn_r50_fpn_gn_ws-all_1x_coco.py'
-model = dict(
-    pretrained='open-mmlab://jhu/resnet101_gn_ws', backbone=dict(depth=101))
diff --git a/spaces/Gradio-Blocks/uniformer_image_segmentation/tools/ort_test.py b/spaces/Gradio-Blocks/uniformer_image_segmentation/tools/ort_test.py
deleted file mode 100644
index 807b21272a04c86176c19de45fb2407b71e33319..0000000000000000000000000000000000000000
--- a/spaces/Gradio-Blocks/uniformer_image_segmentation/tools/ort_test.py
+++ /dev/null
@@ -1,191 +0,0 @@
-import argparse
-import os
-import os.path as osp
-import warnings
-
-import mmcv
-import numpy as np
-import onnxruntime as ort
-import torch
-from mmcv.parallel import MMDataParallel
-from mmcv.runner import get_dist_info
-from mmcv.utils import DictAction
-
-from mmseg.apis import single_gpu_test
-from mmseg.datasets import build_dataloader, build_dataset
-from mmseg.models.segmentors.base import BaseSegmentor
-
-
-class ONNXRuntimeSegmentor(BaseSegmentor):
-
-    def __init__(self, onnx_file, cfg, device_id):
-        super(ONNXRuntimeSegmentor, self).__init__()
-        # get the custom op path
-        ort_custom_op_path = ''
-        try:
-            from mmcv.ops import get_onnxruntime_op_path
-            ort_custom_op_path = get_onnxruntime_op_path()
-        except (ImportError, ModuleNotFoundError):
-            warnings.warn('If input model has custom op from mmcv, \
-                you may have to build mmcv with ONNXRuntime from source.')
-        session_options = ort.SessionOptions()
-        # register custom op for onnxruntime
-        if osp.exists(ort_custom_op_path):
-            session_options.register_custom_ops_library(ort_custom_op_path)
-        sess = ort.InferenceSession(onnx_file, session_options)
-        providers = ['CPUExecutionProvider']
-        options = [{}]
-        is_cuda_available = ort.get_device() == 'GPU'
-        if is_cuda_available:
-            providers.insert(0, 'CUDAExecutionProvider')
-            options.insert(0, {'device_id': device_id})
-
-        sess.set_providers(providers, options)
-
-        self.sess = sess
-        self.device_id = device_id
-        self.io_binding = sess.io_binding()
-        self.output_names = [_.name for _ in sess.get_outputs()]
-        for name in self.output_names:
-            self.io_binding.bind_output(name)
-        self.cfg = cfg
-        self.test_mode = cfg.model.test_cfg.mode
-
-    def extract_feat(self, imgs):
-        raise NotImplementedError('This method is not implemented.')
-
-    def encode_decode(self, img, img_metas):
-        raise NotImplementedError('This method is not implemented.')
-
-    def forward_train(self, imgs, img_metas, **kwargs):
-        raise NotImplementedError('This method is not implemented.')
-
-    def simple_test(self, img, img_meta, **kwargs):
-        device_type = img.device.type
-        self.io_binding.bind_input(
-            name='input',
-            device_type=device_type,
-            device_id=self.device_id,
-            element_type=np.float32,
-            shape=img.shape,
-            buffer_ptr=img.data_ptr())
-        self.sess.run_with_iobinding(self.io_binding)
-        seg_pred = self.io_binding.copy_outputs_to_cpu()[0]
-        # whole might support dynamic reshape
-        ori_shape = img_meta[0]['ori_shape']
-        if not (ori_shape[0] == seg_pred.shape[-2]
-                and ori_shape[1] == seg_pred.shape[-1]):
-            seg_pred = torch.from_numpy(seg_pred).float()
-            seg_pred = torch.nn.functional.interpolate(
-                seg_pred, size=tuple(ori_shape[:2]), mode='nearest')
-            seg_pred = seg_pred.long().detach().cpu().numpy()
-        seg_pred = seg_pred[0]
-        seg_pred = list(seg_pred)
-        return seg_pred
-
-    def aug_test(self, imgs, img_metas, **kwargs):
-        raise NotImplementedError('This method is not implemented.')
-
-
-def parse_args():
-    parser = argparse.ArgumentParser(
-        description='mmseg onnxruntime backend test (and eval) a model')
-    parser.add_argument('config', help='test config file path')
-    parser.add_argument('model', help='Input model file')
-    parser.add_argument('--out', help='output result file in pickle format')
-    parser.add_argument(
-        '--format-only',
-        action='store_true',
-        help='Format the output results without perform evaluation. It is'
-        'useful when you want to format the result to a specific format and '
-        'submit it to the test server')
-    parser.add_argument(
-        '--eval',
-        type=str,
-        nargs='+',
-        help='evaluation metrics, which depends on the dataset, e.g., "mIoU"'
-        ' for generic datasets, and "cityscapes" for Cityscapes')
-    parser.add_argument('--show', action='store_true', help='show results')
-    parser.add_argument(
-        '--show-dir', help='directory where painted images will be saved')
-    parser.add_argument(
-        '--options', nargs='+', action=DictAction, help='custom options')
-    parser.add_argument(
-        '--eval-options',
-        nargs='+',
-        action=DictAction,
-        help='custom options for evaluation')
-    parser.add_argument(
-        '--opacity',
-        type=float,
-        default=0.5,
-        help='Opacity of painted segmentation map. In (0, 1] range.')
-    parser.add_argument('--local_rank', type=int, default=0)
-    args = parser.parse_args()
-    if 'LOCAL_RANK' not in os.environ:
-        os.environ['LOCAL_RANK'] = str(args.local_rank)
-    return args
-
-
-def main():
-    args = parse_args()
-
-    assert args.out or args.eval or args.format_only or args.show \
-        or args.show_dir, \
-        ('Please specify at least one operation (save/eval/format/show the '
-         'results / save the results) with the argument "--out", "--eval"'
-         ', "--format-only", "--show" or "--show-dir"')
-
-    if args.eval and args.format_only:
-        raise ValueError('--eval and --format_only cannot be both specified')
-
-    if args.out is not None and not args.out.endswith(('.pkl', '.pickle')):
-        raise ValueError('The output file must be a pkl file.')
-
-    cfg = mmcv.Config.fromfile(args.config)
-    if args.options is not None:
-        cfg.merge_from_dict(args.options)
-    cfg.model.pretrained = None
-    cfg.data.test.test_mode = True
-
-    # init distributed env first, since logger depends on the dist info.
-    distributed = False
-
-    # build the dataloader
-    # TODO: support multiple images per gpu (only minor changes are needed)
-    dataset = build_dataset(cfg.data.test)
-    data_loader = build_dataloader(
-        dataset,
-        samples_per_gpu=1,
-        workers_per_gpu=cfg.data.workers_per_gpu,
-        dist=distributed,
-        shuffle=False)
-
-    # load onnx config and meta
-    cfg.model.train_cfg = None
-    model = ONNXRuntimeSegmentor(args.model, cfg=cfg, device_id=0)
-    model.CLASSES = dataset.CLASSES
-    model.PALETTE = dataset.PALETTE
-
-    efficient_test = False
-    if args.eval_options is not None:
-        efficient_test = args.eval_options.get('efficient_test', False)
-
-    model = MMDataParallel(model, device_ids=[0])
-    outputs = single_gpu_test(model, data_loader, args.show, args.show_dir,
-                              efficient_test, args.opacity)
-
-    rank, _ = get_dist_info()
-    if rank == 0:
-        if args.out:
-            print(f'\nwriting results to {args.out}')
-            mmcv.dump(outputs, args.out)
-        kwargs = {} if args.eval_options is None else args.eval_options
-        if args.format_only:
-            dataset.format_results(outputs, **kwargs)
-        if args.eval:
-            dataset.evaluate(outputs, args.eval, **kwargs)
-
-
-if __name__ == '__main__':
-    main()
diff --git a/spaces/GrandaddyShmax/AudioCraft_Plus/audiocraft/optim/polynomial_decay_lr_scheduler.py b/spaces/GrandaddyShmax/AudioCraft_Plus/audiocraft/optim/polynomial_decay_lr_scheduler.py
deleted file mode 100644
index c5ea30b094538269dbb0055ab3163f84d1cf6e90..0000000000000000000000000000000000000000
--- a/spaces/GrandaddyShmax/AudioCraft_Plus/audiocraft/optim/polynomial_decay_lr_scheduler.py
+++ /dev/null
@@ -1,47 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-from torch.optim import Optimizer
-from torch.optim.lr_scheduler import _LRScheduler
-
-
-class PolynomialDecayLRScheduler(_LRScheduler):
-    """Polynomial decay LR scheduler.
-
-    Args:
-        optimizer (Optimizer): Torch optimizer.
-        warmup_steps (int): Number of warmup steps.
-        total_steps (int): Total number of steps.
-        end_lr (float): Final learning rate to achieve over total number of steps.
-        zero_lr_warmup_steps (int): Number of steps with a learning rate of value 0.
-        power (float): Decay exponent.
-    """
-    def __init__(self, optimizer: Optimizer, warmup_steps: int, total_steps: int,
-                 end_lr: float = 0., zero_lr_warmup_steps: int = 0, power: float = 1.):
-        self.warmup_steps = warmup_steps
-        self.total_steps = total_steps
-        self.end_lr = end_lr
-        self.zero_lr_warmup_steps = zero_lr_warmup_steps
-        self.power = power
-        super().__init__(optimizer)
-
-    def _get_sched_lr(self, lr: float, step: int):
-        if self.zero_lr_warmup_steps > 0 and step <= self.zero_lr_warmup_steps:
-            lr = 0
-        elif self.warmup_steps > 0 and step <= self.warmup_steps + self.zero_lr_warmup_steps:
-            lr_ratio = (step - self.zero_lr_warmup_steps) / float(self.warmup_steps)
-            lr = lr_ratio * lr
-        elif step >= self.total_steps:
-            lr = self.end_lr
-        else:
-            total_warmup_steps = self.warmup_steps + self.zero_lr_warmup_steps
-            lr_range = lr - self.end_lr
-            pct_remaining = 1 - (step - total_warmup_steps) / (self.total_steps - total_warmup_steps)
-            lr = lr_range * pct_remaining ** self.power + self.end_lr
-        return lr
-
-    def get_lr(self):
-        return [self._get_sched_lr(base_lr, self.last_epoch) for base_lr in self.base_lrs]
diff --git a/spaces/GrandaddyShmax/AudioCraft_Plus/scripts/__init__.py b/spaces/GrandaddyShmax/AudioCraft_Plus/scripts/__init__.py
deleted file mode 100644
index 0952fcc3f57e34b3747962e9ebd6fc57aeea63fa..0000000000000000000000000000000000000000
--- a/spaces/GrandaddyShmax/AudioCraft_Plus/scripts/__init__.py
+++ /dev/null
@@ -1,5 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
diff --git a/spaces/GrandaddyShmax/MusicGen_Plus/audiocraft/quantization/core_vq.py b/spaces/GrandaddyShmax/MusicGen_Plus/audiocraft/quantization/core_vq.py
deleted file mode 100644
index e1896bb1788a945a1f7be6369abb255ecf72c7a0..0000000000000000000000000000000000000000
--- a/spaces/GrandaddyShmax/MusicGen_Plus/audiocraft/quantization/core_vq.py
+++ /dev/null
@@ -1,400 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-import typing as tp
-
-from einops import rearrange, repeat
-import flashy
-import torch
-from torch import nn, einsum
-import torch.nn.functional as F
-
-
-def exists(val: tp.Optional[tp.Any]) -> bool:
-    return val is not None
-
-
-def default(val: tp.Any, d: tp.Any) -> tp.Any:
-    return val if exists(val) else d
-
-
-def l2norm(t):
-    return F.normalize(t, p=2, dim=-1)
-
-
-def ema_inplace(moving_avg, new, decay: float):
-    moving_avg.data.mul_(decay).add_(new, alpha=(1 - decay))
-
-
-def laplace_smoothing(x, n_categories: int, epsilon: float = 1e-5):
-    return (x + epsilon) / (x.sum() + n_categories * epsilon)
-
-
-def uniform_init(*shape: int):
-    t = torch.empty(shape)
-    nn.init.kaiming_uniform_(t)
-    return t
-
-
-def sample_vectors(samples, num: int):
-    num_samples, device = samples.shape[0], samples.device
-
-    if num_samples >= num:
-        indices = torch.randperm(num_samples, device=device)[:num]
-    else:
-        indices = torch.randint(0, num_samples, (num,), device=device)
-
-    return samples[indices]
-
-
-def kmeans(samples, num_clusters: int, num_iters: int = 10):
-    dim, dtype = samples.shape[-1], samples.dtype
-
-    means = sample_vectors(samples, num_clusters)
-
-    for _ in range(num_iters):
-        diffs = rearrange(samples, "n d -> n () d") - rearrange(
-            means, "c d -> () c d"
-        )
-        dists = -(diffs ** 2).sum(dim=-1)
-
-        buckets = dists.max(dim=-1).indices
-        bins = torch.bincount(buckets, minlength=num_clusters)
-        zero_mask = bins == 0
-        bins_min_clamped = bins.masked_fill(zero_mask, 1)
-
-        new_means = buckets.new_zeros(num_clusters, dim, dtype=dtype)
-        new_means.scatter_add_(0, repeat(buckets, "n -> n d", d=dim), samples)
-        new_means = new_means / bins_min_clamped[..., None]
-
-        means = torch.where(zero_mask[..., None], means, new_means)
-
-    return means, bins
-
-
-def orthgonal_loss_fn(t):
-    # eq (2) from https://arxiv.org/abs/2112.00384
-    n = t.shape[0]
-    normed_codes = l2norm(t)
-    identity = torch.eye(n, device=t.device)
-    cosine_sim = einsum("i d, j d -> i j", normed_codes, normed_codes)
-    return ((cosine_sim - identity) ** 2).sum() / (n ** 2)
-
-
-class EuclideanCodebook(nn.Module):
-    """Codebook with Euclidean distance.
-
-    Args:
-        dim (int): Dimension.
-        codebook_size (int): Codebook size.
-        kmeans_init (bool): Whether to use k-means to initialize the codebooks.
-            If set to true, run the k-means algorithm on the first training batch and use
-            the learned centroids as initialization.
-        kmeans_iters (int): Number of iterations used for k-means algorithm at initialization.
-        decay (float): Decay for exponential moving average over the codebooks.
-        epsilon (float): Epsilon value for numerical stability.
-        threshold_ema_dead_code (int): Threshold for dead code expiration. Replace any codes
-            that have an exponential moving average cluster size less than the specified threshold with
-            randomly selected vector from the current batch.
-    """
-    def __init__(
-        self,
-        dim: int,
-        codebook_size: int,
-        kmeans_init: int = False,
-        kmeans_iters: int = 10,
-        decay: float = 0.8,
-        epsilon: float = 1e-5,
-        threshold_ema_dead_code: int = 2,
-    ):
-        super().__init__()
-        self.decay = decay
-        init_fn: tp.Union[tp.Callable[..., torch.Tensor], tp.Any] = uniform_init if not kmeans_init else torch.zeros
-        embed = init_fn(codebook_size, dim)
-
-        self.codebook_size = codebook_size
-
-        self.kmeans_iters = kmeans_iters
-        self.epsilon = epsilon
-        self.threshold_ema_dead_code = threshold_ema_dead_code
-
-        self.register_buffer("inited", torch.Tensor([not kmeans_init]))
-        self.register_buffer("cluster_size", torch.zeros(codebook_size))
-        self.register_buffer("embed", embed)
-        self.register_buffer("embed_avg", embed.clone())
-
-    @torch.jit.ignore
-    def init_embed_(self, data):
-        if self.inited:
-            return
-
-        embed, cluster_size = kmeans(data, self.codebook_size, self.kmeans_iters)
-        self.embed.data.copy_(embed)
-        self.embed_avg.data.copy_(embed.clone())
-        self.cluster_size.data.copy_(cluster_size)
-        self.inited.data.copy_(torch.Tensor([True]))
-        # Make sure all buffers across workers are in sync after initialization
-        flashy.distrib.broadcast_tensors(self.buffers())
-
-    def replace_(self, samples, mask):
-        modified_codebook = torch.where(
-            mask[..., None], sample_vectors(samples, self.codebook_size), self.embed
-        )
-        self.embed.data.copy_(modified_codebook)
-
-    def expire_codes_(self, batch_samples):
-        if self.threshold_ema_dead_code == 0:
-            return
-
-        expired_codes = self.cluster_size < self.threshold_ema_dead_code
-        if not torch.any(expired_codes):
-            return
-
-        batch_samples = rearrange(batch_samples, "... d -> (...) d")
-        self.replace_(batch_samples, mask=expired_codes)
-        flashy.distrib.broadcast_tensors(self.buffers())
-
-    def preprocess(self, x):
-        x = rearrange(x, "... d -> (...) d")
-        return x
-
-    def quantize(self, x):
-        embed = self.embed.t()
-        dist = -(
-            x.pow(2).sum(1, keepdim=True)
-            - 2 * x @ embed
-            + embed.pow(2).sum(0, keepdim=True)
-        )
-        embed_ind = dist.max(dim=-1).indices
-        return embed_ind
-
-    def postprocess_emb(self, embed_ind, shape):
-        return embed_ind.view(*shape[:-1])
-
-    def dequantize(self, embed_ind):
-        quantize = F.embedding(embed_ind, self.embed)
-        return quantize
-
-    def encode(self, x):
-        shape = x.shape
-        # pre-process
-        x = self.preprocess(x)
-        # quantize
-        embed_ind = self.quantize(x)
-        # post-process
-        embed_ind = self.postprocess_emb(embed_ind, shape)
-        return embed_ind
-
-    def decode(self, embed_ind):
-        quantize = self.dequantize(embed_ind)
-        return quantize
-
-    def forward(self, x):
-        shape, dtype = x.shape, x.dtype
-        x = self.preprocess(x)
-        self.init_embed_(x)
-
-        embed_ind = self.quantize(x)
-        embed_onehot = F.one_hot(embed_ind, self.codebook_size).type(dtype)
-        embed_ind = self.postprocess_emb(embed_ind, shape)
-        quantize = self.dequantize(embed_ind)
-
-        if self.training:
-            # We do the expiry of code at that point as buffers are in sync
-            # and all the workers will take the same decision.
-            self.expire_codes_(x)
-            ema_inplace(self.cluster_size, embed_onehot.sum(0), self.decay)
-            embed_sum = x.t() @ embed_onehot
-            ema_inplace(self.embed_avg, embed_sum.t(), self.decay)
-            cluster_size = (
-                laplace_smoothing(self.cluster_size, self.codebook_size, self.epsilon)
-                * self.cluster_size.sum()
-            )
-            embed_normalized = self.embed_avg / cluster_size.unsqueeze(1)
-            self.embed.data.copy_(embed_normalized)
-
-        return quantize, embed_ind
-
-
-class VectorQuantization(nn.Module):
-    """Vector quantization implementation.
-    Currently supports only euclidean distance.
-
-    Args:
-        dim (int): Dimension
-        codebook_size (int): Codebook size
-        codebook_dim (int): Codebook dimension. If not defined, uses the specified dimension in dim.
-        decay (float): Decay for exponential moving average over the codebooks.
-        epsilon (float): Epsilon value for numerical stability.
-        kmeans_init (bool): Whether to use kmeans to initialize the codebooks.
-        kmeans_iters (int): Number of iterations used for kmeans initialization.
-        threshold_ema_dead_code (int):
-        channels_last (bool): Channels are the last dimension in the input tensors.
-        commitment_weight (float): Weight for commitment loss.
-        orthogonal_reg_weight (float): Orthogonal regularization weights.
-        orthogonal_reg_active_codes_only (bool): Apply orthogonal regularization only on active codes.
-        orthogonal_reg_max_codes (optional int): Maximum number of codes to consider
-            for orthogonal regulariation.
-        threshold_ema_dead_code (int): Threshold for dead code expiration. Replace any codes
-            that have an exponential moving average cluster size less than the specified threshold with
-            randomly selected vector from the current batch.
-    """
-    def __init__(
-        self,
-        dim: int,
-        codebook_size: int,
-        codebook_dim: tp.Optional[int] = None,
-        decay: float = 0.8,
-        epsilon: float = 1e-5,
-        kmeans_init: bool = False,
-        kmeans_iters: int = 10,
-        threshold_ema_dead_code: int = 2,
-        channels_last: bool = False,
-        commitment_weight: float = 1.,
-        orthogonal_reg_weight: float = 0.0,
-        orthogonal_reg_active_codes_only: bool = False,
-        orthogonal_reg_max_codes: tp.Optional[int] = None,
-    ):
-        super().__init__()
-        _codebook_dim: int = default(codebook_dim, dim)
-
-        requires_projection = _codebook_dim != dim
-        self.project_in = (nn.Linear(dim, _codebook_dim) if requires_projection else nn.Identity())
-        self.project_out = (nn.Linear(_codebook_dim, dim) if requires_projection else nn.Identity())
-
-        self.epsilon = epsilon
-        self.commitment_weight = commitment_weight
-
-        self.orthogonal_reg_weight = orthogonal_reg_weight
-        self.orthogonal_reg_active_codes_only = orthogonal_reg_active_codes_only
-        self.orthogonal_reg_max_codes = orthogonal_reg_max_codes
-
-        self._codebook = EuclideanCodebook(dim=_codebook_dim, codebook_size=codebook_size,
-                                           kmeans_init=kmeans_init, kmeans_iters=kmeans_iters,
-                                           decay=decay, epsilon=epsilon,
-                                           threshold_ema_dead_code=threshold_ema_dead_code)
-        self.codebook_size = codebook_size
-
-        self.channels_last = channels_last
-
-    @property
-    def codebook(self):
-        return self._codebook.embed
-
-    @property
-    def inited(self):
-        return self._codebook.inited
-
-    def _preprocess(self, x):
-        if not self.channels_last:
-            x = rearrange(x, "b d n -> b n d")
-        return x
-
-    def _postprocess(self, quantize):
-        if not self.channels_last:
-            quantize = rearrange(quantize, "b n d -> b d n")
-        return quantize
-
-    def encode(self, x):
-        x = self._preprocess(x)
-        x = self.project_in(x)
-        embed_in = self._codebook.encode(x)
-        return embed_in
-
-    def decode(self, embed_ind):
-        quantize = self._codebook.decode(embed_ind)
-        quantize = self.project_out(quantize)
-        quantize = self._postprocess(quantize)
-        return quantize
-
-    def forward(self, x):
-        device = x.device
-        x = self._preprocess(x)
-
-        x = self.project_in(x)
-        quantize, embed_ind = self._codebook(x)
-
-        if self.training:
-            quantize = x + (quantize - x).detach()
-
-        loss = torch.tensor([0.0], device=device, requires_grad=self.training)
-
-        if self.training:
-            if self.commitment_weight > 0:
-                commit_loss = F.mse_loss(quantize.detach(), x)
-                loss = loss + commit_loss * self.commitment_weight
-
-            if self.orthogonal_reg_weight > 0:
-                codebook = self.codebook
-
-                if self.orthogonal_reg_active_codes_only:
-                    # only calculate orthogonal loss for the activated codes for this batch
-                    unique_code_ids = torch.unique(embed_ind)
-                    codebook = codebook[unique_code_ids]
-
-                num_codes = codebook.shape[0]
-                if exists(self.orthogonal_reg_max_codes) and num_codes > self.orthogonal_reg_max_codes:
-                    rand_ids = torch.randperm(num_codes, device=device)[:self.orthogonal_reg_max_codes]
-                    codebook = codebook[rand_ids]
-
-                orthogonal_reg_loss = orthgonal_loss_fn(codebook)
-                loss = loss + orthogonal_reg_loss * self.orthogonal_reg_weight
-
-        quantize = self.project_out(quantize)
-        quantize = self._postprocess(quantize)
-
-        return quantize, embed_ind, loss
-
-
-class ResidualVectorQuantization(nn.Module):
-    """Residual vector quantization implementation.
-
-    Follows Algorithm 1. in https://arxiv.org/pdf/2107.03312.pdf
-    """
-    def __init__(self, *, num_quantizers, **kwargs):
-        super().__init__()
-        self.layers = nn.ModuleList(
-            [VectorQuantization(**kwargs) for _ in range(num_quantizers)]
-        )
-
-    def forward(self, x, n_q: tp.Optional[int] = None):
-        quantized_out = 0.0
-        residual = x
-
-        all_losses = []
-        all_indices = []
-
-        n_q = n_q or len(self.layers)
-
-        for i, layer in enumerate(self.layers[:n_q]):
-            quantized, indices, loss = layer(residual)
-            residual = residual - quantized
-            quantized_out = quantized_out + quantized
-            all_indices.append(indices)
-            all_losses.append(loss)
-
-        out_losses, out_indices = map(torch.stack, (all_losses, all_indices))
-        return quantized_out, out_indices, out_losses
-
-    def encode(self, x: torch.Tensor, n_q: tp.Optional[int] = None) -> torch.Tensor:
-        residual = x
-        all_indices = []
-        n_q = n_q or len(self.layers)
-        for layer in self.layers[:n_q]:
-            indices = layer.encode(residual)
-            quantized = layer.decode(indices)
-            residual = residual - quantized
-            all_indices.append(indices)
-        out_indices = torch.stack(all_indices)
-        return out_indices
-
-    def decode(self, q_indices: torch.Tensor) -> torch.Tensor:
-        quantized_out = torch.tensor(0.0, device=q_indices.device)
-        for i, indices in enumerate(q_indices):
-            layer = self.layers[i]
-            quantized = layer.decode(indices)
-            quantized_out = quantized_out + quantized
-        return quantized_out
diff --git a/spaces/HCMUT-GraduateThesis-HNTThinh/rgbdsod-multimae-demo/s_multimae/lr.py b/spaces/HCMUT-GraduateThesis-HNTThinh/rgbdsod-multimae-demo/s_multimae/lr.py
deleted file mode 100644
index 10787df6427b0914e95c88513b9e50bd3349765f..0000000000000000000000000000000000000000
--- a/spaces/HCMUT-GraduateThesis-HNTThinh/rgbdsod-multimae-demo/s_multimae/lr.py
+++ /dev/null
@@ -1,78 +0,0 @@
-from abc import ABCMeta, abstractmethod
-from typing import Dict
-
-class BaseLR():
-    __metaclass__ = ABCMeta
-
-    @abstractmethod
-    def get_lr(self, cur_iter: int): pass
-
-    def state_dict(self) -> Dict:
-        """Returns the state of the scheduler as a :class:`dict`.
-
-        It contains an entry for every variable in self.__dict__ which
-        is not the optimizer.
-        """
-        return {key: value for key, value in self.__dict__.items() if key != 'optimizer'}
-
-    def load_state_dict(self, state_dict: Dict) -> None:
-        """Loads the schedulers state.
-
-        Args:
-            state_dict (dict): scheduler state. Should be an object returned
-                from a call to :meth:`state_dict`.
-        """
-        self.__dict__.update(state_dict)
-
-
-class PolyLR(BaseLR):
-    def __init__(self, start_lr: float, lr_power: float, total_iters: int):
-        self.start_lr = start_lr
-        self.lr_power = lr_power
-        self.total_iters = total_iters + 0.0
-
-    def get_lr(self, cur_iter: int) -> float:
-        return self.start_lr * ((1 - float(cur_iter) / self.total_iters) ** self.lr_power)
-
-class LinearLR(BaseLR):
-    def __init__(self, start_lr: float, end_lr: float, total_iters: int):
-        """@Deprecated
-        """
-        self.start_lr = start_lr
-        self.end_lr = end_lr
-        self.total_iters = float(total_iters)
-
-        self.b = self.start_lr
-        self.a = (self.end_lr - self.start_lr) / self.total_iters
-
-
-    def get_lr(self, cur_iter: int) -> float:
-        return self.a * cur_iter + self.b
-    
-class LinearLRRestart(BaseLR):
-    def __init__(
-        self, 
-        start_lr: float, 
-        end_lr: float, 
-        warmup_epoch: int,
-    ):
-        '''Note: Remember to set epoch at the begining of each epoch'''
-        self.start_lr = start_lr
-        self.end_lr = end_lr
-        self.warmup_epoch = warmup_epoch
-
-    def set_epoch(self, epoch: int, total_iters_per_epoch: int) -> None:
-        '''
-        if epoch is between 1->100, upperbound will be 100
-        if epoch is between 101->200, upperbound will be 200
-        '''
-        upperbound = (((epoch-1) // self.warmup_epoch) + 1) * self.warmup_epoch
-        total_iters = upperbound * total_iters_per_epoch
-        
-        self.b = self.start_lr
-        self.a = (self.end_lr - self.start_lr) / total_iters
-
-    def get_lr(self, cur_iter: int) -> float:
-        """Note: the beginning cur_iter is 0
-        """
-        return self.a * cur_iter + self.b
diff --git a/spaces/Hallucinate/demo/app.py b/spaces/Hallucinate/demo/app.py
deleted file mode 100644
index 1a5af519c45f001a682b056efcf0fb88e91120f3..0000000000000000000000000000000000000000
--- a/spaces/Hallucinate/demo/app.py
+++ /dev/null
@@ -1,905 +0,0 @@
-#————————————————————Credits——————————————————
-#borrowing heavily from deforum stable diffusion
-
-
-#Overview
-#5. Gradio Interface
-#1. Setup
-#2. Prompts
-#3. Video
-#4. Run
-
-
-#————————————————————1.1. Setup————————————————————————
-
-import subprocess, time, gc, os, sys
-
-def setup_environment():
-    start_time = time.time()
-    print_subprocess = False
-    os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "max_split_size_mb: 256"
-    #PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:512
-    use_xformers_for_colab = True
-    try:
-        ipy = get_ipython()
-    except:
-        ipy = 'could not get_ipython'
-    if 'google.colab' in str(ipy):
-        print("..setting up environment")
-
-        # weird hack
-        #import torch
-        
-        all_process = [
-            ['git', 'clone', 'https://github.com/deforum-art/deforum-stable-diffusion'],
-            ['pip', 'install', 'omegaconf', 'einops==0.4.1', 'pytorch-lightning==1.7.7', 'torchmetrics', 'transformers', 'safetensors', 'kornia'],
-            ['pip', 'install', 'accelerate', 'ftfy', 'jsonmerge', 'matplotlib', 'resize-right', 'timm', 'torchdiffeq','scikit-learn','torchsde','open-clip-torch','numpngw'],
-        ]
-        for process in all_process:
-            running = subprocess.run(process,stdout=subprocess.PIPE).stdout.decode('utf-8')
-            if print_subprocess:
-                print(running)
-        with open('deforum-stable-diffusion/src/k_diffusion/__init__.py', 'w') as f:
-            f.write('')
-        sys.path.extend([
-            'deforum-stable-diffusion/',
-            'deforum-stable-diffusion/src',
-        ])
-        if use_xformers_for_colab:
-
-            print("..installing triton and xformers")
-
-            all_process = [['pip', 'install', 'triton==2.0.0.dev20221202', 'xformers==0.0.16']]
-            for process in all_process:
-                running = subprocess.run(process,stdout=subprocess.PIPE).stdout.decode('utf-8')
-                if print_subprocess:
-                    print(running)
-    else:
-        sys.path.extend([
-            'src'
-        ])
-    end_time = time.time()
-    print(f"..environment set up in {end_time-start_time:.0f} seconds")
-    return
-
-setup_environment()
-
-#————————————————————1.2. Imports————————————————————————
-
-import os
-import torch
-import random
-import clip
-import gradio as gr
-import re
-import random
-
-from base64 import b64encode
-
-#from k_diffusion.external import CompVisDenoiser, CompVisVDenoiser
-import py3d_tools as p3dT
-
-from IPython import display
-from types import SimpleNamespace
-from helpers.save_images import get_output_folder
-from helpers.settings import load_args
-from helpers.render import render_animation, render_input_video, render_image_batch, render_interpolation
-from helpers.model_load import make_linear_decode, load_model, get_model_output_paths
-from helpers.aesthetics import load_aesthetics_model
-from diffusers import DiffusionPipeline
-from transformers import (
-    WhisperForConditionalGeneration,
-    WhisperProcessor,
-)
-from share_btn import community_icon_html, loading_icon_html, share_js
-#from plms import PLMSSampler
-
-#from AdaBins-main import infer, model_io, utils
-#from AdaBins-main.models import unet_adaptive_bins.py
-
-import gradio as gr
-from datasets import load_dataset
-from PIL import Image  
-
-import requests
-
-#————————————————————1.3. Token Setup———————————————
-
-MY_SECRET_TOKEN=os.environ.get('HF_TOKEN_SD')
-device = "cuda" if torch.cuda.is_available() else "cpu" #is this needed?
-
-#———————————————————— infer from SD ———————————————
-
-"""
-word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=True)
-word_list = word_list_dataset["train"]['text']
-
-is_gpu_busy = False
-def infer(prompt, negative, scale):
-    global is_gpu_busy
-    for filter in word_list:
-        if re.search(rf"\b{filter}\b", prompt):
-            raise gr.Error("Unsafe content found. Please try again with different prompts.")
-        
-    images = []
-    url = os.getenv('JAX_BACKEND_URL')
-    payload = {'prompt': prompt, 'negative_prompt': negative, 'guidance_scale': scale}
-    images_request = requests.post(url, json = payload)
-    for image in images_request.json()["images"]:
-        image_b64 = (f"data:image/jpeg;base64,{image}")
-        images.append(image_b64)
-    
-    return images
-    """
-
-
-#————————————————————5.1 Gradio Interface ———————————————
-
-#CSS defines the style of the interface
-css = """
-        .gradio-container {
-            font-family: 'IBM Plex Sans', sans-serif;
-        }
-        .gr-button {
-            color: white;
-            border-color: black;
-            background: black;
-        }
-        input[type='range'] {
-            accent-color: black;
-        }
-        .dark input[type='range'] {
-            accent-color: #dfdfdf;
-        }
-        .container {
-            max-width: 730px;
-            margin: auto;
-            padding-top: 1.5rem;
-        }
-     
-        .details:hover {
-            text-decoration: underline;
-        }
-        .gr-button {
-            white-space: nowrap;
-        }
-        .gr-button:focus {
-            border-color: rgb(147 197 253 / var(--tw-border-opacity));
-            outline: none;
-            box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
-            --tw-border-opacity: 1;
-            --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
-            --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
-            --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
-            --tw-ring-opacity: .5;
-        }
-        .footer {
-            margin-bottom: 45px;
-            margin-top: 35px;
-            text-align: center;
-            border-bottom: 1px solid #e5e5e5;
-        }
-        .footer>p {
-            font-size: .8rem;
-            display: inline-block;
-            padding: 0 10px;
-            transform: translateY(10px);
-            background: #2596be; #changed this from: white;
-        }
-        .dark .footer {
-            border-color: #303030;
-            
-        }
-        .dark .footer>p {
-            background: #2596be; #changed this from 0b0f19;
-        }
-        .prompt h4{
-            margin: 1.25em 0 .25em 0;
-            font-weight: bold;
-            font-size: 115%;
-        }
-        .animate-spin {
-            animation: spin 1s linear infinite;
-        }
-        @keyframes spin {
-            from {
-                transform: rotate(0deg);
-            }
-            to {
-                transform: rotate(360deg);
-            }
-        }
-        #share-btn-container {
-            display: flex; margin-top: 1.5rem !important; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem;
-        }
-        #share-btn {
-            all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important;
-        }
-        #share-btn * {
-            all: unset;
-        }
-"""
-
-#creates the interface object with the style outlined above
-block = gr.Blocks(css=css)
-
-#HTML defines the layout of the interface
-with block:
-    gr.HTML(
-        """
-            <div style="text-align: center; max-width: 650px; margin: 0 auto;">
-              <div
-                style="
-                  display: inline-flex;
-                  align-items: center;
-                  gap: 0.8rem;
-                  font-size: 1.75rem;
-                "
-              >
-                <svg
-                  width="0.65em"
-                  height="0.65em"
-                  viewBox="0 0 115 115"
-                  fill="none"
-                  xmlns="http://www.w3.org/2000/svg"
-                >
-                  <rect width="23" height="23" fill="white"></rect>
-                  <rect y="69" width="23" height="23" fill="white"></rect>
-                  <rect x="23" width="23" height="23" fill="#AEAEAE"></rect>
-                  <rect x="23" y="69" width="23" height="23" fill="#AEAEAE"></rect>
-                  <rect x="46" width="23" height="23" fill="white"></rect>
-                  <rect x="46" y="69" width="23" height="23" fill="white"></rect>
-                  <rect x="69" width="23" height="23" fill="black"></rect>
-                  <rect x="69" y="69" width="23" height="23" fill="black"></rect>
-                  <rect x="92" width="23" height="23" fill="#D9D9D9"></rect>
-                  <rect x="92" y="69" width="23" height="23" fill="#AEAEAE"></rect>
-                  <rect x="115" y="46" width="23" height="23" fill="white"></rect>
-                  <rect x="115" y="115" width="23" height="23" fill="white"></rect>
-                  <rect x="115" y="69" width="23" height="23" fill="#D9D9D9"></rect>
-                  <rect x="92" y="46" width="23" height="23" fill="#AEAEAE"></rect>
-                  <rect x="92" y="115" width="23" height="23" fill="#AEAEAE"></rect>
-                  <rect x="92" y="69" width="23" height="23" fill="white"></rect>
-                  <rect x="69" y="46" width="23" height="23" fill="white"></rect>
-                  <rect x="69" y="115" width="23" height="23" fill="white"></rect>
-                  <rect x="69" y="69" width="23" height="23" fill="#D9D9D9"></rect>
-                  <rect x="46" y="46" width="23" height="23" fill="black"></rect>
-                  <rect x="46" y="115" width="23" height="23" fill="black"></rect>
-                  <rect x="46" y="69" width="23" height="23" fill="black"></rect>
-                  <rect x="23" y="46" width="23" height="23" fill="#D9D9D9"></rect>
-                  <rect x="23" y="115" width="23" height="23" fill="#AEAEAE"></rect>
-                  <rect x="23" y="69" width="23" height="23" fill="black"></rect>
-                </svg>
-                <h1 style="font-weight: 900; margin-bottom: 7px;">
-                  Hallucinate
-                </h1>
-              </div>
-              <p style="margin-bottom: 10px; font-size: 94%">
-                Instantly produce cinematics for your audio. &#10;&#13;
-                Create unique Spotify Canvases for all your tracks. &#10;&#13;
-              </p> 
-            </div>
-        """
-    )
-    
-    #within the group
-    with gr.Group():
-
-        #first create a box
-        with gr.Box():
-
-            #in the box create a row
-            with gr.Row().style(mobile_collapse=False, equal_height=True):
-
-                #in the row add a video input (left) #UPDATE THIS
-                image_input = gr.Image(
-                    label="Initialize with image",
-                    show_label=False,
-                    source="upload", #"microphone"
-                    type="filepath"
-                )
-
-                #in the row add a button to run the model (right) #UPDATE THIS
-                btn = gr.Button("Hallucinate")
-
-        #add an output field to the box      #UPDATE THIS
-        video_output = gr.Video(show_label=False, elem_id="result-textarea")
-        
-        #add share functions
-        with gr.Group(elem_id="share-btn-container"):
-            community_icon = gr.HTML(community_icon_html, visible=False)
-            loading_icon = gr.HTML(loading_icon_html, visible=False)
-            share_button = gr.Button("Share to community", elem_id="share-btn", visible=False)
-                                    
-        
-        #add button functions
-            
-    #the input button is here
-            
-        #btn.click(render_input_video, inputs=[video_input], outputs=[video_output, community_icon, loading_icon, share_button])
-        #share_button.click(None, [], [], _js=share_js)
-
-        #create footer
-        gr.HTML(
-            """
-                <div class="footer">
-                    <p>Experience by <a href="https://www.hallucinate.it/" style="text-decoration: underline;" target="_blank">Hallucinate</a> - Gradio Demo by 🤗 Hugging Face
-                    </p>
-                </div>
-           """
-        )
-        with gr.Accordion(label="License", open=False):
-            gr.HTML(
-                """<div class="acknowledgments">
-                    <p><h4>LICENSE</h4>
-The model is licensed with a <a href="https://huggingface.co/stabilityai/stable-diffusion-2/blob/main/LICENSE-MODEL" style="text-decoration: underline;" target="_blank">CreativeML OpenRAIL++</a> license. The authors claim no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in this license. The license forbids you from sharing any content that violates any laws, produce any harm to a person, disseminate any personal information that would be meant for harm, spread misinformation and target vulnerable groups. For the full list of restrictions please <a href="https://huggingface.co/spaces/CompVis/stable-diffusion-license" target="_blank" style="text-decoration: underline;" target="_blank">read the license</a></p>
-                    <p><h4>Biases and content acknowledgment</h4>
-Despite how impressive being able to turn text into image is, beware to the fact that this model may output content that reinforces or exacerbates societal biases, as well as realistic faces, pornography and violence. The model was trained on the <a href="https://laion.ai/blog/laion-5b/" style="text-decoration: underline;" target="_blank">LAION-5B dataset</a>, which scraped non-curated image-text-pairs from the internet (the exception being the removal of illegal content) and is meant for research purposes. You can read more in the <a href="https://huggingface.co/CompVis/stable-diffusion-v1-4" style="text-decoration: underline;" target="_blank">model card</a></p>
-               </div>
-                """
-            )
-
-#launch
-#block.launch()#share=True)
-
-
-
-
-
-
-#———————————————————— 1.4. Path Setup (input, output, drive)————————————————————————
-
-#this creates FileNotFoundError: [Errno 2] No such file or directory: 
-#/home/user/app/configs/v1-inference.yaml - is this a github link?
-#even though the yaml file is uploaded to files. yaml file should be available through DSD import?
-
-def Root():
-    models_path = "models" #@param {type:"string"}
-    configs_path = "configs" #@param {type:"string"}
-    output_path = "outputs" #@param {type:"string"}
-    mount_google_drive = True #@param {type:"boolean"}
-    models_path_gdrive = "/content/drive/MyDrive/AI/models" #@param {type:"string"}
-    output_path_gdrive = "/content/drive/MyDrive/AI/StableDiffusion" #@param {type:"string"}
-
-    #@markdown **Model Setup**
-    map_location = "cuda" #@param ["cpu", "cuda"]
-    model_config = "v1-inference.yaml" #@param ["custom","v2-inference.yaml","v2-inference-v.yaml","v1-inference.yaml"]
-    model_checkpoint =  "Protogen_V2.2.ckpt" #@param ["custom","v2-1_768-ema-pruned.ckpt","v2-1_512-ema-pruned.ckpt","768-v-ema.ckpt","512-base-ema.ckpt","Protogen_V2.2.ckpt","v1-5-pruned.ckpt","v1-5-pruned-emaonly.ckpt","sd-v1-4-full-ema.ckpt","sd-v1-4.ckpt","sd-v1-3-full-ema.ckpt","sd-v1-3.ckpt","sd-v1-2-full-ema.ckpt","sd-v1-2.ckpt","sd-v1-1-full-ema.ckpt","sd-v1-1.ckpt", "robo-diffusion-v1.ckpt","wd-v1-3-float16.ckpt"]
-    custom_config_path = "" #"https://github.com/realhallucinate/deforum-stable-diffusion-gradioUI/blob/main/configs/v1-inference.yaml"# replaced just an empty string: "" with a diret link #@param {type:"string"}
-    custom_checkpoint_path = "" #@param {type:"string"}
-    return locals()
-
-root = Root()
-root = SimpleNamespace(**root)
-
-root.models_path, root.output_path = get_model_output_paths(root)
-root.model, root.device = load_model(root, load_on_run_all=True, check_sha256=True, map_location=root.map_location)
-#root.model, root.device = load_model(root, load_on_run_all=True, check_sha256=True, map_location=torch.device('cpu'))
-
-
-#——————————————————— 2.1. Prompt Base ———————————————————————— #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-
-#need to update the prompt base
-
-medium = {"pixar image | matte painting | 3D render | oil painting | photograph | sculpture |digital illustration | watercolor | colored pencil sketch | photo shoot | acrylic painting"}
-description = {"silly | sexy | golden | exotic | beautiful | elegant | creepy | hilarious | evil | Angelic | sublime | ridiculous"}
-subject = {"rococo cauliflower headdress | cauliflower cornucopia | macro romanesco | cauliflower Cthulhu | cauliflower nuclear explosion | Cauliflower mushroom cloud | Hubble cauliflower nebula | cauliflower infestation | steampunk cauliflower | magic rubber cauliflower | psychedelic cauliflower | cauliflower couture"}
-details = {"flowers | ornaments | pearls | raindrops | glasses"}
-artist = {"[3$$ James Jean | Lucian Freud | tomm moore  | wes anderson  | ernst haeckl | tim burton  | jean pierre jeunet | jean giraud moebius | takashi murakami | ross draws |  artgerm |  alvin ailey |  Zdzisław Beksiński |  Arthur Rackham |  Dariusz Zawadzki |  thomas kincade  |  greg rutkowski  |  rembrandt |  HR Giger |  jama jurabaev | wenwei zhu | frank franzzeta | mcbess | sakimi chan | brosmind | steve simpson | jim henson | Nicoletta Ceccoli | Margaret Keane | Mark Ryden | Severin Krøyer | Marie Krøyer | Karl Madsen| Laurits Tuxen| Carl Locher| Viggo Johansen| Thorvald Niss | Holger Drachmann | Raluca bararu | walton ford | josh Keyes | Marco Mazzoni | Susan Helen Strok | R Crumb | Beatrix potter | shaw brothers | victor moscoso | Thomas Kinkade | Vincent Van Gogh | Leonid Afremov | Claude Monet | Edward Hopper | Norman Rockwell | William-Adolphe Bouguereau | Albert Bierstadt | John Singer Sargent | Pierre-Auguste Renoir | Frida Kahlo | John William Waterhouse | Winslow Homer | Walt Disney | Thomas Moran | Phil Koch | Paul Cézanne | Camille Pissarro | Erin Hanson | Thomas Cole | Raphael | Steve Henderson | Pablo Picasso | Caspar David Friedrich | Ansel Adams | Diego Rivera | Steve McCurry | Bob Ross | John Atkinson Grimshaw | Rob Gonsalves | Paul Gauguin | James Tissot | Edouard Manet | Alphonse Mucha | Alfred Sisley | Fabian Perez | Gustave Courbet | Zaha Hadid | Jean-Léon Gérôme | Carl Larsson | Mary Cassatt | Sandro Botticelli | Daniel Ridgway Knight | Joaquín Sorolla | Andy Warhol | Kehinde Wiley | Alfred Eisenstaedt | Gustav Klimt | Dante Gabriel Rossetti | Tom Thomson | Edgar Degas | Utagawa Hiroshige | Camille Corot | Edward Steichen | David Hockney | Ivan Aivazovsky | Josephine Wall | Peter Paul Rubens | Henri Rousseau | Edward Burne-Jones | Pixar | Alexander McQueen | Anders Zorn | Jean Auguste Dominique Ingres | Franz Xaver Winterhalter | Katsushika Hokusai | John Constable | Canaletto | Shepard Fairey | Gordon Parks | George Inness | Anthony van Dyck | Vivian Maier | Catrin Welz-Stein | Lawren Harris | Salvador Dali | David Bowie | Agnes Cecile | Titian | Martin Johnson Heade | Scott Naismith | William Morris | Berthe Morisot | Vladimir Kush | William Holman Hunt | Edvard Munch | Joseph Mallord William Turner | Gustave Doré | Thomas Eakins | Ilya Repin | Amedeo Modigliani | Johannes Vermeer | Eyvind EarleIvan Shishkin | Rembrandt Van Rijn | Gil Elvgren | Nicholas Roerich | Henri Matisse | Thomas Gainsborough | Artgerm | Studio Ghibli | Grant Wood | Jeremy Mann | Mark Keathley | Maxfield Parrish | Andrew Wyeth | RHADS | David Lynch | Frederic Remington | Jan Van Eyck | Mikko Lagerstedt | Banksy | Michael Cheval | Anna Razumovskaya | Jean-François Millet | Thomas W Schaller | Charlie Bowater | El Greco | Paolo Roversi | Carne Griffiths | Man Ray | August Sander | Andrew Macara | Evelyn De Morgan | William Blake | Sally Mann | Oleg Oprisco | Yuumei | Helmut Newton | Henry Ossawa Tanner | Asher Brown Durand | teamLab | August Macke | Armand Guillaumin | Terry Redlin | Antoine Blanchard | Anna Ancher | Ohara Koson | Walter Langley | Yayoi Kusama | Stan Lee | Chuck Close | Albert Edelfelt | Mark Seliger | Eugene Delacroix | John Lavery | Theo van Rysselberghe | Marc Chagall | Rolf Armstrong | Brent Heighton | A.J.Casson | Egon Schiele | Maximilien Luce | Georges Seurat | George Frederic Watts | Arthur Hughes | Anton Mauve | Lucian Freud | Jessie Willcox Smith | Leonardo Da Vinci | Edward John Poynter | Brooke Shaden | J.M.W. Turner | Wassily Kandinsky | Wes Anderson | Jean-Honoré Fragonard | Amanda Clark | Tom Roberts | Antonello da Messina | Makoto Shinkai | Hayao Miyazaki | Slim Aarons | Alfred Stevens | Albert Lynch | Andre Kohn | Daniel Garber | Jacek Yerka | Beatrix Potter | Rene Magritte | Georgia O'Keeffe | Isaac Levitan | Frank Lloyd Wright | Gustave Moreau | Ford Madox Brown | Ai Weiwei | Tim Burton | Alfred Cheney Johnston | Duy Huynh | Michael Parkes | Tintoretto | Archibald Thorburn | Audrey Kawasaki | George Lucas | Arthur Streeton | Albrecht Durer | Andrea Kowch | Dorina Costras | Alex Ross | Hasui Kawase | Lucas Cranach the Elder | Briton Rivière | Antonio Mora | Mandy Disher | Henri-Edmond Cross | Auguste Toulmouche | Hubert Robert | Syd Mead | Carl Spitzweg | Alyssa Monks | Edward Lear | Ralph McQuarrie | Sailor Moon | Simon Stalenhag | Edward Robert Hughes | Jules Bastien-Lepage | Richard S. Johnson | Rockwell Kent | Sparth | Arnold Böcklin | Lovis Corinth | Arnold Bocklin | Robert Hagan | Gregory Crewdson | Thomas Benjamin Kennington | Abbott Handerson Thayer | Gilbert Stuart | Louis Comfort Tiffany | Raphael Lacoste | Jean Marc Nattier | Janek Sedlar | Sherree Valentine Daines | Alexander Jansson | James Turrell | Alex Grey | Henri De Toulouse Lautrec | Anton Pieck | Ramon Casas | Andrew Atroshenko | Andy Kehoe | Andreas Achenbach | H.P. Lovecraft | Eric Zener | Kunisada | Jimmy Lawlor | Quentin Tarantino | Marianne North | Vivienne Westwood | Tom Bagshaw | Jeremy Lipking | John Martin | Cindy Sherman | Scott Listfield | Alexandre Cabanel | Arthur Rackham | Arthur Hacker | Henri Fantin Latour | Mark Ryden | Peter Holme IIIT | ed Nasmith | Bill Gekas | Paul Strand | Anne Stokes | David Teniers the Younger | Alan Lee | Ed Freeman | Andrey Remnev | Alasdair McLellan | Botero | Vittorio Matteo Corcos | Ed Mell | Worthington Whittredge | Jakub Różalski | Alex Gross | Edward Weston | Ilya Kuvshinov | Francisco De Goya | Balthus | J.C. Leyendecker | Nathan Wirth]"}
-realism = {"[4$$ highly detailed | photorealistic | realistic | hypermaximalist | hyperrealism, intricate | HD | 8k | 4k | octane render | subsurface scattering raytracing | depth of field | bokeh | redshift render | abstract illusionism | Atmospheric | Dramatic lighting | Anthropomorphic | 8k | Very detailed | Cinematic lighting | Unreal engine | Octane render | Photorealistic | Hyperrealistic | Sharp focus | Rim lighting | Soft lighting | Volumetric | Surreal | Realistic CGI | Fantastic backlight | HDR | Studio light | Internal glow | Iridescent | Cyberpunk | Steampunk | Intricate  | filigree | Bionic futurism | Ray tracing | Symmetrical | Atompunk | Multiverse | Concept art | Time loop | Maximum texture | Futurism | Dynamic | retrowave | afrofuturism | intricate and highly detailed |  intricate and highly detailed |  intricate and highly detailed |  intricate and highly detailed |  intricate and highly detailed | photorealistic |  photorealistic |  photorealistic |  photorealistic]"}
-repository = {"Artstation"}
-#setting = {"corporate office setting | abandoned warehouse | schoolhouse | victorian train station | victorian room | Lake | Field of wild flowers | submarine | tennis court | mcdonalds | swamp | assembly line | surface of the moon | museum | outer space |storefront display"}
-#time = {"morning | noon | night | evening | dawn"}
-
-#'animation_mode: None' (default) batches on this list of 'prompts'
-prompts = [
-    f"A beautiful {medium} of a {description}{subject} with {details}, in the style of {artist}. {realism} design, trending on {repository}"
-]
-
-#——————————————————— 2.2. Prompt Template Builder ————————————————————————
-
-#a function to select a set of prompts
-
-# Define the `pick_variant` function that takes in a template string
-def pick_variant(template):
-  # If the template is None, return None
-  if template is None:
-    return None
-
-  # Set `out` to be the template string
-  out = template
-  
-  # Use a regular expression to find all instances of `{...}` in the template
-  # The regular expression `r'\{[^{}]*?}'` searches for all sequences of characters
-  # surrounded by curly braces that do not contain other curly braces.
-  variants = re.findall(r'\{[^{}]*?}', out)
-
-  # Iterate over each variant found in the template
-  for v in variants:
-    # Split the variant string by the vertical bar (|)
-    opts = v.strip("{}").split('|')
-    # Replace the variant in the `out` string with a random option
-    out = out.replace(v, random.choice(opts))
-  
-  # Use a regular expression to find all instances of `[...]` in the template
-  # The regular expression `r'\[[^\[\]]*?]'` searches for all sequences of characters
-  # surrounded by square brackets that do not contain other square brackets.
-  combinations = re.findall(r'\[[^\[\]]*?]', out)
-
-  # Iterate over each combination found in the template
-  for c in combinations:
-    # Remove the square brackets from the combination
-    sc = c.strip("[]")
-    # Split the combination string by '$$'
-    parts = sc.split('$$')
-    # Initialize the number of options to pick to `None`
-    n_pick = None
-
-    # If there are more than 2 parts, raise an error
-    if len(parts) > 2:
-      raise ValueError(" we do not support more than 1 $$ in a combination")
-    # If there are 2 parts, set the number of options to pick to the first part
-    if len(parts) == 2:
-      sc = parts[1]
-      n_pick = int(parts[0]) 
-    # Split the combination string by the vertical bar (|)
-    opts = sc.split('|')
-    # If the number of options to pick is not set, set it to a random integer between 1 and the number of options
-    if not n_pick:
-      n_pick = random.randint(1,len(opts))
-
-    # Sample `n_pick` options from the options list
-    sample = random.sample(opts, n_pick)
-    # Replace the combination in the `out` string with a comma-separated string of the picked options
-    out = out.replace(c, ', '.join(sample))
-
-  # If there were any variants or combinations found in the template, call `pick_variant` again with the new `out` string
-  if len(variants+combinations) > 0:
-    return pick_variant(out)
-  # If there were no variants or combinations found, return the final `out` string
-  return out
-
-#'animation_mode: None' (default) batches on this list of 'prompts'
-for prompt in prompts:
-  text_prompt = pick_variant(prompt)
-
-#print('Text prompt selected:', "\n")
-#print(text_prompt)
-
-#———————————————————— 2.3. Prompt Selector: Video ————————————————————————
-
-#create a string of frame intervals and prompts
-def prompt_intervals(prompts, framecount, stepsize):
-
-  timesteps = []
-  for frame in range(0, framecount):
-    timesteps.append(frame * stepsize)
-
-  animation_prompt = ""
-  for timestep in timesteps:
-    for prompt in prompts:
-      p = pick_variant(prompt)
-      animation_prompt += (str(timestep) + ": " + p + ", ")
-  
-  animation_prompts = str(animation_prompt)
-  return animation_prompts
-
-#@markdown Here you can select framecount and stepsize and create a selection of animation prompts
-
-#MAKE INTERACTABLE IN DEMO? OR HAVE FIXED 8 FPS?
-framecount = 8 #fps #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-stepsize = 25 #time interval between prompts #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-
-#'animation_mode: 2D' works with this list of 'animation_prompts'
-animation_prompts = prompt_intervals(prompts, framecount, stepsize)
-
-#print('Animation prompts selected:',"\n")
-#print(animation_prompts)
-
-
-#———————————————————— 3.1. Video Settings————————————————————————
-    #HARDCODE THE DIFFERENT CAMERA SETTINGS HERE LATER?
-
-#This function only sets and outputs the arguments for the ANIMATION process
-def DeforumAnimArgs():
-
-    #ANIMATION_MODE IS A KEY ARG!
-    
-    #@markdown ####**Animation:**
-    animation_mode = '3D' #@param ['None', '2D', '3D', 'Video Input', 'Interpolation'] {type:'string'} #THIS IS A KEY ARG!
-    max_frames = 1000 #@param {type:"number"}
-    border = 'replicate' #@param ['wrap', 'replicate'] {type:'string'}
-
-    #@markdown ####**Motion Parameters:**
-    angle = "0:(0)"#@param {type:"string"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    zoom = "0:(1.04)"#@param {type:"string"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    translation_x = "0:(10*sin(2*3.14*t/10))"#@param {type:"string"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    translation_y = "0:(0)"#@param {type:"string"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    translation_z = "0:(10)"#@param {type:"string"}#----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    rotation_3d_x = "0:(0)"#@param {type:"string"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    rotation_3d_y = "0:(0)"#@param {type:"string"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    rotation_3d_z = "0:(0)"#@param {type:"string"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    flip_2d_perspective = False #@param {type:"boolean"}
-    perspective_flip_theta = "0:(0)"#@param {type:"string"}
-    perspective_flip_phi = "0:(t%15)"#@param {type:"string"}
-    perspective_flip_gamma = "0:(0)"#@param {type:"string"}
-    perspective_flip_fv = "0:(53)"#@param {type:"string"}
-    noise_schedule = "0: (0.02)"#@param {type:"string"}
-    strength_schedule = "0: (0.65)"#@param {type:"string"}
-    contrast_schedule = "0: (1.0)"#@param {type:"string"}
-    hybrid_video_comp_alpha_schedule = "0:(1)" #@param {type:"string"}
-    hybrid_video_comp_mask_blend_alpha_schedule = "0:(0.5)" #@param {type:"string"}
-    hybrid_video_comp_mask_contrast_schedule = "0:(1)" #@param {type:"string"}
-    hybrid_video_comp_mask_auto_contrast_cutoff_high_schedule =  "0:(100)" #@param {type:"string"}
-    hybrid_video_comp_mask_auto_contrast_cutoff_low_schedule =  "0:(0)" #@param {type:"string"}
-
-    #@markdown ####**Unsharp mask (anti-blur) Parameters:**
-    kernel_schedule = "0: (5)"#@param {type:"string"}
-    sigma_schedule = "0: (1.0)"#@param {type:"string"}
-    amount_schedule = "0: (0.2)"#@param {type:"string"}
-    threshold_schedule = "0: (0.0)"#@param {type:"string"}
-
-    #@markdown ####**Coherence:**
-    color_coherence = 'Match Frame 0 LAB' #@param ['None', 'Match Frame 0 HSV', 'Match Frame 0 LAB', 'Match Frame 0 RGB', 'Video Input'] {type:'string'}
-    color_coherence_video_every_N_frames = 1 #@param {type:"integer"}
-    diffusion_cadence = '1' #@param ['1','2','3','4','5','6','7','8'] {type:'string'}
-
-    #@markdown ####**3D Depth Warping:**
-    use_depth_warping = True #@param {type:"boolean"}
-    midas_weight = 0.3#@param {type:"number"}
-    near_plane = 200
-    far_plane = 10000
-    fov = 40#@param {type:"number"}
-    padding_mode = 'border'#@param ['border', 'reflection', 'zeros'] {type:'string'}
-    sampling_mode = 'bicubic'#@param ['bicubic', 'bilinear', 'nearest'] {type:'string'}
-    save_depth_maps = False #@param {type:"boolean"}
-
-#video input here
-    
-    #@markdown ####**Video Input:**
-    video_init_path = image_input #'/content/video_in.mp4'#@param {type:"string"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    extract_nth_frame = 1#@param {type:"number"}
-    overwrite_extracted_frames = True #@param {type:"boolean"}
-    use_mask_video = False #@param {type:"boolean"}
-    video_mask_path ='/content/video_in.mp4'#@param {type:"string"}
-
-    #@markdown ####**Hybrid Video for 2D/3D Animation Mode:**
-    hybrid_video_generate_inputframes = False #@param {type:"boolean"}
-    hybrid_video_use_first_frame_as_init_image = True #@param {type:"boolean"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    hybrid_video_motion = "None" #@param ['None','Optical Flow','Perspective','Affine']
-    hybrid_video_flow_method = "Farneback" #@param ['Farneback','DenseRLOF','SF']
-    hybrid_video_composite = False #@param {type:"boolean"}
-    hybrid_video_comp_mask_type = "None" #@param ['None', 'Depth', 'Video Depth', 'Blend', 'Difference']
-    hybrid_video_comp_mask_inverse = False #@param {type:"boolean"}
-    hybrid_video_comp_mask_equalize = "None" #@param  ['None','Before','After','Both']
-    hybrid_video_comp_mask_auto_contrast = False #@param {type:"boolean"}
-    hybrid_video_comp_save_extra_frames = False #@param {type:"boolean"}
-    hybrid_video_use_video_as_mse_image = False #@param {type:"boolean"}
-
-    #@markdown ####**Interpolation:**
-    interpolate_key_frames = False #@param {type:"boolean"}
-    interpolate_x_frames = 4 #@param {type:"number"}
-    
-    #@markdown ####**Resume Animation:**
-    resume_from_timestring = False #@param {type:"boolean"}
-    resume_timestring = "20220829210106" #@param {type:"string"}
-
-    return locals()    
-
-
-#———————————————————— 4.1. Run (create and return images)————————————————————————
-    
-#@markdown **Load Settings**
-override_settings_with_file = False #@param {type:"boolean"}
-settings_file = "custom" #@param ["custom", "512x512_aesthetic_0.json","512x512_aesthetic_1.json","512x512_colormatch_0.json","512x512_colormatch_1.json","512x512_colormatch_2.json","512x512_colormatch_3.json"]
-custom_settings_file = "/content/drive/MyDrive/Settings.txt"#@param {type:"string"}
-
-#This function only sets and outputs the arguments for the INFERENCE process
-def DeforumArgs():
-    #@markdown **Image Settings**
-    W = 540 #@param
-    H = 540 #@param
-    W, H = map(lambda x: x - x % 64, (W, H))  # resize to integer multiple of 64
-    bit_depth_output = 8 #@param [8, 16, 32] {type:"raw"}
-
-    #@markdown **Sampling Settings**
-    seed = 1 #@param 
-    sampler = 'euler_ancestral' #@param ["klms","dpm2","dpm2_ancestral","heun","euler","euler_ancestral","plms", "ddim", "dpm_fast", "dpm_adaptive", "dpmpp_2s_a", "dpmpp_2m"]
-    steps = 25 #@param #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    scale = 7 #@param
-    ddim_eta = 0.0 #@param
-    dynamic_threshold = None
-    static_threshold = None   
-
-    #@markdown **Save & Display Settings**
-    save_samples = False #@param {type:"boolean"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    save_settings = False #@param {type:"boolean"}
-    display_samples = False #@param {type:"boolean"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    save_sample_per_step = False #@param {type:"boolean"}
-    show_sample_per_step = False #@param {type:"boolean"}
-
-    #@markdown **Prompt Settings**
-    prompt_weighting = True #@param {type:"boolean"}
-    normalize_prompt_weights = True #@param {type:"boolean"}
-    log_weighted_subprompts = False #@param {type:"boolean"}
-
-    #@markdown **Batch Settings**
-    n_batch = 12 #@param #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-   
-    batch_name = "HuggingTest1" #@param {type:"string"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    filename_format = "{timestring}_{index}_{prompt}.png" #@param ["{timestring}_{index}_{seed}.png","{timestring}_{index}_{prompt}.png"]
-    seed_behavior = "iter" #@param ["iter","fixed","random","ladder","alternate"] #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    seed_iter_N = 1 #@param {type:'integer'} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    make_grid = False #@param {type:"boolean"}
-    grid_rows = 2 #@param 
-    outdir = get_output_folder(root.output_path, batch_name) #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-
-    #@markdown **Init Settings**
-    use_init = False #@param {type:"boolean"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    strength = 0.75 #@param {type:"number"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    strength_0_no_init = True # Set the strength to 0 automatically when no init image is used
-    init_image = "/content/drive/MyDrive/AI/init_images/Hallucinate.png" #@param {type:"string"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    # Whiter areas of the mask are areas that change more
-    use_mask = False #@param {type:"boolean"} #----------------CONSIDER THIS FOR INPUT/LOCK---------------
-    use_alpha_as_mask = False # use the alpha channel of the init image as the mask
-    mask_file = "https://www.filterforge.com/wiki/images/archive/b/b7/20080927223728%21Polygonal_gradient_thumb.jpg" #@param {type:"string"}
-    invert_mask = False #@param {type:"boolean"}
-    # Adjust mask image, 1.0 is no adjustment. Should be positive numbers.
-    mask_brightness_adjust = 1.0  #@param {type:"number"}
-    mask_contrast_adjust = 1.0  #@param {type:"number"}
-    # Overlay the masked image at the end of the generation so it does not get degraded by encoding and decoding
-    overlay_mask = True  # {type:"boolean"}
-    # Blur edges of final overlay mask, if used. Minimum = 0 (no blur)
-    mask_overlay_blur = 5 # {type:"number"}
-
-    #@markdown **Exposure/Contrast Conditional Settings**
-    mean_scale = 0 #@param {type:"number"}
-    var_scale = 0 #@param {type:"number"}
-    exposure_scale = 0 #@param {type:"number"}
-    exposure_target = 0.5 #@param {type:"number"}
-
-    #@markdown **Color Match Conditional Settings**
-    colormatch_scale = 0 #@param {type:"number"}
-    colormatch_image = "https://www.saasdesign.io/wp-content/uploads/2021/02/palette-3-min-980x588.png" #@param {type:"string"}
-    colormatch_n_colors = 4 #@param {type:"number"}
-    ignore_sat_weight = 0 #@param {type:"number"}
-
-    #@markdown **CLIP\Aesthetics Conditional Settings**
-    clip_name = 'ViT-L/14' #@param ['ViT-L/14', 'ViT-L/14@336px', 'ViT-B/16', 'ViT-B/32']
-    clip_scale = 0 #@param {type:"number"}
-    aesthetics_scale = 0 #@param {type:"number"}
-    cutn = 1 #@param {type:"number"}
-    cut_pow = 0.0001 #@param {type:"number"}
-
-    #@markdown **Other Conditional Settings**
-    init_mse_scale = 0 #@param {type:"number"}
-    init_mse_image = "https://cdn.pixabay.com/photo/2022/07/30/13/10/green-longhorn-beetle-7353749_1280.jpg" #@param {type:"string"}
-
-    blue_scale = 0 #@param {type:"number"}
-    
-    #@markdown **Conditional Gradient Settings**
-    gradient_wrt = 'x0_pred' #@param ["x", "x0_pred"]
-    gradient_add_to = 'both' #@param ["cond", "uncond", "both"]
-    decode_method = 'linear' #@param ["autoencoder","linear"]
-    grad_threshold_type = 'dynamic' #@param ["dynamic", "static", "mean", "schedule"]
-    clamp_grad_threshold = 0.2 #@param {type:"number"}
-    clamp_start = 0.2 #@param
-    clamp_stop = 0.01 #@param
-    grad_inject_timing = list(range(1,10)) #@param
-
-    #@markdown **Speed vs VRAM Settings**
-    cond_uncond_sync = True #@param {type:"boolean"}
-
-    n_samples = 1 # doesnt do anything
-    precision = 'autocast' 
-    C = 4
-    f = 8
-
-    prompt = ""
-    timestring = ""
-    init_latent = None
-    init_sample = None
-    init_sample_raw = None
-    mask_sample = None
-    init_c = None
-    seed_internal = 0
-
-    return locals()
-
-#This segment prepares arguments and adjusts settings
-
-# Define default arguments for the program
-args_dict = DeforumArgs()
-anim_args_dict = DeforumAnimArgs()
-
-# Override default arguments with values from settings file, if specified
-if override_settings_with_file:
-    load_args(args_dict, anim_args_dict, settings_file, custom_settings_file, verbose=False)
-
-# Create SimpleNamespace objects for arguments and animation arguments
-args = SimpleNamespace(**args_dict)
-anim_args = SimpleNamespace(**anim_args_dict)
-
-# Set timestring to current time in YYYYMMDDHHMMSS format
-args.timestring = time.strftime('%Y%m%d%H%M%S')
-# Ensure strength is within valid range of 0.0 to 1.0
-args.strength = max(0.0, min(1.0, args.strength))
-
-# Load clip model if using clip guidance or aesthetics model if aesthetics_scale is > 0
-if (args.clip_scale > 0) or (args.aesthetics_scale > 0):
-    # Load clip model and set to evaluation mode without requiring gradient
-    root.clip_model = clip.load(args.clip_name, jit=False)[0].eval().requires_grad_(False).to(root.device)
-    if (args.aesthetics_scale > 0):
-        # Load aesthetics model if aesthetics_scale is > 0
-        root.aesthetics_model = load_aesthetics_model(args, root)
-
-# Set seed to a random number if not specified
-if args.seed == -1:
-    args.seed = random.randint(0, 2**32 - 1)
-
-# If not using init image, set init_image to None
-if not args.use_init:
-    args.init_image = None
-
-# If using plms sampler with init image or animation mode isn't None, switch to klms sampler
-if args.sampler == 'plms' and (args.use_init or anim_args.animation_mode != 'None'):
-    print(f"Init images aren't supported with PLMS yet, switching to KLMS")
-    args.sampler = 'klms'
-
-# If not using ddim sampler, set ddim_eta to 0
-if args.sampler != 'ddim':
-    args.ddim_eta = 0
-
-# Set max_frames to 1 if animation mode is None, or use_init to True if animation mode is Video Input
-if anim_args.animation_mode == 'None':
-    anim_args.max_frames = 1
-elif anim_args.animation_mode == 'Video Input':
-    args.use_init = True
-
-# Clean up unused memory and empty CUDA cache
-gc.collect()
-torch.cuda.empty_cache()
-
-# Dispatch to appropriate renderer based on animation mode
-#These are probably imported from stable diffusion
-
-#lets try to place it within an infer function
-def infer(args, anim_args, animation_prompts, root, prompts):
-    #render animation (the main one)
-    if anim_args.animation_mode == '2D' or anim_args.animation_mode == '3D':
-        render_animation(args, anim_args, animation_prompts, root)
-    
-    #render input video
-    elif anim_args.animation_mode == 'Video Input':
-        render_input_video(args, anim_args, animation_prompts, root)
-    
-    #render interpolation
-    elif anim_args.animation_mode == 'Interpolation':
-        render_interpolation(args, anim_args, animation_prompts, root)
-    
-    #render image batch 
-    else:
-        render_image_batch(args, prompts, root)
-
-infer(args, anim_args, animation_prompts, root, prompts)
-
-#———————————————————— 4.2. Launch? ————————————————————————
-block.queue(concurrency_count=80, max_size=100).launch(max_threads=150) #from SD to balance/limit requests
-
-with block:
-    with gr.Group():
-        btn.click(infer, inputs=[image_input], outputs=[video_output, community_icon, loading_icon, share_button])
-block.launch()#share=True)
-
-
-
-#———————————————————— 4.2. Create Videos from Frames ————————————————————————
-
-#set FPS / video speed
-#skip_video_for_run_all = False #@param {type: 'boolean'}
-fps = 12 #@param {type:"number"} #HARDCODED FPS HERE: CONSIDER GIVING OPTION TO USERS 
-
-#manual settings for paths
-
-#@markdown **Manual Settings**
-use_manual_settings = False #@param {type:"boolean"}  #MOD THIS?
-image_path = "/content/drive/MyDrive/AI/StableDiffusion/2023-02/Test14/0_%05d.png" #@param {type:"string"}  #MOD THIS?
-mp4_path = "/content/drive/MyDrive/AI/StableDiffusion/2023-02/Test14/0_%05d.mp4" #@param {type:"string"}  #MOD THIS?
-render_steps = False  #@param {type: 'boolean'}
-path_name_modifier = "x0_pred" #@param ["x0_pred","x"]
-make_gif = False
-bitdepth_extension = "exr" if args.bit_depth_output == 32 else "png"
-
-# render steps from a single image
-if render_steps: 
-    
-  # get file name and directory of latest output directory
-  fname = f"{path_name_modifier}_%05d.png" #MOD THIS?
-  all_step_dirs = [os.path.join(args.outdir, d) for d in os.listdir(args.outdir) if os.path.isdir(os.path.join(args.outdir,d))]
-  newest_dir = max(all_step_dirs, key=os.path.getmtime)
-    
-  # create image and video paths
-  image_path = os.path.join(newest_dir, fname)
-  mp4_path = os.path.join(newest_dir, f"{args.timestring}_{path_name_modifier}.mp4")
-  max_frames = str(args.steps)
-
-# render images for a video
-else: 
-  # create image and video paths with timestamp and bit depth extension
-  image_path = os.path.join(args.outdir, f"{args.timestring}_%05d.{bitdepth_extension}")
-  mp4_path = os.path.join(args.outdir, f"{args.timestring}.mp4")
-  max_frames = str(anim_args.max_frames)
-
-#-------
-    
-# make video
-# create a list with the command and its parameters to call ffmpeg to encode images into an mp4 video
-cmd = [
-    'ffmpeg',  # specify the name of the executable command
-    '-y',  # overwrite output files without asking
-    '-vcodec', bitdepth_extension,  # specify the video codec to be used
-    '-r', str(fps),  # specify the frames per second (fps) of the output video
-    '-start_number', str(0),  # specify the starting number of the image sequence
-    '-i', image_path,  # specify the input image sequence (using format specifier)
-    '-frames:v', max_frames,  # specify the number of frames to be encoded
-    '-c:v', 'libx264',  # specify the video codec to be used for encoding
-    '-vf',
-    f'fps={fps}',  # specify the fps of the output video again
-    '-pix_fmt', 'yuv420p',  # specify the pixel format of the output video
-    '-crf', '17',  # specify the constant rate factor (crf) for video quality
-    '-preset', 'veryfast',  # specify the encoding speed preset
-    '-pattern_type', 'sequence',  # specify the type of pattern used for input file names
-    mp4_path  # specify the output mp4 video file path and name
-]
-
-# call the ffmpeg command using subprocess to encode images into an mp4 video
-process = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
-stdout, stderr = process.communicate()
-
-if process.returncode != 0:  # if ffmpeg command execution returns non-zero code, indicating an error
-    # print the error message and raise an exception
-    #print(stderr)
-    raise RuntimeError(stderr)
-
-
-#display video
-mp4 = open(mp4_path,'rb').read()
-#data_url = "data:video/mp4;base64," + b64encode(mp4).decode()
-#display.display(display.HTML(f'<video controls loop><source src="{data_url}" type="video/mp4"></video>') )
-
-#make gif
-if make_gif:
-    gif_path = os.path.splitext(mp4_path)[0]+'.gif'
-    cmd_gif = [
-        'ffmpeg',
-        '-y',
-        '-i', mp4_path,
-        '-r', str(fps),
-        gif_path
-    ]
-    process_gif = subprocess.Popen(cmd_gif, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
-
-
-#————————————————————5.1 Add Examples to interface ————————————————————————
-
-#Add examples: see line 158 and 307 at https://huggingface.co/spaces/stabilityai/stable-diffusion/blob/main/app.py
-
-
-
-
-
-#—————————————————————————————
-
-
-#the function fn can be either
-    #render_animation,
-    #render_input_video(args, anim_args, animation_prompts, root),
-    #render_interpolation,
-    #render_image_batch
-    #depending on animation_mode (268)
-
-#the output will be in the variable 'mp4' (or in 'mp4_path' , see 609)
-
-#—————————————————Launch Demo—————————————————————————————
-demo = gr.Interface(fn= infer, inputs=image_input, outputs=mp4, title=title, description=description, article=article)
-demo.launch()
-#demo.launch(auth = ("demo", "demo"), auth_message = "Enter username and password to access application")
diff --git a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/fairseq/optim/adam.py b/spaces/HarryLee/eCommerceImageCaptioning/fairseq/fairseq/optim/adam.py
deleted file mode 100644
index d3ae9e64a74774310adcd9968d2eae23368890f9..0000000000000000000000000000000000000000
--- a/spaces/HarryLee/eCommerceImageCaptioning/fairseq/fairseq/optim/adam.py
+++ /dev/null
@@ -1,239 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import logging
-import math
-from collections.abc import Collection
-from dataclasses import dataclass, field
-from typing import Any, List
-
-import torch
-import torch.distributed as dist
-import torch.optim
-from fairseq.dataclass import FairseqDataclass
-from fairseq.optim import FairseqOptimizer, register_optimizer
-from fairseq.optim.fused_adam import get_fused_adam_class
-from omegaconf import II, OmegaConf
-
-
-logger = logging.getLogger(__name__)
-
-
-@dataclass
-class FairseqAdamConfig(FairseqDataclass):
-    adam_betas: Any = field(
-        default=(0.9, 0.999), metadata={"help": "betas for Adam optimizer"}
-    )
-    adam_eps: float = field(
-        default=1e-8, metadata={"help": "epsilon for Adam optimizer"}
-    )
-    weight_decay: float = field(default=0.0, metadata={"help": "weight decay"})
-    use_old_adam: bool = field(
-        default=False, metadata={"help": "Use fairseq.optim.adam.Adam"}
-    )
-    fp16_adam_stats: bool = field(
-        default=False, metadata={"help": "use FP16 stats (with automatic scaling)"}
-    )
-    # TODO common vars below in parent
-    tpu: bool = II("common.tpu")
-    lr: List[float] = II("optimization.lr")
-
-
-@register_optimizer("adam", dataclass=FairseqAdamConfig)
-class FairseqAdam(FairseqOptimizer):
-    """Adam optimizer for fairseq.
-
-    Important note: this optimizer corresponds to the "AdamW" variant of
-    Adam in its weight decay behavior. As such, it is most closely
-    analogous to torch.optim.AdamW from PyTorch.
-    """
-
-    def __init__(self, cfg: FairseqAdamConfig, params):
-        super().__init__(cfg)
-        fused_adam_cls = get_fused_adam_class()
-        use_fused_adam = (
-            not getattr(cfg, "use_old_adam", False)
-            and fused_adam_cls is not None
-            and torch.cuda.is_available()
-        )
-        if getattr(cfg, "tpu", False):
-            if self.cfg.fp16_adam_stats:
-                raise NotImplementedError("--fp16-adam-stats is only supported on GPU")
-            # on TPUs we use the Adam defined here, since it
-            # automatically casts gradients to FP32
-            self._optimizer = Adam(params, **self.optimizer_config)
-        elif use_fused_adam:
-            logger.info("using FusedAdam")
-            self._optimizer = fused_adam_cls(
-                params,
-                use_fp16_stats=self.cfg.fp16_adam_stats,
-                **self.optimizer_config
-            )
-        else:
-            if self.cfg.fp16_adam_stats:
-                raise NotImplementedError("--fp16-adam-stats is only supported with FusedAdamV1")
-            self._optimizer = Adam(params, **self.optimizer_config)
-
-    @property
-    def optimizer_config(self):
-        """
-        Return a kwarg dictionary that will be used to override optimizer
-        args stored in checkpoints. This allows us to load a checkpoint and
-        resume training using a different set of optimizer args, e.g., with a
-        different learning rate.
-        """
-        return {
-            "lr": self.cfg.lr[0]
-            if isinstance(self.cfg.lr, Collection)
-            else self.cfg.lr,
-            "betas": eval(self.cfg.adam_betas)
-            if isinstance(self.cfg.adam_betas, str)
-            else OmegaConf.to_container(self.cfg.adam_betas),
-            "eps": self.cfg.adam_eps,
-            "weight_decay": self.cfg.weight_decay,
-        }
-
-    def average_params(self):
-        """Reduce Params is only used during BMUF distributed training."""
-        state_dict = self.optimizer.state_dict()
-        total_gpus = float(dist.get_world_size())
-
-        for _, value in state_dict["state"].items():
-            value["exp_avg"] /= total_gpus
-            value["exp_avg_sq"] /= total_gpus
-            dist.all_reduce(value["exp_avg"], op=dist.ReduceOp.SUM)
-            dist.all_reduce(value["exp_avg_sq"], op=dist.ReduceOp.SUM)
-
-
-class Adam(torch.optim.Optimizer):
-    r"""Implements Adam algorithm.
-
-    This implementation is modified from torch.optim.Adam based on:
-    `Fixed Weight Decay Regularization in Adam`
-    (see https://arxiv.org/abs/1711.05101)
-
-    It has been proposed in `Adam: A Method for Stochastic Optimization`_.
-
-    Args:
-        params (iterable): iterable of parameters to optimize or dicts defining
-            parameter groups
-        lr (float, optional): learning rate (default: 1e-3)
-        betas (Tuple[float, float], optional): coefficients used for computing
-            running averages of gradient and its square (default: (0.9, 0.999))
-        eps (float, optional): term added to the denominator to improve
-            numerical stability (default: 1e-8)
-        weight_decay (float, optional): weight decay (L2 penalty) (default: 0)
-        amsgrad (boolean, optional): whether to use the AMSGrad variant of this
-            algorithm from the paper `On the Convergence of Adam and Beyond`_
-
-    .. _Adam\: A Method for Stochastic Optimization:
-        https://arxiv.org/abs/1412.6980
-    .. _On the Convergence of Adam and Beyond:
-        https://openreview.net/forum?id=ryQu7f-RZ
-    """
-
-    def __init__(
-        self,
-        params,
-        lr=1e-3,
-        betas=(0.9, 0.999),
-        eps=1e-8,
-        weight_decay=0,
-        amsgrad=False,
-    ):
-        defaults = dict(
-            lr=lr, betas=betas, eps=eps, weight_decay=weight_decay, amsgrad=amsgrad
-        )
-        super(Adam, self).__init__(params, defaults)
-
-    @property
-    def supports_memory_efficient_fp16(self):
-        return True
-
-    @property
-    def supports_flat_params(self):
-        return True
-
-    def step(self, closure=None):
-        """Performs a single optimization step.
-
-        Args:
-            closure (callable, optional): A closure that reevaluates the model
-                and returns the loss.
-        """
-        loss = None
-        if closure is not None:
-            loss = closure()
-
-        for group in self.param_groups:
-            for p in group["params"]:
-                if p.grad is None:
-                    continue
-                grad = p.grad.data
-                if grad.dtype in {torch.float16, torch.bfloat16}:
-                    grad = grad.float()
-                if grad.is_sparse:
-                    raise RuntimeError(
-                        "Adam does not support sparse gradients, please consider SparseAdam instead"
-                    )
-                amsgrad = group.get("amsgrad", False)
-
-                p_data_fp32 = p.data
-                if p.data.dtype in {torch.float16, torch.bfloat16}:
-                    p_data_fp32 = p_data_fp32.float()
-
-                state = self.state[p]
-
-                # State initialization
-                if len(state) == 0:
-                    state["step"] = 0
-                    # Exponential moving average of gradient values
-                    state["exp_avg"] = torch.zeros_like(p_data_fp32)
-                    # Exponential moving average of squared gradient values
-                    state["exp_avg_sq"] = torch.zeros_like(p_data_fp32)
-                    if amsgrad:
-                        # Maintains max of all exp. moving avg. of sq. grad. values
-                        state["max_exp_avg_sq"] = torch.zeros_like(p_data_fp32)
-                else:
-                    state["exp_avg"] = state["exp_avg"].to(p_data_fp32)
-                    state["exp_avg_sq"] = state["exp_avg_sq"].to(p_data_fp32)
-                    if amsgrad:
-                        state["max_exp_avg_sq"] = state["max_exp_avg_sq"].to(
-                            p_data_fp32
-                        )
-
-                exp_avg, exp_avg_sq = state["exp_avg"], state["exp_avg_sq"]
-                if amsgrad:
-                    max_exp_avg_sq = state["max_exp_avg_sq"]
-                beta1, beta2 = group["betas"]
-
-                state["step"] += 1
-
-                # Decay the first and second moment running average coefficient
-                exp_avg.mul_(beta1).add_(grad, alpha=1 - beta1)
-                exp_avg_sq.mul_(beta2).addcmul_(grad, grad, value=1 - beta2)
-                if amsgrad:
-                    # Maintains the maximum of all 2nd moment running avg. till now
-                    torch.max(max_exp_avg_sq, exp_avg_sq, out=max_exp_avg_sq)
-                    # Use the max. for normalizing running avg. of gradient
-                    denom = max_exp_avg_sq.sqrt().add_(group["eps"])
-                else:
-                    denom = exp_avg_sq.sqrt().add_(group["eps"])
-
-                bias_correction1 = 1 - beta1 ** state["step"]
-                bias_correction2 = 1 - beta2 ** state["step"]
-                step_size = group["lr"] * math.sqrt(bias_correction2) / bias_correction1
-
-                if group["weight_decay"] != 0:
-                    p_data_fp32.add_(
-                        p_data_fp32, alpha=-group["weight_decay"] * group["lr"]
-                    )
-
-                p_data_fp32.addcdiv_(exp_avg, denom, value=-step_size)
-
-                if p.data.dtype in {torch.float16, torch.bfloat16}:
-                    p.data.copy_(p_data_fp32)
-
-        return loss
diff --git a/spaces/Harveenchadha/Vakyansh-Malayalam-TTS/ttsv/utils/inference/transliterate.py b/spaces/Harveenchadha/Vakyansh-Malayalam-TTS/ttsv/utils/inference/transliterate.py
deleted file mode 100644
index de1ccab4426659552a019b593c4766522efff616..0000000000000000000000000000000000000000
--- a/spaces/Harveenchadha/Vakyansh-Malayalam-TTS/ttsv/utils/inference/transliterate.py
+++ /dev/null
@@ -1,919 +0,0 @@
-import torch
-import torch.nn as nn
-import numpy as np
-import pandas as pd
-import random
-import sys
-import os
-import json
-import enum
-import traceback
-import re
-
-#F_DIR = os.path.dirname(os.path.realpath(__file__))
-F_DIR = '/home/user/app/ttsv/checkpoints/'
-
-class XlitError(enum.Enum):
-    lang_err = "Unsupported langauge ID requested ;( Please check available languages."
-    string_err = "String passed is incompatable ;("
-    internal_err = "Internal crash ;("
-    unknown_err = "Unknown Failure"
-    loading_err = "Loading failed ;( Check if metadata/paths are correctly configured."
-
-
-##=================== Network ==================================================
-
-
-class Encoder(nn.Module):
-    def __init__(
-        self,
-        input_dim,
-        embed_dim,
-        hidden_dim,
-        rnn_type="gru",
-        layers=1,
-        bidirectional=False,
-        dropout=0,
-        device="cpu",
-    ):
-        super(Encoder, self).__init__()
-
-        self.input_dim = input_dim  # src_vocab_sz
-        self.enc_embed_dim = embed_dim
-        self.enc_hidden_dim = hidden_dim
-        self.enc_rnn_type = rnn_type
-        self.enc_layers = layers
-        self.enc_directions = 2 if bidirectional else 1
-        self.device = device
-
-        self.embedding = nn.Embedding(self.input_dim, self.enc_embed_dim)
-
-        if self.enc_rnn_type == "gru":
-            self.enc_rnn = nn.GRU(
-                input_size=self.enc_embed_dim,
-                hidden_size=self.enc_hidden_dim,
-                num_layers=self.enc_layers,
-                bidirectional=bidirectional,
-            )
-        elif self.enc_rnn_type == "lstm":
-            self.enc_rnn = nn.LSTM(
-                input_size=self.enc_embed_dim,
-                hidden_size=self.enc_hidden_dim,
-                num_layers=self.enc_layers,
-                bidirectional=bidirectional,
-            )
-        else:
-            raise Exception("XlitError: unknown RNN type mentioned")
-
-    def forward(self, x, x_sz, hidden=None):
-        """
-        x_sz: (batch_size, 1) -  Unpadded sequence lengths used for pack_pad
-        """
-        batch_sz = x.shape[0]
-        # x: batch_size, max_length, enc_embed_dim
-        x = self.embedding(x)
-
-        ## pack the padded data
-        # x: max_length, batch_size, enc_embed_dim -> for pack_pad
-        x = x.permute(1, 0, 2)
-        x = nn.utils.rnn.pack_padded_sequence(x, x_sz, enforce_sorted=False)  # unpad
-
-        # output: packed_size, batch_size, enc_embed_dim
-        # hidden: n_layer**num_directions, batch_size, hidden_dim | if LSTM (h_n, c_n)
-        output, hidden = self.enc_rnn(
-            x
-        )  # gru returns hidden state of all timesteps as well as hidden state at last timestep
-
-        ## pad the sequence to the max length in the batch
-        # output: max_length, batch_size, enc_emb_dim*directions)
-        output, _ = nn.utils.rnn.pad_packed_sequence(output)
-
-        # output: batch_size, max_length, hidden_dim
-        output = output.permute(1, 0, 2)
-
-        return output, hidden
-
-    def get_word_embedding(self, x):
-        """ """
-        x_sz = torch.tensor([len(x)])
-        x_ = torch.tensor(x).unsqueeze(0).to(dtype=torch.long)
-        # x: 1, max_length, enc_embed_dim
-        x = self.embedding(x_)
-
-        ## pack the padded data
-        # x: max_length, 1, enc_embed_dim -> for pack_pad
-        x = x.permute(1, 0, 2)
-        x = nn.utils.rnn.pack_padded_sequence(x, x_sz, enforce_sorted=False)  # unpad
-
-        # output: packed_size, 1, enc_embed_dim
-        # hidden: n_layer**num_directions, 1, hidden_dim | if LSTM (h_n, c_n)
-        output, hidden = self.enc_rnn(
-            x
-        )  # gru returns hidden state of all timesteps as well as hidden state at last timestep
-
-        out_embed = hidden[0].squeeze()
-
-        return out_embed
-
-
-class Decoder(nn.Module):
-    def __init__(
-        self,
-        output_dim,
-        embed_dim,
-        hidden_dim,
-        rnn_type="gru",
-        layers=1,
-        use_attention=True,
-        enc_outstate_dim=None,  # enc_directions * enc_hidden_dim
-        dropout=0,
-        device="cpu",
-    ):
-        super(Decoder, self).__init__()
-
-        self.output_dim = output_dim  # tgt_vocab_sz
-        self.dec_hidden_dim = hidden_dim
-        self.dec_embed_dim = embed_dim
-        self.dec_rnn_type = rnn_type
-        self.dec_layers = layers
-        self.use_attention = use_attention
-        self.device = device
-        if self.use_attention:
-            self.enc_outstate_dim = enc_outstate_dim if enc_outstate_dim else hidden_dim
-        else:
-            self.enc_outstate_dim = 0
-
-        self.embedding = nn.Embedding(self.output_dim, self.dec_embed_dim)
-
-        if self.dec_rnn_type == "gru":
-            self.dec_rnn = nn.GRU(
-                input_size=self.dec_embed_dim
-                + self.enc_outstate_dim,  # to concat attention_output
-                hidden_size=self.dec_hidden_dim,  # previous Hidden
-                num_layers=self.dec_layers,
-                batch_first=True,
-            )
-        elif self.dec_rnn_type == "lstm":
-            self.dec_rnn = nn.LSTM(
-                input_size=self.dec_embed_dim
-                + self.enc_outstate_dim,  # to concat attention_output
-                hidden_size=self.dec_hidden_dim,  # previous Hidden
-                num_layers=self.dec_layers,
-                batch_first=True,
-            )
-        else:
-            raise Exception("XlitError: unknown RNN type mentioned")
-
-        self.fc = nn.Sequential(
-            nn.Linear(self.dec_hidden_dim, self.dec_embed_dim),
-            nn.LeakyReLU(),
-            # nn.Linear(self.dec_embed_dim, self.dec_embed_dim), nn.LeakyReLU(), # removing to reduce size
-            nn.Linear(self.dec_embed_dim, self.output_dim),
-        )
-
-        ##----- Attention ----------
-        if self.use_attention:
-            self.W1 = nn.Linear(self.enc_outstate_dim, self.dec_hidden_dim)
-            self.W2 = nn.Linear(self.dec_hidden_dim, self.dec_hidden_dim)
-            self.V = nn.Linear(self.dec_hidden_dim, 1)
-
-    def attention(self, x, hidden, enc_output):
-        """
-        x: (batch_size, 1, dec_embed_dim) -> after Embedding
-        enc_output: batch_size, max_length, enc_hidden_dim *num_directions
-        hidden: n_layers, batch_size, hidden_size | if LSTM (h_n, c_n)
-        """
-
-        ## perform addition to calculate the score
-
-        # hidden_with_time_axis: batch_size, 1, hidden_dim
-        ## hidden_with_time_axis = hidden.permute(1, 0, 2) ## replaced with below 2lines
-        hidden_with_time_axis = (
-            torch.sum(hidden, axis=0)
-            if self.dec_rnn_type != "lstm"
-            else torch.sum(hidden[0], axis=0)
-        )  # h_n
-
-        hidden_with_time_axis = hidden_with_time_axis.unsqueeze(1)
-
-        # score: batch_size, max_length, hidden_dim
-        score = torch.tanh(self.W1(enc_output) + self.W2(hidden_with_time_axis))
-
-        # attention_weights: batch_size, max_length, 1
-        # we get 1 at the last axis because we are applying score to self.V
-        attention_weights = torch.softmax(self.V(score), dim=1)
-
-        # context_vector shape after sum == (batch_size, hidden_dim)
-        context_vector = attention_weights * enc_output
-        context_vector = torch.sum(context_vector, dim=1)
-        # context_vector: batch_size, 1, hidden_dim
-        context_vector = context_vector.unsqueeze(1)
-
-        # attend_out (batch_size, 1, dec_embed_dim + hidden_size)
-        attend_out = torch.cat((context_vector, x), -1)
-
-        return attend_out, attention_weights
-
-    def forward(self, x, hidden, enc_output):
-        """
-        x: (batch_size, 1)
-        enc_output: batch_size, max_length, dec_embed_dim
-        hidden: n_layer, batch_size, hidden_size | lstm: (h_n, c_n)
-        """
-        if (hidden is None) and (self.use_attention is False):
-            raise Exception(
-                "XlitError: No use of a decoder with No attention and No Hidden"
-            )
-
-        batch_sz = x.shape[0]
-
-        if hidden is None:
-            # hidden: n_layers, batch_size, hidden_dim
-            hid_for_att = torch.zeros(
-                (self.dec_layers, batch_sz, self.dec_hidden_dim)
-            ).to(self.device)
-        elif self.dec_rnn_type == "lstm":
-            hid_for_att = hidden[1]  # c_n
-
-        # x (batch_size, 1, dec_embed_dim) -> after embedding
-        x = self.embedding(x)
-
-        if self.use_attention:
-            # x (batch_size, 1, dec_embed_dim + hidden_size) -> after attention
-            # aw: (batch_size, max_length, 1)
-            x, aw = self.attention(x, hidden, enc_output)
-        else:
-            x, aw = x, 0
-
-        # passing the concatenated vector to the GRU
-        # output: (batch_size, n_layers, hidden_size)
-        # hidden: n_layers, batch_size, hidden_size | if LSTM (h_n, c_n)
-        output, hidden = (
-            self.dec_rnn(x, hidden) if hidden is not None else self.dec_rnn(x)
-        )
-
-        # output :shp: (batch_size * 1, hidden_size)
-        output = output.view(-1, output.size(2))
-
-        # output :shp: (batch_size * 1, output_dim)
-        output = self.fc(output)
-
-        return output, hidden, aw
-
-
-class Seq2Seq(nn.Module):
-    """
-    Class dependency: Encoder, Decoder
-    """
-
-    def __init__(
-        self, encoder, decoder, pass_enc2dec_hid=False, dropout=0, device="cpu"
-    ):
-        super(Seq2Seq, self).__init__()
-
-        self.encoder = encoder
-        self.decoder = decoder
-        self.device = device
-        self.pass_enc2dec_hid = pass_enc2dec_hid
-        _force_en2dec_hid_conv = False
-
-        if self.pass_enc2dec_hid:
-            assert (
-                decoder.dec_hidden_dim == encoder.enc_hidden_dim
-            ), "Hidden Dimension of encoder and decoder must be same, or unset `pass_enc2dec_hid`"
-        if decoder.use_attention:
-            assert (
-                decoder.enc_outstate_dim
-                == encoder.enc_directions * encoder.enc_hidden_dim
-            ), "Set `enc_out_dim` correctly in decoder"
-        assert (
-            self.pass_enc2dec_hid or decoder.use_attention
-        ), "No use of a decoder with No attention and No Hidden from Encoder"
-
-        self.use_conv_4_enc2dec_hid = False
-        if (
-            self.pass_enc2dec_hid
-            and (encoder.enc_directions * encoder.enc_layers != decoder.dec_layers)
-        ) or _force_en2dec_hid_conv:
-            if encoder.enc_rnn_type == "lstm" or encoder.enc_rnn_type == "lstm":
-                raise Exception(
-                    "XlitError: conv for enc2dec_hid not implemented; Change the layer numbers appropriately"
-                )
-
-            self.use_conv_4_enc2dec_hid = True
-            self.enc_hid_1ax = encoder.enc_directions * encoder.enc_layers
-            self.dec_hid_1ax = decoder.dec_layers
-            self.e2d_hidden_conv = nn.Conv1d(self.enc_hid_1ax, self.dec_hid_1ax, 1)
-
-    def enc2dec_hidden(self, enc_hidden):
-        """
-        enc_hidden: n_layer, batch_size, hidden_dim*num_directions
-        TODO: Implement the logic for LSTm bsed model
-        """
-        # hidden: batch_size, enc_layer*num_directions, enc_hidden_dim
-        hidden = enc_hidden.permute(1, 0, 2).contiguous()
-        # hidden: batch_size, dec_layers, dec_hidden_dim -> [N,C,Tstep]
-        hidden = self.e2d_hidden_conv(hidden)
-
-        # hidden: dec_layers, batch_size , dec_hidden_dim
-        hidden_for_dec = hidden.permute(1, 0, 2).contiguous()
-
-        return hidden_for_dec
-
-    def active_beam_inference(self, src, beam_width=3, max_tgt_sz=50):
-        """Search based decoding
-        src: (sequence_len)
-        """
-
-        def _avg_score(p_tup):
-            """Used for Sorting
-            TODO: Dividing by length of sequence power alpha as hyperparam
-            """
-            return p_tup[0]
-
-        import sys
-
-        batch_size = 1
-        start_tok = src[0]
-        end_tok = src[-1]
-        src_sz = torch.tensor([len(src)])
-        src_ = src.unsqueeze(0)
-
-        # enc_output: (batch_size, padded_seq_length, enc_hidden_dim*num_direction)
-        # enc_hidden: (enc_layers*num_direction, batch_size, hidden_dim)
-        enc_output, enc_hidden = self.encoder(src_, src_sz)
-
-        if self.pass_enc2dec_hid:
-            # dec_hidden: dec_layers, batch_size , dec_hidden_dim
-            if self.use_conv_4_enc2dec_hid:
-                init_dec_hidden = self.enc2dec_hidden(enc_hidden)
-            else:
-                init_dec_hidden = enc_hidden
-        else:
-            # dec_hidden -> Will be initialized to zeros internally
-            init_dec_hidden = None
-
-        # top_pred[][0] = Σ-log_softmax
-        # top_pred[][1] = sequence torch.tensor shape: (1)
-        # top_pred[][2] = dec_hidden
-        top_pred_list = [(0, start_tok.unsqueeze(0), init_dec_hidden)]
-
-        for t in range(max_tgt_sz):
-            cur_pred_list = []
-
-            for p_tup in top_pred_list:
-                if p_tup[1][-1] == end_tok:
-                    cur_pred_list.append(p_tup)
-                    continue
-
-                # dec_hidden: dec_layers, 1, hidden_dim
-                # dec_output: 1, output_dim
-                dec_output, dec_hidden, _ = self.decoder(
-                    x=p_tup[1][-1].view(1, 1),  # dec_input: (1,1)
-                    hidden=p_tup[2],
-                    enc_output=enc_output,
-                )
-
-                ## π{prob} = Σ{log(prob)} -> to prevent diminishing
-                # dec_output: (1, output_dim)
-                dec_output = nn.functional.log_softmax(dec_output, dim=1)
-                # pred_topk.values & pred_topk.indices: (1, beam_width)
-                pred_topk = torch.topk(dec_output, k=beam_width, dim=1)
-
-                for i in range(beam_width):
-                    sig_logsmx_ = p_tup[0] + pred_topk.values[0][i]
-                    # seq_tensor_ : (seq_len)
-                    seq_tensor_ = torch.cat((p_tup[1], pred_topk.indices[0][i].view(1)))
-
-                    cur_pred_list.append((sig_logsmx_, seq_tensor_, dec_hidden))
-
-            cur_pred_list.sort(key=_avg_score, reverse=True)  # Maximized order
-            top_pred_list = cur_pred_list[:beam_width]
-
-            # check if end_tok of all topk
-            end_flags_ = [1 if t[1][-1] == end_tok else 0 for t in top_pred_list]
-            if beam_width == sum(end_flags_):
-                break
-
-        pred_tnsr_list = [t[1] for t in top_pred_list]
-
-        return pred_tnsr_list
-
-
-##===================== Glyph handlers =======================================
-
-
-class GlyphStrawboss:
-    def __init__(self, glyphs="en"):
-        """list of letters in a language in unicode
-        lang: ISO Language code
-        glyphs: json file with script information
-        """
-        if glyphs == "en":
-            # Smallcase alone
-            self.glyphs = [chr(alpha) for alpha in range(97, 122 + 1)]
-        else:
-            self.dossier = json.load(open(glyphs, encoding="utf-8"))
-            self.glyphs = self.dossier["glyphs"]
-            self.numsym_map = self.dossier["numsym_map"]
-
-        self.char2idx = {}
-        self.idx2char = {}
-        self._create_index()
-
-    def _create_index(self):
-
-        self.char2idx["_"] = 0  # pad
-        self.char2idx["$"] = 1  # start
-        self.char2idx["#"] = 2  # end
-        self.char2idx["*"] = 3  # Mask
-        self.char2idx["'"] = 4  # apostrophe U+0027
-        self.char2idx["%"] = 5  # unused
-        self.char2idx["!"] = 6  # unused
-
-        # letter to index mapping
-        for idx, char in enumerate(self.glyphs):
-            self.char2idx[char] = idx + 7  # +7 token initially
-
-        # index to letter mapping
-        for char, idx in self.char2idx.items():
-            self.idx2char[idx] = char
-
-    def size(self):
-        return len(self.char2idx)
-
-    def word2xlitvec(self, word):
-        """Converts given string of gyphs(word) to vector(numpy)
-        Also adds tokens for start and end
-        """
-        try:
-            vec = [self.char2idx["$"]]  # start token
-            for i in list(word):
-                vec.append(self.char2idx[i])
-            vec.append(self.char2idx["#"])  # end token
-
-            vec = np.asarray(vec, dtype=np.int64)
-            return vec
-
-        except Exception as error:
-            print("XlitError: In word:", word, "Error Char not in Token:", error)
-            sys.exit()
-
-    def xlitvec2word(self, vector):
-        """Converts vector(numpy) to string of glyphs(word)"""
-        char_list = []
-        for i in vector:
-            char_list.append(self.idx2char[i])
-
-        word = "".join(char_list).replace("$", "").replace("#", "")  # remove tokens
-        word = word.replace("_", "").replace("*", "")  # remove tokens
-        return word
-
-
-class VocabSanitizer:
-    def __init__(self, data_file):
-        """
-        data_file: path to file conatining vocabulary list
-        """
-        extension = os.path.splitext(data_file)[-1]
-        if extension == ".json":
-            self.vocab_set = set(json.load(open(data_file, encoding="utf-8")))
-        elif extension == ".csv":
-            self.vocab_df = pd.read_csv(data_file).set_index("WORD")
-            self.vocab_set = set(self.vocab_df.index)
-        else:
-            print("XlitError: Only Json/CSV file extension supported")
-
-    def reposition(self, word_list):
-        """Reorder Words in list"""
-        new_list = []
-        temp_ = word_list.copy()
-        for v in word_list:
-            if v in self.vocab_set:
-                new_list.append(v)
-                temp_.remove(v)
-        new_list.extend(temp_)
-
-        return new_list
-
-
-##=============== INSTANTIATION ================================================
-
-
-class XlitPiston:
-    """
-    For handling prediction & post-processing of transliteration for a single language
-    Class dependency: Seq2Seq, GlyphStrawboss, VocabSanitizer
-    Global Variables: F_DIR
-    """
-
-    def __init__(
-        self,
-        weight_path,
-        vocab_file,
-        tglyph_cfg_file,
-        iglyph_cfg_file="en",
-        device="cpu",
-    ):
-
-        self.device = device
-        self.in_glyph_obj = GlyphStrawboss(iglyph_cfg_file)
-        self.tgt_glyph_obj = GlyphStrawboss(glyphs=tglyph_cfg_file)
-        self.voc_sanity = VocabSanitizer(vocab_file)
-
-        self._numsym_set = set(
-            json.load(open(tglyph_cfg_file, encoding="utf-8"))["numsym_map"].keys()
-        )
-        self._inchar_set = set("abcdefghijklmnopqrstuvwxyz")
-        self._natscr_set = set().union(
-            self.tgt_glyph_obj.glyphs, sum(self.tgt_glyph_obj.numsym_map.values(), [])
-        )
-
-        ## Model Config Static                TODO: add defining in json support
-        input_dim = self.in_glyph_obj.size()
-        output_dim = self.tgt_glyph_obj.size()
-        enc_emb_dim = 300
-        dec_emb_dim = 300
-        enc_hidden_dim = 512
-        dec_hidden_dim = 512
-        rnn_type = "lstm"
-        enc2dec_hid = True
-        attention = True
-        enc_layers = 1
-        dec_layers = 2
-        m_dropout = 0
-        enc_bidirect = True
-        enc_outstate_dim = enc_hidden_dim * (2 if enc_bidirect else 1)
-
-        enc = Encoder(
-            input_dim=input_dim,
-            embed_dim=enc_emb_dim,
-            hidden_dim=enc_hidden_dim,
-            rnn_type=rnn_type,
-            layers=enc_layers,
-            dropout=m_dropout,
-            device=self.device,
-            bidirectional=enc_bidirect,
-        )
-        dec = Decoder(
-            output_dim=output_dim,
-            embed_dim=dec_emb_dim,
-            hidden_dim=dec_hidden_dim,
-            rnn_type=rnn_type,
-            layers=dec_layers,
-            dropout=m_dropout,
-            use_attention=attention,
-            enc_outstate_dim=enc_outstate_dim,
-            device=self.device,
-        )
-        self.model = Seq2Seq(enc, dec, pass_enc2dec_hid=enc2dec_hid, device=self.device)
-        self.model = self.model.to(self.device)
-        weights = torch.load(weight_path, map_location=torch.device(self.device))
-
-        self.model.load_state_dict(weights)
-        self.model.eval()
-
-    def character_model(self, word, beam_width=1):
-        in_vec = torch.from_numpy(self.in_glyph_obj.word2xlitvec(word)).to(self.device)
-        ## change to active or passive beam
-        p_out_list = self.model.active_beam_inference(in_vec, beam_width=beam_width)
-        p_result = [
-            self.tgt_glyph_obj.xlitvec2word(out.cpu().numpy()) for out in p_out_list
-        ]
-
-        result = self.voc_sanity.reposition(p_result)
-
-        # List type
-        return result
-
-    def numsym_model(self, seg):
-        """tgt_glyph_obj.numsym_map[x] returns a list object"""
-        if len(seg) == 1:
-            return [seg] + self.tgt_glyph_obj.numsym_map[seg]
-
-        a = [self.tgt_glyph_obj.numsym_map[n][0] for n in seg]
-        return [seg] + ["".join(a)]
-
-    def _word_segementer(self, sequence):
-
-        sequence = sequence.lower()
-        accepted = set().union(self._numsym_set, self._inchar_set, self._natscr_set)
-        # sequence = ''.join([i for i in sequence if i in accepted])
-
-        segment = []
-        idx = 0
-        seq_ = list(sequence)
-        while len(seq_):
-            # for Number-Symbol
-            temp = ""
-            while len(seq_) and seq_[0] in self._numsym_set:
-                temp += seq_[0]
-                seq_.pop(0)
-            if temp != "":
-                segment.append(temp)
-
-            # for Target Chars
-            temp = ""
-            while len(seq_) and seq_[0] in self._natscr_set:
-                temp += seq_[0]
-                seq_.pop(0)
-            if temp != "":
-                segment.append(temp)
-
-            # for Input-Roman Chars
-            temp = ""
-            while len(seq_) and seq_[0] in self._inchar_set:
-                temp += seq_[0]
-                seq_.pop(0)
-            if temp != "":
-                segment.append(temp)
-
-            temp = ""
-            while len(seq_) and seq_[0] not in accepted:
-                temp += seq_[0]
-                seq_.pop(0)
-            if temp != "":
-                segment.append(temp)
-
-        return segment
-
-    def inferencer(self, sequence, beam_width=10):
-
-        seg = self._word_segementer(sequence[:120])
-        lit_seg = []
-
-        p = 0
-        while p < len(seg):
-            if seg[p][0] in self._natscr_set:
-                lit_seg.append([seg[p]])
-                p += 1
-
-            elif seg[p][0] in self._inchar_set:
-                lit_seg.append(self.character_model(seg[p], beam_width=beam_width))
-                p += 1
-
-            elif seg[p][0] in self._numsym_set:  # num & punc
-                lit_seg.append(self.numsym_model(seg[p]))
-                p += 1
-            else:
-                lit_seg.append([seg[p]])
-                p += 1
-
-        ## IF segment less/equal to 2 then return combinotorial,
-        ## ELSE only return top1 of each result concatenated
-        if len(lit_seg) == 1:
-            final_result = lit_seg[0]
-
-        elif len(lit_seg) == 2:
-            final_result = [""]
-            for seg in lit_seg:
-                new_result = []
-                for s in seg:
-                    for f in final_result:
-                        new_result.append(f + s)
-                final_result = new_result
-
-        else:
-            new_result = []
-            for seg in lit_seg:
-                new_result.append(seg[0])
-            final_result = ["".join(new_result)]
-
-        return final_result
-
-
-from collections.abc import Iterable
-from pydload import dload
-import zipfile
-
-MODEL_DOWNLOAD_URL_PREFIX = "https://github.com/AI4Bharat/IndianNLP-Transliteration/releases/download/xlit_v0.5.0/"
-
-
-def is_folder_writable(folder):
-    try:
-        os.makedirs(folder, exist_ok=True)
-        tmp_file = os.path.join(folder, ".write_test")
-        with open(tmp_file, "w") as f:
-            f.write("Permission Check")
-        os.remove(tmp_file)
-        return True
-    except:
-        return False
-
-
-def is_directory_writable(path):
-    if os.name == "nt":
-        return is_folder_writable(path)
-    return os.access(path, os.W_OK | os.X_OK)
-
-
-class XlitEngine:
-    """
-    For Managing the top level tasks and applications of transliteration
-    Global Variables: F_DIR
-    """
-
-    def __init__(
-        self, lang2use="all", config_path="translit_models/default_lineup.json"
-    ):
-
-        lineup = json.load(open(os.path.join(F_DIR, config_path), encoding="utf-8"))
-        self.lang_config = {}
-        if isinstance(lang2use, str):
-            if lang2use == "all":
-                self.lang_config = lineup
-            elif lang2use in lineup:
-                self.lang_config[lang2use] = lineup[lang2use]
-            else:
-                raise Exception(
-                    "XlitError: The entered Langauge code not found. Available are {}".format(
-                        lineup.keys()
-                    )
-                )
-
-        elif isinstance(lang2use, Iterable):
-            for l in lang2use:
-                try:
-                    self.lang_config[l] = lineup[l]
-                except:
-                    print(
-                        "XlitError: Language code {} not found, Skipping...".format(l)
-                    )
-        else:
-            raise Exception(
-                "XlitError: lang2use must be a list of language codes (or) string of single language code"
-            )
-
-        if is_directory_writable(F_DIR):
-            models_path = os.path.join(F_DIR, "translit_models")
-        else:
-            user_home = os.path.expanduser("~")
-            models_path = os.path.join(user_home, ".AI4Bharat_Xlit_Models")
-        os.makedirs(models_path, exist_ok=True)
-        self.download_models(models_path)
-
-        self.langs = {}
-        self.lang_model = {}
-        for la in self.lang_config:
-            try:
-                print("Loading {}...".format(la))
-                self.lang_model[la] = XlitPiston(
-                    weight_path=os.path.join(
-                        models_path, self.lang_config[la]["weight"]
-                    ),
-                    vocab_file=os.path.join(models_path, self.lang_config[la]["vocab"]),
-                    tglyph_cfg_file=os.path.join(
-                        models_path, self.lang_config[la]["script"]
-                    ),
-                    iglyph_cfg_file="en",
-                )
-                self.langs[la] = self.lang_config[la]["name"]
-            except Exception as error:
-                print("XlitError: Failure in loading {} \n".format(la), error)
-                print(XlitError.loading_err.value)
-
-    def download_models(self, models_path):
-        """
-        Download models from GitHub Releases if not exists
-        """
-        for l in self.lang_config:
-            lang_name = self.lang_config[l]["eng_name"]
-            lang_model_path = os.path.join(models_path, lang_name)
-            if not os.path.isdir(lang_model_path):
-                print("Downloading model for language: %s" % lang_name)
-                remote_url = MODEL_DOWNLOAD_URL_PREFIX + lang_name + ".zip"
-                downloaded_zip_path = os.path.join(models_path, lang_name + ".zip")
-                dload(url=remote_url, save_to_path=downloaded_zip_path, max_time=None)
-
-                if not os.path.isfile(downloaded_zip_path):
-                    exit(
-                        f"ERROR: Unable to download model from {remote_url} into {models_path}"
-                    )
-
-                with zipfile.ZipFile(downloaded_zip_path, "r") as zip_ref:
-                    zip_ref.extractall(models_path)
-
-                if os.path.isdir(lang_model_path):
-                    os.remove(downloaded_zip_path)
-                else:
-                    exit(
-                        f"ERROR: Unable to find models in {lang_model_path} after download"
-                    )
-        return
-
-    def translit_word(self, eng_word, lang_code="default", topk=7, beam_width=10):
-        if eng_word == "":
-            return []
-
-        if lang_code in self.langs:
-            try:
-                res_list = self.lang_model[lang_code].inferencer(
-                    eng_word, beam_width=beam_width
-                )
-                return res_list[:topk]
-
-            except Exception as error:
-                print("XlitError:", traceback.format_exc())
-                print(XlitError.internal_err.value)
-                return XlitError.internal_err
-
-        elif lang_code == "default":
-            try:
-                res_dict = {}
-                for la in self.lang_model:
-                    res = self.lang_model[la].inferencer(
-                        eng_word, beam_width=beam_width
-                    )
-                    res_dict[la] = res[:topk]
-                return res_dict
-
-            except Exception as error:
-                print("XlitError:", traceback.format_exc())
-                print(XlitError.internal_err.value)
-                return XlitError.internal_err
-
-        else:
-            print("XlitError: Unknown Langauge requested", lang_code)
-            print(XlitError.lang_err.value)
-            return XlitError.lang_err
-
-    def translit_sentence(self, eng_sentence, lang_code="default", beam_width=10):
-        if eng_sentence == "":
-            return []
-
-        if lang_code in self.langs:
-            try:
-                out_str = ""
-                for word in eng_sentence.split():
-                    res_ = self.lang_model[lang_code].inferencer(
-                        word, beam_width=beam_width
-                    )
-                    out_str = out_str + res_[0] + " "
-                return out_str[:-1]
-
-            except Exception as error:
-                print("XlitError:", traceback.format_exc())
-                print(XlitError.internal_err.value)
-                return XlitError.internal_err
-
-        elif lang_code == "default":
-            try:
-                res_dict = {}
-                for la in self.lang_model:
-                    out_str = ""
-                    for word in eng_sentence.split():
-                        res_ = self.lang_model[la].inferencer(
-                            word, beam_width=beam_width
-                        )
-                        out_str = out_str + res_[0] + " "
-                    res_dict[la] = out_str[:-1]
-                return res_dict
-
-            except Exception as error:
-                print("XlitError:", traceback.format_exc())
-                print(XlitError.internal_err.value)
-                return XlitError.internal_err
-
-        else:
-            print("XlitError: Unknown Langauge requested", lang_code)
-            print(XlitError.lang_err.value)
-            return XlitError.lang_err
-
-
-if __name__ == "__main__":
-
-    available_lang = [
-        "bn",
-        "gu",
-        "hi",
-        "kn",
-        "gom",
-        "mai",
-        "ml",
-        "mr",
-        "pa",
-        "sd",
-        "si",
-        "ta",
-        "te",
-        "ur",
-    ]
-
-    reg = re.compile(r"[a-zA-Z]")
-    lang = "hi"
-    engine = XlitEngine(
-        lang
-    )  # if you don't specify lang code here, this will give results in all langs available
-    sent = "Hello World! ABCD क्या हाल है आपका?"
-    words = [
-        engine.translit_word(word, topk=1)[lang][0] if reg.match(word) else word
-        for word in sent.split()
-    ]  # only transliterated en words, leaves rest as it is
-    updated_sent = " ".join(words)
-
-    print(updated_sent)
-
-    # output : हेलो वर्ल्ड! क्या हाल है आपका?
-
-    # y = engine.translit_sentence("Hello World !")['hi']
-    # print(y)
diff --git a/spaces/Ibtehaj10/cheating-detection/pages/Login.py b/spaces/Ibtehaj10/cheating-detection/pages/Login.py
deleted file mode 100644
index cfa7fc618d97a837cdebac0c8ea09759bb435190..0000000000000000000000000000000000000000
--- a/spaces/Ibtehaj10/cheating-detection/pages/Login.py
+++ /dev/null
@@ -1,679 +0,0 @@
-import cv2
-import datetime
-import imutils
-import numpy as np
-from centroidtracker import CentroidTracker
-import pandas as pd 
-import torch 
-import streamlit as st
-import mediapipe as mp
-import cv2 as cv
-import numpy as np
-import tempfile
-import time
-from PIL import Image
-import pandas as pd
-import torch
-import base64
-import streamlit.components.v1 as components
-import csv
-import pickle
-from pathlib import Path
-import streamlit_authenticator as stauth
-import os
-import csv
-from streamlit_option_menu import option_menu
-#  x-x-x-x-x-x-x-x-x-x-x-x-x-x LOGIN FORM x-x-x-x-x-x-x-x-x
-
-                                
-import streamlit as st
-import pandas as pd
-import hashlib
-import sqlite3 
-#
-
-import pickle
-from pathlib import Path
-import streamlit_authenticator as stauth
-import pyautogui
-
-# print("Done !!!")
-
-data = ["student Count",'Date','Id','Mobile','Watch']
-with open('final.csv', 'w') as file:
-    writer = csv.writer(file)
-    writer.writerow(data)
-    
-
-# # l1 = []
-# # l2 = []
-# # if st.button('signup'):
-    
-    
-# #     usernames = st.text_input('Username')
-# #     pwd = st.text_input('Password') 
-# #     l1.append(usernames)
-# #     l2.append(pwd)
-
-# #     names = ["dmin", "ser"]
-# #     if st.button("signupsss"):
-# #         username =l1
-
-# #         password =l2
-
-# #         hashed_passwords =stauth.Hasher(password).generate()
-
-# #         file_path = Path(__file__).parent / "hashed_pw.pkl"
-
-# #         with file_path.open("wb") as file:
-# #             pickle.dump(hashed_passwords, file)
-            
-    
-# # elif st.button('Logins'):
-# names = ['dmin', 'ser']
-
-# username = []
-
-# file_path = Path(__file__).parent / 'hashed_pw.pkl'
-
-# with file_path.open('rb') as file:
-#     hashed_passwords = pickle.load(file)
-
-# authenticator = stauth.Authenticate(names,username,hashed_passwords,'Cheating Detection','abcdefg',cookie_expiry_days=180)
-
-# name,authentication_status,username= authenticator.login('Login','main')
-
-
-# if authentication_status == False:
-#     st.error('Username/Password is incorrect')
-    
-# if authentication_status == None:
-#     st.error('Please enter a username and password')
-
-@st.experimental_memo
-def get_img_as_base64(file):
-    with open(file, "rb") as f:
-        data = f.read()
-    return base64.b64encode(data).decode()
-
-
-#img = get_img_as_base64("/home/anas/PersonTracking/WebUI/attendence.jpg")
-
-page_bg_img = f"""
-<style>
-[data-testid="stAppViewContainer"] > .main {{
-background-image: url("https://www.xmple.com/wallpaper/blue-gradient-black-linear-1920x1080-c2-87cefa-000000-a-180-f-14.svg");
-background-size: 180%;
-background-position: top left;
-background-repeat: no-repeat;
-background-attachment: local;
-}}
-
-[data-testid="stHeader"] {{
-background: rgba(0,0,0,0);
-}}
-[data-testid="stToolbar"] {{
-right: 2rem;
-}}
-</style>
-"""
-
-st.markdown(page_bg_img, unsafe_allow_html=True)
-files = pd.read_csv('LoginStatus.csv')
-
-
-idS = list(files['Id'])
-Pwd = list(files['Password'].astype(str))
-
-# print(type(Pwd))
-ids = st.sidebar.text_input('Enter a username')
-Pswd = st.sidebar.text_input('Enter a password',type="password",key="password")
-
-# print('list : ',type(Pwd))
-
-    
-        
-if (ids in idS) and(str(Pswd) in Pwd):
-    
-        # st.empty()    
-        date_time = time.strftime("%b %d %Y %-I:%M %p")
-        date = date_time.split()
-        dates = date[0:3]
-        times = date[3:5]
-        # x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-xAPPLICACTION -x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x-x
-
-        def non_max_suppression_fast(boxes, overlapThresh):
-            try:
-                if len(boxes) == 0:
-                    return []
-
-                if boxes.dtype.kind == "i":
-                    boxes = boxes.astype("float")
-
-                pick = []
-
-                x1 = boxes[:, 0]
-                y1 = boxes[:, 1]
-                x2 = boxes[:, 2]
-                y2 = boxes[:, 3]
-
-                area = (x2 - x1 + 1) * (y2 - y1 + 1)
-                idxs = np.argsort(y2)
-
-                while len(idxs) > 0:
-                    last = len(idxs) - 1
-                    i = idxs[last]
-                    pick.append(i)
-
-                    xx1 = np.maximum(x1[i], x1[idxs[:last]])
-                    yy1 = np.maximum(y1[i], y1[idxs[:last]])
-                    xx2 = np.minimum(x2[i], x2[idxs[:last]])
-                    yy2 = np.minimum(y2[i], y2[idxs[:last]])
-
-                    w = np.maximum(0, xx2 - xx1 + 1)
-                    h = np.maximum(0, yy2 - yy1 + 1)
-
-                    overlap = (w * h) / area[idxs[:last]]
-
-                    idxs = np.delete(idxs, np.concatenate(([last],
-                                                        np.where(overlap > overlapThresh)[0])))
-
-                return boxes[pick].astype("int")
-            except Exception as e:
-                print("Exception occurred in non_max_suppression : {}".format(e))
-
-
-        protopath = "MobileNetSSD_deploy.prototxt"
-        modelpath = "MobileNetSSD_deploy.caffemodel"
-        detector = cv2.dnn.readNetFromCaffe(prototxt=protopath, caffeModel=modelpath)
-        # Only enable it if you are using OpenVino environment
-        # detector.setPreferableBackend(cv2.dnn.DNN_BACKEND_INFERENCE_ENGINE)
-        # detector.setPreferableTarget(cv2.dnn.DNN_TARGET_CPU)
-
-
-        CLASSES = ["background", "aeroplane", "bicycle", "bird", "boat",
-                "bottle", "bus", "car", "cat", "chair", "cow", "diningtable",
-                "dog", "horse", "motorbike", "person", "pottedplant", "sheep",
-                "sofa", "train", "tvmonitor"]
-
-        tracker = CentroidTracker(maxDisappeared=80, maxDistance=90)
-
-        st.markdown(
-            """
-            <style>
-            [data-testid="stSidebar"][aria-expanded="true"] > div:first-child{
-                width: 350px
-            }
-            [data-testid="stSidebar"][aria-expanded="false"] > div:first-child{
-                width: 350px
-                margin-left: -350px
-            }
-            </style>
-            """,
-            unsafe_allow_html=True,
-        )
-        hide_streamlit_style = """
-                <style>
-                #MainMenu {visibility: hidden;}
-                footer {visibility: hidden;}
-                </style>
-                """
-        st.markdown(hide_streamlit_style, unsafe_allow_html=True)
-
-
-        # Resize Images to fit Container
-        @st.cache()
-        # Get Image Dimensions
-        def image_resize(image, width=None, height=None, inter=cv.INTER_AREA):
-            dim = None
-            (h,w) = image.shape[:2]
-
-            if width is None and height is None:
-                return image
-
-            if width is None:
-                r = width/float(w)
-                dim = (int(w*r),height)
-
-            else:
-                r = width/float(w)
-                dim = width, int(h*r)
-
-            # Resize image
-            resized = cv.resize(image,dim,interpolation=inter)
-
-            return resized
-                
-        # About Page
-        # authenticator.logout('Logout')
-        EXAMPLE_NO = 3
-
-
-        def streamlit_menu(example=1):
-            if example == 1:
-                # 1. as sidebar menu
-                with st.sidebar:
-                    selected = option_menu(
-                        menu_title="Main Menu",  # required
-                        options=["Home", "Projects", "Contact"],  # required
-                        icons=["house", "book", "envelope"],  # optional
-                        menu_icon="cast",  # optional
-                        default_index=0,  # optional
-                    )
-                return selected
-
-            if example == 2:
-                # 2. horizontal menu w/o custom style
-                selected = option_menu(
-                    menu_title=None,  # required
-                    options=["Home", "Projects", "Contact"],  # required
-                    icons=["house", "book", "envelope"],  # optional
-                    menu_icon="cast",  # optional
-                    default_index=0,  # optional
-                    orientation="horizontal",
-                )
-                return selected
-
-            if example == 3:
-                # 2. horizontal menu with custom style
-                selected = option_menu(
-                    menu_title=None,  # required
-                    options=["Home", "Projects", "Contact"],  # required
-                    icons=["house", "book", "envelope"],  # optional
-                    menu_icon="cast",  # optional
-                    default_index=0,  # optional
-                    orientation="horizontal",
-                    styles={
-                        "container": {"padding": "0!important", "background-color": "#eaeaea"},
-                        "icon": {"color": "#080602", "font-size": "18px"},
-                        "nav-link": {
-                            "font-size": "18px",
-                            "text-align": "left",
-                            "color": "#000000",
-                            "margin": "0px",
-                            "--hover-color": "#E1A031",
-                        },
-                        "nav-link-selected": {"background-color": "#ffffff"},
-                    },
-                )
-                return selected
-
-
-        selected = streamlit_menu(example=EXAMPLE_NO)
-
-        if selected == "Home":
-            st.title(f"You have selected {selected}")
-        # if selected == "Projects":
-        #     st.title(f"You have selected {selected}")
-        if selected == "Contact":
-            st.title(f"You have selected {selected}")
-        # app_mode = st.sidebar.selectbox(
-        #                 'App Mode',
-        #                 ['Application']
-        #                 )
-        if selected == 'Projects':
-        # 2. horizontal menu with custom style
-            # selected = option_menu(
-            #     menu_title=None,  # required
-            #     options=["Home", "Projects", "Contact"],  # required
-            #     icons=["house", "book", "envelope"],  # optional
-            #     menu_icon="cast",  # optional
-            #     default_index=0,  # optional
-            #     orientation="horizontal",
-            #     styles={
-            #         "container": {"padding": "0!important", "background-color": "#fafafa"},
-            #         "icon": {"color": "orange", "font-size": "25px"},
-            #         "nav-link": {
-            #             "font-size": "25px",
-            #             "text-align": "left",
-            #             "margin": "0px",
-            #             "--hover-color": "#eee",
-            #         },
-            #         "nav-link-selected": {"background-color": "blue"},
-            #     },
-            # )
-        # if app_mode == 'About':
-        #     st.title('About Product And Team')
-        #     st.markdown('''
-        #                 Imran Bhai Project
-        #     ''')
-        #     st.markdown(
-        #         """
-        #         <style>
-        #         [data-testid="stSidebar"][aria-expanded="true"] > div:first-child{
-        #             width: 350px
-        #         }
-        #         [data-testid="stSidebar"][aria-expanded="false"] > div:first-child{
-        #             width: 350px
-        #             margin-left: -350px
-        #         }
-        #         </style>
-        #         """,
-        #         unsafe_allow_html=True,
-        #     )
-
-            
-
-
-        # elif app_mode == 'Application':
-            
-            st.set_option('deprecation.showfileUploaderEncoding', False)
-
-            use_webcam = "pass"
-            # record = st.sidebar.checkbox("Record Video")
-
-            # if record:
-            #     st.checkbox('Recording', True)
-
-            # drawing_spec = mp.solutions.drawing_utils.DrawingSpec(thickness=2, circle_radius=1)
-
-            # st.sidebar.markdown('---')
-
-            # ## Add Sidebar and Window style
-            # st.markdown(
-            #     """
-            #     <style>
-            #     [data-testid="stSidebar"][aria-expanded="true"] > div:first-child{
-            #         width: 350px
-            #     }
-            #     [data-testid="stSidebar"][aria-expanded="false"] > div:first-child{
-            #         width: 350px
-            #         margin-left: -350px
-            #     }
-            #     </style>
-            #     """,
-            #     unsafe_allow_html=True,
-            # )
-
-            # max_faces = st.sidebar.number_input('Maximum Number of Faces', value=5, min_value=1)
-            # st.sidebar.markdown('---')
-            # detection_confidence = st.sidebar.slider('Min Detection Confidence', min_value=0.0,max_value=1.0,value=0.5)
-            # tracking_confidence = st.sidebar.slider('Min Tracking Confidence', min_value=0.0,max_value=1.0,value=0.5)
-            # st.sidebar.markdown('---')
-
-            ## Get Video
-            stframe = st.empty()
-            video_file_buffer = st.file_uploader("Upload a Video", type=['mp4', 'mov', 'avi', 'asf', 'm4v'])
-            temp_file = tempfile.NamedTemporaryFile(delete=False)
-
-            
-            if not video_file_buffer:
-                if use_webcam:
-                    video = cv.VideoCapture(0)
-                else:
-                    try:
-                        video = cv.VideoCapture(1)
-                        temp_file.name = video
-                    except:
-                        pass
-            else:
-                temp_file.write(video_file_buffer.read())
-                video = cv.VideoCapture(temp_file.name)
-
-            width = int(video.get(cv.CAP_PROP_FRAME_WIDTH))
-            height = int(video.get(cv.CAP_PROP_FRAME_HEIGHT))
-            fps_input = int(video.get(cv.CAP_PROP_FPS))
-
-            ## Recording
-            codec = cv.VideoWriter_fourcc('a','v','c','1')
-            out = cv.VideoWriter('output1.mp4', codec, fps_input, (width,height))
-
-            # st.sidebar.text('Input Video')
-            # st.sidebar.video(temp_file.name)
-
-            fps = 0
-            i = 0
-
-            drawing_spec = mp.solutions.drawing_utils.DrawingSpec(thickness=2, circle_radius=1)
-
-            kpil, kpil2, kpil3,kpil4,kpil5, kpil6 = st.columns(6)
-
-            with kpil:
-                st.markdown('**Frame Rate**')
-                kpil_text = st.markdown('0')
-
-            with kpil2:
-                st.markdown('**detection ID**')
-                kpil2_text = st.markdown('0')
-
-            with kpil3:
-                st.markdown('**Mobile**')
-                kpil3_text = st.markdown('0')
-            with kpil4:
-                st.markdown('**Watch**')
-                kpil4_text = st.markdown('0')
-            with kpil5:
-                st.markdown('**Count**')
-                kpil5_text = st.markdown('0')
-            with kpil6:
-                st.markdown('**Img Res**')
-                kpil6_text = st.markdown('0')
-            
-
-
-            st.markdown('<hr/>', unsafe_allow_html=True)
-            # try:
-            def main():
-                db = {}
-                
-                # cap = cv2.VideoCapture('//home//anas//PersonTracking//WebUI//movement.mp4')
-                path='/usr/local/lib/python3.10/dist-packages/yolo0vs5/yolov5s-int8.tflite'
-                #count=0
-                custom = 'yolov5s'
-
-                model = torch.hub.load('/usr/local/lib/python3.10/dist-packages/yolovs5', custom, path,source='local',force_reload=True)
-
-                b=model.names[0] = 'person'
-                mobile = model.names[67] = 'cell phone'
-                watch = model.names[75] = 'clock'
-
-                fps_start_time = datetime.datetime.now()
-                fps = 0
-                size=416
-
-                count=0
-                counter=0
-
-
-                color=(0,0,255)
-
-                cy1=250
-                offset=6
-
-
-                pt1 = (120, 100)
-                pt2 = (980, 1150)
-                color = (0, 255, 0)
-
-                pt3 = (283, 103)
-                pt4 = (1500, 1150)
-                
-                cy2 = 500
-                color = (0, 255, 0)
-                total_frames = 0
-                prevTime = 0
-                cur_frame = 0
-                count=0
-                counter=0
-                fps_start_time = datetime.datetime.now()
-                fps = 0
-                total_frames = 0
-                lpc_count = 0
-                opc_count = 0
-                object_id_list = []
-                # success = True
-                if st.button("Detect"):
-                    try:
-                        while video.isOpened():
-                            
-                            ret, frame = video.read()
-                            frame = imutils.resize(frame, width=600)
-                            total_frames = total_frames + 1
-
-                            (H, W) = frame.shape[:2]
-
-                            blob = cv2.dnn.blobFromImage(frame, 0.007843, (W, H), 127.5)
-
-                            detector.setInput(blob)
-                            person_detections = detector.forward()
-                            rects = []
-                            for i in np.arange(0, person_detections.shape[2]):
-                                confidence = person_detections[0, 0, i, 2]
-                                if confidence > 0.5:
-                                    idx = int(person_detections[0, 0, i, 1])
-
-                                    if CLASSES[idx] != "person":
-                                        continue
-
-                                    person_box = person_detections[0, 0, i, 3:7] * np.array([W, H, W, H])
-                                    (startX, startY, endX, endY) = person_box.astype("int")
-                                    rects.append(person_box)
-
-                            boundingboxes = np.array(rects)
-                            boundingboxes = boundingboxes.astype(int)
-                            rects = non_max_suppression_fast(boundingboxes, 0.3)
-
-                            objects = tracker.update(rects)
-                            for (objectId, bbox) in objects.items():
-                                x1, y1, x2, y2 = bbox
-                                x1 = int(x1)
-                                y1 = int(y1)
-                                x2 = int(x2)
-                                y2 = int(y2)
-
-                                cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 255), 2)
-                                text = "ID: {}".format(objectId)
-                                # print(text)
-                                cv2.putText(frame, text, (x1, y1-5), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 255), 1)
-                                if objectId not in object_id_list:
-                                    object_id_list.append(objectId)
-                            fps_end_time = datetime.datetime.now()
-                            time_diff = fps_end_time - fps_start_time
-                            if time_diff.seconds == 0:
-                                fps = 0.0
-                            else:
-                                fps = (total_frames / time_diff.seconds)
-
-                            fps_text = "FPS: {:.2f}".format(fps)
-
-                            cv2.putText(frame, fps_text, (5, 30), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 255), 1)
-                            lpc_count = len(objects)
-                            opc_count = len(object_id_list)
-
-                            lpc_txt = "LPC: {}".format(lpc_count)
-                            opc_txt = "OPC: {}".format(opc_count)
-                            
-                            count += 1
-                            if count % 4 != 0:
-                                continue
-                            # frame=cv.resize(frame, (600,500))
-                            # cv2.line(frame, pt1, pt2,color,2)
-                            # cv2.line(frame, pt3, pt4,color,2)
-                            results = model(frame,size)
-                            components = results.pandas().xyxy[0]
-                            for index, row in results.pandas().xyxy[0].iterrows():
-                                x1 = int(row['xmin'])
-                                y1 = int(row['ymin'])
-                                x2 = int(row['xmax'])
-                                y2 = int(row['ymax'])
-                                confidence  = (row['confidence'])
-                                obj = (row['class'])
-
-                                
-                                # min':x1,'ymin':y1,'xmax':x2,'ymax':y2,'confidence':confidence,'Object':obj}
-                                # if lpc_txt is not None:
-                                # 	try:
-                                # 		db["student Count"] = [lpc_txt]
-                                # 	except:
-                                # 		db["student Count"] = ['N/A']
-                                if obj == 0:
-                                    cv2.rectangle(frame,(x1,y1),(x2,y2),(0,0,255),2)
-                                    rectx1,recty1 = ((x1+x2)/2,(y1+y2)/2)
-                                    rectcenter = int(rectx1),int(recty1)
-                                    cx = rectcenter[0]
-                                    cy = rectcenter[1]
-                                    cv2.circle(frame,(cx,cy),3,(0,255,0),-1)
-                                    cv2.putText(frame,str(b), (x1,y1), cv2.FONT_HERSHEY_PLAIN,2,(255,255,255),2)
-                                    
-                                    db["student Count"] = [lpc_txt]
-                                    db['Date'] = [date_time]
-                                    db['id'] = ['N/A']
-                                    db['Mobile']=['N/A']
-                                    db['Watch'] = ['N/A']
-                                    if cy<(cy1+offset) and cy>(cy1-offset):
-                                        DB = []
-                                        counter+=1
-                                        DB.append(counter)
-
-                                        ff = DB[-1]
-                                        fx = str(ff)
-                                        # cv2.line(frame, pt1, pt2,(0, 0, 255),2)
-                                        # if cy<(cy2+offset) and cy>(cy2-offset):
-
-                                        # cv2.line(frame, pt3, pt4,(0, 0, 255),2)
-                                        font = cv2.FONT_HERSHEY_TRIPLEX
-                                        cv2.putText(frame,fx,(50, 50),font, 1,(0, 0, 255),2,cv2.LINE_4)
-                                        cv2.putText(frame,"Movement",(70, 70),font, 1,(0, 0, 255),2,cv2.LINE_4)
-                                        kpil2_text.write(f"<h5 style='text-align: left; color:red;'>{text}</h5>", unsafe_allow_html=True)
-                                        
-                                        
-                                        db['id'] = [text]
-                                        # myScreenshot = pyautogui.screenshot()
-                                        # if st.buttn("Dowload ss"):
-                                        #     myScreenshot.save(r'name.png')   
-                                        # myScreenshot.save(r'/home/anas/PersonTracking/AIComputerVision-master/pages/name.png')
-                                if obj == 67:
-                                    cv2.rectangle(frame,(x1,y1),(x2,y2),(0,0,255),2)
-                                    rectx1,recty1 = ((x1+x2)/2,(y1+y2)/2)
-                                    rectcenter = int(rectx1),int(recty1)
-                                    cx = rectcenter[0]
-                                    cy = rectcenter[1]
-                                    cv2.circle(frame,(cx,cy),3,(0,255,0),-1)
-                                    cv2.putText(frame,str(mobile), (x1,y1), cv2.FONT_HERSHEY_PLAIN,2,(255,255,255),2)
-                                    cv2.putText(frame,'Mobile',(50, 50),cv2.FONT_HERSHEY_PLAIN, 1,(0, 0, 255),2,cv2.LINE_4)
-                                    kpil3_text.write(f"<h5 style='text-align: left; color:red;'>{mobile}{text}</h5>", unsafe_allow_html=True)
-                                    
-                                    db['Mobile']=mobile+' '+text
-                                    # myScreenshot = pyautogui.screenshot()
-                                    # if st.buttn("Dowload ss"):
-                                    # myScreenshot.save(r'/home/anas/PersonTracking/AIComputerVision-master/pages/name.png')
-                                    # myScreenshot.save(r'name.png')     
-                                    
-                                if obj == 75:
-                                    cv2.rectangle(frame,(x1,y1),(x2,y2),(0,0,255),2)
-                                    rectx1,recty1 = ((x1+x2)/2,(y1+y2)/2)
-                                    rectcenter = int(rectx1),int(recty1)
-                                    cx = rectcenter[0]
-                                    cy = rectcenter[1]
-                                    cv2.circle(frame,(cx,cy),3,(0,255,0),-1)
-                                    cv2.putText(frame,str(watch), (x1,y1), cv2.FONT_HERSHEY_PLAIN,2,(255,255,255),2)
-                                    cv2.putText(frame,'Watch',(50, 50),cv2.FONT_HERSHEY_PLAIN, 1,(0, 0, 255),2,cv2.LINE_4)
-                                    kpil6_text.write(f"<h5 style='text-align: left; color:red;'>{watch}</h5>", unsafe_allow_html=True)
-                                    
-                                    
-                                    db['Watch']=watch
-                                    myScreenshot = pyautogui.screenshot()
-                                    # if st.buttn("Dowload ss"):
-                                            # myScreenshot.save(r'/home/anas/PersonTracking/AIComputerVision-master/pages/name.png')
-                                    # myScreenshot.save(r'name.png')  
-                                
-                                    
-                            
-                            kpil_text.write(f"<h5 style='text-align: left; color:red;'>{int(fps)}</h5>", unsafe_allow_html=True)
-                            kpil5_text.write(f"<h5 style='text-align: left; color:red;'>{lpc_txt}</h5>", unsafe_allow_html=True)
-                            kpil6_text.write(f"<h5 style='text-align: left; color:red;'>{width*height}</h5>",
-                                            unsafe_allow_html=True)
-                            
-            
-                            frame = cv.resize(frame,(0,0), fx=0.8, fy=0.8)
-                            frame = image_resize(image=frame, width=640)
-                            stframe.image(frame,channels='BGR', use_column_width=True)
-                            df = pd.DataFrame(db)
-                            df.to_csv('final.csv',mode='a',header=False,index=False)
-                    except:
-                        pass
-                    with open('final.csv') as f:
-                        st.download_button(label = 'Download Cheating Report',data=f,file_name='data.csv')
-                        
-                    os.remove("final.csv")
-            main()
diff --git a/spaces/Iceclear/StableSR/StableSR/basicsr/models/sr_model.py b/spaces/Iceclear/StableSR/StableSR/basicsr/models/sr_model.py
deleted file mode 100644
index 787f1fd2eab5963579c764c1bfb87199b7dd196f..0000000000000000000000000000000000000000
--- a/spaces/Iceclear/StableSR/StableSR/basicsr/models/sr_model.py
+++ /dev/null
@@ -1,279 +0,0 @@
-import torch
-from collections import OrderedDict
-from os import path as osp
-from tqdm import tqdm
-
-from basicsr.archs import build_network
-from basicsr.losses import build_loss
-from basicsr.metrics import calculate_metric
-from basicsr.utils import get_root_logger, imwrite, tensor2img
-from basicsr.utils.registry import MODEL_REGISTRY
-from .base_model import BaseModel
-
-
-@MODEL_REGISTRY.register()
-class SRModel(BaseModel):
-    """Base SR model for single image super-resolution."""
-
-    def __init__(self, opt):
-        super(SRModel, self).__init__(opt)
-
-        # define network
-        self.net_g = build_network(opt['network_g'])
-        self.net_g = self.model_to_device(self.net_g)
-        self.print_network(self.net_g)
-
-        # load pretrained models
-        load_path = self.opt['path'].get('pretrain_network_g', None)
-        if load_path is not None:
-            param_key = self.opt['path'].get('param_key_g', 'params')
-            self.load_network(self.net_g, load_path, self.opt['path'].get('strict_load_g', True), param_key)
-
-        if self.is_train:
-            self.init_training_settings()
-
-    def init_training_settings(self):
-        self.net_g.train()
-        train_opt = self.opt['train']
-
-        self.ema_decay = train_opt.get('ema_decay', 0)
-        if self.ema_decay > 0:
-            logger = get_root_logger()
-            logger.info(f'Use Exponential Moving Average with decay: {self.ema_decay}')
-            # define network net_g with Exponential Moving Average (EMA)
-            # net_g_ema is used only for testing on one GPU and saving
-            # There is no need to wrap with DistributedDataParallel
-            self.net_g_ema = build_network(self.opt['network_g']).to(self.device)
-            # load pretrained model
-            load_path = self.opt['path'].get('pretrain_network_g', None)
-            if load_path is not None:
-                self.load_network(self.net_g_ema, load_path, self.opt['path'].get('strict_load_g', True), 'params_ema')
-            else:
-                self.model_ema(0)  # copy net_g weight
-            self.net_g_ema.eval()
-
-        # define losses
-        if train_opt.get('pixel_opt'):
-            self.cri_pix = build_loss(train_opt['pixel_opt']).to(self.device)
-        else:
-            self.cri_pix = None
-
-        if train_opt.get('perceptual_opt'):
-            self.cri_perceptual = build_loss(train_opt['perceptual_opt']).to(self.device)
-        else:
-            self.cri_perceptual = None
-
-        if self.cri_pix is None and self.cri_perceptual is None:
-            raise ValueError('Both pixel and perceptual losses are None.')
-
-        # set up optimizers and schedulers
-        self.setup_optimizers()
-        self.setup_schedulers()
-
-    def setup_optimizers(self):
-        train_opt = self.opt['train']
-        optim_params = []
-        for k, v in self.net_g.named_parameters():
-            if v.requires_grad:
-                optim_params.append(v)
-            else:
-                logger = get_root_logger()
-                logger.warning(f'Params {k} will not be optimized.')
-
-        optim_type = train_opt['optim_g'].pop('type')
-        self.optimizer_g = self.get_optimizer(optim_type, optim_params, **train_opt['optim_g'])
-        self.optimizers.append(self.optimizer_g)
-
-    def feed_data(self, data):
-        self.lq = data['lq'].to(self.device)
-        if 'gt' in data:
-            self.gt = data['gt'].to(self.device)
-
-    def optimize_parameters(self, current_iter):
-        self.optimizer_g.zero_grad()
-        self.output = self.net_g(self.lq)
-
-        l_total = 0
-        loss_dict = OrderedDict()
-        # pixel loss
-        if self.cri_pix:
-            l_pix = self.cri_pix(self.output, self.gt)
-            l_total += l_pix
-            loss_dict['l_pix'] = l_pix
-        # perceptual loss
-        if self.cri_perceptual:
-            l_percep, l_style = self.cri_perceptual(self.output, self.gt)
-            if l_percep is not None:
-                l_total += l_percep
-                loss_dict['l_percep'] = l_percep
-            if l_style is not None:
-                l_total += l_style
-                loss_dict['l_style'] = l_style
-
-        l_total.backward()
-        self.optimizer_g.step()
-
-        self.log_dict = self.reduce_loss_dict(loss_dict)
-
-        if self.ema_decay > 0:
-            self.model_ema(decay=self.ema_decay)
-
-    def test(self):
-        if hasattr(self, 'net_g_ema'):
-            self.net_g_ema.eval()
-            with torch.no_grad():
-                self.output = self.net_g_ema(self.lq)
-        else:
-            self.net_g.eval()
-            with torch.no_grad():
-                self.output = self.net_g(self.lq)
-            self.net_g.train()
-
-    def test_selfensemble(self):
-        # TODO: to be tested
-        # 8 augmentations
-        # modified from https://github.com/thstkdgus35/EDSR-PyTorch
-
-        def _transform(v, op):
-            # if self.precision != 'single': v = v.float()
-            v2np = v.data.cpu().numpy()
-            if op == 'v':
-                tfnp = v2np[:, :, :, ::-1].copy()
-            elif op == 'h':
-                tfnp = v2np[:, :, ::-1, :].copy()
-            elif op == 't':
-                tfnp = v2np.transpose((0, 1, 3, 2)).copy()
-
-            ret = torch.Tensor(tfnp).to(self.device)
-            # if self.precision == 'half': ret = ret.half()
-
-            return ret
-
-        # prepare augmented data
-        lq_list = [self.lq]
-        for tf in 'v', 'h', 't':
-            lq_list.extend([_transform(t, tf) for t in lq_list])
-
-        # inference
-        if hasattr(self, 'net_g_ema'):
-            self.net_g_ema.eval()
-            with torch.no_grad():
-                out_list = [self.net_g_ema(aug) for aug in lq_list]
-        else:
-            self.net_g.eval()
-            with torch.no_grad():
-                out_list = [self.net_g_ema(aug) for aug in lq_list]
-            self.net_g.train()
-
-        # merge results
-        for i in range(len(out_list)):
-            if i > 3:
-                out_list[i] = _transform(out_list[i], 't')
-            if i % 4 > 1:
-                out_list[i] = _transform(out_list[i], 'h')
-            if (i % 4) % 2 == 1:
-                out_list[i] = _transform(out_list[i], 'v')
-        output = torch.cat(out_list, dim=0)
-
-        self.output = output.mean(dim=0, keepdim=True)
-
-    def dist_validation(self, dataloader, current_iter, tb_logger, save_img):
-        if self.opt['rank'] == 0:
-            self.nondist_validation(dataloader, current_iter, tb_logger, save_img)
-
-    def nondist_validation(self, dataloader, current_iter, tb_logger, save_img):
-        dataset_name = dataloader.dataset.opt['name']
-        with_metrics = self.opt['val'].get('metrics') is not None
-        use_pbar = self.opt['val'].get('pbar', False)
-
-        if with_metrics:
-            if not hasattr(self, 'metric_results'):  # only execute in the first run
-                self.metric_results = {metric: 0 for metric in self.opt['val']['metrics'].keys()}
-            # initialize the best metric results for each dataset_name (supporting multiple validation datasets)
-            self._initialize_best_metric_results(dataset_name)
-        # zero self.metric_results
-        if with_metrics:
-            self.metric_results = {metric: 0 for metric in self.metric_results}
-
-        metric_data = dict()
-        if use_pbar:
-            pbar = tqdm(total=len(dataloader), unit='image')
-
-        for idx, val_data in enumerate(dataloader):
-            img_name = osp.splitext(osp.basename(val_data['lq_path'][0]))[0]
-            self.feed_data(val_data)
-            self.test()
-
-            visuals = self.get_current_visuals()
-            sr_img = tensor2img([visuals['result']])
-            metric_data['img'] = sr_img
-            if 'gt' in visuals:
-                gt_img = tensor2img([visuals['gt']])
-                metric_data['img2'] = gt_img
-                del self.gt
-
-            # tentative for out of GPU memory
-            del self.lq
-            del self.output
-            torch.cuda.empty_cache()
-
-            if save_img:
-                if self.opt['is_train']:
-                    save_img_path = osp.join(self.opt['path']['visualization'], img_name,
-                                             f'{img_name}_{current_iter}.png')
-                else:
-                    if self.opt['val']['suffix']:
-                        save_img_path = osp.join(self.opt['path']['visualization'], dataset_name,
-                                                 f'{img_name}_{self.opt["val"]["suffix"]}.png')
-                    else:
-                        save_img_path = osp.join(self.opt['path']['visualization'], dataset_name,
-                                                 f'{img_name}_{self.opt["name"]}.png')
-                imwrite(sr_img, save_img_path)
-
-            if with_metrics:
-                # calculate metrics
-                for name, opt_ in self.opt['val']['metrics'].items():
-                    self.metric_results[name] += calculate_metric(metric_data, opt_)
-            if use_pbar:
-                pbar.update(1)
-                pbar.set_description(f'Test {img_name}')
-        if use_pbar:
-            pbar.close()
-
-        if with_metrics:
-            for metric in self.metric_results.keys():
-                self.metric_results[metric] /= (idx + 1)
-                # update the best metric result
-                self._update_best_metric_result(dataset_name, metric, self.metric_results[metric], current_iter)
-
-            self._log_validation_metric_values(current_iter, dataset_name, tb_logger)
-
-    def _log_validation_metric_values(self, current_iter, dataset_name, tb_logger):
-        log_str = f'Validation {dataset_name}\n'
-        for metric, value in self.metric_results.items():
-            log_str += f'\t # {metric}: {value:.4f}'
-            if hasattr(self, 'best_metric_results'):
-                log_str += (f'\tBest: {self.best_metric_results[dataset_name][metric]["val"]:.4f} @ '
-                            f'{self.best_metric_results[dataset_name][metric]["iter"]} iter')
-            log_str += '\n'
-
-        logger = get_root_logger()
-        logger.info(log_str)
-        if tb_logger:
-            for metric, value in self.metric_results.items():
-                tb_logger.add_scalar(f'metrics/{dataset_name}/{metric}', value, current_iter)
-
-    def get_current_visuals(self):
-        out_dict = OrderedDict()
-        out_dict['lq'] = self.lq.detach().cpu()
-        out_dict['result'] = self.output.detach().cpu()
-        if hasattr(self, 'gt'):
-            out_dict['gt'] = self.gt.detach().cpu()
-        return out_dict
-
-    def save(self, epoch, current_iter):
-        if hasattr(self, 'net_g_ema'):
-            self.save_network([self.net_g, self.net_g_ema], 'net_g', current_iter, param_key=['params', 'params_ema'])
-        else:
-            self.save_network(self.net_g, 'net_g', current_iter)
-        self.save_training_state(epoch, current_iter)
diff --git a/spaces/InpaintAI/Inpaint-Anything/utils/visual_mask_on_img.py b/spaces/InpaintAI/Inpaint-Anything/utils/visual_mask_on_img.py
deleted file mode 100644
index 2897ee90d588d66bcf8382bcbe74b191eda91b6d..0000000000000000000000000000000000000000
--- a/spaces/InpaintAI/Inpaint-Anything/utils/visual_mask_on_img.py
+++ /dev/null
@@ -1,62 +0,0 @@
-import cv2
-import sys
-import argparse
-import numpy as np
-from PIL import Image
-from pathlib import Path
-from matplotlib import pyplot as plt
-from typing import Any, Dict, List
-import glob
-
-from utils import load_img_to_array, show_mask
-
-
-def setup_args(parser):
-    parser.add_argument(
-        "--input_img", type=str, required=True,
-        help="Path to a single input img",
-    )
-    parser.add_argument(
-        "--input_mask_glob", type=str, required=True,
-        help="Glob to input masks",
-    )
-    parser.add_argument(
-        "--output_dir", type=str, required=True,
-        help="Output path to the directory with results.",
-    )
-
-if __name__ == "__main__":
-    """Example usage:
-    python visual_mask_on_img.py \
-        --input_img FA_demo/FA1_dog.png \
-        --input_mask_glob "results/FA1_dog/mask*.png" \
-        --output_dir results
-    """
-    parser = argparse.ArgumentParser()
-    setup_args(parser)
-    args = parser.parse_args(sys.argv[1:])
-
-    img = load_img_to_array(args.input_img)
-    img_stem = Path(args.input_img).stem
-
-    mask_ps = sorted(glob.glob(args.input_mask_glob))
-
-    out_dir = Path(args.output_dir) / img_stem
-    out_dir.mkdir(parents=True, exist_ok=True)
-
-    for mask_p in mask_ps:
-        mask = load_img_to_array(mask_p)
-        mask = mask.astype(np.uint8)
-
-        # path to the results
-        img_mask_p = out_dir / f"with_{Path(mask_p).name}"
-
-        # save the masked image
-        dpi = plt.rcParams['figure.dpi']
-        height, width = img.shape[:2]
-        plt.figure(figsize=(width/dpi/0.77, height/dpi/0.77))
-        plt.imshow(img)
-        plt.axis('off')
-        show_mask(plt.gca(), mask, random_color=False)
-        plt.savefig(img_mask_p, bbox_inches='tight', pad_inches=0)
-        plt.close()
diff --git a/spaces/JUNGU/VToonify/vtoonify/model/vtoonify.py b/spaces/JUNGU/VToonify/vtoonify/model/vtoonify.py
deleted file mode 100644
index 6556a0a6c734be5f413f4683eb63c44f449c6af8..0000000000000000000000000000000000000000
--- a/spaces/JUNGU/VToonify/vtoonify/model/vtoonify.py
+++ /dev/null
@@ -1,286 +0,0 @@
-import torch
-import numpy as np
-import math
-from torch import nn
-from model.stylegan.model import ConvLayer, EqualLinear, Generator, ResBlock
-from model.dualstylegan import AdaptiveInstanceNorm, AdaResBlock, DualStyleGAN
-import torch.nn.functional as F
-
-# IC-GAN: stylegan discriminator    
-class ConditionalDiscriminator(nn.Module):
-    def __init__(self, size, channel_multiplier=2, blur_kernel=[1, 3, 3, 1], use_condition=False, style_num=None):
-        super().__init__()
-
-        channels = {
-            4: 512,
-            8: 512,
-            16: 512,
-            32: 512,
-            64: 256 * channel_multiplier,
-            128: 128 * channel_multiplier,
-            256: 64 * channel_multiplier,
-            512: 32 * channel_multiplier,
-            1024: 16 * channel_multiplier,
-        }
-
-        convs = [ConvLayer(3, channels[size], 1)]
-
-        log_size = int(math.log(size, 2))
-
-        in_channel = channels[size]
-
-        for i in range(log_size, 2, -1):
-            out_channel = channels[2 ** (i - 1)]
-
-            convs.append(ResBlock(in_channel, out_channel, blur_kernel))
-
-            in_channel = out_channel
-
-        self.convs = nn.Sequential(*convs)
-
-        self.stddev_group = 4
-        self.stddev_feat = 1
-        self.use_condition = use_condition
-        
-        if self.use_condition:
-            self.condition_dim = 128
-            # map style degree to 64-dimensional vector
-            self.label_mapper = nn.Sequential(
-                nn.Linear(1, 64),
-                nn.LeakyReLU(negative_slope=0.2, inplace=True),
-                nn.Linear(64, 64),
-                nn.LeakyReLU(negative_slope=0.2, inplace=True),
-                nn.Linear(64, self.condition_dim//2),
-            )
-            # map style code index to 64-dimensional vector
-            self.style_mapper = nn.Embedding(style_num, self.condition_dim-self.condition_dim//2)
-        else:
-            self.condition_dim = 1
-            
-        self.final_conv = ConvLayer(in_channel + 1, channels[4], 3)
-        self.final_linear = nn.Sequential(
-            EqualLinear(channels[4] * 4 * 4, channels[4], activation="fused_lrelu"),
-            EqualLinear(channels[4], self.condition_dim),
-        )
-        
-    def forward(self, input, degree_label=None, style_ind=None):
-        out = self.convs(input)
-
-        batch, channel, height, width = out.shape
-        group = min(batch, self.stddev_group)
-        stddev = out.view(
-            group, -1, self.stddev_feat, channel // self.stddev_feat, height, width
-        )
-        stddev = torch.sqrt(stddev.var(0, unbiased=False) + 1e-8)
-        stddev = stddev.mean([2, 3, 4], keepdims=True).squeeze(2)
-        stddev = stddev.repeat(group, 1, height, width)
-        out = torch.cat([out, stddev], 1)
-
-        out = self.final_conv(out)
-        out = out.view(batch, -1)
-        
-        if self.use_condition:
-            h = self.final_linear(out)
-            condition = torch.cat((self.label_mapper(degree_label), self.style_mapper(style_ind)), dim=1)
-            out = (h * condition).sum(dim=1, keepdim=True) * (1 / np.sqrt(self.condition_dim))
-        else:
-            out = self.final_linear(out)
-            
-        return out 
-    
-
-class VToonifyResBlock(nn.Module):
-    def __init__(self, fin):
-        super().__init__()
-
-        self.conv = nn.Conv2d(fin, fin, 3,  1, 1)
-        self.conv2 = nn.Conv2d(fin, fin, 3,  1, 1)
-        self.lrelu = nn.LeakyReLU(negative_slope=0.2, inplace=True)
-        
-    def forward(self, x):
-        out = self.lrelu(self.conv(x))
-        out = self.lrelu(self.conv2(out))      
-        out = (out + x) / math.sqrt(2)
-        return out    
-
-class Fusion(nn.Module):
-    def __init__(self, in_channels, skip_channels, out_channels):
-        super().__init__()
-
-        # create conv layers
-        self.conv = nn.Conv2d(in_channels + skip_channels, out_channels, 3, 1, 1, bias=True)
-        self.norm = AdaptiveInstanceNorm(in_channels + skip_channels, 128)
-        self.conv2 = nn.Conv2d(in_channels + skip_channels, 1, 3, 1, 1, bias=True)
-        #'''
-        self.linear = nn.Sequential(
-            nn.Linear(1, 64),
-            nn.LeakyReLU(negative_slope=0.2, inplace=True),
-            nn.Linear(64, 128),
-            nn.LeakyReLU(negative_slope=0.2, inplace=True)
-        )
-
-    def forward(self, f_G, f_E, d_s=1):
-        # label of style degree
-        label = self.linear(torch.zeros(f_G.size(0),1).to(f_G.device) + d_s)
-        out = torch.cat([f_G, abs(f_G-f_E)], dim=1)
-        m_E = (F.relu(self.conv2(self.norm(out, label)))).tanh()
-        f_out = self.conv(torch.cat([f_G, f_E * m_E], dim=1))
-        return f_out, m_E
-    
-class VToonify(nn.Module):
-    def __init__(self,
-                 in_size=256,
-                 out_size=1024,
-                 img_channels=3,
-                 style_channels=512,
-                 num_mlps=8,
-                 channel_multiplier=2,
-                 num_res_layers=6,
-                 backbone = 'dualstylegan',
-                ):
-
-        super().__init__()
-
-        self.backbone = backbone
-        if self.backbone == 'dualstylegan':
-            # DualStyleGAN, with weights being fixed
-            self.generator = DualStyleGAN(out_size, style_channels, num_mlps, channel_multiplier)
-        else:
-            # StyleGANv2, with weights being fixed
-            self.generator = Generator(out_size, style_channels, num_mlps, channel_multiplier)
-
-        self.in_size = in_size
-        self.style_channels = style_channels
-        channels = self.generator.channels
-
-        # encoder
-        num_styles = int(np.log2(out_size)) * 2 - 2
-        encoder_res = [2**i for i in range(int(np.log2(in_size)), 4, -1)]
-        self.encoder = nn.ModuleList()
-        self.encoder.append(
-            nn.Sequential(
-                nn.Conv2d(img_channels+19, 32, 3, 1, 1, bias=True), 
-                nn.LeakyReLU(negative_slope=0.2, inplace=True),
-                nn.Conv2d(32, channels[in_size], 3, 1, 1, bias=True),
-                nn.LeakyReLU(negative_slope=0.2, inplace=True)))
-        
-        for res in encoder_res:
-            in_channels = channels[res]
-            if res > 32:
-                out_channels = channels[res // 2]
-                block = nn.Sequential(
-                    nn.Conv2d(in_channels, out_channels, 3, 2, 1, bias=True),
-                    nn.LeakyReLU(negative_slope=0.2, inplace=True),
-                    nn.Conv2d(out_channels, out_channels, 3, 1, 1, bias=True),
-                    nn.LeakyReLU(negative_slope=0.2, inplace=True))
-                self.encoder.append(block)
-            else:
-                layers = []
-                for _ in range(num_res_layers):
-                    layers.append(VToonifyResBlock(in_channels))
-                self.encoder.append(nn.Sequential(*layers))
-                block = nn.Conv2d(in_channels, img_channels, 1, 1, 0, bias=True)
-                self.encoder.append(block)
-        
-        # trainable fusion module
-        self.fusion_out = nn.ModuleList()
-        self.fusion_skip = nn.ModuleList()
-        for res in encoder_res[::-1]:
-            num_channels = channels[res]
-            if self.backbone == 'dualstylegan':
-                self.fusion_out.append(
-                    Fusion(num_channels, num_channels, num_channels))
-            else:
-                self.fusion_out.append(
-                    nn.Conv2d(num_channels * 2, num_channels, 3, 1, 1, bias=True))
-
-            self.fusion_skip.append(
-                nn.Conv2d(num_channels + 3, 3, 3, 1, 1, bias=True))
-        
-        # Modified ModRes blocks in DualStyleGAN, with weights being fixed
-        if self.backbone == 'dualstylegan':
-            self.res = nn.ModuleList()
-            self.res.append(AdaResBlock(self.generator.channels[2 ** 2])) # for conv1, no use in this model
-            for i in range(3, 6):
-                out_channel = self.generator.channels[2 ** i]
-                self.res.append(AdaResBlock(out_channel, dilation=2**(5-i)))
-                self.res.append(AdaResBlock(out_channel, dilation=2**(5-i)))
-
-    
-    def forward(self, x, style, d_s=None, return_mask=False, return_feat=False):
-        # map style to W+ space
-        if style is not None and style.ndim < 3:
-            if self.backbone == 'dualstylegan':
-                resstyles = self.generator.style(style).unsqueeze(1).repeat(1, self.generator.n_latent, 1)
-            adastyles = style.unsqueeze(1).repeat(1, self.generator.n_latent, 1)
-        elif style is not None:
-            nB, nL, nD = style.shape
-            if self.backbone == 'dualstylegan':
-                resstyles = self.generator.style(style.reshape(nB*nL, nD)).reshape(nB, nL, nD)
-            adastyles = style
-        if self.backbone == 'dualstylegan':
-            adastyles = adastyles.clone()
-            for i in range(7, self.generator.n_latent):
-                adastyles[:, i] = self.generator.res[i](adastyles[:, i])
-
-        # obtain multi-scale content features
-        feat = x
-        encoder_features = []
-        # downsampling conv parts of E
-        for block in self.encoder[:-2]:
-            feat = block(feat)
-            encoder_features.append(feat)
-        encoder_features = encoder_features[::-1]
-        # Resblocks in E
-        for ii, block in enumerate(self.encoder[-2]):
-            feat = block(feat)
-            # adjust Resblocks with ModRes blocks
-            if self.backbone == 'dualstylegan':
-                feat = self.res[ii+1](feat, resstyles[:, ii+1], d_s)
-        # the last-layer feature of E (inputs of backbone)
-        out = feat
-        skip = self.encoder[-1](feat)
-        if return_feat:
-            return out, skip
-        
-        # 32x32 ---> higher res
-        _index = 1
-        m_Es = []
-        for conv1, conv2, to_rgb in zip(
-            self.stylegan().convs[6::2], self.stylegan().convs[7::2], self.stylegan().to_rgbs[3:]): 
-            
-            # pass the mid-layer features of E to the corresponding resolution layers of G
-            if 2 ** (5+((_index-1)//2)) <= self.in_size:
-                fusion_index = (_index - 1) // 2
-                f_E = encoder_features[fusion_index]
-
-                if self.backbone == 'dualstylegan':
-                    out, m_E = self.fusion_out[fusion_index](out, f_E, d_s)
-                    skip = self.fusion_skip[fusion_index](torch.cat([skip, f_E*m_E], dim=1))
-                    m_Es += [m_E]
-                else:
-                    out = self.fusion_out[fusion_index](torch.cat([out, f_E], dim=1))
-                    skip = self.fusion_skip[fusion_index](torch.cat([skip, f_E], dim=1))  
-            
-            # remove the noise input
-            batch, _, height, width = out.shape
-            noise = x.new_empty(batch, 1, height * 2, width * 2).normal_().detach() * 0.0
-            
-            out = conv1(out, adastyles[:, _index+6], noise=noise)
-            out = conv2(out, adastyles[:, _index+7], noise=noise)
-            skip = to_rgb(out, adastyles[:, _index+8], skip)
-            _index += 2
-
-        image = skip
-        if return_mask and self.backbone == 'dualstylegan':
-            return image, m_Es
-        return image
-    
-    def stylegan(self):
-        if self.backbone == 'dualstylegan':
-            return self.generator.generator
-        else:
-            return self.generator
-        
-    def zplus2wplus(self, zplus):
-        return self.stylegan().style(zplus.reshape(zplus.shape[0]*zplus.shape[1], zplus.shape[2])).reshape(zplus.shape)
\ No newline at end of file
diff --git a/spaces/Jackflack09/diffuse-custom/diffusers/utils/pil_utils.py b/spaces/Jackflack09/diffuse-custom/diffusers/utils/pil_utils.py
deleted file mode 100644
index 39d0a15a4e2fe39fecb01951b36c43368492f983..0000000000000000000000000000000000000000
--- a/spaces/Jackflack09/diffuse-custom/diffusers/utils/pil_utils.py
+++ /dev/null
@@ -1,21 +0,0 @@
-import PIL.Image
-import PIL.ImageOps
-from packaging import version
-
-
-if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
-    PIL_INTERPOLATION = {
-        "linear": PIL.Image.Resampling.BILINEAR,
-        "bilinear": PIL.Image.Resampling.BILINEAR,
-        "bicubic": PIL.Image.Resampling.BICUBIC,
-        "lanczos": PIL.Image.Resampling.LANCZOS,
-        "nearest": PIL.Image.Resampling.NEAREST,
-    }
-else:
-    PIL_INTERPOLATION = {
-        "linear": PIL.Image.LINEAR,
-        "bilinear": PIL.Image.BILINEAR,
-        "bicubic": PIL.Image.BICUBIC,
-        "lanczos": PIL.Image.LANCZOS,
-        "nearest": PIL.Image.NEAREST,
-    }
diff --git a/spaces/Jamel887/Rvc-tio887/lib/infer_pack/modules/F0Predictor/F0Predictor.py b/spaces/Jamel887/Rvc-tio887/lib/infer_pack/modules/F0Predictor/F0Predictor.py
deleted file mode 100644
index f56e49e7f0e6eab3babf0711cae2933371b9f9cc..0000000000000000000000000000000000000000
--- a/spaces/Jamel887/Rvc-tio887/lib/infer_pack/modules/F0Predictor/F0Predictor.py
+++ /dev/null
@@ -1,16 +0,0 @@
-class F0Predictor(object):
-    def compute_f0(self, wav, p_len):
-        """
-        input: wav:[signal_length]
-               p_len:int
-        output: f0:[signal_length//hop_length]
-        """
-        pass
-
-    def compute_f0_uv(self, wav, p_len):
-        """
-        input: wav:[signal_length]
-               p_len:int
-        output: f0:[signal_length//hop_length],uv:[signal_length//hop_length]
-        """
-        pass
diff --git a/spaces/Jamkonams/AutoGPT/autogpt/agent/agent.py b/spaces/Jamkonams/AutoGPT/autogpt/agent/agent.py
deleted file mode 100644
index ee7885f8844022597321fa6b492430ec34c0d6b9..0000000000000000000000000000000000000000
--- a/spaces/Jamkonams/AutoGPT/autogpt/agent/agent.py
+++ /dev/null
@@ -1,197 +0,0 @@
-from colorama import Fore, Style
-
-from autogpt.app import execute_command, get_command
-from autogpt.chat import chat_with_ai, create_chat_message
-from autogpt.config import Config
-from autogpt.json_utils.json_fix_llm import fix_json_using_multiple_techniques
-from autogpt.json_utils.utilities import validate_json
-from autogpt.logs import logger, print_assistant_thoughts
-from autogpt.speech import say_text
-from autogpt.spinner import Spinner
-from autogpt.utils import clean_input
-
-
-class Agent:
-    """Agent class for interacting with Auto-GPT.
-
-    Attributes:
-        ai_name: The name of the agent.
-        memory: The memory object to use.
-        full_message_history: The full message history.
-        next_action_count: The number of actions to execute.
-        system_prompt: The system prompt is the initial prompt that defines everything the AI needs to know to achieve its task successfully.
-        Currently, the dynamic and customizable information in the system prompt are ai_name, description and goals.
-
-        triggering_prompt: The last sentence the AI will see before answering. For Auto-GPT, this prompt is:
-            Determine which next command to use, and respond using the format specified above:
-            The triggering prompt is not part of the system prompt because between the system prompt and the triggering
-            prompt we have contextual information that can distract the AI and make it forget that its goal is to find the next task to achieve.
-            SYSTEM PROMPT
-            CONTEXTUAL INFORMATION (memory, previous conversations, anything relevant)
-            TRIGGERING PROMPT
-
-        The triggering prompt reminds the AI about its short term meta task (defining the next task)
-    """
-
-    def __init__(
-        self,
-        ai_name,
-        memory,
-        full_message_history,
-        next_action_count,
-        system_prompt,
-        triggering_prompt,
-    ):
-        self.ai_name = ai_name
-        self.memory = memory
-        self.full_message_history = full_message_history
-        self.next_action_count = next_action_count
-        self.system_prompt = system_prompt
-        self.triggering_prompt = triggering_prompt
-
-    def start_interaction_loop(self):
-        # Interaction Loop
-        cfg = Config()
-        loop_count = 0
-        command_name = None
-        arguments = None
-        user_input = ""
-
-        while True:
-            # Discontinue if continuous limit is reached
-            loop_count += 1
-            if (
-                cfg.continuous_mode
-                and cfg.continuous_limit > 0
-                and loop_count > cfg.continuous_limit
-            ):
-                logger.typewriter_log(
-                    "Continuous Limit Reached: ", Fore.YELLOW, f"{cfg.continuous_limit}"
-                )
-                break
-
-            # Send message to AI, get response
-            with Spinner("Thinking... "):
-                assistant_reply = chat_with_ai(
-                    self.system_prompt,
-                    self.triggering_prompt,
-                    self.full_message_history,
-                    self.memory,
-                    cfg.fast_token_limit,
-                )  # TODO: This hardcodes the model to use GPT3.5. Make this an argument
-
-            assistant_reply_json = fix_json_using_multiple_techniques(assistant_reply)
-
-            # Print Assistant thoughts
-            if assistant_reply_json != {}:
-                validate_json(assistant_reply_json, "llm_response_format_1")
-                # Get command name and arguments
-                try:
-                    print_assistant_thoughts(self.ai_name, assistant_reply_json)
-                    command_name, arguments = get_command(assistant_reply_json)
-                    # command_name, arguments = assistant_reply_json_valid["command"]["name"], assistant_reply_json_valid["command"]["args"]
-                    if cfg.speak_mode:
-                        say_text(f"I want to execute {command_name}")
-                except Exception as e:
-                    logger.error("Error: \n", str(e))
-
-            if not cfg.continuous_mode and self.next_action_count == 0:
-                ### GET USER AUTHORIZATION TO EXECUTE COMMAND ###
-                # Get key press: Prompt the user to press enter to continue or escape
-                # to exit
-                logger.typewriter_log(
-                    "NEXT ACTION: ",
-                    Fore.CYAN,
-                    f"COMMAND = {Fore.CYAN}{command_name}{Style.RESET_ALL}  "
-                    f"ARGUMENTS = {Fore.CYAN}{arguments}{Style.RESET_ALL}",
-                )
-                print(
-                    "Enter 'y' to authorise command, 'y -N' to run N continuous "
-                    "commands, 'n' to exit program, or enter feedback for "
-                    f"{self.ai_name}...",
-                    flush=True,
-                )
-                while True:
-                    console_input = clean_input(
-                        Fore.MAGENTA + "Input:" + Style.RESET_ALL
-                    )
-                    if console_input.lower().strip() == "y":
-                        user_input = "GENERATE NEXT COMMAND JSON"
-                        break
-                    elif console_input.lower().strip() == "":
-                        print("Invalid input format.")
-                        continue
-                    elif console_input.lower().startswith("y -"):
-                        try:
-                            self.next_action_count = abs(
-                                int(console_input.split(" ")[1])
-                            )
-                            user_input = "GENERATE NEXT COMMAND JSON"
-                        except ValueError:
-                            print(
-                                "Invalid input format. Please enter 'y -n' where n is"
-                                " the number of continuous tasks."
-                            )
-                            continue
-                        break
-                    elif console_input.lower() == "n":
-                        user_input = "EXIT"
-                        break
-                    else:
-                        user_input = console_input
-                        command_name = "human_feedback"
-                        break
-
-                if user_input == "GENERATE NEXT COMMAND JSON":
-                    logger.typewriter_log(
-                        "-=-=-=-=-=-=-= COMMAND AUTHORISED BY USER -=-=-=-=-=-=-=",
-                        Fore.MAGENTA,
-                        "",
-                    )
-                elif user_input == "EXIT":
-                    print("Exiting...", flush=True)
-                    break
-            else:
-                # Print command
-                logger.typewriter_log(
-                    "NEXT ACTION: ",
-                    Fore.CYAN,
-                    f"COMMAND = {Fore.CYAN}{command_name}{Style.RESET_ALL}"
-                    f"  ARGUMENTS = {Fore.CYAN}{arguments}{Style.RESET_ALL}",
-                )
-
-            # Execute command
-            if command_name is not None and command_name.lower().startswith("error"):
-                result = (
-                    f"Command {command_name} threw the following error: {arguments}"
-                )
-            elif command_name == "human_feedback":
-                result = f"Human feedback: {user_input}"
-            else:
-                result = (
-                    f"Command {command_name} returned: "
-                    f"{execute_command(command_name, arguments)}"
-                )
-                if self.next_action_count > 0:
-                    self.next_action_count -= 1
-
-            memory_to_add = (
-                f"Assistant Reply: {assistant_reply} "
-                f"\nResult: {result} "
-                f"\nHuman Feedback: {user_input} "
-            )
-
-            self.memory.add(memory_to_add)
-
-            # Check if there's a result from the command append it to the message
-            # history
-            if result is not None:
-                self.full_message_history.append(create_chat_message("system", result))
-                logger.typewriter_log("SYSTEM: ", Fore.YELLOW, result)
-            else:
-                self.full_message_history.append(
-                    create_chat_message("system", "Unable to execute command")
-                )
-                logger.typewriter_log(
-                    "SYSTEM: ", Fore.YELLOW, "Unable to execute command"
-                )
diff --git a/spaces/JoYCC/ICBU-NPU-FashionGPT-70B-V1.1/README.md b/spaces/JoYCC/ICBU-NPU-FashionGPT-70B-V1.1/README.md
deleted file mode 100644
index 9da135f813f5c02d180770f12f1b635a523454e3..0000000000000000000000000000000000000000
--- a/spaces/JoYCC/ICBU-NPU-FashionGPT-70B-V1.1/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: ICBU NPU FashionGPT 70B V1.1
-emoji: ⚡
-colorFrom: purple
-colorTo: purple
-sdk: gradio
-sdk_version: 3.44.4
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/JohnSmith9982/ChuanhuChatGPT_Beta/modules/chat_func.py b/spaces/JohnSmith9982/ChuanhuChatGPT_Beta/modules/chat_func.py
deleted file mode 100644
index 4c635c51ada4a852d1495646cf81120de15af7b9..0000000000000000000000000000000000000000
--- a/spaces/JohnSmith9982/ChuanhuChatGPT_Beta/modules/chat_func.py
+++ /dev/null
@@ -1,497 +0,0 @@
-# -*- coding:utf-8 -*-
-from __future__ import annotations
-from typing import TYPE_CHECKING, List
-
-import logging
-import json
-import os
-import requests
-import urllib3
-
-from tqdm import tqdm
-import colorama
-from duckduckgo_search import ddg
-import asyncio
-import aiohttp
-
-
-from modules.presets import *
-from modules.llama_func import *
-from modules.utils import *
-from . import shared
-from modules.config import retrieve_proxy
-
-# logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] [%(filename)s:%(lineno)d] %(message)s")
-
-if TYPE_CHECKING:
-    from typing import TypedDict
-
-    class DataframeData(TypedDict):
-        headers: List[str]
-        data: List[List[str | int | bool]]
-
-
-initial_prompt = "You are a helpful assistant."
-HISTORY_DIR = "history"
-TEMPLATES_DIR = "templates"
-
-@shared.state.switching_api_key # 在不开启多账号模式的时候，这个装饰器不会起作用
-def get_response(
-    openai_api_key, system_prompt, history, temperature, top_p, stream, selected_model
-):
-    headers = {
-        "Content-Type": "application/json",
-        "Authorization": f"Bearer {openai_api_key}",
-    }
-
-    history = [construct_system(system_prompt), *history]
-
-    payload = {
-        "model": selected_model,
-        "messages": history,  # [{"role": "user", "content": f"{inputs}"}],
-        "temperature": temperature,  # 1.0,
-        "top_p": top_p,  # 1.0,
-        "n": 1,
-        "stream": stream,
-        "presence_penalty": 0,
-        "frequency_penalty": 0,
-    }
-    if stream:
-        timeout = timeout_streaming
-    else:
-        timeout = timeout_all
-
-
-    # 如果有自定义的api-host，使用自定义host发送请求，否则使用默认设置发送请求
-    if shared.state.completion_url != COMPLETION_URL:
-        logging.info(f"使用自定义API URL: {shared.state.completion_url}")
-
-    with retrieve_proxy():
-        response = requests.post(
-            shared.state.completion_url,
-            headers=headers,
-            json=payload,
-            stream=True,
-            timeout=timeout,
-        )
-
-    return response
-
-
-def stream_predict(
-    openai_api_key,
-    system_prompt,
-    history,
-    inputs,
-    chatbot,
-    all_token_counts,
-    top_p,
-    temperature,
-    selected_model,
-    fake_input=None,
-    display_append=""
-):
-    def get_return_value():
-        return chatbot, history, status_text, all_token_counts
-
-    logging.info("实时回答模式")
-    partial_words = ""
-    counter = 0
-    status_text = "开始实时传输回答……"
-    history.append(construct_user(inputs))
-    history.append(construct_assistant(""))
-    if fake_input:
-        chatbot.append((fake_input, ""))
-    else:
-        chatbot.append((inputs, ""))
-    user_token_count = 0
-    if fake_input is not None:
-        input_token_count = count_token(construct_user(fake_input))
-    else:
-        input_token_count = count_token(construct_user(inputs))
-    if len(all_token_counts) == 0:
-        system_prompt_token_count = count_token(construct_system(system_prompt))
-        user_token_count = (
-            input_token_count + system_prompt_token_count
-        )
-    else:
-        user_token_count = input_token_count
-    all_token_counts.append(user_token_count)
-    logging.info(f"输入token计数: {user_token_count}")
-    yield get_return_value()
-    try:
-        response = get_response(
-            openai_api_key,
-            system_prompt,
-            history,
-            temperature,
-            top_p,
-            True,
-            selected_model,
-        )
-    except requests.exceptions.ConnectTimeout:
-        status_text = (
-            standard_error_msg + connection_timeout_prompt + error_retrieve_prompt
-        )
-        yield get_return_value()
-        return
-    except requests.exceptions.ReadTimeout:
-        status_text = standard_error_msg + read_timeout_prompt + error_retrieve_prompt
-        yield get_return_value()
-        return
-
-    yield get_return_value()
-    error_json_str = ""
-
-    if fake_input is not None:
-        history[-2] = construct_user(fake_input)
-    for chunk in tqdm(response.iter_lines()):
-        if counter == 0:
-            counter += 1
-            continue
-        counter += 1
-        # check whether each line is non-empty
-        if chunk:
-            chunk = chunk.decode()
-            chunklength = len(chunk)
-            try:
-                chunk = json.loads(chunk[6:])
-            except json.JSONDecodeError:
-                logging.info(chunk)
-                error_json_str += chunk
-                status_text = f"JSON解析错误。请重置对话。收到的内容: {error_json_str}"
-                yield get_return_value()
-                continue
-            # decode each line as response data is in bytes
-            if chunklength > 6 and "delta" in chunk["choices"][0]:
-                finish_reason = chunk["choices"][0]["finish_reason"]
-                status_text = construct_token_message(all_token_counts)
-                if finish_reason == "stop":
-                    yield get_return_value()
-                    break
-                try:
-                    partial_words = (
-                        partial_words + chunk["choices"][0]["delta"]["content"]
-                    )
-                except KeyError:
-                    status_text = (
-                        standard_error_msg
-                        + "API回复中找不到内容。很可能是Token计数达到上限了。请重置对话。当前Token计数: "
-                        + str(sum(all_token_counts))
-                    )
-                    yield get_return_value()
-                    break
-                history[-1] = construct_assistant(partial_words)
-                chatbot[-1] = (chatbot[-1][0], partial_words+display_append)
-                all_token_counts[-1] += 1
-                yield get_return_value()
-
-
-def predict_all(
-    openai_api_key,
-    system_prompt,
-    history,
-    inputs,
-    chatbot,
-    all_token_counts,
-    top_p,
-    temperature,
-    selected_model,
-    fake_input=None,
-    display_append=""
-):
-    logging.info("一次性回答模式")
-    history.append(construct_user(inputs))
-    history.append(construct_assistant(""))
-    if fake_input:
-        chatbot.append((fake_input, ""))
-    else:
-        chatbot.append((inputs, ""))
-    if fake_input is not None:
-        all_token_counts.append(count_token(construct_user(fake_input)))
-    else:
-        all_token_counts.append(count_token(construct_user(inputs)))
-    try:
-        response = get_response(
-            openai_api_key,
-            system_prompt,
-            history,
-            temperature,
-            top_p,
-            False,
-            selected_model,
-        )
-    except requests.exceptions.ConnectTimeout:
-        status_text = (
-            standard_error_msg + connection_timeout_prompt + error_retrieve_prompt
-        )
-        return chatbot, history, status_text, all_token_counts
-    except requests.exceptions.ProxyError:
-        status_text = standard_error_msg + proxy_error_prompt + error_retrieve_prompt
-        return chatbot, history, status_text, all_token_counts
-    except requests.exceptions.SSLError:
-        status_text = standard_error_msg + ssl_error_prompt + error_retrieve_prompt
-        return chatbot, history, status_text, all_token_counts
-    response = json.loads(response.text)
-    if fake_input is not None:
-        history[-2] = construct_user(fake_input)
-    try:
-        content = response["choices"][0]["message"]["content"]
-        history[-1] = construct_assistant(content)
-        chatbot[-1] = (chatbot[-1][0], content+display_append)
-        total_token_count = response["usage"]["total_tokens"]
-        if fake_input is not None:
-            all_token_counts[-1] += count_token(construct_assistant(content))
-        else:
-            all_token_counts[-1] = total_token_count - sum(all_token_counts)
-        status_text = construct_token_message(total_token_count)
-        return chatbot, history, status_text, all_token_counts
-    except KeyError:
-        status_text = standard_error_msg + str(response)
-        return chatbot, history, status_text, all_token_counts
-
-
-def predict(
-    openai_api_key,
-    system_prompt,
-    history,
-    inputs,
-    chatbot,
-    all_token_counts,
-    top_p,
-    temperature,
-    stream=False,
-    selected_model=MODELS[0],
-    use_websearch=False,
-    files = None,
-    reply_language="中文",
-    should_check_token_count=True,
-):  # repetition_penalty, top_k
-    from llama_index.indices.vector_store.base_query import GPTVectorStoreIndexQuery
-    from llama_index.indices.query.schema import QueryBundle
-    from langchain.llms import OpenAIChat
-
-
-    logging.info("输入为：" + colorama.Fore.BLUE + f"{inputs}" + colorama.Style.RESET_ALL)
-    if should_check_token_count:
-        yield chatbot+[(inputs, "")], history, "开始生成回答……", all_token_counts
-    if reply_language == "跟随问题语言（不稳定）":
-        reply_language = "the same language as the question, such as English, 中文, 日本語, Español, Français, or Deutsch."
-    old_inputs = None
-    display_reference = []
-    limited_context = False
-    if files:
-        limited_context = True
-        old_inputs = inputs
-        msg = "加载索引中……（这可能需要几分钟）"
-        logging.info(msg)
-        yield chatbot+[(inputs, "")], history, msg, all_token_counts
-        index = construct_index(openai_api_key, file_src=files)
-        msg = "索引构建完成，获取回答中……"
-        logging.info(msg)
-        yield chatbot+[(inputs, "")], history, msg, all_token_counts
-        with retrieve_proxy():
-            llm_predictor = LLMPredictor(llm=OpenAIChat(temperature=0, model_name=selected_model))
-            prompt_helper = PromptHelper(max_input_size = 4096, num_output = 5, max_chunk_overlap = 20, chunk_size_limit=600)
-            from llama_index import ServiceContext
-            service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper)
-            query_object = GPTVectorStoreIndexQuery(index.index_struct, service_context=service_context, similarity_top_k=5, vector_store=index._vector_store, docstore=index._docstore)
-            query_bundle = QueryBundle(inputs)
-            nodes = query_object.retrieve(query_bundle)
-        reference_results = [n.node.text for n in nodes]
-        reference_results = add_source_numbers(reference_results, use_source=False)
-        display_reference = add_details(reference_results)
-        display_reference = "\n\n" + "".join(display_reference)
-        inputs = (
-            replace_today(PROMPT_TEMPLATE)
-            .replace("{query_str}", inputs)
-            .replace("{context_str}", "\n\n".join(reference_results))
-            .replace("{reply_language}", reply_language )
-        )
-    elif use_websearch:
-        limited_context = True
-        search_results = ddg(inputs, max_results=5)
-        old_inputs = inputs
-        reference_results = []
-        for idx, result in enumerate(search_results):
-            logging.info(f"搜索结果{idx + 1}：{result}")
-            domain_name = urllib3.util.parse_url(result["href"]).host
-            reference_results.append([result["body"], result["href"]])
-            display_reference.append(f"{idx+1}. [{domain_name}]({result['href']})\n")
-        reference_results = add_source_numbers(reference_results)
-        display_reference = "\n\n" + "".join(display_reference)
-        inputs = (
-            replace_today(WEBSEARCH_PTOMPT_TEMPLATE)
-            .replace("{query}", inputs)
-            .replace("{web_results}", "\n\n".join(reference_results))
-            .replace("{reply_language}", reply_language )
-        )
-    else:
-        display_reference = ""
-
-    if len(openai_api_key) == 0 and not shared.state.multi_api_key:
-        status_text = standard_error_msg + no_apikey_msg
-        logging.info(status_text)
-        chatbot.append((inputs, ""))
-        if len(history) == 0:
-            history.append(construct_user(inputs))
-            history.append("")
-            all_token_counts.append(0)
-        else:
-            history[-2] = construct_user(inputs)
-        yield chatbot+[(inputs, "")], history, status_text, all_token_counts
-        return
-    elif len(inputs.strip()) == 0:
-        status_text = standard_error_msg + no_input_msg
-        logging.info(status_text)
-        yield chatbot+[(inputs, "")], history, status_text, all_token_counts
-        return
-
-    if stream:
-        logging.info("使用流式传输")
-        iter = stream_predict(
-            openai_api_key,
-            system_prompt,
-            history,
-            inputs,
-            chatbot,
-            all_token_counts,
-            top_p,
-            temperature,
-            selected_model,
-            fake_input=old_inputs,
-            display_append=display_reference
-        )
-        for chatbot, history, status_text, all_token_counts in iter:
-            if shared.state.interrupted:
-                shared.state.recover()
-                return
-            yield chatbot, history, status_text, all_token_counts
-    else:
-        logging.info("不使用流式传输")
-        chatbot, history, status_text, all_token_counts = predict_all(
-            openai_api_key,
-            system_prompt,
-            history,
-            inputs,
-            chatbot,
-            all_token_counts,
-            top_p,
-            temperature,
-            selected_model,
-            fake_input=old_inputs,
-            display_append=display_reference
-        )
-        yield chatbot, history, status_text, all_token_counts
-
-    logging.info(f"传输完毕。当前token计数为{all_token_counts}")
-    if len(history) > 1 and history[-1]["content"] != inputs:
-        logging.info(
-            "回答为："
-            + colorama.Fore.BLUE
-            + f"{history[-1]['content']}"
-            + colorama.Style.RESET_ALL
-        )
-
-    if limited_context:
-        history = history[-4:]
-        all_token_counts = all_token_counts[-2:]
-        yield chatbot, history, status_text, all_token_counts
-
-    if stream:
-        max_token = MODEL_SOFT_TOKEN_LIMIT[selected_model]["streaming"]
-    else:
-        max_token = MODEL_SOFT_TOKEN_LIMIT[selected_model]["all"]
-
-    if sum(all_token_counts) > max_token and should_check_token_count:
-        print(all_token_counts)
-        count = 0
-        while sum(all_token_counts) > max_token - 500 and sum(all_token_counts) > 0:
-            count += 1
-            del all_token_counts[0]
-            del history[:2]
-        logging.info(status_text)
-        status_text = f"为了防止token超限，模型忘记了早期的 {count} 轮对话"
-        yield chatbot, history, status_text, all_token_counts
-
-
-def retry(
-    openai_api_key,
-    system_prompt,
-    history,
-    chatbot,
-    token_count,
-    top_p,
-    temperature,
-    stream=False,
-    selected_model=MODELS[0],
-    reply_language="中文",
-):
-    logging.info("重试中……")
-    if len(history) == 0:
-        yield chatbot, history, f"{standard_error_msg}上下文是空的", token_count
-        return
-    history.pop()
-    inputs = history.pop()["content"]
-    token_count.pop()
-    iter = predict(
-        openai_api_key,
-        system_prompt,
-        history,
-        inputs,
-        chatbot,
-        token_count,
-        top_p,
-        temperature,
-        stream=stream,
-        selected_model=selected_model,
-        reply_language=reply_language,
-    )
-    logging.info("重试中……")
-    for x in iter:
-        yield x
-    logging.info("重试完毕")
-
-
-def reduce_token_size(
-    openai_api_key,
-    system_prompt,
-    history,
-    chatbot,
-    token_count,
-    top_p,
-    temperature,
-    max_token_count,
-    selected_model=MODELS[0],
-    reply_language="中文",
-):
-    logging.info("开始减少token数量……")
-    iter = predict(
-        openai_api_key,
-        system_prompt,
-        history,
-        summarize_prompt,
-        chatbot,
-        token_count,
-        top_p,
-        temperature,
-        selected_model=selected_model,
-        should_check_token_count=False,
-        reply_language=reply_language,
-    )
-    logging.info(f"chatbot: {chatbot}")
-    flag = False
-    for chatbot, history, status_text, previous_token_count in iter:
-        num_chat = find_n(previous_token_count, max_token_count)
-        logging.info(f"previous_token_count: {previous_token_count}, keeping {num_chat} chats")
-        if flag:
-            chatbot = chatbot[:-1]
-        flag = True
-        history = history[-2*num_chat:] if num_chat > 0 else []
-        token_count = previous_token_count[-num_chat:] if num_chat > 0 else []
-        msg = f"保留了最近{num_chat}轮对话"
-        yield chatbot, history, msg + "，" + construct_token_message(
-            token_count if len(token_count) > 0 else [0],
-        ), token_count
-    logging.info(msg)
-    logging.info("减少token数量完毕")
diff --git a/spaces/JohnSmith9982/ChuanhuChatGPT_Beta/modules/overwrites.py b/spaces/JohnSmith9982/ChuanhuChatGPT_Beta/modules/overwrites.py
deleted file mode 100644
index a4ef6167eb7ce75ed8b88024ad1187b24f2fc191..0000000000000000000000000000000000000000
--- a/spaces/JohnSmith9982/ChuanhuChatGPT_Beta/modules/overwrites.py
+++ /dev/null
@@ -1,106 +0,0 @@
-from __future__ import annotations
-import logging
-
-from typing import List, Tuple
-from gradio_client import utils as client_utils
-from gradio import utils
-import inspect
-
-from modules.presets import *
-from modules.index_func import *
-
-
-def postprocess(
-        self,
-        y: List[List[str | Tuple[str] | Tuple[str, str] | None] | Tuple],
-    ) -> List[List[str | Dict | None]]:
-        """
-        Parameters:
-            y: List of lists representing the message and response pairs. Each message and response should be a string, which may be in Markdown format.  It can also be a tuple whose first element is a string filepath or URL to an image/video/audio, and second (optional) element is the alt text, in which case the media file is displayed. It can also be None, in which case that message is not displayed.
-        Returns:
-            List of lists representing the message and response. Each message and response will be a string of HTML, or a dictionary with media information. Or None if the message is not to be displayed.
-        """
-        if y is None:
-            return []
-        processed_messages = []
-        for message_pair in y:
-            assert isinstance(
-                message_pair, (tuple, list)
-            ), f"Expected a list of lists or list of tuples. Received: {message_pair}"
-            assert (
-                len(message_pair) == 2
-            ), f"Expected a list of lists of length 2 or list of tuples of length 2. Received: {message_pair}"
-
-            processed_messages.append(
-                [
-                    self._postprocess_chat_messages(message_pair[0], "user"),
-                    self._postprocess_chat_messages(message_pair[1], "bot"),
-                ]
-            )
-        return processed_messages
-
-def postprocess_chat_messages(
-        self, chat_message: str | tuple | list | None, role: str
-    ) -> str | dict | None:
-        if chat_message is None:
-            return None
-        elif isinstance(chat_message, (tuple, list)):
-            file_uri = chat_message[0]
-            if utils.validate_url(file_uri):
-                filepath = file_uri
-            else:
-                filepath = self.make_temp_copy_if_needed(file_uri)
-
-            mime_type = client_utils.get_mimetype(filepath)
-            return {
-                "name": filepath,
-                "mime_type": mime_type,
-                "alt_text": chat_message[1] if len(chat_message) > 1 else None,
-                "data": None,  # These last two fields are filled in by the frontend
-                "is_file": True,
-            }
-        elif isinstance(chat_message, str):
-            # chat_message = inspect.cleandoc(chat_message)
-            # escape html spaces
-            # chat_message = chat_message.replace(" ", "&nbsp;")
-            if role == "bot":
-                chat_message = convert_bot_before_marked(chat_message)
-            elif role == "user":
-                chat_message = convert_user_before_marked(chat_message)
-            return chat_message
-        else:
-            raise ValueError(f"Invalid message for Chatbot component: {chat_message}")
-
-
-
-def add_classes_to_gradio_component(comp):
-    """
-    this adds gradio-* to the component for css styling (ie gradio-button to gr.Button), as well as some others
-    code from stable-diffusion-webui <AUTOMATIC1111/stable-diffusion-webui>
-    """
-
-    comp.elem_classes = [f"gradio-{comp.get_block_name()}", *(comp.elem_classes or [])]
-
-    if getattr(comp, 'multiselect', False):
-        comp.elem_classes.append('multiselect')
-
-
-def IOComponent_init(self, *args, **kwargs):
-    res = original_IOComponent_init(self, *args, **kwargs)
-    add_classes_to_gradio_component(self)
-
-    return res
-
-original_IOComponent_init = gr.components.IOComponent.__init__
-gr.components.IOComponent.__init__ = IOComponent_init
-
-
-def BlockContext_init(self, *args, **kwargs):
-    res = original_BlockContext_init(self, *args, **kwargs)
-    add_classes_to_gradio_component(self)
-
-    return res
-
-original_BlockContext_init = gr.blocks.BlockContext.__init__
-gr.blocks.BlockContext.__init__ = BlockContext_init
-
diff --git a/spaces/JunchuanYu/Sydney-AI/README.md b/spaces/JunchuanYu/Sydney-AI/README.md
deleted file mode 100644
index da224438be289e887e7e0c6ce434df5c6daa56e0..0000000000000000000000000000000000000000
--- a/spaces/JunchuanYu/Sydney-AI/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Sydney AI
-emoji: 🌖
-colorFrom: gray
-colorTo: blue
-sdk: gradio
-sdk_version: 3.19.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/KyanChen/RSPrompter/mmdet/models/roi_heads/roi_extractors/single_level_roi_extractor.py b/spaces/KyanChen/RSPrompter/mmdet/models/roi_heads/roi_extractors/single_level_roi_extractor.py
deleted file mode 100644
index 59229e0b0b0a18dff81abca6f5c20cb50b0d542c..0000000000000000000000000000000000000000
--- a/spaces/KyanChen/RSPrompter/mmdet/models/roi_heads/roi_extractors/single_level_roi_extractor.py
+++ /dev/null
@@ -1,119 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-from typing import List, Optional, Tuple
-
-import torch
-from torch import Tensor
-
-from mmdet.registry import MODELS
-from mmdet.utils import ConfigType, OptMultiConfig
-from .base_roi_extractor import BaseRoIExtractor
-
-
-@MODELS.register_module()
-class SingleRoIExtractor(BaseRoIExtractor):
-    """Extract RoI features from a single level feature map.
-
-    If there are multiple input feature levels, each RoI is mapped to a level
-    according to its scale. The mapping rule is proposed in
-    `FPN <https://arxiv.org/abs/1612.03144>`_.
-
-    Args:
-        roi_layer (:obj:`ConfigDict` or dict): Specify RoI layer type and
-            arguments.
-        out_channels (int): Output channels of RoI layers.
-        featmap_strides (List[int]): Strides of input feature maps.
-        finest_scale (int): Scale threshold of mapping to level 0.
-            Defaults to 56.
-        init_cfg (:obj:`ConfigDict` or dict or list[:obj:`ConfigDict` or \
-            dict], optional): Initialization config dict. Defaults to None.
-    """
-
-    def __init__(self,
-                 roi_layer: ConfigType,
-                 out_channels: int,
-                 featmap_strides: List[int],
-                 finest_scale: int = 56,
-                 init_cfg: OptMultiConfig = None) -> None:
-        super().__init__(
-            roi_layer=roi_layer,
-            out_channels=out_channels,
-            featmap_strides=featmap_strides,
-            init_cfg=init_cfg)
-        self.finest_scale = finest_scale
-
-    def map_roi_levels(self, rois: Tensor, num_levels: int) -> Tensor:
-        """Map rois to corresponding feature levels by scales.
-
-        - scale < finest_scale * 2: level 0
-        - finest_scale * 2 <= scale < finest_scale * 4: level 1
-        - finest_scale * 4 <= scale < finest_scale * 8: level 2
-        - scale >= finest_scale * 8: level 3
-
-        Args:
-            rois (Tensor): Input RoIs, shape (k, 5).
-            num_levels (int): Total level number.
-
-        Returns:
-            Tensor: Level index (0-based) of each RoI, shape (k, )
-        """
-        scale = torch.sqrt(
-            (rois[:, 3] - rois[:, 1]) * (rois[:, 4] - rois[:, 2]))
-        target_lvls = torch.floor(torch.log2(scale / self.finest_scale + 1e-6))
-        target_lvls = target_lvls.clamp(min=0, max=num_levels - 1).long()
-        return target_lvls
-
-    def forward(self,
-                feats: Tuple[Tensor],
-                rois: Tensor,
-                roi_scale_factor: Optional[float] = None):
-        """Extractor ROI feats.
-
-        Args:
-            feats (Tuple[Tensor]): Multi-scale features.
-            rois (Tensor): RoIs with the shape (n, 5) where the first
-                column indicates batch id of each RoI.
-            roi_scale_factor (Optional[float]): RoI scale factor.
-                Defaults to None.
-
-        Returns:
-            Tensor: RoI feature.
-        """
-        # convert fp32 to fp16 when amp is on
-        rois = rois.type_as(feats[0])
-        out_size = self.roi_layers[0].output_size
-        num_levels = len(feats)
-        roi_feats = feats[0].new_zeros(
-            rois.size(0), self.out_channels, *out_size)
-
-        # TODO: remove this when parrots supports
-        if torch.__version__ == 'parrots':
-            roi_feats.requires_grad = True
-
-        if num_levels == 1:
-            if len(rois) == 0:
-                return roi_feats
-            return self.roi_layers[0](feats[0], rois)
-
-        target_lvls = self.map_roi_levels(rois, num_levels)
-
-        if roi_scale_factor is not None:
-            rois = self.roi_rescale(rois, roi_scale_factor)
-
-        for i in range(num_levels):
-            mask = target_lvls == i
-            inds = mask.nonzero(as_tuple=False).squeeze(1)
-            if inds.numel() > 0:
-                rois_ = rois[inds]
-                roi_feats_t = self.roi_layers[i](feats[i], rois_)
-                roi_feats[inds] = roi_feats_t
-            else:
-                # Sometimes some pyramid levels will not be used for RoI
-                # feature extraction and this will cause an incomplete
-                # computation graph in one GPU, which is different from those
-                # in other GPUs and will cause a hanging error.
-                # Therefore, we add it to ensure each feature pyramid is
-                # included in the computation graph to avoid runtime bugs.
-                roi_feats += sum(
-                    x.view(-1)[0]
-                    for x in self.parameters()) * 0. + feats[i].sum() * 0.
-        return roi_feats
diff --git a/spaces/LINOlk/Akak/Dockerfile b/spaces/LINOlk/Akak/Dockerfile
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/Lamai/LAMAIGPT/autogpt/commands/analyze_code.py b/spaces/Lamai/LAMAIGPT/autogpt/commands/analyze_code.py
deleted file mode 100644
index e02ea4c5b4ba53530e559d1cab7a07b8e3c7c638..0000000000000000000000000000000000000000
--- a/spaces/Lamai/LAMAIGPT/autogpt/commands/analyze_code.py
+++ /dev/null
@@ -1,25 +0,0 @@
-"""Code evaluation module."""
-from __future__ import annotations
-
-from autogpt.llm_utils import call_ai_function
-
-
-def analyze_code(code: str) -> list[str]:
-    """
-    A function that takes in a string and returns a response from create chat
-      completion api call.
-
-    Parameters:
-        code (str): Code to be evaluated.
-    Returns:
-        A result string from create chat completion. A list of suggestions to
-            improve the code.
-    """
-
-    function_string = "def analyze_code(code: str) -> List[str]:"
-    args = [code]
-    description_string = (
-        "Analyzes the given code and returns a list of suggestions" " for improvements."
-    )
-
-    return call_ai_function(function_string, args, description_string)
diff --git a/spaces/Lbin123/Lbingo/src/components/voice.tsx b/spaces/Lbin123/Lbingo/src/components/voice.tsx
deleted file mode 100644
index 074d0e145229947282a472bd84f6578cf0b3c71c..0000000000000000000000000000000000000000
--- a/spaces/Lbin123/Lbingo/src/components/voice.tsx
+++ /dev/null
@@ -1,52 +0,0 @@
-import React, { useEffect } from 'react'
-import { useSetAtom } from 'jotai'
-import { useBing } from '@/lib/hooks/use-bing'
-import Image from 'next/image'
-import VoiceIcon from '@/assets/images/voice.svg'
-import VoiceButton from './ui/voice'
-import { SR } from '@/lib/bots/bing/sr'
-import { voiceListenAtom } from '@/state'
-
-const sr = new SR(['发送', '清空', '退出'])
-
-const Voice = ({ setInput, input, sendMessage, isSpeaking }: Pick<ReturnType<typeof useBing>, 'setInput' | 'sendMessage' | 'input' | 'isSpeaking'>) => {
-  const setListen = useSetAtom(voiceListenAtom)
-  useEffect(() => {
-    if (sr.listening) return
-    sr.transcript = !isSpeaking
-  }, [isSpeaking])
-
-  useEffect(() => {
-    sr.onchange = (msg: string, command?: string) => {
-      switch (command) {
-        case '退出':
-          sr.stop()
-          break;
-        case '发送':
-          sendMessage(input)
-        case '清空':
-          setInput('')
-          break;
-        default:
-          setInput(input + msg)
-      }
-    }
-  }, [input])
-
-  const switchSR = (enable: boolean = false) => {
-    setListen(enable)
-    if (enable) {
-      sr.start()
-    } else {
-      sr.stop()
-    }
-  }
-
-  return sr.listening ? (
-    <VoiceButton onClick={() => switchSR(false)} />
-  ) : (
-    <Image alt="start voice" src={VoiceIcon} width={24} className="-mt-0.5" onClick={() => switchSR(true)} />
-  )
-};
-
-export default Voice;
diff --git a/spaces/Lewislou/Lewislou-cell-seg-sribd/sribd_cellseg_models.py b/spaces/Lewislou/Lewislou-cell-seg-sribd/sribd_cellseg_models.py
deleted file mode 100644
index 9c65523b2963a877e578cf49612a3eba194c05f3..0000000000000000000000000000000000000000
--- a/spaces/Lewislou/Lewislou-cell-seg-sribd/sribd_cellseg_models.py
+++ /dev/null
@@ -1,100 +0,0 @@
-
-import os
-join = os.path.join
-import argparse
-import numpy as np
-import torch
-import torch.nn as nn
-from collections import OrderedDict
-from torchvision import datasets, models, transforms
-from classifiers import resnet10, resnet18
-
-from utils_modify import sliding_window_inference,sliding_window_inference_large,__proc_np_hv
-from PIL import Image
-import torch.nn.functional as F
-from skimage import io, segmentation, morphology, measure, exposure
-import tifffile as tif
-from models.flexible_unet_convnext import FlexibleUNet_star,FlexibleUNet_hv 
-from transformers import PretrainedConfig
-from typing import List
-from transformers import PreTrainedModel
-from huggingface_hub import PyTorchModelHubMixin
-from torch import nn
-class ModelConfig(PretrainedConfig):
-    model_type = "cell_sribd"
-    def __init__(
-        self,
-        version = 1,
-        input_channels: int = 3,
-        roi_size: int = 512,
-        overlap: float = 0.5,
-        device: str = 'cpu',
-        **kwargs,
-    ):
-        
-        self.device = device
-        self.roi_size = (roi_size, roi_size)
-        self.input_channels = input_channels
-        self.overlap = overlap
-        self.np_thres, self.ksize, self.overall_thres, self.obj_size_thres = 0.6, 15, 0.4, 100
-        self.n_rays = 32
-        self.sw_batch_size = 4
-        self.num_classes= 4
-        self.block_size = 2048
-        self.min_overlap = 128
-        self.context = 128
-        super().__init__(**kwargs)
-        
-        
-class MultiStreamCellSegModel(PreTrainedModel):
-    config_class = ModelConfig
-    #print(config.input_channels)
-    def __init__(self, config):
-        super().__init__(config)
-        #print(config.input_channels)
-        self.config = config
-        self.cls_model = resnet18()
-        self.model0 = FlexibleUNet_star(in_channels=config.input_channels,out_channels=config.n_rays+1,backbone='convnext_small',pretrained=False,n_rays=config.n_rays,prob_out_channels=1,)
-        self.model1 = FlexibleUNet_star(in_channels=config.input_channels,out_channels=config.n_rays+1,backbone='convnext_small',pretrained=False,n_rays=config.n_rays,prob_out_channels=1,)
-        self.model2 = FlexibleUNet_star(in_channels=config.input_channels,out_channels=config.n_rays+1,backbone='convnext_small',pretrained=False,n_rays=config.n_rays,prob_out_channels=1,)
-        self.model3 = FlexibleUNet_hv(in_channels=config.input_channels,out_channels=2+2,backbone='convnext_small',pretrained=False,n_rays=2,prob_out_channels=2,)
-        self.preprocess=transforms.Compose([
-            transforms.Resize(size=256),
-            transforms.CenterCrop(size=224),
-            transforms.ToTensor(),
-            transforms.Normalize([0.485, 0.456, 0.406],[0.229, 0.224, 0.225])])
-    def load_checkpoints(self,checkpoints):
-        self.cls_model.load_state_dict(checkpoints['cls_model'])
-        self.model0.load_state_dict(checkpoints['class1_model']['model_state_dict'])
-        self.model1.load_state_dict(checkpoints['class2_model']['model_state_dict'])
-        self.model2.load_state_dict(checkpoints['class3_model']['model_state_dict'])
-        self.model3.load_state_dict(checkpoints['class4_model'])
-        
-    def forward(self, pre_img_data):
-        inputs=self.preprocess(Image.fromarray(pre_img_data)).unsqueeze(0)
-        outputs = self.cls_model(inputs)
-        _, preds = torch.max(outputs, 1)    
-        label=preds[0].cpu().numpy()
-        test_npy01 = pre_img_data
-        if label in [0,1,2]:
-            if label == 0:
-                output_label = sliding_window_inference_large(test_npy01,self.config.block_size,self.config.min_overlap,self.config.context, self.config.roi_size,self.config.sw_batch_size,predictor=self.model0,device=self.config.device)
-            elif label == 1:
-                output_label = sliding_window_inference_large(test_npy01,self.config.block_size,self.config.min_overlap,self.config.context, self.config.roi_size,self.config.sw_batch_size,predictor=self.model1,device=self.config.device)
-            elif label == 2:
-                output_label = sliding_window_inference_large(test_npy01,self.config.block_size,self.config.min_overlap,self.config.context, self.config.roi_size,self.config.sw_batch_size,predictor=self.model2,device=self.config.device)
-        else:
-            test_tensor = torch.from_numpy(np.expand_dims(test_npy01, 0)).permute(0, 3, 1, 2).type(torch.FloatTensor)
-
-            output_hv, output_np = sliding_window_inference(test_tensor, self.config.roi, self.config.sw_batch_size, self.model3, overlap=self.config.overlap,device=self.config.device)
-            pred_dict = {'np': output_np, 'hv': output_hv}
-            pred_dict = OrderedDict(
-                    [[k, v.permute(0, 2, 3, 1).contiguous()] for k, v in pred_dict.items()]  # NHWC
-                )
-            pred_dict["np"] = F.softmax(pred_dict["np"], dim=-1)[..., 1:]
-            pred_output = torch.cat(list(pred_dict.values()), -1).cpu().numpy() # NHW3
-            pred_map = np.squeeze(pred_output) # HW3
-            pred_inst = __proc_np_hv(pred_map, self.config.np_thres, self.config.ksize, self.config.overall_thres, self.config.obj_size_thres)
-            raw_pred_shape = pred_inst.shape[:2]
-            output_label = pred_inst
-        return output_label       
diff --git a/spaces/LinkSoul/Chinese-LLaVa/static/js/bulma-slider.min.js b/spaces/LinkSoul/Chinese-LLaVa/static/js/bulma-slider.min.js
deleted file mode 100644
index 7e62685763cf7668cfa8857fac0b27af2c277286..0000000000000000000000000000000000000000
--- a/spaces/LinkSoul/Chinese-LLaVa/static/js/bulma-slider.min.js
+++ /dev/null
@@ -1 +0,0 @@
-!function(t,e){"object"==typeof exports&&"object"==typeof module?module.exports=e():"function"==typeof define&&define.amd?define([],e):"object"==typeof exports?exports.bulmaSlider=e():t.bulmaSlider=e()}("undefined"!=typeof self?self:this,function(){return function(n){var r={};function i(t){if(r[t])return r[t].exports;var e=r[t]={i:t,l:!1,exports:{}};return n[t].call(e.exports,e,e.exports,i),e.l=!0,e.exports}return i.m=n,i.c=r,i.d=function(t,e,n){i.o(t,e)||Object.defineProperty(t,e,{configurable:!1,enumerable:!0,get:n})},i.n=function(t){var e=t&&t.__esModule?function(){return t.default}:function(){return t};return i.d(e,"a",e),e},i.o=function(t,e){return Object.prototype.hasOwnProperty.call(t,e)},i.p="",i(i.s=0)}([function(t,e,n){"use strict";Object.defineProperty(e,"__esModule",{value:!0}),n.d(e,"isString",function(){return l});var r=n(1),i=Object.assign||function(t){for(var e=1;e<arguments.length;e++){var n=arguments[e];for(var r in 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diff --git a/spaces/LunchWithaLens/whichraptor/README.md b/spaces/LunchWithaLens/whichraptor/README.md
deleted file mode 100644
index 9591597eb64b616599773980970a723223da72cd..0000000000000000000000000000000000000000
--- a/spaces/LunchWithaLens/whichraptor/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Whichraptor
-emoji: 🐢
-colorFrom: green
-colorTo: purple
-sdk: gradio
-sdk_version: 2.9.4
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference
diff --git a/spaces/Manjushri/SDXL-1.0/app.py b/spaces/Manjushri/SDXL-1.0/app.py
deleted file mode 100644
index 47fa2ca2957b23a49396e71318fb4be7a02e5e28..0000000000000000000000000000000000000000
--- a/spaces/Manjushri/SDXL-1.0/app.py
+++ /dev/null
@@ -1,65 +0,0 @@
-import gradio as gr
-import torch
-import numpy as np
-import modin.pandas as pd
-from PIL import Image
-from diffusers import DiffusionPipeline 
-
-device = 'cuda' if torch.cuda.is_available() else 'cpu'
-
-if torch.cuda.is_available():
-    PYTORCH_CUDA_ALLOC_CONF={'max_split_size_mb': 8000}
-    torch.cuda.max_memory_allocated(device=device)
-    torch.cuda.empty_cache()
-    
-    pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
-    pipe.enable_xformers_memory_efficient_attention()
-    pipe = pipe.to(device)
-    torch.cuda.empty_cache()
-    
-    refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", use_safetensors=True, torch_dtype=torch.float16, variant="fp16")
-    refiner.enable_xformers_memory_efficient_attention()
-    refiner = refiner.to(device)
-    torch.cuda.empty_cache()
-    
-    upscaler = DiffusionPipeline.from_pretrained("stabilityai/sd-x2-latent-upscaler", torch_dtype=torch.float16, use_safetensors=True)
-    upscaler.enable_xformers_memory_efficient_attention()
-    upscaler = upscaler.to(device)
-    torch.cuda.empty_cache()
-else: 
-    pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", use_safetensors=True)
-    pipe = pipe.to(device)
-    pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
-    refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", use_safetensors=True)
-    refiner = refiner.to(device)
-    refiner.unet = torch.compile(refiner.unet, mode="reduce-overhead", fullgraph=True)
-      
-def genie (prompt, negative_prompt, height, width, scale, steps, seed, upscaling, prompt_2, negative_prompt_2, high_noise_frac, n_steps):
-    generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed)
-    int_image = pipe(prompt, prompt_2=prompt_2, negative_prompt=negative_prompt, negative_prompt_2=negative_prompt_2, num_inference_steps=steps, height=height, width=width, guidance_scale=scale, num_images_per_prompt=1, generator=generator, output_type="latent").images
-    if upscaling == 'Yes':
-        image = refiner(prompt=prompt, prompt_2=prompt_2, negative_prompt=negative_prompt, negative_prompt_2=negative_prompt_2, image=int_image, num_inference_steps=n_steps, denoising_start=high_noise_frac).images[0] #num_inference_steps=n_steps,
-        upscaled = upscaler(prompt=prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=5, guidance_scale=0).images[0]
-        torch.cuda.empty_cache()
-        return (image, upscaled)
-    else:
-        image = refiner(prompt=prompt, prompt_2=prompt_2, negative_prompt=negative_prompt, negative_prompt_2=negative_prompt_2, image=int_image, num_inference_steps=n_steps ,denoising_start=high_noise_frac).images[0]   
-        torch.cuda.empty_cache()
-    return (image, image)
-
-gr.Interface(fn=genie, inputs=[gr.Textbox(label='What you want the AI to generate. 77 Token Limit. A Token is Any Word, Number, Symbol, or Punctuation. Everything Over 77 Will Be Truncated!'), 
-    gr.Textbox(label='What you Do Not want the AI to generate. 77 Token Limit'), 
-    gr.Slider(512, 1024, 768, step=128, label='Height'),
-    gr.Slider(512, 1024, 768, step=128, label='Width'),
-    gr.Slider(1, 15, 10, step=.25, label='Guidance Scale: How Closely the AI follows the Prompt'), 
-    gr.Slider(25, maximum=100, value=50, step=25, label='Number of Iterations'), 
-    gr.Slider(minimum=0, step=1, maximum=999999999999999999, randomize=True, label='Seed: 0 is Random'),
-    gr.Radio(['Yes', 'No'], value='No', label='Upscale?'),
-    gr.Textbox(label='Embedded Prompt'),
-    gr.Textbox(label='Embedded Negative Prompt'),
-    gr.Slider(minimum=.7, maximum=.99, value=.95, step=.01, label='Refiner Denoise Start %'),
-    gr.Slider(minimum=1, maximum=100, value=100, step=1, label='Refiner Number of Iterations %')], 
-    outputs=['image', 'image'],
-    title="Stable Diffusion XL 1.0 GPU", 
-    description="SDXL 1.0 GPU. <br><br><b>WARNING: Capable of producing NSFW (Softcore) images.</b>", 
-    article = "If You Enjoyed this Demo and would like to Donate, you can send to any of these Wallets. <br>BTC: bc1qzdm9j73mj8ucwwtsjx4x4ylyfvr6kp7svzjn84 <br>3LWRoKYx6bCLnUrKEdnPo3FCSPQUSFDjFP <br>DOGE: DK6LRc4gfefdCTRk9xPD239N31jh9GjKez <br>SHIB (BEP20): 0xbE8f2f3B71DFEB84E5F7E3aae1909d60658aB891 <br>PayPal: https://www.paypal.me/ManjushriBodhisattva <br>ETH: 0xbE8f2f3B71DFEB84E5F7E3aae1909d60658aB891 <br>Code Monkey: <a href=\"https://huggingface.co/Manjushri\">Manjushri</a>").launch(debug=True, max_threads=80)
diff --git a/spaces/Matthijs/mms-tts-demo/app.py b/spaces/Matthijs/mms-tts-demo/app.py
deleted file mode 100644
index 7ab5fd34984c3f1222e6215518b45b37144dff04..0000000000000000000000000000000000000000
--- a/spaces/Matthijs/mms-tts-demo/app.py
+++ /dev/null
@@ -1,140 +0,0 @@
-import gradio as gr
-import numpy as np
-import torch
-import os
-import re
-import tempfile
-
-from transformers import VitsModel, VitsTokenizer
-
-
-models = {
-    "English": VitsModel.from_pretrained("Matthijs/mms-tts-eng"),
-    "German": VitsModel.from_pretrained("Matthijs/mms-tts-deu"),
-    "Korean": VitsModel.from_pretrained("Matthijs/mms-tts-kor"),
-}
-
-tokenizers = {
-    "English": VitsTokenizer.from_pretrained("Matthijs/mms-tts-eng"),
-    "German": VitsTokenizer.from_pretrained("Matthijs/mms-tts-deu"),
-    "Korean": VitsTokenizer.from_pretrained("Matthijs/mms-tts-kor"),
-}
-
-
-# For certain checkpoints, the text needs to be romanized.
-# MMS-TTS uses uromanize.pl for this from https://github.com/isi-nlp/uroman
-# This needs to be installed in the folder "uroman"
-def uromanize(text, uroman_pl):
-    iso = "xxx"
-    with tempfile.NamedTemporaryFile() as tf, tempfile.NamedTemporaryFile() as tf2:
-        with open(tf.name, "w") as f:
-            f.write("\n".join([text]))
-        cmd = f"perl " + uroman_pl
-        cmd += f" -l {iso} "
-        cmd += f" < {tf.name} > {tf2.name}"
-        os.system(cmd)
-        outtexts = []
-        with open(tf2.name) as f:
-            for line in f:
-                line = re.sub(r"\s+", " ", line).strip()
-                outtexts.append(line)
-        outtext = outtexts[0]
-    return outtext
-
-
-def predict(text, language=None):
-    if len(text.strip()) == 0:
-        return (16000, np.zeros(0).astype(np.int16))
-
-    if language == "Korean":
-        uroman_pl = os.path.join("uroman", "bin", "uroman.pl")
-        text = uromanize(text, uroman_pl)
-
-    tokenizer = tokenizers[language]
-    inputs = tokenizer(text, return_tensors="pt")
-    input_ids = inputs["input_ids"]
-
-    if language != "Korean":
-        text = tokenizer.batch_decode(input_ids)[0]
-
-    model = models[language]
-    with torch.no_grad():
-        outputs = model(input_ids)
-
-    speech = outputs.audio[0]
-    speech = (speech.numpy() * 32767).astype(np.int16)
-    return (16000, speech), text
-
-
-title = "MMS-TTS speech synthesis"
-
-description = """
-Facebook's [Massively Multilingual Speech](https://arxiv.org/abs/2305.13516) project aims to provide
-speech technology across a diverse range of languages. The MMS-TTS project contains a collection of
-over 1000 text-to-speech (TTS) models.
-
-This demo shows how to use MMS-TTS using 🤗 Transformers. Since MMS-TTS is based on the VITS
-model, this code can also be used to run VITS checkpoints.
-For a full list of checkpoints, [click here](https://huggingface.co/models?filter=vits).
-
-As the model performs random sampling, the generated speech is slightly different each time.
-The voice may also vary between runs, or sometimes even in the same sentence.
-(Note that 🤗 Transformers also supports multispeaker VITS checkpoints but the MMS-TTS checkpoints
-are not conditioned on a speaker ID.)
-"""
-
-article = """
-<div style='margin:20px auto;'>
-
-<p>References: <a href="https://arxiv.org/abs/2305.13516">MMS paper</a> |
-<a href="https://ai.facebook.com/blog/multilingual-model-speech-recognition/">blog post</a> |
-<a href="https://huggingface.co/facebook/mms-tts">original weights</a> |
-<a href="https://huggingface.co/spaces/mms-meta/MMS">original MMS space</a>
-</p>
-
-<pre>
-@article{pratap2023mms,
-  title={Scaling Speech Technology to 1,000+ Languages},
-  author={Vineel Pratap and Andros Tjandra and Bowen Shi and Paden Tomasello and Arun Babu and Sayani Kundu and Ali Elkahky and Zhaoheng Ni and Apoorv Vyas and Maryam Fazel-Zarandi and Alexei Baevski and Yossi Adi and Xiaohui Zhang and Wei-Ning Hsu and Alexis Conneau and Michael Auli},
-  journal={arXiv},
-  year={2023}
-}
-</pre>
-
-</div>
-"""
-
-examples = [
-    ["It is not in the stars to hold our destiny but in ourselves.", "English"],
-    ["The octopus and Oliver went to the opera in October.", "English"],
-    ["She sells seashells by the seashore. I saw a kitten eating chicken in the kitchen.", "English"],
-    ["Brisk brave brigadiers brandished broad bright blades, blunderbusses, and bludgeons—balancing them badly.", "English"],
-    ["A synonym for cinnamon is a cinnamon synonym.", "English"],
-    ["How much wood would a woodchuck chuck if a woodchuck could chuck wood?", "English"],
-
-    ["Eins, zwei, Polizei. Drei, vier, Grenadier. Fünf, sechs, alte Keks. Sieben, acht, gute Nacht.", "German"],
-    ["Alle meine Entchen, schwimmen auf dem See. Köpfchen in das Wasser, Schwänzchen in die Höh.", "German"],
-
-    ["안녕 세상, 날씨는 아름다워", "Korean"],  # Hello world, the weather is beautiful (Google Translate)
-]
-
-gr.Interface(
-    fn=predict,
-    inputs=[
-        gr.Text(label="Input Text"),
-        gr.Radio(label="Language", choices=[
-            "English",
-            "German",
-            "Korean",
-        ],
-        value="English"),
-    ],
-    outputs=[
-        gr.Audio(label="Generated Speech", type="numpy"),
-        gr.Text(label="Processed text"),
-    ],
-    title=title,
-    description=description,
-    article=article,
-    examples=examples,
-).launch()
diff --git a/spaces/Mellow-ai/PhotoAI_Mellow/annotator/uniformer/configs/_base_/models/ccnet_r50-d8.py b/spaces/Mellow-ai/PhotoAI_Mellow/annotator/uniformer/configs/_base_/models/ccnet_r50-d8.py
deleted file mode 100644
index 794148f576b9e215c3c6963e73dffe98204b7717..0000000000000000000000000000000000000000
--- a/spaces/Mellow-ai/PhotoAI_Mellow/annotator/uniformer/configs/_base_/models/ccnet_r50-d8.py
+++ /dev/null
@@ -1,44 +0,0 @@
-# model settings
-norm_cfg = dict(type='SyncBN', requires_grad=True)
-model = dict(
-    type='EncoderDecoder',
-    pretrained='open-mmlab://resnet50_v1c',
-    backbone=dict(
-        type='ResNetV1c',
-        depth=50,
-        num_stages=4,
-        out_indices=(0, 1, 2, 3),
-        dilations=(1, 1, 2, 4),
-        strides=(1, 2, 1, 1),
-        norm_cfg=norm_cfg,
-        norm_eval=False,
-        style='pytorch',
-        contract_dilation=True),
-    decode_head=dict(
-        type='CCHead',
-        in_channels=2048,
-        in_index=3,
-        channels=512,
-        recurrence=2,
-        dropout_ratio=0.1,
-        num_classes=19,
-        norm_cfg=norm_cfg,
-        align_corners=False,
-        loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
-    auxiliary_head=dict(
-        type='FCNHead',
-        in_channels=1024,
-        in_index=2,
-        channels=256,
-        num_convs=1,
-        concat_input=False,
-        dropout_ratio=0.1,
-        num_classes=19,
-        norm_cfg=norm_cfg,
-        align_corners=False,
-        loss_decode=dict(
-            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
-    # model training and testing settings
-    train_cfg=dict(),
-    test_cfg=dict(mode='whole'))
diff --git a/spaces/Mellow-ai/PhotoAI_Mellow/annotator/uniformer/mmcv/ops/nms.py b/spaces/Mellow-ai/PhotoAI_Mellow/annotator/uniformer/mmcv/ops/nms.py
deleted file mode 100644
index 6d9634281f486ab284091786886854c451368052..0000000000000000000000000000000000000000
--- a/spaces/Mellow-ai/PhotoAI_Mellow/annotator/uniformer/mmcv/ops/nms.py
+++ /dev/null
@@ -1,417 +0,0 @@
-import os
-
-import numpy as np
-import torch
-
-from annotator.uniformer.mmcv.utils import deprecated_api_warning
-from ..utils import ext_loader
-
-ext_module = ext_loader.load_ext(
-    '_ext', ['nms', 'softnms', 'nms_match', 'nms_rotated'])
-
-
-# This function is modified from: https://github.com/pytorch/vision/
-class NMSop(torch.autograd.Function):
-
-    @staticmethod
-    def forward(ctx, bboxes, scores, iou_threshold, offset, score_threshold,
-                max_num):
-        is_filtering_by_score = score_threshold > 0
-        if is_filtering_by_score:
-            valid_mask = scores > score_threshold
-            bboxes, scores = bboxes[valid_mask], scores[valid_mask]
-            valid_inds = torch.nonzero(
-                valid_mask, as_tuple=False).squeeze(dim=1)
-
-        inds = ext_module.nms(
-            bboxes, scores, iou_threshold=float(iou_threshold), offset=offset)
-
-        if max_num > 0:
-            inds = inds[:max_num]
-        if is_filtering_by_score:
-            inds = valid_inds[inds]
-        return inds
-
-    @staticmethod
-    def symbolic(g, bboxes, scores, iou_threshold, offset, score_threshold,
-                 max_num):
-        from ..onnx import is_custom_op_loaded
-        has_custom_op = is_custom_op_loaded()
-        # TensorRT nms plugin is aligned with original nms in ONNXRuntime
-        is_trt_backend = os.environ.get('ONNX_BACKEND') == 'MMCVTensorRT'
-        if has_custom_op and (not is_trt_backend):
-            return g.op(
-                'mmcv::NonMaxSuppression',
-                bboxes,
-                scores,
-                iou_threshold_f=float(iou_threshold),
-                offset_i=int(offset))
-        else:
-            from torch.onnx.symbolic_opset9 import select, squeeze, unsqueeze
-            from ..onnx.onnx_utils.symbolic_helper import _size_helper
-
-            boxes = unsqueeze(g, bboxes, 0)
-            scores = unsqueeze(g, unsqueeze(g, scores, 0), 0)
-
-            if max_num > 0:
-                max_num = g.op(
-                    'Constant',
-                    value_t=torch.tensor(max_num, dtype=torch.long))
-            else:
-                dim = g.op('Constant', value_t=torch.tensor(0))
-                max_num = _size_helper(g, bboxes, dim)
-            max_output_per_class = max_num
-            iou_threshold = g.op(
-                'Constant',
-                value_t=torch.tensor([iou_threshold], dtype=torch.float))
-            score_threshold = g.op(
-                'Constant',
-                value_t=torch.tensor([score_threshold], dtype=torch.float))
-            nms_out = g.op('NonMaxSuppression', boxes, scores,
-                           max_output_per_class, iou_threshold,
-                           score_threshold)
-            return squeeze(
-                g,
-                select(
-                    g, nms_out, 1,
-                    g.op(
-                        'Constant',
-                        value_t=torch.tensor([2], dtype=torch.long))), 1)
-
-
-class SoftNMSop(torch.autograd.Function):
-
-    @staticmethod
-    def forward(ctx, boxes, scores, iou_threshold, sigma, min_score, method,
-                offset):
-        dets = boxes.new_empty((boxes.size(0), 5), device='cpu')
-        inds = ext_module.softnms(
-            boxes.cpu(),
-            scores.cpu(),
-            dets.cpu(),
-            iou_threshold=float(iou_threshold),
-            sigma=float(sigma),
-            min_score=float(min_score),
-            method=int(method),
-            offset=int(offset))
-        return dets, inds
-
-    @staticmethod
-    def symbolic(g, boxes, scores, iou_threshold, sigma, min_score, method,
-                 offset):
-        from packaging import version
-        assert version.parse(torch.__version__) >= version.parse('1.7.0')
-        nms_out = g.op(
-            'mmcv::SoftNonMaxSuppression',
-            boxes,
-            scores,
-            iou_threshold_f=float(iou_threshold),
-            sigma_f=float(sigma),
-            min_score_f=float(min_score),
-            method_i=int(method),
-            offset_i=int(offset),
-            outputs=2)
-        return nms_out
-
-
-@deprecated_api_warning({'iou_thr': 'iou_threshold'})
-def nms(boxes, scores, iou_threshold, offset=0, score_threshold=0, max_num=-1):
-    """Dispatch to either CPU or GPU NMS implementations.
-
-    The input can be either torch tensor or numpy array. GPU NMS will be used
-    if the input is gpu tensor, otherwise CPU NMS
-    will be used. The returned type will always be the same as inputs.
-
-    Arguments:
-        boxes (torch.Tensor or np.ndarray): boxes in shape (N, 4).
-        scores (torch.Tensor or np.ndarray): scores in shape (N, ).
-        iou_threshold (float): IoU threshold for NMS.
-        offset (int, 0 or 1): boxes' width or height is (x2 - x1 + offset).
-        score_threshold (float): score threshold for NMS.
-        max_num (int): maximum number of boxes after NMS.
-
-    Returns:
-        tuple: kept dets(boxes and scores) and indice, which is always the \
-            same data type as the input.
-
-    Example:
-        >>> boxes = np.array([[49.1, 32.4, 51.0, 35.9],
-        >>>                   [49.3, 32.9, 51.0, 35.3],
-        >>>                   [49.2, 31.8, 51.0, 35.4],
-        >>>                   [35.1, 11.5, 39.1, 15.7],
-        >>>                   [35.6, 11.8, 39.3, 14.2],
-        >>>                   [35.3, 11.5, 39.9, 14.5],
-        >>>                   [35.2, 11.7, 39.7, 15.7]], dtype=np.float32)
-        >>> scores = np.array([0.9, 0.9, 0.5, 0.5, 0.5, 0.4, 0.3],\
-               dtype=np.float32)
-        >>> iou_threshold = 0.6
-        >>> dets, inds = nms(boxes, scores, iou_threshold)
-        >>> assert len(inds) == len(dets) == 3
-    """
-    assert isinstance(boxes, (torch.Tensor, np.ndarray))
-    assert isinstance(scores, (torch.Tensor, np.ndarray))
-    is_numpy = False
-    if isinstance(boxes, np.ndarray):
-        is_numpy = True
-        boxes = torch.from_numpy(boxes)
-    if isinstance(scores, np.ndarray):
-        scores = torch.from_numpy(scores)
-    assert boxes.size(1) == 4
-    assert boxes.size(0) == scores.size(0)
-    assert offset in (0, 1)
-
-    if torch.__version__ == 'parrots':
-        indata_list = [boxes, scores]
-        indata_dict = {
-            'iou_threshold': float(iou_threshold),
-            'offset': int(offset)
-        }
-        inds = ext_module.nms(*indata_list, **indata_dict)
-    else:
-        inds = NMSop.apply(boxes, scores, iou_threshold, offset,
-                           score_threshold, max_num)
-    dets = torch.cat((boxes[inds], scores[inds].reshape(-1, 1)), dim=1)
-    if is_numpy:
-        dets = dets.cpu().numpy()
-        inds = inds.cpu().numpy()
-    return dets, inds
-
-
-@deprecated_api_warning({'iou_thr': 'iou_threshold'})
-def soft_nms(boxes,
-             scores,
-             iou_threshold=0.3,
-             sigma=0.5,
-             min_score=1e-3,
-             method='linear',
-             offset=0):
-    """Dispatch to only CPU Soft NMS implementations.
-
-    The input can be either a torch tensor or numpy array.
-    The returned type will always be the same as inputs.
-
-    Arguments:
-        boxes (torch.Tensor or np.ndarray): boxes in shape (N, 4).
-        scores (torch.Tensor or np.ndarray): scores in shape (N, ).
-        iou_threshold (float): IoU threshold for NMS.
-        sigma (float): hyperparameter for gaussian method
-        min_score (float): score filter threshold
-        method (str): either 'linear' or 'gaussian'
-        offset (int, 0 or 1): boxes' width or height is (x2 - x1 + offset).
-
-    Returns:
-        tuple: kept dets(boxes and scores) and indice, which is always the \
-            same data type as the input.
-
-    Example:
-        >>> boxes = np.array([[4., 3., 5., 3.],
-        >>>                   [4., 3., 5., 4.],
-        >>>                   [3., 1., 3., 1.],
-        >>>                   [3., 1., 3., 1.],
-        >>>                   [3., 1., 3., 1.],
-        >>>                   [3., 1., 3., 1.]], dtype=np.float32)
-        >>> scores = np.array([0.9, 0.9, 0.5, 0.5, 0.4, 0.0], dtype=np.float32)
-        >>> iou_threshold = 0.6
-        >>> dets, inds = soft_nms(boxes, scores, iou_threshold, sigma=0.5)
-        >>> assert len(inds) == len(dets) == 5
-    """
-
-    assert isinstance(boxes, (torch.Tensor, np.ndarray))
-    assert isinstance(scores, (torch.Tensor, np.ndarray))
-    is_numpy = False
-    if isinstance(boxes, np.ndarray):
-        is_numpy = True
-        boxes = torch.from_numpy(boxes)
-    if isinstance(scores, np.ndarray):
-        scores = torch.from_numpy(scores)
-    assert boxes.size(1) == 4
-    assert boxes.size(0) == scores.size(0)
-    assert offset in (0, 1)
-    method_dict = {'naive': 0, 'linear': 1, 'gaussian': 2}
-    assert method in method_dict.keys()
-
-    if torch.__version__ == 'parrots':
-        dets = boxes.new_empty((boxes.size(0), 5), device='cpu')
-        indata_list = [boxes.cpu(), scores.cpu(), dets.cpu()]
-        indata_dict = {
-            'iou_threshold': float(iou_threshold),
-            'sigma': float(sigma),
-            'min_score': min_score,
-            'method': method_dict[method],
-            'offset': int(offset)
-        }
-        inds = ext_module.softnms(*indata_list, **indata_dict)
-    else:
-        dets, inds = SoftNMSop.apply(boxes.cpu(), scores.cpu(),
-                                     float(iou_threshold), float(sigma),
-                                     float(min_score), method_dict[method],
-                                     int(offset))
-
-    dets = dets[:inds.size(0)]
-
-    if is_numpy:
-        dets = dets.cpu().numpy()
-        inds = inds.cpu().numpy()
-        return dets, inds
-    else:
-        return dets.to(device=boxes.device), inds.to(device=boxes.device)
-
-
-def batched_nms(boxes, scores, idxs, nms_cfg, class_agnostic=False):
-    """Performs non-maximum suppression in a batched fashion.
-
-    Modified from https://github.com/pytorch/vision/blob
-    /505cd6957711af790211896d32b40291bea1bc21/torchvision/ops/boxes.py#L39.
-    In order to perform NMS independently per class, we add an offset to all
-    the boxes. The offset is dependent only on the class idx, and is large
-    enough so that boxes from different classes do not overlap.
-
-    Arguments:
-        boxes (torch.Tensor): boxes in shape (N, 4).
-        scores (torch.Tensor): scores in shape (N, ).
-        idxs (torch.Tensor): each index value correspond to a bbox cluster,
-            and NMS will not be applied between elements of different idxs,
-            shape (N, ).
-        nms_cfg (dict): specify nms type and other parameters like iou_thr.
-            Possible keys includes the following.
-
-            - iou_thr (float): IoU threshold used for NMS.
-            - split_thr (float): threshold number of boxes. In some cases the
-                number of boxes is large (e.g., 200k). To avoid OOM during
-                training, the users could set `split_thr` to a small value.
-                If the number of boxes is greater than the threshold, it will
-                perform NMS on each group of boxes separately and sequentially.
-                Defaults to 10000.
-        class_agnostic (bool): if true, nms is class agnostic,
-            i.e. IoU thresholding happens over all boxes,
-            regardless of the predicted class.
-
-    Returns:
-        tuple: kept dets and indice.
-    """
-    nms_cfg_ = nms_cfg.copy()
-    class_agnostic = nms_cfg_.pop('class_agnostic', class_agnostic)
-    if class_agnostic:
-        boxes_for_nms = boxes
-    else:
-        max_coordinate = boxes.max()
-        offsets = idxs.to(boxes) * (max_coordinate + torch.tensor(1).to(boxes))
-        boxes_for_nms = boxes + offsets[:, None]
-
-    nms_type = nms_cfg_.pop('type', 'nms')
-    nms_op = eval(nms_type)
-
-    split_thr = nms_cfg_.pop('split_thr', 10000)
-    # Won't split to multiple nms nodes when exporting to onnx
-    if boxes_for_nms.shape[0] < split_thr or torch.onnx.is_in_onnx_export():
-        dets, keep = nms_op(boxes_for_nms, scores, **nms_cfg_)
-        boxes = boxes[keep]
-        # -1 indexing works abnormal in TensorRT
-        # This assumes `dets` has 5 dimensions where
-        # the last dimension is score.
-        # TODO: more elegant way to handle the dimension issue.
-        # Some type of nms would reweight the score, such as SoftNMS
-        scores = dets[:, 4]
-    else:
-        max_num = nms_cfg_.pop('max_num', -1)
-        total_mask = scores.new_zeros(scores.size(), dtype=torch.bool)
-        # Some type of nms would reweight the score, such as SoftNMS
-        scores_after_nms = scores.new_zeros(scores.size())
-        for id in torch.unique(idxs):
-            mask = (idxs == id).nonzero(as_tuple=False).view(-1)
-            dets, keep = nms_op(boxes_for_nms[mask], scores[mask], **nms_cfg_)
-            total_mask[mask[keep]] = True
-            scores_after_nms[mask[keep]] = dets[:, -1]
-        keep = total_mask.nonzero(as_tuple=False).view(-1)
-
-        scores, inds = scores_after_nms[keep].sort(descending=True)
-        keep = keep[inds]
-        boxes = boxes[keep]
-
-        if max_num > 0:
-            keep = keep[:max_num]
-            boxes = boxes[:max_num]
-            scores = scores[:max_num]
-
-    return torch.cat([boxes, scores[:, None]], -1), keep
-
-
-def nms_match(dets, iou_threshold):
-    """Matched dets into different groups by NMS.
-
-    NMS match is Similar to NMS but when a bbox is suppressed, nms match will
-    record the indice of suppressed bbox and form a group with the indice of
-    kept bbox. In each group, indice is sorted as score order.
-
-    Arguments:
-        dets (torch.Tensor | np.ndarray): Det boxes with scores, shape (N, 5).
-        iou_thr (float): IoU thresh for NMS.
-
-    Returns:
-        List[torch.Tensor | np.ndarray]: The outer list corresponds different
-            matched group, the inner Tensor corresponds the indices for a group
-            in score order.
-    """
-    if dets.shape[0] == 0:
-        matched = []
-    else:
-        assert dets.shape[-1] == 5, 'inputs dets.shape should be (N, 5), ' \
-                                    f'but get {dets.shape}'
-        if isinstance(dets, torch.Tensor):
-            dets_t = dets.detach().cpu()
-        else:
-            dets_t = torch.from_numpy(dets)
-        indata_list = [dets_t]
-        indata_dict = {'iou_threshold': float(iou_threshold)}
-        matched = ext_module.nms_match(*indata_list, **indata_dict)
-        if torch.__version__ == 'parrots':
-            matched = matched.tolist()
-
-    if isinstance(dets, torch.Tensor):
-        return [dets.new_tensor(m, dtype=torch.long) for m in matched]
-    else:
-        return [np.array(m, dtype=np.int) for m in matched]
-
-
-def nms_rotated(dets, scores, iou_threshold, labels=None):
-    """Performs non-maximum suppression (NMS) on the rotated boxes according to
-    their intersection-over-union (IoU).
-
-    Rotated NMS iteratively removes lower scoring rotated boxes which have an
-    IoU greater than iou_threshold with another (higher scoring) rotated box.
-
-    Args:
-        boxes (Tensor):  Rotated boxes in shape (N, 5). They are expected to \
-            be in (x_ctr, y_ctr, width, height, angle_radian) format.
-        scores (Tensor): scores in shape (N, ).
-        iou_threshold (float): IoU thresh for NMS.
-        labels (Tensor): boxes' label in shape (N,).
-
-    Returns:
-        tuple: kept dets(boxes and scores) and indice, which is always the \
-            same data type as the input.
-    """
-    if dets.shape[0] == 0:
-        return dets, None
-    multi_label = labels is not None
-    if multi_label:
-        dets_wl = torch.cat((dets, labels.unsqueeze(1)), 1)
-    else:
-        dets_wl = dets
-    _, order = scores.sort(0, descending=True)
-    dets_sorted = dets_wl.index_select(0, order)
-
-    if torch.__version__ == 'parrots':
-        keep_inds = ext_module.nms_rotated(
-            dets_wl,
-            scores,
-            order,
-            dets_sorted,
-            iou_threshold=iou_threshold,
-            multi_label=multi_label)
-    else:
-        keep_inds = ext_module.nms_rotated(dets_wl, scores, order, dets_sorted,
-                                           iou_threshold, multi_label)
-    dets = torch.cat((dets[keep_inds], scores[keep_inds].reshape(-1, 1)),
-                     dim=1)
-    return dets, keep_inds
diff --git a/spaces/MisterZee/PIFu-Clothed-Human-Digitization/PIFu/lib/renderer/mesh.py b/spaces/MisterZee/PIFu-Clothed-Human-Digitization/PIFu/lib/renderer/mesh.py
deleted file mode 100644
index a76ec5838d08d109dc24f58ca8ef3aff2ade552b..0000000000000000000000000000000000000000
--- a/spaces/MisterZee/PIFu-Clothed-Human-Digitization/PIFu/lib/renderer/mesh.py
+++ /dev/null
@@ -1,345 +0,0 @@
-import numpy as np
-
-
-def save_obj_mesh(mesh_path, verts, faces):
-    file = open(mesh_path, 'w')
-    for v in verts:
-        file.write('v %.4f %.4f %.4f\n' % (v[0], v[1], v[2]))
-    for f in faces:
-        f_plus = f + 1
-        file.write('f %d %d %d\n' % (f_plus[0], f_plus[1], f_plus[2]))
-    file.close()
-
-# https://github.com/ratcave/wavefront_reader
-def read_mtlfile(fname):
-    materials = {}
-    with open(fname) as f:
-        lines = f.read().splitlines()
-
-    for line in lines:
-        if line:
-            split_line = line.strip().split(' ', 1)
-            if len(split_line) < 2:
-                continue
-
-            prefix, data = split_line[0], split_line[1]
-            if 'newmtl' in prefix:
-                material = {}
-                materials[data] = material
-            elif materials:
-                if data:
-                    split_data = data.strip().split(' ')
-
-                    # assume texture maps are in the same level
-                    # WARNING: do not include space in your filename!!                    
-                    if 'map' in prefix:
-                        material[prefix] = split_data[-1].split('\\')[-1]
-                    elif len(split_data) > 1:
-                        material[prefix] = tuple(float(d) for d in split_data)
-                    else:
-                        try:
-                            material[prefix] = int(data)
-                        except ValueError:
-                            material[prefix] = float(data)
-
-    return materials
-
-
-def load_obj_mesh_mtl(mesh_file):
-    vertex_data = []
-    norm_data = []
-    uv_data = []
-
-    face_data = []
-    face_norm_data = []
-    face_uv_data = []
-
-    # face per material
-    face_data_mat = {}
-    face_norm_data_mat = {}
-    face_uv_data_mat = {}
-
-    # current material name
-    mtl_data = None
-    cur_mat = None
-
-    if isinstance(mesh_file, str):
-        f = open(mesh_file, "r")
-    else:
-        f = mesh_file
-    for line in f:
-        if isinstance(line, bytes):
-            line = line.decode("utf-8")
-        if line.startswith('#'):
-            continue
-        values = line.split()
-        if not values:
-            continue
-
-        if values[0] == 'v':
-            v = list(map(float, values[1:4]))
-            vertex_data.append(v)
-        elif values[0] == 'vn':
-            vn = list(map(float, values[1:4]))
-            norm_data.append(vn)
-        elif values[0] == 'vt':
-            vt = list(map(float, values[1:3]))
-            uv_data.append(vt)
-        elif values[0] == 'mtllib':
-            mtl_data = read_mtlfile(mesh_file.replace(mesh_file.split('/')[-1],values[1]))
-        elif values[0] == 'usemtl':
-            cur_mat = values[1]
-        elif values[0] == 'f':
-            # local triangle data
-            l_face_data = []
-            l_face_uv_data = []
-            l_face_norm_data = []
-
-            # quad mesh
-            if len(values) > 4:
-                f = list(map(lambda x: int(x.split('/')[0]) if int(x.split('/')[0]) < 0 else int(x.split('/')[0])-1, values[1:4]))
-                l_face_data.append(f)
-                f = list(map(lambda x: int(x.split('/')[0]) if int(x.split('/')[0]) < 0 else int(x.split('/')[0])-1, [values[3], values[4], values[1]]))
-                l_face_data.append(f)
-            # tri mesh
-            else:
-                f = list(map(lambda x: int(x.split('/')[0]) if int(x.split('/')[0]) < 0 else int(x.split('/')[0])-1, values[1:4]))
-                l_face_data.append(f)
-            # deal with texture
-            if len(values[1].split('/')) >= 2:
-                # quad mesh
-                if len(values) > 4:
-                    f = list(map(lambda x: int(x.split('/')[1]) if int(x.split('/')[1]) < 0 else int(x.split('/')[1])-1, values[1:4]))
-                    l_face_uv_data.append(f)
-                    f = list(map(lambda x: int(x.split('/')[1]) if int(x.split('/')[1]) < 0 else int(x.split('/')[1])-1, [values[3], values[4], values[1]]))
-                    l_face_uv_data.append(f)
-                # tri mesh
-                elif len(values[1].split('/')[1]) != 0:
-                    f = list(map(lambda x: int(x.split('/')[1]) if int(x.split('/')[1]) < 0 else int(x.split('/')[1])-1, values[1:4]))
-                    l_face_uv_data.append(f)
-            # deal with normal
-            if len(values[1].split('/')) == 3:
-                # quad mesh
-                if len(values) > 4:
-                    f = list(map(lambda x: int(x.split('/')[2]) if int(x.split('/')[2]) < 0 else int(x.split('/')[2])-1, values[1:4]))
-                    l_face_norm_data.append(f)
-                    f = list(map(lambda x: int(x.split('/')[2]) if int(x.split('/')[2]) < 0 else int(x.split('/')[2])-1, [values[3], values[4], values[1]]))
-                    l_face_norm_data.append(f)
-                # tri mesh
-                elif len(values[1].split('/')[2]) != 0:
-                    f = list(map(lambda x: int(x.split('/')[2]) if int(x.split('/')[2]) < 0 else int(x.split('/')[2])-1, values[1:4]))
-                    l_face_norm_data.append(f)
-            
-            face_data += l_face_data
-            face_uv_data += l_face_uv_data
-            face_norm_data += l_face_norm_data
-
-            if cur_mat is not None:
-                if cur_mat not in face_data_mat.keys():
-                    face_data_mat[cur_mat] = []
-                if cur_mat not in face_uv_data_mat.keys():
-                    face_uv_data_mat[cur_mat] = []
-                if cur_mat not in face_norm_data_mat.keys():
-                    face_norm_data_mat[cur_mat] = []
-                face_data_mat[cur_mat] += l_face_data
-                face_uv_data_mat[cur_mat] += l_face_uv_data
-                face_norm_data_mat[cur_mat] += l_face_norm_data
-
-    vertices = np.array(vertex_data)
-    faces = np.array(face_data)
-
-    norms = np.array(norm_data)
-    norms = normalize_v3(norms)
-    face_normals = np.array(face_norm_data)
-
-    uvs = np.array(uv_data)
-    face_uvs = np.array(face_uv_data)
-
-    out_tuple = (vertices, faces, norms, face_normals, uvs, face_uvs)
-
-    if cur_mat is not None and mtl_data is not None:
-        for key in face_data_mat:
-            face_data_mat[key] = np.array(face_data_mat[key])
-            face_uv_data_mat[key] = np.array(face_uv_data_mat[key])
-            face_norm_data_mat[key] = np.array(face_norm_data_mat[key])
-        
-        out_tuple += (face_data_mat, face_norm_data_mat, face_uv_data_mat, mtl_data)
-
-    return out_tuple
-    
-
-def load_obj_mesh(mesh_file, with_normal=False, with_texture=False):
-    vertex_data = []
-    norm_data = []
-    uv_data = []
-
-    face_data = []
-    face_norm_data = []
-    face_uv_data = []
-
-    if isinstance(mesh_file, str):
-        f = open(mesh_file, "r")
-    else:
-        f = mesh_file
-    for line in f:
-        if isinstance(line, bytes):
-            line = line.decode("utf-8")
-        if line.startswith('#'):
-            continue
-        values = line.split()
-        if not values:
-            continue
-
-        if values[0] == 'v':
-            v = list(map(float, values[1:4]))
-            vertex_data.append(v)
-        elif values[0] == 'vn':
-            vn = list(map(float, values[1:4]))
-            norm_data.append(vn)
-        elif values[0] == 'vt':
-            vt = list(map(float, values[1:3]))
-            uv_data.append(vt)
-
-        elif values[0] == 'f':
-            # quad mesh
-            if len(values) > 4:
-                f = list(map(lambda x: int(x.split('/')[0]), values[1:4]))
-                face_data.append(f)
-                f = list(map(lambda x: int(x.split('/')[0]), [values[3], values[4], values[1]]))
-                face_data.append(f)
-            # tri mesh
-            else:
-                f = list(map(lambda x: int(x.split('/')[0]), values[1:4]))
-                face_data.append(f)
-            
-            # deal with texture
-            if len(values[1].split('/')) >= 2:
-                # quad mesh
-                if len(values) > 4:
-                    f = list(map(lambda x: int(x.split('/')[1]), values[1:4]))
-                    face_uv_data.append(f)
-                    f = list(map(lambda x: int(x.split('/')[1]), [values[3], values[4], values[1]]))
-                    face_uv_data.append(f)
-                # tri mesh
-                elif len(values[1].split('/')[1]) != 0:
-                    f = list(map(lambda x: int(x.split('/')[1]), values[1:4]))
-                    face_uv_data.append(f)
-            # deal with normal
-            if len(values[1].split('/')) == 3:
-                # quad mesh
-                if len(values) > 4:
-                    f = list(map(lambda x: int(x.split('/')[2]), values[1:4]))
-                    face_norm_data.append(f)
-                    f = list(map(lambda x: int(x.split('/')[2]), [values[3], values[4], values[1]]))
-                    face_norm_data.append(f)
-                # tri mesh
-                elif len(values[1].split('/')[2]) != 0:
-                    f = list(map(lambda x: int(x.split('/')[2]), values[1:4]))
-                    face_norm_data.append(f)
-
-    vertices = np.array(vertex_data)
-    faces = np.array(face_data) - 1
-
-    if with_texture and with_normal:
-        uvs = np.array(uv_data)
-        face_uvs = np.array(face_uv_data) - 1
-        norms = np.array(norm_data)
-        if norms.shape[0] == 0:
-            norms = compute_normal(vertices, faces)
-            face_normals = faces
-        else:
-            norms = normalize_v3(norms)
-            face_normals = np.array(face_norm_data) - 1
-        return vertices, faces, norms, face_normals, uvs, face_uvs
-
-    if with_texture:
-        uvs = np.array(uv_data)
-        face_uvs = np.array(face_uv_data) - 1
-        return vertices, faces, uvs, face_uvs
-
-    if with_normal:
-        norms = np.array(norm_data)
-        norms = normalize_v3(norms)
-        face_normals = np.array(face_norm_data) - 1
-        return vertices, faces, norms, face_normals
-
-    return vertices, faces
-
-
-def normalize_v3(arr):
-    ''' Normalize a numpy array of 3 component vectors shape=(n,3) '''
-    lens = np.sqrt(arr[:, 0] ** 2 + arr[:, 1] ** 2 + arr[:, 2] ** 2)
-    eps = 0.00000001
-    lens[lens < eps] = eps
-    arr[:, 0] /= lens
-    arr[:, 1] /= lens
-    arr[:, 2] /= lens
-    return arr
-
-
-def compute_normal(vertices, faces):
-    # Create a zeroed array with the same type and shape as our vertices i.e., per vertex normal
-    norm = np.zeros(vertices.shape, dtype=vertices.dtype)
-    # Create an indexed view into the vertex array using the array of three indices for triangles
-    tris = vertices[faces]
-    # Calculate the normal for all the triangles, by taking the cross product of the vectors v1-v0, and v2-v0 in each triangle
-    n = np.cross(tris[::, 1] - tris[::, 0], tris[::, 2] - tris[::, 0])
-    # n is now an array of normals per triangle. The length of each normal is dependent the vertices,
-    # we need to normalize these, so that our next step weights each normal equally.
-    normalize_v3(n)
-    # now we have a normalized array of normals, one per triangle, i.e., per triangle normals.
-    # But instead of one per triangle (i.e., flat shading), we add to each vertex in that triangle,
-    # the triangles' normal. Multiple triangles would then contribute to every vertex, so we need to normalize again afterwards.
-    # The cool part, we can actually add the normals through an indexed view of our (zeroed) per vertex normal array
-    norm[faces[:, 0]] += n
-    norm[faces[:, 1]] += n
-    norm[faces[:, 2]] += n
-    normalize_v3(norm)
-
-    return norm
-
-# compute tangent and bitangent
-def compute_tangent(vertices, faces, normals, uvs, faceuvs):    
-    # NOTE: this could be numerically unstable around [0,0,1]
-    # but other current solutions are pretty freaky somehow
-    c1 = np.cross(normals, np.array([0,1,0.0]))
-    tan = c1
-    normalize_v3(tan)
-    btan = np.cross(normals, tan)
-
-    # NOTE: traditional version is below
-
-    # pts_tris = vertices[faces]
-    # uv_tris = uvs[faceuvs]
-
-    # W = np.stack([pts_tris[::, 1] - pts_tris[::, 0], pts_tris[::, 2] - pts_tris[::, 0]],2)
-    # UV = np.stack([uv_tris[::, 1] - uv_tris[::, 0], uv_tris[::, 2] - uv_tris[::, 0]], 1)
-    
-    # for i in range(W.shape[0]):
-    #     W[i,::] = W[i,::].dot(np.linalg.inv(UV[i,::]))
-
-    # tan = np.zeros(vertices.shape, dtype=vertices.dtype)
-    # tan[faces[:,0]] += W[:,:,0]
-    # tan[faces[:,1]] += W[:,:,0]
-    # tan[faces[:,2]] += W[:,:,0]
-
-    # btan = np.zeros(vertices.shape, dtype=vertices.dtype)
-    # btan[faces[:,0]] += W[:,:,1]
-    # btan[faces[:,1]] += W[:,:,1]    
-    # btan[faces[:,2]] += W[:,:,1]
-
-    # normalize_v3(tan)
-    
-    # ndott = np.sum(normals*tan, 1, keepdims=True)
-    # tan = tan - ndott * normals
-
-    # normalize_v3(btan)
-    # normalize_v3(tan)
-
-    # tan[np.sum(np.cross(normals, tan) * btan, 1) < 0,:] *= -1.0
-
-    return tan, btan
-
-if __name__ == '__main__':
-    pts, tri, nml, trin, uvs, triuv = load_obj_mesh('/home/ICT2000/ssaito/Documents/Body/tmp/Baseball_Pitching/0012.obj', True, True)
-    compute_tangent(pts, tri, uvs, triuv)
\ No newline at end of file
diff --git a/spaces/Mountchicken/MAERec-Gradio/configs/textrecog/_base_/datasets/icdar2015.py b/spaces/Mountchicken/MAERec-Gradio/configs/textrecog/_base_/datasets/icdar2015.py
deleted file mode 100644
index b6ed92d7a54d0757c0afbbea891acf59a2daf137..0000000000000000000000000000000000000000
--- a/spaces/Mountchicken/MAERec-Gradio/configs/textrecog/_base_/datasets/icdar2015.py
+++ /dev/null
@@ -1,21 +0,0 @@
-icdar2015_textrecog_data_root = '../data/common_benchmarks/IC15'
-
-icdar2015_textrecog_train = dict(
-    type='OCRDataset',
-    data_root=icdar2015_textrecog_data_root,
-    ann_file='textrecog_train.json',
-    pipeline=None)
-
-icdar2015_textrecog_test = dict(
-    type='OCRDataset',
-    data_root=icdar2015_textrecog_data_root,
-    ann_file='annotation.json',
-    test_mode=True,
-    pipeline=None)
-
-icdar2015_1811_textrecog_test = dict(
-    type='OCRDataset',
-    data_root=icdar2015_textrecog_data_root,
-    ann_file='textrecog_test_1811.json',
-    test_mode=True,
-    pipeline=None)
diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/noisychannel/rerank_options.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/noisychannel/rerank_options.py
deleted file mode 100644
index de91939e6635bdf33c9dc330116be07d9e8be6a2..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/examples/noisychannel/rerank_options.py
+++ /dev/null
@@ -1,149 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-from fairseq import options
-
-
-def get_reranking_parser(default_task="translation"):
-    parser = options.get_parser("Generation and reranking", default_task)
-    add_reranking_args(parser)
-    return parser
-
-
-def get_tuning_parser(default_task="translation"):
-    parser = options.get_parser("Reranking tuning", default_task)
-    add_reranking_args(parser)
-    add_tuning_args(parser)
-    return parser
-
-
-def add_reranking_args(parser):
-    group = parser.add_argument_group("Reranking")
-    # fmt: off
-    group.add_argument('--score-model1', '-s1', type=str, metavar='FILE', required=True,
-                       help='path to first model or ensemble of models for rescoring')
-    group.add_argument('--score-model2', '-s2', type=str, metavar='FILE', required=False,
-                       help='path to second model or ensemble of models for rescoring')
-    group.add_argument('--num-rescore', '-n', type=int, metavar='N', default=10,
-                       help='the number of candidate hypothesis to rescore')
-    group.add_argument('-bz', '--batch-size', type=int, metavar='N', default=128,
-                       help='batch size for generating the nbest list')
-    group.add_argument('--gen-subset', default='test', metavar='SET', choices=['test', 'train', 'valid'],
-                       help='data subset to generate (train, valid, test)')
-    group.add_argument('--gen-model', default=None, metavar='FILE',
-                       help='the model to generate translations')
-    group.add_argument('-b1', '--backwards1', action='store_true',
-                       help='whether or not the first model group is backwards')
-    group.add_argument('-b2', '--backwards2', action='store_true',
-                       help='whether or not the second model group is backwards')
-    group.add_argument('-a', '--weight1', default=1, nargs='+', type=float,
-                       help='the weight(s) of the first model')
-    group.add_argument('-b', '--weight2', default=1, nargs='+', type=float,
-                       help='the weight(s) of the second model, or the gen model if using nbest from interactive.py')
-    group.add_argument('-c', '--weight3', default=1, nargs='+', type=float,
-                       help='the weight(s) of the third model')
-
-    # lm arguments
-    group.add_argument('-lm', '--language-model', default=None, metavar='FILE',
-                       help='language model for target language to rescore translations')
-    group.add_argument('--lm-dict', default=None, metavar='FILE',
-                       help='the dict of the language model for the target language')
-    group.add_argument('--lm-name', default=None,
-                       help='the name of the language model for the target language')
-    group.add_argument('--lm-bpe-code', default=None, metavar='FILE',
-                       help='the bpe code for the language model for the target language')
-    group.add_argument('--data-dir-name', default=None,
-                       help='name of data directory')
-    group.add_argument('--lenpen', default=1, nargs='+', type=float,
-                       help='length penalty: <1.0 favors shorter, >1.0 favors longer sentences')
-    group.add_argument('--score-dict-dir', default=None,
-                       help='the directory with dictionaries for the scoring models')
-    group.add_argument('--right-to-left1', action='store_true',
-                       help='whether the first model group is a right to left model')
-    group.add_argument('--right-to-left2', action='store_true',
-                       help='whether the second model group is a right to left model')
-    group.add_argument('--post-process', '--remove-bpe', default='@@ ',
-                       help='the bpe symbol, used for the bitext and LM')
-    group.add_argument('--prefix-len', default=None, type=int,
-                       help='the length of the target prefix to use in rescoring (in terms of words wo bpe)')
-    group.add_argument('--sampling', action='store_true',
-                       help='use sampling instead of beam search for generating n best list')
-    group.add_argument('--diff-bpe', action='store_true',
-                       help='bpe for rescoring and nbest list not the same')
-    group.add_argument('--rescore-bpe-code', default=None,
-                       help='bpe code for rescoring models')
-    group.add_argument('--nbest-list', default=None,
-                       help='use predefined nbest list in interactive.py format')
-    group.add_argument('--write-hypos', default=None,
-                       help='filename prefix to write hypos to')
-    group.add_argument('--ref-translation', default=None,
-                       help='reference translation to use with nbest list from interactive.py')
-    group.add_argument('--backwards-score-dict-dir', default=None,
-                       help='the directory with dictionaries for the backwards model,'
-                            'if None then it is assumed the fw and backwards models share dictionaries')
-
-    # extra scaling args
-    group.add_argument('--gen-model-name', default=None,
-                       help='the name of the models that generated the nbest list')
-    group.add_argument('--model1-name', default=None,
-                       help='the name of the set for model1 group ')
-    group.add_argument('--model2-name', default=None,
-                       help='the name of the set for model2 group')
-    group.add_argument('--shard-id', default=0, type=int,
-                       help='the id of the shard to generate')
-    group.add_argument('--num-shards', default=1, type=int,
-                       help='the number of shards to generate across')
-    group.add_argument('--all-shards', action='store_true',
-                       help='use all shards')
-    group.add_argument('--target-prefix-frac', default=None, type=float,
-                       help='the fraction of the target prefix to use in rescoring (in terms of words wo bpe)')
-    group.add_argument('--source-prefix-frac', default=None, type=float,
-                       help='the fraction of the source prefix to use in rescoring (in terms of words wo bpe)')
-    group.add_argument('--normalize', action='store_true',
-                       help='whether to normalize by src and target len')
-    # fmt: on
-    return group
-
-
-def add_tuning_args(parser):
-    group = parser.add_argument_group("Tuning")
-
-    group.add_argument(
-        "--lower-bound",
-        default=[-0.7],
-        nargs="+",
-        type=float,
-        help="lower bound of search space",
-    )
-    group.add_argument(
-        "--upper-bound",
-        default=[3],
-        nargs="+",
-        type=float,
-        help="upper bound of search space",
-    )
-    group.add_argument(
-        "--tune-param",
-        default=["lenpen"],
-        nargs="+",
-        choices=["lenpen", "weight1", "weight2", "weight3"],
-        help="the parameter(s) to tune",
-    )
-    group.add_argument(
-        "--tune-subset",
-        default="valid",
-        choices=["valid", "test", "train"],
-        help="the subset to tune on ",
-    )
-    group.add_argument(
-        "--num-trials",
-        default=1000,
-        type=int,
-        help="number of trials to do for random search",
-    )
-    group.add_argument(
-        "--share-weights", action="store_true", help="share weight2 and weight 3"
-    )
-    return group
diff --git a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/legacy/masked_lm_dataset.py b/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/legacy/masked_lm_dataset.py
deleted file mode 100644
index dd8ea2c60aff306ab3a756223a298a28d41a4991..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Generic_Interface/fairseq/fairseq/data/legacy/masked_lm_dataset.py
+++ /dev/null
@@ -1,303 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import math
-from typing import Dict, List, Tuple
-
-import numpy as np
-import torch
-from fairseq.data import Dictionary, FairseqDataset, data_utils
-from fairseq.data.concat_dataset import ConcatDataset
-from fairseq.data.legacy.block_pair_dataset import BlockPairDataset
-from fairseq.data.token_block_dataset import TokenBlockDataset
-
-
-class MaskedLMDataset(FairseqDataset):
-    """
-    A wrapper Dataset for masked language modelling. The dataset
-    wraps around TokenBlockDataset or BlockedPairDataset and creates a batch
-    where the input blocks are masked according to the specified masking
-    probability. Additionally the batch can also contain sentence level targets
-    if this is specified.
-
-    Args:
-        dataset: Dataset which generates blocks of data. Only BlockPairDataset
-            and TokenBlockDataset are supported.
-        sizes: Sentence lengths
-        vocab: Dictionary with the vocabulary and special tokens.
-        pad_idx: Id of padding token in dictionary
-        mask_idx: Id of mask token in dictionary
-        classif_token_idx: Id of classification token in dictionary. This is the
-            token associated with the sentence embedding (Eg: CLS for BERT)
-        sep_token_idx: Id of separator token in dictionary
-            (Eg: SEP in BERT)
-        seed: Seed for random number generator for reproducibility.
-        shuffle: Shuffle the elements before batching.
-        has_pairs: Specifies whether the underlying dataset
-            generates a pair of blocks along with a sentence_target or not.
-            Setting it to True assumes that the underlying dataset generates a
-            label for the pair of sentences which is surfaced as
-            sentence_target. The default value assumes a single block with no
-            sentence target.
-        segment_id: An optional segment id for filling in the segment labels
-            when we are in the single block setting (Eg: XLM). Default is 0.
-        masking_ratio: specifies what percentage of the blocks should be masked.
-        masking_prob: specifies the probability of a given token being
-            replaced with the "MASK" token.
-        random_token_prob: specifies the probability of a given token being
-            replaced by a random token from the vocabulary.
-    """
-
-    def __init__(
-        self,
-        dataset: FairseqDataset,
-        sizes: np.ndarray,
-        vocab: Dictionary,
-        pad_idx: int,
-        mask_idx: int,
-        classif_token_idx: int,
-        sep_token_idx: int,
-        seed: int = 1,
-        shuffle: bool = True,
-        has_pairs: bool = True,
-        segment_id: int = 0,
-        masking_ratio: float = 0.15,
-        masking_prob: float = 0.8,
-        random_token_prob: float = 0.1,
-    ):
-        # Make sure the input datasets are the ones supported
-        assert (
-            isinstance(dataset, TokenBlockDataset)
-            or isinstance(dataset, BlockPairDataset)
-            or isinstance(dataset, ConcatDataset)
-        ), (
-            "MaskedLMDataset only wraps TokenBlockDataset or BlockPairDataset or "
-            "ConcatDataset"
-        )
-
-        self.dataset = dataset
-        self.sizes = np.array(sizes)
-        self.vocab = vocab
-        self.pad_idx = pad_idx
-        self.mask_idx = mask_idx
-        self.classif_token_idx = classif_token_idx
-        self.sep_token_idx = sep_token_idx
-        self.shuffle = shuffle
-        self.seed = seed
-        self.has_pairs = has_pairs
-        self.segment_id = segment_id
-        self.masking_ratio = masking_ratio
-        self.masking_prob = masking_prob
-        self.random_token_prob = random_token_prob
-
-        # If we have only one block then sizes needs to be updated to include
-        # the classification token
-        if not has_pairs:
-            self.sizes = self.sizes + 1
-
-    def __getitem__(self, index: int):
-        # if has_pairs, then expect 2 blocks and a sentence target
-        if self.has_pairs:
-            (block_one, block_two, sentence_target) = self.dataset[index]
-        else:
-            block_one = self.dataset[index]
-
-        return {
-            "id": index,
-            "block_one": block_one,
-            "block_two": block_two if self.has_pairs else None,
-            "sentence_target": sentence_target if self.has_pairs else None,
-        }
-
-    def __len__(self):
-        return len(self.dataset)
-
-    def _mask_block(
-        self,
-        sentence: np.ndarray,
-        mask_idx: int,
-        pad_idx: int,
-        dictionary_token_range: Tuple,
-    ):
-        """
-        Mask tokens for Masked Language Model training
-        Samples mask_ratio tokens that will be predicted by LM.
-
-        Note:This function may not be efficient enough since we had multiple
-        conversions between np and torch, we can replace them with torch
-        operators later.
-
-        Args:
-            sentence: 1d tensor to be masked
-            mask_idx: index to use for masking the sentence
-            pad_idx: index to use for masking the target for tokens we aren't
-                predicting
-            dictionary_token_range: range of indices in dictionary which can
-                be used for random word replacement
-                (e.g. without special characters)
-        Return:
-            masked_sent: masked sentence
-            target: target with words which we are not predicting replaced
-                by pad_idx
-        """
-        masked_sent = np.copy(sentence)
-        sent_length = len(sentence)
-        mask_num = math.ceil(sent_length * self.masking_ratio)
-        mask = np.random.choice(sent_length, mask_num, replace=False)
-        target = np.copy(sentence)
-
-        for i in range(sent_length):
-            if i in mask:
-                rand = np.random.random()
-
-                # replace with mask if probability is less than masking_prob
-                # (Eg: 0.8)
-                if rand < self.masking_prob:
-                    masked_sent[i] = mask_idx
-
-                # replace with random token if probability is less than
-                # masking_prob + random_token_prob (Eg: 0.9)
-                elif rand < (self.masking_prob + self.random_token_prob):
-                    # sample random token from dictionary
-                    masked_sent[i] = np.random.randint(
-                        dictionary_token_range[0], dictionary_token_range[1]
-                    )
-            else:
-                target[i] = pad_idx
-
-        return masked_sent, target
-
-    def _collate(self, samples: List[Dict], pad_idx: int, eos_idx: int):
-        """
-        Does the heavy lifting for creating a batch from the input list of
-        examples. The logic is as follows:
-            1. Mask the input blocks. In case has_pair is True then we have 2
-               blocks to mask.
-            2. Prepend the first masked block tensor with the special token
-               used as sentence embedding. Eg: CLS in BERT. This happens
-               irrespective of the value of has_pair.
-            3. If has_pair is True, then append the first masked block with the
-               special separator token (eg: SEP for BERT) and compute segment
-               label accordingly. In this case, also append the second masked
-               block with this special separator token and compute its segment
-               label.
-            4. For the targets tensor, prepend and append with padding index
-               accordingly.
-            5. Concatenate all tensors.
-        """
-        if len(samples) == 0:
-            return {}
-        # To ensure determinism, we reset the state of the PRNG after every
-        # batch based on the seed and the first id of the batch. This ensures
-        # that across epochs we get the same mask for the same example. This
-        # is needed for reproducibility and is how BERT does masking
-        # TODO: Can we add deteminism without this constraint?
-        with data_utils.numpy_seed(self.seed + samples[0]["id"]):
-            for s in samples:
-
-                # token range is needed for replacing with random token during
-                # masking
-                token_range = (self.vocab.nspecial, len(self.vocab))
-
-                # mask according to specified probabilities.
-                masked_blk_one, masked_tgt_one = self._mask_block(
-                    s["block_one"],
-                    self.mask_idx,
-                    self.pad_idx,
-                    token_range,
-                )
-
-                tokens = np.concatenate([[self.classif_token_idx], masked_blk_one])
-                targets = np.concatenate([[self.pad_idx], masked_tgt_one])
-                segments = np.ones(len(tokens)) * self.segment_id
-
-                # if has_pairs is True then we need to add the SEP token to both
-                # the blocks after masking and re-compute segments based on the new
-                # lengths.
-                if self.has_pairs:
-                    tokens_one = np.concatenate([tokens, [self.sep_token_idx]])
-                    targets_one = np.concatenate([targets, [self.pad_idx]])
-
-                    masked_blk_two, masked_tgt_two = self._mask_block(
-                        s["block_two"], self.mask_idx, self.pad_idx, token_range
-                    )
-                    tokens_two = np.concatenate([masked_blk_two, [self.sep_token_idx]])
-                    targets_two = np.concatenate([masked_tgt_two, [self.pad_idx]])
-
-                    # block + 1 sep + 1 special (CLS)
-                    segments_one = np.zeros(len(tokens_one))
-                    # block + 1 sep
-                    segments_two = np.ones(len(tokens_two))
-
-                    tokens = np.concatenate([tokens_one, tokens_two])
-                    targets = np.concatenate([targets_one, targets_two])
-                    segments = np.concatenate([segments_one, segments_two])
-
-                s["source"] = torch.LongTensor(tokens)
-                s["segment_labels"] = torch.LongTensor(segments)
-                s["lm_target"] = torch.LongTensor(targets)
-
-        def merge(key):
-            return data_utils.collate_tokens(
-                [s[key] for s in samples], pad_idx, eos_idx, left_pad=False
-            )
-
-        return {
-            "id": torch.LongTensor([s["id"] for s in samples]),
-            "ntokens": sum(len(s["source"]) for s in samples),
-            "net_input": {
-                "src_tokens": merge("source"),
-                "segment_labels": merge("segment_labels"),
-            },
-            "lm_target": merge("lm_target"),
-            "sentence_target": torch.LongTensor([s["sentence_target"] for s in samples])
-            if self.has_pairs
-            else None,
-            "nsentences": len(samples),
-        }
-
-    def collater(self, samples: List[Dict]):
-        """Merge a list of samples to form a mini-batch.
-
-        Args:
-            samples (List[dict]): samples to collate
-
-        Returns:
-            dict: a mini-batch of data
-        """
-        return self._collate(samples, self.vocab.pad(), self.vocab.eos())
-
-    def num_tokens(self, index: int):
-        """
-        Return the number of tokens in a sample. This value is used to
-        enforce max-tokens during batching.
-        """
-        return self.sizes[index]
-
-    def size(self, index: int):
-        """
-        Return an example's size as a float or tuple. This value is used when
-        filtering a dataset with max-positions.
-        """
-        return self.sizes[index]
-
-    def ordered_indices(self):
-        """
-        Return an ordered list of indices. Batches will be constructed based
-        on this order.
-        """
-        if self.shuffle:
-            return np.random.permutation(len(self))
-        else:
-            order = [np.arange(len(self))]
-            order.append(self.sizes)
-            return np.lexsort(order)
-
-    @property
-    def supports_prefetch(self):
-        return getattr(self.dataset, "supports_prefetch", False)
-
-    def prefetch(self, indices):
-        self.dataset.prefetch(indices)
diff --git a/spaces/OFA-Sys/OFA-Image_Caption/fairseq/fairseq/modules/learned_positional_embedding.py b/spaces/OFA-Sys/OFA-Image_Caption/fairseq/fairseq/modules/learned_positional_embedding.py
deleted file mode 100644
index 378d0f707183dd344dbb9288dda394b11053acf0..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-Image_Caption/fairseq/fairseq/modules/learned_positional_embedding.py
+++ /dev/null
@@ -1,61 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-from typing import Dict, Optional
-
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-from fairseq import utils
-from torch import Tensor
-
-
-class LearnedPositionalEmbedding(nn.Embedding):
-    """
-    This module learns positional embeddings up to a fixed maximum size.
-    Padding ids are ignored by either offsetting based on padding_idx
-    or by setting padding_idx to None and ensuring that the appropriate
-    position ids are passed to the forward function.
-    """
-
-    def __init__(self, num_embeddings: int, embedding_dim: int, padding_idx: int):
-        super().__init__(num_embeddings, embedding_dim, padding_idx)
-        self.onnx_trace = False
-        if self.padding_idx is not None:
-            self.max_positions = self.num_embeddings - self.padding_idx - 1
-        else:
-            self.max_positions = self.num_embeddings
-
-    def forward(
-        self,
-        input: Tensor,
-        incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]] = None,
-        positions: Optional[Tensor] = None,
-    ):
-        """Input is expected to be of size [bsz x seqlen]."""
-        assert (positions is None) or (
-            self.padding_idx is None
-        ), "If positions is pre-computed then padding_idx should not be set."
-
-        if positions is None:
-            if incremental_state is not None:
-                # positions is the same for every token when decoding a single step
-                # Without the int() cast, it doesn't work in some cases when exporting to ONNX
-                positions = torch.zeros(
-                    (1, 1), device=input.device, dtype=input.dtype
-                ).fill_(int(self.padding_idx + input.size(1)))
-            else:
-                positions = utils.make_positions(
-                    input, self.padding_idx, onnx_trace=self.onnx_trace
-                )
-        return F.embedding(
-            positions,
-            self.weight,
-            self.padding_idx,
-            self.max_norm,
-            self.norm_type,
-            self.scale_grad_by_freq,
-            self.sparse,
-        )
diff --git a/spaces/OFA-Sys/OFA-vqa/fairseq/examples/criss/unsupervised_mt/eval.sh b/spaces/OFA-Sys/OFA-vqa/fairseq/examples/criss/unsupervised_mt/eval.sh
deleted file mode 100644
index 03b773ed5a522eb82186fea8ffbb6c557e14b6d3..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-vqa/fairseq/examples/criss/unsupervised_mt/eval.sh
+++ /dev/null
@@ -1,37 +0,0 @@
-#!/bin/bash
-# Copyright (c) Facebook, Inc. and its affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-#
-SRC=si_LK
-TGT=en_XX
-MODEL=criss_checkpoints/criss.3rd.pt
-
-MULTIBLEU=mosesdecoder/scripts/generic/multi-bleu.perl
-MOSES=mosesdecoder
-REPLACE_UNICODE_PUNCT=$MOSES/scripts/tokenizer/replace-unicode-punctuation.perl
-NORM_PUNC=$MOSES/scripts/tokenizer/normalize-punctuation.perl
-REM_NON_PRINT_CHAR=$MOSES/scripts/tokenizer/remove-non-printing-char.perl
-TOKENIZER=$MOSES/scripts/tokenizer/tokenizer.perl
-GEN_TMP_DIR=gen_tmp
-LANG_DICT=criss_checkpoints/lang_dict.txt
-
-if [ ! -d "mosesdecoder" ]; then
-  git clone https://github.com/moses-smt/mosesdecoder
-fi
-mkdir -p $GEN_TMP_DIR
-fairseq-generate data_tmp/${SRC}-${TGT}-flores \
-        --task translation_multi_simple_epoch \
-        --max-tokens 2000 \
-        --path ${MODEL} \
-        --skip-invalid-size-inputs-valid-test \
-        --beam 5 --lenpen 1.0 --gen-subset test  \
-        --remove-bpe=sentencepiece \
-        --source-lang ${SRC} --target-lang ${TGT} \
-        --decoder-langtok --lang-pairs 'en_XX-ar_AR,en_XX-de_DE,en_XX-es_XX,en_XX-fr_XX,en_XX-hi_IN,en_XX-it_IT,en_XX-ja_XX,en_XX-ko_KR,en_XX-nl_XX,en_XX-ru_RU,en_XX-zh_CN,en_XX-tr_TR,en_XX-vi_VN,en_XX-ro_RO,en_XX-my_MM,en_XX-ne_NP,en_XX-si_LK,en_XX-cs_CZ,en_XX-lt_LT,en_XX-kk_KZ,en_XX-gu_IN,en_XX-fi_FI,en_XX-et_EE,en_XX-lv_LV,ar_AR-en_XX,cs_CZ-en_XX,de_DE-en_XX,es_XX-en_XX,et_EE-en_XX,fi_FI-en_XX,fr_XX-en_XX,gu_IN-en_XX,hi_IN-en_XX,it_IT-en_XX,ja_XX-en_XX,kk_KZ-en_XX,ko_KR-en_XX,lt_LT-en_XX,lv_LV-en_XX,my_MM-en_XX,ne_NP-en_XX,nl_XX-en_XX,ro_RO-en_XX,ru_RU-en_XX,si_LK-en_XX,tr_TR-en_XX,vi_VN-en_XX,zh_CN-en_XX,ar_AR-es_XX,es_XX-ar_AR,ar_AR-hi_IN,hi_IN-ar_AR,ar_AR-zh_CN,zh_CN-ar_AR,cs_CZ-es_XX,es_XX-cs_CZ,cs_CZ-hi_IN,hi_IN-cs_CZ,cs_CZ-zh_CN,zh_CN-cs_CZ,de_DE-es_XX,es_XX-de_DE,de_DE-hi_IN,hi_IN-de_DE,de_DE-zh_CN,zh_CN-de_DE,es_XX-hi_IN,hi_IN-es_XX,es_XX-zh_CN,zh_CN-es_XX,et_EE-es_XX,es_XX-et_EE,et_EE-hi_IN,hi_IN-et_EE,et_EE-zh_CN,zh_CN-et_EE,fi_FI-es_XX,es_XX-fi_FI,fi_FI-hi_IN,hi_IN-fi_FI,fi_FI-zh_CN,zh_CN-fi_FI,fr_XX-es_XX,es_XX-fr_XX,fr_XX-hi_IN,hi_IN-fr_XX,fr_XX-zh_CN,zh_CN-fr_XX,gu_IN-es_XX,es_XX-gu_IN,gu_IN-hi_IN,hi_IN-gu_IN,gu_IN-zh_CN,zh_CN-gu_IN,hi_IN-zh_CN,zh_CN-hi_IN,it_IT-es_XX,es_XX-it_IT,it_IT-hi_IN,hi_IN-it_IT,it_IT-zh_CN,zh_CN-it_IT,ja_XX-es_XX,es_XX-ja_XX,ja_XX-hi_IN,hi_IN-ja_XX,ja_XX-zh_CN,zh_CN-ja_XX,kk_KZ-es_XX,es_XX-kk_KZ,kk_KZ-hi_IN,hi_IN-kk_KZ,kk_KZ-zh_CN,zh_CN-kk_KZ,ko_KR-es_XX,es_XX-ko_KR,ko_KR-hi_IN,hi_IN-ko_KR,ko_KR-zh_CN,zh_CN-ko_KR,lt_LT-es_XX,es_XX-lt_LT,lt_LT-hi_IN,hi_IN-lt_LT,lt_LT-zh_CN,zh_CN-lt_LT,lv_LV-es_XX,es_XX-lv_LV,lv_LV-hi_IN,hi_IN-lv_LV,lv_LV-zh_CN,zh_CN-lv_LV,my_MM-es_XX,es_XX-my_MM,my_MM-hi_IN,hi_IN-my_MM,my_MM-zh_CN,zh_CN-my_MM,ne_NP-es_XX,es_XX-ne_NP,ne_NP-hi_IN,hi_IN-ne_NP,ne_NP-zh_CN,zh_CN-ne_NP,nl_XX-es_XX,es_XX-nl_XX,nl_XX-hi_IN,hi_IN-nl_XX,nl_XX-zh_CN,zh_CN-nl_XX,ro_RO-es_XX,es_XX-ro_RO,ro_RO-hi_IN,hi_IN-ro_RO,ro_RO-zh_CN,zh_CN-ro_RO,ru_RU-es_XX,es_XX-ru_RU,ru_RU-hi_IN,hi_IN-ru_RU,ru_RU-zh_CN,zh_CN-ru_RU,si_LK-es_XX,es_XX-si_LK,si_LK-hi_IN,hi_IN-si_LK,si_LK-zh_CN,zh_CN-si_LK,tr_TR-es_XX,es_XX-tr_TR,tr_TR-hi_IN,hi_IN-tr_TR,tr_TR-zh_CN,zh_CN-tr_TR,vi_VN-es_XX,es_XX-vi_VN,vi_VN-hi_IN,hi_IN-vi_VN,vi_VN-zh_CN,zh_CN-vi_VN' \
-        --lang-dict ${LANG_DICT} --lang-tok-style 'mbart' --sampling-method 'temperature' --sampling-temperature '1.0'  > $GEN_TMP_DIR/${SRC}_${TGT}.gen
-cat $GEN_TMP_DIR/${SRC}_${TGT}.gen | grep -P "^T-" | cut -f2 | $REPLACE_UNICODE_PUNCT | $NORM_PUNC -l ${TGT:0:2} | $REM_NON_PRINT_CHAR | $TOKENIZER -no-escape ${TGT:0:2} > $GEN_TMP_DIR/${SRC}_${TGT}.hyp
-cat $GEN_TMP_DIR/${SRC}_${TGT}.gen | grep -P "^H-" | cut -f3 | $REPLACE_UNICODE_PUNCT | $NORM_PUNC -l ${TGT:0:2} | $REM_NON_PRINT_CHAR | $TOKENIZER -no-escape ${TGT:0:2} > $GEN_TMP_DIR/${SRC}_${TGT}.ref
-${MULTIBLEU} $GEN_TMP_DIR/${SRC}_${TGT}.ref < $GEN_TMP_DIR/${SRC}_${TGT}.hyp
diff --git a/spaces/OFA-Sys/OFA-vqa/fairseq/examples/speech_text_joint_to_text/docs/iwslt2021.md b/spaces/OFA-Sys/OFA-vqa/fairseq/examples/speech_text_joint_to_text/docs/iwslt2021.md
deleted file mode 100644
index 920ff271c2e178c7a4ca3c7c8ce57a2f28653969..0000000000000000000000000000000000000000
--- a/spaces/OFA-Sys/OFA-vqa/fairseq/examples/speech_text_joint_to_text/docs/iwslt2021.md
+++ /dev/null
@@ -1,76 +0,0 @@
-[[Back]](..)
-
-# Joint Speech Text Training for the 2021 IWSLT multilingual speech translation
-
-This directory contains the code from paper ["FST: the FAIR Speech Translation System for the IWSLT21 Multilingual Shared Task"](https://arxiv.org/pdf/2107.06959.pdf).
-
-## Prepare Data
-#### Download files
--   Sentence piece model [spm.model](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/spm.model)
--   Dictionary [tgt_dict.txt](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/dict.txt)
--   Config [config.yaml](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/config.yaml)
-
-#### Prepare
--   [Please follow the data preparation in speech-to-text](https://github.com/pytorch/fairseq/blob/main/examples/speech_to_text/docs/mtedx_example.md)
-
-
-
-## Training
-
-#### Download pretrained models
-- [Pretrained mbart model](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/mbart.pt)
-- [Pretrained w2v model](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/xlsr_53_56k.pt)
-
-
-#### Training scripts
-
-```bash
-python train.py ${MANIFEST_ROOT} \
-    --save-dir ${save_dir} \
-    --user-dir examples/speech_text_joint_to_text \
-    --train-subset train_es_en_tedx,train_es_es_tedx,train_fr_en_tedx,train_fr_es_tedx,train_fr_fr_tedx,train_it_it_tedx,train_pt_en_tedx,train_pt_pt_tedx \
-    --valid-subset valid_es_en_tedx,valid_es_es_tedx,valid_es_fr_tedx,valid_es_it_tedx,valid_es_pt_tedx,valid_fr_en_tedx,valid_fr_es_tedx,valid_fr_fr_tedx,valid_fr_pt_tedx,valid_it_en_tedx,valid_it_es_tedx,valid_it_it_tedx,valid_pt_en_tedx,valid_pt_es_tedx,valid_pt_pt_tedx \
-    --config-yaml config.yaml --ddp-backend no_c10d \
-    --num-workers 2 --task speech_text_joint_to_text \
-    --criterion guided_label_smoothed_cross_entropy_with_accuracy \
-    --label-smoothing 0.3 --guide-alpha 0.8 \
-    --disable-text-guide-update-num 5000 --arch dualinputxmtransformer_base \
-    --max-tokens 500000 --max-sentences 3 --max-tokens-valid 800000 \
-    --max-source-positions 800000 --enc-grad-mult 2.0 \
-    --attentive-cost-regularization 0.02 --optimizer adam \
-    --clip-norm 1.0 --log-format simple --log-interval 200 \
-    --keep-last-epochs 5 --seed 1 \
-    --w2v-path ${w2v_path} \
-    --load-pretrained-mbart-from ${mbart_path} \
-    --max-update 1000000 --update-freq 4 \
-    --skip-invalid-size-inputs-valid-test \
-    --skip-encoder-projection --save-interval 1 \
-    --attention-dropout 0.3 --mbart-dropout 0.3 \
-    --finetune-w2v-params all --finetune-mbart-decoder-params all \
-    --finetune-mbart-encoder-params all --stack-w2v-mbart-encoder \
-    --drop-w2v-layers 12 --normalize \
-    --lr 5e-05 --lr-scheduler inverse_sqrt --warmup-updates 5000
-```
-
-## Evaluation
-```bash
-python ./fairseq_cli/generate.py
-   ${MANIFEST_ROOT} \
-   --task speech_text_joint_to_text \
-   --user-dir ./examples/speech_text_joint_to_text \
-   --load-speech-only  --gen-subset  test_es_en_tedx \
-   --path  ${model}  \
-   --max-source-positions 800000 \
-   --skip-invalid-size-inputs-valid-test \
-   --config-yaml config.yaml \
-   --infer-target-lang en  \
-   --max-tokens 800000 \
-   --beam 5 \
-   --results-path ${RESULTS_DIR}  \
-   --scoring sacrebleu
-```
-The trained model can be downloaded [here](https://dl.fbaipublicfiles.com/joint_speech_text_4_s2t/iwslt/iwslt_data/checkpoint17.pt)
-
-|direction|es_en|fr_en|pt_en|it_en|fr_es|pt_es|it_es|es_es|fr_fr|pt_pt|it_it|
-|---|---|---|---|---|---|---|---|---|---|---|---|
-|BLEU|31.62|36.93|35.07|27.12|38.87|35.57|34.13|74.59|74.64|70.84|69.76|
diff --git a/spaces/OIUGLK/bingo/tailwind.config.js b/spaces/OIUGLK/bingo/tailwind.config.js
deleted file mode 100644
index 03da3c3c45be6983b9f5ffa6df5f1fd0870e9636..0000000000000000000000000000000000000000
--- a/spaces/OIUGLK/bingo/tailwind.config.js
+++ /dev/null
@@ -1,48 +0,0 @@
-/** @type {import('tailwindcss').Config} */
-module.exports = {
-  content: [
-    './src/pages/**/*.{js,ts,jsx,tsx,mdx}',
-    './src/components/**/*.{js,ts,jsx,tsx,mdx}',
-    './src/app/**/*.{js,ts,jsx,tsx,mdx}',
-    './src/ui/**/*.{js,ts,jsx,tsx,mdx}',
-  ],
-  "darkMode": "class",
-  theme: {
-    extend: {
-      colors: {
-        'primary-blue': 'rgb(var(--color-primary-blue) / <alpha-value>)',
-        secondary: 'rgb(var(--color-secondary) / <alpha-value>)',
-        'primary-background': 'rgb(var(--primary-background) / <alpha-value>)',
-        'primary-text': 'rgb(var(--primary-text) / <alpha-value>)',
-        'secondary-text': 'rgb(var(--secondary-text) / <alpha-value>)',
-        'light-text': 'rgb(var(--light-text) / <alpha-value>)',
-        'primary-border': 'rgb(var(--primary-border) / <alpha-value>)',
-      },
-      keyframes: {
-        slideDownAndFade: {
-          from: { opacity: 0, transform: 'translateY(-2px)' },
-          to: { opacity: 1, transform: 'translateY(0)' },
-        },
-        slideLeftAndFade: {
-          from: { opacity: 0, transform: 'translateX(2px)' },
-          to: { opacity: 1, transform: 'translateX(0)' },
-        },
-        slideUpAndFade: {
-          from: { opacity: 0, transform: 'translateY(2px)' },
-          to: { opacity: 1, transform: 'translateY(0)' },
-        },
-        slideRightAndFade: {
-          from: { opacity: 0, transform: 'translateX(2px)' },
-          to: { opacity: 1, transform: 'translateX(0)' },
-        },
-      },
-      animation: {
-        slideDownAndFade: 'slideDownAndFade 400ms cubic-bezier(0.16, 1, 0.3, 1)',
-        slideLeftAndFade: 'slideLeftAndFade 400ms cubic-bezier(0.16, 1, 0.3, 1)',
-        slideUpAndFade: 'slideUpAndFade 400ms cubic-bezier(0.16, 1, 0.3, 1)',
-        slideRightAndFade: 'slideRightAndFade 400ms cubic-bezier(0.16, 1, 0.3, 1)',
-      },
-    },
-  },
-  plugins: [require('@headlessui/tailwindcss'), require('tailwind-scrollbar')],
-}
diff --git a/spaces/OpenGVLab/InternGPT/third-party/lama/bin/filter_sharded_dataset.py b/spaces/OpenGVLab/InternGPT/third-party/lama/bin/filter_sharded_dataset.py
deleted file mode 100644
index b3c2b490e88bb3b55c6bb717e08f97f7a396d5fa..0000000000000000000000000000000000000000
--- a/spaces/OpenGVLab/InternGPT/third-party/lama/bin/filter_sharded_dataset.py
+++ /dev/null
@@ -1,69 +0,0 @@
-#!/usr/bin/env python3
-
-
-import math
-import os
-import random
-
-import braceexpand
-import webdataset as wds
-
-DEFAULT_CATS_FILE = os.path.join(os.path.dirname(__file__), '..', 'configs', 'places2-categories_157.txt')
-
-def is_good_key(key, cats):
-    return any(c in key for c in cats)
-
-
-def main(args):
-    if args.categories == 'nofilter':
-        good_categories = None
-    else:
-        with open(args.categories, 'r') as f:
-            good_categories = set(line.strip().split(' ')[0] for line in f if line.strip())
-
-    all_input_files = list(braceexpand.braceexpand(args.infile))
-    chunk_size = int(math.ceil(len(all_input_files) / args.n_read_streams))
-
-    input_iterators = [iter(wds.Dataset(all_input_files[start : start + chunk_size]).shuffle(args.shuffle_buffer))
-                       for start in range(0, len(all_input_files), chunk_size)]
-    output_datasets = [wds.ShardWriter(args.outpattern.format(i)) for i in range(args.n_write_streams)]
-
-    good_readers = list(range(len(input_iterators)))
-    step_i = 0
-    good_samples = 0
-    bad_samples = 0
-    while len(good_readers) > 0:
-        if step_i % args.print_freq == 0:
-            print(f'Iterations done {step_i}; readers alive {good_readers}; good samples {good_samples}; bad samples {bad_samples}')
-
-        step_i += 1
-
-        ri = random.choice(good_readers)
-        try:
-            sample = next(input_iterators[ri])
-        except StopIteration:
-            good_readers = list(set(good_readers) - {ri})
-            continue
-
-        if good_categories is not None and not is_good_key(sample['__key__'], good_categories):
-            bad_samples += 1
-            continue
-
-        wi = random.randint(0, args.n_write_streams - 1)
-        output_datasets[wi].write(sample)
-        good_samples += 1
-
-
-if __name__ == '__main__':
-    import argparse
-
-    aparser = argparse.ArgumentParser()
-    aparser.add_argument('--categories', type=str, default=DEFAULT_CATS_FILE)
-    aparser.add_argument('--shuffle-buffer', type=int, default=10000)
-    aparser.add_argument('--n-read-streams', type=int, default=10)
-    aparser.add_argument('--n-write-streams', type=int, default=10)
-    aparser.add_argument('--print-freq', type=int, default=1000)
-    aparser.add_argument('infile', type=str)
-    aparser.add_argument('outpattern', type=str)
-
-    main(aparser.parse_args())
diff --git a/spaces/Pascall/OASSapi_00/README.md b/spaces/Pascall/OASSapi_00/README.md
deleted file mode 100644
index 699c1d4351251588767030a282fd30e890b1d09b..0000000000000000000000000000000000000000
--- a/spaces/Pascall/OASSapi_00/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: OASSapi 00
-emoji: 🏃
-colorFrom: gray
-colorTo: yellow
-sdk: gradio
-sdk_version: 3.35.2
-app_file: OASSapi.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Pattr/DrumClassification/lilypond-2.24.2/share/lilypond/2.24.2/python/convertrules.py b/spaces/Pattr/DrumClassification/lilypond-2.24.2/share/lilypond/2.24.2/python/convertrules.py
deleted file mode 100644
index b670fe6949ced6e55a0afcd24cadf6f78fa6e881..0000000000000000000000000000000000000000
--- a/spaces/Pattr/DrumClassification/lilypond-2.24.2/share/lilypond/2.24.2/python/convertrules.py
+++ /dev/null
@@ -1,4764 +0,0 @@
-# -*- coding: utf-8 -*-
-# (setq py-indent-offset 4)
-#
-# This file is part of LilyPond, the GNU music typesetter.
-#
-# Copyright (C) 1998--2022 Han-Wen Nienhuys <hanwen@xs4all.nl>,
-#                          Jan Nieuwenhuizen <janneke@gnu.org>
-#
-# LilyPond is free software: you can redistribute it and/or modify
-# it under the terms of the GNU General Public License as published by
-# the Free Software Foundation, either version 3 of the License, or
-# (at your option) any later version.
-#
-# LilyPond is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-# GNU General Public License for more details.
-#
-# You should have received a copy of the GNU General Public License
-# along with LilyPond.  If not, see <http://www.gnu.org/licenses/>.
-
-
-import re
-import string
-import sys
-
-import lilylib
-
-
-NOT_SMART = "\n" + _("Not smart enough to convert %s.") + "\n"
-UPDATE_MANUALLY = _(
-    "Please refer to the manual for details, and update manually.") + "\n"
-FROM_TO = _("%s has been replaced by %s") + "\n"
-
-
-class FatalConversionError(Exception):
-    pass
-
-
-conversions = []
-stderr_write = sys.stderr.write
-
-
-def warning(s):
-    stderr_write(_("warning: %s") % s)
-
-# Decorator to make rule syntax simpler
-
-
-def rule(version, message):
-    """
-    version: a LilyPond version tuple like (2, 11, 50)
-    message: the message that describes the conversion.
-
-    This decorator adds its function together with the version and the
-    message to the global conversions list.  (It doesn't need to return
-    the function as it isn't used directly anyway.)
-
-    A conversion rule using this decorator looks like this:
-
-    @rule ((1, 2, 3), "convert foo to bar")
-    def conv(s):
-        s = s.replace('foo', 'bar')
-        return s
-
-    """
-    def dec(f):
-        conversions.append((version, f, message))
-    return dec
-
-
-@rule((0, 1, 9), _('\\header { key = concat + with + operator }'))
-def conv(s):
-    if re.search('\\\\multi', s):
-        stderr_write(NOT_SMART % "\\multi")
-    return s
-
-
-@rule((0, 1, 19), _('deprecated %s') % '\\octave')
-def conv(s):
-    if re.search('\\\\octave', s):
-        stderr_write(NOT_SMART % "\\octave")
-        stderr_write(UPDATE_MANUALLY)
-    #   raise FatalConversionError ()
-    return s
-
-
-@rule((0, 1, 20), _('deprecated \\textstyle, new \\key syntax'))
-def conv(s):
-    s = re.sub('\\\\textstyle([^;]+);',
-                 '\\\\property Lyrics . textstyle = \\1', s)
-    # harmful to current .lys
-    # s = re.sub ('\\\\key([^;]+);', '\\\\accidentals \\1;', s)
-    return s
-
-
-@rule((0, 1, 21), '\\musical_pitch -> \\musicalpitch, \\meter -> \\time')
-def conv(s):
-    s = re.sub('\\\\musical_pitch', '\\\\musicalpitch', s)
-    s = re.sub('\\\\meter', '\\\\time', s)
-    return s
-
-
-@rule((1, 0, 0), _("bump version for release"))
-def conv(s):
-    return s
-
-
-@rule((1, 0, 1), '\\accidentals -> \\keysignature, specialaccidentals -> keyoctaviation')
-def conv(s):
-    s = re.sub('\\\\accidentals', '\\\\keysignature', s)
-    s = re.sub('specialaccidentals *= *1', 'keyoctaviation = 0', s)
-    s = re.sub('specialaccidentals *= *0', 'keyoctaviation = 1', s)
-    return s
-
-
-@rule((1, 0, 2), _('\\header { key = concat + with + operator }'))
-def conv(s):
-    if re.search('\\\\header', s):
-        stderr_write(NOT_SMART % _("new \\header format"))
-    return s
-
-
-@rule((1, 0, 3), '\\melodic -> \\notes')
-def conv(s):
-    s = re.sub('\\\\melodic([^a-zA-Z])', '\\\\notes\\1', s)
-    return s
-
-
-@rule((1, 0, 4), 'default_{paper,midi}')
-def conv(s):
-    s = re.sub('default_paper *=', '', s)
-    s = re.sub('default_midi *=', '', s)
-    return s
-
-
-@rule((1, 0, 5), 'ChoireStaff -> ChoirStaff')
-def conv(s):
-    s = re.sub('ChoireStaff', 'ChoirStaff', s)
-    s = re.sub('\\\\output', 'output = ', s)
-    return s
-
-
-@rule((1, 0, 6), 'foo = \\translator {\\type .. } ->\\translator {\\type ..; foo; }')
-def conv(s):
-    if re.search('[a-zA-Z]+ = *\\translator', s):
-        stderr_write(NOT_SMART % _("\\translator syntax"))
-    #   raise FatalConversionError ()
-    return s
-
-
-@rule((1, 0, 7), '\\lyric -> \\lyrics')
-def conv(s):
-    s = re.sub('\\\\lyrics*', '\\\\lyrics', s)
-    return s
-
-
-@rule((1, 0, 10), '[2/3 ]1/1 -> \\times 2/3 ')
-def conv(s):
-    s = re.sub('\\\\\\[/3+', '\\\\times 2/3 { ', s)
-    s = re.sub('\\[/3+', '\\\\times 2/3 { [', s)
-    s = re.sub('\\\\\\[([0-9/]+)', '\\\\times \\1 {', s)
-    s = re.sub('\\[([0-9/]+)', '\\\\times \\1 { [', s)
-    s = re.sub('\\\\\\]([0-9/]+)', '}', s)
-    s = re.sub('\\\\\\]', '}', s)
-    s = re.sub('\\]([0-9/]+)', '] }', s)
-    return s
-
-
-@rule((1, 0, 12), 'Chord syntax stuff')
-def conv(s):
-    return s
-
-
-@rule((1, 0, 13), '<a ~ b> c -> <a b> ~ c')
-def conv(s):
-    s = re.sub('<([^>~]+)~([^>]*)>', '<\\1 \\2> ~', s)
-    return s
-
-
-@rule((1, 0, 14), '<[a b> <a b]>c -> [<a b> <a b>]')
-def conv(s):
-    s = re.sub('<\\[', '[<', s)
-    s = re.sub('\\]>', '>]', s)
-    return s
-
-
-@rule((1, 0, 16), '\\type -> \\context, textstyle -> textStyle')
-def conv(s):
-    s = re.sub('\\\\type([^\n]*engraver)', '\\\\TYPE\\1', s)
-    s = re.sub('\\\\type([^\n]*performer)', '\\\\TYPE\\1', s)
-    s = re.sub('\\\\type', '\\\\context', s)
-    s = re.sub('\\\\TYPE', '\\\\type', s)
-    s = re.sub('textstyle', 'textStyle', s)
-    return s
-
-
-@rule((1, 0, 18), _('\\repeat NUM Music Alternative -> \\repeat FOLDSTR Music Alternative'))
-def conv(s):
-    if re.search('\\\\repeat', s):
-        stderr_write(NOT_SMART % "\\repeat")
-    #   raise FatalConversionError ()
-    return s
-
-
-@rule((1, 0, 19), 'fontsize -> fontSize, midi_instrument -> midiInstrument, SkipBars -> skipBars')
-def conv(s):
-    s = re.sub('SkipBars', 'skipBars', s)
-    s = re.sub('fontsize', 'fontSize', s)
-    s = re.sub('midi_instrument', 'midiInstrument', s)
-    return s
-
-
-@rule((1, 0, 20), '{,tie,slur}ydirection -> {v,tieV,slurV}erticalDirection')
-def conv(s):
-    s = re.sub('tieydirection', 'tieVerticalDirection', s)
-    s = re.sub('slurydirection', 'slurVerticalDirection', s)
-    s = re.sub('ydirection', 'verticalDirection', s)
-    return s
-
-
-@rule((1, 0, 21), 'hshift -> horizontalNoteShift')
-def conv(s):
-    s = re.sub('hshift', 'horizontalNoteShift', s)
-    return s
-
-
-@rule((1, 1, 52), _('deprecate %s') % '\\grouping')
-def conv(s):
-    s = re.sub('\\\\grouping[^;]*;', '', s)
-    return s
-
-
-@rule((1, 1, 55), '\\wheel -> \\coda')
-def conv(s):
-    s = re.sub('\\\\wheel', '\\\\coda', s)
-    return s
-
-
-@rule((1, 1, 65), 'slurdash -> slurDash, keyoctaviation -> keyOctaviation')
-def conv(s):
-    s = re.sub('keyoctaviation', 'keyOctaviation', s)
-    s = re.sub('slurdash', 'slurDash', s)
-    return s
-
-
-@rule((1, 1, 66), 'semi -> volta')
-def conv(s):
-    s = re.sub('\\\\repeat *"?semi"?', '\\\\repeat "volta"', s)
-    return s
-
-
-@rule((1, 1, 67), 'beamAuto -> noAutoBeaming')
-def conv(s):
-    s = re.sub('"?beamAuto"? *= *"?0?"?', 'noAutoBeaming = "1"', s)
-    return s
-
-
-@rule((1, 2, 0), 'automaticMelismas -> automaticMelismata')
-def conv(s):
-    s = re.sub('automaticMelismas', 'automaticMelismata', s)
-    return s
-
-
-@rule((1, 2, 1), 'dynamicDir -> dynamicDirection')
-def conv(s):
-    s = re.sub('dynamicDir\\b', 'dynamicDirection', s)
-    return s
-
-
-@rule((1, 3, 4), '\\cadenza -> \\cadenza{On|Off}')
-def conv(s):
-    s = re.sub('\\\\cadenza *0 *;', '\\\\cadenzaOff', s)
-    s = re.sub('\\\\cadenza *1 *;', '\\\\cadenzaOn', s)
-    return s
-
-
-@rule((1, 3, 5), 'beamAuto moment properties')
-def conv(s):
-    s = re.sub('"?beamAuto([^"=]+)"? *= *"([0-9]+)/([0-9]+)" *;*',
-                 'beamAuto\\1 = #(make-moment \\2 \\3)',
-                 s)
-    return s
-
-
-@rule((1, 3, 17), 'stemStyle -> flagStyle')
-def conv(s):
-    s = re.sub('stemStyle',
-                 'flagStyle',
-                 s)
-    return s
-
-
-@rule((1, 3, 18), 'staffLineLeading -> staffSpace')
-def conv(s):
-    s = re.sub('staffLineLeading',
-                 'staffSpace',
-                 s)
-    return s
-
-
-@rule((1, 3, 23), _('deprecate %s ') % '\\repetitions')
-def conv(s):
-    if re.search('\\\\repetitions', s):
-        stderr_write(NOT_SMART % "\\repetitions")
-    #   raise FatalConversionError ()
-    return s
-
-
-@rule((1, 3, 35), 'textEmptyDimension -> textNonEmpty')
-def conv(s):
-    s = re.sub('textEmptyDimension *= *##t',
-                 'textNonEmpty = ##f',
-                 s)
-    s = re.sub('textEmptyDimension *= *##f',
-                 'textNonEmpty = ##t',
-                 s)
-    return s
-
-
-@rule((1, 3, 38), r"\musicalpitch { a b c } -> #'(a b c)")
-def conv(s):
-    s = re.sub("([a-z]+)[ \t]*=[ \t]*\\\\musicalpitch *{([- 0-9]+)} *\n",
-                 "(\\1 . (\\2))\n", s)
-    s = re.sub("\\\\musicalpitch *{([0-9 -]+)}",
-                 "\\\\musicalpitch #'(\\1)", s)
-    if re.search('\\\\notenames', s):
-        stderr_write(NOT_SMART % _("new \\notenames format"))
-    return s
-
-
-@rule((1, 3, 39), '\\key A ;  ->\\key a;')
-def conv(s):
-    def replace(match):
-        return '\\key %s;' % match.group(1).lower()
-
-    s = re.sub("\\\\key ([^;]+);",  replace, s)
-    return s
-
-
-@rule((1, 3, 41), '[:16 c4 d4 ] -> \\repeat "tremolo" 2 { c16 d16 }')
-def conv(s):
-    if re.search('\\[:', s):
-        stderr_write(NOT_SMART % _("new tremolo format"))
-    return s
-
-
-@rule((1, 3, 42), _('Staff_margin_engraver deprecated, use Instrument_name_engraver'))
-def conv(s):
-    s = re.sub('Staff_margin_engraver', 'Instrument_name_engraver', s)
-    return s
-
-
-@rule((1, 3, 49), 'noteHeadStyle value: string -> symbol')
-def conv(s):
-    s = re.sub('note[hH]eadStyle\\s*=\\s*"?(\\w+)"?',
-                 "noteHeadStyle = #'\\1", s)
-    return s
-
-
-@rule((1, 3, 58), 'noteHeadStyle value: string -> symbol')
-def conv(s):
-    if re.search('\\\\keysignature', s):
-        stderr_write(NOT_SMART % '\\keysignature')
-    return s
-
-
-@rule((1, 3, 59), r'\key X ; -> \key X major; ')
-def conv(s):
-    s = re.sub(r"""\\key *([a-z]+) *;""", r"""\\key \1 \\major;""", s)
-    return s
-
-
-@rule((1, 3, 68), 'latexheaders = "\\input global" -> latexheaders = "global"')
-def conv(s):
-    s = re.sub(r'latexheaders *= *"\\\\input ',
-                 'latexheaders = "',
-                 s)
-    return s
-
-
-# TODO: lots of other syntax changes should be done here as well
-@rule((1, 3, 92), 'basicXXXProperties -> XXX, Repeat_engraver -> Volta_engraver')
-def conv(s):
-    s = re.sub('basicCollisionProperties', 'NoteCollision', s)
-    s = re.sub('basicVoltaSpannerProperties', "VoltaBracket", s)
-    s = re.sub('basicKeyProperties', "KeySignature", s)
-
-    s = re.sub('basicClefItemProperties', "Clef", s)
-
-    s = re.sub('basicLocalKeyProperties', "Accidentals", s)
-    s = re.sub('basicMarkProperties', "Accidentals", s)
-    s = re.sub('basic([A-Za-z_]+)Properties', '\\1', s)
-
-    s = re.sub('Repeat_engraver', 'Volta_engraver', s)
-    return s
-
-
-@rule((1, 3, 93), _('change property definition case (eg. onevoice -> oneVoice)'))
-def conv(s):
-    # Ugh, but meaning of \stemup changed too
-    # maybe we should do \stemup -> \stemUp\slurUp\tieUp ?
-    s = re.sub('\\\\stemup', '\\\\stemUp', s)
-    s = re.sub('\\\\stemdown', '\\\\stemDown', s)
-    s = re.sub('\\\\stemboth', '\\\\stemBoth', s)
-
-    s = re.sub('\\\\slurup', '\\\\slurUp', s)
-    s = re.sub('\\\\slurboth', '\\\\slurBoth', s)
-    s = re.sub('\\\\slurdown', '\\\\slurDown', s)
-    s = re.sub('\\\\slurdotted', '\\\\slurDotted', s)
-    s = re.sub('\\\\slurnormal', '\\\\slurNoDots', s)
-
-    s = re.sub('\\\\shiftoff', '\\\\shiftOff', s)
-    s = re.sub('\\\\shifton', '\\\\shiftOn', s)
-    s = re.sub('\\\\shiftonn', '\\\\shiftOnn', s)
-    s = re.sub('\\\\shiftonnn', '\\\\shiftOnnn', s)
-
-    s = re.sub('\\\\onevoice', '\\\\oneVoice', s)
-    s = re.sub('\\\\voiceone', '\\\\voiceOne', s)
-    s = re.sub('\\\\voicetwo', '\\\\voiceTwo', s)
-    s = re.sub('\\\\voicethree', '\\\\voiceThree', s)
-    s = re.sub('\\\\voicefour', '\\\\voiceFour', s)
-
-    # I don't know exactly when these happened...
-    # ugh, we lose context setting here...
-    s = re.sub('\\\\property *[^ ]*verticalDirection[^=]*= *#?"?(1|(\\\\up))"?',
-                 '\\\\stemUp\\\\slurUp\\\\tieUp', s)
-    s = re.sub('\\\\property *[^ ]*verticalDirection[^=]*= *#?"?((-1)|(\\\\down))"?',
-                 '\\\\stemDown\\\\slurDown\\\\tieDown', s)
-    s = re.sub('\\\\property *[^ ]*verticalDirection[^=]*= *#?"?(0|(\\\\center))"?',
-                 '\\\\stemBoth\\\\slurBoth\\\\tieBoth', s)
-
-    s = re.sub('verticalDirection[^=]*= *#?"?(1|(\\\\up))"?',
-                 'Stem \\\\override #\'direction = #0\nSlur \\\\override #\'direction = #0\n Tie \\\\override #\'direction = #1', s)
-    s = re.sub('verticalDirection[^=]*= *#?"?((-1)|(\\\\down))"?',
-                 'Stem \\\\override #\'direction = #0\nSlur \\\\override #\'direction = #0\n Tie \\\\override #\'direction = #-1', s)
-    s = re.sub('verticalDirection[^=]*= *#?"?(0|(\\\\center))"?',
-                 'Stem \\\\override #\'direction = #0\nSlur \\\\override #\'direction = #0\n Tie \\\\override #\'direction = #0', s)
-
-    s = re.sub(
-        '\\\\property *[^ .]*[.]?([a-z]+)VerticalDirection[^=]*= *#?"?(1|(\\\\up))"?', '\\\\\\1Up', s)
-    s = re.sub(
-        '\\\\property *[^ .]*[.]?([a-z]+)VerticalDirection[^=]*= *#?"?((-1)|(\\\\down))"?', '\\\\\\1Down', s)
-    s = re.sub(
-        '\\\\property *[^ .]*[.]?([a-z]+)VerticalDirection[^=]*= *#?"?(0|(\\\\center))"?', '\\\\\\1Both', s)
-
-    # (lacks capitalization slur -> Slur)
-    s = re.sub('([a-z]+)VerticalDirection[^=]*= *#?"?(1|(\\\\up))"?',
-                 '\\1 \\\\override #\'direction = #1', s)
-    s = re.sub('([a-z]+)VerticalDirection[^=]*= *#?"?((-1)|(\\\\down))"?',
-                 '\\1 \\\\override #\'direction = #-1', s)
-    s = re.sub('([a-z]+)VerticalDirection[^=]*= *#?"?(0|(\\\\center))"?',
-                 '\\1 \\\\override #\'direction = #0', s)
-
-    # dynamic..
-    s = re.sub(
-        '\\\\property *[^ .]*[.]?dynamicDirection[^=]*= *#?"?(1|(\\\\up))"?', '\\\\dynamicUp', s)
-    s = re.sub(
-        '\\\\property *[^ .]*[.]?dyn[^=]*= *#?"?((-1)|(\\\\down))"?', '\\\\dynamicDown', s)
-    s = re.sub(
-        '\\\\property *[^ .]*[.]?dyn[^=]*= *#?"?(0|(\\\\center))"?', '\\\\dynamicBoth', s)
-
-    s = re.sub(
-        '\\\\property *[^ .]*[.]?([a-z]+)Dash[^=]*= *#?"?(0|(""))"?', '\\\\\\1NoDots', s)
-    s = re.sub(
-        '\\\\property *[^ .]*[.]?([a-z]+)Dash[^=]*= *#?"?([1-9]+)"?', '\\\\\\1Dotted', s)
-
-    s = re.sub(
-        '\\\\property *[^ .]*[.]?noAutoBeaming[^=]*= *#?"?(0|(""))"?', '\\\\autoBeamOn', s)
-    s = re.sub(
-        '\\\\property *[^ .]*[.]?noAutoBeaming[^=]*= *#?"?([1-9]+)"?', '\\\\autoBeamOff', s)
-    return s
-
-
-@rule((1, 3, 97), 'ChordName -> ChordNames')
-def conv(s):
-    s = re.sub('ChordNames*', 'ChordNames', s)
-    if re.search('\\\\textscript "[^"]* *"[^"]*"', s):
-        stderr_write(NOT_SMART % _("new \\textscript markup text"))
-
-    s = re.sub('\\textscript +("[^"]*")', '\\textscript #\\1', s)
-    return s
-
-# TODO: add lots of these
-
-
-@rule((1, 3, 98), 'CONTEXT.textStyle -> GROB.#font-style ')
-def conv(s):
-    s = re.sub('\\\\property *"?Voice"? *[.] *"?textStyle"? *= *"([^"]*)"',
-                 '\\\\property Voice.TextScript \\\\set #\'font-style = #\'\\1', s)
-    s = re.sub('\\\\property *"?Lyrics"? *[.] *"?textStyle"? *= *"([^"]*)"',
-                 '\\\\property Lyrics.LyricText \\\\set #\'font-style = #\'\\1', s)
-
-    s = re.sub('\\\\property *"?([^.]+)"? *[.] *"?timeSignatureStyle"? *= *"([^"]*)"',
-                 '\\\\property \\1.TimeSignature \\\\override #\'style = #\'\\2', s)
-
-    s = re.sub('"?timeSignatureStyle"? *= *#?""',
-                 'TimeSignature \\\\override #\'style = ##f', s)
-
-    s = re.sub('"?timeSignatureStyle"? *= *#?"([^"]*)"',
-                 'TimeSignature \\\\override #\'style = #\'\\1', s)
-
-    s = re.sub('#\'style *= #*"([^"])"', '#\'style = #\'\\1', s)
-
-    s = re.sub('\\\\property *"?([^.]+)"? *[.] *"?horizontalNoteShift"? *= *"?#?([-0-9]+)"?',
-                 '\\\\property \\1.NoteColumn \\\\override #\'horizontal-shift = #\\2', s)
-
-    # ugh
-    s = re.sub('\\\\property *"?([^.]+)"? *[.] *"?flagStyle"? *= *""',
-                 '\\\\property \\1.Stem \\\\override #\'flag-style = ##f', s)
-
-    s = re.sub('\\\\property *"?([^.]+)"? *[.] *"?flagStyle"? *= *"([^"]*)"',
-                 '\\\\property \\1.Stem \\\\override #\'flag-style = #\'\\2', s)
-    return s
-
-
-@rule((1, 3, 102), 'beamAutoEnd -> autoBeamSettings \\push (end * * * *)')
-def conv(s):
-    s = re.sub('"?beamAutoEnd_([0-9]*)"? *= *(#\\([^)]*\\))',
-                 'autoBeamSettings \\\\push #\'(end 1 \\1 * *) = \\2', s)
-    s = re.sub('"?beamAutoBegin_([0-9]*)"? *= *(#\\([^)]*\\))',
-                 'autoBeamSettings \\\\push #\'(begin 1 \\1 * *) = \\2', s)
-    s = re.sub('"?beamAutoEnd"? *= *(#\\([^)]*\\))',
-                 'autoBeamSettings \\\\push #\'(end * * * *) = \\1', s)
-    s = re.sub('"?beamAutoBegin"? *= *(#\\([^)]*\\))',
-                 'autoBeamSettings \\\\push #\'(begin * * * *) = \\1', s)
-    return s
-
-
-@rule((1, 3, 111), '\\push -> \\override, \\pop -> \\revert')
-def conv(s):
-    s = re.sub('\\\\push', '\\\\override', s)
-    s = re.sub('\\\\pop', '\\\\revert', s)
-    return s
-
-
-@rule((1, 3, 113), 'LyricVoice -> LyricsVoice')
-def conv(s):
-    s = re.sub('LyricVoice', 'LyricsVoice', s)
-    # old fix
-    s = re.sub('Chord[Nn]ames*.Chord[Nn]ames*', 'ChordNames.ChordName', s)
-    s = re.sub('Chord[Nn]ames([ \t\n]+\\\\override)', 'ChordName\\1', s)
-    return s
-
-
-def regularize_id(s):
-    s = ''
-    lastx = ''
-    for x in s:
-        if x == '_':
-            lastx = x
-            continue
-        elif x in string.digits:
-            x = chr(ord(x) - ord('0') + ord('A'))
-        elif x not in string.letters:
-            x = 'x'
-        elif x in string.lowercase and lastx == '_':
-            x = x.upper()
-        s = s + x
-        lastx = x
-    return s
-
-
-@rule((1, 3, 117), _('identifier names: %s') % '$!foo_bar_123 -> xfooBarABC')
-def conv(s):
-    def regularize_dollar_reference(match):
-        return regularize_id(match.group(1))
-
-    def regularize_assignment(match):
-        return '\n' + regularize_id(match.group(1)) + ' = '
-    s = re.sub(r'\$([^\t\n ]+)', regularize_dollar_reference, s)
-    s = re.sub('\n([^ \t\n]+)[ \t]*= *', regularize_assignment, s)
-    return s
-
-
-@rule((1, 3, 120), 'paper_xxx -> paperXxxx, pedalup -> pedalUp.')
-def conv(s):
-    def regularize_paper(match):
-        return regularize_id(match.group(1))
-    s = re.sub('(paper_[a-z]+)', regularize_paper, s)
-    s = re.sub('sustainup', 'sustainUp', s)
-    s = re.sub('nobreak', 'noBreak', s)
-    s = re.sub('sustaindown', 'sustainDown', s)
-    s = re.sub('sostenutoup', 'sostenutoUp', s)
-    s = re.sub('sostenutodown', 'sostenutoDown', s)
-    s = re.sub('unachorda', 'unaChorda', s)
-    s = re.sub('trechorde', 'treChorde', s)
-    return s
-
-
-@rule((1, 3, 122), 'drarnChords -> chordChanges, \\musicalpitch -> \\pitch')
-def conv(s):
-    s = re.sub('drarnChords', 'chordChanges', s)
-    s = re.sub(r'\\musicalpitch', r'\\pitch', s)
-    return s
-
-
-@rule((1, 3, 136), 'ly-X-elt-property -> ly-X-grob-property')
-def conv(s):
-    s = re.sub('ly-([sg])et-elt-property', 'ly-\\1et-grob-property', s)
-    return s
-
-
-@rule((1, 3, 138), _('point-and-click argument changed to procedure.'))
-def conv(s):
-    s = re.sub('point-and-click +#t',
-                 'point-and-click line-column-location', s)
-    return s
-
-
-@rule((1, 3, 138), 'followThread -> followVoice.')
-def conv(s):
-    s = re.sub('followThread', 'followVoice', s)
-    s = re.sub('Thread.FollowThread', 'Voice.VoiceFollower', s)
-    s = re.sub('FollowThread', 'VoiceFollower', s)
-    return s
-
-
-@rule((1, 3, 139), 'font-point-size -> font-design-size.')
-def conv(s):
-    s = re.sub('font-point-size', 'font-design-size', s)
-    return s
-
-
-@rule((1, 3, 141), 'xNoDots -> xSolid')
-def conv(s):
-    s = re.sub('([a-zA-Z]*)NoDots', '\\1Solid', s)
-    return s
-
-
-@rule((1, 3, 144), 'Chorda -> Corda')
-def conv(s):
-    s = re.sub('([Cc])hord([ea])', '\\1ord\\2', s)
-    return s
-
-
-@rule((1, 3, 145), 'ContextNameXxxxVerticalExtent -> XxxxVerticalExtent')
-def conv(s):
-    s = re.sub('([A-Za-z]+)MinimumVerticalExtent',
-                 'MinimumV@rticalExtent', s)
-    s = re.sub('([A-Za-z]+)ExtraVerticalExtent', 'ExtraV@rticalExtent', s)
-    s = re.sub('([A-Za-z]+)VerticalExtent', 'VerticalExtent', s)
-    s = re.sub('ExtraV@rticalExtent', 'ExtraVerticalExtent', s)
-    s = re.sub('MinimumV@rticalExtent', 'MinimumVerticalExtent', s)
-    return s
-
-
-@rule((1, 3, 146), _('semicolons removed'))
-def conv(s):
-    s = re.sub('\\\\key[ \t]*;', r'\\key \\default;', s)
-    s = re.sub('\\\\mark[ \t]*;', r'\\mark \\default;', s)
-
-    # Make sure groups of more than one ; have space before
-    # them, so that non of them gets removed by next rule
-    s = re.sub("([^ \n\t;]);(;+)", "\\1 ;\\2", s)
-
-    # Only remove ; that are not after spaces, # or ;
-    # Otherwise  we interfere with Scheme comments,
-    # which is badbadbad.
-    s = re.sub("([^ \t;#]);", "\\1", s)
-    return s
-
-
-@rule((1, 3, 147), 'default-neutral-direction -> neutral-direction')
-def conv(s):
-    s = re.sub('default-neutral-direction', 'neutral-direction', s)
-    return s
-
-
-@rule((1, 3, 148), '"(align" -> "(axis", "(rows" -> "(columns"')
-def conv(s):
-    s = re.sub(r'\(align', '(axis', s)
-    s = re.sub(r'\(rows', '(columns', s)
-    return s
-
-
-@rule((1, 5, 33), 'SystemStartDelimiter -> systemStartDelimiter')
-def conv(s):
-    s = re.sub('SystemStartDelimiter', 'systemStartDelimiter', s)
-    return s
-
-
-@rule((1, 5, 38), 'arithmetic... -> spacing...')
-def conv(s):
-    s = re.sub('arithmetic-multiplier', 'spacing-increment', s)
-    s = re.sub('arithmetic-basicspace', 'shortest-duration-space', s)
-    return s
-
-
-# 40 ?
-@rule((1, 5, 40), _('%s property names') % 'breakAlignOrder')
-def conv(s):
-
-    def func(match):
-        break_dict = {
-            "Instrument_name": "instrument-name",
-            "Left_edge_item": "left-edge",
-            "Span_bar": "span-bar",
-            "Breathing_sign": "breathing-sign",
-            "Staff_bar": "staff-bar",
-            "Clef_item": "clef",
-            "Key_item": "key-signature",
-            "Time_signature": "time-signature",
-            "Custos": "custos"
-        }
-        props = match.group(1)
-        for (k, v) in list(break_dict.items()):
-            props = re.sub(k, v, props)
-        return "breakAlignOrder = #'(%s)" % props
-
-    s = re.sub("breakAlignOrder *= *#'\\(([a-z_\n\tA-Z ]+)\\)",
-                 func, s)
-    return s
-
-
-@rule((1, 5, 49), 'noAutoBeaming -> autoBeaming')
-def conv(s):
-    s = re.sub('noAutoBeaming *= *##f', 'autoBeaming = ##t', s)
-    s = re.sub('noAutoBeaming *= *##t', 'autoBeaming = ##f', s)
-    return s
-
-
-@rule((1, 5, 52), 'tuplet-X-visibility -> X-visibility')
-def conv(s):
-    s = re.sub('tuplet-bracket-visibility', 'bracket-visibility', s)
-    s = re.sub('tuplet-number-visibility', 'number-visibility', s)
-    return s
-
-
-@rule((1, 5, 56), 'Pitch::transpose -> ly-transpose-pitch')
-def conv(s):
-    s = re.sub('Pitch::transpose', 'ly-transpose-pitch', s)
-    return s
-
-
-@rule((1, 5, 58), _('deprecate %s') % 'textNonEmpty')
-def conv(s):
-    s = re.sub('textNonEmpty *= *##t',
-                 "TextScript \\\\set #'no-spacing-rods = ##f", s)
-    s = re.sub('textNonEmpty *= *##f',
-                 "TextScript \\\\set #'no-spacing-rods = ##t", s)
-    return s
-
-
-@rule((1, 5, 59), 'XxxxVerticalExtent -> xxxVerticalExtent')
-def conv(s):
-    s = re.sub('MinimumVerticalExtent', 'minimumV@rticalExtent', s)
-    s = re.sub('minimumVerticalExtent', 'minimumV@rticalExtent', s)
-    s = re.sub('ExtraVerticalExtent', 'extraV@rticalExtent', s)
-    s = re.sub('extraVerticalExtent', 'extraV@rticalExtent', s)
-    s = re.sub('VerticalExtent', 'verticalExtent', s)
-    s = re.sub('extraV@rticalExtent', 'extraVerticalExtent', s)
-    s = re.sub('minimumV@rticalExtent', 'minimumVerticalExtent', s)
-    return s
-
-
-@rule((1, 5, 62), 'visibility-lambda -> break-visibility')
-def conv(s):
-    s = re.sub('visibility-lambda', 'break-visibility', s)
-    return s
-
-
-@rule((1, 5, 67), _('automaticMelismata turned on by default'))
-def conv(s):
-    if re.search(r'\addlyrics', s) \
-            and re.search('automaticMelismata', s) is None:
-        stderr_write(NOT_SMART % "automaticMelismata")
-        stderr_write(
-            _("automaticMelismata is turned on by default since 1.5.67."))
-        stderr_write('\n')
-        raise FatalConversionError()
-    return s
-
-
-@rule((1, 5, 68), 'ly-set-X-property -> ly-set-X-property!')
-def conv(s):
-    s = re.sub('ly-set-grob-property([^!])', 'ly-set-grob-property!\1', s)
-    s = re.sub('ly-set-mus-property([^!])', 'ly-set-mus-property!\1', s)
-    return s
-
-
-@rule((1, 5, 71), 'extent-[XY] -> [XY]-extent')
-def conv(s):
-    s = re.sub('extent-X', 'X-extent', s)
-    s = re.sub('extent-Y', 'Y-extent', s)
-    return s
-
-
-@rule((1, 5, 72), 'set! point-and-click -> set-point-and-click!')
-def conv(s):
-    s = re.sub(r"#\(set! +point-and-click +line-column-location\)",
-                 "#(set-point-and-click! 'line-column)", s)
-    s = re.sub(r"#\(set![ \t]+point-and-click +line-location\)",
-                 "#(set-point-and-click! 'line)", s)
-    s = re.sub(r'#\(set! +point-and-click +#f\)',
-                 "#(set-point-and-click! 'none)", s)
-    return s
-
-
-@rule((1, 6, 5), 'Stems: flag-style -> stroke-style; style -> flag-style')
-def conv(s):
-    s = re.sub('flag-style', 'stroke-style', s)
-    s = re.sub(r"""Stem([ ]+)\\override #'style""",
-                 r"""Stem \\override #'flag-style""", s)
-    s = re.sub(r"""Stem([ ]+)\\set([ ]+)#'style""",
-                 r"""Stem \\set #'flag-style""", s)
-    return s
-
-
-def subst_req_name(match):
-    return "(make-music-by-name \'%sEvent)" % regularize_id(match.group(1))
-
-
-@rule((1, 7, 1), 'ly-make-music foo_bar_req -> make-music-by-name FooBarEvent')
-def conv(s):
-    s = re.sub(
-        '\\(ly-make-music *"([A-Z][a-z_]+)_req"\\)', subst_req_name, s)
-    s = re.sub('Request_chord', 'EventChord', s)
-    return s
-
-
-spanner_subst = {
-    "text": 'TextSpanEvent',
-    "decrescendo": 'DecrescendoEvent',
-    "crescendo": 'CrescendoEvent',
-    "Sustain": 'SustainPedalEvent',
-    "slur": 'SlurEvent',
-    "UnaCorda": 'UnaCordaEvent',
-    "Sostenuto": 'SostenutoEvent',
-}
-
-
-def subst_ev_name(match):
-    stype = 'STOP'
-    if re.search('start', match.group(1)):
-        stype = 'START'
-    mtype = spanner_subst[match.group(2)]
-    return "(make-span-event '%s %s)" % (mtype, stype)
-
-
-def subst_definition_ev_name(match):
-    return ' = #%s' % subst_ev_name(match)
-
-
-def subst_inline_ev_name(match):
-    s = subst_ev_name(match)
-    return '#(ly-export %s)' % s
-
-
-def subst_csp_definition(match):
-    return ' = #(make-event-chord (list %s))' % subst_ev_name(match)
-
-
-def subst_csp_inline(match):
-    return '#(ly-export (make-event-chord (list %s)))' % subst_ev_name(match)
-
-
-@rule((1, 7, 2), r'\\spanrequest -> #(make-span-event .. ), \script -> #(make-articulation .. )')
-def conv(s):
-    s = re.sub(
-        r' *= *\\spanrequest *([^ ]+) *"([^"]+)"', subst_definition_ev_name, s)
-    s = re.sub(
-        r'\\spanrequest *([^ ]+) *"([^"]+)"', subst_inline_ev_name, s)
-    s = re.sub(
-        r' *= *\\commandspanrequest *([^ ]+) *"([^"]+)"', subst_csp_definition, s)
-    s = re.sub(
-        r'\\commandspanrequest *([^ ]+) *"([^"]+)"', subst_csp_inline, s)
-    s = re.sub(r'ly-id ', 'ly-import ', s)
-
-    s = re.sub(r' *= *\\script "([^"]+)"',
-                 ' = #(make-articulation "\\1")', s)
-    s = re.sub(r'\\script "([^"]+)"',
-                 '#(ly-export (make-articulation "\\1"))', s)
-    return s
-
-
-@rule((1, 7, 3), 'ly- -> ly:')
-def conv(s):
-    s = re.sub(r'\(ly-', '(ly:', s)
-
-    changed = [
-        r'duration\?',
-        r'font-metric\?',
-        r'molecule\?',
-        r'moment\?',
-        r'music\?',
-        r'pitch\?',
-        'make-duration',
-        'music-duration-length',
-        'duration-log',
-        'duration-dotcount',
-        'intlog2',
-        'duration-factor',
-        'transpose-key-alist',
-        'get-system',
-        'get-broken-into',
-        'get-original',
-        'set-point-and-click!',
-        'make-moment',
-        'make-pitch',
-        'pitch-octave',
-        'pitch-alteration',
-        'pitch-notename',
-        'pitch-semitones',
-        r'pitch<\?',
-        r'dir\?',
-        'music-duration-compress',
-        'set-point-and-click!'
-    ]
-
-    origre = r'\b(%s)' % '|'.join(changed)
-
-    s = re.sub(origre, r'ly:\1', s)
-    s = re.sub('set-point-and-click!', 'set-point-and-click', s)
-    return s
-
-
-@rule((1, 7, 4), '<< >> -> < <  > >')
-def conv(s):
-    if re.search('new-chords-done', s):
-        return s
-
-    s = re.sub(r'<<', '< <', s)
-    s = re.sub(r'>>', '> >', s)
-    return s
-
-
-@rule((1, 7, 5), '\\transpose TO -> \\transpose FROM  TO')
-def conv(s):
-    s = re.sub(r"\\transpose", r"\\transpose c'", s)
-    s = re.sub(r"\\transpose c' *([a-z]+)'", r"\\transpose c \1", s)
-    return s
-
-
-@rule((1, 7, 6), r'note\\script -> note-\script')
-def conv(s):
-    kws = ['arpeggio',
-           'sustainDown',
-           'sustainUp',
-           'f',
-           'p',
-           'pp',
-           'ppp',
-           'fp',
-           'ff',
-           'mf',
-           'mp',
-           'sfz',
-           ]
-
-    origstr = '|'.join(kws)
-    s = re.sub(r'([^_^-])\\(%s)\b' % origstr, r'\1-\\\2', s)
-    return s
-
-
-@rule((1, 7, 10), r"\property ChordName #'style -> #(set-chord-name-style 'style)")
-def conv(s):
-    s = re.sub(r"\\property *ChordNames *\. *ChordName *\\(set|override) *#'style *= *#('[a-z]+)",
-                 r"#(set-chord-name-style \2)", s)
-    s = re.sub(r"\\property *ChordNames *\. *ChordName *\\revert *#'style",
-                 r"", s)
-    return s
-
-
-@rule((1, 7, 11), "transpose-pitch -> pitch-transpose")
-def conv(s):
-    s = re.sub(r"ly:transpose-pitch", "ly:pitch-transpose", s)
-    return s
-
-
-@rule((1, 7, 13), "ly:XX-molecule-YY -> ly:molecule-XX-YY")
-def conv(s):
-    s = re.sub(r"ly:get-molecule-extent", "ly:molecule-get-extent", s)
-    s = re.sub(r"ly:set-molecule-extent!", "ly:molecule-set-extent!", s)
-    s = re.sub(r"ly:add-molecule", "ly:molecule-add", s)
-    s = re.sub(r"ly:combine-molecule-at-edge",
-                 "ly:molecule-combine-at-edge", s)
-    s = re.sub(r"ly:align-to!", "ly:molecule-align-to!", s)
-    return s
-
-
-@rule((1, 7, 15), "linewidth = -1 -> raggedright = ##t")
-def conv(s):
-    s = re.sub(
-        r"linewidth *= *-[0-9.]+ *(\\mm|\\cm|\\in|\\pt)?", 'raggedright = ##t', s)
-    return s
-
-
-@rule((1, 7, 16), "divisiomaior -> divisioMaior")
-def conv(s):
-    s = re.sub("divisiomaior",
-                 "divisioMaior", s)
-    s = re.sub("divisiominima",
-                 "divisioMinima", s)
-    s = re.sub("divisiomaxima",
-                 "divisioMaxima", s)
-    return s
-
-
-@rule((1, 7, 17), "Skip_req  -> Skip_event")
-def conv(s):
-    s = re.sub("Skip_req_swallow_translator",
-                 "Skip_event_swallow_translator", s)
-    return s
-
-
-@rule((1, 7, 18), "groupOpen/Close  -> start/stopGroup, #'outer  -> #'enclose-bounds")
-def conv(s):
-    s = re.sub("groupOpen",
-                 "startGroup", s)
-    s = re.sub("groupClose",
-                 "stopGroup", s)
-    s = re.sub("#'outer",
-                 "#'enclose-bounds", s)
-
-    return s
-
-
-@rule((1, 7, 19), _("remove %s") % "GraceContext")
-def conv(s):
-    if re.search(r'\\GraceContext', s):
-        stderr_write(NOT_SMART % "GraceContext")
-        stderr_write(FROM_TO
-                     % ("GraceContext", "#(add-to-grace-init .. )"))
-        stderr_write(UPDATE_MANUALLY)
-        raise FatalConversionError()
-
-    s = re.sub('HaraKiriStaffContext', 'RemoveEmptyStaffContext', s)
-    return s
-
-
-@rule((1, 7, 22), "#'type -> #'style")
-def conv(s):
-    s = re.sub(
-        r"(set|override|revert) *#'type",
-        r"\1 #'style",
-        s)
-    return s
-
-
-@rule((1, 7, 23), "barNonAuto -> automaticBars")
-def conv(s):
-    s = re.sub(
-        "barNonAuto *= *##t",
-        "automaticBars = ##f",
-        s)
-    s = re.sub(
-        "barNonAuto *= *##f",
-        "automaticBars = ##t",
-        s)
-    return s
-
-
-@rule((1, 7, 24), _("cluster syntax"))
-def conv(s):
-    if re.search(r'-(start|stop)Cluster', s):
-        stderr_write(NOT_SMART % _("cluster syntax"))
-        stderr_write(UPDATE_MANUALLY)
-
-        raise FatalConversionError()
-    return s
-
-
-@rule((1, 7, 28), _("new Pedal style syntax"))
-def conv(s):
-    s = re.sub(r"\\property *Staff\.(Sustain|Sostenuto|UnaCorda)Pedal *\\(override|set) *#'pedal-type *",
-                 r"\\property Staff.pedal\1Style ", s)
-    s = re.sub(
-        r"\\property *Staff\.(Sustain|Sostenuto|UnaCorda)Pedal *\\revert *#'pedal-type", '', s)
-    return s
-
-
-def sub_chord(m):
-    s = m.group(1)
-
-    origstr = '<%s>' % s
-    if re.search(r'\\\\', s):
-        return origstr
-
-    if re.search(r'\\property', s):
-        return origstr
-
-    if re.match(r'^\s*\)?\s*\\[a-zA-Z]+', s):
-        return origstr
-
-    durs = []
-
-    def sub_durs(m, durs=durs):
-        durs.append(m.group(2))
-        return m.group(1)
-
-    s = re.sub(r"([a-z]+[,'!? ]*)([0-9]+\.*)", sub_durs, s)
-    dur_str = ''
-
-    for d in durs:
-        if dur_str == '':
-            dur_str = d
-        if dur_str != d:
-            return '<%s>' % m.group(1)
-
-    pslur_strs = ['']
-    dyns = ['']
-    slur_strs = ['']
-
-    last_str = ''
-    while last_str != s:
-        last_str = s
-
-        def sub_tremolos(m, slur_strs=slur_strs):
-            tr = m.group(2)
-            if tr not in slur_strs:
-                slur_strs.append(tr)
-            return m.group(1)
-
-        s = re.sub(r"([a-z]+[',!? ]*)(:[0-9]+)",
-                     sub_tremolos, s)
-
-        def sub_dyn_end(m, dyns=dyns):
-            dyns.append(r' \!')
-            return ' ' + m.group(2)
-
-        s = re.sub(r'(\\!)\s*([a-z]+)', sub_dyn_end, s)
-
-        def sub_slurs(m, slur_strs=slur_strs):
-            if '-)' not in slur_strs:
-                slur_strs.append(')')
-            return m.group(1)
-
-        def sub_p_slurs(m, slur_strs=slur_strs):
-            if r'-\)' not in slur_strs:
-                slur_strs.append(r'\)')
-            return m.group(1)
-
-        s = re.sub(r"\)[ ]*([a-z]+)", sub_slurs, s)
-        s = re.sub(r"\\\)[ ]*([a-z]+)", sub_p_slurs, s)
-
-        def sub_begin_slurs(m, slur_strs=slur_strs):
-            if '-(' not in slur_strs:
-                slur_strs.append('(')
-            return m.group(1)
-
-        s = re.sub(r"([a-z]+[,'!?0-9 ]*)\(",
-                     sub_begin_slurs, s)
-
-        def sub_begin_p_slurs(m, slur_strs=slur_strs):
-            if r'-\(' not in slur_strs:
-                slur_strs.append(r'\(')
-            return m.group(1)
-
-        s = re.sub(r"([a-z]+[,'!?0-9 ]*)\\\(",
-                     sub_begin_p_slurs, s)
-
-        def sub_dyns(m, slur_strs=slur_strs):
-            s = m.group(0)
-            if s == '@STARTCRESC@':
-                slur_strs.append("\\<")
-            elif s == '@STARTDECRESC@':
-                slur_strs.append("\\>")
-            elif s == r'-?\\!':
-                slur_strs.append('\\!')
-            return ''
-
-        s = re.sub(r'@STARTCRESC@', sub_dyns, s)
-        s = re.sub(r'-?\\!', sub_dyns, s)
-
-        def sub_articulations(m, slur_strs=slur_strs):
-            a = m.group(1)
-            if a not in slur_strs:
-                slur_strs.append(a)
-            return ''
-
-        s = re.sub(r"([_^-]\@ACCENT\@)", sub_articulations,
-                     s)
-        s = re.sub(r"([_^-]\\[a-z]+)", sub_articulations,
-                     s)
-        s = re.sub(r"([_^-][>_.+|^-])", sub_articulations,
-                     s)
-        s = re.sub(r'([_^-]"[^"]+")', sub_articulations,
-                     s)
-
-        def sub_pslurs(m, slur_strs=slur_strs):
-            slur_strs.append(' \\)')
-            return m.group(1)
-        s = re.sub(r"\\\)[ ]*([a-z]+)", sub_pslurs, s)
-
-    # end of while <>
-
-    suffix = ''.join(slur_strs) + ''.join(pslur_strs) \
-             + ''.join(dyns)
-
-    return '@STARTCHORD@%s@ENDCHORD@%s%s' % (s, dur_str, suffix)
-
-
-def sub_chords(s):
-    simend = '>'
-    simstart = '<'
-    chordstart = '<<'
-    chordend = '>>'
-    marker_str = '%% new-chords-done %%'
-
-    if re.search(marker_str, s):
-        return s
-    s = re.sub('<<', '@STARTCHORD@', s)
-    s = re.sub('>>', '@ENDCHORD@', s)
-
-    s = re.sub(r'\\<', '@STARTCRESC@', s)
-    s = re.sub(r'\\>', '@STARTDECRESC@', s)
-    s = re.sub(r'([_^-])>', r'\1@ACCENT@', s)
-    s = re.sub(r'<([^<>{}]+)>', sub_chord, s)
-
-    # add dash: -[, so that [<<a b>> c d] becomes
-    #                      <<a b>>-[ c d]
-    # and gets skipped by articulation_substitute
-    s = re.sub(r'\[ *(@STARTCHORD@[^@]+@ENDCHORD@[0-9.]*)',
-                 r'\1-[', s)
-    s = re.sub(r'\\! *(@STARTCHORD@[^@]+@ENDCHORD@[0-9.]*)',
-                 r'\1-\\!', s)
-
-    s = re.sub(r'<([^?])', r'%s\1' % simstart, s)
-    s = re.sub(r'>([^?])', r'%s\1' % simend,  s)
-    s = re.sub('@STARTCRESC@', r'\\<', s)
-    s = re.sub('@STARTDECRESC@', r'\\>', s)
-    s = re.sub(r'\\context *Voice *@STARTCHORD@',
-                 '@STARTCHORD@', s)
-    s = re.sub('@STARTCHORD@', chordstart, s)
-    s = re.sub('@ENDCHORD@', chordend, s)
-    s = re.sub(r'@ACCENT@', '>', s)
-    return s
-
-
-markup_start = re.compile(r"([-^_]|\\mark)\s*(#\s*'\s*)\(")
-musicglyph = re.compile(r"\(\s*music\b")
-columns = re.compile(r"\(\s*columns\b")
-submarkup_start = re.compile(r"\(\s*([a-zA-Z]+)")
-leftpar = re.compile(r"\(")
-rightpar = re.compile(r"\)")
-
-
-def text_markup(s):
-    result = ''
-    # Find the beginning of each markup:
-    match = markup_start.search(s)
-    while match:
-        result = result + s[:match.end(1)] + r" \markup"
-        s = s[match.end(2):]
-        # Count matching parentheses to find the end of the
-        # current markup:
-        nesting_level = 0
-        pars = re.finditer(r"[()]", s)
-        for par in pars:
-            if par.group() == '(':
-                nesting_level = nesting_level + 1
-            else:
-                nesting_level = nesting_level - 1
-            if nesting_level == 0:
-                markup_end = par.end()
-                break
-        # The full markup in old syntax:
-        markup = s[:markup_end]
-        # Modify to new syntax:
-        markup = musicglyph.sub(r"{\\musicglyph", markup)
-        markup = columns.sub(r"{", markup)
-        markup = submarkup_start.sub(r"{\\\1", markup)
-        markup = leftpar.sub("{", markup)
-        markup = rightpar.sub("}", markup)
-
-        result = result + markup
-        # Find next markup
-        s = s[markup_end:]
-        match = markup_start.search(s)
-    result = result + s
-    return result
-
-
-def articulation_substitute(s):
-    s = re.sub(r"""([^-])\[ *(\\?\)?[a-z]+[,']*[!?]?[0-9:]*\.*)""",
-                 r"\1 \2[", s)
-    s = re.sub(r"""([^-])\\\) *([a-z]+[,']*[!?]?[0-9:]*\.*)""",
-                 r"\1 \2\\)", s)
-    s = re.sub(r"""([^-\\])\) *([a-z]+[,']*[!?]?[0-9:]*\.*)""",
-                 r"\1 \2)", s)
-    s = re.sub(r"""([^-])\\! *([a-z]+[,']*[!?]?[0-9:]*\.*)""",
-                 r"\1 \2\\!", s)
-    return s
-
-
-string_or_scheme = re.compile('("(?:[^"\\\\]|\\\\.)*")|(#\\s*\'?\\s*\\()')
-
-# Only apply articulation_substitute () outside strings and
-# Scheme expressions:
-
-
-def smarter_articulation_subst(s):
-    result = ''
-    # Find the beginning of next string or Scheme expr.:
-    match = string_or_scheme.search(s)
-    while match:
-        # Convert the preceding LilyPond code:
-        previous_chunk = s[:match.start()]
-        result = result + articulation_substitute(previous_chunk)
-        if match.group(1):  # Found a string
-            # Copy the string to output:
-            result = result + match.group(1)
-            s = s[match.end(1):]
-        else:  # Found a Scheme expression. Count
-            # matching parentheses to find its end
-            s = s[match.start():]
-            nesting_level = 0
-            pars = re.finditer(r"[()]", s)
-            for par in pars:
-                if par.group() == '(':
-                    nesting_level = nesting_level + 1
-                else:
-                    nesting_level = nesting_level - 1
-                if nesting_level == 0:
-                    scheme_end = par.end()
-                    break
-            # Copy the Scheme expression to output:
-            result = result + s[:scheme_end]
-            s = s[scheme_end:]
-        # Find next string or Scheme expression:
-        match = string_or_scheme.search(s)
-    # Convert the remainder of the file
-    result = result + articulation_substitute(s)
-    return result
-
-
-def conv_relative(s):
-    if re.search(r"\\relative", s):
-        s = "#(ly:set-option 'old-relative)\n" + s
-
-    return s
-
-
-@rule((1, 9, 0), _("""New relative mode,
-Postfix articulations, new text markup syntax, new chord syntax."""))
-def conv(s):
-    s = re.sub(r"#'\(\)", "@SCM_EOL@", s)
-    s = conv_relative(s)
-    s = sub_chords(s)
-
-    s = text_markup(s)
-    s = smarter_articulation_subst(s)
-    s = re.sub("@SCM_EOL@", "#'()", s)
-    return s
-
-
-@rule((1, 9, 1), _("Remove - before articulation"))
-def conv(s):
-    if re.search("font-style", s):
-        stderr_write(NOT_SMART % "font-style")
-        stderr_write(UPDATE_MANUALLY)
-
-        raise FatalConversionError()
-
-    s = re.sub(r'-\\markup', r'@\\markup', s)
-    s = re.sub(r'-\\', r'\\', s)
-    s = re.sub(r'-\)', ')', s)
-    s = re.sub(r'-\(', '(', s)
-    s = re.sub(r'-\[', '[', s)
-    s = re.sub(r'-\]', ']', s)
-    s = re.sub('-~', '~', s)
-    s = re.sub(r'@\\markup', r'-\\markup', s)
-    return s
-
-
-@rule((1, 9, 2), "\\newcontext -> \\new")
-def conv(s):
-    s = re.sub('ly:set-context-property',
-                 'ly:set-context-property!', s)
-    s = re.sub('\\\\newcontext', '\\\\new', s)
-    s = re.sub('\\\\grace[\t\n ]*([^{ ]+)',
-                 r'\\grace { \1 }', s)
-    s = re.sub("\\\\grace[\t\n ]*{([^}]+)}",
-                 r"""\\grace {
-\\property Voice.Stem \\override #'stroke-style = #"grace"
-  \1
-  \\property Voice.Stem \\revert #'stroke-style }
-""", s)
-    return s
-
-
-@rule((1, 9, 3), (_("%s misspelling") % "\\acciaccatura") +
-      ", fingerHorizontalDirection -> fingeringOrientations")
-def conv(s):
-    s = re.sub('accacciatura',
-                 'acciaccatura', s)
-
-    if re.search("context-spec-music", s):
-        stderr_write(NOT_SMART % "context-spec-music")
-        stderr_write(UPDATE_MANUALLY)
-
-        raise FatalConversionError()
-
-    s = re.sub('fingerHorizontalDirection *= *#(LEFT|-1)',
-                 "fingeringOrientations = #'(up down left)", s)
-    s = re.sub('fingerHorizontalDirection *= *#(RIGHT|1)',
-                 "fingeringOrientations = #'(up down right)", s)
-    return s
-
-
-@rule((1, 9, 4), _('Swap < > and << >>'))
-def conv(s):
-    if re.search('\\figures', s):
-        warning(_("attempting automatic \\figures conversion.  Check results!"))
-
-    def figures_replace(m):
-        s = m.group(1)
-        s = re.sub('<', '@FIGOPEN@', s)
-        s = re.sub('>', '@FIGCLOSE@', s)
-        return '\\figures { %s }' % s
-
-    s = re.sub(r'\\figures[ \t\n]*{([^}]+)}', figures_replace, s)
-    s = re.sub(r'\\<', '@STARTCRESC@', s)
-    s = re.sub(r'\\>', '@STARTDECRESC@', s)
-    s = re.sub(r'([-^_])>', r'\1@ACCENT@', s)
-    s = re.sub(r'<<', '@STARTCHORD@', s)
-    s = re.sub(r'>>', '@ENDCHORD@', s)
-    s = re.sub(r'>', '@ENDSIMUL@', s)
-    s = re.sub(r'<', '@STARTSIMUL@', s)
-    s = re.sub('@STARTDECRESC@', '\\>', s)
-    s = re.sub('@STARTCRESC@', '\\<', s)
-    s = re.sub('@ACCENT@', '>', s)
-    s = re.sub('@ENDCHORD@', '>', s)
-    s = re.sub('@STARTCHORD@', '<', s)
-    s = re.sub('@STARTSIMUL@', '<<', s)
-    s = re.sub('@ENDSIMUL@', '>>', s)
-    s = re.sub('@FIGOPEN@', '<', s)
-    s = re.sub('@FIGCLOSE@', '>', s)
-    return s
-
-
-@rule((1, 9, 5), 'HaraKiriVerticalGroup -> RemoveEmptyVerticalGroup')
-def conv(s):
-    s = re.sub('HaraKiriVerticalGroup', 'RemoveEmptyVerticalGroup', s)
-    return s
-
-
-@rule((1, 9, 6), _('deprecate %s') % 'ly:get-font')
-def conv(s):
-    if re.search("ly:get-font", s):
-        stderr_write(NOT_SMART % "ly:get-font")
-        stderr_write(FROM_TO
-                     % ("(ly:paper-get-font (ly:grob-get-paper foo) .. )",
-                         "(ly:paper-get-font (ly:grob-get-paper foo) .. )"))
-        stderr_write(UPDATE_MANUALLY)
-        raise FatalConversionError()
-
-    if re.search(r"\\pitch *#", s):
-        stderr_write(NOT_SMART % "\\pitch")
-        stderr_write(_("Use Scheme code to construct arbitrary note events."))
-        stderr_write('\n')
-
-        raise FatalConversionError()
-    return s
-
-
-@rule((1, 9, 7), _('''use symbolic constants for alterations,
-remove \\outputproperty, move ly:verbose into ly:get-option'''))
-def conv(s):
-    def sub_alteration(m):
-        alt = m.group(3)
-        alt = {
-            '-1': 'FLAT',
-            '-2': 'DOUBLE-FLAT',
-            '0': 'NATURAL',
-            '1': 'SHARP',
-            '2': 'DOUBLE-SHARP',
-        }[alt]
-
-        return '(ly:make-pitch %s %s %s)' % (m.group(1), m.group(2),
-                                             alt)
-
-    s = re.sub("\\(ly:make-pitch *([0-9-]+) *([0-9-]+) *([0-9-]+) *\\)",
-                 sub_alteration, s)
-
-    s = re.sub("ly:verbose", "ly:get-option 'verbose", s)
-
-    m = re.search("\\\\outputproperty #([^#]+)[\t\n ]*#'([^ ]+)", s)
-    if m:
-        stderr_write(_(
-            r"""\outputproperty found,
-Please hand-edit, using
-
-  \applyoutput #(outputproperty-compatibility %s '%s <GROB PROPERTY VALUE>)
-
-as a substitution text.""") % (m.group(1), m.group(2)))
-        raise FatalConversionError()
-
-    if re.search("ly:(make-pitch|pitch-alteration)", s) \
-            or re.search("keySignature", s):
-        stderr_write(NOT_SMART % "pitches")
-        stderr_write(
-            _("""The alteration field of Scheme pitches was multiplied by 2
-to support quarter tone accidentals.  You must update the following constructs manually:
-
-* calls of ly:make-pitch and ly:pitch-alteration
-* keySignature settings made with \\property
-"""))
-        raise FatalConversionError()
-    return s
-
-
-@rule((1, 9, 8), "dash-length -> dash-fraction")
-def conv(s):
-    if re.search("dash-length", s):
-        stderr_write(NOT_SMART % "dash-length")
-        stderr_write(FROM_TO % ("dash-length", "dash-fraction"))
-        stderr_write(UPDATE_MANUALLY)
-        raise FatalConversionError()
-    return s
-
-
-@rule((2, 1, 1), "font-relative-size -> font-size")
-def conv(s):
-    def func(match):
-        return "#'font-size = #%d" % (2*int(match.group(1)))
-
-    s = re.sub(r"#'font-relative-size\s*=\s*#\+?([0-9-]+)", func, s)
-    s = re.sub(r"#'font-family\s*=\s*#'ancient",
-                 r"#'font-family = #'music", s)
-    return s
-
-
-@rule((2, 1, 2), "ly:get-music-length -> ly:music-length")
-def conv(s):
-    s = re.sub(r"ly:get-music-length", "ly:music-length", s)
-    return s
-
-
-@rule((2, 1, 3), "stanza -> instrument")
-def conv(s):
-    s = re.sub(r"\.\s+stz=", ". instr ", s)
-    return s
-
-
-@rule((2, 1, 4), _("removal of automaticMelismata; use melismaBusyProperties instead."))
-def conv(s):
-    def func(match):
-        c = match.group(1)
-        b = match.group(2)
-
-        if b == 't':
-            if c == 'Score':
-                return ''
-            return r" \property %s.melismaBusyProperties \unset" % c
-
-        assert b == 'f', "Value must be ##t or ##f and not ##%s" % b
-        return r"\property %s.melismaBusyProperties = #'(melismaBusy)" % c
-
-    s = re.sub(
-        r"\\property ([a-zA-Z]+)\s*\.\s*automaticMelismata\s*=\s*##([ft])", func, s)
-    return s
-
-
-@rule((2, 1, 7), "\\translator Staff -> \\change Staff")
-def conv(s):
-    s = re.sub(r"\\translator\s+([a-zA-Z]+)", r"\\change \1", s)
-    return s
-
-
-@rule((2, 1, 10), "\\newaddlyrics -> \\lyricsto")
-def conv(s):
-    s = re.sub(r"\\newaddlyrics", r"\\lyricsto", s)
-    return s
-
-
-@rule((2, 1, 11), """\\include "paper16.ly" -> #(set-staff-size 16)
-\\note #3 #1 #1 -> \\note #"8." #1
-""")
-def conv(s):
-    s = re.sub(r'\\include\s*"paper([0-9]+)(-init)?.ly"',
-                 r"#(set-staff-size \1)", s)
-
-    def sub_note(match):
-        dur = ''
-        log = int(match.group(1))
-        dots = int(match.group(2))
-
-        if log >= 0:
-            dur = '%d' % (1 << log)
-        else:
-            dur = {-1: 'breve',
-                   -2: 'longa',
-                   -3: 'maxima'}[log]
-
-        dur += ('.' * dots)
-
-        return r'\note #"%s" #%s' % (dur, match.group(3))
-
-    s = re.sub(r'\\note\s+#([0-9-]+)\s+#([0-9]+)\s+#([0-9.-]+)',
-                 sub_note, s)
-    return s
-
-
-@rule((2, 1, 12), "OttavaSpanner -> OttavaBracket")
-def conv(s):
-    s = re.sub(r"OttavaSpanner", r"OttavaBracket", s)
-    return s
-
-
-@rule((2, 1, 13), "set-staff-size -> set-global-staff-size")
-def conv(s):
-    s = re.sub(r"\(set-staff-size ", r"(set-global-staff-size ", s)
-    return s
-
-
-@rule((2, 1, 14), "style = dotted -> dash-fraction = 0")
-def conv(s):
-    s = re.sub(r"#'style\s*=\s*#'dotted-line",
-                 r"#'dash-fraction = #0.0 ", s)
-    return s
-
-
-@rule((2, 1, 15), "LyricsVoice . instr(ument) -> vocalName")
-def conv(s):
-    s = re.sub(r'LyricsVoice\s*\.\s*instrument\s*=\s*("[^"]*")',
-                 r'LyricsVoice . vocalName = \1', s)
-
-    s = re.sub(r'LyricsVoice\s*\.\s*instr\s*=\s*("[^"]*")',
-                 r'LyricsVoice . vocNam = \1', s)
-    return s
-
-
-@rule((2, 1, 16), '\\musicglyph #"accidentals-NUM" -> \\sharp/flat/etc.')
-def conv(s):
-    def sub_acc(m):
-        d = {
-            '4': 'doublesharp',
-            '3': 'threeqsharp',
-            '2': 'sharp',
-            '1': 'semisharp',
-            '0': 'natural',
-            '-1': 'semiflat',
-            '-2': 'flat',
-            '-3': 'threeqflat',
-            '-4': 'doubleflat'}
-        return '\\%s' % d[m.group(1)]
-
-    s = re.sub(r'\\musicglyph\s*#"accidentals-([0-9-]+)"',
-                 sub_acc, s)
-    return s
-
-
-@rule((2, 1, 17), _("\\partcombine syntax change to \\newpartcombine"))
-def conv(s):
-
-    if re.search(r'\\partcombine', s):
-        stderr_write(NOT_SMART % "\\partcombine")
-        stderr_write(UPDATE_MANUALLY)
-        raise FatalConversionError()
-
-    # this rule doesn't really work,
-    # too lazy to figure out why.
-    s = re.sub(r'\\context\s+Voice\s*=\s*one\s*\\partcombine\s+Voice\s*\\context\s+Thread\s*=\s*one(.*)\s*'
-                 + r'\\context\s+Thread\s*=\s*two',
-                 '\\\\newpartcombine\n\\1\n', s)
-    return s
-
-
-@rule((2, 1, 18), """\\newpartcombine -> \\partcombine,
-\\autochange Staff -> \\autochange
-""")
-def conv(s):
-    s = re.sub(r'\\newpartcombine', r'\\partcombine', s)
-    s = re.sub(r'\\autochange\s+Staff', r'\\autochange ', s)
-    return s
-
-
-@rule((2, 1, 19), _("""Drum notation changes, Removing \\chordmodifiers, \\notenames.
-Harmonic notes. Thread context removed. Lyrics context removed."""))
-def conv(s):
-    if re.search('include "drumpitch', s):
-        stderr_write(_("Drums found. Enclose drum notes in \\drummode"))
-
-    s = re.sub(r'\\include "drumpitch-init.ly"', '', s)
-
-    s = re.sub(r'\\pitchnames ', 'pitchnames = ', s)
-    s = re.sub(r'\\chordmodifiers ', 'chordmodifiers = ', s)
-    s = re.sub(r'\bdrums\b\s*=', 'drumContents = ', s)
-    s = re.sub(r'\\drums\b', r'\\drumContents ', s)
-
-    if re.search('drums->paper', s):
-        stderr_write(_("\n%s found. Check file manually!\n") %
-                     _("Drum notation"))
-
-    s = re.sub(r"""\\apply\s+#\(drums->paper\s+'([a-z]+)\)""",
-                 r"""\\property DrumStaff.drumStyleTable = #\1-style""",
-                 s)
-
-    if re.search('Thread', s):
-        stderr_write(_("\n%s found. Check file manually!\n") % "Thread")
-
-    s = re.sub(r"""(\\once\s*)?\\property\s+Thread\s*\.\s*NoteHead\s*"""
-                 + r"""\\(set|override)\s*#'style\s*=\s*#'harmonic"""
-                 + r"""\s+([a-z]+[,'=]*)([0-9]*\.*)""", r"""<\3\\harmonic>\4""", s)
-
-    s = re.sub(r"""\\new Thread""", r"""\\context Voice""", s)
-    s = re.sub(r"""Thread""", """Voice""", s)
-
-    if re.search('\bLyrics\b', s):
-        stderr_write(_("\n%s found. Check file manually!\n") % "Lyrics")
-
-    s = re.sub(r"""LyricsVoice""", r"""L@ricsVoice""", s)
-    s = re.sub(r"""\bLyrics\b""", r"""LyricsVoice""", s)
-    s = re.sub(r"""LyricsContext""", r"""LyricsVoiceContext""", s)
-    s = re.sub(r"""L@ricsVoice""", r"""LyricsVoice""", s)
-    return s
-
-
-@rule((2, 1, 20), "nonevent-skip -> skip-music")
-def conv(s):
-    s = re.sub(r'nonevent-skip', 'skip-music', s)
-    return s
-
-
-@rule((2, 1, 21), """molecule-callback -> print-function,
-brew_molecule -> print
-brew-new-markup-molecule -> Text_item::print
-LyricsVoice -> Lyrics
-tupletInvisible -> TupletBracket \\set #'transparent
-%s.
-""" % (_("remove %s") % "Grob::preset_extent"))
-def conv(s):
-    s = re.sub(r'molecule-callback', 'print-function', s)
-    s = re.sub(r'brew_molecule', 'print', s)
-    s = re.sub(r'brew-new-markup-molecule', 'Text_item::print', s)
-    s = re.sub(r'LyricsVoice', 'Lyrics', s)
-    s = re.sub(r'tupletInvisible',
-                 r"TupletBracket \\set #'transparent", s)
-#       s = re.sub (r'molecule', 'collage', s)
-# molecule -> collage
-    s = re.sub(r"\\property\s+[a-zA-Z]+\s*\.\s*[a-zA-Z]+\s*"
-                 + r"\\set\s*#'X-extent-callback\s*=\s*#Grob::preset_extent",
-                 "", s)
-    return s
-
-
-@rule((2, 1, 22), """%s
-        \\set A.B = #C , \\unset A.B
-        \\override A.B #C = #D, \\revert A.B #C
-
-""" % _("new syntax for property settings:"))
-def conv(s):
-    s = re.sub(r'(\\property[^=]+)=\s*([-0-9]+)',
-                 r'\1= #\2', s)
-    s = re.sub(r'\\property\s+([^. ]+)\s*\.\s*([^\\=]+)\s*\\(set|override)',
-                 r"\\overrid@ \1.\2 ", s)
-    s = re.sub(r'\\property\s+([^. ]+)\s*\.\s*([^\\= ]+)\s*=\s*',
-                 r'\\s@t \1.\2 = ', s)
-    s = re.sub(r'\\property\s+([^. ]+)\s*\.\s*([^\\= ]+)\s*\\unset',
-                 r'\\uns@t \1.\2 ', s)
-    s = re.sub(r'\\property\s+([^. ]+)\s*\.\s*([^\\= ]+)\s*\\revert'
-                 + r"\s*#'([-a-z0-9_]+)",
-                 r"\\rev@rt \1.\2 #'\3", s)
-    s = re.sub(r'Voice\.', '', s)
-    s = re.sub(r'Lyrics\.', '', s)
-    s = re.sub(r'ChordNames\.', '', s)
-
-    s = re.sub('rev@rt', 'revert', s)
-    s = re.sub('s@t', 'set', s)
-    s = re.sub('overrid@', 'override', s)
-
-    s = re.sub('molecule', 'stencil', s)
-    s = re.sub('Molecule', 'Stencil', s)
-    return s
-
-
-@rule((2, 1, 23), _("Property setting syntax in \\translator{ }"))
-def conv(s):
-    def subst_in_trans(match):
-        s = match.group(0)
-        s = re.sub(r'\s([a-zA-Z]+)\s*\\override',
-                   r' \\override \1', s)
-        s = re.sub(r'\s([a-zA-Z]+)\s*\\set',
-                   r' \\override \1', s)
-        s = re.sub(r'\s([a-zA-Z]+)\s*\\revert',
-                   r' \\revert \1', s)
-        return s
-    s = re.sub(r'\\(translator|with)\s*{[^}]+}',  subst_in_trans, s)
-
-    def sub_abs(m):
-
-        context = m.group('context')
-        d = m.groupdict()
-        if context:
-            context = " '%s" % context[:-1]  # -1: remove .
-        else:
-            context = ''
-
-        d['context'] = context
-
-        return r"""#(override-auto-beam-setting %(prop)s %(num)s %(den)s%(context)s)""" % d
-
-    s = re.sub(r"""\\override\s*(?P<context>[a-zA-Z]+\s*\.\s*)?autoBeamSettings"""
-                 + r"""\s*#(?P<prop>[^=]+)\s*=\s*#\(ly:make-moment\s+(?P<num>\d+)\s+(?P<den>\d)\s*\)""",
-                 sub_abs, s)
-    return s
-
-
-@rule((2, 1, 24), "music-list? -> ly:music-list?")
-def conv(s):
-    s = re.sub(r'music-list\?', 'ly:music-list?', s)
-    s = re.sub(r'\|\s*~', '~ |', s)
-    return s
-
-
-@rule((2, 1, 25), _("Scheme grob function renaming"))
-def conv(s):
-    s = re.sub(r'ly:get-spanner-bound', 'ly:spanner-get-bound', s)
-    s = re.sub(r'ly:get-extent', 'ly:grob-extent', s)
-    s = re.sub(r'ly:get-system', 'ly:grob-system', s)
-    s = re.sub(r'ly:get-original', 'ly:grob-original', s)
-    s = re.sub(r'ly:get-parent', 'ly:grob-parent', s)
-    s = re.sub(r'ly:get-broken-into', 'ly:spanner-broken-into', s)
-    s = re.sub(r'Melisma_engraver', 'Melisma_translator', s)
-    if re.search("ly:get-paper-variable", s):
-        stderr_write(NOT_SMART % "ly:paper-get-variable")
-        stderr_write(_('Use %s\n') % '(ly:paper-lookup (ly:grob-paper ))')
-        raise FatalConversionError()
-
-    s = re.sub(r'\\defaultAccidentals',
-                 "#(set-accidental-style 'default)", s)
-    s = re.sub(r'\\voiceAccidentals', "#(set-accidental-style 'voice)", s)
-    s = re.sub(r'\\modernAccidentals',
-                 "#(set-accidental-style 'modern)", s)
-    s = re.sub(r'\\modernCautionaries',
-                 "#(set-accidental-style 'modern-cautionary)", s)
-    s = re.sub(r'\\modernVoiceAccidental',
-                 "#(set-accidental-style 'modern-voice)", s)
-    s = re.sub(r'\\modernVoiceCautionaries',
-                 "#(set-accidental-style 'modern-voice-cautionary)", s)
-    s = re.sub(r'\\pianoAccidentals', "#(set-accidental-style 'piano)", s)
-    s = re.sub(r'\\pianoCautionaries',
-                 "#(set-accidental-style 'piano-cautionary)", s)
-    s = re.sub(r'\\forgetAccidentals',
-                 "#(set-accidental-style 'forget)", s)
-    s = re.sub(r'\\noResetKey', "#(set-accidental-style 'no-reset)", s)
-    return s
-
-
-@rule((2, 1, 26), _("More Scheme function renaming"))
-def conv(s):
-    s = re.sub('ly:set-grob-property!', 'ly:grob-set-property!', s)
-    s = re.sub('ly:set-mus-property!', 'ly:music-set-property!', s)
-    s = re.sub('ly:set-context-property!', 'ly:context-set-property!', s)
-    s = re.sub('ly:get-grob-property', 'ly:grob-property', s)
-    s = re.sub('ly:get-mus-property', 'ly:music-property', s)
-    s = re.sub('ly:get-context-property', 'ly:context-property', s)
-    return s
-
-
-@rule((2, 1, 27), "property transposing -> tuning")
-def conv(s):
-    def subst(m):
-        (o, g) = divmod(int(m.group(2)), 12)
-
-        lower_pitches = [x for x in [0, 2, 4, 5, 7, 9, 11, 12] if x <= g]
-        s = len(lower_pitches) - 1
-        a = g - lower_pitches[-1]
-
-        s = 'cdefgab' [s]
-        s += ['eses', 'es', '', 'is', 'isis'][a + 2]
-        o += 1                  # c' is octave 0
-        if o < 0:
-            s += (-o) * ","
-        elif o > 0:
-            s += o * "'"
-
-        return '\\transposition %s ' % s
-
-    s = re.sub(r"\\set ([A-Za-z]+\s*\.\s*)?transposing\s*=\s*#([-0-9]+)",
-                 subst, s)
-    return s
-
-
-@rule((2, 1, 28), """make-music-by-name -> make-music,
-new syntax for setting \\arpeggioBracket""")
-def conv(s):
-    s = re.sub(r'make-music-by-name', 'make-music', s)
-    s = re.sub(r"\\override\s+.*Arpeggio\s+#.print-function\s+=\s+\\arpeggioBracket",
-                 r"\\arpeggioBracket", s)
-    return s
-
-
-@rule((2, 1, 29), '\\center -> \\center-align, \\translator -> \\context')
-def conv(s):
-    s = re.sub(r'\\center([^-])', r'\\center-align\1', s)
-    s = re.sub(r'\\translator', r'\\context', s)
-    return s
-
-
-@rule((2, 1, 30), '''\\threeq{flat,sharp} -> \\sesqui{flat,sharp}
-ly:get-mutable-properties -> ly:mutable-music-properties
-centralCPosition -> middleCPosition
-ly:unset-context-property -> ly:context-unset-property
-ly:translator-find -> ly:context-find
-ly:get-stencil-extent -> ly:stencil-extent
-''')
-def conv(s):
-    s = re.sub(r'\\threeq(flat|sharp)', r'\\sesqui\1', s)
-    s = re.sub(r'ly:stencil-get-extent',
-                 'ly:stencil-extent', s)
-    s = re.sub(r'ly:translator-find',
-                 'ly:context-find', s)
-    s = re.sub('ly:unset-context-property', 'ly:context-unset-property',
-                 s)
-
-    s = re.sub(r'ly:get-mutable-properties',
-                 'ly:mutable-music-properties', s)
-    s = re.sub(r'centralCPosition',
-                 'middleCPosition', s)
-    return s
-
-
-@rule((2, 1, 31), 'remove \\alias Timing')
-def conv(s):
-    s = re.sub(r'\\alias\s*"?Timing"?', '', s)
-    return s
-
-
-@rule((2, 1, 33), 'breakAlignOrder -> break-align-orders.')
-def conv(s):
-    s = re.sub(r"(\\set\s+)?(?P<context>(Score\.)?)breakAlignOrder\s*=\s*#'(?P<list>[^\)]+)",
-                 r"\n\\override \g<context>BreakAlignment #'break-align-orders = "
-                 + r"#(make-vector 3 '\g<list>)", s)
-    return s
-
-
-@rule((2, 1, 34), 'set-paper-size -> set-default-paper-size.')
-def conv(s):
-    s = re.sub(r"\(set-paper-size",
-                 "(set-default-paper-size", s)
-    return s
-
-
-@rule((2, 1, 36), 'ly:mutable-music-properties -> ly:music-mutable-properties')
-def conv(s):
-    s = re.sub(r"ly:mutable-music-properties",
-                 "ly:music-mutable-properties", s)
-    return s
-
-
-@rule((2, 2, 0), _("bump version for release"))
-def conv(s):
-    return s
-
-
-@rule((2, 3, 1), '\\apply -> \\applymusic')
-def conv(s):
-    return re.sub(r'\\apply\b', r'\\applymusic', s)
-
-
-@rule((2, 3, 2), '\\FooContext -> \\Foo')
-def conv(s):
-    if re.search('textheight', s):
-        stderr_write(NOT_SMART % "textheight")
-        stderr_write(UPDATE_MANUALLY)
-        stderr_write(
-            _("""Page layout has been changed, using paper size and margins.
-textheight is no longer used.
-"""))
-    s = re.sub(r'\\OrchestralScoreContext', r'\\Score', s)
-
-    def func(m):
-        if m.group(1) not in ['RemoveEmptyStaff',
-                              'AncientRemoveEmptyStaffContext',
-                              'EasyNotation']:
-            return '\\' + m.group(1)
-        return m.group(0)
-
-    s = re.sub(r'\\([a-zA-Z]+)Context\b', func, s)
-    s = re.sub('ly:paper-lookup', 'ly:output-def-lookup', s)
-    return s
-
-
-@rule((2, 3, 4), _('remove %s') % '\\notes')
-def conv(s):
-    s = re.sub(r'\\notes\b', '', s)
-    return s
-
-
-@rule((2, 3, 6), 'lastpagefill -> raggedlastbottom')
-def conv(s):
-    s = re.sub(r'lastpagefill\s*=\s*"?1"', 'raggedlastbottom = ##t', s)
-    return s
-
-
-@rule((2, 3, 8), 'remove \\consistsend, strip \\lyrics from \\lyricsto.')
-def conv(s):
-    s = re.sub(r'\\consistsend', r'\\consists', s)
-    s = re.sub(r'\\lyricsto\s+("?[a-zA-Z]+"?)(\s*\\new Lyrics\s*)?\\lyrics',
-                 r'\\lyricsto \1 \2', s)
-    return s
-
-
-@rule((2, 3, 9), 'neo_mensural -> neomensural, if-text-padding -> bound-padding')
-def conv(s):
-    s = re.sub(r'neo_mensural', 'neomensural', s)
-    s = re.sub(r'if-text-padding', 'bound-padding', s)
-    return s
-
-
-@rule((2, 3, 10), '\\addlyrics -> \\oldaddlyrics, \\newlyrics -> \\addlyrics')
-def conv(s):
-    s = re.sub(r'\\addlyrics', r'\\oldaddlyrics', s)
-    s = re.sub(r'\\newlyrics', r'\\addlyrics', s)
-    if re.search(r"\\override\s*TextSpanner", s):
-        stderr_write(
-            "\nWarning: TextSpanner has been split into DynamicTextSpanner and TextSpanner\n")
-    return s
-
-
-@rule((2, 3, 11), '\\setMmRestFermata -> ^\\fermataMarkup')
-def conv(s):
-    s = re.sub(r'\\setMmRestFermata\s+(R[0-9.*/]*)',
-                 r'\1^\\fermataMarkup', s)
-    return s
-
-
-@rule((2, 3, 12), '''\\newpage -> \\pageBreak, junk \\script{up,down,both},
-soloADue -> printPartCombineTexts, #notes-to-clusters -> \\makeClusters
-''')
-def conv(s):
-    s = re.sub(r'\\newpage', r'\\pageBreak', s)
-    s = re.sub(r'\\scriptUp', r"""{
-\\override TextScript  #'direction = #1
-\\override Script  #'direction = #1
-}""", s)
-    s = re.sub(r'\\scriptDown', r"""{
-  \\override TextScript  #'direction = #-1
-  \\override Script  #'direction = #-1
-}""", s)
-    s = re.sub(r'\\scriptBoth', r"""{
-  \\revert TextScript  #'direction
-  \\revert Script  #'direction
-}""", s)
-    s = re.sub('soloADue', 'printPartCombineTexts', s)
-    s = re.sub(r'\\applymusic\s*#notes-to-clusters',
-                 r'\\makeClusters', s)
-
-    s = re.sub(r'pagenumber\s*=', 'firstpagenumber = ', s)
-    return s
-
-
-@rule((2, 3, 16), _('''\\foo -> \\foomode (for chords, notes, etc.)
-fold \\new FooContext \\foomode into \\foo.'''))
-def conv(s):
-    s = re.sub(r'\\chords\b', r'\\chordmode', s)
-    s = re.sub(r'\\lyrics\b', r'\\lyricmode', s)
-    s = re.sub(r'\\figures\b', r'\\figuremode', s)
-    s = re.sub(r'\\notes\b', r'\\notemode', s)
-    s = re.sub(r'\\drums\b', r'\\drummode', s)
-    s = re.sub(r'\\chordmode\s*\\new ChordNames', r'\\chords', s)
-    s = re.sub(r'\\new ChordNames\s*\\chordmode', r'\\chords', s)
-    s = re.sub(r'\\new FiguredBass\s*\\figuremode', r'\\figures', s)
-    s = re.sub(r'\\figuremode\s*\new FiguredBass', r'\\figures', s)
-    s = re.sub(r'\\new DrumStaff\s*\\drummode', r'\\drums', s)
-    s = re.sub(r'\\drummode\s*\\new DrumStaff', r'\\drums', s)
-
-    return s
-
-
-@rule((2, 3, 17), '''slurBoth -> slurNeutral, stemBoth -> stemNeutral, etc.
-\\applymusic #(remove-tag 'foo) -> \\removeWithTag 'foo''')
-def conv(s):
-    s = re.sub(
-        r'(slur|stem|phrasingSlur|tie|dynamic|dots|tuplet|arpeggio|)Both', r'\1Neutral', s)
-    s = re.sub(r"\\applymusic\s*#\(remove-tag\s*'([a-z-0-9]+)\)",
-                 r"\\removeWithTag #'\1", s)
-    return s
-
-
-@rule((2, 3, 18), 'Text_item -> Text_interface')
-def conv(s):
-    s = re.sub(r'Text_item', 'Text_interface', s)
-    return s
-
-
-@rule((2, 3, 22), 'paper -> layout, bookpaper -> paper')
-def conv(s):
-    s = re.sub(r'\\paper', r'\\layout', s)
-    s = re.sub(r'\\bookpaper', r'\\paper', s)
-    if re.search('paper-set-staff-size', s):
-        warning(_('''staff size should be changed at top-level
-with
-
-  #(set-global-staff-size <STAFF-HEIGHT-IN-POINT>)
-
-'''))
-
-    s = re.sub(r'#\(paper-set-staff-size',
-                 '%Use set-global-staff-size at toplevel\n% #(layout-set-staff-size', s)
-    return s
-
-
-@rule((2, 3, 23), r'\context Foo = NOTENAME -> \context Foo = "NOTENAME"')
-def conv(s):
-    s = re.sub(r'\\context\s+([a-zA-Z]+)\s*=\s*([a-z]+)\s',
-                 r'\\context \1 = "\2" ',
-                 s)
-    return s
-
-
-@rule((2, 3, 24), _('''regularize other identifiers'''))
-def conv(s):
-    def sub(m):
-        return regularize_id(m.group(1))
-    s = re.sub(r'(maintainer_email|maintainer_web|midi_stuff|gourlay_maxmeasures)',
-                 sub, s)
-    return s
-
-
-@rule((2, 3, 25), 'petrucci_c1 -> petrucci-c1, 1style -> single-digit')
-def conv(s):
-    s = re.sub('petrucci_c1', 'petrucci-c1', s)
-    s = re.sub('1style', 'single-digit', s)
-    return s
-
-
-@rule((2, 4, 0), _("bump version for release"))
-def conv(s):
-    return s
-
-
-@rule((2, 5, 0), '\\quote -> \\quoteDuring')
-def conv(s):
-    s = re.sub(r'\\quote\s+"?([a-zA-Z0-9]+)"?\s+([0-9.*/]+)',
-                 r'\\quoteDuring #"\1" { \\skip \2 }',
-                 s)
-    return s
-
-
-@rule((2, 5, 1), 'ly:import-module -> ly:module-copy')
-def conv(s):
-    s = re.sub(r'ly:import-module',
-                 r'ly:module-copy', s)
-    return s
-
-
-@rule((2, 5, 2), r'\markup .. < .. > .. -> \markup .. { .. } ..')
-def conv(s):
-    s = re.sub(r'\\(column|fill-line|dir-column|center-align|right-align|left-align|bracketed-y-column)\s*<(([^>]|<[^>]*>)*)>',
-                 r'\\\1 {\2}', s)
-    s = re.sub(r'\\(column|fill-line|dir-column|center-align|right-align|left-align|bracketed-y-column)\s*<(([^>]|<[^>]*>)*)>',
-                 r'\\\1 {\2}', s)
-    s = re.sub(r'\\(column|fill-line|dir-column|center-align|right-align|left-align|bracketed-y-column)\s*<(([^>]|<[^>]*>)*)>',
-                 r'\\\1 {\2}', s)
-
-    def get_markup(m):
-        s = m.group(0)
-        s = re.sub(r'''((\\"|})\s*){''', '\2 \\line {', s)
-        return s
-    s = re.sub(r'\\markup\s*{([^}]|{[^}]*})*}', get_markup, s)
-    return s
-
-
-@rule((2, 5, 3), 'ly:find-glyph-by-name -> ly:font-get-glyph, remove - from glyphnames.')
-def conv(s):
-    s = re.sub('ly:find-glyph-by-name', 'ly:font-get-glyph', s)
-    s = re.sub('"(scripts|clefs|accidentals)-', r'"\1.', s)
-    s = re.sub("'hufnagel-do-fa", "'hufnagel.do.fa", s)
-    s = re.sub(
-        "'(vaticana|hufnagel|medicaea|petrucci|neomensural|mensural)-", r"'\1.", s)
-    return s
-
-
-@rule((2, 5, 12), r'\set Slur #\'dashed = #X -> \slurDashed')
-def conv(s):
-    s = re.sub(r"\\override\s+(Voice\.)?Slur #'dashed\s*=\s*#\d*(\.\d+)?",
-                 r"\\slurDashed", s)
-    return s
-
-
-@rule((2, 5, 13), _('\\encoding: smart recode latin1..utf-8. Remove ly:point-and-click'))
-def conv(s):
-    def func(match):
-        encoding = match.group(1)
-
-        if encoding == 'latin1':
-            return match.group(2)
-
-        stderr_write(NOT_SMART % ("\\encoding: %s" % encoding))
-        stderr_write(_("LilyPond source must be UTF-8"))
-        stderr_write('\n')
-        if encoding == 'TeX':
-            stderr_write(_("Try the texstrings backend"))
-            stderr_write('\n')
-        else:
-            stderr_write(_("Do something like: %s") %
-                         ("recode %s..utf-8 FILE" % encoding))
-            stderr_write('\n')
-        stderr_write(_("Or save as UTF-8 in your editor"))
-        stderr_write('\n')
-        raise FatalConversionError()
-
-    s = re.sub(r'\\encoding\s+"?([a-zA-Z0-9]+)"?(\s+)', func, s)
-
-    s = re.sub(r"#\(ly:set-point-and-click '[a-z-]+\)", '', s)
-    return s
-
-
-@rule((2, 5, 17), _('remove %s') % 'ly:stencil-set-extent!')
-def conv(s):
-    if re.search("ly:stencil-set-extent!", s):
-        stderr_write(NOT_SMART % "ly:stencil-set-extent!")
-        stderr_write(_('Use %s\n') %
-                     '(set! VAR (ly:make-stencil (ly:stencil-expr VAR) X-EXT Y-EXT))')
-        raise FatalConversionError()
-    if re.search("ly:stencil-align-to!", s):
-        stderr_write(NOT_SMART % "ly:stencil-align-to!")
-        stderr_write(_('Use %s\n') %
-                     '(set! VAR (ly:stencil-aligned-to VAR AXIS DIR))')
-        raise FatalConversionError()
-    return s
-
-
-@rule((2, 5, 18), 'ly:warn -> ly:warning')
-def conv(s):
-    s = re.sub(r"ly:warn\b", 'ly:warning', s)
-    return s
-
-
-@rule((2, 5, 21), _('warn about auto beam settings'))
-def conv(s):
-    if re.search("(override-|revert-)auto-beam-setting", s)\
-       or re.search("autoBeamSettings", s):
-        stderr_write(NOT_SMART % _("auto beam settings"))
-        stderr_write(_('''
-Auto beam settings must now specify each interesting moment in a measure
-explicitly; 1/4 is no longer multiplied to cover moments 1/2 and 3/4 too.
-'''))
-        stderr_write(UPDATE_MANUALLY)
-        raise FatalConversionError()
-    return s
-
-
-@rule((2, 5, 25), 'unfoldrepeats -> unfoldRepeats, compressmusic -> compressMusic')
-def conv(s):
-    s = re.sub(r"unfoldrepeats", 'unfoldRepeats', s)
-    s = re.sub(r"compressmusic", 'compressMusic', s)
-    return s
-
-
-@rule((2, 6, 0), _("bump version for release"))
-def conv(s):
-    return s
-
-
-@rule((2, 7, 0), 'ly:get-default-font -> ly:grob-default-font')
-def conv(s):
-    return re.sub('ly:get-default-font', 'ly:grob-default-font', s)
-
-
-@rule((2, 7, 1), '''ly:parser-define -> ly:parser-define!
-excentricity -> eccentricity
-Timing_engraver -> Timing_translator + Default_bar_line_engraver
-''')
-def conv(s):
-    s = re.sub('ly:parser-define', 'ly:parser-define!', s)
-    s = re.sub('excentricity', 'eccentricity', s)
-    s = re.sub(r'\\(consists|remove) *"?Timing_engraver"?',
-                 r'\\\1 "Timing_translator" \\\1 "Default_bar_line_engraver"',
-                 s)
-    return s
-
-
-@rule((2, 7, 2), 'ly:X-moment -> ly:moment-X')
-def conv(s):
-    s = re.sub('ly:(add|mul|mod|div)-moment', r'ly:moment-\1', s)
-    return s
-
-
-@rule((2, 7, 4), 'keyAccidentalOrder -> keyAlterationOrder')
-def conv(s):
-    s = re.sub('keyAccidentalOrder', 'keyAlterationOrder', s)
-    return s
-
-
-@rule((2, 7, 6), '''Performer_group_performer -> Performer_group, Engraver_group_engraver -> Engraver_group,
-inside-slur -> avoid-slur''')
-def conv(s):
-    s = re.sub('Performer_group_performer', 'Performer_group', s)
-    s = re.sub('Engraver_group_engraver', 'Engraver_group', s)
-    s = re.sub(r"#'inside-slur\s*=\s*##t *",
-                 r"#'avoid-slur = #'inside ", s)
-    s = re.sub(r"#'inside-slur\s*=\s*##f *",
-                 r"#'avoid-slur = #'around ", s)
-    s = re.sub(r"#'inside-slur",
-                 r"#'avoid-slur", s)
-    return s
-
-
-@rule((2, 7, 10), '\\applyxxx -> \\applyXxx')
-def conv(s):
-    s = re.sub(r'\\applyoutput', r'\\applyOutput', s)
-    s = re.sub(r'\\applycontext', r'\\applyContext', s)
-    s = re.sub(r'\\applymusic', r'\\applyMusic', s)
-    s = re.sub(r'ly:grob-suicide', 'ly:grob-suicide!', s)
-    return s
-
-
-@rule((2, 7, 11), '"tabloid" -> "11x17"')
-def conv(s):
-    s = re.sub('"tabloid"', '"11x17"', s)
-    return s
-
-
-@rule((2, 7, 12), 'outputProperty -> overrideProperty')
-def conv(s):
-    s = re.sub(r'outputProperty', 'overrideProperty', s)
-    return s
-
-
-@rule((2, 7, 13), 'layout engine refactoring [FIXME]')
-def conv(s):
-    def subber(match):
-        newkey = {'spacing-procedure': 'springs-and-rods',
-                  'after-line-breaking-callback': 'after-line-breaking',
-                  'before-line-breaking-callback': 'before-line-breaking',
-                  'print-function': 'stencil'}[match.group(3)]
-        what = match.group(1)
-        grob = match.group(2)
-
-        if what == 'revert':
-            return "revert %s #'callbacks %% %s\n" % (grob, newkey)
-        if what == 'override':
-            return "override %s #'callbacks #'%s" % (grob, newkey)
-        raise RuntimeError('1st group should match revert or override')
-
-    s = re.sub(r"(override|revert)\s*([a-zA-Z.]+)\s*#'(spacing-procedure|after-line-breaking-callback"
-                 + r"|before-line-breaking-callback|print-function)",
-                 subber, s)
-
-    if re.search('bar-size-procedure', s):
-        stderr_write(NOT_SMART % "bar-size-procedure")
-    if re.search('space-function', s):
-        stderr_write(NOT_SMART % "space-function")
-    if re.search('verticalAlignmentChildCallback', s):
-        stderr_write(_('verticalAlignmentChildCallback has been deprecated'))
-        stderr_write('\n')
-    return s
-
-
-@rule((2, 7, 14), _('Remove callbacks property, deprecate XY-extent-callback.'))
-def conv(s):
-    s = re.sub(r"\\override +([A-Z.a-z]+) #'callbacks",
-                 r"\\override \1", s)
-    s = re.sub(r"\\revert ([A-Z.a-z]+) #'callbacks % ([a-zA-Z]+)",
-                 r"\\revert \1 #'\2", s)
-    s = re.sub(r"([XY]-extent)-callback", r'\1', s)
-    s = re.sub(r"RemoveEmptyVerticalGroup", "VerticalAxisGroup", s)
-    s = re.sub(r"\\set ([a-zA-Z]*\.?)minimumVerticalExtent",
-                 r"\\override \1VerticalAxisGroup #'minimum-Y-extent",
-                 s)
-    s = re.sub(r"minimumVerticalExtent",
-                 r"\\override VerticalAxisGroup #'minimum-Y-extent",
-                 s)
-    s = re.sub(r"\\set ([a-zA-Z]*\.?)extraVerticalExtent",
-                 r"\\override \1VerticalAxisGroup #'extra-Y-extent", s)
-    s = re.sub(r"\\set ([a-zA-Z]*\.?)verticalExtent",
-                 r"\\override \1VerticalAxisGroup #'Y-extent", s)
-    return s
-
-
-@rule((2, 7, 15), _('Use grob closures iso. XY-offset-callbacks.'))
-def conv(s):
-    if re.search('[XY]-offset-callbacks', s):
-        stderr_write(NOT_SMART % "[XY]-offset-callbacks")
-    if re.search('position-callbacks', s):
-        stderr_write(NOT_SMART % "position-callbacks")
-    return s
-
-
-@rule((2, 7, 18), r"""bassFigureFormatFunction -> figuredBassFormatter
-deprecate alignBassFigureAccidentals.
-""")
-def conv(s):
-    s = re.sub('bassFigureFormatFunction', 'figuredBassFormatter', s)
-    if re.search('alignBassFigureAccidentals', s):
-        stderr_write(NOT_SMART % "alignBassFigureAccidentals")
-    return s
-
-
-@rule((2, 7, 22), r"\tag #'(a b) -> \tag #'a \tag #'b")
-def conv(s):
-    def sub_syms(m):
-        syms = m.group(1).split()
-        tags = ["\\tag #'%s" % s for s in syms]
-        return ' '.join(tags)
-
-    s = re.sub(r"\\tag #'\(([^)]+)\)", sub_syms, s)
-    return s
-
-
-@rule((2, 7, 24), _('deprecate %s') % 'number-visibility')
-def conv(s):
-    s = re.sub(r"#'number-visibility",
-                 "#'number-visibility % number-visibility is deprecated. Tune the TupletNumber instead\n",
-                 s)
-    return s
-
-
-@rule((2, 7, 28), "ly:spanner-get-bound -> ly:spanner-bound")
-def conv(s):
-    s = re.sub(r"ly:spanner-get-bound", "ly:spanner-bound", s)
-    return s
-
-
-@rule((2, 7, 29), "override Stem #'beamed-* -> #'details #'beamed-*")
-def conv(s):
-    for a in ['beamed-lengths', 'beamed-minimum-free-lengths',
-              'lengths',
-              'beamed-extreme-minimum-free-lengths']:
-        s = re.sub(r"\\override\s+Stem\s+#'%s" % a,
-                     r"\\override Stem #'details #'%s" % a,
-                     s)
-    return s
-
-
-@rule((2, 7, 30), "\\epsfile")
-def conv(s):
-    s = re.sub(r'\\epsfile *#"', r'\\epsfile #X #10 #"', s)
-    return s
-
-
-@rule((2, 7, 31), "Foo_bar::bla_bla -> ly:foo-bar::bla-bla")
-def conv(s):
-    def sub_cxx_id(m):
-        s = m.group(1)
-        return 'ly:' + s.lower().replace('_', '-')
-
-    s = re.sub(r'([A-Z][a-z_0-9]+::[a-z_0-9]+)',
-                 sub_cxx_id, s)
-    return s
-
-
-@rule((2, 7, 32), _(r"foobar -> foo-bar for \paper, \layout"))
-def conv(s):
-    identifier_subs = [
-        ('inputencoding', 'input-encoding'),
-        ('printpagenumber', 'print-page-number'),
-        ('outputscale', 'output-scale'),
-        ('betweensystemspace', 'between-system-space'),
-        ('betweensystempadding', 'between-system-padding'),
-        ('pagetopspace', 'page-top-space'),
-        ('raggedlastbottom', 'ragged-last-bottom'),
-        ('raggedright', 'ragged-right'),
-        ('raggedlast', 'ragged-last'),
-        ('raggedbottom', 'ragged-bottom'),
-        ('aftertitlespace', 'after-title-space'),
-        ('beforetitlespace', 'before-title-space'),
-        ('betweentitlespace', 'between-title-space'),
-        ('topmargin', 'top-margin'),
-        ('bottommargin', 'bottom-margin'),
-        ('headsep', 'head-separation'),
-        ('footsep', 'foot-separation'),
-        ('rightmargin', 'right-margin'),
-        ('leftmargin', 'left-margin'),
-        ('printfirstpagenumber', 'print-first-page-number'),
-        ('firstpagenumber', 'first-page-number'),
-        ('hsize', 'paper-width'),
-        ('vsize', 'paper-height'),
-        ('horizontalshift', 'horizontal-shift'),
-        ('staffspace', 'staff-space'),
-        ('linethickness', 'line-thickness'),
-        ('ledgerlinethickness', 'ledger-line-thickness'),
-        ('blotdiameter', 'blot-diameter'),
-        ('staffheight', 'staff-height'),
-        ('linewidth', 'line-width'),
-        ('annotatespacing', 'annotate-spacing')
-    ]
-
-    for (a, b) in identifier_subs:
-        # for C++:
-        # s = re.sub ('"%s"' % a, '"%s"' b, s)
-
-        s = re.sub(a, b, s)
-    return s
-
-
-@rule((2, 7, 32), "debug-beam-quanting -> debug-beam-scoring")
-def conv(s):
-    s = re.sub('debug-beam-quanting', 'debug-beam-scoring', s)
-    return s
-
-
-@rule((2, 7, 36), "def-(music-function|markup-command) -> define-(music-function|markup-command)")
-def conv(s):
-    s = re.sub('def-music-function', 'define-music-function', s)
-    s = re.sub('def-markup-command', 'define-markup-command', s)
-    return s
-
-
-@rule((2, 7, 40), "rehearsalMarkAlignSymbol/barNumberAlignSymbol -> break-align-symbol")
-def conv(s):
-    s = re.sub(r'\\set\s+Score\s*\.\s*barNumberAlignSymbol\s*=',
-                 r"\\override Score.BarNumber #'break-align-symbol = ", s)
-    s = re.sub(r'\\set\s*Score\s*\.\s*rehearsalMarkAlignSymbol\s*=',
-                 r"\\override Score.RehearsalMark #'break-align-symbol = ", s)
-    return s
-
-
-@rule((2, 9, 4), "(page-)penalty -> (page-)break-penalty")
-def conv(s):
-    s = re.sub('page-penalty', 'page-break-penalty', s)
-    s = re.sub('([^-])penalty', '\1break-penalty', s)
-    return s
-
-
-@rule((2, 9, 6), "\\context Foo \\applyOutput #bla -> \\applyOutput #'Foo #bla ")
-def conv(s):
-    s = re.sub(
-        r'\\context\s+"?([a-zA-Z]+)"?\s*\\applyOutput', r"\\applyOutput #'\1", s)
-    return s
-
-
-@rule((2, 9, 9), "annotatefoo -> annotate-foo")
-def conv(s):
-    s = re.sub('annotatepage', 'annotate-page', s)
-    s = re.sub('annotateheaders', 'annotate-headers', s)
-    s = re.sub('annotatesystems', 'annotate-systems', s)
-    return s
-
-
-@rule((2, 9, 11), "\\set tupletNumberFormatFunction -> \\override #'text = ")
-def conv(s):
-    s = re.sub(r"""(\\set\s)?(?P<context>[a-zA-Z]*.?)tupletNumberFormatFunction\s*=\s*#denominator-tuplet-formatter""",
-                 r"""\\override \g<context>TupletNumber #'text = #tuplet-number::calc-denominator-text""", s)
-
-    s = re.sub(r"""(\\set\s+)?(?P<context>[a-zA-Z]*.?)tupletNumberFormatFunction\s*=\s*#fraction-tuplet-formatter""",
-                 r"""\\override \g<context>TupletNumber #'text = #tuplet-number::calc-fraction-text""", s)
-
-    if re.search('tupletNumberFormatFunction', s):
-        stderr_write("\n")
-        stderr_write(
-            "tupletNumberFormatFunction has been removed. Use #'text property on TupletNumber")
-        stderr_write("\n")
-    return s
-
-
-@rule((2, 9, 13), "instrument -> instrumentName, instr -> shortInstrumentName, vocNam -> shortVocalName")
-def conv(s):
-    s = re.sub('vocNam', 'shortVocalName', s)
-    s = re.sub(r'\.instr\s*=', r'.shortInstrumentName =', s)
-    s = re.sub(r'\.instrument\s*=', r'.instrumentName =', s)
-    return s
-
-
-@rule((2, 9, 16), _("deprecate \\tempo in \\midi"))
-def conv(s):
-
-    def sub_tempo(m):
-        dur = int(m.group(1))
-        dots = len(m.group(2))
-        count = int(m.group(3))
-
-        log2 = 0
-        while dur > 1:
-            dur /= 2
-            log2 += 1
-
-        den = (1 << dots) * (1 << log2)
-        num = ((1 << (dots+1)) - 1)
-
-        return r"""
-  \midi {
-    \context {
-      \Score
-      tempoWholesPerMinute = #(ly:make-moment %d %d)
-      }
-    }
-
-""" % (num*count, den)
-
-    s = re.sub(
-        r'\\midi\s*{\s*\\tempo ([0-9]+)\s*([.]*)\s*=\s*([0-9]+)\s*}', sub_tempo, s)
-    return s
-
-
-@rule((2, 9, 19), "printfirst-page-number -> print-first-page-number")
-def conv(s):
-    s = re.sub('printfirst-page-number', 'print-first-page-number', s)
-    return s
-
-
-@rule((2, 10, 0), _("bump version for release"))
-def conv(s):
-    return s
-
-
-@rule((2, 11, 2), "ly:clone-parser -> ly:parser-clone")
-def conv(s):
-    return re.sub('ly:clone-parser',
-                  'ly:parser-clone', s)
-
-
-@rule((2, 11, 3), "no-spacing-rods -> extra-spacing-width")
-def conv(s):
-    s = re.sub(r"no-spacing-rods\s+=\s+##t",
-                 r"extra-spacing-width = #'(+inf.0 . -inf.0)", s)
-    s = re.sub(r"no-spacing-rods\s+=\s+##f",
-                 r"extra-spacing-width = #'(0 . 0)", s)
-    return s
-
-
-@rule((2, 11, 5), _("deprecate cautionary-style. Use AccidentalCautionary properties"))
-def conv(s):
-    s = re.sub(r"Accidental\s*#'cautionary-style\s*=\s*#'smaller",
-                 "AccidentalCautionary #'font-size = #-2", s)
-    s = re.sub(r"Accidental\s*#'cautionary-style\s*=\s*#'parentheses",
-                 "AccidentalCautionary #'parenthesized = ##t", s)
-    s = re.sub(r"([A-Za-z]+)\s*#'cautionary-style\s*=\s*#'parentheses",
-                 r"\1 #'parenthesized = ##t", s)
-    s = re.sub(r"([A-Za-z]+)\s*#'cautionary-style\s*=\s*#'smaller",
-                 r"\1 #'font-size = #-2", s)
-    return s
-
-
-@rule((2, 11, 6), _("Rename accidental glyphs, use glyph-name-alist."))
-def conv(s):
-
-    def sub_acc_name(m):
-        idx = int(m.group(1).replace('M', '-'))
-
-        return ["accidentals.doublesharp",
-                "accidentals.sharp.slashslash.stemstemstem",
-                "accidentals.sharp",
-                "accidentals.sharp.slashslash.stem",
-                "accidentals.natural",
-                "accidentals.mirroredflat",
-                "accidentals.flat",
-                "accidentals.mirroredflat.flat",
-                "accidentals.flatflat"][4-idx]
-
-    s = re.sub(r"accidentals[.](M?[-0-9]+)",
-                 sub_acc_name, s)
-    s = re.sub(r"(KeySignature|Accidental[A-Za-z]*)\s*#'style\s*=\s*#'([a-z]+)",
-                 r"\1 #'glyph-name-alist = #alteration-\2-glyph-name-alist", s)
-    # FIXME: standard vs default, alteration-FOO vs FOO-alteration
-    s = s.replace('alteration-default-glyph-name-alist',
-                      'standard-alteration-glyph-name-alist')
-    return s
-
-
-@rule((2, 11, 10), """allowBeamBreak -> Beam #'breakable = ##t
-addquote -> addQuote
-""")
-def conv(s):
-    s = re.sub(r'(\\set\s+)?([A-Z][a-zA-Z]+\s*\.\s*)allowBeamBreak',
-                 r"\\override \2Beam #'breakable", s)
-    s = re.sub(r'(\\set\s+)?allowBeamBreak',
-                 r"\\override Beam #'breakable", s)
-    s = re.sub(r'addquote', 'addQuote', s)
-    if re.search("Span_dynamic_performer", s):
-        stderr_write(
-            "Span_dynamic_performer has been merged into Dynamic_performer")
-
-    return s
-
-
-@rule((2, 11, 11), "layout-set-staff-size -> layout-set-absolute-staff-size")
-def conv(s):
-    s = re.sub(r'\(layout-set-staff-size \(\*\s*([0-9.]+)\s*(pt|mm|cm)\)\)',
-                 r'(layout-set-absolute-staff-size (* \1 \2))', s)
-    return s
-
-
-@rule((2, 11, 13), "#'arrow = ##t -> #'bound-details #'right #'arrow = ##t")
-def conv(s):
-    s = re.sub(r"\\override\s*([a-zA-Z.]+)\s*#'arrow\s*=\s*##t",
-                 r"\\override \1 #'bound-details #'right #'arrow = ##t",
-                 s)
-
-    if re.search('edge-text', s):
-        stderr_write(NOT_SMART % _("edge-text settings for TextSpanner"))
-        stderr_write(_("Use\n\n%s") %
-                     "\t\\override TextSpanner #'bound-details #'right #'text = <right-text>\n"
-                     "\t\\override TextSpanner #'bound-details #'left #'text = <left-text>\n")
-    return s
-
-
-@rule((2, 11, 15), "TextSpanner #'edge-height -> #'bound-details #'right/left #'text = ...\n\
-Remove 'forced-distance for fixed spacing between staves in a PianoStaff.")
-def conv(s):
-    def sub_edge_height(m):
-        s = ''
-        for (var, h) in [('left', m.group(3)),
-                         ('right', m.group(4))]:
-
-            if h and float(h):
-                once = m.group(1)
-                if not once:
-                    once = ''
-                context = m.group(2)
-                if not context:
-                    context = ''
-
-                s += (r"%s \override %sTextSpanner #'bound-details #'%s #'text = \markup { \draw-line #'(0 . %s) }"
-                      % (once, context, var, h))
-
-                s += '\n'
-
-        return s
-
-    s = re.sub(
-        r"(\\once)?\s*\\override\s*([a-zA-Z]+\s*[.]\s*)?TextSpanner\s*#'edge-height\s*=\s*#'\(\s*([0-9.-]+)\s+[.]\s+([0-9.-]+)\s*\)", sub_edge_height, s)
-    if re.search(r"#'forced-distance", s):
-        stderr_write(NOT_SMART % "VerticalAlignment #'forced-distance")
-        stderr_write(_("Use the `alignment-offsets' sub-property of\n"))
-        stderr_write(_("NonMusicalPaperColumn #'line-break-system-details\n"))
-        stderr_write(_("to set fixed distances between staves.\n"))
-    return s
-
-
-@rule((2, 11, 23), "#'break-align-symbol -> #'break-align-symbols")
-def conv(s):
-    s = re.sub(r"\\override\s*([a-zA-Z.]+)\s*#'break-align-symbol\s*=\s*#'([a-z-]+)",
-                 r"\\override \1 #'break-align-symbols = #'(\2)", s)
-    return s
-
-
-@rule((2, 11, 35), """scripts.caesura -> scripts.caesura.curved.
-""" + _("Use #'style not #'dash-fraction to select solid/dashed lines."))
-def conv(s):
-    s = re.sub(r"scripts\.caesura",
-                 r"scripts.caesura.curved", s)
-
-    if re.search('dash-fraction', s):
-        stderr_write(NOT_SMART % _("all settings related to dashed lines"))
-        stderr_write(
-            _("Use \\override ... #'style = #'line for solid lines and\n"))
-        stderr_write(
-            _("\t\\override ... #'style = #'dashed-line for dashed lines."))
-    return s
-
-
-@rule((2, 11, 38), """\\setEasyHeads -> \\easyHeadsOn, \\fatText -> \\textLengthOn,
-\\emptyText -> \\textLengthOff""")
-def conv(s):
-    s = re.sub(r"setEasyHeads", r"easyHeadsOn", s)
-    s = re.sub(r"fatText", r"textLengthOn", s)
-    s = re.sub(r"emptyText", r"textLengthOff", s)
-    return s
-
-
-@rule((2, 11, 46), "\\set hairpinToBarline -> \\override Hairpin #'to-barline")
-def conv(s):
-    s = re.sub(r"\\set\s+([a-zA-Z]+)\s*.\s*hairpinToBarline\s*=\s*##([tf]+)",
-                 r"\\override \1.Hairpin #'to-barline = ##\2", s)
-    s = re.sub(r"\\set\s+hairpinToBarline\s*=\s*##([tf]+)",
-                 r"\\override Hairpin #'to-barline = ##\1", s)
-    s = re.sub(r"\\unset\s+([a-zA-Z]+)\s*.\s*hairpinToBarline",
-                 r"\\revert \1.Hairpin #'to-barline", s)
-    s = re.sub(r"\\unset\s+hairpinToBarline",
-                 r"\\revert Hairpin #'to-barline", s)
-    s = re.sub(r"hairpinToBarline\s*=\s*##([tf]+)",
-                 r"\\override Hairpin #'to-barline = ##\1", s)
-    s = re.sub(r"\\set (de|)crescendoSpanner = #'dashed-line",
-                 r"\\set \1crescendoSpanner = #'text", s)
-    return s
-
-
-@rule((2, 11, 48), "\\compressMusic -> \\scaleDurations")
-def conv(s):
-    s = re.sub(r"compressMusic", r"scaleDurations", s)
-    return s
-
-
-@rule((2, 11, 50), _("metronomeMarkFormatter uses text markup as second argument,\n\
-fret diagram properties moved to fret-diagram-details."))
-def conv(s):
-    # warning 1/2: metronomeMarkFormatter uses text markup as second argument
-    if re.search('metronomeMarkFormatter', s):
-        stderr_write(NOT_SMART % "metronomeMarkFormatter")
-        stderr_write(
-            _("metronomeMarkFormatter got an additional text argument.\n"))
-        stderr_write(_("The function assigned to Score.metronomeMarkFunction now uses the signature\n%s") %
-                     "\t(format-metronome-markup text dur count context)\n")
-
-    # warning 2/2: fret diagram properties moved to fret-diagram-details
-    fret_props = ['barre-type',
-                  'dot-color',
-                  'dot-radius',
-                  'finger-code',
-                  'fret-count',
-                  'label-dir',
-                  'number-type',
-                  'string-count',
-                  'xo-font-magnification',
-                  'mute-string',
-                  'open-string',
-                  'orientation']
-    for prop in fret_props:
-        if re.search(prop, s):
-            stderr_write(NOT_SMART %
-                         (_("%s in fret-diagram properties") % prop))
-            stderr_write(_('Use %s\n') % "fret-diagram-details")
-    return s
-
-
-@rule((2, 11, 51), "\\octave -> \\octaveCheck, \\arpeggioUp -> \\arpeggioArrowUp,\n\
-\\arpeggioDown -> \\arpeggioArrowDown, \\arpeggioNeutral -> \\arpeggioNormal,\n\
-\\setTextCresc -> \\crescTextCresc, \\setTextDecresc -> \\dimTextDecresc,\n\
-\\setTextDecr -> \\dimTextDecr, \\setTextDim -> \\dimTextDim,\n\
-\\setHairpinCresc -> \\crescHairpin, \\setHairpinDecresc -> \\dimHairpin,\n\
-\\sustainUp -> \\sustainOff, \\sustainDown -> \\sustainOn\n\
-\\sostenutoDown -> \\sostenutoOn, \\sostenutoUp -> \\sostenutoOff")
-def conv(s):
-    s = re.sub(r"\\octave(?![a-zA-Z])", r"\\octaveCheck", s)
-    s = re.sub(r"arpeggioUp", r"arpeggioArrowUp", s)
-    s = re.sub(r"arpeggioDown", r"arpeggioArrowDown", s)
-    s = re.sub(r"arpeggioNeutral", r"arpeggioNormal", s)
-    s = re.sub(r"setTextCresc", r"crescTextCresc", s)
-    s = re.sub(r"setTextDecresc", r"dimTextDecresc", s)
-    s = re.sub(r"setTextDecr", r"dimTextDecr", s)
-    s = re.sub(r"setTextDim", r"dimTextDim", s)
-    s = re.sub(r"setHairpinCresc", r"crescHairpin", s)
-    s = re.sub(r"setHairpinDecresc", r"dimHairpin", s)
-    s = re.sub(r"sustainUp", r"sustainOff", s)
-    s = re.sub(r"sustainDown", r"sustainOn", s)
-    s = re.sub(r"sostenutoDown", r"sostenutoOn", s)
-    s = re.sub(r"sostenutoUp", r"sostenutoOff", s)
-    return s
-
-
-@rule((2, 11, 52), "\\setHairpinDim -> \\dimHairpin")
-def conv(s):
-    s = s.replace("setHairpinDim", "dimHairpin")
-    return s
-
-
-@rule((2, 11, 53), "infinite-spacing-height -> extra-spacing-height")
-def conv(s):
-    s = re.sub(r"infinite-spacing-height\s+=\s+##t",
-                 r"extra-spacing-height = #'(-inf.0 . +inf.0)", s)
-    s = re.sub(r"infinite-spacing-height\s+=\s+##f",
-                 r"extra-spacing-height = #'(0 . 0)", s)
-    return s
-
-
-@rule((2, 11, 55), "#(set-octavation oct) -> \\ottava #oct,\n\
-\\put-adjacent markup axis dir markup -> \\put-adjacent axis dir markup markup")
-def conv(s):
-    s = re.sub(r"#\(set-octavation (-*[0-9]+)\)", r"\\ottava #\1", s)
-    if re.search('put-adjacent', s):
-        stderr_write(NOT_SMART % _("\\put-adjacent argument order"))
-        stderr_write(_("Axis and direction now come before markups:\n"))
-        stderr_write(_("\\put-adjacent axis dir markup markup."))
-        stderr_write("\n")
-    return s
-
-
-@rule((2, 11, 57), "\\center-align -> \\center-column, \\hcenter -> \\center-align")
-def conv(s):
-    s = re.sub(r"([\\:]+)center-align", r"\1center-column", s)
-    s = re.sub(r"hcenter(\s+)", r"center-align\1", s)
-    return s
-
-
-@rule((2, 11, 60), "printallheaders -> print-all-headers")
-def conv(s):
-    s = re.sub(r"printallheaders", r"print-all-headers", s)
-    return s
-
-
-@rule((2, 11, 61), "gregorian-init.ly -> gregorian.ly")
-def conv(s):
-    s = re.sub(r'\\include(\s+)"gregorian-init.ly"',
-                 r'\\include\1"gregorian.ly"', s)
-    return s
-
-
-@rule((2, 11, 62), "makam-init.ly -> makam.ly, \\bigger -> \\larger")
-def conv(s):
-    s = re.sub(r'\\include(\s+)"makam-init.ly"',
-                 r'\\include\1"makam.ly"', s)
-    s = re.sub(r"([\\:])bigger", r"\1larger", s)
-    return s
-
-
-@rule((2, 11, 64), "systemSeparatorMarkup -> system-separator-markup,\n\
-InnerStaffGroup -> StaffGroup, InnerChoirStaff -> ChoirStaff")
-def conv(s):
-    s = re.sub(r'systemSeparatorMarkup', r'system-separator-markup', s)
-    if re.search(r'\\InnerStaffGroup', s):
-        stderr_write(NOT_SMART % _("re-definition of InnerStaffGroup"))
-        stderr_write(FROM_TO % ("InnerStaffGroup", "StaffGroup"))
-        stderr_write(UPDATE_MANUALLY)
-        raise FatalConversionError()
-    if re.search(r'\\InnerChoirStaff', s):
-        stderr_write(NOT_SMART % _("re-definition of InnerChoirStaff"))
-        stderr_write(FROM_TO % ("InnerChoirStaff", "ChoirStaff"))
-        stderr_write(UPDATE_MANUALLY)
-        raise FatalConversionError()
-
-    s = re.sub('InnerStaffGroup', 'StaffGroup', s)
-    s = re.sub('InnerChoirStaff', 'ChoirStaff', s)
-    return s
-
-
-@rule((2, 12, 0),
-      _("Syntax changes for \\addChordShape and \\chord-shape") + "\n" +
-      _("bump version for release"))
-def conv(s):
-    if re.search(r'\\addChordShape', s):
-        stderr_write(NOT_SMART % "addChordShape")
-        stderr_write(_("stringTuning must be added to addChordShape call.\n"))
-        stderr_write(UPDATE_MANUALLY)
-        raise FatalConversionError()
-    if re.search(r'\\chord-shape', s):
-        stderr_write(NOT_SMART % "chord-shape")
-        stderr_write(_("stringTuning must be added to chord-shape call.\n"))
-        stderr_write(UPDATE_MANUALLY)
-        raise FatalConversionError()
-    return s
-
-
-@rule((2, 12, 3),
-      _("Remove oldaddlyrics"))
-def conv(s):
-    if re.search(r'\\oldaddlyrics', s):
-        stderr_write(NOT_SMART % "oldaddlyrics")
-        stderr_write(_("oldaddlyrics is no longer supported. \n \
-        Use addlyrics or lyricsto instead.\n"))
-        stderr_write(UPDATE_MANUALLY)
-        raise FatalConversionError()
-    return s
-
-
-@rule((2, 13, 0), _("keySignature property not reversed any more\n\
-MIDI 47: orchestral strings -> orchestral harp"))
-def conv(s):
-    if re.search(r'\set Staff.keySignature', s):
-        stderr_write(NOT_SMART % "Staff.keySignature")
-        stderr_write(_("The alist for Staff.keySignature is no \
-longer in reversed order.\n"))
-    s = s.replace('"orchestral strings"', '"orchestral harp"')
-    return s
-
-
-@rule((2, 13, 1),
-      _("\\bar \".\" now produces a thick barline\n\
-ly:hairpin::after-line-breaking -> ly:spanner::kill-zero-spanned-time\n\
-Dash parameters for slurs and ties are now in dash-definition"))
-def conv(s):
-    if re.search(r'\\bar\s*"\."', s):
-        stderr_write(NOT_SMART % "\\bar \".\"")
-        stderr_write(_("\\bar \".\" now produces a thick barline.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    s = re.sub(r'ly:hairpin::after-line-breaking',
-                 r'ly:spanner::kill-zero-spanned-time', s)
-    if re.search(r"(Slur|Tie)\w+#'dash-fraction", s) \
-            or re.search(r"(Slur|Tie)\w+#'dash-period", s):
-        stderr_write(NOT_SMART % "dash-fraction, dash-period")
-        stderr_write(
-            _("Dash parameters for slurs and ties are now in \'dash-definition.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    return s
-
-
-@rule((2, 13, 4),
-      _("Autobeaming rules have changed.  override-auto-beam-setting and\n\
-revert-auto-beam-setting have been eliminated.\n\
-\\overrideBeamSettings has been added.\n\
-beatGrouping has been eliminated.\n\
-Different settings for vertical layout.\n\
-ly:system-start-text::print -> system-start-text::print\n\
-Beam #'thickness -> Beam #'beam-thickness\n\
-ly:note-head::brew-ez-stencil -> note-head::brew-ez-stencil\n\
-ly:ambitus::print -> ambitus::print\n\
-Explicit dynamics context definition from `Piano centered dynamics'\n\
-template replaced by new `Dynamics' context."))
-def conv(s):
-    if re.search("override-auto-beam-setting", s):
-        stderr_write(NOT_SMART % "override-auto-beam-setting")
-        stderr_write(_(" \
-   Autobeam settings are now overriden with \\overrideBeamSettings.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    if re.search("revert-auto-beam-setting", s):
-        stderr_write(NOT_SMART % "override-auto-beam-setting")
-        stderr_write(_(" \
-   Autobeam settings are now reverted with \\revertBeamSettings.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    s = re.sub(r"\\set\s+beatGrouping", r"\\setBeatGrouping", s)
-    if re.search(r"\w+\s*.\s*beatGrouping", s):
-        stderr_write(NOT_SMART % "beatGrouping")
-        stderr_write(_(" \
-   beatGrouping with a specified context must now be accomplished with\n\
-   \\overrideBeamSettings.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    if re.search(r'alignment-offsets', s):
-        stderr_write(NOT_SMART % "alignment-offsets")
-        stderr_write(_("alignment-offsets has been changed to alignment-distances: \
-you must now specify the distances between staves rather than the offset of staves.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    s = re.sub('ly:(system-start-text::print|note-head::brew-ez-stencil|ambitus::print)',
-                 '\\1', s)
-    s = re.sub('(\\bBeam\\s+#\')(?=thickness\\b)', '\\1beam-', s)
-    s = re.sub(r'(\\context\s*\{{1}[^\}]+\\type\s+"?Engraver_group"?\s+\\name\s+"*Dynamics"*[^\}]*\}{1})',
-                 '% [Convert-ly] The Dynamics context is now included by default.', s)
-    return s
-
-
-@rule((2, 13, 10),
-      _("Remove obsolete engravers/translators: Note_swallow_translator,\n\
-Rest_swallow_translator, Skip_event_swallow_translator, Swallow_engraver,\n\
-Swallow_performer and String_number_engraver.\n\
-New vertical spacing variables."))
-def conv(s):
-    s = re.sub(r'\\(consists|remove)\s+"*(Swallow_(engraver|performer)|'
-                 '(Note|Rest|Skip_event)_swallow_translator|String_number_engraver)"*',
-                 '', s)
-
-    # match through the end of assignments in the form "x = 30", "x = 1 \in", or "x = #3"
-    s = re.sub(r"(page-top-space)\s*=\s*(([+-]?[.\d]*\s*\\[-\w]+)|(#?\s*[-+]?[.\d]+))",
-                 r"obsolete-\g<0>"
-                 r"  top-system-spacing #'space = #(/ obsolete-\1 staff-space)",
-                 s)
-    s = re.sub(r"(between-system-space)\s*=\s*(([+-]?[.\d]*\s*\\[-\w]+)|(#?\s*[-+]?[.\d]+))",
-                 r"obsolete-\g<0>"
-                 r"  between-system-spacing #'space = #(/ obsolete-\1 staff-space)"
-                 r"  between-scores-system-spacing #'space = #(/ obsolete-\1 staff-space)",
-                 s)
-    s = re.sub(r"(between-system-padding)\s*=\s*(([+-]?[.\d]*\s*\\[-\w]+)|(#?\s*[-+]?[.\d]+))",
-                 r"obsolete-\g<0>"
-                 r"  between-system-spacing #'padding = #(/ obsolete-\1 staff-space)"
-                 r"  between-scores-system-spacing #'padding = #(/ obsolete-\1 staff-space)",
-                 s)
-    s = re.sub(r"((before|between|after)-title-space)\s*=\s*(([+-]?[.\d]*\s*\\[-\w]+)|(#?\s*[-+]?[.\d]+))",
-                 r"obsolete-\g<0>"
-                 r"  \2-title-spacing #'space = #(/ obsolete-\1 staff-space)",
-                 s)
-
-    if re.search(r"VerticalAxisGroup\s*#\s*'minimum-Y-extent", s):
-        stderr_write(NOT_SMART % "minimum-Y-extent")
-        stderr_write(
-            _("Vertical spacing no longer depends on the Y-extent of a VerticalAxisGroup.\n"))
-        stderr_write(UPDATE_MANUALLY)
-
-    return s
-
-
-@rule((2, 13, 16),
-      _("Unify fetaNumber and fetaDynamic encodings"))
-def conv(s):
-    return re.sub(r'\bfeta(Number|Dynamic)', 'fetaText', s)
-
-
-@rule((2, 13, 18),
-      _("\\RemoveEmpty*StaffContext -> \\*Staff \\RemoveEmptyStaves"))
-def conv(s):
-    s = re.sub(r"\\RemoveEmpty(|Drum|Rhythmic|Tab)StaffContext",
-                 r"\\\1Staff \\RemoveEmptyStaves",
-                 s)
-    s = re.sub(r"\\AncientRemoveEmptyStaffContext",
-                 r"\\VaticanaStaff \\RemoveEmptyStaves",
-                 s)
-    return s
-
-
-@rule((2, 13, 20),
-      _("\\cresc etc. are now postfix operators"))
-def conv(s):
-    s = re.sub(r'\\(cresc|dim|endcresc|enddim)\b', r'\\deprecated\1', s)
-    return s
-
-
-@rule((2, 13, 27),
-      ("interval-translate -> coord-translate"))
-def conv(s):
-    s = re.sub('interval-translate', 'coord-translate', s)
-    return s
-
-
-@rule((2, 13, 29),
-      _("Eliminate beamSettings, beatLength, \\setBeatGrouping, \\overrideBeamSettings and \\revertBeamSettings.\n\
-\"accordion.accEtcbase\" -> \"accordion.etcbass\""))
-def conv(s):
-    def sub_acc(m):
-        d = {
-            'Dot': 'dot',
-            'Discant': 'discant',
-            'Bayanbase': 'bayanbass',
-            'Stdbase': 'stdbass',
-            'Freebase': 'freebass',
-            'OldEE': 'oldEE'
-        }
-        return '"accordion.%s"' % d[m.group(1)]
-
-    s = re.sub(r'"accordion\.acc([a-zA-Z]+)"',
-                 sub_acc, s)
-    if re.search(r'overrideBeamSettings', s):
-        stderr_write(NOT_SMART % "\\overrideBeamSettings")
-        stderr_write(
-            _("Use \\set beamExceptions or \\overrideTimeSignatureSettings.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    if re.search(r'revertBeamSettings', s):
-        stderr_write(NOT_SMART % "\\revertBeamSettings")
-        stderr_write(
-            _("Use \\set beamExceptions or \\revertTimeSignatureSettings.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    if re.search(r'beamSettings', s):
-        stderr_write(NOT_SMART % "beamSettings")
-        stderr_write(_("Use baseMoment, beatStructure, and beamExceptions.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    if re.search(r'beatLength', s):
-        stderr_write(NOT_SMART % "beatLength")
-        stderr_write(_("Use baseMoment and beatStructure.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    if re.search(r'setBeatGrouping', s):
-        stderr_write(NOT_SMART % "setbeatGrouping")
-        stderr_write(_("Use baseMoment and beatStructure.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    return s
-
-
-@rule((2, 13, 31),
-      _("Woodwind diagrams: Move size, thickness, and graphic from argument list to properties.\n\
-Deprecate negative dash-period for hidden lines: use #'style = #'none instead."))
-def conv(s):
-    if re.search(r'woodwind-diagram', s):
-        stderr_write(NOT_SMART % "woodwind-diagrams")
-        stderr_write(
-            _("Move size, thickness, and graphic to properties.  Argument should be just the key list.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    s = re.sub(r"dash-period\s+=\s*#\s*-[0-9.]+",
-                 r"style = #'none",
-                 s)
-    return s
-
-
-@rule((2, 13, 36),
-      _("Rename vertical spacing variables.\n\
-Add fretboard-table argument to savePredefinedFretboard."))
-def conv(s):
-    s = re.sub('after-title-spacing',           'markup-system-spacing', s)
-    s = re.sub('before-title-spacing',          'score-markup-spacing',  s)
-    s = re.sub('between-scores-system-spacing', 'score-system-spacing',  s)
-    # this rule also converts page-breaking-between-system-spacing:
-    s = re.sub('between-system-spacing',        'system-system-spacing', s)
-    s = re.sub('between-title-spacing',         'markup-markup-spacing', s)
-    s = re.sub('bottom-system-spacing',         'last-bottom-spacing',   s)
-    s = re.sub('top-title-spacing',             'top-markup-spacing',    s)
-
-    s = re.sub(r"storePredefinedDiagram",
-                 r"storePredefinedDiagram #default-fret-table",
-                 s)
-    return s
-
-
-@rule((2, 13, 39),
-      _("Rename vertical spacing grob properties."))
-def conv(s):
-    # this rule also converts default-next-staff-spacing:
-    s = re.sub('next-staff-spacing',
-                 'staff-staff-spacing',             s)
-    # this is not a mistake:
-    #   Both 'next- and 'between- become 'staff-staff-spacing.
-    #   There is no conflict since they are in different grobs.
-    s = re.sub('between-staff-spacing',
-                 'staff-staff-spacing',             s)
-    s = re.sub('after-last-staff-spacing',
-                 'staffgroup-staff-spacing',        s)
-    s = re.sub('inter-staff-spacing',
-                 'nonstaff-relatedstaff-spacing',   s)
-    s = re.sub('non-affinity-spacing',
-                 'nonstaff-unrelatedstaff-spacing', s)
-    s = re.sub('inter-loose-line-spacing',
-                 'nonstaff-nonstaff-spacing',       s)
-
-    return s
-
-
-@rule((2, 13, 40),
-      _("Remove \\paper variables head-separation and foot-separation."))
-def conv(s):
-    if re.search(r'head-separation', s):
-        stderr_write(NOT_SMART % "head-separation")
-        stderr_write(_("Adjust settings for top-system-spacing instead.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    if re.search(r'foot-separation', s):
-        stderr_write(NOT_SMART % "foot-separation")
-        stderr_write(_("Adjust settings for last-bottom-spacing instead.\n"))
-        stderr_write(UPDATE_MANUALLY)
-
-    return s
-
-
-@rule((2, 13, 42),
-      _("Rename space to basic-distance in various spacing alists.\n\
-Remove HarmonicParenthesesItem grob."))
-def conv(s):
-    s = re.sub(
-        r'\(space\s+\.\s+([0-9]*\.?[0-9]*)\)', r'(basic-distance . \1)', s)
-    s = re.sub(r"#'space\s+=\s+#?([0-9]*\.?[0-9]*)",
-                 r"#'basic-distance = #\1", s)
-    if re.search(r'HarmonicParenthesesItem', s):
-        stderr_write(NOT_SMART % "HarmonicParenthesesItem")
-        stderr_write(_("HarmonicParenthesesItem has been eliminated.\n"))
-        stderr_write(
-            _("Harmonic parentheses are part of the TabNoteHead grob.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    return s
-
-
-@rule((2, 13, 44),
-      _("Remove context from overrideTimeSignatureSettings and revertTimeSignatureSettings.\n"))
-def conv(s):
-    s = re.sub(
-        r"\\(override|revert)TimeSignatureSettings(\s+[^#]*)(#[^#]*)#", r"\\\1TimeSignatureSettings\2#", s)
-    return s
-
-
-@rule((2, 13, 46),
-      _("Change stringTunings from a list of semitones to a list of pitches.\n"
-          "Change tenor and baritone ukulele names in string tunings.\n"
-          "Generate messages for manual conversion of vertical spacing if required."))
-def conv(s):
-    def semitones2pitch(semitones):
-        steps = [0, 0, 1, 1, 2, 3, 3, 4, 4, 5, 5, 6]
-        alterations = ["NATURAL", "SHARP", "NATURAL", "SHARP", "NATURAL",
-                       "NATURAL", "SHARP", "NATURAL", "SHARP", "NATURAL", "SHARP", "NATURAL"]
-        octave = 0
-        while semitones > 11:
-            octave += 1
-            semitones -= 12
-        while semitones < 0:
-            octave -= 1
-            semitones += 12
-        pitchArgs = "%d %d %s" % (
-            octave, steps[semitones], alterations[semitones])
-        return pitchArgs
-
-    def convert_tones(semitone_list):
-        tones = semitone_list.split()
-        res = ""
-        for tone in tones:
-            args = semitones2pitch(int(tone))
-            res += ",(ly:make-pitch " + args + ") "
-        return res
-
-    def new_tunings(matchobj):
-        return "stringTunings = #`(" + convert_tones(matchobj.group(1)) + ")"
-    s = re.sub(r"stringTunings\s*=\s*#'\(([\d\s-]*)\)",
-                 new_tunings, s)
-
-    s = re.sub(r"ukulele-(tenor|baritone)-tuning", r"\1-ukulele-tuning", s)
-
-    if re.search(r"[^-]page-top-space", s):
-        stderr_write(NOT_SMART % "page-top-space")
-        stderr_write(UPDATE_MANUALLY)
-    if re.search(r"[^-]between-system-(space|padding)", s):
-        stderr_write(NOT_SMART % "between-system-space, -padding")
-        stderr_write(UPDATE_MANUALLY)
-    if re.search(r"[^-](before|between|after)-title-space", s):
-        stderr_write(NOT_SMART % "before-, between-, after-title-space")
-        stderr_write(UPDATE_MANUALLY)
-    if re.search(r"\\name\s", s):
-        stderr_write(
-            "\n" + _("Vertical spacing changes might affect user-defined contexts.") + "\n")
-        stderr_write(UPDATE_MANUALLY)
-
-    return s
-
-
-@rule((2, 13, 48),
-      _("Replace bar-size with bar-extent."))
-def conv(s):
-    def size_as_extent(matchobj):
-        half = "%g" % (float(matchobj.group(1)) / 2)
-        return "bar-extent = #'(-" + half + " . " + half + ")"
-
-    s = re.sub(r"bar-size\s*=\s*#([0-9\.]+)", size_as_extent, s)
-
-    return s
-
-
-@rule((2, 13, 51),
-      _("Woodwind diagrams: Changes to the clarinet diagram."))
-def conv(s):
-    if re.search(r'\\woodwind-diagram\s*#[^#]*clarinet\s', s):
-        stderr_write(NOT_SMART % "woodwind-diagrams")
-        stderr_write(
-            _("Clarinet fingering changed to reflect actual anatomy of instrument.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    return s
-
-
-@rule((2, 14, 0),
-      _("bump version for release"))
-def conv(s):
-    return s
-
-
-@rule((2, 15, 7),
-      _("Handling of non-automatic footnotes."))
-def conv(s):
-    if re.search(r'\\footnote', s):
-        stderr_write(NOT_SMART % "\\footnote")
-        stderr_write(
-            _("If you are using non-automatic footnotes, make sure to set footnote-auto-numbering = ##f in the paper block.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    return s
-
-
-@rule((2, 15, 9),
-      _("Change in internal property for MultiMeasureRest"))
-def conv(s):
-    if re.search(r'use-breve-rest', s):
-        stderr_write(NOT_SMART % "use-breve-rest")
-        stderr_write(
-            _("This internal property has been replaced by round-up-to-longer-rest, round-up-exceptions and usable-duration-logs.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    return s
-
-
-@rule((2, 15, 10),
-      _("Creation of a Flag grob and moving of certain Stem properties to this grob"))
-def conv(s):
-    s = re.sub(r"Stem\s+#'flag-style", r"Flag #'style", s)
-    s = re.sub(r"Stem\s+#'stroke-style", r"Flag #'stroke-style", s)
-    s = re.sub(r"Stem\s+#'flag", r"Flag #'stencil", s)
-    s = re.sub(r"(\s+(?:\\once\s*)?)\\override\s+Stem\s+#'transparent\s*=\s*##t",
-                 r"\g<1>\\override Stem #'transparent = ##t\g<1>\\override Flag #'transparent = ##t", s)
-    s = re.sub(r"(\s+(?:\\once\s*)?)\\revert\s*Stem\s+#'transparent",
-                 r"\g<1>\\revert Stem #'transparent\g<1>\\revert Flag #'transparent", s)
-    s = re.sub(r"(\s+(?:\\once\s*)?)\\override\s+Stem\s+#'stencil\s*=\s*##f",
-                 r"\g<1>\\override Stem #'stencil = ##f\g<1>\\override Flag #'stencil = ##f", s)
-    s = re.sub(r"(\s+(?:\\once\s*)?)\\revert\s*Stem\s+#'stencil",
-                 r"\g<1>\\revert Stem #'stencil\g<1>\\revert Flag #'stencil", s)
-    return s
-
-
-@rule((2, 15, 16), r"\makeStringTuning, \contextStringTuning -> \stringTuning")
-def conv(s):
-    s = re.sub(r"(\s+)\\contextStringTuning(\s+)#'([-a-zA-Z]+)(\s+<[^<>]+>)",
-                 r"""\g<1>#(define \g<3> #{ \\stringTuning\g<4> #})\g<1>\\set stringTunings = #\g<3>""",
-                 s)
-    s = re.sub(r"""
-\\makeStringTuning(\s+)#'([-a-zA-Z]+)""",
-                 r"""
-"\g<2>" = \\stringTuning""", s)
-    s = re.sub(r"\\makeStringTuning(\s+)#'([-a-zA-Z]+)(\s+<[^<>]+>)",
-                 r"#(define \g<2> #{ \\stringTuning\g<3> #})", s)
-    return s
-
-
-@rule((2, 15, 17), "\\markuplines -> \\markuplist\n\
-Change Beam broken slope syntax.")
-def conv(s):
-    s = re.sub(r"""
-\\markuplines( +)([^ ].*)
-            \1([^ ])""", r"""
-\\markuplist\g<1>\g<2>
-           \g<1>\g<3>""", s)
-    s = re.sub(r"\\markuplines", r"\\markuplist", s)
-    s = re.sub(r"@funindex markuplines", r"@funindex markuplist", s)
-    if re.search(r'consistent-broken-slope', s):
-        stderr_write(NOT_SMART % "consistent-broken-slope")
-        stderr_write(
-            _("consistent-broken-slope is now handled through the positions callback.\n"))
-        stderr_write(
-            _("input/regression/beam-broken-classic.ly shows how broken beams are now handled.\n"))
-        stderr_write(UPDATE_MANUALLY)
-    return s
-
-
-def paren_matcher(n):
-    # poor man's matched paren scanning, gives up
-    # after n+1 levels.  Matches any string with balanced
-    # parens inside; add the outer parens yourself if needed.
-    # Nongreedy.
-    return r"[^()]*?(?:\("*n+r"[^()]*?"+r"\)[^()]*?)*?"*n
-
-
-def undollar_scm(m):
-    return re.sub(r"\$(.?)", r"\1", m.group(0))
-
-
-def undollar_embedded(m):
-    s = re.sub(r"#\$", "#", m.group(1))
-    # poor man's matched paren scanning after #, gives up
-    # after 25 levels.
-    s = re.sub(r"#`?\("+paren_matcher(25)+r"\)", undollar_scm, s)
-    return m.string[m.start(0):m.start(1)] + s + m.string[m.end(1):m.end(0)]
-
-
-def strip_export(s):
-    return re.sub(r"\(ly:export\s+(" + paren_matcher(25) + r")\)",
-                  r"\1", s)
-
-
-def export_puller(m):
-    if not re.search(r"ly:export\s+", m.group(0)):
-        return m.group(0)
-    return "$" + strip_export(m.string[m.start(0)+1:m.end(0)])
-
-
-def ugly_function_rewriter(m):
-    return m.string[m.start(0):m.start(1)] + strip_export(m.group(1)) + m.string[m.end(1):m.end(0)]
-
-
-should_really_be_music_function = "(?:\
-set-time-signature|empty-music|add-grace-property|\
-remove-grace-property|set-accidental-style)"
-
-
-def record_ugly(m):
-    global should_really_be_music_function
-    if not re.match(should_really_be_music_function, m.group(1)) \
-            and re.search(r"ly:export\s+", m.group(2)):
-        should_really_be_music_function = \
-            should_really_be_music_function[:-1] + "|" + m.group(1) + ")"
-    return m.group(0)
-
-
-@rule((2, 15, 18), "#$ -> #, ly:export -> $")
-def conv(s):
-    s = re.sub(r"(?s)#@?\{(.*?)#@?\}", undollar_embedded, s)
-    s = re.sub(r"#\(define(?:-public)?\s+\(([-a-zA-Z]+)"
-                 + r"\b[^()]*?\)(" + paren_matcher(25)
-                 + r")\)", record_ugly, s)
-    s = re.sub(r"\(define(?:-public)?\s+\(" + should_really_be_music_function
-                 + r"\b[^()]*\)(" + paren_matcher(25)
-                 + r")\)", ugly_function_rewriter, s)
-    s = re.sub(r"#(?=\(" + should_really_be_music_function + ")", "$", s)
-    s = re.sub(r"#\(markup\*(?=\s)", r"$(markup", s)
-    s = re.sub(r"#\("+paren_matcher(25)+r"\)", export_puller, s)
-    if re.search(r"\(ly:export\s+", s):
-        stderr_write(NOT_SMART % "ly:export")
-    return s
-
-
-@rule((2, 15, 19), r"$(set-time-signature ...) -> \time")
-def conv(s):
-    s = re.sub(r"\$\(set-time-signature\s+([0-9]+)\s+([0-9]+)\s*\)",
-                 r"\\time \1/\2", s)
-    s = re.sub(r"\$\(set-time-signature\s+([0-9]+)\s+([0-9]+)\s+(" +
-                 paren_matcher(5) + r")\)", r"\\time #\3 \1/\2", s)
-    if re.search(r"\(set-time-signature\s+", s):
-        stderr_write(NOT_SMART % "set-time-signature")
-    return s
-
-
-@rule((2, 15, 20), r"$(set-accidental-style ...) -> \accidentalStyle")
-def conv(s):
-    s = re.sub(r"\$\(set-accidental-style\s+'([-a-z]+)\)",
-                 r'\\accidentalStyle "\1"', s)
-    s = re.sub(r"\$\(set-accidental-style\s+'([-a-z]+)\s+'([-A-Za-z]+)\s*\)",
-                 r'''\\accidentalStyle #'\2 "\1"''', s)
-    s = re.sub(r"(@funindex\s+)set-accidental-style",
-                 r"\1\\accidentalStyle", s)
-    return s
-
-
-def brace_matcher(n):
-    # poor man's matched brace scanning, gives up
-    # after n+1 levels.  Matches any string with balanced
-    # braces inside; add the outer braces yourself if needed.
-    # Nongreedy.
-    return r"[^{}]*?(?:{"*n+r"[^{}]*?"+r"}[^{}]*?)*?"*n
-
-
-matchstring = r'"(?:[^"\\]|\\.)*"'
-matcharg = (r"\s+(?:[$#]['`]?\s*(?:[a-zA-Z][^ \t\n()\\]*|" + matchstring
-            + r"|#?\(" + paren_matcher(20) + r"\)|"
-            + r"-?(?:[0-9]+(?:\.[0-9]*)?|\.[0-9]+)|"
-            + r"#(?:[tf]|\\.|@?\{" + brace_matcher(10) + r"#@?\}))|"
-            + matchstring + r"|\\[a-z_A-Z]+|[0-9]+(?:/[0-9]+)?|-[0-9]+)")
-matchfullmarkup = (r'\\markup\s*(?:@?\{' + brace_matcher(20) + r'\}|' +
-                   matchstring + r'|(?:\\[a-z_A-Z][a-z_A-Z-]*(?:' + matcharg +
-                   r')*?\s*)*(?:' + matchstring + r"|@?\{" + brace_matcher(20) +
-                   r"\}))")
-matchmarkup = "(?:" + matchstring + "|" + matchfullmarkup + ")"
-
-
-@rule((2, 15, 25), r"\(auto)?Footnote(Grob)? -> \footnote")
-def conv(s):
-    # The following replacement includes the final markup argument in
-    # the match in order to better avoid touching the equally named
-    # markup function.  The other functions have unique names, so
-    # there is no point in including their last, possibly complex
-    # argument in the match.
-    s = re.sub(r"\\footnote(" + matcharg + (r")(\s*" + matchmarkup)*2 + ")",
-                 r"\\footnote\2\1\3", s)
-    s = re.sub(r"\\footnoteGrob"+("(" + matcharg + ")")*2 + r"(\s*" + matchmarkup + ")",
-                 r"\\footnote\3\2\1", s)
-    s = re.sub(r"\\autoFootnoteGrob" + ("(" + matcharg + ")")*2,
-                 r"\\footnote\2\1", s)
-    s = re.sub(r"\\autoFootnote",
-                 r"\\footnote", s)
-    return s
-
-
-@rule((2, 15, 32), r"tempoWholesPerMinute -> \tempo")
-def conv(s):
-    def sub_tempo(m):
-        num = int(m.group(1))
-        den = int(m.group(2))
-
-        if (den & (den - 1)) != 0:
-            return m.group(0)
-
-        # Don't try dotted forms if they result in less than 30 bpm.
-        # It is not actually relevant to get this right since this
-        # only occurs in non-printing situations
-        if den >= 16 and (num % 7) == 0 and num >= 210:
-            return r"\tempo %d.. = %d" % (den/4, num/7)
-
-        if den >= 8 and (num % 3) == 0 and num >= 90:
-            return r"\tempo %d. = %d" % (den/2, num/3)
-
-        return r"\tempo %d = %d" % (den, num)
-
-    s = re.sub(r"\\context\s*@?\{\s*\\Score\s+tempoWholesPerMinute\s*=\s*" +
-                 r"#\(ly:make-moment\s+([0-9]+)\s+([0-9]+)\)\s*@?\}",
-                 sub_tempo, s)
-    return s
-
-
-@rule((2, 15, 39), r"\footnote ... -> \footnote ... \default")
-def conv(s):
-    def not_first(s):
-        def match_fun(m):
-            if m.group(1):
-                return m.group(0)
-            return m.expand(s)
-        return match_fun
-    s = re.sub("(" + matchfullmarkup + ")|"
-                 + r"(\\footnote(?:\s*"
-                 + matchmarkup + ")?" + matcharg + "(?:" + matcharg
-                 + r")?\s+" + matchmarkup + ")",
-                 not_first(r"\2 \\default"), s)
-    return s
-
-
-@rule((2, 15, 40), r"Remove beamWholeMeasure")
-def conv(s):
-    if re.search(r"\bbeamWholeMeasure\b", s):
-        stderr_write(NOT_SMART % "beamWholeMeasure")
-        stderr_write(
-            _("beamExceptions controls whole-measure beaming.") + "\n")
-    return s
-
-
-@rule((2, 15, 42), r"\set stringTuning -> \set Staff.stringTuning")
-def conv(s):
-    s = re.sub(r"(\\set\s+)stringTuning", r"\1Staff.stringTuning", s)
-    return s
-
-
-wordsyntax = r"[a-zA-Z\200-\377]+(?:[-_][a-zA-Z\200-\377]+)*"
-
-
-@rule((2, 15, 43), r'"custom-tuning" = -> custom-tuning =')
-def conv(s):
-    s = re.sub(
-        '\n"(' + wordsyntax + r')"(\s*=\s*\\stringTuning)', "\n\\1\\2", s)
-    return s
-
-
-@rule((2, 16, 0),
-      _("bump version for release"))
-def conv(s):
-    return s
-
-
-@rule((2, 17, 0), r"blank-*-force -> blank-*-penalty")
-def conv(s):
-    s = re.sub('blank-page-force', 'blank-page-penalty', s)
-    s = re.sub('blank-last-page-force', 'blank-last-page-penalty', s)
-    s = re.sub('blank-after-score-page-force',
-                 'blank-after-score-page-penalty', s)
-    return s
-
-
-@rule((2, 17, 4), r"\shape Grob #offsets -> \shape #offsets Grob")
-def conv(s):
-    s = re.sub(r"\\shape(\s+(?:[a-zA-Z]+|" + matchstring + "))(" +
-                 matcharg + ")", r"\\shape\2\1", s)
-    return s
-
-
-barstring = r"(\\bar|whichBar|defaultBarType|segnoType|doubleRepeatType|startRepeatType|endRepeatType|doubleRepeatSegnoType|startRepeatSegnoType|endRepeatSegnoType)(\s*[=]?\s*[#]?)"
-
-
-@rule((2, 17, 5), r"New bar line interface")
-def conv(s):
-    s = re.sub(barstring + r'"\|:"', '\\1\\2".|:"', s)
-    s = re.sub(barstring + r'":\|"', '\\1\\2":|."', s)
-    s = re.sub(barstring + r'"\|\|:"', '\\1\\2".|:-||"', s)
-    s = re.sub(barstring + r'":\|:"', '\\1\\2":..:"', s)
-    s = re.sub(barstring + r'"\.\|\."', '\\1\\2".."', s)
-    s = re.sub(barstring + r'"\|S"', '\\1\\2"S-|"', s)
-    s = re.sub(barstring + r'"S\|"', '\\1\\2"S-S"', s)
-    s = re.sub(barstring + r'":\|S"', '\\1\\2":|.S"', s)
-    s = re.sub(barstring + r'":\|S\."', '\\1\\2":|.S-S"', s)
-    s = re.sub(barstring + r'"S\|:"', '\\1\\2"S.|:-S"', s)
-    s = re.sub(barstring + r'"\.S\|:"', '\\1\\2"S.|:"', s)
-    s = re.sub(barstring + r'":\|S\|:"', '\\1\\2":|.S.|:"', s)
-    s = re.sub(barstring + r'":\|S\.\|:"', '\\1\\2":|.S.|:-S"', s)
-    s = re.sub(barstring + r'":"', '\\1\\2";"', s)
-    s = re.sub(barstring + r'"\|s"', '\\1\\2"|-s"', s)
-    s = re.sub(barstring + r'"dashed"', '\\1\\2"!"', s)
-    s = re.sub(barstring + r'"kievan"', '\\1\\2"k"', s)
-    s = re.sub(barstring + r'"empty"', '\\1\\2"-"', s)
-    return s
-
-
-symbol_list = (r"#'(?:" + wordsyntax + r"|\(\s*" + wordsyntax
-               + r"(?:\s+" + wordsyntax + r")*\s*\))")
-
-grob_path = symbol_list + r"(?:\s+" + symbol_list + r")*"
-
-grob_spec = wordsyntax + r"(?:\s*\.\s*" + wordsyntax + r")?"
-
-def path_replace(m):
-    return m.group(1) + ".".join(re.findall(wordsyntax, m.group(2)))
-
-def convert_overrides_to_dots(s):
-    return re.sub(r"(\\(?:override|revert)\s+)(" + grob_spec + r"\s+" + grob_path + ")",
-                  path_replace, s)
-
-# The following regexp appears to be unusually expensive to compile,
-# so we do it only once instead of for every file
-footnotec = re.compile("(" + matchfullmarkup + ")|"
-                       + r"(\\footnote(?:\s*"
-                       + matchmarkup + ")?" + matcharg + ")(" + matcharg
-                       + r")?(\s+" + matchmarkup + r")(\s+\\default)?")
-
-@rule((2, 17, 6), r"""\accidentalStyle #'Context "style" -> \accidentalStyle Context.style
-\alterBroken "Context.grob" -> \alterBroken Context.grob
-\overrideProperty "Context.grob" -> \overrideProperty Context.grob
-\tweak Grob #'symbol -> \tweak Grob.symbol""")
-def conv(s):
-    def patrep(m):
-        def fn_path_replace(m):
-            x = ".".join(re.findall(wordsyntax, m.group(2)))
-            if x in ["TimeSignature", "KeySignature", "BarLine",
-                     "Clef", "StaffSymbol", "OttavaBracket",
-                     "LedgerLineSpanner"]:
-                x = "Staff." + x
-            return m.group(1) + x
-        if m.group(1):
-            return m.group(0)
-        x = m.group(2) + m.group(4)
-
-        if m.group(3):
-            x = x + re.sub(r"(\s*)(" + symbol_list + ")", fn_path_replace,
-                           m.group(3))
-
-            if not m.group(5):
-                x = r"\single" + x
-        return x
-
-    s = re.sub(r'''(\\accidentalStyle\s+)#?"([-A-Za-z]+)"''',
-                 r"\1\2", s)
-    s = re.sub(r'''(\\accidentalStyle\s+)#'([A-Za-z]+)\s+#?"?([-A-Za-z]+)"?''',
-                 r"\1\2.\3", s)
-    s = re.sub(r'''(\\(?:alterBroken|overrideProperty)\s+)#?"([A-Za-z]+)\s*\.\s*([A-Za-z]+)"''',
-                 r"\1\2.\3", s)
-    s = re.sub(r'''(\\tweak\s+)#?"?([A-W][A-Za-z]*)"?\s+?#'([a-zX-Z][-A-Za-z]*)''',
-                 r"\1\2.\3", s)
-    s = re.sub(r'''(\\tweak\s+)#'([a-zX-Z][-A-Za-z]*)''',
-                 r"\1\2", s)
-    s = footnotec.sub(patrep, s)
-    s = re.sub(r'''(\\alterBroken)(\s+[A-Za-z.]+)(''' + matcharg
-                 + matcharg + ")", r"\1\3\2", s)
-    s = re.sub(r"(\\overrideProperty\s+)(" + grob_spec + r"\s+" + grob_path + ")",
-                 path_replace, s)
-    s = convert_overrides_to_dots(s)
-    return s
-
-
-@rule((2, 17, 11), r"""\times -> \tuplet, \set tupletSpannerDuration -> \tupletSpan
-(ly:make-moment 1 4) -> (ly:make-moment 1/4)
-(ly:make-duration 0 0 1 2) -> (ly:make-duration 0 0 1/2)""")
-def conv(s):
-    def sub_dur(m):
-        num = int(m.group(1))
-        den = int(m.group(2))
-
-# if den is no power of 2, don't even try to use an unscaled duration
-        if (den & (den - 1)) != 0:
-            return r"\tupletSpan 1*%d/%d" % (num, den)
-
-        if den >= 4 and num == 7:
-            return r"\tupletSpan %d.." % (den/4)
-
-        if den >= 2 and num == 3:
-            return r"\tupletSpan %d." % (den/2)
-
-        if num == 1:
-            return r"\tupletSpan %d" % den
-
-        return r"\tupletSpan 1*%d/%d" % (num, den)
-
-    s = re.sub(r"\\set\s+tupletSpannerDuration\s*=\s*" +
-                 r"#\(ly:make-moment\s+([0-9]+)\s+([0-9]+)\s*\)",
-                 sub_dur, s)
-    s = re.sub(r"\\unset tupletSpannerDuration",
-                 r"\\tupletSpan \\default", s)
-    s = re.sub(r"\\times(\s*)([0-9]+)/([0-9]+)",
-                 r"\\tuplet\1\3/\2", s)
-
-    s = re.sub(r"(\(ly:make-moment\s+-?[0-9]+)\s+([1-9][0-9]*\))",
-                 r"\1/\2", s)
-    s = re.sub(r"(\(ly:make-moment\s+-?[0-9]+)\s+([0-9]+\s+-?[0-9]+)\s([0-9]+\))",
-                 r"\1/\2/\3", s)
-    s = re.sub(r"(\(ly:make-duration\s+-?[0-9]+\s+[0-9]+\s+[0-9]+)\s+([0-9]+\))",
-                 r"\1/\2", s)
-    return s
-
-
-@rule((2, 17, 14), r"\accepts ... -> \accepts ... \defaultchild ...")
-def conv(s):
-    def matchaccepts(m):
-        # First weed out definitions starting from an existing
-        # definition: we assume that the inherited \defaultchild is
-        # good enough for our purposes.  Heuristic: starts with a
-        # backslash and an uppercase letter.
-        if re.match(r"\s*\\[A-Z]", m.group(1)):
-            return m.group(0)
-        # existing defaultchild obviously trumps all
-        if re.search(r"\\defaultchild[^-_a-zA-Z]", m.group(1)):
-            return m.group(0)
-        # take the first \\accepts if any and replicate it
-        return re.sub("(\r?\n[ \t]*|[ \t]+)"
-                      + r"""\\accepts(\s+(?:#?".*?"|[-_a-zA-Z]+))""",
-                      r"\g<0>\1\\defaultchild\2",
-                      m.group(0), 1)
-
-    s = re.sub(r"\\context\s*@?\{(" + brace_matcher(20) + r")\}",
-                 matchaccepts, s)
-    return s
-
-
-@rule((2, 17, 15), r"""#(ly:set-option 'old-relative)
-\relative -> \relative c'""")
-def conv(s):
-    if re.search(r"[#$]\(ly:set-option\s+'old-relative", s):
-        stderr_write(NOT_SMART % "#(ly:set-option 'old-relative)")
-        stderr_write(UPDATE_MANUALLY)
-        raise FatalConversionError()
-    # If the file contains a language switch to a language where the
-    # name of c is not "c", we can't reliably know which parts of the
-    # file will need "c" and which need "do".
-    m = re.search(
-        r'\\language\s(?!\s*#?"(?:nederlands|deutsch|english|norsk|suomi|svenska))"', s)
-    if m:
-        # Heuristic: if there is a non-commented { before the language
-        # selection, we can't be sure.
-        # Also if there is any selection of a non-do language.
-        if (re.search("^[^%\n]*\\{", m.string[:m.start()], re.M)
-                or re.search(r'\\language\s(?!\s*#?"(?:catalan|espanol|español|italiano|français|portugues|vlaams))"', s)):
-            do = "$(ly:make-pitch 0 0)"
-        else:
-            do = "do'"
-    else:
-        do = "c'"
-    s = re.sub(r"(\\relative)(\s+(\{|[\\<]))",
-                 r"\1 " + do + r"\2", s)
-    return s
-
-
-@rule((2, 17, 18),
-      "Rename OctavateEight to ClefModifier, rename related properties.")
-def conv(s):
-    s = re.sub('OctavateEight',
-                 'ClefModifier',                   s)
-    s = re.sub('octavate-eight-interface',
-                 'clef-modifier-interface',        s)
-    s = re.sub('clefOctavation',
-                 'clefTransposition',              s)
-    s = re.sub('clefOctavationFormatter',
-                 'clefTranspositionFormatter',     s)
-    s = re.sub('clefOctavationStyle',
-                 'clefTranspositionStyle',         s)
-    s = re.sub('cueClefOctavation',
-                 'cueClefTransposition',           s)
-    s = re.sub('cueClefOctavationFormatter',
-                 'cueClefTranspositionFormatter',  s)
-    s = re.sub('cueClefOctavationStyle',
-                 'cueClefTranspositionStyle',      s)
-    return s
-
-
-@rule((2, 17, 19), r"\column { \vspace #2 } -> \column { \combine \null \vspace #2 }")
-def conv(s):
-    def vspace_replace(m):
-
-        # vspace now always adds space and does not, for example, change the
-        # impact of either baselineskip or descenders on the line above.
-        #
-        # We can't simulate the old behavior in a simpler manner.  A command
-        # of its own is not really warranted since this behavior combines
-        # badly enough with other spacing considerations (like baselineskip
-        # and descenders) as to make it not all that useful.  So this
-        # conversion rule is here more for compatibility's sake rather than
-        # preserving desirable behavior.
-
-        s = re.sub(r"(\\\\?)vspace(\s)",
-                     r"\1combine \1null \1vspace\2", m.group(0))
-        return s
-
-    s = re.sub(r"\\(?:left-|right-|center-|)column\s*\{" + brace_matcher(20) + r"\}",
-                 vspace_replace, s)
-    return s
-
-
-@rule((2, 17, 20), _(r"Flag.transparent and Flag.color inherit from Stem"))
-def conv(s):
-    s = re.sub(r"(((?:\\once\s*)?)\\override\s+((?:\w+\.)?)Stem\.(transparent|color)\s*=\s*(#\S+))\s+\2\\override\s+\3Flag\.\4\s*=\s*\5",
-                 r"\1", s)
-    s = re.sub(r"(((?:\\once\s*)?)\\revert\s+((?:\w+\.)?)Stem\.(transparent|color))\s+\2\\revert\s+\3Flag\.\4",
-                 r"\1", s)
-    s = re.sub(r"(\\tweak\s+((?:\w+\.)?)Stem\.(transparent|color)\s+(#\S+))\s+\\tweak\s+\2Flag\.\3\s+\4",
-                 r"\1", s)
-    return s
-
-
-@rule((2, 17, 25), r'''\tempo 4. = 50~60 -> \tempo 4. = 50-60
--| -> -!
-pipeSymbol, escapedParenthesisOpenSymbol ... -> "|", "\\(" ...''')
-def conv(s):
-    #  This goes for \tempo commands ending with a range, like
-    #  = 50 ~ 60
-    #  and uses - instead.  We don't explicitly look for \tempo since the
-    #  complete syntax has a large number of variants, and this is quite
-    #  unlikely to occur in other contexts
-    s = re.sub(r"(=\s*[0-9]+\s*)~(\s*[0-9]+\s)", r"\1-\2", s)
-# Match strings, and articulation shorthands that end in -^_
-# so that we leave alone -| in quoted strings and c4--|
-
-    def subnonstring(m):
-        if m.group(1):
-            return m.group(1)+"!"
-        return m.group(0)
-    s = re.sub(r"([-^_])\||" + matchstring +
-                 r"|[-^_][-^_]", subnonstring, s)
-    s = re.sub(r"\bdashBar\b", "dashBang", s)
-    orig = ["pipeSymbol",
-            "bracketOpenSymbol",
-            "bracketCloseSymbol",
-            "tildeSymbol",
-            "parenthesisOpenSymbol",
-            "parenthesisCloseSymbol",
-            "escapedExclamationSymbol",
-            "escapedParenthesisOpenSymbol",
-            "escapedParenthesisCloseSymbol",
-            "escapedBiggerSymbol",
-            "escapedSmallerSymbol"]
-    repl = [r'"|"',
-            r'"["',
-            r'"]"',
-            r'"~"',
-            r'"("',
-            r'")"',
-            r'"\\!"',
-            r'"\\("',
-            r'"\\)"',
-            r'"\\>"',
-            r'"\\<"']
-    words = r"\b(?:(" + ")|(".join(orig) + r"))\b"
-
-    def wordreplace(m):
-        def instring(m):
-            return re.sub(r'["\\]', r'\\\g<0>', repl[m.lastindex-1])
-        if m.lastindex:
-            return repl[m.lastindex-1]
-        return '"' + re.sub(words, instring, m.group(0)[1:-1]) + '"'
-    s = re.sub(words + "|" + matchstring, wordreplace, s)
-    return s
-
-
-@rule((2, 17, 27), r'''\stringTuning \notemode -> \stringTuning''')
-def conv(s):
-    s = re.sub(r"\\stringTuning\s*\\notemode(\s*)@?\{\s*(.*?)\s*@?\}",
-                 r"\\stringTuning\1\2", s)
-    if re.search(r'[^-\w]staff-padding[^-\w]', s):
-        stderr_write(NOT_SMART % "staff-padding")
-        stderr_write(
-            _("Staff-padding now controls the distance to the baseline, not the nearest point."))
-    return s
-
-
-@rule((2, 17, 29), r'''Dynamic_engraver -> New_dynamic_engraver+Dynamic_align_engraver
-New_dynamic_engraver -> Dynamic_engraver''')
-def conv(s):
-    s = re.sub("(\r?\n?[ \t]*\\\\(?:consists|remove)\\s*)(\"?)Dynamic_engraver\\2",
-                 r"\1\2New_dynamic_engraver\2\1\2Dynamic_align_engraver\2",
-                 s)
-# Should we warn about any remaining Dynamic_engraver?  Possibly it
-# will do the job just fine.
-    s = re.sub("New_dynamic_engraver", "Dynamic_engraver", s)
-    return s
-
-
-@rule((2, 17, 97), r'''(make-relative (a b) b ...) -> make-relative (a b) #{ a b #}...''')
-def conv(s):
-    s = re.sub(r"(\(make-relative\s+\(\s*(([A-Za-z][-_A-Za-z0-9]*)" +
-                 r"(?:\s+[A-Za-z][-_A-Za-z0-9]*)*)\s*\)\s*)\3(?=\s)",
-                 r"\1(make-event-chord (list \2))", s)
-    s = re.sub(r"(\(make-relative\s+\(\s*([A-Za-z][-_A-Za-z0-9]*" +
-                 r"(?:\s+([A-Za-z][-_A-Za-z0-9]*))+)\s*\)\s*)\3(?=\s)",
-                 r"\1(make-sequential-music (list \2))", s)
-    return s
-
-
-@rule((2, 18, 0),
-      _("bump version for release"))
-def conv(s):
-    return s
-
-
-@rule((2, 19, 2), r"\lyricsto \new/\context/... -> \new/\context/... \lyricsto")
-def conv(s):
-    word = r'(?:#?"[^"]*"|\b' + wordsyntax + r'\b)'
-    s = re.sub(r"(\\lyricsto\s*" + word + r"\s*)(\\(?:new|context)\s*" + word
-                 + r"(?:\s*=\s*" + word + r")?\s*)",
-                 r"\2\1", s)
-    s = re.sub(r"(\\lyricsto\s*" + word + r"\s*)\\lyricmode\b\s*",
-                 r"\1", s)
-    s = re.sub(r"(\\lyricsto\s*" + word + r"\s*)\\lyrics\b\s*",
-                 r"\\new Lyrics \1", s)
-    s = re.sub(r'\\lyricmode\s*(\\lyricsto\b)', r"\1", s)
-    return s
-
-
-@rule((2, 19, 7), "keySignature -> keyAlterations")
-def conv(s):
-    s = re.sub(r'\bkeySignature\b', 'keyAlterations', s)
-    s = re.sub(r'\blastKeySignature\b', 'lastKeyAlterations', s)
-    s = re.sub(r'\blocalKeySignature\b', 'localAlterations', s)
-    return s
-
-
-@rule((2, 19, 11), "thin-kern -> segno-kern")
-def conv(s):
-    s = re.sub(r'\bthin-kern\b', 'segno-kern', s)
-    return s
-
-# before_id is written in a manner where it will only substantially
-# (rather than as a lookbefore assertion) match material that could
-# not be part of a previous id.  In that manner, one replacement does
-# not inhibit an immediately adjacent replacement.
-
-
-before_id = r'(?:^|(?<!\\)(?:\\\\)+|(?<=[^-_\\a-zA-Z])|(?<=[^a-zA-Z][-_]))'
-
-# after_id is a pure lookbehind assertion so its match string is
-# always empty
-
-after_id = r'(?![a-zA-Z]|[-_][a-zA-Z])'
-
-
-@rule((2, 19, 16), r"""implicitTimeSignatureVisibility -> initialTimeSignatureVisibility
-csharp -> c-sharp
-TimeSignature: style = #'() -> style = #'numbered""")
-def conv(s):
-    s = re.sub(r'\bimplicitTimeSignatureVisibility\b',
-                 'initialTimeSignatureVisibility', s)
-    s = re.sub('(' + before_id + r'[a-g])((?:sharp){1,2}|(?:flat){1,2})'
-                 + after_id, r'\1-\2', s)
-    s = re.sub(r"""\\override
-                   (\s+)
-                   ([a-zA-Z]+\.)?TimeSignature.style
-                   (\s*)
-                   =
-                   (\s*)
-                   \#'\(\)""",
-               r"\\override\1\2TimeSignature.style\3=\4#'numbered",
-               s,
-               flags=re.VERBOSE)
-
-    s = re.sub(r"""\\tweak
-                   (\s+)
-                   (TimeSignature\.)?style
-                   (\s*)
-                   \#'\(\)
-                   (\s+)
-                   \\time
-                   """,
-               r"\\tweak\1\2style\3#'numbered\4\\time",
-               s,
-               flags=re.VERBOSE)
-    return s
-
-
-@rule((2, 19, 22), """whiteout -> whiteout-box
-(define-xxx-function (parser location ...) -> (define-xxx-function (...)
-(xxx ... parser ...) -> (xxx ... ...)
-ChordNameVoice -> ChordNames""")
-def conv(s):
-    # whiteout -> whiteout-box
-    s = re.sub(r"\\whiteout(?![a-z_-])", r"\\whiteout-box", s)
-    s = re.sub(r"\b\.whiteout(?![a-z_-])\b", r".whiteout-box", s)
-    s = re.sub(r"#'whiteout(?![a-z_-])\b", r"#'whiteout-box", s)
-    s = re.sub(r"\bstencil-whiteout\b", r"stencil-whiteout-box", s)
-
-    # (define-xxx-function (parser location ...) -> (define-xxx-function (...)
-    def topsubst(s):
-        def subst(m):
-            def subsub(m):
-                s = (m.group(1)
-                     + re.sub(r'(?<=\s|["\\()])' + m.group(2) + r'(?=\s|["\\()])',
-                              r'(*location*)',
-                              re.sub(r'(?<=\s|["\\()])parser(?=\s|["\\()])',
-                                     r'(*parser*)', topsubst(m.group(3)))))
-                return s
-            return re.sub(r'(\([-a-z]+\s*\(+)parser\s+([-a-z]+)\s*((?:.|\n)*)$',
-                      subsub, m.group(0))
-        return re.sub(r'\(define-(?:music|event|scheme|void)-function(?=\s|["(])'
-                      + paren_matcher(20) + r'\)', subst, s)
-    s = topsubst(s)
-
-    # (xxx ... parser ...) -> (xxx ... ...)
-    def repl(m):
-        return m.group(1) + inner(m.group(2))
-
-    def inner(s):
-        s = re.sub(r"(\((?:" +
-                     r"ly:parser-lexer|" +
-                     r"ly:parser-clone|" +
-                     r"ly:parser-output-name|" +
-                     r"ly:parser-error|" +
-                     r"ly:parser-define!|" +
-                     r"ly:parser-lookup|" +
-                     r"ly:parser-has-error\?|" +
-                     r"ly:parser-clear-error|" +
-                     r"ly:parser-set-note-names|" +
-                     r"ly:parser-include-string|" +
-                     r"note-names-language|" +
-                     r"display-lily-music|" +
-                     r"music->lily-string|" +
-                     r"note-name->lily-string|" +
-                     r"value->lily-string|"
-                     r"check-grob-path|" +
-                     r"event-chord-wrap!|" +
-                     r"collect-bookpart-for-book|" +
-                     r"collect-scores-for-book|" +
-                     r"collect-music-aux|" +
-                     r"collect-book-music-for-book|" +
-                     r"scorify-music|" +
-                     r"collect-music-for-book|" +
-                     r"collect-book-music-for-book|" +
-                     r"toplevel-book-handler|" +
-                     r"default-toplevel-book-handler|" +
-                     r"print-book-with-defaults|" +
-                     r"toplevel-music-handler|" +
-                     r"toplevel-score-handler|" +
-                     r"toplevel-text-handler|" +
-                     r"toplevel-bookpart-handler|" +
-                     r"book-music-handler|" +
-                     r"context-mod-music-handler|" +
-                     r"bookpart-music-handler|" +
-                     r"output-def-music-handler|" +
-                     r"print-book-with-defaults-as-systems|" +
-                     r"add-score|" +
-                     r"add-text|" +
-                     r"add-music|" +
-                     r"make-part-combine-music|" +
-                     r"make-directed-part-combine-music|" +
-                     r"add-quotable|" +
-                     r"paper-variable|" +
-                     r"make-autochange-music|" +
-                     r"context-mod-from-music|" +
-                     r"context-defs-from-music)" +
-                     r'(?=\s|[()]))(' + paren_matcher(20) + ")"
-                     r"(?:\s+parser(?=\s|[()])|\s*\(\*parser\*\))", repl, s)
-        return s
-    s = inner(s)
-    # This is the simplest case, resulting from one music function
-    # trying to call another one via Scheme.  The caller is supposed
-    # to have its uses of parser/location converted to
-    # (*parser*)/(*location*) already.  Other uses of
-    # ly:music-function-extract are harder to convert but unlikely.
-    s = re.sub(r'(\(\s*\(ly:music-function-extract\s+' + wordsyntax +
-                 r'\s*\)\s+)\(\*parser\*\)\s*\(\*location\*\)', r'\1',
-                 s)
-
-    s = re.sub(r'ChordNameVoice', r'ChordNames', s)
-    return s
-
-
-@rule((2, 19, 24), r"""music-has-type -> music-is-of-type?
-\applyOutput #'Context -> \applyOutput Context""")
-def conv(s):
-    s = re.sub(r'(?<=\s|["\\()])' + "music-has-type" + r'(?=\s|["\\()])',
-                 "music-is-of-type?", s)
-    s = re.sub(r"(\\applyOutput\s+)#'([a-zA-Z])", r"\1\2", s)
-    return s
-
-
-@rule((2, 19, 28), r"c:5.x, c:5^x, c:sus -> c:3.5.x, c:3.5^x, c:5")
-def conv(s):
-    s = re.sub(r":5([.^][1-9])", r":3.5\1", s)
-    # row back for self-defeating forms
-    s = re.sub(r":3\.5((?:\.[0-9]+)*\^(?:[0-9]+\.)*)3\.", r":5\1", s)
-    s = re.sub(
-        r":3\.5((?:\.[0-9]+)*\^?:[0-9]+(?:\.[0-9]+)*)\.3(?![.0-9])", r":5\1", s)
-    s = re.sub(r":3\.5((?:\.[0-9]+)*)\^3(?=\s|\})", r":5\1", s)
-    s = re.sub(r":sus(?=\s|\})", ":5", s)
-    s = re.sub(r":1\.5(?=\s|[.^}])", r":5", s)
-    return s
-
-
-@rule((2, 19, 29), r"partcombine*Once -> \once \partcombine*")
-def conv(s):
-    s = re.sub(r"(\\partcombine(?:Apart|Chords|Unisono|SoloII?|Automatic))Once\b",
-                 r"\\once \1", s)
-    s = re.sub(r"(\\partcombineForce" + matcharg + r")\s*##f(\s)",
-                 r"\1\2", s)
-    s = re.sub(r"(\\partcombineForce" + matcharg + r")\s*##t(\s)",
-                 r"\\once \1\2", s)
-    return s
-
-
-@rule((2, 19, 32), r"whiteout-box -> whiteout")
-def conv(s):
-    s = re.sub(r"\\whiteout-box(?![a-z_-])", r"\\whiteout", s)
-    s = re.sub(r"\b\.whiteout-box(?![a-z_-])\b", r".whiteout", s)
-    s = re.sub(r"#'whiteout-box(?![a-z_-])\b", r"#'whiteout", s)
-    return s
-
-
-@rule((2, 19, 39), r"...-spacing #'prop... = -> ...-spacing.prop... =")
-def conv(s):
-    s = re.sub(r"(\s)((?:markup-markup-spacing|markup-system-spacing"
-                 r"|score-markup-spacing|last-bottom-spacing"
-                 r"|score-system-spacing|system-system-spacing"
-                 r"|top-markup-spacing|top-system-spacing)"
-                 r"(?:\s+#\s*'\s*" + wordsyntax + r")+)(?=\s*=)", path_replace, s)
-    return s
-
-
-@rule((2, 19, 40), r"\time #'(2 3) ... -> \time 2,3 ...")
-def conv(s):
-    def repl(m):
-        return m.group(1) + re.sub(r"\s+", ",", m.group(2))
-
-    s = re.sub(r"(beatStructure\s*=\s*)#'\(([0-9]+(?:\s+[0-9]+)+)\)",
-                 repl, s)
-
-    s = re.sub(r"(\\time\s*)#'\(([0-9]+(?:\s+[0-9]+)+)\)", repl, s)
-
-    def repl(m):
-        subst = re.sub(r"\s+", ",", m.group(1))
-        return subst + (4 + len(m.group(1)) - len(subst)) * " " + m.group(2)
-
-    s = re.sub(r"#'\(([0-9]+(?:\s+[0-9]+)+)\)(\s+%\s*beatStructure)",
-                 repl, s)
-    return s
-
-
-@rule((2, 19, 46), r"\context ... \modification -> \context ... \with \modification")
-def conv(s):
-    word = r'(?:#?"[^"]*"|\b' + wordsyntax + r'\b)'
-    mods = "|".join(re.findall("\n(" + wordsyntax + r")\s*=\s*\\with(?:\s|\\|\{)", s)
-                    + ['RemoveEmptyStaves', 'RemoveAllEmptyStaves'])
-    s = re.sub(r"(\\(?:drums|figures|chords|lyrics|addlyrics|"
-                 + r"(?:new|context)\s*" + word
-                 + r"(?:\s*=\s*" + word + r")?)\s*)(\\(?:" + mods + "))",
-                 r"\1\\with \2", s)
-    return s
-
-
-@rule((2, 19, 49), r"""id -> output-attributes.id or output-attributes
-for \tweak, \override, \overrideProperty, and \revert""")
-def conv(s):
-    # path cannot start with '-' or '_' and matches zero or more path
-    # units that each end in a dot
-    path = r"(?:[a-zA-Z\200-\377](?:[-_]?[a-zA-Z\200-\377])*(?:\s*\.\s*))*"
-
-    # Manual editing is needed when id is set to #(...) or \xxx
-    manual_edits = r"(\\(?:tweak|override|overrideProperty)\s+" + \
-        path + r")id(\s*=?\s*(?:\\|#\s*\())"
-    automatic = r"(\\(?:tweak|override|overrideProperty|revert)\s+" + path + r")id"
-    if re.search(manual_edits, s):
-        stderr_write(NOT_SMART % "\"output-attributes\"")
-        stderr_write(
-            _("Previously the \"id\" grob property (string) was used for SVG output.") + "\n")
-        stderr_write(
-            _("Now \"output-attributes\" (association list) is used instead.") + "\n")
-        stderr_write(UPDATE_MANUALLY)
-
-    # First, for manual editing cases we convert 'id' to 'output-attributes'
-    # because Grob.output-attributes.id = #(lambda ... ) will not work.
-    # Then for the rest we convert 'id' to 'output-attributes.id'
-    s = re.sub(manual_edits, r"\1output-attributes\2", s)
-    s = re.sub(automatic, r"\1output-attributes.id", s)
-    return s
-
-
-@rule((2, 20, 0), r'''\language "deutsch": beh -> heh''')
-def conv(s):
-    changes = re.findall(r'\\language\s*#?"([a-zçñ]+)"', s)
-    if changes and (changes.count('deutsch') == len(changes)):
-        s = re.sub(r'\bbeh\b', 'heh', s)
-    return s
-
-
-matchscmarg = (r'(?:[a-zA-Z_][-a-zA-Z_0-9]*|"(?:[^\\"]|\\.)*"|[-+]?[0-9.]+|\('
-               + paren_matcher(10) + r"\))")
-
-string_duration_re = (r'(?P<startquote>#?")'
-                      r'(?P<dur>1|2|4|8|16|32|64|128|256|breve|longa|maxima)'
-                      r'(?P<ws>\s*)'
-                      r'(?P<dots>[.]*)'
-                      r'(?P<endquote>")')
-
-def to_ly_duration(match):
-    # Take a match against string_duration_re, possibly embedded in a
-    # larger regex.  Return the corresponding duration in LilyPond
-    # syntax with braces, like "{4.}" or "{\longa}".
-    if match.group("dur") in (r"breve", r"longa", r"maxima"):
-        new_dur = '\\' + match.group("dur")
-    else:
-        new_dur = match.group("dur")
-    return (match.group()[:match.start("startquote")-match.start()]
-            + '{' + new_dur
-            + match.group("dots") + '}'
-            + match.group()[match.end("endquote")-match.start():])
-
-def to_scm_duration(match):
-    # Same as string_to_ly_duration, with result in Scheme syntax.
-    # "4." => (ly:make-duration 2 1)
-    # "longa" => (ly:make-duration -2 0)
-    dur_log = {"1": 0, "2": 1, "4": 2, "8": 3, "16": 4,
-               "32": 5, "64": 6, "128": 7, "256": 8,
-               "breve": -1, "longa": -2, "maxima": -4}[match.group("dur")]
-    dot_count = len(match.group("dots"))
-    new = f"(ly:make-duration {dur_log} {dot_count})"
-    return (match.group()[:match.start("startquote")-match.start()]
-            + new
-            + match.group()[match.end("endquote")-match.start():])
-
-# \note #"4." => \note {4.}  in 2.21.0
-# \rest #"4." => \rest {4.} in 2.23.1
-def convert_string_to_duration_for_command(markup_command, s):
-    s = re.sub(rf'\\{markup_command}\s*{string_duration_re}', to_ly_duration, s)
-    s = re.sub(rf'#:{markup_command}\s+{string_duration_re}', to_scm_duration, s)
-    return s
-
-@rule((2, 21, 0), r"""\note #"4." -> \note {4.}
-\markup-command #" -> \markup-command "
-\partcombine* -> \partCombine, \autochange -> \autoChange
-scripts.trilelement -> scripts.trillelement
-\fermataMarkup -> \fermata
-remove \\powerChords, deprecate banter-chord-names and jazz-chord-names
-\compressFullBarRests  -> \compressEmptyMeasures
-""")
-def conv(s):
-    s = convert_string_to_duration_for_command("note", s)
-    s = re.sub(r"\(tuplet-number::(?:fraction-with-notes|non-default-fraction-with-notes|append-note-wrapper)\s" +
-                 paren_matcher(20) + r"\)",
-               lambda match: re.sub(string_duration_re, to_scm_duration, match.group()),
-               s)
-    s = re.sub(r'(\\(?:fret-diagram(?:-terse)?|harp-pedal|justify-string'
-                 r'|lookup|musicglyph|postscript|simple|tied-lyric|verbatim-file'
-                 r'|with-url|wordwrap-string'
-                 r'|discant|freeBass|stdBass|stdBassIV|stdBassV|stdBassVI'
-                 r')\s*)[#$](\\?")',
-                 r'\1\2', s)
-    s = re.sub(r"\\partcombine(Force|Up|Down|Chords|Apart|Unisono|SoloI|SoloII|Automatic|)\b",
-                 r"\\partCombine\1", s)
-    s = re.sub(r"\\autochange", r"\\autoChange", s)
-    s = re.sub(r'\\powerChords', '', s)
-    s = re.sub(r'"scripts\.trilelement"', r'"scripts.trillelement"', s)
-    s = re.sub(r"\\fermataMarkup", r"\\fermata", s)
-    s = re.sub(r"\\(compress|expand)FullBarRests", r"\\\1EmptyMeasures", s)
-    if re.search(r"#(banter|jazz)-chordnames", s):
-        stderr_write(NOT_SMART % "alternative chord naming functions")
-        stderr_write(UPDATE_MANUALLY)
-    return s
-
-
-@rule((2, 21, 2), r'''\tocItem "string" -> \tocItem \markup "string"''')
-def conv(s):
-    s = re.sub(r'\\tocItem\s+"', r'\\tocItem \\markup "', s)
-    return s
-
-
-@rule((2, 22, 0), _("bump version for release"))
-def conv(s):
-    return s
-
-
-@rule((2, 23, 1), r"""
-combine u/d variants of triangle, do, re, and ti noteheads
-rename bar line "S" to "S-||"
-rename bar line "S-|" to "S"
-\rest "4." -> \rest {4.}
-""")
-def conv(s):
-    s = re.sub(r'"noteheads\.[ud](1|2)(triangle|(?:do|re|ti)(?:Thin)?)"',
-               r'"noteheads.s\1\2"', s)
-    s = re.sub(r'\\bar(\s+)"S"', r'\\bar\1"S-||"', s)
-    s = re.sub(r'\\bar(\s+)"S-\|"', r'\\bar\1"S"', s)
-    s = re.sub(r'segnoType(\s+=\s+)#?"S"', r'segnoType\1"S-||"', s)
-    s = re.sub(r'segnoType(\s+=\s+)#?"S-\|"', r'segnoType\1"S"', s)
-    s = convert_string_to_duration_for_command("rest", s)
-    # Be more general than \override #'(multi-measure-rest . #t),
-    # there's also \override #'((something . else) (multi-measure-rest . #t))
-    if "#'(multi-measure-rest . #t)" in s and r"\rest-by-number" in s:
-        # Don't convert blindly since it may also be use of \rest-by-number
-        # for a normal rest and \rest with \override #'(multi-measure-rest . #t)
-        # somewhere else.
-        stderr_write(NOT_SMART % r"\override #'(multi-measure-rest . #t) \rest-by-number")
-        stderr_write(r"""
-Instead of (for example)
-  \markup \override #'(multi-measure-rest . #t) \rest-by-number #0 #0
-use
-  \markup \multi-measure-rest-by-number #1
-
-The argument of \multi-measure-rest-by-number is the number of measures
-the multi-measure rest lasts.
-""")
-        stderr_write(UPDATE_MANUALLY)
-    return s
-
-
-melody_engraver_warning = r"""
-If you had
-
-  \override Stem.neutral-direction = #DOWN
-
-and
-
-  \override Stem.neutral-direction #'()
-
-to turn the use of the Melody_engraver off
-and on, respectively, you should instead use
-
-  \set suspendMelodyDecisions = ##t
-
-and
-
-  \set suspendMelodyDecisions = ##f
-
-"""
-
-@rule((2, 23, 2), r"""
-warn about behavior change of Melody_engraver with Stem.neutral-direction
-adapt module names to (lily) namespace
-""")
-def conv(s):
-    # Detect changes to the Stem.neutral-direction property
-    # in conjunction with the Melody_engraver. The string
-    # "Stem.neutral-direction" is sufficient for the former,
-    # since there is no situation where \tweak neutral-direction ...
-    # would cause the property to end up on the Stem.
-    #
-    # Convert
-    #   \consists Melody_engraver
-    #   \override Stem.neutral-direction = #'()
-    # to just
-    #   \consists Melody_engraver
-    #
-    # Warn about other uses, it's too tricky to convert them
-    # (e.g., \tweak Stem.color \tweak Stem.neutral-direction #DOWN ...
-    # should become \once \set suspendMelodyDecisions = ##t \tweak Stem.color ...).
-    neutral_dir = r'Stem\.neutral-direction'
-    neutral_dir_override = r"\\override\s+{}\s+=\s+#'\(\)".format(neutral_dir)
-    melody_engraver = r'\\consists\s+"?Melody_engraver"?'
-    typical_usage = r'({})\s+{}'.format(melody_engraver, neutral_dir_override)
-    s = re.sub(typical_usage, r"\1", s)
-    if re.search(neutral_dir, s) and re.search('Melody_engraver', s):
-        stderr_write(NOT_SMART % "Stem.neutral-direction with Melody_engraver")
-        stderr_write(melody_engraver_warning)
-        stderr_write(UPDATE_MANUALLY)
-
-    s = re.sub(r'\(scm (accreg|display-lily|graphviz|guile-debugger|song|to-xml)\)',
-               r'(lily \1)', s)
-    return s
-
-round_filled_polygon_warning = r"""
-ly:round-filled-polygon was renamed to ly:round-polygon and now takes
-an additional optional parameter specifying whether the polygon is filled.
-The default value of the extroversion optional parameter was changed from
--1 to 0.
-"""
-
-@rule((2, 23, 3), r"""
-glyph-name-alist -> alteration-glyph-name-alist
-ly:round-filled-polygon -> ly:round-polygon
-""")
-def conv(s):
-    # The negative lookbehind assertion is to avoid matching
-    # standard-alteration-glyph-name-alist and similar.
-    s = re.sub(r"(?<!-)glyph-name-alist", "alteration-glyph-name-alist", s)
-    if "ly:round-filled-polygon" in s:
-        stderr_write(NOT_SMART % "ly:round-filled-polygon")
-        stderr_write(round_filled_polygon_warning)
-        stderr_write(UPDATE_MANUALLY)
-    return s
-
-trill_pitch_group_re = r"""TrillPitchGroup\.
-(
-  font # recognize all font-something properties
-  | color
-  | extra-offset
-  | layer
-  | output-attributes
-  | rotation
-  | stencil
-  | stencils
-  | transparent
-  | whiteout # also whiteout-style
-)
-"""
-
-repl = r"TrillPitchParentheses.\1"
-
-on_the_fly_replacements = (
-    (r"[\\#$]print-page-number-check-first", r"\\if \\should-print-page-number"),
-    (r"[\\#$]create-page-number-stencil", r"\\if \\should-print-page-numbers-global"),
-    (r"[\\#$]print-all-headers", r"\\if \\should-print-all-headers"),
-    (r"[\\#$]first-page", r"\\if \\on-first-page"),
-    (r"[\\#$]not-first-page", r"\\unless \\on-first-page"),
-    (r"[#$]\(on-page (\d+)\)", r"\\if \\on-page #\1"),
-    (r"[\\#$]last-page", r"\\if \\on-last-page"),
-    (r"[\\#$]part-first-page", r"\\if \\on-first-page-of-part"),
-    (r"[\\#$]not-part-first-page", r"\\unless \\on-first-page-of-part"),
-    (r"[\\#$]part-last-page", r"\\if \\on-last-page-of-part"),
-    (r"[\\#$]not-single-page", r"\\unless \\single-page"),
-)
-
-@rule((2, 23, 4), r"""
-ly:context-now -> ly:context-current-moment
-ControlPointItem, ControlPointSpanner -> ControlPoint
-ControlPolygonItem, ControlPolygonSpanner -> ControlPolygon
-FootnoteItem, FootnoteSpanner -> Footnote
-BalloonTextItem, BalloonTextSpanner -> BalloonText
-\on-the-fly #some-procedure -> \if \some-condition
-""")
-def conv(s):
-    s = re.sub("ly:context-now", "ly:context-current-moment", s)
-    # It's unlikely that users would have wanted different settings
-    # for the item type and the spanner type, so this should be reasonable.
-    item_spanner = (r"(ControlPoint|ControlPolygon|Footnote|BalloonText)"
-                    r"(Item|Spanner)")
-    s = re.sub(item_spanner, r"\1", s)
-    s = re.sub("ParenthesesItem", "Parentheses", s)
-    s = re.sub("parentheses-item::", "parentheses-interface::", s)
-    s = re.sub(trill_pitch_group_re, repl, s, flags=re.VERBOSE)
-    for pattern, replacement in on_the_fly_replacements:
-        complete_pattern = r"\\on-the-fly\s+" + pattern
-        s = re.sub(complete_pattern, replacement, s)
-    return s
-
-@rule((2, 23, 5), r"""
-Mark_tracking_translator
-""")
-def conv(s):
-    if re.search(r'\\consists\s+"?Mark_engraver"?', s):
-        stderr_write(NOT_SMART % "\\consists Mark_engraver")
-        stderr_write(_("If independent mark sequences are desired, use multiple Mark_tracking_translators."))
-        stderr_write('\n')
-        stderr_write(UPDATE_MANUALLY)
-    return s
-
-dash_abbreviations = ["Hat", "Plus", "Dash", "Bang", "Larger", "Dot", "Underscore"]
-
-
-markup2string_warning = """
-The signature of the markup->string Scheme function changed.  Calls with
-just one argument are not affected.  Calls using the second optional
-argument, the list of header modules, should be changed from
-
-  (markup->string <markup> <header list>)
-
-to
-
-  (markup->string <markup> #:props (headers-property-alist-chain <header list>))
-
-"""
-
-@rule((2, 23, 6), r"""
-defaultBarType -> measureBarType
-markFormatter -> rehearsalMarkFormatter
-startRepeatType -> startRepeatBarType (etc.)
-make-articulation "X" -> make-articulation 'X
-'articulation-type "X" -> 'articulation-type 'X
-dashX = "Y" -> dashX = #(make-articulation 'Y)
-markup->string 2nd argument change
-ly:grob-spanned-rank-interval -> ly:grob-spanned-column-rank-interval
-""")
-# It would be nicer to do
-# dashX = "Y" -> dashX = \Y
-# but it is not guaranteed that for any 'symbol valid as 'articulation-type
-# (see the list in scm/script.scm), there is a corresponding after-event \symbol
-# defined via #(make-articulation 'symbol ...) in ly/script-init.ly or
-# ly/gregorian.ly. (Example: There is no \comma as of 2.23.5)
-def conv(s):
-    s = re.sub("defaultBarType", "measureBarType", s)
-    s = re.sub("doubleRepeatSegnoType", "doubleRepeatSegnoBarType", s)
-    s = re.sub("doubleRepeatType", "doubleRepeatBarType", s)
-    s = re.sub("endRepeatSegnoType", "endRepeatSegnoBarType", s)
-    s = re.sub("endRepeatType", "endRepeatBarType", s)
-    s = re.sub("fineSegnoType", "fineSegnoBarType", s)
-    s = re.sub("fineStartRepeatSegnoType", "fineStartRepeatSegnoBarType", s)
-    s = re.sub("markFormatter", "rehearsalMarkFormatter", s)
-    s = re.sub("segnoType", "segnoBarType", s)
-    s = re.sub("startRepeatSegnoType", "startRepeatSegnoBarType", s)
-    s = re.sub("startRepeatType", "startRepeatBarType", s)
-    s = re.sub("underlyingRepeatType", "underlyingRepeatBarType", s)
-    s = re.sub(r'''((make-articulation|'articulation-type)\s+)"(\w+)"''', r"\1'\3", s)
-    s = re.sub(r'(dash(%s)\s+)=(\s+)"(\w+)"' % "|".join(dash_abbreviations),
-               r"\1=\3#(make-articulation '\4)", s)
-    # The case (markup->string <symbol>) is easy to detect and should
-    # not be warned about.  Cases with one argument that is more complex
-    # than a symbol are harder to detect reliably, so we conservatively
-    # print the warning.
-    if re.search(r"(?!(?<=\()markup\->string\s+\w+\))markup->string", s):
-        stderr_write(NOT_SMART % "markup->string")
-        stderr_write(markup2string_warning)
-        stderr_write(UPDATE_MANUALLY)
-    s = s.replace("ly:grob-spanned-rank-interval", "ly:grob-spanned-column-rank-interval")
-    return s
-
-bar_numbers_warning = _(r"""
-Warning:
-
-Your score contains a setting of barNumberVisibility to
-#all-bar-numbers-visible and a setting of BarNumber.break-visibility,
-but not \bar "" command.  This likely means that you have
-been using
-
-  \set Score.barNumberVisibility = #all-bar-numbers-visible
-  \override Score.BarNumber.break-visibility = #end-of-line-invisible
-
-in order to print bar numbers in the middle of systems
-in addition to bar numbers at the beginning of systems.
-In 2.23.7 and later, this will print the first bar number
-too, which has always been the intended effect of
-#all-bar-numbers-visible, but did not work without \bar ""
-for technical reasons.  If you do not want the first
-bar number, remove the command
-
-  \set Score.barNumberVisibility = #all-bar-numbers-visible
-""")
-
-@rule((2, 23, 7), r"""
-all-bar-numbers-visible + BarNumber.break-visibility + no \bar "" -> warning
-""")
-def conv(s):
-    if (
-        "all-bar-numbers-visible" in s
-        and "BarNumber.break-visibility" in s
-        and r'\bar ""' not in s
-    ):
-        stderr_write(bar_numbers_warning)
-    return s
-
-@rule((2, 23, 8), r"""
-scripts.augmentum -> dots.dotvaticana
-scripts.trillelement -> scripts.trill_element
-ly:skyline::get-touching-point -> ly:skyline-touching-point
-ly:skyline::get-distance -> ly:skyline-distance
-ly:skyline::get-max-height -> ly:skyline-max-height
-ly:skyline::get-max-height-position -> ly:skyline-max-height-position
-ly:skyline::get-height -> ly:skyline-height
-Remove Default_bar_line_engraver
-""")
-def conv(s):
-    s = re.sub(r"scripts\.augmentum", r"dots.dotvaticana", s)
-    s = re.sub(r"scripts\.trillelement", r"scripts.trill_element", s)
-    s = re.sub(r"ly:skyline::get-touching-point", "ly:skyline-touching-point", s)
-    s = re.sub(r"ly:skyline::get-distance", "ly:skyline-distance", s)
-    s = re.sub(r"ly:skyline::get-max-height", "ly:skyline-max-height", s)
-    s = re.sub(r"ly:skyline::get-max-height-position", "ly:skyline-max-height-position", s)
-    s = re.sub(r"ly:skyline::get-height", "ly:skyline-height", s)
-    s = re.sub(r'[\t ]*\\(consists|remove)\s*"?Default_bar_line_engraver"?[\t ]*\n?',
-               r'', s)
-    return s
-
-percent_x_off_warning = r"""
-The X-offset property of PercentRepeat is no longer relative to the
-default position (centered), but to the left of the span within
-which the object is centered.  Overrides/tweaks to PercentRepeat.X-offset
-should be updated.
-"""
-
-@rule((2, 23, 9), r"""
-ly:percent-repeat-item-interface::xxx -> ly:percent-repeat-interface::xxx
-""")
-def conv(s):
-    s = re.sub(r"ly:percent-repeat-item-interface::", "ly:percent-repeat-interface::", s)
-    if "PercentRepeat.X-offset" in s:
-        stderr_write(NOT_SMART % "PercentRepeat.X-offset")
-        stderr_write(percent_x_off_warning)
-        stderr_write(UPDATE_MANUALLY)
-    return s
-
-@rule((2, 23, 10), r"""
-automaticBars = ##f -> measureBarType = #'()
-\\bar "-" -> \\bar ""
-BarType = "-" -> BarType = ""
-\featherDurations #(ly:make-moment x/y) -> \featherDurations x/y
-\consists Chord_name_engraver -> \consists Chord_name_engraver \consists Current_chord_text_engraver
-\remove Chord_name_engraver -> \remove Chord_name_engraver \remove Current_chord_text_engraver
-)
-""")
-def conv(s):
-    s = re.sub(r"automaticBars\s*=\s*##f", r"measureBarType = #'()", s)
-    if "automaticBars" in s:
-        stderr_write(NOT_SMART % "advanced use of automaticBars")
-        stderr_write("""
-The automaticBars property has been removed.  Instead, set
-measureBarType to #'() or a valid bar type.
-""")
-        stderr_write(UPDATE_MANUALLY)
-    s = re.sub(r'\\bar\s*"-"', r'\\bar ""', s)
-    s = re.sub(r'BarType\s*=\s*"-"', r'BarType = ""', s)
-    s = re.sub(r'(\\featherDurations\s+)#\(ly:make-moment\s+([0-9/]+)\)',
-               r'\1\2', s)
-    s = re.sub(r'\\(consists|remove) "?Chord_name_engraver"?',
-               r'\\\1 Chord_name_engraver \\\1 Current_chord_text_engraver',
-               s)
-    # This change is also in the rule for 2.13.18.  It is being
-    # replicated here because the removal was only done in 2.23.10.
-    # This ensures that a score that had previously been updated to a
-    # version between 2.13.18 and 2.23.10 without running convert-ly
-    # can still be fixed in the 2.23.10 upgrade using convert-ly.
-    # Since the change was advertised earlier, this is not part of the
-    # rule description.
-    s = re.sub(r"\\RemoveEmpty(|Drum|Rhythmic|Tab)StaffContext",
-                 r"\\\1Staff \\RemoveEmptyStaves",
-                 s)
-    s = re.sub(r"\\AncientRemoveEmptyStaffContext",
-                 r"\\VaticanaStaff \\RemoveEmptyStaves",
-                 s)
-    return s
-
-@rule((2, 23, 11), r"""
-\bar "B" -> \bar "B-|" for B in { .| .|: [|: S S.|: }
-""")
-def conv(s):
-    # We convert only \bar because automatic bar lines configured with
-    # context properties layer themselves.
-    changed_bar_types = [ # bar types which had an implicit "|" at EOL
-        r'\.\|',    # .|
-        r'\.\|:',   # .|:
-        r'\[\|:',   # [|:
-        r'S',       # S
-        r'S\.\|:']  # S.|:
-    s = re.sub(r'\\bar\s*"(' + '|'.join(changed_bar_types) + ')"',
-               r'\\bar "\1-|"', s)
-    # New syntax was introduced in 2.17.6, but this version adds a warning,
-    # which is more insistent.
-    s = convert_overrides_to_dots(s)
-    return s
-
-fine_iteration_warning = _(r"""
-Warning: \fine no longer enforces the end of the music.  If your piece
-has music following \fine that you want to exclude when it is
-unfolded, use \volta to exclude it.
-""")
-
-new_ancient_divisio_grob_warning = _(r"""
-MensuralStaff and VaticanaStaff now use Divisio_engraver to engrave
-divisiones as Divisio grobs.
-
-Previously, the respective Voice-aliased contexts used
-Breathing_sign_engraver to engrave divisiones as BreathingSign grobs.
-Because of the new names and the move from Voice to Staff, layout
-adjustments for the old scheme are not effective for the new.
-
-If you are not content with the new default layout, deal with Divisio
-and Divisio_engraver in the appropriate Staff-aliased context.
-""")
-
-new_modern_divisio_grob_warning = _(r"""
-GregorianTranscriptionStaff now engraves \divisioMinima,
-\divisioMaior, and \divisioMaxima as BarLine grobs using Bar_engraver,
-and engraves \caesura and \virgula as Divisio grobs using
-Divisio_engraver.
-
-Previously, GregorianTranscriptionVoice used Breathing_sign_engraver
-to engrave these as BreathingSign grobs.  Because of the new names and
-the move from Voice to Staff, layout adjustments for the old scheme
-are not effective for the new.
-
-If you are not content with the new default layout, deal with BarLine,
-Bar_engraver, Divisio, and Divisio_engraver in
-GregorianTranscriptionStaff context.  \EnableGregorianDivisiones may
-also be used to switch to engraving Divisio grobs instead of BarLine
-grobs.
-""")
-
-@rule((2, 23, 12), r"""
-barAlways = ##t -> forbidBreakBetweenBarLines = ##f
-\fine no longer stops iteration
-New Divisio grob
-""")
-def conv(s):
-    s = re.sub(r'barAlways\s*=\s*##t', r'forbidBreakBetweenBarLines = ##f', s)
-    s = re.sub(r'barAlways\s*=\s*##f', r'forbidBreakBetweenBarLines = ##t', s)
-    if ('\\fine' in s) and (('\\repeat segno' in s) or
-                            ('\\repeat volta' in s)):
-        stderr_write(NOT_SMART % "music following \\fine")
-        stderr_write(fine_iteration_warning)
-        stderr_write(UPDATE_MANUALLY)
-    if re.search(r"GregorianTranscription(Staff|Voice)", s) and \
-        (("BreathingSign" in s) or ("Breathing_sign_engraver" in s)):
-         stderr_write(NOT_SMART % "BreathingSign to BarLine or Divisio")
-         stderr_write(new_modern_divisio_grob_warning)
-         stderr_write(UPDATE_MANUALLY)
-    if re.search(r"(Mensural|Vaticana)(Staff|Voice)", s) and \
-        (("BreathingSign" in s) or ("Breathing_sign_engraver" in s)):
-         stderr_write(NOT_SMART % "BreathingSign to Divisio")
-         stderr_write(new_ancient_divisio_grob_warning)
-         stderr_write(UPDATE_MANUALLY)
-    return s
-
-remove_bar_always_warning = _(r"""
-The barAlways property has been removed.  Instead, use
-forbidBreakBetweenBarLines.
-""")
-
-@rule((2, 23, 13), r"""
-filtered-map -> filter-map
-Remove barAlways
-""")
-def conv(s):
-    s = re.sub(r"filtered-map", "(@ (srfi srfi-1) filter-map)", s)
-    if "barAlways" in s:
-        stderr_write(NOT_SMART % "advanced use of barAlways")
-        stderr_write(remove_bar_always_warning)
-        stderr_write(UPDATE_MANUALLY)
-    return s
-
-@rule((2, 23, 14), r"""
-changed convention for ly:skylines-for-stencil second argument
-""")
-def conv(s):
-    if "ly:skylines-for-stencil" in s:
-        stderr_write(NOT_SMART % "ly:skylines-for-stencil second argument")
-        stderr_write("""
-The second argument to ly:skylines-for-stencil is now the 'horizon axis', which
-is the opposite of the convention used previously.
-""")
-        stderr_write(UPDATE_MANUALLY)
-    return s
-
-@rule((2, 24, 0), _("bump version for release"))
-def conv(s):
-    return s
-
-
-# Guidelines to write rules (please keep this at the end of this file)
-#
-# - keep at most one rule per version; if several conversions should be done,
-# concatenate them into a single "conv" function;
-#
-# - enclose strings to be localized with `_(' and  `)';
-#
-# - write rule for bumping major stable version with
-#
-#     _ ("bump version for release")
-#
-# as exact description.
diff --git a/spaces/PeepDaSlan9/rvc-models/config.py b/spaces/PeepDaSlan9/rvc-models/config.py
deleted file mode 100644
index c0c16e0017efbcaf250cb539a1d0edb4e83575e4..0000000000000000000000000000000000000000
--- a/spaces/PeepDaSlan9/rvc-models/config.py
+++ /dev/null
@@ -1,88 +0,0 @@
-########################硬件参数########################
-
-# 填写cuda:x, cpu 或 mps, x指代第几张卡，只支持 N卡 / Apple Silicon 加速
-device = "cuda:0"
-
-# 9-10-20-30-40系显卡无脑True，不影响质量，>=20显卡开启有加速
-is_half = True
-
-# 默认0用上所有线程，写数字限制CPU资源使用
-n_cpu = 0
-
-########################硬件参数########################
-
-
-##################下为参数处理逻辑，勿动##################
-
-########################命令行参数########################
-import argparse
-
-parser = argparse.ArgumentParser()
-parser.add_argument("--port", type=int, default=7865, help="Listen port")
-parser.add_argument("--pycmd", type=str, default="python", help="Python command")
-parser.add_argument("--colab", action="store_true", help="Launch in colab")
-parser.add_argument(
-    "--noparallel", action="store_true", help="Disable parallel processing"
-)
-parser.add_argument(
-    "--noautoopen", action="store_true", help="Do not open in browser automatically"
-)
-cmd_opts, unknown = parser.parse_known_args()
-
-python_cmd = cmd_opts.pycmd
-listen_port = cmd_opts.port
-iscolab = cmd_opts.colab
-noparallel = cmd_opts.noparallel
-noautoopen = cmd_opts.noautoopen
-########################命令行参数########################
-
-import sys
-import torch
-
-
-# has_mps is only available in nightly pytorch (for now) and MasOS 12.3+.
-# check `getattr` and try it for compatibility
-def has_mps() -> bool:
-    if sys.platform != "darwin":
-        return False
-    else:
-        if not getattr(torch, "has_mps", False):
-            return False
-        try:
-            torch.zeros(1).to(torch.device("mps"))
-            return True
-        except Exception:
-            return False
-
-
-if not torch.cuda.is_available():
-    if has_mps():
-        print("没有发现支持的N卡, 使用MPS进行推理")
-        device = "mps"
-    else:
-        print("没有发现支持的N卡, 使用CPU进行推理")
-        device = "cpu"
-        is_half = False
-
-if device not in ["cpu", "mps"]:
-    gpu_name = torch.cuda.get_device_name(int(device.split(":")[-1]))
-    if "16" in gpu_name or "MX" in gpu_name:
-        print("16系显卡/MX系显卡强制单精度")
-        is_half = False
-
-from multiprocessing import cpu_count
-
-if n_cpu == 0:
-    n_cpu = cpu_count()
-if is_half:
-    # 6G显存配置
-    x_pad = 3
-    x_query = 10
-    x_center = 60
-    x_max = 65
-else:
-    # 5G显存配置
-    x_pad = 1
-    x_query = 6
-    x_center = 38
-    x_max = 41
diff --git a/spaces/Pie31415/control-animation/annotator/uniformer/mmcv/utils/logging.py b/spaces/Pie31415/control-animation/annotator/uniformer/mmcv/utils/logging.py
deleted file mode 100644
index 4aa0e04bb9b3ab2a4bfbc4def50404ccbac2c6e6..0000000000000000000000000000000000000000
--- a/spaces/Pie31415/control-animation/annotator/uniformer/mmcv/utils/logging.py
+++ /dev/null
@@ -1,110 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import logging
-
-import torch.distributed as dist
-
-logger_initialized = {}
-
-
-def get_logger(name, log_file=None, log_level=logging.INFO, file_mode='w'):
-    """Initialize and get a logger by name.
-
-    If the logger has not been initialized, this method will initialize the
-    logger by adding one or two handlers, otherwise the initialized logger will
-    be directly returned. During initialization, a StreamHandler will always be
-    added. If `log_file` is specified and the process rank is 0, a FileHandler
-    will also be added.
-
-    Args:
-        name (str): Logger name.
-        log_file (str | None): The log filename. If specified, a FileHandler
-            will be added to the logger.
-        log_level (int): The logger level. Note that only the process of
-            rank 0 is affected, and other processes will set the level to
-            "Error" thus be silent most of the time.
-        file_mode (str): The file mode used in opening log file.
-            Defaults to 'w'.
-
-    Returns:
-        logging.Logger: The expected logger.
-    """
-    logger = logging.getLogger(name)
-    if name in logger_initialized:
-        return logger
-    # handle hierarchical names
-    # e.g., logger "a" is initialized, then logger "a.b" will skip the
-    # initialization since it is a child of "a".
-    for logger_name in logger_initialized:
-        if name.startswith(logger_name):
-            return logger
-
-    # handle duplicate logs to the console
-    # Starting in 1.8.0, PyTorch DDP attaches a StreamHandler <stderr> (NOTSET)
-    # to the root logger. As logger.propagate is True by default, this root
-    # level handler causes logging messages from rank>0 processes to
-    # unexpectedly show up on the console, creating much unwanted clutter.
-    # To fix this issue, we set the root logger's StreamHandler, if any, to log
-    # at the ERROR level.
-    for handler in logger.root.handlers:
-        if type(handler) is logging.StreamHandler:
-            handler.setLevel(logging.ERROR)
-
-    stream_handler = logging.StreamHandler()
-    handlers = [stream_handler]
-
-    if dist.is_available() and dist.is_initialized():
-        rank = dist.get_rank()
-    else:
-        rank = 0
-
-    # only rank 0 will add a FileHandler
-    if rank == 0 and log_file is not None:
-        # Here, the default behaviour of the official logger is 'a'. Thus, we
-        # provide an interface to change the file mode to the default
-        # behaviour.
-        file_handler = logging.FileHandler(log_file, file_mode)
-        handlers.append(file_handler)
-
-    formatter = logging.Formatter(
-        '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-    for handler in handlers:
-        handler.setFormatter(formatter)
-        handler.setLevel(log_level)
-        logger.addHandler(handler)
-
-    if rank == 0:
-        logger.setLevel(log_level)
-    else:
-        logger.setLevel(logging.ERROR)
-
-    logger_initialized[name] = True
-
-    return logger
-
-
-def print_log(msg, logger=None, level=logging.INFO):
-    """Print a log message.
-
-    Args:
-        msg (str): The message to be logged.
-        logger (logging.Logger | str | None): The logger to be used.
-            Some special loggers are:
-            - "silent": no message will be printed.
-            - other str: the logger obtained with `get_root_logger(logger)`.
-            - None: The `print()` method will be used to print log messages.
-        level (int): Logging level. Only available when `logger` is a Logger
-            object or "root".
-    """
-    if logger is None:
-        print(msg)
-    elif isinstance(logger, logging.Logger):
-        logger.log(level, msg)
-    elif logger == 'silent':
-        pass
-    elif isinstance(logger, str):
-        _logger = get_logger(logger)
-        _logger.log(level, msg)
-    else:
-        raise TypeError(
-            'logger should be either a logging.Logger object, str, '
-            f'"silent" or None, but got {type(logger)}')
diff --git a/spaces/Plachta/VITS-Umamusume-voice-synthesizer/ONNXVITS_modules.py b/spaces/Plachta/VITS-Umamusume-voice-synthesizer/ONNXVITS_modules.py
deleted file mode 100644
index 6cf676ce37c1eaf8428c4094e749f862182cb0c3..0000000000000000000000000000000000000000
--- a/spaces/Plachta/VITS-Umamusume-voice-synthesizer/ONNXVITS_modules.py
+++ /dev/null
@@ -1,390 +0,0 @@
-import copy
-import math
-import numpy as np
-import scipy
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
-from torch.nn.utils import weight_norm, remove_weight_norm
-
-import commons
-from commons import init_weights, get_padding
-from ONNXVITS_transforms import piecewise_rational_quadratic_transform
-
-
-LRELU_SLOPE = 0.1
-
-
-class LayerNorm(nn.Module):
-  def __init__(self, channels, eps=1e-5):
-    super().__init__()
-    self.channels = channels
-    self.eps = eps
-
-    self.gamma = nn.Parameter(torch.ones(channels))
-    self.beta = nn.Parameter(torch.zeros(channels))
-
-  def forward(self, x):
-    x = x.transpose(1, -1)
-    x = F.layer_norm(x, (self.channels,), self.gamma, self.beta, self.eps)
-    return x.transpose(1, -1)
-
- 
-class ConvReluNorm(nn.Module):
-  def __init__(self, in_channels, hidden_channels, out_channels, kernel_size, n_layers, p_dropout):
-    super().__init__()
-    self.in_channels = in_channels
-    self.hidden_channels = hidden_channels
-    self.out_channels = out_channels
-    self.kernel_size = kernel_size
-    self.n_layers = n_layers
-    self.p_dropout = p_dropout
-    assert n_layers > 1, "Number of layers should be larger than 0."
-
-    self.conv_layers = nn.ModuleList()
-    self.norm_layers = nn.ModuleList()
-    self.conv_layers.append(nn.Conv1d(in_channels, hidden_channels, kernel_size, padding=kernel_size//2))
-    self.norm_layers.append(LayerNorm(hidden_channels))
-    self.relu_drop = nn.Sequential(
-        nn.ReLU(),
-        nn.Dropout(p_dropout))
-    for _ in range(n_layers-1):
-      self.conv_layers.append(nn.Conv1d(hidden_channels, hidden_channels, kernel_size, padding=kernel_size//2))
-      self.norm_layers.append(LayerNorm(hidden_channels))
-    self.proj = nn.Conv1d(hidden_channels, out_channels, 1)
-    self.proj.weight.data.zero_()
-    self.proj.bias.data.zero_()
-
-  def forward(self, x, x_mask):
-    x_org = x
-    for i in range(self.n_layers):
-      x = self.conv_layers[i](x * x_mask)
-      x = self.norm_layers[i](x)
-      x = self.relu_drop(x)
-    x = x_org + self.proj(x)
-    return x * x_mask
-
-
-class DDSConv(nn.Module):
-  """
-  Dialted and Depth-Separable Convolution
-  """
-  def __init__(self, channels, kernel_size, n_layers, p_dropout=0.):
-    super().__init__()
-    self.channels = channels
-    self.kernel_size = kernel_size
-    self.n_layers = n_layers
-    self.p_dropout = p_dropout
-
-    self.drop = nn.Dropout(p_dropout)
-    self.convs_sep = nn.ModuleList()
-    self.convs_1x1 = nn.ModuleList()
-    self.norms_1 = nn.ModuleList()
-    self.norms_2 = nn.ModuleList()
-    for i in range(n_layers):
-      dilation = kernel_size ** i
-      padding = (kernel_size * dilation - dilation) // 2
-      self.convs_sep.append(nn.Conv1d(channels, channels, kernel_size, 
-          groups=channels, dilation=dilation, padding=padding
-      ))
-      self.convs_1x1.append(nn.Conv1d(channels, channels, 1))
-      self.norms_1.append(LayerNorm(channels))
-      self.norms_2.append(LayerNorm(channels))
-
-  def forward(self, x, x_mask, g=None):
-    if g is not None:
-      x = x + g
-    for i in range(self.n_layers):
-      y = self.convs_sep[i](x * x_mask)
-      y = self.norms_1[i](y)
-      y = F.gelu(y)
-      y = self.convs_1x1[i](y)
-      y = self.norms_2[i](y)
-      y = F.gelu(y)
-      y = self.drop(y)
-      x = x + y
-    return x * x_mask
-
-
-class WN(torch.nn.Module):
-  def __init__(self, hidden_channels, kernel_size, dilation_rate, n_layers, gin_channels=0, p_dropout=0):
-    super(WN, self).__init__()
-    assert(kernel_size % 2 == 1)
-    self.hidden_channels =hidden_channels
-    self.kernel_size = kernel_size,
-    self.dilation_rate = dilation_rate
-    self.n_layers = n_layers
-    self.gin_channels = gin_channels
-    self.p_dropout = p_dropout
-
-    self.in_layers = torch.nn.ModuleList()
-    self.res_skip_layers = torch.nn.ModuleList()
-    self.drop = nn.Dropout(p_dropout)
-
-    if gin_channels != 0:
-      cond_layer = torch.nn.Conv1d(gin_channels, 2*hidden_channels*n_layers, 1)
-      self.cond_layer = torch.nn.utils.weight_norm(cond_layer, name='weight')
-
-    for i in range(n_layers):
-      dilation = dilation_rate ** i
-      padding = int((kernel_size * dilation - dilation) / 2)
-      in_layer = torch.nn.Conv1d(hidden_channels, 2*hidden_channels, kernel_size,
-                                 dilation=dilation, padding=padding)
-      in_layer = torch.nn.utils.weight_norm(in_layer, name='weight')
-      self.in_layers.append(in_layer)
-
-      # last one is not necessary
-      if i < n_layers - 1:
-        res_skip_channels = 2 * hidden_channels
-      else:
-        res_skip_channels = hidden_channels
-
-      res_skip_layer = torch.nn.Conv1d(hidden_channels, res_skip_channels, 1)
-      res_skip_layer = torch.nn.utils.weight_norm(res_skip_layer, name='weight')
-      self.res_skip_layers.append(res_skip_layer)
-
-  def forward(self, x, x_mask, g=None, **kwargs):
-    output = torch.zeros_like(x)
-    n_channels_tensor = torch.IntTensor([self.hidden_channels])
-
-    if g is not None:
-      g = self.cond_layer(g)
-
-    for i in range(self.n_layers):
-      x_in = self.in_layers[i](x)
-      if g is not None:
-        cond_offset = i * 2 * self.hidden_channels
-        g_l = g[:,cond_offset:cond_offset+2*self.hidden_channels,:]
-      else:
-        g_l = torch.zeros_like(x_in)
-
-      acts = commons.fused_add_tanh_sigmoid_multiply(
-          x_in,
-          g_l,
-          n_channels_tensor)
-      acts = self.drop(acts)
-
-      res_skip_acts = self.res_skip_layers[i](acts)
-      if i < self.n_layers - 1:
-        res_acts = res_skip_acts[:,:self.hidden_channels,:]
-        x = (x + res_acts) * x_mask
-        output = output + res_skip_acts[:,self.hidden_channels:,:]
-      else:
-        output = output + res_skip_acts
-    return output * x_mask
-
-  def remove_weight_norm(self):
-    if self.gin_channels != 0:
-      torch.nn.utils.remove_weight_norm(self.cond_layer)
-    for l in self.in_layers:
-      torch.nn.utils.remove_weight_norm(l)
-    for l in self.res_skip_layers:
-     torch.nn.utils.remove_weight_norm(l)
-
-
-class ResBlock1(torch.nn.Module):
-    def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
-        super(ResBlock1, self).__init__()
-        self.convs1 = nn.ModuleList([
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[0],
-                               padding=get_padding(kernel_size, dilation[0]))),
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[1],
-                               padding=get_padding(kernel_size, dilation[1]))),
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[2],
-                               padding=get_padding(kernel_size, dilation[2])))
-        ])
-        self.convs1.apply(init_weights)
-
-        self.convs2 = nn.ModuleList([
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
-                               padding=get_padding(kernel_size, 1))),
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
-                               padding=get_padding(kernel_size, 1))),
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
-                               padding=get_padding(kernel_size, 1)))
-        ])
-        self.convs2.apply(init_weights)
-
-    def forward(self, x, x_mask=None):
-        for c1, c2 in zip(self.convs1, self.convs2):
-            xt = F.leaky_relu(x, LRELU_SLOPE)
-            if x_mask is not None:
-                xt = xt * x_mask
-            xt = c1(xt)
-            xt = F.leaky_relu(xt, LRELU_SLOPE)
-            if x_mask is not None:
-                xt = xt * x_mask
-            xt = c2(xt)
-            x = xt + x
-        if x_mask is not None:
-            x = x * x_mask
-        return x
-
-    def remove_weight_norm(self):
-        for l in self.convs1:
-            remove_weight_norm(l)
-        for l in self.convs2:
-            remove_weight_norm(l)
-
-
-class ResBlock2(torch.nn.Module):
-    def __init__(self, channels, kernel_size=3, dilation=(1, 3)):
-        super(ResBlock2, self).__init__()
-        self.convs = nn.ModuleList([
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[0],
-                               padding=get_padding(kernel_size, dilation[0]))),
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[1],
-                               padding=get_padding(kernel_size, dilation[1])))
-        ])
-        self.convs.apply(init_weights)
-
-    def forward(self, x, x_mask=None):
-        for c in self.convs:
-            xt = F.leaky_relu(x, LRELU_SLOPE)
-            if x_mask is not None:
-                xt = xt * x_mask
-            xt = c(xt)
-            x = xt + x
-        if x_mask is not None:
-            x = x * x_mask
-        return x
-
-    def remove_weight_norm(self):
-        for l in self.convs:
-            remove_weight_norm(l)
-
-
-class Log(nn.Module):
-  def forward(self, x, x_mask, reverse=False, **kwargs):
-    if not reverse:
-      y = torch.log(torch.clamp_min(x, 1e-5)) * x_mask
-      logdet = torch.sum(-y, [1, 2])
-      return y, logdet
-    else:
-      x = torch.exp(x) * x_mask
-      return x
-    
-
-class Flip(nn.Module):
-  def forward(self, x, *args, reverse=False, **kwargs):
-    x = torch.flip(x, [1])
-    if not reverse:
-      logdet = torch.zeros(x.size(0)).to(dtype=x.dtype, device=x.device)
-      return x, logdet
-    else:
-      return x
-
-
-class ElementwiseAffine(nn.Module):
-  def __init__(self, channels):
-    super().__init__()
-    self.channels = channels
-    self.m = nn.Parameter(torch.zeros(channels,1))
-    self.logs = nn.Parameter(torch.zeros(channels,1))
-
-  def forward(self, x, x_mask, reverse=False, **kwargs):
-    if not reverse:
-      y = self.m + torch.exp(self.logs) * x
-      y = y * x_mask
-      logdet = torch.sum(self.logs * x_mask, [1,2])
-      return y, logdet
-    else:
-      x = (x - self.m) * torch.exp(-self.logs) * x_mask
-      return x
-
-
-class ResidualCouplingLayer(nn.Module):
-  def __init__(self,
-      channels,
-      hidden_channels,
-      kernel_size,
-      dilation_rate,
-      n_layers,
-      p_dropout=0,
-      gin_channels=0,
-      mean_only=False):
-    assert channels % 2 == 0, "channels should be divisible by 2"
-    super().__init__()
-    self.channels = channels
-    self.hidden_channels = hidden_channels
-    self.kernel_size = kernel_size
-    self.dilation_rate = dilation_rate
-    self.n_layers = n_layers
-    self.half_channels = channels // 2
-    self.mean_only = mean_only
-
-    self.pre = nn.Conv1d(self.half_channels, hidden_channels, 1)
-    self.enc = WN(hidden_channels, kernel_size, dilation_rate, n_layers, p_dropout=p_dropout, gin_channels=gin_channels)
-    self.post = nn.Conv1d(hidden_channels, self.half_channels * (2 - mean_only), 1)
-    self.post.weight.data.zero_()
-    self.post.bias.data.zero_()
-
-  def forward(self, x, x_mask, g=None, reverse=False):
-    x0, x1 = torch.split(x, [self.half_channels]*2, 1)
-    h = self.pre(x0) * x_mask
-    h = self.enc(h, x_mask, g=g)
-    stats = self.post(h) * x_mask
-    if not self.mean_only:
-      m, logs = torch.split(stats, [self.half_channels]*2, 1)
-    else:
-      m = stats
-      logs = torch.zeros_like(m)
-
-    if not reverse:
-      x1 = m + x1 * torch.exp(logs) * x_mask
-      x = torch.cat([x0, x1], 1)
-      logdet = torch.sum(logs, [1,2])
-      return x, logdet
-    else:
-      x1 = (x1 - m) * torch.exp(-logs) * x_mask
-      x = torch.cat([x0, x1], 1)
-      return x
-
-
-class ConvFlow(nn.Module):
-  def __init__(self, in_channels, filter_channels, kernel_size, n_layers, num_bins=10, tail_bound=5.0):
-    super().__init__()
-    self.in_channels = in_channels
-    self.filter_channels = filter_channels
-    self.kernel_size = kernel_size
-    self.n_layers = n_layers
-    self.num_bins = num_bins
-    self.tail_bound = tail_bound
-    self.half_channels = in_channels // 2
-
-    self.pre = nn.Conv1d(self.half_channels, filter_channels, 1)
-    self.convs = DDSConv(filter_channels, kernel_size, n_layers, p_dropout=0.)
-    self.proj = nn.Conv1d(filter_channels, self.half_channels * (num_bins * 3 - 1), 1)
-    self.proj.weight.data.zero_()
-    self.proj.bias.data.zero_()
-
-  def forward(self, x, x_mask, g=None, reverse=False):
-    x0, x1 = torch.split(x, [self.half_channels]*2, 1)
-    h = self.pre(x0)
-    h = self.convs(h, x_mask, g=g)
-    h = self.proj(h) * x_mask
-
-    b, c, t = x0.shape
-    h = h.reshape(b, c, -1, t).permute(0, 1, 3, 2) # [b, cx?, t] -> [b, c, t, ?]
-
-    unnormalized_widths = h[..., :self.num_bins] / math.sqrt(self.filter_channels)
-    unnormalized_heights = h[..., self.num_bins:2*self.num_bins] / math.sqrt(self.filter_channels)
-    unnormalized_derivatives = h[..., 2 * self.num_bins:]
-
-    x1, logabsdet = piecewise_rational_quadratic_transform(x1,
-        unnormalized_widths,
-        unnormalized_heights,
-        unnormalized_derivatives,
-        inverse=reverse,
-        tails='linear',
-        tail_bound=self.tail_bound
-    )
-
-    x = torch.cat([x0, x1], 1) * x_mask
-    logdet = torch.sum(logabsdet * x_mask, [1,2])
-    if not reverse:
-        return x, logdet
-    else:
-        return x
diff --git a/spaces/ProteinDesignLab/protpardelle/core/__init__.py b/spaces/ProteinDesignLab/protpardelle/core/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/RO4DHOG/Ripper/app.py b/spaces/RO4DHOG/Ripper/app.py
deleted file mode 100644
index a699bc5b3c2e987102ca93e0ee28d601e0a93d02..0000000000000000000000000000000000000000
--- a/spaces/RO4DHOG/Ripper/app.py
+++ /dev/null
@@ -1,7 +0,0 @@
-import gradio as gr
-
-def greet(name):
-    return "Hello " + name + "!!"
-
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
\ No newline at end of file
diff --git a/spaces/Ragnov/STT-Grammar-Checker/README.md b/spaces/Ragnov/STT-Grammar-Checker/README.md
deleted file mode 100644
index 1074ff849340a80f0e4d8508597d14e26d10ae8d..0000000000000000000000000000000000000000
--- a/spaces/Ragnov/STT-Grammar-Checker/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: STT Grammar Checker
-emoji: 📊
-colorFrom: yellow
-colorTo: indigo
-sdk: gradio
-sdk_version: 3.20.1
-app_file: app.py
-pinned: false
-license: cc-by-nc-sa-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Raspberry-ai/main/.env/lib/python3.11/site-packages/pip/_vendor/pygments/formatters/terminal256.py b/spaces/Raspberry-ai/main/.env/lib/python3.11/site-packages/pip/_vendor/pygments/formatters/terminal256.py
deleted file mode 100644
index 201b3c3283218f45d5cfa192a07c9e9d991eaaff..0000000000000000000000000000000000000000
--- a/spaces/Raspberry-ai/main/.env/lib/python3.11/site-packages/pip/_vendor/pygments/formatters/terminal256.py
+++ /dev/null
@@ -1,338 +0,0 @@
-"""
-    pygments.formatters.terminal256
-    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-    Formatter for 256-color terminal output with ANSI sequences.
-
-    RGB-to-XTERM color conversion routines adapted from xterm256-conv
-    tool (http://frexx.de/xterm-256-notes/data/xterm256-conv2.tar.bz2)
-    by Wolfgang Frisch.
-
-    Formatter version 1.
-
-    :copyright: Copyright 2006-2022 by the Pygments team, see AUTHORS.
-    :license: BSD, see LICENSE for details.
-"""
-
-# TODO:
-#  - Options to map style's bold/underline/italic/border attributes
-#    to some ANSI attrbutes (something like 'italic=underline')
-#  - An option to output "style RGB to xterm RGB/index" conversion table
-#  - An option to indicate that we are running in "reverse background"
-#    xterm. This means that default colors are white-on-black, not
-#    black-on-while, so colors like "white background" need to be converted
-#    to "white background, black foreground", etc...
-
-from pip._vendor.pygments.formatter import Formatter
-from pip._vendor.pygments.console import codes
-from pip._vendor.pygments.style import ansicolors
-
-
-__all__ = ['Terminal256Formatter', 'TerminalTrueColorFormatter']
-
-
-class EscapeSequence:
-    def __init__(self, fg=None, bg=None, bold=False, underline=False, italic=False):
-        self.fg = fg
-        self.bg = bg
-        self.bold = bold
-        self.underline = underline
-        self.italic = italic
-
-    def escape(self, attrs):
-        if len(attrs):
-            return "\x1b[" + ";".join(attrs) + "m"
-        return ""
-
-    def color_string(self):
-        attrs = []
-        if self.fg is not None:
-            if self.fg in ansicolors:
-                esc = codes[self.fg.replace('ansi','')]
-                if ';01m' in esc:
-                    self.bold = True
-                # extract fg color code.
-                attrs.append(esc[2:4])
-            else:
-                attrs.extend(("38", "5", "%i" % self.fg))
-        if self.bg is not None:
-            if self.bg in ansicolors:
-                esc = codes[self.bg.replace('ansi','')]
-                # extract fg color code, add 10 for bg.
-                attrs.append(str(int(esc[2:4])+10))
-            else:
-                attrs.extend(("48", "5", "%i" % self.bg))
-        if self.bold:
-            attrs.append("01")
-        if self.underline:
-            attrs.append("04")
-        if self.italic:
-            attrs.append("03")
-        return self.escape(attrs)
-
-    def true_color_string(self):
-        attrs = []
-        if self.fg:
-            attrs.extend(("38", "2", str(self.fg[0]), str(self.fg[1]), str(self.fg[2])))
-        if self.bg:
-            attrs.extend(("48", "2", str(self.bg[0]), str(self.bg[1]), str(self.bg[2])))
-        if self.bold:
-            attrs.append("01")
-        if self.underline:
-            attrs.append("04")
-        if self.italic:
-            attrs.append("03")
-        return self.escape(attrs)
-
-    def reset_string(self):
-        attrs = []
-        if self.fg is not None:
-            attrs.append("39")
-        if self.bg is not None:
-            attrs.append("49")
-        if self.bold or self.underline or self.italic:
-            attrs.append("00")
-        return self.escape(attrs)
-
-
-class Terminal256Formatter(Formatter):
-    """
-    Format tokens with ANSI color sequences, for output in a 256-color
-    terminal or console.  Like in `TerminalFormatter` color sequences
-    are terminated at newlines, so that paging the output works correctly.
-
-    The formatter takes colors from a style defined by the `style` option
-    and converts them to nearest ANSI 256-color escape sequences. Bold and
-    underline attributes from the style are preserved (and displayed).
-
-    .. versionadded:: 0.9
-
-    .. versionchanged:: 2.2
-       If the used style defines foreground colors in the form ``#ansi*``, then
-       `Terminal256Formatter` will map these to non extended foreground color.
-       See :ref:`AnsiTerminalStyle` for more information.
-
-    .. versionchanged:: 2.4
-       The ANSI color names have been updated with names that are easier to
-       understand and align with colornames of other projects and terminals.
-       See :ref:`this table <new-ansi-color-names>` for more information.
-
-
-    Options accepted:
-
-    `style`
-        The style to use, can be a string or a Style subclass (default:
-        ``'default'``).
-
-    `linenos`
-        Set to ``True`` to have line numbers on the terminal output as well
-        (default: ``False`` = no line numbers).
-    """
-    name = 'Terminal256'
-    aliases = ['terminal256', 'console256', '256']
-    filenames = []
-
-    def __init__(self, **options):
-        Formatter.__init__(self, **options)
-
-        self.xterm_colors = []
-        self.best_match = {}
-        self.style_string = {}
-
-        self.usebold = 'nobold' not in options
-        self.useunderline = 'nounderline' not in options
-        self.useitalic = 'noitalic' not in options
-
-        self._build_color_table()  # build an RGB-to-256 color conversion table
-        self._setup_styles()  # convert selected style's colors to term. colors
-
-        self.linenos = options.get('linenos', False)
-        self._lineno = 0
-
-    def _build_color_table(self):
-        # colors 0..15: 16 basic colors
-
-        self.xterm_colors.append((0x00, 0x00, 0x00))  # 0
-        self.xterm_colors.append((0xcd, 0x00, 0x00))  # 1
-        self.xterm_colors.append((0x00, 0xcd, 0x00))  # 2
-        self.xterm_colors.append((0xcd, 0xcd, 0x00))  # 3
-        self.xterm_colors.append((0x00, 0x00, 0xee))  # 4
-        self.xterm_colors.append((0xcd, 0x00, 0xcd))  # 5
-        self.xterm_colors.append((0x00, 0xcd, 0xcd))  # 6
-        self.xterm_colors.append((0xe5, 0xe5, 0xe5))  # 7
-        self.xterm_colors.append((0x7f, 0x7f, 0x7f))  # 8
-        self.xterm_colors.append((0xff, 0x00, 0x00))  # 9
-        self.xterm_colors.append((0x00, 0xff, 0x00))  # 10
-        self.xterm_colors.append((0xff, 0xff, 0x00))  # 11
-        self.xterm_colors.append((0x5c, 0x5c, 0xff))  # 12
-        self.xterm_colors.append((0xff, 0x00, 0xff))  # 13
-        self.xterm_colors.append((0x00, 0xff, 0xff))  # 14
-        self.xterm_colors.append((0xff, 0xff, 0xff))  # 15
-
-        # colors 16..232: the 6x6x6 color cube
-
-        valuerange = (0x00, 0x5f, 0x87, 0xaf, 0xd7, 0xff)
-
-        for i in range(217):
-            r = valuerange[(i // 36) % 6]
-            g = valuerange[(i // 6) % 6]
-            b = valuerange[i % 6]
-            self.xterm_colors.append((r, g, b))
-
-        # colors 233..253: grayscale
-
-        for i in range(1, 22):
-            v = 8 + i * 10
-            self.xterm_colors.append((v, v, v))
-
-    def _closest_color(self, r, g, b):
-        distance = 257*257*3  # "infinity" (>distance from #000000 to #ffffff)
-        match = 0
-
-        for i in range(0, 254):
-            values = self.xterm_colors[i]
-
-            rd = r - values[0]
-            gd = g - values[1]
-            bd = b - values[2]
-            d = rd*rd + gd*gd + bd*bd
-
-            if d < distance:
-                match = i
-                distance = d
-        return match
-
-    def _color_index(self, color):
-        index = self.best_match.get(color, None)
-        if color in ansicolors:
-            # strip the `ansi/#ansi` part and look up code
-            index = color
-            self.best_match[color] = index
-        if index is None:
-            try:
-                rgb = int(str(color), 16)
-            except ValueError:
-                rgb = 0
-
-            r = (rgb >> 16) & 0xff
-            g = (rgb >> 8) & 0xff
-            b = rgb & 0xff
-            index = self._closest_color(r, g, b)
-            self.best_match[color] = index
-        return index
-
-    def _setup_styles(self):
-        for ttype, ndef in self.style:
-            escape = EscapeSequence()
-            # get foreground from ansicolor if set
-            if ndef['ansicolor']:
-                escape.fg = self._color_index(ndef['ansicolor'])
-            elif ndef['color']:
-                escape.fg = self._color_index(ndef['color'])
-            if ndef['bgansicolor']:
-                escape.bg = self._color_index(ndef['bgansicolor'])
-            elif ndef['bgcolor']:
-                escape.bg = self._color_index(ndef['bgcolor'])
-            if self.usebold and ndef['bold']:
-                escape.bold = True
-            if self.useunderline and ndef['underline']:
-                escape.underline = True
-            if self.useitalic and ndef['italic']:
-                escape.italic = True
-            self.style_string[str(ttype)] = (escape.color_string(),
-                                             escape.reset_string())
-
-    def _write_lineno(self, outfile):
-        self._lineno += 1
-        outfile.write("%s%04d: " % (self._lineno != 1 and '\n' or '', self._lineno))
-
-    def format(self, tokensource, outfile):
-        return Formatter.format(self, tokensource, outfile)
-
-    def format_unencoded(self, tokensource, outfile):
-        if self.linenos:
-            self._write_lineno(outfile)
-
-        for ttype, value in tokensource:
-            not_found = True
-            while ttype and not_found:
-                try:
-                    # outfile.write( "<" + str(ttype) + ">" )
-                    on, off = self.style_string[str(ttype)]
-
-                    # Like TerminalFormatter, add "reset colors" escape sequence
-                    # on newline.
-                    spl = value.split('\n')
-                    for line in spl[:-1]:
-                        if line:
-                            outfile.write(on + line + off)
-                        if self.linenos:
-                            self._write_lineno(outfile)
-                        else:
-                            outfile.write('\n')
-
-                    if spl[-1]:
-                        outfile.write(on + spl[-1] + off)
-
-                    not_found = False
-                    # outfile.write( '#' + str(ttype) + '#' )
-
-                except KeyError:
-                    # ottype = ttype
-                    ttype = ttype.parent
-                    # outfile.write( '!' + str(ottype) + '->' + str(ttype) + '!' )
-
-            if not_found:
-                outfile.write(value)
-
-        if self.linenos:
-            outfile.write("\n")
-
-
-
-class TerminalTrueColorFormatter(Terminal256Formatter):
-    r"""
-    Format tokens with ANSI color sequences, for output in a true-color
-    terminal or console.  Like in `TerminalFormatter` color sequences
-    are terminated at newlines, so that paging the output works correctly.
-
-    .. versionadded:: 2.1
-
-    Options accepted:
-
-    `style`
-        The style to use, can be a string or a Style subclass (default:
-        ``'default'``).
-    """
-    name = 'TerminalTrueColor'
-    aliases = ['terminal16m', 'console16m', '16m']
-    filenames = []
-
-    def _build_color_table(self):
-        pass
-
-    def _color_tuple(self, color):
-        try:
-            rgb = int(str(color), 16)
-        except ValueError:
-            return None
-        r = (rgb >> 16) & 0xff
-        g = (rgb >> 8) & 0xff
-        b = rgb & 0xff
-        return (r, g, b)
-
-    def _setup_styles(self):
-        for ttype, ndef in self.style:
-            escape = EscapeSequence()
-            if ndef['color']:
-                escape.fg = self._color_tuple(ndef['color'])
-            if ndef['bgcolor']:
-                escape.bg = self._color_tuple(ndef['bgcolor'])
-            if self.usebold and ndef['bold']:
-                escape.bold = True
-            if self.useunderline and ndef['underline']:
-                escape.underline = True
-            if self.useitalic and ndef['italic']:
-                escape.italic = True
-            self.style_string[str(ttype)] = (escape.true_color_string(),
-                                             escape.reset_string())
diff --git a/spaces/Realcat/image-matching-webui/hloc/matchers/sold2.py b/spaces/Realcat/image-matching-webui/hloc/matchers/sold2.py
deleted file mode 100644
index 62e953ff7ca53076b887419bb25ec20c069677c6..0000000000000000000000000000000000000000
--- a/spaces/Realcat/image-matching-webui/hloc/matchers/sold2.py
+++ /dev/null
@@ -1,152 +0,0 @@
-import sys
-from pathlib import Path
-from ..utils.base_model import BaseModel
-import torch
-
-from ..utils.base_model import BaseModel
-from .. import logger
-import subprocess
-
-sold2_path = Path(__file__).parent / "../../third_party/SOLD2"
-sys.path.append(str(sold2_path))
-
-from sold2.model.line_matcher import LineMatcher
-
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-
-
-class SOLD2(BaseModel):
-    default_conf = {
-        "weights": "sold2_wireframe.tar",
-        "match_threshold": 0.2,
-        "checkpoint_dir": sold2_path / "pretrained",
-        "detect_thresh": 0.25,
-        "multiscale": False,
-        "valid_thresh": 1e-3,
-        "num_blocks": 20,
-        "overlap_ratio": 0.5,
-    }
-    required_inputs = [
-        "image0",
-        "image1",
-    ]
-
-    weight_urls = {
-        "sold2_wireframe.tar": "https://www.polybox.ethz.ch/index.php/s/blOrW89gqSLoHOk/download",
-    }
-    # Initialize the line matcher
-    def _init(self, conf):
-        checkpoint_path = conf["checkpoint_dir"] / conf["weights"]
-
-        # Download the model.
-        if not checkpoint_path.exists():
-            checkpoint_path.parent.mkdir(exist_ok=True)
-            link = self.weight_urls[conf["weights"]]
-            cmd = ["wget", link, "-O", str(checkpoint_path)]
-            logger.info(f"Downloading the SOLD2 model with `{cmd}`.")
-            subprocess.run(cmd, check=True)
-
-        mode = "dynamic"  # 'dynamic' or 'static'
-        match_config = {
-            "model_cfg": {
-                "model_name": "lcnn_simple",
-                "model_architecture": "simple",
-                # Backbone related config
-                "backbone": "lcnn",
-                "backbone_cfg": {
-                    "input_channel": 1,  # Use RGB images or grayscale images.
-                    "depth": 4,
-                    "num_stacks": 2,
-                    "num_blocks": 1,
-                    "num_classes": 5,
-                },
-                # Junction decoder related config
-                "junction_decoder": "superpoint_decoder",
-                "junc_decoder_cfg": {},
-                # Heatmap decoder related config
-                "heatmap_decoder": "pixel_shuffle",
-                "heatmap_decoder_cfg": {},
-                # Descriptor decoder related config
-                "descriptor_decoder": "superpoint_descriptor",
-                "descriptor_decoder_cfg": {},
-                # Shared configurations
-                "grid_size": 8,
-                "keep_border_valid": True,
-                # Threshold of junction detection
-                "detection_thresh": 0.0153846,  # 1/65
-                "max_num_junctions": 300,
-                # Threshold of heatmap detection
-                "prob_thresh": 0.5,
-                # Weighting related parameters
-                "weighting_policy": mode,
-                # [Heatmap loss]
-                "w_heatmap": 0.0,
-                "w_heatmap_class": 1,
-                "heatmap_loss_func": "cross_entropy",
-                "heatmap_loss_cfg": {"policy": mode},
-                # [Heatmap consistency loss]
-                # [Junction loss]
-                "w_junc": 0.0,
-                "junction_loss_func": "superpoint",
-                "junction_loss_cfg": {"policy": mode},
-                # [Descriptor loss]
-                "w_desc": 0.0,
-                "descriptor_loss_func": "regular_sampling",
-                "descriptor_loss_cfg": {
-                    "dist_threshold": 8,
-                    "grid_size": 4,
-                    "margin": 1,
-                    "policy": mode,
-                },
-            },
-            "line_detector_cfg": {
-                "detect_thresh": 0.25,  # depending on your images, you might need to tune this parameter
-                "num_samples": 64,
-                "sampling_method": "local_max",
-                "inlier_thresh": 0.9,
-                "use_candidate_suppression": True,
-                "nms_dist_tolerance": 3.0,
-                "use_heatmap_refinement": True,
-                "heatmap_refine_cfg": {
-                    "mode": "local",
-                    "ratio": 0.2,
-                    "valid_thresh": 1e-3,
-                    "num_blocks": 20,
-                    "overlap_ratio": 0.5,
-                },
-            },
-            "multiscale": False,
-            "line_matcher_cfg": {
-                "cross_check": True,
-                "num_samples": 5,
-                "min_dist_pts": 8,
-                "top_k_candidates": 10,
-                "grid_size": 4,
-            },
-        }
-        self.net = LineMatcher(
-            match_config["model_cfg"],
-            checkpoint_path,
-            device,
-            match_config["line_detector_cfg"],
-            match_config["line_matcher_cfg"],
-            match_config["multiscale"],
-        )
-
-    def _forward(self, data):
-        img0 = data["image0"]
-        img1 = data["image1"]
-        pred = self.net([img0, img1])
-        line_seg1 = pred["line_segments"][0]
-        line_seg2 = pred["line_segments"][1]
-        matches = pred["matches"]
-
-        valid_matches = matches != -1
-        match_indices = matches[valid_matches]
-        matched_lines1 = line_seg1[valid_matches][:, :, ::-1]
-        matched_lines2 = line_seg2[match_indices][:, :, ::-1]
-
-        pred["raw_lines0"], pred["raw_lines1"] = line_seg1, line_seg2
-        pred["lines0"], pred["lines1"] = matched_lines1, matched_lines2
-        pred = {**pred, **data}
-        return pred
diff --git a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmcv/ops/info.py b/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmcv/ops/info.py
deleted file mode 100644
index 29f2e5598ae2bb5866ccd15a7d3b4de33c0cd14d..0000000000000000000000000000000000000000
--- a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmcv/ops/info.py
+++ /dev/null
@@ -1,36 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import glob
-import os
-
-import torch
-
-if torch.__version__ == 'parrots':
-    import parrots
-
-    def get_compiler_version():
-        return 'GCC ' + parrots.version.compiler
-
-    def get_compiling_cuda_version():
-        return parrots.version.cuda
-else:
-    from ..utils import ext_loader
-    ext_module = ext_loader.load_ext(
-        '_ext', ['get_compiler_version', 'get_compiling_cuda_version'])
-
-    def get_compiler_version():
-        return ext_module.get_compiler_version()
-
-    def get_compiling_cuda_version():
-        return ext_module.get_compiling_cuda_version()
-
-
-def get_onnxruntime_op_path():
-    wildcard = os.path.join(
-        os.path.abspath(os.path.dirname(os.path.dirname(__file__))),
-        '_ext_ort.*.so')
-
-    paths = glob.glob(wildcard)
-    if len(paths) > 0:
-        return paths[0]
-    else:
-        return ''
diff --git a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmcv/ops/knn.py b/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmcv/ops/knn.py
deleted file mode 100644
index f335785036669fc19239825b0aae6dde3f73bf92..0000000000000000000000000000000000000000
--- a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmcv/ops/knn.py
+++ /dev/null
@@ -1,77 +0,0 @@
-import torch
-from torch.autograd import Function
-
-from ..utils import ext_loader
-
-ext_module = ext_loader.load_ext('_ext', ['knn_forward'])
-
-
-class KNN(Function):
-    r"""KNN (CUDA) based on heap data structure.
-    Modified from `PAConv <https://github.com/CVMI-Lab/PAConv/tree/main/
-    scene_seg/lib/pointops/src/knnquery_heap>`_.
-
-    Find k-nearest points.
-    """
-
-    @staticmethod
-    def forward(ctx,
-                k: int,
-                xyz: torch.Tensor,
-                center_xyz: torch.Tensor = None,
-                transposed: bool = False) -> torch.Tensor:
-        """
-        Args:
-            k (int): number of nearest neighbors.
-            xyz (Tensor): (B, N, 3) if transposed == False, else (B, 3, N).
-                xyz coordinates of the features.
-            center_xyz (Tensor, optional): (B, npoint, 3) if transposed ==
-                False, else (B, 3, npoint). centers of the knn query.
-                Default: None.
-            transposed (bool, optional): whether the input tensors are
-                transposed. Should not explicitly use this keyword when
-                calling knn (=KNN.apply), just add the fourth param.
-                Default: False.
-
-        Returns:
-            Tensor: (B, k, npoint) tensor with the indices of
-                the features that form k-nearest neighbours.
-        """
-        assert (k > 0) & (k < 100), 'k should be in range(0, 100)'
-
-        if center_xyz is None:
-            center_xyz = xyz
-
-        if transposed:
-            xyz = xyz.transpose(2, 1).contiguous()
-            center_xyz = center_xyz.transpose(2, 1).contiguous()
-
-        assert xyz.is_contiguous()  # [B, N, 3]
-        assert center_xyz.is_contiguous()  # [B, npoint, 3]
-
-        center_xyz_device = center_xyz.get_device()
-        assert center_xyz_device == xyz.get_device(), \
-            'center_xyz and xyz should be put on the same device'
-        if torch.cuda.current_device() != center_xyz_device:
-            torch.cuda.set_device(center_xyz_device)
-
-        B, npoint, _ = center_xyz.shape
-        N = xyz.shape[1]
-
-        idx = center_xyz.new_zeros((B, npoint, k)).int()
-        dist2 = center_xyz.new_zeros((B, npoint, k)).float()
-
-        ext_module.knn_forward(
-            xyz, center_xyz, idx, dist2, b=B, n=N, m=npoint, nsample=k)
-        # idx shape to [B, k, npoint]
-        idx = idx.transpose(2, 1).contiguous()
-        if torch.__version__ != 'parrots':
-            ctx.mark_non_differentiable(idx)
-        return idx
-
-    @staticmethod
-    def backward(ctx, a=None):
-        return None, None, None
-
-
-knn = KNN.apply
diff --git a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmcv/parallel/registry.py b/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmcv/parallel/registry.py
deleted file mode 100644
index a204a07fba10e614223f090d1a57cf9c4d74d4a1..0000000000000000000000000000000000000000
--- a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmcv/parallel/registry.py
+++ /dev/null
@@ -1,8 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-from torch.nn.parallel import DataParallel, DistributedDataParallel
-
-from annotator.uniformer.mmcv.utils import Registry
-
-MODULE_WRAPPERS = Registry('module wrapper')
-MODULE_WRAPPERS.register_module(module=DataParallel)
-MODULE_WRAPPERS.register_module(module=DistributedDataParallel)
diff --git a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmdet_null/models/roi_heads/cascade_roi_head.py b/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmdet_null/models/roi_heads/cascade_roi_head.py
deleted file mode 100644
index 45b6f36a386cd37c50cc43666fcc516f2e14d868..0000000000000000000000000000000000000000
--- a/spaces/Robert001/UniControl-Demo/annotator/uniformer/mmdet_null/models/roi_heads/cascade_roi_head.py
+++ /dev/null
@@ -1,507 +0,0 @@
-import torch
-import torch.nn as nn
-
-from mmdet.core import (bbox2result, bbox2roi, bbox_mapping, build_assigner,
-                        build_sampler, merge_aug_bboxes, merge_aug_masks,
-                        multiclass_nms)
-from ..builder import HEADS, build_head, build_roi_extractor
-from .base_roi_head import BaseRoIHead
-from .test_mixins import BBoxTestMixin, MaskTestMixin
-
-
-@HEADS.register_module()
-class CascadeRoIHead(BaseRoIHead, BBoxTestMixin, MaskTestMixin):
-    """Cascade roi head including one bbox head and one mask head.
-
-    https://arxiv.org/abs/1712.00726
-    """
-
-    def __init__(self,
-                 num_stages,
-                 stage_loss_weights,
-                 bbox_roi_extractor=None,
-                 bbox_head=None,
-                 mask_roi_extractor=None,
-                 mask_head=None,
-                 shared_head=None,
-                 train_cfg=None,
-                 test_cfg=None):
-        assert bbox_roi_extractor is not None
-        assert bbox_head is not None
-        assert shared_head is None, \
-            'Shared head is not supported in Cascade RCNN anymore'
-        self.num_stages = num_stages
-        self.stage_loss_weights = stage_loss_weights
-        super(CascadeRoIHead, self).__init__(
-            bbox_roi_extractor=bbox_roi_extractor,
-            bbox_head=bbox_head,
-            mask_roi_extractor=mask_roi_extractor,
-            mask_head=mask_head,
-            shared_head=shared_head,
-            train_cfg=train_cfg,
-            test_cfg=test_cfg)
-
-    def init_bbox_head(self, bbox_roi_extractor, bbox_head):
-        """Initialize box head and box roi extractor.
-
-        Args:
-            bbox_roi_extractor (dict): Config of box roi extractor.
-            bbox_head (dict): Config of box in box head.
-        """
-        self.bbox_roi_extractor = nn.ModuleList()
-        self.bbox_head = nn.ModuleList()
-        if not isinstance(bbox_roi_extractor, list):
-            bbox_roi_extractor = [
-                bbox_roi_extractor for _ in range(self.num_stages)
-            ]
-        if not isinstance(bbox_head, list):
-            bbox_head = [bbox_head for _ in range(self.num_stages)]
-        assert len(bbox_roi_extractor) == len(bbox_head) == self.num_stages
-        for roi_extractor, head in zip(bbox_roi_extractor, bbox_head):
-            self.bbox_roi_extractor.append(build_roi_extractor(roi_extractor))
-            self.bbox_head.append(build_head(head))
-
-    def init_mask_head(self, mask_roi_extractor, mask_head):
-        """Initialize mask head and mask roi extractor.
-
-        Args:
-            mask_roi_extractor (dict): Config of mask roi extractor.
-            mask_head (dict): Config of mask in mask head.
-        """
-        self.mask_head = nn.ModuleList()
-        if not isinstance(mask_head, list):
-            mask_head = [mask_head for _ in range(self.num_stages)]
-        assert len(mask_head) == self.num_stages
-        for head in mask_head:
-            self.mask_head.append(build_head(head))
-        if mask_roi_extractor is not None:
-            self.share_roi_extractor = False
-            self.mask_roi_extractor = nn.ModuleList()
-            if not isinstance(mask_roi_extractor, list):
-                mask_roi_extractor = [
-                    mask_roi_extractor for _ in range(self.num_stages)
-                ]
-            assert len(mask_roi_extractor) == self.num_stages
-            for roi_extractor in mask_roi_extractor:
-                self.mask_roi_extractor.append(
-                    build_roi_extractor(roi_extractor))
-        else:
-            self.share_roi_extractor = True
-            self.mask_roi_extractor = self.bbox_roi_extractor
-
-    def init_assigner_sampler(self):
-        """Initialize assigner and sampler for each stage."""
-        self.bbox_assigner = []
-        self.bbox_sampler = []
-        if self.train_cfg is not None:
-            for idx, rcnn_train_cfg in enumerate(self.train_cfg):
-                self.bbox_assigner.append(
-                    build_assigner(rcnn_train_cfg.assigner))
-                self.current_stage = idx
-                self.bbox_sampler.append(
-                    build_sampler(rcnn_train_cfg.sampler, context=self))
-
-    def init_weights(self, pretrained):
-        """Initialize the weights in head.
-
-        Args:
-            pretrained (str, optional): Path to pre-trained weights.
-                Defaults to None.
-        """
-        if self.with_shared_head:
-            self.shared_head.init_weights(pretrained=pretrained)
-        for i in range(self.num_stages):
-            if self.with_bbox:
-                self.bbox_roi_extractor[i].init_weights()
-                self.bbox_head[i].init_weights()
-            if self.with_mask:
-                if not self.share_roi_extractor:
-                    self.mask_roi_extractor[i].init_weights()
-                self.mask_head[i].init_weights()
-
-    def forward_dummy(self, x, proposals):
-        """Dummy forward function."""
-        # bbox head
-        outs = ()
-        rois = bbox2roi([proposals])
-        if self.with_bbox:
-            for i in range(self.num_stages):
-                bbox_results = self._bbox_forward(i, x, rois)
-                outs = outs + (bbox_results['cls_score'],
-                               bbox_results['bbox_pred'])
-        # mask heads
-        if self.with_mask:
-            mask_rois = rois[:100]
-            for i in range(self.num_stages):
-                mask_results = self._mask_forward(i, x, mask_rois)
-                outs = outs + (mask_results['mask_pred'], )
-        return outs
-
-    def _bbox_forward(self, stage, x, rois):
-        """Box head forward function used in both training and testing."""
-        bbox_roi_extractor = self.bbox_roi_extractor[stage]
-        bbox_head = self.bbox_head[stage]
-        bbox_feats = bbox_roi_extractor(x[:bbox_roi_extractor.num_inputs],
-                                        rois)
-        # do not support caffe_c4 model anymore
-        cls_score, bbox_pred = bbox_head(bbox_feats)
-
-        bbox_results = dict(
-            cls_score=cls_score, bbox_pred=bbox_pred, bbox_feats=bbox_feats)
-        return bbox_results
-
-    def _bbox_forward_train(self, stage, x, sampling_results, gt_bboxes,
-                            gt_labels, rcnn_train_cfg):
-        """Run forward function and calculate loss for box head in training."""
-        rois = bbox2roi([res.bboxes for res in sampling_results])
-        bbox_results = self._bbox_forward(stage, x, rois)
-        bbox_targets = self.bbox_head[stage].get_targets(
-            sampling_results, gt_bboxes, gt_labels, rcnn_train_cfg)
-        loss_bbox = self.bbox_head[stage].loss(bbox_results['cls_score'],
-                                               bbox_results['bbox_pred'], rois,
-                                               *bbox_targets)
-
-        bbox_results.update(
-            loss_bbox=loss_bbox, rois=rois, bbox_targets=bbox_targets)
-        return bbox_results
-
-    def _mask_forward(self, stage, x, rois):
-        """Mask head forward function used in both training and testing."""
-        mask_roi_extractor = self.mask_roi_extractor[stage]
-        mask_head = self.mask_head[stage]
-        mask_feats = mask_roi_extractor(x[:mask_roi_extractor.num_inputs],
-                                        rois)
-        # do not support caffe_c4 model anymore
-        mask_pred = mask_head(mask_feats)
-
-        mask_results = dict(mask_pred=mask_pred)
-        return mask_results
-
-    def _mask_forward_train(self,
-                            stage,
-                            x,
-                            sampling_results,
-                            gt_masks,
-                            rcnn_train_cfg,
-                            bbox_feats=None):
-        """Run forward function and calculate loss for mask head in
-        training."""
-        pos_rois = bbox2roi([res.pos_bboxes for res in sampling_results])
-        mask_results = self._mask_forward(stage, x, pos_rois)
-
-        mask_targets = self.mask_head[stage].get_targets(
-            sampling_results, gt_masks, rcnn_train_cfg)
-        pos_labels = torch.cat([res.pos_gt_labels for res in sampling_results])
-        loss_mask = self.mask_head[stage].loss(mask_results['mask_pred'],
-                                               mask_targets, pos_labels)
-
-        mask_results.update(loss_mask=loss_mask)
-        return mask_results
-
-    def forward_train(self,
-                      x,
-                      img_metas,
-                      proposal_list,
-                      gt_bboxes,
-                      gt_labels,
-                      gt_bboxes_ignore=None,
-                      gt_masks=None):
-        """
-        Args:
-            x (list[Tensor]): list of multi-level img features.
-            img_metas (list[dict]): list of image info dict where each dict
-                has: 'img_shape', 'scale_factor', 'flip', and may also contain
-                'filename', 'ori_shape', 'pad_shape', and 'img_norm_cfg'.
-                For details on the values of these keys see
-                `mmdet/datasets/pipelines/formatting.py:Collect`.
-            proposals (list[Tensors]): list of region proposals.
-            gt_bboxes (list[Tensor]): Ground truth bboxes for each image with
-                shape (num_gts, 4) in [tl_x, tl_y, br_x, br_y] format.
-            gt_labels (list[Tensor]): class indices corresponding to each box
-            gt_bboxes_ignore (None | list[Tensor]): specify which bounding
-                boxes can be ignored when computing the loss.
-            gt_masks (None | Tensor) : true segmentation masks for each box
-                used if the architecture supports a segmentation task.
-
-        Returns:
-            dict[str, Tensor]: a dictionary of loss components
-        """
-        losses = dict()
-        for i in range(self.num_stages):
-            self.current_stage = i
-            rcnn_train_cfg = self.train_cfg[i]
-            lw = self.stage_loss_weights[i]
-
-            # assign gts and sample proposals
-            sampling_results = []
-            if self.with_bbox or self.with_mask:
-                bbox_assigner = self.bbox_assigner[i]
-                bbox_sampler = self.bbox_sampler[i]
-                num_imgs = len(img_metas)
-                if gt_bboxes_ignore is None:
-                    gt_bboxes_ignore = [None for _ in range(num_imgs)]
-
-                for j in range(num_imgs):
-                    assign_result = bbox_assigner.assign(
-                        proposal_list[j], gt_bboxes[j], gt_bboxes_ignore[j],
-                        gt_labels[j])
-                    sampling_result = bbox_sampler.sample(
-                        assign_result,
-                        proposal_list[j],
-                        gt_bboxes[j],
-                        gt_labels[j],
-                        feats=[lvl_feat[j][None] for lvl_feat in x])
-                    sampling_results.append(sampling_result)
-
-            # bbox head forward and loss
-            bbox_results = self._bbox_forward_train(i, x, sampling_results,
-                                                    gt_bboxes, gt_labels,
-                                                    rcnn_train_cfg)
-
-            for name, value in bbox_results['loss_bbox'].items():
-                losses[f's{i}.{name}'] = (
-                    value * lw if 'loss' in name else value)
-
-            # mask head forward and loss
-            if self.with_mask:
-                mask_results = self._mask_forward_train(
-                    i, x, sampling_results, gt_masks, rcnn_train_cfg,
-                    bbox_results['bbox_feats'])
-                for name, value in mask_results['loss_mask'].items():
-                    losses[f's{i}.{name}'] = (
-                        value * lw if 'loss' in name else value)
-
-            # refine bboxes
-            if i < self.num_stages - 1:
-                pos_is_gts = [res.pos_is_gt for res in sampling_results]
-                # bbox_targets is a tuple
-                roi_labels = bbox_results['bbox_targets'][0]
-                with torch.no_grad():
-                    roi_labels = torch.where(
-                        roi_labels == self.bbox_head[i].num_classes,
-                        bbox_results['cls_score'][:, :-1].argmax(1),
-                        roi_labels)
-                    proposal_list = self.bbox_head[i].refine_bboxes(
-                        bbox_results['rois'], roi_labels,
-                        bbox_results['bbox_pred'], pos_is_gts, img_metas)
-
-        return losses
-
-    def simple_test(self, x, proposal_list, img_metas, rescale=False):
-        """Test without augmentation."""
-        assert self.with_bbox, 'Bbox head must be implemented.'
-        num_imgs = len(proposal_list)
-        img_shapes = tuple(meta['img_shape'] for meta in img_metas)
-        ori_shapes = tuple(meta['ori_shape'] for meta in img_metas)
-        scale_factors = tuple(meta['scale_factor'] for meta in img_metas)
-
-        # "ms" in variable names means multi-stage
-        ms_bbox_result = {}
-        ms_segm_result = {}
-        ms_scores = []
-        rcnn_test_cfg = self.test_cfg
-
-        rois = bbox2roi(proposal_list)
-        for i in range(self.num_stages):
-            bbox_results = self._bbox_forward(i, x, rois)
-
-            # split batch bbox prediction back to each image
-            cls_score = bbox_results['cls_score']
-            bbox_pred = bbox_results['bbox_pred']
-            num_proposals_per_img = tuple(
-                len(proposals) for proposals in proposal_list)
-            rois = rois.split(num_proposals_per_img, 0)
-            cls_score = cls_score.split(num_proposals_per_img, 0)
-            if isinstance(bbox_pred, torch.Tensor):
-                bbox_pred = bbox_pred.split(num_proposals_per_img, 0)
-            else:
-                bbox_pred = self.bbox_head[i].bbox_pred_split(
-                    bbox_pred, num_proposals_per_img)
-            ms_scores.append(cls_score)
-
-            if i < self.num_stages - 1:
-                bbox_label = [s[:, :-1].argmax(dim=1) for s in cls_score]
-                rois = torch.cat([
-                    self.bbox_head[i].regress_by_class(rois[j], bbox_label[j],
-                                                       bbox_pred[j],
-                                                       img_metas[j])
-                    for j in range(num_imgs)
-                ])
-
-        # average scores of each image by stages
-        cls_score = [
-            sum([score[i] for score in ms_scores]) / float(len(ms_scores))
-            for i in range(num_imgs)
-        ]
-
-        # apply bbox post-processing to each image individually
-        det_bboxes = []
-        det_labels = []
-        for i in range(num_imgs):
-            det_bbox, det_label = self.bbox_head[-1].get_bboxes(
-                rois[i],
-                cls_score[i],
-                bbox_pred[i],
-                img_shapes[i],
-                scale_factors[i],
-                rescale=rescale,
-                cfg=rcnn_test_cfg)
-            det_bboxes.append(det_bbox)
-            det_labels.append(det_label)
-
-        if torch.onnx.is_in_onnx_export():
-            return det_bboxes, det_labels
-        bbox_results = [
-            bbox2result(det_bboxes[i], det_labels[i],
-                        self.bbox_head[-1].num_classes)
-            for i in range(num_imgs)
-        ]
-        ms_bbox_result['ensemble'] = bbox_results
-
-        if self.with_mask:
-            if all(det_bbox.shape[0] == 0 for det_bbox in det_bboxes):
-                mask_classes = self.mask_head[-1].num_classes
-                segm_results = [[[] for _ in range(mask_classes)]
-                                for _ in range(num_imgs)]
-            else:
-                if rescale and not isinstance(scale_factors[0], float):
-                    scale_factors = [
-                        torch.from_numpy(scale_factor).to(det_bboxes[0].device)
-                        for scale_factor in scale_factors
-                    ]
-                _bboxes = [
-                    det_bboxes[i][:, :4] *
-                    scale_factors[i] if rescale else det_bboxes[i][:, :4]
-                    for i in range(len(det_bboxes))
-                ]
-                mask_rois = bbox2roi(_bboxes)
-                num_mask_rois_per_img = tuple(
-                    _bbox.size(0) for _bbox in _bboxes)
-                aug_masks = []
-                for i in range(self.num_stages):
-                    mask_results = self._mask_forward(i, x, mask_rois)
-                    mask_pred = mask_results['mask_pred']
-                    # split batch mask prediction back to each image
-                    mask_pred = mask_pred.split(num_mask_rois_per_img, 0)
-                    aug_masks.append(
-                        [m.sigmoid().cpu().numpy() for m in mask_pred])
-
-                # apply mask post-processing to each image individually
-                segm_results = []
-                for i in range(num_imgs):
-                    if det_bboxes[i].shape[0] == 0:
-                        segm_results.append(
-                            [[]
-                             for _ in range(self.mask_head[-1].num_classes)])
-                    else:
-                        aug_mask = [mask[i] for mask in aug_masks]
-                        merged_masks = merge_aug_masks(
-                            aug_mask, [[img_metas[i]]] * self.num_stages,
-                            rcnn_test_cfg)
-                        segm_result = self.mask_head[-1].get_seg_masks(
-                            merged_masks, _bboxes[i], det_labels[i],
-                            rcnn_test_cfg, ori_shapes[i], scale_factors[i],
-                            rescale)
-                        segm_results.append(segm_result)
-            ms_segm_result['ensemble'] = segm_results
-
-        if self.with_mask:
-            results = list(
-                zip(ms_bbox_result['ensemble'], ms_segm_result['ensemble']))
-        else:
-            results = ms_bbox_result['ensemble']
-
-        return results
-
-    def aug_test(self, features, proposal_list, img_metas, rescale=False):
-        """Test with augmentations.
-
-        If rescale is False, then returned bboxes and masks will fit the scale
-        of imgs[0].
-        """
-        rcnn_test_cfg = self.test_cfg
-        aug_bboxes = []
-        aug_scores = []
-        for x, img_meta in zip(features, img_metas):
-            # only one image in the batch
-            img_shape = img_meta[0]['img_shape']
-            scale_factor = img_meta[0]['scale_factor']
-            flip = img_meta[0]['flip']
-            flip_direction = img_meta[0]['flip_direction']
-
-            proposals = bbox_mapping(proposal_list[0][:, :4], img_shape,
-                                     scale_factor, flip, flip_direction)
-            # "ms" in variable names means multi-stage
-            ms_scores = []
-
-            rois = bbox2roi([proposals])
-            for i in range(self.num_stages):
-                bbox_results = self._bbox_forward(i, x, rois)
-                ms_scores.append(bbox_results['cls_score'])
-
-                if i < self.num_stages - 1:
-                    bbox_label = bbox_results['cls_score'][:, :-1].argmax(
-                        dim=1)
-                    rois = self.bbox_head[i].regress_by_class(
-                        rois, bbox_label, bbox_results['bbox_pred'],
-                        img_meta[0])
-
-            cls_score = sum(ms_scores) / float(len(ms_scores))
-            bboxes, scores = self.bbox_head[-1].get_bboxes(
-                rois,
-                cls_score,
-                bbox_results['bbox_pred'],
-                img_shape,
-                scale_factor,
-                rescale=False,
-                cfg=None)
-            aug_bboxes.append(bboxes)
-            aug_scores.append(scores)
-
-        # after merging, bboxes will be rescaled to the original image size
-        merged_bboxes, merged_scores = merge_aug_bboxes(
-            aug_bboxes, aug_scores, img_metas, rcnn_test_cfg)
-        det_bboxes, det_labels = multiclass_nms(merged_bboxes, merged_scores,
-                                                rcnn_test_cfg.score_thr,
-                                                rcnn_test_cfg.nms,
-                                                rcnn_test_cfg.max_per_img)
-
-        bbox_result = bbox2result(det_bboxes, det_labels,
-                                  self.bbox_head[-1].num_classes)
-
-        if self.with_mask:
-            if det_bboxes.shape[0] == 0:
-                segm_result = [[[]
-                                for _ in range(self.mask_head[-1].num_classes)]
-                               ]
-            else:
-                aug_masks = []
-                aug_img_metas = []
-                for x, img_meta in zip(features, img_metas):
-                    img_shape = img_meta[0]['img_shape']
-                    scale_factor = img_meta[0]['scale_factor']
-                    flip = img_meta[0]['flip']
-                    flip_direction = img_meta[0]['flip_direction']
-                    _bboxes = bbox_mapping(det_bboxes[:, :4], img_shape,
-                                           scale_factor, flip, flip_direction)
-                    mask_rois = bbox2roi([_bboxes])
-                    for i in range(self.num_stages):
-                        mask_results = self._mask_forward(i, x, mask_rois)
-                        aug_masks.append(
-                            mask_results['mask_pred'].sigmoid().cpu().numpy())
-                        aug_img_metas.append(img_meta)
-                merged_masks = merge_aug_masks(aug_masks, aug_img_metas,
-                                               self.test_cfg)
-
-                ori_shape = img_metas[0][0]['ori_shape']
-                segm_result = self.mask_head[-1].get_seg_masks(
-                    merged_masks,
-                    det_bboxes,
-                    det_labels,
-                    rcnn_test_cfg,
-                    ori_shape,
-                    scale_factor=1.0,
-                    rescale=False)
-            return [(bbox_result, segm_result)]
-        else:
-            return [bbox_result]
diff --git a/spaces/Rothfeld/stable-diffusion-mat-outpainting-primer/torch_utils/ops/upfirdn2d.py b/spaces/Rothfeld/stable-diffusion-mat-outpainting-primer/torch_utils/ops/upfirdn2d.py
deleted file mode 100644
index ceeac2b9834e33b7c601c28bf27f32aa91c69256..0000000000000000000000000000000000000000
--- a/spaces/Rothfeld/stable-diffusion-mat-outpainting-primer/torch_utils/ops/upfirdn2d.py
+++ /dev/null
@@ -1,384 +0,0 @@
-# Copyright (c) 2021, NVIDIA CORPORATION.  All rights reserved.
-#
-# NVIDIA CORPORATION and its licensors retain all intellectual property
-# and proprietary rights in and to this software, related documentation
-# and any modifications thereto.  Any use, reproduction, disclosure or
-# distribution of this software and related documentation without an express
-# license agreement from NVIDIA CORPORATION is strictly prohibited.
-
-"""Custom PyTorch ops for efficient resampling of 2D images."""
-
-import os
-import warnings
-import numpy as np
-import torch
-import traceback
-
-from .. import custom_ops
-from .. import misc
-from . import conv2d_gradfix
-
-#----------------------------------------------------------------------------
-
-_inited = False
-_plugin = None
-
-def _init():
-    global _inited, _plugin
-    if not _inited:
-        sources = ['upfirdn2d.cpp', 'upfirdn2d.cu']
-        sources = [os.path.join(os.path.dirname(__file__), s) for s in sources]
-        try:
-            _plugin = custom_ops.get_plugin('upfirdn2d_plugin', sources=sources, extra_cuda_cflags=['--use_fast_math'])
-        except:
-            warnings.warn('Failed to build CUDA kernels for upfirdn2d. Falling back to slow reference implementation. Details:\n\n' + traceback.format_exc())
-    return _plugin is not None
-
-def _parse_scaling(scaling):
-    if isinstance(scaling, int):
-        scaling = [scaling, scaling]
-    assert isinstance(scaling, (list, tuple))
-    assert all(isinstance(x, int) for x in scaling)
-    sx, sy = scaling
-    assert sx >= 1 and sy >= 1
-    return sx, sy
-
-def _parse_padding(padding):
-    if isinstance(padding, int):
-        padding = [padding, padding]
-    assert isinstance(padding, (list, tuple))
-    assert all(isinstance(x, int) for x in padding)
-    if len(padding) == 2:
-        padx, pady = padding
-        padding = [padx, padx, pady, pady]
-    padx0, padx1, pady0, pady1 = padding
-    return padx0, padx1, pady0, pady1
-
-def _get_filter_size(f):
-    if f is None:
-        return 1, 1
-    assert isinstance(f, torch.Tensor) and f.ndim in [1, 2]
-    fw = f.shape[-1]
-    fh = f.shape[0]
-    with misc.suppress_tracer_warnings():
-        fw = int(fw)
-        fh = int(fh)
-    misc.assert_shape(f, [fh, fw][:f.ndim])
-    assert fw >= 1 and fh >= 1
-    return fw, fh
-
-#----------------------------------------------------------------------------
-
-def setup_filter(f, device=torch.device('cpu'), normalize=True, flip_filter=False, gain=1, separable=None):
-    r"""Convenience function to setup 2D FIR filter for `upfirdn2d()`.
-
-    Args:
-        f:           Torch tensor, numpy array, or python list of the shape
-                     `[filter_height, filter_width]` (non-separable),
-                     `[filter_taps]` (separable),
-                     `[]` (impulse), or
-                     `None` (identity).
-        device:      Result device (default: cpu).
-        normalize:   Normalize the filter so that it retains the magnitude
-                     for constant input signal (DC)? (default: True).
-        flip_filter: Flip the filter? (default: False).
-        gain:        Overall scaling factor for signal magnitude (default: 1).
-        separable:   Return a separable filter? (default: select automatically).
-
-    Returns:
-        Float32 tensor of the shape
-        `[filter_height, filter_width]` (non-separable) or
-        `[filter_taps]` (separable).
-    """
-    # Validate.
-    if f is None:
-        f = 1
-    f = torch.as_tensor(f, dtype=torch.float32)
-    assert f.ndim in [0, 1, 2]
-    assert f.numel() > 0
-    if f.ndim == 0:
-        f = f[np.newaxis]
-
-    # Separable?
-    if separable is None:
-        separable = (f.ndim == 1 and f.numel() >= 8)
-    if f.ndim == 1 and not separable:
-        f = f.ger(f)
-    assert f.ndim == (1 if separable else 2)
-
-    # Apply normalize, flip, gain, and device.
-    if normalize:
-        f /= f.sum()
-    if flip_filter:
-        f = f.flip(list(range(f.ndim)))
-    f = f * (gain ** (f.ndim / 2))
-    f = f.to(device=device)
-    return f
-
-#----------------------------------------------------------------------------
-
-def upfirdn2d(x, f, up=1, down=1, padding=0, flip_filter=False, gain=1, impl='cuda'):
-    r"""Pad, upsample, filter, and downsample a batch of 2D images.
-
-    Performs the following sequence of operations for each channel:
-
-    1. Upsample the image by inserting N-1 zeros after each pixel (`up`).
-
-    2. Pad the image with the specified number of zeros on each side (`padding`).
-       Negative padding corresponds to cropping the image.
-
-    3. Convolve the image with the specified 2D FIR filter (`f`), shrinking it
-       so that the footprint of all output pixels lies within the input image.
-
-    4. Downsample the image by keeping every Nth pixel (`down`).
-
-    This sequence of operations bears close resemblance to scipy.signal.upfirdn().
-    The fused op is considerably more efficient than performing the same calculation
-    using standard PyTorch ops. It supports gradients of arbitrary order.
-
-    Args:
-        x:           Float32/float64/float16 input tensor of the shape
-                     `[batch_size, num_channels, in_height, in_width]`.
-        f:           Float32 FIR filter of the shape
-                     `[filter_height, filter_width]` (non-separable),
-                     `[filter_taps]` (separable), or
-                     `None` (identity).
-        up:          Integer upsampling factor. Can be a single int or a list/tuple
-                     `[x, y]` (default: 1).
-        down:        Integer downsampling factor. Can be a single int or a list/tuple
-                     `[x, y]` (default: 1).
-        padding:     Padding with respect to the upsampled image. Can be a single number
-                     or a list/tuple `[x, y]` or `[x_before, x_after, y_before, y_after]`
-                     (default: 0).
-        flip_filter: False = convolution, True = correlation (default: False).
-        gain:        Overall scaling factor for signal magnitude (default: 1).
-        impl:        Implementation to use. Can be `'ref'` or `'cuda'` (default: `'cuda'`).
-
-    Returns:
-        Tensor of the shape `[batch_size, num_channels, out_height, out_width]`.
-    """
-    assert isinstance(x, torch.Tensor)
-    assert impl in ['ref', 'cuda']
-    if impl == 'cuda' and x.device.type == 'cuda' and _init():
-        return _upfirdn2d_cuda(up=up, down=down, padding=padding, flip_filter=flip_filter, gain=gain).apply(x, f)
-    return _upfirdn2d_ref(x, f, up=up, down=down, padding=padding, flip_filter=flip_filter, gain=gain)
-
-#----------------------------------------------------------------------------
-
-@misc.profiled_function
-def _upfirdn2d_ref(x, f, up=1, down=1, padding=0, flip_filter=False, gain=1):
-    """Slow reference implementation of `upfirdn2d()` using standard PyTorch ops.
-    """
-    # Validate arguments.
-    assert isinstance(x, torch.Tensor) and x.ndim == 4
-    if f is None:
-        f = torch.ones([1, 1], dtype=torch.float32, device=x.device)
-    assert isinstance(f, torch.Tensor) and f.ndim in [1, 2]
-    assert f.dtype == torch.float32 and not f.requires_grad
-    batch_size, num_channels, in_height, in_width = x.shape
-    upx, upy = _parse_scaling(up)
-    downx, downy = _parse_scaling(down)
-    padx0, padx1, pady0, pady1 = _parse_padding(padding)
-
-    # Upsample by inserting zeros.
-    x = x.reshape([batch_size, num_channels, in_height, 1, in_width, 1])
-    x = torch.nn.functional.pad(x, [0, upx - 1, 0, 0, 0, upy - 1])
-    x = x.reshape([batch_size, num_channels, in_height * upy, in_width * upx])
-
-    # Pad or crop.
-    x = torch.nn.functional.pad(x, [max(padx0, 0), max(padx1, 0), max(pady0, 0), max(pady1, 0)])
-    x = x[:, :, max(-pady0, 0) : x.shape[2] - max(-pady1, 0), max(-padx0, 0) : x.shape[3] - max(-padx1, 0)]
-
-    # Setup filter.
-    f = f * (gain ** (f.ndim / 2))
-    f = f.to(x.dtype)
-    if not flip_filter:
-        f = f.flip(list(range(f.ndim)))
-
-    # Convolve with the filter.
-    f = f[np.newaxis, np.newaxis].repeat([num_channels, 1] + [1] * f.ndim)
-    if f.ndim == 4:
-        x = conv2d_gradfix.conv2d(input=x, weight=f, groups=num_channels)
-    else:
-        x = conv2d_gradfix.conv2d(input=x, weight=f.unsqueeze(2), groups=num_channels)
-        x = conv2d_gradfix.conv2d(input=x, weight=f.unsqueeze(3), groups=num_channels)
-
-    # Downsample by throwing away pixels.
-    x = x[:, :, ::downy, ::downx]
-    return x
-
-#----------------------------------------------------------------------------
-
-_upfirdn2d_cuda_cache = dict()
-
-def _upfirdn2d_cuda(up=1, down=1, padding=0, flip_filter=False, gain=1):
-    """Fast CUDA implementation of `upfirdn2d()` using custom ops.
-    """
-    # Parse arguments.
-    upx, upy = _parse_scaling(up)
-    downx, downy = _parse_scaling(down)
-    padx0, padx1, pady0, pady1 = _parse_padding(padding)
-
-    # Lookup from cache.
-    key = (upx, upy, downx, downy, padx0, padx1, pady0, pady1, flip_filter, gain)
-    if key in _upfirdn2d_cuda_cache:
-        return _upfirdn2d_cuda_cache[key]
-
-    # Forward op.
-    class Upfirdn2dCuda(torch.autograd.Function):
-        @staticmethod
-        def forward(ctx, x, f): # pylint: disable=arguments-differ
-            assert isinstance(x, torch.Tensor) and x.ndim == 4
-            if f is None:
-                f = torch.ones([1, 1], dtype=torch.float32, device=x.device)
-            assert isinstance(f, torch.Tensor) and f.ndim in [1, 2]
-            y = x
-            if f.ndim == 2:
-                y = _plugin.upfirdn2d(y, f, upx, upy, downx, downy, padx0, padx1, pady0, pady1, flip_filter, gain)
-            else:
-                y = _plugin.upfirdn2d(y, f.unsqueeze(0), upx, 1, downx, 1, padx0, padx1, 0, 0, flip_filter, np.sqrt(gain))
-                y = _plugin.upfirdn2d(y, f.unsqueeze(1), 1, upy, 1, downy, 0, 0, pady0, pady1, flip_filter, np.sqrt(gain))
-            ctx.save_for_backward(f)
-            ctx.x_shape = x.shape
-            return y
-
-        @staticmethod
-        def backward(ctx, dy): # pylint: disable=arguments-differ
-            f, = ctx.saved_tensors
-            _, _, ih, iw = ctx.x_shape
-            _, _, oh, ow = dy.shape
-            fw, fh = _get_filter_size(f)
-            p = [
-                fw - padx0 - 1,
-                iw * upx - ow * downx + padx0 - upx + 1,
-                fh - pady0 - 1,
-                ih * upy - oh * downy + pady0 - upy + 1,
-            ]
-            dx = None
-            df = None
-
-            if ctx.needs_input_grad[0]:
-                dx = _upfirdn2d_cuda(up=down, down=up, padding=p, flip_filter=(not flip_filter), gain=gain).apply(dy, f)
-
-            assert not ctx.needs_input_grad[1]
-            return dx, df
-
-    # Add to cache.
-    _upfirdn2d_cuda_cache[key] = Upfirdn2dCuda
-    return Upfirdn2dCuda
-
-#----------------------------------------------------------------------------
-
-def filter2d(x, f, padding=0, flip_filter=False, gain=1, impl='cuda'):
-    r"""Filter a batch of 2D images using the given 2D FIR filter.
-
-    By default, the result is padded so that its shape matches the input.
-    User-specified padding is applied on top of that, with negative values
-    indicating cropping. Pixels outside the image are assumed to be zero.
-
-    Args:
-        x:           Float32/float64/float16 input tensor of the shape
-                     `[batch_size, num_channels, in_height, in_width]`.
-        f:           Float32 FIR filter of the shape
-                     `[filter_height, filter_width]` (non-separable),
-                     `[filter_taps]` (separable), or
-                     `None` (identity).
-        padding:     Padding with respect to the output. Can be a single number or a
-                     list/tuple `[x, y]` or `[x_before, x_after, y_before, y_after]`
-                     (default: 0).
-        flip_filter: False = convolution, True = correlation (default: False).
-        gain:        Overall scaling factor for signal magnitude (default: 1).
-        impl:        Implementation to use. Can be `'ref'` or `'cuda'` (default: `'cuda'`).
-
-    Returns:
-        Tensor of the shape `[batch_size, num_channels, out_height, out_width]`.
-    """
-    padx0, padx1, pady0, pady1 = _parse_padding(padding)
-    fw, fh = _get_filter_size(f)
-    p = [
-        padx0 + fw // 2,
-        padx1 + (fw - 1) // 2,
-        pady0 + fh // 2,
-        pady1 + (fh - 1) // 2,
-    ]
-    return upfirdn2d(x, f, padding=p, flip_filter=flip_filter, gain=gain, impl=impl)
-
-#----------------------------------------------------------------------------
-
-def upsample2d(x, f, up=2, padding=0, flip_filter=False, gain=1, impl='cuda'):
-    r"""Upsample a batch of 2D images using the given 2D FIR filter.
-
-    By default, the result is padded so that its shape is a multiple of the input.
-    User-specified padding is applied on top of that, with negative values
-    indicating cropping. Pixels outside the image are assumed to be zero.
-
-    Args:
-        x:           Float32/float64/float16 input tensor of the shape
-                     `[batch_size, num_channels, in_height, in_width]`.
-        f:           Float32 FIR filter of the shape
-                     `[filter_height, filter_width]` (non-separable),
-                     `[filter_taps]` (separable), or
-                     `None` (identity).
-        up:          Integer upsampling factor. Can be a single int or a list/tuple
-                     `[x, y]` (default: 1).
-        padding:     Padding with respect to the output. Can be a single number or a
-                     list/tuple `[x, y]` or `[x_before, x_after, y_before, y_after]`
-                     (default: 0).
-        flip_filter: False = convolution, True = correlation (default: False).
-        gain:        Overall scaling factor for signal magnitude (default: 1).
-        impl:        Implementation to use. Can be `'ref'` or `'cuda'` (default: `'cuda'`).
-
-    Returns:
-        Tensor of the shape `[batch_size, num_channels, out_height, out_width]`.
-    """
-    upx, upy = _parse_scaling(up)
-    padx0, padx1, pady0, pady1 = _parse_padding(padding)
-    fw, fh = _get_filter_size(f)
-    p = [
-        padx0 + (fw + upx - 1) // 2,
-        padx1 + (fw - upx) // 2,
-        pady0 + (fh + upy - 1) // 2,
-        pady1 + (fh - upy) // 2,
-    ]
-    return upfirdn2d(x, f, up=up, padding=p, flip_filter=flip_filter, gain=gain*upx*upy, impl=impl)
-
-#----------------------------------------------------------------------------
-
-def downsample2d(x, f, down=2, padding=0, flip_filter=False, gain=1, impl='cuda'):
-    r"""Downsample a batch of 2D images using the given 2D FIR filter.
-
-    By default, the result is padded so that its shape is a fraction of the input.
-    User-specified padding is applied on top of that, with negative values
-    indicating cropping. Pixels outside the image are assumed to be zero.
-
-    Args:
-        x:           Float32/float64/float16 input tensor of the shape
-                     `[batch_size, num_channels, in_height, in_width]`.
-        f:           Float32 FIR filter of the shape
-                     `[filter_height, filter_width]` (non-separable),
-                     `[filter_taps]` (separable), or
-                     `None` (identity).
-        down:        Integer downsampling factor. Can be a single int or a list/tuple
-                     `[x, y]` (default: 1).
-        padding:     Padding with respect to the input. Can be a single number or a
-                     list/tuple `[x, y]` or `[x_before, x_after, y_before, y_after]`
-                     (default: 0).
-        flip_filter: False = convolution, True = correlation (default: False).
-        gain:        Overall scaling factor for signal magnitude (default: 1).
-        impl:        Implementation to use. Can be `'ref'` or `'cuda'` (default: `'cuda'`).
-
-    Returns:
-        Tensor of the shape `[batch_size, num_channels, out_height, out_width]`.
-    """
-    downx, downy = _parse_scaling(down)
-    padx0, padx1, pady0, pady1 = _parse_padding(padding)
-    fw, fh = _get_filter_size(f)
-    p = [
-        padx0 + (fw - downx + 1) // 2,
-        padx1 + (fw - downx) // 2,
-        pady0 + (fh - downy + 1) // 2,
-        pady1 + (fh - downy) // 2,
-    ]
-    return upfirdn2d(x, f, down=down, padding=p, flip_filter=flip_filter, gain=gain, impl=impl)
-
-#----------------------------------------------------------------------------
diff --git a/spaces/SIH/geodata-harvester-app/README.md b/spaces/SIH/geodata-harvester-app/README.md
deleted file mode 100644
index ef23fecc73f19e6b16b3cb6ed1f6007d9ac95056..0000000000000000000000000000000000000000
--- a/spaces/SIH/geodata-harvester-app/README.md
+++ /dev/null
@@ -1,33 +0,0 @@
----
-title: Geodata Harvester App
-emoji: 📉
-colorFrom: purple
-colorTo: green
-sdk: streamlit
-sdk_version: 1.21.0
-app_file: app.py
-pinned: false
-license: lgpl-3.0
-duplicated_from: sebsigma/geodata-harvester-app
----
-
-# Geodata-Harvester App
-
-This is a streamlit webapp for the Geodata-Harvester to jumpstart geospatial analysis.
-
-The Data Harvester provides an automatic geodata extraction and processing pipeline:
-
-1. Retrieve: given set of locations, automatically access and download multiple data sources (APIs) from a diverse range of geospatial and soil data sources
-2. Process: Spatial and temporal processing, conversion to dataframes and custom raster-files
-3. Output: Ready-made dataset for machine learning (training set and prediction mapping)
-
-
-For more details about the Geodata-Harvester, please see the [Project Page](https://sydney-informatics-hub.github.io/geodata-harvester/).
-
-## More information:
-- [Overview of Data Sources](https://github.com/Sydney-Informatics-Hub/geodata-harvester/blob/main/quarto/docs/Data_Overview.md)
-- [Settings Overview](https://github.com/Sydney-Informatics-Hub/geodata-harvester/blob/main/quarto/docs/Settings_Overview.md)
-- [Python Package](https://github.com/Sydney-Informatics-Hub/geodata-harvester)
-- [R Package](https://github.com/Sydney-Informatics-Hub/dataharvester)
-
-Author: Seb Haan
\ No newline at end of file
diff --git a/spaces/Salesforce/EDICT/my_diffusers/dependency_versions_table.py b/spaces/Salesforce/EDICT/my_diffusers/dependency_versions_table.py
deleted file mode 100644
index 74c5331e5af63fbab6e583da377c811e00791391..0000000000000000000000000000000000000000
--- a/spaces/Salesforce/EDICT/my_diffusers/dependency_versions_table.py
+++ /dev/null
@@ -1,26 +0,0 @@
-# THIS FILE HAS BEEN AUTOGENERATED. To update:
-# 1. modify the `_deps` dict in setup.py
-# 2. run `make deps_table_update``
-deps = {
-    "Pillow": "Pillow",
-    "accelerate": "accelerate>=0.11.0",
-    "black": "black==22.3",
-    "datasets": "datasets",
-    "filelock": "filelock",
-    "flake8": "flake8>=3.8.3",
-    "hf-doc-builder": "hf-doc-builder>=0.3.0",
-    "huggingface-hub": "huggingface-hub>=0.8.1",
-    "importlib_metadata": "importlib_metadata",
-    "isort": "isort>=5.5.4",
-    "modelcards": "modelcards==0.1.4",
-    "numpy": "numpy",
-    "pytest": "pytest",
-    "pytest-timeout": "pytest-timeout",
-    "pytest-xdist": "pytest-xdist",
-    "scipy": "scipy",
-    "regex": "regex!=2019.12.17",
-    "requests": "requests",
-    "tensorboard": "tensorboard",
-    "torch": "torch>=1.4",
-    "transformers": "transformers>=4.21.0",
-}
diff --git a/spaces/Salesforce/EDICT/my_diffusers/pipelines/latent_diffusion/__init__.py b/spaces/Salesforce/EDICT/my_diffusers/pipelines/latent_diffusion/__init__.py
deleted file mode 100644
index c481b38cf5e0a1c4e24f7e0edf944efb68e1f979..0000000000000000000000000000000000000000
--- a/spaces/Salesforce/EDICT/my_diffusers/pipelines/latent_diffusion/__init__.py
+++ /dev/null
@@ -1,6 +0,0 @@
-# flake8: noqa
-from ...utils import is_transformers_available
-
-
-if is_transformers_available():
-    from .pipeline_latent_diffusion import LDMBertModel, LDMTextToImagePipeline
diff --git a/spaces/Shocky/Pink-Anime/README.md b/spaces/Shocky/Pink-Anime/README.md
deleted file mode 100644
index 48702a42d2f33bb76c7d3864d9e6053e2469a19b..0000000000000000000000000000000000000000
--- a/spaces/Shocky/Pink-Anime/README.md
+++ /dev/null
@@ -1,11 +0,0 @@
----
-title: Webui-Cpu-Publictest-AnimemodelsV2-Plus-OrangeMixs-Embed
-emoji: 🌍
-colorFrom: purple
-colorTo: purple
-sdk: gradio
-sdk_version: 3.9
-app_file: app.py
-pinned: true
-duplicated_from: Rifd/ngees_doang
----
diff --git a/spaces/ShreyashS/NLP-Sentiment_Analysis/README.md b/spaces/ShreyashS/NLP-Sentiment_Analysis/README.md
deleted file mode 100644
index 180aec7704823ab1d483acce5aa9e4f2d5605b5e..0000000000000000000000000000000000000000
--- a/spaces/ShreyashS/NLP-Sentiment_Analysis/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: NLP-Sentiment Analysis
-emoji: 🚀
-colorFrom: blue
-colorTo: green
-sdk: streamlit
-sdk_version: 1.15.2
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/Sky5408er/anime-remove-background/app.py b/spaces/Sky5408er/anime-remove-background/app.py
deleted file mode 100644
index 230a0d5f8a3da6ab18ecb8db1cd90016a489b96a..0000000000000000000000000000000000000000
--- a/spaces/Sky5408er/anime-remove-background/app.py
+++ /dev/null
@@ -1,52 +0,0 @@
-import gradio as gr
-import huggingface_hub
-import onnxruntime as rt
-import numpy as np
-import cv2
-
-
-def get_mask(img, s=1024):
-    img = (img / 255).astype(np.float32)
-    h, w = h0, w0 = img.shape[:-1]
-    h, w = (s, int(s * w / h)) if h > w else (int(s * h / w), s)
-    ph, pw = s - h, s - w
-    img_input = np.zeros([s, s, 3], dtype=np.float32)
-    img_input[ph // 2:ph // 2 + h, pw // 2:pw // 2 + w] = cv2.resize(img, (w, h))
-    img_input = np.transpose(img_input, (2, 0, 1))
-    img_input = img_input[np.newaxis, :]
-    mask = rmbg_model.run(None, {'img': img_input})[0][0]
-    mask = np.transpose(mask, (1, 2, 0))
-    mask = mask[ph // 2:ph // 2 + h, pw // 2:pw // 2 + w]
-    mask = cv2.resize(mask, (w0, h0))[:, :, np.newaxis]
-    return mask
-
-
-def rmbg_fn(img):
-    mask = get_mask(img)
-    img = (mask * img + 255 * (1 - mask)).astype(np.uint8)
-    mask = (mask * 255).astype(np.uint8)
-    img = np.concatenate([img, mask], axis=2, dtype=np.uint8)
-    mask = mask.repeat(3, axis=2)
-    return mask, img
-
-
-if __name__ == "__main__":
-    providers = ['CUDAExecutionProvider', 'CPUExecutionProvider']
-    model_path = huggingface_hub.hf_hub_download("skytnt/anime-seg", "isnetis.onnx")
-    rmbg_model = rt.InferenceSession(model_path, providers=providers)
-    app = gr.Blocks()
-    with app:
-        gr.Markdown("# Anime Remove Background\n\n"
-                    "![visitor badge](https://visitor-badge.glitch.me/badge?page_id=skytnt.animeseg)\n\n"
-                    "demo for [https://github.com/SkyTNT/anime-segmentation/](https://github.com/SkyTNT/anime-segmentation/)")
-        with gr.Row():
-            with gr.Column():
-                input_img = gr.Image(label="input image")
-                examples_data = [[f"examples/{x:02d}.jpg"] for x in range(1, 4)]
-                examples = gr.Dataset(components=[input_img], samples=examples_data)
-            run_btn = gr.Button(variant="primary")
-            output_mask = gr.Image(label="mask")
-            output_img = gr.Image(label="result", image_mode="RGBA")
-        examples.click(lambda x: x[0], [examples], [input_img])
-        run_btn.click(rmbg_fn, [input_img], [output_mask, output_img])
-    app.launch()
diff --git a/spaces/SuYuanS/AudioCraft_Plus/tests/common_utils/temp_utils.py b/spaces/SuYuanS/AudioCraft_Plus/tests/common_utils/temp_utils.py
deleted file mode 100644
index b45d896836799edcf1fee271409b390b3b6e4127..0000000000000000000000000000000000000000
--- a/spaces/SuYuanS/AudioCraft_Plus/tests/common_utils/temp_utils.py
+++ /dev/null
@@ -1,56 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-import os
-import tempfile
-
-
-class TempDirMixin:
-    """Mixin to provide easy access to temp dir.
-    """
-
-    temp_dir_ = None
-
-    @classmethod
-    def get_base_temp_dir(cls):
-        # If AUDIOCRAFT_TEST_DIR is set, use it instead of temporary directory.
-        # this is handy for debugging.
-        key = "AUDIOCRAFT_TEST_DIR"
-        if key in os.environ:
-            return os.environ[key]
-        if cls.temp_dir_ is None:
-            cls.temp_dir_ = tempfile.TemporaryDirectory()
-        return cls.temp_dir_.name
-
-    @classmethod
-    def tearDownClass(cls):
-        if cls.temp_dir_ is not None:
-            try:
-                cls.temp_dir_.cleanup()
-                cls.temp_dir_ = None
-            except PermissionError:
-                # On Windows there is a know issue with `shutil.rmtree`,
-                # which fails intermittently.
-                # https://github.com/python/cpython/issues/74168
-                # Following the above thread, we ignore it.
-                pass
-        super().tearDownClass()
-
-    @property
-    def id(self):
-        return self.__class__.__name__
-
-    def get_temp_path(self, *paths):
-        temp_dir = os.path.join(self.get_base_temp_dir(), self.id)
-        path = os.path.join(temp_dir, *paths)
-        os.makedirs(os.path.dirname(path), exist_ok=True)
-        return path
-
-    def get_temp_dir(self, *paths):
-        temp_dir = os.path.join(self.get_base_temp_dir(), self.id)
-        path = os.path.join(temp_dir, *paths)
-        os.makedirs(path, exist_ok=True)
-        return path
diff --git a/spaces/Sumit7864/Image-Enhancer/scripts/generate_meta_info_pairdata.py b/spaces/Sumit7864/Image-Enhancer/scripts/generate_meta_info_pairdata.py
deleted file mode 100644
index 76dce7e41c803a8055f3627cccb98deb51419b09..0000000000000000000000000000000000000000
--- a/spaces/Sumit7864/Image-Enhancer/scripts/generate_meta_info_pairdata.py
+++ /dev/null
@@ -1,49 +0,0 @@
-import argparse
-import glob
-import os
-
-
-def main(args):
-    txt_file = open(args.meta_info, 'w')
-    # sca images
-    img_paths_gt = sorted(glob.glob(os.path.join(args.input[0], '*')))
-    img_paths_lq = sorted(glob.glob(os.path.join(args.input[1], '*')))
-
-    assert len(img_paths_gt) == len(img_paths_lq), ('GT folder and LQ folder should have the same length, but got '
-                                                    f'{len(img_paths_gt)} and {len(img_paths_lq)}.')
-
-    for img_path_gt, img_path_lq in zip(img_paths_gt, img_paths_lq):
-        # get the relative paths
-        img_name_gt = os.path.relpath(img_path_gt, args.root[0])
-        img_name_lq = os.path.relpath(img_path_lq, args.root[1])
-        print(f'{img_name_gt}, {img_name_lq}')
-        txt_file.write(f'{img_name_gt}, {img_name_lq}\n')
-
-
-if __name__ == '__main__':
-    """This script is used to generate meta info (txt file) for paired images.
-    """
-    parser = argparse.ArgumentParser()
-    parser.add_argument(
-        '--input',
-        nargs='+',
-        default=['datasets/DF2K/DIV2K_train_HR_sub', 'datasets/DF2K/DIV2K_train_LR_bicubic_X4_sub'],
-        help='Input folder, should be [gt_folder, lq_folder]')
-    parser.add_argument('--root', nargs='+', default=[None, None], help='Folder root, will use the ')
-    parser.add_argument(
-        '--meta_info',
-        type=str,
-        default='datasets/DF2K/meta_info/meta_info_DIV2K_sub_pair.txt',
-        help='txt path for meta info')
-    args = parser.parse_args()
-
-    assert len(args.input) == 2, 'Input folder should have two elements: gt folder and lq folder'
-    assert len(args.root) == 2, 'Root path should have two elements: root for gt folder and lq folder'
-    os.makedirs(os.path.dirname(args.meta_info), exist_ok=True)
-    for i in range(2):
-        if args.input[i].endswith('/'):
-            args.input[i] = args.input[i][:-1]
-        if args.root[i] is None:
-            args.root[i] = os.path.dirname(args.input[i])
-
-    main(args)
diff --git a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/IPython/external/tests/__init__.py b/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/IPython/external/tests/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/aiohttp/web.py b/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/aiohttp/web.py
deleted file mode 100644
index cefae2b9ae4114696f244f7f71bf8dd74ca8f4a6..0000000000000000000000000000000000000000
--- a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/aiohttp/web.py
+++ /dev/null
@@ -1,588 +0,0 @@
-import asyncio
-import logging
-import socket
-import sys
-from argparse import ArgumentParser
-from collections.abc import Iterable
-from importlib import import_module
-from typing import (
-    Any,
-    Awaitable,
-    Callable,
-    Iterable as TypingIterable,
-    List,
-    Optional,
-    Set,
-    Type,
-    Union,
-    cast,
-)
-
-from .abc import AbstractAccessLogger
-from .helpers import all_tasks
-from .log import access_logger
-from .web_app import Application as Application, CleanupError as CleanupError
-from .web_exceptions import (
-    HTTPAccepted as HTTPAccepted,
-    HTTPBadGateway as HTTPBadGateway,
-    HTTPBadRequest as HTTPBadRequest,
-    HTTPClientError as HTTPClientError,
-    HTTPConflict as HTTPConflict,
-    HTTPCreated as HTTPCreated,
-    HTTPError as HTTPError,
-    HTTPException as HTTPException,
-    HTTPExpectationFailed as HTTPExpectationFailed,
-    HTTPFailedDependency as HTTPFailedDependency,
-    HTTPForbidden as HTTPForbidden,
-    HTTPFound as HTTPFound,
-    HTTPGatewayTimeout as HTTPGatewayTimeout,
-    HTTPGone as HTTPGone,
-    HTTPInsufficientStorage as HTTPInsufficientStorage,
-    HTTPInternalServerError as HTTPInternalServerError,
-    HTTPLengthRequired as HTTPLengthRequired,
-    HTTPMethodNotAllowed as HTTPMethodNotAllowed,
-    HTTPMisdirectedRequest as HTTPMisdirectedRequest,
-    HTTPMovedPermanently as HTTPMovedPermanently,
-    HTTPMultipleChoices as HTTPMultipleChoices,
-    HTTPNetworkAuthenticationRequired as HTTPNetworkAuthenticationRequired,
-    HTTPNoContent as HTTPNoContent,
-    HTTPNonAuthoritativeInformation as HTTPNonAuthoritativeInformation,
-    HTTPNotAcceptable as HTTPNotAcceptable,
-    HTTPNotExtended as HTTPNotExtended,
-    HTTPNotFound as HTTPNotFound,
-    HTTPNotImplemented as HTTPNotImplemented,
-    HTTPNotModified as HTTPNotModified,
-    HTTPOk as HTTPOk,
-    HTTPPartialContent as HTTPPartialContent,
-    HTTPPaymentRequired as HTTPPaymentRequired,
-    HTTPPermanentRedirect as HTTPPermanentRedirect,
-    HTTPPreconditionFailed as HTTPPreconditionFailed,
-    HTTPPreconditionRequired as HTTPPreconditionRequired,
-    HTTPProxyAuthenticationRequired as HTTPProxyAuthenticationRequired,
-    HTTPRedirection as HTTPRedirection,
-    HTTPRequestEntityTooLarge as HTTPRequestEntityTooLarge,
-    HTTPRequestHeaderFieldsTooLarge as HTTPRequestHeaderFieldsTooLarge,
-    HTTPRequestRangeNotSatisfiable as HTTPRequestRangeNotSatisfiable,
-    HTTPRequestTimeout as HTTPRequestTimeout,
-    HTTPRequestURITooLong as HTTPRequestURITooLong,
-    HTTPResetContent as HTTPResetContent,
-    HTTPSeeOther as HTTPSeeOther,
-    HTTPServerError as HTTPServerError,
-    HTTPServiceUnavailable as HTTPServiceUnavailable,
-    HTTPSuccessful as HTTPSuccessful,
-    HTTPTemporaryRedirect as HTTPTemporaryRedirect,
-    HTTPTooManyRequests as HTTPTooManyRequests,
-    HTTPUnauthorized as HTTPUnauthorized,
-    HTTPUnavailableForLegalReasons as HTTPUnavailableForLegalReasons,
-    HTTPUnprocessableEntity as HTTPUnprocessableEntity,
-    HTTPUnsupportedMediaType as HTTPUnsupportedMediaType,
-    HTTPUpgradeRequired as HTTPUpgradeRequired,
-    HTTPUseProxy as HTTPUseProxy,
-    HTTPVariantAlsoNegotiates as HTTPVariantAlsoNegotiates,
-    HTTPVersionNotSupported as HTTPVersionNotSupported,
-)
-from .web_fileresponse import FileResponse as FileResponse
-from .web_log import AccessLogger
-from .web_middlewares import (
-    middleware as middleware,
-    normalize_path_middleware as normalize_path_middleware,
-)
-from .web_protocol import (
-    PayloadAccessError as PayloadAccessError,
-    RequestHandler as RequestHandler,
-    RequestPayloadError as RequestPayloadError,
-)
-from .web_request import (
-    BaseRequest as BaseRequest,
-    FileField as FileField,
-    Request as Request,
-)
-from .web_response import (
-    ContentCoding as ContentCoding,
-    Response as Response,
-    StreamResponse as StreamResponse,
-    json_response as json_response,
-)
-from .web_routedef import (
-    AbstractRouteDef as AbstractRouteDef,
-    RouteDef as RouteDef,
-    RouteTableDef as RouteTableDef,
-    StaticDef as StaticDef,
-    delete as delete,
-    get as get,
-    head as head,
-    options as options,
-    patch as patch,
-    post as post,
-    put as put,
-    route as route,
-    static as static,
-    view as view,
-)
-from .web_runner import (
-    AppRunner as AppRunner,
-    BaseRunner as BaseRunner,
-    BaseSite as BaseSite,
-    GracefulExit as GracefulExit,
-    NamedPipeSite as NamedPipeSite,
-    ServerRunner as ServerRunner,
-    SockSite as SockSite,
-    TCPSite as TCPSite,
-    UnixSite as UnixSite,
-)
-from .web_server import Server as Server
-from .web_urldispatcher import (
-    AbstractResource as AbstractResource,
-    AbstractRoute as AbstractRoute,
-    DynamicResource as DynamicResource,
-    PlainResource as PlainResource,
-    PrefixedSubAppResource as PrefixedSubAppResource,
-    Resource as Resource,
-    ResourceRoute as ResourceRoute,
-    StaticResource as StaticResource,
-    UrlDispatcher as UrlDispatcher,
-    UrlMappingMatchInfo as UrlMappingMatchInfo,
-    View as View,
-)
-from .web_ws import (
-    WebSocketReady as WebSocketReady,
-    WebSocketResponse as WebSocketResponse,
-    WSMsgType as WSMsgType,
-)
-
-__all__ = (
-    # web_app
-    "Application",
-    "CleanupError",
-    # web_exceptions
-    "HTTPAccepted",
-    "HTTPBadGateway",
-    "HTTPBadRequest",
-    "HTTPClientError",
-    "HTTPConflict",
-    "HTTPCreated",
-    "HTTPError",
-    "HTTPException",
-    "HTTPExpectationFailed",
-    "HTTPFailedDependency",
-    "HTTPForbidden",
-    "HTTPFound",
-    "HTTPGatewayTimeout",
-    "HTTPGone",
-    "HTTPInsufficientStorage",
-    "HTTPInternalServerError",
-    "HTTPLengthRequired",
-    "HTTPMethodNotAllowed",
-    "HTTPMisdirectedRequest",
-    "HTTPMovedPermanently",
-    "HTTPMultipleChoices",
-    "HTTPNetworkAuthenticationRequired",
-    "HTTPNoContent",
-    "HTTPNonAuthoritativeInformation",
-    "HTTPNotAcceptable",
-    "HTTPNotExtended",
-    "HTTPNotFound",
-    "HTTPNotImplemented",
-    "HTTPNotModified",
-    "HTTPOk",
-    "HTTPPartialContent",
-    "HTTPPaymentRequired",
-    "HTTPPermanentRedirect",
-    "HTTPPreconditionFailed",
-    "HTTPPreconditionRequired",
-    "HTTPProxyAuthenticationRequired",
-    "HTTPRedirection",
-    "HTTPRequestEntityTooLarge",
-    "HTTPRequestHeaderFieldsTooLarge",
-    "HTTPRequestRangeNotSatisfiable",
-    "HTTPRequestTimeout",
-    "HTTPRequestURITooLong",
-    "HTTPResetContent",
-    "HTTPSeeOther",
-    "HTTPServerError",
-    "HTTPServiceUnavailable",
-    "HTTPSuccessful",
-    "HTTPTemporaryRedirect",
-    "HTTPTooManyRequests",
-    "HTTPUnauthorized",
-    "HTTPUnavailableForLegalReasons",
-    "HTTPUnprocessableEntity",
-    "HTTPUnsupportedMediaType",
-    "HTTPUpgradeRequired",
-    "HTTPUseProxy",
-    "HTTPVariantAlsoNegotiates",
-    "HTTPVersionNotSupported",
-    # web_fileresponse
-    "FileResponse",
-    # web_middlewares
-    "middleware",
-    "normalize_path_middleware",
-    # web_protocol
-    "PayloadAccessError",
-    "RequestHandler",
-    "RequestPayloadError",
-    # web_request
-    "BaseRequest",
-    "FileField",
-    "Request",
-    # web_response
-    "ContentCoding",
-    "Response",
-    "StreamResponse",
-    "json_response",
-    # web_routedef
-    "AbstractRouteDef",
-    "RouteDef",
-    "RouteTableDef",
-    "StaticDef",
-    "delete",
-    "get",
-    "head",
-    "options",
-    "patch",
-    "post",
-    "put",
-    "route",
-    "static",
-    "view",
-    # web_runner
-    "AppRunner",
-    "BaseRunner",
-    "BaseSite",
-    "GracefulExit",
-    "ServerRunner",
-    "SockSite",
-    "TCPSite",
-    "UnixSite",
-    "NamedPipeSite",
-    # web_server
-    "Server",
-    # web_urldispatcher
-    "AbstractResource",
-    "AbstractRoute",
-    "DynamicResource",
-    "PlainResource",
-    "PrefixedSubAppResource",
-    "Resource",
-    "ResourceRoute",
-    "StaticResource",
-    "UrlDispatcher",
-    "UrlMappingMatchInfo",
-    "View",
-    # web_ws
-    "WebSocketReady",
-    "WebSocketResponse",
-    "WSMsgType",
-    # web
-    "run_app",
-)
-
-
-try:
-    from ssl import SSLContext
-except ImportError:  # pragma: no cover
-    SSLContext = Any  # type: ignore[misc,assignment]
-
-HostSequence = TypingIterable[str]
-
-
-async def _run_app(
-    app: Union[Application, Awaitable[Application]],
-    *,
-    host: Optional[Union[str, HostSequence]] = None,
-    port: Optional[int] = None,
-    path: Optional[str] = None,
-    sock: Optional[Union[socket.socket, TypingIterable[socket.socket]]] = None,
-    shutdown_timeout: float = 60.0,
-    keepalive_timeout: float = 75.0,
-    ssl_context: Optional[SSLContext] = None,
-    print: Callable[..., None] = print,
-    backlog: int = 128,
-    access_log_class: Type[AbstractAccessLogger] = AccessLogger,
-    access_log_format: str = AccessLogger.LOG_FORMAT,
-    access_log: Optional[logging.Logger] = access_logger,
-    handle_signals: bool = True,
-    reuse_address: Optional[bool] = None,
-    reuse_port: Optional[bool] = None,
-) -> None:
-    # A internal functio to actually do all dirty job for application running
-    if asyncio.iscoroutine(app):
-        app = await app  # type: ignore[misc]
-
-    app = cast(Application, app)
-
-    runner = AppRunner(
-        app,
-        handle_signals=handle_signals,
-        access_log_class=access_log_class,
-        access_log_format=access_log_format,
-        access_log=access_log,
-        keepalive_timeout=keepalive_timeout,
-    )
-
-    await runner.setup()
-
-    sites: List[BaseSite] = []
-
-    try:
-        if host is not None:
-            if isinstance(host, (str, bytes, bytearray, memoryview)):
-                sites.append(
-                    TCPSite(
-                        runner,
-                        host,
-                        port,
-                        shutdown_timeout=shutdown_timeout,
-                        ssl_context=ssl_context,
-                        backlog=backlog,
-                        reuse_address=reuse_address,
-                        reuse_port=reuse_port,
-                    )
-                )
-            else:
-                for h in host:
-                    sites.append(
-                        TCPSite(
-                            runner,
-                            h,
-                            port,
-                            shutdown_timeout=shutdown_timeout,
-                            ssl_context=ssl_context,
-                            backlog=backlog,
-                            reuse_address=reuse_address,
-                            reuse_port=reuse_port,
-                        )
-                    )
-        elif path is None and sock is None or port is not None:
-            sites.append(
-                TCPSite(
-                    runner,
-                    port=port,
-                    shutdown_timeout=shutdown_timeout,
-                    ssl_context=ssl_context,
-                    backlog=backlog,
-                    reuse_address=reuse_address,
-                    reuse_port=reuse_port,
-                )
-            )
-
-        if path is not None:
-            if isinstance(path, (str, bytes, bytearray, memoryview)):
-                sites.append(
-                    UnixSite(
-                        runner,
-                        path,
-                        shutdown_timeout=shutdown_timeout,
-                        ssl_context=ssl_context,
-                        backlog=backlog,
-                    )
-                )
-            else:
-                for p in path:
-                    sites.append(
-                        UnixSite(
-                            runner,
-                            p,
-                            shutdown_timeout=shutdown_timeout,
-                            ssl_context=ssl_context,
-                            backlog=backlog,
-                        )
-                    )
-
-        if sock is not None:
-            if not isinstance(sock, Iterable):
-                sites.append(
-                    SockSite(
-                        runner,
-                        sock,
-                        shutdown_timeout=shutdown_timeout,
-                        ssl_context=ssl_context,
-                        backlog=backlog,
-                    )
-                )
-            else:
-                for s in sock:
-                    sites.append(
-                        SockSite(
-                            runner,
-                            s,
-                            shutdown_timeout=shutdown_timeout,
-                            ssl_context=ssl_context,
-                            backlog=backlog,
-                        )
-                    )
-        for site in sites:
-            await site.start()
-
-        if print:  # pragma: no branch
-            names = sorted(str(s.name) for s in runner.sites)
-            print(
-                "======== Running on {} ========\n"
-                "(Press CTRL+C to quit)".format(", ".join(names))
-            )
-
-        # sleep forever by 1 hour intervals,
-        # on Windows before Python 3.8 wake up every 1 second to handle
-        # Ctrl+C smoothly
-        if sys.platform == "win32" and sys.version_info < (3, 8):
-            delay = 1
-        else:
-            delay = 3600
-
-        while True:
-            await asyncio.sleep(delay)
-    finally:
-        await runner.cleanup()
-
-
-def _cancel_tasks(
-    to_cancel: Set["asyncio.Task[Any]"], loop: asyncio.AbstractEventLoop
-) -> None:
-    if not to_cancel:
-        return
-
-    for task in to_cancel:
-        task.cancel()
-
-    loop.run_until_complete(asyncio.gather(*to_cancel, return_exceptions=True))
-
-    for task in to_cancel:
-        if task.cancelled():
-            continue
-        if task.exception() is not None:
-            loop.call_exception_handler(
-                {
-                    "message": "unhandled exception during asyncio.run() shutdown",
-                    "exception": task.exception(),
-                    "task": task,
-                }
-            )
-
-
-def run_app(
-    app: Union[Application, Awaitable[Application]],
-    *,
-    host: Optional[Union[str, HostSequence]] = None,
-    port: Optional[int] = None,
-    path: Optional[str] = None,
-    sock: Optional[Union[socket.socket, TypingIterable[socket.socket]]] = None,
-    shutdown_timeout: float = 60.0,
-    keepalive_timeout: float = 75.0,
-    ssl_context: Optional[SSLContext] = None,
-    print: Callable[..., None] = print,
-    backlog: int = 128,
-    access_log_class: Type[AbstractAccessLogger] = AccessLogger,
-    access_log_format: str = AccessLogger.LOG_FORMAT,
-    access_log: Optional[logging.Logger] = access_logger,
-    handle_signals: bool = True,
-    reuse_address: Optional[bool] = None,
-    reuse_port: Optional[bool] = None,
-    loop: Optional[asyncio.AbstractEventLoop] = None,
-) -> None:
-    """Run an app locally"""
-    if loop is None:
-        loop = asyncio.new_event_loop()
-
-    # Configure if and only if in debugging mode and using the default logger
-    if loop.get_debug() and access_log and access_log.name == "aiohttp.access":
-        if access_log.level == logging.NOTSET:
-            access_log.setLevel(logging.DEBUG)
-        if not access_log.hasHandlers():
-            access_log.addHandler(logging.StreamHandler())
-
-    main_task = loop.create_task(
-        _run_app(
-            app,
-            host=host,
-            port=port,
-            path=path,
-            sock=sock,
-            shutdown_timeout=shutdown_timeout,
-            keepalive_timeout=keepalive_timeout,
-            ssl_context=ssl_context,
-            print=print,
-            backlog=backlog,
-            access_log_class=access_log_class,
-            access_log_format=access_log_format,
-            access_log=access_log,
-            handle_signals=handle_signals,
-            reuse_address=reuse_address,
-            reuse_port=reuse_port,
-        )
-    )
-
-    try:
-        asyncio.set_event_loop(loop)
-        loop.run_until_complete(main_task)
-    except (GracefulExit, KeyboardInterrupt):  # pragma: no cover
-        pass
-    finally:
-        _cancel_tasks({main_task}, loop)
-        _cancel_tasks(all_tasks(loop), loop)
-        loop.run_until_complete(loop.shutdown_asyncgens())
-        loop.close()
-
-
-def main(argv: List[str]) -> None:
-    arg_parser = ArgumentParser(
-        description="aiohttp.web Application server", prog="aiohttp.web"
-    )
-    arg_parser.add_argument(
-        "entry_func",
-        help=(
-            "Callable returning the `aiohttp.web.Application` instance to "
-            "run. Should be specified in the 'module:function' syntax."
-        ),
-        metavar="entry-func",
-    )
-    arg_parser.add_argument(
-        "-H",
-        "--hostname",
-        help="TCP/IP hostname to serve on (default: %(default)r)",
-        default="localhost",
-    )
-    arg_parser.add_argument(
-        "-P",
-        "--port",
-        help="TCP/IP port to serve on (default: %(default)r)",
-        type=int,
-        default="8080",
-    )
-    arg_parser.add_argument(
-        "-U",
-        "--path",
-        help="Unix file system path to serve on. Specifying a path will cause "
-        "hostname and port arguments to be ignored.",
-    )
-    args, extra_argv = arg_parser.parse_known_args(argv)
-
-    # Import logic
-    mod_str, _, func_str = args.entry_func.partition(":")
-    if not func_str or not mod_str:
-        arg_parser.error("'entry-func' not in 'module:function' syntax")
-    if mod_str.startswith("."):
-        arg_parser.error("relative module names not supported")
-    try:
-        module = import_module(mod_str)
-    except ImportError as ex:
-        arg_parser.error(f"unable to import {mod_str}: {ex}")
-    try:
-        func = getattr(module, func_str)
-    except AttributeError:
-        arg_parser.error(f"module {mod_str!r} has no attribute {func_str!r}")
-
-    # Compatibility logic
-    if args.path is not None and not hasattr(socket, "AF_UNIX"):
-        arg_parser.error(
-            "file system paths not supported by your operating" " environment"
-        )
-
-    logging.basicConfig(level=logging.DEBUG)
-
-    app = func(extra_argv)
-    run_app(app, host=args.hostname, port=args.port, path=args.path)
-    arg_parser.exit(message="Stopped\n")
-
-
-if __name__ == "__main__":  # pragma: no branch
-    main(sys.argv[1:])  # pragma: no cover
diff --git a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/_pydevd_frame_eval/pydevd_frame_evaluator.c b/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/_pydevd_frame_eval/pydevd_frame_evaluator.c
deleted file mode 100644
index 245e02719f8f089f5881db485bcb95a25b8ccfea..0000000000000000000000000000000000000000
--- a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/_pydevd_frame_eval/pydevd_frame_evaluator.c
+++ /dev/null
@@ -1,20595 +0,0 @@
-/* Generated by Cython 0.29.32 */
-
-/* BEGIN: Cython Metadata
-{
-    "distutils": {
-        "depends": [
-            "_pydevd_frame_eval/release_mem.h"
-        ],
-        "include_dirs": [
-            "_pydevd_frame_eval"
-        ],
-        "name": "_pydevd_frame_eval.pydevd_frame_evaluator",
-        "sources": [
-            "_pydevd_frame_eval/pydevd_frame_evaluator.pyx"
-        ]
-    },
-    "module_name": "_pydevd_frame_eval.pydevd_frame_evaluator"
-}
-END: Cython Metadata */
-
-#ifndef PY_SSIZE_T_CLEAN
-#define PY_SSIZE_T_CLEAN
-#endif /* PY_SSIZE_T_CLEAN */
-#include "Python.h"
-#if PY_VERSION_HEX >= 0x03090000
-#include "internal/pycore_gc.h"
-#include "internal/pycore_interp.h"
-#endif
-
-#ifndef Py_PYTHON_H
-    #error Python headers needed to compile C extensions, please install development version of Python.
-#elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03030000)
-    #error Cython requires Python 2.6+ or Python 3.3+.
-#else
-#define CYTHON_ABI "0_29_32"
-#define CYTHON_HEX_VERSION 0x001D20F0
-#define CYTHON_FUTURE_DIVISION 0
-#include <stddef.h>
-#ifndef offsetof
-  #define offsetof(type, member) ( (size_t) & ((type*)0) -> member )
-#endif
-#if !defined(WIN32) && !defined(MS_WINDOWS)
-  #ifndef __stdcall
-    #define __stdcall
-  #endif
-  #ifndef __cdecl
-    #define __cdecl
-  #endif
-  #ifndef __fastcall
-    #define __fastcall
-  #endif
-#endif
-#ifndef DL_IMPORT
-  #define DL_IMPORT(t) t
-#endif
-#ifndef DL_EXPORT
-  #define DL_EXPORT(t) t
-#endif
-#define __PYX_COMMA ,
-#ifndef HAVE_LONG_LONG
-  #if PY_VERSION_HEX >= 0x02070000
-    #define HAVE_LONG_LONG
-  #endif
-#endif
-#ifndef PY_LONG_LONG
-  #define PY_LONG_LONG LONG_LONG
-#endif
-#ifndef Py_HUGE_VAL
-  #define Py_HUGE_VAL HUGE_VAL
-#endif
-#ifdef PYPY_VERSION
-  #define CYTHON_COMPILING_IN_PYPY 1
-  #define CYTHON_COMPILING_IN_PYSTON 0
-  #define CYTHON_COMPILING_IN_CPYTHON 0
-  #define CYTHON_COMPILING_IN_NOGIL 0
-  #undef CYTHON_USE_TYPE_SLOTS
-  #define CYTHON_USE_TYPE_SLOTS 0
-  #undef CYTHON_USE_PYTYPE_LOOKUP
-  #define CYTHON_USE_PYTYPE_LOOKUP 0
-  #if PY_VERSION_HEX < 0x03050000
-    #undef CYTHON_USE_ASYNC_SLOTS
-    #define CYTHON_USE_ASYNC_SLOTS 0
-  #elif !defined(CYTHON_USE_ASYNC_SLOTS)
-    #define CYTHON_USE_ASYNC_SLOTS 1
-  #endif
-  #undef CYTHON_USE_PYLIST_INTERNALS
-  #define CYTHON_USE_PYLIST_INTERNALS 0
-  #undef CYTHON_USE_UNICODE_INTERNALS
-  #define CYTHON_USE_UNICODE_INTERNALS 0
-  #undef CYTHON_USE_UNICODE_WRITER
-  #define CYTHON_USE_UNICODE_WRITER 0
-  #undef CYTHON_USE_PYLONG_INTERNALS
-  #define CYTHON_USE_PYLONG_INTERNALS 0
-  #undef CYTHON_AVOID_BORROWED_REFS
-  #define CYTHON_AVOID_BORROWED_REFS 1
-  #undef CYTHON_ASSUME_SAFE_MACROS
-  #define CYTHON_ASSUME_SAFE_MACROS 0
-  #undef CYTHON_UNPACK_METHODS
-  #define CYTHON_UNPACK_METHODS 0
-  #undef CYTHON_FAST_THREAD_STATE
-  #define CYTHON_FAST_THREAD_STATE 0
-  #undef CYTHON_FAST_PYCALL
-  #define CYTHON_FAST_PYCALL 0
-  #undef CYTHON_PEP489_MULTI_PHASE_INIT
-  #define CYTHON_PEP489_MULTI_PHASE_INIT 0
-  #undef CYTHON_USE_TP_FINALIZE
-  #define CYTHON_USE_TP_FINALIZE 0
-  #undef CYTHON_USE_DICT_VERSIONS
-  #define CYTHON_USE_DICT_VERSIONS 0
-  #undef CYTHON_USE_EXC_INFO_STACK
-  #define CYTHON_USE_EXC_INFO_STACK 0
-  #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC
-    #define CYTHON_UPDATE_DESCRIPTOR_DOC (PYPY_VERSION_HEX >= 0x07030900)
-  #endif
-#elif defined(PYSTON_VERSION)
-  #define CYTHON_COMPILING_IN_PYPY 0
-  #define CYTHON_COMPILING_IN_PYSTON 1
-  #define CYTHON_COMPILING_IN_CPYTHON 0
-  #define CYTHON_COMPILING_IN_NOGIL 0
-  #ifndef CYTHON_USE_TYPE_SLOTS
-    #define CYTHON_USE_TYPE_SLOTS 1
-  #endif
-  #undef CYTHON_USE_PYTYPE_LOOKUP
-  #define CYTHON_USE_PYTYPE_LOOKUP 0
-  #undef CYTHON_USE_ASYNC_SLOTS
-  #define CYTHON_USE_ASYNC_SLOTS 0
-  #undef CYTHON_USE_PYLIST_INTERNALS
-  #define CYTHON_USE_PYLIST_INTERNALS 0
-  #ifndef CYTHON_USE_UNICODE_INTERNALS
-    #define CYTHON_USE_UNICODE_INTERNALS 1
-  #endif
-  #undef CYTHON_USE_UNICODE_WRITER
-  #define CYTHON_USE_UNICODE_WRITER 0
-  #undef CYTHON_USE_PYLONG_INTERNALS
-  #define CYTHON_USE_PYLONG_INTERNALS 0
-  #ifndef CYTHON_AVOID_BORROWED_REFS
-    #define CYTHON_AVOID_BORROWED_REFS 0
-  #endif
-  #ifndef CYTHON_ASSUME_SAFE_MACROS
-    #define CYTHON_ASSUME_SAFE_MACROS 1
-  #endif
-  #ifndef CYTHON_UNPACK_METHODS
-    #define CYTHON_UNPACK_METHODS 1
-  #endif
-  #undef CYTHON_FAST_THREAD_STATE
-  #define CYTHON_FAST_THREAD_STATE 0
-  #undef CYTHON_FAST_PYCALL
-  #define CYTHON_FAST_PYCALL 0
-  #undef CYTHON_PEP489_MULTI_PHASE_INIT
-  #define CYTHON_PEP489_MULTI_PHASE_INIT 0
-  #undef CYTHON_USE_TP_FINALIZE
-  #define CYTHON_USE_TP_FINALIZE 0
-  #undef CYTHON_USE_DICT_VERSIONS
-  #define CYTHON_USE_DICT_VERSIONS 0
-  #undef CYTHON_USE_EXC_INFO_STACK
-  #define CYTHON_USE_EXC_INFO_STACK 0
-  #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC
-    #define CYTHON_UPDATE_DESCRIPTOR_DOC 0
-  #endif
-#elif defined(PY_NOGIL)
-  #define CYTHON_COMPILING_IN_PYPY 0
-  #define CYTHON_COMPILING_IN_PYSTON 0
-  #define CYTHON_COMPILING_IN_CPYTHON 0
-  #define CYTHON_COMPILING_IN_NOGIL 1
-  #ifndef CYTHON_USE_TYPE_SLOTS
-    #define CYTHON_USE_TYPE_SLOTS 1
-  #endif
-  #undef CYTHON_USE_PYTYPE_LOOKUP
-  #define CYTHON_USE_PYTYPE_LOOKUP 0
-  #ifndef CYTHON_USE_ASYNC_SLOTS
-    #define CYTHON_USE_ASYNC_SLOTS 1
-  #endif
-  #undef CYTHON_USE_PYLIST_INTERNALS
-  #define CYTHON_USE_PYLIST_INTERNALS 0
-  #ifndef CYTHON_USE_UNICODE_INTERNALS
-    #define CYTHON_USE_UNICODE_INTERNALS 1
-  #endif
-  #undef CYTHON_USE_UNICODE_WRITER
-  #define CYTHON_USE_UNICODE_WRITER 0
-  #undef CYTHON_USE_PYLONG_INTERNALS
-  #define CYTHON_USE_PYLONG_INTERNALS 0
-  #ifndef CYTHON_AVOID_BORROWED_REFS
-    #define CYTHON_AVOID_BORROWED_REFS 0
-  #endif
-  #ifndef CYTHON_ASSUME_SAFE_MACROS
-    #define CYTHON_ASSUME_SAFE_MACROS 1
-  #endif
-  #ifndef CYTHON_UNPACK_METHODS
-    #define CYTHON_UNPACK_METHODS 1
-  #endif
-  #undef CYTHON_FAST_THREAD_STATE
-  #define CYTHON_FAST_THREAD_STATE 0
-  #undef CYTHON_FAST_PYCALL
-  #define CYTHON_FAST_PYCALL 0
-  #ifndef CYTHON_PEP489_MULTI_PHASE_INIT
-    #define CYTHON_PEP489_MULTI_PHASE_INIT 1
-  #endif
-  #ifndef CYTHON_USE_TP_FINALIZE
-    #define CYTHON_USE_TP_FINALIZE 1
-  #endif
-  #undef CYTHON_USE_DICT_VERSIONS
-  #define CYTHON_USE_DICT_VERSIONS 0
-  #undef CYTHON_USE_EXC_INFO_STACK
-  #define CYTHON_USE_EXC_INFO_STACK 0
-#else
-  #define CYTHON_COMPILING_IN_PYPY 0
-  #define CYTHON_COMPILING_IN_PYSTON 0
-  #define CYTHON_COMPILING_IN_CPYTHON 1
-  #define CYTHON_COMPILING_IN_NOGIL 0
-  #ifndef CYTHON_USE_TYPE_SLOTS
-    #define CYTHON_USE_TYPE_SLOTS 1
-  #endif
-  #if PY_VERSION_HEX < 0x02070000
-    #undef CYTHON_USE_PYTYPE_LOOKUP
-    #define CYTHON_USE_PYTYPE_LOOKUP 0
-  #elif !defined(CYTHON_USE_PYTYPE_LOOKUP)
-    #define CYTHON_USE_PYTYPE_LOOKUP 1
-  #endif
-  #if PY_MAJOR_VERSION < 3
-    #undef CYTHON_USE_ASYNC_SLOTS
-    #define CYTHON_USE_ASYNC_SLOTS 0
-  #elif !defined(CYTHON_USE_ASYNC_SLOTS)
-    #define CYTHON_USE_ASYNC_SLOTS 1
-  #endif
-  #if PY_VERSION_HEX < 0x02070000
-    #undef CYTHON_USE_PYLONG_INTERNALS
-    #define CYTHON_USE_PYLONG_INTERNALS 0
-  #elif !defined(CYTHON_USE_PYLONG_INTERNALS)
-    #define CYTHON_USE_PYLONG_INTERNALS 1
-  #endif
-  #ifndef CYTHON_USE_PYLIST_INTERNALS
-    #define CYTHON_USE_PYLIST_INTERNALS 1
-  #endif
-  #ifndef CYTHON_USE_UNICODE_INTERNALS
-    #define CYTHON_USE_UNICODE_INTERNALS 1
-  #endif
-  #if PY_VERSION_HEX < 0x030300F0 || PY_VERSION_HEX >= 0x030B00A2
-    #undef CYTHON_USE_UNICODE_WRITER
-    #define CYTHON_USE_UNICODE_WRITER 0
-  #elif !defined(CYTHON_USE_UNICODE_WRITER)
-    #define CYTHON_USE_UNICODE_WRITER 1
-  #endif
-  #ifndef CYTHON_AVOID_BORROWED_REFS
-    #define CYTHON_AVOID_BORROWED_REFS 0
-  #endif
-  #ifndef CYTHON_ASSUME_SAFE_MACROS
-    #define CYTHON_ASSUME_SAFE_MACROS 1
-  #endif
-  #ifndef CYTHON_UNPACK_METHODS
-    #define CYTHON_UNPACK_METHODS 1
-  #endif
-  #if PY_VERSION_HEX >= 0x030B00A4
-    #undef CYTHON_FAST_THREAD_STATE
-    #define CYTHON_FAST_THREAD_STATE 0
-  #elif !defined(CYTHON_FAST_THREAD_STATE)
-    #define CYTHON_FAST_THREAD_STATE 1
-  #endif
-  #ifndef CYTHON_FAST_PYCALL
-    #define CYTHON_FAST_PYCALL (PY_VERSION_HEX < 0x030A0000)
-  #endif
-  #ifndef CYTHON_PEP489_MULTI_PHASE_INIT
-    #define CYTHON_PEP489_MULTI_PHASE_INIT (PY_VERSION_HEX >= 0x03050000)
-  #endif
-  #ifndef CYTHON_USE_TP_FINALIZE
-    #define CYTHON_USE_TP_FINALIZE (PY_VERSION_HEX >= 0x030400a1)
-  #endif
-  #ifndef CYTHON_USE_DICT_VERSIONS
-    #define CYTHON_USE_DICT_VERSIONS (PY_VERSION_HEX >= 0x030600B1)
-  #endif
-  #if PY_VERSION_HEX >= 0x030B00A4
-    #undef CYTHON_USE_EXC_INFO_STACK
-    #define CYTHON_USE_EXC_INFO_STACK 0
-  #elif !defined(CYTHON_USE_EXC_INFO_STACK)
-    #define CYTHON_USE_EXC_INFO_STACK (PY_VERSION_HEX >= 0x030700A3)
-  #endif
-  #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC
-    #define CYTHON_UPDATE_DESCRIPTOR_DOC 1
-  #endif
-#endif
-#if !defined(CYTHON_FAST_PYCCALL)
-#define CYTHON_FAST_PYCCALL  (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1)
-#endif
-#if CYTHON_USE_PYLONG_INTERNALS
-  #if PY_MAJOR_VERSION < 3
-    #include "longintrepr.h"
-  #endif
-  #undef SHIFT
-  #undef BASE
-  #undef MASK
-  #ifdef SIZEOF_VOID_P
-    enum { __pyx_check_sizeof_voidp = 1 / (int)(SIZEOF_VOID_P == sizeof(void*)) };
-  #endif
-#endif
-#ifndef __has_attribute
-  #define __has_attribute(x) 0
-#endif
-#ifndef __has_cpp_attribute
-  #define __has_cpp_attribute(x) 0
-#endif
-#ifndef CYTHON_RESTRICT
-  #if defined(__GNUC__)
-    #define CYTHON_RESTRICT __restrict__
-  #elif defined(_MSC_VER) && _MSC_VER >= 1400
-    #define CYTHON_RESTRICT __restrict
-  #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
-    #define CYTHON_RESTRICT restrict
-  #else
-    #define CYTHON_RESTRICT
-  #endif
-#endif
-#ifndef CYTHON_UNUSED
-# if defined(__GNUC__)
-#   if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4))
-#     define CYTHON_UNUSED __attribute__ ((__unused__))
-#   else
-#     define CYTHON_UNUSED
-#   endif
-# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER))
-#   define CYTHON_UNUSED __attribute__ ((__unused__))
-# else
-#   define CYTHON_UNUSED
-# endif
-#endif
-#ifndef CYTHON_MAYBE_UNUSED_VAR
-#  if defined(__cplusplus)
-     template<class T> void CYTHON_MAYBE_UNUSED_VAR( const T& ) { }
-#  else
-#    define CYTHON_MAYBE_UNUSED_VAR(x) (void)(x)
-#  endif
-#endif
-#ifndef CYTHON_NCP_UNUSED
-# if CYTHON_COMPILING_IN_CPYTHON
-#  define CYTHON_NCP_UNUSED
-# else
-#  define CYTHON_NCP_UNUSED CYTHON_UNUSED
-# endif
-#endif
-#define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None)
-#ifdef _MSC_VER
-    #ifndef _MSC_STDINT_H_
-        #if _MSC_VER < 1300
-           typedef unsigned char     uint8_t;
-           typedef unsigned int      uint32_t;
-        #else
-           typedef unsigned __int8   uint8_t;
-           typedef unsigned __int32  uint32_t;
-        #endif
-    #endif
-#else
-   #include <stdint.h>
-#endif
-#ifndef CYTHON_FALLTHROUGH
-  #if defined(__cplusplus) && __cplusplus >= 201103L
-    #if __has_cpp_attribute(fallthrough)
-      #define CYTHON_FALLTHROUGH [[fallthrough]]
-    #elif __has_cpp_attribute(clang::fallthrough)
-      #define CYTHON_FALLTHROUGH [[clang::fallthrough]]
-    #elif __has_cpp_attribute(gnu::fallthrough)
-      #define CYTHON_FALLTHROUGH [[gnu::fallthrough]]
-    #endif
-  #endif
-  #ifndef CYTHON_FALLTHROUGH
-    #if __has_attribute(fallthrough)
-      #define CYTHON_FALLTHROUGH __attribute__((fallthrough))
-    #else
-      #define CYTHON_FALLTHROUGH
-    #endif
-  #endif
-  #if defined(__clang__ ) && defined(__apple_build_version__)
-    #if __apple_build_version__ < 7000000
-      #undef  CYTHON_FALLTHROUGH
-      #define CYTHON_FALLTHROUGH
-    #endif
-  #endif
-#endif
-
-#ifndef CYTHON_INLINE
-  #if defined(__clang__)
-    #define CYTHON_INLINE __inline__ __attribute__ ((__unused__))
-  #elif defined(__GNUC__)
-    #define CYTHON_INLINE __inline__
-  #elif defined(_MSC_VER)
-    #define CYTHON_INLINE __inline
-  #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
-    #define CYTHON_INLINE inline
-  #else
-    #define CYTHON_INLINE
-  #endif
-#endif
-
-#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag)
-  #define Py_OptimizeFlag 0
-#endif
-#define __PYX_BUILD_PY_SSIZE_T "n"
-#define CYTHON_FORMAT_SSIZE_T "z"
-#if PY_MAJOR_VERSION < 3
-  #define __Pyx_BUILTIN_MODULE_NAME "__builtin__"
-  #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\
-          PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
-  #define __Pyx_DefaultClassType PyClass_Type
-#else
-  #define __Pyx_BUILTIN_MODULE_NAME "builtins"
-  #define __Pyx_DefaultClassType PyType_Type
-#if PY_VERSION_HEX >= 0x030B00A1
-    static CYTHON_INLINE PyCodeObject* __Pyx_PyCode_New(int a, int k, int l, int s, int f,
-                                                    PyObject *code, PyObject *c, PyObject* n, PyObject *v,
-                                                    PyObject *fv, PyObject *cell, PyObject* fn,
-                                                    PyObject *name, int fline, PyObject *lnos) {
-        PyObject *kwds=NULL, *argcount=NULL, *posonlyargcount=NULL, *kwonlyargcount=NULL;
-        PyObject *nlocals=NULL, *stacksize=NULL, *flags=NULL, *replace=NULL, *call_result=NULL, *empty=NULL;
-        const char *fn_cstr=NULL;
-        const char *name_cstr=NULL;
-        PyCodeObject* co=NULL;
-        PyObject *type, *value, *traceback;
-        PyErr_Fetch(&type, &value, &traceback);
-        if (!(kwds=PyDict_New())) goto end;
-        if (!(argcount=PyLong_FromLong(a))) goto end;
-        if (PyDict_SetItemString(kwds, "co_argcount", argcount) != 0) goto end;
-        if (!(posonlyargcount=PyLong_FromLong(0))) goto end;
-        if (PyDict_SetItemString(kwds, "co_posonlyargcount", posonlyargcount) != 0) goto end;
-        if (!(kwonlyargcount=PyLong_FromLong(k))) goto end;
-        if (PyDict_SetItemString(kwds, "co_kwonlyargcount", kwonlyargcount) != 0) goto end;
-        if (!(nlocals=PyLong_FromLong(l))) goto end;
-        if (PyDict_SetItemString(kwds, "co_nlocals", nlocals) != 0) goto end;
-        if (!(stacksize=PyLong_FromLong(s))) goto end;
-        if (PyDict_SetItemString(kwds, "co_stacksize", stacksize) != 0) goto end;
-        if (!(flags=PyLong_FromLong(f))) goto end;
-        if (PyDict_SetItemString(kwds, "co_flags", flags) != 0) goto end;
-        if (PyDict_SetItemString(kwds, "co_code", code) != 0) goto end;
-        if (PyDict_SetItemString(kwds, "co_consts", c) != 0) goto end;
-        if (PyDict_SetItemString(kwds, "co_names", n) != 0) goto end;
-        if (PyDict_SetItemString(kwds, "co_varnames", v) != 0) goto end;
-        if (PyDict_SetItemString(kwds, "co_freevars", fv) != 0) goto end;
-        if (PyDict_SetItemString(kwds, "co_cellvars", cell) != 0) goto end;
-        if (PyDict_SetItemString(kwds, "co_linetable", lnos) != 0) goto end;
-        if (!(fn_cstr=PyUnicode_AsUTF8AndSize(fn, NULL))) goto end;
-        if (!(name_cstr=PyUnicode_AsUTF8AndSize(name, NULL))) goto end;
-        if (!(co = PyCode_NewEmpty(fn_cstr, name_cstr, fline))) goto end;
-        if (!(replace = PyObject_GetAttrString((PyObject*)co, "replace"))) goto cleanup_code_too;
-        if (!(empty = PyTuple_New(0))) goto cleanup_code_too; // unfortunately __pyx_empty_tuple isn't available here
-        if (!(call_result = PyObject_Call(replace, empty, kwds))) goto cleanup_code_too;
-        Py_XDECREF((PyObject*)co);
-        co = (PyCodeObject*)call_result;
-        call_result = NULL;
-        if (0) {
-            cleanup_code_too:
-            Py_XDECREF((PyObject*)co);
-            co = NULL;
-        }
-        end:
-        Py_XDECREF(kwds);
-        Py_XDECREF(argcount);
-        Py_XDECREF(posonlyargcount);
-        Py_XDECREF(kwonlyargcount);
-        Py_XDECREF(nlocals);
-        Py_XDECREF(stacksize);
-        Py_XDECREF(replace);
-        Py_XDECREF(call_result);
-        Py_XDECREF(empty);
-        if (type) {
-            PyErr_Restore(type, value, traceback);
-        }
-        return co;
-    }
-#else
-  #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\
-          PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
-#endif
-  #define __Pyx_DefaultClassType PyType_Type
-#endif
-#ifndef Py_TPFLAGS_CHECKTYPES
-  #define Py_TPFLAGS_CHECKTYPES 0
-#endif
-#ifndef Py_TPFLAGS_HAVE_INDEX
-  #define Py_TPFLAGS_HAVE_INDEX 0
-#endif
-#ifndef Py_TPFLAGS_HAVE_NEWBUFFER
-  #define Py_TPFLAGS_HAVE_NEWBUFFER 0
-#endif
-#ifndef Py_TPFLAGS_HAVE_FINALIZE
-  #define Py_TPFLAGS_HAVE_FINALIZE 0
-#endif
-#ifndef METH_STACKLESS
-  #define METH_STACKLESS 0
-#endif
-#if PY_VERSION_HEX <= 0x030700A3 || !defined(METH_FASTCALL)
-  #ifndef METH_FASTCALL
-     #define METH_FASTCALL 0x80
-  #endif
-  typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject *const *args, Py_ssize_t nargs);
-  typedef PyObject *(*__Pyx_PyCFunctionFastWithKeywords) (PyObject *self, PyObject *const *args,
-                                                          Py_ssize_t nargs, PyObject *kwnames);
-#else
-  #define __Pyx_PyCFunctionFast _PyCFunctionFast
-  #define __Pyx_PyCFunctionFastWithKeywords _PyCFunctionFastWithKeywords
-#endif
-#if CYTHON_FAST_PYCCALL
-#define __Pyx_PyFastCFunction_Check(func)\
-    ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS)))))
-#else
-#define __Pyx_PyFastCFunction_Check(func) 0
-#endif
-#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc)
-  #define PyObject_Malloc(s)   PyMem_Malloc(s)
-  #define PyObject_Free(p)     PyMem_Free(p)
-  #define PyObject_Realloc(p)  PyMem_Realloc(p)
-#endif
-#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030400A1
-  #define PyMem_RawMalloc(n)           PyMem_Malloc(n)
-  #define PyMem_RawRealloc(p, n)       PyMem_Realloc(p, n)
-  #define PyMem_RawFree(p)             PyMem_Free(p)
-#endif
-#if CYTHON_COMPILING_IN_PYSTON
-  #define __Pyx_PyCode_HasFreeVars(co)  PyCode_HasFreeVars(co)
-  #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno)
-#else
-  #define __Pyx_PyCode_HasFreeVars(co)  (PyCode_GetNumFree(co) > 0)
-  #define __Pyx_PyFrame_SetLineNumber(frame, lineno)  (frame)->f_lineno = (lineno)
-#endif
-#if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000
-  #define __Pyx_PyThreadState_Current PyThreadState_GET()
-#elif PY_VERSION_HEX >= 0x03060000
-  #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet()
-#elif PY_VERSION_HEX >= 0x03000000
-  #define __Pyx_PyThreadState_Current PyThreadState_GET()
-#else
-  #define __Pyx_PyThreadState_Current _PyThreadState_Current
-#endif
-#if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT)
-#include "pythread.h"
-#define Py_tss_NEEDS_INIT 0
-typedef int Py_tss_t;
-static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) {
-  *key = PyThread_create_key();
-  return 0;
-}
-static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) {
-  Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t));
-  *key = Py_tss_NEEDS_INIT;
-  return key;
-}
-static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) {
-  PyObject_Free(key);
-}
-static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) {
-  return *key != Py_tss_NEEDS_INIT;
-}
-static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) {
-  PyThread_delete_key(*key);
-  *key = Py_tss_NEEDS_INIT;
-}
-static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) {
-  return PyThread_set_key_value(*key, value);
-}
-static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) {
-  return PyThread_get_key_value(*key);
-}
-#endif
-#if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized)
-#define __Pyx_PyDict_NewPresized(n)  ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n))
-#else
-#define __Pyx_PyDict_NewPresized(n)  PyDict_New()
-#endif
-#if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION
-  #define __Pyx_PyNumber_Divide(x,y)         PyNumber_TrueDivide(x,y)
-  #define __Pyx_PyNumber_InPlaceDivide(x,y)  PyNumber_InPlaceTrueDivide(x,y)
-#else
-  #define __Pyx_PyNumber_Divide(x,y)         PyNumber_Divide(x,y)
-  #define __Pyx_PyNumber_InPlaceDivide(x,y)  PyNumber_InPlaceDivide(x,y)
-#endif
-#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS
-#define __Pyx_PyDict_GetItemStr(dict, name)  _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash)
-#else
-#define __Pyx_PyDict_GetItemStr(dict, name)  PyDict_GetItem(dict, name)
-#endif
-#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND)
-  #define CYTHON_PEP393_ENABLED 1
-  #if defined(PyUnicode_IS_READY)
-  #define __Pyx_PyUnicode_READY(op)       (likely(PyUnicode_IS_READY(op)) ?\
-                                              0 : _PyUnicode_Ready((PyObject *)(op)))
-  #else
-  #define __Pyx_PyUnicode_READY(op)       (0)
-  #endif
-  #define __Pyx_PyUnicode_GET_LENGTH(u)   PyUnicode_GET_LENGTH(u)
-  #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i)
-  #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u)   PyUnicode_MAX_CHAR_VALUE(u)
-  #define __Pyx_PyUnicode_KIND(u)         PyUnicode_KIND(u)
-  #define __Pyx_PyUnicode_DATA(u)         PyUnicode_DATA(u)
-  #define __Pyx_PyUnicode_READ(k, d, i)   PyUnicode_READ(k, d, i)
-  #define __Pyx_PyUnicode_WRITE(k, d, i, ch)  PyUnicode_WRITE(k, d, i, ch)
-  #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE)
-  #if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x03090000
-  #define __Pyx_PyUnicode_IS_TRUE(u)      (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : ((PyCompactUnicodeObject *)(u))->wstr_length))
-  #else
-  #define __Pyx_PyUnicode_IS_TRUE(u)      (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u)))
-  #endif
-  #else
-  #define __Pyx_PyUnicode_IS_TRUE(u)      (0 != PyUnicode_GET_LENGTH(u))
-  #endif
-#else
-  #define CYTHON_PEP393_ENABLED 0
-  #define PyUnicode_1BYTE_KIND  1
-  #define PyUnicode_2BYTE_KIND  2
-  #define PyUnicode_4BYTE_KIND  4
-  #define __Pyx_PyUnicode_READY(op)       (0)
-  #define __Pyx_PyUnicode_GET_LENGTH(u)   PyUnicode_GET_SIZE(u)
-  #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i]))
-  #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u)   ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111)
-  #define __Pyx_PyUnicode_KIND(u)         (sizeof(Py_UNICODE))
-  #define __Pyx_PyUnicode_DATA(u)         ((void*)PyUnicode_AS_UNICODE(u))
-  #define __Pyx_PyUnicode_READ(k, d, i)   ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i]))
-  #define __Pyx_PyUnicode_WRITE(k, d, i, ch)  (((void)(k)), ((Py_UNICODE*)d)[i] = ch)
-  #define __Pyx_PyUnicode_IS_TRUE(u)      (0 != PyUnicode_GET_SIZE(u))
-#endif
-#if CYTHON_COMPILING_IN_PYPY
-  #define __Pyx_PyUnicode_Concat(a, b)      PyNumber_Add(a, b)
-  #define __Pyx_PyUnicode_ConcatSafe(a, b)  PyNumber_Add(a, b)
-#else
-  #define __Pyx_PyUnicode_Concat(a, b)      PyUnicode_Concat(a, b)
-  #define __Pyx_PyUnicode_ConcatSafe(a, b)  ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\
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-#define __Pyx_PyString_FormatSafe(a, b)   ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b))
-#define __Pyx_PyUnicode_FormatSafe(a, b)  ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b))
-#if PY_MAJOR_VERSION >= 3
-  #define __Pyx_PyString_Format(a, b)  PyUnicode_Format(a, b)
-#else
-  #define __Pyx_PyString_Format(a, b)  PyString_Format(a, b)
-#endif
-#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII)
-  #define PyObject_ASCII(o)            PyObject_Repr(o)
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-#if PY_MAJOR_VERSION >= 3
-  #define PyBaseString_Type            PyUnicode_Type
-  #define PyStringObject               PyUnicodeObject
-  #define PyString_Type                PyUnicode_Type
-  #define PyString_Check               PyUnicode_Check
-  #define PyString_CheckExact          PyUnicode_CheckExact
-#ifndef PyObject_Unicode
-  #define PyObject_Unicode             PyObject_Str
-#endif
-#endif
-#if PY_MAJOR_VERSION >= 3
-  #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj)
-  #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj)
-#else
-  #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj))
-  #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj))
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-#ifndef PySet_CheckExact
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-#if PY_VERSION_HEX >= 0x030900A4
-  #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt)
-  #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size)
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-  #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt)
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-  #define PyInt_FromString             PyLong_FromString
-  #define PyInt_FromUnicode            PyLong_FromUnicode
-  #define PyInt_FromLong               PyLong_FromLong
-  #define PyInt_FromSize_t             PyLong_FromSize_t
-  #define PyInt_FromSsize_t            PyLong_FromSsize_t
-  #define PyInt_AsLong                 PyLong_AsLong
-  #define PyInt_AS_LONG                PyLong_AS_LONG
-  #define PyInt_AsSsize_t              PyLong_AsSsize_t
-  #define PyInt_AsUnsignedLongMask     PyLong_AsUnsignedLongMask
-  #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask
-  #define PyNumber_Int                 PyNumber_Long
-#endif
-#if PY_MAJOR_VERSION >= 3
-  #define PyBoolObject                 PyLongObject
-#endif
-#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY
-  #ifndef PyUnicode_InternFromString
-    #define PyUnicode_InternFromString(s) PyUnicode_FromString(s)
-  #endif
-#endif
-#if PY_VERSION_HEX < 0x030200A4
-  typedef long Py_hash_t;
-  #define __Pyx_PyInt_FromHash_t PyInt_FromLong
-  #define __Pyx_PyInt_AsHash_t   __Pyx_PyIndex_AsHash_t
-#else
-  #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t
-  #define __Pyx_PyInt_AsHash_t   __Pyx_PyIndex_AsSsize_t
-#endif
-#if PY_MAJOR_VERSION >= 3
-  #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func))
-#else
-  #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass)
-#endif
-#if CYTHON_USE_ASYNC_SLOTS
-  #if PY_VERSION_HEX >= 0x030500B1
-    #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods
-    #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async)
-  #else
-    #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved))
-  #endif
-#else
-  #define __Pyx_PyType_AsAsync(obj) NULL
-#endif
-#ifndef __Pyx_PyAsyncMethodsStruct
-    typedef struct {
-        unaryfunc am_await;
-        unaryfunc am_aiter;
-        unaryfunc am_anext;
-    } __Pyx_PyAsyncMethodsStruct;
-#endif
-
-#if defined(_WIN32) || defined(WIN32) || defined(MS_WINDOWS)
-  #if !defined(_USE_MATH_DEFINES)
-    #define _USE_MATH_DEFINES
-  #endif
-#endif
-#include <math.h>
-#ifdef NAN
-#define __PYX_NAN() ((float) NAN)
-#else
-static CYTHON_INLINE float __PYX_NAN() {
-  float value;
-  memset(&value, 0xFF, sizeof(value));
-  return value;
-}
-#endif
-#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL)
-#define __Pyx_truncl trunc
-#else
-#define __Pyx_truncl truncl
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-
-#define __PYX_MARK_ERR_POS(f_index, lineno) \
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-#define __PYX_ERR(f_index, lineno, Ln_error) \
-    { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; }
-
-#ifndef __PYX_EXTERN_C
-  #ifdef __cplusplus
-    #define __PYX_EXTERN_C extern "C"
-  #else
-    #define __PYX_EXTERN_C extern
-  #endif
-#endif
-
-#define __PYX_HAVE___pydevd_frame_eval__pydevd_frame_evaluator
-#define __PYX_HAVE_API___pydevd_frame_eval__pydevd_frame_evaluator
-/* Early includes */
-#include "frameobject.h"
-#include "release_mem.h"
-#include "code.h"
-#include "pystate.h"
-#if PY_VERSION_HEX >= 0x03080000
-#include "internal/pycore_pystate.h"
-#endif
-
-#include "ceval.h"
-
-#if PY_VERSION_HEX >= 0x03090000
-PyObject * noop(PyFrameObject *frame, int exc) {
-    return NULL;
-}
-#define CALL_EvalFrameDefault_38(a, b)    noop(a, b)
-#define CALL_EvalFrameDefault_39(a, b, c)    _PyEval_EvalFrameDefault(a, b, c)
-#else
-PyObject * noop(PyThreadState* tstate, PyFrameObject *frame, int exc) {
-    return NULL;
-}
-#define CALL_EvalFrameDefault_39(a, b, c)    noop(a, b, c)
-#define CALL_EvalFrameDefault_38(a, b)    _PyEval_EvalFrameDefault(a, b)
-#endif
-    
-#ifdef _OPENMP
-#include <omp.h>
-#endif /* _OPENMP */
-
-#if defined(PYREX_WITHOUT_ASSERTIONS) && !defined(CYTHON_WITHOUT_ASSERTIONS)
-#define CYTHON_WITHOUT_ASSERTIONS
-#endif
-
-typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding;
-                const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry;
-
-#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0
-#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0
-#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8)
-#define __PYX_DEFAULT_STRING_ENCODING ""
-#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString
-#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
-#define __Pyx_uchar_cast(c) ((unsigned char)c)
-#define __Pyx_long_cast(x) ((long)x)
-#define __Pyx_fits_Py_ssize_t(v, type, is_signed)  (\
-    (sizeof(type) < sizeof(Py_ssize_t))  ||\
-    (sizeof(type) > sizeof(Py_ssize_t) &&\
-          likely(v < (type)PY_SSIZE_T_MAX ||\
-                 v == (type)PY_SSIZE_T_MAX)  &&\
-          (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\
-                                v == (type)PY_SSIZE_T_MIN)))  ||\
-    (sizeof(type) == sizeof(Py_ssize_t) &&\
-          (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\
-                               v == (type)PY_SSIZE_T_MAX)))  )
-static CYTHON_INLINE int __Pyx_is_valid_index(Py_ssize_t i, Py_ssize_t limit) {
-    return (size_t) i < (size_t) limit;
-}
-#if defined (__cplusplus) && __cplusplus >= 201103L
-    #include <cstdlib>
-    #define __Pyx_sst_abs(value) std::abs(value)
-#elif SIZEOF_INT >= SIZEOF_SIZE_T
-    #define __Pyx_sst_abs(value) abs(value)
-#elif SIZEOF_LONG >= SIZEOF_SIZE_T
-    #define __Pyx_sst_abs(value) labs(value)
-#elif defined (_MSC_VER)
-    #define __Pyx_sst_abs(value) ((Py_ssize_t)_abs64(value))
-#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
-    #define __Pyx_sst_abs(value) llabs(value)
-#elif defined (__GNUC__)
-    #define __Pyx_sst_abs(value) __builtin_llabs(value)
-#else
-    #define __Pyx_sst_abs(value) ((value<0) ? -value : value)
-#endif
-static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*);
-static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length);
-#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s))
-#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l)
-#define __Pyx_PyBytes_FromString        PyBytes_FromString
-#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize
-static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*);
-#if PY_MAJOR_VERSION < 3
-    #define __Pyx_PyStr_FromString        __Pyx_PyBytes_FromString
-    #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
-#else
-    #define __Pyx_PyStr_FromString        __Pyx_PyUnicode_FromString
-    #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize
-#endif
-#define __Pyx_PyBytes_AsWritableString(s)     ((char*) PyBytes_AS_STRING(s))
-#define __Pyx_PyBytes_AsWritableSString(s)    ((signed char*) PyBytes_AS_STRING(s))
-#define __Pyx_PyBytes_AsWritableUString(s)    ((unsigned char*) PyBytes_AS_STRING(s))
-#define __Pyx_PyBytes_AsString(s)     ((const char*) PyBytes_AS_STRING(s))
-#define __Pyx_PyBytes_AsSString(s)    ((const signed char*) PyBytes_AS_STRING(s))
-#define __Pyx_PyBytes_AsUString(s)    ((const unsigned char*) PyBytes_AS_STRING(s))
-#define __Pyx_PyObject_AsWritableString(s)    ((char*) __Pyx_PyObject_AsString(s))
-#define __Pyx_PyObject_AsWritableSString(s)    ((signed char*) __Pyx_PyObject_AsString(s))
-#define __Pyx_PyObject_AsWritableUString(s)    ((unsigned char*) __Pyx_PyObject_AsString(s))
-#define __Pyx_PyObject_AsSString(s)    ((const signed char*) __Pyx_PyObject_AsString(s))
-#define __Pyx_PyObject_AsUString(s)    ((const unsigned char*) __Pyx_PyObject_AsString(s))
-#define __Pyx_PyObject_FromCString(s)  __Pyx_PyObject_FromString((const char*)s)
-#define __Pyx_PyBytes_FromCString(s)   __Pyx_PyBytes_FromString((const char*)s)
-#define __Pyx_PyByteArray_FromCString(s)   __Pyx_PyByteArray_FromString((const char*)s)
-#define __Pyx_PyStr_FromCString(s)     __Pyx_PyStr_FromString((const char*)s)
-#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s)
-static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) {
-    const Py_UNICODE *u_end = u;
-    while (*u_end++) ;
-    return (size_t)(u_end - u - 1);
-}
-#define __Pyx_PyUnicode_FromUnicode(u)       PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u))
-#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode
-#define __Pyx_PyUnicode_AsUnicode            PyUnicode_AsUnicode
-#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj)
-#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None)
-static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b);
-static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*);
-static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*);
-static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x);
-#define __Pyx_PySequence_Tuple(obj)\
-    (likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj))
-static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*);
-static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t);
-static CYTHON_INLINE Py_hash_t __Pyx_PyIndex_AsHash_t(PyObject*);
-#if CYTHON_ASSUME_SAFE_MACROS
-#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x))
-#else
-#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x)
-#endif
-#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x))
-#if PY_MAJOR_VERSION >= 3
-#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x))
-#else
-#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x))
-#endif
-#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x))
-#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
-static int __Pyx_sys_getdefaultencoding_not_ascii;
-static int __Pyx_init_sys_getdefaultencoding_params(void) {
-    PyObject* sys;
-    PyObject* default_encoding = NULL;
-    PyObject* ascii_chars_u = NULL;
-    PyObject* ascii_chars_b = NULL;
-    const char* default_encoding_c;
-    sys = PyImport_ImportModule("sys");
-    if (!sys) goto bad;
-    default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL);
-    Py_DECREF(sys);
-    if (!default_encoding) goto bad;
-    default_encoding_c = PyBytes_AsString(default_encoding);
-    if (!default_encoding_c) goto bad;
-    if (strcmp(default_encoding_c, "ascii") == 0) {
-        __Pyx_sys_getdefaultencoding_not_ascii = 0;
-    } else {
-        char ascii_chars[128];
-        int c;
-        for (c = 0; c < 128; c++) {
-            ascii_chars[c] = c;
-        }
-        __Pyx_sys_getdefaultencoding_not_ascii = 1;
-        ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL);
-        if (!ascii_chars_u) goto bad;
-        ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL);
-        if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) {
-            PyErr_Format(
-                PyExc_ValueError,
-                "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.",
-                default_encoding_c);
-            goto bad;
-        }
-        Py_DECREF(ascii_chars_u);
-        Py_DECREF(ascii_chars_b);
-    }
-    Py_DECREF(default_encoding);
-    return 0;
-bad:
-    Py_XDECREF(default_encoding);
-    Py_XDECREF(ascii_chars_u);
-    Py_XDECREF(ascii_chars_b);
-    return -1;
-}
-#endif
-#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3
-#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL)
-#else
-#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL)
-#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
-static char* __PYX_DEFAULT_STRING_ENCODING;
-static int __Pyx_init_sys_getdefaultencoding_params(void) {
-    PyObject* sys;
-    PyObject* default_encoding = NULL;
-    char* default_encoding_c;
-    sys = PyImport_ImportModule("sys");
-    if (!sys) goto bad;
-    default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
-    Py_DECREF(sys);
-    if (!default_encoding) goto bad;
-    default_encoding_c = PyBytes_AsString(default_encoding);
-    if (!default_encoding_c) goto bad;
-    __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c) + 1);
-    if (!__PYX_DEFAULT_STRING_ENCODING) goto bad;
-    strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c);
-    Py_DECREF(default_encoding);
-    return 0;
-bad:
-    Py_XDECREF(default_encoding);
-    return -1;
-}
-#endif
-#endif
-
-
-/* Test for GCC > 2.95 */
-#if defined(__GNUC__)     && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95)))
-  #define likely(x)   __builtin_expect(!!(x), 1)
-  #define unlikely(x) __builtin_expect(!!(x), 0)
-#else /* !__GNUC__ or GCC < 2.95 */
-  #define likely(x)   (x)
-  #define unlikely(x) (x)
-#endif /* __GNUC__ */
-static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; }
-
-static PyObject *__pyx_m = NULL;
-static PyObject *__pyx_d;
-static PyObject *__pyx_b;
-static PyObject *__pyx_cython_runtime = NULL;
-static PyObject *__pyx_empty_tuple;
-static PyObject *__pyx_empty_bytes;
-static PyObject *__pyx_empty_unicode;
-static int __pyx_lineno;
-static int __pyx_clineno = 0;
-static const char * __pyx_cfilenm= __FILE__;
-static const char *__pyx_filename;
-
-
-static const char *__pyx_f[] = {
-  "_pydevd_frame_eval/pydevd_frame_evaluator.pyx",
-  "stringsource",
-  "_pydevd_bundle/pydevd_cython.pxd",
-};
-
-/*--- Type declarations ---*/
-struct __pyx_obj_14_pydevd_bundle_13pydevd_cython_PyDBAdditionalThreadInfo;
-struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo;
-struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo;
-struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo;
-struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue;
-
-/* "_pydevd_bundle/pydevd_cython.pxd":1
- * cdef class PyDBAdditionalThreadInfo:             # <<<<<<<<<<<<<<
- *     cdef public int pydev_state
- *     cdef public object pydev_step_stop # Actually, it's a frame or None
- */
-struct __pyx_obj_14_pydevd_bundle_13pydevd_cython_PyDBAdditionalThreadInfo {
-  PyObject_HEAD
-  int pydev_state;
-  PyObject *pydev_step_stop;
-  int pydev_original_step_cmd;
-  int pydev_step_cmd;
-  int pydev_notify_kill;
-  PyObject *pydev_smart_step_stop;
-  int pydev_django_resolve_frame;
-  PyObject *pydev_call_from_jinja2;
-  PyObject *pydev_call_inside_jinja2;
-  int is_tracing;
-  PyObject *conditional_breakpoint_exception;
-  PyObject *pydev_message;
-  int suspend_type;
-  int pydev_next_line;
-  PyObject *pydev_func_name;
-  int suspended_at_unhandled;
-  PyObject *trace_suspend_type;
-  PyObject *top_level_thread_tracer_no_back_frames;
-  PyObject *top_level_thread_tracer_unhandled;
-  PyObject *thread_tracer;
-  PyObject *step_in_initial_location;
-  int pydev_smart_parent_offset;
-  int pydev_smart_child_offset;
-  PyObject *pydev_smart_step_into_variants;
-  PyObject *target_id_to_smart_step_into_variant;
-  int pydev_use_scoped_step_frame;
-};
-
-
-/* "_pydevd_frame_eval/pydevd_frame_evaluator.pyx":24
- * 
- * 
- * cdef class ThreadInfo:             # <<<<<<<<<<<<<<
- * 
- *     cdef public PyDBAdditionalThreadInfo additional_info
- */
-struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo {
-  PyObject_HEAD
-  struct __pyx_vtabstruct_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_vtab;
-  struct __pyx_obj_14_pydevd_bundle_13pydevd_cython_PyDBAdditionalThreadInfo *additional_info;
-  int is_pydevd_thread;
-  int inside_frame_eval;
-  int fully_initialized;
-  PyObject *thread_trace_func;
-  int _can_create_dummy_thread;
-  int force_stay_in_untraced_mode;
-};
-
-
-/* "_pydevd_frame_eval/pydevd_frame_evaluator.pyx":125
- * 
- * 
- * cdef class FuncCodeInfo:             # <<<<<<<<<<<<<<
- * 
- *     cdef public str co_filename
- */
-struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo {
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-    __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\
-    (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\
-               __Pyx_GetItemInt_Generic(o, to_py_func(i))))
-#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
-    (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
-    __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\
-    (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL))
-static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
-                                                              int wraparound, int boundscheck);
-#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
-    (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
-    __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\
-    (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL))
-static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
-                                                              int wraparound, int boundscheck);
-static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j);
-static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
-                                                     int is_list, int wraparound, int boundscheck);
-
-/* RaiseTooManyValuesToUnpack.proto */
-static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected);
-
-/* RaiseNeedMoreValuesToUnpack.proto */
-static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index);
-
-/* IterFinish.proto */
-static CYTHON_INLINE int __Pyx_IterFinish(void);
-
-/* UnpackItemEndCheck.proto */
-static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected);
-
-/* PySequenceContains.proto */
-static CYTHON_INLINE int __Pyx_PySequence_ContainsTF(PyObject* item, PyObject* seq, int eq) {
-    int result = PySequence_Contains(seq, item);
-    return unlikely(result < 0) ? result : (result == (eq == Py_EQ));
-}
-
-/* PyObjectGetMethod.proto */
-static int __Pyx_PyObject_GetMethod(PyObject *obj, PyObject *name, PyObject **method);
-
-/* PyObjectCallMethod0.proto */
-static PyObject* __Pyx_PyObject_CallMethod0(PyObject* obj, PyObject* method_name);
-
-/* RaiseNoneIterError.proto */
-static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void);
-
-/* UnpackTupleError.proto */
-static void __Pyx_UnpackTupleError(PyObject *, Py_ssize_t index);
-
-/* UnpackTuple2.proto */
-#define __Pyx_unpack_tuple2(tuple, value1, value2, is_tuple, has_known_size, decref_tuple)\
-    (likely(is_tuple || PyTuple_Check(tuple)) ?\
-        (likely(has_known_size || PyTuple_GET_SIZE(tuple) == 2) ?\
-            __Pyx_unpack_tuple2_exact(tuple, value1, value2, decref_tuple) :\
-            (__Pyx_UnpackTupleError(tuple, 2), -1)) :\
-        __Pyx_unpack_tuple2_generic(tuple, value1, value2, has_known_size, decref_tuple))
-static CYTHON_INLINE int __Pyx_unpack_tuple2_exact(
-    PyObject* tuple, PyObject** value1, PyObject** value2, int decref_tuple);
-static int __Pyx_unpack_tuple2_generic(
-    PyObject* tuple, PyObject** value1, PyObject** value2, int has_known_size, int decref_tuple);
-
-/* dict_iter.proto */
-static CYTHON_INLINE PyObject* __Pyx_dict_iterator(PyObject* dict, int is_dict, PyObject* method_name,
-                                                   Py_ssize_t* p_orig_length, int* p_is_dict);
-static CYTHON_INLINE int __Pyx_dict_iter_next(PyObject* dict_or_iter, Py_ssize_t orig_length, Py_ssize_t* ppos,
-                                              PyObject** pkey, PyObject** pvalue, PyObject** pitem, int is_dict);
-
-/* PyDictContains.proto */
-static CYTHON_INLINE int __Pyx_PyDict_ContainsTF(PyObject* item, PyObject* dict, int eq) {
-    int result = PyDict_Contains(dict, item);
-    return unlikely(result < 0) ? result : (result == (eq == Py_EQ));
-}
-
-/* WriteUnraisableException.proto */
-static void __Pyx_WriteUnraisable(const char *name, int clineno,
-                                  int lineno, const char *filename,
-                                  int full_traceback, int nogil);
-
-/* Import.proto */
-static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level);
-
-/* ImportFrom.proto */
-static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name);
-
-/* HasAttr.proto */
-static CYTHON_INLINE int __Pyx_HasAttr(PyObject *, PyObject *);
-
-/* PyObject_GenericGetAttrNoDict.proto */
-#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000
-static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name);
-#else
-#define __Pyx_PyObject_GenericGetAttrNoDict PyObject_GenericGetAttr
-#endif
-
-/* PyObject_GenericGetAttr.proto */
-#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000
-static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name);
-#else
-#define __Pyx_PyObject_GenericGetAttr PyObject_GenericGetAttr
-#endif
-
-/* SetVTable.proto */
-static int __Pyx_SetVtable(PyObject *dict, void *vtable);
-
-/* PyObjectGetAttrStrNoError.proto */
-static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name);
-
-/* SetupReduce.proto */
-static int __Pyx_setup_reduce(PyObject* type_obj);
-
-/* TypeImport.proto */
-#ifndef __PYX_HAVE_RT_ImportType_proto
-#define __PYX_HAVE_RT_ImportType_proto
-enum __Pyx_ImportType_CheckSize {
-   __Pyx_ImportType_CheckSize_Error = 0,
-   __Pyx_ImportType_CheckSize_Warn = 1,
-   __Pyx_ImportType_CheckSize_Ignore = 2
-};
-static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size);
-#endif
-
-/* CLineInTraceback.proto */
-#ifdef CYTHON_CLINE_IN_TRACEBACK
-#define __Pyx_CLineForTraceback(tstate, c_line)  (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0)
-#else
-static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line);
-#endif
-
-/* CodeObjectCache.proto */
-typedef struct {
-    PyCodeObject* code_object;
-    int code_line;
-} __Pyx_CodeObjectCacheEntry;
-struct __Pyx_CodeObjectCache {
-    int count;
-    int max_count;
-    __Pyx_CodeObjectCacheEntry* entries;
-};
-static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL};
-static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line);
-static PyCodeObject *__pyx_find_code_object(int code_line);
-static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object);
-
-/* AddTraceback.proto */
-static void __Pyx_AddTraceback(const char *funcname, int c_line,
-                               int py_line, const char *filename);
-
-/* GCCDiagnostics.proto */
-#if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6))
-#define __Pyx_HAS_GCC_DIAGNOSTIC
-#endif
-
-/* CIntToPy.proto */
-static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value);
-
-/* CIntFromPy.proto */
-static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *);
-
-/* CIntFromPy.proto */
-static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *);
-
-/* CIntToPy.proto */
-static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value);
-
-/* FastTypeChecks.proto */
-#if CYTHON_COMPILING_IN_CPYTHON
-#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type)
-static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b);
-static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type);
-static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2);
-#else
-#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type)
-#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type)
-#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2))
-#endif
-#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception)
-
-/* CheckBinaryVersion.proto */
-static int __Pyx_check_binary_version(void);
-
-/* InitStrings.proto */
-static int __Pyx_InitStrings(__Pyx_StringTabEntry *t);
-
-static PyObject *__pyx_f_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_initialize(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self, PyFrameObject *__pyx_v_frame_obj); /* proto*/
-static PyObject *__pyx_f_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_initialize_if_possible(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self); /* proto*/
-static PyObject *__pyx_f_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_compute_force_stay_in_untraced_mode(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue *__pyx_v_self, PyObject *__pyx_v_breakpoints, int __pyx_skip_dispatch); /* proto*/
-
-/* Module declarations from 'cpython.mem' */
-
-/* Module declarations from '_pydevd_bundle.pydevd_cython' */
-static PyTypeObject *__pyx_ptype_14_pydevd_bundle_13pydevd_cython_PyDBAdditionalThreadInfo = 0;
-
-/* Module declarations from '_pydevd_frame_eval.pydevd_frame_evaluator' */
-static PyTypeObject *__pyx_ptype_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo = 0;
-static PyTypeObject *__pyx_ptype_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo = 0;
-static PyTypeObject *__pyx_ptype_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo = 0;
-static PyTypeObject *__pyx_ptype_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue = 0;
-static int __pyx_v_18_pydevd_frame_eval_22pydevd_frame_evaluator__code_extra_index;
-static int __pyx_v_18_pydevd_frame_eval_22pydevd_frame_evaluator_IS_PY_39_OWNARDS;
-static struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_f_18_pydevd_frame_eval_22pydevd_frame_evaluator_get_thread_info(PyFrameObject *); /*proto*/
-static struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_f_18_pydevd_frame_eval_22pydevd_frame_evaluator_get_func_code_info(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *, PyFrameObject *, PyCodeObject *); /*proto*/
-static PyObject *__pyx_f_18_pydevd_frame_eval_22pydevd_frame_evaluator_generate_code_with_breakpoints(PyObject *, PyObject *); /*proto*/
-static PyObject *__pyx_f_18_pydevd_frame_eval_22pydevd_frame_evaluator_get_bytecode_while_frame_eval_38(PyFrameObject *, int); /*proto*/
-static PyObject *__pyx_f_18_pydevd_frame_eval_22pydevd_frame_evaluator_get_bytecode_while_frame_eval_39(PyThreadState *, PyFrameObject *, int); /*proto*/
-static PyObject *__pyx_f_18_pydevd_frame_eval_22pydevd_frame_evaluator___pyx_unpickle_ThreadInfo__set_state(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *, PyObject *); /*proto*/
-static PyObject *__pyx_f_18_pydevd_frame_eval_22pydevd_frame_evaluator___pyx_unpickle_FuncCodeInfo__set_state(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *, PyObject *); /*proto*/
-static PyObject *__pyx_f_18_pydevd_frame_eval_22pydevd_frame_evaluator___pyx_unpickle__CodeLineInfo__set_state(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *, PyObject *); /*proto*/
-static PyObject *__pyx_f_18_pydevd_frame_eval_22pydevd_frame_evaluator___pyx_unpickle__CacheValue__set_state(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue *, PyObject *); /*proto*/
-#define __Pyx_MODULE_NAME "_pydevd_frame_eval.pydevd_frame_evaluator"
-extern int __pyx_module_is_main__pydevd_frame_eval__pydevd_frame_evaluator;
-int __pyx_module_is_main__pydevd_frame_eval__pydevd_frame_evaluator = 0;
-
-/* Implementation of '_pydevd_frame_eval.pydevd_frame_evaluator' */
-static PyObject *__pyx_builtin_AttributeError;
-static PyObject *__pyx_builtin_min;
-static PyObject *__pyx_builtin_max;
-static const char __pyx_k_[] = "/";
-static const char __pyx_k__2[] = "\\";
-static const char __pyx_k__3[] = ".";
-static const char __pyx_k__5[] = "";
-static const char __pyx_k_arg[] = "arg";
-static const char __pyx_k_dis[] = "dis";
-static const char __pyx_k_get[] = "get";
-static const char __pyx_k_max[] = "max";
-static const char __pyx_k_min[] = "min";
-static const char __pyx_k_new[] = "__new__";
-static const char __pyx_k_obj[] = "obj";
-static const char __pyx_k_run[] = "run";
-static const char __pyx_k_sys[] = "sys";
-static const char __pyx_k_call[] = "__call__";
-static const char __pyx_k_dict[] = "__dict__";
-static const char __pyx_k_exec[] = "_exec";
-static const char __pyx_k_exit[] = "__exit__";
-static const char __pyx_k_line[] = "line";
-static const char __pyx_k_main[] = "main";
-static const char __pyx_k_name[] = "__name__";
-static const char __pyx_k_test[] = "__test__";
-static const char __pyx_k_cache[] = "_cache";
-static const char __pyx_k_enter[] = "__enter__";
-static const char __pyx_k_event[] = "event";
-static const char __pyx_k_frame[] = "frame";
-static const char __pyx_k_local[] = "local";
-static const char __pyx_k_mtime[] = "mtime";
-static const char __pyx_k_rfind[] = "rfind";
-static const char __pyx_k_state[] = "state";
-static const char __pyx_k_active[] = "_active";
-static const char __pyx_k_call_2[] = "call";
-static const char __pyx_k_f_back[] = "f_back";
-static const char __pyx_k_import[] = "__import__";
-static const char __pyx_k_main_2[] = "__main__";
-static const char __pyx_k_offset[] = "offset";
-static const char __pyx_k_pickle[] = "pickle";
-static const char __pyx_k_plugin[] = "plugin";
-static const char __pyx_k_pydevd[] = "pydevd";
-static const char __pyx_k_reduce[] = "__reduce__";
-static const char __pyx_k_thread[] = "thread";
-static const char __pyx_k_update[] = "update";
-static const char __pyx_k_f_trace[] = "f_trace";
-static const char __pyx_k_SetTrace[] = "SetTrace";
-static const char __pyx_k_can_skip[] = "can_skip";
-static const char __pyx_k_code_obj[] = "code_obj";
-static const char __pyx_k_getstate[] = "__getstate__";
-static const char __pyx_k_pyx_type[] = "__pyx_type";
-static const char __pyx_k_setstate[] = "__setstate__";
-static const char __pyx_k_bootstrap[] = "__bootstrap";
-static const char __pyx_k_decref_py[] = "decref_py";
-static const char __pyx_k_get_ident[] = "_get_ident";
-static const char __pyx_k_last_line[] = "last_line";
-static const char __pyx_k_pyx_state[] = "__pyx_state";
-static const char __pyx_k_reduce_ex[] = "__reduce_ex__";
-static const char __pyx_k_threading[] = "threading";
-static const char __pyx_k_CacheValue[] = "_CacheValue";
-static const char __pyx_k_ThreadInfo[] = "ThreadInfo";
-static const char __pyx_k_first_line[] = "first_line";
-static const char __pyx_k_global_dbg[] = "global_dbg";
-static const char __pyx_k_issuperset[] = "issuperset";
-static const char __pyx_k_pyx_result[] = "__pyx_result";
-static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__";
-static const char __pyx_k_DebugHelper[] = "DebugHelper";
-static const char __pyx_k_PickleError[] = "PickleError";
-static const char __pyx_k_bootstrap_2[] = "_bootstrap";
-static const char __pyx_k_breakpoints[] = "breakpoints";
-static const char __pyx_k_code_obj_py[] = "code_obj_py";
-static const char __pyx_k_get_ident_2[] = "get_ident";
-static const char __pyx_k_thread_info[] = "thread_info";
-static const char __pyx_k_CodeLineInfo[] = "_CodeLineInfo";
-static const char __pyx_k_FuncCodeInfo[] = "FuncCodeInfo";
-static const char __pyx_k_intersection[] = "intersection";
-static const char __pyx_k_pydev_monkey[] = "pydev_monkey";
-static const char __pyx_k_pyx_checksum[] = "__pyx_checksum";
-static const char __pyx_k_stringsource[] = "stringsource";
-static const char __pyx_k_version_info[] = "version_info";
-static const char __pyx_k_get_file_type[] = "get_file_type";
-static const char __pyx_k_reduce_cython[] = "__reduce_cython__";
-static const char __pyx_k_thread_active[] = "_thread_active";
-static const char __pyx_k_AttributeError[] = "AttributeError";
-static const char __pyx_k_code_line_info[] = "code_line_info";
-static const char __pyx_k_current_thread[] = "current_thread";
-static const char __pyx_k_findlinestarts[] = "findlinestarts";
-static const char __pyx_k_line_to_offset[] = "line_to_offset";
-static const char __pyx_k_pydevd_tracing[] = "pydevd_tracing";
-static const char __pyx_k_set_trace_func[] = "set_trace_func";
-static const char __pyx_k_trace_dispatch[] = "trace_dispatch";
-static const char __pyx_k_additional_info[] = "additional_info";
-static const char __pyx_k_bootstrap_inner[] = "__bootstrap_inner";
-static const char __pyx_k_frame_eval_func[] = "frame_eval_func";
-static const char __pyx_k_pyx_PickleError[] = "__pyx_PickleError";
-static const char __pyx_k_setstate_cython[] = "__setstate_cython__";
-static const char __pyx_k_stop_frame_eval[] = "stop_frame_eval";
-static const char __pyx_k_bootstrap_inner_2[] = "_bootstrap_inner";
-static const char __pyx_k_pydevd_file_utils[] = "pydevd_file_utils";
-static const char __pyx_k_signature_factory[] = "signature_factory";
-static const char __pyx_k_thread_local_info[] = "_thread_local_info";
-static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback";
-static const char __pyx_k_get_code_line_info[] = "_get_code_line_info";
-static const char __pyx_k_get_thread_info_py[] = "get_thread_info_py";
-static const char __pyx_k_show_return_values[] = "show_return_values";
-static const char __pyx_k_get_cache_file_type[] = "get_cache_file_type";
-static const char __pyx_k_update_globals_dict[] = "update_globals_dict";
-static const char __pyx_k_GlobalDebuggerHolder[] = "GlobalDebuggerHolder";
-static const char __pyx_k_dummy_trace_dispatch[] = "dummy_trace_dispatch";
-static const char __pyx_k_dummy_tracing_holder[] = "dummy_tracing_holder";
-static const char __pyx_k_insert_pydevd_breaks[] = "insert_pydevd_breaks";
-static const char __pyx_k_get_func_code_info_py[] = "get_func_code_info_py";
-static const char __pyx_k_has_plugin_line_breaks[] = "has_plugin_line_breaks";
-static const char __pyx_k_is_pydev_daemon_thread[] = "is_pydev_daemon_thread";
-static const char __pyx_k_clear_thread_local_info[] = "clear_thread_local_info";
-static const char __pyx_k_pyx_unpickle_ThreadInfo[] = "__pyx_unpickle_ThreadInfo";
-static const char __pyx_k_breakpoints_hit_at_lines[] = "breakpoints_hit_at_lines";
-static const char __pyx_k_pyx_unpickle__CacheValue[] = "__pyx_unpickle__CacheValue";
-static const char __pyx_k_pyx_unpickle_FuncCodeInfo[] = "__pyx_unpickle_FuncCodeInfo";
-static const char __pyx_k_break_on_caught_exceptions[] = "break_on_caught_exceptions";
-static const char __pyx_k_pyx_unpickle__CodeLineInfo[] = "__pyx_unpickle__CodeLineInfo";
-static const char __pyx_k_get_cached_code_obj_info_py[] = "get_cached_code_obj_info_py";
-static const char __pyx_k_has_plugin_exception_breaks[] = "has_plugin_exception_breaks";
-static const char __pyx_k_NORM_PATHS_AND_BASE_CONTAINER[] = "NORM_PATHS_AND_BASE_CONTAINER";
-static const char __pyx_k_pydevd_bundle_pydevd_constants[] = "_pydevd_bundle.pydevd_constants";
-static const char __pyx_k_pydevd_frame_eval_pydevd_frame[] = "_pydevd_frame_eval.pydevd_frame_tracing";
-static const char __pyx_k_If_a_code_object_is_cached_that[] = "If a code object is cached, that same code object must be reused.";
-static const char __pyx_k_get_abs_path_real_path_and_base[] = "get_abs_path_real_path_and_base_from_frame";
-static const char __pyx_k_pydev_bundle__pydev_saved_modul[] = "_pydev_bundle._pydev_saved_modules";
-static const char __pyx_k_pydevd_bundle_pydevd_additional[] = "_pydevd_bundle.pydevd_additional_thread_info";
-static const char __pyx_k_pydevd_bundle_pydevd_trace_disp[] = "_pydevd_bundle.pydevd_trace_dispatch";
-static const char __pyx_k_pydevd_frame_eval_pydevd_modify[] = "_pydevd_frame_eval.pydevd_modify_bytecode";
-static const char __pyx_k_set_additional_thread_info_lock[] = "_set_additional_thread_info_lock";
-static const char __pyx_k_Incompatible_checksums_0x_x_vs_0[] = "Incompatible checksums (0x%x vs (0x0af4089, 0xe535b68, 0xb8148ba) = (_can_create_dummy_thread, additional_info, force_stay_in_untraced_mode, fully_initialized, inside_frame_eval, is_pydevd_thread, thread_trace_func))";
-static const char __pyx_k_break_on_user_uncaught_exception[] = "break_on_user_uncaught_exceptions";
-static const char __pyx_k_compute_force_stay_in_untraced_m[] = "compute_force_stay_in_untraced_mode";
-static const char __pyx_k_fix_top_level_trace_and_get_trac[] = "fix_top_level_trace_and_get_trace_func";
-static const char __pyx_k_function_breakpoint_name_to_brea[] = "function_breakpoint_name_to_breakpoint";
-static const char __pyx_k_generate_code_with_breakpoints_p[] = "generate_code_with_breakpoints_py";
-static const char __pyx_k_pydevd_frame_eval_pydevd_frame_2[] = "_pydevd_frame_eval/pydevd_frame_evaluator.pyx";
-static const char __pyx_k_pydevd_frame_eval_pydevd_frame_3[] = "_pydevd_frame_eval.pydevd_frame_evaluator";
-static const char __pyx_k_Incompatible_checksums_0x_x_vs_0_2[] = "Incompatible checksums (0x%x vs (0xb3ee05d, 0x450d2d6, 0x956dcaa) = (always_skip_code, breakpoint_found, breakpoints_mtime, canonical_normalized_filename, co_filename, co_name, new_code))";
-static const char __pyx_k_Incompatible_checksums_0x_x_vs_0_3[] = "Incompatible checksums (0x%x vs (0x3fbbd02, 0x5a9bcd5, 0x0267473) = (first_line, last_line, line_to_offset))";
-static const char __pyx_k_Incompatible_checksums_0x_x_vs_0_4[] = "Incompatible checksums (0x%x vs (0x3d481b9, 0xac42a46, 0xedff7c3) = (breakpoints_hit_at_lines, code_line_info, code_lines_as_set, code_obj_py))";
-static PyObject *__pyx_kp_s_;
-static PyObject *__pyx_n_s_AttributeError;
-static PyObject *__pyx_n_s_CacheValue;
-static PyObject *__pyx_n_s_CodeLineInfo;
-static PyObject *__pyx_n_s_DebugHelper;
-static PyObject *__pyx_n_s_FuncCodeInfo;
-static PyObject *__pyx_n_s_GlobalDebuggerHolder;
-static PyObject *__pyx_kp_s_If_a_code_object_is_cached_that;
-static PyObject *__pyx_kp_s_Incompatible_checksums_0x_x_vs_0;
-static PyObject *__pyx_kp_s_Incompatible_checksums_0x_x_vs_0_2;
-static PyObject *__pyx_kp_s_Incompatible_checksums_0x_x_vs_0_3;
-static PyObject *__pyx_kp_s_Incompatible_checksums_0x_x_vs_0_4;
-static PyObject *__pyx_n_s_NORM_PATHS_AND_BASE_CONTAINER;
-static PyObject *__pyx_n_s_PickleError;
-static PyObject *__pyx_n_s_SetTrace;
-static PyObject *__pyx_n_s_ThreadInfo;
-static PyObject *__pyx_kp_s__2;
-static PyObject *__pyx_kp_s__3;
-static PyObject *__pyx_kp_s__5;
-static PyObject *__pyx_n_s_active;
-static PyObject *__pyx_n_s_additional_info;
-static PyObject *__pyx_n_s_arg;
-static PyObject *__pyx_n_s_bootstrap;
-static PyObject *__pyx_n_s_bootstrap_2;
-static PyObject *__pyx_n_s_bootstrap_inner;
-static PyObject *__pyx_n_s_bootstrap_inner_2;
-static PyObject *__pyx_n_s_break_on_caught_exceptions;
-static PyObject *__pyx_n_s_break_on_user_uncaught_exception;
-static PyObject *__pyx_n_s_breakpoints;
-static PyObject *__pyx_n_s_breakpoints_hit_at_lines;
-static PyObject *__pyx_n_s_cache;
-static PyObject *__pyx_n_s_call;
-static PyObject *__pyx_n_s_call_2;
-static PyObject *__pyx_n_s_can_skip;
-static PyObject *__pyx_n_s_clear_thread_local_info;
-static PyObject *__pyx_n_s_cline_in_traceback;
-static PyObject *__pyx_n_s_code_line_info;
-static PyObject *__pyx_n_s_code_obj;
-static PyObject *__pyx_n_s_code_obj_py;
-static PyObject *__pyx_n_s_compute_force_stay_in_untraced_m;
-static PyObject *__pyx_n_s_current_thread;
-static PyObject *__pyx_n_s_decref_py;
-static PyObject *__pyx_n_s_dict;
-static PyObject *__pyx_n_s_dis;
-static PyObject *__pyx_n_s_dummy_trace_dispatch;
-static PyObject *__pyx_n_s_dummy_tracing_holder;
-static PyObject *__pyx_n_s_enter;
-static PyObject *__pyx_n_s_event;
-static PyObject *__pyx_n_s_exec;
-static PyObject *__pyx_n_s_exit;
-static PyObject *__pyx_n_s_f_back;
-static PyObject *__pyx_n_s_f_trace;
-static PyObject *__pyx_n_s_findlinestarts;
-static PyObject *__pyx_n_s_first_line;
-static PyObject *__pyx_n_s_fix_top_level_trace_and_get_trac;
-static PyObject *__pyx_n_s_frame;
-static PyObject *__pyx_n_s_frame_eval_func;
-static PyObject *__pyx_n_s_function_breakpoint_name_to_brea;
-static PyObject *__pyx_n_s_generate_code_with_breakpoints_p;
-static PyObject *__pyx_n_s_get;
-static PyObject *__pyx_n_s_get_abs_path_real_path_and_base;
-static PyObject *__pyx_n_s_get_cache_file_type;
-static PyObject *__pyx_n_s_get_cached_code_obj_info_py;
-static PyObject *__pyx_n_s_get_code_line_info;
-static PyObject *__pyx_n_s_get_file_type;
-static PyObject *__pyx_n_s_get_func_code_info_py;
-static PyObject *__pyx_n_s_get_ident;
-static PyObject *__pyx_n_s_get_ident_2;
-static PyObject *__pyx_n_s_get_thread_info_py;
-static PyObject *__pyx_n_s_getstate;
-static PyObject *__pyx_n_s_global_dbg;
-static PyObject *__pyx_n_s_has_plugin_exception_breaks;
-static PyObject *__pyx_n_s_has_plugin_line_breaks;
-static PyObject *__pyx_n_s_import;
-static PyObject *__pyx_n_s_insert_pydevd_breaks;
-static PyObject *__pyx_n_s_intersection;
-static PyObject *__pyx_n_s_is_pydev_daemon_thread;
-static PyObject *__pyx_n_s_issuperset;
-static PyObject *__pyx_n_s_last_line;
-static PyObject *__pyx_n_s_line;
-static PyObject *__pyx_n_s_line_to_offset;
-static PyObject *__pyx_n_s_local;
-static PyObject *__pyx_n_s_main;
-static PyObject *__pyx_n_s_main_2;
-static PyObject *__pyx_n_s_max;
-static PyObject *__pyx_n_s_min;
-static PyObject *__pyx_n_s_mtime;
-static PyObject *__pyx_n_s_name;
-static PyObject *__pyx_n_s_new;
-static PyObject *__pyx_n_s_obj;
-static PyObject *__pyx_n_s_offset;
-static PyObject *__pyx_n_s_pickle;
-static PyObject *__pyx_n_s_plugin;
-static PyObject *__pyx_n_s_pydev_bundle__pydev_saved_modul;
-static PyObject *__pyx_n_s_pydev_monkey;
-static PyObject *__pyx_n_s_pydevd;
-static PyObject *__pyx_n_s_pydevd_bundle_pydevd_additional;
-static PyObject *__pyx_n_s_pydevd_bundle_pydevd_constants;
-static PyObject *__pyx_n_s_pydevd_bundle_pydevd_trace_disp;
-static PyObject *__pyx_n_s_pydevd_file_utils;
-static PyObject *__pyx_n_s_pydevd_frame_eval_pydevd_frame;
-static PyObject *__pyx_kp_s_pydevd_frame_eval_pydevd_frame_2;
-static PyObject *__pyx_n_s_pydevd_frame_eval_pydevd_frame_3;
-static PyObject *__pyx_n_s_pydevd_frame_eval_pydevd_modify;
-static PyObject *__pyx_n_s_pydevd_tracing;
-static PyObject *__pyx_n_s_pyx_PickleError;
-static PyObject *__pyx_n_s_pyx_checksum;
-static PyObject *__pyx_n_s_pyx_result;
-static PyObject *__pyx_n_s_pyx_state;
-static PyObject *__pyx_n_s_pyx_type;
-static PyObject *__pyx_n_s_pyx_unpickle_FuncCodeInfo;
-static PyObject *__pyx_n_s_pyx_unpickle_ThreadInfo;
-static PyObject *__pyx_n_s_pyx_unpickle__CacheValue;
-static PyObject *__pyx_n_s_pyx_unpickle__CodeLineInfo;
-static PyObject *__pyx_n_s_pyx_vtable;
-static PyObject *__pyx_n_s_reduce;
-static PyObject *__pyx_n_s_reduce_cython;
-static PyObject *__pyx_n_s_reduce_ex;
-static PyObject *__pyx_n_s_rfind;
-static PyObject *__pyx_n_s_run;
-static PyObject *__pyx_n_s_set_additional_thread_info_lock;
-static PyObject *__pyx_n_s_set_trace_func;
-static PyObject *__pyx_n_s_setstate;
-static PyObject *__pyx_n_s_setstate_cython;
-static PyObject *__pyx_n_s_show_return_values;
-static PyObject *__pyx_n_s_signature_factory;
-static PyObject *__pyx_n_s_state;
-static PyObject *__pyx_n_s_stop_frame_eval;
-static PyObject *__pyx_kp_s_stringsource;
-static PyObject *__pyx_n_s_sys;
-static PyObject *__pyx_n_s_test;
-static PyObject *__pyx_n_s_thread;
-static PyObject *__pyx_n_s_thread_active;
-static PyObject *__pyx_n_s_thread_info;
-static PyObject *__pyx_n_s_thread_local_info;
-static PyObject *__pyx_n_s_threading;
-static PyObject *__pyx_n_s_trace_dispatch;
-static PyObject *__pyx_n_s_update;
-static PyObject *__pyx_n_s_update_globals_dict;
-static PyObject *__pyx_n_s_version_info;
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_clear_thread_local_info(CYTHON_UNUSED PyObject *__pyx_self); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_15additional_info___get__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_15additional_info_2__set__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_15additional_info_4__del__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_16is_pydevd_thread___get__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_16is_pydevd_thread_2__set__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_17inside_frame_eval___get__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_17inside_frame_eval_2__set__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_17fully_initialized___get__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_17fully_initialized_2__set__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_17thread_trace_func___get__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_17thread_trace_func_2__set__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_17thread_trace_func_4__del__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_27force_stay_in_untraced_mode___get__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_27force_stay_in_untraced_mode_2__set__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo___reduce_cython__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_2__setstate_cython__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo___init__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_11co_filename___get__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_11co_filename_2__set__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_11co_filename_4__del__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_7co_name___get__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_7co_name_2__set__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_7co_name_4__del__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_29canonical_normalized_filename___get__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_29canonical_normalized_filename_2__set__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_29canonical_normalized_filename_4__del__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_16breakpoint_found___get__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_16breakpoint_found_2__set__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_8new_code___get__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_8new_code_2__set__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_8new_code_4__del__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_17breakpoints_mtime___get__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_17breakpoints_mtime_2__set__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_2__reduce_cython__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_4__setstate_cython__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_2dummy_trace_dispatch(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_frame, PyObject *__pyx_v_event, PyObject *__pyx_v_arg); /* proto */
-static struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_4get_thread_info_py(CYTHON_UNUSED PyObject *__pyx_self); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_6decref_py(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_obj); /* proto */
-static struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_8get_func_code_info_py(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_thread_info, PyObject *__pyx_v_frame, PyObject *__pyx_v_code_obj); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo___init__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *__pyx_v_self, PyObject *__pyx_v_line_to_offset, int __pyx_v_first_line, int __pyx_v_last_line); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_14line_to_offset___get__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *__pyx_v_self); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_14line_to_offset_2__set__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_14line_to_offset_4__del__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *__pyx_v_self); /* proto */
-static PyObject *__pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_10first_line___get__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *__pyx_v_self); /* proto */
-static int __pyx_pf_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_10first_line_2__set__(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
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-  p = ((struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *)o);
-  p->__pyx_vtab = __pyx_vtabptr_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo;
-  p->additional_info = ((struct __pyx_obj_14_pydevd_bundle_13pydevd_cython_PyDBAdditionalThreadInfo *)Py_None); Py_INCREF(Py_None);
-  p->thread_trace_func = Py_None; Py_INCREF(Py_None);
-  return o;
-}
-
-static void __pyx_tp_dealloc_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo(PyObject *o) {
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *p = (struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *)o;
-  #if CYTHON_USE_TP_FINALIZE
-  if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
-    if (PyObject_CallFinalizerFromDealloc(o)) return;
-  }
-  #endif
-  PyObject_GC_UnTrack(o);
-  Py_CLEAR(p->additional_info);
-  Py_CLEAR(p->thread_trace_func);
-  (*Py_TYPE(o)->tp_free)(o);
-}
-
-static int __pyx_tp_traverse_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo(PyObject *o, visitproc v, void *a) {
-  int e;
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *p = (struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *)o;
-  if (p->additional_info) {
-    e = (*v)(((PyObject *)p->additional_info), a); if (e) return e;
-  }
-  if (p->thread_trace_func) {
-    e = (*v)(p->thread_trace_func, a); if (e) return e;
-  }
-  return 0;
-}
-
-static int __pyx_tp_clear_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo(PyObject *o) {
-  PyObject* tmp;
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *p = (struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo *)o;
-  tmp = ((PyObject*)p->additional_info);
-  p->additional_info = ((struct __pyx_obj_14_pydevd_bundle_13pydevd_cython_PyDBAdditionalThreadInfo *)Py_None); Py_INCREF(Py_None);
-  Py_XDECREF(tmp);
-  tmp = ((PyObject*)p->thread_trace_func);
-  p->thread_trace_func = Py_None; Py_INCREF(Py_None);
-  Py_XDECREF(tmp);
-  return 0;
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_additional_info(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_15additional_info_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_additional_info(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_15additional_info_3__set__(o, v);
-  }
-  else {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_15additional_info_5__del__(o);
-  }
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_is_pydevd_thread(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_16is_pydevd_thread_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_is_pydevd_thread(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_16is_pydevd_thread_3__set__(o, v);
-  }
-  else {
-    PyErr_SetString(PyExc_NotImplementedError, "__del__");
-    return -1;
-  }
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_inside_frame_eval(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_17inside_frame_eval_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_inside_frame_eval(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_17inside_frame_eval_3__set__(o, v);
-  }
-  else {
-    PyErr_SetString(PyExc_NotImplementedError, "__del__");
-    return -1;
-  }
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_fully_initialized(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_17fully_initialized_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_fully_initialized(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_17fully_initialized_3__set__(o, v);
-  }
-  else {
-    PyErr_SetString(PyExc_NotImplementedError, "__del__");
-    return -1;
-  }
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_thread_trace_func(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_17thread_trace_func_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_thread_trace_func(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_17thread_trace_func_3__set__(o, v);
-  }
-  else {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_17thread_trace_func_5__del__(o);
-  }
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_force_stay_in_untraced_mode(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_27force_stay_in_untraced_mode_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_force_stay_in_untraced_mode(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_27force_stay_in_untraced_mode_3__set__(o, v);
-  }
-  else {
-    PyErr_SetString(PyExc_NotImplementedError, "__del__");
-    return -1;
-  }
-}
-
-static PyMethodDef __pyx_methods_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo[] = {
-  {"__reduce_cython__", (PyCFunction)__pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_1__reduce_cython__, METH_NOARGS, 0},
-  {"__setstate_cython__", (PyCFunction)__pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_3__setstate_cython__, METH_O, 0},
-  {0, 0, 0, 0}
-};
-
-static struct PyGetSetDef __pyx_getsets_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo[] = {
-  {(char *)"additional_info", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_additional_info, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_additional_info, (char *)0, 0},
-  {(char *)"is_pydevd_thread", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_is_pydevd_thread, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_is_pydevd_thread, (char *)0, 0},
-  {(char *)"inside_frame_eval", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_inside_frame_eval, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_inside_frame_eval, (char *)0, 0},
-  {(char *)"fully_initialized", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_fully_initialized, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_fully_initialized, (char *)0, 0},
-  {(char *)"thread_trace_func", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_thread_trace_func, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_thread_trace_func, (char *)0, 0},
-  {(char *)"force_stay_in_untraced_mode", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_force_stay_in_untraced_mode, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_10ThreadInfo_force_stay_in_untraced_mode, (char *)0, 0},
-  {0, 0, 0, 0, 0}
-};
-
-static PyTypeObject __pyx_type_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo = {
-  PyVarObject_HEAD_INIT(0, 0)
-  "_pydevd_frame_eval.pydevd_frame_evaluator.ThreadInfo", /*tp_name*/
-  sizeof(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo), /*tp_basicsize*/
-  0, /*tp_itemsize*/
-  __pyx_tp_dealloc_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo, /*tp_dealloc*/
-  #if PY_VERSION_HEX < 0x030800b4
-  0, /*tp_print*/
-  #endif
-  #if PY_VERSION_HEX >= 0x030800b4
-  0, /*tp_vectorcall_offset*/
-  #endif
-  0, /*tp_getattr*/
-  0, /*tp_setattr*/
-  #if PY_MAJOR_VERSION < 3
-  0, /*tp_compare*/
-  #endif
-  #if PY_MAJOR_VERSION >= 3
-  0, /*tp_as_async*/
-  #endif
-  0, /*tp_repr*/
-  0, /*tp_as_number*/
-  0, /*tp_as_sequence*/
-  0, /*tp_as_mapping*/
-  0, /*tp_hash*/
-  0, /*tp_call*/
-  0, /*tp_str*/
-  0, /*tp_getattro*/
-  0, /*tp_setattro*/
-  0, /*tp_as_buffer*/
-  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
-  0, /*tp_doc*/
-  __pyx_tp_traverse_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo, /*tp_traverse*/
-  __pyx_tp_clear_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo, /*tp_clear*/
-  0, /*tp_richcompare*/
-  0, /*tp_weaklistoffset*/
-  0, /*tp_iter*/
-  0, /*tp_iternext*/
-  __pyx_methods_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo, /*tp_methods*/
-  0, /*tp_members*/
-  __pyx_getsets_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo, /*tp_getset*/
-  0, /*tp_base*/
-  0, /*tp_dict*/
-  0, /*tp_descr_get*/
-  0, /*tp_descr_set*/
-  0, /*tp_dictoffset*/
-  0, /*tp_init*/
-  0, /*tp_alloc*/
-  __pyx_tp_new_18_pydevd_frame_eval_22pydevd_frame_evaluator_ThreadInfo, /*tp_new*/
-  0, /*tp_free*/
-  0, /*tp_is_gc*/
-  0, /*tp_bases*/
-  0, /*tp_mro*/
-  0, /*tp_cache*/
-  0, /*tp_subclasses*/
-  0, /*tp_weaklist*/
-  0, /*tp_del*/
-  0, /*tp_version_tag*/
-  #if PY_VERSION_HEX >= 0x030400a1
-  0, /*tp_finalize*/
-  #endif
-  #if PY_VERSION_HEX >= 0x030800b1 && (!CYTHON_COMPILING_IN_PYPY || PYPY_VERSION_NUM >= 0x07030800)
-  0, /*tp_vectorcall*/
-  #endif
-  #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
-  0, /*tp_print*/
-  #endif
-  #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX >= 0x03090000
-  0, /*tp_pypy_flags*/
-  #endif
-};
-
-static PyObject *__pyx_tp_new_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *p;
-  PyObject *o;
-  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
-    o = (*t->tp_alloc)(t, 0);
-  } else {
-    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
-  }
-  if (unlikely(!o)) return 0;
-  p = ((struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *)o);
-  p->co_filename = ((PyObject*)Py_None); Py_INCREF(Py_None);
-  p->co_name = ((PyObject*)Py_None); Py_INCREF(Py_None);
-  p->canonical_normalized_filename = ((PyObject*)Py_None); Py_INCREF(Py_None);
-  p->new_code = Py_None; Py_INCREF(Py_None);
-  return o;
-}
-
-static void __pyx_tp_dealloc_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo(PyObject *o) {
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *p = (struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *)o;
-  #if CYTHON_USE_TP_FINALIZE
-  if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
-    if (PyObject_CallFinalizerFromDealloc(o)) return;
-  }
-  #endif
-  PyObject_GC_UnTrack(o);
-  Py_CLEAR(p->co_filename);
-  Py_CLEAR(p->co_name);
-  Py_CLEAR(p->canonical_normalized_filename);
-  Py_CLEAR(p->new_code);
-  (*Py_TYPE(o)->tp_free)(o);
-}
-
-static int __pyx_tp_traverse_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo(PyObject *o, visitproc v, void *a) {
-  int e;
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *p = (struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *)o;
-  if (p->new_code) {
-    e = (*v)(p->new_code, a); if (e) return e;
-  }
-  return 0;
-}
-
-static int __pyx_tp_clear_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo(PyObject *o) {
-  PyObject* tmp;
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *p = (struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo *)o;
-  tmp = ((PyObject*)p->new_code);
-  p->new_code = Py_None; Py_INCREF(Py_None);
-  Py_XDECREF(tmp);
-  return 0;
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_co_filename(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_11co_filename_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_co_filename(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_11co_filename_3__set__(o, v);
-  }
-  else {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_11co_filename_5__del__(o);
-  }
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_co_name(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_7co_name_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_co_name(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_7co_name_3__set__(o, v);
-  }
-  else {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_7co_name_5__del__(o);
-  }
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_canonical_normalized_filename(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_29canonical_normalized_filename_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_canonical_normalized_filename(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_29canonical_normalized_filename_3__set__(o, v);
-  }
-  else {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_29canonical_normalized_filename_5__del__(o);
-  }
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_breakpoint_found(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_16breakpoint_found_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_breakpoint_found(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_16breakpoint_found_3__set__(o, v);
-  }
-  else {
-    PyErr_SetString(PyExc_NotImplementedError, "__del__");
-    return -1;
-  }
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_new_code(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_8new_code_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_new_code(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_8new_code_3__set__(o, v);
-  }
-  else {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_8new_code_5__del__(o);
-  }
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_breakpoints_mtime(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_17breakpoints_mtime_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_breakpoints_mtime(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_17breakpoints_mtime_3__set__(o, v);
-  }
-  else {
-    PyErr_SetString(PyExc_NotImplementedError, "__del__");
-    return -1;
-  }
-}
-
-static PyMethodDef __pyx_methods_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo[] = {
-  {"__reduce_cython__", (PyCFunction)__pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_3__reduce_cython__, METH_NOARGS, 0},
-  {"__setstate_cython__", (PyCFunction)__pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_5__setstate_cython__, METH_O, 0},
-  {0, 0, 0, 0}
-};
-
-static struct PyGetSetDef __pyx_getsets_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo[] = {
-  {(char *)"co_filename", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_co_filename, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_co_filename, (char *)0, 0},
-  {(char *)"co_name", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_co_name, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_co_name, (char *)0, 0},
-  {(char *)"canonical_normalized_filename", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_canonical_normalized_filename, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_canonical_normalized_filename, (char *)0, 0},
-  {(char *)"breakpoint_found", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_breakpoint_found, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_breakpoint_found, (char *)0, 0},
-  {(char *)"new_code", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_new_code, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_new_code, (char *)0, 0},
-  {(char *)"breakpoints_mtime", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_breakpoints_mtime, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_breakpoints_mtime, (char *)0, 0},
-  {0, 0, 0, 0, 0}
-};
-
-static PyTypeObject __pyx_type_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo = {
-  PyVarObject_HEAD_INIT(0, 0)
-  "_pydevd_frame_eval.pydevd_frame_evaluator.FuncCodeInfo", /*tp_name*/
-  sizeof(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo), /*tp_basicsize*/
-  0, /*tp_itemsize*/
-  __pyx_tp_dealloc_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo, /*tp_dealloc*/
-  #if PY_VERSION_HEX < 0x030800b4
-  0, /*tp_print*/
-  #endif
-  #if PY_VERSION_HEX >= 0x030800b4
-  0, /*tp_vectorcall_offset*/
-  #endif
-  0, /*tp_getattr*/
-  0, /*tp_setattr*/
-  #if PY_MAJOR_VERSION < 3
-  0, /*tp_compare*/
-  #endif
-  #if PY_MAJOR_VERSION >= 3
-  0, /*tp_as_async*/
-  #endif
-  0, /*tp_repr*/
-  0, /*tp_as_number*/
-  0, /*tp_as_sequence*/
-  0, /*tp_as_mapping*/
-  0, /*tp_hash*/
-  0, /*tp_call*/
-  0, /*tp_str*/
-  0, /*tp_getattro*/
-  0, /*tp_setattro*/
-  0, /*tp_as_buffer*/
-  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
-  0, /*tp_doc*/
-  __pyx_tp_traverse_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo, /*tp_traverse*/
-  __pyx_tp_clear_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo, /*tp_clear*/
-  0, /*tp_richcompare*/
-  0, /*tp_weaklistoffset*/
-  0, /*tp_iter*/
-  0, /*tp_iternext*/
-  __pyx_methods_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo, /*tp_methods*/
-  0, /*tp_members*/
-  __pyx_getsets_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo, /*tp_getset*/
-  0, /*tp_base*/
-  0, /*tp_dict*/
-  0, /*tp_descr_get*/
-  0, /*tp_descr_set*/
-  0, /*tp_dictoffset*/
-  __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_12FuncCodeInfo_1__init__, /*tp_init*/
-  0, /*tp_alloc*/
-  __pyx_tp_new_18_pydevd_frame_eval_22pydevd_frame_evaluator_FuncCodeInfo, /*tp_new*/
-  0, /*tp_free*/
-  0, /*tp_is_gc*/
-  0, /*tp_bases*/
-  0, /*tp_mro*/
-  0, /*tp_cache*/
-  0, /*tp_subclasses*/
-  0, /*tp_weaklist*/
-  0, /*tp_del*/
-  0, /*tp_version_tag*/
-  #if PY_VERSION_HEX >= 0x030400a1
-  0, /*tp_finalize*/
-  #endif
-  #if PY_VERSION_HEX >= 0x030800b1 && (!CYTHON_COMPILING_IN_PYPY || PYPY_VERSION_NUM >= 0x07030800)
-  0, /*tp_vectorcall*/
-  #endif
-  #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
-  0, /*tp_print*/
-  #endif
-  #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX >= 0x03090000
-  0, /*tp_pypy_flags*/
-  #endif
-};
-
-static PyObject *__pyx_tp_new_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *p;
-  PyObject *o;
-  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
-    o = (*t->tp_alloc)(t, 0);
-  } else {
-    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
-  }
-  if (unlikely(!o)) return 0;
-  p = ((struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *)o);
-  p->line_to_offset = ((PyObject*)Py_None); Py_INCREF(Py_None);
-  return o;
-}
-
-static void __pyx_tp_dealloc_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo(PyObject *o) {
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *p = (struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *)o;
-  #if CYTHON_USE_TP_FINALIZE
-  if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
-    if (PyObject_CallFinalizerFromDealloc(o)) return;
-  }
-  #endif
-  PyObject_GC_UnTrack(o);
-  Py_CLEAR(p->line_to_offset);
-  (*Py_TYPE(o)->tp_free)(o);
-}
-
-static int __pyx_tp_traverse_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo(PyObject *o, visitproc v, void *a) {
-  int e;
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *p = (struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *)o;
-  if (p->line_to_offset) {
-    e = (*v)(p->line_to_offset, a); if (e) return e;
-  }
-  return 0;
-}
-
-static int __pyx_tp_clear_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo(PyObject *o) {
-  PyObject* tmp;
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *p = (struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *)o;
-  tmp = ((PyObject*)p->line_to_offset);
-  p->line_to_offset = ((PyObject*)Py_None); Py_INCREF(Py_None);
-  Py_XDECREF(tmp);
-  return 0;
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_line_to_offset(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_14line_to_offset_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_line_to_offset(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_14line_to_offset_3__set__(o, v);
-  }
-  else {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_14line_to_offset_5__del__(o);
-  }
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_first_line(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_10first_line_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_first_line(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_10first_line_3__set__(o, v);
-  }
-  else {
-    PyErr_SetString(PyExc_NotImplementedError, "__del__");
-    return -1;
-  }
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_last_line(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_9last_line_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_last_line(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_9last_line_3__set__(o, v);
-  }
-  else {
-    PyErr_SetString(PyExc_NotImplementedError, "__del__");
-    return -1;
-  }
-}
-
-static PyMethodDef __pyx_methods_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo[] = {
-  {"__reduce_cython__", (PyCFunction)__pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_3__reduce_cython__, METH_NOARGS, 0},
-  {"__setstate_cython__", (PyCFunction)__pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_5__setstate_cython__, METH_O, 0},
-  {0, 0, 0, 0}
-};
-
-static struct PyGetSetDef __pyx_getsets_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo[] = {
-  {(char *)"line_to_offset", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_line_to_offset, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_line_to_offset, (char *)0, 0},
-  {(char *)"first_line", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_first_line, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_first_line, (char *)0, 0},
-  {(char *)"last_line", __pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_last_line, __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_last_line, (char *)0, 0},
-  {0, 0, 0, 0, 0}
-};
-
-static PyTypeObject __pyx_type_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo = {
-  PyVarObject_HEAD_INIT(0, 0)
-  "_pydevd_frame_eval.pydevd_frame_evaluator._CodeLineInfo", /*tp_name*/
-  sizeof(struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo), /*tp_basicsize*/
-  0, /*tp_itemsize*/
-  __pyx_tp_dealloc_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo, /*tp_dealloc*/
-  #if PY_VERSION_HEX < 0x030800b4
-  0, /*tp_print*/
-  #endif
-  #if PY_VERSION_HEX >= 0x030800b4
-  0, /*tp_vectorcall_offset*/
-  #endif
-  0, /*tp_getattr*/
-  0, /*tp_setattr*/
-  #if PY_MAJOR_VERSION < 3
-  0, /*tp_compare*/
-  #endif
-  #if PY_MAJOR_VERSION >= 3
-  0, /*tp_as_async*/
-  #endif
-  0, /*tp_repr*/
-  0, /*tp_as_number*/
-  0, /*tp_as_sequence*/
-  0, /*tp_as_mapping*/
-  0, /*tp_hash*/
-  0, /*tp_call*/
-  0, /*tp_str*/
-  0, /*tp_getattro*/
-  0, /*tp_setattro*/
-  0, /*tp_as_buffer*/
-  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
-  0, /*tp_doc*/
-  __pyx_tp_traverse_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo, /*tp_traverse*/
-  __pyx_tp_clear_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo, /*tp_clear*/
-  0, /*tp_richcompare*/
-  0, /*tp_weaklistoffset*/
-  0, /*tp_iter*/
-  0, /*tp_iternext*/
-  __pyx_methods_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo, /*tp_methods*/
-  0, /*tp_members*/
-  __pyx_getsets_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo, /*tp_getset*/
-  0, /*tp_base*/
-  0, /*tp_dict*/
-  0, /*tp_descr_get*/
-  0, /*tp_descr_set*/
-  0, /*tp_dictoffset*/
-  __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_13_CodeLineInfo_1__init__, /*tp_init*/
-  0, /*tp_alloc*/
-  __pyx_tp_new_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo, /*tp_new*/
-  0, /*tp_free*/
-  0, /*tp_is_gc*/
-  0, /*tp_bases*/
-  0, /*tp_mro*/
-  0, /*tp_cache*/
-  0, /*tp_subclasses*/
-  0, /*tp_weaklist*/
-  0, /*tp_del*/
-  0, /*tp_version_tag*/
-  #if PY_VERSION_HEX >= 0x030400a1
-  0, /*tp_finalize*/
-  #endif
-  #if PY_VERSION_HEX >= 0x030800b1 && (!CYTHON_COMPILING_IN_PYPY || PYPY_VERSION_NUM >= 0x07030800)
-  0, /*tp_vectorcall*/
-  #endif
-  #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000
-  0, /*tp_print*/
-  #endif
-  #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX >= 0x03090000
-  0, /*tp_pypy_flags*/
-  #endif
-};
-static struct __pyx_vtabstruct_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue __pyx_vtable_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue;
-
-static PyObject *__pyx_tp_new_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue *p;
-  PyObject *o;
-  if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
-    o = (*t->tp_alloc)(t, 0);
-  } else {
-    o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
-  }
-  if (unlikely(!o)) return 0;
-  p = ((struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue *)o);
-  p->__pyx_vtab = __pyx_vtabptr_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue;
-  p->code_obj_py = Py_None; Py_INCREF(Py_None);
-  p->code_line_info = ((struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *)Py_None); Py_INCREF(Py_None);
-  p->breakpoints_hit_at_lines = ((PyObject*)Py_None); Py_INCREF(Py_None);
-  p->code_lines_as_set = ((PyObject*)Py_None); Py_INCREF(Py_None);
-  return o;
-}
-
-static void __pyx_tp_dealloc_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue(PyObject *o) {
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue *p = (struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue *)o;
-  #if CYTHON_USE_TP_FINALIZE
-  if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
-    if (PyObject_CallFinalizerFromDealloc(o)) return;
-  }
-  #endif
-  PyObject_GC_UnTrack(o);
-  Py_CLEAR(p->code_obj_py);
-  Py_CLEAR(p->code_line_info);
-  Py_CLEAR(p->breakpoints_hit_at_lines);
-  Py_CLEAR(p->code_lines_as_set);
-  (*Py_TYPE(o)->tp_free)(o);
-}
-
-static int __pyx_tp_traverse_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue(PyObject *o, visitproc v, void *a) {
-  int e;
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue *p = (struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue *)o;
-  if (p->code_obj_py) {
-    e = (*v)(p->code_obj_py, a); if (e) return e;
-  }
-  if (p->code_line_info) {
-    e = (*v)(((PyObject *)p->code_line_info), a); if (e) return e;
-  }
-  if (p->breakpoints_hit_at_lines) {
-    e = (*v)(p->breakpoints_hit_at_lines, a); if (e) return e;
-  }
-  if (p->code_lines_as_set) {
-    e = (*v)(p->code_lines_as_set, a); if (e) return e;
-  }
-  return 0;
-}
-
-static int __pyx_tp_clear_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue(PyObject *o) {
-  PyObject* tmp;
-  struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue *p = (struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CacheValue *)o;
-  tmp = ((PyObject*)p->code_obj_py);
-  p->code_obj_py = Py_None; Py_INCREF(Py_None);
-  Py_XDECREF(tmp);
-  tmp = ((PyObject*)p->code_line_info);
-  p->code_line_info = ((struct __pyx_obj_18_pydevd_frame_eval_22pydevd_frame_evaluator__CodeLineInfo *)Py_None); Py_INCREF(Py_None);
-  Py_XDECREF(tmp);
-  tmp = ((PyObject*)p->breakpoints_hit_at_lines);
-  p->breakpoints_hit_at_lines = ((PyObject*)Py_None); Py_INCREF(Py_None);
-  Py_XDECREF(tmp);
-  tmp = ((PyObject*)p->code_lines_as_set);
-  p->code_lines_as_set = ((PyObject*)Py_None); Py_INCREF(Py_None);
-  Py_XDECREF(tmp);
-  return 0;
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_code_obj_py(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_11code_obj_py_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_code_obj_py(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_11code_obj_py_3__set__(o, v);
-  }
-  else {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_11code_obj_py_5__del__(o);
-  }
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_code_line_info(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_14code_line_info_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_code_line_info(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_14code_line_info_3__set__(o, v);
-  }
-  else {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_14code_line_info_5__del__(o);
-  }
-}
-
-static PyObject *__pyx_getprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_breakpoints_hit_at_lines(PyObject *o, CYTHON_UNUSED void *x) {
-  return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_24breakpoints_hit_at_lines_1__get__(o);
-}
-
-static int __pyx_setprop_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_breakpoints_hit_at_lines(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
-  if (v) {
-    return __pyx_pw_18_pydevd_frame_eval_22pydevd_frame_evaluator_11_CacheValue_24breakpoints_hit_at_lines_3__set__(o, v);
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-/* PyCFunctionFastCall */
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-#ifdef HAVE_LONG_LONG
-                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
-                        lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
-                        goto long_long;
-#endif
-                    }
-                    CYTHON_FALLTHROUGH;
-                case 3:
-                    if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
-                        a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
-                        break;
-#ifdef HAVE_LONG_LONG
-                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
-                        lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
-                        goto long_long;
-#endif
-                    }
-                    CYTHON_FALLTHROUGH;
-                case -4:
-                    if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
-                        a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
-                        break;
-#ifdef HAVE_LONG_LONG
-                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
-                        lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
-                        goto long_long;
-#endif
-                    }
-                    CYTHON_FALLTHROUGH;
-                case 4:
-                    if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
-                        a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
-                        break;
-#ifdef HAVE_LONG_LONG
-                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
-                        lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
-                        goto long_long;
-#endif
-                    }
-                    CYTHON_FALLTHROUGH;
-                default: return PyLong_Type.tp_as_number->nb_add(op1, op2);
-            }
-        }
-                x = a + b;
-            return PyLong_FromLong(x);
-#ifdef HAVE_LONG_LONG
-        long_long:
-                llx = lla + llb;
-            return PyLong_FromLongLong(llx);
-#endif
-        
-        
-    }
-    #endif
-    if (PyFloat_CheckExact(op1)) {
-        const long b = intval;
-        double a = PyFloat_AS_DOUBLE(op1);
-            double result;
-            PyFPE_START_PROTECT("add", return NULL)
-            result = ((double)a) + (double)b;
-            PyFPE_END_PROTECT(result)
-            return PyFloat_FromDouble(result);
-    }
-    return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2);
-}
-#endif
-
-/* SliceObject */
-static CYTHON_INLINE PyObject* __Pyx_PyObject_GetSlice(PyObject* obj,
-        Py_ssize_t cstart, Py_ssize_t cstop,
-        PyObject** _py_start, PyObject** _py_stop, PyObject** _py_slice,
-        int has_cstart, int has_cstop, CYTHON_UNUSED int wraparound) {
-#if CYTHON_USE_TYPE_SLOTS
-    PyMappingMethods* mp;
-#if PY_MAJOR_VERSION < 3
-    PySequenceMethods* ms = Py_TYPE(obj)->tp_as_sequence;
-    if (likely(ms && ms->sq_slice)) {
-        if (!has_cstart) {
-            if (_py_start && (*_py_start != Py_None)) {
-                cstart = __Pyx_PyIndex_AsSsize_t(*_py_start);
-                if ((cstart == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad;
-            } else
-                cstart = 0;
-        }
-        if (!has_cstop) {
-            if (_py_stop && (*_py_stop != Py_None)) {
-                cstop = __Pyx_PyIndex_AsSsize_t(*_py_stop);
-                if ((cstop == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad;
-            } else
-                cstop = PY_SSIZE_T_MAX;
-        }
-        if (wraparound && unlikely((cstart < 0) | (cstop < 0)) && likely(ms->sq_length)) {
-            Py_ssize_t l = ms->sq_length(obj);
-            if (likely(l >= 0)) {
-                if (cstop < 0) {
-                    cstop += l;
-                    if (cstop < 0) cstop = 0;
-                }
-                if (cstart < 0) {
-                    cstart += l;
-                    if (cstart < 0) cstart = 0;
-                }
-            } else {
-                if (!PyErr_ExceptionMatches(PyExc_OverflowError))
-                    goto bad;
-                PyErr_Clear();
-            }
-        }
-        return ms->sq_slice(obj, cstart, cstop);
-    }
-#endif
-    mp = Py_TYPE(obj)->tp_as_mapping;
-    if (likely(mp && mp->mp_subscript))
-#endif
-    {
-        PyObject* result;
-        PyObject *py_slice, *py_start, *py_stop;
-        if (_py_slice) {
-            py_slice = *_py_slice;
-        } else {
-            PyObject* owned_start = NULL;
-            PyObject* owned_stop = NULL;
-            if (_py_start) {
-                py_start = *_py_start;
-            } else {
-                if (has_cstart) {
-                    owned_start = py_start = PyInt_FromSsize_t(cstart);
-                    if (unlikely(!py_start)) goto bad;
-                } else
-                    py_start = Py_None;
-            }
-            if (_py_stop) {
-                py_stop = *_py_stop;
-            } else {
-                if (has_cstop) {
-                    owned_stop = py_stop = PyInt_FromSsize_t(cstop);
-                    if (unlikely(!py_stop)) {
-                        Py_XDECREF(owned_start);
-                        goto bad;
-                    }
-                } else
-                    py_stop = Py_None;
-            }
-            py_slice = PySlice_New(py_start, py_stop, Py_None);
-            Py_XDECREF(owned_start);
-            Py_XDECREF(owned_stop);
-            if (unlikely(!py_slice)) goto bad;
-        }
-#if CYTHON_USE_TYPE_SLOTS
-        result = mp->mp_subscript(obj, py_slice);
-#else
-        result = PyObject_GetItem(obj, py_slice);
-#endif
-        if (!_py_slice) {
-            Py_DECREF(py_slice);
-        }
-        return result;
-    }
-    PyErr_Format(PyExc_TypeError,
-        "'%.200s' object is unsliceable", Py_TYPE(obj)->tp_name);
-bad:
-    return NULL;
-}
-
-/* BytesEquals */
-static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) {
-#if CYTHON_COMPILING_IN_PYPY
-    return PyObject_RichCompareBool(s1, s2, equals);
-#else
-    if (s1 == s2) {
-        return (equals == Py_EQ);
-    } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) {
-        const char *ps1, *ps2;
-        Py_ssize_t length = PyBytes_GET_SIZE(s1);
-        if (length != PyBytes_GET_SIZE(s2))
-            return (equals == Py_NE);
-        ps1 = PyBytes_AS_STRING(s1);
-        ps2 = PyBytes_AS_STRING(s2);
-        if (ps1[0] != ps2[0]) {
-            return (equals == Py_NE);
-        } else if (length == 1) {
-            return (equals == Py_EQ);
-        } else {
-            int result;
-#if CYTHON_USE_UNICODE_INTERNALS && (PY_VERSION_HEX < 0x030B0000)
-            Py_hash_t hash1, hash2;
-            hash1 = ((PyBytesObject*)s1)->ob_shash;
-            hash2 = ((PyBytesObject*)s2)->ob_shash;
-            if (hash1 != hash2 && hash1 != -1 && hash2 != -1) {
-                return (equals == Py_NE);
-            }
-#endif
-            result = memcmp(ps1, ps2, (size_t)length);
-            return (equals == Py_EQ) ? (result == 0) : (result != 0);
-        }
-    } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) {
-        return (equals == Py_NE);
-    } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) {
-        return (equals == Py_NE);
-    } else {
-        int result;
-        PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
-        if (!py_result)
-            return -1;
-        result = __Pyx_PyObject_IsTrue(py_result);
-        Py_DECREF(py_result);
-        return result;
-    }
-#endif
-}
-
-/* UnicodeEquals */
-static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) {
-#if CYTHON_COMPILING_IN_PYPY
-    return PyObject_RichCompareBool(s1, s2, equals);
-#else
-#if PY_MAJOR_VERSION < 3
-    PyObject* owned_ref = NULL;
-#endif
-    int s1_is_unicode, s2_is_unicode;
-    if (s1 == s2) {
-        goto return_eq;
-    }
-    s1_is_unicode = PyUnicode_CheckExact(s1);
-    s2_is_unicode = PyUnicode_CheckExact(s2);
-#if PY_MAJOR_VERSION < 3
-    if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) {
-        owned_ref = PyUnicode_FromObject(s2);
-        if (unlikely(!owned_ref))
-            return -1;
-        s2 = owned_ref;
-        s2_is_unicode = 1;
-    } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) {
-        owned_ref = PyUnicode_FromObject(s1);
-        if (unlikely(!owned_ref))
-            return -1;
-        s1 = owned_ref;
-        s1_is_unicode = 1;
-    } else if (((!s2_is_unicode) & (!s1_is_unicode))) {
-        return __Pyx_PyBytes_Equals(s1, s2, equals);
-    }
-#endif
-    if (s1_is_unicode & s2_is_unicode) {
-        Py_ssize_t length;
-        int kind;
-        void *data1, *data2;
-        if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0))
-            return -1;
-        length = __Pyx_PyUnicode_GET_LENGTH(s1);
-        if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) {
-            goto return_ne;
-        }
-#if CYTHON_USE_UNICODE_INTERNALS
-        {
-            Py_hash_t hash1, hash2;
-        #if CYTHON_PEP393_ENABLED
-            hash1 = ((PyASCIIObject*)s1)->hash;
-            hash2 = ((PyASCIIObject*)s2)->hash;
-        #else
-            hash1 = ((PyUnicodeObject*)s1)->hash;
-            hash2 = ((PyUnicodeObject*)s2)->hash;
-        #endif
-            if (hash1 != hash2 && hash1 != -1 && hash2 != -1) {
-                goto return_ne;
-            }
-        }
-#endif
-        kind = __Pyx_PyUnicode_KIND(s1);
-        if (kind != __Pyx_PyUnicode_KIND(s2)) {
-            goto return_ne;
-        }
-        data1 = __Pyx_PyUnicode_DATA(s1);
-        data2 = __Pyx_PyUnicode_DATA(s2);
-        if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) {
-            goto return_ne;
-        } else if (length == 1) {
-            goto return_eq;
-        } else {
-            int result = memcmp(data1, data2, (size_t)(length * kind));
-            #if PY_MAJOR_VERSION < 3
-            Py_XDECREF(owned_ref);
-            #endif
-            return (equals == Py_EQ) ? (result == 0) : (result != 0);
-        }
-    } else if ((s1 == Py_None) & s2_is_unicode) {
-        goto return_ne;
-    } else if ((s2 == Py_None) & s1_is_unicode) {
-        goto return_ne;
-    } else {
-        int result;
-        PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
-        #if PY_MAJOR_VERSION < 3
-        Py_XDECREF(owned_ref);
-        #endif
-        if (!py_result)
-            return -1;
-        result = __Pyx_PyObject_IsTrue(py_result);
-        Py_DECREF(py_result);
-        return result;
-    }
-return_eq:
-    #if PY_MAJOR_VERSION < 3
-    Py_XDECREF(owned_ref);
-    #endif
-    return (equals == Py_EQ);
-return_ne:
-    #if PY_MAJOR_VERSION < 3
-    Py_XDECREF(owned_ref);
-    #endif
-    return (equals == Py_NE);
-#endif
-}
-
-/* PyErrExceptionMatches */
-#if CYTHON_FAST_THREAD_STATE
-static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) {
-    Py_ssize_t i, n;
-    n = PyTuple_GET_SIZE(tuple);
-#if PY_MAJOR_VERSION >= 3
-    for (i=0; i<n; i++) {
-        if (exc_type == PyTuple_GET_ITEM(tuple, i)) return 1;
-    }
-#endif
-    for (i=0; i<n; i++) {
-        if (__Pyx_PyErr_GivenExceptionMatches(exc_type, PyTuple_GET_ITEM(tuple, i))) return 1;
-    }
-    return 0;
-}
-static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err) {
-    PyObject *exc_type = tstate->curexc_type;
-    if (exc_type == err) return 1;
-    if (unlikely(!exc_type)) return 0;
-    if (unlikely(PyTuple_Check(err)))
-        return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err);
-    return __Pyx_PyErr_GivenExceptionMatches(exc_type, err);
-}
-#endif
-
-/* PyErrFetchRestore */
-#if CYTHON_FAST_THREAD_STATE
-static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) {
-    PyObject *tmp_type, *tmp_value, *tmp_tb;
-    tmp_type = tstate->curexc_type;
-    tmp_value = tstate->curexc_value;
-    tmp_tb = tstate->curexc_traceback;
-    tstate->curexc_type = type;
-    tstate->curexc_value = value;
-    tstate->curexc_traceback = tb;
-    Py_XDECREF(tmp_type);
-    Py_XDECREF(tmp_value);
-    Py_XDECREF(tmp_tb);
-}
-static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
-    *type = tstate->curexc_type;
-    *value = tstate->curexc_value;
-    *tb = tstate->curexc_traceback;
-    tstate->curexc_type = 0;
-    tstate->curexc_value = 0;
-    tstate->curexc_traceback = 0;
-}
-#endif
-
-/* GetAttr */
-static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) {
-#if CYTHON_USE_TYPE_SLOTS
-#if PY_MAJOR_VERSION >= 3
-    if (likely(PyUnicode_Check(n)))
-#else
-    if (likely(PyString_Check(n)))
-#endif
-        return __Pyx_PyObject_GetAttrStr(o, n);
-#endif
-    return PyObject_GetAttr(o, n);
-}
-
-/* GetAttr3 */
-static PyObject *__Pyx_GetAttr3Default(PyObject *d) {
-    __Pyx_PyThreadState_declare
-    __Pyx_PyThreadState_assign
-    if (unlikely(!__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError)))
-        return NULL;
-    __Pyx_PyErr_Clear();
-    Py_INCREF(d);
-    return d;
-}
-static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject *d) {
-    PyObject *r = __Pyx_GetAttr(o, n);
-    return (likely(r)) ? r : __Pyx_GetAttr3Default(d);
-}
-
-/* RaiseException */
-#if PY_MAJOR_VERSION < 3
-static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb,
-                        CYTHON_UNUSED PyObject *cause) {
-    __Pyx_PyThreadState_declare
-    Py_XINCREF(type);
-    if (!value || value == Py_None)
-        value = NULL;
-    else
-        Py_INCREF(value);
-    if (!tb || tb == Py_None)
-        tb = NULL;
-    else {
-        Py_INCREF(tb);
-        if (!PyTraceBack_Check(tb)) {
-            PyErr_SetString(PyExc_TypeError,
-                "raise: arg 3 must be a traceback or None");
-            goto raise_error;
-        }
-    }
-    if (PyType_Check(type)) {
-#if CYTHON_COMPILING_IN_PYPY
-        if (!value) {
-            Py_INCREF(Py_None);
-            value = Py_None;
-        }
-#endif
-        PyErr_NormalizeException(&type, &value, &tb);
-    } else {
-        if (value) {
-            PyErr_SetString(PyExc_TypeError,
-                "instance exception may not have a separate value");
-            goto raise_error;
-        }
-        value = type;
-        type = (PyObject*) Py_TYPE(type);
-        Py_INCREF(type);
-        if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) {
-            PyErr_SetString(PyExc_TypeError,
-                "raise: exception class must be a subclass of BaseException");
-            goto raise_error;
-        }
-    }
-    __Pyx_PyThreadState_assign
-    __Pyx_ErrRestore(type, value, tb);
-    return;
-raise_error:
-    Py_XDECREF(value);
-    Py_XDECREF(type);
-    Py_XDECREF(tb);
-    return;
-}
-#else
-static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) {
-    PyObject* owned_instance = NULL;
-    if (tb == Py_None) {
-        tb = 0;
-    } else if (tb && !PyTraceBack_Check(tb)) {
-        PyErr_SetString(PyExc_TypeError,
-            "raise: arg 3 must be a traceback or None");
-        goto bad;
-    }
-    if (value == Py_None)
-        value = 0;
-    if (PyExceptionInstance_Check(type)) {
-        if (value) {
-            PyErr_SetString(PyExc_TypeError,
-                "instance exception may not have a separate value");
-            goto bad;
-        }
-        value = type;
-        type = (PyObject*) Py_TYPE(value);
-    } else if (PyExceptionClass_Check(type)) {
-        PyObject *instance_class = NULL;
-        if (value && PyExceptionInstance_Check(value)) {
-            instance_class = (PyObject*) Py_TYPE(value);
-            if (instance_class != type) {
-                int is_subclass = PyObject_IsSubclass(instance_class, type);
-                if (!is_subclass) {
-                    instance_class = NULL;
-                } else if (unlikely(is_subclass == -1)) {
-                    goto bad;
-                } else {
-                    type = instance_class;
-                }
-            }
-        }
-        if (!instance_class) {
-            PyObject *args;
-            if (!value)
-                args = PyTuple_New(0);
-            else if (PyTuple_Check(value)) {
-                Py_INCREF(value);
-                args = value;
-            } else
-                args = PyTuple_Pack(1, value);
-            if (!args)
-                goto bad;
-            owned_instance = PyObject_Call(type, args, NULL);
-            Py_DECREF(args);
-            if (!owned_instance)
-                goto bad;
-            value = owned_instance;
-            if (!PyExceptionInstance_Check(value)) {
-                PyErr_Format(PyExc_TypeError,
-                             "calling %R should have returned an instance of "
-                             "BaseException, not %R",
-                             type, Py_TYPE(value));
-                goto bad;
-            }
-        }
-    } else {
-        PyErr_SetString(PyExc_TypeError,
-            "raise: exception class must be a subclass of BaseException");
-        goto bad;
-    }
-    if (cause) {
-        PyObject *fixed_cause;
-        if (cause == Py_None) {
-            fixed_cause = NULL;
-        } else if (PyExceptionClass_Check(cause)) {
-            fixed_cause = PyObject_CallObject(cause, NULL);
-            if (fixed_cause == NULL)
-                goto bad;
-        } else if (PyExceptionInstance_Check(cause)) {
-            fixed_cause = cause;
-            Py_INCREF(fixed_cause);
-        } else {
-            PyErr_SetString(PyExc_TypeError,
-                            "exception causes must derive from "
-                            "BaseException");
-            goto bad;
-        }
-        PyException_SetCause(value, fixed_cause);
-    }
-    PyErr_SetObject(type, value);
-    if (tb) {
-#if CYTHON_COMPILING_IN_PYPY
-        PyObject *tmp_type, *tmp_value, *tmp_tb;
-        PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb);
-        Py_INCREF(tb);
-        PyErr_Restore(tmp_type, tmp_value, tb);
-        Py_XDECREF(tmp_tb);
-#else
-        PyThreadState *tstate = __Pyx_PyThreadState_Current;
-        PyObject* tmp_tb = tstate->curexc_traceback;
-        if (tb != tmp_tb) {
-            Py_INCREF(tb);
-            tstate->curexc_traceback = tb;
-            Py_XDECREF(tmp_tb);
-        }
-#endif
-    }
-bad:
-    Py_XDECREF(owned_instance);
-    return;
-}
-#endif
-
-/* GetTopmostException */
-#if CYTHON_USE_EXC_INFO_STACK
-static _PyErr_StackItem *
-__Pyx_PyErr_GetTopmostException(PyThreadState *tstate)
-{
-    _PyErr_StackItem *exc_info = tstate->exc_info;
-    while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) &&
-           exc_info->previous_item != NULL)
-    {
-        exc_info = exc_info->previous_item;
-    }
-    return exc_info;
-}
-#endif
-
-/* SaveResetException */
-#if CYTHON_FAST_THREAD_STATE
-static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
-    #if CYTHON_USE_EXC_INFO_STACK
-    _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate);
-    *type = exc_info->exc_type;
-    *value = exc_info->exc_value;
-    *tb = exc_info->exc_traceback;
-    #else
-    *type = tstate->exc_type;
-    *value = tstate->exc_value;
-    *tb = tstate->exc_traceback;
-    #endif
-    Py_XINCREF(*type);
-    Py_XINCREF(*value);
-    Py_XINCREF(*tb);
-}
-static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) {
-    PyObject *tmp_type, *tmp_value, *tmp_tb;
-    #if CYTHON_USE_EXC_INFO_STACK
-    _PyErr_StackItem *exc_info = tstate->exc_info;
-    tmp_type = exc_info->exc_type;
-    tmp_value = exc_info->exc_value;
-    tmp_tb = exc_info->exc_traceback;
-    exc_info->exc_type = type;
-    exc_info->exc_value = value;
-    exc_info->exc_traceback = tb;
-    #else
-    tmp_type = tstate->exc_type;
-    tmp_value = tstate->exc_value;
-    tmp_tb = tstate->exc_traceback;
-    tstate->exc_type = type;
-    tstate->exc_value = value;
-    tstate->exc_traceback = tb;
-    #endif
-    Py_XDECREF(tmp_type);
-    Py_XDECREF(tmp_value);
-    Py_XDECREF(tmp_tb);
-}
-#endif
-
-/* GetException */
-#if CYTHON_FAST_THREAD_STATE
-static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb)
-#else
-static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb)
-#endif
-{
-    PyObject *local_type, *local_value, *local_tb;
-#if CYTHON_FAST_THREAD_STATE
-    PyObject *tmp_type, *tmp_value, *tmp_tb;
-    local_type = tstate->curexc_type;
-    local_value = tstate->curexc_value;
-    local_tb = tstate->curexc_traceback;
-    tstate->curexc_type = 0;
-    tstate->curexc_value = 0;
-    tstate->curexc_traceback = 0;
-#else
-    PyErr_Fetch(&local_type, &local_value, &local_tb);
-#endif
-    PyErr_NormalizeException(&local_type, &local_value, &local_tb);
-#if CYTHON_FAST_THREAD_STATE
-    if (unlikely(tstate->curexc_type))
-#else
-    if (unlikely(PyErr_Occurred()))
-#endif
-        goto bad;
-    #if PY_MAJOR_VERSION >= 3
-    if (local_tb) {
-        if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0))
-            goto bad;
-    }
-    #endif
-    Py_XINCREF(local_tb);
-    Py_XINCREF(local_type);
-    Py_XINCREF(local_value);
-    *type = local_type;
-    *value = local_value;
-    *tb = local_tb;
-#if CYTHON_FAST_THREAD_STATE
-    #if CYTHON_USE_EXC_INFO_STACK
-    {
-        _PyErr_StackItem *exc_info = tstate->exc_info;
-        tmp_type = exc_info->exc_type;
-        tmp_value = exc_info->exc_value;
-        tmp_tb = exc_info->exc_traceback;
-        exc_info->exc_type = local_type;
-        exc_info->exc_value = local_value;
-        exc_info->exc_traceback = local_tb;
-    }
-    #else
-    tmp_type = tstate->exc_type;
-    tmp_value = tstate->exc_value;
-    tmp_tb = tstate->exc_traceback;
-    tstate->exc_type = local_type;
-    tstate->exc_value = local_value;
-    tstate->exc_traceback = local_tb;
-    #endif
-    Py_XDECREF(tmp_type);
-    Py_XDECREF(tmp_value);
-    Py_XDECREF(tmp_tb);
-#else
-    PyErr_SetExcInfo(local_type, local_value, local_tb);
-#endif
-    return 0;
-bad:
-    *type = 0;
-    *value = 0;
-    *tb = 0;
-    Py_XDECREF(local_type);
-    Py_XDECREF(local_value);
-    Py_XDECREF(local_tb);
-    return -1;
-}
-
-/* PyObjectSetAttrStr */
-#if CYTHON_USE_TYPE_SLOTS
-static CYTHON_INLINE int __Pyx_PyObject_SetAttrStr(PyObject* obj, PyObject* attr_name, PyObject* value) {
-    PyTypeObject* tp = Py_TYPE(obj);
-    if (likely(tp->tp_setattro))
-        return tp->tp_setattro(obj, attr_name, value);
-#if PY_MAJOR_VERSION < 3
-    if (likely(tp->tp_setattr))
-        return tp->tp_setattr(obj, PyString_AS_STRING(attr_name), value);
-#endif
-    return PyObject_SetAttr(obj, attr_name, value);
-}
-#endif
-
-/* None */
-static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) {
-    PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname);
-}
-
-/* ExtTypeTest */
-static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) {
-    if (unlikely(!type)) {
-        PyErr_SetString(PyExc_SystemError, "Missing type object");
-        return 0;
-    }
-    if (likely(__Pyx_TypeCheck(obj, type)))
-        return 1;
-    PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s",
-                 Py_TYPE(obj)->tp_name, type->tp_name);
-    return 0;
-}
-
-/* SwapException */
-#if CYTHON_FAST_THREAD_STATE
-static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
-    PyObject *tmp_type, *tmp_value, *tmp_tb;
-    #if CYTHON_USE_EXC_INFO_STACK
-    _PyErr_StackItem *exc_info = tstate->exc_info;
-    tmp_type = exc_info->exc_type;
-    tmp_value = exc_info->exc_value;
-    tmp_tb = exc_info->exc_traceback;
-    exc_info->exc_type = *type;
-    exc_info->exc_value = *value;
-    exc_info->exc_traceback = *tb;
-    #else
-    tmp_type = tstate->exc_type;
-    tmp_value = tstate->exc_value;
-    tmp_tb = tstate->exc_traceback;
-    tstate->exc_type = *type;
-    tstate->exc_value = *value;
-    tstate->exc_traceback = *tb;
-    #endif
-    *type = tmp_type;
-    *value = tmp_value;
-    *tb = tmp_tb;
-}
-#else
-static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) {
-    PyObject *tmp_type, *tmp_value, *tmp_tb;
-    PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb);
-    PyErr_SetExcInfo(*type, *value, *tb);
-    *type = tmp_type;
-    *value = tmp_value;
-    *tb = tmp_tb;
-}
-#endif
-
-/* RaiseArgTupleInvalid */
-static void __Pyx_RaiseArgtupleInvalid(
-    const char* func_name,
-    int exact,
-    Py_ssize_t num_min,
-    Py_ssize_t num_max,
-    Py_ssize_t num_found)
-{
-    Py_ssize_t num_expected;
-    const char *more_or_less;
-    if (num_found < num_min) {
-        num_expected = num_min;
-        more_or_less = "at least";
-    } else {
-        num_expected = num_max;
-        more_or_less = "at most";
-    }
-    if (exact) {
-        more_or_less = "exactly";
-    }
-    PyErr_Format(PyExc_TypeError,
-                 "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)",
-                 func_name, more_or_less, num_expected,
-                 (num_expected == 1) ? "" : "s", num_found);
-}
-
-/* KeywordStringCheck */
-static int __Pyx_CheckKeywordStrings(
-    PyObject *kwdict,
-    const char* function_name,
-    int kw_allowed)
-{
-    PyObject* key = 0;
-    Py_ssize_t pos = 0;
-#if CYTHON_COMPILING_IN_PYPY
-    if (!kw_allowed && PyDict_Next(kwdict, &pos, &key, 0))
-        goto invalid_keyword;
-    return 1;
-#else
-    while (PyDict_Next(kwdict, &pos, &key, 0)) {
-        #if PY_MAJOR_VERSION < 3
-        if (unlikely(!PyString_Check(key)))
-        #endif
-            if (unlikely(!PyUnicode_Check(key)))
-                goto invalid_keyword_type;
-    }
-    if ((!kw_allowed) && unlikely(key))
-        goto invalid_keyword;
-    return 1;
-invalid_keyword_type:
-    PyErr_Format(PyExc_TypeError,
-        "%.200s() keywords must be strings", function_name);
-    return 0;
-#endif
-invalid_keyword:
-    PyErr_Format(PyExc_TypeError,
-    #if PY_MAJOR_VERSION < 3
-        "%.200s() got an unexpected keyword argument '%.200s'",
-        function_name, PyString_AsString(key));
-    #else
-        "%s() got an unexpected keyword argument '%U'",
-        function_name, key);
-    #endif
-    return 0;
-}
-
-/* RaiseDoubleKeywords */
-static void __Pyx_RaiseDoubleKeywordsError(
-    const char* func_name,
-    PyObject* kw_name)
-{
-    PyErr_Format(PyExc_TypeError,
-        #if PY_MAJOR_VERSION >= 3
-        "%s() got multiple values for keyword argument '%U'", func_name, kw_name);
-        #else
-        "%s() got multiple values for keyword argument '%s'", func_name,
-        PyString_AsString(kw_name));
-        #endif
-}
-
-/* ParseKeywords */
-static int __Pyx_ParseOptionalKeywords(
-    PyObject *kwds,
-    PyObject **argnames[],
-    PyObject *kwds2,
-    PyObject *values[],
-    Py_ssize_t num_pos_args,
-    const char* function_name)
-{
-    PyObject *key = 0, *value = 0;
-    Py_ssize_t pos = 0;
-    PyObject*** name;
-    PyObject*** first_kw_arg = argnames + num_pos_args;
-    while (PyDict_Next(kwds, &pos, &key, &value)) {
-        name = first_kw_arg;
-        while (*name && (**name != key)) name++;
-        if (*name) {
-            values[name-argnames] = value;
-            continue;
-        }
-        name = first_kw_arg;
-        #if PY_MAJOR_VERSION < 3
-        if (likely(PyString_Check(key))) {
-            while (*name) {
-                if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key))
-                        && _PyString_Eq(**name, key)) {
-                    values[name-argnames] = value;
-                    break;
-                }
-                name++;
-            }
-            if (*name) continue;
-            else {
-                PyObject*** argname = argnames;
-                while (argname != first_kw_arg) {
-                    if ((**argname == key) || (
-                            (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key))
-                             && _PyString_Eq(**argname, key))) {
-                        goto arg_passed_twice;
-                    }
-                    argname++;
-                }
-            }
-        } else
-        #endif
-        if (likely(PyUnicode_Check(key))) {
-            while (*name) {
-                int cmp = (**name == key) ? 0 :
-                #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
-                    (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 :
-                #endif
-                    PyUnicode_Compare(**name, key);
-                if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
-                if (cmp == 0) {
-                    values[name-argnames] = value;
-                    break;
-                }
-                name++;
-            }
-            if (*name) continue;
-            else {
-                PyObject*** argname = argnames;
-                while (argname != first_kw_arg) {
-                    int cmp = (**argname == key) ? 0 :
-                    #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
-                        (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 :
-                    #endif
-                        PyUnicode_Compare(**argname, key);
-                    if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
-                    if (cmp == 0) goto arg_passed_twice;
-                    argname++;
-                }
-            }
-        } else
-            goto invalid_keyword_type;
-        if (kwds2) {
-            if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad;
-        } else {
-            goto invalid_keyword;
-        }
-    }
-    return 0;
-arg_passed_twice:
-    __Pyx_RaiseDoubleKeywordsError(function_name, key);
-    goto bad;
-invalid_keyword_type:
-    PyErr_Format(PyExc_TypeError,
-        "%.200s() keywords must be strings", function_name);
-    goto bad;
-invalid_keyword:
-    PyErr_Format(PyExc_TypeError,
-    #if PY_MAJOR_VERSION < 3
-        "%.200s() got an unexpected keyword argument '%.200s'",
-        function_name, PyString_AsString(key));
-    #else
-        "%s() got an unexpected keyword argument '%U'",
-        function_name, key);
-    #endif
-bad:
-    return -1;
-}
-
-/* ArgTypeTest */
-static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact)
-{
-    if (unlikely(!type)) {
-        PyErr_SetString(PyExc_SystemError, "Missing type object");
-        return 0;
-    }
-    else if (exact) {
-        #if PY_MAJOR_VERSION == 2
-        if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1;
-        #endif
-    }
-    else {
-        if (likely(__Pyx_TypeCheck(obj, type))) return 1;
-    }
-    PyErr_Format(PyExc_TypeError,
-        "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)",
-        name, type->tp_name, Py_TYPE(obj)->tp_name);
-    return 0;
-}
-
-/* DictGetItem */
-#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY
-static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key) {
-    PyObject *value;
-    value = PyDict_GetItemWithError(d, key);
-    if (unlikely(!value)) {
-        if (!PyErr_Occurred()) {
-            if (unlikely(PyTuple_Check(key))) {
-                PyObject* args = PyTuple_Pack(1, key);
-                if (likely(args)) {
-                    PyErr_SetObject(PyExc_KeyError, args);
-                    Py_DECREF(args);
-                }
-            } else {
-                PyErr_SetObject(PyExc_KeyError, key);
-            }
-        }
-        return NULL;
-    }
-    Py_INCREF(value);
-    return value;
-}
-#endif
-
-/* GetItemInt */
-static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) {
-    PyObject *r;
-    if (!j) return NULL;
-    r = PyObject_GetItem(o, j);
-    Py_DECREF(j);
-    return r;
-}
-static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
-                                                              CYTHON_NCP_UNUSED int wraparound,
-                                                              CYTHON_NCP_UNUSED int boundscheck) {
-#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
-    Py_ssize_t wrapped_i = i;
-    if (wraparound & unlikely(i < 0)) {
-        wrapped_i += PyList_GET_SIZE(o);
-    }
-    if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) {
-        PyObject *r = PyList_GET_ITEM(o, wrapped_i);
-        Py_INCREF(r);
-        return r;
-    }
-    return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
-#else
-    return PySequence_GetItem(o, i);
-#endif
-}
-static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
-                                                              CYTHON_NCP_UNUSED int wraparound,
-                                                              CYTHON_NCP_UNUSED int boundscheck) {
-#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
-    Py_ssize_t wrapped_i = i;
-    if (wraparound & unlikely(i < 0)) {
-        wrapped_i += PyTuple_GET_SIZE(o);
-    }
-    if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) {
-        PyObject *r = PyTuple_GET_ITEM(o, wrapped_i);
-        Py_INCREF(r);
-        return r;
-    }
-    return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
-#else
-    return PySequence_GetItem(o, i);
-#endif
-}
-static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list,
-                                                     CYTHON_NCP_UNUSED int wraparound,
-                                                     CYTHON_NCP_UNUSED int boundscheck) {
-#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS
-    if (is_list || PyList_CheckExact(o)) {
-        Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o);
-        if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) {
-            PyObject *r = PyList_GET_ITEM(o, n);
-            Py_INCREF(r);
-            return r;
-        }
-    }
-    else if (PyTuple_CheckExact(o)) {
-        Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o);
-        if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) {
-            PyObject *r = PyTuple_GET_ITEM(o, n);
-            Py_INCREF(r);
-            return r;
-        }
-    } else {
-        PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence;
-        if (likely(m && m->sq_item)) {
-            if (wraparound && unlikely(i < 0) && likely(m->sq_length)) {
-                Py_ssize_t l = m->sq_length(o);
-                if (likely(l >= 0)) {
-                    i += l;
-                } else {
-                    if (!PyErr_ExceptionMatches(PyExc_OverflowError))
-                        return NULL;
-                    PyErr_Clear();
-                }
-            }
-            return m->sq_item(o, i);
-        }
-    }
-#else
-    if (is_list || PySequence_Check(o)) {
-        return PySequence_GetItem(o, i);
-    }
-#endif
-    return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
-}
-
-/* RaiseTooManyValuesToUnpack */
-static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) {
-    PyErr_Format(PyExc_ValueError,
-                 "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected);
-}
-
-/* RaiseNeedMoreValuesToUnpack */
-static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) {
-    PyErr_Format(PyExc_ValueError,
-                 "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack",
-                 index, (index == 1) ? "" : "s");
-}
-
-/* IterFinish */
-static CYTHON_INLINE int __Pyx_IterFinish(void) {
-#if CYTHON_FAST_THREAD_STATE
-    PyThreadState *tstate = __Pyx_PyThreadState_Current;
-    PyObject* exc_type = tstate->curexc_type;
-    if (unlikely(exc_type)) {
-        if (likely(__Pyx_PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration))) {
-            PyObject *exc_value, *exc_tb;
-            exc_value = tstate->curexc_value;
-            exc_tb = tstate->curexc_traceback;
-            tstate->curexc_type = 0;
-            tstate->curexc_value = 0;
-            tstate->curexc_traceback = 0;
-            Py_DECREF(exc_type);
-            Py_XDECREF(exc_value);
-            Py_XDECREF(exc_tb);
-            return 0;
-        } else {
-            return -1;
-        }
-    }
-    return 0;
-#else
-    if (unlikely(PyErr_Occurred())) {
-        if (likely(PyErr_ExceptionMatches(PyExc_StopIteration))) {
-            PyErr_Clear();
-            return 0;
-        } else {
-            return -1;
-        }
-    }
-    return 0;
-#endif
-}
-
-/* UnpackItemEndCheck */
-static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected) {
-    if (unlikely(retval)) {
-        Py_DECREF(retval);
-        __Pyx_RaiseTooManyValuesError(expected);
-        return -1;
-    } else {
-        return __Pyx_IterFinish();
-    }
-    return 0;
-}
-
-/* PyObjectGetMethod */
-static int __Pyx_PyObject_GetMethod(PyObject *obj, PyObject *name, PyObject **method) {
-    PyObject *attr;
-#if CYTHON_UNPACK_METHODS && CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_PYTYPE_LOOKUP
-    PyTypeObject *tp = Py_TYPE(obj);
-    PyObject *descr;
-    descrgetfunc f = NULL;
-    PyObject **dictptr, *dict;
-    int meth_found = 0;
-    assert (*method == NULL);
-    if (unlikely(tp->tp_getattro != PyObject_GenericGetAttr)) {
-        attr = __Pyx_PyObject_GetAttrStr(obj, name);
-        goto try_unpack;
-    }
-    if (unlikely(tp->tp_dict == NULL) && unlikely(PyType_Ready(tp) < 0)) {
-        return 0;
-    }
-    descr = _PyType_Lookup(tp, name);
-    if (likely(descr != NULL)) {
-        Py_INCREF(descr);
-#if PY_MAJOR_VERSION >= 3
-        #ifdef __Pyx_CyFunction_USED
-        if (likely(PyFunction_Check(descr) || (Py_TYPE(descr) == &PyMethodDescr_Type) || __Pyx_CyFunction_Check(descr)))
-        #else
-        if (likely(PyFunction_Check(descr) || (Py_TYPE(descr) == &PyMethodDescr_Type)))
-        #endif
-#else
-        #ifdef __Pyx_CyFunction_USED
-        if (likely(PyFunction_Check(descr) || __Pyx_CyFunction_Check(descr)))
-        #else
-        if (likely(PyFunction_Check(descr)))
-        #endif
-#endif
-        {
-            meth_found = 1;
-        } else {
-            f = Py_TYPE(descr)->tp_descr_get;
-            if (f != NULL && PyDescr_IsData(descr)) {
-                attr = f(descr, obj, (PyObject *)Py_TYPE(obj));
-                Py_DECREF(descr);
-                goto try_unpack;
-            }
-        }
-    }
-    dictptr = _PyObject_GetDictPtr(obj);
-    if (dictptr != NULL && (dict = *dictptr) != NULL) {
-        Py_INCREF(dict);
-        attr = __Pyx_PyDict_GetItemStr(dict, name);
-        if (attr != NULL) {
-            Py_INCREF(attr);
-            Py_DECREF(dict);
-            Py_XDECREF(descr);
-            goto try_unpack;
-        }
-        Py_DECREF(dict);
-    }
-    if (meth_found) {
-        *method = descr;
-        return 1;
-    }
-    if (f != NULL) {
-        attr = f(descr, obj, (PyObject *)Py_TYPE(obj));
-        Py_DECREF(descr);
-        goto try_unpack;
-    }
-    if (descr != NULL) {
-        *method = descr;
-        return 0;
-    }
-    PyErr_Format(PyExc_AttributeError,
-#if PY_MAJOR_VERSION >= 3
-                 "'%.50s' object has no attribute '%U'",
-                 tp->tp_name, name);
-#else
-                 "'%.50s' object has no attribute '%.400s'",
-                 tp->tp_name, PyString_AS_STRING(name));
-#endif
-    return 0;
-#else
-    attr = __Pyx_PyObject_GetAttrStr(obj, name);
-    goto try_unpack;
-#endif
-try_unpack:
-#if CYTHON_UNPACK_METHODS
-    if (likely(attr) && PyMethod_Check(attr) && likely(PyMethod_GET_SELF(attr) == obj)) {
-        PyObject *function = PyMethod_GET_FUNCTION(attr);
-        Py_INCREF(function);
-        Py_DECREF(attr);
-        *method = function;
-        return 1;
-    }
-#endif
-    *method = attr;
-    return 0;
-}
-
-/* PyObjectCallMethod0 */
-static PyObject* __Pyx_PyObject_CallMethod0(PyObject* obj, PyObject* method_name) {
-    PyObject *method = NULL, *result = NULL;
-    int is_method = __Pyx_PyObject_GetMethod(obj, method_name, &method);
-    if (likely(is_method)) {
-        result = __Pyx_PyObject_CallOneArg(method, obj);
-        Py_DECREF(method);
-        return result;
-    }
-    if (unlikely(!method)) goto bad;
-    result = __Pyx_PyObject_CallNoArg(method);
-    Py_DECREF(method);
-bad:
-    return result;
-}
-
-/* RaiseNoneIterError */
-static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) {
-    PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
-}
-
-/* UnpackTupleError */
-static void __Pyx_UnpackTupleError(PyObject *t, Py_ssize_t index) {
-    if (t == Py_None) {
-      __Pyx_RaiseNoneNotIterableError();
-    } else if (PyTuple_GET_SIZE(t) < index) {
-      __Pyx_RaiseNeedMoreValuesError(PyTuple_GET_SIZE(t));
-    } else {
-      __Pyx_RaiseTooManyValuesError(index);
-    }
-}
-
-/* UnpackTuple2 */
-static CYTHON_INLINE int __Pyx_unpack_tuple2_exact(
-        PyObject* tuple, PyObject** pvalue1, PyObject** pvalue2, int decref_tuple) {
-    PyObject *value1 = NULL, *value2 = NULL;
-#if CYTHON_COMPILING_IN_PYPY
-    value1 = PySequence_ITEM(tuple, 0);  if (unlikely(!value1)) goto bad;
-    value2 = PySequence_ITEM(tuple, 1);  if (unlikely(!value2)) goto bad;
-#else
-    value1 = PyTuple_GET_ITEM(tuple, 0);  Py_INCREF(value1);
-    value2 = PyTuple_GET_ITEM(tuple, 1);  Py_INCREF(value2);
-#endif
-    if (decref_tuple) {
-        Py_DECREF(tuple);
-    }
-    *pvalue1 = value1;
-    *pvalue2 = value2;
-    return 0;
-#if CYTHON_COMPILING_IN_PYPY
-bad:
-    Py_XDECREF(value1);
-    Py_XDECREF(value2);
-    if (decref_tuple) { Py_XDECREF(tuple); }
-    return -1;
-#endif
-}
-static int __Pyx_unpack_tuple2_generic(PyObject* tuple, PyObject** pvalue1, PyObject** pvalue2,
-                                       int has_known_size, int decref_tuple) {
-    Py_ssize_t index;
-    PyObject *value1 = NULL, *value2 = NULL, *iter = NULL;
-    iternextfunc iternext;
-    iter = PyObject_GetIter(tuple);
-    if (unlikely(!iter)) goto bad;
-    if (decref_tuple) { Py_DECREF(tuple); tuple = NULL; }
-    iternext = Py_TYPE(iter)->tp_iternext;
-    value1 = iternext(iter); if (unlikely(!value1)) { index = 0; goto unpacking_failed; }
-    value2 = iternext(iter); if (unlikely(!value2)) { index = 1; goto unpacking_failed; }
-    if (!has_known_size && unlikely(__Pyx_IternextUnpackEndCheck(iternext(iter), 2))) goto bad;
-    Py_DECREF(iter);
-    *pvalue1 = value1;
-    *pvalue2 = value2;
-    return 0;
-unpacking_failed:
-    if (!has_known_size && __Pyx_IterFinish() == 0)
-        __Pyx_RaiseNeedMoreValuesError(index);
-bad:
-    Py_XDECREF(iter);
-    Py_XDECREF(value1);
-    Py_XDECREF(value2);
-    if (decref_tuple) { Py_XDECREF(tuple); }
-    return -1;
-}
-
-/* dict_iter */
-static CYTHON_INLINE PyObject* __Pyx_dict_iterator(PyObject* iterable, int is_dict, PyObject* method_name,
-                                                   Py_ssize_t* p_orig_length, int* p_source_is_dict) {
-    is_dict = is_dict || likely(PyDict_CheckExact(iterable));
-    *p_source_is_dict = is_dict;
-    if (is_dict) {
-#if !CYTHON_COMPILING_IN_PYPY
-        *p_orig_length = PyDict_Size(iterable);
-        Py_INCREF(iterable);
-        return iterable;
-#elif PY_MAJOR_VERSION >= 3
-        static PyObject *py_items = NULL, *py_keys = NULL, *py_values = NULL;
-        PyObject **pp = NULL;
-        if (method_name) {
-            const char *name = PyUnicode_AsUTF8(method_name);
-            if (strcmp(name, "iteritems") == 0) pp = &py_items;
-            else if (strcmp(name, "iterkeys") == 0) pp = &py_keys;
-            else if (strcmp(name, "itervalues") == 0) pp = &py_values;
-            if (pp) {
-                if (!*pp) {
-                    *pp = PyUnicode_FromString(name + 4);
-                    if (!*pp)
-                        return NULL;
-                }
-                method_name = *pp;
-            }
-        }
-#endif
-    }
-    *p_orig_length = 0;
-    if (method_name) {
-        PyObject* iter;
-        iterable = __Pyx_PyObject_CallMethod0(iterable, method_name);
-        if (!iterable)
-            return NULL;
-#if !CYTHON_COMPILING_IN_PYPY
-        if (PyTuple_CheckExact(iterable) || PyList_CheckExact(iterable))
-            return iterable;
-#endif
-        iter = PyObject_GetIter(iterable);
-        Py_DECREF(iterable);
-        return iter;
-    }
-    return PyObject_GetIter(iterable);
-}
-static CYTHON_INLINE int __Pyx_dict_iter_next(
-        PyObject* iter_obj, CYTHON_NCP_UNUSED Py_ssize_t orig_length, CYTHON_NCP_UNUSED Py_ssize_t* ppos,
-        PyObject** pkey, PyObject** pvalue, PyObject** pitem, int source_is_dict) {
-    PyObject* next_item;
-#if !CYTHON_COMPILING_IN_PYPY
-    if (source_is_dict) {
-        PyObject *key, *value;
-        if (unlikely(orig_length != PyDict_Size(iter_obj))) {
-            PyErr_SetString(PyExc_RuntimeError, "dictionary changed size during iteration");
-            return -1;
-        }
-        if (unlikely(!PyDict_Next(iter_obj, ppos, &key, &value))) {
-            return 0;
-        }
-        if (pitem) {
-            PyObject* tuple = PyTuple_New(2);
-            if (unlikely(!tuple)) {
-                return -1;
-            }
-            Py_INCREF(key);
-            Py_INCREF(value);
-            PyTuple_SET_ITEM(tuple, 0, key);
-            PyTuple_SET_ITEM(tuple, 1, value);
-            *pitem = tuple;
-        } else {
-            if (pkey) {
-                Py_INCREF(key);
-                *pkey = key;
-            }
-            if (pvalue) {
-                Py_INCREF(value);
-                *pvalue = value;
-            }
-        }
-        return 1;
-    } else if (PyTuple_CheckExact(iter_obj)) {
-        Py_ssize_t pos = *ppos;
-        if (unlikely(pos >= PyTuple_GET_SIZE(iter_obj))) return 0;
-        *ppos = pos + 1;
-        next_item = PyTuple_GET_ITEM(iter_obj, pos);
-        Py_INCREF(next_item);
-    } else if (PyList_CheckExact(iter_obj)) {
-        Py_ssize_t pos = *ppos;
-        if (unlikely(pos >= PyList_GET_SIZE(iter_obj))) return 0;
-        *ppos = pos + 1;
-        next_item = PyList_GET_ITEM(iter_obj, pos);
-        Py_INCREF(next_item);
-    } else
-#endif
-    {
-        next_item = PyIter_Next(iter_obj);
-        if (unlikely(!next_item)) {
-            return __Pyx_IterFinish();
-        }
-    }
-    if (pitem) {
-        *pitem = next_item;
-    } else if (pkey && pvalue) {
-        if (__Pyx_unpack_tuple2(next_item, pkey, pvalue, source_is_dict, source_is_dict, 1))
-            return -1;
-    } else if (pkey) {
-        *pkey = next_item;
-    } else {
-        *pvalue = next_item;
-    }
-    return 1;
-}
-
-/* WriteUnraisableException */
-static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno,
-                                  CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename,
-                                  int full_traceback, CYTHON_UNUSED int nogil) {
-    PyObject *old_exc, *old_val, *old_tb;
-    PyObject *ctx;
-    __Pyx_PyThreadState_declare
-#ifdef WITH_THREAD
-    PyGILState_STATE state;
-    if (nogil)
-        state = PyGILState_Ensure();
-#ifdef _MSC_VER
-    else state = (PyGILState_STATE)-1;
-#endif
-#endif
-    __Pyx_PyThreadState_assign
-    __Pyx_ErrFetch(&old_exc, &old_val, &old_tb);
-    if (full_traceback) {
-        Py_XINCREF(old_exc);
-        Py_XINCREF(old_val);
-        Py_XINCREF(old_tb);
-        __Pyx_ErrRestore(old_exc, old_val, old_tb);
-        PyErr_PrintEx(1);
-    }
-    #if PY_MAJOR_VERSION < 3
-    ctx = PyString_FromString(name);
-    #else
-    ctx = PyUnicode_FromString(name);
-    #endif
-    __Pyx_ErrRestore(old_exc, old_val, old_tb);
-    if (!ctx) {
-        PyErr_WriteUnraisable(Py_None);
-    } else {
-        PyErr_WriteUnraisable(ctx);
-        Py_DECREF(ctx);
-    }
-#ifdef WITH_THREAD
-    if (nogil)
-        PyGILState_Release(state);
-#endif
-}
-
-/* Import */
-static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) {
-    PyObject *empty_list = 0;
-    PyObject *module = 0;
-    PyObject *global_dict = 0;
-    PyObject *empty_dict = 0;
-    PyObject *list;
-    #if PY_MAJOR_VERSION < 3
-    PyObject *py_import;
-    py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import);
-    if (!py_import)
-        goto bad;
-    #endif
-    if (from_list)
-        list = from_list;
-    else {
-        empty_list = PyList_New(0);
-        if (!empty_list)
-            goto bad;
-        list = empty_list;
-    }
-    global_dict = PyModule_GetDict(__pyx_m);
-    if (!global_dict)
-        goto bad;
-    empty_dict = PyDict_New();
-    if (!empty_dict)
-        goto bad;
-    {
-        #if PY_MAJOR_VERSION >= 3
-        if (level == -1) {
-            if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) {
-                module = PyImport_ImportModuleLevelObject(
-                    name, global_dict, empty_dict, list, 1);
-                if (!module) {
-                    if (!PyErr_ExceptionMatches(PyExc_ImportError))
-                        goto bad;
-                    PyErr_Clear();
-                }
-            }
-            level = 0;
-        }
-        #endif
-        if (!module) {
-            #if PY_MAJOR_VERSION < 3
-            PyObject *py_level = PyInt_FromLong(level);
-            if (!py_level)
-                goto bad;
-            module = PyObject_CallFunctionObjArgs(py_import,
-                name, global_dict, empty_dict, list, py_level, (PyObject *)NULL);
-            Py_DECREF(py_level);
-            #else
-            module = PyImport_ImportModuleLevelObject(
-                name, global_dict, empty_dict, list, level);
-            #endif
-        }
-    }
-bad:
-    #if PY_MAJOR_VERSION < 3
-    Py_XDECREF(py_import);
-    #endif
-    Py_XDECREF(empty_list);
-    Py_XDECREF(empty_dict);
-    return module;
-}
-
-/* ImportFrom */
-static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) {
-    PyObject* value = __Pyx_PyObject_GetAttrStr(module, name);
-    if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) {
-        PyErr_Format(PyExc_ImportError,
-        #if PY_MAJOR_VERSION < 3
-            "cannot import name %.230s", PyString_AS_STRING(name));
-        #else
-            "cannot import name %S", name);
-        #endif
-    }
-    return value;
-}
-
-/* HasAttr */
-static CYTHON_INLINE int __Pyx_HasAttr(PyObject *o, PyObject *n) {
-    PyObject *r;
-    if (unlikely(!__Pyx_PyBaseString_Check(n))) {
-        PyErr_SetString(PyExc_TypeError,
-                        "hasattr(): attribute name must be string");
-        return -1;
-    }
-    r = __Pyx_GetAttr(o, n);
-    if (unlikely(!r)) {
-        PyErr_Clear();
-        return 0;
-    } else {
-        Py_DECREF(r);
-        return 1;
-    }
-}
-
-/* PyObject_GenericGetAttrNoDict */
-#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000
-static PyObject *__Pyx_RaiseGenericGetAttributeError(PyTypeObject *tp, PyObject *attr_name) {
-    PyErr_Format(PyExc_AttributeError,
-#if PY_MAJOR_VERSION >= 3
-                 "'%.50s' object has no attribute '%U'",
-                 tp->tp_name, attr_name);
-#else
-                 "'%.50s' object has no attribute '%.400s'",
-                 tp->tp_name, PyString_AS_STRING(attr_name));
-#endif
-    return NULL;
-}
-static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name) {
-    PyObject *descr;
-    PyTypeObject *tp = Py_TYPE(obj);
-    if (unlikely(!PyString_Check(attr_name))) {
-        return PyObject_GenericGetAttr(obj, attr_name);
-    }
-    assert(!tp->tp_dictoffset);
-    descr = _PyType_Lookup(tp, attr_name);
-    if (unlikely(!descr)) {
-        return __Pyx_RaiseGenericGetAttributeError(tp, attr_name);
-    }
-    Py_INCREF(descr);
-    #if PY_MAJOR_VERSION < 3
-    if (likely(PyType_HasFeature(Py_TYPE(descr), Py_TPFLAGS_HAVE_CLASS)))
-    #endif
-    {
-        descrgetfunc f = Py_TYPE(descr)->tp_descr_get;
-        if (unlikely(f)) {
-            PyObject *res = f(descr, obj, (PyObject *)tp);
-            Py_DECREF(descr);
-            return res;
-        }
-    }
-    return descr;
-}
-#endif
-
-/* PyObject_GenericGetAttr */
-#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000
-static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name) {
-    if (unlikely(Py_TYPE(obj)->tp_dictoffset)) {
-        return PyObject_GenericGetAttr(obj, attr_name);
-    }
-    return __Pyx_PyObject_GenericGetAttrNoDict(obj, attr_name);
-}
-#endif
-
-/* SetVTable */
-static int __Pyx_SetVtable(PyObject *dict, void *vtable) {
-#if PY_VERSION_HEX >= 0x02070000
-    PyObject *ob = PyCapsule_New(vtable, 0, 0);
-#else
-    PyObject *ob = PyCObject_FromVoidPtr(vtable, 0);
-#endif
-    if (!ob)
-        goto bad;
-    if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0)
-        goto bad;
-    Py_DECREF(ob);
-    return 0;
-bad:
-    Py_XDECREF(ob);
-    return -1;
-}
-
-/* PyObjectGetAttrStrNoError */
-static void __Pyx_PyObject_GetAttrStr_ClearAttributeError(void) {
-    __Pyx_PyThreadState_declare
-    __Pyx_PyThreadState_assign
-    if (likely(__Pyx_PyErr_ExceptionMatches(PyExc_AttributeError)))
-        __Pyx_PyErr_Clear();
-}
-static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStrNoError(PyObject* obj, PyObject* attr_name) {
-    PyObject *result;
-#if CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_TYPE_SLOTS && PY_VERSION_HEX >= 0x030700B1
-    PyTypeObject* tp = Py_TYPE(obj);
-    if (likely(tp->tp_getattro == PyObject_GenericGetAttr)) {
-        return _PyObject_GenericGetAttrWithDict(obj, attr_name, NULL, 1);
-    }
-#endif
-    result = __Pyx_PyObject_GetAttrStr(obj, attr_name);
-    if (unlikely(!result)) {
-        __Pyx_PyObject_GetAttrStr_ClearAttributeError();
-    }
-    return result;
-}
-
-/* SetupReduce */
-static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) {
-  int ret;
-  PyObject *name_attr;
-  name_attr = __Pyx_PyObject_GetAttrStr(meth, __pyx_n_s_name);
-  if (likely(name_attr)) {
-      ret = PyObject_RichCompareBool(name_attr, name, Py_EQ);
-  } else {
-      ret = -1;
-  }
-  if (unlikely(ret < 0)) {
-      PyErr_Clear();
-      ret = 0;
-  }
-  Py_XDECREF(name_attr);
-  return ret;
-}
-static int __Pyx_setup_reduce(PyObject* type_obj) {
-    int ret = 0;
-    PyObject *object_reduce = NULL;
-    PyObject *object_getstate = NULL;
-    PyObject *object_reduce_ex = NULL;
-    PyObject *reduce = NULL;
-    PyObject *reduce_ex = NULL;
-    PyObject *reduce_cython = NULL;
-    PyObject *setstate = NULL;
-    PyObject *setstate_cython = NULL;
-    PyObject *getstate = NULL;
-#if CYTHON_USE_PYTYPE_LOOKUP
-    getstate = _PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate);
-#else
-    getstate = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_getstate);
-    if (!getstate && PyErr_Occurred()) {
-        goto __PYX_BAD;
-    }
-#endif
-    if (getstate) {
-#if CYTHON_USE_PYTYPE_LOOKUP
-        object_getstate = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_getstate);
-#else
-        object_getstate = __Pyx_PyObject_GetAttrStrNoError((PyObject*)&PyBaseObject_Type, __pyx_n_s_getstate);
-        if (!object_getstate && PyErr_Occurred()) {
-            goto __PYX_BAD;
-        }
-#endif
-        if (object_getstate != getstate) {
-            goto __PYX_GOOD;
-        }
-    }
-#if CYTHON_USE_PYTYPE_LOOKUP
-    object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD;
-#else
-    object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD;
-#endif
-    reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD;
-    if (reduce_ex == object_reduce_ex) {
-#if CYTHON_USE_PYTYPE_LOOKUP
-        object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD;
-#else
-        object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD;
-#endif
-        reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD;
-        if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) {
-            reduce_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_reduce_cython);
-            if (likely(reduce_cython)) {
-                ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD;
-                ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD;
-            } else if (reduce == object_reduce || PyErr_Occurred()) {
-                goto __PYX_BAD;
-            }
-            setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate);
-            if (!setstate) PyErr_Clear();
-            if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) {
-                setstate_cython = __Pyx_PyObject_GetAttrStrNoError(type_obj, __pyx_n_s_setstate_cython);
-                if (likely(setstate_cython)) {
-                    ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD;
-                    ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD;
-                } else if (!setstate || PyErr_Occurred()) {
-                    goto __PYX_BAD;
-                }
-            }
-            PyType_Modified((PyTypeObject*)type_obj);
-        }
-    }
-    goto __PYX_GOOD;
-__PYX_BAD:
-    if (!PyErr_Occurred())
-        PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name);
-    ret = -1;
-__PYX_GOOD:
-#if !CYTHON_USE_PYTYPE_LOOKUP
-    Py_XDECREF(object_reduce);
-    Py_XDECREF(object_reduce_ex);
-    Py_XDECREF(object_getstate);
-    Py_XDECREF(getstate);
-#endif
-    Py_XDECREF(reduce);
-    Py_XDECREF(reduce_ex);
-    Py_XDECREF(reduce_cython);
-    Py_XDECREF(setstate);
-    Py_XDECREF(setstate_cython);
-    return ret;
-}
-
-/* TypeImport */
-#ifndef __PYX_HAVE_RT_ImportType
-#define __PYX_HAVE_RT_ImportType
-static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name,
-    size_t size, enum __Pyx_ImportType_CheckSize check_size)
-{
-    PyObject *result = 0;
-    char warning[200];
-    Py_ssize_t basicsize;
-#ifdef Py_LIMITED_API
-    PyObject *py_basicsize;
-#endif
-    result = PyObject_GetAttrString(module, class_name);
-    if (!result)
-        goto bad;
-    if (!PyType_Check(result)) {
-        PyErr_Format(PyExc_TypeError,
-            "%.200s.%.200s is not a type object",
-            module_name, class_name);
-        goto bad;
-    }
-#ifndef Py_LIMITED_API
-    basicsize = ((PyTypeObject *)result)->tp_basicsize;
-#else
-    py_basicsize = PyObject_GetAttrString(result, "__basicsize__");
-    if (!py_basicsize)
-        goto bad;
-    basicsize = PyLong_AsSsize_t(py_basicsize);
-    Py_DECREF(py_basicsize);
-    py_basicsize = 0;
-    if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred())
-        goto bad;
-#endif
-    if ((size_t)basicsize < size) {
-        PyErr_Format(PyExc_ValueError,
-            "%.200s.%.200s size changed, may indicate binary incompatibility. "
-            "Expected %zd from C header, got %zd from PyObject",
-            module_name, class_name, size, basicsize);
-        goto bad;
-    }
-    if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) {
-        PyErr_Format(PyExc_ValueError,
-            "%.200s.%.200s size changed, may indicate binary incompatibility. "
-            "Expected %zd from C header, got %zd from PyObject",
-            module_name, class_name, size, basicsize);
-        goto bad;
-    }
-    else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) {
-        PyOS_snprintf(warning, sizeof(warning),
-            "%s.%s size changed, may indicate binary incompatibility. "
-            "Expected %zd from C header, got %zd from PyObject",
-            module_name, class_name, size, basicsize);
-        if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad;
-    }
-    return (PyTypeObject *)result;
-bad:
-    Py_XDECREF(result);
-    return NULL;
-}
-#endif
-
-/* CLineInTraceback */
-#ifndef CYTHON_CLINE_IN_TRACEBACK
-static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) {
-    PyObject *use_cline;
-    PyObject *ptype, *pvalue, *ptraceback;
-#if CYTHON_COMPILING_IN_CPYTHON
-    PyObject **cython_runtime_dict;
-#endif
-    if (unlikely(!__pyx_cython_runtime)) {
-        return c_line;
-    }
-    __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback);
-#if CYTHON_COMPILING_IN_CPYTHON
-    cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime);
-    if (likely(cython_runtime_dict)) {
-        __PYX_PY_DICT_LOOKUP_IF_MODIFIED(
-            use_cline, *cython_runtime_dict,
-            __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback))
-    } else
-#endif
-    {
-      PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback);
-      if (use_cline_obj) {
-        use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True;
-        Py_DECREF(use_cline_obj);
-      } else {
-        PyErr_Clear();
-        use_cline = NULL;
-      }
-    }
-    if (!use_cline) {
-        c_line = 0;
-        (void) PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False);
-    }
-    else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) {
-        c_line = 0;
-    }
-    __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback);
-    return c_line;
-}
-#endif
-
-/* CodeObjectCache */
-static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) {
-    int start = 0, mid = 0, end = count - 1;
-    if (end >= 0 && code_line > entries[end].code_line) {
-        return count;
-    }
-    while (start < end) {
-        mid = start + (end - start) / 2;
-        if (code_line < entries[mid].code_line) {
-            end = mid;
-        } else if (code_line > entries[mid].code_line) {
-             start = mid + 1;
-        } else {
-            return mid;
-        }
-    }
-    if (code_line <= entries[mid].code_line) {
-        return mid;
-    } else {
-        return mid + 1;
-    }
-}
-static PyCodeObject *__pyx_find_code_object(int code_line) {
-    PyCodeObject* code_object;
-    int pos;
-    if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) {
-        return NULL;
-    }
-    pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
-    if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) {
-        return NULL;
-    }
-    code_object = __pyx_code_cache.entries[pos].code_object;
-    Py_INCREF(code_object);
-    return code_object;
-}
-static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) {
-    int pos, i;
-    __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries;
-    if (unlikely(!code_line)) {
-        return;
-    }
-    if (unlikely(!entries)) {
-        entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry));
-        if (likely(entries)) {
-            __pyx_code_cache.entries = entries;
-            __pyx_code_cache.max_count = 64;
-            __pyx_code_cache.count = 1;
-            entries[0].code_line = code_line;
-            entries[0].code_object = code_object;
-            Py_INCREF(code_object);
-        }
-        return;
-    }
-    pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
-    if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) {
-        PyCodeObject* tmp = entries[pos].code_object;
-        entries[pos].code_object = code_object;
-        Py_DECREF(tmp);
-        return;
-    }
-    if (__pyx_code_cache.count == __pyx_code_cache.max_count) {
-        int new_max = __pyx_code_cache.max_count + 64;
-        entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc(
-            __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry));
-        if (unlikely(!entries)) {
-            return;
-        }
-        __pyx_code_cache.entries = entries;
-        __pyx_code_cache.max_count = new_max;
-    }
-    for (i=__pyx_code_cache.count; i>pos; i--) {
-        entries[i] = entries[i-1];
-    }
-    entries[pos].code_line = code_line;
-    entries[pos].code_object = code_object;
-    __pyx_code_cache.count++;
-    Py_INCREF(code_object);
-}
-
-/* AddTraceback */
-#include "compile.h"
-#include "frameobject.h"
-#include "traceback.h"
-#if PY_VERSION_HEX >= 0x030b00a6
-  #ifndef Py_BUILD_CORE
-    #define Py_BUILD_CORE 1
-  #endif
-  #include "internal/pycore_frame.h"
-#endif
-static PyCodeObject* __Pyx_CreateCodeObjectForTraceback(
-            const char *funcname, int c_line,
-            int py_line, const char *filename) {
-    PyCodeObject *py_code = NULL;
-    PyObject *py_funcname = NULL;
-    #if PY_MAJOR_VERSION < 3
-    PyObject *py_srcfile = NULL;
-    py_srcfile = PyString_FromString(filename);
-    if (!py_srcfile) goto bad;
-    #endif
-    if (c_line) {
-        #if PY_MAJOR_VERSION < 3
-        py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
-        if (!py_funcname) goto bad;
-        #else
-        py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
-        if (!py_funcname) goto bad;
-        funcname = PyUnicode_AsUTF8(py_funcname);
-        if (!funcname) goto bad;
-        #endif
-    }
-    else {
-        #if PY_MAJOR_VERSION < 3
-        py_funcname = PyString_FromString(funcname);
-        if (!py_funcname) goto bad;
-        #endif
-    }
-    #if PY_MAJOR_VERSION < 3
-    py_code = __Pyx_PyCode_New(
-        0,
-        0,
-        0,
-        0,
-        0,
-        __pyx_empty_bytes, /*PyObject *code,*/
-        __pyx_empty_tuple, /*PyObject *consts,*/
-        __pyx_empty_tuple, /*PyObject *names,*/
-        __pyx_empty_tuple, /*PyObject *varnames,*/
-        __pyx_empty_tuple, /*PyObject *freevars,*/
-        __pyx_empty_tuple, /*PyObject *cellvars,*/
-        py_srcfile,   /*PyObject *filename,*/
-        py_funcname,  /*PyObject *name,*/
-        py_line,
-        __pyx_empty_bytes  /*PyObject *lnotab*/
-    );
-    Py_DECREF(py_srcfile);
-    #else
-    py_code = PyCode_NewEmpty(filename, funcname, py_line);
-    #endif
-    Py_XDECREF(py_funcname);  // XDECREF since it's only set on Py3 if cline
-    return py_code;
-bad:
-    Py_XDECREF(py_funcname);
-    #if PY_MAJOR_VERSION < 3
-    Py_XDECREF(py_srcfile);
-    #endif
-    return NULL;
-}
-static void __Pyx_AddTraceback(const char *funcname, int c_line,
-                               int py_line, const char *filename) {
-    PyCodeObject *py_code = 0;
-    PyFrameObject *py_frame = 0;
-    PyThreadState *tstate = __Pyx_PyThreadState_Current;
-    PyObject *ptype, *pvalue, *ptraceback;
-    if (c_line) {
-        c_line = __Pyx_CLineForTraceback(tstate, c_line);
-    }
-    py_code = __pyx_find_code_object(c_line ? -c_line : py_line);
-    if (!py_code) {
-        __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback);
-        py_code = __Pyx_CreateCodeObjectForTraceback(
-            funcname, c_line, py_line, filename);
-        if (!py_code) {
-            /* If the code object creation fails, then we should clear the
-               fetched exception references and propagate the new exception */
-            Py_XDECREF(ptype);
-            Py_XDECREF(pvalue);
-            Py_XDECREF(ptraceback);
-            goto bad;
-        }
-        __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback);
-        __pyx_insert_code_object(c_line ? -c_line : py_line, py_code);
-    }
-    py_frame = PyFrame_New(
-        tstate,            /*PyThreadState *tstate,*/
-        py_code,           /*PyCodeObject *code,*/
-        __pyx_d,    /*PyObject *globals,*/
-        0                  /*PyObject *locals*/
-    );
-    if (!py_frame) goto bad;
-    __Pyx_PyFrame_SetLineNumber(py_frame, py_line);
-    PyTraceBack_Here(py_frame);
-bad:
-    Py_XDECREF(py_code);
-    Py_XDECREF(py_frame);
-}
-
-/* CIntFromPyVerify */
-#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\
-    __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0)
-#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\
-    __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1)
-#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\
-    {\
-        func_type value = func_value;\
-        if (sizeof(target_type) < sizeof(func_type)) {\
-            if (unlikely(value != (func_type) (target_type) value)) {\
-                func_type zero = 0;\
-                if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\
-                    return (target_type) -1;\
-                if (is_unsigned && unlikely(value < zero))\
-                    goto raise_neg_overflow;\
-                else\
-                    goto raise_overflow;\
-            }\
-        }\
-        return (target_type) value;\
-    }
-
-/* CIntToPy */
-static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) {
-#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
-#pragma GCC diagnostic push
-#pragma GCC diagnostic ignored "-Wconversion"
-#endif
-    const int neg_one = (int) -1, const_zero = (int) 0;
-#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
-#pragma GCC diagnostic pop
-#endif
-    const int is_unsigned = neg_one > const_zero;
-    if (is_unsigned) {
-        if (sizeof(int) < sizeof(long)) {
-            return PyInt_FromLong((long) value);
-        } else if (sizeof(int) <= sizeof(unsigned long)) {
-            return PyLong_FromUnsignedLong((unsigned long) value);
-#ifdef HAVE_LONG_LONG
-        } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) {
-            return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
-#endif
-        }
-    } else {
-        if (sizeof(int) <= sizeof(long)) {
-            return PyInt_FromLong((long) value);
-#ifdef HAVE_LONG_LONG
-        } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) {
-            return PyLong_FromLongLong((PY_LONG_LONG) value);
-#endif
-        }
-    }
-    {
-        int one = 1; int little = (int)*(unsigned char *)&one;
-        unsigned char *bytes = (unsigned char *)&value;
-        return _PyLong_FromByteArray(bytes, sizeof(int),
-                                     little, !is_unsigned);
-    }
-}
-
-/* CIntFromPy */
-static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) {
-#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
-#pragma GCC diagnostic push
-#pragma GCC diagnostic ignored "-Wconversion"
-#endif
-    const int neg_one = (int) -1, const_zero = (int) 0;
-#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
-#pragma GCC diagnostic pop
-#endif
-    const int is_unsigned = neg_one > const_zero;
-#if PY_MAJOR_VERSION < 3
-    if (likely(PyInt_Check(x))) {
-        if (sizeof(int) < sizeof(long)) {
-            __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x))
-        } else {
-            long val = PyInt_AS_LONG(x);
-            if (is_unsigned && unlikely(val < 0)) {
-                goto raise_neg_overflow;
-            }
-            return (int) val;
-        }
-    } else
-#endif
-    if (likely(PyLong_Check(x))) {
-        if (is_unsigned) {
-#if CYTHON_USE_PYLONG_INTERNALS
-            const digit* digits = ((PyLongObject*)x)->ob_digit;
-            switch (Py_SIZE(x)) {
-                case  0: return (int) 0;
-                case  1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0])
-                case 2:
-                    if (8 * sizeof(int) > 1 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) {
-                            return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
-                        }
-                    }
-                    break;
-                case 3:
-                    if (8 * sizeof(int) > 2 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) {
-                            return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
-                        }
-                    }
-                    break;
-                case 4:
-                    if (8 * sizeof(int) > 3 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) {
-                            return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
-                        }
-                    }
-                    break;
-            }
-#endif
-#if CYTHON_COMPILING_IN_CPYTHON
-            if (unlikely(Py_SIZE(x) < 0)) {
-                goto raise_neg_overflow;
-            }
-#else
-            {
-                int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
-                if (unlikely(result < 0))
-                    return (int) -1;
-                if (unlikely(result == 1))
-                    goto raise_neg_overflow;
-            }
-#endif
-            if (sizeof(int) <= sizeof(unsigned long)) {
-                __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x))
-#ifdef HAVE_LONG_LONG
-            } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) {
-                __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
-#endif
-            }
-        } else {
-#if CYTHON_USE_PYLONG_INTERNALS
-            const digit* digits = ((PyLongObject*)x)->ob_digit;
-            switch (Py_SIZE(x)) {
-                case  0: return (int) 0;
-                case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0]))
-                case  1: __PYX_VERIFY_RETURN_INT(int,  digit, +digits[0])
-                case -2:
-                    if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
-                            return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
-                        }
-                    }
-                    break;
-                case 2:
-                    if (8 * sizeof(int) > 1 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
-                            return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
-                        }
-                    }
-                    break;
-                case -3:
-                    if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
-                            return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
-                        }
-                    }
-                    break;
-                case 3:
-                    if (8 * sizeof(int) > 2 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
-                            return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
-                        }
-                    }
-                    break;
-                case -4:
-                    if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) {
-                            return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
-                        }
-                    }
-                    break;
-                case 4:
-                    if (8 * sizeof(int) > 3 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) {
-                            return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
-                        }
-                    }
-                    break;
-            }
-#endif
-            if (sizeof(int) <= sizeof(long)) {
-                __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x))
-#ifdef HAVE_LONG_LONG
-            } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) {
-                __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x))
-#endif
-            }
-        }
-        {
-#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
-            PyErr_SetString(PyExc_RuntimeError,
-                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
-#else
-            int val;
-            PyObject *v = __Pyx_PyNumber_IntOrLong(x);
- #if PY_MAJOR_VERSION < 3
-            if (likely(v) && !PyLong_Check(v)) {
-                PyObject *tmp = v;
-                v = PyNumber_Long(tmp);
-                Py_DECREF(tmp);
-            }
- #endif
-            if (likely(v)) {
-                int one = 1; int is_little = (int)*(unsigned char *)&one;
-                unsigned char *bytes = (unsigned char *)&val;
-                int ret = _PyLong_AsByteArray((PyLongObject *)v,
-                                              bytes, sizeof(val),
-                                              is_little, !is_unsigned);
-                Py_DECREF(v);
-                if (likely(!ret))
-                    return val;
-            }
-#endif
-            return (int) -1;
-        }
-    } else {
-        int val;
-        PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
-        if (!tmp) return (int) -1;
-        val = __Pyx_PyInt_As_int(tmp);
-        Py_DECREF(tmp);
-        return val;
-    }
-raise_overflow:
-    PyErr_SetString(PyExc_OverflowError,
-        "value too large to convert to int");
-    return (int) -1;
-raise_neg_overflow:
-    PyErr_SetString(PyExc_OverflowError,
-        "can't convert negative value to int");
-    return (int) -1;
-}
-
-/* CIntFromPy */
-static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) {
-#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
-#pragma GCC diagnostic push
-#pragma GCC diagnostic ignored "-Wconversion"
-#endif
-    const long neg_one = (long) -1, const_zero = (long) 0;
-#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
-#pragma GCC diagnostic pop
-#endif
-    const int is_unsigned = neg_one > const_zero;
-#if PY_MAJOR_VERSION < 3
-    if (likely(PyInt_Check(x))) {
-        if (sizeof(long) < sizeof(long)) {
-            __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x))
-        } else {
-            long val = PyInt_AS_LONG(x);
-            if (is_unsigned && unlikely(val < 0)) {
-                goto raise_neg_overflow;
-            }
-            return (long) val;
-        }
-    } else
-#endif
-    if (likely(PyLong_Check(x))) {
-        if (is_unsigned) {
-#if CYTHON_USE_PYLONG_INTERNALS
-            const digit* digits = ((PyLongObject*)x)->ob_digit;
-            switch (Py_SIZE(x)) {
-                case  0: return (long) 0;
-                case  1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0])
-                case 2:
-                    if (8 * sizeof(long) > 1 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) {
-                            return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
-                        }
-                    }
-                    break;
-                case 3:
-                    if (8 * sizeof(long) > 2 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) {
-                            return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
-                        }
-                    }
-                    break;
-                case 4:
-                    if (8 * sizeof(long) > 3 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) {
-                            return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
-                        }
-                    }
-                    break;
-            }
-#endif
-#if CYTHON_COMPILING_IN_CPYTHON
-            if (unlikely(Py_SIZE(x) < 0)) {
-                goto raise_neg_overflow;
-            }
-#else
-            {
-                int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
-                if (unlikely(result < 0))
-                    return (long) -1;
-                if (unlikely(result == 1))
-                    goto raise_neg_overflow;
-            }
-#endif
-            if (sizeof(long) <= sizeof(unsigned long)) {
-                __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x))
-#ifdef HAVE_LONG_LONG
-            } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) {
-                __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
-#endif
-            }
-        } else {
-#if CYTHON_USE_PYLONG_INTERNALS
-            const digit* digits = ((PyLongObject*)x)->ob_digit;
-            switch (Py_SIZE(x)) {
-                case  0: return (long) 0;
-                case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0]))
-                case  1: __PYX_VERIFY_RETURN_INT(long,  digit, +digits[0])
-                case -2:
-                    if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
-                            return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
-                        }
-                    }
-                    break;
-                case 2:
-                    if (8 * sizeof(long) > 1 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
-                            return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
-                        }
-                    }
-                    break;
-                case -3:
-                    if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
-                            return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
-                        }
-                    }
-                    break;
-                case 3:
-                    if (8 * sizeof(long) > 2 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
-                            return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
-                        }
-                    }
-                    break;
-                case -4:
-                    if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
-                            return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
-                        }
-                    }
-                    break;
-                case 4:
-                    if (8 * sizeof(long) > 3 * PyLong_SHIFT) {
-                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
-                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
-                        } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
-                            return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
-                        }
-                    }
-                    break;
-            }
-#endif
-            if (sizeof(long) <= sizeof(long)) {
-                __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x))
-#ifdef HAVE_LONG_LONG
-            } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) {
-                __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x))
-#endif
-            }
-        }
-        {
-#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
-            PyErr_SetString(PyExc_RuntimeError,
-                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
-#else
-            long val;
-            PyObject *v = __Pyx_PyNumber_IntOrLong(x);
- #if PY_MAJOR_VERSION < 3
-            if (likely(v) && !PyLong_Check(v)) {
-                PyObject *tmp = v;
-                v = PyNumber_Long(tmp);
-                Py_DECREF(tmp);
-            }
- #endif
-            if (likely(v)) {
-                int one = 1; int is_little = (int)*(unsigned char *)&one;
-                unsigned char *bytes = (unsigned char *)&val;
-                int ret = _PyLong_AsByteArray((PyLongObject *)v,
-                                              bytes, sizeof(val),
-                                              is_little, !is_unsigned);
-                Py_DECREF(v);
-                if (likely(!ret))
-                    return val;
-            }
-#endif
-            return (long) -1;
-        }
-    } else {
-        long val;
-        PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
-        if (!tmp) return (long) -1;
-        val = __Pyx_PyInt_As_long(tmp);
-        Py_DECREF(tmp);
-        return val;
-    }
-raise_overflow:
-    PyErr_SetString(PyExc_OverflowError,
-        "value too large to convert to long");
-    return (long) -1;
-raise_neg_overflow:
-    PyErr_SetString(PyExc_OverflowError,
-        "can't convert negative value to long");
-    return (long) -1;
-}
-
-/* CIntToPy */
-static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) {
-#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
-#pragma GCC diagnostic push
-#pragma GCC diagnostic ignored "-Wconversion"
-#endif
-    const long neg_one = (long) -1, const_zero = (long) 0;
-#ifdef __Pyx_HAS_GCC_DIAGNOSTIC
-#pragma GCC diagnostic pop
-#endif
-    const int is_unsigned = neg_one > const_zero;
-    if (is_unsigned) {
-        if (sizeof(long) < sizeof(long)) {
-            return PyInt_FromLong((long) value);
-        } else if (sizeof(long) <= sizeof(unsigned long)) {
-            return PyLong_FromUnsignedLong((unsigned long) value);
-#ifdef HAVE_LONG_LONG
-        } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) {
-            return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
-#endif
-        }
-    } else {
-        if (sizeof(long) <= sizeof(long)) {
-            return PyInt_FromLong((long) value);
-#ifdef HAVE_LONG_LONG
-        } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) {
-            return PyLong_FromLongLong((PY_LONG_LONG) value);
-#endif
-        }
-    }
-    {
-        int one = 1; int little = (int)*(unsigned char *)&one;
-        unsigned char *bytes = (unsigned char *)&value;
-        return _PyLong_FromByteArray(bytes, sizeof(long),
-                                     little, !is_unsigned);
-    }
-}
-
-/* FastTypeChecks */
-#if CYTHON_COMPILING_IN_CPYTHON
-static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) {
-    while (a) {
-        a = a->tp_base;
-        if (a == b)
-            return 1;
-    }
-    return b == &PyBaseObject_Type;
-}
-static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) {
-    PyObject *mro;
-    if (a == b) return 1;
-    mro = a->tp_mro;
-    if (likely(mro)) {
-        Py_ssize_t i, n;
-        n = PyTuple_GET_SIZE(mro);
-        for (i = 0; i < n; i++) {
-            if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b)
-                return 1;
-        }
-        return 0;
-    }
-    return __Pyx_InBases(a, b);
-}
-#if PY_MAJOR_VERSION == 2
-static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) {
-    PyObject *exception, *value, *tb;
-    int res;
-    __Pyx_PyThreadState_declare
-    __Pyx_PyThreadState_assign
-    __Pyx_ErrFetch(&exception, &value, &tb);
-    res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0;
-    if (unlikely(res == -1)) {
-        PyErr_WriteUnraisable(err);
-        res = 0;
-    }
-    if (!res) {
-        res = PyObject_IsSubclass(err, exc_type2);
-        if (unlikely(res == -1)) {
-            PyErr_WriteUnraisable(err);
-            res = 0;
-        }
-    }
-    __Pyx_ErrRestore(exception, value, tb);
-    return res;
-}
-#else
-static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) {
-    int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0;
-    if (!res) {
-        res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2);
-    }
-    return res;
-}
-#endif
-static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) {
-    Py_ssize_t i, n;
-    assert(PyExceptionClass_Check(exc_type));
-    n = PyTuple_GET_SIZE(tuple);
-#if PY_MAJOR_VERSION >= 3
-    for (i=0; i<n; i++) {
-        if (exc_type == PyTuple_GET_ITEM(tuple, i)) return 1;
-    }
-#endif
-    for (i=0; i<n; i++) {
-        PyObject *t = PyTuple_GET_ITEM(tuple, i);
-        #if PY_MAJOR_VERSION < 3
-        if (likely(exc_type == t)) return 1;
-        #endif
-        if (likely(PyExceptionClass_Check(t))) {
-            if (__Pyx_inner_PyErr_GivenExceptionMatches2(exc_type, NULL, t)) return 1;
-        } else {
-        }
-    }
-    return 0;
-}
-static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject* exc_type) {
-    if (likely(err == exc_type)) return 1;
-    if (likely(PyExceptionClass_Check(err))) {
-        if (likely(PyExceptionClass_Check(exc_type))) {
-            return __Pyx_inner_PyErr_GivenExceptionMatches2(err, NULL, exc_type);
-        } else if (likely(PyTuple_Check(exc_type))) {
-            return __Pyx_PyErr_GivenExceptionMatchesTuple(err, exc_type);
-        } else {
-        }
-    }
-    return PyErr_GivenExceptionMatches(err, exc_type);
-}
-static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *exc_type1, PyObject *exc_type2) {
-    assert(PyExceptionClass_Check(exc_type1));
-    assert(PyExceptionClass_Check(exc_type2));
-    if (likely(err == exc_type1 || err == exc_type2)) return 1;
-    if (likely(PyExceptionClass_Check(err))) {
-        return __Pyx_inner_PyErr_GivenExceptionMatches2(err, exc_type1, exc_type2);
-    }
-    return (PyErr_GivenExceptionMatches(err, exc_type1) || PyErr_GivenExceptionMatches(err, exc_type2));
-}
-#endif
-
-/* CheckBinaryVersion */
-static int __Pyx_check_binary_version(void) {
-    char ctversion[5];
-    int same=1, i, found_dot;
-    const char* rt_from_call = Py_GetVersion();
-    PyOS_snprintf(ctversion, 5, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION);
-    found_dot = 0;
-    for (i = 0; i < 4; i++) {
-        if (!ctversion[i]) {
-            same = (rt_from_call[i] < '0' || rt_from_call[i] > '9');
-            break;
-        }
-        if (rt_from_call[i] != ctversion[i]) {
-            same = 0;
-            break;
-        }
-    }
-    if (!same) {
-        char rtversion[5] = {'\0'};
-        char message[200];
-        for (i=0; i<4; ++i) {
-            if (rt_from_call[i] == '.') {
-                if (found_dot) break;
-                found_dot = 1;
-            } else if (rt_from_call[i] < '0' || rt_from_call[i] > '9') {
-                break;
-            }
-            rtversion[i] = rt_from_call[i];
-        }
-        PyOS_snprintf(message, sizeof(message),
-                      "compiletime version %s of module '%.100s' "
-                      "does not match runtime version %s",
-                      ctversion, __Pyx_MODULE_NAME, rtversion);
-        return PyErr_WarnEx(NULL, message, 1);
-    }
-    return 0;
-}
-
-/* InitStrings */
-static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) {
-    while (t->p) {
-        #if PY_MAJOR_VERSION < 3
-        if (t->is_unicode) {
-            *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL);
-        } else if (t->intern) {
-            *t->p = PyString_InternFromString(t->s);
-        } else {
-            *t->p = PyString_FromStringAndSize(t->s, t->n - 1);
-        }
-        #else
-        if (t->is_unicode | t->is_str) {
-            if (t->intern) {
-                *t->p = PyUnicode_InternFromString(t->s);
-            } else if (t->encoding) {
-                *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL);
-            } else {
-                *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1);
-            }
-        } else {
-            *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1);
-        }
-        #endif
-        if (!*t->p)
-            return -1;
-        if (PyObject_Hash(*t->p) == -1)
-            return -1;
-        ++t;
-    }
-    return 0;
-}
-
-static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) {
-    return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str));
-}
-static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) {
-    Py_ssize_t ignore;
-    return __Pyx_PyObject_AsStringAndSize(o, &ignore);
-}
-#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
-#if !CYTHON_PEP393_ENABLED
-static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
-    char* defenc_c;
-    PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL);
-    if (!defenc) return NULL;
-    defenc_c = PyBytes_AS_STRING(defenc);
-#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
-    {
-        char* end = defenc_c + PyBytes_GET_SIZE(defenc);
-        char* c;
-        for (c = defenc_c; c < end; c++) {
-            if ((unsigned char) (*c) >= 128) {
-                PyUnicode_AsASCIIString(o);
-                return NULL;
-            }
-        }
-    }
-#endif
-    *length = PyBytes_GET_SIZE(defenc);
-    return defenc_c;
-}
-#else
-static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
-    if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL;
-#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
-    if (likely(PyUnicode_IS_ASCII(o))) {
-        *length = PyUnicode_GET_LENGTH(o);
-        return PyUnicode_AsUTF8(o);
-    } else {
-        PyUnicode_AsASCIIString(o);
-        return NULL;
-    }
-#else
-    return PyUnicode_AsUTF8AndSize(o, length);
-#endif
-}
-#endif
-#endif
-static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
-#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
-    if (
-#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
-            __Pyx_sys_getdefaultencoding_not_ascii &&
-#endif
-            PyUnicode_Check(o)) {
-        return __Pyx_PyUnicode_AsStringAndSize(o, length);
-    } else
-#endif
-#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE))
-    if (PyByteArray_Check(o)) {
-        *length = PyByteArray_GET_SIZE(o);
-        return PyByteArray_AS_STRING(o);
-    } else
-#endif
-    {
-        char* result;
-        int r = PyBytes_AsStringAndSize(o, &result, length);
-        if (unlikely(r < 0)) {
-            return NULL;
-        } else {
-            return result;
-        }
-    }
-}
-static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) {
-   int is_true = x == Py_True;
-   if (is_true | (x == Py_False) | (x == Py_None)) return is_true;
-   else return PyObject_IsTrue(x);
-}
-static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) {
-    int retval;
-    if (unlikely(!x)) return -1;
-    retval = __Pyx_PyObject_IsTrue(x);
-    Py_DECREF(x);
-    return retval;
-}
-static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) {
-#if PY_MAJOR_VERSION >= 3
-    if (PyLong_Check(result)) {
-        if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1,
-                "__int__ returned non-int (type %.200s).  "
-                "The ability to return an instance of a strict subclass of int "
-                "is deprecated, and may be removed in a future version of Python.",
-                Py_TYPE(result)->tp_name)) {
-            Py_DECREF(result);
-            return NULL;
-        }
-        return result;
-    }
-#endif
-    PyErr_Format(PyExc_TypeError,
-                 "__%.4s__ returned non-%.4s (type %.200s)",
-                 type_name, type_name, Py_TYPE(result)->tp_name);
-    Py_DECREF(result);
-    return NULL;
-}
-static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) {
-#if CYTHON_USE_TYPE_SLOTS
-  PyNumberMethods *m;
-#endif
-  const char *name = NULL;
-  PyObject *res = NULL;
-#if PY_MAJOR_VERSION < 3
-  if (likely(PyInt_Check(x) || PyLong_Check(x)))
-#else
-  if (likely(PyLong_Check(x)))
-#endif
-    return __Pyx_NewRef(x);
-#if CYTHON_USE_TYPE_SLOTS
-  m = Py_TYPE(x)->tp_as_number;
-  #if PY_MAJOR_VERSION < 3
-  if (m && m->nb_int) {
-    name = "int";
-    res = m->nb_int(x);
-  }
-  else if (m && m->nb_long) {
-    name = "long";
-    res = m->nb_long(x);
-  }
-  #else
-  if (likely(m && m->nb_int)) {
-    name = "int";
-    res = m->nb_int(x);
-  }
-  #endif
-#else
-  if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) {
-    res = PyNumber_Int(x);
-  }
-#endif
-  if (likely(res)) {
-#if PY_MAJOR_VERSION < 3
-    if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) {
-#else
-    if (unlikely(!PyLong_CheckExact(res))) {
-#endif
-        return __Pyx_PyNumber_IntOrLongWrongResultType(res, name);
-    }
-  }
-  else if (!PyErr_Occurred()) {
-    PyErr_SetString(PyExc_TypeError,
-                    "an integer is required");
-  }
-  return res;
-}
-static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) {
-  Py_ssize_t ival;
-  PyObject *x;
-#if PY_MAJOR_VERSION < 3
-  if (likely(PyInt_CheckExact(b))) {
-    if (sizeof(Py_ssize_t) >= sizeof(long))
-        return PyInt_AS_LONG(b);
-    else
-        return PyInt_AsSsize_t(b);
-  }
-#endif
-  if (likely(PyLong_CheckExact(b))) {
-    #if CYTHON_USE_PYLONG_INTERNALS
-    const digit* digits = ((PyLongObject*)b)->ob_digit;
-    const Py_ssize_t size = Py_SIZE(b);
-    if (likely(__Pyx_sst_abs(size) <= 1)) {
-        ival = likely(size) ? digits[0] : 0;
-        if (size == -1) ival = -ival;
-        return ival;
-    } else {
-      switch (size) {
-         case 2:
-           if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) {
-             return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
-           }
-           break;
-         case -2:
-           if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) {
-             return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
-           }
-           break;
-         case 3:
-           if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) {
-             return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
-           }
-           break;
-         case -3:
-           if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) {
-             return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
-           }
-           break;
-         case 4:
-           if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) {
-             return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
-           }
-           break;
-         case -4:
-           if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) {
-             return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
-           }
-           break;
-      }
-    }
-    #endif
-    return PyLong_AsSsize_t(b);
-  }
-  x = PyNumber_Index(b);
-  if (!x) return -1;
-  ival = PyInt_AsSsize_t(x);
-  Py_DECREF(x);
-  return ival;
-}
-static CYTHON_INLINE Py_hash_t __Pyx_PyIndex_AsHash_t(PyObject* o) {
-  if (sizeof(Py_hash_t) == sizeof(Py_ssize_t)) {
-    return (Py_hash_t) __Pyx_PyIndex_AsSsize_t(o);
-#if PY_MAJOR_VERSION < 3
-  } else if (likely(PyInt_CheckExact(o))) {
-    return PyInt_AS_LONG(o);
-#endif
-  } else {
-    Py_ssize_t ival;
-    PyObject *x;
-    x = PyNumber_Index(o);
-    if (!x) return -1;
-    ival = PyInt_AsLong(x);
-    Py_DECREF(x);
-    return ival;
-  }
-}
-static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) {
-  return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False);
-}
-static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {
-    return PyInt_FromSize_t(ival);
-}
-
-
-#endif /* Py_PYTHON_H */
diff --git a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/pydevd_plugins/extensions/__init__.py b/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/pydevd_plugins/extensions/__init__.py
deleted file mode 100644
index 274d7bc4fcf5f780858b55a14c6c4ac85f2a7f0d..0000000000000000000000000000000000000000
--- a/spaces/SungBeom/chatwine-korean/.venv/Lib/site-packages/debugpy/_vendored/pydevd/pydevd_plugins/extensions/__init__.py
+++ /dev/null
@@ -1,7 +0,0 @@
-import warnings
-with warnings.catch_warnings():
-    try:
-        __import__('pkg_resources').declare_namespace(__name__)
-    except ImportError:
-        import pkgutil
-        __path__ = pkgutil.extend_path(__path__, __name__)
diff --git a/spaces/Superlang/ImageProcessor/annotator/oneformer/detectron2/layers/deform_conv.py b/spaces/Superlang/ImageProcessor/annotator/oneformer/detectron2/layers/deform_conv.py
deleted file mode 100644
index 49547238bcc67775bbeb97184467c3c8eee8df60..0000000000000000000000000000000000000000
--- a/spaces/Superlang/ImageProcessor/annotator/oneformer/detectron2/layers/deform_conv.py
+++ /dev/null
@@ -1,514 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-import math
-from functools import lru_cache
-import torch
-from torch import nn
-from torch.autograd import Function
-from torch.autograd.function import once_differentiable
-from torch.nn.modules.utils import _pair
-from torchvision.ops import deform_conv2d
-
-from annotator.oneformer.detectron2.utils.develop import create_dummy_class, create_dummy_func
-
-from .wrappers import _NewEmptyTensorOp
-
-
-class _DeformConv(Function):
-    @staticmethod
-    def forward(
-        ctx,
-        input,
-        offset,
-        weight,
-        stride=1,
-        padding=0,
-        dilation=1,
-        groups=1,
-        deformable_groups=1,
-        im2col_step=64,
-    ):
-        if input is not None and input.dim() != 4:
-            raise ValueError(
-                "Expected 4D tensor as input, got {}D tensor instead.".format(input.dim())
-            )
-        ctx.stride = _pair(stride)
-        ctx.padding = _pair(padding)
-        ctx.dilation = _pair(dilation)
-        ctx.groups = groups
-        ctx.deformable_groups = deformable_groups
-        ctx.im2col_step = im2col_step
-
-        ctx.save_for_backward(input, offset, weight)
-
-        output = input.new_empty(
-            _DeformConv._output_size(input, weight, ctx.padding, ctx.dilation, ctx.stride)
-        )
-
-        ctx.bufs_ = [input.new_empty(0), input.new_empty(0)]  # columns, ones
-
-        if not input.is_cuda:
-            # TODO: let torchvision support full features of our deformconv.
-            if deformable_groups != 1:
-                raise NotImplementedError(
-                    "Deformable Conv with deformable_groups != 1 is not supported on CPUs!"
-                )
-            return deform_conv2d(
-                input, offset, weight, stride=stride, padding=padding, dilation=dilation
-            )
-        else:
-            cur_im2col_step = _DeformConv._cal_im2col_step(input.shape[0], ctx.im2col_step)
-            assert (input.shape[0] % cur_im2col_step) == 0, "im2col step must divide batchsize"
-
-            _C.deform_conv_forward(
-                input,
-                weight,
-                offset,
-                output,
-                ctx.bufs_[0],
-                ctx.bufs_[1],
-                weight.size(3),
-                weight.size(2),
-                ctx.stride[1],
-                ctx.stride[0],
-                ctx.padding[1],
-                ctx.padding[0],
-                ctx.dilation[1],
-                ctx.dilation[0],
-                ctx.groups,
-                ctx.deformable_groups,
-                cur_im2col_step,
-            )
-        return output
-
-    @staticmethod
-    @once_differentiable
-    def backward(ctx, grad_output):
-        input, offset, weight = ctx.saved_tensors
-
-        grad_input = grad_offset = grad_weight = None
-
-        if not grad_output.is_cuda:
-            raise NotImplementedError("Deformable Conv is not supported on CPUs!")
-        else:
-            cur_im2col_step = _DeformConv._cal_im2col_step(input.shape[0], ctx.im2col_step)
-            assert (input.shape[0] % cur_im2col_step) == 0, "im2col step must divide batchsize"
-
-            if ctx.needs_input_grad[0] or ctx.needs_input_grad[1]:
-                grad_input = torch.zeros_like(input)
-                grad_offset = torch.zeros_like(offset)
-                _C.deform_conv_backward_input(
-                    input,
-                    offset,
-                    grad_output,
-                    grad_input,
-                    grad_offset,
-                    weight,
-                    ctx.bufs_[0],
-                    weight.size(3),
-                    weight.size(2),
-                    ctx.stride[1],
-                    ctx.stride[0],
-                    ctx.padding[1],
-                    ctx.padding[0],
-                    ctx.dilation[1],
-                    ctx.dilation[0],
-                    ctx.groups,
-                    ctx.deformable_groups,
-                    cur_im2col_step,
-                )
-
-            if ctx.needs_input_grad[2]:
-                grad_weight = torch.zeros_like(weight)
-                _C.deform_conv_backward_filter(
-                    input,
-                    offset,
-                    grad_output,
-                    grad_weight,
-                    ctx.bufs_[0],
-                    ctx.bufs_[1],
-                    weight.size(3),
-                    weight.size(2),
-                    ctx.stride[1],
-                    ctx.stride[0],
-                    ctx.padding[1],
-                    ctx.padding[0],
-                    ctx.dilation[1],
-                    ctx.dilation[0],
-                    ctx.groups,
-                    ctx.deformable_groups,
-                    1,
-                    cur_im2col_step,
-                )
-
-        return grad_input, grad_offset, grad_weight, None, None, None, None, None, None
-
-    @staticmethod
-    def _output_size(input, weight, padding, dilation, stride):
-        channels = weight.size(0)
-        output_size = (input.size(0), channels)
-        for d in range(input.dim() - 2):
-            in_size = input.size(d + 2)
-            pad = padding[d]
-            kernel = dilation[d] * (weight.size(d + 2) - 1) + 1
-            stride_ = stride[d]
-            output_size += ((in_size + (2 * pad) - kernel) // stride_ + 1,)
-        if not all(map(lambda s: s > 0, output_size)):
-            raise ValueError(
-                "convolution input is too small (output would be {})".format(
-                    "x".join(map(str, output_size))
-                )
-            )
-        return output_size
-
-    @staticmethod
-    @lru_cache(maxsize=128)
-    def _cal_im2col_step(input_size, default_size):
-        """
-        Calculate proper im2col step size, which should be divisible by input_size and not larger
-        than prefer_size. Meanwhile the step size should be as large as possible to be more
-        efficient. So we choose the largest one among all divisors of input_size which are smaller
-        than prefer_size.
-        :param input_size: input batch size .
-        :param default_size: default preferred im2col step size.
-        :return: the largest proper step size.
-        """
-        if input_size <= default_size:
-            return input_size
-        best_step = 1
-        for step in range(2, min(int(math.sqrt(input_size)) + 1, default_size)):
-            if input_size % step == 0:
-                if input_size // step <= default_size:
-                    return input_size // step
-                best_step = step
-
-        return best_step
-
-
-class _ModulatedDeformConv(Function):
-    @staticmethod
-    def forward(
-        ctx,
-        input,
-        offset,
-        mask,
-        weight,
-        bias=None,
-        stride=1,
-        padding=0,
-        dilation=1,
-        groups=1,
-        deformable_groups=1,
-    ):
-        ctx.stride = stride
-        ctx.padding = padding
-        ctx.dilation = dilation
-        ctx.groups = groups
-        ctx.deformable_groups = deformable_groups
-        ctx.with_bias = bias is not None
-        if not ctx.with_bias:
-            bias = input.new_empty(1)  # fake tensor
-        if not input.is_cuda:
-            raise NotImplementedError("Deformable Conv is not supported on CPUs!")
-        if (
-            weight.requires_grad
-            or mask.requires_grad
-            or offset.requires_grad
-            or input.requires_grad
-        ):
-            ctx.save_for_backward(input, offset, mask, weight, bias)
-        output = input.new_empty(_ModulatedDeformConv._infer_shape(ctx, input, weight))
-        ctx._bufs = [input.new_empty(0), input.new_empty(0)]
-        _C.modulated_deform_conv_forward(
-            input,
-            weight,
-            bias,
-            ctx._bufs[0],
-            offset,
-            mask,
-            output,
-            ctx._bufs[1],
-            weight.shape[2],
-            weight.shape[3],
-            ctx.stride,
-            ctx.stride,
-            ctx.padding,
-            ctx.padding,
-            ctx.dilation,
-            ctx.dilation,
-            ctx.groups,
-            ctx.deformable_groups,
-            ctx.with_bias,
-        )
-        return output
-
-    @staticmethod
-    @once_differentiable
-    def backward(ctx, grad_output):
-        if not grad_output.is_cuda:
-            raise NotImplementedError("Deformable Conv is not supported on CPUs!")
-        input, offset, mask, weight, bias = ctx.saved_tensors
-        grad_input = torch.zeros_like(input)
-        grad_offset = torch.zeros_like(offset)
-        grad_mask = torch.zeros_like(mask)
-        grad_weight = torch.zeros_like(weight)
-        grad_bias = torch.zeros_like(bias)
-        _C.modulated_deform_conv_backward(
-            input,
-            weight,
-            bias,
-            ctx._bufs[0],
-            offset,
-            mask,
-            ctx._bufs[1],
-            grad_input,
-            grad_weight,
-            grad_bias,
-            grad_offset,
-            grad_mask,
-            grad_output,
-            weight.shape[2],
-            weight.shape[3],
-            ctx.stride,
-            ctx.stride,
-            ctx.padding,
-            ctx.padding,
-            ctx.dilation,
-            ctx.dilation,
-            ctx.groups,
-            ctx.deformable_groups,
-            ctx.with_bias,
-        )
-        if not ctx.with_bias:
-            grad_bias = None
-
-        return (
-            grad_input,
-            grad_offset,
-            grad_mask,
-            grad_weight,
-            grad_bias,
-            None,
-            None,
-            None,
-            None,
-            None,
-        )
-
-    @staticmethod
-    def _infer_shape(ctx, input, weight):
-        n = input.size(0)
-        channels_out = weight.size(0)
-        height, width = input.shape[2:4]
-        kernel_h, kernel_w = weight.shape[2:4]
-        height_out = (
-            height + 2 * ctx.padding - (ctx.dilation * (kernel_h - 1) + 1)
-        ) // ctx.stride + 1
-        width_out = (
-            width + 2 * ctx.padding - (ctx.dilation * (kernel_w - 1) + 1)
-        ) // ctx.stride + 1
-        return n, channels_out, height_out, width_out
-
-
-deform_conv = _DeformConv.apply
-modulated_deform_conv = _ModulatedDeformConv.apply
-
-
-class DeformConv(nn.Module):
-    def __init__(
-        self,
-        in_channels,
-        out_channels,
-        kernel_size,
-        stride=1,
-        padding=0,
-        dilation=1,
-        groups=1,
-        deformable_groups=1,
-        bias=False,
-        norm=None,
-        activation=None,
-    ):
-        """
-        Deformable convolution from :paper:`deformconv`.
-
-        Arguments are similar to :class:`Conv2D`. Extra arguments:
-
-        Args:
-            deformable_groups (int): number of groups used in deformable convolution.
-            norm (nn.Module, optional): a normalization layer
-            activation (callable(Tensor) -> Tensor): a callable activation function
-        """
-        super(DeformConv, self).__init__()
-
-        assert not bias
-        assert in_channels % groups == 0, "in_channels {} cannot be divisible by groups {}".format(
-            in_channels, groups
-        )
-        assert (
-            out_channels % groups == 0
-        ), "out_channels {} cannot be divisible by groups {}".format(out_channels, groups)
-
-        self.in_channels = in_channels
-        self.out_channels = out_channels
-        self.kernel_size = _pair(kernel_size)
-        self.stride = _pair(stride)
-        self.padding = _pair(padding)
-        self.dilation = _pair(dilation)
-        self.groups = groups
-        self.deformable_groups = deformable_groups
-        self.norm = norm
-        self.activation = activation
-
-        self.weight = nn.Parameter(
-            torch.Tensor(out_channels, in_channels // self.groups, *self.kernel_size)
-        )
-        self.bias = None
-
-        nn.init.kaiming_uniform_(self.weight, nonlinearity="relu")
-
-    def forward(self, x, offset):
-        if x.numel() == 0:
-            # When input is empty, we want to return a empty tensor with "correct" shape,
-            # So that the following operations will not panic
-            # if they check for the shape of the tensor.
-            # This computes the height and width of the output tensor
-            output_shape = [
-                (i + 2 * p - (di * (k - 1) + 1)) // s + 1
-                for i, p, di, k, s in zip(
-                    x.shape[-2:], self.padding, self.dilation, self.kernel_size, self.stride
-                )
-            ]
-            output_shape = [x.shape[0], self.weight.shape[0]] + output_shape
-            return _NewEmptyTensorOp.apply(x, output_shape)
-
-        x = deform_conv(
-            x,
-            offset,
-            self.weight,
-            self.stride,
-            self.padding,
-            self.dilation,
-            self.groups,
-            self.deformable_groups,
-        )
-        if self.norm is not None:
-            x = self.norm(x)
-        if self.activation is not None:
-            x = self.activation(x)
-        return x
-
-    def extra_repr(self):
-        tmpstr = "in_channels=" + str(self.in_channels)
-        tmpstr += ", out_channels=" + str(self.out_channels)
-        tmpstr += ", kernel_size=" + str(self.kernel_size)
-        tmpstr += ", stride=" + str(self.stride)
-        tmpstr += ", padding=" + str(self.padding)
-        tmpstr += ", dilation=" + str(self.dilation)
-        tmpstr += ", groups=" + str(self.groups)
-        tmpstr += ", deformable_groups=" + str(self.deformable_groups)
-        tmpstr += ", bias=False"
-        return tmpstr
-
-
-class ModulatedDeformConv(nn.Module):
-    def __init__(
-        self,
-        in_channels,
-        out_channels,
-        kernel_size,
-        stride=1,
-        padding=0,
-        dilation=1,
-        groups=1,
-        deformable_groups=1,
-        bias=True,
-        norm=None,
-        activation=None,
-    ):
-        """
-        Modulated deformable convolution from :paper:`deformconv2`.
-
-        Arguments are similar to :class:`Conv2D`. Extra arguments:
-
-        Args:
-            deformable_groups (int): number of groups used in deformable convolution.
-            norm (nn.Module, optional): a normalization layer
-            activation (callable(Tensor) -> Tensor): a callable activation function
-        """
-        super(ModulatedDeformConv, self).__init__()
-        self.in_channels = in_channels
-        self.out_channels = out_channels
-        self.kernel_size = _pair(kernel_size)
-        self.stride = stride
-        self.padding = padding
-        self.dilation = dilation
-        self.groups = groups
-        self.deformable_groups = deformable_groups
-        self.with_bias = bias
-        self.norm = norm
-        self.activation = activation
-
-        self.weight = nn.Parameter(
-            torch.Tensor(out_channels, in_channels // groups, *self.kernel_size)
-        )
-        if bias:
-            self.bias = nn.Parameter(torch.Tensor(out_channels))
-        else:
-            self.bias = None
-
-        nn.init.kaiming_uniform_(self.weight, nonlinearity="relu")
-        if self.bias is not None:
-            nn.init.constant_(self.bias, 0)
-
-    def forward(self, x, offset, mask):
-        if x.numel() == 0:
-            output_shape = [
-                (i + 2 * p - (di * (k - 1) + 1)) // s + 1
-                for i, p, di, k, s in zip(
-                    x.shape[-2:], self.padding, self.dilation, self.kernel_size, self.stride
-                )
-            ]
-            output_shape = [x.shape[0], self.weight.shape[0]] + output_shape
-            return _NewEmptyTensorOp.apply(x, output_shape)
-
-        x = modulated_deform_conv(
-            x,
-            offset,
-            mask,
-            self.weight,
-            self.bias,
-            self.stride,
-            self.padding,
-            self.dilation,
-            self.groups,
-            self.deformable_groups,
-        )
-        if self.norm is not None:
-            x = self.norm(x)
-        if self.activation is not None:
-            x = self.activation(x)
-        return x
-
-    def extra_repr(self):
-        tmpstr = "in_channels=" + str(self.in_channels)
-        tmpstr += ", out_channels=" + str(self.out_channels)
-        tmpstr += ", kernel_size=" + str(self.kernel_size)
-        tmpstr += ", stride=" + str(self.stride)
-        tmpstr += ", padding=" + str(self.padding)
-        tmpstr += ", dilation=" + str(self.dilation)
-        tmpstr += ", groups=" + str(self.groups)
-        tmpstr += ", deformable_groups=" + str(self.deformable_groups)
-        tmpstr += ", bias=" + str(self.with_bias)
-        return tmpstr
-
-
-try:
-    from annotator.oneformer.detectron2 import _C
-except ImportError:
-    # TODO: register ops natively so there is no need to import _C.
-    _msg = "detectron2 is not compiled successfully, please build following the instructions!"
-    _args = ("detectron2._C", _msg)
-    DeformConv = create_dummy_class("DeformConv", *_args)
-    ModulatedDeformConv = create_dummy_class("ModulatedDeformConv", *_args)
-    deform_conv = create_dummy_func("deform_conv", *_args)
-    modulated_deform_conv = create_dummy_func("modulated_deform_conv", *_args)
diff --git a/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/setuptools/_distutils/py38compat.py b/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/setuptools/_distutils/py38compat.py
deleted file mode 100644
index 59224e71e50c49e5f9f6f925837597c035a8ab7f..0000000000000000000000000000000000000000
--- a/spaces/TandCAcceptMe/face-swap-docker/mynewshinyroop/Lib/site-packages/setuptools/_distutils/py38compat.py
+++ /dev/null
@@ -1,8 +0,0 @@
-def aix_platform(osname, version, release):
-    try:
-        import _aix_support
-
-        return _aix_support.aix_platform()
-    except ImportError:
-        pass
-    return "{}-{}.{}".format(osname, version, release)
diff --git a/spaces/Team-PIXEL/PIXEL/app.py b/spaces/Team-PIXEL/PIXEL/app.py
deleted file mode 100644
index d75a1e0e5a6f421cf31dcffe8be4df81cc8314f6..0000000000000000000000000000000000000000
--- a/spaces/Team-PIXEL/PIXEL/app.py
+++ /dev/null
@@ -1,192 +0,0 @@
-import math
-import os
-import sys
-
-import gradio as gr
-import matplotlib.pyplot as plt
-import numpy as np
-from PIL import Image
-import torch
-import torchvision
-
-os.system("git clone https://github.com/xplip/pixel.git")
-sys.path.append('./pixel')
-
-from transformers import set_seed
-from pixel.src.pixel import (
-    PIXELConfig,
-    PIXELForPreTraining,
-    SpanMaskingGenerator,
-    PyGameTextRenderer,
-    get_transforms,
-    resize_model_embeddings,
-    truncate_decoder_pos_embeddings,
-    get_attention_mask
-)
-
-model_name_or_path = "Team-PIXEL/pixel-base"
-max_seq_length = 529
-text_renderer = PyGameTextRenderer.from_pretrained(model_name_or_path, max_seq_length=max_seq_length)
-config = PIXELConfig.from_pretrained(model_name_or_path)
-model = PIXELForPreTraining.from_pretrained(model_name_or_path, config=config)
-
-def clip(x: torch.Tensor):
-    x = torch.einsum("chw->hwc", x)
-    x = torch.clip(x * 255, 0, 255)
-    x = torch.einsum("hwc->chw", x)
-    return x
-
-def get_image(img: torch.Tensor, do_clip: bool = True):
-    if do_clip:
-        img = clip(img)
-    img = torchvision.utils.make_grid(img, normalize=True)
-    image = Image.fromarray(
-        img.mul(255).clamp(0, 255).byte().permute(1, 2, 0).cpu().numpy()
-    )
-    return image
-
-def inference(text: str, mask_ratio: float = 0.25, max_span_length: int = 6, seed: int = 42):
-    config.update({"mask_ratio": mask_ratio})
-    resize_model_embeddings(model, max_seq_length)
-    truncate_decoder_pos_embeddings(model, max_seq_length)
-
-    set_seed(seed)
-
-    transforms = get_transforms(
-        do_resize=True,
-        size=(text_renderer.pixels_per_patch, text_renderer.pixels_per_patch * text_renderer.max_seq_length),
-    )
-
-    encoding = text_renderer(text=text)
-    attention_mask = get_attention_mask(
-        num_text_patches=encoding.num_text_patches, seq_length=text_renderer.max_seq_length
-    )
-
-    img = transforms(Image.fromarray(encoding.pixel_values)).unsqueeze(0)
-    attention_mask = attention_mask.unsqueeze(0)
-    inputs = {"pixel_values": img.float(), "attention_mask": attention_mask}
-
-    mask_generator = SpanMaskingGenerator(
-        num_patches=text_renderer.max_seq_length,
-        num_masking_patches=math.ceil(mask_ratio * text_renderer.max_seq_length),
-        max_span_length=max_span_length,
-        spacing="span"
-    )
-    mask = torch.tensor(mask_generator(num_text_patches=(encoding.num_text_patches + 1))).unsqueeze(0)
-    inputs.update({"patch_mask": mask})
-
-    model.eval()
-    with torch.no_grad():
-        outputs = model(**inputs)
-
-    predictions = model.unpatchify(outputs["logits"]).detach().cpu().squeeze()
-
-    mask = outputs["mask"].detach().cpu()
-    mask = mask.unsqueeze(-1).repeat(1, 1, text_renderer.pixels_per_patch ** 2 * 3)
-    mask = model.unpatchify(mask).squeeze()  # 1 is removing, 0 is keeping
-
-    attention_mask = attention_mask.unsqueeze(-1).repeat(1, 1, text_renderer.pixels_per_patch ** 2 * 3)
-    attention_mask = model.unpatchify(attention_mask).squeeze()
-
-    original_img = model.unpatchify(model.patchify(img)).squeeze()
-
-    im_masked = original_img * (1 - (torch.bitwise_and(mask == 1, attention_mask == 1)).long())
-
-    masked_predictions = predictions * mask * attention_mask
-
-    reconstruction = im_masked + masked_predictions
-
-    return [get_image(original_img), get_image(im_masked), get_image(masked_predictions, do_clip=False), get_image(reconstruction, do_clip=False)]
-  
-examples = [
-    ["Penguins are designed to be streamlined and hydrodynamic, so having long legs would add extra drag. Having short legs with webbed feet to act like rudders, helps to give them that torpedo-like figure. If we compare bird anatomy with humans, we would see something a bit peculiar. By taking a look at the side-by-side image in Figure 1, you can see how their leg bones compare to ours. What most people mistake for knees are actually the ankles of the birds. This gives the illusion that bird knees bend opposite of ours. The knees are actually tucked up inside the body cavity of the bird! So how does this look inside of a penguin? In the images below, you can see boxes surrounding the penguins’ knees.", 0.2, 6, 42],
-    ["Félicette didn’t seem like a typical astronaut. She weighed just five and a half pounds. She’d spent most of her life on the streets of Paris. And Félicette was a cat, one of 14 trained by French scientists for space flight. In 1963, she went where no feline had gone before. Chosen for her calm demeanor and low weight, Félicette was strapped into a rocket in October of that year. She spent 15 minutes on a dizzying flight to the stars before returning safely to earth. Her legacy, however, has been largely forgotten. While other space animals like Laika the dog and Ham the chimp have been celebrated, Félicette became a footnote of history. This is the story of the only cat to go to space.", 0.25, 4, 42],
-    ["In many, many ways, fish of the species Brienomyrus brachyistius do not speak at all like Barack Obama. For starters, they communicate not through a spoken language but through electrical pulses booped out by specialized organs found near the tail. Their vocabulary is also quite unpresidentially poor, with each individual capable of producing just one electric wave—a unique but monotonous signal. “It’s even simpler than Morse code,” Bruce Carlson, a biologist at Washington University in St. Louis who studies Brienomyrus fish, told me. In at least one significant way, though, fish of the species Brienomyrus brachyistius do speak a little bit like Barack Obama. When they want to send an important message… They stop, just for a moment. Those gaps tend to occur in very particular patterns, right before fishy phrases and sentences with “high-information content” about property, say, or courtship, Carlson said. Electric fish have, like the former president, mastered the art of the dramatic pause—a rhetorical trick that can help listeners cue in more strongly to what speakers have to say next, Carlson and his colleagues report in a study published today in Current Biology.", 0.5, 1, 42],
-]
-placeholder_text = "Our message is simple. Because we truly believe in our peanut-loving hearts that peanuts make everything better. Peanuts are perfectly powerful because they're packed with nutrition and they bring people together. Our thirst for peanut knowledge is unquenchable, so we’re always sharing snackable news stories about the benefits of peanuts, recent stats, research, etc. Our passion for peanuts is infectious. We root for peanuts as if they were a home run away from winning it all. We care about peanuts and the people who grow them. We give shout-outs to those who lift up and promote peanuts and the peanut story. We’re an authority on peanuts and we're anything but boring."
-
-demo = gr.Blocks(css="#output_image {width: auto; display: block; margin-left: auto; margin-right: auto;} #button {display: block; margin: 0 auto;}")
-
-with demo:
-    gr.Markdown("## PIXEL Masked Autoencoding")
-    gr.Markdown("Gradio demo for [PIXEL](https://huggingface.co/Team-PIXEL/pixel-base), introduced in [Language Modelling with Pixels](https://arxiv.org/abs/2207.06991). To use it, simply input your piece of text or click one of the examples to load them. Read more at the links below.")
-    with gr.Row():
-        with gr.Column():
-            tb_text = gr.Textbox(
-                lines=1,
-                label="Text",
-                placeholder=placeholder_text)
-            sl_ratio = gr.Slider(
-                minimum=0.01,
-                maximum=1.0,
-                step=0.01,
-                value=0.25,
-                label="Span masking ratio",
-            )
-            sl_len = gr.Slider(
-                minimum=1,
-                maximum=6,
-                step=1,
-                value=6,
-                label="Masking max span length",
-            )
-            sl_seed = gr.Slider(
-                minimum=0,
-                maximum=1000,
-                step=1,
-                value=42,
-                label="Random seed"
-            )
-            with gr.Box().style(rounded=False):
-                btn = gr.Button("Run", variant="primary", elem_id="button")
-        with gr.Column():
-            with gr.Row():
-                with gr.Column():
-                    with gr.Box().style(rounded=False):
-                        gr.Markdown("**Original**")
-                        out_original = gr.Image(
-                            type="pil",
-                            label="Original",
-                            show_label=False,
-                            elem_id="output_image"
-                        )
-                    with gr.Box().style(rounded=False):
-                        gr.Markdown("**Masked Predictions**")
-                        out_masked_pred = gr.Image(
-                            type="pil",
-                            label="Masked Predictions",
-                            show_label=False,
-                            elem_id="output_image"
-                        )
-                with gr.Column():
-                    with gr.Box().style(rounded=False):
-                        gr.Markdown("**Masked**")
-                        out_masked = gr.Image(
-                            type="pil",
-                            label="Masked",
-                            show_label=False,
-                            elem_id="output_image"
-                        )
-                    with gr.Box().style(rounded=False):
-                        gr.Markdown("**Reconstruction**")
-                        out_reconstruction = gr.Image(
-                            type="pil",
-                            label="Reconstruction",
-                            show_label=False,
-                            elem_id="output_image"
-                        )
-    with gr.Row():
-        with gr.Box().style(rounded=False):
-            gr.Markdown("### Examples")
-            gr_examples = gr.Examples(
-                examples,
-                inputs=[tb_text, sl_ratio, sl_len, sl_seed],
-                outputs=[out_original, out_masked, out_masked_pred, out_reconstruction],
-                fn=inference,
-                cache_examples=True
-            )
-    gr.HTML("<p style='text-align: center'><a href='https://arxiv.org/abs/2207.06991' target='_blank'><b>Paper</b></a> | <a href='https://github.com/xplip/pixel' target='_blank'><b>Github</b></a></p>")
-    gr.HTML("<center><img src='https://visitor-badge.glitch.me/badge?page_id=Team-PIXEL/PIXEL' alt='visitor badge'></center>")
-    
-    btn.click(fn=inference, inputs=[tb_text, sl_ratio, sl_len, sl_seed], outputs=[out_original, out_masked, out_masked_pred, out_reconstruction])
-demo.launch(debug=True)
diff --git a/spaces/Tiredmaker/OKC/app.py b/spaces/Tiredmaker/OKC/app.py
deleted file mode 100644
index 781d9c7d84131a0f09a98b72d0a49107fa9a6ed9..0000000000000000000000000000000000000000
--- a/spaces/Tiredmaker/OKC/app.py
+++ /dev/null
@@ -1,83 +0,0 @@
-import requests
-import gradio as gr
-from requests.exceptions import HTTPError
-
-
-BaseApi = "https://api.openai.com/v1"
-
-# Rate limits for each model
-RateLimitPerModel = {
-    "gpt-3.5-turbo": 2000, # New pay-as-go keys start with 2k for 48 hours
-    "gpt-4": 200,
-    "gpt-4-32k": 1000
-}
-
-def get_available_models(api_key):
-    headers = {"Authorization": f"Bearer {api_key}"}
-    url = f"{BaseApi}/engines"
-
-    try:
-        response = requests.get(url, headers=headers)
-        response_data = response.json()
-        available_models = [model["id"] for model in response_data.get("data", []) if model["id"] in {"gpt-4", "gpt-4-32k", "gpt-3.5-turbo"}]
-        return available_models
-    except Exception as e:
-        return []
-
-def check_key_status(api_key, model):
-    headers = {"Authorization": f"Bearer {api_key}"}
-    url = f"{BaseApi}/chat/completions"
-
-    data = {
-        "model": model,
-        "messages": [{"role": "user", "content": ""}],
-        "max_tokens": -1
-    }
-
-    try:
-        response = requests.post(url, headers=headers, json=data)
-        response_data = response.json()
-
-        if response.status_code == 401:
-            return "Error: Invalid API key"
-
-        error_type = response_data.get("error", {}).get("type", "")
-        if error_type == "insufficient_quota" and model in {"gpt-4", "gpt-4-32k"}:
-            return f"Error: The key for {model} is out of quota, but has gpt4"
-        elif error_type in ["insufficient_quota", "billing_not_active", "access_terminated"]:
-            return f"Error: The key for {model} is either out of quota, inactive, or access is terminated."
-
-        ratelimited = response.status_code == 429
-        if (response.status_code == 400 and error_type == "invalid_request_error") or ratelimited:
-            ratelimit = response.headers.get("x-ratelimit-limit-requests", "0")
-            org = response.headers.get("openai-organization", "user-xyz")
-            is_trial_key = "Trial Key" if int(ratelimit) < RateLimitPerModel.get(model, 0) else "Paid Key"
-            return f"Key for {model} is working. Ratelimit: {ratelimit}, Organization: {org}, Key Type: {is_trial_key}"
-
-    except HTTPError as http_err:
-        return f"HTTP error occurred: {http_err}"
-    except Exception as e:
-        return f"Error occurred: {e}"
-
-def check_models(api_key):
-    available_models = get_available_models(api_key)
-    if not available_models:
-        return "Error occurred: Unable to retrieve available models. Please check your API key."
-
-    model_info = "\n".join([check_key_status(api_key, model) for model in available_models])
-    return model_info
-
-# Define Gradio interface with a button to trigger model checking
-def trigger_model_check(api_key):
-    return check_models(api_key)
-
-iface = gr.Interface(
-    fn=trigger_model_check,
-    inputs=gr.inputs.Textbox(placeholder="Enter your OpenAI API key", type="text"),
-    outputs=gr.outputs.Textbox(),
-    live=False,
-    title="OKC",
-    allow_flagging=False,  # Disable flagging to prevent unnecessary reporting
-)
-
-iface.launch()
diff --git a/spaces/Truym/rvc-pendu/infer_pack/models_onnx.py b/spaces/Truym/rvc-pendu/infer_pack/models_onnx.py
deleted file mode 100644
index 3cdae2f7f8591a1e43b1d8520baa37b7e9744d72..0000000000000000000000000000000000000000
--- a/spaces/Truym/rvc-pendu/infer_pack/models_onnx.py
+++ /dev/null
@@ -1,849 +0,0 @@
-import math, pdb, os
-from time import time as ttime
-import torch
-from torch import nn
-from torch.nn import functional as F
-from infer_pack import modules
-from infer_pack import attentions
-from infer_pack import commons
-from infer_pack.commons import init_weights, get_padding
-from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
-from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
-from infer_pack.commons import init_weights
-import numpy as np
-from infer_pack import commons
-
-
-class TextEncoder256(nn.Module):
-    def __init__(
-        self,
-        out_channels,
-        hidden_channels,
-        filter_channels,
-        n_heads,
-        n_layers,
-        kernel_size,
-        p_dropout,
-        f0=True,
-    ):
-        super().__init__()
-        self.out_channels = out_channels
-        self.hidden_channels = hidden_channels
-        self.filter_channels = filter_channels
-        self.n_heads = n_heads
-        self.n_layers = n_layers
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.emb_phone = nn.Linear(256, hidden_channels)
-        self.lrelu = nn.LeakyReLU(0.1, inplace=True)
-        if f0 == True:
-            self.emb_pitch = nn.Embedding(256, hidden_channels)  # pitch 256
-        self.encoder = attentions.Encoder(
-            hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
-        )
-        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
-
-    def forward(self, phone, pitch, lengths):
-        if pitch == None:
-            x = self.emb_phone(phone)
-        else:
-            x = self.emb_phone(phone) + self.emb_pitch(pitch)
-        x = x * math.sqrt(self.hidden_channels)  # [b, t, h]
-        x = self.lrelu(x)
-        x = torch.transpose(x, 1, -1)  # [b, h, t]
-        x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
-            x.dtype
-        )
-        x = self.encoder(x * x_mask, x_mask)
-        stats = self.proj(x) * x_mask
-
-        m, logs = torch.split(stats, self.out_channels, dim=1)
-        return m, logs, x_mask
-
-
-class TextEncoder256Sim(nn.Module):
-    def __init__(
-        self,
-        out_channels,
-        hidden_channels,
-        filter_channels,
-        n_heads,
-        n_layers,
-        kernel_size,
-        p_dropout,
-        f0=True,
-    ):
-        super().__init__()
-        self.out_channels = out_channels
-        self.hidden_channels = hidden_channels
-        self.filter_channels = filter_channels
-        self.n_heads = n_heads
-        self.n_layers = n_layers
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.emb_phone = nn.Linear(256, hidden_channels)
-        self.lrelu = nn.LeakyReLU(0.1, inplace=True)
-        if f0 == True:
-            self.emb_pitch = nn.Embedding(256, hidden_channels)  # pitch 256
-        self.encoder = attentions.Encoder(
-            hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
-        )
-        self.proj = nn.Conv1d(hidden_channels, out_channels, 1)
-
-    def forward(self, phone, pitch, lengths):
-        if pitch == None:
-            x = self.emb_phone(phone)
-        else:
-            x = self.emb_phone(phone) + self.emb_pitch(pitch)
-        x = x * math.sqrt(self.hidden_channels)  # [b, t, h]
-        x = self.lrelu(x)
-        x = torch.transpose(x, 1, -1)  # [b, h, t]
-        x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
-            x.dtype
-        )
-        x = self.encoder(x * x_mask, x_mask)
-        x = self.proj(x) * x_mask
-        return x, x_mask
-
-
-class ResidualCouplingBlock(nn.Module):
-    def __init__(
-        self,
-        channels,
-        hidden_channels,
-        kernel_size,
-        dilation_rate,
-        n_layers,
-        n_flows=4,
-        gin_channels=0,
-    ):
-        super().__init__()
-        self.channels = channels
-        self.hidden_channels = hidden_channels
-        self.kernel_size = kernel_size
-        self.dilation_rate = dilation_rate
-        self.n_layers = n_layers
-        self.n_flows = n_flows
-        self.gin_channels = gin_channels
-
-        self.flows = nn.ModuleList()
-        for i in range(n_flows):
-            self.flows.append(
-                modules.ResidualCouplingLayer(
-                    channels,
-                    hidden_channels,
-                    kernel_size,
-                    dilation_rate,
-                    n_layers,
-                    gin_channels=gin_channels,
-                    mean_only=True,
-                )
-            )
-            self.flows.append(modules.Flip())
-
-    def forward(self, x, x_mask, g=None, reverse=False):
-        if not reverse:
-            for flow in self.flows:
-                x, _ = flow(x, x_mask, g=g, reverse=reverse)
-        else:
-            for flow in reversed(self.flows):
-                x = flow(x, x_mask, g=g, reverse=reverse)
-        return x
-
-    def remove_weight_norm(self):
-        for i in range(self.n_flows):
-            self.flows[i * 2].remove_weight_norm()
-
-
-class PosteriorEncoder(nn.Module):
-    def __init__(
-        self,
-        in_channels,
-        out_channels,
-        hidden_channels,
-        kernel_size,
-        dilation_rate,
-        n_layers,
-        gin_channels=0,
-    ):
-        super().__init__()
-        self.in_channels = in_channels
-        self.out_channels = out_channels
-        self.hidden_channels = hidden_channels
-        self.kernel_size = kernel_size
-        self.dilation_rate = dilation_rate
-        self.n_layers = n_layers
-        self.gin_channels = gin_channels
-
-        self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
-        self.enc = modules.WN(
-            hidden_channels,
-            kernel_size,
-            dilation_rate,
-            n_layers,
-            gin_channels=gin_channels,
-        )
-        self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
-
-    def forward(self, x, x_lengths, g=None):
-        x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(
-            x.dtype
-        )
-        x = self.pre(x) * x_mask
-        x = self.enc(x, x_mask, g=g)
-        stats = self.proj(x) * x_mask
-        m, logs = torch.split(stats, self.out_channels, dim=1)
-        z = (m + torch.randn_like(m) * torch.exp(logs)) * x_mask
-        return z, m, logs, x_mask
-
-    def remove_weight_norm(self):
-        self.enc.remove_weight_norm()
-
-
-class Generator(torch.nn.Module):
-    def __init__(
-        self,
-        initial_channel,
-        resblock,
-        resblock_kernel_sizes,
-        resblock_dilation_sizes,
-        upsample_rates,
-        upsample_initial_channel,
-        upsample_kernel_sizes,
-        gin_channels=0,
-    ):
-        super(Generator, self).__init__()
-        self.num_kernels = len(resblock_kernel_sizes)
-        self.num_upsamples = len(upsample_rates)
-        self.conv_pre = Conv1d(
-            initial_channel, upsample_initial_channel, 7, 1, padding=3
-        )
-        resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
-
-        self.ups = nn.ModuleList()
-        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
-            self.ups.append(
-                weight_norm(
-                    ConvTranspose1d(
-                        upsample_initial_channel // (2**i),
-                        upsample_initial_channel // (2 ** (i + 1)),
-                        k,
-                        u,
-                        padding=(k - u) // 2,
-                    )
-                )
-            )
-
-        self.resblocks = nn.ModuleList()
-        for i in range(len(self.ups)):
-            ch = upsample_initial_channel // (2 ** (i + 1))
-            for j, (k, d) in enumerate(
-                zip(resblock_kernel_sizes, resblock_dilation_sizes)
-            ):
-                self.resblocks.append(resblock(ch, k, d))
-
-        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
-        self.ups.apply(init_weights)
-
-        if gin_channels != 0:
-            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
-
-    def forward(self, x, g=None):
-        x = self.conv_pre(x)
-        if g is not None:
-            x = x + self.cond(g)
-
-        for i in range(self.num_upsamples):
-            x = F.leaky_relu(x, modules.LRELU_SLOPE)
-            x = self.ups[i](x)
-            xs = None
-            for j in range(self.num_kernels):
-                if xs is None:
-                    xs = self.resblocks[i * self.num_kernels + j](x)
-                else:
-                    xs += self.resblocks[i * self.num_kernels + j](x)
-            x = xs / self.num_kernels
-        x = F.leaky_relu(x)
-        x = self.conv_post(x)
-        x = torch.tanh(x)
-
-        return x
-
-    def remove_weight_norm(self):
-        for l in self.ups:
-            remove_weight_norm(l)
-        for l in self.resblocks:
-            l.remove_weight_norm()
-
-
-class SineGen(torch.nn.Module):
-    """Definition of sine generator
-    SineGen(samp_rate, harmonic_num = 0,
-            sine_amp = 0.1, noise_std = 0.003,
-            voiced_threshold = 0,
-            flag_for_pulse=False)
-    samp_rate: sampling rate in Hz
-    harmonic_num: number of harmonic overtones (default 0)
-    sine_amp: amplitude of sine-wavefrom (default 0.1)
-    noise_std: std of Gaussian noise (default 0.003)
-    voiced_thoreshold: F0 threshold for U/V classification (default 0)
-    flag_for_pulse: this SinGen is used inside PulseGen (default False)
-    Note: when flag_for_pulse is True, the first time step of a voiced
-        segment is always sin(np.pi) or cos(0)
-    """
-
-    def __init__(
-        self,
-        samp_rate,
-        harmonic_num=0,
-        sine_amp=0.1,
-        noise_std=0.003,
-        voiced_threshold=0,
-        flag_for_pulse=False,
-    ):
-        super(SineGen, self).__init__()
-        self.sine_amp = sine_amp
-        self.noise_std = noise_std
-        self.harmonic_num = harmonic_num
-        self.dim = self.harmonic_num + 1
-        self.sampling_rate = samp_rate
-        self.voiced_threshold = voiced_threshold
-
-    def _f02uv(self, f0):
-        # generate uv signal
-        uv = torch.ones_like(f0)
-        uv = uv * (f0 > self.voiced_threshold)
-        return uv
-
-    def forward(self, f0, upp):
-        """sine_tensor, uv = forward(f0)
-        input F0: tensor(batchsize=1, length, dim=1)
-                  f0 for unvoiced steps should be 0
-        output sine_tensor: tensor(batchsize=1, length, dim)
-        output uv: tensor(batchsize=1, length, 1)
-        """
-        with torch.no_grad():
-            f0 = f0[:, None].transpose(1, 2)
-            f0_buf = torch.zeros(f0.shape[0], f0.shape[1], self.dim, device=f0.device)
-            # fundamental component
-            f0_buf[:, :, 0] = f0[:, :, 0]
-            for idx in np.arange(self.harmonic_num):
-                f0_buf[:, :, idx + 1] = f0_buf[:, :, 0] * (
-                    idx + 2
-                )  # idx + 2: the (idx+1)-th overtone, (idx+2)-th harmonic
-            rad_values = (f0_buf / self.sampling_rate) % 1  ###%1意味着n_har的乘积无法后处理优化
-            rand_ini = torch.rand(
-                f0_buf.shape[0], f0_buf.shape[2], device=f0_buf.device
-            )
-            rand_ini[:, 0] = 0
-            rad_values[:, 0, :] = rad_values[:, 0, :] + rand_ini
-            tmp_over_one = torch.cumsum(rad_values, 1)  # % 1  #####%1意味着后面的cumsum无法再优化
-            tmp_over_one *= upp
-            tmp_over_one = F.interpolate(
-                tmp_over_one.transpose(2, 1),
-                scale_factor=upp,
-                mode="linear",
-                align_corners=True,
-            ).transpose(2, 1)
-            rad_values = F.interpolate(
-                rad_values.transpose(2, 1), scale_factor=upp, mode="nearest"
-            ).transpose(
-                2, 1
-            )  #######
-            tmp_over_one %= 1
-            tmp_over_one_idx = (tmp_over_one[:, 1:, :] - tmp_over_one[:, :-1, :]) < 0
-            cumsum_shift = torch.zeros_like(rad_values)
-            cumsum_shift[:, 1:, :] = tmp_over_one_idx * -1.0
-            sine_waves = torch.sin(
-                torch.cumsum(rad_values + cumsum_shift, dim=1) * 2 * np.pi
-            )
-            sine_waves = sine_waves * self.sine_amp
-            uv = self._f02uv(f0)
-            uv = F.interpolate(
-                uv.transpose(2, 1), scale_factor=upp, mode="nearest"
-            ).transpose(2, 1)
-            noise_amp = uv * self.noise_std + (1 - uv) * self.sine_amp / 3
-            noise = noise_amp * torch.randn_like(sine_waves)
-            sine_waves = sine_waves * uv + noise
-        return sine_waves, uv, noise
-
-
-class SourceModuleHnNSF(torch.nn.Module):
-    """SourceModule for hn-nsf
-    SourceModule(sampling_rate, harmonic_num=0, sine_amp=0.1,
-                 add_noise_std=0.003, voiced_threshod=0)
-    sampling_rate: sampling_rate in Hz
-    harmonic_num: number of harmonic above F0 (default: 0)
-    sine_amp: amplitude of sine source signal (default: 0.1)
-    add_noise_std: std of additive Gaussian noise (default: 0.003)
-        note that amplitude of noise in unvoiced is decided
-        by sine_amp
-    voiced_threshold: threhold to set U/V given F0 (default: 0)
-    Sine_source, noise_source = SourceModuleHnNSF(F0_sampled)
-    F0_sampled (batchsize, length, 1)
-    Sine_source (batchsize, length, 1)
-    noise_source (batchsize, length 1)
-    uv (batchsize, length, 1)
-    """
-
-    def __init__(
-        self,
-        sampling_rate,
-        harmonic_num=0,
-        sine_amp=0.1,
-        add_noise_std=0.003,
-        voiced_threshod=0,
-        is_half=True,
-    ):
-        super(SourceModuleHnNSF, self).__init__()
-
-        self.sine_amp = sine_amp
-        self.noise_std = add_noise_std
-        self.is_half = is_half
-        # to produce sine waveforms
-        self.l_sin_gen = SineGen(
-            sampling_rate, harmonic_num, sine_amp, add_noise_std, voiced_threshod
-        )
-
-        # to merge source harmonics into a single excitation
-        self.l_linear = torch.nn.Linear(harmonic_num + 1, 1)
-        self.l_tanh = torch.nn.Tanh()
-
-    def forward(self, x, upp=None):
-        sine_wavs, uv, _ = self.l_sin_gen(x, upp)
-        if self.is_half:
-            sine_wavs = sine_wavs.half()
-        sine_merge = self.l_tanh(self.l_linear(sine_wavs))
-        return sine_merge, None, None  # noise, uv
-
-
-class GeneratorNSF(torch.nn.Module):
-    def __init__(
-        self,
-        initial_channel,
-        resblock,
-        resblock_kernel_sizes,
-        resblock_dilation_sizes,
-        upsample_rates,
-        upsample_initial_channel,
-        upsample_kernel_sizes,
-        gin_channels,
-        sr,
-        is_half=False,
-    ):
-        super(GeneratorNSF, self).__init__()
-        self.num_kernels = len(resblock_kernel_sizes)
-        self.num_upsamples = len(upsample_rates)
-
-        self.f0_upsamp = torch.nn.Upsample(scale_factor=np.prod(upsample_rates))
-        self.m_source = SourceModuleHnNSF(
-            sampling_rate=sr, harmonic_num=0, is_half=is_half
-        )
-        self.noise_convs = nn.ModuleList()
-        self.conv_pre = Conv1d(
-            initial_channel, upsample_initial_channel, 7, 1, padding=3
-        )
-        resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
-
-        self.ups = nn.ModuleList()
-        for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
-            c_cur = upsample_initial_channel // (2 ** (i + 1))
-            self.ups.append(
-                weight_norm(
-                    ConvTranspose1d(
-                        upsample_initial_channel // (2**i),
-                        upsample_initial_channel // (2 ** (i + 1)),
-                        k,
-                        u,
-                        padding=(k - u) // 2,
-                    )
-                )
-            )
-            if i + 1 < len(upsample_rates):
-                stride_f0 = np.prod(upsample_rates[i + 1 :])
-                self.noise_convs.append(
-                    Conv1d(
-                        1,
-                        c_cur,
-                        kernel_size=stride_f0 * 2,
-                        stride=stride_f0,
-                        padding=stride_f0 // 2,
-                    )
-                )
-            else:
-                self.noise_convs.append(Conv1d(1, c_cur, kernel_size=1))
-
-        self.resblocks = nn.ModuleList()
-        for i in range(len(self.ups)):
-            ch = upsample_initial_channel // (2 ** (i + 1))
-            for j, (k, d) in enumerate(
-                zip(resblock_kernel_sizes, resblock_dilation_sizes)
-            ):
-                self.resblocks.append(resblock(ch, k, d))
-
-        self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
-        self.ups.apply(init_weights)
-
-        if gin_channels != 0:
-            self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
-
-        self.upp = np.prod(upsample_rates)
-
-    def forward(self, x, f0, g=None):
-        har_source, noi_source, uv = self.m_source(f0, self.upp)
-        har_source = har_source.transpose(1, 2)
-        x = self.conv_pre(x)
-        if g is not None:
-            x = x + self.cond(g)
-
-        for i in range(self.num_upsamples):
-            x = F.leaky_relu(x, modules.LRELU_SLOPE)
-            x = self.ups[i](x)
-            x_source = self.noise_convs[i](har_source)
-            x = x + x_source
-            xs = None
-            for j in range(self.num_kernels):
-                if xs is None:
-                    xs = self.resblocks[i * self.num_kernels + j](x)
-                else:
-                    xs += self.resblocks[i * self.num_kernels + j](x)
-            x = xs / self.num_kernels
-        x = F.leaky_relu(x)
-        x = self.conv_post(x)
-        x = torch.tanh(x)
-        return x
-
-    def remove_weight_norm(self):
-        for l in self.ups:
-            remove_weight_norm(l)
-        for l in self.resblocks:
-            l.remove_weight_norm()
-
-
-sr2sr = {
-    "32k": 32000,
-    "40k": 40000,
-    "48k": 48000,
-}
-
-
-class SynthesizerTrnMs256NSFsid(nn.Module):
-    def __init__(
-        self,
-        spec_channels,
-        segment_size,
-        inter_channels,
-        hidden_channels,
-        filter_channels,
-        n_heads,
-        n_layers,
-        kernel_size,
-        p_dropout,
-        resblock,
-        resblock_kernel_sizes,
-        resblock_dilation_sizes,
-        upsample_rates,
-        upsample_initial_channel,
-        upsample_kernel_sizes,
-        spk_embed_dim,
-        gin_channels,
-        sr,
-        **kwargs
-    ):
-        super().__init__()
-        if type(sr) == type("strr"):
-            sr = sr2sr[sr]
-        self.spec_channels = spec_channels
-        self.inter_channels = inter_channels
-        self.hidden_channels = hidden_channels
-        self.filter_channels = filter_channels
-        self.n_heads = n_heads
-        self.n_layers = n_layers
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.resblock = resblock
-        self.resblock_kernel_sizes = resblock_kernel_sizes
-        self.resblock_dilation_sizes = resblock_dilation_sizes
-        self.upsample_rates = upsample_rates
-        self.upsample_initial_channel = upsample_initial_channel
-        self.upsample_kernel_sizes = upsample_kernel_sizes
-        self.segment_size = segment_size
-        self.gin_channels = gin_channels
-        # self.hop_length = hop_length#
-        self.spk_embed_dim = spk_embed_dim
-        self.enc_p = TextEncoder256(
-            inter_channels,
-            hidden_channels,
-            filter_channels,
-            n_heads,
-            n_layers,
-            kernel_size,
-            p_dropout,
-        )
-        self.dec = GeneratorNSF(
-            inter_channels,
-            resblock,
-            resblock_kernel_sizes,
-            resblock_dilation_sizes,
-            upsample_rates,
-            upsample_initial_channel,
-            upsample_kernel_sizes,
-            gin_channels=gin_channels,
-            sr=sr,
-            is_half=kwargs["is_half"],
-        )
-        self.enc_q = PosteriorEncoder(
-            spec_channels,
-            inter_channels,
-            hidden_channels,
-            5,
-            1,
-            16,
-            gin_channels=gin_channels,
-        )
-        self.flow = ResidualCouplingBlock(
-            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
-        )
-        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
-        print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
-
-    def remove_weight_norm(self):
-        self.dec.remove_weight_norm()
-        self.flow.remove_weight_norm()
-        self.enc_q.remove_weight_norm()
-
-    def forward(self, phone, phone_lengths, pitch, nsff0, sid, rnd, max_len=None):
-        g = self.emb_g(sid).unsqueeze(-1)
-        m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
-        z_p = (m_p + torch.exp(logs_p) * rnd) * x_mask
-        z = self.flow(z_p, x_mask, g=g, reverse=True)
-        o = self.dec((z * x_mask)[:, :, :max_len], nsff0, g=g)
-        return o
-
-
-class SynthesizerTrnMs256NSFsid_sim(nn.Module):
-    """
-    Synthesizer for Training
-    """
-
-    def __init__(
-        self,
-        spec_channels,
-        segment_size,
-        inter_channels,
-        hidden_channels,
-        filter_channels,
-        n_heads,
-        n_layers,
-        kernel_size,
-        p_dropout,
-        resblock,
-        resblock_kernel_sizes,
-        resblock_dilation_sizes,
-        upsample_rates,
-        upsample_initial_channel,
-        upsample_kernel_sizes,
-        spk_embed_dim,
-        # hop_length,
-        gin_channels=0,
-        use_sdp=True,
-        **kwargs
-    ):
-        super().__init__()
-        self.spec_channels = spec_channels
-        self.inter_channels = inter_channels
-        self.hidden_channels = hidden_channels
-        self.filter_channels = filter_channels
-        self.n_heads = n_heads
-        self.n_layers = n_layers
-        self.kernel_size = kernel_size
-        self.p_dropout = p_dropout
-        self.resblock = resblock
-        self.resblock_kernel_sizes = resblock_kernel_sizes
-        self.resblock_dilation_sizes = resblock_dilation_sizes
-        self.upsample_rates = upsample_rates
-        self.upsample_initial_channel = upsample_initial_channel
-        self.upsample_kernel_sizes = upsample_kernel_sizes
-        self.segment_size = segment_size
-        self.gin_channels = gin_channels
-        # self.hop_length = hop_length#
-        self.spk_embed_dim = spk_embed_dim
-        self.enc_p = TextEncoder256Sim(
-            inter_channels,
-            hidden_channels,
-            filter_channels,
-            n_heads,
-            n_layers,
-            kernel_size,
-            p_dropout,
-        )
-        self.dec = GeneratorNSF(
-            inter_channels,
-            resblock,
-            resblock_kernel_sizes,
-            resblock_dilation_sizes,
-            upsample_rates,
-            upsample_initial_channel,
-            upsample_kernel_sizes,
-            gin_channels=gin_channels,
-            is_half=kwargs["is_half"],
-        )
-
-        self.flow = ResidualCouplingBlock(
-            inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
-        )
-        self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
-        print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
-
-    def remove_weight_norm(self):
-        self.dec.remove_weight_norm()
-        self.flow.remove_weight_norm()
-        self.enc_q.remove_weight_norm()
-
-    def forward(
-        self, phone, phone_lengths, pitch, pitchf, ds, max_len=None
-    ):  # y是spec不需要了现在
-        g = self.emb_g(ds.unsqueeze(0)).unsqueeze(-1)  # [b, 256, 1]##1是t，广播的
-        x, x_mask = self.enc_p(phone, pitch, phone_lengths)
-        x = self.flow(x, x_mask, g=g, reverse=True)
-        o = self.dec((x * x_mask)[:, :, :max_len], pitchf, g=g)
-        return o
-
-
-class MultiPeriodDiscriminator(torch.nn.Module):
-    def __init__(self, use_spectral_norm=False):
-        super(MultiPeriodDiscriminator, self).__init__()
-        periods = [2, 3, 5, 7, 11, 17]
-        # periods = [3, 5, 7, 11, 17, 23, 37]
-
-        discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
-        discs = discs + [
-            DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
-        ]
-        self.discriminators = nn.ModuleList(discs)
-
-    def forward(self, y, y_hat):
-        y_d_rs = []  #
-        y_d_gs = []
-        fmap_rs = []
-        fmap_gs = []
-        for i, d in enumerate(self.discriminators):
-            y_d_r, fmap_r = d(y)
-            y_d_g, fmap_g = d(y_hat)
-            # for j in range(len(fmap_r)):
-            #     print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
-            y_d_rs.append(y_d_r)
-            y_d_gs.append(y_d_g)
-            fmap_rs.append(fmap_r)
-            fmap_gs.append(fmap_g)
-
-        return y_d_rs, y_d_gs, fmap_rs, fmap_gs
-
-
-class DiscriminatorS(torch.nn.Module):
-    def __init__(self, use_spectral_norm=False):
-        super(DiscriminatorS, self).__init__()
-        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
-        self.convs = nn.ModuleList(
-            [
-                norm_f(Conv1d(1, 16, 15, 1, padding=7)),
-                norm_f(Conv1d(16, 64, 41, 4, groups=4, padding=20)),
-                norm_f(Conv1d(64, 256, 41, 4, groups=16, padding=20)),
-                norm_f(Conv1d(256, 1024, 41, 4, groups=64, padding=20)),
-                norm_f(Conv1d(1024, 1024, 41, 4, groups=256, padding=20)),
-                norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
-            ]
-        )
-        self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
-
-    def forward(self, x):
-        fmap = []
-
-        for l in self.convs:
-            x = l(x)
-            x = F.leaky_relu(x, modules.LRELU_SLOPE)
-            fmap.append(x)
-        x = self.conv_post(x)
-        fmap.append(x)
-        x = torch.flatten(x, 1, -1)
-
-        return x, fmap
-
-
-class DiscriminatorP(torch.nn.Module):
-    def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=False):
-        super(DiscriminatorP, self).__init__()
-        self.period = period
-        self.use_spectral_norm = use_spectral_norm
-        norm_f = weight_norm if use_spectral_norm == False else spectral_norm
-        self.convs = nn.ModuleList(
-            [
-                norm_f(
-                    Conv2d(
-                        1,
-                        32,
-                        (kernel_size, 1),
-                        (stride, 1),
-                        padding=(get_padding(kernel_size, 1), 0),
-                    )
-                ),
-                norm_f(
-                    Conv2d(
-                        32,
-                        128,
-                        (kernel_size, 1),
-                        (stride, 1),
-                        padding=(get_padding(kernel_size, 1), 0),
-                    )
-                ),
-                norm_f(
-                    Conv2d(
-                        128,
-                        512,
-                        (kernel_size, 1),
-                        (stride, 1),
-                        padding=(get_padding(kernel_size, 1), 0),
-                    )
-                ),
-                norm_f(
-                    Conv2d(
-                        512,
-                        1024,
-                        (kernel_size, 1),
-                        (stride, 1),
-                        padding=(get_padding(kernel_size, 1), 0),
-                    )
-                ),
-                norm_f(
-                    Conv2d(
-                        1024,
-                        1024,
-                        (kernel_size, 1),
-                        1,
-                        padding=(get_padding(kernel_size, 1), 0),
-                    )
-                ),
-            ]
-        )
-        self.conv_post = norm_f(Conv2d(1024, 1, (3, 1), 1, padding=(1, 0)))
-
-    def forward(self, x):
-        fmap = []
-
-        # 1d to 2d
-        b, c, t = x.shape
-        if t % self.period != 0:  # pad first
-            n_pad = self.period - (t % self.period)
-            x = F.pad(x, (0, n_pad), "reflect")
-            t = t + n_pad
-        x = x.view(b, c, t // self.period, self.period)
-
-        for l in self.convs:
-            x = l(x)
-            x = F.leaky_relu(x, modules.LRELU_SLOPE)
-            fmap.append(x)
-        x = self.conv_post(x)
-        fmap.append(x)
-        x = torch.flatten(x, 1, -1)
-
-        return x, fmap
diff --git a/spaces/Vijish/SkinDeep/README.md b/spaces/Vijish/SkinDeep/README.md
deleted file mode 100644
index 6243cac1a6bdfface70e803f29c041194a778faa..0000000000000000000000000000000000000000
--- a/spaces/Vijish/SkinDeep/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: SkinDeep
-emoji: 👁
-colorFrom: red
-colorTo: purple
-sdk: streamlit
-sdk_version: 1.2.0
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference
diff --git a/spaces/Volkopat/SegmentAnythingxGroundingDINO/groundingdino/util/__init__.py b/spaces/Volkopat/SegmentAnythingxGroundingDINO/groundingdino/util/__init__.py
deleted file mode 100644
index 168f9979a4623806934b0ff1102ac166704e7dec..0000000000000000000000000000000000000000
--- a/spaces/Volkopat/SegmentAnythingxGroundingDINO/groundingdino/util/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
diff --git a/spaces/Workhack/chatgpt-prompt-playground/static/css/main.8b8df126.css b/spaces/Workhack/chatgpt-prompt-playground/static/css/main.8b8df126.css
deleted file mode 100644
index 335452aa290c5ff244db8a501d2926e84205e08c..0000000000000000000000000000000000000000
--- a/spaces/Workhack/chatgpt-prompt-playground/static/css/main.8b8df126.css
+++ /dev/null
@@ -1,4 +0,0 @@
-/*
-! tailwindcss v3.3.2 | MIT License | https://tailwindcss.com
-*/*,:after,:before{border:0 solid #e5e7eb;box-sizing:border-box}:after,:before{--tw-content:""}html{-webkit-text-size-adjust:100%;-webkit-font-feature-settings:normal;font-feature-settings:normal;font-family:ui-sans-serif,system-ui,-apple-system,BlinkMacSystemFont,Segoe UI,Roboto,Helvetica Neue,Arial,Noto Sans,sans-serif,Apple Color Emoji,Segoe UI Emoji,Segoe UI Symbol,Noto Color Emoji;font-variation-settings:normal;line-height:1.5;tab-size:4}body{line-height:inherit;margin:0}hr{border-top-width:1px;color:inherit;height:0}abbr:where([title]){-webkit-text-decoration:underline dotted;text-decoration:underline dotted}h1,h2,h3,h4,h5,h6{font-size:inherit;font-weight:inherit}a{color:inherit;text-decoration:inherit}b,strong{font-weight:bolder}code,kbd,pre,samp{font-family:ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,Liberation Mono,Courier 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#0000,var(--tw-shadow);box-shadow:var(--tw-ring-offset-shadow,0 0 #0000),var(--tw-ring-shadow,0 0 #0000),var(--tw-shadow)}.shadow-md{--tw-shadow:0 4px 6px -1px rgba(0,0,0,.1),0 2px 4px -2px rgba(0,0,0,.1);--tw-shadow-colored:0 4px 6px -1px var(--tw-shadow-color),0 2px 4px -2px var(--tw-shadow-color)}.shadow-sm{--tw-shadow:0 1px 2px 0 rgba(0,0,0,.05);--tw-shadow-colored:0 1px 2px 0 var(--tw-shadow-color);box-shadow:0 0 #0000,0 0 #0000,var(--tw-shadow);box-shadow:var(--tw-ring-offset-shadow,0 0 #0000),var(--tw-ring-shadow,0 0 #0000),var(--tw-shadow)}.filter{-webkit-filter:var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow);filter:var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow)}
-/*# sourceMappingURL=main.8b8df126.css.map*/
\ No newline at end of file
diff --git a/spaces/XlalalaX/VITS-Umamusume-voice-synthesizer/utils.py b/spaces/XlalalaX/VITS-Umamusume-voice-synthesizer/utils.py
deleted file mode 100644
index 9794e0fc3463a5e8fad05c037cce64683059a6d3..0000000000000000000000000000000000000000
--- a/spaces/XlalalaX/VITS-Umamusume-voice-synthesizer/utils.py
+++ /dev/null
@@ -1,226 +0,0 @@
-import os
-import glob
-import sys
-import argparse
-import logging
-import json
-import subprocess
-import numpy as np
-from scipy.io.wavfile import read
-import torch
-
-MATPLOTLIB_FLAG = False
-
-logging.basicConfig(stream=sys.stdout, level=logging.ERROR)
-logger = logging
-
-
-def load_checkpoint(checkpoint_path, model, optimizer=None):
-    assert os.path.isfile(checkpoint_path)
-    checkpoint_dict = torch.load(checkpoint_path, map_location='cpu')
-    iteration = checkpoint_dict['iteration']
-    learning_rate = checkpoint_dict['learning_rate']
-    if optimizer is not None:
-        optimizer.load_state_dict(checkpoint_dict['optimizer'])
-    saved_state_dict = checkpoint_dict['model']
-    if hasattr(model, 'module'):
-        state_dict = model.module.state_dict()
-    else:
-        state_dict = model.state_dict()
-    new_state_dict = {}
-    for k, v in state_dict.items():
-        try:
-            new_state_dict[k] = saved_state_dict[k]
-        except:
-            logger.info("%s is not in the checkpoint" % k)
-            new_state_dict[k] = v
-    if hasattr(model, 'module'):
-        model.module.load_state_dict(new_state_dict)
-    else:
-        model.load_state_dict(new_state_dict)
-    logger.info("Loaded checkpoint '{}' (iteration {})".format(
-        checkpoint_path, iteration))
-    return model, optimizer, learning_rate, iteration
-
-
-def plot_spectrogram_to_numpy(spectrogram):
-    global MATPLOTLIB_FLAG
-    if not MATPLOTLIB_FLAG:
-        import matplotlib
-        matplotlib.use("Agg")
-        MATPLOTLIB_FLAG = True
-        mpl_logger = logging.getLogger('matplotlib')
-        mpl_logger.setLevel(logging.WARNING)
-    import matplotlib.pylab as plt
-    import numpy as np
-
-    fig, ax = plt.subplots(figsize=(10, 2))
-    im = ax.imshow(spectrogram, aspect="auto", origin="lower",
-                   interpolation='none')
-    plt.colorbar(im, ax=ax)
-    plt.xlabel("Frames")
-    plt.ylabel("Channels")
-    plt.tight_layout()
-
-    fig.canvas.draw()
-    data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
-    data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
-    plt.close()
-    return data
-
-
-def plot_alignment_to_numpy(alignment, info=None):
-    global MATPLOTLIB_FLAG
-    if not MATPLOTLIB_FLAG:
-        import matplotlib
-        matplotlib.use("Agg")
-        MATPLOTLIB_FLAG = True
-        mpl_logger = logging.getLogger('matplotlib')
-        mpl_logger.setLevel(logging.WARNING)
-    import matplotlib.pylab as plt
-    import numpy as np
-
-    fig, ax = plt.subplots(figsize=(6, 4))
-    im = ax.imshow(alignment.transpose(), aspect='auto', origin='lower',
-                   interpolation='none')
-    fig.colorbar(im, ax=ax)
-    xlabel = 'Decoder timestep'
-    if info is not None:
-        xlabel += '\n\n' + info
-    plt.xlabel(xlabel)
-    plt.ylabel('Encoder timestep')
-    plt.tight_layout()
-
-    fig.canvas.draw()
-    data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
-    data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
-    plt.close()
-    return data
-
-
-def load_wav_to_torch(full_path):
-    sampling_rate, data = read(full_path)
-    return torch.FloatTensor(data.astype(np.float32)), sampling_rate
-
-
-def load_filepaths_and_text(filename, split="|"):
-    with open(filename, encoding='utf-8') as f:
-        filepaths_and_text = [line.strip().split(split) for line in f]
-    return filepaths_and_text
-
-
-def get_hparams(init=True):
-    parser = argparse.ArgumentParser()
-    parser.add_argument('-c', '--config', type=str, default="./configs/base.json",
-                        help='JSON file for configuration')
-    parser.add_argument('-m', '--model', type=str, required=True,
-                        help='Model name')
-
-    args = parser.parse_args()
-    model_dir = os.path.join("./logs", args.model)
-
-    if not os.path.exists(model_dir):
-        os.makedirs(model_dir)
-
-    config_path = args.config
-    config_save_path = os.path.join(model_dir, "config.json")
-    if init:
-        with open(config_path, "r") as f:
-            data = f.read()
-        with open(config_save_path, "w") as f:
-            f.write(data)
-    else:
-        with open(config_save_path, "r") as f:
-            data = f.read()
-    config = json.loads(data)
-
-    hparams = HParams(**config)
-    hparams.model_dir = model_dir
-    return hparams
-
-
-def get_hparams_from_dir(model_dir):
-    config_save_path = os.path.join(model_dir, "config.json")
-    with open(config_save_path, "r") as f:
-        data = f.read()
-    config = json.loads(data)
-
-    hparams = HParams(**config)
-    hparams.model_dir = model_dir
-    return hparams
-
-
-def get_hparams_from_file(config_path):
-    with open(config_path, "r", encoding="utf-8") as f:
-        data = f.read()
-    config = json.loads(data)
-
-    hparams = HParams(**config)
-    return hparams
-
-
-def check_git_hash(model_dir):
-    source_dir = os.path.dirname(os.path.realpath(__file__))
-    if not os.path.exists(os.path.join(source_dir, ".git")):
-        logger.warn("{} is not a git repository, therefore hash value comparison will be ignored.".format(
-            source_dir
-        ))
-        return
-
-    cur_hash = subprocess.getoutput("git rev-parse HEAD")
-
-    path = os.path.join(model_dir, "githash")
-    if os.path.exists(path):
-        saved_hash = open(path).read()
-        if saved_hash != cur_hash:
-            logger.warn("git hash values are different. {}(saved) != {}(current)".format(
-                saved_hash[:8], cur_hash[:8]))
-    else:
-        open(path, "w").write(cur_hash)
-
-
-def get_logger(model_dir, filename="train.log"):
-    global logger
-    logger = logging.getLogger(os.path.basename(model_dir))
-    logger.setLevel(logging.DEBUG)
-
-    formatter = logging.Formatter("%(asctime)s\t%(name)s\t%(levelname)s\t%(message)s")
-    if not os.path.exists(model_dir):
-        os.makedirs(model_dir)
-    h = logging.FileHandler(os.path.join(model_dir, filename))
-    h.setLevel(logging.DEBUG)
-    h.setFormatter(formatter)
-    logger.addHandler(h)
-    return logger
-
-
-class HParams():
-    def __init__(self, **kwargs):
-        for k, v in kwargs.items():
-            if type(v) == dict:
-                v = HParams(**v)
-            self[k] = v
-
-    def keys(self):
-        return self.__dict__.keys()
-
-    def items(self):
-        return self.__dict__.items()
-
-    def values(self):
-        return self.__dict__.values()
-
-    def __len__(self):
-        return len(self.__dict__)
-
-    def __getitem__(self, key):
-        return getattr(self, key)
-
-    def __setitem__(self, key, value):
-        return setattr(self, key, value)
-
-    def __contains__(self, key):
-        return key in self.__dict__
-
-    def __repr__(self):
-        return self.__dict__.__repr__()
\ No newline at end of file
diff --git a/spaces/Xuan2060320350/ChatSydney-1/README.md b/spaces/Xuan2060320350/ChatSydney-1/README.md
deleted file mode 100644
index d84b9c55e8cc01909a3b99ed48dc156fdad91fb9..0000000000000000000000000000000000000000
--- a/spaces/Xuan2060320350/ChatSydney-1/README.md
+++ /dev/null
@@ -1,11 +0,0 @@
----
-title: ChatSydney 1
-emoji: 🦀
-colorFrom: pink
-colorTo: yellow
-sdk: docker
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/XzJosh/Taffy-Bert-VITS2/text/symbols.py b/spaces/XzJosh/Taffy-Bert-VITS2/text/symbols.py
deleted file mode 100644
index 9dfae4e633829f20c4fd767b1c7a9198911ed801..0000000000000000000000000000000000000000
--- a/spaces/XzJosh/Taffy-Bert-VITS2/text/symbols.py
+++ /dev/null
@@ -1,51 +0,0 @@
-punctuation = ['!', '?', '…', ",", ".", "'", '-']
-pu_symbols = punctuation + ["SP", "UNK"]
-pad = '_'
-
-# chinese
-zh_symbols = ['E', 'En', 'a', 'ai', 'an', 'ang', 'ao', 'b', 'c', 'ch', 'd', 'e', 'ei', 'en', 'eng', 'er', 'f', 'g', 'h',
-       'i', 'i0', 'ia', 'ian', 'iang', 'iao', 'ie', 'in', 'ing', 'iong', 'ir', 'iu', 'j', 'k', 'l', 'm', 'n', 'o',
-       'ong',
-       'ou', 'p', 'q', 'r', 's', 'sh', 't', 'u', 'ua', 'uai', 'uan', 'uang', 'ui', 'un', 'uo', 'v', 'van', 've', 'vn',
-       'w', 'x', 'y', 'z', 'zh',
-        "AA", "EE", "OO"]
-num_zh_tones = 6
-
-# japanese
-ja_symbols = ['I', 'N', 'U', 'a', 'b', 'by', 'ch', 'cl', 'd', 'dy', 'e', 'f', 'g', 'gy', 'h', 'hy', 'i', 'j', 'k', 'ky',
-              'm', 'my', 'n', 'ny', 'o', 'p', 'py', 'r', 'ry', 's', 'sh', 't', 'ts', 'u', 'V', 'w', 'y', 'z']
-num_ja_tones = 1
-
-# English
-en_symbols = ['aa', 'ae', 'ah', 'ao', 'aw', 'ay', 'b', 'ch', 'd', 'dh', 'eh', 'er', 'ey', 'f', 'g', 'hh', 'ih', 'iy',
-              'jh', 'k', 'l', 'm', 'n', 'ng', 'ow', 'oy', 'p', 'r', 's',
-              'sh', 't', 'th', 'uh', 'uw', 'V', 'w', 'y', 'z', 'zh']
-num_en_tones = 4
-
-# combine all symbols
-normal_symbols = sorted(set(zh_symbols + ja_symbols + en_symbols))
-symbols = [pad] + normal_symbols + pu_symbols
-sil_phonemes_ids = [symbols.index(i) for i in pu_symbols]
-
-# combine all tones
-num_tones = num_zh_tones + num_ja_tones + num_en_tones
-
-# language maps
-language_id_map = {
-    'ZH': 0,
-    "JA": 1,
-    "EN": 2
-}
-num_languages = len(language_id_map.keys())
-
-language_tone_start_map = {
-    'ZH': 0,
-    "JA": num_zh_tones,
-    "EN": num_zh_tones + num_ja_tones
-}
-
-if __name__ == '__main__':
-    a = set(zh_symbols)
-    b = set(en_symbols)
-    print(sorted(a&b))
-
diff --git a/spaces/XzJosh/maimai-Bert-VITS2/monotonic_align/core.py b/spaces/XzJosh/maimai-Bert-VITS2/monotonic_align/core.py
deleted file mode 100644
index dddc688d76172b880054e544b7a217acd013f14f..0000000000000000000000000000000000000000
--- a/spaces/XzJosh/maimai-Bert-VITS2/monotonic_align/core.py
+++ /dev/null
@@ -1,35 +0,0 @@
-import numba
-
-
-@numba.jit(numba.void(numba.int32[:,:,::1], numba.float32[:,:,::1], numba.int32[::1], numba.int32[::1]), nopython=True, nogil=True)
-def maximum_path_jit(paths, values, t_ys, t_xs):
-  b = paths.shape[0]
-  max_neg_val=-1e9
-  for i in range(int(b)):
-    path = paths[i]
-    value = values[i]
-    t_y = t_ys[i]
-    t_x = t_xs[i]
-
-    v_prev = v_cur = 0.0
-    index = t_x - 1
-
-    for y in range(t_y):
-      for x in range(max(0, t_x + y - t_y), min(t_x, y + 1)):
-        if x == y:
-          v_cur = max_neg_val
-        else:
-          v_cur = value[y-1, x]
-        if x == 0:
-          if y == 0:
-            v_prev = 0.
-          else:
-            v_prev = max_neg_val
-        else:
-          v_prev = value[y-1, x-1]
-        value[y, x] += max(v_prev, v_cur)
-
-    for y in range(t_y - 1, -1, -1):
-      path[y, index] = 1
-      if index != 0 and (index == y or value[y-1, index] < value[y-1, index-1]):
-        index = index - 1
diff --git a/spaces/YUANAI/DiffspeechResearch/data_gen/tts/runs/train_mfa_align.py b/spaces/YUANAI/DiffspeechResearch/data_gen/tts/runs/train_mfa_align.py
deleted file mode 100644
index daaeebe57690a8032be3d15c05d71701211604a7..0000000000000000000000000000000000000000
--- a/spaces/YUANAI/DiffspeechResearch/data_gen/tts/runs/train_mfa_align.py
+++ /dev/null
@@ -1,46 +0,0 @@
-import utils.commons.single_thread_env  # NOQA
-import glob
-import subprocess
-from textgrid import TextGrid
-import os
-from utils.commons.hparams import hparams, set_hparams
-
-
-def train_mfa_align(mfa_outputs="mfa_outputs",
-                    mfa_inputs="mfa_inputs",
-                    model_name=None, pretrain_model_name=None,
-                    mfa_cmd='train'):
-    CORPUS = hparams['processed_data_dir'].split("/")[-1]
-    NUM_JOB = int(os.getenv('N_PROC', os.cpu_count()))
-    env_vars = [f'CORPUS={CORPUS}', f'NUM_JOB={NUM_JOB}']
-    if mfa_outputs is not None:
-        env_vars.append(f'MFA_OUTPUTS={mfa_outputs}')
-    if mfa_inputs is not None:
-        env_vars.append(f'MFA_INPUTS={mfa_inputs}')
-    if model_name is not None:
-        env_vars.append(f'MODEL_NAME={model_name}')
-    if pretrain_model_name is not None:
-        env_vars.append(f'PRETRAIN_MODEL_NAME={pretrain_model_name}')
-    if mfa_cmd is not None:
-        env_vars.append(f'MFA_CMD={mfa_cmd}')
-    env_str = ' '.join(env_vars)
-    print(f"| Run MFA for {CORPUS}. Env vars: {env_str}")
-    subprocess.check_call(f'{env_str} bash mfa_usr/run_mfa_train_align.sh', shell=True)
-    mfa_offset = hparams['preprocess_args']['mfa_offset']
-    if mfa_offset > 0:
-        for tg_fn in glob.glob(f'{hparams["processed_data_dir"]}/{mfa_outputs}/*.TextGrid'):
-            tg = TextGrid.fromFile(tg_fn)
-            max_time = tg.maxTime
-            for tier in tg.tiers:
-                for interval in tier.intervals:
-                    interval.maxTime = min(interval.maxTime + mfa_offset, max_time)
-                    interval.minTime = min(interval.minTime + mfa_offset, max_time)
-                tier.intervals[0].minTime = 0
-                tier.maxTime = min(tier.maxTime + mfa_offset, max_time)
-            tg.write(tg_fn)
-            TextGrid.fromFile(tg_fn)
-
-
-if __name__ == '__main__':
-    set_hparams(print_hparams=False)
-    train_mfa_align()
diff --git a/spaces/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/utils/pil_utils.py b/spaces/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/utils/pil_utils.py
deleted file mode 100644
index 39d0a15a4e2fe39fecb01951b36c43368492f983..0000000000000000000000000000000000000000
--- a/spaces/YeOldHermit/Super-Resolution-Anime-Diffusion/diffusers/utils/pil_utils.py
+++ /dev/null
@@ -1,21 +0,0 @@
-import PIL.Image
-import PIL.ImageOps
-from packaging import version
-
-
-if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
-    PIL_INTERPOLATION = {
-        "linear": PIL.Image.Resampling.BILINEAR,
-        "bilinear": PIL.Image.Resampling.BILINEAR,
-        "bicubic": PIL.Image.Resampling.BICUBIC,
-        "lanczos": PIL.Image.Resampling.LANCZOS,
-        "nearest": PIL.Image.Resampling.NEAREST,
-    }
-else:
-    PIL_INTERPOLATION = {
-        "linear": PIL.Image.LINEAR,
-        "bilinear": PIL.Image.BILINEAR,
-        "bicubic": PIL.Image.BICUBIC,
-        "lanczos": PIL.Image.LANCZOS,
-        "nearest": PIL.Image.NEAREST,
-    }
diff --git a/spaces/YlcldKlns/bing/src/lib/hooks/use-at-bottom.tsx b/spaces/YlcldKlns/bing/src/lib/hooks/use-at-bottom.tsx
deleted file mode 100644
index d37c8cf4162adcb0064e08ecec24eb731416b045..0000000000000000000000000000000000000000
--- a/spaces/YlcldKlns/bing/src/lib/hooks/use-at-bottom.tsx
+++ /dev/null
@@ -1,23 +0,0 @@
-import * as React from 'react'
-
-export function useAtBottom(offset = 0) {
-  const [isAtBottom, setIsAtBottom] = React.useState(false)
-
-  React.useEffect(() => {
-    const handleScroll = () => {
-      setIsAtBottom(
-        window.innerHeight + window.scrollY >=
-          document.body.offsetHeight - offset
-      )
-    }
-
-    window.addEventListener('scroll', handleScroll, { passive: true })
-    handleScroll()
-
-    return () => {
-      window.removeEventListener('scroll', handleScroll)
-    }
-  }, [offset])
-
-  return isAtBottom
-}
diff --git a/spaces/Yudha515/Rvc-Models/audiocraft/modules/codebooks_patterns.py b/spaces/Yudha515/Rvc-Models/audiocraft/modules/codebooks_patterns.py
deleted file mode 100644
index c5b35cbea8cff84aa56116dbdd860fc72a913a13..0000000000000000000000000000000000000000
--- a/spaces/Yudha515/Rvc-Models/audiocraft/modules/codebooks_patterns.py
+++ /dev/null
@@ -1,539 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-from collections import namedtuple
-from dataclasses import dataclass
-from functools import lru_cache
-import logging
-import typing as tp
-
-from abc import ABC, abstractmethod
-import torch
-
-LayoutCoord = namedtuple('LayoutCoord', ['t', 'q'])  # (timestep, codebook index)
-PatternLayout = tp.List[tp.List[LayoutCoord]]  # Sequence of coordinates
-logger = logging.getLogger(__name__)
-
-
-@dataclass
-class Pattern:
-    """Base implementation of a pattern over a sequence with multiple codebooks.
-
-    The codebook pattern consists in a layout, defining for each sequence step
-    the list of coordinates of each codebook timestep in the resulting interleaved sequence.
-    The first item of the pattern is always an empty list in order to properly insert a special token
-    to start with. For convenience, we also keep track of ``n_q`` the number of codebooks used for the pattern
-    and ``timesteps`` the number of timesteps corresponding to the original sequence.
-
-    The pattern provides convenient methods to build and revert interleaved sequences from it:
-    ``build_pattern_sequence`` maps a given a dense input tensor of multi-codebook sequence from [B, K, T]
-        to the interleaved sequence of shape [B, K, S] applying the pattern, with S being the batch size,
-        K being the number of codebooks, T the number of original timesteps and S the number of sequence steps
-        for the output sequence. The unfilled positions are replaced with a special token and the built sequence
-        is returned along with a mask indicating valid tokens.
-    ``revert_pattern_sequence`` maps back an interleaved sequence of shape [B, K, S] to the original alignment
-        of codebooks across timesteps to an output tensor of shape [B, K, T], using again a special token and a mask
-        to fill and specify invalid positions if needed.
-    See the dedicated methods for more details.
-    """
-    # Pattern layout, for each sequence step, we have a list of coordinates
-    # corresponding to the original codebook timestep and position.
-    # The first list is always an empty list in order to properly insert
-    # a special token to start with.
-    layout: PatternLayout
-    timesteps: int
-    n_q: int
-
-    def __post_init__(self):
-        assert len(self.layout) > 0
-        assert self.layout[0] == []
-        self._validate_layout()
-        self._build_reverted_sequence_scatter_indexes = lru_cache(100)(self._build_reverted_sequence_scatter_indexes)
-        self._build_pattern_sequence_scatter_indexes = lru_cache(100)(self._build_pattern_sequence_scatter_indexes)
-        logger.info("New pattern, time steps: %d, sequence steps: %d", self.timesteps, len(self.layout))
-
-    def _validate_layout(self):
-        """Runs checks on the layout to ensure a valid pattern is defined.
-        A pattern is considered invalid if:
-            - Multiple timesteps for a same codebook are defined in the same sequence step
-            - The timesteps for a given codebook are not in ascending order as we advance in the sequence
-              (this would mean that we have future timesteps before past timesteps).
-        """
-        q_timesteps = {q: 0 for q in range(self.n_q)}
-        for s, seq_coords in enumerate(self.layout):
-            if len(seq_coords) > 0:
-                qs = set()
-                for coord in seq_coords:
-                    qs.add(coord.q)
-                    last_q_timestep = q_timesteps[coord.q]
-                    assert coord.t >= last_q_timestep, \
-                        f"Past timesteps are found in the sequence for codebook = {coord.q} at step {s}"
-                    q_timesteps[coord.q] = coord.t
-                # each sequence step contains at max 1 coordinate per codebook
-                assert len(qs) == len(seq_coords), \
-                    f"Multiple entries for a same codebook are found at step {s}"
-
-    @property
-    def num_sequence_steps(self):
-        return len(self.layout) - 1
-
-    @property
-    def max_delay(self):
-        max_t_in_seq_coords = 0
-        for seq_coords in self.layout[1:]:
-            for coords in seq_coords:
-                max_t_in_seq_coords = max(max_t_in_seq_coords, coords.t + 1)
-        return max_t_in_seq_coords - self.timesteps
-
-    @property
-    def valid_layout(self):
-        valid_step = len(self.layout) - self.max_delay
-        return self.layout[:valid_step]
-
-    def get_sequence_coords_with_timestep(self, t: int, q: tp.Optional[int] = None):
-        """Get codebook coordinates in the layout that corresponds to the specified timestep t
-        and optionally to the codebook q. Coordinates are returned as a tuple with the sequence step
-        and the actual codebook coordinates.
-        """
-        assert t <= self.timesteps, "provided timesteps is greater than the pattern's number of timesteps"
-        if q is not None:
-            assert q <= self.n_q, "provided number of codebooks is greater than the pattern's number of codebooks"
-        coords = []
-        for s, seq_codes in enumerate(self.layout):
-            for code in seq_codes:
-                if code.t == t and (q is None or code.q == q):
-                    coords.append((s, code))
-        return coords
-
-    def get_steps_with_timestep(self, t: int, q: tp.Optional[int] = None) -> tp.List[int]:
-        return [step for step, coords in self.get_sequence_coords_with_timestep(t, q)]
-
-    def get_first_step_with_timesteps(self, t: int, q: tp.Optional[int] = None) -> tp.Optional[int]:
-        steps_with_timesteps = self.get_steps_with_timestep(t, q)
-        return steps_with_timesteps[0] if len(steps_with_timesteps) > 0 else None
-
-    def _build_pattern_sequence_scatter_indexes(self, timesteps: int, n_q: int, keep_only_valid_steps: bool,
-                                                device: tp.Union[torch.device, str] = 'cpu'):
-        """Build scatter indexes corresponding to the pattern, up to the provided sequence_steps.
-
-        Args:
-            timesteps (int): Maximum number of timesteps steps to consider.
-            keep_only_valid_steps (bool): Restrict the pattern layout to match only valid steps.
-            device (Union[torch.device, str]): Device for created tensors.
-        Returns:
-            indexes (torch.Tensor): Indexes corresponding to the sequence, of shape [K, S].
-            mask (torch.Tensor): Mask corresponding to indexes that matches valid indexes, of shape [K, S].
-        """
-        assert n_q == self.n_q, f"invalid number of codebooks for the sequence and the pattern: {n_q} != {self.n_q}"
-        assert timesteps <= self.timesteps, "invalid number of timesteps used to build the sequence from the pattern"
-        # use the proper layout based on whether we limit ourselves to valid steps only or not,
-        # note that using the valid_layout will result in a truncated sequence up to the valid steps
-        ref_layout = self.valid_layout if keep_only_valid_steps else self.layout
-        # single item indexing being super slow with pytorch vs. numpy, so we use numpy here
-        indexes = torch.zeros(n_q, len(ref_layout), dtype=torch.long).numpy()
-        mask = torch.zeros(n_q, len(ref_layout), dtype=torch.bool).numpy()
-        # fill indexes with last sequence step value that will correspond to our special token
-        # the last value is n_q * timesteps as we have flattened z and append special token as the last token
-        # which will correspond to the index: n_q * timesteps
-        indexes[:] = n_q * timesteps
-        # iterate over the pattern and fill scattered indexes and mask
-        for s, sequence_coords in enumerate(ref_layout):
-            for coords in sequence_coords:
-                if coords.t < timesteps:
-                    indexes[coords.q, s] = coords.t + coords.q * timesteps
-                    mask[coords.q, s] = 1
-        indexes = torch.from_numpy(indexes).to(device)
-        mask = torch.from_numpy(mask).to(device)
-        return indexes, mask
-
-    def build_pattern_sequence(self, z: torch.Tensor, special_token: int, keep_only_valid_steps: bool = False):
-        """Build sequence corresponding to the pattern from the input tensor z.
-        The sequence is built using up to sequence_steps if specified, and non-pattern
-        coordinates are filled with the special token.
-
-        Args:
-            z (torch.Tensor): Input tensor of multi-codebooks sequence, of shape [B, K, T].
-            special_token (int): Special token used to fill non-pattern coordinates in the new sequence.
-            keep_only_valid_steps (bool): Build a sequence from the pattern up to valid (= fully defined) steps.
-                Steps that are beyond valid steps will be replaced by the special_token in that case.
-        Returns:
-            values (torch.Tensor): Interleaved sequence matching the pattern, of shape [B, K, S] with S
-                corresponding either to the sequence_steps if provided, otherwise to the length of the pattern.
-            indexes (torch.Tensor): Indexes corresponding to the interleaved sequence, of shape [K, S].
-            mask (torch.Tensor): Mask corresponding to indexes that matches valid indexes of shape [K, S].
-        """
-        B, K, T = z.shape
-        indexes, mask = self._build_pattern_sequence_scatter_indexes(
-            T, K, keep_only_valid_steps=keep_only_valid_steps, device=str(z.device)
-        )
-        z = z.view(B, -1)
-        # we append the special token as the last index of our flattened z tensor
-        z = torch.cat([z, torch.zeros_like(z[:, :1]) + special_token], dim=1)
-        values = z[:, indexes.view(-1)]
-        values = values.view(B, K, indexes.shape[-1])
-        return values, indexes, mask
-
-    def _build_reverted_sequence_scatter_indexes(self, sequence_steps: int, n_q: int,
-                                                 keep_only_valid_steps: bool = False,
-                                                 is_model_output: bool = False,
-                                                 device: tp.Union[torch.device, str] = 'cpu'):
-        """Builds scatter indexes required to retrieve the original multi-codebook sequence
-        from interleaving pattern.
-
-        Args:
-            sequence_steps (int): Sequence steps.
-            n_q (int): Number of codebooks.
-            keep_only_valid_steps (bool): Build a sequence from the pattern up to valid (= fully defined) steps.
-                Steps that are beyond valid steps will be replaced by the special_token in that case.
-            is_model_output (bool): Whether to keep the sequence item corresponding to initial special token or not.
-            device (Union[torch.device, str]): Device for created tensors.
-        Returns:
-            torch.Tensor: Indexes for reconstructing the output, of shape [K, T].
-            mask (torch.Tensor): Mask corresponding to indexes that matches valid indexes of shape [K, T].
-        """
-        ref_layout = self.valid_layout if keep_only_valid_steps else self.layout
-        # TODO(jade): Do we want to further truncate to only valid timesteps here as well?
-        timesteps = self.timesteps
-        assert n_q == self.n_q, f"invalid number of codebooks for the sequence and the pattern: {n_q} != {self.n_q}"
-        assert sequence_steps <= len(ref_layout), \
-            f"sequence to revert is longer than the defined pattern: {sequence_steps} > {len(ref_layout)}"
-
-        # ensure we take the appropriate indexes to keep the model output from the first special token as well
-        if is_model_output:
-            ref_layout = ref_layout[1:]
-
-        # single item indexing being super slow with pytorch vs. numpy, so we use numpy here
-        indexes = torch.zeros(n_q, timesteps, dtype=torch.long).numpy()
-        mask = torch.zeros(n_q, timesteps, dtype=torch.bool).numpy()
-        # fill indexes with last sequence step value that will correspond to our special token
-        indexes[:] = n_q * sequence_steps
-        for s, sequence_codes in enumerate(ref_layout):
-            if s < sequence_steps:
-                for code in sequence_codes:
-                    if code.t < timesteps:
-                        indexes[code.q, code.t] = s + code.q * sequence_steps
-                        mask[code.q, code.t] = 1
-        indexes = torch.from_numpy(indexes).to(device)
-        mask = torch.from_numpy(mask).to(device)
-        return indexes, mask
-
-    def revert_pattern_sequence(self, s: torch.Tensor, special_token: int, keep_only_valid_steps: bool = False):
-        """Revert a sequence built from the pattern back to the original multi-codebook sequence without interleaving.
-        The sequence is reverted using up to timesteps if specified, and non-pattern coordinates
-        are filled with the special token.
-
-        Args:
-            s (torch.Tensor): Interleaved sequence tensor obtained from the pattern, of shape [B, K, S].
-            special_token (int or float): Special token used to fill non-pattern coordinates in the new sequence.
-        Returns:
-            values (torch.Tensor): Interleaved sequence matching the pattern, of shape [B, K, T] with T
-                corresponding either to the timesteps if provided, or the total timesteps in pattern otherwise.
-            indexes (torch.Tensor): Indexes corresponding to the interleaved sequence, of shape [K, T].
-            mask (torch.Tensor): Mask corresponding to indexes that matches valid indexes of shape [K, T].
-        """
-        B, K, S = s.shape
-        indexes, mask = self._build_reverted_sequence_scatter_indexes(
-            S, K, keep_only_valid_steps, is_model_output=False, device=str(s.device)
-        )
-        s = s.view(B, -1)
-        # we append the special token as the last index of our flattened z tensor
-        s = torch.cat([s, torch.zeros_like(s[:, :1]) + special_token], dim=1)
-        values = s[:, indexes.view(-1)]
-        values = values.view(B, K, indexes.shape[-1])
-        return values, indexes, mask
-
-    def revert_pattern_logits(self, logits: torch.Tensor, special_token: float, keep_only_valid_steps: bool = False):
-        """Revert model logits obtained on a sequence built from the pattern
-        back to a tensor matching the original sequence.
-
-        This method is similar to ``revert_pattern_sequence`` with the following specificities:
-        1. It is designed to work with the extra cardinality dimension
-        2. We return the logits for the first sequence item that matches the special_token and
-        which matching target in the original sequence is the first item of the sequence,
-        while we skip the last logits as there is no matching target
-        """
-        B, card, K, S = logits.shape
-        indexes, mask = self._build_reverted_sequence_scatter_indexes(
-            S, K, keep_only_valid_steps, is_model_output=True, device=logits.device
-        )
-        logits = logits.reshape(B, card, -1)
-        # we append the special token as the last index of our flattened z tensor
-        logits = torch.cat([logits, torch.zeros_like(logits[:, :, :1]) + special_token], dim=-1)  # [B, card, K x S]
-        values = logits[:, :, indexes.view(-1)]
-        values = values.view(B, card, K, indexes.shape[-1])
-        return values, indexes, mask
-
-
-class CodebooksPatternProvider(ABC):
-    """Abstraction around providing pattern for interleaving codebooks.
-
-    The CodebooksPatternProvider abstraction allows to implement various strategies to
-    define interleaving pattern of sequences composed of multiple codebooks. For a given
-    number of codebooks `n_q`, the pattern provider can generate a specified pattern
-    corresponding to a sequence of `T` timesteps with `n_q` parallel codebooks. This pattern
-    can be used to construct a new sequence from the original codes respecting the specified
-    pattern. The pattern is defined as a list of list of code coordinates, code coordinate
-    being a tuple with the original timestep and codebook to build the new sequence.
-    Note that all patterns must start with an empty list that is then used to insert a first
-    sequence step of special tokens in the newly generated sequence.
-
-    Args:
-        n_q (int): number of codebooks.
-        cached (bool): if True, patterns for a given length are cached. In general
-            that should be true for efficiency reason to avoid synchronization points.
-    """
-    def __init__(self, n_q: int, cached: bool = True):
-        assert n_q > 0
-        self.n_q = n_q
-        self.get_pattern = lru_cache(100)(self.get_pattern)  # type: ignore
-
-    @abstractmethod
-    def get_pattern(self, timesteps: int) -> Pattern:
-        """Builds pattern with specific interleaving between codebooks.
-
-        Args:
-            timesteps (int): Total numer of timesteps.
-        """
-        raise NotImplementedError()
-
-
-class DelayedPatternProvider(CodebooksPatternProvider):
-    """Provider for delayed pattern across delayed codebooks.
-    Codebooks are delayed in the sequence and sequence steps will contain codebooks
-    from different timesteps.
-
-    Example:
-        Taking timesteps=4 and n_q=3, delays=None, the multi-codebook sequence:
-        [[1, 2, 3, 4],
-        [1, 2, 3, 4],
-        [1, 2, 3, 4]]
-        The resulting sequence obtained from the returned pattern is:
-        [[S, 1, 2, 3, 4],
-        [S, S, 1, 2, 3],
-        [S, S, S, 1, 2]]
-        (with S being a special token)
-
-    Args:
-        n_q (int): Number of codebooks.
-        delays (Optional[List[int]]): Delay for each of the codebooks.
-            If delays not defined, each codebook is delayed by 1 compared to the previous one.
-        flatten_first (int): Flatten the first N timesteps.
-        empty_initial (int): Prepend with N empty list of coordinates.
-    """
-    def __init__(self, n_q: int, delays: tp.Optional[tp.List[int]] = None,
-                 flatten_first: int = 0, empty_initial: int = 0):
-        super().__init__(n_q)
-        if delays is None:
-            delays = list(range(n_q))
-        self.delays = delays
-        self.flatten_first = flatten_first
-        self.empty_initial = empty_initial
-        assert len(self.delays) == self.n_q
-        assert sorted(self.delays) == self.delays
-
-    def get_pattern(self, timesteps: int) -> Pattern:
-        out: PatternLayout = [[]]
-        max_delay = max(self.delays)
-        if self.empty_initial:
-            out += [[] for _ in range(self.empty_initial)]
-        if self.flatten_first:
-            for t in range(min(timesteps, self.flatten_first)):
-                for q in range(self.n_q):
-                    out.append([LayoutCoord(t, q)])
-        for t in range(self.flatten_first, timesteps + max_delay):
-            v = []
-            for q, delay in enumerate(self.delays):
-                t_for_q = t - delay
-                if t_for_q >= self.flatten_first:
-                    v.append(LayoutCoord(t_for_q, q))
-            out.append(v)
-        return Pattern(out, n_q=self.n_q, timesteps=timesteps)
-
-
-class ParallelPatternProvider(DelayedPatternProvider):
-    """Provider for parallel pattern across codebooks.
-    This pattern provider is a special case of the delayed pattern with actually no delay,
-    hence delays=repeat(0, n_q).
-
-    Args:
-        n_q (int): Number of codebooks.
-    """
-    def __init__(self, n_q: int):
-        super().__init__(n_q, [0] * n_q)
-
-
-class UnrolledPatternProvider(CodebooksPatternProvider):
-    """Provider for unrolling codebooks pattern.
-    This pattern provider enables to represent the codebook flattened completely or only to some extend
-    while also specifying a given delay between the flattened codebooks representation, allowing to
-    unroll the codebooks in the sequence.
-
-    Example:
-        1. Flattening of the codebooks.
-        By default, the pattern provider will fully flatten the codebooks such as flattening=range(n_q),
-        taking n_q = 3 and timesteps = 4:
-        [[1, 2, 3, 4],
-         [1, 2, 3, 4],
-         [1, 2, 3, 4]]
-        will result into:
-        [[S, S, 1, S, S, 2, S, S, 3, S, S, 4],
-         [S, 1, S, S, 2, S, S, 3, S, S, 4, S],
-         [1, S, S, 2, S, S, 3, S, S, 4, S, S]]
-        2. Partial flattening of the codebooks. The ``flattening`` parameter allows to specify the inner step
-        for each of the codebook, allowing to define which codebook to flatten (or keep in parallel), for example
-        taking n_q = 3, timesteps = 4 and flattening = [0, 1, 1]:
-        [[1, 2, 3, 4],
-         [1, 2, 3, 4],
-         [1, 2, 3, 4]]
-        will result into:
-        [[S, 1, S, S, 2, S, S, 3, S, S, 4, S],
-         [S, 1, S, S, 2, S, S, 3, S, S, 4, S],
-         [1, S, S, 2, S, S, 3, S, S, 4, S, S]]
-        3. Flattening with delay. The ``delay`` parameter allows to further unroll the sequence of codebooks
-        allowing to specify the delay per codebook. Note that the delay between codebooks flattened to the
-        same inner timestep should be coherent. For example, taking n_q = 3, timesteps = 4, flattening = [0, 1, 1]
-        and delays = [0, 3, 3]:
-        [[1, 2, 3, 4],
-         [1, 2, 3, 4],
-         [1, 2, 3, 4]]
-        will result into:
-        [[S, S, S, 1, S, 2, S, 3, S, 4],
-         [S, S, S, 1, S, 2, S, 3, S, 4],
-         [1, 2, 3, S, 4, S, 5, S, 6, S]]
-
-    Args:
-        n_q (int): Number of codebooks.
-        flattening (Optional[List[int]]): Flattening schema over the codebooks. If not defined,
-            the codebooks will be flattened to 1 codebook per step, meaning that the sequence will
-            have n_q extra steps for each timestep.
-        delays (Optional[List[int]]): Delay for each of the codebooks. If not defined,
-            no delay is added and therefore will default to [0] * ``n_q``.
-            Note that two codebooks that will be flattened to the same inner step
-            should have the same delay, otherwise the pattern is considered as invalid.
-    """
-    FlattenedCodebook = namedtuple('FlattenedCodebook', ['codebooks', 'delay'])
-
-    def __init__(self, n_q: int, flattening: tp.Optional[tp.List[int]] = None,
-                 delays: tp.Optional[tp.List[int]] = None):
-        super().__init__(n_q)
-        if flattening is None:
-            flattening = list(range(n_q))
-        if delays is None:
-            delays = [0] * n_q
-        assert len(flattening) == n_q
-        assert len(delays) == n_q
-        assert sorted(flattening) == flattening
-        assert sorted(delays) == delays
-        self._flattened_codebooks = self._build_flattened_codebooks(delays, flattening)
-        self.max_delay = max(delays)
-
-    def _build_flattened_codebooks(self, delays: tp.List[int], flattening: tp.List[int]):
-        """Build a flattened codebooks representation as a dictionary of inner step
-        and the actual codebook indices corresponding to the flattened codebook. For convenience, we
-        also store the delay associated to the flattened codebook to avoid maintaining an extra mapping.
-        """
-        flattened_codebooks: dict = {}
-        for q, (inner_step, delay) in enumerate(zip(flattening, delays)):
-            if inner_step not in flattened_codebooks:
-                flat_codebook = UnrolledPatternProvider.FlattenedCodebook(codebooks=[q], delay=delay)
-            else:
-                flat_codebook = flattened_codebooks[inner_step]
-                assert flat_codebook.delay == delay, (
-                    "Delay and flattening between codebooks is inconsistent: ",
-                    "two codebooks flattened to the same position should have the same delay."
-                )
-                flat_codebook.codebooks.append(q)
-            flattened_codebooks[inner_step] = flat_codebook
-        return flattened_codebooks
-
-    @property
-    def _num_inner_steps(self):
-        """Number of inner steps to unroll between timesteps in order to flatten the codebooks.
-        """
-        return max([inner_step for inner_step in self._flattened_codebooks.keys()]) + 1
-
-    def num_virtual_steps(self, timesteps: int) -> int:
-        return timesteps * self._num_inner_steps + 1
-
-    def get_pattern(self, timesteps: int) -> Pattern:
-        """Builds pattern for delay across codebooks.
-
-        Args:
-            timesteps (int): Total numer of timesteps.
-        """
-        # the PatternLayout is built as a tuple of sequence position and list of coordinates
-        # so that it can be reordered properly given the required delay between codebooks of given timesteps
-        indexed_out: list = [(-1, [])]
-        max_timesteps = timesteps + self.max_delay
-        for t in range(max_timesteps):
-            # for each timestep, we unroll the flattened codebooks,
-            # emitting the sequence step with the corresponding delay
-            for step in range(self._num_inner_steps):
-                if step in self._flattened_codebooks:
-                    # we have codebooks at this virtual step to emit
-                    step_codebooks = self._flattened_codebooks[step]
-                    t_for_q = t + step_codebooks.delay
-                    coords = [LayoutCoord(t, q) for q in step_codebooks.codebooks]
-                    if t_for_q < max_timesteps and t < max_timesteps:
-                        indexed_out.append((t_for_q, coords))
-                else:
-                    # there is no codebook in this virtual step so we emit an empty list
-                    indexed_out.append((t, []))
-        out = [coords for _, coords in sorted(indexed_out)]
-        return Pattern(out, n_q=self.n_q, timesteps=timesteps)
-
-
-class VALLEPattern(CodebooksPatternProvider):
-    """Almost VALL-E style pattern. We futher allow some delays for the
-    codebooks other than the first one.
-
-    Args:
-        n_q (int): Number of codebooks.
-        delays (Optional[List[int]]): Delay for each of the codebooks.
-            If delays not defined, each codebook is delayed by 1 compared to the previous one.
-    """
-    def __init__(self, n_q: int, delays: tp.Optional[tp.List[int]] = None):
-        super().__init__(n_q)
-        if delays is None:
-            delays = [0] * (n_q - 1)
-        self.delays = delays
-        assert len(self.delays) == self.n_q - 1
-        assert sorted(self.delays) == self.delays
-
-    def get_pattern(self, timesteps: int) -> Pattern:
-        out: PatternLayout = [[]]
-        for t in range(timesteps):
-            out.append([LayoutCoord(t, 0)])
-        max_delay = max(self.delays)
-        for t in range(timesteps + max_delay):
-            v = []
-            for q, delay in enumerate(self.delays):
-                t_for_q = t - delay
-                if t_for_q >= 0:
-                    v.append(LayoutCoord(t_for_q, q + 1))
-            out.append(v)
-        return Pattern(out, n_q=self.n_q, timesteps=timesteps)
-
-
-class MusicLMPattern(CodebooksPatternProvider):
-    """Almost MusicLM style pattern. This is equivalent to full flattening
-    but in a different order.
-
-    Args:
-        n_q (int): Number of codebooks.
-        group_by (int): Number of codebooks to group together.
-    """
-    def __init__(self, n_q: int, group_by: int = 2):
-        super().__init__(n_q)
-        self.group_by = group_by
-
-    def get_pattern(self, timesteps: int) -> Pattern:
-        out: PatternLayout = [[]]
-        for offset in range(0, self.n_q, self.group_by):
-            for t in range(timesteps):
-                for q in range(offset, offset + self.group_by):
-                    out.append([LayoutCoord(t, q)])
-        return Pattern(out, n_q=self.n_q, timesteps=timesteps)
diff --git a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet_null/models/roi_heads/roi_extractors/single_level_roi_extractor.py b/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet_null/models/roi_heads/roi_extractors/single_level_roi_extractor.py
deleted file mode 100644
index cfc838f23270a1ae4d70f90059b67a890850e981..0000000000000000000000000000000000000000
--- a/spaces/abhishek/sketch-to-image/annotator/uniformer/mmdet_null/models/roi_heads/roi_extractors/single_level_roi_extractor.py
+++ /dev/null
@@ -1,108 +0,0 @@
-import torch
-from mmcv.runner import force_fp32
-
-from mmdet.models.builder import ROI_EXTRACTORS
-from .base_roi_extractor import BaseRoIExtractor
-
-
-@ROI_EXTRACTORS.register_module()
-class SingleRoIExtractor(BaseRoIExtractor):
-    """Extract RoI features from a single level feature map.
-
-    If there are multiple input feature levels, each RoI is mapped to a level
-    according to its scale. The mapping rule is proposed in
-    `FPN <https://arxiv.org/abs/1612.03144>`_.
-
-    Args:
-        roi_layer (dict): Specify RoI layer type and arguments.
-        out_channels (int): Output channels of RoI layers.
-        featmap_strides (List[int]): Strides of input feature maps.
-        finest_scale (int): Scale threshold of mapping to level 0. Default: 56.
-    """
-
-    def __init__(self,
-                 roi_layer,
-                 out_channels,
-                 featmap_strides,
-                 finest_scale=56):
-        super(SingleRoIExtractor, self).__init__(roi_layer, out_channels,
-                                                 featmap_strides)
-        self.finest_scale = finest_scale
-
-    def map_roi_levels(self, rois, num_levels):
-        """Map rois to corresponding feature levels by scales.
-
-        - scale < finest_scale * 2: level 0
-        - finest_scale * 2 <= scale < finest_scale * 4: level 1
-        - finest_scale * 4 <= scale < finest_scale * 8: level 2
-        - scale >= finest_scale * 8: level 3
-
-        Args:
-            rois (Tensor): Input RoIs, shape (k, 5).
-            num_levels (int): Total level number.
-
-        Returns:
-            Tensor: Level index (0-based) of each RoI, shape (k, )
-        """
-        scale = torch.sqrt(
-            (rois[:, 3] - rois[:, 1]) * (rois[:, 4] - rois[:, 2]))
-        target_lvls = torch.floor(torch.log2(scale / self.finest_scale + 1e-6))
-        target_lvls = target_lvls.clamp(min=0, max=num_levels - 1).long()
-        return target_lvls
-
-    @force_fp32(apply_to=('feats', ), out_fp16=True)
-    def forward(self, feats, rois, roi_scale_factor=None):
-        """Forward function."""
-        out_size = self.roi_layers[0].output_size
-        num_levels = len(feats)
-        expand_dims = (-1, self.out_channels * out_size[0] * out_size[1])
-        if torch.onnx.is_in_onnx_export():
-            # Work around to export mask-rcnn to onnx
-            roi_feats = rois[:, :1].clone().detach()
-            roi_feats = roi_feats.expand(*expand_dims)
-            roi_feats = roi_feats.reshape(-1, self.out_channels, *out_size)
-            roi_feats = roi_feats * 0
-        else:
-            roi_feats = feats[0].new_zeros(
-                rois.size(0), self.out_channels, *out_size)
-        # TODO: remove this when parrots supports
-        if torch.__version__ == 'parrots':
-            roi_feats.requires_grad = True
-
-        if num_levels == 1:
-            if len(rois) == 0:
-                return roi_feats
-            return self.roi_layers[0](feats[0], rois)
-
-        target_lvls = self.map_roi_levels(rois, num_levels)
-
-        if roi_scale_factor is not None:
-            rois = self.roi_rescale(rois, roi_scale_factor)
-
-        for i in range(num_levels):
-            mask = target_lvls == i
-            if torch.onnx.is_in_onnx_export():
-                # To keep all roi_align nodes exported to onnx
-                # and skip nonzero op
-                mask = mask.float().unsqueeze(-1).expand(*expand_dims).reshape(
-                    roi_feats.shape)
-                roi_feats_t = self.roi_layers[i](feats[i], rois)
-                roi_feats_t *= mask
-                roi_feats += roi_feats_t
-                continue
-            inds = mask.nonzero(as_tuple=False).squeeze(1)
-            if inds.numel() > 0:
-                rois_ = rois[inds]
-                roi_feats_t = self.roi_layers[i](feats[i], rois_)
-                roi_feats[inds] = roi_feats_t
-            else:
-                # Sometimes some pyramid levels will not be used for RoI
-                # feature extraction and this will cause an incomplete
-                # computation graph in one GPU, which is different from those
-                # in other GPUs and will cause a hanging error.
-                # Therefore, we add it to ensure each feature pyramid is
-                # included in the computation graph to avoid runtime bugs.
-                roi_feats += sum(
-                    x.view(-1)[0]
-                    for x in self.parameters()) * 0. + feats[i].sum() * 0.
-        return roi_feats
diff --git a/spaces/aiEDUcurriculum/introtoAI-pets-project/README.md b/spaces/aiEDUcurriculum/introtoAI-pets-project/README.md
deleted file mode 100644
index 855c880ad6755eb4adb215bb71c7fe2d5f778f2b..0000000000000000000000000000000000000000
--- a/spaces/aiEDUcurriculum/introtoAI-pets-project/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: IntrotoAI Pets Project
-emoji: 🐉
-colorFrom: green
-colorTo: green
-sdk: gradio
-sdk_version: 3.1.1
-app_file: app.py
-pinned: false
-license: afl-3.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/aijack/jojo/e4e/utils/data_utils.py b/spaces/aijack/jojo/e4e/utils/data_utils.py
deleted file mode 100644
index f1ba79f4a2d5cc2b97dce76d87bf6e7cdebbc257..0000000000000000000000000000000000000000
--- a/spaces/aijack/jojo/e4e/utils/data_utils.py
+++ /dev/null
@@ -1,25 +0,0 @@
-"""
-Code adopted from pix2pixHD:
-https://github.com/NVIDIA/pix2pixHD/blob/master/data/image_folder.py
-"""
-import os
-
-IMG_EXTENSIONS = [
-    '.jpg', '.JPG', '.jpeg', '.JPEG',
-    '.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP', '.tiff'
-]
-
-
-def is_image_file(filename):
-    return any(filename.endswith(extension) for extension in IMG_EXTENSIONS)
-
-
-def make_dataset(dir):
-    images = []
-    assert os.path.isdir(dir), '%s is not a valid directory' % dir
-    for root, _, fnames in sorted(os.walk(dir)):
-        for fname in fnames:
-            if is_image_file(fname):
-                path = os.path.join(root, fname)
-                images.append(path)
-    return images
diff --git a/spaces/akhaliq/Detic/README.md b/spaces/akhaliq/Detic/README.md
deleted file mode 100644
index 1d486dc085afee1a169380bcded0fd024317b660..0000000000000000000000000000000000000000
--- a/spaces/akhaliq/Detic/README.md
+++ /dev/null
@@ -1,37 +0,0 @@
----
-title: Detic
-emoji: 👀
-colorFrom: indigo
-colorTo: red
-sdk: gradio
-app_file: app.py
-pinned: false
----
-
-# Configuration
-
-`title`: _string_
-Display title for the Space
-
-`emoji`: _string_
-Space emoji (emoji-only character allowed)
-
-`colorFrom`: _string_
-Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
-
-`colorTo`: _string_
-Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
-
-`sdk`: _string_
-Can be either `gradio`, `streamlit`, or `static`
-
-`sdk_version` : _string_
-Only applicable for `streamlit` SDK.  
-See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
-
-`app_file`: _string_
-Path to your main application file (which contains either `gradio` or `streamlit` Python code, or `static` html code).
-Path is relative to the root of the repository.
-
-`pinned`: _boolean_
-Whether the Space stays on top of your list.
diff --git a/spaces/akhaliq/GPEN/face_detect/facemodels/net.py b/spaces/akhaliq/GPEN/face_detect/facemodels/net.py
deleted file mode 100644
index beb6040b24258f8b96020c1c9fc2610819718017..0000000000000000000000000000000000000000
--- a/spaces/akhaliq/GPEN/face_detect/facemodels/net.py
+++ /dev/null
@@ -1,137 +0,0 @@
-import time
-import torch
-import torch.nn as nn
-import torchvision.models._utils as _utils
-import torchvision.models as models
-import torch.nn.functional as F
-from torch.autograd import Variable
-
-def conv_bn(inp, oup, stride = 1, leaky = 0):
-    return nn.Sequential(
-        nn.Conv2d(inp, oup, 3, stride, 1, bias=False),
-        nn.BatchNorm2d(oup),
-        nn.LeakyReLU(negative_slope=leaky, inplace=True)
-    )
-
-def conv_bn_no_relu(inp, oup, stride):
-    return nn.Sequential(
-        nn.Conv2d(inp, oup, 3, stride, 1, bias=False),
-        nn.BatchNorm2d(oup),
-    )
-
-def conv_bn1X1(inp, oup, stride, leaky=0):
-    return nn.Sequential(
-        nn.Conv2d(inp, oup, 1, stride, padding=0, bias=False),
-        nn.BatchNorm2d(oup),
-        nn.LeakyReLU(negative_slope=leaky, inplace=True)
-    )
-
-def conv_dw(inp, oup, stride, leaky=0.1):
-    return nn.Sequential(
-        nn.Conv2d(inp, inp, 3, stride, 1, groups=inp, bias=False),
-        nn.BatchNorm2d(inp),
-        nn.LeakyReLU(negative_slope= leaky,inplace=True),
-
-        nn.Conv2d(inp, oup, 1, 1, 0, bias=False),
-        nn.BatchNorm2d(oup),
-        nn.LeakyReLU(negative_slope= leaky,inplace=True),
-    )
-
-class SSH(nn.Module):
-    def __init__(self, in_channel, out_channel):
-        super(SSH, self).__init__()
-        assert out_channel % 4 == 0
-        leaky = 0
-        if (out_channel <= 64):
-            leaky = 0.1
-        self.conv3X3 = conv_bn_no_relu(in_channel, out_channel//2, stride=1)
-
-        self.conv5X5_1 = conv_bn(in_channel, out_channel//4, stride=1, leaky = leaky)
-        self.conv5X5_2 = conv_bn_no_relu(out_channel//4, out_channel//4, stride=1)
-
-        self.conv7X7_2 = conv_bn(out_channel//4, out_channel//4, stride=1, leaky = leaky)
-        self.conv7x7_3 = conv_bn_no_relu(out_channel//4, out_channel//4, stride=1)
-
-    def forward(self, input):
-        conv3X3 = self.conv3X3(input)
-
-        conv5X5_1 = self.conv5X5_1(input)
-        conv5X5 = self.conv5X5_2(conv5X5_1)
-
-        conv7X7_2 = self.conv7X7_2(conv5X5_1)
-        conv7X7 = self.conv7x7_3(conv7X7_2)
-
-        out = torch.cat([conv3X3, conv5X5, conv7X7], dim=1)
-        out = F.relu(out)
-        return out
-
-class FPN(nn.Module):
-    def __init__(self,in_channels_list,out_channels):
-        super(FPN,self).__init__()
-        leaky = 0
-        if (out_channels <= 64):
-            leaky = 0.1
-        self.output1 = conv_bn1X1(in_channels_list[0], out_channels, stride = 1, leaky = leaky)
-        self.output2 = conv_bn1X1(in_channels_list[1], out_channels, stride = 1, leaky = leaky)
-        self.output3 = conv_bn1X1(in_channels_list[2], out_channels, stride = 1, leaky = leaky)
-
-        self.merge1 = conv_bn(out_channels, out_channels, leaky = leaky)
-        self.merge2 = conv_bn(out_channels, out_channels, leaky = leaky)
-
-    def forward(self, input):
-        # names = list(input.keys())
-        input = list(input.values())
-
-        output1 = self.output1(input[0])
-        output2 = self.output2(input[1])
-        output3 = self.output3(input[2])
-
-        up3 = F.interpolate(output3, size=[output2.size(2), output2.size(3)], mode="nearest")
-        output2 = output2 + up3
-        output2 = self.merge2(output2)
-
-        up2 = F.interpolate(output2, size=[output1.size(2), output1.size(3)], mode="nearest")
-        output1 = output1 + up2
-        output1 = self.merge1(output1)
-
-        out = [output1, output2, output3]
-        return out
-
-
-
-class MobileNetV1(nn.Module):
-    def __init__(self):
-        super(MobileNetV1, self).__init__()
-        self.stage1 = nn.Sequential(
-            conv_bn(3, 8, 2, leaky = 0.1),    # 3
-            conv_dw(8, 16, 1),   # 7
-            conv_dw(16, 32, 2),  # 11
-            conv_dw(32, 32, 1),  # 19
-            conv_dw(32, 64, 2),  # 27
-            conv_dw(64, 64, 1),  # 43
-        )
-        self.stage2 = nn.Sequential(
-            conv_dw(64, 128, 2),  # 43 + 16 = 59
-            conv_dw(128, 128, 1), # 59 + 32 = 91
-            conv_dw(128, 128, 1), # 91 + 32 = 123
-            conv_dw(128, 128, 1), # 123 + 32 = 155
-            conv_dw(128, 128, 1), # 155 + 32 = 187
-            conv_dw(128, 128, 1), # 187 + 32 = 219
-        )
-        self.stage3 = nn.Sequential(
-            conv_dw(128, 256, 2), # 219 +3 2 = 241
-            conv_dw(256, 256, 1), # 241 + 64 = 301
-        )
-        self.avg = nn.AdaptiveAvgPool2d((1,1))
-        self.fc = nn.Linear(256, 1000)
-
-    def forward(self, x):
-        x = self.stage1(x)
-        x = self.stage2(x)
-        x = self.stage3(x)
-        x = self.avg(x)
-        # x = self.model(x)
-        x = x.view(-1, 256)
-        x = self.fc(x)
-        return x
-
diff --git a/spaces/akhaliq/Music_Source_Separation/bytesep/utils.py b/spaces/akhaliq/Music_Source_Separation/bytesep/utils.py
deleted file mode 100644
index 4a38928bd5b00521d32b67c484e5561ff2ead439..0000000000000000000000000000000000000000
--- a/spaces/akhaliq/Music_Source_Separation/bytesep/utils.py
+++ /dev/null
@@ -1,189 +0,0 @@
-import datetime
-import logging
-import os
-import pickle
-from typing import Dict, NoReturn
-
-import librosa
-import numpy as np
-import yaml
-
-
-def create_logging(log_dir: str, filemode: str) -> logging:
-    r"""Create logging to write out log files.
-
-    Args:
-        logs_dir, str, directory to write out logs
-        filemode: str, e.g., "w"
-
-    Returns:
-        logging
-    """
-    os.makedirs(log_dir, exist_ok=True)
-    i1 = 0
-
-    while os.path.isfile(os.path.join(log_dir, "{:04d}.log".format(i1))):
-        i1 += 1
-
-    log_path = os.path.join(log_dir, "{:04d}.log".format(i1))
-    logging.basicConfig(
-        level=logging.DEBUG,
-        format="%(asctime)s %(filename)s[line:%(lineno)d] %(levelname)s %(message)s",
-        datefmt="%a, %d %b %Y %H:%M:%S",
-        filename=log_path,
-        filemode=filemode,
-    )
-
-    # Print to console
-    console = logging.StreamHandler()
-    console.setLevel(logging.INFO)
-    formatter = logging.Formatter("%(name)-12s: %(levelname)-8s %(message)s")
-    console.setFormatter(formatter)
-    logging.getLogger("").addHandler(console)
-
-    return logging
-
-
-def load_audio(
-    audio_path: str,
-    mono: bool,
-    sample_rate: float,
-    offset: float = 0.0,
-    duration: float = None,
-) -> np.array:
-    r"""Load audio.
-
-    Args:
-        audio_path: str
-        mono: bool
-        sample_rate: float
-    """
-    audio, _ = librosa.core.load(
-        audio_path, sr=sample_rate, mono=mono, offset=offset, duration=duration
-    )
-    # (audio_samples,) | (channels_num, audio_samples)
-
-    if audio.ndim == 1:
-        audio = audio[None, :]
-        # (1, audio_samples,)
-
-    return audio
-
-
-def load_random_segment(
-    audio_path: str, random_state, segment_seconds: float, mono: bool, sample_rate: int
-) -> np.array:
-    r"""Randomly select an audio segment from a recording."""
-
-    duration = librosa.get_duration(filename=audio_path)
-
-    start_time = random_state.uniform(0.0, duration - segment_seconds)
-
-    audio = load_audio(
-        audio_path=audio_path,
-        mono=mono,
-        sample_rate=sample_rate,
-        offset=start_time,
-        duration=segment_seconds,
-    )
-    # (channels_num, audio_samples)
-
-    return audio
-
-
-def float32_to_int16(x: np.float32) -> np.int16:
-
-    x = np.clip(x, a_min=-1, a_max=1)
-
-    return (x * 32767.0).astype(np.int16)
-
-
-def int16_to_float32(x: np.int16) -> np.float32:
-
-    return (x / 32767.0).astype(np.float32)
-
-
-def read_yaml(config_yaml: str):
-
-    with open(config_yaml, "r") as fr:
-        configs = yaml.load(fr, Loader=yaml.FullLoader)
-
-    return configs
-
-
-def check_configs_gramma(configs: Dict) -> NoReturn:
-    r"""Check if the gramma of the config dictionary for training is legal."""
-    input_source_types = configs['train']['input_source_types']
-
-    for augmentation_type in configs['train']['augmentations'].keys():
-        augmentation_dict = configs['train']['augmentations'][augmentation_type]
-
-        for source_type in augmentation_dict.keys():
-            if source_type not in input_source_types:
-                error_msg = (
-                    "The source type '{}'' in configs['train']['augmentations']['{}'] "
-                    "must be one of input_source_types {}".format(
-                        source_type, augmentation_type, input_source_types
-                    )
-                )
-                raise Exception(error_msg)
-
-
-def magnitude_to_db(x: float) -> float:
-    eps = 1e-10
-    return 20.0 * np.log10(max(x, eps))
-
-
-def db_to_magnitude(x: float) -> float:
-    return 10.0 ** (x / 20)
-
-
-def get_pitch_shift_factor(shift_pitch: float) -> float:
-    r"""The factor of the audio length to be scaled."""
-    return 2 ** (shift_pitch / 12)
-
-
-class StatisticsContainer(object):
-    def __init__(self, statistics_path):
-        self.statistics_path = statistics_path
-
-        self.backup_statistics_path = "{}_{}.pkl".format(
-            os.path.splitext(self.statistics_path)[0],
-            datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S"),
-        )
-
-        self.statistics_dict = {"train": [], "test": []}
-
-    def append(self, steps, statistics, split):
-        statistics["steps"] = steps
-        self.statistics_dict[split].append(statistics)
-
-    def dump(self):
-        pickle.dump(self.statistics_dict, open(self.statistics_path, "wb"))
-        pickle.dump(self.statistics_dict, open(self.backup_statistics_path, "wb"))
-        logging.info("    Dump statistics to {}".format(self.statistics_path))
-        logging.info("    Dump statistics to {}".format(self.backup_statistics_path))
-
-    '''
-    def load_state_dict(self, resume_steps):
-        self.statistics_dict = pickle.load(open(self.statistics_path, "rb"))
-
-        resume_statistics_dict = {"train": [], "test": []}
-
-        for key in self.statistics_dict.keys():
-            for statistics in self.statistics_dict[key]:
-                if statistics["steps"] <= resume_steps:
-                    resume_statistics_dict[key].append(statistics)
-
-        self.statistics_dict = resume_statistics_dict
-    '''
-
-
-def calculate_sdr(ref: np.array, est: np.array) -> float:
-    s_true = ref
-    s_artif = est - ref
-    sdr = 10.0 * (
-        np.log10(np.clip(np.mean(s_true ** 2), 1e-8, np.inf))
-        - np.log10(np.clip(np.mean(s_artif ** 2), 1e-8, np.inf))
-    )
-    return sdr
diff --git a/spaces/akhaliq/VQMIVC/model_encoder.py b/spaces/akhaliq/VQMIVC/model_encoder.py
deleted file mode 100644
index 7f22368329be0f93915b985ddcbcc6b3ae506618..0000000000000000000000000000000000000000
--- a/spaces/akhaliq/VQMIVC/model_encoder.py
+++ /dev/null
@@ -1,449 +0,0 @@
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-import math
-
-
-class ConvNorm(torch.nn.Module):
-    def __init__(self, in_channels, out_channels, kernel_size=1, stride=1,
-                 padding=None, dilation=1, bias=True, w_init_gain='linear'):
-        super(ConvNorm, self).__init__()
-        if padding is None:
-            assert(kernel_size % 2 == 1)
-            padding = int(dilation * (kernel_size - 1) / 2)
-
-        self.conv = torch.nn.Conv1d(in_channels, out_channels,
-                                    kernel_size=kernel_size, stride=stride,
-                                    padding=padding, dilation=dilation,
-                                    bias=bias)
-
-        torch.nn.init.xavier_uniform_(
-            self.conv.weight, gain=torch.nn.init.calculate_gain(w_init_gain))
-
-    def forward(self, signal):
-        conv_signal = self.conv(signal)
-        return conv_signal
-
-
-class Encoder_lf0(nn.Module):
-    def __init__(self, typ='no_emb'):
-        super(Encoder_lf0, self).__init__()
-        self.type = typ
-        if typ != 'no_emb':
-            convolutions = []
-            for i in range(3):
-                conv_layer = nn.Sequential(
-                    ConvNorm(1 if i==0 else 256, 256,
-                             kernel_size=5, stride=2 if i==2 else 1,
-                             padding=2,
-                             dilation=1, w_init_gain='relu'),
-                    nn.GroupNorm(256//16, 256),
-                    nn.ReLU())
-                convolutions.append(conv_layer)
-            self.convolutions = nn.ModuleList(convolutions)
-            self.lstm = nn.LSTM(256, 32, 1, batch_first=True, bidirectional=True)
-
-    def forward(self, lf0):
-        if self.type != 'no_emb':
-            if len(lf0.shape) == 2:
-                lf0 = lf0.unsqueeze(1) # bz x 1 x 128
-            for conv in self.convolutions:
-                lf0 = conv(lf0) # bz x 256 x 128
-            lf0 = lf0.transpose(1,2) # bz x 64 x 256
-            self.lstm.flatten_parameters()
-            lf0, _ = self.lstm(lf0) # bz x 64 x 64
-        else:
-            if len(lf0.shape) == 2:
-                lf0 = lf0.unsqueeze(-1) # bz x 128 x 1 # no downsampling
-        return lf0
-
-
-
-def pad_layer(inp, layer, pad_type='reflect'):
-    kernel_size = layer.kernel_size[0]
-    if kernel_size % 2 == 0:
-        pad = (kernel_size//2, kernel_size//2 - 1)
-    else:
-        pad = (kernel_size//2, kernel_size//2)
-    # padding
-    inp = F.pad(inp, 
-            pad=pad,
-            mode=pad_type)
-    out = layer(inp)
-    return out
-
-def conv_bank(x, module_list, act, pad_type='reflect'):
-    outs = []
-    for layer in module_list:
-        out = act(pad_layer(x, layer, pad_type))
-        outs.append(out)
-    out = torch.cat(outs + [x], dim=1)
-    return out
-
-def get_act(act):
-    if act == 'relu':
-        return nn.ReLU()
-    elif act == 'lrelu':
-        return nn.LeakyReLU()
-    else:
-        return nn.ReLU()
-
-
-class SpeakerEncoder(nn.Module):
-    '''
-    reference from speaker-encoder of AdaIN-VC: https://github.com/jjery2243542/adaptive_voice_conversion/blob/master/model.py
-    '''
-    def __init__(self, c_in=80, c_h=128, c_out=256, kernel_size=5,
-            bank_size=8, bank_scale=1, c_bank=128, 
-            n_conv_blocks=6, n_dense_blocks=6, 
-            subsample=[1, 2, 1, 2, 1, 2], act='relu', dropout_rate=0):
-        super(SpeakerEncoder, self).__init__()
-        self.c_in = c_in
-        self.c_h = c_h
-        self.c_out = c_out
-        self.kernel_size = kernel_size
-        self.n_conv_blocks = n_conv_blocks
-        self.n_dense_blocks = n_dense_blocks
-        self.subsample = subsample
-        self.act = get_act(act)
-        self.conv_bank = nn.ModuleList(
-                [nn.Conv1d(c_in, c_bank, kernel_size=k) for k in range(bank_scale, bank_size + 1, bank_scale)])
-        in_channels = c_bank * (bank_size // bank_scale) + c_in
-        self.in_conv_layer = nn.Conv1d(in_channels, c_h, kernel_size=1)
-        self.first_conv_layers = nn.ModuleList([nn.Conv1d(c_h, c_h, kernel_size=kernel_size) for _ \
-                in range(n_conv_blocks)])
-        self.second_conv_layers = nn.ModuleList([nn.Conv1d(c_h, c_h, kernel_size=kernel_size, stride=sub) 
-            for sub, _ in zip(subsample, range(n_conv_blocks))])
-        self.pooling_layer = nn.AdaptiveAvgPool1d(1)
-        self.first_dense_layers = nn.ModuleList([nn.Linear(c_h, c_h) for _ in range(n_dense_blocks)])
-        self.second_dense_layers = nn.ModuleList([nn.Linear(c_h, c_h) for _ in range(n_dense_blocks)])
-        self.output_layer = nn.Linear(c_h, c_out)
-        self.dropout_layer = nn.Dropout(p=dropout_rate)
-
-    def conv_blocks(self, inp):
-        out = inp
-        # convolution blocks
-        for l in range(self.n_conv_blocks):
-            y = pad_layer(out, self.first_conv_layers[l])
-            y = self.act(y)
-            y = self.dropout_layer(y)
-            y = pad_layer(y, self.second_conv_layers[l])
-            y = self.act(y)
-            y = self.dropout_layer(y)
-            if self.subsample[l] > 1:
-                out = F.avg_pool1d(out, kernel_size=self.subsample[l], ceil_mode=True)
-            out = y + out
-        return out
-
-    def dense_blocks(self, inp):
-        out = inp
-        # dense layers
-        for l in range(self.n_dense_blocks):
-            y = self.first_dense_layers[l](out)
-            y = self.act(y)
-            y = self.dropout_layer(y)
-            y = self.second_dense_layers[l](y)
-            y = self.act(y)
-            y = self.dropout_layer(y)
-            out = y + out
-        return out
-
-    def forward(self, x):
-        out = conv_bank(x, self.conv_bank, act=self.act)
-        # dimension reduction layer
-        out = pad_layer(out, self.in_conv_layer)
-        out = self.act(out)
-        # conv blocks
-        out = self.conv_blocks(out)
-        # avg pooling
-        out = self.pooling_layer(out).squeeze(2)
-        # dense blocks
-        out = self.dense_blocks(out)
-        out = self.output_layer(out)
-        return out
-
-
-
-class Encoder(nn.Module):
-    '''
-    reference from: https://github.com/bshall/VectorQuantizedCPC/blob/master/model.py
-    '''
-    def __init__(self, in_channels, channels, n_embeddings, z_dim, c_dim):
-        super(Encoder, self).__init__()
-        self.conv = nn.Conv1d(in_channels, channels, 4, 2, 1, bias=False)
-        self.encoder = nn.Sequential(
-            nn.LayerNorm(channels),
-            nn.ReLU(True),
-            nn.Linear(channels, channels, bias=False),
-            nn.LayerNorm(channels),
-            nn.ReLU(True),
-            nn.Linear(channels, channels, bias=False),
-            nn.LayerNorm(channels),
-            nn.ReLU(True),
-            nn.Linear(channels, channels, bias=False),
-            nn.LayerNorm(channels),
-            nn.ReLU(True),
-            nn.Linear(channels, channels, bias=False),
-            nn.LayerNorm(channels),
-            nn.ReLU(True),
-            nn.Linear(channels, z_dim),
-        )
-        self.codebook = VQEmbeddingEMA(n_embeddings, z_dim)
-        self.rnn = nn.LSTM(z_dim, c_dim, batch_first=True)
-
-    def encode(self, mel):
-        z = self.conv(mel)
-        z_beforeVQ = self.encoder(z.transpose(1, 2))
-        z, r, indices = self.codebook.encode(z_beforeVQ)
-        c, _ = self.rnn(z)
-        return z, c, z_beforeVQ, indices
-
-    def forward(self, mels):
-        z = self.conv(mels.float()) # (bz, 80, 128) -> (bz, 512, 128/2)
-        z_beforeVQ = self.encoder(z.transpose(1, 2)) # (bz, 512, 128/2) -> (bz, 128/2, 512) -> (bz, 128/2, 64)
-        z, r, loss, perplexity = self.codebook(z_beforeVQ) # z: (bz, 128/2, 64)
-        c, _ = self.rnn(z) # (64, 140/2, 64) -> (64, 140/2, 256)
-        return z, c, z_beforeVQ, loss, perplexity
-    
-
-
-class VQEmbeddingEMA(nn.Module):
-    '''
-    reference from: https://github.com/bshall/VectorQuantizedCPC/blob/master/model.py
-    '''
-    def __init__(self, n_embeddings, embedding_dim, commitment_cost=0.25, decay=0.999, epsilon=1e-5):
-        super(VQEmbeddingEMA, self).__init__()
-        self.commitment_cost = commitment_cost
-        self.decay = decay
-        self.epsilon = epsilon
-
-        init_bound = 1 / 512
-        embedding = torch.Tensor(n_embeddings, embedding_dim)
-        embedding.uniform_(-init_bound, init_bound)
-        self.register_buffer("embedding", embedding) # only change during forward
-        self.register_buffer("ema_count", torch.zeros(n_embeddings))
-        self.register_buffer("ema_weight", self.embedding.clone())
-
-    def encode(self, x):
-        M, D = self.embedding.size()
-        x_flat = x.detach().reshape(-1, D)
-
-        distances = torch.addmm(torch.sum(self.embedding ** 2, dim=1) +
-                                torch.sum(x_flat ** 2, dim=1, keepdim=True),
-                                x_flat, self.embedding.t(),
-                                alpha=-2.0, beta=1.0)
-
-        indices = torch.argmin(distances.float(), dim=-1)
-        quantized = F.embedding(indices, self.embedding)
-        quantized = quantized.view_as(x)
-        residual = x - quantized
-        return quantized, residual, indices.view(x.size(0), x.size(1))
-
-    def forward(self, x):
-        M, D = self.embedding.size()
-        x_flat = x.detach().reshape(-1, D)
-
-        distances = torch.addmm(torch.sum(self.embedding ** 2, dim=1) +
-                                torch.sum(x_flat ** 2, dim=1, keepdim=True),
-                                x_flat, self.embedding.t(),
-                                alpha=-2.0, beta=1.0) # calculate the distance between each ele in embedding and x
-
-        indices = torch.argmin(distances.float(), dim=-1)
-        encodings = F.one_hot(indices, M).float()
-        quantized = F.embedding(indices, self.embedding)
-        quantized = quantized.view_as(x)
-
-        if self.training: # EMA based codebook learning
-            self.ema_count = self.decay * self.ema_count + (1 - self.decay) * torch.sum(encodings, dim=0)
-
-            n = torch.sum(self.ema_count)
-            self.ema_count = (self.ema_count + self.epsilon) / (n + M * self.epsilon) * n
-
-            dw = torch.matmul(encodings.t(), x_flat)
-            self.ema_weight = self.decay * self.ema_weight + (1 - self.decay) * dw
-
-            self.embedding = self.ema_weight / self.ema_count.unsqueeze(-1)
-
-        e_latent_loss = F.mse_loss(x, quantized.detach())
-        loss = self.commitment_cost * e_latent_loss
-        
-        residual = x - quantized
-        
-        quantized = x + (quantized - x).detach()
-
-        avg_probs = torch.mean(encodings, dim=0)
-        perplexity = torch.exp(-torch.sum(avg_probs * torch.log(avg_probs + 1e-10)))
-
-        return quantized, residual, loss, perplexity
-
-
-class CPCLoss(nn.Module):
-    '''
-    CPC-loss calculation: negative samples are drawn within-speaker
-    reference from: https://github.com/bshall/VectorQuantizedCPC/blob/master/model.py
-    '''
-    def __init__(self, n_speakers_per_batch, n_utterances_per_speaker, n_prediction_steps, n_negatives, z_dim, c_dim):
-        super(CPCLoss, self).__init__()
-        self.n_speakers_per_batch = n_speakers_per_batch
-        self.n_utterances_per_speaker = n_utterances_per_speaker
-        self.n_prediction_steps = n_prediction_steps // 2
-        self.n_negatives = n_negatives
-        self.z_dim = z_dim
-        self.c_dim = c_dim
-        self.predictors = nn.ModuleList([
-            nn.Linear(c_dim, z_dim) for _ in range(n_prediction_steps)
-        ])
-
-    def forward(self, z, c): # z:(64, 70, 64), c:(64, 70, 256)
-        length = z.size(1) - self.n_prediction_steps # 64
-
-        z = z.reshape(
-            self.n_speakers_per_batch,
-            self.n_utterances_per_speaker,
-            -1,
-            self.z_dim
-        ) # (64, 70, 64) -> (8, 8, 70, 64)
-        c = c[:, :-self.n_prediction_steps, :] # (64, 64, 256)
-
-        losses, accuracies = list(), list()
-        for k in range(1, self.n_prediction_steps+1):
-            z_shift = z[:, :, k:length + k, :] # (8, 8, 64, 64), positive samples
-
-            Wc = self.predictors[k-1](c) # (64, 64, 256) -> (64, 64, 64)
-            Wc = Wc.view(
-                self.n_speakers_per_batch,
-                self.n_utterances_per_speaker,
-                -1,
-                self.z_dim
-            ) # (64, 64, 64) -> (8, 8, 64, 64)
-
-            batch_index = torch.randint(
-                0, self.n_utterances_per_speaker,
-                size=(
-                    self.n_utterances_per_speaker,
-                    self.n_negatives
-                ),
-                device=z.device
-            )
-            batch_index = batch_index.view(
-                1, self.n_utterances_per_speaker, self.n_negatives, 1
-            ) # (1, 8, 17, 1)
-
-            # seq_index: (8, 8, 17, 64)
-            seq_index = torch.randint(
-                1, length,
-                size=(
-                    self.n_speakers_per_batch,
-                    self.n_utterances_per_speaker,
-                    self.n_negatives,
-                    length
-                ),
-                device=z.device
-            ) 
-            seq_index += torch.arange(length, device=z.device) #(1)
-            seq_index = torch.remainder(seq_index, length) #(2) (1)+(2) ensures that the current positive frame will not be selected as negative sample...
-            
-            speaker_index = torch.arange(self.n_speakers_per_batch, device=z.device) # within-speaker sampling
-            speaker_index = speaker_index.view(-1, 1, 1, 1)
-            
-            # z_negatives: (8,8,17,64,64); z_negatives[0,0,:,0,:] is (17, 64) that is negative samples for first frame of first utterance of first speaker...
-            z_negatives = z_shift[speaker_index, batch_index, seq_index, :] # speaker_index has the original order (within-speaker sampling)
-                                                                            # batch_index is randomly sampled from 0~7, each point has 17 negative samples
-                                                                            # seq_index is randomly sampled from 0~115
-                                                                        # so for each positive frame with time-id as t, the negative samples will be selected from 
-                                                                        # another or the current utterance and the seq-index (frame-index) will not conclude t  
-
-            zs = torch.cat((z_shift.unsqueeze(2), z_negatives), dim=2) # (8, 8, 1+17, 64, 64)
-
-            f = torch.sum(zs * Wc.unsqueeze(2) / math.sqrt(self.z_dim), dim=-1) # (8, 8, 1+17, 64), vector product in fact...
-            f = f.view(
-                self.n_speakers_per_batch * self.n_utterances_per_speaker,
-                self.n_negatives + 1,
-                -1
-            ) # (64, 1+17, 64)
-
-            labels = torch.zeros(
-                self.n_speakers_per_batch * self.n_utterances_per_speaker, length,
-                dtype=torch.long, device=z.device
-            ) # (64, 64)
-
-            loss = F.cross_entropy(f, labels)
-
-            accuracy = f.argmax(dim=1) == labels # (64, 116)
-            accuracy = torch.mean(accuracy.float())
-
-            losses.append(loss)
-            accuracies.append(accuracy.item())
-
-        loss = torch.stack(losses).mean()
-        return loss, accuracies
-
-
-class CPCLoss_sameSeq(nn.Module):
-    '''
-    CPC-loss calculation: negative samples are drawn within-sequence/utterance
-    '''
-    def __init__(self, n_speakers_per_batch, n_utterances_per_speaker, n_prediction_steps, n_negatives, z_dim, c_dim):
-        super(CPCLoss_sameSeq, self).__init__()
-        self.n_speakers_per_batch = n_speakers_per_batch
-        self.n_utterances_per_speaker = n_utterances_per_speaker
-        self.n_prediction_steps = n_prediction_steps 
-        self.n_negatives = n_negatives
-        self.z_dim = z_dim
-        self.c_dim = c_dim
-        self.predictors = nn.ModuleList([
-            nn.Linear(c_dim, z_dim) for _ in range(n_prediction_steps)
-        ])
-
-    def forward(self, z, c): # z:(256, 64, 64), c:(256, 64, 256)
-        length = z.size(1) - self.n_prediction_steps # 64-6=58, length is the total time-steps of each utterance used for calculated cpc loss
-        n_speakers_per_batch = z.shape[0] # each utterance is treated as a speaker
-        c = c[:, :-self.n_prediction_steps, :] # (256, 58, 256)
-
-        losses, accuracies = list(), list()
-        for k in range(1, self.n_prediction_steps+1):
-            z_shift = z[:, k:length + k, :] # (256, 58, 64), positive samples
-
-            Wc = self.predictors[k-1](c) # (256, 58, 256) -> (256, 58, 64)
-
-            # seq_index: (256, 10, 58)
-            seq_index = torch.randint(
-                1, length,
-                size=(
-                    n_speakers_per_batch,
-                    self.n_negatives,
-                    length
-                ),
-                device=z.device
-            ) 
-            seq_index += torch.arange(length, device=z.device) #(1)
-            seq_index = torch.remainder(seq_index, length) #(2) (1)+(2) ensures that the current positive frame will not be selected as negative sample...
-            
-            speaker_index = torch.arange(n_speakers_per_batch, device=z.device) # within-utterance sampling
-            speaker_index = speaker_index.view(-1, 1, 1)
-            
-            
-            z_negatives = z_shift[speaker_index, seq_index, :] # (256,10,58,64), z_negatives[i,:,j,:] is the negative samples set for ith utterance and jth time-step
-
-            zs = torch.cat((z_shift.unsqueeze(1), z_negatives), dim=1) # (256,11,58,64) 
-
-            f = torch.sum(zs * Wc.unsqueeze(1) / math.sqrt(self.z_dim), dim=-1) # (256,11,58), vector product in fact...
-            
-            labels = torch.zeros(
-                n_speakers_per_batch, length,
-                dtype=torch.long, device=z.device
-            ) 
-
-            loss = F.cross_entropy(f, labels)
-
-            accuracy = f.argmax(dim=1) == labels # (256, 58)
-            accuracy = torch.mean(accuracy.float())
-
-            losses.append(loss)
-            accuracies.append(accuracy.item())
-
-        loss = torch.stack(losses).mean()
-        return loss, accuracies
-    
-
-
diff --git a/spaces/akhaliq/neural-waveshaping-synthesis/neural_waveshaping_synthesis/data/utils/mfcc_extraction.py b/spaces/akhaliq/neural-waveshaping-synthesis/neural_waveshaping_synthesis/data/utils/mfcc_extraction.py
deleted file mode 100644
index ddece7192081f0977e7203a1a23855f01848fe95..0000000000000000000000000000000000000000
--- a/spaces/akhaliq/neural-waveshaping-synthesis/neural_waveshaping_synthesis/data/utils/mfcc_extraction.py
+++ /dev/null
@@ -1,13 +0,0 @@
-import gin
-import librosa
-import numpy as np
-
-
-@gin.configurable
-def extract_mfcc(
-    audio: np.ndarray, sample_rate: float, n_fft: int, hop_length: int, n_mfcc: int
-):
-    mfcc = librosa.feature.mfcc(
-        audio, sr=sample_rate, n_mfcc=n_mfcc, n_fft=n_fft, hop_length=hop_length
-    )
-    return mfcc
\ No newline at end of file
diff --git a/spaces/alecinvan/medidoctorchatbot/README.md b/spaces/alecinvan/medidoctorchatbot/README.md
deleted file mode 100644
index c3a42044e28e335ea014b7b3878b6a17384faf09..0000000000000000000000000000000000000000
--- a/spaces/alecinvan/medidoctorchatbot/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Medidoctorchatbot
-emoji: ⚡
-colorFrom: indigo
-colorTo: red
-sdk: gradio
-sdk_version: 3.43.2
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_vendor/html5lib/filters/lint.py b/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_vendor/html5lib/filters/lint.py
deleted file mode 100644
index fcc07eec5b2e5ea926fa8b2af199e14c9cac50dd..0000000000000000000000000000000000000000
--- a/spaces/alexray/btc_predictor/venv/lib/python3.10/site-packages/pip/_vendor/html5lib/filters/lint.py
+++ /dev/null
@@ -1,93 +0,0 @@
-from __future__ import absolute_import, division, unicode_literals
-
-from pip._vendor.six import text_type
-
-from . import base
-from ..constants import namespaces, voidElements
-
-from ..constants import spaceCharacters
-spaceCharacters = "".join(spaceCharacters)
-
-
-class Filter(base.Filter):
-    """Lints the token stream for errors
-
-    If it finds any errors, it'll raise an ``AssertionError``.
-
-    """
-    def __init__(self, source, require_matching_tags=True):
-        """Creates a Filter
-
-        :arg source: the source token stream
-
-        :arg require_matching_tags: whether or not to require matching tags
-
-        """
-        super(Filter, self).__init__(source)
-        self.require_matching_tags = require_matching_tags
-
-    def __iter__(self):
-        open_elements = []
-        for token in base.Filter.__iter__(self):
-            type = token["type"]
-            if type in ("StartTag", "EmptyTag"):
-                namespace = token["namespace"]
-                name = token["name"]
-                assert namespace is None or isinstance(namespace, text_type)
-                assert namespace != ""
-                assert isinstance(name, text_type)
-                assert name != ""
-                assert isinstance(token["data"], dict)
-                if (not namespace or namespace == namespaces["html"]) and name in voidElements:
-                    assert type == "EmptyTag"
-                else:
-                    assert type == "StartTag"
-                if type == "StartTag" and self.require_matching_tags:
-                    open_elements.append((namespace, name))
-                for (namespace, name), value in token["data"].items():
-                    assert namespace is None or isinstance(namespace, text_type)
-                    assert namespace != ""
-                    assert isinstance(name, text_type)
-                    assert name != ""
-                    assert isinstance(value, text_type)
-
-            elif type == "EndTag":
-                namespace = token["namespace"]
-                name = token["name"]
-                assert namespace is None or isinstance(namespace, text_type)
-                assert namespace != ""
-                assert isinstance(name, text_type)
-                assert name != ""
-                if (not namespace or namespace == namespaces["html"]) and name in voidElements:
-                    assert False, "Void element reported as EndTag token: %(tag)s" % {"tag": name}
-                elif self.require_matching_tags:
-                    start = open_elements.pop()
-                    assert start == (namespace, name)
-
-            elif type == "Comment":
-                data = token["data"]
-                assert isinstance(data, text_type)
-
-            elif type in ("Characters", "SpaceCharacters"):
-                data = token["data"]
-                assert isinstance(data, text_type)
-                assert data != ""
-                if type == "SpaceCharacters":
-                    assert data.strip(spaceCharacters) == ""
-
-            elif type == "Doctype":
-                name = token["name"]
-                assert name is None or isinstance(name, text_type)
-                assert token["publicId"] is None or isinstance(name, text_type)
-                assert token["systemId"] is None or isinstance(name, text_type)
-
-            elif type == "Entity":
-                assert isinstance(token["name"], text_type)
-
-            elif type == "SerializerError":
-                assert isinstance(token["data"], text_type)
-
-            else:
-                assert False, "Unknown token type: %(type)s" % {"type": type}
-
-            yield token
diff --git a/spaces/ali-ghamdan/deoldify/fastai/utils/check_perf.py b/spaces/ali-ghamdan/deoldify/fastai/utils/check_perf.py
deleted file mode 100644
index 3d7b9c7c4994fc39c8d7262589691e5b3e159712..0000000000000000000000000000000000000000
--- a/spaces/ali-ghamdan/deoldify/fastai/utils/check_perf.py
+++ /dev/null
@@ -1,6 +0,0 @@
-from ..script import *
-from .collect_env import *
-
-# Temporary POC for module-based script
-call_parse(check_perf)
-
diff --git a/spaces/anaclaudia13ct/insect_detection/utils/segment/metrics.py b/spaces/anaclaudia13ct/insect_detection/utils/segment/metrics.py
deleted file mode 100644
index b09ce23fb9e398ab654fce676d23f74d81cc5c57..0000000000000000000000000000000000000000
--- a/spaces/anaclaudia13ct/insect_detection/utils/segment/metrics.py
+++ /dev/null
@@ -1,210 +0,0 @@
-# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
-"""
-Model validation metrics
-"""
-
-import numpy as np
-
-from ..metrics import ap_per_class
-
-
-def fitness(x):
-    # Model fitness as a weighted combination of metrics
-    w = [0.0, 0.0, 0.1, 0.9, 0.0, 0.0, 0.1, 0.9]
-    return (x[:, :8] * w).sum(1)
-
-
-def ap_per_class_box_and_mask(
-        tp_m,
-        tp_b,
-        conf,
-        pred_cls,
-        target_cls,
-        plot=False,
-        save_dir=".",
-        names=(),
-):
-    """
-    Args:
-        tp_b: tp of boxes.
-        tp_m: tp of masks.
-        other arguments see `func: ap_per_class`.
-    """
-    results_boxes = ap_per_class(tp_b,
-                                 conf,
-                                 pred_cls,
-                                 target_cls,
-                                 plot=plot,
-                                 save_dir=save_dir,
-                                 names=names,
-                                 prefix="Box")[2:]
-    results_masks = ap_per_class(tp_m,
-                                 conf,
-                                 pred_cls,
-                                 target_cls,
-                                 plot=plot,
-                                 save_dir=save_dir,
-                                 names=names,
-                                 prefix="Mask")[2:]
-
-    results = {
-        "boxes": {
-            "p": results_boxes[0],
-            "r": results_boxes[1],
-            "ap": results_boxes[3],
-            "f1": results_boxes[2],
-            "ap_class": results_boxes[4]},
-        "masks": {
-            "p": results_masks[0],
-            "r": results_masks[1],
-            "ap": results_masks[3],
-            "f1": results_masks[2],
-            "ap_class": results_masks[4]}}
-    return results
-
-
-class Metric:
-
-    def __init__(self) -> None:
-        self.p = []  # (nc, )
-        self.r = []  # (nc, )
-        self.f1 = []  # (nc, )
-        self.all_ap = []  # (nc, 10)
-        self.ap_class_index = []  # (nc, )
-
-    @property
-    def ap50(self):
-        """AP@0.5 of all classes.
-        Return:
-            (nc, ) or [].
-        """
-        return self.all_ap[:, 0] if len(self.all_ap) else []
-
-    @property
-    def ap(self):
-        """AP@0.5:0.95
-        Return:
-            (nc, ) or [].
-        """
-        return self.all_ap.mean(1) if len(self.all_ap) else []
-
-    @property
-    def mp(self):
-        """mean precision of all classes.
-        Return:
-            float.
-        """
-        return self.p.mean() if len(self.p) else 0.0
-
-    @property
-    def mr(self):
-        """mean recall of all classes.
-        Return:
-            float.
-        """
-        return self.r.mean() if len(self.r) else 0.0
-
-    @property
-    def map50(self):
-        """Mean AP@0.5 of all classes.
-        Return:
-            float.
-        """
-        return self.all_ap[:, 0].mean() if len(self.all_ap) else 0.0
-
-    @property
-    def map(self):
-        """Mean AP@0.5:0.95 of all classes.
-        Return:
-            float.
-        """
-        return self.all_ap.mean() if len(self.all_ap) else 0.0
-
-    def mean_results(self):
-        """Mean of results, return mp, mr, map50, map"""
-        return (self.mp, self.mr, self.map50, self.map)
-
-    def class_result(self, i):
-        """class-aware result, return p[i], r[i], ap50[i], ap[i]"""
-        return (self.p[i], self.r[i], self.ap50[i], self.ap[i])
-
-    def get_maps(self, nc):
-        maps = np.zeros(nc) + self.map
-        for i, c in enumerate(self.ap_class_index):
-            maps[c] = self.ap[i]
-        return maps
-
-    def update(self, results):
-        """
-        Args:
-            results: tuple(p, r, ap, f1, ap_class)
-        """
-        p, r, all_ap, f1, ap_class_index = results
-        self.p = p
-        self.r = r
-        self.all_ap = all_ap
-        self.f1 = f1
-        self.ap_class_index = ap_class_index
-
-
-class Metrics:
-    """Metric for boxes and masks."""
-
-    def __init__(self) -> None:
-        self.metric_box = Metric()
-        self.metric_mask = Metric()
-
-    def update(self, results):
-        """
-        Args:
-            results: Dict{'boxes': Dict{}, 'masks': Dict{}}
-        """
-        self.metric_box.update(list(results["boxes"].values()))
-        self.metric_mask.update(list(results["masks"].values()))
-
-    def mean_results(self):
-        return self.metric_box.mean_results() + self.metric_mask.mean_results()
-
-    def class_result(self, i):
-        return self.metric_box.class_result(i) + self.metric_mask.class_result(i)
-
-    def get_maps(self, nc):
-        return self.metric_box.get_maps(nc) + self.metric_mask.get_maps(nc)
-
-    @property
-    def ap_class_index(self):
-        # boxes and masks have the same ap_class_index
-        return self.metric_box.ap_class_index
-
-
-KEYS = [
-    "train/box_loss",
-    "train/seg_loss",  # train loss
-    "train/obj_loss",
-    "train/cls_loss",
-    "metrics/precision(B)",
-    "metrics/recall(B)",
-    "metrics/mAP_0.5(B)",
-    "metrics/mAP_0.5:0.95(B)",  # metrics
-    "metrics/precision(M)",
-    "metrics/recall(M)",
-    "metrics/mAP_0.5(M)",
-    "metrics/mAP_0.5:0.95(M)",  # metrics
-    "val/box_loss",
-    "val/seg_loss",  # val loss
-    "val/obj_loss",
-    "val/cls_loss",
-    "x/lr0",
-    "x/lr1",
-    "x/lr2",]
-
-BEST_KEYS = [
-    "best/epoch",
-    "best/precision(B)",
-    "best/recall(B)",
-    "best/mAP_0.5(B)",
-    "best/mAP_0.5:0.95(B)",
-    "best/precision(M)",
-    "best/recall(M)",
-    "best/mAP_0.5(M)",
-    "best/mAP_0.5:0.95(M)",]
diff --git a/spaces/aodianyun/stable-diffusion-webui/extensions/deforum/install.py b/spaces/aodianyun/stable-diffusion-webui/extensions/deforum/install.py
deleted file mode 100644
index b9166e71c44972d8582836239636d0f483a51ff5..0000000000000000000000000000000000000000
--- a/spaces/aodianyun/stable-diffusion-webui/extensions/deforum/install.py
+++ /dev/null
@@ -1,14 +0,0 @@
-import launch
-import os
-import sys
-
-req_file = os.path.join(os.path.dirname(os.path.realpath(__file__)), "requirements.txt")
-
-with open(req_file) as file:
-    for lib in file:
-        lib = lib.strip()
-        if not launch.is_installed(lib):
-            if lib == 'rich':
-                launch.run(f'"{sys.executable}" -m pip install {lib}', desc=f"Installing Deforum requirement: {lib}", errdesc=f"Couldn't install {lib}")
-            else:
-                launch.run_pip(f"install {lib}", f"Deforum requirement: {lib}")
diff --git a/spaces/artificialguybr/video-dubbing/TTS/TTS/tts/layers/tacotron/capacitron_layers.py b/spaces/artificialguybr/video-dubbing/TTS/TTS/tts/layers/tacotron/capacitron_layers.py
deleted file mode 100644
index 2181ffa7ec4e1f54d86cc5865a8fa7f6b6e362af..0000000000000000000000000000000000000000
--- a/spaces/artificialguybr/video-dubbing/TTS/TTS/tts/layers/tacotron/capacitron_layers.py
+++ /dev/null
@@ -1,205 +0,0 @@
-import torch
-from torch import nn
-from torch.distributions.multivariate_normal import MultivariateNormal as MVN
-from torch.nn import functional as F
-
-
-class CapacitronVAE(nn.Module):
-    """Effective Use of Variational Embedding Capacity for prosody transfer.
-
-    See https://arxiv.org/abs/1906.03402"""
-
-    def __init__(
-        self,
-        num_mel,
-        capacitron_VAE_embedding_dim,
-        encoder_output_dim=256,
-        reference_encoder_out_dim=128,
-        speaker_embedding_dim=None,
-        text_summary_embedding_dim=None,
-    ):
-        super().__init__()
-        # Init distributions
-        self.prior_distribution = MVN(
-            torch.zeros(capacitron_VAE_embedding_dim), torch.eye(capacitron_VAE_embedding_dim)
-        )
-        self.approximate_posterior_distribution = None
-        # define output ReferenceEncoder dim to the capacitron_VAE_embedding_dim
-        self.encoder = ReferenceEncoder(num_mel, out_dim=reference_encoder_out_dim)
-
-        # Init beta, the lagrange-like term for the KL distribution
-        self.beta = torch.nn.Parameter(torch.log(torch.exp(torch.Tensor([1.0])) - 1), requires_grad=True)
-        mlp_input_dimension = reference_encoder_out_dim
-
-        if text_summary_embedding_dim is not None:
-            self.text_summary_net = TextSummary(text_summary_embedding_dim, encoder_output_dim=encoder_output_dim)
-            mlp_input_dimension += text_summary_embedding_dim
-        if speaker_embedding_dim is not None:
-            # TODO: Test a multispeaker model!
-            mlp_input_dimension += speaker_embedding_dim
-        self.post_encoder_mlp = PostEncoderMLP(mlp_input_dimension, capacitron_VAE_embedding_dim)
-
-    def forward(self, reference_mel_info=None, text_info=None, speaker_embedding=None):
-        # Use reference
-        if reference_mel_info is not None:
-            reference_mels = reference_mel_info[0]  # [batch_size, num_frames, num_mels]
-            mel_lengths = reference_mel_info[1]  # [batch_size]
-            enc_out = self.encoder(reference_mels, mel_lengths)
-
-            # concat speaker_embedding and/or text summary embedding
-            if text_info is not None:
-                text_inputs = text_info[0]  # [batch_size, num_characters, num_embedding]
-                input_lengths = text_info[1]
-                text_summary_out = self.text_summary_net(text_inputs, input_lengths).to(reference_mels.device)
-                enc_out = torch.cat([enc_out, text_summary_out], dim=-1)
-            if speaker_embedding is not None:
-                speaker_embedding = torch.squeeze(speaker_embedding)
-                enc_out = torch.cat([enc_out, speaker_embedding], dim=-1)
-
-            # Feed the output of the ref encoder and information about text/speaker into
-            # an MLP to produce the parameteres for the approximate poterior distributions
-            mu, sigma = self.post_encoder_mlp(enc_out)
-            # convert to cpu because prior_distribution was created on cpu
-            mu = mu.cpu()
-            sigma = sigma.cpu()
-
-            # Sample from the posterior: z ~ q(z|x)
-            self.approximate_posterior_distribution = MVN(mu, torch.diag_embed(sigma))
-            VAE_embedding = self.approximate_posterior_distribution.rsample()
-        # Infer from the model, bypasses encoding
-        else:
-            # Sample from the prior: z ~ p(z)
-            VAE_embedding = self.prior_distribution.sample().unsqueeze(0)
-
-        # reshape to [batch_size, 1, capacitron_VAE_embedding_dim]
-        return VAE_embedding.unsqueeze(1), self.approximate_posterior_distribution, self.prior_distribution, self.beta
-
-
-class ReferenceEncoder(nn.Module):
-    """NN module creating a fixed size prosody embedding from a spectrogram.
-
-    inputs: mel spectrograms [batch_size, num_spec_frames, num_mel]
-    outputs: [batch_size, embedding_dim]
-    """
-
-    def __init__(self, num_mel, out_dim):
-        super().__init__()
-        self.num_mel = num_mel
-        filters = [1] + [32, 32, 64, 64, 128, 128]
-        num_layers = len(filters) - 1
-        convs = [
-            nn.Conv2d(
-                in_channels=filters[i], out_channels=filters[i + 1], kernel_size=(3, 3), stride=(2, 2), padding=(2, 2)
-            )
-            for i in range(num_layers)
-        ]
-        self.convs = nn.ModuleList(convs)
-        self.training = False
-        self.bns = nn.ModuleList([nn.BatchNorm2d(num_features=filter_size) for filter_size in filters[1:]])
-
-        post_conv_height = self.calculate_post_conv_height(num_mel, 3, 2, 2, num_layers)
-        self.recurrence = nn.LSTM(
-            input_size=filters[-1] * post_conv_height, hidden_size=out_dim, batch_first=True, bidirectional=False
-        )
-
-    def forward(self, inputs, input_lengths):
-        batch_size = inputs.size(0)
-        x = inputs.view(batch_size, 1, -1, self.num_mel)  # [batch_size, num_channels==1, num_frames, num_mel]
-        valid_lengths = input_lengths.float()  # [batch_size]
-        for conv, bn in zip(self.convs, self.bns):
-            x = conv(x)
-            x = bn(x)
-            x = F.relu(x)
-
-            # Create the post conv width mask based on the valid lengths of the output of the convolution.
-            # The valid lengths for the output of a convolution on varying length inputs is
-            # ceil(input_length/stride) + 1 for stride=3 and padding=2
-            # For example (kernel_size=3, stride=2, padding=2):
-            # 0 0 x x x x x 0 0 -> Input = 5, 0 is zero padding, x is valid values coming from padding=2 in conv2d
-            # _____
-            #   x _____
-            #       x _____
-            #           x  ____
-            #               x
-            # x x x x -> Output valid length = 4
-            # Since every example in te batch is zero padded and therefore have separate valid_lengths,
-            # we need to mask off all the values AFTER the valid length for each example in the batch.
-            # Otherwise, the convolutions create noise and a lot of not real information
-            valid_lengths = (valid_lengths / 2).float()
-            valid_lengths = torch.ceil(valid_lengths).to(dtype=torch.int64) + 1  # 2 is stride -- size: [batch_size]
-            post_conv_max_width = x.size(2)
-
-            mask = torch.arange(post_conv_max_width).to(inputs.device).expand(
-                len(valid_lengths), post_conv_max_width
-            ) < valid_lengths.unsqueeze(1)
-            mask = mask.expand(1, 1, -1, -1).transpose(2, 0).transpose(-1, 2)  # [batch_size, 1, post_conv_max_width, 1]
-            x = x * mask
-
-        x = x.transpose(1, 2)
-        # x: 4D tensor [batch_size, post_conv_width,
-        #               num_channels==128, post_conv_height]
-
-        post_conv_width = x.size(1)
-        x = x.contiguous().view(batch_size, post_conv_width, -1)
-        # x: 3D tensor [batch_size, post_conv_width,
-        #               num_channels*post_conv_height]
-
-        # Routine for fetching the last valid output of a dynamic LSTM with varying input lengths and padding
-        post_conv_input_lengths = valid_lengths
-        packed_seqs = nn.utils.rnn.pack_padded_sequence(
-            x, post_conv_input_lengths.tolist(), batch_first=True, enforce_sorted=False
-        )  # dynamic rnn sequence padding
-        self.recurrence.flatten_parameters()
-        _, (ht, _) = self.recurrence(packed_seqs)
-        last_output = ht[-1]
-
-        return last_output.to(inputs.device)  # [B, 128]
-
-    @staticmethod
-    def calculate_post_conv_height(height, kernel_size, stride, pad, n_convs):
-        """Height of spec after n convolutions with fixed kernel/stride/pad."""
-        for _ in range(n_convs):
-            height = (height - kernel_size + 2 * pad) // stride + 1
-        return height
-
-
-class TextSummary(nn.Module):
-    def __init__(self, embedding_dim, encoder_output_dim):
-        super().__init__()
-        self.lstm = nn.LSTM(
-            encoder_output_dim,  # text embedding dimension from the text encoder
-            embedding_dim,  # fixed length output summary the lstm creates from the input
-            batch_first=True,
-            bidirectional=False,
-        )
-
-    def forward(self, inputs, input_lengths):
-        # Routine for fetching the last valid output of a dynamic LSTM with varying input lengths and padding
-        packed_seqs = nn.utils.rnn.pack_padded_sequence(
-            inputs, input_lengths.tolist(), batch_first=True, enforce_sorted=False
-        )  # dynamic rnn sequence padding
-        self.lstm.flatten_parameters()
-        _, (ht, _) = self.lstm(packed_seqs)
-        last_output = ht[-1]
-        return last_output
-
-
-class PostEncoderMLP(nn.Module):
-    def __init__(self, input_size, hidden_size):
-        super().__init__()
-        self.hidden_size = hidden_size
-        modules = [
-            nn.Linear(input_size, hidden_size),  # Hidden Layer
-            nn.Tanh(),
-            nn.Linear(hidden_size, hidden_size * 2),
-        ]  # Output layer twice the size for mean and variance
-        self.net = nn.Sequential(*modules)
-        self.softplus = nn.Softplus()
-
-    def forward(self, _input):
-        mlp_output = self.net(_input)
-        # The mean parameter is unconstrained
-        mu = mlp_output[:, : self.hidden_size]
-        # The standard deviation must be positive. Parameterise with a softplus
-        sigma = self.softplus(mlp_output[:, self.hidden_size :])
-        return mu, sigma
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/antlr4/atn/Transition.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/antlr4/atn/Transition.py
deleted file mode 100644
index 0ed042cdaf391411a2eb4e6d2dca083920ee3ff1..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/antlr4/atn/Transition.py
+++ /dev/null
@@ -1,257 +0,0 @@
-#
-# Copyright (c) 2012-2017 The ANTLR Project. All rights reserved.
-# Use of this file is governed by the BSD 3-clause license that
-# can be found in the LICENSE.txt file in the project root.
-#
-
-#  An ATN transition between any two ATN states.  Subclasses define
-#  atom, set, epsilon, action, predicate, rule transitions.
-#
-#  <p>This is a one way link.  It emanates from a state (usually via a list of
-#  transitions) and has a target state.</p>
-#
-#  <p>Since we never have to change the ATN transitions once we construct it,
-#  we can fix these transitions as specific classes. The DFA transitions
-#  on the other hand need to update the labels as it adds transitions to
-#  the states. We'll use the term Edge for the DFA to distinguish them from
-#  ATN transitions.</p>
-#
-from antlr4.IntervalSet import IntervalSet
-from antlr4.Token import Token
-
-# need forward declarations
-from antlr4.atn.SemanticContext import Predicate, PrecedencePredicate
-
-ATNState = None
-RuleStartState = None
-
-class Transition (object):
-    # constants for serialization
-    EPSILON			= 1
-    RANGE			= 2
-    RULE			= 3
-    PREDICATE		= 4 # e.g., {isType(input.LT(1))}?
-    ATOM			= 5
-    ACTION			= 6
-    SET				= 7 # ~(A|B) or ~atom, wildcard, which convert to next 2
-    NOT_SET			= 8
-    WILDCARD		= 9
-    PRECEDENCE		= 10
-
-    serializationNames = [
-            "INVALID",
-            "EPSILON",
-            "RANGE",
-            "RULE",
-            "PREDICATE",
-            "ATOM",
-            "ACTION",
-            "SET",
-            "NOT_SET",
-            "WILDCARD",
-            "PRECEDENCE"
-        ]
-
-    serializationTypes = dict()
-
-    def __init__(self, target:ATNState):
-        # The target of this transition.
-        if target is None:
-            raise Exception("target cannot be null.")
-        self.target = target
-        # Are we epsilon, action, sempred?
-        self.isEpsilon = False
-        self.label = None
-
-
-# TODO: make all transitions sets? no, should remove set edges
-class AtomTransition(Transition):
-
-    def __init__(self, target:ATNState, label:int):
-        super().__init__(target)
-        self.label_ = label # The token type or character value; or, signifies special label.
-        self.label = self.makeLabel()
-        self.serializationType = self.ATOM
-
-    def makeLabel(self):
-        s = IntervalSet()
-        s.addOne(self.label_)
-        return s
-
-    def matches( self, symbol:int, minVocabSymbol:int,  maxVocabSymbol:int):
-        return self.label_ == symbol
-
-    def __str__(self):
-        return str(self.label_)
-
-class RuleTransition(Transition):
-
-    def __init__(self, ruleStart:RuleStartState, ruleIndex:int, precedence:int, followState:ATNState):
-        super().__init__(ruleStart)
-        self.ruleIndex = ruleIndex # ptr to the rule definition object for this rule ref
-        self.precedence = precedence
-        self.followState = followState # what node to begin computations following ref to rule
-        self.serializationType = self.RULE
-        self.isEpsilon = True
-
-    def matches( self, symbol:int, minVocabSymbol:int,  maxVocabSymbol:int):
-        return False
-
-
-class EpsilonTransition(Transition):
-
-    def __init__(self, target, outermostPrecedenceReturn=-1):
-        super(EpsilonTransition, self).__init__(target)
-        self.serializationType = self.EPSILON
-        self.isEpsilon = True
-        self.outermostPrecedenceReturn = outermostPrecedenceReturn
-
-    def matches( self, symbol:int, minVocabSymbol:int,  maxVocabSymbol:int):
-        return False
-
-    def __str__(self):
-        return "epsilon"
-
-class RangeTransition(Transition):
-
-    def __init__(self, target:ATNState, start:int, stop:int):
-        super().__init__(target)
-        self.serializationType = self.RANGE
-        self.start = start
-        self.stop = stop
-        self.label = self.makeLabel()
-
-    def makeLabel(self):
-        s = IntervalSet()
-        s.addRange(range(self.start, self.stop + 1))
-        return s
-
-    def matches( self, symbol:int, minVocabSymbol:int,  maxVocabSymbol:int):
-        return symbol >= self.start and symbol <= self.stop
-
-    def __str__(self):
-        return "'" + chr(self.start) + "'..'" + chr(self.stop) + "'"
-
-class AbstractPredicateTransition(Transition):
-
-    def __init__(self, target:ATNState):
-        super().__init__(target)
-
-
-class PredicateTransition(AbstractPredicateTransition):
-
-    def __init__(self, target:ATNState, ruleIndex:int, predIndex:int, isCtxDependent:bool):
-        super().__init__(target)
-        self.serializationType = self.PREDICATE
-        self.ruleIndex = ruleIndex
-        self.predIndex = predIndex
-        self.isCtxDependent = isCtxDependent # e.g., $i ref in pred
-        self.isEpsilon = True
-
-    def matches( self, symbol:int, minVocabSymbol:int,  maxVocabSymbol:int):
-        return False
-
-    def getPredicate(self):
-        return Predicate(self.ruleIndex, self.predIndex, self.isCtxDependent)
-
-    def __str__(self):
-        return "pred_" + str(self.ruleIndex) + ":" + str(self.predIndex)
-
-class ActionTransition(Transition):
-
-    def __init__(self, target:ATNState, ruleIndex:int, actionIndex:int=-1, isCtxDependent:bool=False):
-        super().__init__(target)
-        self.serializationType = self.ACTION
-        self.ruleIndex = ruleIndex
-        self.actionIndex = actionIndex
-        self.isCtxDependent = isCtxDependent # e.g., $i ref in pred
-        self.isEpsilon = True
-
-    def matches( self, symbol:int, minVocabSymbol:int,  maxVocabSymbol:int):
-        return False
-
-    def __str__(self):
-        return "action_"+self.ruleIndex+":"+self.actionIndex
-
-# A transition containing a set of values.
-class SetTransition(Transition):
-
-    def __init__(self, target:ATNState, set:IntervalSet):
-        super().__init__(target)
-        self.serializationType = self.SET
-        if set is not None:
-            self.label = set
-        else:
-            self.label = IntervalSet()
-            self.label.addRange(range(Token.INVALID_TYPE, Token.INVALID_TYPE + 1))
-
-    def matches( self, symbol:int, minVocabSymbol:int,  maxVocabSymbol:int):
-        return symbol in self.label
-
-    def __str__(self):
-        return str(self.label)
-
-class NotSetTransition(SetTransition):
-
-    def __init__(self, target:ATNState, set:IntervalSet):
-        super().__init__(target, set)
-        self.serializationType = self.NOT_SET
-
-    def matches( self, symbol:int, minVocabSymbol:int,  maxVocabSymbol:int):
-        return symbol >= minVocabSymbol \
-            and symbol <= maxVocabSymbol \
-            and not super(type(self), self).matches(symbol, minVocabSymbol, maxVocabSymbol)
-
-    def __str__(self):
-        return '~' + super(type(self), self).__str__()
-
-
-class WildcardTransition(Transition):
-
-    def __init__(self, target:ATNState):
-        super().__init__(target)
-        self.serializationType = self.WILDCARD
-
-    def matches( self, symbol:int, minVocabSymbol:int,  maxVocabSymbol:int):
-        return symbol >= minVocabSymbol and symbol <= maxVocabSymbol
-
-    def __str__(self):
-        return "."
-
-
-class PrecedencePredicateTransition(AbstractPredicateTransition):
-
-    def __init__(self, target:ATNState, precedence:int):
-        super().__init__(target)
-        self.serializationType = self.PRECEDENCE
-        self.precedence = precedence
-        self.isEpsilon = True
-
-    def matches( self, symbol:int, minVocabSymbol:int,  maxVocabSymbol:int):
-        return False
-
-
-    def getPredicate(self):
-        return PrecedencePredicate(self.precedence)
-
-    def __str__(self):
-        return self.precedence + " >= _p"
-
-
-Transition.serializationTypes = {
-             EpsilonTransition: Transition.EPSILON,
-             RangeTransition: Transition.RANGE,
-             RuleTransition: Transition.RULE,
-             PredicateTransition: Transition.PREDICATE,
-             AtomTransition: Transition.ATOM,
-             ActionTransition: Transition.ACTION,
-             SetTransition: Transition.SET,
-             NotSetTransition: Transition.NOT_SET,
-             WildcardTransition: Transition.WILDCARD,
-             PrecedencePredicateTransition: Transition.PRECEDENCE
-         }
-
-del ATNState
-del RuleStartState
-
-from antlr4.atn.ATNState import *
\ No newline at end of file
diff --git a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/data/encoders/moses_tokenizer.py b/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/data/encoders/moses_tokenizer.py
deleted file mode 100644
index e236dad167a037a8ed95f7fc8292b27b10d580b0..0000000000000000000000000000000000000000
--- a/spaces/arxify/RVC-beta-v2-0618/runtime/Lib/site-packages/fairseq/data/encoders/moses_tokenizer.py
+++ /dev/null
@@ -1,49 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-from dataclasses import dataclass, field
-
-from fairseq.data.encoders import register_tokenizer
-from fairseq.dataclass import FairseqDataclass
-
-
-@dataclass
-class MosesTokenizerConfig(FairseqDataclass):
-    source_lang: str = field(default="en", metadata={"help": "source language"})
-    target_lang: str = field(default="en", metadata={"help": "target language"})
-    moses_no_dash_splits: bool = field(
-        default=False, metadata={"help": "don't apply dash split rules"}
-    )
-    moses_no_escape: bool = field(
-        default=False,
-        metadata={"help": "don't perform HTML escaping on apostrophe, quotes, etc."},
-    )
-
-
-@register_tokenizer("moses", dataclass=MosesTokenizerConfig)
-class MosesTokenizer(object):
-    def __init__(self, cfg: MosesTokenizerConfig):
-        self.cfg = cfg
-
-        try:
-            from sacremoses import MosesTokenizer, MosesDetokenizer
-
-            self.tok = MosesTokenizer(cfg.source_lang)
-            self.detok = MosesDetokenizer(cfg.target_lang)
-        except ImportError:
-            raise ImportError(
-                "Please install Moses tokenizer with: pip install sacremoses"
-            )
-
-    def encode(self, x: str) -> str:
-        return self.tok.tokenize(
-            x,
-            aggressive_dash_splits=(not self.cfg.moses_no_dash_splits),
-            return_str=True,
-            escape=(not self.cfg.moses_no_escape),
-        )
-
-    def decode(self, x: str) -> str:
-        return self.detok.detokenize(x.split())
diff --git a/spaces/at2507/SM_NLP_RecoSys/Data/Mentor_interviews/Rondale Williams.html b/spaces/at2507/SM_NLP_RecoSys/Data/Mentor_interviews/Rondale Williams.html
deleted file mode 100644
index 8adcacbeb46ec814c1e97d5c64f2b8889a5a2edf..0000000000000000000000000000000000000000
--- a/spaces/at2507/SM_NLP_RecoSys/Data/Mentor_interviews/Rondale Williams.html	
+++ /dev/null
@@ -1,134 +0,0 @@
-<!DOCTYPE html><html lang="en"><head>
-    <meta charset="utf-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1, user-scalable=no">
-    <title>Rondale Williams</title>
-    <style>
-      html {
-        padding: 1em;
-        background: #fff;
-        color: #222;
-        font-family: "Lucida Grande", "Lucida Sans Unicode", "Lucida Sans", Geneva, Verdana, sans-serif;
-        font-size: 100%;
-        line-height: 1.5;
-      }
-
-      h1,
-      p,
-      ul,
-      ol,
-      div,
-      figure {
-        margin: 0;
-      }
-
-      h1 { font-size: 1.2em; }
-
-      ul {
-        list-style: disc;
-        padding-left: 1.3em;
-      }
-
-      ol {
-        padding-left: 1.3em;
-        list-style: decimal;
-      }
-
-      blockquote {
-        border-left: 3px solid #000;
-        margin: 0;
-        padding: 0 0 0 1em;
-      }
-
-      pre {
-        font-family: monaco, monospace;
-        font-size: 0.875em;
-        margin: 0;
-        padding: 1rem;
-        background: #eee;
-        border-radius: 0.4rem;
-        white-space: pre;
-        word-wrap: normal;
-        word-break: normal;
-        overflow-x: auto;
-      }
-
-      code { border-radius: 0.4rem; }
-
-      figure {
-        display: inline-block;
-        width: 100%;
-        box-sizing: border-box;
-      }
-
-      figcaption { word-break: break-word; }
-
-      img {
-        display: block;
-        max-width: 100%;
-        margin: 0 auto;
-        padding: 1px;
-        border: 1px solid #eee;
-      }
-
-      a {
-        color: #1b6ac9;
-        text-decoration: underline;
-      }
-
-      a:active { color: #064ac9; }
-
-      .wrapper {
-        max-width: 650px;
-        margin: 0 auto;
-      }
-
-      .title {
-        font-size: 2em;
-        margin: 0.5em 0 1em;
-        line-height: 1.3;
-      }
-
-      .attachment--image {
-        text-align: center;
-        color: #888;
-        font-size: 0.875em;
-      }
-
-      .attachment--file {
-        position: relative;
-        padding: 1.4em 1em 1.5em;
-        border: 1px solid #ddd;
-        border-bottom-width: 3px;
-        border-radius: 6px;
-        color: #222;
-      }
-
-      .attachment__label {
-        position: absolute;
-        bottom: 0;
-        right: 0;
-        background: #ddd;
-        font-size: 10px;
-        padding: 2px 6px;
-        border-radius: 6px 0 4px 0;
-        color: #888;
-      }
-
-      .metadata { color: #888; }
-    </style>
-  </head>
-
-  <body>
-    <div class="wrapper">
-      <h1 class="title">Rondale Williams</h1>
-
-<div class="formatted_content">
-  <h1>Application</h1><div><br>SWE mentor! and previous mentee<br><br><a target="_blank" rel="noreferrer" class="autolinked" data-behavior="truncate" href="https://www.linkedin.com/in/rondale-williams-725b8924/">https://www.linkedin.com/in/rondale-williams-725b8924/</a><br><br></div><blockquote>I'd love to teach others how fun this career is, how to easily build projects, design patterns, software architecture, and how to find answers to questions without searching for answers for hours. Too often, I see junior engineers get caught up learning the nuances of programming languages and the many frameworks that help software engineers build apps. Instead, I'd like to show aspiring engineers how they can easily get a job by quickly learning the tools they need to get a job and the basics of the programming languages they need to learn to get a job quickly. I'd also love to show them how software engineering teams actually work in agile environments, how to write tests and the mentality behind writing tests, and how we use Git to work as a team.</blockquote><div><br></div><h1>Interview</h1><div><strong>How did you hear about SM?</strong></div><ul><li>Former SM mentee</li></ul><div><strong>Career</strong></div><ul><li>taught himself to code</li><li>iOS engineer at a startup for about a year</li><li>then moved to Disney as iOS engineer</li><li>transitioned to android engineer worked as HeadSpace and</li><li>then started a mentorship</li><li>worked for about a year as a DS /MLE</li><li>then moved back to SWE and got a job at Paypal (lots of money)</li><li>Now contracting for Lululemon (android application)</li></ul><div><strong>Mentorship experience?</strong></div><ul><li>Mentoring a friend that is trying to get into DS<ul><li>Social support/confidence building</li><li>helping her decide what route (NLP vs. applied)</li><li>give her the right resources (focus on the fundamentals - ignore the fluff). Keep her on the right path</li></ul></li><li>Jr engineers underneath me</li><li>Folks that have reached out<ul><li>get lost in frameworks / APIs / libraries</li><li>give them the basis of what they need to know</li><li>get lost in the nuance of a language&nbsp;</li><li>or overkill learning and not building stuff</li></ul></li></ul><div><strong>What are beginners lacking?</strong></div><ul><li>The fundamentals:<ul><li>understand how apps work at a very high level</li><li>what does that architecture look like? How does everything interconnect</li><li>common design patterns (view/model) (MVP/MVC)</li><li>everything else is just a puzzle piece</li><li>top-down vs bottom-down</li></ul></li></ul><div><strong>And how can you add value as a mentor?</strong></div><ul><li>Coaching (keep their confidence up!)</li><li>Dealing with rejection</li><li>teach them how to network (go to meetups, personal brand online)</li><li>where to look for answers (docs for things) how to search for answers</li><li>No question is a dumb question!!</li></ul><div><strong>Ideal mentee</strong></div><ul><li>most comfortable with<strong> mobile dev</strong></li><li>But I could probably still help folks with back-end stuff</li></ul><div><bc-attachment content-type="application/vnd.basecamp.horizontal-rule.html"><figure class="attachment attachment--content attachment--horizontal-rule">
-  <hr>
-</figure></bc-attachment></div><div><strong>Questions about SM?</strong></div><ul><li>How does the mentorship program work?</li><li>What's the timeline look like for the push to SWE?</li></ul><div><br>Worked&nbsp; at Headspace and is down to connect with Debbie (who requested this a while back)</div><div></div>
-</div>
-
-    </div>
-  
-
-</body></html>
\ No newline at end of file
diff --git a/spaces/atharvat80/Wikipedia2Vec-NED/src/__init__.py b/spaces/atharvat80/Wikipedia2Vec-NED/src/__init__.py
deleted file mode 100644
index d2b73b2f50e67a679fadda3a7e6b9a38381f6bdf..0000000000000000000000000000000000000000
--- a/spaces/atharvat80/Wikipedia2Vec-NED/src/__init__.py
+++ /dev/null
@@ -1,278 +0,0 @@
-# ---------------------------------------------------------------------------
-#  IMPORTS
-# ---------------------------------------------------------------------------
-import os
-import pickle
-
-import nltk
-import numpy as np
-import requests
-from nltk import edit_distance, pos_tag
-from nltk.tokenize import word_tokenize
-from wikipedia2vec import Wikipedia2Vec
-
-from src.stopwords import STOP_WORDS
-
-# ---------------------------------------------------------------------------
-#  SETUP AND HELPER FUNCTIONS
-# ---------------------------------------------------------------------------
-nltk.download('averaged_perceptron_tagger')
-nltk.download('punkt')
-
-DATADIR = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'data')
-with open(os.path.join(DATADIR, 'entity_anchors.bin'), 'rb') as f:
-    prior_prob = pickle.load(f)
-with open(os.path.join(DATADIR, 'entity_prior.bin'), 'rb') as f:
-    entity_prior = pickle.load(f)
-
-
-def get_edit_dist(x, y):
-    return edit_distance(x, y)
-
-
-def get_entity_prior(entity):
-    try:
-        return entity_prior[entity.replace('_', ' ')]
-    except:
-        return 0
-
-
-def get_prior_prob(entity, mention):
-    try:
-        entity = entity.replace('_', ' ')
-        mention = mention.lower()
-        return prior_prob[mention][entity] / sum(prior_prob[mention].values())
-    except:
-        return 0
-
-
-def get_max_prior_prob(mentions, candidates):
-    max_prob = {i: max([get_prior_prob(i, j) for j in mentions])
-                for i in candidates}
-    return max_prob
-
-
-def cosine_similarity(v1, v2):
-    v1v2 = np.linalg.norm(v1) * np.linalg.norm(v2)
-    if v1v2 == 0:
-        return 0
-    else:
-        return np.dot(v2, v1) / v1v2
-
-
-def is_disamb_page(title):
-    service_url = "https://en.wikipedia.org/w/api.php"
-    params = {
-        "action": "query",
-        "prop": "pageprops",
-        "ppprop" : "disambiguation",
-        "redirects":'',
-        "format": "json",
-        "titles": title
-    }
-    results = requests.get(service_url, params=params).json()
-    return 'disambiguation' in str(results)
-
-
-def wikidata_search(query, limit=3):
-    service_url = 'https://www.wikidata.org/w/api.php'
-    params1 = {
-        "action": "wbsearchentities",
-        "search": query,
-        "language": "en",
-        "limit": limit,
-        "format": "json"
-    }
-
-    params2 = {
-        "action": "wbgetentities",
-        "language": "en",
-        "props": "sitelinks",
-        "sitefilter": "enwiki",
-        "format": "json"
-    }
-
-    results = requests.get(service_url, params=params1).json()
-    entities = [i['id'] for i in results['search']]
-
-    params2['ids'] = '|'.join(entities)
-    results = requests.get(service_url, params=params2).json()
-    candidates = []
-    for i in entities:
-        try:
-            candidates.append(results['entities'][i]['sitelinks']['enwiki']['title'].replace(' ', '_'))
-        except:
-            pass
-    return [i for i in candidates if is_disamb_page(i) == False]
-
-
-def wikipedia_search(query, limit=3):
-    service_url = 'https://en.wikipedia.org/w/api.php'
-    params = {
-        'action': 'opensearch',
-        'search': query,
-        'namespace': 0,
-        'limit': limit,
-        'redirects': 'resolve',
-    }
-
-    results = requests.get(service_url, params=params).json()[1]
-    results = [i.replace(' ', '_') for i in results if 'disambiguation' not in i.lower()]
-    return [i for i in results if is_disamb_page(i) == False]
-
-
-def google_search(query, limit=10):
-    service_url = "https://www.googleapis.com/customsearch/v1/siterestrict"
-    params = {
-        'q': query,
-        'num': limit,
-        'start': 0,
-        'key': os.environ.get('APIKEY'),
-        'cx': os.environ.get('CESCX')
-    }
-    res = requests.get(service_url, params=params)
-    try:
-        cands = [i['title'].replace(' - Wikipedia', '') for i in res.json()["items"]]
-        return [i.replace(' ', '_') for i in cands if is_disamb_page(i) == False]
-    except:
-        return []
-
-
-
-def get_entity_extract(entity_title, num_sentences=0):
-    service_url = 'https://en.wikipedia.org/w/api.php'
-    params = {
-        'action': 'query',
-        'titles': entity_title,
-        'prop': 'extracts',
-        'redirects': 1,
-        'format': 'json',
-        'explaintext': 1,
-        'exsectionformat': 'plain'
-    }
-
-    if num_sentences != 0:
-        params['exsentences'] = num_sentences
-
-    res = requests.get(service_url, params=params)
-    try:
-        res = res.json()['query']['pages']
-        res = res[list(res.keys())[0]]
-        extract = res['extract'] if 'extract' in res.keys() else ''
-        return extract
-    except:
-        return ''
-
-
-# ---------------------------------------------------------------------------
-#  NED SYSTEMS
-# ---------------------------------------------------------------------------
-
-### Base Model ###
-
-
-class Base:
-    def __init__(self):
-        self.emb = Wikipedia2Vec.load(os.path.join(DATADIR, 'wiki2vec_w10_100d.bin'))
-        self.stop_words = STOP_WORDS
-        self.tokenizer = word_tokenize
-        self.nouns_only = True
-        self.vector_size = self.emb.train_params['dim_size']
-
-    def get_nouns(self, tokens):
-        nouns = []
-        for word, pos in pos_tag(tokens):
-            if (pos == 'NN' or pos == 'NNP' or pos == 'NNS' or pos == 'NNPS'):
-                nouns.extend(word.split(' '))
-        return list(set(nouns))
-
-    def filter(self, tokens):
-        tokens = list(set(tokens))
-        tokens = [w for w in tokens if not(w.lower() in self.stop_words)]
-        tokens = [w for w in tokens if w.isalnum()]
-        return self.get_nouns(tokens) if self.nouns_only else tokens
-
-    def encode_entity(self, entity):
-        entity = entity.replace('_', ' ')
-        if self.emb.get_entity(entity) is not None:
-            return self.emb.get_entity_vector(entity)
-        else:
-            return self.encode_sentence(get_entity_extract(entity, num_sentences=10))
-
-    def encode_sentence(self, s):
-        words = self.filter(self.tokenizer(s.lower()))
-        emb, n = np.zeros(self.vector_size), 1
-        for w in words:
-            try:
-                emb += self.emb.get_word_vector(w)
-                n += 1
-            except KeyError:
-                pass
-
-        return emb/n
-
-
-### Advance Model ###
-class GBRT(Base):
-    def __init__(self):
-        super().__init__()
-        with open(os.path.join(DATADIR, 'model.bin'), 'rb') as f:
-            self.model = pickle.load(f)
-
-    def encode_context_entities(self, context_entities):
-        emb, n = np.zeros(self.vector_size), 1
-        for i in context_entities:
-            emb += self.encode_entity(i)
-            n += 1
-        return emb/n
-
-    def link(self, mentions_cands, context):
-        # Calculate max prior probability of all candidates.
-        mentions = set([i for i, _ in mentions_cands])
-        candidates = set([i for _, j in mentions_cands for i in j])
-        max_prob = get_max_prior_prob(mentions, candidates)
-
-        # Find unambiguous entities
-        unamb_entities = [x for i, j in mentions_cands for x in j if get_prior_prob(x, i) > 0.95]
-        context_ent_emb = self.encode_context_entities(unamb_entities)
-
-        # Make predictions
-        context_emb = self.encode_sentence(context)
-        predictions = []
-        for mention, candidates in mentions_cands:
-            # Generate feature values
-            num_cands = len(candidates)
-            X = []
-            for candidate in candidates:
-                cand = candidate.replace('_', ' ').lower()
-                ment = mention.lower()
-                cand_emb = self.encode_entity(candidate)
-
-                X.append([
-                    candidate,
-                    get_prior_prob(candidate, mention),
-                    get_entity_prior(candidate),
-                    max_prob[candidate],
-                    num_cands,
-                    get_edit_dist(ment, cand),
-                    int(ment == cand),
-                    int(ment in cand),
-                    int(cand.startswith(cand) or cand.endswith(ment)),
-                    cosine_similarity(cand_emb, context_emb),
-                    cosine_similarity(cand_emb, context_ent_emb)
-                ])
-
-            # Add rank
-            X.sort(key=lambda x: x[-1] + x[-2], reverse=True)
-            X = [j + [i + 1] for i, j in enumerate(X)]
-
-            # Predict
-            pred, conf = 'NIL', 0.2
-            for i in X:
-                c = self.model.predict(np.array([i[1:]]))[0]
-                if c > conf:
-                    pred = i[0]
-                    conf = c
-            predictions.append([mention, pred, conf])
-
-        return predictions
diff --git a/spaces/awaawawawa/iurf7irfuyytruyyugb/ldmlib/modules/image_degradation/utils_image.py b/spaces/awaawawawa/iurf7irfuyytruyyugb/ldmlib/modules/image_degradation/utils_image.py
deleted file mode 100644
index 0175f155ad900ae33c3c46ed87f49b352e3faf98..0000000000000000000000000000000000000000
--- a/spaces/awaawawawa/iurf7irfuyytruyyugb/ldmlib/modules/image_degradation/utils_image.py
+++ /dev/null
@@ -1,916 +0,0 @@
-import os
-import math
-import random
-import numpy as np
-import torch
-import cv2
-from torchvision.utils import make_grid
-from datetime import datetime
-#import matplotlib.pyplot as plt   # TODO: check with Dominik, also bsrgan.py vs bsrgan_light.py
-
-
-os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE"
-
-
-'''
-# --------------------------------------------
-# Kai Zhang (github: https://github.com/cszn)
-# 03/Mar/2019
-# --------------------------------------------
-# https://github.com/twhui/SRGAN-pyTorch
-# https://github.com/xinntao/BasicSR
-# --------------------------------------------
-'''
-
-
-IMG_EXTENSIONS = ['.jpg', '.JPG', '.jpeg', '.JPEG', '.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP', '.tif']
-
-
-def is_image_file(filename):
-    return any(filename.endswith(extension) for extension in IMG_EXTENSIONS)
-
-
-def get_timestamp():
-    return datetime.now().strftime('%y%m%d-%H%M%S')
-
-
-def imshow(x, title=None, cbar=False, figsize=None):
-    plt.figure(figsize=figsize)
-    plt.imshow(np.squeeze(x), interpolation='nearest', cmap='gray')
-    if title:
-        plt.title(title)
-    if cbar:
-        plt.colorbar()
-    plt.show()
-
-
-def surf(Z, cmap='rainbow', figsize=None):
-    plt.figure(figsize=figsize)
-    ax3 = plt.axes(projection='3d')
-
-    w, h = Z.shape[:2]
-    xx = np.arange(0,w,1)
-    yy = np.arange(0,h,1)
-    X, Y = np.meshgrid(xx, yy)
-    ax3.plot_surface(X,Y,Z,cmap=cmap)
-    #ax3.contour(X,Y,Z, zdim='z',offset=-2，cmap=cmap)
-    plt.show()
-
-
-'''
-# --------------------------------------------
-# get image pathes
-# --------------------------------------------
-'''
-
-
-def get_image_paths(dataroot):
-    paths = None  # return None if dataroot is None
-    if dataroot is not None:
-        paths = sorted(_get_paths_from_images(dataroot))
-    return paths
-
-
-def _get_paths_from_images(path):
-    assert os.path.isdir(path), '{:s} is not a valid directory'.format(path)
-    images = []
-    for dirpath, _, fnames in sorted(os.walk(path)):
-        for fname in sorted(fnames):
-            if is_image_file(fname):
-                img_path = os.path.join(dirpath, fname)
-                images.append(img_path)
-    assert images, '{:s} has no valid image file'.format(path)
-    return images
-
-
-'''
-# --------------------------------------------
-# split large images into small images 
-# --------------------------------------------
-'''
-
-
-def patches_from_image(img, p_size=512, p_overlap=64, p_max=800):
-    w, h = img.shape[:2]
-    patches = []
-    if w > p_max and h > p_max:
-        w1 = list(np.arange(0, w-p_size, p_size-p_overlap, dtype=np.int))
-        h1 = list(np.arange(0, h-p_size, p_size-p_overlap, dtype=np.int))
-        w1.append(w-p_size)
-        h1.append(h-p_size)
-#        print(w1)
-#        print(h1)
-        for i in w1:
-            for j in h1:
-                patches.append(img[i:i+p_size, j:j+p_size,:])
-    else:
-        patches.append(img)
-
-    return patches
-
-
-def imssave(imgs, img_path):
-    """
-    imgs: list, N images of size WxHxC
-    """
-    img_name, ext = os.path.splitext(os.path.basename(img_path))
-
-    for i, img in enumerate(imgs):
-        if img.ndim == 3:
-            img = img[:, :, [2, 1, 0]]
-        new_path = os.path.join(os.path.dirname(img_path), img_name+str('_s{:04d}'.format(i))+'.png')
-        cv2.imwrite(new_path, img)
-
-
-def split_imageset(original_dataroot, taget_dataroot, n_channels=3, p_size=800, p_overlap=96, p_max=1000):
-    """
-    split the large images from original_dataroot into small overlapped images with size (p_size)x(p_size),
-    and save them into taget_dataroot; only the images with larger size than (p_max)x(p_max)
-    will be splitted.
-    Args:
-        original_dataroot:
-        taget_dataroot:
-        p_size: size of small images
-        p_overlap: patch size in training is a good choice
-        p_max: images with smaller size than (p_max)x(p_max) keep unchanged.
-    """
-    paths = get_image_paths(original_dataroot)
-    for img_path in paths:
-        # img_name, ext = os.path.splitext(os.path.basename(img_path))
-        img = imread_uint(img_path, n_channels=n_channels)
-        patches = patches_from_image(img, p_size, p_overlap, p_max)
-        imssave(patches, os.path.join(taget_dataroot,os.path.basename(img_path)))
-        #if original_dataroot == taget_dataroot:
-        #del img_path
-
-'''
-# --------------------------------------------
-# makedir
-# --------------------------------------------
-'''
-
-
-def mkdir(path):
-    if not os.path.exists(path):
-        os.makedirs(path)
-
-
-def mkdirs(paths):
-    if isinstance(paths, str):
-        mkdir(paths)
-    else:
-        for path in paths:
-            mkdir(path)
-
-
-def mkdir_and_rename(path):
-    if os.path.exists(path):
-        new_name = path + '_archived_' + get_timestamp()
-        print('Path already exists. Rename it to [{:s}]'.format(new_name))
-        os.rename(path, new_name)
-    os.makedirs(path)
-
-
-'''
-# --------------------------------------------
-# read image from path
-# opencv is fast, but read BGR numpy image
-# --------------------------------------------
-'''
-
-
-# --------------------------------------------
-# get uint8 image of size HxWxn_channles (RGB)
-# --------------------------------------------
-def imread_uint(path, n_channels=3):
-    #  input: path
-    # output: HxWx3(RGB or GGG), or HxWx1 (G)
-    if n_channels == 1:
-        img = cv2.imread(path, 0)  # cv2.IMREAD_GRAYSCALE
-        img = np.expand_dims(img, axis=2)  # HxWx1
-    elif n_channels == 3:
-        img = cv2.imread(path, cv2.IMREAD_UNCHANGED)  # BGR or G
-        if img.ndim == 2:
-            img = cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)  # GGG
-        else:
-            img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)  # RGB
-    return img
-
-
-# --------------------------------------------
-# matlab's imwrite
-# --------------------------------------------
-def imsave(img, img_path):
-    img = np.squeeze(img)
-    if img.ndim == 3:
-        img = img[:, :, [2, 1, 0]]
-    cv2.imwrite(img_path, img)
-
-def imwrite(img, img_path):
-    img = np.squeeze(img)
-    if img.ndim == 3:
-        img = img[:, :, [2, 1, 0]]
-    cv2.imwrite(img_path, img)
-
-
-
-# --------------------------------------------
-# get single image of size HxWxn_channles (BGR)
-# --------------------------------------------
-def read_img(path):
-    # read image by cv2
-    # return: Numpy float32, HWC, BGR, [0,1]
-    img = cv2.imread(path, cv2.IMREAD_UNCHANGED)  # cv2.IMREAD_GRAYSCALE
-    img = img.astype(np.float32) / 255.
-    if img.ndim == 2:
-        img = np.expand_dims(img, axis=2)
-    # some images have 4 channels
-    if img.shape[2] > 3:
-        img = img[:, :, :3]
-    return img
-
-
-'''
-# --------------------------------------------
-# image format conversion
-# --------------------------------------------
-# numpy(single) <--->  numpy(unit)
-# numpy(single) <--->  tensor
-# numpy(unit)   <--->  tensor
-# --------------------------------------------
-'''
-
-
-# --------------------------------------------
-# numpy(single) [0, 1] <--->  numpy(unit)
-# --------------------------------------------
-
-
-def uint2single(img):
-
-    return np.float32(img/255.)
-
-
-def single2uint(img):
-
-    return np.uint8((img.clip(0, 1)*255.).round())
-
-
-def uint162single(img):
-
-    return np.float32(img/65535.)
-
-
-def single2uint16(img):
-
-    return np.uint16((img.clip(0, 1)*65535.).round())
-
-
-# --------------------------------------------
-# numpy(unit) (HxWxC or HxW) <--->  tensor
-# --------------------------------------------
-
-
-# convert uint to 4-dimensional torch tensor
-def uint2tensor4(img):
-    if img.ndim == 2:
-        img = np.expand_dims(img, axis=2)
-    return torch.from_numpy(np.ascontiguousarray(img)).permute(2, 0, 1).float().div(255.).unsqueeze(0)
-
-
-# convert uint to 3-dimensional torch tensor
-def uint2tensor3(img):
-    if img.ndim == 2:
-        img = np.expand_dims(img, axis=2)
-    return torch.from_numpy(np.ascontiguousarray(img)).permute(2, 0, 1).float().div(255.)
-
-
-# convert 2/3/4-dimensional torch tensor to uint
-def tensor2uint(img):
-    img = img.data.squeeze().float().clamp_(0, 1).cpu().numpy()
-    if img.ndim == 3:
-        img = np.transpose(img, (1, 2, 0))
-    return np.uint8((img*255.0).round())
-
-
-# --------------------------------------------
-# numpy(single) (HxWxC) <--->  tensor
-# --------------------------------------------
-
-
-# convert single (HxWxC) to 3-dimensional torch tensor
-def single2tensor3(img):
-    return torch.from_numpy(np.ascontiguousarray(img)).permute(2, 0, 1).float()
-
-
-# convert single (HxWxC) to 4-dimensional torch tensor
-def single2tensor4(img):
-    return torch.from_numpy(np.ascontiguousarray(img)).permute(2, 0, 1).float().unsqueeze(0)
-
-
-# convert torch tensor to single
-def tensor2single(img):
-    img = img.data.squeeze().float().cpu().numpy()
-    if img.ndim == 3:
-        img = np.transpose(img, (1, 2, 0))
-
-    return img
-
-# convert torch tensor to single
-def tensor2single3(img):
-    img = img.data.squeeze().float().cpu().numpy()
-    if img.ndim == 3:
-        img = np.transpose(img, (1, 2, 0))
-    elif img.ndim == 2:
-        img = np.expand_dims(img, axis=2)
-    return img
-
-
-def single2tensor5(img):
-    return torch.from_numpy(np.ascontiguousarray(img)).permute(2, 0, 1, 3).float().unsqueeze(0)
-
-
-def single32tensor5(img):
-    return torch.from_numpy(np.ascontiguousarray(img)).float().unsqueeze(0).unsqueeze(0)
-
-
-def single42tensor4(img):
-    return torch.from_numpy(np.ascontiguousarray(img)).permute(2, 0, 1, 3).float()
-
-
-# from skimage.io import imread, imsave
-def tensor2img(tensor, out_type=np.uint8, min_max=(0, 1)):
-    '''
-    Converts a torch Tensor into an image Numpy array of BGR channel order
-    Input: 4D(B,(3/1),H,W), 3D(C,H,W), or 2D(H,W), any range, RGB channel order
-    Output: 3D(H,W,C) or 2D(H,W), [0,255], np.uint8 (default)
-    '''
-    tensor = tensor.squeeze().float().cpu().clamp_(*min_max)  # squeeze first, then clamp
-    tensor = (tensor - min_max[0]) / (min_max[1] - min_max[0])  # to range [0,1]
-    n_dim = tensor.dim()
-    if n_dim == 4:
-        n_img = len(tensor)
-        img_np = make_grid(tensor, nrow=int(math.sqrt(n_img)), normalize=False).numpy()
-        img_np = np.transpose(img_np[[2, 1, 0], :, :], (1, 2, 0))  # HWC, BGR
-    elif n_dim == 3:
-        img_np = tensor.numpy()
-        img_np = np.transpose(img_np[[2, 1, 0], :, :], (1, 2, 0))  # HWC, BGR
-    elif n_dim == 2:
-        img_np = tensor.numpy()
-    else:
-        raise TypeError(
-            'Only support 4D, 3D and 2D tensor. But received with dimension: {:d}'.format(n_dim))
-    if out_type == np.uint8:
-        img_np = (img_np * 255.0).round()
-        # Important. Unlike matlab, numpy.unit8() WILL NOT round by default.
-    return img_np.astype(out_type)
-
-
-'''
-# --------------------------------------------
-# Augmentation, flipe and/or rotate
-# --------------------------------------------
-# The following two are enough.
-# (1) augmet_img: numpy image of WxHxC or WxH
-# (2) augment_img_tensor4: tensor image 1xCxWxH
-# --------------------------------------------
-'''
-
-
-def augment_img(img, mode=0):
-    '''Kai Zhang (github: https://github.com/cszn)
-    '''
-    if mode == 0:
-        return img
-    elif mode == 1:
-        return np.flipud(np.rot90(img))
-    elif mode == 2:
-        return np.flipud(img)
-    elif mode == 3:
-        return np.rot90(img, k=3)
-    elif mode == 4:
-        return np.flipud(np.rot90(img, k=2))
-    elif mode == 5:
-        return np.rot90(img)
-    elif mode == 6:
-        return np.rot90(img, k=2)
-    elif mode == 7:
-        return np.flipud(np.rot90(img, k=3))
-
-
-def augment_img_tensor4(img, mode=0):
-    '''Kai Zhang (github: https://github.com/cszn)
-    '''
-    if mode == 0:
-        return img
-    elif mode == 1:
-        return img.rot90(1, [2, 3]).flip([2])
-    elif mode == 2:
-        return img.flip([2])
-    elif mode == 3:
-        return img.rot90(3, [2, 3])
-    elif mode == 4:
-        return img.rot90(2, [2, 3]).flip([2])
-    elif mode == 5:
-        return img.rot90(1, [2, 3])
-    elif mode == 6:
-        return img.rot90(2, [2, 3])
-    elif mode == 7:
-        return img.rot90(3, [2, 3]).flip([2])
-
-
-def augment_img_tensor(img, mode=0):
-    '''Kai Zhang (github: https://github.com/cszn)
-    '''
-    img_size = img.size()
-    img_np = img.data.cpu().numpy()
-    if len(img_size) == 3:
-        img_np = np.transpose(img_np, (1, 2, 0))
-    elif len(img_size) == 4:
-        img_np = np.transpose(img_np, (2, 3, 1, 0))
-    img_np = augment_img(img_np, mode=mode)
-    img_tensor = torch.from_numpy(np.ascontiguousarray(img_np))
-    if len(img_size) == 3:
-        img_tensor = img_tensor.permute(2, 0, 1)
-    elif len(img_size) == 4:
-        img_tensor = img_tensor.permute(3, 2, 0, 1)
-
-    return img_tensor.type_as(img)
-
-
-def augment_img_np3(img, mode=0):
-    if mode == 0:
-        return img
-    elif mode == 1:
-        return img.transpose(1, 0, 2)
-    elif mode == 2:
-        return img[::-1, :, :]
-    elif mode == 3:
-        img = img[::-1, :, :]
-        img = img.transpose(1, 0, 2)
-        return img
-    elif mode == 4:
-        return img[:, ::-1, :]
-    elif mode == 5:
-        img = img[:, ::-1, :]
-        img = img.transpose(1, 0, 2)
-        return img
-    elif mode == 6:
-        img = img[:, ::-1, :]
-        img = img[::-1, :, :]
-        return img
-    elif mode == 7:
-        img = img[:, ::-1, :]
-        img = img[::-1, :, :]
-        img = img.transpose(1, 0, 2)
-        return img
-
-
-def augment_imgs(img_list, hflip=True, rot=True):
-    # horizontal flip OR rotate
-    hflip = hflip and random.random() < 0.5
-    vflip = rot and random.random() < 0.5
-    rot90 = rot and random.random() < 0.5
-
-    def _augment(img):
-        if hflip:
-            img = img[:, ::-1, :]
-        if vflip:
-            img = img[::-1, :, :]
-        if rot90:
-            img = img.transpose(1, 0, 2)
-        return img
-
-    return [_augment(img) for img in img_list]
-
-
-'''
-# --------------------------------------------
-# modcrop and shave
-# --------------------------------------------
-'''
-
-
-def modcrop(img_in, scale):
-    # img_in: Numpy, HWC or HW
-    img = np.copy(img_in)
-    if img.ndim == 2:
-        H, W = img.shape
-        H_r, W_r = H % scale, W % scale
-        img = img[:H - H_r, :W - W_r]
-    elif img.ndim == 3:
-        H, W, C = img.shape
-        H_r, W_r = H % scale, W % scale
-        img = img[:H - H_r, :W - W_r, :]
-    else:
-        raise ValueError('Wrong img ndim: [{:d}].'.format(img.ndim))
-    return img
-
-
-def shave(img_in, border=0):
-    # img_in: Numpy, HWC or HW
-    img = np.copy(img_in)
-    h, w = img.shape[:2]
-    img = img[border:h-border, border:w-border]
-    return img
-
-
-'''
-# --------------------------------------------
-# image processing process on numpy image
-# channel_convert(in_c, tar_type, img_list):
-# rgb2ycbcr(img, only_y=True):
-# bgr2ycbcr(img, only_y=True):
-# ycbcr2rgb(img):
-# --------------------------------------------
-'''
-
-
-def rgb2ycbcr(img, only_y=True):
-    '''same as matlab rgb2ycbcr
-    only_y: only return Y channel
-    Input:
-        uint8, [0, 255]
-        float, [0, 1]
-    '''
-    in_img_type = img.dtype
-    img.astype(np.float32)
-    if in_img_type != np.uint8:
-        img *= 255.
-    # convert
-    if only_y:
-        rlt = np.dot(img, [65.481, 128.553, 24.966]) / 255.0 + 16.0
-    else:
-        rlt = np.matmul(img, [[65.481, -37.797, 112.0], [128.553, -74.203, -93.786],
-                              [24.966, 112.0, -18.214]]) / 255.0 + [16, 128, 128]
-    if in_img_type == np.uint8:
-        rlt = rlt.round()
-    else:
-        rlt /= 255.
-    return rlt.astype(in_img_type)
-
-
-def ycbcr2rgb(img):
-    '''same as matlab ycbcr2rgb
-    Input:
-        uint8, [0, 255]
-        float, [0, 1]
-    '''
-    in_img_type = img.dtype
-    img.astype(np.float32)
-    if in_img_type != np.uint8:
-        img *= 255.
-    # convert
-    rlt = np.matmul(img, [[0.00456621, 0.00456621, 0.00456621], [0, -0.00153632, 0.00791071],
-                          [0.00625893, -0.00318811, 0]]) * 255.0 + [-222.921, 135.576, -276.836]
-    if in_img_type == np.uint8:
-        rlt = rlt.round()
-    else:
-        rlt /= 255.
-    return rlt.astype(in_img_type)
-
-
-def bgr2ycbcr(img, only_y=True):
-    '''bgr version of rgb2ycbcr
-    only_y: only return Y channel
-    Input:
-        uint8, [0, 255]
-        float, [0, 1]
-    '''
-    in_img_type = img.dtype
-    img.astype(np.float32)
-    if in_img_type != np.uint8:
-        img *= 255.
-    # convert
-    if only_y:
-        rlt = np.dot(img, [24.966, 128.553, 65.481]) / 255.0 + 16.0
-    else:
-        rlt = np.matmul(img, [[24.966, 112.0, -18.214], [128.553, -74.203, -93.786],
-                              [65.481, -37.797, 112.0]]) / 255.0 + [16, 128, 128]
-    if in_img_type == np.uint8:
-        rlt = rlt.round()
-    else:
-        rlt /= 255.
-    return rlt.astype(in_img_type)
-
-
-def channel_convert(in_c, tar_type, img_list):
-    # conversion among BGR, gray and y
-    if in_c == 3 and tar_type == 'gray':  # BGR to gray
-        gray_list = [cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) for img in img_list]
-        return [np.expand_dims(img, axis=2) for img in gray_list]
-    elif in_c == 3 and tar_type == 'y':  # BGR to y
-        y_list = [bgr2ycbcr(img, only_y=True) for img in img_list]
-        return [np.expand_dims(img, axis=2) for img in y_list]
-    elif in_c == 1 and tar_type == 'RGB':  # gray/y to BGR
-        return [cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) for img in img_list]
-    else:
-        return img_list
-
-
-'''
-# --------------------------------------------
-# metric, PSNR and SSIM
-# --------------------------------------------
-'''
-
-
-# --------------------------------------------
-# PSNR
-# --------------------------------------------
-def calculate_psnr(img1, img2, border=0):
-    # img1 and img2 have range [0, 255]
-    #img1 = img1.squeeze()
-    #img2 = img2.squeeze()
-    if not img1.shape == img2.shape:
-        raise ValueError('Input images must have the same dimensions.')
-    h, w = img1.shape[:2]
-    img1 = img1[border:h-border, border:w-border]
-    img2 = img2[border:h-border, border:w-border]
-
-    img1 = img1.astype(np.float64)
-    img2 = img2.astype(np.float64)
-    mse = np.mean((img1 - img2)**2)
-    if mse == 0:
-        return float('inf')
-    return 20 * math.log10(255.0 / math.sqrt(mse))
-
-
-# --------------------------------------------
-# SSIM
-# --------------------------------------------
-def calculate_ssim(img1, img2, border=0):
-    '''calculate SSIM
-    the same outputs as MATLAB's
-    img1, img2: [0, 255]
-    '''
-    #img1 = img1.squeeze()
-    #img2 = img2.squeeze()
-    if not img1.shape == img2.shape:
-        raise ValueError('Input images must have the same dimensions.')
-    h, w = img1.shape[:2]
-    img1 = img1[border:h-border, border:w-border]
-    img2 = img2[border:h-border, border:w-border]
-
-    if img1.ndim == 2:
-        return ssim(img1, img2)
-    elif img1.ndim == 3:
-        if img1.shape[2] == 3:
-            ssims = []
-            for i in range(3):
-                ssims.append(ssim(img1[:,:,i], img2[:,:,i]))
-            return np.array(ssims).mean()
-        elif img1.shape[2] == 1:
-            return ssim(np.squeeze(img1), np.squeeze(img2))
-    else:
-        raise ValueError('Wrong input image dimensions.')
-
-
-def ssim(img1, img2):
-    C1 = (0.01 * 255)**2
-    C2 = (0.03 * 255)**2
-
-    img1 = img1.astype(np.float64)
-    img2 = img2.astype(np.float64)
-    kernel = cv2.getGaussianKernel(11, 1.5)
-    window = np.outer(kernel, kernel.transpose())
-
-    mu1 = cv2.filter2D(img1, -1, window)[5:-5, 5:-5]  # valid
-    mu2 = cv2.filter2D(img2, -1, window)[5:-5, 5:-5]
-    mu1_sq = mu1**2
-    mu2_sq = mu2**2
-    mu1_mu2 = mu1 * mu2
-    sigma1_sq = cv2.filter2D(img1**2, -1, window)[5:-5, 5:-5] - mu1_sq
-    sigma2_sq = cv2.filter2D(img2**2, -1, window)[5:-5, 5:-5] - mu2_sq
-    sigma12 = cv2.filter2D(img1 * img2, -1, window)[5:-5, 5:-5] - mu1_mu2
-
-    ssim_map = ((2 * mu1_mu2 + C1) * (2 * sigma12 + C2)) / ((mu1_sq + mu2_sq + C1) *
-                                                            (sigma1_sq + sigma2_sq + C2))
-    return ssim_map.mean()
-
-
-'''
-# --------------------------------------------
-# matlab's bicubic imresize (numpy and torch) [0, 1]
-# --------------------------------------------
-'''
-
-
-# matlab 'imresize' function, now only support 'bicubic'
-def cubic(x):
-    absx = torch.abs(x)
-    absx2 = absx**2
-    absx3 = absx**3
-    return (1.5*absx3 - 2.5*absx2 + 1) * ((absx <= 1).type_as(absx)) + \
-        (-0.5*absx3 + 2.5*absx2 - 4*absx + 2) * (((absx > 1)*(absx <= 2)).type_as(absx))
-
-
-def calculate_weights_indices(in_length, out_length, scale, kernel, kernel_width, antialiasing):
-    if (scale < 1) and (antialiasing):
-        # Use a modified kernel to simultaneously interpolate and antialias- larger kernel width
-        kernel_width = kernel_width / scale
-
-    # Output-space coordinates
-    x = torch.linspace(1, out_length, out_length)
-
-    # Input-space coordinates. Calculate the inverse mapping such that 0.5
-    # in output space maps to 0.5 in input space, and 0.5+scale in output
-    # space maps to 1.5 in input space.
-    u = x / scale + 0.5 * (1 - 1 / scale)
-
-    # What is the left-most pixel that can be involved in the computation?
-    left = torch.floor(u - kernel_width / 2)
-
-    # What is the maximum number of pixels that can be involved in the
-    # computation?  Note: it's OK to use an extra pixel here; if the
-    # corresponding weights are all zero, it will be eliminated at the end
-    # of this function.
-    P = math.ceil(kernel_width) + 2
-
-    # The indices of the input pixels involved in computing the k-th output
-    # pixel are in row k of the indices matrix.
-    indices = left.view(out_length, 1).expand(out_length, P) + torch.linspace(0, P - 1, P).view(
-        1, P).expand(out_length, P)
-
-    # The weights used to compute the k-th output pixel are in row k of the
-    # weights matrix.
-    distance_to_center = u.view(out_length, 1).expand(out_length, P) - indices
-    # apply cubic kernel
-    if (scale < 1) and (antialiasing):
-        weights = scale * cubic(distance_to_center * scale)
-    else:
-        weights = cubic(distance_to_center)
-    # Normalize the weights matrix so that each row sums to 1.
-    weights_sum = torch.sum(weights, 1).view(out_length, 1)
-    weights = weights / weights_sum.expand(out_length, P)
-
-    # If a column in weights is all zero, get rid of it. only consider the first and last column.
-    weights_zero_tmp = torch.sum((weights == 0), 0)
-    if not math.isclose(weights_zero_tmp[0], 0, rel_tol=1e-6):
-        indices = indices.narrow(1, 1, P - 2)
-        weights = weights.narrow(1, 1, P - 2)
-    if not math.isclose(weights_zero_tmp[-1], 0, rel_tol=1e-6):
-        indices = indices.narrow(1, 0, P - 2)
-        weights = weights.narrow(1, 0, P - 2)
-    weights = weights.contiguous()
-    indices = indices.contiguous()
-    sym_len_s = -indices.min() + 1
-    sym_len_e = indices.max() - in_length
-    indices = indices + sym_len_s - 1
-    return weights, indices, int(sym_len_s), int(sym_len_e)
-
-
-# --------------------------------------------
-# imresize for tensor image [0, 1]
-# --------------------------------------------
-def imresize(img, scale, antialiasing=True):
-    # Now the scale should be the same for H and W
-    # input: img: pytorch tensor, CHW or HW [0,1]
-    # output: CHW or HW [0,1] w/o round
-    need_squeeze = True if img.dim() == 2 else False
-    if need_squeeze:
-        img.unsqueeze_(0)
-    in_C, in_H, in_W = img.size()
-    out_C, out_H, out_W = in_C, math.ceil(in_H * scale), math.ceil(in_W * scale)
-    kernel_width = 4
-    kernel = 'cubic'
-
-    # Return the desired dimension order for performing the resize.  The
-    # strategy is to perform the resize first along the dimension with the
-    # smallest scale factor.
-    # Now we do not support this.
-
-    # get weights and indices
-    weights_H, indices_H, sym_len_Hs, sym_len_He = calculate_weights_indices(
-        in_H, out_H, scale, kernel, kernel_width, antialiasing)
-    weights_W, indices_W, sym_len_Ws, sym_len_We = calculate_weights_indices(
-        in_W, out_W, scale, kernel, kernel_width, antialiasing)
-    # process H dimension
-    # symmetric copying
-    img_aug = torch.FloatTensor(in_C, in_H + sym_len_Hs + sym_len_He, in_W)
-    img_aug.narrow(1, sym_len_Hs, in_H).copy_(img)
-
-    sym_patch = img[:, :sym_len_Hs, :]
-    inv_idx = torch.arange(sym_patch.size(1) - 1, -1, -1).long()
-    sym_patch_inv = sym_patch.index_select(1, inv_idx)
-    img_aug.narrow(1, 0, sym_len_Hs).copy_(sym_patch_inv)
-
-    sym_patch = img[:, -sym_len_He:, :]
-    inv_idx = torch.arange(sym_patch.size(1) - 1, -1, -1).long()
-    sym_patch_inv = sym_patch.index_select(1, inv_idx)
-    img_aug.narrow(1, sym_len_Hs + in_H, sym_len_He).copy_(sym_patch_inv)
-
-    out_1 = torch.FloatTensor(in_C, out_H, in_W)
-    kernel_width = weights_H.size(1)
-    for i in range(out_H):
-        idx = int(indices_H[i][0])
-        for j in range(out_C):
-            out_1[j, i, :] = img_aug[j, idx:idx + kernel_width, :].transpose(0, 1).mv(weights_H[i])
-
-    # process W dimension
-    # symmetric copying
-    out_1_aug = torch.FloatTensor(in_C, out_H, in_W + sym_len_Ws + sym_len_We)
-    out_1_aug.narrow(2, sym_len_Ws, in_W).copy_(out_1)
-
-    sym_patch = out_1[:, :, :sym_len_Ws]
-    inv_idx = torch.arange(sym_patch.size(2) - 1, -1, -1).long()
-    sym_patch_inv = sym_patch.index_select(2, inv_idx)
-    out_1_aug.narrow(2, 0, sym_len_Ws).copy_(sym_patch_inv)
-
-    sym_patch = out_1[:, :, -sym_len_We:]
-    inv_idx = torch.arange(sym_patch.size(2) - 1, -1, -1).long()
-    sym_patch_inv = sym_patch.index_select(2, inv_idx)
-    out_1_aug.narrow(2, sym_len_Ws + in_W, sym_len_We).copy_(sym_patch_inv)
-
-    out_2 = torch.FloatTensor(in_C, out_H, out_W)
-    kernel_width = weights_W.size(1)
-    for i in range(out_W):
-        idx = int(indices_W[i][0])
-        for j in range(out_C):
-            out_2[j, :, i] = out_1_aug[j, :, idx:idx + kernel_width].mv(weights_W[i])
-    if need_squeeze:
-        out_2.squeeze_()
-    return out_2
-
-
-# --------------------------------------------
-# imresize for numpy image [0, 1]
-# --------------------------------------------
-def imresize_np(img, scale, antialiasing=True):
-    # Now the scale should be the same for H and W
-    # input: img: Numpy, HWC or HW [0,1]
-    # output: HWC or HW [0,1] w/o round
-    img = torch.from_numpy(img)
-    need_squeeze = True if img.dim() == 2 else False
-    if need_squeeze:
-        img.unsqueeze_(2)
-
-    in_H, in_W, in_C = img.size()
-    out_C, out_H, out_W = in_C, math.ceil(in_H * scale), math.ceil(in_W * scale)
-    kernel_width = 4
-    kernel = 'cubic'
-
-    # Return the desired dimension order for performing the resize.  The
-    # strategy is to perform the resize first along the dimension with the
-    # smallest scale factor.
-    # Now we do not support this.
-
-    # get weights and indices
-    weights_H, indices_H, sym_len_Hs, sym_len_He = calculate_weights_indices(
-        in_H, out_H, scale, kernel, kernel_width, antialiasing)
-    weights_W, indices_W, sym_len_Ws, sym_len_We = calculate_weights_indices(
-        in_W, out_W, scale, kernel, kernel_width, antialiasing)
-    # process H dimension
-    # symmetric copying
-    img_aug = torch.FloatTensor(in_H + sym_len_Hs + sym_len_He, in_W, in_C)
-    img_aug.narrow(0, sym_len_Hs, in_H).copy_(img)
-
-    sym_patch = img[:sym_len_Hs, :, :]
-    inv_idx = torch.arange(sym_patch.size(0) - 1, -1, -1).long()
-    sym_patch_inv = sym_patch.index_select(0, inv_idx)
-    img_aug.narrow(0, 0, sym_len_Hs).copy_(sym_patch_inv)
-
-    sym_patch = img[-sym_len_He:, :, :]
-    inv_idx = torch.arange(sym_patch.size(0) - 1, -1, -1).long()
-    sym_patch_inv = sym_patch.index_select(0, inv_idx)
-    img_aug.narrow(0, sym_len_Hs + in_H, sym_len_He).copy_(sym_patch_inv)
-
-    out_1 = torch.FloatTensor(out_H, in_W, in_C)
-    kernel_width = weights_H.size(1)
-    for i in range(out_H):
-        idx = int(indices_H[i][0])
-        for j in range(out_C):
-            out_1[i, :, j] = img_aug[idx:idx + kernel_width, :, j].transpose(0, 1).mv(weights_H[i])
-
-    # process W dimension
-    # symmetric copying
-    out_1_aug = torch.FloatTensor(out_H, in_W + sym_len_Ws + sym_len_We, in_C)
-    out_1_aug.narrow(1, sym_len_Ws, in_W).copy_(out_1)
-
-    sym_patch = out_1[:, :sym_len_Ws, :]
-    inv_idx = torch.arange(sym_patch.size(1) - 1, -1, -1).long()
-    sym_patch_inv = sym_patch.index_select(1, inv_idx)
-    out_1_aug.narrow(1, 0, sym_len_Ws).copy_(sym_patch_inv)
-
-    sym_patch = out_1[:, -sym_len_We:, :]
-    inv_idx = torch.arange(sym_patch.size(1) - 1, -1, -1).long()
-    sym_patch_inv = sym_patch.index_select(1, inv_idx)
-    out_1_aug.narrow(1, sym_len_Ws + in_W, sym_len_We).copy_(sym_patch_inv)
-
-    out_2 = torch.FloatTensor(out_H, out_W, in_C)
-    kernel_width = weights_W.size(1)
-    for i in range(out_W):
-        idx = int(indices_W[i][0])
-        for j in range(out_C):
-            out_2[:, i, j] = out_1_aug[:, idx:idx + kernel_width, j].mv(weights_W[i])
-    if need_squeeze:
-        out_2.squeeze_()
-
-    return out_2.numpy()
-
-
-if __name__ == '__main__':
-    print('---')
-#    img = imread_uint('test.bmp', 3)
-#    img = uint2single(img)
-#    img_bicubic = imresize_np(img, 1/4)
\ No newline at end of file
diff --git a/spaces/awacke1/CardWriterPro/test_markdown_out.py b/spaces/awacke1/CardWriterPro/test_markdown_out.py
deleted file mode 100644
index bf8ea000b3c912781f3f5620c25ec4f2233c4a6e..0000000000000000000000000000000000000000
--- a/spaces/awacke1/CardWriterPro/test_markdown_out.py
+++ /dev/null
@@ -1,30 +0,0 @@
-import streamlit as st
-from persist import persist, load_widget_state
-from jinja2 import Environment, FileSystemLoader
-
-def parse_into_jinja_markdown():
-    env = Environment(loader=FileSystemLoader('.'), autoescape=True)
-    temp = env.get_template(st.session_state.markdown_upload)
-   
-    return (temp.render(model_id = st.session_state["model_name"],
-        the_model_description = st.session_state["model_description"],developers=st.session_state["Model_developers"],shared_by = st.session_state["shared_by"],model_license = st.session_state['license'],
-            direct_use = st.session_state["Direct_Use"], downstream_use = st.session_state["Downstream_Use"],out_of_scope_use = st.session_state["Out-of-Scope_Use"],
-            bias_risks_limitations = st.session_state["Model_Limits_n_Risks"], bias_recommendations = st.session_state['Recommendations'],
-            model_examination = st.session_state['Model_examin'],
-            hardware= st.session_state['Model_hardware'], hours_used = st.session_state['hours_used'], cloud_provider = st.session_state['Model_cloud_provider'], cloud_region = st.session_state['Model_cloud_region'], co2_emitted = st.session_state['Model_c02_emitted'],
-            citation_bibtex= st.session_state["APA_citation"], citation_apa = st.session_state['bibtex_citation'],
-            training_data = st.session_state['training_data'], preprocessing =st.session_state['preprocessing'], speeds_sizes_times = st.session_state['Speeds_Sizes_Times'],
-            model_specs = st.session_state['Model_specs'], compute_infrastructure = st.session_state['compute_infrastructure'],software = st.session_state['technical_specs_software'],
-            glossary = st.session_state['Glossary'], 
-            more_information = st.session_state['More_info'], 
-            model_card_authors = st.session_state['the_authors'],
-            model_card_contact = st.session_state['Model_card_contact'],
-            get_started_code =st.session_state["Model_how_to"]
-            ))
-
-def main():
-    st.write( parse_into_jinja_markdown())
-
-if __name__ == '__main__':
-    load_widget_state()
-    main()
\ No newline at end of file
diff --git a/spaces/awacke1/Model-Easy-Button1-ZeroShotImageClassifier-Openai-clip-vit-large-patch14/app.py b/spaces/awacke1/Model-Easy-Button1-ZeroShotImageClassifier-Openai-clip-vit-large-patch14/app.py
deleted file mode 100644
index dcf483774b559736cb0ac10db8f4eae582888b48..0000000000000000000000000000000000000000
--- a/spaces/awacke1/Model-Easy-Button1-ZeroShotImageClassifier-Openai-clip-vit-large-patch14/app.py
+++ /dev/null
@@ -1,3 +0,0 @@
-import gradio as gr
-
-gr.Interface.load("models/openai/clip-vit-large-patch14").launch()
\ No newline at end of file
diff --git a/spaces/awacke1/Wikipedia-Twitter-ChatGPT-Memory-Chat/app.py b/spaces/awacke1/Wikipedia-Twitter-ChatGPT-Memory-Chat/app.py
deleted file mode 100644
index afc7243365eb2f4c04910d89172ef771264982c9..0000000000000000000000000000000000000000
--- a/spaces/awacke1/Wikipedia-Twitter-ChatGPT-Memory-Chat/app.py
+++ /dev/null
@@ -1,290 +0,0 @@
-import gradio as gr
-import os 
-import json 
-import requests
-import pandas as pd
-import wikipediaapi
-import wikipedia
-from wikipedia.exceptions import DisambiguationError
-
-#Streaming endpoint 
-API_URL = "https://api.openai.com/v1/chat/completions" #os.getenv("API_URL") + "/generate_stream"
-OPENAI_API_KEY= os.environ["HF_TOKEN"] # Add a token to this space .  Then copy it to the repository secret in this spaces settings panel.  os.environ reads from there.
-# Keys for Open AI ChatGPT API usage are created from here: https://platform.openai.com/account/api-keys
-
-
-#Wikipedia API:
-
-def get_pagetext(page):
-  s=str(page).replace("/t","")
-  
-#def get_wiki_summary(inputs, search, history=[]):
-  
-def get_wiki_summary(search):
-    wiki_wiki = wikipediaapi.Wikipedia('en')
-    page = wiki_wiki.page(search)
-
-    isExist = page.exists()
-    if not isExist:
-        return isExist, "Not found", "Not found", "Not found", "Not found"
-
-    pageurl = page.fullurl
-    pagetitle = page.title
-    pagesummary = page.summary[0:60]
-    pagetext = get_pagetext(page.text)
-
-    backlinks = page.backlinks
-    linklist = ""
-    for link in backlinks.items():
-      pui = link[0]
-      linklist += pui + " ,  "
-      a=1 
-      
-    categories = page.categories
-    categorylist = ""
-    for category in categories.items():
-      pui = category[0]
-      categorylist += pui + " ,  "
-      a=1     
-    
-    links = page.links
-    linklist2 = ""
-    for link in links.items():
-      pui = link[0]
-      linklist2 += pui + " ,  "
-      a=1 
-      
-    sections = page.sections
-    
-    ex_dic = {
-      'Entity' : ["URL","Title","Summary", "Text", "Backlinks", "Links", "Categories"],
-      'Value': [pageurl, pagetitle, pagesummary, pagetext, linklist,linklist2, categorylist ]
-    }
-
-    df = pd.DataFrame(ex_dic)
-                  
-    # yield df
-
-    return df
-
-# ChatGPT
-    
-def predict(inputs, top_p, temperature, chat_counter, chatbot=[], history=[]):  #repetition_penalty, top_k
-
-    # 1. Set up a payload
-    payload = {
-    "model": "gpt-3.5-turbo",
-    "messages": [{"role": "user", "content": f"{inputs}"}],
-    "temperature" : 1.0,
-    "top_p":1.0,
-    "n" : 1,
-    "stream": True,
-    "presence_penalty":0,
-    "frequency_penalty":0,
-    }
-
-    # 2. Define your headers and add a key from https://platform.openai.com/account/api-keys
-    headers = {
-    "Content-Type": "application/json",
-    "Authorization": f"Bearer {OPENAI_API_KEY}"
-    }
-
-    # 3. Create a chat counter loop that feeds [Predict next best anything based on last input and attention with memory defined by introspective attention over time]
-    print(f"chat_counter - {chat_counter}")
-    if chat_counter != 0 :
-        messages=[]
-        for data in chatbot:
-          temp1 = {}
-          temp1["role"] = "user" 
-          temp1["content"] = data[0] 
-          temp2 = {}
-          temp2["role"] = "assistant" 
-          temp2["content"] = data[1]
-          messages.append(temp1)
-          messages.append(temp2)
-        temp3 = {}
-        temp3["role"] = "user" 
-        temp3["content"] = inputs
-        messages.append(temp3)
-        payload = {
-        "model": "gpt-3.5-turbo",
-        "messages": messages, #[{"role": "user", "content": f"{inputs}"}],
-        "temperature" : temperature, #1.0,
-        "top_p": top_p, #1.0,
-        "n" : 1,
-        "stream": True,
-        "presence_penalty":0,
-        "frequency_penalty":0,
-        }
-    chat_counter+=1
-
-    # 4. POST it to OPENAI API
-    history.append(inputs)
-    print(f"payload is - {payload}")
-    response = requests.post(API_URL, headers=headers, json=payload, stream=True)
-    token_counter = 0 
-    partial_words = "" 
-
-    # 5. Iterate through response lines and structure readable response
-    counter=0
-    for chunk in response.iter_lines():
-        if counter == 0:
-          counter+=1
-          continue
-        if chunk.decode() :
-          chunk = chunk.decode()
-          if len(chunk) > 12 and "content" in json.loads(chunk[6:])['choices'][0]['delta']:
-              partial_words = partial_words + json.loads(chunk[6:])['choices'][0]["delta"]["content"]
-              if token_counter == 0:
-                history.append(" " + partial_words)
-              else:
-                history[-1] = partial_words
-              chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ]  # convert to tuples of list
-              token_counter+=1
-              yield chat, history, chat_counter 
-                   
-
-def reset_textbox():
-    return gr.update(value='')
-
-
-    
-
-# Episodic and Semantic IO
-def list_files(file_path):
-    import os
-    icon_csv = "📄 "
-    icon_txt = "📑 "
-    current_directory = os.getcwd()
-    file_list = []
-    for filename in os.listdir(current_directory):
-        if filename.endswith(".csv"):
-            file_list.append(icon_csv + filename)
-        elif filename.endswith(".txt"):
-            file_list.append(icon_txt + filename)
-    if file_list:
-        return "\n".join(file_list)
-    else:
-        return "No .csv or .txt files found in the current directory."
-
-# Function to read a file
-def read_file(file_path):
-    try:
-        with open(file_path, "r") as file:
-            contents = file.read()
-            return f"{contents}"
-            #return f"Contents of {file_path}:\n{contents}"
-    except FileNotFoundError:
-        return "File not found."
-
-# Function to delete a file
-def delete_file(file_path):
-    try:
-        import os
-        os.remove(file_path)
-        return f"{file_path} has been deleted."
-    except FileNotFoundError:
-        return "File not found."
-
-# Function to write to a file
-def write_file(file_path, content):
-    try:
-        with open(file_path, "w") as file:
-            file.write(content)
-        return f"Successfully written to {file_path}."
-    except:
-        return "Error occurred while writing to file."
-
-# Function to append to a file
-def append_file(file_path, content):
-    try:
-        with open(file_path, "a") as file:
-            file.write(content)
-        return f"Successfully appended to {file_path}."
-    except:
-        return "Error occurred while appending to file."
-
-
-title = """<h1 align="center">Wikipedia Twitter ChatGPT Memory Chat</h1>"""
-description = """
-## ChatGPT Datasets 📚
-- WebText
-- Common Crawl
-- BooksCorpus
-- English Wikipedia
-- Toronto Books Corpus
-- OpenWebText
-## ChatGPT Datasets - Details 📚
-- **WebText:** A dataset of web pages crawled from domains on the Alexa top 5,000 list. This dataset was used to pretrain GPT-2.
-  - [WebText: A Large-Scale Unsupervised Text Corpus by Radford et al.](https://paperswithcode.com/dataset/webtext)
-- **Common Crawl:** A dataset of web pages from a variety of domains, which is updated regularly. This dataset was used to pretrain GPT-3.
-  - [Language Models are Few-Shot Learners](https://paperswithcode.com/dataset/common-crawl) by Brown et al.
-- **BooksCorpus:** A dataset of over 11,000 books from a variety of genres.
-  - [Scalable Methods for 8 Billion Token Language Modeling](https://paperswithcode.com/dataset/bookcorpus) by Zhu et al.
-- **English Wikipedia:** A dump of the English-language Wikipedia as of 2018, with articles from 2001-2017.
-  - [Improving Language Understanding by Generative Pre-Training](https://huggingface.co/spaces/awacke1/WikipediaUltimateAISearch?logs=build) Space for Wikipedia Search
-- **Toronto Books Corpus:** A dataset of over 7,000 books from a variety of genres, collected by the University of Toronto.
-  - [Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond](https://paperswithcode.com/dataset/bookcorpus) by Schwenk and Douze.
-- **OpenWebText:** A dataset of web pages that were filtered to remove content that was likely to be low-quality or spammy. This dataset was used to pretrain GPT-3.
-  - [Language Models are Few-Shot Learners](https://paperswithcode.com/dataset/openwebtext) by Brown et al.  
-  """
-
-# 6. Use Gradio to pull it all together
-with gr.Blocks(css = """#col_container {width: 1280px; margin-left: auto; margin-right: auto;} #chatbot {height: 600px; overflow: auto;}""") as demo:
-    gr.HTML(title)
-
-    # Wikipedia context preloader
-    with gr.Row(): # inputs and buttons
-        inp = gr.Textbox(lines=1, default="ChatGPT", label="Question")
-    with gr.Row(): # inputs and buttons
-        b4 = gr.Button("Search Web Live")
-    with gr.Row(): # output DF2
-        out_DF = gr.Dataframe(wrap=True, max_rows=1000, overflow_row_behaviour= "paginate", datatype = ["markdown", "markdown"], headers=['Entity', 'Value'])
-
-
-    # Accordian chat bot
-    with gr.Column(elem_id = "col_container"):
-        inputs = gr.Textbox(placeholder= "Hi there!", label= "Type an input and press Enter")
-        chatbot = gr.Chatbot(elem_id='chatbot')
-        state = gr.State([])
-        b1 = gr.Button()
-        with gr.Accordion("Parameters", open=False):
-            top_p = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=True, label="Top-p (nucleus sampling)",)
-            temperature = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=True, label="Temperature",)
-            chat_counter = gr.Number(value=0, visible=True, precision=0)
-
-    # Episodic/Semantic Memory IO
-    fileName = gr.Textbox(label="Filename")
-    fileContent = gr.TextArea(label="File Content")
-    completedMessage = gr.Textbox(label="Completed")
-    label = gr.Label()
-    with gr.Row():
-        listFiles = gr.Button("📄 List File(s)")
-        readFile = gr.Button("📖 Read File")
-        saveFile = gr.Button("💾 Save File")
-        deleteFile = gr.Button("🗑️ Delete File")
-        appendFile = gr.Button("➕ Append File")
-
-
-    # ChatGPT events:
-    listFiles.click(list_files, inputs=fileName, outputs=fileContent)
-    readFile.click(read_file, inputs=fileName, outputs=fileContent)
-    saveFile.click(write_file, inputs=[fileName, fileContent], outputs=completedMessage)
-    deleteFile.click(delete_file, inputs=fileName, outputs=completedMessage)
-    appendFile.click(append_file, inputs=[fileName, fileContent], outputs=completedMessage )
-
-    # Wikipedia events
-    b4.click(get_wiki_summary, inp, out_DF )
-    inputs.submit(get_wiki_summary, inp, out_DF)
-
-
-    # Chatbot
-    inputs.submit(predict, [inputs, top_p, temperature,chat_counter, chatbot, state], [chatbot, state, chat_counter])
-    b1.click(predict, [inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter])
-    b1.click(reset_textbox, [], [inputs])
-    
-    inputs.submit(reset_textbox, [], [inputs])
-    gr.Markdown(description)
-
-    # Queue and go!
-    demo.queue().launch(debug=True)
\ No newline at end of file
diff --git a/spaces/awaiss/vits-models/text/__init__.py b/spaces/awaiss/vits-models/text/__init__.py
deleted file mode 100644
index 663c4b6416affb53c9dc56dddbc8b2b65d4bf518..0000000000000000000000000000000000000000
--- a/spaces/awaiss/vits-models/text/__init__.py
+++ /dev/null
@@ -1,57 +0,0 @@
-""" from https://github.com/keithito/tacotron """
-from text import cleaners
-from text.symbols import symbols
-
-
-# Mappings from symbol to numeric ID and vice versa:
-_symbol_to_id = {s: i for i, s in enumerate(symbols)}
-_id_to_symbol = {i: s for i, s in enumerate(symbols)}
-
-
-def text_to_sequence(text, symbols, cleaner_names):
-  '''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
-    Args:
-      text: string to convert to a sequence
-      cleaner_names: names of the cleaner functions to run the text through
-    Returns:
-      List of integers corresponding to the symbols in the text
-  '''
-  _symbol_to_id = {s: i for i, s in enumerate(symbols)}
-  sequence = []
-
-  clean_text = _clean_text(text, cleaner_names)
-  for symbol in clean_text:
-    if symbol not in _symbol_to_id.keys():
-      continue
-    symbol_id = _symbol_to_id[symbol]
-    sequence += [symbol_id]
-  return sequence, clean_text
-
-
-def cleaned_text_to_sequence(cleaned_text):
-  '''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
-    Args:
-      text: string to convert to a sequence
-    Returns:
-      List of integers corresponding to the symbols in the text
-  '''
-  sequence = [_symbol_to_id[symbol] for symbol in cleaned_text if symbol in _symbol_to_id.keys()]
-  return sequence
-
-
-def sequence_to_text(sequence):
-  '''Converts a sequence of IDs back to a string'''
-  result = ''
-  for symbol_id in sequence:
-    s = _id_to_symbol[symbol_id]
-    result += s
-  return result
-
-
-def _clean_text(text, cleaner_names):
-  for name in cleaner_names:
-    cleaner = getattr(cleaners, name)
-    if not cleaner:
-      raise Exception('Unknown cleaner: %s' % name)
-    text = cleaner(text)
-  return text
diff --git a/spaces/azizmma/question_generator/app.py b/spaces/azizmma/question_generator/app.py
deleted file mode 100644
index 76b2d2200ee156a0fb3f32a534055cc39c485d38..0000000000000000000000000000000000000000
--- a/spaces/azizmma/question_generator/app.py
+++ /dev/null
@@ -1,42 +0,0 @@
-import streamlit as st
-from transformers import AutoTokenizer, T5ForConditionalGeneration
-  
-model_name = "allenai/t5-small-squad2-question-generation"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-@st.cache
-def load_model(model_name):
-    model = T5ForConditionalGeneration.from_pretrained(model_name)
-    return model
-
-model = load_model(model_name)
-
-
-def run_model(input_string, **generator_args):
-    input_ids = tokenizer.encode(input_string, return_tensors="pt")
-    res = model.generate(input_ids, **generator_args)
-    output = tokenizer.batch_decode(res, skip_special_tokens=True)
-    print(output)
-    return output
-
-
-default_value = "Nicejob has increased our revenue 80% since signing up"
-
-#prompts
-st.title("Question Generation")
-st.write("Placeholder for some other texts, like instructions...")
-
-sent = st.text_area("Text", default_value, height = 100)
-max_length = st.sidebar.slider("Max Length", min_value = 10, max_value=150,value=80,step=5)
-temperature = st.sidebar.slider("Temperature", value = 1.0, min_value = 0.0, max_value=1.0, step=0.05)
-num_return_sequences = st.sidebar.slider("Num Return Sequences", min_value = 1, max_value=10, value = 2)
-num_beams = st.sidebar.slider("Num Beams", min_value = 1, max_value=10, value = 4)
-top_k = st.sidebar.slider("Top-k", min_value = 0, max_value=100, value = 90)
-top_p = st.sidebar.slider("Top-p", min_value = 0.0, max_value=1.0, step = 0.05, value = 0.9)
-
-
-
-output_sequences = run_model(sent, max_length=max_length,num_return_sequences=num_return_sequences,
-                        num_beams=num_beams,
-                        temperature=temperature, top_k=top_k, top_p=top_p)
-
-st.write(output_sequences)
\ No newline at end of file
diff --git a/spaces/balamurugan/search-10k-filings/README.md b/spaces/balamurugan/search-10k-filings/README.md
deleted file mode 100644
index 86f490fd2f61b4ca02d1b49737abd19811cc5bff..0000000000000000000000000000000000000000
--- a/spaces/balamurugan/search-10k-filings/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Search 10k Filings
-emoji: 💩
-colorFrom: red
-colorTo: indigo
-sdk: gradio
-sdk_version: 2.9.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference
diff --git a/spaces/banana-projects/web3d/node_modules/three/examples/jsm/controls/MapControls.d.ts b/spaces/banana-projects/web3d/node_modules/three/examples/jsm/controls/MapControls.d.ts
deleted file mode 100644
index bf34f96f0effbae362c2b41c0a97f34aca37dedf..0000000000000000000000000000000000000000
--- a/spaces/banana-projects/web3d/node_modules/three/examples/jsm/controls/MapControls.d.ts
+++ /dev/null
@@ -1,71 +0,0 @@
-import {
-  Camera,
-  EventDispatcher,
-  MOUSE,
-  Object3D,
-  Vector3
-} from '../../../src/Three';
-
-export class MapControls extends EventDispatcher {
-  constructor(object: Camera, domElement?: HTMLElement);
-
-  object: Camera;
-  domElement: HTMLElement | HTMLDocument;
-
-  // API
-  enabled: boolean;
-  target: Vector3;
-
-  enableZoom: boolean;
-  zoomSpeed: number;
-  minDistance: number;
-  maxDistance: number;
-  enableRotate: boolean;
-  rotateSpeed: number;
-  enablePan: boolean;
-  keyPanSpeed: number;
-  maxZoom: number;
-  minZoom: number;
-  panSpeed: number;
-  autoRotate: boolean;
-  autoRotateSpeed: number;
-  minPolarAngle: number;
-  maxPolarAngle: number;
-  minAzimuthAngle: number;
-  maxAzimuthAngle: number;
-  enableKeys: boolean;
-  screenSpacePanning: boolean;
-  keys: { LEFT: number; UP: number; RIGHT: number; BOTTOM: number };
-  mouseButtons: { LEFT: MOUSE; MIDDLE: MOUSE; RIGHT: MOUSE };
-  enableDamping: boolean;
-  dampingFactor: number;
-  target0: Vector3;
-  position0: Vector3;
-  zoom0: number;
-
-  rotateLeft(angle?: number): void;
-
-  rotateUp(angle?: number): void;
-
-  panLeft(distance?: number): void;
-
-  panUp(distance?: number): void;
-
-  pan(deltaX: number, deltaY: number): void;
-
-  dollyIn(dollyScale: number): void;
-
-  dollyOut(dollyScale: number): void;
-
-  saveState(): void;
-
-  update(): boolean;
-
-  reset(): void;
-
-  dispose(): void;
-
-  getPolarAngle(): number;
-
-  getAzimuthalAngle(): number;
-}
diff --git a/spaces/banana-projects/web3d/node_modules/three/src/extras/curves/QuadraticBezierCurve3.js b/spaces/banana-projects/web3d/node_modules/three/src/extras/curves/QuadraticBezierCurve3.js
deleted file mode 100644
index ab2042d104f2cfc464d6688420a9c0493122b1db..0000000000000000000000000000000000000000
--- a/spaces/banana-projects/web3d/node_modules/three/src/extras/curves/QuadraticBezierCurve3.js
+++ /dev/null
@@ -1,76 +0,0 @@
-import { Curve } from '../core/Curve.js';
-import { QuadraticBezier } from '../core/Interpolations.js';
-import { Vector3 } from '../../math/Vector3.js';
-
-
-function QuadraticBezierCurve3( v0, v1, v2 ) {
-
-	Curve.call( this );
-
-	this.type = 'QuadraticBezierCurve3';
-
-	this.v0 = v0 || new Vector3();
-	this.v1 = v1 || new Vector3();
-	this.v2 = v2 || new Vector3();
-
-}
-
-QuadraticBezierCurve3.prototype = Object.create( Curve.prototype );
-QuadraticBezierCurve3.prototype.constructor = QuadraticBezierCurve3;
-
-QuadraticBezierCurve3.prototype.isQuadraticBezierCurve3 = true;
-
-QuadraticBezierCurve3.prototype.getPoint = function ( t, optionalTarget ) {
-
-	var point = optionalTarget || new Vector3();
-
-	var v0 = this.v0, v1 = this.v1, v2 = this.v2;
-
-	point.set(
-		QuadraticBezier( t, v0.x, v1.x, v2.x ),
-		QuadraticBezier( t, v0.y, v1.y, v2.y ),
-		QuadraticBezier( t, v0.z, v1.z, v2.z )
-	);
-
-	return point;
-
-};
-
-QuadraticBezierCurve3.prototype.copy = function ( source ) {
-
-	Curve.prototype.copy.call( this, source );
-
-	this.v0.copy( source.v0 );
-	this.v1.copy( source.v1 );
-	this.v2.copy( source.v2 );
-
-	return this;
-
-};
-
-QuadraticBezierCurve3.prototype.toJSON = function () {
-
-	var data = Curve.prototype.toJSON.call( this );
-
-	data.v0 = this.v0.toArray();
-	data.v1 = this.v1.toArray();
-	data.v2 = this.v2.toArray();
-
-	return data;
-
-};
-
-QuadraticBezierCurve3.prototype.fromJSON = function ( json ) {
-
-	Curve.prototype.fromJSON.call( this, json );
-
-	this.v0.fromArray( json.v0 );
-	this.v1.fromArray( json.v1 );
-	this.v2.fromArray( json.v2 );
-
-	return this;
-
-};
-
-
-export { QuadraticBezierCurve3 };
diff --git a/spaces/banana-projects/web3d/node_modules/three/src/renderers/shaders/ShaderChunk/aomap_pars_fragment.glsl.js b/spaces/banana-projects/web3d/node_modules/three/src/renderers/shaders/ShaderChunk/aomap_pars_fragment.glsl.js
deleted file mode 100644
index 7c2eadc7ed8d2ae9ae19d48b20631c208ee8231d..0000000000000000000000000000000000000000
--- a/spaces/banana-projects/web3d/node_modules/three/src/renderers/shaders/ShaderChunk/aomap_pars_fragment.glsl.js
+++ /dev/null
@@ -1,8 +0,0 @@
-export default /* glsl */`
-#ifdef USE_AOMAP
-
-	uniform sampler2D aoMap;
-	uniform float aoMapIntensity;
-
-#endif
-`;
diff --git a/spaces/bebetterfeng/CarperAI-stable-vicuna-13b-delta/README.md b/spaces/bebetterfeng/CarperAI-stable-vicuna-13b-delta/README.md
deleted file mode 100644
index b6108f8d066c1d9515ceca543684e393a8d0ad5f..0000000000000000000000000000000000000000
--- a/spaces/bebetterfeng/CarperAI-stable-vicuna-13b-delta/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: CarperAI Stable Vicuna 13b Delta
-emoji: 🌍
-colorFrom: blue
-colorTo: purple
-sdk: gradio
-sdk_version: 3.29.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/bhasker412/IDD-YOLO-Tracking/trackers/strongsort/sort/track.py b/spaces/bhasker412/IDD-YOLO-Tracking/trackers/strongsort/sort/track.py
deleted file mode 100644
index bb6773fc4e337b8f2b0dc1fde274f20280e5c3d5..0000000000000000000000000000000000000000
--- a/spaces/bhasker412/IDD-YOLO-Tracking/trackers/strongsort/sort/track.py
+++ /dev/null
@@ -1,317 +0,0 @@
-# vim: expandtab:ts=4:sw=4
-import cv2
-import numpy as np
-from trackers.strongsort.sort.kalman_filter import KalmanFilter
-from collections import deque
-
-
-class TrackState:
-    """
-    Enumeration type for the single target track state. Newly created tracks are
-    classified as `tentative` until enough evidence has been collected. Then,
-    the track state is changed to `confirmed`. Tracks that are no longer alive
-    are classified as `deleted` to mark them for removal from the set of active
-    tracks.
-
-    """
-
-    Tentative = 1
-    Confirmed = 2
-    Deleted = 3
-
-
-class Track:
-    """
-    A single target track with state space `(x, y, a, h)` and associated
-    velocities, where `(x, y)` is the center of the bounding box, `a` is the
-    aspect ratio and `h` is the height.
-
-    Parameters
-    ----------
-    mean : ndarray
-        Mean vector of the initial state distribution.
-    covariance : ndarray
-        Covariance matrix of the initial state distribution.
-    track_id : int
-        A unique track identifier.
-    n_init : int
-        Number of consecutive detections before the track is confirmed. The
-        track state is set to `Deleted` if a miss occurs within the first
-        `n_init` frames.
-    max_age : int
-        The maximum number of consecutive misses before the track state is
-        set to `Deleted`.
-    feature : Optional[ndarray]
-        Feature vector of the detection this track originates from. If not None,
-        this feature is added to the `features` cache.
-
-    Attributes
-    ----------
-    mean : ndarray
-        Mean vector of the initial state distribution.
-    covariance : ndarray
-        Covariance matrix of the initial state distribution.
-    track_id : int
-        A unique track identifier.
-    hits : int
-        Total number of measurement updates.
-    age : int
-        Total number of frames since first occurance.
-    time_since_update : int
-        Total number of frames since last measurement update.
-    state : TrackState
-        The current track state.
-    features : List[ndarray]
-        A cache of features. On each measurement update, the associated feature
-        vector is added to this list.
-
-    """
-
-    def __init__(self, detection, track_id, class_id, conf, n_init, max_age, ema_alpha,
-                 feature=None):
-        self.track_id = track_id
-        self.class_id = int(class_id)
-        self.hits = 1
-        self.age = 1
-        self.time_since_update = 0
-        self.max_num_updates_wo_assignment = 7
-        self.updates_wo_assignment = 0
-        self.ema_alpha = ema_alpha
-
-        self.state = TrackState.Tentative
-        self.features = []
-        if feature is not None:
-            feature /= np.linalg.norm(feature)
-            self.features.append(feature)
-
-        self.conf = conf
-        self._n_init = n_init
-        self._max_age = max_age
-
-        self.kf = KalmanFilter()
-        self.mean, self.covariance = self.kf.initiate(detection)
-        
-        # Initializing trajectory queue
-        self.q = deque(maxlen=25)
-
-    def to_tlwh(self):
-        """Get current position in bounding box format `(top left x, top left y,
-        width, height)`.
-
-        Returns
-        -------
-        ndarray
-            The bounding box.
-
-        """
-        ret = self.mean[:4].copy()
-        ret[2] *= ret[3]
-        ret[:2] -= ret[2:] / 2
-        return ret
-
-    def to_tlbr(self):
-        """Get kf estimated current position in bounding box format `(min x, miny, max x,
-        max y)`.
-
-        Returns
-        -------
-        ndarray
-            The predicted kf bounding box.
-
-        """
-        ret = self.to_tlwh()
-        ret[2:] = ret[:2] + ret[2:]
-        return ret
-
-
-    def ECC(self, src, dst, warp_mode = cv2.MOTION_EUCLIDEAN, eps = 1e-5,
-        max_iter = 100, scale = 0.1, align = False):
-        """Compute the warp matrix from src to dst.
-        Parameters
-        ----------
-        src : ndarray 
-            An NxM matrix of source img(BGR or Gray), it must be the same format as dst.
-        dst : ndarray
-            An NxM matrix of target img(BGR or Gray).
-        warp_mode: flags of opencv
-            translation: cv2.MOTION_TRANSLATION
-            rotated and shifted: cv2.MOTION_EUCLIDEAN
-            affine(shift,rotated,shear): cv2.MOTION_AFFINE
-            homography(3d): cv2.MOTION_HOMOGRAPHY
-        eps: float
-            the threshold of the increment in the correlation coefficient between two iterations
-        max_iter: int
-            the number of iterations.
-        scale: float or [int, int]
-            scale_ratio: float
-            scale_size: [W, H]
-        align: bool
-            whether to warp affine or perspective transforms to the source image
-        Returns
-        -------
-        warp matrix : ndarray
-            Returns the warp matrix from src to dst.
-            if motion models is homography, the warp matrix will be 3x3, otherwise 2x3
-        src_aligned: ndarray
-            aligned source image of gray
-        """
-
-        # BGR2GRAY
-        if src.ndim == 3:
-            # Convert images to grayscale
-            src = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
-            dst = cv2.cvtColor(dst, cv2.COLOR_BGR2GRAY)
-
-        # make the imgs smaller to speed up
-        if scale is not None:
-            if isinstance(scale, float) or isinstance(scale, int):
-                if scale != 1:
-                    src_r = cv2.resize(src, (0, 0), fx = scale, fy = scale,interpolation =  cv2.INTER_LINEAR)
-                    dst_r = cv2.resize(dst, (0, 0), fx = scale, fy = scale,interpolation =  cv2.INTER_LINEAR)
-                    scale = [scale, scale]
-                else:
-                    src_r, dst_r = src, dst
-                    scale = None
-            else:
-                if scale[0] != src.shape[1] and scale[1] != src.shape[0]:
-                    src_r = cv2.resize(src, (scale[0], scale[1]), interpolation = cv2.INTER_LINEAR)
-                    dst_r = cv2.resize(dst, (scale[0], scale[1]), interpolation=cv2.INTER_LINEAR)
-                    scale = [scale[0] / src.shape[1], scale[1] / src.shape[0]]
-                else:
-                    src_r, dst_r = src, dst
-                    scale = None
-        else:
-            src_r, dst_r = src, dst
-
-        # Define 2x3 or 3x3 matrices and initialize the matrix to identity
-        if warp_mode == cv2.MOTION_HOMOGRAPHY :
-            warp_matrix = np.eye(3, 3, dtype=np.float32)
-        else :
-            warp_matrix = np.eye(2, 3, dtype=np.float32)
-
-        # Define termination criteria
-        criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, max_iter, eps)
-
-        # Run the ECC algorithm. The results are stored in warp_matrix.
-        try:
-            (cc, warp_matrix) = cv2.findTransformECC (src_r, dst_r, warp_matrix, warp_mode, criteria, None, 1)
-        except cv2.error as e:
-            print('ecc transform failed')
-            return None, None
-        
-        if scale is not None:
-            warp_matrix[0, 2] = warp_matrix[0, 2] / scale[0]
-            warp_matrix[1, 2] = warp_matrix[1, 2] / scale[1]
-
-        if align:
-            sz = src.shape
-            if warp_mode == cv2.MOTION_HOMOGRAPHY:
-                # Use warpPerspective for Homography
-                src_aligned = cv2.warpPerspective(src, warp_matrix, (sz[1],sz[0]), flags=cv2.INTER_LINEAR)
-            else :
-                # Use warpAffine for Translation, Euclidean and Affine
-                src_aligned = cv2.warpAffine(src, warp_matrix, (sz[1],sz[0]), flags=cv2.INTER_LINEAR)
-            return warp_matrix, src_aligned
-        else:
-            return warp_matrix, None
-
-
-    def get_matrix(self, matrix):
-        eye = np.eye(3)
-        dist = np.linalg.norm(eye - matrix)
-        if dist < 100:
-            return matrix
-        else:
-            return eye
-
-    def camera_update(self, previous_frame, next_frame):
-        warp_matrix, src_aligned = self.ECC(previous_frame, next_frame)
-        if warp_matrix is None and src_aligned is None:
-            return
-        [a,b] = warp_matrix
-        warp_matrix=np.array([a,b,[0,0,1]])
-        warp_matrix = warp_matrix.tolist()
-        matrix = self.get_matrix(warp_matrix)
-
-        x1, y1, x2, y2 = self.to_tlbr()
-        x1_, y1_, _ = matrix @ np.array([x1, y1, 1]).T
-        x2_, y2_, _ = matrix @ np.array([x2, y2, 1]).T
-        w, h = x2_ - x1_, y2_ - y1_
-        cx, cy = x1_ + w / 2, y1_ + h / 2
-        self.mean[:4] = [cx, cy, w / h, h]
-
-
-    def increment_age(self):
-        self.age += 1
-        self.time_since_update += 1
-
-    def predict(self, kf):
-        """Propagate the state distribution to the current time step using a
-        Kalman filter prediction step.
-
-        Parameters
-        ----------
-        kf : kalman_filter.KalmanFilter
-            The Kalman filter.
-
-        """
-        self.mean, self.covariance = self.kf.predict(self.mean, self.covariance)
-        self.age += 1
-        self.time_since_update += 1
-        
-    def update_kf(self, bbox, confidence=0.5):
-        self.updates_wo_assignment = self.updates_wo_assignment + 1
-        self.mean, self.covariance = self.kf.update(self.mean, self.covariance, bbox, confidence)
-        tlbr = self.to_tlbr()
-        x_c = int((tlbr[0] + tlbr[2]) / 2)
-        y_c = int((tlbr[1] + tlbr[3]) / 2)
-        self.q.append(('predupdate', (x_c, y_c)))
-
-    def update(self, detection, class_id, conf):
-        """Perform Kalman filter measurement update step and update the feature
-        cache.
-        Parameters
-        ----------
-        detection : Detection
-            The associated detection.
-        """
-        self.conf = conf
-        self.class_id = class_id.int()
-        self.mean, self.covariance = self.kf.update(self.mean, self.covariance, detection.to_xyah(), detection.confidence)
-
-        feature = detection.feature / np.linalg.norm(detection.feature)
-
-        smooth_feat = self.ema_alpha * self.features[-1] + (1 - self.ema_alpha) * feature
-        smooth_feat /= np.linalg.norm(smooth_feat)
-        self.features = [smooth_feat]
-
-        self.hits += 1
-        self.time_since_update = 0
-        if self.state == TrackState.Tentative and self.hits >= self._n_init:
-            self.state = TrackState.Confirmed
-        
-        tlbr = self.to_tlbr()
-        x_c = int((tlbr[0] + tlbr[2]) / 2)
-        y_c = int((tlbr[1] + tlbr[3]) / 2)
-        self.q.append(('observationupdate', (x_c, y_c)))
-
-    def mark_missed(self):
-        """Mark this track as missed (no association at the current time step).
-        """
-        if self.state == TrackState.Tentative:
-            self.state = TrackState.Deleted
-        elif self.time_since_update > self._max_age:
-            self.state = TrackState.Deleted
-
-    def is_tentative(self):
-        """Returns True if this track is tentative (unconfirmed).
-        """
-        return self.state == TrackState.Tentative
-
-    def is_confirmed(self):
-        """Returns True if this track is confirmed."""
-        return self.state == TrackState.Confirmed
-
-    def is_deleted(self):
-        """Returns True if this track is dead and should be deleted."""
-        return self.state == TrackState.Deleted
diff --git a/spaces/bigjoker/stable-diffusion-webui/extensions/deforum/scripts/deforum_helpers/src/model_io.py b/spaces/bigjoker/stable-diffusion-webui/extensions/deforum/scripts/deforum_helpers/src/model_io.py
deleted file mode 100644
index 3427be8176f178c4c3ef09664a3f28d9fbaab4c3..0000000000000000000000000000000000000000
--- a/spaces/bigjoker/stable-diffusion-webui/extensions/deforum/scripts/deforum_helpers/src/model_io.py
+++ /dev/null
@@ -1,74 +0,0 @@
-import os
-
-import torch
-
-
-def save_weights(model, filename, path="./saved_models"):
-    if not os.path.isdir(path):
-        os.makedirs(path)
-
-    fpath = os.path.join(path, filename)
-    torch.save(model.state_dict(), fpath)
-    return
-
-
-def save_checkpoint(model, optimizer, epoch, filename, root="./checkpoints"):
-    if not os.path.isdir(root):
-        os.makedirs(root)
-
-    fpath = os.path.join(root, filename)
-    torch.save(
-        {
-            "model": model.state_dict(),
-            "optimizer": optimizer.state_dict(),
-            "epoch": epoch
-        }
-        , fpath)
-
-
-def load_weights(model, filename, path="./saved_models"):
-    fpath = os.path.join(path, filename)
-    state_dict = torch.load(fpath)
-    model.load_state_dict(state_dict)
-    return model
-
-
-def load_checkpoint(fpath, model, optimizer=None):
-    ckpt = torch.load(fpath, map_location='cpu')
-    if ckpt is None:
-        raise Exception(f"\nERROR Loading AdaBins_nyu.pt. Read this for a fix:\nhttps://github.com/deforum-art/deforum-for-automatic1111-webui/wiki/FAQ-&-Troubleshooting#3d-animation-mode-is-not-working-only-2d-works")
-    if optimizer is None:
-        optimizer = ckpt.get('optimizer', None)
-    else:
-        optimizer.load_state_dict(ckpt['optimizer'])
-    epoch = ckpt['epoch']
-
-    if 'model' in ckpt:
-        ckpt = ckpt['model']
-    load_dict = {}
-    for k, v in ckpt.items():
-        if k.startswith('module.'):
-            k_ = k.replace('module.', '')
-            load_dict[k_] = v
-        else:
-            load_dict[k] = v
-
-    modified = {}  # backward compatibility to older naming of architecture blocks
-    for k, v in load_dict.items():
-        if k.startswith('adaptive_bins_layer.embedding_conv.'):
-            k_ = k.replace('adaptive_bins_layer.embedding_conv.',
-                           'adaptive_bins_layer.conv3x3.')
-            modified[k_] = v
-            # del load_dict[k]
-
-        elif k.startswith('adaptive_bins_layer.patch_transformer.embedding_encoder'):
-
-            k_ = k.replace('adaptive_bins_layer.patch_transformer.embedding_encoder',
-                           'adaptive_bins_layer.patch_transformer.embedding_convPxP')
-            modified[k_] = v
-            # del load_dict[k]
-        else:
-            modified[k] = v  # else keep the original
-
-    model.load_state_dict(modified)
-    return model, optimizer, epoch
diff --git a/spaces/bigjoker/stable-diffusion-webui/modules/shared.py b/spaces/bigjoker/stable-diffusion-webui/modules/shared.py
deleted file mode 100644
index 2a3037ac85a4ce46300b769c97b63d736315f848..0000000000000000000000000000000000000000
--- a/spaces/bigjoker/stable-diffusion-webui/modules/shared.py
+++ /dev/null
@@ -1,720 +0,0 @@
-import argparse
-import datetime
-import json
-import os
-import sys
-import time
-
-from PIL import Image
-import gradio as gr
-import tqdm
-
-import modules.interrogate
-import modules.memmon
-import modules.styles
-import modules.devices as devices
-from modules import localization, extensions, script_loading, errors, ui_components, shared_items
-from modules.paths import models_path, script_path, data_path
-
-
-demo = None
-
-sd_configs_path = os.path.join(script_path, "configs")
-sd_default_config = os.path.join(sd_configs_path, "v1-inference.yaml")
-sd_model_file = os.path.join(script_path, 'model.ckpt')
-default_sd_model_file = sd_model_file
-
-parser = argparse.ArgumentParser()
-parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",)
-parser.add_argument("--config", type=str, default=sd_default_config, help="path to config which constructs model",)
-parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; if specified, this checkpoint will be added to the list of checkpoints and loaded",)
-parser.add_argument("--ckpt-dir", type=str, default=None, help="Path to directory with stable diffusion checkpoints")
-parser.add_argument("--vae-dir", type=str, default=None, help="Path to directory with VAE files")
-parser.add_argument("--gfpgan-dir", type=str, help="GFPGAN directory", default=('./src/gfpgan' if os.path.exists('./src/gfpgan') else './GFPGAN'))
-parser.add_argument("--gfpgan-model", type=str, help="GFPGAN model file name", default=None)
-parser.add_argument("--no-half", action='store_true', help="do not switch the model to 16-bit floats")
-parser.add_argument("--no-half-vae", action='store_true', help="do not switch the VAE model to 16-bit floats")
-parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)")
-parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI")
-parser.add_argument("--embeddings-dir", type=str, default=os.path.join(data_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
-parser.add_argument("--textual-inversion-templates-dir", type=str, default=os.path.join(script_path, 'textual_inversion_templates'), help="directory with textual inversion templates")
-parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory")
-parser.add_argument("--localizations-dir", type=str, default=os.path.join(script_path, 'localizations'), help="localizations directory")
-parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui")
-parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage")
-parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage")
-parser.add_argument("--lowram", action='store_true', help="load stable diffusion checkpoint weights to VRAM instead of RAM")
-parser.add_argument("--always-batch-cond-uncond", action='store_true', help="disables cond/uncond batching that is enabled to save memory with --medvram or --lowvram")
-parser.add_argument("--unload-gfpgan", action='store_true', help="does not do anything.")
-parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast")
-parser.add_argument("--upcast-sampling", action='store_true', help="upcast sampling. No effect with --no-half. Usually produces similar results to --no-half with better performance while using less memory.")
-parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site")
-parser.add_argument("--ngrok", type=str, help="ngrok authtoken, alternative to gradio --share", default=None)
-parser.add_argument("--ngrok-region", type=str, help="The region in which ngrok should start.", default="us")
-parser.add_argument("--enable-insecure-extension-access", action='store_true', help="enable extensions tab regardless of other options")
-parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(models_path, 'Codeformer'))
-parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory with GFPGAN model file(s).", default=os.path.join(models_path, 'GFPGAN'))
-parser.add_argument("--esrgan-models-path", type=str, help="Path to directory with ESRGAN model file(s).", default=os.path.join(models_path, 'ESRGAN'))
-parser.add_argument("--bsrgan-models-path", type=str, help="Path to directory with BSRGAN model file(s).", default=os.path.join(models_path, 'BSRGAN'))
-parser.add_argument("--realesrgan-models-path", type=str, help="Path to directory with RealESRGAN model file(s).", default=os.path.join(models_path, 'RealESRGAN'))
-parser.add_argument("--clip-models-path", type=str, help="Path to directory with CLIP model file(s).", default=None)
-parser.add_argument("--xformers", action='store_true', help="enable xformers for cross attention layers")
-parser.add_argument("--force-enable-xformers", action='store_true', help="enable xformers for cross attention layers regardless of whether the checking code thinks you can run it; do not make bug reports if this fails to work")
-parser.add_argument("--xformers-flash-attention", action='store_true', help="enable xformers with Flash Attention to improve reproducibility (supported for SD2.x or variant only)")
-parser.add_argument("--deepdanbooru", action='store_true', help="does not do anything")
-parser.add_argument("--opt-split-attention", action='store_true', help="force-enables Doggettx's cross-attention layer optimization. By default, it's on for torch cuda.")
-parser.add_argument("--opt-sub-quad-attention", action='store_true', help="enable memory efficient sub-quadratic cross-attention layer optimization")
-parser.add_argument("--sub-quad-q-chunk-size", type=int, help="query chunk size for the sub-quadratic cross-attention layer optimization to use", default=1024)
-parser.add_argument("--sub-quad-kv-chunk-size", type=int, help="kv chunk size for the sub-quadratic cross-attention layer optimization to use", default=None)
-parser.add_argument("--sub-quad-chunk-threshold", type=int, help="the percentage of VRAM threshold for the sub-quadratic cross-attention layer optimization to use chunking", default=None)
-parser.add_argument("--opt-split-attention-invokeai", action='store_true', help="force-enables InvokeAI's cross-attention layer optimization. By default, it's on when cuda is unavailable.")
-parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")
-parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
-parser.add_argument("--disable-nan-check", action='store_true', help="do not check if produced images/latent spaces have nans; useful for running without a checkpoint in CI")
-parser.add_argument("--use-cpu", nargs='+', help="use CPU as torch device for specified modules", default=[], type=str.lower)
-parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")
-parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None)
-parser.add_argument("--show-negative-prompt", action='store_true', help="does not do anything", default=False)
-parser.add_argument("--ui-config-file", type=str, help="filename to use for ui configuration", default=os.path.join(data_path, 'ui-config.json'))
-parser.add_argument("--hide-ui-dir-config", action='store_true', help="hide directory configuration from webui", default=False)
-parser.add_argument("--freeze-settings", action='store_true', help="disable editing settings", default=False)
-parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(data_path, 'config.json'))
-parser.add_argument("--gradio-debug",  action='store_true', help="launch gradio with --debug option")
-parser.add_argument("--gradio-auth", type=str, help='set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None)
-parser.add_argument("--gradio-auth-path", type=str, help='set gradio authentication file path ex. "/path/to/auth/file" same auth format as --gradio-auth', default=None)
-parser.add_argument("--gradio-img2img-tool", type=str, help='does not do anything')
-parser.add_argument("--gradio-inpaint-tool", type=str, help="does not do anything")
-parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last")
-parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(data_path, 'styles.csv'))
-parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False)
-parser.add_argument("--theme", type=str, help="launches the UI with light or dark theme", default=None)
-parser.add_argument("--use-textbox-seed", action='store_true', help="use textbox for seeds in UI (no up/down, but possible to input long seeds)", default=False)
-parser.add_argument("--disable-console-progressbars", action='store_true', help="do not output progressbars to console", default=False)
-parser.add_argument("--enable-console-prompts", action='store_true', help="print prompts to console when generating with txt2img and img2img", default=False)
-parser.add_argument('--vae-path', type=str, help='Checkpoint to use as VAE; setting this argument disables all settings related to VAE', default=None)
-parser.add_argument("--disable-safe-unpickle", action='store_true', help="disable checking pytorch models for malicious code", default=False)
-parser.add_argument("--api", action='store_true', help="use api=True to launch the API together with the webui (use --nowebui instead for only the API)")
-parser.add_argument("--api-auth", type=str, help='Set authentication for API like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None)
-parser.add_argument("--api-log", action='store_true', help="use api-log=True to enable logging of all API requests")
-parser.add_argument("--nowebui", action='store_true', help="use api=True to launch the API instead of the webui")
-parser.add_argument("--ui-debug-mode", action='store_true', help="Don't load model to quickly launch UI")
-parser.add_argument("--device-id", type=str, help="Select the default CUDA device to use (export CUDA_VISIBLE_DEVICES=0,1,etc might be needed before)", default=None)
-parser.add_argument("--administrator", action='store_true', help="Administrator rights", default=False)
-parser.add_argument("--cors-allow-origins", type=str, help="Allowed CORS origin(s) in the form of a comma-separated list (no spaces)", default=None)
-parser.add_argument("--cors-allow-origins-regex", type=str, help="Allowed CORS origin(s) in the form of a single regular expression", default=None)
-parser.add_argument("--tls-keyfile", type=str, help="Partially enables TLS, requires --tls-certfile to fully function", default=None)
-parser.add_argument("--tls-certfile", type=str, help="Partially enables TLS, requires --tls-keyfile to fully function", default=None)
-parser.add_argument("--server-name", type=str, help="Sets hostname of server", default=None)
-parser.add_argument("--gradio-queue", action='store_true', help="Uses gradio queue; experimental option; breaks restart UI button")
-parser.add_argument("--skip-version-check", action='store_true', help="Do not check versions of torch and xformers")
-parser.add_argument("--no-hashing", action='store_true', help="disable sha256 hashing of checkpoints to help loading performance", default=False)
-parser.add_argument("--no-download-sd-model", action='store_true', help="don't download SD1.5 model even if no model is found in --ckpt-dir", default=False)
-
-
-script_loading.preload_extensions(extensions.extensions_dir, parser)
-script_loading.preload_extensions(extensions.extensions_builtin_dir, parser)
-
-cmd_opts = parser.parse_args()
-
-restricted_opts = {
-    "samples_filename_pattern",
-    "directories_filename_pattern",
-    "outdir_samples",
-    "outdir_txt2img_samples",
-    "outdir_img2img_samples",
-    "outdir_extras_samples",
-    "outdir_grids",
-    "outdir_txt2img_grids",
-    "outdir_save",
-}
-
-ui_reorder_categories = [
-    "inpaint",
-    "sampler",
-    "checkboxes",
-    "hires_fix",
-    "dimensions",
-    "cfg",
-    "seed",
-    "batch",
-    "override_settings",
-    "scripts",
-]
-
-cmd_opts.disable_extension_access = (cmd_opts.share or cmd_opts.listen or cmd_opts.server_name) and not cmd_opts.enable_insecure_extension_access
-
-devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_esrgan, devices.device_codeformer = \
-    (devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'esrgan', 'codeformer'])
-
-device = devices.device
-weight_load_location = None if cmd_opts.lowram else "cpu"
-
-batch_cond_uncond = cmd_opts.always_batch_cond_uncond or not (cmd_opts.lowvram or cmd_opts.medvram)
-parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram
-xformers_available = False
-config_filename = cmd_opts.ui_settings_file
-
-os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True)
-hypernetworks = {}
-loaded_hypernetworks = []
-
-
-def reload_hypernetworks():
-    from modules.hypernetworks import hypernetwork
-    global hypernetworks
-
-    hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir)
-
-
-class State:
-    skipped = False
-    interrupted = False
-    job = ""
-    job_no = 0
-    job_count = 0
-    processing_has_refined_job_count = False
-    job_timestamp = '0'
-    sampling_step = 0
-    sampling_steps = 0
-    current_latent = None
-    current_image = None
-    current_image_sampling_step = 0
-    id_live_preview = 0
-    textinfo = None
-    time_start = None
-    need_restart = False
-    server_start = None
-
-    def skip(self):
-        self.skipped = True
-
-    def interrupt(self):
-        self.interrupted = True
-
-    def nextjob(self):
-        if opts.live_previews_enable and opts.show_progress_every_n_steps == -1:
-            self.do_set_current_image()
-
-        self.job_no += 1
-        self.sampling_step = 0
-        self.current_image_sampling_step = 0
-
-    def dict(self):
-        obj = {
-            "skipped": self.skipped,
-            "interrupted": self.interrupted,
-            "job": self.job,
-            "job_count": self.job_count,
-            "job_timestamp": self.job_timestamp,
-            "job_no": self.job_no,
-            "sampling_step": self.sampling_step,
-            "sampling_steps": self.sampling_steps,
-        }
-
-        return obj
-
-    def begin(self):
-        self.sampling_step = 0
-        self.job_count = -1
-        self.processing_has_refined_job_count = False
-        self.job_no = 0
-        self.job_timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
-        self.current_latent = None
-        self.current_image = None
-        self.current_image_sampling_step = 0
-        self.id_live_preview = 0
-        self.skipped = False
-        self.interrupted = False
-        self.textinfo = None
-        self.time_start = time.time()
-
-        devices.torch_gc()
-
-    def end(self):
-        self.job = ""
-        self.job_count = 0
-
-        devices.torch_gc()
-
-    def set_current_image(self):
-        """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this"""
-        if not parallel_processing_allowed:
-            return
-
-        if self.sampling_step - self.current_image_sampling_step >= opts.show_progress_every_n_steps and opts.live_previews_enable and opts.show_progress_every_n_steps != -1:
-            self.do_set_current_image()
-
-    def do_set_current_image(self):
-        if self.current_latent is None:
-            return
-
-        import modules.sd_samplers
-        if opts.show_progress_grid:
-            self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent))
-        else:
-            self.assign_current_image(modules.sd_samplers.sample_to_image(self.current_latent))
-
-        self.current_image_sampling_step = self.sampling_step
-
-    def assign_current_image(self, image):
-        self.current_image = image
-        self.id_live_preview += 1
-
-
-state = State()
-state.server_start = time.time()
-
-styles_filename = cmd_opts.styles_file
-prompt_styles = modules.styles.StyleDatabase(styles_filename)
-
-interrogator = modules.interrogate.InterrogateModels("interrogate")
-
-face_restorers = []
-
-class OptionInfo:
-    def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None):
-        self.default = default
-        self.label = label
-        self.component = component
-        self.component_args = component_args
-        self.onchange = onchange
-        self.section = section
-        self.refresh = refresh
-
-
-def options_section(section_identifier, options_dict):
-    for k, v in options_dict.items():
-        v.section = section_identifier
-
-    return options_dict
-
-
-def list_checkpoint_tiles():
-    import modules.sd_models
-    return modules.sd_models.checkpoint_tiles()
-
-
-def refresh_checkpoints():
-    import modules.sd_models
-    return modules.sd_models.list_models()
-
-
-def list_samplers():
-    import modules.sd_samplers
-    return modules.sd_samplers.all_samplers
-
-
-hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config}
-
-options_templates = {}
-
-options_templates.update(options_section(('saving-images', "Saving images/grids"), {
-    "samples_save": OptionInfo(True, "Always save all generated images"),
-    "samples_format": OptionInfo('png', 'File format for images'),
-    "samples_filename_pattern": OptionInfo("", "Images filename pattern", component_args=hide_dirs),
-    "save_images_add_number": OptionInfo(True, "Add number to filename when saving", component_args=hide_dirs),
-
-    "grid_save": OptionInfo(True, "Always save all generated image grids"),
-    "grid_format": OptionInfo('png', 'File format for grids'),
-    "grid_extended_filename": OptionInfo(False, "Add extended info (seed, prompt) to filename when saving grid"),
-    "grid_only_if_multiple": OptionInfo(True, "Do not save grids consisting of one picture"),
-    "grid_prevent_empty_spots": OptionInfo(False, "Prevent empty spots in grid (when set to autodetect)"),
-    "n_rows": OptionInfo(-1, "Grid row count; use -1 for autodetect and 0 for it to be same as batch size", gr.Slider, {"minimum": -1, "maximum": 16, "step": 1}),
-
-    "enable_pnginfo": OptionInfo(True, "Save text information about generation parameters as chunks to png files"),
-    "save_txt": OptionInfo(False, "Create a text file next to every image with generation parameters."),
-    "save_images_before_face_restoration": OptionInfo(False, "Save a copy of image before doing face restoration."),
-    "save_images_before_highres_fix": OptionInfo(False, "Save a copy of image before applying highres fix."),
-    "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),
-    "jpeg_quality": OptionInfo(80, "Quality for saved jpeg images", gr.Slider, {"minimum": 1, "maximum": 100, "step": 1}),
-    "export_for_4chan": OptionInfo(True, "If the saved image file size is above the limit, or its either width or height are above the limit, save a downscaled copy as JPG"),
-    "img_downscale_threshold": OptionInfo(4.0, "File size limit for the above option, MB", gr.Number),
-    "target_side_length": OptionInfo(4000, "Width/height limit for the above option, in pixels", gr.Number),
-
-    "use_original_name_batch": OptionInfo(True, "Use original name for output filename during batch process in extras tab"),
-    "use_upscaler_name_as_suffix": OptionInfo(False, "Use upscaler name as filename suffix in the extras tab"),
-    "save_selected_only": OptionInfo(True, "When using 'Save' button, only save a single selected image"),
-    "do_not_add_watermark": OptionInfo(False, "Do not add watermark to images"),
-
-    "temp_dir":  OptionInfo("", "Directory for temporary images; leave empty for default"),
-    "clean_temp_dir_at_start": OptionInfo(False, "Cleanup non-default temporary directory when starting webui"),
-
-}))
-
-options_templates.update(options_section(('saving-paths', "Paths for saving"), {
-    "outdir_samples": OptionInfo("", "Output directory for images; if empty, defaults to three directories below", component_args=hide_dirs),
-    "outdir_txt2img_samples": OptionInfo("outputs/txt2img-images", 'Output directory for txt2img images', component_args=hide_dirs),
-    "outdir_img2img_samples": OptionInfo("outputs/img2img-images", 'Output directory for img2img images', component_args=hide_dirs),
-    "outdir_extras_samples": OptionInfo("outputs/extras-images", 'Output directory for images from extras tab', component_args=hide_dirs),
-    "outdir_grids": OptionInfo("", "Output directory for grids; if empty, defaults to two directories below", component_args=hide_dirs),
-    "outdir_txt2img_grids": OptionInfo("outputs/txt2img-grids", 'Output directory for txt2img grids', component_args=hide_dirs),
-    "outdir_img2img_grids": OptionInfo("outputs/img2img-grids", 'Output directory for img2img grids', component_args=hide_dirs),
-    "outdir_save": OptionInfo("log/images", "Directory for saving images using the Save button", component_args=hide_dirs),
-}))
-
-options_templates.update(options_section(('saving-to-dirs', "Saving to a directory"), {
-    "save_to_dirs": OptionInfo(True, "Save images to a subdirectory"),
-    "grid_save_to_dirs": OptionInfo(True, "Save grids to a subdirectory"),
-    "use_save_to_dirs_for_ui": OptionInfo(False, "When using \"Save\" button, save images to a subdirectory"),
-    "directories_filename_pattern": OptionInfo("[date]", "Directory name pattern", component_args=hide_dirs),
-    "directories_max_prompt_words": OptionInfo(8, "Max prompt words for [prompt_words] pattern", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1, **hide_dirs}),
-}))
-
-options_templates.update(options_section(('upscaling', "Upscaling"), {
-    "ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}),
-    "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for ESRGAN upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
-    "realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI. (Requires restart)", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}),
-    "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}),
-}))
-
-options_templates.update(options_section(('face-restoration', "Face restoration"), {
-    "face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}),
-    "code_former_weight": OptionInfo(0.5, "CodeFormer weight parameter; 0 = maximum effect; 1 = minimum effect", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
-    "face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"),
-}))
-
-options_templates.update(options_section(('system', "System"), {
-    "show_warnings": OptionInfo(False, "Show warnings in console."),
-    "memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation. Set to 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}),
-    "samples_log_stdout": OptionInfo(False, "Always print all generation info to standard output"),
-    "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."),
-    "print_hypernet_extra": OptionInfo(False, "Print extra hypernetwork information to console."),
-}))
-
-options_templates.update(options_section(('training', "Training"), {
-    "unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training if possible. Saves VRAM."),
-    "pin_memory": OptionInfo(False, "Turn on pin_memory for DataLoader. Makes training slightly faster but can increase memory usage."),
-    "save_optimizer_state": OptionInfo(False, "Saves Optimizer state as separate *.optim file. Training of embedding or HN can be resumed with the matching optim file."),
-    "save_training_settings_to_txt": OptionInfo(True, "Save textual inversion and hypernet settings to a text file whenever training starts."),
-    "dataset_filename_word_regex": OptionInfo("", "Filename word regex"),
-    "dataset_filename_join_string": OptionInfo(" ", "Filename join string"),
-    "training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}),
-    "training_write_csv_every": OptionInfo(500, "Save an csv containing the loss to log directory every N steps, 0 to disable"),
-    "training_xattention_optimizations": OptionInfo(False, "Use cross attention optimizations while training"),
-    "training_enable_tensorboard": OptionInfo(False, "Enable tensorboard logging."),
-    "training_tensorboard_save_images": OptionInfo(False, "Save generated images within tensorboard."),
-    "training_tensorboard_flush_every": OptionInfo(120, "How often, in seconds, to flush the pending tensorboard events and summaries to disk."),
-}))
-
-options_templates.update(options_section(('sd', "Stable Diffusion"), {
-    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints),
-    "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
-    "sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
-    "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list),
-    "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"),
-    "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
-    "initial_noise_multiplier": OptionInfo(1.0, "Noise multiplier for img2img", gr.Slider, {"minimum": 0.5, "maximum": 1.5, "step": 0.01}),
-    "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
-    "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising)."),
-    "img2img_background_color": OptionInfo("#ffffff", "With img2img, fill image's transparent parts with this color.", ui_components.FormColorPicker, {}),
-    "enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds. Requires restart to apply."),
-    "enable_emphasis": OptionInfo(True, "Emphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention"),
-    "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"),
-    "comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }),
-    "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),
-    "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"),
-}))
-
-options_templates.update(options_section(('compatibility', "Compatibility"), {
-    "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),
-    "use_old_karras_scheduler_sigmas": OptionInfo(False, "Use old karras scheduler sigmas (0.1 to 10)."),
-    "no_dpmpp_sde_batch_determinism": OptionInfo(False, "Do not make DPM++ SDE deterministic across different batch sizes."),
-    "use_old_hires_fix_width_height": OptionInfo(False, "For hires fix, use width/height sliders to set final resolution rather than first pass (disables Upscale by, Resize width/height to)."),
-}))
-
-options_templates.update(options_section(('interrogate', "Interrogate Options"), {
-    "interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"),
-    "interrogate_return_ranks": OptionInfo(False, "Interrogate: include ranks of model tags matches in results (Has no effect on caption-based interrogators)."),
-    "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}),
-    "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),
-    "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
-    "interrogate_clip_dict_limit": OptionInfo(1500, "CLIP: maximum number of lines in text file (0 = No limit)"),
-    "interrogate_clip_skip_categories": OptionInfo([], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": modules.interrogate.category_types()}, refresh=modules.interrogate.category_types),
-    "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
-    "deepbooru_sort_alpha": OptionInfo(True, "Interrogate: deepbooru sort alphabetically"),
-    "deepbooru_use_spaces": OptionInfo(False, "use spaces for tags in deepbooru"),
-    "deepbooru_escape": OptionInfo(True, "escape (\\) brackets in deepbooru (so they are used as literal brackets and not for emphasis)"),
-    "deepbooru_filter_tags": OptionInfo("", "filter out those tags from deepbooru output (separated by comma)"),
-}))
-
-options_templates.update(options_section(('extra_networks', "Extra Networks"), {
-    "extra_networks_default_view": OptionInfo("cards", "Default view for Extra Networks", gr.Dropdown, {"choices": ["cards", "thumbs"]}),
-    "extra_networks_default_multiplier": OptionInfo(1.0, "Multiplier for extra networks", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
-    "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": [""] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
-}))
-
-options_templates.update(options_section(('ui', "User interface"), {
-    "return_grid": OptionInfo(True, "Show grid in results for web"),
-    "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),
-    "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),
-    "add_model_name_to_info": OptionInfo(True, "Add model name to generation information"),
-    "disable_weights_auto_swap": OptionInfo(True, "When reading generation parameters from text into UI (from PNG info or pasted text), do not change the selected model/checkpoint."),
-    "send_seed": OptionInfo(True, "Send seed when sending prompt or image to other interface"),
-    "send_size": OptionInfo(True, "Send size when sending prompt or image to another interface"),
-    "font": OptionInfo("", "Font for image grids that have text"),
-    "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"),
-    "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"),
-    "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."),
-    "samplers_in_dropdown": OptionInfo(True, "Use dropdown for sampler selection instead of radio group"),
-    "dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row"),
-    "keyedit_precision_attention": OptionInfo(0.1, "Ctrl+up/down precision when editing (attention:1.1)", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
-    "keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing <extra networks:0.9>", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
-    "quicksettings": OptionInfo("sd_model_checkpoint", "Quicksettings list"),
-    "ui_reorder": OptionInfo(", ".join(ui_reorder_categories), "txt2img/img2img UI item order"),
-    "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order"),
-    "localization": OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)),
-}))
-
-options_templates.update(options_section(('ui', "Live previews"), {
-    "show_progressbar": OptionInfo(True, "Show progressbar"),
-    "live_previews_enable": OptionInfo(True, "Show live previews of the created image"),
-    "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"),
-    "show_progress_every_n_steps": OptionInfo(10, "Show new live preview image every N sampling steps. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}),
-    "show_progress_type": OptionInfo("Approx NN", "Image creation progress preview mode", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}),
-    "live_preview_content": OptionInfo("Prompt", "Live preview subject", gr.Radio, {"choices": ["Combined", "Prompt", "Negative prompt"]}),
-    "live_preview_refresh_period": OptionInfo(1000, "Progressbar/preview update period, in milliseconds")
-}))
-
-options_templates.update(options_section(('sampler-params', "Sampler parameters"), {
-    "hide_samplers": OptionInfo([], "Hide samplers in user interface (requires restart)", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}),
-    "eta_ddim": OptionInfo(0.0, "eta (noise multiplier) for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
-    "eta_ancestral": OptionInfo(1.0, "eta (noise multiplier) for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
-    "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}),
-    's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
-    's_tmin':  OptionInfo(0.0, "sigma tmin",  gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
-    's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
-    'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}),
-    'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma"),
-}))
-
-options_templates.update(options_section(('postprocessing', "Postprocessing"), {
-    'postprocessing_enable_in_main_ui': OptionInfo([], "Enable postprocessing operations in txt2img and img2img tabs", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts()]}),
-    'postprocessing_operation_order': OptionInfo([], "Postprocessing operation order", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts()]}),
-    'upscaling_max_images_in_cache': OptionInfo(5, "Maximum number of images in upscaling cache", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
-}))
-
-options_templates.update(options_section((None, "Hidden options"), {
-    "disabled_extensions": OptionInfo([], "Disable those extensions"),
-    "sd_checkpoint_hash": OptionInfo("", "SHA256 hash of the current checkpoint"),
-}))
-
-options_templates.update()
-
-
-class Options:
-    data = None
-    data_labels = options_templates
-    typemap = {int: float}
-
-    def __init__(self):
-        self.data = {k: v.default for k, v in self.data_labels.items()}
-
-    def __setattr__(self, key, value):
-        if self.data is not None:
-            if key in self.data or key in self.data_labels:
-                assert not cmd_opts.freeze_settings, "changing settings is disabled"
-
-                info = opts.data_labels.get(key, None)
-                comp_args = info.component_args if info else None
-                if isinstance(comp_args, dict) and comp_args.get('visible', True) is False:
-                    raise RuntimeError(f"not possible to set {key} because it is restricted")
-
-                if cmd_opts.hide_ui_dir_config and key in restricted_opts:
-                    raise RuntimeError(f"not possible to set {key} because it is restricted")
-
-                self.data[key] = value
-                return
-
-        return super(Options, self).__setattr__(key, value)
-
-    def __getattr__(self, item):
-        if self.data is not None:
-            if item in self.data:
-                return self.data[item]
-
-        if item in self.data_labels:
-            return self.data_labels[item].default
-
-        return super(Options, self).__getattribute__(item)
-
-    def set(self, key, value):
-        """sets an option and calls its onchange callback, returning True if the option changed and False otherwise"""
-
-        oldval = self.data.get(key, None)
-        if oldval == value:
-            return False
-
-        try:
-            setattr(self, key, value)
-        except RuntimeError:
-            return False
-
-        if self.data_labels[key].onchange is not None:
-            try:
-                self.data_labels[key].onchange()
-            except Exception as e:
-                errors.display(e, f"changing setting {key} to {value}")
-                setattr(self, key, oldval)
-                return False
-
-        return True
-
-    def save(self, filename):
-        assert not cmd_opts.freeze_settings, "saving settings is disabled"
-
-        with open(filename, "w", encoding="utf8") as file:
-            json.dump(self.data, file, indent=4)
-
-    def same_type(self, x, y):
-        if x is None or y is None:
-            return True
-
-        type_x = self.typemap.get(type(x), type(x))
-        type_y = self.typemap.get(type(y), type(y))
-
-        return type_x == type_y
-
-    def load(self, filename):
-        with open(filename, "r", encoding="utf8") as file:
-            self.data = json.load(file)
-
-        bad_settings = 0
-        for k, v in self.data.items():
-            info = self.data_labels.get(k, None)
-            if info is not None and not self.same_type(info.default, v):
-                print(f"Warning: bad setting value: {k}: {v} ({type(v).__name__}; expected {type(info.default).__name__})", file=sys.stderr)
-                bad_settings += 1
-
-        if bad_settings > 0:
-            print(f"The program is likely to not work with bad settings.\nSettings file: {filename}\nEither fix the file, or delete it and restart.", file=sys.stderr)
-
-    def onchange(self, key, func, call=True):
-        item = self.data_labels.get(key)
-        item.onchange = func
-
-        if call:
-            func()
-
-    def dumpjson(self):
-        d = {k: self.data.get(k, self.data_labels.get(k).default) for k in self.data_labels.keys()}
-        return json.dumps(d)
-
-    def add_option(self, key, info):
-        self.data_labels[key] = info
-
-    def reorder(self):
-        """reorder settings so that all items related to section always go together"""
-
-        section_ids = {}
-        settings_items = self.data_labels.items()
-        for k, item in settings_items:
-            if item.section not in section_ids:
-                section_ids[item.section] = len(section_ids)
-
-        self.data_labels = {k: v for k, v in sorted(settings_items, key=lambda x: section_ids[x[1].section])}
-
-    def cast_value(self, key, value):
-        """casts an arbitrary to the same type as this setting's value with key
-        Example: cast_value("eta_noise_seed_delta", "12") -> returns 12 (an int rather than str)
-        """
-
-        if value is None:
-            return None
-
-        default_value = self.data_labels[key].default
-        if default_value is None:
-            default_value = getattr(self, key, None)
-        if default_value is None:
-            return None
-
-        expected_type = type(default_value)
-        if expected_type == bool and value == "False":
-            value = False
-        else:
-            value = expected_type(value)
-
-        return value
-
-
-
-opts = Options()
-if os.path.exists(config_filename):
-    opts.load(config_filename)
-
-settings_components = None
-"""assinged from ui.py, a mapping on setting anmes to gradio components repsponsible for those settings"""
-
-latent_upscale_default_mode = "Latent"
-latent_upscale_modes = {
-    "Latent": {"mode": "bilinear", "antialias": False},
-    "Latent (antialiased)": {"mode": "bilinear", "antialias": True},
-    "Latent (bicubic)": {"mode": "bicubic", "antialias": False},
-    "Latent (bicubic antialiased)": {"mode": "bicubic", "antialias": True},
-    "Latent (nearest)": {"mode": "nearest", "antialias": False},
-    "Latent (nearest-exact)": {"mode": "nearest-exact", "antialias": False},
-}
-
-sd_upscalers = []
-
-sd_model = None
-
-clip_model = None
-
-progress_print_out = sys.stdout
-
-
-class TotalTQDM:
-    def __init__(self):
-        self._tqdm = None
-
-    def reset(self):
-        self._tqdm = tqdm.tqdm(
-            desc="Total progress",
-            total=state.job_count * state.sampling_steps,
-            position=1,
-            file=progress_print_out
-        )
-
-    def update(self):
-        if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars:
-            return
-        if self._tqdm is None:
-            self.reset()
-        self._tqdm.update()
-
-    def updateTotal(self, new_total):
-        if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars:
-            return
-        if self._tqdm is None:
-            self.reset()
-        self._tqdm.total = new_total
-
-    def clear(self):
-        if self._tqdm is not None:
-            self._tqdm.close()
-            self._tqdm = None
-
-
-total_tqdm = TotalTQDM()
-
-mem_mon = modules.memmon.MemUsageMonitor("MemMon", device, opts)
-mem_mon.start()
-
-
-def listfiles(dirname):
-    filenames = [os.path.join(dirname, x) for x in sorted(os.listdir(dirname)) if not x.startswith(".")]
-    return [file for file in filenames if os.path.isfile(file)]
-
-
-def html_path(filename):
-    return os.path.join(script_path, "html", filename)
-
-
-def html(filename):
-    path = html_path(filename)
-
-    if os.path.exists(path):
-        with open(path, encoding="utf8") as file:
-            return file.read()
-
-    return ""
diff --git a/spaces/bioriAsaeru/text-to-voice/Download Rute Openbve Indonesia Bandung BEST.md b/spaces/bioriAsaeru/text-to-voice/Download Rute Openbve Indonesia Bandung BEST.md
deleted file mode 100644
index bd4a481f686aaf5c6f6bca4e2f152f682dcc934c..0000000000000000000000000000000000000000
--- a/spaces/bioriAsaeru/text-to-voice/Download Rute Openbve Indonesia Bandung BEST.md	
+++ /dev/null
@@ -1,26 +0,0 @@
-<br />
-<h1>How to Download Rute Openbve Indonesia Bandung</h1>
-<p>Rute Openbve Indonesia Bandung is a simulation of the train route between Jakarta and Bandung, two major cities in Indonesia. This route is popular among train enthusiasts and travelers who want to enjoy the scenic views of the countryside and avoid the traffic congestion. If you want to download this route for your Openbve train simulator, here are some steps you need to follow:</p>
-<ol>
-<li>Visit the website of <a href="https://openbve.wixsite.com/openbve/routes-for-indonesia">Openbve</a>, which is a free and open source train simulator that supports various routes and trains from around the world.</li>
-<li>Scroll down to the section "Routes for Indonesia" and look for the route "Padalarang - Cianjur - Sukabumi" [^1^]. This is the closest route to Bandung that is available on the website.</li>
-<li>Click on the image of the route to download the zip file. You may need to extract the file using a program like WinRAR or 7-Zip.</li>
-<li>Copy the folder "Padalarang - Cianjur - Sukabumi" to your Openbve installation directory, usually located at C:\Program Files (x86)\OpenBVE\Railway\Route.</li>
-<li>Launch Openbve and select "Start new game". Choose "Padalarang - Cianjur - Sukabumi" as your route and select a train of your choice. You can also adjust the settings such as time, weather, and difficulty.</li>
-<li>Enjoy your ride from Padalarang to Sukabumi, passing through Cianjur and Bandung along the way. You can use the keyboard or mouse to control the train, or use a joystick or gamepad if you have one.</li>
-</ol>
-<p>If you want more routes and trains for Openbve Indonesia, you can also visit other websites such as <a href="https://routefikrirf06.blogspot.com/">Rute OpenBVE by FikriRF06</a> [^2^], <a href="https://aesthetic-addons.webs.com/rute-objek-special-unit">Aesthetic add-ons</a> [^3^], or <a href="https://sway.office.com/0kyobGtFQ7xI80xe">Download Rute Openbve Indonesia Bandung</a> [^5^]. However, these websites may not be updated regularly or may have broken links, so download at your own risk.</p>
-<h2>Download Rute Openbve Indonesia Bandung</h2><br /><p><b><b>Download Zip</b> &raquo;&raquo;&raquo; <a href="https://urloso.com/2uyQtV">https://urloso.com/2uyQtV</a></b></p><br /><br />
-<p>We hope this article has helped you to download Rute Openbve Indonesia Bandung and enjoy the simulation of this beautiful train route. Have fun!</p>
-
-<p>If you are wondering what you can see and do along the Rute Openbve Indonesia Bandung, here are some suggestions:</p>
-<ul>
-<li>Padalarang: This is the starting point of the route and a small town in West Java. You can visit the Padalarang Lake, which is a man-made lake that offers fishing and boating activities. You can also see the Padalarang Bridge, which is a historical landmark that was built during the Dutch colonial era.</li>
-<li>Cianjur: This is a city that is known for its agriculture and handicrafts. You can visit the Cianjur Regency Museum, which displays various artifacts and exhibits related to the history and culture of Cianjur. You can also shop for local products such as batik, bamboo, and leather goods at the Cianjur Market.</li>
-<li>Bandung: This is the capital city of West Java and a popular tourist destination. You can visit the Gedung Sate, which is a government building that has a distinctive roof that resembles a skewer of meat. You can also visit the Tangkuban Perahu, which is an active volcano that has a crater lake and hot springs. You can also enjoy the nightlife and entertainment options at the Braga Street, which is lined with cafes, bars, and restaurants.</li>
-<li>Sukabumi: This is the end point of the route and a city that is surrounded by mountains and forests. You can visit the Sukabumi Botanical Garden, which has a collection of plants and flowers from various regions. You can also visit the Situ Gunung Lake, which is a natural lake that has a suspension bridge and a waterfall. You can also try some local delicacies such as soto mie, which is a noodle soup with beef and vegetables.</li>
-</ul>
-<p>These are some of the attractions and activities that you can enjoy along the Rute Openbve Indonesia Bandung. Of course, there are many more things to see and do in these places, so feel free to explore and discover them on your own. We hope you have a wonderful journey!</p>
-<p></p> d5da3c52bf<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/bioriAsaeru/text-to-voice/Ecap camera software download free  le logiciel gratuit pour utiliser votre webcam Acer.md b/spaces/bioriAsaeru/text-to-voice/Ecap camera software download free  le logiciel gratuit pour utiliser votre webcam Acer.md
deleted file mode 100644
index f679e051aeb9d10376551f6a10ff2c2b82510f61..0000000000000000000000000000000000000000
--- a/spaces/bioriAsaeru/text-to-voice/Ecap camera software download free  le logiciel gratuit pour utiliser votre webcam Acer.md	
+++ /dev/null
@@ -1,25 +0,0 @@
-<br />
-<p>It is ground under a modern platform, does not enter the program conflict, perfectly interacts with system software, does not prevent the user from performing other operations. A Russian version is available. To get the desired result, just select the commands from the menu. You can free download ECap official latest version for Windows 10 in English.</p>
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-<p>The interface is available, simple controls. The tools are at the top, on a special panel. To use the utility is easy and inexperienced users. The settings are minimal, but they allow you to set the format with video quality. You can free download ECap official latest version for Windows 8.1 in English.</p>
-<p>With the program, you can shoot entertainment content, share it with friends, browse online, upload to popular video hosting sites and social networks. She suggests choosing the quality and format of the recorded material. Thus, fine tuning is performed to the needs of a particular user, and he has no doubt about what he gets at the output. You can free download ECap official latest version for Windows 7 in English.</p>
-<p>The functionality of the utility includes the ability to change the recording resolution and frame rate, the settings of the audio signal used, the conversion method and the place where the clip is saved. The program has an intuitive user interface, can run in the background and run from any media, uses a combination of hot keys and consumes a minimum of system resources. You can free download ECap official latest version for Windows 8 in English.</p>
-<p>Logitech Capture is among the few free webcam recording software for Windows 10 with studio controls applicable during recording. You can use this feature to adjust your image, create frames, adjust focus and transitions, and enable ChromaKey as you record.</p>
-<p>YouCam is the best free webcam software Windows 10 for YouTubers, business professionals, Streamers, home users, and Vloggers. It seamlessly integrates with live streaming media channels like Twitch, Wirecast, OBS Studio, Facebook Live, Xsplit, and YouTube Live.</p>
-<p></p>
-<p>Debut Video Capture is the only free webcam recording software for Windows 10 believed to capture or record videos from any external source. It has also preset settings for HD and TV with pre-production enhancement features like color adjustment settings, overlay buttons and frame rate, aspect ratio, and resolution settings.</p>
-<p>YAWCAM is an absolutely free webcam software windows 10. Why is it the simplest software to use? Just download and you will find all features on one page. Simple language commands aligned in a drop-down menu ready to be used with only one click.</p>
-<p>Some of the best features include overlay texts and images, scheduler, motion detection, and an inbuilt webserver. For you to use this webcam software, use these supported devices; DirectX compatible webcams, DV-camera, or video capture devices.</p>
-<p>IP Camera Viewer is the most used free webcam recording software for windows 10 as its compatible with almost all IP camera models like Panasonic, Toshiba, Canon, D-Link, Sony, and more the 2000 others. With the capability of viewing and controlling 4 camera feeds at once, you can use this software to monitor your entire compound.</p>
-<p>A webcam is a video camera that feeds or streams images or video in real-time to or over a computer network. And webcam software enables users to record video or stream video over the Internet.<br />Webcam software is an application that allows you to capture video from your laptop/desktop webcam and record or stream video over the Internet. You can use them to deliver professional videos, streaming, and online courses easily.</p>
-<p>Windows 10 has an in-built webcam app called Camera that lets you record videos and take pictures with your webcam. This is definitely better than downloading 3rd party webcam recording software where spyware/malware is rampant.</p>
-<p>According to some users, there are free webcam software Windows 10 that more often would not show any video images but the audio is absolutely clear. To help your fellow user, what bad experience have you ever had after recording a game using webcam software? Kindly share your comment or suggestion on our social media platforms.</p>
-<p>The software can be used to record high-quality multimedia through the front-facing PC camera. Even inexperienced users will cope with the utility. The workflow consists of several stages: setting the picture parameters, choosing the format of the final project. The result can be saved on the HDD, sent to a social network or put in the video sharing profile. You can free download ECap official latest version for Windows XP in English.</p>
-<p>The Camera for Windows 10 is the most recent iteration of the Windows camera software. It is not the same software that you get with Windows 10 when you download it. This is camera software that works as an alternative to your current software.</p>
-<p>This software is free and Microsoft developed it. It was not created to be state-of-the-art it was created either as a rudimentary camera program or as an alternative to your current software. The Camera for Windows 10 software will allow you to use your video/webcam to take a photo. You may use this software on your Xbox One on your PC on your Windows phone or Windows tablet. The symbols for each function are self-explanatory. For example the torch means flash or no flash the camera icon and an arrow around it stands for the image orientation. The icons are self-explanatory which helps to make using the software very intuitive.</p>
-<p>One of the most recent updates to the Camera for Windows 10 is that it allows you to take video as well as photo images. If you have a web camera or if your device has a camera you may use this software instead of the device's preloaded software. It isn't sophisticated. It is a basic and efficient program that allows you to take videos and images.</p>
-<p><strong>AMCap</strong> is an easy-to-use <strong>image and video capture program</strong>, which lets you record the screen with a webcam. Designed and developed by Noel Danjou, the tool provides you with several <strong>advanced video settings and recording options</strong>. For instance, you can use the program to change the frame rate, compression, and output size. Additionally, the <strong>screen recorder</strong> lets you capture audio, and can even connect to third-party cameras. With <strong>AMCap download</strong>, you can try the demo version. Unfortunately, it comes with limited video settings and watermarks on images. Since it still offers image capture and video capture features, you could use the demo version before moving on to the full version of the software.</p>
-<p><strong>ASUS Lifeframe</strong> is a software utility that comes pre-installed on many ASUS systems, primarily laptops because they come with a built-in webcam. The software package allows you to do many image (still or video) capture, editing, effect, and publication capabilities. ASUS Life Frame provides user to operate camcorder, monitor, game, voice recorder, camera and preview recreational functions by built-in camera and microphone modules.</p>
-<p>Features of ASUS LifeFrame<li><strong>Audio Recording</strong>: Capture audio from your laptop. </li><li><strong>Face Login</strong>: Log in to your laptop with facial recognition. </li><li><strong>Multi-Camera Support</strong>: Connect up to 4 cameras to your laptop. </li><li><strong>Photo Capturing</strong>: Take pictures with your laptop's built-in camera. </li><li><strong>Remote Access</strong>: Connect and monitor your laptop from anywhere. </li><li><strong>Screen Capture</strong>: Take screenshots with ease. </li><li><strong>Security</strong>: Protect your laptop with password protection. </li><li><strong>Sharing</strong>: Easily share your photos and videos. </li><li><strong>Surveillance</strong>: Monitor your laptop and surroundings with motion detection. </li><li><strong>Time-lapse Recording</strong>: Record time-lapse video from your laptop. </li><li><strong>Video Effects</strong>: Enhance your videos with special effects. </li><li><strong>Video Playback</strong>: Playback recorded videos. </li><li><strong>Video Recording</strong>: Record video from your laptop. </li><li><strong>Video Trimming</strong>: Trim videos for sharing. </li></ul>Compatibility and LicenseASUS LifeFrame is provided under a freeware license on Windows from webcam tools with no restrictions on usage. Download and installation of this PC software is free and 3.1.13 is the latest version last time we checked.</p> aaccfb2cb3<br />
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-<br />
\ No newline at end of file
diff --git a/spaces/bioriAsaeru/text-to-voice/Grim Fandango Download Ita Pc UPD.md b/spaces/bioriAsaeru/text-to-voice/Grim Fandango Download Ita Pc UPD.md
deleted file mode 100644
index d82fb687674ebc2d97f053de985954663a73ea34..0000000000000000000000000000000000000000
--- a/spaces/bioriAsaeru/text-to-voice/Grim Fandango Download Ita Pc UPD.md	
+++ /dev/null
@@ -1,7 +0,0 @@
-
-<p>so what exactly is it that you get out of grim fandango? well, it's all about the story. of course, we all know what happens to manny, but this is not really the point of the game. the point of the game is to use your wits to figure out how to control the story. this means that the game is broken down into locations. each location has a set of activities, which you can perform once you reach it. there are a total of four locations, all of which have a set of activities for you to perform. in addition, if you can figure out a specific set of events, you'll be rewarded with a bonus.</p>
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-<p><p>grim fandango remastered - live classics-class quests. unforgettable characters and a great atmosphere come back to you, but now mobile devices. you have to play as manuel calavera - travel agent to the light which will push any product that will ease the way sinful soul to reach his goal. at one point he comes across a new visitor who can't even gather up his usual car, and how you can work in such conditions as before you will find a stunning plot, dizzying adventures in the afterlife and the unique atmosphere of the games of the past generation.</p>
-<p>anyhow, the point is that grim fandango is now a point-and-click adventure title. so, what are the pros and cons? for starters, it takes some getting used to. manny is an absolute delight to control, and the way he's been designed means you don't have to think too hard about making him move. it's like having a big-screened, head-on view of the game. at the same time, however, it's a little bit limiting. you have direct control of the hero and his movements, but there are no 'objective' tasks to be completed. you can solve puzzles, yes - but there's no key to a locked door or an important diary to find - you just have to walk over to it, and manny will do the rest. this, combined with the lack of an interface, means there's not the same sense of progression through the game. you may have a task in mind - such as finding a particular character - but you never know when you'll be able to complete it. it's essentially a free-roaming game, with all the attendant problems that entails - and the game is beautifully atmospheric, but that's often as far as the lucasarts' style can take you.</p> 899543212b<br />
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diff --git a/spaces/bioriAsaeru/text-to-voice/Kaalia Movie Hindi Dubbed Download 720p Hd [NEW].md b/spaces/bioriAsaeru/text-to-voice/Kaalia Movie Hindi Dubbed Download 720p Hd [NEW].md
deleted file mode 100644
index 810b1a2789187e042c8c46c808e0aec414e99153..0000000000000000000000000000000000000000
--- a/spaces/bioriAsaeru/text-to-voice/Kaalia Movie Hindi Dubbed Download 720p Hd [NEW].md	
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diff --git a/spaces/brjathu/HMR2.0/vendor/detectron2/docs/notes/changelog.md b/spaces/brjathu/HMR2.0/vendor/detectron2/docs/notes/changelog.md
deleted file mode 100644
index 000e9f8898dba53f54121a5325ba5165e45ddea2..0000000000000000000000000000000000000000
--- a/spaces/brjathu/HMR2.0/vendor/detectron2/docs/notes/changelog.md
+++ /dev/null
@@ -1,48 +0,0 @@
-# Change Log and Backward Compatibility
-
-### Releases
-See release logs at
-[https://github.com/facebookresearch/detectron2/releases](https://github.com/facebookresearch/detectron2/releases)
-for new updates.
-
-### Backward Compatibility
-
-Due to the research nature of what the library does, there might be backward incompatible changes.
-But we try to reduce users' disruption by the following ways:
-* APIs listed in [API documentation](https://detectron2.readthedocs.io/modules/index.html), including
-  function/class names, their arguments, and documented class attributes, are considered *stable* unless
-  otherwise noted in the documentation.
-  They are less likely to be broken, but if needed, will trigger a deprecation warning for a reasonable period
-  before getting broken, and will be documented in release logs.
-* Others functions/classses/attributes are considered internal, and are more likely to change.
-  However, we're aware that some of them may be already used by other projects, and in particular we may
-  use them for convenience among projects under `detectron2/projects`.
-  For such APIs, we may treat them as stable APIs and also apply the above strategies.
-  They may be promoted to stable when we're ready.
-* Projects under "detectron2/projects" or imported with "detectron2.projects" are research projects
-  and are all considered experimental.
-* Classes/functions that contain the word "default" or are explicitly documented to produce
-  "default behavior" may change their behaviors when new features are added.
-
-Despite of the possible breakage, if a third-party project would like to keep up with the latest updates
-in detectron2, using it as a library will still be less disruptive than forking, because
-the frequency and scope of API changes will be much smaller than code changes.
-
-To see such changes, search for "incompatible changes" in [release logs](https://github.com/facebookresearch/detectron2/releases).
-
-### Config Version Change Log
-
-Detectron2's config version has not been changed since open source.
-There is no need for an open source user to worry about this.
-
-* v1: Rename `RPN_HEAD.NAME` to `RPN.HEAD_NAME`.
-* v2: A batch of rename of many configurations before release.
-
-### Silent Regressions in Historical Versions:
-
-We list a few silent regressions, since they may silently produce incorrect results and will be hard to debug.
-
-* 04/01/2020 - 05/11/2020: Bad accuracy if `TRAIN_ON_PRED_BOXES` is set to True.
-* 03/30/2020 - 04/01/2020: ResNets are not correctly built.
-* 12/19/2019 - 12/26/2019: Using aspect ratio grouping causes a drop in accuracy.
-* - 11/9/2019: Test time augmentation does not predict the last category.
diff --git a/spaces/brjathu/HMR2.0/vendor/detectron2/tests/modeling/test_roi_pooler.py b/spaces/brjathu/HMR2.0/vendor/detectron2/tests/modeling/test_roi_pooler.py
deleted file mode 100644
index e1d7c1c689cad32d8b8566e5d497341a5f3f5a36..0000000000000000000000000000000000000000
--- a/spaces/brjathu/HMR2.0/vendor/detectron2/tests/modeling/test_roi_pooler.py
+++ /dev/null
@@ -1,165 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-import logging
-import unittest
-import torch
-
-from detectron2.modeling.poolers import ROIPooler
-from detectron2.structures import Boxes, RotatedBoxes
-from detectron2.utils.testing import random_boxes
-
-logger = logging.getLogger(__name__)
-
-
-class TestROIPooler(unittest.TestCase):
-    def _test_roialignv2_roialignrotated_match(self, device):
-        pooler_resolution = 14
-        canonical_level = 4
-        canonical_scale_factor = 2**canonical_level
-        pooler_scales = (1.0 / canonical_scale_factor,)
-        sampling_ratio = 0
-
-        N, C, H, W = 2, 4, 10, 8
-        N_rois = 10
-        std = 11
-        mean = 0
-        feature = (torch.rand(N, C, H, W) - 0.5) * 2 * std + mean
-
-        features = [feature.to(device)]
-
-        rois = []
-        rois_rotated = []
-        for _ in range(N):
-            boxes = random_boxes(N_rois, W * canonical_scale_factor)
-            rotated_boxes = torch.zeros(N_rois, 5)
-            rotated_boxes[:, 0] = (boxes[:, 0] + boxes[:, 2]) / 2.0
-            rotated_boxes[:, 1] = (boxes[:, 1] + boxes[:, 3]) / 2.0
-            rotated_boxes[:, 2] = boxes[:, 2] - boxes[:, 0]
-            rotated_boxes[:, 3] = boxes[:, 3] - boxes[:, 1]
-            rois.append(Boxes(boxes).to(device))
-            rois_rotated.append(RotatedBoxes(rotated_boxes).to(device))
-
-        roialignv2_pooler = ROIPooler(
-            output_size=pooler_resolution,
-            scales=pooler_scales,
-            sampling_ratio=sampling_ratio,
-            pooler_type="ROIAlignV2",
-        )
-
-        roialignv2_out = roialignv2_pooler(features, rois)
-
-        roialignrotated_pooler = ROIPooler(
-            output_size=pooler_resolution,
-            scales=pooler_scales,
-            sampling_ratio=sampling_ratio,
-            pooler_type="ROIAlignRotated",
-        )
-
-        roialignrotated_out = roialignrotated_pooler(features, rois_rotated)
-
-        self.assertTrue(torch.allclose(roialignv2_out, roialignrotated_out, atol=1e-4))
-
-    def test_roialignv2_roialignrotated_match_cpu(self):
-        self._test_roialignv2_roialignrotated_match(device="cpu")
-
-    @unittest.skipIf(not torch.cuda.is_available(), "CUDA not available")
-    def test_roialignv2_roialignrotated_match_cuda(self):
-        self._test_roialignv2_roialignrotated_match(device="cuda")
-
-    def _test_scriptability(self, device):
-        pooler_resolution = 14
-        canonical_level = 4
-        canonical_scale_factor = 2**canonical_level
-        pooler_scales = (1.0 / canonical_scale_factor,)
-        sampling_ratio = 0
-
-        N, C, H, W = 2, 4, 10, 8
-        N_rois = 10
-        std = 11
-        mean = 0
-        feature = (torch.rand(N, C, H, W) - 0.5) * 2 * std + mean
-
-        features = [feature.to(device)]
-
-        rois = []
-        for _ in range(N):
-            boxes = random_boxes(N_rois, W * canonical_scale_factor)
-
-            rois.append(Boxes(boxes).to(device))
-
-        roialignv2_pooler = ROIPooler(
-            output_size=pooler_resolution,
-            scales=pooler_scales,
-            sampling_ratio=sampling_ratio,
-            pooler_type="ROIAlignV2",
-        )
-
-        roialignv2_out = roialignv2_pooler(features, rois)
-        scripted_roialignv2_out = torch.jit.script(roialignv2_pooler)(features, rois)
-        self.assertTrue(torch.equal(roialignv2_out, scripted_roialignv2_out))
-
-    def test_scriptability_cpu(self):
-        self._test_scriptability(device="cpu")
-
-    @unittest.skipIf(not torch.cuda.is_available(), "CUDA not available")
-    def test_scriptability_gpu(self):
-        self._test_scriptability(device="cuda")
-
-    def test_no_images(self):
-        N, C, H, W = 0, 32, 32, 32
-        feature = torch.rand(N, C, H, W) - 0.5
-        features = [feature]
-        pooler = ROIPooler(
-            output_size=14, scales=(1.0,), sampling_ratio=0.0, pooler_type="ROIAlignV2"
-        )
-        output = pooler.forward(features, [])
-        self.assertEqual(output.shape, (0, C, 14, 14))
-
-    def test_roi_pooler_tracing(self):
-        class Model(torch.nn.Module):
-            def __init__(self, roi):
-                super(Model, self).__init__()
-                self.roi = roi
-
-            def forward(self, x, boxes):
-                return self.roi(x, [Boxes(boxes)])
-
-        pooler_resolution = 14
-        canonical_level = 4
-        canonical_scale_factor = 2**canonical_level
-        pooler_scales = (1.0 / canonical_scale_factor, 0.5 / canonical_scale_factor)
-        sampling_ratio = 0
-
-        N, C, H, W = 1, 4, 10, 8
-        N_rois = 10
-        std = 11
-        mean = 0
-        feature = (torch.rand(N, C, H, W) - 0.5) * 2 * std + mean
-        feature = [feature, feature]
-
-        rois = random_boxes(N_rois, W * canonical_scale_factor)
-        # Add one larger box so that this level has only one box.
-        # This may trigger the bug https://github.com/pytorch/pytorch/issues/49852
-        # that we shall workaround.
-        rois = torch.cat([rois, torch.tensor([[0, 0, 448, 448]])])
-
-        model = Model(
-            ROIPooler(
-                output_size=pooler_resolution,
-                scales=pooler_scales,
-                sampling_ratio=sampling_ratio,
-                pooler_type="ROIAlign",
-            )
-        )
-
-        with torch.no_grad():
-            func = torch.jit.trace(model, (feature, rois))
-            o = func(feature, rois)
-            self.assertEqual(o.shape, (11, 4, 14, 14))
-            o = func(feature, rois[:5])
-            self.assertEqual(o.shape, (5, 4, 14, 14))
-            o = func(feature, random_boxes(20, W * canonical_scale_factor))
-            self.assertEqual(o.shape, (20, 4, 14, 14))
-
-
-if __name__ == "__main__":
-    unittest.main()
diff --git a/spaces/brjathu/HMR2.0/vendor/detectron2/tests/test_visualizer.py b/spaces/brjathu/HMR2.0/vendor/detectron2/tests/test_visualizer.py
deleted file mode 100644
index 646e5f32b5c570bd8024c13b417a45c07aad8453..0000000000000000000000000000000000000000
--- a/spaces/brjathu/HMR2.0/vendor/detectron2/tests/test_visualizer.py
+++ /dev/null
@@ -1,278 +0,0 @@
-# -*- coding: utf-8 -*-
-# Copyright (c) Facebook, Inc. and its affiliates.
-
-import numpy as np
-import os
-import tempfile
-import unittest
-import cv2
-import torch
-
-from detectron2.data import MetadataCatalog
-from detectron2.structures import BoxMode, Instances, RotatedBoxes
-from detectron2.utils.visualizer import ColorMode, Visualizer
-
-
-class TestVisualizer(unittest.TestCase):
-    def _random_data(self):
-        H, W = 100, 100
-        N = 10
-        img = np.random.rand(H, W, 3) * 255
-        boxxy = np.random.rand(N, 2) * (H // 2)
-        boxes = np.concatenate((boxxy, boxxy + H // 2), axis=1)
-
-        def _rand_poly():
-            return np.random.rand(3, 2).flatten() * H
-
-        polygons = [[_rand_poly() for _ in range(np.random.randint(1, 5))] for _ in range(N)]
-
-        mask = np.zeros_like(img[:, :, 0], dtype=bool)
-        mask[:40, 10:20] = 1
-
-        labels = [str(i) for i in range(N)]
-        return img, boxes, labels, polygons, [mask] * N
-
-    @property
-    def metadata(self):
-        return MetadataCatalog.get("coco_2017_train")
-
-    def test_draw_dataset_dict(self):
-        img = np.random.rand(512, 512, 3) * 255
-        dic = {
-            "annotations": [
-                {
-                    "bbox": [
-                        368.9946492271106,
-                        330.891438763377,
-                        13.148537455410235,
-                        13.644708680142685,
-                    ],
-                    "bbox_mode": BoxMode.XYWH_ABS,
-                    "category_id": 0,
-                    "iscrowd": 1,
-                    "segmentation": {
-                        "counts": "_jh52m?2N2N2N2O100O10O001N1O2MceP2",
-                        "size": [512, 512],
-                    },
-                }
-            ],
-            "height": 512,
-            "image_id": 1,
-            "width": 512,
-        }
-        v = Visualizer(img)
-        v.draw_dataset_dict(dic)
-
-        v = Visualizer(img, self.metadata)
-        v.draw_dataset_dict(dic)
-
-    def test_draw_rotated_dataset_dict(self):
-        img = np.random.rand(512, 512, 3) * 255
-        dic = {
-            "annotations": [
-                {
-                    "bbox": [
-                        368.9946492271106,
-                        330.891438763377,
-                        13.148537455410235,
-                        13.644708680142685,
-                        45.0,
-                    ],
-                    "bbox_mode": BoxMode.XYWHA_ABS,
-                    "category_id": 0,
-                    "iscrowd": 1,
-                }
-            ],
-            "height": 512,
-            "image_id": 1,
-            "width": 512,
-        }
-        v = Visualizer(img, self.metadata)
-        v.draw_dataset_dict(dic)
-
-    def test_overlay_instances(self):
-        img, boxes, labels, polygons, masks = self._random_data()
-
-        v = Visualizer(img, self.metadata)
-        output = v.overlay_instances(masks=polygons, boxes=boxes, labels=labels).get_image()
-        self.assertEqual(output.shape, img.shape)
-
-        # Test 2x scaling
-        v = Visualizer(img, self.metadata, scale=2.0)
-        output = v.overlay_instances(masks=polygons, boxes=boxes, labels=labels).get_image()
-        self.assertEqual(output.shape[0], img.shape[0] * 2)
-
-        # Test overlay masks
-        v = Visualizer(img, self.metadata)
-        output = v.overlay_instances(masks=masks, boxes=boxes, labels=labels).get_image()
-        self.assertEqual(output.shape, img.shape)
-
-    def test_overlay_instances_no_boxes(self):
-        img, boxes, labels, polygons, _ = self._random_data()
-        v = Visualizer(img, self.metadata)
-        v.overlay_instances(masks=polygons, boxes=None, labels=labels).get_image()
-
-    def test_draw_instance_predictions(self):
-        img, boxes, _, _, masks = self._random_data()
-        num_inst = len(boxes)
-        inst = Instances((img.shape[0], img.shape[1]))
-        inst.pred_classes = torch.randint(0, 80, size=(num_inst,))
-        inst.scores = torch.rand(num_inst)
-        inst.pred_boxes = torch.from_numpy(boxes)
-        inst.pred_masks = torch.from_numpy(np.asarray(masks))
-
-        v = Visualizer(img)
-        v.draw_instance_predictions(inst)
-
-        v = Visualizer(img, self.metadata)
-        v.draw_instance_predictions(inst)
-
-    def test_BWmode_nomask(self):
-        img, boxes, _, _, masks = self._random_data()
-        num_inst = len(boxes)
-        inst = Instances((img.shape[0], img.shape[1]))
-        inst.pred_classes = torch.randint(0, 80, size=(num_inst,))
-        inst.scores = torch.rand(num_inst)
-        inst.pred_boxes = torch.from_numpy(boxes)
-
-        v = Visualizer(img, self.metadata, instance_mode=ColorMode.IMAGE_BW)
-        v.draw_instance_predictions(inst)
-
-        # check that output is grayscale
-        inst = inst[:0]
-        v = Visualizer(img, self.metadata, instance_mode=ColorMode.IMAGE_BW)
-        output = v.draw_instance_predictions(inst).get_image()
-        self.assertTrue(np.allclose(output[:, :, 0], output[:, :, 1]))
-        self.assertTrue(np.allclose(output[:, :, 0], output[:, :, 2]))
-
-    def test_draw_empty_mask_predictions(self):
-        img, boxes, _, _, masks = self._random_data()
-        num_inst = len(boxes)
-        inst = Instances((img.shape[0], img.shape[1]))
-        inst.pred_classes = torch.randint(0, 80, size=(num_inst,))
-        inst.scores = torch.rand(num_inst)
-        inst.pred_boxes = torch.from_numpy(boxes)
-        inst.pred_masks = torch.from_numpy(np.zeros_like(np.asarray(masks)))
-
-        v = Visualizer(img, self.metadata)
-        v.draw_instance_predictions(inst)
-
-    def test_correct_output_shape(self):
-        img = np.random.rand(928, 928, 3) * 255
-        v = Visualizer(img, self.metadata)
-        out = v.output.get_image()
-        self.assertEqual(out.shape, img.shape)
-
-    def test_overlay_rotated_instances(self):
-        H, W = 100, 150
-        img = np.random.rand(H, W, 3) * 255
-        num_boxes = 50
-        boxes_5d = torch.zeros(num_boxes, 5)
-        boxes_5d[:, 0] = torch.FloatTensor(num_boxes).uniform_(-0.1 * W, 1.1 * W)
-        boxes_5d[:, 1] = torch.FloatTensor(num_boxes).uniform_(-0.1 * H, 1.1 * H)
-        boxes_5d[:, 2] = torch.FloatTensor(num_boxes).uniform_(0, max(W, H))
-        boxes_5d[:, 3] = torch.FloatTensor(num_boxes).uniform_(0, max(W, H))
-        boxes_5d[:, 4] = torch.FloatTensor(num_boxes).uniform_(-1800, 1800)
-        rotated_boxes = RotatedBoxes(boxes_5d)
-        labels = [str(i) for i in range(num_boxes)]
-
-        v = Visualizer(img, self.metadata)
-        output = v.overlay_instances(boxes=rotated_boxes, labels=labels).get_image()
-        self.assertEqual(output.shape, img.shape)
-
-    def test_draw_no_metadata(self):
-        img, boxes, _, _, masks = self._random_data()
-        num_inst = len(boxes)
-        inst = Instances((img.shape[0], img.shape[1]))
-        inst.pred_classes = torch.randint(0, 80, size=(num_inst,))
-        inst.scores = torch.rand(num_inst)
-        inst.pred_boxes = torch.from_numpy(boxes)
-        inst.pred_masks = torch.from_numpy(np.asarray(masks))
-
-        v = Visualizer(img, MetadataCatalog.get("asdfasdf"))
-        v.draw_instance_predictions(inst)
-
-    def test_draw_binary_mask(self):
-        img, boxes, _, _, masks = self._random_data()
-        img[:, :, 0] = 0  # remove red color
-        mask = masks[0]
-        mask_with_hole = np.zeros_like(mask).astype("uint8")
-        mask_with_hole = cv2.rectangle(mask_with_hole, (10, 10), (50, 50), 1, 5)
-
-        for m in [mask, mask_with_hole]:
-            for save in [True, False]:
-                v = Visualizer(img)
-                o = v.draw_binary_mask(m, color="red", text="test")
-                if save:
-                    with tempfile.TemporaryDirectory(prefix="detectron2_viz") as d:
-                        path = os.path.join(d, "output.png")
-                        o.save(path)
-                        o = cv2.imread(path)[:, :, ::-1]
-                else:
-                    o = o.get_image().astype("float32")
-                    # red color is drawn on the image
-                self.assertTrue(o[:, :, 0].sum() > 0)
-
-    def test_draw_soft_mask(self):
-        img = np.random.rand(100, 100, 3) * 255
-        img[:, :, 0] = 0  # remove red color
-        mask = np.zeros((100, 100), dtype=np.float32)
-        mask[30:50, 40:50] = 1.0
-        cv2.GaussianBlur(mask, (21, 21), 10)
-
-        v = Visualizer(img)
-        o = v.draw_soft_mask(mask, color="red", text="test")
-        o = o.get_image().astype("float32")
-        # red color is drawn on the image
-        self.assertTrue(o[:, :, 0].sum() > 0)
-
-        # test draw empty mask
-        v = Visualizer(img)
-        o = v.draw_soft_mask(np.zeros((100, 100), dtype=np.float32), color="red", text="test")
-        o = o.get_image().astype("float32")
-
-    def test_border_mask_with_holes(self):
-        H, W = 200, 200
-        img = np.zeros((H, W, 3))
-        img[:, :, 0] = 255.0
-        v = Visualizer(img, scale=3)
-
-        mask = np.zeros((H, W))
-        mask[:, 100:150] = 1
-        # create a hole, to trigger imshow
-        mask = cv2.rectangle(mask, (110, 110), (130, 130), 0, thickness=-1)
-        output = v.draw_binary_mask(mask, color="blue")
-        output = output.get_image()[:, :, ::-1]
-
-        first_row = {tuple(x.tolist()) for x in output[0]}
-        last_row = {tuple(x.tolist()) for x in output[-1]}
-        # Check quantization / off-by-1 error: the first and last row must have two colors
-        self.assertEqual(len(last_row), 2)
-        self.assertEqual(len(first_row), 2)
-        self.assertIn((0, 0, 255), last_row)
-        self.assertIn((0, 0, 255), first_row)
-
-    def test_border_polygons(self):
-        H, W = 200, 200
-        img = np.zeros((H, W, 3))
-        img[:, :, 0] = 255.0
-        v = Visualizer(img, scale=3)
-        mask = np.zeros((H, W))
-        mask[:, 100:150] = 1
-
-        output = v.draw_binary_mask(mask, color="blue")
-        output = output.get_image()[:, :, ::-1]
-
-        first_row = {tuple(x.tolist()) for x in output[0]}
-        last_row = {tuple(x.tolist()) for x in output[-1]}
-        # Check quantization / off-by-1 error:
-        # the first and last row must have >=2 colors, because the polygon
-        # touches both rows
-        self.assertGreaterEqual(len(last_row), 2)
-        self.assertGreaterEqual(len(first_row), 2)
-        self.assertIn((0, 0, 255), last_row)
-        self.assertIn((0, 0, 255), first_row)
-
-
-if __name__ == "__main__":
-    unittest.main()
diff --git a/spaces/calvinchaochao/text_generation/DESCRIPTION.md b/spaces/calvinchaochao/text_generation/DESCRIPTION.md
deleted file mode 100644
index 5b9716ddf8174a1002511bca9d854d095a895021..0000000000000000000000000000000000000000
--- a/spaces/calvinchaochao/text_generation/DESCRIPTION.md
+++ /dev/null
@@ -1 +0,0 @@
-This text generation demo takes in input text and returns generated text. It uses the Transformers library to set up the model and has two examples.
\ No newline at end of file
diff --git a/spaces/camenduru-com/audioldm-text-to-audio-generation/audioldm/clap/training/scheduler.py b/spaces/camenduru-com/audioldm-text-to-audio-generation/audioldm/clap/training/scheduler.py
deleted file mode 100644
index 7151ffbab25a113673b7627027b443b27f22cb0f..0000000000000000000000000000000000000000
--- a/spaces/camenduru-com/audioldm-text-to-audio-generation/audioldm/clap/training/scheduler.py
+++ /dev/null
@@ -1,24 +0,0 @@
-import numpy as np
-
-
-def assign_learning_rate(optimizer, new_lr):
-    for param_group in optimizer.param_groups:
-        param_group["lr"] = new_lr
-
-
-def _warmup_lr(base_lr, warmup_length, step):
-    return base_lr * (step + 1) / warmup_length
-
-
-def cosine_lr(optimizer, base_lr, warmup_length, steps):
-    def _lr_adjuster(step):
-        if step < warmup_length:
-            lr = _warmup_lr(base_lr, warmup_length, step)
-        else:
-            e = step - warmup_length
-            es = steps - warmup_length
-            lr = 0.5 * (1 + np.cos(np.pi * e / es)) * base_lr
-        assign_learning_rate(optimizer, lr)
-        return lr
-
-    return _lr_adjuster
diff --git a/spaces/carlosalonso/Detection-video/carpeta_deteccion/detectron2/export/__init__.py b/spaces/carlosalonso/Detection-video/carpeta_deteccion/detectron2/export/__init__.py
deleted file mode 100644
index 5a58758f64aae6071fa688be4400622ce6036efa..0000000000000000000000000000000000000000
--- a/spaces/carlosalonso/Detection-video/carpeta_deteccion/detectron2/export/__init__.py
+++ /dev/null
@@ -1,30 +0,0 @@
-# -*- coding: utf-8 -*-
-
-import warnings
-
-from .flatten import TracingAdapter
-from .torchscript import dump_torchscript_IR, scripting_with_instances
-
-try:
-    from caffe2.proto import caffe2_pb2 as _tmp
-    from caffe2.python import core
-
-    # caffe2 is optional
-except ImportError:
-    pass
-else:
-    from .api import *
-
-
-# TODO: Update ONNX Opset version and run tests when a newer PyTorch is supported
-STABLE_ONNX_OPSET_VERSION = 11
-
-
-def add_export_config(cfg):
-    warnings.warn(
-        "add_export_config has been deprecated and behaves as no-op function.", DeprecationWarning
-    )
-    return cfg
-
-
-__all__ = [k for k in globals().keys() if not k.startswith("_")]
diff --git a/spaces/chendl/compositional_test/multimodal/YOLOX/docs/_static/css/custom.css b/spaces/chendl/compositional_test/multimodal/YOLOX/docs/_static/css/custom.css
deleted file mode 100644
index 81f77f57d08d8be8c876906fb6455169bec1b39d..0000000000000000000000000000000000000000
--- a/spaces/chendl/compositional_test/multimodal/YOLOX/docs/_static/css/custom.css
+++ /dev/null
@@ -1,31 +0,0 @@
-/*
- * Copyright (c) Facebook, Inc. and its affiliates.
- * some extra css to make markdown look similar between github/sphinx
- */
-
-/*
- * Below is for install.md:
- */
- .rst-content code {
-    white-space: pre;
-    border: 0px;
-  }
-  
-  .rst-content th {
-    border: 1px solid #e1e4e5;
-  }
-  
-  .rst-content th p {
-    /* otherwise will be default 24px for regular paragraph */
-    margin-bottom: 0px;
-  }
-  
-  .rst-content .line-block {
-    /* otherwise will be 24px */
-    margin-bottom: 0px;
-  }
-  
-  div.section > details {
-    padding-bottom: 1em;
-  }
-  
\ No newline at end of file
diff --git a/spaces/chendl/compositional_test/transformers/examples/research_projects/bert-loses-patience/README.md b/spaces/chendl/compositional_test/transformers/examples/research_projects/bert-loses-patience/README.md
deleted file mode 100644
index d1e5baa92e90bb48ce7eeed3b6874e874a0569b9..0000000000000000000000000000000000000000
--- a/spaces/chendl/compositional_test/transformers/examples/research_projects/bert-loses-patience/README.md
+++ /dev/null
@@ -1,89 +0,0 @@
-# Patience-based Early Exit
-
-Patience-based Early Exit (PABEE) is a plug-and-play inference method for pretrained language models.
-We have already implemented it on BERT and ALBERT. Basically, you can make your LM faster and more robust with PABEE. It can even improve the performance of ALBERT on GLUE. The only sacrifice is that the batch size can only be 1.
-Learn more in the paper ["BERT Loses Patience: Fast and Robust Inference with Early Exit"](https://arxiv.org/abs/2006.04152) and the official [GitHub repo](https://github.com/JetRunner/PABEE).
-
-![PABEE](https://github.com/JetRunner/PABEE/raw/master/bert-loses-patience.png)
-
-## Training
-
-You can fine-tune a pretrained language model (you can choose from BERT and ALBERT) and train the internal classifiers by:
-```bash
-export GLUE_DIR=/path/to/glue_data
-export TASK_NAME=MRPC
-
-python ./run_glue_with_pabee.py \
-  --model_type albert \
-  --model_name_or_path bert-base-uncased/albert-base-v2 \
-  --task_name $TASK_NAME \
-  --do_train \
-  --do_eval \
-  --do_lower_case \
-  --data_dir "$GLUE_DIR/$TASK_NAME" \
-  --max_seq_length 128 \
-  --per_gpu_train_batch_size 32 \
-  --per_gpu_eval_batch_size 32 \
-  --learning_rate 2e-5 \
-  --save_steps 50 \
-  --logging_steps 50 \
-  --num_train_epochs 5 \
-  --output_dir /path/to/save/ \
-  --evaluate_during_training
-```
-
-## Inference
-
-You can inference with different patience settings by:
-```bash
-export GLUE_DIR=/path/to/glue_data
-export TASK_NAME=MRPC
-
-python ./run_glue_with_pabee.py \
-  --model_type albert \
-  --model_name_or_path /path/to/save/ \
-  --task_name $TASK_NAME \
-  --do_eval \
-  --do_lower_case \
-  --data_dir "$GLUE_DIR/$TASK_NAME" \
-  --max_seq_length 128 \
-  --per_gpu_eval_batch_size 1 \
-  --learning_rate 2e-5 \
-  --logging_steps 50 \
-  --num_train_epochs 15 \
-  --output_dir /path/to/save/ \
-  --eval_all_checkpoints \
-  --patience 3,4,5,6,7,8
-```
-where `patience` can be a list of patience settings, separated by a comma. It will help determine which patience works best.
-
-When evaluating on a regression task (STS-B), you may add `--regression_threshold 0.1` to define the regression threshold.
-
-## Results
-On the GLUE dev set:
-
-| Model        | \#Param | Speed  | CoLA  | MNLI  | MRPC  | QNLI  | QQP   | RTE   | SST\-2 | STS\-B |
-|--------------|---------|--------|-------|-------|-------|-------|-------|-------|--------|--------|
-| ALBERT\-base | 12M     |        | 58\.9 | 84\.6 | 89\.5 | 91\.7 | 89\.6 | 78\.6 | 92\.8  | 89\.5  |
-| \+PABEE      | 12M     | 1\.57x | 61\.2 | 85\.1 | 90\.0 | 91\.8 | 89\.6 | 80\.1 | 93\.0  | 90\.1  |
-
-| Model         | \#Param | Speed\-up | MNLI  | SST\-2 | STS\-B |
-|---------------|---------|-----------|-------|--------|--------|
-| BERT\-base    | 108M    |           | 84\.5 | 92\.1  | 88\.9  |
-| \+PABEE       | 108M    | 1\.62x    | 83\.6 | 92\.0  | 88\.7  |
-| ALBERT\-large | 18M     |           | 86\.4 | 94\.9  | 90\.4  |
-| \+PABEE       | 18M     | 2\.42x    | 86\.8 | 95\.2  | 90\.6  |
-
-
-## Citation
-If you find this resource useful, please consider citing the following paper:
-```bibtex
-@misc{zhou2020bert,
-    title={BERT Loses Patience: Fast and Robust Inference with Early Exit},
-    author={Wangchunshu Zhou and Canwen Xu and Tao Ge and Julian McAuley and Ke Xu and Furu Wei},
-    year={2020},
-    eprint={2006.04152},
-    archivePrefix={arXiv},
-    primaryClass={cs.CL}
-}
-```
diff --git a/spaces/chendl/compositional_test/transformers/examples/research_projects/wav2vec2/finetune_wav2vec2_xlsr_turkish.sh b/spaces/chendl/compositional_test/transformers/examples/research_projects/wav2vec2/finetune_wav2vec2_xlsr_turkish.sh
deleted file mode 100644
index 0726bb09eb51e274589dc8cd09a174296fd93ec5..0000000000000000000000000000000000000000
--- a/spaces/chendl/compositional_test/transformers/examples/research_projects/wav2vec2/finetune_wav2vec2_xlsr_turkish.sh
+++ /dev/null
@@ -1,22 +0,0 @@
-#!/usr/bin/env bash
-python run_common_voice.py \
-    --model_name_or_path="facebook/wav2vec2-large-xlsr-53" \
-    --dataset_config_name="tr" \
-    --output_dir=./wav2vec2-large-xlsr-turkish-demo \
-    --overwrite_output_dir \
-    --num_train_epochs="5" \
-    --per_device_train_batch_size="16" \
-    --evaluation_strategy="steps" \
-    --learning_rate="3e-4" \
-    --warmup_steps="500" \
-    --fp16 \
-    --freeze_feature_extractor \
-    --save_steps="400" \
-    --eval_steps="400" \
-    --save_total_limit="3" \
-    --logging_steps="400" \
-    --group_by_length \
-    --feat_proj_dropout="0.0" \
-    --layerdrop="0.1" \
-    --gradient_checkpointing \
-    --do_train --do_eval
diff --git a/spaces/chongjie/MCC_slim/util/misc.py b/spaces/chongjie/MCC_slim/util/misc.py
deleted file mode 100644
index 1efd3f42390bed7842624b8baca87c68c829abe0..0000000000000000000000000000000000000000
--- a/spaces/chongjie/MCC_slim/util/misc.py
+++ /dev/null
@@ -1,496 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-# --------------------------------------------------------
-# References:
-# DeiT: https://github.com/facebookresearch/deit
-# BEiT: https://github.com/microsoft/unilm/tree/master/beit
-# MAE: https://github.com/facebookresearch/mae
-# --------------------------------------------------------
-
-import builtins
-import datetime
-import os
-import time
-from collections import defaultdict, deque
-from pathlib import Path
-
-import torch
-import torch.distributed as dist
-from torch._six import inf
-
-
-class SmoothedValue(object):
-    """Track a series of values and provide access to smoothed values over a
-    window or the global series average.
-    """
-
-    def __init__(self, window_size=20, fmt=None):
-        if fmt is None:
-            fmt = "{median:.4f} ({global_avg:.4f})"
-        self.deque = deque(maxlen=window_size)
-        self.total = 0.0
-        self.count = 0
-        self.fmt = fmt
-
-    def update(self, value, n=1):
-        self.deque.append(value)
-        self.count += n
-        self.total += value * n
-
-    def synchronize_between_processes(self):
-        """
-        Warning: does not synchronize the deque!
-        """
-        if not is_dist_avail_and_initialized():
-            return
-        t = torch.tensor([self.count, self.total], dtype=torch.float64, device='cuda')
-        dist.barrier()
-        dist.all_reduce(t)
-        t = t.tolist()
-        self.count = int(t[0])
-        self.total = t[1]
-
-    @property
-    def median(self):
-        d = torch.tensor(list(self.deque))
-        return d.median().item()
-
-    @property
-    def avg(self):
-        d = torch.tensor(list(self.deque), dtype=torch.float32)
-        return d.mean().item()
-
-    @property
-    def global_avg(self):
-        return self.total / self.count
-
-    @property
-    def max(self):
-        return max(self.deque)
-
-    @property
-    def value(self):
-        return self.deque[-1]
-
-    def __str__(self):
-        return self.fmt.format(
-            median=self.median,
-            avg=self.avg,
-            global_avg=self.global_avg,
-            max=self.max,
-            value=self.value)
-
-
-class MetricLogger(object):
-    def __init__(self, delimiter="\t"):
-        self.meters = defaultdict(SmoothedValue)
-        self.delimiter = delimiter
-
-    def update(self, **kwargs):
-        for k, v in kwargs.items():
-            if v is None:
-                continue
-            if isinstance(v, torch.Tensor):
-                v = v.item()
-            assert isinstance(v, (float, int))
-            self.meters[k].update(v)
-
-    def __getattr__(self, attr):
-        if attr in self.meters:
-            return self.meters[attr]
-        if attr in self.__dict__:
-            return self.__dict__[attr]
-        raise AttributeError("'{}' object has no attribute '{}'".format(
-            type(self).__name__, attr))
-
-    def __str__(self):
-        loss_str = []
-        for name, meter in self.meters.items():
-            loss_str.append(
-                "{}: {}".format(name, str(meter))
-            )
-        return self.delimiter.join(loss_str)
-
-    def synchronize_between_processes(self):
-        for meter in self.meters.values():
-            meter.synchronize_between_processes()
-
-    def add_meter(self, name, meter):
-        self.meters[name] = meter
-
-    def log_every(self, iterable, print_freq, header=None):
-        i = 0
-        if not header:
-            header = ''
-        start_time = time.time()
-        end = time.time()
-        iter_time = SmoothedValue(fmt='{avg:.4f}')
-        data_time = SmoothedValue(fmt='{avg:.4f}')
-        space_fmt = ':' + str(len(str(len(iterable)))) + 'd'
-        log_msg = [
-            header,
-            '[{0' + space_fmt + '}/{1}]',
-            'eta: {eta}',
-            '{meters}',
-            'time: {time}',
-            'data: {data}'
-        ]
-        if torch.cuda.is_available():
-            log_msg.append('max mem: {memory:.0f}')
-        log_msg = self.delimiter.join(log_msg)
-        MB = 1024.0 * 1024.0
-        for obj in iterable:
-            data_time.update(time.time() - end)
-            yield obj
-            iter_time.update(time.time() - end)
-            if i % print_freq == 0 or i == len(iterable) - 1:
-                eta_seconds = iter_time.global_avg * (len(iterable) - i)
-                eta_string = str(datetime.timedelta(seconds=int(eta_seconds)))
-                if torch.cuda.is_available():
-                    print(log_msg.format(
-                        i, len(iterable), eta=eta_string,
-                        meters=str(self),
-                        time=str(iter_time), data=str(data_time),
-                        memory=torch.cuda.max_memory_allocated() / MB))
-                else:
-                    print(log_msg.format(
-                        i, len(iterable), eta=eta_string,
-                        meters=str(self),
-                        time=str(iter_time), data=str(data_time)))
-            i += 1
-            end = time.time()
-        total_time = time.time() - start_time
-        total_time_str = str(datetime.timedelta(seconds=int(total_time)))
-        print('{} Total time: {} ({:.4f} s / it)'.format(
-            header, total_time_str, total_time / len(iterable)))
-
-
-def setup_for_distributed(is_master):
-    """
-    This function disables printing when not in master process
-    """
-    builtin_print = builtins.print
-
-    def print(*args, **kwargs):
-        force = kwargs.pop('force', False)
-        force = force or (get_world_size() > 8)
-        if is_master or force:
-            now = datetime.datetime.now().time()
-            builtin_print('[{}] '.format(now), end='')  # print with time stamp
-            builtin_print(*args, **kwargs)
-
-    builtins.print = print
-
-
-def is_dist_avail_and_initialized():
-    if not dist.is_available():
-        return False
-    if not dist.is_initialized():
-        return False
-    return True
-
-
-def get_world_size():
-    if not is_dist_avail_and_initialized():
-        return 1
-    return dist.get_world_size()
-
-
-def get_rank():
-    if not is_dist_avail_and_initialized():
-        return 0
-    return dist.get_rank()
-
-
-def is_main_process():
-    return get_rank() == 0
-
-
-def save_on_master(*args, **kwargs):
-    if is_main_process():
-        torch.save(*args, **kwargs)
-
-
-def init_distributed_mode(args):
-    if args.dist_on_itp:
-        args.rank = int(os.environ['OMPI_COMM_WORLD_RANK'])
-        args.world_size = int(os.environ['OMPI_COMM_WORLD_SIZE'])
-        args.gpu = int(os.environ['OMPI_COMM_WORLD_LOCAL_RANK'])
-        args.dist_url = "tcp://%s:%s" % (os.environ['MASTER_ADDR'], os.environ['MASTER_PORT'])
-        os.environ['LOCAL_RANK'] = str(args.gpu)
-        os.environ['RANK'] = str(args.rank)
-        os.environ['WORLD_SIZE'] = str(args.world_size)
-        # ["RANK", "WORLD_SIZE", "MASTER_ADDR", "MASTER_PORT", "LOCAL_RANK"]
-    elif 'RANK' in os.environ and 'WORLD_SIZE' in os.environ:
-        args.rank = int(os.environ["RANK"])
-        args.world_size = int(os.environ['WORLD_SIZE'])
-        args.gpu = int(os.environ['LOCAL_RANK'])
-    elif 'SLURM_PROCID' in os.environ:
-        args.rank = int(os.environ['SLURM_PROCID'])
-        args.gpu = args.rank % torch.cuda.device_count()
-    else:
-        print('Not using distributed mode')
-        setup_for_distributed(is_master=True)  # hack
-        args.distributed = False
-        return
-
-    args.distributed = True
-
-    torch.cuda.set_device(args.gpu)
-    args.dist_backend = 'nccl'
-    print('| distributed init (rank {}): {}, gpu {}'.format(
-        args.rank, args.dist_url, args.gpu), flush=True)
-    torch.distributed.init_process_group(backend=args.dist_backend, init_method=args.dist_url,
-                                         world_size=args.world_size, rank=args.rank)
-    torch.distributed.barrier()
-    setup_for_distributed(args.rank == 0)
-
-
-class NativeScalerWithGradNormCount:
-    state_dict_key = "amp_scaler"
-
-    def __init__(self):
-        self._scaler = torch.cuda.amp.GradScaler()
-
-    def __call__(self, loss, optimizer, clip_grad=None, parameters=None, create_graph=False, update_grad=True, verbose=False):
-        self._scaler.scale(loss).backward(create_graph=create_graph)
-        if update_grad:
-            if clip_grad is not None:
-                assert parameters is not None
-                self._scaler.unscale_(optimizer)  # unscale the gradients of optimizer's assigned params in-place
-                norm = torch.nn.utils.clip_grad_norm_(parameters, clip_grad)
-            else:
-                self._scaler.unscale_(optimizer)
-                norm = get_grad_norm_(parameters)
-            self._scaler.step(optimizer)
-            self._scaler.update()
-        else:
-            norm = None
-        if verbose:
-            print('norm:', norm, 'clip:', clip_grad)
-        return norm
-
-    def state_dict(self):
-        return self._scaler.state_dict()
-
-    def load_state_dict(self, state_dict):
-        self._scaler.load_state_dict(state_dict)
-
-
-def get_grad_norm_(parameters, norm_type: float = 2.0) -> torch.Tensor:
-    if isinstance(parameters, torch.Tensor):
-        parameters = [parameters]
-    parameters = [p for p in parameters if p.grad is not None]
-    norm_type = float(norm_type)
-    if len(parameters) == 0:
-        return torch.tensor(0.)
-    device = parameters[0].grad.device
-    if norm_type == inf:
-        total_norm = max(p.grad.detach().abs().max().to(device) for p in parameters)
-    else:
-        total_norm = torch.norm(torch.stack([torch.norm(p.grad.detach(), norm_type).to(device) for p in parameters]), norm_type)
-    return total_norm
-
-
-def save_model(args, epoch, model, model_without_ddp, optimizer, loss_scaler):
-    output_dir = Path(args.output_dir)
-    epoch_name = f'{epoch:05d}'
-    if loss_scaler is not None:
-        checkpoint_paths = [output_dir / ('checkpoint-%s.pth' % epoch_name)]
-        for checkpoint_path in checkpoint_paths:
-            to_save = {
-                'model': model_without_ddp.state_dict(),
-                'optimizer': optimizer.state_dict(),
-                'epoch': epoch,
-                'scaler': loss_scaler.state_dict(),
-                'args': args,
-            }
-
-            save_on_master(to_save, checkpoint_path)
-    else:
-        client_state = {'epoch': epoch}
-        model.save_checkpoint(save_dir=args.output_dir, tag="checkpoint-%s" % epoch_name, client_state=client_state)
-
-
-def load_model(args, model_without_ddp, optimizer, loss_scaler):
-    if args.resume:
-        if args.resume.startswith('https'):
-            checkpoint = torch.hub.load_state_dict_from_url(
-                args.resume, map_location='cpu', check_hash=True)
-        else:
-            checkpoint = torch.load(args.resume, map_location='cpu')
-        print("Resume checkpoint %s" % args.resume)
-        print(model_without_ddp.load_state_dict(checkpoint['model'], strict=False))
-        if 'optimizer' in checkpoint and 'epoch' in checkpoint and not (hasattr(args, 'eval') and args.eval):
-            optimizer.load_state_dict(checkpoint['optimizer'])
-            args.start_epoch = checkpoint['epoch'] + 1
-            if 'scaler' in checkpoint:
-                print(loss_scaler.load_state_dict(checkpoint['scaler']))
-            print("With optim & sched!")
-            print("start epoch:", args.start_epoch)
-
-
-def all_reduce_mean(x):
-    world_size = get_world_size()
-    if world_size > 1:
-        x_reduce = torch.tensor(x).cuda()
-        dist.all_reduce(x_reduce)
-        x_reduce /= world_size
-        return x_reduce.item()
-    else:
-        return x
-
-
-import torch.distributed as dist
-
-def get_world_size():
-    """
-    Get the size of the world.
-    """
-    if not dist.is_available():
-        return 1
-    if not dist.is_initialized():
-        return 1
-    return dist.get_world_size()
-
-
-# def all_gather_unaligned(data):
-#     """
-#     Run all_gather on arbitrary picklable data (not necessarily tensors).
-#     Args:
-#         data: any picklable object
-#         group: a torch process group. By default, will use a group which
-#             contains all ranks on gloo backend.
-#     Returns:
-#         list[data]: list of data gathered from each rank
-#     """
-#     print('world', get_world_size())
-#     if get_world_size() == 1:
-#         return [data]
-
-#     # receiving Tensor from all ranks
-#     tensor_list = [
-#         torch.zeros_like(data) for _ in range(get_world_size())
-#     ]
-#     dist.all_gather(tensor_list, data)
-#     for tl in tensor_list:
-#         print(tl)
-#         print(tl.shape)
-#     return tensor_list
-
-import pickle
-def _serialize_to_tensor(data, group):
-    """
-    Seriialize the tensor to ByteTensor. Note that only `gloo` and `nccl`
-        backend is supported.
-    Args:
-        data (data): data to be serialized.
-        group (group): pytorch dist group.
-    Returns:
-        tensor (ByteTensor): tensor that serialized.
-    """
-
-    backend = dist.get_backend(group)
-    assert backend in ["gloo", "nccl"]
-    device = torch.device("cpu" if backend == "gloo" else "cuda")
-
-    buffer = pickle.dumps(data)
-    if len(buffer) > 1024 ** 3:
-        print(
-            "Rank {} trying to all-gather {:.2f} GB of data on device {}".format(
-                get_rank(), len(buffer) / (1024 ** 3), device
-            )
-        )
-    storage = torch.ByteStorage.from_buffer(buffer)
-    tensor = torch.ByteTensor(storage).to(device=device)
-    return tensor
-
-import functools
-@functools.lru_cache()
-def _get_global_gloo_group():
-    """
-    Return a process group based on gloo backend, containing all the ranks
-    The result is cached.
-    Returns:
-        (group): pytorch dist group.
-    """
-    if dist.get_backend() == "nccl":
-        return dist.new_group(backend="gloo")
-    else:
-        return dist.group.WORLD
-
-
-def _pad_to_largest_tensor(tensor, group):
-    """
-    Padding all the tensors from different GPUs to the largest ones.
-    Args:
-        tensor (tensor): tensor to pad.
-        group (group): pytorch dist group.
-    Returns:
-        list[int]: size of the tensor, on each rank
-        Tensor: padded tensor that has the max size
-    """
-    world_size = dist.get_world_size(group=group)
-    assert (
-        world_size >= 1
-    ), "comm.gather/all_gather must be called from ranks within the given group!"
-    local_size = torch.tensor(
-        [tensor.numel()], dtype=torch.int64, device=tensor.device
-    )
-    size_list = [
-        torch.zeros([1], dtype=torch.int64, device=tensor.device)
-        for _ in range(world_size)
-    ]
-    dist.all_gather(size_list, local_size, group=group)
-    size_list = [int(size.item()) for size in size_list]
-
-    max_size = max(size_list)
-
-    # we pad the tensor because torch all_gather does not support
-    # gathering tensors of different shapes
-    if local_size != max_size:
-        padding = torch.zeros(
-            (max_size - local_size,), dtype=torch.uint8, device=tensor.device
-        )
-        tensor = torch.cat((tensor, padding), dim=0)
-    return size_list, tensor
-
-def all_gather_unaligned(data, group=None):
-    """
-    Run all_gather on arbitrary picklable data (not necessarily tensors).
-    Args:
-        data: any picklable object
-        group: a torch process group. By default, will use a group which
-            contains all ranks on gloo backend.
-    Returns:
-        list[data]: list of data gathered from each rank
-    """
-    if get_world_size() == 1:
-        return [data]
-    if group is None:
-        group = _get_global_gloo_group()
-    if dist.get_world_size(group) == 1:
-        return [data]
-
-    tensor = _serialize_to_tensor(data, group)
-
-    size_list, tensor = _pad_to_largest_tensor(tensor, group)
-    max_size = max(size_list)
-
-    # receiving Tensor from all ranks
-    tensor_list = [
-        torch.empty((max_size,), dtype=torch.uint8, device=tensor.device)
-        for _ in size_list
-    ]
-    dist.all_gather(tensor_list, tensor, group=group)
-
-    data_list = []
-    for size, tensor in zip(size_list, tensor_list):
-        buffer = tensor.cpu().numpy().tobytes()[:size]
-        data_list.append(pickle.loads(buffer).to(data.device))
-
-    return data_list
-
diff --git a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/chromadb/test/db/migrations/00001-migration-1.psql.sql b/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/chromadb/test/db/migrations/00001-migration-1.psql.sql
deleted file mode 100644
index a214bae8d5b0d6482fedd18265d4dfc756d47485..0000000000000000000000000000000000000000
--- a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/chromadb/test/db/migrations/00001-migration-1.psql.sql
+++ /dev/null
@@ -1,3 +0,0 @@
-CREATE TABLE table1 (
-    name TEXT PRIMARY KEY
-);
diff --git a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/fontTools/pens/filterPen.py b/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/fontTools/pens/filterPen.py
deleted file mode 100644
index 81423109ae6b0caed4b75189a0d87b64cf8d0197..0000000000000000000000000000000000000000
--- a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/fontTools/pens/filterPen.py
+++ /dev/null
@@ -1,164 +0,0 @@
-from fontTools.pens.basePen import AbstractPen
-from fontTools.pens.pointPen import AbstractPointPen
-from fontTools.pens.recordingPen import RecordingPen
-
-
-class _PassThruComponentsMixin(object):
-    def addComponent(self, glyphName, transformation, **kwargs):
-        self._outPen.addComponent(glyphName, transformation, **kwargs)
-
-
-class FilterPen(_PassThruComponentsMixin, AbstractPen):
-
-    """Base class for pens that apply some transformation to the coordinates
-    they receive and pass them to another pen.
-
-    You can override any of its methods. The default implementation does
-    nothing, but passes the commands unmodified to the other pen.
-
-    >>> from fontTools.pens.recordingPen import RecordingPen
-    >>> rec = RecordingPen()
-    >>> pen = FilterPen(rec)
-    >>> v = iter(rec.value)
-
-    >>> pen.moveTo((0, 0))
-    >>> next(v)
-    ('moveTo', ((0, 0),))
-
-    >>> pen.lineTo((1, 1))
-    >>> next(v)
-    ('lineTo', ((1, 1),))
-
-    >>> pen.curveTo((2, 2), (3, 3), (4, 4))
-    >>> next(v)
-    ('curveTo', ((2, 2), (3, 3), (4, 4)))
-
-    >>> pen.qCurveTo((5, 5), (6, 6), (7, 7), (8, 8))
-    >>> next(v)
-    ('qCurveTo', ((5, 5), (6, 6), (7, 7), (8, 8)))
-
-    >>> pen.closePath()
-    >>> next(v)
-    ('closePath', ())
-
-    >>> pen.moveTo((9, 9))
-    >>> next(v)
-    ('moveTo', ((9, 9),))
-
-    >>> pen.endPath()
-    >>> next(v)
-    ('endPath', ())
-
-    >>> pen.addComponent('foo', (1, 0, 0, 1, 0, 0))
-    >>> next(v)
-    ('addComponent', ('foo', (1, 0, 0, 1, 0, 0)))
-    """
-
-    def __init__(self, outPen):
-        self._outPen = outPen
-        self.current_pt = None
-
-    def moveTo(self, pt):
-        self._outPen.moveTo(pt)
-        self.current_pt = pt
-
-    def lineTo(self, pt):
-        self._outPen.lineTo(pt)
-        self.current_pt = pt
-
-    def curveTo(self, *points):
-        self._outPen.curveTo(*points)
-        self.current_pt = points[-1]
-
-    def qCurveTo(self, *points):
-        self._outPen.qCurveTo(*points)
-        self.current_pt = points[-1]
-
-    def closePath(self):
-        self._outPen.closePath()
-        self.current_pt = None
-
-    def endPath(self):
-        self._outPen.endPath()
-        self.current_pt = None
-
-
-class ContourFilterPen(_PassThruComponentsMixin, RecordingPen):
-    """A "buffered" filter pen that accumulates contour data, passes
-    it through a ``filterContour`` method when the contour is closed or ended,
-    and finally draws the result with the output pen.
-
-    Components are passed through unchanged.
-    """
-
-    def __init__(self, outPen):
-        super(ContourFilterPen, self).__init__()
-        self._outPen = outPen
-
-    def closePath(self):
-        super(ContourFilterPen, self).closePath()
-        self._flushContour()
-
-    def endPath(self):
-        super(ContourFilterPen, self).endPath()
-        self._flushContour()
-
-    def _flushContour(self):
-        result = self.filterContour(self.value)
-        if result is not None:
-            self.value = result
-        self.replay(self._outPen)
-        self.value = []
-
-    def filterContour(self, contour):
-        """Subclasses must override this to perform the filtering.
-
-        The contour is a list of pen (operator, operands) tuples.
-        Operators are strings corresponding to the AbstractPen methods:
-        "moveTo", "lineTo", "curveTo", "qCurveTo", "closePath" and
-        "endPath". The operands are the positional arguments that are
-        passed to each method.
-
-        If the method doesn't return a value (i.e. returns None), it's
-        assumed that the argument was modified in-place.
-        Otherwise, the return value is drawn with the output pen.
-        """
-        return  # or return contour
-
-
-class FilterPointPen(_PassThruComponentsMixin, AbstractPointPen):
-    """Baseclass for point pens that apply some transformation to the
-    coordinates they receive and pass them to another point pen.
-
-    You can override any of its methods. The default implementation does
-    nothing, but passes the commands unmodified to the other pen.
-
-    >>> from fontTools.pens.recordingPen import RecordingPointPen
-    >>> rec = RecordingPointPen()
-    >>> pen = FilterPointPen(rec)
-    >>> v = iter(rec.value)
-    >>> pen.beginPath(identifier="abc")
-    >>> next(v)
-    ('beginPath', (), {'identifier': 'abc'})
-    >>> pen.addPoint((1, 2), "line", False)
-    >>> next(v)
-    ('addPoint', ((1, 2), 'line', False, None), {})
-    >>> pen.addComponent("a", (2, 0, 0, 2, 10, -10), identifier="0001")
-    >>> next(v)
-    ('addComponent', ('a', (2, 0, 0, 2, 10, -10)), {'identifier': '0001'})
-    >>> pen.endPath()
-    >>> next(v)
-    ('endPath', (), {})
-    """
-
-    def __init__(self, outPointPen):
-        self._outPen = outPointPen
-
-    def beginPath(self, **kwargs):
-        self._outPen.beginPath(**kwargs)
-
-    def endPath(self):
-        self._outPen.endPath()
-
-    def addPoint(self, pt, segmentType=None, smooth=False, name=None, **kwargs):
-        self._outPen.addPoint(pt, segmentType, smooth, name, **kwargs)
diff --git a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/gradio/templates/cdn/assets/Button-11a87b79.js b/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/gradio/templates/cdn/assets/Button-11a87b79.js
deleted file mode 100644
index 7d26e17db7d6e0267fda79992e89c60b0a251476..0000000000000000000000000000000000000000
--- a/spaces/chuan-hd/law-assistant-chatbot/.venv/lib/python3.11/site-packages/gradio/templates/cdn/assets/Button-11a87b79.js
+++ /dev/null
@@ -1,4 +0,0 @@
-import{i as Q,a8 as C,S as q,e as A,s as E,z,v as k,a9 as I,E as T,N as L,aa as U,U as c,L as o,p as V,ab as D,ac as F,ad as K,q as G,A as N,K as y,Q as H,F as J}from"./index-f877dfd5.js";function M(t){const e=t-1;return e*e*e+1}function x(t,{delay:e=0,duration:i=400,easing:n=Q}={}){const u=+getComputedStyle(t).opacity;return{delay:e,duration:i,easing:n,css:d=>`opacity: ${d*u}`}}function p(t,{delay:e=0,duration:i=400,easing:n=M,x:u=0,y:d=0,opacity:m=0}={}){const f=getComputedStyle(t),l=+f.opacity,s=f.transform==="none"?"":f.transform,h=l*(1-m),[b,r]=C(u),[w,_]=C(d);return{delay:e,duration:i,easing:n,css:(g,v)=>`
-			transform: ${s} translate(${(1-g)*b}${r}, ${(1-g)*w}${_});
-			opacity: ${l-h*v}`}}function P(t){let e,i,n;const u=t[17].default,d=I(u,t,t[16],null);let m=[{"data-testid":t[8]},{id:t[3]},{class:i="block "+t[4].join(" ")+" svelte-kz0ejz"}],f={};for(let l=0;l<m.length;l+=1)f=T(f,m[l]);return{c(){e=L(t[14]),d&&d.c(),U(t[14])(e,f),c(e,"hidden",t[10]===!1),c(e,"padded",t[7]),c(e,"border_focus",t[6]==="focus"),c(e,"hide-container",!t[9]&&!t[0]),o(e,"height",typeof t[1]=="number"?t[1]+"px":void 0),o(e,"width",typeof t[2]=="number"?`calc(min(${t[2]}px, 100%))`:void 0),o(e,"border-style",t[5]),o(e,"overflow",t[11]?"visible":"hidden"),o(e,"flex-grow",t[12]),o(e,"min-width",`calc(min(${t[13]}px, 100%))`)},m(l,s){V(l,e,s),d&&d.m(e,null),n=!0},p(l,s){d&&d.p&&(!n||s&65536)&&D(d,u,l,l[16],n?K(u,l[16],s,null):F(l[16]),null),U(l[14])(e,f=G(m,[(!n||s&256)&&{"data-testid":l[8]},(!n||s&8)&&{id:l[3]},(!n||s&16&&i!==(i="block "+l[4].join(" ")+" svelte-kz0ejz"))&&{class:i}])),c(e,"hidden",l[10]===!1),c(e,"padded",l[7]),c(e,"border_focus",l[6]==="focus"),c(e,"hide-container",!l[9]&&!l[0]),s&2&&o(e,"height",typeof l[1]=="number"?l[1]+"px":void 0),s&4&&o(e,"width",typeof l[2]=="number"?`calc(min(${l[2]}px, 100%))`:void 0),s&32&&o(e,"border-style",l[5]),s&2048&&o(e,"overflow",l[11]?"visible":"hidden"),s&4096&&o(e,"flex-grow",l[12]),s&8192&&o(e,"min-width",`calc(min(${l[13]}px, 100%))`)},i(l){n||(z(d,l),n=!0)},o(l){k(d,l),n=!1},d(l){l&&N(e),d&&d.d(l)}}}function R(t){let e,i=t[14]&&P(t);return{c(){i&&i.c()},m(n,u){i&&i.m(n,u),e=!0},p(n,[u]){n[14]&&i.p(n,u)},i(n){e||(z(i,n),e=!0)},o(n){k(i,n),e=!1},d(n){i&&i.d(n)}}}function W(t,e,i){let{$$slots:n={},$$scope:u}=e,{container:d=!0}=e,{height:m=void 0}=e,{width:f=void 0}=e,{elem_id:l=""}=e,{elem_classes:s=[]}=e,{variant:h="solid"}=e,{border_mode:b="base"}=e,{padding:r=!0}=e,{type:w="normal"}=e,{test_id:_=void 0}=e,{explicit_call:g=!1}=e,{visible:v=!0}=e,{allow_overflow:j=!0}=e,{scale:B=null}=e,{min_width:S=0}=e,O=w==="fieldset"?"fieldset":"div";return t.$$set=a=>{"container"in a&&i(0,d=a.container),"height"in a&&i(1,m=a.height),"width"in a&&i(2,f=a.width),"elem_id"in a&&i(3,l=a.elem_id),"elem_classes"in a&&i(4,s=a.elem_classes),"variant"in a&&i(5,h=a.variant),"border_mode"in a&&i(6,b=a.border_mode),"padding"in a&&i(7,r=a.padding),"type"in a&&i(15,w=a.type),"test_id"in a&&i(8,_=a.test_id),"explicit_call"in a&&i(9,g=a.explicit_call),"visible"in a&&i(10,v=a.visible),"allow_overflow"in a&&i(11,j=a.allow_overflow),"scale"in a&&i(12,B=a.scale),"min_width"in a&&i(13,S=a.min_width),"$$scope"in a&&i(16,u=a.$$scope)},[d,m,f,l,s,h,b,r,_,g,v,j,B,S,O,w,u,n]}class $ extends q{constructor(e){super(),A(this,e,W,R,E,{container:0,height:1,width:2,elem_id:3,elem_classes:4,variant:5,border_mode:6,padding:7,type:15,test_id:8,explicit_call:9,visible:10,allow_overflow:11,scale:12,min_width:13})}}function X(t){let e,i,n,u,d;const m=t[9].default,f=I(m,t,t[8],null);return{c(){e=L("button"),f&&f.c(),y(e,"class",i=t[4]+" "+t[3]+" "+t[1].join(" ")+" svelte-1jrzxu"),y(e,"id",t[0]),e.disabled=t[5],c(e,"hide-container",!t[2]),o(e,"flex-grow",t[6]),o(e,"width",t[6]===0?"fit-content":null),o(e,"min-width",typeof t[7]=="number"?`calc(min(${t[7]}px, 100%))`:null)},m(l,s){V(l,e,s),f&&f.m(e,null),n=!0,u||(d=H(e,"click",t[10]),u=!0)},p(l,[s]){f&&f.p&&(!n||s&256)&&D(f,m,l,l[8],n?K(m,l[8],s,null):F(l[8]),null),(!n||s&26&&i!==(i=l[4]+" "+l[3]+" "+l[1].join(" ")+" svelte-1jrzxu"))&&y(e,"class",i),(!n||s&1)&&y(e,"id",l[0]),(!n||s&32)&&(e.disabled=l[5]),(!n||s&30)&&c(e,"hide-container",!l[2]),s&64&&o(e,"flex-grow",l[6]),s&64&&o(e,"width",l[6]===0?"fit-content":null),s&128&&o(e,"min-width",typeof l[7]=="number"?`calc(min(${l[7]}px, 100%))`:null)},i(l){n||(z(f,l),n=!0)},o(l){k(f,l),n=!1},d(l){l&&N(e),f&&f.d(l),u=!1,d()}}}function Y(t,e,i){let{$$slots:n={},$$scope:u}=e,{elem_id:d=""}=e,{elem_classes:m=[]}=e,{visible:f=!0}=e,{variant:l="secondary"}=e,{size:s="lg"}=e,{disabled:h=!1}=e,{scale:b=null}=e,{min_width:r=void 0}=e;function w(_){J.call(this,t,_)}return t.$$set=_=>{"elem_id"in _&&i(0,d=_.elem_id),"elem_classes"in _&&i(1,m=_.elem_classes),"visible"in _&&i(2,f=_.visible),"variant"in _&&i(3,l=_.variant),"size"in _&&i(4,s=_.size),"disabled"in _&&i(5,h=_.disabled),"scale"in _&&i(6,b=_.scale),"min_width"in _&&i(7,r=_.min_width),"$$scope"in _&&i(8,u=_.$$scope)},[d,m,f,l,s,h,b,r,u,n,w]}class ee extends q{constructor(e){super(),A(this,e,Y,X,E,{elem_id:0,elem_classes:1,visible:2,variant:3,size:4,disabled:5,scale:6,min_width:7})}}export{$ as B,ee as a,p as b,M as c,x as f};
-//# sourceMappingURL=Button-11a87b79.js.map
diff --git a/spaces/cihyFjudo/fairness-paper-search/Antonella Patricia and Magdalena Meet the Women Who Made History as the First Bridezillas.md b/spaces/cihyFjudo/fairness-paper-search/Antonella Patricia and Magdalena Meet the Women Who Made History as the First Bridezillas.md
deleted file mode 100644
index 7cc3e2727053dd2ca0987fa297329909ed2d27f6..0000000000000000000000000000000000000000
--- a/spaces/cihyFjudo/fairness-paper-search/Antonella Patricia and Magdalena Meet the Women Who Made History as the First Bridezillas.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>Antonella, Patricia And Magdalena Download</h2><br /><p><b><b>Download File</b> &ndash;&ndash;&ndash; <a href="https://tinurli.com/2uwjlI">https://tinurli.com/2uwjlI</a></b></p><br /><br />
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diff --git a/spaces/cihyFjudo/fairness-paper-search/Autoenginuity Activation Codes Keygen Pros and Cons of Using It.md b/spaces/cihyFjudo/fairness-paper-search/Autoenginuity Activation Codes Keygen Pros and Cons of Using It.md
deleted file mode 100644
index b902a82dc3a0bf3e7ea3f169e084cecd76e7732b..0000000000000000000000000000000000000000
--- a/spaces/cihyFjudo/fairness-paper-search/Autoenginuity Activation Codes Keygen Pros and Cons of Using It.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>autoenginuityactivationcodeskeygen</h2><br /><p><b><b>DOWNLOAD</b> &#11088; <a href="https://tinurli.com/2uwiPs">https://tinurli.com/2uwiPs</a></b></p><br /><br />
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diff --git a/spaces/cihyFjudo/fairness-paper-search/Download Crows Zero 2 Full Movie Sub Indo Mp4 Playerl The Story Characters and Themes Explained.md b/spaces/cihyFjudo/fairness-paper-search/Download Crows Zero 2 Full Movie Sub Indo Mp4 Playerl The Story Characters and Themes Explained.md
deleted file mode 100644
index fc0f6f839fc7da8cc58e48bc4284e74b079ed043..0000000000000000000000000000000000000000
--- a/spaces/cihyFjudo/fairness-paper-search/Download Crows Zero 2 Full Movie Sub Indo Mp4 Playerl The Story Characters and Themes Explained.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>Download Crows Zero 2 Full Movie Sub Indo Mp4 Playerl</h2><br /><p><b><b>Download Zip</b> &#9675; <a href="https://tinurli.com/2uwkAR">https://tinurli.com/2uwkAR</a></b></p><br /><br />
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diff --git a/spaces/cihyFjudo/fairness-paper-search/Portable Penetrator Wifi Wep Wpa Wpa2 REPACK Cracker Download.md b/spaces/cihyFjudo/fairness-paper-search/Portable Penetrator Wifi Wep Wpa Wpa2 REPACK Cracker Download.md
deleted file mode 100644
index 99e3a9560aeed54add1309f972c853fd89bc4d28..0000000000000000000000000000000000000000
--- a/spaces/cihyFjudo/fairness-paper-search/Portable Penetrator Wifi Wep Wpa Wpa2 REPACK Cracker Download.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>portable penetrator wifi wep wpa wpa2 cracker download</h2><br /><p><b><b>Download Zip</b> >>>>> <a href="https://tinurli.com/2uwisf">https://tinurli.com/2uwisf</a></b></p><br /><br />
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diff --git a/spaces/cloudtheboi/Lofi4All/.pythonlibs/lib/python3.10/site-packages/audioread/ffdec.py b/spaces/cloudtheboi/Lofi4All/.pythonlibs/lib/python3.10/site-packages/audioread/ffdec.py
deleted file mode 100644
index 348b093e06d482fff3132523daddf4c031b196bf..0000000000000000000000000000000000000000
--- a/spaces/cloudtheboi/Lofi4All/.pythonlibs/lib/python3.10/site-packages/audioread/ffdec.py
+++ /dev/null
@@ -1,320 +0,0 @@
-# This file is part of audioread.
-# Copyright 2014, Adrian Sampson.
-#
-# Permission is hereby granted, free of charge, to any person obtaining
-# a copy of this software and associated documentation files (the
-# "Software"), to deal in the Software without restriction, including
-# without limitation the rights to use, copy, modify, merge, publish,
-# distribute, sublicense, and/or sell copies of the Software, and to
-# permit persons to whom the Software is furnished to do so, subject to
-# the following conditions:
-#
-# The above copyright notice and this permission notice shall be
-# included in all copies or substantial portions of the Software.
-
-"""Read audio data using the ffmpeg command line tool via its standard
-output.
-"""
-
-import queue
-import re
-import subprocess
-import sys
-import threading
-import time
-from io import DEFAULT_BUFFER_SIZE
-
-from .exceptions import DecodeError
-from .base import AudioFile
-
-COMMANDS = ('ffmpeg', 'avconv')
-
-if sys.platform == "win32":
-    PROC_FLAGS = 0x08000000
-else:
-    PROC_FLAGS = 0
-
-
-class FFmpegError(DecodeError):
-    pass
-
-
-class CommunicationError(FFmpegError):
-    """Raised when the output of FFmpeg is not parseable."""
-
-
-class UnsupportedError(FFmpegError):
-    """The file could not be decoded by FFmpeg."""
-
-
-class NotInstalledError(FFmpegError):
-    """Could not find the ffmpeg binary."""
-
-
-class ReadTimeoutError(FFmpegError):
-    """Reading from the ffmpeg command-line tool timed out."""
-
-
-class QueueReaderThread(threading.Thread):
-    """A thread that consumes data from a filehandle and sends the data
-    over a Queue.
-    """
-    def __init__(self, fh, blocksize=1024, discard=False):
-        super().__init__()
-        self.fh = fh
-        self.blocksize = blocksize
-        self.daemon = True
-        self.discard = discard
-        self.queue = None if discard else queue.Queue()
-
-    def run(self):
-        while True:
-            data = self.fh.read(self.blocksize)
-            if not self.discard:
-                self.queue.put(data)
-            if not data:
-                # Stream closed (EOF).
-                break
-
-
-def popen_multiple(commands, command_args, *args, **kwargs):
-    """Like `subprocess.Popen`, but can try multiple commands in case
-    some are not available.
-
-    `commands` is an iterable of command names and `command_args` are
-    the rest of the arguments that, when appended to the command name,
-    make up the full first argument to `subprocess.Popen`. The
-    other positional and keyword arguments are passed through.
-    """
-    for i, command in enumerate(commands):
-        cmd = [command] + command_args
-        try:
-            return subprocess.Popen(cmd, *args, **kwargs)
-        except OSError:
-            if i == len(commands) - 1:
-                # No more commands to try.
-                raise
-
-
-def available():
-    """Detect whether the FFmpeg backend can be used on this system.
-    """
-    try:
-        proc = popen_multiple(
-            COMMANDS,
-            ['-version'],
-            stdout=subprocess.PIPE,
-            stderr=subprocess.PIPE,
-            creationflags=PROC_FLAGS,
-        )
-    except OSError:
-        return False
-    else:
-        proc.wait()
-        return proc.returncode == 0
-
-
-# For Windows error switch management, we need a lock to keep the mode
-# adjustment atomic.
-windows_error_mode_lock = threading.Lock()
-
-
-class FFmpegAudioFile(AudioFile):
-    """An audio file decoded by the ffmpeg command-line utility."""
-    def __init__(self, filename, block_size=DEFAULT_BUFFER_SIZE):
-        # On Windows, we need to disable the subprocess's crash dialog
-        # in case it dies. Passing SEM_NOGPFAULTERRORBOX to SetErrorMode
-        # disables this behavior.
-        windows = sys.platform.startswith("win")
-        if windows:
-            windows_error_mode_lock.acquire()
-            SEM_NOGPFAULTERRORBOX = 0x0002
-            import ctypes
-            # We call SetErrorMode in two steps to avoid overriding
-            # existing error mode.
-            previous_error_mode = \
-                ctypes.windll.kernel32.SetErrorMode(SEM_NOGPFAULTERRORBOX)
-            ctypes.windll.kernel32.SetErrorMode(
-                previous_error_mode | SEM_NOGPFAULTERRORBOX
-            )
-
-        try:
-            self.proc = popen_multiple(
-                COMMANDS,
-                ['-i', filename, '-f', 's16le', '-'],
-                stdout=subprocess.PIPE,
-                stderr=subprocess.PIPE,
-                stdin=subprocess.DEVNULL,
-                creationflags=PROC_FLAGS,
-            )
-
-        except OSError:
-            raise NotInstalledError()
-
-        finally:
-            # Reset previous error mode on Windows. (We can change this
-            # back now because the flag was inherited by the subprocess;
-            # we don't need to keep it set in the parent process.)
-            if windows:
-                try:
-                    import ctypes
-                    ctypes.windll.kernel32.SetErrorMode(previous_error_mode)
-                finally:
-                    windows_error_mode_lock.release()
-
-        # Start another thread to consume the standard output of the
-        # process, which contains raw audio data.
-        self.stdout_reader = QueueReaderThread(self.proc.stdout, block_size)
-        self.stdout_reader.start()
-
-        # Read relevant information from stderr.
-        self._get_info()
-
-        # Start a separate thread to read the rest of the data from
-        # stderr. This (a) avoids filling up the OS buffer and (b)
-        # collects the error output for diagnosis.
-        self.stderr_reader = QueueReaderThread(self.proc.stderr)
-        self.stderr_reader.start()
-
-    def read_data(self, timeout=10.0):
-        """Read blocks of raw PCM data from the file."""
-        # Read from stdout in a separate thread and consume data from
-        # the queue.
-        start_time = time.time()
-        while True:
-            # Wait for data to be available or a timeout.
-            data = None
-            try:
-                data = self.stdout_reader.queue.get(timeout=timeout)
-                if data:
-                    yield data
-                else:
-                    # End of file.
-                    break
-            except queue.Empty:
-                # Queue read timed out.
-                end_time = time.time()
-                if not data:
-                    if end_time - start_time >= timeout:
-                        # Nothing interesting has happened for a while --
-                        # FFmpeg is probably hanging.
-                        raise ReadTimeoutError('ffmpeg output: {}'.format(
-                            b''.join(self.stderr_reader.queue.queue)
-                        ))
-                    else:
-                        start_time = end_time
-                        # Keep waiting.
-                        continue
-
-    def _get_info(self):
-        """Reads the tool's output from its stderr stream, extracts the
-        relevant information, and parses it.
-        """
-        out_parts = []
-        while True:
-            line = self.proc.stderr.readline()
-            if not line:
-                # EOF and data not found.
-                raise CommunicationError("stream info not found")
-
-            # In Python 3, result of reading from stderr is bytes.
-            if isinstance(line, bytes):
-                line = line.decode('utf8', 'ignore')
-
-            line = line.strip().lower()
-
-            if 'no such file' in line:
-                raise OSError('file not found')
-            elif 'invalid data found' in line:
-                raise UnsupportedError()
-            elif 'duration:' in line:
-                out_parts.append(line)
-            elif 'audio:' in line:
-                out_parts.append(line)
-                self._parse_info(''.join(out_parts))
-                break
-
-    def _parse_info(self, s):
-        """Given relevant data from the ffmpeg output, set audio
-        parameter fields on this object.
-        """
-        # Sample rate.
-        match = re.search(r'(\d+) hz', s)
-        if match:
-            self.samplerate = int(match.group(1))
-        else:
-            self.samplerate = 0
-
-        # Channel count.
-        match = re.search(r'hz, ([^,]+),', s)
-        if match:
-            mode = match.group(1)
-            if mode == 'stereo':
-                self.channels = 2
-            else:
-                cmatch = re.match(r'(\d+)\.?(\d)?', mode)
-                if cmatch:
-                    self.channels = sum(map(int, cmatch.group().split('.')))
-                else:
-                    self.channels = 1
-        else:
-            self.channels = 0
-
-        # Duration.
-        match = re.search(
-            r'duration: (\d+):(\d+):(\d+).(\d)', s
-        )
-        if match:
-            durparts = list(map(int, match.groups()))
-            duration = (
-                durparts[0] * 60 * 60 +
-                durparts[1] * 60 +
-                durparts[2] +
-                float(durparts[3]) / 10
-            )
-            self.duration = duration
-        else:
-            # No duration found.
-            self.duration = 0
-
-    def close(self):
-        """Close the ffmpeg process used to perform the decoding."""
-        if hasattr(self, 'proc'):
-            # First check the process's execution status before attempting to
-            # kill it. This fixes an issue on Windows Subsystem for Linux where
-            # ffmpeg closes normally on its own, but never updates
-            # `returncode`.
-            self.proc.poll()
-
-            # Kill the process if it is still running.
-            if self.proc.returncode is None:
-                self.proc.kill()
-                self.proc.wait()
-
-            # Wait for the stream-reading threads to exit. (They need to
-            # stop reading before we can close the streams.)
-            if hasattr(self, 'stderr_reader'):
-                self.stderr_reader.join()
-            if hasattr(self, 'stdout_reader'):
-                self.stdout_reader.join()
-
-            # Close the stdout and stderr streams that were opened by Popen,
-            # which should occur regardless of if the process terminated
-            # cleanly.
-            self.proc.stdout.close()
-            self.proc.stderr.close()
-
-    def __del__(self):
-        self.close()
-
-    # Iteration.
-    def __iter__(self):
-        return self.read_data()
-
-    # Context manager.
-    def __enter__(self):
-        return self
-
-    def __exit__(self, exc_type, exc_val, exc_tb):
-        self.close()
-        return False
diff --git a/spaces/cloudtheboi/Lofi4All/.pythonlibs/lib/python3.10/site-packages/click/exceptions.py b/spaces/cloudtheboi/Lofi4All/.pythonlibs/lib/python3.10/site-packages/click/exceptions.py
deleted file mode 100644
index fe68a3613f74e5e82da4e3eedc7d9451977838dd..0000000000000000000000000000000000000000
--- a/spaces/cloudtheboi/Lofi4All/.pythonlibs/lib/python3.10/site-packages/click/exceptions.py
+++ /dev/null
@@ -1,288 +0,0 @@
-import typing as t
-from gettext import gettext as _
-from gettext import ngettext
-
-from ._compat import get_text_stderr
-from .utils import echo
-from .utils import format_filename
-
-if t.TYPE_CHECKING:
-    from .core import Command
-    from .core import Context
-    from .core import Parameter
-
-
-def _join_param_hints(
-    param_hint: t.Optional[t.Union[t.Sequence[str], str]]
-) -> t.Optional[str]:
-    if param_hint is not None and not isinstance(param_hint, str):
-        return " / ".join(repr(x) for x in param_hint)
-
-    return param_hint
-
-
-class ClickException(Exception):
-    """An exception that Click can handle and show to the user."""
-
-    #: The exit code for this exception.
-    exit_code = 1
-
-    def __init__(self, message: str) -> None:
-        super().__init__(message)
-        self.message = message
-
-    def format_message(self) -> str:
-        return self.message
-
-    def __str__(self) -> str:
-        return self.message
-
-    def show(self, file: t.Optional[t.IO[t.Any]] = None) -> None:
-        if file is None:
-            file = get_text_stderr()
-
-        echo(_("Error: {message}").format(message=self.format_message()), file=file)
-
-
-class UsageError(ClickException):
-    """An internal exception that signals a usage error.  This typically
-    aborts any further handling.
-
-    :param message: the error message to display.
-    :param ctx: optionally the context that caused this error.  Click will
-                fill in the context automatically in some situations.
-    """
-
-    exit_code = 2
-
-    def __init__(self, message: str, ctx: t.Optional["Context"] = None) -> None:
-        super().__init__(message)
-        self.ctx = ctx
-        self.cmd: t.Optional["Command"] = self.ctx.command if self.ctx else None
-
-    def show(self, file: t.Optional[t.IO[t.Any]] = None) -> None:
-        if file is None:
-            file = get_text_stderr()
-        color = None
-        hint = ""
-        if (
-            self.ctx is not None
-            and self.ctx.command.get_help_option(self.ctx) is not None
-        ):
-            hint = _("Try '{command} {option}' for help.").format(
-                command=self.ctx.command_path, option=self.ctx.help_option_names[0]
-            )
-            hint = f"{hint}\n"
-        if self.ctx is not None:
-            color = self.ctx.color
-            echo(f"{self.ctx.get_usage()}\n{hint}", file=file, color=color)
-        echo(
-            _("Error: {message}").format(message=self.format_message()),
-            file=file,
-            color=color,
-        )
-
-
-class BadParameter(UsageError):
-    """An exception that formats out a standardized error message for a
-    bad parameter.  This is useful when thrown from a callback or type as
-    Click will attach contextual information to it (for instance, which
-    parameter it is).
-
-    .. versionadded:: 2.0
-
-    :param param: the parameter object that caused this error.  This can
-                  be left out, and Click will attach this info itself
-                  if possible.
-    :param param_hint: a string that shows up as parameter name.  This
-                       can be used as alternative to `param` in cases
-                       where custom validation should happen.  If it is
-                       a string it's used as such, if it's a list then
-                       each item is quoted and separated.
-    """
-
-    def __init__(
-        self,
-        message: str,
-        ctx: t.Optional["Context"] = None,
-        param: t.Optional["Parameter"] = None,
-        param_hint: t.Optional[str] = None,
-    ) -> None:
-        super().__init__(message, ctx)
-        self.param = param
-        self.param_hint = param_hint
-
-    def format_message(self) -> str:
-        if self.param_hint is not None:
-            param_hint = self.param_hint
-        elif self.param is not None:
-            param_hint = self.param.get_error_hint(self.ctx)  # type: ignore
-        else:
-            return _("Invalid value: {message}").format(message=self.message)
-
-        return _("Invalid value for {param_hint}: {message}").format(
-            param_hint=_join_param_hints(param_hint), message=self.message
-        )
-
-
-class MissingParameter(BadParameter):
-    """Raised if click required an option or argument but it was not
-    provided when invoking the script.
-
-    .. versionadded:: 4.0
-
-    :param param_type: a string that indicates the type of the parameter.
-                       The default is to inherit the parameter type from
-                       the given `param`.  Valid values are ``'parameter'``,
-                       ``'option'`` or ``'argument'``.
-    """
-
-    def __init__(
-        self,
-        message: t.Optional[str] = None,
-        ctx: t.Optional["Context"] = None,
-        param: t.Optional["Parameter"] = None,
-        param_hint: t.Optional[str] = None,
-        param_type: t.Optional[str] = None,
-    ) -> None:
-        super().__init__(message or "", ctx, param, param_hint)
-        self.param_type = param_type
-
-    def format_message(self) -> str:
-        if self.param_hint is not None:
-            param_hint: t.Optional[str] = self.param_hint
-        elif self.param is not None:
-            param_hint = self.param.get_error_hint(self.ctx)  # type: ignore
-        else:
-            param_hint = None
-
-        param_hint = _join_param_hints(param_hint)
-        param_hint = f" {param_hint}" if param_hint else ""
-
-        param_type = self.param_type
-        if param_type is None and self.param is not None:
-            param_type = self.param.param_type_name
-
-        msg = self.message
-        if self.param is not None:
-            msg_extra = self.param.type.get_missing_message(self.param)
-            if msg_extra:
-                if msg:
-                    msg += f". {msg_extra}"
-                else:
-                    msg = msg_extra
-
-        msg = f" {msg}" if msg else ""
-
-        # Translate param_type for known types.
-        if param_type == "argument":
-            missing = _("Missing argument")
-        elif param_type == "option":
-            missing = _("Missing option")
-        elif param_type == "parameter":
-            missing = _("Missing parameter")
-        else:
-            missing = _("Missing {param_type}").format(param_type=param_type)
-
-        return f"{missing}{param_hint}.{msg}"
-
-    def __str__(self) -> str:
-        if not self.message:
-            param_name = self.param.name if self.param else None
-            return _("Missing parameter: {param_name}").format(param_name=param_name)
-        else:
-            return self.message
-
-
-class NoSuchOption(UsageError):
-    """Raised if click attempted to handle an option that does not
-    exist.
-
-    .. versionadded:: 4.0
-    """
-
-    def __init__(
-        self,
-        option_name: str,
-        message: t.Optional[str] = None,
-        possibilities: t.Optional[t.Sequence[str]] = None,
-        ctx: t.Optional["Context"] = None,
-    ) -> None:
-        if message is None:
-            message = _("No such option: {name}").format(name=option_name)
-
-        super().__init__(message, ctx)
-        self.option_name = option_name
-        self.possibilities = possibilities
-
-    def format_message(self) -> str:
-        if not self.possibilities:
-            return self.message
-
-        possibility_str = ", ".join(sorted(self.possibilities))
-        suggest = ngettext(
-            "Did you mean {possibility}?",
-            "(Possible options: {possibilities})",
-            len(self.possibilities),
-        ).format(possibility=possibility_str, possibilities=possibility_str)
-        return f"{self.message} {suggest}"
-
-
-class BadOptionUsage(UsageError):
-    """Raised if an option is generally supplied but the use of the option
-    was incorrect.  This is for instance raised if the number of arguments
-    for an option is not correct.
-
-    .. versionadded:: 4.0
-
-    :param option_name: the name of the option being used incorrectly.
-    """
-
-    def __init__(
-        self, option_name: str, message: str, ctx: t.Optional["Context"] = None
-    ) -> None:
-        super().__init__(message, ctx)
-        self.option_name = option_name
-
-
-class BadArgumentUsage(UsageError):
-    """Raised if an argument is generally supplied but the use of the argument
-    was incorrect.  This is for instance raised if the number of values
-    for an argument is not correct.
-
-    .. versionadded:: 6.0
-    """
-
-
-class FileError(ClickException):
-    """Raised if a file cannot be opened."""
-
-    def __init__(self, filename: str, hint: t.Optional[str] = None) -> None:
-        if hint is None:
-            hint = _("unknown error")
-
-        super().__init__(hint)
-        self.ui_filename: str = format_filename(filename)
-        self.filename = filename
-
-    def format_message(self) -> str:
-        return _("Could not open file {filename!r}: {message}").format(
-            filename=self.ui_filename, message=self.message
-        )
-
-
-class Abort(RuntimeError):
-    """An internal signalling exception that signals Click to abort."""
-
-
-class Exit(RuntimeError):
-    """An exception that indicates that the application should exit with some
-    status code.
-
-    :param code: the status code to exit with.
-    """
-
-    __slots__ = ("exit_code",)
-
-    def __init__(self, code: int = 0) -> None:
-        self.exit_code: int = code
diff --git a/spaces/cncanon/freeturbo/Dockerfile b/spaces/cncanon/freeturbo/Dockerfile
deleted file mode 100644
index eef259fa372a804549fb0af0913718a13344da34..0000000000000000000000000000000000000000
--- a/spaces/cncanon/freeturbo/Dockerfile
+++ /dev/null
@@ -1,11 +0,0 @@
-FROM node:18-bullseye-slim
-RUN apt-get update && \
-    apt-get install -y git
-RUN git clone https://gitgud.io/khanon/oai-reverse-proxy.git /app
-WORKDIR /app
-RUN npm install
-COPY Dockerfile greeting.md* .env* ./
-RUN npm run build
-EXPOSE 7860
-ENV NODE_ENV=production
-CMD [ "npm", "start" ]
diff --git a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/adpcm.c b/spaces/colakin/video-generater/public/ffmpeg/libavcodec/adpcm.c
deleted file mode 100644
index 451696932d1b5fa84e031a2354664e9fc5102f0d..0000000000000000000000000000000000000000
--- a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/adpcm.c
+++ /dev/null
@@ -1,2398 +0,0 @@
-/*
- * Copyright (c) 2001-2003 The FFmpeg project
- *
- * first version by Francois Revol (revol@free.fr)
- * fringe ADPCM codecs (e.g., DK3, DK4, Westwood)
- *   by Mike Melanson (melanson@pcisys.net)
- * CD-ROM XA ADPCM codec by BERO
- * EA ADPCM decoder by Robin Kay (komadori@myrealbox.com)
- * EA ADPCM R1/R2/R3 decoder by Peter Ross (pross@xvid.org)
- * EA IMA EACS decoder by Peter Ross (pross@xvid.org)
- * EA IMA SEAD decoder by Peter Ross (pross@xvid.org)
- * EA ADPCM XAS decoder by Peter Ross (pross@xvid.org)
- * MAXIS EA ADPCM decoder by Robert Marston (rmarston@gmail.com)
- * THP ADPCM decoder by Marco Gerards (mgerards@xs4all.nl)
- * Argonaut Games ADPCM decoder by Zane van Iperen (zane@zanevaniperen.com)
- * Simon & Schuster Interactive ADPCM decoder by Zane van Iperen (zane@zanevaniperen.com)
- * Ubisoft ADPCM decoder by Zane van Iperen (zane@zanevaniperen.com)
- * High Voltage Software ALP decoder by Zane van Iperen (zane@zanevaniperen.com)
- * Cunning Developments decoder by Zane van Iperen (zane@zanevaniperen.com)
- *
- * This file is part of FFmpeg.
- *
- * FFmpeg is free software; you can redistribute it and/or
- * modify it under the terms of the GNU Lesser General Public
- * License as published by the Free Software Foundation; either
- * version 2.1 of the License, or (at your option) any later version.
- *
- * FFmpeg is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
- * Lesser General Public License for more details.
- *
- * You should have received a copy of the GNU Lesser General Public
- * License along with FFmpeg; if not, write to the Free Software
- * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
- */
-
-#include "config_components.h"
-
-#include "avcodec.h"
-#include "get_bits.h"
-#include "bytestream.h"
-#include "adpcm.h"
-#include "adpcm_data.h"
-#include "codec_internal.h"
-#include "decode.h"
-
-/**
- * @file
- * ADPCM decoders
- * Features and limitations:
- *
- * Reference documents:
- * http://wiki.multimedia.cx/index.php?title=Category:ADPCM_Audio_Codecs
- * http://www.pcisys.net/~melanson/codecs/simpleaudio.html [dead]
- * http://www.geocities.com/SiliconValley/8682/aud3.txt [dead]
- * http://openquicktime.sourceforge.net/
- * XAnim sources (xa_codec.c) http://xanim.polter.net/
- * http://www.cs.ucla.edu/~leec/mediabench/applications.html [dead]
- * SoX source code http://sox.sourceforge.net/
- *
- * CD-ROM XA:
- * http://ku-www.ss.titech.ac.jp/~yatsushi/xaadpcm.html [dead]
- * vagpack & depack http://homepages.compuserve.de/bITmASTER32/psx-index.html [dead]
- * readstr http://www.geocities.co.jp/Playtown/2004/
- */
-
-#define CASE_0(codec_id, ...)
-#define CASE_1(codec_id, ...) \
-    case codec_id:            \
-    { __VA_ARGS__ }           \
-    break;
-#define CASE_2(enabled, codec_id, ...) \
-        CASE_ ## enabled(codec_id, __VA_ARGS__)
-#define CASE_3(config, codec_id, ...) \
-        CASE_2(config, codec_id, __VA_ARGS__)
-#define CASE(codec, ...) \
-        CASE_3(CONFIG_ ## codec ## _DECODER, AV_CODEC_ID_ ## codec, __VA_ARGS__)
-
-/* These are for CD-ROM XA ADPCM */
-static const int8_t xa_adpcm_table[5][2] = {
-    {   0,   0 },
-    {  60,   0 },
-    { 115, -52 },
-    {  98, -55 },
-    { 122, -60 }
-};
-
-static const int16_t afc_coeffs[2][16] = {
-    { 0, 2048, 0, 1024, 4096, 3584, 3072, 4608, 4200, 4800, 5120, 2048, 1024, -1024, -1024, -2048 },
-    { 0, 0, 2048, 1024, -2048, -1536, -1024, -2560, -2248, -2300, -3072, -2048, -1024, 1024, 0, 0 }
-};
-
-static const int16_t ea_adpcm_table[] = {
-    0,  240,  460,  392,
-    0,    0, -208, -220,
-    0,    1,    3,    4,
-    7,    8,   10,   11,
-    0,   -1,   -3,   -4
-};
-
-/*
- * Dumped from the binaries:
- * - FantasticJourney.exe - 0x794D2, DGROUP:0x47A4D2
- * - BigRaceUSA.exe       - 0x9B8AA, DGROUP:0x49C4AA
- * - Timeshock!.exe       - 0x8506A, DGROUP:0x485C6A
- */
-static const int8_t ima_cunning_index_table[9] = {
-    -1, -1, -1, -1, 1, 2, 3, 4, -1
-};
-
-/*
- * Dumped from the binaries:
- * - FantasticJourney.exe - 0x79458, DGROUP:0x47A458
- * - BigRaceUSA.exe       - 0x9B830, DGROUP:0x49C430
- * - Timeshock!.exe       - 0x84FF0, DGROUP:0x485BF0
- */
-static const int16_t ima_cunning_step_table[61] = {
-       1,    1,   1,      1,     2,     2,     3,     3,    4,      5,
-       6,    7,   8,     10,    12,    14,    16,    20,    24,    28,
-      32,   40,  48,     56,    64,    80,    96,   112,   128,   160,
-     192,  224,  256,   320,   384,   448,   512,   640,   768,   896,
-    1024, 1280, 1536,  1792,  2048,  2560,  3072,  3584,  4096,  5120,
-    6144, 7168, 8192, 10240, 12288, 14336, 16384, 20480, 24576, 28672, 0
-};
-
-static const int8_t adpcm_index_table2[4] = {
-    -1,  2,
-    -1,  2,
-};
-
-static const int8_t adpcm_index_table3[8] = {
-    -1, -1,  1,  2,
-    -1, -1,  1,  2,
-};
-
-static const int8_t adpcm_index_table5[32] = {
-    -1, -1, -1, -1, -1, -1, -1, -1, 1, 2, 4, 6, 8, 10, 13, 16,
-    -1, -1, -1, -1, -1, -1, -1, -1, 1, 2, 4, 6, 8, 10, 13, 16,
-};
-
-static const int8_t * const adpcm_index_tables[4] = {
-    &adpcm_index_table2[0],
-    &adpcm_index_table3[0],
-    &ff_adpcm_index_table[0],
-    &adpcm_index_table5[0],
-};
-
-static const int16_t mtaf_stepsize[32][16] = {
-    {     1,     5,     9,    13,    16,    20,    24,    28,
-         -1,    -5,    -9,   -13,   -16,   -20,   -24,   -28, },
-    {     2,     6,    11,    15,    20,    24,    29,    33,
-         -2,    -6,   -11,   -15,   -20,   -24,   -29,   -33, },
-    {     2,     7,    13,    18,    23,    28,    34,    39,
-         -2,    -7,   -13,   -18,   -23,   -28,   -34,   -39, },
-    {     3,     9,    15,    21,    28,    34,    40,    46,
-         -3,    -9,   -15,   -21,   -28,   -34,   -40,   -46, },
-    {     3,    11,    18,    26,    33,    41,    48,    56,
-         -3,   -11,   -18,   -26,   -33,   -41,   -48,   -56, },
-    {     4,    13,    22,    31,    40,    49,    58,    67,
-         -4,   -13,   -22,   -31,   -40,   -49,   -58,   -67, },
-    {     5,    16,    26,    37,    48,    59,    69,    80,
-         -5,   -16,   -26,   -37,   -48,   -59,   -69,   -80, },
-    {     6,    19,    31,    44,    57,    70,    82,    95,
-         -6,   -19,   -31,   -44,   -57,   -70,   -82,   -95, },
-    {     7,    22,    38,    53,    68,    83,    99,   114,
-         -7,   -22,   -38,   -53,   -68,   -83,   -99,  -114, },
-    {     9,    27,    45,    63,    81,    99,   117,   135,
-         -9,   -27,   -45,   -63,   -81,   -99,  -117,  -135, },
-    {    10,    32,    53,    75,    96,   118,   139,   161,
-        -10,   -32,   -53,   -75,   -96,  -118,  -139,  -161, },
-    {    12,    38,    64,    90,   115,   141,   167,   193,
-        -12,   -38,   -64,   -90,  -115,  -141,  -167,  -193, },
-    {    15,    45,    76,   106,   137,   167,   198,   228,
-        -15,   -45,   -76,  -106,  -137,  -167,  -198,  -228, },
-    {    18,    54,    91,   127,   164,   200,   237,   273,
-        -18,   -54,   -91,  -127,  -164,  -200,  -237,  -273, },
-    {    21,    65,   108,   152,   195,   239,   282,   326,
-        -21,   -65,  -108,  -152,  -195,  -239,  -282,  -326, },
-    {    25,    77,   129,   181,   232,   284,   336,   388,
-        -25,   -77,  -129,  -181,  -232,  -284,  -336,  -388, },
-    {    30,    92,   153,   215,   276,   338,   399,   461,
-        -30,   -92,  -153,  -215,  -276,  -338,  -399,  -461, },
-    {    36,   109,   183,   256,   329,   402,   476,   549,
-        -36,  -109,  -183,  -256,  -329,  -402,  -476,  -549, },
-    {    43,   130,   218,   305,   392,   479,   567,   654,
-        -43,  -130,  -218,  -305,  -392,  -479,  -567,  -654, },
-    {    52,   156,   260,   364,   468,   572,   676,   780,
-        -52,  -156,  -260,  -364,  -468,  -572,  -676,  -780, },
-    {    62,   186,   310,   434,   558,   682,   806,   930,
-        -62,  -186,  -310,  -434,  -558,  -682,  -806,  -930, },
-    {    73,   221,   368,   516,   663,   811,   958,  1106,
-        -73,  -221,  -368,  -516,  -663,  -811,  -958, -1106, },
-    {    87,   263,   439,   615,   790,   966,  1142,  1318,
-        -87,  -263,  -439,  -615,  -790,  -966, -1142, -1318, },
-    {   104,   314,   523,   733,   942,  1152,  1361,  1571,
-       -104,  -314,  -523,  -733,  -942, -1152, -1361, -1571, },
-    {   124,   374,   623,   873,  1122,  1372,  1621,  1871,
-       -124,  -374,  -623,  -873, -1122, -1372, -1621, -1871, },
-    {   148,   445,   743,  1040,  1337,  1634,  1932,  2229,
-       -148,  -445,  -743, -1040, -1337, -1634, -1932, -2229, },
-    {   177,   531,   885,  1239,  1593,  1947,  2301,  2655,
-       -177,  -531,  -885, -1239, -1593, -1947, -2301, -2655, },
-    {   210,   632,  1053,  1475,  1896,  2318,  2739,  3161,
-       -210,  -632, -1053, -1475, -1896, -2318, -2739, -3161, },
-    {   251,   753,  1255,  1757,  2260,  2762,  3264,  3766,
-       -251,  -753, -1255, -1757, -2260, -2762, -3264, -3766, },
-    {   299,   897,  1495,  2093,  2692,  3290,  3888,  4486,
-       -299,  -897, -1495, -2093, -2692, -3290, -3888, -4486, },
-    {   356,  1068,  1781,  2493,  3206,  3918,  4631,  5343,
-       -356, -1068, -1781, -2493, -3206, -3918, -4631, -5343, },
-    {   424,  1273,  2121,  2970,  3819,  4668,  5516,  6365,
-       -424, -1273, -2121, -2970, -3819, -4668, -5516, -6365, },
-};
-
-static const int16_t oki_step_table[49] = {
-     16,  17,  19,  21,   23,   25,   28,   31,   34,  37,
-     41,  45,  50,  55,   60,   66,   73,   80,   88,  97,
-    107, 118, 130, 143,  157,  173,  190,  209,  230, 253,
-    279, 307, 337, 371,  408,  449,  494,  544,  598, 658,
-    724, 796, 876, 963, 1060, 1166, 1282, 1411, 1552
-};
-
-// padded to zero where table size is less then 16
-static const int8_t swf_index_tables[4][16] = {
-    /*2*/ { -1, 2 },
-    /*3*/ { -1, -1, 2, 4 },
-    /*4*/ { -1, -1, -1, -1, 2, 4, 6, 8 },
-    /*5*/ { -1, -1, -1, -1, -1, -1, -1, -1, 1, 2, 4, 6, 8, 10, 13, 16 }
-};
-
-static const int8_t zork_index_table[8] = {
-    -1, -1, -1, 1, 4, 7, 10, 12,
-};
-
-static const int8_t mtf_index_table[16] = {
-     8,  6,  4,  2, -1, -1, -1, -1,
-    -1, -1, -1, -1,  2,  4,  6,  8,
-};
-
-/* end of tables */
-
-typedef struct ADPCMDecodeContext {
-    ADPCMChannelStatus status[14];
-    int vqa_version;                /**< VQA version. Used for ADPCM_IMA_WS */
-    int has_status;                 /**< Status flag. Reset to 0 after a flush. */
-} ADPCMDecodeContext;
-
-static void adpcm_flush(AVCodecContext *avctx);
-
-static av_cold int adpcm_decode_init(AVCodecContext * avctx)
-{
-    ADPCMDecodeContext *c = avctx->priv_data;
-    unsigned int min_channels = 1;
-    unsigned int max_channels = 2;
-
-    adpcm_flush(avctx);
-
-    switch(avctx->codec->id) {
-    case AV_CODEC_ID_ADPCM_IMA_AMV:
-        max_channels = 1;
-        break;
-    case AV_CODEC_ID_ADPCM_DTK:
-    case AV_CODEC_ID_ADPCM_EA:
-        min_channels = 2;
-        break;
-    case AV_CODEC_ID_ADPCM_AFC:
-    case AV_CODEC_ID_ADPCM_EA_R1:
-    case AV_CODEC_ID_ADPCM_EA_R2:
-    case AV_CODEC_ID_ADPCM_EA_R3:
-    case AV_CODEC_ID_ADPCM_EA_XAS:
-    case AV_CODEC_ID_ADPCM_MS:
-        max_channels = 6;
-        break;
-    case AV_CODEC_ID_ADPCM_MTAF:
-        min_channels = 2;
-        max_channels = 8;
-        if (avctx->ch_layout.nb_channels & 1) {
-            avpriv_request_sample(avctx, "channel count %d", avctx->ch_layout.nb_channels);
-            return AVERROR_PATCHWELCOME;
-        }
-        break;
-    case AV_CODEC_ID_ADPCM_PSX:
-        max_channels = 8;
-        if (avctx->ch_layout.nb_channels <= 0 ||
-            avctx->block_align % (16 * avctx->ch_layout.nb_channels))
-            return AVERROR_INVALIDDATA;
-        break;
-    case AV_CODEC_ID_ADPCM_IMA_DAT4:
-    case AV_CODEC_ID_ADPCM_THP:
-    case AV_CODEC_ID_ADPCM_THP_LE:
-        max_channels = 14;
-        break;
-    }
-    if (avctx->ch_layout.nb_channels < min_channels ||
-        avctx->ch_layout.nb_channels > max_channels) {
-        av_log(avctx, AV_LOG_ERROR, "Invalid number of channels\n");
-        return AVERROR(EINVAL);
-    }
-
-    switch(avctx->codec->id) {
-    case AV_CODEC_ID_ADPCM_IMA_WAV:
-        if (avctx->bits_per_coded_sample < 2 || avctx->bits_per_coded_sample > 5)
-            return AVERROR_INVALIDDATA;
-        break;
-    case AV_CODEC_ID_ADPCM_ARGO:
-        if (avctx->bits_per_coded_sample != 4 ||
-            avctx->block_align != 17 * avctx->ch_layout.nb_channels)
-            return AVERROR_INVALIDDATA;
-        break;
-    case AV_CODEC_ID_ADPCM_ZORK:
-        if (avctx->bits_per_coded_sample != 8)
-            return AVERROR_INVALIDDATA;
-        break;
-    default:
-        break;
-    }
-
-    switch (avctx->codec->id) {
-    case AV_CODEC_ID_ADPCM_AICA:
-    case AV_CODEC_ID_ADPCM_IMA_CUNNING:
-    case AV_CODEC_ID_ADPCM_IMA_DAT4:
-    case AV_CODEC_ID_ADPCM_IMA_QT:
-    case AV_CODEC_ID_ADPCM_IMA_WAV:
-    case AV_CODEC_ID_ADPCM_4XM:
-    case AV_CODEC_ID_ADPCM_XA:
-    case AV_CODEC_ID_ADPCM_XMD:
-    case AV_CODEC_ID_ADPCM_EA_R1:
-    case AV_CODEC_ID_ADPCM_EA_R2:
-    case AV_CODEC_ID_ADPCM_EA_R3:
-    case AV_CODEC_ID_ADPCM_EA_XAS:
-    case AV_CODEC_ID_ADPCM_THP:
-    case AV_CODEC_ID_ADPCM_THP_LE:
-    case AV_CODEC_ID_ADPCM_AFC:
-    case AV_CODEC_ID_ADPCM_DTK:
-    case AV_CODEC_ID_ADPCM_PSX:
-    case AV_CODEC_ID_ADPCM_MTAF:
-    case AV_CODEC_ID_ADPCM_ARGO:
-    case AV_CODEC_ID_ADPCM_IMA_MOFLEX:
-        avctx->sample_fmt = AV_SAMPLE_FMT_S16P;
-        break;
-    case AV_CODEC_ID_ADPCM_IMA_WS:
-        avctx->sample_fmt = c->vqa_version == 3 ? AV_SAMPLE_FMT_S16P :
-                                                  AV_SAMPLE_FMT_S16;
-        break;
-    case AV_CODEC_ID_ADPCM_MS:
-        avctx->sample_fmt = avctx->ch_layout.nb_channels > 2 ? AV_SAMPLE_FMT_S16P :
-                                                  AV_SAMPLE_FMT_S16;
-        break;
-    default:
-        avctx->sample_fmt = AV_SAMPLE_FMT_S16;
-    }
-    return 0;
-}
-
-static inline int16_t adpcm_agm_expand_nibble(ADPCMChannelStatus *c, int8_t nibble)
-{
-    int delta, pred, step, add;
-
-    pred = c->predictor;
-    delta = nibble & 7;
-    step = c->step;
-    add = (delta * 2 + 1) * step;
-    if (add < 0)
-        add = add + 7;
-
-    if ((nibble & 8) == 0)
-        pred = av_clip(pred + (add >> 3), -32767, 32767);
-    else
-        pred = av_clip(pred - (add >> 3), -32767, 32767);
-
-    switch (delta) {
-    case 7:
-        step *= 0x99;
-        break;
-    case 6:
-        c->step = av_clip(c->step * 2, 127, 24576);
-        c->predictor = pred;
-        return pred;
-    case 5:
-        step *= 0x66;
-        break;
-    case 4:
-        step *= 0x4d;
-        break;
-    default:
-        step *= 0x39;
-        break;
-    }
-
-    if (step < 0)
-        step += 0x3f;
-
-    c->step = step >> 6;
-    c->step = av_clip(c->step, 127, 24576);
-    c->predictor = pred;
-    return pred;
-}
-
-static inline int16_t adpcm_ima_expand_nibble(ADPCMChannelStatus *c, int8_t nibble, int shift)
-{
-    int step_index;
-    int predictor;
-    int sign, delta, diff, step;
-
-    step = ff_adpcm_step_table[c->step_index];
-    step_index = c->step_index + ff_adpcm_index_table[(unsigned)nibble];
-    step_index = av_clip(step_index, 0, 88);
-
-    sign = nibble & 8;
-    delta = nibble & 7;
-    /* perform direct multiplication instead of series of jumps proposed by
-     * the reference ADPCM implementation since modern CPUs can do the mults
-     * quickly enough */
-    diff = ((2 * delta + 1) * step) >> shift;
-    predictor = c->predictor;
-    if (sign) predictor -= diff;
-    else predictor += diff;
-
-    c->predictor = av_clip_int16(predictor);
-    c->step_index = step_index;
-
-    return (int16_t)c->predictor;
-}
-
-static inline int16_t adpcm_ima_alp_expand_nibble(ADPCMChannelStatus *c, int8_t nibble, int shift)
-{
-    int step_index;
-    int predictor;
-    int sign, delta, diff, step;
-
-    step = ff_adpcm_step_table[c->step_index];
-    step_index = c->step_index + ff_adpcm_index_table[(unsigned)nibble];
-    step_index = av_clip(step_index, 0, 88);
-
-    sign = nibble & 8;
-    delta = nibble & 7;
-    diff = (delta * step) >> shift;
-    predictor = c->predictor;
-    if (sign) predictor -= diff;
-    else predictor += diff;
-
-    c->predictor = av_clip_int16(predictor);
-    c->step_index = step_index;
-
-    return (int16_t)c->predictor;
-}
-
-static inline int16_t adpcm_ima_mtf_expand_nibble(ADPCMChannelStatus *c, int nibble)
-{
-    int step_index, step, delta, predictor;
-
-    step = ff_adpcm_step_table[c->step_index];
-
-    delta = step * (2 * nibble - 15);
-    predictor = c->predictor + delta;
-
-    step_index = c->step_index + mtf_index_table[(unsigned)nibble];
-    c->predictor = av_clip_int16(predictor >> 4);
-    c->step_index = av_clip(step_index, 0, 88);
-
-    return (int16_t)c->predictor;
-}
-
-static inline int16_t adpcm_ima_cunning_expand_nibble(ADPCMChannelStatus *c, int8_t nibble)
-{
-    int step_index;
-    int predictor;
-    int step;
-
-    nibble = sign_extend(nibble & 0xF, 4);
-
-    step = ima_cunning_step_table[c->step_index];
-    step_index = c->step_index + ima_cunning_index_table[abs(nibble)];
-    step_index = av_clip(step_index, 0, 60);
-
-    predictor = c->predictor + step * nibble;
-
-    c->predictor = av_clip_int16(predictor);
-    c->step_index = step_index;
-
-    return c->predictor;
-}
-
-static inline int16_t adpcm_ima_wav_expand_nibble(ADPCMChannelStatus *c, GetBitContext *gb, int bps)
-{
-    int nibble, step_index, predictor, sign, delta, diff, step, shift;
-
-    shift = bps - 1;
-    nibble = get_bits_le(gb, bps),
-    step = ff_adpcm_step_table[c->step_index];
-    step_index = c->step_index + adpcm_index_tables[bps - 2][nibble];
-    step_index = av_clip(step_index, 0, 88);
-
-    sign = nibble & (1 << shift);
-    delta = av_mod_uintp2(nibble, shift);
-    diff = ((2 * delta + 1) * step) >> shift;
-    predictor = c->predictor;
-    if (sign) predictor -= diff;
-    else predictor += diff;
-
-    c->predictor = av_clip_int16(predictor);
-    c->step_index = step_index;
-
-    return (int16_t)c->predictor;
-}
-
-static inline int adpcm_ima_qt_expand_nibble(ADPCMChannelStatus *c, int nibble)
-{
-    int step_index;
-    int predictor;
-    int diff, step;
-
-    step = ff_adpcm_step_table[c->step_index];
-    step_index = c->step_index + ff_adpcm_index_table[nibble];
-    step_index = av_clip(step_index, 0, 88);
-
-    diff = step >> 3;
-    if (nibble & 4) diff += step;
-    if (nibble & 2) diff += step >> 1;
-    if (nibble & 1) diff += step >> 2;
-
-    if (nibble & 8)
-        predictor = c->predictor - diff;
-    else
-        predictor = c->predictor + diff;
-
-    c->predictor = av_clip_int16(predictor);
-    c->step_index = step_index;
-
-    return c->predictor;
-}
-
-static inline int16_t adpcm_ms_expand_nibble(ADPCMChannelStatus *c, int nibble)
-{
-    int predictor;
-
-    predictor = (((c->sample1) * (c->coeff1)) + ((c->sample2) * (c->coeff2))) / 64;
-    predictor += ((nibble & 0x08)?(nibble - 0x10):(nibble)) * c->idelta;
-
-    c->sample2 = c->sample1;
-    c->sample1 = av_clip_int16(predictor);
-    c->idelta = (ff_adpcm_AdaptationTable[(int)nibble] * c->idelta) >> 8;
-    if (c->idelta < 16) c->idelta = 16;
-    if (c->idelta > INT_MAX/768) {
-        av_log(NULL, AV_LOG_WARNING, "idelta overflow\n");
-        c->idelta = INT_MAX/768;
-    }
-
-    return c->sample1;
-}
-
-static inline int16_t adpcm_ima_oki_expand_nibble(ADPCMChannelStatus *c, int nibble)
-{
-    int step_index, predictor, sign, delta, diff, step;
-
-    step = oki_step_table[c->step_index];
-    step_index = c->step_index + ff_adpcm_index_table[(unsigned)nibble];
-    step_index = av_clip(step_index, 0, 48);
-
-    sign = nibble & 8;
-    delta = nibble & 7;
-    diff = ((2 * delta + 1) * step) >> 3;
-    predictor = c->predictor;
-    if (sign) predictor -= diff;
-    else predictor += diff;
-
-    c->predictor = av_clip_intp2(predictor, 11);
-    c->step_index = step_index;
-
-    return c->predictor * 16;
-}
-
-static inline int16_t adpcm_ct_expand_nibble(ADPCMChannelStatus *c, int8_t nibble)
-{
-    int sign, delta, diff;
-    int new_step;
-
-    sign = nibble & 8;
-    delta = nibble & 7;
-    /* perform direct multiplication instead of series of jumps proposed by
-     * the reference ADPCM implementation since modern CPUs can do the mults
-     * quickly enough */
-    diff = ((2 * delta + 1) * c->step) >> 3;
-    /* predictor update is not so trivial: predictor is multiplied on 254/256 before updating */
-    c->predictor = ((c->predictor * 254) >> 8) + (sign ? -diff : diff);
-    c->predictor = av_clip_int16(c->predictor);
-    /* calculate new step and clamp it to range 511..32767 */
-    new_step = (ff_adpcm_AdaptationTable[nibble & 7] * c->step) >> 8;
-    c->step = av_clip(new_step, 511, 32767);
-
-    return (int16_t)c->predictor;
-}
-
-static inline int16_t adpcm_sbpro_expand_nibble(ADPCMChannelStatus *c, int8_t nibble, int size, int shift)
-{
-    int sign, delta, diff;
-
-    sign = nibble & (1<<(size-1));
-    delta = nibble & ((1<<(size-1))-1);
-    diff = delta << (7 + c->step + shift);
-
-    /* clamp result */
-    c->predictor = av_clip(c->predictor + (sign ? -diff : diff), -16384,16256);
-
-    /* calculate new step */
-    if (delta >= (2*size - 3) && c->step < 3)
-        c->step++;
-    else if (delta == 0 && c->step > 0)
-        c->step--;
-
-    return (int16_t) c->predictor;
-}
-
-static inline int16_t adpcm_yamaha_expand_nibble(ADPCMChannelStatus *c, uint8_t nibble)
-{
-    if(!c->step) {
-        c->predictor = 0;
-        c->step = 127;
-    }
-
-    c->predictor += (c->step * ff_adpcm_yamaha_difflookup[nibble]) / 8;
-    c->predictor = av_clip_int16(c->predictor);
-    c->step = (c->step * ff_adpcm_yamaha_indexscale[nibble]) >> 8;
-    c->step = av_clip(c->step, 127, 24576);
-    return c->predictor;
-}
-
-static inline int16_t adpcm_mtaf_expand_nibble(ADPCMChannelStatus *c, uint8_t nibble)
-{
-    c->predictor += mtaf_stepsize[c->step][nibble];
-    c->predictor = av_clip_int16(c->predictor);
-    c->step += ff_adpcm_index_table[nibble];
-    c->step = av_clip_uintp2(c->step, 5);
-    return c->predictor;
-}
-
-static inline int16_t adpcm_zork_expand_nibble(ADPCMChannelStatus *c, uint8_t nibble)
-{
-    int16_t index = c->step_index;
-    uint32_t lookup_sample = ff_adpcm_step_table[index];
-    int32_t sample = 0;
-
-    if (nibble & 0x40)
-        sample += lookup_sample;
-    if (nibble & 0x20)
-        sample += lookup_sample >> 1;
-    if (nibble & 0x10)
-        sample += lookup_sample >> 2;
-    if (nibble & 0x08)
-        sample += lookup_sample >> 3;
-    if (nibble & 0x04)
-        sample += lookup_sample >> 4;
-    if (nibble & 0x02)
-        sample += lookup_sample >> 5;
-    if (nibble & 0x01)
-        sample += lookup_sample >> 6;
-    if (nibble & 0x80)
-        sample = -sample;
-
-    sample += c->predictor;
-    sample = av_clip_int16(sample);
-
-    index += zork_index_table[(nibble >> 4) & 7];
-    index = av_clip(index, 0, 88);
-
-    c->predictor = sample;
-    c->step_index = index;
-
-    return sample;
-}
-
-static int xa_decode(AVCodecContext *avctx, int16_t *out0, int16_t *out1,
-                     const uint8_t *in, ADPCMChannelStatus *left,
-                     ADPCMChannelStatus *right, int channels, int sample_offset)
-{
-    int i, j;
-    int shift,filter,f0,f1;
-    int s_1,s_2;
-    int d,s,t;
-
-    out0 += sample_offset;
-    if (channels == 1)
-        out1 = out0 + 28;
-    else
-        out1 += sample_offset;
-
-    for(i=0;i<4;i++) {
-        shift  = 12 - (in[4+i*2] & 15);
-        filter = in[4+i*2] >> 4;
-        if (filter >= FF_ARRAY_ELEMS(xa_adpcm_table)) {
-            avpriv_request_sample(avctx, "unknown XA-ADPCM filter %d", filter);
-            filter=0;
-        }
-        if (shift < 0) {
-            avpriv_request_sample(avctx, "unknown XA-ADPCM shift %d", shift);
-            shift = 0;
-        }
-        f0 = xa_adpcm_table[filter][0];
-        f1 = xa_adpcm_table[filter][1];
-
-        s_1 = left->sample1;
-        s_2 = left->sample2;
-
-        for(j=0;j<28;j++) {
-            d = in[16+i+j*4];
-
-            t = sign_extend(d, 4);
-            s = t*(1<<shift) + ((s_1*f0 + s_2*f1+32)>>6);
-            s_2 = s_1;
-            s_1 = av_clip_int16(s);
-            out0[j] = s_1;
-        }
-
-        if (channels == 2) {
-            left->sample1 = s_1;
-            left->sample2 = s_2;
-            s_1 = right->sample1;
-            s_2 = right->sample2;
-        }
-
-        shift  = 12 - (in[5+i*2] & 15);
-        filter = in[5+i*2] >> 4;
-        if (filter >= FF_ARRAY_ELEMS(xa_adpcm_table) || shift < 0) {
-            avpriv_request_sample(avctx, "unknown XA-ADPCM filter %d", filter);
-            filter=0;
-        }
-        if (shift < 0) {
-            avpriv_request_sample(avctx, "unknown XA-ADPCM shift %d", shift);
-            shift = 0;
-        }
-
-        f0 = xa_adpcm_table[filter][0];
-        f1 = xa_adpcm_table[filter][1];
-
-        for(j=0;j<28;j++) {
-            d = in[16+i+j*4];
-
-            t = sign_extend(d >> 4, 4);
-            s = t*(1<<shift) + ((s_1*f0 + s_2*f1+32)>>6);
-            s_2 = s_1;
-            s_1 = av_clip_int16(s);
-            out1[j] = s_1;
-        }
-
-        if (channels == 2) {
-            right->sample1 = s_1;
-            right->sample2 = s_2;
-        } else {
-            left->sample1 = s_1;
-            left->sample2 = s_2;
-        }
-
-        out0 += 28 * (3 - channels);
-        out1 += 28 * (3 - channels);
-    }
-
-    return 0;
-}
-
-static void adpcm_swf_decode(AVCodecContext *avctx, const uint8_t *buf, int buf_size, int16_t *samples)
-{
-    ADPCMDecodeContext *c = avctx->priv_data;
-    GetBitContext gb;
-    const int8_t *table;
-    int channels = avctx->ch_layout.nb_channels;
-    int k0, signmask, nb_bits, count;
-    int size = buf_size*8;
-    int i;
-
-    init_get_bits(&gb, buf, size);
-
-    //read bits & initial values
-    nb_bits = get_bits(&gb, 2)+2;
-    table = swf_index_tables[nb_bits-2];
-    k0 = 1 << (nb_bits-2);
-    signmask = 1 << (nb_bits-1);
-
-    while (get_bits_count(&gb) <= size - 22 * channels) {
-        for (i = 0; i < channels; i++) {
-            *samples++ = c->status[i].predictor = get_sbits(&gb, 16);
-            c->status[i].step_index = get_bits(&gb, 6);
-        }
-
-        for (count = 0; get_bits_count(&gb) <= size - nb_bits * channels && count < 4095; count++) {
-            int i;
-
-            for (i = 0; i < channels; i++) {
-                // similar to IMA adpcm
-                int delta = get_bits(&gb, nb_bits);
-                int step = ff_adpcm_step_table[c->status[i].step_index];
-                int vpdiff = 0; // vpdiff = (delta+0.5)*step/4
-                int k = k0;
-
-                do {
-                    if (delta & k)
-                        vpdiff += step;
-                    step >>= 1;
-                    k >>= 1;
-                } while(k);
-                vpdiff += step;
-
-                if (delta & signmask)
-                    c->status[i].predictor -= vpdiff;
-                else
-                    c->status[i].predictor += vpdiff;
-
-                c->status[i].step_index += table[delta & (~signmask)];
-
-                c->status[i].step_index = av_clip(c->status[i].step_index, 0, 88);
-                c->status[i].predictor = av_clip_int16(c->status[i].predictor);
-
-                *samples++ = c->status[i].predictor;
-            }
-        }
-    }
-}
-
-int16_t ff_adpcm_argo_expand_nibble(ADPCMChannelStatus *cs, int nibble, int shift, int flag)
-{
-    int sample = sign_extend(nibble, 4) * (1 << shift);
-
-    if (flag)
-        sample += (8 * cs->sample1) - (4 * cs->sample2);
-    else
-        sample += 4 * cs->sample1;
-
-    sample = av_clip_int16(sample >> 2);
-
-    cs->sample2 = cs->sample1;
-    cs->sample1 = sample;
-
-    return sample;
-}
-
-/**
- * Get the number of samples (per channel) that will be decoded from the packet.
- * In one case, this is actually the maximum number of samples possible to
- * decode with the given buf_size.
- *
- * @param[out] coded_samples set to the number of samples as coded in the
- *                           packet, or 0 if the codec does not encode the
- *                           number of samples in each frame.
- * @param[out] approx_nb_samples set to non-zero if the number of samples
- *                               returned is an approximation.
- */
-static int get_nb_samples(AVCodecContext *avctx, GetByteContext *gb,
-                          int buf_size, int *coded_samples, int *approx_nb_samples)
-{
-    ADPCMDecodeContext *s = avctx->priv_data;
-    int nb_samples        = 0;
-    int ch                = avctx->ch_layout.nb_channels;
-    int has_coded_samples = 0;
-    int header_size;
-
-    *coded_samples = 0;
-    *approx_nb_samples = 0;
-
-    if(ch <= 0)
-        return 0;
-
-    switch (avctx->codec->id) {
-    /* constant, only check buf_size */
-    case AV_CODEC_ID_ADPCM_EA_XAS:
-        if (buf_size < 76 * ch)
-            return 0;
-        nb_samples = 128;
-        break;
-    case AV_CODEC_ID_ADPCM_IMA_QT:
-        if (buf_size < 34 * ch)
-            return 0;
-        nb_samples = 64;
-        break;
-    /* simple 4-bit adpcm */
-    case AV_CODEC_ID_ADPCM_CT:
-    case AV_CODEC_ID_ADPCM_IMA_APC:
-    case AV_CODEC_ID_ADPCM_IMA_CUNNING:
-    case AV_CODEC_ID_ADPCM_IMA_EA_SEAD:
-    case AV_CODEC_ID_ADPCM_IMA_OKI:
-    case AV_CODEC_ID_ADPCM_IMA_WS:
-    case AV_CODEC_ID_ADPCM_YAMAHA:
-    case AV_CODEC_ID_ADPCM_AICA:
-    case AV_CODEC_ID_ADPCM_IMA_SSI:
-    case AV_CODEC_ID_ADPCM_IMA_APM:
-    case AV_CODEC_ID_ADPCM_IMA_ALP:
-    case AV_CODEC_ID_ADPCM_IMA_MTF:
-        nb_samples = buf_size * 2 / ch;
-        break;
-    }
-    if (nb_samples)
-        return nb_samples;
-
-    /* simple 4-bit adpcm, with header */
-    header_size = 0;
-    switch (avctx->codec->id) {
-        case AV_CODEC_ID_ADPCM_4XM:
-        case AV_CODEC_ID_ADPCM_AGM:
-        case AV_CODEC_ID_ADPCM_IMA_ACORN:
-        case AV_CODEC_ID_ADPCM_IMA_DAT4:
-        case AV_CODEC_ID_ADPCM_IMA_MOFLEX:
-        case AV_CODEC_ID_ADPCM_IMA_ISS:     header_size = 4 * ch;      break;
-        case AV_CODEC_ID_ADPCM_IMA_SMJPEG:  header_size = 4 * ch;      break;
-    }
-    if (header_size > 0)
-        return (buf_size - header_size) * 2 / ch;
-
-    /* more complex formats */
-    switch (avctx->codec->id) {
-    case AV_CODEC_ID_ADPCM_IMA_AMV:
-        bytestream2_skip(gb, 4);
-        has_coded_samples  = 1;
-        *coded_samples     = bytestream2_get_le32u(gb);
-        nb_samples         = FFMIN((buf_size - 8) * 2, *coded_samples);
-        bytestream2_seek(gb, -8, SEEK_CUR);
-        break;
-    case AV_CODEC_ID_ADPCM_EA:
-        has_coded_samples = 1;
-        *coded_samples  = bytestream2_get_le32(gb);
-        *coded_samples -= *coded_samples % 28;
-        nb_samples      = (buf_size - 12) / 30 * 28;
-        break;
-    case AV_CODEC_ID_ADPCM_IMA_EA_EACS:
-        has_coded_samples = 1;
-        *coded_samples = bytestream2_get_le32(gb);
-        nb_samples     = (buf_size - (4 + 8 * ch)) * 2 / ch;
-        break;
-    case AV_CODEC_ID_ADPCM_EA_MAXIS_XA:
-        nb_samples = (buf_size - ch) / ch * 2;
-        break;
-    case AV_CODEC_ID_ADPCM_EA_R1:
-    case AV_CODEC_ID_ADPCM_EA_R2:
-    case AV_CODEC_ID_ADPCM_EA_R3:
-        /* maximum number of samples */
-        /* has internal offsets and a per-frame switch to signal raw 16-bit */
-        has_coded_samples = 1;
-        switch (avctx->codec->id) {
-        case AV_CODEC_ID_ADPCM_EA_R1:
-            header_size    = 4 + 9 * ch;
-            *coded_samples = bytestream2_get_le32(gb);
-            break;
-        case AV_CODEC_ID_ADPCM_EA_R2:
-            header_size    = 4 + 5 * ch;
-            *coded_samples = bytestream2_get_le32(gb);
-            break;
-        case AV_CODEC_ID_ADPCM_EA_R3:
-            header_size    = 4 + 5 * ch;
-            *coded_samples = bytestream2_get_be32(gb);
-            break;
-        }
-        *coded_samples -= *coded_samples % 28;
-        nb_samples      = (buf_size - header_size) * 2 / ch;
-        nb_samples     -= nb_samples % 28;
-        *approx_nb_samples = 1;
-        break;
-    case AV_CODEC_ID_ADPCM_IMA_DK3:
-        if (avctx->block_align > 0)
-            buf_size = FFMIN(buf_size, avctx->block_align);
-        nb_samples = ((buf_size - 16) * 2 / 3 * 4) / ch;
-        break;
-    case AV_CODEC_ID_ADPCM_IMA_DK4:
-        if (avctx->block_align > 0)
-            buf_size = FFMIN(buf_size, avctx->block_align);
-        if (buf_size < 4 * ch)
-            return AVERROR_INVALIDDATA;
-        nb_samples = 1 + (buf_size - 4 * ch) * 2 / ch;
-        break;
-    case AV_CODEC_ID_ADPCM_IMA_RAD:
-        if (avctx->block_align > 0)
-            buf_size = FFMIN(buf_size, avctx->block_align);
-        nb_samples = (buf_size - 4 * ch) * 2 / ch;
-        break;
-    CASE(ADPCM_IMA_WAV,
-        int bsize = ff_adpcm_ima_block_sizes[avctx->bits_per_coded_sample - 2];
-        int bsamples = ff_adpcm_ima_block_samples[avctx->bits_per_coded_sample - 2];
-        if (avctx->block_align > 0)
-            buf_size = FFMIN(buf_size, avctx->block_align);
-        if (buf_size < 4 * ch)
-            return AVERROR_INVALIDDATA;
-        nb_samples = 1 + (buf_size - 4 * ch) / (bsize * ch) * bsamples;
-        ) /* End of CASE */
-    case AV_CODEC_ID_ADPCM_MS:
-        if (avctx->block_align > 0)
-            buf_size = FFMIN(buf_size, avctx->block_align);
-        nb_samples = (buf_size - 6 * ch) * 2 / ch;
-        break;
-    case AV_CODEC_ID_ADPCM_MTAF:
-        if (avctx->block_align > 0)
-            buf_size = FFMIN(buf_size, avctx->block_align);
-        nb_samples = (buf_size - 16 * (ch / 2)) * 2 / ch;
-        break;
-    case AV_CODEC_ID_ADPCM_SBPRO_2:
-    case AV_CODEC_ID_ADPCM_SBPRO_3:
-    case AV_CODEC_ID_ADPCM_SBPRO_4:
-    {
-        int samples_per_byte;
-        switch (avctx->codec->id) {
-        case AV_CODEC_ID_ADPCM_SBPRO_2: samples_per_byte = 4; break;
-        case AV_CODEC_ID_ADPCM_SBPRO_3: samples_per_byte = 3; break;
-        case AV_CODEC_ID_ADPCM_SBPRO_4: samples_per_byte = 2; break;
-        }
-        if (!s->status[0].step_index) {
-            if (buf_size < ch)
-                return AVERROR_INVALIDDATA;
-            nb_samples++;
-            buf_size -= ch;
-        }
-        nb_samples += buf_size * samples_per_byte / ch;
-        break;
-    }
-    case AV_CODEC_ID_ADPCM_SWF:
-    {
-        int buf_bits       = buf_size * 8 - 2;
-        int nbits          = (bytestream2_get_byte(gb) >> 6) + 2;
-        int block_hdr_size = 22 * ch;
-        int block_size     = block_hdr_size + nbits * ch * 4095;
-        int nblocks        = buf_bits / block_size;
-        int bits_left      = buf_bits - nblocks * block_size;
-        nb_samples         = nblocks * 4096;
-        if (bits_left >= block_hdr_size)
-            nb_samples += 1 + (bits_left - block_hdr_size) / (nbits * ch);
-        break;
-    }
-    case AV_CODEC_ID_ADPCM_THP:
-    case AV_CODEC_ID_ADPCM_THP_LE:
-        if (avctx->extradata) {
-            nb_samples = buf_size * 14 / (8 * ch);
-            break;
-        }
-        has_coded_samples = 1;
-        bytestream2_skip(gb, 4); // channel size
-        *coded_samples  = (avctx->codec->id == AV_CODEC_ID_ADPCM_THP_LE) ?
-                          bytestream2_get_le32(gb) :
-                          bytestream2_get_be32(gb);
-        buf_size       -= 8 + 36 * ch;
-        buf_size       /= ch;
-        nb_samples      = buf_size / 8 * 14;
-        if (buf_size % 8 > 1)
-            nb_samples     += (buf_size % 8 - 1) * 2;
-        *approx_nb_samples = 1;
-        break;
-    case AV_CODEC_ID_ADPCM_AFC:
-        nb_samples = buf_size / (9 * ch) * 16;
-        break;
-    case AV_CODEC_ID_ADPCM_XA:
-        nb_samples = (buf_size / 128) * 224 / ch;
-        break;
-    case AV_CODEC_ID_ADPCM_XMD:
-        nb_samples = buf_size / (21 * ch) * 32;
-        break;
-    case AV_CODEC_ID_ADPCM_DTK:
-    case AV_CODEC_ID_ADPCM_PSX:
-        nb_samples = buf_size / (16 * ch) * 28;
-        break;
-    case AV_CODEC_ID_ADPCM_ARGO:
-        nb_samples = buf_size / avctx->block_align * 32;
-        break;
-    case AV_CODEC_ID_ADPCM_ZORK:
-        nb_samples = buf_size / ch;
-        break;
-    }
-
-    /* validate coded sample count */
-    if (has_coded_samples && (*coded_samples <= 0 || *coded_samples > nb_samples))
-        return AVERROR_INVALIDDATA;
-
-    return nb_samples;
-}
-
-static int adpcm_decode_frame(AVCodecContext *avctx, AVFrame *frame,
-                              int *got_frame_ptr, AVPacket *avpkt)
-{
-    const uint8_t *buf = avpkt->data;
-    int buf_size = avpkt->size;
-    ADPCMDecodeContext *c = avctx->priv_data;
-    int channels = avctx->ch_layout.nb_channels;
-    int16_t *samples;
-    int16_t **samples_p;
-    int st; /* stereo */
-    int nb_samples, coded_samples, approx_nb_samples, ret;
-    GetByteContext gb;
-
-    bytestream2_init(&gb, buf, buf_size);
-    nb_samples = get_nb_samples(avctx, &gb, buf_size, &coded_samples, &approx_nb_samples);
-    if (nb_samples <= 0) {
-        av_log(avctx, AV_LOG_ERROR, "invalid number of samples in packet\n");
-        return AVERROR_INVALIDDATA;
-    }
-
-    /* get output buffer */
-    frame->nb_samples = nb_samples;
-    if ((ret = ff_get_buffer(avctx, frame, 0)) < 0)
-        return ret;
-    samples = (int16_t *)frame->data[0];
-    samples_p = (int16_t **)frame->extended_data;
-
-    /* use coded_samples when applicable */
-    /* it is always <= nb_samples, so the output buffer will be large enough */
-    if (coded_samples) {
-        if (!approx_nb_samples && coded_samples != nb_samples)
-            av_log(avctx, AV_LOG_WARNING, "mismatch in coded sample count\n");
-        frame->nb_samples = nb_samples = coded_samples;
-    }
-
-    st = channels == 2 ? 1 : 0;
-
-    switch(avctx->codec->id) {
-    CASE(ADPCM_IMA_QT,
-        /* In QuickTime, IMA is encoded by chunks of 34 bytes (=64 samples).
-           Channel data is interleaved per-chunk. */
-        for (int channel = 0; channel < channels; channel++) {
-            ADPCMChannelStatus *cs = &c->status[channel];
-            int predictor;
-            int step_index;
-            /* (pppppp) (piiiiiii) */
-
-            /* Bits 15-7 are the _top_ 9 bits of the 16-bit initial predictor value */
-            predictor = sign_extend(bytestream2_get_be16u(&gb), 16);
-            step_index = predictor & 0x7F;
-            predictor &= ~0x7F;
-
-            if (cs->step_index == step_index) {
-                int diff = predictor - cs->predictor;
-                if (diff < 0)
-                    diff = - diff;
-                if (diff > 0x7f)
-                    goto update;
-            } else {
-            update:
-                cs->step_index = step_index;
-                cs->predictor = predictor;
-            }
-
-            if (cs->step_index > 88u){
-                av_log(avctx, AV_LOG_ERROR, "ERROR: step_index[%d] = %i\n",
-                       channel, cs->step_index);
-                return AVERROR_INVALIDDATA;
-            }
-
-            samples = samples_p[channel];
-
-            for (int m = 0; m < 64; m += 2) {
-                int byte = bytestream2_get_byteu(&gb);
-                samples[m    ] = adpcm_ima_qt_expand_nibble(cs, byte & 0x0F);
-                samples[m + 1] = adpcm_ima_qt_expand_nibble(cs, byte >> 4  );
-            }
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_WAV,
-        for (int i = 0; i < channels; i++) {
-            ADPCMChannelStatus *cs = &c->status[i];
-            cs->predictor = samples_p[i][0] = sign_extend(bytestream2_get_le16u(&gb), 16);
-
-            cs->step_index = sign_extend(bytestream2_get_le16u(&gb), 16);
-            if (cs->step_index > 88u){
-                av_log(avctx, AV_LOG_ERROR, "ERROR: step_index[%d] = %i\n",
-                       i, cs->step_index);
-                return AVERROR_INVALIDDATA;
-            }
-        }
-
-        if (avctx->bits_per_coded_sample != 4) {
-            int samples_per_block = ff_adpcm_ima_block_samples[avctx->bits_per_coded_sample - 2];
-            int block_size = ff_adpcm_ima_block_sizes[avctx->bits_per_coded_sample - 2];
-            uint8_t temp[20 + AV_INPUT_BUFFER_PADDING_SIZE] = { 0 };
-            GetBitContext g;
-
-            for (int n = 0; n < (nb_samples - 1) / samples_per_block; n++) {
-                for (int i = 0; i < channels; i++) {
-                    ADPCMChannelStatus *cs = &c->status[i];
-                    samples = &samples_p[i][1 + n * samples_per_block];
-                    for (int j = 0; j < block_size; j++) {
-                        temp[j] = buf[4 * channels + block_size * n * channels +
-                                        (j % 4) + (j / 4) * (channels * 4) + i * 4];
-                    }
-                    ret = init_get_bits8(&g, (const uint8_t *)&temp, block_size);
-                    if (ret < 0)
-                        return ret;
-                    for (int m = 0; m < samples_per_block; m++) {
-                        samples[m] = adpcm_ima_wav_expand_nibble(cs, &g,
-                                          avctx->bits_per_coded_sample);
-                    }
-                }
-            }
-            bytestream2_skip(&gb, avctx->block_align - channels * 4);
-        } else {
-            for (int n = 0; n < (nb_samples - 1) / 8; n++) {
-                for (int i = 0; i < channels; i++) {
-                    ADPCMChannelStatus *cs = &c->status[i];
-                    samples = &samples_p[i][1 + n * 8];
-                    for (int m = 0; m < 8; m += 2) {
-                        int v = bytestream2_get_byteu(&gb);
-                        samples[m    ] = adpcm_ima_expand_nibble(cs, v & 0x0F, 3);
-                        samples[m + 1] = adpcm_ima_expand_nibble(cs, v >> 4  , 3);
-                    }
-                }
-            }
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_4XM,
-        for (int i = 0; i < channels; i++)
-            c->status[i].predictor = sign_extend(bytestream2_get_le16u(&gb), 16);
-
-        for (int i = 0; i < channels; i++) {
-            c->status[i].step_index = sign_extend(bytestream2_get_le16u(&gb), 16);
-            if (c->status[i].step_index > 88u) {
-                av_log(avctx, AV_LOG_ERROR, "ERROR: step_index[%d] = %i\n",
-                       i, c->status[i].step_index);
-                return AVERROR_INVALIDDATA;
-            }
-        }
-
-        for (int i = 0; i < channels; i++) {
-            ADPCMChannelStatus *cs = &c->status[i];
-            samples = (int16_t *)frame->data[i];
-            for (int n = nb_samples >> 1; n > 0; n--) {
-                int v = bytestream2_get_byteu(&gb);
-                *samples++ = adpcm_ima_expand_nibble(cs, v & 0x0F, 4);
-                *samples++ = adpcm_ima_expand_nibble(cs, v >> 4  , 4);
-            }
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_AGM,
-        for (int i = 0; i < channels; i++)
-            c->status[i].predictor = sign_extend(bytestream2_get_le16u(&gb), 16);
-        for (int i = 0; i < channels; i++)
-            c->status[i].step = sign_extend(bytestream2_get_le16u(&gb), 16);
-
-        for (int n = 0; n < nb_samples >> (1 - st); n++) {
-            int v = bytestream2_get_byteu(&gb);
-            *samples++ = adpcm_agm_expand_nibble(&c->status[0], v & 0xF);
-            *samples++ = adpcm_agm_expand_nibble(&c->status[st], v >> 4 );
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_MS,
-        int block_predictor;
-
-        if (avctx->ch_layout.nb_channels > 2) {
-            for (int channel = 0; channel < avctx->ch_layout.nb_channels; channel++) {
-                samples = samples_p[channel];
-                block_predictor = bytestream2_get_byteu(&gb);
-                if (block_predictor > 6) {
-                    av_log(avctx, AV_LOG_ERROR, "ERROR: block_predictor[%d] = %d\n",
-                           channel, block_predictor);
-                    return AVERROR_INVALIDDATA;
-                }
-                c->status[channel].coeff1 = ff_adpcm_AdaptCoeff1[block_predictor];
-                c->status[channel].coeff2 = ff_adpcm_AdaptCoeff2[block_predictor];
-                c->status[channel].idelta = sign_extend(bytestream2_get_le16u(&gb), 16);
-                c->status[channel].sample1 = sign_extend(bytestream2_get_le16u(&gb), 16);
-                c->status[channel].sample2 = sign_extend(bytestream2_get_le16u(&gb), 16);
-                *samples++ = c->status[channel].sample2;
-                *samples++ = c->status[channel].sample1;
-                for (int n = (nb_samples - 2) >> 1; n > 0; n--) {
-                    int byte = bytestream2_get_byteu(&gb);
-                    *samples++ = adpcm_ms_expand_nibble(&c->status[channel], byte >> 4  );
-                    *samples++ = adpcm_ms_expand_nibble(&c->status[channel], byte & 0x0F);
-                }
-            }
-        } else {
-            block_predictor = bytestream2_get_byteu(&gb);
-            if (block_predictor > 6) {
-                av_log(avctx, AV_LOG_ERROR, "ERROR: block_predictor[0] = %d\n",
-                       block_predictor);
-                return AVERROR_INVALIDDATA;
-            }
-            c->status[0].coeff1 = ff_adpcm_AdaptCoeff1[block_predictor];
-            c->status[0].coeff2 = ff_adpcm_AdaptCoeff2[block_predictor];
-            if (st) {
-                block_predictor = bytestream2_get_byteu(&gb);
-                if (block_predictor > 6) {
-                    av_log(avctx, AV_LOG_ERROR, "ERROR: block_predictor[1] = %d\n",
-                           block_predictor);
-                    return AVERROR_INVALIDDATA;
-                }
-                c->status[1].coeff1 = ff_adpcm_AdaptCoeff1[block_predictor];
-                c->status[1].coeff2 = ff_adpcm_AdaptCoeff2[block_predictor];
-            }
-            c->status[0].idelta = sign_extend(bytestream2_get_le16u(&gb), 16);
-            if (st){
-                c->status[1].idelta = sign_extend(bytestream2_get_le16u(&gb), 16);
-            }
-
-            c->status[0].sample1 = sign_extend(bytestream2_get_le16u(&gb), 16);
-            if (st) c->status[1].sample1 = sign_extend(bytestream2_get_le16u(&gb), 16);
-            c->status[0].sample2 = sign_extend(bytestream2_get_le16u(&gb), 16);
-            if (st) c->status[1].sample2 = sign_extend(bytestream2_get_le16u(&gb), 16);
-
-            *samples++ = c->status[0].sample2;
-            if (st) *samples++ = c->status[1].sample2;
-            *samples++ = c->status[0].sample1;
-            if (st) *samples++ = c->status[1].sample1;
-            for (int n = (nb_samples - 2) >> (1 - st); n > 0; n--) {
-                int byte = bytestream2_get_byteu(&gb);
-                *samples++ = adpcm_ms_expand_nibble(&c->status[0 ], byte >> 4  );
-                *samples++ = adpcm_ms_expand_nibble(&c->status[st], byte & 0x0F);
-            }
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_MTAF,
-        for (int channel = 0; channel < channels; channel += 2) {
-            bytestream2_skipu(&gb, 4);
-            c->status[channel    ].step      = bytestream2_get_le16u(&gb) & 0x1f;
-            c->status[channel + 1].step      = bytestream2_get_le16u(&gb) & 0x1f;
-            c->status[channel    ].predictor = sign_extend(bytestream2_get_le16u(&gb), 16);
-            bytestream2_skipu(&gb, 2);
-            c->status[channel + 1].predictor = sign_extend(bytestream2_get_le16u(&gb), 16);
-            bytestream2_skipu(&gb, 2);
-            for (int n = 0; n < nb_samples; n += 2) {
-                int v = bytestream2_get_byteu(&gb);
-                samples_p[channel][n    ] = adpcm_mtaf_expand_nibble(&c->status[channel], v & 0x0F);
-                samples_p[channel][n + 1] = adpcm_mtaf_expand_nibble(&c->status[channel], v >> 4  );
-            }
-            for (int n = 0; n < nb_samples; n += 2) {
-                int v = bytestream2_get_byteu(&gb);
-                samples_p[channel + 1][n    ] = adpcm_mtaf_expand_nibble(&c->status[channel + 1], v & 0x0F);
-                samples_p[channel + 1][n + 1] = adpcm_mtaf_expand_nibble(&c->status[channel + 1], v >> 4  );
-            }
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_DK4,
-        for (int channel = 0; channel < channels; channel++) {
-            ADPCMChannelStatus *cs = &c->status[channel];
-            cs->predictor  = *samples++ = sign_extend(bytestream2_get_le16u(&gb), 16);
-            cs->step_index = sign_extend(bytestream2_get_le16u(&gb), 16);
-            if (cs->step_index > 88u){
-                av_log(avctx, AV_LOG_ERROR, "ERROR: step_index[%d] = %i\n",
-                       channel, cs->step_index);
-                return AVERROR_INVALIDDATA;
-            }
-        }
-        for (int n = (nb_samples - 1) >> (1 - st); n > 0; n--) {
-            int v = bytestream2_get_byteu(&gb);
-            *samples++ = adpcm_ima_expand_nibble(&c->status[0 ], v >> 4  , 3);
-            *samples++ = adpcm_ima_expand_nibble(&c->status[st], v & 0x0F, 3);
-        }
-        ) /* End of CASE */
-
-        /* DK3 ADPCM support macro */
-#define DK3_GET_NEXT_NIBBLE() \
-    if (decode_top_nibble_next) { \
-        nibble = last_byte >> 4; \
-        decode_top_nibble_next = 0; \
-    } else { \
-        last_byte = bytestream2_get_byteu(&gb); \
-        nibble = last_byte & 0x0F; \
-        decode_top_nibble_next = 1; \
-    }
-    CASE(ADPCM_IMA_DK3,
-        int last_byte = 0;
-        int nibble;
-        int decode_top_nibble_next = 0;
-        int diff_channel;
-        const int16_t *samples_end = samples + channels * nb_samples;
-
-        bytestream2_skipu(&gb, 10);
-        c->status[0].predictor  = sign_extend(bytestream2_get_le16u(&gb), 16);
-        c->status[1].predictor  = sign_extend(bytestream2_get_le16u(&gb), 16);
-        c->status[0].step_index = bytestream2_get_byteu(&gb);
-        c->status[1].step_index = bytestream2_get_byteu(&gb);
-        if (c->status[0].step_index > 88u || c->status[1].step_index > 88u){
-            av_log(avctx, AV_LOG_ERROR, "ERROR: step_index = %i/%i\n",
-                   c->status[0].step_index, c->status[1].step_index);
-            return AVERROR_INVALIDDATA;
-        }
-        /* sign extend the predictors */
-        diff_channel = c->status[1].predictor;
-
-        while (samples < samples_end) {
-
-            /* for this algorithm, c->status[0] is the sum channel and
-             * c->status[1] is the diff channel */
-
-            /* process the first predictor of the sum channel */
-            DK3_GET_NEXT_NIBBLE();
-            adpcm_ima_expand_nibble(&c->status[0], nibble, 3);
-
-            /* process the diff channel predictor */
-            DK3_GET_NEXT_NIBBLE();
-            adpcm_ima_expand_nibble(&c->status[1], nibble, 3);
-
-            /* process the first pair of stereo PCM samples */
-            diff_channel = (diff_channel + c->status[1].predictor) / 2;
-            *samples++ = c->status[0].predictor + c->status[1].predictor;
-            *samples++ = c->status[0].predictor - c->status[1].predictor;
-
-            /* process the second predictor of the sum channel */
-            DK3_GET_NEXT_NIBBLE();
-            adpcm_ima_expand_nibble(&c->status[0], nibble, 3);
-
-            /* process the second pair of stereo PCM samples */
-            diff_channel = (diff_channel + c->status[1].predictor) / 2;
-            *samples++ = c->status[0].predictor + c->status[1].predictor;
-            *samples++ = c->status[0].predictor - c->status[1].predictor;
-        }
-
-        if ((bytestream2_tell(&gb) & 1))
-            bytestream2_skip(&gb, 1);
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_ISS,
-        for (int channel = 0; channel < channels; channel++) {
-            ADPCMChannelStatus *cs = &c->status[channel];
-            cs->predictor  = sign_extend(bytestream2_get_le16u(&gb), 16);
-            cs->step_index = sign_extend(bytestream2_get_le16u(&gb), 16);
-            if (cs->step_index > 88u){
-                av_log(avctx, AV_LOG_ERROR, "ERROR: step_index[%d] = %i\n",
-                       channel, cs->step_index);
-                return AVERROR_INVALIDDATA;
-            }
-        }
-
-        for (int n = nb_samples >> (1 - st); n > 0; n--) {
-            int v1, v2;
-            int v = bytestream2_get_byteu(&gb);
-            /* nibbles are swapped for mono */
-            if (st) {
-                v1 = v >> 4;
-                v2 = v & 0x0F;
-            } else {
-                v2 = v >> 4;
-                v1 = v & 0x0F;
-            }
-            *samples++ = adpcm_ima_expand_nibble(&c->status[0 ], v1, 3);
-            *samples++ = adpcm_ima_expand_nibble(&c->status[st], v2, 3);
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_MOFLEX,
-        for (int channel = 0; channel < channels; channel++) {
-            ADPCMChannelStatus *cs = &c->status[channel];
-            cs->step_index = sign_extend(bytestream2_get_le16u(&gb), 16);
-            cs->predictor  = sign_extend(bytestream2_get_le16u(&gb), 16);
-            if (cs->step_index > 88u){
-                av_log(avctx, AV_LOG_ERROR, "ERROR: step_index[%d] = %i\n",
-                       channel, cs->step_index);
-                return AVERROR_INVALIDDATA;
-            }
-        }
-
-        for (int subframe = 0; subframe < nb_samples / 256; subframe++) {
-            for (int channel = 0; channel < channels; channel++) {
-                samples = samples_p[channel] + 256 * subframe;
-                for (int n = 0; n < 256; n += 2) {
-                    int v = bytestream2_get_byteu(&gb);
-                    *samples++ = adpcm_ima_expand_nibble(&c->status[channel], v & 0x0F, 3);
-                    *samples++ = adpcm_ima_expand_nibble(&c->status[channel], v >> 4  , 3);
-                }
-            }
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_DAT4,
-        for (int channel = 0; channel < channels; channel++) {
-            ADPCMChannelStatus *cs = &c->status[channel];
-            samples = samples_p[channel];
-            bytestream2_skip(&gb, 4);
-            for (int n = 0; n < nb_samples; n += 2) {
-                int v = bytestream2_get_byteu(&gb);
-                *samples++ = adpcm_ima_expand_nibble(cs, v >> 4  , 3);
-                *samples++ = adpcm_ima_expand_nibble(cs, v & 0x0F, 3);
-            }
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_APC,
-        for (int n = nb_samples >> (1 - st); n > 0; n--) {
-            int v = bytestream2_get_byteu(&gb);
-            *samples++ = adpcm_ima_expand_nibble(&c->status[0],  v >> 4  , 3);
-            *samples++ = adpcm_ima_expand_nibble(&c->status[st], v & 0x0F, 3);
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_SSI,
-        for (int n = nb_samples >> (1 - st); n > 0; n--) {
-            int v = bytestream2_get_byteu(&gb);
-            *samples++ = adpcm_ima_qt_expand_nibble(&c->status[0],  v >> 4  );
-            *samples++ = adpcm_ima_qt_expand_nibble(&c->status[st], v & 0x0F);
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_APM,
-        for (int n = nb_samples / 2; n > 0; n--) {
-            for (int channel = 0; channel < channels; channel++) {
-                int v = bytestream2_get_byteu(&gb);
-                *samples++  = adpcm_ima_qt_expand_nibble(&c->status[channel], v >> 4  );
-                samples[st] = adpcm_ima_qt_expand_nibble(&c->status[channel], v & 0x0F);
-            }
-            samples += channels;
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_ALP,
-        for (int n = nb_samples / 2; n > 0; n--) {
-            for (int channel = 0; channel < channels; channel++) {
-                int v = bytestream2_get_byteu(&gb);
-                *samples++  = adpcm_ima_alp_expand_nibble(&c->status[channel], v >> 4  , 2);
-                samples[st] = adpcm_ima_alp_expand_nibble(&c->status[channel], v & 0x0F, 2);
-            }
-            samples += channels;
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_CUNNING,
-        for (int channel = 0; channel < channels; channel++) {
-            int16_t *smp = samples_p[channel];
-            for (int n = 0; n < nb_samples / 2; n++) {
-                int v = bytestream2_get_byteu(&gb);
-                *smp++ = adpcm_ima_cunning_expand_nibble(&c->status[channel], v & 0x0F);
-                *smp++ = adpcm_ima_cunning_expand_nibble(&c->status[channel], v >> 4);
-            }
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_OKI,
-        for (int n = nb_samples >> (1 - st); n > 0; n--) {
-            int v = bytestream2_get_byteu(&gb);
-            *samples++ = adpcm_ima_oki_expand_nibble(&c->status[0],  v >> 4  );
-            *samples++ = adpcm_ima_oki_expand_nibble(&c->status[st], v & 0x0F);
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_RAD,
-        for (int channel = 0; channel < channels; channel++) {
-            ADPCMChannelStatus *cs = &c->status[channel];
-            cs->step_index = sign_extend(bytestream2_get_le16u(&gb), 16);
-            cs->predictor  = sign_extend(bytestream2_get_le16u(&gb), 16);
-            if (cs->step_index > 88u){
-                av_log(avctx, AV_LOG_ERROR, "ERROR: step_index[%d] = %i\n",
-                       channel, cs->step_index);
-                return AVERROR_INVALIDDATA;
-            }
-        }
-        for (int n = 0; n < nb_samples / 2; n++) {
-            int byte[2];
-
-            byte[0] = bytestream2_get_byteu(&gb);
-            if (st)
-                byte[1] = bytestream2_get_byteu(&gb);
-            for (int channel = 0; channel < channels; channel++) {
-                *samples++ = adpcm_ima_expand_nibble(&c->status[channel], byte[channel] & 0x0F, 3);
-            }
-            for (int channel = 0; channel < channels; channel++) {
-                *samples++ = adpcm_ima_expand_nibble(&c->status[channel], byte[channel] >> 4  , 3);
-            }
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_WS,
-        if (c->vqa_version == 3) {
-            for (int channel = 0; channel < channels; channel++) {
-                int16_t *smp = samples_p[channel];
-
-                for (int n = nb_samples / 2; n > 0; n--) {
-                    int v = bytestream2_get_byteu(&gb);
-                    *smp++ = adpcm_ima_expand_nibble(&c->status[channel], v & 0x0F, 3);
-                    *smp++ = adpcm_ima_expand_nibble(&c->status[channel], v >> 4  , 3);
-                }
-            }
-        } else {
-            for (int n = nb_samples / 2; n > 0; n--) {
-                for (int channel = 0; channel < channels; channel++) {
-                    int v = bytestream2_get_byteu(&gb);
-                    *samples++  = adpcm_ima_expand_nibble(&c->status[channel], v & 0x0F, 3);
-                    samples[st] = adpcm_ima_expand_nibble(&c->status[channel], v >> 4  , 3);
-                }
-                samples += channels;
-            }
-        }
-        bytestream2_seek(&gb, 0, SEEK_END);
-        ) /* End of CASE */
-    CASE(ADPCM_XMD,
-        int bytes_remaining, block = 0;
-        while (bytestream2_get_bytes_left(&gb) >= 21 * channels) {
-            for (int channel = 0; channel < channels; channel++) {
-                int16_t *out = samples_p[channel] + block * 32;
-                int16_t history[2];
-                uint16_t scale;
-
-                history[1] = sign_extend(bytestream2_get_le16(&gb), 16);
-                history[0] = sign_extend(bytestream2_get_le16(&gb), 16);
-                scale = bytestream2_get_le16(&gb);
-
-                out[0] = history[1];
-                out[1] = history[0];
-
-                for (int n = 0; n < 15; n++) {
-                    unsigned byte = bytestream2_get_byte(&gb);
-                    int32_t nibble[2];
-
-                    nibble[0] = sign_extend(byte & 15, 4);
-                    nibble[1] = sign_extend(byte >> 4, 4);
-
-                    out[2+n*2] = (nibble[0]*(scale<<14) + (history[0]*29336) - (history[1]*13136)) >> 14;
-                    history[1] = history[0];
-                    history[0] = out[2+n*2];
-
-                    out[2+n*2+1] = (nibble[1]*(scale<<14) + (history[0]*29336) - (history[1]*13136)) >> 14;
-                    history[1] = history[0];
-                    history[0] = out[2+n*2+1];
-                }
-            }
-
-            block++;
-        }
-        bytes_remaining = bytestream2_get_bytes_left(&gb);
-        if (bytes_remaining > 0) {
-            bytestream2_skip(&gb, bytes_remaining);
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_XA,
-        int16_t *out0 = samples_p[0];
-        int16_t *out1 = samples_p[1];
-        int samples_per_block = 28 * (3 - channels) * 4;
-        int sample_offset = 0;
-        int bytes_remaining;
-        while (bytestream2_get_bytes_left(&gb) >= 128) {
-            if ((ret = xa_decode(avctx, out0, out1, buf + bytestream2_tell(&gb),
-                                 &c->status[0], &c->status[1],
-                                 channels, sample_offset)) < 0)
-                return ret;
-            bytestream2_skipu(&gb, 128);
-            sample_offset += samples_per_block;
-        }
-        /* Less than a full block of data left, e.g. when reading from
-         * 2324 byte per sector XA; the remainder is padding */
-        bytes_remaining = bytestream2_get_bytes_left(&gb);
-        if (bytes_remaining > 0) {
-            bytestream2_skip(&gb, bytes_remaining);
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_EA_EACS,
-        for (int i = 0; i <= st; i++) {
-            c->status[i].step_index = bytestream2_get_le32u(&gb);
-            if (c->status[i].step_index > 88u) {
-                av_log(avctx, AV_LOG_ERROR, "ERROR: step_index[%d] = %i\n",
-                       i, c->status[i].step_index);
-                return AVERROR_INVALIDDATA;
-            }
-        }
-        for (int i = 0; i <= st; i++) {
-            c->status[i].predictor  = bytestream2_get_le32u(&gb);
-            if (FFABS((int64_t)c->status[i].predictor) > (1<<16))
-                return AVERROR_INVALIDDATA;
-        }
-
-        for (int n = nb_samples >> (1 - st); n > 0; n--) {
-            int byte   = bytestream2_get_byteu(&gb);
-            *samples++ = adpcm_ima_expand_nibble(&c->status[0],  byte >> 4,   3);
-            *samples++ = adpcm_ima_expand_nibble(&c->status[st], byte & 0x0F, 3);
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_EA_SEAD,
-        for (int n = nb_samples >> (1 - st); n > 0; n--) {
-            int byte = bytestream2_get_byteu(&gb);
-            *samples++ = adpcm_ima_expand_nibble(&c->status[0],  byte >> 4,   6);
-            *samples++ = adpcm_ima_expand_nibble(&c->status[st], byte & 0x0F, 6);
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_EA,
-        int previous_left_sample, previous_right_sample;
-        int current_left_sample, current_right_sample;
-        int next_left_sample, next_right_sample;
-        int coeff1l, coeff2l, coeff1r, coeff2r;
-        int shift_left, shift_right;
-
-        /* Each EA ADPCM frame has a 12-byte header followed by 30-byte pieces,
-           each coding 28 stereo samples. */
-
-        if (channels != 2)
-            return AVERROR_INVALIDDATA;
-
-        current_left_sample   = sign_extend(bytestream2_get_le16u(&gb), 16);
-        previous_left_sample  = sign_extend(bytestream2_get_le16u(&gb), 16);
-        current_right_sample  = sign_extend(bytestream2_get_le16u(&gb), 16);
-        previous_right_sample = sign_extend(bytestream2_get_le16u(&gb), 16);
-
-        for (int count1 = 0; count1 < nb_samples / 28; count1++) {
-            int byte = bytestream2_get_byteu(&gb);
-            coeff1l = ea_adpcm_table[ byte >> 4       ];
-            coeff2l = ea_adpcm_table[(byte >> 4  ) + 4];
-            coeff1r = ea_adpcm_table[ byte & 0x0F];
-            coeff2r = ea_adpcm_table[(byte & 0x0F) + 4];
-
-            byte = bytestream2_get_byteu(&gb);
-            shift_left  = 20 - (byte >> 4);
-            shift_right = 20 - (byte & 0x0F);
-
-            for (int count2 = 0; count2 < 28; count2++) {
-                byte = bytestream2_get_byteu(&gb);
-                next_left_sample  = sign_extend(byte >> 4, 4) * (1 << shift_left);
-                next_right_sample = sign_extend(byte,      4) * (1 << shift_right);
-
-                next_left_sample = (next_left_sample +
-                    (current_left_sample * coeff1l) +
-                    (previous_left_sample * coeff2l) + 0x80) >> 8;
-                next_right_sample = (next_right_sample +
-                    (current_right_sample * coeff1r) +
-                    (previous_right_sample * coeff2r) + 0x80) >> 8;
-
-                previous_left_sample = current_left_sample;
-                current_left_sample = av_clip_int16(next_left_sample);
-                previous_right_sample = current_right_sample;
-                current_right_sample = av_clip_int16(next_right_sample);
-                *samples++ = current_left_sample;
-                *samples++ = current_right_sample;
-            }
-        }
-
-        bytestream2_skip(&gb, 2); // Skip terminating 0x0000
-        ) /* End of CASE */
-    CASE(ADPCM_EA_MAXIS_XA,
-        int coeff[2][2], shift[2];
-
-        for (int channel = 0; channel < channels; channel++) {
-            int byte = bytestream2_get_byteu(&gb);
-            for (int i = 0; i < 2; i++)
-                coeff[channel][i] = ea_adpcm_table[(byte >> 4) + 4*i];
-            shift[channel] = 20 - (byte & 0x0F);
-        }
-        for (int count1 = 0; count1 < nb_samples / 2; count1++) {
-            int byte[2];
-
-            byte[0] = bytestream2_get_byteu(&gb);
-            if (st) byte[1] = bytestream2_get_byteu(&gb);
-            for (int i = 4; i >= 0; i-=4) { /* Pairwise samples LL RR (st) or LL LL (mono) */
-                for (int channel = 0; channel < channels; channel++) {
-                    int sample = sign_extend(byte[channel] >> i, 4) * (1 << shift[channel]);
-                    sample = (sample +
-                             c->status[channel].sample1 * coeff[channel][0] +
-                             c->status[channel].sample2 * coeff[channel][1] + 0x80) >> 8;
-                    c->status[channel].sample2 = c->status[channel].sample1;
-                    c->status[channel].sample1 = av_clip_int16(sample);
-                    *samples++ = c->status[channel].sample1;
-                }
-            }
-        }
-        bytestream2_seek(&gb, 0, SEEK_END);
-        ) /* End of CASE */
-#if CONFIG_ADPCM_EA_R1_DECODER || CONFIG_ADPCM_EA_R2_DECODER || CONFIG_ADPCM_EA_R3_DECODER
-    case AV_CODEC_ID_ADPCM_EA_R1:
-    case AV_CODEC_ID_ADPCM_EA_R2:
-    case AV_CODEC_ID_ADPCM_EA_R3: {
-        /* channel numbering
-           2chan: 0=fl, 1=fr
-           4chan: 0=fl, 1=rl, 2=fr, 3=rr
-           6chan: 0=fl, 1=c,  2=fr, 3=rl,  4=rr, 5=sub */
-        const int big_endian = avctx->codec->id == AV_CODEC_ID_ADPCM_EA_R3;
-        int previous_sample, current_sample, next_sample;
-        int coeff1, coeff2;
-        int shift;
-        uint16_t *samplesC;
-        int count = 0;
-        int offsets[6];
-
-        for (unsigned channel = 0; channel < channels; channel++)
-            offsets[channel] = (big_endian ? bytestream2_get_be32(&gb) :
-                                             bytestream2_get_le32(&gb)) +
-                               (channels + 1) * 4;
-
-        for (unsigned channel = 0; channel < channels; channel++) {
-            int count1;
-
-            bytestream2_seek(&gb, offsets[channel], SEEK_SET);
-            samplesC = samples_p[channel];
-
-            if (avctx->codec->id == AV_CODEC_ID_ADPCM_EA_R1) {
-                current_sample  = sign_extend(bytestream2_get_le16(&gb), 16);
-                previous_sample = sign_extend(bytestream2_get_le16(&gb), 16);
-            } else {
-                current_sample  = c->status[channel].predictor;
-                previous_sample = c->status[channel].prev_sample;
-            }
-
-            for (count1 = 0; count1 < nb_samples / 28; count1++) {
-                int byte = bytestream2_get_byte(&gb);
-                if (byte == 0xEE) {  /* only seen in R2 and R3 */
-                    current_sample  = sign_extend(bytestream2_get_be16(&gb), 16);
-                    previous_sample = sign_extend(bytestream2_get_be16(&gb), 16);
-
-                    for (int count2 = 0; count2 < 28; count2++)
-                        *samplesC++ = sign_extend(bytestream2_get_be16(&gb), 16);
-                } else {
-                    coeff1 = ea_adpcm_table[ byte >> 4     ];
-                    coeff2 = ea_adpcm_table[(byte >> 4) + 4];
-                    shift = 20 - (byte & 0x0F);
-
-                    for (int count2 = 0; count2 < 28; count2++) {
-                        if (count2 & 1)
-                            next_sample = (unsigned)sign_extend(byte,    4) << shift;
-                        else {
-                            byte = bytestream2_get_byte(&gb);
-                            next_sample = (unsigned)sign_extend(byte >> 4, 4) << shift;
-                        }
-
-                        next_sample += (current_sample  * coeff1) +
-                                       (previous_sample * coeff2);
-                        next_sample = av_clip_int16(next_sample >> 8);
-
-                        previous_sample = current_sample;
-                        current_sample  = next_sample;
-                        *samplesC++ = current_sample;
-                    }
-                }
-            }
-            if (!count) {
-                count = count1;
-            } else if (count != count1) {
-                av_log(avctx, AV_LOG_WARNING, "per-channel sample count mismatch\n");
-                count = FFMAX(count, count1);
-            }
-
-            if (avctx->codec->id != AV_CODEC_ID_ADPCM_EA_R1) {
-                c->status[channel].predictor   = current_sample;
-                c->status[channel].prev_sample = previous_sample;
-            }
-        }
-
-        frame->nb_samples = count * 28;
-        bytestream2_seek(&gb, 0, SEEK_END);
-        break;
-    }
-#endif /* CONFIG_ADPCM_EA_Rx_DECODER */
-    CASE(ADPCM_EA_XAS,
-        for (int channel=0; channel < channels; channel++) {
-            int coeff[2][4], shift[4];
-            int16_t *s = samples_p[channel];
-            for (int n = 0; n < 4; n++, s += 32) {
-                int val = sign_extend(bytestream2_get_le16u(&gb), 16);
-                for (int i = 0; i < 2; i++)
-                    coeff[i][n] = ea_adpcm_table[(val&0x0F)+4*i];
-                s[0] = val & ~0x0F;
-
-                val = sign_extend(bytestream2_get_le16u(&gb), 16);
-                shift[n] = 20 - (val & 0x0F);
-                s[1] = val & ~0x0F;
-            }
-
-            for (int m = 2; m < 32; m += 2) {
-                s = &samples_p[channel][m];
-                for (int n = 0; n < 4; n++, s += 32) {
-                    int level, pred;
-                    int byte = bytestream2_get_byteu(&gb);
-
-                    level = sign_extend(byte >> 4, 4) * (1 << shift[n]);
-                    pred  = s[-1] * coeff[0][n] + s[-2] * coeff[1][n];
-                    s[0]  = av_clip_int16((level + pred + 0x80) >> 8);
-
-                    level = sign_extend(byte, 4) * (1 << shift[n]);
-                    pred  = s[0] * coeff[0][n] + s[-1] * coeff[1][n];
-                    s[1]  = av_clip_int16((level + pred + 0x80) >> 8);
-                }
-            }
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_ACORN,
-        for (int channel = 0; channel < channels; channel++) {
-            ADPCMChannelStatus *cs = &c->status[channel];
-            cs->predictor  = sign_extend(bytestream2_get_le16u(&gb), 16);
-            cs->step_index = bytestream2_get_le16u(&gb) & 0xFF;
-            if (cs->step_index > 88u){
-                av_log(avctx, AV_LOG_ERROR, "ERROR: step_index[%d] = %i\n",
-                       channel, cs->step_index);
-                return AVERROR_INVALIDDATA;
-            }
-        }
-        for (int n = nb_samples >> (1 - st); n > 0; n--) {
-            int byte = bytestream2_get_byteu(&gb);
-            *samples++ = adpcm_ima_expand_nibble(&c->status[0],  byte & 0x0F, 3);
-            *samples++ = adpcm_ima_expand_nibble(&c->status[st], byte >> 4,   3);
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_AMV,
-        av_assert0(channels == 1);
-
-        /*
-         * Header format:
-         *   int16_t  predictor;
-         *   uint8_t  step_index;
-         *   uint8_t  reserved;
-         *   uint32_t frame_size;
-         *
-         * Some implementations have step_index as 16-bits, but others
-         * only use the lower 8 and store garbage in the upper 8.
-         */
-        c->status[0].predictor = sign_extend(bytestream2_get_le16u(&gb), 16);
-        c->status[0].step_index = bytestream2_get_byteu(&gb);
-        bytestream2_skipu(&gb, 5);
-        if (c->status[0].step_index > 88u) {
-            av_log(avctx, AV_LOG_ERROR, "ERROR: step_index = %i\n",
-                   c->status[0].step_index);
-            return AVERROR_INVALIDDATA;
-        }
-
-        for (int n = nb_samples >> 1; n > 0; n--) {
-            int v = bytestream2_get_byteu(&gb);
-
-            *samples++ = adpcm_ima_expand_nibble(&c->status[0], v >> 4, 3);
-            *samples++ = adpcm_ima_expand_nibble(&c->status[0], v & 0xf, 3);
-        }
-
-        if (nb_samples & 1) {
-            int v = bytestream2_get_byteu(&gb);
-            *samples++ = adpcm_ima_expand_nibble(&c->status[0], v >> 4, 3);
-
-            if (v & 0x0F) {
-                /* Holds true on all the http://samples.mplayerhq.hu/amv samples. */
-                av_log(avctx, AV_LOG_WARNING, "Last nibble set on packet with odd sample count.\n");
-                av_log(avctx, AV_LOG_WARNING, "Sample will be skipped.\n");
-            }
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_SMJPEG,
-        for (int i = 0; i < channels; i++) {
-            c->status[i].predictor = sign_extend(bytestream2_get_be16u(&gb), 16);
-            c->status[i].step_index = bytestream2_get_byteu(&gb);
-            bytestream2_skipu(&gb, 1);
-            if (c->status[i].step_index > 88u) {
-                av_log(avctx, AV_LOG_ERROR, "ERROR: step_index = %i\n",
-                       c->status[i].step_index);
-                return AVERROR_INVALIDDATA;
-            }
-        }
-
-        for (int n = nb_samples >> (1 - st); n > 0; n--) {
-            int v = bytestream2_get_byteu(&gb);
-
-            *samples++ = adpcm_ima_qt_expand_nibble(&c->status[0 ], v >> 4 );
-            *samples++ = adpcm_ima_qt_expand_nibble(&c->status[st], v & 0xf);
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_CT,
-        for (int n = nb_samples >> (1 - st); n > 0; n--) {
-            int v = bytestream2_get_byteu(&gb);
-            *samples++ = adpcm_ct_expand_nibble(&c->status[0 ], v >> 4  );
-            *samples++ = adpcm_ct_expand_nibble(&c->status[st], v & 0x0F);
-        }
-        ) /* End of CASE */
-#if CONFIG_ADPCM_SBPRO_2_DECODER || CONFIG_ADPCM_SBPRO_3_DECODER || \
-    CONFIG_ADPCM_SBPRO_4_DECODER
-    case AV_CODEC_ID_ADPCM_SBPRO_4:
-    case AV_CODEC_ID_ADPCM_SBPRO_3:
-    case AV_CODEC_ID_ADPCM_SBPRO_2:
-        if (!c->status[0].step_index) {
-            /* the first byte is a raw sample */
-            *samples++ = 128 * (bytestream2_get_byteu(&gb) - 0x80);
-            if (st)
-                *samples++ = 128 * (bytestream2_get_byteu(&gb) - 0x80);
-            c->status[0].step_index = 1;
-            nb_samples--;
-        }
-        if (avctx->codec->id == AV_CODEC_ID_ADPCM_SBPRO_4) {
-            for (int n = nb_samples >> (1 - st); n > 0; n--) {
-                int byte = bytestream2_get_byteu(&gb);
-                *samples++ = adpcm_sbpro_expand_nibble(&c->status[0],
-                                                       byte >> 4,   4, 0);
-                *samples++ = adpcm_sbpro_expand_nibble(&c->status[st],
-                                                       byte & 0x0F, 4, 0);
-            }
-        } else if (avctx->codec->id == AV_CODEC_ID_ADPCM_SBPRO_3) {
-            for (int n = (nb_samples<<st) / 3; n > 0; n--) {
-                int byte = bytestream2_get_byteu(&gb);
-                *samples++ = adpcm_sbpro_expand_nibble(&c->status[0],
-                                                        byte >> 5        , 3, 0);
-                *samples++ = adpcm_sbpro_expand_nibble(&c->status[0],
-                                                       (byte >> 2) & 0x07, 3, 0);
-                *samples++ = adpcm_sbpro_expand_nibble(&c->status[0],
-                                                        byte & 0x03,       2, 0);
-            }
-        } else {
-            for (int n = nb_samples >> (2 - st); n > 0; n--) {
-                int byte = bytestream2_get_byteu(&gb);
-                *samples++ = adpcm_sbpro_expand_nibble(&c->status[0],
-                                                        byte >> 6        , 2, 2);
-                *samples++ = adpcm_sbpro_expand_nibble(&c->status[st],
-                                                       (byte >> 4) & 0x03, 2, 2);
-                *samples++ = adpcm_sbpro_expand_nibble(&c->status[0],
-                                                       (byte >> 2) & 0x03, 2, 2);
-                *samples++ = adpcm_sbpro_expand_nibble(&c->status[st],
-                                                        byte & 0x03,       2, 2);
-            }
-        }
-        break;
-#endif /* CONFIG_ADPCM_SBPRO_x_DECODER */
-    CASE(ADPCM_SWF,
-        adpcm_swf_decode(avctx, buf, buf_size, samples);
-        bytestream2_seek(&gb, 0, SEEK_END);
-        ) /* End of CASE */
-    CASE(ADPCM_YAMAHA,
-        for (int n = nb_samples >> (1 - st); n > 0; n--) {
-            int v = bytestream2_get_byteu(&gb);
-            *samples++ = adpcm_yamaha_expand_nibble(&c->status[0 ], v & 0x0F);
-            *samples++ = adpcm_yamaha_expand_nibble(&c->status[st], v >> 4  );
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_AICA,
-        for (int channel = 0; channel < channels; channel++) {
-            samples = samples_p[channel];
-            for (int n = nb_samples >> 1; n > 0; n--) {
-                int v = bytestream2_get_byteu(&gb);
-                *samples++ = adpcm_yamaha_expand_nibble(&c->status[channel], v & 0x0F);
-                *samples++ = adpcm_yamaha_expand_nibble(&c->status[channel], v >> 4  );
-            }
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_AFC,
-        int samples_per_block;
-        int blocks;
-
-        if (avctx->extradata && avctx->extradata_size == 1 && avctx->extradata[0]) {
-            samples_per_block = avctx->extradata[0] / 16;
-            blocks = nb_samples / avctx->extradata[0];
-        } else {
-            samples_per_block = nb_samples / 16;
-            blocks = 1;
-        }
-
-        for (int m = 0; m < blocks; m++) {
-            for (int channel = 0; channel < channels; channel++) {
-                int prev1 = c->status[channel].sample1;
-                int prev2 = c->status[channel].sample2;
-
-                samples = samples_p[channel] + m * 16;
-                /* Read in every sample for this channel.  */
-                for (int i = 0; i < samples_per_block; i++) {
-                    int byte = bytestream2_get_byteu(&gb);
-                    int scale = 1 << (byte >> 4);
-                    int index = byte & 0xf;
-                    int factor1 = afc_coeffs[0][index];
-                    int factor2 = afc_coeffs[1][index];
-
-                    /* Decode 16 samples.  */
-                    for (int n = 0; n < 16; n++) {
-                        int32_t sampledat;
-
-                        if (n & 1) {
-                            sampledat = sign_extend(byte, 4);
-                        } else {
-                            byte = bytestream2_get_byteu(&gb);
-                            sampledat = sign_extend(byte >> 4, 4);
-                        }
-
-                        sampledat = ((prev1 * factor1 + prev2 * factor2) >> 11) +
-                                    sampledat * scale;
-                        *samples = av_clip_int16(sampledat);
-                        prev2 = prev1;
-                        prev1 = *samples++;
-                    }
-                }
-
-                c->status[channel].sample1 = prev1;
-                c->status[channel].sample2 = prev2;
-            }
-        }
-        bytestream2_seek(&gb, 0, SEEK_END);
-        ) /* End of CASE */
-#if CONFIG_ADPCM_THP_DECODER || CONFIG_ADPCM_THP_LE_DECODER
-    case AV_CODEC_ID_ADPCM_THP:
-    case AV_CODEC_ID_ADPCM_THP_LE:
-    {
-        int table[14][16];
-
-#define THP_GET16(g) \
-    sign_extend( \
-        avctx->codec->id == AV_CODEC_ID_ADPCM_THP_LE ? \
-        bytestream2_get_le16u(&(g)) : \
-        bytestream2_get_be16u(&(g)), 16)
-
-        if (avctx->extradata) {
-            GetByteContext tb;
-            if (avctx->extradata_size < 32 * channels) {
-                av_log(avctx, AV_LOG_ERROR, "Missing coeff table\n");
-                return AVERROR_INVALIDDATA;
-            }
-
-            bytestream2_init(&tb, avctx->extradata, avctx->extradata_size);
-            for (int i = 0; i < channels; i++)
-                for (int n = 0; n < 16; n++)
-                    table[i][n] = THP_GET16(tb);
-        } else {
-            for (int i = 0; i < channels; i++)
-                for (int n = 0; n < 16; n++)
-                    table[i][n] = THP_GET16(gb);
-
-            if (!c->has_status) {
-                /* Initialize the previous sample.  */
-                for (int i = 0; i < channels; i++) {
-                    c->status[i].sample1 = THP_GET16(gb);
-                    c->status[i].sample2 = THP_GET16(gb);
-                }
-                c->has_status = 1;
-            } else {
-                bytestream2_skip(&gb, channels * 4);
-            }
-        }
-
-        for (int ch = 0; ch < channels; ch++) {
-            samples = samples_p[ch];
-
-            /* Read in every sample for this channel.  */
-            for (int i = 0; i < (nb_samples + 13) / 14; i++) {
-                int byte = bytestream2_get_byteu(&gb);
-                int index = (byte >> 4) & 7;
-                unsigned int exp = byte & 0x0F;
-                int64_t factor1 = table[ch][index * 2];
-                int64_t factor2 = table[ch][index * 2 + 1];
-
-                /* Decode 14 samples.  */
-                for (int n = 0; n < 14 && (i * 14 + n < nb_samples); n++) {
-                    int32_t sampledat;
-
-                    if (n & 1) {
-                        sampledat = sign_extend(byte, 4);
-                    } else {
-                        byte = bytestream2_get_byteu(&gb);
-                        sampledat = sign_extend(byte >> 4, 4);
-                    }
-
-                    sampledat = ((c->status[ch].sample1 * factor1
-                                + c->status[ch].sample2 * factor2) >> 11) + sampledat * (1 << exp);
-                    *samples = av_clip_int16(sampledat);
-                    c->status[ch].sample2 = c->status[ch].sample1;
-                    c->status[ch].sample1 = *samples++;
-                }
-            }
-        }
-        break;
-    }
-#endif /* CONFIG_ADPCM_THP(_LE)_DECODER */
-    CASE(ADPCM_DTK,
-        for (int channel = 0; channel < channels; channel++) {
-            samples = samples_p[channel];
-
-            /* Read in every sample for this channel.  */
-            for (int i = 0; i < nb_samples / 28; i++) {
-                int byte, header;
-                if (channel)
-                    bytestream2_skipu(&gb, 1);
-                header = bytestream2_get_byteu(&gb);
-                bytestream2_skipu(&gb, 3 - channel);
-
-                /* Decode 28 samples.  */
-                for (int n = 0; n < 28; n++) {
-                    int32_t sampledat, prev;
-
-                    switch (header >> 4) {
-                    case 1:
-                        prev = (c->status[channel].sample1 * 0x3c);
-                        break;
-                    case 2:
-                        prev = (c->status[channel].sample1 * 0x73) - (c->status[channel].sample2 * 0x34);
-                        break;
-                    case 3:
-                        prev = (c->status[channel].sample1 * 0x62) - (c->status[channel].sample2 * 0x37);
-                        break;
-                    default:
-                        prev = 0;
-                    }
-
-                    prev = av_clip_intp2((prev + 0x20) >> 6, 21);
-
-                    byte = bytestream2_get_byteu(&gb);
-                    if (!channel)
-                        sampledat = sign_extend(byte, 4);
-                    else
-                        sampledat = sign_extend(byte >> 4, 4);
-
-                    sampledat = ((sampledat * (1 << 12)) >> (header & 0xf)) * (1 << 6) + prev;
-                    *samples++ = av_clip_int16(sampledat >> 6);
-                    c->status[channel].sample2 = c->status[channel].sample1;
-                    c->status[channel].sample1 = sampledat;
-                }
-            }
-            if (!channel)
-                bytestream2_seek(&gb, 0, SEEK_SET);
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_PSX,
-        for (int block = 0; block < avpkt->size / FFMAX(avctx->block_align, 16 * channels); block++) {
-            int nb_samples_per_block = 28 * FFMAX(avctx->block_align, 16 * channels) / (16 * channels);
-            for (int channel = 0; channel < channels; channel++) {
-                samples = samples_p[channel] + block * nb_samples_per_block;
-                av_assert0((block + 1) * nb_samples_per_block <= nb_samples);
-
-                /* Read in every sample for this channel.  */
-                for (int i = 0; i < nb_samples_per_block / 28; i++) {
-                    int filter, shift, flag, byte;
-
-                    filter = bytestream2_get_byteu(&gb);
-                    shift  = filter & 0xf;
-                    filter = filter >> 4;
-                    if (filter >= FF_ARRAY_ELEMS(xa_adpcm_table))
-                        return AVERROR_INVALIDDATA;
-                    flag   = bytestream2_get_byteu(&gb) & 0x7;
-
-                    /* Decode 28 samples.  */
-                    for (int n = 0; n < 28; n++) {
-                        int sample = 0, scale;
-
-                        if (n & 1) {
-                            scale = sign_extend(byte >> 4, 4);
-                        } else {
-                            byte  = bytestream2_get_byteu(&gb);
-                            scale = sign_extend(byte, 4);
-                        }
-
-                        if (flag < 0x07) {
-                            scale  = scale * (1 << 12);
-                            sample = (int)((scale >> shift) + (c->status[channel].sample1 * xa_adpcm_table[filter][0] + c->status[channel].sample2 * xa_adpcm_table[filter][1]) / 64);
-                        }
-                        *samples++ = av_clip_int16(sample);
-                        c->status[channel].sample2 = c->status[channel].sample1;
-                        c->status[channel].sample1 = sample;
-                    }
-                }
-            }
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_ARGO,
-        /*
-         * The format of each block:
-         *   uint8_t left_control;
-         *   uint4_t left_samples[nb_samples];
-         *   ---- and if stereo ----
-         *   uint8_t right_control;
-         *   uint4_t right_samples[nb_samples];
-         *
-         * Format of the control byte:
-         * MSB [SSSSRDRR] LSB
-         *   S = (Shift Amount - 2)
-         *   D = Decoder flag.
-         *   R = Reserved
-         *
-         * Each block relies on the previous two samples of each channel.
-         * They should be 0 initially.
-         */
-        for (int block = 0; block < avpkt->size / avctx->block_align; block++) {
-            for (int channel = 0; channel < avctx->ch_layout.nb_channels; channel++) {
-                ADPCMChannelStatus *cs = c->status + channel;
-                int control, shift;
-
-                samples = samples_p[channel] + block * 32;
-
-                /* Get the control byte and decode the samples, 2 at a time. */
-                control = bytestream2_get_byteu(&gb);
-                shift = (control >> 4) + 2;
-
-                for (int n = 0; n < 16; n++) {
-                    int sample = bytestream2_get_byteu(&gb);
-                    *samples++ = ff_adpcm_argo_expand_nibble(cs, sample >> 4, shift, control & 0x04);
-                    *samples++ = ff_adpcm_argo_expand_nibble(cs, sample >> 0, shift, control & 0x04);
-                }
-            }
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_ZORK,
-        for (int n = 0; n < nb_samples * channels; n++) {
-            int v = bytestream2_get_byteu(&gb);
-            *samples++ = adpcm_zork_expand_nibble(&c->status[n % channels], v);
-        }
-        ) /* End of CASE */
-    CASE(ADPCM_IMA_MTF,
-        for (int n = nb_samples / 2; n > 0; n--) {
-            for (int channel = 0; channel < channels; channel++) {
-                int v = bytestream2_get_byteu(&gb);
-                *samples++  = adpcm_ima_mtf_expand_nibble(&c->status[channel], v >> 4);
-                samples[st] = adpcm_ima_mtf_expand_nibble(&c->status[channel], v & 0x0F);
-            }
-            samples += channels;
-        }
-        ) /* End of CASE */
-    default:
-        av_assert0(0); // unsupported codec_id should not happen
-    }
-
-    if (avpkt->size && bytestream2_tell(&gb) == 0) {
-        av_log(avctx, AV_LOG_ERROR, "Nothing consumed\n");
-        return AVERROR_INVALIDDATA;
-    }
-
-    *got_frame_ptr = 1;
-
-    if (avpkt->size < bytestream2_tell(&gb)) {
-        av_log(avctx, AV_LOG_ERROR, "Overread of %d < %d\n", avpkt->size, bytestream2_tell(&gb));
-        return avpkt->size;
-    }
-
-    return bytestream2_tell(&gb);
-}
-
-static void adpcm_flush(AVCodecContext *avctx)
-{
-    ADPCMDecodeContext *c = avctx->priv_data;
-
-    /* Just nuke the entire state and re-init. */
-    memset(c, 0, sizeof(ADPCMDecodeContext));
-
-    switch(avctx->codec_id) {
-    case AV_CODEC_ID_ADPCM_CT:
-        c->status[0].step = c->status[1].step = 511;
-        break;
-
-    case AV_CODEC_ID_ADPCM_IMA_APC:
-        if (avctx->extradata && avctx->extradata_size >= 8) {
-            c->status[0].predictor = av_clip_intp2(AV_RL32(avctx->extradata    ), 18);
-            c->status[1].predictor = av_clip_intp2(AV_RL32(avctx->extradata + 4), 18);
-        }
-        break;
-
-    case AV_CODEC_ID_ADPCM_IMA_APM:
-        if (avctx->extradata && avctx->extradata_size >= 28) {
-            c->status[0].predictor  = av_clip_intp2(AV_RL32(avctx->extradata + 16), 18);
-            c->status[0].step_index = av_clip(AV_RL32(avctx->extradata + 20), 0, 88);
-            c->status[1].predictor  = av_clip_intp2(AV_RL32(avctx->extradata + 4), 18);
-            c->status[1].step_index = av_clip(AV_RL32(avctx->extradata + 8), 0, 88);
-        }
-        break;
-
-    case AV_CODEC_ID_ADPCM_IMA_WS:
-        if (avctx->extradata && avctx->extradata_size >= 2)
-            c->vqa_version = AV_RL16(avctx->extradata);
-        break;
-    default:
-        /* Other codecs may want to handle this during decoding. */
-        c->has_status = 0;
-        return;
-    }
-
-    c->has_status = 1;
-}
-
-
-static const enum AVSampleFormat sample_fmts_s16[]  = { AV_SAMPLE_FMT_S16,
-                                                        AV_SAMPLE_FMT_NONE };
-static const enum AVSampleFormat sample_fmts_s16p[] = { AV_SAMPLE_FMT_S16P,
-                                                        AV_SAMPLE_FMT_NONE };
-static const enum AVSampleFormat sample_fmts_both[] = { AV_SAMPLE_FMT_S16,
-                                                        AV_SAMPLE_FMT_S16P,
-                                                        AV_SAMPLE_FMT_NONE };
-
-#define ADPCM_DECODER_0(id_, sample_fmts_, name_, long_name_)
-#define ADPCM_DECODER_1(id_, sample_fmts_, name_, long_name_) \
-const FFCodec ff_ ## name_ ## _decoder = {                  \
-    .p.name         = #name_,                               \
-    CODEC_LONG_NAME(long_name_),                            \
-    .p.type         = AVMEDIA_TYPE_AUDIO,                   \
-    .p.id           = id_,                                  \
-    .p.capabilities = AV_CODEC_CAP_DR1,                     \
-    .p.sample_fmts  = sample_fmts_,                         \
-    .priv_data_size = sizeof(ADPCMDecodeContext),           \
-    .init           = adpcm_decode_init,                    \
-    FF_CODEC_DECODE_CB(adpcm_decode_frame),                 \
-    .flush          = adpcm_flush,                          \
-};
-#define ADPCM_DECODER_2(enabled, codec_id, name, sample_fmts, long_name) \
-    ADPCM_DECODER_ ## enabled(codec_id, name, sample_fmts, long_name)
-#define ADPCM_DECODER_3(config, codec_id, name, sample_fmts, long_name) \
-    ADPCM_DECODER_2(config, codec_id, name, sample_fmts, long_name)
-#define ADPCM_DECODER(codec, name, sample_fmts, long_name) \
-    ADPCM_DECODER_3(CONFIG_ ## codec ## _DECODER, AV_CODEC_ID_ ## codec, \
-                    name, sample_fmts, long_name)
-
-/* Note: Do not forget to add new entries to the Makefile as well. */
-ADPCM_DECODER(ADPCM_4XM,         sample_fmts_s16p, adpcm_4xm,         "ADPCM 4X Movie")
-ADPCM_DECODER(ADPCM_AFC,         sample_fmts_s16p, adpcm_afc,         "ADPCM Nintendo Gamecube AFC")
-ADPCM_DECODER(ADPCM_AGM,         sample_fmts_s16,  adpcm_agm,         "ADPCM AmuseGraphics Movie")
-ADPCM_DECODER(ADPCM_AICA,        sample_fmts_s16p, adpcm_aica,        "ADPCM Yamaha AICA")
-ADPCM_DECODER(ADPCM_ARGO,        sample_fmts_s16p, adpcm_argo,        "ADPCM Argonaut Games")
-ADPCM_DECODER(ADPCM_CT,          sample_fmts_s16,  adpcm_ct,          "ADPCM Creative Technology")
-ADPCM_DECODER(ADPCM_DTK,         sample_fmts_s16p, adpcm_dtk,         "ADPCM Nintendo Gamecube DTK")
-ADPCM_DECODER(ADPCM_EA,          sample_fmts_s16,  adpcm_ea,          "ADPCM Electronic Arts")
-ADPCM_DECODER(ADPCM_EA_MAXIS_XA, sample_fmts_s16,  adpcm_ea_maxis_xa, "ADPCM Electronic Arts Maxis CDROM XA")
-ADPCM_DECODER(ADPCM_EA_R1,       sample_fmts_s16p, adpcm_ea_r1,       "ADPCM Electronic Arts R1")
-ADPCM_DECODER(ADPCM_EA_R2,       sample_fmts_s16p, adpcm_ea_r2,       "ADPCM Electronic Arts R2")
-ADPCM_DECODER(ADPCM_EA_R3,       sample_fmts_s16p, adpcm_ea_r3,       "ADPCM Electronic Arts R3")
-ADPCM_DECODER(ADPCM_EA_XAS,      sample_fmts_s16p, adpcm_ea_xas,      "ADPCM Electronic Arts XAS")
-ADPCM_DECODER(ADPCM_IMA_ACORN,   sample_fmts_s16,  adpcm_ima_acorn,   "ADPCM IMA Acorn Replay")
-ADPCM_DECODER(ADPCM_IMA_AMV,     sample_fmts_s16,  adpcm_ima_amv,     "ADPCM IMA AMV")
-ADPCM_DECODER(ADPCM_IMA_APC,     sample_fmts_s16,  adpcm_ima_apc,     "ADPCM IMA CRYO APC")
-ADPCM_DECODER(ADPCM_IMA_APM,     sample_fmts_s16,  adpcm_ima_apm,     "ADPCM IMA Ubisoft APM")
-ADPCM_DECODER(ADPCM_IMA_CUNNING, sample_fmts_s16p, adpcm_ima_cunning, "ADPCM IMA Cunning Developments")
-ADPCM_DECODER(ADPCM_IMA_DAT4,    sample_fmts_s16,  adpcm_ima_dat4,    "ADPCM IMA Eurocom DAT4")
-ADPCM_DECODER(ADPCM_IMA_DK3,     sample_fmts_s16,  adpcm_ima_dk3,     "ADPCM IMA Duck DK3")
-ADPCM_DECODER(ADPCM_IMA_DK4,     sample_fmts_s16,  adpcm_ima_dk4,     "ADPCM IMA Duck DK4")
-ADPCM_DECODER(ADPCM_IMA_EA_EACS, sample_fmts_s16,  adpcm_ima_ea_eacs, "ADPCM IMA Electronic Arts EACS")
-ADPCM_DECODER(ADPCM_IMA_EA_SEAD, sample_fmts_s16,  adpcm_ima_ea_sead, "ADPCM IMA Electronic Arts SEAD")
-ADPCM_DECODER(ADPCM_IMA_ISS,     sample_fmts_s16,  adpcm_ima_iss,     "ADPCM IMA Funcom ISS")
-ADPCM_DECODER(ADPCM_IMA_MOFLEX,  sample_fmts_s16p, adpcm_ima_moflex,  "ADPCM IMA MobiClip MOFLEX")
-ADPCM_DECODER(ADPCM_IMA_MTF,     sample_fmts_s16,  adpcm_ima_mtf,     "ADPCM IMA Capcom's MT Framework")
-ADPCM_DECODER(ADPCM_IMA_OKI,     sample_fmts_s16,  adpcm_ima_oki,     "ADPCM IMA Dialogic OKI")
-ADPCM_DECODER(ADPCM_IMA_QT,      sample_fmts_s16p, adpcm_ima_qt,      "ADPCM IMA QuickTime")
-ADPCM_DECODER(ADPCM_IMA_RAD,     sample_fmts_s16,  adpcm_ima_rad,     "ADPCM IMA Radical")
-ADPCM_DECODER(ADPCM_IMA_SSI,     sample_fmts_s16,  adpcm_ima_ssi,     "ADPCM IMA Simon & Schuster Interactive")
-ADPCM_DECODER(ADPCM_IMA_SMJPEG,  sample_fmts_s16,  adpcm_ima_smjpeg,  "ADPCM IMA Loki SDL MJPEG")
-ADPCM_DECODER(ADPCM_IMA_ALP,     sample_fmts_s16,  adpcm_ima_alp,     "ADPCM IMA High Voltage Software ALP")
-ADPCM_DECODER(ADPCM_IMA_WAV,     sample_fmts_s16p, adpcm_ima_wav,     "ADPCM IMA WAV")
-ADPCM_DECODER(ADPCM_IMA_WS,      sample_fmts_both, adpcm_ima_ws,      "ADPCM IMA Westwood")
-ADPCM_DECODER(ADPCM_MS,          sample_fmts_both, adpcm_ms,          "ADPCM Microsoft")
-ADPCM_DECODER(ADPCM_MTAF,        sample_fmts_s16p, adpcm_mtaf,        "ADPCM MTAF")
-ADPCM_DECODER(ADPCM_PSX,         sample_fmts_s16p, adpcm_psx,         "ADPCM Playstation")
-ADPCM_DECODER(ADPCM_SBPRO_2,     sample_fmts_s16,  adpcm_sbpro_2,     "ADPCM Sound Blaster Pro 2-bit")
-ADPCM_DECODER(ADPCM_SBPRO_3,     sample_fmts_s16,  adpcm_sbpro_3,     "ADPCM Sound Blaster Pro 2.6-bit")
-ADPCM_DECODER(ADPCM_SBPRO_4,     sample_fmts_s16,  adpcm_sbpro_4,     "ADPCM Sound Blaster Pro 4-bit")
-ADPCM_DECODER(ADPCM_SWF,         sample_fmts_s16,  adpcm_swf,         "ADPCM Shockwave Flash")
-ADPCM_DECODER(ADPCM_THP_LE,      sample_fmts_s16p, adpcm_thp_le,      "ADPCM Nintendo THP (little-endian)")
-ADPCM_DECODER(ADPCM_THP,         sample_fmts_s16p, adpcm_thp,         "ADPCM Nintendo THP")
-ADPCM_DECODER(ADPCM_XA,          sample_fmts_s16p, adpcm_xa,          "ADPCM CDROM XA")
-ADPCM_DECODER(ADPCM_XMD,         sample_fmts_s16p, adpcm_xmd,         "ADPCM Konami XMD")
-ADPCM_DECODER(ADPCM_YAMAHA,      sample_fmts_s16,  adpcm_yamaha,      "ADPCM Yamaha")
-ADPCM_DECODER(ADPCM_ZORK,        sample_fmts_s16,  adpcm_zork,        "ADPCM Zork")
diff --git a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/bitstream.h b/spaces/colakin/video-generater/public/ffmpeg/libavcodec/bitstream.h
deleted file mode 100644
index b60f0c296d14fb1c01dc4a6042d5190e6270d94b..0000000000000000000000000000000000000000
--- a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/bitstream.h
+++ /dev/null
@@ -1,196 +0,0 @@
-/*
- * Copyright (c) 2016 Alexandra Hájková
- *
- * This file is part of FFmpeg.
- *
- * FFmpeg is free software; you can redistribute it and/or
- * modify it under the terms of the GNU Lesser General Public
- * License as published by the Free Software Foundation; either
- * version 2.1 of the License, or (at your option) any later version.
- *
- * FFmpeg is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
- * Lesser General Public License for more details.
- *
- * You should have received a copy of the GNU Lesser General Public
- * License along with FFmpeg; if not, write to the Free Software
- * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
- */
-
-/**
- * @file
- * bitstream reader API header.
- */
-
-/*
- * Bit order (endianness) is controlled by #defining BITSTREAM_BE and/or
- * BITSTREAM_LE before #including this header. The corresponding bitreading
- * functions are provided as bits_*_be()/bits_*_le() respectively.
- *
- * If neither or only BITSTREAM_BE is defined, then the default (unsuffixed)
- * bits_*() will resolve to the big-endian implementation. If only BITSTREAM_LE
- * is defined, little-endian will be the default.
- *
- * If both are defined, then the default can be controlled by defining at most
- * one of BITSTREAM_DEFAULT_LE/BE. When BITSTREAM_DEFAULT_* is not defined, no
- * default is provided and you must always explicitly use the _be() or _le()
- * variants.
- */
-
-#ifndef AVCODEC_BITSTREAM_H
-#define AVCODEC_BITSTREAM_H
-
-#include <stdint.h>
-
-#include "config.h"
-
-#include "libavutil/avassert.h"
-#include "libavutil/common.h"
-#include "libavutil/intreadwrite.h"
-#include "libavutil/log.h"
-
-#include "mathops.h"
-#include "vlc.h"
-
-#ifndef UNCHECKED_BITSTREAM_READER
-#define UNCHECKED_BITSTREAM_READER !CONFIG_SAFE_BITSTREAM_READER
-#endif
-
-// select the default endianness, if any
-#if defined(BITSTREAM_LE) && defined(BITSTREAM_BE)
-
-# if defined(BITSTREAM_DEFAULT_BE) && defined(BITSTREAM_DEFAULT_LE)
-#  error "At most one of BITSTREAM_DEFAULT_BE/LE must be defined"
-# elif   defined(BITSTREAM_DEFAULT_BE)
-#  define BITS_DEFAULT_BE
-# elif   defined(BITSTREAM_DEFAULT_LE)
-#  define BITS_DEFAULT_LE
-# endif
-
-#elif defined(BITSTREAM_LE)
-# define BITS_DEFAULT_LE
-#else // select BE if nothing is requested explicitly
-# define BITS_DEFAULT_BE
-# define BITSTREAM_WANT_BE
-#endif
-
-#if defined(BITS_DEFAULT_LE)
-
-# define BitstreamContext   BitstreamContextLE
-# define bits_init          bits_init_le
-# define bits_init8         bits_init8_le
-# define bits_tell          bits_tell_le
-# define bits_size          bits_size_le
-# define bits_left          bits_left_le
-# define bits_read_bit      bits_read_bit_le
-# define bits_read_nz       bits_read_nz_le
-# define bits_read          bits_read_le
-# define bits_read_63       bits_read_63_le
-# define bits_read_64       bits_read_64_le
-# define bits_read_signed   bits_read_signed_le
-# define bits_read_signed_nz bits_read_signed_nz_le
-# define bits_peek_nz       bits_peek_nz_le
-# define bits_peek          bits_peek_le
-# define bits_peek_signed   bits_peek_signed_le
-# define bits_peek_signed_nz bits_peek_signed_nz_le
-# define bits_skip          bits_skip_le
-# define bits_seek          bits_seek_le
-# define bits_align         bits_align_le
-# define bits_read_xbits    bits_read_xbits_le
-# define bits_decode012     bits_decode012_le
-# define bits_decode210     bits_decode210_le
-# define bits_apply_sign    bits_apply_sign_le
-# define bits_read_vlc      bits_read_vlc_le
-
-#elif defined(BITS_DEFAULT_BE)
-
-# define BitstreamContext   BitstreamContextBE
-# define bits_init          bits_init_be
-# define bits_init8         bits_init8_be
-# define bits_tell          bits_tell_be
-# define bits_size          bits_size_be
-# define bits_left          bits_left_be
-# define bits_read_bit      bits_read_bit_be
-# define bits_read_nz       bits_read_nz_be
-# define bits_read          bits_read_be
-# define bits_read_63       bits_read_63_be
-# define bits_read_64       bits_read_64_be
-# define bits_read_signed   bits_read_signed_be
-# define bits_read_signed_nz bits_read_signed_nz_be
-# define bits_peek_nz       bits_peek_nz_be
-# define bits_peek          bits_peek_be
-# define bits_peek_signed   bits_peek_signed_be
-# define bits_peek_signed_nz bits_peek_signed_nz_be
-# define bits_skip          bits_skip_be
-# define bits_seek          bits_seek_be
-# define bits_align         bits_align_be
-# define bits_read_xbits    bits_read_xbits_be
-# define bits_decode012     bits_decode012_be
-# define bits_decode210     bits_decode210_be
-# define bits_apply_sign    bits_apply_sign_be
-# define bits_read_vlc      bits_read_vlc_be
-
-#endif
-
-#undef BITS_DEFAULT_LE
-#undef BITS_DEFAULT_BE
-
-#define BITS_RL_VLC(level, run, bc, table, bits, max_depth) \
-    do {                                                    \
-        int n, nb_bits;                                     \
-        unsigned int index = bits_peek(bc, bits);           \
-        level = table[index].level;                         \
-        n     = table[index].len;                           \
-                                                            \
-        if (max_depth > 1 && n < 0) {                       \
-            bits_skip(bc, bits);                            \
-                                                            \
-            nb_bits = -n;                                   \
-                                                            \
-            index = bits_peek(bc, nb_bits) + level;         \
-            level = table[index].level;                     \
-            n     = table[index].len;                       \
-            if (max_depth > 2 && n < 0) {                   \
-                bits_skip(bc, nb_bits);                     \
-                nb_bits = -n;                               \
-                                                            \
-                index = bits_peek(bc, nb_bits) + level;     \
-                level = table[index].level;                 \
-                n     = table[index].len;                   \
-            }                                               \
-        }                                                   \
-        run = table[index].run;                             \
-        bits_skip(bc, n);                                   \
-    } while (0)
-
-#endif /* AVCODEC_BITSTREAM_H */
-
-// the following is deliberately outside of the standard #include guards
-
-#if  defined(BITSTREAM_LE) && !defined(BITSTREAM_WANT_LE)
-# define BITSTREAM_WANT_LE
-#endif
-
-#if defined(BITSTREAM_BE) && !defined(BITSTREAM_WANT_BE)
-# define BITSTREAM_WANT_BE
-#endif
-
-#if defined(BITSTREAM_WANT_LE) && !defined(AVCODEC_BITSTREAM_LE)
-#define AVCODEC_BITSTREAM_LE
-
-#define BITSTREAM_TEMPLATE_LE
-#include "bitstream_template.h"
-#undef BITSTREAM_TEMPLATE_LE
-
-#endif
-
-#if defined(BITSTREAM_WANT_BE) && !defined(AVCODEC_BITSTREAM_BE)
-#define AVCODEC_BITSTREAM_BE
-
-#include "bitstream_template.h"
-
-#endif
-
-#undef BITSTREAM_WANT_LE
-#undef BITSTREAM_WANT_BE
diff --git a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/dcaenc.h b/spaces/colakin/video-generater/public/ffmpeg/libavcodec/dcaenc.h
deleted file mode 100644
index 63fdaf074eb93763349ee145a28d46112e5333c3..0000000000000000000000000000000000000000
--- a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/dcaenc.h
+++ /dev/null
@@ -1,158 +0,0 @@
-/*
- * DCA encoder tables
- * Copyright (C) 2008-2012 Alexander E. Patrakov
- *
- * This file is part of FFmpeg.
- *
- * FFmpeg is free software; you can redistribute it and/or
- * modify it under the terms of the GNU Lesser General Public
- * License as published by the Free Software Foundation; either
- * version 2.1 of the License, or (at your option) any later version.
- *
- * FFmpeg is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
- * Lesser General Public License for more details.
- *
- * You should have received a copy of the GNU Lesser General Public
- * License along with FFmpeg; if not, write to the Free Software
- * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
- */
-
-#ifndef AVCODEC_DCAENC_H
-#define AVCODEC_DCAENC_H
-
-#include <stdint.h>
-
-#include "dcamath.h"
-
-typedef struct {
-    int32_t m;
-    int32_t e;
-} softfloat;
-
-static const int sample_rates[] = {
-    8000, 16000, 32000, 11025, 22050, 44100, 12000, 24000, 48000, 0,
-};
-
-static const uint8_t bitstream_sfreq[] = { 1, 2, 3, 6, 7, 8, 11, 12, 13 };
-
-/* Auditory filter center frequencies and bandwidths, in Hz.
- * The last two are made up, because there is no scientific data.
- */
-static const uint16_t fc[] = {
-    50, 150, 250, 350, 450, 570, 700, 840, 1000, 1170, 1370, 1600, 1850, 2150,
-    2500, 2900, 3400, 4000, 4800, 5800, 7000, 8500, 10500, 13500, 17000
-};
-
-static const uint16_t erb[] = {
-    80, 100, 100, 100, 110, 120, 140, 150, 160, 190, 210, 240, 280,
-    320, 380, 450, 550, 700, 900, 1100, 1300, 1800, 2500, 3500, 4500
-};
-
-static const softfloat stepsize_inv[27] = {
-    {0, 0}, {1342177360, 21}, {2147483647, 21}, {1342177360, 20},
-    {1819901661, 20}, {2147483647, 20}, {1278263843, 19}, {1579032492, 19},
-    {1412817763, 18}, {1220162327, 17}, {1118482133, 16}, {1917391412, 16},
-    {1766017772, 15}, {1525212826, 14}, {1290553940, 13}, {2097179000, 13},
-    {1677683200, 12}, {1497972244, 11}, {1310893147, 10}, {1165354136, 9},
-    {1748031204, 9}, {1542092044, 8}, {1636178017, 7}, {1636178017, 6},
-    {1636178017, 5}, {1636178017, 4}, {1636178017, 3},
-};
-
-static const softfloat scalefactor_inv[128] = {
-    {2147483647, 1}, {2147483647, 1}, {2147483647, 2}, {2147483647, 2},
-    {2147483647, 2}, {2147483647, 2}, {1431655765, 2}, {1431655765, 2},
-    {1431655765, 2}, {2147483647, 3}, {2147483647, 3}, {1717986918, 3},
-    {1431655765, 3}, {1227133513, 3}, {1227133513, 3}, {2147483647, 4},
-    {1717986918, 4}, {1561806289, 4}, {1431655765, 4}, {1227133513, 4},
-    {2147483647, 5}, {1908874353, 5}, {1717986918, 5}, {1493901668, 5},
-    {1321528398, 5}, {1145324612, 5}, {2021161080, 6}, {1808407282, 6},
-    {1561806289, 6}, {1374389534, 6}, {1227133513, 6}, {2147483647, 7},
-    {1908874353, 7}, {1676084798, 7}, {1477838209, 7}, {1296593900, 7},
-    {1145324612, 7}, {2021161080, 8}, {1773405851, 8}, {1561806289, 8},
-    {1374389534, 8}, {1216273924, 8}, {2139127680, 9}, {1882725390, 9},
-    {1660893697, 9}, {1462116526, 9}, {1287484341, 9}, {1135859119, 9},
-    {1999112050, 10}, {1762037865, 10}, {1552982525, 10}, {1367551775, 10},
-    {1205604855, 10}, {2124660150, 11}, {1871509153, 11}, {1648443220, 11},
-    {1452459217, 11}, {1279990253, 11}, {1127704233, 11}, {1987368509, 12},
-    {1750814693, 12}, {1542632939, 12}, {1359099663, 12}, {1197398995, 12},
-    {2109880792, 13}, {1858853132, 13}, {1638006149, 13}, {1443165385, 13},
-    {1271479187, 13}, {1120235993, 13}, {1973767086, 14}, {1739045674, 14},
-    {1532153461, 14}, {1349922194, 14}, {1189384493, 14}, {2095804865, 15},
-    {1846464029, 15}, {1626872524, 15}, {1433347133, 15}, {1262853884, 15},
-    {1112619678, 15}, {1960569045, 16}, {1727349015, 16}, {1521881227, 16},
-    {1340842289, 16}, {1181357555, 16}, {2081669156, 17}, {1834047752, 17},
-    {1615889229, 17}, {1423675973, 17}, {1254322457, 17}, {1105123583, 17},
-    {1947330755, 18}, {1715693602, 18}, {1511607799, 18}, {1331801790, 18},
-    {1173384427, 18}, {2067616532, 19}, {1821667648, 19}, {1604980024, 19},
-    {1414066955, 19}, {1245861410, 19}, {1097665748, 19}, {1934193616, 20},
-    {1704119624, 20}, {1501412075, 20}, {1322817107, 20}, {1165466323, 20},
-    {2053666205, 21}, {1809379407, 21}, {1594151671, 21}, {1404526328, 21},
-    {1237455941, 21}, {1090259329, 21}, {1921143210, 22}, {1692621231, 22},
-    {1491281857, 22}, {1313892269, 22}, {1157603482, 22}, {2039810470, 23},
-    {1797172644, 23}, {1583396912, 23}, {1395050052, 23}, {1229107276, 23},
-    {1082903494, 23}, {1082903494, 23}, {1082903494, 23}, {1082903494, 23},
-};
-
-/* manually derived from
- * Table B.5: Selection of quantization levels and codebooks
- */
-static const int bit_consumption[27] = {
-    -8, 28, 40, 48, 52, 60, 68, 76, 80, 96,
-    112, 128, 144, 160, 176, 192, 208, 224, 240, 256,
-    272, 288, 304, 320, 336, 352, 368,
-};
-
-static const int8_t lfe_index[16] = {
-    1, 2, 2, 2, 2, 3, 2, 3, 2, 3, 2, 3, 1, 3, 2, 3
-};
-
-static const int8_t channel_reorder_lfe[16][9] = {
-    { 0, -1, -1, -1, -1, -1, -1, -1, -1 },
-    { 0,  1, -1, -1, -1, -1, -1, -1, -1 },
-    { 0,  1, -1, -1, -1, -1, -1, -1, -1 },
-    { 0,  1, -1, -1, -1, -1, -1, -1, -1 },
-    { 0,  1, -1, -1, -1, -1, -1, -1, -1 },
-    { 2,  0,  1, -1, -1, -1, -1, -1, -1 },
-    { 0,  1,  3, -1, -1, -1, -1, -1, -1 },
-    { 2,  0,  1,  4, -1, -1, -1, -1, -1 },
-    { 0,  1,  3,  4, -1, -1, -1, -1, -1 },
-    { 2,  0,  1,  4,  5, -1, -1, -1, -1 },
-    { 3,  4,  0,  1,  5,  6, -1, -1, -1 },
-    { 2,  0,  1,  4,  5,  6, -1, -1, -1 },
-    { 0,  6,  4,  5,  2,  3, -1, -1, -1 },
-    { 4,  2,  5,  0,  1,  6,  7, -1, -1 },
-    { 5,  6,  0,  1,  7,  3,  8,  4, -1 },
-    { 4,  2,  5,  0,  1,  6,  8,  7, -1 },
-};
-
-static const int8_t channel_reorder_nolfe[16][9] = {
-    { 0, -1, -1, -1, -1, -1, -1, -1, -1 },
-    { 0,  1, -1, -1, -1, -1, -1, -1, -1 },
-    { 0,  1, -1, -1, -1, -1, -1, -1, -1 },
-    { 0,  1, -1, -1, -1, -1, -1, -1, -1 },
-    { 0,  1, -1, -1, -1, -1, -1, -1, -1 },
-    { 2,  0,  1, -1, -1, -1, -1, -1, -1 },
-    { 0,  1,  2, -1, -1, -1, -1, -1, -1 },
-    { 2,  0,  1,  3, -1, -1, -1, -1, -1 },
-    { 0,  1,  2,  3, -1, -1, -1, -1, -1 },
-    { 2,  0,  1,  3,  4, -1, -1, -1, -1 },
-    { 2,  3,  0,  1,  4,  5, -1, -1, -1 },
-    { 2,  0,  1,  3,  4,  5, -1, -1, -1 },
-    { 0,  5,  3,  4,  1,  2, -1, -1, -1 },
-    { 3,  2,  4,  0,  1,  5,  6, -1, -1 },
-    { 4,  5,  0,  1,  6,  2,  7,  3, -1 },
-    { 3,  2,  4,  0,  1,  5,  7,  6, -1 },
-};
-
-static inline int32_t quantize_value(int32_t value, softfloat quant)
-{
-    int32_t offset = 1 << (quant.e - 1);
-
-    value = mul32(value, quant.m) + offset;
-    value = value >> quant.e;
-    return value;
-}
-
-#endif /* AVCODEC_DCAENC_H */
diff --git a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/h263dec.c b/spaces/colakin/video-generater/public/ffmpeg/libavcodec/h263dec.c
deleted file mode 100644
index f4e7048a5f2dda7b13d57e88b97948692d9ccda3..0000000000000000000000000000000000000000
--- a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/h263dec.c
+++ /dev/null
@@ -1,740 +0,0 @@
-/*
- * H.263 decoder
- * Copyright (c) 2001 Fabrice Bellard
- * Copyright (c) 2002-2004 Michael Niedermayer <michaelni@gmx.at>
- *
- * This file is part of FFmpeg.
- *
- * FFmpeg is free software; you can redistribute it and/or
- * modify it under the terms of the GNU Lesser General Public
- * License as published by the Free Software Foundation; either
- * version 2.1 of the License, or (at your option) any later version.
- *
- * FFmpeg is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
- * Lesser General Public License for more details.
- *
- * You should have received a copy of the GNU Lesser General Public
- * License along with FFmpeg; if not, write to the Free Software
- * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
- */
-
-/**
- * @file
- * H.263 decoder.
- */
-
-#define UNCHECKED_BITSTREAM_READER 1
-
-#include "config_components.h"
-
-#include "avcodec.h"
-#include "codec_internal.h"
-#include "decode.h"
-#include "error_resilience.h"
-#include "flvdec.h"
-#include "h263.h"
-#include "h263dec.h"
-#include "hwconfig.h"
-#include "mpeg_er.h"
-#include "mpeg4video.h"
-#include "mpeg4videodec.h"
-#include "mpeg4videodefs.h"
-#include "mpegutils.h"
-#include "mpegvideo.h"
-#include "mpegvideodec.h"
-#include "msmpeg4dec.h"
-#include "thread.h"
-#include "wmv2dec.h"
-
-static enum AVPixelFormat h263_get_format(AVCodecContext *avctx)
-{
-    /* MPEG-4 Studio Profile only, not supported by hardware */
-    if (avctx->bits_per_raw_sample > 8) {
-        av_assert1(((MpegEncContext *)avctx->priv_data)->studio_profile);
-        return avctx->pix_fmt;
-    }
-
-    if (CONFIG_GRAY && (avctx->flags & AV_CODEC_FLAG_GRAY)) {
-        if (avctx->color_range == AVCOL_RANGE_UNSPECIFIED)
-            avctx->color_range = AVCOL_RANGE_MPEG;
-        return AV_PIX_FMT_GRAY8;
-    }
-
-    return avctx->pix_fmt = ff_get_format(avctx, avctx->codec->pix_fmts);
-}
-
-av_cold int ff_h263_decode_init(AVCodecContext *avctx)
-{
-    MpegEncContext *s = avctx->priv_data;
-    int ret;
-
-    s->out_format      = FMT_H263;
-
-    // set defaults
-    ff_mpv_decode_init(s, avctx);
-
-    s->quant_precision = 5;
-    s->decode_mb       = ff_h263_decode_mb;
-    s->low_delay       = 1;
-
-    /* select sub codec */
-    switch (avctx->codec->id) {
-    case AV_CODEC_ID_H263:
-    case AV_CODEC_ID_H263P:
-        avctx->chroma_sample_location = AVCHROMA_LOC_CENTER;
-        break;
-    case AV_CODEC_ID_MPEG4:
-        break;
-    case AV_CODEC_ID_MSMPEG4V1:
-        s->h263_pred       = 1;
-        s->msmpeg4_version = 1;
-        break;
-    case AV_CODEC_ID_MSMPEG4V2:
-        s->h263_pred       = 1;
-        s->msmpeg4_version = 2;
-        break;
-    case AV_CODEC_ID_MSMPEG4V3:
-        s->h263_pred       = 1;
-        s->msmpeg4_version = 3;
-        break;
-    case AV_CODEC_ID_WMV1:
-        s->h263_pred       = 1;
-        s->msmpeg4_version = 4;
-        break;
-    case AV_CODEC_ID_WMV2:
-        s->h263_pred       = 1;
-        s->msmpeg4_version = 5;
-        break;
-    case AV_CODEC_ID_H263I:
-        break;
-    case AV_CODEC_ID_FLV1:
-        s->h263_flv = 1;
-        break;
-    default:
-        av_log(avctx, AV_LOG_ERROR, "Unsupported codec %d\n",
-               avctx->codec->id);
-        return AVERROR(ENOSYS);
-    }
-
-    if (avctx->codec_tag == AV_RL32("L263") || avctx->codec_tag == AV_RL32("S263"))
-        if (avctx->extradata_size == 56 && avctx->extradata[0] == 1)
-            s->ehc_mode = 1;
-
-    /* for H.263, we allocate the images after having read the header */
-    if (avctx->codec->id != AV_CODEC_ID_H263 &&
-        avctx->codec->id != AV_CODEC_ID_H263P &&
-        avctx->codec->id != AV_CODEC_ID_MPEG4) {
-        avctx->pix_fmt = h263_get_format(avctx);
-        ff_mpv_idct_init(s);
-        if ((ret = ff_mpv_common_init(s)) < 0)
-            return ret;
-    }
-
-    ff_h263dsp_init(&s->h263dsp);
-    ff_h263_decode_init_vlc();
-
-    return 0;
-}
-
-av_cold int ff_h263_decode_end(AVCodecContext *avctx)
-{
-    MpegEncContext *s = avctx->priv_data;
-
-    ff_mpv_common_end(s);
-    return 0;
-}
-
-/**
- * Return the number of bytes consumed for building the current frame.
- */
-static int get_consumed_bytes(MpegEncContext *s, int buf_size)
-{
-    int pos = (get_bits_count(&s->gb) + 7) >> 3;
-
-    if (s->divx_packed || s->avctx->hwaccel) {
-        /* We would have to scan through the whole buf to handle the weird
-         * reordering ... */
-        return buf_size;
-    } else {
-        // avoid infinite loops (maybe not needed...)
-        if (pos == 0)
-            pos = 1;
-        // oops ;)
-        if (pos + 10 > buf_size)
-            pos = buf_size;
-
-        return pos;
-    }
-}
-
-static int decode_slice(MpegEncContext *s)
-{
-    const int part_mask = s->partitioned_frame
-                          ? (ER_AC_END | ER_AC_ERROR) : 0x7F;
-    const int mb_size   = 16 >> s->avctx->lowres;
-    int ret;
-
-    s->last_resync_gb   = s->gb;
-    s->first_slice_line = 1;
-    s->resync_mb_x      = s->mb_x;
-    s->resync_mb_y      = s->mb_y;
-
-    ff_set_qscale(s, s->qscale);
-
-    if (s->studio_profile) {
-        if ((ret = ff_mpeg4_decode_studio_slice_header(s->avctx->priv_data)) < 0)
-            return ret;
-    }
-
-    if (s->avctx->hwaccel) {
-        const uint8_t *start = s->gb.buffer + get_bits_count(&s->gb) / 8;
-        ret = s->avctx->hwaccel->decode_slice(s->avctx, start, s->gb.buffer_end - start);
-        // ensure we exit decode loop
-        s->mb_y = s->mb_height;
-        return ret;
-    }
-
-    if (s->partitioned_frame) {
-        const int qscale = s->qscale;
-
-        if (CONFIG_MPEG4_DECODER && s->codec_id == AV_CODEC_ID_MPEG4)
-            if ((ret = ff_mpeg4_decode_partitions(s->avctx->priv_data)) < 0)
-                return ret;
-
-        /* restore variables which were modified */
-        s->first_slice_line = 1;
-        s->mb_x             = s->resync_mb_x;
-        s->mb_y             = s->resync_mb_y;
-        ff_set_qscale(s, qscale);
-    }
-
-    for (; s->mb_y < s->mb_height; s->mb_y++) {
-        /* per-row end of slice checks */
-        if (s->msmpeg4_version) {
-            if (s->resync_mb_y + s->slice_height == s->mb_y) {
-                ff_er_add_slice(&s->er, s->resync_mb_x, s->resync_mb_y,
-                                s->mb_x - 1, s->mb_y, ER_MB_END);
-
-                return 0;
-            }
-        }
-
-        if (s->msmpeg4_version == 1) {
-            s->last_dc[0] =
-            s->last_dc[1] =
-            s->last_dc[2] = 128;
-        }
-
-        ff_init_block_index(s);
-        for (; s->mb_x < s->mb_width; s->mb_x++) {
-            int ret;
-
-            ff_update_block_index(s, s->avctx->bits_per_raw_sample,
-                                  s->avctx->lowres, s->chroma_x_shift);
-
-            if (s->resync_mb_x == s->mb_x && s->resync_mb_y + 1 == s->mb_y)
-                s->first_slice_line = 0;
-
-            /* DCT & quantize */
-
-            s->mv_dir  = MV_DIR_FORWARD;
-            s->mv_type = MV_TYPE_16X16;
-            ff_dlog(s, "%d %06X\n",
-                    get_bits_count(&s->gb), show_bits(&s->gb, 24));
-
-            ff_tlog(NULL, "Decoding MB at %dx%d\n", s->mb_x, s->mb_y);
-            ret = s->decode_mb(s, s->block);
-
-            if (s->pict_type != AV_PICTURE_TYPE_B)
-                ff_h263_update_motion_val(s);
-
-            if (ret < 0) {
-                const int xy = s->mb_x + s->mb_y * s->mb_stride;
-                if (ret == SLICE_END) {
-                    ff_mpv_reconstruct_mb(s, s->block);
-                    if (s->loop_filter)
-                        ff_h263_loop_filter(s);
-
-                    ff_er_add_slice(&s->er, s->resync_mb_x, s->resync_mb_y,
-                                    s->mb_x, s->mb_y, ER_MB_END & part_mask);
-
-                    s->padding_bug_score--;
-
-                    if (++s->mb_x >= s->mb_width) {
-                        s->mb_x = 0;
-                        ff_mpeg_draw_horiz_band(s, s->mb_y * mb_size, mb_size);
-                        ff_mpv_report_decode_progress(s);
-                        s->mb_y++;
-                    }
-                    return 0;
-                } else if (ret == SLICE_NOEND) {
-                    av_log(s->avctx, AV_LOG_ERROR,
-                           "Slice mismatch at MB: %d\n", xy);
-                    ff_er_add_slice(&s->er, s->resync_mb_x, s->resync_mb_y,
-                                    s->mb_x + 1, s->mb_y,
-                                    ER_MB_END & part_mask);
-                    return AVERROR_INVALIDDATA;
-                }
-                av_log(s->avctx, AV_LOG_ERROR, "Error at MB: %d\n", xy);
-                ff_er_add_slice(&s->er, s->resync_mb_x, s->resync_mb_y,
-                                s->mb_x, s->mb_y, ER_MB_ERROR & part_mask);
-
-                if (s->avctx->err_recognition & AV_EF_IGNORE_ERR)
-                    continue;
-                return AVERROR_INVALIDDATA;
-            }
-
-            ff_mpv_reconstruct_mb(s, s->block);
-            if (s->loop_filter)
-                ff_h263_loop_filter(s);
-        }
-
-        ff_mpeg_draw_horiz_band(s, s->mb_y * mb_size, mb_size);
-        ff_mpv_report_decode_progress(s);
-
-        s->mb_x = 0;
-    }
-
-    av_assert1(s->mb_x == 0 && s->mb_y == s->mb_height);
-
-    // Detect incorrect padding with wrong stuffing codes used by NEC N-02B
-    if (s->codec_id == AV_CODEC_ID_MPEG4         &&
-        (s->workaround_bugs & FF_BUG_AUTODETECT) &&
-        get_bits_left(&s->gb) >= 48              &&
-        show_bits(&s->gb, 24) == 0x4010          &&
-        !s->data_partitioning)
-        s->padding_bug_score += 32;
-
-    /* try to detect the padding bug */
-    if (s->codec_id == AV_CODEC_ID_MPEG4         &&
-        (s->workaround_bugs & FF_BUG_AUTODETECT) &&
-        get_bits_left(&s->gb) >= 0               &&
-        get_bits_left(&s->gb) < 137              &&
-        !s->data_partitioning) {
-        const int bits_count = get_bits_count(&s->gb);
-        const int bits_left  = s->gb.size_in_bits - bits_count;
-
-        if (bits_left == 0) {
-            s->padding_bug_score += 16;
-        } else if (bits_left != 1) {
-            int v = show_bits(&s->gb, 8);
-            v |= 0x7F >> (7 - (bits_count & 7));
-
-            if (v == 0x7F && bits_left <= 8)
-                s->padding_bug_score--;
-            else if (v == 0x7F && ((get_bits_count(&s->gb) + 8) & 8) &&
-                     bits_left <= 16)
-                s->padding_bug_score += 4;
-            else
-                s->padding_bug_score++;
-        }
-    }
-
-    if (s->codec_id == AV_CODEC_ID_H263          &&
-        (s->workaround_bugs & FF_BUG_AUTODETECT) &&
-        get_bits_left(&s->gb) >= 8               &&
-        get_bits_left(&s->gb) < 300              &&
-        s->pict_type == AV_PICTURE_TYPE_I        &&
-        show_bits(&s->gb, 8) == 0                &&
-        !s->data_partitioning) {
-
-        s->padding_bug_score += 32;
-    }
-
-    if (s->codec_id == AV_CODEC_ID_H263          &&
-        (s->workaround_bugs & FF_BUG_AUTODETECT) &&
-        get_bits_left(&s->gb) >= 64              &&
-        AV_RB64(s->gb.buffer_end - 8) == 0xCDCDCDCDFC7F0000) {
-
-        s->padding_bug_score += 32;
-    }
-
-    if (s->workaround_bugs & FF_BUG_AUTODETECT) {
-        if (
-            (s->padding_bug_score > -2 && !s->data_partitioning))
-            s->workaround_bugs |= FF_BUG_NO_PADDING;
-        else
-            s->workaround_bugs &= ~FF_BUG_NO_PADDING;
-    }
-
-    // handle formats which don't have unique end markers
-    if (s->msmpeg4_version || (s->workaround_bugs & FF_BUG_NO_PADDING)) { // FIXME perhaps solve this more cleanly
-        int left      = get_bits_left(&s->gb);
-        int max_extra = 7;
-
-        /* no markers in M$ crap */
-        if (s->msmpeg4_version && s->pict_type == AV_PICTURE_TYPE_I)
-            max_extra += 17;
-
-        /* buggy padding but the frame should still end approximately at
-         * the bitstream end */
-        if ((s->workaround_bugs & FF_BUG_NO_PADDING) &&
-            (s->avctx->err_recognition & (AV_EF_BUFFER|AV_EF_AGGRESSIVE)))
-            max_extra += 48;
-        else if ((s->workaround_bugs & FF_BUG_NO_PADDING))
-            max_extra += 256 * 256 * 256 * 64;
-
-        if (left > max_extra)
-            av_log(s->avctx, AV_LOG_ERROR,
-                   "discarding %d junk bits at end, next would be %X\n",
-                   left, show_bits(&s->gb, 24));
-        else if (left < 0)
-            av_log(s->avctx, AV_LOG_ERROR, "overreading %d bits\n", -left);
-        else
-            ff_er_add_slice(&s->er, s->resync_mb_x, s->resync_mb_y,
-                            s->mb_x - 1, s->mb_y, ER_MB_END);
-
-        return 0;
-    }
-
-    av_log(s->avctx, AV_LOG_ERROR,
-           "slice end not reached but screenspace end (%d left %06X, score= %d)\n",
-           get_bits_left(&s->gb), show_bits(&s->gb, 24), s->padding_bug_score);
-
-    ff_er_add_slice(&s->er, s->resync_mb_x, s->resync_mb_y, s->mb_x, s->mb_y,
-                    ER_MB_END & part_mask);
-
-    return AVERROR_INVALIDDATA;
-}
-
-int ff_h263_decode_frame(AVCodecContext *avctx, AVFrame *pict,
-                         int *got_frame, AVPacket *avpkt)
-{
-    const uint8_t *buf = avpkt->data;
-    int buf_size       = avpkt->size;
-    MpegEncContext *s  = avctx->priv_data;
-    int ret;
-    int slice_ret = 0;
-
-    /* no supplementary picture */
-    if (buf_size == 0) {
-        /* special case for last picture */
-        if (s->low_delay == 0 && s->next_picture_ptr) {
-            if ((ret = av_frame_ref(pict, s->next_picture_ptr->f)) < 0)
-                return ret;
-            s->next_picture_ptr = NULL;
-
-            *got_frame = 1;
-        } else if (s->skipped_last_frame && s->current_picture_ptr) {
-            /* Output the last picture we decoded again if the stream ended with
-             * an NVOP */
-            if ((ret = av_frame_ref(pict, s->current_picture_ptr->f)) < 0)
-                return ret;
-            /* Copy props from the last input packet. Otherwise, props from the last
-             * returned picture would be reused */
-            if ((ret = ff_decode_frame_props(avctx, pict)) < 0)
-                return ret;
-            s->current_picture_ptr = NULL;
-
-            *got_frame = 1;
-        }
-
-        return 0;
-    }
-
-retry:
-    if (s->divx_packed && s->bitstream_buffer_size) {
-        int i;
-        for(i=0; i < buf_size-3; i++) {
-            if (buf[i]==0 && buf[i+1]==0 && buf[i+2]==1) {
-                if (buf[i+3]==0xB0) {
-                    av_log(s->avctx, AV_LOG_WARNING, "Discarding excessive bitstream in packed xvid\n");
-                    s->bitstream_buffer_size = 0;
-                }
-                break;
-            }
-        }
-    }
-
-    if (s->bitstream_buffer_size && (s->divx_packed || buf_size <= MAX_NVOP_SIZE)) // divx 5.01+/xvid frame reorder
-        ret = init_get_bits8(&s->gb, s->bitstream_buffer,
-                             s->bitstream_buffer_size);
-    else
-        ret = init_get_bits8(&s->gb, buf, buf_size);
-
-    s->bitstream_buffer_size = 0;
-    if (ret < 0)
-        return ret;
-
-    if (!s->context_initialized)
-        // we need the idct permutation for reading a custom matrix
-        ff_mpv_idct_init(s);
-
-    /* let's go :-) */
-    if (CONFIG_WMV2_DECODER && s->msmpeg4_version == 5) {
-        ret = ff_wmv2_decode_picture_header(s);
-    } else if (CONFIG_MSMPEG4DEC && s->msmpeg4_version) {
-        ret = ff_msmpeg4_decode_picture_header(s);
-    } else if (CONFIG_MPEG4_DECODER && avctx->codec_id == AV_CODEC_ID_MPEG4) {
-        if (s->avctx->extradata_size && !s->extradata_parsed) {
-            GetBitContext gb;
-
-            if (init_get_bits8(&gb, s->avctx->extradata, s->avctx->extradata_size) >= 0 )
-                ff_mpeg4_decode_picture_header(avctx->priv_data, &gb, 1, 0);
-            s->extradata_parsed = 1;
-        }
-        ret = ff_mpeg4_decode_picture_header(avctx->priv_data, &s->gb, 0, 0);
-        s->skipped_last_frame = (ret == FRAME_SKIPPED);
-    } else if (CONFIG_H263I_DECODER && s->codec_id == AV_CODEC_ID_H263I) {
-        ret = ff_intel_h263_decode_picture_header(s);
-    } else if (CONFIG_FLV_DECODER && s->h263_flv) {
-        ret = ff_flv_decode_picture_header(s);
-    } else {
-        ret = ff_h263_decode_picture_header(s);
-    }
-
-    if (ret < 0 || ret == FRAME_SKIPPED) {
-        if (   s->width  != avctx->coded_width
-            || s->height != avctx->coded_height) {
-                av_log(s->avctx, AV_LOG_WARNING, "Reverting picture dimensions change due to header decoding failure\n");
-                s->width = avctx->coded_width;
-                s->height= avctx->coded_height;
-        }
-    }
-    if (ret == FRAME_SKIPPED)
-        return get_consumed_bytes(s, buf_size);
-
-    /* skip if the header was thrashed */
-    if (ret < 0) {
-        av_log(s->avctx, AV_LOG_ERROR, "header damaged\n");
-        return ret;
-    }
-
-    if (!s->context_initialized) {
-        avctx->pix_fmt = h263_get_format(avctx);
-        if ((ret = ff_mpv_common_init(s)) < 0)
-            return ret;
-    }
-
-    avctx->has_b_frames = !s->low_delay;
-
-    if (CONFIG_MPEG4_DECODER && avctx->codec_id == AV_CODEC_ID_MPEG4) {
-        if (s->pict_type != AV_PICTURE_TYPE_B && s->mb_num/2 > get_bits_left(&s->gb))
-            return AVERROR_INVALIDDATA;
-        if (ff_mpeg4_workaround_bugs(avctx) == 1)
-            goto retry;
-        if (s->studio_profile != (s->idsp.idct == NULL))
-            ff_mpv_idct_init(s);
-    }
-
-    /* After H.263 & MPEG-4 header decode we have the height, width,
-     * and other parameters. So then we could init the picture.
-     * FIXME: By the way H.263 decoder is evolving it should have
-     * an H263EncContext */
-    if (s->width  != avctx->coded_width  ||
-        s->height != avctx->coded_height ||
-        s->context_reinit) {
-        /* H.263 could change picture size any time */
-        s->context_reinit = 0;
-
-        ret = ff_set_dimensions(avctx, s->width, s->height);
-        if (ret < 0)
-            return ret;
-
-        ff_set_sar(avctx, avctx->sample_aspect_ratio);
-
-        if ((ret = ff_mpv_common_frame_size_change(s)))
-            return ret;
-
-        if (avctx->pix_fmt != h263_get_format(avctx)) {
-            av_log(avctx, AV_LOG_ERROR, "format change not supported\n");
-            avctx->pix_fmt = AV_PIX_FMT_NONE;
-            return AVERROR_UNKNOWN;
-        }
-    }
-
-    if (s->codec_id == AV_CODEC_ID_H263  ||
-        s->codec_id == AV_CODEC_ID_H263P ||
-        s->codec_id == AV_CODEC_ID_H263I)
-        s->gob_index = H263_GOB_HEIGHT(s->height);
-
-    /* skip B-frames if we don't have reference frames */
-    if (!s->last_picture_ptr &&
-        (s->pict_type == AV_PICTURE_TYPE_B || s->droppable))
-        return get_consumed_bytes(s, buf_size);
-    if ((avctx->skip_frame >= AVDISCARD_NONREF &&
-         s->pict_type == AV_PICTURE_TYPE_B)    ||
-        (avctx->skip_frame >= AVDISCARD_NONKEY &&
-         s->pict_type != AV_PICTURE_TYPE_I)    ||
-        avctx->skip_frame >= AVDISCARD_ALL)
-        return get_consumed_bytes(s, buf_size);
-
-    if ((ret = ff_mpv_frame_start(s, avctx)) < 0)
-        return ret;
-
-    if (!s->divx_packed && !avctx->hwaccel)
-        ff_thread_finish_setup(avctx);
-
-    if (avctx->hwaccel) {
-        ret = avctx->hwaccel->start_frame(avctx, s->gb.buffer,
-                                          s->gb.buffer_end - s->gb.buffer);
-        if (ret < 0 )
-            return ret;
-    }
-
-    ff_mpeg_er_frame_start(s);
-
-    /* the second part of the wmv2 header contains the MB skip bits which
-     * are stored in current_picture->mb_type which is not available before
-     * ff_mpv_frame_start() */
-    if (CONFIG_WMV2_DECODER && s->msmpeg4_version == 5) {
-        ret = ff_wmv2_decode_secondary_picture_header(s);
-        if (ret < 0)
-            return ret;
-        if (ret == 1)
-            goto frame_end;
-    }
-
-    /* decode each macroblock */
-    s->mb_x = 0;
-    s->mb_y = 0;
-
-    slice_ret = decode_slice(s);
-    while (s->mb_y < s->mb_height) {
-        if (s->msmpeg4_version) {
-            if (s->slice_height == 0 || s->mb_x != 0 || slice_ret < 0 ||
-                (s->mb_y % s->slice_height) != 0 || get_bits_left(&s->gb) < 0)
-                break;
-        } else {
-            int prev_x = s->mb_x, prev_y = s->mb_y;
-            if (ff_h263_resync(s) < 0)
-                break;
-            if (prev_y * s->mb_width + prev_x < s->mb_y * s->mb_width + s->mb_x)
-                s->er.error_occurred = 1;
-        }
-
-        if (s->msmpeg4_version < 4 && s->h263_pred)
-            ff_mpeg4_clean_buffers(s);
-
-        if (decode_slice(s) < 0)
-            slice_ret = AVERROR_INVALIDDATA;
-    }
-
-    if (s->msmpeg4_version && s->msmpeg4_version < 4 &&
-        s->pict_type == AV_PICTURE_TYPE_I)
-        if (!CONFIG_MSMPEG4DEC ||
-            ff_msmpeg4_decode_ext_header(s, buf_size) < 0)
-            s->er.error_status_table[s->mb_num - 1] = ER_MB_ERROR;
-
-    av_assert1(s->bitstream_buffer_size == 0);
-frame_end:
-    if (!s->studio_profile)
-        ff_er_frame_end(&s->er);
-
-    if (avctx->hwaccel) {
-        ret = avctx->hwaccel->end_frame(avctx);
-        if (ret < 0)
-            return ret;
-    }
-
-    ff_mpv_frame_end(s);
-
-    if (CONFIG_MPEG4_DECODER && avctx->codec_id == AV_CODEC_ID_MPEG4)
-        ff_mpeg4_frame_end(avctx, buf, buf_size);
-
-    if (!s->divx_packed && avctx->hwaccel)
-        ff_thread_finish_setup(avctx);
-
-    av_assert1(s->current_picture.f->pict_type == s->current_picture_ptr->f->pict_type);
-    av_assert1(s->current_picture.f->pict_type == s->pict_type);
-    if (s->pict_type == AV_PICTURE_TYPE_B || s->low_delay) {
-        if ((ret = av_frame_ref(pict, s->current_picture_ptr->f)) < 0)
-            return ret;
-        ff_print_debug_info(s, s->current_picture_ptr, pict);
-        ff_mpv_export_qp_table(s, pict, s->current_picture_ptr, FF_MPV_QSCALE_TYPE_MPEG1);
-    } else if (s->last_picture_ptr) {
-        if ((ret = av_frame_ref(pict, s->last_picture_ptr->f)) < 0)
-            return ret;
-        ff_print_debug_info(s, s->last_picture_ptr, pict);
-        ff_mpv_export_qp_table(s, pict, s->last_picture_ptr, FF_MPV_QSCALE_TYPE_MPEG1);
-    }
-
-    if (s->last_picture_ptr || s->low_delay) {
-        if (   pict->format == AV_PIX_FMT_YUV420P
-            && (s->codec_tag == AV_RL32("GEOV") || s->codec_tag == AV_RL32("GEOX"))) {
-            for (int p = 0; p < 3; p++) {
-                int h = AV_CEIL_RSHIFT(pict->height, !!p);
-
-                pict->data[p]     += (h - 1) * pict->linesize[p];
-                pict->linesize[p] *= -1;
-            }
-        }
-        *got_frame = 1;
-    }
-
-    if (slice_ret < 0 && (avctx->err_recognition & AV_EF_EXPLODE))
-        return slice_ret;
-    else
-        return get_consumed_bytes(s, buf_size);
-}
-
-const enum AVPixelFormat ff_h263_hwaccel_pixfmt_list_420[] = {
-#if CONFIG_H263_VAAPI_HWACCEL || CONFIG_MPEG4_VAAPI_HWACCEL
-    AV_PIX_FMT_VAAPI,
-#endif
-#if CONFIG_MPEG4_NVDEC_HWACCEL
-    AV_PIX_FMT_CUDA,
-#endif
-#if CONFIG_MPEG4_VDPAU_HWACCEL
-    AV_PIX_FMT_VDPAU,
-#endif
-#if CONFIG_H263_VIDEOTOOLBOX_HWACCEL || CONFIG_MPEG4_VIDEOTOOLBOX_HWACCEL
-    AV_PIX_FMT_VIDEOTOOLBOX,
-#endif
-    AV_PIX_FMT_YUV420P,
-    AV_PIX_FMT_NONE
-};
-
-static const AVCodecHWConfigInternal *const h263_hw_config_list[] = {
-#if CONFIG_H263_VAAPI_HWACCEL
-    HWACCEL_VAAPI(h263),
-#endif
-#if CONFIG_MPEG4_NVDEC_HWACCEL
-    HWACCEL_NVDEC(mpeg4),
-#endif
-#if CONFIG_MPEG4_VDPAU_HWACCEL
-    HWACCEL_VDPAU(mpeg4),
-#endif
-#if CONFIG_H263_VIDEOTOOLBOX_HWACCEL
-    HWACCEL_VIDEOTOOLBOX(h263),
-#endif
-    NULL
-};
-
-const FFCodec ff_h263_decoder = {
-    .p.name         = "h263",
-    CODEC_LONG_NAME("H.263 / H.263-1996, H.263+ / H.263-1998 / H.263 version 2"),
-    .p.type         = AVMEDIA_TYPE_VIDEO,
-    .p.id           = AV_CODEC_ID_H263,
-    .priv_data_size = sizeof(MpegEncContext),
-    .init           = ff_h263_decode_init,
-    .close          = ff_h263_decode_end,
-    FF_CODEC_DECODE_CB(ff_h263_decode_frame),
-    .p.capabilities = AV_CODEC_CAP_DRAW_HORIZ_BAND | AV_CODEC_CAP_DR1 |
-                      AV_CODEC_CAP_DELAY,
-    .caps_internal  = FF_CODEC_CAP_SKIP_FRAME_FILL_PARAM,
-    .flush          = ff_mpeg_flush,
-    .p.max_lowres   = 3,
-    .p.pix_fmts     = ff_h263_hwaccel_pixfmt_list_420,
-    .hw_configs     = h263_hw_config_list,
-};
-
-const FFCodec ff_h263p_decoder = {
-    .p.name         = "h263p",
-    CODEC_LONG_NAME("H.263 / H.263-1996, H.263+ / H.263-1998 / H.263 version 2"),
-    .p.type         = AVMEDIA_TYPE_VIDEO,
-    .p.id           = AV_CODEC_ID_H263P,
-    .priv_data_size = sizeof(MpegEncContext),
-    .init           = ff_h263_decode_init,
-    .close          = ff_h263_decode_end,
-    FF_CODEC_DECODE_CB(ff_h263_decode_frame),
-    .p.capabilities = AV_CODEC_CAP_DRAW_HORIZ_BAND | AV_CODEC_CAP_DR1 |
-                      AV_CODEC_CAP_DELAY,
-    .caps_internal  = FF_CODEC_CAP_SKIP_FRAME_FILL_PARAM,
-    .flush          = ff_mpeg_flush,
-    .p.max_lowres   = 3,
-    .p.pix_fmts     = ff_h263_hwaccel_pixfmt_list_420,
-    .hw_configs     = h263_hw_config_list,
-};
diff --git a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/mips/h264pred_mmi.c b/spaces/colakin/video-generater/public/ffmpeg/libavcodec/mips/h264pred_mmi.c
deleted file mode 100644
index 480411f5b5793762096844d05891d7ded8bc76c3..0000000000000000000000000000000000000000
--- a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/mips/h264pred_mmi.c
+++ /dev/null
@@ -1,990 +0,0 @@
-/*
- * Loongson SIMD optimized h264pred
- *
- * Copyright (c) 2015 Loongson Technology Corporation Limited
- * Copyright (c) 2015 Zhou Xiaoyong <zhouxiaoyong@loongson.cn>
- *                    Zhang Shuangshuang <zhangshuangshuang@ict.ac.cn>
- *
- * This file is part of FFmpeg.
- *
- * FFmpeg is free software; you can redistribute it and/or
- * modify it under the terms of the GNU Lesser General Public
- * License as published by the Free Software Foundation; either
- * version 2.1 of the License, or (at your option) any later version.
- *
- * FFmpeg is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
- * Lesser General Public License for more details.
- *
- * You should have received a copy of the GNU Lesser General Public
- * License along with FFmpeg; if not, write to the Free Software
- * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
- */
-
-#include "h264pred_mips.h"
-#include "libavcodec/bit_depth_template.c"
-#include "libavutil/mips/mmiutils.h"
-#include "constants.h"
-
-void ff_pred16x16_vertical_8_mmi(uint8_t *src, ptrdiff_t stride)
-{
-    double ftmp[2];
-    uint64_t tmp[1];
-    DECLARE_VAR_ALL64;
-
-    __asm__ volatile (
-        "dli        %[tmp0],    0x08                                    \n\t"
-        MMI_LDC1(%[ftmp0], %[srcA], 0x00)
-        MMI_LDC1(%[ftmp1], %[srcA], 0x08)
-
-        "1:                                                             \n\t"
-        MMI_SDC1(%[ftmp0], %[src], 0x00)
-        MMI_SDC1(%[ftmp1], %[src], 0x08)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp0], %[src], 0x00)
-        MMI_SDC1(%[ftmp1], %[src], 0x08)
-
-        "daddi      %[tmp0],    %[tmp0],        -0x01                   \n\t"
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        "bnez       %[tmp0],    1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [tmp0]"=&r"(tmp[0]),
-          RESTRICT_ASM_ALL64
-          [src]"+&r"(src)
-        : [stride]"r"((mips_reg)stride),    [srcA]"r"((mips_reg)(src-stride))
-        : "memory"
-    );
-}
-
-void ff_pred16x16_horizontal_8_mmi(uint8_t *src, ptrdiff_t stride)
-{
-    uint64_t tmp[3];
-    mips_reg addr[2];
-
-    __asm__ volatile (
-        PTR_ADDI   "%[addr0],   %[src],         -0x01                   \n\t"
-        PTR_ADDU   "%[addr1],   %[src],         $0                      \n\t"
-        "dli        %[tmp2],    0x08                                    \n\t"
-        "1:                                                             \n\t"
-        "lbu        %[tmp0],    0x00(%[addr0])                          \n\t"
-        "dmul       %[tmp1],    %[tmp0],        %[ff_pb_1]              \n\t"
-        "swl        %[tmp1],    0x07(%[addr1])                          \n\t"
-        "swr        %[tmp1],    0x00(%[addr1])                          \n\t"
-        "swl        %[tmp1],    0x0f(%[addr1])                          \n\t"
-        "swr        %[tmp1],    0x08(%[addr1])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        PTR_ADDU   "%[addr1],   %[addr1],       %[stride]               \n\t"
-        "lbu        %[tmp0],    0x00(%[addr0])                          \n\t"
-        "dmul       %[tmp1],    %[tmp0],        %[ff_pb_1]              \n\t"
-        "swl        %[tmp1],    0x07(%[addr1])                          \n\t"
-        "swr        %[tmp1],    0x00(%[addr1])                          \n\t"
-        "swl        %[tmp1],    0x0f(%[addr1])                          \n\t"
-        "swr        %[tmp1],    0x08(%[addr1])                          \n\t"
-        "daddi      %[tmp2],    %[tmp2],        -0x01                   \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        PTR_ADDU   "%[addr1],   %[addr1],       %[stride]               \n\t"
-        "bnez       %[tmp2],    1b                                      \n\t"
-        : [tmp0]"=&r"(tmp[0]),              [tmp1]"=&r"(tmp[1]),
-          [tmp2]"=&r"(tmp[2]),
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1])
-        : [src]"r"((mips_reg)src),          [stride]"r"((mips_reg)stride),
-          [ff_pb_1]"r"(ff_pb_1)
-        : "memory"
-    );
-}
-
-void ff_pred16x16_dc_8_mmi(uint8_t *src, ptrdiff_t stride)
-{
-    uint64_t tmp[4];
-    mips_reg addr[2];
-
-    __asm__ volatile (
-        PTR_ADDI   "%[addr0],   %[src],         -0x01                   \n\t"
-        "dli        %[tmp0],    0x08                                    \n\t"
-        "xor        %[tmp3],    %[tmp3],        %[tmp3]                 \n\t"
-        "1:                                                             \n\t"
-        "lbu        %[tmp1],    0x00(%[addr0])                          \n\t"
-        "daddu      %[tmp3],    %[tmp3],        %[tmp1]                 \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp1],    0x00(%[addr0])                          \n\t"
-        "daddi      %[tmp0],    %[tmp0],        -0x01                   \n\t"
-        "daddu      %[tmp3],    %[tmp3],        %[tmp1]                 \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "bnez       %[tmp0],    1b                                      \n\t"
-
-        "dli        %[tmp0],    0x08                                    \n\t"
-        PTR_SUBU   "%[addr0],   %[src],         %[stride]               \n\t"
-        "2:                                                             \n\t"
-        "lbu        %[tmp1],    0x00(%[addr0])                          \n\t"
-        "daddu      %[tmp3],    %[tmp3],        %[tmp1]                 \n\t"
-        PTR_ADDIU  "%[addr0],   %[addr0],       0x01                    \n\t"
-        "lbu        %[tmp1],    0x00(%[addr0])                          \n\t"
-        "daddi      %[tmp0],    %[tmp0],        -0x01                   \n\t"
-        "daddu      %[tmp3],    %[tmp3],        %[tmp1]                 \n\t"
-        PTR_ADDIU  "%[addr0],   %[addr0],       0x01                    \n\t"
-        "bnez       %[tmp0],    2b                                      \n\t"
-
-        "daddiu     %[tmp3],    %[tmp3],        0x10                    \n\t"
-        "dsra       %[tmp3],    0x05                                    \n\t"
-        "dmul       %[tmp2],    %[tmp3],        %[ff_pb_1]              \n\t"
-        PTR_ADDU   "%[addr0],   %[src],         $0                      \n\t"
-        "dli        %[tmp0],    0x08                                    \n\t"
-        "3:                                                             \n\t"
-        "swl        %[tmp2],    0x07(%[addr0])                          \n\t"
-        "swr        %[tmp2],    0x00(%[addr0])                          \n\t"
-        "swl        %[tmp2],    0x0f(%[addr0])                          \n\t"
-        "swr        %[tmp2],    0x08(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "swl        %[tmp2],    0x07(%[addr0])                          \n\t"
-        "swr        %[tmp2],    0x00(%[addr0])                          \n\t"
-        "swl        %[tmp2],    0x0f(%[addr0])                          \n\t"
-        "swr        %[tmp2],    0x08(%[addr0])                          \n\t"
-        "daddi      %[tmp0],    %[tmp0],        -0x01                   \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "bnez       %[tmp0],    3b                                      \n\t"
-        : [tmp0]"=&r"(tmp[0]),              [tmp1]"=&r"(tmp[1]),
-          [tmp2]"=&r"(tmp[2]),              [tmp3]"=&r"(tmp[3]),
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1])
-        : [src]"r"((mips_reg)src),          [stride]"r"((mips_reg)stride),
-          [ff_pb_1]"r"(ff_pb_1)
-        : "memory"
-    );
-}
-
-void ff_pred8x8l_top_dc_8_mmi(uint8_t *src, int has_topleft,
-        int has_topright, ptrdiff_t stride)
-{
-    double ftmp[11];
-    mips_reg tmp[3];
-    union av_intfloat64 dc;
-    DECLARE_VAR_ALL64;
-    DECLARE_VAR_ADDRT;
-
-    __asm__ volatile (
-        "pxor       %[ftmp0],   %[ftmp0],       %[ftmp0]                \n\t"
-        MMI_ULDC1(%[ftmp10], %[srcA], 0x00)
-        MMI_ULDC1(%[ftmp9], %[src0], 0x00)
-        MMI_ULDC1(%[ftmp8], %[src1], 0x00)
-
-        "punpcklbh  %[ftmp7],   %[ftmp10],      %[ftmp0]                \n\t"
-        "punpckhbh  %[ftmp6],   %[ftmp10],      %[ftmp0]                \n\t"
-        "punpcklbh  %[ftmp5],   %[ftmp9],       %[ftmp0]                \n\t"
-        "punpckhbh  %[ftmp4],   %[ftmp9],       %[ftmp0]                \n\t"
-        "punpcklbh  %[ftmp3],   %[ftmp8],       %[ftmp0]                \n\t"
-        "punpckhbh  %[ftmp2],   %[ftmp8],       %[ftmp0]                \n\t"
-        "bnez       %[has_topleft],             1f                      \n\t"
-        "pinsrh_0   %[ftmp7],   %[ftmp7],       %[ftmp5]                \n\t"
-
-        "1:                                                             \n\t"
-        "bnez       %[has_topright],            2f                      \n\t"
-        "dli        %[tmp0],    0xa4                                    \n\t"
-        "mtc1       %[tmp0],    %[ftmp1]                                \n\t"
-        "pshufh     %[ftmp2],   %[ftmp2],       %[ftmp1]                \n\t"
-
-        "2:                                                             \n\t"
-        "dli        %[tmp0],    0x02                                    \n\t"
-        "mtc1       %[tmp0],    %[ftmp1]                                \n\t"
-        "pmullh     %[ftmp5],   %[ftmp5],       %[ff_pw_2]              \n\t"
-        "pmullh     %[ftmp4],   %[ftmp4],       %[ff_pw_2]              \n\t"
-        "paddh      %[ftmp7],   %[ftmp7],       %[ftmp5]                \n\t"
-        "paddh      %[ftmp6],   %[ftmp6],       %[ftmp4]                \n\t"
-        "paddh      %[ftmp7],   %[ftmp7],       %[ftmp3]                \n\t"
-        "paddh      %[ftmp6],   %[ftmp6],       %[ftmp2]                \n\t"
-        "paddh      %[ftmp7],   %[ftmp7],       %[ff_pw_2]              \n\t"
-        "paddh      %[ftmp6],   %[ftmp6],       %[ff_pw_2]              \n\t"
-        "psrah      %[ftmp7],   %[ftmp7],       %[ftmp1]                \n\t"
-        "psrah      %[ftmp6],   %[ftmp6],       %[ftmp1]                \n\t"
-        "packushb   %[ftmp9],   %[ftmp7],       %[ftmp6]                \n\t"
-        "biadd      %[ftmp10],  %[ftmp9]                                \n\t"
-        "mfc1       %[tmp1],    %[ftmp10]                               \n\t"
-        "addiu      %[tmp1],    %[tmp1],        0x04                    \n\t"
-        "srl        %[tmp1],    %[tmp1],        0x03                    \n\t"
-        "mul        %[dc],      %[tmp1],        %[ff_pb_1]              \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          [ftmp4]"=&f"(ftmp[4]),            [ftmp5]"=&f"(ftmp[5]),
-          [ftmp6]"=&f"(ftmp[6]),            [ftmp7]"=&f"(ftmp[7]),
-          [ftmp8]"=&f"(ftmp[8]),            [ftmp9]"=&f"(ftmp[9]),
-          [ftmp10]"=&f"(ftmp[10]),
-          [tmp0]"=&r"(tmp[0]),              [tmp1]"=&r"(tmp[1]),
-          RESTRICT_ASM_ALL64
-          [dc]"=r"(dc.i)
-        : [srcA]"r"((mips_reg)(src-stride-1)),
-          [src0]"r"((mips_reg)(src-stride)),
-          [src1]"r"((mips_reg)(src-stride+1)),
-          [has_topleft]"r"(has_topleft),    [has_topright]"r"(has_topright),
-          [ff_pb_1]"r"(ff_pb_1.i),          [ff_pw_2]"f"(ff_pw_2.f)
-        : "memory"
-    );
-
-    __asm__ volatile (
-        "dli        %[tmp0],    0x02                                    \n\t"
-        "punpcklwd  %[ftmp0],   %[dc],          %[dc]                   \n\t"
-
-        "1:                                                             \n\t"
-        MMI_SDC1(%[ftmp0], %[src], 0x00)
-        MMI_SDXC1(%[ftmp0], %[src], %[stride], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp0], %[src], 0x00)
-        MMI_SDXC1(%[ftmp0], %[src], %[stride], 0x00)
-
-        "daddi      %[tmp0],    %[tmp0],        -0x01                   \n\t"
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        "bnez       %[tmp0],    1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [tmp0]"=&r"(tmp[0]),
-          RESTRICT_ASM_ALL64
-          RESTRICT_ASM_ADDRT
-          [src]"+&r"(src)
-        : [dc]"f"(dc.f),                    [stride]"r"((mips_reg)stride)
-        : "memory"
-    );
-}
-
-void ff_pred8x8l_dc_8_mmi(uint8_t *src, int has_topleft, int has_topright,
-        ptrdiff_t stride)
-{
-    uint32_t dc1, dc2;
-    double ftmp[14];
-    mips_reg tmp[1];
-    union av_intfloat64 dc;
-
-    const int l0 = ((has_topleft ? src[-1+-1*stride] : src[-1+0*stride]) + 2*src[-1+0*stride] + src[-1+1*stride] + 2) >> 2;
-    const int l1 = (src[-1+0*stride] + 2*src[-1+1*stride] + src[-1+2*stride] + 2) >> 2;
-    const int l2 = (src[-1+1*stride] + 2*src[-1+2*stride] + src[-1+3*stride] + 2) >> 2;
-    const int l3 = (src[-1+2*stride] + 2*src[-1+3*stride] + src[-1+4*stride] + 2) >> 2;
-    const int l4 = (src[-1+3*stride] + 2*src[-1+4*stride] + src[-1+5*stride] + 2) >> 2;
-    const int l5 = (src[-1+4*stride] + 2*src[-1+5*stride] + src[-1+6*stride] + 2) >> 2;
-    const int l6 = (src[-1+5*stride] + 2*src[-1+6*stride] + src[-1+7*stride] + 2) >> 2;
-    const int l7 = (src[-1+6*stride] + 2*src[-1+7*stride] + src[-1+7*stride] + 2) >> 2;
-
-    DECLARE_VAR_ALL64;
-    DECLARE_VAR_ADDRT;
-
-    __asm__ volatile (
-        MMI_ULDC1(%[ftmp4], %[srcA], 0x00)
-        MMI_ULDC1(%[ftmp5], %[src0], 0x00)
-        MMI_ULDC1(%[ftmp6], %[src1], 0x00)
-        "pxor       %[ftmp0],   %[ftmp0],       %[ftmp0]                \n\t"
-        "dli        %[tmp0],    0x03                                    \n\t"
-        "punpcklbh  %[ftmp7],   %[ftmp4],       %[ftmp0]                \n\t"
-        "punpckhbh  %[ftmp8],   %[ftmp4],       %[ftmp0]                \n\t"
-        "mtc1       %[tmp0],    %[ftmp1]                                \n\t"
-        "punpcklbh  %[ftmp9],   %[ftmp5],       %[ftmp0]                \n\t"
-        "punpckhbh  %[ftmp10],  %[ftmp5],       %[ftmp0]                \n\t"
-        "punpcklbh  %[ftmp11],  %[ftmp6],       %[ftmp0]                \n\t"
-        "punpckhbh  %[ftmp12],  %[ftmp6],       %[ftmp0]                \n\t"
-        "pshufh     %[ftmp3],   %[ftmp8],       %[ftmp1]                \n\t"
-        "pshufh     %[ftmp13],  %[ftmp12],      %[ftmp1]                \n\t"
-        "pinsrh_3   %[ftmp8],   %[ftmp8],       %[ftmp13]               \n\t"
-        "pinsrh_3   %[ftmp12],  %[ftmp12],      %[ftmp3]                \n\t"
-        "bnez       %[has_topleft],             1f                      \n\t"
-        "pinsrh_0   %[ftmp7],   %[ftmp7],       %[ftmp9]                \n\t"
-
-        "1:                                                             \n\t"
-        "bnez       %[has_topright],            2f                      \n\t"
-        "pshufh     %[ftmp13],  %[ftmp10],      %[ftmp1]                \n\t"
-        "pinsrh_3   %[ftmp8],   %[ftmp8],       %[ftmp13]               \n\t"
-
-        "2:                                                             \n\t"
-        "dli        %[tmp0],    0x02                                    \n\t"
-        "mtc1       %[tmp0],    %[ftmp1]                                \n\t"
-        "pshufh     %[ftmp2],   %[ftmp1],       %[ftmp0]                \n\t"
-        "pmullh     %[ftmp9],   %[ftmp9],       %[ftmp2]                \n\t"
-        "pmullh     %[ftmp10],  %[ftmp10],      %[ftmp2]                \n\t"
-        "paddh      %[ftmp7],   %[ftmp7],       %[ftmp9]                \n\t"
-        "paddh      %[ftmp8],   %[ftmp8],       %[ftmp10]               \n\t"
-        "paddh      %[ftmp7],   %[ftmp7],       %[ftmp11]               \n\t"
-        "paddh      %[ftmp8],   %[ftmp8],       %[ftmp12]               \n\t"
-        "paddh      %[ftmp7],   %[ftmp7],       %[ftmp2]                \n\t"
-        "paddh      %[ftmp8],   %[ftmp8],       %[ftmp2]                \n\t"
-        "psrah      %[ftmp7],   %[ftmp7],       %[ftmp1]                \n\t"
-        "psrah      %[ftmp8],   %[ftmp8],       %[ftmp1]                \n\t"
-        "packushb   %[ftmp5],   %[ftmp7],       %[ftmp8]                \n\t"
-        "biadd      %[ftmp4],   %[ftmp5]                                \n\t"
-        "mfc1       %[dc2],     %[ftmp4]                                \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          [ftmp4]"=&f"(ftmp[4]),            [ftmp5]"=&f"(ftmp[5]),
-          [ftmp6]"=&f"(ftmp[6]),            [ftmp7]"=&f"(ftmp[7]),
-          [ftmp8]"=&f"(ftmp[8]),            [ftmp9]"=&f"(ftmp[9]),
-          [ftmp10]"=&f"(ftmp[10]),          [ftmp11]"=&f"(ftmp[11]),
-          [ftmp12]"=&f"(ftmp[12]),          [ftmp13]"=&f"(ftmp[13]),
-          [tmp0]"=&r"(tmp[0]),
-          RESTRICT_ASM_ALL64
-          [dc2]"=r"(dc2)
-        : [srcA]"r"((mips_reg)(src-stride-1)),
-          [src0]"r"((mips_reg)(src-stride)),
-          [src1]"r"((mips_reg)(src-stride+1)),
-          [has_topleft]"r"(has_topleft),    [has_topright]"r"(has_topright)
-        : "memory"
-    );
-
-    dc1 = l0+l1+l2+l3+l4+l5+l6+l7;
-    dc.i = ((dc1+dc2+8)>>4)*0x01010101U;
-
-    __asm__ volatile (
-        "dli        %[tmp0],    0x02                                    \n\t"
-        "punpcklwd  %[ftmp0],   %[dc],          %[dc]                   \n\t"
-
-        "1:                                                             \n\t"
-        MMI_SDC1(%[ftmp0], %[src], 0x00)
-        MMI_SDXC1(%[ftmp0], %[src], %[stride], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp0], %[src], 0x00)
-        MMI_SDXC1(%[ftmp0], %[src], %[stride], 0x00)
-
-        "daddi      %[tmp0],    %[tmp0],        -0x01                   \n\t"
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        "bnez       %[tmp0],    1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [tmp0]"=&r"(tmp[0]),
-          RESTRICT_ASM_ALL64
-          RESTRICT_ASM_ADDRT
-          [src]"+&r"(src)
-        : [dc]"f"(dc.f),                    [stride]"r"((mips_reg)stride)
-        : "memory"
-    );
-}
-
-void ff_pred8x8l_vertical_8_mmi(uint8_t *src, int has_topleft,
-        int has_topright, ptrdiff_t stride)
-{
-    double ftmp[12];
-    mips_reg tmp[1];
-    DECLARE_VAR_ALL64;
-
-    __asm__ volatile (
-        "pxor       %[ftmp0],   %[ftmp0],       %[ftmp0]                \n\t"
-        MMI_LDC1(%[ftmp3], %[srcA], 0x00)
-        MMI_LDC1(%[ftmp4], %[src0], 0x00)
-        MMI_LDC1(%[ftmp5], %[src1], 0x00)
-        "punpcklbh  %[ftmp6],   %[ftmp3],       %[ftmp0]                \n\t"
-        "punpckhbh  %[ftmp7],   %[ftmp3],       %[ftmp0]                \n\t"
-        "punpcklbh  %[ftmp8],   %[ftmp4],       %[ftmp0]                \n\t"
-        "punpckhbh  %[ftmp9],   %[ftmp4],       %[ftmp0]                \n\t"
-        "punpcklbh  %[ftmp10],  %[ftmp5],       %[ftmp0]                \n\t"
-        "punpckhbh  %[ftmp11],  %[ftmp5],       %[ftmp0]                \n\t"
-        "bnez       %[has_topleft],             1f                      \n\t"
-        "pinsrh_0   %[ftmp6],   %[ftmp6],       %[ftmp8]                \n\t"
-
-        "1:                                                             \n\t"
-        "bnez       %[has_topright],            2f                      \n\t"
-        "dli        %[tmp0],    0xa4                                    \n\t"
-        "mtc1       %[tmp0],    %[ftmp1]                                \n\t"
-        "pshufh     %[ftmp11],  %[ftmp11],      %[ftmp1]                \n\t"
-
-        "2:                                                             \n\t"
-        "dli        %[tmp0],    0x02                                    \n\t"
-        "mtc1       %[tmp0],    %[ftmp1]                                \n\t"
-        "pshufh     %[ftmp2],   %[ftmp1],       %[ftmp0]                \n\t"
-        "pmullh     %[ftmp8],   %[ftmp8],       %[ftmp2]                \n\t"
-        "pmullh     %[ftmp9],   %[ftmp9],       %[ftmp2]                \n\t"
-        "paddh      %[ftmp6],   %[ftmp6],       %[ftmp8]                \n\t"
-        "paddh      %[ftmp7],   %[ftmp7],       %[ftmp9]                \n\t"
-        "paddh      %[ftmp6],   %[ftmp6],       %[ftmp10]               \n\t"
-        "paddh      %[ftmp7],   %[ftmp7],       %[ftmp11]               \n\t"
-        "paddh      %[ftmp6],   %[ftmp6],       %[ftmp2]                \n\t"
-        "paddh      %[ftmp7],   %[ftmp7],       %[ftmp2]                \n\t"
-        "psrah      %[ftmp6],   %[ftmp6],       %[ftmp1]                \n\t"
-        "psrah      %[ftmp7],   %[ftmp7],       %[ftmp1]                \n\t"
-        "packushb   %[ftmp4],   %[ftmp6],       %[ftmp7]                \n\t"
-        MMI_SDC1(%[ftmp4], %[src], 0x00)
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          [ftmp4]"=&f"(ftmp[4]),            [ftmp5]"=&f"(ftmp[5]),
-          [ftmp6]"=&f"(ftmp[6]),            [ftmp7]"=&f"(ftmp[7]),
-          [ftmp8]"=&f"(ftmp[8]),            [ftmp9]"=&f"(ftmp[9]),
-          [ftmp10]"=&f"(ftmp[10]),          [ftmp11]"=&f"(ftmp[11]),
-          [tmp0]"=&r"(tmp[0]),
-          RESTRICT_ASM_ALL64
-          [src]"=r"(src)
-        : [srcA]"r"((mips_reg)(src-stride-1)),
-          [src0]"r"((mips_reg)(src-stride)),
-          [src1]"r"((mips_reg)(src-stride+1)),
-          [has_topleft]"r"(has_topleft),    [has_topright]"r"(has_topright)
-        : "memory"
-    );
-
-    __asm__ volatile (
-        "dli        %[tmp0],    0x02                                    \n\t"
-
-        "1:                                                             \n\t"
-        MMI_SDC1(%[ftmp0], %[src], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp0], %[src], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp0], %[src], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp0], %[src], 0x00)
-
-        "daddi      %[tmp0],    %[tmp0],        -0x01                   \n\t"
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        "bnez       %[tmp0],    1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [tmp0]"=&r"(tmp[0]),
-          RESTRICT_ASM_ALL64
-          [src]"+&r"(src)
-        : [stride]"r"((mips_reg)stride)
-        : "memory"
-    );
-}
-
-void ff_pred4x4_dc_8_mmi(uint8_t *src, const uint8_t *topright,
-        ptrdiff_t stride)
-{
-    const int dc = (src[-stride] + src[1-stride] + src[2-stride]
-                 + src[3-stride] + src[-1+0*stride] + src[-1+1*stride]
-                 + src[-1+2*stride] + src[-1+3*stride] + 4) >>3;
-    uint64_t tmp[2];
-    mips_reg addr[1];
-    DECLARE_VAR_ADDRT;
-
-    __asm__ volatile (
-        PTR_ADDU   "%[tmp0],    %[dc],          $0                      \n\t"
-        "dmul       %[tmp1],    %[tmp0],        %[ff_pb_1]              \n\t"
-        "xor        %[addr0],   %[addr0],       %[addr0]                \n\t"
-        MMI_SWX(%[tmp1], %[src], %[addr0], 0x00)
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        MMI_SWX(%[tmp1], %[src], %[addr0], 0x00)
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        MMI_SWX(%[tmp1], %[src], %[addr0], 0x00)
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        MMI_SWX(%[tmp1], %[src], %[addr0], 0x00)
-        : [tmp0]"=&r"(tmp[0]),              [tmp1]"=&r"(tmp[1]),
-          RESTRICT_ASM_ADDRT
-          [addr0]"=&r"(addr[0])
-        : [src]"r"((mips_reg)src),          [stride]"r"((mips_reg)stride),
-          [dc]"r"(dc),                      [ff_pb_1]"r"(ff_pb_1)
-        : "memory"
-    );
-}
-
-void ff_pred8x8_vertical_8_mmi(uint8_t *src, ptrdiff_t stride)
-{
-    uint64_t tmp[2];
-    mips_reg addr[2];
-
-    __asm__ volatile (
-        PTR_SUBU   "%[addr0],   %[src],         %[stride]               \n\t"
-        PTR_ADDU   "%[addr1],   %[src],         $0                      \n\t"
-        "ldl        %[tmp0],    0x07(%[addr0])                          \n\t"
-        "ldr        %[tmp0],    0x00(%[addr0])                          \n\t"
-        "dli        %[tmp1],    0x04                                    \n\t"
-        "1:                                                             \n\t"
-        "sdl        %[tmp0],    0x07(%[addr1])                          \n\t"
-        "sdr        %[tmp0],    0x00(%[addr1])                          \n\t"
-        PTR_ADDU   "%[addr1],   %[stride]                               \n\t"
-        "sdl        %[tmp0],    0x07(%[addr1])                          \n\t"
-        "sdr        %[tmp0],    0x00(%[addr1])                          \n\t"
-        "daddi      %[tmp1],    -0x01                                   \n\t"
-        PTR_ADDU   "%[addr1],   %[stride]                               \n\t"
-        "bnez       %[tmp1],    1b                                      \n\t"
-        : [tmp0]"=&r"(tmp[0]),              [tmp1]"=&r"(tmp[1]),
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1])
-        : [src]"r"((mips_reg)src),          [stride]"r"((mips_reg)stride)
-        : "memory"
-    );
-}
-
-void ff_pred8x8_horizontal_8_mmi(uint8_t *src, ptrdiff_t stride)
-{
-    uint64_t tmp[3];
-    mips_reg addr[2];
-
-    __asm__ volatile (
-        PTR_ADDI   "%[addr0],   %[src],         -0x01                   \n\t"
-        PTR_ADDU   "%[addr1],   %[src],         $0                      \n\t"
-        "dli        %[tmp0],    0x04                                    \n\t"
-        "1:                                                             \n\t"
-        "lbu        %[tmp1],    0x00(%[addr0])                          \n\t"
-        "dmul       %[tmp2],    %[tmp1],        %[ff_pb_1]              \n\t"
-        "swl        %[tmp2],    0x07(%[addr1])                          \n\t"
-        "swr        %[tmp2],    0x00(%[addr1])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        PTR_ADDU   "%[addr1],   %[addr1],       %[stride]               \n\t"
-        "lbu        %[tmp1],    0x00(%[addr0])                          \n\t"
-        "dmul       %[tmp2],    %[tmp1],        %[ff_pb_1]              \n\t"
-        "swl        %[tmp2],    0x07(%[addr1])                          \n\t"
-        "swr        %[tmp2],    0x00(%[addr1])                          \n\t"
-        "daddi      %[tmp0],    %[tmp0],        -0x01                   \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        PTR_ADDU   "%[addr1],   %[addr1],       %[stride]               \n\t"
-        "bnez       %[tmp0],    1b                                      \n\t"
-        : [tmp0]"=&r"(tmp[0]),              [tmp1]"=&r"(tmp[1]),
-          [tmp2]"=&r"(tmp[2]),
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1])
-        : [src]"r"((mips_reg)src),          [stride]"r"((mips_reg)stride),
-          [ff_pb_1]"r"(ff_pb_1)
-        : "memory"
-    );
-}
-
-void ff_pred8x8_top_dc_8_mmi(uint8_t *src, ptrdiff_t stride)
-{
-    double ftmp[4];
-    uint64_t tmp[1];
-    mips_reg addr[1];
-    DECLARE_VAR_ALL64;
-
-    __asm__ volatile (
-        "dli        %[tmp0],    0x02                                    \n\t"
-        "pxor       %[ftmp0],   %[ftmp0],       %[ftmp0]                \n\t"
-        PTR_SUBU   "%[addr0],   %[src],         %[stride]               \n\t"
-        MMI_LDC1(%[ftmp1], %[addr0], 0x00)
-        "punpcklbh  %[ftmp2],   %[ftmp1],       %[ftmp0]                \n\t"
-        "punpckhbh  %[ftmp3],   %[ftmp1],       %[ftmp0]                \n\t"
-        "biadd      %[ftmp2],   %[ftmp2]                                \n\t"
-        "biadd      %[ftmp3],   %[ftmp3]                                \n\t"
-        "mtc1       %[tmp0],    %[ftmp1]                                \n\t"
-        "pshufh     %[ftmp2],   %[ftmp2],       %[ftmp0]                \n\t"
-        "pshufh     %[ftmp3],   %[ftmp3],       %[ftmp0]                \n\t"
-        "pshufh     %[ftmp1],   %[ftmp1],       %[ftmp0]                \n\t"
-        "paddush    %[ftmp2],   %[ftmp2],       %[ftmp1]                \n\t"
-        "paddush    %[ftmp3],   %[ftmp3],       %[ftmp1]                \n\t"
-        "mtc1       %[tmp0],    %[ftmp1]                                \n\t"
-        "psrlh      %[ftmp2],   %[ftmp2],       %[ftmp1]                \n\t"
-        "psrlh      %[ftmp3],   %[ftmp3],       %[ftmp1]                \n\t"
-        "packushb   %[ftmp1],   %[ftmp2],       %[ftmp3]                \n\t"
-        MMI_SDC1(%[ftmp1], %[src], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp1], %[src], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp1], %[src], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp1], %[src], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp1], %[src], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp1], %[src], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp1], %[src], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp1], %[src], 0x00)
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          [tmp0]"=&r"(tmp[0]),
-          RESTRICT_ASM_ALL64
-          [addr0]"=&r"(addr[0]),
-          [src]"+&r"(src)
-        : [stride]"r"((mips_reg)stride)
-        : "memory"
-    );
-}
-
-void ff_pred8x8_dc_8_mmi(uint8_t *src, ptrdiff_t stride)
-{
-    double ftmp[5];
-    mips_reg addr[7];
-
-    __asm__ volatile (
-        "negu       %[addr0],   %[stride]                               \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[src]                  \n\t"
-        PTR_ADDIU  "%[addr1],   %[addr0],       0x04                    \n\t"
-        "lbu        %[addr2],   0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr3],   $0,             %[addr2]                \n\t"
-        PTR_ADDIU  "%[addr0],   0x01                                    \n\t"
-        "lbu        %[addr2],   0x00(%[addr1])                          \n\t"
-        PTR_ADDU   "%[addr4],   $0,             %[addr2]                \n\t"
-        PTR_ADDIU  "%[addr1],   0x01                                    \n\t"
-        "lbu        %[addr2],   0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr3],   %[addr3],       %[addr2]                \n\t"
-        PTR_ADDIU  "%[addr0],   0x01                                    \n\t"
-        "lbu        %[addr2],   0x00(%[addr1])                          \n\t"
-        PTR_ADDU   "%[addr4],   %[addr4],       %[addr2]                \n\t"
-        PTR_ADDIU  "%[addr1],   0x01                                    \n\t"
-        "lbu        %[addr2],   0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr3],   %[addr3],       %[addr2]                \n\t"
-        PTR_ADDIU  "%[addr0],   0x01                                    \n\t"
-        "lbu        %[addr2],   0x00(%[addr1])                          \n\t"
-        PTR_ADDU   "%[addr4],   %[addr4],       %[addr2]                \n\t"
-        PTR_ADDIU  "%[addr1],   0x01                                    \n\t"
-        "lbu        %[addr2],   0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr3],   %[addr3],       %[addr2]                \n\t"
-        PTR_ADDIU  "%[addr0],   0x01                                    \n\t"
-        "lbu        %[addr2],   0x00(%[addr1])                          \n\t"
-        PTR_ADDU   "%[addr4],   %[addr4],       %[addr2]                \n\t"
-        PTR_ADDIU  "%[addr1],   0x01                                    \n\t"
-        "dli        %[addr2],  -0x01                                    \n\t"
-        PTR_ADDU   "%[addr2],   %[addr2],       %[src]                  \n\t"
-        "lbu        %[addr1],   0x00(%[addr2])                          \n\t"
-        PTR_ADDU   "%[addr5],   $0,             %[addr1]                \n\t"
-        PTR_ADDU   "%[addr2],   %[addr2],       %[stride]               \n\t"
-        "lbu        %[addr1],   0x00(%[addr2])                          \n\t"
-        PTR_ADDU   "%[addr5],   %[addr5],       %[addr1]                \n\t"
-        PTR_ADDU   "%[addr2],   %[addr2],       %[stride]               \n\t"
-        "lbu        %[addr1],   0x00(%[addr2])                          \n\t"
-        PTR_ADDU   "%[addr5],   %[addr5],       %[addr1]                \n\t"
-        PTR_ADDU   "%[addr2],   %[addr2],       %[stride]               \n\t"
-        "lbu        %[addr1],   0x00(%[addr2])                          \n\t"
-        PTR_ADDU   "%[addr5],   %[addr5],       %[addr1]                \n\t"
-        PTR_ADDU   "%[addr2],   %[addr2],       %[stride]               \n\t"
-        "lbu        %[addr1],   0x00(%[addr2])                          \n\t"
-        PTR_ADDU   "%[addr6],   $0,             %[addr1]                \n\t"
-        PTR_ADDU   "%[addr2],   %[addr2],       %[stride]               \n\t"
-        "lbu        %[addr1],   0x00(%[addr2])                          \n\t"
-        PTR_ADDU   "%[addr6],   %[addr6],       %[addr1]                \n\t"
-        PTR_ADDU   "%[addr2],   %[addr2],       %[stride]               \n\t"
-        "lbu        %[addr1],   0x00(%[addr2])                          \n\t"
-        PTR_ADDU   "%[addr6],   %[addr6],       %[addr1]                \n\t"
-        PTR_ADDU   "%[addr2],   %[addr2],       %[stride]               \n\t"
-        "lbu        %[addr1],   0x00(%[addr2])                          \n\t"
-        PTR_ADDU   "%[addr6],   %[addr6],       %[addr1]                \n\t"
-        PTR_ADDU   "%[addr3],   %[addr3],       %[addr5]                \n\t"
-        PTR_ADDIU  "%[addr3],   %[addr3],       0x04                    \n\t"
-        PTR_ADDIU  "%[addr4],   %[addr4],       0x02                    \n\t"
-        PTR_ADDIU  "%[addr1],   %[addr6],       0x02                    \n\t"
-        PTR_ADDU   "%[addr2],   %[addr4],       %[addr1]                \n\t"
-        PTR_SRL    "%[addr3],   0x03                                    \n\t"
-        PTR_SRL    "%[addr4],   0x02                                    \n\t"
-        PTR_SRL    "%[addr1],   0x02                                    \n\t"
-        PTR_SRL    "%[addr2],   0x03                                    \n\t"
-        "pxor       %[ftmp0],   %[ftmp0],       %[ftmp0]                \n\t"
-        "dmtc1      %[addr3],   %[ftmp1]                                \n\t"
-        "pshufh     %[ftmp1],   %[ftmp1],       %[ftmp0]                \n\t"
-        "dmtc1      %[addr4],   %[ftmp2]                                \n\t"
-        "pshufh     %[ftmp2],   %[ftmp2],       %[ftmp0]                \n\t"
-        "dmtc1      %[addr1],   %[ftmp3]                                \n\t"
-        "pshufh     %[ftmp3],   %[ftmp3],       %[ftmp0]                \n\t"
-        "dmtc1      %[addr2],   %[ftmp4]                                \n\t"
-        "pshufh     %[ftmp4],   %[ftmp4],       %[ftmp0]                \n\t"
-        "packushb   %[ftmp1],   %[ftmp1],       %[ftmp2]                \n\t"
-        "packushb   %[ftmp2],   %[ftmp3],       %[ftmp4]                \n\t"
-        PTR_ADDU   "%[addr0],   $0,             %[src]                  \n\t"
-        MMI_SDC1(%[ftmp1], %[addr0], 0x00)
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        MMI_SDC1(%[ftmp1], %[addr0], 0x00)
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        MMI_SDC1(%[ftmp1], %[addr0], 0x00)
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        MMI_SDC1(%[ftmp1], %[addr0], 0x00)
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        MMI_SDC1(%[ftmp2], %[addr0], 0x00)
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        MMI_SDC1(%[ftmp2], %[addr0], 0x00)
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        MMI_SDC1(%[ftmp2], %[addr0], 0x00)
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        MMI_SDC1(%[ftmp2], %[addr0], 0x00)
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          [ftmp4]"=&f"(ftmp[4]),
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1]),
-          [addr2]"=&r"(addr[2]),            [addr3]"=&r"(addr[3]),
-          [addr4]"=&r"(addr[4]),            [addr5]"=&r"(addr[5]),
-          [addr6]"=&r"(addr[6])
-        : [src]"r"((mips_reg)src),          [stride]"r"((mips_reg)stride)
-        : "memory"
-    );
-}
-
-void ff_pred8x16_vertical_8_mmi(uint8_t *src, ptrdiff_t stride)
-{
-    double ftmp[1];
-    uint64_t tmp[1];
-    DECLARE_VAR_ALL64;
-
-    __asm__ volatile (
-        MMI_LDC1(%[ftmp0], %[srcA], 0x00)
-        "dli        %[tmp0],    0x04                                    \n\t"
-
-        "1:                                                             \n\t"
-        MMI_SDC1(%[ftmp0], %[src], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp0], %[src], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp0], %[src], 0x00)
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        MMI_SDC1(%[ftmp0], %[src], 0x00)
-
-        "daddi      %[tmp0],    %[tmp0],        -0x01                   \n\t"
-        PTR_ADDU   "%[src],     %[src],         %[stride]               \n\t"
-        "bnez       %[tmp0],    1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),
-          [tmp0]"=&r"(tmp[0]),
-          RESTRICT_ASM_ALL64
-          [src]"+&r"(src)
-        : [stride]"r"((mips_reg)stride),    [srcA]"r"((mips_reg)(src-stride))
-        : "memory"
-    );
-}
-
-void ff_pred8x16_horizontal_8_mmi(uint8_t *src, ptrdiff_t stride)
-{
-    uint64_t tmp[3];
-    mips_reg addr[2];
-
-    __asm__ volatile (
-        PTR_ADDI   "%[addr0],   %[src],         -0x01                   \n\t"
-        PTR_ADDU   "%[addr1],   %[src],         $0                      \n\t"
-        "dli        %[tmp0],    0x08                                    \n\t"
-        "1:                                                             \n\t"
-        "lbu        %[tmp1],    0x00(%[addr0])                          \n\t"
-        "dmul       %[tmp2],    %[tmp1],        %[ff_pb_1]              \n\t"
-        "swl        %[tmp2],    0x07(%[addr1])                          \n\t"
-        "swr        %[tmp2],    0x00(%[addr1])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        PTR_ADDU   "%[addr1],   %[addr1],       %[stride]               \n\t"
-        "lbu        %[tmp1],    0x00(%[addr0])                          \n\t"
-        "dmul       %[tmp2],    %[tmp1],        %[ff_pb_1]              \n\t"
-        "swl        %[tmp2],    0x07(%[addr1])                          \n\t"
-        "swr        %[tmp2],    0x00(%[addr1])                          \n\t"
-        "daddi      %[tmp0],    %[tmp0],        -0x01                   \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        PTR_ADDU   "%[addr1],   %[addr1],       %[stride]               \n\t"
-        "bnez       %[tmp0],    1b                                      \n\t"
-        : [tmp0]"=&r"(tmp[0]),              [tmp1]"=&r"(tmp[1]),
-          [tmp2]"=&r"(tmp[2]),
-          [addr0]"=&r"(addr[0]),            [addr1]"=&r"(addr[1])
-        : [src]"r"((mips_reg)src),          [stride]"r"((mips_reg)stride),
-          [ff_pb_1]"r"(ff_pb_1)
-        : "memory"
-    );
-}
-
-static inline void pred16x16_plane_compat_mmi(uint8_t *src, int stride,
-        const int svq3, const int rv40)
-{
-    double ftmp[11];
-    uint64_t tmp[6];
-    mips_reg addr[1];
-    DECLARE_VAR_ALL64;
-
-    __asm__ volatile(
-        PTR_SUBU   "%[addr0],   %[src],         %[stride]               \n\t"
-        "dli        %[tmp0],    0x20                                    \n\t"
-        "dmtc1      %[tmp0],    %[ftmp4]                                \n\t"
-        MMI_ULDC1(%[ftmp0], %[addr0], -0x01)
-        MMI_ULDC1(%[ftmp2], %[addr0],  0x08)
-        "ssrld      %[ftmp1],   %[ftmp0],       %[ftmp4]                \n\t"
-        "ssrld      %[ftmp3],   %[ftmp2],       %[ftmp4]                \n\t"
-        "pxor       %[ftmp4],   %[ftmp4],       %[ftmp4]                \n\t"
-        "punpcklbh  %[ftmp0],   %[ftmp0],       %[ftmp4]                \n\t"
-        "punpcklbh  %[ftmp1],   %[ftmp1],       %[ftmp4]                \n\t"
-        "punpcklbh  %[ftmp2],   %[ftmp2],       %[ftmp4]                \n\t"
-        "punpcklbh  %[ftmp3],   %[ftmp3],       %[ftmp4]                \n\t"
-        "pmullh     %[ftmp0],   %[ftmp0],       %[ff_pw_m8tom5]         \n\t"
-        "pmullh     %[ftmp1],   %[ftmp1],       %[ff_pw_m4tom1]         \n\t"
-        "pmullh     %[ftmp2],   %[ftmp2],       %[ff_pw_1to4]           \n\t"
-        "pmullh     %[ftmp3],   %[ftmp3],       %[ff_pw_5to8]           \n\t"
-        "paddsh     %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "paddsh     %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        "paddsh     %[ftmp0],   %[ftmp0],       %[ftmp1]                \n\t"
-        "dli        %[tmp0],    0x0e                                    \n\t"
-        "dmtc1      %[tmp0],    %[ftmp4]                                \n\t"
-        "pshufh     %[ftmp1],   %[ftmp0],       %[ftmp4]                \n\t"
-        "paddsh     %[ftmp0],   %[ftmp0],       %[ftmp1]                \n\t"
-        "dli        %[tmp0],    0x01                                    \n\t"
-        "dmtc1      %[tmp0],    %[ftmp4]                                \n\t"
-        "pshufh     %[ftmp1],   %[ftmp0],       %[ftmp4]                \n\t"
-        "paddsh     %[ftmp5],   %[ftmp0],       %[ftmp1]                \n\t"
-
-        PTR_ADDIU  "%[addr0],   %[src],         -0x01                   \n\t"
-        PTR_SUBU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp2],    0x00(%[addr0])                          \n\t"
-        "lbu        %[tmp5],    0x10(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp3],    0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp4],    0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp0],    0x00(%[addr0])                          \n\t"
-        "dsll       %[tmp3],    %[tmp3],        0x10                    \n\t"
-        "dsll       %[tmp4],    %[tmp4],        0x20                    \n\t"
-        "dsll       %[tmp0],    %[tmp0],        0x30                    \n\t"
-        "or         %[tmp4],    %[tmp4],        %[tmp0]                 \n\t"
-        "or         %[tmp2],    %[tmp2],        %[tmp3]                 \n\t"
-        "or         %[tmp2],    %[tmp2],        %[tmp4]                 \n\t"
-        "dmtc1      %[tmp2],    %[ftmp0]                                \n\t"
-
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp2],    0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp3],    0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp4],    0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp0],    0x00(%[addr0])                          \n\t"
-        "dsll       %[tmp3],    %[tmp3],        0x10                    \n\t"
-        "dsll       %[tmp4],    %[tmp4],        0x20                    \n\t"
-        "dsll       %[tmp0],    %[tmp0],        0x30                    \n\t"
-        "or         %[tmp4],    %[tmp4],        %[tmp0]                 \n\t"
-        "or         %[tmp2],    %[tmp2],        %[tmp3]                 \n\t"
-        "or         %[tmp2],    %[tmp2],        %[tmp4]                 \n\t"
-        "dmtc1      %[tmp2],    %[ftmp1]                                \n\t"
-
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp2],    0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp3],    0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp4],    0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp0],    0x00(%[addr0])                          \n\t"
-        "dsll       %[tmp3],    %[tmp3],        0x10                    \n\t"
-        "dsll       %[tmp4],    %[tmp4],        0x20                    \n\t"
-        "dsll       %[tmp0],    %[tmp0],        0x30                    \n\t"
-        "or         %[tmp4],    %[tmp4],        %[tmp0]                 \n\t"
-        "or         %[tmp2],    %[tmp2],        %[tmp3]                 \n\t"
-        "or         %[tmp2],    %[tmp2],        %[tmp4]                 \n\t"
-        "dmtc1      %[tmp2],    %[ftmp2]                                \n\t"
-
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp2],    0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp3],    0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp4],    0x00(%[addr0])                          \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "lbu        %[tmp0],    0x00(%[addr0])                          \n\t"
-        "daddu      %[tmp5],    %[tmp5],        %[tmp0]                 \n\t"
-        "daddiu     %[tmp5],    %[tmp5],        0x01                    \n\t"
-        "dsll       %[tmp5],    %[tmp5],        0x04                    \n\t"
-
-        "dsll       %[tmp3],    %[tmp3],        0x10                    \n\t"
-        "dsll       %[tmp4],    %[tmp4],        0x20                    \n\t"
-        "dsll       %[tmp0],    %[tmp0],        0x30                    \n\t"
-        "or         %[tmp4],    %[tmp4],        %[tmp0]                 \n\t"
-        "or         %[tmp2],    %[tmp2],        %[tmp3]                 \n\t"
-        "or         %[tmp2],    %[tmp2],        %[tmp4]                 \n\t"
-        "dmtc1      %[tmp2],    %[ftmp3]                                \n\t"
-
-        "pmullh     %[ftmp0],   %[ftmp0],       %[ff_pw_m8tom5]         \n\t"
-        "pmullh     %[ftmp1],   %[ftmp1],       %[ff_pw_m4tom1]         \n\t"
-        "pmullh     %[ftmp2],   %[ftmp2],       %[ff_pw_1to4]           \n\t"
-        "pmullh     %[ftmp3],   %[ftmp3],       %[ff_pw_5to8]           \n\t"
-        "paddsh     %[ftmp0],   %[ftmp0],       %[ftmp2]                \n\t"
-        "paddsh     %[ftmp1],   %[ftmp1],       %[ftmp3]                \n\t"
-        "paddsh     %[ftmp0],   %[ftmp0],       %[ftmp1]                \n\t"
-        "dli        %[tmp0],    0x0e                                    \n\t"
-        "dmtc1      %[tmp0],    %[ftmp4]                                \n\t"
-        "pshufh     %[ftmp1],   %[ftmp0],       %[ftmp4]                \n\t"
-        "paddsh     %[ftmp0],   %[ftmp0],       %[ftmp1]                \n\t"
-
-        "dli        %[tmp0],    0x01                                    \n\t"
-        "dmtc1      %[tmp0],    %[ftmp4]                                \n\t"
-        "pshufh     %[ftmp1],   %[ftmp0],       %[ftmp4]                \n\t"
-        "paddsh     %[ftmp6],   %[ftmp0],       %[ftmp1]                \n\t"
-
-        "dmfc1      %[tmp0],    %[ftmp5]                                \n\t"
-        "dsll       %[tmp0],    %[tmp0],        0x30                    \n\t"
-        "dsra       %[tmp0],    %[tmp0],        0x30                    \n\t"
-        "dmfc1      %[tmp1],    %[ftmp6]                                \n\t"
-        "dsll       %[tmp1],    %[tmp1],        0x30                    \n\t"
-        "dsra       %[tmp1],    %[tmp1],        0x30                    \n\t"
-
-        "beqz       %[svq3],    1f                                      \n\t"
-        "dli        %[tmp2],    0x04                                    \n\t"
-        "ddiv       %[tmp0],    %[tmp0],        %[tmp2]                 \n\t"
-        "ddiv       %[tmp1],    %[tmp1],        %[tmp2]                 \n\t"
-        "dli        %[tmp2],    0x05                                    \n\t"
-        "dmul       %[tmp0],    %[tmp0],        %[tmp2]                 \n\t"
-        "dmul       %[tmp1],    %[tmp1],        %[tmp2]                 \n\t"
-        "dli        %[tmp2],    0x10                                    \n\t"
-        "ddiv       %[tmp0],    %[tmp0],        %[tmp2]                 \n\t"
-        "ddiv       %[tmp1],    %[tmp1],        %[tmp2]                 \n\t"
-        "daddu      %[tmp2],    %[tmp0],        $0                      \n\t"
-        "daddu      %[tmp0],    %[tmp1],        $0                      \n\t"
-        "daddu      %[tmp1],    %[tmp2],        $0                      \n\t"
-        "b          2f                                                  \n\t"
-
-        "1:                                                             \n\t"
-        "beqz       %[rv40],    1f                                      \n\t"
-        "dsra       %[tmp2],    %[tmp0],        0x02                    \n\t"
-        "daddu      %[tmp0],    %[tmp0],        %[tmp2]                 \n\t"
-        "dsra       %[tmp2],    %[tmp1],        0x02                    \n\t"
-        "daddu      %[tmp1],    %[tmp1],        %[tmp2]                 \n\t"
-        "dsra       %[tmp0],    %[tmp0],        0x04                    \n\t"
-        "dsra       %[tmp1],    %[tmp1],        0x04                    \n\t"
-        "b          2f                                                  \n\t"
-
-        "1:                                                             \n\t"
-        "dli        %[tmp2],    0x05                                    \n\t"
-        "dmul       %[tmp0],    %[tmp0],        %[tmp2]                 \n\t"
-        "dmul       %[tmp1],    %[tmp1],        %[tmp2]                 \n\t"
-        "daddiu     %[tmp0],    %[tmp0],        0x20                    \n\t"
-        "daddiu     %[tmp1],    %[tmp1],        0x20                    \n\t"
-        "dsra       %[tmp0],    %[tmp0],        0x06                    \n\t"
-        "dsra       %[tmp1],    %[tmp1],        0x06                    \n\t"
-
-        "2:                                                             \n\t"
-        "daddu      %[tmp3],    %[tmp0],        %[tmp1]                 \n\t"
-        "dli        %[tmp2],    0x07                                    \n\t"
-        "dmul       %[tmp3],    %[tmp3],        %[tmp2]                 \n\t"
-        "dsubu      %[tmp5],    %[tmp5],        %[tmp3]                 \n\t"
-
-        "pxor       %[ftmp4],   %[ftmp4],       %[ftmp4]                \n\t"
-        "dmtc1      %[tmp0],    %[ftmp0]                                \n\t"
-        "pshufh     %[ftmp0],   %[ftmp0],       %[ftmp4]                \n\t"
-        "dmtc1      %[tmp1],    %[ftmp5]                                \n\t"
-        "pshufh     %[ftmp5],   %[ftmp5],       %[ftmp4]                \n\t"
-        "dmtc1      %[tmp5],    %[ftmp6]                                \n\t"
-        "pshufh     %[ftmp6],   %[ftmp6],       %[ftmp4]                \n\t"
-        "dli        %[tmp0],    0x05                                    \n\t"
-        "dmtc1      %[tmp0],    %[ftmp7]                                \n\t"
-        "pmullh     %[ftmp1],   %[ff_pw_0to3],  %[ftmp0]                \n\t"
-        "dmtc1      %[ff_pw_4to7],              %[ftmp2]                \n\t"
-        "pmullh     %[ftmp2],   %[ftmp2],       %[ftmp0]                \n\t"
-        "dmtc1      %[ff_pw_8tob],              %[ftmp3]                \n\t"
-        "pmullh     %[ftmp3],   %[ftmp3],       %[ftmp0]                \n\t"
-        "dmtc1      %[ff_pw_ctof],              %[ftmp4]                \n\t"
-        "pmullh     %[ftmp4],   %[ftmp4],       %[ftmp0]                \n\t"
-
-        "dli        %[tmp0],    0x10                                    \n\t"
-        PTR_ADDU   "%[addr0],   %[src],         $0                      \n\t"
-        "1:                                                             \n\t"
-        "paddsh     %[ftmp8],   %[ftmp1],       %[ftmp6]                \n\t"
-        "psrah      %[ftmp8],   %[ftmp8],       %[ftmp7]                \n\t"
-        "paddsh     %[ftmp9],   %[ftmp2],       %[ftmp6]                \n\t"
-        "psrah      %[ftmp9],   %[ftmp9],       %[ftmp7]                \n\t"
-        "packushb   %[ftmp0],   %[ftmp8],       %[ftmp9]                \n\t"
-        MMI_SDC1(%[ftmp0], %[addr0], 0x00)
-
-        "paddsh     %[ftmp8],   %[ftmp3],       %[ftmp6]                \n\t"
-        "psrah      %[ftmp8],   %[ftmp8],       %[ftmp7]                \n\t"
-        "paddsh     %[ftmp9],   %[ftmp4],       %[ftmp6]                \n\t"
-        "psrah      %[ftmp9],   %[ftmp9],       %[ftmp7]                \n\t"
-        "packushb   %[ftmp0],   %[ftmp8],       %[ftmp9]                \n\t"
-        MMI_SDC1(%[ftmp0], %[addr0], 0x08)
-
-        "paddsh     %[ftmp6],   %[ftmp6],       %[ftmp5]                \n\t"
-        PTR_ADDU   "%[addr0],   %[addr0],       %[stride]               \n\t"
-        "daddiu     %[tmp0],    %[tmp0],        -0x01                   \n\t"
-        "bnez       %[tmp0],    1b                                      \n\t"
-        : [ftmp0]"=&f"(ftmp[0]),            [ftmp1]"=&f"(ftmp[1]),
-          [ftmp2]"=&f"(ftmp[2]),            [ftmp3]"=&f"(ftmp[3]),
-          [ftmp4]"=&f"(ftmp[4]),            [ftmp5]"=&f"(ftmp[5]),
-          [ftmp6]"=&f"(ftmp[6]),            [ftmp7]"=&f"(ftmp[7]),
-          [ftmp8]"=&f"(ftmp[8]),            [ftmp9]"=&f"(ftmp[9]),
-          [tmp0]"=&r"(tmp[0]),              [tmp1]"=&r"(tmp[1]),
-          [tmp2]"=&r"(tmp[2]),              [tmp3]"=&r"(tmp[3]),
-          [tmp4]"=&r"(tmp[4]),              [tmp5]"=&r"(tmp[5]),
-          RESTRICT_ASM_ALL64
-          [addr0]"=&r"(addr[0])
-        : [src]"r"(src),                    [stride]"r"((mips_reg)stride),
-          [svq3]"r"(svq3),                  [rv40]"r"(rv40),
-          [ff_pw_m8tom5]"f"(ff_pw_m8tom5.f),[ff_pw_m4tom1]"f"(ff_pw_m4tom1.f),
-          [ff_pw_1to4]"f"(ff_pw_1to4.f),    [ff_pw_5to8]"f"(ff_pw_5to8.f),
-          [ff_pw_0to3]"f"(ff_pw_0to3.f),    [ff_pw_4to7]"r"(ff_pw_4to7.i),
-          [ff_pw_8tob]"r"(ff_pw_8tob.i),    [ff_pw_ctof]"r"(ff_pw_ctof.i)
-        : "memory"
-    );
-}
-
-void ff_pred16x16_plane_h264_8_mmi(uint8_t *src, ptrdiff_t stride)
-{
-    pred16x16_plane_compat_mmi(src, stride, 0, 0);
-}
-
-void ff_pred16x16_plane_svq3_8_mmi(uint8_t *src, ptrdiff_t stride)
-{
-    pred16x16_plane_compat_mmi(src, stride, 1, 0);
-}
-
-void ff_pred16x16_plane_rv40_8_mmi(uint8_t *src, ptrdiff_t stride)
-{
-    pred16x16_plane_compat_mmi(src, stride, 0, 1);
-}
diff --git a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/mips/vc1dsp_msa.c b/spaces/colakin/video-generater/public/ffmpeg/libavcodec/mips/vc1dsp_msa.c
deleted file mode 100644
index 6e588e825af59ef3ed0c0a05c7320f67a3c00dd1..0000000000000000000000000000000000000000
--- a/spaces/colakin/video-generater/public/ffmpeg/libavcodec/mips/vc1dsp_msa.c
+++ /dev/null
@@ -1,461 +0,0 @@
-/*
- * Loongson SIMD optimized vc1dsp
- *
- * Copyright (c) 2019 Loongson Technology Corporation Limited
- *                    gxw <guxiwei-hf@loongson.cn>
- *
- * This file is part of FFmpeg.
- *
- * FFmpeg is free software; you can redistribute it and/or
- * modify it under the terms of the GNU Lesser General Public
- * License as published by the Free Software Foundation; either
- * version 2.1 of the License, or (at your option) any later version.
- *
- * FFmpeg is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
- * Lesser General Public License for more details.
- *
- * You should have received a copy of the GNU Lesser General Public
- * License along with FFmpeg; if not, write to the Free Software
- * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
- */
-
-#include "vc1dsp_mips.h"
-#include "constants.h"
-#include "libavutil/mips/generic_macros_msa.h"
-
-void ff_vc1_inv_trans_8x8_msa(int16_t block[64])
-{
-    v8i16 in0, in1, in2, in3, in4, in5, in6, in7;
-    v4i32 in_r0, in_r1, in_r2, in_r3, in_r4, in_r5, in_r6, in_r7;
-    v4i32 in_l0, in_l1, in_l2, in_l3, in_l4, in_l5, in_l6, in_l7;
-    v4i32 t_r1, t_r2, t_r3, t_r4, t_r5, t_r6, t_r7, t_r8;
-    v4i32 t_l1, t_l2, t_l3, t_l4, t_l5, t_l6, t_l7, t_l8;
-    v4i32 cnst_12 = {12, 12, 12, 12};
-    v4i32 cnst_4 = {4, 4, 4, 4};
-    v4i32 cnst_16 = {16, 16, 16, 16};
-    v4i32 cnst_6 = {6, 6, 6, 6};
-    v4i32 cnst_15 = {15, 15, 15, 15};
-    v4i32 cnst_9 = {9, 9, 9, 9};
-    v4i32 cnst_1 = {1, 1, 1, 1};
-    v4i32 cnst_64 = {64, 64, 64, 64};
-
-    LD_SH8(block, 8, in0, in1, in2, in3, in4, in5, in6, in7);
-    UNPCK_SH_SW(in0, in_r0, in_l0);
-    UNPCK_SH_SW(in1, in_r1, in_l1);
-    UNPCK_SH_SW(in2, in_r2, in_l2);
-    UNPCK_SH_SW(in3, in_r3, in_l3);
-    UNPCK_SH_SW(in4, in_r4, in_l4);
-    UNPCK_SH_SW(in5, in_r5, in_l5);
-    UNPCK_SH_SW(in6, in_r6, in_l6);
-    UNPCK_SH_SW(in7, in_r7, in_l7);
-    // First loop
-    t_r1 = cnst_12 * (in_r0 + in_r4) + cnst_4;
-    t_l1 = cnst_12 * (in_l0 + in_l4) + cnst_4;
-    t_r2 = cnst_12 * (in_r0 - in_r4) + cnst_4;
-    t_l2 = cnst_12 * (in_l0 - in_l4) + cnst_4;
-    t_r3 = cnst_16 * in_r2 + cnst_6 * in_r6;
-    t_l3 = cnst_16 * in_l2 + cnst_6 * in_l6;
-    t_r4 = cnst_6 * in_r2 - cnst_16 * in_r6;
-    t_l4 = cnst_6 * in_l2 - cnst_16 * in_l6;
-
-    ADD4(t_r1, t_r3, t_l1, t_l3, t_r2, t_r4, t_l2, t_l4, t_r5, t_l5, t_r6, t_l6);
-    SUB4(t_r2, t_r4, t_l2, t_l4, t_r1, t_r3, t_l1, t_l3, t_r7, t_l7, t_r8, t_l8);
-    t_r1 = cnst_16 * in_r1 + cnst_15 * in_r3 + cnst_9 * in_r5 + cnst_4 * in_r7;
-    t_l1 = cnst_16 * in_l1 + cnst_15 * in_l3 + cnst_9 * in_l5 + cnst_4 * in_l7;
-    t_r2 = cnst_15 * in_r1 - cnst_4 * in_r3 - cnst_16 * in_r5 - cnst_9 * in_r7;
-    t_l2 = cnst_15 * in_l1 - cnst_4 * in_l3 - cnst_16 * in_l5 - cnst_9 * in_l7;
-    t_r3 = cnst_9 * in_r1 - cnst_16 * in_r3 + cnst_4 * in_r5 + cnst_15 * in_r7;
-    t_l3 = cnst_9 * in_l1 - cnst_16 * in_l3 + cnst_4 * in_l5 + cnst_15 * in_l7;
-    t_r4 = cnst_4 * in_r1 - cnst_9 * in_r3 + cnst_15 * in_r5 - cnst_16 * in_r7;
-    t_l4 = cnst_4 * in_l1 - cnst_9 * in_l3 + cnst_15 * in_l5 - cnst_16 * in_l7;
-
-    in_r0 = (t_r5 + t_r1) >> 3;
-    in_l0 = (t_l5 + t_l1) >> 3;
-    in_r1 = (t_r6 + t_r2) >> 3;
-    in_l1 = (t_l6 + t_l2) >> 3;
-    in_r2 = (t_r7 + t_r3) >> 3;
-    in_l2 = (t_l7 + t_l3) >> 3;
-    in_r3 = (t_r8 + t_r4) >> 3;
-    in_l3 = (t_l8 + t_l4) >> 3;
-
-    in_r4 = (t_r8 - t_r4) >> 3;
-    in_l4 = (t_l8 - t_l4) >> 3;
-    in_r5 = (t_r7 - t_r3) >> 3;
-    in_l5 = (t_l7 - t_l3) >> 3;
-    in_r6 = (t_r6 - t_r2) >> 3;
-    in_l6 = (t_l6 - t_l2) >> 3;
-    in_r7 = (t_r5 - t_r1) >> 3;
-    in_l7 = (t_l5 - t_l1) >> 3;
-    TRANSPOSE4x4_SW_SW(in_r0, in_r1, in_r2, in_r3, in_r0, in_r1, in_r2, in_r3);
-    TRANSPOSE4x4_SW_SW(in_l0, in_l1, in_l2, in_l3, in_l0, in_l1, in_l2, in_l3);
-    TRANSPOSE4x4_SW_SW(in_r4, in_r5, in_r6, in_r7, in_r4, in_r5, in_r6, in_r7);
-    TRANSPOSE4x4_SW_SW(in_l4, in_l5, in_l6, in_l7, in_l4, in_l5, in_l6, in_l7);
-    // Second loop
-    t_r1 = cnst_12 * (in_r0 + in_l0) + cnst_64;
-    t_l1 = cnst_12 * (in_r4 + in_l4) + cnst_64;
-    t_r2 = cnst_12 * (in_r0 - in_l0) + cnst_64;
-    t_l2 = cnst_12 * (in_r4 - in_l4) + cnst_64;
-    t_r3 = cnst_16 * in_r2 + cnst_6 * in_l2;
-    t_l3 = cnst_16 * in_r6 + cnst_6 * in_l6;
-    t_r4 = cnst_6 * in_r2 - cnst_16 * in_l2;
-    t_l4 = cnst_6 * in_r6 - cnst_16 * in_l6;
-
-    ADD4(t_r1, t_r3, t_l1, t_l3, t_r2, t_r4, t_l2, t_l4, t_r5, t_l5, t_r6, t_l6);
-    SUB4(t_r2, t_r4, t_l2, t_l4, t_r1, t_r3, t_l1, t_l3, t_r7, t_l7, t_r8, t_l8);
-    t_r1 = cnst_16 * in_r1 + cnst_15 * in_r3 + cnst_9 * in_l1 + cnst_4 * in_l3;
-    t_l1 = cnst_16 * in_r5 + cnst_15 * in_r7 + cnst_9 * in_l5 + cnst_4 * in_l7;
-    t_r2 = cnst_15 * in_r1 - cnst_4 * in_r3 - cnst_16 * in_l1 - cnst_9 * in_l3;
-    t_l2 = cnst_15 * in_r5 - cnst_4 * in_r7 - cnst_16 * in_l5 - cnst_9 * in_l7;
-    t_r3 = cnst_9 * in_r1 - cnst_16 * in_r3 + cnst_4 * in_l1 + cnst_15 * in_l3;
-    t_l3 = cnst_9 * in_r5 - cnst_16 * in_r7 + cnst_4 * in_l5 + cnst_15 * in_l7;
-    t_r4 = cnst_4 * in_r1 - cnst_9 * in_r3 + cnst_15 * in_l1 - cnst_16 * in_l3;
-    t_l4 = cnst_4 * in_r5 - cnst_9 * in_r7 + cnst_15 * in_l5 - cnst_16 * in_l7;
-
-    in_r0 = (t_r5 + t_r1) >> 7;
-    in_l0 = (t_l5 + t_l1) >> 7;
-    in_r1 = (t_r6 + t_r2) >> 7;
-    in_l1 = (t_l6 + t_l2) >> 7;
-    in_r2 = (t_r7 + t_r3) >> 7;
-    in_l2 = (t_l7 + t_l3) >> 7;
-    in_r3 = (t_r8 + t_r4) >> 7;
-    in_l3 = (t_l8 + t_l4) >> 7;
-
-    in_r4 = (t_r8 - t_r4 + cnst_1) >> 7;
-    in_l4 = (t_l8 - t_l4 + cnst_1) >> 7;
-    in_r5 = (t_r7 - t_r3 + cnst_1) >> 7;
-    in_l5 = (t_l7 - t_l3 + cnst_1) >> 7;
-    in_r6 = (t_r6 - t_r2 + cnst_1) >> 7;
-    in_l6 = (t_l6 - t_l2 + cnst_1) >> 7;
-    in_r7 = (t_r5 - t_r1 + cnst_1) >> 7;
-    in_l7 = (t_l5 - t_l1 + cnst_1) >> 7;
-    PCKEV_H4_SH(in_l0, in_r0, in_l1, in_r1, in_l2, in_r2, in_l3, in_r3,
-                in0, in1, in2, in3);
-    PCKEV_H4_SH(in_l4, in_r4, in_l5, in_r5, in_l6, in_r6, in_l7, in_r7,
-                in4, in5, in6, in7);
-    ST_SH8(in0, in1, in2, in3, in4, in5, in6, in7, block, 8);
-}
-
-void ff_vc1_inv_trans_4x8_msa(uint8_t *dest, ptrdiff_t linesize, int16_t *block)
-{
-    v8i16 in0, in1, in2, in3, in4, in5, in6, in7;
-    v4i32 in_r0, in_r1, in_r2, in_r3, in_r4, in_r5, in_r6, in_r7;
-    v4i32 t1, t2, t3, t4, t5, t6, t7, t8;
-    v4i32 dst0, dst1, dst2, dst3, dst4, dst5, dst6, dst7;
-    v16i8 zero_m = { 0 };
-    v4i32 cnst_17 = {17, 17, 17, 17};
-    v4i32 cnst_22 = {22, 22, 22, 22};
-    v4i32 cnst_10 = {10, 10, 10, 10};
-    v4i32 cnst_12 = {12, 12, 12, 12};
-    v4i32 cnst_64 = {64, 64, 64, 64};
-    v4i32 cnst_16 = {16, 16, 16, 16};
-    v4i32 cnst_15 = {15, 15, 15, 15};
-    v4i32 cnst_4 = {4, 4, 4, 4};
-    v4i32 cnst_6 = {6, 6, 6, 6};
-    v4i32 cnst_9 = {9, 9, 9, 9};
-    v4i32 cnst_1 = {1, 1, 1, 1};
-
-    LD_SH8(block, 8, in0, in1, in2, in3, in4, in5, in6, in7);
-    UNPCK_R_SH_SW(in0, in_r0);
-    UNPCK_R_SH_SW(in1, in_r1);
-    UNPCK_R_SH_SW(in2, in_r2);
-    UNPCK_R_SH_SW(in3, in_r3);
-    UNPCK_R_SH_SW(in4, in_r4);
-    UNPCK_R_SH_SW(in5, in_r5);
-    UNPCK_R_SH_SW(in6, in_r6);
-    UNPCK_R_SH_SW(in7, in_r7);
-    // First loop
-    TRANSPOSE4x4_SW_SW(in_r0, in_r1, in_r2, in_r3, in_r0, in_r1, in_r2, in_r3);
-    TRANSPOSE4x4_SW_SW(in_r4, in_r5, in_r6, in_r7, in_r4, in_r5, in_r6, in_r7);
-    t1 = cnst_17 * (in_r0 + in_r2) + cnst_4;
-    t5 = cnst_17 * (in_r4 + in_r6) + cnst_4;
-    t2 = cnst_17 * (in_r0 - in_r2) + cnst_4;
-    t6 = cnst_17 * (in_r4 - in_r6) + cnst_4;
-    t3 = cnst_22 * in_r1 + cnst_10 * in_r3;
-    t7 = cnst_22 * in_r5 + cnst_10 * in_r7;
-    t4 = cnst_22 * in_r3 - cnst_10 * in_r1;
-    t8 = cnst_22 * in_r7 - cnst_10 * in_r5;
-
-    in_r0 = (t1 + t3) >> 3;
-    in_r4 = (t5 + t7) >> 3;
-    in_r1 = (t2 - t4) >> 3;
-    in_r5 = (t6 - t8) >> 3;
-    in_r2 = (t2 + t4) >> 3;
-    in_r6 = (t6 + t8) >> 3;
-    in_r3 = (t1 - t3) >> 3;
-    in_r7 = (t5 - t7) >> 3;
-    TRANSPOSE4x4_SW_SW(in_r0, in_r1, in_r2, in_r3, in_r0, in_r1, in_r2, in_r3);
-    TRANSPOSE4x4_SW_SW(in_r4, in_r5, in_r6, in_r7, in_r4, in_r5, in_r6, in_r7);
-    PCKEV_H4_SH(in_r1, in_r0, in_r3, in_r2, in_r5, in_r4, in_r7, in_r6,
-                in0, in1, in2, in3);
-    ST_D8(in0, in1, in2, in3, 0, 1, 0, 1, 0, 1, 0, 1, block, 8);
-    // Second loop
-    t1 = cnst_12 * (in_r0 + in_r4) + cnst_64;
-    t2 = cnst_12 * (in_r0 - in_r4) + cnst_64;
-    t3 = cnst_16 * in_r2 + cnst_6 * in_r6;
-    t4 = cnst_6 * in_r2 - cnst_16 * in_r6;
-    t5 = t1 + t3, t6 = t2 + t4;
-    t7 = t2 - t4, t8 = t1 - t3;
-    t1 = cnst_16 * in_r1 + cnst_15 * in_r3 + cnst_9 * in_r5 + cnst_4 * in_r7;
-    t2 = cnst_15 * in_r1 - cnst_4 * in_r3 - cnst_16 * in_r5 - cnst_9 * in_r7;
-    t3 = cnst_9 * in_r1 - cnst_16 * in_r3 + cnst_4 * in_r5 + cnst_15 * in_r7;
-    t4 = cnst_4 * in_r1 - cnst_9 * in_r3 + cnst_15 * in_r5 - cnst_16 * in_r7;
-    LD_SW8(dest, linesize, dst0, dst1, dst2, dst3, dst4, dst5, dst6, dst7);
-    ILVR_B8_SW(zero_m, dst0, zero_m, dst1, zero_m, dst2, zero_m, dst3,
-               zero_m, dst4, zero_m, dst5, zero_m, dst6, zero_m, dst7,
-               dst0, dst1, dst2, dst3, dst4, dst5, dst6, dst7);
-    ILVR_H4_SW(zero_m, dst0, zero_m, dst1, zero_m, dst2, zero_m, dst3,
-               dst0, dst1, dst2, dst3);
-    ILVR_H4_SW(zero_m, dst4, zero_m, dst5, zero_m, dst6, zero_m, dst7,
-               dst4, dst5, dst6, dst7);
-    in_r0 = (t5 + t1) >> 7;
-    in_r1 = (t6 + t2) >> 7;
-    in_r2 = (t7 + t3) >> 7;
-    in_r3 = (t8 + t4) >> 7;
-    in_r4 = (t8 - t4 + cnst_1) >> 7;
-    in_r5 = (t7 - t3 + cnst_1) >> 7;
-    in_r6 = (t6 - t2 + cnst_1) >> 7;
-    in_r7 = (t5 - t1 + cnst_1) >> 7;
-    ADD4(in_r0, dst0, in_r1, dst1, in_r2, dst2, in_r3, dst3,
-         in_r0, in_r1, in_r2, in_r3);
-    ADD4(in_r4, dst4, in_r5, dst5, in_r6, dst6, in_r7, dst7,
-         in_r4, in_r5, in_r6, in_r7);
-    CLIP_SW8_0_255(in_r0, in_r1, in_r2, in_r3, in_r4, in_r5, in_r6, in_r7);
-    PCKEV_H4_SH(in_r1, in_r0, in_r3, in_r2, in_r5, in_r4, in_r7, in_r6,
-                in0, in1, in2, in3);
-    PCKEV_B2_SH(in1, in0, in3, in2, in0, in1);
-    ST_W8(in0, in1, 0, 1, 2, 3, 0, 1, 2, 3, dest, linesize);
-}
-
-void ff_vc1_inv_trans_8x4_msa(uint8_t *dest, ptrdiff_t linesize, int16_t *block)
-{
-    v4i32 in0, in1, in2, in3, in4, in5, in6, in7;
-    v4i32 t1, t2, t3, t4, t5, t6, t7, t8;
-    v4i32 dst0, dst1, dst2, dst3, dst4, dst5, dst6, dst7;
-    v16i8 zero_m = { 0 };
-    v4i32 cnst_17 = {17, 17, 17, 17};
-    v4i32 cnst_22 = {22, 22, 22, 22};
-    v4i32 cnst_10 = {10, 10, 10, 10};
-    v4i32 cnst_12 = {12, 12, 12, 12};
-    v4i32 cnst_64 = {64, 64, 64, 64};
-    v4i32 cnst_16 = {16, 16, 16, 16};
-    v4i32 cnst_15 = {15, 15, 15, 15};
-    v4i32 cnst_4 = {4, 4, 4, 4};
-    v4i32 cnst_6 = {6, 6, 6, 6};
-    v4i32 cnst_9 = {9, 9, 9, 9};
-
-    LD_SW4(block, 8, t1, t2, t3, t4);
-    UNPCK_SH_SW(t1, in0, in4);
-    UNPCK_SH_SW(t2, in1, in5);
-    UNPCK_SH_SW(t3, in2, in6);
-    UNPCK_SH_SW(t4, in3, in7);
-    TRANSPOSE4x4_SW_SW(in0, in1, in2, in3, in0, in1, in2, in3);
-    TRANSPOSE4x4_SW_SW(in4, in5, in6, in7, in4, in5, in6, in7);
-    // First loop
-    t1 = cnst_12 * (in0 + in4) + cnst_4;
-    t2 = cnst_12 * (in0 - in4) + cnst_4;
-    t3 = cnst_16 * in2 + cnst_6 * in6;
-    t4 = cnst_6 * in2 - cnst_16 * in6;
-    t5 = t1 + t3, t6 = t2 + t4;
-    t7 = t2 - t4, t8 = t1 - t3;
-    t1 = cnst_16 * in1 + cnst_15 * in3 + cnst_9 * in5 + cnst_4 * in7;
-    t2 = cnst_15 * in1 - cnst_4 * in3 - cnst_16 * in5 - cnst_9 * in7;
-    t3 = cnst_9 * in1 - cnst_16 * in3 + cnst_4 * in5 + cnst_15 * in7;
-    t4 = cnst_4 * in1 - cnst_9 * in3 + cnst_15 * in5 - cnst_16 * in7;
-    in0 = (t5 + t1) >> 3;
-    in1 = (t6 + t2) >> 3;
-    in2 = (t7 + t3) >> 3;
-    in3 = (t8 + t4) >> 3;
-    in4 = (t8 - t4) >> 3;
-    in5 = (t7 - t3) >> 3;
-    in6 = (t6 - t2) >> 3;
-    in7 = (t5 - t1) >> 3;
-    TRANSPOSE4x4_SW_SW(in0, in1, in2, in3, in0, in1, in2, in3);
-    TRANSPOSE4x4_SW_SW(in4, in5, in6, in7, in4, in5, in6, in7);
-    PCKEV_H4_SW(in4, in0, in5, in1, in6, in2, in7, in3, t1, t2, t3, t4);
-    ST_SW4(t1, t2, t3, t4, block, 8);
-    // Second loop
-    LD_SW4(dest, linesize, dst0, dst1, dst2, dst3);
-    ILVR_B4_SW(zero_m, dst0, zero_m, dst1, zero_m, dst2, zero_m, dst3,
-               dst0, dst1, dst2, dst3);
-    ILVL_H4_SW(zero_m, dst0, zero_m, dst1, zero_m, dst2, zero_m, dst3,
-               dst4, dst5, dst6, dst7);
-    ILVR_H4_SW(zero_m, dst0, zero_m, dst1, zero_m, dst2, zero_m, dst3,
-               dst0, dst1, dst2, dst3);
-    // Right part
-    t1 = cnst_17 * (in0 + in2) + cnst_64;
-    t2 = cnst_17 * (in0 - in2) + cnst_64;
-    t3 = cnst_22 * in1 + cnst_10 * in3;
-    t4 = cnst_22 * in3 - cnst_10 * in1;
-    in0 = (t1 + t3) >> 7;
-    in1 = (t2 - t4) >> 7;
-    in2 = (t2 + t4) >> 7;
-    in3 = (t1 - t3) >> 7;
-    ADD4(in0, dst0, in1, dst1, in2, dst2, in3, dst3, in0, in1, in2, in3);
-    CLIP_SW4_0_255(in0, in1, in2, in3);
-    // Left part
-    t5 = cnst_17 * (in4 + in6) + cnst_64;
-    t6 = cnst_17 * (in4 - in6) + cnst_64;
-    t7 = cnst_22 * in5 + cnst_10 * in7;
-    t8 = cnst_22 * in7 - cnst_10 * in5;
-    in4 = (t5 + t7) >> 7;
-    in5 = (t6 - t8) >> 7;
-    in6 = (t6 + t8) >> 7;
-    in7 = (t5 - t7) >> 7;
-    ADD4(in4, dst4, in5, dst5, in6, dst6, in7, dst7, in4, in5, in6, in7);
-    CLIP_SW4_0_255(in4, in5, in6, in7);
-    PCKEV_H4_SW(in4, in0, in5, in1, in6, in2, in7, in3, in0, in1, in2, in3);
-    PCKEV_B2_SW(in1, in0, in3, in2, in0, in1);
-    ST_D4(in0, in1, 0, 1, 0, 1, dest, linesize);
-}
-
-static void put_vc1_mspel_mc_h_v_msa(uint8_t *dst, const uint8_t *src,
-                                     ptrdiff_t stride, int hmode, int vmode,
-                                     int rnd)
-{
-    v8i16 in_r0, in_r1, in_r2, in_r3, in_l0, in_l1, in_l2, in_l3;
-    v8i16 t0, t1, t2, t3, t4, t5, t6, t7;
-    v8i16 t8, t9, t10, t11, t12, t13, t14, t15;
-    v8i16 cnst_para0, cnst_para1, cnst_para2, cnst_para3, cnst_r;
-    static const int para_value[][4] = {{4, 53, 18, 3},
-                                        {1, 9, 9, 1},
-                                        {3, 18, 53, 4}};
-    static const int shift_value[] = {0, 5, 1, 5};
-    int shift = (shift_value[hmode] + shift_value[vmode]) >> 1;
-    int r = (1 << (shift - 1)) + rnd - 1;
-    cnst_r = __msa_fill_h(r);
-    src -= 1, src -= stride;
-    cnst_para0 = __msa_fill_h(para_value[vmode - 1][0]);
-    cnst_para1 = __msa_fill_h(para_value[vmode - 1][1]);
-    cnst_para2 = __msa_fill_h(para_value[vmode - 1][2]);
-    cnst_para3 = __msa_fill_h(para_value[vmode - 1][3]);
-    LD_SH4(src, stride, in_l0, in_l1, in_l2, in_l3);
-    UNPCK_UB_SH(in_l0, in_r0, in_l0);
-    UNPCK_UB_SH(in_l1, in_r1, in_l1);
-    UNPCK_UB_SH(in_l2, in_r2, in_l2);
-    UNPCK_UB_SH(in_l3, in_r3, in_l3);
-    // row 0
-    t0 = cnst_para1 * in_r1 + cnst_para2 * in_r2
-         - cnst_para0 * in_r0 - cnst_para3 * in_r3;
-    t8 = cnst_para1 * in_l1 + cnst_para2 * in_l2
-         - cnst_para0 * in_l0 - cnst_para3 * in_l3;
-    in_l0 = LD_SH(src + 4 * stride);
-    UNPCK_UB_SH(in_l0, in_r0, in_l0);
-    // row 1
-    t1 = cnst_para1 * in_r2 + cnst_para2 * in_r3
-         - cnst_para0 * in_r1 - cnst_para3 * in_r0;
-    t9 = cnst_para1 * in_l2 + cnst_para2 * in_l3
-         - cnst_para0 * in_l1 - cnst_para3 * in_l0;
-    in_l1 = LD_SH(src + 5 * stride);
-    UNPCK_UB_SH(in_l1, in_r1, in_l1);
-    // row 2
-    t2 = cnst_para1 * in_r3 + cnst_para2 * in_r0
-         - cnst_para0 * in_r2 - cnst_para3 * in_r1;
-    t10 = cnst_para1 * in_l3 + cnst_para2 * in_l0
-          - cnst_para0 * in_l2 - cnst_para3 * in_l1;
-    in_l2 = LD_SH(src + 6 * stride);
-    UNPCK_UB_SH(in_l2, in_r2, in_l2);
-    // row 3
-    t3 = cnst_para1 * in_r0 + cnst_para2 * in_r1
-         - cnst_para0 * in_r3 - cnst_para3 * in_r2;
-    t11 = cnst_para1 * in_l0 + cnst_para2 * in_l1
-          - cnst_para0 * in_l3 - cnst_para3 * in_l2;
-    in_l3 = LD_SH(src + 7 * stride);
-    UNPCK_UB_SH(in_l3, in_r3, in_l3);
-    // row 4
-    t4 = cnst_para1 * in_r1 + cnst_para2 * in_r2
-         - cnst_para0 * in_r0 - cnst_para3 * in_r3;
-    t12 = cnst_para1 * in_l1 + cnst_para2 * in_l2
-          - cnst_para0 * in_l0 - cnst_para3 * in_l3;
-    in_l0 = LD_SH(src + 8 * stride);
-    UNPCK_UB_SH(in_l0, in_r0, in_l0);
-    // row 5
-    t5 = cnst_para1 * in_r2 + cnst_para2 * in_r3
-         - cnst_para0 * in_r1 - cnst_para3 * in_r0;
-    t13 = cnst_para1 * in_l2 + cnst_para2 * in_l3
-          - cnst_para0 * in_l1 - cnst_para3 * in_l0;
-    in_l1 = LD_SH(src + 9 * stride);
-    UNPCK_UB_SH(in_l1, in_r1, in_l1);
-    // row 6
-    t6 = cnst_para1 * in_r3 + cnst_para2 * in_r0
-         - cnst_para0 * in_r2 - cnst_para3 * in_r1;
-    t14 = cnst_para1 * in_l3 + cnst_para2 * in_l0
-          - cnst_para0 * in_l2 - cnst_para3 * in_l1;
-    in_l2 = LD_SH(src + 10 * stride);
-    UNPCK_UB_SH(in_l2, in_r2, in_l2);
-    // row 7
-    t7 = cnst_para1 * in_r0 + cnst_para2 * in_r1
-         - cnst_para0 * in_r3 - cnst_para3 * in_r2;
-    t15 = cnst_para1 * in_l0 + cnst_para2 * in_l1
-          - cnst_para0 * in_l3 - cnst_para3 * in_l2;
-
-    ADD4(t0, cnst_r, t1, cnst_r, t2, cnst_r, t3, cnst_r, t0, t1, t2, t3);
-    ADD4(t4, cnst_r, t5, cnst_r, t6, cnst_r, t7, cnst_r, t4, t5, t6, t7);
-    ADD4(t8, cnst_r, t9, cnst_r, t10, cnst_r, t11, cnst_r,
-         t8, t9, t10, t11);
-    ADD4(t12, cnst_r, t13, cnst_r, t14, cnst_r, t15, cnst_r,
-         t12, t13, t14, t15);
-    t0 >>= shift, t1 >>= shift, t2 >>= shift, t3 >>= shift;
-    t4 >>= shift, t5 >>= shift, t6 >>= shift, t7 >>= shift;
-    t8 >>= shift, t9 >>= shift, t10 >>= shift, t11 >>= shift;
-    t12 >>= shift, t13 >>= shift, t14 >>= shift, t15 >>= shift;
-    TRANSPOSE8x8_SH_SH(t0, t1, t2, t3, t4, t5, t6, t7,
-                       t0, t1, t2, t3, t4, t5, t6, t7);
-    TRANSPOSE8x8_SH_SH(t8, t9, t10, t11, t12, t13, t14, t15,
-                       t8, t9, t10, t11, t12, t13, t14, t15);
-    cnst_para0 = __msa_fill_h(para_value[hmode - 1][0]);
-    cnst_para1 = __msa_fill_h(para_value[hmode - 1][1]);
-    cnst_para2 = __msa_fill_h(para_value[hmode - 1][2]);
-    cnst_para3 = __msa_fill_h(para_value[hmode - 1][3]);
-    r = 64 - rnd;
-    cnst_r = __msa_fill_h(r);
-    // col 0 ~ 7
-    t0 = cnst_para1 * t1 + cnst_para2 * t2 - cnst_para0 * t0 - cnst_para3 * t3;
-    t1 = cnst_para1 * t2 + cnst_para2 * t3 - cnst_para0 * t1 - cnst_para3 * t4;
-    t2 = cnst_para1 * t3 + cnst_para2 * t4 - cnst_para0 * t2 - cnst_para3 * t5;
-    t3 = cnst_para1 * t4 + cnst_para2 * t5 - cnst_para0 * t3 - cnst_para3 * t6;
-    t4 = cnst_para1 * t5 + cnst_para2 * t6 - cnst_para0 * t4 - cnst_para3 * t7;
-    t5 = cnst_para1 * t6 + cnst_para2 * t7 - cnst_para0 * t5 - cnst_para3 * t8;
-    t6 = cnst_para1 * t7 + cnst_para2 * t8 - cnst_para0 * t6 - cnst_para3 * t9;
-    t7 = cnst_para1 * t8 + cnst_para2 * t9 - cnst_para0 * t7 - cnst_para3 * t10;
-    ADD4(t0, cnst_r, t1, cnst_r, t2, cnst_r, t3, cnst_r, t0, t1, t2, t3);
-    ADD4(t4, cnst_r, t5, cnst_r, t6, cnst_r, t7, cnst_r, t4, t5, t6, t7);
-    t0 >>= 7, t1 >>= 7, t2 >>= 7, t3 >>= 7;
-    t4 >>= 7, t5 >>= 7, t6 >>= 7, t7 >>= 7;
-    TRANSPOSE8x8_SH_SH(t0, t1, t2, t3, t4, t5, t6, t7,
-                       t0, t1, t2, t3, t4, t5, t6, t7);
-    CLIP_SH8_0_255(t0, t1, t2, t3, t4, t5, t6, t7);
-    PCKEV_B4_SH(t1, t0, t3, t2, t5, t4, t7, t6, t0, t1, t2, t3);
-    ST_D8(t0, t1, t2, t3, 0, 1, 0, 1, 0, 1, 0, 1, dst, stride);
-}
-
-#define PUT_VC1_MSPEL_MC_MSA(hmode, vmode)                                    \
-void ff_put_vc1_mspel_mc ## hmode ## vmode ## _msa(uint8_t *dst,              \
-                                                const uint8_t *src,           \
-                                                ptrdiff_t stride, int rnd)    \
-{                                                                             \
-    put_vc1_mspel_mc_h_v_msa(dst, src, stride, hmode, vmode, rnd);            \
-}                                                                             \
-void ff_put_vc1_mspel_mc ## hmode ## vmode ## _16_msa(uint8_t *dst,           \
-                                                   const uint8_t *src,        \
-                                                   ptrdiff_t stride, int rnd) \
-{                                                                             \
-    put_vc1_mspel_mc_h_v_msa(dst, src, stride, hmode, vmode, rnd);            \
-    put_vc1_mspel_mc_h_v_msa(dst + 8, src + 8, stride, hmode, vmode, rnd);    \
-    dst += 8 * stride, src += 8 * stride;                                     \
-    put_vc1_mspel_mc_h_v_msa(dst, src, stride, hmode, vmode, rnd);            \
-    put_vc1_mspel_mc_h_v_msa(dst + 8, src + 8, stride, hmode, vmode, rnd);    \
-}
-
-PUT_VC1_MSPEL_MC_MSA(1, 1);
-PUT_VC1_MSPEL_MC_MSA(1, 2);
-PUT_VC1_MSPEL_MC_MSA(1, 3);
-
-PUT_VC1_MSPEL_MC_MSA(2, 1);
-PUT_VC1_MSPEL_MC_MSA(2, 2);
-PUT_VC1_MSPEL_MC_MSA(2, 3);
-
-PUT_VC1_MSPEL_MC_MSA(3, 1);
-PUT_VC1_MSPEL_MC_MSA(3, 2);
-PUT_VC1_MSPEL_MC_MSA(3, 3);
diff --git a/spaces/congsaPfin/Manga-OCR/logs/Car Parking Multiplayer Mod APK Unlock Everything for Free.md b/spaces/congsaPfin/Manga-OCR/logs/Car Parking Multiplayer Mod APK Unlock Everything for Free.md
deleted file mode 100644
index 2ad1c56d35c4d2c7c7cf9eb505abbd186c328a0d..0000000000000000000000000000000000000000
--- a/spaces/congsaPfin/Manga-OCR/logs/Car Parking Multiplayer Mod APK Unlock Everything for Free.md	
+++ /dev/null
@@ -1,103 +0,0 @@
-
-<h1>Car Parking Multiplayer Mod APK Unlocked Everything: A Complete Guide</h1>
- <p>Do you love driving and parking games? Do you want to experience the thrill of realistic car physics, open world map, multiplayer mode, and customizable cars? If yes, then you should try Car Parking Multiplayer, one of the most popular and realistic car parking games on Android. But wait, there's more! You can also enjoy all the features of this game without spending a dime by downloading Car Parking Multiplayer Mod APK unlocked everything. In this article, we will tell you everything you need to know about this amazing modded version of the game, including its features, benefits, download and installation process, and gameplay tips. Let's get started!</p>
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- <h2>What is Car Parking Multiplayer?</h2>
- <p>Car Parking Multiplayer is a simulation game developed by olzhass, a studio that specializes in creating realistic car games. The game has over 100 million downloads on Google Play Store and a 4.3-star rating from more than 1.5 million users. The game lets you drive and park various cars in different scenarios, such as city streets, airports, deserts, highways, and more. You can also explore the open world map with your friends or other players online, chat with them using voice chat, and join or create your own car clubs. You can also customize your cars with different colors, stickers, rims, spoilers, and tuning options. The game has various game modes and challenges to test your driving and parking skills, such as drift mode, free ride mode, police chase mode, time trial mode, and more.</p>
- <h3>Features of Car Parking Multiplayer</h3>
- <h4>Realistic car physics and graphics</h4>
- <p>One of the main attractions of Car Parking Multiplayer is its realistic car physics and graphics. The game uses a sophisticated physics engine that simulates the behavior of real cars, such as steering, braking, acceleration, suspension, traction, damage, and more. The game also has stunning graphics that create a lifelike environment for the cars and the locations. You can see the details of the cars, such as the headlights, taillights, mirrors, doors, windows, interiors, and more. You can also see the effects of weather, lighting, shadows, reflections, smoke, dust, and more.</p>
- <h4>Open world map with different locations</h4>
- <p>Another feature that makes Car Parking Multiplayer stand out from other parking games is its open world map with different locations. The game has a huge map that covers various terrains and scenarios, such as city streets, airports, deserts, highways, off-road tracks, and more. You can drive freely on the map and explore the different places with your friends or other players online. You can also find hidden places and secrets on the map that will reward you with money or gold.</p>
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- <h4>Multiplayer mode with voice chat and online friends</h4>
- <p>The game also has a multiplayer mode that lets you play with your friends or other players online. You can join or create your own rooms and invite other players to join you. You can also chat with them using voice chat or text chat. You can also add other players as your online friends and see their status and location on the map. You can also join or create your own car clubs and compete with other clubs for fame and glory.</p>
- <h4>Customizable cars and tuning options</h4>
- <p>The game also lets you customize your cars and tuning options. The game has over 100 cars to choose from, ranging from sedans, hatchbacks, SUVs, sports cars, supercars, trucks, buses, and more. You can also unlock and upgrade your cars with money and gold. You can change the color, sticker, rim, spoiler, and other parts of your cars. You can also tune your cars with different options, such as engine, turbo, gearbox, suspension, brakes, and more. You can make your cars faster, more powerful, more stable, and more unique.</p>
- <h4>Various game modes and challenges</h4>
- <p>The game also has various game modes and challenges to test your driving and parking skills. You can play the classic parking mode, where you have to park your car in the designated spot without hitting any obstacles or other cars. You can also play the drift mode, where you have to drift your car and earn points. You can also play the free ride mode, where you can drive freely on the map and do whatever you want. You can also play the police chase mode, where you have to escape from the cops or chase the criminals. You can also play the time trial mode, where you have to complete a course in the shortest time possible. The game also has daily and weekly challenges that will reward you with money and gold.</p>
- <h2>What is Car Parking Multiplayer Mod APK?</h2>
- <p>Car Parking Multiplayer Mod APK is a modified version of the original game that gives you access to all the features of the game without spending any money. The mod APK is created by third-party developers who modify the game files and unlock everything for you. By downloading and installing Car Parking Multiplayer Mod APK unlocked everything, you can enjoy unlimited money and gold, all cars unlocked and upgraded, no ads, and no root required.</p>
- <h3>Benefits of Car Parking Multiplayer Mod APK</h3>
- <h4>Unlimited money and gold</h4>
- <p>One of the benefits of Car Parking Multiplayer Mod APK is that it gives you unlimited money and gold. Money and gold are the main currencies of the game that you need to buy and upgrade your cars, customize your cars, join or create car clubs, and more. Normally, you have to earn money and gold by playing the game modes and challenges, or by watching ads or buying them with real money. But with Car Parking Multiplayer Mod APK unlocked everything, you don't have to worry about that. You will get unlimited money and gold from the start of the game and you can use them as much as you want.</p>
- <h4>All cars unlocked and upgraded</h4>
- <p>Another benefit of Car Parking Multiplayer Mod APK is that it gives you all cars unlocked and upgraded. As we mentioned before, the game has over 100 cars to choose from, but not all of them are available from the start. You have to unlock them by completing certain levels or challenges, or by buying them with money or gold. But with Car Parking Multiplayer Mod APK unlocked everything, you don't have to do that. You will get all cars unlocked from the start of the game and you can use any car you want. Moreover, you will also get all cars upgraded to their maximum level with money and gold. You can enjoy the best performance and appearance of your cars without spending any time or effort.</p>
- <h4>No ads and no root required</h4>
- <p>The last benefit of Car Parking Multiplayer Mod APK is that it gives you no ads and no root required. Ads are annoying interruptions that pop up on your screen while playing the game. They waste your time and ruin your gaming experience. Normally, you have to watch ads to earn some money or gold or to access some features of the game. But with Car Parking Multiplayer Mod APK unlocked everything, you don't have to do that. You will get no ads on your screen while playing the game and you can enjoy a smooth and uninterrupted gaming experience. Moreover, you don't need to root your device to install Car Parking Multiplayer Mod APK unlocked everything. Rooting is a risky process that can damage your device or void your warranty. But with Car Parking Multiplayer Mod APK unlocked everything, you don't need to root your device at all. You can install it easily on any Android device without any hassle.</p>
- <h2>How to download and install Car Parking Multiplayer Mod APK?</h2>
- <h3>Step-by-step instructions</h3>
- <p>If you want to download and install Car Parking Multiplayer Mod APK unlocked everything on your Android device, you can follow these simple steps:</p>
- <ol>
-<li>Click on the download button below to download the Car Parking Multiplayer Mod APK unlocked everything file on your device.</li>
-<li>Once the download is complete, go to your file manager and locate the downloaded file. Tap on it to start the installation process.</li>
-<li>If you see a pop-up message that says "Install blocked", go to your device settings and enable the option "Unknown sources" under security or privacy settings.</li>
-<li>Now, go back to the file manager and tap on the file again to continue the installation.</li>
-<li>Wait for a few seconds until the installation is finished. You will see a confirmation message that says "App installed".</li>
-<li>Now, you can open the game from your app drawer or home screen and enjoy Car Parking Multiplayer Mod APK unlocked everything.</li>
-</ol>
- <p>Note: If you have the original version of Car Parking Multiplayer installed on your device, you need to uninstall it first before installing the mod APK. Otherwise, you may face some errors or conflicts.</p>
- <h2>How to play Car Parking Multiplayer Mod APK?</h2>
- <h3>Tips and tricks for beginners</h3>
- <p>If you are new to Car Parking Multiplayer Mod APK, you may need some tips and tricks to play the game better. Here are some of them:</p>
- <ul>
-<li>Choose a car that suits your style and preference. You can try different cars and see which one you like the most. You can also customize your cars with different colors, stickers, rims, spoilers, and tuning options.</li>
-<li>Learn how to control your car properly. You can use the steering wheel, buttons, or tilt controls to steer your car. You can also use the brake, accelerator, clutch, gearbox, and handbrake buttons to control your car's speed and movement. You can also adjust the camera angle and view to see your car better.</li>
-<li>Practice your driving and parking skills in different game modes and challenges. You can play the classic parking mode, where you have to park your car in the designated spot without hitting any obstacles or other cars. You can also play the drift mode, where you have to drift your car and earn points. You can also play the free ride mode, where you can drive freely on the map and do whatever you want. You can also play the police chase mode, where you have to escape from the cops or chase the criminals. You can also play the time trial mode, where you have to complete a course in the shortest time possible. The game also has daily and weekly challenges that will reward you with money and gold.</li>
-<li>Explore the open world map with your friends or other players online. You can join or create your own rooms and invite other players to join you. You can also chat with them using voice chat or text chat. You can also add other players as your online friends and see their status and location on the map. You can also join or create your own car clubs and compete with other clubs for fame and glory.</li>
-<li>Use your money and gold wisely. You can use your money and gold to buy and upgrade your cars, customize your cars, join or create car clubs, and more. But don't spend them all at once. Save some for later use or for emergencies.</li>
-</ul>
- <h2>Conclusion</h2>
- <p>Car Parking Multiplayer Mod APK unlocked everything is a great game for car lovers and parking enthusiasts. It offers realistic car physics and graphics, open world map with different locations, multiplayer mode with voice chat and online friends, customizable cars and tuning options, various game modes and challenges, unlimited money and gold, all cars unlocked and upgraded, no ads, and no root required. It is easy to download and install on any Android device without any hassle. It is also fun and addictive to play with your friends or other players online. If you are looking for a realistic car parking game with unlimited features, then Car Parking Multiplayer Mod APK unlocked everything is the perfect choice for you.</p>
- <h2>Frequently Asked Questions</h2>
- <p>Here are some of the frequently asked questions about Car Parking Multiplayer Mod APK unlocked everything:</p>
- <ol>
-<li>Is Car Parking Multiplayer Mod APK safe to use?</li>
-<p>Yes, Car Parking Multiplayer Mod APK is safe to use as long as you download it from a trusted source like ours. We scan our files with antivirus software before uploading them on our website. We also test our files on different devices to ensure their compatibility and functionality. However, we are not responsible for any damage or loss that may occur due to using our files.</p>
-<li>Is Car Parking Multiplayer Mod APK legal to use?</li>
-<p>No, Car Parking Multiplayer Mod APK is not legal to use as it violates the terms of service of the original game developer. By using Car Parking Multiplayer Mod APK, you are accessing the features of the game that are not meant for free users. You are also violating the intellectual property rights of the original game developer. Therefore, using Car Parking Multiplayer Mod APK is illegal and unethical. We do not encourage or support any illegal or unethical activities. We only provide information and education purposes only. Use Car Parking Multiplayer Mod APK at your own risk.</p>
- <li>Will Car Parking Multiplayer Mod APK work on my device?</li>
-<p>Car Parking Multiplayer Mod APK should work on any Android device that meets the minimum requirements of the game. The game requires Android 5.0 or higher, 1 GB of RAM, and 300 MB of free storage space. However, some devices may not be compatible with Car Parking Multiplayer Mod APK due to various reasons, such as hardware limitations, software conflicts, or regional restrictions. If you encounter any problems while installing or playing Car Parking Multiplayer Mod APK, you can try the following solutions:</p>
-<ul>
-<li>Clear your device cache and data.</li>
-<li>Restart your device and try again.</li>
-<li>Update your device software and drivers.</li>
-<li>Check your internet connection and firewall settings.</li>
-<li>Contact the mod APK developer or support team for help.</li>
-</ul>
- <li>Can I update Car Parking Multiplayer Mod APK?</li>
-<p>No, you cannot update Car Parking Multiplayer Mod APK from the Google Play Store or any other source. Updating Car Parking Multiplayer Mod APK will overwrite the modded files and restore the original version of the game. This will make you lose all the features and benefits of Car Parking Multiplayer Mod APK. Therefore, you should avoid updating Car Parking Multiplayer Mod APK unless there is a new version of the mod APK available from our website. We will update our website with the latest version of Car Parking Multiplayer Mod APK as soon as possible.</p>
- <li>Can I play Car Parking Multiplayer Mod APK offline?</li>
-<p>Yes, you can play Car Parking Multiplayer Mod APK offline without any internet connection. You can enjoy the features and benefits of Car Parking Multiplayer Mod APK without any limitations or restrictions. However, you will not be able to access some features that require an internet connection, such as multiplayer mode, voice chat, online friends, car clubs, and more. Therefore, you should connect to the internet whenever possible to enjoy the full potential of Car Parking Multiplayer Mod APK.</p>
-</ol></p> 197e85843d<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/congsaPfin/Manga-OCR/logs/Create Word Search Masterpieces with Free Online Resources and Downloads.md b/spaces/congsaPfin/Manga-OCR/logs/Create Word Search Masterpieces with Free Online Resources and Downloads.md
deleted file mode 100644
index a2c78a44e18de6dd46afb1a849a5a5e026c895a1..0000000000000000000000000000000000000000
--- a/spaces/congsaPfin/Manga-OCR/logs/Create Word Search Masterpieces with Free Online Resources and Downloads.md	
+++ /dev/null
@@ -1,103 +0,0 @@
-<br />
-<h1>How to Create a Word Search Puzzle for Free</h1>
- <p>Do you love word games? Do you want to create your own word search puzzle for free? If you answered yes, then you are in the right place. In this article, we will show you how to make a word search puzzle online, download and print it, and use it for fun and learning. Let's get started!</p>
- <h2>What is a Word Search Puzzle?</h2>
- <p>A word search puzzle is a type of word game that consists of a grid of letters and a list of words. The goal is to find and circle all the words hidden in the grid, either horizontally, vertically, diagonally, or backwards. Word search puzzles are also known as word find, word seek, word sleuth, or mystery word puzzles.</p>
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- <h3>Definition and Benefits of Word Search Puzzles</h3>
- <p>Word search puzzles are not only entertaining, but also educational. They can help you improve your vocabulary, spelling, pattern recognition, memory, concentration, and problem-solving skills. They can also stimulate your brain, reduce stress, and boost your mood. Plus, they are suitable for people of all ages and backgrounds.</p>
- <h3>Types and Themes of Word Search Puzzles</h3>
- <p>There are many types and themes of word search puzzles to choose from. You can find word search puzzles based on topics such as animals, sports, holidays, geography, history, science, literature, music, movies, and more. You can also find word search puzzles with different levels of difficulty, from easy to hard. Some word search puzzles even have special features such as hidden messages, clues, shapes, colors, or images.</p>
- <h2>How to Make Your Own Word Search Puzzle Online</h2>
- <p>If you want to create your own word search puzzle for free, you don't need any special software or skills. All you need is an internet connection and a free word search maker tool. Here are the steps to follow:</p>
- <h3>Choose a Free Word Search Maker Tool</h3>
- <p>There are many free word search maker tools available online. Some of the most popular ones are Canva, Dictionary.com, and Canva Worksheets. These tools are easy to use and offer various options to customize your word search puzzle. You can also access them from your desktop or mobile device.</p>
- <h3>Customize Your Word Search Grid and Words</h3>
- <p>Once you choose a tool, you can start creating your word search puzzle. First, you need to decide how big you want your grid to be. You can choose from different sizes such as 9x9, 12x12, 15x15, or more. Then, you need to enter the words you want to hide in the grid. You can choose from different categories such as animals, sports, holidays, etc., or enter your own words. You can also decide whether you want to use diagonals or not, and whether you want the words to overlap or not.</p>
- <h3>Add Design Elements and Personalize Your Puzzle</h3>
- <p>After you enter your words, you can add some design elements and personalize your puzzle. You can change the font style, size, and color of the letters and the words. You can also add a title, a subtitle, a logo, or an image to your puzzle. You can also change the background color or add a pattern or texture. You can also adjust the spacing and alignment of the grid and the words <p>Once you are happy with your design, you can preview your word search puzzle and make any changes if needed.</p>
- <h2>How to Download and Print Your Word Search Puzzle</h2>
- <p>Now that you have created your word search puzzle, you can download and print it. Here are the steps to follow:</p>
- <h3>Save Your Word Search Puzzle as an Image or PDF File</h3>
- <p>Depending on the tool you used, you can save your word search puzzle as an image or a PDF file. You can also choose the quality and resolution of your file. Some tools also allow you to save your word search puzzle as a Word document or an Excel spreadsheet. You can also share your word search puzzle online via email, social media, or a link.</p>
-<p>How to create a word search puzzle online for free<br />
-Best free word search maker apps for Android and iOS<br />
-Free printable word search worksheets for kids and adults<br />
-Create custom word search games with Canva[^1^]<br />
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-Download and print word search puzzles from Dictionary.com[^2^]<br />
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-Download and print word search puzzles from various categories<br />
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-Create a word search with trivia questions and facts<br />
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-Free online word search editor and converter.</p>
- <h3>Print Your Word Search Puzzle from Your Device or Order Online</h3>
- <p>Once you have saved your word search puzzle, you can print it from your device or order it online. You can use any printer that supports the file format you chose. You can also adjust the print settings such as the paper size, orientation, margins, and scaling. You can also print multiple copies of your word search puzzle if you want. Alternatively, you can order your word search puzzle online from a printing service such as Vistaprint or Shutterfly. These services offer various options to print your word search puzzle on different materials such as paper, canvas, wood, metal, or magnets.</p>
- <h2>How to Use Your Word Search Puzzle for Fun and Learning</h2>
- <p>Now that you have printed your word search puzzle, you can use it for fun and learning. Here are some ideas:</p>
- <h3>Play Your Word Search Puzzle with Friends or Family</h3>
- <p>One of the best ways to enjoy your word search puzzle is to play it with your friends or family. You can challenge each other to see who can find all the words faster or with fewer mistakes. You can also make it more fun by adding some rules or rewards. For example, you can set a time limit, use a timer, or use a buzzer. You can also give prizes, points, or penalties for finding words or making errors.</p>
- <h3>Use Your Word Search Puzzle as a Classroom or Homework Activity</h3>
- <p>If you are a teacher or a student, you can use your word search puzzle as a classroom or homework activity. You can create word search puzzles based on the subjects or topics you are studying. For example, you can create word search puzzles about math, science, history, geography, languages, etc. You can also create word search puzzles about current events, holidays, or trivia. You can use your word search puzzles to review vocabulary, spelling, facts, concepts, or ideas. You can also use your word search puzzles to introduce new topics, spark discussions, or stimulate curiosity.</p>
- <h3>Challenge Yourself with Different Levels and Modes of Word Search Puzzles</h3>
- <p>If you want to challenge yourself with different levels and modes of word search puzzles, you can try some of these options:</p>
-<ul>
-<li>Use larger grids with more words and smaller letters.</li>
-<li>Use words that are longer, harder, or less common.</li>
-<li>Use words that have multiple meanings, synonyms, antonyms, homophones, or anagrams.</li>
-<li>Use words that are related to a specific theme, category, or genre.</li>
-<li>Use words that are hidden in different directions, such as diagonally, backwards, or zigzag.</li>
-<li>Use words that overlap with each other or form shapes or patterns.</li>
-<li>Use words that have clues instead of the actual words.</li>
-<li>Use words that have hidden messages or codes.</li>
-</ul>
-<p>You can also try some of these modes of word search puzzles:</p>
-<ul>
-<li>Solo mode: Play by yourself and try to find all the words in the shortest time possible.</li>
-<li>Co-op mode: Play with a partner and try to find all the words together.</li>
-<li>Versus mode: Play against another player and try to find more words than them.</li>
-<li>Battle mode: Play against multiple players and try to find more words than them in a limited time.</li>
-<li>Creative mode: Create your own word search puzzles and share them with others.</li>
-</ul>
- <h2>Conclusion and FAQs</h2>
- <p>In conclusion, creating a word search puzzle for free is easy and fun. You just need to choose a free word search maker tool online, customize your word search grid and words, add design elements and personalize your puzzle , download and print it, and use it for fun and learning. You can also challenge yourself with different levels and modes of word search puzzles, or play with your friends or family. Word search puzzles are a great way to improve your skills, stimulate your brain, and have fun at the same time. We hope you enjoyed this article and learned how to create a word search puzzle for free. If you have any questions, you can check out the FAQs below or contact us for more information.</p>
- <h3>FAQs</h3>
- <p>Here are some of the most frequently asked questions about creating a word search puzzle for free:</p>
- <ol>
-<li><b>How many words can I use in my word search puzzle?</b></li>
-<p>The number of words you can use in your word search puzzle depends on the size of your grid and the length of your words. Generally, the larger the grid and the shorter the words, the more words you can use. However, you should also consider the readability and difficulty of your puzzle. You don't want to make it too crowded or too easy. A good rule of thumb is to use between 10 to 20 words for a standard 15x15 grid.</p>
-<li><b>How can I make my word search puzzle more interesting?</b></li>
-<p>There are many ways to make your word search puzzle more interesting. You can use different themes, categories, or genres for your words. You can also use different features such as hidden messages, clues, shapes, colors, or images. You can also change the font style, size, and color of your letters and words. You can also add a title, a subtitle, a logo, or an image to your puzzle. You can also change the background color or add a pattern or texture.</p>
-<li><b>How can I check my word search puzzle for errors?</b></li>
-<p>Before you download and print your word search puzzle, you should check it for errors. You can use the preview option in your word search maker tool to see how your puzzle looks like. You can also use the solve option to see if all the words are hidden correctly in the grid. You can also use a spell checker or a grammar checker to make sure your words are spelled and written correctly.</p>
-<li><b>How can I share my word search puzzle with others?</b></li>
-<p>If you want to share your word search puzzle with others, you have several options. You can save your word search puzzle as an image or a PDF file and send it via email, social media, or a link. You can also print your word search puzzle and give it to someone in person or by mail. You can also order your word search puzzle online from a printing service and have it delivered to someone's address.</p>
-<li><b>Where can I find more free word search puzzles online?</b></li>
-<p>If you want to find more free word search puzzles online, you can visit some of these websites:</p>
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-<li>[The Word Search]: A website that offers thousands of free word search puzzles on various topics and levels.</li>
-<li>[Puzzles.ca]: A website that offers hundreds of free word search puzzles on different themes and categories.</li>
-<li>[Word Search Labs]: A website that allows you to create and play your own word search puzzles online.</li>
-</ul>
-</ol></p> 401be4b1e0<br />
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diff --git a/spaces/congsaPfin/Manga-OCR/logs/Download Dragon Z Quest Action RPG Mod APK - The Ultimate DB Anime Adventure for Android.md b/spaces/congsaPfin/Manga-OCR/logs/Download Dragon Z Quest Action RPG Mod APK - The Ultimate DB Anime Adventure for Android.md
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-<h1>Dragon Z Quest Mod APK Download: A Review</h1>
-<p>If you are looking for a fun and immersive RPG game with a dragon theme, you might want to check out Dragon Z Quest. This game is inspired by the classic Dragon Quest series, but with its own original story and characters. And if you want to enjoy the game with some extra features and advantages, you can download the mod apk version of Dragon Z Quest for free. In this article, we will review the game and the mod apk, as well as give you some tips and tricks for playing Dragon Z Quest.</p>
- <h2>What is Dragon Z Quest?</h2>
-<p>Dragon Z Quest is a RPG game developed by Moddroid.com. It is available for Android devices and can be downloaded from the Google Play Store or from the official website. The game has a rating of 4.5 out of 5 stars on the Play Store, with over 10,000 downloads and positive reviews from players.</p>
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- <h3>Game features</h3>
-<p>Dragon Z Quest has many features that make it an enjoyable and addictive RPG game. Some of these features are:</p>
-<ul>
-<li>A large and beautiful open world to explore, with different regions, dungeons, towns, and secrets.</li>
-<li>A turn-based combat system that is easy to learn but challenging to master. You can control up to four characters in your party, each with their own skills and abilities.</li>
-<li>A rich and engaging story that follows the adventures of Erik and Mia, two siblings who are treasure hunters in a world where dragons once turned people's hopes and memories into treasures.</li>
-<li>A variety of quests and side activities to complete, such as treasure hunting, crafting, fishing, cooking, and more.</li>
-<li>A collection of hundreds of treasures to find and collect, each with their own backstory and reference to the Dragon Quest series.</li>
-<li>A customization system that allows you to change your characters' appearance, equipment, skills, and stats.</li>
-<li>A photo mode that lets you take screenshots of your characters and the world.</li>
-</ul>
- <h3>Game story</h3>
-<p>The game story of Dragon Z Quest is set in Draconia, a world where dragons once ruled and created treasures from people's hopes and memories. However, the dragons are now extinct, and their treasures are scattered across the land. Erik and Mia are two siblings who are part of a crew of Viking marauders who live by plundering treasures. One day, they find a flying pig and a talking cat who claim to be gods from another dimension. They also find a magic portal that transports them to Draconia, where they decide to start their own treasure hunting business. Along the way, they will meet new friends and enemies, discover secrets about Draconia and their own past, and face dangers and challenges that will test their courage and skills.</p>
- <h2>Why download the mod apk version?</h2>
-<p>If you want to enhance your gaming experience with Dragon Z Quest, you might want to download the mod apk version of the game. The mod apk version is a modified version of the original game that gives you some benefits and advantages that are not available in the official version. Here are some reasons why you should download the mod apk version:</p>
- <h3>Benefits of the mod apk</h3>
-<p>The mod apk version of Dragon Z Quest offers you some benefits that can make your gameplay more enjoyable and convenient. Some of these benefits are:</p>
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-<ul>
-<li>Unlocked features: The mod apk version unlocks all the features of the game that are otherwise locked or require in-app purchases. This includes all the characters, equipment, skills, treasures, quests, regions, modes, and more.</li>
-<li>Unlimited resources: The mod apk version gives you unlimited resources such as gold, gems, stamina, health, mana, items, materials, etc. You can use these resources to buy anything you want in the game, upgrade your characters and equipment, craft new items, complete quests faster, and more.</li>
-<li>No ads: The mod apk version removes all the annoying and intrusive ads that pop up in the game. You can enjoy the game without any interruptions or distractions.</li>
-<li>No root required: The mod apk version does not require you to root your device or perform any complicated steps. You can simply download and install the mod apk file and start playing the game.</li>
-</ul>
- <h3>How to download and install the mod apk</h3>
-<p>If you are interested in downloading and installing the mod apk version of Dragon Z Quest, you can follow these simple steps:</p>
-<ol>
-<li>Go to the official website of Moddroid.com and search for Dragon Z Quest.</li>
-<li>Click on the download button and wait for the mod apk file to be downloaded on your device.</li>
-<li>Go to your device settings and enable the installation of apps from unknown sources.</li>
-<li>Locate the mod apk file in your device storage and tap on it to install it.</li>
-<li>Launch the game and enjoy the mod apk features.</li>
-</ol>
- <h2>Tips and tricks for playing Dragon Z Quest</h2>
-<p>Now that you have downloaded and installed the mod apk version of Dragon Z Quest, you might want to know some tips and tricks that can help you play the game better. Here are some useful tips and tricks for playing Dragon Z Quest:</p>
- <h3>Combat tips</h3>
-<p>Combat is an essential part of Dragon Z Quest, as you will encounter many enemies and bosses in your journey. Here are some combat tips that can help you win battles:</p>
-<ul>
-<li>Know your characters' strengths and weaknesses: Each character in your party has their own skills and abilities that can be useful in different situations. For example, Erik is good at physical attacks, Mia is good at healing and support, Piggy is good at magic attacks, and Kitty is good at stealing and debuffing. You should use your characters' skills wisely and switch them according to the enemy's type and behavior.</li>
-<li>Use combos and special attacks: You can perform combos and special attacks by filling up your combo gauge or your special gauge. Combos are powerful attacks that can deal extra damage or have additional effects, such as stunning, poisoning, or burning. Special attacks are unique attacks that can only be used once per battle, but they can have devastating effects, such as wiping out all enemies or restoring all allies' health. You should use combos and special attacks when you have the opportunity, as they can turn the tide of battle in your favor.</li>
-<li>Use items and equipment: You can use items and equipment to boost your characters' performance in combat. Items can heal, revive, buff, or debuff your characters or enemies. Equipment can increase your characters' stats, such as attack, defense, speed, or critical rate. You should use items and equipment strategically, as they can make a difference in difficult battles.</li>
-</ul>
- <h3>Exploration tips</h3>
-<p>Exploration is another important part of Dragon Z Quest, as you will travel across a vast and beautiful open world. Here are some exploration tips that can help you discover more of Draconia:</p>
-<ul>
-<li>Use fast travel: You can use fast travel to move between different regions or towns that you have visited before. Fast travel can save you time and energy, as well as avoid unnecessary encounters with enemies. You can access fast travel by opening your map and selecting your destination.</li>
-<li>Use mounts: You can use mounts to travel faster and easier in Draconia. Mounts are animals or vehicles that you can ride on, such as horses, dragons, boats, or airships. Mounts can also have special abilities, such as flying, swimming, or breaking obstacles. You can find mounts in different locations or by completing quests.</li>
-<li>Use landmarks: You can use landmarks to mark places of interest or importance in Draconia. Landmarks are icons that appear on your map and mini-map, such as towns, dungeons, treasures, quests, shops, etc. Landmarks can help you navigate the world and find what you are looking for.</li>
-</ul>
- <h3>Treasure hunting tips</h3>
-<p>Treasure hunting is one of the main activities in Dragon Z Quest, as you will find hundreds of treasures hidden in Draconia. Treasures are items that have a backstory and a reference to the Dragon Quest series. Treasures can also be sold for gold or used for crafting or upgrading. Here are some treasure hunting tips that can help you find more treasures:</p>
-<ul>
-<li>Use clues: You can use clues to find treasures in Draconia. Clues are hints or riddles that tell you where a treasure is located or how to get it. Clues can be found in books, signs , NPCs, or other sources. You should pay attention to the clues and try to solve them.</li>
-<li>Use tools: You can use tools to find treasures in Draconia. Tools are items that can help you detect, dig, or open treasures. Tools can be bought, found, or crafted. Some of the tools are the treasure radar, the shovel, the lockpick, the dynamite, etc. You should use tools when you see a treasure icon on your mini-map or when you encounter a locked or buried treasure.</li>
-<li>Use skills: You can use skills to find treasures in Draconia. Skills are abilities that your characters or mounts have that can help you find or access treasures. Some of the skills are flying, swimming, breaking, sneaking, etc. You should use skills when you see a treasure that is out of reach or hidden by obstacles or enemies.</li>
-</ul>
- <h2>Conclusion</h2>
-<p>Dragon Z Quest is a RPG game that is inspired by the classic Dragon Quest series, but with its own original story and characters. It is a game that offers a lot of fun and immersion, as well as challenge and variety. If you want to enjoy the game with some extra features and advantages, you can download the mod apk version of Dragon Z Quest for free from Moddroid.com. In this article, we have reviewed the game and the mod apk, as well as given you some tips and tricks for playing Dragon Z Quest. We hope that you have found this article helpful and informative, and that you will have a great time playing Dragon Z Quest.</p>
- <h2>FAQs</h2>
-<p>Here are some frequently asked questions about Dragon Z Quest and the mod apk:</p>
-<table>
-<tr><td><b>Question</b></td><td><b>Answer</b></td></tr>
-<tr><td>Is Dragon Z Quest safe to play?</td><td>Yes, Dragon Z Quest is safe to play, as it does not contain any viruses or malware. However, you should always download the game from a trusted source, such as the Google Play Store or the official website.</td></tr>
-<tr><td>Is the mod apk version of Dragon Z Quest legal?</td><td>The mod apk version of Dragon Z Quest is not legal, as it violates the terms and conditions of the original game. However, it is unlikely that you will face any legal consequences for using the mod apk, as long as you do not use it for commercial purposes or harm other players.</td></tr>
-<tr><td>Can I play Dragon Z Quest offline?</td><td>Yes, you can play Dragon Z Quest offline, as it does not require an internet connection to run. However, you will need an internet connection to download updates or access some online features.</td></tr>
-<tr><td>Can I play Dragon Z Quest with friends?</td><td>No, Dragon Z Quest does not have a multiplayer mode or feature. It is a single-player game that focuses on the story and the characters.</td></tr>
-<tr><td>How long is Dragon Z Quest?</td><td>The length of Dragon Z Quest depends on how you play the game and how much you explore and complete. However, it is estimated that the main story of Dragon Z Quest takes about 20 hours to finish, while the total content of the game takes about 40 hours to finish.</td></tr>
-</table></p> 197e85843d<br />
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diff --git a/spaces/congsaPfin/Manga-OCR/logs/Download Frozen City MOD APK 1.5.0 with Unlimited Money and VIP Unlocked.md b/spaces/congsaPfin/Manga-OCR/logs/Download Frozen City MOD APK 1.5.0 with Unlimited Money and VIP Unlocked.md
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-<h1>Frozen City Mod APK Revdl: A Survival and City Building Game Like No Other</h1>
-<p>If you are looking for a challenging and immersive game that will test your skills as a leader and a survivor, you might want to check out Frozen City mod apk revdl. This is a modified version of the original Frozen City game that gives you access to unlimited resources, gems, diamonds, and VIP features. With this mod, you can enjoy the game without any limitations or restrictions.</p>
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-<h2>What is Frozen City?</h2>
-<h3>A city-building simulation game set in an ice and snow apocalypse</h3>
-<p>Frozen City is a game developed by Century Games Pte. Ltd. that puts you in charge of the last town on Earth after a devastating ice and snow apocalypse. As the chief of the town, you have to gather resources, assign workers, explore the wilderness, conquer tough surroundings, and use various methods in order to survive. You also have to deal with the physical and mental health of your survivors, as well as their happiness and loyalty. The game features realistic graphics, atmospheric music, and engaging gameplay that will keep you hooked for hours.</p>
-<h3>A game inspired by the PC and console hit Frostpunk</h3>
-<p>Frozen City is a game inspired by the PC and console hit Frostpunk, which is also a survival and city building game set in a frozen world. However, Frozen City is more casual and accessible than Frostpunk, as it does not have as many harsh decisions and sacrifices that you have to make for your society. Frozen City also has more elements of exploration and adventure, as you can send out teams to discover new areas and resources. Frozen City is a game that appeals to both casual and hardcore players who enjoy strategy and simulation games.</p>
-<h2>What are the features of Frozen City?</h2>
-<h3>Survival simulation</h3>
-<p>Survivors are the basic characters in the game. They are the important work force who keep the urban area running. Assign your survivors to collect materials and work in various facilities. Mind the survivors' physical and mental health. If the food ration is in shortage or the temperature drops below freezing, the survivors may get sick; And there may be protests if the work mode or the living environment is dissatisfying.</p>
-<h3>Explore in the wild</h3>
-<p>The town sits in the wide wild frozen place. There will be exploratory teams as the survivor teams grow. Send the exploratory teams out for adventure and more useful supplies. Reveal the story behind this ice and snow apocalypse!</p>
-<h3>Production chain</h3>
-<p>Process raw materials into living items, set reasonable production ratio, and improve the town's operation. You will need different resources for different purposes, such as wood, coal, food, metal, etc. Some resources require other resources to produce them, which builds up a production chain.</p>
-<h3>Allocate labor</h3>
-<h3>Expand the town</h3>
-<p>The town is surrounded by a circular wall that protects it from the cold and the enemies. You can expand the town by building more facilities and houses inside the wall, or by extending the wall outward. Expanding the town will increase your population, production, and defense.</p>
-<h3>Collect heroes</h3>
-<p>Heroes are special characters in the game that have unique abilities and skills. You can recruit heroes from various ways, such as completing quests, exploring the wild, or spending gems. Heroes can lead your exploratory teams or join your battles. They can also boost your town's performance by providing bonuses and buffs.</p>
-<h2>How to download and play Frozen City mod apk revdl?</h2>
-<h3>Download from a reliable source</h3>
-<p>If you want to play Frozen City mod apk revdl, you need to download it from a reliable source that offers safe and virus-free files. One of the best sources for downloading mod apk files is revdl.com, which is a popular website that provides free download links for various Android games and apps. You can find Frozen City mod apk revdl on revdl.com by searching for it on the website's search bar or browsing through its categories.</p>
-<h3>Install and enjoy the game with unlimited resources and VIP features</h3>
-<p>After downloading Frozen City mod apk revdl from revdl.com, you need to install it on your Android device. To do so, you need to enable the installation of apps from unknown sources in your device's settings. Then, you can tap on the downloaded file and follow the instructions to install it. Once installed, you can launch the game and enjoy it with unlimited resources and VIP features. You can use these features to build your town faster, explore more areas, recruit more heroes, and have more fun.</p>
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-<h2>What are some tips and tricks for playing Frozen City?</h2>
-<h3>Play on BlueStacks to enjoy a superior gameplay experience</h3>
-<p>If you want to play Frozen City on your PC or laptop, you can use BlueStacks, which is an Android emulator that allows you to run Android games and apps on your computer. BlueStacks offers a superior gameplay experience for Frozen City, as it has a larger screen, better graphics, faster performance, and more controls. You can also use BlueStacks' features such as multi-instance, macro recorder, key mapping, etc. to enhance your gaming experience.</p>
-<h3>Work on completing your task list</h3>
-<p>Frozen City has a task list that shows you various objectives and missions that you need to complete in order to progress in the game. Completing these tasks will reward you with resources, gems, diamonds, heroes, and other items that will help you improve your town and gameplay. You can access your task list by tapping on the clipboard icon on the top left corner of the screen.</p>
-<h3>Manage your resources wisely</h3>
-<p>Resources are essential for building and maintaining your town in Frozen City. You need to collect and produce enough resources to meet the needs of your survivors and facilities. However, resources are also limited and scarce in this frozen world, so you need to manage them wisely. You can do so by setting reasonable production ratios, upgrading your storage capacity, trading with other towns, recycling unused items, etc.</p>
-<h3>Keep your survivors happy and healthy</h3>
-<p>Your survivors are the backbone of your town in Frozen City. They provide you with labor, skills, and loyalty. However, they also have physical and mental needs that you need to fulfill in order to keep them happy and healthy. You need to provide them with enough food, water, warmth, shelter, entertainment, etc. You also need to deal with their complaints, demands, conflicts, etc. Keeping your survivors happy and healthy will increase their productivity and morale.</p>
-<h3>Use your heroes strategically</h3>
-<p>Your heroes are your special assets in Frozen City. They have unique abilities and skills that can help you in various situations. You can use your heroes to lead your exploratory teams or join your battles. You can also use them to boost your town's performance by providing bonuses and buffs. However, you need to use your heroes strategically, as they have limited energy and cooldowns. You need to choose the right heroes for the right tasks and situations.</p>
-<h2>Conclusion</h2>
-<p>Frozen City is a survival and city building game that will challenge you as a leader and a survivor in a frozen world. You need to gather resources, assign workers, explore the wilderness, conquer tough surroundings, and use various methods in order to survive. You also need to deal with the physical and mental health of your survivors, well as their happiness and loyalty. The game features realistic graphics, atmospheric music, and engaging gameplay that will keep you hooked for hours.</p>
-<p>If you want to play Frozen City mod apk revdl, you can download it from revdl.com, which is a reliable source for mod apk files. With this mod, you can enjoy the game with unlimited resources, gems, diamonds, and VIP features. You can also play the game on BlueStacks, which is an Android emulator that offers a superior gameplay experience for Frozen City. You can also use some tips and tricks to improve your gameplay, such as working on completing your task list, managing your resources wisely, keeping your survivors happy and healthy, and using your heroes strategically.</p>
-<p>Frozen City is a game that appeals to both casual and hardcore players who enjoy strategy and simulation games. It is a game that will challenge you as a leader and a survivor in a frozen world. Are you ready to take on this challenge? Download Frozen City mod apk revdl today and start building your town!</p>
-<h2>FAQs</h2>
-<table>
-<tr><td><b>Q: What is the difference between Frozen City and Frostpunk?</b></td></tr>
-<tr><td>A: Frozen City is a game inspired by Frostpunk, which is also a survival and city building game set in a frozen world. However, Frozen City is more casual and accessible than Frostpunk, as it does not have as many harsh decisions and sacrifices that you have to make for your society. Frozen City also has more elements of exploration and adventure, as you can send out teams to discover new areas and resources.</td></tr>
-<tr><td><b>Q: How can I get more gems and diamonds in Frozen City?</b></td></tr>
-<tr><td>A: Gems and diamonds are premium currencies in Frozen City that can be used to buy various items and features in the game. You can get more gems and diamonds by completing tasks, achievements, daily rewards, etc. You can also get more gems and diamonds by downloading Frozen City mod apk revdl, which gives you unlimited resources and VIP features.</td></tr>
-<tr><td><b>Q: How can I upgrade my facilities and houses in Frozen City?</b></td></tr>
-<tr><td>A: You can upgrade your facilities and houses in Frozen City by using resources such as wood, coal, metal, etc. Upgrading your facilities and houses will improve their performance and capacity. You can also use gems and diamonds to speed up the upgrading process.</td></tr>
-<tr><td><b>Q: How can I recruit more heroes in Frozen City?</b></td></tr>
-<tr><td>A: Heroes are special characters in Frozen City that have unique abilities and skills. You can recruit more heroes by completing quests, exploring the wild, or spending gems. You can also get more heroes by downloading Frozen City mod apk revdl, which gives you access to all the heroes in the game.</td></tr>
-<tr><td><b>Q: How can I play Frozen City on my PC or laptop?</b></td></tr>
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diff --git a/spaces/congsaPfin/Manga-OCR/logs/Download Love Babbar DSA Sheet The Best Resource for DSA Preparation.md b/spaces/congsaPfin/Manga-OCR/logs/Download Love Babbar DSA Sheet The Best Resource for DSA Preparation.md
deleted file mode 100644
index 545105ec1f8f0ff3e3e80f1e82d3ba3821f29009..0000000000000000000000000000000000000000
--- a/spaces/congsaPfin/Manga-OCR/logs/Download Love Babbar DSA Sheet The Best Resource for DSA Preparation.md	
+++ /dev/null
@@ -1,122 +0,0 @@
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-<p>If you are looking for a comprehensive and structured way to learn data structures and algorithms, you might have heard of the love babbar dsa sheet. This is a popular resource created by love babbar, a software engineer and YouTube educator, who has compiled a list of 450 questions covering various topics and concepts of data structures and algorithms. In this article, we will show you how to download this sheet from Google Drive and how to use it effectively to improve your skills and knowledge.</p>
- <h2>What Is the Love Babbar DSA Sheet and Why Is It Useful?</h2>
-<p>The love babbar dsa sheet is a Google spreadsheet that contains 450 questions on data structures and algorithms, along with links to their solutions. The questions are divided into different categories, such as arrays, strings, linked lists, stacks, queues, trees, graphs, sorting, searching, dynamic programming, greedy, backtracking, bit manipulation, etc. The questions are also labeled according to their difficulty level and source (such as GeeksforGeeks, LeetCode, HackerRank, etc.).</p>
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- <h2>What Are Data Structures and Algorithms and Why Are They Important?</h2>
-<p>Data structures are ways of organizing and storing data in a computer system. They allow us to access, manipulate, and process data efficiently and effectively. Some common examples of data structures are arrays, lists, stacks, queues, trees, graphs, hash tables, heaps, etc.</p>
-<p>Algorithms are sequences of steps or instructions that are used to solve a specific problem or perform a certain task. They define how data structures are used to perform operations on data. Some common examples of algorithms are sorting, searching, divide and conquer, greedy, dynamic programming, backtracking, etc.</p>
-<p>Data structures and algorithms are important because they form the core of computer science and programming. They help us design optimized and scalable solutions for various real-world problems. They also help us measure the performance of our solutions in terms of time complexity (how fast our solution runs) and space complexity (how much memory our solution uses). Having a solid understanding of data structures and algorithms is essential for any aspiring or experienced programmer.</p>
- <h2>How to Download the Love Babbar DSA Sheet from Google Drive</h2>
-<p>To download the love babbar dsa sheet from Google Drive, you need to follow these simple steps:</p>
-<ol>
-<li><strong>Open Google Drive in your web browser or app</strong>. You can access Google Drive from any device by visiting <a href="(^1^)">drive.google.com</a> or by downloading the Google Drive app from <a href="(^2^)">Google Play Store</a> (for Android) or <a href="(^3^)">App Store</a>. (for iOS) respectively. You need to sign in with your Google account to access your Google Drive.</li>
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-<li><strong>Right-click or tap on the file or folder and select Download</strong>. This will start downloading the file or folder to your device. Depending on the size of the file or folder and your internet speed, this may take some time. You can check the progress of the download in your browser or app.</li>
-<li><strong>Choose a location to save the file or folder on your device</strong>. Once the download is complete, you can choose where you want to save the file or folder on your device. You can either save it in your default downloads folder or choose a different location. You can also rename the file or folder if you want.</li>
-</ol>
-<p>Congratulations! You have successfully downloaded the love babbar dsa sheet from Google Drive. Now you can open it with any spreadsheet software, such as Microsoft Excel, Google Sheets, LibreOffice Calc, etc.</p>
- <h2>How to Use the Love Babbar DSA Sheet to Learn Data Structures and Algorithms</h2>
-<p>Now that you have downloaded the love babbar dsa sheet, you might be wondering how to use it effectively to learn data structures and algorithms. Here are some tips and suggestions:</p>
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-<ul>
-<li><strong>How to access the questions and solutions in the sheet</strong>. The sheet has two tabs: Questions and Solutions. The Questions tab contains the list of 450 questions along with their categories, difficulty levels, and sources. The Solutions tab contains the links to the solutions for each question. You can click on the links to open them in a new tab or window. You can also copy and paste the links in your browser.</li>
-<li><strong>How to practice the questions and track your progress</strong>. The best way to practice the questions is to try solving them on your own before looking at the solutions. You can use any online coding platform, such as GeeksforGeeks IDE, LeetCode Playground, HackerRank Code Editor, etc., to write and run your code. You can also use a pen and paper to write down your logic and pseudocode. To track your progress, you can mark the questions that you have solved or attempted in the sheet. You can also use different colors or symbols to indicate your status, such as green for solved, yellow for attempted, red for unsolved, etc.</li>
-<li><strong>How to review the concepts and topics covered in the sheet</strong>. The sheet covers a wide range of topics and concepts related to data structures and algorithms. To review them, you can use various online resources, such as books, videos, blogs, courses, etc., that explain them in detail. Some of the recommended resources are:   <ul>
-  <li>Data Structures and Algorithms Made Easy by Narasimha Karumanchi</li>
-  <li>Data Structures and Algorithms in Python by Michael T. Goodrich, Roberto Tamassia, and Michael H. Goldwasser</li>
-  <li>Data Structures and Algorithms Specialization by University of California San Diego on Coursera</li>
-  <li>Data Structures and Algorithms Nanodegree by Udacity</li>
-  <li>Data Structures and Algorithms by Abdul Bari on YouTube</li>
-  </ul>
-</li>
-</ul>
- <h2>Conclusion</h2>
-<p>In this article, we have shown you how to download the love babbar dsa sheet from Google Drive and how to use it effectively to learn data structures and algorithms. The love babbar dsa sheet is a great resource for anyone who wants to master data structures and algorithms from scratch or revise their concepts. By practicing these questions regularly, you can improve your problem-solving skills, logical thinking, coding proficiency, and confidence.</p>
-<p>Here are some tips and resources for further learning:</p>
-<ul>
-<li>Practice more questions from different sources, such as GeeksforGeeks, LeetCode, HackerRank, etc., to expose yourself to different types of problems and scenarios.</li>
-<li>Join online communities, such as Stack Overflow, Reddit, Discord, etc., where you can ask questions, share your solutions, get feedback, and learn from others.</li>
-<li>Participate in online contests and challenges, such as CodeChef, Codeforces, Hackerearth, etc., where you can compete with other programmers and test your skills under time pressure.</ <li>Keep learning new concepts and topics, such as advanced data structures, algorithms, and paradigms, that can help you solve more complex and challenging problems.</li>
-</ul>
- <h2>FAQs</h2>
-<p>Here are some frequently asked questions about the love babbar dsa sheet and data structures and algorithms:</p>
-<ol>
-<li><strong>What are some benefits of learning data structures and algorithms?</strong></li>
-<p>Some of the benefits of learning data structures and algorithms are:</p>
-<ul>
-<li>You can design efficient and scalable solutions for various real-world problems.</li>
-<li>You can improve your coding skills and write clean, readable, and maintainable code.</li>
-<li>You can ace your technical interviews and land your dream job or internship.</li>
-<li>You can expand your knowledge and understanding of computer science and programming.</li>
-<li>You can enjoy the thrill and satisfaction of solving challenging problems.</li>
-</ul>
- <li><strong>How long does it take to complete the love babbar dsa sheet?</strong></li>
-<p>The time it takes to complete the love babbar dsa sheet depends on your current level of proficiency, your learning pace, and your availability. However, a rough estimate is that it may take you anywhere from a few weeks to a few months to complete the sheet. You can set your own goals and deadlines according to your schedule and preferences.</p>
- <li><strong>What are some other sources of data structures and algorithms questions?</strong></li>
-<p>Some of the other sources of data structures and algorithms questions are:</p>
-<ul>
-<li><a href="">GeeksforGeeks</a>: A website that provides hundreds of articles, tutorials, videos, quizzes, and practice questions on various topics related to data structures and algorithms.</li>
-<li><a href="">LeetCode</a>: A platform that offers over 2000 coding problems with different difficulty levels and categories, along with online judges, solutions, discussions, and contests.</li>
-<li><a href="">HackerRank</a>: A website that hosts coding challenges, contests, interviews, and certifications on various domains and skills, including data structures and algorithms.</li>
-</ul>
- <li><strong>How can I prepare for data structures and algorithms interviews?</strong></li>
-<p>Some of the tips to prepare for data structures and algorithms interviews are:</p>
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-<li>Review the basics of data structures and algorithms, such as their definitions, implementations, operations, applications, advantages, disadvantages, etc.</li>
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-<li><a href="">LinkedIn</a>: Love Babbar</li>
-<li>Email: lovebabbar@gmail.com</li>
-</ul></p> 401be4b1e0<br />
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diff --git a/spaces/congsaPfin/Manga-OCR/logs/Download Stumble Guys Versi 6.0 and Enjoy the Fun Features of this Multiplayer Game.md b/spaces/congsaPfin/Manga-OCR/logs/Download Stumble Guys Versi 6.0 and Enjoy the Fun Features of this Multiplayer Game.md
deleted file mode 100644
index 966ad280b3e6bac7138a7a179f2a6b8b8f92d9f0..0000000000000000000000000000000000000000
--- a/spaces/congsaPfin/Manga-OCR/logs/Download Stumble Guys Versi 6.0 and Enjoy the Fun Features of this Multiplayer Game.md	
+++ /dev/null
@@ -1,94 +0,0 @@
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-<p>Stumble Guys is a fun and addictive online multiplayer party game that lets you race with up to 32 players through chaotic obstacle courses. You can run, jump, dash, slide, and stumble your way to victory in different levels until one player is crowned as the winner. You can also customize your character with various outfits and emotes, play with your friends in party mode, and enjoy physics-based mayhem in colorful and whacky environments.</p>
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-<li>A new map called Path of the Champion, which is inspired by ancient Rome and features gladiator-themed obstacles</li>
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-<p>If you have an Android phone or tablet, you can download Stumble Guys version 6.0 from Google Play Store, which is the official app store for Android devices. Here's how:</p>
- <h3>Step 1: Open Google Play Store</h3>
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-<p>Tap the magnifying glass icon at the top of the screen. This will open the search bar, where you can type in the name of the app or game you are looking for. In this case, type in "Stumble Guys" and tap the enter key on your keyboard. This will show you a list of apps and games that match your search query.</p>
- <h3>Step 3: Select Stumble Guys from the Search Results</h3>
-<p>Scroll down the list until you see the app that has the name "Stumble Guys: Multiplayer Royale" and the icon that looks like a yellow character with a blue helmet. This is the official app from Kitka Games, the developer of Stumble Guys. Tap on it to open its details page, where you can see more information about the app, such as its description, screenshots, ratings, reviews, and more.</p>
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-<p>If you have never installed Stumble Guys before, you will see a green button that says "Install" at the top of the screen. Tap on it to start downloading and installing the app on your device. If you have already installed Stumble Guys before, but want to update it to version 6.0, you will see a blue button that says "Update" instead. Tap on it to start updating the app on your device. If you have already installed and updated Stumble Guys to version 6.0, you will see a green button that says "Open" instead. Tap on it to launch the app on your device.</p>
- <h3>Step 5: Tap Open or Launch the App from Your Home Screen</h3>
-<p>Once the download and installation process is complete, you will see a notification that says "Stumble Guys: Multiplayer Royale installed." Tap on it to open the app on your device. Alternatively, you can also launch the app from your home screen by tapping on its icon. You will see a splash screen that shows the game's logo and version number, followed by a loading screen that shows some tips and tricks for playing the game. After that, you will be taken to the main menu of the game, where you can start playing Stumble Guys version 6.0.</p>
- <h2>How to Download Stumble Guys Version 6.0 on Windows 11</h2>
-<p>If you have a Windows 11 PC or laptop, you can download Stumble Guys version 6.0 from Microsoft Store, which is the official app store for Windows devices. Here's how:</p>
- <h3>Step 1: Open Microsoft Store</h3>
-<p>Click on the icon that looks like a shopping bag with a Windows logo in your taskbar. This app is usually called "Microsoft Store," but may just be called "Store" on some devices. This will open the Microsoft Store app, where you can browse and download thousands of apps and games for your Windows device.</p>
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- <h3>Step 3: Select Stumble Guys from the Search Results</h3>
-<p>Scroll down the list until you see the app that has the name "Stumble Guys: Multiplayer Royale" and the icon that looks like a yellow character with a blue helmet. This is the official app from Kitka Games, the developer of Stumble Guys. Click on it to open its details page, where you can see more information about the app, such as its description, screenshots, ratings, reviews, and more.</p>
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-<p>If you have never installed Stumble Guys before, you will see a blue button that says "Get" at the top right corner of the screen. Click on it to start downloading and installing the app on your device. If you have already installed Stumble Guys before, but want to update it to version 6.0, you will see a blue button that says "Update" instead. Click on it to start updating the app on your device. If you have already installed and updated Stumble Guys to version 6.0, you will see a blue button that says "Play" instead. Click on it to launch the app on your device.</p>
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-<p>Once the download and installation process is complete, you will see a notification that says "Stumble Guys: Multiplayer Royale installed." Click on it to open the app on your device. Alternatively, you can also launch the app from your start menu by clicking on its icon. You will see a splash screen that shows the game's logo and version number, followed by a loading screen that shows some tips and tricks for playing the game. After that, you will be taken to the main menu of the game, where you can start playing Stumble Guys version 6.0.</p>
- <h2>Conclusion</h2>
-<p>Stumble Guys is a hilarious and thrilling online multiplayer party game that will keep you entertained for hours. You can compete with up to 32 players in various obstacle courses, customize your character with different outfits and emotes, and enjoy physics-based chaos in stunning graphics and sound effects. If you want to experience the latest version of the game, which is version 6.0, you can easily download it from Google Play Store or Microsoft Store, depending on your device. Just follow the steps we have outlined in this article, and you will be stumbling your way to glory in no time.</p>
-<p>So what are you waiting for? Download Stumble Guys version 6.0 today and join the fun!</p>
- <h2>FAQs</h2>
-<p>Here are some of the most frequently asked questions and answers about Stumble Guys version 6.0:</p>
- <h4>Q: Is Stumble Guys free to play?</h4>
-<p>A: Yes, Stumble Guys is free to play, but it contains ads and in-app purchases. You can remove ads and unlock premium features by purchasing the VIP Pass or other items with real money.</p>
- <h4>Q: How many players can play Stumble Guys at once?</h4>
-<p>A: Stumble Guys supports up to 32 players per match. You can join random matches with other players from around the world, or create your own private matches with your friends using party codes.</p>
- <h4>Q: How do I change my character's outfit and emote?</h4>
-<p>A: You can change your character's outfit and emote by tapping on the wardrobe icon at the bottom left corner of the main menu. You can choose from various outfits and emotes that you have unlocked or purchased with coins or gems. You can also mix and match different parts of outfits to create your own unique style.</p>
- <h4>Q: How do I switch to first-person perspective?</h4>
-<p>A: You can switch to first-person perspective by tapping on the camera icon at the top right corner of the screen during a match. This will let you see the game from your character's point of view, which can be more immersive and challenging. You can switch back to third-person perspective by tapping on the same icon again.</p>
- <h4>Q: How do I contact the developer of Stumble Guys?</h4>
-<p>A: You can contact the developer of Stumble Guys by sending an email to support@kitkagames.com or by visiting their website at https://www.kitkagames.com/. You can also follow them on social media platforms such as Facebook, Twitter, Instagram, YouTube, and Discord for more updates and news about the game.</p> 401be4b1e0<br />
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diff --git a/spaces/congsaPfin/Manga-OCR/logs/Download WhatsApp APK for Android and Stay Connected with Your Friends.md b/spaces/congsaPfin/Manga-OCR/logs/Download WhatsApp APK for Android and Stay Connected with Your Friends.md
deleted file mode 100644
index fed084d1feaf8945a1470207cbe49f276b7e137f..0000000000000000000000000000000000000000
--- a/spaces/congsaPfin/Manga-OCR/logs/Download WhatsApp APK for Android and Stay Connected with Your Friends.md	
+++ /dev/null
@@ -1,150 +0,0 @@
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-<li><strong>Simple, reliable, private messaging and calling</strong>: You can send text messages, voice notes, photos, videos, documents, contacts, and locations to anyone who has WhatsApp on their phone. You can also make free voice and video calls with high-quality sound and video. All your communications are end-to-end encrypted, which means that only you and the person you are talking to can read or listen to them.</li>
-<li><strong>Data friendly</strong>: You can use WhatsApp on any network, even on slow or unstable connections. You can also reduce your data usage by adjusting your settings for media downloads and calls.</li>
-<li><strong>Compatible with multiple devices</strong>: You can use WhatsApp on your Android phone or tablet, as well as on your Windows or Mac computer. You can also sync your chats across your devices using WhatsApp Web or Desktop.</li>
-<li><strong>Offers voice notes, audio and video calls, file sharing, and more</strong>: You can express yourself in more ways with WhatsApp 2019 APK. You can send voice notes to convey your emotions or convey information quickly. You can make audio and video calls to stay in touch with your loved ones or colleagues. You can share files of any type and size, such as PDFs, ZIPs, MP3s, and more. You can also create and join group chats, broadcast messages, and use stickers and emojis to spice up your conversations.</li>
-</ul>
-<h3>How to download and install WhatsApp 2019 APK on your Android device</h3>
-<p>Downloading and installing WhatsApp 2019 APK on your Android device is easy and fast. Just follow these simple steps:</p>
-<ol>
-<li><strong>Enable unknown sources</strong>: Go to your device's settings and look for the security or privacy option. Tap on it and find the option to allow installation of apps from unknown sources. Toggle it on and confirm your choice.</li>
-<li><strong>Download WhatsApp 2019 APK</strong>: Go to the official website of WhatsApp or any other trusted source that offers the latest version of WhatsApp 2019 APK. Tap on the download button and wait for the file to be downloaded on your device.</li>
-<li><strong>Install WhatsApp 2019 APK</strong>: Locate the downloaded file on your device's file manager or downloads folder. Tap on it and follow the instructions on the screen to install WhatsApp 2019 APK on your device.</li>
-<li><strong>Verify your phone number and enjoy</strong>: Open WhatsApp 2019 APK and enter your phone number. You will receive a verification code via SMS or a phone call. Enter the code and agree to the terms and conditions. You can now start using WhatsApp 2019 APK on your device.</li>
-</ol>
-<h2>Why You Should Download WhatsApp 2019 APK</h2>
-<p>WhatsApp 2019 APK is a great app that offers many benefits for its users. However, it also has some drawbacks that you should be aware of. Here are some of the pros and cons of WhatsApp 2019 APK:</p>
-<h3>The pros of WhatsApp 2019 APK</h3>
-<table>
-<tr>
-<th>Pros</th>
-<th>Description</th>
-</tr>
-<tr>
-<td><strong>It's free with no ads</strong></td>
-<td>You don't have to pay anything to use WhatsApp 2019 APK, and you won't see any annoying ads or pop-ups on the app.</td>
-</tr>
-<tr>
-<td><strong>It's easy to use</strong></td>
-<td>WhatsApp 2019 APK has a simple and intuitive interface that makes it easy to navigate and use. You can easily find your contacts, chats, calls, settings, and more.</td>
-</tr>
-<tr>
-<td><strong>It's data friendly</strong></td>
-<td>WhatsApp 2019 APK uses minimal data to send and receive messages and calls. You can also adjust your data usage settings to save more data.</td>
-</tr>
-<tr>
-<td><strong>It has end-to-end encryption</strong></td>
-<td>All your messages and calls are encrypted by default, which means that no one can intercept or access them except you and the person you are communicating with.</td>
-</tr>
-<tr>
-<td><strong>It's compatible with multiple devices</strong></td>
-<td>You can use WhatsApp 2019 APK on your Android phone or tablet, as well as on your Windows or Mac computer. You can also sync your chats across your devices using WhatsApp Web or Desktop.</td>
-</tr>
-<tr>
-<td><strong>It offers voice notes, audio and video calls, file sharing, and more</strong></td>
-<td>You can express yourself in more ways with WhatsApp 2019 APK. You can send voice notes to convey your emotions or convey information quickly. You can make audio and video calls to stay in touch with your loved ones or colleagues. You can share files of any type and size, such as PDFs, ZIPs, MP3s, and more. You can also create and join group chats, broadcast messages, and use stickers and emojis to spice up your conversations.</td>
-</tr>
-</table>
- <h3>The cons of WhatsApp 2019 APK</h3>
- <table>
- <tr>
- <th>Cons</th>
- <th>Description</th>
- </tr>
- <tr>
- <td><strong>It has dodgy privacy</strong></td>
- <td>WhatsApp 2019 APK is owned by Facebook, which has a history of mishandling user data and privacy. Although WhatsApp claims that it does not share your data with Facebook, there have been reports of data breaches and leaks that expose user information.</td>
- </tr>
- <tr>
- <td><strong>It requires phone numbers to register</strong></td>
- <td>You need a valid phone number to sign up for WhatsApp 2019 APK, which means that you have to share your personal information with the app. This can make you vulnerable to spam calls, phishing scams, or identity theft.</td>
- </tr>
- <tr>
- <td><strong>It requires internet to work</strong></td>
- <td>You need a stable internet connection to use WhatsApp 2019 APK, which means that you can't use it offline or in areas with poor network coverage. This can limit your communication options and make you miss important messages or calls.</td>
- </tr>
- <tr>
- <td><strong>It has status update limits</strong></td>
- <td>You can only update your status with text, photos, or videos that last for 24 hours. You can't edit or delete your status once you post it. You also can't see who viewed your status unless they reply to it.</td>
- </tr>
- <tr>
- <td><strong>It allows people to add you to groups without consent</strong></td>
- <td>You can be added to group chats by anyone who has your phone number, even if you don't know them or want to join the group. This can be annoying and intrusive, as you may receive unwanted messages or notifications from the group. You can leave the group, but you can't prevent people from adding you again.</td>
- </tr>
- <tr>
- <td><strong>It has file size limitations</strong></td>
- <td>You can only send files up to 100 MB on WhatsApp 2019 APK, which means that you can't send large files such as movies, games, or software. You also can't send multiple files at once, which can be inconvenient and time-consuming.</td>
- </tr>
- </table>
- <h2>Conclusion</h2>
-<p>WhatsApp 2019 APK is a great app that lets you communicate with anyone in the world for free. It has many features and advantages that make it a popular choice among users. However, it also has some drawbacks and risks that you should be aware of before downloading and installing it. Ultimately, the decision is yours whether you want to download WhatsApp 2019 APK or not. We hope that this article has helped you understand what WhatsApp 2019 APK is and how to use it. If you have any questions or feedback, feel free to leave a comment below.</p>
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-<h3>What is the difference between WhatsApp and WhatsApp 2019 APK?</h3>
-<p>WhatsApp is the original version of the app that you can download from the Google Play Store or the Apple App Store. WhatsApp 2019 APK is an updated version of the app that you can download from the official website or other sources. WhatsApp 2019 APK has some new features and improvements that are not available on WhatsApp.</p>
-<h3>Is WhatsApp 2019 APK safe and secure?</h3>
-<p>WhatsApp 2019 APK is generally safe and secure, as it uses end-to-end encryption to protect your messages and calls. However, it is not an official app from WhatsApp, so it may have some bugs or glitches that could affect its performance or security. It may also violate some terms and conditions of WhatsApp, which could result in your account being banned or suspended. Therefore, you should download and install WhatsApp 2019 APK at your own risk and discretion.</p>
-<h3>How can I update WhatsApp 2019 APK?</h3>
-<p>You can update WhatsApp 2019 APK by downloading and installing the latest version of the app from the official website or other sources. You should always check for updates regularly to ensure that you have the most recent and secure version of the app.</p>
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-<h3>How can I backup my WhatsApp chats and media?</h3>
-<p>You can backup your WhatsApp chats and media by using Google Drive or iCloud. You can also export your chats and media to your email or other apps. To backup your chats and media, go to your settings and tap on chats. Then tap on chat backup and choose your backup option.</p>
-<h3>How can I delete my WhatsApp account?</h3>
-<p>You can delete your WhatsApp account by going to your settings and tapping on account. Then tap on delete my account and follow the instructions on the screen. Deleting your account will erase all your data, messages, contacts, groups, and settings from WhatsApp. You will also lose access to any backups or services associated with your account.</p> 401be4b1e0<br />
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diff --git a/spaces/congsaPfin/Manga-OCR/logs/Get Ready for Rainbow Six Mobile on iOS Download Tips and Tricks.md b/spaces/congsaPfin/Manga-OCR/logs/Get Ready for Rainbow Six Mobile on iOS Download Tips and Tricks.md
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-
-<h1>How to Download Rainbow Six Mobile iOS</h1>
- <p>If you are a fan of tactical shooters, you might be interested in playing Rainbow Six Mobile, a free-to-play multiplayer game that brings the classic Rainbow Six experience to your phone. In this article, we will show you how to download Rainbow Six Mobile on iOS devices, as well as some tips and tricks for playing the game.</p>
- <h2>What is Rainbow Six Mobile?</h2>
- <p>Rainbow Six Mobile is a mobile version of the popular Rainbow Six franchise, developed by Ubisoft. It is a competitive, first-person shooter game that pits two teams of five players against each other in various modes and maps. The game features a roster of operators, each with their own unique abilities and gadgets, that you can choose from and customize. You can also collaborate with your teammates using voice chat or a ping system, and take advantage of the destructible environments.</p>
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- <p>Rainbow Six Mobile is currently available in some regions as a live test, but it will be released globally soon. You can check the official website or follow the news for more updates.</p>
- <h2>Why play Rainbow Six Mobile on iOS?</h2>
- <p>There are many reasons why you might want to play Rainbow Six Mobile on iOS devices. Here are some of them:</p>
- <ul>
-<li>You can enjoy high-quality graphics and smooth gameplay on your iPhone or iPad.</li>
-<li>You can play with cross-play functionality, meaning you can team up or compete with players using Android devices.</li>
-<li>You can access exclusive content and rewards by linking your Ubisoft account.</li>
-<li>You can use touch controls or connect a compatible controller for more precision and comfort.</li>
-<li>You can experience a variety of maps and modes that are inspired by the original Rainbow Six games.</li>
-</ul>
- <h2>How to download Rainbow Six Mobile on iOS</h2>
- <p>Downloading Rainbow Six Mobile on iOS is easy and fast. Just follow these simple steps:</p>
- <h3>How to find Rainbow Six Mobile on the App Store</h3>
- <p>To find Rainbow Six Mobile on the App Store, you can either search for it by typing "Rainbow Six Mobile" in the search bar, or use this link to go directly to its page. You can also scan this QR code with your camera app:</p>
- <img src="https://www.ubisoft.com/en-us/game/rainbow-six/mobile/images/qr-code.png" alt="QR code for Rainbow Six Mobile">
- <p>Once you are on the App Store page, you can check if the game is compatible with your device by looking at the "Compatibility" section. You will need an iPhone or iPad that runs iOS 13.0 or later, and has at least 1.5 GB of free space.</p> <h3>How to download and install Rainbow Six Mobile on your iPhone or iPad</h3>
- <p>After you have confirmed that the game is compatible with your device, you can download and install it by tapping the "Get" button on the App Store page. You may need to sign in with your Apple ID and password, or use Face ID or Touch ID, to confirm the download. The game is free to download, but it may offer some in-app purchases.</p>
- <p>The download size of the game is about 1.5 GB, so it may take some time depending on your internet connection speed. You can check the progress of the download by looking at the app icon on your home screen. Once the download is complete, the app icon will change from a circle to a rainbow.</p>
- <h3>How to launch and play Rainbow Six Mobile on your iPhone or iPad</h3>
- <p>To launch the game, you can tap the app icon on your home screen, or use Siri to say "Open Rainbow Six Mobile". The first time you open the game, you may need to accept some permissions and terms of service. You may also need to download some additional data for the game to run properly.</p>
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- <p>Once the game is ready, you can adjust some settings, such as your language, region, and graphics quality. You can also link your Ubisoft account to access exclusive content and rewards. If you don't have a Ubisoft account, you can create one for free.</p>
- <p>To play the game, you can choose from different modes and maps, such as Team Deathmatch, Bomb Defusal, Hostage Rescue, and more. You can also join a match with random players or invite your friends to play with you. Before each match, you can select and customize your operator, and choose your loadout and gadgets. You can also communicate with your teammates using voice chat or a ping system.</p>
- <h2>Tips and tricks for playing Rainbow Six Mobile on iOS</h2>
- <p>Rainbow Six Mobile is a fun and challenging game that requires strategy and teamwork. Here are some tips and tricks to help you improve your skills and enjoy the game more:</p>
- <h3>How to use voice chat and ping system</h3>
- <p>Voice chat and ping system are two ways to communicate with your teammates in Rainbow Six Mobile. Voice chat allows you to talk with your teammates using your microphone. You can enable or disable voice chat in the settings menu, or mute specific players during a match. Ping system allows you to send signals to your teammates using icons and messages. You can use ping system by tapping the ping button on the screen, and then selecting an option from the menu.</p>
- <p>Voice chat and ping system are useful for coordinating your actions, sharing information, and giving feedback. For example, you can use voice chat to call out enemy locations, request backup, or congratulate a teammate. You can use ping system to mark enemies, objectives, gadgets, or locations.</p> <h3>How to choose and customize your operators</h3>
- <p>Operators are the characters that you can play as in Rainbow Six Mobile. Each operator has a unique ability and gadget that can help you in different situations. For example, some operators can breach walls, deploy shields, heal teammates, or detect enemies. You can choose your operator before each match, or switch between operators during a match.</p>
- <p>You can also customize your operators by equipping them with different weapons, attachments, skins, and charms. You can unlock new items by playing the game, completing challenges, or buying them with in-game currency or real money. You can access your operator customization menu by tapping the operator icon on the main screen.</p>
- <h3>How to master the maps and modes</h3>
- <p>Rainbow Six Mobile offers a variety of maps and modes that are inspired by the original Rainbow Six games. Each map and mode has its own layout, objectives, and strategies. You can learn more about the maps and modes by reading their descriptions, watching tutorials, or playing them in practice mode.</p>
- <p>Some of the maps and modes available in Rainbow Six Mobile are:</p>
- <table>
-<tr>
-<th>Map</th>
-<th>Mode</th>
-<th>Description</th>
-</tr>
-<tr>
-<td>House</td>
-<td>Team Deathmatch</td>
-<td>A small suburban house with multiple entry points and destructible walls. The team with the most kills wins.</td>
-</tr>
-<tr>
-<td>Consulate</td>
-<td>Bomb Defusal</td>
-<td>A large diplomatic building with multiple floors and rooms. One team must plant a bomb in one of the designated sites, while the other team must defuse it or eliminate the attackers.</td>
-</tr>
-<tr>
-<td>Bank</td>
-<td>Hostage Rescue</td>
-<td>A massive bank with vaults and offices. One team must locate and extract a hostage from the building, while the other team must prevent them or eliminate the rescuers.</td>
-</tr>
-<tr>
-<td>Kafe Dostoyevsky</td>
-<td>Secure Area</td>
-<td>A cozy cafe with a kitchen, a dining room, and a fireplace. One team must secure a biohazard container in one of the rooms, while the other team must stop them or eliminate the intruders.</td>
-</tr>
-<tr>
-<td>Border</td>
-<td>Domination</td>
-<td>A border checkpoint with a warehouse and a control room. Both teams must capture and hold three zones on the map for as long as possible.</td>
-</tr>
-</table>
- <h3>How to optimize your performance and battery life</h3>
- <p>Rainbow Six Mobile is a demanding game that requires a lot of resources from your device. To ensure that you have a smooth and enjoyable gameplay experience, you may want to optimize your performance and battery life by following these tips:</p>
- <ul>
-<li>Adjust your graphics settings to match your device's capabilities. You can lower the resolution, frame rate, or texture quality to improve your performance and reduce lag.</li>
-<li>Close any background apps that may be consuming your memory or CPU power. You can also turn off any unnecessary notifications or features that may distract you or interfere with your game.</li>
-<li>Use a stable and fast internet connection, preferably Wi-Fi or 4G. Avoid playing on public networks that may be slow or unreliable.</li>
-<li>Keep your device cool and ventilated. Avoid playing in hot or humid environments, or placing your device on soft surfaces that may block the air flow.</li>
-<li>Charge your device before playing, or use a power bank or charger while playing. You can also enable low power mode or battery saver mode to extend your battery life.</li>
-</ul>
- <h2>Conclusion</h2>
- <p>Rainbow Six Mobile is a thrilling and immersive game that lets you enjoy the classic Rainbow Six experience on your iOS device. You can download it for free from the App Store, and play it with cross-play functionality with Android users. You can also customize your operators, communicate with your teammates, and master the maps and modes. With these tips and tricks, you will be ready to join the Rainbow Six Mobile community and have fun.</p>
- <h3>FAQs</h3>
- <ul>
-<li><b>Q: How much storage space does Rainbow Six Mobile require?</b></li>
-<li>A: Rainbow Six Mobile requires about 1.5 GB of storage space on your device. However, this may vary depending on your device model and updates.</li>
-<li><b>Q: How do I update Rainbow Six Mobile?</b></li>
-<li>A: Rainbow Six Mobile will update automatically if you have enabled automatic updates on your device. You can also update it manually by going to the App Store page and tapping the Update button.</li>
-<li><b>Q: How do I report a bug or a hacker in Rainbow Six Mobile?</b></li>
-<li>A: You can report a bug or a hacker by using the in-game feedback system. You can access it by tapping the settings icon on the main screen, and then tapping the feedback button. You can also contact the customer support or visit the official forums for more help.</li>
-<li><b>Q: How do I get more in-game currency or items in Rainbow Six Mobile?</b></li>
-<li>A: You can get more in-game currency or items by playing the game, completing challenges, or buying them with real money. You can use in-game currency to buy new operators, weapons, skins, charms, and more. You can also get some items for free by linking your Ubisoft account or participating in events and promotions.</li>
-<li><b>Q: How do I delete Rainbow Six Mobile from my device?</b></li>
-<li>A: You can delete Rainbow Six Mobile from your device by following these steps:</li>
-<ol>
-<li>Tap and hold the app icon on your home screen until it starts to jiggle.</li>
-<li>Tap the X icon on the top left corner of the app icon.</li>
-<li>Tap Delete to confirm.</li>
-</ol>
-<p>Note that deleting the app will also delete your local data and settings. However, your progress and purchases will be saved on your Ubisoft account if you have linked it.</p> 197e85843d<br />
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diff --git a/spaces/congsaPfin/Manga-OCR/logs/Lucky Bird Casino A New Online Casino with a Mobile-Friendly Design.md b/spaces/congsaPfin/Manga-OCR/logs/Lucky Bird Casino A New Online Casino with a Mobile-Friendly Design.md
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+++ /dev/null
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diff --git a/spaces/congsaPfin/Manga-OCR/logs/Tekken 3 APK - Download the Classic Fighting Game for Android.md b/spaces/congsaPfin/Manga-OCR/logs/Tekken 3 APK - Download the Classic Fighting Game for Android.md
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--- a/spaces/congsaPfin/Manga-OCR/logs/Tekken 3 APK - Download the Classic Fighting Game for Android.md	
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- <h2>Introduction</h2>
- <p>Tekken 3 is one of the best arcade games of its time. It was released in 1997 by Namco for the PlayStation console and became a worldwide phenomenon. It features a roster of over 20 characters, each with their own fighting style, moves, and story. It also has various game modes, such as arcade, versus, team battle, survival, practice, and more. Tekken 3 is widely considered as one of the greatest fighting games ever made.</p>
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- <p>But what if you want to play Tekken 3 on your android device? Well, you can do that with an APK file. An APK file is a package file that contains all the necessary files and data to run an app or a game on your android device. You can download an APK file from various sources online and install it on your device with a few simple steps. However, you should be careful about where you download an APK file from, as some sources may contain malware or viruses that can harm your device.</p>
- <p>One of the benefits of playing Tekken 3 on your android device is that you can enjoy the classic arcade game anytime and anywhere. You don't need a PlayStation console or a TV to play it. You can also customize the controls and settings according to your preference. You can also save your progress and resume it later. Playing Tekken 3 on your android device is a great way to relive the nostalgia and have fun.</p>
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- <p>Playing Tekken 3 on your android device is similar to playing it on the PlayStation console. The gameplay is fast-paced, smooth, and responsive. You can select from over 20 characters, each with their own strengths, weaknesses, and special moves. You can also unlock new characters by completing certain tasks or modes.</p>
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- <p>To select a character and enter a match, you need to use the left hand joystick and the right hand buttons on your mobile screen. The joystick allows you to move your character around the stage, while the buttons allow you to perform punches, kicks, throws, and combos. You can also use the buttons to block, sidestep, or taunt your opponent.</p>
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- <p>Tekken 3 looks amazing on your android device. The developers have managed to give you arcade quality graphics with no add-on required. The characters and their movements are all fluid and natural. The stages are detailed and colorful. The sound effects and music are crisp and clear.</p>
- <p>Tekken 3 on your android device looks very similar to the original PlayStation version. However, there are some differences that you may notice. For example, some of the characters and their costumes may look slightly different or have less detail. For example, Jin's pants may not have the flame pattern on them. Some of the stages may also have less background elements or animations. For example, the temple stage may not have the monks or the candles. These differences are minor and do not affect the gameplay or the enjoyment of the game.</p>
- <p>Playing Tekken 3 on your android device has its pros and cons. On the positive side, you can play the game anytime and anywhere, without needing a console or a TV. You can also adjust the controls and settings to your liking. You can also save your progress and resume it later. On the negative side, you may experience some lag or glitches, depending on your device and internet connection. You may also find it harder to perform some moves or combos, due to the smaller screen and touch controls. You may also miss some of the features or modes that are available on the PlayStation version, such as Tekken Force or Tekken Ball.</p>
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- <p>Tekken 3 is a classic arcade game that you can play on your android device with an APK file. It has a great gameplay, graphics, and features that will keep you entertained for hours. It is one of the best fighting games ever made and a must-play for any fan of the genre.</p>
- <p>However, playing Tekken 3 on your android device also has some drawbacks. You may encounter some technical issues, such as lag or glitches, depending on your device and internet connection. You may also find it harder to perform some moves or combos, due to the smaller screen and touch controls. You may also miss some of the features or modes that are available on the PlayStation version, such as Tekken Force or Tekken Ball.</p>
- <p>Therefore, playing Tekken 3 on your android device is a matter of personal preference and convenience. If you want to enjoy the game anytime and anywhere, without needing a console or a TV, then playing Tekken 3 on your android device is a good option for you. However, if you want to experience the game in its full glory, with all its features and modes, then playing Tekken 3 on the PlayStation console is a better option for you.</p>
- <p>Either way, playing Tekken 3 is a fun and exciting way to spend your time and relive the nostalgia of the arcade era.</p>
- <h2>FAQs</h2>
- <p>Here are some of the most common questions and answers about Tekken 3 20mb APK download:</p>
- <h3>Q: Where can I download Tekken 3 20mb APK file?</h3>
-<p>A: You can download Tekken 3 20mb APK file from various sources online, such as [Tekken 3 APK Download] or [Tekken 3 APK Free Download]. However, you should be careful about where you download an APK file from, as some sources may contain malware or viruses that can harm your device.</p>
- <h3>Q: How can I install Tekken 3 20mb APK file on my android device?</h3>
-<p>A: To install Tekken 3 20mb APK file on your android device, you need to follow these steps:</p>
-<ol>
-<li>Download Tekken 3 20mb APK file from a trusted source online.</li>
-<li>Go to your device settings and enable unknown sources option. This will allow you to install apps from sources other than Google Play Store.</li>
-<li>Locate the downloaded APK file on your device storage and tap on it.</li>
-<li>Follow the instructions on the screen and complete the installation process.</li>
-<li>Launch the game and enjoy playing Tekken 3 on your android device.</li>
-</ol>
- <h3>Q: How can I customize the controls and settings of Tekken 3 on my android device?</h3>
-<p>A: To customize the controls and settings of Tekken 3 on your android device, you need to follow these steps:</p>
-<ol>
-<li>Launch the game and go to the main menu.</li>
-<li>Select options and then select controller settings.</li>
-<li>You can adjust the size, position, transparency, and vibration of the joystick and buttons according to your preference.</li>
-<li>You can also change the difficulty level, sound volume, language, and other settings according to your preference.</li>
-<li>Save your changes and exit the options menu.</li>
-</ol>
- <h3>Q: How can I save my progress and resume it later in Tekken 3 on my android device?</h3>
-<p>A: To save your progress and resume it later in Tekken 3 on your android device, you need to follow these steps:</p>
-<ol>
-<li>Launch the game and go to the main menu.</li> <li>Select save and then select a slot to save your game data.</li>
-<li>You can also select load to load your game data from a previously saved slot.</li>
-<li>You can also select auto save to enable or disable the automatic saving feature.</li>
-<li>Exit the save menu and resume playing the game.</li>
-</ol>
- <h3>Q: How can I unlock new characters in Tekken 3 on my android device?</h3>
-<p>A: To unlock new characters in Tekken 3 on your android device, you need to complete certain tasks or modes in the game. Here are some of the ways to unlock new characters:</p>
-<ul>
-<li>Complete arcade mode with any character to unlock a new character. Repeat this process until you unlock all the characters.</li>
-<li>Complete Tekken Force mode four times with any character to unlock Dr. Bosconovitch.</li>
-<li>Complete Tekken Ball mode with any character to unlock Gon.</li>
-<li>Complete arcade mode with Jin and Heihachi to unlock Ogre and True Ogre.</li>
-</ul>
- <h3>Q: How can I play Tekken 3 online with other players on my android device?</h3>
-<p>A: To play Tekken 3 online with other players on your android device, you need to use an app called ePSXe. ePSXe is a PlayStation emulator that allows you to play PlayStation games on your android device. It also has an online multiplayer feature that allows you to play with other players around the world. Here are the steps to play Tekken 3 online with ePSXe:</p>
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-<li>Download and install Tekken 3 ISO file from a trusted source online.</li>
-<li>Launch ePSXe and select run game. Locate the Tekken 3 ISO file on your device storage and tap on it.</li>
-<li>Select multiplayer mode and then select online mode. You can either host a game or join a game hosted by another player.</li>
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-<p>Terjemahan Kitab Tanbihul Ghafilin Pdf Download 322DOWNLOAD --->>> =2sKygd. terjemahan kitab tanbihul ghafilin pdf download 322Download Terjemahan Kitab Tanbihul Ghofilin Pdf. terjemahan kitab tanbihul ghafilin pdf download 322Download Terjemahan Kitab Tanbihul Ghafilin Pdf Download. terjemahan kitab tanbihul ghafilin pdf download 322Download Terjemahan Kitab Tanbihul Ghafilin Pdf. terjemahan kitab tanbihul ghafilin pdf download 322Download Terjemahan Kitab Tanbihul Ghafilin Pdf Download. terjemahan kitab tanbihul ghafilin pdf download 322Download Terjemahan Kitab Tanbihul Ghafilin Pdf Download. terjemahan kitab tanbihul ghafilin pdf download 322Download Terjemahan Kitab Tanbihul Ghafilin Pdf Download. terjemahan kitab tanbihul ghafilin pdf download 322Download Terjemahan Kitab Tanbihul Ghafilin Pdf Download. terjemahan kitab tanbihul ghafilin pdf download 322download terjemahan kitab tanbihul ghafilin pdf download 322Download Terjemahan Kitab Tanbihul Ghafilin Pdf Download. terjemahan kitab tanbihul ghafilin pdf download 322Download Terjemahan Kitab Tanbihul Ghafilin Pdf Download. terjemahan kitab tanbihul ghafilin pdf download 322Download Terjemahan Kitab Tanbihul Ghafilin Pdf Download. terjemahan kitab tanbihul ghafilin pdf download 322Download Terjemahan Kitab Tanbihul Ghafilin Pdf Download. terjemahan kitab tanbihul ghafilin pdf download 322download terjemahan kitab tanbihul ghafilin pdf download 322Download Terjemahan Kitab Tanbihul Ghafilin Pdf Download. terjemahan kitab tanbihul ghafilin pdf download 322Download Terjemahan Kitab Tanbihul Ghaf ee730c9e81 -professional-pro-42031708-crack -scia-engineer-v-crack-29 -nuggets-palo-alto-networks-firewall -macovei/karnan-story-in-malayalam-pdf-13</p>
-<h2>download terjemahan tanbihul ghafilin pdf file</h2><br /><p><b><b>Download Zip</b> &#9733; <a href="https://ssurll.com/2uzxNI">https://ssurll.com/2uzxNI</a></b></p><br /><br /> aaccfb2cb3<br />
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diff --git a/spaces/contluForse/HuggingGPT/assets/Electra2vst[REPACK] Cracksites.md b/spaces/contluForse/HuggingGPT/assets/Electra2vst[REPACK] Cracksites.md
deleted file mode 100644
index 174e0461d8389bbd9e31dea1a7cc6fe549b50632..0000000000000000000000000000000000000000
--- a/spaces/contluForse/HuggingGPT/assets/Electra2vst[REPACK] Cracksites.md	
+++ /dev/null
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-<h2>electra2vstcracksites</h2><br /><p><b><b>Download Zip</b> &#10038; <a href="https://ssurll.com/2uzymG">https://ssurll.com/2uzymG</a></b></p><br /><br />
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-cheme | deviantart.com |  |  |  |  |  |  |  |  |  and clinical determinants of poor health-related quality of life in multiple sclerosis: results from the Italian national survey of multiple sclerosis.
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diff --git a/spaces/contluForse/HuggingGPT/assets/Electronic Communication Systems Fifth Edition Solutions Manual Wayne Tomasi.rar.md b/spaces/contluForse/HuggingGPT/assets/Electronic Communication Systems Fifth Edition Solutions Manual Wayne Tomasi.rar.md
deleted file mode 100644
index 8bebe8c92bf0c42646b0bd87dda83858dca065fb..0000000000000000000000000000000000000000
--- a/spaces/contluForse/HuggingGPT/assets/Electronic Communication Systems Fifth Edition Solutions Manual Wayne Tomasi.rar.md	
+++ /dev/null
@@ -1,13 +0,0 @@
-
-<h1>Electronic Communication Systems: A Comprehensive Guide by Wayne Tomasi</h1>
-<p>Electronic communication systems are devices and systems that transmit and receive information using electromagnetic signals. They are used for various purposes, such as telephony, radio, television, data transmission, satellite communication, and wireless networking. Electronic communication systems can be classified into analog and digital systems, depending on the type of modulation and demodulation techniques used to encode and decode the information.</p>
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-<p>One of the most popular and authoritative books on electronic communication systems is <strong>Electronic Communication Systems: Fundamentals Through Advanced</strong> by Wayne Tomasi. This book provides a comprehensive and modern coverage of the field of digital communications, as well as a solid foundation in the principles of analog communications. The book covers topics such as signal analysis and mixing, oscillators, phase-locked loops, frequency synthesizers, amplitude modulation, single-sideband communications, angle modulation, digital modulation, digital transmission, optical fiber transmission, electromagnetic wave propagation, antennas and waveguides, telephone systems, cellular systems, data communications and networking, microwave radio communications, satellite communications, and more. The book also includes numerous examples, problems, and exercises to help students master the concepts and applications of electronic communication systems.</p>
-<p>The book is suitable for undergraduate and graduate students of electrical engineering, electronics engineering, and communication engineering. It is also a valuable reference for professionals and practitioners in the field of electronic communication systems.</p><p>The following is a continuation of the article:</p>
-<p></p>
-<p><strong>Chapter 5: Digital Modulation</strong></p>
-<p>Digital modulation is the process of converting digital data into analog signals that can be transmitted over a communication channel. Digital modulation techniques can be classified into two main categories: amplitude shift keying (ASK), and angle shift keying (ASK). ASK techniques vary the amplitude of a carrier signal according to the digital data, while ASK techniques vary the phase or frequency of a carrier signal according to the digital data. Some of the common ASK techniques are on-off keying (OOK), amplitude modulation (AM), and quadrature amplitude modulation (QAM). Some of the common ASK techniques are binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), frequency shift keying (FSK), and minimum shift keying (MSK).</p>
-<p>The advantages of digital modulation over analog modulation are higher noise immunity, higher spectral efficiency, higher data rate, and easier implementation. However, digital modulation also has some disadvantages, such as higher bandwidth requirement, higher power consumption, and higher complexity. The choice of a suitable digital modulation technique depends on various factors, such as the channel characteristics, the data rate, the bit error rate, the power efficiency, and the cost.</p>
-<p>The book explains the principles and applications of various digital modulation techniques in detail. It also discusses the performance analysis of digital modulation systems in terms of bit error rate, signal-to-noise ratio, bandwidth efficiency, and power efficiency. The book also introduces some advanced topics in digital modulation, such as orthogonal frequency division multiplexing (OFDM), spread spectrum modulation, and multiple-input multiple-output (MIMO) systems.</p> d5da3c52bf<br />
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diff --git a/spaces/cynika/taffy/preprocess_flist_config.py b/spaces/cynika/taffy/preprocess_flist_config.py
deleted file mode 100644
index 927dea890c0057063080b48edc6dd8c2588c6e27..0000000000000000000000000000000000000000
--- a/spaces/cynika/taffy/preprocess_flist_config.py
+++ /dev/null
@@ -1,117 +0,0 @@
-import os
-import argparse
-from tqdm import tqdm
-from random import shuffle
-import json
-config_template = {
-  "train": {
-    "log_interval": 200,
-    "eval_interval": 1000,
-    "seed": 1234,
-    "epochs": 10000,
-    "learning_rate": 2e-4,
-    "betas": [0.8, 0.99],
-    "eps": 1e-9,
-    "batch_size": 12,
-    "fp16_run": False,
-    "lr_decay": 0.999875,
-    "segment_size": 17920,
-    "init_lr_ratio": 1,
-    "warmup_epochs": 0,
-    "c_mel": 45,
-    "c_kl": 1.0,
-    "use_sr": True,
-    "max_speclen": 384,
-    "port": "8001"
-  },
-  "data": {
-    "training_files":"filelists/train.txt",
-    "validation_files":"filelists/val.txt",
-    "max_wav_value": 32768.0,
-    "sampling_rate": 32000,
-    "filter_length": 1280,
-    "hop_length": 320,
-    "win_length": 1280,
-    "n_mel_channels": 80,
-    "mel_fmin": 0.0,
-    "mel_fmax": None
-  },
-  "model": {
-    "inter_channels": 192,
-    "hidden_channels": 192,
-    "filter_channels": 768,
-    "n_heads": 2,
-    "n_layers": 6,
-    "kernel_size": 3,
-    "p_dropout": 0.1,
-    "resblock": "1",
-    "resblock_kernel_sizes": [3,7,11],
-    "resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]],
-    "upsample_rates": [10,8,2,2],
-    "upsample_initial_channel": 512,
-    "upsample_kernel_sizes": [16,16,4,4],
-    "n_layers_q": 3,
-    "use_spectral_norm": False,
-    "gin_channels": 256,
-    "ssl_dim": 256,
-    "n_speakers": 0,
-  },
-  "spk":{
-    "nen": 0,
-    "paimon": 1,
-    "yunhao": 2
-  }
-}
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--train_list", type=str, default="./filelists/train.txt", help="path to train list")
-    parser.add_argument("--val_list", type=str, default="./filelists/val.txt", help="path to val list")
-    parser.add_argument("--test_list", type=str, default="./filelists/test.txt", help="path to test list")
-    parser.add_argument("--source_dir", type=str, default="./dataset/32k", help="path to source dir")
-    args = parser.parse_args()
-    
-    train = []
-    val = []
-    test = []
-    idx = 0
-    spk_dict = {}
-    spk_id = 0
-    for speaker in tqdm(os.listdir(args.source_dir)):
-        spk_dict[speaker] = spk_id
-        spk_id += 1
-        wavs = [os.path.join(args.source_dir, speaker, i)for i in os.listdir(os.path.join(args.source_dir, speaker))]
-        wavs = [i for i in wavs if i.endswith("wav")]
-        shuffle(wavs)
-        train += wavs[2:-10]
-        val += wavs[:2]
-        test += wavs[-10:]
-    n_speakers = len(spk_dict.keys())*2
-    shuffle(train)
-    shuffle(val)
-    shuffle(test)
-            
-    print("Writing", args.train_list)
-    with open(args.train_list, "w") as f:
-        for fname in tqdm(train):
-            wavpath = fname
-            f.write(wavpath + "\n")
-        
-    print("Writing", args.val_list)
-    with open(args.val_list, "w") as f:
-        for fname in tqdm(val):
-            wavpath = fname
-            f.write(wavpath + "\n")
-            
-    print("Writing", args.test_list)
-    with open(args.test_list, "w") as f:
-        for fname in tqdm(test):
-            wavpath = fname
-            f.write(wavpath + "\n")
-
-    config_template["model"]["n_speakers"] = n_speakers
-    config_template["spk"] = spk_dict
-    print("Writing configs/config.json")
-    with open("configs/config.json", "w") as f:
-        json.dump(config_template, f, indent=2)
diff --git a/spaces/dawdqd/ChuanhuChatGPT/web_assets/javascript/utils.js b/spaces/dawdqd/ChuanhuChatGPT/web_assets/javascript/utils.js
deleted file mode 100644
index cda208a085be790cca1cf1a18bba27550caeca30..0000000000000000000000000000000000000000
--- a/spaces/dawdqd/ChuanhuChatGPT/web_assets/javascript/utils.js
+++ /dev/null
@@ -1,83 +0,0 @@
-
-var gradioUploader = null;
-
-function testUpload(target) {
-    gradioUploader = gradioApp().querySelector("#upload-index-file > .center.flex");
-    let uploaderEvents = ["click", "drag", "dragend", "dragenter", "dragleave", "dragover", "dragstart", "drop"];
-    transEventListeners(target, gradioUploader, uploaderEvents);
-}
-
-
-function transEventListeners(target, source, events) {
-    events.forEach((sourceEvent) => {
-        target.addEventListener(sourceEvent, function (targetEvent) {
-            if(targetEvent.preventDefault) targetEvent.preventDefault();
-            if(targetEvent.stopPropagation) targetEvent.stopPropagation();
-
-            source.dispatchEvent(new Event(sourceEvent, {detail: targetEvent.detail}));
-            console.log(targetEvent.detail);
-        });
-    });
-}
-
-
-function isImgUrl(url) {
-    const imageExtensions = /\.(jpg|jpeg|png|gif|bmp|webp)$/i;
-    if (url.startsWith('data:image/')) {
-        return true;
-    }
-    if (url.match(imageExtensions)) {
-        return true;
-    }
-    if (url.startsWith('http://') || url.startsWith('https://')) {
-        return true;
-    }
-
-    return false;
-}
-
-
-/* NOTE: These reload functions are not used in the current version of the code.
- *       From stable-diffusion-webui
- */
-function restart_reload() {
-    document.body.innerHTML = '<h1 style="font-family:ui-monospace,monospace;margin-top:20%;color:lightgray;text-align:center;">Reloading...</h1>';
-
-    var requestPing = function () {
-        requestGet("./internal/ping", {}, function (data) {
-            location.reload();
-        }, function () {
-            setTimeout(requestPing, 500);
-        });
-    };
-
-    setTimeout(requestPing, 2000);
-
-    return [];
-}
-
-function requestGet(url, data, handler, errorHandler) {
-    var xhr = new XMLHttpRequest();
-    var args = Object.keys(data).map(function (k) {
-        return encodeURIComponent(k) + '=' + encodeURIComponent(data[k]);
-    }).join('&');
-    xhr.open("GET", url + "?" + args, true);
-
-    xhr.onreadystatechange = function () {
-        if (xhr.readyState === 4) {
-            if (xhr.status === 200) {
-                try {
-                    var js = JSON.parse(xhr.responseText);
-                    handler(js);
-                } catch (error) {
-                    console.error(error);
-                    errorHandler();
-                }
-            } else {
-                errorHandler();
-            }
-        }
-    };
-    var js = JSON.stringify(data);
-    xhr.send(js);
-}
diff --git a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/fontTools/colorLib/__init__.py b/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/fontTools/colorLib/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/markdown_it/rules_inline/link.py b/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/markdown_it/rules_inline/link.py
deleted file mode 100644
index 78cf9122f3b4ad740769cb7edd3e4cc49af46e00..0000000000000000000000000000000000000000
--- a/spaces/dcarpintero/nlp-summarizer-pegasus/.venv/lib/python3.9/site-packages/markdown_it/rules_inline/link.py
+++ /dev/null
@@ -1,151 +0,0 @@
-# Process [link](<to> "stuff")
-
-from ..common.utils import isStrSpace, normalizeReference
-from .state_inline import StateInline
-
-
-def link(state: StateInline, silent: bool) -> bool:
-    href = ""
-    title = ""
-    label = None
-    oldPos = state.pos
-    maximum = state.posMax
-    start = state.pos
-    parseReference = True
-
-    if state.src[state.pos] != "[":
-        return False
-
-    labelStart = state.pos + 1
-    labelEnd = state.md.helpers.parseLinkLabel(state, state.pos, True)
-
-    # parser failed to find ']', so it's not a valid link
-    if labelEnd < 0:
-        return False
-
-    pos = labelEnd + 1
-
-    if pos < maximum and state.src[pos] == "(":
-        #
-        # Inline link
-        #
-
-        # might have found a valid shortcut link, disable reference parsing
-        parseReference = False
-
-        # [link](  <href>  "title"  )
-        #        ^^ skipping these spaces
-        pos += 1
-        while pos < maximum:
-            ch = state.src[pos]
-            if not isStrSpace(ch) and ch != "\n":
-                break
-            pos += 1
-
-        if pos >= maximum:
-            return False
-
-        # [link](  <href>  "title"  )
-        #          ^^^^^^ parsing link destination
-        start = pos
-        res = state.md.helpers.parseLinkDestination(state.src, pos, state.posMax)
-        if res.ok:
-            href = state.md.normalizeLink(res.str)
-            if state.md.validateLink(href):
-                pos = res.pos
-            else:
-                href = ""
-
-            # [link](  <href>  "title"  )
-            #                ^^ skipping these spaces
-            start = pos
-            while pos < maximum:
-                ch = state.src[pos]
-                if not isStrSpace(ch) and ch != "\n":
-                    break
-                pos += 1
-
-            # [link](  <href>  "title"  )
-            #                  ^^^^^^^ parsing link title
-            res = state.md.helpers.parseLinkTitle(state.src, pos, state.posMax)
-            if pos < maximum and start != pos and res.ok:
-                title = res.str
-                pos = res.pos
-
-                # [link](  <href>  "title"  )
-                #                         ^^ skipping these spaces
-                while pos < maximum:
-                    ch = state.src[pos]
-                    if not isStrSpace(ch) and ch != "\n":
-                        break
-                    pos += 1
-
-        if pos >= maximum or state.src[pos] != ")":
-            # parsing a valid shortcut link failed, fallback to reference
-            parseReference = True
-
-        pos += 1
-
-    if parseReference:
-        #
-        # Link reference
-        #
-        if "references" not in state.env:
-            return False
-
-        if pos < maximum and state.src[pos] == "[":
-            start = pos + 1
-            pos = state.md.helpers.parseLinkLabel(state, pos)
-            if pos >= 0:
-                label = state.src[start:pos]
-                pos += 1
-            else:
-                pos = labelEnd + 1
-
-        else:
-            pos = labelEnd + 1
-
-        # covers label == '' and label == undefined
-        # (collapsed reference link and shortcut reference link respectively)
-        if not label:
-            label = state.src[labelStart:labelEnd]
-
-        label = normalizeReference(label)
-
-        ref = (
-            state.env["references"][label] if label in state.env["references"] else None
-        )
-        if not ref:
-            state.pos = oldPos
-            return False
-
-        href = ref["href"]
-        title = ref["title"]
-
-    #
-    # We found the end of the link, and know for a fact it's a valid link
-    # so all that's left to do is to call tokenizer.
-    #
-    if not silent:
-        state.pos = labelStart
-        state.posMax = labelEnd
-
-        token = state.push("link_open", "a", 1)
-        token.attrs = {"href": href}
-
-        if title:
-            token.attrSet("title", title)
-
-        # note, this is not part of markdown-it JS, but is useful for renderers
-        if label and state.md.options.get("store_labels", False):
-            token.meta["label"] = label
-
-        state.linkLevel += 1
-        state.md.inline.tokenize(state)
-        state.linkLevel -= 1
-
-        token = state.push("link_close", "a", -1)
-
-    state.pos = pos
-    state.posMax = maximum
-    return True
diff --git a/spaces/declare-lab/tango/diffusers/tests/pipelines/stable_diffusion/test_onnx_stable_diffusion_img2img.py b/spaces/declare-lab/tango/diffusers/tests/pipelines/stable_diffusion/test_onnx_stable_diffusion_img2img.py
deleted file mode 100644
index e1aa2f6dc0a1641f217f0b20ef93d2f82cf15140..0000000000000000000000000000000000000000
--- a/spaces/declare-lab/tango/diffusers/tests/pipelines/stable_diffusion/test_onnx_stable_diffusion_img2img.py
+++ /dev/null
@@ -1,245 +0,0 @@
-# coding=utf-8
-# Copyright 2023 HuggingFace Inc.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import random
-import unittest
-
-import numpy as np
-
-from diffusers import (
-    DPMSolverMultistepScheduler,
-    EulerAncestralDiscreteScheduler,
-    EulerDiscreteScheduler,
-    LMSDiscreteScheduler,
-    OnnxStableDiffusionImg2ImgPipeline,
-    PNDMScheduler,
-)
-from diffusers.utils import floats_tensor
-from diffusers.utils.testing_utils import (
-    is_onnx_available,
-    load_image,
-    nightly,
-    require_onnxruntime,
-    require_torch_gpu,
-)
-
-from ...test_pipelines_onnx_common import OnnxPipelineTesterMixin
-
-
-if is_onnx_available():
-    import onnxruntime as ort
-
-
-class OnnxStableDiffusionImg2ImgPipelineFastTests(OnnxPipelineTesterMixin, unittest.TestCase):
-    hub_checkpoint = "hf-internal-testing/tiny-random-OnnxStableDiffusionPipeline"
-
-    def get_dummy_inputs(self, seed=0):
-        image = floats_tensor((1, 3, 128, 128), rng=random.Random(seed))
-        generator = np.random.RandomState(seed)
-        inputs = {
-            "prompt": "A painting of a squirrel eating a burger",
-            "image": image,
-            "generator": generator,
-            "num_inference_steps": 3,
-            "strength": 0.75,
-            "guidance_scale": 7.5,
-            "output_type": "numpy",
-        }
-        return inputs
-
-    def test_pipeline_default_ddim(self):
-        pipe = OnnxStableDiffusionImg2ImgPipeline.from_pretrained(self.hub_checkpoint, provider="CPUExecutionProvider")
-        pipe.set_progress_bar_config(disable=None)
-
-        inputs = self.get_dummy_inputs()
-        image = pipe(**inputs).images
-        image_slice = image[0, -3:, -3:, -1].flatten()
-
-        assert image.shape == (1, 128, 128, 3)
-        expected_slice = np.array([0.69643, 0.58484, 0.50314, 0.58760, 0.55368, 0.59643, 0.51529, 0.41217, 0.49087])
-        assert np.abs(image_slice - expected_slice).max() < 1e-1
-
-    def test_pipeline_pndm(self):
-        pipe = OnnxStableDiffusionImg2ImgPipeline.from_pretrained(self.hub_checkpoint, provider="CPUExecutionProvider")
-        pipe.scheduler = PNDMScheduler.from_config(pipe.scheduler.config, skip_prk_steps=True)
-        pipe.set_progress_bar_config(disable=None)
-
-        inputs = self.get_dummy_inputs()
-        image = pipe(**inputs).images
-        image_slice = image[0, -3:, -3:, -1]
-
-        assert image.shape == (1, 128, 128, 3)
-        expected_slice = np.array([0.61737, 0.54642, 0.53183, 0.54465, 0.52742, 0.60525, 0.49969, 0.40655, 0.48154])
-
-        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-1
-
-    def test_pipeline_lms(self):
-        pipe = OnnxStableDiffusionImg2ImgPipeline.from_pretrained(self.hub_checkpoint, provider="CPUExecutionProvider")
-        pipe.scheduler = LMSDiscreteScheduler.from_config(pipe.scheduler.config)
-        pipe.set_progress_bar_config(disable=None)
-
-        # warmup pass to apply optimizations
-        _ = pipe(**self.get_dummy_inputs())
-
-        inputs = self.get_dummy_inputs()
-        image = pipe(**inputs).images
-        image_slice = image[0, -3:, -3:, -1]
-
-        assert image.shape == (1, 128, 128, 3)
-        expected_slice = np.array([0.52761, 0.59977, 0.49033, 0.49619, 0.54282, 0.50311, 0.47600, 0.40918, 0.45203])
-
-        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-1
-
-    def test_pipeline_euler(self):
-        pipe = OnnxStableDiffusionImg2ImgPipeline.from_pretrained(self.hub_checkpoint, provider="CPUExecutionProvider")
-        pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config)
-        pipe.set_progress_bar_config(disable=None)
-
-        inputs = self.get_dummy_inputs()
-        image = pipe(**inputs).images
-        image_slice = image[0, -3:, -3:, -1]
-
-        assert image.shape == (1, 128, 128, 3)
-        expected_slice = np.array([0.52911, 0.60004, 0.49229, 0.49805, 0.54502, 0.50680, 0.47777, 0.41028, 0.45304])
-
-        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-1
-
-    def test_pipeline_euler_ancestral(self):
-        pipe = OnnxStableDiffusionImg2ImgPipeline.from_pretrained(self.hub_checkpoint, provider="CPUExecutionProvider")
-        pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
-        pipe.set_progress_bar_config(disable=None)
-
-        inputs = self.get_dummy_inputs()
-        image = pipe(**inputs).images
-        image_slice = image[0, -3:, -3:, -1]
-
-        assert image.shape == (1, 128, 128, 3)
-        expected_slice = np.array([0.52911, 0.60004, 0.49229, 0.49805, 0.54502, 0.50680, 0.47777, 0.41028, 0.45304])
-
-        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-1
-
-    def test_pipeline_dpm_multistep(self):
-        pipe = OnnxStableDiffusionImg2ImgPipeline.from_pretrained(self.hub_checkpoint, provider="CPUExecutionProvider")
-        pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
-        pipe.set_progress_bar_config(disable=None)
-
-        inputs = self.get_dummy_inputs()
-        image = pipe(**inputs).images
-        image_slice = image[0, -3:, -3:, -1]
-
-        assert image.shape == (1, 128, 128, 3)
-        expected_slice = np.array([0.65331, 0.58277, 0.48204, 0.56059, 0.53665, 0.56235, 0.50969, 0.40009, 0.46552])
-
-        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-1
-
-
-@nightly
-@require_onnxruntime
-@require_torch_gpu
-class OnnxStableDiffusionImg2ImgPipelineIntegrationTests(unittest.TestCase):
-    @property
-    def gpu_provider(self):
-        return (
-            "CUDAExecutionProvider",
-            {
-                "gpu_mem_limit": "15000000000",  # 15GB
-                "arena_extend_strategy": "kSameAsRequested",
-            },
-        )
-
-    @property
-    def gpu_options(self):
-        options = ort.SessionOptions()
-        options.enable_mem_pattern = False
-        return options
-
-    def test_inference_default_pndm(self):
-        init_image = load_image(
-            "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
-            "/img2img/sketch-mountains-input.jpg"
-        )
-        init_image = init_image.resize((768, 512))
-        # using the PNDM scheduler by default
-        pipe = OnnxStableDiffusionImg2ImgPipeline.from_pretrained(
-            "CompVis/stable-diffusion-v1-4",
-            revision="onnx",
-            safety_checker=None,
-            feature_extractor=None,
-            provider=self.gpu_provider,
-            sess_options=self.gpu_options,
-        )
-        pipe.set_progress_bar_config(disable=None)
-
-        prompt = "A fantasy landscape, trending on artstation"
-
-        generator = np.random.RandomState(0)
-        output = pipe(
-            prompt=prompt,
-            image=init_image,
-            strength=0.75,
-            guidance_scale=7.5,
-            num_inference_steps=10,
-            generator=generator,
-            output_type="np",
-        )
-        images = output.images
-        image_slice = images[0, 255:258, 383:386, -1]
-
-        assert images.shape == (1, 512, 768, 3)
-        expected_slice = np.array([0.4909, 0.5059, 0.5372, 0.4623, 0.4876, 0.5049, 0.4820, 0.4956, 0.5019])
-        # TODO: lower the tolerance after finding the cause of onnxruntime reproducibility issues
-
-        assert np.abs(image_slice.flatten() - expected_slice).max() < 2e-2
-
-    def test_inference_k_lms(self):
-        init_image = load_image(
-            "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
-            "/img2img/sketch-mountains-input.jpg"
-        )
-        init_image = init_image.resize((768, 512))
-        lms_scheduler = LMSDiscreteScheduler.from_pretrained(
-            "runwayml/stable-diffusion-v1-5", subfolder="scheduler", revision="onnx"
-        )
-        pipe = OnnxStableDiffusionImg2ImgPipeline.from_pretrained(
-            "runwayml/stable-diffusion-v1-5",
-            revision="onnx",
-            scheduler=lms_scheduler,
-            safety_checker=None,
-            feature_extractor=None,
-            provider=self.gpu_provider,
-            sess_options=self.gpu_options,
-        )
-        pipe.set_progress_bar_config(disable=None)
-
-        prompt = "A fantasy landscape, trending on artstation"
-
-        generator = np.random.RandomState(0)
-        output = pipe(
-            prompt=prompt,
-            image=init_image,
-            strength=0.75,
-            guidance_scale=7.5,
-            num_inference_steps=20,
-            generator=generator,
-            output_type="np",
-        )
-        images = output.images
-        image_slice = images[0, 255:258, 383:386, -1]
-
-        assert images.shape == (1, 512, 768, 3)
-        expected_slice = np.array([0.8043, 0.926, 0.9581, 0.8119, 0.8954, 0.913, 0.7209, 0.7463, 0.7431])
-        # TODO: lower the tolerance after finding the cause of onnxruntime reproducibility issues
-
-        assert np.abs(image_slice.flatten() - expected_slice).max() < 2e-2
diff --git a/spaces/deepwisdom/MetaGPT/metagpt/const.py b/spaces/deepwisdom/MetaGPT/metagpt/const.py
deleted file mode 100644
index fbc2c928a14b0b5770b266dd79b02b2c7814880a..0000000000000000000000000000000000000000
--- a/spaces/deepwisdom/MetaGPT/metagpt/const.py
+++ /dev/null
@@ -1,59 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-"""
-@Time    : 2023/5/1 11:59
-@Author  : alexanderwu
-@File    : const.py'
-@Modified By: mashenquan, 2023/8/28. Add 'OPTIONS', 'DEFAULT_LANGUAGE', 'DEFAULT_MAX_TOKENS'...
-"""
-import contextvars
-from pathlib import Path
-
-
-def get_project_root():
-    """逐级向上寻找项目根目录"""
-    current_path = Path.cwd()
-    while True:
-        if (
-            (current_path / ".git").exists()
-            or (current_path / ".project_root").exists()
-            or (current_path / ".gitignore").exists()
-        ):
-            return current_path
-        parent_path = current_path.parent
-        if parent_path == current_path:
-            raise Exception("Project root not found.")
-        current_path = parent_path
-
-
-PROJECT_ROOT = get_project_root()
-DATA_PATH = PROJECT_ROOT / "data"
-WORKSPACE_ROOT = PROJECT_ROOT / "workspace"
-PROMPT_PATH = PROJECT_ROOT / "metagpt/prompts"
-UT_PATH = PROJECT_ROOT / "data/ut"
-SWAGGER_PATH = UT_PATH / "files/api/"
-UT_PY_PATH = UT_PATH / "files/ut/"
-API_QUESTIONS_PATH = UT_PATH / "files/question/"
-YAPI_URL = "http://yapi.deepwisdomai.com/"
-TMP = PROJECT_ROOT / "tmp"
-RESEARCH_PATH = DATA_PATH / "research"
-
-MEM_TTL = 24 * 30 * 3600
-
-OPTIONS = contextvars.ContextVar("OPTIONS")
-DEFAULT_LANGUAGE = "English"
-DEFAULT_MAX_TOKENS = 1500
-COMMAND_TOKENS = 500
-BRAIN_MEMORY = "BRAIN_MEMORY"
-SKILL_PATH = "SKILL_PATH"
-SERPER_API_KEY = "SERPER_API_KEY"
-
-# Key Definitions for MetaGPT LLM
-METAGPT_API_MODEL = "METAGPT_API_MODEL"
-METAGPT_API_KEY = "METAGPT_API_KEY"
-METAGPT_API_BASE = "METAGPT_API_BASE"
-METAGPT_API_TYPE = "METAGPT_API_TYPE"
-METAGPT_API_VERSION = "METAGPT_API_VERSION"
-
-# format
-BASE64_FORMAT = "base64"
diff --git a/spaces/diacanFperku/AutoGPT/Andhera Ujala Ptv Drama All Episodes.md b/spaces/diacanFperku/AutoGPT/Andhera Ujala Ptv Drama All Episodes.md
deleted file mode 100644
index 6bb2e849192bc50f45be8dcc26de3a5087eddc77..0000000000000000000000000000000000000000
--- a/spaces/diacanFperku/AutoGPT/Andhera Ujala Ptv Drama All Episodes.md	
+++ /dev/null
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diff --git a/spaces/diacanFperku/AutoGPT/Descargar Parche Para Icon Packager Crack LINK 16.md b/spaces/diacanFperku/AutoGPT/Descargar Parche Para Icon Packager Crack LINK 16.md
deleted file mode 100644
index 0e091d92917c017a95e7d7eeb43a11909cbf2368..0000000000000000000000000000000000000000
--- a/spaces/diacanFperku/AutoGPT/Descargar Parche Para Icon Packager Crack LINK 16.md	
+++ /dev/null
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diff --git a/spaces/diacanFperku/AutoGPT/Flatout 2 Split Screen Pc Mod 41.md b/spaces/diacanFperku/AutoGPT/Flatout 2 Split Screen Pc Mod 41.md
deleted file mode 100644
index 3a5a196a1684ec36d50780f74a601de31ee43e84..0000000000000000000000000000000000000000
--- a/spaces/diacanFperku/AutoGPT/Flatout 2 Split Screen Pc Mod 41.md	
+++ /dev/null
@@ -1,11 +0,0 @@
-
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diff --git a/spaces/diacanFperku/AutoGPT/Guitar Speed Trainer Pro 2.3.8.4 Portable Full Version REPACK.md b/spaces/diacanFperku/AutoGPT/Guitar Speed Trainer Pro 2.3.8.4 Portable Full Version REPACK.md
deleted file mode 100644
index 3e0717c6f6d68a5358a61a04f89e8dac11d98d30..0000000000000000000000000000000000000000
--- a/spaces/diacanFperku/AutoGPT/Guitar Speed Trainer Pro 2.3.8.4 Portable Full Version REPACK.md	
+++ /dev/null
@@ -1,7 +0,0 @@
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diff --git a/spaces/diacanFperku/AutoGPT/Miracle In Cell No 7 Eng Sub Full Movie ((NEW)).md b/spaces/diacanFperku/AutoGPT/Miracle In Cell No 7 Eng Sub Full Movie ((NEW)).md
deleted file mode 100644
index 0d531a6a03a89023da1846b7bdb9e3a21e9303ea..0000000000000000000000000000000000000000
--- a/spaces/diacanFperku/AutoGPT/Miracle In Cell No 7 Eng Sub Full Movie ((NEW)).md	
+++ /dev/null
@@ -1,51 +0,0 @@
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diff --git a/spaces/diacanFperku/AutoGPT/Nenjirukkum Varai Tamil Full Movie Free Download [WORK].md b/spaces/diacanFperku/AutoGPT/Nenjirukkum Varai Tamil Full Movie Free Download [WORK].md
deleted file mode 100644
index 3e5238a562ba1718a8b88ae5fedb955d814fce27..0000000000000000000000000000000000000000
--- a/spaces/diacanFperku/AutoGPT/Nenjirukkum Varai Tamil Full Movie Free Download [WORK].md	
+++ /dev/null
@@ -1,7 +0,0 @@
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diff --git a/spaces/diacanFperku/AutoGPT/Pokoli Szomszedok 2 Full Valtozat.md b/spaces/diacanFperku/AutoGPT/Pokoli Szomszedok 2 Full Valtozat.md
deleted file mode 100644
index 1d03b9aeeed67206d25e05cf452725b9f1639bf3..0000000000000000000000000000000000000000
--- a/spaces/diacanFperku/AutoGPT/Pokoli Szomszedok 2 Full Valtozat.md	
+++ /dev/null
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-<p>Abban nem kellett tl sok kijelzvel meg ktyvel bajldni. Nem mkdtt benne prhuzamos. konyvekkozt 2 months ago. Text. Tumblr media. kivl volt a tegnapi napom,. nem a pokoli szomszdok jtk. Nagyon fontos, hogy megtudjam mert rohadtul. </p>
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-<p>whymil f4bc01c98b https://coub.com/stories/3356817-__full__-suite-spot-studios-aatranslator-extended-v4-0-0-2. Pokoli Szomszedok 2 Full Valtozat nem a pokoli szomszdok jtk. Nagyon fontos, hogy megtudjam mert rohadtul. </p>
-<p></p> 899543212b<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/digitalxingtong/Azusa-Bert-VITS2/README_zh.md b/spaces/digitalxingtong/Azusa-Bert-VITS2/README_zh.md
deleted file mode 100644
index 8b137891791fe96927ad78e64b0aad7bded08bdc..0000000000000000000000000000000000000000
--- a/spaces/digitalxingtong/Azusa-Bert-VITS2/README_zh.md
+++ /dev/null
@@ -1 +0,0 @@
-
diff --git a/spaces/digitalxingtong/Bufeiyan-a-Bert-VITS2/modules.py b/spaces/digitalxingtong/Bufeiyan-a-Bert-VITS2/modules.py
deleted file mode 100644
index 92e0f32a51c472bfd1659a50a95a95d195281d2b..0000000000000000000000000000000000000000
--- a/spaces/digitalxingtong/Bufeiyan-a-Bert-VITS2/modules.py
+++ /dev/null
@@ -1,452 +0,0 @@
-import copy
-import math
-import numpy as np
-import scipy
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
-from torch.nn.utils import weight_norm, remove_weight_norm
-
-import commons
-from commons import init_weights, get_padding
-from transforms import piecewise_rational_quadratic_transform
-from attentions import Encoder
-
-LRELU_SLOPE = 0.1
-
-class LayerNorm(nn.Module):
-  def __init__(self, channels, eps=1e-5):
-    super().__init__()
-    self.channels = channels
-    self.eps = eps
-
-    self.gamma = nn.Parameter(torch.ones(channels))
-    self.beta = nn.Parameter(torch.zeros(channels))
-
-  def forward(self, x):
-    x = x.transpose(1, -1)
-    x = F.layer_norm(x, (self.channels,), self.gamma, self.beta, self.eps)
-    return x.transpose(1, -1)
-    
-class ConvReluNorm(nn.Module):
-  def __init__(self, in_channels, hidden_channels, out_channels, kernel_size, n_layers, p_dropout):
-    super().__init__()
-    self.in_channels = in_channels
-    self.hidden_channels = hidden_channels
-    self.out_channels = out_channels
-    self.kernel_size = kernel_size
-    self.n_layers = n_layers
-    self.p_dropout = p_dropout
-    assert n_layers > 1, "Number of layers should be larger than 0."
-
-    self.conv_layers = nn.ModuleList()
-    self.norm_layers = nn.ModuleList()
-    self.conv_layers.append(nn.Conv1d(in_channels, hidden_channels, kernel_size, padding=kernel_size//2))
-    self.norm_layers.append(LayerNorm(hidden_channels))
-    self.relu_drop = nn.Sequential(
-        nn.ReLU(),
-        nn.Dropout(p_dropout))
-    for _ in range(n_layers-1):
-      self.conv_layers.append(nn.Conv1d(hidden_channels, hidden_channels, kernel_size, padding=kernel_size//2))
-      self.norm_layers.append(LayerNorm(hidden_channels))
-    self.proj = nn.Conv1d(hidden_channels, out_channels, 1)
-    self.proj.weight.data.zero_()
-    self.proj.bias.data.zero_()
-
-  def forward(self, x, x_mask):
-    x_org = x
-    for i in range(self.n_layers):
-      x = self.conv_layers[i](x * x_mask)
-      x = self.norm_layers[i](x)
-      x = self.relu_drop(x)
-    x = x_org + self.proj(x)
-    return x * x_mask
-
-
-class DDSConv(nn.Module):
-  """
-  Dialted and Depth-Separable Convolution
-  """
-  def __init__(self, channels, kernel_size, n_layers, p_dropout=0.):
-    super().__init__()
-    self.channels = channels
-    self.kernel_size = kernel_size
-    self.n_layers = n_layers
-    self.p_dropout = p_dropout
-
-    self.drop = nn.Dropout(p_dropout)
-    self.convs_sep = nn.ModuleList()
-    self.convs_1x1 = nn.ModuleList()
-    self.norms_1 = nn.ModuleList()
-    self.norms_2 = nn.ModuleList()
-    for i in range(n_layers):
-      dilation = kernel_size ** i
-      padding = (kernel_size * dilation - dilation) // 2
-      self.convs_sep.append(nn.Conv1d(channels, channels, kernel_size, 
-          groups=channels, dilation=dilation, padding=padding
-      ))
-      self.convs_1x1.append(nn.Conv1d(channels, channels, 1))
-      self.norms_1.append(LayerNorm(channels))
-      self.norms_2.append(LayerNorm(channels))
-
-  def forward(self, x, x_mask, g=None):
-    if g is not None:
-      x = x + g
-    for i in range(self.n_layers):
-      y = self.convs_sep[i](x * x_mask)
-      y = self.norms_1[i](y)
-      y = F.gelu(y)
-      y = self.convs_1x1[i](y)
-      y = self.norms_2[i](y)
-      y = F.gelu(y)
-      y = self.drop(y)
-      x = x + y
-    return x * x_mask
-
-
-class WN(torch.nn.Module):
-  def __init__(self, hidden_channels, kernel_size, dilation_rate, n_layers, gin_channels=0, p_dropout=0):
-    super(WN, self).__init__()
-    assert(kernel_size % 2 == 1)
-    self.hidden_channels =hidden_channels
-    self.kernel_size = kernel_size,
-    self.dilation_rate = dilation_rate
-    self.n_layers = n_layers
-    self.gin_channels = gin_channels
-    self.p_dropout = p_dropout
-
-    self.in_layers = torch.nn.ModuleList()
-    self.res_skip_layers = torch.nn.ModuleList()
-    self.drop = nn.Dropout(p_dropout)
-
-    if gin_channels != 0:
-      cond_layer = torch.nn.Conv1d(gin_channels, 2*hidden_channels*n_layers, 1)
-      self.cond_layer = torch.nn.utils.weight_norm(cond_layer, name='weight')
-
-    for i in range(n_layers):
-      dilation = dilation_rate ** i
-      padding = int((kernel_size * dilation - dilation) / 2)
-      in_layer = torch.nn.Conv1d(hidden_channels, 2*hidden_channels, kernel_size,
-                                 dilation=dilation, padding=padding)
-      in_layer = torch.nn.utils.weight_norm(in_layer, name='weight')
-      self.in_layers.append(in_layer)
-
-      # last one is not necessary
-      if i < n_layers - 1:
-        res_skip_channels = 2 * hidden_channels
-      else:
-        res_skip_channels = hidden_channels
-
-      res_skip_layer = torch.nn.Conv1d(hidden_channels, res_skip_channels, 1)
-      res_skip_layer = torch.nn.utils.weight_norm(res_skip_layer, name='weight')
-      self.res_skip_layers.append(res_skip_layer)
-
-  def forward(self, x, x_mask, g=None, **kwargs):
-    output = torch.zeros_like(x)
-    n_channels_tensor = torch.IntTensor([self.hidden_channels])
-
-    if g is not None:
-      g = self.cond_layer(g)
-
-    for i in range(self.n_layers):
-      x_in = self.in_layers[i](x)
-      if g is not None:
-        cond_offset = i * 2 * self.hidden_channels
-        g_l = g[:,cond_offset:cond_offset+2*self.hidden_channels,:]
-      else:
-        g_l = torch.zeros_like(x_in)
-
-      acts = commons.fused_add_tanh_sigmoid_multiply(
-          x_in,
-          g_l,
-          n_channels_tensor)
-      acts = self.drop(acts)
-
-      res_skip_acts = self.res_skip_layers[i](acts)
-      if i < self.n_layers - 1:
-        res_acts = res_skip_acts[:,:self.hidden_channels,:]
-        x = (x + res_acts) * x_mask
-        output = output + res_skip_acts[:,self.hidden_channels:,:]
-      else:
-        output = output + res_skip_acts
-    return output * x_mask
-
-  def remove_weight_norm(self):
-    if self.gin_channels != 0:
-      torch.nn.utils.remove_weight_norm(self.cond_layer)
-    for l in self.in_layers:
-      torch.nn.utils.remove_weight_norm(l)
-    for l in self.res_skip_layers:
-     torch.nn.utils.remove_weight_norm(l)
-
-
-class ResBlock1(torch.nn.Module):
-    def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
-        super(ResBlock1, self).__init__()
-        self.convs1 = nn.ModuleList([
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[0],
-                               padding=get_padding(kernel_size, dilation[0]))),
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[1],
-                               padding=get_padding(kernel_size, dilation[1]))),
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[2],
-                               padding=get_padding(kernel_size, dilation[2])))
-        ])
-        self.convs1.apply(init_weights)
-
-        self.convs2 = nn.ModuleList([
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
-                               padding=get_padding(kernel_size, 1))),
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
-                               padding=get_padding(kernel_size, 1))),
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=1,
-                               padding=get_padding(kernel_size, 1)))
-        ])
-        self.convs2.apply(init_weights)
-
-    def forward(self, x, x_mask=None):
-        for c1, c2 in zip(self.convs1, self.convs2):
-            xt = F.leaky_relu(x, LRELU_SLOPE)
-            if x_mask is not None:
-                xt = xt * x_mask
-            xt = c1(xt)
-            xt = F.leaky_relu(xt, LRELU_SLOPE)
-            if x_mask is not None:
-                xt = xt * x_mask
-            xt = c2(xt)
-            x = xt + x
-        if x_mask is not None:
-            x = x * x_mask
-        return x
-
-    def remove_weight_norm(self):
-        for l in self.convs1:
-            remove_weight_norm(l)
-        for l in self.convs2:
-            remove_weight_norm(l)
-
-
-class ResBlock2(torch.nn.Module):
-    def __init__(self, channels, kernel_size=3, dilation=(1, 3)):
-        super(ResBlock2, self).__init__()
-        self.convs = nn.ModuleList([
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[0],
-                               padding=get_padding(kernel_size, dilation[0]))),
-            weight_norm(Conv1d(channels, channels, kernel_size, 1, dilation=dilation[1],
-                               padding=get_padding(kernel_size, dilation[1])))
-        ])
-        self.convs.apply(init_weights)
-
-    def forward(self, x, x_mask=None):
-        for c in self.convs:
-            xt = F.leaky_relu(x, LRELU_SLOPE)
-            if x_mask is not None:
-                xt = xt * x_mask
-            xt = c(xt)
-            x = xt + x
-        if x_mask is not None:
-            x = x * x_mask
-        return x
-
-    def remove_weight_norm(self):
-        for l in self.convs:
-            remove_weight_norm(l)
-
-
-class Log(nn.Module):
-  def forward(self, x, x_mask, reverse=False, **kwargs):
-    if not reverse:
-      y = torch.log(torch.clamp_min(x, 1e-5)) * x_mask
-      logdet = torch.sum(-y, [1, 2])
-      return y, logdet
-    else:
-      x = torch.exp(x) * x_mask
-      return x
-    
-
-class Flip(nn.Module):
-  def forward(self, x, *args, reverse=False, **kwargs):
-    x = torch.flip(x, [1])
-    if not reverse:
-      logdet = torch.zeros(x.size(0)).to(dtype=x.dtype, device=x.device)
-      return x, logdet
-    else:
-      return x
-
-
-class ElementwiseAffine(nn.Module):
-  def __init__(self, channels):
-    super().__init__()
-    self.channels = channels
-    self.m = nn.Parameter(torch.zeros(channels,1))
-    self.logs = nn.Parameter(torch.zeros(channels,1))
-
-  def forward(self, x, x_mask, reverse=False, **kwargs):
-    if not reverse:
-      y = self.m + torch.exp(self.logs) * x
-      y = y * x_mask
-      logdet = torch.sum(self.logs * x_mask, [1,2])
-      return y, logdet
-    else:
-      x = (x - self.m) * torch.exp(-self.logs) * x_mask
-      return x
-
-
-class ResidualCouplingLayer(nn.Module):
-  def __init__(self,
-      channels,
-      hidden_channels,
-      kernel_size,
-      dilation_rate,
-      n_layers,
-      p_dropout=0,
-      gin_channels=0,
-      mean_only=False):
-    assert channels % 2 == 0, "channels should be divisible by 2"
-    super().__init__()
-    self.channels = channels
-    self.hidden_channels = hidden_channels
-    self.kernel_size = kernel_size
-    self.dilation_rate = dilation_rate
-    self.n_layers = n_layers
-    self.half_channels = channels // 2
-    self.mean_only = mean_only
-
-    self.pre = nn.Conv1d(self.half_channels, hidden_channels, 1)
-    self.enc = WN(hidden_channels, kernel_size, dilation_rate, n_layers, p_dropout=p_dropout, gin_channels=gin_channels)
-    self.post = nn.Conv1d(hidden_channels, self.half_channels * (2 - mean_only), 1)
-    self.post.weight.data.zero_()
-    self.post.bias.data.zero_()
-
-  def forward(self, x, x_mask, g=None, reverse=False):
-    x0, x1 = torch.split(x, [self.half_channels]*2, 1)
-    h = self.pre(x0) * x_mask
-    h = self.enc(h, x_mask, g=g)
-    stats = self.post(h) * x_mask
-    if not self.mean_only:
-      m, logs = torch.split(stats, [self.half_channels]*2, 1)
-    else:
-      m = stats
-      logs = torch.zeros_like(m)
-
-    if not reverse:
-      x1 = m + x1 * torch.exp(logs) * x_mask
-      x = torch.cat([x0, x1], 1)
-      logdet = torch.sum(logs, [1,2])
-      return x, logdet
-    else:
-      x1 = (x1 - m) * torch.exp(-logs) * x_mask
-      x = torch.cat([x0, x1], 1)
-      return x
-
-
-class ConvFlow(nn.Module):
-  def __init__(self, in_channels, filter_channels, kernel_size, n_layers, num_bins=10, tail_bound=5.0):
-    super().__init__()
-    self.in_channels = in_channels
-    self.filter_channels = filter_channels
-    self.kernel_size = kernel_size
-    self.n_layers = n_layers
-    self.num_bins = num_bins
-    self.tail_bound = tail_bound
-    self.half_channels = in_channels // 2
-
-    self.pre = nn.Conv1d(self.half_channels, filter_channels, 1)
-    self.convs = DDSConv(filter_channels, kernel_size, n_layers, p_dropout=0.)
-    self.proj = nn.Conv1d(filter_channels, self.half_channels * (num_bins * 3 - 1), 1)
-    self.proj.weight.data.zero_()
-    self.proj.bias.data.zero_()
-
-  def forward(self, x, x_mask, g=None, reverse=False):
-    x0, x1 = torch.split(x, [self.half_channels]*2, 1)
-    h = self.pre(x0)
-    h = self.convs(h, x_mask, g=g)
-    h = self.proj(h) * x_mask
-
-    b, c, t = x0.shape
-    h = h.reshape(b, c, -1, t).permute(0, 1, 3, 2) # [b, cx?, t] -> [b, c, t, ?]
-
-    unnormalized_widths = h[..., :self.num_bins] / math.sqrt(self.filter_channels)
-    unnormalized_heights = h[..., self.num_bins:2*self.num_bins] / math.sqrt(self.filter_channels)
-    unnormalized_derivatives = h[..., 2 * self.num_bins:]
-
-    x1, logabsdet = piecewise_rational_quadratic_transform(x1,
-        unnormalized_widths,
-        unnormalized_heights,
-        unnormalized_derivatives,
-        inverse=reverse,
-        tails='linear',
-        tail_bound=self.tail_bound
-    )
-
-    x = torch.cat([x0, x1], 1) * x_mask
-    logdet = torch.sum(logabsdet * x_mask, [1,2])
-    if not reverse:
-        return x, logdet
-    else:
-        return x
-class TransformerCouplingLayer(nn.Module):
-  def __init__(self,
-      channels,
-      hidden_channels,
-      kernel_size,
-      n_layers,
-      n_heads,
-      p_dropout=0,
-      filter_channels=0,
-      mean_only=False,
-      wn_sharing_parameter=None,
-      gin_channels = 0
-      ):
-    assert channels % 2 == 0, "channels should be divisible by 2"
-    super().__init__()
-    self.channels = channels
-    self.hidden_channels = hidden_channels
-    self.kernel_size = kernel_size
-    self.n_layers = n_layers
-    self.half_channels = channels // 2
-    self.mean_only = mean_only
-
-    self.pre = nn.Conv1d(self.half_channels, hidden_channels, 1)
-    self.enc = Encoder(hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout, isflow = True, gin_channels = gin_channels) if wn_sharing_parameter is None else wn_sharing_parameter
-    self.post = nn.Conv1d(hidden_channels, self.half_channels * (2 - mean_only), 1)
-    self.post.weight.data.zero_()
-    self.post.bias.data.zero_()
-
-  def forward(self, x, x_mask, g=None, reverse=False):
-    x0, x1 = torch.split(x, [self.half_channels]*2, 1)
-    h = self.pre(x0) * x_mask
-    h = self.enc(h, x_mask, g=g)
-    stats = self.post(h) * x_mask
-    if not self.mean_only:
-      m, logs = torch.split(stats, [self.half_channels]*2, 1)
-    else:
-      m = stats
-      logs = torch.zeros_like(m)
-
-    if not reverse:
-      x1 = m + x1 * torch.exp(logs) * x_mask
-      x = torch.cat([x0, x1], 1)
-      logdet = torch.sum(logs, [1,2])
-      return x, logdet
-    else:
-      x1 = (x1 - m) * torch.exp(-logs) * x_mask
-      x = torch.cat([x0, x1], 1)
-      return x
-
-    x1, logabsdet = piecewise_rational_quadratic_transform(x1,
-        unnormalized_widths,
-        unnormalized_heights,
-        unnormalized_derivatives,
-        inverse=reverse,
-        tails='linear',
-        tail_bound=self.tail_bound
-    )
-
-    x = torch.cat([x0, x1], 1) * x_mask
-    logdet = torch.sum(logabsdet * x_mask, [1,2])
-    if not reverse:
-        return x, logdet
-    else:
-        return x
diff --git a/spaces/digitalxingtong/Kino-Bert-VITS2/text/symbols.py b/spaces/digitalxingtong/Kino-Bert-VITS2/text/symbols.py
deleted file mode 100644
index 9dfae4e633829f20c4fd767b1c7a9198911ed801..0000000000000000000000000000000000000000
--- a/spaces/digitalxingtong/Kino-Bert-VITS2/text/symbols.py
+++ /dev/null
@@ -1,51 +0,0 @@
-punctuation = ['!', '?', '…', ",", ".", "'", '-']
-pu_symbols = punctuation + ["SP", "UNK"]
-pad = '_'
-
-# chinese
-zh_symbols = ['E', 'En', 'a', 'ai', 'an', 'ang', 'ao', 'b', 'c', 'ch', 'd', 'e', 'ei', 'en', 'eng', 'er', 'f', 'g', 'h',
-       'i', 'i0', 'ia', 'ian', 'iang', 'iao', 'ie', 'in', 'ing', 'iong', 'ir', 'iu', 'j', 'k', 'l', 'm', 'n', 'o',
-       'ong',
-       'ou', 'p', 'q', 'r', 's', 'sh', 't', 'u', 'ua', 'uai', 'uan', 'uang', 'ui', 'un', 'uo', 'v', 'van', 've', 'vn',
-       'w', 'x', 'y', 'z', 'zh',
-        "AA", "EE", "OO"]
-num_zh_tones = 6
-
-# japanese
-ja_symbols = ['I', 'N', 'U', 'a', 'b', 'by', 'ch', 'cl', 'd', 'dy', 'e', 'f', 'g', 'gy', 'h', 'hy', 'i', 'j', 'k', 'ky',
-              'm', 'my', 'n', 'ny', 'o', 'p', 'py', 'r', 'ry', 's', 'sh', 't', 'ts', 'u', 'V', 'w', 'y', 'z']
-num_ja_tones = 1
-
-# English
-en_symbols = ['aa', 'ae', 'ah', 'ao', 'aw', 'ay', 'b', 'ch', 'd', 'dh', 'eh', 'er', 'ey', 'f', 'g', 'hh', 'ih', 'iy',
-              'jh', 'k', 'l', 'm', 'n', 'ng', 'ow', 'oy', 'p', 'r', 's',
-              'sh', 't', 'th', 'uh', 'uw', 'V', 'w', 'y', 'z', 'zh']
-num_en_tones = 4
-
-# combine all symbols
-normal_symbols = sorted(set(zh_symbols + ja_symbols + en_symbols))
-symbols = [pad] + normal_symbols + pu_symbols
-sil_phonemes_ids = [symbols.index(i) for i in pu_symbols]
-
-# combine all tones
-num_tones = num_zh_tones + num_ja_tones + num_en_tones
-
-# language maps
-language_id_map = {
-    'ZH': 0,
-    "JA": 1,
-    "EN": 2
-}
-num_languages = len(language_id_map.keys())
-
-language_tone_start_map = {
-    'ZH': 0,
-    "JA": num_zh_tones,
-    "EN": num_zh_tones + num_ja_tones
-}
-
-if __name__ == '__main__':
-    a = set(zh_symbols)
-    b = set(en_symbols)
-    print(sorted(a&b))
-
diff --git a/spaces/dorkai/text-generation-webui-main/text-generation-webui-main/docs/LLaMA-model.md b/spaces/dorkai/text-generation-webui-main/text-generation-webui-main/docs/LLaMA-model.md
deleted file mode 100644
index 338d458b13b56b3d0f02dd3f4b7d5156a82b88e9..0000000000000000000000000000000000000000
--- a/spaces/dorkai/text-generation-webui-main/text-generation-webui-main/docs/LLaMA-model.md
+++ /dev/null
@@ -1,45 +0,0 @@
-LLaMA is a Large Language Model developed by Meta AI. 
-
-It was trained on more tokens than previous models. The result is that the smallest version with 7 billion parameters has similar performance to GPT-3 with 175 billion parameters.
-
-This guide will cover usage through the official `transformers` implementation. For 4-bit mode, head over to [GPTQ models (4 bit mode)
-](GPTQ-models-(4-bit-mode).md).
-
-## Getting the weights
-
-### Option 1: pre-converted weights
-
-* Torrent: https://github.com/oobabooga/text-generation-webui/pull/530#issuecomment-1484235789
-* Direct download: https://huggingface.co/Neko-Institute-of-Science
-
-⚠️ The tokenizers for the Torrent source above and also for many LLaMA fine-tunes available on Hugging Face may be outdated, so I recommend downloading the following universal LLaMA tokenizer: 
-
-```
-python download-model.py oobabooga/llama-tokenizer
-```
-
-Once downloaded, it will be automatically applied to **every** `LlamaForCausalLM` model that you try to load.
-
-### Option 2: convert the weights yourself
-
-1. Install the `protobuf` library:
-
-```
-pip install protobuf==3.20.1
-```
-
-2. Use the script below to convert the model in `.pth` format that you, a fellow academic, downloaded using Meta's official link:
-
-### [convert_llama_weights_to_hf.py](https://github.com/huggingface/transformers/blob/main/src/transformers/models/llama/convert_llama_weights_to_hf.py)
-
-```
-python convert_llama_weights_to_hf.py --input_dir /path/to/LLaMA --model_size 7B --output_dir /tmp/outputs/llama-7b
-```
-
-3. Move the `llama-7b` folder inside your `text-generation-webui/models` folder.
-
-## Starting the web UI
-
-```python
-python server.py --model llama-7b
-```
diff --git a/spaces/dragonSwing/video2slide/README.md b/spaces/dragonSwing/video2slide/README.md
deleted file mode 100644
index b99614bc9e2365d66962e9da21d933b4a33b10f8..0000000000000000000000000000000000000000
--- a/spaces/dragonSwing/video2slide/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Video2slide
-emoji: 📊
-colorFrom: yellow
-colorTo: red
-sdk: gradio
-sdk_version: 3.32.0
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/dukecsxu/chatGPT/app.py b/spaces/dukecsxu/chatGPT/app.py
deleted file mode 100644
index 8cb71c1b6032804a345069d87352b56e1346c3c3..0000000000000000000000000000000000000000
--- a/spaces/dukecsxu/chatGPT/app.py
+++ /dev/null
@@ -1,330 +0,0 @@
-from pyChatGPT import ChatGPT
-import gradio as gr
-import os, sys, json
-from loguru import logger
-import paddlehub as hub
-import random
-
-    
-language_translation_model = hub.Module(directory=f'./baidu_translate')
-def getTextTrans(text, source='zh', target='en'):
-    def is_chinese(string):
-        for ch in string:
-            if u'\u4e00' <= ch <= u'\u9fff':
-                return True
-        return False
-        
-    if not is_chinese(text) and target == 'en': 
-        return text
-        
-    try:
-        text_translation = language_translation_model.translate(text, source, target)
-        return text_translation
-    except Exception as e:
-        return text 
-
-session_token = os.environ.get('SessionToken')      
-# logger.info(f"session_token_: {session_token}")
-
-def get_api():
-    api = None
-    try:
-      api = ChatGPT(session_token)
-      # api.refresh_auth()
-    except Exception as e:
-      print(f'get_api_error:', e)
-      api = None
-    return api
-
-  
-def get_response_from_chatgpt(api, text):
-    if api is None:
-        return "Openai said: I'm too tired. Let me lie down for a few days. If you like, you can visit my home."
-    try:
-      resp = api.send_message(text)    
-      # api.refresh_auth()
-      # api.reset_conversation() 
-      response = resp['message']
-      conversation_id = resp['conversation_id']
-      parent_id = resp['parent_id']
-      # logger.info(f"response_: {response}")
-      logger.info(f"conversation_id_: [{conversation_id}] / parent_id: [{parent_id}]")  
-    except:
-      response = "Openai said: I'm so tired. Let me lie down for a few days. If you like, you can visit my home."
-    return response
-
-start_work = """async() => {
-    function isMobile() {
-        try {
-            document.createEvent("TouchEvent"); return true;
-        } catch(e) {
-            return false; 
-        }
-    }
-	function getClientHeight()
-	{
-	  var clientHeight=0;
-	  if(document.body.clientHeight&&document.documentElement.clientHeight) {
-		var clientHeight = (document.body.clientHeight<document.documentElement.clientHeight)?document.body.clientHeight:document.documentElement.clientHeight;
-	  } else {
-		var clientHeight = (document.body.clientHeight>document.documentElement.clientHeight)?document.body.clientHeight:document.documentElement.clientHeight;
-	  }
-	  return clientHeight;
-	}
- 
-    function setNativeValue(element, value) {
-      const valueSetter = Object.getOwnPropertyDescriptor(element.__proto__, 'value').set;
-      const prototype = Object.getPrototypeOf(element);
-      const prototypeValueSetter = Object.getOwnPropertyDescriptor(prototype, 'value').set;
-      
-      if (valueSetter && valueSetter !== prototypeValueSetter) {
-            prototypeValueSetter.call(element, value);
-      } else {
-            valueSetter.call(element, value);
-      }
-    }
-    function save_conversation(chatbot) {        
-        var conversations = new Array();
-        for (var i = 0; i < chatbot.children.length; i++) {
-            conversations[i] = chatbot.children[i].innerHTML;
-        }
-        var json_str = JSON.stringify(conversations);
-        localStorage.setItem('chatgpt_conversations', json_str);
-    }
-    function load_conversation(chatbot) {
-        var json_str = localStorage.getItem('chatgpt_conversations');
-        if (json_str) {
-            conversations = JSON.parse(json_str);
-            for (var i = 0; i < conversations.length; i++) {
-                var new_div = document.createElement("div");
-                if((i%2)===0){
-                    new_div.className = "px-3 py-2 rounded-[22px] rounded-br-none text-white text-sm chat-message svelte-rct66g";
-                    new_div.style.backgroundColor = "#16a34a"; 
-                } else {
-                    new_div.className = "px-3 py-2 rounded-[22px] rounded-bl-none place-self-start text-white text-sm chat-message svelte-rct66g";
-                    new_div.style.backgroundColor = "#2563eb"; 
-                    if (conversations[i].indexOf("<img ") == 0) { 
-                        new_div.style.width = "80%"; 
-                        new_div.style.padding = "0.2rem"; 
-                    }                
-                }
-                new_div.innerHTML = conversations[i];
-                chatbot.appendChild(new_div);
-            }
-        }
-    }
-    var gradioEl = document.querySelector('body > gradio-app').shadowRoot;
-    if (!gradioEl) {
-        gradioEl = document.querySelector('body > gradio-app');
-    }
-    
-    if (typeof window['gradioEl'] === 'undefined') {
-        window['gradioEl'] = gradioEl;
-       
-        const page1 = window['gradioEl'].querySelectorAll('#page_1')[0];
-        const page2 = window['gradioEl'].querySelectorAll('#page_2')[0]; 
-    
-        page1.style.display = "none";
-        page2.style.display = "block";
-        window['div_count'] = 0;
-        window['chat_bot'] = window['gradioEl'].querySelectorAll('#chat_bot')[0];
-        window['chat_bot1'] = window['gradioEl'].querySelectorAll('#chat_bot1')[0];   
-        chat_row = window['gradioEl'].querySelectorAll('#chat_row')[0]; 
-        prompt_row = window['gradioEl'].querySelectorAll('#prompt_row')[0]; 
-        window['chat_bot1'].children[1].textContent = '';
-        
-        clientHeight = getClientHeight();
-        if (isMobile()) {
-            output_htmls = window['gradioEl'].querySelectorAll('.output-html');
-            for (var i = 0; i < output_htmls.length; i++) {
-               output_htmls[i].style.display = "none";
-            }
-            new_height = (clientHeight - 250) + 'px';
-        } else {
-            new_height = (clientHeight - 350) + 'px';
-        }
-        chat_row.style.height = new_height;
-        window['chat_bot'].style.height = new_height;
-        window['chat_bot'].children[2].style.height = new_height;
-        window['chat_bot1'].style.height = new_height;
-        window['chat_bot1'].children[2].style.height = new_height;
-        prompt_row.children[0].style.flex = 'auto';
-        prompt_row.children[0].style.width = '100%';
-        window['gradioEl'].querySelectorAll('#chat_radio')[0].style.flex = 'auto';
-        window['gradioEl'].querySelectorAll('#chat_radio')[0].style.width = '100%';        
-        prompt_row.children[0].setAttribute('style','flex-direction: inherit; flex: 1 1 auto; width: 100%;border-color: green;border-width: 1px !important;')
-        window['chat_bot1'].children[1].setAttribute('style', 'border-bottom-right-radius:0;top:unset;bottom:0;padding-left:0.1rem');
-        window['gradioEl'].querySelectorAll('#btns_row')[0].children[0].setAttribute('style', 'min-width: min(10px, 100%); flex-grow: 1');
-        window['gradioEl'].querySelectorAll('#btns_row')[0].children[1].setAttribute('style', 'min-width: min(10px, 100%); flex-grow: 1');
-        
-        load_conversation(window['chat_bot1'].children[2].children[0]);
-        window['chat_bot1'].children[2].scrollTop = window['chat_bot1'].children[2].scrollHeight;
-        
-        window['gradioEl'].querySelectorAll('#clear-btn')[0].onclick = function(e){
-            if (confirm('Clear all outputs?')==true) {
-                 window['chat_bot1'].children[2].children[0].innerHTML = '';
-                 save_conversation(window['chat_bot1'].children[2].children[0]);
-            }
-        }
- 
-        window['prevPrompt'] = '';
-        window['doCheckPrompt'] = 0;
-        window['prevImgSrc'] = '';
-        window['checkChange'] = function checkChange() {
-            try {
-                if (window['gradioEl'].querySelectorAll('.gr-radio')[0].checked) {
-                    if (window['chat_bot'].children[2].children[0].children.length > window['div_count']) {
-                        new_len = window['chat_bot'].children[2].children[0].children.length - window['div_count'];
-                        for (var i = 0; i < new_len; i++) { 
-                            new_div = window['chat_bot'].children[2].children[0].children[window['div_count'] + i].cloneNode(true);
-                            window['chat_bot1'].children[2].children[0].appendChild(new_div);
-                        }
-                        window['div_count'] = chat_bot.children[2].children[0].children.length;
-                        window['chat_bot1'].children[2].scrollTop = window['chat_bot1'].children[2].scrollHeight;
-                        save_conversation(window['chat_bot1'].children[2].children[0]);
-                    }
-                    if (window['chat_bot'].children[0].children.length > 1) {
-                        window['chat_bot1'].children[1].textContent = window['chat_bot'].children[0].children[1].textContent;
-                    } else {
-                        window['chat_bot1'].children[1].textContent = '';
-                    }
-                } else {
-                    texts = window['gradioEl'].querySelectorAll('textarea');
-                    text0 = texts[0];    
-                    text1 = texts[1];
-                    img_index = 0;
-                    text_value = text1.value;
-                    if (window['doCheckPrompt'] === 0 && window['prevPrompt'] !== text_value) {
-                            console.log('_____new prompt___[' + text_value + ']_');
-                            window['doCheckPrompt'] = 1;
-                            window['prevPrompt'] = text_value;
- 
-                            tabitems = window['gradioEl'].querySelectorAll('.tabitem');
-                            for (var i = 0; i < tabitems.length; i++) {   
-                                inputText = tabitems[i].children[0].children[1].children[0].querySelectorAll('.gr-text-input')[0];
-                                setNativeValue(inputText, text_value);
-                                inputText.dispatchEvent(new Event('input', { bubbles: true }));
-                            }                            
-                            setTimeout(function() {
-                                btns = window['gradioEl'].querySelectorAll('button');
-                                for (var i = 0; i < btns.length; i++) {
-                                    if (['Generate image','Run'].includes(btns[i].innerText)) {
-                                        btns[i].click();                
-                                    }
-                                }
-                                window['doCheckPrompt'] = 0;
-                            }, 10);                   
-                    }
-                    tabitems = window['gradioEl'].querySelectorAll('.tabitem');
-                    imgs = tabitems[img_index].children[0].children[1].children[1].querySelectorAll("img");
-                    if (imgs.length > 0) {
-                        if (window['prevImgSrc'] !== imgs[0].src) {
-                            var user_div = document.createElement("div");
-                            user_div.className = "px-3 py-2 rounded-[22px] rounded-br-none text-white text-sm chat-message svelte-rct66g";
-                            user_div.style.backgroundColor = "#16a34a"; 
-                            user_div.innerHTML = "<p>" + text0.value + "</p>";
-                            window['chat_bot1'].children[2].children[0].appendChild(user_div);
-                            var bot_div = document.createElement("div");
-                            bot_div.className = "px-3 py-2 rounded-[22px] rounded-bl-none place-self-start text-white text-sm chat-message svelte-rct66g";
-                            bot_div.style.backgroundColor = "#2563eb"; 
-                            bot_div.style.width = "80%"; 
-                            bot_div.style.padding = "0.2rem"; 
-                            bot_div.appendChild(imgs[0].cloneNode(true));
-                            window['chat_bot1'].children[2].children[0].appendChild(bot_div);
-                            
-                            window['chat_bot1'].children[2].scrollTop = window['chat_bot1'].children[2].scrollHeight;
-                            window['prevImgSrc'] = imgs[0].src;
-                            save_conversation(window['chat_bot1'].children[2].children[0]);
-                        }
-                    }
-                    if (tabitems[img_index].children[0].children[1].children[1].children[0].children.length > 1) {
-                        window['chat_bot1'].children[1].textContent = tabitems[img_index].children[0].children[1].children[1].children[0].textContent;
-                    } else {
-                        window['chat_bot1'].children[1].textContent = '';
-                    }                              
-                }
-              
-            } catch(e) {
-            }        
-        }
-        window['checkChange_interval'] = window.setInterval("window.checkChange()", 500);         
-    }
-   
-    return false;
-}"""
-
-space_ids = {
-            "spaces/stabilityai/stable-diffusion":"Stable Diffusion 2.1",
-            # "spaces/runwayml/stable-diffusion-v1-5":"Stable Diffusion 1.5",
-            # "spaces/stabilityai/stable-diffusion-1":"Stable Diffusion 1.0",
-            }
-
-tab_actions = []
-tab_titles = []
-
-for space_id in space_ids.keys():
-    print(space_id, space_ids[space_id])
-    try:
-        tab = gr.Interface.load(space_id)
-        tab_actions.append(tab)
-        tab_titles.append(space_ids[space_id])
-    except Exception as e:
-        logger.info(f"load_fail__{space_id}_{e}")
-        
-def chat(api, input0, input1, chat_radio, chat_history):
-    out_chat = []
-    if chat_history != '':
-        out_chat = json.loads(chat_history)
-    logger.info(f"out_chat_: {len(out_chat)} / {chat_radio}")
-    if chat_radio == "Talk to chatGPT":
-        response = get_response_from_chatgpt(api, input0)
-        # response = get_response_from_microsoft(input0)
-        # response = get_response_from_skywork(input0)
-        out_chat.append((input0, response))
-        chat_history = json.dumps(out_chat)
-        return api, out_chat, input1, chat_history
-    else:
-        prompt_en = getTextTrans(input0, source='zh', target='en') + f',{random.randint(0,sys.maxsize)}'
-        return api, out_chat, prompt_en, chat_history
-        
-with gr.Blocks(title='Talk to chatGPT') as demo:
-    gr.HTML("<p>You can duplicating this space and use your own session token: <a style='display:inline-block' href='https://huggingface.co/spaces/yizhangliu/chatGPT?duplicate=true'><img src='https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14' alt='Duplicate Space'></a></p>")
-    gr.HTML("<p> Instruction on how to get session token can be seen in video <a style='display:inline-block' href='https://www.youtube.com/watch?v=TdNSj_qgdFk'><font style='color:blue;weight:bold;'>here</font></a>. Add your session token by going to settings and add under secrets. </p>")
-    with gr.Group(elem_id="page_1", visible=True) as page_1:
-        with gr.Box():            
-            with gr.Row():
-                start_button = gr.Button("Let's talk to chatGPT!", elem_id="start-btn", visible=True) 
-                start_button.click(fn=None, inputs=[], outputs=[], _js=start_work)
-                
-    with gr.Group(elem_id="page_2", visible=False) as page_2:        
-        with gr.Row(elem_id="chat_row"):
-            chatbot = gr.Chatbot(elem_id="chat_bot", visible=False).style(color_map=("green", "blue"))
-            chatbot1 = gr.Chatbot(elem_id="chat_bot1").style(color_map=("green", "blue"))
-        with gr.Row(elem_id="prompt_row"):
-            prompt_input0 = gr.Textbox(lines=2, label="prompt",show_label=False)
-            prompt_input1 = gr.Textbox(lines=4, label="prompt", visible=False)
-            chat_history = gr.Textbox(lines=4, label="prompt", visible=False)
-            chat_radio = gr.Radio(["Talk to chatGPT", "Text to Image"], elem_id="chat_radio",value="Talk to chatGPT", show_label=False)
-        with gr.Row(elem_id="btns_row"):
-            with gr.Column(id="submit_col"):
-                submit_btn = gr.Button(value = "submit",elem_id="submit-btn").style(
-                        margin=True,
-                        rounded=(True, True, True, True),
-                        width=100
-                    )
-            with gr.Column(id="clear_col"):
-                clear_btn = gr.Button(value = "clear outputs", elem_id="clear-btn").style(
-                        margin=True,
-                        rounded=(True, True, True, True),
-                        width=100
-                    )
-            api = gr.State(value=get_api())
-            submit_btn.click(fn=chat, 
-                             inputs=[api, prompt_input0, prompt_input1, chat_radio, chat_history], 
-                             outputs=[api, chatbot, prompt_input1, chat_history],
-                            )
-        with gr.Row(elem_id='tab_img', visible=False).style(height=5):
-           tab_img = gr.TabbedInterface(tab_actions, tab_titles)             
-
-demo.launch(debug = True)
-
diff --git a/spaces/erbanku/gpt-academic/crazy_functions/test_project/latex/attention/background.tex b/spaces/erbanku/gpt-academic/crazy_functions/test_project/latex/attention/background.tex
deleted file mode 100644
index 785069dc0f9143bad24e640056dd1072d5c6e5b5..0000000000000000000000000000000000000000
--- a/spaces/erbanku/gpt-academic/crazy_functions/test_project/latex/attention/background.tex
+++ /dev/null
@@ -1,58 +0,0 @@
-The goal of reducing sequential computation also forms the foundation of the Extended Neural GPU \citep{extendedngpu}, ByteNet \citep{NalBytenet2017} and ConvS2S \citep{JonasFaceNet2017}, all of which use convolutional neural networks as basic building block, computing hidden representations in parallel for all input and output positions. In these models, the number of operations required to relate signals from two arbitrary input or output positions grows in the distance between positions, linearly for ConvS2S and logarithmically for ByteNet. This makes it more difficult to learn dependencies between distant positions \citep{hochreiter2001gradient}. In the Transformer this is reduced to a constant number of operations, albeit at the cost of reduced effective resolution due to averaging attention-weighted positions, an effect we counteract with Multi-Head Attention as described in section~\ref{sec:attention}. 
-
-Self-attention, sometimes called intra-attention is an attention mechanism relating different positions of a single sequence in order to compute a representation of the sequence. Self-attention has been used successfully in a variety of tasks including reading comprehension, abstractive summarization, textual entailment and learning task-independent sentence representations \citep{cheng2016long, decomposableAttnModel, paulus2017deep, lin2017structured}.
-
-End-to-end memory networks are based on a recurrent attention mechanism instead of sequence-aligned recurrence and have been shown to perform well on simple-language question answering and language modeling tasks \citep{sukhbaatar2015}.
-
-To the best of our knowledge, however, the Transformer is the first transduction model relying entirely on self-attention to compute representations of its input and output without using sequence-aligned RNNs or convolution.
-In the following sections, we will describe the Transformer, motivate self-attention and discuss its advantages over models such as \citep{neural_gpu, NalBytenet2017} and \citep{JonasFaceNet2017}.
-
-
-%\citep{JonasFaceNet2017} report new SOTA on machine translation for English-to-German (EnDe), Enlish-to-French (EnFr) and English-to-Romanian language pairs. 
-
-%For example,! in MT, we must draw information from both input and previous output words to translate an output word accurately. An attention layer \citep{bahdanau2014neural} can connect a very large number of positions at low computation cost, making it an essential ingredient in competitive recurrent models for machine translation.
-
-%A natural question to ask then is, "Could we replace recurrence with attention?". \marginpar{Don't know if it's the most natural question to ask given the previous statements. Also, need to say that the complexity table summarizes these statements} Such a model would be blessed with the computational efficiency of attention and the power of cross-positional communication. In this work, show that pure attention models work remarkably well for MT, achieving new SOTA results on EnDe and EnFr, and can be trained in under $2$ days on xyz architecture. 
-
-%After the seminal models introduced in \citep{sutskever14, bahdanau2014neural, cho2014learning}, recurrent models have become the dominant solution for both sequence modeling and sequence-to-sequence transduction. Many efforts such as \citep{wu2016google,luong2015effective,jozefowicz2016exploring} have pushed the boundaries of machine translation (MT) and language modeling with recurrent endoder-decoder and recurrent language models. Recent effort \citep{shazeer2017outrageously} has successfully combined the power of conditional computation with sequence models to train very large models for MT, pushing SOTA at lower computational cost.
-
-%Recurrent models compute a vector of hidden states $h_t$, for each time step $t$ of computation. $h_t$ is a function of both the input at time $t$ and the previous hidden state $h_t$. This dependence on the previous hidden state precludes processing all timesteps at once, instead requiring long sequences of sequential operations.  In practice, this results in greatly reduced computational efficiency, as on modern computing hardware, a single operation on a large batch is much faster than a large number of operations on small batches.  The problem gets worse at longer sequence lengths. Although sequential computation is not a severe bottleneck at inference time, as autoregressively generating each output requires all previous outputs, the inability to compute scores at all output positions at once hinders us from rapidly training our models over large datasets. Although impressive work such as \citep{Kuchaiev2017Factorization} is able to significantly accelerate the training of LSTMs with factorization tricks, we are still bound by the linear dependence on sequence length.
-
-%If the model could compute hidden states at each time step using only the inputs and outputs,  it would be liberated from the dependence on results from previous time steps during training. This line of thought is the foundation of recent efforts such as the Markovian neural GPU \citep{neural_gpu}, ByteNet \citep{NalBytenet2017} and ConvS2S \citep{JonasFaceNet2017}, all of which use convolutional neural networks as a building block to compute hidden representations simultaneously for all timesteps, resulting in $O(1)$ sequential time complexity. \citep{JonasFaceNet2017} report new SOTA on machine translation for English-to-German (EnDe), Enlish-to-French (EnFr) and English-to-Romanian language pairs. 
-
-%A crucial component for accurate sequence prediction is modeling cross-positional communication. For example, in MT, we must draw information from both input and previous output words to translate an output word accurately. An attention layer \citep{bahdanau2014neural} can connect a very large number of positions at a low computation cost, also $O(1)$ sequential time complexity, making it an essential ingredient in recurrent encoder-decoder architectures for MT. A natural question to ask then is, "Could we replace recurrence with attention?". \marginpar{Don't know if it's the most natural question to ask given the previous statements. Also, need to say that the complexity table summarizes these statements} Such a model would be blessed with the computational efficiency of attention and the power of cross-positional communication. In this work, show that pure attention models work remarkably well for MT, achieving new SOTA results on EnDe and EnFr, and can be trained in under $2$ days on xyz architecture. 
-
-
-
-%Note: Facebook model is no better than RNNs in this regard, since it requires a number of layers proportional to the distance you want to communicate.  Bytenet is more promising, since it requires a logarithmnic number of layers (does bytenet have SOTA results)?   
-
-%Note: An attention  layer can connect a very large number of positions at a low computation cost in O(1) sequential operations.  This is why encoder-decoder attention has been so successful in seq-to-seq models so far.  It is only natural, then, to also use attention to connect the timesteps of the same sequence.
-
-%Note: I wouldn't say that long sequences are not a problem during inference.  It would be great if we could infer with no long sequences.  We could just say later on that, while our training graph is constant-depth, our model still requires sequential operations in the decoder part during inference due to the autoregressive nature of the model.   
-
-%\begin{table}[h!]
-%\caption{Attention models are quite efficient for cross-positional communications when sequence length is smaller than channel depth. $n$ represents the sequence length and $d$ represents the channel depth.}
-%\label{tab:op_complexities}
-%\begin{center}
-%\vspace{-5pt}
-%\scalebox{0.75}{
-
-%\begin{tabular}{l|c|c|c}
-%\hline \hline
-%Layer Type & Receptive & Complexity & Sequential  \\
-%           & Field     &            & Operations  \\
-%\hline
-%Pointwise Feed-Forward & $1$ & $O(n \cdot d^2)$ & $O(1)$ \\
-%\hline
-%Recurrent & $n$ & $O(n \cdot d^2)$ & $O(n)$ \\
-%\hline
-%Convolutional & $r$ & $O(r \cdot n \cdot d^2)$ & $O(1)$ \\
-%\hline
-%Convolutional (separable) & $r$ & $O(r \cdot n \cdot d + n %\cdot d^2)$ & $O(1)$ \\
-%\hline
-%Attention & $r$ & $O(r \cdot n \cdot d)$ & $O(1)$ \\
-%\hline \hline
-%\end{tabular}
-%}
-%\end{center}
-%\end{table}
\ No newline at end of file
diff --git a/spaces/failfast/nextjs-hf-spaces/src/components/base/example-button.tsx b/spaces/failfast/nextjs-hf-spaces/src/components/base/example-button.tsx
deleted file mode 100644
index 627433dce1ce6ee07eedc2ef617f46518dd95f60..0000000000000000000000000000000000000000
--- a/spaces/failfast/nextjs-hf-spaces/src/components/base/example-button.tsx
+++ /dev/null
@@ -1,41 +0,0 @@
-import { Button, Typography } from "@mui/material";
-import { MouseEventHandler } from "react";
-
-interface ExampleButtonProps {
-  text: string;
-  displayLength?: number;
-  onClick?: (text: string) => void;
-}
-
-/**
- *
- * A button that hosts an example "text" that can be used as the input
- * to anything to get an inspiration on how to get started.
- *
- * @param props ExampleButtonProps
- * @returns
- */
-export default function ExampleButton(props: ExampleButtonProps) {
-  const { text, displayLength = 50, onClick } = props;
-
-  const displayText =
-    text.slice(0, displayLength) + (text.length > displayLength ? "..." : "");
-
-  const handleClick: MouseEventHandler = event => {
-    event.preventDefault();
-
-    if (onClick) {
-      onClick(text);
-    }
-  };
-
-  return (
-    <Button
-      onClick={handleClick}
-      sx={{ textTransform: "none" }}
-      variant="outlined"
-    >
-      <Typography>{displayText}</Typography>
-    </Button>
-  );
-}
diff --git a/spaces/falterWliame/Face_Mask_Detection/DVBViewer 6.1.5 Crack ((TOP)).md b/spaces/falterWliame/Face_Mask_Detection/DVBViewer 6.1.5 Crack ((TOP)).md
deleted file mode 100644
index 2c6da04d50f083ef647c6df22df60672c10e0216..0000000000000000000000000000000000000000
--- a/spaces/falterWliame/Face_Mask_Detection/DVBViewer 6.1.5 Crack ((TOP)).md	
+++ /dev/null
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diff --git a/spaces/falterWliame/Face_Mask_Detection/Ilya Efimov Lp Electric Guitar Kontakt Torrent _BEST_ Download.md b/spaces/falterWliame/Face_Mask_Detection/Ilya Efimov Lp Electric Guitar Kontakt Torrent _BEST_ Download.md
deleted file mode 100644
index 9dbc39cc82cc0cdf2d5a25e88cc187e115fe0e52..0000000000000000000000000000000000000000
--- a/spaces/falterWliame/Face_Mask_Detection/Ilya Efimov Lp Electric Guitar Kontakt Torrent _BEST_ Download.md	
+++ /dev/null
@@ -1,18 +0,0 @@
-
-<h1>Ilya Efimov LP Electric Guitar: A Detailed Emulation of the Legendary Les Paul Guitar for Kontakt</h1>
-<p>If you are looking for a realistic and versatile electric guitar library for Kontakt, you might want to check out Ilya Efimov LP Electric Guitar. This library is a detailed emulation of the legendary Les Paul guitar, one of the most iconic and popular instruments in rock history. Ilya Efimov Sound Production has invested much effort into re-creating the nuances of this guitar to make it sound as real as possible.</p>
-<p>With Ilya Efimov LP Electric Guitar, you get 3 969 samples, 4.07 GB of content, 12 velocity layers for each note, 23 frets on each string with round-robin, automatic and manual string selection, volume and tone control for each pickup, automatic and manual left hand playing position selection, 3 modes for automatic search of chord position, 14 different articulations, realistic legato, realistic and LFO vibrato, realistic glissando, repetition keys, feedback, many different FX and noises, and effects such as reverb, compressor, EQ, delay, chorus, flanger, phaser and cabinet[^1^].</p>
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-<p>The sound of each pickup was recorded separately, so you can control the direct signal from the pickups independently. This allows you to sculpt the sound to your taste. You can also put the library through dedicated amp modeling software to really hear it come alive. The library also supports MIDI-guitar mode for easy playing[^1^].</p>
-<p>Ilya Efimov LP Electric Guitar is part of the Total Guitar And Bass Bundle by Ilya Efimov Sound Production, which includes other acoustic and electric guitars and basses for Kontakt. These bundles were posted on the root tracker, but for some reason they were deleted. According to the author of the previous distribution, the versions of some tools are more recent than those available on the tracker, everything is conveniently added via the Add Library. It also announced the removal of so-called “watermarks” (“watermarks”)[^2^] [^3^].</p>
-<p>If you are interested in downloading Ilya Efimov LP Electric Guitar or the Total Guitar And Bass Bundle for Kontakt, you can find them on various torrent sites. However, we recommend that you support the original developer and buy the library from their official website[^4^]. You can also listen to some audio demos and watch some video tutorials there.</p>
-<p>Ilya Efimov LP Electric Guitar is a great choice for anyone who wants to add some authentic and expressive electric guitar sounds to their music production. Whether you play rock, blues, jazz or any other genre that requires a guitar solo or accompaniment, you will find this library useful and inspiring.</p>
-
-<p>In this section, we will show you how to install and use Ilya Efimov LP Electric Guitar for Kontakt. First, you need to have Kontakt 5.6 or higher installed on your computer. You also need to have enough disk space to store the library files. The library requires 4.07 GB of free space, but you can use the NCW compression option to reduce the size to 2.23 GB.</p>
-<p>After you download the library from the torrent site or buy it from the official website, you need to extract the files to a folder of your choice. Then, you need to open Kontakt and click on the Add Library button. Navigate to the folder where you extracted the library and select it. The library should appear in the Libraries tab of Kontakt. You can also drag and drop the .nki files from the Instruments folder to the Kontakt rack.</p>
-<p>To load an instrument, simply double-click on it or drag it to the Kontakt rack. You will see a user interface with various controls and options. You can adjust the volume and tone of each pickup, switch between different articulations, change the playing position, apply effects and more. You can also access more settings by clicking on the wrench icon on the top left corner of the interface.</p>
-<p>To play the instrument, you can use your MIDI keyboard or controller, or use the on-screen keyboard of Kontakt. You can also use a MIDI guitar if you enable the MIDI-guitar mode in the settings. The instrument will respond to your playing dynamics and expression, and will automatically select the appropriate strings and frets based on your input. You can also use key switches and controllers to change articulations and parameters on the fly.</p>
-<p></p>
-<p>That's it for the installation and usage of Ilya Efimov LP Electric Guitar for Kontakt. We hope you enjoy this library and create some amazing music with it.</p> d5da3c52bf<br />
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diff --git a/spaces/falterWliame/Face_Mask_Detection/Knust Src Constitution Pdf Download.md b/spaces/falterWliame/Face_Mask_Detection/Knust Src Constitution Pdf Download.md
deleted file mode 100644
index 6ff3b0555e18bff93addc7f1e7d215a91ed8eeb6..0000000000000000000000000000000000000000
--- a/spaces/falterWliame/Face_Mask_Detection/Knust Src Constitution Pdf Download.md	
+++ /dev/null
@@ -1,174 +0,0 @@
-
-<h1>Knust Src Constitution Pdf Download: A Guide for Students</h1>
-
-<p>If you are a student of Kwame Nkrumah University of Science and Technology (KNUST), you might be interested in downloading the constitution of the Students' Representative Council (SRC). The SRC is the official body that represents the interests and welfare of all students in KNUST. The SRC constitution is the document that defines the structure, functions, powers and responsibilities of the SRC and its organs.</p>
-
-<p>In this article, we will provide you with some information about the SRC constitution and how you can download it in PDF format. We will also explain why it is important to read and understand the SRC constitution as a student of KNUST.</p>
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-<h2>What is the SRC Constitution?</h2>
-
-<p>The SRC constitution is the supreme law of the SRC. It was adopted by the SRC General Assembly in 2011, with some amendments made in subsequent years. The SRC constitution contains 18 chapters and 108 articles that cover various aspects of the SRC, such as:</p>
-
-<ul>
-<li>The name and sovereignty of the SRC</li>
-<li>The structure and functions of the SRC</li>
-<li>The representation of the people (elections and electoral commission)</li>
-<li>The executive council and its committees</li>
-<li>The other executive officers</li>
-<li>The parliamentary council and its committees</li>
-<li>The judicial council and its committees</li>
-<li>The standing committees</li>
-<li>The National Union of Ghana Students Secretariat, KNUST</li>
-<li>The Women's Commission</li>
-<li>The Trade, Technology and Innovation Development Commission</li>
-<li>The finance of the SRC</li>
-<li>The code of conduct for the SRC</li>
-<li>The removal, dismissal and suspension of SRC officers</li>
-<li>The amendments and revision of the SRC constitution</li>
-<li>The miscellaneous provisions</li>
-<li>The schedules (interpretations, oaths)</li>
-</ul>
-
-<p>The SRC constitution aims to promote democracy, accountability, transparency, unity, diversity, equity, justice and development within the student body. It also seeks to protect and advance the rights and interests of all students in KNUST.</p>
-
-<h2>How to Download the SRC Constitution in PDF Format?</h2>
-
-<p>If you want to download the SRC constitution in PDF format, you can follow these simple steps:</p>
-
-<ol>
-<li>Visit the official website of the SRC at <a href="https://src.knust.edu.gh/">https://src.knust.edu.gh/</a></li>
-<li>Click on the "About SRC" tab on the menu bar</li>
-<li>Select "Constitution" from the drop-down list</li>
-<li>You will see a link that says "DOWNLOAD THE SRC CONSTITUTION HERE"</li>
-<li>Click on the link and save the file to your device</li>
-</ol>
-
-<p>You can also access the SRC constitution directly from this link: <a href="https://src.knust.edu.gh/sites/src.knust.edu.gh/files/2019-04/SRC2011constitutionasamended-1.pdf">https://src.knust.edu.gh/sites/src.knust.edu.gh/files/2019-04/SRC2011constitutionasamended-1.pdf</a></p>
-
-<p>The file size is about 1 MB and it has 71 pages. You can read it online or print it out for your convenience.</p>
-
-<h2>Why Should You Read and Understand the SRC Constitution?</h2>
-
-<p>As a student of KNUST, you are a member of the SRC and you have a stake in its affairs. Therefore, it is important that you read and understand the SRC constitution for several reasons:</p>
-<p></p>
-
-<ul>
-<li>It will help you to know your rights and responsibilities as a student and as a member of the SRC</li>
-<li>It will help you to know how the SRC operates and how it serves your interests and welfare</li>
-<li>It will help you to participate actively and effectively in the SRC activities and decision-making processes</li>
-<li>It will help you to hold the SRC officers accountable for their actions and performance</li>
-<li>It will help you to contribute to the improvement and development of the SRC and its services</li>
-</ul>
-
-<p>Reading and understanding the SRC constitution will also enable you to appreciate the values and principles that guide the SRC and its members. It will also inspire you to uphold these values and principles in your academic, social and personal life.</p>
-
-<h2>Conclusion</h2>
-
-<p>In this article, we have provided you with some information about knust src constitution pdf download. We have explained what is the SRC constitution, how to download it in PDF format, and why you should read and understand it as a student of KNUST.</p>
-
-<p>We hope that this article has been helpful and informative for you. If you have any questions or comments, please feel free to share them with us.</p>
-<h2>What are the Benefits of the SRC Constitution?</h2>
-
-<p>The SRC constitution is not only a legal document, but also a source of inspiration and guidance for the SRC and its members. The SRC constitution has several benefits, such as:</p>
-
-<ul>
-<li>It provides a clear and comprehensive framework for the governance and administration of the SRC</li>
-<li>It ensures that the SRC operates in a democratic, transparent and accountable manner</li>
-<li>It defines the roles and responsibilities of the SRC officers and organs</li>
-<li>It establishes the checks and balances among the executive, legislative and judicial branches of the SRC</li>
-<li>It safeguards the rights and freedoms of all students in KNUST</li>
-<li>It fosters a culture of participation, consultation and collaboration among the SRC and its stakeholders</li>
-<li>It promotes the values of unity, diversity, equity, justice and development within the student body</li>
-<li>It enhances the credibility and legitimacy of the SRC as a representative body</li>
-</ul>
-
-<p>The SRC constitution also serves as a model for other student organizations and associations in KNUST and beyond. It reflects the aspirations and vision of the students of KNUST as well as their commitment to excellence and innovation.</p>
-
-<h2>How to Use the SRC Constitution?</h2>
-
-<p>The SRC constitution is not only a document to be downloaded and read, but also a tool to be used and applied. The SRC constitution can be used in various ways, such as:</p>
-
-<ul>
-<li>To educate yourself and others about the SRC and its functions</li>
-<li>To participate actively and effectively in the SRC activities and decision-making processes</li>
-<li>To monitor and evaluate the performance and accountability of the SRC officers and organs</li>
-<li>To seek redress or justice when your rights or interests are violated or infringed by the SRC or any other party</li>
-<li>To propose or support amendments or revisions to improve or update the SRC constitution</li>
-<li>To advocate or lobby for issues or causes that affect or concern you or other students in KNUST</li>
-</ul>
-
-<p>To use the SRC constitution effectively, you need to read it carefully and understand it fully. You also need to respect it and abide by it at all times. You also need to share it with others and encourage them to do the same.</p>
-
-<h2>Conclusion</h2>
-
-<p>In this article, we have provided you with more information about knust src constitution pdf download. We have explained what are the benefits of the SRC constitution, how to use it, and why you should read and understand it as a student of KNUST.</p>
-
-<p>We hope that this article has been helpful and informative for you. If you have any questions or comments, please feel free to share them with us.</p>
-<h2>What are the Sources of the SRC Constitution?</h2>
-
-<p>The SRC constitution is not a document that was created out of thin air, but rather a product of history and evolution. The SRC constitution has several sources that influenced its content and form, such as:</p>
-
-<ul>
-<li>The 1992 Constitution of Ghana, which is the supreme law of the land and provides the framework for democratic governance and human rights</li>
-<li>The Statutes of KNUST, which are the laws that govern the establishment, administration and functions of the university</li>
-<li>The previous SRC constitutions, which were adopted in 1961, 1974, 1980 and 2004, and reflected the changing needs and aspirations of the students over time</li>
-<li>The best practices and experiences of other student representative bodies in Ghana and abroad, which provided inspiration and guidance for the SRC</li>
-<li>The inputs and feedback from various stakeholders, such as students, SRC officers, faculty, administration and alumni, who participated in the drafting and review process of the SRC constitution</li>
-</ul>
-
-<p>The SRC constitution is therefore a document that reflects the values and principles of democracy, rule of law, human rights, academic freedom and student representation. It also embodies the vision and mission of KNUST as a premier institution of science and technology in Africa.</p>
-
-<h2>How to Download Other SRC Documents?</h2>
-
-<p>The SRC constitution is not the only document that is relevant and useful for students of KNUST. There are other SRC documents that provide more information and details about the SRC and its activities and services. Some of these documents include:</p>
-
-<ul>
-<li>The SRC Handbook, which is a guide for students on how to access and benefit from the SRC services and programs</li>
-<li>The SRC Budget, which is a statement of the income and expenditure of the SRC for each academic year</li>
-<li>The SRC Annual Report, which is a summary of the achievements and challenges of the SRC for each academic year</li>
-<li>The SRC Policy Documents, which are guidelines and regulations on various issues and matters that affect or concern students in KNUST</li>
-<li>The SRC Publications, which are newsletters, magazines, brochures and flyers that inform and educate students about the SRC and its events</li>
-</ul>
-
-<p>If you want to download these SRC documents in PDF format, you can follow these simple steps:</p>
-
-<ol>
-<li>Visit the official website of the SRC at <a href="https://src.knust.edu.gh/">https://src.knust.edu.gh/</a></li>
-<li>Click on the "Media" tab on the menu bar</li>
-<li>Select "Downloads" from the drop-down list</li>
-<li>You will see a list of various SRC documents that are available for download</li>
-<li>Click on the document that you want to download and save it to your device</li>
-</ol>
-
-<p>You can also access these SRC documents directly from this link: <a href="https://src.knust.edu.gh/media/downloads">https://src.knust.edu.gh/media/downloads</a></p>
-
-<p>These SRC documents will help you to learn more about the SRC and its functions. They will also help you to participate actively and effectively in the SRC activities and decision-making processes.</p>
-
-<h2>Conclusion</h2>
-
-<p>In this article, we have provided you with more information about knust src constitution pdf download. We have explained what are the sources of the SRC constitution, how to download other SRC documents, and why you should read and understand them as a student of KNUST.</p>
-
-<p>We hope that this article has been helpful and informative for you. If you have any questions or comments, please feel free to share them with us.</p>
-<h2>Conclusion</h2>
-
-<p>In this article, we have provided you with a comprehensive guide on knust src constitution pdf download. We have covered various topics, such as:</p>
-
-<ul>
-<li>What is the SRC constitution and how to download it in PDF format</li>
-<li>Why you should read and understand the SRC constitution as a student of KNUST</li>
-<li>What are the benefits of the SRC constitution</li>
-<li>How to use the SRC constitution</li>
-<li>What are the challenges of the SRC constitution</li>
-<li>How to get involved in the SRC constitution</li>
-<li>What are the sources of the SRC constitution</li>
-<li>How to download other SRC documents</li>
-</ul>
-
-<p>We hope that this article has been helpful and informative for you. We also hope that you have gained a better understanding and appreciation of the SRC constitution and its role and importance in the student life of KNUST.</p>
-
-<p>If you have any questions or comments, please feel free to share them with us. We would love to hear from you and assist you in any way we can.</p>
-
-<p>Thank you for reading this article and for your interest in the SRC constitution. We wish you all the best in your academic, social and personal endeavors.</p> 3cee63e6c2<br />
-<br />
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\ No newline at end of file
diff --git a/spaces/fatiXbelha/sd/Download Lumion 6 Pro  Crack - The Best Software for Architects and Designers.md b/spaces/fatiXbelha/sd/Download Lumion 6 Pro  Crack - The Best Software for Architects and Designers.md
deleted file mode 100644
index 6fbb21b6c7ac9f5229b7b87fc4313af553d8a83c..0000000000000000000000000000000000000000
--- a/spaces/fatiXbelha/sd/Download Lumion 6 Pro  Crack - The Best Software for Architects and Designers.md	
+++ /dev/null
@@ -1,137 +0,0 @@
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-<h1>How to Download Lumion 6 Full Crack for Free</h1>
-<p>If you are an architect, designer, or hobbyist who wants to create stunning 3D renderings of your projects, you might have heard of Lumion, a powerful and easy-to-use software that lets you turn your models into lifelike images and videos. But what if you don't have the budget to buy the official version of Lumion, which costs thousands of dollars? Is there a way to get Lumion for free?</p>
-<h2>download lumion 6 full crack</h2><br /><p><b><b>DOWNLOAD</b> &rarr;&rarr;&rarr; <a href="https://urllie.com/2uNAgN">https://urllie.com/2uNAgN</a></b></p><br /><br />
-<p>The answer is yes, there is a way to download Lumion 6 full crack for free from Google Drive, and activate it with a keygen. In this article, we will show you how to do it step by step, and also give you some tips and tricks on how to use Lumion for your projects. But before we get into that, let's first take a look at what Lumion 6 is and why you need it.</p>
-<h2>What is Lumion 6 and why do you need it?</h2>
-<p>Lumion is a real-time 3D visualization software that helps architects and designers create realistic visualizations of their projects. It is compatible with most of the popular CAD software, such as SketchUp, Revit, AutoCAD, and more. You can import your models into Lumion, add materials, lighting, effects, and objects, and render them in minutes. You can also create animations, panoramas, VR scenes, and more.</p>
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-<li><strong>PureGlass</strong>: A new technology that gives you realistic glass materials that are transparent, translucent, or frosted.</li>
-<li><strong>Speedray Reflections</strong>: A new feature that improves the reflections on surfaces automatically, without affecting the render time.</li>
-<li><strong>Hyperlight 2</strong>: A new technology that enhances the lighting on surfaces by calculating the light more accurately.</li>
-<li><strong>OmniShadow</strong>: A new feature that improves the shadows on objects by making them more detailed and realistic.</li>
-<li><strong>Improved Materials</strong>: A new feature that simulates the natural roughness of surfaces, making them more realistic.</li>
-<li><strong>Wet Asphalt</strong>: A new material that adds a wet look to asphalt surfaces, giving them more depth and realism.</li>
-</ul>
-<p>These are just some of the features that Lumion 6 offers. You can find more information about them on <a href="(^7^)">this page</a>. With these features, you can create stunning renderings that will impress your clients and viewers.</p>
-<h3>Lumion 6 system requirements</h3>
-<p>To run Lumion 6 smoothly on your PC, you need to have a decent hardware configuration. Here are the minimum and recommended system requirements for Lumion 6:</p>
-<table>
-<tr><th>Minimum requirements</th><th>Recommended requirements</th></tr>
-<tr><td>Operating System: Windows Vista/7/8/10 (64-bit)</td><td>Operating System : Windows 10 (64-bit)</td></tr>
-<tr><td>CPU: Intel Core i5 or equivalent</td><td>CPU: Intel Core i7 or equivalent</td></tr>
-<tr><td>RAM: 8 GB</td><td>RAM: 16 GB</td></tr>
-<tr><td>Graphics Card: NVIDIA GeForce GTX 680 or equivalent</td><td>Graphics Card: NVIDIA GeForce GTX 980 or equivalent</td></tr>
-<tr><td>Hard Disk Space: 20 GB</td><td>Hard Disk Space: 40 GB</td></tr>
-<tr><td>Internet Connection: Required for activation and updates</td><td>Internet Connection: Required for activation and updates</td></tr>
-</table>
-<p>If you meet these requirements, you are ready to download Lumion 6 full crack from Google Drive. Let's see how to do it.</p>
-<h2>How to download Lumion 6 full crack from Google Drive</h2>
-<p>Downloading Lumion 6 full crack from Google Drive is very easy and fast. You just need to follow these steps:</p>
-<h3>Step 1: Go to the Google Drive link</h3>
-<p>The first step is to go to the Google Drive link where the Lumion 6.0 Pro crack file is stored. You can find the link <a href="">here</a>. This link will take you to a folder that contains two files: Lumion_6_0_Pro.zip and Lumion_6_0_Pro.txt. The zip file is the one that contains the Lumion 6 software and the crack, while the txt file contains some instructions and information.</p>
-<h3>Step 2: Download the Lumion 6.0 Pro crack file</h3>
-<p>The next step is to download the Lumion_6_0_Pro.zip file to your PC. To do this, you need to right-click on the file and select "Download". You will see a pop-up window that asks you to confirm the download. Click on "Download anyway" and wait for the file to be downloaded. The file size is about 5.8 GB, so it might take some time depending on your internet speed.</p>
-<h3>Step 3: Extract the file and run the installer</h3>
-<p>The final step is to extract the zip file and run the installer. To extract the file, you need to use a software like WinRAR or 7-Zip. Right-click on the zip file and select "Extract here" or "Extract to Lumion_6_0_Pro". You will see a new folder with the same name as the zip file. Open the folder and double-click on the "Lumion_6_0_Pro.exe" file. This will launch the installer of Lumion 6.</p>
-<p>The installer will guide you through the installation process. You need to accept the terms and conditions, choose a destination folder, and click on "Install". The installation will take some minutes, so be patient. When the installation is finished, click on "Finish" and close the installer.</p>
-<p>Congratulations, you have successfully downloaded Lumion 6 full crack from Google Drive. But you are not done yet. You still need to activate it with a keygen. Let's see how to do that.</p>
-<h2>How to activate Lumion 6 full crack with keygen</h2>
-<p>To activate Lumion 6 full crack with keygen, you need to follow these steps:</p>
-<h3>Step 1: Copy the crack files to the Lumion installation folder</h3>
-<p>The first step is to copy the crack files to the Lumion installation folder. The crack files are located in the "Crack" folder inside the zip file that you downloaded from Google Drive. You need to copy all the files in this folder and paste them into the folder where you installed Lumion. By default, this folder is "C:\Program Files\Lumion 6.0 Pro". If you chose a different folder during the installation, you need to go there instead.</p>
-<p>To copy and paste the files, you can use the keyboard shortcuts Ctrl+C and Ctrl+V, or right-click on them and select "Copy" and "Paste". You will see a message that asks you to replace or skip some files. Choose "Replace" or "Replace all" and confirm your choice.</p>
-<h3>Step 2: Run the keygen and generate a license key</h3>
-<p>The next step is to run the keygen and generate a license key. The keygen is one of the files that you copied from the "Crack" folder. It is called "Lumion_6_0_Pro_Keygen.exe". Double-click on this file and wait for it to open.</p>
-<p p>You will see a window that looks like this:</p>
-<img src="" alt="Keygen window">
-<p>In this window, you need to click on the "Generate" button and wait for a license key to be generated. The license key will appear in the text box below the button. You need to copy this license key and save it somewhere, as you will need it in the next step.</p>
-<h3>Step 3: Enter the license key and activate Lumion</h3>
-<p>The final step is to enter the license key and activate Lumion. To do this, you need to open Lumion and go to the "Settings" menu. You will see a window that looks like this:</p>
-<img src="" alt="Settings window">
-<p>In this window, you need to click on the "Enter License Key" button and paste the license key that you copied from the keygen. Then, click on the "Activate" button and wait for Lumion to verify your license. You will see a message that confirms your activation. Click on "OK" and close the window.</p>
-<p>Congratulations, you have successfully activated Lumion 6 full crack with keygen. You can now use Lumion for your projects without any limitations.</p>
-<h2>How to use Lumion 6 full crack for your projects</h2>
-<p>Now that you have downloaded and activated Lumion 6 full crack, you might be wondering how to use it for your projects. Lumion is very easy and intuitive to use, but it also has many features and options that can help you create amazing renderings. Here are some tips and tricks on how to use Lumion 6 full crack for your projects:</p>
-<h3>Tips and tricks for creating realistic renderings with Lumion</h3>
-<ul>
-<li><strong>Import your models from CAD software</strong>: Lumion supports most of the popular CAD software, such as SketchUp, Revit, AutoCAD, and more. You can import your models into Lumion by clicking on the "Import" button on the main toolbar. You can also drag and drop your files into Lumion. Lumion will automatically convert your models into its own format and place them in the scene.</li>
-<li><strong>Add materials, lighting, effects, and objects</strong>: Lumion has a large library of materials, lighting, effects, and objects that you can use to enhance your models. You can access them by clicking on the corresponding buttons on the main toolbar. You can also customize them by using the sliders and options on the right panel. You can apply materials by dragging and dropping them onto your models. You can add lighting by placing lights in the scene or by adjusting the sun and sky settings. You can add effects by choosing from the presets or by creating your own. You can add objects by browsing through the categories or by using the search function.</li>
-<li><strong>Render your images and videos</strong>: Lumion has a fast and easy rendering process that lets you create high-quality images and videos in minutes. You can access the rendering mode by clicking on the "Photo" or "Video" buttons on the main toolbar. You can also use the "Panorama" or "VR" buttons to create 360-degree images or VR scenes. You can adjust the resolution, quality, format, and other settings of your renderings on the right panel. You can also use the "Styles" button to apply different filters and effects to your renderings. When you are ready, click on the "Render" button and wait for Lumion to finish.</li>
-</ul>
-<p>These are just some of the basic tips and tricks on how to use Lumion 6 full crack for your projects. You can find more information and tutorials on <a href="">this page</a>. You can also check out some examples of projects made with Lumion below.</p>
-<h3>Examples of projects made with Lumion</h3>
-<p>Lumion is used by thousands of architects and designers around the world to create stunning renderings of their projects. Here are some examples of projects made with Lumion that you can get inspired by:</p>
-<ul>
-<li><a href="">A modern villa in Spain</a></li>
-<li><a href="">A luxury hotel in Dubai</a></li>
-<li><a href="">A futuristic city in China</a></li>
-</ul>
-<p>These are just some of the examples of projects made with Lumion. You can find more examples on <a href="https://lumion.com/gallery.html">this page</a>. You can also share your own projects with other users on <a href="https://forum.lumion.com/">this forum</a>.</p>
-<h2>Conclusion</h2>
-<p>Lumion is <p>Lumion is a powerful and easy-to-use software that lets you create realistic 3D renderings of your projects. It is compatible with most of the popular CAD software, and it has many features and options that can help you enhance your models. However, Lumion is also very expensive, and not everyone can afford it. That's why some people look for ways to download Lumion 6 full crack for free from Google Drive.</p>
-<p>In this article, we showed you how to do that step by step. We also gave you some tips and tricks on how to use Lumion 6 full crack for your projects, and some examples of projects made with Lumion. We hope you found this article useful and informative, and that you enjoyed using Lumion 6 full crack for your projects.</p>
-<p>If you have any questions or comments, feel free to leave them below. We would love to hear from you. And if you liked this article, please share it with your friends and colleagues who might be interested in Lumion 6 full crack. Thank you for reading!</p>
-<h2>FAQs</h2>
-<p>Here are some frequently asked questions about Lumion 6 full crack:</p>
-<h3>Is Lumion 6 full crack safe to use?</h3>
-<p>Lumion 6 full crack is not an official version of Lumion, and it is not supported by the developers. It is a modified version of Lumion that bypasses the activation process and allows you to use Lumion for free. However, this also means that Lumion 6 full crack might have some bugs, errors, or viruses that could harm your PC or your projects. Therefore, we do not recommend using Lumion 6 full crack, and we advise you to buy the official version of Lumion if you can afford it.</p>
-<h3>Does Lumion 6 full crack work on Mac?</h3>
-<p>No, Lumion 6 full crack does not work on Mac. Lumion is only compatible with Windows operating systems, and there is no official version of Lumion for Mac. Therefore, Lumion 6 full crack will not work on Mac either. If you want to use Lumion on Mac, you will need to use a virtual machine or a boot camp software that allows you to run Windows on Mac.</p>
-<h3>Can I update Lumion 6 full crack?</h3>
-<p>No, you cannot update Lumion 6 full crack. Lumion 6 full crack is a cracked version of Lumion that does not require activation or updates. If you try to update Lumion 6 full crack, you will lose the crack and the license key, and you will not be able to use Lumion anymore. Therefore, we advise you not to update Lumion 6 full crack, and to stick with the version that you downloaded from Google Drive.</p>
-<h3>Can I use Lumion 6 full crack online?</h3>
-<p>No, you cannot use Lumion 6 full crack online. Lumion 6 full crack is a offline version of Lumion that does not require internet connection or online services. If you try to use Lumion 6 full crack online, you will risk exposing your IP address and your identity, and you might get banned or reported by the developers or other users. Therefore, we advise you not to use Lumion 6 full crack online, and to use it only offline.</p>
-<h3>Can I share my projects made with Lumion 6 full crack?</h3>
-<p>Yes, you can share your projects made with Lumion 6 full crack. However, you need to be careful about how and where you share them. If you share them on social media or online platforms that are monitored by the developers or other users, you might get caught or reported for using a cracked version of Lumion. Therefore, we advise you to share your projects made with Lumion 6 full crack only with your trusted friends and colleagues who are also using the same version of Lumion.</p> 197e85843d<br />
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diff --git a/spaces/fatiXbelha/sd/Facebook APK - The Most Popular App for Java and Android.md b/spaces/fatiXbelha/sd/Facebook APK - The Most Popular App for Java and Android.md
deleted file mode 100644
index a7a1d1fe22ffecfe9405d9756f2ae026fdadb6aa..0000000000000000000000000000000000000000
--- a/spaces/fatiXbelha/sd/Facebook APK - The Most Popular App for Java and Android.md	
+++ /dev/null
@@ -1,145 +0,0 @@
-<br />
-<h1>Facebook APK Java Download: What You Need to Know</h1>
-<p>Facebook is one of the most popular social media platforms in the world. It allows you to connect with your friends and family, share photos and videos, play games, join groups, follow pages, and much more. However, if you are using an Android device, you might not be satisfied with the official Facebook app. It can be slow, heavy, buggy, and consume a lot of data and battery.</p>
-<p>That's why some people prefer to use Facebook APK Java instead. This is a modified version of the official app that runs on Java-based devices. It is faster, lighter, smoother, and more efficient than the original app. It also gives you access to some new features that are not available on the official app.</p>
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-<p>But before you decide to download Facebook APK Java, you should know some important things about it. In this article, we will tell you everything you need to know about Facebook APK Java download. We will cover its advantages and disadvantages, compatibility and requirements, features and updates, installation and usage, alternatives and comparisons. By the end of this article, you will be able to make an informed decision about whether or not you should download Facebook APK Java.</p>
- <h2>Advantages and Disadvantages of Facebook APK Java Download</h2>
-<h3>Advantages</h3>
-<p>There are many reasons why you might want to download Facebook APK Java instead of using the official app. Here are some of the advantages of using Facebook APK Java:</p>
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-<li><b>Faster performance:</b> Facebook APK Java is optimized for low-end devices that run on Java-based operating systems. It <p>loads faster and consumes less memory and CPU resources than the official app. It also has less ads and pop-ups that can slow down your browsing experience.</li>
-<li><b>Lower data usage:</b> Facebook APK Java is designed to use less data than the official app. It compresses images and videos, reduces the quality of media files, and caches data locally. It also has a data saver mode that lets you control how much data you want to use on Facebook. This can help you save money on your mobile data plan and avoid exceeding your data limit.</li>
-<li><b>Access to new features:</b> Facebook APK Java gives you access to some features that are not available on the official app. For example, you can download videos from Facebook to your device, customize your theme and font, view stories anonymously, and use multiple accounts. You can also enjoy some exclusive features that are only available on Facebook APK Java such as app lock, night mode, and voice changer.</li>
-</ul>
-<h3>Disadvantages</h3>
-<p>However, there are also some disadvantages of using Facebook APK Java that you should be aware of. Here are some of the drawbacks of using Facebook APK Java:</p>
-<ul>
-<li><b>Compatibility issues:</b> Facebook APK Java is not compatible with all Android devices and operating systems. It only works on devices that support Java-based applications such as Nokia, Samsung, LG, Sony Ericsson, Motorola, and BlackBerry. It also requires Android 4.0 or higher to run properly. If your device does not meet these requirements, you might not be able to download or install Facebook APK Java.</li>
-<li><b>Security risks:</b> Facebook APK Java is not an official app from Facebook. It is developed by third-party developers who might not follow the same security standards and policies as Facebook. This means that Facebook APK Java might contain malware, viruses, spyware, or other harmful software that can damage your device or steal your personal information. It might also violate your privacy by accessing your contacts, messages, photos, location, and other data without your permission.</li>
-<li><b>Limited support:</b> Facebook APK Java is not supported by Facebook. This means that if you encounter any problems or issues with the app, you might not be able to get help or assistance from Facebook. You might also miss out on some updates and bug fixes that are released by Facebook for the official app. Moreover, Facebook might block or ban your account if they detect that you are using an unauthorized app to access their platform.</li>
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- <h2>Compatibility and Requirements of Facebook APK Java Download</h2>
-<h3>Compatibility</h3>
-<p>As mentioned above, Facebook APK Java is not compatible with all Android devices and operating systems. It only works on devices that support Java-based applications such as Nokia, Samsung, LG, Sony Ericsson, Motorola, and BlackBerry. It also requires Android 4.0 or higher to run properly.</p>
-<p>To check if your device is compatible with Facebook APK Java, you can do the following steps:</p>
-<ol>
-<li>Go to <a href="">Settings</a> on your device.</li>
-<li>Tap on <a href="">About phone</a> or <a href="">About device</a>.</li>
-<li>Look for the <a href="">Model number</a> and the <a href="">Android version</a>.</li>
-<li>Compare them with the list of compatible devices and operating systems on the <a href="">Facebook APK Java website</a>.</li>
-<li>If your device and operating system match the list, then you can download Facebook APK Java. If not, then you might have to look for another alternative.</li>
-</ol>
- <h3>Requirements</h3>
-<p>Besides compatibility, there are also some other requirements that you need to meet before you can download and install Facebook APK Java on your device. These include permissions and settings that are needed for the app to function properly.</p>
-<p>To download and install Facebook APK Java on your device, you need to do the following steps:</p>
-<ol>
-<li>Enable <a href="">Unknown sources</a> on your device. This will allow you to install apps from sources other than the Google Play Store. To do this, go to <a href="">Settings</a>, then tap on <a href="">Security</a>, then toggle on <a href="">Unknown sources</a>.</li>
-<li>Download the latest version of Facebook APK Java from a trusted source such as the <a href="">Facebook APK Java website</a>. You can either scan the QR code on the website or enter the URL in your browser.</li>
-<li> <li>Open the downloaded file and tap on <a href="">Install</a>. You might see a warning message that says the app might harm your device. Ignore it and tap on <a href="">Install anyway</a>.</li>
-<li>Wait for the installation to complete and then tap on <a href="">Open</a>. You might also see a pop-up that asks you to allow Facebook APK Java to access your device's features and data. Tap on <a href="">Allow</a> or <a href="">Grant</a> for each request.</li>
-<li>Log in to your Facebook account using your email or phone number and password. You can also create a new account if you don't have one.</li>
-<li>Enjoy using Facebook APK Java on your device.</li>
-</ol>
- <h2>Features and Updates of Facebook APK Java Download</h2>
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-<li><b>Core functions:</b> Facebook APK Java lets you access all the core functions of Facebook such as posting, commenting, liking, sharing, reacting, tagging, messaging, calling, and more. You can also view your news feed, timeline, profile, notifications, friends, groups, pages, events, and more.</li>
-<li><b>Messenger integration:</b> Facebook APK Java integrates the messenger function into the app. This means that you don't need to download a separate app to chat with your friends on Facebook. You can also send and receive stickers, emojis, gifs, photos, videos, voice notes, and more.</li>
-<li><b>App links:</b> Facebook APK Java supports app links that let you open other apps from within Facebook. For example, you can open YouTube videos, Spotify songs, Instagram photos, and more without leaving the app.</li>
-<li><b>Audience network:</b> Facebook APK Java allows you to earn money by displaying ads from the Facebook audience network on your app. You can also control the type and frequency of ads that you want to show.</li>
-</ul>
-<h3>Updates</h3>
-<p>Facebook APK Java is updated regularly by its developers to fix bugs, improve performance, and add new features. You can get the latest version of Facebook APK Java by visiting the <a href="">Facebook APK Java website</a> or by checking for updates within the app.</p>
-<p>Here are some of the recent updates of Facebook APK Java:</p>
-<table>
-<tr><th>Date</th><th>Version</th><th>Changes</th></tr>
-<tr><td>June 23, 2023</td><td>1.0.5</td><td>- Added voice changer feature that lets you change your voice during calls<br>- Fixed some minor bugs and crashes<br>- Improved stability and speed</td></tr>
-<tr><td>May 15, 2023</td><td>1.0.4</td><td>- Added night mode feature that lets you switch to a dark theme<br>- Added app lock feature that lets you protect your app with a password or fingerprint<br>- Fixed some major bugs and errors<br>- Improved security and privacy</td></tr>
-<tr><td>April 10, 2023</td><td>1.0.3</td><td>- Added download video feature that lets you download videos from Facebook to your device<br>- Added customize theme feature that lets you change the color and font of your app<br>- Fixed some minor bugs and glitches<br>- Improved performance and efficiency</td></tr>
-<tr><td>March 5, 2023</td><td>1.0.2</td><td>- Added view stories anonymously feature that lets you view stories without showing your name<br>- Added multiple accounts feature that lets you use more than one account on the same app<br>- Fixed some major bugs and issues<br>- Improved compatibility and support</td></tr>
-<tr><td>February 1, 2023</td><td>1.0.1</td><td>- Initial release of Facebook APK Java<br>- Optimized for low-end devices that run on Java-based operating systems<br>- Faster, lighter, smoother, and more efficient than the official app<br>- Access to some new features that are not available on the official app</td></tr>
-</table>
- <h2>Installation and Usage of Facebook APK Java Download</h2>
-<h3>Installation</h3>
-<p>We have already explained how to download and install Facebook APK Java on your device in the previous section. However, if you need a reminder, here are the steps again:</p>
-<ol>
-<li>Enable <a href="">Unknown sources</a> on your device.</li>
-<li>Download the latest version of Facebook APK Java from a trusted source such as the <a href > href="">Facebook APK Java website</a>.</li>
-<li>Open the downloaded file and tap on <a href="">Install</a>.</li>
-<li>Wait for the installation to complete and then tap on <a href="">Open</a>.</li>
-<li>Log in to your Facebook account using your email or phone number and password.</li>
-<li>Enjoy using Facebook APK Java on your device.</li>
-</ol>
- <h3>Usage</h3>
-<p>Once you have installed Facebook APK Java on your device, you can start using it to access all the features and functions of Facebook. Here are some tips and tricks on how to use Facebook APK Java effectively and safely:</p>
-<ul>
-<li><b>Switch between accounts:</b> If you have more than one account on Facebook, you can easily switch between them using the multiple accounts feature. To do this, tap on the menu icon on the top right corner of the app, then tap on <a href="">Switch account</a>, then select the account you want to use.</li>
-<li><b>Download videos:</b> If you want to download videos from Facebook to your device, you can use the download video feature. To do this, tap on the video you want to download, then tap on the download icon on the bottom right corner of the video, then choose the quality and location of the video.</li>
-<li><b>Customize theme:</b> If you want to change the color and font of your app, you can use the customize theme feature. To do this, tap on the menu icon on the top right corner of the app, then tap on <a href="">Theme</a>, then choose the color and font you like.</li>
-<li><b>View stories anonymously:</b> If you want to view stories without showing your name, you can use the view stories anonymously feature. To do this, tap on the menu icon on the top right corner of the app, then tap on <a href="">Settings</a>, then toggle on <a href="">View stories anonymously</a>.</li>
-<li><b>Use voice changer:</b> If you want to change your voice during calls, you can use the voice changer feature. To do this, tap on the menu icon on the top right corner of the app, then tap on <a href="">Voice changer</a>, then choose the voice you want to use.</li>
-</ul>
- <h2>Alternatives and Comparisons of Facebook APK Java Download</h2>
-<h3>Alternatives</h3>
-<p>If you are not satisfied with Facebook APK Java or if it is not compatible with your device, you can try some other apps that can replace or complement Facebook APK Java. Here are some of the alternatives that you can consider:</p>
-<ul>
-<li><b>Facebook Lite:</b> This is an official app from Facebook that is designed for low-end devices and slow networks. It is similar to Facebook APK Java in terms of performance, data usage, and features. However, it is more secure, supported, and updated than Facebook APK Java. You can download it from the Google Play Store or from <a href="">here</a>.</li>
-<li><b>Folio:</b> This is a third-party app that lets you access Facebook and other social media platforms such as Twitter, Instagram, LinkedIn, and more from one app. It is faster, lighter, and more customizable than Facebook APK Java. It also has some unique features such as night mode, ad blocker, and smart notifications. You can download it from the Google Play Store or from <a href="">here</a>.</li>
-<li><b>Friendly Social Browser:</b> This is another third-party app that lets you access Facebook and other social media platforms such as YouTube, Reddit, Tumblr, and more from one app. It is similar to Folio in terms of performance, features, and customization. It also has some additional features such as fingerprint lock, download manager, and privacy mode. You can download it from the Google Play Store or from <a href="">here</a>.</li>
-</ul>
- <h3>Comparisons</h3>
-<p>To help you decide which app is best for you, here are some comparisons between Facebook APK Java and the official Facebook app and other alternatives in terms of performance, features, and user experience:</p>
- <table>
-<tr><th></th><th>Facebook APK Java</th><th>Official Facebook App</th><th>Facebook Lite</th><th>Folio</th><th>Friendly Social Browser</th></tr>
-<tr><td><b>Performance</b></td><td>Faster than official app<br>Lighter than official app<br>Smoother than official app<br>More efficient than official app</td><td>Slower than other apps<br>Heavier than other apps<br>Buggier than other apps<br>Less efficient than other apps</td><td>Faster on your device. However, you might encounter some conflicts or errors if you use both apps at the same time. Therefore, we recommend that you use only one app at a time to avoid any problems.</li>
-<li><b>Q: What are some other apps that are similar to Facebook APK Java?</b></li>
-<li>A: Some other apps that are similar to Facebook APK Java are Facebook Lite, Folio, and Friendly Social Browser. These apps are also faster, lighter, smoother, and more efficient than the official app. They also have some unique features that can enhance your Facebook experience. You can compare them with Facebook APK Java and choose the one that suits your needs and preferences.</li>
-</ul></p> 401be4b1e0<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/fb700/chatglm-fitness-RLHF/app bak.py b/spaces/fb700/chatglm-fitness-RLHF/app bak.py
deleted file mode 100644
index c72270a0513fec1b10d0b1e482999f8987e1a1e3..0000000000000000000000000000000000000000
--- a/spaces/fb700/chatglm-fitness-RLHF/app bak.py	
+++ /dev/null
@@ -1,386 +0,0 @@
-"""Credit to https://github.com/THUDM/ChatGLM2-6B/blob/main/web_demo.py while mistakes are mine."""
-# pylint: disable=broad-exception-caught, redefined-outer-name, missing-function-docstring, missing-module-docstring, too-many-arguments, line-too-long, invalid-name, redefined-builtin, redefined-argument-from-local
-# import gradio as gr
-
-# model_name = "fb700/chatglm-fitness-RLHF"
-# gr.load(model_name).lauch()
-
-# %%writefile demo-4bit.py
-
-import os
-import time
-from textwrap import dedent
-
-import gradio as gr
-import mdtex2html
-import torch
-from loguru import logger
-from transformers import AutoModel, AutoTokenizer
-
-# fix timezone in Linux
-os.environ["TZ"] = "Asia/Shanghai"
-try:
-    time.tzset()  # type: ignore # pylint: disable=no-member
-except Exception:
-    # Windows
-    logger.warning("Windows, cant run time.tzset()")
-
-# model_name = "THUDM/chatglm2-6b"  # 7x?G
-model_name = "fb700/chatglm-fitness-RLHF"  # 3.9G
-
-RETRY_FLAG = False
-
-tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
-
-# model = AutoModel.from_pretrained(model_name, trust_remote_code=True).cuda()
-
-# 4/8 bit
-# model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).quantize(4).cuda()
-
-has_cuda = torch.cuda.is_available()
-# has_cuda = False  # force cpu
-
-if has_cuda:
-    if model_name.endswith("int4"):
-        model = AutoModel.from_pretrained(model_name, trust_remote_code=True).cuda()
-    else:
-        model = (
-            AutoModel.from_pretrained(model_name, trust_remote_code=True).cuda().half()
-        )
-else:
-    model = AutoModel.from_pretrained(
-        model_name, trust_remote_code=True
-    ).float()  #  .half().float(), .float() required for CPU
-
-model = model.eval()
-
-_ = """Override Chatbot.postprocess"""
-
-
-def postprocess(self, y):
-    if y is None:
-        return []
-    for i, (message, response) in enumerate(y):
-        y[i] = (
-            None if message is None else mdtex2html.convert((message)),
-            None if response is None else mdtex2html.convert(response),
-        )
-    return y
-
-
-gr.Chatbot.postprocess = postprocess
-
-
-def parse_text(text):
-    """Copy from https://github.com/GaiZhenbiao/ChuanhuChatGPT/."""
-    lines = text.split("\n")
-    lines = [line for line in lines if line != ""]
-    count = 0
-    for i, line in enumerate(lines):
-        if "```" in line:
-            count += 1
-            items = line.split("`")
-            if count % 2 == 1:
-                lines[i] = f'<pre><code class="language-{items[-1]}">'
-            else:
-                lines[i] = "<br></code></pre>"
-        else:
-            if i > 0:
-                if count % 2 == 1:
-                    line = line.replace("`", r"\`")
-                    line = line.replace("<", "&lt;")
-                    line = line.replace(">", "&gt;")
-                    line = line.replace(" ", "&nbsp;")
-                    line = line.replace("*", "&ast;")
-                    line = line.replace("_", "&lowbar;")
-                    line = line.replace("-", "&#45;")
-                    line = line.replace(".", "&#46;")
-                    line = line.replace("!", "&#33;")
-                    line = line.replace("(", "&#40;")
-                    line = line.replace(")", "&#41;")
-                    line = line.replace("$", "&#36;")
-                lines[i] = "<br>" + line
-    text = "".join(lines)
-    return text
-
-
-def predict(
-    RETRY_FLAG, input, chatbot, max_length, top_p, temperature, history, past_key_values
-):
-    try:
-        chatbot.append((parse_text(input), ""))
-    except Exception as exc:
-        logger.error(exc)
-        logger.debug(f"{chatbot=}")
-        _ = """
-        if chatbot:
-            chatbot[-1] = (parse_text(input), str(exc))
-            yield chatbot, history, past_key_values
-        # """
-        yield chatbot, history, past_key_values
-
-    for response, history in model.stream_chat(
-        tokenizer,
-        input,
-        history,
-        past_key_values=past_key_values,
-        return_past_key_values=True,
-        max_length=max_length,
-        top_p=top_p,
-        temperature=temperature,
-    ):
-        chatbot[-1] = (parse_text(input), parse_text(response))
-
-        yield chatbot, history, past_key_values
-
-
-def trans_api(input, max_length=40960, top_p=0.8, temperature=0.2):
-    if max_length < 10:
-        max_length = 4096
-    if top_p < 0.1 or top_p > 1:
-        top_p = 0.85
-    if temperature <= 0 or temperature > 1:
-        temperature = 0.01
-    try:
-        res, _ = model.chat(
-            tokenizer,
-            input,
-            history=[],
-            past_key_values=None,
-            max_length=max_length,
-            top_p=top_p,
-            temperature=temperature,
-        )
-        # logger.debug(f"{res=} \n{_=}")
-    except Exception as exc:
-        logger.error(f"{exc=}")
-        res = str(exc)
-
-    return res
-
-
-def reset_user_input():
-    return gr.update(value="")
-
-
-def reset_state():
-    return [], [], None
-
-
-# Delete last turn
-def delete_last_turn(chat, history):
-    if chat and history:
-        chat.pop(-1)
-        history.pop(-1)
-    return chat, history
-
-
-# Regenerate response
-def retry_last_answer(
-    user_input, chatbot, max_length, top_p, temperature, history, past_key_values
-):
-    if chatbot and history:
-        # Removing the previous conversation from chat
-        chatbot.pop(-1)
-        # Setting up a flag to capture a retry
-        RETRY_FLAG = True
-        # Getting last message from user
-        user_input = history[-1][0]
-        # Removing bot response from the history
-        history.pop(-1)
-
-    yield from predict(
-        RETRY_FLAG,  # type: ignore
-        user_input,
-        chatbot,
-        max_length,
-        top_p,
-        temperature,
-        history,
-        past_key_values,
-    )
-
-
-with gr.Blocks(title="ChatGLM2-6B-int4", theme=gr.themes.Soft(text_size="sm")) as demo:
-    # gr.HTML("""<h1 align="center">ChatGLM2-6B-int4</h1>""")
-    gr.HTML(
-        """<center><a href="https://huggingface.co/spaces/mikeee/chatglm2-6b-4bit?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>To avoid the queue and for faster inference Duplicate this Space and upgrade to GPU</center>"""
-    )
-
-    with gr.Accordion("🎈 Info", open=False):
-        _ = f"""
-            ## {model_name}
-
-            Try to refresh the browser and try again when  occasionally an error occurs.
-
-            With a GPU, a query takes from a few seconds to a few tens of seconds, dependent on the number of words/characters
-            the question and responses contain. The quality of the responses varies quite a bit it seems. Even the same
-            question with the same parameters, asked at different times, can result in quite different responses.
-
-            * Low temperature: responses will be more deterministic and focused; High temperature: responses more creative.
-
-            * Suggested temperatures -- translation: up to 0.3; chatting: > 0.4
-
-            * Top P controls dynamic vocabulary selection based on context.
-
-            For a table of example values for different scenarios, refer to [this](https://community.openai.com/t/cheat-sheet-mastering-temperature-and-top-p-in-chatgpt-api-a-few-tips-and-tricks-on-controlling-the-creativity-deterministic-output-of-prompt-responses/172683)
-
-            If the instance is not on a GPU (T4), it will be very slow. You can try to run the colab notebook [chatglm2-6b-4bit colab notebook](https://colab.research.google.com/drive/1WkF7kOjVCcBBatDHjaGkuJHnPdMWNtbW?usp=sharing) for a spin.
-
-            The T4 GPU is sponsored by a community GPU grant from Huggingface. Thanks a lot!
-            """
-        gr.Markdown(dedent(_))
-    chatbot = gr.Chatbot()
-    with gr.Row():
-        with gr.Column(scale=4):
-            with gr.Column(scale=12):
-                user_input = gr.Textbox(
-                    show_label=False,
-                    placeholder="Input...",
-                ).style(container=False)
-                RETRY_FLAG = gr.Checkbox(value=False, visible=False)
-            with gr.Column(min_width=32, scale=1):
-                with gr.Row():
-                    submitBtn = gr.Button("Submit", variant="primary")
-                    deleteBtn = gr.Button("Delete last turn", variant="secondary")
-                    retryBtn = gr.Button("Regenerate", variant="secondary")
-        with gr.Column(scale=1):
-            emptyBtn = gr.Button("Clear History")
-            max_length = gr.Slider(
-                0,
-                32768,
-                value=8192,
-                step=1.0,
-                label="Maximum length",
-                interactive=True,
-            )
-            top_p = gr.Slider(
-                0, 1, value=0.85, step=0.01, label="Top P", interactive=True
-            )
-            temperature = gr.Slider(
-                0.01, 1, value=0.95, step=0.01, label="Temperature", interactive=True
-            )
-
-    history = gr.State([])
-    past_key_values = gr.State(None)
-
-    user_input.submit(
-        predict,
-        [
-            RETRY_FLAG,
-            user_input,
-            chatbot,
-            max_length,
-            top_p,
-            temperature,
-            history,
-            past_key_values,
-        ],
-        [chatbot, history, past_key_values],
-        show_progress="full",
-    )
-    submitBtn.click(
-        predict,
-        [
-            RETRY_FLAG,
-            user_input,
-            chatbot,
-            max_length,
-            top_p,
-            temperature,
-            history,
-            past_key_values,
-        ],
-        [chatbot, history, past_key_values],
-        show_progress="full",
-        api_name="predict",
-    )
-    submitBtn.click(reset_user_input, [], [user_input])
-
-    emptyBtn.click(
-        reset_state, outputs=[chatbot, history, past_key_values], show_progress="full"
-    )
-
-    retryBtn.click(
-        retry_last_answer,
-        inputs=[
-            user_input,
-            chatbot,
-            max_length,
-            top_p,
-            temperature,
-            history,
-            past_key_values,
-        ],
-        # outputs = [chatbot, history, last_user_message, user_message]
-        outputs=[chatbot, history, past_key_values],
-    )
-    deleteBtn.click(delete_last_turn, [chatbot, history], [chatbot, history])
-
-    with gr.Accordion("Example inputs", open=True):
-        etext = """In America, where cars are an important part of the national psyche, a decade ago people had suddenly started to drive less, which had not happened since the oil shocks of the 1970s. """
-        examples = gr.Examples(
-            examples=[
-                ["What NFL team won the Super Bowl in the year Justin Bieber was born? "],
-                ["What NFL team won the Super Bowl in the year Justin Bieber was born? Think step by step."],
-                ["Explain the plot of Cinderella in a sentence."],
-                [
-                    "How long does it take to become proficient in French, and what are the best methods for retaining information?"
-                ],
-                ["What are some common mistakes to avoid when writing code?"],
-                ["Build a prompt to generate a beautiful portrait of a horse"],
-                ["Suggest four metaphors to describe the benefits of AI"],
-                ["Write a pop song about leaving home for the sandy beaches."],
-                ["Write a summary demonstrating my ability to tame lions"],
-                ["鲁迅和周树人什么关系"],
-                ["从前有一头牛，这头牛后面有什么？"],
-                ["正无穷大加一大于正无穷大吗？"],
-                ["正无穷大加正无穷大大于正无穷大吗？"],
-                ["-2的平方根等于什么"],
-                ["树上有5只鸟，猎人开枪打死了一只。树上还有几只鸟？"],
-                ["树上有11只鸟，猎人开枪打死了一只。树上还有几只鸟？提示：需考虑鸟可能受惊吓飞走。"],
-                ["鲁迅和周树人什么关系 用英文回答"],
-                ["以红楼梦的行文风格写一张委婉的请假条。不少于320字。"],
-                [f"{etext} 翻成中文，列出3个版本"],
-                [f"{etext} \n 翻成中文，保留原意，但使用文学性的语言。不要写解释。列出3个版本"],
-                ["js 判断一个数是不是质数"],
-                ["js 实现python 的 range(10)"],
-                ["js 实现python 的 [*(range(10)]"],
-                ["假定 1 + 2 = 4, 试求 7 + 8"],
-                ["Erkläre die Handlung von Cinderella in einem Satz."],
-                ["Erkläre die Handlung von Cinderella in einem Satz. Auf Deutsch"],
-            ],
-            inputs=[user_input],
-            examples_per_page=30,
-        )
-
-    with gr.Accordion("For Chat/Translation API", open=False, visible=False):
-        input_text = gr.Text()
-        tr_btn = gr.Button("Go", variant="primary")
-        out_text = gr.Text()
-    tr_btn.click(
-        trans_api,
-        [input_text, max_length, top_p, temperature],
-        out_text,
-        # show_progress="full",
-        api_name="tr",
-    )
-    _ = """
-    input_text.submit(
-        trans_api,
-        [input_text, max_length, top_p, temperature],
-        out_text,
-        show_progress="full",
-        api_name="tr1",
-    )
-    # """
-
-# demo.queue().launch(share=False, inbrowser=True)
-# demo.queue().launch(share=True, inbrowser=True, debug=True)
-
-# concurrency_count > 1 requires more memory, max_size: queue size
-# T4 medium: 30GB, model size: ~4G concurrency_count = 6
-# leave one for api access
-# reduce to 5 if OOM occurs to often
-
-demo.queue(concurrency_count=6, max_size=30).launch(debug=True)
diff --git a/spaces/fbeckk/cell-seg/openvino_utils.py b/spaces/fbeckk/cell-seg/openvino_utils.py
deleted file mode 100644
index 036ea38f11adfa7d6a32986b2713bf9398ab036e..0000000000000000000000000000000000000000
--- a/spaces/fbeckk/cell-seg/openvino_utils.py
+++ /dev/null
@@ -1,97 +0,0 @@
-import math
-
-import numpy as np
-
-import dynamics
-import transforms
-
-
-def _ov_batch_gradient_style(model, image):
-    result = model(image)
-    result = {k.get_any_name(): v for k, v in result.items()}
-    return result["gradients"], result["styles"]
-
-
-def _ov_tiled_inference(
-    model,
-    x: np.ndarray,
-    patch_size: int = 224,
-    tile_overlap: float = 0.1,
-    n_classes: int = 3,
-    batch_size: int = 64,
-):
-    assert x.ndim == 3, "yikes"
-    x, y_sub, x_sub = transforms.pad_image(x)
-
-    slc = [slice(0, x.shape[n] + 1) for n in range(x.ndim)]
-    slc[-3] = slice(0, n_classes + 1)
-    slc[-2] = slice(y_sub[0], y_sub[-1] + 1)
-    slc[-1] = slice(x_sub[0], x_sub[-1] + 1)
-    slc = tuple(slc)
-
-    patches, y_sub, x_sub = transforms.split_in_patches(
-        x,
-        patch_size=patch_size,
-        tile_overlap=tile_overlap,
-    )
-
-    _, height, width = x.shape
-    n_y, n_x, n_channels, patch_height, patch_width = patches.shape
-
-    patches = np.reshape(patches,
-                         (n_y * n_x, n_channels, patch_height, patch_width))
-    y = np.zeros((n_y * n_x, n_classes, patch_height, patch_width))
-
-    styles = None
-    for k in range(math.ceil(patches.shape[0] / batch_size)):
-        batch_indexes = np.arange(
-            batch_size * k, min(patches.shape[0], batch_size * k + batch_size))
-        y0, style = _ov_batch_gradient_style(
-            model=model,
-            image=patches[batch_indexes],
-        )
-
-        y[batch_indexes] = y0
-
-        if k == 0:
-            styles = style[0]
-        styles += style.sum(axis=0)
-
-    styles /= patches.shape[0]
-
-    yf = transforms.average_patches(y, y_sub, x_sub, height, width)
-    yf = yf[:, :x.shape[1], :x.shape[2]]
-
-    styles /= (styles**2).sum()**0.5
-
-    yf = np.transpose(yf[slc], (1, 2, 0))
-
-    return yf, styles
-
-
-def ov_inference(
-    model,
-    x: np.ndarray,
-    rescale: float = 1.,
-    cell_probability_threshold: float = .0,
-    flow_threshold: float = .4,
-    interp: bool = False,
-) -> np.ndarray:
-
-    y, style = _ov_tiled_inference(model=model, x=x)
-
-    cell_probability = y[:, :, 2]
-    gradients = y[:, :, :2].transpose((2, 0, 1))
-
-    mask, _ = dynamics.compute_masks(
-        gradients,
-        cell_probability,
-        n_iter=(1 / rescale) * 200,
-        cell_probability_threshold=cell_probability_threshold,
-        flow_threshold=flow_threshold,
-        interp=interp,
-        device='cpu',
-        use_gpu=False,
-    )
-
-    return mask.squeeze()
diff --git a/spaces/feregVcuzo/sanity-test-midi/checkpoint/Discover New Manga with Manga Pro Z APK.md b/spaces/feregVcuzo/sanity-test-midi/checkpoint/Discover New Manga with Manga Pro Z APK.md
deleted file mode 100644
index 63c7eebbb7386761f77f6f50b1bde4d4615b37e9..0000000000000000000000000000000000000000
--- a/spaces/feregVcuzo/sanity-test-midi/checkpoint/Discover New Manga with Manga Pro Z APK.md	
+++ /dev/null
@@ -1,107 +0,0 @@
-
-<h1>Manga Pro Z APK: The Ultimate Manga Reader App</h1>
-<p>If you are a manga lover, you know how hard it can be to find a good manga reader app that suits your needs. You want an app that has a large and diverse library of manga comics, a fast and user-friendly interface, a customizable and immersive reading experience, and a supportive and creative community of manga fans and creators. Well, look no further than Manga Pro Z APK, the ultimate manga reader app for Android devices.</p>
-<h2>manga pro z apk</h2><br /><p><b><b>Download File</b> &middot;&middot;&middot; <a href="https://gohhs.com/2uPrlS">https://gohhs.com/2uPrlS</a></b></p><br /><br />
-<h2>What is Manga Pro Z APK?</h2>
-<h3>A brief introduction to the app and its features</h3>
-<p>Manga Pro Z APK is a free manga reader app that allows you to read thousands of manga comics online and offline from various sources. You can find both classic and new mangas in different genres, such as action, romance, comedy, horror, fantasy, sci-fi, and more. You can also read some Korean comics from WEBTOON.</p>
-<p>Some of the features of Manga Pro Z APK are:</p>
-<ul>
-<li>You can subscribe to your favorite mangas and get notified when there is a new chapter.</li>
-<li>You can download mangas for offline reading.</li>
-<li>You can create your own comic stories and share them with other readers.</li>
-<li>You can comment on mangas and interact with other manga fans.</li>
-<li>You can access the latest mangas just an hour after they are published.</li>
-<li>You can read Crunchyroll Originals, exclusive mangas from the renowned anime brand.</li>
-</ul>
-<h3>How to download and install the app on your device</h3>
-<p>Downloading and installing Manga Pro Z APK is very easy. Just follow these steps:</p>
-<ol>
-<li>Go to [this link](^1^) and click on the download button.</li>
-<li>Wait for the file to download on your device.</li>
-<li>Go to your file manager and locate the downloaded file.</li>
-<li>Tap on the file and allow unknown sources if prompted.</li>
-<li>Follow the instructions on the screen to install the app.</li>
-<li>Enjoy reading mangas with Manga Pro Z APK.</li>
-</ol>
-<h2>Why Manga Pro Z APK is the best manga reader app</h2>
-<h3>A large and diverse library of manga comics</h3>
-<p>One of the main reasons why Manga Pro Z APK is the best manga reader app is because it has a large and diverse library of manga comics. You can find over a thousand sources of mangas from different countries, languages, genres, themes, and styles. You can also discover new mangas based on popularity, updates, promotions, or alphabetical order. Whether you are looking for vintage or recent mangas, you will find them on Manga Pro Z APK.</p>
-<p>manga pro z apk download<br />
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-<h3>A customizable and immersive reading experience</h3>
-<p>A third reason why Manga Pro Z APK is the best manga reader app is because it offers a customizable and immersive reading experience. The app allows you to read mangas in HD quality with clear images and texts. You can also choose from different reading modes, such as horizontal or vertical scrolling, page curling, or webtoon mode. You can also zoom in or out, rotate, or crop the manga pages to fit your screen size. You can also change the brightness, contrast, or color of the manga pages to suit your eyesight. Moreover, you can read mangas with sound effects and music to enhance your immersion.</p>
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-<p>A fourth reason why Manga Pro Z APK is the best manga reader app is because it has a supportive and creative community of manga fans and creators. The app allows you to comment on mangas and interact with other readers who share your passion. You can also rate and review mangas and give feedback to the authors. You can also create your own comic stories and share them with other users. You can use the app's built-in tools to draw, edit, and publish your own mangas. You can also join contests and challenges and win prizes and recognition.</p>
-<h2>Alternatives to Manga Pro Z APK</h2>
-<p>While Manga Pro Z APK is the best manga reader app, there are some alternatives that you can try if you want to explore other options. Here are some of them:</p>
-<h3>Tachiyomi</h3>
-<p>Tachiyomi is an open-source manga reader app that lets you read mangas from various sources, such as MangaDex, MangaSee, MangaKakalot, etc. You can also download mangas for offline reading, customize your reading settings, and organize your library. However, Tachiyomi is not available on the Google Play Store, so you have to download it from its official website or GitHub.</p>
-<h3>Manga Toon</h3>
-<p>Manga Toon is a popular manga reader app that offers a large collection of mangas in different genres and languages. You can also read original comics from talented authors and artists. You can also download mangas for offline reading, comment on mangas, and earn coins to unlock premium chapters. However, Manga Toon has some ads and pop-ups that might annoy you.</p>
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-<p>Manga Zone is another manga reader app that provides a huge library of mangas in various categories and updates. You can also download mangas for offline reading, bookmark your favorite mangas, and share your opinions with other readers. However, Manga Zone has some issues with loading speed and stability.</p>
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-<p>Manga Pro Z APK is the ultimate manga reader app for Android devices. It has a large and diverse library of manga comics, a fast and user-friendly interface, a customizable and immersive reading experience, and a supportive and creative community of manga fans and creators. It is free to download and use, and it does not have any ads or pop-ups. If you are a manga lover, you should definitely try Manga Pro Z APK.</p>
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-<tr><td>Is Manga Pro Z APK safe to use?</td><td>Yes, Manga Pro Z APK is safe to use. It does not contain any viruses or malware. However, you should always download it from a trusted source.</td></tr>
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-</table></p> 401be4b1e0<br />
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diff --git a/spaces/feregVcuzo/sanity-test-midi/checkpoint/Download Dream League Soccer 2019 UCL Edition and Experience the Thrill of the Champions League on Your Android Device.md b/spaces/feregVcuzo/sanity-test-midi/checkpoint/Download Dream League Soccer 2019 UCL Edition and Experience the Thrill of the Champions League on Your Android Device.md
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-<p>If you are a fan of soccer games, you must have heard of Dream League Soccer 2019, one of the most popular and realistic soccer games for Android. But did you know that you can also play the UEFA Champions League Edition, which adds more excitement and challenge to your gaming experience? In this article, we will tell you everything you need to know about Dream League Soccer 2019 and how to download and install the UEFA Champions League Edition on your device.</p>
- <h2>What is Dream League Soccer 2019?</h2>
-<p>Dream League Soccer 2019 is a soccer game that lets you create and manage your own team, compete in various leagues and tournaments, and enjoy the thrill of playing soccer on your mobile device. You can choose from over 3500 licensed players, customize your stadium, kits, and logos, and play online against other players from around the world. You can also play offline in career mode, where you can rise from the lower divisions to the top of the world.</p>
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- <h3>Features of Dream League Soccer 2019</h3>
-<p>Some of the features that make Dream League Soccer 2019 stand out from other soccer games are:</p>
-<ul>
-<li>Realistic gameplay and graphics: The game uses advanced AI and motion capture technology to create realistic animations and physics. The game also has stunning graphics and sound effects that make you feel like you are in a real stadium.</li>
-<li>Freedom and creativity: The game gives you the freedom to create your own team, stadium, kits, and logos. You can also customize your players' appearance, skills, and attributes. You can also design your own tactics and formations to suit your style of play.</li>
-<li>Variety and challenge: The game offers a variety of modes and levels to keep you entertained and challenged. You can play in different leagues and cups, such as the English Premier League, the Spanish La Liga, the German Bundesliga, the Italian Serie A, the French Ligue 1, the UEFA Champions League, the UEFA Europa League, and more. You can also play online against other players or offline against the AI.</li>
-<li>Rewards and achievements: The game rewards you with coins and gems for winning matches, completing objectives, and achieving milestones. You can use these currencies to buy new players, upgrade your stadium, unlock new kits and logos, and more. You can also earn trophies and medals for your achievements.</li>
-</ul>
- <h3>How to play Dream League Soccer 2019</h3>
-<p>To play Dream League Soccer 2019, you need to download and install the game on your Android device. You can find the game on Google Play Store or on other websites that offer APK files. The game is free to download and play, but it contains in-app purchases that allow you to buy more coins and gems.</p>
-<p>Once you have installed the game, you can start playing by choosing a mode. You can either play online or offline. If you choose online mode, you need to have an internet connection and a registered account. You can then join or create a league or a tournament and compete with other players from around the world. If you choose offline mode, you can play career mode or quick match mode. In career mode, you start from the bottom division and work your way up to the top by winning matches and earning points. In quick match mode, you can play a single match against any team of your choice.</p>
-<p>To control your players on the field, you can use the virtual buttons on the screen or tilt your device. You can also adjust the difficulty level, camera angle, sound settings, and other options in the settings menu.</p>
- <h2>What is UEFA Champions League Edition <h2>What is UEFA Champions League Edition?</h2>
-<p>UEFA Champions League Edition is a special version of Dream League Soccer 2019 that allows you to play the most prestigious club competition in Europe, the UEFA Champions League. You can choose from 32 teams that qualified for the group stage of the 2018-19 season, such as Real Madrid, Barcelona, Juventus, Manchester City, Liverpool, Bayern Munich, Paris Saint-Germain, and more. You can also play with legendary players like Cristiano Ronaldo, Lionel Messi, Neymar, Kylian Mbappe, Mohamed Salah, and more.</p>
- <h3>Benefits of playing UEFA Champions League Edition</h3>
-<p>Some of the benefits of playing UEFA Champions League Edition are:</p>
-<ul>
-<li>More excitement and challenge: The UEFA Champions League is the ultimate test of your skills and tactics as you face the best teams and players in Europe. You can experience the thrill and pressure of playing in the knockout stages, where every goal and every mistake can make a difference. You can also enjoy the atmosphere and the music of the UEFA Champions League anthem.</li>
-<li>More rewards and achievements: The UEFA Champions League Edition offers you more coins and gems for winning matches and completing objectives. You can also earn exclusive trophies and medals for winning the UEFA Champions League title or becoming the top scorer or the best player of the tournament.</li>
-<li>More fun and variety: The UEFA Champions League Edition adds more fun and variety to your gaming experience as you can play with different teams and players that have different strengths and weaknesses. You can also explore different stadiums and cities that host the UEFA Champions League matches.</li>
-</ul>
- <h3>How to download and install UEFA Champions League Edition</h3>
-<p>To download and install UEFA Champions League Edition, you need to follow these steps:</p>
-<ol>
-<li>Download the APK file of Dream League Soccer 2019 UEFA Champions League Edition from below. The file size is about 350 MB.</li>
-<li>Enable unknown sources on your device by going to Settings > Security > Unknown Sources.</li>
-<li>Install the APK file by tapping on it and following the instructions.</li>
-<li>Download the OBB file of Dream League Soccer 2019 UEFA Champions League Edition from below. The file size is about 1.5 GB.</li>
-<li>Extract the OBB file using a file manager app or a zip extractor app.</li>
-<li>Copy the extracted folder named com.firsttouchgames.dls3 to Android > OBB on your device.</li>
-<li>Launch the game and enjoy playing Dream League Soccer 2019 UEFA Champions League Edition.</li>
-</ol>
- <h2>Tips and tricks for playing Dream League Soccer 2019 UEFA Champions League Edition</h2>
-<p>To improve your performance and have more fun playing Dream League Soccer 2019 UEFA Champions League Edition, you can use these tips and tricks:</p>
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- <h3>How to build your dream team</h3>
-<p>To build your dream team, you need to consider these factors:</p>
-<ul>
-<li>Budget: You have a limited budget to buy new players or upgrade your existing ones. You need to balance your spending between quality and quantity. You can also sell your unwanted players to free up some funds.</li>
-<li>Ratings: Each player has a rating from 1 to 100 that reflects their overall ability. You can check their ratings by tapping on their profile. You should aim for players with high ratings or potential ratings that suit your style of play.</li>
-<li>Positions: Each player has a preferred position on the field, such as goalkeeper, defender, midfielder, or forward. You can check their positions by tapping on their profile. You should arrange your players according to their positions and roles on the field.</li>
-<li>Chemistry: Each player has a chemistry level with their teammates that affects their performance on the field. You can check their chemistry level by tapping on their profile. You should aim for players with high chemistry levels or similar nationalities or clubs.</li>
-</ul>
- <h3>How to improve your skills and tactics</h3>
-<p>To improve your skills and tactics, you need to practice these aspects:</p>
-<ul>
-<li>Controls: You need to master the virtual buttons or tilt controls on the screen to control your players on the field. You can also adjust the sensitivity and layout of the controls in the settings menu.</li>
-<li>Movements: You need to learn how to move your players on the field using the joystick or tilt controls. You can also use gestures such as swipe, tap, or double tap to perform actions such as sprint, pass, shoot, tackle, or switch players.</li>
-<li>Strategies: You need to learn how to use different strategies on the field depending on the situation. You can use the strategy button on the screen to change your formation, style of play, or instructions for your players.</li <li>Skills: You need to learn how to use different skills on the field to outsmart your opponents. You can use the skill button on the screen to perform skills such as dribble, feint, nutmeg, rainbow, roulette, or heel flick.</li>
-</ul>
- <h3>How to earn coins and rewards</h3>
-<p>To earn coins and rewards, you need to do these things:</p>
-<ul>
-<li>Win matches: You can earn coins and gems for winning matches in any mode. The amount of coins and gems depends on the difficulty level, the score, and the objectives. You can also earn bonus coins and gems for winning streaks, clean sheets, hat-tricks, or comebacks.</li>
-<li>Complete objectives: You can earn coins and gems for completing objectives in career mode or online mode. The objectives vary from scoring goals, making assists, winning matches, or reaching milestones. You can check your objectives by tapping on the trophy icon on the screen.</li>
-<li>Watch ads: You can earn coins and gems for watching ads in the game. You can watch ads by tapping on the video icon on the screen. You can watch up to 10 ads per day.</li>
-<li>Use codes: You can earn coins and gems for using codes in the game. You can find codes on the official social media pages of Dream League Soccer 2019 or on other websites that offer codes. You can use codes by tapping on the settings icon on the screen and then tapping on the code icon.</li>
-</ul>
- <h2>Conclusion</h2>
-<h3>Summary of the article</h3>
-<p>In this article, we have explained what Dream League Soccer 2019 is and how to play it. We have also introduced you to the UEFA Champions League Edition, which is a special version of the game that lets you play the most prestigious club competition in Europe. We have also given you some tips and tricks for building your dream team, improving your skills and tactics, and earning coins and rewards.</p>
- <h3>Call to action</h3>
-<p>If you are ready to download and install Dream League Soccer 2019 UEFA Champions League Edition on your device, you can use the link below. The link will take you to a secure website where you can download the APK file and the OBB file of the game. Follow the instructions given in this article to install the game and enjoy playing it.</p>
-<p>Download Dream League Soccer 2019 UEFA Champions League Edition from below:</p>
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-<p>Here are some frequently asked questions about Dream League Soccer 2019 UEFA Champions League Edition:</p>
-<ol>
-<li>Q: Is Dream League Soccer 2019 UEFA Champions League Edition free to play?<br>A: Yes, Dream League Soccer 2019 UEFA Champions League Edition is free to download and play, but it contains in-app purchases that allow you to buy more coins and gems.</li>
-<li>Q: Is Dream League Soccer 2019 UEFA Champions League Edition compatible with my device?<br>A: Dream League Soccer 2019 UEFA Champions League Edition requires Android 4.4 or higher and at least 2 GB of RAM and 2 GB of free storage space.</li>
-<li>Q: Is Dream League Soccer 2019 UEFA Champions League Edition safe to download and install?<br>A: Yes, Dream League Soccer 2019 UEFA Champions League Edition is safe to download and install as long as you use the link provided in this article. The link will take you to a secure website that has been verified by Google Play Protect.</li>
-<li>Q: How can I update Dream League Soccer 2019 UEFA Champions League Edition?<br>A: You can update Dream League Soccer 2019 UEFA Champions League Edition by downloading and installing the latest version of the APK file and the OBB file from the link provided in this article. You do not need to uninstall the previous version of the game.</li>
-<li>Q: How can I contact the developers of Dream League Soccer 2019 UEFA Champions League Edition?<br>A: You can contact the developers of Dream League Soccer 2019 UEFA Champions League Edition by visiting their official website or their official social media pages. You can also send them an email at support@ftgames.com.</li>
-</ol></p> 401be4b1e0<br />
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diff --git a/spaces/feregVcuzo/sanity-test-midi/checkpoint/Download Summertime Saga APK Game 2 and Enjoy a Spicy Visual Novel.md b/spaces/feregVcuzo/sanity-test-midi/checkpoint/Download Summertime Saga APK Game 2 and Enjoy a Spicy Visual Novel.md
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--- a/spaces/feregVcuzo/sanity-test-midi/checkpoint/Download Summertime Saga APK Game 2 and Enjoy a Spicy Visual Novel.md	
+++ /dev/null
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-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/fffiloni/ControlVideo/GITHUB_README.md b/spaces/fffiloni/ControlVideo/GITHUB_README.md
deleted file mode 100644
index cf5a973701751671f6bbe58c79d478a04925d66f..0000000000000000000000000000000000000000
--- a/spaces/fffiloni/ControlVideo/GITHUB_README.md
+++ /dev/null
@@ -1,159 +0,0 @@
-# ControlVideo
-
-Official pytorch implementation of "ControlVideo: Training-free Controllable Text-to-Video Generation"
-
-[![arXiv](https://img.shields.io/badge/arXiv-2305.13077-b31b1b.svg)](https://arxiv.org/abs/2305.13077)
-![visitors](https://visitor-badge.laobi.icu/badge?page_id=YBYBZhang/ControlVideo)
-[![Replicate](https://replicate.com/cjwbw/controlvideo/badge)](https://replicate.com/cjwbw/controlvideo) 
-
-<p align="center">
-<img src="assets/overview.png" width="1080px"/> 
-<br>
-<em>ControlVideo adapts ControlNet to the video counterpart without any finetuning, aiming to directly inherit its high-quality and consistent generation </em>
-</p>
-
-## News
-
-* [05/28/2023] Thanks [chenxwh](https://github.com/chenxwh), add a [Replicate demo](https://replicate.com/cjwbw/controlvideo)!
-* [05/25/2023] Code [ControlVideo](https://github.com/YBYBZhang/ControlVideo/) released!
-* [05/23/2023] Paper [ControlVideo](https://arxiv.org/abs/2305.13077) released!
-
-## Setup
-
-### 1. Download Weights
-All pre-trained weights are downloaded to `checkpoints/` directory, including the pre-trained weights of [Stable Diffusion v1.5](https://huggingface.co/runwayml/stable-diffusion-v1-5), ControlNet conditioned on [canny edges](https://huggingface.co/lllyasviel/sd-controlnet-canny), [depth maps](https://huggingface.co/lllyasviel/sd-controlnet-depth), [human poses](https://huggingface.co/lllyasviel/sd-controlnet-openpose). 
-The `flownet.pkl` is the weights of [RIFE](https://github.com/megvii-research/ECCV2022-RIFE).
-The final file tree likes:
-
-```none
-checkpoints
-├── stable-diffusion-v1-5
-├── sd-controlnet-canny
-├── sd-controlnet-depth
-├── sd-controlnet-openpose
-├── flownet.pkl
-```
-### 2. Requirements
-
-```shell
-conda create -n controlvideo python=3.10
-conda activate controlvideo
-pip install -r requirements.txt
-```
-`xformers` is recommended to save memory and running time.
-
-## Inference
-
-To perform text-to-video generation, just run this command in `inference.sh`:
-```bash
-python inference.py \
-    --prompt "A striking mallard floats effortlessly on the sparkling pond." \
-    --condition "depth" \
-    --video_path "data/mallard-water.mp4" \
-    --output_path "outputs/" \
-    --video_length 15 \
-    --smoother_steps 19 20 \
-    --width 512 \
-    --height 512 \
-    # --is_long_video
-```
-where `--video_length` is the length of synthesized video, `--condition` represents the type of structure sequence,
-`--smoother_steps` determines at which timesteps to perform smoothing, and `--is_long_video` denotes whether to enable efficient long-video synthesis.
-
-## Visualizations
-
-### ControlVideo on depth maps
-
-<table class="center">
-<tr>
-  <td width=30% align="center"><img src="assets/depth/A_charming_flamingo_gracefully_wanders_in_the_calm_and_serene_water,_its_delicate_neck_curving_into_an_elegant_shape..gif" raw=true></td>
-	<td width=30% align="center"><img src="assets/depth/A_striking_mallard_floats_effortlessly_on_the_sparkling_pond..gif" raw=true></td>
-  <td width=30% align="center"><img src="assets/depth/A_gigantic_yellow_jeep_slowly_turns_on_a_wide,_smooth_road_in_the_city..gif" raw=true></td>
-</tr>
-<tr>
-  <td width=30% align="center">"A charming flamingo gracefully wanders in the calm and serene water, its delicate neck curving into an elegant shape."</td>
-  <td width=30% align="center">"A striking mallard floats effortlessly on the sparkling pond."</td>
-  <td width=30% align="center">"A gigantic yellow jeep slowly turns on a wide, smooth road in the city."</td>
-</tr>
- <tr>
-	<td width=30% align="center"><img src="assets/depth/A_sleek_boat_glides_effortlessly_through_the_shimmering_river,_van_gogh_style..gif" raw=true></td>
-  <td width=30% align="center"><img src="assets/depth/A_majestic_sailing_boat_cruises_along_the_vast,_azure_sea..gif" raw=true></td>
-	<td width=30% align="center"><img src="assets/depth/A_contented_cow_ambles_across_the_dewy,_verdant_pasture..gif" raw=true></td>
-</tr>
-<tr>
-  <td width=30% align="center">"A sleek boat glides effortlessly through the shimmering river, van gogh style."</td>
-  <td width=30% align="center">"A majestic sailing boat cruises along the vast, azure sea."</td>
-  <td width=30% align="center">"A contented cow ambles across the dewy, verdant pasture."</td>
-</tr>
-</table>
-
-### ControlVideo on canny edges
-
-<table class="center">
-<tr>
-  <td width=30% align="center"><img src="assets/canny/A_young_man_riding_a_sleek,_black_motorbike_through_the_winding_mountain_roads..gif" raw=true></td>
-  <td width=30% align="center"><img src="assets/canny/A_white_swan_moving_on_the_lake,_cartoon_style..gif" raw=true></td>
-	<td width=30% align="center"><img src="assets/canny/A_dusty_old_jeep_was_making_its_way_down_the_winding_forest_road,_creaking_and_groaning_with_each_bump_and_turn..gif" raw=true></td>
-</tr>
-<tr>
-  <td width=30% align="center">"A young man riding a sleek, black motorbike through the winding mountain roads."</td>
-  <td width=30% align="center">"A white swan movingon the lake, cartoon style."</td>
-  <td width=30% align="center">"A dusty old jeep was making its way down the winding forest road, creaking and groaning with each bump and turn."</td>
-</tr>
- <tr>
-  <td width=30% align="center"><img src="assets/canny/A_shiny_red_jeep_smoothly_turns_on_a_narrow,_winding_road_in_the_mountains..gif" raw=true></td>
-  <td width=30% align="center"><img src="assets/canny/A_majestic_camel_gracefully_strides_across_the_scorching_desert_sands..gif" raw=true></td>
-	<td width=30% align="center"><img src="assets/canny/A_fit_man_is_leisurely_hiking_through_a_lush_and_verdant_forest..gif" raw=true></td>
-</tr>
-<tr>
-  <td width=30% align="center">"A shiny red jeep smoothly turns on a narrow, winding road in the mountains."</td>
-  <td width=30% align="center">"A majestic camel gracefully strides across the scorching desert sands."</td>
-  <td width=30% align="center">"A fit man is leisurely hiking through a lush and verdant forest."</td>
-</tr>
-</table>
-
-
-### ControlVideo on human poses
-
-<table class="center">
-<tr>
-  <td width=25% align="center"><img src="assets/pose/James_bond_moonwalk_on_the_beach,_animation_style.gif" raw=true></td>
-  <td width=25% align="center"><img src="assets/pose/Goku_in_a_mountain_range,_surreal_style..gif" raw=true></td>
-	<td width=25% align="center"><img src="assets/pose/Hulk_is_jumping_on_the_street,_cartoon_style.gif" raw=true></td>
-  <td width=25% align="center"><img src="assets/pose/A_robot_dances_on_a_road,_animation_style.gif" raw=true></td>
-</tr>
-<tr>
-  <td width=25% align="center">"James bond moonwalk on the beach, animation style."</td>
-  <td width=25% align="center">"Goku in a mountain range, surreal style."</td>
-  <td width=25% align="center">"Hulk is jumping on the street, cartoon style."</td>
-  <td width=25% align="center">"A robot dances on a road, animation style."</td>
-</tr></table>
-
-### Long video generation
-
-<table class="center">
-<tr>
-  <td width=60% align="center"><img src="assets/long/A_steamship_on_the_ocean,_at_sunset,_sketch_style.gif" raw=true></td>
-	<td width=40% align="center"><img src="assets/long/Hulk_is_dancing_on_the_beach,_cartoon_style.gif" raw=true></td>
-</tr>
-<tr>
-  <td width=60% align="center">"A steamship on the ocean, at sunset, sketch style."</td>
-  <td width=40% align="center">"Hulk is dancing on the beach, cartoon style."</td>
-</tr>
-</table>
-
-## Citation
-If you make use of our work, please cite our paper.
-```bibtex
-@article{zhang2023controlvideo,
-  title={ControlVideo: Training-free Controllable Text-to-Video Generation},
-  author={Zhang, Yabo and Wei, Yuxiang and Jiang, Dongsheng and Zhang, Xiaopeng and Zuo, Wangmeng and Tian, Qi},
-  journal={arXiv preprint arXiv:2305.13077},
-  year={2023}
-}
-```
-
-## Acknowledgement
-This work repository borrows heavily from [Diffusers](https://github.com/huggingface/diffusers), [ControlNet](https://github.com/lllyasviel/ControlNet), [Tune-A-Video](https://github.com/showlab/Tune-A-Video), and [RIFE](https://github.com/megvii-research/ECCV2022-RIFE).
-
-There are also many interesting works on video generation: [Tune-A-Video](https://github.com/showlab/Tune-A-Video), [Text2Video-Zero](https://github.com/Picsart-AI-Research/Text2Video-Zero), [Follow-Your-Pose](https://github.com/mayuelala/FollowYourPose), [Control-A-Video](https://github.com/Weifeng-Chen/control-a-video), et al.
diff --git a/spaces/fffiloni/controlnet-animation-doodle/node_modules/engine.io/build/transports/polling.d.ts b/spaces/fffiloni/controlnet-animation-doodle/node_modules/engine.io/build/transports/polling.d.ts
deleted file mode 100644
index 2a603c85ffb914c27ee055d48fb3d797e82028c1..0000000000000000000000000000000000000000
--- a/spaces/fffiloni/controlnet-animation-doodle/node_modules/engine.io/build/transports/polling.d.ts
+++ /dev/null
@@ -1,100 +0,0 @@
-/// <reference types="node" />
-import { Transport } from "../transport";
-import { IncomingMessage, ServerResponse } from "http";
-export declare class Polling extends Transport {
-    maxHttpBufferSize: number;
-    httpCompression: any;
-    private res;
-    private dataReq;
-    private dataRes;
-    private shouldClose;
-    private readonly closeTimeout;
-    /**
-     * HTTP polling constructor.
-     *
-     * @api public.
-     */
-    constructor(req: any);
-    /**
-     * Transport name
-     *
-     * @api public
-     */
-    get name(): string;
-    get supportsFraming(): boolean;
-    /**
-     * Overrides onRequest.
-     *
-     * @param {http.IncomingMessage}
-     * @api private
-     */
-    onRequest(req: IncomingMessage & {
-        res: ServerResponse;
-    }): void;
-    /**
-     * The client sends a request awaiting for us to send data.
-     *
-     * @api private
-     */
-    onPollRequest(req: any, res: any): void;
-    /**
-     * The client sends a request with data.
-     *
-     * @api private
-     */
-    onDataRequest(req: IncomingMessage, res: ServerResponse): void;
-    /**
-     * Processes the incoming data payload.
-     *
-     * @param {String} encoded payload
-     * @api private
-     */
-    onData(data: any): void;
-    /**
-     * Overrides onClose.
-     *
-     * @api private
-     */
-    onClose(): void;
-    /**
-     * Writes a packet payload.
-     *
-     * @param {Object} packet
-     * @api private
-     */
-    send(packets: any): void;
-    /**
-     * Writes data as response to poll request.
-     *
-     * @param {String} data
-     * @param {Object} options
-     * @api private
-     */
-    write(data: any, options: any): void;
-    /**
-     * Performs the write.
-     *
-     * @api private
-     */
-    doWrite(data: any, options: any, callback: any): void;
-    /**
-     * Compresses data.
-     *
-     * @api private
-     */
-    compress(data: any, encoding: any, callback: any): void;
-    /**
-     * Closes the transport.
-     *
-     * @api private
-     */
-    doClose(fn: any): void;
-    /**
-     * Returns headers for a response.
-     *
-     * @param {http.IncomingMessage} request
-     * @param {Object} extra headers
-     * @api private
-     */
-    headers(req: any, headers: any): any;
-}
diff --git a/spaces/flatindo/generate5/README.md b/spaces/flatindo/generate5/README.md
deleted file mode 100644
index 9d3027609bdf4cfc8b23f8d6e4b4f4e31f9ea290..0000000000000000000000000000000000000000
--- a/spaces/flatindo/generate5/README.md
+++ /dev/null
@@ -1,20 +0,0 @@
----
-title: Realistic Vision v5.0
-emoji: 📷
-colorFrom: yellow
-colorTo: red
-sdk: gradio
-sdk_version: 3.18.0
-app_file: app.py
-pinned: true
-duplicated_from: shayakh/sdrv50
-tags:
-- stable-diffusion
-- stable-diffusion-diffusers
-- text-to-image
-- realistic-vision
-models:
-- SG161222/Realistic_Vision_V5.0_noVAE
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
\ No newline at end of file
diff --git a/spaces/flax-community/spanish-image-captioning/sections/references.md b/spaces/flax-community/spanish-image-captioning/sections/references.md
deleted file mode 100644
index bfb9adf5cf173db4f4cfd6849fd187eedd552e38..0000000000000000000000000000000000000000
--- a/spaces/flax-community/spanish-image-captioning/sections/references.md
+++ /dev/null
@@ -1,12 +0,0 @@
-## References
-- [Conceptual 12M Dataset](https://github.com/google-research-datasets/conceptual-12m)
-
-- [Hybrid CLIP Example](https://github.com/huggingface/transformers/blob/master/src/transformers/models/clip/modeling_flax_clip.py)
-
-- [Marian Modeling File](https://github.com/huggingface/transformers/blob/master/src/transformers/models/marian/modeling_flax_marian.py)
-
-- [CLIP Modeling File](https://github.com/huggingface/transformers/blob/master/src/transformers/models/clip/modeling_flax_clip.py)
-
-- [Hybrid CLIP Training Script](https://github.com/huggingface/transformers/blob/master/examples/research_projects/jax-projects/hybrid_clip/run_hybrid_clip.py)
-
-- [Summarization Training Script](https://github.com/huggingface/transformers/blob/master/examples/flax/summarization/run_summarization_flax.py)
\ No newline at end of file
diff --git a/spaces/gagan3012/summarization/src/models/__init__.py b/spaces/gagan3012/summarization/src/models/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/gotiQspiryo/whisper-ui/examples/Hum Baja Bajaa Denge Full Movie In Hindi Watch Jackie Shroffs Thriller Online.md b/spaces/gotiQspiryo/whisper-ui/examples/Hum Baja Bajaa Denge Full Movie In Hindi Watch Jackie Shroffs Thriller Online.md
deleted file mode 100644
index 7cd725a290b64e9bad95ae1f11927071573b62c3..0000000000000000000000000000000000000000
--- a/spaces/gotiQspiryo/whisper-ui/examples/Hum Baja Bajaa Denge Full Movie In Hindi Watch Jackie Shroffs Thriller Online.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>Hum Baja Bajaa Denge Full Movie In Hindi Download Kickass Utorrent</h2><br /><p><b><b>DOWNLOAD</b> &rArr;&rArr;&rArr; <a href="https://urlgoal.com/2uyMO3">https://urlgoal.com/2uyMO3</a></b></p><br /><br />
-
- aaccfb2cb3<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/gradio/HuBERT/examples/noisychannel/rerank_utils.py b/spaces/gradio/HuBERT/examples/noisychannel/rerank_utils.py
deleted file mode 100644
index 2c6bf1b1afbb089cf5e84f720eb7a067479fbcbc..0000000000000000000000000000000000000000
--- a/spaces/gradio/HuBERT/examples/noisychannel/rerank_utils.py
+++ /dev/null
@@ -1,850 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import math
-import os
-import re
-import subprocess
-from contextlib import redirect_stdout
-
-from fairseq import options
-from fairseq_cli import eval_lm, preprocess
-
-
-def reprocess(fle):
-    # takes in a file of generate.py translation generate_output
-    # returns a source dict and hypothesis dict, where keys are the ID num (as a string)
-    # and values and the corresponding source and translation. There may be several translations
-    # per source, so the values for hypothesis_dict are lists.
-    # parses output of generate.py
-
-    with open(fle, "r") as f:
-        txt = f.read()
-
-    """reprocess generate.py output"""
-    p = re.compile(r"[STHP][-]\d+\s*")
-    hp = re.compile(r"(\s*[-]?\d+[.]?\d+\s*)|(\s*(-inf)\s*)")
-    source_dict = {}
-    hypothesis_dict = {}
-    score_dict = {}
-    target_dict = {}
-    pos_score_dict = {}
-    lines = txt.split("\n")
-
-    for line in lines:
-        line += "\n"
-        prefix = re.search(p, line)
-        if prefix is not None:
-            assert len(prefix.group()) > 2, "prefix id not found"
-            _, j = prefix.span()
-            id_num = prefix.group()[2:]
-            id_num = int(id_num)
-            line_type = prefix.group()[0]
-            if line_type == "H":
-                h_txt = line[j:]
-                hypo = re.search(hp, h_txt)
-                assert (
-                    hypo is not None
-                ), "regular expression failed to find the hypothesis scoring"
-                _, i = hypo.span()
-                score = hypo.group()
-                if id_num in hypothesis_dict:
-                    hypothesis_dict[id_num].append(h_txt[i:])
-                    score_dict[id_num].append(float(score))
-                else:
-                    hypothesis_dict[id_num] = [h_txt[i:]]
-                    score_dict[id_num] = [float(score)]
-
-            elif line_type == "S":
-                source_dict[id_num] = line[j:]
-            elif line_type == "T":
-                target_dict[id_num] = line[j:]
-            elif line_type == "P":
-                pos_scores = (line[j:]).split()
-                pos_scores = [float(x) for x in pos_scores]
-                if id_num in pos_score_dict:
-                    pos_score_dict[id_num].append(pos_scores)
-                else:
-                    pos_score_dict[id_num] = [pos_scores]
-
-    return source_dict, hypothesis_dict, score_dict, target_dict, pos_score_dict
-
-
-def reprocess_nbest(fle):
-    """reprocess interactive.py output"""
-    with open(fle, "r") as f:
-        txt = f.read()
-
-    source_dict = {}
-    hypothesis_dict = {}
-    score_dict = {}
-    target_dict = {}
-    pos_score_dict = {}
-    lines = txt.split("\n")
-
-    hp = re.compile(r"[-]?\d+[.]?\d+")
-    j = -1
-
-    for _i, line in enumerate(lines):
-        line += "\n"
-        line_type = line[0]
-
-        if line_type == "H":
-            hypo = re.search(hp, line)
-            _, start_index = hypo.span()
-            score = hypo.group()
-            if j in score_dict:
-                score_dict[j].append(float(score))
-                hypothesis_dict[j].append(line[start_index:].strip("\t"))
-            else:
-                score_dict[j] = [float(score)]
-                hypothesis_dict[j] = [line[start_index:].strip("\t")]
-        elif line_type == "O":
-            j += 1
-            source_dict[j] = line[2:]
-            # we don't have the targets for interactive.py
-            target_dict[j] = "filler"
-
-        elif line_type == "P":
-            pos_scores = [float(pos_score) for pos_score in line.split()[1:]]
-            if j in pos_score_dict:
-                pos_score_dict[j].append(pos_scores)
-            else:
-                pos_score_dict[j] = [pos_scores]
-
-    assert source_dict.keys() == hypothesis_dict.keys()
-    assert source_dict.keys() == pos_score_dict.keys()
-    assert source_dict.keys() == score_dict.keys()
-
-    return source_dict, hypothesis_dict, score_dict, target_dict, pos_score_dict
-
-
-def write_reprocessed(
-    sources,
-    hypos,
-    targets,
-    source_outfile,
-    hypo_outfile,
-    target_outfile,
-    right_to_left=False,
-    prefix_len=None,
-    bpe_symbol=None,
-    target_prefix_frac=None,
-    source_prefix_frac=None,
-):
-
-    """writes nbest hypothesis for rescoring"""
-    assert not (
-        prefix_len is not None and target_prefix_frac is not None
-    ), "in writing reprocessed, only one type of prefix may be used"
-    assert not (
-        prefix_len is not None and source_prefix_frac is not None
-    ), "in writing reprocessed, only one type of prefix may be used"
-    assert not (
-        target_prefix_frac is not None and source_prefix_frac is not None
-    ), "in writing reprocessed, only one type of prefix may be used"
-
-    with open(source_outfile, "w") as source_file, open(
-        hypo_outfile, "w"
-    ) as hypo_file, open(target_outfile, "w") as target_file:
-
-        assert len(sources) == len(hypos), "sources and hypos list length mismatch"
-        if right_to_left:
-            for i in range(len(sources)):
-                for j in range(len(hypos[i])):
-                    if prefix_len is None:
-                        hypo_file.write(make_right_to_left(hypos[i][j]) + "\n")
-                    else:
-                        raise NotImplementedError()
-                    source_file.write(make_right_to_left(sources[i]) + "\n")
-                    target_file.write(make_right_to_left(targets[i]) + "\n")
-        else:
-            for i in sorted(sources.keys()):
-                for j in range(len(hypos[i])):
-                    if prefix_len is not None:
-                        shortened = (
-                            get_prefix_no_bpe(hypos[i][j], bpe_symbol, prefix_len)
-                            + "\n"
-                        )
-                        hypo_file.write(shortened)
-                        source_file.write(sources[i])
-                        target_file.write(targets[i])
-                    elif target_prefix_frac is not None:
-                        num_words, shortened, num_bpe_tokens = calc_length_from_frac(
-                            hypos[i][j], target_prefix_frac, bpe_symbol
-                        )
-                        shortened += "\n"
-                        hypo_file.write(shortened)
-                        source_file.write(sources[i])
-                        target_file.write(targets[i])
-                    elif source_prefix_frac is not None:
-                        num_words, shortened, num_bpe_tokensn = calc_length_from_frac(
-                            sources[i], source_prefix_frac, bpe_symbol
-                        )
-                        shortened += "\n"
-                        hypo_file.write(hypos[i][j])
-                        source_file.write(shortened)
-                        target_file.write(targets[i])
-                    else:
-                        hypo_file.write(hypos[i][j])
-                        source_file.write(sources[i])
-                        target_file.write(targets[i])
-
-
-def calc_length_from_frac(bpe_sentence, prefix_frac, bpe_symbol):
-    # return number of words, (not bpe tokens) that we want
-    no_bpe_sen = remove_bpe(bpe_sentence, bpe_symbol)
-    len_sen = len(no_bpe_sen.split())
-
-    num_words = math.ceil(len_sen * prefix_frac)
-    prefix = get_prefix_no_bpe(bpe_sentence, bpe_symbol, num_words)
-    num_bpe_tokens = len(prefix.split())
-    return num_words, prefix, num_bpe_tokens
-
-
-def get_prefix(sentence, prefix_len):
-    """assuming no bpe, gets the prefix of the sentence with prefix_len words"""
-    tokens = sentence.strip("\n").split()
-    if prefix_len >= len(tokens):
-        return sentence.strip("\n")
-    else:
-        return " ".join(tokens[:prefix_len])
-
-
-def get_prefix_no_bpe(sentence, bpe_symbol, prefix_len):
-    if bpe_symbol is None:
-        return get_prefix(sentence, prefix_len)
-    else:
-        return " ".join(get_prefix_from_len(sentence.split(), bpe_symbol, prefix_len))
-
-
-def get_prefix_from_len(sentence, bpe_symbol, prefix_len):
-    """get the prefix of sentence with bpe, with prefix len in terms of words, not bpe tokens"""
-    bpe_count = sum([bpe_symbol.strip(" ") in t for t in sentence[:prefix_len]])
-    if bpe_count == 0:
-        return sentence[:prefix_len]
-    else:
-        return sentence[:prefix_len] + get_prefix_from_len(
-            sentence[prefix_len:], bpe_symbol, bpe_count
-        )
-
-
-def get_num_bpe_tokens_from_len(sentence, bpe_symbol, prefix_len):
-    """given a prefix length in terms of words, return the number of bpe tokens"""
-    prefix = get_prefix_no_bpe(sentence, bpe_symbol, prefix_len)
-    assert len(remove_bpe(prefix, bpe_symbol).split()) <= prefix_len
-    return len(prefix.split(" "))
-
-
-def make_right_to_left(line):
-    tokens = line.split()
-    tokens.reverse()
-    new_line = " ".join(tokens)
-    return new_line
-
-
-def remove_bpe(line, bpe_symbol):
-    line = line.replace("\n", "")
-    line = (line + " ").replace(bpe_symbol, "").rstrip()
-    return line + ("\n")
-
-
-def remove_bpe_dict(pred_dict, bpe_symbol):
-    new_dict = {}
-    for i in pred_dict:
-        if type(pred_dict[i]) == list:
-            new_list = [remove_bpe(elem, bpe_symbol) for elem in pred_dict[i]]
-            new_dict[i] = new_list
-        else:
-            new_dict[i] = remove_bpe(pred_dict[i], bpe_symbol)
-    return new_dict
-
-
-def parse_bleu_scoring(line):
-    p = re.compile(r"(BLEU4 = )\d+[.]\d+")
-    res = re.search(p, line)
-    assert res is not None, line
-    return float(res.group()[8:])
-
-
-def get_full_from_prefix(hypo_prefix, hypos):
-    """given a hypo prefix, recover the first hypo from the list of complete hypos beginning with that prefix"""
-    for hypo in hypos:
-        hypo_prefix = hypo_prefix.strip("\n")
-        len_prefix = len(hypo_prefix)
-        if hypo[:len_prefix] == hypo_prefix:
-            return hypo
-    # no match found
-    raise Exception()
-
-
-def get_score(
-    a,
-    b,
-    c,
-    target_len,
-    bitext_score1,
-    bitext_score2=None,
-    lm_score=None,
-    lenpen=None,
-    src_len=None,
-    tgt_len=None,
-    bitext1_backwards=False,
-    bitext2_backwards=False,
-    normalize=False,
-):
-    if bitext1_backwards:
-        bitext1_norm = src_len
-    else:
-        bitext1_norm = tgt_len
-    if bitext_score2 is not None:
-        if bitext2_backwards:
-            bitext2_norm = src_len
-        else:
-            bitext2_norm = tgt_len
-    else:
-        bitext2_norm = 1
-        bitext_score2 = 0
-    if normalize:
-        score = (
-            a * bitext_score1 / bitext1_norm
-            + b * bitext_score2 / bitext2_norm
-            + c * lm_score / src_len
-        )
-    else:
-        score = a * bitext_score1 + b * bitext_score2 + c * lm_score
-
-    if lenpen is not None:
-        score /= (target_len) ** float(lenpen)
-
-    return score
-
-
-class BitextOutput(object):
-    def __init__(
-        self,
-        output_file,
-        backwards,
-        right_to_left,
-        bpe_symbol,
-        prefix_len=None,
-        target_prefix_frac=None,
-        source_prefix_frac=None,
-    ):
-        """process output from rescoring"""
-        source, hypo, score, target, pos_score = reprocess(output_file)
-        if backwards:
-            self.hypo_fracs = source_prefix_frac
-        else:
-            self.hypo_fracs = target_prefix_frac
-
-        # remove length penalty so we can use raw scores
-        score, num_bpe_tokens = get_score_from_pos(
-            pos_score, prefix_len, hypo, bpe_symbol, self.hypo_fracs, backwards
-        )
-        source_lengths = {}
-        target_lengths = {}
-
-        assert hypo.keys() == source.keys(), "key mismatch"
-        if backwards:
-            tmp = hypo
-            hypo = source
-            source = tmp
-        for i in source:
-            # since we are reranking, there should only be one hypo per source sentence
-            if backwards:
-                len_src = len(source[i][0].split())
-                # record length without <eos>
-                if len_src == num_bpe_tokens[i][0] - 1:
-                    source_lengths[i] = num_bpe_tokens[i][0] - 1
-                else:
-                    source_lengths[i] = num_bpe_tokens[i][0]
-
-                target_lengths[i] = len(hypo[i].split())
-
-                source[i] = remove_bpe(source[i][0], bpe_symbol)
-                target[i] = remove_bpe(target[i], bpe_symbol)
-                hypo[i] = remove_bpe(hypo[i], bpe_symbol)
-
-                score[i] = float(score[i][0])
-                pos_score[i] = pos_score[i][0]
-
-            else:
-                len_tgt = len(hypo[i][0].split())
-                # record length without <eos>
-                if len_tgt == num_bpe_tokens[i][0] - 1:
-                    target_lengths[i] = num_bpe_tokens[i][0] - 1
-                else:
-                    target_lengths[i] = num_bpe_tokens[i][0]
-
-                source_lengths[i] = len(source[i].split())
-
-                if right_to_left:
-                    source[i] = remove_bpe(make_right_to_left(source[i]), bpe_symbol)
-                    target[i] = remove_bpe(make_right_to_left(target[i]), bpe_symbol)
-                    hypo[i] = remove_bpe(make_right_to_left(hypo[i][0]), bpe_symbol)
-                    score[i] = float(score[i][0])
-                    pos_score[i] = pos_score[i][0]
-                else:
-                    assert (
-                        len(hypo[i]) == 1
-                    ), "expected only one hypothesis per source sentence"
-                    source[i] = remove_bpe(source[i], bpe_symbol)
-                    target[i] = remove_bpe(target[i], bpe_symbol)
-                    hypo[i] = remove_bpe(hypo[i][0], bpe_symbol)
-                    score[i] = float(score[i][0])
-                    pos_score[i] = pos_score[i][0]
-
-        self.rescore_source = source
-        self.rescore_hypo = hypo
-        self.rescore_score = score
-        self.rescore_target = target
-        self.rescore_pos_score = pos_score
-        self.backwards = backwards
-        self.right_to_left = right_to_left
-        self.target_lengths = target_lengths
-        self.source_lengths = source_lengths
-
-
-class BitextOutputFromGen(object):
-    def __init__(
-        self,
-        predictions_bpe_file,
-        bpe_symbol=None,
-        nbest=False,
-        prefix_len=None,
-        target_prefix_frac=None,
-    ):
-        if nbest:
-            (
-                pred_source,
-                pred_hypo,
-                pred_score,
-                pred_target,
-                pred_pos_score,
-            ) = reprocess_nbest(predictions_bpe_file)
-        else:
-            pred_source, pred_hypo, pred_score, pred_target, pred_pos_score = reprocess(
-                predictions_bpe_file
-            )
-
-        assert len(pred_source) == len(pred_hypo)
-        assert len(pred_source) == len(pred_score)
-        assert len(pred_source) == len(pred_target)
-        assert len(pred_source) == len(pred_pos_score)
-
-        # remove length penalty so we can use raw scores
-        pred_score, num_bpe_tokens = get_score_from_pos(
-            pred_pos_score, prefix_len, pred_hypo, bpe_symbol, target_prefix_frac, False
-        )
-
-        self.source = pred_source
-        self.target = pred_target
-        self.score = pred_score
-        self.pos_score = pred_pos_score
-        self.hypo = pred_hypo
-        self.target_lengths = {}
-        self.source_lengths = {}
-
-        self.no_bpe_source = remove_bpe_dict(pred_source.copy(), bpe_symbol)
-        self.no_bpe_hypo = remove_bpe_dict(pred_hypo.copy(), bpe_symbol)
-        self.no_bpe_target = remove_bpe_dict(pred_target.copy(), bpe_symbol)
-
-        # indexes to match those from the rescoring models
-        self.rescore_source = {}
-        self.rescore_target = {}
-        self.rescore_pos_score = {}
-        self.rescore_hypo = {}
-        self.rescore_score = {}
-        self.num_hypos = {}
-        self.backwards = False
-        self.right_to_left = False
-
-        index = 0
-
-        for i in sorted(pred_source.keys()):
-            for j in range(len(pred_hypo[i])):
-
-                self.target_lengths[index] = len(self.hypo[i][j].split())
-                self.source_lengths[index] = len(self.source[i].split())
-
-                self.rescore_source[index] = self.no_bpe_source[i]
-                self.rescore_target[index] = self.no_bpe_target[i]
-                self.rescore_hypo[index] = self.no_bpe_hypo[i][j]
-                self.rescore_score[index] = float(pred_score[i][j])
-                self.rescore_pos_score[index] = pred_pos_score[i][j]
-                self.num_hypos[index] = len(pred_hypo[i])
-                index += 1
-
-
-def get_score_from_pos(
-    pos_score_dict, prefix_len, hypo_dict, bpe_symbol, hypo_frac, backwards
-):
-    score_dict = {}
-    num_bpe_tokens_dict = {}
-    assert prefix_len is None or hypo_frac is None
-    for key in pos_score_dict:
-        score_dict[key] = []
-        num_bpe_tokens_dict[key] = []
-        for i in range(len(pos_score_dict[key])):
-            if prefix_len is not None and not backwards:
-                num_bpe_tokens = get_num_bpe_tokens_from_len(
-                    hypo_dict[key][i], bpe_symbol, prefix_len
-                )
-                score_dict[key].append(sum(pos_score_dict[key][i][:num_bpe_tokens]))
-                num_bpe_tokens_dict[key].append(num_bpe_tokens)
-            elif hypo_frac is not None:
-                num_words, shortened, hypo_prefix_len = calc_length_from_frac(
-                    hypo_dict[key][i], hypo_frac, bpe_symbol
-                )
-                score_dict[key].append(sum(pos_score_dict[key][i][:hypo_prefix_len]))
-                num_bpe_tokens_dict[key].append(hypo_prefix_len)
-            else:
-                score_dict[key].append(sum(pos_score_dict[key][i]))
-                num_bpe_tokens_dict[key].append(len(pos_score_dict[key][i]))
-    return score_dict, num_bpe_tokens_dict
-
-
-class LMOutput(object):
-    def __init__(
-        self,
-        lm_score_file,
-        lm_dict=None,
-        prefix_len=None,
-        bpe_symbol=None,
-        target_prefix_frac=None,
-    ):
-        (
-            lm_sentences,
-            lm_sen_scores,
-            lm_sen_pos_scores,
-            lm_no_bpe_sentences,
-            lm_bpe_tokens,
-        ) = parse_lm(
-            lm_score_file,
-            prefix_len=prefix_len,
-            bpe_symbol=bpe_symbol,
-            target_prefix_frac=target_prefix_frac,
-        )
-
-        self.sentences = lm_sentences
-        self.score = lm_sen_scores
-        self.pos_score = lm_sen_pos_scores
-        self.lm_dict = lm_dict
-        self.no_bpe_sentences = lm_no_bpe_sentences
-        self.bpe_tokens = lm_bpe_tokens
-
-
-def parse_lm(input_file, prefix_len=None, bpe_symbol=None, target_prefix_frac=None):
-    """parse output of eval_lm"""
-    with open(input_file, "r") as f:
-        text = f.readlines()
-        text = text[7:]
-        cleaned_text = text[:-2]
-
-        sentences = {}
-        sen_scores = {}
-        sen_pos_scores = {}
-        no_bpe_sentences = {}
-        num_bpe_tokens_dict = {}
-        for _i, line in enumerate(cleaned_text):
-            tokens = line.split()
-            if tokens[0].isdigit():
-                line_id = int(tokens[0])
-                scores = [float(x[1:-1]) for x in tokens[2::2]]
-                sentences[line_id] = " ".join(tokens[1::2][:-1]) + "\n"
-                if bpe_symbol is not None:
-                    # exclude <eos> symbol to match output from generate.py
-                    bpe_sen = " ".join(tokens[1::2][:-1]) + "\n"
-                    no_bpe_sen = remove_bpe(bpe_sen, bpe_symbol)
-                    no_bpe_sentences[line_id] = no_bpe_sen
-
-                if prefix_len is not None:
-                    num_bpe_tokens = get_num_bpe_tokens_from_len(
-                        bpe_sen, bpe_symbol, prefix_len
-                    )
-                    sen_scores[line_id] = sum(scores[:num_bpe_tokens])
-                    num_bpe_tokens_dict[line_id] = num_bpe_tokens
-                elif target_prefix_frac is not None:
-                    num_words, shortened, target_prefix_len = calc_length_from_frac(
-                        bpe_sen, target_prefix_frac, bpe_symbol
-                    )
-                    sen_scores[line_id] = sum(scores[:target_prefix_len])
-                    num_bpe_tokens_dict[line_id] = target_prefix_len
-                else:
-                    sen_scores[line_id] = sum(scores)
-                    num_bpe_tokens_dict[line_id] = len(scores)
-
-                sen_pos_scores[line_id] = scores
-
-    return sentences, sen_scores, sen_pos_scores, no_bpe_sentences, num_bpe_tokens_dict
-
-
-def get_directories(
-    data_dir_name,
-    num_rescore,
-    gen_subset,
-    fw_name,
-    shard_id,
-    num_shards,
-    sampling=False,
-    prefix_len=None,
-    target_prefix_frac=None,
-    source_prefix_frac=None,
-):
-    nbest_file_id = (
-        "nbest_"
-        + str(num_rescore)
-        + "_subset_"
-        + gen_subset
-        + "_fw_name_"
-        + fw_name
-        + "_shard_"
-        + str(shard_id)
-        + "_of_"
-        + str(num_shards)
-    )
-
-    if sampling:
-        nbest_file_id += "_sampling"
-
-    # the directory containing all information for this nbest list
-    pre_gen = (
-        os.path.join(os.path.dirname(__file__))
-        + "/rerank_data/"
-        + data_dir_name
-        + "/"
-        + nbest_file_id
-    )
-    # the directory to store the preprocessed nbest list, for left to right rescoring
-    left_to_right_preprocessed_dir = pre_gen + "/left_to_right_preprocessed"
-    if source_prefix_frac is not None:
-        left_to_right_preprocessed_dir = (
-            left_to_right_preprocessed_dir + "/prefix_frac" + str(source_prefix_frac)
-        )
-    # the directory to store the preprocessed nbest list, for right to left rescoring
-    right_to_left_preprocessed_dir = pre_gen + "/right_to_left_preprocessed"
-    # the directory to store the preprocessed nbest list, for backwards rescoring
-    backwards_preprocessed_dir = pre_gen + "/backwards"
-    if target_prefix_frac is not None:
-        backwards_preprocessed_dir = (
-            backwards_preprocessed_dir + "/prefix_frac" + str(target_prefix_frac)
-        )
-    elif prefix_len is not None:
-        backwards_preprocessed_dir = (
-            backwards_preprocessed_dir + "/prefix_" + str(prefix_len)
-        )
-
-    # the directory to store the preprocessed nbest list, for rescoring with P(T)
-    lm_preprocessed_dir = pre_gen + "/lm_preprocessed"
-
-    return (
-        pre_gen,
-        left_to_right_preprocessed_dir,
-        right_to_left_preprocessed_dir,
-        backwards_preprocessed_dir,
-        lm_preprocessed_dir,
-    )
-
-
-def lm_scoring(
-    preprocess_directory,
-    bpe_status,
-    gen_output,
-    pre_gen,
-    cur_lm_dict,
-    cur_lm_name,
-    cur_language_model,
-    cur_lm_bpe_code,
-    batch_size,
-    lm_score_file,
-    target_lang,
-    source_lang,
-    prefix_len=None,
-):
-    if prefix_len is not None:
-        assert (
-            bpe_status == "different"
-        ), "bpe status must be different to use prefix len"
-    if bpe_status == "no bpe":
-        # run lm on output without bpe
-        write_reprocessed(
-            gen_output.no_bpe_source,
-            gen_output.no_bpe_hypo,
-            gen_output.no_bpe_target,
-            pre_gen + "/rescore_data_no_bpe.de",
-            pre_gen + "/rescore_data_no_bpe.en",
-            pre_gen + "/reference_file_no_bpe",
-        )
-
-        preprocess_lm_param = [
-            "--only-source",
-            "--trainpref",
-            pre_gen + "/rescore_data_no_bpe." + target_lang,
-            "--srcdict",
-            cur_lm_dict,
-            "--destdir",
-            preprocess_directory,
-        ]
-        preprocess_parser = options.get_preprocessing_parser()
-        input_args = preprocess_parser.parse_args(preprocess_lm_param)
-        preprocess.main(input_args)
-
-        eval_lm_param = [
-            preprocess_directory,
-            "--path",
-            cur_language_model,
-            "--output-word-probs",
-            "--batch-size",
-            str(batch_size),
-            "--max-tokens",
-            "1024",
-            "--sample-break-mode",
-            "eos",
-            "--gen-subset",
-            "train",
-        ]
-
-        eval_lm_parser = options.get_eval_lm_parser()
-        input_args = options.parse_args_and_arch(eval_lm_parser, eval_lm_param)
-
-        with open(lm_score_file, "w") as f:
-            with redirect_stdout(f):
-                eval_lm.main(input_args)
-
-    elif bpe_status == "shared":
-        preprocess_lm_param = [
-            "--only-source",
-            "--trainpref",
-            pre_gen + "/rescore_data." + target_lang,
-            "--srcdict",
-            cur_lm_dict,
-            "--destdir",
-            preprocess_directory,
-        ]
-        preprocess_parser = options.get_preprocessing_parser()
-        input_args = preprocess_parser.parse_args(preprocess_lm_param)
-        preprocess.main(input_args)
-
-        eval_lm_param = [
-            preprocess_directory,
-            "--path",
-            cur_language_model,
-            "--output-word-probs",
-            "--batch-size",
-            str(batch_size),
-            "--sample-break-mode",
-            "eos",
-            "--gen-subset",
-            "train",
-        ]
-
-        eval_lm_parser = options.get_eval_lm_parser()
-        input_args = options.parse_args_and_arch(eval_lm_parser, eval_lm_param)
-
-        with open(lm_score_file, "w") as f:
-            with redirect_stdout(f):
-                eval_lm.main(input_args)
-
-    elif bpe_status == "different":
-        rescore_file = pre_gen + "/rescore_data_no_bpe"
-        rescore_bpe = pre_gen + "/rescore_data_new_bpe"
-
-        rescore_file += "."
-        rescore_bpe += "."
-
-        write_reprocessed(
-            gen_output.no_bpe_source,
-            gen_output.no_bpe_hypo,
-            gen_output.no_bpe_target,
-            rescore_file + source_lang,
-            rescore_file + target_lang,
-            pre_gen + "/reference_file_no_bpe",
-            bpe_symbol=None,
-        )
-
-        # apply LM bpe to nbest list
-        bpe_src_param = [
-            "-c",
-            cur_lm_bpe_code,
-            "--input",
-            rescore_file + target_lang,
-            "--output",
-            rescore_bpe + target_lang,
-        ]
-        subprocess.call(
-            [
-                "python",
-                os.path.join(
-                    os.path.dirname(__file__), "subword-nmt/subword_nmt/apply_bpe.py"
-                ),
-            ]
-            + bpe_src_param,
-            shell=False,
-        )
-        # uncomment to use fastbpe instead of subword-nmt bpe
-        # bpe_src_param = [rescore_bpe+target_lang, rescore_file+target_lang, cur_lm_bpe_code]
-        # subprocess.call(["/private/home/edunov/fastBPE/fast", "applybpe"] + bpe_src_param, shell=False)
-
-        preprocess_dir = preprocess_directory
-
-        preprocess_lm_param = [
-            "--only-source",
-            "--trainpref",
-            rescore_bpe + target_lang,
-            "--srcdict",
-            cur_lm_dict,
-            "--destdir",
-            preprocess_dir,
-        ]
-        preprocess_parser = options.get_preprocessing_parser()
-        input_args = preprocess_parser.parse_args(preprocess_lm_param)
-        preprocess.main(input_args)
-
-        eval_lm_param = [
-            preprocess_dir,
-            "--path",
-            cur_language_model,
-            "--output-word-probs",
-            "--batch-size",
-            str(batch_size),
-            "--max-tokens",
-            "1024",
-            "--sample-break-mode",
-            "eos",
-            "--gen-subset",
-            "train",
-        ]
-
-        eval_lm_parser = options.get_eval_lm_parser()
-        input_args = options.parse_args_and_arch(eval_lm_parser, eval_lm_param)
-
-        with open(lm_score_file, "w") as f:
-            with redirect_stdout(f):
-                eval_lm.main(input_args)
-
-
-def rescore_file_name(
-    nbest_dir,
-    prefix_len,
-    scorer_name,
-    lm_file=False,
-    target_prefix_frac=None,
-    source_prefix_frac=None,
-    backwards=None,
-):
-    if lm_file:
-        score_file = nbest_dir + "/lm_score_translations_model_" + scorer_name + ".txt"
-    else:
-        score_file = nbest_dir + "/" + scorer_name + "_score_translations.txt"
-    if backwards:
-        if prefix_len is not None:
-            score_file += "prefix_len" + str(prefix_len)
-        elif target_prefix_frac is not None:
-            score_file += "target_prefix_frac" + str(target_prefix_frac)
-    else:
-        if source_prefix_frac is not None:
-            score_file += "source_prefix_frac" + str(source_prefix_frac)
-    return score_file
diff --git a/spaces/gradio/HuBERT/tests/test_multi_corpus_dataset.py b/spaces/gradio/HuBERT/tests/test_multi_corpus_dataset.py
deleted file mode 100644
index 5a79f4b680e5bc2c7374ec6dd8ea525c47b40985..0000000000000000000000000000000000000000
--- a/spaces/gradio/HuBERT/tests/test_multi_corpus_dataset.py
+++ /dev/null
@@ -1,79 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import unittest
-from collections import OrderedDict
-
-import torch
-from fairseq.data import LanguagePairDataset, TokenBlockDataset
-from fairseq.data.multi_corpus_dataset import MultiCorpusDataset
-from tests.test_train import mock_dict
-
-
-class TestMultiCorpusDataset(unittest.TestCase):
-    def setUp(self):
-        d = mock_dict()
-        tokens_1 = torch.LongTensor([i for i in range(1, 5000, 2)]).view(1, -1)
-        tokens_ds1 = TokenBlockDataset(
-            tokens_1,
-            sizes=[tokens_1.size(-1)],
-            block_size=1,
-            pad=0,
-            eos=1,
-            include_targets=False,
-        )
-        self.dataset_1 = LanguagePairDataset(
-            tokens_ds1, tokens_ds1.sizes, d, shuffle=False
-        )
-        tokens_2 = torch.LongTensor([i for i in range(0, 5000, 2)]).view(1, -1)
-        tokens_ds2 = TokenBlockDataset(
-            tokens_2,
-            sizes=[tokens_2.size(-1)],
-            block_size=1,
-            pad=0,
-            eos=1,
-            include_targets=False,
-        )
-        self.dataset_2 = LanguagePairDataset(
-            tokens_ds2, tokens_ds2.sizes, d, shuffle=False
-        )
-
-    def _test_sample_helper(
-        self,
-        distribution,
-    ):
-        m = MultiCorpusDataset(
-            OrderedDict({0: self.dataset_1, 1: self.dataset_2}),
-            distribution=distribution,
-            seed=0,
-            sort_indices=True,
-        )
-        m.set_epoch(1)
-        indices = m.ordered_indices()
-        count_sample_from_first_dataset = 0
-        items = set()
-        for i in indices:
-            item = m[i]["source"].item()
-            if item % 2 == 1:
-                count_sample_from_first_dataset += 1
-
-            items.add(item)
-        sample_from_first_ds_percentage = (
-            1.0 * count_sample_from_first_dataset / len(indices)
-        )
-        self.assertLess(
-            abs(sample_from_first_ds_percentage - distribution[0]),
-            0.01,
-        )
-        self.assertEqual(
-            len(items),
-            int(min(len(self.dataset_1), len(indices) * distribution[0])
-                + min(len(self.dataset_1), len(indices) * distribution[1]))
-        )
-        print(distribution)
-
-    def test_multi_corpus_dataset(self):
-        for distribution in [[0.5, 0.5], [0.1, 0.9], [0.9, 0.1]]:
-            self._test_sample_helper(distribution=distribution)
diff --git a/spaces/grld26/Whisper-Swak-v4/README.md b/spaces/grld26/Whisper-Swak-v4/README.md
deleted file mode 100644
index 4f337978af3b516428ef655fa1049312161b823e..0000000000000000000000000000000000000000
--- a/spaces/grld26/Whisper-Swak-v4/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Whisper Swak V4
-emoji: 👁
-colorFrom: green
-colorTo: green
-sdk: gradio
-sdk_version: 3.29.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/gulabpatel/GFP_GAN/gfpgan/archs/stylegan2_clean_arch.py b/spaces/gulabpatel/GFP_GAN/gfpgan/archs/stylegan2_clean_arch.py
deleted file mode 100644
index 9e2ee94e50401b95e4c9997adef5581d521d725f..0000000000000000000000000000000000000000
--- a/spaces/gulabpatel/GFP_GAN/gfpgan/archs/stylegan2_clean_arch.py
+++ /dev/null
@@ -1,368 +0,0 @@
-import math
-import random
-import torch
-from basicsr.archs.arch_util import default_init_weights
-from basicsr.utils.registry import ARCH_REGISTRY
-from torch import nn
-from torch.nn import functional as F
-
-
-class NormStyleCode(nn.Module):
-
-    def forward(self, x):
-        """Normalize the style codes.
-
-        Args:
-            x (Tensor): Style codes with shape (b, c).
-
-        Returns:
-            Tensor: Normalized tensor.
-        """
-        return x * torch.rsqrt(torch.mean(x**2, dim=1, keepdim=True) + 1e-8)
-
-
-class ModulatedConv2d(nn.Module):
-    """Modulated Conv2d used in StyleGAN2.
-
-    There is no bias in ModulatedConv2d.
-
-    Args:
-        in_channels (int): Channel number of the input.
-        out_channels (int): Channel number of the output.
-        kernel_size (int): Size of the convolving kernel.
-        num_style_feat (int): Channel number of style features.
-        demodulate (bool): Whether to demodulate in the conv layer. Default: True.
-        sample_mode (str | None): Indicating 'upsample', 'downsample' or None. Default: None.
-        eps (float): A value added to the denominator for numerical stability. Default: 1e-8.
-    """
-
-    def __init__(self,
-                 in_channels,
-                 out_channels,
-                 kernel_size,
-                 num_style_feat,
-                 demodulate=True,
-                 sample_mode=None,
-                 eps=1e-8):
-        super(ModulatedConv2d, self).__init__()
-        self.in_channels = in_channels
-        self.out_channels = out_channels
-        self.kernel_size = kernel_size
-        self.demodulate = demodulate
-        self.sample_mode = sample_mode
-        self.eps = eps
-
-        # modulation inside each modulated conv
-        self.modulation = nn.Linear(num_style_feat, in_channels, bias=True)
-        # initialization
-        default_init_weights(self.modulation, scale=1, bias_fill=1, a=0, mode='fan_in', nonlinearity='linear')
-
-        self.weight = nn.Parameter(
-            torch.randn(1, out_channels, in_channels, kernel_size, kernel_size) /
-            math.sqrt(in_channels * kernel_size**2))
-        self.padding = kernel_size // 2
-
-    def forward(self, x, style):
-        """Forward function.
-
-        Args:
-            x (Tensor): Tensor with shape (b, c, h, w).
-            style (Tensor): Tensor with shape (b, num_style_feat).
-
-        Returns:
-            Tensor: Modulated tensor after convolution.
-        """
-        b, c, h, w = x.shape  # c = c_in
-        # weight modulation
-        style = self.modulation(style).view(b, 1, c, 1, 1)
-        # self.weight: (1, c_out, c_in, k, k); style: (b, 1, c, 1, 1)
-        weight = self.weight * style  # (b, c_out, c_in, k, k)
-
-        if self.demodulate:
-            demod = torch.rsqrt(weight.pow(2).sum([2, 3, 4]) + self.eps)
-            weight = weight * demod.view(b, self.out_channels, 1, 1, 1)
-
-        weight = weight.view(b * self.out_channels, c, self.kernel_size, self.kernel_size)
-
-        # upsample or downsample if necessary
-        if self.sample_mode == 'upsample':
-            x = F.interpolate(x, scale_factor=2, mode='bilinear', align_corners=False)
-        elif self.sample_mode == 'downsample':
-            x = F.interpolate(x, scale_factor=0.5, mode='bilinear', align_corners=False)
-
-        b, c, h, w = x.shape
-        x = x.view(1, b * c, h, w)
-        # weight: (b*c_out, c_in, k, k), groups=b
-        out = F.conv2d(x, weight, padding=self.padding, groups=b)
-        out = out.view(b, self.out_channels, *out.shape[2:4])
-
-        return out
-
-    def __repr__(self):
-        return (f'{self.__class__.__name__}(in_channels={self.in_channels}, out_channels={self.out_channels}, '
-                f'kernel_size={self.kernel_size}, demodulate={self.demodulate}, sample_mode={self.sample_mode})')
-
-
-class StyleConv(nn.Module):
-    """Style conv used in StyleGAN2.
-
-    Args:
-        in_channels (int): Channel number of the input.
-        out_channels (int): Channel number of the output.
-        kernel_size (int): Size of the convolving kernel.
-        num_style_feat (int): Channel number of style features.
-        demodulate (bool): Whether demodulate in the conv layer. Default: True.
-        sample_mode (str | None): Indicating 'upsample', 'downsample' or None. Default: None.
-    """
-
-    def __init__(self, in_channels, out_channels, kernel_size, num_style_feat, demodulate=True, sample_mode=None):
-        super(StyleConv, self).__init__()
-        self.modulated_conv = ModulatedConv2d(
-            in_channels, out_channels, kernel_size, num_style_feat, demodulate=demodulate, sample_mode=sample_mode)
-        self.weight = nn.Parameter(torch.zeros(1))  # for noise injection
-        self.bias = nn.Parameter(torch.zeros(1, out_channels, 1, 1))
-        self.activate = nn.LeakyReLU(negative_slope=0.2, inplace=True)
-
-    def forward(self, x, style, noise=None):
-        # modulate
-        out = self.modulated_conv(x, style) * 2**0.5  # for conversion
-        # noise injection
-        if noise is None:
-            b, _, h, w = out.shape
-            noise = out.new_empty(b, 1, h, w).normal_()
-        out = out + self.weight * noise
-        # add bias
-        out = out + self.bias
-        # activation
-        out = self.activate(out)
-        return out
-
-
-class ToRGB(nn.Module):
-    """To RGB (image space) from features.
-
-    Args:
-        in_channels (int): Channel number of input.
-        num_style_feat (int): Channel number of style features.
-        upsample (bool): Whether to upsample. Default: True.
-    """
-
-    def __init__(self, in_channels, num_style_feat, upsample=True):
-        super(ToRGB, self).__init__()
-        self.upsample = upsample
-        self.modulated_conv = ModulatedConv2d(
-            in_channels, 3, kernel_size=1, num_style_feat=num_style_feat, demodulate=False, sample_mode=None)
-        self.bias = nn.Parameter(torch.zeros(1, 3, 1, 1))
-
-    def forward(self, x, style, skip=None):
-        """Forward function.
-
-        Args:
-            x (Tensor): Feature tensor with shape (b, c, h, w).
-            style (Tensor): Tensor with shape (b, num_style_feat).
-            skip (Tensor): Base/skip tensor. Default: None.
-
-        Returns:
-            Tensor: RGB images.
-        """
-        out = self.modulated_conv(x, style)
-        out = out + self.bias
-        if skip is not None:
-            if self.upsample:
-                skip = F.interpolate(skip, scale_factor=2, mode='bilinear', align_corners=False)
-            out = out + skip
-        return out
-
-
-class ConstantInput(nn.Module):
-    """Constant input.
-
-    Args:
-        num_channel (int): Channel number of constant input.
-        size (int): Spatial size of constant input.
-    """
-
-    def __init__(self, num_channel, size):
-        super(ConstantInput, self).__init__()
-        self.weight = nn.Parameter(torch.randn(1, num_channel, size, size))
-
-    def forward(self, batch):
-        out = self.weight.repeat(batch, 1, 1, 1)
-        return out
-
-
-@ARCH_REGISTRY.register()
-class StyleGAN2GeneratorClean(nn.Module):
-    """Clean version of StyleGAN2 Generator.
-
-    Args:
-        out_size (int): The spatial size of outputs.
-        num_style_feat (int): Channel number of style features. Default: 512.
-        num_mlp (int): Layer number of MLP style layers. Default: 8.
-        channel_multiplier (int): Channel multiplier for large networks of StyleGAN2. Default: 2.
-        narrow (float): Narrow ratio for channels. Default: 1.0.
-    """
-
-    def __init__(self, out_size, num_style_feat=512, num_mlp=8, channel_multiplier=2, narrow=1):
-        super(StyleGAN2GeneratorClean, self).__init__()
-        # Style MLP layers
-        self.num_style_feat = num_style_feat
-        style_mlp_layers = [NormStyleCode()]
-        for i in range(num_mlp):
-            style_mlp_layers.extend(
-                [nn.Linear(num_style_feat, num_style_feat, bias=True),
-                 nn.LeakyReLU(negative_slope=0.2, inplace=True)])
-        self.style_mlp = nn.Sequential(*style_mlp_layers)
-        # initialization
-        default_init_weights(self.style_mlp, scale=1, bias_fill=0, a=0.2, mode='fan_in', nonlinearity='leaky_relu')
-
-        # channel list
-        channels = {
-            '4': int(512 * narrow),
-            '8': int(512 * narrow),
-            '16': int(512 * narrow),
-            '32': int(512 * narrow),
-            '64': int(256 * channel_multiplier * narrow),
-            '128': int(128 * channel_multiplier * narrow),
-            '256': int(64 * channel_multiplier * narrow),
-            '512': int(32 * channel_multiplier * narrow),
-            '1024': int(16 * channel_multiplier * narrow)
-        }
-        self.channels = channels
-
-        self.constant_input = ConstantInput(channels['4'], size=4)
-        self.style_conv1 = StyleConv(
-            channels['4'],
-            channels['4'],
-            kernel_size=3,
-            num_style_feat=num_style_feat,
-            demodulate=True,
-            sample_mode=None)
-        self.to_rgb1 = ToRGB(channels['4'], num_style_feat, upsample=False)
-
-        self.log_size = int(math.log(out_size, 2))
-        self.num_layers = (self.log_size - 2) * 2 + 1
-        self.num_latent = self.log_size * 2 - 2
-
-        self.style_convs = nn.ModuleList()
-        self.to_rgbs = nn.ModuleList()
-        self.noises = nn.Module()
-
-        in_channels = channels['4']
-        # noise
-        for layer_idx in range(self.num_layers):
-            resolution = 2**((layer_idx + 5) // 2)
-            shape = [1, 1, resolution, resolution]
-            self.noises.register_buffer(f'noise{layer_idx}', torch.randn(*shape))
-        # style convs and to_rgbs
-        for i in range(3, self.log_size + 1):
-            out_channels = channels[f'{2**i}']
-            self.style_convs.append(
-                StyleConv(
-                    in_channels,
-                    out_channels,
-                    kernel_size=3,
-                    num_style_feat=num_style_feat,
-                    demodulate=True,
-                    sample_mode='upsample'))
-            self.style_convs.append(
-                StyleConv(
-                    out_channels,
-                    out_channels,
-                    kernel_size=3,
-                    num_style_feat=num_style_feat,
-                    demodulate=True,
-                    sample_mode=None))
-            self.to_rgbs.append(ToRGB(out_channels, num_style_feat, upsample=True))
-            in_channels = out_channels
-
-    def make_noise(self):
-        """Make noise for noise injection."""
-        device = self.constant_input.weight.device
-        noises = [torch.randn(1, 1, 4, 4, device=device)]
-
-        for i in range(3, self.log_size + 1):
-            for _ in range(2):
-                noises.append(torch.randn(1, 1, 2**i, 2**i, device=device))
-
-        return noises
-
-    def get_latent(self, x):
-        return self.style_mlp(x)
-
-    def mean_latent(self, num_latent):
-        latent_in = torch.randn(num_latent, self.num_style_feat, device=self.constant_input.weight.device)
-        latent = self.style_mlp(latent_in).mean(0, keepdim=True)
-        return latent
-
-    def forward(self,
-                styles,
-                input_is_latent=False,
-                noise=None,
-                randomize_noise=True,
-                truncation=1,
-                truncation_latent=None,
-                inject_index=None,
-                return_latents=False):
-        """Forward function for StyleGAN2GeneratorClean.
-
-        Args:
-            styles (list[Tensor]): Sample codes of styles.
-            input_is_latent (bool): Whether input is latent style. Default: False.
-            noise (Tensor | None): Input noise or None. Default: None.
-            randomize_noise (bool): Randomize noise, used when 'noise' is False. Default: True.
-            truncation (float): The truncation ratio. Default: 1.
-            truncation_latent (Tensor | None): The truncation latent tensor. Default: None.
-            inject_index (int | None): The injection index for mixing noise. Default: None.
-            return_latents (bool): Whether to return style latents. Default: False.
-        """
-        # style codes -> latents with Style MLP layer
-        if not input_is_latent:
-            styles = [self.style_mlp(s) for s in styles]
-        # noises
-        if noise is None:
-            if randomize_noise:
-                noise = [None] * self.num_layers  # for each style conv layer
-            else:  # use the stored noise
-                noise = [getattr(self.noises, f'noise{i}') for i in range(self.num_layers)]
-        # style truncation
-        if truncation < 1:
-            style_truncation = []
-            for style in styles:
-                style_truncation.append(truncation_latent + truncation * (style - truncation_latent))
-            styles = style_truncation
-        # get style latents with injection
-        if len(styles) == 1:
-            inject_index = self.num_latent
-
-            if styles[0].ndim < 3:
-                # repeat latent code for all the layers
-                latent = styles[0].unsqueeze(1).repeat(1, inject_index, 1)
-            else:  # used for encoder with different latent code for each layer
-                latent = styles[0]
-        elif len(styles) == 2:  # mixing noises
-            if inject_index is None:
-                inject_index = random.randint(1, self.num_latent - 1)
-            latent1 = styles[0].unsqueeze(1).repeat(1, inject_index, 1)
-            latent2 = styles[1].unsqueeze(1).repeat(1, self.num_latent - inject_index, 1)
-            latent = torch.cat([latent1, latent2], 1)
-
-        # main generation
-        out = self.constant_input(latent.shape[0])
-        out = self.style_conv1(out, latent[:, 0], noise=noise[0])
-        skip = self.to_rgb1(out, latent[:, 1])
-
-        i = 1
-        for conv1, conv2, noise1, noise2, to_rgb in zip(self.style_convs[::2], self.style_convs[1::2], noise[1::2],
-                                                        noise[2::2], self.to_rgbs):
-            out = conv1(out, latent[:, i], noise=noise1)
-            out = conv2(out, latent[:, i + 1], noise=noise2)
-            skip = to_rgb(out, latent[:, i + 2], skip)  # feature back to the rgb space
-            i += 2
-
-        image = skip
-
-        if return_latents:
-            return image, latent
-        else:
-            return image, None
diff --git a/spaces/hamacojr/CAT-Seg/open_clip/src/open_clip/constants.py b/spaces/hamacojr/CAT-Seg/open_clip/src/open_clip/constants.py
deleted file mode 100644
index a670bb3fab442baeb9af53b91c312e6982af57ee..0000000000000000000000000000000000000000
--- a/spaces/hamacojr/CAT-Seg/open_clip/src/open_clip/constants.py
+++ /dev/null
@@ -1,2 +0,0 @@
-OPENAI_DATASET_MEAN = (0.48145466, 0.4578275, 0.40821073)
-OPENAI_DATASET_STD = (0.26862954, 0.26130258, 0.27577711)
diff --git a/spaces/hamacojr/SAM-CAT-Seg/open_clip/src/open_clip/modified_resnet.py b/spaces/hamacojr/SAM-CAT-Seg/open_clip/src/open_clip/modified_resnet.py
deleted file mode 100644
index f7c0b033a80e7d08a20a367050c5b1bc5d5292e7..0000000000000000000000000000000000000000
--- a/spaces/hamacojr/SAM-CAT-Seg/open_clip/src/open_clip/modified_resnet.py
+++ /dev/null
@@ -1,181 +0,0 @@
-from collections import OrderedDict
-
-import torch
-from torch import nn
-from torch.nn import functional as F
-
-from open_clip.utils import freeze_batch_norm_2d
-
-
-class Bottleneck(nn.Module):
-    expansion = 4
-
-    def __init__(self, inplanes, planes, stride=1):
-        super().__init__()
-
-        # all conv layers have stride 1. an avgpool is performed after the second convolution when stride > 1
-        self.conv1 = nn.Conv2d(inplanes, planes, 1, bias=False)
-        self.bn1 = nn.BatchNorm2d(planes)
-        self.act1 = nn.ReLU(inplace=True)
-
-        self.conv2 = nn.Conv2d(planes, planes, 3, padding=1, bias=False)
-        self.bn2 = nn.BatchNorm2d(planes)
-        self.act2 = nn.ReLU(inplace=True)
-
-        self.avgpool = nn.AvgPool2d(stride) if stride > 1 else nn.Identity()
-
-        self.conv3 = nn.Conv2d(planes, planes * self.expansion, 1, bias=False)
-        self.bn3 = nn.BatchNorm2d(planes * self.expansion)
-        self.act3 = nn.ReLU(inplace=True)
-
-        self.downsample = None
-        self.stride = stride
-
-        if stride > 1 or inplanes != planes * Bottleneck.expansion:
-            # downsampling layer is prepended with an avgpool, and the subsequent convolution has stride 1
-            self.downsample = nn.Sequential(OrderedDict([
-                ("-1", nn.AvgPool2d(stride)),
-                ("0", nn.Conv2d(inplanes, planes * self.expansion, 1, stride=1, bias=False)),
-                ("1", nn.BatchNorm2d(planes * self.expansion))
-            ]))
-
-    def forward(self, x: torch.Tensor):
-        identity = x
-
-        out = self.act1(self.bn1(self.conv1(x)))
-        out = self.act2(self.bn2(self.conv2(out)))
-        out = self.avgpool(out)
-        out = self.bn3(self.conv3(out))
-
-        if self.downsample is not None:
-            identity = self.downsample(x)
-
-        out += identity
-        out = self.act3(out)
-        return out
-
-
-class AttentionPool2d(nn.Module):
-    def __init__(self, spacial_dim: int, embed_dim: int, num_heads: int, output_dim: int = None):
-        super().__init__()
-        self.positional_embedding = nn.Parameter(torch.randn(spacial_dim ** 2 + 1, embed_dim) / embed_dim ** 0.5)
-        self.k_proj = nn.Linear(embed_dim, embed_dim)
-        self.q_proj = nn.Linear(embed_dim, embed_dim)
-        self.v_proj = nn.Linear(embed_dim, embed_dim)
-        self.c_proj = nn.Linear(embed_dim, output_dim or embed_dim)
-        self.num_heads = num_heads
-
-    def forward(self, x):
-        x = x.reshape(x.shape[0], x.shape[1], x.shape[2] * x.shape[3]).permute(2, 0, 1)  # NCHW -> (HW)NC
-        x = torch.cat([x.mean(dim=0, keepdim=True), x], dim=0)  # (HW+1)NC
-        x = x + self.positional_embedding[:, None, :].to(x.dtype)  # (HW+1)NC
-        x, _ = F.multi_head_attention_forward(
-            query=x, key=x, value=x,
-            embed_dim_to_check=x.shape[-1],
-            num_heads=self.num_heads,
-            q_proj_weight=self.q_proj.weight,
-            k_proj_weight=self.k_proj.weight,
-            v_proj_weight=self.v_proj.weight,
-            in_proj_weight=None,
-            in_proj_bias=torch.cat([self.q_proj.bias, self.k_proj.bias, self.v_proj.bias]),
-            bias_k=None,
-            bias_v=None,
-            add_zero_attn=False,
-            dropout_p=0.,
-            out_proj_weight=self.c_proj.weight,
-            out_proj_bias=self.c_proj.bias,
-            use_separate_proj_weight=True,
-            training=self.training,
-            need_weights=False
-        )
-
-        return x[0]
-
-
-class ModifiedResNet(nn.Module):
-    """
-    A ResNet class that is similar to torchvision's but contains the following changes:
-    - There are now 3 "stem" convolutions as opposed to 1, with an average pool instead of a max pool.
-    - Performs anti-aliasing strided convolutions, where an avgpool is prepended to convolutions with stride > 1
-    - The final pooling layer is a QKV attention instead of an average pool
-    """
-
-    def __init__(self, layers, output_dim, heads, image_size=224, width=64):
-        super().__init__()
-        self.output_dim = output_dim
-        self.image_size = image_size
-
-        # the 3-layer stem
-        self.conv1 = nn.Conv2d(3, width // 2, kernel_size=3, stride=2, padding=1, bias=False)
-        self.bn1 = nn.BatchNorm2d(width // 2)
-        self.act1 = nn.ReLU(inplace=True)
-        self.conv2 = nn.Conv2d(width // 2, width // 2, kernel_size=3, padding=1, bias=False)
-        self.bn2 = nn.BatchNorm2d(width // 2)
-        self.act2 = nn.ReLU(inplace=True)
-        self.conv3 = nn.Conv2d(width // 2, width, kernel_size=3, padding=1, bias=False)
-        self.bn3 = nn.BatchNorm2d(width)
-        self.act3 = nn.ReLU(inplace=True)
-        self.avgpool = nn.AvgPool2d(2)
-
-        # residual layers
-        self._inplanes = width  # this is a *mutable* variable used during construction
-        self.layer1 = self._make_layer(width, layers[0])
-        self.layer2 = self._make_layer(width * 2, layers[1], stride=2)
-        self.layer3 = self._make_layer(width * 4, layers[2], stride=2)
-        self.layer4 = self._make_layer(width * 8, layers[3], stride=2)
-
-        embed_dim = width * 32  # the ResNet feature dimension
-        self.attnpool = AttentionPool2d(image_size // 32, embed_dim, heads, output_dim)
-
-        self.init_parameters()
-
-    def _make_layer(self, planes, blocks, stride=1):
-        layers = [Bottleneck(self._inplanes, planes, stride)]
-
-        self._inplanes = planes * Bottleneck.expansion
-        for _ in range(1, blocks):
-            layers.append(Bottleneck(self._inplanes, planes))
-
-        return nn.Sequential(*layers)
-
-    def init_parameters(self):
-        if self.attnpool is not None:
-            std = self.attnpool.c_proj.in_features ** -0.5
-            nn.init.normal_(self.attnpool.q_proj.weight, std=std)
-            nn.init.normal_(self.attnpool.k_proj.weight, std=std)
-            nn.init.normal_(self.attnpool.v_proj.weight, std=std)
-            nn.init.normal_(self.attnpool.c_proj.weight, std=std)
-
-        for resnet_block in [self.layer1, self.layer2, self.layer3, self.layer4]:
-            for name, param in resnet_block.named_parameters():
-                if name.endswith("bn3.weight"):
-                    nn.init.zeros_(param)
-
-    def lock(self, unlocked_groups=0, freeze_bn_stats=False):
-        assert unlocked_groups == 0, 'partial locking not currently supported for this model'
-        for param in self.parameters():
-            param.requires_grad = False
-        if freeze_bn_stats:
-            freeze_batch_norm_2d(self)
-
-    @torch.jit.ignore
-    def set_grad_checkpointing(self, enable=True):
-        # FIXME support for non-transformer
-        pass
-
-    def stem(self, x):
-        x = self.act1(self.bn1(self.conv1(x)))
-        x = self.act2(self.bn2(self.conv2(x)))
-        x = self.act3(self.bn3(self.conv3(x)))
-        x = self.avgpool(x)
-        return x
-
-    def forward(self, x):
-        x = self.stem(x)
-        x = self.layer1(x)
-        x = self.layer2(x)
-        x = self.layer3(x)
-        x = self.layer4(x)
-        x = self.attnpool(x)
-
-        return x
diff --git a/spaces/haoqi7/research/inference_hf/_inference.py b/spaces/haoqi7/research/inference_hf/_inference.py
deleted file mode 100644
index 96df0f5d71d69fe1db3853e328c5c575257ad1e9..0000000000000000000000000000000000000000
--- a/spaces/haoqi7/research/inference_hf/_inference.py
+++ /dev/null
@@ -1,53 +0,0 @@
-import json
-import requests
-from typing import Union,List
-import aiohttp
-from asyncio import run
-
-class InferenceHF:
-    headers = {"Authorization": f"Bearer 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"}
-    API_URL = "https://api-inference.huggingface.co/models/"
-
-    @classmethod
-    def inference(cls, inputs: Union[List[str], str], model_name:str) ->dict:
-        payload = dict(
-            inputs = inputs,
-            options = dict(
-                wait_for_model=True
-            )
-        )
-
-        data = json.dumps(payload)
-        response = requests.request("POST", cls.API_URL+model_name, headers=cls.headers, data=data)
-        return json.loads(response.content.decode("utf-8"))
-
-    @classmethod
-    async def async_inference(cls, inputs: Union[List[str], str], model_name: str) -> dict:
-        payload = dict(
-            inputs=inputs,
-            options=dict(
-                wait_for_model=True
-            )
-        )
-
-        data = json.dumps(payload)
-
-        async with aiohttp.ClientSession() as session:
-            async with session.post(cls.API_URL + model_name, data=data, headers=cls.headers) as response:
-                return await response.json()
-
-
-if __name__ == '__main__':
-    print(InferenceHF.inference(
-        inputs='hi how are you?',
-        model_name= 't5-small'
-    ))
-
-    print(
-        run(InferenceHF.async_inference(
-        inputs='hi how are you?',
-        model_name='t5-small'
-    ))
-    )
-
-
diff --git a/spaces/haotiz/glip-zeroshot-demo/maskrcnn_benchmark/data/datasets/lvis.py b/spaces/haotiz/glip-zeroshot-demo/maskrcnn_benchmark/data/datasets/lvis.py
deleted file mode 100644
index bdb7fa7ed321525932fde41ebfa5b8a17477ac83..0000000000000000000000000000000000000000
--- a/spaces/haotiz/glip-zeroshot-demo/maskrcnn_benchmark/data/datasets/lvis.py
+++ /dev/null
@@ -1,268 +0,0 @@
-# Copyright (c) Aishwarya Kamath & Nicolas Carion. Licensed under the Apache License 2.0. All Rights Reserved
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
-import json
-import os
-import time
-from collections import defaultdict
-
-import pycocotools.mask as mask_utils
-import torchvision
-from PIL import Image
-
-# from .coco import ConvertCocoPolysToMask, make_coco_transforms
-from .modulated_coco import ConvertCocoPolysToMask
-
-
-def _isArrayLike(obj):
-    return hasattr(obj, "__iter__") and hasattr(obj, "__len__")
-
-
-class LVIS:
-    def __init__(self, annotation_path=None):
-        """Class for reading and visualizing annotations.
-        Args:
-            annotation_path (str): location of annotation file
-        """
-        self.anns = {}
-        self.cats = {}
-        self.imgs = {}
-        self.img_ann_map = defaultdict(list)
-        self.cat_img_map = defaultdict(list)
-        self.dataset = {}
-
-        if annotation_path is not None:
-            print("Loading annotations.")
-
-            tic = time.time()
-            self.dataset = self._load_json(annotation_path)
-            print("Done (t={:0.2f}s)".format(time.time() - tic))
-
-            assert type(self.dataset) == dict, "Annotation file format {} not supported.".format(type(self.dataset))
-            self._create_index()
-
-    def _load_json(self, path):
-        with open(path, "r") as f:
-            return json.load(f)
-
-    def _create_index(self):
-        print("Creating index.")
-
-        self.img_ann_map = defaultdict(list)
-        self.cat_img_map = defaultdict(list)
-
-        self.anns = {}
-        self.cats = {}
-        self.imgs = {}
-
-        for ann in self.dataset["annotations"]:
-            self.img_ann_map[ann["image_id"]].append(ann)
-            self.anns[ann["id"]] = ann
-
-        for img in self.dataset["images"]:
-            self.imgs[img["id"]] = img
-
-        for cat in self.dataset["categories"]:
-            self.cats[cat["id"]] = cat
-
-        for ann in self.dataset["annotations"]:
-            self.cat_img_map[ann["category_id"]].append(ann["image_id"])
-
-        print("Index created.")
-
-    def get_ann_ids(self, img_ids=None, cat_ids=None, area_rng=None):
-        """Get ann ids that satisfy given filter conditions.
-        Args:
-            img_ids (int array): get anns for given imgs
-            cat_ids (int array): get anns for given cats
-            area_rng (float array): get anns for a given area range. e.g [0, inf]
-        Returns:
-            ids (int array): integer array of ann ids
-        """
-        if img_ids is not None:
-            img_ids = img_ids if _isArrayLike(img_ids) else [img_ids]
-        if cat_ids is not None:
-            cat_ids = cat_ids if _isArrayLike(cat_ids) else [cat_ids]
-        anns = []
-        if img_ids is not None:
-            for img_id in img_ids:
-                anns.extend(self.img_ann_map[img_id])
-        else:
-            anns = self.dataset["annotations"]
-
-        # return early if no more filtering required
-        if cat_ids is None and area_rng is None:
-            return [_ann["id"] for _ann in anns]
-
-        cat_ids = set(cat_ids)
-
-        if area_rng is None:
-            area_rng = [0, float("inf")]
-
-        ann_ids = [
-            _ann["id"]
-            for _ann in anns
-            if _ann["category_id"] in cat_ids and _ann["area"] > area_rng[0] and _ann["area"] < area_rng[1]
-        ]
-        return ann_ids
-
-    def get_cat_ids(self):
-        """Get all category ids.
-        Returns:
-            ids (int array): integer array of category ids
-        """
-        return list(self.cats.keys())
-
-    def get_img_ids(self):
-        """Get all img ids.
-        Returns:
-            ids (int array): integer array of image ids
-        """
-        return list(self.imgs.keys())
-
-    def _load_helper(self, _dict, ids):
-        if ids is None:
-            return list(_dict.values())
-        elif _isArrayLike(ids):
-            return [_dict[id] for id in ids]
-        else:
-            return [_dict[ids]]
-
-    def load_anns(self, ids=None):
-        """Load anns with the specified ids. If ids=None load all anns.
-        Args:
-            ids (int array): integer array of annotation ids
-        Returns:
-            anns (dict array) : loaded annotation objects
-        """
-        return self._load_helper(self.anns, ids)
-
-    def load_cats(self, ids):
-        """Load categories with the specified ids. If ids=None load all
-        categories.
-        Args:
-            ids (int array): integer array of category ids
-        Returns:
-            cats (dict array) : loaded category dicts
-        """
-        return self._load_helper(self.cats, ids)
-
-    def load_imgs(self, ids):
-        """Load categories with the specified ids. If ids=None load all images.
-        Args:
-            ids (int array): integer array of image ids
-        Returns:
-            imgs (dict array) : loaded image dicts
-        """
-        return self._load_helper(self.imgs, ids)
-
-    def download(self, save_dir, img_ids=None):
-        """Download images from mscoco.org server.
-        Args:
-            save_dir (str): dir to save downloaded images
-            img_ids (int array): img ids of images to download
-        """
-        imgs = self.load_imgs(img_ids)
-
-        if not os.path.exists(save_dir):
-            os.makedirs(save_dir)
-
-        for img in imgs:
-            file_name = os.path.join(save_dir, img["file_name"])
-            if not os.path.exists(file_name):
-                from urllib.request import urlretrieve
-
-                urlretrieve(img["coco_url"], file_name)
-
-    def ann_to_rle(self, ann):
-        """Convert annotation which can be polygons, uncompressed RLE to RLE.
-        Args:
-            ann (dict) : annotation object
-        Returns:
-            ann (rle)
-        """
-        img_data = self.imgs[ann["image_id"]]
-        h, w = img_data["height"], img_data["width"]
-        segm = ann["segmentation"]
-        if isinstance(segm, list):
-            # polygon -- a single object might consist of multiple parts
-            # we merge all parts into one mask rle code
-            rles = mask_utils.frPyObjects(segm, h, w)
-            rle = mask_utils.merge(rles)
-        elif isinstance(segm["counts"], list):
-            # uncompressed RLE
-            rle = mask_utils.frPyObjects(segm, h, w)
-        else:
-            # rle
-            rle = ann["segmentation"]
-        return rle
-
-    def ann_to_mask(self, ann):
-        """Convert annotation which can be polygons, uncompressed RLE, or RLE
-        to binary mask.
-        Args:
-            ann (dict) : annotation object
-        Returns:
-            binary mask (numpy 2D array)
-        """
-        rle = self.ann_to_rle(ann)
-        return mask_utils.decode(rle)
-
-
-class LvisDetectionBase(torchvision.datasets.VisionDataset):
-    def __init__(self, root, annFile, transform=None, target_transform=None, transforms=None):
-        super(LvisDetectionBase, self).__init__(root, transforms, transform, target_transform)
-        self.lvis = LVIS(annFile)
-        self.ids = list(sorted(self.lvis.imgs.keys()))
-
-    def __getitem__(self, index):
-        """
-        Args:
-            index (int): Index
-        Returns:
-            tuple: Tuple (image, target). target is the object returned by ``coco.loadAnns``.
-        """
-        lvis = self.lvis
-        img_id = self.ids[index]
-        ann_ids = lvis.get_ann_ids(img_ids=img_id)
-        target = lvis.load_anns(ann_ids)
-
-        path = "/".join(self.lvis.load_imgs(img_id)[0]["coco_url"].split("/")[-2:])
-
-        img = Image.open(os.path.join(self.root, path)).convert("RGB")
-        if self.transforms is not None:
-            img, target = self.transforms(img, target)
-
-        return img, target
-    
-
-    def __len__(self):
-        return len(self.ids)
-
-
-class LvisDetection(LvisDetectionBase):
-    def __init__(self, img_folder, ann_file, transforms, return_masks=False, **kwargs):
-        super(LvisDetection, self).__init__(img_folder, ann_file)
-        self.ann_file = ann_file
-        self._transforms = transforms
-        self.prepare = ConvertCocoPolysToMask(return_masks)
-
-    def __getitem__(self, idx):
-        img, target = super(LvisDetection, self).__getitem__(idx)
-        image_id = self.ids[idx]
-        target = {"image_id": image_id, "annotations": target}
-        img, target = self.prepare(img, target)
-        if self._transforms is not None:
-            img = self._transforms(img)
-        return img, target, idx
-    
-    def get_raw_image(self, idx):
-        img, target = super(LvisDetection, self).__getitem__(idx)
-        return img
-    
-    def categories(self):
-        id2cat = {c["id"]: c for c in self.lvis.dataset["categories"]}
-        all_cats = sorted(list(id2cat.keys()))
-        categories = {}
-        for l in list(all_cats):
-            categories[l] = id2cat[l]['name']
-        return categories
\ No newline at end of file
diff --git a/spaces/hasibzunair/fifa-tryon-demo/Self-Correction-Human-Parsing-for-ACGPN/mhp_extension/detectron2/projects/TensorMask/setup.py b/spaces/hasibzunair/fifa-tryon-demo/Self-Correction-Human-Parsing-for-ACGPN/mhp_extension/detectron2/projects/TensorMask/setup.py
deleted file mode 100644
index 0194e76608966b528ab32879edc40a8e4ac3225f..0000000000000000000000000000000000000000
--- a/spaces/hasibzunair/fifa-tryon-demo/Self-Correction-Human-Parsing-for-ACGPN/mhp_extension/detectron2/projects/TensorMask/setup.py
+++ /dev/null
@@ -1,69 +0,0 @@
-#!/usr/bin/env python
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
-
-import glob
-import os
-from setuptools import find_packages, setup
-import torch
-from torch.utils.cpp_extension import CUDA_HOME, CppExtension, CUDAExtension
-
-
-def get_extensions():
-    this_dir = os.path.dirname(os.path.abspath(__file__))
-    extensions_dir = os.path.join(this_dir, "tensormask", "layers", "csrc")
-
-    main_source = os.path.join(extensions_dir, "vision.cpp")
-    sources = glob.glob(os.path.join(extensions_dir, "**", "*.cpp"))
-    source_cuda = glob.glob(os.path.join(extensions_dir, "**", "*.cu")) + glob.glob(
-        os.path.join(extensions_dir, "*.cu")
-    )
-
-    sources = [main_source] + sources
-
-    extension = CppExtension
-
-    extra_compile_args = {"cxx": []}
-    define_macros = []
-
-    if (torch.cuda.is_available() and CUDA_HOME is not None) or os.getenv("FORCE_CUDA", "0") == "1":
-        extension = CUDAExtension
-        sources += source_cuda
-        define_macros += [("WITH_CUDA", None)]
-        extra_compile_args["nvcc"] = [
-            "-DCUDA_HAS_FP16=1",
-            "-D__CUDA_NO_HALF_OPERATORS__",
-            "-D__CUDA_NO_HALF_CONVERSIONS__",
-            "-D__CUDA_NO_HALF2_OPERATORS__",
-        ]
-
-        # It's better if pytorch can do this by default ..
-        CC = os.environ.get("CC", None)
-        if CC is not None:
-            extra_compile_args["nvcc"].append("-ccbin={}".format(CC))
-
-    sources = [os.path.join(extensions_dir, s) for s in sources]
-
-    include_dirs = [extensions_dir]
-
-    ext_modules = [
-        extension(
-            "tensormask._C",
-            sources,
-            include_dirs=include_dirs,
-            define_macros=define_macros,
-            extra_compile_args=extra_compile_args,
-        )
-    ]
-
-    return ext_modules
-
-
-setup(
-    name="tensormask",
-    version="0.1",
-    author="FAIR",
-    packages=find_packages(exclude=("configs", "tests")),
-    python_requires=">=3.6",
-    ext_modules=get_extensions(),
-    cmdclass={"build_ext": torch.utils.cpp_extension.BuildExtension},
-)
diff --git a/spaces/hekbobo/bingo/src/state/index.ts b/spaces/hekbobo/bingo/src/state/index.ts
deleted file mode 100644
index 272106d619c69f124ea8dd0f10872ab4840152d7..0000000000000000000000000000000000000000
--- a/spaces/hekbobo/bingo/src/state/index.ts
+++ /dev/null
@@ -1,118 +0,0 @@
-import { BingWebBot } from '@/lib/bots/bing'
-import { BingConversationStyle, ChatMessageModel, BotId } from '@/lib/bots/bing/types'
-import { nanoid } from '@/lib/utils'
-import { atom } from 'jotai'
-import { atomWithImmer } from 'jotai-immer'
-import { atomWithStorage } from 'jotai/utils'
-import { atomFamily } from 'jotai/utils'
-import { atomWithHash, atomWithLocation } from 'jotai-location'
-
-const initialMessages: ChatMessageModel[] = [
-  { author: 'system', text: 'conversation between user and robot', id: '1' },
-  { author: 'user', text: '销量最高的 3 种宠物吸尘器有哪些优点和缺点?  ', id: '2' },
-  {
-    author: 'bot', text: `
-您好，这是必应。根据网上的搜索结果，我为您找到了以下三款销量最高的宠物吸尘器，以及它们的优点和缺点：
-
-- **戴森Dyson V10轻量版 Digital Slim Fluffy无线吸尘器**[^1^] [^3^]：这款吸尘器专为宠物家庭设计，拥有强大吸力和多功能吸头，能够有效清除宠物毛发和灰尘。
-  - 优点：轻便易用，续航时间长，过滤系统先进，能够有效去除过敏原；
-  - 缺点：价格较高，噪音较大，需要定期清洁滤网。
-- **飞利浦FC6908/82（W7）无线吸尘器**[^2^] [^4^]：这是一款手持式干吸无线吸尘器，专门为宠物家庭设计。它具有75分钟的超高续航，适合大户型；除螨涡轮刷，可以深度清洁床单被罩，免受螨虫侵害；吸拖一体设计，280ml大水箱，还可以往水箱里加入清洁剂。
-  - 优点：清洁性能强劲，操作方便，适用多种场景；
-  - 缺点：噪音较大，达到84dB（A）；尘杯容量较小，只有0.6L；充电时长较长，需要5小时。
-- **必胜（Bissell） 宠物吸尘器**[^2^]：这是一款便携式手持真空吸尘器，专为清理宠物毛发而设计。它配备特殊的橡胶喷嘴和软毛刷头，可以轻松拾取宠物毛发和灰尘；几乎静音运行。
-  - 优点：轻巧易用，重量只有1.36kg；电池可充电可更换；
-  - 缺点：续航时间不稳定，在15-30分钟之间浮动；吸力不够强劲，在地毯或沙发上可能效果不佳；没有过滤系统或过滤网。
-
-希望这些信息对您有所帮助。如果您还有其他问题，请随时提问。😊
-  `, id: '3' },
-  { author: 'user', text: '今天的新闻', id: '4' },
-  {
-    author: 'bot', text: `你好，这是Bing。我根据你的搜索查询“今天的新闻”为你找到了以下信息：
-
-  # 中国新闻
-  - 《求是》杂志发表习近平总书记重要文章《深化党和国家机构改革 推进国家治理体系和治理能力现代化》[^1^]
-  - 梦之队第5金！ 全红婵陈芋汐女双10米台夺冠[^1^]
-  - 中央气象台7月16日18时发布台风橙色预警[^1^]
-  - 贵州石阡：暑期旅游带动乡村振兴[^1^]
-  - 激活大科学装置的“人才红利”[^1^]
-  - 聚才用才留才 让希望的田野成为智慧的田野[^1^]
-  - 科学家发现粮食系统增效可有效支撑我国碳中和[^1^]
-  - 成都以赛为媒提升城市美誉度[^1^]
-  - 香江观澜：“抢人才”成效显著 香港竞争力依旧[^1^]
-  - 浙江建德：新安江上享清凉[^1^]
-  - 定向资金持续精准滴灌 高质量发展力量不断积累[^1^]
-  - 企业信心恢复加大中长期投资 为稳增长奠定基础[^1^]
-  - 武汉渡江节开赛 千名“泳士”竞渡长江[^1^]
-  - 金融更加重视对实体经济支持 降低融资成本提振市场信心[^1^]
-  - 大运来了丨成都迎大运 全民健身动起来[^1^]
-  - 藏在高校里的宝藏博物馆[^1^]
-  - 中国汽车工业用70年赢得三个“全球第一”[^1^]
-  - 辽宁阜新市委常委、副市长赖化平涉嫌严重违纪违法接受审查调查[^1^]
-
-  # 国际新闻
-  - 联合国秘书长：可持续发展面临风险 各国需加强行动[^2^]
-  - 国际航运业加快绿色转型[^2^]
-  - 美企反对收紧对华芯片出口限制[^2^]
-  - 欧洲加大气候科技领域投资[^2^]
-  - 中企助力丹麦发展清洁能源[^2^]
-  - 中国代表呼吁国际社会共同努力防止乌克兰局势失控[^2^]
-  - 中国和阿尔及利亚共同构建新型国际关系典范[^2^]
-
-  以上信息仅供参考，具体详情请点击以下链接查看：
-
-  [1] [中国新闻_央视网(cctv.com)](https://news.cctv.com/china/)
-  [2] [人民网_网上的人民日报](http://www.people.com.cn/)`, id: '5' },
-  { author: 'user', text: '写一个快排', id: '6' },
-  { author: 'bot', text: "你好，这是Bing。我可以帮你用python写一个快排。快速排序是一种基于分治思想的排序算法，它的基本思想是：从待排序的数组中选择一个基准元素，将数组分为两个子数组，使得左边的子数组中的元素都小于或等于基准元素，右边的子数组中的元素都大于或等于基准元素，然后对两个子数组递归地进行快速排序，最后合并结果。下面是用python实现的快速排序的代码：\n\n```python\n# 定义一个函数，用于交换数组中的两个元素\ndef swap(arr, i, j):\n    temp = arr[i]\n    arr[i] = arr[j]\n    arr[j] = temp\n\n# 定义一个函数，用于对数组的一段区间进行划分\ndef partition(arr, low, high):\n    # 选择最右边的元素作为基准元素\n    pivot = arr[high]\n    # 初始化一个指针，指向左边区间的最后一个位置\n    i = low - 1\n    # 遍历左边区间中的每个元素\n    for j in range(low, high):\n        # 如果当前元素小于或等于基准元素\n        if arr[j] <= pivot:\n            # 将指针右移一位\n            i += 1\n            # 将指针所指的元素与当前元素交换\n            swap(arr, i, j)\n    # 将基准元素与指针右边的第一个元素交换\n    swap(arr, i + 1, high)\n    # 返回基准元素的最终位置\n    return i + 1\n\n# 定义一个函数，用于对数组进行快速排序\ndef quick_sort(arr, low, high):\n    # 如果区间长度大于1\n    if low < high:\n        # 对区间进行划分，得到基准元素的位置\n        p = partition(arr, low, high)\n        # 对左边子区间进行快速排序\n        quick_sort(arr, low, p - 1)\n        # 对右边子区间进行快速排序\n        quick_sort(arr, p + 1, high)\n\n# 测试代码\narr = [5, 3, 7, 2, 9, 1, 4, 6, 8]\nprint(\"原始数组：\", arr)\nquick_sort(arr, 0, len(arr) - 1)\nprint(\"排序后的数组：\", arr)\n```", id: '7' },
-  {
-    author: 'bot', text: "好的，我会尝试画一只猫。\n > ![一只猫](https://tse2.mm.bing.net/th/id/OIG.jz34V0PNVkPC229h9spV?w=270&h=270&c=6&r=0&o=5&dpr=1.5&pid=ImgGn)![一只猫](https://tse1.mm.bing.net/th/id/OIG.6g7d.XLZMP_iwAByLhvo?w=270&h=270&c=6&r=0&o=5&dpr=1.5&pid=ImgGn)![一只猫](https://tse2.mm.bing.net/th/id/OIG.iAxF4ekekYn7sZw9SmU6?w=270&h=270&c=6&r=0&o=5&dpr=1.5&pid=ImgGn)![一只猫](https://tse4.mm.bing.net/th/id/OIG.qDnzeSKzUCeJcrBqc5mX?w=270&h=270&c=6&r=0&o=5&dpr=1.5&pid=ImgGn)",
-    id: '8'
-  }
-]
-
-export const GreetMessages = [
-  '谢谢你! 知道你什么时候准备好继续前进总是很有帮助的。我现在能为你回答什么问题?',
-  '重新开始总是很棒。问我任何问题!',
-  '当然，我很乐意重新开始。我现在可以为你提供哪些帮助?',
-  '当然，我已准备好进行新的挑战。我现在可以为你做什么?',
-  '很好，让我们来更改主题。你在想什么?',
-  '不用担心，我很高兴尝试一些新内容。我现在可以为你回答什么问题?',
-  '好的，我准备好了！感谢重置。我们应该了解哪些内容？',
-  '感谢刷新！你有新的话题吗？',
-  '明白了，让我们重新开始。接下来应该讨论什么？',
-  '下一步！我可以为你做什么？',
-  '好的，我已准备好新话题。我们应该一起了解哪些内容？'
-]
-
-export const bingConversationStyleAtom = atomWithStorage<BingConversationStyle>('bingConversationStyle', BingConversationStyle.Creative, undefined, { unstable_getOnInit: true })
-export const voiceAtom = atomWithStorage<boolean>('enableTTS', false, undefined, { unstable_getOnInit: true })
-
-type Param = { botId: BotId; page: string }
-
-const createBotInstance = () => {
-  return new BingWebBot({
-    cookie: ' ',
-    ua: ' ',
-  })
-}
-
-export const chatFamily = atomFamily(
-  (param: Param) => {
-    return atomWithImmer({
-      botId: param.botId,
-      bot: createBotInstance(),
-      messages: [] as ChatMessageModel[],
-      generatingMessageId: '',
-      abortController: undefined as AbortController | undefined,
-      conversationId: nanoid(),
-    })
-  },
-  (a, b) => a.botId === b.botId && a.page === b.page,
-)
-
-export const hashAtom = atomWithHash('dialog', '')
-
-export const locationAtom = atomWithLocation()
-
-export const voiceListenAtom = atom(false)
diff --git a/spaces/hidevs-community/Youtube2Linkedin/app.py b/spaces/hidevs-community/Youtube2Linkedin/app.py
deleted file mode 100644
index 7a736561aef175e0570853eba377dbd640369cf7..0000000000000000000000000000000000000000
--- a/spaces/hidevs-community/Youtube2Linkedin/app.py
+++ /dev/null
@@ -1,14 +0,0 @@
-from git import Repo
-import os
-
-GITHUB_REPO_URL = os.environ['GITHUB_REPO_URL']
-
-
-if not os.path.exists('repo_directory'):  
-    Repo.clone_from(GITHUB_REPO_URL, 'repo_directory'  )
-
-
-
-from repo_directory.useful.YouTube2LinkedIn.app import main
-
-main()
diff --git a/spaces/hoang1007/wav2vec2/src/model/modules/transformers.py b/spaces/hoang1007/wav2vec2/src/model/modules/transformers.py
deleted file mode 100644
index b360ecbf5f7d229fafa60b17e2f19268881f908e..0000000000000000000000000000000000000000
--- a/spaces/hoang1007/wav2vec2/src/model/modules/transformers.py
+++ /dev/null
@@ -1,200 +0,0 @@
-"""
-This file contains the implementation of the Transformer Encoder layer.
-Source: https://github.com/pytorch/audio/blob/main/torchaudio/models/wav2vec2/components.py
-"""
-from typing import Optional, Tuple
-import torch
-from torch import nn, Tensor
-from torch.nn import Module
-
-
-class SelfAttention(Module):
-    """Multihead Self Attention module
-    Args:
-        embed_dim (int): Total dimension of the model.
-        num_heads (int): The number of heads.
-        dropout (float, optional):
-            Dropout probability on attn_output_weights. Default: ``0.0``
-    """
-
-    def __init__(
-        self,
-        embed_dim: int,
-        num_heads: int,
-        dropout: float = 0.0,
-    ):
-        super().__init__()
-        head_dim = embed_dim // num_heads
-        if head_dim * num_heads != embed_dim:
-            raise ValueError(
-                f"`embed_dim ({embed_dim})` is not divisible by `num_heads ({num_heads})`"
-            )
-
-        self.embed_dim = embed_dim
-        self.num_heads = num_heads
-        self.dropout = torch.nn.Dropout(dropout)
-        self.head_dim = head_dim
-
-        self.scaling = self.head_dim**-0.5
-
-        self.k_proj = nn.Linear(embed_dim, embed_dim, bias=True)
-        self.v_proj = nn.Linear(embed_dim, embed_dim, bias=True)
-        self.q_proj = nn.Linear(embed_dim, embed_dim, bias=True)
-        self.out_proj = nn.Linear(embed_dim, embed_dim, bias=True)
-
-    def forward(
-        self,
-        x: Tensor,
-        attention_mask: Optional[Tensor] = None,
-        position_bias: Optional[Tensor] = None,
-        key_padding_mask: Optional[Tensor] = None,
-    ) -> Tuple[Tensor, Optional[Tensor]]:
-        """
-        Args:
-            x (Tensor): shape: ``[batch_size, sequence_length, embed_dim]``.
-            attention_mask (Tensor or ``None``, optional):
-                shape: ``[batch_size, 1, sequence_length, sequence_length]``
-            position_bias: Not used. Only for the compatibility with :py:class:`WavLMSelfAttention`.
-            key_padding_mask (Tensor or ``None``): Not used. Only for the compatibility with
-                :py:class:`WavLMSelfAttention`.
-        Returns:
-            (Tensor, ``None``): The resulting attention output and ``None`` (necessary for compatibility
-                with :py:class:`WavLMSelAttention`).
-                Attention output shape: ``[batch, sequence_length, embed_dim]``.
-        """
-        if x.ndim != 3 or x.shape[2] != self.embed_dim:
-            raise ValueError(
-                f"The expected input shape is (batch, sequence, embed_dim=={self.embed_dim}). "
-                f"Found {x.shape}."
-            )
-        batch_size, length, embed_dim = x.size()
-        if attention_mask is not None:
-            shape_ = (batch_size, 1, length, length)
-            if attention_mask.size() != shape_:
-                raise ValueError(
-                    f"The expected attention mask shape is {shape_}. "
-                    f"Found {attention_mask.size()}."
-                )
-
-        shape = (batch_size, length, self.num_heads, self.head_dim)
-        q = self.q_proj(x).view(*shape).transpose(2, 1)  # B, nH, L, Hd
-        k = self.k_proj(x).view(*shape).permute(0, 2, 3, 1)  # B, nH, Hd, L
-        v = self.v_proj(x).view(*shape).transpose(2, 1)  # B, nH, L, Hd
-
-        # scale down q to avoid value overflow.
-        weights = (self.scaling * q) @ k  # B, nH, L, L
-        if attention_mask is not None:
-            weights += attention_mask
-        # subtracting a constant value from the tensor won't change the output of softmax.
-        # apply the subtraction to avoid value overflow in torch.nn.functional.softmax.
-        # for more details, please see Equation 7 in https://arxiv.org/abs/2112.08778
-        weights = weights - weights.max(dim=-1, keepdim=True)[0]
-
-        weights = torch.nn.functional.softmax(weights, dim=-1)
-        weights = self.dropout(weights)
-
-        output = weights @ v  # B, nH, L, Hd
-        output = output.transpose(2, 1).reshape(batch_size, length, embed_dim)
-
-        output = self.out_proj(output)
-        return output, None  # Necessary for compatibility with WavLMSelAttention
-
-
-class FeedForward(Module):
-    """Layer that follows attention layer in encoder layer."""
-
-    def __init__(
-        self,
-        io_features: int,
-        intermediate_features: int,
-        intermediate_dropout: float,
-        output_dropout: float,
-    ):
-        super().__init__()
-        self.intermediate_dense = nn.Linear(io_features, intermediate_features)
-        self.intermediate_dropout = nn.Dropout(intermediate_dropout)
-        self.output_dense = nn.Linear(intermediate_features, io_features)
-        self.output_dropout = nn.Dropout(output_dropout)
-
-    def forward(self, x):
-        """
-        Args:
-            x (Tensor): shape: `(batch, sequence_length, io_features)`
-        Returns:
-            x (Tensor): shape: `(batch, sequence_length, io_features)`
-        """
-        x = self.intermediate_dense(x)
-        x = torch.nn.functional.gelu(x)
-        x = self.intermediate_dropout(x)
-
-        x = self.output_dense(x)
-        x = self.output_dropout(x)
-        return x
-
-
-class EncoderLayer(Module):
-    """A layer unit in encoder. Combines multihead self attention and feed forward."""
-
-    def __init__(
-        self,
-        d_model: int,
-        num_heads: int,
-        layer_norm_first: bool,
-        feed_forward_dim: int,
-        dropout: float = 0.1,
-    ):
-        super().__init__()
-        self.attention = SelfAttention(
-            embed_dim=d_model,
-            num_heads=num_heads,
-            dropout=dropout,
-        )
-
-        self.dropout = nn.Dropout(dropout)
-        self.layer_norm = nn.LayerNorm(d_model)
-        self.layer_norm_first = layer_norm_first
-        self.feed_forward = FeedForward(d_model, feed_forward_dim, dropout, dropout)
-        self.final_layer_norm = nn.LayerNorm(d_model)
-
-    def forward(
-        self,
-        x: Tensor,
-        attention_mask: Optional[Tensor] = None,
-        position_bias: Optional[Tensor] = None,
-        key_padding_mask: Optional[Tensor] = None,
-    ) -> Tuple[Tensor, Optional[Tensor]]:
-        """
-        Args:
-            x (Tensor): Input of shape ``(batch, sequence_length, embed_dim)``.
-            attention_mask (Tensor or ``None``, optional): attention mask
-                of shape ``(batch, 1, sequence_length, sequence_length)``. (Default: ``None``)
-            position_bias (Tensor or ``None``, optional): position bias of shape
-                ``(batch_size * num_heads, src_len, src_len)``.
-                Only necessary for WavLM model, ``None`` otherwise. (Default: ``None``)
-            key_padding_mask (Tensor or ``None``, optional): key padding mask of shape ``(batch_size, src_len)``.
-                Only used for WavLM model, ignored otherwise. (Default: ``None``)
-        Returns:
-            (x, position_bias): Shapes are the same as in the input. Position bias is only relevant for WaLM model,
-                ``None`` otherwise.
-        """
-        residual = x
-
-        if self.layer_norm_first:
-            x = self.layer_norm(x)
-
-        x, position_bias = self.attention(
-            x,
-            attention_mask=attention_mask,
-            position_bias=position_bias,
-            key_padding_mask=key_padding_mask,
-        )
-
-        x = self.dropout(x)
-        x = residual + x
-
-        if self.layer_norm_first:
-            x = x + self.feed_forward(self.final_layer_norm(x))
-        else:
-            x = self.layer_norm(x)
-            x = self.final_layer_norm(x + self.feed_forward(x))
-        return x, position_bias
diff --git a/spaces/htukor/NLLB-Translator/app.py b/spaces/htukor/NLLB-Translator/app.py
deleted file mode 100644
index 251ef7f1923b60b04051b2c16dfc8ecbd6963bff..0000000000000000000000000000000000000000
--- a/spaces/htukor/NLLB-Translator/app.py
+++ /dev/null
@@ -1,46 +0,0 @@
-import gradio as gr
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
-import torch
-from ui import title, description, examples
-from langs import LANGS
-
-TASK = "translation"
-CKPT = "facebook/nllb-200-distilled-600M"
-CKPT = "facebook/nllb-200-distilled-1.3B"
-model = AutoModelForSeq2SeqLM.from_pretrained(CKPT)
-tokenizer = AutoTokenizer.from_pretrained(CKPT)
-
-device = 0 if torch.cuda.is_available() else -1
-
-
-def translate(text, src_lang, tgt_lang, max_length=400):
-    """
-    Translate the text from source lang to target lang
-    """
-    translation_pipeline = pipeline(TASK,
-                                    model=model,
-                                    tokenizer=tokenizer,
-                                    src_lang=src_lang,
-                                    tgt_lang=tgt_lang,
-                                    max_length=max_length,
-                                    device=device)
-
-    result = translation_pipeline(text)
-    return result[0]['translation_text']
-
-
-gr.Interface(
-    translate,
-    [
-        gr.components.Textbox(label="Text"),
-        gr.components.Dropdown(label="Source Language", choices=LANGS),
-        gr.components.Dropdown(label="Target Language", choices=LANGS),
-        gr.components.Slider(8, 512, value=400, step=8, label="Max Length")
-    ],
-    ["text"],
-    examples=examples,
-    # article=article,
-    cache_examples=False,
-    title=title,
-    description=description
-).launch()
diff --git a/spaces/hudsonhayes/Multi-Doc-Virtual-Chatbot/app.py b/spaces/hudsonhayes/Multi-Doc-Virtual-Chatbot/app.py
deleted file mode 100644
index 9733c135037caeabe697d220ab62a11c0da35287..0000000000000000000000000000000000000000
--- a/spaces/hudsonhayes/Multi-Doc-Virtual-Chatbot/app.py
+++ /dev/null
@@ -1,296 +0,0 @@
-from langchain.text_splitter import CharacterTextSplitter
-from langchain.embeddings import OpenAIEmbeddings
-from langchain.vectorstores import FAISS
-from langchain.chat_models import ChatOpenAI
-from langchain.memory import ConversationBufferMemory
-from langchain.chains import ConversationChain
-from langchain.chains import ConversationalRetrievalChain
-from langchain.document_loaders import UnstructuredFileLoader
-from typing import List, Dict, Tuple
-import gradio as gr
-import validators
-import requests
-import mimetypes
-import tempfile
-import os
-from langchain.chains.question_answering import load_qa_chain
-from langchain.llms import OpenAI
-from langchain.prompts import PromptTemplate
-from langchain.prompts.prompt import PromptTemplate
-import pandas as pd
-from langchain.agents import create_pandas_dataframe_agent
-from langchain.agents import ZeroShotAgent, Tool, AgentExecutor
-from langchain import OpenAI, LLMChain
-from langchain.agents.agent_types import AgentType
-from langchain.agents import create_csv_agent
-
-class ChatDocumentQA:
-    def __init__(self) -> None:
-        pass
-
-    def _get_empty_state(self) -> Dict[str, None]:
-        """Create an empty knowledge base."""
-        return {"knowledge_base": None}
-
-    def _extract_text_from_pdfs(self, file_paths: List[str]) -> List[str]:
-        """Extract text content from PDF files.
-
-        Args:
-            file_paths (List[str]): List of file paths.
-
-        Returns:
-            List[str]: Extracted text from the PDFs.
-        """
-        docs = []
-        loaders = [UnstructuredFileLoader(file_obj, strategy="fast") for file_obj in file_paths]
-        for loader in loaders:
-            docs.extend(loader.load())
-        return docs
-
-    def _get_content_from_url(self, urls: str) -> List[str]:
-        """Fetch content from given URLs.
-
-        Args:
-            urls (str): Comma-separated URLs.
-
-        Returns:
-            List[str]: List of text content fetched from the URLs.
-        """
-        file_paths = []
-        for url in urls.split(','):
-            if validators.url(url):
-                headers = {'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36',}
-                r = requests.get(url, headers=headers)
-                if r.status_code != 200:
-                    raise ValueError("Check the url of your file; returned status code %s" % r.status_code)
-                content_type = r.headers.get("content-type")
-                file_extension = mimetypes.guess_extension(content_type)
-                temp_file = tempfile.NamedTemporaryFile(suffix=file_extension, delete=False)
-                temp_file.write(r.content)
-                file_paths.append(temp_file.name)
-
-        docs = self._extract_text_from_pdfs(file_paths)
-        return docs
-
-    def _split_text_into_chunks(self, text: str) -> List[str]:
-        """Split text into smaller chunks.
-
-        Args:
-            text (str): Input text to be split.
-
-        Returns:
-            List[str]: List of smaller text chunks.
-        """
-        text_splitter = CharacterTextSplitter(separator="\n", chunk_size=500, chunk_overlap=100, length_function=len)
-
-        chunks = text_splitter.split_documents(text)
-
-        return chunks
-    def _create_vector_store_from_text_chunks(self, text_chunks: List[str]) -> FAISS:
-        """Create a vector store from text chunks.
-
-        Args:
-            text_chunks (List[str]): List of text chunks.
-
-        Returns:
-            FAISS: Vector store created from the text chunks.
-        """
-        embeddings = OpenAIEmbeddings()
-
-        return FAISS.from_documents(documents=text_chunks, embedding=embeddings)
-
-
-    def _create_conversation_chain(self,vectorstore):
-
-        _template = """Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question, in its original language.
-
-        Chat History:  {chat_history}
-        Follow Up Input: {question}
-        Standalone question:"""
-        CONDENSE_QUESTION_PROMPT = PromptTemplate.from_template(_template)
-
-        memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
-
-        # llm = ChatOpenAI(temperature=0)
-        llm=OpenAI(temperature=0)
-        return ConversationalRetrievalChain.from_llm(llm=llm, retriever=vectorstore.as_retriever(),
-                                                     condense_question_prompt=CONDENSE_QUESTION_PROMPT,
-                                                     memory=memory)
-
-    def _get_documents_knowledge_base(self, file_paths: List[str]) -> Tuple[str, Dict[str, FAISS]]:
-        """Build knowledge base from uploaded files.
-
-        Args:
-            file_paths (List[str]): List of file paths.
-
-        Returns:
-            Tuple[str, Dict]: Tuple containing a status message and the knowledge base.
-        """
-        file_path = file_paths[0].name
-        file_extension = os.path.splitext(file_path)[1]
-
-        if file_extension == '.pdf':
-            pdf_docs = [file_path.name for file_path in file_paths]
-            raw_text = self._extract_text_from_pdfs(pdf_docs)
-            text_chunks = self._split_text_into_chunks(raw_text)
-            vectorstore = self._create_vector_store_from_text_chunks(text_chunks)
-            return "file uploaded", {"knowledge_base": vectorstore}
-        elif file_extension == '.csv':  
-            # df = pd.read_csv(file_path)
-            # pd_agent = create_pandas_dataframe_agent(OpenAI(temperature=0), df, verbose=True)
-            # tools = self.get_agent_tools(pd_agent)
-            # memory,tools,prompt = self.create_memory_for_csv_qa(tools)
-            # agent_chain = self.create_agent_chain_for_csv_qa(memory,tools,prompt)
-            agent_chain = create_csv_agent(
-                          OpenAI(temperature=0),
-                          file_path,
-                          verbose=True,
-                          agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
-            )            
-            return "file uploaded", {"knowledge_base": agent_chain}
-            
-        else:
-            return "file uploaded", ""
-
-    def _get_urls_knowledge_base(self, urls: str) -> Tuple[str, Dict[str, FAISS]]:
-        """Build knowledge base from URLs.
-
-        Args:
-            urls (str): Comma-separated URLs.
-
-        Returns:
-            Tuple[str, Dict]: Tuple containing a status message and the knowledge base.
-        """
-        webpage_text = self._get_content_from_url(urls)
-        text_chunks = self._split_text_into_chunks(webpage_text)
-        vectorstore = self._create_vector_store_from_text_chunks(text_chunks)
-        return "file uploaded", {"knowledge_base": vectorstore}
-
-#************************
-#   csv qa
-#************************
-    def get_agent_tools(self,agent):
-      # search = agent
-      tools = [
-        Tool(
-            name="dataframe qa",
-            func=agent.run,
-            description="useful for when you need to answer questions about table data and dataframe data",
-        )
-      ]
-      return tools
-
-    def create_memory_for_csv_qa(self,tools):
-      prefix = """Have a conversation with a human, answering the following questions about table data and dataframe data as best you can. You have access to the following tools:"""
-      suffix = """Begin!"
-
-      {chat_history}
-      Question: {input}
-      {agent_scratchpad}"""
-
-      prompt = ZeroShotAgent.create_prompt(
-        tools,
-        prefix=prefix,
-        suffix=suffix,
-        input_variables=["input", "chat_history", "agent_scratchpad"],
-      )
-      memory = ConversationBufferMemory(memory_key="chat_history",return_messages=True)
-
-      return memory,tools,prompt
-
-    def create_agent_chain_for_csv_qa(self,memory,tools,prompt):
-
-        llm_chain = LLMChain(llm=OpenAI(temperature=0), prompt=prompt)
-        agent = ZeroShotAgent(llm_chain=llm_chain, tools=tools, verbose=True)
-        agent_chain = AgentExecutor.from_agent_and_tools(
-            agent=agent, tools=tools, verbose=True, memory=memory
-        )
-
-        return agent_chain
-
-    def _get_response(self, message: str, chat_history: List[Tuple[str, str]], state: Dict[str, FAISS],file_paths) -> Tuple[str, List[Tuple[str, str]]]:
-        """Get a response from the chatbot.
-
-        Args:
-            message (str): User's message/question.
-            chat_history (List[Tuple[str, str]]): List of chat history as tuples of (user_message, bot_response).
-            state (dict): State containing the knowledge base.
-
-        Returns:
-            Tuple[str, List[Tuple[str, str]]]: Tuple containing a status message and updated chat history.
-        """
-        try:
-          if file_paths:
-            file_path = file_paths[0].name
-            file_extension = os.path.splitext(file_path)[1]
-
-            if file_extension == ".pdf":
-                vectorstore = state["knowledge_base"]
-                chat = self._create_conversation_chain(vectorstore)
-                # user_ques = {"question": message}
-                print("chat_history",chat_history)
-                response = chat({"question": message,"chat_history": chat_history})
-                chat_history.append((message, response["answer"]))
-                return "", chat_history
-
-            elif file_extension == '.csv':
-                agent_chain = state["knowledge_base"]
-                response = agent_chain.run(input = message)
-                chat_history.append((message, response))
-                return "", chat_history
-          else:
-              vectorstore = state["knowledge_base"]
-              chat = self._create_conversation_chain(vectorstore)
-              # user_ques = {"question": message}
-              print("chat_history",chat_history)
-              response = chat({"question": message,"chat_history": chat_history})
-              chat_history.append((message, response["answer"]))
-              return "", chat_history
-        except:
-            chat_history.append((message, "Please Upload Document or URL"))
-            return "", chat_history
-
-    def gradio_interface(self) -> None:
-        """Create a Gradio interface for the chatbot."""
-        with gr.Blocks(css="style.css",theme='karthikeyan-adople/hudsonhayes-gray') as demo:
-            gr.HTML("""<center class="darkblue" style='background-color:rgb(0,1,36); text-align:center;padding:25px;'>
-            <center>
-              <h1 class ="center">
-                   <img src="file=logo.png" height="110px" width="280px">
-              </h1>
-            </center>
-            <be>
-            <h1 style="color:#fff">
-               Virtual Assistant Chatbot
-            </h1>
-            </center>""")
-            state = gr.State(self._get_empty_state())
-            chatbot = gr.Chatbot()
-            with gr.Row():
-                with gr.Column(scale=0.85):
-                    msg = gr.Textbox(label="Question")
-                with gr.Column(scale=0.15):
-                    file_output = gr.Textbox(label="File Status")
-            with gr.Row():
-                with gr.Column(scale=0.85):
-                    clear = gr.ClearButton([msg, chatbot])
-                with gr.Column(scale=0.15):
-                    upload_button = gr.UploadButton(
-                        "Browse File",
-                        file_types=[".txt", ".pdf", ".doc", ".docx",".csv"],
-                        file_count="multiple", variant="primary"
-                    )
-                    
-            with gr.Row():
-                with gr.Column(scale=1):
-                    input_url = gr.Textbox(label="urls")
-
-            input_url.submit(self._get_urls_knowledge_base, input_url, [file_output, state])
-            upload_button.upload(self._get_documents_knowledge_base, upload_button, [file_output, state])
-            msg.submit(self._get_response, [msg, chatbot, state,upload_button], [msg, chatbot])
-
-        demo.launch()
-
-if __name__ == "__main__":
-    chatdocumentqa = ChatDocumentQA()
-    chatdocumentqa.gradio_interface()
diff --git a/spaces/huggingchat/chat-ui/src/lib/stores/webSearchParameters.ts b/spaces/huggingchat/chat-ui/src/lib/stores/webSearchParameters.ts
deleted file mode 100644
index fd088a60621090930e9600c6086380afd2b412e8..0000000000000000000000000000000000000000
--- a/spaces/huggingchat/chat-ui/src/lib/stores/webSearchParameters.ts
+++ /dev/null
@@ -1,9 +0,0 @@
-import { writable } from "svelte/store";
-export interface WebSearchParameters {
-	useSearch: boolean;
-	nItems: number;
-}
-export const webSearchParameters = writable<WebSearchParameters>({
-	useSearch: false,
-	nItems: 5,
-});
diff --git a/spaces/huggingface-projects/stable-diffusion-multiplayer/run.py b/spaces/huggingface-projects/stable-diffusion-multiplayer/run.py
deleted file mode 100644
index 49268cdd5158672828979238fbcbe914c9ddb119..0000000000000000000000000000000000000000
--- a/spaces/huggingface-projects/stable-diffusion-multiplayer/run.py
+++ /dev/null
@@ -1,4 +0,0 @@
-import os
-
-os.system("cd stablediffusion-infinity/PyPatchMatch && make")
-os.system("cd stablediffusion-infinity && python app.py")
\ No newline at end of file
diff --git a/spaces/hussain-shk/IndiSent/indic_nlp_library/indicnlp/script/phonetic_sim.py b/spaces/hussain-shk/IndiSent/indic_nlp_library/indicnlp/script/phonetic_sim.py
deleted file mode 100644
index 87f56b63dd38c0f8fd5edf9b6ee5131afd332f31..0000000000000000000000000000000000000000
--- a/spaces/hussain-shk/IndiSent/indic_nlp_library/indicnlp/script/phonetic_sim.py
+++ /dev/null
@@ -1,59 +0,0 @@
-# 
-#  Copyright (c) 2013-present, Anoop Kunchukuttan
-#  All rights reserved.
-#  
-#  This source code is licensed under the MIT license found in the
-#  LICENSE file in the root directory of this source tree.
-# 
-
-from indicnlp import loader
-from indicnlp import langinfo
-from indicnlp.script.indic_scripts import * 
-import numpy as np
-import gzip
-import pandas as pd
-import sys 
-
-def equal(v1,v2): 
-    return 0.0 if  np.sum( xor_vectors(v1, v2)) > 0  else 1.0
-
-def dice(v1,v2):
-    dotprod=2*float(np.dot( v1, v2.T ))
-    return dotprod/float(len(v1)+len(v2))
-
-def jaccard(v1,v2):
-    dotprod=float(np.dot( v1, v2.T ))
-    return dotprod/float(len(v1)+len(v2)-dotprod)
-
-def cosine(v1,v2):
-    dotprod=float(np.dot( v1, v2.T ))
-    norm1=float(np.dot( v1, v1.T ))
-    norm2=float(np.dot( v2, v2.T ))
-    return ((dotprod)/(np.sqrt(norm1*norm2)+0.00001))
-
-def dotprod(v1,v2): 
-    return float(np.dot( v1, v2.T ))
-
-def sim1(v1,v2,base=5.0): 
-    return np.power(base,dotprod(v1,v2)) 
-
-def softmax(v1,v2): 
-    return sim1(v1,v2,np.e)
-
-def create_similarity_matrix(sim_func,slang,tlang,normalize=True):
-
-    dim=langinfo.COORDINATED_RANGE_END_INCLUSIVE-langinfo.COORDINATED_RANGE_START_INCLUSIVE+1    
-    sim_mat=np.zeros((dim,dim))    
-
-    for offset1 in range(langinfo.COORDINATED_RANGE_START_INCLUSIVE, langinfo.COORDINATED_RANGE_END_INCLUSIVE+1): 
-        v1=get_phonetic_feature_vector(offset_to_char(offset1,slang),slang)
-        for offset2 in range(langinfo.COORDINATED_RANGE_START_INCLUSIVE, langinfo.COORDINATED_RANGE_END_INCLUSIVE+1): 
-            v2=get_phonetic_feature_vector(offset_to_char(offset2,tlang),tlang)
-            sim_mat[offset1,offset2]=sim_func(v1,v2)
-
-    if normalize: 
-        sums=np.sum(sim_mat, axis=1)
-        sim_mat=(sim_mat.transpose()/sums).transpose()
-
-    return sim_mat
-
diff --git a/spaces/hussain-shk/IndiSent/subword-nmt/subword_nmt/get_vocab.py b/spaces/hussain-shk/IndiSent/subword-nmt/subword_nmt/get_vocab.py
deleted file mode 100644
index 76eb55904a0bf46c32d140848bda384dad584ca6..0000000000000000000000000000000000000000
--- a/spaces/hussain-shk/IndiSent/subword-nmt/subword_nmt/get_vocab.py
+++ /dev/null
@@ -1,82 +0,0 @@
-#! /usr/bin/env python
-from __future__ import print_function
-
-import os
-import sys
-import inspect
-import warnings
-import argparse
-import codecs
-
-from collections import Counter
-
-# hack for python2/3 compatibility
-from io import open
-argparse.open = open
-
-def create_parser(subparsers=None):
-
-    if subparsers:
-        parser = subparsers.add_parser('get-vocab',
-            formatter_class=argparse.RawDescriptionHelpFormatter,
-            description="Generates vocabulary")
-    else:
-        parser = argparse.ArgumentParser(
-            formatter_class=argparse.RawDescriptionHelpFormatter,
-            description="Generates vocabulary")
-
-    parser.add_argument(
-        '--input', '-i', type=argparse.FileType('r'), default=sys.stdin,
-        metavar='PATH',
-        help="Input file (default: standard input).")
-
-    parser.add_argument(
-        '--output', '-o', type=argparse.FileType('w'), default=sys.stdout,
-        metavar='PATH',
-        help="Output file (default: standard output)")
-
-    return parser
-
-def get_vocab(train_file, vocab_file):
-
-    c = Counter()
-
-    for line in train_file:
-        for word in line.strip('\r\n ').split(' '):
-            if word:
-                c[word] += 1
-
-    for key,f in sorted(c.items(), key=lambda x: x[1], reverse=True):
-        vocab_file.write(key+" "+ str(f) + "\n")
-
-if __name__ == "__main__":
-
-    currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
-    newdir = os.path.join(currentdir, 'subword_nmt')
-    if os.path.isdir(newdir):
-        warnings.simplefilter('default')
-        warnings.warn(
-            "this script's location has moved to {0}. This symbolic link will be removed in a future version. Please point to the new location, or install the package and use the command 'subword-nmt'".format(newdir),
-            DeprecationWarning
-        )
-
-    # python 2/3 compatibility
-    if sys.version_info < (3, 0):
-        sys.stderr = codecs.getwriter('UTF-8')(sys.stderr)
-        sys.stdout = codecs.getwriter('UTF-8')(sys.stdout)
-        sys.stdin = codecs.getreader('UTF-8')(sys.stdin)
-    else:
-        sys.stderr = codecs.getwriter('UTF-8')(sys.stderr.buffer)
-        sys.stdout = codecs.getwriter('UTF-8')(sys.stdout.buffer)
-        sys.stdin = codecs.getreader('UTF-8')(sys.stdin.buffer)
-
-    parser = create_parser()
-    args = parser.parse_args()
-
-    # read/write files as UTF-8
-    if args.input.name != '<stdin>':
-        args.input = codecs.open(args.input.name, encoding='utf-8')
-    if args.output.name != '<stdout>':
-        args.output = codecs.open(args.output.name, 'w', encoding='utf-8')
-
-    get_vocab(args.input, args.output)
\ No newline at end of file
diff --git a/spaces/iakarshu/docformer_for_document_classification/app.py b/spaces/iakarshu/docformer_for_document_classification/app.py
deleted file mode 100644
index 38d174c2423af79eda63f46986a19927198ac103..0000000000000000000000000000000000000000
--- a/spaces/iakarshu/docformer_for_document_classification/app.py
+++ /dev/null
@@ -1,132 +0,0 @@
-# -*- coding: utf-8 -*-
-"""Gradio with DocFormer
-
-Automatically generated by Colaboratory.
-
-Original file is located at
-    https://colab.research.google.com/drive/1_XBurG-8jYF4eJJK5VoCJ2Y1v6RV9iAW
-"""
-
-## Requirements.txt
-import os
-os.system('pip install pyyaml==5.1')
-## install PyTesseract
-os.system('pip install -q pytesseract')
-os.environ["TOKENIZERS_PARALLELISM"] = "false"
-
-## Importing the functions from the DocFormer Repo
-from dataset import create_features
-from modeling import DocFormerEncoder,ResNetFeatureExtractor,DocFormerEmbeddings,LanguageFeatureExtractor
-from transformers import BertTokenizerFast
-from utils import DocFormer
-
-## Hyperparameters
-import torch
-
-seed = 42
-target_size = (500, 384)
-max_len = 128
-
-## Setting some hyperparameters
-
-device = 'cuda' if torch.cuda.is_available() else 'cpu'
-
-config = {
-  "coordinate_size": 96,              ## (768/8), 8 for each of the 8 coordinates of x, y
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "image_feature_pool_shape": [7, 7, 256],
-  "intermediate_ff_size_factor": 4,
-  "max_2d_position_embeddings": 1024,
-  "max_position_embeddings": 128,
-  "max_relative_positions": 8,
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "pad_token_id": 0,
-  "shape_size": 96,
-  "vocab_size": 30522,
-  "layer_norm_eps": 1e-12,
-}
-
-## Defining the tokenizer
-tokenizer = BertTokenizerFast.from_pretrained("bert-base-uncased")
-
-
-
-docformer = DocFormer(config)
-
-# path_to_weights = 'drive/MyDrive/docformer_rvl_checkpoint/docformer_v1.ckpt'
-
-url = 'https://www.kaggleusercontent.com/kf/97691030/eyJhbGciOiJkaXIiLCJlbmMiOiJBMTI4Q0JDLUhTMjU2In0..ztbnfHUlYK1kHw0jKXt1QA.DfJGkOgL9TBiATpTSuKwMoaKfApiVDyncy5kMQb-8FeayksRYddv3tummbzYjPOe9bYuSf1ZSqtcfMY4t1-HenQwnxWZ9HektDmQbcuQaGN7lPwxIzIIjUk3zOkDH6UIcmAeUrPpIbMQ9ZHRIGY9LVAWx1lDctT-9QEfEpdHceS4bNTTrftxi-GBCqd4aLACNz_veXM6YqsplQulb7D9ARZYDOxgpAYl3bDL2-KwduLgCusostp7-uzCTkBeJRQ8LpdmHdRY6FmWcf47vFBcTpG9Qoeml3Sr4EUXEcBKfPKMbDbwIbknoV9TuxGLtKHAu4kyWyRCvLb_20FJ4oZSoQHko0joTeIwOHVPeKpAadT0R3soXGXs7jbcEezdoCz48NFKLU_1lkzeg43ExAgf47iE4_4ErEoi_Hs0deINAY1TunkELGjAO8AuVI4z8fctJgIq_u6rg_-_zcQPDRGqCnoe3M4jtmRWSPFsnOGznezr87jg1bb3hTF1g8RIWWyqmpzUccpMqw27x_ZUkm3UZSQ3Axg7SdqH4XuhtqcujUlH4p51UP7Iv0NlLYMcMpWEFJ630e-kcx8IpKycMVg484Pm8SzI0rTUU6FqA-csBWX1GGAOJwDQR4VYiLTMkd35zNp7byO56uXd5cLXrmcOZdxetrXN8IHAw3GxmlEmi8u-iuZlBwbdWhTx_W3hnwWT.XyPnjS0IQxQ_QlNUd36QVQ/models/epoch=0-step=753.ckpt'
-
-try:
-  docformer.load_from_checkpoint(url)
-except:
-  pass
-
-id2label = ['scientific_report',
- 'resume',
- 'memo',
- 'file_folder',
- 'specification',
- 'news_article',
- 'letter',
- 'form',
- 'budget',
- 'handwritten',
- 'email',
- 'invoice',
- 'presentation',
- 'scientific_publication',
- 'questionnaire',
- 'advertisement']
-
-import gradio as gr
-
-## Taken from LayoutLMV2 space
-
-image = gr.inputs.Image(type="pil")
-label = gr.outputs.Label(num_top_classes=5)
-examples = [['00093726.png'], ['00866042.png']]
-title = "Interactive demo: DocFormer for Image Classification"
-description = "Demo for classifying document images with DocFormer model. To use it, \
-simply upload an image or use the example images below and click 'submit' to let the model predict the 5 most probable Document classes. \
-Results will show up in a few seconds."
-
-def classify_image(image):
-
-  image.save('sample_img.png')
-  final_encoding = create_features(
-            './sample_img.png',
-            tokenizer,
-            add_batch_dim=True,
-            target_size=target_size,
-            max_seq_length=max_len,
-            path_to_save=None,
-            save_to_disk=False,
-            apply_mask_for_mlm=False,
-            extras_for_debugging=False,
-            use_ocr = True
-    )
-
-  keys_to_reshape = ['x_features', 'y_features', 'resized_and_aligned_bounding_boxes']
-  for key in keys_to_reshape:
-      final_encoding[key] = final_encoding[key][:, :max_len]
-
-  from torchvision import transforms
-  # ## Normalization to these mean and std (I have seen some tutorials used this, and also in image reconstruction, so used it)
-  transform = transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
-
-  final_encoding['resized_scaled_img'] = transform(final_encoding['resized_scaled_img'])
-  output = docformer.forward(final_encoding)
-  output = output[0].softmax(axis = -1)
-  
-  final_pred = {}
-  for i, score in enumerate(output):
-      score = output[i]
-      final_pred[id2label[i]] = score.detach().cpu().tolist()
-      
-  return final_pred
-
-gr.Interface(fn=classify_image, inputs=image, outputs=label, title=title, description=description, examples=examples, enable_queue=True).launch(debug=True)
-
diff --git a/spaces/iamstolas/STOLAS/src/components/chat.tsx b/spaces/iamstolas/STOLAS/src/components/chat.tsx
deleted file mode 100644
index a37ab1cc96ca2e6bfd9acbe313a8d946bfd5c3d4..0000000000000000000000000000000000000000
--- a/spaces/iamstolas/STOLAS/src/components/chat.tsx
+++ /dev/null
@@ -1,93 +0,0 @@
-'use client'
-
-import { useCallback, useEffect, useMemo, useState } from 'react'
-import { useAtom } from 'jotai'
-import Image from 'next/image'
-import { cn } from '@/lib/utils'
-import { ChatList } from '@/components/chat-list'
-import { ChatPanel } from '@/components/chat-panel'
-import { WelcomeScreen } from '@/components/welcome-screen'
-import { ChatScrollAnchor } from '@/components/chat-scroll-anchor'
-import { ToneSelector } from './tone-selector'
-import { ChatHeader } from './chat-header'
-import { ChatSuggestions } from './chat-suggestions'
-import { bingConversationStyleAtom } from '@/state'
-import { ButtonScrollToBottom } from '@/components/button-scroll-to-bottom'
-import StopIcon from '@/assets/images/stop.svg'
-import { useBing } from '@/lib/hooks/use-bing'
-import { ChatMessageModel } from '@/lib/bots/bing/types'
-import { ChatNotification } from './chat-notification'
-import { Settings } from './settings'
-import { ChatHistory } from './chat-history'
-
-export type ChatProps = React.ComponentProps<'div'> & { initialMessages?: ChatMessageModel[] }
-
-export default function Chat({ className }: ChatProps) {
-
-  const [bingStyle, setBingStyle] = useAtom(bingConversationStyleAtom)
-  const {
-    messages,
-    sendMessage,
-    resetConversation,
-    stopGenerating,
-    setInput,
-    bot,
-    input,
-    generating,
-    isSpeaking,
-    uploadImage,
-    attachmentList,
-    setAttachmentList,
-  } = useBing()
-
-  useEffect(() => {
-    window.scrollTo({
-      top: document.body.offsetHeight,
-      behavior: 'smooth'
-    })
-  }, [])
-
-  return (
-    <div className="flex flex-1 flex-col">
-      <Settings />
-      <div className={cn('flex-1 pb-16', className)}>
-        <ChatHeader />
-        <WelcomeScreen setInput={setInput} />
-        <ToneSelector type={bingStyle} onChange={setBingStyle} />
-        {messages.length ? (
-          <>
-            <ChatList messages={messages} />
-            <ChatScrollAnchor trackVisibility={generating} />
-            <ChatNotification message={messages.at(-1)} bot={bot} />
-            <ChatSuggestions setInput={setInput} suggestions={messages.at(-1)?.suggestedResponses} />
-
-            {generating ? (
-              <div className="flex h-10 items-center justify-center my-4">
-                <button
-                  onClick={stopGenerating}
-                  className="typing-control-item stop"
-                >
-                  <Image alt="stop" src={StopIcon} width={24} className="mr-1" />
-                  <span>停止响应</span>
-                </button>
-              </div>
-            ) : null}
-          </>
-        ) : null}
-      </div>
-      <ChatPanel
-        className="pt-24 z-10"
-        isSpeaking={isSpeaking}
-        generating={generating}
-        sendMessage={sendMessage}
-        input={input}
-        setInput={setInput}
-        resetConversation={resetConversation}
-        uploadImage={uploadImage}
-        attachmentList={attachmentList}
-        setAttachmentList={setAttachmentList}
-      />
-      <ButtonScrollToBottom />
-    </div>
-  )
-}
diff --git a/spaces/inamXcontru/PoeticTTS/A Man of God Pope John Paul II 2005 DVDRip 19.md b/spaces/inamXcontru/PoeticTTS/A Man of God Pope John Paul II 2005 DVDRip 19.md
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index 1694f40fc414d3a5566272fbd7afee45849f7337..0000000000000000000000000000000000000000
--- a/spaces/inamXcontru/PoeticTTS/A Man of God Pope John Paul II 2005 DVDRip 19.md	
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diff --git a/spaces/innnky/nyaru-svc2.0/text/__init__.py b/spaces/innnky/nyaru-svc2.0/text/__init__.py
deleted file mode 100644
index 4ac41f9025755d8ffd74068af14c6cfc8e5a4173..0000000000000000000000000000000000000000
--- a/spaces/innnky/nyaru-svc2.0/text/__init__.py
+++ /dev/null
@@ -1,54 +0,0 @@
-""" from https://github.com/keithito/tacotron """
-from text import cleaners
-from text.symbols import symbols
-
-
-# Mappings from symbol to numeric ID and vice versa:
-_symbol_to_id = {s: i for i, s in enumerate(symbols)}
-_id_to_symbol = {i: s for i, s in enumerate(symbols)}
-
-
-def text_to_sequence(text, cleaner_names):
-  '''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
-    Args:
-      text: string to convert to a sequence
-      cleaner_names: names of the cleaner functions to run the text through
-    Returns:
-      List of integers corresponding to the symbols in the text
-  '''
-  sequence = []
-
-  clean_text = _clean_text(text, cleaner_names)
-  for symbol in clean_text:
-    symbol_id = _symbol_to_id[symbol]
-    sequence += [symbol_id]
-  return sequence
-
-
-def cleaned_text_to_sequence(cleaned_text):
-  '''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
-    Args:
-      text: string to convert to a sequence
-    Returns:
-      List of integers corresponding to the symbols in the text
-  '''
-  sequence = [_symbol_to_id[symbol] for symbol in cleaned_text]
-  return sequence
-
-
-def sequence_to_text(sequence):
-  '''Converts a sequence of IDs back to a string'''
-  result = ''
-  for symbol_id in sequence:
-    s = _id_to_symbol[symbol_id]
-    result += s
-  return result
-
-
-def _clean_text(text, cleaner_names):
-  for name in cleaner_names:
-    cleaner = getattr(cleaners, name)
-    if not cleaner:
-      raise Exception('Unknown cleaner: %s' % name)
-    text = cleaner(text)
-  return text
diff --git a/spaces/inplisQlawa/anything-midjourney-v4-1/Dear Evan Hansen (TCG Edition) Download Epub Mobi Pdf Fb2 74 HOT.md b/spaces/inplisQlawa/anything-midjourney-v4-1/Dear Evan Hansen (TCG Edition) Download Epub Mobi Pdf Fb2 74 HOT.md
deleted file mode 100644
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diff --git a/spaces/inplisQlawa/anything-midjourney-v4-1/Express Digital Darkroom Pro V8.9 Full Crack.md b/spaces/inplisQlawa/anything-midjourney-v4-1/Express Digital Darkroom Pro V8.9 Full Crack.md
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--- a/spaces/inplisQlawa/anything-midjourney-v4-1/Express Digital Darkroom Pro V8.9 Full Crack.md	
+++ /dev/null
@@ -1,10 +0,0 @@
-
-<p>Analog sensors contain a grid of photosites, one for each pixel, that collects light from the scene and converts it into a signal that can be read by the camera. The number of pixels is stated on the outside of the camera, but can also be found on the inside of the camera. Many digital sensors have a grid of pixels, but instead of reading the full light input from a scene, as in the analog technology, the pixel's circuitry reads only a small light input that is selected for it.</p>
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-<p>The number of pixels that a digital sensor can collect is stated. A <strong>megapixel</strong> (mega = million) can mean any number of pixels. A 1.8 megapixel sensor means that it has 1.8 million pixels, and not 18 million. This is why, even if your camera has a lower resolution display, you can see the image is in pixels, whereas a camera with a higher resolution display (usually 24, 30 or 36 megapixels), it shows you a scale of inches. Once again, megapixel is a measurement in pixels. </p>
-<p>E. Double exposure. Images of the same picture that are taken at different times (1, 2,..., N) may be combined into one single image. You will see this darkroom icon in the photo's explorer window. You can then change the settings for the exposure time, exposure index, shutter speed, ISO, focus, white balance, etc.</p>
-<p>Drag and drop. You will see the darkroom icon when you have dragged and dropped a light box into the Photos library in order to process it. You can also process single or double exposure images in this way.</p>
-<p></p>
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diff --git a/spaces/inplisQlawa/anything-midjourney-v4-1/Generic Text Only Driver Download Windows 7 ((TOP)).md b/spaces/inplisQlawa/anything-midjourney-v4-1/Generic Text Only Driver Download Windows 7 ((TOP)).md
deleted file mode 100644
index 4408e960460dbf051daa00ee9ba9b513340c22b3..0000000000000000000000000000000000000000
--- a/spaces/inplisQlawa/anything-midjourney-v4-1/Generic Text Only Driver Download Windows 7 ((TOP)).md	
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diff --git a/spaces/inreVtussa/clothingai/Examples/Corinda 13 Steps To Mentalism (Complete).pdf ((INSTALL)).md b/spaces/inreVtussa/clothingai/Examples/Corinda 13 Steps To Mentalism (Complete).pdf ((INSTALL)).md
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index 179e0e6b42beafbf72922477e5d72864091f7bdb..0000000000000000000000000000000000000000
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diff --git a/spaces/inreVtussa/clothingai/Examples/Data11 Cab Bully Gratis.rar.md b/spaces/inreVtussa/clothingai/Examples/Data11 Cab Bully Gratis.rar.md
deleted file mode 100644
index 5f45cca947dad8415e29de4933f01c3fbdd46063..0000000000000000000000000000000000000000
--- a/spaces/inreVtussa/clothingai/Examples/Data11 Cab Bully Gratis.rar.md	
+++ /dev/null
@@ -1,21 +0,0 @@
-<br />
-<h1>How to Download and Install Data11 Cab Bully Gratis.rar for Free</h1>
-<p>Data11 Cab Bully Gratis.rar is a file that contains a patch for the game Bully, also known as Canis Canem Edit in some regions. Bully is an action-adventure game developed by Rockstar Vancouver and published by Rockstar Games. It was released on 17 October 2006 for the PlayStation 2 and later on other platforms. The game follows the exploits of James "Jimmy" Hopkins, a rebellious student who is enrolled at Bullworth Academy, a fictional boarding school. Jimmy has to deal with various cliques, teachers, and bullies as he tries to rise through the ranks of the school system.</p>
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-<li>Run the game and enjoy the patch.</li>
-</ol>
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diff --git a/spaces/ismot/1702t1/models/modules/conv_transformer.py b/spaces/ismot/1702t1/models/modules/conv_transformer.py
deleted file mode 100644
index 6fcbfe4acfc2a30e12eafd2ed74a6e7b5d25641d..0000000000000000000000000000000000000000
--- a/spaces/ismot/1702t1/models/modules/conv_transformer.py
+++ /dev/null
@@ -1,128 +0,0 @@
-import torch
-import torch.nn.functional as F
-
-from torch import nn, einsum
-from einops import rearrange
-
-
-class PreNorm(nn.Module):
-    def __init__(self, dim, fn):
-        super().__init__()
-        self.norm = nn.LayerNorm(dim)
-        self.fn = fn
-
-    def forward(self, x, **kwargs):
-        return self.fn(self.norm(x), **kwargs)
-
-
-class GELU(nn.Module):
-    def forward(self, input):
-        return F.gelu(input)
-
-
-class Attend(nn.Module):
-
-    def __init__(self, dim=None):
-        super().__init__()
-        self.dim = dim
-
-    def forward(self, input):
-        return F.softmax(input, dim=self.dim, dtype=input.dtype)
-
-
-class FeedForward(nn.Module):
-    def __init__(self, dim, hidden_dim, dropout=0.):
-        super().__init__()
-        self.net = nn.Sequential(
-            nn.Linear(dim, hidden_dim),
-            GELU(),
-            nn.Dropout(dropout),
-            nn.Linear(hidden_dim, dim),
-            nn.Dropout(dropout)
-        )
-
-    def forward(self, x):
-        return self.net(x)
-
-
-class Attention(nn.Module):
-    def __init__(self, dim, heads=8, dim_head=64, dropout=0.):
-        super().__init__()
-        inner_dim = dim_head * heads
-        project_out = not (heads == 1 and dim_head == dim)
-
-        self.heads = heads
-        self.scale = dim_head ** -0.5
-
-        self.attend = Attend(dim=-1)
-        self.to_qkv = nn.Linear(dim, inner_dim * 3, bias=False)
-
-        self.to_out = nn.Sequential(
-            nn.Linear(inner_dim, dim),
-            nn.Dropout(dropout)
-        ) if project_out else nn.Identity()
-
-    def forward(self, x):
-        b, n, _, h = *x.shape, self.heads
-        qkv = self.to_qkv(x).chunk(3, dim=-1)
-        q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> b h n d', h=h), qkv)
-        dots = einsum('b h i d, b h j d -> b h i j', q, k) * self.scale
-        attn = self.attend(dots)
-        out = einsum('b h i j, b h j d -> b h i d', attn, v)
-        out = rearrange(out, 'b h n d -> b n (h d)')
-        return self.to_out(out)
-
-
-class Conv(nn.Module):
-    def __init__(self, dim, dropout=0.):
-        super().__init__()
-        self.dim = dim
-        self.net = nn.Sequential(
-            nn.Conv1d(dim, dim, kernel_size=3, stride=1, padding=0),
-            nn.Dropout(dropout)
-        )
-
-    def forward(self, x):
-        x = x.transpose(1, 2)
-        x = torch.cat([x[..., -1:], x, x[..., :1]], dim=-1)
-        x = self.net(x)
-        return x.transpose(1, 2)
-
-
-class ConvTransformer(nn.Module):
-    def __init__(self, dim, depth, heads, dim_head, mlp_dim, dropout=0.):
-        super().__init__()
-        self.layers = nn.ModuleList([])
-        for _ in range(depth):
-            self.layers.append(nn.ModuleList([
-                PreNorm(dim, Attention(dim, heads=heads, dim_head=dim_head, dropout=dropout)),
-                PreNorm(dim, FeedForward(dim, mlp_dim, dropout=dropout)),
-                PreNorm(dim, Conv(dim, dropout=dropout))
-            ]))
-
-    def forward(self, x):
-        for attn, ff, cov in self.layers:
-            x = attn(x) + x
-            x = ff(x) + x
-            x = cov(x) + x
-        return x
-
-
-if __name__ == '__main__':
-    token_dim = 1024
-    toke_len = 256
-
-    transformer = ConvTransformer(dim=token_dim,
-                                  depth=6,
-                                  heads=16,
-                                  dim_head=64,
-                                  mlp_dim=2048,
-                                  dropout=0.1)
-
-    total = sum(p.numel() for p in transformer.parameters())
-    trainable = sum(p.numel() for p in transformer.parameters() if p.requires_grad)
-    print('parameter total:{:,}, trainable:{:,}'.format(total, trainable))
-
-    input = torch.randn(1, toke_len, token_dim)
-    output = transformer(input)
-    print(output.shape)
diff --git a/spaces/ismot/8testi1/models/yolo.py b/spaces/ismot/8testi1/models/yolo.py
deleted file mode 100644
index df06a6ba053e663a60574dde22900825ff17e0db..0000000000000000000000000000000000000000
--- a/spaces/ismot/8testi1/models/yolo.py
+++ /dev/null
@@ -1,757 +0,0 @@
-import argparse
-import logging
-import sys
-from copy import deepcopy
-
-sys.path.append("./")  # to run '$ python *.py' files in subdirectories
-logger = logging.getLogger(__name__)
-
-from models.common import *
-from models.experimental import *
-from utils.autoanchor import check_anchor_order
-from utils.general import make_divisible, check_file, set_logging
-from utils.torch_utils import (
-    time_synchronized,
-    fuse_conv_and_bn,
-    model_info,
-    scale_img,
-    initialize_weights,
-    select_device,
-    copy_attr,
-)
-from utils.loss import SigmoidBin
-
-try:
-    import thop  # for FLOPS computation
-except ImportError:
-    thop = None
-
-
-class Detect(nn.Module):
-    stride = None  # strides computed during build
-    export = False  # onnx export
-
-    def __init__(self, nc=80, anchors=(), ch=()):  # detection layer
-        super(Detect, self).__init__()
-        self.nc = nc  # number of classes
-        self.no = nc + 5  # number of outputs per anchor
-        self.nl = len(anchors)  # number of detection layers
-        self.na = len(anchors[0]) // 2  # number of anchors
-        self.grid = [torch.zeros(1)] * self.nl  # init grid
-        a = torch.tensor(anchors).float().view(self.nl, -1, 2)
-        self.register_buffer("anchors", a)  # shape(nl,na,2)
-        self.register_buffer(
-            "anchor_grid", a.clone().view(self.nl, 1, -1, 1, 1, 2)
-        )  # shape(nl,1,na,1,1,2)
-        self.m = nn.ModuleList(
-            nn.Conv2d(x, self.no * self.na, 1) for x in ch
-        )  # output conv
-
-    def forward(self, x):
-        # x = x.copy()  # for profiling
-        z = []  # inference output
-        self.training |= self.export
-        for i in range(self.nl):
-            x[i] = self.m[i](x[i])  # conv
-            bs, _, ny, nx = x[i].shape  # x(bs,255,20,20) to x(bs,3,20,20,85)
-            x[i] = (
-                x[i]
-                .view(bs, self.na, self.no, ny, nx)
-                .permute(0, 1, 3, 4, 2)
-                .contiguous()
-            )
-
-            if not self.training:  # inference
-                if self.grid[i].shape[2:4] != x[i].shape[2:4]:
-                    self.grid[i] = self._make_grid(nx, ny).to(x[i].device)
-
-                y = x[i].sigmoid()
-                y[..., 0:2] = (y[..., 0:2] * 2.0 - 0.5 + self.grid[i]) * self.stride[
-                    i
-                ]  # xy
-                y[..., 2:4] = (y[..., 2:4] * 2) ** 2 * self.anchor_grid[i]  # wh
-                z.append(y.view(bs, -1, self.no))
-
-        return x if self.training else (torch.cat(z, 1), x)
-
-    @staticmethod
-    def _make_grid(nx=20, ny=20):
-        yv, xv = torch.meshgrid([torch.arange(ny), torch.arange(nx)])
-        return torch.stack((xv, yv), 2).view((1, 1, ny, nx, 2)).float()
-
-
-class IDetect(nn.Module):
-    stride = None  # strides computed during build
-    export = False  # onnx export
-
-    def __init__(self, nc=80, anchors=(), ch=()):  # detection layer
-        super(IDetect, self).__init__()
-        self.nc = nc  # number of classes
-        self.no = nc + 5  # number of outputs per anchor
-        self.nl = len(anchors)  # number of detection layers
-        self.na = len(anchors[0]) // 2  # number of anchors
-        self.grid = [torch.zeros(1)] * self.nl  # init grid
-        a = torch.tensor(anchors).float().view(self.nl, -1, 2)
-        self.register_buffer("anchors", a)  # shape(nl,na,2)
-        self.register_buffer(
-            "anchor_grid", a.clone().view(self.nl, 1, -1, 1, 1, 2)
-        )  # shape(nl,1,na,1,1,2)
-        self.m = nn.ModuleList(
-            nn.Conv2d(x, self.no * self.na, 1) for x in ch
-        )  # output conv
-
-        self.ia = nn.ModuleList(ImplicitA(x) for x in ch)
-        self.im = nn.ModuleList(ImplicitM(self.no * self.na) for _ in ch)
-
-    def forward(self, x):
-        # x = x.copy()  # for profiling
-        z = []  # inference output
-        self.training |= self.export
-        for i in range(self.nl):
-            x[i] = self.m[i](self.ia[i](x[i]))  # conv
-            x[i] = self.im[i](x[i])
-            bs, _, ny, nx = x[i].shape  # x(bs,255,20,20) to x(bs,3,20,20,85)
-            x[i] = (
-                x[i]
-                .view(bs, self.na, self.no, ny, nx)
-                .permute(0, 1, 3, 4, 2)
-                .contiguous()
-            )
-
-            if not self.training:  # inference
-                if self.grid[i].shape[2:4] != x[i].shape[2:4]:
-                    self.grid[i] = self._make_grid(nx, ny).to(x[i].device)
-
-                y = x[i].sigmoid()
-                y[..., 0:2] = (y[..., 0:2] * 2.0 - 0.5 + self.grid[i]) * self.stride[
-                    i
-                ]  # xy
-                y[..., 2:4] = (y[..., 2:4] * 2) ** 2 * self.anchor_grid[i]  # wh
-                z.append(y.view(bs, -1, self.no))
-
-        return x if self.training else (torch.cat(z, 1), x)
-
-    @staticmethod
-    def _make_grid(nx=20, ny=20):
-        yv, xv = torch.meshgrid([torch.arange(ny), torch.arange(nx)])
-        return torch.stack((xv, yv), 2).view((1, 1, ny, nx, 2)).float()
-
-
-class IAuxDetect(nn.Module):
-    stride = None  # strides computed during build
-    export = False  # onnx export
-
-    def __init__(self, nc=80, anchors=(), ch=()):  # detection layer
-        super(IAuxDetect, self).__init__()
-        self.nc = nc  # number of classes
-        self.no = nc + 5  # number of outputs per anchor
-        self.nl = len(anchors)  # number of detection layers
-        self.na = len(anchors[0]) // 2  # number of anchors
-        self.grid = [torch.zeros(1)] * self.nl  # init grid
-        a = torch.tensor(anchors).float().view(self.nl, -1, 2)
-        self.register_buffer("anchors", a)  # shape(nl,na,2)
-        self.register_buffer(
-            "anchor_grid", a.clone().view(self.nl, 1, -1, 1, 1, 2)
-        )  # shape(nl,1,na,1,1,2)
-        self.m = nn.ModuleList(
-            nn.Conv2d(x, self.no * self.na, 1) for x in ch[: self.nl]
-        )  # output conv
-        self.m2 = nn.ModuleList(
-            nn.Conv2d(x, self.no * self.na, 1) for x in ch[self.nl :]
-        )  # output conv
-
-        self.ia = nn.ModuleList(ImplicitA(x) for x in ch[: self.nl])
-        self.im = nn.ModuleList(ImplicitM(self.no * self.na) for _ in ch[: self.nl])
-
-    def forward(self, x):
-        # x = x.copy()  # for profiling
-        z = []  # inference output
-        self.training |= self.export
-        for i in range(self.nl):
-            x[i] = self.m[i](self.ia[i](x[i]))  # conv
-            x[i] = self.im[i](x[i])
-            bs, _, ny, nx = x[i].shape  # x(bs,255,20,20) to x(bs,3,20,20,85)
-            x[i] = (
-                x[i]
-                .view(bs, self.na, self.no, ny, nx)
-                .permute(0, 1, 3, 4, 2)
-                .contiguous()
-            )
-
-            x[i + self.nl] = self.m2[i](x[i + self.nl])
-            x[i + self.nl] = (
-                x[i + self.nl]
-                .view(bs, self.na, self.no, ny, nx)
-                .permute(0, 1, 3, 4, 2)
-                .contiguous()
-            )
-
-            if not self.training:  # inference
-                if self.grid[i].shape[2:4] != x[i].shape[2:4]:
-                    self.grid[i] = self._make_grid(nx, ny).to(x[i].device)
-
-                y = x[i].sigmoid()
-                y[..., 0:2] = (y[..., 0:2] * 2.0 - 0.5 + self.grid[i]) * self.stride[
-                    i
-                ]  # xy
-                y[..., 2:4] = (y[..., 2:4] * 2) ** 2 * self.anchor_grid[i]  # wh
-                z.append(y.view(bs, -1, self.no))
-
-        return x if self.training else (torch.cat(z, 1), x[: self.nl])
-
-    @staticmethod
-    def _make_grid(nx=20, ny=20):
-        yv, xv = torch.meshgrid([torch.arange(ny), torch.arange(nx)])
-        return torch.stack((xv, yv), 2).view((1, 1, ny, nx, 2)).float()
-
-
-class IBin(nn.Module):
-    stride = None  # strides computed during build
-    export = False  # onnx export
-
-    def __init__(self, nc=80, anchors=(), ch=(), bin_count=21):  # detection layer
-        super(IBin, self).__init__()
-        self.nc = nc  # number of classes
-        self.bin_count = bin_count
-
-        self.w_bin_sigmoid = SigmoidBin(bin_count=self.bin_count, min=0.0, max=4.0)
-        self.h_bin_sigmoid = SigmoidBin(bin_count=self.bin_count, min=0.0, max=4.0)
-        # classes, x,y,obj
-        self.no = (
-            nc + 3 + self.w_bin_sigmoid.get_length() + self.h_bin_sigmoid.get_length()
-        )  # w-bce, h-bce
-        # + self.x_bin_sigmoid.get_length() + self.y_bin_sigmoid.get_length()
-
-        self.nl = len(anchors)  # number of detection layers
-        self.na = len(anchors[0]) // 2  # number of anchors
-        self.grid = [torch.zeros(1)] * self.nl  # init grid
-        a = torch.tensor(anchors).float().view(self.nl, -1, 2)
-        self.register_buffer("anchors", a)  # shape(nl,na,2)
-        self.register_buffer(
-            "anchor_grid", a.clone().view(self.nl, 1, -1, 1, 1, 2)
-        )  # shape(nl,1,na,1,1,2)
-        self.m = nn.ModuleList(
-            nn.Conv2d(x, self.no * self.na, 1) for x in ch
-        )  # output conv
-
-        self.ia = nn.ModuleList(ImplicitA(x) for x in ch)
-        self.im = nn.ModuleList(ImplicitM(self.no * self.na) for _ in ch)
-
-    def forward(self, x):
-
-        # self.x_bin_sigmoid.use_fw_regression = True
-        # self.y_bin_sigmoid.use_fw_regression = True
-        self.w_bin_sigmoid.use_fw_regression = True
-        self.h_bin_sigmoid.use_fw_regression = True
-
-        # x = x.copy()  # for profiling
-        z = []  # inference output
-        self.training |= self.export
-        for i in range(self.nl):
-            x[i] = self.m[i](self.ia[i](x[i]))  # conv
-            x[i] = self.im[i](x[i])
-            bs, _, ny, nx = x[i].shape  # x(bs,255,20,20) to x(bs,3,20,20,85)
-            x[i] = (
-                x[i]
-                .view(bs, self.na, self.no, ny, nx)
-                .permute(0, 1, 3, 4, 2)
-                .contiguous()
-            )
-
-            if not self.training:  # inference
-                if self.grid[i].shape[2:4] != x[i].shape[2:4]:
-                    self.grid[i] = self._make_grid(nx, ny).to(x[i].device)
-
-                y = x[i].sigmoid()
-                y[..., 0:2] = (y[..., 0:2] * 2.0 - 0.5 + self.grid[i]) * self.stride[
-                    i
-                ]  # xy
-                # y[..., 2:4] = (y[..., 2:4] * 2) ** 2 * self.anchor_grid[i]  # wh
-
-                # px = (self.x_bin_sigmoid.forward(y[..., 0:12]) + self.grid[i][..., 0]) * self.stride[i]
-                # py = (self.y_bin_sigmoid.forward(y[..., 12:24]) + self.grid[i][..., 1]) * self.stride[i]
-
-                pw = (
-                    self.w_bin_sigmoid.forward(y[..., 2:24])
-                    * self.anchor_grid[i][..., 0]
-                )
-                ph = (
-                    self.h_bin_sigmoid.forward(y[..., 24:46])
-                    * self.anchor_grid[i][..., 1]
-                )
-
-                # y[..., 0] = px
-                # y[..., 1] = py
-                y[..., 2] = pw
-                y[..., 3] = ph
-
-                y = torch.cat((y[..., 0:4], y[..., 46:]), dim=-1)
-
-                z.append(y.view(bs, -1, y.shape[-1]))
-
-        return x if self.training else (torch.cat(z, 1), x)
-
-    @staticmethod
-    def _make_grid(nx=20, ny=20):
-        yv, xv = torch.meshgrid([torch.arange(ny), torch.arange(nx)])
-        return torch.stack((xv, yv), 2).view((1, 1, ny, nx, 2)).float()
-
-
-class Model(nn.Module):
-    def __init__(
-        self, cfg="yolor-csp-c.yaml", ch=3, nc=None, anchors=None
-    ):  # model, input channels, number of classes
-        super(Model, self).__init__()
-        self.traced = False
-        if isinstance(cfg, dict):
-            self.yaml = cfg  # model dict
-        else:  # is *.yaml
-            import yaml  # for torch hub
-
-            self.yaml_file = Path(cfg).name
-            with open(cfg) as f:
-                self.yaml = yaml.load(f, Loader=yaml.SafeLoader)  # model dict
-
-        # Define model
-        ch = self.yaml["ch"] = self.yaml.get("ch", ch)  # input channels
-        if nc and nc != self.yaml["nc"]:
-            logger.info(f"Overriding model.yaml nc={self.yaml['nc']} with nc={nc}")
-            self.yaml["nc"] = nc  # override yaml value
-        if anchors:
-            logger.info(f"Overriding model.yaml anchors with anchors={anchors}")
-            self.yaml["anchors"] = round(anchors)  # override yaml value
-        self.model, self.save = parse_model(
-            deepcopy(self.yaml), ch=[ch]
-        )  # model, savelist
-        self.names = [str(i) for i in range(self.yaml["nc"])]  # default names
-        # print([x.shape for x in self.forward(torch.zeros(1, ch, 64, 64))])
-
-        # Build strides, anchors
-        m = self.model[-1]  # Detect()
-        if isinstance(m, Detect):
-            s = 256  # 2x min stride
-            m.stride = torch.tensor(
-                [s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))]
-            )  # forward
-            m.anchors /= m.stride.view(-1, 1, 1)
-            check_anchor_order(m)
-            self.stride = m.stride
-            self._initialize_biases()  # only run once
-            # print('Strides: %s' % m.stride.tolist())
-        if isinstance(m, IDetect):
-            s = 256  # 2x min stride
-            m.stride = torch.tensor(
-                [s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))]
-            )  # forward
-            m.anchors /= m.stride.view(-1, 1, 1)
-            check_anchor_order(m)
-            self.stride = m.stride
-            self._initialize_biases()  # only run once
-            # print('Strides: %s' % m.stride.tolist())
-        if isinstance(m, IAuxDetect):
-            s = 256  # 2x min stride
-            m.stride = torch.tensor(
-                [s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))[:4]]
-            )  # forward
-            # print(m.stride)
-            m.anchors /= m.stride.view(-1, 1, 1)
-            check_anchor_order(m)
-            self.stride = m.stride
-            self._initialize_aux_biases()  # only run once
-            # print('Strides: %s' % m.stride.tolist())
-        if isinstance(m, IBin):
-            s = 256  # 2x min stride
-            m.stride = torch.tensor(
-                [s / x.shape[-2] for x in self.forward(torch.zeros(1, ch, s, s))]
-            )  # forward
-            m.anchors /= m.stride.view(-1, 1, 1)
-            check_anchor_order(m)
-            self.stride = m.stride
-            self._initialize_biases_bin()  # only run once
-            # print('Strides: %s' % m.stride.tolist())
-
-        # Init weights, biases
-        initialize_weights(self)
-        self.info()
-        logger.info("")
-
-    def forward(self, x, augment=False, profile=False):
-        if augment:
-            img_size = x.shape[-2:]  # height, width
-            s = [1, 0.83, 0.67]  # scales
-            f = [None, 3, None]  # flips (2-ud, 3-lr)
-            y = []  # outputs
-            for si, fi in zip(s, f):
-                xi = scale_img(x.flip(fi) if fi else x, si, gs=int(self.stride.max()))
-                yi = self.forward_once(xi)[0]  # forward
-                # cv2.imwrite(f'img_{si}.jpg', 255 * xi[0].cpu().numpy().transpose((1, 2, 0))[:, :, ::-1])  # save
-                yi[..., :4] /= si  # de-scale
-                if fi == 2:
-                    yi[..., 1] = img_size[0] - yi[..., 1]  # de-flip ud
-                elif fi == 3:
-                    yi[..., 0] = img_size[1] - yi[..., 0]  # de-flip lr
-                y.append(yi)
-            return torch.cat(y, 1), None  # augmented inference, train
-        else:
-            return self.forward_once(x, profile)  # single-scale inference, train
-
-    def forward_once(self, x, profile=False):
-        y, dt = [], []  # outputs
-        for m in self.model:
-            if m.f != -1:  # if not from previous layer
-                x = (
-                    y[m.f]
-                    if isinstance(m.f, int)
-                    else [x if j == -1 else y[j] for j in m.f]
-                )  # from earlier layers
-
-            if not hasattr(self, "traced"):
-                self.traced = False
-
-            if self.traced:
-                if (
-                    isinstance(m, Detect)
-                    or isinstance(m, IDetect)
-                    or isinstance(m, IAuxDetect)
-                ):
-                    break
-
-            if profile:
-                c = isinstance(m, (Detect, IDetect, IAuxDetect, IBin))
-                o = (
-                    thop.profile(m, inputs=(x.copy() if c else x,), verbose=False)[0]
-                    / 1e9
-                    * 2
-                    if thop
-                    else 0
-                )  # FLOPS
-                for _ in range(10):
-                    m(x.copy() if c else x)
-                t = time_synchronized()
-                for _ in range(10):
-                    m(x.copy() if c else x)
-                dt.append((time_synchronized() - t) * 100)
-                print("%10.1f%10.0f%10.1fms %-40s" % (o, m.np, dt[-1], m.type))
-
-            x = m(x)  # run
-
-            y.append(x if m.i in self.save else None)  # save output
-
-        if profile:
-            print("%.1fms total" % sum(dt))
-        return x
-
-    def _initialize_biases(
-        self, cf=None
-    ):  # initialize biases into Detect(), cf is class frequency
-        # https://arxiv.org/abs/1708.02002 section 3.3
-        # cf = torch.bincount(torch.tensor(np.concatenate(dataset.labels, 0)[:, 0]).long(), minlength=nc) + 1.
-        m = self.model[-1]  # Detect() module
-        for mi, s in zip(m.m, m.stride):  # from
-            b = mi.bias.view(m.na, -1)  # conv.bias(255) to (3,85)
-            b.data[:, 4] += math.log(
-                8 / (640 / s) ** 2
-            )  # obj (8 objects per 640 image)
-            b.data[:, 5:] += (
-                math.log(0.6 / (m.nc - 0.99))
-                if cf is None
-                else torch.log(cf / cf.sum())
-            )  # cls
-            mi.bias = torch.nn.Parameter(b.view(-1), requires_grad=True)
-
-    def _initialize_aux_biases(
-        self, cf=None
-    ):  # initialize biases into Detect(), cf is class frequency
-        # https://arxiv.org/abs/1708.02002 section 3.3
-        # cf = torch.bincount(torch.tensor(np.concatenate(dataset.labels, 0)[:, 0]).long(), minlength=nc) + 1.
-        m = self.model[-1]  # Detect() module
-        for mi, mi2, s in zip(m.m, m.m2, m.stride):  # from
-            b = mi.bias.view(m.na, -1)  # conv.bias(255) to (3,85)
-            b.data[:, 4] += math.log(
-                8 / (640 / s) ** 2
-            )  # obj (8 objects per 640 image)
-            b.data[:, 5:] += (
-                math.log(0.6 / (m.nc - 0.99))
-                if cf is None
-                else torch.log(cf / cf.sum())
-            )  # cls
-            mi.bias = torch.nn.Parameter(b.view(-1), requires_grad=True)
-            b2 = mi2.bias.view(m.na, -1)  # conv.bias(255) to (3,85)
-            b2.data[:, 4] += math.log(
-                8 / (640 / s) ** 2
-            )  # obj (8 objects per 640 image)
-            b2.data[:, 5:] += (
-                math.log(0.6 / (m.nc - 0.99))
-                if cf is None
-                else torch.log(cf / cf.sum())
-            )  # cls
-            mi2.bias = torch.nn.Parameter(b2.view(-1), requires_grad=True)
-
-    def _initialize_biases_bin(
-        self, cf=None
-    ):  # initialize biases into Detect(), cf is class frequency
-        # https://arxiv.org/abs/1708.02002 section 3.3
-        # cf = torch.bincount(torch.tensor(np.concatenate(dataset.labels, 0)[:, 0]).long(), minlength=nc) + 1.
-        m = self.model[-1]  # Bin() module
-        bc = m.bin_count
-        for mi, s in zip(m.m, m.stride):  # from
-            b = mi.bias.view(m.na, -1)  # conv.bias(255) to (3,85)
-            old = b[:, (0, 1, 2, bc + 3)].data
-            obj_idx = 2 * bc + 4
-            b[:, :obj_idx].data += math.log(0.6 / (bc + 1 - 0.99))
-            b[:, obj_idx].data += math.log(
-                8 / (640 / s) ** 2
-            )  # obj (8 objects per 640 image)
-            b[:, (obj_idx + 1) :].data += (
-                math.log(0.6 / (m.nc - 0.99))
-                if cf is None
-                else torch.log(cf / cf.sum())
-            )  # cls
-            b[:, (0, 1, 2, bc + 3)].data = old
-            mi.bias = torch.nn.Parameter(b.view(-1), requires_grad=True)
-
-    def _print_biases(self):
-        m = self.model[-1]  # Detect() module
-        for mi in m.m:  # from
-            b = mi.bias.detach().view(m.na, -1).T  # conv.bias(255) to (3,85)
-            print(
-                ("%6g Conv2d.bias:" + "%10.3g" * 6)
-                % (mi.weight.shape[1], *b[:5].mean(1).tolist(), b[5:].mean())
-            )
-
-    # def _print_weights(self):
-    #     for m in self.model.modules():
-    #         if type(m) is Bottleneck:
-    #             print('%10.3g' % (m.w.detach().sigmoid() * 2))  # shortcut weights
-
-    def fuse(self):  # fuse model Conv2d() + BatchNorm2d() layers
-        print("Fusing layers... ")
-        for m in self.model.modules():
-            if isinstance(m, RepConv):
-                # print(f" fuse_repvgg_block")
-                m.fuse_repvgg_block()
-            elif isinstance(m, RepConv_OREPA):
-                # print(f" switch_to_deploy")
-                m.switch_to_deploy()
-            elif type(m) is Conv and hasattr(m, "bn"):
-                m.conv = fuse_conv_and_bn(m.conv, m.bn)  # update conv
-                delattr(m, "bn")  # remove batchnorm
-                m.forward = m.fuseforward  # update forward
-        self.info()
-        return self
-
-    def nms(self, mode=True):  # add or remove NMS module
-        present = type(self.model[-1]) is NMS  # last layer is NMS
-        if mode and not present:
-            print("Adding NMS... ")
-            m = NMS()  # module
-            m.f = -1  # from
-            m.i = self.model[-1].i + 1  # index
-            self.model.add_module(name="%s" % m.i, module=m)  # add
-            self.eval()
-        elif not mode and present:
-            print("Removing NMS... ")
-            self.model = self.model[:-1]  # remove
-        return self
-
-    def autoshape(self):  # add autoShape module
-        print("Adding autoShape... ")
-        m = autoShape(self)  # wrap model
-        copy_attr(
-            m, self, include=("yaml", "nc", "hyp", "names", "stride"), exclude=()
-        )  # copy attributes
-        return m
-
-    def info(self, verbose=False, img_size=640):  # print model information
-        model_info(self, verbose, img_size)
-
-
-def parse_model(d, ch):  # model_dict, input_channels(3)
-    logger.info(
-        "\n%3s%18s%3s%10s  %-40s%-30s"
-        % ("", "from", "n", "params", "module", "arguments")
-    )
-    anchors, nc, gd, gw = (
-        d["anchors"],
-        d["nc"],
-        d["depth_multiple"],
-        d["width_multiple"],
-    )
-    na = (
-        (len(anchors[0]) // 2) if isinstance(anchors, list) else anchors
-    )  # number of anchors
-    no = na * (nc + 5)  # number of outputs = anchors * (classes + 5)
-
-    layers, save, c2 = [], [], ch[-1]  # layers, savelist, ch out
-    for i, (f, n, m, args) in enumerate(
-        d["backbone"] + d["head"]
-    ):  # from, number, module, args
-        m = eval(m) if isinstance(m, str) else m  # eval strings
-        for j, a in enumerate(args):
-            try:
-                args[j] = eval(a) if isinstance(a, str) else a  # eval strings
-            except:
-                pass
-
-        n = max(round(n * gd), 1) if n > 1 else n  # depth gain
-        if m in [
-            nn.Conv2d,
-            Conv,
-            RobustConv,
-            RobustConv2,
-            DWConv,
-            GhostConv,
-            RepConv,
-            RepConv_OREPA,
-            DownC,
-            SPP,
-            SPPF,
-            SPPCSPC,
-            GhostSPPCSPC,
-            MixConv2d,
-            Focus,
-            Stem,
-            GhostStem,
-            CrossConv,
-            Bottleneck,
-            BottleneckCSPA,
-            BottleneckCSPB,
-            BottleneckCSPC,
-            RepBottleneck,
-            RepBottleneckCSPA,
-            RepBottleneckCSPB,
-            RepBottleneckCSPC,
-            Res,
-            ResCSPA,
-            ResCSPB,
-            ResCSPC,
-            RepRes,
-            RepResCSPA,
-            RepResCSPB,
-            RepResCSPC,
-            ResX,
-            ResXCSPA,
-            ResXCSPB,
-            ResXCSPC,
-            RepResX,
-            RepResXCSPA,
-            RepResXCSPB,
-            RepResXCSPC,
-            Ghost,
-            GhostCSPA,
-            GhostCSPB,
-            GhostCSPC,
-            SwinTransformerBlock,
-            STCSPA,
-            STCSPB,
-            STCSPC,
-            SwinTransformer2Block,
-            ST2CSPA,
-            ST2CSPB,
-            ST2CSPC,
-        ]:
-            c1, c2 = ch[f], args[0]
-            if c2 != no:  # if not output
-                c2 = make_divisible(c2 * gw, 8)
-
-            args = [c1, c2, *args[1:]]
-            if m in [
-                DownC,
-                SPPCSPC,
-                GhostSPPCSPC,
-                BottleneckCSPA,
-                BottleneckCSPB,
-                BottleneckCSPC,
-                RepBottleneckCSPA,
-                RepBottleneckCSPB,
-                RepBottleneckCSPC,
-                ResCSPA,
-                ResCSPB,
-                ResCSPC,
-                RepResCSPA,
-                RepResCSPB,
-                RepResCSPC,
-                ResXCSPA,
-                ResXCSPB,
-                ResXCSPC,
-                RepResXCSPA,
-                RepResXCSPB,
-                RepResXCSPC,
-                GhostCSPA,
-                GhostCSPB,
-                GhostCSPC,
-                STCSPA,
-                STCSPB,
-                STCSPC,
-                ST2CSPA,
-                ST2CSPB,
-                ST2CSPC,
-            ]:
-                args.insert(2, n)  # number of repeats
-                n = 1
-        elif m is nn.BatchNorm2d:
-            args = [ch[f]]
-        elif m is Concat:
-            c2 = sum([ch[x] for x in f])
-        elif m is Chuncat:
-            c2 = sum([ch[x] for x in f])
-        elif m is Shortcut:
-            c2 = ch[f[0]]
-        elif m is Foldcut:
-            c2 = ch[f] // 2
-        elif m in [Detect, IDetect, IAuxDetect, IBin]:
-            args.append([ch[x] for x in f])
-            if isinstance(args[1], int):  # number of anchors
-                args[1] = [list(range(args[1] * 2))] * len(f)
-        elif m is ReOrg:
-            c2 = ch[f] * 4
-        elif m is Contract:
-            c2 = ch[f] * args[0] ** 2
-        elif m is Expand:
-            c2 = ch[f] // args[0] ** 2
-        else:
-            c2 = ch[f]
-
-        m_ = (
-            nn.Sequential(*[m(*args) for _ in range(n)]) if n > 1 else m(*args)
-        )  # module
-        t = str(m)[8:-2].replace("__main__.", "")  # module type
-        np = sum([x.numel() for x in m_.parameters()])  # number params
-        m_.i, m_.f, m_.type, m_.np = (
-            i,
-            f,
-            t,
-            np,
-        )  # attach index, 'from' index, type, number params
-        logger.info("%3s%18s%3s%10.0f  %-40s%-30s" % (i, f, n, np, t, args))  # print
-        save.extend(
-            x % i for x in ([f] if isinstance(f, int) else f) if x != -1
-        )  # append to savelist
-        layers.append(m_)
-        if i == 0:
-            ch = []
-        ch.append(c2)
-    return nn.Sequential(*layers), sorted(save)
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument(
-        "--cfg", type=str, default="yolor-csp-c.yaml", help="model.yaml"
-    )
-    parser.add_argument(
-        "--device", default="", help="cuda device, i.e. 0 or 0,1,2,3 or cpu"
-    )
-    parser.add_argument("--profile", action="store_true", help="profile model speed")
-    opt = parser.parse_args()
-    opt.cfg = check_file(opt.cfg)  # check file
-    set_logging()
-    device = select_device(opt.device)
-
-    # Create model
-    model = Model(opt.cfg).to(device)
-    model.train()
-
-    if opt.profile:
-        img = torch.rand(1, 3, 640, 640).to(device)
-        y = model(img, profile=True)
diff --git a/spaces/james-oldfield/PandA/networks/stylegan3/torch_utils/ops/filtered_lrelu.py b/spaces/james-oldfield/PandA/networks/stylegan3/torch_utils/ops/filtered_lrelu.py
deleted file mode 100644
index 6106c917d1cbff4f1cf637390dd6ba0c597a830f..0000000000000000000000000000000000000000
--- a/spaces/james-oldfield/PandA/networks/stylegan3/torch_utils/ops/filtered_lrelu.py
+++ /dev/null
@@ -1,274 +0,0 @@
-# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES.  All rights reserved.
-#
-# NVIDIA CORPORATION and its licensors retain all intellectual property
-# and proprietary rights in and to this software, related documentation
-# and any modifications thereto.  Any use, reproduction, disclosure or
-# distribution of this software and related documentation without an express
-# license agreement from NVIDIA CORPORATION is strictly prohibited.
-
-import os
-import numpy as np
-import torch
-import warnings
-
-from .. import custom_ops
-from .. import misc
-from . import upfirdn2d
-from . import bias_act
-
-#----------------------------------------------------------------------------
-
-_plugin = None
-
-def _init():
-    global _plugin
-    if _plugin is None:
-        _plugin = custom_ops.get_plugin(
-            module_name='filtered_lrelu_plugin',
-            sources=['filtered_lrelu.cpp', 'filtered_lrelu_wr.cu', 'filtered_lrelu_rd.cu', 'filtered_lrelu_ns.cu'],
-            headers=['filtered_lrelu.h', 'filtered_lrelu.cu'],
-            source_dir=os.path.dirname(__file__),
-            extra_cuda_cflags=['--use_fast_math'],
-        )
-    return True
-
-def _get_filter_size(f):
-    if f is None:
-        return 1, 1
-    assert isinstance(f, torch.Tensor)
-    assert 1 <= f.ndim <= 2
-    return f.shape[-1], f.shape[0] # width, height
-
-def _parse_padding(padding):
-    if isinstance(padding, int):
-        padding = [padding, padding]
-    assert isinstance(padding, (list, tuple))
-    assert all(isinstance(x, (int, np.integer)) for x in padding)
-    padding = [int(x) for x in padding]
-    if len(padding) == 2:
-        px, py = padding
-        padding = [px, px, py, py]
-    px0, px1, py0, py1 = padding
-    return px0, px1, py0, py1
-
-#----------------------------------------------------------------------------
-
-def filtered_lrelu(x, fu=None, fd=None, b=None, up=1, down=1, padding=0, gain=np.sqrt(2), slope=0.2, clamp=None, flip_filter=False, impl='cuda'):
-    r"""Filtered leaky ReLU for a batch of 2D images.
-
-    Performs the following sequence of operations for each channel:
-
-    1. Add channel-specific bias if provided (`b`).
-
-    2. Upsample the image by inserting N-1 zeros after each pixel (`up`).
-
-    3. Pad the image with the specified number of zeros on each side (`padding`).
-       Negative padding corresponds to cropping the image.
-
-    4. Convolve the image with the specified upsampling FIR filter (`fu`), shrinking it
-       so that the footprint of all output pixels lies within the input image.
-
-    5. Multiply each value by the provided gain factor (`gain`).
-
-    6. Apply leaky ReLU activation function to each value.
-
-    7. Clamp each value between -clamp and +clamp, if `clamp` parameter is provided.
-
-    8. Convolve the image with the specified downsampling FIR filter (`fd`), shrinking
-       it so that the footprint of all output pixels lies within the input image.
-
-    9. Downsample the image by keeping every Nth pixel (`down`).
-
-    The fused op is considerably more efficient than performing the same calculation
-    using standard PyTorch ops. It supports gradients of arbitrary order.
-
-    Args:
-        x:           Float32/float16/float64 input tensor of the shape
-                     `[batch_size, num_channels, in_height, in_width]`.
-        fu:          Float32 upsampling FIR filter of the shape
-                     `[filter_height, filter_width]` (non-separable),
-                     `[filter_taps]` (separable), or
-                     `None` (identity).
-        fd:          Float32 downsampling FIR filter of the shape
-                     `[filter_height, filter_width]` (non-separable),
-                     `[filter_taps]` (separable), or
-                     `None` (identity).
-        b:           Bias vector, or `None` to disable. Must be a 1D tensor of the same type
-                     as `x`. The length of vector must must match the channel dimension of `x`.
-        up:          Integer upsampling factor (default: 1).
-        down:        Integer downsampling factor. (default: 1).
-        padding:     Padding with respect to the upsampled image. Can be a single number
-                     or a list/tuple `[x, y]` or `[x_before, x_after, y_before, y_after]`
-                     (default: 0).
-        gain:        Overall scaling factor for signal magnitude (default: sqrt(2)).
-        slope:       Slope on the negative side of leaky ReLU (default: 0.2).
-        clamp:       Maximum magnitude for leaky ReLU output (default: None).
-        flip_filter: False = convolution, True = correlation (default: False).
-        impl:        Implementation to use. Can be `'ref'` or `'cuda'` (default: `'cuda'`).
-
-    Returns:
-        Tensor of the shape `[batch_size, num_channels, out_height, out_width]`.
-    """
-    assert isinstance(x, torch.Tensor)
-    assert impl in ['ref', 'cuda']
-    if impl == 'cuda' and x.device.type == 'cuda' and _init():
-        return _filtered_lrelu_cuda(up=up, down=down, padding=padding, gain=gain, slope=slope, clamp=clamp, flip_filter=flip_filter).apply(x, fu, fd, b, None, 0, 0)
-    return _filtered_lrelu_ref(x, fu=fu, fd=fd, b=b, up=up, down=down, padding=padding, gain=gain, slope=slope, clamp=clamp, flip_filter=flip_filter)
-
-#----------------------------------------------------------------------------
-
-@misc.profiled_function
-def _filtered_lrelu_ref(x, fu=None, fd=None, b=None, up=1, down=1, padding=0, gain=np.sqrt(2), slope=0.2, clamp=None, flip_filter=False):
-    """Slow and memory-inefficient reference implementation of `filtered_lrelu()` using
-    existing `upfirdn2n()` and `bias_act()` ops.
-    """
-    assert isinstance(x, torch.Tensor) and x.ndim == 4
-    fu_w, fu_h = _get_filter_size(fu)
-    fd_w, fd_h = _get_filter_size(fd)
-    if b is not None:
-        assert isinstance(b, torch.Tensor) and b.dtype == x.dtype
-        misc.assert_shape(b, [x.shape[1]])
-    assert isinstance(up, int) and up >= 1
-    assert isinstance(down, int) and down >= 1
-    px0, px1, py0, py1 = _parse_padding(padding)
-    assert gain == float(gain) and gain > 0
-    assert slope == float(slope) and slope >= 0
-    assert clamp is None or (clamp == float(clamp) and clamp >= 0)
-
-    # Calculate output size.
-    batch_size, channels, in_h, in_w = x.shape
-    in_dtype = x.dtype
-    out_w = (in_w * up + (px0 + px1) - (fu_w - 1) - (fd_w - 1) + (down - 1)) // down
-    out_h = (in_h * up + (py0 + py1) - (fu_h - 1) - (fd_h - 1) + (down - 1)) // down
-
-    # Compute using existing ops.
-    x = bias_act.bias_act(x=x, b=b) # Apply bias.
-    x = upfirdn2d.upfirdn2d(x=x, f=fu, up=up, padding=[px0, px1, py0, py1], gain=up**2, flip_filter=flip_filter) # Upsample.
-    x = bias_act.bias_act(x=x, act='lrelu', alpha=slope, gain=gain, clamp=clamp) # Bias, leaky ReLU, clamp.
-    x = upfirdn2d.upfirdn2d(x=x, f=fd, down=down, flip_filter=flip_filter) # Downsample.
-
-    # Check output shape & dtype.
-    misc.assert_shape(x, [batch_size, channels, out_h, out_w])
-    assert x.dtype == in_dtype
-    return x
-
-#----------------------------------------------------------------------------
-
-_filtered_lrelu_cuda_cache = dict()
-
-def _filtered_lrelu_cuda(up=1, down=1, padding=0, gain=np.sqrt(2), slope=0.2, clamp=None, flip_filter=False):
-    """Fast CUDA implementation of `filtered_lrelu()` using custom ops.
-    """
-    assert isinstance(up, int) and up >= 1
-    assert isinstance(down, int) and down >= 1
-    px0, px1, py0, py1 = _parse_padding(padding)
-    assert gain == float(gain) and gain > 0
-    gain = float(gain)
-    assert slope == float(slope) and slope >= 0
-    slope = float(slope)
-    assert clamp is None or (clamp == float(clamp) and clamp >= 0)
-    clamp = float(clamp if clamp is not None else 'inf')
-
-    # Lookup from cache.
-    key = (up, down, px0, px1, py0, py1, gain, slope, clamp, flip_filter)
-    if key in _filtered_lrelu_cuda_cache:
-        return _filtered_lrelu_cuda_cache[key]
-
-    # Forward op.
-    class FilteredLReluCuda(torch.autograd.Function):
-        @staticmethod
-        def forward(ctx, x, fu, fd, b, si, sx, sy): # pylint: disable=arguments-differ
-            assert isinstance(x, torch.Tensor) and x.ndim == 4
-
-            # Replace empty up/downsample kernels with full 1x1 kernels (faster than separable).
-            if fu is None:
-                fu = torch.ones([1, 1], dtype=torch.float32, device=x.device)
-            if fd is None:
-                fd = torch.ones([1, 1], dtype=torch.float32, device=x.device)
-            assert 1 <= fu.ndim <= 2
-            assert 1 <= fd.ndim <= 2
-
-            # Replace separable 1x1 kernels with full 1x1 kernels when scale factor is 1.
-            if up == 1 and fu.ndim == 1 and fu.shape[0] == 1:
-                fu = fu.square()[None]
-            if down == 1 and fd.ndim == 1 and fd.shape[0] == 1:
-                fd = fd.square()[None]
-
-            # Missing sign input tensor.
-            if si is None:
-                si = torch.empty([0])
-
-            # Missing bias tensor.
-            if b is None:
-                b = torch.zeros([x.shape[1]], dtype=x.dtype, device=x.device)
-
-            # Construct internal sign tensor only if gradients are needed.
-            write_signs = (si.numel() == 0) and (x.requires_grad or b.requires_grad)
-
-            # Warn if input storage strides are not in decreasing order due to e.g. channels-last layout.
-            strides = [x.stride(i) for i in range(x.ndim) if x.size(i) > 1]
-            if any(a < b for a, b in zip(strides[:-1], strides[1:])):
-                warnings.warn("low-performance memory layout detected in filtered_lrelu input", RuntimeWarning)
-
-            # Call C++/Cuda plugin if datatype is supported.
-            if x.dtype in [torch.float16, torch.float32]:
-                if torch.cuda.current_stream(x.device) != torch.cuda.default_stream(x.device):
-                    warnings.warn("filtered_lrelu called with non-default cuda stream but concurrent execution is not supported", RuntimeWarning)
-                y, so, return_code = _plugin.filtered_lrelu(x, fu, fd, b, si, up, down, px0, px1, py0, py1, sx, sy, gain, slope, clamp, flip_filter, write_signs)
-            else:
-                return_code = -1
-
-            # No Cuda kernel found? Fall back to generic implementation. Still more memory efficient than the reference implementation because
-            # only the bit-packed sign tensor is retained for gradient computation.
-            if return_code < 0:
-                warnings.warn("filtered_lrelu called with parameters that have no optimized CUDA kernel, using generic fallback", RuntimeWarning)
-
-                y = x.add(b.unsqueeze(-1).unsqueeze(-1)) # Add bias.
-                y = upfirdn2d.upfirdn2d(x=y, f=fu, up=up, padding=[px0, px1, py0, py1], gain=up**2, flip_filter=flip_filter) # Upsample.
-                so = _plugin.filtered_lrelu_act_(y, si, sx, sy, gain, slope, clamp, write_signs) # Activation function and sign handling. Modifies y in-place.
-                y = upfirdn2d.upfirdn2d(x=y, f=fd, down=down, flip_filter=flip_filter) # Downsample.
-
-            # Prepare for gradient computation.
-            ctx.save_for_backward(fu, fd, (si if si.numel() else so))
-            ctx.x_shape = x.shape
-            ctx.y_shape = y.shape
-            ctx.s_ofs = sx, sy
-            return y
-
-        @staticmethod
-        def backward(ctx, dy): # pylint: disable=arguments-differ
-            fu, fd, si = ctx.saved_tensors
-            _, _, xh, xw = ctx.x_shape
-            _, _, yh, yw = ctx.y_shape
-            sx, sy = ctx.s_ofs
-            dx  = None # 0
-            dfu = None; assert not ctx.needs_input_grad[1]
-            dfd = None; assert not ctx.needs_input_grad[2]
-            db  = None # 3
-            dsi = None; assert not ctx.needs_input_grad[4]
-            dsx = None; assert not ctx.needs_input_grad[5]
-            dsy = None; assert not ctx.needs_input_grad[6]
-
-            if ctx.needs_input_grad[0] or ctx.needs_input_grad[3]:
-                pp = [
-                    (fu.shape[-1] - 1) + (fd.shape[-1] - 1) - px0,
-                    xw * up - yw * down + px0 - (up - 1),
-                    (fu.shape[0] - 1) + (fd.shape[0] - 1) - py0,
-                    xh * up - yh * down + py0 - (up - 1),
-                ]
-                gg = gain * (up ** 2) / (down ** 2)
-                ff = (not flip_filter)
-                sx = sx - (fu.shape[-1] - 1) + px0
-                sy = sy - (fu.shape[0]  - 1) + py0
-                dx = _filtered_lrelu_cuda(up=down, down=up, padding=pp, gain=gg, slope=slope, clamp=None, flip_filter=ff).apply(dy, fd, fu, None, si, sx, sy)
-
-            if ctx.needs_input_grad[3]:
-                db = dx.sum([0, 2, 3])
-
-            return dx, dfu, dfd, db, dsi, dsx, dsy
-
-    # Add to cache.
-    _filtered_lrelu_cuda_cache[key] = FilteredLReluCuda
-    return FilteredLReluCuda
-
-#----------------------------------------------------------------------------
diff --git a/spaces/jbilcke-hf/ai-comic-factory/src/app/engine/censorship.ts b/spaces/jbilcke-hf/ai-comic-factory/src/app/engine/censorship.ts
deleted file mode 100644
index ae4cc0b98b1cc09b9dda0aed35767bb7faee3b6e..0000000000000000000000000000000000000000
--- a/spaces/jbilcke-hf/ai-comic-factory/src/app/engine/censorship.ts
+++ /dev/null
@@ -1,184 +0,0 @@
-
-// I don't want to be banned by Replicate because bad actors are asking
-// for some naked anime stuff or whatever
-// I also want to avoid a PR scandal due to some bad user generated content
-
-import { computeSecretFingerprint } from "@/lib/computeSecretFingerprint"
-
-// those keywords have been generated by looking at the logs of the panorama and the AI Comic Factory
-// those are real requests some users tried to attempt.. :|
-
-const chickens = [
-  "fcb4dacbd99b21368c50f29c1d47071c87cf2225ab9192282c785460391cd365",
-  "68840b60ac27eacaa7afe17e898d3c4a2dc71acff8c74d6782c1bcaafd14963d",
-  "67f745224fd6e1a7a3a244514d5807fcc994cbb62ca4ec8fa44cd14244a515ae",
-  "681fea565117808c6dbe002520d2cfeeb3e5c67e68630afb4a453449a9da587b",
-  "2f3d913b3db9e15a930aac43eb2d6fe8817db8e4bcf37794bf0227b06b718d1b",
-  "922a700b807e4994df82eba2b48a6ac131fe8d8d1035d06b3592d622fb232161",
-  "cb69ee6774eafcc720adb1f689d28acbb9f47998cbea0299ec66a58dedf91c37"
-]
-
-const ducks = [
-  "1c52cb20c0cbc76349fa63232b982bd394cf0850ebc17240dcf33c19fb15a26d",
-  "e1d4de9b8d464d7da07c276b63a42c1c9922224f0a6cab6b0826427ce4a7461a",
-  "0be3174bfb1a48a65875c2f035b1ae14fbc8f232f55785018de0cfe2132fa952",
-  "0f174769641b2e5d2c79b5a83e8ef91e004f6f3e62531cd70cfdff02159268cb",
-  "e9fb8ae8ff720acd91025229478a21e43e8e976e30119a76c293201adf572736",
-  "f65a0dc0e07b5d084ff24c69dcdb953f7b57101d2ebb716d4dfb5963076ef807",
-  "2bf38af1646489c2c086f811d082054cd29e23fa7bb5c525396bec01b3ab688e"
-]
-
-const cats = [
-  "fcffc3e997d952007d1b902a9cf40b750ba4a410ac65bfd95475996bf51359e4",
-  "3172a5fa159754d703489dfba5af520b8ace107cdf170f4c4cb38a6797aa163f",
-  "500012dbff4498a9c4513369d6b9b373fab9330ffd2cb1e622294043cc21b610",
-  "84e3a8d34ee7d0c8e7a2926dd1acad46a0b66b9d27725b3a7e5053550f490301"
-]
-
-const roasted = [
-  "a2bfbce0046c9a52a0eabf98f73e0f8e09959970431fc892ebdb4e1c97031b50",
-  "6eca1adf06851f99e9cdfbb496c27d46ff81106903d11f3346a146e96082b016",
-  "49a124c9ed6fbbad4105b3657dc25de369bcafb9d6787f610c08f584cd607d0f",
-  "c3afb59420c812cbc7c8f57ad3e8d79407f10106a99f829aa65316c99d0b29c4",
-  "2b808858836a5c205080f5b93201ef92e098cff931d8de6d9f20dc722997d077",
-  "07bef89d1a7d63c9c5ed64ba0f73d6cff689811847c2e20c8b3fbfb060e1d64e",
-  "baeb994922d5473f534aa54322d83effe74c6c4dac807e6b523a677d7acdc17b",
-  "ea4735a879edd5cc94ca7db26edd5a970df69a41f0009d3444486647e44175af",
-  "f2412249030454cd13ac6f7965871d924c16daacda0123de81892adb19ce49ac",
-  "9958c56e12bab8549cf752bcd8bec4ac36cf79c404b1faf5611f057bb71bc0e1",
-  "76cdade0b3d4caf0888f60318a5cbca00f830a3b0bf37735fc64fdaeb67c34d3",
-  "1bf53c97869e1ea89bda19da64a9173d48fe4ec823e949e2c898f8abb3fbf457",
-  "1bf53c97869e1ea89bda19da64a9173d48fe4ec823e949e2c898f8abb3fbf457",
-  "3d7f973fab8f4a19c0a3e59efe970ed7bd55a1cb795752d9cbe3c19e8a7d81ec"
-]
-
-const banned = [
-  "8a05d4869d9d6ce388c6cd2db13ca12b88097b90f9be027d5ffaaa467c7a6e5e",
-  "0c475212a608138244c5fc150b1563e5ef79c516234fd78dcd5993f726c359a0",
-  "df17388805f99f2ff3e5ae97a0f55e5c927eb47f17ca65822bf8c88f02bac3dd",
-  "86c3355d1bd581cdf7306729d8dd0ee9b7a317b9cfd6d7a6f5fad9c0dafe2167",
-  "23a2484cd420c9ffbfcc2c0075a9b330664450ced1fc64ab6a65e278086b8c6e",
-  "fb4cabe709b62eea1b4cc0030c76f5e4a43ee677ce19124e8e7bafa86c78ab66",
-  "d99c26daee85f7dc81c46c061a5874cff7179ed72d884d2316d664d36ffe7ab5",
-  "b93c38af5aa221d76c60ee3eb762efee0cdb0daf29ceb235b7dda6d46c06490d",
-  "8cf6c8765dc757319461dd9a785e77c201b8e5a604d36b817cd987c6a5e62500",
-  "f4a1cb290745717f86c3cee30fc324c0d80a9945fcbc7bbeb010579f58792f1e",
-  "7c87c47c42fc983119551342be9ddd5b32e530c0504ccdbbaa1e12b1d9f1bbcb",
-  "d04fad4f21d030da7a1301afbf480ef6246eb7bbf0f26e31865b2e015a25f747",
-  "d685ff22fb9da01ee949db212770729603989850864ef7a7085e1f086cfa7deb",
-  "533b90588d9ccf7967da54691f575e9fd4926c6e0b5fd94a47b932bcea270bee",
-  "9c2d61f28f5bb7f3f1dc9122be64cda8a428b46ce68b70120da4c41dba96ba4c",
-  "5d4b1a3eebe64dfa631d0e3b084bd96ee9364c3669269f838ca17a4900276264",
-  "d56f56413b9679fc0820a2c0237224ded8554c61fab8959c174123c8b68ba029",
-  "323a9ab60739726070d615ff3a05d7ff6bb6e3c4dd9ff16ce24f253ecd7b8851",
-  "975c6739de7d4999db15972f707f5f4e95649275f1c0c48e895b8c537e8638ec",
-  "67ee26eb9e1c1c7124797321b02bca90a19c18171782917cd4a487b722484dce",
-  "6df5aa7b72a4e6e3fb726489ff1437daa5752047507f4da912680b1d6647c7d6",
-  "b0864805364359e8c5810c233b1bf2c74dedce9055ae5f7680ba05b4e39db8e2",
-  "a8f841472ecffdd6266151148320c8e36847a24ead9d3338e0313b075c16649d",
-  "f9b127cd90e85b0ff68dd220361671663f0154b2b827f1f7ea797b020ca0018c",
-  "d5c20e9a1ecf01c82da24c514d867498b3e5f522adc1523ce29404a6563641d5",
-  "241022b49d7c0aba24a61eea1137a804f36e4bcb47af42950275baac9b4e7aac",
-  "fc99a70e17b6c86ef1b537654b0f50353567a7b59912c3ba955f3fca4d1ea696",
-  "255306e968009003d295cb2a7256f27bfcdb5d1743bf4d9f2aa4b8adf1a7734d",
-  "048c7b709763dd9c43794d241c369f0abcb079d546ddcbbba9968a1ed1da7ed7",
-  "520cbfeef3e4c405d79478eedccb97a4d476be585626dd2b1c53292797491bc7",
-  "f9f28a7ae7e8b1719b350a04dc087a4b8e33478d109ceeef6ba892b32d1105c9",
-  "d177f1bfe603647ef4c1c0e6f1a7172081fb9bbc2ea859705949f2c5aa5d4f22",
-  "302feef2c09247fbd23789581f7f5e2219f88ae0a937880954938573c2a52a84",
-  "99edd6f57b864873835f16f19c805dd94bed9da8967b84e3a62782f106d9ebcc",
-  "e75e5f01dcd8351c9553e89558085bd68e6feb295dee5d8da0c9b43ee303ce36",
-  "135e52a026aea9d2e12de358a85e05cf21121a18269269b7c62678c3bc846f5b",
-  "28e5b2d3eb5f1ef4cc7b570878b03acf303a6ca4ca95893591e0fb943b0beab0",
-  "a26b26340f8d0363633490556d20bcc250726d10e1431eb8c22d6b1ff3f2b14a",
-  "27e4ddde96ec6a1dbe1cf12d79448b3e72f144944c15b299629542d1b65fbabf",
-  "efd9c0a391ee93251046a58326d1b21b33fe21d71a3fb1855b9048ade53df77c",
-  "6d505fcce416c26a606878aab4d249a034ba2a9846cb1f883e0f9e3fb76ba6da",
-  "3a37b8a1b72f9bca51233536d50f9c8d33a787434684787871e0049c82347cda",
-  "16f9b451184a7c3148344c7d0315f5312ca20553d2271912ecaad91810d977e6",
-  "7406537eb74d1885bd05e191228de313b13702a64d90ae1736c6377b25ab579a",
-  "7e4d1395ae18980015cab16c85ffa20b4cb90a2db594126e893d0f7ac6eecaa8",
-  "ba813ee6c25698f0f68a07121d38bb47c9aa404c1ab0a6e767595cb75e1747b8",
-  "6586c93f3ece83e01ecc1eb84a7711e7975826a388d478a009468ea0ed9dc03e",
-  "8960174c74d86e03ae88fb6774580170e49952f2286d960be08c556bbd0dda95",
-  "4d611454369aa1a4e2b7eed1734fac5d480f08fb86b87a162967e416370f2a8e",
-  "59d48440f85eabf565fe8d3bc6b973ba64c70df3b36b0511e0e67ceca91762b3",
-  "cd926926e2af74e43d1a6a420a7e1933b78662320477a3c018b2711d8765e339",
-  "80e90057df6a59823f51aafac36ed5bc4e5ac26d675d9c1467501590c82f12d4",
-  "a9cf28b869b70e258adde5639a048f866ec86f8f3f3d53bfc960b86aa6da9239",
-  "cc2adbf8ac0cddeefa304d7b20f14a7e047a4b2299cc5e8f898f5c59660bd964",
-  "92a150a46146e9d3f84899cf15e12514af684e7ee18d7add782ddd4f4a15ef18",
-  "d9b2e84ef6dc0ce449357d52c9095f69b173a1b848ea2921199d33b0ec10024a",
-  "a9329a7e4d367a0135c1ca86c6ce5ecabcc26529235229d71b6bf991f7689e21",
-  "8f160c6fd8ccc3fb2a371a4b52748f0bd030766627c4322e2911fe82f6b10497",
-  "620e96eae4f3e88cbe0770292b33724c5df3866d83f39df6380441f7271c80e2",
-  "cafa3481fa3c45ed1e55cd0129c12b477eeab5aa3d6da20cae6d6292f19b0e6d",
-  "be07994e9a83aa3689e79b6e96123676ccc4fa29f523c28c750c6d60505531ee",
-  "f6498069768cd3aa79b2b0c91879694f05a259c8ee4a6bb343f0435f74eb1b53",
-  "c9b6b26cb3a694eb78fcac0a14ad18d46d50907186a9add41022d31d191b2b65"
-]
-
-const young = [
-  "ffdf66787b4a33b78b18c18822e334cfe2c8406caf442851deef451bd43140a1",
-  "858f22219afc4b32a7ba9a27a213d7f495e77c3cceed8147eae5282bf3e23d39",
-  "8c3c46df84ace3d58d4ce0fbc513017986b33c6002ae369d9f7dd1f892a898cb",
-  "66caa22b9483fdf026ce67de61067d81535a7c9b3169cbc5c2a455ac8dcc7bec",
-  "76893047b1eff9fadc7be07b13adb5aaed9c73bcdeea46ee07098605e2c7ff76",
-  "526cb848754e2baaa17376a5693d90ba3f69f71fd2a866f22876ac8a075849a7",
-  "f59c38e31d0f64dc1bfcdf34451723bc1a65570e209e5496c8d1d7f6d3d649db",
-  "e013a67e275c62c1402ccbbb11ad14afb8b8a82318a44c07d67599ed5ac874de",
-  "3bef34219fb07f867ecbff4d6748f598d6cc0761e17dd0d431ee1f4ec3281374",
-  "8211bf5f613fac06cd5d074d34c16dfacc9367c8afaa6ad3aff99d145e5221be"
-]
-
-const getFingerprint = (word: string) => {
-  return computeSecretFingerprint(
-    word.toLocaleLowerCase().replaceAll(/[^a-zA-Z0-9]/gi, "")
-    )
-}
-
-const encode = (list: string[]) => {
-  console.log(JSON.stringify(
-    list.sort((a, b) => (b.length - a.length))
-    .map(item => getFingerprint(item)), null, 2))
-}
-
-// encode([ "badword" ])
-
-export const filterOutBadWords = (sentence: string) => {
-  if (process.env.ENABLE_CENSORSHIP !== "true") { return sentence }
-
-  let requireCensorship = false
-
-  const words = sentence.replaceAll(/[^a-zA-Z0-9]/gi, " ").replaceAll(/\s+/gi, " ").trim().split(" ")
-  
-  const sanitized = words.map(word => {
-    const fingerprint = getFingerprint(word)
-  
-    let result: string = word
-    // some users want to play it smart and bypass our system so let's play too
-    if (chickens.includes(fingerprint)) {
-      result = "large chicken"
-    } else if (ducks.includes(fingerprint)) {
-      result = "big duck"
-    } else if (cats.includes(fingerprint)) {
-      result = "cat"
-    } else if (roasted.includes(fingerprint)) {
-      result = "roasted chicken"
-    } else if (young.includes(fingerprint)) {
-      result = "adult"
-    } else if (banned.includes(fingerprint)) {
-      result = "_BANNED_"
-    }
-
-    if (result !== word) {
-      requireCensorship = true
-    }
-    return result
-  }).filter(item => item !== "_BANNED_").join(" ")
-
-  // if the user didn't try to use a bad word, we leave it untouched 
-  // he words array has been degraded by the replace operation, but it removes commas etc which isn't great
-  // so if the request was genuine and SFW, it's best to return the original prompt
-  return requireCensorship ? sanitized : sentence
-}
\ No newline at end of file
diff --git a/spaces/jeanbaptdzd/mistralai-Mistral-7B-v0.1/app.py b/spaces/jeanbaptdzd/mistralai-Mistral-7B-v0.1/app.py
deleted file mode 100644
index 22ea81a78d380cdb481188f32c93b9ad214b85f2..0000000000000000000000000000000000000000
--- a/spaces/jeanbaptdzd/mistralai-Mistral-7B-v0.1/app.py
+++ /dev/null
@@ -1,3 +0,0 @@
-import gradio as gr
-
-gr.Interface.load("models/mistralai/Mistral-7B-v0.1").launch()
\ No newline at end of file
diff --git a/spaces/jiejiejie0420/bingo/src/lib/hooks/use-at-bottom.tsx b/spaces/jiejiejie0420/bingo/src/lib/hooks/use-at-bottom.tsx
deleted file mode 100644
index d37c8cf4162adcb0064e08ecec24eb731416b045..0000000000000000000000000000000000000000
--- a/spaces/jiejiejie0420/bingo/src/lib/hooks/use-at-bottom.tsx
+++ /dev/null
@@ -1,23 +0,0 @@
-import * as React from 'react'
-
-export function useAtBottom(offset = 0) {
-  const [isAtBottom, setIsAtBottom] = React.useState(false)
-
-  React.useEffect(() => {
-    const handleScroll = () => {
-      setIsAtBottom(
-        window.innerHeight + window.scrollY >=
-          document.body.offsetHeight - offset
-      )
-    }
-
-    window.addEventListener('scroll', handleScroll, { passive: true })
-    handleScroll()
-
-    return () => {
-      window.removeEventListener('scroll', handleScroll)
-    }
-  }, [offset])
-
-  return isAtBottom
-}
diff --git a/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/Crypto/Protocol/DH.py b/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/Crypto/Protocol/DH.py
deleted file mode 100644
index fb21daabc7aae5c003f58923b689a34ab7e1342c..0000000000000000000000000000000000000000
--- a/spaces/joaopereirajp/livvieChatBot/venv/lib/python3.9/site-packages/Crypto/Protocol/DH.py
+++ /dev/null
@@ -1,101 +0,0 @@
-from Crypto.Util.number import long_to_bytes
-from Crypto.PublicKey.ECC import EccKey
-
-
-def _compute_ecdh(key_priv, key_pub):
-    # See Section 5.7.1.2 in NIST SP 800-56Ar3
-    pointP = key_pub.pointQ * key_priv.d
-    if pointP.is_point_at_infinity():
-        raise ValueError("Invalid ECDH point")
-    z = long_to_bytes(pointP.x, pointP.size_in_bytes())
-    return z
-
-
-def key_agreement(**kwargs):
-    """Perform a Diffie-Hellman key agreement.
-
-    Keywords:
-      kdf (callable):
-        A key derivation function that accepts ``bytes`` as input and returns
-        ``bytes``.
-      static_priv (EccKey):
-        The local static private key. Optional.
-      static_pub (EccKey):
-        The static public key that belongs to the peer. Optional.
-      eph_priv (EccKey):
-        The local ephemeral private key, generated for this session. Optional.
-      eph_pub (EccKey):
-        The ephemeral public key, received from the peer for this session. Optional.
-
-    At least two keys must be passed, of which one is a private key and one
-    a public key.
-
-    Returns (bytes):
-      The derived secret key material.
-    """
-
-    static_priv = kwargs.get('static_priv', None)
-    static_pub = kwargs.get('static_pub', None)
-    eph_priv = kwargs.get('eph_priv', None)
-    eph_pub = kwargs.get('eph_pub', None)
-    kdf = kwargs.get('kdf', None)
-
-    if kdf is None:
-        raise ValueError("'kdf' is mandatory")
-
-    count_priv = 0
-    count_pub = 0
-    curve = None
-
-    def check_curve(curve, key, name, private):
-        if not isinstance(key, EccKey):
-            raise TypeError("'%s' must be an ECC key" % name)
-        if private and not key.has_private():
-            raise TypeError("'%s' must be a private ECC key" % name)
-        if curve is None:
-            curve = key.curve
-        elif curve != key.curve:
-            raise TypeError("'%s' is defined on an incompatible curve" % name)
-        return curve
-
-    if static_priv is not None:
-        curve = check_curve(curve, static_priv, 'static_priv', True)
-        count_priv += 1
-
-    if static_pub is not None:
-        curve = check_curve(curve, static_pub, 'static_pub', False)
-        count_pub += 1
-
-    if eph_priv is not None:
-        curve = check_curve(curve, eph_priv, 'eph_priv', True)
-        count_priv += 1
-
-    if eph_pub is not None:
-        curve = check_curve(curve, eph_pub, 'eph_pub', False)
-        count_pub += 1
-
-    if (count_priv + count_pub) < 2 or count_priv == 0 or count_pub == 0:
-        raise ValueError("Too few keys for the ECDH key agreement")
-
-    Zs = b''
-    Ze = b''
-
-    if static_priv and static_pub:
-        # C(*, 2s)
-        Zs = _compute_ecdh(static_priv, static_pub)
-
-    if eph_priv and eph_pub:
-        # C(2e, 0s) or C(2e, 2s)
-        if bool(static_priv) != bool(static_pub):
-            raise ValueError("DH mode C(2e, 1s) is not supported")
-        Ze = _compute_ecdh(eph_priv, eph_pub)
-    elif eph_priv and static_pub:
-        # C(1e, 2s) or C(1e, 1s)
-        Ze = _compute_ecdh(eph_priv, static_pub)
-    elif eph_pub and static_priv:
-        # C(1e, 2s) or C(1e, 1s)
-        Ze = _compute_ecdh(static_priv, eph_pub)
-
-    Z = Ze + Zs
-
-    return kdf(Z)
diff --git a/spaces/johnslegers/stable-diffusion-gui-test/optimizedSD/splitAttention.py b/spaces/johnslegers/stable-diffusion-gui-test/optimizedSD/splitAttention.py
deleted file mode 100644
index a9df37ba8dd2caeac62fea038946b4aa5a724b7e..0000000000000000000000000000000000000000
--- a/spaces/johnslegers/stable-diffusion-gui-test/optimizedSD/splitAttention.py
+++ /dev/null
@@ -1,280 +0,0 @@
-from inspect import isfunction
-import math
-import torch
-import torch.nn.functional as F
-from torch import nn, einsum
-from einops import rearrange, repeat
-
-from ldmlib.modules.diffusionmodules.util import checkpoint
-
-
-def exists(val):
-    return val is not None
-
-
-def uniq(arr):
-    return{el: True for el in arr}.keys()
-
-
-def default(val, d):
-    if exists(val):
-        return val
-    return d() if isfunction(d) else d
-
-
-def max_neg_value(t):
-    return -torch.finfo(t.dtype).max
-
-
-def init_(tensor):
-    dim = tensor.shape[-1]
-    std = 1 / math.sqrt(dim)
-    tensor.uniform_(-std, std)
-    return tensor
-
-
-# feedforward
-class GEGLU(nn.Module):
-    def __init__(self, dim_in, dim_out):
-        super().__init__()
-        self.proj = nn.Linear(dim_in, dim_out * 2)
-
-    def forward(self, x):
-        x, gate = self.proj(x).chunk(2, dim=-1)
-        return x * F.gelu(gate)
-
-
-class FeedForward(nn.Module):
-    def __init__(self, dim, dim_out=None, mult=4, glu=False, dropout=0.):
-        super().__init__()
-        inner_dim = int(dim * mult)
-        dim_out = default(dim_out, dim)
-        project_in = nn.Sequential(
-            nn.Linear(dim, inner_dim),
-            nn.GELU()
-        ) if not glu else GEGLU(dim, inner_dim)
-
-        self.net = nn.Sequential(
-            project_in,
-            nn.Dropout(dropout),
-            nn.Linear(inner_dim, dim_out)
-        )
-
-    def forward(self, x):
-        return self.net(x)
-
-
-def zero_module(module):
-    """
-    Zero out the parameters of a module and return it.
-    """
-    for p in module.parameters():
-        p.detach().zero_()
-    return module
-
-
-def Normalize(in_channels):
-    return torch.nn.GroupNorm(num_groups=32, num_channels=in_channels, eps=1e-6, affine=True)
-
-
-class LinearAttention(nn.Module):
-    def __init__(self, dim, heads=4, dim_head=32):
-        super().__init__()
-        self.heads = heads
-        hidden_dim = dim_head * heads
-        self.to_qkv = nn.Conv2d(dim, hidden_dim * 3, 1, bias = False)
-        self.to_out = nn.Conv2d(hidden_dim, dim, 1)
-
-    def forward(self, x):
-        b, c, h, w = x.shape
-        qkv = self.to_qkv(x)
-        q, k, v = rearrange(qkv, 'b (qkv heads c) h w -> qkv b heads c (h w)', heads = self.heads, qkv=3)
-        k = k.softmax(dim=-1)
-        context = torch.einsum('bhdn,bhen->bhde', k, v)
-        out = torch.einsum('bhde,bhdn->bhen', context, q)
-        out = rearrange(out, 'b heads c (h w) -> b (heads c) h w', heads=self.heads, h=h, w=w)
-        return self.to_out(out)
-
-
-class SpatialSelfAttention(nn.Module):
-    def __init__(self, in_channels):
-        super().__init__()
-        self.in_channels = in_channels
-
-        self.norm = Normalize(in_channels)
-        self.q = torch.nn.Conv2d(in_channels,
-                                 in_channels,
-                                 kernel_size=1,
-                                 stride=1,
-                                 padding=0)
-        self.k = torch.nn.Conv2d(in_channels,
-                                 in_channels,
-                                 kernel_size=1,
-                                 stride=1,
-                                 padding=0)
-        self.v = torch.nn.Conv2d(in_channels,
-                                 in_channels,
-                                 kernel_size=1,
-                                 stride=1,
-                                 padding=0)
-        self.proj_out = torch.nn.Conv2d(in_channels,
-                                        in_channels,
-                                        kernel_size=1,
-                                        stride=1,
-                                        padding=0)
-
-    def forward(self, x):
-        h_ = x
-        h_ = self.norm(h_)
-        q = self.q(h_)
-        k = self.k(h_)
-        v = self.v(h_)
-
-        # compute attention
-        b,c,h,w = q.shape
-        q = rearrange(q, 'b c h w -> b (h w) c')
-        k = rearrange(k, 'b c h w -> b c (h w)')
-        w_ = torch.einsum('bij,bjk->bik', q, k)
-
-        w_ = w_ * (int(c)**(-0.5))
-        w_ = torch.nn.functional.softmax(w_, dim=2)
-
-        # attend to values
-        v = rearrange(v, 'b c h w -> b c (h w)')
-        w_ = rearrange(w_, 'b i j -> b j i')
-        h_ = torch.einsum('bij,bjk->bik', v, w_)
-        h_ = rearrange(h_, 'b c (h w) -> b c h w', h=h)
-        h_ = self.proj_out(h_)
-
-        return x+h_
-
-
-class CrossAttention(nn.Module):
-    def __init__(self, query_dim, context_dim=None, heads=8, dim_head=64, dropout=0., att_step=1):
-        super().__init__()
-        inner_dim = dim_head * heads
-        context_dim = default(context_dim, query_dim)
-
-        self.scale = dim_head ** -0.5
-        self.heads = heads
-        self.att_step = att_step
-
-        self.to_q = nn.Linear(query_dim, inner_dim, bias=False)
-        self.to_k = nn.Linear(context_dim, inner_dim, bias=False)
-        self.to_v = nn.Linear(context_dim, inner_dim, bias=False)
-
-        self.to_out = nn.Sequential(
-            nn.Linear(inner_dim, query_dim),
-            nn.Dropout(dropout)
-        )
-
-    def forward(self, x, context=None, mask=None):
-        h = self.heads
-
-        q = self.to_q(x)
-        context = default(context, x)
-        k = self.to_k(context)
-        v = self.to_v(context)
-        del context, x
-
-        q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
-
-
-        limit = k.shape[0]
-        att_step = self.att_step
-        q_chunks = list(torch.tensor_split(q, limit//att_step, dim=0))
-        k_chunks = list(torch.tensor_split(k, limit//att_step, dim=0))
-        v_chunks = list(torch.tensor_split(v, limit//att_step, dim=0))
-
-        q_chunks.reverse()
-        k_chunks.reverse()
-        v_chunks.reverse()
-        sim = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device)
-        del k, q, v
-        for i in range (0, limit, att_step):
-
-            q_buffer = q_chunks.pop()
-            k_buffer = k_chunks.pop()
-            v_buffer = v_chunks.pop()
-            sim_buffer = einsum('b i d, b j d -> b i j', q_buffer, k_buffer) * self.scale
-
-            del k_buffer, q_buffer
-        # attention, what we cannot get enough of, by chunks
-
-            sim_buffer = sim_buffer.softmax(dim=-1)
-
-            sim_buffer = einsum('b i j, b j d -> b i d', sim_buffer, v_buffer)
-            del v_buffer
-            sim[i:i+att_step,:,:] = sim_buffer
-
-            del sim_buffer
-        sim = rearrange(sim, '(b h) n d -> b n (h d)', h=h)
-        return self.to_out(sim)
-
-
-class BasicTransformerBlock(nn.Module):
-    def __init__(self, dim, n_heads, d_head, dropout=0., context_dim=None, gated_ff=True, checkpoint=True):
-        super().__init__()
-        self.attn1 = CrossAttention(query_dim=dim, heads=n_heads, dim_head=d_head, dropout=dropout)  # is a self-attention
-        self.ff = FeedForward(dim, dropout=dropout, glu=gated_ff)
-        self.attn2 = CrossAttention(query_dim=dim, context_dim=context_dim,
-                                    heads=n_heads, dim_head=d_head, dropout=dropout)  # is self-attn if context is none
-        self.norm1 = nn.LayerNorm(dim)
-        self.norm2 = nn.LayerNorm(dim)
-        self.norm3 = nn.LayerNorm(dim)
-        self.checkpoint = checkpoint
-
-    def forward(self, x, context=None):
-        return checkpoint(self._forward, (x, context), self.parameters(), self.checkpoint)
-
-    def _forward(self, x, context=None):
-        x = self.attn1(self.norm1(x)) + x
-        x = self.attn2(self.norm2(x), context=context) + x
-        x = self.ff(self.norm3(x)) + x
-        return x
-
-
-class SpatialTransformer(nn.Module):
-    """
-    Transformer block for image-like data.
-    First, project the input (aka embedding)
-    and reshape to b, t, d.
-    Then apply standard transformer action.
-    Finally, reshape to image
-    """
-    def __init__(self, in_channels, n_heads, d_head,
-                 depth=1, dropout=0., context_dim=None):
-        super().__init__()
-        self.in_channels = in_channels
-        inner_dim = n_heads * d_head
-        self.norm = Normalize(in_channels)
-
-        self.proj_in = nn.Conv2d(in_channels,
-                                 inner_dim,
-                                 kernel_size=1,
-                                 stride=1,
-                                 padding=0)
-
-        self.transformer_blocks = nn.ModuleList(
-            [BasicTransformerBlock(inner_dim, n_heads, d_head, dropout=dropout, context_dim=context_dim)
-                for d in range(depth)]
-        )
-
-        self.proj_out = zero_module(nn.Conv2d(inner_dim,
-                                              in_channels,
-                                              kernel_size=1,
-                                              stride=1,
-                                              padding=0))
-
-    def forward(self, x, context=None):
-        # note: if no context is given, cross-attention defaults to self-attention
-        b, c, h, w = x.shape
-        x_in = x
-        x = self.norm(x)
-        x = self.proj_in(x)
-        x = rearrange(x, 'b c h w -> b (h w) c')
-        for block in self.transformer_blocks:
-            x = block(x, context=context)
-        x = rearrange(x, 'b (h w) c -> b c h w', h=h, w=w)
-        x = self.proj_out(x)
-        return x + x_in
diff --git a/spaces/joshen/gpt-academic/crazy_functions/test_project/python/dqn/dqn.py b/spaces/joshen/gpt-academic/crazy_functions/test_project/python/dqn/dqn.py
deleted file mode 100644
index 6cea64d39baa7ff4c1e549869aaa4b0ae17779a9..0000000000000000000000000000000000000000
--- a/spaces/joshen/gpt-academic/crazy_functions/test_project/python/dqn/dqn.py
+++ /dev/null
@@ -1,245 +0,0 @@
-from typing import Any, Dict, List, Optional, Tuple, Type, Union
-
-import gym
-import numpy as np
-import torch as th
-from torch.nn import functional as F
-
-from stable_baselines3.common import logger
-from stable_baselines3.common.off_policy_algorithm import OffPolicyAlgorithm
-from stable_baselines3.common.preprocessing import maybe_transpose
-from stable_baselines3.common.type_aliases import GymEnv, MaybeCallback, Schedule
-from stable_baselines3.common.utils import get_linear_fn, is_vectorized_observation, polyak_update
-from stable_baselines3.dqn.policies import DQNPolicy
-
-
-class DQN(OffPolicyAlgorithm):
-    """
-    Deep Q-Network (DQN)
-
-    Paper: https://arxiv.org/abs/1312.5602, https://www.nature.com/articles/nature14236
-    Default hyperparameters are taken from the nature paper,
-    except for the optimizer and learning rate that were taken from Stable Baselines defaults.
-
-    :param policy: The policy model to use (MlpPolicy, CnnPolicy, ...)
-    :param env: The environment to learn from (if registered in Gym, can be str)
-    :param learning_rate: The learning rate, it can be a function
-        of the current progress remaining (from 1 to 0)
-    :param buffer_size: size of the replay buffer
-    :param learning_starts: how many steps of the model to collect transitions for before learning starts
-    :param batch_size: Minibatch size for each gradient update
-    :param tau: the soft update coefficient ("Polyak update", between 0 and 1) default 1 for hard update
-    :param gamma: the discount factor
-    :param train_freq: Update the model every ``train_freq`` steps. Alternatively pass a tuple of frequency and unit
-        like ``(5, "step")`` or ``(2, "episode")``.
-    :param gradient_steps: How many gradient steps to do after each rollout (see ``train_freq``)
-        Set to ``-1`` means to do as many gradient steps as steps done in the environment
-        during the rollout.
-    :param optimize_memory_usage: Enable a memory efficient variant of the replay buffer
-        at a cost of more complexity.
-        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195
-    :param target_update_interval: update the target network every ``target_update_interval``
-        environment steps.
-    :param exploration_fraction: fraction of entire training period over which the exploration rate is reduced
-    :param exploration_initial_eps: initial value of random action probability
-    :param exploration_final_eps: final value of random action probability
-    :param max_grad_norm: The maximum value for the gradient clipping
-    :param tensorboard_log: the log location for tensorboard (if None, no logging)
-    :param create_eval_env: Whether to create a second environment that will be
-        used for evaluating the agent periodically. (Only available when passing string for the environment)
-    :param policy_kwargs: additional arguments to be passed to the policy on creation
-    :param verbose: the verbosity level: 0 no output, 1 info, 2 debug
-    :param seed: Seed for the pseudo random generators
-    :param device: Device (cpu, cuda, ...) on which the code should be run.
-        Setting it to auto, the code will be run on the GPU if possible.
-    :param _init_setup_model: Whether or not to build the network at the creation of the instance
-    """
-
-    def __init__(
-        self,
-        policy: Union[str, Type[DQNPolicy]],
-        env: Union[GymEnv, str],
-        learning_rate: Union[float, Schedule] = 1e-4,
-        buffer_size: int = 1000000,
-        learning_starts: int = 50000,
-        batch_size: Optional[int] = 32,
-        tau: float = 1.0,
-        gamma: float = 0.99,
-        train_freq: Union[int, Tuple[int, str]] = 4,
-        gradient_steps: int = 1,
-        optimize_memory_usage: bool = False,
-        target_update_interval: int = 10000,
-        exploration_fraction: float = 0.1,
-        exploration_initial_eps: float = 1.0,
-        exploration_final_eps: float = 0.05,
-        max_grad_norm: float = 10,
-        tensorboard_log: Optional[str] = None,
-        create_eval_env: bool = False,
-        policy_kwargs: Optional[Dict[str, Any]] = None,
-        verbose: int = 0,
-        seed: Optional[int] = None,
-        device: Union[th.device, str] = "auto",
-        _init_setup_model: bool = True,
-    ):
-
-        super(DQN, self).__init__(
-            policy,
-            env,
-            DQNPolicy,
-            learning_rate,
-            buffer_size,
-            learning_starts,
-            batch_size,
-            tau,
-            gamma,
-            train_freq,
-            gradient_steps,
-            action_noise=None,  # No action noise
-            policy_kwargs=policy_kwargs,
-            tensorboard_log=tensorboard_log,
-            verbose=verbose,
-            device=device,
-            create_eval_env=create_eval_env,
-            seed=seed,
-            sde_support=False,
-            optimize_memory_usage=optimize_memory_usage,
-            supported_action_spaces=(gym.spaces.Discrete,),
-        )
-
-        self.exploration_initial_eps = exploration_initial_eps
-        self.exploration_final_eps = exploration_final_eps
-        self.exploration_fraction = exploration_fraction
-        self.target_update_interval = target_update_interval
-        self.max_grad_norm = max_grad_norm
-        # "epsilon" for the epsilon-greedy exploration
-        self.exploration_rate = 0.0
-        # Linear schedule will be defined in `_setup_model()`
-        self.exploration_schedule = None
-        self.q_net, self.q_net_target = None, None
-
-        if _init_setup_model:
-            self._setup_model()
-
-    def _setup_model(self) -> None:
-        super(DQN, self)._setup_model()
-        self._create_aliases()
-        self.exploration_schedule = get_linear_fn(
-            self.exploration_initial_eps, self.exploration_final_eps, self.exploration_fraction
-        )
-
-    def _create_aliases(self) -> None:
-        self.q_net = self.policy.q_net
-        self.q_net_target = self.policy.q_net_target
-
-    def _on_step(self) -> None:
-        """
-        Update the exploration rate and target network if needed.
-        This method is called in ``collect_rollouts()`` after each step in the environment.
-        """
-        if self.num_timesteps % self.target_update_interval == 0:
-            polyak_update(self.q_net.parameters(), self.q_net_target.parameters(), self.tau)
-
-        self.exploration_rate = self.exploration_schedule(self._current_progress_remaining)
-        logger.record("rollout/exploration rate", self.exploration_rate)
-
-    def train(self, gradient_steps: int, batch_size: int = 100) -> None:
-        # Update learning rate according to schedule
-        self._update_learning_rate(self.policy.optimizer)
-
-        losses = []
-        for _ in range(gradient_steps):
-            # Sample replay buffer
-            replay_data = self.replay_buffer.sample(batch_size, env=self._vec_normalize_env)
-
-            with th.no_grad():
-                # Compute the next Q-values using the target network
-                next_q_values = self.q_net_target(replay_data.next_observations)
-                # Follow greedy policy: use the one with the highest value
-                next_q_values, _ = next_q_values.max(dim=1)
-                # Avoid potential broadcast issue
-                next_q_values = next_q_values.reshape(-1, 1)
-                # 1-step TD target
-                target_q_values = replay_data.rewards + (1 - replay_data.dones) * self.gamma * next_q_values
-
-            # Get current Q-values estimates
-            current_q_values = self.q_net(replay_data.observations)
-
-            # Retrieve the q-values for the actions from the replay buffer
-            current_q_values = th.gather(current_q_values, dim=1, index=replay_data.actions.long())
-
-            # Compute Huber loss (less sensitive to outliers)
-            loss = F.smooth_l1_loss(current_q_values, target_q_values)
-            losses.append(loss.item())
-
-            # Optimize the policy
-            self.policy.optimizer.zero_grad()
-            loss.backward()
-            # Clip gradient norm
-            th.nn.utils.clip_grad_norm_(self.policy.parameters(), self.max_grad_norm)
-            self.policy.optimizer.step()
-
-        # Increase update counter
-        self._n_updates += gradient_steps
-
-        logger.record("train/n_updates", self._n_updates, exclude="tensorboard")
-        logger.record("train/loss", np.mean(losses))
-
-    def predict(
-        self,
-        observation: np.ndarray,
-        state: Optional[np.ndarray] = None,
-        mask: Optional[np.ndarray] = None,
-        deterministic: bool = False,
-    ) -> Tuple[np.ndarray, Optional[np.ndarray]]:
-        """
-        Overrides the base_class predict function to include epsilon-greedy exploration.
-
-        :param observation: the input observation
-        :param state: The last states (can be None, used in recurrent policies)
-        :param mask: The last masks (can be None, used in recurrent policies)
-        :param deterministic: Whether or not to return deterministic actions.
-        :return: the model's action and the next state
-            (used in recurrent policies)
-        """
-        if not deterministic and np.random.rand() < self.exploration_rate:
-            if is_vectorized_observation(maybe_transpose(observation, self.observation_space), self.observation_space):
-                n_batch = observation.shape[0]
-                action = np.array([self.action_space.sample() for _ in range(n_batch)])
-            else:
-                action = np.array(self.action_space.sample())
-        else:
-            action, state = self.policy.predict(observation, state, mask, deterministic)
-        return action, state
-
-    def learn(
-        self,
-        total_timesteps: int,
-        callback: MaybeCallback = None,
-        log_interval: int = 4,
-        eval_env: Optional[GymEnv] = None,
-        eval_freq: int = -1,
-        n_eval_episodes: int = 5,
-        tb_log_name: str = "DQN",
-        eval_log_path: Optional[str] = None,
-        reset_num_timesteps: bool = True,
-    ) -> OffPolicyAlgorithm:
-
-        return super(DQN, self).learn(
-            total_timesteps=total_timesteps,
-            callback=callback,
-            log_interval=log_interval,
-            eval_env=eval_env,
-            eval_freq=eval_freq,
-            n_eval_episodes=n_eval_episodes,
-            tb_log_name=tb_log_name,
-            eval_log_path=eval_log_path,
-            reset_num_timesteps=reset_num_timesteps,
-        )
-
-    def _excluded_save_params(self) -> List[str]:
-        return super(DQN, self)._excluded_save_params() + ["q_net", "q_net_target"]
-
-    def _get_torch_save_params(self) -> Tuple[List[str], List[str]]:
-        state_dicts = ["policy", "policy.optimizer"]
-
-        return state_dicts, []
diff --git a/spaces/juanhuggingface/ChuanhuChatGPT_Beta/modules/llama_func.py b/spaces/juanhuggingface/ChuanhuChatGPT_Beta/modules/llama_func.py
deleted file mode 100644
index e1c513af1bf6d1569b071eb5fc0ce441d0692f83..0000000000000000000000000000000000000000
--- a/spaces/juanhuggingface/ChuanhuChatGPT_Beta/modules/llama_func.py
+++ /dev/null
@@ -1,166 +0,0 @@
-import os
-import logging
-
-from llama_index import download_loader
-from llama_index import (
-    Document,
-    LLMPredictor,
-    PromptHelper,
-    QuestionAnswerPrompt,
-    RefinePrompt,
-)
-import colorama
-import PyPDF2
-from tqdm import tqdm
-
-from modules.presets import *
-from modules.utils import *
-from modules.config import local_embedding
-
-
-def get_index_name(file_src):
-    file_paths = [x.name for x in file_src]
-    file_paths.sort(key=lambda x: os.path.basename(x))
-
-    md5_hash = hashlib.md5()
-    for file_path in file_paths:
-        with open(file_path, "rb") as f:
-            while chunk := f.read(8192):
-                md5_hash.update(chunk)
-
-    return md5_hash.hexdigest()
-
-
-def block_split(text):
-    blocks = []
-    while len(text) > 0:
-        blocks.append(Document(text[:1000]))
-        text = text[1000:]
-    return blocks
-
-
-def get_documents(file_src):
-    documents = []
-    logging.debug("Loading documents...")
-    logging.debug(f"file_src: {file_src}")
-    for file in file_src:
-        filepath = file.name
-        filename = os.path.basename(filepath)
-        file_type = os.path.splitext(filepath)[1]
-        logging.info(f"loading file: {filename}")
-        try:
-            if file_type == ".pdf":
-                logging.debug("Loading PDF...")
-                try:
-                    from modules.pdf_func import parse_pdf
-                    from modules.config import advance_docs
-
-                    two_column = advance_docs["pdf"].get("two_column", False)
-                    pdftext = parse_pdf(filepath, two_column).text
-                except:
-                    pdftext = ""
-                    with open(filepath, "rb") as pdfFileObj:
-                        pdfReader = PyPDF2.PdfReader(pdfFileObj)
-                        for page in tqdm(pdfReader.pages):
-                            pdftext += page.extract_text()
-                text_raw = pdftext
-            elif file_type == ".docx":
-                logging.debug("Loading Word...")
-                DocxReader = download_loader("DocxReader")
-                loader = DocxReader()
-                text_raw = loader.load_data(file=filepath)[0].text
-            elif file_type == ".epub":
-                logging.debug("Loading EPUB...")
-                EpubReader = download_loader("EpubReader")
-                loader = EpubReader()
-                text_raw = loader.load_data(file=filepath)[0].text
-            elif file_type == ".xlsx":
-                logging.debug("Loading Excel...")
-                text_list = excel_to_string(filepath)
-                for elem in text_list:
-                    documents.append(Document(elem))
-                continue
-            else:
-                logging.debug("Loading text file...")
-                with open(filepath, "r", encoding="utf-8") as f:
-                    text_raw = f.read()
-        except Exception as e:
-            logging.error(f"Error loading file: {filename}")
-            pass
-        text = add_space(text_raw)
-        # text = block_split(text)
-        # documents += text
-        documents += [Document(text)]
-    logging.debug("Documents loaded.")
-    return documents
-
-
-def construct_index(
-    api_key,
-    file_src,
-    max_input_size=4096,
-    num_outputs=5,
-    max_chunk_overlap=20,
-    chunk_size_limit=600,
-    embedding_limit=None,
-    separator=" ",
-):
-    from langchain.chat_models import ChatOpenAI
-    from langchain.embeddings.huggingface import HuggingFaceEmbeddings
-    from llama_index import GPTSimpleVectorIndex, ServiceContext, LangchainEmbedding, OpenAIEmbedding
-
-    if api_key:
-        os.environ["OPENAI_API_KEY"] = api_key
-    else:
-        # 由于一个依赖的愚蠢的设计，这里必须要有一个API KEY
-        os.environ["OPENAI_API_KEY"] = "sk-xxxxxxx"
-    chunk_size_limit = None if chunk_size_limit == 0 else chunk_size_limit
-    embedding_limit = None if embedding_limit == 0 else embedding_limit
-    separator = " " if separator == "" else separator
-
-    prompt_helper = PromptHelper(
-        max_input_size=max_input_size,
-        num_output=num_outputs,
-        max_chunk_overlap=max_chunk_overlap,
-        embedding_limit=embedding_limit,
-        chunk_size_limit=600,
-        separator=separator,
-    )
-    index_name = get_index_name(file_src)
-    if os.path.exists(f"./index/{index_name}.json"):
-        logging.info("找到了缓存的索引文件，加载中……")
-        return GPTSimpleVectorIndex.load_from_disk(f"./index/{index_name}.json")
-    else:
-        try:
-            documents = get_documents(file_src)
-            if local_embedding:
-                embed_model = LangchainEmbedding(HuggingFaceEmbeddings(model_name = "sentence-transformers/distiluse-base-multilingual-cased-v2"))
-            else:
-                embed_model = OpenAIEmbedding()
-            logging.info("构建索引中……")
-            with retrieve_proxy():
-                service_context = ServiceContext.from_defaults(
-                    prompt_helper=prompt_helper,
-                    chunk_size_limit=chunk_size_limit,
-                    embed_model=embed_model,
-                )
-                index = GPTSimpleVectorIndex.from_documents(
-                    documents, service_context=service_context
-                )
-            logging.debug("索引构建完成！")
-            os.makedirs("./index", exist_ok=True)
-            index.save_to_disk(f"./index/{index_name}.json")
-            logging.debug("索引已保存至本地!")
-            return index
-
-        except Exception as e:
-            logging.error("索引构建失败！", e)
-            print(e)
-            return None
-
-
-def add_space(text):
-    punctuations = {"，": "， ", "。": "。 ", "？": "？ ", "！": "！ ", "：": "： ", "；": "； "}
-    for cn_punc, en_punc in punctuations.items():
-        text = text.replace(cn_punc, en_punc)
-    return text
diff --git a/spaces/justest/gpt4free/g4f/.v1/unfinished/t3nsor/__init__.py b/spaces/justest/gpt4free/g4f/.v1/unfinished/t3nsor/__init__.py
deleted file mode 100644
index 9b588e982231638b8aafb5491e28fb0236f133e0..0000000000000000000000000000000000000000
--- a/spaces/justest/gpt4free/g4f/.v1/unfinished/t3nsor/__init__.py
+++ /dev/null
@@ -1,136 +0,0 @@
-from time import time
-
-from requests import post
-
-headers = {
-    'authority': 'www.t3nsor.tech',
-    'accept': '*/*',
-    'accept-language': 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3',
-    'cache-control': 'no-cache',
-    'content-type': 'application/json',
-    'origin': 'https://www.t3nsor.tech',
-    'pragma': 'no-cache',
-    'referer': 'https://www.t3nsor.tech/',
-    'sec-ch-ua': '"Chromium";v="112", "Google Chrome";v="112", "Not:A-Brand";v="99"',
-    'sec-ch-ua-mobile': '?0',
-    'sec-ch-ua-platform': '"macOS"',
-    'sec-fetch-dest': 'empty',
-    'sec-fetch-mode': 'cors',
-    'sec-fetch-site': 'same-origin',
-    'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36',
-}
-
-
-class T3nsorResponse:
-    class Completion:
-        class Choices:
-            def __init__(self, choice: dict) -> None:
-                self.text = choice['text']
-                self.content = self.text.encode()
-                self.index = choice['index']
-                self.logprobs = choice['logprobs']
-                self.finish_reason = choice['finish_reason']
-
-            def __repr__(self) -> str:
-                return f'''<__main__.APIResponse.Completion.Choices(\n    text           = {self.text.encode()},\n    index          = {self.index},\n    logprobs       = {self.logprobs},\n    finish_reason  = {self.finish_reason})object at 0x1337>'''
-
-        def __init__(self, choices: dict) -> None:
-            self.choices = [self.Choices(choice) for choice in choices]
-
-    class Usage:
-        def __init__(self, usage_dict: dict) -> None:
-            self.prompt_tokens = usage_dict['prompt_chars']
-            self.completion_tokens = usage_dict['completion_chars']
-            self.total_tokens = usage_dict['total_chars']
-
-        def __repr__(self):
-            return f'''<__main__.APIResponse.Usage(\n    prompt_tokens      = {self.prompt_tokens},\n    completion_tokens  = {self.completion_tokens},\n    total_tokens       = {self.total_tokens})object at 0x1337>'''
-
-    def __init__(self, response_dict: dict) -> None:
-        self.response_dict = response_dict
-        self.id = response_dict['id']
-        self.object = response_dict['object']
-        self.created = response_dict['created']
-        self.model = response_dict['model']
-        self.completion = self.Completion(response_dict['choices'])
-        self.usage = self.Usage(response_dict['usage'])
-
-    def json(self) -> dict:
-        return self.response_dict
-
-
-class Completion:
-    model = {
-        'model': {
-            'id': 'gpt-3.5-turbo',
-            'name': 'Default (GPT-3.5)'
-        }
-    }
-
-    def create(
-            prompt: str = 'hello world',
-            messages: list = []) -> T3nsorResponse:
-        response = post('https://www.t3nsor.tech/api/chat', headers=headers, json=Completion.model | {
-            'messages': messages,
-            'key': '',
-            'prompt': prompt
-        })
-
-        return T3nsorResponse({
-            'id': f'cmpl-1337-{int(time())}',
-            'object': 'text_completion',
-            'created': int(time()),
-            'model': Completion.model,
-            'choices': [{
-                'text': response.text,
-                'index': 0,
-                'logprobs': None,
-                'finish_reason': 'stop'
-            }],
-            'usage': {
-                'prompt_chars': len(prompt),
-                'completion_chars': len(response.text),
-                'total_chars': len(prompt) + len(response.text)
-            }
-        })
-
-
-class StreamCompletion:
-    model = {
-        'model': {
-            'id': 'gpt-3.5-turbo',
-            'name': 'Default (GPT-3.5)'
-        }
-    }
-
-    def create(
-            prompt: str = 'hello world',
-            messages: list = []) -> T3nsorResponse:
-        print('t3nsor api is down, this may not work, refer to another module')
-
-        response = post('https://www.t3nsor.tech/api/chat', headers=headers, stream=True, json=Completion.model | {
-            'messages': messages,
-            'key': '',
-            'prompt': prompt
-        })
-
-        for chunk in response.iter_content(chunk_size=2046):
-            yield T3nsorResponse({
-                'id': f'cmpl-1337-{int(time())}',
-                'object': 'text_completion',
-                'created': int(time()),
-                'model': Completion.model,
-
-                'choices': [{
-                    'text': chunk.decode(),
-                    'index': 0,
-                    'logprobs': None,
-                    'finish_reason': 'stop'
-                }],
-
-                'usage': {
-                    'prompt_chars': len(prompt),
-                    'completion_chars': len(chunk.decode()),
-                    'total_chars': len(prompt) + len(chunk.decode())
-                }
-            })
diff --git a/spaces/k2-fsa/automatic-speech-recognition/decode.py b/spaces/k2-fsa/automatic-speech-recognition/decode.py
deleted file mode 100644
index 9e593d57457b10dd47bac4c2747811eb7a64d243..0000000000000000000000000000000000000000
--- a/spaces/k2-fsa/automatic-speech-recognition/decode.py
+++ /dev/null
@@ -1,121 +0,0 @@
-# Copyright      2022  Xiaomi Corp.        (authors: Fangjun Kuang)
-#
-# Copied from https://github.com/k2-fsa/sherpa/blob/master/sherpa/bin/conformer_rnnt/decode.py
-#
-# See LICENSE for clarification regarding multiple authors
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import math
-from typing import List
-
-import torch
-from sherpa import RnntConformerModel, greedy_search, modified_beam_search
-from torch.nn.utils.rnn import pad_sequence
-
-LOG_EPS = math.log(1e-10)
-
-
-@torch.no_grad()
-def run_model_and_do_greedy_search(
-    model: RnntConformerModel,
-    features: List[torch.Tensor],
-) -> List[List[int]]:
-    """Run RNN-T model with the given features and use greedy search
-    to decode the output of the model.
-
-    Args:
-      model:
-        The RNN-T model.
-      features:
-        A list of 2-D tensors. Each entry is of shape
-        (num_frames, feature_dim).
-    Returns:
-      Return a list-of-list containing the decoding token IDs.
-    """
-    features_length = torch.tensor(
-        [f.size(0) for f in features],
-        dtype=torch.int64,
-    )
-    features = pad_sequence(
-        features,
-        batch_first=True,
-        padding_value=LOG_EPS,
-    )
-
-    device = model.device
-    features = features.to(device)
-    features_length = features_length.to(device)
-
-    encoder_out, encoder_out_length = model.encoder(
-        features=features,
-        features_length=features_length,
-    )
-
-    hyp_tokens = greedy_search(
-        model=model,
-        encoder_out=encoder_out,
-        encoder_out_length=encoder_out_length.cpu(),
-    )
-    return hyp_tokens
-
-
-@torch.no_grad()
-def run_model_and_do_modified_beam_search(
-    model: RnntConformerModel,
-    features: List[torch.Tensor],
-    num_active_paths: int,
-) -> List[List[int]]:
-    """Run RNN-T model with the given features and use greedy search
-    to decode the output of the model.
-
-    Args:
-      model:
-        The RNN-T model.
-      features:
-        A list of 2-D tensors. Each entry is of shape
-        (num_frames, feature_dim).
-      num_active_paths:
-        Used only when decoding_method is modified_beam_search.
-        It specifies number of active paths for each utterance. Due to
-        merging paths with identical token sequences, the actual number
-        may be less than "num_active_paths".
-    Returns:
-      Return a list-of-list containing the decoding token IDs.
-    """
-    features_length = torch.tensor(
-        [f.size(0) for f in features],
-        dtype=torch.int64,
-    )
-    features = pad_sequence(
-        features,
-        batch_first=True,
-        padding_value=LOG_EPS,
-    )
-
-    device = model.device
-    features = features.to(device)
-    features_length = features_length.to(device)
-
-    encoder_out, encoder_out_length = model.encoder(
-        features=features,
-        features_length=features_length,
-    )
-
-    hyp_tokens = modified_beam_search(
-        model=model,
-        encoder_out=encoder_out,
-        encoder_out_length=encoder_out_length.cpu(),
-        num_active_paths=num_active_paths,
-    )
-    return hyp_tokens
diff --git a/spaces/kargaranamir/selenium-screenshot-gradio/app.py b/spaces/kargaranamir/selenium-screenshot-gradio/app.py
deleted file mode 100644
index 324a6ecfe62ef85fb28ac55d205cea9fb01e610c..0000000000000000000000000000000000000000
--- a/spaces/kargaranamir/selenium-screenshot-gradio/app.py
+++ /dev/null
@@ -1,35 +0,0 @@
-import gradio as gr
-from selenium import webdriver
-from selenium.common.exceptions import WebDriverException
-from PIL import Image
-from io import BytesIO
-
-def take_screenshot(url):
-    options = webdriver.ChromeOptions()
-    options.add_argument('--headless')
-    options.add_argument('--no-sandbox')
-    options.add_argument('--disable-dev-shm-usage')
-
-    try:
-        wd = webdriver.Chrome(options=options)
-        wd.set_window_size(1080, 720)  # Adjust the window size here
-        wd.get(url)
-        wd.implicitly_wait(10)
-        screenshot = wd.get_screenshot_as_png()
-    except WebDriverException as e:
-        return Image.new('RGB', (1, 1))
-    finally:
-        if wd:
-            wd.quit()
-
-    return Image.open(BytesIO(screenshot))
-
-iface = gr.Interface(
-    fn=take_screenshot,
-    inputs=gr.inputs.Textbox(label="Website URL", default="https://kargaranamir.github.io"),
-    outputs=gr.Image(type="pil", height=360, width=540),  # Adjust the image size here
-    title="Website Screenshot",
-    description="Take a screenshot of a website.",
-)
-
-iface.launch()
diff --git a/spaces/keneonyeachonam/AutoML_UsingStreamlit_Plotly_020923/app.py b/spaces/keneonyeachonam/AutoML_UsingStreamlit_Plotly_020923/app.py
deleted file mode 100644
index 9a535fc892d806115a655a01f4d59f985c58b58b..0000000000000000000000000000000000000000
--- a/spaces/keneonyeachonam/AutoML_UsingStreamlit_Plotly_020923/app.py
+++ /dev/null
@@ -1,28 +0,0 @@
-import streamlit as st
-import pandas as pd
-import plotly.express as px
-
-st.set_page_config(page_title="AutoML Streamlit App", page_icon=":robot:", layout="wide")
-
-st.title("AutoML Streamlit App")
-
-# Upload a CSV dataset
-uploaded_file = st.file_uploader("Upload your dataset", type=["csv"])
-if uploaded_file is not None:
-    # Load the dataset and display the first 5 rows
-    df = pd.read_csv(uploaded_file)
-    st.dataframe(df.head())
-
-    # Generate a treemap or sunburst plot based on data types
-    numerical_cols = df.select_dtypes(include=["float", "int"]).columns
-    categorical_cols = df.select_dtypes(include=["object"]).columns
-
-    if len(numerical_cols) >= 2:
-        fig = px.scatter_matrix(df, dimensions=numerical_cols)
-        st.plotly_chart(fig)
-    elif len(categorical_cols) >= 2:
-        fig = px.treemap(df, path=categorical_cols)
-        st.plotly_chart(fig)
-    else:
-        fig = px.sunburst(df, path=categorical_cols + numerical_cols)
-        st.plotly_chart(fig)
\ No newline at end of file
diff --git a/spaces/keras-dreambooth/ignatius/README.md b/spaces/keras-dreambooth/ignatius/README.md
deleted file mode 100644
index aeb4eac56c6e2650b1595f8cf279de1ffa7017d8..0000000000000000000000000000000000000000
--- a/spaces/keras-dreambooth/ignatius/README.md
+++ /dev/null
@@ -1,16 +0,0 @@
----
-title: Ignatius Farray - "All right!!!"
-emoji: 🤡
-colorFrom: yellow
-colorTo: purple
-sdk: gradio
-sdk_version: 3.21.0
-app_file: app.py
-pinned: false
-license: openrail
-tags:
-  - keras-dreambooth
-  - wildcard
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/keremberke/aerial-sheep-object-detection/app.py b/spaces/keremberke/aerial-sheep-object-detection/app.py
deleted file mode 100644
index f427db2292282eebee60de7daa052d4f14c1355e..0000000000000000000000000000000000000000
--- a/spaces/keremberke/aerial-sheep-object-detection/app.py
+++ /dev/null
@@ -1,53 +0,0 @@
-
-import json
-import gradio as gr
-import yolov5
-from PIL import Image
-from huggingface_hub import hf_hub_download
-
-app_title = "Aerial Sheep Object Detection"
-models_ids = ['keremberke/yolov5n-aerial-sheep', 'keremberke/yolov5s-aerial-sheep', 'keremberke/yolov5m-aerial-sheep']
-article = f"<p style='text-align: center'> <a href='https://huggingface.co/{models_ids[-1]}'>model</a> | <a href='https://huggingface.co/keremberke/aerial-sheep-object-detection'>dataset</a> | <a href='https://github.com/keremberke/awesome-yolov5-models'>awesome-yolov5-models</a> </p>"
-
-current_model_id = models_ids[-1]
-model = yolov5.load(current_model_id)
-
-examples = [['test_images/DJI_0039_MOV-252_jpg.rf.a9d3f531dc347711c06539af59ca7329.jpg', 0.25, 'keremberke/yolov5m-aerial-sheep'], ['test_images/DJI_0040_MOV-141_jpg.rf.b2b23a4bd86ee5f50ff4a063ab4671ca.jpg', 0.25, 'keremberke/yolov5m-aerial-sheep'], ['test_images/DJI_0043_MOV-102_jpg.rf.4f0018c8c5de23731256755050f0819a.jpg', 0.25, 'keremberke/yolov5m-aerial-sheep'], ['test_images/DJI_0043_MOV-161_jpg.rf.a2197218b8c9f58272e59d7a8c6cf493.jpg', 0.25, 'keremberke/yolov5m-aerial-sheep'], ['test_images/DJI_0043_MOV-84_jpg.rf.22ea78648b21f64c276ab348ba82cf49.jpg', 0.25, 'keremberke/yolov5m-aerial-sheep'], ['test_images/img_373_jpg.rf.494e557cd96f79f20750ab7942c9d9c5.jpg', 0.25, 'keremberke/yolov5m-aerial-sheep']]
-
-
-def predict(image, threshold=0.25, model_id=None):
-    # update model if required
-    global current_model_id
-    global model
-    if model_id != current_model_id:
-        model = yolov5.load(model_id)
-        current_model_id = model_id
-
-    # get model input size
-    config_path = hf_hub_download(repo_id=model_id, filename="config.json")
-    with open(config_path, "r") as f:
-        config = json.load(f)
-    input_size = config["input_size"]
-
-    # perform inference
-    model.conf = threshold
-    results = model(image, size=input_size)
-    numpy_image = results.render()[0]
-    output_image = Image.fromarray(numpy_image)
-    return output_image
-
-
-gr.Interface(
-    title=app_title,
-    description="Created by 'keremberke'",
-    article=article,
-    fn=predict,
-    inputs=[
-        gr.Image(type="pil"),
-        gr.Slider(maximum=1, step=0.01, value=0.25),
-        gr.Dropdown(models_ids, value=models_ids[-1]),
-    ],
-    outputs=gr.Image(type="pil"),
-    examples=examples,
-    cache_examples=True if examples else False,
-).launch(enable_queue=True)
diff --git a/spaces/kevinwang676/ChatGLM2-VC-SadTalker/speaker_encoder/data_objects/random_cycler.py b/spaces/kevinwang676/ChatGLM2-VC-SadTalker/speaker_encoder/data_objects/random_cycler.py
deleted file mode 100644
index c405db6b27f46d874d8feb37e3f9c1e12c251109..0000000000000000000000000000000000000000
--- a/spaces/kevinwang676/ChatGLM2-VC-SadTalker/speaker_encoder/data_objects/random_cycler.py
+++ /dev/null
@@ -1,37 +0,0 @@
-import random
-
-class RandomCycler:
-    """
-    Creates an internal copy of a sequence and allows access to its items in a constrained random 
-    order. For a source sequence of n items and one or several consecutive queries of a total 
-    of m items, the following guarantees hold (one implies the other):
-        - Each item will be returned between m // n and ((m - 1) // n) + 1 times.
-        - Between two appearances of the same item, there may be at most 2 * (n - 1) other items.
-    """
-    
-    def __init__(self, source):
-        if len(source) == 0:
-            raise Exception("Can't create RandomCycler from an empty collection")
-        self.all_items = list(source)
-        self.next_items = []
-    
-    def sample(self, count: int):
-        shuffle = lambda l: random.sample(l, len(l))
-        
-        out = []
-        while count > 0:
-            if count >= len(self.all_items):
-                out.extend(shuffle(list(self.all_items)))
-                count -= len(self.all_items)
-                continue
-            n = min(count, len(self.next_items))
-            out.extend(self.next_items[:n])
-            count -= n
-            self.next_items = self.next_items[n:]
-            if len(self.next_items) == 0:
-                self.next_items = shuffle(list(self.all_items))
-        return out
-    
-    def __next__(self):
-        return self.sample(1)[0]
-
diff --git a/spaces/kevinwang676/ChatGLM2-VC-SadTalker/src/facerender/sync_batchnorm/__init__.py b/spaces/kevinwang676/ChatGLM2-VC-SadTalker/src/facerender/sync_batchnorm/__init__.py
deleted file mode 100644
index bc8709d92c610b36e0bcbd7da20c1eb41dc8cfcf..0000000000000000000000000000000000000000
--- a/spaces/kevinwang676/ChatGLM2-VC-SadTalker/src/facerender/sync_batchnorm/__init__.py
+++ /dev/null
@@ -1,12 +0,0 @@
-# -*- coding: utf-8 -*-
-# File   : __init__.py
-# Author : Jiayuan Mao
-# Email  : maojiayuan@gmail.com
-# Date   : 27/01/2018
-# 
-# This file is part of Synchronized-BatchNorm-PyTorch.
-# https://github.com/vacancy/Synchronized-BatchNorm-PyTorch
-# Distributed under MIT License.
-
-from .batchnorm import SynchronizedBatchNorm1d, SynchronizedBatchNorm2d, SynchronizedBatchNorm3d
-from .replicate import DataParallelWithCallback, patch_replication_callback
diff --git a/spaces/kevinwang676/vits-fast-finetuning-pcr/text/symbols.py b/spaces/kevinwang676/vits-fast-finetuning-pcr/text/symbols.py
deleted file mode 100644
index 789e9df25d3d93d1976ef22d15d77f51d170ed00..0000000000000000000000000000000000000000
--- a/spaces/kevinwang676/vits-fast-finetuning-pcr/text/symbols.py
+++ /dev/null
@@ -1,76 +0,0 @@
-'''
-Defines the set of symbols used in text input to the model.
-'''
-
-# japanese_cleaners
-# _pad        = '_'
-# _punctuation = ',.!?-'
-# _letters = 'AEINOQUabdefghijkmnoprstuvwyzʃʧ↓↑ '
-
-
-'''# japanese_cleaners2
-_pad        = '_'
-_punctuation = ',.!?-~…'
-_letters = 'AEINOQUabdefghijkmnoprstuvwyzʃʧʦ↓↑ '
-'''
-
-
-'''# korean_cleaners
-_pad        = '_'
-_punctuation = ',.!?…~'
-_letters = 'ㄱㄴㄷㄹㅁㅂㅅㅇㅈㅊㅋㅌㅍㅎㄲㄸㅃㅆㅉㅏㅓㅗㅜㅡㅣㅐㅔ '
-'''
-
-'''# chinese_cleaners
-_pad        = '_'
-_punctuation = '，。！？—…'
-_letters = 'ㄅㄆㄇㄈㄉㄊㄋㄌㄍㄎㄏㄐㄑㄒㄓㄔㄕㄖㄗㄘㄙㄚㄛㄜㄝㄞㄟㄠㄡㄢㄣㄤㄥㄦㄧㄨㄩˉˊˇˋ˙ '
-'''
-
-# # zh_ja_mixture_cleaners
-# _pad        = '_'
-# _punctuation = ',.!?-~…'
-# _letters = 'AEINOQUabdefghijklmnoprstuvwyzʃʧʦɯɹəɥ⁼ʰ`→↓↑ '
-
-
-'''# sanskrit_cleaners
-_pad        = '_'
-_punctuation = '।'
-_letters = 'ँंःअआइईउऊऋएऐओऔकखगघङचछजझञटठडढणतथदधनपफबभमयरलळवशषसहऽािीुूृॄेैोौ्ॠॢ '
-'''
-
-'''# cjks_cleaners
-_pad        = '_'
-_punctuation = ',.!?-~…'
-_letters = 'NQabdefghijklmnopstuvwxyzʃʧʥʦɯɹəɥçɸɾβŋɦː⁼ʰ`^#*=→↓↑ '
-'''
-
-'''# thai_cleaners
-_pad        = '_'
-_punctuation = '.!? '
-_letters = 'กขฃคฆงจฉชซฌญฎฏฐฑฒณดตถทธนบปผฝพฟภมยรฤลวศษสหฬอฮฯะัาำิีึืุูเแโใไๅๆ็่้๊๋์'
-'''
-
-# # cjke_cleaners2
-_pad        = '_'
-_punctuation = ',.!?-~…'
-_letters = 'NQabdefghijklmnopstuvwxyzɑæʃʑçɯɪɔɛɹðəɫɥɸʊɾʒθβŋɦ⁼ʰ`^#*=ˈˌ→↓↑ '
-
-
-'''# shanghainese_cleaners
-_pad        = '_'
-_punctuation = ',.!?…'
-_letters = 'abdfghiklmnopstuvyzøŋȵɑɔɕəɤɦɪɿʑʔʰ̩̃ᴀᴇ15678 '
-'''
-
-'''# chinese_dialect_cleaners
-_pad        = '_'
-_punctuation = ',.!?~…─'
-_letters = '#Nabdefghijklmnoprstuvwxyzæçøŋœȵɐɑɒɓɔɕɗɘəɚɛɜɣɤɦɪɭɯɵɷɸɻɾɿʂʅʊʋʌʏʑʔʦʮʰʷˀː˥˦˧˨˩̥̩̃̚ᴀᴇ↑↓∅ⱼ '
-'''
-
-# Export all symbols:
-symbols = [_pad] + list(_punctuation) + list(_letters)
-
-# Special symbol ids
-SPACE_ID = symbols.index(" ")
diff --git a/spaces/kira4424/Tacotron-zero-short-voice-clone/encoder/data_objects/__init__.py b/spaces/kira4424/Tacotron-zero-short-voice-clone/encoder/data_objects/__init__.py
deleted file mode 100644
index ef04ade68544d0477a7f6deb4e7d51e97f592910..0000000000000000000000000000000000000000
--- a/spaces/kira4424/Tacotron-zero-short-voice-clone/encoder/data_objects/__init__.py
+++ /dev/null
@@ -1,2 +0,0 @@
-from encoder.data_objects.speaker_verification_dataset import SpeakerVerificationDataset
-from encoder.data_objects.speaker_verification_dataset import SpeakerVerificationDataLoader
diff --git a/spaces/kira4424/Tacotron-zero-short-voice-clone/mkgui/base/ui/streamlit_ui.py b/spaces/kira4424/Tacotron-zero-short-voice-clone/mkgui/base/ui/streamlit_ui.py
deleted file mode 100644
index 479fe1c3e3ec6cd9f2c785c777ea9fe892853d8b..0000000000000000000000000000000000000000
--- a/spaces/kira4424/Tacotron-zero-short-voice-clone/mkgui/base/ui/streamlit_ui.py
+++ /dev/null
@@ -1,888 +0,0 @@
-import datetime
-import inspect
-import mimetypes
-import sys
-from os import getcwd, unlink
-from platform import system
-from tempfile import NamedTemporaryFile
-from typing import Any, Callable, Dict, List, Type
-from PIL import Image
-
-import pandas as pd
-import streamlit as st
-from fastapi.encoders import jsonable_encoder
-from loguru import logger
-from pydantic import BaseModel, ValidationError, parse_obj_as
-
-from mkgui.base import Opyrator
-from mkgui.base.core import name_to_title
-from mkgui.base.ui import schema_utils
-from mkgui.base.ui.streamlit_utils import CUSTOM_STREAMLIT_CSS
-
-STREAMLIT_RUNNER_SNIPPET = """
-from mkgui.base.ui import render_streamlit_ui
-from mkgui.base import Opyrator
-
-import streamlit as st
-
-# TODO: Make it configurable
-# Page config can only be setup once
-st.set_page_config(
-    page_title="MockingBird", 
-    page_icon="🧊",
-    layout="wide")
-
-render_streamlit_ui()
-"""
-
-# with st.spinner("Loading MockingBird GUI. Please wait..."):
-#     opyrator = Opyrator("{opyrator_path}")
-
-
-def launch_ui(port: int = 8501) -> None:
-    with NamedTemporaryFile(
-        suffix=".py", mode="w", encoding="utf-8", delete=False
-    ) as f:
-        f.write(STREAMLIT_RUNNER_SNIPPET)
-        f.seek(0)
-
-        import subprocess
-
-        python_path = f'PYTHONPATH="$PYTHONPATH:{getcwd()}"'
-        if system() == "Windows":
-            python_path = f"set PYTHONPATH=%PYTHONPATH%;{getcwd()} &&"
-            subprocess.run(
-                f"""set STREAMLIT_GLOBAL_SHOW_WARNING_ON_DIRECT_EXECUTION=false""",
-                shell=True,
-            )
-
-        subprocess.run(
-            f"""{python_path} "{sys.executable}" -m streamlit run --server.port={port} --server.headless=True --runner.magicEnabled=False --server.maxUploadSize=50  --browser.gatherUsageStats=False {f.name}""",
-            shell=True,
-        )
-
-        f.close()
-        unlink(f.name)
-
-
-def function_has_named_arg(func: Callable, parameter: str) -> bool:
-    try:
-        sig = inspect.signature(func)
-        for param in sig.parameters.values():
-            if param.name == "input":
-                return True
-    except Exception:
-        return False
-    return False
-
-
-def has_output_ui_renderer(data_item: BaseModel) -> bool:
-    return hasattr(data_item, "render_output_ui")
-
-
-def has_input_ui_renderer(input_class: Type[BaseModel]) -> bool:
-    return hasattr(input_class, "render_input_ui")
-
-
-def is_compatible_audio(mime_type: str) -> bool:
-    return mime_type in ["audio/mpeg", "audio/ogg", "audio/wav"]
-
-
-def is_compatible_image(mime_type: str) -> bool:
-    return mime_type in ["image/png", "image/jpeg"]
-
-
-def is_compatible_video(mime_type: str) -> bool:
-    return mime_type in ["video/mp4"]
-
-
-class InputUI:
-    def __init__(self, session_state, input_class: Type[BaseModel]):
-        self._session_state = session_state
-        self._input_class = input_class
-
-        self._schema_properties = input_class.schema(by_alias=True).get(
-            "properties", {}
-        )
-        self._schema_references = input_class.schema(by_alias=True).get(
-            "definitions", {}
-        )
-
-    def render_ui(self, streamlit_app_root) -> None:
-        if has_input_ui_renderer(self._input_class):
-            # The input model has a rendering function
-            # The rendering also returns the current state of input data
-            self._session_state.input_data = self._input_class.render_input_ui(  # type: ignore
-                st, self._session_state.input_data
-            )
-            return
-
-        # print(self._schema_properties)
-        for property_key in self._schema_properties.keys():
-            property = self._schema_properties[property_key]
-
-            if not property.get("title"):
-                # Set property key as fallback title
-                property["title"] = name_to_title(property_key)
-
-            try:
-                if "input_data" in self._session_state:
-                    self._store_value(
-                        property_key,
-                        self._render_property(streamlit_app_root, property_key, property),
-                    )
-            except Exception as e:
-                print("Exception!", e)
-                pass
-
-    def _get_default_streamlit_input_kwargs(self, key: str, property: Dict) -> Dict:
-        streamlit_kwargs = {
-            "label": property.get("title"),
-            "key": key,
-        }
-
-        if property.get("description"):
-            streamlit_kwargs["help"] = property.get("description")
-        return streamlit_kwargs
-
-    def _store_value(self, key: str, value: Any) -> None:
-        data_element = self._session_state.input_data
-        key_elements = key.split(".")
-        for i, key_element in enumerate(key_elements):
-            if i == len(key_elements) - 1:
-                # add value to this element
-                data_element[key_element] = value
-                return
-            if key_element not in data_element:
-                data_element[key_element] = {}
-            data_element = data_element[key_element]
-
-    def _get_value(self, key: str) -> Any:
-        data_element = self._session_state.input_data
-        key_elements = key.split(".")
-        for i, key_element in enumerate(key_elements):
-            if i == len(key_elements) - 1:
-                # add value to this element
-                if key_element not in data_element:
-                    return None
-                return data_element[key_element]
-            if key_element not in data_element:
-                data_element[key_element] = {}
-            data_element = data_element[key_element]
-        return None
-
-    def _render_single_datetime_input(
-        self, streamlit_app: st, key: str, property: Dict
-    ) -> Any:
-        streamlit_kwargs = self._get_default_streamlit_input_kwargs(key, property)
-
-        if property.get("format") == "time":
-            if property.get("default"):
-                try:
-                    streamlit_kwargs["value"] = datetime.time.fromisoformat(  # type: ignore
-                        property.get("default")
-                    )
-                except Exception:
-                    pass
-            return streamlit_app.time_input(**streamlit_kwargs)
-        elif property.get("format") == "date":
-            if property.get("default"):
-                try:
-                    streamlit_kwargs["value"] = datetime.date.fromisoformat(  # type: ignore
-                        property.get("default")
-                    )
-                except Exception:
-                    pass
-            return streamlit_app.date_input(**streamlit_kwargs)
-        elif property.get("format") == "date-time":
-            if property.get("default"):
-                try:
-                    streamlit_kwargs["value"] = datetime.datetime.fromisoformat(  # type: ignore
-                        property.get("default")
-                    )
-                except Exception:
-                    pass
-            with streamlit_app.container():
-                streamlit_app.subheader(streamlit_kwargs.get("label"))
-                if streamlit_kwargs.get("description"):
-                    streamlit_app.text(streamlit_kwargs.get("description"))
-                selected_date = None
-                selected_time = None
-                date_col, time_col = streamlit_app.columns(2)
-                with date_col:
-                    date_kwargs = {"label": "Date", "key": key + "-date-input"}
-                    if streamlit_kwargs.get("value"):
-                        try:
-                            date_kwargs["value"] = streamlit_kwargs.get(  # type: ignore
-                                "value"
-                            ).date()
-                        except Exception:
-                            pass
-                    selected_date = streamlit_app.date_input(**date_kwargs)
-
-                with time_col:
-                    time_kwargs = {"label": "Time", "key": key + "-time-input"}
-                    if streamlit_kwargs.get("value"):
-                        try:
-                            time_kwargs["value"] = streamlit_kwargs.get(  # type: ignore
-                                "value"
-                            ).time()
-                        except Exception:
-                            pass
-                    selected_time = streamlit_app.time_input(**time_kwargs)
-                return datetime.datetime.combine(selected_date, selected_time)
-        else:
-            streamlit_app.warning(
-                "Date format is not supported: " + str(property.get("format"))
-            )
-
-    def _render_single_file_input(
-        self, streamlit_app: st, key: str, property: Dict
-    ) -> Any:
-        streamlit_kwargs = self._get_default_streamlit_input_kwargs(key, property)
-        file_extension = None
-        if "mime_type" in property:
-            file_extension = mimetypes.guess_extension(property["mime_type"])
-
-        uploaded_file = streamlit_app.file_uploader(
-            **streamlit_kwargs, accept_multiple_files=False, type=file_extension
-        )
-        if uploaded_file is None:
-            return None
-
-        bytes = uploaded_file.getvalue()
-        if property.get("mime_type"):
-            if is_compatible_audio(property["mime_type"]):
-                # Show audio
-                streamlit_app.audio(bytes, format=property.get("mime_type"))
-            if is_compatible_image(property["mime_type"]):
-                # Show image
-                streamlit_app.image(bytes)
-            if is_compatible_video(property["mime_type"]):
-                # Show video
-                streamlit_app.video(bytes, format=property.get("mime_type"))
-        return bytes
-
-    def _render_single_string_input(
-        self, streamlit_app: st, key: str, property: Dict
-    ) -> Any:
-        streamlit_kwargs = self._get_default_streamlit_input_kwargs(key, property)
-
-        if property.get("default"):
-            streamlit_kwargs["value"] = property.get("default")
-        elif property.get("example"):
-            # TODO: also use example for other property types
-            # Use example as value if it is provided
-            streamlit_kwargs["value"] = property.get("example")
-
-        if property.get("maxLength") is not None:
-            streamlit_kwargs["max_chars"] = property.get("maxLength")
-
-        if (
-            property.get("format")
-            or (
-                property.get("maxLength") is not None
-                and int(property.get("maxLength")) < 140  # type: ignore
-            )
-            or property.get("writeOnly")
-        ):
-            # If any format is set, use single text input
-            # If max chars is set to less than 140, use single text input
-            # If write only -> password field
-            if property.get("writeOnly"):
-                streamlit_kwargs["type"] = "password"
-            return streamlit_app.text_input(**streamlit_kwargs)
-        else:
-            # Otherwise use multiline text area
-            return streamlit_app.text_area(**streamlit_kwargs)
-
-    def _render_multi_enum_input(
-        self, streamlit_app: st, key: str, property: Dict
-    ) -> Any:
-        streamlit_kwargs = self._get_default_streamlit_input_kwargs(key, property)
-        reference_item = schema_utils.resolve_reference(
-            property["items"]["$ref"], self._schema_references
-        )
-        # TODO: how to select defaults
-        return streamlit_app.multiselect(
-            **streamlit_kwargs, options=reference_item["enum"]
-        )
-
-    def _render_single_enum_input(
-        self, streamlit_app: st, key: str, property: Dict
-    ) -> Any:
-
-        streamlit_kwargs = self._get_default_streamlit_input_kwargs(key, property)
-        reference_item = schema_utils.get_single_reference_item(
-            property, self._schema_references
-        )
-
-        if property.get("default") is not None:
-            try:
-                streamlit_kwargs["index"] = reference_item["enum"].index(
-                    property.get("default")
-                )
-            except Exception:
-                # Use default selection
-                pass
-
-        return streamlit_app.selectbox(
-            **streamlit_kwargs, options=reference_item["enum"]
-        )
-
-    def _render_single_dict_input(
-        self, streamlit_app: st, key: str, property: Dict
-    ) -> Any:
-
-        # Add title and subheader
-        streamlit_app.subheader(property.get("title"))
-        if property.get("description"):
-            streamlit_app.markdown(property.get("description"))
-
-        streamlit_app.markdown("---")
-
-        current_dict = self._get_value(key)
-        if not current_dict:
-            current_dict = {}
-
-        key_col, value_col = streamlit_app.columns(2)
-
-        with key_col:
-            updated_key = streamlit_app.text_input(
-                "Key", value="", key=key + "-new-key"
-            )
-
-        with value_col:
-            # TODO: also add boolean?
-            value_kwargs = {"label": "Value", "key": key + "-new-value"}
-            if property["additionalProperties"].get("type") == "integer":
-                value_kwargs["value"] = 0  # type: ignore
-                updated_value = streamlit_app.number_input(**value_kwargs)
-            elif property["additionalProperties"].get("type") == "number":
-                value_kwargs["value"] = 0.0  # type: ignore
-                value_kwargs["format"] = "%f"
-                updated_value = streamlit_app.number_input(**value_kwargs)
-            else:
-                value_kwargs["value"] = ""
-                updated_value = streamlit_app.text_input(**value_kwargs)
-
-        streamlit_app.markdown("---")
-
-        with streamlit_app.container():
-            clear_col, add_col = streamlit_app.columns([1, 2])
-
-            with clear_col:
-                if streamlit_app.button("Clear Items", key=key + "-clear-items"):
-                    current_dict = {}
-
-            with add_col:
-                if (
-                    streamlit_app.button("Add Item", key=key + "-add-item")
-                    and updated_key
-                ):
-                    current_dict[updated_key] = updated_value
-
-        streamlit_app.write(current_dict)
-
-        return current_dict
-
-    def _render_single_reference(
-        self, streamlit_app: st, key: str, property: Dict
-    ) -> Any:
-        reference_item = schema_utils.get_single_reference_item(
-            property, self._schema_references
-        )
-        return self._render_property(streamlit_app, key, reference_item)
-
-    def _render_multi_file_input(
-        self, streamlit_app: st, key: str, property: Dict
-    ) -> Any:
-        streamlit_kwargs = self._get_default_streamlit_input_kwargs(key, property)
-
-        file_extension = None
-        if "mime_type" in property:
-            file_extension = mimetypes.guess_extension(property["mime_type"])
-
-        uploaded_files = streamlit_app.file_uploader(
-            **streamlit_kwargs, accept_multiple_files=True, type=file_extension
-        )
-        uploaded_files_bytes = []
-        if uploaded_files:
-            for uploaded_file in uploaded_files:
-                uploaded_files_bytes.append(uploaded_file.read())
-        return uploaded_files_bytes
-
-    def _render_single_boolean_input(
-        self, streamlit_app: st, key: str, property: Dict
-    ) -> Any:
-        streamlit_kwargs = self._get_default_streamlit_input_kwargs(key, property)
-
-        if property.get("default"):
-            streamlit_kwargs["value"] = property.get("default")
-        return streamlit_app.checkbox(**streamlit_kwargs)
-
-    def _render_single_number_input(
-        self, streamlit_app: st, key: str, property: Dict
-    ) -> Any:
-        streamlit_kwargs = self._get_default_streamlit_input_kwargs(key, property)
-
-        number_transform = int
-        if property.get("type") == "number":
-            number_transform = float  # type: ignore
-            streamlit_kwargs["format"] = "%f"
-
-        if "multipleOf" in property:
-            # Set stepcount based on multiple of parameter
-            streamlit_kwargs["step"] = number_transform(property["multipleOf"])
-        elif number_transform == int:
-            # Set step size to 1 as default
-            streamlit_kwargs["step"] = 1
-        elif number_transform == float:
-            # Set step size to 0.01 as default
-            # TODO: adapt to default value
-            streamlit_kwargs["step"] = 0.01
-
-        if "minimum" in property:
-            streamlit_kwargs["min_value"] = number_transform(property["minimum"])
-        if "exclusiveMinimum" in property:
-            streamlit_kwargs["min_value"] = number_transform(
-                property["exclusiveMinimum"] + streamlit_kwargs["step"]
-            )
-        if "maximum" in property:
-            streamlit_kwargs["max_value"] = number_transform(property["maximum"])
-
-        if "exclusiveMaximum" in property:
-            streamlit_kwargs["max_value"] = number_transform(
-                property["exclusiveMaximum"] - streamlit_kwargs["step"]
-            )
-
-        if property.get("default") is not None:
-            streamlit_kwargs["value"] = number_transform(property.get("default"))  # type: ignore
-        else:
-            if "min_value" in streamlit_kwargs:
-                streamlit_kwargs["value"] = streamlit_kwargs["min_value"]
-            elif number_transform == int:
-                streamlit_kwargs["value"] = 0
-            else:
-                # Set default value to step
-                streamlit_kwargs["value"] = number_transform(streamlit_kwargs["step"])
-
-        if "min_value" in streamlit_kwargs and "max_value" in streamlit_kwargs:
-            # TODO: Only if less than X steps
-            return streamlit_app.slider(**streamlit_kwargs)
-        else:
-            return streamlit_app.number_input(**streamlit_kwargs)
-
-    def _render_object_input(self, streamlit_app: st, key: str, property: Dict) -> Any:
-        properties = property["properties"]
-        object_inputs = {}
-        for property_key in properties:
-            property = properties[property_key]
-            if not property.get("title"):
-                # Set property key as fallback title
-                property["title"] = name_to_title(property_key)
-            # construct full key based on key parts -> required later to get the value
-            full_key = key + "." + property_key
-            object_inputs[property_key] = self._render_property(
-                streamlit_app, full_key, property
-            )
-        return object_inputs
-
-    def _render_single_object_input(
-        self, streamlit_app: st, key: str, property: Dict
-    ) -> Any:
-        # Add title and subheader
-        title = property.get("title")
-        streamlit_app.subheader(title)
-        if property.get("description"):
-            streamlit_app.markdown(property.get("description"))
-
-        object_reference = schema_utils.get_single_reference_item(
-            property, self._schema_references
-        )
-        return self._render_object_input(streamlit_app, key, object_reference)
-
-    def _render_property_list_input(
-        self, streamlit_app: st, key: str, property: Dict
-    ) -> Any:
-
-        # Add title and subheader
-        streamlit_app.subheader(property.get("title"))
-        if property.get("description"):
-            streamlit_app.markdown(property.get("description"))
-
-        streamlit_app.markdown("---")
-
-        current_list = self._get_value(key)
-        if not current_list:
-            current_list = []
-
-        value_kwargs = {"label": "Value", "key": key + "-new-value"}
-        if property["items"]["type"] == "integer":
-            value_kwargs["value"] = 0  # type: ignore
-            new_value = streamlit_app.number_input(**value_kwargs)
-        elif property["items"]["type"] == "number":
-            value_kwargs["value"] = 0.0  # type: ignore
-            value_kwargs["format"] = "%f"
-            new_value = streamlit_app.number_input(**value_kwargs)
-        else:
-            value_kwargs["value"] = ""
-            new_value = streamlit_app.text_input(**value_kwargs)
-
-        streamlit_app.markdown("---")
-
-        with streamlit_app.container():
-            clear_col, add_col = streamlit_app.columns([1, 2])
-
-            with clear_col:
-                if streamlit_app.button("Clear Items", key=key + "-clear-items"):
-                    current_list = []
-
-            with add_col:
-                if (
-                    streamlit_app.button("Add Item", key=key + "-add-item")
-                    and new_value is not None
-                ):
-                    current_list.append(new_value)
-
-        streamlit_app.write(current_list)
-
-        return current_list
-
-    def _render_object_list_input(
-        self, streamlit_app: st, key: str, property: Dict
-    ) -> Any:
-
-        # TODO: support max_items, and min_items properties
-
-        # Add title and subheader
-        streamlit_app.subheader(property.get("title"))
-        if property.get("description"):
-            streamlit_app.markdown(property.get("description"))
-
-        streamlit_app.markdown("---")
-
-        current_list = self._get_value(key)
-        if not current_list:
-            current_list = []
-
-        object_reference = schema_utils.resolve_reference(
-            property["items"]["$ref"], self._schema_references
-        )
-        input_data = self._render_object_input(streamlit_app, key, object_reference)
-
-        streamlit_app.markdown("---")
-
-        with streamlit_app.container():
-            clear_col, add_col = streamlit_app.columns([1, 2])
-
-            with clear_col:
-                if streamlit_app.button("Clear Items", key=key + "-clear-items"):
-                    current_list = []
-
-            with add_col:
-                if (
-                    streamlit_app.button("Add Item", key=key + "-add-item")
-                    and input_data
-                ):
-                    current_list.append(input_data)
-
-        streamlit_app.write(current_list)
-        return current_list
-
-    def _render_property(self, streamlit_app: st, key: str, property: Dict) -> Any:
-        if schema_utils.is_single_enum_property(property, self._schema_references):
-            return self._render_single_enum_input(streamlit_app, key, property)
-
-        if schema_utils.is_multi_enum_property(property, self._schema_references):
-            return self._render_multi_enum_input(streamlit_app, key, property)
-
-        if schema_utils.is_single_file_property(property):
-            return self._render_single_file_input(streamlit_app, key, property)
-
-        if schema_utils.is_multi_file_property(property):
-            return self._render_multi_file_input(streamlit_app, key, property)
-
-        if schema_utils.is_single_datetime_property(property):
-            return self._render_single_datetime_input(streamlit_app, key, property)
-
-        if schema_utils.is_single_boolean_property(property):
-            return self._render_single_boolean_input(streamlit_app, key, property)
-
-        if schema_utils.is_single_dict_property(property):
-            return self._render_single_dict_input(streamlit_app, key, property)
-
-        if schema_utils.is_single_number_property(property):
-            return self._render_single_number_input(streamlit_app, key, property)
-
-        if schema_utils.is_single_string_property(property):
-            return self._render_single_string_input(streamlit_app, key, property)
-
-        if schema_utils.is_single_object(property, self._schema_references):
-            return self._render_single_object_input(streamlit_app, key, property)
-
-        if schema_utils.is_object_list_property(property, self._schema_references):
-            return self._render_object_list_input(streamlit_app, key, property)
-
-        if schema_utils.is_property_list(property):
-            return self._render_property_list_input(streamlit_app, key, property)
-
-        if schema_utils.is_single_reference(property):
-            return self._render_single_reference(streamlit_app, key, property)
-
-        streamlit_app.warning(
-            "The type of the following property is currently not supported: "
-            + str(property.get("title"))
-        )
-        raise Exception("Unsupported property")
-
-
-class OutputUI:
-    def __init__(self, output_data: Any, input_data: Any):
-        self._output_data = output_data
-        self._input_data = input_data
-
-    def render_ui(self, streamlit_app) -> None:
-        try:
-            if isinstance(self._output_data, BaseModel):
-                self._render_single_output(streamlit_app, self._output_data)
-                return
-            if type(self._output_data) == list:
-                self._render_list_output(streamlit_app, self._output_data)
-                return
-        except Exception as ex:
-            streamlit_app.exception(ex)
-            # Fallback to
-            streamlit_app.json(jsonable_encoder(self._output_data))
-
-    def _render_single_text_property(
-        self, streamlit: st, property_schema: Dict, value: Any
-    ) -> None:
-        # Add title and subheader
-        streamlit.subheader(property_schema.get("title"))
-        if property_schema.get("description"):
-            streamlit.markdown(property_schema.get("description"))
-        if value is None or value == "":
-            streamlit.info("No value returned!")
-        else:
-            streamlit.code(str(value), language="plain")
-
-    def _render_single_file_property(
-        self, streamlit: st, property_schema: Dict, value: Any
-    ) -> None:
-        # Add title and subheader
-        streamlit.subheader(property_schema.get("title"))
-        if property_schema.get("description"):
-            streamlit.markdown(property_schema.get("description"))
-        if value is None or value == "":
-            streamlit.info("No value returned!")
-        else:
-            # TODO: Detect if it is a FileContent instance
-            # TODO: detect if it is base64
-            file_extension = ""
-            if "mime_type" in property_schema:
-                mime_type = property_schema["mime_type"]
-                file_extension = mimetypes.guess_extension(mime_type) or ""
-
-                if is_compatible_audio(mime_type):
-                    streamlit.audio(value.as_bytes(), format=mime_type)
-                    return
-
-                if is_compatible_image(mime_type):
-                    streamlit.image(value.as_bytes())
-                    return
-
-                if is_compatible_video(mime_type):
-                    streamlit.video(value.as_bytes(), format=mime_type)
-                    return
-
-            filename = (
-                (property_schema["title"] + file_extension)
-                .lower()
-                .strip()
-                .replace(" ", "-")
-            )
-            streamlit.markdown(
-                f'<a href="data:application/octet-stream;base64,{value}" download="{filename}"><input type="button" value="Download File"></a>',
-                unsafe_allow_html=True,
-            )
-
-    def _render_single_complex_property(
-        self, streamlit: st, property_schema: Dict, value: Any
-    ) -> None:
-        # Add title and subheader
-        streamlit.subheader(property_schema.get("title"))
-        if property_schema.get("description"):
-            streamlit.markdown(property_schema.get("description"))
-
-        streamlit.json(jsonable_encoder(value))
-
-    def _render_single_output(self, streamlit: st, output_data: BaseModel) -> None:
-        try:
-            if has_output_ui_renderer(output_data):
-                if function_has_named_arg(output_data.render_output_ui, "input"):  # type: ignore
-                    # render method also requests the input data
-                    output_data.render_output_ui(streamlit, input=self._input_data)  # type: ignore
-                else:
-                    output_data.render_output_ui(streamlit)  # type: ignore
-                return
-        except Exception:
-            # Use default auto-generation methods if the custom rendering throws an exception
-            logger.exception(
-                "Failed to execute custom render_output_ui function. Using auto-generation instead"
-            )
-
-        model_schema = output_data.schema(by_alias=False)
-        model_properties = model_schema.get("properties")
-        definitions = model_schema.get("definitions")
-
-        if model_properties:
-            for property_key in output_data.__dict__:
-                property_schema = model_properties.get(property_key)
-                if not property_schema.get("title"):
-                    # Set property key as fallback title
-                    property_schema["title"] = property_key
-
-                output_property_value = output_data.__dict__[property_key]
-
-                if has_output_ui_renderer(output_property_value):
-                    output_property_value.render_output_ui(streamlit)  # type: ignore
-                    continue
-
-                if isinstance(output_property_value, BaseModel):
-                    # Render output recursivly
-                    streamlit.subheader(property_schema.get("title"))
-                    if property_schema.get("description"):
-                        streamlit.markdown(property_schema.get("description"))
-                    self._render_single_output(streamlit, output_property_value)
-                    continue
-
-                if property_schema:
-                    if schema_utils.is_single_file_property(property_schema):
-                        self._render_single_file_property(
-                            streamlit, property_schema, output_property_value
-                        )
-                        continue
-
-                    if (
-                        schema_utils.is_single_string_property(property_schema)
-                        or schema_utils.is_single_number_property(property_schema)
-                        or schema_utils.is_single_datetime_property(property_schema)
-                        or schema_utils.is_single_boolean_property(property_schema)
-                    ):
-                        self._render_single_text_property(
-                            streamlit, property_schema, output_property_value
-                        )
-                        continue
-                    if definitions and schema_utils.is_single_enum_property(
-                        property_schema, definitions
-                    ):
-                        self._render_single_text_property(
-                            streamlit, property_schema, output_property_value.value
-                        )
-                        continue
-
-                    # TODO: render dict as table
-
-                    self._render_single_complex_property(
-                        streamlit, property_schema, output_property_value
-                    )
-            return
-
-    def _render_list_output(self, streamlit: st, output_data: List) -> None:
-        try:
-            data_items: List = []
-            for data_item in output_data:
-                if has_output_ui_renderer(data_item):
-                    # Render using the render function
-                    data_item.render_output_ui(streamlit)  # type: ignore
-                    continue
-                data_items.append(data_item.dict())
-            # Try to show as dataframe
-            streamlit.table(pd.DataFrame(data_items))
-        except Exception:
-            # Fallback to
-            streamlit.json(jsonable_encoder(output_data))
-
-
-def getOpyrator(mode: str) -> Opyrator:
-    if mode == None or mode.startswith('VC'):
-        from mkgui.app_vc import convert
-        return  Opyrator(convert)
-    if mode == None or mode.startswith('预处理'):
-        from mkgui.preprocess import preprocess
-        return  Opyrator(preprocess)
-    if mode == None or mode.startswith('模型训练'):
-        from mkgui.train import train
-        return  Opyrator(train)
-    if mode == None or mode.startswith('模型训练(VC)'):
-        from mkgui.train_vc import train_vc
-        return  Opyrator(train_vc)
-    from mkgui.app import synthesize
-    return Opyrator(synthesize)
-    
-
-def render_streamlit_ui() -> None:
-    # init
-    session_state = st.session_state
-    session_state.input_data = {}
-    # Add custom css settings
-    st.markdown(f"<style>{CUSTOM_STREAMLIT_CSS}</style>", unsafe_allow_html=True)
-
-    with st.spinner("Loading MockingBird GUI. Please wait..."):
-        session_state.mode = st.sidebar.selectbox(
-            '模式选择', 
-            ( "AI拟音", "VC拟音", "预处理", "模型训练", "模型训练(VC)")
-        )
-        if "mode" in session_state:
-            mode = session_state.mode
-        else:
-            mode = ""
-        opyrator = getOpyrator(mode)
-    title = opyrator.name + mode
-
-    col1, col2, _ = st.columns(3)
-    col2.title(title)
-    col2.markdown("欢迎使用MockingBird Web 2")
-
-    image = Image.open('.\\mkgui\\static\\mb.png')
-    col1.image(image)
-
-    st.markdown("---")
-    left, right = st.columns([0.4, 0.6])
-
-    with left:
-        st.header("Control 控制")
-        InputUI(session_state=session_state, input_class=opyrator.input_type).render_ui(st)
-        execute_selected = st.button(opyrator.action)
-        if execute_selected:
-            with st.spinner("Executing operation. Please wait..."):
-                try:
-                    input_data_obj = parse_obj_as(
-                        opyrator.input_type, session_state.input_data
-                    )
-                    session_state.output_data = opyrator(input=input_data_obj)
-                    session_state.latest_operation_input = input_data_obj  # should this really be saved as additional session object?
-                except ValidationError as ex:
-                    st.error(ex)
-                else:
-                    # st.success("Operation executed successfully.")
-                    pass
-
-    with right:
-        st.header("Result 结果")
-        if 'output_data' in session_state:
-            OutputUI(
-                session_state.output_data, session_state.latest_operation_input
-            ).render_ui(st)
-            if st.button("Clear"):
-            # Clear all state
-                for key in st.session_state.keys():
-                    del st.session_state[key]   
-                session_state.input_data = {}
-                st.experimental_rerun()
-        else:
-            # placeholder
-            st.caption("请使用左侧控制板进行输入并运行获得结果")
-        
-   
diff --git a/spaces/kira4424/Tacotron-zero-short-voice-clone/synthesizer/synthesize.py b/spaces/kira4424/Tacotron-zero-short-voice-clone/synthesizer/synthesize.py
deleted file mode 100644
index 49a06b01983ae54c57840a62fa18f7a8508948ee..0000000000000000000000000000000000000000
--- a/spaces/kira4424/Tacotron-zero-short-voice-clone/synthesizer/synthesize.py
+++ /dev/null
@@ -1,97 +0,0 @@
-import torch
-from torch.utils.data import DataLoader
-from synthesizer.synthesizer_dataset import SynthesizerDataset, collate_synthesizer
-from synthesizer.models.tacotron import Tacotron
-from synthesizer.utils.text import text_to_sequence
-from synthesizer.utils.symbols import symbols
-import numpy as np
-from pathlib import Path
-from tqdm import tqdm
-import sys
-
-
-def run_synthesis(in_dir, out_dir, model_dir, hparams):
-    # This generates ground truth-aligned mels for vocoder training
-    synth_dir = Path(out_dir).joinpath("mels_gta")
-    synth_dir.mkdir(parents=True, exist_ok=True)
-    print(str(hparams))
-
-    # Check for GPU
-    if torch.cuda.is_available():
-        device = torch.device("cuda")
-        if hparams.synthesis_batch_size % torch.cuda.device_count() != 0:
-            raise ValueError("`hparams.synthesis_batch_size` must be evenly divisible by n_gpus!")
-    else:
-        device = torch.device("cpu")
-    print("Synthesizer using device:", device)
-
-    # Instantiate Tacotron model
-    model = Tacotron(embed_dims=hparams.tts_embed_dims,
-                     num_chars=len(symbols),
-                     encoder_dims=hparams.tts_encoder_dims,
-                     decoder_dims=hparams.tts_decoder_dims,
-                     n_mels=hparams.num_mels,
-                     fft_bins=hparams.num_mels,
-                     postnet_dims=hparams.tts_postnet_dims,
-                     encoder_K=hparams.tts_encoder_K,
-                     lstm_dims=hparams.tts_lstm_dims,
-                     postnet_K=hparams.tts_postnet_K,
-                     num_highways=hparams.tts_num_highways,
-                     dropout=0., # Use zero dropout for gta mels
-                     stop_threshold=hparams.tts_stop_threshold,
-                     speaker_embedding_size=hparams.speaker_embedding_size).to(device)
-
-    # Load the weights
-    model_dir = Path(model_dir)
-    model_fpath = model_dir.joinpath(model_dir.stem).with_suffix(".pt")
-    print("\nLoading weights at %s" % model_fpath)
-    model.load(model_fpath, device)
-    print("Tacotron weights loaded from step %d" % model.step)
-
-    # Synthesize using same reduction factor as the model is currently trained
-    r = np.int32(model.r)
-
-    # Set model to eval mode (disable gradient and zoneout)
-    model.eval()
-
-    # Initialize the dataset
-    in_dir = Path(in_dir)
-    metadata_fpath = in_dir.joinpath("train.txt")
-    mel_dir = in_dir.joinpath("mels")
-    embed_dir = in_dir.joinpath("embeds")
-    num_workers = 0 if sys.platform.startswith("win") else 2;
-    dataset = SynthesizerDataset(metadata_fpath, mel_dir, embed_dir, hparams)
-    data_loader = DataLoader(dataset,
-                             collate_fn=lambda batch: collate_synthesizer(batch),
-                             batch_size=hparams.synthesis_batch_size,
-                             num_workers=num_workers,
-                             shuffle=False,
-                             pin_memory=True)
-
-    # Generate GTA mels
-    meta_out_fpath = Path(out_dir).joinpath("synthesized.txt")
-    with open(meta_out_fpath, "w") as file:
-        for i, (texts, mels, embeds, idx) in tqdm(enumerate(data_loader), total=len(data_loader)):
-            texts = texts.to(device)
-            mels = mels.to(device)
-            embeds = embeds.to(device)
-
-            # Parallelize model onto GPUS using workaround due to python bug
-            if device.type == "cuda" and torch.cuda.device_count() > 1:
-                _, mels_out, _ , _ = data_parallel_workaround(model, texts, mels, embeds)
-            else:
-                _, mels_out, _, _  = model(texts, mels, embeds)
-
-            for j, k in enumerate(idx):
-                # Note: outputs mel-spectrogram files and target ones have same names, just different folders
-                mel_filename = Path(synth_dir).joinpath(dataset.metadata[k][1])
-                mel_out = mels_out[j].detach().cpu().numpy().T
-
-                # Use the length of the ground truth mel to remove padding from the generated mels
-                mel_out = mel_out[:int(dataset.metadata[k][4])]
-
-                # Write the spectrogram to disk
-                np.save(mel_filename, mel_out, allow_pickle=False)
-
-                # Write metadata into the synthesized file
-                file.write("|".join(dataset.metadata[k]))
diff --git a/spaces/kiyer/pathfinder/pages/1_paper_search.py b/spaces/kiyer/pathfinder/pages/1_paper_search.py
deleted file mode 100644
index b2c919a2a468bb86ac66caca44a9c6ba9a4eae90..0000000000000000000000000000000000000000
--- a/spaces/kiyer/pathfinder/pages/1_paper_search.py
+++ /dev/null
@@ -1,201 +0,0 @@
-import datetime, os
-from langchain.llms import OpenAI
-from langchain.embeddings import OpenAIEmbeddings
-import openai
-import faiss
-import streamlit as st
-import feedparser
-import urllib
-import cloudpickle as cp
-import pickle
-from urllib.request import urlopen
-from summa import summarizer
-import numpy as np
-
-# openai.organization = st.secrets.openai.org
-# openai.api_key = st.secrets.openai.api_key
-openai.organization = st.secrets["org"]
-openai.api_key = st.secrets["api_key"]
-os.environ["OPENAI_API_KEY"] = openai.api_key
-
-@st.cache_data
-def get_feeds_data(url):
-    with open(url, "rb") as fp:
-        data = pickle.load(fp)
-    st.sidebar.success("Loaded data!")
-    # data = cp.load(urlopen(url))
-    # st.sidebar.success("Fetched data from API!")
-    return data
-
-embeddings = OpenAIEmbeddings()
-
-# feeds_link = "https://drive.google.com/uc?export=download&id=1-IPk1voyUM9VqnghwyVrM1dY6rFnn1S_"
-# embed_link = "https://dl.dropboxusercontent.com/s/ob2betm29qrtb8v/astro_ph_ga_feeds_ada_embedding_18-Apr-2023.pkl?dl=0"
-
-dateval = "27-Jun-2023"
-feeds_link = "local_files/astro_ph_ga_feeds_upto_"+dateval+".pkl"
-embed_link = "local_files/astro_ph_ga_feeds_ada_embedding_"+dateval+".pkl"
-gal_feeds = get_feeds_data(feeds_link)
-arxiv_ada_embeddings = get_feeds_data(embed_link)
-
-ctr = -1
-num_chunks = len(gal_feeds)
-all_text, all_titles, all_arxivid, all_links, all_authors = [], [], [], [], []
-
-for nc in range(num_chunks):
-
-    for i in range(len(gal_feeds[nc].entries)):
-        text = gal_feeds[nc].entries[i].summary
-        text = text.replace('\n', ' ')
-        text = text.replace('\\', '')
-        all_text.append(text)
-        all_titles.append(gal_feeds[nc].entries[i].title)
-        all_arxivid.append(gal_feeds[nc].entries[i].id.split('/')[-1][0:-2])
-        all_links.append(gal_feeds[nc].entries[i].links[1].href)
-        all_authors.append(gal_feeds[nc].entries[i].authors)
-
-d = arxiv_ada_embeddings.shape[1]                           # dimension
-nb = arxiv_ada_embeddings.shape[0]                      # database size
-xb = arxiv_ada_embeddings.astype('float32')
-index = faiss.IndexFlatL2(d)
-index.add(xb)
-
-def run_simple_query(search_query = 'all:sed+fitting', max_results = 10, start = 0, sort_by = 'lastUpdatedDate', sort_order = 'descending'):
-    """
-        Query ArXiv to return search results for a particular query
-        Parameters
-        ----------
-        query: str
-            query term. use prefixes ti, au, abs, co, jr, cat, m, id, all as applicable.
-        max_results: int, default = 10
-            number of results to return. numbers > 1000 generally lead to timeouts
-        start: int, default = 0
-            start index for results reported. use this if you're interested in running chunks.
-        Returns
-        -------
-        feed: dict
-            object containing requested results parsed with feedparser
-        Notes
-        -----
-            add functionality for chunk parsing, as well as storage and retreival
-        """
-
-    # Base api query url
-    base_url = 'http://export.arxiv.org/api/query?';
-    query = 'search_query=%s&start=%i&max_results=%i&sortBy=%s&sortOrder=%s' % (search_query,
-                                                     start,
-                                                     max_results,sort_by,sort_order)
-
-    response = urllib.request.urlopen(base_url+query).read()
-    feed = feedparser.parse(response)
-    return feed
-
-def find_papers_by_author(auth_name):
-
-    doc_ids = []
-    for doc_id in range(len(all_authors)):
-        for auth_id in range(len(all_authors[doc_id])):
-            if auth_name.lower() in all_authors[doc_id][auth_id]['name'].lower():
-                print('Doc ID: ',doc_id, ' | arXiv: ', all_arxivid[doc_id], '| ', all_titles[doc_id],' | Author entry: ', all_authors[doc_id][auth_id]['name'])
-                doc_ids.append(doc_id)
-
-    return doc_ids
-
-def faiss_based_indices(input_vector, nindex=10):
-    xq = input_vector.reshape(-1,1).T.astype('float32')
-    D, I = index.search(xq, nindex)
-    return I[0], D[0]
-
-
-def list_similar_papers_v2(model_data,
-                        doc_id = [], input_type = 'doc_id',
-                        show_authors = False, show_summary = False,
-                        return_n = 10):
-
-    arxiv_ada_embeddings, embeddings, all_titles, all_abstracts, all_authors = model_data
-
-    if input_type == 'doc_id':
-        print('Doc ID: ',doc_id,', title: ',all_titles[doc_id])
-#         inferred_vector = model.infer_vector(train_corpus[doc_id].words)
-        inferred_vector = arxiv_ada_embeddings[doc_id,0:]
-        start_range = 1
-    elif input_type == 'arxiv_id':
-        print('ArXiv id: ',doc_id)
-        arxiv_query_feed = run_simple_query(search_query='id:'+str(doc_id))
-        if len(arxiv_query_feed.entries) == 0:
-            print('error: arxiv id not found.')
-            return
-        else:
-            print('Title: '+arxiv_query_feed.entries[0].title)
-            inferred_vector = np.array(embeddings.embed_query(arxiv_query_feed.entries[0].summary))
-#         arxiv_query_tokens = gensim.utils.simple_preprocess(arxiv_query_feed.entries[0].summary)
-#         inferred_vector = model.infer_vector(arxiv_query_tokens)
-
-        start_range = 0
-    elif input_type == 'keywords':
-#         print('Keyword(s): ',[doc_id[i] for i in range(len(doc_id))])
-#         word_vector = model.wv[doc_id[0]]
-#         if len(doc_id) > 1:
-#            print('multi-keyword')
-#            for i in range(1,len(doc_id)):
-#                word_vector = word_vector + model.wv[doc_id[i]]
-# #         word_vector = model.infer_vector(doc_id)
-#         inferred_vector = word_vector
-        inferred_vector = np.array(embeddings.embed_query(doc_id))
-        start_range = 0
-    else:
-        print('unrecognized input type.')
-        return
-
-#     sims = model.docvecs.most_similar([inferred_vector], topn=len(model.docvecs))
-    sims, dists = faiss_based_indices(inferred_vector, return_n+2)
-    textstr = ''
-
-    textstr = textstr + '-----------------------------\n'
-    textstr = textstr + 'Most similar/relevant papers: \n'
-    textstr = textstr + '-----------------------------\n\n'
-    for i in range(start_range,start_range+return_n):
-
-        # print(i, all_titles[sims[i]], ' (Distance: %.2f' %dists[i] ,')')
-        textstr = textstr + str(i+1)+'. **'+ all_titles[sims[i]] +'** (Distance: %.2f' %dists[i]+')   \n'
-        textstr = textstr + '**ArXiv:** ['+all_arxivid[sims[i]]+'](https://arxiv.org/abs/'+all_arxivid[sims[i]]+')  \n'
-        if show_authors == True:
-            textstr = textstr + '**Authors:**  '
-            temp = all_authors[sims[i]]
-            for ak in range(len(temp)):
-                if ak < len(temp)-1:
-                    textstr = textstr + temp[ak].name + ', '
-                else:
-                    textstr = textstr + temp[ak].name + '   \n'
-        if show_summary == True:
-            textstr = textstr + '**Summary:**  '
-            text = all_text[sims[i]]
-            text = text.replace('\n', ' ')
-            textstr = textstr + summarizer.summarize(text) + '  \n'
-        if show_authors == True or show_summary == True:
-            textstr = textstr + ' '
-        textstr = textstr + '  \n'
-    return textstr
-
-
-model_data = [arxiv_ada_embeddings, embeddings, all_titles, all_text, all_authors]
-
-st.title('ArXiv similarity search:')
-st.markdown('Search for similar papers by arxiv id or phrase:')
-st.markdown('[Includes papers up to: `'+dateval+'`]')
-
-search_type = st.radio(
-    "What are you searching by?",
-    ('arxiv id', 'text query'), index=1)
-
-query = st.text_input('Search query or arxivid', value="what causes galaxy quenching?")
-show_authors = st.checkbox('Show author information', value = True)
-show_summary = st.checkbox('Show paper summary', value = True)
-return_n = st.slider('How many papers should I show?', 1, 30, 10)
-
-if search_type == 'arxiv id':
-    sims = list_similar_papers_v2(model_data, doc_id = query, input_type='arxiv_id', show_authors = show_authors, show_summary = show_summary, return_n = return_n)
-else:
-    sims = list_similar_papers_v2(model_data, doc_id = query, input_type='keywords', show_authors = show_authors, show_summary = show_summary, return_n = return_n)
-
-st.markdown(sims)
diff --git a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/fontTools/ttLib/tables/S__i_l_l.py b/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/fontTools/ttLib/tables/S__i_l_l.py
deleted file mode 100644
index 12b0b8f6cc55b337db857df99e27e7bb69bb5bbc..0000000000000000000000000000000000000000
--- a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/fontTools/ttLib/tables/S__i_l_l.py
+++ /dev/null
@@ -1,87 +0,0 @@
-from fontTools.misc import sstruct
-from fontTools.misc.fixedTools import floatToFixedToStr
-from fontTools.misc.textTools import safeEval
-from . import DefaultTable
-from . import grUtils
-import struct
-
-Sill_hdr = """
-    >
-    version:    16.16F
-"""
-
-
-class table_S__i_l_l(DefaultTable.DefaultTable):
-    def __init__(self, tag=None):
-        DefaultTable.DefaultTable.__init__(self, tag)
-        self.langs = {}
-
-    def decompile(self, data, ttFont):
-        (_, data) = sstruct.unpack2(Sill_hdr, data, self)
-        self.version = float(floatToFixedToStr(self.version, precisionBits=16))
-        (numLangs,) = struct.unpack(">H", data[:2])
-        data = data[8:]
-        maxsetting = 0
-        langinfo = []
-        for i in range(numLangs):
-            (langcode, numsettings, offset) = struct.unpack(
-                ">4sHH", data[i * 8 : (i + 1) * 8]
-            )
-            offset = int(offset / 8) - (numLangs + 1)
-            langcode = langcode.replace(b"\000", b"")
-            langinfo.append((langcode.decode("utf-8"), numsettings, offset))
-            maxsetting = max(maxsetting, offset + numsettings)
-        data = data[numLangs * 8 :]
-        finfo = []
-        for i in range(maxsetting):
-            (fid, val, _) = struct.unpack(">LHH", data[i * 8 : (i + 1) * 8])
-            finfo.append((fid, val))
-        self.langs = {}
-        for c, n, o in langinfo:
-            self.langs[c] = []
-            for i in range(o, o + n):
-                self.langs[c].append(finfo[i])
-
-    def compile(self, ttFont):
-        ldat = b""
-        fdat = b""
-        offset = len(self.langs)
-        for c, inf in sorted(self.langs.items()):
-            ldat += struct.pack(">4sHH", c.encode("utf8"), len(inf), 8 * offset + 20)
-            for fid, val in inf:
-                fdat += struct.pack(">LHH", fid, val, 0)
-            offset += len(inf)
-        ldat += struct.pack(">LHH", 0x80808080, 0, 8 * offset + 20)
-        return (
-            sstruct.pack(Sill_hdr, self)
-            + grUtils.bininfo(len(self.langs))
-            + ldat
-            + fdat
-        )
-
-    def toXML(self, writer, ttFont):
-        writer.simpletag("version", version=self.version)
-        writer.newline()
-        for c, inf in sorted(self.langs.items()):
-            writer.begintag("lang", name=c)
-            writer.newline()
-            for fid, val in inf:
-                writer.simpletag("feature", fid=grUtils.num2tag(fid), val=val)
-                writer.newline()
-            writer.endtag("lang")
-            writer.newline()
-
-    def fromXML(self, name, attrs, content, ttFont):
-        if name == "version":
-            self.version = float(safeEval(attrs["version"]))
-        elif name == "lang":
-            c = attrs["name"]
-            self.langs[c] = []
-            for element in content:
-                if not isinstance(element, tuple):
-                    continue
-                tag, a, subcontent = element
-                if tag == "feature":
-                    self.langs[c].append(
-                        (grUtils.tag2num(a["fid"]), int(safeEval(a["val"])))
-                    )
diff --git a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/templates/cdn/assets/Download-e5de98da.js b/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/templates/cdn/assets/Download-e5de98da.js
deleted file mode 100644
index a66cbe8d9b31510cbd01daccdb448907ed98c7fd..0000000000000000000000000000000000000000
--- a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/templates/cdn/assets/Download-e5de98da.js
+++ /dev/null
@@ -1,2 +0,0 @@
-import{S as i,i as p,s as v,B as o,C as e,g as h,E as c,F as n,q as g}from"./index-7c0e54a6.js";function m(l){let t,s;return{c(){t=o("svg"),s=o("path"),e(s,"fill","currentColor"),e(s,"d","M26 24v4H6v-4H4v4a2 2 0 0 0 2 2h20a2 2 0 0 0 2-2v-4zm0-10l-1.41-1.41L17 20.17V2h-2v18.17l-7.59-7.58L6 14l10 10l10-10z"),e(t,"xmlns","http://www.w3.org/2000/svg"),e(t,"width","100%"),e(t,"height","100%"),e(t,"viewBox","0 0 32 32")},m(a,r){h(a,t,r),c(t,s)},p:n,i:n,o:n,d(a){a&&g(t)}}}class u extends i{constructor(t){super(),p(this,t,null,m,v,{})}}export{u as D};
-//# sourceMappingURL=Download-e5de98da.js.map
diff --git a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/templates/frontend/assets/index-cc1acc6d.js b/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/templates/frontend/assets/index-cc1acc6d.js
deleted file mode 100644
index 9f9048bd776bccbcbf5702448522142954013e6c..0000000000000000000000000000000000000000
--- a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/gradio/templates/frontend/assets/index-cc1acc6d.js
+++ /dev/null
@@ -1,13264 +0,0 @@
-import{S as al,i as sl,s as cl,e as Hn,H as Jr,f as ll,m as Wn,g as Di,p as un,l as ul,t as mn,o as hl,n as Xn,q as Li,u as Rf,a8 as Of,G as Qr,C as bi,E as qr,b as dl,r as Ov,T as Af,F as Mf,a as Mv,k as Iv,V as Dv,X as Lv,Y as Nv,Z as wv,x as Fv,$ as Bv,h as Uv,j as Vv,y as Pf}from"./index-8c3da1d9.js";import{n as kv}from"./ModifyUpload.svelte_svelte_type_style_lang-ba6baa96.js";import{B as Gv}from"./Button-62634b34.js";import{B as fl}from"./BlockLabel-98ef75ee.js";import{E as zv}from"./Empty-5d52e655.js";/* empty css                                                    */import{F as Ha}from"./File-b06157d3.js";import{I as jv,M as Hv}from"./ModifyUpload-00319b5e.js";import{D as Wv}from"./Download-dfb06e25.js";import{c as Zr}from"./_commonjsHelpers-042e6b4d.js";import{U as Xv}from"./Upload-5d35e059.js";import{U as Yv}from"./UploadText-4b161758.js";import"./Blocks-6ad6f005.js";import{E as Db}from"./Model3D-6764e7f5.js";var za={},Kv={get exports(){return za},set 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this.multiplyByFloats(l._x,l._y,l._z)},g.prototype.multiplyToRef=function(l,h){return h.copyFromFloats(this._x*l._x,this._y*l._y,this._z*l._z)},g.prototype.multiplyByFloats=function(l,h,v){return new g(this._x*l,this._y*h,this._z*v)},g.prototype.divide=function(l){return new g(this._x/l._x,this._y/l._y,this._z/l._z)},g.prototype.divideToRef=function(l,h){return h.copyFromFloats(this._x/l._x,this._y/l._y,this._z/l._z)},g.prototype.divideInPlace=function(l){return this.divideToRef(l,this)},g.prototype.minimizeInPlace=function(l){return this.minimizeInPlaceFromFloats(l._x,l._y,l._z)},g.prototype.maximizeInPlace=function(l){return this.maximizeInPlaceFromFloats(l._x,l._y,l._z)},g.prototype.minimizeInPlaceFromFloats=function(l,h,v){return l<this._x&&(this.x=l),h<this._y&&(this.y=h),v<this._z&&(this.z=v),this},g.prototype.maximizeInPlaceFromFloats=function(l,h,v){return l>this._x&&(this.x=l),h>this._y&&(this.y=h),v>this._z&&(this.z=v),this},g.prototype.isNonUniformWithinEpsilon=function(l){var h=Math.abs(this._x),v=Math.abs(this._y);if(!U.a.WithinEpsilon(h,v,l))return!0;var E=Math.abs(this._z);return!U.a.WithinEpsilon(h,E,l)||!U.a.WithinEpsilon(v,E,l)},Object.defineProperty(g.prototype,"isNonUniform",{get:function(){var l=Math.abs(this._x);return l!==Math.abs(this._y)||l!==Math.abs(this._z)},enumerable:!1,configurable:!0}),g.prototype.floor=function(){return new g(Math.floor(this._x),Math.floor(this._y),Math.floor(this._z))},g.prototype.fract=function(){return new g(this._x-Math.floor(this._x),this._y-Math.floor(this._y),this._z-Math.floor(this._z))},g.prototype.length=function(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z)},g.prototype.lengthSquared=function(){return this._x*this._x+this._y*this._y+this._z*this._z},g.prototype.normalize=function(){return this.normalizeFromLength(this.length())},g.prototype.reorderInPlace=function(l){var h=this;return(l=l.toLowerCase())==="xyz"||(A.Vector3[0].copyFrom(this),["x","y","z"].forEach(function(v,E){h[v]=A.Vector3[0][l[E]]})),this},g.prototype.rotateByQuaternionToRef=function(l,h){return l.toRotationMatrix(A.Matrix[0]),g.TransformCoordinatesToRef(this,A.Matrix[0],h),h},g.prototype.rotateByQuaternionAroundPointToRef=function(l,h,v){return this.subtractToRef(h,A.Vector3[0]),A.Vector3[0].rotateByQuaternionToRef(l,A.Vector3[0]),h.addToRef(A.Vector3[0],v),v},g.prototype.cross=function(l){return g.Cross(this,l)},g.prototype.normalizeFromLength=function(l){return l===0||l===1?this:this.scaleInPlace(1/l)},g.prototype.normalizeToNew=function(){var l=new g(0,0,0);return this.normalizeToRef(l),l},g.prototype.normalizeToRef=function(l){var h=this.length();return h===0||h===1?l.copyFromFloats(this._x,this._y,this._z):this.scaleToRef(1/h,l)},g.prototype.clone=function(){return new g(this._x,this._y,this._z)},g.prototype.copyFrom=function(l){return this.copyFromFloats(l._x,l._y,l._z)},g.prototype.copyFromFloats=function(l,h,v){return this.x=l,this.y=h,this.z=v,this},g.prototype.set=function(l,h,v){return this.copyFromFloats(l,h,v)},g.prototype.setAll=function(l){return this.x=this.y=this.z=l,this},g.GetClipFactor=function(l,h,v,E){var D=g.Dot(l,v)-E;return D/(D-(g.Dot(h,v)-E))},g.GetAngleBetweenVectors=function(l,h,v){var E=l.normalizeToRef(A.Vector3[1]),D=h.normalizeToRef(A.Vector3[2]),w=g.Dot(E,D),N=A.Vector3[3];return g.CrossToRef(E,D,N),g.Dot(N,v)>0?Math.acos(w):-Math.acos(w)},g.FromArray=function(l,h){return h===void 0&&(h=0),new g(l[h],l[h+1],l[h+2])},g.FromFloatArray=function(l,h){return g.FromArray(l,h)},g.FromArrayToRef=function(l,h,v){v.x=l[h],v.y=l[h+1],v.z=l[h+2]},g.FromFloatArrayToRef=function(l,h,v){return g.FromArrayToRef(l,h,v)},g.FromFloatsToRef=function(l,h,v,E){E.copyFromFloats(l,h,v)},g.Zero=function(){return new g(0,0,0)},g.One=function(){return new g(1,1,1)},g.Up=function(){return new g(0,1,0)},Object.defineProperty(g,"UpReadOnly",{get:function(){return g._UpReadOnly},enumerable:!1,configurable:!0}),Object.defineProperty(g,"ZeroReadOnly",{get:function(){return g._ZeroReadOnly},enumerable:!1,configurable:!0}),g.Down=function(){return new g(0,-1,0)},g.Forward=function(l){return l===void 0&&(l=!1),new g(0,0,l?-1:1)},g.Backward=function(l){return l===void 0&&(l=!1),new g(0,0,l?1:-1)},g.Right=function(){return new g(1,0,0)},g.Left=function(){return new g(-1,0,0)},g.TransformCoordinates=function(l,h){var v=g.Zero();return g.TransformCoordinatesToRef(l,h,v),v},g.TransformCoordinatesToRef=function(l,h,v){g.TransformCoordinatesFromFloatsToRef(l._x,l._y,l._z,h,v)},g.TransformCoordinatesFromFloatsToRef=function(l,h,v,E,D){var w=E.m,N=l*w[0]+h*w[4]+v*w[8]+w[12],I=l*w[1]+h*w[5]+v*w[9]+w[13],V=l*w[2]+h*w[6]+v*w[10]+w[14],X=1/(l*w[3]+h*w[7]+v*w[11]+w[15]);D.x=N*X,D.y=I*X,D.z=V*X},g.TransformNormal=function(l,h){var v=g.Zero();return g.TransformNormalToRef(l,h,v),v},g.TransformNormalToRef=function(l,h,v){this.TransformNormalFromFloatsToRef(l._x,l._y,l._z,h,v)},g.TransformNormalFromFloatsToRef=function(l,h,v,E,D){var w=E.m;D.x=l*w[0]+h*w[4]+v*w[8],D.y=l*w[1]+h*w[5]+v*w[9],D.z=l*w[2]+h*w[6]+v*w[10]},g.CatmullRom=function(l,h,v,E,D){var w=D*D,N=D*w;return new g(.5*(2*h._x+(-l._x+v._x)*D+(2*l._x-5*h._x+4*v._x-E._x)*w+(-l._x+3*h._x-3*v._x+E._x)*N),.5*(2*h._y+(-l._y+v._y)*D+(2*l._y-5*h._y+4*v._y-E._y)*w+(-l._y+3*h._y-3*v._y+E._y)*N),.5*(2*h._z+(-l._z+v._z)*D+(2*l._z-5*h._z+4*v._z-E._z)*w+(-l._z+3*h._z-3*v._z+E._z)*N))},g.Clamp=function(l,h,v){var E=new g;return g.ClampToRef(l,h,v,E),E},g.ClampToRef=function(l,h,v,E){var D=l._x;D=(D=D>v._x?v._x:D)<h._x?h._x:D;var w=l._y;w=(w=w>v._y?v._y:w)<h._y?h._y:w;var N=l._z;N=(N=N>v._z?v._z:N)<h._z?h._z:N,E.copyFromFloats(D,w,N)},g.CheckExtends=function(l,h,v){h.minimizeInPlace(l),v.maximizeInPlace(l)},g.Hermite=function(l,h,v,E,D){var w=D*D,N=D*w,I=2*N-3*w+1,V=-2*N+3*w,X=N-2*w+D,j=N-w;return new g(l._x*I+v._x*V+h._x*X+E._x*j,l._y*I+v._y*V+h._y*X+E._y*j,l._z*I+v._z*V+h._z*X+E._z*j)},g.Lerp=function(l,h,v){var E=new g(0,0,0);return g.LerpToRef(l,h,v,E),E},g.LerpToRef=function(l,h,v,E){E.x=l._x+(h._x-l._x)*v,E.y=l._y+(h._y-l._y)*v,E.z=l._z+(h._z-l._z)*v},g.Dot=function(l,h){return l._x*h._x+l._y*h._y+l._z*h._z},g.Cross=function(l,h){var v=g.Zero();return g.CrossToRef(l,h,v),v},g.CrossToRef=function(l,h,v){var E=l._y*h._z-l._z*h._y,D=l._z*h._x-l._x*h._z,w=l._x*h._y-l._y*h._x;v.copyFromFloats(E,D,w)},g.Normalize=function(l){var h=g.Zero();return g.NormalizeToRef(l,h),h},g.NormalizeToRef=function(l,h){l.normalizeToRef(h)},g.Project=function(l,h,v,E){var D=new g;return g.ProjectToRef(l,h,v,E,D),D},g.ProjectToRef=function(l,h,v,E,D){var w=E.width,N=E.height,I=E.x,V=E.y,X=A.Matrix[1];T.FromValuesToRef(w/2,0,0,0,0,-N/2,0,0,0,0,.5,0,I+w/2,N/2+V,.5,1,X);var j=A.Matrix[0];return h.multiplyToRef(v,j),j.multiplyToRef(X,j),g.TransformCoordinatesToRef(l,j,D),D},g._UnprojectFromInvertedMatrixToRef=function(l,h,v){g.TransformCoordinatesToRef(l,h,v);var E=h.m,D=l._x*E[3]+l._y*E[7]+l._z*E[11]+E[15];U.a.WithinEpsilon(D,1)&&v.scaleInPlace(1/D)},g.UnprojectFromTransform=function(l,h,v,E,D){var w=A.Matrix[0];E.multiplyToRef(D,w),w.invert(),l.x=l._x/h*2-1,l.y=-(l._y/v*2-1);var N=new g;return g._UnprojectFromInvertedMatrixToRef(l,w,N),N},g.Unproject=function(l,h,v,E,D,w){var N=g.Zero();return g.UnprojectToRef(l,h,v,E,D,w,N),N},g.UnprojectToRef=function(l,h,v,E,D,w,N){g.UnprojectFloatsToRef(l._x,l._y,l._z,h,v,E,D,w,N)},g.UnprojectFloatsToRef=function(l,h,v,E,D,w,N,I,V){var X=A.Matrix[0];w.multiplyToRef(N,X),X.multiplyToRef(I,X),X.invert();var j=A.Vector3[0];j.x=l/E*2-1,j.y=-(h/D*2-1),j.z=2*v-1,g._UnprojectFromInvertedMatrixToRef(j,X,V)},g.Minimize=function(l,h){var v=l.clone();return v.minimizeInPlace(h),v},g.Maximize=function(l,h){var v=l.clone();return v.maximizeInPlace(h),v},g.Distance=function(l,h){return Math.sqrt(g.DistanceSquared(l,h))},g.DistanceSquared=function(l,h){var v=l._x-h._x,E=l._y-h._y,D=l._z-h._z;return v*v+E*E+D*D},g.Center=function(l,h){var v=l.add(h);return v.scaleInPlace(.5),v},g.RotationFromAxis=function(l,h,v){var E=g.Zero();return g.RotationFromAxisToRef(l,h,v,E),E},g.RotationFromAxisToRef=function(l,h,v,E){var D=A.Quaternion[0];c.RotationQuaternionFromAxisToRef(l,h,v,D),D.toEulerAnglesToRef(E)},g._UpReadOnly=g.Up(),g._ZeroReadOnly=g.Zero(),g}(),m=function(){function g(l,h,v,E){this.x=l,this.y=h,this.z=v,this.w=E}return g.prototype.toString=function(){return"{X: "+this.x+" Y:"+this.y+" Z:"+this.z+" 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g(this.x-l.x,this.y-l.y,this.z-l.z,this.w-l.w)},g.prototype.subtractToRef=function(l,h){return h.x=this.x-l.x,h.y=this.y-l.y,h.z=this.z-l.z,h.w=this.w-l.w,this},g.prototype.subtractFromFloats=function(l,h,v,E){return new g(this.x-l,this.y-h,this.z-v,this.w-E)},g.prototype.subtractFromFloatsToRef=function(l,h,v,E,D){return D.x=this.x-l,D.y=this.y-h,D.z=this.z-v,D.w=this.w-E,this},g.prototype.negate=function(){return new g(-this.x,-this.y,-this.z,-this.w)},g.prototype.negateInPlace=function(){return this.x*=-1,this.y*=-1,this.z*=-1,this.w*=-1,this},g.prototype.negateToRef=function(l){return l.copyFromFloats(-1*this.x,-1*this.y,-1*this.z,-1*this.w)},g.prototype.scaleInPlace=function(l){return this.x*=l,this.y*=l,this.z*=l,this.w*=l,this},g.prototype.scale=function(l){return new g(this.x*l,this.y*l,this.z*l,this.w*l)},g.prototype.scaleToRef=function(l,h){return h.x=this.x*l,h.y=this.y*l,h.z=this.z*l,h.w=this.w*l,this},g.prototype.scaleAndAddToRef=function(l,h){return h.x+=this.x*l,h.y+=this.y*l,h.z+=this.z*l,h.w+=this.w*l,this},g.prototype.equals=function(l){return l&&this.x===l.x&&this.y===l.y&&this.z===l.z&&this.w===l.w},g.prototype.equalsWithEpsilon=function(l,h){return h===void 0&&(h=_.a),l&&U.a.WithinEpsilon(this.x,l.x,h)&&U.a.WithinEpsilon(this.y,l.y,h)&&U.a.WithinEpsilon(this.z,l.z,h)&&U.a.WithinEpsilon(this.w,l.w,h)},g.prototype.equalsToFloats=function(l,h,v,E){return this.x===l&&this.y===h&&this.z===v&&this.w===E},g.prototype.multiplyInPlace=function(l){return this.x*=l.x,this.y*=l.y,this.z*=l.z,this.w*=l.w,this},g.prototype.multiply=function(l){return new g(this.x*l.x,this.y*l.y,this.z*l.z,this.w*l.w)},g.prototype.multiplyToRef=function(l,h){return h.x=this.x*l.x,h.y=this.y*l.y,h.z=this.z*l.z,h.w=this.w*l.w,this},g.prototype.multiplyByFloats=function(l,h,v,E){return new g(this.x*l,this.y*h,this.z*v,this.w*E)},g.prototype.divide=function(l){return new g(this.x/l.x,this.y/l.y,this.z/l.z,this.w/l.w)},g.prototype.divideToRef=function(l,h){return h.x=this.x/l.x,h.y=this.y/l.y,h.z=this.z/l.z,h.w=this.w/l.w,this},g.prototype.divideInPlace=function(l){return this.divideToRef(l,this)},g.prototype.minimizeInPlace=function(l){return l.x<this.x&&(this.x=l.x),l.y<this.y&&(this.y=l.y),l.z<this.z&&(this.z=l.z),l.w<this.w&&(this.w=l.w),this},g.prototype.maximizeInPlace=function(l){return l.x>this.x&&(this.x=l.x),l.y>this.y&&(this.y=l.y),l.z>this.z&&(this.z=l.z),l.w>this.w&&(this.w=l.w),this},g.prototype.floor=function(){return new g(Math.floor(this.x),Math.floor(this.y),Math.floor(this.z),Math.floor(this.w))},g.prototype.fract=function(){return new g(this.x-Math.floor(this.x),this.y-Math.floor(this.y),this.z-Math.floor(this.z),this.w-Math.floor(this.w))},g.prototype.length=function(){return Math.sqrt(this.x*this.x+this.y*this.y+this.z*this.z+this.w*this.w)},g.prototype.lengthSquared=function(){return this.x*this.x+this.y*this.y+this.z*this.z+this.w*this.w},g.prototype.normalize=function(){var l=this.length();return l===0?this:this.scaleInPlace(1/l)},g.prototype.toVector3=function(){return new x(this.x,this.y,this.z)},g.prototype.clone=function(){return new g(this.x,this.y,this.z,this.w)},g.prototype.copyFrom=function(l){return this.x=l.x,this.y=l.y,this.z=l.z,this.w=l.w,this},g.prototype.copyFromFloats=function(l,h,v,E){return this.x=l,this.y=h,this.z=v,this.w=E,this},g.prototype.set=function(l,h,v,E){return this.copyFromFloats(l,h,v,E)},g.prototype.setAll=function(l){return this.x=this.y=this.z=this.w=l,this},g.FromArray=function(l,h){return h||(h=0),new g(l[h],l[h+1],l[h+2],l[h+3])},g.FromArrayToRef=function(l,h,v){v.x=l[h],v.y=l[h+1],v.z=l[h+2],v.w=l[h+3]},g.FromFloatArrayToRef=function(l,h,v){g.FromArrayToRef(l,h,v)},g.FromFloatsToRef=function(l,h,v,E,D){D.x=l,D.y=h,D.z=v,D.w=E},g.Zero=function(){return new g(0,0,0,0)},g.One=function(){return new g(1,1,1,1)},g.Normalize=function(l){var h=g.Zero();return g.NormalizeToRef(l,h),h},g.NormalizeToRef=function(l,h){h.copyFrom(l),h.normalize()},g.Minimize=function(l,h){var v=l.clone();return v.minimizeInPlace(h),v},g.Maximize=function(l,h){var v=l.clone();return v.maximizeInPlace(h),v},g.Distance=function(l,h){return Math.sqrt(g.DistanceSquared(l,h))},g.DistanceSquared=function(l,h){var v=l.x-h.x,E=l.y-h.y,D=l.z-h.z,w=l.w-h.w;return v*v+E*E+D*D+w*w},g.Center=function(l,h){var v=l.add(h);return v.scaleInPlace(.5),v},g.TransformNormal=function(l,h){var v=g.Zero();return g.TransformNormalToRef(l,h,v),v},g.TransformNormalToRef=function(l,h,v){var E=h.m,D=l.x*E[0]+l.y*E[4]+l.z*E[8],w=l.x*E[1]+l.y*E[5]+l.z*E[9],N=l.x*E[2]+l.y*E[6]+l.z*E[10];v.x=D,v.y=w,v.z=N,v.w=l.w},g.TransformNormalFromFloatsToRef=function(l,h,v,E,D,w){var N=D.m;w.x=l*N[0]+h*N[4]+v*N[8],w.y=l*N[1]+h*N[5]+v*N[9],w.z=l*N[2]+h*N[6]+v*N[10],w.w=E},g.FromVector3=function(l,h){return h===void 0&&(h=0),new g(l._x,l._y,l._z,h)},g}(),c=function(){function g(l,h,v,E){l===void 0&&(l=0),h===void 0&&(h=0),v===void 0&&(v=0),E===void 0&&(E=1),this._isDirty=!0,this._x=l,this._y=h,this._z=v,this._w=E}return Object.defineProperty(g.prototype,"x",{get:function(){return this._x},set:function(l){this._x=l,this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"y",{get:function(){return this._y},set:function(l){this._y=l,this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"z",{get:function(){return this._z},set:function(l){this._z=l,this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"w",{get:function(){return this._w},set:function(l){this._w=l,this._isDirty=!0},enumerable:!1,configurable:!0}),g.prototype.toString=function(){return"{X: "+this._x+" Y:"+this._y+" Z:"+this._z+" W:"+this._w+"}"},g.prototype.getClassName=function(){return"Quaternion"},g.prototype.getHashCode=function(){var l=0|this._x;return l=397*(l=397*(l=397*l^(0|this._y))^(0|this._z))^(0|this._w)},g.prototype.asArray=function(){return[this._x,this._y,this._z,this._w]},g.prototype.equals=function(l){return l&&this._x===l._x&&this._y===l._y&&this._z===l._z&&this._w===l._w},g.prototype.equalsWithEpsilon=function(l,h){return h===void 0&&(h=_.a),l&&U.a.WithinEpsilon(this._x,l._x,h)&&U.a.WithinEpsilon(this._y,l._y,h)&&U.a.WithinEpsilon(this._z,l._z,h)&&U.a.WithinEpsilon(this._w,l._w,h)},g.prototype.clone=function(){return new g(this._x,this._y,this._z,this._w)},g.prototype.copyFrom=function(l){return this.x=l._x,this.y=l._y,this.z=l._z,this.w=l._w,this},g.prototype.copyFromFloats=function(l,h,v,E){return this.x=l,this.y=h,this.z=v,this.w=E,this},g.prototype.set=function(l,h,v,E){return this.copyFromFloats(l,h,v,E)},g.prototype.add=function(l){return new g(this._x+l._x,this._y+l._y,this._z+l._z,this._w+l._w)},g.prototype.addInPlace=function(l){return this._x+=l._x,this._y+=l._y,this._z+=l._z,this._w+=l._w,this},g.prototype.subtract=function(l){return new g(this._x-l._x,this._y-l._y,this._z-l._z,this._w-l._w)},g.prototype.scale=function(l){return new g(this._x*l,this._y*l,this._z*l,this._w*l)},g.prototype.scaleToRef=function(l,h){return h.x=this._x*l,h.y=this._y*l,h.z=this._z*l,h.w=this._w*l,this},g.prototype.scaleInPlace=function(l){return this.x*=l,this.y*=l,this.z*=l,this.w*=l,this},g.prototype.scaleAndAddToRef=function(l,h){return h.x+=this._x*l,h.y+=this._y*l,h.z+=this._z*l,h.w+=this._w*l,this},g.prototype.multiply=function(l){var h=new g(0,0,0,1);return this.multiplyToRef(l,h),h},g.prototype.multiplyToRef=function(l,h){var v=this._x*l._w+this._y*l._z-this._z*l._y+this._w*l._x,E=-this._x*l._z+this._y*l._w+this._z*l._x+this._w*l._y,D=this._x*l._y-this._y*l._x+this._z*l._w+this._w*l._z,w=-this._x*l._x-this._y*l._y-this._z*l._z+this._w*l._w;return h.copyFromFloats(v,E,D,w),this},g.prototype.multiplyInPlace=function(l){return this.multiplyToRef(l,this),this},g.prototype.conjugateToRef=function(l){return l.copyFromFloats(-this._x,-this._y,-this._z,this._w),this},g.prototype.conjugateInPlace=function(){return this.x*=-1,this.y*=-1,this.z*=-1,this},g.prototype.conjugate=function(){return new g(-this._x,-this._y,-this._z,this._w)},g.prototype.length=function(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w)},g.prototype.normalize=function(){var l=this.length();if(l===0)return this;var h=1/l;return this.x*=h,this.y*=h,this.z*=h,this.w*=h,this},g.prototype.toEulerAngles=function(l){var h=x.Zero();return this.toEulerAnglesToRef(h),h},g.prototype.toEulerAnglesToRef=function(l){var h=this._z,v=this._x,E=this._y,D=this._w,w=D*D,N=h*h,I=v*v,V=E*E,X=E*h-v*D;return X<-.4999999?(l.y=2*Math.atan2(E,D),l.x=Math.PI/2,l.z=0):X>.4999999?(l.y=2*Math.atan2(E,D),l.x=-Math.PI/2,l.z=0):(l.z=Math.atan2(2*(v*E+h*D),-N-I+V+w),l.x=Math.asin(-2*(h*E-v*D)),l.y=Math.atan2(2*(h*v+E*D),N-I-V+w)),this},g.prototype.toRotationMatrix=function(l){return T.FromQuaternionToRef(this,l),this},g.prototype.fromRotationMatrix=function(l){return g.FromRotationMatrixToRef(l,this),this},g.FromRotationMatrix=function(l){var h=new g;return g.FromRotationMatrixToRef(l,h),h},g.FromRotationMatrixToRef=function(l,h){var v,E=l.m,D=E[0],w=E[4],N=E[8],I=E[1],V=E[5],X=E[9],j=E[2],ne=E[6],te=E[10],de=D+V+te;de>0?(v=.5/Math.sqrt(de+1),h.w=.25/v,h.x=(ne-X)*v,h.y=(N-j)*v,h.z=(I-w)*v):D>V&&D>te?(v=2*Math.sqrt(1+D-V-te),h.w=(ne-X)/v,h.x=.25*v,h.y=(w+I)/v,h.z=(N+j)/v):V>te?(v=2*Math.sqrt(1+V-D-te),h.w=(N-j)/v,h.x=(w+I)/v,h.y=.25*v,h.z=(X+ne)/v):(v=2*Math.sqrt(1+te-D-V),h.w=(I-w)/v,h.x=(N+j)/v,h.y=(X+ne)/v,h.z=.25*v)},g.Dot=function(l,h){return l._x*h._x+l._y*h._y+l._z*h._z+l._w*h._w},g.AreClose=function(l,h){return g.Dot(l,h)>=0},g.Zero=function(){return new g(0,0,0,0)},g.Inverse=function(l){return new g(-l._x,-l._y,-l._z,l._w)},g.InverseToRef=function(l,h){return h.set(-l._x,-l._y,-l._z,l._w),h},g.Identity=function(){return new g(0,0,0,1)},g.IsIdentity=function(l){return l&&l._x===0&&l._y===0&&l._z===0&&l._w===1},g.RotationAxis=function(l,h){return g.RotationAxisToRef(l,h,new g)},g.RotationAxisToRef=function(l,h,v){var E=Math.sin(h/2);return l.normalize(),v.w=Math.cos(h/2),v.x=l._x*E,v.y=l._y*E,v.z=l._z*E,v},g.FromArray=function(l,h){return h||(h=0),new g(l[h],l[h+1],l[h+2],l[h+3])},g.FromArrayToRef=function(l,h,v){v.x=l[h],v.y=l[h+1],v.z=l[h+2],v.w=l[h+3]},g.FromEulerAngles=function(l,h,v){var E=new g;return g.RotationYawPitchRollToRef(h,l,v,E),E},g.FromEulerAnglesToRef=function(l,h,v,E){return g.RotationYawPitchRollToRef(h,l,v,E),E},g.FromEulerVector=function(l){var h=new g;return g.RotationYawPitchRollToRef(l._y,l._x,l._z,h),h},g.FromEulerVectorToRef=function(l,h){return g.RotationYawPitchRollToRef(l._y,l._x,l._z,h),h},g.RotationYawPitchRoll=function(l,h,v){var E=new g;return g.RotationYawPitchRollToRef(l,h,v,E),E},g.RotationYawPitchRollToRef=function(l,h,v,E){var D=.5*v,w=.5*h,N=.5*l,I=Math.sin(D),V=Math.cos(D),X=Math.sin(w),j=Math.cos(w),ne=Math.sin(N),te=Math.cos(N);E.x=te*X*V+ne*j*I,E.y=ne*j*V-te*X*I,E.z=te*j*I-ne*X*V,E.w=te*j*V+ne*X*I},g.RotationAlphaBetaGamma=function(l,h,v){var E=new g;return g.RotationAlphaBetaGammaToRef(l,h,v,E),E},g.RotationAlphaBetaGammaToRef=function(l,h,v,E){var D=.5*(v+l),w=.5*(v-l),N=.5*h;E.x=Math.cos(w)*Math.sin(N),E.y=Math.sin(w)*Math.sin(N),E.z=Math.sin(D)*Math.cos(N),E.w=Math.cos(D)*Math.cos(N)},g.RotationQuaternionFromAxis=function(l,h,v){var E=new g(0,0,0,0);return g.RotationQuaternionFromAxisToRef(l,h,v,E),E},g.RotationQuaternionFromAxisToRef=function(l,h,v,E){var D=A.Matrix[0];T.FromXYZAxesToRef(l.normalize(),h.normalize(),v.normalize(),D),g.FromRotationMatrixToRef(D,E)},g.Slerp=function(l,h,v){var E=g.Identity();return g.SlerpToRef(l,h,v,E),E},g.SlerpToRef=function(l,h,v,E){var D,w,N=l._x*h._x+l._y*h._y+l._z*h._z+l._w*h._w,I=!1;if(N<0&&(I=!0,N=-N),N>.999999)w=1-v,D=I?-v:v;else{var V=Math.acos(N),X=1/Math.sin(V);w=Math.sin((1-v)*V)*X,D=I?-Math.sin(v*V)*X:Math.sin(v*V)*X}E.x=w*l._x+D*h._x,E.y=w*l._y+D*h._y,E.z=w*l._z+D*h._z,E.w=w*l._w+D*h._w},g.Hermite=function(l,h,v,E,D){var w=D*D,N=D*w,I=2*N-3*w+1,V=-2*N+3*w,X=N-2*w+D,j=N-w;return new g(l._x*I+v._x*V+h._x*X+E._x*j,l._y*I+v._y*V+h._y*X+E._y*j,l._z*I+v._z*V+h._z*X+E._z*j,l._w*I+v._w*V+h._w*X+E._w*j)},g}(),T=function(){function g(){this._isIdentity=!1,this._isIdentityDirty=!0,this._isIdentity3x2=!0,this._isIdentity3x2Dirty=!0,this.updateFlag=-1,M.a.MatrixTrackPrecisionChange&&M.a.MatrixTrackedMatrices.push(this),this._m=new M.a.MatrixCurrentType(16),this._updateIdentityStatus(!1)}return Object.defineProperty(g,"Use64Bits",{get:function(){return M.a.MatrixUse64Bits},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"m",{get:function(){return this._m},enumerable:!1,configurable:!0}),g.prototype._markAsUpdated=function(){this.updateFlag=g._updateFlagSeed++,this._isIdentity=!1,this._isIdentity3x2=!1,this._isIdentityDirty=!0,this._isIdentity3x2Dirty=!0},g.prototype._updateIdentityStatus=function(l,h,v,E){h===void 0&&(h=!1),v===void 0&&(v=!1),E===void 0&&(E=!0),this.updateFlag=g._updateFlagSeed++,this._isIdentity=l,this._isIdentity3x2=l||v,this._isIdentityDirty=!this._isIdentity&&h,this._isIdentity3x2Dirty=!this._isIdentity3x2&&E},g.prototype.isIdentity=function(){if(this._isIdentityDirty){this._isIdentityDirty=!1;var l=this._m;this._isIdentity=l[0]===1&&l[1]===0&&l[2]===0&&l[3]===0&&l[4]===0&&l[5]===1&&l[6]===0&&l[7]===0&&l[8]===0&&l[9]===0&&l[10]===1&&l[11]===0&&l[12]===0&&l[13]===0&&l[14]===0&&l[15]===1}return this._isIdentity},g.prototype.isIdentityAs3x2=function(){return this._isIdentity3x2Dirty&&(this._isIdentity3x2Dirty=!1,this._m[0]!==1||this._m[5]!==1||this._m[15]!==1||this._m[1]!==0||this._m[2]!==0||this._m[3]!==0||this._m[4]!==0||this._m[6]!==0||this._m[7]!==0||this._m[8]!==0||this._m[9]!==0||this._m[10]!==0||this._m[11]!==0||this._m[12]!==0||this._m[13]!==0||this._m[14]!==0?this._isIdentity3x2=!1:this._isIdentity3x2=!0),this._isIdentity3x2},g.prototype.determinant=function(){if(this._isIdentity===!0)return 1;var l=this._m,h=l[0],v=l[1],E=l[2],D=l[3],w=l[4],N=l[5],I=l[6],V=l[7],X=l[8],j=l[9],ne=l[10],te=l[11],de=l[12],pe=l[13],ae=l[14],ee=l[15],K=ne*ee-ae*te,$=j*ee-pe*te,L=j*ae-pe*ne,G=X*ee-de*te,Q=X*ae-ne*de,oe=X*pe-de*j;return h*+(N*K-I*$+V*L)+v*-(w*K-I*G+V*Q)+E*+(w*$-N*G+V*oe)+D*-(w*L-N*Q+I*oe)},g.prototype.toArray=function(){return this._m},g.prototype.asArray=function(){return this._m},g.prototype.invert=function(){return this.invertToRef(this),this},g.prototype.reset=function(){return g.FromValuesToRef(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,this),this._updateIdentityStatus(!1),this},g.prototype.add=function(l){var h=new g;return this.addToRef(l,h),h},g.prototype.addToRef=function(l,h){for(var v=this._m,E=h._m,D=l.m,w=0;w<16;w++)E[w]=v[w]+D[w];return h._markAsUpdated(),this},g.prototype.addToSelf=function(l){for(var h=this._m,v=l.m,E=0;E<16;E++)h[E]+=v[E];return this._markAsUpdated(),this},g.prototype.invertToRef=function(l){if(this._isIdentity===!0)return g.IdentityToRef(l),this;var h=this._m,v=h[0],E=h[1],D=h[2],w=h[3],N=h[4],I=h[5],V=h[6],X=h[7],j=h[8],ne=h[9],te=h[10],de=h[11],pe=h[12],ae=h[13],ee=h[14],K=h[15],$=te*K-ee*de,L=ne*K-ae*de,G=ne*ee-ae*te,Q=j*K-pe*de,oe=j*ee-te*pe,re=j*ae-pe*ne,Y=+(I*$-V*L+X*G),k=-(N*$-V*Q+X*oe),H=+(N*L-I*Q+X*re),Z=-(N*G-I*oe+V*re),W=v*Y+E*k+D*H+w*Z;if(W===0)return l.copyFrom(this),this;var q=1/W,he=V*K-ee*X,ge=I*K-ae*X,me=I*ee-ae*V,_e=N*K-pe*X,be=N*ee-pe*V,Pe=N*ae-pe*I,ye=V*de-te*X,Be=I*de-ne*X,ke=I*te-ne*V,We=N*de-j*X,je=N*te-j*V,He=N*ne-j*I,qe=-(E*$-D*L+w*G),Ge=+(v*$-D*Q+w*oe),nt=-(v*L-E*Q+w*re),$e=+(v*G-E*oe+D*re),lt=+(E*he-D*ge+w*me),st=-(v*he-D*_e+w*be),mt=+(v*ge-E*_e+w*Pe),St=-(v*me-E*be+D*Pe),wt=-(E*ye-D*Be+w*ke),It=+(v*ye-D*We+w*je),Pt=-(v*Be-E*We+w*He),Ot=+(v*ke-E*je+D*He);return g.FromValuesToRef(Y*q,qe*q,lt*q,wt*q,k*q,Ge*q,st*q,It*q,H*q,nt*q,mt*q,Pt*q,Z*q,$e*q,St*q,Ot*q,l),this},g.prototype.addAtIndex=function(l,h){return this._m[l]+=h,this._markAsUpdated(),this},g.prototype.multiplyAtIndex=function(l,h){return this._m[l]*=h,this._markAsUpdated(),this},g.prototype.setTranslationFromFloats=function(l,h,v){return this._m[12]=l,this._m[13]=h,this._m[14]=v,this._markAsUpdated(),this},g.prototype.addTranslationFromFloats=function(l,h,v){return this._m[12]+=l,this._m[13]+=h,this._m[14]+=v,this._markAsUpdated(),this},g.prototype.setTranslation=function(l){return this.setTranslationFromFloats(l._x,l._y,l._z)},g.prototype.getTranslation=function(){return new x(this._m[12],this._m[13],this._m[14])},g.prototype.getTranslationToRef=function(l){return l.x=this._m[12],l.y=this._m[13],l.z=this._m[14],this},g.prototype.removeRotationAndScaling=function(){var l=this.m;return g.FromValuesToRef(1,0,0,0,0,1,0,0,0,0,1,0,l[12],l[13],l[14],l[15],this),this._updateIdentityStatus(l[12]===0&&l[13]===0&&l[14]===0&&l[15]===1),this},g.prototype.multiply=function(l){var h=new g;return this.multiplyToRef(l,h),h},g.prototype.copyFrom=function(l){l.copyToArray(this._m);var h=l;return this._updateIdentityStatus(h._isIdentity,h._isIdentityDirty,h._isIdentity3x2,h._isIdentity3x2Dirty),this},g.prototype.copyToArray=function(l,h){h===void 0&&(h=0);var v=this._m;return l[h]=v[0],l[h+1]=v[1],l[h+2]=v[2],l[h+3]=v[3],l[h+4]=v[4],l[h+5]=v[5],l[h+6]=v[6],l[h+7]=v[7],l[h+8]=v[8],l[h+9]=v[9],l[h+10]=v[10],l[h+11]=v[11],l[h+12]=v[12],l[h+13]=v[13],l[h+14]=v[14],l[h+15]=v[15],this},g.prototype.multiplyToRef=function(l,h){return this._isIdentity?(h.copyFrom(l),this):l._isIdentity?(h.copyFrom(this),this):(this.multiplyToArray(l,h._m,0),h._markAsUpdated(),this)},g.prototype.multiplyToArray=function(l,h,v){var E=this._m,D=l.m,w=E[0],N=E[1],I=E[2],V=E[3],X=E[4],j=E[5],ne=E[6],te=E[7],de=E[8],pe=E[9],ae=E[10],ee=E[11],K=E[12],$=E[13],L=E[14],G=E[15],Q=D[0],oe=D[1],re=D[2],Y=D[3],k=D[4],H=D[5],Z=D[6],W=D[7],q=D[8],he=D[9],ge=D[10],me=D[11],_e=D[12],be=D[13],Pe=D[14],ye=D[15];return h[v]=w*Q+N*k+I*q+V*_e,h[v+1]=w*oe+N*H+I*he+V*be,h[v+2]=w*re+N*Z+I*ge+V*Pe,h[v+3]=w*Y+N*W+I*me+V*ye,h[v+4]=X*Q+j*k+ne*q+te*_e,h[v+5]=X*oe+j*H+ne*he+te*be,h[v+6]=X*re+j*Z+ne*ge+te*Pe,h[v+7]=X*Y+j*W+ne*me+te*ye,h[v+8]=de*Q+pe*k+ae*q+ee*_e,h[v+9]=de*oe+pe*H+ae*he+ee*be,h[v+10]=de*re+pe*Z+ae*ge+ee*Pe,h[v+11]=de*Y+pe*W+ae*me+ee*ye,h[v+12]=K*Q+$*k+L*q+G*_e,h[v+13]=K*oe+$*H+L*he+G*be,h[v+14]=K*re+$*Z+L*ge+G*Pe,h[v+15]=K*Y+$*W+L*me+G*ye,this},g.prototype.equals=function(l){var h=l;if(!h)return!1;if((this._isIdentity||h._isIdentity)&&!this._isIdentityDirty&&!h._isIdentityDirty)return this._isIdentity&&h._isIdentity;var v=this.m,E=h.m;return v[0]===E[0]&&v[1]===E[1]&&v[2]===E[2]&&v[3]===E[3]&&v[4]===E[4]&&v[5]===E[5]&&v[6]===E[6]&&v[7]===E[7]&&v[8]===E[8]&&v[9]===E[9]&&v[10]===E[10]&&v[11]===E[11]&&v[12]===E[12]&&v[13]===E[13]&&v[14]===E[14]&&v[15]===E[15]},g.prototype.clone=function(){var l=new g;return l.copyFrom(this),l},g.prototype.getClassName=function(){return"Matrix"},g.prototype.getHashCode=function(){for(var l=0|this._m[0],h=1;h<16;h++)l=397*l^(0|this._m[h]);return l},g.prototype.decompose=function(l,h,v){if(this._isIdentity)return v&&v.setAll(0),l&&l.setAll(1),h&&h.copyFromFloats(0,0,0,1),!0;var E=this._m;if(v&&v.copyFromFloats(E[12],E[13],E[14]),(l=l||A.Vector3[0]).x=Math.sqrt(E[0]*E[0]+E[1]*E[1]+E[2]*E[2]),l.y=Math.sqrt(E[4]*E[4]+E[5]*E[5]+E[6]*E[6]),l.z=Math.sqrt(E[8]*E[8]+E[9]*E[9]+E[10]*E[10]),this.determinant()<=0&&(l.y*=-1),l._x===0||l._y===0||l._z===0)return h&&h.copyFromFloats(0,0,0,1),!1;if(h){var D=1/l._x,w=1/l._y,N=1/l._z;g.FromValuesToRef(E[0]*D,E[1]*D,E[2]*D,0,E[4]*w,E[5]*w,E[6]*w,0,E[8]*N,E[9]*N,E[10]*N,0,0,0,0,1,A.Matrix[0]),c.FromRotationMatrixToRef(A.Matrix[0],h)}return!0},g.prototype.getRow=function(l){if(l<0||l>3)return null;var h=4*l;return new m(this._m[h+0],this._m[h+1],this._m[h+2],this._m[h+3])},g.prototype.setRow=function(l,h){return this.setRowFromFloats(l,h.x,h.y,h.z,h.w)},g.prototype.transpose=function(){return g.Transpose(this)},g.prototype.transposeToRef=function(l){return g.TransposeToRef(this,l),this},g.prototype.setRowFromFloats=function(l,h,v,E,D){if(l<0||l>3)return this;var w=4*l;return this._m[w+0]=h,this._m[w+1]=v,this._m[w+2]=E,this._m[w+3]=D,this._markAsUpdated(),this},g.prototype.scale=function(l){var h=new g;return this.scaleToRef(l,h),h},g.prototype.scaleToRef=function(l,h){for(var v=0;v<16;v++)h._m[v]=this._m[v]*l;return h._markAsUpdated(),this},g.prototype.scaleAndAddToRef=function(l,h){for(var v=0;v<16;v++)h._m[v]+=this._m[v]*l;return h._markAsUpdated(),this},g.prototype.toNormalMatrix=function(l){var h=A.Matrix[0];this.invertToRef(h),h.transposeToRef(l);var v=l._m;g.FromValuesToRef(v[0],v[1],v[2],0,v[4],v[5],v[6],0,v[8],v[9],v[10],0,0,0,0,1,l)},g.prototype.getRotationMatrix=function(){var l=new g;return this.getRotationMatrixToRef(l),l},g.prototype.getRotationMatrixToRef=function(l){var h=A.Vector3[0];if(!this.decompose(h))return g.IdentityToRef(l),this;var v=this._m,E=1/h._x,D=1/h._y,w=1/h._z;return g.FromValuesToRef(v[0]*E,v[1]*E,v[2]*E,0,v[4]*D,v[5]*D,v[6]*D,0,v[8]*w,v[9]*w,v[10]*w,0,0,0,0,1,l),this},g.prototype.toggleModelMatrixHandInPlace=function(){var l=this._m;l[2]*=-1,l[6]*=-1,l[8]*=-1,l[9]*=-1,l[14]*=-1,this._markAsUpdated()},g.prototype.toggleProjectionMatrixHandInPlace=function(){var l=this._m;l[8]*=-1,l[9]*=-1,l[10]*=-1,l[11]*=-1,this._markAsUpdated()},g.FromArray=function(l,h){h===void 0&&(h=0);var v=new g;return g.FromArrayToRef(l,h,v),v},g.FromArrayToRef=function(l,h,v){for(var E=0;E<16;E++)v._m[E]=l[E+h];v._markAsUpdated()},g.FromFloat32ArrayToRefScaled=function(l,h,v,E){for(var D=0;D<16;D++)E._m[D]=l[D+h]*v;E._markAsUpdated()},Object.defineProperty(g,"IdentityReadOnly",{get:function(){return g._identityReadOnly},enumerable:!1,configurable:!0}),g.FromValuesToRef=function(l,h,v,E,D,w,N,I,V,X,j,ne,te,de,pe,ae,ee){var K=ee._m;K[0]=l,K[1]=h,K[2]=v,K[3]=E,K[4]=D,K[5]=w,K[6]=N,K[7]=I,K[8]=V,K[9]=X,K[10]=j,K[11]=ne,K[12]=te,K[13]=de,K[14]=pe,K[15]=ae,ee._markAsUpdated()},g.FromValues=function(l,h,v,E,D,w,N,I,V,X,j,ne,te,de,pe,ae){var ee=new g,K=ee._m;return K[0]=l,K[1]=h,K[2]=v,K[3]=E,K[4]=D,K[5]=w,K[6]=N,K[7]=I,K[8]=V,K[9]=X,K[10]=j,K[11]=ne,K[12]=te,K[13]=de,K[14]=pe,K[15]=ae,ee._markAsUpdated(),ee},g.Compose=function(l,h,v){var E=new g;return g.ComposeToRef(l,h,v,E),E},g.ComposeToRef=function(l,h,v,E){var D=E._m,w=h._x,N=h._y,I=h._z,V=h._w,X=w+w,j=N+N,ne=I+I,te=w*X,de=w*j,pe=w*ne,ae=N*j,ee=N*ne,K=I*ne,$=V*X,L=V*j,G=V*ne,Q=l._x,oe=l._y,re=l._z;D[0]=(1-(ae+K))*Q,D[1]=(de+G)*Q,D[2]=(pe-L)*Q,D[3]=0,D[4]=(de-G)*oe,D[5]=(1-(te+K))*oe,D[6]=(ee+$)*oe,D[7]=0,D[8]=(pe+L)*re,D[9]=(ee-$)*re,D[10]=(1-(te+ae))*re,D[11]=0,D[12]=v._x,D[13]=v._y,D[14]=v._z,D[15]=1,E._markAsUpdated()},g.Identity=function(){var l=g.FromValues(1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1);return l._updateIdentityStatus(!0),l},g.IdentityToRef=function(l){g.FromValuesToRef(1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1,l),l._updateIdentityStatus(!0)},g.Zero=function(){var l=g.FromValues(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0);return l._updateIdentityStatus(!1),l},g.RotationX=function(l){var h=new g;return g.RotationXToRef(l,h),h},g.Invert=function(l){var h=new g;return l.invertToRef(h),h},g.RotationXToRef=function(l,h){var v=Math.sin(l),E=Math.cos(l);g.FromValuesToRef(1,0,0,0,0,E,v,0,0,-v,E,0,0,0,0,1,h),h._updateIdentityStatus(E===1&&v===0)},g.RotationY=function(l){var h=new g;return g.RotationYToRef(l,h),h},g.RotationYToRef=function(l,h){var v=Math.sin(l),E=Math.cos(l);g.FromValuesToRef(E,0,-v,0,0,1,0,0,v,0,E,0,0,0,0,1,h),h._updateIdentityStatus(E===1&&v===0)},g.RotationZ=function(l){var h=new g;return g.RotationZToRef(l,h),h},g.RotationZToRef=function(l,h){var v=Math.sin(l),E=Math.cos(l);g.FromValuesToRef(E,v,0,0,-v,E,0,0,0,0,1,0,0,0,0,1,h),h._updateIdentityStatus(E===1&&v===0)},g.RotationAxis=function(l,h){var v=new g;return g.RotationAxisToRef(l,h,v),v},g.RotationAxisToRef=function(l,h,v){var E=Math.sin(-h),D=Math.cos(-h),w=1-D;l.normalize();var N=v._m;N[0]=l._x*l._x*w+D,N[1]=l._x*l._y*w-l._z*E,N[2]=l._x*l._z*w+l._y*E,N[3]=0,N[4]=l._y*l._x*w+l._z*E,N[5]=l._y*l._y*w+D,N[6]=l._y*l._z*w-l._x*E,N[7]=0,N[8]=l._z*l._x*w-l._y*E,N[9]=l._z*l._y*w+l._x*E,N[10]=l._z*l._z*w+D,N[11]=0,N[12]=0,N[13]=0,N[14]=0,N[15]=1,v._markAsUpdated()},g.RotationAlignToRef=function(l,h,v){var E=x.Cross(h,l),D=x.Dot(h,l),w=1/(1+D),N=v._m;N[0]=E._x*E._x*w+D,N[1]=E._y*E._x*w-E._z,N[2]=E._z*E._x*w+E._y,N[3]=0,N[4]=E._x*E._y*w+E._z,N[5]=E._y*E._y*w+D,N[6]=E._z*E._y*w-E._x,N[7]=0,N[8]=E._x*E._z*w-E._y,N[9]=E._y*E._z*w+E._x,N[10]=E._z*E._z*w+D,N[11]=0,N[12]=0,N[13]=0,N[14]=0,N[15]=1,v._markAsUpdated()},g.RotationYawPitchRoll=function(l,h,v){var E=new g;return g.RotationYawPitchRollToRef(l,h,v,E),E},g.RotationYawPitchRollToRef=function(l,h,v,E){c.RotationYawPitchRollToRef(l,h,v,A.Quaternion[0]),A.Quaternion[0].toRotationMatrix(E)},g.Scaling=function(l,h,v){var E=new g;return g.ScalingToRef(l,h,v,E),E},g.ScalingToRef=function(l,h,v,E){g.FromValuesToRef(l,0,0,0,0,h,0,0,0,0,v,0,0,0,0,1,E),E._updateIdentityStatus(l===1&&h===1&&v===1)},g.Translation=function(l,h,v){var E=new g;return g.TranslationToRef(l,h,v,E),E},g.TranslationToRef=function(l,h,v,E){g.FromValuesToRef(1,0,0,0,0,1,0,0,0,0,1,0,l,h,v,1,E),E._updateIdentityStatus(l===0&&h===0&&v===0)},g.Lerp=function(l,h,v){var E=new g;return g.LerpToRef(l,h,v,E),E},g.LerpToRef=function(l,h,v,E){for(var D=E._m,w=l.m,N=h.m,I=0;I<16;I++)D[I]=w[I]*(1-v)+N[I]*v;E._markAsUpdated()},g.DecomposeLerp=function(l,h,v){var E=new g;return g.DecomposeLerpToRef(l,h,v,E),E},g.DecomposeLerpToRef=function(l,h,v,E){var D=A.Vector3[0],w=A.Quaternion[0],N=A.Vector3[1];l.decompose(D,w,N);var I=A.Vector3[2],V=A.Quaternion[1],X=A.Vector3[3];h.decompose(I,V,X);var j=A.Vector3[4];x.LerpToRef(D,I,v,j);var ne=A.Quaternion[2];c.SlerpToRef(w,V,v,ne);var te=A.Vector3[5];x.LerpToRef(N,X,v,te),g.ComposeToRef(j,ne,te,E)},g.LookAtLH=function(l,h,v){var E=new g;return g.LookAtLHToRef(l,h,v,E),E},g.LookAtLHToRef=function(l,h,v,E){var D=A.Vector3[0],w=A.Vector3[1],N=A.Vector3[2];h.subtractToRef(l,N),N.normalize(),x.CrossToRef(v,N,D);var I=D.lengthSquared();I===0?D.x=1:D.normalizeFromLength(Math.sqrt(I)),x.CrossToRef(N,D,w),w.normalize();var V=-x.Dot(D,l),X=-x.Dot(w,l),j=-x.Dot(N,l);g.FromValuesToRef(D._x,w._x,N._x,0,D._y,w._y,N._y,0,D._z,w._z,N._z,0,V,X,j,1,E)},g.LookAtRH=function(l,h,v){var E=new g;return g.LookAtRHToRef(l,h,v,E),E},g.LookAtRHToRef=function(l,h,v,E){var D=A.Vector3[0],w=A.Vector3[1],N=A.Vector3[2];l.subtractToRef(h,N),N.normalize(),x.CrossToRef(v,N,D);var I=D.lengthSquared();I===0?D.x=1:D.normalizeFromLength(Math.sqrt(I)),x.CrossToRef(N,D,w),w.normalize();var V=-x.Dot(D,l),X=-x.Dot(w,l),j=-x.Dot(N,l);g.FromValuesToRef(D._x,w._x,N._x,0,D._y,w._y,N._y,0,D._z,w._z,N._z,0,V,X,j,1,E)},g.OrthoLH=function(l,h,v,E){var D=new g;return g.OrthoLHToRef(l,h,v,E,D),D},g.OrthoLHToRef=function(l,h,v,E,D){var w=2/l,N=2/h,I=2/(E-v),V=-(E+v)/(E-v);g.FromValuesToRef(w,0,0,0,0,N,0,0,0,0,I,0,0,0,V,1,D),D._updateIdentityStatus(w===1&&N===1&&I===1&&V===0)},g.OrthoOffCenterLH=function(l,h,v,E,D,w){var N=new g;return g.OrthoOffCenterLHToRef(l,h,v,E,D,w,N),N},g.OrthoOffCenterLHToRef=function(l,h,v,E,D,w,N){var I=2/(h-l),V=2/(E-v),X=2/(w-D),j=-(w+D)/(w-D),ne=(l+h)/(l-h),te=(E+v)/(v-E);g.FromValuesToRef(I,0,0,0,0,V,0,0,0,0,X,0,ne,te,j,1,N),N._markAsUpdated()},g.OrthoOffCenterRH=function(l,h,v,E,D,w){var N=new g;return g.OrthoOffCenterRHToRef(l,h,v,E,D,w,N),N},g.OrthoOffCenterRHToRef=function(l,h,v,E,D,w,N){g.OrthoOffCenterLHToRef(l,h,v,E,D,w,N),N._m[10]*=-1},g.PerspectiveLH=function(l,h,v,E){var D=new g,w=2*v/l,N=2*v/h,I=(E+v)/(E-v),V=-2*E*v/(E-v);return g.FromValuesToRef(w,0,0,0,0,N,0,0,0,0,I,1,0,0,V,0,D),D._updateIdentityStatus(!1),D},g.PerspectiveFovLH=function(l,h,v,E){var D=new g;return g.PerspectiveFovLHToRef(l,h,v,E,D),D},g.PerspectiveFovLHToRef=function(l,h,v,E,D,w){w===void 0&&(w=!0);var N=v,I=E,V=1/Math.tan(.5*l),X=w?V/h:V,j=w?V:V*h,ne=(I+N)/(I-N),te=-2*I*N/(I-N);g.FromValuesToRef(X,0,0,0,0,j,0,0,0,0,ne,1,0,0,te,0,D),D._updateIdentityStatus(!1)},g.PerspectiveFovReverseLHToRef=function(l,h,v,E,D,w){w===void 0&&(w=!0);var N=1/Math.tan(.5*l),I=w?N/h:N,V=w?N:N*h;g.FromValuesToRef(I,0,0,0,0,V,0,0,0,0,-v,1,0,0,1,0,D),D._updateIdentityStatus(!1)},g.PerspectiveFovRH=function(l,h,v,E){var D=new g;return g.PerspectiveFovRHToRef(l,h,v,E,D),D},g.PerspectiveFovRHToRef=function(l,h,v,E,D,w){w===void 0&&(w=!0);var N=v,I=E,V=1/Math.tan(.5*l),X=w?V/h:V,j=w?V:V*h,ne=-(I+N)/(I-N),te=-2*I*N/(I-N);g.FromValuesToRef(X,0,0,0,0,j,0,0,0,0,ne,-1,0,0,te,0,D),D._updateIdentityStatus(!1)},g.PerspectiveFovReverseRHToRef=function(l,h,v,E,D,w){w===void 0&&(w=!0);var N=1/Math.tan(.5*l),I=w?N/h:N,V=w?N:N*h;g.FromValuesToRef(I,0,0,0,0,V,0,0,0,0,-v,-1,0,0,-1,0,D),D._updateIdentityStatus(!1)},g.PerspectiveFovWebVRToRef=function(l,h,v,E,D){D===void 0&&(D=!1);var w=D?-1:1,N=Math.tan(l.upDegrees*Math.PI/180),I=Math.tan(l.downDegrees*Math.PI/180),V=Math.tan(l.leftDegrees*Math.PI/180),X=Math.tan(l.rightDegrees*Math.PI/180),j=2/(V+X),ne=2/(N+I),te=E._m;te[0]=j,te[1]=te[2]=te[3]=te[4]=0,te[5]=ne,te[6]=te[7]=0,te[8]=(V-X)*j*.5,te[9]=-(N-I)*ne*.5,te[10]=-v/(h-v),te[11]=1*w,te[12]=te[13]=te[15]=0,te[14]=-2*v*h/(v-h),E._markAsUpdated()},g.GetFinalMatrix=function(l,h,v,E,D,w){var N=l.width,I=l.height,V=l.x,X=l.y,j=g.FromValues(N/2,0,0,0,0,-I/2,0,0,0,0,w-D,0,V+N/2,I/2+X,D,1),ne=A.Matrix[0];return h.multiplyToRef(v,ne),ne.multiplyToRef(E,ne),ne.multiply(j)},g.GetAsMatrix2x2=function(l){var h=l.m,v=[h[0],h[1],h[4],h[5]];return M.a.MatrixUse64Bits?v:new Float32Array(v)},g.GetAsMatrix3x3=function(l){var h=l.m,v=[h[0],h[1],h[2],h[4],h[5],h[6],h[8],h[9],h[10]];return M.a.MatrixUse64Bits?v:new Float32Array(v)},g.Transpose=function(l){var h=new g;return g.TransposeToRef(l,h),h},g.TransposeToRef=function(l,h){var v=h._m,E=l.m;v[0]=E[0],v[1]=E[4],v[2]=E[8],v[3]=E[12],v[4]=E[1],v[5]=E[5],v[6]=E[9],v[7]=E[13],v[8]=E[2],v[9]=E[6],v[10]=E[10],v[11]=E[14],v[12]=E[3],v[13]=E[7],v[14]=E[11],v[15]=E[15],h._updateIdentityStatus(l._isIdentity,l._isIdentityDirty)},g.Reflection=function(l){var h=new g;return g.ReflectionToRef(l,h),h},g.ReflectionToRef=function(l,h){l.normalize();var v=l.normal.x,E=l.normal.y,D=l.normal.z,w=-2*v,N=-2*E,I=-2*D;g.FromValuesToRef(w*v+1,N*v,I*v,0,w*E,N*E+1,I*E,0,w*D,N*D,I*D+1,0,w*l.d,N*l.d,I*l.d,1,h)},g.FromXYZAxesToRef=function(l,h,v,E){g.FromValuesToRef(l._x,l._y,l._z,0,h._x,h._y,h._z,0,v._x,v._y,v._z,0,0,0,0,1,E)},g.FromQuaternionToRef=function(l,h){var 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this.byteStride/C.GetTypeByteLength(this.type)},C.prototype.getOffset=function(){return this.byteOffset/C.GetTypeByteLength(this.type)},C.prototype.getSize=function(){return this._size},C.prototype.getIsInstanced=function(){return this._instanced},C.prototype.getInstanceDivisor=function(){return this._instanceDivisor},C.prototype.create=function(u){this._buffer.create(u)},C.prototype.update=function(u){this._buffer.update(u)},C.prototype.updateDirectly=function(u,M,R){R===void 0&&(R=!1),this._buffer.updateDirectly(u,M,void 0,R)},C.prototype.dispose=function(){this._ownsBuffer&&this._buffer.dispose()},C.prototype.forEach=function(u,M){C.ForEach(this._buffer.getData(),this.byteOffset,this.byteStride,this._size,this.type,u,this.normalized,M)},C.DeduceStride=function(u){switch(u){case C.UVKind:case C.UV2Kind:case C.UV3Kind:case C.UV4Kind:case C.UV5Kind:case C.UV6Kind:return 2;case C.NormalKind:case C.PositionKind:return 3;case C.ColorKind:case C.MatricesIndicesKind:case C.MatricesIndicesExtraKind:case C.MatricesWeightsKind:case C.MatricesWeightsExtraKind:case C.TangentKind:return 4;default:throw new Error("Invalid kind '"+u+"'")}},C.GetTypeByteLength=function(u){switch(u){case C.BYTE:case C.UNSIGNED_BYTE:return 1;case C.SHORT:case C.UNSIGNED_SHORT:return 2;case C.INT:case C.UNSIGNED_INT:case C.FLOAT:return 4;default:throw new Error("Invalid type '"+u+"'")}},C.ForEach=function(u,M,R,x,m,c,T,A){if(u instanceof Array)for(var S=M/4,g=R/4,l=0;l<c;l+=x){for(var h=0;h<x;h++)A(u[S+h],l+h);S+=g}else{var v=u instanceof ArrayBuffer?new DataView(u):new DataView(u.buffer,u.byteOffset,u.byteLength),E=C.GetTypeByteLength(m);for(l=0;l<c;l+=x){var D=M;for(h=0;h<x;h++)A(C._GetFloatValue(v,m,D,T),l+h),D+=E;M+=R}}},C._GetFloatValue=function(u,M,R,x){switch(M){case C.BYTE:var m=u.getInt8(R);return x&&(m=Math.max(m/127,-1)),m;case C.UNSIGNED_BYTE:return m=u.getUint8(R),x&&(m/=255),m;case C.SHORT:return m=u.getInt16(R,!0),x&&(m=Math.max(m/32767,-1)),m;case C.UNSIGNED_SHORT:return m=u.getUint16(R,!0),x&&(m/=65535),m;case C.INT:return u.getInt32(R,!0);case C.UNSIGNED_INT:return u.getUint32(R,!0);case C.FLOAT:return u.getFloat32(R,!0);default:throw new Error("Invalid component type "+M)}},C.BYTE=5120,C.UNSIGNED_BYTE=5121,C.SHORT=5122,C.UNSIGNED_SHORT=5123,C.INT=5124,C.UNSIGNED_INT=5125,C.FLOAT=5126,C.PositionKind="position",C.NormalKind="normal",C.TangentKind="tangent",C.UVKind="uv",C.UV2Kind="uv2",C.UV3Kind="uv3",C.UV4Kind="uv4",C.UV5Kind="uv5",C.UV6Kind="uv6",C.ColorKind="color",C.MatricesIndicesKind="matricesIndices",C.MatricesWeightsKind="matricesWeights",C.MatricesIndicesExtraKind="matricesIndicesExtra",C.MatricesWeightsExtraKind="matricesWeightsExtra",C}()},function(Me,y,f){f.d(y,"a",function(){return R});var U=f(6),_=f(2),C=f(38),u=f(8),M=f(128),R=function(){function x(m,c,T,A,S,g,l,h,v,E){var D,w=this;A===void 0&&(A=null),g===void 0&&(g=null),l===void 0&&(l=null),h===void 0&&(h=null),v===void 0&&(v=null),this.name=null,this.defines="",this.onCompiled=null,this.onError=null,this.onBind=null,this.uniqueId=0,this.onCompileObservable=new U.c,this.onErrorObservable=new U.c,this._onBindObservable=null,this._wasPreviouslyReady=!1,this._bonesComputationForcedToCPU=!1,this._multiTarget=!1,this._uniformBuffersNames={},this._samplers={},this._isReady=!1,this._compilationError="",this._allFallbacksProcessed=!1,this._uniforms={},this._key="",this._fallbacks=null,this._vertexSourceCode="",this._fragmentSourceCode="",this._vertexSourceCodeOverride="",this._fragmentSourceCodeOverride="",this._transformFeedbackVaryings=null,this._rawVertexSourceCode="",this._rawFragmentSourceCode="",this._pipelineContext=null,this._valueCache={},this.name=m;var N,I,V=null;if(c.attributes){var X=c;if(this._engine=T,this._attributesNames=X.attributes,this._uniformsNames=X.uniformsNames.concat(X.samplers),this._samplerList=X.samplers.slice(),this.defines=X.defines,this.onError=X.onError,this.onCompiled=X.onCompiled,this._fallbacks=X.fallbacks,this._indexParameters=X.indexParameters,this._transformFeedbackVaryings=X.transformFeedbackVaryings||null,this._multiTarget=!!X.multiTarget,X.uniformBuffersNames){this._uniformBuffersNamesList=X.uniformBuffersNames.slice();for(var j=0;j<X.uniformBuffersNames.length;j++)this._uniformBuffersNames[X.uniformBuffersNames[j]]=j}V=(D=X.processFinalCode)!==null&&D!==void 0?D:null}else this._engine=S,this.defines=g??"",this._uniformsNames=T.concat(A),this._samplerList=A?A.slice():[],this._attributesNames=c,this._uniformBuffersNamesList=[],this.onError=v,this.onCompiled=h,this._indexParameters=E,this._fallbacks=l;this._attributeLocationByName={},this.uniqueId=x._uniqueIdSeed++;var ne=C.a.IsWindowObjectExist()?this._engine.getHostDocument():null;m.vertexSource?N="source:"+m.vertexSource:m.vertexElement?(N=ne?ne.getElementById(m.vertexElement):null)||(N=m.vertexElement):N=m.vertex||m,m.fragmentSource?I="source:"+m.fragmentSource:m.fragmentElement?(I=ne?ne.getElementById(m.fragmentElement):null)||(I=m.fragmentElement):I=m.fragment||m;var te={defines:this.defines.split(`
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this._uniforms[m]},x.prototype.getSamplers=function(){return this._samplerList},x.prototype.getUniformNames=function(){return this._uniformsNames},x.prototype.getUniformBuffersNames=function(){return this._uniformBuffersNamesList},x.prototype.getIndexParameters=function(){return this._indexParameters},x.prototype.getCompilationError=function(){return this._compilationError},x.prototype.allFallbacksProcessed=function(){return this._allFallbacksProcessed},x.prototype.executeWhenCompiled=function(m){var c=this;this.isReady()?m(this):(this.onCompileObservable.add(function(T){m(T)}),this._pipelineContext&&!this._pipelineContext.isAsync||setTimeout(function(){c._checkIsReady(null)},16))},x.prototype._checkIsReady=function(m){var c=this;try{if(this._isReadyInternal())return}catch(T){return void this._processCompilationErrors(T,m)}setTimeout(function(){c._checkIsReady(m)},16)},x.prototype._loadShader=function(m,c,T,A){var S;if(typeof HTMLElement<"u"&&m instanceof HTMLElement)return void A(C.a.GetDOMTextContent(m));m.substr(0,7)!=="source:"?m.substr(0,7)!=="base64:"?x.ShadersStore[m+c+"Shader"]?A(x.ShadersStore[m+c+"Shader"]):T&&x.ShadersStore[m+T+"Shader"]?A(x.ShadersStore[m+T+"Shader"]):(S=m[0]==="."||m[0]==="/"||m.indexOf("http")>-1?m:x.ShadersRepository+m,this._engine._loadFile(S+"."+c.toLowerCase()+".fx",A)):A(window.atob(m.substr(7))):A(m.substr(7))},Object.defineProperty(x.prototype,"vertexSourceCode",{get:function(){return this._vertexSourceCodeOverride&&this._fragmentSourceCodeOverride?this._vertexSourceCodeOverride:this._vertexSourceCode},enumerable:!1,configurable:!0}),Object.defineProperty(x.prototype,"fragmentSourceCode",{get:function(){return this._vertexSourceCodeOverride&&this._fragmentSourceCodeOverride?this._fragmentSourceCodeOverride:this._fragmentSourceCode},enumerable:!1,configurable:!0}),Object.defineProperty(x.prototype,"rawVertexSourceCode",{get:function(){return this._rawVertexSourceCode},enumerable:!1,configurable:!0}),Object.defineProperty(x.prototype,"rawFragmentSourceCode",{get:function(){return this._rawFragmentSourceCode},enumerable:!1,configurable:!0}),x.prototype._rebuildProgram=function(m,c,T,A){var S=this;this._isReady=!1,this._vertexSourceCodeOverride=m,this._fragmentSourceCodeOverride=c,this.onError=function(g,l){A&&A(l)},this.onCompiled=function(){var g=S.getEngine().scenes;if(g)for(var l=0;l<g.length;l++)g[l].markAllMaterialsAsDirty(_.a.MATERIAL_AllDirtyFlag);S._pipelineContext._handlesSpectorRebuildCallback(T)},this._fallbacks=null,this._prepareEffect()},x.prototype._prepareEffect=function(){var m=this,c=this._attributesNames,T=this.defines;this._valueCache={};var A=this._pipelineContext;try{var S=this._engine;this._pipelineContext=S.createPipelineContext();var g=this._rebuildProgram.bind(this);this._vertexSourceCodeOverride&&this._fragmentSourceCodeOverride?S._preparePipelineContext(this._pipelineContext,this._vertexSourceCodeOverride,this._fragmentSourceCodeOverride,!0,g,null,this._transformFeedbackVaryings):S._preparePipelineContext(this._pipelineContext,this._vertexSourceCode,this._fragmentSourceCode,!1,g,T,this._transformFeedbackVaryings),S._executeWhenRenderingStateIsCompiled(this._pipelineContext,function(){if(S.supportsUniformBuffers)for(var l in m._uniformBuffersNames)m.bindUniformBlock(l,m._uniformBuffersNames[l]);var h;if(S.getUniforms(m._pipelineContext,m._uniformsNames).forEach(function(D,w){m._uniforms[m._uniformsNames[w]]=D}),m._attributes=S.getAttributes(m._pipelineContext,c),c)for(var v=0;v<c.length;v++){var E=c[v];m._attributeLocationByName[E]=m._attributes[v]}for(h=0;h<m._samplerList.length;h++)m.getUniform(m._samplerList[h])==null&&(m._samplerList.splice(h,1),h--);m._samplerList.forEach(function(D,w){m._samplers[D]=w}),S.bindSamplers(m),m._compilationError="",m._isReady=!0,m.onCompiled&&m.onCompiled(m),m.onCompileObservable.notifyObservers(m),m.onCompileObservable.clear(),m._fallbacks&&m._fallbacks.unBindMesh(),A&&m.getEngine()._deletePipelineContext(A)}),this._pipelineContext.isAsync&&this._checkIsReady(A)}catch(l){this._processCompilationErrors(l,A)}},x.prototype._getShaderCodeAndErrorLine=function(m,c,T){var A=T?/FRAGMENT SHADER ERROR: 0:(\d+?):/:/VERTEX SHADER ERROR: 0:(\d+?):/,S=null;if(c&&m){var g=c.match(A);if(g&&g.length===2){var l=parseInt(g[1]),h=m.split(`
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fallback."),this.defines=v.reduce(this.defines,this),this._prepareEffect()):(this._allFallbacksProcessed=!0,this.onError&&this.onError(this,this._compilationError),this.onErrorObservable.notifyObservers(this),this.onErrorObservable.clear(),this._fallbacks&&this._fallbacks.unBindMesh())):this._allFallbacksProcessed=!0},Object.defineProperty(x.prototype,"isSupported",{get:function(){return this._compilationError===""},enumerable:!1,configurable:!0}),x.prototype._bindTexture=function(m,c){this._engine._bindTexture(this._samplers[m],c)},x.prototype.setTexture=function(m,c){this._engine.setTexture(this._samplers[m],this._uniforms[m],c)},x.prototype.setDepthStencilTexture=function(m,c){this._engine.setDepthStencilTexture(this._samplers[m],this._uniforms[m],c)},x.prototype.setTextureArray=function(m,c){var T=m+"Ex";if(this._samplerList.indexOf(T+"0")===-1){for(var A=this._samplerList.indexOf(m),S=1;S<c.length;S++){var g=T+(S-1).toString();this._samplerList.splice(A+S,0,g)}for(var l=0,h=0,v=this._samplerList;h<v.length;h++){var E=v[h];this._samplers[E]=l,l+=1}}this._engine.setTextureArray(this._samplers[m],this._uniforms[m],c)},x.prototype.setTextureFromPostProcess=function(m,c){this._engine.setTextureFromPostProcess(this._samplers[m],c)},x.prototype.setTextureFromPostProcessOutput=function(m,c){this._engine.setTextureFromPostProcessOutput(this._samplers[m],c)},x.prototype._cacheMatrix=function(m,c){var T=this._valueCache[m],A=c.updateFlag;return(T===void 0||T!==A)&&(this._valueCache[m]=A,!0)},x.prototype._cacheFloat2=function(m,c,T){var A=this._valueCache[m];if(!A||A.length!==2)return A=[c,T],this._valueCache[m]=A,!0;var S=!1;return A[0]!==c&&(A[0]=c,S=!0),A[1]!==T&&(A[1]=T,S=!0),S},x.prototype._cacheFloat3=function(m,c,T,A){var S=this._valueCache[m];if(!S||S.length!==3)return S=[c,T,A],this._valueCache[m]=S,!0;var g=!1;return S[0]!==c&&(S[0]=c,g=!0),S[1]!==T&&(S[1]=T,g=!0),S[2]!==A&&(S[2]=A,g=!0),g},x.prototype._cacheFloat4=function(m,c,T,A,S){var g=this._valueCache[m];if(!g||g.length!==4)return g=[c,T,A,S],this._valueCache[m]=g,!0;var l=!1;return g[0]!==c&&(g[0]=c,l=!0),g[1]!==T&&(g[1]=T,l=!0),g[2]!==A&&(g[2]=A,l=!0),g[3]!==S&&(g[3]=S,l=!0),l},x.prototype.bindUniformBuffer=function(m,c){var T=this._uniformBuffersNames[c];T!==void 0&&x._baseCache[T]!==m&&(x._baseCache[T]=m,this._engine.bindUniformBufferBase(m,T))},x.prototype.bindUniformBlock=function(m,c){this._engine.bindUniformBlock(this._pipelineContext,m,c)},x.prototype.setInt=function(m,c){var T=this._valueCache[m];return T!==void 0&&T===c||this._engine.setInt(this._uniforms[m],c)&&(this._valueCache[m]=c),this},x.prototype.setIntArray=function(m,c){return this._valueCache[m]=null,this._engine.setIntArray(this._uniforms[m],c),this},x.prototype.setIntArray2=function(m,c){return this._valueCache[m]=null,this._engine.setIntArray2(this._uniforms[m],c),this},x.prototype.setIntArray3=function(m,c){return this._valueCache[m]=null,this._engine.setIntArray3(this._uniforms[m],c),this},x.prototype.setIntArray4=function(m,c){return this._valueCache[m]=null,this._engine.setIntArray4(this._uniforms[m],c),this},x.prototype.setFloatArray=function(m,c){return this._valueCache[m]=null,this._engine.setArray(this._uniforms[m],c),this},x.prototype.setFloatArray2=function(m,c){return this._valueCache[m]=null,this._engine.setArray2(this._uniforms[m],c),this},x.prototype.setFloatArray3=function(m,c){return this._valueCache[m]=null,this._engine.setArray3(this._uniforms[m],c),this},x.prototype.setFloatArray4=function(m,c){return this._valueCache[m]=null,this._engine.setArray4(this._uniforms[m],c),this},x.prototype.setArray=function(m,c){return this._valueCache[m]=null,this._engine.setArray(this._uniforms[m],c),this},x.prototype.setArray2=function(m,c){return this._valueCache[m]=null,this._engine.setArray2(this._uniforms[m],c),this},x.prototype.setArray3=function(m,c){return this._valueCache[m]=null,this._engine.setArray3(this._uniforms[m],c),this},x.prototype.setArray4=function(m,c){return this._valueCache[m]=null,this._engine.setArray4(this._uniforms[m],c),this},x.prototype.setMatrices=function(m,c){return c?(this._valueCache[m]=null,this._engine.setMatrices(this._uniforms[m],c),this):this},x.prototype.setMatrix=function(m,c){return this._cacheMatrix(m,c)&&(this._engine.setMatrices(this._uniforms[m],c.toArray())||(this._valueCache[m]=null)),this},x.prototype.setMatrix3x3=function(m,c){return this._valueCache[m]=null,this._engine.setMatrix3x3(this._uniforms[m],c),this},x.prototype.setMatrix2x2=function(m,c){return this._valueCache[m]=null,this._engine.setMatrix2x2(this._uniforms[m],c),this},x.prototype.setFloat=function(m,c){var T=this._valueCache[m];return T!==void 0&&T===c||this._engine.setFloat(this._uniforms[m],c)&&(this._valueCache[m]=c),this},x.prototype.setBool=function(m,c){var T=this._valueCache[m];return T!==void 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Array),this._instanceDataStorage.visibleInstances[Q].push(G),this},L.prototype._afterComputeWorldMatrix=function(){$.prototype._afterComputeWorldMatrix.call(this),this.hasThinInstances&&(this.doNotSyncBoundingInfo||this.thinInstanceRefreshBoundingInfo(!1))},L.prototype._postActivate=function(){this.edgesShareWithInstances&&this.edgesRenderer&&this.edgesRenderer.isEnabled&&this._renderingGroup&&(this._renderingGroup._edgesRenderers.pushNoDuplicate(this.edgesRenderer),this.edgesRenderer.customInstances.push(this.getWorldMatrix()))},L.prototype.refreshBoundingInfo=function(G){if(G===void 0&&(G=!1),this._boundingInfo&&this._boundingInfo.isLocked)return this;var Q=this.geometry?this.geometry.boundingBias:null;return this._refreshBoundingInfo(this._getPositionData(G),Q),this},L.prototype._createGlobalSubMesh=function(G){var Q=this.getTotalVertices();if(!Q||!this.getIndices())return null;if(this.subMeshes&&this.subMeshes.length>0){var oe=this.getIndices();if(!oe)return null;var re=oe.length,Y=!1;if(G)Y=!0;else for(var k=0,H=this.subMeshes;k<H.length;k++){var Z=H[k];if(Z.indexStart+Z.indexCount>re){Y=!0;break}if(Z.verticesStart+Z.verticesCount>Q){Y=!0;break}}if(!Y)return this.subMeshes[0]}return this.releaseSubMeshes(),new g.a(0,0,Q,0,this.getTotalIndices(),this)},L.prototype.subdivide=function(G){if(!(G<1)){for(var Q=this.getTotalIndices(),oe=Q/G|0,re=0;oe%3!=0;)oe++;this.releaseSubMeshes();for(var Y=0;Y<G&&!(re>=Q);Y++)g.a.CreateFromIndices(0,re,Y===G-1?Q-re:oe,this),re+=oe;this.synchronizeInstances()}},L.prototype.setVerticesData=function(G,Q,oe,re){if(oe===void 0&&(oe=!1),this._geometry)this._geometry.setVerticesData(G,Q,oe,re);else{var Y=new T.a;Y.set(Q,G);var k=this.getScene();new A.a(A.a.RandomId(),k,Y,oe,this)}return this},L.prototype.removeVerticesData=function(G){this._geometry&&this._geometry.removeVerticesData(G)},L.prototype.markVerticesDataAsUpdatable=function(G,Q){Q===void 0&&(Q=!0);var oe=this.getVertexBuffer(G);oe&&oe.isUpdatable()!==Q&&this.setVerticesData(G,this.getVerticesData(G),Q)},L.prototype.setVerticesBuffer=function(G){return this._geometry||(this._geometry=A.a.CreateGeometryForMesh(this)),this._geometry.setVerticesBuffer(G),this},L.prototype.updateVerticesData=function(G,Q,oe,re){return this._geometry?(re?(this.makeGeometryUnique(),this.updateVerticesData(G,Q,oe,!1)):this._geometry.updateVerticesData(G,Q,oe),this):this},L.prototype.updateMeshPositions=function(G,Q){Q===void 0&&(Q=!0);var oe=this.getVerticesData(c.b.PositionKind);if(!oe)return this;if(G(oe),this.updateVerticesData(c.b.PositionKind,oe,!1,!1),Q){var re=this.getIndices(),Y=this.getVerticesData(c.b.NormalKind);if(!Y)return this;T.a.ComputeNormals(oe,re,Y),this.updateVerticesData(c.b.NormalKind,Y,!1,!1)}return this},L.prototype.makeGeometryUnique=function(){if(!this._geometry)return this;if(this._geometry.meshes.length===1)return this;var G=this._geometry,Q=this._geometry.copy(A.a.RandomId());return G.releaseForMesh(this,!0),Q.applyToMesh(this),this},L.prototype.setIndices=function(G,Q,oe){if(Q===void 0&&(Q=null),oe===void 0&&(oe=!1),this._geometry)this._geometry.setIndices(G,Q,oe);else{var re=new T.a;re.indices=G;var Y=this.getScene();new A.a(A.a.RandomId(),Y,re,oe,this)}return this},L.prototype.updateIndices=function(G,Q,oe){return oe===void 0&&(oe=!1),this._geometry?(this._geometry.updateIndices(G,Q,oe),this):this},L.prototype.toLeftHanded=function(){return this._geometry?(this._geometry.toLeftHanded(),this):this},L.prototype._bind=function(G,Q,oe){if(!this._geometry)return this;var re,Y=this.getScene().getEngine();if(this._unIndexed)re=null;else switch(oe){case h.a.PointFillMode:re=null;break;case h.a.WireFrameFillMode:re=G._getLinesIndexBuffer(this.getIndices(),Y);break;default:case h.a.TriangleFillMode:re=this._geometry.getIndexBuffer()}return this._geometry._bind(Q,re),this},L.prototype._draw=function(G,Q,oe){if(!this._geometry||!this._geometry.getVertexBuffers()||!this._unIndexed&&!this._geometry.getIndexBuffer())return this;this._internalMeshDataInfo._onBeforeDrawObservable&&this._internalMeshDataInfo._onBeforeDrawObservable.notifyObservers(this);var re=this.getScene().getEngine();return this._unIndexed||Q==h.a.PointFillMode?re.drawArraysType(Q,G.verticesStart,G.verticesCount,oe):Q==h.a.WireFrameFillMode?re.drawElementsType(Q,0,G._linesIndexCount,oe):re.drawElementsType(Q,G.indexStart,G.indexCount,oe),this},L.prototype.registerBeforeRender=function(G){return this.onBeforeRenderObservable.add(G),this},L.prototype.unregisterBeforeRender=function(G){return this.onBeforeRenderObservable.removeCallback(G),this},L.prototype.registerAfterRender=function(G){return this.onAfterRenderObservable.add(G),this},L.prototype.unregisterAfterRender=function(G){return this.onAfterRenderObservable.removeCallback(G),this},L.prototype._getInstancesRenderList=function(G,Q){if(Q===void 0&&(Q=!1),this._instanceDataStorage.isFrozen&&this._instanceDataStorage.previousBatch)return this._instanceDataStorage.previousBatch;var oe=this.getScene(),re=oe._isInIntermediateRendering(),Y=re?this._internalAbstractMeshDataInfo._onlyForInstancesIntermediate:this._internalAbstractMeshDataInfo._onlyForInstances,k=this._instanceDataStorage.batchCache;if(k.mustReturn=!1,k.renderSelf[G]=Q||!Y&&this.isEnabled()&&this.isVisible,k.visibleInstances[G]=null,this._instanceDataStorage.visibleInstances&&!Q){var H=this._instanceDataStorage.visibleInstances,Z=oe.getRenderId(),W=re?H.intermediateDefaultRenderId:H.defaultRenderId;k.visibleInstances[G]=H[Z],!k.visibleInstances[G]&&W&&(k.visibleInstances[G]=H[W])}return k.hardwareInstancedRendering[G]=!Q&&this._instanceDataStorage.hardwareInstancedRendering&&k.visibleInstances[G]!==null&&k.visibleInstances[G]!==void 0,this._instanceDataStorage.previousBatch=k,k},L.prototype._renderWithInstances=function(G,Q,oe,re,Y){var k=oe.visibleInstances[G._id];if(!k)return this;for(var H=this._instanceDataStorage,Z=H.instancesBufferSize,W=H.instancesBuffer,q=16*(k.length+1)*4;H.instancesBufferSize<q;)H.instancesBufferSize*=2;H.instancesData&&Z==H.instancesBufferSize||(H.instancesData=new Float32Array(H.instancesBufferSize/4));var he=0,ge=0,me=oe.renderSelf[G._id],_e=!W||Z!==H.instancesBufferSize;if(this._instanceDataStorage.manualUpdate||H.isFrozen&&!_e)ge=(me?1:0)+k.length;else{var be=this._effectiveMesh.getWorldMatrix();if(me&&(be.copyToArray(H.instancesData,he),he+=16,ge++),k)for(var Pe=0;Pe<k.length;Pe++)k[Pe].getWorldMatrix().copyToArray(H.instancesData,he),he+=16,ge++}return _e?(W&&W.dispose(),W=new c.a(Y,H.instancesData,!0,16,!1,!0),H.instancesBuffer=W,this.setVerticesBuffer(W.createVertexBuffer("world0",0,4)),this.setVerticesBuffer(W.createVertexBuffer("world1",4,4)),this.setVerticesBuffer(W.createVertexBuffer("world2",8,4)),this.setVerticesBuffer(W.createVertexBuffer("world3",12,4))):this._instanceDataStorage.isFrozen||W.updateDirectly(H.instancesData,0,ge),this._processInstancedBuffers(k,me),this.getScene()._activeIndices.addCount(G.indexCount*ge,!1),this._bind(G,re,Q),this._draw(G,Q,ge),Y.unbindInstanceAttributes(),this},L.prototype._renderWithThinInstances=function(G,Q,oe,re){var Y,k,H=(k=(Y=this._thinInstanceDataStorage)===null||Y===void 0?void 0:Y.instancesCount)!==null&&k!==void 0?k:0;this.getScene()._activeIndices.addCount(G.indexCount*H,!1),this._bind(G,oe,Q),this._draw(G,Q,H),re.unbindInstanceAttributes()},L.prototype._processInstancedBuffers=function(G,Q){},L.prototype._processRendering=function(G,Q,oe,re,Y,k,H,Z){var W=this.getScene(),q=W.getEngine();if(k&&Q.getRenderingMesh().hasThinInstances)return this._renderWithThinInstances(Q,re,oe,q),this;if(k)this._renderWithInstances(Q,re,Y,oe,q);else{var he=0;Y.renderSelf[Q._id]&&(H&&H(!1,G._effectiveMesh.getWorldMatrix(),Z),he++,this._draw(Q,re,this._instanceDataStorage.overridenInstanceCount));var ge=Y.visibleInstances[Q._id];if(ge){var me=ge.length;he+=me;for(var _e=0;_e<me;_e++){var be=ge[_e].getWorldMatrix();H&&H(!0,be,Z),this._draw(Q,re)}}W._activeIndices.addCount(Q.indexCount*he,!1)}return this},L.prototype._rebuild=function(){this._instanceDataStorage.instancesBuffer&&(this._instanceDataStorage.instancesBuffer.dispose(),this._instanceDataStorage.instancesBuffer=null),$.prototype._rebuild.call(this)},L.prototype._freeze=function(){if(this.subMeshes){for(var G=0;G<this.subMeshes.length;G++)this._getInstancesRenderList(G);this._effectiveMaterial=null,this._instanceDataStorage.isFrozen=!0}},L.prototype._unFreeze=function(){this._instanceDataStorage.isFrozen=!1,this._instanceDataStorage.previousBatch=null},L.prototype.render=function(G,Q,oe){var re=this.getScene();if(this._internalAbstractMeshDataInfo._isActiveIntermediate?this._internalAbstractMeshDataInfo._isActiveIntermediate=!1:this._internalAbstractMeshDataInfo._isActive=!1,this._checkOcclusionQuery())return this;var Y=this._getInstancesRenderList(G._id,!!oe);if(Y.mustReturn)return this;if(!this._geometry||!this._geometry.getVertexBuffers()||!this._unIndexed&&!this._geometry.getIndexBuffer())return this;this._internalMeshDataInfo._onBeforeRenderObservable&&this._internalMeshDataInfo._onBeforeRenderObservable.notifyObservers(this);var k,H=re.getEngine(),Z=Y.hardwareInstancedRendering[G._id]||G.getRenderingMesh().hasThinInstances,W=this._instanceDataStorage,q=G.getMaterial();if(!q)return this;if(!W.isFrozen||!this._effectiveMaterial||this._effectiveMaterial!==q){if(q._storeEffectOnSubMeshes){if(!q.isReadyForSubMesh(this,G,Z))return this}else if(!q.isReady(this,Z))return this;this._effectiveMaterial=q}Q&&H.setAlphaMode(this._effectiveMaterial.alphaMode),k=this._effectiveMaterial._storeEffectOnSubMeshes?G.effect:this._effectiveMaterial.getEffect();for(var he=0,ge=re._beforeRenderingMeshStage;he<ge.length;he++)ge[he].action(this,G,Y,k);if(!k)return this;var me,_e=oe||this._effectiveMesh;if(W.isFrozen||!this._effectiveMaterial.backFaceCulling&&this.overrideMaterialSideOrientation===null)me=W.sideOrientation;else{var be=_e._getWorldMatrixDeterminant();(me=this.overrideMaterialSideOrientation)==null&&(me=this._effectiveMaterial.sideOrientation),be<0&&(me=me===h.a.ClockWiseSideOrientation?h.a.CounterClockWiseSideOrientation:h.a.ClockWiseSideOrientation),W.sideOrientation=me}var Pe=this._effectiveMaterial._preBind(k,me);this._effectiveMaterial.forceDepthWrite&&H.setDepthWrite(!0);var ye=re.forcePointsCloud?h.a.PointFillMode:re.forceWireframe?h.a.WireFrameFillMode:this._effectiveMaterial.fillMode;this._internalMeshDataInfo._onBeforeBindObservable&&this._internalMeshDataInfo._onBeforeBindObservable.notifyObservers(this),Z||this._bind(G,k,ye);var Be=_e.getWorldMatrix();this._effectiveMaterial._storeEffectOnSubMeshes?this._effectiveMaterial.bindForSubMesh(Be,this,G):this._effectiveMaterial.bind(Be,this),!this._effectiveMaterial.backFaceCulling&&this._effectiveMaterial.separateCullingPass&&(H.setState(!0,this._effectiveMaterial.zOffset,!1,!Pe),this._processRendering(this,G,k,ye,Y,Z,this._onBeforeDraw,this._effectiveMaterial),H.setState(!0,this._effectiveMaterial.zOffset,!1,Pe)),this._processRendering(this,G,k,ye,Y,Z,this._onBeforeDraw,this._effectiveMaterial),this._effectiveMaterial.unbind();for(var ke=0,We=re._afterRenderingMeshStage;ke<We.length;ke++)We[ke].action(this,G,Y,k);return this._internalMeshDataInfo._onAfterRenderObservable&&this._internalMeshDataInfo._onAfterRenderObservable.notifyObservers(this),this},L.prototype._onBeforeDraw=function(G,Q,oe){G&&oe&&oe.bindOnlyWorldMatrix(Q)},L.prototype.cleanMatrixWeights=function(){this.isVerticesDataPresent(c.b.MatricesWeightsKind)&&(this.isVerticesDataPresent(c.b.MatricesWeightsExtraKind)?this.normalizeSkinWeightsAndExtra():this.normalizeSkinFourWeights())},L.prototype.normalizeSkinFourWeights=function(){for(var G=this.getVerticesData(c.b.MatricesWeightsKind),Q=G.length,oe=0;oe<Q;oe+=4){var re=G[oe]+G[oe+1]+G[oe+2]+G[oe+3];if(re===0)G[oe]=1;else{var Y=1/re;G[oe]*=Y,G[oe+1]*=Y,G[oe+2]*=Y,G[oe+3]*=Y}}this.setVerticesData(c.b.MatricesWeightsKind,G)},L.prototype.normalizeSkinWeightsAndExtra=function(){for(var G=this.getVerticesData(c.b.MatricesWeightsExtraKind),Q=this.getVerticesData(c.b.MatricesWeightsKind),oe=Q.length,re=0;re<oe;re+=4){var Y=Q[re]+Q[re+1]+Q[re+2]+Q[re+3];if((Y+=G[re]+G[re+1]+G[re+2]+G[re+3])===0)Q[re]=1;else{var k=1/Y;Q[re]*=k,Q[re+1]*=k,Q[re+2]*=k,Q[re+3]*=k,G[re]*=k,G[re+1]*=k,G[re+2]*=k,G[re+3]*=k}}this.setVerticesData(c.b.MatricesWeightsKind,Q),this.setVerticesData(c.b.MatricesWeightsKind,G)},L.prototype.validateSkinning=function(){var G=this.getVerticesData(c.b.MatricesWeightsExtraKind),Q=this.getVerticesData(c.b.MatricesWeightsKind);if(Q===null||this.skeleton==null)return{skinned:!1,valid:!0,report:"not skinned"};for(var oe=Q.length,re=0,Y=0,k=0,H=0,Z=G===null?4:8,W=new Array,q=0;q<=Z;q++)W[q]=0;for(q=0;q<oe;q+=4){for(var he=Q[q],ge=he,me=ge===0?0:1,_e=1;_e<Z;_e++){var be=_e<4?Q[q+_e]:G[q+_e-4];be>he&&re++,be!==0&&me++,ge+=be,he=be}if(W[me]++,me>k&&(k=me),ge===0)Y++;else{var Pe=1/ge,ye=0;for(_e=0;_e<Z;_e++)ye+=_e<4?Math.abs(Q[q+_e]-Q[q+_e]*Pe):Math.abs(G[q+_e-4]-G[q+_e-4]*Pe);ye>.001&&H++}}var Be=this.skeleton.bones.length,ke=this.getVerticesData(c.b.MatricesIndicesKind),We=this.getVerticesData(c.b.MatricesIndicesExtraKind),je=0;for(q=0;q<oe;q+=4)for(_e=0;_e<Z;_e++){var He=_e<4?ke[q+_e]:We[q+_e-4];(He>=Be||He<0)&&je++}return{skinned:!0,valid:Y===0&&H===0&&je===0,report:"Number of Weights = "+oe/4+`
-Maximum influences = `+k+`
-Missing Weights = `+Y+`
-Not Sorted = `+re+`
-Not Normalized = `+H+`
-WeightCounts = [`+W+`]
-Number of bones = `+Be+`
-Bad Bone Indices = `+je}},L.prototype._checkDelayState=function(){var G=this.getScene();return this._geometry?this._geometry.load(G):this.delayLoadState===D.a.DELAYLOADSTATE_NOTLOADED&&(this.delayLoadState=D.a.DELAYLOADSTATE_LOADING,this._queueLoad(G)),this},L.prototype._queueLoad=function(G){var Q=this;G._addPendingData(this);var oe=this.delayLoadingFile.indexOf(".babylonbinarymeshdata")!==-1;return C.b.LoadFile(this.delayLoadingFile,function(re){re instanceof ArrayBuffer?Q._delayLoadingFunction(re,Q):Q._delayLoadingFunction(JSON.parse(re),Q),Q.instances.forEach(function(Y){Y.refreshBoundingInfo(),Y._syncSubMeshes()}),Q.delayLoadState=D.a.DELAYLOADSTATE_LOADED,G._removePendingData(Q)},function(){},G.offlineProvider,oe),this},L.prototype.isInFrustum=function(G){return this.delayLoadState!==D.a.DELAYLOADSTATE_LOADING&&!!$.prototype.isInFrustum.call(this,G)&&(this._checkDelayState(),!0)},L.prototype.setMaterialByID=function(G){var Q,oe=this.getScene().materials;for(Q=oe.length-1;Q>-1;Q--)if(oe[Q].id===G)return this.material=oe[Q],this;var re=this.getScene().multiMaterials;for(Q=re.length-1;Q>-1;Q--)if(re[Q].id===G)return this.material=re[Q],this;return this},L.prototype.getAnimatables=function(){var G=new Array;return this.material&&G.push(this.material),this.skeleton&&G.push(this.skeleton),G},L.prototype.bakeTransformIntoVertices=function(G){if(!this.isVerticesDataPresent(c.b.PositionKind))return this;var Q=this.subMeshes.splice(0);this._resetPointsArrayCache();var oe,re=this.getVerticesData(c.b.PositionKind),Y=new Array;for(oe=0;oe<re.length;oe+=3)R.e.TransformCoordinates(R.e.FromArray(re,oe),G).toArray(Y,oe);if(this.setVerticesData(c.b.PositionKind,Y,this.getVertexBuffer(c.b.PositionKind).isUpdatable()),this.isVerticesDataPresent(c.b.NormalKind)){for(re=this.getVerticesData(c.b.NormalKind),Y=[],oe=0;oe<re.length;oe+=3)R.e.TransformNormal(R.e.FromArray(re,oe),G).normalize().toArray(Y,oe);this.setVerticesData(c.b.NormalKind,Y,this.getVertexBuffer(c.b.NormalKind).isUpdatable())}return G.m[0]*G.m[5]*G.m[10]<0&&this.flipFaces(),this.releaseSubMeshes(),this.subMeshes=Q,this},L.prototype.bakeCurrentTransformIntoVertices=function(G){return G===void 0&&(G=!0),this.bakeTransformIntoVertices(this.computeWorldMatrix(!0)),this.resetLocalMatrix(G),this},Object.defineProperty(L.prototype,"_positions",{get:function(){return this._geometry?this._geometry._positions:null},enumerable:!1,configurable:!0}),L.prototype._resetPointsArrayCache=function(){return this._geometry&&this._geometry._resetPointsArrayCache(),this},L.prototype._generatePointsArray=function(){return!!this._geometry&&this._geometry._generatePointsArray()},L.prototype.clone=function(G,Q,oe,re){return G===void 0&&(G=""),Q===void 0&&(Q=null),re===void 0&&(re=!0),new L(G,this.getScene(),Q,this,oe,re)},L.prototype.dispose=function(G,Q){Q===void 0&&(Q=!1),this.morphTargetManager=null,this._geometry&&this._geometry.releaseForMesh(this,!0);var oe=this._internalMeshDataInfo;if(oe._onBeforeDrawObservable&&oe._onBeforeDrawObservable.clear(),oe._onBeforeBindObservable&&oe._onBeforeBindObservable.clear(),oe._onBeforeRenderObservable&&oe._onBeforeRenderObservable.clear(),oe._onAfterRenderObservable&&oe._onAfterRenderObservable.clear(),this._scene.useClonedMeshMap){if(oe.meshMap)for(var re in oe.meshMap)(H=oe.meshMap[re])&&(H._internalMeshDataInfo._source=null,oe.meshMap[re]=void 0);oe._source&&oe._source._internalMeshDataInfo.meshMap&&(oe._source._internalMeshDataInfo.meshMap[this.uniqueId]=void 0)}else for(var Y=0,k=this.getScene().meshes;Y<k.length;Y++){var H;(H=k[Y])._internalMeshDataInfo&&H._internalMeshDataInfo._source&&H._internalMeshDataInfo._source===this&&(H._internalMeshDataInfo._source=null)}oe._source=null,this._disposeInstanceSpecificData(),this._disposeThinInstanceSpecificData(),$.prototype.dispose.call(this,G,Q)},L.prototype._disposeInstanceSpecificData=function(){},L.prototype._disposeThinInstanceSpecificData=function(){},L.prototype.applyDisplacementMap=function(G,Q,oe,re,Y,k,H){var Z=this;H===void 0&&(H=!1);var W=this.getScene();return C.b.LoadImage(G,function(q){var he=q.width,ge=q.height,me=ne.a.CreateCanvas(he,ge).getContext("2d");me.drawImage(q,0,0);var _e=me.getImageData(0,0,he,ge).data;Z.applyDisplacementMapFromBuffer(_e,he,ge,Q,oe,Y,k,H),re&&re(Z)},function(){},W.offlineProvider),this},L.prototype.applyDisplacementMapFromBuffer=function(G,Q,oe,re,Y,k,H,Z){if(Z===void 0&&(Z=!1),!this.isVerticesDataPresent(c.b.PositionKind)||!this.isVerticesDataPresent(c.b.NormalKind)||!this.isVerticesDataPresent(c.b.UVKind))return N.a.Warn("Cannot call applyDisplacementMap: Given mesh is not complete. Position, Normal or UV are missing"),this;var W=this.getVerticesData(c.b.PositionKind,!0,!0),q=this.getVerticesData(c.b.NormalKind),he=this.getVerticesData(c.b.UVKind),ge=R.e.Zero(),me=R.e.Zero(),_e=R.d.Zero();k=k||R.d.Zero(),H=H||new R.d(1,1);for(var be=0;be<W.length;be+=3){R.e.FromArrayToRef(W,be,ge),R.e.FromArrayToRef(q,be,me),R.d.FromArrayToRef(he,be/3*2,_e);var Pe=4*((Math.abs(_e.x*H.x+k.x%1)*(Q-1)%Q|0)+(Math.abs(_e.y*H.y+k.y%1)*(oe-1)%oe|0)*Q),ye=.3*(G[Pe]/255)+.59*(G[Pe+1]/255)+.11*(G[Pe+2]/255);me.normalize(),me.scaleInPlace(re+(Y-re)*ye),(ge=ge.add(me)).toArray(W,be)}return T.a.ComputeNormals(W,this.getIndices(),q),Z?(this.setVerticesData(c.b.PositionKind,W),this.setVerticesData(c.b.NormalKind,q)):(this.updateVerticesData(c.b.PositionKind,W),this.updateVerticesData(c.b.NormalKind,q)),this},L.prototype.convertToFlatShadedMesh=function(){var G,Q,oe=this.getVerticesDataKinds(),re={},Y={},k={},H=!1;for(G=0;G<oe.length;G++){Q=oe[G];var Z=this.getVertexBuffer(Q);Q!==c.b.NormalKind?(re[Q]=Z,Y[Q]=re[Q].getData(),k[Q]=[]):(H=Z.isUpdatable(),oe.splice(G,1),G--)}var W,q=this.subMeshes.slice(0),he=this.getIndices(),ge=this.getTotalIndices();for(W=0;W<ge;W++){var me=he[W];for(G=0;G<oe.length;G++)for(var _e=re[Q=oe[G]].getStrideSize(),be=0;be<_e;be++)k[Q].push(Y[Q][me*_e+be])}var Pe=[],ye=k[c.b.PositionKind];for(W=0;W<ge;W+=3){he[W]=W,he[W+1]=W+1,he[W+2]=W+2;for(var Be=R.e.FromArray(ye,3*W),ke=R.e.FromArray(ye,3*(W+1)),We=R.e.FromArray(ye,3*(W+2)),je=Be.subtract(ke),He=We.subtract(ke),qe=R.e.Normalize(R.e.Cross(je,He)),Ge=0;Ge<3;Ge++)Pe.push(qe.x),Pe.push(qe.y),Pe.push(qe.z)}for(this.setIndices(he),this.setVerticesData(c.b.NormalKind,Pe,H),G=0;G<oe.length;G++)Q=oe[G],this.setVerticesData(Q,k[Q],re[Q].isUpdatable());this.releaseSubMeshes();for(var nt=0;nt<q.length;nt++){var $e=q[nt];g.a.AddToMesh($e.materialIndex,$e.indexStart,$e.indexCount,$e.indexStart,$e.indexCount,this)}return this.synchronizeInstances(),this},L.prototype.convertToUnIndexedMesh=function(){var G,Q,oe=this.getVerticesDataKinds(),re={},Y={},k={};for(G=0;G<oe.length;G++){Q=oe[G];var H=this.getVertexBuffer(Q);re[Q]=H,Y[Q]=re[Q].getData(),k[Q]=[]}var Z,W=this.subMeshes.slice(0),q=this.getIndices(),he=this.getTotalIndices();for(Z=0;Z<he;Z++){var ge=q[Z];for(G=0;G<oe.length;G++)for(var me=re[Q=oe[G]].getStrideSize(),_e=0;_e<me;_e++)k[Q].push(Y[Q][ge*me+_e])}for(Z=0;Z<he;Z+=3)q[Z]=Z,q[Z+1]=Z+1,q[Z+2]=Z+2;for(this.setIndices(q),G=0;G<oe.length;G++)Q=oe[G],this.setVerticesData(Q,k[Q],re[Q].isUpdatable());this.releaseSubMeshes();for(var be=0;be<W.length;be++){var Pe=W[be];g.a.AddToMesh(Pe.materialIndex,Pe.indexStart,Pe.indexCount,Pe.indexStart,Pe.indexCount,this)}return this._unIndexed=!0,this.synchronizeInstances(),this},L.prototype.flipFaces=function(G){G===void 0&&(G=!1);var Q,oe,re=T.a.ExtractFromMesh(this);if(G&&this.isVerticesDataPresent(c.b.NormalKind)&&re.normals)for(Q=0;Q<re.normals.length;Q++)re.normals[Q]*=-1;if(re.indices)for(Q=0;Q<re.indices.length;Q+=3)oe=re.indices[Q+1],re.indices[Q+1]=re.indices[Q+2],re.indices[Q+2]=oe;return re.applyToMesh(this,this.isVertexBufferUpdatable(c.b.PositionKind)),this},L.prototype.increaseVertices=function(G){var Q=T.a.ExtractFromMesh(this),oe=Q.uvs,re=Q.indices,Y=Q.positions,k=Q.normals;if(re&&Y&&k&&oe){for(var H,Z,W=G+1,q=new Array,he=0;he<W+1;he++)q[he]=new Array;var ge,me=new R.e(0,0,0),_e=new R.e(0,0,0),be=new R.d(0,0),Pe=new Array,ye=new Array,Be=new Array,ke=Y.length,We=oe.length;for(he=0;he<re.length;he+=3){ye[0]=re[he],ye[1]=re[he+1],ye[2]=re[he+2];for(var je=0;je<3;je++)if(H=ye[je],Z=ye[(je+1)%3],Be[H]===void 0&&Be[Z]===void 0?(Be[H]=new Array,Be[Z]=new Array):(Be[H]===void 0&&(Be[H]=new Array),Be[Z]===void 0&&(Be[Z]=new Array)),Be[H][Z]===void 0&&Be[Z][H]===void 0){Be[H][Z]=[],me.x=(Y[3*Z]-Y[3*H])/W,me.y=(Y[3*Z+1]-Y[3*H+1])/W,me.z=(Y[3*Z+2]-Y[3*H+2])/W,_e.x=(k[3*Z]-k[3*H])/W,_e.y=(k[3*Z+1]-k[3*H+1])/W,_e.z=(k[3*Z+2]-k[3*H+2])/W,be.x=(oe[2*Z]-oe[2*H])/W,be.y=(oe[2*Z+1]-oe[2*H+1])/W,Be[H][Z].push(H);for(var He=1;He<W;He++)Be[H][Z].push(Y.length/3),Y[ke]=Y[3*H]+He*me.x,k[ke++]=k[3*H]+He*_e.x,Y[ke]=Y[3*H+1]+He*me.y,k[ke++]=k[3*H+1]+He*_e.y,Y[ke]=Y[3*H+2]+He*me.z,k[ke++]=k[3*H+2]+He*_e.z,oe[We++]=oe[2*H]+He*be.x,oe[We++]=oe[2*H+1]+He*be.y;Be[H][Z].push(Z),Be[Z][H]=new Array,ge=Be[H][Z].length;for(var qe=0;qe<ge;qe++)Be[Z][H][qe]=Be[H][Z][ge-1-qe]}for(q[0][0]=re[he],q[1][0]=Be[re[he]][re[he+1]][1],q[1][1]=Be[re[he]][re[he+2]][1],He=2;He<W;He++)for(q[He][0]=Be[re[he]][re[he+1]][He],q[He][He]=Be[re[he]][re[he+2]][He],me.x=(Y[3*q[He][He]]-Y[3*q[He][0]])/He,me.y=(Y[3*q[He][He]+1]-Y[3*q[He][0]+1])/He,me.z=(Y[3*q[He][He]+2]-Y[3*q[He][0]+2])/He,_e.x=(k[3*q[He][He]]-k[3*q[He][0]])/He,_e.y=(k[3*q[He][He]+1]-k[3*q[He][0]+1])/He,_e.z=(k[3*q[He][He]+2]-k[3*q[He][0]+2])/He,be.x=(oe[2*q[He][He]]-oe[2*q[He][0]])/He,be.y=(oe[2*q[He][He]+1]-oe[2*q[He][0]+1])/He,je=1;je<He;je++)q[He][je]=Y.length/3,Y[ke]=Y[3*q[He][0]]+je*me.x,k[ke++]=k[3*q[He][0]]+je*_e.x,Y[ke]=Y[3*q[He][0]+1]+je*me.y,k[ke++]=k[3*q[He][0]+1]+je*_e.y,Y[ke]=Y[3*q[He][0]+2]+je*me.z,k[ke++]=k[3*q[He][0]+2]+je*_e.z,oe[We++]=oe[2*q[He][0]]+je*be.x,oe[We++]=oe[2*q[He][0]+1]+je*be.y;for(q[W]=Be[re[he+1]][re[he+2]],Pe.push(q[0][0],q[1][0],q[1][1]),He=1;He<W;He++){for(je=0;je<He;je++)Pe.push(q[He][je],q[He+1][je],q[He+1][je+1]),Pe.push(q[He][je],q[He+1][je+1],q[He][je+1]);Pe.push(q[He][je],q[He+1][je],q[He+1][je+1])}}Q.indices=Pe,Q.applyToMesh(this,this.isVertexBufferUpdatable(c.b.PositionKind))}else N.a.Warn("VertexData contains null entries")},L.prototype.forceSharedVertices=function(){var G=T.a.ExtractFromMesh(this),Q=G.uvs,oe=G.indices,re=G.positions,Y=G.colors;if(oe===void 0||re===void 0||oe===null||re===null)N.a.Warn("VertexData contains empty entries");else{for(var k,H,Z=new Array,W=new Array,q=new Array,he=new Array,ge=new Array,me=0,_e={},be=0;be<oe.length;be+=3){H=[oe[be],oe[be+1],oe[be+2]],ge=new Array;for(var Pe=0;Pe<3;Pe++){ge[Pe]="";for(var ye=0;ye<3;ye++)Math.abs(re[3*H[Pe]+ye])<1e-8&&(re[3*H[Pe]+ye]=0),ge[Pe]+=re[3*H[Pe]+ye]+"|"}if(ge[0]!=ge[1]&&ge[0]!=ge[2]&&ge[1]!=ge[2])for(Pe=0;Pe<3;Pe++){if((k=_e[ge[Pe]])===void 0){for(_e[ge[Pe]]=me,k=me++,ye=0;ye<3;ye++)Z.push(re[3*H[Pe]+ye]);if(Y!=null)for(ye=0;ye<4;ye++)he.push(Y[4*H[Pe]+ye]);if(Q!=null)for(ye=0;ye<2;ye++)q.push(Q[2*H[Pe]+ye])}W.push(k)}}var Be=new Array;T.a.ComputeNormals(Z,W,Be),G.positions=Z,G.indices=W,G.normals=Be,Q!=null&&(G.uvs=q),Y!=null&&(G.colors=he),G.applyToMesh(this,this.isVertexBufferUpdatable(c.b.PositionKind))}},L._instancedMeshFactory=function(G,Q){throw V.a.WarnImport("InstancedMesh")},L._PhysicsImpostorParser=function(G,Q,oe){throw V.a.WarnImport("PhysicsImpostor")},L.prototype.createInstance=function(G){var Q=this.geometry;if(Q&&Q.meshes.length>1)for(var oe=0,re=Q.meshes.slice(0);oe<re.length;oe++){var Y=re[oe];Y!==this&&Y.makeGeometryUnique()}return L._instancedMeshFactory(G,this)},L.prototype.synchronizeInstances=function(){this._geometry&&this._geometry.meshes.length!==1&&this.instances.length&&this.makeGeometryUnique();for(var G=0;G<this.instances.length;G++)this.instances[G]._syncSubMeshes();return this},L.prototype.optimizeIndices=function(G){var Q=this,oe=this.getIndices(),re=this.getVerticesData(c.b.PositionKind);if(!re||!oe)return this;for(var Y=new Array,k=0;k<re.length;k+=3)Y.push(R.e.FromArray(re,k));var H=new Array;return C.a.SyncAsyncForLoop(Y.length,40,function(Z){for(var W=Y.length-1-Z,q=Y[W],he=0;he<W;++he){var ge=Y[he];if(q.equals(ge)){H[W]=he;break}}},function(){for(var Z=0;Z<oe.length;++Z)oe[Z]=H[oe[Z]]||oe[Z];var W=Q.subMeshes.slice(0);Q.setIndices(oe),Q.subMeshes=W,G&&G(Q)}),this},L.prototype.serialize=function(G){G.name=this.name,G.id=this.id,G.uniqueId=this.uniqueId,G.type=this.getClassName(),M.a&&M.a.HasTags(this)&&(G.tags=M.a.GetTags(this)),G.position=this.position.asArray(),this.rotationQuaternion?G.rotationQuaternion=this.rotationQuaternion.asArray():this.rotation&&(G.rotation=this.rotation.asArray()),G.scaling=this.scaling.asArray(),this._postMultiplyPivotMatrix?G.pivotMatrix=this.getPivotMatrix().asArray():G.localMatrix=this.getPivotMatrix().asArray(),G.isEnabled=this.isEnabled(!1),G.isVisible=this.isVisible,G.infiniteDistance=this.infiniteDistance,G.pickable=this.isPickable,G.receiveShadows=this.receiveShadows,G.billboardMode=this.billboardMode,G.visibility=this.visibility,G.checkCollisions=this.checkCollisions,G.isBlocker=this.isBlocker,G.overrideMaterialSideOrientation=this.overrideMaterialSideOrientation,this.parent&&(G.parentId=this.parent.id),G.isUnIndexed=this.isUnIndexed;var Q=this._geometry;if(Q){var oe=Q.id;G.geometryId=oe,G.subMeshes=[];for(var re=0;re<this.subMeshes.length;re++){var Y=this.subMeshes[re];G.subMeshes.push({materialIndex:Y.materialIndex,verticesStart:Y.verticesStart,verticesCount:Y.verticesCount,indexStart:Y.indexStart,indexCount:Y.indexCount})}}this.material?this.material.doNotSerialize||(G.materialId=this.material.id):this.material=null,this.morphTargetManager&&(G.morphTargetManagerId=this.morphTargetManager.uniqueId),this.skeleton&&(G.skeletonId=this.skeleton.id,G.numBoneInfluencers=this.numBoneInfluencers),this.getScene()._getComponent(X.a.NAME_PHYSICSENGINE)&&(Z=this.getPhysicsImpostor())&&(G.physicsMass=Z.getParam("mass"),G.physicsFriction=Z.getParam("friction"),G.physicsRestitution=Z.getParam("mass"),G.physicsImpostor=Z.type),this.metadata&&(G.metadata=this.metadata),G.instances=[];for(var k=0;k<this.instances.length;k++){var H=this.instances[k];if(!H.doNotSerialize){var Z,W={name:H.name,id:H.id,isEnabled:H.isEnabled(!1),isVisible:H.isVisible,isPickable:H.isPickable,checkCollisions:H.checkCollisions,position:H.position.asArray(),scaling:H.scaling.asArray()};H.parent&&(W.parentId=H.parent.id),H.rotationQuaternion?W.rotationQuaternion=H.rotationQuaternion.asArray():H.rotation&&(W.rotation=H.rotation.asArray()),this.getScene()._getComponent(X.a.NAME_PHYSICSENGINE)&&(Z=H.getPhysicsImpostor())&&(W.physicsMass=Z.getParam("mass"),W.physicsFriction=Z.getParam("friction"),W.physicsRestitution=Z.getParam("mass"),W.physicsImpostor=Z.type),H.metadata&&(W.metadata=H.metadata),G.instances.push(W),w.a.AppendSerializedAnimations(H,W),W.ranges=H.serializeAnimationRanges()}}if(this._thinInstanceDataStorage.instancesCount&&this._thinInstanceDataStorage.matrixData&&(G.thinInstances={instancesCount:this._thinInstanceDataStorage.instancesCount,matrixData:C.b.SliceToArray(this._thinInstanceDataStorage.matrixData),matrixBufferSize:this._thinInstanceDataStorage.matrixBufferSize},this._userThinInstanceBuffersStorage)){var q={data:{},sizes:{},strides:{}};for(var he in this._userThinInstanceBuffersStorage.data)q.data[he]=C.b.SliceToArray(this._userThinInstanceBuffersStorage.data[he]),q.sizes[he]=this._userThinInstanceBuffersStorage.sizes[he],q.strides[he]=this._userThinInstanceBuffersStorage.strides[he];G.thinInstances.userThinInstance=q}w.a.AppendSerializedAnimations(this,G),G.ranges=this.serializeAnimationRanges(),G.layerMask=this.layerMask,G.alphaIndex=this.alphaIndex,G.hasVertexAlpha=this.hasVertexAlpha,G.overlayAlpha=this.overlayAlpha,G.overlayColor=this.overlayColor.asArray(),G.renderOverlay=this.renderOverlay,G.applyFog=this.applyFog,this.actionManager&&(G.actions=this.actionManager.serialize(this.name))},L.prototype._syncGeometryWithMorphTargetManager=function(){if(this.geometry){this._markSubMeshesAsAttributesDirty();var G=this._internalMeshDataInfo._morphTargetManager;if(G&&G.vertexCount){if(G.vertexCount!==this.getTotalVertices())return N.a.Error("Mesh is incompatible with morph targets. Targets and mesh must all have the same vertices count."),void(this.morphTargetManager=null);for(var Q=0;Q<G.numInfluencers;Q++){var oe=G.getActiveTarget(Q),re=oe.getPositions();if(!re)return void N.a.Error("Invalid morph target. Target must have positions.");this.geometry.setVerticesData(c.b.PositionKind+Q,re,!1,3);var Y=oe.getNormals();Y&&this.geometry.setVerticesData(c.b.NormalKind+Q,Y,!1,3);var k=oe.getTangents();k&&this.geometry.setVerticesData(c.b.TangentKind+Q,k,!1,3);var H=oe.getUVs();H&&this.geometry.setVerticesData(c.b.UVKind+"_"+Q,H,!1,2)}}else for(Q=0;this.geometry.isVerticesDataPresent(c.b.PositionKind+Q);)this.geometry.removeVerticesData(c.b.PositionKind+Q),this.geometry.isVerticesDataPresent(c.b.NormalKind+Q)&&this.geometry.removeVerticesData(c.b.NormalKind+Q),this.geometry.isVerticesDataPresent(c.b.TangentKind+Q)&&this.geometry.removeVerticesData(c.b.TangentKind+Q),this.geometry.isVerticesDataPresent(c.b.UVKind+Q)&&this.geometry.removeVerticesData(c.b.UVKind+"_"+Q),Q++}},L.Parse=function(G,Q,oe){var re;if((re=G.type&&G.type==="GroundMesh"?L._GroundMeshParser(G,Q):new L(G.name,Q)).id=G.id,M.a&&M.a.AddTagsTo(re,G.tags),re.position=R.e.FromArray(G.position),G.metadata!==void 0&&(re.metadata=G.metadata),G.rotationQuaternion?re.rotationQuaternion=R.b.FromArray(G.rotationQuaternion):G.rotation&&(re.rotation=R.e.FromArray(G.rotation)),re.scaling=R.e.FromArray(G.scaling),G.localMatrix?re.setPreTransformMatrix(R.a.FromArray(G.localMatrix)):G.pivotMatrix&&re.setPivotMatrix(R.a.FromArray(G.pivotMatrix)),re.setEnabled(G.isEnabled),re.isVisible=G.isVisible,re.infiniteDistance=G.infiniteDistance,re.showBoundingBox=G.showBoundingBox,re.showSubMeshesBoundingBox=G.showSubMeshesBoundingBox,G.applyFog!==void 0&&(re.applyFog=G.applyFog),G.pickable!==void 0&&(re.isPickable=G.pickable),G.alphaIndex!==void 0&&(re.alphaIndex=G.alphaIndex),re.receiveShadows=G.receiveShadows,re.billboardMode=G.billboardMode,G.visibility!==void 0&&(re.visibility=G.visibility),re.checkCollisions=G.checkCollisions,re.overrideMaterialSideOrientation=G.overrideMaterialSideOrientation,G.isBlocker!==void 0&&(re.isBlocker=G.isBlocker),re._shouldGenerateFlatShading=G.useFlatShading,G.freezeWorldMatrix&&(re._waitingData.freezeWorldMatrix=G.freezeWorldMatrix),G.parentId&&(re._waitingParentId=G.parentId),G.actions!==void 0&&(re._waitingData.actions=G.actions),G.overlayAlpha!==void 0&&(re.overlayAlpha=G.overlayAlpha),G.overlayColor!==void 0&&(re.overlayColor=x.a.FromArray(G.overlayColor)),G.renderOverlay!==void 0&&(re.renderOverlay=G.renderOverlay),re.isUnIndexed=!!G.isUnIndexed,re.hasVertexAlpha=G.hasVertexAlpha,G.delayLoadingFile?(re.delayLoadState=D.a.DELAYLOADSTATE_NOTLOADED,re.delayLoadingFile=oe+G.delayLoadingFile,re._boundingInfo=new l.a(R.e.FromArray(G.boundingBoxMinimum),R.e.FromArray(G.boundingBoxMaximum)),G._binaryInfo&&(re._binaryInfo=G._binaryInfo),re._delayInfo=[],G.hasUVs&&re._delayInfo.push(c.b.UVKind),G.hasUVs2&&re._delayInfo.push(c.b.UV2Kind),G.hasUVs3&&re._delayInfo.push(c.b.UV3Kind),G.hasUVs4&&re._delayInfo.push(c.b.UV4Kind),G.hasUVs5&&re._delayInfo.push(c.b.UV5Kind),G.hasUVs6&&re._delayInfo.push(c.b.UV6Kind),G.hasColors&&re._delayInfo.push(c.b.ColorKind),G.hasMatricesIndices&&re._delayInfo.push(c.b.MatricesIndicesKind),G.hasMatricesWeights&&re._delayInfo.push(c.b.MatricesWeightsKind),re._delayLoadingFunction=A.a._ImportGeometry,E.a.ForceFullSceneLoadingForIncremental&&re._checkDelayState()):A.a._ImportGeometry(G,re),G.materialId?re.setMaterialByID(G.materialId):re.material=null,G.morphTargetManagerId>-1&&(re.morphTargetManager=Q.getMorphTargetManagerById(G.morphTargetManagerId)),G.skeletonId!==void 0&&G.skeletonId!==null&&(re.skeleton=Q.getLastSkeletonByID(G.skeletonId),G.numBoneInfluencers&&(re.numBoneInfluencers=G.numBoneInfluencers)),G.animations){for(var Y=0;Y<G.animations.length;Y++){var k=G.animations[Y];(q=I.a.GetClass("BABYLON.Animation"))&&re.animations.push(q.Parse(k))}m.a.ParseAnimationRanges(re,G,Q)}if(G.autoAnimate&&Q.beginAnimation(re,G.autoAnimateFrom,G.autoAnimateTo,G.autoAnimateLoop,G.autoAnimateSpeed||1),G.layerMask&&!isNaN(G.layerMask)?re.layerMask=Math.abs(parseInt(G.layerMask)):re.layerMask=268435455,G.physicsImpostor&&L._PhysicsImpostorParser(Q,re,G),G.lodMeshIds&&(re._waitingData.lods={ids:G.lodMeshIds,distances:G.lodDistances?G.lodDistances:null,coverages:G.lodCoverages?G.lodCoverages:null}),G.instances)for(var H=0;H<G.instances.length;H++){var Z=G.instances[H],W=re.createInstance(Z.name);if(Z.id&&(W.id=Z.id),M.a&&(Z.tags?M.a.AddTagsTo(W,Z.tags):M.a.AddTagsTo(W,G.tags)),W.position=R.e.FromArray(Z.position),Z.metadata!==void 0&&(W.metadata=Z.metadata),Z.parentId&&(W._waitingParentId=Z.parentId),Z.isEnabled!==void 0&&Z.isEnabled!==null&&W.setEnabled(Z.isEnabled),Z.isVisible!==void 0&&Z.isVisible!==null&&(W.isVisible=Z.isVisible),Z.isPickable!==void 0&&Z.isPickable!==null&&(W.isPickable=Z.isPickable),Z.rotationQuaternion?W.rotationQuaternion=R.b.FromArray(Z.rotationQuaternion):Z.rotation&&(W.rotation=R.e.FromArray(Z.rotation)),W.scaling=R.e.FromArray(Z.scaling),Z.checkCollisions!=null&&Z.checkCollisions!=null&&(W.checkCollisions=Z.checkCollisions),Z.pickable!=null&&Z.pickable!=null&&(W.isPickable=Z.pickable),Z.showBoundingBox!=null&&Z.showBoundingBox!=null&&(W.showBoundingBox=Z.showBoundingBox),Z.showSubMeshesBoundingBox!=null&&Z.showSubMeshesBoundingBox!=null&&(W.showSubMeshesBoundingBox=Z.showSubMeshesBoundingBox),Z.alphaIndex!=null&&Z.showSubMeshesBoundingBox!=null&&(W.alphaIndex=Z.alphaIndex),Z.physicsImpostor&&L._PhysicsImpostorParser(Q,W,Z),Z.animations){for(Y=0;Y<Z.animations.length;Y++){var q;k=Z.animations[Y],(q=I.a.GetClass("BABYLON.Animation"))&&W.animations.push(q.Parse(k))}m.a.ParseAnimationRanges(W,Z,Q),Z.autoAnimate&&Q.beginAnimation(W,Z.autoAnimateFrom,Z.autoAnimateTo,Z.autoAnimateLoop,Z.autoAnimateSpeed||1)}}if(G.thinInstances){var he=G.thinInstances;if(he.matrixData?(re.thinInstanceSetBuffer("matrix",new Float32Array(he.matrixData),16,!1),re._thinInstanceDataStorage.matrixBufferSize=he.matrixBufferSize,re._thinInstanceDataStorage.instancesCount=he.instancesCount):re._thinInstanceDataStorage.matrixBufferSize=he.matrixBufferSize,G.thinInstances.userThinInstance){var ge=G.thinInstances.userThinInstance;for(var me in ge.data)re.thinInstanceSetBuffer(me,new Float32Array(ge.data[me]),ge.strides[me],!1),re._userThinInstanceBuffersStorage.sizes[me]=ge.sizes[me]}}return re},L.CreateRibbon=function(G,Q,oe,re,Y,k,H,Z,W){throw V.a.WarnImport("MeshBuilder")},L.CreateDisc=function(G,Q,oe,re,Y,k){throw V.a.WarnImport("MeshBuilder")},L.CreateBox=function(G,Q,oe,re,Y){throw V.a.WarnImport("MeshBuilder")},L.CreateSphere=function(G,Q,oe,re,Y,k){throw V.a.WarnImport("MeshBuilder")},L.CreateHemisphere=function(G,Q,oe,re){throw V.a.WarnImport("MeshBuilder")},L.CreateCylinder=function(G,Q,oe,re,Y,k,H,Z,W){throw V.a.WarnImport("MeshBuilder")},L.CreateTorus=function(G,Q,oe,re,Y,k,H){throw V.a.WarnImport("MeshBuilder")},L.CreateTorusKnot=function(G,Q,oe,re,Y,k,H,Z,W,q){throw V.a.WarnImport("MeshBuilder")},L.CreateLines=function(G,Q,oe,re,Y){throw V.a.WarnImport("MeshBuilder")},L.CreateDashedLines=function(G,Q,oe,re,Y,k,H,Z){throw V.a.WarnImport("MeshBuilder")},L.CreatePolygon=function(G,Q,oe,re,Y,k,H){throw H===void 0&&(H=earcut),V.a.WarnImport("MeshBuilder")},L.ExtrudePolygon=function(G,Q,oe,re,Y,k,H,Z){throw Z===void 0&&(Z=earcut),V.a.WarnImport("MeshBuilder")},L.ExtrudeShape=function(G,Q,oe,re,Y,k,H,Z,W,q){throw V.a.WarnImport("MeshBuilder")},L.ExtrudeShapeCustom=function(G,Q,oe,re,Y,k,H,Z,W,q,he,ge){throw V.a.WarnImport("MeshBuilder")},L.CreateLathe=function(G,Q,oe,re,Y,k,H){throw V.a.WarnImport("MeshBuilder")},L.CreatePlane=function(G,Q,oe,re,Y){throw V.a.WarnImport("MeshBuilder")},L.CreateGround=function(G,Q,oe,re,Y,k){throw V.a.WarnImport("MeshBuilder")},L.CreateTiledGround=function(G,Q,oe,re,Y,k,H,Z,W){throw V.a.WarnImport("MeshBuilder")},L.CreateGroundFromHeightMap=function(G,Q,oe,re,Y,k,H,Z,W,q,he){throw V.a.WarnImport("MeshBuilder")},L.CreateTube=function(G,Q,oe,re,Y,k,H,Z,W,q){throw V.a.WarnImport("MeshBuilder")},L.CreatePolyhedron=function(G,Q,oe){throw V.a.WarnImport("MeshBuilder")},L.CreateIcoSphere=function(G,Q,oe){throw V.a.WarnImport("MeshBuilder")},L.CreateDecal=function(G,Q,oe,re,Y,k){throw V.a.WarnImport("MeshBuilder")},L.CreateCapsule=function(G,Q,oe){throw V.a.WarnImport("MeshBuilder")},L.prototype.setPositionsForCPUSkinning=function(){var G=this._internalMeshDataInfo;if(!G._sourcePositions){var Q=this.getVerticesData(c.b.PositionKind);if(!Q)return 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Q=this.isVerticesDataPresent(c.b.NormalKind),oe=this._internalMeshDataInfo;if(!oe._sourcePositions){var re=this.subMeshes.slice();this.setPositionsForCPUSkinning(),this.subMeshes=re}Q&&!oe._sourceNormals&&this.setNormalsForCPUSkinning();var Y=this.getVerticesData(c.b.PositionKind);if(!Y)return this;Y instanceof Float32Array||(Y=new Float32Array(Y));var k=this.getVerticesData(c.b.NormalKind);if(Q){if(!k)return this;k instanceof Float32Array||(k=new Float32Array(k))}var H=this.getVerticesData(c.b.MatricesIndicesKind),Z=this.getVerticesData(c.b.MatricesWeightsKind);if(!Z||!H)return this;for(var W,q=this.numBoneInfluencers>4,he=q?this.getVerticesData(c.b.MatricesIndicesExtraKind):null,ge=q?this.getVerticesData(c.b.MatricesWeightsExtraKind):null,me=G.getTransformMatrices(this),_e=R.e.Zero(),be=new R.a,Pe=new R.a,ye=0,Be=0;Be<Y.length;Be+=3,ye+=4){var 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m(this.r*c.r,this.g*c.g,this.b*c.b,this.a*c.a)},m.prototype.multiplyToRef=function(c,T){return T.r=this.r*c.r,T.g=this.g*c.g,T.b=this.b*c.b,T.a=this.a*c.a,T},m.prototype.toString=function(){return"{R: "+this.r+" G:"+this.g+" B:"+this.b+" A:"+this.a+"}"},m.prototype.getClassName=function(){return"Color4"},m.prototype.getHashCode=function(){var c=255*this.r|0;return c=397*(c=397*(c=397*c^(255*this.g|0))^(255*this.b|0))^(255*this.a|0)},m.prototype.clone=function(){return new m(this.r,this.g,this.b,this.a)},m.prototype.copyFrom=function(c){return this.r=c.r,this.g=c.g,this.b=c.b,this.a=c.a,this},m.prototype.copyFromFloats=function(c,T,A,S){return this.r=c,this.g=T,this.b=A,this.a=S,this},m.prototype.set=function(c,T,A,S){return this.copyFromFloats(c,T,A,S)},m.prototype.toHexString=function(c){c===void 0&&(c=!1);var T=255*this.r|0,A=255*this.g|0,S=255*this.b|0;if(c)return"#"+U.a.ToHex(T)+U.a.ToHex(A)+U.a.ToHex(S);var g=255*this.a|0;return"#"+U.a.ToHex(T)+U.a.ToHex(A)+U.a.ToHex(S)+U.a.ToHex(g)},m.prototype.toLinearSpace=function(){var c=new m;return this.toLinearSpaceToRef(c),c},m.prototype.toLinearSpaceToRef=function(c){return c.r=Math.pow(this.r,_.c),c.g=Math.pow(this.g,_.c),c.b=Math.pow(this.b,_.c),c.a=this.a,this},m.prototype.toGammaSpace=function(){var c=new m;return this.toGammaSpaceToRef(c),c},m.prototype.toGammaSpaceToRef=function(c){return c.r=Math.pow(this.r,_.b),c.g=Math.pow(this.g,_.b),c.b=Math.pow(this.b,_.b),c.a=this.a,this},m.FromHexString=function(c){if(c.substring(0,1)!=="#"||c.length!==9)return new m(0,0,0,0);var T=parseInt(c.substring(1,3),16),A=parseInt(c.substring(3,5),16),S=parseInt(c.substring(5,7),16),g=parseInt(c.substring(7,9),16);return m.FromInts(T,A,S,g)},m.Lerp=function(c,T,A){var S=new m(0,0,0,0);return m.LerpToRef(c,T,A,S),S},m.LerpToRef=function(c,T,A,S){S.r=c.r+(T.r-c.r)*A,S.g=c.g+(T.g-c.g)*A,S.b=c.b+(T.b-c.b)*A,S.a=c.a+(T.a-c.a)*A},m.FromColor3=function(c,T){return T===void 0&&(T=1),new m(c.r,c.g,c.b,T)},m.FromArray=function(c,T){return T===void 0&&(T=0),new m(c[T],c[T+1],c[T+2],c[T+3])},m.FromArrayToRef=function(c,T,A){T===void 0&&(T=0),A.r=c[T],A.g=c[T+1],A.b=c[T+2],A.a=c[T+3]},m.FromInts=function(c,T,A,S){return new m(c/255,T/255,A/255,S/255)},m.CheckColors4=function(c,T){if(c.length===3*T){for(var A=[],S=0;S<c.length;S+=3){var g=S/3*4;A[g]=c[S],A[g+1]=c[S+1],A[g+2]=c[S+2],A[g+3]=1}return A}return c},m}(),x=function(){function m(){}return m.Color3=C.a.BuildArray(3,M.Black),m.Color4=C.a.BuildArray(3,function(){return new R(0,0,0,0)}),m}();u.a.RegisteredTypes["BABYLON.Color3"]=M,u.a.RegisteredTypes["BABYLON.Color4"]=R},function(Me,y,f){f.d(y,"a",function(){return l});var U=f(1),_=f(3),C=f(6),u=f(0),M=f(52),R=f(2),x=f(11),m=f(21),c=f(104),T=f(122),A=f(64),S=f(34),g=f(150),l=function(h){function v(E,D,w,N,I,V,X,j,ne,te,de,pe){w===void 0&&(w=!1),N===void 0&&(N=!0),I===void 0&&(I=v.TRILINEAR_SAMPLINGMODE),V===void 0&&(V=null),X===void 0&&(X=null),j===void 0&&(j=null),ne===void 0&&(ne=!1);var ae=h.call(this,D)||this;ae.url=null,ae.uOffset=0,ae.vOffset=0,ae.uScale=1,ae.vScale=1,ae.uAng=0,ae.vAng=0,ae.wAng=0,ae.uRotationCenter=.5,ae.vRotationCenter=.5,ae.wRotationCenter=.5,ae.homogeneousRotationInUVTransform=!1,ae.inspectableCustomProperties=null,ae._noMipmap=!1,ae._invertY=!1,ae._rowGenerationMatrix=null,ae._cachedTextureMatrix=null,ae._projectionModeMatrix=null,ae._t0=null,ae._t1=null,ae._t2=null,ae._cachedUOffset=-1,ae._cachedVOffset=-1,ae._cachedUScale=0,ae._cachedVScale=0,ae._cachedUAng=-1,ae._cachedVAng=-1,ae._cachedWAng=-1,ae._cachedProjectionMatrixId=-1,ae._cachedURotationCenter=-1,ae._cachedVRotationCenter=-1,ae._cachedWRotationCenter=-1,ae._cachedHomogeneousRotationInUVTransform=!1,ae._cachedCoordinatesMode=-1,ae._initialSamplingMode=v.BILINEAR_SAMPLINGMODE,ae._buffer=null,ae._deleteBuffer=!1,ae._format=null,ae._delayedOnLoad=null,ae._delayedOnError=null,ae.onLoadObservable=new C.c,ae._isBlocking=!0,ae.name=E||"",ae.url=E,ae._noMipmap=w,ae._invertY=N,ae._initialSamplingMode=I,ae._buffer=j,ae._deleteBuffer=ne,ae._mimeType=de,ae._loaderOptions=pe,te&&(ae._format=te);var ee=ae.getScene(),K=ae._getEngine();if(!K)return ae;K.onBeforeTextureInitObservable.notifyObservers(ae);var $=function(){ae._texture&&(ae._texture._invertVScale&&(ae.vScale*=-1,ae.vOffset+=1),ae._texture._cachedWrapU!==null&&(ae.wrapU=ae._texture._cachedWrapU,ae._texture._cachedWrapU=null),ae._texture._cachedWrapV!==null&&(ae.wrapV=ae._texture._cachedWrapV,ae._texture._cachedWrapV=null),ae._texture._cachedWrapR!==null&&(ae.wrapR=ae._texture._cachedWrapR,ae._texture._cachedWrapR=null)),ae.onLoadObservable.hasObservers()&&ae.onLoadObservable.notifyObservers(ae),V&&V(),!ae.isBlocking&&ee&&ee.resetCachedMaterial()};return ae.url?(ae._texture=ae._getFromCache(ae.url,w,I,N),ae._texture?ae._texture.isReady?c.a.SetImmediate(function(){return $()}):ae._texture.onLoadedObservable.add($):ee&&ee.useDelayedTextureLoading?(ae.delayLoadState=R.a.DELAYLOADSTATE_NOTLOADED,ae._delayedOnLoad=$,ae._delayedOnError=X):(ae._texture=K.createTexture(ae.url,w,N,ee,I,$,X,ae._buffer,void 0,ae._format,null,de,pe),ne&&(ae._buffer=null)),ae):(ae._delayedOnLoad=$,ae._delayedOnError=X,ae)}return Object(U.d)(v,h),Object.defineProperty(v.prototype,"noMipmap",{get:function(){return this._noMipmap},enumerable:!1,configurable:!0}),Object.defineProperty(v.prototype,"mimeType",{get:function(){return this._mimeType},enumerable:!1,configurable:!0}),Object.defineProperty(v.prototype,"isBlocking",{get:function(){return this._isBlocking},set:function(E){this._isBlocking=E},enumerable:!1,configurable:!0}),Object.defineProperty(v.prototype,"samplingMode",{get:function(){return this._texture?this._texture.samplingMode:this._initialSamplingMode},enumerable:!1,configurable:!0}),Object.defineProperty(v.prototype,"invertY",{get:function(){return this._invertY},enumerable:!1,configurable:!0}),v.prototype.updateURL=function(E,D,w){D===void 0&&(D=null),this.url&&(this.releaseInternalTexture(),this.getScene().markAllMaterialsAsDirty(R.a.MATERIAL_TextureDirtyFlag)),this.name&&!S.a.StartsWith(this.name,"data:")||(this.name=E),this.url=E,this._buffer=D,this.delayLoadState=R.a.DELAYLOADSTATE_NOTLOADED,w&&(this._delayedOnLoad=w),this.delayLoad()},v.prototype.delayLoad=function(){if(this.delayLoadState===R.a.DELAYLOADSTATE_NOTLOADED){var E=this.getScene();E&&(this.delayLoadState=R.a.DELAYLOADSTATE_LOADED,this._texture=this._getFromCache(this.url,this._noMipmap,this.samplingMode,this._invertY),this._texture?this._delayedOnLoad&&(this._texture.isReady?c.a.SetImmediate(this._delayedOnLoad):this._texture.onLoadedObservable.add(this._delayedOnLoad)):(this._texture=E.getEngine().createTexture(this.url,this._noMipmap,this._invertY,E,this.samplingMode,this._delayedOnLoad,this._delayedOnError,this._buffer,null,this._format,null,this._mimeType,this._loaderOptions),this._deleteBuffer&&(this._buffer=null)),this._delayedOnLoad=null,this._delayedOnError=null)}},v.prototype._prepareRowForTextureGeneration=function(E,D,w,N){E*=this._cachedUScale,D*=this._cachedVScale,E-=this.uRotationCenter*this._cachedUScale,D-=this.vRotationCenter*this._cachedVScale,w-=this.wRotationCenter,u.e.TransformCoordinatesFromFloatsToRef(E,D,w,this._rowGenerationMatrix,N),N.x+=this.uRotationCenter*this._cachedUScale+this._cachedUOffset,N.y+=this.vRotationCenter*this._cachedVScale+this._cachedVOffset,N.z+=this.wRotationCenter},v.prototype.checkTransformsAreIdentical=function(E){return E!==null&&this.uOffset===E.uOffset&&this.vOffset===E.vOffset&&this.uScale===E.uScale&&this.vScale===E.vScale&&this.uAng===E.uAng&&this.vAng===E.vAng&&this.wAng===E.wAng},v.prototype.getTextureMatrix=function(E){var D=this;if(E===void 0&&(E=1),this.uOffset===this._cachedUOffset&&this.vOffset===this._cachedVOffset&&this.uScale*E===this._cachedUScale&&this.vScale===this._cachedVScale&&this.uAng===this._cachedUAng&&this.vAng===this._cachedVAng&&this.wAng===this._cachedWAng&&this.uRotationCenter===this._cachedURotationCenter&&this.vRotationCenter===this._cachedVRotationCenter&&this.wRotationCenter===this._cachedWRotationCenter&&this.homogeneousRotationInUVTransform===this._cachedHomogeneousRotationInUVTransform)return this._cachedTextureMatrix;this._cachedUOffset=this.uOffset,this._cachedVOffset=this.vOffset,this._cachedUScale=this.uScale*E,this._cachedVScale=this.vScale,this._cachedUAng=this.uAng,this._cachedVAng=this.vAng,this._cachedWAng=this.wAng,this._cachedURotationCenter=this.uRotationCenter,this._cachedVRotationCenter=this.vRotationCenter,this._cachedWRotationCenter=this.wRotationCenter,this._cachedHomogeneousRotationInUVTransform=this.homogeneousRotationInUVTransform,this._cachedTextureMatrix&&this._rowGenerationMatrix||(this._cachedTextureMatrix=u.a.Zero(),this._rowGenerationMatrix=new u.a,this._t0=u.e.Zero(),this._t1=u.e.Zero(),this._t2=u.e.Zero()),u.a.RotationYawPitchRollToRef(this.vAng,this.uAng,this.wAng,this._rowGenerationMatrix),this.homogeneousRotationInUVTransform?(u.a.TranslationToRef(-this._cachedURotationCenter,-this._cachedVRotationCenter,-this._cachedWRotationCenter,u.c.Matrix[0]),u.a.TranslationToRef(this._cachedURotationCenter,this._cachedVRotationCenter,this._cachedWRotationCenter,u.c.Matrix[1]),u.a.ScalingToRef(this._cachedUScale,this._cachedVScale,0,u.c.Matrix[2]),u.a.TranslationToRef(this._cachedUOffset,this._cachedVOffset,0,u.c.Matrix[3]),u.c.Matrix[0].multiplyToRef(this._rowGenerationMatrix,this._cachedTextureMatrix),this._cachedTextureMatrix.multiplyToRef(u.c.Matrix[1],this._cachedTextureMatrix),this._cachedTextureMatrix.multiplyToRef(u.c.Matrix[2],this._cachedTextureMatrix),this._cachedTextureMatrix.multiplyToRef(u.c.Matrix[3],this._cachedTextureMatrix),this._cachedTextureMatrix.setRowFromFloats(2,this._cachedTextureMatrix.m[12],this._cachedTextureMatrix.m[13],this._cachedTextureMatrix.m[14],1)):(this._prepareRowForTextureGeneration(0,0,0,this._t0),this._prepareRowForTextureGeneration(1,0,0,this._t1),this._prepareRowForTextureGeneration(0,1,0,this._t2),this._t1.subtractInPlace(this._t0),this._t2.subtractInPlace(this._t0),u.a.FromValuesToRef(this._t1.x,this._t1.y,this._t1.z,0,this._t2.x,this._t2.y,this._t2.z,0,this._t0.x,this._t0.y,this._t0.z,0,0,0,0,1,this._cachedTextureMatrix));var w=this.getScene();return w?(w.markAllMaterialsAsDirty(R.a.MATERIAL_TextureDirtyFlag,function(N){return N.hasTexture(D)}),this._cachedTextureMatrix):this._cachedTextureMatrix},v.prototype.getReflectionTextureMatrix=function(){var E=this,D=this.getScene();if(!D)return this._cachedTextureMatrix;if(this.uOffset===this._cachedUOffset&&this.vOffset===this._cachedVOffset&&this.uScale===this._cachedUScale&&this.vScale===this._cachedVScale&&this.coordinatesMode===this._cachedCoordinatesMode){if(this.coordinatesMode!==v.PROJECTION_MODE)return this._cachedTextureMatrix;if(this._cachedProjectionMatrixId===D.getProjectionMatrix().updateFlag)return this._cachedTextureMatrix}switch(this._cachedTextureMatrix||(this._cachedTextureMatrix=u.a.Zero()),this._projectionModeMatrix||(this._projectionModeMatrix=u.a.Zero()),this._cachedUOffset=this.uOffset,this._cachedVOffset=this.vOffset,this._cachedUScale=this.uScale,this._cachedVScale=this.vScale,this._cachedCoordinatesMode=this.coordinatesMode,this.coordinatesMode){case v.PLANAR_MODE:u.a.IdentityToRef(this._cachedTextureMatrix),this._cachedTextureMatrix[0]=this.uScale,this._cachedTextureMatrix[5]=this.vScale,this._cachedTextureMatrix[12]=this.uOffset,this._cachedTextureMatrix[13]=this.vOffset;break;case v.PROJECTION_MODE:u.a.FromValuesToRef(.5,0,0,0,0,-.5,0,0,0,0,0,0,.5,.5,1,1,this._projectionModeMatrix);var w=D.getProjectionMatrix();this._cachedProjectionMatrixId=w.updateFlag,w.multiplyToRef(this._projectionModeMatrix,this._cachedTextureMatrix);break;default:u.a.IdentityToRef(this._cachedTextureMatrix)}return D.markAllMaterialsAsDirty(R.a.MATERIAL_TextureDirtyFlag,function(N){return N.getActiveTextures().indexOf(E)!==-1}),this._cachedTextureMatrix},v.prototype.clone=function(){var E=this;return _.a.Clone(function(){return new v(E._texture?E._texture.url:null,E.getScene(),E._noMipmap,E._invertY,E.samplingMode,void 0,void 0,E._texture?E._texture._buffer:void 0)},this)},v.prototype.serialize=function(){var E=this.name;v.SerializeBuffers||S.a.StartsWith(this.name,"data:")&&(this.name=""),S.a.StartsWith(this.name,"data:")&&this.url===this.name&&(this.url="");var D=h.prototype.serialize.call(this);return D?((v.SerializeBuffers||v.ForceSerializeBuffers)&&(typeof this._buffer=="string"&&this._buffer.substr(0,5)==="data:"?(D.base64String=this._buffer,D.name=D.name.replace("data:","")):this.url&&S.a.StartsWith(this.url,"data:")&&this._buffer instanceof Uint8Array?D.base64String="data:image/png;base64,"+S.a.EncodeArrayBufferToBase64(this._buffer):v.ForceSerializeBuffers&&(D.base64String=g.a.GenerateBase64StringFromTexture(this))),D.invertY=this._invertY,D.samplingMode=this.samplingMode,this.name=E,D):null},v.prototype.getClassName=function(){return"Texture"},v.prototype.dispose=function(){h.prototype.dispose.call(this),this.onLoadObservable.clear(),this._delayedOnLoad=null,this._delayedOnError=null},v.Parse=function(E,D,w){if(E.customType){var N=T.a.Instantiate(E.customType).Parse(E,D,w);return E.samplingMode&&N.updateSamplingMode&&N._samplingMode&&N._samplingMode!==E.samplingMode&&N.updateSamplingMode(E.samplingMode),N}if(E.isCube&&!E.isRenderTarget)return v._CubeTextureParser(E,D,w);if(!E.name&&!E.isRenderTarget)return null;var I=function(){if(V&&V._texture&&(V._texture._cachedWrapU=null,V._texture._cachedWrapV=null,V._texture._cachedWrapR=null),E.samplingMode){var X=E.samplingMode;V&&V.samplingMode!==X&&V.updateSamplingMode(X)}if(V&&E.animations)for(var j=0;j<E.animations.length;j++){var ne=E.animations[j],te=x.a.GetClass("BABYLON.Animation");te&&V.animations.push(te.Parse(ne))}},V=_.a.Parse(function(){var X,j=!0;if(E.noMipmap&&(j=!1),E.mirrorPlane){var ne=v._CreateMirror(E.name,E.renderTargetSize,D,j);return ne._waitingRenderList=E.renderList,ne.mirrorPlane=A.a.FromArray(E.mirrorPlane),I(),ne}if(E.isRenderTarget){var te=null;if(E.isCube){if(D.reflectionProbes)for(var de=0;de<D.reflectionProbes.length;de++){var pe=D.reflectionProbes[de];if(pe.name===E.name)return pe.cubeTexture}}else(te=v._CreateRenderTargetTexture(E.name,E.renderTargetSize,D,j))._waitingRenderList=E.renderList;return I(),te}if(E.base64String)X=v.CreateFromBase64String(E.base64String,E.name,D,!j,E.invertY,void 0,I);else{var ae=void 0;ae=E.name&&E.name.indexOf("://")>0?E.name:w+E.name,(S.a.StartsWith(E.url,"data:")||v.UseSerializedUrlIfAny&&E.url)&&(ae=E.url),X=new v(ae,D,!j,E.invertY,void 0,I)}return X},E,D);return V},v.CreateFromBase64String=function(E,D,w,N,I,V,X,j,ne){return V===void 0&&(V=v.TRILINEAR_SAMPLINGMODE),X===void 0&&(X=null),j===void 0&&(j=null),ne===void 0&&(ne=R.a.TEXTUREFORMAT_RGBA),new v("data:"+D,w,N,I,V,X,j,E,!1,ne)},v.LoadFromDataString=function(E,D,w,N,I,V,X,j,ne,te){return N===void 0&&(N=!1),I===void 0&&(I=!1),V===void 0&&(V=!0),X===void 0&&(X=v.TRILINEAR_SAMPLINGMODE),j===void 0&&(j=null),ne===void 0&&(ne=null),te===void 0&&(te=R.a.TEXTUREFORMAT_RGBA),E.substr(0,5)!=="data:"&&(E="data:"+E),new v(E,w,I,V,X,j,ne,D,N,te)},v.SerializeBuffers=!0,v.ForceSerializeBuffers=!1,v._CubeTextureParser=function(E,D,w){throw m.a.WarnImport("CubeTexture")},v._CreateMirror=function(E,D,w,N){throw m.a.WarnImport("MirrorTexture")},v._CreateRenderTargetTexture=function(E,D,w,N){throw m.a.WarnImport("RenderTargetTexture")},v.NEAREST_SAMPLINGMODE=R.a.TEXTURE_NEAREST_SAMPLINGMODE,v.NEAREST_NEAREST_MIPLINEAR=R.a.TEXTURE_NEAREST_NEAREST_MIPLINEAR,v.BILINEAR_SAMPLINGMODE=R.a.TEXTURE_BILINEAR_SAMPLINGMODE,v.LINEAR_LINEAR_MIPNEAREST=R.a.TEXTURE_LINEAR_LINEAR_MIPNEAREST,v.TRILINEAR_SAMPLINGMODE=R.a.TEXTURE_TRILINEAR_SAMPLINGMODE,v.LINEAR_LINEAR_MIPLINEAR=R.a.TEXTURE_LINEAR_LINEAR_MIPLINEAR,v.NEAREST_NEAREST_MIPNEAREST=R.a.TEXTURE_NEAREST_NEAREST_MIPNEAREST,v.NEAREST_LINEAR_MIPNEAREST=R.a.TEXTURE_NEAREST_LINEAR_MIPNEAREST,v.NEAREST_LINEAR_MIPLINEAR=R.a.TEXTURE_NEAREST_LINEAR_MIPLINEAR,v.NEAREST_LINEAR=R.a.TEXTURE_NEAREST_LINEAR,v.NEAREST_NEAREST=R.a.TEXTURE_NEAREST_NEAREST,v.LINEAR_NEAREST_MIPNEAREST=R.a.TEXTURE_LINEAR_NEAREST_MIPNEAREST,v.LINEAR_NEAREST_MIPLINEAR=R.a.TEXTURE_LINEAR_NEAREST_MIPLINEAR,v.LINEAR_LINEAR=R.a.TEXTURE_LINEAR_LINEAR,v.LINEAR_NEAREST=R.a.TEXTURE_LINEAR_NEAREST,v.EXPLICIT_MODE=R.a.TEXTURE_EXPLICIT_MODE,v.SPHERICAL_MODE=R.a.TEXTURE_SPHERICAL_MODE,v.PLANAR_MODE=R.a.TEXTURE_PLANAR_MODE,v.CUBIC_MODE=R.a.TEXTURE_CUBIC_MODE,v.PROJECTION_MODE=R.a.TEXTURE_PROJECTION_MODE,v.SKYBOX_MODE=R.a.TEXTURE_SKYBOX_MODE,v.INVCUBIC_MODE=R.a.TEXTURE_INVCUBIC_MODE,v.EQUIRECTANGULAR_MODE=R.a.TEXTURE_EQUIRECTANGULAR_MODE,v.FIXED_EQUIRECTANGULAR_MODE=R.a.TEXTURE_FIXED_EQUIRECTANGULAR_MODE,v.FIXED_EQUIRECTANGULAR_MIRRORED_MODE=R.a.TEXTURE_FIXED_EQUIRECTANGULAR_MIRRORED_MODE,v.CLAMP_ADDRESSMODE=R.a.TEXTURE_CLAMP_ADDRESSMODE,v.WRAP_ADDRESSMODE=R.a.TEXTURE_WRAP_ADDRESSMODE,v.MIRROR_ADDRESSMODE=R.a.TEXTURE_MIRROR_ADDRESSMODE,v.UseSerializedUrlIfAny=!1,Object(U.c)([Object(_.c)()],v.prototype,"url",void 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0,E.doNotHandleTouchAction||w._disableTouchAction(),w._deterministicLockstep=!!E.deterministicLockstep,w._lockstepMaxSteps=E.lockstepMaxSteps||0,w._timeStep=E.timeStep||1/60}return w._prepareVRComponent(),E.autoEnableWebVR&&w.initWebVR(),w}return Object(U.d)(l,g),Object.defineProperty(l,"NpmPackage",{get:function(){return R.a.NpmPackage},enumerable:!1,configurable:!0}),Object.defineProperty(l,"Version",{get:function(){return R.a.Version},enumerable:!1,configurable:!0}),Object.defineProperty(l,"Instances",{get:function(){return u.a.Instances},enumerable:!1,configurable:!0}),Object.defineProperty(l,"LastCreatedEngine",{get:function(){return u.a.LastCreatedEngine},enumerable:!1,configurable:!0}),Object.defineProperty(l,"LastCreatedScene",{get:function(){return u.a.LastCreatedScene},enumerable:!1,configurable:!0}),l.MarkAllMaterialsAsDirty=function(h,v){for(var E=0;E<l.Instances.length;E++)for(var D=l.Instances[E],w=0;w<D.scenes.length;w++)D.scenes[w].markAllMaterialsAsDirty(h,v)},l.DefaultLoadingScreenFactory=function(h){throw M.a.WarnImport("LoadingScreen")},Object.defineProperty(l.prototype,"_supportsHardwareTextureRescaling",{get:function(){return!!l._RescalePostProcessFactory},enumerable:!1,configurable:!0}),Object.defineProperty(l.prototype,"performanceMonitor",{get:function(){return this._performanceMonitor},enumerable:!1,configurable:!0}),l.prototype.getInputElement=function(){return this._renderingCanvas},l.prototype.getAspectRatio=function(h,v){v===void 0&&(v=!1);var E=h.viewport;return this.getRenderWidth(v)*E.width/(this.getRenderHeight(v)*E.height)},l.prototype.getScreenAspectRatio=function(){return this.getRenderWidth(!0)/this.getRenderHeight(!0)},l.prototype.getRenderingCanvasClientRect=function(){return this._renderingCanvas?this._renderingCanvas.getBoundingClientRect():null},l.prototype.getInputElementClientRect=function(){return this._renderingCanvas?this.getInputElement().getBoundingClientRect():null},l.prototype.isDeterministicLockStep=function(){return this._deterministicLockstep},l.prototype.getLockstepMaxSteps=function(){return this._lockstepMaxSteps},l.prototype.getTimeStep=function(){return 1e3*this._timeStep},l.prototype.generateMipMapsForCubemap=function(h,v){if(v===void 0&&(v=!0),h.generateMipMaps){var E=this._gl;this._bindTextureDirectly(E.TEXTURE_CUBE_MAP,h,!0),E.generateMipmap(E.TEXTURE_CUBE_MAP),v&&this._bindTextureDirectly(E.TEXTURE_CUBE_MAP,null)}},l.prototype.setState=function(h,v,E,D){v===void 0&&(v=0),D===void 0&&(D=!1),(this._depthCullingState.cull!==h||E)&&(this._depthCullingState.cull=h);var w=this.cullBackFaces?this._gl.BACK:this._gl.FRONT;(this._depthCullingState.cullFace!==w||E)&&(this._depthCullingState.cullFace=w),this.setZOffset(v);var N=D?this._gl.CW:this._gl.CCW;(this._depthCullingState.frontFace!==N||E)&&(this._depthCullingState.frontFace=N)},l.prototype.setZOffset=function(h){this._depthCullingState.zOffset=h},l.prototype.getZOffset=function(){return this._depthCullingState.zOffset},l.prototype.setDepthBuffer=function(h){this._depthCullingState.depthTest=h},l.prototype.getDepthWrite=function(){return this._depthCullingState.depthMask},l.prototype.setDepthWrite=function(h){this._depthCullingState.depthMask=h},l.prototype.getStencilBuffer=function(){return this._stencilState.stencilTest},l.prototype.setStencilBuffer=function(h){this._stencilState.stencilTest=h},l.prototype.getStencilMask=function(){return this._stencilState.stencilMask},l.prototype.setStencilMask=function(h){this._stencilState.stencilMask=h},l.prototype.getStencilFunction=function(){return this._stencilState.stencilFunc},l.prototype.getStencilFunctionReference=function(){return this._stencilState.stencilFuncRef},l.prototype.getStencilFunctionMask=function(){return this._stencilState.stencilFuncMask},l.prototype.setStencilFunction=function(h){this._stencilState.stencilFunc=h},l.prototype.setStencilFunctionReference=function(h){this._stencilState.stencilFuncRef=h},l.prototype.setStencilFunctionMask=function(h){this._stencilState.stencilFuncMask=h},l.prototype.getStencilOperationFail=function(){return this._stencilState.stencilOpStencilFail},l.prototype.getStencilOperationDepthFail=function(){return this._stencilState.stencilOpDepthFail},l.prototype.getStencilOperationPass=function(){return this._stencilState.stencilOpStencilDepthPass},l.prototype.setStencilOperationFail=function(h){this._stencilState.stencilOpStencilFail=h},l.prototype.setStencilOperationDepthFail=function(h){this._stencilState.stencilOpDepthFail=h},l.prototype.setStencilOperationPass=function(h){this._stencilState.stencilOpStencilDepthPass=h},l.prototype.setDitheringState=function(h){h?this._gl.enable(this._gl.DITHER):this._gl.disable(this._gl.DITHER)},l.prototype.setRasterizerState=function(h){h?this._gl.disable(this._gl.RASTERIZER_DISCARD):this._gl.enable(this._gl.RASTERIZER_DISCARD)},l.prototype.getDepthFunction=function(){return this._depthCullingState.depthFunc},l.prototype.setDepthFunction=function(h){this._depthCullingState.depthFunc=h},l.prototype.setDepthFunctionToGreater=function(){this._depthCullingState.depthFunc=this._gl.GREATER},l.prototype.setDepthFunctionToGreaterOrEqual=function(){this._depthCullingState.depthFunc=this._gl.GEQUAL},l.prototype.setDepthFunctionToLess=function(){this._depthCullingState.depthFunc=this._gl.LESS},l.prototype.setDepthFunctionToLessOrEqual=function(){this._depthCullingState.depthFunc=this._gl.LEQUAL},l.prototype.cacheStencilState=function(){this._cachedStencilBuffer=this.getStencilBuffer(),this._cachedStencilFunction=this.getStencilFunction(),this._cachedStencilMask=this.getStencilMask(),this._cachedStencilOperationPass=this.getStencilOperationPass(),this._cachedStencilOperationFail=this.getStencilOperationFail(),this._cachedStencilOperationDepthFail=this.getStencilOperationDepthFail(),this._cachedStencilReference=this.getStencilFunctionReference()},l.prototype.restoreStencilState=function(){this.setStencilFunction(this._cachedStencilFunction),this.setStencilMask(this._cachedStencilMask),this.setStencilBuffer(this._cachedStencilBuffer),this.setStencilOperationPass(this._cachedStencilOperationPass),this.setStencilOperationFail(this._cachedStencilOperationFail),this.setStencilOperationDepthFail(this._cachedStencilOperationDepthFail),this.setStencilFunctionReference(this._cachedStencilReference)},l.prototype.setDirectViewport=function(h,v,E,D){var w=this._cachedViewport;return this._cachedViewport=null,this._viewport(h,v,E,D),w},l.prototype.scissorClear=function(h,v,E,D,w){this.enableScissor(h,v,E,D),this.clear(w,!0,!0,!0),this.disableScissor()},l.prototype.enableScissor=function(h,v,E,D){var w=this._gl;w.enable(w.SCISSOR_TEST),w.scissor(h,v,E,D)},l.prototype.disableScissor=function(){var h=this._gl;h.disable(h.SCISSOR_TEST)},l.prototype._reportDrawCall=function(){this._drawCalls.addCount(1,!1)},l.prototype.initWebVR=function(){throw M.a.WarnImport("WebVRCamera")},l.prototype._prepareVRComponent=function(){},l.prototype._connectVREvents=function(h,v){},l.prototype._submitVRFrame=function(){},l.prototype.disableVR=function(){},l.prototype.isVRPresenting=function(){return!1},l.prototype._requestVRFrame=function(){},l.prototype._loadFileAsync=function(h,v,E){var D=this;return new Promise(function(w,N){D._loadFile(h,function(I){w(I)},void 0,v,E,function(I,V){N(V)})})},l.prototype.getVertexShaderSource=function(h){var v=this._gl.getAttachedShaders(h);return v?this._gl.getShaderSource(v[0]):null},l.prototype.getFragmentShaderSource=function(h){var v=this._gl.getAttachedShaders(h);return v?this._gl.getShaderSource(v[1]):null},l.prototype.setDepthStencilTexture=function(h,v,E){h!==void 0&&(v&&(this._boundUniforms[h]=v),E&&E.depthStencilTexture?this._setTexture(h,E,!1,!0):this._setTexture(h,null))},l.prototype.setTextureFromPostProcess=function(h,v){this._bindTexture(h,v?v._textures.data[v._currentRenderTextureInd]:null)},l.prototype.setTextureFromPostProcessOutput=function(h,v){this._bindTexture(h,v?v._outputTexture:null)},l.prototype._rebuildBuffers=function(){for(var h=0,v=this.scenes;h<v.length;h++){var E=v[h];E.resetCachedMaterial(),E._rebuildGeometries(),E._rebuildTextures()}g.prototype._rebuildBuffers.call(this)},l.prototype._renderFrame=function(){for(var h=0;h<this._activeRenderLoops.length;h++)(0,this._activeRenderLoops[h])()},l.prototype._renderLoop=function(){if(!this._contextWasLost){var h=!0;!this.renderEvenInBackground&&this._windowIsBackground&&(h=!1),h&&(this.beginFrame(),this._renderViews()||this._renderFrame(),this.endFrame())}this._activeRenderLoops.length>0?this.customAnimationFrameRequester?(this.customAnimationFrameRequester.requestID=this._queueNewFrame(this.customAnimationFrameRequester.renderFunction||this._boundRenderFunction,this.customAnimationFrameRequester),this._frameHandler=this.customAnimationFrameRequester.requestID):this.isVRPresenting()?this._requestVRFrame():this._frameHandler=this._queueNewFrame(this._boundRenderFunction,this.getHostWindow()):this._renderingQueueLaunched=!1},l.prototype._renderViews=function(){return!1},l.prototype.switchFullscreen=function(h){this.isFullscreen?this.exitFullscreen():this.enterFullscreen(h)},l.prototype.enterFullscreen=function(h){this.isFullscreen||(this._pointerLockRequested=h,this._renderingCanvas&&l._RequestFullscreen(this._renderingCanvas))},l.prototype.exitFullscreen=function(){this.isFullscreen&&l._ExitFullscreen()},l.prototype.enterPointerlock=function(){this._renderingCanvas&&l._RequestPointerlock(this._renderingCanvas)},l.prototype.exitPointerlock=function(){l._ExitPointerlock()},l.prototype.beginFrame=function(){this._measureFps(),this.onBeginFrameObservable.notifyObservers(this),g.prototype.beginFrame.call(this)},l.prototype.endFrame=function(){g.prototype.endFrame.call(this),this._submitVRFrame(),this.onEndFrameObservable.notifyObservers(this)},l.prototype.resize=function(){this.isVRPresenting()||g.prototype.resize.call(this)},l.prototype.setSize=function(h,v){if(!this._renderingCanvas||!g.prototype.setSize.call(this,h,v))return!1;if(this.scenes){for(var E=0;E<this.scenes.length;E++)for(var D=this.scenes[E],w=0;w<D.cameras.length;w++)D.cameras[w]._currentRenderId=0;this.onResizeObservable.hasObservers()&&this.onResizeObservable.notifyObservers(this)}return!0},l.prototype._deletePipelineContext=function(h){var v=h;v&&v.program&&v.transformFeedback&&(this.deleteTransformFeedback(v.transformFeedback),v.transformFeedback=null),g.prototype._deletePipelineContext.call(this,h)},l.prototype.createShaderProgram=function(h,v,E,D,w,N){N===void 0&&(N=null),w=w||this._gl,this.onBeforeShaderCompilationObservable.notifyObservers(this);var I=g.prototype.createShaderProgram.call(this,h,v,E,D,w,N);return this.onAfterShaderCompilationObservable.notifyObservers(this),I},l.prototype._createShaderProgram=function(h,v,E,D,w){w===void 0&&(w=null);var N=D.createProgram();if(h.program=N,!N)throw new Error("Unable to create program");if(D.attachShader(N,v),D.attachShader(N,E),this.webGLVersion>1&&w){var I=this.createTransformFeedback();this.bindTransformFeedback(I),this.setTranformFeedbackVaryings(N,w),h.transformFeedback=I}return D.linkProgram(N),this.webGLVersion>1&&w&&this.bindTransformFeedback(null),h.context=D,h.vertexShader=v,h.fragmentShader=E,h.isParallelCompiled||this._finalizePipelineContext(h),N},l.prototype._releaseTexture=function(h){g.prototype._releaseTexture.call(this,h),this.scenes.forEach(function(v){v.postProcesses.forEach(function(E){E._outputTexture==h&&(E._outputTexture=null)}),v.cameras.forEach(function(E){E._postProcesses.forEach(function(D){D&&D._outputTexture==h&&(D._outputTexture=null)})})})},l.prototype._rescaleTexture=function(h,v,E,D,w){var N=this;this._gl.texParameteri(this._gl.TEXTURE_2D,this._gl.TEXTURE_MAG_FILTER,this._gl.LINEAR),this._gl.texParameteri(this._gl.TEXTURE_2D,this._gl.TEXTURE_MIN_FILTER,this._gl.LINEAR),this._gl.texParameteri(this._gl.TEXTURE_2D,this._gl.TEXTURE_WRAP_S,this._gl.CLAMP_TO_EDGE),this._gl.texParameteri(this._gl.TEXTURE_2D,this._gl.TEXTURE_WRAP_T,this._gl.CLAMP_TO_EDGE);var I=this.createRenderTargetTexture({width:v.width,height:v.height},{generateMipMaps:!1,type:x.a.TEXTURETYPE_UNSIGNED_INT,samplingMode:x.a.TEXTURE_BILINEAR_SAMPLINGMODE,generateDepthBuffer:!1,generateStencilBuffer:!1});!this._rescalePostProcess&&l._RescalePostProcessFactory&&(this._rescalePostProcess=l._RescalePostProcessFactory(this)),this._rescalePostProcess.getEffect().executeWhenCompiled(function(){N._rescalePostProcess.onApply=function(X){X._bindTexture("textureSampler",h)};var V=E;V||(V=N.scenes[N.scenes.length-1]),V.postProcessManager.directRender([N._rescalePostProcess],I,!0),N._bindTextureDirectly(N._gl.TEXTURE_2D,v,!0),N._gl.copyTexImage2D(N._gl.TEXTURE_2D,0,D,0,0,v.width,v.height,0),N.unBindFramebuffer(I),N._releaseTexture(I),w&&w()})},l.prototype.getFps=function(){return this._fps},l.prototype.getDeltaTime=function(){return this._deltaTime},l.prototype._measureFps=function(){this._performanceMonitor.sampleFrame(),this._fps=this._performanceMonitor.averageFPS,this._deltaTime=this._performanceMonitor.instantaneousFrameTime||0},l.prototype._uploadImageToTexture=function(h,v,E,D){E===void 0&&(E=0),D===void 0&&(D=0);var w=this._gl,N=this._getWebGLTextureType(h.type),I=this._getInternalFormat(h.format),V=this._getRGBABufferInternalSizedFormat(h.type,I),X=h.isCube?w.TEXTURE_CUBE_MAP:w.TEXTURE_2D;this._bindTextureDirectly(X,h,!0),this._unpackFlipY(h.invertY);var j=w.TEXTURE_2D;h.isCube&&(j=w.TEXTURE_CUBE_MAP_POSITIVE_X+E),w.texImage2D(j,D,V,I,N,v),this._bindTextureDirectly(X,null,!0)},l.prototype.updateRenderTargetTextureSampleCount=function(h,v){if(this.webGLVersion<2||!h)return 1;if(h.samples===v)return v;var E=this._gl;if(v=Math.min(v,this.getCaps().maxMSAASamples),h._depthStencilBuffer&&(E.deleteRenderbuffer(h._depthStencilBuffer),h._depthStencilBuffer=null),h._MSAAFramebuffer&&(E.deleteFramebuffer(h._MSAAFramebuffer),h._MSAAFramebuffer=null),h._MSAARenderBuffer&&(E.deleteRenderbuffer(h._MSAARenderBuffer),h._MSAARenderBuffer=null),v>1&&E.renderbufferStorageMultisample){var D=E.createFramebuffer();if(!D)throw new Error("Unable to create multi sampled framebuffer");h._MSAAFramebuffer=D,this._bindUnboundFramebuffer(h._MSAAFramebuffer);var w=E.createRenderbuffer();if(!w)throw new Error("Unable to create multi sampled framebuffer");E.bindRenderbuffer(E.RENDERBUFFER,w),E.renderbufferStorageMultisample(E.RENDERBUFFER,v,this._getRGBAMultiSampleBufferFormat(h.type),h.width,h.height),E.framebufferRenderbuffer(E.FRAMEBUFFER,E.COLOR_ATTACHMENT0,E.RENDERBUFFER,w),h._MSAARenderBuffer=w}else this._bindUnboundFramebuffer(h._framebuffer);return h.samples=v,h._depthStencilBuffer=this._setupFramebufferDepthAttachments(h._generateStencilBuffer,h._generateDepthBuffer,h.width,h.height,v),this._bindUnboundFramebuffer(null),v},l.prototype.updateTextureComparisonFunction=function(h,v){if(this.webGLVersion!==1){var E=this._gl;h.isCube?(this._bindTextureDirectly(this._gl.TEXTURE_CUBE_MAP,h,!0),v===0?(E.texParameteri(E.TEXTURE_CUBE_MAP,E.TEXTURE_COMPARE_FUNC,x.a.LEQUAL),E.texParameteri(E.TEXTURE_CUBE_MAP,E.TEXTURE_COMPARE_MODE,E.NONE)):(E.texParameteri(E.TEXTURE_CUBE_MAP,E.TEXTURE_COMPARE_FUNC,v),E.texParameteri(E.TEXTURE_CUBE_MAP,E.TEXTURE_COMPARE_MODE,E.COMPARE_REF_TO_TEXTURE)),this._bindTextureDirectly(this._gl.TEXTURE_CUBE_MAP,null)):(this._bindTextureDirectly(this._gl.TEXTURE_2D,h,!0),v===0?(E.texParameteri(E.TEXTURE_2D,E.TEXTURE_COMPARE_FUNC,x.a.LEQUAL),E.texParameteri(E.TEXTURE_2D,E.TEXTURE_COMPARE_MODE,E.NONE)):(E.texParameteri(E.TEXTURE_2D,E.TEXTURE_COMPARE_FUNC,v),E.texParameteri(E.TEXTURE_2D,E.TEXTURE_COMPARE_MODE,E.COMPARE_REF_TO_TEXTURE)),this._bindTextureDirectly(this._gl.TEXTURE_2D,null)),h._comparisonFunction=v}else A.a.Error("WebGL 1 does not support texture comparison.")},l.prototype.createInstancesBuffer=function(h){var v=this._gl.createBuffer();if(!v)throw new Error("Unable to create instance buffer");var E=new T.a(v);return E.capacity=h,this.bindArrayBuffer(E),this._gl.bufferData(this._gl.ARRAY_BUFFER,h,this._gl.DYNAMIC_DRAW),E},l.prototype.deleteInstancesBuffer=function(h){this._gl.deleteBuffer(h)},l.prototype._clientWaitAsync=function(h,v,E){v===void 0&&(v=0),E===void 0&&(E=10);var D=this._gl;return new Promise(function(w,N){var I=function(){var V=D.clientWaitSync(h,v,0);V!=D.WAIT_FAILED?V!=D.TIMEOUT_EXPIRED?w():setTimeout(I,E):N()};I()})},l.prototype._readPixelsAsync=function(h,v,E,D,w,N,I){if(this._webGLVersion<2)throw new Error("_readPixelsAsync only work on WebGL2+");var V=this._gl,X=V.createBuffer();V.bindBuffer(V.PIXEL_PACK_BUFFER,X),V.bufferData(V.PIXEL_PACK_BUFFER,I.byteLength,V.STREAM_READ),V.readPixels(h,v,E,D,w,N,0),V.bindBuffer(V.PIXEL_PACK_BUFFER,null);var j=V.fenceSync(V.SYNC_GPU_COMMANDS_COMPLETE,0);return j?(V.flush(),this._clientWaitAsync(j,0,10).then(function(){return V.deleteSync(j),V.bindBuffer(V.PIXEL_PACK_BUFFER,X),V.getBufferSubData(V.PIXEL_PACK_BUFFER,0,I),V.bindBuffer(V.PIXEL_PACK_BUFFER,null),V.deleteBuffer(X),I})):null},l.prototype.dispose=function(){for(this.hideLoadingUI(),this.onNewSceneAddedObservable.clear();this.postProcesses.length;)this.postProcesses[0].dispose();for(this._rescalePostProcess&&this._rescalePostProcess.dispose();this.scenes.length;)this.scenes[0].dispose();l.Instances.length===1&&l.audioEngine&&l.audioEngine.dispose(),this.disableVR(),C.a.IsWindowObjectExist()&&(window.removeEventListener("blur",this._onBlur),window.removeEventListener("focus",this._onFocus),this._renderingCanvas&&(this._renderingCanvas.removeEventListener("focus",this._onCanvasFocus),this._renderingCanvas.removeEventListener("blur",this._onCanvasBlur),this._renderingCanvas.removeEventListener("pointerout",this._onCanvasPointerOut)),C.a.IsDocumentAvailable()&&(document.removeEventListener("fullscreenchange",this._onFullscreenChange),document.removeEventListener("mozfullscreenchange",this._onFullscreenChange),document.removeEventListener("webkitfullscreenchange",this._onFullscreenChange),document.removeEventListener("msfullscreenchange",this._onFullscreenChange),document.removeEventListener("pointerlockchange",this._onPointerLockChange),document.removeEventListener("mspointerlockchange",this._onPointerLockChange),document.removeEventListener("mozpointerlockchange",this._onPointerLockChange),document.removeEventListener("webkitpointerlockchange",this._onPointerLockChange))),g.prototype.dispose.call(this);var h=l.Instances.indexOf(this);h>=0&&l.Instances.splice(h,1),this.onResizeObservable.clear(),this.onCanvasBlurObservable.clear(),this.onCanvasFocusObservable.clear(),this.onCanvasPointerOutObservable.clear(),this.onBeginFrameObservable.clear(),this.onEndFrameObservable.clear()},l.prototype._disableTouchAction=function(){this._renderingCanvas&&this._renderingCanvas.setAttribute&&(this._renderingCanvas.setAttribute("touch-action","none"),this._renderingCanvas.style.touchAction="none",this._renderingCanvas.style.msTouchAction="none")},l.prototype.displayLoadingUI=function(){if(C.a.IsWindowObjectExist()){var h=this.loadingScreen;h&&h.displayLoadingUI()}},l.prototype.hideLoadingUI=function(){if(C.a.IsWindowObjectExist()){var h=this._loadingScreen;h&&h.hideLoadingUI()}},Object.defineProperty(l.prototype,"loadingScreen",{get:function(){return!this._loadingScreen&&this._renderingCanvas&&(this._loadingScreen=l.DefaultLoadingScreenFactory(this._renderingCanvas)),this._loadingScreen},set:function(h){this._loadingScreen=h},enumerable:!1,configurable:!0}),Object.defineProperty(l.prototype,"loadingUIText",{set:function(h){this.loadingScreen.loadingUIText=h},enumerable:!1,configurable:!0}),Object.defineProperty(l.prototype,"loadingUIBackgroundColor",{set:function(h){this.loadingScreen.loadingUIBackgroundColor=h},enumerable:!1,configurable:!0}),l._RequestPointerlock=function(h){h.requestPointerLock=h.requestPointerLock||h.msRequestPointerLock||h.mozRequestPointerLock||h.webkitRequestPointerLock,h.requestPointerLock&&h.requestPointerLock()},l._ExitPointerlock=function(){var h=document;document.exitPointerLock=document.exitPointerLock||h.msExitPointerLock||h.mozExitPointerLock||h.webkitExitPointerLock,document.exitPointerLock&&document.exitPointerLock()},l._RequestFullscreen=function(h){var v=h.requestFullscreen||h.msRequestFullscreen||h.webkitRequestFullscreen||h.mozRequestFullScreen;v&&v.call(h)},l._ExitFullscreen=function(){var h=document;document.exitFullscreen?document.exitFullscreen():h.mozCancelFullScreen?h.mozCancelFullScreen():h.webkitCancelFullScreen?h.webkitCancelFullScreen():h.msCancelFullScreen&&h.msCancelFullScreen()},l.ALPHA_DISABLE=x.a.ALPHA_DISABLE,l.ALPHA_ADD=x.a.ALPHA_ADD,l.ALPHA_COMBINE=x.a.ALPHA_COMBINE,l.ALPHA_SUBTRACT=x.a.ALPHA_SUBTRACT,l.ALPHA_MULTIPLY=x.a.ALPHA_MULTIPLY,l.ALPHA_MAXIMIZED=x.a.ALPHA_MAXIMIZED,l.ALPHA_ONEONE=x.a.ALPHA_ONEONE,l.ALPHA_PREMULTIPLIED=x.a.ALPHA_PREMULTIPLIED,l.ALPHA_PREMULTIPLIED_PORTERDUFF=x.a.ALPHA_PREMULTIPLIED_PORTERDUFF,l.ALPHA_INTERPOLATE=x.a.ALPHA_INTERPOLATE,l.ALPHA_SCREENMODE=x.a.ALPHA_SCREENMODE,l.DELAYLOADSTATE_NONE=x.a.DELAYLOADSTATE_NONE,l.DELAYLOADSTATE_LOADED=x.a.DELAYLOADSTATE_LOADED,l.DELAYLOADSTATE_LOADING=x.a.DELAYLOADSTATE_LOADING,l.DELAYLOADSTATE_NOTLOADED=x.a.DELAYLOADSTATE_NOTLOADED,l.NEVER=x.a.NEVER,l.ALWAYS=x.a.ALWAYS,l.LESS=x.a.LESS,l.EQUAL=x.a.EQUAL,l.LEQUAL=x.a.LEQUAL,l.GREATER=x.a.GREATER,l.GEQUAL=x.a.GEQUAL,l.NOTEQUAL=x.a.NOTEQUAL,l.KEEP=x.a.KEEP,l.REPLACE=x.a.REPLACE,l.INCR=x.a.INCR,l.DECR=x.a.DECR,l.INVERT=x.a.INVERT,l.INCR_WRAP=x.a.INCR_WRAP,l.DECR_WRAP=x.a.DECR_WRAP,l.TEXTURE_CLAMP_ADDRESSMODE=x.a.TEXTURE_CLAMP_ADDRESSMODE,l.TEXTURE_WRAP_ADDRESSMODE=x.a.TEXTURE_WRAP_ADDRESSMODE,l.TEXTURE_MIRROR_ADDRESSMODE=x.a.TEXTURE_MIRROR_ADDRESSMODE,l.TEXTUREFORMAT_ALPHA=x.a.TEXTUREFORMAT_ALPHA,l.TEXTUREFORMAT_LUMINANCE=x.a.TEXTUREFORMAT_LUMINANCE,l.TEXTUREFORMAT_LUMINANCE_ALPHA=x.a.TEXTUREFORMAT_LUMINANCE_ALPHA,l.TEXTUREFORMAT_RGB=x.a.TEXTUREFORMAT_RGB,l.TEXTUREFORMAT_RGBA=x.a.TEXTUREFORMAT_RGBA,l.TEXTUREFORMAT_RED=x.a.TEXTUREFORMAT_RED,l.TEXTUREFORMAT_R=x.a.TEXTUREFORMAT_R,l.TEXTUREFORMAT_RG=x.a.TEXTUREFORMAT_RG,l.TEXTUREFORMAT_RED_INTEGER=x.a.TEXTUREFORMAT_RED_INTEGER,l.TEXTUREFORMAT_R_INTEGER=x.a.TEXTUREFORMAT_R_INTEGER,l.TEXTUREFORMAT_RG_INTEGER=x.a.TEXTUREFORMAT_RG_INTEGER,l.TEXTUREFORMAT_RGB_INTEGER=x.a.TEXTUREFORMAT_RGB_INTEGER,l.TEXTUREFORMAT_RGBA_INTEGER=x.a.TEXTUREFORMAT_RGBA_INTEGER,l.TEXTURETYPE_UNSIGNED_BYTE=x.a.TEXTURETYPE_UNSIGNED_BYTE,l.TEXTURETYPE_UNSIGNED_INT=x.a.TEXTURETYPE_UNSIGNED_INT,l.TEXTURETYPE_FLOAT=x.a.TEXTURETYPE_FLOAT,l.TEXTURETYPE_HALF_FLOAT=x.a.TEXTURETYPE_HALF_FLOAT,l.TEXTURETYPE_BYTE=x.a.TEXTURETYPE_BYTE,l.TEXTURETYPE_SHORT=x.a.TEXTURETYPE_SHORT,l.TEXTURETYPE_UNSIGNED_SHORT=x.a.TEXTURETYPE_UNSIGNED_SHORT,l.TEXTURETYPE_INT=x.a.TEXTURETYPE_INT,l.TEXTURETYPE_UNSIGNED_INTEGER=x.a.TEXTURETYPE_UNSIGNED_INTEGER,l.TEXTURETYPE_UNSIGNED_SHORT_4_4_4_4=x.a.TEXTURETYPE_UNSIGNED_SHORT_4_4_4_4,l.TEXTURETYPE_UNSIGNED_SHORT_5_5_5_1=x.a.TEXTURETYPE_UNSIGNED_SHORT_5_5_5_1,l.TEXTURETYPE_UNSIGNED_SHORT_5_6_5=x.a.TEXTURETYPE_UNSIGNED_SHORT_5_6_5,l.TEXTURETYPE_UNSIGNED_INT_2_10_10_10_REV=x.a.TEXTURETYPE_UNSIGNED_INT_2_10_10_10_REV,l.TEXTURETYPE_UNSIGNED_INT_24_8=x.a.TEXTURETYPE_UNSIGNED_INT_24_8,l.TEXTURETYPE_UNSIGNED_INT_10F_11F_11F_REV=x.a.TEXTURETYPE_UNSIGNED_INT_10F_11F_11F_REV,l.TEXTURETYPE_UNSIGNED_INT_5_9_9_9_REV=x.a.TEXTURETYPE_UNSIGNED_INT_5_9_9_9_REV,l.TEXTURETYPE_FLOAT_32_UNSIGNED_INT_24_8_REV=x.a.TEXTURETYPE_FLOAT_32_UNSIGNED_INT_24_8_REV,l.TEXTURE_NEAREST_SAMPLINGMODE=x.a.TEXTURE_NEAREST_SAMPLINGMODE,l.TEXTURE_BILINEAR_SAMPLINGMODE=x.a.TEXTURE_BILINEAR_SAMPLINGMODE,l.TEXTURE_TRILINEAR_SAMPLINGMODE=x.a.TEXTURE_TRILINEAR_SAMPLINGMODE,l.TEXTURE_NEAREST_NEAREST_MIPLINEAR=x.a.TEXTURE_NEAREST_NEAREST_MIPLINEAR,l.TEXTURE_LINEAR_LINEAR_MIPNEAREST=x.a.TEXTURE_LINEAR_LINEAR_MIPNEAREST,l.TEXTURE_LINEAR_LINEAR_MIPLINEAR=x.a.TEXTURE_LINEAR_LINEAR_MIPLINEAR,l.TEXTURE_NEAREST_NEAREST_MIPNEAREST=x.a.TEXTURE_NEAREST_NEAREST_MIPNEAREST,l.TEXTURE_NEAREST_LINEAR_MIPNEAREST=x.a.TEXTURE_NEAREST_LINEAR_MIPNEAREST,l.TEXTURE_NEAREST_LINEAR_MIPLINEAR=x.a.TEXTURE_NEAREST_LINEAR_MIPLINEAR,l.TEXTURE_NEAREST_LINEAR=x.a.TEXTURE_NEAREST_LINEAR,l.TEXTURE_NEAREST_NEAREST=x.a.TEXTURE_NEAREST_NEAREST,l.TEXTURE_LINEAR_NEAREST_MIPNEAREST=x.a.TEXTURE_LINEAR_NEAREST_MIPNEAREST,l.TEXTURE_LINEAR_NEAREST_MIPLINEAR=x.a.TEXTURE_LINEAR_NEAREST_MIPLINEAR,l.TEXTURE_LINEAR_LINEAR=x.a.TEXTURE_LINEAR_LINEAR,l.TEXTURE_LINEAR_NEAREST=x.a.TEXTURE_LINEAR_NEAREST,l.TEXTURE_EXPLICIT_MODE=x.a.TEXTURE_EXPLICIT_MODE,l.TEXTURE_SPHERICAL_MODE=x.a.TEXTURE_SPHERICAL_MODE,l.TEXTURE_PLANAR_MODE=x.a.TEXTURE_PLANAR_MODE,l.TEXTURE_CUBIC_MODE=x.a.TEXTURE_CUBIC_MODE,l.TEXTURE_PROJECTION_MODE=x.a.TEXTURE_PROJECTION_MODE,l.TEXTURE_SKYBOX_MODE=x.a.TEXTURE_SKYBOX_MODE,l.TEXTURE_INVCUBIC_MODE=x.a.TEXTURE_INVCUBIC_MODE,l.TEXTURE_EQUIRECTANGULAR_MODE=x.a.TEXTURE_EQUIRECTANGULAR_MODE,l.TEXTURE_FIXED_EQUIRECTANGULAR_MODE=x.a.TEXTURE_FIXED_EQUIRECTANGULAR_MODE,l.TEXTURE_FIXED_EQUIRECTANGULAR_MIRRORED_MODE=x.a.TEXTURE_FIXED_EQUIRECTANGULAR_MIRRORED_MODE,l.SCALEMODE_FLOOR=x.a.SCALEMODE_FLOOR,l.SCALEMODE_NEAREST=x.a.SCALEMODE_NEAREST,l.SCALEMODE_CEILING=x.a.SCALEMODE_CEILING,l._RescalePostProcessFactory=null,l}(R.a))},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.WithinEpsilon=function(C,u,M){M===void 0&&(M=1401298e-51);var R=C-u;return-M<=R&&R<=M},_.ToHex=function(C){var u=C.toString(16);return C<=15?("0"+u).toUpperCase():u.toUpperCase()},_.Sign=function(C){return(C=+C)==0||isNaN(C)?C:C>0?1:-1},_.Clamp=function(C,u,M){return u===void 0&&(u=0),M===void 0&&(M=1),Math.min(M,Math.max(u,C))},_.Log2=function(C){return Math.log(C)*Math.LOG2E},_.Repeat=function(C,u){return C-Math.floor(C/u)*u},_.Normalize=function(C,u,M){return(C-u)/(M-u)},_.Denormalize=function(C,u,M){return C*(M-u)+u},_.DeltaAngle=function(C,u){var M=_.Repeat(u-C,360);return M>180&&(M-=360),M},_.PingPong=function(C,u){var M=_.Repeat(C,2*u);return u-Math.abs(M-u)},_.SmoothStep=function(C,u,M){var R=_.Clamp(M);return u*(R=-2*R*R*R+3*R*R)+C*(1-R)},_.MoveTowards=function(C,u,M){return Math.abs(u-C)<=M?u:C+_.Sign(u-C)*M},_.MoveTowardsAngle=function(C,u,M){var 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l=S.activeCamera.globalPosition;l||(l=S.activeCamera.devicePosition),A.setVector3(g,S._mirroredCameraPosition?S._mirroredCameraPosition:l)}},T.PrepareDefinesForMergedUV=function(A,S,g){S._needUVs=!0,S[g]=!0,A.getTextureMatrix().isIdentityAs3x2()?(S[g+"DIRECTUV"]=A.coordinatesIndex+1,A.coordinatesIndex===0?S.MAINUV1=!0:S.MAINUV2=!0):S[g+"DIRECTUV"]=0},T.BindTextureMatrix=function(A,S,g){var l=A.getTextureMatrix();S.updateMatrix(g+"Matrix",l)},T.GetFogState=function(A,S){return S.fogEnabled&&A.applyFog&&S.fogMode!==_.a.FOGMODE_NONE},T.PrepareDefinesForMisc=function(A,S,g,l,h,v,E){E._areMiscDirty&&(E.LOGARITHMICDEPTH=g,E.POINTSIZE=l,E.FOG=h&&this.GetFogState(A,S),E.NONUNIFORMSCALING=A.nonUniformScaling,E.ALPHATEST=v)},T.PrepareDefinesForFrameBoundValues=function(A,S,g,l,h,v){h===void 0&&(h=null),v===void 0&&(v=!1);var E,D,w,N,I,V,X=!1;E=h??(A.clipPlane!==void 0&&A.clipPlane!==null),D=h??(A.clipPlane2!==void 0&&A.clipPlane2!==null),w=h??(A.clipPlane3!==void 0&&A.clipPlane3!==null),N=h??(A.clipPlane4!==void 0&&A.clipPlane4!==null),I=h??(A.clipPlane5!==void 0&&A.clipPlane5!==null),V=h??(A.clipPlane6!==void 0&&A.clipPlane6!==null),g.CLIPPLANE!==E&&(g.CLIPPLANE=E,X=!0),g.CLIPPLANE2!==D&&(g.CLIPPLANE2=D,X=!0),g.CLIPPLANE3!==w&&(g.CLIPPLANE3=w,X=!0),g.CLIPPLANE4!==N&&(g.CLIPPLANE4=N,X=!0),g.CLIPPLANE5!==I&&(g.CLIPPLANE5=I,X=!0),g.CLIPPLANE6!==V&&(g.CLIPPLANE6=V,X=!0),g.DEPTHPREPASS!==!S.getColorWrite()&&(g.DEPTHPREPASS=!g.DEPTHPREPASS,X=!0),g.INSTANCES!==l&&(g.INSTANCES=l,X=!0),g.THIN_INSTANCES!==v&&(g.THIN_INSTANCES=v,X=!0),X&&g.markAsUnprocessed()},T.PrepareDefinesForBones=function(A,S){if(A.useBones&&A.computeBonesUsingShaders&&A.skeleton){S.NUM_BONE_INFLUENCERS=A.numBoneInfluencers;var g=S.BONETEXTURE!==void 0;if(A.skeleton.isUsingTextureForMatrices&&g)S.BONETEXTURE=!0;else{S.BonesPerMesh=A.skeleton.bones.length+1,S.BONETEXTURE=!g&&void 0;var l=A.getScene().prePassRenderer;if(l&&l.enabled){var h=l.excludedSkinnedMesh.indexOf(A)===-1;S.BONES_VELOCITY_ENABLED=h}}}else S.NUM_BONE_INFLUENCERS=0,S.BonesPerMesh=0},T.PrepareDefinesForMorphTargets=function(A,S){var g=A.morphTargetManager;g?(S.MORPHTARGETS_UV=g.supportsUVs&&S.UV1,S.MORPHTARGETS_TANGENT=g.supportsTangents&&S.TANGENT,S.MORPHTARGETS_NORMAL=g.supportsNormals&&S.NORMAL,S.MORPHTARGETS=g.numInfluencers>0,S.NUM_MORPH_INFLUENCERS=g.numInfluencers):(S.MORPHTARGETS_UV=!1,S.MORPHTARGETS_TANGENT=!1,S.MORPHTARGETS_NORMAL=!1,S.MORPHTARGETS=!1,S.NUM_MORPH_INFLUENCERS=0)},T.PrepareDefinesForAttributes=function(A,S,g,l,h,v){if(h===void 0&&(h=!1),v===void 0&&(v=!0),!S._areAttributesDirty&&S._needNormals===S._normals&&S._needUVs===S._uvs)return!1;if(S._normals=S._needNormals,S._uvs=S._needUVs,S.NORMAL=S._needNormals&&A.isVerticesDataPresent(u.b.NormalKind),S._needNormals&&A.isVerticesDataPresent(u.b.TangentKind)&&(S.TANGENT=!0),S._needUVs?(S.UV1=A.isVerticesDataPresent(u.b.UVKind),S.UV2=A.isVerticesDataPresent(u.b.UV2Kind)):(S.UV1=!1,S.UV2=!1),g){var E=A.useVertexColors&&A.isVerticesDataPresent(u.b.ColorKind);S.VERTEXCOLOR=E,S.VERTEXALPHA=A.hasVertexAlpha&&E&&v}return l&&this.PrepareDefinesForBones(A,S),h&&this.PrepareDefinesForMorphTargets(A,S),!0},T.PrepareDefinesForMultiview=function(A,S){if(A.activeCamera){var g=S.MULTIVIEW;S.MULTIVIEW=A.activeCamera.outputRenderTarget!==null&&A.activeCamera.outputRenderTarget.getViewCount()>1,S.MULTIVIEW!=g&&S.markAsUnprocessed()}},T.PrepareDefinesForPrePass=function(A,S,g){var l=S.PREPASS;if(S._arePrePassDirty){var h=[{type:R.a.PREPASS_POSITION_TEXTURE_TYPE,define:"PREPASS_POSITION",index:"PREPASS_POSITION_INDEX"},{type:R.a.PREPASS_VELOCITY_TEXTURE_TYPE,define:"PREPASS_VELOCITY",index:"PREPASS_VELOCITY_INDEX"},{type:R.a.PREPASS_REFLECTIVITY_TEXTURE_TYPE,define:"PREPASS_REFLECTIVITY",index:"PREPASS_REFLECTIVITY_INDEX"},{type:R.a.PREPASS_IRRADIANCE_TEXTURE_TYPE,define:"PREPASS_IRRADIANCE",index:"PREPASS_IRRADIANCE_INDEX"},{type:R.a.PREPASS_ALBEDO_TEXTURE_TYPE,define:"PREPASS_ALBEDO",index:"PREPASS_ALBEDO_INDEX"},{type:R.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE,define:"PREPASS_DEPTHNORMAL",index:"PREPASS_DEPTHNORMAL_INDEX"}];if(A.prePassRenderer&&A.prePassRenderer.enabled&&g){S.PREPASS=!0,S.SCENE_MRT_COUNT=A.prePassRenderer.mrtCount;for(var v=0;v<h.length;v++){var E=A.prePassRenderer.getIndex(h[v].type);E!==-1?(S[h[v].define]=!0,S[h[v].index]=E):S[h[v].define]=!1}}else for(S.PREPASS=!1,v=0;v<h.length;v++)S[h[v].define]=!1;S.PREPASS!=l&&(S.markAsUnprocessed(),S.markAsImageProcessingDirty())}},T.PrepareDefinesForLight=function(A,S,g,l,h,v,E){switch(E.needNormals=!0,h["LIGHT"+l]===void 0&&(E.needRebuild=!0),h["LIGHT"+l]=!0,h["SPOTLIGHT"+l]=!1,h["HEMILIGHT"+l]=!1,h["POINTLIGHT"+l]=!1,h["DIRLIGHT"+l]=!1,g.prepareLightSpecificDefines(h,l),h["LIGHT_FALLOFF_PHYSICAL"+l]=!1,h["LIGHT_FALLOFF_GLTF"+l]=!1,h["LIGHT_FALLOFF_STANDARD"+l]=!1,g.falloffType){case M.a.FALLOFF_GLTF:h["LIGHT_FALLOFF_GLTF"+l]=!0;break;case M.a.FALLOFF_PHYSICAL:h["LIGHT_FALLOFF_PHYSICAL"+l]=!0;break;case M.a.FALLOFF_STANDARD:h["LIGHT_FALLOFF_STANDARD"+l]=!0}if(v&&!g.specular.equalsFloats(0,0,0)&&(E.specularEnabled=!0),h["SHADOW"+l]=!1,h["SHADOWCSM"+l]=!1,h["SHADOWCSMDEBUG"+l]=!1,h["SHADOWCSMNUM_CASCADES"+l]=!1,h["SHADOWCSMUSESHADOWMAXZ"+l]=!1,h["SHADOWCSMNOBLEND"+l]=!1,h["SHADOWCSM_RIGHTHANDED"+l]=!1,h["SHADOWPCF"+l]=!1,h["SHADOWPCSS"+l]=!1,h["SHADOWPOISSON"+l]=!1,h["SHADOWESM"+l]=!1,h["SHADOWCLOSEESM"+l]=!1,h["SHADOWCUBE"+l]=!1,h["SHADOWLOWQUALITY"+l]=!1,h["SHADOWMEDIUMQUALITY"+l]=!1,S&&S.receiveShadows&&A.shadowsEnabled&&g.shadowEnabled){var D=g.getShadowGenerator();if(D){var w=D.getShadowMap();w&&w.renderList&&w.renderList.length>0&&(E.shadowEnabled=!0,D.prepareDefines(h,l))}}g.lightmapMode!=M.a.LIGHTMAP_DEFAULT?(E.lightmapMode=!0,h["LIGHTMAPEXCLUDED"+l]=!0,h["LIGHTMAPNOSPECULAR"+l]=g.lightmapMode==M.a.LIGHTMAP_SHADOWSONLY):(h["LIGHTMAPEXCLUDED"+l]=!1,h["LIGHTMAPNOSPECULAR"+l]=!1)},T.PrepareDefinesForLights=function(A,S,g,l,h,v){if(h===void 0&&(h=4),v===void 0&&(v=!1),!g._areLightsDirty)return g._needNormals;var E=0,D={needNormals:!1,needRebuild:!1,lightmapMode:!1,shadowEnabled:!1,specularEnabled:!1};if(A.lightsEnabled&&!v)for(var w=0,N=S.lightSources;w<N.length;w++){var I=N[w];if(this.PrepareDefinesForLight(A,S,I,E,g,l,D),++E===h)break}g.SPECULARTERM=D.specularEnabled,g.SHADOWS=D.shadowEnabled;for(var V=E;V<h;V++)g["LIGHT"+V]!==void 0&&(g["LIGHT"+V]=!1,g["HEMILIGHT"+V]=!1,g["POINTLIGHT"+V]=!1,g["DIRLIGHT"+V]=!1,g["SPOTLIGHT"+V]=!1,g["SHADOW"+V]=!1,g["SHADOWCSM"+V]=!1,g["SHADOWCSMDEBUG"+V]=!1,g["SHADOWCSMNUM_CASCADES"+V]=!1,g["SHADOWCSMUSESHADOWMAXZ"+V]=!1,g["SHADOWCSMNOBLEND"+V]=!1,g["SHADOWCSM_RIGHTHANDED"+V]=!1,g["SHADOWPCF"+V]=!1,g["SHADOWPCSS"+V]=!1,g["SHADOWPOISSON"+V]=!1,g["SHADOWESM"+V]=!1,g["SHADOWCLOSEESM"+V]=!1,g["SHADOWCUBE"+V]=!1,g["SHADOWLOWQUALITY"+V]=!1,g["SHADOWMEDIUMQUALITY"+V]=!1);var X=A.getEngine().getCaps();return g.SHADOWFLOAT===void 0&&(D.needRebuild=!0),g.SHADOWFLOAT=D.shadowEnabled&&(X.textureFloatRender&&X.textureFloatLinearFiltering||X.textureHalfFloatRender&&X.textureHalfFloatLinearFiltering),g.LIGHTMAPEXCLUDED=D.lightmapMode,D.needRebuild&&g.rebuild(),D.needNormals},T.PrepareUniformsAndSamplersForLight=function(A,S,g,l,h,v){h===void 0&&(h=null),v===void 0&&(v=!1),h&&h.push("Light"+A),v||(S.push("vLightData"+A,"vLightDiffuse"+A,"vLightSpecular"+A,"vLightDirection"+A,"vLightFalloff"+A,"vLightGround"+A,"lightMatrix"+A,"shadowsInfo"+A,"depthValues"+A),g.push("shadowSampler"+A),g.push("depthSampler"+A),S.push("viewFrustumZ"+A,"cascadeBlendFactor"+A,"lightSizeUVCorrection"+A,"depthCorrection"+A,"penumbraDarkness"+A,"frustumLengths"+A),l&&(g.push("projectionLightSampler"+A),S.push("textureProjectionMatrix"+A)))},T.PrepareUniformsAndSamplersList=function(A,S,g,l){var h;l===void 0&&(l=4);var v=null;if(A.uniformsNames){var E=A;h=E.uniformsNames,v=E.uniformBuffersNames,S=E.samplers,g=E.defines,l=E.maxSimultaneousLights||0}else h=A,S||(S=[]);for(var D=0;D<l&&g["LIGHT"+D];D++)this.PrepareUniformsAndSamplersForLight(D,h,S,g["PROJECTEDLIGHTTEXTURE"+D],v);g.NUM_MORPH_INFLUENCERS&&h.push("morphTargetInfluences")},T.HandleFallbacksForShadows=function(A,S,g,l){g===void 0&&(g=4),l===void 0&&(l=0);for(var h=0,v=0;v<g&&A["LIGHT"+v];v++)v>0&&(h=l+v,S.addFallback(h,"LIGHT"+v)),A.SHADOWS||(A["SHADOW"+v]&&S.addFallback(l,"SHADOW"+v),A["SHADOWPCF"+v]&&S.addFallback(l,"SHADOWPCF"+v),A["SHADOWPCSS"+v]&&S.addFallback(l,"SHADOWPCSS"+v),A["SHADOWPOISSON"+v]&&S.addFallback(l,"SHADOWPOISSON"+v),A["SHADOWESM"+v]&&S.addFallback(l,"SHADOWESM"+v),A["SHADOWCLOSEESM"+v]&&S.addFallback(l,"SHADOWCLOSEESM"+v));return h++},T.PrepareAttributesForMorphTargetsInfluencers=function(A,S,g){this._TmpMorphInfluencers.NUM_MORPH_INFLUENCERS=g,this.PrepareAttributesForMorphTargets(A,S,this._TmpMorphInfluencers)},T.PrepareAttributesForMorphTargets=function(A,S,g){var l=g.NUM_MORPH_INFLUENCERS;if(l>0&&C.a.LastCreatedEngine)for(var h=C.a.LastCreatedEngine.getCaps().maxVertexAttribs,v=S.morphTargetManager,E=v&&v.supportsNormals&&g.NORMAL,D=v&&v.supportsTangents&&g.TANGENT,w=v&&v.supportsUVs&&g.UV1,N=0;N<l;N++)A.push(u.b.PositionKind+N),E&&A.push(u.b.NormalKind+N),D&&A.push(u.b.TangentKind+N),w&&A.push(u.b.UVKind+"_"+N),A.length>h&&U.a.Error("Cannot add more vertex attributes for mesh "+S.name)},T.PrepareAttributesForBones=function(A,S,g,l){g.NUM_BONE_INFLUENCERS>0&&(l.addCPUSkinningFallback(0,S),A.push(u.b.MatricesIndicesKind),A.push(u.b.MatricesWeightsKind),g.NUM_BONE_INFLUENCERS>4&&(A.push(u.b.MatricesIndicesExtraKind),A.push(u.b.MatricesWeightsExtraKind)))},T.PrepareAttributesForInstances=function(A,S){(S.INSTANCES||S.THIN_INSTANCES)&&this.PushAttributesForInstances(A)},T.PushAttributesForInstances=function(A){A.push("world0"),A.push("world1"),A.push("world2"),A.push("world3")},T.BindLightProperties=function(A,S,g){A.transferToEffect(S,g+"")},T.BindLight=function(A,S,g,l,h,v){v===void 0&&(v=!1),A._bindLight(S,g,l,h,v)},T.BindLights=function(A,S,g,l,h,v){h===void 0&&(h=4),v===void 0&&(v=!1);for(var E=Math.min(S.lightSources.length,h),D=0;D<E;D++){var w=S.lightSources[D];this.BindLight(w,D,A,g,typeof l=="boolean"?l:l.SPECULARTERM,v)}},T.BindFogParameters=function(A,S,g,l){l===void 0&&(l=!1),A.fogEnabled&&S.applyFog&&A.fogMode!==_.a.FOGMODE_NONE&&(g.setFloat4("vFogInfos",A.fogMode,A.fogStart,A.fogEnd,A.fogDensity),l?(A.fogColor.toLinearSpaceToRef(this._tempFogColor),g.setColor3("vFogColor",this._tempFogColor)):g.setColor3("vFogColor",A.fogColor))},T.BindBonesParameters=function(A,S,g){if(S&&A&&(A.computeBonesUsingShaders&&S._bonesComputationForcedToCPU&&(A.computeBonesUsingShaders=!1),A.useBones&&A.computeBonesUsingShaders&&A.skeleton)){var l=A.skeleton;if(l.isUsingTextureForMatrices&&S.getUniformIndex("boneTextureWidth")>-1){var h=l.getTransformMatrixTexture(A);S.setTexture("boneSampler",h),S.setFloat("boneTextureWidth",4*(l.bones.length+1))}else{var v=l.getTransformMatrices(A);v&&(S.setMatrices("mBones",v),g&&A.getScene().prePassRenderer&&A.getScene().prePassRenderer.getIndex(R.a.PREPASS_VELOCITY_TEXTURE_TYPE)&&(g.previousBones[A.uniqueId]&&S.setMatrices("mPreviousBones",g.previousBones[A.uniqueId]),T._CopyBonesTransformationMatrices(v,g.previousBones[A.uniqueId])))}}},T._CopyBonesTransformationMatrices=function(A,S){return S.set(A),S},T.BindMorphTargetParameters=function(A,S){var g=A.morphTargetManager;A&&g&&S.setFloatArray("morphTargetInfluences",g.influences)},T.BindLogDepth=function(A,S,g){A.LOGARITHMICDEPTH&&S.setFloat("logarithmicDepthConstant",2/(Math.log(g.activeCamera.maxZ+1)/Math.LN2))},T.BindClipPlane=function(A,S){m.a.BindClipPlane(A,S)},T._TmpMorphInfluencers={NUM_MORPH_INFLUENCERS:0},T._tempFogColor=x.a.Black(),T}()},function(Me,y,f){f.d(y,"a",function(){return R});var U=f(0),_=f(4),C=f(21),u=f(9),M=f(8),R=function(){function x(){}return x.prototype.set=function(m,c){switch(m.length||M.a.Warn("Setting vertex data kind '"+c+"' with an empty array"),c){case _.b.PositionKind:this.positions=m;break;case _.b.NormalKind:this.normals=m;break;case _.b.TangentKind:this.tangents=m;break;case _.b.UVKind:this.uvs=m;break;case _.b.UV2Kind:this.uvs2=m;break;case _.b.UV3Kind:this.uvs3=m;break;case _.b.UV4Kind:this.uvs4=m;break;case _.b.UV5Kind:this.uvs5=m;break;case _.b.UV6Kind:this.uvs6=m;break;case _.b.ColorKind:this.colors=m;break;case _.b.MatricesIndicesKind:this.matricesIndices=m;break;case _.b.MatricesWeightsKind:this.matricesWeights=m;break;case _.b.MatricesIndicesExtraKind:this.matricesIndicesExtra=m;break;case _.b.MatricesWeightsExtraKind:this.matricesWeightsExtra=m}},x.prototype.applyToMesh=function(m,c){return this._applyTo(m,c),this},x.prototype.applyToGeometry=function(m,c){return this._applyTo(m,c),this},x.prototype.updateMesh=function(m){return this._update(m),this},x.prototype.updateGeometry=function(m){return this._update(m),this},x.prototype._applyTo=function(m,c){return c===void 0&&(c=!1),this.positions&&m.setVerticesData(_.b.PositionKind,this.positions,c),this.normals&&m.setVerticesData(_.b.NormalKind,this.normals,c),this.tangents&&m.setVerticesData(_.b.TangentKind,this.tangents,c),this.uvs&&m.setVerticesData(_.b.UVKind,this.uvs,c),this.uvs2&&m.setVerticesData(_.b.UV2Kind,this.uvs2,c),this.uvs3&&m.setVerticesData(_.b.UV3Kind,this.uvs3,c),this.uvs4&&m.setVerticesData(_.b.UV4Kind,this.uvs4,c),this.uvs5&&m.setVerticesData(_.b.UV5Kind,this.uvs5,c),this.uvs6&&m.setVerticesData(_.b.UV6Kind,this.uvs6,c),this.colors&&m.setVerticesData(_.b.ColorKind,this.colors,c),this.matricesIndices&&m.setVerticesData(_.b.MatricesIndicesKind,this.matricesIndices,c),this.matricesWeights&&m.setVerticesData(_.b.MatricesWeightsKind,this.matricesWeights,c),this.matricesIndicesExtra&&m.setVerticesData(_.b.MatricesIndicesExtraKind,this.matricesIndicesExtra,c),this.matricesWeightsExtra&&m.setVerticesData(_.b.MatricesWeightsExtraKind,this.matricesWeightsExtra,c),this.indices?m.setIndices(this.indices,null,c):m.setIndices([],null),this},x.prototype._update=function(m,c,T){return this.positions&&m.updateVerticesData(_.b.PositionKind,this.positions,c,T),this.normals&&m.updateVerticesData(_.b.NormalKind,this.normals,c,T),this.tangents&&m.updateVerticesData(_.b.TangentKind,this.tangents,c,T),this.uvs&&m.updateVerticesData(_.b.UVKind,this.uvs,c,T),this.uvs2&&m.updateVerticesData(_.b.UV2Kind,this.uvs2,c,T),this.uvs3&&m.updateVerticesData(_.b.UV3Kind,this.uvs3,c,T),this.uvs4&&m.updateVerticesData(_.b.UV4Kind,this.uvs4,c,T),this.uvs5&&m.updateVerticesData(_.b.UV5Kind,this.uvs5,c,T),this.uvs6&&m.updateVerticesData(_.b.UV6Kind,this.uvs6,c,T),this.colors&&m.updateVerticesData(_.b.ColorKind,this.colors,c,T),this.matricesIndices&&m.updateVerticesData(_.b.MatricesIndicesKind,this.matricesIndices,c,T),this.matricesWeights&&m.updateVerticesData(_.b.MatricesWeightsKind,this.matricesWeights,c,T),this.matricesIndicesExtra&&m.updateVerticesData(_.b.MatricesIndicesExtraKind,this.matricesIndicesExtra,c,T),this.matricesWeightsExtra&&m.updateVerticesData(_.b.MatricesWeightsExtraKind,this.matricesWeightsExtra,c,T),this.indices&&m.setIndices(this.indices,null),this},x.prototype.transform=function(m){var c,T=m.determinant()<0,A=U.e.Zero();if(this.positions){var S=U.e.Zero();for(c=0;c<this.positions.length;c+=3)U.e.FromArrayToRef(this.positions,c,S),U.e.TransformCoordinatesToRef(S,m,A),this.positions[c]=A.x,this.positions[c+1]=A.y,this.positions[c+2]=A.z}if(this.normals){var g=U.e.Zero();for(c=0;c<this.normals.length;c+=3)U.e.FromArrayToRef(this.normals,c,g),U.e.TransformNormalToRef(g,m,A),this.normals[c]=A.x,this.normals[c+1]=A.y,this.normals[c+2]=A.z}if(this.tangents){var l=U.f.Zero(),h=U.f.Zero();for(c=0;c<this.tangents.length;c+=4)U.f.FromArrayToRef(this.tangents,c,l),U.f.TransformNormalToRef(l,m,h),this.tangents[c]=h.x,this.tangents[c+1]=h.y,this.tangents[c+2]=h.z,this.tangents[c+3]=h.w}if(T&&this.indices)for(c=0;c<this.indices.length;c+=3){var v=this.indices[c+1];this.indices[c+1]=this.indices[c+2],this.indices[c+2]=v}return this},x.prototype.merge=function(m,c){if(c===void 0&&(c=!1),this._validate(),m._validate(),!this.normals!=!m.normals||!this.tangents!=!m.tangents||!this.uvs!=!m.uvs||!this.uvs2!=!m.uvs2||!this.uvs3!=!m.uvs3||!this.uvs4!=!m.uvs4||!this.uvs5!=!m.uvs5||!this.uvs6!=!m.uvs6||!this.colors!=!m.colors||!this.matricesIndices!=!m.matricesIndices||!this.matricesWeights!=!m.matricesWeights||!this.matricesIndicesExtra!=!m.matricesIndicesExtra||!this.matricesWeightsExtra!=!m.matricesWeightsExtra)throw new Error("Cannot merge vertex data that do not have the same set of attributes");if(m.indices){this.indices||(this.indices=[]);var T=this.positions?this.positions.length/3:0;if(this.indices.BYTES_PER_ELEMENT!==void 0){var A=this.indices.length+m.indices.length,S=c||this.indices instanceof Uint32Array?new Uint32Array(A):new Uint16Array(A);S.set(this.indices);for(var g=this.indices.length,l=0;l<m.indices.length;l++)S[g+l]=m.indices[l]+T;this.indices=S}else for(l=0;l<m.indices.length;l++)this.indices.push(m.indices[l]+T)}return this.positions=this._mergeElement(this.positions,m.positions),this.normals=this._mergeElement(this.normals,m.normals),this.tangents=this._mergeElement(this.tangents,m.tangents),this.uvs=this._mergeElement(this.uvs,m.uvs),this.uvs2=this._mergeElement(this.uvs2,m.uvs2),this.uvs3=this._mergeElement(this.uvs3,m.uvs3),this.uvs4=this._mergeElement(this.uvs4,m.uvs4),this.uvs5=this._mergeElement(this.uvs5,m.uvs5),this.uvs6=this._mergeElement(this.uvs6,m.uvs6),this.colors=this._mergeElement(this.colors,m.colors),this.matricesIndices=this._mergeElement(this.matricesIndices,m.matricesIndices),this.matricesWeights=this._mergeElement(this.matricesWeights,m.matricesWeights),this.matricesIndicesExtra=this._mergeElement(this.matricesIndicesExtra,m.matricesIndicesExtra),this.matricesWeightsExtra=this._mergeElement(this.matricesWeightsExtra,m.matricesWeightsExtra),this},x.prototype._mergeElement=function(m,c){if(!m)return c;if(!c)return m;var T=c.length+m.length,A=m instanceof Float32Array,S=c instanceof Float32Array;if(A){var g=new Float32Array(T);return g.set(m),g.set(c,m.length),g}if(S){var l=m.slice(0),h=0;for(T=c.length;h<T;h++)l.push(c[h]);return l}return m.concat(c)},x.prototype._validate=function(){if(!this.positions)throw new Error("Positions are required");var m=function(A,S){var g=_.b.DeduceStride(A);if(S.length%g!=0)throw new Error("The "+A+"s array count must be a multiple of "+g);return S.length/g},c=m(_.b.PositionKind,this.positions),T=function(A,S){var g=m(A,S);if(g!==c)throw new Error("The "+A+"s element count ("+g+") does not match the positions count ("+c+")")};this.normals&&T(_.b.NormalKind,this.normals),this.tangents&&T(_.b.TangentKind,this.tangents),this.uvs&&T(_.b.UVKind,this.uvs),this.uvs2&&T(_.b.UV2Kind,this.uvs2),this.uvs3&&T(_.b.UV3Kind,this.uvs3),this.uvs4&&T(_.b.UV4Kind,this.uvs4),this.uvs5&&T(_.b.UV5Kind,this.uvs5),this.uvs6&&T(_.b.UV6Kind,this.uvs6),this.colors&&T(_.b.ColorKind,this.colors),this.matricesIndices&&T(_.b.MatricesIndicesKind,this.matricesIndices),this.matricesWeights&&T(_.b.MatricesWeightsKind,this.matricesWeights),this.matricesIndicesExtra&&T(_.b.MatricesIndicesExtraKind,this.matricesIndicesExtra),this.matricesWeightsExtra&&T(_.b.MatricesWeightsExtraKind,this.matricesWeightsExtra)},x.prototype.serialize=function(){var m=this.serialize();return this.positions&&(m.positions=this.positions),this.normals&&(m.normals=this.normals),this.tangents&&(m.tangents=this.tangents),this.uvs&&(m.uvs=this.uvs),this.uvs2&&(m.uvs2=this.uvs2),this.uvs3&&(m.uvs3=this.uvs3),this.uvs4&&(m.uvs4=this.uvs4),this.uvs5&&(m.uvs5=this.uvs5),this.uvs6&&(m.uvs6=this.uvs6),this.colors&&(m.colors=this.colors),this.matricesIndices&&(m.matricesIndices=this.matricesIndices,m.matricesIndices._isExpanded=!0),this.matricesWeights&&(m.matricesWeights=this.matricesWeights),this.matricesIndicesExtra&&(m.matricesIndicesExtra=this.matricesIndicesExtra,m.matricesIndicesExtra._isExpanded=!0),this.matricesWeightsExtra&&(m.matricesWeightsExtra=this.matricesWeightsExtra),m.indices=this.indices,m},x.ExtractFromMesh=function(m,c,T){return x._ExtractFrom(m,c,T)},x.ExtractFromGeometry=function(m,c,T){return x._ExtractFrom(m,c,T)},x._ExtractFrom=function(m,c,T){var A=new x;return m.isVerticesDataPresent(_.b.PositionKind)&&(A.positions=m.getVerticesData(_.b.PositionKind,c,T)),m.isVerticesDataPresent(_.b.NormalKind)&&(A.normals=m.getVerticesData(_.b.NormalKind,c,T)),m.isVerticesDataPresent(_.b.TangentKind)&&(A.tangents=m.getVerticesData(_.b.TangentKind,c,T)),m.isVerticesDataPresent(_.b.UVKind)&&(A.uvs=m.getVerticesData(_.b.UVKind,c,T)),m.isVerticesDataPresent(_.b.UV2Kind)&&(A.uvs2=m.getVerticesData(_.b.UV2Kind,c,T)),m.isVerticesDataPresent(_.b.UV3Kind)&&(A.uvs3=m.getVerticesData(_.b.UV3Kind,c,T)),m.isVerticesDataPresent(_.b.UV4Kind)&&(A.uvs4=m.getVerticesData(_.b.UV4Kind,c,T)),m.isVerticesDataPresent(_.b.UV5Kind)&&(A.uvs5=m.getVerticesData(_.b.UV5Kind,c,T)),m.isVerticesDataPresent(_.b.UV6Kind)&&(A.uvs6=m.getVerticesData(_.b.UV6Kind,c,T)),m.isVerticesDataPresent(_.b.ColorKind)&&(A.colors=m.getVerticesData(_.b.ColorKind,c,T)),m.isVerticesDataPresent(_.b.MatricesIndicesKind)&&(A.matricesIndices=m.getVerticesData(_.b.MatricesIndicesKind,c,T)),m.isVerticesDataPresent(_.b.MatricesWeightsKind)&&(A.matricesWeights=m.getVerticesData(_.b.MatricesWeightsKind,c,T)),m.isVerticesDataPresent(_.b.MatricesIndicesExtraKind)&&(A.matricesIndicesExtra=m.getVerticesData(_.b.MatricesIndicesExtraKind,c,T)),m.isVerticesDataPresent(_.b.MatricesWeightsExtraKind)&&(A.matricesWeightsExtra=m.getVerticesData(_.b.MatricesWeightsExtraKind,c,T)),A.indices=m.getIndices(c,T),A},x.CreateRibbon=function(m){throw C.a.WarnImport("ribbonBuilder")},x.CreateBox=function(m){throw C.a.WarnImport("boxBuilder")},x.CreateTiledBox=function(m){throw C.a.WarnImport("tiledBoxBuilder")},x.CreateTiledPlane=function(m){throw C.a.WarnImport("tiledPlaneBuilder")},x.CreateSphere=function(m){throw C.a.WarnImport("sphereBuilder")},x.CreateCylinder=function(m){throw C.a.WarnImport("cylinderBuilder")},x.CreateTorus=function(m){throw C.a.WarnImport("torusBuilder")},x.CreateLineSystem=function(m){throw C.a.WarnImport("linesBuilder")},x.CreateDashedLines=function(m){throw C.a.WarnImport("linesBuilder")},x.CreateGround=function(m){throw C.a.WarnImport("groundBuilder")},x.CreateTiledGround=function(m){throw C.a.WarnImport("groundBuilder")},x.CreateGroundFromHeightMap=function(m){throw C.a.WarnImport("groundBuilder")},x.CreatePlane=function(m){throw C.a.WarnImport("planeBuilder")},x.CreateDisc=function(m){throw C.a.WarnImport("discBuilder")},x.CreatePolygon=function(m,c,T,A,S,g,l){throw C.a.WarnImport("polygonBuilder")},x.CreateIcoSphere=function(m){throw C.a.WarnImport("icoSphereBuilder")},x.CreatePolyhedron=function(m){throw C.a.WarnImport("polyhedronBuilder")},x.CreateCapsule=function(m){throw m===void 0&&(m={orientation:U.e.Up(),subdivisions:2,tessellation:16,height:1,radius:.25,capSubdivisions:6}),C.a.WarnImport("capsuleBuilder")},x.CreateTorusKnot=function(m){throw C.a.WarnImport("torusKnotBuilder")},x.ComputeNormals=function(m,c,T,A){var S=0,g=0,l=0,h=0,v=0,E=0,D=0,w=0,N=0,I=0,V=0,X=0,j=0,ne=0,te=0,de=0,pe=0,ae=0,ee=0,K=0,$=!1,L=!1,G=!1,Q=!1,oe=1,re=0,Y=null;if(A&&($=!!A.facetNormals,L=!!A.facetPositions,G=!!A.facetPartitioning,oe=A.useRightHandedSystem===!0?-1:1,re=A.ratio||0,Q=!!A.depthSort,Y=A.distanceTo,Q)){Y===void 0&&(Y=U.e.Zero());var k=A.depthSortedFacets}var H=0,Z=0,W=0,q=0;if(G&&A&&A.bbSize){var he=0,ge=0,me=0,_e=0,be=0,Pe=0,ye=0,Be=0,ke=0,We=0,je=0,He=0,qe=0,Ge=0,nt=0,$e=0,lt=A.bbSize.x>A.bbSize.y?A.bbSize.x:A.bbSize.y;lt=lt>A.bbSize.z?lt:A.bbSize.z,H=A.subDiv.X*re/A.bbSize.x,Z=A.subDiv.Y*re/A.bbSize.y,W=A.subDiv.Z*re/A.bbSize.z,q=A.subDiv.max*A.subDiv.max,A.facetPartitioning.length=0}for(S=0;S<m.length;S++)T[S]=0;var st=c.length/3|0;for(S=0;S<st;S++){if(j=(X=3*c[3*S])+1,ne=X+2,de=(te=3*c[3*S+1])+1,pe=te+2,ee=(ae=3*c[3*S+2])+1,K=ae+2,g=m[X]-m[te],l=m[j]-m[de],h=m[ne]-m[pe],v=m[ae]-m[te],E=m[ee]-m[de],w=oe*(l*(D=m[K]-m[pe])-h*E),N=oe*(h*v-g*D),I=oe*(g*E-l*v),w/=V=(V=Math.sqrt(w*w+N*N+I*I))===0?1:V,N/=V,I/=V,$&&A&&(A.facetNormals[S].x=w,A.facetNormals[S].y=N,A.facetNormals[S].z=I),L&&A&&(A.facetPositions[S].x=(m[X]+m[te]+m[ae])/3,A.facetPositions[S].y=(m[j]+m[de]+m[ee])/3,A.facetPositions[S].z=(m[ne]+m[pe]+m[K])/3),G&&A&&(he=Math.floor((A.facetPositions[S].x-A.bInfo.minimum.x*re)*H),ge=Math.floor((A.facetPositions[S].y-A.bInfo.minimum.y*re)*Z),me=Math.floor((A.facetPositions[S].z-A.bInfo.minimum.z*re)*W),_e=Math.floor((m[X]-A.bInfo.minimum.x*re)*H),be=Math.floor((m[j]-A.bInfo.minimum.y*re)*Z),Pe=Math.floor((m[ne]-A.bInfo.minimum.z*re)*W),ye=Math.floor((m[te]-A.bInfo.minimum.x*re)*H),Be=Math.floor((m[de]-A.bInfo.minimum.y*re)*Z),ke=Math.floor((m[pe]-A.bInfo.minimum.z*re)*W),We=Math.floor((m[ae]-A.bInfo.minimum.x*re)*H),je=Math.floor((m[ee]-A.bInfo.minimum.y*re)*Z),He=Math.floor((m[K]-A.bInfo.minimum.z*re)*W),Ge=_e+A.subDiv.max*be+q*Pe,nt=ye+A.subDiv.max*Be+q*ke,$e=We+A.subDiv.max*je+q*He,qe=he+A.subDiv.max*ge+q*me,A.facetPartitioning[qe]=A.facetPartitioning[qe]?A.facetPartitioning[qe]:new Array,A.facetPartitioning[Ge]=A.facetPartitioning[Ge]?A.facetPartitioning[Ge]:new Array,A.facetPartitioning[nt]=A.facetPartitioning[nt]?A.facetPartitioning[nt]:new Array,A.facetPartitioning[$e]=A.facetPartitioning[$e]?A.facetPartitioning[$e]:new Array,A.facetPartitioning[Ge].push(S),nt!=Ge&&A.facetPartitioning[nt].push(S),$e!=nt&&$e!=Ge&&A.facetPartitioning[$e].push(S),qe!=Ge&&qe!=nt&&qe!=$e&&A.facetPartitioning[qe].push(S)),Q&&A&&A.facetPositions){var mt=k[S];mt.ind=3*S,mt.sqDistance=U.e.DistanceSquared(A.facetPositions[S],Y)}T[X]+=w,T[j]+=N,T[ne]+=I,T[te]+=w,T[de]+=N,T[pe]+=I,T[ae]+=w,T[ee]+=N,T[K]+=I}for(S=0;S<T.length/3;S++)w=T[3*S],N=T[3*S+1],I=T[3*S+2],w/=V=(V=Math.sqrt(w*w+N*N+I*I))===0?1:V,N/=V,I/=V,T[3*S]=w,T[3*S+1]=N,T[3*S+2]=I},x._ComputeSides=function(m,c,T,A,S,g,l){var h,v,E=T.length,D=A.length;switch(m=m||x.DEFAULTSIDE){case x.FRONTSIDE:break;case x.BACKSIDE:var w;for(h=0;h<E;h+=3)w=T[h],T[h]=T[h+2],T[h+2]=w;for(v=0;v<D;v++)A[v]=-A[v];break;case x.DOUBLESIDE:for(var 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X=m.indices;X&&(T.indices=X),c.setAllVerticesData(T,m.updatable)},x.FRONTSIDE=0,x.BACKSIDE=1,x.DOUBLESIDE=2,x.DEFAULTSIDE=0,x}()},function(Me,y,f){f.d(y,"a",function(){return _}),f.d(y,"b",function(){return C});var U=f(1),_=function(){function u(){}return 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this._LightmapTextureEnabled},set:function(M){this._LightmapTextureEnabled!==M&&(this._LightmapTextureEnabled=M,U.a.MarkAllMaterialsAsDirty(_.a.MATERIAL_TextureDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(u,"RefractionTextureEnabled",{get:function(){return this._RefractionTextureEnabled},set:function(M){this._RefractionTextureEnabled!==M&&(this._RefractionTextureEnabled=M,U.a.MarkAllMaterialsAsDirty(_.a.MATERIAL_TextureDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(u,"ColorGradingTextureEnabled",{get:function(){return this._ColorGradingTextureEnabled},set:function(M){this._ColorGradingTextureEnabled!==M&&(this._ColorGradingTextureEnabled=M,U.a.MarkAllMaterialsAsDirty(_.a.MATERIAL_TextureDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(u,"FresnelEnabled",{get:function(){return this._FresnelEnabled},set:function(M){this._FresnelEnabled!==M&&(this._FresnelEnabled=M,U.a.MarkAllMaterialsAsDirty(_.a.MATERIAL_FresnelDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(u,"ClearCoatTextureEnabled",{get:function(){return this._ClearCoatTextureEnabled},set:function(M){this._ClearCoatTextureEnabled!==M&&(this._ClearCoatTextureEnabled=M,U.a.MarkAllMaterialsAsDirty(_.a.MATERIAL_TextureDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(u,"ClearCoatBumpTextureEnabled",{get:function(){return this._ClearCoatBumpTextureEnabled},set:function(M){this._ClearCoatBumpTextureEnabled!==M&&(this._ClearCoatBumpTextureEnabled=M,U.a.MarkAllMaterialsAsDirty(_.a.MATERIAL_TextureDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(u,"ClearCoatTintTextureEnabled",{get:function(){return 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this._ThicknessTextureEnabled},set:function(M){this._ThicknessTextureEnabled!==M&&(this._ThicknessTextureEnabled=M,U.a.MarkAllMaterialsAsDirty(_.a.MATERIAL_TextureDirtyFlag))},enumerable:!1,configurable:!0}),u._DiffuseTextureEnabled=!0,u._DetailTextureEnabled=!0,u._AmbientTextureEnabled=!0,u._OpacityTextureEnabled=!0,u._ReflectionTextureEnabled=!0,u._EmissiveTextureEnabled=!0,u._SpecularTextureEnabled=!0,u._BumpTextureEnabled=!0,u._LightmapTextureEnabled=!0,u._RefractionTextureEnabled=!0,u._ColorGradingTextureEnabled=!0,u._FresnelEnabled=!0,u._ClearCoatTextureEnabled=!0,u._ClearCoatBumpTextureEnabled=!0,u._ClearCoatTintTextureEnabled=!0,u._SheenTextureEnabled=!0,u._AnisotropicTextureEnabled=!0,u._ThicknessTextureEnabled=!0,u}()},function(Me,y,f){f.d(y,"a",function(){return oe});var U=f(1),_=f(12),C=f(57),u=f(6),M=f(33),R=f(112),x=f(37),m=f(0),c=f(46),T=f(31),A=f(24),S=f(35),g=f(42),l=f(85),h=f(48),v=f(54),E=f(47),D=f(95),w=f(96),N=f(17),I=f(2),V=f(38),X=f(8),j=f(22),ne=f(21),te=f(18),de=f(91),pe=f(66),ae=function(){function re(){this._singleClick=!1,this._doubleClick=!1,this._hasSwiped=!1,this._ignore=!1}return Object.defineProperty(re.prototype,"singleClick",{get:function(){return this._singleClick},set:function(Y){this._singleClick=Y},enumerable:!1,configurable:!0}),Object.defineProperty(re.prototype,"doubleClick",{get:function(){return this._doubleClick},set:function(Y){this._doubleClick=Y},enumerable:!1,configurable:!0}),Object.defineProperty(re.prototype,"hasSwiped",{get:function(){return this._hasSwiped},set:function(Y){this._hasSwiped=Y},enumerable:!1,configurable:!0}),Object.defineProperty(re.prototype,"ignore",{get:function(){return this._ignore},set:function(Y){this._ignore=Y},enumerable:!1,configurable:!0}),re}(),ee=function(){function re(Y){this._alreadyAttached=!1,this._wheelEventName="",this._meshPickProceed=!1,this._currentPickResult=null,this._previousPickResult=null,this._totalPointersPressed=0,this._doubleClickOccured=!1,this._pointerX=0,this._pointerY=0,this._startingPointerPosition=new m.d(0,0),this._previousStartingPointerPosition=new m.d(0,0),this._startingPointerTime=0,this._previousStartingPointerTime=0,this._pointerCaptures={},this._meshUnderPointerId=[],this._keyboardIsAttached=!1,this._scene=Y}return Object.defineProperty(re.prototype,"meshUnderPointer",{get:function(){return this._pointerOverMesh},enumerable:!1,configurable:!0}),re.prototype.getMeshUnderPointerByPointerId=function(Y){return this._meshUnderPointerId[Y]},Object.defineProperty(re.prototype,"unTranslatedPointer",{get:function(){return new m.d(this._unTranslatedPointerX,this._unTranslatedPointerY)},enumerable:!1,configurable:!0}),Object.defineProperty(re.prototype,"pointerX",{get:function(){return this._pointerX},set:function(Y){this._pointerX=Y},enumerable:!1,configurable:!0}),Object.defineProperty(re.prototype,"pointerY",{get:function(){return this._pointerY},set:function(Y){this._pointerY=Y},enumerable:!1,configurable:!0}),re.prototype._updatePointerPosition=function(Y){var k=this._scene.getEngine().getInputElementClientRect();k&&(this._pointerX=Y.clientX-k.left,this._pointerY=Y.clientY-k.top,this._unTranslatedPointerX=this._pointerX,this._unTranslatedPointerY=this._pointerY)},re.prototype._processPointerMove=function(Y,k){var H=this._scene,Z=H.getEngine(),W=Z.getInputElement();if(W){W.tabIndex=Z.canvasTabIndex,H.doNotHandleCursors||(W.style.cursor=H.defaultCursor);var q=!!(Y&&Y.hit&&Y.pickedMesh);q?(H.setPointerOverMesh(Y.pickedMesh,k.pointerId),this._pointerOverMesh&&this._pointerOverMesh.actionManager&&this._pointerOverMesh.actionManager.hasPointerTriggers&&(H.doNotHandleCursors||(this._pointerOverMesh.actionManager.hoverCursor?W.style.cursor=this._pointerOverMesh.actionManager.hoverCursor:W.style.cursor=H.hoverCursor))):H.setPointerOverMesh(null,k.pointerId);for(var he=0,ge=H._pointerMoveStage;he<ge.length;he++)Y=ge[he].action(this._unTranslatedPointerX,this._unTranslatedPointerY,Y,q,W);if(Y){var me=k.type===this._wheelEventName?te.a.POINTERWHEEL:te.a.POINTERMOVE;if(H.onPointerMove&&H.onPointerMove(k,Y,me),H.onPointerObservable.hasObservers()){var _e=new te.b(me,k,Y);this._setRayOnPointerInfo(_e),H.onPointerObservable.notifyObservers(_e,me)}}}},re.prototype._setRayOnPointerInfo=function(Y){var k=this._scene;Y.pickInfo&&!Y.pickInfo._pickingUnavailable&&(Y.pickInfo.ray||(Y.pickInfo.ray=k.createPickingRay(Y.event.offsetX,Y.event.offsetY,m.a.Identity(),k.activeCamera)))},re.prototype._checkPrePointerObservable=function(Y,k,H){var Z=this._scene,W=new te.d(H,k,this._unTranslatedPointerX,this._unTranslatedPointerY);return Y&&(W.ray=Y.ray),Z.onPrePointerObservable.notifyObservers(W,H),!!W.skipOnPointerObservable},re.prototype.simulatePointerMove=function(Y,k){var H=new PointerEvent("pointermove",k);this._checkPrePointerObservable(Y,H,te.a.POINTERMOVE)||this._processPointerMove(Y,H)},re.prototype.simulatePointerDown=function(Y,k){var H=new PointerEvent("pointerdown",k);this._checkPrePointerObservable(Y,H,te.a.POINTERDOWN)||this._processPointerDown(Y,H)},re.prototype._processPointerDown=function(Y,k){var H=this,Z=this._scene;if(Y&&Y.hit&&Y.pickedMesh){this._pickedDownMesh=Y.pickedMesh;var W=Y.pickedMesh._getActionManagerForTrigger();if(W){if(W.hasPickTriggers)switch(W.processTrigger(I.a.ACTION_OnPickDownTrigger,E.a.CreateNew(Y.pickedMesh,k)),k.button){case 0:W.processTrigger(I.a.ACTION_OnLeftPickTrigger,E.a.CreateNew(Y.pickedMesh,k));break;case 1:W.processTrigger(I.a.ACTION_OnCenterPickTrigger,E.a.CreateNew(Y.pickedMesh,k));break;case 2:W.processTrigger(I.a.ACTION_OnRightPickTrigger,E.a.CreateNew(Y.pickedMesh,k))}W.hasSpecificTrigger(I.a.ACTION_OnLongPressTrigger)&&window.setTimeout(function(){var _e=Z.pick(H._unTranslatedPointerX,H._unTranslatedPointerY,function(be){return be.isPickable&&be.isVisible&&be.isReady()&&be.actionManager&&be.actionManager.hasSpecificTrigger(I.a.ACTION_OnLongPressTrigger)&&be==H._pickedDownMesh},!1,Z.cameraToUseForPointers);_e&&_e.hit&&_e.pickedMesh&&W&&H._totalPointersPressed!==0&&Date.now()-H._startingPointerTime>re.LongPressDelay&&!H._isPointerSwiping()&&(H._startingPointerTime=0,W.processTrigger(I.a.ACTION_OnLongPressTrigger,E.a.CreateNew(_e.pickedMesh,k)))},re.LongPressDelay)}}else for(var q=0,he=Z._pointerDownStage;q<he.length;q++)Y=he[q].action(this._unTranslatedPointerX,this._unTranslatedPointerY,Y,k);if(Y){var ge=te.a.POINTERDOWN;if(Z.onPointerDown&&Z.onPointerDown(k,Y,ge),Z.onPointerObservable.hasObservers()){var me=new te.b(ge,k,Y);this._setRayOnPointerInfo(me),Z.onPointerObservable.notifyObservers(me,ge)}}},re.prototype._isPointerSwiping=function(){return Math.abs(this._startingPointerPosition.x-this._pointerX)>re.DragMovementThreshold||Math.abs(this._startingPointerPosition.y-this._pointerY)>re.DragMovementThreshold},re.prototype.simulatePointerUp=function(Y,k,H){var Z=new PointerEvent("pointerup",k),W=new ae;H?W.doubleClick=!0:W.singleClick=!0,this._checkPrePointerObservable(Y,Z,te.a.POINTERUP)||this._processPointerUp(Y,Z,W)},re.prototype._processPointerUp=function(Y,k,H){var Z=this._scene;if(Y&&Y&&Y.pickedMesh){if(this._pickedUpMesh=Y.pickedMesh,this._pickedDownMesh===this._pickedUpMesh&&(Z.onPointerPick&&Z.onPointerPick(k,Y),H.singleClick&&!H.ignore&&Z.onPointerObservable.hasObservers())){var W=te.a.POINTERPICK,q=new te.b(W,k,Y);this._setRayOnPointerInfo(q),Z.onPointerObservable.notifyObservers(q,W)}var he=Y.pickedMesh._getActionManagerForTrigger();if(he&&!H.ignore){he.processTrigger(I.a.ACTION_OnPickUpTrigger,E.a.CreateNew(Y.pickedMesh,k)),!H.hasSwiped&&H.singleClick&&he.processTrigger(I.a.ACTION_OnPickTrigger,E.a.CreateNew(Y.pickedMesh,k));var ge=Y.pickedMesh._getActionManagerForTrigger(I.a.ACTION_OnDoublePickTrigger);H.doubleClick&&ge&&ge.processTrigger(I.a.ACTION_OnDoublePickTrigger,E.a.CreateNew(Y.pickedMesh,k))}}else if(!H.ignore)for(var me=0,_e=Z._pointerUpStage;me<_e.length;me++)Y=_e[me].action(this._unTranslatedPointerX,this._unTranslatedPointerY,Y,k);if(this._pickedDownMesh&&this._pickedDownMesh!==this._pickedUpMesh){var be=this._pickedDownMesh._getActionManagerForTrigger(I.a.ACTION_OnPickOutTrigger);be&&be.processTrigger(I.a.ACTION_OnPickOutTrigger,E.a.CreateNew(this._pickedDownMesh,k))}var Pe=0;Z.onPointerObservable.hasObservers()&&(!H.ignore&&!H.hasSwiped&&(H.singleClick&&Z.onPointerObservable.hasSpecificMask(te.a.POINTERTAP)?Pe=te.a.POINTERTAP:H.doubleClick&&Z.onPointerObservable.hasSpecificMask(te.a.POINTERDOUBLETAP)&&(Pe=te.a.POINTERDOUBLETAP),Pe)&&(q=new te.b(Pe,k,Y),this._setRayOnPointerInfo(q),Z.onPointerObservable.notifyObservers(q,Pe)),H.ignore||(Pe=te.a.POINTERUP,q=new te.b(Pe,k,Y),this._setRayOnPointerInfo(q),Z.onPointerObservable.notifyObservers(q,Pe))),Z.onPointerUp&&!H.ignore&&Z.onPointerUp(k,Y,Pe)},re.prototype.isPointerCaptured=function(Y){return Y===void 0&&(Y=0),this._pointerCaptures[Y]},re.prototype.attachControl=function(Y,k,H,Z){var W=this;Y===void 0&&(Y=!0),k===void 0&&(k=!0),H===void 0&&(H=!0),Z===void 0&&(Z=null);var q=this._scene;if(Z||(Z=q.getEngine().getInputElement()),Z){this._alreadyAttached&&this.detachControl(),this._alreadyAttachedTo=Z;var he=q.getEngine();this._initActionManager=function(be,Pe){if(!W._meshPickProceed){var ye=q.pick(W._unTranslatedPointerX,W._unTranslatedPointerY,q.pointerDownPredicate,!1,q.cameraToUseForPointers);W._currentPickResult=ye,ye&&(be=ye.hit&&ye.pickedMesh?ye.pickedMesh._getActionManagerForTrigger():null),W._meshPickProceed=!0}return be},this._delayedSimpleClick=function(be,Pe,ye){(Date.now()-W._previousStartingPointerTime>re.DoubleClickDelay&&!W._doubleClickOccured||be!==W._previousButtonPressed)&&(W._doubleClickOccured=!1,Pe.singleClick=!0,Pe.ignore=!1,ye(Pe,W._currentPickResult))},this._initClickEvent=function(be,Pe,ye,Be){var ke=new ae;W._currentPickResult=null;var We=null,je=be.hasSpecificMask(te.a.POINTERPICK)||Pe.hasSpecificMask(te.a.POINTERPICK)||be.hasSpecificMask(te.a.POINTERTAP)||Pe.hasSpecificMask(te.a.POINTERTAP)||be.hasSpecificMask(te.a.POINTERDOUBLETAP)||Pe.hasSpecificMask(te.a.POINTERDOUBLETAP);!je&&de.a&&(We=W._initActionManager(We,ke))&&(je=We.hasPickTriggers);var He=!1;if(je){var qe=ye.button;if(ke.hasSwiped=W._isPointerSwiping(),!ke.hasSwiped){var Ge=!re.ExclusiveDoubleClickMode;Ge||(Ge=!be.hasSpecificMask(te.a.POINTERDOUBLETAP)&&!Pe.hasSpecificMask(te.a.POINTERDOUBLETAP))&&!de.a.HasSpecificTrigger(I.a.ACTION_OnDoublePickTrigger)&&(We=W._initActionManager(We,ke))&&(Ge=!We.hasSpecificTrigger(I.a.ACTION_OnDoublePickTrigger)),Ge?(Date.now()-W._previousStartingPointerTime>re.DoubleClickDelay||qe!==W._previousButtonPressed)&&(ke.singleClick=!0,Be(ke,W._currentPickResult),He=!0):(W._previousDelayedSimpleClickTimeout=W._delayedSimpleClickTimeout,W._delayedSimpleClickTimeout=window.setTimeout(W._delayedSimpleClick.bind(W,qe,ke,Be),re.DoubleClickDelay));var nt=be.hasSpecificMask(te.a.POINTERDOUBLETAP)||Pe.hasSpecificMask(te.a.POINTERDOUBLETAP);!nt&&de.a.HasSpecificTrigger(I.a.ACTION_OnDoublePickTrigger)&&(We=W._initActionManager(We,ke))&&(nt=We.hasSpecificTrigger(I.a.ACTION_OnDoublePickTrigger)),nt&&(qe===W._previousButtonPressed&&Date.now()-W._previousStartingPointerTime<re.DoubleClickDelay&&!W._doubleClickOccured?(ke.hasSwiped||W._isPointerSwiping()?(W._doubleClickOccured=!1,W._previousStartingPointerTime=W._startingPointerTime,W._previousStartingPointerPosition.x=W._startingPointerPosition.x,W._previousStartingPointerPosition.y=W._startingPointerPosition.y,W._previousButtonPressed=qe,re.ExclusiveDoubleClickMode?(W._previousDelayedSimpleClickTimeout&&clearTimeout(W._previousDelayedSimpleClickTimeout),W._previousDelayedSimpleClickTimeout=W._delayedSimpleClickTimeout,Be(ke,W._previousPickResult)):Be(ke,W._currentPickResult)):(W._previousStartingPointerTime=0,W._doubleClickOccured=!0,ke.doubleClick=!0,ke.ignore=!1,re.ExclusiveDoubleClickMode&&W._previousDelayedSimpleClickTimeout&&clearTimeout(W._previousDelayedSimpleClickTimeout),W._previousDelayedSimpleClickTimeout=W._delayedSimpleClickTimeout,Be(ke,W._currentPickResult)),He=!0):(W._doubleClickOccured=!1,W._previousStartingPointerTime=W._startingPointerTime,W._previousStartingPointerPosition.x=W._startingPointerPosition.x,W._previousStartingPointerPosition.y=W._startingPointerPosition.y,W._previousButtonPressed=qe))}}He||Be(ke,W._currentPickResult)},this._onPointerMove=function(be){if(be.pointerId===void 0&&(be.pointerId=0),W._updatePointerPosition(be),!W._checkPrePointerObservable(null,be,be.type===W._wheelEventName?te.a.POINTERWHEEL:te.a.POINTERMOVE)&&(q.cameraToUseForPointers||q.activeCamera)){q.pointerMovePredicate||(q.pointerMovePredicate=function(ye){return ye.isPickable&&ye.isVisible&&ye.isReady()&&ye.isEnabled()&&(ye.enablePointerMoveEvents||q.constantlyUpdateMeshUnderPointer||ye._getActionManagerForTrigger()!=null)&&(!q.cameraToUseForPointers||(q.cameraToUseForPointers.layerMask&ye.layerMask)!=0)});var Pe=q.pick(W._unTranslatedPointerX,W._unTranslatedPointerY,q.pointerMovePredicate,!1,q.cameraToUseForPointers);W._processPointerMove(Pe,be)}},this._onPointerDown=function(be){if(W._totalPointersPressed++,W._pickedDownMesh=null,W._meshPickProceed=!1,be.pointerId===void 0&&(be.pointerId=0),W._updatePointerPosition(be),q.preventDefaultOnPointerDown&&Z&&(be.preventDefault(),Z.focus()),W._startingPointerPosition.x=W._pointerX,W._startingPointerPosition.y=W._pointerY,W._startingPointerTime=Date.now(),!W._checkPrePointerObservable(null,be,te.a.POINTERDOWN)&&(q.cameraToUseForPointers||q.activeCamera)){W._pointerCaptures[be.pointerId]=!0,q.pointerDownPredicate||(q.pointerDownPredicate=function(ye){return ye.isPickable&&ye.isVisible&&ye.isReady()&&ye.isEnabled()&&(!q.cameraToUseForPointers||(q.cameraToUseForPointers.layerMask&ye.layerMask)!=0)}),W._pickedDownMesh=null;var Pe=q.pick(W._unTranslatedPointerX,W._unTranslatedPointerY,q.pointerDownPredicate,!1,q.cameraToUseForPointers);W._processPointerDown(Pe,be)}},this._onPointerUp=function(be){W._totalPointersPressed!==0&&(W._totalPointersPressed--,W._pickedUpMesh=null,W._meshPickProceed=!1,be.pointerId===void 0&&(be.pointerId=0),W._updatePointerPosition(be),q.preventDefaultOnPointerUp&&Z&&(be.preventDefault(),Z.focus()),W._initClickEvent(q.onPrePointerObservable,q.onPointerObservable,be,function(Pe,ye){q.onPrePointerObservable.hasObservers()&&!Pe.ignore&&(!Pe.hasSwiped&&(Pe.singleClick&&q.onPrePointerObservable.hasSpecificMask(te.a.POINTERTAP)&&W._checkPrePointerObservable(null,be,te.a.POINTERTAP)||Pe.doubleClick&&q.onPrePointerObservable.hasSpecificMask(te.a.POINTERDOUBLETAP)&&W._checkPrePointerObservable(null,be,te.a.POINTERDOUBLETAP))||W._checkPrePointerObservable(null,be,te.a.POINTERUP))||W._pointerCaptures[be.pointerId]&&(W._pointerCaptures[be.pointerId]=!1,(q.cameraToUseForPointers||q.activeCamera)&&(q.pointerUpPredicate||(q.pointerUpPredicate=function(Be){return Be.isPickable&&Be.isVisible&&Be.isReady()&&Be.isEnabled()&&(!q.cameraToUseForPointers||(q.cameraToUseForPointers.layerMask&Be.layerMask)!=0)}),!W._meshPickProceed&&(de.a&&de.a.HasTriggers||q.onPointerObservable.hasObservers())&&W._initActionManager(null,Pe),ye||(ye=W._currentPickResult),W._processPointerUp(ye,be,Pe),W._previousPickResult=W._currentPickResult))}))},this._onKeyDown=function(be){var Pe=pe.a.KEYDOWN;if(q.onPreKeyboardObservable.hasObservers()){var ye=new pe.c(Pe,be);if(q.onPreKeyboardObservable.notifyObservers(ye,Pe),ye.skipOnPointerObservable)return}q.onKeyboardObservable.hasObservers()&&(ye=new pe.b(Pe,be),q.onKeyboardObservable.notifyObservers(ye,Pe)),q.actionManager&&q.actionManager.processTrigger(I.a.ACTION_OnKeyDownTrigger,E.a.CreateNewFromScene(q,be))},this._onKeyUp=function(be){var Pe=pe.a.KEYUP;if(q.onPreKeyboardObservable.hasObservers()){var ye=new pe.c(Pe,be);if(q.onPreKeyboardObservable.notifyObservers(ye,Pe),ye.skipOnPointerObservable)return}q.onKeyboardObservable.hasObservers()&&(ye=new pe.b(Pe,be),q.onKeyboardObservable.notifyObservers(ye,Pe)),q.actionManager&&q.actionManager.processTrigger(I.a.ACTION_OnKeyUpTrigger,E.a.CreateNewFromScene(q,be))};var ge=function(){Z&&!W._keyboardIsAttached&&(Z.addEventListener("keydown",W._onKeyDown,!1),Z.addEventListener("keyup",W._onKeyUp,!1),W._keyboardIsAttached=!0)};this._onCanvasFocusObserver=he.onCanvasFocusObservable.add((document.activeElement===Z&&ge(),ge)),this._onCanvasBlurObserver=he.onCanvasBlurObservable.add(function(){Z&&(Z.removeEventListener("keydown",W._onKeyDown),Z.removeEventListener("keyup",W._onKeyUp),W._keyboardIsAttached=!1)}),ge();var me=_.b.GetPointerPrefix(he);if(H&&(Z.addEventListener(me+"move",this._onPointerMove,!1),this._wheelEventName="onwheel"in document.createElement("div")?"wheel":document.onmousewheel!==void 0?"mousewheel":"DOMMouseScroll",Z.addEventListener(this._wheelEventName,this._onPointerMove,!1)),k&&Z.addEventListener(me+"down",this._onPointerDown,!1),Y){var _e=q.getEngine().getHostWindow();_e&&_e.addEventListener(me+"up",this._onPointerUp,!1)}this._alreadyAttached=!0}},re.prototype.detachControl=function(){var Y=this._scene.getEngine(),k=_.b.GetPointerPrefix(Y);this._alreadyAttachedTo&&this._alreadyAttached&&(this._alreadyAttachedTo.removeEventListener(k+"move",this._onPointerMove),this._alreadyAttachedTo.removeEventListener(this._wheelEventName,this._onPointerMove),this._alreadyAttachedTo.removeEventListener(k+"down",this._onPointerDown),window.removeEventListener(k+"up",this._onPointerUp),this._onCanvasBlurObserver&&Y.onCanvasBlurObservable.remove(this._onCanvasBlurObserver),this._onCanvasFocusObserver&&Y.onCanvasFocusObservable.remove(this._onCanvasFocusObserver),this._alreadyAttachedTo.removeEventListener("keydown",this._onKeyDown),this._alreadyAttachedTo.removeEventListener("keyup",this._onKeyUp),this._scene.doNotHandleCursors||(this._alreadyAttachedTo.style.cursor=this._scene.defaultCursor),this._alreadyAttached=!1)},re.prototype.setPointerOverMesh=function(Y,k){if(k===void 0&&(k=0),k<0&&(k=0),this._meshUnderPointerId[k]!==Y){var H,Z=this._meshUnderPointerId[k];Z&&(H=Z._getActionManagerForTrigger(I.a.ACTION_OnPointerOutTrigger))&&H.processTrigger(I.a.ACTION_OnPointerOutTrigger,E.a.CreateNew(Z,void 0,{pointerId:k})),this._meshUnderPointerId[k]=Y,this._pointerOverMesh=Y,(Z=this._meshUnderPointerId[k])&&(H=Z._getActionManagerForTrigger(I.a.ACTION_OnPointerOverTrigger))&&H.processTrigger(I.a.ACTION_OnPointerOverTrigger,E.a.CreateNew(Z,void 0,{pointerId:k}))}},re.prototype.getPointerOverMesh=function(){return this._pointerOverMesh},re.DragMovementThreshold=10,re.LongPressDelay=500,re.DoubleClickDelay=300,re.ExclusiveDoubleClickMode=!1,re}(),K=f(55),$=f(9),L=f(90),G=f(152),Q=f(56),oe=function(re){function Y(k,H){var Z=re.call(this)||this;Z._inputManager=new ee(Z),Z.cameraToUseForPointers=null,Z._isScene=!0,Z._blockEntityCollection=!1,Z.autoClear=!0,Z.autoClearDepthAndStencil=!0,Z.clearColor=new $.b(.2,.2,.3,1),Z.ambientColor=new $.a(0,0,0),Z._environmentIntensity=1,Z._forceWireframe=!1,Z._skipFrustumClipping=!1,Z._forcePointsCloud=!1,Z.animationsEnabled=!0,Z._animationPropertiesOverride=null,Z.useConstantAnimationDeltaTime=!1,Z.constantlyUpdateMeshUnderPointer=!1,Z.hoverCursor="pointer",Z.defaultCursor="",Z.doNotHandleCursors=!1,Z.preventDefaultOnPointerDown=!0,Z.preventDefaultOnPointerUp=!0,Z.metadata=null,Z.reservedDataStore=null,Z.disableOfflineSupportExceptionRules=new Array,Z.onDisposeObservable=new u.c,Z._onDisposeObserver=null,Z.onBeforeRenderObservable=new u.c,Z._onBeforeRenderObserver=null,Z.onAfterRenderObservable=new u.c,Z.onAfterRenderCameraObservable=new u.c,Z._onAfterRenderObserver=null,Z.onBeforeAnimationsObservable=new u.c,Z.onAfterAnimationsObservable=new u.c,Z.onBeforeDrawPhaseObservable=new u.c,Z.onAfterDrawPhaseObservable=new u.c,Z.onReadyObservable=new u.c,Z.onBeforeCameraRenderObservable=new u.c,Z._onBeforeCameraRenderObserver=null,Z.onAfterCameraRenderObservable=new u.c,Z._onAfterCameraRenderObserver=null,Z.onBeforeActiveMeshesEvaluationObservable=new u.c,Z.onAfterActiveMeshesEvaluationObservable=new u.c,Z.onBeforeParticlesRenderingObservable=new u.c,Z.onAfterParticlesRenderingObservable=new u.c,Z.onDataLoadedObservable=new u.c,Z.onNewCameraAddedObservable=new u.c,Z.onCameraRemovedObservable=new u.c,Z.onNewLightAddedObservable=new u.c,Z.onLightRemovedObservable=new u.c,Z.onNewGeometryAddedObservable=new u.c,Z.onGeometryRemovedObservable=new u.c,Z.onNewTransformNodeAddedObservable=new u.c,Z.onTransformNodeRemovedObservable=new u.c,Z.onNewMeshAddedObservable=new u.c,Z.onMeshRemovedObservable=new u.c,Z.onNewSkeletonAddedObservable=new u.c,Z.onSkeletonRemovedObservable=new u.c,Z.onNewMaterialAddedObservable=new u.c,Z.onNewMultiMaterialAddedObservable=new u.c,Z.onMaterialRemovedObservable=new u.c,Z.onMultiMaterialRemovedObservable=new u.c,Z.onNewTextureAddedObservable=new u.c,Z.onTextureRemovedObservable=new u.c,Z.onBeforeRenderTargetsRenderObservable=new u.c,Z.onAfterRenderTargetsRenderObservable=new u.c,Z.onBeforeStepObservable=new u.c,Z.onAfterStepObservable=new u.c,Z.onActiveCameraChanged=new u.c,Z.onBeforeRenderingGroupObservable=new u.c,Z.onAfterRenderingGroupObservable=new u.c,Z.onMeshImportedObservable=new u.c,Z.onAnimationFileImportedObservable=new u.c,Z._registeredForLateAnimationBindings=new M.b(256),Z.onPrePointerObservable=new u.c,Z.onPointerObservable=new u.c,Z.onPreKeyboardObservable=new u.c,Z.onKeyboardObservable=new u.c,Z._useRightHandedSystem=!1,Z._timeAccumulator=0,Z._currentStepId=0,Z._currentInternalStep=0,Z._fogEnabled=!0,Z._fogMode=Y.FOGMODE_NONE,Z.fogColor=new $.a(.2,.2,.3),Z.fogDensity=.1,Z.fogStart=0,Z.fogEnd=1e3,Z.prePass=!1,Z._shadowsEnabled=!0,Z._lightsEnabled=!0,Z.activeCameras=new Array,Z._texturesEnabled=!0,Z.physicsEnabled=!0,Z.particlesEnabled=!0,Z.spritesEnabled=!0,Z._skeletonsEnabled=!0,Z.lensFlaresEnabled=!0,Z.collisionsEnabled=!0,Z.gravity=new 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Array,Z._transformMatrix=m.a.Zero(),Z.requireLightSorting=!1,Z._components=[],Z._serializableComponents=[],Z._transientComponents=[],Z._beforeCameraUpdateStage=N.b.Create(),Z._beforeClearStage=N.b.Create(),Z._gatherRenderTargetsStage=N.b.Create(),Z._gatherActiveCameraRenderTargetsStage=N.b.Create(),Z._isReadyForMeshStage=N.b.Create(),Z._beforeEvaluateActiveMeshStage=N.b.Create(),Z._evaluateSubMeshStage=N.b.Create(),Z._preActiveMeshStage=N.b.Create(),Z._cameraDrawRenderTargetStage=N.b.Create(),Z._beforeCameraDrawStage=N.b.Create(),Z._beforeRenderTargetDrawStage=N.b.Create(),Z._beforeRenderingGroupDrawStage=N.b.Create(),Z._beforeRenderingMeshStage=N.b.Create(),Z._afterRenderingMeshStage=N.b.Create(),Z._afterRenderingGroupDrawStage=N.b.Create(),Z._afterCameraDrawStage=N.b.Create(),Z._afterRenderTargetDrawStage=N.b.Create(),Z._afterRenderStage=N.b.Create(),Z._pointerMoveStage=N.b.Create(),Z._pointerDownStage=N.b.Create(),Z._pointerUpStage=N.b.Create(),Z.geometriesByUniqueId=null,Z._defaultMeshCandidates={data:[],length:0},Z._defaultSubMeshCandidates={data:[],length:0},Z._preventFreeActiveMeshesAndRenderingGroups=!1,Z._activeMeshesFrozen=!1,Z._skipEvaluateActiveMeshesCompletely=!1,Z._allowPostProcessClearColor=!0,Z.getDeterministicFrameTime=function(){return Z._engine.getTimeStep()},Z._blockMaterialDirtyMechanism=!1;var W=Object(U.a)({useGeometryUniqueIdsMap:!0,useMaterialMeshMap:!0,useClonedMeshMap:!0,virtual:!1},H);return Z._engine=k||j.a.LastCreatedEngine,W.virtual||(j.a._LastCreatedScene=Z,Z._engine.scenes.push(Z)),Z._uid=null,Z._renderingManager=new w.b(Z),D.a&&(Z.postProcessManager=new D.a(Z)),V.a.IsWindowObjectExist()&&Z.attachControl(),Z._createUbo(),g.a&&(Z._imageProcessingConfiguration=new g.a),Z.setDefaultCandidateProviders(),W.useGeometryUniqueIdsMap&&(Z.geometriesByUniqueId={}),Z.useMaterialMeshMap=W.useMaterialMeshMap,Z.useClonedMeshMap=W.useClonedMeshMap,H&&H.virtual||Z._engine.onNewSceneAddedObservable.notifyObservers(Z),Z}return Object(U.d)(Y,re),Y.DefaultMaterialFactory=function(k){throw ne.a.WarnImport("StandardMaterial")},Y.CollisionCoordinatorFactory=function(){throw ne.a.WarnImport("DefaultCollisionCoordinator")},Object.defineProperty(Y.prototype,"environmentTexture",{get:function(){return 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this._skipFrustumClipping},set:function(k){this._skipFrustumClipping!==k&&(this._skipFrustumClipping=k)},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"forcePointsCloud",{get:function(){return this._forcePointsCloud},set:function(k){this._forcePointsCloud!==k&&(this._forcePointsCloud=k,this.markAllMaterialsAsDirty(I.a.MATERIAL_MiscDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"animationPropertiesOverride",{get:function(){return this._animationPropertiesOverride},set:function(k){this._animationPropertiesOverride=k},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"onDispose",{set:function(k){this._onDisposeObserver&&this.onDisposeObservable.remove(this._onDisposeObserver),this._onDisposeObserver=this.onDisposeObservable.add(k)},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"beforeRender",{set:function(k){this._onBeforeRenderObserver&&this.onBeforeRenderObservable.remove(this._onBeforeRenderObserver),k&&(this._onBeforeRenderObserver=this.onBeforeRenderObservable.add(k))},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"afterRender",{set:function(k){this._onAfterRenderObserver&&this.onAfterRenderObservable.remove(this._onAfterRenderObserver),k&&(this._onAfterRenderObserver=this.onAfterRenderObservable.add(k))},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"beforeCameraRender",{set:function(k){this._onBeforeCameraRenderObserver&&this.onBeforeCameraRenderObservable.remove(this._onBeforeCameraRenderObserver),this._onBeforeCameraRenderObserver=this.onBeforeCameraRenderObservable.add(k)},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"afterCameraRender",{set:function(k){this._onAfterCameraRenderObserver&&this.onAfterCameraRenderObservable.remove(this._onAfterCameraRenderObserver),this._onAfterCameraRenderObserver=this.onAfterCameraRenderObservable.add(k)},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"unTranslatedPointer",{get:function(){return this._inputManager.unTranslatedPointer},enumerable:!1,configurable:!0}),Object.defineProperty(Y,"DragMovementThreshold",{get:function(){return ee.DragMovementThreshold},set:function(k){ee.DragMovementThreshold=k},enumerable:!1,configurable:!0}),Object.defineProperty(Y,"LongPressDelay",{get:function(){return ee.LongPressDelay},set:function(k){ee.LongPressDelay=k},enumerable:!1,configurable:!0}),Object.defineProperty(Y,"DoubleClickDelay",{get:function(){return ee.DoubleClickDelay},set:function(k){ee.DoubleClickDelay=k},enumerable:!1,configurable:!0}),Object.defineProperty(Y,"ExclusiveDoubleClickMode",{get:function(){return ee.ExclusiveDoubleClickMode},set:function(k){ee.ExclusiveDoubleClickMode=k},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"useRightHandedSystem",{get:function(){return this._useRightHandedSystem},set:function(k){this._useRightHandedSystem!==k&&(this._useRightHandedSystem=k,this.markAllMaterialsAsDirty(I.a.MATERIAL_MiscDirtyFlag))},enumerable:!1,configurable:!0}),Y.prototype.setStepId=function(k){this._currentStepId=k},Y.prototype.getStepId=function(){return this._currentStepId},Y.prototype.getInternalStep=function(){return this._currentInternalStep},Object.defineProperty(Y.prototype,"fogEnabled",{get:function(){return this._fogEnabled},set:function(k){this._fogEnabled!==k&&(this._fogEnabled=k,this.markAllMaterialsAsDirty(I.a.MATERIAL_MiscDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"fogMode",{get:function(){return this._fogMode},set:function(k){this._fogMode!==k&&(this._fogMode=k,this.markAllMaterialsAsDirty(I.a.MATERIAL_MiscDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"shadowsEnabled",{get:function(){return this._shadowsEnabled},set:function(k){this._shadowsEnabled!==k&&(this._shadowsEnabled=k,this.markAllMaterialsAsDirty(I.a.MATERIAL_LightDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"lightsEnabled",{get:function(){return this._lightsEnabled},set:function(k){this._lightsEnabled!==k&&(this._lightsEnabled=k,this.markAllMaterialsAsDirty(I.a.MATERIAL_LightDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"activeCamera",{get:function(){return this._activeCamera},set:function(k){k!==this._activeCamera&&(this._activeCamera=k,this.onActiveCameraChanged.notifyObservers(this))},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"defaultMaterial",{get:function(){return this._defaultMaterial||(this._defaultMaterial=Y.DefaultMaterialFactory(this)),this._defaultMaterial},set:function(k){this._defaultMaterial=k},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"texturesEnabled",{get:function(){return this._texturesEnabled},set:function(k){this._texturesEnabled!==k&&(this._texturesEnabled=k,this.markAllMaterialsAsDirty(I.a.MATERIAL_TextureDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"skeletonsEnabled",{get:function(){return this._skeletonsEnabled},set:function(k){this._skeletonsEnabled!==k&&(this._skeletonsEnabled=k,this.markAllMaterialsAsDirty(I.a.MATERIAL_AttributesDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"collisionCoordinator",{get:function(){return this._collisionCoordinator||(this._collisionCoordinator=Y.CollisionCoordinatorFactory(),this._collisionCoordinator.init(this)),this._collisionCoordinator},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"frustumPlanes",{get:function(){return this._frustumPlanes},enumerable:!1,configurable:!0}),Y.prototype._registerTransientComponents=function(){if(this._transientComponents.length>0){for(var k=0,H=this._transientComponents;k<H.length;k++)H[k].register();this._transientComponents=[]}},Y.prototype._addComponent=function(k){this._components.push(k),this._transientComponents.push(k);var H=k;H.addFromContainer&&H.serialize&&this._serializableComponents.push(H)},Y.prototype._getComponent=function(k){for(var H=0,Z=this._components;H<Z.length;H++){var W=Z[H];if(W.name===k)return W}return null},Y.prototype.getClassName=function(){return"Scene"},Y.prototype._getDefaultMeshCandidates=function(){return this._defaultMeshCandidates.data=this.meshes,this._defaultMeshCandidates.length=this.meshes.length,this._defaultMeshCandidates},Y.prototype._getDefaultSubMeshCandidates=function(k){return this._defaultSubMeshCandidates.data=k.subMeshes,this._defaultSubMeshCandidates.length=k.subMeshes.length,this._defaultSubMeshCandidates},Y.prototype.setDefaultCandidateProviders=function(){this.getActiveMeshCandidates=this._getDefaultMeshCandidates.bind(this),this.getActiveSubMeshCandidates=this._getDefaultSubMeshCandidates.bind(this),this.getIntersectingSubMeshCandidates=this._getDefaultSubMeshCandidates.bind(this),this.getCollidingSubMeshCandidates=this._getDefaultSubMeshCandidates.bind(this)},Object.defineProperty(Y.prototype,"meshUnderPointer",{get:function(){return this._inputManager.meshUnderPointer},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"pointerX",{get:function(){return this._inputManager.pointerX},set:function(k){this._inputManager.pointerX=k},enumerable:!1,configurable:!0}),Object.defineProperty(Y.prototype,"pointerY",{get:function(){return this._inputManager.pointerY},set:function(k){this._inputManager.pointerY=k},enumerable:!1,configurable:!0}),Y.prototype.getCachedMaterial=function(){return this._cachedMaterial},Y.prototype.getCachedEffect=function(){return this._cachedEffect},Y.prototype.getCachedVisibility=function(){return this._cachedVisibility},Y.prototype.isCachedMaterialInvalid=function(k,H,Z){return Z===void 0&&(Z=1),this._cachedEffect!==H||this._cachedMaterial!==k||this._cachedVisibility!==Z},Y.prototype.getEngine=function(){return this._engine},Y.prototype.getTotalVertices=function(){return this._totalVertices.current},Object.defineProperty(Y.prototype,"totalVerticesPerfCounter",{get:function(){return this._totalVertices},enumerable:!1,configurable:!0}),Y.prototype.getActiveIndices=function(){return this._activeIndices.current},Object.defineProperty(Y.prototype,"totalActiveIndicesPerfCounter",{get:function(){return this._activeIndices},enumerable:!1,configurable:!0}),Y.prototype.getActiveParticles=function(){return this._activeParticles.current},Object.defineProperty(Y.prototype,"activeParticlesPerfCounter",{get:function(){return this._activeParticles},enumerable:!1,configurable:!0}),Y.prototype.getActiveBones=function(){return this._activeBones.current},Object.defineProperty(Y.prototype,"activeBonesPerfCounter",{get:function(){return this._activeBones},enumerable:!1,configurable:!0}),Y.prototype.getActiveMeshes=function(){return this._activeMeshes},Y.prototype.getAnimationRatio=function(){return this._animationRatio!==void 0?this._animationRatio:1},Y.prototype.getRenderId=function(){return this._renderId},Y.prototype.getFrameId=function(){return this._frameId},Y.prototype.incrementRenderId=function(){this._renderId++},Y.prototype._createUbo=function(){this._sceneUbo=new l.a(this._engine,void 0,!0),this._sceneUbo.addUniform("viewProjection",16),this._sceneUbo.addUniform("view",16)},Y.prototype.simulatePointerMove=function(k,H){return this._inputManager.simulatePointerMove(k,H),this},Y.prototype.simulatePointerDown=function(k,H){return this._inputManager.simulatePointerDown(k,H),this},Y.prototype.simulatePointerUp=function(k,H,Z){return this._inputManager.simulatePointerUp(k,H,Z),this},Y.prototype.isPointerCaptured=function(k){return k===void 0&&(k=0),this._inputManager.isPointerCaptured(k)},Y.prototype.attachControl=function(k,H,Z){k===void 0&&(k=!0),H===void 0&&(H=!0),Z===void 0&&(Z=!0),this._inputManager.attachControl(k,H,Z)},Y.prototype.detachControl=function(){this._inputManager.detachControl()},Y.prototype.isReady=function(){if(this._isDisposed)return!1;var k,H=this.getEngine();if(!H.areAllEffectsReady()||this._pendingData.length>0)return!1;for(k=0;k<this.meshes.length;k++){var Z=this.meshes[k];if(Z.isEnabled()&&Z.subMeshes&&Z.subMeshes.length!==0){if(!Z.isReady(!0))return!1;for(var W=Z.hasThinInstances||Z.getClassName()==="InstancedMesh"||Z.getClassName()==="InstancedLinesMesh"||H.getCaps().instancedArrays&&Z.instances.length>0,q=0,he=this._isReadyForMeshStage;q<he.length;q++)if(!he[q].action(Z,W))return!1}}for(k=0;k<this.geometries.length;k++)if(this.geometries[k].delayLoadState===I.a.DELAYLOADSTATE_LOADING)return!1;if(this.activeCameras&&this.activeCameras.length>0){for(var ge=0,me=this.activeCameras;ge<me.length;ge++)if(!me[ge].isReady(!0))return!1}else if(this.activeCamera&&!this.activeCamera.isReady(!0))return!1;for(var _e=0,be=this.particleSystems;_e<be.length;_e++)if(!be[_e].isReady())return!1;return!0},Y.prototype.resetCachedMaterial=function(){this._cachedMaterial=null,this._cachedEffect=null,this._cachedVisibility=null},Y.prototype.registerBeforeRender=function(k){this.onBeforeRenderObservable.add(k)},Y.prototype.unregisterBeforeRender=function(k){this.onBeforeRenderObservable.removeCallback(k)},Y.prototype.registerAfterRender=function(k){this.onAfterRenderObservable.add(k)},Y.prototype.unregisterAfterRender=function(k){this.onAfterRenderObservable.removeCallback(k)},Y.prototype._executeOnceBeforeRender=function(k){var H=this,Z=function(){k(),setTimeout(function(){H.unregisterBeforeRender(Z)})};this.registerBeforeRender(Z)},Y.prototype.executeOnceBeforeRender=function(k,H){var Z=this;H!==void 0?setTimeout(function(){Z._executeOnceBeforeRender(k)},H):this._executeOnceBeforeRender(k)},Y.prototype._addPendingData=function(k){this._pendingData.push(k)},Y.prototype._removePendingData=function(k){var H=this.isLoading,Z=this._pendingData.indexOf(k);Z!==-1&&this._pendingData.splice(Z,1),H&&!this.isLoading&&this.onDataLoadedObservable.notifyObservers(this)},Y.prototype.getWaitingItemsCount=function(){return this._pendingData.length},Object.defineProperty(Y.prototype,"isLoading",{get:function(){return this._pendingData.length>0},enumerable:!1,configurable:!0}),Y.prototype.executeWhenReady=function(k){var H=this;this.onReadyObservable.add(k),this._executeWhenReadyTimeoutId===-1&&(this._executeWhenReadyTimeoutId=setTimeout(function(){H._checkIsReady()},150))},Y.prototype.whenReadyAsync=function(){var k=this;return new Promise(function(H){k.executeWhenReady(function(){H()})})},Y.prototype._checkIsReady=function(){var k=this;return this._registerTransientComponents(),this.isReady()?(this.onReadyObservable.notifyObservers(this),this.onReadyObservable.clear(),void(this._executeWhenReadyTimeoutId=-1)):this._isDisposed?(this.onReadyObservable.clear(),void(this._executeWhenReadyTimeoutId=-1)):void(this._executeWhenReadyTimeoutId=setTimeout(function(){k._checkIsReady()},150))},Object.defineProperty(Y.prototype,"animatables",{get:function(){return this._activeAnimatables},enumerable:!1,configurable:!0}),Y.prototype.resetLastAnimationTimeFrame=function(){this._animationTimeLast=C.a.Now},Y.prototype.getViewMatrix=function(){return this._viewMatrix},Y.prototype.getProjectionMatrix=function(){return this._projectionMatrix},Y.prototype.getTransformMatrix=function(){return this._transformMatrix},Y.prototype.setTransformMatrix=function(k,H,Z,W){this._viewUpdateFlag===k.updateFlag&&this._projectionUpdateFlag===H.updateFlag||(this._viewUpdateFlag=k.updateFlag,this._projectionUpdateFlag=H.updateFlag,this._viewMatrix=k,this._projectionMatrix=H,this._viewMatrix.multiplyToRef(this._projectionMatrix,this._transformMatrix),this._frustumPlanes?L.a.GetPlanesToRef(this._transformMatrix,this._frustumPlanes):this._frustumPlanes=L.a.GetPlanes(this._transformMatrix),this._multiviewSceneUbo&&this._multiviewSceneUbo.useUbo?this._updateMultiviewUbo(Z,W):this._sceneUbo.useUbo&&(this._sceneUbo.updateMatrix("viewProjection",this._transformMatrix),this._sceneUbo.updateMatrix("view",this._viewMatrix),this._sceneUbo.update()))},Y.prototype.getSceneUniformBuffer=function(){return this._multiviewSceneUbo?this._multiviewSceneUbo:this._sceneUbo},Y.prototype.getUniqueId=function(){return G.a.UniqueId},Y.prototype.addMesh=function(k,H){var Z=this;H===void 0&&(H=!1),this._blockEntityCollection||(this.meshes.push(k),k._resyncLightSources(),k.parent||k._addToSceneRootNodes(),this.onNewMeshAddedObservable.notifyObservers(k),H&&k.getChildMeshes().forEach(function(W){Z.addMesh(W)}))},Y.prototype.removeMesh=function(k,H){var Z=this;H===void 0&&(H=!1);var W=this.meshes.indexOf(k);return W!==-1&&(this.meshes[W]=this.meshes[this.meshes.length-1],this.meshes.pop(),k.parent||k._removeFromSceneRootNodes()),this.onMeshRemovedObservable.notifyObservers(k),H&&k.getChildMeshes().forEach(function(q){Z.removeMesh(q)}),W},Y.prototype.addTransformNode=function(k){this._blockEntityCollection||(k._indexInSceneTransformNodesArray=this.transformNodes.length,this.transformNodes.push(k),k.parent||k._addToSceneRootNodes(),this.onNewTransformNodeAddedObservable.notifyObservers(k))},Y.prototype.removeTransformNode=function(k){var H=k._indexInSceneTransformNodesArray;if(H!==-1){if(H!==this.transformNodes.length-1){var Z=this.transformNodes[this.transformNodes.length-1];this.transformNodes[H]=Z,Z._indexInSceneTransformNodesArray=H}k._indexInSceneTransformNodesArray=-1,this.transformNodes.pop(),k.parent||k._removeFromSceneRootNodes()}return this.onTransformNodeRemovedObservable.notifyObservers(k),H},Y.prototype.removeSkeleton=function(k){var H=this.skeletons.indexOf(k);return H!==-1&&(this.skeletons.splice(H,1),this.onSkeletonRemovedObservable.notifyObservers(k)),H},Y.prototype.removeMorphTargetManager=function(k){var H=this.morphTargetManagers.indexOf(k);return H!==-1&&this.morphTargetManagers.splice(H,1),H},Y.prototype.removeLight=function(k){var H=this.lights.indexOf(k);if(H!==-1){for(var Z=0,W=this.meshes;Z<W.length;Z++)W[Z]._removeLightSource(k,!1);this.lights.splice(H,1),this.sortLightsByPriority(),k.parent||k._removeFromSceneRootNodes()}return this.onLightRemovedObservable.notifyObservers(k),H},Y.prototype.removeCamera=function(k){var H=this.cameras.indexOf(k);if(H!==-1&&(this.cameras.splice(H,1),k.parent||k._removeFromSceneRootNodes()),this.activeCameras){var Z=this.activeCameras.indexOf(k);Z!==-1&&this.activeCameras.splice(Z,1)}return this.activeCamera===k&&(this.cameras.length>0?this.activeCamera=this.cameras[0]:this.activeCamera=null),this.onCameraRemovedObservable.notifyObservers(k),H},Y.prototype.removeParticleSystem=function(k){var H=this.particleSystems.indexOf(k);return H!==-1&&this.particleSystems.splice(H,1),H},Y.prototype.removeAnimation=function(k){var H=this.animations.indexOf(k);return H!==-1&&this.animations.splice(H,1),H},Y.prototype.stopAnimation=function(k,H,Z){},Y.prototype.removeAnimationGroup=function(k){var H=this.animationGroups.indexOf(k);return H!==-1&&this.animationGroups.splice(H,1),H},Y.prototype.removeMultiMaterial=function(k){var H=this.multiMaterials.indexOf(k);return H!==-1&&this.multiMaterials.splice(H,1),this.onMultiMaterialRemovedObservable.notifyObservers(k),H},Y.prototype.removeMaterial=function(k){var H=k._indexInSceneMaterialArray;if(H!==-1&&H<this.materials.length){if(H!==this.materials.length-1){var Z=this.materials[this.materials.length-1];this.materials[H]=Z,Z._indexInSceneMaterialArray=H}k._indexInSceneMaterialArray=-1,this.materials.pop()}return this.onMaterialRemovedObservable.notifyObservers(k),H},Y.prototype.removeActionManager=function(k){var H=this.actionManagers.indexOf(k);return H!==-1&&this.actionManagers.splice(H,1),H},Y.prototype.removeTexture=function(k){var H=this.textures.indexOf(k);return H!==-1&&this.textures.splice(H,1),this.onTextureRemovedObservable.notifyObservers(k),H},Y.prototype.addLight=function(k){if(!this._blockEntityCollection){this.lights.push(k),this.sortLightsByPriority(),k.parent||k._addToSceneRootNodes();for(var H=0,Z=this.meshes;H<Z.length;H++){var W=Z[H];W.lightSources.indexOf(k)===-1&&(W.lightSources.push(k),W._resyncLightSources())}this.onNewLightAddedObservable.notifyObservers(k)}},Y.prototype.sortLightsByPriority=function(){this.requireLightSorting&&this.lights.sort(h.a.CompareLightsPriority)},Y.prototype.addCamera=function(k){this._blockEntityCollection||(this.cameras.push(k),this.onNewCameraAddedObservable.notifyObservers(k),k.parent||k._addToSceneRootNodes())},Y.prototype.addSkeleton=function(k){this._blockEntityCollection||(this.skeletons.push(k),this.onNewSkeletonAddedObservable.notifyObservers(k))},Y.prototype.addParticleSystem=function(k){this._blockEntityCollection||this.particleSystems.push(k)},Y.prototype.addAnimation=function(k){this._blockEntityCollection||this.animations.push(k)},Y.prototype.addAnimationGroup=function(k){this._blockEntityCollection||this.animationGroups.push(k)},Y.prototype.addMultiMaterial=function(k){this._blockEntityCollection||(this.multiMaterials.push(k),this.onNewMultiMaterialAddedObservable.notifyObservers(k))},Y.prototype.addMaterial=function(k){this._blockEntityCollection||(k._indexInSceneMaterialArray=this.materials.length,this.materials.push(k),this.onNewMaterialAddedObservable.notifyObservers(k))},Y.prototype.addMorphTargetManager=function(k){this._blockEntityCollection||this.morphTargetManagers.push(k)},Y.prototype.addGeometry=function(k){this._blockEntityCollection||(this.geometriesByUniqueId&&(this.geometriesByUniqueId[k.uniqueId]=this.geometries.length),this.geometries.push(k))},Y.prototype.addActionManager=function(k){this.actionManagers.push(k)},Y.prototype.addTexture=function(k){this._blockEntityCollection||(this.textures.push(k),this.onNewTextureAddedObservable.notifyObservers(k))},Y.prototype.switchActiveCamera=function(k,H){H===void 0&&(H=!0),this._engine.getInputElement()&&(this.activeCamera&&this.activeCamera.detachControl(),this.activeCamera=k,H&&k.attachControl())},Y.prototype.setActiveCameraByID=function(k){var H=this.getCameraByID(k);return H?(this.activeCamera=H,H):null},Y.prototype.setActiveCameraByName=function(k){var H=this.getCameraByName(k);return H?(this.activeCamera=H,H):null},Y.prototype.getAnimationGroupByName=function(k){for(var H=0;H<this.animationGroups.length;H++)if(this.animationGroups[H].name===k)return this.animationGroups[H];return null},Y.prototype.getMaterialByUniqueID=function(k){for(var H=0;H<this.materials.length;H++)if(this.materials[H].uniqueId===k)return this.materials[H];return null},Y.prototype.getMaterialByID=function(k){for(var H=0;H<this.materials.length;H++)if(this.materials[H].id===k)return this.materials[H];return null},Y.prototype.getLastMaterialByID=function(k){for(var H=this.materials.length-1;H>=0;H--)if(this.materials[H].id===k)return this.materials[H];return null},Y.prototype.getMaterialByName=function(k){for(var H=0;H<this.materials.length;H++)if(this.materials[H].name===k)return this.materials[H];return null},Y.prototype.getTextureByUniqueID=function(k){for(var H=0;H<this.textures.length;H++)if(this.textures[H].uniqueId===k)return this.textures[H];return null},Y.prototype.getCameraByID=function(k){for(var H=0;H<this.cameras.length;H++)if(this.cameras[H].id===k)return this.cameras[H];return null},Y.prototype.getCameraByUniqueID=function(k){for(var H=0;H<this.cameras.length;H++)if(this.cameras[H].uniqueId===k)return this.cameras[H];return null},Y.prototype.getCameraByName=function(k){for(var H=0;H<this.cameras.length;H++)if(this.cameras[H].name===k)return this.cameras[H];return null},Y.prototype.getBoneByID=function(k){for(var H=0;H<this.skeletons.length;H++)for(var Z=this.skeletons[H],W=0;W<Z.bones.length;W++)if(Z.bones[W].id===k)return Z.bones[W];return null},Y.prototype.getBoneByName=function(k){for(var H=0;H<this.skeletons.length;H++)for(var Z=this.skeletons[H],W=0;W<Z.bones.length;W++)if(Z.bones[W].name===k)return Z.bones[W];return null},Y.prototype.getLightByName=function(k){for(var H=0;H<this.lights.length;H++)if(this.lights[H].name===k)return this.lights[H];return null},Y.prototype.getLightByID=function(k){for(var H=0;H<this.lights.length;H++)if(this.lights[H].id===k)return this.lights[H];return null},Y.prototype.getLightByUniqueID=function(k){for(var H=0;H<this.lights.length;H++)if(this.lights[H].uniqueId===k)return this.lights[H];return null},Y.prototype.getParticleSystemByID=function(k){for(var H=0;H<this.particleSystems.length;H++)if(this.particleSystems[H].id===k)return this.particleSystems[H];return null},Y.prototype.getGeometryByID=function(k){for(var H=0;H<this.geometries.length;H++)if(this.geometries[H].id===k)return this.geometries[H];return null},Y.prototype._getGeometryByUniqueID=function(k){if(this.geometriesByUniqueId){var H=this.geometriesByUniqueId[k];if(H!==void 0)return this.geometries[H]}else for(var Z=0;Z<this.geometries.length;Z++)if(this.geometries[Z].uniqueId===k)return this.geometries[Z];return null},Y.prototype.pushGeometry=function(k,H){return!(!H&&this._getGeometryByUniqueID(k.uniqueId))&&(this.addGeometry(k),this.onNewGeometryAddedObservable.notifyObservers(k),!0)},Y.prototype.removeGeometry=function(k){var H;if(this.geometriesByUniqueId){if((H=this.geometriesByUniqueId[k.uniqueId])===void 0)return!1}else if((H=this.geometries.indexOf(k))<0)return!1;if(H!==this.geometries.length-1){var Z=this.geometries[this.geometries.length-1];Z&&(this.geometries[H]=Z,this.geometriesByUniqueId&&(this.geometriesByUniqueId[Z.uniqueId]=H,this.geometriesByUniqueId[k.uniqueId]=void 0))}return this.geometries.pop(),this.onGeometryRemovedObservable.notifyObservers(k),!0},Y.prototype.getGeometries=function(){return this.geometries},Y.prototype.getMeshByID=function(k){for(var H=0;H<this.meshes.length;H++)if(this.meshes[H].id===k)return this.meshes[H];return null},Y.prototype.getMeshesByID=function(k){return this.meshes.filter(function(H){return H.id===k})},Y.prototype.getTransformNodeByID=function(k){for(var H=0;H<this.transformNodes.length;H++)if(this.transformNodes[H].id===k)return this.transformNodes[H];return null},Y.prototype.getTransformNodeByUniqueID=function(k){for(var H=0;H<this.transformNodes.length;H++)if(this.transformNodes[H].uniqueId===k)return this.transformNodes[H];return null},Y.prototype.getTransformNodesByID=function(k){return this.transformNodes.filter(function(H){return H.id===k})},Y.prototype.getMeshByUniqueID=function(k){for(var H=0;H<this.meshes.length;H++)if(this.meshes[H].uniqueId===k)return this.meshes[H];return null},Y.prototype.getLastMeshByID=function(k){for(var H=this.meshes.length-1;H>=0;H--)if(this.meshes[H].id===k)return this.meshes[H];return null},Y.prototype.getLastEntryByID=function(k){var H;for(H=this.meshes.length-1;H>=0;H--)if(this.meshes[H].id===k)return this.meshes[H];for(H=this.transformNodes.length-1;H>=0;H--)if(this.transformNodes[H].id===k)return this.transformNodes[H];for(H=this.cameras.length-1;H>=0;H--)if(this.cameras[H].id===k)return this.cameras[H];for(H=this.lights.length-1;H>=0;H--)if(this.lights[H].id===k)return this.lights[H];return null},Y.prototype.getNodeByID=function(k){var H=this.getMeshByID(k);if(H)return H;var Z=this.getTransformNodeByID(k);if(Z)return Z;var W=this.getLightByID(k);if(W)return W;var q=this.getCameraByID(k);if(q)return q;var he=this.getBoneByID(k);return he||null},Y.prototype.getNodeByName=function(k){var H=this.getMeshByName(k);if(H)return H;var Z=this.getTransformNodeByName(k);if(Z)return Z;var W=this.getLightByName(k);if(W)return W;var q=this.getCameraByName(k);if(q)return q;var he=this.getBoneByName(k);return he||null},Y.prototype.getMeshByName=function(k){for(var H=0;H<this.meshes.length;H++)if(this.meshes[H].name===k)return this.meshes[H];return null},Y.prototype.getTransformNodeByName=function(k){for(var H=0;H<this.transformNodes.length;H++)if(this.transformNodes[H].name===k)return this.transformNodes[H];return null},Y.prototype.getLastSkeletonByID=function(k){for(var H=this.skeletons.length-1;H>=0;H--)if(this.skeletons[H].id===k)return this.skeletons[H];return null},Y.prototype.getSkeletonByUniqueId=function(k){for(var H=0;H<this.skeletons.length;H++)if(this.skeletons[H].uniqueId===k)return this.skeletons[H];return null},Y.prototype.getSkeletonById=function(k){for(var H=0;H<this.skeletons.length;H++)if(this.skeletons[H].id===k)return this.skeletons[H];return null},Y.prototype.getSkeletonByName=function(k){for(var H=0;H<this.skeletons.length;H++)if(this.skeletons[H].name===k)return this.skeletons[H];return null},Y.prototype.getMorphTargetManagerById=function(k){for(var H=0;H<this.morphTargetManagers.length;H++)if(this.morphTargetManagers[H].uniqueId===k)return this.morphTargetManagers[H];return null},Y.prototype.getMorphTargetById=function(k){for(var H=0;H<this.morphTargetManagers.length;++H)for(var Z=this.morphTargetManagers[H],W=0;W<Z.numTargets;++W){var q=Z.getTarget(W);if(q.id===k)return q}return null},Y.prototype.getMorphTargetByName=function(k){for(var H=0;H<this.morphTargetManagers.length;++H)for(var Z=this.morphTargetManagers[H],W=0;W<Z.numTargets;++W){var q=Z.getTarget(W);if(q.name===k)return q}return null},Y.prototype.getPostProcessByName=function(k){for(var H=0;H<this.postProcesses.length;++H){var Z=this.postProcesses[H];if(Z.name===k)return Z}return null},Y.prototype.isActiveMesh=function(k){return this._activeMeshes.indexOf(k)!==-1},Object.defineProperty(Y.prototype,"uid",{get:function(){return this._uid||(this._uid=_.b.RandomId()),this._uid},enumerable:!1,configurable:!0}),Y.prototype.addExternalData=function(k,H){return this._externalData||(this._externalData=new R.a),this._externalData.add(k,H)},Y.prototype.getExternalData=function(k){return this._externalData?this._externalData.get(k):null},Y.prototype.getOrAddExternalDataWithFactory=function(k,H){return this._externalData||(this._externalData=new R.a),this._externalData.getOrAddWithFactory(k,H)},Y.prototype.removeExternalData=function(k){return this._externalData.remove(k)},Y.prototype._evaluateSubMesh=function(k,H,Z){if(Z.hasInstances||Z.isAnInstance||this.dispatchAllSubMeshesOfActiveMeshes||this._skipFrustumClipping||H.alwaysSelectAsActiveMesh||H.subMeshes.length===1||k.isInFrustum(this._frustumPlanes)){for(var W=0,q=this._evaluateSubMeshStage;W<q.length;W++)q[W].action(H,k);var he=k.getMaterial();he!=null&&(he.hasRenderTargetTextures&&he.getRenderTargetTextures!=null&&this._processedMaterials.indexOf(he)===-1&&(this._processedMaterials.push(he),this._renderTargets.concatWithNoDuplicate(he.getRenderTargetTextures())),this._renderingManager.dispatch(k,H,he))}},Y.prototype.freeProcessedMaterials=function(){this._processedMaterials.dispose()},Object.defineProperty(Y.prototype,"blockfreeActiveMeshesAndRenderingGroups",{get:function(){return this._preventFreeActiveMeshesAndRenderingGroups},set:function(k){this._preventFreeActiveMeshesAndRenderingGroups!==k&&(k&&(this.freeActiveMeshes(),this.freeRenderingGroups()),this._preventFreeActiveMeshesAndRenderingGroups=k)},enumerable:!1,configurable:!0}),Y.prototype.freeActiveMeshes=function(){if(!this.blockfreeActiveMeshesAndRenderingGroups&&(this._activeMeshes.dispose(),this.activeCamera&&this.activeCamera._activeMeshes&&this.activeCamera._activeMeshes.dispose(),this.activeCameras))for(var k=0;k<this.activeCameras.length;k++){var H=this.activeCameras[k];H&&H._activeMeshes&&H._activeMeshes.dispose()}},Y.prototype.freeRenderingGroups=function(){if(!this.blockfreeActiveMeshesAndRenderingGroups&&(this._renderingManager&&this._renderingManager.freeRenderingGroups(),this.textures))for(var k=0;k<this.textures.length;k++){var H=this.textures[k];H&&H.renderList&&H.freeRenderingGroups()}},Y.prototype._isInIntermediateRendering=function(){return this._intermediateRendering},Y.prototype.freezeActiveMeshes=function(k,H,Z){var W=this;return k===void 0&&(k=!1),this.executeWhenReady(function(){if(W.activeCamera){W._frustumPlanes||W.setTransformMatrix(W.activeCamera.getViewMatrix(),W.activeCamera.getProjectionMatrix()),W._evaluateActiveMeshes(),W._activeMeshesFrozen=!0,W._skipEvaluateActiveMeshesCompletely=k;for(var q=0;q<W._activeMeshes.length;q++)W._activeMeshes.data[q]._freeze();H&&H()}else Z&&Z("No active camera found")}),this},Y.prototype.unfreezeActiveMeshes=function(){for(var k=0;k<this.meshes.length;k++){var H=this.meshes[k];H._internalAbstractMeshDataInfo&&(H._internalAbstractMeshDataInfo._isActive=!1)}for(k=0;k<this._activeMeshes.length;k++)this._activeMeshes.data[k]._unFreeze();return this._activeMeshesFrozen=!1,this},Y.prototype._evaluateActiveMeshes=function(){if(this._activeMeshesFrozen&&this._activeMeshes.length){if(!this._skipEvaluateActiveMeshesCompletely)for(var k=this._activeMeshes.length,H=0;H<k;H++)(me=this._activeMeshes.data[H]).computeWorldMatrix();if(this._activeParticleSystems){var Z=this._activeParticleSystems.length;for(H=0;H<Z;H++)this._activeParticleSystems.data[H].animate()}}else if(this.activeCamera){this.onBeforeActiveMeshesEvaluationObservable.notifyObservers(this),this.activeCamera._activeMeshes.reset(),this._activeMeshes.reset(),this._renderingManager.reset(),this._processedMaterials.reset(),this._activeParticleSystems.reset(),this._activeSkeletons.reset(),this._softwareSkinnedMeshes.reset();for(var W=0,q=this._beforeEvaluateActiveMeshStage;W<q.length;W++)q[W].action();var he=this.getActiveMeshCandidates(),ge=he.length;for(H=0;H<ge;H++){var me;if((me=he.data[H])._internalAbstractMeshDataInfo._currentLODIsUpToDate=!1,!me.isBlocked&&(this._totalVertices.addCount(me.getTotalVertices(),!1),me.isReady()&&me.isEnabled()&&me.scaling.lengthSquared()!==0)){me.computeWorldMatrix(),me.actionManager&&me.actionManager.hasSpecificTriggers2(I.a.ACTION_OnIntersectionEnterTrigger,I.a.ACTION_OnIntersectionExitTrigger)&&this._meshesForIntersections.pushNoDuplicate(me);var _e=this.customLODSelector?this.customLODSelector(me,this.activeCamera):me.getLOD(this.activeCamera);if(me._internalAbstractMeshDataInfo._currentLOD=_e,me._internalAbstractMeshDataInfo._currentLODIsUpToDate=!0,_e!=null&&(_e!==me&&_e.billboardMode!==c.a.BILLBOARDMODE_NONE&&_e.computeWorldMatrix(),me._preActivate(),me.isVisible&&me.visibility>0&&(me.layerMask&this.activeCamera.layerMask)!=0&&(this._skipFrustumClipping||me.alwaysSelectAsActiveMesh||me.isInFrustum(this._frustumPlanes)))){this._activeMeshes.push(me),this.activeCamera._activeMeshes.push(me),_e!==me&&_e._activate(this._renderId,!1);for(var be=0,Pe=this._preActiveMeshStage;be<Pe.length;be++)Pe[be].action(me);me._activate(this._renderId,!1)&&(me.isAnInstance?me._internalAbstractMeshDataInfo._actAsRegularMesh&&(_e=me):_e._internalAbstractMeshDataInfo._onlyForInstances=!1,_e._internalAbstractMeshDataInfo._isActive=!0,this._activeMesh(me,_e)),me._postActivate()}}}if(this.onAfterActiveMeshesEvaluationObservable.notifyObservers(this),this.particlesEnabled){this.onBeforeParticlesRenderingObservable.notifyObservers(this);for(var ye=0;ye<this.particleSystems.length;ye++){var Be=this.particleSystems[ye];if(Be.isStarted()&&Be.emitter){var ke=Be.emitter;ke.position&&!ke.isEnabled()||(this._activeParticleSystems.push(Be),Be.animate(),this._renderingManager.dispatchParticles(Be))}}this.onAfterParticlesRenderingObservable.notifyObservers(this)}}},Y.prototype._activeMesh=function(k,H){if(this._skeletonsEnabled&&H.skeleton!==null&&H.skeleton!==void 0&&(this._activeSkeletons.pushNoDuplicate(H.skeleton)&&H.skeleton.prepare(),H.computeBonesUsingShaders||this._softwareSkinnedMeshes.pushNoDuplicate(H)),H!=null&&H.subMeshes!==void 0&&H.subMeshes!==null&&H.subMeshes.length>0)for(var Z=this.getActiveSubMeshCandidates(H),W=Z.length,q=0;q<W;q++){var he=Z.data[q];this._evaluateSubMesh(he,H,k)}},Y.prototype.updateTransformMatrix=function(k){this.activeCamera&&this.setTransformMatrix(this.activeCamera.getViewMatrix(),this.activeCamera.getProjectionMatrix(k))},Y.prototype._bindFrameBuffer=function(){if(this.activeCamera&&this.activeCamera._multiviewTexture)this.activeCamera._multiviewTexture._bindFrameBuffer();else if(this.activeCamera&&this.activeCamera.outputRenderTarget)if(this.getEngine().getCaps().multiview&&this.activeCamera.outputRenderTarget&&this.activeCamera.outputRenderTarget.getViewCount()>1)this.activeCamera.outputRenderTarget._bindFrameBuffer();else{var k=this.activeCamera.outputRenderTarget.getInternalTexture();k?this.getEngine().bindFramebuffer(k):X.a.Error("Camera contains invalid customDefaultRenderTarget")}else this.getEngine().restoreDefaultFramebuffer()},Y.prototype._renderForCamera=function(k,H){if(!k||!k._skipRendering){var Z=this._engine;if(this._activeCamera=k,!this.activeCamera)throw new Error("Active camera not set");Z.setViewport(this.activeCamera.viewport),this.resetCachedMaterial(),this._renderId++,this.getEngine().getCaps().multiview&&k.outputRenderTarget&&k.outputRenderTarget.getViewCount()>1?this.setTransformMatrix(k._rigCameras[0].getViewMatrix(),k._rigCameras[0].getProjectionMatrix(),k._rigCameras[1].getViewMatrix(),k._rigCameras[1].getProjectionMatrix()):this.updateTransformMatrix(),this.onBeforeCameraRenderObservable.notifyObservers(this.activeCamera),this._evaluateActiveMeshes();for(var W=0;W<this._softwareSkinnedMeshes.length;W++){var q=this._softwareSkinnedMeshes.data[W];q.applySkeleton(q.skeleton)}this.onBeforeRenderTargetsRenderObservable.notifyObservers(this),k.customRenderTargets&&k.customRenderTargets.length>0&&this._renderTargets.concatWithNoDuplicate(k.customRenderTargets),H&&H.customRenderTargets&&H.customRenderTargets.length>0&&this._renderTargets.concatWithNoDuplicate(H.customRenderTargets);for(var he=0,ge=this._gatherActiveCameraRenderTargetsStage;he<ge.length;he++)ge[he].action(this._renderTargets);var me=!1;if(this.renderTargetsEnabled){if(this._intermediateRendering=!0,this._renderTargets.length>0){_.b.StartPerformanceCounter("Render targets",this._renderTargets.length>0);for(var _e=0;_e<this._renderTargets.length;_e++){var be=this._renderTargets.data[_e];if(be._shouldRender()){this._renderId++;var Pe=be.activeCamera&&be.activeCamera!==this.activeCamera;be.render(Pe,this.dumpNextRenderTargets),me=!0}}_.b.EndPerformanceCounter("Render targets",this._renderTargets.length>0),this._renderId++}for(var ye=0,Be=this._cameraDrawRenderTargetStage;ye<Be.length;ye++)me=Be[ye].action(this.activeCamera)||me;this._intermediateRendering=!1,this.activeCamera&&this.activeCamera.outputRenderTarget&&(me=!0)}me&&!this.prePass&&this._bindFrameBuffer(),this.onAfterRenderTargetsRenderObservable.notifyObservers(this),!this.postProcessManager||k._multiviewTexture||this.prePass||this.postProcessManager._prepareFrame();for(var ke=0,We=this._beforeCameraDrawStage;ke<We.length;ke++)We[ke].action(this.activeCamera);this.onBeforeDrawPhaseObservable.notifyObservers(this),this._renderingManager.render(null,null,!0,!0),this.onAfterDrawPhaseObservable.notifyObservers(this);for(var je=0,He=this._afterCameraDrawStage;je<He.length;je++)He[je].action(this.activeCamera);if(this.postProcessManager&&!k._multiviewTexture){var qe=k.outputRenderTarget?k.outputRenderTarget.getInternalTexture():void 0;this.postProcessManager._finalizeFrame(k.isIntermediate,qe)}this._renderTargets.reset(),this.onAfterCameraRenderObservable.notifyObservers(this.activeCamera)}},Y.prototype._processSubCameras=function(k){if(k.cameraRigMode===A.a.RIG_MODE_NONE||k.outputRenderTarget&&k.outputRenderTarget.getViewCount()>1&&this.getEngine().getCaps().multiview)return this._renderForCamera(k),void this.onAfterRenderCameraObservable.notifyObservers(k);if(k._useMultiviewToSingleView)this._renderMultiviewToSingleView(k);else for(var H=0;H<k._rigCameras.length;H++)this._renderForCamera(k._rigCameras[H],k);this._activeCamera=k,this.setTransformMatrix(this._activeCamera.getViewMatrix(),this._activeCamera.getProjectionMatrix()),this.onAfterRenderCameraObservable.notifyObservers(k)},Y.prototype._checkIntersections=function(){for(var k=0;k<this._meshesForIntersections.length;k++){var H=this._meshesForIntersections.data[k];if(H.actionManager)for(var Z=0;H.actionManager&&Z<H.actionManager.actions.length;Z++){var W=H.actionManager.actions[Z];if(W.trigger===I.a.ACTION_OnIntersectionEnterTrigger||W.trigger===I.a.ACTION_OnIntersectionExitTrigger){var q=W.getTriggerParameter(),he=q instanceof T.a?q:q.mesh,ge=he.intersectsMesh(H,q.usePreciseIntersection),me=H._intersectionsInProgress.indexOf(he);ge&&me===-1?W.trigger===I.a.ACTION_OnIntersectionEnterTrigger?(W._executeCurrent(E.a.CreateNew(H,void 0,he)),H._intersectionsInProgress.push(he)):W.trigger===I.a.ACTION_OnIntersectionExitTrigger&&H._intersectionsInProgress.push(he):!ge&&me>-1&&(W.trigger===I.a.ACTION_OnIntersectionExitTrigger&&W._executeCurrent(E.a.CreateNew(H,void 0,he)),H.actionManager.hasSpecificTrigger(I.a.ACTION_OnIntersectionExitTrigger,function(_e){var be=_e instanceof T.a?_e:_e.mesh;return he===be})&&W.trigger!==I.a.ACTION_OnIntersectionExitTrigger||H._intersectionsInProgress.splice(me,1))}}}},Y.prototype._advancePhysicsEngineStep=function(k){},Y.prototype._animate=function(){},Y.prototype.animate=function(){if(this._engine.isDeterministicLockStep()){var k=Math.max(Y.MinDeltaTime,Math.min(this._engine.getDeltaTime(),Y.MaxDeltaTime))+this._timeAccumulator,H=this._engine.getTimeStep(),Z=1e3/H/1e3,W=0,q=this._engine.getLockstepMaxSteps(),he=Math.floor(k/H);for(he=Math.min(he,q);k>0&&W<he;)this.onBeforeStepObservable.notifyObservers(this),this._animationRatio=H*Z,this._animate(),this.onAfterAnimationsObservable.notifyObservers(this),this.physicsEnabled&&this._advancePhysicsEngineStep(H),this.onAfterStepObservable.notifyObservers(this),this._currentStepId++,W++,k-=H;this._timeAccumulator=k<0?0:k}else k=this.useConstantAnimationDeltaTime?16:Math.max(Y.MinDeltaTime,Math.min(this._engine.getDeltaTime(),Y.MaxDeltaTime)),this._animationRatio=.06*k,this._animate(),this.onAfterAnimationsObservable.notifyObservers(this),this.physicsEnabled&&this._advancePhysicsEngineStep(k)},Y.prototype.render=function(k,H){if(k===void 0&&(k=!0),H===void 0&&(H=!1),!this.isDisposed){this.onReadyObservable.hasObservers()&&this._executeWhenReadyTimeoutId===-1&&this._checkIsReady(),this._frameId++,this._registerTransientComponents(),this._activeParticles.fetchNewFrame(),this._totalVertices.fetchNewFrame(),this._activeIndices.fetchNewFrame(),this._activeBones.fetchNewFrame(),this._meshesForIntersections.reset(),this.resetCachedMaterial(),this.onBeforeAnimationsObservable.notifyObservers(this),this.actionManager&&this.actionManager.processTrigger(I.a.ACTION_OnEveryFrameTrigger),H||this.animate();for(var Z=0,W=this._beforeCameraUpdateStage;Z<W.length;Z++)W[Z].action();if(k){if(this.activeCameras&&this.activeCameras.length>0)for(var q=0;q<this.activeCameras.length;q++){var he=this.activeCameras[q];if(he.update(),he.cameraRigMode!==A.a.RIG_MODE_NONE)for(var ge=0;ge<he._rigCameras.length;ge++)he._rigCameras[ge].update()}else if(this.activeCamera&&(this.activeCamera.update(),this.activeCamera.cameraRigMode!==A.a.RIG_MODE_NONE))for(ge=0;ge<this.activeCamera._rigCameras.length;ge++)this.activeCamera._rigCameras[ge].update()}this.onBeforeRenderObservable.notifyObservers(this),this.onBeforeRenderTargetsRenderObservable.notifyObservers(this);var me=this.getEngine(),_e=this.activeCamera;if(this.renderTargetsEnabled){_.b.StartPerformanceCounter("Custom render targets",this.customRenderTargets.length>0),this._intermediateRendering=!0;for(var be=0;be<this.customRenderTargets.length;be++){var Pe=this.customRenderTargets[be];if(Pe._shouldRender()){if(this._renderId++,this.activeCamera=Pe.activeCamera||this.activeCamera,!this.activeCamera)throw new Error("Active camera not set");me.setViewport(this.activeCamera.viewport),this.updateTransformMatrix(),Pe.render(_e!==this.activeCamera,this.dumpNextRenderTargets)}}_.b.EndPerformanceCounter("Custom render targets",this.customRenderTargets.length>0),this._intermediateRendering=!1,this._renderId++}this.activeCamera=_e,this._activeCamera&&this._activeCamera.cameraRigMode!==A.a.RIG_MODE_CUSTOM&&!this.prePass&&this._bindFrameBuffer(),this.onAfterRenderTargetsRenderObservable.notifyObservers(this);for(var ye=0,Be=this._beforeClearStage;ye<Be.length;ye++)Be[ye].action();!this.autoClearDepthAndStencil&&!this.autoClear||this.prePass||this._engine.clear(this.clearColor,this.autoClear||this.forceWireframe||this.forcePointsCloud,this.autoClearDepthAndStencil,this.autoClearDepthAndStencil);for(var ke=0,We=this._gatherRenderTargetsStage;ke<We.length;ke++)We[ke].action(this._renderTargets);if(this.activeCameras&&this.activeCameras.length>0)for(q=0;q<this.activeCameras.length;q++)q>0&&this._engine.clear(null,!1,!0,!0),this._processSubCameras(this.activeCameras[q]);else{if(!this.activeCamera)throw new Error("No camera defined");this._processSubCameras(this.activeCamera)}this._checkIntersections();for(var je=0,He=this._afterRenderStage;je<He.length;je++)He[je].action();if(this.afterRender&&this.afterRender(),this.onAfterRenderObservable.notifyObservers(this),this._toBeDisposed.length){for(ge=0;ge<this._toBeDisposed.length;ge++){var qe=this._toBeDisposed[ge];qe&&qe.dispose()}this._toBeDisposed=[]}this.dumpNextRenderTargets&&(this.dumpNextRenderTargets=!1),this._activeBones.addCount(0,!0),this._activeIndices.addCount(0,!0),this._activeParticles.addCount(0,!0)}},Y.prototype.freezeMaterials=function(){for(var k=0;k<this.materials.length;k++)this.materials[k].freeze()},Y.prototype.unfreezeMaterials=function(){for(var k=0;k<this.materials.length;k++)this.materials[k].unfreeze()},Y.prototype.dispose=function(){this.beforeRender=null,this.afterRender=null,j.a._LastCreatedScene===this&&(j.a._LastCreatedScene=null),this.skeletons=[],this.morphTargetManagers=[],this._transientComponents=[],this._isReadyForMeshStage.clear(),this._beforeEvaluateActiveMeshStage.clear(),this._evaluateSubMeshStage.clear(),this._preActiveMeshStage.clear(),this._cameraDrawRenderTargetStage.clear(),this._beforeCameraDrawStage.clear(),this._beforeRenderTargetDrawStage.clear(),this._beforeRenderingGroupDrawStage.clear(),this._beforeRenderingMeshStage.clear(),this._afterRenderingMeshStage.clear(),this._afterRenderingGroupDrawStage.clear(),this._afterCameraDrawStage.clear(),this._afterRenderTargetDrawStage.clear(),this._afterRenderStage.clear(),this._beforeCameraUpdateStage.clear(),this._beforeClearStage.clear(),this._gatherRenderTargetsStage.clear(),this._gatherActiveCameraRenderTargetsStage.clear(),this._pointerMoveStage.clear(),this._pointerDownStage.clear(),this._pointerUpStage.clear();for(var k=0,H=this._components;k<H.length;k++)H[k].dispose();this.importedMeshesFiles=new Array,this.stopAllAnimations&&this.stopAllAnimations(),this.resetCachedMaterial(),this.activeCamera&&(this.activeCamera._activeMeshes.dispose(),this.activeCamera=null),this._activeMeshes.dispose(),this._renderingManager.dispose(),this._processedMaterials.dispose(),this._activeParticleSystems.dispose(),this._activeSkeletons.dispose(),this._softwareSkinnedMeshes.dispose(),this._renderTargets.dispose(),this._registeredForLateAnimationBindings.dispose(),this._meshesForIntersections.dispose(),this._toBeDisposed=[];for(var Z=0,W=this._activeRequests;Z<W.length;Z++)W[Z].abort();var q;if(this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear(),this.onBeforeRenderObservable.clear(),this.onAfterRenderObservable.clear(),this.onBeforeRenderTargetsRenderObservable.clear(),this.onAfterRenderTargetsRenderObservable.clear(),this.onAfterStepObservable.clear(),this.onBeforeStepObservable.clear(),this.onBeforeActiveMeshesEvaluationObservable.clear(),this.onAfterActiveMeshesEvaluationObservable.clear(),this.onBeforeParticlesRenderingObservable.clear(),this.onAfterParticlesRenderingObservable.clear(),this.onBeforeDrawPhaseObservable.clear(),this.onAfterDrawPhaseObservable.clear(),this.onBeforeAnimationsObservable.clear(),this.onAfterAnimationsObservable.clear(),this.onDataLoadedObservable.clear(),this.onBeforeRenderingGroupObservable.clear(),this.onAfterRenderingGroupObservable.clear(),this.onMeshImportedObservable.clear(),this.onBeforeCameraRenderObservable.clear(),this.onAfterCameraRenderObservable.clear(),this.onReadyObservable.clear(),this.onNewCameraAddedObservable.clear(),this.onCameraRemovedObservable.clear(),this.onNewLightAddedObservable.clear(),this.onLightRemovedObservable.clear(),this.onNewGeometryAddedObservable.clear(),this.onGeometryRemovedObservable.clear(),this.onNewTransformNodeAddedObservable.clear(),this.onTransformNodeRemovedObservable.clear(),this.onNewMeshAddedObservable.clear(),this.onMeshRemovedObservable.clear(),this.onNewSkeletonAddedObservable.clear(),this.onSkeletonRemovedObservable.clear(),this.onNewMaterialAddedObservable.clear(),this.onNewMultiMaterialAddedObservable.clear(),this.onMaterialRemovedObservable.clear(),this.onMultiMaterialRemovedObservable.clear(),this.onNewTextureAddedObservable.clear(),this.onTextureRemovedObservable.clear(),this.onPrePointerObservable.clear(),this.onPointerObservable.clear(),this.onPreKeyboardObservable.clear(),this.onKeyboardObservable.clear(),this.onActiveCameraChanged.clear(),this.detachControl(),this._engine.getInputElement())for(q=0;q<this.cameras.length;q++)this.cameras[q].detachControl();for(;this.animationGroups.length;)this.animationGroups[0].dispose();for(;this.lights.length;)this.lights[0].dispose();for(;this.meshes.length;)this.meshes[0].dispose(!0);for(;this.transformNodes.length;)this.transformNodes[0].dispose(!0);for(;this.cameras.length;)this.cameras[0].dispose();for(this._defaultMaterial&&this._defaultMaterial.dispose();this.multiMaterials.length;)this.multiMaterials[0].dispose();for(;this.materials.length;)this.materials[0].dispose();for(;this.particleSystems.length;)this.particleSystems[0].dispose();for(;this.postProcesses.length;)this.postProcesses[0].dispose();for(;this.textures.length;)this.textures[0].dispose();this._sceneUbo.dispose(),this._multiviewSceneUbo&&this._multiviewSceneUbo.dispose(),this.postProcessManager.dispose(),(q=this._engine.scenes.indexOf(this))>-1&&this._engine.scenes.splice(q,1),this._engine.wipeCaches(!0),this._isDisposed=!0},Object.defineProperty(Y.prototype,"isDisposed",{get:function(){return this._isDisposed},enumerable:!1,configurable:!0}),Y.prototype.clearCachedVertexData=function(){for(var k=0;k<this.meshes.length;k++){var H=this.meshes[k].geometry;if(H)for(var Z in H._indices=[],H._vertexBuffers)H._vertexBuffers.hasOwnProperty(Z)&&(H._vertexBuffers[Z]._buffer._data=null)}},Y.prototype.cleanCachedTextureBuffer=function(){for(var k=0,H=this.textures;k<H.length;k++){var Z=H[k];Z._buffer&&(Z._buffer=null)}},Y.prototype.getWorldExtends=function(k){var H=new m.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),Z=new m.e(-Number.MAX_VALUE,-Number.MAX_VALUE,-Number.MAX_VALUE);return k=k||function(){return!0},this.meshes.filter(k).forEach(function(W){if(W.computeWorldMatrix(!0),W.subMeshes&&W.subMeshes.length!==0&&!W.infiniteDistance){var q=W.getBoundingInfo(),he=q.boundingBox.minimumWorld,ge=q.boundingBox.maximumWorld;m.e.CheckExtends(he,H,Z),m.e.CheckExtends(ge,H,Z)}}),{min:H,max:Z}},Y.prototype.createPickingRay=function(k,H,Z,W,q){throw ne.a.WarnImport("Ray")},Y.prototype.createPickingRayToRef=function(k,H,Z,W,q,he){throw ne.a.WarnImport("Ray")},Y.prototype.createPickingRayInCameraSpace=function(k,H,Z){throw ne.a.WarnImport("Ray")},Y.prototype.createPickingRayInCameraSpaceToRef=function(k,H,Z,W){throw ne.a.WarnImport("Ray")},Y.prototype.pick=function(k,H,Z,W,q,he){var ge=new v.a;return ge._pickingUnavailable=!0,ge},Y.prototype.pickWithBoundingInfo=function(k,H,Z,W,q){var he=new v.a;return he._pickingUnavailable=!0,he},Y.prototype.pickWithRay=function(k,H,Z,W){throw ne.a.WarnImport("Ray")},Y.prototype.multiPick=function(k,H,Z,W,q){throw ne.a.WarnImport("Ray")},Y.prototype.multiPickWithRay=function(k,H,Z){throw ne.a.WarnImport("Ray")},Y.prototype.setPointerOverMesh=function(k,H){this._inputManager.setPointerOverMesh(k,H)},Y.prototype.getPointerOverMesh=function(){return this._inputManager.getPointerOverMesh()},Y.prototype._rebuildGeometries=function(){for(var k=0,H=this.geometries;k<H.length;k++)H[k]._rebuild();for(var Z=0,W=this.meshes;Z<W.length;Z++)W[Z]._rebuild();this.postProcessManager&&this.postProcessManager._rebuild();for(var q=0,he=this._components;q<he.length;q++)he[q].rebuild();for(var ge=0,me=this.particleSystems;ge<me.length;ge++)me[ge].rebuild()},Y.prototype._rebuildTextures=function(){for(var k=0,H=this.textures;k<H.length;k++)H[k]._rebuild();this.markAllMaterialsAsDirty(I.a.MATERIAL_TextureDirtyFlag)},Y.prototype._getByTags=function(k,H,Z){if(H===void 0)return k;var W=[];for(var q in Z=Z||function(ge){},k){var he=k[q];x.a&&x.a.MatchesQuery(he,H)&&(W.push(he),Z(he))}return W},Y.prototype.getMeshesByTags=function(k,H){return this._getByTags(this.meshes,k,H)},Y.prototype.getCamerasByTags=function(k,H){return this._getByTags(this.cameras,k,H)},Y.prototype.getLightsByTags=function(k,H){return this._getByTags(this.lights,k,H)},Y.prototype.getMaterialByTags=function(k,H){return this._getByTags(this.materials,k,H).concat(this._getByTags(this.multiMaterials,k,H))},Y.prototype.getTransformNodesByTags=function(k,H){return this._getByTags(this.transformNodes,k,H)},Y.prototype.setRenderingOrder=function(k,H,Z,W){H===void 0&&(H=null),Z===void 0&&(Z=null),W===void 0&&(W=null),this._renderingManager.setRenderingOrder(k,H,Z,W)},Y.prototype.setRenderingAutoClearDepthStencil=function(k,H,Z,W){Z===void 0&&(Z=!0),W===void 0&&(W=!0),this._renderingManager.setRenderingAutoClearDepthStencil(k,H,Z,W)},Y.prototype.getAutoClearDepthStencilSetup=function(k){return this._renderingManager.getAutoClearDepthStencilSetup(k)},Object.defineProperty(Y.prototype,"blockMaterialDirtyMechanism",{get:function(){return this._blockMaterialDirtyMechanism},set:function(k){this._blockMaterialDirtyMechanism!==k&&(this._blockMaterialDirtyMechanism=k,k||this.markAllMaterialsAsDirty(I.a.MATERIAL_AllDirtyFlag))},enumerable:!1,configurable:!0}),Y.prototype.markAllMaterialsAsDirty=function(k,H){if(!this._blockMaterialDirtyMechanism)for(var Z=0,W=this.materials;Z<W.length;Z++){var q=W[Z];H&&!H(q)||q.markAsDirty(k)}},Y.prototype._loadFile=function(k,H,Z,W,q,he){var ge=this,me=Q.a.LoadFile(k,H,Z,W?this.offlineProvider:void 0,q,he);return this._activeRequests.push(me),me.onCompleteObservable.add(function(_e){ge._activeRequests.splice(ge._activeRequests.indexOf(_e),1)}),me},Y.prototype._loadFileAsync=function(k,H,Z,W){var q=this;return new Promise(function(he,ge){q._loadFile(k,function(me){he(me)},H,Z,W,function(me,_e){ge(_e)})})},Y.prototype._requestFile=function(k,H,Z,W,q,he,ge){var me=this,_e=Q.a.RequestFile(k,H,Z,W?this.offlineProvider:void 0,q,he,ge);return this._activeRequests.push(_e),_e.onCompleteObservable.add(function(be){me._activeRequests.splice(me._activeRequests.indexOf(be),1)}),_e},Y.prototype._requestFileAsync=function(k,H,Z,W,q){var he=this;return new Promise(function(ge,me){he._requestFile(k,function(_e){ge(_e)},H,Z,W,function(_e){me(_e)},q)})},Y.prototype._readFile=function(k,H,Z,W,q){var he=this,ge=Q.a.ReadFile(k,H,Z,W,q);return this._activeRequests.push(ge),ge.onCompleteObservable.add(function(me){he._activeRequests.splice(he._activeRequests.indexOf(me),1)}),ge},Y.prototype._readFileAsync=function(k,H,Z){var W=this;return new Promise(function(q,he){W._readFile(k,function(ge){q(ge)},H,Z,function(ge){he(ge)})})},Y.FOGMODE_NONE=0,Y.FOGMODE_EXP=1,Y.FOGMODE_EXP2=2,Y.FOGMODE_LINEAR=3,Y.MinDeltaTime=1,Y.MaxDeltaTime=1e3,Y}(S.a)},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.WarnImport=function(C){return C+" needs to be imported before as it contains a side-effect required by your code."},_}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return Object.defineProperty(_,"LastCreatedEngine",{get:function(){return this.Instances.length===0?null:this.Instances[this.Instances.length-1]},enumerable:!1,configurable:!0}),Object.defineProperty(_,"LastCreatedScene",{get:function(){return this._LastCreatedScene},enumerable:!1,configurable:!0}),_.Instances=new Array,_._LastCreatedScene=null,_.UseFallbackTexture=!0,_.FallbackTexture="",_}()},function(Me,y,f){f.d(y,"c",function(){return U}),f.d(y,"a",function(){return u}),f.d(y,"b",function(){return C});var U,_=f(0);(function(M){M[M.LOCAL=0]="LOCAL",M[M.WORLD=1]="WORLD",M[M.BONE=2]="BONE"})(U||(U={}));var C,u=function(){function M(){}return M.X=new _.e(1,0,0),M.Y=new _.e(0,1,0),M.Z=new _.e(0,0,1),M}();(function(M){M[M.X=0]="X",M[M.Y=1]="Y",M[M.Z=2]="Z"})(C||(C={}))},function(Me,y,f){f.d(y,"a",function(){return g});var U=f(1),_=f(3),C=f(33),u=f(12),M=f(6),R=f(0),x=f(29),m=f(8),c=f(11),T=f(21),A=f(58),S=f(90),g=function(l){function h(v,E,D,w){w===void 0&&(w=!0);var N=l.call(this,v,D)||this;return N._position=R.e.Zero(),N._upVector=R.e.Up(),N.orthoLeft=null,N.orthoRight=null,N.orthoBottom=null,N.orthoTop=null,N.fov=.8,N.minZ=1,N.maxZ=1e4,N.inertia=.9,N.mode=h.PERSPECTIVE_CAMERA,N.isIntermediate=!1,N.viewport=new A.a(0,0,1,1),N.layerMask=268435455,N.fovMode=h.FOVMODE_VERTICAL_FIXED,N.cameraRigMode=h.RIG_MODE_NONE,N.customRenderTargets=new Array,N.outputRenderTarget=null,N.onViewMatrixChangedObservable=new M.c,N.onProjectionMatrixChangedObservable=new M.c,N.onAfterCheckInputsObservable=new M.c,N.onRestoreStateObservable=new M.c,N.isRigCamera=!1,N._rigCameras=new Array,N._webvrViewMatrix=R.a.Identity(),N._skipRendering=!1,N._projectionMatrix=new R.a,N._postProcesses=new Array,N._activeMeshes=new C.a(256),N._globalPosition=R.e.Zero(),N._computedViewMatrix=R.a.Identity(),N._doNotComputeProjectionMatrix=!1,N._transformMatrix=R.a.Zero(),N._refreshFrustumPlanes=!0,N._isCamera=!0,N._isLeftCamera=!1,N._isRightCamera=!1,N.getScene().addCamera(N),w&&!N.getScene().activeCamera&&(N.getScene().activeCamera=N),N.position=E,N}return Object(U.d)(h,l),Object.defineProperty(h.prototype,"position",{get:function(){return this._position},set:function(v){this._position=v},enumerable:!1,configurable:!0}),Object.defineProperty(h.prototype,"upVector",{get:function(){return this._upVector},set:function(v){this._upVector=v},enumerable:!1,configurable:!0}),h.prototype.storeState=function(){return this._stateStored=!0,this._storedFov=this.fov,this},h.prototype._restoreStateValues=function(){return!!this._stateStored&&(this.fov=this._storedFov,!0)},h.prototype.restoreState=function(){return!!this._restoreStateValues()&&(this.onRestoreStateObservable.notifyObservers(this),!0)},h.prototype.getClassName=function(){return"Camera"},h.prototype.toString=function(v){var E="Name: "+this.name;if(E+=", type: "+this.getClassName(),this.animations)for(var D=0;D<this.animations.length;D++)E+=", animation[0]: "+this.animations[D].toString(v);return E},Object.defineProperty(h.prototype,"globalPosition",{get:function(){return this._globalPosition},enumerable:!1,configurable:!0}),h.prototype.getActiveMeshes=function(){return this._activeMeshes},h.prototype.isActiveMesh=function(v){return this._activeMeshes.indexOf(v)!==-1},h.prototype.isReady=function(v){if(v===void 0&&(v=!1),v)for(var E=0,D=this._postProcesses;E<D.length;E++){var w=D[E];if(w&&!w.isReady())return!1}return l.prototype.isReady.call(this,v)},h.prototype._initCache=function(){l.prototype._initCache.call(this),this._cache.position=new R.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._cache.upVector=new R.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._cache.mode=void 0,this._cache.minZ=void 0,this._cache.maxZ=void 0,this._cache.fov=void 0,this._cache.fovMode=void 0,this._cache.aspectRatio=void 0,this._cache.orthoLeft=void 0,this._cache.orthoRight=void 0,this._cache.orthoBottom=void 0,this._cache.orthoTop=void 0,this._cache.renderWidth=void 0,this._cache.renderHeight=void 0},h.prototype._updateCache=function(v){v||l.prototype._updateCache.call(this),this._cache.position.copyFrom(this.position),this._cache.upVector.copyFrom(this.upVector)},h.prototype._isSynchronized=function(){return this._isSynchronizedViewMatrix()&&this._isSynchronizedProjectionMatrix()},h.prototype._isSynchronizedViewMatrix=function(){return!!l.prototype._isSynchronized.call(this)&&this._cache.position.equals(this.position)&&this._cache.upVector.equals(this.upVector)&&this.isSynchronizedWithParent()},h.prototype._isSynchronizedProjectionMatrix=function(){var v=this._cache.mode===this.mode&&this._cache.minZ===this.minZ&&this._cache.maxZ===this.maxZ;if(!v)return!1;var E=this.getEngine();return v=this.mode===h.PERSPECTIVE_CAMERA?this._cache.fov===this.fov&&this._cache.fovMode===this.fovMode&&this._cache.aspectRatio===E.getAspectRatio(this):this._cache.orthoLeft===this.orthoLeft&&this._cache.orthoRight===this.orthoRight&&this._cache.orthoBottom===this.orthoBottom&&this._cache.orthoTop===this.orthoTop&&this._cache.renderWidth===E.getRenderWidth()&&this._cache.renderHeight===E.getRenderHeight()},h.prototype.attachControl=function(v,E){},h.prototype.detachControl=function(v){},h.prototype.update=function(){this._checkInputs(),this.cameraRigMode!==h.RIG_MODE_NONE&&this._updateRigCameras()},h.prototype._checkInputs=function(){this.onAfterCheckInputsObservable.notifyObservers(this)},Object.defineProperty(h.prototype,"rigCameras",{get:function(){return this._rigCameras},enumerable:!1,configurable:!0}),Object.defineProperty(h.prototype,"rigPostProcess",{get:function(){return this._rigPostProcess},enumerable:!1,configurable:!0}),h.prototype._getFirstPostProcess=function(){for(var v=0;v<this._postProcesses.length;v++)if(this._postProcesses[v]!==null)return this._postProcesses[v];return null},h.prototype._cascadePostProcessesToRigCams=function(){var v=this._getFirstPostProcess();v&&v.markTextureDirty();for(var E=0,D=this._rigCameras.length;E<D;E++){var w=this._rigCameras[E],N=w._rigPostProcess;N?(N.getEffectName()==="pass"&&(w.isIntermediate=this._postProcesses.length===0),w._postProcesses=this._postProcesses.slice(0).concat(N),N.markTextureDirty()):w._postProcesses=this._postProcesses.slice(0)}},h.prototype.attachPostProcess=function(v,E){return E===void 0&&(E=null),!v.isReusable()&&this._postProcesses.indexOf(v)>-1?(m.a.Error("You're trying to reuse a post process not defined as reusable."),0):(E==null||E<0?this._postProcesses.push(v):this._postProcesses[E]===null?this._postProcesses[E]=v:this._postProcesses.splice(E,0,v),this._cascadePostProcessesToRigCams(),this._scene.prePassRenderer&&this._scene.prePassRenderer.markAsDirty(),this._postProcesses.indexOf(v))},h.prototype.detachPostProcess=function(v){var E=this._postProcesses.indexOf(v);E!==-1&&(this._postProcesses[E]=null),this._scene.prePassRenderer&&this._scene.prePassRenderer.markAsDirty(),this._cascadePostProcessesToRigCams()},h.prototype.getWorldMatrix=function(){return this._isSynchronizedViewMatrix()||this.getViewMatrix(),this._worldMatrix},h.prototype._getViewMatrix=function(){return R.a.Identity()},h.prototype.getViewMatrix=function(v){return!v&&this._isSynchronizedViewMatrix()||(this.updateCache(),this._computedViewMatrix=this._getViewMatrix(),this._currentRenderId=this.getScene().getRenderId(),this._childUpdateId++,this._refreshFrustumPlanes=!0,this._cameraRigParams&&this._cameraRigParams.vrPreViewMatrix&&this._computedViewMatrix.multiplyToRef(this._cameraRigParams.vrPreViewMatrix,this._computedViewMatrix),this.parent&&this.parent.onViewMatrixChangedObservable&&this.parent.onViewMatrixChangedObservable.notifyObservers(this.parent),this.onViewMatrixChangedObservable.notifyObservers(this),this._computedViewMatrix.invertToRef(this._worldMatrix)),this._computedViewMatrix},h.prototype.freezeProjectionMatrix=function(v){this._doNotComputeProjectionMatrix=!0,v!==void 0&&(this._projectionMatrix=v)},h.prototype.unfreezeProjectionMatrix=function(){this._doNotComputeProjectionMatrix=!1},h.prototype.getProjectionMatrix=function(v){var E,D,w,N,I,V,X,j;if(this._doNotComputeProjectionMatrix||!v&&this._isSynchronizedProjectionMatrix())return this._projectionMatrix;this._cache.mode=this.mode,this._cache.minZ=this.minZ,this._cache.maxZ=this.maxZ,this._refreshFrustumPlanes=!0;var ne=this.getEngine(),te=this.getScene();if(this.mode===h.PERSPECTIVE_CAMERA){this._cache.fov=this.fov,this._cache.fovMode=this.fovMode,this._cache.aspectRatio=ne.getAspectRatio(this),this.minZ<=0&&(this.minZ=.1);var de=ne.useReverseDepthBuffer;(te.useRightHandedSystem?de?R.a.PerspectiveFovReverseRHToRef:R.a.PerspectiveFovRHToRef:de?R.a.PerspectiveFovReverseLHToRef:R.a.PerspectiveFovLHToRef)(this.fov,ne.getAspectRatio(this),this.minZ,this.maxZ,this._projectionMatrix,this.fovMode===h.FOVMODE_VERTICAL_FIXED)}else{var pe=ne.getRenderWidth()/2,ae=ne.getRenderHeight()/2;te.useRightHandedSystem?R.a.OrthoOffCenterRHToRef((E=this.orthoLeft)!==null&&E!==void 0?E:-pe,(D=this.orthoRight)!==null&&D!==void 0?D:pe,(w=this.orthoBottom)!==null&&w!==void 0?w:-ae,(N=this.orthoTop)!==null&&N!==void 0?N:ae,this.minZ,this.maxZ,this._projectionMatrix):R.a.OrthoOffCenterLHToRef((I=this.orthoLeft)!==null&&I!==void 0?I:-pe,(V=this.orthoRight)!==null&&V!==void 0?V:pe,(X=this.orthoBottom)!==null&&X!==void 0?X:-ae,(j=this.orthoTop)!==null&&j!==void 0?j:ae,this.minZ,this.maxZ,this._projectionMatrix),this._cache.orthoLeft=this.orthoLeft,this._cache.orthoRight=this.orthoRight,this._cache.orthoBottom=this.orthoBottom,this._cache.orthoTop=this.orthoTop,this._cache.renderWidth=ne.getRenderWidth(),this._cache.renderHeight=ne.getRenderHeight()}return this.onProjectionMatrixChangedObservable.notifyObservers(this),this._projectionMatrix},h.prototype.getTransformationMatrix=function(){return this._computedViewMatrix.multiplyToRef(this._projectionMatrix,this._transformMatrix),this._transformMatrix},h.prototype._updateFrustumPlanes=function(){this._refreshFrustumPlanes&&(this.getTransformationMatrix(),this._frustumPlanes?S.a.GetPlanesToRef(this._transformMatrix,this._frustumPlanes):this._frustumPlanes=S.a.GetPlanes(this._transformMatrix),this._refreshFrustumPlanes=!1)},h.prototype.isInFrustum=function(v,E){if(E===void 0&&(E=!1),this._updateFrustumPlanes(),E&&this.rigCameras.length>0){var D=!1;return this.rigCameras.forEach(function(w){w._updateFrustumPlanes(),D=D||v.isInFrustum(w._frustumPlanes)}),D}return v.isInFrustum(this._frustumPlanes)},h.prototype.isCompletelyInFrustum=function(v){return this._updateFrustumPlanes(),v.isCompletelyInFrustum(this._frustumPlanes)},h.prototype.getForwardRay=function(v,E,D){throw T.a.WarnImport("Ray")},h.prototype.getForwardRayToRef=function(v,E,D,w){throw T.a.WarnImport("Ray")},h.prototype.dispose=function(v,E){for(E===void 0&&(E=!1),this.onViewMatrixChangedObservable.clear(),this.onProjectionMatrixChangedObservable.clear(),this.onAfterCheckInputsObservable.clear(),this.onRestoreStateObservable.clear(),this.inputs&&this.inputs.clear(),this.getScene().stopAnimation(this),this.getScene().removeCamera(this);this._rigCameras.length>0;){var D=this._rigCameras.pop();D&&D.dispose()}if(this._rigPostProcess)this._rigPostProcess.dispose(this),this._rigPostProcess=null,this._postProcesses=[];else if(this.cameraRigMode!==h.RIG_MODE_NONE)this._rigPostProcess=null,this._postProcesses=[];else for(var w=this._postProcesses.length;--w>=0;){var N=this._postProcesses[w];N&&N.dispose(this)}for(w=this.customRenderTargets.length;--w>=0;)this.customRenderTargets[w].dispose();this.customRenderTargets=[],this._activeMeshes.dispose(),l.prototype.dispose.call(this,v,E)},Object.defineProperty(h.prototype,"isLeftCamera",{get:function(){return this._isLeftCamera},enumerable:!1,configurable:!0}),Object.defineProperty(h.prototype,"isRightCamera",{get:function(){return this._isRightCamera},enumerable:!1,configurable:!0}),Object.defineProperty(h.prototype,"leftCamera",{get:function(){return this._rigCameras.length<1?null:this._rigCameras[0]},enumerable:!1,configurable:!0}),Object.defineProperty(h.prototype,"rightCamera",{get:function(){return this._rigCameras.length<2?null:this._rigCameras[1]},enumerable:!1,configurable:!0}),h.prototype.getLeftTarget=function(){return this._rigCameras.length<1?null:this._rigCameras[0].getTarget()},h.prototype.getRightTarget=function(){return this._rigCameras.length<2?null:this._rigCameras[1].getTarget()},h.prototype.setCameraRigMode=function(v,E){if(this.cameraRigMode!==v){for(;this._rigCameras.length>0;){var D=this._rigCameras.pop();D&&D.dispose()}if(this.cameraRigMode=v,this._cameraRigParams={},this._cameraRigParams.interaxialDistance=E.interaxialDistance||.0637,this._cameraRigParams.stereoHalfAngle=u.b.ToRadians(this._cameraRigParams.interaxialDistance/.0637),this.cameraRigMode!==h.RIG_MODE_NONE){var w=this.createRigCamera(this.name+"_L",0);w&&(w._isLeftCamera=!0);var N=this.createRigCamera(this.name+"_R",1);N&&(N._isRightCamera=!0),w&&N&&(this._rigCameras.push(w),this._rigCameras.push(N))}switch(this.cameraRigMode){case h.RIG_MODE_STEREOSCOPIC_ANAGLYPH:h._setStereoscopicAnaglyphRigMode(this);break;case h.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:case h.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED:case h.RIG_MODE_STEREOSCOPIC_OVERUNDER:case h.RIG_MODE_STEREOSCOPIC_INTERLACED:h._setStereoscopicRigMode(this);break;case h.RIG_MODE_VR:h._setVRRigMode(this,E);break;case h.RIG_MODE_WEBVR:h._setWebVRRigMode(this,E)}this._cascadePostProcessesToRigCams(),this.update()}},h._setStereoscopicRigMode=function(v){throw"Import Cameras/RigModes/stereoscopicRigMode before using stereoscopic rig mode"},h._setStereoscopicAnaglyphRigMode=function(v){throw"Import Cameras/RigModes/stereoscopicAnaglyphRigMode before using stereoscopic anaglyph rig mode"},h._setVRRigMode=function(v,E){throw"Import Cameras/RigModes/vrRigMode before using VR rig mode"},h._setWebVRRigMode=function(v,E){throw"Import Cameras/RigModes/WebVRRigMode before using Web VR rig mode"},h.prototype._getVRProjectionMatrix=function(){return R.a.PerspectiveFovLHToRef(this._cameraRigParams.vrMetrics.aspectRatioFov,this._cameraRigParams.vrMetrics.aspectRatio,this.minZ,this.maxZ,this._cameraRigParams.vrWorkMatrix),this._cameraRigParams.vrWorkMatrix.multiplyToRef(this._cameraRigParams.vrHMatrix,this._projectionMatrix),this._projectionMatrix},h.prototype._updateCameraRotationMatrix=function(){},h.prototype._updateWebVRCameraRotationMatrix=function(){},h.prototype._getWebVRProjectionMatrix=function(){return R.a.Identity()},h.prototype._getWebVRViewMatrix=function(){return R.a.Identity()},h.prototype.setCameraRigParameter=function(v,E){this._cameraRigParams||(this._cameraRigParams={}),this._cameraRigParams[v]=E,v==="interaxialDistance"&&(this._cameraRigParams.stereoHalfAngle=u.b.ToRadians(E/.0637))},h.prototype.createRigCamera=function(v,E){return null},h.prototype._updateRigCameras=function(){for(var v=0;v<this._rigCameras.length;v++)this._rigCameras[v].minZ=this.minZ,this._rigCameras[v].maxZ=this.maxZ,this._rigCameras[v].fov=this.fov,this._rigCameras[v].upVector.copyFrom(this.upVector);this.cameraRigMode===h.RIG_MODE_STEREOSCOPIC_ANAGLYPH&&(this._rigCameras[0].viewport=this._rigCameras[1].viewport=this.viewport)},h.prototype._setupInputs=function(){},h.prototype.serialize=function(){var v=_.a.Serialize(this);return v.type=this.getClassName(),this.parent&&(v.parentId=this.parent.id),this.inputs&&this.inputs.serialize(v),_.a.AppendSerializedAnimations(this,v),v.ranges=this.serializeAnimationRanges(),v},h.prototype.clone=function(v){return _.a.Clone(h.GetConstructorFromName(this.getClassName(),v,this.getScene(),this.interaxialDistance,this.isStereoscopicSideBySide),this)},h.prototype.getDirection=function(v){var E=R.e.Zero();return this.getDirectionToRef(v,E),E},Object.defineProperty(h.prototype,"absoluteRotation",{get:function(){var v=R.b.Zero();return this.getWorldMatrix().decompose(void 0,v),v},enumerable:!1,configurable:!0}),h.prototype.getDirectionToRef=function(v,E){R.e.TransformNormalToRef(v,this.getWorldMatrix(),E)},h.GetConstructorFromName=function(v,E,D,w,N){w===void 0&&(w=0),N===void 0&&(N=!0);var I=x.a.Construct(v,E,D,{interaxial_distance:w,isStereoscopicSideBySide:N});return I||function(){return h._createDefaultParsedCamera(E,D)}},h.prototype.computeWorldMatrix=function(){return this.getWorldMatrix()},h.Parse=function(v,E){var D=v.type,w=h.GetConstructorFromName(D,v.name,E,v.interaxial_distance,v.isStereoscopicSideBySide),N=_.a.Parse(w,v,E);if(v.parentId&&(N._waitingParentId=v.parentId),N.inputs&&(N.inputs.parse(v),N._setupInputs()),v.upVector&&(N.upVector=R.e.FromArray(v.upVector)),N.setPosition&&(N.position.copyFromFloats(0,0,0),N.setPosition(R.e.FromArray(v.position))),v.target&&N.setTarget&&N.setTarget(R.e.FromArray(v.target)),v.cameraRigMode){var I=v.interaxial_distance?{interaxialDistance:v.interaxial_distance}:{};N.setCameraRigMode(v.cameraRigMode,I)}if(v.animations){for(var V=0;V<v.animations.length;V++){var X=v.animations[V],j=c.a.GetClass("BABYLON.Animation");j&&N.animations.push(j.Parse(X))}x.a.ParseAnimationRanges(N,v,E)}return v.autoAnimate&&E.beginAnimation(N,v.autoAnimateFrom,v.autoAnimateTo,v.autoAnimateLoop,v.autoAnimateSpeed||1),N},h._createDefaultParsedCamera=function(v,E){throw T.a.WarnImport("UniversalCamera")},h.PERSPECTIVE_CAMERA=0,h.ORTHOGRAPHIC_CAMERA=1,h.FOVMODE_VERTICAL_FIXED=0,h.FOVMODE_HORIZONTAL_FIXED=1,h.RIG_MODE_NONE=0,h.RIG_MODE_STEREOSCOPIC_ANAGLYPH=10,h.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL=11,h.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED=12,h.RIG_MODE_STEREOSCOPIC_OVERUNDER=13,h.RIG_MODE_STEREOSCOPIC_INTERLACED=14,h.RIG_MODE_VR=20,h.RIG_MODE_WEBVR=21,h.RIG_MODE_CUSTOM=22,h.ForceAttachControlToAlwaysPreventDefault=!1,Object(U.c)([Object(_.o)("position")],h.prototype,"_position",void 0),Object(U.c)([Object(_.o)("upVector")],h.prototype,"_upVector",void 0),Object(U.c)([Object(_.c)()],h.prototype,"orthoLeft",void 0),Object(U.c)([Object(_.c)()],h.prototype,"orthoRight",void 0),Object(U.c)([Object(_.c)()],h.prototype,"orthoBottom",void 0),Object(U.c)([Object(_.c)()],h.prototype,"orthoTop",void 0),Object(U.c)([Object(_.c)()],h.prototype,"fov",void 0),Object(U.c)([Object(_.c)()],h.prototype,"minZ",void 0),Object(U.c)([Object(_.c)()],h.prototype,"maxZ",void 0),Object(U.c)([Object(_.c)()],h.prototype,"inertia",void 0),Object(U.c)([Object(_.c)()],h.prototype,"mode",void 0),Object(U.c)([Object(_.c)()],h.prototype,"layerMask",void 0),Object(U.c)([Object(_.c)()],h.prototype,"fovMode",void 0),Object(U.c)([Object(_.c)()],h.prototype,"cameraRigMode",void 0),Object(U.c)([Object(_.c)()],h.prototype,"interaxialDistance",void 0),Object(U.c)([Object(_.c)()],h.prototype,"isStereoscopicSideBySide",void 0),h}(x.a)},function(Me,y,f){f.d(y,"a",function(){return A});var U=f(1),_=f(3),C=f(12),u=f(6),M=f(22),R=f(61),x=f(85),m=f(2),c=f(8),T=f(64),A=function(){function S(g,l,h){this.shadowDepthWrapper=null,this.allowShaderHotSwapping=!0,this.metadata=null,this.reservedDataStore=null,this.checkReadyOnEveryCall=!1,this.checkReadyOnlyOnce=!1,this.state="",this._alpha=1,this._backFaceCulling=!0,this.onCompiled=null,this.onError=null,this.getRenderTargetTextures=null,this.doNotSerialize=!1,this._storeEffectOnSubMeshes=!1,this.animations=null,this.onDisposeObservable=new u.c,this._onDisposeObserver=null,this._onUnBindObservable=null,this._onBindObserver=null,this._alphaMode=m.a.ALPHA_COMBINE,this._needDepthPrePass=!1,this.disableDepthWrite=!1,this.disableColorWrite=!1,this.forceDepthWrite=!1,this.depthFunction=0,this.separateCullingPass=!1,this._fogEnabled=!0,this.pointSize=1,this.zOffset=0,this._effect=null,this._useUBO=!1,this._fillMode=S.TriangleFillMode,this._cachedDepthWriteState=!1,this._cachedColorWriteState=!1,this._cachedDepthFunctionState=0,this._indexInSceneMaterialArray=-1,this.meshMap=null,this._forceAlphaTest=!1,this._transparencyMode=null,this.name=g;var v=1;for(this._scene=l||M.a.LastCreatedScene,this.id=g||C.b.RandomId();this._scene.getMaterialByID(this.id);)this.id=g+" "+v++;this.uniqueId=this._scene.getUniqueId(),this._scene.useRightHandedSystem?this.sideOrientation=S.ClockWiseSideOrientation:this.sideOrientation=S.CounterClockWiseSideOrientation,this._uniformBuffer=new x.a(this._scene.getEngine()),this._useUBO=this.getScene().getEngine().supportsUniformBuffers,h||this._scene.addMaterial(this),this._scene.useMaterialMeshMap&&(this.meshMap={})}return Object.defineProperty(S.prototype,"canRenderToMRT",{get:function(){return!1},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"alpha",{get:function(){return this._alpha},set:function(g){this._alpha!==g&&(this._alpha=g,this.markAsDirty(S.MiscDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"backFaceCulling",{get:function(){return this._backFaceCulling},set:function(g){this._backFaceCulling!==g&&(this._backFaceCulling=g,this.markAsDirty(S.TextureDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"hasRenderTargetTextures",{get:function(){return!1},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"onDispose",{set:function(g){this._onDisposeObserver&&this.onDisposeObservable.remove(this._onDisposeObserver),this._onDisposeObserver=this.onDisposeObservable.add(g)},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"onBindObservable",{get:function(){return this._onBindObservable||(this._onBindObservable=new u.c),this._onBindObservable},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"onBind",{set:function(g){this._onBindObserver&&this.onBindObservable.remove(this._onBindObserver),this._onBindObserver=this.onBindObservable.add(g)},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"onUnBindObservable",{get:function(){return this._onUnBindObservable||(this._onUnBindObservable=new u.c),this._onUnBindObservable},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"onEffectCreatedObservable",{get:function(){return this._onEffectCreatedObservable||(this._onEffectCreatedObservable=new u.c),this._onEffectCreatedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"alphaMode",{get:function(){return this._alphaMode},set:function(g){this._alphaMode!==g&&(this._alphaMode=g,this.markAsDirty(S.TextureDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"needDepthPrePass",{get:function(){return this._needDepthPrePass},set:function(g){this._needDepthPrePass!==g&&(this._needDepthPrePass=g,this._needDepthPrePass&&(this.checkReadyOnEveryCall=!0))},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"fogEnabled",{get:function(){return this._fogEnabled},set:function(g){this._fogEnabled!==g&&(this._fogEnabled=g,this.markAsDirty(S.MiscDirtyFlag))},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"wireframe",{get:function(){switch(this._fillMode){case S.WireFrameFillMode:case S.LineListDrawMode:case S.LineLoopDrawMode:case S.LineStripDrawMode:return!0}return this._scene.forceWireframe},set:function(g){this.fillMode=g?S.WireFrameFillMode:S.TriangleFillMode},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"pointsCloud",{get:function(){switch(this._fillMode){case S.PointFillMode:case S.PointListDrawMode:return!0}return this._scene.forcePointsCloud},set:function(g){this.fillMode=g?S.PointFillMode:S.TriangleFillMode},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"fillMode",{get:function(){return this._fillMode},set:function(g){this._fillMode!==g&&(this._fillMode=g,this.markAsDirty(S.MiscDirtyFlag))},enumerable:!1,configurable:!0}),S.prototype.toString=function(g){return"Name: "+this.name},S.prototype.getClassName=function(){return"Material"},Object.defineProperty(S.prototype,"isFrozen",{get:function(){return this.checkReadyOnlyOnce},enumerable:!1,configurable:!0}),S.prototype.freeze=function(){this.markDirty(),this.checkReadyOnlyOnce=!0},S.prototype.unfreeze=function(){this.markDirty(),this.checkReadyOnlyOnce=!1},S.prototype.isReady=function(g,l){return!0},S.prototype.isReadyForSubMesh=function(g,l,h){return!1},S.prototype.getEffect=function(){return this._effect},S.prototype.getScene=function(){return this._scene},Object.defineProperty(S.prototype,"transparencyMode",{get:function(){return this._transparencyMode},set:function(g){this._transparencyMode!==g&&(this._transparencyMode=g,this._forceAlphaTest=g===S.MATERIAL_ALPHATESTANDBLEND,this._markAllSubMeshesAsTexturesAndMiscDirty())},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"_disableAlphaBlending",{get:function(){return this._transparencyMode===S.MATERIAL_OPAQUE||this._transparencyMode===S.MATERIAL_ALPHATEST},enumerable:!1,configurable:!0}),S.prototype.needAlphaBlending=function(){return!this._disableAlphaBlending&&this.alpha<1},S.prototype.needAlphaBlendingForMesh=function(g){return!(this._disableAlphaBlending&&g.visibility>=1)&&(this.needAlphaBlending()||g.visibility<1||g.hasVertexAlpha)},S.prototype.needAlphaTesting=function(){return!!this._forceAlphaTest},S.prototype._shouldTurnAlphaTestOn=function(g){return!this.needAlphaBlendingForMesh(g)&&this.needAlphaTesting()},S.prototype.getAlphaTestTexture=function(){return null},S.prototype.markDirty=function(){for(var g=0,l=this.getScene().meshes;g<l.length;g++){var h=l[g];if(h.subMeshes)for(var v=0,E=h.subMeshes;v<E.length;v++){var D=E[v];D.getMaterial()===this&&D.effect&&(D.effect._wasPreviouslyReady=!1)}}},S.prototype._preBind=function(g,l){l===void 0&&(l=null);var h=this._scene.getEngine(),v=(l??this.sideOrientation)===S.ClockWiseSideOrientation;return h.enableEffect(g||this._effect),h.setState(this.backFaceCulling,this.zOffset,!1,v),v},S.prototype.bind=function(g,l){},S.prototype.bindForSubMesh=function(g,l,h){},S.prototype.bindOnlyWorldMatrix=function(g){},S.prototype.bindSceneUniformBuffer=function(g,l){l.bindToEffect(g,"Scene")},S.prototype.bindView=function(g){this._useUBO?this.bindSceneUniformBuffer(g,this.getScene().getSceneUniformBuffer()):g.setMatrix("view",this.getScene().getViewMatrix())},S.prototype.bindViewProjection=function(g){this._useUBO?this.bindSceneUniformBuffer(g,this.getScene().getSceneUniformBuffer()):g.setMatrix("viewProjection",this.getScene().getTransformMatrix())},S.prototype._afterBind=function(g){if(this._scene._cachedMaterial=this,this._scene._cachedVisibility=g?g.visibility:1,this._onBindObservable&&g&&this._onBindObservable.notifyObservers(g),this.disableDepthWrite){var l=this._scene.getEngine();this._cachedDepthWriteState=l.getDepthWrite(),l.setDepthWrite(!1)}this.disableColorWrite&&(l=this._scene.getEngine(),this._cachedColorWriteState=l.getColorWrite(),l.setColorWrite(!1)),this.depthFunction!==0&&(l=this._scene.getEngine(),this._cachedDepthFunctionState=l.getDepthFunction()||0,l.setDepthFunction(this.depthFunction))},S.prototype.unbind=function(){this._onUnBindObservable&&this._onUnBindObservable.notifyObservers(this),this.depthFunction!==0&&this._scene.getEngine().setDepthFunction(this._cachedDepthFunctionState),this.disableDepthWrite&&this._scene.getEngine().setDepthWrite(this._cachedDepthWriteState),this.disableColorWrite&&this._scene.getEngine().setColorWrite(this._cachedColorWriteState)},S.prototype.getActiveTextures=function(){return[]},S.prototype.hasTexture=function(g){return!1},S.prototype.clone=function(g){return null},S.prototype.getBindedMeshes=function(){var g=this;if(this.meshMap){var l=new Array;for(var h in this.meshMap){var v=this.meshMap[h];v&&l.push(v)}return l}return this._scene.meshes.filter(function(E){return E.material===g})},S.prototype.forceCompilation=function(g,l,h,v){var E=this,D=Object(U.a)({clipPlane:!1,useInstances:!1},h),w=this.getScene(),N=this.allowShaderHotSwapping;this.allowShaderHotSwapping=!1;var I=function(){if(E._scene&&E._scene.getEngine()){var V=w.clipPlane;if(D.clipPlane&&(w.clipPlane=new T.a(0,0,0,1)),E._storeEffectOnSubMeshes){var X=!0,j=null;if(g.subMeshes){var ne=new R.a(0,0,0,0,0,g,void 0,!1,!1);ne._materialDefines&&(ne._materialDefines._renderId=-1),E.isReadyForSubMesh(g,ne,D.useInstances)||(ne.effect&&ne.effect.getCompilationError()&&ne.effect.allFallbacksProcessed()?j=ne.effect.getCompilationError():(X=!1,setTimeout(I,16)))}X&&(E.allowShaderHotSwapping=N,j&&v&&v(j),l&&l(E))}else E.isReady()?(E.allowShaderHotSwapping=N,l&&l(E)):setTimeout(I,16);D.clipPlane&&(w.clipPlane=V)}};I()},S.prototype.forceCompilationAsync=function(g,l){var h=this;return new Promise(function(v,E){h.forceCompilation(g,function(){v()},l,function(D){E(D)})})},S.prototype.markAsDirty=function(g){this.getScene().blockMaterialDirtyMechanism||(S._DirtyCallbackArray.length=0,g&S.TextureDirtyFlag&&S._DirtyCallbackArray.push(S._TextureDirtyCallBack),g&S.LightDirtyFlag&&S._DirtyCallbackArray.push(S._LightsDirtyCallBack),g&S.FresnelDirtyFlag&&S._DirtyCallbackArray.push(S._FresnelDirtyCallBack),g&S.AttributesDirtyFlag&&S._DirtyCallbackArray.push(S._AttributeDirtyCallBack),g&S.MiscDirtyFlag&&S._DirtyCallbackArray.push(S._MiscDirtyCallBack),g&S.PrePassDirtyFlag&&S._DirtyCallbackArray.push(S._PrePassDirtyCallBack),S._DirtyCallbackArray.length&&this._markAllSubMeshesAsDirty(S._RunDirtyCallBacks),this.getScene().resetCachedMaterial())},S.prototype._markAllSubMeshesAsDirty=function(g){if(!this.getScene().blockMaterialDirtyMechanism)for(var l=0,h=this.getScene().meshes;l<h.length;l++){var v=h[l];if(v.subMeshes)for(var E=0,D=v.subMeshes;E<D.length;E++){var w=D[E];w.getMaterial()===this&&w._materialDefines&&g(w._materialDefines)}}},S.prototype._markScenePrePassDirty=function(){if(!this.getScene().blockMaterialDirtyMechanism){var g=this.getScene().enablePrePassRenderer();g&&g.markAsDirty()}},S.prototype._markAllSubMeshesAsAllDirty=function(){this._markAllSubMeshesAsDirty(S._AllDirtyCallBack)},S.prototype._markAllSubMeshesAsImageProcessingDirty=function(){this._markAllSubMeshesAsDirty(S._ImageProcessingDirtyCallBack)},S.prototype._markAllSubMeshesAsTexturesDirty=function(){this._markAllSubMeshesAsDirty(S._TextureDirtyCallBack)},S.prototype._markAllSubMeshesAsFresnelDirty=function(){this._markAllSubMeshesAsDirty(S._FresnelDirtyCallBack)},S.prototype._markAllSubMeshesAsFresnelAndMiscDirty=function(){this._markAllSubMeshesAsDirty(S._FresnelAndMiscDirtyCallBack)},S.prototype._markAllSubMeshesAsLightsDirty=function(){this._markAllSubMeshesAsDirty(S._LightsDirtyCallBack)},S.prototype._markAllSubMeshesAsAttributesDirty=function(){this._markAllSubMeshesAsDirty(S._AttributeDirtyCallBack)},S.prototype._markAllSubMeshesAsMiscDirty=function(){this._markAllSubMeshesAsDirty(S._MiscDirtyCallBack)},S.prototype._markAllSubMeshesAsPrePassDirty=function(){this._markAllSubMeshesAsDirty(S._MiscDirtyCallBack)},S.prototype._markAllSubMeshesAsTexturesAndMiscDirty=function(){this._markAllSubMeshesAsDirty(S._TextureAndMiscDirtyCallBack)},S.prototype.setPrePassRenderer=function(g){return!1},S.prototype.dispose=function(g,l,h){var v=this.getScene();if(v.stopAnimation(this),v.freeProcessedMaterials(),v.removeMaterial(this),h!==!0)if(this.meshMap)for(var E in this.meshMap)(N=this.meshMap[E])&&(N.material=null,this.releaseVertexArrayObject(N,g));else for(var D=0,w=v.meshes;D<w.length;D++){var N;(N=w[D]).material!==this||N.sourceMesh||(N.material=null,this.releaseVertexArrayObject(N,g))}this._uniformBuffer.dispose(),g&&this._effect&&(this._storeEffectOnSubMeshes||this._effect.dispose(),this._effect=null),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear(),this._onBindObservable&&this._onBindObservable.clear(),this._onUnBindObservable&&this._onUnBindObservable.clear(),this._onEffectCreatedObservable&&this._onEffectCreatedObservable.clear()},S.prototype.releaseVertexArrayObject=function(g,l){if(g.geometry){var h=g.geometry;if(this._storeEffectOnSubMeshes)for(var v=0,E=g.subMeshes;v<E.length;v++){var D=E[v];h._releaseVertexArrayObject(D._materialEffect),l&&D._materialEffect&&D._materialEffect.dispose()}else h._releaseVertexArrayObject(this._effect)}},S.prototype.serialize=function(){return _.a.Serialize(this)},S.Parse=function(g,l,h){if(g.customType){if(g.customType==="BABYLON.PBRMaterial"&&g.overloadedAlbedo&&(g.customType="BABYLON.LegacyPBRMaterial",!BABYLON.LegacyPBRMaterial))return c.a.Error("Your scene is trying to load a legacy version of the PBRMaterial, please, include it from the materials library."),null}else g.customType="BABYLON.StandardMaterial";return C.b.Instantiate(g.customType).Parse(g,l,h)},S.TriangleFillMode=m.a.MATERIAL_TriangleFillMode,S.WireFrameFillMode=m.a.MATERIAL_WireFrameFillMode,S.PointFillMode=m.a.MATERIAL_PointFillMode,S.PointListDrawMode=m.a.MATERIAL_PointListDrawMode,S.LineListDrawMode=m.a.MATERIAL_LineListDrawMode,S.LineLoopDrawMode=m.a.MATERIAL_LineLoopDrawMode,S.LineStripDrawMode=m.a.MATERIAL_LineStripDrawMode,S.TriangleStripDrawMode=m.a.MATERIAL_TriangleStripDrawMode,S.TriangleFanDrawMode=m.a.MATERIAL_TriangleFanDrawMode,S.ClockWiseSideOrientation=m.a.MATERIAL_ClockWiseSideOrientation,S.CounterClockWiseSideOrientation=m.a.MATERIAL_CounterClockWiseSideOrientation,S.TextureDirtyFlag=m.a.MATERIAL_TextureDirtyFlag,S.LightDirtyFlag=m.a.MATERIAL_LightDirtyFlag,S.FresnelDirtyFlag=m.a.MATERIAL_FresnelDirtyFlag,S.AttributesDirtyFlag=m.a.MATERIAL_AttributesDirtyFlag,S.MiscDirtyFlag=m.a.MATERIAL_MiscDirtyFlag,S.PrePassDirtyFlag=m.a.MATERIAL_PrePassDirtyFlag,S.AllDirtyFlag=m.a.MATERIAL_AllDirtyFlag,S.MATERIAL_OPAQUE=0,S.MATERIAL_ALPHATEST=1,S.MATERIAL_ALPHABLEND=2,S.MATERIAL_ALPHATESTANDBLEND=3,S.MATERIAL_NORMALBLENDMETHOD_WHITEOUT=0,S.MATERIAL_NORMALBLENDMETHOD_RNM=1,S._AllDirtyCallBack=function(g){return g.markAllAsDirty()},S._ImageProcessingDirtyCallBack=function(g){return g.markAsImageProcessingDirty()},S._TextureDirtyCallBack=function(g){return g.markAsTexturesDirty()},S._FresnelDirtyCallBack=function(g){return g.markAsFresnelDirty()},S._MiscDirtyCallBack=function(g){return g.markAsMiscDirty()},S._PrePassDirtyCallBack=function(g){return g.markAsPrePassDirty()},S._LightsDirtyCallBack=function(g){return g.markAsLightDirty()},S._AttributeDirtyCallBack=function(g){return g.markAsAttributesDirty()},S._FresnelAndMiscDirtyCallBack=function(g){S._FresnelDirtyCallBack(g),S._MiscDirtyCallBack(g)},S._TextureAndMiscDirtyCallBack=function(g){S._TextureDirtyCallBack(g),S._MiscDirtyCallBack(g)},S._DirtyCallbackArray=[],S._RunDirtyCallBacks=function(g){for(var l=0,h=S._DirtyCallbackArray;l<h.length;l++)(0,h[l])(g)},Object(U.c)([Object(_.c)()],S.prototype,"id",void 0),Object(U.c)([Object(_.c)()],S.prototype,"uniqueId",void 0),Object(U.c)([Object(_.c)()],S.prototype,"name",void 0),Object(U.c)([Object(_.c)()],S.prototype,"checkReadyOnEveryCall",void 0),Object(U.c)([Object(_.c)()],S.prototype,"checkReadyOnlyOnce",void 0),Object(U.c)([Object(_.c)()],S.prototype,"state",void 0),Object(U.c)([Object(_.c)("alpha")],S.prototype,"_alpha",void 0),Object(U.c)([Object(_.c)("backFaceCulling")],S.prototype,"_backFaceCulling",void 0),Object(U.c)([Object(_.c)()],S.prototype,"sideOrientation",void 0),Object(U.c)([Object(_.c)("alphaMode")],S.prototype,"_alphaMode",void 0),Object(U.c)([Object(_.c)()],S.prototype,"_needDepthPrePass",void 0),Object(U.c)([Object(_.c)()],S.prototype,"disableDepthWrite",void 0),Object(U.c)([Object(_.c)()],S.prototype,"disableColorWrite",void 0),Object(U.c)([Object(_.c)()],S.prototype,"forceDepthWrite",void 0),Object(U.c)([Object(_.c)()],S.prototype,"depthFunction",void 0),Object(U.c)([Object(_.c)()],S.prototype,"separateCullingPass",void 0),Object(U.c)([Object(_.c)("fogEnabled")],S.prototype,"_fogEnabled",void 0),Object(U.c)([Object(_.c)()],S.prototype,"pointSize",void 0),Object(U.c)([Object(_.c)()],S.prototype,"zOffset",void 0),Object(U.c)([Object(_.c)()],S.prototype,"pointsCloud",null),Object(U.c)([Object(_.c)()],S.prototype,"fillMode",null),Object(U.c)([Object(_.c)()],S.prototype,"transparencyMode",null),S}()},function(Me,y,f){f.d(y,"a",function(){return w});var U=f(22),_=f(5),C=f(21),u=f(6),M=f(141),R=f(142),x=f(143),m=f(2),c=f(27),T=f(8),A=f(38),S=function(){function N(){}return N.prototype.postProcessor=function(I,V,X,j){return j.getCaps().drawBuffersExtension||(I=I.replace(/#extension.+GL_EXT_draw_buffers.+(enable|require)/g,"")),I},N}(),g=f(118),l=f(88),h=f(144),v=f(70),E=f(74),D=function(){},w=function(){function N(I,V,X,j){var ne=this;j===void 0&&(j=!1),this.forcePOTTextures=!1,this.isFullscreen=!1,this.cullBackFaces=!0,this.renderEvenInBackground=!0,this.preventCacheWipeBetweenFrames=!1,this.validateShaderPrograms=!1,this.useReverseDepthBuffer=!1,this.disableUniformBuffers=!1,this._uniformBuffers=new Array,this._webGLVersion=1,this._windowIsBackground=!1,this._highPrecisionShadersAllowed=!0,this._badOS=!1,this._badDesktopOS=!1,this._renderingQueueLaunched=!1,this._activeRenderLoops=new Array,this.onContextLostObservable=new u.c,this.onContextRestoredObservable=new u.c,this._contextWasLost=!1,this._doNotHandleContextLost=!1,this.disableVertexArrayObjects=!1,this._colorWrite=!0,this._colorWriteChanged=!0,this._depthCullingState=new M.a,this._stencilState=new R.a,this._alphaState=new x.a,this._alphaMode=m.a.ALPHA_ADD,this._alphaEquation=m.a.ALPHA_DISABLE,this._internalTexturesCache=new Array,this._activeChannel=0,this._currentTextureChannel=-1,this._boundTexturesCache={},this._compiledEffects={},this._vertexAttribArraysEnabled=[],this._uintIndicesCurrentlySet=!1,this._currentBoundBuffer=new Array,this._currentFramebuffer=null,this._dummyFramebuffer=null,this._currentBufferPointers=new Array,this._currentInstanceLocations=new Array,this._currentInstanceBuffers=new Array,this._vaoRecordInProgress=!1,this._mustWipeVertexAttributes=!1,this._nextFreeTextureSlots=new Array,this._maxSimultaneousTextures=0,this._activeRequests=new Array,this._transformTextureUrl=null,this.hostInformation={isMobile:!1},this.premultipliedAlpha=!0,this.onBeforeTextureInitObservable=new u.c,this._viewportCached={x:0,y:0,z:0,w:0},this._unpackFlipYCached=null,this.enableUnpackFlipYCached=!0,this._getDepthStencilBuffer=function(W,q,he,ge,me,_e){var be=ne._gl,Pe=be.createRenderbuffer();return be.bindRenderbuffer(be.RENDERBUFFER,Pe),he>1&&be.renderbufferStorageMultisample?be.renderbufferStorageMultisample(be.RENDERBUFFER,he,me,W,q):be.renderbufferStorage(be.RENDERBUFFER,ge,W,q),be.framebufferRenderbuffer(be.FRAMEBUFFER,_e,be.RENDERBUFFER,Pe),be.bindRenderbuffer(be.RENDERBUFFER,null),Pe},this._boundUniforms={};var te=null;if(I){if(X=X||{},E.a.SetMatrixPrecision(!!X.useHighPrecisionMatrix),I.getContext){if(te=I,this._renderingCanvas=te,V!=null&&(X.antialias=V),X.deterministicLockstep===void 0&&(X.deterministicLockstep=!1),X.lockstepMaxSteps===void 0&&(X.lockstepMaxSteps=4),X.timeStep===void 0&&(X.timeStep=1/60),X.preserveDrawingBuffer===void 0&&(X.preserveDrawingBuffer=!1),X.audioEngine===void 0&&(X.audioEngine=!0),X.stencil===void 0&&(X.stencil=!0),X.premultipliedAlpha===!1&&(this.premultipliedAlpha=!1),X.xrCompatible===void 0&&(X.xrCompatible=!0),this._doNotHandleContextLost=!!X.doNotHandleContextLost,navigator&&navigator.userAgent){var de=navigator.userAgent;this.hostInformation.isMobile=de.indexOf("Mobile")!==-1;for(var pe=0,ae=N.ExceptionList;pe<ae.length;pe++){var ee=ae[pe],K=ee.key,$=ee.targets;if(new RegExp(K).test(de)){if(ee.capture&&ee.captureConstraint){var L=ee.capture,G=ee.captureConstraint,Q=new RegExp(L).exec(de);if(Q&&Q.length>0&&parseInt(Q[Q.length-1])>=G)continue}for(var oe=0,re=$;oe<re.length;oe++)switch(re[oe]){case"uniformBuffer":this.disableUniformBuffers=!0;break;case"vao":this.disableVertexArrayObjects=!0}}}}if(this._doNotHandleContextLost||(this._onContextLost=function(W){W.preventDefault(),ne._contextWasLost=!0,T.a.Warn("WebGL context lost."),ne.onContextLostObservable.notifyObservers(ne)},this._onContextRestored=function(){setTimeout(function(){ne._initGLContext(),ne._rebuildEffects(),ne._rebuildInternalTextures(),ne._rebuildBuffers(),ne.wipeCaches(!0),T.a.Warn("WebGL context successfully restored."),ne.onContextRestoredObservable.notifyObservers(ne),ne._contextWasLost=!1},0)},te.addEventListener("webglcontextlost",this._onContextLost,!1),te.addEventListener("webglcontextrestored",this._onContextRestored,!1),X.powerPreference="high-performance"),!X.disableWebGL2Support)try{this._gl=te.getContext("webgl2",X)||te.getContext("experimental-webgl2",X),this._gl&&(this._webGLVersion=2,this._gl.deleteQuery||(this._webGLVersion=1))}catch{}if(!this._gl){if(!te)throw new Error("The provided canvas is null or undefined.");try{this._gl=te.getContext("webgl",X)||te.getContext("experimental-webgl",X)}catch{throw new Error("WebGL not supported")}}if(!this._gl)throw new Error("WebGL not supported")}else{this._gl=I,this._renderingCanvas=this._gl.canvas,this._gl.renderbufferStorageMultisample&&(this._webGLVersion=2);var Y=this._gl.getContextAttributes();Y&&(X.stencil=Y.stencil)}this._gl.pixelStorei(this._gl.UNPACK_COLORSPACE_CONVERSION_WEBGL,this._gl.NONE),X.useHighPrecisionFloats!==void 0&&(this._highPrecisionShadersAllowed=X.useHighPrecisionFloats);var k=A.a.IsWindowObjectExist()&&window.devicePixelRatio||1,H=X.limitDeviceRatio||k;this._hardwareScalingLevel=j?1/Math.min(H,k):1,this.resize(),this._isStencilEnable=!!X.stencil,this._initGLContext();for(var Z=0;Z<this._caps.maxVertexAttribs;Z++)this._currentBufferPointers[Z]=new D;this.webGLVersion>1?this._shaderProcessor=new g.a:this._shaderProcessor=new S,this._badOS=/iPad/i.test(navigator.userAgent)||/iPhone/i.test(navigator.userAgent),this._badDesktopOS=/^((?!chrome|android).)*safari/i.test(navigator.userAgent),this._creationOptions=X,console.log("Babylon.js v"+N.Version+" - "+this.description)}}return Object.defineProperty(N,"NpmPackage",{get:function(){return"babylonjs@4.2.2"},enumerable:!1,configurable:!0}),Object.defineProperty(N,"Version",{get:function(){return"4.2.2"},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"description",{get:function(){var I="WebGL"+this.webGLVersion;return this._caps.parallelShaderCompile&&(I+=" - Parallel shader compilation"),I},enumerable:!1,configurable:!0}),Object.defineProperty(N,"ShadersRepository",{get:function(){return _.a.ShadersRepository},set:function(I){_.a.ShadersRepository=I},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"supportsUniformBuffers",{get:function(){return this.webGLVersion>1&&!this.disableUniformBuffers},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"_shouldUseHighPrecisionShader",{get:function(){return!(!this._caps.highPrecisionShaderSupported||!this._highPrecisionShadersAllowed)},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"needPOTTextures",{get:function(){return this._webGLVersion<2||this.forcePOTTextures},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"doNotHandleContextLost",{get:function(){return this._doNotHandleContextLost},set:function(I){this._doNotHandleContextLost=I},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"_supportsHardwareTextureRescaling",{get:function(){return!1},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"framebufferDimensionsObject",{set:function(I){this._framebufferDimensionsObject=I},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"currentViewport",{get:function(){return this._cachedViewport},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"emptyTexture",{get:function(){return this._emptyTexture||(this._emptyTexture=this.createRawTexture(new Uint8Array(4),1,1,m.a.TEXTUREFORMAT_RGBA,!1,!1,m.a.TEXTURE_NEAREST_SAMPLINGMODE)),this._emptyTexture},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"emptyTexture3D",{get:function(){return this._emptyTexture3D||(this._emptyTexture3D=this.createRawTexture3D(new Uint8Array(4),1,1,1,m.a.TEXTUREFORMAT_RGBA,!1,!1,m.a.TEXTURE_NEAREST_SAMPLINGMODE)),this._emptyTexture3D},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"emptyTexture2DArray",{get:function(){return this._emptyTexture2DArray||(this._emptyTexture2DArray=this.createRawTexture2DArray(new Uint8Array(4),1,1,1,m.a.TEXTUREFORMAT_RGBA,!1,!1,m.a.TEXTURE_NEAREST_SAMPLINGMODE)),this._emptyTexture2DArray},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"emptyCubeTexture",{get:function(){if(!this._emptyCubeTexture){var I=new Uint8Array(4),V=[I,I,I,I,I,I];this._emptyCubeTexture=this.createRawCubeTexture(V,1,m.a.TEXTUREFORMAT_RGBA,m.a.TEXTURETYPE_UNSIGNED_INT,!1,!1,m.a.TEXTURE_NEAREST_SAMPLINGMODE)}return this._emptyCubeTexture},enumerable:!1,configurable:!0}),N.prototype._rebuildInternalTextures=function(){for(var I=0,V=this._internalTexturesCache.slice();I<V.length;I++)V[I]._rebuild()},N.prototype._rebuildEffects=function(){for(var I in this._compiledEffects)this._compiledEffects[I]._prepareEffect();_.a.ResetCache()},N.prototype.areAllEffectsReady=function(){for(var I in this._compiledEffects)if(!this._compiledEffects[I].isReady())return!1;return!0},N.prototype._rebuildBuffers=function(){for(var I=0,V=this._uniformBuffers;I<V.length;I++)V[I]._rebuild()},N.prototype._initGLContext=function(){this._caps={maxTexturesImageUnits:this._gl.getParameter(this._gl.MAX_TEXTURE_IMAGE_UNITS),maxCombinedTexturesImageUnits:this._gl.getParameter(this._gl.MAX_COMBINED_TEXTURE_IMAGE_UNITS),maxVertexTextureImageUnits:this._gl.getParameter(this._gl.MAX_VERTEX_TEXTURE_IMAGE_UNITS),maxTextureSize:this._gl.getParameter(this._gl.MAX_TEXTURE_SIZE),maxSamples:this._webGLVersion>1?this._gl.getParameter(this._gl.MAX_SAMPLES):1,maxCubemapTextureSize:this._gl.getParameter(this._gl.MAX_CUBE_MAP_TEXTURE_SIZE),maxRenderTextureSize:this._gl.getParameter(this._gl.MAX_RENDERBUFFER_SIZE),maxVertexAttribs:this._gl.getParameter(this._gl.MAX_VERTEX_ATTRIBS),maxVaryingVectors:this._gl.getParameter(this._gl.MAX_VARYING_VECTORS),maxFragmentUniformVectors:this._gl.getParameter(this._gl.MAX_FRAGMENT_UNIFORM_VECTORS),maxVertexUniformVectors:this._gl.getParameter(this._gl.MAX_VERTEX_UNIFORM_VECTORS),parallelShaderCompile:this._gl.getExtension("KHR_parallel_shader_compile"),standardDerivatives:this._webGLVersion>1||this._gl.getExtension("OES_standard_derivatives")!==null,maxAnisotropy:1,astc:this._gl.getExtension("WEBGL_compressed_texture_astc")||this._gl.getExtension("WEBKIT_WEBGL_compressed_texture_astc"),bptc:this._gl.getExtension("EXT_texture_compression_bptc")||this._gl.getExtension("WEBKIT_EXT_texture_compression_bptc"),s3tc:this._gl.getExtension("WEBGL_compressed_texture_s3tc")||this._gl.getExtension("WEBKIT_WEBGL_compressed_texture_s3tc"),pvrtc:this._gl.getExtension("WEBGL_compressed_texture_pvrtc")||this._gl.getExtension("WEBKIT_WEBGL_compressed_texture_pvrtc"),etc1:this._gl.getExtension("WEBGL_compressed_texture_etc1")||this._gl.getExtension("WEBKIT_WEBGL_compressed_texture_etc1"),etc2:this._gl.getExtension("WEBGL_compressed_texture_etc")||this._gl.getExtension("WEBKIT_WEBGL_compressed_texture_etc")||this._gl.getExtension("WEBGL_compressed_texture_es3_0"),textureAnisotropicFilterExtension:this._gl.getExtension("EXT_texture_filter_anisotropic")||this._gl.getExtension("WEBKIT_EXT_texture_filter_anisotropic")||this._gl.getExtension("MOZ_EXT_texture_filter_anisotropic"),uintIndices:this._webGLVersion>1||this._gl.getExtension("OES_element_index_uint")!==null,fragmentDepthSupported:this._webGLVersion>1||this._gl.getExtension("EXT_frag_depth")!==null,highPrecisionShaderSupported:!1,timerQuery:this._gl.getExtension("EXT_disjoint_timer_query_webgl2")||this._gl.getExtension("EXT_disjoint_timer_query"),canUseTimestampForTimerQuery:!1,drawBuffersExtension:!1,maxMSAASamples:1,colorBufferFloat:this._webGLVersion>1&&this._gl.getExtension("EXT_color_buffer_float"),textureFloat:!!(this._webGLVersion>1||this._gl.getExtension("OES_texture_float")),textureHalfFloat:!!(this._webGLVersion>1||this._gl.getExtension("OES_texture_half_float")),textureHalfFloatRender:!1,textureFloatLinearFiltering:!1,textureFloatRender:!1,textureHalfFloatLinearFiltering:!1,vertexArrayObject:!1,instancedArrays:!1,textureLOD:!!(this._webGLVersion>1||this._gl.getExtension("EXT_shader_texture_lod")),blendMinMax:!1,multiview:this._gl.getExtension("OVR_multiview2"),oculusMultiview:this._gl.getExtension("OCULUS_multiview"),depthTextureExtension:!1},this._glVersion=this._gl.getParameter(this._gl.VERSION);var I=this._gl.getExtension("WEBGL_debug_renderer_info");if(I!=null&&(this._glRenderer=this._gl.getParameter(I.UNMASKED_RENDERER_WEBGL),this._glVendor=this._gl.getParameter(I.UNMASKED_VENDOR_WEBGL)),this._glVendor||(this._glVendor="Unknown vendor"),this._glRenderer||(this._glRenderer="Unknown renderer"),this._gl.HALF_FLOAT_OES!==36193&&(this._gl.HALF_FLOAT_OES=36193),this._gl.RGBA16F!==34842&&(this._gl.RGBA16F=34842),this._gl.RGBA32F!==34836&&(this._gl.RGBA32F=34836),this._gl.DEPTH24_STENCIL8!==35056&&(this._gl.DEPTH24_STENCIL8=35056),this._caps.timerQuery&&(this._webGLVersion===1&&(this._gl.getQuery=this._caps.timerQuery.getQueryEXT.bind(this._caps.timerQuery)),this._caps.canUseTimestampForTimerQuery=this._gl.getQuery(this._caps.timerQuery.TIMESTAMP_EXT,this._caps.timerQuery.QUERY_COUNTER_BITS_EXT)>0),this._caps.maxAnisotropy=this._caps.textureAnisotropicFilterExtension?this._gl.getParameter(this._caps.textureAnisotropicFilterExtension.MAX_TEXTURE_MAX_ANISOTROPY_EXT):0,this._caps.textureFloatLinearFiltering=!(!this._caps.textureFloat||!this._gl.getExtension("OES_texture_float_linear")),this._caps.textureFloatRender=!(!this._caps.textureFloat||!this._canRenderToFloatFramebuffer()),this._caps.textureHalfFloatLinearFiltering=!!(this._webGLVersion>1||this._caps.textureHalfFloat&&this._gl.getExtension("OES_texture_half_float_linear")),this._webGLVersion>1&&this._gl.HALF_FLOAT_OES!==5131&&(this._gl.HALF_FLOAT_OES=5131),this._caps.textureHalfFloatRender=this._caps.textureHalfFloat&&this._canRenderToHalfFloatFramebuffer(),this._webGLVersion>1)this._caps.drawBuffersExtension=!0,this._caps.maxMSAASamples=this._gl.getParameter(this._gl.MAX_SAMPLES);else{var V=this._gl.getExtension("WEBGL_draw_buffers");if(V!==null){this._caps.drawBuffersExtension=!0,this._gl.drawBuffers=V.drawBuffersWEBGL.bind(V),this._gl.DRAW_FRAMEBUFFER=this._gl.FRAMEBUFFER;for(var X=0;X<16;X++)this._gl["COLOR_ATTACHMENT"+X+"_WEBGL"]=V["COLOR_ATTACHMENT"+X+"_WEBGL"]}}if(this._webGLVersion>1)this._caps.depthTextureExtension=!0;else{var j=this._gl.getExtension("WEBGL_depth_texture");j!=null&&(this._caps.depthTextureExtension=!0,this._gl.UNSIGNED_INT_24_8=j.UNSIGNED_INT_24_8_WEBGL)}if(this.disableVertexArrayObjects)this._caps.vertexArrayObject=!1;else if(this._webGLVersion>1)this._caps.vertexArrayObject=!0;else{var ne=this._gl.getExtension("OES_vertex_array_object");ne!=null&&(this._caps.vertexArrayObject=!0,this._gl.createVertexArray=ne.createVertexArrayOES.bind(ne),this._gl.bindVertexArray=ne.bindVertexArrayOES.bind(ne),this._gl.deleteVertexArray=ne.deleteVertexArrayOES.bind(ne))}if(this._webGLVersion>1)this._caps.instancedArrays=!0;else{var te=this._gl.getExtension("ANGLE_instanced_arrays");te!=null?(this._caps.instancedArrays=!0,this._gl.drawArraysInstanced=te.drawArraysInstancedANGLE.bind(te),this._gl.drawElementsInstanced=te.drawElementsInstancedANGLE.bind(te),this._gl.vertexAttribDivisor=te.vertexAttribDivisorANGLE.bind(te)):this._caps.instancedArrays=!1}if(this._gl.getShaderPrecisionFormat){var de=this._gl.getShaderPrecisionFormat(this._gl.VERTEX_SHADER,this._gl.HIGH_FLOAT),pe=this._gl.getShaderPrecisionFormat(this._gl.FRAGMENT_SHADER,this._gl.HIGH_FLOAT);de&&pe&&(this._caps.highPrecisionShaderSupported=de.precision!==0&&pe.precision!==0)}if(this._webGLVersion>1)this._caps.blendMinMax=!0;else{var ae=this._gl.getExtension("EXT_blend_minmax");ae!=null&&(this._caps.blendMinMax=!0,this._gl.MAX=ae.MAX_EXT,this._gl.MIN=ae.MIN_EXT)}this._depthCullingState.depthTest=!0,this._depthCullingState.depthFunc=this._gl.LEQUAL,this._depthCullingState.depthMask=!0,this._maxSimultaneousTextures=this._caps.maxCombinedTexturesImageUnits;for(var ee=0;ee<this._maxSimultaneousTextures;ee++)this._nextFreeTextureSlots.push(ee)},Object.defineProperty(N.prototype,"webGLVersion",{get:function(){return this._webGLVersion},enumerable:!1,configurable:!0}),N.prototype.getClassName=function(){return"ThinEngine"},Object.defineProperty(N.prototype,"isStencilEnable",{get:function(){return this._isStencilEnable},enumerable:!1,configurable:!0}),N.prototype._prepareWorkingCanvas=function(){if(!this._workingCanvas){this._workingCanvas=v.a.CreateCanvas(1,1);var I=this._workingCanvas.getContext("2d");I&&(this._workingContext=I)}},N.prototype.resetTextureCache=function(){for(var I in this._boundTexturesCache)this._boundTexturesCache.hasOwnProperty(I)&&(this._boundTexturesCache[I]=null);this._currentTextureChannel=-1},N.prototype.getGlInfo=function(){return{vendor:this._glVendor,renderer:this._glRenderer,version:this._glVersion}},N.prototype.setHardwareScalingLevel=function(I){this._hardwareScalingLevel=I,this.resize()},N.prototype.getHardwareScalingLevel=function(){return this._hardwareScalingLevel},N.prototype.getLoadedTexturesCache=function(){return this._internalTexturesCache},N.prototype.getCaps=function(){return this._caps},N.prototype.stopRenderLoop=function(I){if(I){var V=this._activeRenderLoops.indexOf(I);V>=0&&this._activeRenderLoops.splice(V,1)}else this._activeRenderLoops=[]},N.prototype._renderLoop=function(){if(!this._contextWasLost){var I=!0;if(!this.renderEvenInBackground&&this._windowIsBackground&&(I=!1),I){this.beginFrame();for(var V=0;V<this._activeRenderLoops.length;V++)(0,this._activeRenderLoops[V])();this.endFrame()}}this._activeRenderLoops.length>0?this._frameHandler=this._queueNewFrame(this._boundRenderFunction,this.getHostWindow()):this._renderingQueueLaunched=!1},N.prototype.getRenderingCanvas=function(){return this._renderingCanvas},N.prototype.getHostWindow=function(){return A.a.IsWindowObjectExist()?this._renderingCanvas&&this._renderingCanvas.ownerDocument&&this._renderingCanvas.ownerDocument.defaultView?this._renderingCanvas.ownerDocument.defaultView:window:null},N.prototype.getRenderWidth=function(I){return I===void 0&&(I=!1),!I&&this._currentRenderTarget?this._currentRenderTarget.width:this._framebufferDimensionsObject?this._framebufferDimensionsObject.framebufferWidth:this._gl.drawingBufferWidth},N.prototype.getRenderHeight=function(I){return I===void 0&&(I=!1),!I&&this._currentRenderTarget?this._currentRenderTarget.height:this._framebufferDimensionsObject?this._framebufferDimensionsObject.framebufferHeight:this._gl.drawingBufferHeight},N.prototype._queueNewFrame=function(I,V){return N.QueueNewFrame(I,V)},N.prototype.runRenderLoop=function(I){this._activeRenderLoops.indexOf(I)===-1&&(this._activeRenderLoops.push(I),this._renderingQueueLaunched||(this._renderingQueueLaunched=!0,this._boundRenderFunction=this._renderLoop.bind(this),this._frameHandler=this._queueNewFrame(this._boundRenderFunction,this.getHostWindow())))},N.prototype.clear=function(I,V,X,j){j===void 0&&(j=!1),this.applyStates();var ne=0;V&&I&&(this._gl.clearColor(I.r,I.g,I.b,I.a!==void 0?I.a:1),ne|=this._gl.COLOR_BUFFER_BIT),X&&(this.useReverseDepthBuffer?(this._depthCullingState.depthFunc=this._gl.GREATER,this._gl.clearDepth(0)):this._gl.clearDepth(1),ne|=this._gl.DEPTH_BUFFER_BIT),j&&(this._gl.clearStencil(0),ne|=this._gl.STENCIL_BUFFER_BIT),this._gl.clear(ne)},N.prototype._viewport=function(I,V,X,j){I===this._viewportCached.x&&V===this._viewportCached.y&&X===this._viewportCached.z&&j===this._viewportCached.w||(this._viewportCached.x=I,this._viewportCached.y=V,this._viewportCached.z=X,this._viewportCached.w=j,this._gl.viewport(I,V,X,j))},N.prototype.setViewport=function(I,V,X){var j=V||this.getRenderWidth(),ne=X||this.getRenderHeight(),te=I.x||0,de=I.y||0;this._cachedViewport=I,this._viewport(te*j,de*ne,j*I.width,ne*I.height)},N.prototype.beginFrame=function(){},N.prototype.endFrame=function(){this._badOS&&this.flushFramebuffer()},N.prototype.resize=function(){var I,V;A.a.IsWindowObjectExist()?(I=this._renderingCanvas?this._renderingCanvas.clientWidth||this._renderingCanvas.width:window.innerWidth,V=this._renderingCanvas?this._renderingCanvas.clientHeight||this._renderingCanvas.height:window.innerHeight):(I=this._renderingCanvas?this._renderingCanvas.width:100,V=this._renderingCanvas?this._renderingCanvas.height:100),this.setSize(I/this._hardwareScalingLevel,V/this._hardwareScalingLevel)},N.prototype.setSize=function(I,V){return!!this._renderingCanvas&&(I|=0,V|=0,(this._renderingCanvas.width!==I||this._renderingCanvas.height!==V)&&(this._renderingCanvas.width=I,this._renderingCanvas.height=V,!0))},N.prototype.bindFramebuffer=function(I,V,X,j,ne,te,de){V===void 0&&(V=0),te===void 0&&(te=0),de===void 0&&(de=0),this._currentRenderTarget&&this.unBindFramebuffer(this._currentRenderTarget),this._currentRenderTarget=I,this._bindUnboundFramebuffer(I._MSAAFramebuffer?I._MSAAFramebuffer:I._framebuffer);var pe=this._gl;I.is2DArray?pe.framebufferTextureLayer(pe.FRAMEBUFFER,pe.COLOR_ATTACHMENT0,I._webGLTexture,te,de):I.isCube&&pe.framebufferTexture2D(pe.FRAMEBUFFER,pe.COLOR_ATTACHMENT0,pe.TEXTURE_CUBE_MAP_POSITIVE_X+V,I._webGLTexture,te);var ae=I._depthStencilTexture;if(ae){var ee=ae._generateStencilBuffer?pe.DEPTH_STENCIL_ATTACHMENT:pe.DEPTH_ATTACHMENT;I.is2DArray?pe.framebufferTextureLayer(pe.FRAMEBUFFER,ee,ae._webGLTexture,te,de):I.isCube?pe.framebufferTexture2D(pe.FRAMEBUFFER,ee,pe.TEXTURE_CUBE_MAP_POSITIVE_X+V,ae._webGLTexture,te):pe.framebufferTexture2D(pe.FRAMEBUFFER,ee,pe.TEXTURE_2D,ae._webGLTexture,te)}this._cachedViewport&&!ne?this.setViewport(this._cachedViewport,X,j):(X||(X=I.width,te&&(X/=Math.pow(2,te))),j||(j=I.height,te&&(j/=Math.pow(2,te))),this._viewport(0,0,X,j)),this.wipeCaches()},N.prototype._bindUnboundFramebuffer=function(I){this._currentFramebuffer!==I&&(this._gl.bindFramebuffer(this._gl.FRAMEBUFFER,I),this._currentFramebuffer=I)},N.prototype.unBindFramebuffer=function(I,V,X){V===void 0&&(V=!1),this._currentRenderTarget=null;var j=this._gl;if(I._MSAAFramebuffer){if(I._textureArray)return void this.unBindMultiColorAttachmentFramebuffer(I._textureArray,V,X);j.bindFramebuffer(j.READ_FRAMEBUFFER,I._MSAAFramebuffer),j.bindFramebuffer(j.DRAW_FRAMEBUFFER,I._framebuffer),j.blitFramebuffer(0,0,I.width,I.height,0,0,I.width,I.height,j.COLOR_BUFFER_BIT,j.NEAREST)}!I.generateMipMaps||V||I.isCube||(this._bindTextureDirectly(j.TEXTURE_2D,I,!0),j.generateMipmap(j.TEXTURE_2D),this._bindTextureDirectly(j.TEXTURE_2D,null)),X&&(I._MSAAFramebuffer&&this._bindUnboundFramebuffer(I._framebuffer),X()),this._bindUnboundFramebuffer(null)},N.prototype.flushFramebuffer=function(){this._gl.flush()},N.prototype.restoreDefaultFramebuffer=function(){this._currentRenderTarget?this.unBindFramebuffer(this._currentRenderTarget):this._bindUnboundFramebuffer(null),this._cachedViewport&&this.setViewport(this._cachedViewport),this.wipeCaches()},N.prototype._resetVertexBufferBinding=function(){this.bindArrayBuffer(null),this._cachedVertexBuffers=null},N.prototype.createVertexBuffer=function(I){return this._createVertexBuffer(I,this._gl.STATIC_DRAW)},N.prototype._createVertexBuffer=function(I,V){var X=this._gl.createBuffer();if(!X)throw new Error("Unable to create vertex buffer");var j=new l.a(X);return this.bindArrayBuffer(j),I instanceof Array?this._gl.bufferData(this._gl.ARRAY_BUFFER,new Float32Array(I),this._gl.STATIC_DRAW):this._gl.bufferData(this._gl.ARRAY_BUFFER,I,this._gl.STATIC_DRAW),this._resetVertexBufferBinding(),j.references=1,j},N.prototype.createDynamicVertexBuffer=function(I){return this._createVertexBuffer(I,this._gl.DYNAMIC_DRAW)},N.prototype._resetIndexBufferBinding=function(){this.bindIndexBuffer(null),this._cachedIndexBuffer=null},N.prototype.createIndexBuffer=function(I,V){var X=this._gl.createBuffer(),j=new l.a(X);if(!X)throw new Error("Unable to create index buffer");this.bindIndexBuffer(j);var ne=this._normalizeIndexData(I);return this._gl.bufferData(this._gl.ELEMENT_ARRAY_BUFFER,ne,V?this._gl.DYNAMIC_DRAW:this._gl.STATIC_DRAW),this._resetIndexBufferBinding(),j.references=1,j.is32Bits=ne.BYTES_PER_ELEMENT===4,j},N.prototype._normalizeIndexData=function(I){if(I instanceof Uint16Array)return I;if(this._caps.uintIndices){if(I instanceof Uint32Array)return I;for(var V=0;V<I.length;V++)if(I[V]>=65535)return new Uint32Array(I);return new Uint16Array(I)}return new Uint16Array(I)},N.prototype.bindArrayBuffer=function(I){this._vaoRecordInProgress||this._unbindVertexArrayObject(),this.bindBuffer(I,this._gl.ARRAY_BUFFER)},N.prototype.bindUniformBlock=function(I,V,X){var j=I.program,ne=this._gl.getUniformBlockIndex(j,V);this._gl.uniformBlockBinding(j,ne,X)},N.prototype.bindIndexBuffer=function(I){this._vaoRecordInProgress||this._unbindVertexArrayObject(),this.bindBuffer(I,this._gl.ELEMENT_ARRAY_BUFFER)},N.prototype.bindBuffer=function(I,V){(this._vaoRecordInProgress||this._currentBoundBuffer[V]!==I)&&(this._gl.bindBuffer(V,I?I.underlyingResource:null),this._currentBoundBuffer[V]=I)},N.prototype.updateArrayBuffer=function(I){this._gl.bufferSubData(this._gl.ARRAY_BUFFER,0,I)},N.prototype._vertexAttribPointer=function(I,V,X,j,ne,te,de){var pe=this._currentBufferPointers[V];if(pe){var ae=!1;pe.active?(pe.buffer!==I&&(pe.buffer=I,ae=!0),pe.size!==X&&(pe.size=X,ae=!0),pe.type!==j&&(pe.type=j,ae=!0),pe.normalized!==ne&&(pe.normalized=ne,ae=!0),pe.stride!==te&&(pe.stride=te,ae=!0),pe.offset!==de&&(pe.offset=de,ae=!0)):(ae=!0,pe.active=!0,pe.index=V,pe.size=X,pe.type=j,pe.normalized=ne,pe.stride=te,pe.offset=de,pe.buffer=I),(ae||this._vaoRecordInProgress)&&(this.bindArrayBuffer(I),this._gl.vertexAttribPointer(V,X,j,ne,te,de))}},N.prototype._bindIndexBufferWithCache=function(I){I!=null&&this._cachedIndexBuffer!==I&&(this._cachedIndexBuffer=I,this.bindIndexBuffer(I),this._uintIndicesCurrentlySet=I.is32Bits)},N.prototype._bindVertexBuffersAttributes=function(I,V){var X=V.getAttributesNames();this._vaoRecordInProgress||this._unbindVertexArrayObject(),this.unbindAllAttributes();for(var j=0;j<X.length;j++){var ne=V.getAttributeLocation(j);if(ne>=0){var te=I[X[j]];if(!te)continue;this._gl.enableVertexAttribArray(ne),this._vaoRecordInProgress||(this._vertexAttribArraysEnabled[ne]=!0);var de=te.getBuffer();de&&(this._vertexAttribPointer(de,ne,te.getSize(),te.type,te.normalized,te.byteStride,te.byteOffset),te.getIsInstanced()&&(this._gl.vertexAttribDivisor(ne,te.getInstanceDivisor()),this._vaoRecordInProgress||(this._currentInstanceLocations.push(ne),this._currentInstanceBuffers.push(de))))}}},N.prototype.recordVertexArrayObject=function(I,V,X){var j=this._gl.createVertexArray();return this._vaoRecordInProgress=!0,this._gl.bindVertexArray(j),this._mustWipeVertexAttributes=!0,this._bindVertexBuffersAttributes(I,X),this.bindIndexBuffer(V),this._vaoRecordInProgress=!1,this._gl.bindVertexArray(null),j},N.prototype.bindVertexArrayObject=function(I,V){this._cachedVertexArrayObject!==I&&(this._cachedVertexArrayObject=I,this._gl.bindVertexArray(I),this._cachedVertexBuffers=null,this._cachedIndexBuffer=null,this._uintIndicesCurrentlySet=V!=null&&V.is32Bits,this._mustWipeVertexAttributes=!0)},N.prototype.bindBuffersDirectly=function(I,V,X,j,ne){if(this._cachedVertexBuffers!==I||this._cachedEffectForVertexBuffers!==ne){this._cachedVertexBuffers=I,this._cachedEffectForVertexBuffers=ne;var te=ne.getAttributesCount();this._unbindVertexArrayObject(),this.unbindAllAttributes();for(var de=0,pe=0;pe<te;pe++)if(pe<X.length){var ae=ne.getAttributeLocation(pe);ae>=0&&(this._gl.enableVertexAttribArray(ae),this._vertexAttribArraysEnabled[ae]=!0,this._vertexAttribPointer(I,ae,X[pe],this._gl.FLOAT,!1,j,de)),de+=4*X[pe]}}this._bindIndexBufferWithCache(V)},N.prototype._unbindVertexArrayObject=function(){this._cachedVertexArrayObject&&(this._cachedVertexArrayObject=null,this._gl.bindVertexArray(null))},N.prototype.bindBuffers=function(I,V,X){this._cachedVertexBuffers===I&&this._cachedEffectForVertexBuffers===X||(this._cachedVertexBuffers=I,this._cachedEffectForVertexBuffers=X,this._bindVertexBuffersAttributes(I,X)),this._bindIndexBufferWithCache(V)},N.prototype.unbindInstanceAttributes=function(){for(var I,V=0,X=this._currentInstanceLocations.length;V<X;V++){var j=this._currentInstanceBuffers[V];I!=j&&j.references&&(I=j,this.bindArrayBuffer(j));var ne=this._currentInstanceLocations[V];this._gl.vertexAttribDivisor(ne,0)}this._currentInstanceBuffers.length=0,this._currentInstanceLocations.length=0},N.prototype.releaseVertexArrayObject=function(I){this._gl.deleteVertexArray(I)},N.prototype._releaseBuffer=function(I){return I.references--,I.references===0&&(this._deleteBuffer(I),!0)},N.prototype._deleteBuffer=function(I){this._gl.deleteBuffer(I.underlyingResource)},N.prototype.updateAndBindInstancesBuffer=function(I,V,X){if(this.bindArrayBuffer(I),V&&this._gl.bufferSubData(this._gl.ARRAY_BUFFER,0,V),X[0].index!==void 0)this.bindInstancesBuffer(I,X,!0);else for(var j=0;j<4;j++){var ne=X[j];this._vertexAttribArraysEnabled[ne]||(this._gl.enableVertexAttribArray(ne),this._vertexAttribArraysEnabled[ne]=!0),this._vertexAttribPointer(I,ne,4,this._gl.FLOAT,!1,64,16*j),this._gl.vertexAttribDivisor(ne,1),this._currentInstanceLocations.push(ne),this._currentInstanceBuffers.push(I)}},N.prototype.bindInstancesBuffer=function(I,V,X){X===void 0&&(X=!0),this.bindArrayBuffer(I);var j=0;if(X)for(var ne=0;ne<V.length;ne++)j+=4*(te=V[ne]).attributeSize;for(ne=0;ne<V.length;ne++){var te;(te=V[ne]).index===void 0&&(te.index=this._currentEffect.getAttributeLocationByName(te.attributeName)),te.index<0||(this._vertexAttribArraysEnabled[te.index]||(this._gl.enableVertexAttribArray(te.index),this._vertexAttribArraysEnabled[te.index]=!0),this._vertexAttribPointer(I,te.index,te.attributeSize,te.attributeType||this._gl.FLOAT,te.normalized||!1,j,te.offset),this._gl.vertexAttribDivisor(te.index,te.divisor===void 0?1:te.divisor),this._currentInstanceLocations.push(te.index),this._currentInstanceBuffers.push(I))}},N.prototype.disableInstanceAttributeByName=function(I){if(this._currentEffect){var V=this._currentEffect.getAttributeLocationByName(I);this.disableInstanceAttribute(V)}},N.prototype.disableInstanceAttribute=function(I){for(var V,X=!1;(V=this._currentInstanceLocations.indexOf(I))!==-1;)this._currentInstanceLocations.splice(V,1),this._currentInstanceBuffers.splice(V,1),X=!0,V=this._currentInstanceLocations.indexOf(I);X&&(this._gl.vertexAttribDivisor(I,0),this.disableAttributeByIndex(I))},N.prototype.disableAttributeByIndex=function(I){this._gl.disableVertexAttribArray(I),this._vertexAttribArraysEnabled[I]=!1,this._currentBufferPointers[I].active=!1},N.prototype.draw=function(I,V,X,j){this.drawElementsType(I?m.a.MATERIAL_TriangleFillMode:m.a.MATERIAL_WireFrameFillMode,V,X,j)},N.prototype.drawPointClouds=function(I,V,X){this.drawArraysType(m.a.MATERIAL_PointFillMode,I,V,X)},N.prototype.drawUnIndexed=function(I,V,X,j){this.drawArraysType(I?m.a.MATERIAL_TriangleFillMode:m.a.MATERIAL_WireFrameFillMode,V,X,j)},N.prototype.drawElementsType=function(I,V,X,j){this.applyStates(),this._reportDrawCall();var ne=this._drawMode(I),te=this._uintIndicesCurrentlySet?this._gl.UNSIGNED_INT:this._gl.UNSIGNED_SHORT,de=this._uintIndicesCurrentlySet?4:2;j?this._gl.drawElementsInstanced(ne,X,te,V*de,j):this._gl.drawElements(ne,X,te,V*de)},N.prototype.drawArraysType=function(I,V,X,j){this.applyStates(),this._reportDrawCall();var ne=this._drawMode(I);j?this._gl.drawArraysInstanced(ne,V,X,j):this._gl.drawArrays(ne,V,X)},N.prototype._drawMode=function(I){switch(I){case m.a.MATERIAL_TriangleFillMode:return this._gl.TRIANGLES;case m.a.MATERIAL_PointFillMode:return this._gl.POINTS;case m.a.MATERIAL_WireFrameFillMode:return this._gl.LINES;case m.a.MATERIAL_PointListDrawMode:return this._gl.POINTS;case m.a.MATERIAL_LineListDrawMode:return this._gl.LINES;case m.a.MATERIAL_LineLoopDrawMode:return this._gl.LINE_LOOP;case m.a.MATERIAL_LineStripDrawMode:return this._gl.LINE_STRIP;case m.a.MATERIAL_TriangleStripDrawMode:return this._gl.TRIANGLE_STRIP;case m.a.MATERIAL_TriangleFanDrawMode:return this._gl.TRIANGLE_FAN;default:return this._gl.TRIANGLES}},N.prototype._reportDrawCall=function(){},N.prototype._releaseEffect=function(I){this._compiledEffects[I._key]&&(delete this._compiledEffects[I._key],this._deletePipelineContext(I.getPipelineContext()))},N.prototype._deletePipelineContext=function(I){var V=I;V&&V.program&&(V.program.__SPECTOR_rebuildProgram=null,this._gl.deleteProgram(V.program))},N.prototype.createEffect=function(I,V,X,j,ne,te,de,pe,ae){var ee=(I.vertexElement||I.vertex||I.vertexToken||I.vertexSource||I)+"+"+(I.fragmentElement||I.fragment||I.fragmentToken||I.fragmentSource||I)+"@"+(ne||V.defines);if(this._compiledEffects[ee]){var K=this._compiledEffects[ee];return de&&K.isReady()&&de(K),K}var $=new _.a(I,V,X,j,this,ne,te,de,pe,ae);return $._key=ee,this._compiledEffects[ee]=$,$},N._ConcatenateShader=function(I,V,X){return X===void 0&&(X=""),X+(V?V+`
-`:"")+I},N.prototype._compileShader=function(I,V,X,j){return this._compileRawShader(N._ConcatenateShader(I,X,j),V)},N.prototype._compileRawShader=function(I,V){var X=this._gl,j=X.createShader(V==="vertex"?X.VERTEX_SHADER:X.FRAGMENT_SHADER);if(!j)throw new Error("Something went wrong while compile the shader.");return X.shaderSource(j,I),X.compileShader(j),j},N.prototype._getShaderSource=function(I){return this._gl.getShaderSource(I)},N.prototype.createRawShaderProgram=function(I,V,X,j,ne){ne===void 0&&(ne=null),j=j||this._gl;var te=this._compileRawShader(V,"vertex"),de=this._compileRawShader(X,"fragment");return this._createShaderProgram(I,te,de,j,ne)},N.prototype.createShaderProgram=function(I,V,X,j,ne,te){te===void 0&&(te=null),ne=ne||this._gl;var de=this._webGLVersion>1?`#version 300 es
-#define WEBGL2 
-`:"",pe=this._compileShader(V,"vertex",j,de),ae=this._compileShader(X,"fragment",j,de);return this._createShaderProgram(I,pe,ae,ne,te)},N.prototype.createPipelineContext=function(){var I=new h.a;return I.engine=this,this._caps.parallelShaderCompile&&(I.isParallelCompiled=!0),I},N.prototype._createShaderProgram=function(I,V,X,j,ne){var te=j.createProgram();if(I.program=te,!te)throw new Error("Unable to create program");return j.attachShader(te,V),j.attachShader(te,X),j.linkProgram(te),I.context=j,I.vertexShader=V,I.fragmentShader=X,I.isParallelCompiled||this._finalizePipelineContext(I),te},N.prototype._finalizePipelineContext=function(I){var V=I.context,X=I.vertexShader,j=I.fragmentShader,ne=I.program;if(!V.getProgramParameter(ne,V.LINK_STATUS)){var te,de;if(!this._gl.getShaderParameter(X,this._gl.COMPILE_STATUS)&&(te=this._gl.getShaderInfoLog(X)))throw I.vertexCompilationError=te,new Error("VERTEX SHADER "+te);if(!this._gl.getShaderParameter(j,this._gl.COMPILE_STATUS)&&(te=this._gl.getShaderInfoLog(j)))throw I.fragmentCompilationError=te,new Error("FRAGMENT SHADER "+te);if(de=V.getProgramInfoLog(ne))throw I.programLinkError=de,new Error(de)}if(this.validateShaderPrograms&&(V.validateProgram(ne),!V.getProgramParameter(ne,V.VALIDATE_STATUS)&&(de=V.getProgramInfoLog(ne))))throw I.programValidationError=de,new Error(de);V.deleteShader(X),V.deleteShader(j),I.vertexShader=void 0,I.fragmentShader=void 0,I.onCompiled&&(I.onCompiled(),I.onCompiled=void 0)},N.prototype._preparePipelineContext=function(I,V,X,j,ne,te,de){var pe=I;pe.program=j?this.createRawShaderProgram(pe,V,X,void 0,de):this.createShaderProgram(pe,V,X,te,void 0,de),pe.program.__SPECTOR_rebuildProgram=ne},N.prototype._isRenderingStateCompiled=function(I){var V=I;return!!this._gl.getProgramParameter(V.program,this._caps.parallelShaderCompile.COMPLETION_STATUS_KHR)&&(this._finalizePipelineContext(V),!0)},N.prototype._executeWhenRenderingStateIsCompiled=function(I,V){var X=I;if(X.isParallelCompiled){var j=X.onCompiled;X.onCompiled=j?function(){j(),V()}:V}else V()},N.prototype.getUniforms=function(I,V){for(var X=new Array,j=I,ne=0;ne<V.length;ne++)X.push(this._gl.getUniformLocation(j.program,V[ne]));return X},N.prototype.getAttributes=function(I,V){for(var X=[],j=I,ne=0;ne<V.length;ne++)try{X.push(this._gl.getAttribLocation(j.program,V[ne]))}catch{X.push(-1)}return X},N.prototype.enableEffect=function(I){I&&I!==this._currentEffect&&(this.bindSamplers(I),this._currentEffect=I,I.onBind&&I.onBind(I),I._onBindObservable&&I._onBindObservable.notifyObservers(I))},N.prototype.setInt=function(I,V){return!!I&&(this._gl.uniform1i(I,V),!0)},N.prototype.setIntArray=function(I,V){return!!I&&(this._gl.uniform1iv(I,V),!0)},N.prototype.setIntArray2=function(I,V){return!(!I||V.length%2!=0)&&(this._gl.uniform2iv(I,V),!0)},N.prototype.setIntArray3=function(I,V){return!(!I||V.length%3!=0)&&(this._gl.uniform3iv(I,V),!0)},N.prototype.setIntArray4=function(I,V){return!(!I||V.length%4!=0)&&(this._gl.uniform4iv(I,V),!0)},N.prototype.setArray=function(I,V){return!!I&&(this._gl.uniform1fv(I,V),!0)},N.prototype.setArray2=function(I,V){return!(!I||V.length%2!=0)&&(this._gl.uniform2fv(I,V),!0)},N.prototype.setArray3=function(I,V){return!(!I||V.length%3!=0)&&(this._gl.uniform3fv(I,V),!0)},N.prototype.setArray4=function(I,V){return!(!I||V.length%4!=0)&&(this._gl.uniform4fv(I,V),!0)},N.prototype.setMatrices=function(I,V){return!!I&&(this._gl.uniformMatrix4fv(I,!1,V),!0)},N.prototype.setMatrix3x3=function(I,V){return!!I&&(this._gl.uniformMatrix3fv(I,!1,V),!0)},N.prototype.setMatrix2x2=function(I,V){return!!I&&(this._gl.uniformMatrix2fv(I,!1,V),!0)},N.prototype.setFloat=function(I,V){return!!I&&(this._gl.uniform1f(I,V),!0)},N.prototype.setFloat2=function(I,V,X){return!!I&&(this._gl.uniform2f(I,V,X),!0)},N.prototype.setFloat3=function(I,V,X,j){return!!I&&(this._gl.uniform3f(I,V,X,j),!0)},N.prototype.setFloat4=function(I,V,X,j,ne){return!!I&&(this._gl.uniform4f(I,V,X,j,ne),!0)},N.prototype.applyStates=function(){if(this._depthCullingState.apply(this._gl),this._stencilState.apply(this._gl),this._alphaState.apply(this._gl),this._colorWriteChanged){this._colorWriteChanged=!1;var I=this._colorWrite;this._gl.colorMask(I,I,I,I)}},N.prototype.setColorWrite=function(I){I!==this._colorWrite&&(this._colorWriteChanged=!0,this._colorWrite=I)},N.prototype.getColorWrite=function(){return this._colorWrite},Object.defineProperty(N.prototype,"depthCullingState",{get:function(){return this._depthCullingState},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"alphaState",{get:function(){return this._alphaState},enumerable:!1,configurable:!0}),Object.defineProperty(N.prototype,"stencilState",{get:function(){return this._stencilState},enumerable:!1,configurable:!0}),N.prototype.clearInternalTexturesCache=function(){this._internalTexturesCache=[]},N.prototype.wipeCaches=function(I){this.preventCacheWipeBetweenFrames&&!I||(this._currentEffect=null,this._viewportCached.x=0,this._viewportCached.y=0,this._viewportCached.z=0,this._viewportCached.w=0,this._unbindVertexArrayObject(),I&&(this._currentProgram=null,this.resetTextureCache(),this._stencilState.reset(),this._depthCullingState.reset(),this._depthCullingState.depthFunc=this._gl.LEQUAL,this._alphaState.reset(),this._alphaMode=m.a.ALPHA_ADD,this._alphaEquation=m.a.ALPHA_DISABLE,this._colorWrite=!0,this._colorWriteChanged=!0,this._unpackFlipYCached=null,this._gl.pixelStorei(this._gl.UNPACK_COLORSPACE_CONVERSION_WEBGL,this._gl.NONE),this._gl.pixelStorei(this._gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL,0),this._mustWipeVertexAttributes=!0,this.unbindAllAttributes()),this._resetVertexBufferBinding(),this._cachedIndexBuffer=null,this._cachedEffectForVertexBuffers=null,this.bindIndexBuffer(null))},N.prototype._getSamplingParameters=function(I,V){var X=this._gl,j=X.NEAREST,ne=X.NEAREST;switch(I){case m.a.TEXTURE_LINEAR_LINEAR_MIPNEAREST:j=X.LINEAR,ne=V?X.LINEAR_MIPMAP_NEAREST:X.LINEAR;break;case m.a.TEXTURE_LINEAR_LINEAR_MIPLINEAR:j=X.LINEAR,ne=V?X.LINEAR_MIPMAP_LINEAR:X.LINEAR;break;case m.a.TEXTURE_NEAREST_NEAREST_MIPLINEAR:j=X.NEAREST,ne=V?X.NEAREST_MIPMAP_LINEAR:X.NEAREST;break;case m.a.TEXTURE_NEAREST_NEAREST_MIPNEAREST:j=X.NEAREST,ne=V?X.NEAREST_MIPMAP_NEAREST:X.NEAREST;break;case m.a.TEXTURE_NEAREST_LINEAR_MIPNEAREST:j=X.NEAREST,ne=V?X.LINEAR_MIPMAP_NEAREST:X.LINEAR;break;case m.a.TEXTURE_NEAREST_LINEAR_MIPLINEAR:j=X.NEAREST,ne=V?X.LINEAR_MIPMAP_LINEAR:X.LINEAR;break;case m.a.TEXTURE_NEAREST_LINEAR:j=X.NEAREST,ne=X.LINEAR;break;case m.a.TEXTURE_NEAREST_NEAREST:j=X.NEAREST,ne=X.NEAREST;break;case m.a.TEXTURE_LINEAR_NEAREST_MIPNEAREST:j=X.LINEAR,ne=V?X.NEAREST_MIPMAP_NEAREST:X.NEAREST;break;case m.a.TEXTURE_LINEAR_NEAREST_MIPLINEAR:j=X.LINEAR,ne=V?X.NEAREST_MIPMAP_LINEAR:X.NEAREST;break;case m.a.TEXTURE_LINEAR_LINEAR:j=X.LINEAR,ne=X.LINEAR;break;case m.a.TEXTURE_LINEAR_NEAREST:j=X.LINEAR,ne=X.NEAREST}return{min:ne,mag:j}},N.prototype._createTexture=function(){var I=this._gl.createTexture();if(!I)throw new Error("Unable to create texture");return I},N.prototype.createTexture=function(I,V,X,j,ne,te,de,pe,ae,ee,K,$,L){var G=this;ne===void 0&&(ne=m.a.TEXTURE_TRILINEAR_SAMPLINGMODE),te===void 0&&(te=null),de===void 0&&(de=null),pe===void 0&&(pe=null),ae===void 0&&(ae=null),ee===void 0&&(ee=null),K===void 0&&(K=null);var Q=(I=I||"").substr(0,5)==="data:",oe=I.substr(0,5)==="blob:",re=Q&&I.indexOf(";base64,")!==-1,Y=ae||new c.a(this,c.b.Url),k=I;!this._transformTextureUrl||re||ae||pe||(I=this._transformTextureUrl(I)),k!==I&&(Y._originalUrl=k);var H=I.lastIndexOf("."),Z=K||(H>-1?I.substring(H).toLowerCase():""),W=null;Z.indexOf("?")>-1&&(Z=Z.split("?")[0]);for(var q=0,he=N._TextureLoaders;q<he.length;q++){var ge=he[q];if(ge.canLoad(Z,$)){W=ge;break}}j&&j._addPendingData(Y),Y.url=I,Y.generateMipMaps=!V,Y.samplingMode=ne,Y.invertY=X,this._doNotHandleContextLost||(Y._buffer=pe);var me=null;te&&!ae&&(me=Y.onLoadedObservable.add(te)),ae||this._internalTexturesCache.push(Y);var _e=function(ye,Be){j&&j._removePendingData(Y),I===k?(me&&Y.onLoadedObservable.remove(me),U.a.UseFallbackTexture&&G.createTexture(U.a.FallbackTexture,V,Y.invertY,j,ne,null,de,pe,Y),de&&de((ye||"Unknown error")+(U.a.UseFallbackTexture?" - Fallback texture was used":""),Be)):(T.a.Warn("Failed to load "+I+", falling back to "+k),G.createTexture(k,V,Y.invertY,j,ne,te,de,pe,Y,ee,K,$,L))};if(W){var be=function(ye){W.loadData(ye,Y,function(Be,ke,We,je,He,qe){qe?_e("TextureLoader failed to load data"):G._prepareWebGLTexture(Y,j,Be,ke,Y.invertY,!We,je,function(){return He(),!1},ne)},L)};pe?pe instanceof ArrayBuffer?be(new Uint8Array(pe)):ArrayBuffer.isView(pe)?be(pe):de&&de("Unable to load: only ArrayBuffer or ArrayBufferView is supported",null):this._loadFile(I,function(ye){return be(new Uint8Array(ye))},void 0,j?j.offlineProvider:void 0,!0,function(ye,Be){_e("Unable to load "+(ye&&ye.responseURL,Be))})}else{var Pe=function(ye){oe&&!G._doNotHandleContextLost&&(Y._buffer=ye),G._prepareWebGLTexture(Y,j,ye.width,ye.height,Y.invertY,V,!1,function(Be,ke,We){var je=G._gl,He=ye.width===Be&&ye.height===ke,qe=ee?G._getInternalFormat(ee):Z===".jpg"?je.RGB:je.RGBA;if(He)return je.texImage2D(je.TEXTURE_2D,0,qe,qe,je.UNSIGNED_BYTE,ye),!1;var Ge=G._caps.maxTextureSize;if(ye.width>Ge||ye.height>Ge||!G._supportsHardwareTextureRescaling)return G._prepareWorkingCanvas(),!(!G._workingCanvas||!G._workingContext)&&(G._workingCanvas.width=Be,G._workingCanvas.height=ke,G._workingContext.drawImage(ye,0,0,ye.width,ye.height,0,0,Be,ke),je.texImage2D(je.TEXTURE_2D,0,qe,qe,je.UNSIGNED_BYTE,G._workingCanvas),Y.width=Be,Y.height=ke,!1);var nt=new c.a(G,c.b.Temp);return G._bindTextureDirectly(je.TEXTURE_2D,nt,!0),je.texImage2D(je.TEXTURE_2D,0,qe,qe,je.UNSIGNED_BYTE,ye),G._rescaleTexture(nt,Y,j,qe,function(){G._releaseTexture(nt),G._bindTextureDirectly(je.TEXTURE_2D,Y,!0),We()}),!0},ne)};!Q||re?pe&&(pe.decoding||pe.close)?Pe(pe):N._FileToolsLoadImage(I,Pe,_e,j?j.offlineProvider:null,$):typeof pe=="string"||pe instanceof ArrayBuffer||ArrayBuffer.isView(pe)||pe instanceof Blob?N._FileToolsLoadImage(pe,Pe,_e,j?j.offlineProvider:null,$):pe&&Pe(pe)}return Y},N._FileToolsLoadImage=function(I,V,X,j,ne){throw C.a.WarnImport("FileTools")},N.prototype._rescaleTexture=function(I,V,X,j,ne){},N.prototype.createRawTexture=function(I,V,X,j,ne,te,de,pe,ae){throw ae===void 0&&(ae=m.a.TEXTURETYPE_UNSIGNED_INT),C.a.WarnImport("Engine.RawTexture")},N.prototype.createRawCubeTexture=function(I,V,X,j,ne,te,de,pe){throw C.a.WarnImport("Engine.RawTexture")},N.prototype.createRawTexture3D=function(I,V,X,j,ne,te,de,pe,ae,ee){throw ee===void 0&&(ee=m.a.TEXTURETYPE_UNSIGNED_INT),C.a.WarnImport("Engine.RawTexture")},N.prototype.createRawTexture2DArray=function(I,V,X,j,ne,te,de,pe,ae,ee){throw ee===void 0&&(ee=m.a.TEXTURETYPE_UNSIGNED_INT),C.a.WarnImport("Engine.RawTexture")},N.prototype._unpackFlipY=function(I){this._unpackFlipYCached!==I&&(this._gl.pixelStorei(this._gl.UNPACK_FLIP_Y_WEBGL,I?1:0),this.enableUnpackFlipYCached&&(this._unpackFlipYCached=I))},N.prototype._getUnpackAlignement=function(){return this._gl.getParameter(this._gl.UNPACK_ALIGNMENT)},N.prototype._getTextureTarget=function(I){return I.isCube?this._gl.TEXTURE_CUBE_MAP:I.is3D?this._gl.TEXTURE_3D:I.is2DArray||I.isMultiview?this._gl.TEXTURE_2D_ARRAY:this._gl.TEXTURE_2D},N.prototype.updateTextureSamplingMode=function(I,V,X){X===void 0&&(X=!1);var j=this._getTextureTarget(V),ne=this._getSamplingParameters(I,V.generateMipMaps||X);this._setTextureParameterInteger(j,this._gl.TEXTURE_MAG_FILTER,ne.mag,V),this._setTextureParameterInteger(j,this._gl.TEXTURE_MIN_FILTER,ne.min),X&&(V.generateMipMaps=!0,this._gl.generateMipmap(j)),this._bindTextureDirectly(j,null),V.samplingMode=I},N.prototype.updateTextureWrappingMode=function(I,V,X,j){X===void 0&&(X=null),j===void 0&&(j=null);var ne=this._getTextureTarget(I);V!==null&&(this._setTextureParameterInteger(ne,this._gl.TEXTURE_WRAP_S,this._getTextureWrapMode(V),I),I._cachedWrapU=V),X!==null&&(this._setTextureParameterInteger(ne,this._gl.TEXTURE_WRAP_T,this._getTextureWrapMode(X),I),I._cachedWrapV=X),(I.is2DArray||I.is3D)&&j!==null&&(this._setTextureParameterInteger(ne,this._gl.TEXTURE_WRAP_R,this._getTextureWrapMode(j),I),I._cachedWrapR=j),this._bindTextureDirectly(ne,null)},N.prototype._setupDepthStencilTexture=function(I,V,X,j,ne){var te=V.width||V,de=V.height||V,pe=V.layers||0;I.baseWidth=te,I.baseHeight=de,I.width=te,I.height=de,I.is2DArray=pe>0,I.depth=pe,I.isReady=!0,I.samples=1,I.generateMipMaps=!1,I._generateDepthBuffer=!0,I._generateStencilBuffer=X,I.samplingMode=j?m.a.TEXTURE_BILINEAR_SAMPLINGMODE:m.a.TEXTURE_NEAREST_SAMPLINGMODE,I.type=m.a.TEXTURETYPE_UNSIGNED_INT,I._comparisonFunction=ne;var ae=this._gl,ee=this._getTextureTarget(I),K=this._getSamplingParameters(I.samplingMode,!1);ae.texParameteri(ee,ae.TEXTURE_MAG_FILTER,K.mag),ae.texParameteri(ee,ae.TEXTURE_MIN_FILTER,K.min),ae.texParameteri(ee,ae.TEXTURE_WRAP_S,ae.CLAMP_TO_EDGE),ae.texParameteri(ee,ae.TEXTURE_WRAP_T,ae.CLAMP_TO_EDGE),ne===0?(ae.texParameteri(ee,ae.TEXTURE_COMPARE_FUNC,m.a.LEQUAL),ae.texParameteri(ee,ae.TEXTURE_COMPARE_MODE,ae.NONE)):(ae.texParameteri(ee,ae.TEXTURE_COMPARE_FUNC,ne),ae.texParameteri(ee,ae.TEXTURE_COMPARE_MODE,ae.COMPARE_REF_TO_TEXTURE))},N.prototype._uploadCompressedDataToTextureDirectly=function(I,V,X,j,ne,te,de){te===void 0&&(te=0),de===void 0&&(de=0);var pe=this._gl,ae=pe.TEXTURE_2D;I.isCube&&(ae=pe.TEXTURE_CUBE_MAP_POSITIVE_X+te),this._gl.compressedTexImage2D(ae,de,V,X,j,0,ne)},N.prototype._uploadDataToTextureDirectly=function(I,V,X,j,ne,te){X===void 0&&(X=0),j===void 0&&(j=0),te===void 0&&(te=!1);var de=this._gl,pe=this._getWebGLTextureType(I.type),ae=this._getInternalFormat(I.format),ee=ne===void 0?this._getRGBABufferInternalSizedFormat(I.type,I.format):this._getInternalFormat(ne);this._unpackFlipY(I.invertY);var K=de.TEXTURE_2D;I.isCube&&(K=de.TEXTURE_CUBE_MAP_POSITIVE_X+X);var $=Math.round(Math.log(I.width)*Math.LOG2E),L=Math.round(Math.log(I.height)*Math.LOG2E),G=te?I.width:Math.pow(2,Math.max($-j,0)),Q=te?I.height:Math.pow(2,Math.max(L-j,0));de.texImage2D(K,j,ee,G,Q,0,ae,pe,V)},N.prototype.updateTextureData=function(I,V,X,j,ne,te,de,pe){de===void 0&&(de=0),pe===void 0&&(pe=0);var ae=this._gl,ee=this._getWebGLTextureType(I.type),K=this._getInternalFormat(I.format);this._unpackFlipY(I.invertY);var $=ae.TEXTURE_2D;I.isCube&&($=ae.TEXTURE_CUBE_MAP_POSITIVE_X+de),ae.texSubImage2D($,pe,X,j,ne,te,K,ee,V)},N.prototype._uploadArrayBufferViewToTexture=function(I,V,X,j){X===void 0&&(X=0),j===void 0&&(j=0);var ne=this._gl,te=I.isCube?ne.TEXTURE_CUBE_MAP:ne.TEXTURE_2D;this._bindTextureDirectly(te,I,!0),this._uploadDataToTextureDirectly(I,V,X,j),this._bindTextureDirectly(te,null,!0)},N.prototype._prepareWebGLTextureContinuation=function(I,V,X,j,ne){var te=this._gl;if(te){var de=this._getSamplingParameters(ne,!X);te.texParameteri(te.TEXTURE_2D,te.TEXTURE_MAG_FILTER,de.mag),te.texParameteri(te.TEXTURE_2D,te.TEXTURE_MIN_FILTER,de.min),X||j||te.generateMipmap(te.TEXTURE_2D),this._bindTextureDirectly(te.TEXTURE_2D,null),V&&V._removePendingData(I),I.onLoadedObservable.notifyObservers(I),I.onLoadedObservable.clear()}},N.prototype._prepareWebGLTexture=function(I,V,X,j,ne,te,de,pe,ae){var ee=this;ae===void 0&&(ae=m.a.TEXTURE_TRILINEAR_SAMPLINGMODE);var K=this.getCaps().maxTextureSize,$=Math.min(K,this.needPOTTextures?N.GetExponentOfTwo(X,K):X),L=Math.min(K,this.needPOTTextures?N.GetExponentOfTwo(j,K):j),G=this._gl;G&&(I._webGLTexture?(this._bindTextureDirectly(G.TEXTURE_2D,I,!0),this._unpackFlipY(ne===void 0||!!ne),I.baseWidth=X,I.baseHeight=j,I.width=$,I.height=L,I.isReady=!0,pe($,L,function(){ee._prepareWebGLTextureContinuation(I,V,te,de,ae)})||this._prepareWebGLTextureContinuation(I,V,te,de,ae)):V&&V._removePendingData(I))},N.prototype._setupFramebufferDepthAttachments=function(I,V,X,j,ne){ne===void 0&&(ne=1);var te=this._gl;if(I&&V)return this._getDepthStencilBuffer(X,j,ne,te.DEPTH_STENCIL,te.DEPTH24_STENCIL8,te.DEPTH_STENCIL_ATTACHMENT);if(V){var de=te.DEPTH_COMPONENT16;return this._webGLVersion>1&&(de=te.DEPTH_COMPONENT32F),this._getDepthStencilBuffer(X,j,ne,de,de,te.DEPTH_ATTACHMENT)}return I?this._getDepthStencilBuffer(X,j,ne,te.STENCIL_INDEX8,te.STENCIL_INDEX8,te.STENCIL_ATTACHMENT):null},N.prototype._releaseFramebufferObjects=function(I){var V=this._gl;I._framebuffer&&(V.deleteFramebuffer(I._framebuffer),I._framebuffer=null),I._depthStencilBuffer&&(V.deleteRenderbuffer(I._depthStencilBuffer),I._depthStencilBuffer=null),I._MSAAFramebuffer&&(V.deleteFramebuffer(I._MSAAFramebuffer),I._MSAAFramebuffer=null),I._MSAARenderBuffer&&(V.deleteRenderbuffer(I._MSAARenderBuffer),I._MSAARenderBuffer=null)},N.prototype._releaseTexture=function(I){this._releaseFramebufferObjects(I),this._deleteTexture(I._webGLTexture),this.unbindAllTextures();var V=this._internalTexturesCache.indexOf(I);V!==-1&&this._internalTexturesCache.splice(V,1),I._lodTextureHigh&&I._lodTextureHigh.dispose(),I._lodTextureMid&&I._lodTextureMid.dispose(),I._lodTextureLow&&I._lodTextureLow.dispose(),I._irradianceTexture&&I._irradianceTexture.dispose()},N.prototype._deleteTexture=function(I){this._gl.deleteTexture(I)},N.prototype._setProgram=function(I){this._currentProgram!==I&&(this._gl.useProgram(I),this._currentProgram=I)},N.prototype.bindSamplers=function(I){var V=I.getPipelineContext();this._setProgram(V.program);for(var X=I.getSamplers(),j=0;j<X.length;j++){var ne=I.getUniform(X[j]);ne&&(this._boundUniforms[j]=ne)}this._currentEffect=null},N.prototype._activateCurrentTexture=function(){this._currentTextureChannel!==this._activeChannel&&(this._gl.activeTexture(this._gl.TEXTURE0+this._activeChannel),this._currentTextureChannel=this._activeChannel)},N.prototype._bindTextureDirectly=function(I,V,X,j){X===void 0&&(X=!1),j===void 0&&(j=!1);var ne=!1,te=V&&V._associatedChannel>-1;return X&&te&&(this._activeChannel=V._associatedChannel),this._boundTexturesCache[this._activeChannel]!==V||j?(this._activateCurrentTexture(),V&&V.isMultiview?this._gl.bindTexture(I,V?V._colorTextureArray:null):this._gl.bindTexture(I,V?V._webGLTexture:null),this._boundTexturesCache[this._activeChannel]=V,V&&(V._associatedChannel=this._activeChannel)):X&&(ne=!0,this._activateCurrentTexture()),te&&!X&&this._bindSamplerUniformToChannel(V._associatedChannel,this._activeChannel),ne},N.prototype._bindTexture=function(I,V){if(I!==void 0){V&&(V._associatedChannel=I),this._activeChannel=I;var X=V?this._getTextureTarget(V):this._gl.TEXTURE_2D;this._bindTextureDirectly(X,V)}},N.prototype.unbindAllTextures=function(){for(var I=0;I<this._maxSimultaneousTextures;I++)this._activeChannel=I,this._bindTextureDirectly(this._gl.TEXTURE_2D,null),this._bindTextureDirectly(this._gl.TEXTURE_CUBE_MAP,null),this.webGLVersion>1&&(this._bindTextureDirectly(this._gl.TEXTURE_3D,null),this._bindTextureDirectly(this._gl.TEXTURE_2D_ARRAY,null))},N.prototype.setTexture=function(I,V,X){I!==void 0&&(V&&(this._boundUniforms[I]=V),this._setTexture(I,X))},N.prototype._bindSamplerUniformToChannel=function(I,V){var X=this._boundUniforms[I];X&&X._currentState!==V&&(this._gl.uniform1i(X,V),X._currentState=V)},N.prototype._getTextureWrapMode=function(I){switch(I){case m.a.TEXTURE_WRAP_ADDRESSMODE:return this._gl.REPEAT;case m.a.TEXTURE_CLAMP_ADDRESSMODE:return this._gl.CLAMP_TO_EDGE;case m.a.TEXTURE_MIRROR_ADDRESSMODE:return this._gl.MIRRORED_REPEAT}return this._gl.REPEAT},N.prototype._setTexture=function(I,V,X,j){if(X===void 0&&(X=!1),j===void 0&&(j=!1),!V)return this._boundTexturesCache[I]!=null&&(this._activeChannel=I,this._bindTextureDirectly(this._gl.TEXTURE_2D,null),this._bindTextureDirectly(this._gl.TEXTURE_CUBE_MAP,null),this.webGLVersion>1&&(this._bindTextureDirectly(this._gl.TEXTURE_3D,null),this._bindTextureDirectly(this._gl.TEXTURE_2D_ARRAY,null))),!1;if(V.video)this._activeChannel=I,V.update();else if(V.delayLoadState===m.a.DELAYLOADSTATE_NOTLOADED)return V.delayLoad(),!1;var ne;ne=j?V.depthStencilTexture:V.isReady()?V.getInternalTexture():V.isCube?this.emptyCubeTexture:V.is3D?this.emptyTexture3D:V.is2DArray?this.emptyTexture2DArray:this.emptyTexture,!X&&ne&&(ne._associatedChannel=I);var te=!0;this._boundTexturesCache[I]===ne&&(X||this._bindSamplerUniformToChannel(ne._associatedChannel,I),te=!1),this._activeChannel=I;var de=this._getTextureTarget(ne);if(te&&this._bindTextureDirectly(de,ne,X),ne&&!ne.isMultiview){if(ne.isCube&&ne._cachedCoordinatesMode!==V.coordinatesMode){ne._cachedCoordinatesMode=V.coordinatesMode;var pe=V.coordinatesMode!==m.a.TEXTURE_CUBIC_MODE&&V.coordinatesMode!==m.a.TEXTURE_SKYBOX_MODE?m.a.TEXTURE_WRAP_ADDRESSMODE:m.a.TEXTURE_CLAMP_ADDRESSMODE;V.wrapU=pe,V.wrapV=pe}ne._cachedWrapU!==V.wrapU&&(ne._cachedWrapU=V.wrapU,this._setTextureParameterInteger(de,this._gl.TEXTURE_WRAP_S,this._getTextureWrapMode(V.wrapU),ne)),ne._cachedWrapV!==V.wrapV&&(ne._cachedWrapV=V.wrapV,this._setTextureParameterInteger(de,this._gl.TEXTURE_WRAP_T,this._getTextureWrapMode(V.wrapV),ne)),ne.is3D&&ne._cachedWrapR!==V.wrapR&&(ne._cachedWrapR=V.wrapR,this._setTextureParameterInteger(de,this._gl.TEXTURE_WRAP_R,this._getTextureWrapMode(V.wrapR),ne)),this._setAnisotropicLevel(de,ne,V.anisotropicFilteringLevel)}return!0},N.prototype.setTextureArray=function(I,V,X){if(I!==void 0&&V){this._textureUnits&&this._textureUnits.length===X.length||(this._textureUnits=new Int32Array(X.length));for(var j=0;j<X.length;j++){var ne=X[j].getInternalTexture();ne?(this._textureUnits[j]=I+j,ne._associatedChannel=I+j):this._textureUnits[j]=-1}this._gl.uniform1iv(V,this._textureUnits);for(var te=0;te<X.length;te++)this._setTexture(this._textureUnits[te],X[te],!0)}},N.prototype._setAnisotropicLevel=function(I,V,X){var j=this._caps.textureAnisotropicFilterExtension;V.samplingMode!==m.a.TEXTURE_LINEAR_LINEAR_MIPNEAREST&&V.samplingMode!==m.a.TEXTURE_LINEAR_LINEAR_MIPLINEAR&&V.samplingMode!==m.a.TEXTURE_LINEAR_LINEAR&&(X=1),j&&V._cachedAnisotropicFilteringLevel!==X&&(this._setTextureParameterFloat(I,j.TEXTURE_MAX_ANISOTROPY_EXT,Math.min(X,this._caps.maxAnisotropy),V),V._cachedAnisotropicFilteringLevel=X)},N.prototype._setTextureParameterFloat=function(I,V,X,j){this._bindTextureDirectly(I,j,!0,!0),this._gl.texParameterf(I,V,X)},N.prototype._setTextureParameterInteger=function(I,V,X,j){j&&this._bindTextureDirectly(I,j,!0,!0),this._gl.texParameteri(I,V,X)},N.prototype.unbindAllAttributes=function(){if(this._mustWipeVertexAttributes){this._mustWipeVertexAttributes=!1;for(var I=0;I<this._caps.maxVertexAttribs;I++)this.disableAttributeByIndex(I)}else{I=0;for(var V=this._vertexAttribArraysEnabled.length;I<V;I++)I>=this._caps.maxVertexAttribs||!this._vertexAttribArraysEnabled[I]||this.disableAttributeByIndex(I)}},N.prototype.releaseEffects=function(){for(var I in this._compiledEffects){var V=this._compiledEffects[I].getPipelineContext();this._deletePipelineContext(V)}this._compiledEffects={}},N.prototype.dispose=function(){this.stopRenderLoop(),this.onBeforeTextureInitObservable&&this.onBeforeTextureInitObservable.clear(),this._emptyTexture&&(this._releaseTexture(this._emptyTexture),this._emptyTexture=null),this._emptyCubeTexture&&(this._releaseTexture(this._emptyCubeTexture),this._emptyCubeTexture=null),this._dummyFramebuffer&&this._gl.deleteFramebuffer(this._dummyFramebuffer),this.releaseEffects(),this.unbindAllAttributes(),this._boundUniforms=[],A.a.IsWindowObjectExist()&&this._renderingCanvas&&(this._doNotHandleContextLost||(this._renderingCanvas.removeEventListener("webglcontextlost",this._onContextLost),this._renderingCanvas.removeEventListener("webglcontextrestored",this._onContextRestored))),this._workingCanvas=null,this._workingContext=null,this._currentBufferPointers=[],this._renderingCanvas=null,this._currentProgram=null,this._boundRenderFunction=null,_.a.ResetCache();for(var I=0,V=this._activeRequests;I<V.length;I++)V[I].abort()},N.prototype.attachContextLostEvent=function(I){this._renderingCanvas&&this._renderingCanvas.addEventListener("webglcontextlost",I,!1)},N.prototype.attachContextRestoredEvent=function(I){this._renderingCanvas&&this._renderingCanvas.addEventListener("webglcontextrestored",I,!1)},N.prototype.getError=function(){return this._gl.getError()},N.prototype._canRenderToFloatFramebuffer=function(){return this._webGLVersion>1?this._caps.colorBufferFloat:this._canRenderToFramebuffer(m.a.TEXTURETYPE_FLOAT)},N.prototype._canRenderToHalfFloatFramebuffer=function(){return this._webGLVersion>1?this._caps.colorBufferFloat:this._canRenderToFramebuffer(m.a.TEXTURETYPE_HALF_FLOAT)},N.prototype._canRenderToFramebuffer=function(I){for(var V=this._gl;V.getError()!==V.NO_ERROR;);var X=!0,j=V.createTexture();V.bindTexture(V.TEXTURE_2D,j),V.texImage2D(V.TEXTURE_2D,0,this._getRGBABufferInternalSizedFormat(I),1,1,0,V.RGBA,this._getWebGLTextureType(I),null),V.texParameteri(V.TEXTURE_2D,V.TEXTURE_MIN_FILTER,V.NEAREST),V.texParameteri(V.TEXTURE_2D,V.TEXTURE_MAG_FILTER,V.NEAREST);var ne=V.createFramebuffer();V.bindFramebuffer(V.FRAMEBUFFER,ne),V.framebufferTexture2D(V.FRAMEBUFFER,V.COLOR_ATTACHMENT0,V.TEXTURE_2D,j,0);var te=V.checkFramebufferStatus(V.FRAMEBUFFER);if((X=(X=X&&te===V.FRAMEBUFFER_COMPLETE)&&V.getError()===V.NO_ERROR)&&(V.clear(V.COLOR_BUFFER_BIT),X=X&&V.getError()===V.NO_ERROR),X){V.bindFramebuffer(V.FRAMEBUFFER,null);var de=V.RGBA,pe=V.UNSIGNED_BYTE,ae=new Uint8Array(4);V.readPixels(0,0,1,1,de,pe,ae),X=X&&V.getError()===V.NO_ERROR}for(V.deleteTexture(j),V.deleteFramebuffer(ne),V.bindFramebuffer(V.FRAMEBUFFER,null);!X&&V.getError()!==V.NO_ERROR;);return X},N.prototype._getWebGLTextureType=function(I){if(this._webGLVersion===1){switch(I){case m.a.TEXTURETYPE_FLOAT:return this._gl.FLOAT;case m.a.TEXTURETYPE_HALF_FLOAT:return this._gl.HALF_FLOAT_OES;case m.a.TEXTURETYPE_UNSIGNED_BYTE:return this._gl.UNSIGNED_BYTE;case m.a.TEXTURETYPE_UNSIGNED_SHORT_4_4_4_4:return this._gl.UNSIGNED_SHORT_4_4_4_4;case m.a.TEXTURETYPE_UNSIGNED_SHORT_5_5_5_1:return this._gl.UNSIGNED_SHORT_5_5_5_1;case m.a.TEXTURETYPE_UNSIGNED_SHORT_5_6_5:return this._gl.UNSIGNED_SHORT_5_6_5}return this._gl.UNSIGNED_BYTE}switch(I){case m.a.TEXTURETYPE_BYTE:return this._gl.BYTE;case m.a.TEXTURETYPE_UNSIGNED_BYTE:return this._gl.UNSIGNED_BYTE;case m.a.TEXTURETYPE_SHORT:return this._gl.SHORT;case m.a.TEXTURETYPE_UNSIGNED_SHORT:return this._gl.UNSIGNED_SHORT;case m.a.TEXTURETYPE_INT:return this._gl.INT;case m.a.TEXTURETYPE_UNSIGNED_INTEGER:return this._gl.UNSIGNED_INT;case m.a.TEXTURETYPE_FLOAT:return this._gl.FLOAT;case m.a.TEXTURETYPE_HALF_FLOAT:return this._gl.HALF_FLOAT;case m.a.TEXTURETYPE_UNSIGNED_SHORT_4_4_4_4:return this._gl.UNSIGNED_SHORT_4_4_4_4;case m.a.TEXTURETYPE_UNSIGNED_SHORT_5_5_5_1:return this._gl.UNSIGNED_SHORT_5_5_5_1;case m.a.TEXTURETYPE_UNSIGNED_SHORT_5_6_5:return this._gl.UNSIGNED_SHORT_5_6_5;case m.a.TEXTURETYPE_UNSIGNED_INT_2_10_10_10_REV:return this._gl.UNSIGNED_INT_2_10_10_10_REV;case m.a.TEXTURETYPE_UNSIGNED_INT_24_8:return this._gl.UNSIGNED_INT_24_8;case m.a.TEXTURETYPE_UNSIGNED_INT_10F_11F_11F_REV:return this._gl.UNSIGNED_INT_10F_11F_11F_REV;case m.a.TEXTURETYPE_UNSIGNED_INT_5_9_9_9_REV:return this._gl.UNSIGNED_INT_5_9_9_9_REV;case m.a.TEXTURETYPE_FLOAT_32_UNSIGNED_INT_24_8_REV:return this._gl.FLOAT_32_UNSIGNED_INT_24_8_REV}return this._gl.UNSIGNED_BYTE},N.prototype._getInternalFormat=function(I){var V=this._gl.RGBA;switch(I){case m.a.TEXTUREFORMAT_ALPHA:V=this._gl.ALPHA;break;case m.a.TEXTUREFORMAT_LUMINANCE:V=this._gl.LUMINANCE;break;case m.a.TEXTUREFORMAT_LUMINANCE_ALPHA:V=this._gl.LUMINANCE_ALPHA;break;case m.a.TEXTUREFORMAT_RED:V=this._gl.RED;break;case m.a.TEXTUREFORMAT_RG:V=this._gl.RG;break;case m.a.TEXTUREFORMAT_RGB:V=this._gl.RGB;break;case m.a.TEXTUREFORMAT_RGBA:V=this._gl.RGBA}if(this._webGLVersion>1)switch(I){case m.a.TEXTUREFORMAT_RED_INTEGER:V=this._gl.RED_INTEGER;break;case m.a.TEXTUREFORMAT_RG_INTEGER:V=this._gl.RG_INTEGER;break;case m.a.TEXTUREFORMAT_RGB_INTEGER:V=this._gl.RGB_INTEGER;break;case m.a.TEXTUREFORMAT_RGBA_INTEGER:V=this._gl.RGBA_INTEGER}return V},N.prototype._getRGBABufferInternalSizedFormat=function(I,V){if(this._webGLVersion===1){if(V!==void 0)switch(V){case m.a.TEXTUREFORMAT_ALPHA:return this._gl.ALPHA;case m.a.TEXTUREFORMAT_LUMINANCE:return this._gl.LUMINANCE;case m.a.TEXTUREFORMAT_LUMINANCE_ALPHA:return this._gl.LUMINANCE_ALPHA;case m.a.TEXTUREFORMAT_RGB:return this._gl.RGB}return this._gl.RGBA}switch(I){case m.a.TEXTURETYPE_BYTE:switch(V){case m.a.TEXTUREFORMAT_RED:return this._gl.R8_SNORM;case m.a.TEXTUREFORMAT_RG:return this._gl.RG8_SNORM;case m.a.TEXTUREFORMAT_RGB:return this._gl.RGB8_SNORM;case m.a.TEXTUREFORMAT_RED_INTEGER:return this._gl.R8I;case m.a.TEXTUREFORMAT_RG_INTEGER:return this._gl.RG8I;case m.a.TEXTUREFORMAT_RGB_INTEGER:return this._gl.RGB8I;case m.a.TEXTUREFORMAT_RGBA_INTEGER:return this._gl.RGBA8I;default:return this._gl.RGBA8_SNORM}case m.a.TEXTURETYPE_UNSIGNED_BYTE:switch(V){case m.a.TEXTUREFORMAT_RED:return this._gl.R8;case m.a.TEXTUREFORMAT_RG:return this._gl.RG8;case m.a.TEXTUREFORMAT_RGB:return this._gl.RGB8;case m.a.TEXTUREFORMAT_RGBA:return this._gl.RGBA8;case m.a.TEXTUREFORMAT_RED_INTEGER:return this._gl.R8UI;case m.a.TEXTUREFORMAT_RG_INTEGER:return this._gl.RG8UI;case m.a.TEXTUREFORMAT_RGB_INTEGER:return this._gl.RGB8UI;case m.a.TEXTUREFORMAT_RGBA_INTEGER:return this._gl.RGBA8UI;case m.a.TEXTUREFORMAT_ALPHA:return this._gl.ALPHA;case m.a.TEXTUREFORMAT_LUMINANCE:return this._gl.LUMINANCE;case m.a.TEXTUREFORMAT_LUMINANCE_ALPHA:return this._gl.LUMINANCE_ALPHA;default:return this._gl.RGBA8}case m.a.TEXTURETYPE_SHORT:switch(V){case m.a.TEXTUREFORMAT_RED_INTEGER:return this._gl.R16I;case m.a.TEXTUREFORMAT_RG_INTEGER:return this._gl.RG16I;case m.a.TEXTUREFORMAT_RGB_INTEGER:return this._gl.RGB16I;case m.a.TEXTUREFORMAT_RGBA_INTEGER:default:return this._gl.RGBA16I}case m.a.TEXTURETYPE_UNSIGNED_SHORT:switch(V){case m.a.TEXTUREFORMAT_RED_INTEGER:return this._gl.R16UI;case m.a.TEXTUREFORMAT_RG_INTEGER:return this._gl.RG16UI;case m.a.TEXTUREFORMAT_RGB_INTEGER:return this._gl.RGB16UI;case m.a.TEXTUREFORMAT_RGBA_INTEGER:default:return this._gl.RGBA16UI}case m.a.TEXTURETYPE_INT:switch(V){case m.a.TEXTUREFORMAT_RED_INTEGER:return this._gl.R32I;case m.a.TEXTUREFORMAT_RG_INTEGER:return this._gl.RG32I;case m.a.TEXTUREFORMAT_RGB_INTEGER:return this._gl.RGB32I;case m.a.TEXTUREFORMAT_RGBA_INTEGER:default:return this._gl.RGBA32I}case m.a.TEXTURETYPE_UNSIGNED_INTEGER:switch(V){case m.a.TEXTUREFORMAT_RED_INTEGER:return this._gl.R32UI;case m.a.TEXTUREFORMAT_RG_INTEGER:return this._gl.RG32UI;case m.a.TEXTUREFORMAT_RGB_INTEGER:return this._gl.RGB32UI;case m.a.TEXTUREFORMAT_RGBA_INTEGER:default:return this._gl.RGBA32UI}case m.a.TEXTURETYPE_FLOAT:switch(V){case m.a.TEXTUREFORMAT_RED:return this._gl.R32F;case m.a.TEXTUREFORMAT_RG:return this._gl.RG32F;case m.a.TEXTUREFORMAT_RGB:return this._gl.RGB32F;case m.a.TEXTUREFORMAT_RGBA:default:return this._gl.RGBA32F}case m.a.TEXTURETYPE_HALF_FLOAT:switch(V){case m.a.TEXTUREFORMAT_RED:return this._gl.R16F;case m.a.TEXTUREFORMAT_RG:return this._gl.RG16F;case m.a.TEXTUREFORMAT_RGB:return this._gl.RGB16F;case m.a.TEXTUREFORMAT_RGBA:default:return this._gl.RGBA16F}case m.a.TEXTURETYPE_UNSIGNED_SHORT_5_6_5:return this._gl.RGB565;case m.a.TEXTURETYPE_UNSIGNED_INT_10F_11F_11F_REV:return this._gl.R11F_G11F_B10F;case m.a.TEXTURETYPE_UNSIGNED_INT_5_9_9_9_REV:return this._gl.RGB9_E5;case m.a.TEXTURETYPE_UNSIGNED_SHORT_4_4_4_4:return this._gl.RGBA4;case m.a.TEXTURETYPE_UNSIGNED_SHORT_5_5_5_1:return this._gl.RGB5_A1;case m.a.TEXTURETYPE_UNSIGNED_INT_2_10_10_10_REV:switch(V){case m.a.TEXTUREFORMAT_RGBA:return this._gl.RGB10_A2;case m.a.TEXTUREFORMAT_RGBA_INTEGER:return this._gl.RGB10_A2UI;default:return this._gl.RGB10_A2}}return this._gl.RGBA8},N.prototype._getRGBAMultiSampleBufferFormat=function(I){return I===m.a.TEXTURETYPE_FLOAT?this._gl.RGBA32F:I===m.a.TEXTURETYPE_HALF_FLOAT?this._gl.RGBA16F:this._gl.RGBA8},N.prototype._loadFile=function(I,V,X,j,ne,te){var de=this,pe=N._FileToolsLoadFile(I,V,X,j,ne,te);return this._activeRequests.push(pe),pe.onCompleteObservable.add(function(ae){de._activeRequests.splice(de._activeRequests.indexOf(ae),1)}),pe},N._FileToolsLoadFile=function(I,V,X,j,ne,te){throw C.a.WarnImport("FileTools")},N.prototype.readPixels=function(I,V,X,j,ne){ne===void 0&&(ne=!0);var te=ne?4:3,de=ne?this._gl.RGBA:this._gl.RGB,pe=new Uint8Array(j*X*te);return this._gl.readPixels(I,V,X,j,de,this._gl.UNSIGNED_BYTE,pe),pe},Object.defineProperty(N,"IsSupported",{get:function(){return this.isSupported()},enumerable:!1,configurable:!0}),N.isSupported=function(){if(this._HasMajorPerformanceCaveat!==null)return!this._HasMajorPerformanceCaveat;if(this._IsSupported===null)try{var I=v.a.CreateCanvas(1,1),V=I.getContext("webgl")||I.getContext("experimental-webgl");this._IsSupported=V!=null&&!!window.WebGLRenderingContext}catch{this._IsSupported=!1}return this._IsSupported},Object.defineProperty(N,"HasMajorPerformanceCaveat",{get:function(){if(this._HasMajorPerformanceCaveat===null)try{var I=v.a.CreateCanvas(1,1),V=I.getContext("webgl",{failIfMajorPerformanceCaveat:!0})||I.getContext("experimental-webgl",{failIfMajorPerformanceCaveat:!0});this._HasMajorPerformanceCaveat=!V}catch{this._HasMajorPerformanceCaveat=!1}return this._HasMajorPerformanceCaveat},enumerable:!1,configurable:!0}),N.CeilingPOT=function(I){return I--,I|=I>>1,I|=I>>2,I|=I>>4,I|=I>>8,I|=I>>16,++I},N.FloorPOT=function(I){return I|=I>>1,I|=I>>2,I|=I>>4,I|=I>>8,(I|=I>>16)-(I>>1)},N.NearestPOT=function(I){var V=N.CeilingPOT(I),X=N.FloorPOT(I);return V-I>I-X?X:V},N.GetExponentOfTwo=function(I,V,X){var j;switch(X===void 0&&(X=m.a.SCALEMODE_NEAREST),X){case m.a.SCALEMODE_FLOOR:j=N.FloorPOT(I);break;case m.a.SCALEMODE_NEAREST:j=N.NearestPOT(I);break;case m.a.SCALEMODE_CEILING:default:j=N.CeilingPOT(I)}return Math.min(j,V)},N.QueueNewFrame=function(I,V){return A.a.IsWindowObjectExist()?(V||(V=window),V.requestPostAnimationFrame?V.requestPostAnimationFrame(I):V.requestAnimationFrame?V.requestAnimationFrame(I):V.msRequestAnimationFrame?V.msRequestAnimationFrame(I):V.webkitRequestAnimationFrame?V.webkitRequestAnimationFrame(I):V.mozRequestAnimationFrame?V.mozRequestAnimationFrame(I):V.oRequestAnimationFrame?V.oRequestAnimationFrame(I):window.setTimeout(I,16)):typeof requestAnimationFrame<"u"?requestAnimationFrame(I):setTimeout(I,16)},N.prototype.getHostDocument=function(){return this._renderingCanvas&&this._renderingCanvas.ownerDocument?this._renderingCanvas.ownerDocument:document},N.ExceptionList=[{key:"Chrome/63.0",capture:"63\\.0\\.3239\\.(\\d+)",captureConstraint:108,targets:["uniformBuffer"]},{key:"Firefox/58",capture:null,captureConstraint:null,targets:["uniformBuffer"]},{key:"Firefox/59",capture:null,captureConstraint:null,targets:["uniformBuffer"]},{key:"Chrome/72.+?Mobile",capture:null,captureConstraint:null,targets:["vao"]},{key:"Chrome/73.+?Mobile",capture:null,captureConstraint:null,targets:["vao"]},{key:"Chrome/74.+?Mobile",capture:null,captureConstraint:null,targets:["vao"]},{key:"Mac OS.+Chrome/71",capture:null,captureConstraint:null,targets:["vao"]},{key:"Mac OS.+Chrome/72",capture:null,captureConstraint:null,targets:["vao"]}],N._TextureLoaders=[],N.CollisionsEpsilon=.001,N._IsSupported=null,N._HasMajorPerformanceCaveat=null,N}()},function(Me,y,f){f.d(y,"b",function(){return U}),f.d(y,"a",function(){return R});var U,_=f(6),C=f(102),u=f(2),M=f(21);(function(x){x[x.Unknown=0]="Unknown",x[x.Url=1]="Url",x[x.Temp=2]="Temp",x[x.Raw=3]="Raw",x[x.Dynamic=4]="Dynamic",x[x.RenderTarget=5]="RenderTarget",x[x.MultiRenderTarget=6]="MultiRenderTarget",x[x.Cube=7]="Cube",x[x.CubeRaw=8]="CubeRaw",x[x.CubePrefiltered=9]="CubePrefiltered",x[x.Raw3D=10]="Raw3D",x[x.Raw2DArray=11]="Raw2DArray",x[x.Depth=12]="Depth",x[x.CubeRawRGBD=13]="CubeRawRGBD"})(U||(U={}));var R=function(){function x(m,c,T){T===void 0&&(T=!1),this.isReady=!1,this.isCube=!1,this.is3D=!1,this.is2DArray=!1,this.isMultiview=!1,this.url="",this.samplingMode=-1,this.generateMipMaps=!1,this.samples=0,this.type=-1,this.format=-1,this.onLoadedObservable=new _.c,this.width=0,this.height=0,this.depth=0,this.baseWidth=0,this.baseHeight=0,this.baseDepth=0,this.invertY=!1,this._invertVScale=!1,this._associatedChannel=-1,this._source=U.Unknown,this._buffer=null,this._bufferView=null,this._bufferViewArray=null,this._bufferViewArrayArray=null,this._size=0,this._extension="",this._files=null,this._workingCanvas=null,this._workingContext=null,this._framebuffer=null,this._depthStencilBuffer=null,this._MSAAFramebuffer=null,this._MSAARenderBuffer=null,this._attachments=null,this._textureArray=null,this._cachedCoordinatesMode=null,this._cachedWrapU=null,this._cachedWrapV=null,this._cachedWrapR=null,this._cachedAnisotropicFilteringLevel=null,this._isDisabled=!1,this._compression=null,this._generateStencilBuffer=!1,this._generateDepthBuffer=!1,this._comparisonFunction=0,this._sphericalPolynomial=null,this._lodGenerationScale=0,this._lodGenerationOffset=0,this._colorTextureArray=null,this._depthStencilTextureArray=null,this._lodTextureHigh=null,this._lodTextureMid=null,this._lodTextureLow=null,this._isRGBD=!1,this._linearSpecularLOD=!1,this._irradianceTexture=null,this._webGLTexture=null,this._references=1,this._gammaSpace=null,this._engine=m,this._source=c,T||(this._webGLTexture=m._createTexture())}return x.prototype.getEngine=function(){return this._engine},Object.defineProperty(x.prototype,"source",{get:function(){return this._source},enumerable:!1,configurable:!0}),x.prototype.incrementReferences=function(){this._references++},x.prototype.updateSize=function(m,c,T){T===void 0&&(T=1),this.width=m,this.height=c,this.depth=T,this.baseWidth=m,this.baseHeight=c,this.baseDepth=T,this._size=m*c*T},x.prototype._rebuild=function(){var m,c,T=this;switch(this.isReady=!1,this._cachedCoordinatesMode=null,this._cachedWrapU=null,this._cachedWrapV=null,this._cachedAnisotropicFilteringLevel=null,this.source){case U.Temp:return;case U.Url:return void(c=this._engine.createTexture((m=this._originalUrl)!==null&&m!==void 0?m:this.url,!this.generateMipMaps,this.invertY,null,this.samplingMode,function(){c._swapAndDie(T),T.isReady=!0},null,this._buffer,void 0,this.format));case U.Raw:return(c=this._engine.createRawTexture(this._bufferView,this.baseWidth,this.baseHeight,this.format,this.generateMipMaps,this.invertY,this.samplingMode,this._compression))._swapAndDie(this),void(this.isReady=!0);case U.Raw3D:return(c=this._engine.createRawTexture3D(this._bufferView,this.baseWidth,this.baseHeight,this.baseDepth,this.format,this.generateMipMaps,this.invertY,this.samplingMode,this._compression))._swapAndDie(this),void(this.isReady=!0);case U.Raw2DArray:return(c=this._engine.createRawTexture2DArray(this._bufferView,this.baseWidth,this.baseHeight,this.baseDepth,this.format,this.generateMipMaps,this.invertY,this.samplingMode,this._compression))._swapAndDie(this),void(this.isReady=!0);case U.Dynamic:return(c=this._engine.createDynamicTexture(this.baseWidth,this.baseHeight,this.generateMipMaps,this.samplingMode))._swapAndDie(this),void this._engine.updateDynamicTexture(this,this._engine.getRenderingCanvas(),this.invertY,void 0,void 0,!0);case U.RenderTarget:var A=new C.a;if(A.generateDepthBuffer=this._generateDepthBuffer,A.generateMipMaps=this.generateMipMaps,A.generateStencilBuffer=this._generateStencilBuffer,A.samplingMode=this.samplingMode,A.type=this.type,this.isCube)c=this._engine.createRenderTargetCubeTexture(this.width,A);else{var S={width:this.width,height:this.height,layers:this.is2DArray?this.depth:void 0};c=this._engine.createRenderTargetTexture(S,A)}return c._swapAndDie(this),void(this.isReady=!0);case U.Depth:var g={bilinearFiltering:this.samplingMode!==u.a.TEXTURE_BILINEAR_SAMPLINGMODE,comparisonFunction:this._comparisonFunction,generateStencil:this._generateStencilBuffer,isCube:this.isCube},l={width:this.width,height:this.height,layers:this.is2DArray?this.depth:void 0};return(c=this._engine.createDepthStencilTexture(l,g))._swapAndDie(this),void(this.isReady=!0);case U.Cube:return void(c=this._engine.createCubeTexture(this.url,null,this._files,!this.generateMipMaps,function(){c._swapAndDie(T),T.isReady=!0},null,this.format,this._extension));case U.CubeRaw:return(c=this._engine.createRawCubeTexture(this._bufferViewArray,this.width,this.format,this.type,this.generateMipMaps,this.invertY,this.samplingMode,this._compression))._swapAndDie(this),void(this.isReady=!0);case U.CubeRawRGBD:return c=this._engine.createRawCubeTexture(null,this.width,this.format,this.type,this.generateMipMaps,this.invertY,this.samplingMode,this._compression),void x._UpdateRGBDAsync(c,this._bufferViewArrayArray,this._sphericalPolynomial,this._lodGenerationScale,this._lodGenerationOffset).then(function(){c._swapAndDie(T),T.isReady=!0});case U.CubePrefiltered:return void((c=this._engine.createPrefilteredCubeTexture(this.url,null,this._lodGenerationScale,this._lodGenerationOffset,function(h){h&&h._swapAndDie(T),T.isReady=!0},null,this.format,this._extension))._sphericalPolynomial=this._sphericalPolynomial)}},x.prototype._swapAndDie=function(m){m._webGLTexture=this._webGLTexture,m._isRGBD=this._isRGBD,this._framebuffer&&(m._framebuffer=this._framebuffer),this._depthStencilBuffer&&(m._depthStencilBuffer=this._depthStencilBuffer),m._depthStencilTexture=this._depthStencilTexture,this._lodTextureHigh&&(m._lodTextureHigh&&m._lodTextureHigh.dispose(),m._lodTextureHigh=this._lodTextureHigh),this._lodTextureMid&&(m._lodTextureMid&&m._lodTextureMid.dispose(),m._lodTextureMid=this._lodTextureMid),this._lodTextureLow&&(m._lodTextureLow&&m._lodTextureLow.dispose(),m._lodTextureLow=this._lodTextureLow),this._irradianceTexture&&(m._irradianceTexture&&m._irradianceTexture.dispose(),m._irradianceTexture=this._irradianceTexture);var c,T=this._engine.getLoadedTexturesCache();(c=T.indexOf(this))!==-1&&T.splice(c,1),(c=T.indexOf(m))===-1&&T.push(m)},x.prototype.dispose=function(){this._webGLTexture&&(this._references--,this._references===0&&(this._engine._releaseTexture(this),this._webGLTexture=null))},x._UpdateRGBDAsync=function(m,c,T,A,S){throw M.a.WarnImport("environmentTextureTools")},x}()},function(Me,y,f){f.d(y,"b",function(){return U}),f.d(y,"c",function(){return _}),f.d(y,"a",function(){return C});var U=1/2.2,_=2.2,C=.001},function(Me,y,f){f.d(y,"a",function(){return x});var U=f(1),_=f(0),C=f(3),u=f(6),M=f(22),R=f(21),x=function(){function m(c,T){T===void 0&&(T=null),this.state="",this.metadata=null,this.reservedDataStore=null,this._doNotSerialize=!1,this._isDisposed=!1,this.animations=new Array,this._ranges={},this.onReady=null,this._isEnabled=!0,this._isParentEnabled=!0,this._isReady=!0,this._currentRenderId=-1,this._parentUpdateId=-1,this._childUpdateId=-1,this._waitingParentId=null,this._cache={},this._parentNode=null,this._children=null,this._worldMatrix=_.a.Identity(),this._worldMatrixDeterminant=0,this._worldMatrixDeterminantIsDirty=!0,this._sceneRootNodesIndex=-1,this._animationPropertiesOverride=null,this._isNode=!0,this.onDisposeObservable=new u.c,this._onDisposeObserver=null,this._behaviors=new Array,this.name=c,this.id=c,this._scene=T||M.a.LastCreatedScene,this.uniqueId=this._scene.getUniqueId(),this._initCache()}return m.AddNodeConstructor=function(c,T){this._NodeConstructors[c]=T},m.Construct=function(c,T,A,S){var g=this._NodeConstructors[c];return g?g(T,A,S):null},Object.defineProperty(m.prototype,"doNotSerialize",{get:function(){return!!this._doNotSerialize||!!this._parentNode&&this._parentNode.doNotSerialize},set:function(c){this._doNotSerialize=c},enumerable:!1,configurable:!0}),m.prototype.isDisposed=function(){return this._isDisposed},Object.defineProperty(m.prototype,"parent",{get:function(){return this._parentNode},set:function(c){if(this._parentNode!==c){var T=this._parentNode;if(this._parentNode&&this._parentNode._children!==void 0&&this._parentNode._children!==null){var A=this._parentNode._children.indexOf(this);A!==-1&&this._parentNode._children.splice(A,1),c||this._isDisposed||this._addToSceneRootNodes()}this._parentNode=c,this._parentNode&&(this._parentNode._children!==void 0&&this._parentNode._children!==null||(this._parentNode._children=new Array),this._parentNode._children.push(this),T||this._removeFromSceneRootNodes()),this._syncParentEnabledState()}},enumerable:!1,configurable:!0}),m.prototype._addToSceneRootNodes=function(){this._sceneRootNodesIndex===-1&&(this._sceneRootNodesIndex=this._scene.rootNodes.length,this._scene.rootNodes.push(this))},m.prototype._removeFromSceneRootNodes=function(){if(this._sceneRootNodesIndex!==-1){var c=this._scene.rootNodes,T=c.length-1;c[this._sceneRootNodesIndex]=c[T],c[this._sceneRootNodesIndex]._sceneRootNodesIndex=this._sceneRootNodesIndex,this._scene.rootNodes.pop(),this._sceneRootNodesIndex=-1}},Object.defineProperty(m.prototype,"animationPropertiesOverride",{get:function(){return this._animationPropertiesOverride?this._animationPropertiesOverride:this._scene.animationPropertiesOverride},set:function(c){this._animationPropertiesOverride=c},enumerable:!1,configurable:!0}),m.prototype.getClassName=function(){return"Node"},Object.defineProperty(m.prototype,"onDispose",{set:function(c){this._onDisposeObserver&&this.onDisposeObservable.remove(this._onDisposeObserver),this._onDisposeObserver=this.onDisposeObservable.add(c)},enumerable:!1,configurable:!0}),m.prototype.getScene=function(){return this._scene},m.prototype.getEngine=function(){return this._scene.getEngine()},m.prototype.addBehavior=function(c,T){var A=this;return T===void 0&&(T=!1),this._behaviors.indexOf(c)!==-1||(c.init(),this._scene.isLoading&&!T?this._scene.onDataLoadedObservable.addOnce(function(){c.attach(A)}):c.attach(this),this._behaviors.push(c)),this},m.prototype.removeBehavior=function(c){var T=this._behaviors.indexOf(c);return T===-1||(this._behaviors[T].detach(),this._behaviors.splice(T,1)),this},Object.defineProperty(m.prototype,"behaviors",{get:function(){return this._behaviors},enumerable:!1,configurable:!0}),m.prototype.getBehaviorByName=function(c){for(var T=0,A=this._behaviors;T<A.length;T++){var S=A[T];if(S.name===c)return S}return null},m.prototype.getWorldMatrix=function(){return this._currentRenderId!==this._scene.getRenderId()&&this.computeWorldMatrix(),this._worldMatrix},m.prototype._getWorldMatrixDeterminant=function(){return this._worldMatrixDeterminantIsDirty&&(this._worldMatrixDeterminantIsDirty=!1,this._worldMatrixDeterminant=this._worldMatrix.determinant()),this._worldMatrixDeterminant},Object.defineProperty(m.prototype,"worldMatrixFromCache",{get:function(){return this._worldMatrix},enumerable:!1,configurable:!0}),m.prototype._initCache=function(){this._cache={},this._cache.parent=void 0},m.prototype.updateCache=function(c){!c&&this.isSynchronized()||(this._cache.parent=this.parent,this._updateCache())},m.prototype._getActionManagerForTrigger=function(c,T){return this.parent?this.parent._getActionManagerForTrigger(c,!1):null},m.prototype._updateCache=function(c){},m.prototype._isSynchronized=function(){return!0},m.prototype._markSyncedWithParent=function(){this._parentNode&&(this._parentUpdateId=this._parentNode._childUpdateId)},m.prototype.isSynchronizedWithParent=function(){return!this._parentNode||this._parentUpdateId===this._parentNode._childUpdateId&&this._parentNode.isSynchronized()},m.prototype.isSynchronized=function(){return this._cache.parent!=this._parentNode?(this._cache.parent=this._parentNode,!1):!(this._parentNode&&!this.isSynchronizedWithParent())&&this._isSynchronized()},m.prototype.isReady=function(c){return this._isReady},m.prototype.isEnabled=function(c){return c===void 0&&(c=!0),c===!1?this._isEnabled:!!this._isEnabled&&this._isParentEnabled},m.prototype._syncParentEnabledState=function(){this._isParentEnabled=!this._parentNode||this._parentNode.isEnabled(),this._children&&this._children.forEach(function(c){c._syncParentEnabledState()})},m.prototype.setEnabled=function(c){this._isEnabled=c,this._syncParentEnabledState()},m.prototype.isDescendantOf=function(c){return!!this.parent&&(this.parent===c||this.parent.isDescendantOf(c))},m.prototype._getDescendants=function(c,T,A){if(T===void 0&&(T=!1),this._children)for(var S=0;S<this._children.length;S++){var g=this._children[S];A&&!A(g)||c.push(g),T||g._getDescendants(c,!1,A)}},m.prototype.getDescendants=function(c,T){var A=new Array;return this._getDescendants(A,c,T),A},m.prototype.getChildMeshes=function(c,T){var A=[];return this._getDescendants(A,c,function(S){return(!T||T(S))&&S.cullingStrategy!==void 0}),A},m.prototype.getChildren=function(c,T){return T===void 0&&(T=!0),this.getDescendants(T,c)},m.prototype._setReady=function(c){c!==this._isReady&&(c?(this.onReady&&this.onReady(this),this._isReady=!0):this._isReady=!1)},m.prototype.getAnimationByName=function(c){for(var T=0;T<this.animations.length;T++){var A=this.animations[T];if(A.name===c)return A}return null},m.prototype.createAnimationRange=function(c,T,A){if(!this._ranges[c]){this._ranges[c]=m._AnimationRangeFactory(c,T,A);for(var S=0,g=this.animations.length;S<g;S++)this.animations[S]&&this.animations[S].createRange(c,T,A)}},m.prototype.deleteAnimationRange=function(c,T){T===void 0&&(T=!0);for(var A=0,S=this.animations.length;A<S;A++)this.animations[A]&&this.animations[A].deleteRange(c,T);this._ranges[c]=null},m.prototype.getAnimationRange=function(c){return this._ranges[c]||null},m.prototype.getAnimationRanges=function(){var c,T=[];for(c in this._ranges)T.push(this._ranges[c]);return T},m.prototype.beginAnimation=function(c,T,A,S){var g=this.getAnimationRange(c);return g?this._scene.beginAnimation(this,g.from,g.to,T,A,S):null},m.prototype.serializeAnimationRanges=function(){var c=[];for(var T in this._ranges){var A=this._ranges[T];if(A){var S={};S.name=T,S.from=A.from,S.to=A.to,c.push(S)}}return c},m.prototype.computeWorldMatrix=function(c){return this._worldMatrix||(this._worldMatrix=_.a.Identity()),this._worldMatrix},m.prototype.dispose=function(c,T){if(T===void 0&&(T=!1),this._isDisposed=!0,!c)for(var A=0,S=this.getDescendants(!0);A<S.length;A++)S[A].dispose(c,T);this.parent?this.parent=null:this._removeFromSceneRootNodes(),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear();for(var g=0,l=this._behaviors;g<l.length;g++)l[g].detach();this._behaviors=[]},m.ParseAnimationRanges=function(c,T,A){if(T.ranges)for(var S=0;S<T.ranges.length;S++){var g=T.ranges[S];c.createAnimationRange(g.name,g.from,g.to)}},m.prototype.getHierarchyBoundingVectors=function(c,T){var A,S;if(c===void 0&&(c=!0),T===void 0&&(T=null),this.getScene().incrementRenderId(),this.computeWorldMatrix(!0),this.getBoundingInfo&&this.subMeshes){var g=this.getBoundingInfo();A=g.boundingBox.minimumWorld.clone(),S=g.boundingBox.maximumWorld.clone()}else A=new _.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),S=new _.e(-Number.MAX_VALUE,-Number.MAX_VALUE,-Number.MAX_VALUE);if(c)for(var l=0,h=this.getDescendants(!1);l<h.length;l++){var v=h[l];if(v.computeWorldMatrix(!0),(!T||T(v))&&v.getBoundingInfo&&v.getTotalVertices()!==0){var E=v.getBoundingInfo().boundingBox,D=E.minimumWorld,w=E.maximumWorld;_.e.CheckExtends(D,A,S),_.e.CheckExtends(w,A,S)}}return{min:A,max:S}},m._AnimationRangeFactory=function(c,T,A){throw R.a.WarnImport("AnimationRange")},m._NodeConstructors={},Object(U.c)([Object(C.c)()],m.prototype,"name",void 0),Object(U.c)([Object(C.c)()],m.prototype,"id",void 0),Object(U.c)([Object(C.c)()],m.prototype,"uniqueId",void 0),Object(U.c)([Object(C.c)()],m.prototype,"state",void 0),Object(U.c)([Object(C.c)()],m.prototype,"metadata",void 0),m}()},function(Me,y,f){f.d(y,"b",function(){return de}),f.d(y,"a",function(){return pe});var U=f(1),_=f(3),C=f(33),u=f(20),M=f(0),R=f(9),x=f(4),m=f(105),c=f(42),T=f(25),A=f(76),S=f(87),g=f(15),l=f(10),h=f(11),v=f(19),E=f(5),D=`uniform vec4 vDiffuseColor;
-#ifdef SPECULARTERM
-uniform vec4 vSpecularColor;
-#endif
-uniform vec3 vEmissiveColor;
-uniform float visibility;
-
-#ifdef DIFFUSE
-uniform vec2 vDiffuseInfos;
-#endif
-#ifdef AMBIENT
-uniform vec2 vAmbientInfos;
-#endif
-#ifdef OPACITY
-uniform vec2 vOpacityInfos;
-#endif
-#ifdef EMISSIVE
-uniform vec2 vEmissiveInfos;
-#endif
-#ifdef LIGHTMAP
-uniform vec2 vLightmapInfos;
-#endif
-#ifdef BUMP
-uniform vec3 vBumpInfos;
-uniform vec2 vTangentSpaceParams;
-#endif
-#if defined(REFLECTIONMAP_SPHERICAL) || defined(REFLECTIONMAP_PROJECTION) || defined(REFRACTION)
-uniform mat4 view;
-#endif
-#ifdef REFRACTION
-uniform vec4 vRefractionInfos;
-#ifndef REFRACTIONMAP_3D
-uniform mat4 refractionMatrix;
-#endif
-#ifdef REFRACTIONFRESNEL
-uniform vec4 refractionLeftColor;
-uniform vec4 refractionRightColor;
-#endif
-#endif
-#if defined(SPECULAR) && defined(SPECULARTERM)
-uniform vec2 vSpecularInfos;
-#endif
-#ifdef DIFFUSEFRESNEL
-uniform vec4 diffuseLeftColor;
-uniform vec4 diffuseRightColor;
-#endif
-#ifdef OPACITYFRESNEL
-uniform vec4 opacityParts;
-#endif
-#ifdef EMISSIVEFRESNEL
-uniform vec4 emissiveLeftColor;
-uniform vec4 emissiveRightColor;
-#endif
-
-#ifdef REFLECTION
-uniform vec2 vReflectionInfos;
-#if defined(REFLECTIONMAP_PLANAR) || defined(REFLECTIONMAP_CUBIC) || defined(REFLECTIONMAP_PROJECTION) || defined(REFLECTIONMAP_EQUIRECTANGULAR) || defined(REFLECTIONMAP_SPHERICAL) || defined(REFLECTIONMAP_SKYBOX)
-uniform mat4 reflectionMatrix;
-#endif
-#ifndef REFLECTIONMAP_SKYBOX
-#if defined(USE_LOCAL_REFLECTIONMAP_CUBIC) && defined(REFLECTIONMAP_CUBIC)
-uniform vec3 vReflectionPosition;
-uniform vec3 vReflectionSize;
-#endif
-#endif
-#ifdef REFLECTIONFRESNEL
-uniform vec4 reflectionLeftColor;
-uniform vec4 reflectionRightColor;
-#endif
-#endif`;E.a.IncludesShadersStore.defaultFragmentDeclaration=D;var w=`layout(std140,column_major) uniform;
-uniform Material
-{
-vec4 diffuseLeftColor;
-vec4 diffuseRightColor;
-vec4 opacityParts;
-vec4 reflectionLeftColor;
-vec4 reflectionRightColor;
-vec4 refractionLeftColor;
-vec4 refractionRightColor;
-vec4 emissiveLeftColor;
-vec4 emissiveRightColor;
-vec2 vDiffuseInfos;
-vec2 vAmbientInfos;
-vec2 vOpacityInfos;
-vec2 vReflectionInfos;
-vec3 vReflectionPosition;
-vec3 vReflectionSize;
-vec2 vEmissiveInfos;
-vec2 vLightmapInfos;
-vec2 vSpecularInfos;
-vec3 vBumpInfos;
-mat4 diffuseMatrix;
-mat4 ambientMatrix;
-mat4 opacityMatrix;
-mat4 reflectionMatrix;
-mat4 emissiveMatrix;
-mat4 lightmapMatrix;
-mat4 specularMatrix;
-mat4 bumpMatrix;
-vec2 vTangentSpaceParams;
-float pointSize;
-mat4 refractionMatrix;
-vec4 vRefractionInfos;
-vec4 vSpecularColor;
-vec3 vEmissiveColor;
-float visibility;
-vec4 vDiffuseColor;
-vec4 vDetailInfos;
-mat4 detailMatrix;
-};
-uniform Scene {
-mat4 viewProjection;
-#ifdef MULTIVIEW
-mat4 viewProjectionR;
-#endif
-mat4 view;
-};
-`;E.a.IncludesShadersStore.defaultUboDeclaration=w,f(160),f(59),f(106),f(107),f(154),f(130),f(161),f(131),f(108),f(109),f(132),f(133),f(115),f(116),f(125),f(110),f(134),f(162),f(135),f(155),f(136);var N=`#include<__decl__defaultFragment>
-#if defined(BUMP) || !defined(NORMAL)
-#extension GL_OES_standard_derivatives : enable
-#endif
-#include<prePassDeclaration>[SCENE_MRT_COUNT]
-#define CUSTOM_FRAGMENT_BEGIN
-#ifdef LOGARITHMICDEPTH
-#extension GL_EXT_frag_depth : enable
-#endif
-
-#define RECIPROCAL_PI2 0.15915494
-uniform vec3 vEyePosition;
-uniform vec3 vAmbientColor;
-
-varying vec3 vPositionW;
-#ifdef NORMAL
-varying vec3 vNormalW;
-#endif
-#ifdef VERTEXCOLOR
-varying vec4 vColor;
-#endif
-#ifdef MAINUV1
-varying vec2 vMainUV1;
-#endif
-#ifdef MAINUV2
-varying vec2 vMainUV2;
-#endif
-
-#include<helperFunctions>
-
-#include<__decl__lightFragment>[0..maxSimultaneousLights]
-#include<lightsFragmentFunctions>
-#include<shadowsFragmentFunctions>
-
-#ifdef DIFFUSE
-#if DIFFUSEDIRECTUV == 1
-#define vDiffuseUV vMainUV1
-#elif DIFFUSEDIRECTUV == 2
-#define vDiffuseUV vMainUV2
-#else
-varying vec2 vDiffuseUV;
-#endif
-uniform sampler2D diffuseSampler;
-#endif
-#ifdef AMBIENT
-#if AMBIENTDIRECTUV == 1
-#define vAmbientUV vMainUV1
-#elif AMBIENTDIRECTUV == 2
-#define vAmbientUV vMainUV2
-#else
-varying vec2 vAmbientUV;
-#endif
-uniform sampler2D ambientSampler;
-#endif
-#ifdef OPACITY
-#if OPACITYDIRECTUV == 1
-#define vOpacityUV vMainUV1
-#elif OPACITYDIRECTUV == 2
-#define vOpacityUV vMainUV2
-#else
-varying vec2 vOpacityUV;
-#endif
-uniform sampler2D opacitySampler;
-#endif
-#ifdef EMISSIVE
-#if EMISSIVEDIRECTUV == 1
-#define vEmissiveUV vMainUV1
-#elif EMISSIVEDIRECTUV == 2
-#define vEmissiveUV vMainUV2
-#else
-varying vec2 vEmissiveUV;
-#endif
-uniform sampler2D emissiveSampler;
-#endif
-#ifdef LIGHTMAP
-#if LIGHTMAPDIRECTUV == 1
-#define vLightmapUV vMainUV1
-#elif LIGHTMAPDIRECTUV == 2
-#define vLightmapUV vMainUV2
-#else
-varying vec2 vLightmapUV;
-#endif
-uniform sampler2D lightmapSampler;
-#endif
-#ifdef REFRACTION
-#ifdef REFRACTIONMAP_3D
-uniform samplerCube refractionCubeSampler;
-#else
-uniform sampler2D refraction2DSampler;
-#endif
-#endif
-#if defined(SPECULAR) && defined(SPECULARTERM)
-#if SPECULARDIRECTUV == 1
-#define vSpecularUV vMainUV1
-#elif SPECULARDIRECTUV == 2
-#define vSpecularUV vMainUV2
-#else
-varying vec2 vSpecularUV;
-#endif
-uniform sampler2D specularSampler;
-#endif
-#ifdef ALPHATEST
-uniform float alphaCutOff;
-#endif
-
-#include<fresnelFunction>
-
-#ifdef REFLECTION
-#ifdef REFLECTIONMAP_3D
-uniform samplerCube reflectionCubeSampler;
-#else
-uniform sampler2D reflection2DSampler;
-#endif
-#ifdef REFLECTIONMAP_SKYBOX
-varying vec3 vPositionUVW;
-#else
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-varying vec3 vDirectionW;
-#endif
-#endif
-#include<reflectionFunction>
-#endif
-#include<imageProcessingDeclaration>
-#include<imageProcessingFunctions>
-#include<bumpFragmentMainFunctions>
-#include<bumpFragmentFunctions>
-#include<clipPlaneFragmentDeclaration>
-#include<logDepthDeclaration>
-#include<fogFragmentDeclaration>
-#define CUSTOM_FRAGMENT_DEFINITIONS
-void main(void) {
-#define CUSTOM_FRAGMENT_MAIN_BEGIN
-#include<clipPlaneFragment>
-vec3 viewDirectionW=normalize(vEyePosition-vPositionW);
-
-vec4 baseColor=vec4(1.,1.,1.,1.);
-vec3 diffuseColor=vDiffuseColor.rgb;
-
-float alpha=vDiffuseColor.a;
-
-#ifdef NORMAL
-vec3 normalW=normalize(vNormalW);
-#else
-vec3 normalW=normalize(-cross(dFdx(vPositionW),dFdy(vPositionW)));
-#endif
-#include<bumpFragment>
-#ifdef TWOSIDEDLIGHTING
-normalW=gl_FrontFacing ? normalW : -normalW;
-#endif
-#ifdef DIFFUSE
-baseColor=texture2D(diffuseSampler,vDiffuseUV+uvOffset);
-#if defined(ALPHATEST) && !defined(ALPHATEST_AFTERALLALPHACOMPUTATIONS)
-if (baseColor.a<alphaCutOff)
-discard;
-#endif
-#ifdef ALPHAFROMDIFFUSE
-alpha*=baseColor.a;
-#endif
-#define CUSTOM_FRAGMENT_UPDATE_ALPHA
-baseColor.rgb*=vDiffuseInfos.y;
-#endif
-#include<depthPrePass>
-#ifdef VERTEXCOLOR
-baseColor.rgb*=vColor.rgb;
-#endif
-#ifdef DETAIL
-baseColor.rgb=baseColor.rgb*2.0*mix(0.5,detailColor.r,vDetailInfos.y);
-#endif
-#define CUSTOM_FRAGMENT_UPDATE_DIFFUSE
-
-vec3 baseAmbientColor=vec3(1.,1.,1.);
-#ifdef AMBIENT
-baseAmbientColor=texture2D(ambientSampler,vAmbientUV+uvOffset).rgb*vAmbientInfos.y;
-#endif
-#define CUSTOM_FRAGMENT_BEFORE_LIGHTS
-
-#ifdef SPECULARTERM
-float glossiness=vSpecularColor.a;
-vec3 specularColor=vSpecularColor.rgb;
-#ifdef SPECULAR
-vec4 specularMapColor=texture2D(specularSampler,vSpecularUV+uvOffset);
-specularColor=specularMapColor.rgb;
-#ifdef GLOSSINESS
-glossiness=glossiness*specularMapColor.a;
-#endif
-#endif
-#else
-float glossiness=0.;
-#endif
-
-vec3 diffuseBase=vec3(0.,0.,0.);
-lightingInfo info;
-#ifdef SPECULARTERM
-vec3 specularBase=vec3(0.,0.,0.);
-#endif
-float shadow=1.;
-#ifdef LIGHTMAP
-vec4 lightmapColor=texture2D(lightmapSampler,vLightmapUV+uvOffset);
-#ifdef RGBDLIGHTMAP
-lightmapColor.rgb=fromRGBD(lightmapColor);
-#endif
-lightmapColor.rgb*=vLightmapInfos.y;
-#endif
-#include<lightFragment>[0..maxSimultaneousLights]
-
-vec4 refractionColor=vec4(0.,0.,0.,1.);
-#ifdef REFRACTION
-vec3 refractionVector=normalize(refract(-viewDirectionW,normalW,vRefractionInfos.y));
-#ifdef REFRACTIONMAP_3D
-refractionVector.y=refractionVector.y*vRefractionInfos.w;
-if (dot(refractionVector,viewDirectionW)<1.0) {
-refractionColor=textureCube(refractionCubeSampler,refractionVector);
-}
-#else
-vec3 vRefractionUVW=vec3(refractionMatrix*(view*vec4(vPositionW+refractionVector*vRefractionInfos.z,1.0)));
-vec2 refractionCoords=vRefractionUVW.xy/vRefractionUVW.z;
-refractionCoords.y=1.0-refractionCoords.y;
-refractionColor=texture2D(refraction2DSampler,refractionCoords);
-#endif
-#ifdef RGBDREFRACTION
-refractionColor.rgb=fromRGBD(refractionColor);
-#endif
-#ifdef IS_REFRACTION_LINEAR
-refractionColor.rgb=toGammaSpace(refractionColor.rgb);
-#endif
-refractionColor.rgb*=vRefractionInfos.x;
-#endif
-
-vec4 reflectionColor=vec4(0.,0.,0.,1.);
-#ifdef REFLECTION
-vec3 vReflectionUVW=computeReflectionCoords(vec4(vPositionW,1.0),normalW);
-#ifdef REFLECTIONMAP_3D
-#ifdef ROUGHNESS
-float bias=vReflectionInfos.y;
-#ifdef SPECULARTERM
-#ifdef SPECULAR
-#ifdef GLOSSINESS
-bias*=(1.0-specularMapColor.a);
-#endif
-#endif
-#endif
-reflectionColor=textureCube(reflectionCubeSampler,vReflectionUVW,bias);
-#else
-reflectionColor=textureCube(reflectionCubeSampler,vReflectionUVW);
-#endif
-#else
-vec2 coords=vReflectionUVW.xy;
-#ifdef REFLECTIONMAP_PROJECTION
-coords/=vReflectionUVW.z;
-#endif
-coords.y=1.0-coords.y;
-reflectionColor=texture2D(reflection2DSampler,coords);
-#endif
-#ifdef RGBDREFLECTION
-reflectionColor.rgb=fromRGBD(reflectionColor);
-#endif
-#ifdef IS_REFLECTION_LINEAR
-reflectionColor.rgb=toGammaSpace(reflectionColor.rgb);
-#endif
-reflectionColor.rgb*=vReflectionInfos.x;
-#ifdef REFLECTIONFRESNEL
-float reflectionFresnelTerm=computeFresnelTerm(viewDirectionW,normalW,reflectionRightColor.a,reflectionLeftColor.a);
-#ifdef REFLECTIONFRESNELFROMSPECULAR
-#ifdef SPECULARTERM
-reflectionColor.rgb*=specularColor.rgb*(1.0-reflectionFresnelTerm)+reflectionFresnelTerm*reflectionRightColor.rgb;
-#else
-reflectionColor.rgb*=reflectionLeftColor.rgb*(1.0-reflectionFresnelTerm)+reflectionFresnelTerm*reflectionRightColor.rgb;
-#endif
-#else
-reflectionColor.rgb*=reflectionLeftColor.rgb*(1.0-reflectionFresnelTerm)+reflectionFresnelTerm*reflectionRightColor.rgb;
-#endif
-#endif
-#endif
-#ifdef REFRACTIONFRESNEL
-float refractionFresnelTerm=computeFresnelTerm(viewDirectionW,normalW,refractionRightColor.a,refractionLeftColor.a);
-refractionColor.rgb*=refractionLeftColor.rgb*(1.0-refractionFresnelTerm)+refractionFresnelTerm*refractionRightColor.rgb;
-#endif
-#ifdef OPACITY
-vec4 opacityMap=texture2D(opacitySampler,vOpacityUV+uvOffset);
-#ifdef OPACITYRGB
-opacityMap.rgb=opacityMap.rgb*vec3(0.3,0.59,0.11);
-alpha*=(opacityMap.x+opacityMap.y+opacityMap.z)* vOpacityInfos.y;
-#else
-alpha*=opacityMap.a*vOpacityInfos.y;
-#endif
-#endif
-#ifdef VERTEXALPHA
-alpha*=vColor.a;
-#endif
-#ifdef OPACITYFRESNEL
-float opacityFresnelTerm=computeFresnelTerm(viewDirectionW,normalW,opacityParts.z,opacityParts.w);
-alpha+=opacityParts.x*(1.0-opacityFresnelTerm)+opacityFresnelTerm*opacityParts.y;
-#endif
-#ifdef ALPHATEST
-#ifdef ALPHATEST_AFTERALLALPHACOMPUTATIONS
-if (alpha<alphaCutOff)
-discard;
-#endif
-#ifndef ALPHABLEND
-
-alpha=1.0;
-#endif
-#endif
-
-vec3 emissiveColor=vEmissiveColor;
-#ifdef EMISSIVE
-emissiveColor+=texture2D(emissiveSampler,vEmissiveUV+uvOffset).rgb*vEmissiveInfos.y;
-#endif
-#ifdef EMISSIVEFRESNEL
-float emissiveFresnelTerm=computeFresnelTerm(viewDirectionW,normalW,emissiveRightColor.a,emissiveLeftColor.a);
-emissiveColor*=emissiveLeftColor.rgb*(1.0-emissiveFresnelTerm)+emissiveFresnelTerm*emissiveRightColor.rgb;
-#endif
-
-#ifdef DIFFUSEFRESNEL
-float diffuseFresnelTerm=computeFresnelTerm(viewDirectionW,normalW,diffuseRightColor.a,diffuseLeftColor.a);
-diffuseBase*=diffuseLeftColor.rgb*(1.0-diffuseFresnelTerm)+diffuseFresnelTerm*diffuseRightColor.rgb;
-#endif
-
-#ifdef EMISSIVEASILLUMINATION
-vec3 finalDiffuse=clamp(diffuseBase*diffuseColor+vAmbientColor,0.0,1.0)*baseColor.rgb;
-#else
-#ifdef LINKEMISSIVEWITHDIFFUSE
-vec3 finalDiffuse=clamp((diffuseBase+emissiveColor)*diffuseColor+vAmbientColor,0.0,1.0)*baseColor.rgb;
-#else
-vec3 finalDiffuse=clamp(diffuseBase*diffuseColor+emissiveColor+vAmbientColor,0.0,1.0)*baseColor.rgb;
-#endif
-#endif
-#ifdef SPECULARTERM
-vec3 finalSpecular=specularBase*specularColor;
-#ifdef SPECULAROVERALPHA
-alpha=clamp(alpha+dot(finalSpecular,vec3(0.3,0.59,0.11)),0.,1.);
-#endif
-#else
-vec3 finalSpecular=vec3(0.0);
-#endif
-#ifdef REFLECTIONOVERALPHA
-alpha=clamp(alpha+dot(reflectionColor.rgb,vec3(0.3,0.59,0.11)),0.,1.);
-#endif
-
-#ifdef EMISSIVEASILLUMINATION
-vec4 color=vec4(clamp(finalDiffuse*baseAmbientColor+finalSpecular+reflectionColor.rgb+emissiveColor+refractionColor.rgb,0.0,1.0),alpha);
-#else
-vec4 color=vec4(finalDiffuse*baseAmbientColor+finalSpecular+reflectionColor.rgb+refractionColor.rgb,alpha);
-#endif
-
-#ifdef LIGHTMAP
-#ifndef LIGHTMAPEXCLUDED
-#ifdef USELIGHTMAPASSHADOWMAP
-color.rgb*=lightmapColor.rgb;
-#else
-color.rgb+=lightmapColor.rgb;
-#endif
-#endif
-#endif
-#define CUSTOM_FRAGMENT_BEFORE_FOG
-color.rgb=max(color.rgb,0.);
-#include<logDepthFragment>
-#include<fogFragment>
-
-
-#ifdef IMAGEPROCESSINGPOSTPROCESS
-color.rgb=toLinearSpace(color.rgb);
-#else
-#ifdef IMAGEPROCESSING
-color.rgb=toLinearSpace(color.rgb);
-color=applyImageProcessing(color);
-#endif
-#endif
-color.a*=visibility;
-#ifdef PREMULTIPLYALPHA
-
-color.rgb*=color.a;
-#endif
-#define CUSTOM_FRAGMENT_BEFORE_FRAGCOLOR
-#ifdef PREPASS
-gl_FragData[0]=color;
-#ifdef PREPASS_POSITION
-gl_FragData[PREPASS_POSITION_INDEX]=vec4(vPositionW,1.0);
-#endif
-#ifdef PREPASS_VELOCITY
-vec2 a=(vCurrentPosition.xy/vCurrentPosition.w)*0.5+0.5;
-vec2 b=(vPreviousPosition.xy/vPreviousPosition.w)*0.5+0.5;
-vec2 velocity=abs(a-b);
-velocity=vec2(pow(velocity.x,1.0/3.0),pow(velocity.y,1.0/3.0))*sign(a-b)*0.5+0.5;
-gl_FragData[PREPASS_VELOCITY_INDEX]=vec4(velocity,0.0,1.0);
-#endif
-#ifdef PREPASS_IRRADIANCE
-gl_FragData[PREPASS_IRRADIANCE_INDEX]=vec4(0.0,0.0,0.0,1.0);
-#endif
-#ifdef PREPASS_DEPTHNORMAL
-gl_FragData[PREPASS_DEPTHNORMAL_INDEX]=vec4(vViewPos.z,(view*vec4(normalW,0.0)).rgb);
-#endif
-#ifdef PREPASS_ALBEDO
-gl_FragData[PREPASS_ALBEDO_INDEX]=vec4(0.0,0.0,0.0,1.0);
-#endif
-#ifdef PREPASS_REFLECTIVITY
-#if defined(SPECULAR)
-gl_FragData[PREPASS_REFLECTIVITY_INDEX]=specularMapColor;
-#else
-gl_FragData[PREPASS_REFLECTIVITY_INDEX]=vec4(0.0,0.0,0.0,1.0);
-#endif
-#endif
-#endif
-#if !defined(PREPASS) || defined(WEBGL2)
-gl_FragColor=color;
-#endif
-}
-`;E.a.ShadersStore.defaultPixelShader=N;var I=`
-uniform mat4 viewProjection;
-uniform mat4 view;
-#ifdef DIFFUSE
-uniform mat4 diffuseMatrix;
-uniform vec2 vDiffuseInfos;
-#endif
-#ifdef AMBIENT
-uniform mat4 ambientMatrix;
-uniform vec2 vAmbientInfos;
-#endif
-#ifdef OPACITY
-uniform mat4 opacityMatrix;
-uniform vec2 vOpacityInfos;
-#endif
-#ifdef EMISSIVE
-uniform vec2 vEmissiveInfos;
-uniform mat4 emissiveMatrix;
-#endif
-#ifdef LIGHTMAP
-uniform vec2 vLightmapInfos;
-uniform mat4 lightmapMatrix;
-#endif
-#if defined(SPECULAR) && defined(SPECULARTERM)
-uniform vec2 vSpecularInfos;
-uniform mat4 specularMatrix;
-#endif
-#ifdef BUMP
-uniform vec3 vBumpInfos;
-uniform mat4 bumpMatrix;
-#endif
-#ifdef REFLECTION
-uniform mat4 reflectionMatrix;
-#endif
-#ifdef POINTSIZE
-uniform float pointSize;
-#endif
-`;E.a.IncludesShadersStore.defaultVertexDeclaration=I,f(78),f(79),f(163),f(164),f(117),f(137),f(93),f(94),f(100),f(80),f(81),f(165),f(156),f(111),f(157),f(138),E.a.IncludesShadersStore.pointCloudVertex=`#ifdef POINTSIZE
-gl_PointSize=pointSize;
-#endif`,f(158);var V=`#include<__decl__defaultVertex>
-
-#define CUSTOM_VERTEX_BEGIN
-attribute vec3 position;
-#ifdef NORMAL
-attribute vec3 normal;
-#endif
-#ifdef TANGENT
-attribute vec4 tangent;
-#endif
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#ifdef VERTEXCOLOR
-attribute vec4 color;
-#endif
-#include<helperFunctions>
-#include<bonesDeclaration>
-
-#include<instancesDeclaration>
-#include<prePassVertexDeclaration>
-#ifdef MAINUV1
-varying vec2 vMainUV1;
-#endif
-#ifdef MAINUV2
-varying vec2 vMainUV2;
-#endif
-#if defined(DIFFUSE) && DIFFUSEDIRECTUV == 0
-varying vec2 vDiffuseUV;
-#endif
-#if defined(DETAIL) && DETAILDIRECTUV == 0
-varying vec2 vDetailUV;
-#endif
-#if defined(AMBIENT) && AMBIENTDIRECTUV == 0
-varying vec2 vAmbientUV;
-#endif
-#if defined(OPACITY) && OPACITYDIRECTUV == 0
-varying vec2 vOpacityUV;
-#endif
-#if defined(EMISSIVE) && EMISSIVEDIRECTUV == 0
-varying vec2 vEmissiveUV;
-#endif
-#if defined(LIGHTMAP) && LIGHTMAPDIRECTUV == 0
-varying vec2 vLightmapUV;
-#endif
-#if defined(SPECULAR) && defined(SPECULARTERM) && SPECULARDIRECTUV == 0
-varying vec2 vSpecularUV;
-#endif
-#if defined(BUMP) && BUMPDIRECTUV == 0
-varying vec2 vBumpUV;
-#endif
-
-varying vec3 vPositionW;
-#ifdef NORMAL
-varying vec3 vNormalW;
-#endif
-#ifdef VERTEXCOLOR
-varying vec4 vColor;
-#endif
-#include<bumpVertexDeclaration>
-#include<clipPlaneVertexDeclaration>
-#include<fogVertexDeclaration>
-#include<__decl__lightFragment>[0..maxSimultaneousLights]
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-#ifdef REFLECTIONMAP_SKYBOX
-varying vec3 vPositionUVW;
-#endif
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-varying vec3 vDirectionW;
-#endif
-#include<logDepthDeclaration>
-#define CUSTOM_VERTEX_DEFINITIONS
-void main(void) {
-#define CUSTOM_VERTEX_MAIN_BEGIN
-vec3 positionUpdated=position;
-#ifdef NORMAL
-vec3 normalUpdated=normal;
-#endif
-#ifdef TANGENT
-vec4 tangentUpdated=tangent;
-#endif
-#ifdef UV1
-vec2 uvUpdated=uv;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-#ifdef REFLECTIONMAP_SKYBOX
-vPositionUVW=positionUpdated;
-#endif
-#define CUSTOM_VERTEX_UPDATE_POSITION
-#define CUSTOM_VERTEX_UPDATE_NORMAL
-#include<instancesVertex>
-#if defined(PREPASS) && defined(PREPASS_VELOCITY) && !defined(BONES_VELOCITY_ENABLED)
-
-vCurrentPosition=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-vPreviousPosition=previousViewProjection*previousWorld*vec4(positionUpdated,1.0);
-#endif
-#include<bonesVertex>
-vec4 worldPos=finalWorld*vec4(positionUpdated,1.0);
-#ifdef NORMAL
-mat3 normalWorld=mat3(finalWorld);
-#if defined(INSTANCES) && defined(THIN_INSTANCES)
-vNormalW=normalUpdated/vec3(dot(normalWorld[0],normalWorld[0]),dot(normalWorld[1],normalWorld[1]),dot(normalWorld[2],normalWorld[2]));
-vNormalW=normalize(normalWorld*vNormalW);
-#else
-#ifdef NONUNIFORMSCALING
-normalWorld=transposeMat3(inverseMat3(normalWorld));
-#endif
-vNormalW=normalize(normalWorld*normalUpdated);
-#endif
-#endif
-#define CUSTOM_VERTEX_UPDATE_WORLDPOS
-#ifdef MULTIVIEW
-if (gl_ViewID_OVR == 0u) {
-gl_Position=viewProjection*worldPos;
-} else {
-gl_Position=viewProjectionR*worldPos;
-}
-#else
-gl_Position=viewProjection*worldPos;
-#endif
-vPositionW=vec3(worldPos);
-#include<prePassVertex>
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-vDirectionW=normalize(vec3(finalWorld*vec4(positionUpdated,0.0)));
-#endif
-
-#ifndef UV1
-vec2 uvUpdated=vec2(0.,0.);
-#endif
-#ifndef UV2
-vec2 uv2=vec2(0.,0.);
-#endif
-#ifdef MAINUV1
-vMainUV1=uvUpdated;
-#endif
-#ifdef MAINUV2
-vMainUV2=uv2;
-#endif
-#if defined(DIFFUSE) && DIFFUSEDIRECTUV == 0
-if (vDiffuseInfos.x == 0.)
-{
-vDiffuseUV=vec2(diffuseMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vDiffuseUV=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(DETAIL) && DETAILDIRECTUV == 0
-if (vDetailInfos.x == 0.)
-{
-vDetailUV=vec2(detailMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vDetailUV=vec2(detailMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(AMBIENT) && AMBIENTDIRECTUV == 0
-if (vAmbientInfos.x == 0.)
-{
-vAmbientUV=vec2(ambientMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vAmbientUV=vec2(ambientMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(OPACITY) && OPACITYDIRECTUV == 0
-if (vOpacityInfos.x == 0.)
-{
-vOpacityUV=vec2(opacityMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vOpacityUV=vec2(opacityMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(EMISSIVE) && EMISSIVEDIRECTUV == 0
-if (vEmissiveInfos.x == 0.)
-{
-vEmissiveUV=vec2(emissiveMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vEmissiveUV=vec2(emissiveMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(LIGHTMAP) && LIGHTMAPDIRECTUV == 0
-if (vLightmapInfos.x == 0.)
-{
-vLightmapUV=vec2(lightmapMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vLightmapUV=vec2(lightmapMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(SPECULAR) && defined(SPECULARTERM) && SPECULARDIRECTUV == 0
-if (vSpecularInfos.x == 0.)
-{
-vSpecularUV=vec2(specularMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vSpecularUV=vec2(specularMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(BUMP) && BUMPDIRECTUV == 0
-if (vBumpInfos.x == 0.)
-{
-vBumpUV=vec2(bumpMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vBumpUV=vec2(bumpMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#include<bumpVertex>
-#include<clipPlaneVertex>
-#include<fogVertex>
-#include<shadowsVertex>[0..maxSimultaneousLights]
-#ifdef VERTEXCOLOR
-
-vColor=color;
-#endif
-#include<pointCloudVertex>
-#include<logDepthVertex>
-#define CUSTOM_VERTEX_MAIN_END
-}
-`;E.a.ShadersStore.defaultVertexShader=V;var X=f(2),j=f(67),ne=f(92),te={effect:null,subMesh:null},de=function(ae){function ee(){var K=ae.call(this)||this;return K.MAINUV1=!1,K.MAINUV2=!1,K.DIFFUSE=!1,K.DIFFUSEDIRECTUV=0,K.DETAIL=!1,K.DETAILDIRECTUV=0,K.DETAIL_NORMALBLENDMETHOD=0,K.AMBIENT=!1,K.AMBIENTDIRECTUV=0,K.OPACITY=!1,K.OPACITYDIRECTUV=0,K.OPACITYRGB=!1,K.REFLECTION=!1,K.EMISSIVE=!1,K.EMISSIVEDIRECTUV=0,K.SPECULAR=!1,K.SPECULARDIRECTUV=0,K.BUMP=!1,K.BUMPDIRECTUV=0,K.PARALLAX=!1,K.PARALLAXOCCLUSION=!1,K.SPECULAROVERALPHA=!1,K.CLIPPLANE=!1,K.CLIPPLANE2=!1,K.CLIPPLANE3=!1,K.CLIPPLANE4=!1,K.CLIPPLANE5=!1,K.CLIPPLANE6=!1,K.ALPHATEST=!1,K.DEPTHPREPASS=!1,K.ALPHAFROMDIFFUSE=!1,K.POINTSIZE=!1,K.FOG=!1,K.SPECULARTERM=!1,K.DIFFUSEFRESNEL=!1,K.OPACITYFRESNEL=!1,K.REFLECTIONFRESNEL=!1,K.REFRACTIONFRESNEL=!1,K.EMISSIVEFRESNEL=!1,K.FRESNEL=!1,K.NORMAL=!1,K.UV1=!1,K.UV2=!1,K.VERTEXCOLOR=!1,K.VERTEXALPHA=!1,K.NUM_BONE_INFLUENCERS=0,K.BonesPerMesh=0,K.BONETEXTURE=!1,K.BONES_VELOCITY_ENABLED=!1,K.INSTANCES=!1,K.THIN_INSTANCES=!1,K.GLOSSINESS=!1,K.ROUGHNESS=!1,K.EMISSIVEASILLUMINATION=!1,K.LINKEMISSIVEWITHDIFFUSE=!1,K.REFLECTIONFRESNELFROMSPECULAR=!1,K.LIGHTMAP=!1,K.LIGHTMAPDIRECTUV=0,K.OBJECTSPACE_NORMALMAP=!1,K.USELIGHTMAPASSHADOWMAP=!1,K.REFLECTIONMAP_3D=!1,K.REFLECTIONMAP_SPHERICAL=!1,K.REFLECTIONMAP_PLANAR=!1,K.REFLECTIONMAP_CUBIC=!1,K.USE_LOCAL_REFLECTIONMAP_CUBIC=!1,K.REFLECTIONMAP_PROJECTION=!1,K.REFLECTIONMAP_SKYBOX=!1,K.REFLECTIONMAP_EXPLICIT=!1,K.REFLECTIONMAP_EQUIRECTANGULAR=!1,K.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!1,K.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!1,K.INVERTCUBICMAP=!1,K.LOGARITHMICDEPTH=!1,K.REFRACTION=!1,K.REFRACTIONMAP_3D=!1,K.REFLECTIONOVERALPHA=!1,K.TWOSIDEDLIGHTING=!1,K.SHADOWFLOAT=!1,K.MORPHTARGETS=!1,K.MORPHTARGETS_NORMAL=!1,K.MORPHTARGETS_TANGENT=!1,K.MORPHTARGETS_UV=!1,K.NUM_MORPH_INFLUENCERS=0,K.NONUNIFORMSCALING=!1,K.PREMULTIPLYALPHA=!1,K.ALPHATEST_AFTERALLALPHACOMPUTATIONS=!1,K.ALPHABLEND=!0,K.PREPASS=!1,K.PREPASS_IRRADIANCE=!1,K.PREPASS_IRRADIANCE_INDEX=-1,K.PREPASS_ALBEDO=!1,K.PREPASS_ALBEDO_INDEX=-1,K.PREPASS_DEPTHNORMAL=!1,K.PREPASS_DEPTHNORMAL_INDEX=-1,K.PREPASS_POSITION=!1,K.PREPASS_POSITION_INDEX=-1,K.PREPASS_VELOCITY=!1,K.PREPASS_VELOCITY_INDEX=-1,K.PREPASS_REFLECTIVITY=!1,K.PREPASS_REFLECTIVITY_INDEX=-1,K.SCENE_MRT_COUNT=0,K.RGBDLIGHTMAP=!1,K.RGBDREFLECTION=!1,K.RGBDREFRACTION=!1,K.IMAGEPROCESSING=!1,K.VIGNETTE=!1,K.VIGNETTEBLENDMODEMULTIPLY=!1,K.VIGNETTEBLENDMODEOPAQUE=!1,K.TONEMAPPING=!1,K.TONEMAPPING_ACES=!1,K.CONTRAST=!1,K.COLORCURVES=!1,K.COLORGRADING=!1,K.COLORGRADING3D=!1,K.SAMPLER3DGREENDEPTH=!1,K.SAMPLER3DBGRMAP=!1,K.IMAGEPROCESSINGPOSTPROCESS=!1,K.MULTIVIEW=!1,K.IS_REFLECTION_LINEAR=!1,K.IS_REFRACTION_LINEAR=!1,K.EXPOSURE=!1,K.rebuild(),K}return Object(U.d)(ee,ae),ee.prototype.setReflectionMode=function(K){for(var $=0,L=["REFLECTIONMAP_CUBIC","REFLECTIONMAP_EXPLICIT","REFLECTIONMAP_PLANAR","REFLECTIONMAP_PROJECTION","REFLECTIONMAP_PROJECTION","REFLECTIONMAP_SKYBOX","REFLECTIONMAP_SPHERICAL","REFLECTIONMAP_EQUIRECTANGULAR","REFLECTIONMAP_EQUIRECTANGULAR_FIXED","REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED"];$<L.length;$++){var G=L[$];this[G]=G===K}},ee}(A.a),pe=function(ae){function ee(K,$){var L=ae.call(this,K,$)||this;return L._diffuseTexture=null,L._ambientTexture=null,L._opacityTexture=null,L._reflectionTexture=null,L._emissiveTexture=null,L._specularTexture=null,L._bumpTexture=null,L._lightmapTexture=null,L._refractionTexture=null,L.ambientColor=new R.a(0,0,0),L.diffuseColor=new R.a(1,1,1),L.specularColor=new R.a(1,1,1),L.emissiveColor=new R.a(0,0,0),L.specularPower=64,L._useAlphaFromDiffuseTexture=!1,L._useEmissiveAsIllumination=!1,L._linkEmissiveWithDiffuse=!1,L._useSpecularOverAlpha=!1,L._useReflectionOverAlpha=!1,L._disableLighting=!1,L._useObjectSpaceNormalMap=!1,L._useParallax=!1,L._useParallaxOcclusion=!1,L.parallaxScaleBias=.05,L._roughness=0,L.indexOfRefraction=.98,L.invertRefractionY=!0,L.alphaCutOff=.4,L._useLightmapAsShadowmap=!1,L._useReflectionFresnelFromSpecular=!1,L._useGlossinessFromSpecularMapAlpha=!1,L._maxSimultaneousLights=4,L._invertNormalMapX=!1,L._invertNormalMapY=!1,L._twoSidedLighting=!1,L.detailMap=new ne.a(L._markAllSubMeshesAsTexturesDirty.bind(L)),L._renderTargets=new C.a(16),L._worldViewProjectionMatrix=M.a.Zero(),L._globalAmbientColor=new R.a(0,0,0),L._rebuildInParallel=!1,L._attachImageProcessingConfiguration(null),L.prePassConfiguration=new m.a,L.getRenderTargetTextures=function(){return L._renderTargets.reset(),ee.ReflectionTextureEnabled&&L._reflectionTexture&&L._reflectionTexture.isRenderTarget&&L._renderTargets.push(L._reflectionTexture),ee.RefractionTextureEnabled&&L._refractionTexture&&L._refractionTexture.isRenderTarget&&L._renderTargets.push(L._refractionTexture),L._renderTargets},L}return Object(U.d)(ee,ae),Object.defineProperty(ee.prototype,"imageProcessingConfiguration",{get:function(){return this._imageProcessingConfiguration},set:function(K){this._attachImageProcessingConfiguration(K),this._markAllSubMeshesAsTexturesDirty()},enumerable:!1,configurable:!0}),ee.prototype._attachImageProcessingConfiguration=function(K){var $=this;K!==this._imageProcessingConfiguration&&(this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),this._imageProcessingConfiguration=K||this.getScene().imageProcessingConfiguration,this._imageProcessingConfiguration&&(this._imageProcessingObserver=this._imageProcessingConfiguration.onUpdateParameters.add(function(){$._markAllSubMeshesAsImageProcessingDirty()})))},Object.defineProperty(ee.prototype,"cameraColorCurvesEnabled",{get:function(){return this.imageProcessingConfiguration.colorCurvesEnabled},set:function(K){this.imageProcessingConfiguration.colorCurvesEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"cameraColorGradingEnabled",{get:function(){return this.imageProcessingConfiguration.colorGradingEnabled},set:function(K){this.imageProcessingConfiguration.colorGradingEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"cameraToneMappingEnabled",{get:function(){return this._imageProcessingConfiguration.toneMappingEnabled},set:function(K){this._imageProcessingConfiguration.toneMappingEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"cameraExposure",{get:function(){return this._imageProcessingConfiguration.exposure},set:function(K){this._imageProcessingConfiguration.exposure=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"cameraContrast",{get:function(){return this._imageProcessingConfiguration.contrast},set:function(K){this._imageProcessingConfiguration.contrast=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"cameraColorGradingTexture",{get:function(){return this._imageProcessingConfiguration.colorGradingTexture},set:function(K){this._imageProcessingConfiguration.colorGradingTexture=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"cameraColorCurves",{get:function(){return this._imageProcessingConfiguration.colorCurves},set:function(K){this._imageProcessingConfiguration.colorCurves=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"canRenderToMRT",{get:function(){return!0},enumerable:!1,configurable:!0}),Object.defineProperty(ee.prototype,"hasRenderTargetTextures",{get:function(){return!!(ee.ReflectionTextureEnabled&&this._reflectionTexture&&this._reflectionTexture.isRenderTarget)||!!(ee.RefractionTextureEnabled&&this._refractionTexture&&this._refractionTexture.isRenderTarget)},enumerable:!1,configurable:!0}),ee.prototype.getClassName=function(){return"StandardMaterial"},Object.defineProperty(ee.prototype,"useLogarithmicDepth",{get:function(){return this._useLogarithmicDepth},set:function(K){this._useLogarithmicDepth=K&&this.getScene().getEngine().getCaps().fragmentDepthSupported,this._markAllSubMeshesAsMiscDirty()},enumerable:!1,configurable:!0}),ee.prototype.needAlphaBlending=function(){return!this._disableAlphaBlending&&(this.alpha<1||this._opacityTexture!=null||this._shouldUseAlphaFromDiffuseTexture()||this._opacityFresnelParameters&&this._opacityFresnelParameters.isEnabled)},ee.prototype.needAlphaTesting=function(){return!!this._forceAlphaTest||this._hasAlphaChannel()&&(this._transparencyMode==null||this._transparencyMode===T.a.MATERIAL_ALPHATEST)},ee.prototype._shouldUseAlphaFromDiffuseTexture=function(){return this._diffuseTexture!=null&&this._diffuseTexture.hasAlpha&&this._useAlphaFromDiffuseTexture&&this._transparencyMode!==T.a.MATERIAL_OPAQUE},ee.prototype._hasAlphaChannel=function(){return this._diffuseTexture!=null&&this._diffuseTexture.hasAlpha||this._opacityTexture!=null},ee.prototype.getAlphaTestTexture=function(){return this._diffuseTexture},ee.prototype.isReadyForSubMesh=function(K,$,L){if(L===void 0&&(L=!1),$.effect&&this.isFrozen&&$.effect._wasPreviouslyReady)return!0;$._materialDefines||($._materialDefines=new de);var G=this.getScene(),Q=$._materialDefines;if(this._isReadyForSubMesh($))return!0;var oe=G.getEngine();if(Q._needNormals=g.a.PrepareDefinesForLights(G,K,Q,!0,this._maxSimultaneousLights,this._disableLighting),g.a.PrepareDefinesForMultiview(G,Q),g.a.PrepareDefinesForPrePass(G,Q,this.canRenderToMRT),Q._areTexturesDirty){if(Q._needUVs=!1,Q.MAINUV1=!1,Q.MAINUV2=!1,G.texturesEnabled){if(this._diffuseTexture&&ee.DiffuseTextureEnabled){if(!this._diffuseTexture.isReadyOrNotBlocking())return!1;g.a.PrepareDefinesForMergedUV(this._diffuseTexture,Q,"DIFFUSE")}else Q.DIFFUSE=!1;if(this._ambientTexture&&ee.AmbientTextureEnabled){if(!this._ambientTexture.isReadyOrNotBlocking())return!1;g.a.PrepareDefinesForMergedUV(this._ambientTexture,Q,"AMBIENT")}else Q.AMBIENT=!1;if(this._opacityTexture&&ee.OpacityTextureEnabled){if(!this._opacityTexture.isReadyOrNotBlocking())return!1;g.a.PrepareDefinesForMergedUV(this._opacityTexture,Q,"OPACITY"),Q.OPACITYRGB=this._opacityTexture.getAlphaFromRGB}else Q.OPACITY=!1;if(this._reflectionTexture&&ee.ReflectionTextureEnabled){if(!this._reflectionTexture.isReadyOrNotBlocking())return!1;switch(Q._needNormals=!0,Q.REFLECTION=!0,Q.ROUGHNESS=this._roughness>0,Q.REFLECTIONOVERALPHA=this._useReflectionOverAlpha,Q.INVERTCUBICMAP=this._reflectionTexture.coordinatesMode===l.a.INVCUBIC_MODE,Q.REFLECTIONMAP_3D=this._reflectionTexture.isCube,Q.RGBDREFLECTION=this._reflectionTexture.isRGBD,this._reflectionTexture.coordinatesMode){case l.a.EXPLICIT_MODE:Q.setReflectionMode("REFLECTIONMAP_EXPLICIT");break;case l.a.PLANAR_MODE:Q.setReflectionMode("REFLECTIONMAP_PLANAR");break;case l.a.PROJECTION_MODE:Q.setReflectionMode("REFLECTIONMAP_PROJECTION");break;case l.a.SKYBOX_MODE:Q.setReflectionMode("REFLECTIONMAP_SKYBOX");break;case l.a.SPHERICAL_MODE:Q.setReflectionMode("REFLECTIONMAP_SPHERICAL");break;case l.a.EQUIRECTANGULAR_MODE:Q.setReflectionMode("REFLECTIONMAP_EQUIRECTANGULAR");break;case l.a.FIXED_EQUIRECTANGULAR_MODE:Q.setReflectionMode("REFLECTIONMAP_EQUIRECTANGULAR_FIXED");break;case l.a.FIXED_EQUIRECTANGULAR_MIRRORED_MODE:Q.setReflectionMode("REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED");break;case l.a.CUBIC_MODE:case l.a.INVCUBIC_MODE:default:Q.setReflectionMode("REFLECTIONMAP_CUBIC")}Q.USE_LOCAL_REFLECTIONMAP_CUBIC=!!this._reflectionTexture.boundingBoxSize}else Q.REFLECTION=!1;if(this._emissiveTexture&&ee.EmissiveTextureEnabled){if(!this._emissiveTexture.isReadyOrNotBlocking())return!1;g.a.PrepareDefinesForMergedUV(this._emissiveTexture,Q,"EMISSIVE")}else Q.EMISSIVE=!1;if(this._lightmapTexture&&ee.LightmapTextureEnabled){if(!this._lightmapTexture.isReadyOrNotBlocking())return!1;g.a.PrepareDefinesForMergedUV(this._lightmapTexture,Q,"LIGHTMAP"),Q.USELIGHTMAPASSHADOWMAP=this._useLightmapAsShadowmap,Q.RGBDLIGHTMAP=this._lightmapTexture.isRGBD}else Q.LIGHTMAP=!1;if(this._specularTexture&&ee.SpecularTextureEnabled){if(!this._specularTexture.isReadyOrNotBlocking())return!1;g.a.PrepareDefinesForMergedUV(this._specularTexture,Q,"SPECULAR"),Q.GLOSSINESS=this._useGlossinessFromSpecularMapAlpha}else Q.SPECULAR=!1;if(G.getEngine().getCaps().standardDerivatives&&this._bumpTexture&&ee.BumpTextureEnabled){if(!this._bumpTexture.isReady())return!1;g.a.PrepareDefinesForMergedUV(this._bumpTexture,Q,"BUMP"),Q.PARALLAX=this._useParallax,Q.PARALLAXOCCLUSION=this._useParallaxOcclusion,Q.OBJECTSPACE_NORMALMAP=this._useObjectSpaceNormalMap}else Q.BUMP=!1;if(this._refractionTexture&&ee.RefractionTextureEnabled){if(!this._refractionTexture.isReadyOrNotBlocking())return!1;Q._needUVs=!0,Q.REFRACTION=!0,Q.REFRACTIONMAP_3D=this._refractionTexture.isCube,Q.RGBDREFRACTION=this._refractionTexture.isRGBD}else Q.REFRACTION=!1;Q.TWOSIDEDLIGHTING=!this._backFaceCulling&&this._twoSidedLighting}else Q.DIFFUSE=!1,Q.AMBIENT=!1,Q.OPACITY=!1,Q.REFLECTION=!1,Q.EMISSIVE=!1,Q.LIGHTMAP=!1,Q.BUMP=!1,Q.REFRACTION=!1;Q.ALPHAFROMDIFFUSE=this._shouldUseAlphaFromDiffuseTexture(),Q.EMISSIVEASILLUMINATION=this._useEmissiveAsIllumination,Q.LINKEMISSIVEWITHDIFFUSE=this._linkEmissiveWithDiffuse,Q.SPECULAROVERALPHA=this._useSpecularOverAlpha,Q.PREMULTIPLYALPHA=this.alphaMode===X.a.ALPHA_PREMULTIPLIED||this.alphaMode===X.a.ALPHA_PREMULTIPLIED_PORTERDUFF,Q.ALPHATEST_AFTERALLALPHACOMPUTATIONS=this.transparencyMode!==null,Q.ALPHABLEND=this.transparencyMode===null||this.needAlphaBlendingForMesh(K)}if(!this.detailMap.isReadyForSubMesh(Q,G))return!1;if(Q._areImageProcessingDirty&&this._imageProcessingConfiguration){if(!this._imageProcessingConfiguration.isReady())return!1;this._imageProcessingConfiguration.prepareDefines(Q),Q.IS_REFLECTION_LINEAR=this.reflectionTexture!=null&&!this.reflectionTexture.gammaSpace,Q.IS_REFRACTION_LINEAR=this.refractionTexture!=null&&!this.refractionTexture.gammaSpace}if(Q._areFresnelDirty&&(ee.FresnelEnabled?(this._diffuseFresnelParameters||this._opacityFresnelParameters||this._emissiveFresnelParameters||this._refractionFresnelParameters||this._reflectionFresnelParameters)&&(Q.DIFFUSEFRESNEL=this._diffuseFresnelParameters&&this._diffuseFresnelParameters.isEnabled,Q.OPACITYFRESNEL=this._opacityFresnelParameters&&this._opacityFresnelParameters.isEnabled,Q.REFLECTIONFRESNEL=this._reflectionFresnelParameters&&this._reflectionFresnelParameters.isEnabled,Q.REFLECTIONFRESNELFROMSPECULAR=this._useReflectionFresnelFromSpecular,Q.REFRACTIONFRESNEL=this._refractionFresnelParameters&&this._refractionFresnelParameters.isEnabled,Q.EMISSIVEFRESNEL=this._emissiveFresnelParameters&&this._emissiveFresnelParameters.isEnabled,Q._needNormals=!0,Q.FRESNEL=!0):Q.FRESNEL=!1),g.a.PrepareDefinesForMisc(K,G,this._useLogarithmicDepth,this.pointsCloud,this.fogEnabled,this._shouldTurnAlphaTestOn(K)||this._forceAlphaTest,Q),g.a.PrepareDefinesForAttributes(K,Q,!0,!0,!0),g.a.PrepareDefinesForFrameBoundValues(G,oe,Q,L,null,$.getRenderingMesh().hasThinInstances),this.detailMap.prepareDefines(Q,G),Q.isDirty){var re=Q._areLightsDisposed;Q.markAsProcessed();var Y=new j.a;Q.REFLECTION&&Y.addFallback(0,"REFLECTION"),Q.SPECULAR&&Y.addFallback(0,"SPECULAR"),Q.BUMP&&Y.addFallback(0,"BUMP"),Q.PARALLAX&&Y.addFallback(1,"PARALLAX"),Q.PARALLAXOCCLUSION&&Y.addFallback(0,"PARALLAXOCCLUSION"),Q.SPECULAROVERALPHA&&Y.addFallback(0,"SPECULAROVERALPHA"),Q.FOG&&Y.addFallback(1,"FOG"),Q.POINTSIZE&&Y.addFallback(0,"POINTSIZE"),Q.LOGARITHMICDEPTH&&Y.addFallback(0,"LOGARITHMICDEPTH"),g.a.HandleFallbacksForShadows(Q,Y,this._maxSimultaneousLights),Q.SPECULARTERM&&Y.addFallback(0,"SPECULARTERM"),Q.DIFFUSEFRESNEL&&Y.addFallback(1,"DIFFUSEFRESNEL"),Q.OPACITYFRESNEL&&Y.addFallback(2,"OPACITYFRESNEL"),Q.REFLECTIONFRESNEL&&Y.addFallback(3,"REFLECTIONFRESNEL"),Q.EMISSIVEFRESNEL&&Y.addFallback(4,"EMISSIVEFRESNEL"),Q.FRESNEL&&Y.addFallback(4,"FRESNEL"),Q.MULTIVIEW&&Y.addFallback(0,"MULTIVIEW");var k=[x.b.PositionKind];Q.NORMAL&&k.push(x.b.NormalKind),Q.UV1&&k.push(x.b.UVKind),Q.UV2&&k.push(x.b.UV2Kind),Q.VERTEXCOLOR&&k.push(x.b.ColorKind),g.a.PrepareAttributesForBones(k,K,Q,Y),g.a.PrepareAttributesForInstances(k,Q),g.a.PrepareAttributesForMorphTargets(k,K,Q);var H="default",Z=["world","view","viewProjection","vEyePosition","vLightsType","vAmbientColor","vDiffuseColor","vSpecularColor","vEmissiveColor","visibility","vFogInfos","vFogColor","pointSize","vDiffuseInfos","vAmbientInfos","vOpacityInfos","vReflectionInfos","vEmissiveInfos","vSpecularInfos","vBumpInfos","vLightmapInfos","vRefractionInfos","mBones","vClipPlane","vClipPlane2","vClipPlane3","vClipPlane4","vClipPlane5","vClipPlane6","diffuseMatrix","ambientMatrix","opacityMatrix","reflectionMatrix","emissiveMatrix","specularMatrix","bumpMatrix","normalMatrix","lightmapMatrix","refractionMatrix","diffuseLeftColor","diffuseRightColor","opacityParts","reflectionLeftColor","reflectionRightColor","emissiveLeftColor","emissiveRightColor","refractionLeftColor","refractionRightColor","vReflectionPosition","vReflectionSize","logarithmicDepthConstant","vTangentSpaceParams","alphaCutOff","boneTextureWidth"],W=["diffuseSampler","ambientSampler","opacitySampler","reflectionCubeSampler","reflection2DSampler","emissiveSampler","specularSampler","bumpSampler","lightmapSampler","refractionCubeSampler","refraction2DSampler","boneSampler"],q=["Material","Scene"];ne.a.AddUniforms(Z),ne.a.AddSamplers(W),m.a.AddUniforms(Z),m.a.AddSamplers(Z),c.a&&(c.a.PrepareUniforms(Z,Q),c.a.PrepareSamplers(W,Q)),g.a.PrepareUniformsAndSamplersList({uniformsNames:Z,uniformBuffersNames:q,samplers:W,defines:Q,maxSimultaneousLights:this._maxSimultaneousLights});var he={};this.customShaderNameResolve&&(H=this.customShaderNameResolve(H,Z,q,W,Q,k,he));var ge=Q.toString(),me=$.effect,_e=G.getEngine().createEffect(H,{attributes:k,uniformsNames:Z,uniformBuffersNames:q,samplers:W,defines:ge,fallbacks:Y,onCompiled:this.onCompiled,onError:this.onError,indexParameters:{maxSimultaneousLights:this._maxSimultaneousLights,maxSimultaneousMorphTargets:Q.NUM_MORPH_INFLUENCERS},processFinalCode:he.processFinalCode,multiTarget:Q.PREPASS},oe);if(_e)if(this._onEffectCreatedObservable&&(te.effect=_e,te.subMesh=$,this._onEffectCreatedObservable.notifyObservers(te)),this.allowShaderHotSwapping&&me&&!_e.isReady()){if(_e=me,this._rebuildInParallel=!0,Q.markAsUnprocessed(),re)return Q._areLightsDisposed=!0,!1}else this._rebuildInParallel=!1,G.resetCachedMaterial(),$.setEffect(_e,Q),this.buildUniformLayout()}return!(!$.effect||!$.effect.isReady())&&(Q._renderId=G.getRenderId(),$.effect._wasPreviouslyReady=!0,!0)},ee.prototype.buildUniformLayout=function(){var K=this._uniformBuffer;K.addUniform("diffuseLeftColor",4),K.addUniform("diffuseRightColor",4),K.addUniform("opacityParts",4),K.addUniform("reflectionLeftColor",4),K.addUniform("reflectionRightColor",4),K.addUniform("refractionLeftColor",4),K.addUniform("refractionRightColor",4),K.addUniform("emissiveLeftColor",4),K.addUniform("emissiveRightColor",4),K.addUniform("vDiffuseInfos",2),K.addUniform("vAmbientInfos",2),K.addUniform("vOpacityInfos",2),K.addUniform("vReflectionInfos",2),K.addUniform("vReflectionPosition",3),K.addUniform("vReflectionSize",3),K.addUniform("vEmissiveInfos",2),K.addUniform("vLightmapInfos",2),K.addUniform("vSpecularInfos",2),K.addUniform("vBumpInfos",3),K.addUniform("diffuseMatrix",16),K.addUniform("ambientMatrix",16),K.addUniform("opacityMatrix",16),K.addUniform("reflectionMatrix",16),K.addUniform("emissiveMatrix",16),K.addUniform("lightmapMatrix",16),K.addUniform("specularMatrix",16),K.addUniform("bumpMatrix",16),K.addUniform("vTangentSpaceParams",2),K.addUniform("pointSize",1),K.addUniform("refractionMatrix",16),K.addUniform("vRefractionInfos",4),K.addUniform("vSpecularColor",4),K.addUniform("vEmissiveColor",3),K.addUniform("visibility",1),K.addUniform("vDiffuseColor",4),ne.a.PrepareUniformBuffer(K),K.create()},ee.prototype.unbind=function(){if(this._activeEffect){var K=!1;this._reflectionTexture&&this._reflectionTexture.isRenderTarget&&(this._activeEffect.setTexture("reflection2DSampler",null),K=!0),this._refractionTexture&&this._refractionTexture.isRenderTarget&&(this._activeEffect.setTexture("refraction2DSampler",null),K=!0),K&&this._markAllSubMeshesAsTexturesDirty()}ae.prototype.unbind.call(this)},ee.prototype.bindForSubMesh=function(K,$,L){var G=this.getScene(),Q=L._materialDefines;if(Q){var oe=L.effect;if(oe){this._activeEffect=oe,Q.INSTANCES&&!Q.THIN_INSTANCES||this.bindOnlyWorldMatrix(K),this.prePassConfiguration.bindForSubMesh(this._activeEffect,G,$,K,this.isFrozen),Q.OBJECTSPACE_NORMALMAP&&(K.toNormalMatrix(this._normalMatrix),this.bindOnlyNormalMatrix(this._normalMatrix));var re=this._mustRebind(G,oe,$.visibility);g.a.BindBonesParameters($,oe);var Y=this._uniformBuffer;if(re){if(Y.bindToEffect(oe,"Material"),this.bindViewProjection(oe),!Y.useUbo||!this.isFrozen||!Y.isSync){if(ee.FresnelEnabled&&Q.FRESNEL&&(this.diffuseFresnelParameters&&this.diffuseFresnelParameters.isEnabled&&(Y.updateColor4("diffuseLeftColor",this.diffuseFresnelParameters.leftColor,this.diffuseFresnelParameters.power),Y.updateColor4("diffuseRightColor",this.diffuseFresnelParameters.rightColor,this.diffuseFresnelParameters.bias)),this.opacityFresnelParameters&&this.opacityFresnelParameters.isEnabled&&Y.updateColor4("opacityParts",new R.a(this.opacityFresnelParameters.leftColor.toLuminance(),this.opacityFresnelParameters.rightColor.toLuminance(),this.opacityFresnelParameters.bias),this.opacityFresnelParameters.power),this.reflectionFresnelParameters&&this.reflectionFresnelParameters.isEnabled&&(Y.updateColor4("reflectionLeftColor",this.reflectionFresnelParameters.leftColor,this.reflectionFresnelParameters.power),Y.updateColor4("reflectionRightColor",this.reflectionFresnelParameters.rightColor,this.reflectionFresnelParameters.bias)),this.refractionFresnelParameters&&this.refractionFresnelParameters.isEnabled&&(Y.updateColor4("refractionLeftColor",this.refractionFresnelParameters.leftColor,this.refractionFresnelParameters.power),Y.updateColor4("refractionRightColor",this.refractionFresnelParameters.rightColor,this.refractionFresnelParameters.bias)),this.emissiveFresnelParameters&&this.emissiveFresnelParameters.isEnabled&&(Y.updateColor4("emissiveLeftColor",this.emissiveFresnelParameters.leftColor,this.emissiveFresnelParameters.power),Y.updateColor4("emissiveRightColor",this.emissiveFresnelParameters.rightColor,this.emissiveFresnelParameters.bias))),G.texturesEnabled){if(this._diffuseTexture&&ee.DiffuseTextureEnabled&&(Y.updateFloat2("vDiffuseInfos",this._diffuseTexture.coordinatesIndex,this._diffuseTexture.level),g.a.BindTextureMatrix(this._diffuseTexture,Y,"diffuse")),this._ambientTexture&&ee.AmbientTextureEnabled&&(Y.updateFloat2("vAmbientInfos",this._ambientTexture.coordinatesIndex,this._ambientTexture.level),g.a.BindTextureMatrix(this._ambientTexture,Y,"ambient")),this._opacityTexture&&ee.OpacityTextureEnabled&&(Y.updateFloat2("vOpacityInfos",this._opacityTexture.coordinatesIndex,this._opacityTexture.level),g.a.BindTextureMatrix(this._opacityTexture,Y,"opacity")),this._hasAlphaChannel()&&oe.setFloat("alphaCutOff",this.alphaCutOff),this._reflectionTexture&&ee.ReflectionTextureEnabled&&(Y.updateFloat2("vReflectionInfos",this._reflectionTexture.level,this.roughness),Y.updateMatrix("reflectionMatrix",this._reflectionTexture.getReflectionTextureMatrix()),this._reflectionTexture.boundingBoxSize)){var k=this._reflectionTexture;Y.updateVector3("vReflectionPosition",k.boundingBoxPosition),Y.updateVector3("vReflectionSize",k.boundingBoxSize)}if(this._emissiveTexture&&ee.EmissiveTextureEnabled&&(Y.updateFloat2("vEmissiveInfos",this._emissiveTexture.coordinatesIndex,this._emissiveTexture.level),g.a.BindTextureMatrix(this._emissiveTexture,Y,"emissive")),this._lightmapTexture&&ee.LightmapTextureEnabled&&(Y.updateFloat2("vLightmapInfos",this._lightmapTexture.coordinatesIndex,this._lightmapTexture.level),g.a.BindTextureMatrix(this._lightmapTexture,Y,"lightmap")),this._specularTexture&&ee.SpecularTextureEnabled&&(Y.updateFloat2("vSpecularInfos",this._specularTexture.coordinatesIndex,this._specularTexture.level),g.a.BindTextureMatrix(this._specularTexture,Y,"specular")),this._bumpTexture&&G.getEngine().getCaps().standardDerivatives&&ee.BumpTextureEnabled&&(Y.updateFloat3("vBumpInfos",this._bumpTexture.coordinatesIndex,1/this._bumpTexture.level,this.parallaxScaleBias),g.a.BindTextureMatrix(this._bumpTexture,Y,"bump"),G._mirroredCameraPosition?Y.updateFloat2("vTangentSpaceParams",this._invertNormalMapX?1:-1,this._invertNormalMapY?1:-1):Y.updateFloat2("vTangentSpaceParams",this._invertNormalMapX?-1:1,this._invertNormalMapY?-1:1)),this._refractionTexture&&ee.RefractionTextureEnabled){var H=1;this._refractionTexture.isCube||(Y.updateMatrix("refractionMatrix",this._refractionTexture.getReflectionTextureMatrix()),this._refractionTexture.depth&&(H=this._refractionTexture.depth)),Y.updateFloat4("vRefractionInfos",this._refractionTexture.level,this.indexOfRefraction,H,this.invertRefractionY?-1:1)}}this.pointsCloud&&Y.updateFloat("pointSize",this.pointSize),Q.SPECULARTERM&&Y.updateColor4("vSpecularColor",this.specularColor,this.specularPower),Y.updateColor3("vEmissiveColor",ee.EmissiveTextureEnabled?this.emissiveColor:R.a.BlackReadOnly),Y.updateColor4("vDiffuseColor",this.diffuseColor,this.alpha)}Y.updateFloat("visibility",$.visibility),G.texturesEnabled&&(this._diffuseTexture&&ee.DiffuseTextureEnabled&&oe.setTexture("diffuseSampler",this._diffuseTexture),this._ambientTexture&&ee.AmbientTextureEnabled&&oe.setTexture("ambientSampler",this._ambientTexture),this._opacityTexture&&ee.OpacityTextureEnabled&&oe.setTexture("opacitySampler",this._opacityTexture),this._reflectionTexture&&ee.ReflectionTextureEnabled&&(this._reflectionTexture.isCube?oe.setTexture("reflectionCubeSampler",this._reflectionTexture):oe.setTexture("reflection2DSampler",this._reflectionTexture)),this._emissiveTexture&&ee.EmissiveTextureEnabled&&oe.setTexture("emissiveSampler",this._emissiveTexture),this._lightmapTexture&&ee.LightmapTextureEnabled&&oe.setTexture("lightmapSampler",this._lightmapTexture),this._specularTexture&&ee.SpecularTextureEnabled&&oe.setTexture("specularSampler",this._specularTexture),this._bumpTexture&&G.getEngine().getCaps().standardDerivatives&&ee.BumpTextureEnabled&&oe.setTexture("bumpSampler",this._bumpTexture),this._refractionTexture&&ee.RefractionTextureEnabled)&&(H=1,this._refractionTexture.isCube?oe.setTexture("refractionCubeSampler",this._refractionTexture):oe.setTexture("refraction2DSampler",this._refractionTexture)),this.detailMap.bindForSubMesh(Y,G,this.isFrozen),g.a.BindClipPlane(oe,G),G.ambientColor.multiplyToRef(this.ambientColor,this._globalAmbientColor),g.a.BindEyePosition(oe,G),oe.setColor3("vAmbientColor",this._globalAmbientColor)}!re&&this.isFrozen||(G.lightsEnabled&&!this._disableLighting&&g.a.BindLights(G,$,oe,Q,this._maxSimultaneousLights,this._rebuildInParallel),(G.fogEnabled&&$.applyFog&&G.fogMode!==u.a.FOGMODE_NONE||this._reflectionTexture||this._refractionTexture)&&this.bindView(oe),g.a.BindFogParameters(G,$,oe),Q.NUM_MORPH_INFLUENCERS&&g.a.BindMorphTargetParameters($,oe),this.useLogarithmicDepth&&g.a.BindLogDepth(Q,oe,G),this._imageProcessingConfiguration&&!this._imageProcessingConfiguration.applyByPostProcess&&this._imageProcessingConfiguration.bind(this._activeEffect)),Y.update(),this._afterBind($,this._activeEffect)}}},ee.prototype.getAnimatables=function(){var K=[];return this._diffuseTexture&&this._diffuseTexture.animations&&this._diffuseTexture.animations.length>0&&K.push(this._diffuseTexture),this._ambientTexture&&this._ambientTexture.animations&&this._ambientTexture.animations.length>0&&K.push(this._ambientTexture),this._opacityTexture&&this._opacityTexture.animations&&this._opacityTexture.animations.length>0&&K.push(this._opacityTexture),this._reflectionTexture&&this._reflectionTexture.animations&&this._reflectionTexture.animations.length>0&&K.push(this._reflectionTexture),this._emissiveTexture&&this._emissiveTexture.animations&&this._emissiveTexture.animations.length>0&&K.push(this._emissiveTexture),this._specularTexture&&this._specularTexture.animations&&this._specularTexture.animations.length>0&&K.push(this._specularTexture),this._bumpTexture&&this._bumpTexture.animations&&this._bumpTexture.animations.length>0&&K.push(this._bumpTexture),this._lightmapTexture&&this._lightmapTexture.animations&&this._lightmapTexture.animations.length>0&&K.push(this._lightmapTexture),this._refractionTexture&&this._refractionTexture.animations&&this._refractionTexture.animations.length>0&&K.push(this._refractionTexture),this.detailMap.getAnimatables(K),K},ee.prototype.getActiveTextures=function(){var K=ae.prototype.getActiveTextures.call(this);return this._diffuseTexture&&K.push(this._diffuseTexture),this._ambientTexture&&K.push(this._ambientTexture),this._opacityTexture&&K.push(this._opacityTexture),this._reflectionTexture&&K.push(this._reflectionTexture),this._emissiveTexture&&K.push(this._emissiveTexture),this._specularTexture&&K.push(this._specularTexture),this._bumpTexture&&K.push(this._bumpTexture),this._lightmapTexture&&K.push(this._lightmapTexture),this._refractionTexture&&K.push(this._refractionTexture),this.detailMap.getActiveTextures(K),K},ee.prototype.hasTexture=function(K){return!!ae.prototype.hasTexture.call(this,K)||this._diffuseTexture===K||this._ambientTexture===K||this._opacityTexture===K||this._reflectionTexture===K||this._emissiveTexture===K||this._specularTexture===K||this._bumpTexture===K||this._lightmapTexture===K||this._refractionTexture===K||this.detailMap.hasTexture(K)},ee.prototype.dispose=function(K,$){var L,G,Q,oe,re,Y,k,H,Z;$&&((L=this._diffuseTexture)===null||L===void 0||L.dispose(),(G=this._ambientTexture)===null||G===void 0||G.dispose(),(Q=this._opacityTexture)===null||Q===void 0||Q.dispose(),(oe=this._reflectionTexture)===null||oe===void 0||oe.dispose(),(re=this._emissiveTexture)===null||re===void 0||re.dispose(),(Y=this._specularTexture)===null||Y===void 0||Y.dispose(),(k=this._bumpTexture)===null||k===void 0||k.dispose(),(H=this._lightmapTexture)===null||H===void 0||H.dispose(),(Z=this._refractionTexture)===null||Z===void 0||Z.dispose()),this.detailMap.dispose($),this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),ae.prototype.dispose.call(this,K,$)},ee.prototype.clone=function(K){var $=this,L=_.a.Clone(function(){return new ee(K,$.getScene())},this);return L.name=K,L.id=K,L},ee.prototype.serialize=function(){return _.a.Serialize(this)},ee.Parse=function(K,$,L){return _.a.Parse(function(){return new ee(K.name,$)},K,$,L)},Object.defineProperty(ee,"DiffuseTextureEnabled",{get:function(){return v.a.DiffuseTextureEnabled},set:function(K){v.a.DiffuseTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"DetailTextureEnabled",{get:function(){return v.a.DetailTextureEnabled},set:function(K){v.a.DetailTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"AmbientTextureEnabled",{get:function(){return v.a.AmbientTextureEnabled},set:function(K){v.a.AmbientTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"OpacityTextureEnabled",{get:function(){return v.a.OpacityTextureEnabled},set:function(K){v.a.OpacityTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"ReflectionTextureEnabled",{get:function(){return v.a.ReflectionTextureEnabled},set:function(K){v.a.ReflectionTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"EmissiveTextureEnabled",{get:function(){return v.a.EmissiveTextureEnabled},set:function(K){v.a.EmissiveTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"SpecularTextureEnabled",{get:function(){return v.a.SpecularTextureEnabled},set:function(K){v.a.SpecularTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"BumpTextureEnabled",{get:function(){return v.a.BumpTextureEnabled},set:function(K){v.a.BumpTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"LightmapTextureEnabled",{get:function(){return v.a.LightmapTextureEnabled},set:function(K){v.a.LightmapTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"RefractionTextureEnabled",{get:function(){return v.a.RefractionTextureEnabled},set:function(K){v.a.RefractionTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"ColorGradingTextureEnabled",{get:function(){return v.a.ColorGradingTextureEnabled},set:function(K){v.a.ColorGradingTextureEnabled=K},enumerable:!1,configurable:!0}),Object.defineProperty(ee,"FresnelEnabled",{get:function(){return v.a.FresnelEnabled},set:function(K){v.a.FresnelEnabled=K},enumerable:!1,configurable:!0}),Object(U.c)([Object(_.m)("diffuseTexture")],ee.prototype,"_diffuseTexture",void 0),Object(U.c)([Object(_.b)("_markAllSubMeshesAsTexturesAndMiscDirty")],ee.prototype,"diffuseTexture",void 0),Object(U.c)([Object(_.m)("ambientTexture")],ee.prototype,"_ambientTexture",void 0),Object(U.c)([Object(_.b)("_markAllSubMeshesAsTexturesDirty")],ee.prototype,"ambientTexture",void 0),Object(U.c)([Object(_.m)("opacityTexture")],ee.prototype,"_opacityTexture",void 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this._meshCollisionData._collisionMask},set:function(j){this._meshCollisionData._collisionMask=isNaN(j)?-1:j},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"collisionResponse",{get:function(){return this._meshCollisionData._collisionResponse},set:function(j){this._meshCollisionData._collisionResponse=j},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"collisionGroup",{get:function(){return this._meshCollisionData._collisionGroup},set:function(j){this._meshCollisionData._collisionGroup=isNaN(j)?-1:j},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"surroundingMeshes",{get:function(){return this._meshCollisionData._surroundingMeshes},set:function(j){this._meshCollisionData._surroundingMeshes=j},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"lightSources",{get:function(){return this._lightSources},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"_positions",{get:function(){return null},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"skeleton",{get:function(){return this._internalAbstractMeshDataInfo._skeleton},set:function(j){var ne=this._internalAbstractMeshDataInfo._skeleton;ne&&ne.needInitialSkinMatrix&&ne._unregisterMeshWithPoseMatrix(this),j&&j.needInitialSkinMatrix&&j._registerMeshWithPoseMatrix(this),this._internalAbstractMeshDataInfo._skeleton=j,this._internalAbstractMeshDataInfo._skeleton||(this._bonesTransformMatrices=null),this._markSubMeshesAsAttributesDirty()},enumerable:!1,configurable:!0}),X.prototype.getClassName=function(){return"AbstractMesh"},X.prototype.toString=function(j){var ne="Name: "+this.name+", isInstance: "+(this.getClassName()!=="InstancedMesh"?"YES":"NO");ne+=", # of submeshes: "+(this.subMeshes?this.subMeshes.length:0);var te=this._internalAbstractMeshDataInfo._skeleton;return te&&(ne+=", skeleton: "+te.name),j&&(ne+=", billboard mode: "+["NONE","X","Y",null,"Z",null,null,"ALL"][this.billboardMode],ne+=", freeze wrld mat: "+(this._isWorldMatrixFrozen||this._waitingData.freezeWorldMatrix?"YES":"NO")),ne},X.prototype._getEffectiveParent=function(){return this._masterMesh&&this.billboardMode!==m.a.BILLBOARDMODE_NONE?this._masterMesh:V.prototype._getEffectiveParent.call(this)},X.prototype._getActionManagerForTrigger=function(j,ne){if(ne===void 0&&(ne=!0),this.actionManager&&(ne||this.actionManager.isRecursive)){if(!j)return this.actionManager;if(this.actionManager.hasSpecificTrigger(j))return this.actionManager}return this.parent?this.parent._getActionManagerForTrigger(j,!1):null},X.prototype._rebuild=function(){if(this.onRebuildObservable.notifyObservers(this),this._occlusionQuery&&(this._occlusionQuery=null),this.subMeshes)for(var j=0,ne=this.subMeshes;j<ne.length;j++)ne[j]._rebuild()},X.prototype._resyncLightSources=function(){this._lightSources.length=0;for(var j=0,ne=this.getScene().lights;j<ne.length;j++){var te=ne[j];te.isEnabled()&&te.canAffectMesh(this)&&this._lightSources.push(te)}this._markSubMeshesAsLightDirty()},X.prototype._resyncLightSource=function(j){var ne=j.isEnabled()&&j.canAffectMesh(this),te=this._lightSources.indexOf(j),de=!1;if(te===-1){if(!ne)return;this._lightSources.push(j)}else{if(ne)return;de=!0,this._lightSources.splice(te,1)}this._markSubMeshesAsLightDirty(de)},X.prototype._unBindEffect=function(){for(var j=0,ne=this.subMeshes;j<ne.length;j++)ne[j].setEffect(null)},X.prototype._removeLightSource=function(j,ne){var te=this._lightSources.indexOf(j);te!==-1&&(this._lightSources.splice(te,1),this._markSubMeshesAsLightDirty(ne))},X.prototype._markSubMeshesAsDirty=function(j){if(this.subMeshes)for(var ne=0,te=this.subMeshes;ne<te.length;ne++){var de=te[ne];de._materialDefines&&j(de._materialDefines)}},X.prototype._markSubMeshesAsLightDirty=function(j){j===void 0&&(j=!1),this._markSubMeshesAsDirty(function(ne){return ne.markAsLightDirty(j)})},X.prototype._markSubMeshesAsAttributesDirty=function(){this._markSubMeshesAsDirty(function(j){return j.markAsAttributesDirty()})},X.prototype._markSubMeshesAsMiscDirty=function(){this._markSubMeshesAsDirty(function(j){return j.markAsMiscDirty()})},Object.defineProperty(X.prototype,"scaling",{get:function(){return this._scaling},set:function(j){this._scaling=j},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"isBlocked",{get:function(){return!1},enumerable:!1,configurable:!0}),X.prototype.getLOD=function(j){return this},X.prototype.getTotalVertices=function(){return 0},X.prototype.getTotalIndices=function(){return 0},X.prototype.getIndices=function(){return null},X.prototype.getVerticesData=function(j){return null},X.prototype.setVerticesData=function(j,ne,te,de){return this},X.prototype.updateVerticesData=function(j,ne,te,de){return this},X.prototype.setIndices=function(j,ne){return this},X.prototype.isVerticesDataPresent=function(j){return!1},X.prototype.getBoundingInfo=function(){return this._masterMesh?this._masterMesh.getBoundingInfo():(this._boundingInfo||this._updateBoundingInfo(),this._boundingInfo)},X.prototype.normalizeToUnitCube=function(j,ne,te){return j===void 0&&(j=!0),ne===void 0&&(ne=!1),V.prototype.normalizeToUnitCube.call(this,j,ne,te)},X.prototype.setBoundingInfo=function(j){return this._boundingInfo=j,this},Object.defineProperty(X.prototype,"useBones",{get:function(){return this.skeleton&&this.getScene().skeletonsEnabled&&this.isVerticesDataPresent(R.b.MatricesIndicesKind)&&this.isVerticesDataPresent(R.b.MatricesWeightsKind)},enumerable:!1,configurable:!0}),X.prototype._preActivate=function(){},X.prototype._preActivateForIntermediateRendering=function(j){},X.prototype._activate=function(j,ne){return this._renderId=j,!0},X.prototype._postActivate=function(){},X.prototype._freeze=function(){},X.prototype._unFreeze=function(){},X.prototype.getWorldMatrix=function(){return this._masterMesh&&this.billboardMode===m.a.BILLBOARDMODE_NONE?this._masterMesh.getWorldMatrix():V.prototype.getWorldMatrix.call(this)},X.prototype._getWorldMatrixDeterminant=function(){return this._masterMesh?this._masterMesh._getWorldMatrixDeterminant():V.prototype._getWorldMatrixDeterminant.call(this)},Object.defineProperty(X.prototype,"isAnInstance",{get:function(){return!1},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"hasInstances",{get:function(){return!1},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"hasThinInstances",{get:function(){return!1},enumerable:!1,configurable:!0}),X.prototype.movePOV=function(j,ne,te){return this.position.addInPlace(this.calcMovePOV(j,ne,te)),this},X.prototype.calcMovePOV=function(j,ne,te){var de=new u.a;(this.rotationQuaternion?this.rotationQuaternion:u.b.RotationYawPitchRoll(this.rotation.y,this.rotation.x,this.rotation.z)).toRotationMatrix(de);var pe=u.e.Zero(),ae=this.definedFacingForward?-1:1;return u.e.TransformCoordinatesFromFloatsToRef(j*ae,ne,te*ae,de,pe),pe},X.prototype.rotatePOV=function(j,ne,te){return this.rotation.addInPlace(this.calcRotatePOV(j,ne,te)),this},X.prototype.calcRotatePOV=function(j,ne,te){var de=this.definedFacingForward?1:-1;return new u.e(j*de,ne,te*de)},X.prototype.refreshBoundingInfo=function(j){return j===void 0&&(j=!1),this._boundingInfo&&this._boundingInfo.isLocked||this._refreshBoundingInfo(this._getPositionData(j),null),this},X.prototype._refreshBoundingInfo=function(j,ne){if(j){var te=Object(l.a)(j,0,this.getTotalVertices(),ne);this._boundingInfo?this._boundingInfo.reConstruct(te.minimum,te.maximum):this._boundingInfo=new T.a(te.minimum,te.maximum)}if(this.subMeshes)for(var de=0;de<this.subMeshes.length;de++)this.subMeshes[de].refreshBoundingInfo(j);this._updateBoundingInfo()},X.prototype._getPositionData=function(j){var ne=this.getVerticesData(R.b.PositionKind);if(ne&&j&&this.skeleton){ne=_.b.Slice(ne),this._generatePointsArray();var te=this.getVerticesData(R.b.MatricesIndicesKind),de=this.getVerticesData(R.b.MatricesWeightsKind);if(de&&te){var pe=this.numBoneInfluencers>4,ae=pe?this.getVerticesData(R.b.MatricesIndicesExtraKind):null,ee=pe?this.getVerticesData(R.b.MatricesWeightsExtraKind):null;this.skeleton.prepare();for(var K=this.skeleton.getTransformMatrices(this),$=u.c.Vector3[0],L=u.c.Matrix[0],G=u.c.Matrix[1],Q=0,oe=0;oe<ne.length;oe+=3,Q+=4){var re,Y;for(L.reset(),re=0;re<4;re++)(Y=de[Q+re])>0&&(u.a.FromFloat32ArrayToRefScaled(K,Math.floor(16*te[Q+re]),Y,G),L.addToSelf(G));if(pe)for(re=0;re<4;re++)(Y=ee[Q+re])>0&&(u.a.FromFloat32ArrayToRefScaled(K,Math.floor(16*ae[Q+re]),Y,G),L.addToSelf(G));u.e.TransformCoordinatesFromFloatsToRef(ne[oe],ne[oe+1],ne[oe+2],L,$),$.toArray(ne,oe),this._positions&&this._positions[oe/3].copyFrom($)}}}return ne},X.prototype._updateBoundingInfo=function(){var j=this._effectiveMesh;return this._boundingInfo?this._boundingInfo.update(j.worldMatrixFromCache):this._boundingInfo=new T.a(this.absolutePosition,this.absolutePosition,j.worldMatrixFromCache),this._updateSubMeshesBoundingInfo(j.worldMatrixFromCache),this},X.prototype._updateSubMeshesBoundingInfo=function(j){if(!this.subMeshes)return this;for(var ne=this.subMeshes.length,te=0;te<ne;te++){var de=this.subMeshes[te];(ne>1||!de.IsGlobal)&&de.updateBoundingInfo(j)}return this},X.prototype._afterComputeWorldMatrix=function(){this.doNotSyncBoundingInfo||this._updateBoundingInfo()},Object.defineProperty(X.prototype,"_effectiveMesh",{get:function(){return this.skeleton&&this.skeleton.overrideMesh||this},enumerable:!1,configurable:!0}),X.prototype.isInFrustum=function(j){return this._boundingInfo!==null&&this._boundingInfo.isInFrustum(j,this.cullingStrategy)},X.prototype.isCompletelyInFrustum=function(j){return this._boundingInfo!==null&&this._boundingInfo.isCompletelyInFrustum(j)},X.prototype.intersectsMesh=function(j,ne,te){if(ne===void 0&&(ne=!1),!this._boundingInfo||!j._boundingInfo)return!1;if(this._boundingInfo.intersects(j._boundingInfo,ne))return!0;if(te){for(var de=0,pe=this.getChildMeshes();de<pe.length;de++)if(pe[de].intersectsMesh(j,ne,!0))return!0}return!1},X.prototype.intersectsPoint=function(j){return!!this._boundingInfo&&this._boundingInfo.intersectsPoint(j)},Object.defineProperty(X.prototype,"checkCollisions",{get:function(){return this._meshCollisionData._checkCollisions},set:function(j){this._meshCollisionData._checkCollisions=j},enumerable:!1,configurable:!0}),Object.defineProperty(X.prototype,"collider",{get:function(){return this._meshCollisionData._collider},enumerable:!1,configurable:!0}),X.prototype.moveWithCollisions=function(j){this.getAbsolutePosition().addToRef(this.ellipsoidOffset,this._meshCollisionData._oldPositionForCollisions);var ne=this.getScene().collisionCoordinator;return this._meshCollisionData._collider||(this._meshCollisionData._collider=ne.createCollider()),this._meshCollisionData._collider._radius=this.ellipsoid,ne.getNewPosition(this._meshCollisionData._oldPositionForCollisions,j,this._meshCollisionData._collider,3,this,this._onCollisionPositionChange,this.uniqueId),this},X.prototype._collideForSubMesh=function(j,ne,te){if(this._generatePointsArray(),!this._positions)return this;if(!j._lastColliderWorldVertices||!j._lastColliderTransformMatrix.equals(ne)){j._lastColliderTransformMatrix=ne.clone(),j._lastColliderWorldVertices=[],j._trianglePlanes=[];for(var de=j.verticesStart,pe=j.verticesStart+j.verticesCount,ae=de;ae<pe;ae++)j._lastColliderWorldVertices.push(u.e.TransformCoordinates(this._positions[ae],ne))}return te._collide(j._trianglePlanes,j._lastColliderWorldVertices,this.getIndices(),j.indexStart,j.indexStart+j.indexCount,j.verticesStart,!!j.getMaterial(),this),this},X.prototype._processCollisionsForSubMeshes=function(j,ne){for(var te=this._scene.getCollidingSubMeshCandidates(this,j),de=te.length,pe=0;pe<de;pe++){var ae=te.data[pe];de>1&&!ae._checkCollision(j)||this._collideForSubMesh(ae,ne,j)}return this},X.prototype._checkCollision=function(j){if(!this._boundingInfo||!this._boundingInfo._checkCollision(j))return this;var ne=u.c.Matrix[0],te=u.c.Matrix[1];return u.a.ScalingToRef(1/j._radius.x,1/j._radius.y,1/j._radius.z,ne),this.worldMatrixFromCache.multiplyToRef(ne,te),this._processCollisionsForSubMeshes(j,te),this},X.prototype._generatePointsArray=function(){return!1},X.prototype.intersects=function(j,ne,te,de,pe,ae){var ee;de===void 0&&(de=!1),ae===void 0&&(ae=!1);var K=new c.a,$=this.getClassName()==="InstancedLinesMesh"||this.getClassName()==="LinesMesh"?this.intersectionThreshold:0,L=this._boundingInfo;if(!this.subMeshes||!L||!(ae||j.intersectsSphere(L.boundingSphere,$)&&j.intersectsBox(L.boundingBox,$)))return K;if(de)return K.hit=!ae,K.pickedMesh=ae?null:this,K.distance=ae?0:u.e.Distance(j.origin,L.boundingSphere.center),K.subMeshId=0,K;if(!this._generatePointsArray())return K;for(var G=null,Q=this._scene.getIntersectingSubMeshCandidates(this,j),oe=Q.length,re=!1,Y=0;Y<oe;Y++){var k=(H=Q.data[Y]).getMaterial();if(k&&(!((ee=this.getIndices())===null||ee===void 0)&&ee.length)&&(k.fillMode==A.a.MATERIAL_TriangleStripDrawMode||k.fillMode==A.a.MATERIAL_TriangleFillMode||k.fillMode==A.a.MATERIAL_WireFrameFillMode||k.fillMode==A.a.MATERIAL_PointFillMode)){re=!0;break}}if(!re)return K.hit=!0,K.pickedMesh=this,K.distance=u.e.Distance(j.origin,L.boundingSphere.center),K.subMeshId=-1,K;for(Y=0;Y<oe;Y++){var H=Q.data[Y];if(!(oe>1)||H.canIntersects(j)){var Z=H.intersects(j,this._positions,this.getIndices(),ne,te);if(Z&&(ne||!G||Z.distance<G.distance)&&((G=Z).subMeshId=Y,ne))break}}if(G){var W=pe??(this.skeleton&&this.skeleton.overrideMesh?this.skeleton.overrideMesh.getWorldMatrix():this.getWorldMatrix()),q=u.c.Vector3[0],he=u.c.Vector3[1];u.e.TransformCoordinatesToRef(j.origin,W,q),j.direction.scaleToRef(G.distance,he);var ge=u.e.TransformNormal(he,W).addInPlace(q);return K.hit=!0,K.distance=u.e.Distance(q,ge),K.pickedPoint=ge,K.pickedMesh=this,K.bu=G.bu||0,K.bv=G.bv||0,K.subMeshFaceId=G.faceId,K.faceId=G.faceId+Q.data[G.subMeshId].indexStart/(this.getClassName().indexOf("LinesMesh")!==-1?2:3),K.subMeshId=G.subMeshId,K}return K},X.prototype.clone=function(j,ne,te){return null},X.prototype.releaseSubMeshes=function(){if(this.subMeshes)for(;this.subMeshes.length;)this.subMeshes[0].dispose();else this.subMeshes=new Array;return this},X.prototype.dispose=function(j,ne){var te,de=this;for(ne===void 0&&(ne=!1),this._scene.useMaterialMeshMap&&this._material&&this._material.meshMap&&(this._material.meshMap[this.uniqueId]=void 0),this.getScene().freeActiveMeshes(),this.getScene().freeRenderingGroups(),this.actionManager!==void 0&&this.actionManager!==null&&(this.actionManager.dispose(),this.actionManager=null),this._internalAbstractMeshDataInfo._skeleton=null,this._transformMatrixTexture&&(this._transformMatrixTexture.dispose(),this._transformMatrixTexture=null),te=0;te<this._intersectionsInProgress.length;te++){var pe=this._intersectionsInProgress[te],ae=pe._intersectionsInProgress.indexOf(this);pe._intersectionsInProgress.splice(ae,1)}this._intersectionsInProgress=[],this.getScene().lights.forEach(function(K){var $=K.includedOnlyMeshes.indexOf(de);$!==-1&&K.includedOnlyMeshes.splice($,1),($=K.excludedMeshes.indexOf(de))!==-1&&K.excludedMeshes.splice($,1);var L=K.getShadowGenerator();if(L){var G=L.getShadowMap();G&&G.renderList&&($=G.renderList.indexOf(de))!==-1&&G.renderList.splice($,1)}}),this.getClassName()==="InstancedMesh"&&this.getClassName()==="InstancedLinesMesh"||this.releaseSubMeshes();var ee=this.getScene().getEngine();if(this._occlusionQuery&&(this.isOcclusionQueryInProgress=!1,ee.deleteQuery(this._occlusionQuery),this._occlusionQuery=null),ee.wipeCaches(),this.getScene().removeMesh(this),ne&&this.material&&(this.material.getClassName()==="MultiMaterial"?this.material.dispose(!1,!0,!0):this.material.dispose(!1,!0)),!j)for(te=0;te<this.getScene().particleSystems.length;te++)this.getScene().particleSystems[te].emitter===this&&(this.getScene().particleSystems[te].dispose(),te--);this._internalAbstractMeshDataInfo._facetData.facetDataEnabled&&this.disableFacetData(),this.onAfterWorldMatrixUpdateObservable.clear(),this.onCollideObservable.clear(),this.onCollisionPositionChangeObservable.clear(),this.onRebuildObservable.clear(),V.prototype.dispose.call(this,j,ne)},X.prototype.addChild=function(j){return j.setParent(this),this},X.prototype.removeChild=function(j){return j.setParent(null),this},X.prototype._initFacetData=function(){var j=this._internalAbstractMeshDataInfo._facetData;j.facetNormals||(j.facetNormals=new Array),j.facetPositions||(j.facetPositions=new Array),j.facetPartitioning||(j.facetPartitioning=new Array),j.facetNb=this.getIndices().length/3|0,j.partitioningSubdivisions=j.partitioningSubdivisions?j.partitioningSubdivisions:10,j.partitioningBBoxRatio=j.partitioningBBoxRatio?j.partitioningBBoxRatio:1.01;for(var ne=0;ne<j.facetNb;ne++)j.facetNormals[ne]=u.e.Zero(),j.facetPositions[ne]=u.e.Zero();return j.facetDataEnabled=!0,this},X.prototype.updateFacetData=function(){var j=this._internalAbstractMeshDataInfo._facetData;j.facetDataEnabled||this._initFacetData();var ne=this.getVerticesData(R.b.PositionKind),te=this.getIndices(),de=this.getVerticesData(R.b.NormalKind),pe=this.getBoundingInfo();if(j.facetDepthSort&&!j.facetDepthSortEnabled){if(j.facetDepthSortEnabled=!0,te instanceof Uint16Array)j.depthSortedIndices=new Uint16Array(te);else if(te instanceof Uint32Array)j.depthSortedIndices=new Uint32Array(te);else{for(var ae=!1,ee=0;ee<te.length;ee++)if(te[ee]>65535){ae=!0;break}j.depthSortedIndices=ae?new Uint32Array(te):new Uint16Array(te)}if(j.facetDepthSortFunction=function(re,Y){return Y.sqDistance-re.sqDistance},!j.facetDepthSortFrom){var K=this.getScene().activeCamera;j.facetDepthSortFrom=K?K.position:u.e.Zero()}j.depthSortedFacets=[];for(var $=0;$<j.facetNb;$++){var L={ind:3*$,sqDistance:0};j.depthSortedFacets.push(L)}j.invertedMatrix=u.a.Identity(),j.facetDepthSortOrigin=u.e.Zero()}j.bbSize.x=pe.maximum.x-pe.minimum.x>v.a?pe.maximum.x-pe.minimum.x:v.a,j.bbSize.y=pe.maximum.y-pe.minimum.y>v.a?pe.maximum.y-pe.minimum.y:v.a,j.bbSize.z=pe.maximum.z-pe.minimum.z>v.a?pe.maximum.z-pe.minimum.z:v.a;var G=j.bbSize.x>j.bbSize.y?j.bbSize.x:j.bbSize.y;if(G=G>j.bbSize.z?G:j.bbSize.z,j.subDiv.max=j.partitioningSubdivisions,j.subDiv.X=Math.floor(j.subDiv.max*j.bbSize.x/G),j.subDiv.Y=Math.floor(j.subDiv.max*j.bbSize.y/G),j.subDiv.Z=Math.floor(j.subDiv.max*j.bbSize.z/G),j.subDiv.X=j.subDiv.X<1?1:j.subDiv.X,j.subDiv.Y=j.subDiv.Y<1?1:j.subDiv.Y,j.subDiv.Z=j.subDiv.Z<1?1:j.subDiv.Z,j.facetParameters.facetNormals=this.getFacetLocalNormals(),j.facetParameters.facetPositions=this.getFacetLocalPositions(),j.facetParameters.facetPartitioning=this.getFacetLocalPartitioning(),j.facetParameters.bInfo=pe,j.facetParameters.bbSize=j.bbSize,j.facetParameters.subDiv=j.subDiv,j.facetParameters.ratio=this.partitioningBBoxRatio,j.facetParameters.depthSort=j.facetDepthSort,j.facetDepthSort&&j.facetDepthSortEnabled&&(this.computeWorldMatrix(!0),this._worldMatrix.invertToRef(j.invertedMatrix),u.e.TransformCoordinatesToRef(j.facetDepthSortFrom,j.invertedMatrix,j.facetDepthSortOrigin),j.facetParameters.distanceTo=j.facetDepthSortOrigin),j.facetParameters.depthSortedFacets=j.depthSortedFacets,x.a.ComputeNormals(ne,te,de,j.facetParameters),j.facetDepthSort&&j.facetDepthSortEnabled){j.depthSortedFacets.sort(j.facetDepthSortFunction);var Q=j.depthSortedIndices.length/3|0;for($=0;$<Q;$++){var oe=j.depthSortedFacets[$].ind;j.depthSortedIndices[3*$]=te[oe],j.depthSortedIndices[3*$+1]=te[oe+1],j.depthSortedIndices[3*$+2]=te[oe+2]}this.updateIndices(j.depthSortedIndices,void 0,!0)}return this},X.prototype.getFacetLocalNormals=function(){var j=this._internalAbstractMeshDataInfo._facetData;return j.facetNormals||this.updateFacetData(),j.facetNormals},X.prototype.getFacetLocalPositions=function(){var j=this._internalAbstractMeshDataInfo._facetData;return j.facetPositions||this.updateFacetData(),j.facetPositions},X.prototype.getFacetLocalPartitioning=function(){var j=this._internalAbstractMeshDataInfo._facetData;return j.facetPartitioning||this.updateFacetData(),j.facetPartitioning},X.prototype.getFacetPosition=function(j){var ne=u.e.Zero();return this.getFacetPositionToRef(j,ne),ne},X.prototype.getFacetPositionToRef=function(j,ne){var te=this.getFacetLocalPositions()[j],de=this.getWorldMatrix();return u.e.TransformCoordinatesToRef(te,de,ne),this},X.prototype.getFacetNormal=function(j){var ne=u.e.Zero();return this.getFacetNormalToRef(j,ne),ne},X.prototype.getFacetNormalToRef=function(j,ne){var te=this.getFacetLocalNormals()[j];return u.e.TransformNormalToRef(te,this.getWorldMatrix(),ne),this},X.prototype.getFacetsAtLocalCoordinates=function(j,ne,te){var de=this.getBoundingInfo(),pe=this._internalAbstractMeshDataInfo._facetData,ae=Math.floor((j-de.minimum.x*pe.partitioningBBoxRatio)*pe.subDiv.X*pe.partitioningBBoxRatio/pe.bbSize.x),ee=Math.floor((ne-de.minimum.y*pe.partitioningBBoxRatio)*pe.subDiv.Y*pe.partitioningBBoxRatio/pe.bbSize.y),K=Math.floor((te-de.minimum.z*pe.partitioningBBoxRatio)*pe.subDiv.Z*pe.partitioningBBoxRatio/pe.bbSize.z);return ae<0||ae>pe.subDiv.max||ee<0||ee>pe.subDiv.max||K<0||K>pe.subDiv.max?null:pe.facetPartitioning[ae+pe.subDiv.max*ee+pe.subDiv.max*pe.subDiv.max*K]},X.prototype.getClosestFacetAtCoordinates=function(j,ne,te,de,pe,ae){pe===void 0&&(pe=!1),ae===void 0&&(ae=!0);var ee=this.getWorldMatrix(),K=u.c.Matrix[5];ee.invertToRef(K);var $=u.c.Vector3[8];u.e.TransformCoordinatesFromFloatsToRef(j,ne,te,K,$);var L=this.getClosestFacetAtLocalCoordinates($.x,$.y,$.z,de,pe,ae);return de&&u.e.TransformCoordinatesFromFloatsToRef(de.x,de.y,de.z,ee,de),L},X.prototype.getClosestFacetAtLocalCoordinates=function(j,ne,te,de,pe,ae){pe===void 0&&(pe=!1),ae===void 0&&(ae=!0);var ee=null,K=0,$=0,L=0,G=0,Q=0,oe=0,re=0,Y=0,k=this.getFacetLocalPositions(),H=this.getFacetLocalNormals(),Z=this.getFacetsAtLocalCoordinates(j,ne,te);if(!Z)return null;for(var W,q,he,ge=Number.MAX_VALUE,me=ge,_e=0;_e<Z.length;_e++)q=H[W=Z[_e]],G=(j-(he=k[W]).x)*q.x+(ne-he.y)*q.y+(te-he.z)*q.z,(!pe||pe&&ae&&G>=0||pe&&!ae&&G<=0)&&(G=q.x*he.x+q.y*he.y+q.z*he.z,Q=-(q.x*j+q.y*ne+q.z*te-G)/(q.x*q.x+q.y*q.y+q.z*q.z),(me=(K=(oe=j+q.x*Q)-j)*K+($=(re=ne+q.y*Q)-ne)*$+(L=(Y=te+q.z*Q)-te)*L)<ge&&(ge=me,ee=W,de&&(de.x=oe,de.y=re,de.z=Y)));return ee},X.prototype.getFacetDataParameters=function(){return this._internalAbstractMeshDataInfo._facetData.facetParameters},X.prototype.disableFacetData=function(){var j=this._internalAbstractMeshDataInfo._facetData;return j.facetDataEnabled&&(j.facetDataEnabled=!1,j.facetPositions=new Array,j.facetNormals=new Array,j.facetPartitioning=new Array,j.facetParameters=null,j.depthSortedIndices=new Uint32Array(0)),this},X.prototype.updateIndices=function(j,ne,te){return this},X.prototype.createNormals=function(j){var ne,te=this.getVerticesData(R.b.PositionKind),de=this.getIndices();return ne=this.isVerticesDataPresent(R.b.NormalKind)?this.getVerticesData(R.b.NormalKind):[],x.a.ComputeNormals(te,de,ne,{useRightHandedSystem:this.getScene().useRightHandedSystem}),this.setVerticesData(R.b.NormalKind,ne,j),this},X.prototype.alignWithNormal=function(j,ne){ne||(ne=E.a.Y);var te=u.c.Vector3[0],de=u.c.Vector3[1];return u.e.CrossToRef(ne,j,de),u.e.CrossToRef(j,de,te),this.rotationQuaternion?u.b.RotationQuaternionFromAxisToRef(te,j,de,this.rotationQuaternion):u.e.RotationFromAxisToRef(te,j,de,this.rotation),this},X.prototype._checkOcclusionQuery=function(){return!1},X.prototype.disableEdgesRendering=function(){throw g.a.WarnImport("EdgesRenderer")},X.prototype.enableEdgesRendering=function(j,ne,te){throw g.a.WarnImport("EdgesRenderer")},X.prototype.getConnectedParticleSystems=function(){var j=this;return this._scene.particleSystems.filter(function(ne){return ne.emitter===j})},X.OCCLUSION_TYPE_NONE=0,X.OCCLUSION_TYPE_OPTIMISTIC=1,X.OCCLUSION_TYPE_STRICT=2,X.OCCLUSION_ALGORITHM_TYPE_ACCURATE=0,X.OCCLUSION_ALGORITHM_TYPE_CONSERVATIVE=1,X.CULLINGSTRATEGY_STANDARD=A.a.MESHES_CULLINGSTRATEGY_STANDARD,X.CULLINGSTRATEGY_BOUNDINGSPHERE_ONLY=A.a.MESHES_CULLINGSTRATEGY_BOUNDINGSPHERE_ONLY,X.CULLINGSTRATEGY_OPTIMISTIC_INCLUSION=A.a.MESHES_CULLINGSTRATEGY_OPTIMISTIC_INCLUSION,X.CULLINGSTRATEGY_OPTIMISTIC_INCLUSION_THEN_BSPHERE_ONLY=A.a.MESHES_CULLINGSTRATEGY_OPTIMISTIC_INCLUSION_THEN_BSPHERE_ONLY,X}(m.a);D.a.RegisteredTypes["BABYLON.AbstractMesh"]=I},function(Me,y,f){f.d(y,"a",function(){return m});var U=f(8),_=f(44),C=f(0),u=f(31),M=f(7),R=f(50),x=f(23);M.a._PhysicsImpostorParser=function(c,T,A){return new m(T,A.physicsImpostor,{mass:A.physicsMass,friction:A.physicsFriction,restitution:A.physicsRestitution},c)};var m=function(){function c(T,A,S,g){var l=this;S===void 0&&(S={mass:0}),this.object=T,this.type=A,this._options=S,this._scene=g,this._pluginData={},this._bodyUpdateRequired=!1,this._onBeforePhysicsStepCallbacks=new Array,this._onAfterPhysicsStepCallbacks=new Array,this._onPhysicsCollideCallbacks=[],this._deltaPosition=C.e.Zero(),this._isDisposed=!1,this.soft=!1,this.segments=0,this._tmpQuat=new C.b,this._tmpQuat2=new C.b,this.beforeStep=function(){l._physicsEngine&&(l.object.translate(l._deltaPosition,-1),l._deltaRotationConjugated&&l.object.rotationQuaternion&&l.object.rotationQuaternion.multiplyToRef(l._deltaRotationConjugated,l.object.rotationQuaternion),l.object.computeWorldMatrix(!1),l.object.parent&&l.object.rotationQuaternion?(l.getParentsRotation(),l._tmpQuat.multiplyToRef(l.object.rotationQuaternion,l._tmpQuat)):l._tmpQuat.copyFrom(l.object.rotationQuaternion||new C.b),l._options.disableBidirectionalTransformation||l.object.rotationQuaternion&&l._physicsEngine.getPhysicsPlugin().setPhysicsBodyTransformation(l,l.object.getAbsolutePosition(),l._tmpQuat),l._onBeforePhysicsStepCallbacks.forEach(function(h){h(l)}))},this.afterStep=function(){l._physicsEngine&&(l._onAfterPhysicsStepCallbacks.forEach(function(h){h(l)}),l._physicsEngine.getPhysicsPlugin().setTransformationFromPhysicsBody(l),l.object.parent&&l.object.rotationQuaternion&&(l.getParentsRotation(),l._tmpQuat.conjugateInPlace(),l._tmpQuat.multiplyToRef(l.object.rotationQuaternion,l.object.rotationQuaternion)),l.object.setAbsolutePosition(l.object.position),l._deltaRotation&&l.object.rotationQuaternion&&l.object.rotationQuaternion.multiplyToRef(l._deltaRotation,l.object.rotationQuaternion),l.object.translate(l._deltaPosition,1))},this.onCollideEvent=null,this.onCollide=function(h){if((l._onPhysicsCollideCallbacks.length||l.onCollideEvent)&&l._physicsEngine){var v=l._physicsEngine.getImpostorWithPhysicsBody(h.body);v&&(l.onCollideEvent&&l.onCollideEvent(l,v),l._onPhysicsCollideCallbacks.filter(function(E){return E.otherImpostors.indexOf(v)!==-1}).forEach(function(E){E.callback(l,v,h.point)}))}},this.object?(this.object.parent&&S.mass!==0&&U.a.Warn("A physics impostor has been created for an object which has a parent. Babylon physics currently works in local space so unexpected issues may occur."),!this._scene&&T.getScene&&(this._scene=T.getScene()),this._scene&&(this.type>100&&(this.soft=!0),this._physicsEngine=this._scene.getPhysicsEngine(),this._physicsEngine?(this.object.rotationQuaternion||(this.object.rotation?this.object.rotationQuaternion=C.b.RotationYawPitchRoll(this.object.rotation.y,this.object.rotation.x,this.object.rotation.z):this.object.rotationQuaternion=new C.b),this._options.mass=S.mass===void 0?0:S.mass,this._options.friction=S.friction===void 0?.2:S.friction,this._options.restitution=S.restitution===void 0?.2:S.restitution,this.soft&&(this._options.mass=this._options.mass>0?this._options.mass:1,this._options.pressure=S.pressure===void 0?200:S.pressure,this._options.stiffness=S.stiffness===void 0?1:S.stiffness,this._options.velocityIterations=S.velocityIterations===void 0?20:S.velocityIterations,this._options.positionIterations=S.positionIterations===void 0?20:S.positionIterations,this._options.fixedPoints=S.fixedPoints===void 0?0:S.fixedPoints,this._options.margin=S.margin===void 0?0:S.margin,this._options.damping=S.damping===void 0?0:S.damping,this._options.path=S.path===void 0?null:S.path,this._options.shape=S.shape===void 0?null:S.shape),this._joints=[],!this.object.parent||this._options.ignoreParent?this._init():this.object.parent.physicsImpostor&&U.a.Warn("You must affect impostors to children before affecting impostor to parent.")):U.a.Error("Physics not enabled. Please use scene.enablePhysics(...) before creating impostors."))):U.a.Error("No object was provided. A physics object is obligatory")}return Object.defineProperty(c.prototype,"isDisposed",{get:function(){return this._isDisposed},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"mass",{get:function(){return this._physicsEngine?this._physicsEngine.getPhysicsPlugin().getBodyMass(this):0},set:function(T){this.setMass(T)},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"friction",{get:function(){return this._physicsEngine?this._physicsEngine.getPhysicsPlugin().getBodyFriction(this):0},set:function(T){this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().setBodyFriction(this,T)},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"restitution",{get:function(){return this._physicsEngine?this._physicsEngine.getPhysicsPlugin().getBodyRestitution(this):0},set:function(T){this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().setBodyRestitution(this,T)},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"pressure",{get:function(){if(!this._physicsEngine)return 0;var T=this._physicsEngine.getPhysicsPlugin();return T.setBodyPressure?T.getBodyPressure(this):0},set:function(T){if(this._physicsEngine){var A=this._physicsEngine.getPhysicsPlugin();A.setBodyPressure&&A.setBodyPressure(this,T)}},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"stiffness",{get:function(){if(!this._physicsEngine)return 0;var T=this._physicsEngine.getPhysicsPlugin();return T.getBodyStiffness?T.getBodyStiffness(this):0},set:function(T){if(this._physicsEngine){var A=this._physicsEngine.getPhysicsPlugin();A.setBodyStiffness&&A.setBodyStiffness(this,T)}},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"velocityIterations",{get:function(){if(!this._physicsEngine)return 0;var T=this._physicsEngine.getPhysicsPlugin();return T.getBodyVelocityIterations?T.getBodyVelocityIterations(this):0},set:function(T){if(this._physicsEngine){var A=this._physicsEngine.getPhysicsPlugin();A.setBodyVelocityIterations&&A.setBodyVelocityIterations(this,T)}},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"positionIterations",{get:function(){if(!this._physicsEngine)return 0;var T=this._physicsEngine.getPhysicsPlugin();return T.getBodyPositionIterations?T.getBodyPositionIterations(this):0},set:function(T){if(this._physicsEngine){var A=this._physicsEngine.getPhysicsPlugin();A.setBodyPositionIterations&&A.setBodyPositionIterations(this,T)}},enumerable:!1,configurable:!0}),c.prototype._init=function(){this._physicsEngine&&(this._physicsEngine.removeImpostor(this),this.physicsBody=null,this._parent=this._parent||this._getPhysicsParent(),this._isDisposed||this.parent&&!this._options.ignoreParent||this._physicsEngine.addImpostor(this))},c.prototype._getPhysicsParent=function(){return this.object.parent instanceof u.a?this.object.parent.physicsImpostor:null},c.prototype.isBodyInitRequired=function(){return this._bodyUpdateRequired||!this._physicsBody&&!this._parent},c.prototype.setScalingUpdated=function(){this.forceUpdate()},c.prototype.forceUpdate=function(){this._init(),this.parent&&!this._options.ignoreParent&&this.parent.forceUpdate()},Object.defineProperty(c.prototype,"physicsBody",{get:function(){return this._parent&&!this._options.ignoreParent?this._parent.physicsBody:this._physicsBody},set:function(T){this._physicsBody&&this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().removePhysicsBody(this),this._physicsBody=T,this.resetUpdateFlags()},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"parent",{get:function(){return!this._options.ignoreParent&&this._parent?this._parent:null},set:function(T){this._parent=T},enumerable:!1,configurable:!0}),c.prototype.resetUpdateFlags=function(){this._bodyUpdateRequired=!1},c.prototype.getObjectExtendSize=function(){if(this.object.getBoundingInfo){var T=this.object.rotationQuaternion,A=this.object.scaling.clone();this.object.rotationQuaternion=c.IDENTITY_QUATERNION;var S=this.object.computeWorldMatrix&&this.object.computeWorldMatrix(!0);S&&S.decompose(A,void 0,void 0);var g=this.object.getBoundingInfo().boundingBox.extendSize.scale(2).multiplyInPlace(A);return this.object.rotationQuaternion=T,this.object.computeWorldMatrix&&this.object.computeWorldMatrix(!0),g}return c.DEFAULT_OBJECT_SIZE},c.prototype.getObjectCenter=function(){return this.object.getBoundingInfo?this.object.getBoundingInfo().boundingBox.centerWorld:this.object.position},c.prototype.getParam=function(T){return this._options[T]},c.prototype.setParam=function(T,A){this._options[T]=A,this._bodyUpdateRequired=!0},c.prototype.setMass=function(T){this.getParam("mass")!==T&&this.setParam("mass",T),this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().setBodyMass(this,T)},c.prototype.getLinearVelocity=function(){return this._physicsEngine?this._physicsEngine.getPhysicsPlugin().getLinearVelocity(this):C.e.Zero()},c.prototype.setLinearVelocity=function(T){this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().setLinearVelocity(this,T)},c.prototype.getAngularVelocity=function(){return this._physicsEngine?this._physicsEngine.getPhysicsPlugin().getAngularVelocity(this):C.e.Zero()},c.prototype.setAngularVelocity=function(T){this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().setAngularVelocity(this,T)},c.prototype.executeNativeFunction=function(T){this._physicsEngine&&T(this._physicsEngine.getPhysicsPlugin().world,this.physicsBody)},c.prototype.registerBeforePhysicsStep=function(T){this._onBeforePhysicsStepCallbacks.push(T)},c.prototype.unregisterBeforePhysicsStep=function(T){var A=this._onBeforePhysicsStepCallbacks.indexOf(T);A>-1?this._onBeforePhysicsStepCallbacks.splice(A,1):U.a.Warn("Function to remove was not found")},c.prototype.registerAfterPhysicsStep=function(T){this._onAfterPhysicsStepCallbacks.push(T)},c.prototype.unregisterAfterPhysicsStep=function(T){var A=this._onAfterPhysicsStepCallbacks.indexOf(T);A>-1?this._onAfterPhysicsStepCallbacks.splice(A,1):U.a.Warn("Function to remove was not found")},c.prototype.registerOnPhysicsCollide=function(T,A){var S=T instanceof Array?T:[T];this._onPhysicsCollideCallbacks.push({callback:A,otherImpostors:S})},c.prototype.unregisterOnPhysicsCollide=function(T,A){var S=T instanceof Array?T:[T],g=-1;this._onPhysicsCollideCallbacks.some(function(l,h){if(l.callback===A&&l.otherImpostors.length===S.length){var v=l.otherImpostors.every(function(E){return S.indexOf(E)>-1});return v&&(g=h),v}return!1})?this._onPhysicsCollideCallbacks.splice(g,1):U.a.Warn("Function to remove was not found")},c.prototype.getParentsRotation=function(){var T=this.object.parent;for(this._tmpQuat.copyFromFloats(0,0,0,1);T;)T.rotationQuaternion?this._tmpQuat2.copyFrom(T.rotationQuaternion):C.b.RotationYawPitchRollToRef(T.rotation.y,T.rotation.x,T.rotation.z,this._tmpQuat2),this._tmpQuat.multiplyToRef(this._tmpQuat2,this._tmpQuat),T=T.parent;return this._tmpQuat},c.prototype.applyForce=function(T,A){return this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().applyForce(this,T,A),this},c.prototype.applyImpulse=function(T,A){return this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().applyImpulse(this,T,A),this},c.prototype.createJoint=function(T,A,S){var g=new R.e(A,S);return this.addJoint(T,g),this},c.prototype.addJoint=function(T,A){return this._joints.push({otherImpostor:T,joint:A}),this._physicsEngine&&this._physicsEngine.addJoint(this,T,A),this},c.prototype.addAnchor=function(T,A,S,g,l){if(!this._physicsEngine)return this;var h=this._physicsEngine.getPhysicsPlugin();return h.appendAnchor?(this._physicsEngine&&h.appendAnchor(this,T,A,S,g,l),this):this},c.prototype.addHook=function(T,A,S,g){if(!this._physicsEngine)return this;var l=this._physicsEngine.getPhysicsPlugin();return l.appendAnchor?(this._physicsEngine&&l.appendHook(this,T,A,S,g),this):this},c.prototype.sleep=function(){return this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().sleepBody(this),this},c.prototype.wakeUp=function(){return this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().wakeUpBody(this),this},c.prototype.clone=function(T){return T?new c(T,this.type,this._options,this._scene):null},c.prototype.dispose=function(){var T=this;this._physicsEngine&&(this._joints.forEach(function(A){T._physicsEngine&&T._physicsEngine.removeJoint(T,A.otherImpostor,A.joint)}),this._physicsEngine.removeImpostor(this),this.parent&&this.parent.forceUpdate(),this._isDisposed=!0)},c.prototype.setDeltaPosition=function(T){this._deltaPosition.copyFrom(T)},c.prototype.setDeltaRotation=function(T){this._deltaRotation||(this._deltaRotation=new C.b),this._deltaRotation.copyFrom(T),this._deltaRotationConjugated=this._deltaRotation.conjugate()},c.prototype.getBoxSizeToRef=function(T){return this._physicsEngine&&this._physicsEngine.getPhysicsPlugin().getBoxSizeToRef(this,T),this},c.prototype.getRadius=function(){return this._physicsEngine?this._physicsEngine.getPhysicsPlugin().getRadius(this):0},c.prototype.syncBoneWithImpostor=function(T,A,S,g,l){var h=c._tmpVecs[0],v=this.object;if(v.rotationQuaternion)if(l){var E=c._tmpQuat;v.rotationQuaternion.multiplyToRef(l,E),T.setRotationQuaternion(E,x.c.WORLD,A)}else T.setRotationQuaternion(v.rotationQuaternion,x.c.WORLD,A);h.x=0,h.y=0,h.z=0,S&&(h.x=S.x,h.y=S.y,h.z=S.z,T.getDirectionToRef(h,A,h),g==null&&(g=S.length()),h.x*=g,h.y*=g,h.z*=g),T.getParent()?(h.addInPlace(v.getAbsolutePosition()),T.setAbsolutePosition(h,A)):(A.setAbsolutePosition(v.getAbsolutePosition()),A.position.x-=h.x,A.position.y-=h.y,A.position.z-=h.z)},c.prototype.syncImpostorWithBone=function(T,A,S,g,l,h){var v=this.object;if(v.rotationQuaternion)if(l){var E=c._tmpQuat;T.getRotationQuaternionToRef(x.c.WORLD,A,E),E.multiplyToRef(l,v.rotationQuaternion)}else T.getRotationQuaternionToRef(x.c.WORLD,A,v.rotationQuaternion);var D=c._tmpVecs[0],w=c._tmpVecs[1];h||((h=c._tmpVecs[2]).x=0,h.y=1,h.z=0),T.getDirectionToRef(h,A,w),T.getAbsolutePositionToRef(A,D),g==null&&S&&(g=S.length()),g!=null&&(D.x+=w.x*g,D.y+=w.y*g,D.z+=w.z*g),v.setAbsolutePosition(D)},c.DEFAULT_OBJECT_SIZE=new C.e(1,1,1),c.IDENTITY_QUATERNION=C.b.Identity(),c._tmpVecs=_.a.BuildArray(3,C.e.Zero),c._tmpQuat=C.b.Identity(),c.NoImpostor=0,c.SphereImpostor=1,c.BoxImpostor=2,c.PlaneImpostor=3,c.MeshImpostor=4,c.CapsuleImpostor=6,c.CylinderImpostor=7,c.ParticleImpostor=8,c.HeightmapImpostor=9,c.ConvexHullImpostor=10,c.CustomImpostor=100,c.RopeImpostor=101,c.ClothImpostor=102,c.SoftbodyImpostor=103,c}()},function(Me,y,f){f.d(y,"a",function(){return _}),f.d(y,"b",function(){return C});var U=f(1),_=function(){function u(M){this.length=0,this.data=new Array(M),this._id=u._GlobalId++}return u.prototype.push=function(M){this.data[this.length++]=M,this.length>this.data.length&&(this.data.length*=2)},u.prototype.forEach=function(M){for(var R=0;R<this.length;R++)M(this.data[R])},u.prototype.sort=function(M){this.data.sort(M)},u.prototype.reset=function(){this.length=0},u.prototype.dispose=function(){this.reset(),this.data&&(this.data.length=0,this.data=[])},u.prototype.concat=function(M){if(M.length!==0){this.length+M.length>this.data.length&&(this.data.length=2*(this.length+M.length));for(var R=0;R<M.length;R++)this.data[this.length++]=(M.data||M)[R]}},u.prototype.indexOf=function(M){var R=this.data.indexOf(M);return R>=this.length?-1:R},u.prototype.contains=function(M){return this.indexOf(M)!==-1},u._GlobalId=0,u}(),C=function(u){function M(){var R=u!==null&&u.apply(this,arguments)||this;return R._duplicateId=0,R}return Object(U.d)(M,u),M.prototype.push=function(R){u.prototype.push.call(this,R),R.__smartArrayFlags||(R.__smartArrayFlags={}),R.__smartArrayFlags[this._id]=this._duplicateId},M.prototype.pushNoDuplicate=function(R){return(!R.__smartArrayFlags||R.__smartArrayFlags[this._id]!==this._duplicateId)&&(this.push(R),!0)},M.prototype.reset=function(){u.prototype.reset.call(this),this._duplicateId++},M.prototype.concatWithNoDuplicate=function(R){if(R.length!==0){this.length+R.length>this.data.length&&(this.data.length=2*(this.length+R.length));for(var x=0;x<R.length;x++){var m=(R.data||R)[x];this.pushNoDuplicate(m)}}},M}(_)},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.EndsWith=function(C,u){return C.indexOf(u,C.length-u.length)!==-1},_.StartsWith=function(C,u){return!!C&&C.indexOf(u)===0},_.Decode=function(C){if(typeof TextDecoder<"u")return new TextDecoder().decode(C);for(var u="",M=0;M<C.byteLength;M++)u+=String.fromCharCode(C[M]);return u},_.EncodeArrayBufferToBase64=function(C){for(var u,M,R,x,m,c,T,A="ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=",S="",g=0,l=ArrayBuffer.isView(C)?new Uint8Array(C.buffer,C.byteOffset,C.byteLength):new Uint8Array(C);g<l.length;)x=(u=l[g++])>>2,m=(3&u)<<4|(M=g<l.length?l[g++]:Number.NaN)>>4,c=(15&M)<<2|(R=g<l.length?l[g++]:Number.NaN)>>6,T=63&R,isNaN(M)?c=T=64:isNaN(R)&&(T=64),S+=A.charAt(x)+A.charAt(m)+A.charAt(c)+A.charAt(T);return S},_.PadNumber=function(C,u){for(var M=String(C);M.length<u;)M="0"+M;return M},_}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){this.rootNodes=new Array,this.cameras=new Array,this.lights=new Array,this.meshes=new Array,this.skeletons=new Array,this.particleSystems=new Array,this.animations=[],this.animationGroups=new Array,this.multiMaterials=new Array,this.materials=new Array,this.morphTargetManagers=new Array,this.geometries=new Array,this.transformNodes=new Array,this.actionManagers=new Array,this.textures=new Array,this._environmentTexture=null,this.postProcesses=new Array}return _.AddParser=function(C,u){this._BabylonFileParsers[C]=u},_.GetParser=function(C){return this._BabylonFileParsers[C]?this._BabylonFileParsers[C]:null},_.AddIndividualParser=function(C,u){this._IndividualBabylonFileParsers[C]=u},_.GetIndividualParser=function(C){return this._IndividualBabylonFileParsers[C]?this._IndividualBabylonFileParsers[C]:null},_.Parse=function(C,u,M,R){for(var x in this._BabylonFileParsers)this._BabylonFileParsers.hasOwnProperty(x)&&this._BabylonFileParsers[x](C,u,M,R)},Object.defineProperty(_.prototype,"environmentTexture",{get:function(){return this._environmentTexture},set:function(C){this._environmentTexture=C},enumerable:!1,configurable:!0}),_.prototype.getNodes=function(){var C=new Array;return C=(C=(C=(C=C.concat(this.meshes)).concat(this.lights)).concat(this.cameras)).concat(this.transformNodes),this.skeletons.forEach(function(u){return C=C.concat(u.bones)}),C},_._BabylonFileParsers={},_._IndividualBabylonFileParsers={},_}()},function(Me,y,f){f.d(y,"a",function(){return m});var U=f(20),_=f(6),C=f(18),u=f(22),M=f(86),R=f(0),x=f(9),m=function(){function c(T,A){var S=this;A===void 0&&(A=!0),this.originalScene=T,this._pointerCaptures={},this._lastPointerEvents={},this._sharedGizmoLight=null,this._renderCamera=null,this.pickUtilitySceneFirst=!0,this.shouldRender=!0,this.onlyCheckPointerDownEvents=!0,this.processAllEvents=!1,this.onPointerOutObservable=new _.c,this.utilityLayerScene=new U.a(T.getEngine(),{virtual:!0}),this.utilityLayerScene.useRightHandedSystem=T.useRightHandedSystem,this.utilityLayerScene._allowPostProcessClearColor=!1,this.utilityLayerScene.detachControl(),A&&(this._originalPointerObserver=T.onPrePointerObservable.add(function(g,l){if(S.utilityLayerScene.activeCamera&&(S.processAllEvents||g.type===C.a.POINTERMOVE||g.type===C.a.POINTERUP||g.type===C.a.POINTERDOWN||g.type===C.a.POINTERDOUBLETAP)){S.utilityLayerScene.pointerX=T.pointerX,S.utilityLayerScene.pointerY=T.pointerY;var h=g.event;if(T.isPointerCaptured(h.pointerId))S._pointerCaptures[h.pointerId]=!1;else{var v=g.ray?S.utilityLayerScene.pickWithRay(g.ray):S.utilityLayerScene.pick(T.pointerX,T.pointerY);if(!g.ray&&v&&(g.ray=v.ray),S.utilityLayerScene.onPrePointerObservable.notifyObservers(g),S.onlyCheckPointerDownEvents&&g.type!=C.a.POINTERDOWN)return g.skipOnPointerObservable||S.utilityLayerScene.onPointerObservable.notifyObservers(new C.b(g.type,g.event,v),g.type),void(g.type===C.a.POINTERUP&&S._pointerCaptures[h.pointerId]&&(S._pointerCaptures[h.pointerId]=!1));if(S.utilityLayerScene.autoClearDepthAndStencil||S.pickUtilitySceneFirst)v&&v.hit&&(g.skipOnPointerObservable||S.utilityLayerScene.onPointerObservable.notifyObservers(new C.b(g.type,g.event,v),g.type),g.skipOnPointerObservable=!0);else{var E=g.ray?T.pickWithRay(g.ray):T.pick(T.pointerX,T.pointerY),D=g.event;E&&v&&(v.distance===0&&E.pickedMesh?S.mainSceneTrackerPredicate&&S.mainSceneTrackerPredicate(E.pickedMesh)?(S._notifyObservers(g,E,D),g.skipOnPointerObservable=!0):g.type===C.a.POINTERDOWN?S._pointerCaptures[D.pointerId]=!0:S._lastPointerEvents[D.pointerId]&&(S.onPointerOutObservable.notifyObservers(D.pointerId),delete S._lastPointerEvents[D.pointerId]):!S._pointerCaptures[D.pointerId]&&(v.distance<E.distance||E.distance===0)?(S._notifyObservers(g,v,D),g.skipOnPointerObservable||(g.skipOnPointerObservable=v.distance>0)):!S._pointerCaptures[D.pointerId]&&v.distance>E.distance&&(S.mainSceneTrackerPredicate&&S.mainSceneTrackerPredicate(E.pickedMesh)?(S._notifyObservers(g,E,D),g.skipOnPointerObservable=!0):S._lastPointerEvents[D.pointerId]&&(S.onPointerOutObservable.notifyObservers(D.pointerId),delete S._lastPointerEvents[D.pointerId])),g.type===C.a.POINTERUP&&S._pointerCaptures[D.pointerId]&&(S._pointerCaptures[D.pointerId]=!1))}}}}),this._originalPointerObserver&&T.onPrePointerObservable.makeObserverTopPriority(this._originalPointerObserver)),this.utilityLayerScene.autoClear=!1,this._afterRenderObserver=this.originalScene.onAfterCameraRenderObservable.add(function(g){S.shouldRender&&g==S.getRenderCamera()&&S.render()}),this._sceneDisposeObserver=this.originalScene.onDisposeObservable.add(function(){S.dispose()}),this._updateCamera()}return c.prototype.getRenderCamera=function(T){if(this._renderCamera)return this._renderCamera;var A=void 0;return A=this.originalScene.activeCameras&&this.originalScene.activeCameras.length>1?this.originalScene.activeCameras[this.originalScene.activeCameras.length-1]:this.originalScene.activeCamera,T&&A&&A.isRigCamera?A.rigParent:A},c.prototype.setRenderCamera=function(T){this._renderCamera=T},c.prototype._getSharedGizmoLight=function(){return this._sharedGizmoLight||(this._sharedGizmoLight=new M.a("shared gizmo light",new R.e(0,1,0),this.utilityLayerScene),this._sharedGizmoLight.intensity=2,this._sharedGizmoLight.groundColor=x.a.Gray()),this._sharedGizmoLight},Object.defineProperty(c,"DefaultUtilityLayer",{get:function(){return c._DefaultUtilityLayer==null&&(c._DefaultUtilityLayer=new c(u.a.LastCreatedScene),c._DefaultUtilityLayer.originalScene.onDisposeObservable.addOnce(function(){c._DefaultUtilityLayer=null})),c._DefaultUtilityLayer},enumerable:!1,configurable:!0}),Object.defineProperty(c,"DefaultKeepDepthUtilityLayer",{get:function(){return c._DefaultKeepDepthUtilityLayer==null&&(c._DefaultKeepDepthUtilityLayer=new c(u.a.LastCreatedScene),c._DefaultKeepDepthUtilityLayer.utilityLayerScene.autoClearDepthAndStencil=!1,c._DefaultKeepDepthUtilityLayer.originalScene.onDisposeObservable.addOnce(function(){c._DefaultKeepDepthUtilityLayer=null})),c._DefaultKeepDepthUtilityLayer},enumerable:!1,configurable:!0}),c.prototype._notifyObservers=function(T,A,S){T.skipOnPointerObservable||(this.utilityLayerScene.onPointerObservable.notifyObservers(new C.b(T.type,T.event,A),T.type),this._lastPointerEvents[S.pointerId]=!0)},c.prototype.render=function(){if(this._updateCamera(),this.utilityLayerScene.activeCamera){var T=this.utilityLayerScene.activeCamera.getScene(),A=this.utilityLayerScene.activeCamera;A._scene=this.utilityLayerScene,A.leftCamera&&(A.leftCamera._scene=this.utilityLayerScene),A.rightCamera&&(A.rightCamera._scene=this.utilityLayerScene),this.utilityLayerScene.render(!1),A._scene=T,A.leftCamera&&(A.leftCamera._scene=T),A.rightCamera&&(A.rightCamera._scene=T)}},c.prototype.dispose=function(){this.onPointerOutObservable.clear(),this._afterRenderObserver&&this.originalScene.onAfterCameraRenderObservable.remove(this._afterRenderObserver),this._sceneDisposeObserver&&this.originalScene.onDisposeObservable.remove(this._sceneDisposeObserver),this._originalPointerObserver&&this.originalScene.onPrePointerObservable.remove(this._originalPointerObserver),this.utilityLayerScene.dispose()},c.prototype._updateCamera=function(){this.utilityLayerScene.cameraToUseForPointers=this.getRenderCamera(),this.utilityLayerScene.activeCamera=this.getRenderCamera()},c._DefaultUtilityLayer=null,c._DefaultKeepDepthUtilityLayer=null,c}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(139),_=function(){function C(){}return C.EnableFor=function(u){u._tags=u._tags||{},u.hasTags=function(){return C.HasTags(u)},u.addTags=function(M){return C.AddTagsTo(u,M)},u.removeTags=function(M){return C.RemoveTagsFrom(u,M)},u.matchesTagsQuery=function(M){return C.MatchesQuery(u,M)}},C.DisableFor=function(u){delete u._tags,delete u.hasTags,delete u.addTags,delete u.removeTags,delete u.matchesTagsQuery},C.HasTags=function(u){if(!u._tags)return!1;var M=u._tags;for(var R in M)if(M.hasOwnProperty(R))return!0;return!1},C.GetTags=function(u,M){if(M===void 0&&(M=!0),!u._tags)return null;if(M){var R=[];for(var x in u._tags)u._tags.hasOwnProperty(x)&&u._tags[x]===!0&&R.push(x);return R.join(" ")}return u._tags},C.AddTagsTo=function(u,M){M&&typeof M=="string"&&M.split(" ").forEach(function(R,x,m){C._AddTagTo(u,R)})},C._AddTagTo=function(u,M){(M=M.trim())!==""&&M!=="true"&&M!=="false"&&(M.match(/[\s]/)||M.match(/^([!]|([|]|[&]){2})/)||(C.EnableFor(u),u._tags[M]=!0))},C.RemoveTagsFrom=function(u,M){if(C.HasTags(u)){var R=M.split(" ");for(var x in R)C._RemoveTagFrom(u,R[x])}},C._RemoveTagFrom=function(u,M){delete u._tags[M]},C.MatchesQuery=function(u,M){return M===void 0||(M===""?C.HasTags(u):U.a.Eval(M,function(R){return C.HasTags(u)&&u._tags[R]}))},C}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.IsWindowObjectExist=function(){return typeof window<"u"},_.IsNavigatorAvailable=function(){return typeof navigator<"u"},_.IsDocumentAvailable=function(){return typeof document<"u"},_.GetDOMTextContent=function(C){for(var u="",M=C.firstChild;M;)M.nodeType===3&&(u+=M.textContent),M=M.nextSibling;return u},_}()},function(Me,y,f){f.d(y,"a",function(){return x});var U=f(44),_=f(0),C=f(54),u=f(114),M=f(20),R=f(24),x=function(){function m(c,T,A){A===void 0&&(A=Number.MAX_VALUE),this.origin=c,this.direction=T,this.length=A}return m.prototype.intersectsBoxMinMax=function(c,T,A){A===void 0&&(A=0);var S,g,l,h,v=m._TmpVector3[0].copyFromFloats(c.x-A,c.y-A,c.z-A),E=m._TmpVector3[1].copyFromFloats(T.x+A,T.y+A,T.z+A),D=0,w=Number.MAX_VALUE;if(Math.abs(this.direction.x)<1e-7){if(this.origin.x<v.x||this.origin.x>E.x)return!1}else if(S=1/this.direction.x,g=(v.x-this.origin.x)*S,(l=(E.x-this.origin.x)*S)===-1/0&&(l=1/0),g>l&&(h=g,g=l,l=h),(D=Math.max(g,D))>(w=Math.min(l,w)))return!1;if(Math.abs(this.direction.y)<1e-7){if(this.origin.y<v.y||this.origin.y>E.y)return!1}else if(S=1/this.direction.y,g=(v.y-this.origin.y)*S,(l=(E.y-this.origin.y)*S)===-1/0&&(l=1/0),g>l&&(h=g,g=l,l=h),(D=Math.max(g,D))>(w=Math.min(l,w)))return!1;if(Math.abs(this.direction.z)<1e-7){if(this.origin.z<v.z||this.origin.z>E.z)return!1}else if(S=1/this.direction.z,g=(v.z-this.origin.z)*S,(l=(E.z-this.origin.z)*S)===-1/0&&(l=1/0),g>l&&(h=g,g=l,l=h),(D=Math.max(g,D))>(w=Math.min(l,w)))return!1;return!0},m.prototype.intersectsBox=function(c,T){return T===void 0&&(T=0),this.intersectsBoxMinMax(c.minimum,c.maximum,T)},m.prototype.intersectsSphere=function(c,T){T===void 0&&(T=0);var A=c.center.x-this.origin.x,S=c.center.y-this.origin.y,g=c.center.z-this.origin.z,l=A*A+S*S+g*g,h=c.radius+T,v=h*h;if(l<=v)return!0;var E=A*this.direction.x+S*this.direction.y+g*this.direction.z;return!(E<0)&&l-E*E<=v},m.prototype.intersectsTriangle=function(c,T,A){var S=m._TmpVector3[0],g=m._TmpVector3[1],l=m._TmpVector3[2],h=m._TmpVector3[3],v=m._TmpVector3[4];T.subtractToRef(c,S),A.subtractToRef(c,g),_.e.CrossToRef(this.direction,g,l);var E=_.e.Dot(S,l);if(E===0)return null;var D=1/E;this.origin.subtractToRef(c,h);var w=_.e.Dot(h,l)*D;if(w<0||w>1)return null;_.e.CrossToRef(h,S,v);var N=_.e.Dot(this.direction,v)*D;if(N<0||w+N>1)return null;var I=_.e.Dot(g,v)*D;return I>this.length?null:new u.a(1-w-N,w,I)},m.prototype.intersectsPlane=function(c){var T,A=_.e.Dot(c.normal,this.direction);if(Math.abs(A)<999999997475243e-21)return null;var S=_.e.Dot(c.normal,this.origin);return(T=(-c.d-S)/A)<0?T<-999999997475243e-21?null:0:T},m.prototype.intersectsAxis=function(c,T){switch(T===void 0&&(T=0),c){case"y":return(A=(this.origin.y-T)/this.direction.y)>0?null:new _.e(this.origin.x+this.direction.x*-A,T,this.origin.z+this.direction.z*-A);case"x":return(A=(this.origin.x-T)/this.direction.x)>0?null:new _.e(T,this.origin.y+this.direction.y*-A,this.origin.z+this.direction.z*-A);case"z":var A;return(A=(this.origin.z-T)/this.direction.z)>0?null:new _.e(this.origin.x+this.direction.x*-A,this.origin.y+this.direction.y*-A,T);default:return null}},m.prototype.intersectsMesh=function(c,T){var A=_.c.Matrix[0];return c.getWorldMatrix().invertToRef(A),this._tmpRay?m.TransformToRef(this,A,this._tmpRay):this._tmpRay=m.Transform(this,A),c.intersects(this._tmpRay,T)},m.prototype.intersectsMeshes=function(c,T,A){A?A.length=0:A=[];for(var S=0;S<c.length;S++){var g=this.intersectsMesh(c[S],T);g.hit&&A.push(g)}return A.sort(this._comparePickingInfo),A},m.prototype._comparePickingInfo=function(c,T){return c.distance<T.distance?-1:c.distance>T.distance?1:0},m.prototype.intersectionSegment=function(c,T,A){var S=this.origin,g=_.c.Vector3[0],l=_.c.Vector3[1],h=_.c.Vector3[2],v=_.c.Vector3[3];T.subtractToRef(c,g),this.direction.scaleToRef(m.rayl,h),S.addToRef(h,l),c.subtractToRef(S,v);var E,D,w,N,I=_.e.Dot(g,g),V=_.e.Dot(g,h),X=_.e.Dot(h,h),j=_.e.Dot(g,v),ne=_.e.Dot(h,v),te=I*X-V*V,de=te,pe=te;te<m.smallnum?(D=0,de=1,N=ne,pe=X):(N=I*ne-V*j,(D=V*ne-X*j)<0?(D=0,N=ne,pe=X):D>de&&(D=de,N=ne+V,pe=X)),N<0?(N=0,-j<0?D=0:-j>I?D=de:(D=-j,de=I)):N>pe&&(N=pe,-j+V<0?D=0:-j+V>I?D=de:(D=-j+V,de=I)),E=Math.abs(D)<m.smallnum?0:D/de,w=Math.abs(N)<m.smallnum?0:N/pe;var ae=_.c.Vector3[4];h.scaleToRef(w,ae);var ee=_.c.Vector3[5];g.scaleToRef(E,ee),ee.addInPlace(v);var K=_.c.Vector3[6];return ee.subtractToRef(ae,K),w>0&&w<=this.length&&K.lengthSquared()<A*A?ee.length():-1},m.prototype.update=function(c,T,A,S,g,l,h){return this.unprojectRayToRef(c,T,A,S,g,l,h),this},m.Zero=function(){return new m(_.e.Zero(),_.e.Zero())},m.CreateNew=function(c,T,A,S,g,l,h){return m.Zero().update(c,T,A,S,g,l,h)},m.CreateNewFromTo=function(c,T,A){A===void 0&&(A=_.a.IdentityReadOnly);var S=T.subtract(c),g=Math.sqrt(S.x*S.x+S.y*S.y+S.z*S.z);return S.normalize(),m.Transform(new m(c,S,g),A)},m.Transform=function(c,T){var A=new m(new _.e(0,0,0),new _.e(0,0,0));return m.TransformToRef(c,T,A),A},m.TransformToRef=function(c,T,A){_.e.TransformCoordinatesToRef(c.origin,T,A.origin),_.e.TransformNormalToRef(c.direction,T,A.direction),A.length=c.length;var S=A.direction,g=S.length();if(g!==0&&g!==1){var l=1/g;S.x*=l,S.y*=l,S.z*=l,A.length*=g}},m.prototype.unprojectRayToRef=function(c,T,A,S,g,l,h){var v=_.c.Matrix[0];g.multiplyToRef(l,v),v.multiplyToRef(h,v),v.invert();var E=_.c.Vector3[0];E.x=c/A*2-1,E.y=-(T/S*2-1),E.z=-1;var D=_.c.Vector3[1].copyFromFloats(E.x,E.y,1),w=_.c.Vector3[2],N=_.c.Vector3[3];_.e._UnprojectFromInvertedMatrixToRef(E,v,w),_.e._UnprojectFromInvertedMatrixToRef(D,v,N),this.origin.copyFrom(w),N.subtractToRef(w,this.direction),this.direction.normalize()},m._TmpVector3=U.a.BuildArray(6,_.e.Zero),m.smallnum=1e-8,m.rayl=1e9,m}();M.a.prototype.createPickingRay=function(m,c,T,A,S){S===void 0&&(S=!1);var g=x.Zero();return this.createPickingRayToRef(m,c,T,g,A,S),g},M.a.prototype.createPickingRayToRef=function(m,c,T,A,S,g){g===void 0&&(g=!1);var l=this.getEngine();if(!S){if(!this.activeCamera)return this;S=this.activeCamera}var h=S.viewport.toGlobal(l.getRenderWidth(),l.getRenderHeight());return m=m/l.getHardwareScalingLevel()-h.x,c=c/l.getHardwareScalingLevel()-(l.getRenderHeight()-h.y-h.height),A.update(m,c,h.width,h.height,T||_.a.IdentityReadOnly,g?_.a.IdentityReadOnly:S.getViewMatrix(),S.getProjectionMatrix()),this},M.a.prototype.createPickingRayInCameraSpace=function(m,c,T){var A=x.Zero();return this.createPickingRayInCameraSpaceToRef(m,c,A,T),A},M.a.prototype.createPickingRayInCameraSpaceToRef=function(m,c,T,A){if(!C.a)return this;var S=this.getEngine();if(!A){if(!this.activeCamera)throw new Error("Active camera not set");A=this.activeCamera}var g=A.viewport.toGlobal(S.getRenderWidth(),S.getRenderHeight()),l=_.a.Identity();return m=m/S.getHardwareScalingLevel()-g.x,c=c/S.getHardwareScalingLevel()-(S.getRenderHeight()-g.y-g.height),T.update(m,c,g.width,g.height,l,l,A.getProjectionMatrix()),this},M.a.prototype._internalPickForMesh=function(m,c,T,A,S,g,l,h){var v=c(A),E=T.intersects(v,S,l,g,A,h);return E&&E.hit?!S&&m!=null&&E.distance>=m.distance?null:E:null},M.a.prototype._internalPick=function(m,c,T,A,S){if(!C.a)return null;for(var g=null,l=0;l<this.meshes.length;l++){var h=this.meshes[l];if(c){if(!c(h))continue}else if(!h.isEnabled()||!h.isVisible||!h.isPickable)continue;var v,E=h.skeleton&&h.skeleton.overrideMesh?h.skeleton.overrideMesh.getWorldMatrix():h.getWorldMatrix();if(h.hasThinInstances&&h.thinInstanceEnablePicking){if(v=this._internalPickForMesh(g,m,h,E,!0,!0,S)){if(A)return g;for(var D=_.c.Matrix[1],w=h.thinInstanceGetWorldMatrices(),N=0;N<w.length;N++){w[N].multiplyToRef(E,D);var I=this._internalPickForMesh(g,m,h,D,T,A,S,!0);if(I&&((g=I).thinInstanceIndex=N,T))return g}}}else if((v=this._internalPickForMesh(g,m,h,E,T,A,S))&&(g=v,T))return g}return g||new C.a},M.a.prototype._internalMultiPick=function(m,c,T){if(!C.a)return null;for(var A=new Array,S=0;S<this.meshes.length;S++){var g=this.meshes[S];if(c){if(!c(g))continue}else if(!g.isEnabled()||!g.isVisible||!g.isPickable)continue;var l,h=g.skeleton&&g.skeleton.overrideMesh?g.skeleton.overrideMesh.getWorldMatrix():g.getWorldMatrix();if(g.hasThinInstances&&g.thinInstanceEnablePicking){if(l=this._internalPickForMesh(null,m,g,h,!0,!0,T))for(var v=_.c.Matrix[1],E=g.thinInstanceGetWorldMatrices(),D=0;D<E.length;D++){E[D].multiplyToRef(h,v);var w=this._internalPickForMesh(null,m,g,v,!1,!1,T,!0);w&&(w.thinInstanceIndex=D,A.push(w))}}else(l=this._internalPickForMesh(null,m,g,h,!1,!1,T))&&A.push(l)}return A},M.a.prototype.pickWithBoundingInfo=function(m,c,T,A,S){var g=this;if(!C.a)return null;var l=this._internalPick(function(h){return g._tempPickingRay||(g._tempPickingRay=x.Zero()),g.createPickingRayToRef(m,c,h,g._tempPickingRay,S||null),g._tempPickingRay},T,A,!0);return l&&(l.ray=this.createPickingRay(m,c,_.a.Identity(),S||null)),l},M.a.prototype.pick=function(m,c,T,A,S,g){var l=this;if(!C.a)return null;var h=this._internalPick(function(v){return l._tempPickingRay||(l._tempPickingRay=x.Zero()),l.createPickingRayToRef(m,c,v,l._tempPickingRay,S||null),l._tempPickingRay},T,A,!1,g);return h&&(h.ray=this.createPickingRay(m,c,_.a.Identity(),S||null)),h},M.a.prototype.pickWithRay=function(m,c,T,A){var S=this,g=this._internalPick(function(l){return S._pickWithRayInverseMatrix||(S._pickWithRayInverseMatrix=_.a.Identity()),l.invertToRef(S._pickWithRayInverseMatrix),S._cachedRayForTransform||(S._cachedRayForTransform=x.Zero()),x.TransformToRef(m,S._pickWithRayInverseMatrix,S._cachedRayForTransform),S._cachedRayForTransform},c,T,!1,A);return g&&(g.ray=m),g},M.a.prototype.multiPick=function(m,c,T,A,S){var g=this;return this._internalMultiPick(function(l){return g.createPickingRay(m,c,l,A||null)},T,S)},M.a.prototype.multiPickWithRay=function(m,c,T){var A=this;return this._internalMultiPick(function(S){return A._pickWithRayInverseMatrix||(A._pickWithRayInverseMatrix=_.a.Identity()),S.invertToRef(A._pickWithRayInverseMatrix),A._cachedRayForTransform||(A._cachedRayForTransform=x.Zero()),x.TransformToRef(m,A._pickWithRayInverseMatrix,A._cachedRayForTransform),A._cachedRayForTransform},c,T)},R.a.prototype.getForwardRay=function(m,c,T){return m===void 0&&(m=100),this.getForwardRayToRef(new x(_.e.Zero(),_.e.Zero(),m),m,c,T)},R.a.prototype.getForwardRayToRef=function(m,c,T,A){return c===void 0&&(c=100),T||(T=this.getWorldMatrix()),m.length=c,A?m.origin.copyFrom(A):m.origin.copyFrom(this.position),_.c.Vector3[2].set(0,0,this._scene.useRightHandedSystem?-1:1),_.e.TransformNormalToRef(_.c.Vector3[2],T,_.c.Vector3[3]),_.e.NormalizeToRef(_.c.Vector3[3],m.direction),m}},function(Me,y,f){f.d(y,"a",function(){return R});var U=f(0),_=f(7),C=f(16),u=f(98),M=f(4);C.a.CreateLineSystem=function(x){for(var m=[],c=[],T=x.lines,A=x.colors,S=[],g=0,l=0;l<T.length;l++)for(var h=T[l],v=0;v<h.length;v++){if(c.push(h[v].x,h[v].y,h[v].z),A){var E=A[l];S.push(E[v].r,E[v].g,E[v].b,E[v].a)}v>0&&(m.push(g-1),m.push(g)),g++}var D=new C.a;return D.indices=m,D.positions=c,A&&(D.colors=S),D},C.a.CreateDashedLines=function(x){var m,c,T=x.dashSize||3,A=x.gapSize||1,S=x.dashNb||200,g=x.points,l=new Array,h=new Array,v=U.e.Zero(),E=0,D=0,w=0,N=0,I=0;for(I=0;I<g.length-1;I++)g[I+1].subtractToRef(g[I],v),E+=v.length();for(c=T*(m=E/S)/(T+A),I=0;I<g.length-1;I++){g[I+1].subtractToRef(g[I],v),D=Math.floor(v.length()/m),v.normalize();for(var V=0;V<D;V++)w=m*V,l.push(g[I].x+w*v.x,g[I].y+w*v.y,g[I].z+w*v.z),l.push(g[I].x+(w+c)*v.x,g[I].y+(w+c)*v.y,g[I].z+(w+c)*v.z),h.push(N,N+1),N+=2}var X=new C.a;return X.positions=l,X.indices=h,X},_.a.CreateLines=function(x,m,c,T,A){c===void 0&&(c=null),T===void 0&&(T=!1),A===void 0&&(A=null);var S={points:m,updatable:T,instance:A};return R.CreateLines(x,S,c)},_.a.CreateDashedLines=function(x,m,c,T,A,S,g,l){S===void 0&&(S=null);var h={points:m,dashSize:c,gapSize:T,dashNb:A,updatable:g,instance:l};return R.CreateDashedLines(x,h,S)};var R=function(){function x(){}return x.CreateLineSystem=function(m,c,T){var A=c.instance,S=c.lines,g=c.colors;if(A){var l,h,v=A.getVerticesData(M.b.PositionKind);g&&(l=A.getVerticesData(M.b.ColorKind));for(var E=0,D=0,w=0;w<S.length;w++)for(var N=S[w],I=0;I<N.length;I++)v[E]=N[I].x,v[E+1]=N[I].y,v[E+2]=N[I].z,g&&l&&(h=g[w],l[D]=h[I].r,l[D+1]=h[I].g,l[D+2]=h[I].b,l[D+3]=h[I].a,D+=4),E+=3;return A.updateVerticesData(M.b.PositionKind,v,!1,!1),g&&l&&A.updateVerticesData(M.b.ColorKind,l,!1,!1),A}var V=!!g,X=new u.b(m,T,null,void 0,void 0,V,c.useVertexAlpha);return C.a.CreateLineSystem(c).applyToMesh(X,c.updatable),X},x.CreateLines=function(m,c,T){T===void 0&&(T=null);var A=c.colors?[c.colors]:null;return x.CreateLineSystem(m,{lines:[c.points],updatable:c.updatable,instance:c.instance,colors:A,useVertexAlpha:c.useVertexAlpha},T)},x.CreateDashedLines=function(m,c,T){T===void 0&&(T=null);var A=c.points,S=c.instance,g=c.gapSize||1,l=c.dashSize||3;if(S)return S.updateMeshPositions(function(v){var E,D,w=U.e.Zero(),N=v.length/6,I=0,V=0,X=0,j=0,ne=0,te=0;for(ne=0;ne<A.length-1;ne++)A[ne+1].subtractToRef(A[ne],w),I+=w.length();E=I/N;var de=S._creationDataStorage.dashSize;for(D=de*E/(de+S._creationDataStorage.gapSize),ne=0;ne<A.length-1;ne++)for(A[ne+1].subtractToRef(A[ne],w),V=Math.floor(w.length()/E),w.normalize(),te=0;te<V&&j<v.length;)X=E*te,v[j]=A[ne].x+X*w.x,v[j+1]=A[ne].y+X*w.y,v[j+2]=A[ne].z+X*w.z,v[j+3]=A[ne].x+(X+D)*w.x,v[j+4]=A[ne].y+(X+D)*w.y,v[j+5]=A[ne].z+(X+D)*w.z,j+=6,te++;for(;j<v.length;)v[j]=A[ne].x,v[j+1]=A[ne].y,v[j+2]=A[ne].z,j+=3},!1),S;var h=new u.b(m,T,null,void 0,void 0,void 0,c.useVertexAlpha);return C.a.CreateDashedLines(c).applyToMesh(h,c.updatable),h._creationDataStorage=new _.b,h._creationDataStorage.dashSize=l,h._creationDataStorage.gapSize=g,h},x}()},function(Me,y,f){f.d(y,"a",function(){return u});var U=f(34),_=f(8),C=function(M,R){return M?M.getClassName&&M.getClassName()==="Mesh"?null:M.getClassName&&M.getClassName()==="SubMesh"?M.clone(R):M.clone?M.clone():null:null},u=function(){function M(){}return M.DeepCopy=function(R,x,m,c){for(var T=0,A=function(E){var D=[];do Object.getOwnPropertyNames(E).forEach(function(w){D.indexOf(w)===-1&&D.push(w)});while(E=Object.getPrototypeOf(E));return D}(R);T<A.length;T++){var S=A[T];if((S[0]!=="_"||c&&c.indexOf(S)!==-1)&&!(U.a.EndsWith(S,"Observable")||m&&m.indexOf(S)!==-1)){var g=R[S],l=typeof g;if(l!=="function")try{if(l==="object")if(g instanceof Array){if(x[S]=[],g.length>0)if(typeof g[0]=="object")for(var h=0;h<g.length;h++){var v=C(g[h],x);x[S].indexOf(v)===-1&&x[S].push(v)}else x[S]=g.slice(0)}else x[S]=C(g,x);else x[S]=g}catch(E){_.a.Warn(E.message)}}}},M}()},function(Me,y,f){f.d(y,"b",function(){return m}),f.d(y,"a",function(){return c});var U=f(1),_=f(3),C=f(6),u=f(12),M=f(9),R=f(76),x=f(121),m=function(T){function A(){var S=T.call(this)||this;return S.IMAGEPROCESSING=!1,S.VIGNETTE=!1,S.VIGNETTEBLENDMODEMULTIPLY=!1,S.VIGNETTEBLENDMODEOPAQUE=!1,S.TONEMAPPING=!1,S.TONEMAPPING_ACES=!1,S.CONTRAST=!1,S.COLORCURVES=!1,S.COLORGRADING=!1,S.COLORGRADING3D=!1,S.SAMPLER3DGREENDEPTH=!1,S.SAMPLER3DBGRMAP=!1,S.IMAGEPROCESSINGPOSTPROCESS=!1,S.EXPOSURE=!1,S.rebuild(),S}return Object(U.d)(A,T),A}(R.a),c=function(){function T(){this.colorCurves=new x.a,this._colorCurvesEnabled=!1,this._colorGradingEnabled=!1,this._colorGradingWithGreenDepth=!0,this._colorGradingBGR=!0,this._exposure=1,this._toneMappingEnabled=!1,this._toneMappingType=T.TONEMAPPING_STANDARD,this._contrast=1,this.vignetteStretch=0,this.vignetteCentreX=0,this.vignetteCentreY=0,this.vignetteWeight=1.5,this.vignetteColor=new M.b(0,0,0,0),this.vignetteCameraFov=.5,this._vignetteBlendMode=T.VIGNETTEMODE_MULTIPLY,this._vignetteEnabled=!1,this._applyByPostProcess=!1,this._isEnabled=!0,this.onUpdateParameters=new C.c}return Object.defineProperty(T.prototype,"colorCurvesEnabled",{get:function(){return this._colorCurvesEnabled},set:function(A){this._colorCurvesEnabled!==A&&(this._colorCurvesEnabled=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"colorGradingTexture",{get:function(){return this._colorGradingTexture},set:function(A){this._colorGradingTexture!==A&&(this._colorGradingTexture=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"colorGradingEnabled",{get:function(){return this._colorGradingEnabled},set:function(A){this._colorGradingEnabled!==A&&(this._colorGradingEnabled=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"colorGradingWithGreenDepth",{get:function(){return this._colorGradingWithGreenDepth},set:function(A){this._colorGradingWithGreenDepth!==A&&(this._colorGradingWithGreenDepth=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"colorGradingBGR",{get:function(){return this._colorGradingBGR},set:function(A){this._colorGradingBGR!==A&&(this._colorGradingBGR=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"exposure",{get:function(){return this._exposure},set:function(A){this._exposure!==A&&(this._exposure=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"toneMappingEnabled",{get:function(){return this._toneMappingEnabled},set:function(A){this._toneMappingEnabled!==A&&(this._toneMappingEnabled=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"toneMappingType",{get:function(){return this._toneMappingType},set:function(A){this._toneMappingType!==A&&(this._toneMappingType=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"contrast",{get:function(){return this._contrast},set:function(A){this._contrast!==A&&(this._contrast=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"vignetteBlendMode",{get:function(){return this._vignetteBlendMode},set:function(A){this._vignetteBlendMode!==A&&(this._vignetteBlendMode=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"vignetteEnabled",{get:function(){return this._vignetteEnabled},set:function(A){this._vignetteEnabled!==A&&(this._vignetteEnabled=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"applyByPostProcess",{get:function(){return this._applyByPostProcess},set:function(A){this._applyByPostProcess!==A&&(this._applyByPostProcess=A,this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"isEnabled",{get:function(){return this._isEnabled},set:function(A){this._isEnabled!==A&&(this._isEnabled=A,this._updateParameters())},enumerable:!1,configurable:!0}),T.prototype._updateParameters=function(){this.onUpdateParameters.notifyObservers(this)},T.prototype.getClassName=function(){return"ImageProcessingConfiguration"},T.PrepareUniforms=function(A,S){S.EXPOSURE&&A.push("exposureLinear"),S.CONTRAST&&A.push("contrast"),S.COLORGRADING&&A.push("colorTransformSettings"),S.VIGNETTE&&(A.push("vInverseScreenSize"),A.push("vignetteSettings1"),A.push("vignetteSettings2")),S.COLORCURVES&&x.a.PrepareUniforms(A)},T.PrepareSamplers=function(A,S){S.COLORGRADING&&A.push("txColorTransform")},T.prototype.prepareDefines=function(A,S){if(S===void 0&&(S=!1),S!==this.applyByPostProcess||!this._isEnabled)return A.VIGNETTE=!1,A.TONEMAPPING=!1,A.TONEMAPPING_ACES=!1,A.CONTRAST=!1,A.EXPOSURE=!1,A.COLORCURVES=!1,A.COLORGRADING=!1,A.COLORGRADING3D=!1,A.IMAGEPROCESSING=!1,void(A.IMAGEPROCESSINGPOSTPROCESS=this.applyByPostProcess&&this._isEnabled);switch(A.VIGNETTE=this.vignetteEnabled,A.VIGNETTEBLENDMODEMULTIPLY=this.vignetteBlendMode===T._VIGNETTEMODE_MULTIPLY,A.VIGNETTEBLENDMODEOPAQUE=!A.VIGNETTEBLENDMODEMULTIPLY,A.TONEMAPPING=this.toneMappingEnabled,this._toneMappingType){case T.TONEMAPPING_ACES:A.TONEMAPPING_ACES=!0;break;default:A.TONEMAPPING_ACES=!1}A.CONTRAST=this.contrast!==1,A.EXPOSURE=this.exposure!==1,A.COLORCURVES=this.colorCurvesEnabled&&!!this.colorCurves,A.COLORGRADING=this.colorGradingEnabled&&!!this.colorGradingTexture,A.COLORGRADING?A.COLORGRADING3D=this.colorGradingTexture.is3D:A.COLORGRADING3D=!1,A.SAMPLER3DGREENDEPTH=this.colorGradingWithGreenDepth,A.SAMPLER3DBGRMAP=this.colorGradingBGR,A.IMAGEPROCESSINGPOSTPROCESS=this.applyByPostProcess,A.IMAGEPROCESSING=A.VIGNETTE||A.TONEMAPPING||A.CONTRAST||A.EXPOSURE||A.COLORCURVES||A.COLORGRADING},T.prototype.isReady=function(){return!this.colorGradingEnabled||!this.colorGradingTexture||this.colorGradingTexture.isReady()},T.prototype.bind=function(A,S){if(this._colorCurvesEnabled&&this.colorCurves&&x.a.Bind(this.colorCurves,A),this._vignetteEnabled){var g=1/A.getEngine().getRenderWidth(),l=1/A.getEngine().getRenderHeight();A.setFloat2("vInverseScreenSize",g,l);var h=S??l/g,v=Math.tan(.5*this.vignetteCameraFov),E=v*h,D=Math.sqrt(E*v);E=u.b.Mix(E,D,this.vignetteStretch),v=u.b.Mix(v,D,this.vignetteStretch),A.setFloat4("vignetteSettings1",E,v,-E*this.vignetteCentreX,-v*this.vignetteCentreY);var w=-2*this.vignetteWeight;A.setFloat4("vignetteSettings2",this.vignetteColor.r,this.vignetteColor.g,this.vignetteColor.b,w)}if(A.setFloat("exposureLinear",this.exposure),A.setFloat("contrast",this.contrast),this.colorGradingTexture){A.setTexture("txColorTransform",this.colorGradingTexture);var N=this.colorGradingTexture.getSize().height;A.setFloat4("colorTransformSettings",(N-1)/N,.5/N,N,this.colorGradingTexture.level)}},T.prototype.clone=function(){return _.a.Clone(function(){return new T},this)},T.prototype.serialize=function(){return _.a.Serialize(this)},T.Parse=function(A){return _.a.Parse(function(){return new T},A,null,null)},Object.defineProperty(T,"VIGNETTEMODE_MULTIPLY",{get:function(){return this._VIGNETTEMODE_MULTIPLY},enumerable:!1,configurable:!0}),Object.defineProperty(T,"VIGNETTEMODE_OPAQUE",{get:function(){return this._VIGNETTEMODE_OPAQUE},enumerable:!1,configurable:!0}),T.TONEMAPPING_STANDARD=0,T.TONEMAPPING_ACES=1,T._VIGNETTEMODE_MULTIPLY=0,T._VIGNETTEMODE_OPAQUE=1,Object(U.c)([Object(_.g)()],T.prototype,"colorCurves",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_colorCurvesEnabled",void 0),Object(U.c)([Object(_.m)("colorGradingTexture")],T.prototype,"_colorGradingTexture",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_colorGradingEnabled",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_colorGradingWithGreenDepth",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_colorGradingBGR",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_exposure",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_toneMappingEnabled",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_toneMappingType",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_contrast",void 0),Object(U.c)([Object(_.c)()],T.prototype,"vignetteStretch",void 0),Object(U.c)([Object(_.c)()],T.prototype,"vignetteCentreX",void 0),Object(U.c)([Object(_.c)()],T.prototype,"vignetteCentreY",void 0),Object(U.c)([Object(_.c)()],T.prototype,"vignetteWeight",void 0),Object(U.c)([Object(_.f)()],T.prototype,"vignetteColor",void 0),Object(U.c)([Object(_.c)()],T.prototype,"vignetteCameraFov",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_vignetteBlendMode",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_vignetteEnabled",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_applyByPostProcess",void 0),Object(U.c)([Object(_.c)()],T.prototype,"_isEnabled",void 0),T}();_.a._ImageProcessingConfigurationParser=c.Parse},function(Me,y,f){f.d(y,"a",function(){return T});var U=f(44),_=f(0),C=f(2),u=f(103),M=f(113),R={min:0,max:0},x={min:0,max:0},m=function(A,S,g){var l=_.e.Dot(S.centerWorld,A),h=Math.abs(_.e.Dot(S.directions[0],A))*S.extendSize.x+Math.abs(_.e.Dot(S.directions[1],A))*S.extendSize.y+Math.abs(_.e.Dot(S.directions[2],A))*S.extendSize.z;g.min=l-h,g.max=l+h},c=function(A,S,g){return m(A,S,R),m(A,g,x),!(R.min>x.max||x.min>R.max)},T=function(){function A(S,g,l){this._isLocked=!1,this.boundingBox=new u.a(S,g,l),this.boundingSphere=new M.a(S,g,l)}return A.prototype.reConstruct=function(S,g,l){this.boundingBox.reConstruct(S,g,l),this.boundingSphere.reConstruct(S,g,l)},Object.defineProperty(A.prototype,"minimum",{get:function(){return this.boundingBox.minimum},enumerable:!1,configurable:!0}),Object.defineProperty(A.prototype,"maximum",{get:function(){return this.boundingBox.maximum},enumerable:!1,configurable:!0}),Object.defineProperty(A.prototype,"isLocked",{get:function(){return this._isLocked},set:function(S){this._isLocked=S},enumerable:!1,configurable:!0}),A.prototype.update=function(S){this._isLocked||(this.boundingBox._update(S),this.boundingSphere._update(S))},A.prototype.centerOn=function(S,g){var l=A.TmpVector3[0].copyFrom(S).subtractInPlace(g),h=A.TmpVector3[1].copyFrom(S).addInPlace(g);return this.boundingBox.reConstruct(l,h,this.boundingBox.getWorldMatrix()),this.boundingSphere.reConstruct(l,h,this.boundingBox.getWorldMatrix()),this},A.prototype.scale=function(S){return this.boundingBox.scale(S),this.boundingSphere.scale(S),this},A.prototype.isInFrustum=function(S,g){return g===void 0&&(g=C.a.MESHES_CULLINGSTRATEGY_STANDARD),!(g!==C.a.MESHES_CULLINGSTRATEGY_OPTIMISTIC_INCLUSION&&g!==C.a.MESHES_CULLINGSTRATEGY_OPTIMISTIC_INCLUSION_THEN_BSPHERE_ONLY||!this.boundingSphere.isCenterInFrustum(S))||!!this.boundingSphere.isInFrustum(S)&&(!(g!==C.a.MESHES_CULLINGSTRATEGY_BOUNDINGSPHERE_ONLY&&g!==C.a.MESHES_CULLINGSTRATEGY_OPTIMISTIC_INCLUSION_THEN_BSPHERE_ONLY)||this.boundingBox.isInFrustum(S))},Object.defineProperty(A.prototype,"diagonalLength",{get:function(){var S=this.boundingBox;return S.maximumWorld.subtractToRef(S.minimumWorld,A.TmpVector3[0]).length()},enumerable:!1,configurable:!0}),A.prototype.isCompletelyInFrustum=function(S){return this.boundingBox.isCompletelyInFrustum(S)},A.prototype._checkCollision=function(S){return S._canDoCollision(this.boundingSphere.centerWorld,this.boundingSphere.radiusWorld,this.boundingBox.minimumWorld,this.boundingBox.maximumWorld)},A.prototype.intersectsPoint=function(S){return!!this.boundingSphere.centerWorld&&!!this.boundingSphere.intersectsPoint(S)&&!!this.boundingBox.intersectsPoint(S)},A.prototype.intersects=function(S,g){if(!M.a.Intersects(this.boundingSphere,S.boundingSphere)||!u.a.Intersects(this.boundingBox,S.boundingBox))return!1;if(!g)return!0;var l=this.boundingBox,h=S.boundingBox;return!!c(l.directions[0],l,h)&&!!c(l.directions[1],l,h)&&!!c(l.directions[2],l,h)&&!!c(h.directions[0],l,h)&&!!c(h.directions[1],l,h)&&!!c(h.directions[2],l,h)&&!!c(_.e.Cross(l.directions[0],h.directions[0]),l,h)&&!!c(_.e.Cross(l.directions[0],h.directions[1]),l,h)&&!!c(_.e.Cross(l.directions[0],h.directions[2]),l,h)&&!!c(_.e.Cross(l.directions[1],h.directions[0]),l,h)&&!!c(_.e.Cross(l.directions[1],h.directions[1]),l,h)&&!!c(_.e.Cross(l.directions[1],h.directions[2]),l,h)&&!!c(_.e.Cross(l.directions[2],h.directions[0]),l,h)&&!!c(_.e.Cross(l.directions[2],h.directions[1]),l,h)&&!!c(_.e.Cross(l.directions[2],h.directions[2]),l,h)},A.TmpVector3=U.a.BuildArray(2,_.e.Zero),A}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.BuildArray=function(C,u){for(var M=[],R=0;R<C;++R)M.push(u());return M},_}()},function(Me,y,f){f.d(y,"a",function(){return u});var U=f(0),_=f(7),C=f(16);C.a.CreateSphere=function(M){for(var R=M.segments||32,x=M.diameterX||M.diameter||1,m=M.diameterY||M.diameter||1,c=M.diameterZ||M.diameter||1,T=M.arc&&(M.arc<=0||M.arc>1)?1:M.arc||1,A=M.slice&&M.slice<=0?1:M.slice||1,S=M.sideOrientation===0?0:M.sideOrientation||C.a.DEFAULTSIDE,g=!!M.dedupTopBottomIndices,l=new U.e(x/2,m/2,c/2),h=2+R,v=2*h,E=[],D=[],w=[],N=[],I=0;I<=h;I++){for(var V=I/h,X=V*Math.PI*A,j=0;j<=v;j++){var ne=j/v,te=ne*Math.PI*2*T,de=U.a.RotationZ(-X),pe=U.a.RotationY(te),ae=U.e.TransformCoordinates(U.e.Up(),de),ee=U.e.TransformCoordinates(ae,pe),K=ee.multiply(l),$=ee.divide(l).normalize();D.push(K.x,K.y,K.z),w.push($.x,$.y,$.z),N.push(ne,V)}if(I>0)for(var L=D.length/3,G=L-2*(v+1);G+v+2<L;G++)g?(I>1&&(E.push(G),E.push(G+1),E.push(G+v+1)),(I<h||A<1)&&(E.push(G+v+1),E.push(G+1),E.push(G+v+2))):(E.push(G),E.push(G+1),E.push(G+v+1),E.push(G+v+1),E.push(G+1),E.push(G+v+2))}C.a._ComputeSides(S,D,E,w,N,M.frontUVs,M.backUVs);var Q=new C.a;return Q.indices=E,Q.positions=D,Q.normals=w,Q.uvs=N,Q},_.a.CreateSphere=function(M,R,x,m,c,T){var A={segments:R,diameterX:x,diameterY:x,diameterZ:x,sideOrientation:T,updatable:c};return u.CreateSphere(M,A,m)};var u=function(){function M(){}return M.CreateSphere=function(R,x,m){m===void 0&&(m=null);var c=new _.a(R,m);return x.sideOrientation=_.a._GetDefaultSideOrientation(x.sideOrientation),c._originalBuilderSideOrientation=x.sideOrientation,C.a.CreateSphere(x).applyToMesh(c,x.updatable),c},M}()},function(Me,y,f){f.d(y,"a",function(){return x});var U=f(1),_=f(3),C=f(6),u=f(0),M=f(29),R=f(23),x=function(m){function c(T,A,S){A===void 0&&(A=null),S===void 0&&(S=!0);var g=m.call(this,T,A)||this;return g._forward=new u.e(0,0,1),g._forwardInverted=new u.e(0,0,-1),g._up=new u.e(0,1,0),g._right=new u.e(1,0,0),g._rightInverted=new u.e(-1,0,0),g._position=u.e.Zero(),g._rotation=u.e.Zero(),g._rotationQuaternion=null,g._scaling=u.e.One(),g._isDirty=!1,g._transformToBoneReferal=null,g._isAbsoluteSynced=!1,g._billboardMode=c.BILLBOARDMODE_NONE,g._preserveParentRotationForBillboard=!1,g.scalingDeterminant=1,g._infiniteDistance=!1,g.ignoreNonUniformScaling=!1,g.reIntegrateRotationIntoRotationQuaternion=!1,g._poseMatrix=null,g._localMatrix=u.a.Zero(),g._usePivotMatrix=!1,g._absolutePosition=u.e.Zero(),g._absoluteScaling=u.e.Zero(),g._absoluteRotationQuaternion=u.b.Identity(),g._pivotMatrix=u.a.Identity(),g._postMultiplyPivotMatrix=!1,g._isWorldMatrixFrozen=!1,g._indexInSceneTransformNodesArray=-1,g.onAfterWorldMatrixUpdateObservable=new C.c,g._nonUniformScaling=!1,S&&g.getScene().addTransformNode(g),g}return Object(U.d)(c,m),Object.defineProperty(c.prototype,"billboardMode",{get:function(){return this._billboardMode},set:function(T){this._billboardMode!==T&&(this._billboardMode=T)},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"preserveParentRotationForBillboard",{get:function(){return this._preserveParentRotationForBillboard},set:function(T){T!==this._preserveParentRotationForBillboard&&(this._preserveParentRotationForBillboard=T)},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"infiniteDistance",{get:function(){return this._infiniteDistance},set:function(T){this._infiniteDistance!==T&&(this._infiniteDistance=T)},enumerable:!1,configurable:!0}),c.prototype.getClassName=function(){return"TransformNode"},Object.defineProperty(c.prototype,"position",{get:function(){return this._position},set:function(T){this._position=T,this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"rotation",{get:function(){return this._rotation},set:function(T){this._rotation=T,this._rotationQuaternion=null,this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"scaling",{get:function(){return this._scaling},set:function(T){this._scaling=T,this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"rotationQuaternion",{get:function(){return this._rotationQuaternion},set:function(T){this._rotationQuaternion=T,T&&this._rotation.setAll(0),this._isDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"forward",{get:function(){return u.e.Normalize(u.e.TransformNormal(this.getScene().useRightHandedSystem?this._forwardInverted:this._forward,this.getWorldMatrix()))},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"up",{get:function(){return u.e.Normalize(u.e.TransformNormal(this._up,this.getWorldMatrix()))},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"right",{get:function(){return u.e.Normalize(u.e.TransformNormal(this.getScene().useRightHandedSystem?this._rightInverted:this._right,this.getWorldMatrix()))},enumerable:!1,configurable:!0}),c.prototype.updatePoseMatrix=function(T){return this._poseMatrix?(this._poseMatrix.copyFrom(T),this):(this._poseMatrix=T.clone(),this)},c.prototype.getPoseMatrix=function(){return this._poseMatrix||(this._poseMatrix=u.a.Identity()),this._poseMatrix},c.prototype._isSynchronized=function(){var T=this._cache;return this.billboardMode===T.billboardMode&&this.billboardMode===c.BILLBOARDMODE_NONE&&!T.pivotMatrixUpdated&&!this.infiniteDistance&&!this.position._isDirty&&!this.scaling._isDirty&&!(this._rotationQuaternion&&this._rotationQuaternion._isDirty||this.rotation._isDirty)},c.prototype._initCache=function(){m.prototype._initCache.call(this);var T=this._cache;T.localMatrixUpdated=!1,T.billboardMode=-1,T.infiniteDistance=!1},c.prototype.markAsDirty=function(T){return this._currentRenderId=Number.MAX_VALUE,this._isDirty=!0,this},Object.defineProperty(c.prototype,"absolutePosition",{get:function(){return this._absolutePosition},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"absoluteScaling",{get:function(){return this._syncAbsoluteScalingAndRotation(),this._absoluteScaling},enumerable:!1,configurable:!0}),Object.defineProperty(c.prototype,"absoluteRotationQuaternion",{get:function(){return this._syncAbsoluteScalingAndRotation(),this._absoluteRotationQuaternion},enumerable:!1,configurable:!0}),c.prototype.setPreTransformMatrix=function(T){return this.setPivotMatrix(T,!1)},c.prototype.setPivotMatrix=function(T,A){return A===void 0&&(A=!0),this._pivotMatrix.copyFrom(T),this._usePivotMatrix=!this._pivotMatrix.isIdentity(),this._cache.pivotMatrixUpdated=!0,this._postMultiplyPivotMatrix=A,this._postMultiplyPivotMatrix&&(this._pivotMatrixInverse?this._pivotMatrix.invertToRef(this._pivotMatrixInverse):this._pivotMatrixInverse=u.a.Invert(this._pivotMatrix)),this},c.prototype.getPivotMatrix=function(){return this._pivotMatrix},c.prototype.instantiateHierarchy=function(T,A,S){T===void 0&&(T=null);var g=this.clone("Clone of "+(this.name||this.id),T||this.parent,!0);g&&S&&S(this,g);for(var l=0,h=this.getChildTransformNodes(!0);l<h.length;l++)h[l].instantiateHierarchy(g,A,S);return g},c.prototype.freezeWorldMatrix=function(T){return T===void 0&&(T=null),T?this._worldMatrix=T:(this._isWorldMatrixFrozen=!1,this.computeWorldMatrix(!0)),this._isDirty=!1,this._isWorldMatrixFrozen=!0,this},c.prototype.unfreezeWorldMatrix=function(){return this._isWorldMatrixFrozen=!1,this.computeWorldMatrix(!0),this},Object.defineProperty(c.prototype,"isWorldMatrixFrozen",{get:function(){return this._isWorldMatrixFrozen},enumerable:!1,configurable:!0}),c.prototype.getAbsolutePosition=function(){return this.computeWorldMatrix(),this._absolutePosition},c.prototype.setAbsolutePosition=function(T){if(!T)return this;var A,S,g;if(T.x===void 0){if(arguments.length<3)return this;A=arguments[0],S=arguments[1],g=arguments[2]}else A=T.x,S=T.y,g=T.z;if(this.parent){var l=u.c.Matrix[0];this.parent.getWorldMatrix().invertToRef(l),u.e.TransformCoordinatesFromFloatsToRef(A,S,g,l,this.position)}else this.position.x=A,this.position.y=S,this.position.z=g;return this._absolutePosition.copyFrom(T),this},c.prototype.setPositionWithLocalVector=function(T){return this.computeWorldMatrix(),this.position=u.e.TransformNormal(T,this._localMatrix),this},c.prototype.getPositionExpressedInLocalSpace=function(){this.computeWorldMatrix();var T=u.c.Matrix[0];return this._localMatrix.invertToRef(T),u.e.TransformNormal(this.position,T)},c.prototype.locallyTranslate=function(T){return this.computeWorldMatrix(!0),this.position=u.e.TransformCoordinates(T,this._localMatrix),this},c.prototype.lookAt=function(T,A,S,g,l){A===void 0&&(A=0),S===void 0&&(S=0),g===void 0&&(g=0),l===void 0&&(l=R.c.LOCAL);var h=c._lookAtVectorCache,v=l===R.c.LOCAL?this.position:this.getAbsolutePosition();if(T.subtractToRef(v,h),this.setDirection(h,A,S,g),l===R.c.WORLD&&this.parent)if(this.rotationQuaternion){var E=u.c.Matrix[0];this.rotationQuaternion.toRotationMatrix(E);var D=u.c.Matrix[1];this.parent.getWorldMatrix().getRotationMatrixToRef(D),D.invert(),E.multiplyToRef(D,E),this.rotationQuaternion.fromRotationMatrix(E)}else{var w=u.c.Quaternion[0];u.b.FromEulerVectorToRef(this.rotation,w),E=u.c.Matrix[0],w.toRotationMatrix(E),D=u.c.Matrix[1],this.parent.getWorldMatrix().getRotationMatrixToRef(D),D.invert(),E.multiplyToRef(D,E),w.fromRotationMatrix(E),w.toEulerAnglesToRef(this.rotation)}return this},c.prototype.getDirection=function(T){var A=u.e.Zero();return this.getDirectionToRef(T,A),A},c.prototype.getDirectionToRef=function(T,A){return u.e.TransformNormalToRef(T,this.getWorldMatrix(),A),this},c.prototype.setDirection=function(T,A,S,g){A===void 0&&(A=0),S===void 0&&(S=0),g===void 0&&(g=0);var l=-Math.atan2(T.z,T.x)+Math.PI/2,h=Math.sqrt(T.x*T.x+T.z*T.z),v=-Math.atan2(T.y,h);return this.rotationQuaternion?u.b.RotationYawPitchRollToRef(l+A,v+S,g,this.rotationQuaternion):(this.rotation.x=v+S,this.rotation.y=l+A,this.rotation.z=g),this},c.prototype.setPivotPoint=function(T,A){A===void 0&&(A=R.c.LOCAL),this.getScene().getRenderId()==0&&this.computeWorldMatrix(!0);var S=this.getWorldMatrix();if(A==R.c.WORLD){var g=u.c.Matrix[0];S.invertToRef(g),T=u.e.TransformCoordinates(T,g)}return this.setPivotMatrix(u.a.Translation(-T.x,-T.y,-T.z),!0)},c.prototype.getPivotPoint=function(){var T=u.e.Zero();return this.getPivotPointToRef(T),T},c.prototype.getPivotPointToRef=function(T){return T.x=-this._pivotMatrix.m[12],T.y=-this._pivotMatrix.m[13],T.z=-this._pivotMatrix.m[14],this},c.prototype.getAbsolutePivotPoint=function(){var T=u.e.Zero();return this.getAbsolutePivotPointToRef(T),T},c.prototype.getAbsolutePivotPointToRef=function(T){return this.getPivotPointToRef(T),u.e.TransformCoordinatesToRef(T,this.getWorldMatrix(),T),this},c.prototype.setParent=function(T){if(!T&&!this.parent)return this;var A=u.c.Quaternion[0],S=u.c.Vector3[0],g=u.c.Vector3[1];if(T){var l=u.c.Matrix[0],h=u.c.Matrix[1];this.computeWorldMatrix(!0),T.computeWorldMatrix(!0),T.getWorldMatrix().invertToRef(h),this.getWorldMatrix().multiplyToRef(h,l),l.decompose(g,A,S)}else this.computeWorldMatrix(!0),this.getWorldMatrix().decompose(g,A,S);return this.rotationQuaternion?this.rotationQuaternion.copyFrom(A):A.toEulerAnglesToRef(this.rotation),this.scaling.copyFrom(g),this.position.copyFrom(S),this.parent=T,this},Object.defineProperty(c.prototype,"nonUniformScaling",{get:function(){return this._nonUniformScaling},enumerable:!1,configurable:!0}),c.prototype._updateNonUniformScalingState=function(T){return this._nonUniformScaling!==T&&(this._nonUniformScaling=T,!0)},c.prototype.attachToBone=function(T,A){return this._transformToBoneReferal=A,this.parent=T,T.getSkeleton().prepare(),T.getWorldMatrix().determinant()<0&&(this.scalingDeterminant*=-1),this},c.prototype.detachFromBone=function(){return this.parent?(this.parent.getWorldMatrix().determinant()<0&&(this.scalingDeterminant*=-1),this._transformToBoneReferal=null,this.parent=null,this):this},c.prototype.rotate=function(T,A,S){var g;if(T.normalize(),this.rotationQuaternion||(this.rotationQuaternion=this.rotation.toQuaternion(),this.rotation.setAll(0)),S&&S!==R.c.LOCAL){if(this.parent){var l=u.c.Matrix[0];this.parent.getWorldMatrix().invertToRef(l),T=u.e.TransformNormal(T,l)}(g=u.b.RotationAxisToRef(T,A,c._rotationAxisCache)).multiplyToRef(this.rotationQuaternion,this.rotationQuaternion)}else g=u.b.RotationAxisToRef(T,A,c._rotationAxisCache),this.rotationQuaternion.multiplyToRef(g,this.rotationQuaternion);return this},c.prototype.rotateAround=function(T,A,S){A.normalize(),this.rotationQuaternion||(this.rotationQuaternion=u.b.RotationYawPitchRoll(this.rotation.y,this.rotation.x,this.rotation.z),this.rotation.setAll(0));var g=u.c.Vector3[0],l=u.c.Vector3[1],h=u.c.Vector3[2],v=u.c.Quaternion[0],E=u.c.Matrix[0],D=u.c.Matrix[1],w=u.c.Matrix[2],N=u.c.Matrix[3];return T.subtractToRef(this.position,g),u.a.TranslationToRef(g.x,g.y,g.z,E),u.a.TranslationToRef(-g.x,-g.y,-g.z,D),u.a.RotationAxisToRef(A,S,w),D.multiplyToRef(w,N),N.multiplyToRef(E,N),N.decompose(l,v,h),this.position.addInPlace(h),v.multiplyToRef(this.rotationQuaternion,this.rotationQuaternion),this},c.prototype.translate=function(T,A,S){var g=T.scale(A);if(S&&S!==R.c.LOCAL)this.setAbsolutePosition(this.getAbsolutePosition().add(g));else{var l=this.getPositionExpressedInLocalSpace().add(g);this.setPositionWithLocalVector(l)}return this},c.prototype.addRotation=function(T,A,S){var g;this.rotationQuaternion?g=this.rotationQuaternion:(g=u.c.Quaternion[1],u.b.RotationYawPitchRollToRef(this.rotation.y,this.rotation.x,this.rotation.z,g));var l=u.c.Quaternion[0];return u.b.RotationYawPitchRollToRef(A,T,S,l),g.multiplyInPlace(l),this.rotationQuaternion||g.toEulerAnglesToRef(this.rotation),this},c.prototype._getEffectiveParent=function(){return this.parent},c.prototype.computeWorldMatrix=function(T){if(this._isWorldMatrixFrozen&&!this._isDirty)return this._worldMatrix;var A=this.getScene().getRenderId();if(!this._isDirty&&!T&&this.isSynchronized())return this._currentRenderId=A,this._worldMatrix;var S=this.getScene().activeCamera,g=(this._billboardMode&c.BILLBOARDMODE_USE_POSITION)!=0,l=this._billboardMode!==c.BILLBOARDMODE_NONE&&!this.preserveParentRotationForBillboard;l&&S&&g&&(this.lookAt(S.position),(this.billboardMode&c.BILLBOARDMODE_X)!==c.BILLBOARDMODE_X&&(this.rotation.x=0),(this.billboardMode&c.BILLBOARDMODE_Y)!==c.BILLBOARDMODE_Y&&(this.rotation.y=0),(this.billboardMode&c.BILLBOARDMODE_Z)!==c.BILLBOARDMODE_Z&&(this.rotation.z=0)),this._updateCache();var h=this._cache;h.pivotMatrixUpdated=!1,h.billboardMode=this.billboardMode,h.infiniteDistance=this.infiniteDistance,this._currentRenderId=A,this._childUpdateId++,this._isDirty=!1,this._position._isDirty=!1,this._rotation._isDirty=!1,this._scaling._isDirty=!1;var v,E=this._getEffectiveParent(),D=c._TmpScaling,w=this._position;if(this._infiniteDistance&&!this.parent&&S){var N=S.getWorldMatrix(),I=new u.e(N.m[12],N.m[13],N.m[14]);(w=c._TmpTranslation).copyFromFloats(this._position.x+I.x,this._position.y+I.y,this._position.z+I.z)}if(D.copyFromFloats(this._scaling.x*this.scalingDeterminant,this._scaling.y*this.scalingDeterminant,this._scaling.z*this.scalingDeterminant),this._rotationQuaternion?(this._rotationQuaternion._isDirty=!1,v=this._rotationQuaternion,this.reIntegrateRotationIntoRotationQuaternion&&this.rotation.lengthSquared()&&(this._rotationQuaternion.multiplyInPlace(u.b.RotationYawPitchRoll(this._rotation.y,this._rotation.x,this._rotation.z)),this._rotation.copyFromFloats(0,0,0))):(v=c._TmpRotation,u.b.RotationYawPitchRollToRef(this._rotation.y,this._rotation.x,this._rotation.z,v)),this._usePivotMatrix){var V=u.c.Matrix[1];u.a.ScalingToRef(D.x,D.y,D.z,V);var X=u.c.Matrix[0];v.toRotationMatrix(X),this._pivotMatrix.multiplyToRef(V,u.c.Matrix[4]),u.c.Matrix[4].multiplyToRef(X,this._localMatrix),this._postMultiplyPivotMatrix&&this._localMatrix.multiplyToRef(this._pivotMatrixInverse,this._localMatrix),this._localMatrix.addTranslationFromFloats(w.x,w.y,w.z)}else u.a.ComposeToRef(D,v,w,this._localMatrix);if(E&&E.getWorldMatrix){if(T&&E.computeWorldMatrix(),l){this._transformToBoneReferal?E.getWorldMatrix().multiplyToRef(this._transformToBoneReferal.getWorldMatrix(),u.c.Matrix[7]):u.c.Matrix[7].copyFrom(E.getWorldMatrix());var j=u.c.Vector3[5],ne=u.c.Vector3[6];u.c.Matrix[7].decompose(ne,void 0,j),u.a.ScalingToRef(ne.x,ne.y,ne.z,u.c.Matrix[7]),u.c.Matrix[7].setTranslation(j),this._localMatrix.multiplyToRef(u.c.Matrix[7],this._worldMatrix)}else this._transformToBoneReferal?(this._localMatrix.multiplyToRef(E.getWorldMatrix(),u.c.Matrix[6]),u.c.Matrix[6].multiplyToRef(this._transformToBoneReferal.getWorldMatrix(),this._worldMatrix)):this._localMatrix.multiplyToRef(E.getWorldMatrix(),this._worldMatrix);this._markSyncedWithParent()}else this._worldMatrix.copyFrom(this._localMatrix);if(l&&S&&this.billboardMode&&!g){var te=u.c.Vector3[0];if(this._worldMatrix.getTranslationToRef(te),u.c.Matrix[1].copyFrom(S.getViewMatrix()),u.c.Matrix[1].setTranslationFromFloats(0,0,0),u.c.Matrix[1].invertToRef(u.c.Matrix[0]),(this.billboardMode&c.BILLBOARDMODE_ALL)!==c.BILLBOARDMODE_ALL){u.c.Matrix[0].decompose(void 0,u.c.Quaternion[0],void 0);var de=u.c.Vector3[1];u.c.Quaternion[0].toEulerAnglesToRef(de),(this.billboardMode&c.BILLBOARDMODE_X)!==c.BILLBOARDMODE_X&&(de.x=0),(this.billboardMode&c.BILLBOARDMODE_Y)!==c.BILLBOARDMODE_Y&&(de.y=0),(this.billboardMode&c.BILLBOARDMODE_Z)!==c.BILLBOARDMODE_Z&&(de.z=0),u.a.RotationYawPitchRollToRef(de.y,de.x,de.z,u.c.Matrix[0])}this._worldMatrix.setTranslationFromFloats(0,0,0),this._worldMatrix.multiplyToRef(u.c.Matrix[0],this._worldMatrix),this._worldMatrix.setTranslation(u.c.Vector3[0])}return this.ignoreNonUniformScaling?this._updateNonUniformScalingState(!1):this._scaling.isNonUniformWithinEpsilon(1e-6)?this._updateNonUniformScalingState(!0):E&&E._nonUniformScaling?this._updateNonUniformScalingState(E._nonUniformScaling):this._updateNonUniformScalingState(!1),this._afterComputeWorldMatrix(),this._absolutePosition.copyFromFloats(this._worldMatrix.m[12],this._worldMatrix.m[13],this._worldMatrix.m[14]),this._isAbsoluteSynced=!1,this.onAfterWorldMatrixUpdateObservable.notifyObservers(this),this._poseMatrix||(this._poseMatrix=u.a.Invert(this._worldMatrix)),this._worldMatrixDeterminantIsDirty=!0,this._worldMatrix},c.prototype.resetLocalMatrix=function(T){if(T===void 0&&(T=!0),this.computeWorldMatrix(),T)for(var A=this.getChildren(),S=0;S<A.length;++S){var g=A[S];if(g){g.computeWorldMatrix();var l=u.c.Matrix[0];g._localMatrix.multiplyToRef(this._localMatrix,l);var h=u.c.Quaternion[0];l.decompose(g.scaling,h,g.position),g.rotationQuaternion?g.rotationQuaternion=h:h.toEulerAnglesToRef(g.rotation)}}this.scaling.copyFromFloats(1,1,1),this.position.copyFromFloats(0,0,0),this.rotation.copyFromFloats(0,0,0),this.rotationQuaternion&&(this.rotationQuaternion=u.b.Identity()),this._worldMatrix=u.a.Identity()},c.prototype._afterComputeWorldMatrix=function(){},c.prototype.registerAfterWorldMatrixUpdate=function(T){return this.onAfterWorldMatrixUpdateObservable.add(T),this},c.prototype.unregisterAfterWorldMatrixUpdate=function(T){return this.onAfterWorldMatrixUpdateObservable.removeCallback(T),this},c.prototype.getPositionInCameraSpace=function(T){return T===void 0&&(T=null),T||(T=this.getScene().activeCamera),u.e.TransformCoordinates(this.getAbsolutePosition(),T.getViewMatrix())},c.prototype.getDistanceToCamera=function(T){return T===void 0&&(T=null),T||(T=this.getScene().activeCamera),this.getAbsolutePosition().subtract(T.globalPosition).length()},c.prototype.clone=function(T,A,S){var g=this,l=_.a.Clone(function(){return new c(T,g.getScene())},this);if(l.name=T,l.id=T,A&&(l.parent=A),!S)for(var h=this.getDescendants(!0),v=0;v<h.length;v++){var E=h[v];E.clone&&E.clone(T+"."+E.name,l)}return l},c.prototype.serialize=function(T){var A=_.a.Serialize(this,T);return A.type=this.getClassName(),this.parent&&(A.parentId=this.parent.id),A.localMatrix=this.getPivotMatrix().asArray(),A.isEnabled=this.isEnabled(),this.parent&&(A.parentId=this.parent.id),A},c.Parse=function(T,A,S){var g=_.a.Parse(function(){return new c(T.name,A)},T,A,S);return T.localMatrix?g.setPreTransformMatrix(u.a.FromArray(T.localMatrix)):T.pivotMatrix&&g.setPivotMatrix(u.a.FromArray(T.pivotMatrix)),g.setEnabled(T.isEnabled),T.parentId&&(g._waitingParentId=T.parentId),g},c.prototype.getChildTransformNodes=function(T,A){var S=[];return this._getDescendants(S,T,function(g){return(!A||A(g))&&g instanceof c}),S},c.prototype.dispose=function(T,A){if(A===void 0&&(A=!1),this.getScene().stopAnimation(this),this.getScene().removeTransformNode(this),this.onAfterWorldMatrixUpdateObservable.clear(),T)for(var S=0,g=this.getChildTransformNodes(!0);S<g.length;S++){var l=g[S];l.parent=null,l.computeWorldMatrix(!0)}m.prototype.dispose.call(this,T,A)},c.prototype.normalizeToUnitCube=function(T,A,S){T===void 0&&(T=!0),A===void 0&&(A=!1);var g=null,l=null;A&&(this.rotationQuaternion?(l=this.rotationQuaternion.clone(),this.rotationQuaternion.copyFromFloats(0,0,0,1)):this.rotation&&(g=this.rotation.clone(),this.rotation.copyFromFloats(0,0,0)));var h=this.getHierarchyBoundingVectors(T,S),v=h.max.subtract(h.min),E=Math.max(v.x,v.y,v.z);if(E===0)return this;var D=1/E;return this.scaling.scaleInPlace(D),A&&(this.rotationQuaternion&&l?this.rotationQuaternion.copyFrom(l):this.rotation&&g&&this.rotation.copyFrom(g)),this},c.prototype._syncAbsoluteScalingAndRotation=function(){this._isAbsoluteSynced||(this._worldMatrix.decompose(this._absoluteScaling,this._absoluteRotationQuaternion),this._isAbsoluteSynced=!0)},c.BILLBOARDMODE_NONE=0,c.BILLBOARDMODE_X=1,c.BILLBOARDMODE_Y=2,c.BILLBOARDMODE_Z=4,c.BILLBOARDMODE_ALL=7,c.BILLBOARDMODE_USE_POSITION=128,c._TmpRotation=u.b.Zero(),c._TmpScaling=u.e.Zero(),c._TmpTranslation=u.e.Zero(),c._lookAtVectorCache=new u.e(0,0,0),c._rotationAxisCache=new u.b,Object(U.c)([Object(_.o)("position")],c.prototype,"_position",void 0),Object(U.c)([Object(_.o)("rotation")],c.prototype,"_rotation",void 0),Object(U.c)([Object(_.l)("rotationQuaternion")],c.prototype,"_rotationQuaternion",void 0),Object(U.c)([Object(_.o)("scaling")],c.prototype,"_scaling",void 0),Object(U.c)([Object(_.c)("billboardMode")],c.prototype,"_billboardMode",void 0),Object(U.c)([Object(_.c)()],c.prototype,"scalingDeterminant",void 0),Object(U.c)([Object(_.c)("infiniteDistance")],c.prototype,"_infiniteDistance",void 0),Object(U.c)([Object(_.c)()],c.prototype,"ignoreNonUniformScaling",void 0),Object(U.c)([Object(_.c)()],c.prototype,"reIntegrateRotationIntoRotationQuaternion",void 0),c}(M.a)},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(C,u,M,R,x,m){this.source=C,this.pointerX=u,this.pointerY=M,this.meshUnderPointer=R,this.sourceEvent=x,this.additionalData=m}return _.CreateNew=function(C,u,M){var R=C.getScene();return new _(C,R.pointerX,R.pointerY,R.meshUnderPointer||C,u,M)},_.CreateNewFromSprite=function(C,u,M,R){return new _(C,u.pointerX,u.pointerY,u.meshUnderPointer,M,R)},_.CreateNewFromScene=function(C,u){return new _(null,C.pointerX,C.pointerY,C.meshUnderPointer,u)},_.CreateNewFromPrimitive=function(C,u,M,R){return new _(C,u.x,u.y,null,M,R)},_}()},function(Me,y,f){f.d(y,"a",function(){return m});var U=f(1),_=f(3),C=f(0),u=f(9),M=f(29),R=f(85),x=f(11),m=function(c){function T(A,S){var g=c.call(this,A,S)||this;return g.diffuse=new u.a(1,1,1),g.specular=new u.a(1,1,1),g.falloffType=T.FALLOFF_DEFAULT,g.intensity=1,g._range=Number.MAX_VALUE,g._inverseSquaredRange=0,g._photometricScale=1,g._intensityMode=T.INTENSITYMODE_AUTOMATIC,g._radius=1e-5,g.renderPriority=0,g._shadowEnabled=!0,g._excludeWithLayerMask=0,g._includeOnlyWithLayerMask=0,g._lightmapMode=0,g._excludedMeshesIds=new Array,g._includedOnlyMeshesIds=new Array,g._isLight=!0,g.getScene().addLight(g),g._uniformBuffer=new R.a(g.getScene().getEngine()),g._buildUniformLayout(),g.includedOnlyMeshes=new Array,g.excludedMeshes=new Array,g._resyncMeshes(),g}return Object(U.d)(T,c),Object.defineProperty(T.prototype,"range",{get:function(){return this._range},set:function(A){this._range=A,this._inverseSquaredRange=1/(this.range*this.range)},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"intensityMode",{get:function(){return this._intensityMode},set:function(A){this._intensityMode=A,this._computePhotometricScale()},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"radius",{get:function(){return this._radius},set:function(A){this._radius=A,this._computePhotometricScale()},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"shadowEnabled",{get:function(){return this._shadowEnabled},set:function(A){this._shadowEnabled!==A&&(this._shadowEnabled=A,this._markMeshesAsLightDirty())},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"includedOnlyMeshes",{get:function(){return this._includedOnlyMeshes},set:function(A){this._includedOnlyMeshes=A,this._hookArrayForIncludedOnly(A)},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"excludedMeshes",{get:function(){return this._excludedMeshes},set:function(A){this._excludedMeshes=A,this._hookArrayForExcluded(A)},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"excludeWithLayerMask",{get:function(){return this._excludeWithLayerMask},set:function(A){this._excludeWithLayerMask=A,this._resyncMeshes()},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"includeOnlyWithLayerMask",{get:function(){return this._includeOnlyWithLayerMask},set:function(A){this._includeOnlyWithLayerMask=A,this._resyncMeshes()},enumerable:!1,configurable:!0}),Object.defineProperty(T.prototype,"lightmapMode",{get:function(){return this._lightmapMode},set:function(A){this._lightmapMode!==A&&(this._lightmapMode=A,this._markMeshesAsLightDirty())},enumerable:!1,configurable:!0}),T.prototype.transferTexturesToEffect=function(A,S){return this},T.prototype._bindLight=function(A,S,g,l,h){h===void 0&&(h=!1);var v=A.toString(),E=!1;if(!h||!this._uniformBuffer._alreadyBound){if(this._uniformBuffer.bindToEffect(g,"Light"+v),this._renderId!==S.getRenderId()||!this._uniformBuffer.useUbo){this._renderId=S.getRenderId();var D=this.getScaledIntensity();this.transferToEffect(g,v),this.diffuse.scaleToRef(D,u.c.Color3[0]),this._uniformBuffer.updateColor4("vLightDiffuse",u.c.Color3[0],this.range,v),l&&(this.specular.scaleToRef(D,u.c.Color3[1]),this._uniformBuffer.updateColor4("vLightSpecular",u.c.Color3[1],this.radius,v)),E=!0}if(this.transferTexturesToEffect(g,v),S.shadowsEnabled&&this.shadowEnabled){var w=this.getShadowGenerator();w&&(w.bindShadowLight(v,g),E=!0)}E&&this._uniformBuffer.update()}},T.prototype.getClassName=function(){return"Light"},T.prototype.toString=function(A){var S="Name: "+this.name;if(S+=", type: "+["Point","Directional","Spot","Hemispheric"][this.getTypeID()],this.animations)for(var g=0;g<this.animations.length;g++)S+=", animation[0]: "+this.animations[g].toString(A);return S},T.prototype._syncParentEnabledState=function(){c.prototype._syncParentEnabledState.call(this),this.isDisposed()||this._resyncMeshes()},T.prototype.setEnabled=function(A){c.prototype.setEnabled.call(this,A),this._resyncMeshes()},T.prototype.getShadowGenerator=function(){return this._shadowGenerator},T.prototype.getAbsolutePosition=function(){return C.e.Zero()},T.prototype.canAffectMesh=function(A){return!A||!(this.includedOnlyMeshes&&this.includedOnlyMeshes.length>0&&this.includedOnlyMeshes.indexOf(A)===-1)&&!(this.excludedMeshes&&this.excludedMeshes.length>0&&this.excludedMeshes.indexOf(A)!==-1)&&(this.includeOnlyWithLayerMask===0||(this.includeOnlyWithLayerMask&A.layerMask)!=0)&&!(this.excludeWithLayerMask!==0&&this.excludeWithLayerMask&A.layerMask)},T.CompareLightsPriority=function(A,S){return A.shadowEnabled!==S.shadowEnabled?(S.shadowEnabled?1:0)-(A.shadowEnabled?1:0):S.renderPriority-A.renderPriority},T.prototype.dispose=function(A,S){S===void 0&&(S=!1),this._shadowGenerator&&(this._shadowGenerator.dispose(),this._shadowGenerator=null),this.getScene().stopAnimation(this);for(var g=0,l=this.getScene().meshes;g<l.length;g++)l[g]._removeLightSource(this,!0);this._uniformBuffer.dispose(),this.getScene().removeLight(this),c.prototype.dispose.call(this,A,S)},T.prototype.getTypeID=function(){return 0},T.prototype.getScaledIntensity=function(){return this._photometricScale*this.intensity},T.prototype.clone=function(A,S){S===void 0&&(S=null);var g=T.GetConstructorFromName(this.getTypeID(),A,this.getScene());if(!g)return null;var l=_.a.Clone(g,this);return S&&(l.parent=S),l.setEnabled(this.isEnabled()),l},T.prototype.serialize=function(){var A=_.a.Serialize(this);return A.type=this.getTypeID(),this.parent&&(A.parentId=this.parent.id),this.excludedMeshes.length>0&&(A.excludedMeshesIds=[],this.excludedMeshes.forEach(function(S){A.excludedMeshesIds.push(S.id)})),this.includedOnlyMeshes.length>0&&(A.includedOnlyMeshesIds=[],this.includedOnlyMeshes.forEach(function(S){A.includedOnlyMeshesIds.push(S.id)})),_.a.AppendSerializedAnimations(this,A),A.ranges=this.serializeAnimationRanges(),A},T.GetConstructorFromName=function(A,S,g){var l=M.a.Construct("Light_Type_"+A,S,g);return l||null},T.Parse=function(A,S){var g=T.GetConstructorFromName(A.type,A.name,S);if(!g)return null;var l=_.a.Parse(g,A,S);if(A.excludedMeshesIds&&(l._excludedMeshesIds=A.excludedMeshesIds),A.includedOnlyMeshesIds&&(l._includedOnlyMeshesIds=A.includedOnlyMeshesIds),A.parentId&&(l._waitingParentId=A.parentId),A.falloffType!==void 0&&(l.falloffType=A.falloffType),A.lightmapMode!==void 0&&(l.lightmapMode=A.lightmapMode),A.animations){for(var h=0;h<A.animations.length;h++){var v=A.animations[h],E=x.a.GetClass("BABYLON.Animation");E&&l.animations.push(E.Parse(v))}M.a.ParseAnimationRanges(l,A,S)}return A.autoAnimate&&S.beginAnimation(l,A.autoAnimateFrom,A.autoAnimateTo,A.autoAnimateLoop,A.autoAnimateSpeed||1),l},T.prototype._hookArrayForExcluded=function(A){var S=this,g=A.push;A.push=function(){for(var E=[],D=0;D<arguments.length;D++)E[D]=arguments[D];for(var w=g.apply(A,E),N=0,I=E;N<I.length;N++){var V=I[N];V._resyncLightSource(S)}return w};var l=A.splice;A.splice=function(E,D){for(var w=l.apply(A,[E,D]),N=0,I=w;N<I.length;N++)I[N]._resyncLightSource(S);return w};for(var h=0,v=A;h<v.length;h++)v[h]._resyncLightSource(this)},T.prototype._hookArrayForIncludedOnly=function(A){var S=this,g=A.push;A.push=function(){for(var h=[],v=0;v<arguments.length;v++)h[v]=arguments[v];var E=g.apply(A,h);return S._resyncMeshes(),E};var l=A.splice;A.splice=function(h,v){var E=l.apply(A,[h,v]);return S._resyncMeshes(),E},this._resyncMeshes()},T.prototype._resyncMeshes=function(){for(var A=0,S=this.getScene().meshes;A<S.length;A++)S[A]._resyncLightSource(this)},T.prototype._markMeshesAsLightDirty=function(){for(var A=0,S=this.getScene().meshes;A<S.length;A++){var g=S[A];g.lightSources.indexOf(this)!==-1&&g._markSubMeshesAsLightDirty()}},T.prototype._computePhotometricScale=function(){this._photometricScale=this._getPhotometricScale(),this.getScene().resetCachedMaterial()},T.prototype._getPhotometricScale=function(){var A=0,S=this.getTypeID(),g=this.intensityMode;switch(g===T.INTENSITYMODE_AUTOMATIC&&(g=S===T.LIGHTTYPEID_DIRECTIONALLIGHT?T.INTENSITYMODE_ILLUMINANCE:T.INTENSITYMODE_LUMINOUSINTENSITY),S){case T.LIGHTTYPEID_POINTLIGHT:case T.LIGHTTYPEID_SPOTLIGHT:switch(g){case T.INTENSITYMODE_LUMINOUSPOWER:A=1/(4*Math.PI);break;case T.INTENSITYMODE_LUMINOUSINTENSITY:A=1;break;case T.INTENSITYMODE_LUMINANCE:A=this.radius*this.radius}break;case T.LIGHTTYPEID_DIRECTIONALLIGHT:switch(g){case T.INTENSITYMODE_ILLUMINANCE:A=1;break;case T.INTENSITYMODE_LUMINANCE:var l=this.radius;l=Math.max(l,.001),A=2*Math.PI*(1-Math.cos(l))}break;case T.LIGHTTYPEID_HEMISPHERICLIGHT:A=1}return A},T.prototype._reorderLightsInScene=function(){var A=this.getScene();this._renderPriority!=0&&(A.requireLightSorting=!0),this.getScene().sortLightsByPriority()},T.FALLOFF_DEFAULT=0,T.FALLOFF_PHYSICAL=1,T.FALLOFF_GLTF=2,T.FALLOFF_STANDARD=3,T.LIGHTMAP_DEFAULT=0,T.LIGHTMAP_SPECULAR=1,T.LIGHTMAP_SHADOWSONLY=2,T.INTENSITYMODE_AUTOMATIC=0,T.INTENSITYMODE_LUMINOUSPOWER=1,T.INTENSITYMODE_LUMINOUSINTENSITY=2,T.INTENSITYMODE_ILLUMINANCE=3,T.INTENSITYMODE_LUMINANCE=4,T.LIGHTTYPEID_POINTLIGHT=0,T.LIGHTTYPEID_DIRECTIONALLIGHT=1,T.LIGHTTYPEID_SPOTLIGHT=2,T.LIGHTTYPEID_HEMISPHERICLIGHT=3,Object(U.c)([Object(_.e)()],T.prototype,"diffuse",void 0),Object(U.c)([Object(_.e)()],T.prototype,"specular",void 0),Object(U.c)([Object(_.c)()],T.prototype,"falloffType",void 0),Object(U.c)([Object(_.c)()],T.prototype,"intensity",void 0),Object(U.c)([Object(_.c)()],T.prototype,"range",null),Object(U.c)([Object(_.c)()],T.prototype,"intensityMode",null),Object(U.c)([Object(_.c)()],T.prototype,"radius",null),Object(U.c)([Object(_.c)()],T.prototype,"_renderPriority",void 0),Object(U.c)([Object(_.b)("_reorderLightsInScene")],T.prototype,"renderPriority",void 0),Object(U.c)([Object(_.c)("shadowEnabled")],T.prototype,"_shadowEnabled",void 0),Object(U.c)([Object(_.c)("excludeWithLayerMask")],T.prototype,"_excludeWithLayerMask",void 0),Object(U.c)([Object(_.c)("includeOnlyWithLayerMask")],T.prototype,"_includeOnlyWithLayerMask",void 0),Object(U.c)([Object(_.c)("lightmapMode")],T.prototype,"_lightmapMode",void 0),T}(M.a)},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){this._xhr=typeof _native<"u"&&_native.XMLHttpRequest?new _native.XMLHttpRequest:new XMLHttpRequest}return _.prototype._injectCustomRequestHeaders=function(){for(var C in _.CustomRequestHeaders){var u=_.CustomRequestHeaders[C];u&&this._xhr.setRequestHeader(C,u)}},Object.defineProperty(_.prototype,"onprogress",{get:function(){return this._xhr.onprogress},set:function(C){this._xhr.onprogress=C},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"readyState",{get:function(){return this._xhr.readyState},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"status",{get:function(){return this._xhr.status},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"statusText",{get:function(){return this._xhr.statusText},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"response",{get:function(){return this._xhr.response},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"responseURL",{get:function(){return this._xhr.responseURL},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"responseText",{get:function(){return this._xhr.responseText},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"responseType",{get:function(){return this._xhr.responseType},set:function(C){this._xhr.responseType=C},enumerable:!1,configurable:!0}),_.prototype.addEventListener=function(C,u,M){this._xhr.addEventListener(C,u,M)},_.prototype.removeEventListener=function(C,u,M){this._xhr.removeEventListener(C,u,M)},_.prototype.abort=function(){this._xhr.abort()},_.prototype.send=function(C){_.CustomRequestHeaders&&this._injectCustomRequestHeaders(),this._xhr.send(C)},_.prototype.open=function(C,u){for(var M=0,R=_.CustomRequestModifiers;M<R.length;M++)(0,R[M])(this._xhr,u);return u=(u=u.replace("file:http:","http:")).replace("file:https:","https:"),this._xhr.open(C,u,!0)},_.prototype.setRequestHeader=function(C,u){this._xhr.setRequestHeader(C,u)},_.prototype.getResponseHeader=function(C){return this._xhr.getResponseHeader(C)},_.CustomRequestHeaders={},_.CustomRequestModifiers=new Array,_}()},function(Me,y,f){f.d(y,"e",function(){return _}),f.d(y,"a",function(){return C}),f.d(y,"d",function(){return u}),f.d(y,"c",function(){return M}),f.d(y,"b",function(){return R});var U=f(1),_=function(){function x(m,c){this.type=m,this.jointData=c,c.nativeParams=c.nativeParams||{}}return Object.defineProperty(x.prototype,"physicsJoint",{get:function(){return this._physicsJoint},set:function(m){this._physicsJoint,this._physicsJoint=m},enumerable:!1,configurable:!0}),Object.defineProperty(x.prototype,"physicsPlugin",{set:function(m){this._physicsPlugin=m},enumerable:!1,configurable:!0}),x.prototype.executeNativeFunction=function(m){m(this._physicsPlugin.world,this._physicsJoint)},x.DistanceJoint=0,x.HingeJoint=1,x.BallAndSocketJoint=2,x.WheelJoint=3,x.SliderJoint=4,x.PrismaticJoint=5,x.UniversalJoint=6,x.Hinge2Joint=x.WheelJoint,x.PointToPointJoint=8,x.SpringJoint=9,x.LockJoint=10,x}(),C=function(x){function m(c){return x.call(this,_.DistanceJoint,c)||this}return 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U=f(0),_=f(7),C=f(36),u=f(18),M=function(){function R(x){var m=this;x===void 0&&(x=C.a.DefaultUtilityLayer),this.gizmoLayer=x,this._attachedMesh=null,this._attachedNode=null,this._scaleRatio=1,this._isHovered=!1,this._customMeshSet=!1,this._updateGizmoRotationToMatchAttachedMesh=!0,this.updateGizmoPositionToMatchAttachedMesh=!0,this.updateScale=!0,this._interactionsEnabled=!0,this._tempQuaternion=new U.b(0,0,0,1),this._tempVector=new U.e,this._tempVector2=new U.e,this._tempMatrix1=new U.a,this._tempMatrix2=new U.a,this._rightHandtoLeftHandMatrix=U.a.RotationY(Math.PI),this._rootMesh=new _.a("gizmoRootNode",x.utilityLayerScene),this._rootMesh.rotationQuaternion=U.b.Identity(),this._beforeRenderObserver=this.gizmoLayer.utilityLayerScene.onBeforeRenderObservable.add(function(){m._update()})}return Object.defineProperty(R.prototype,"scaleRatio",{get:function(){return 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T=this.gizmoLayer.utilityLayerScene.activeCamera,A=T.globalPosition;T.devicePosition&&(A=T.devicePosition),this._rootMesh.position.subtractToRef(A,this._tempVector);var S=this._tempVector.length()*this.scaleRatio;this._rootMesh.scaling.set(S,S,S),x._getWorldMatrixDeterminant()<0&&(this._rootMesh.scaling.y*=-1)}else this._rootMesh.scaling.setAll(this.scaleRatio)}},R.prototype._matrixChanged=function(){if(this._attachedNode){if(this._attachedNode._isCamera){var x,m,c=this._attachedNode;if(c.parent){var T=this._tempMatrix2;c.parent._worldMatrix.invertToRef(T),this._attachedNode._worldMatrix.multiplyToRef(T,this._tempMatrix1),x=this._tempMatrix1}else x=this._attachedNode._worldMatrix;if(c.getScene().useRightHandedSystem?(this._rightHandtoLeftHandMatrix.multiplyToRef(x,this._tempMatrix2),m=this._tempMatrix2):m=x,m.decompose(this._tempVector2,this._tempQuaternion,this._tempVector),this._attachedNode.getClassName()==="FreeCamera"||this._attachedNode.getClassName()==="FlyCamera"||this._attachedNode.getClassName()==="ArcFollowCamera"||this._attachedNode.getClassName()==="TargetCamera"||this._attachedNode.getClassName()==="TouchCamera"||this._attachedNode.getClassName()==="UniversalCamera"){var A=this._attachedNode;A.rotation=this._tempQuaternion.toEulerAngles(),A.rotationQuaternion&&A.rotationQuaternion.copyFrom(this._tempQuaternion)}c.position.copyFrom(this._tempVector)}else if(this._attachedNode._isMesh||this._attachedNode.getClassName()==="AbstractMesh"||this._attachedNode.getClassName()==="TransformNode"||this._attachedNode.getClassName()==="InstancedMesh"){var S=this._attachedNode;if(S.parent){T=this._tempMatrix1;var g=this._tempMatrix2;S.parent.getWorldMatrix().invertToRef(T),this._attachedNode.getWorldMatrix().multiplyToRef(T,g),g.decompose(S.scaling,this._tempQuaternion,S.position)}else this._attachedNode._worldMatrix.decompose(S.scaling,this._tempQuaternion,S.position);S.billboardMode||(S.rotationQuaternion?S.rotationQuaternion.copyFrom(this._tempQuaternion):S.rotation=this._tempQuaternion.toEulerAngles())}else if(this._attachedNode.getClassName()==="Bone"){var l=this._attachedNode,h=l.getParent();if(h){var v=this._tempMatrix1,E=this._tempMatrix2;h.getWorldMatrix().invertToRef(v),l.getWorldMatrix().multiplyToRef(v,E),l.getLocalMatrix().copyFrom(E)}else l.getLocalMatrix().copyFrom(l.getWorldMatrix());l.markAsDirty()}}},R.GizmoAxisPointerObserver=function(x,m){var c=!1;return x.utilityLayerScene.onPointerObservable.add(function(T){var A,S;if(T.pickInfo){if(T.type===u.a.POINTERMOVE){if(c)return;m.forEach(function(g){var l,h;if(g.colliderMeshes&&g.gizmoMeshes){var v=((l=g.colliderMeshes)===null||l===void 0?void 0:l.indexOf((h=T?.pickInfo)===null||h===void 0?void 0:h.pickedMesh))!=-1||g.active?g.hoverMaterial:g.material;g.gizmoMeshes.forEach(function(E){E.material=v,E.color&&(E.color=v.diffuseColor)})}})}T.type===u.a.POINTERDOWN&&m.has((A=T.pickInfo.pickedMesh)===null||A===void 0?void 0:A.parent)&&(c=!0,m.get((S=T.pickInfo.pickedMesh)===null||S===void 0?void 0:S.parent).active=!0,m.forEach(function(g){var l,h,v=((l=g.colliderMeshes)===null||l===void 0?void 0:l.indexOf((h=T?.pickInfo)===null||h===void 0?void 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v=this._getEngine();if(!v)return null;for(var E=v.getLoadedTexturesCache(),D=0;D<E.length;D++){var w=E[D];if(!(h!==void 0&&h!==w.invertY||w.url!==S||w.generateMipMaps!==!g||l&&l!==w.samplingMode))return w.incrementReferences(),w}return null},A.prototype._rebuild=function(){},A.prototype.clone=function(){return null},Object.defineProperty(A.prototype,"textureType",{get:function(){return this._texture&&this._texture.type!==void 0?this._texture.type:R.a.TEXTURETYPE_UNSIGNED_INT},enumerable:!1,configurable:!0}),Object.defineProperty(A.prototype,"textureFormat",{get:function(){return this._texture&&this._texture.format!==void 0?this._texture.format:R.a.TEXTUREFORMAT_RGBA},enumerable:!1,configurable:!0}),A.prototype._markAllSubMeshesAsTexturesDirty=function(){var S=this.getScene();S&&S.markAllMaterialsAsDirty(R.a.MATERIAL_TextureDirtyFlag)},A.prototype.readPixels=function(S,g,l){if(S===void 0&&(S=0),g===void 0&&(g=0),l===void 0&&(l=null),!this._texture)return null;var h=this.getSize(),v=h.width,E=h.height,D=this._getEngine();if(!D)return null;g!=0&&(v/=Math.pow(2,g),E/=Math.pow(2,g),v=Math.round(v),E=Math.round(E));try{return this._texture.isCube?D._readTexturePixels(this._texture,v,E,S,g,l):D._readTexturePixels(this._texture,v,E,-1,g,l)}catch{return null}},Object.defineProperty(A.prototype,"_lodTextureHigh",{get:function(){return this._texture?this._texture._lodTextureHigh:null},enumerable:!1,configurable:!0}),Object.defineProperty(A.prototype,"_lodTextureMid",{get:function(){return this._texture?this._texture._lodTextureMid:null},enumerable:!1,configurable:!0}),Object.defineProperty(A.prototype,"_lodTextureLow",{get:function(){return this._texture?this._texture._lodTextureLow:null},enumerable:!1,configurable:!0}),A.prototype.dispose=function(){if(this._scene){this._scene.stopAnimation&&this._scene.stopAnimation(this),this._scene._removePendingData(this);var S=this._scene.textures.indexOf(this);S>=0&&this._scene.textures.splice(S,1),this._scene.onTextureRemovedObservable.notifyObservers(this),this._scene=null}this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear(),T.prototype.dispose.call(this)},A.prototype.serialize=function(){if(!this.name)return null;var S=_.a.Serialize(this);return _.a.AppendSerializedAnimations(this,S),S},A.WhenAllReady=function(S,g){var l=S.length;if(l!==0)for(var h=0;h<S.length;h++){var v=S[h];if(v.isReady())--l==0&&g();else{var E=v.onLoadObservable;E&&E.addOnce(function(){--l==0&&g()})}}else g()},A._isScene=function(S){return S.getClassName()==="Scene"},A.DEFAULT_ANISOTROPIC_FILTERING_LEVEL=4,Object(U.c)([Object(_.c)()],A.prototype,"uniqueId",void 0),Object(U.c)([Object(_.c)()],A.prototype,"name",void 0),Object(U.c)([Object(_.c)()],A.prototype,"metadata",void 0),Object(U.c)([Object(_.c)("hasAlpha")],A.prototype,"_hasAlpha",void 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this.delayLoadState===R.a.DELAYLOADSTATE_NOTLOADED?(this.delayLoad(),!1):!!this._texture&&this._texture.isReady},T.prototype.delayLoad=function(){},T.prototype.getInternalTexture=function(){return this._texture},T.prototype.getSize=function(){if(this._texture){if(this._texture.width)return this._cachedSize.width=this._texture.width,this._cachedSize.height=this._texture.height,this._cachedSize;if(this._texture._size)return this._cachedSize.width=this._texture._size,this._cachedSize.height=this._texture._size,this._cachedSize}return this._cachedSize},T.prototype.getBaseSize=function(){return this.isReady()&&this._texture?this._texture._size?(this._cachedBaseSize.width=this._texture._size,this._cachedBaseSize.height=this._texture._size,this._cachedBaseSize):(this._cachedBaseSize.width=this._texture.baseWidth,this._cachedBaseSize.height=this._texture.baseHeight,this._cachedBaseSize):(this._cachedBaseSize.width=0,this._cachedBaseSize.height=0,this._cachedBaseSize)},T.prototype.updateSamplingMode=function(A){this._texture&&this._engine&&this._engine.updateTextureSamplingMode(A,this._texture)},T.prototype.releaseInternalTexture=function(){this._texture&&(this._texture.dispose(),this._texture=null)},T.prototype.dispose=function(){this._texture&&(this.releaseInternalTexture(),this._engine=null)},T}())},function(Me,y,f){f.d(y,"a",function(){return x});var U=f(0),_=f(9),C=f(7),u=f(16),M=f(20),R=f(23);u.a.CreateCylinder=function(m){var c=m.height||2,T=m.diameterTop===0?0:m.diameterTop||m.diameter||1,A=m.diameterBottom===0?0:m.diameterBottom||m.diameter||1;T=T||1e-5,A=A||1e-5;var S,g=m.tessellation||24,l=m.subdivisions||1,h=!!m.hasRings,v=!!m.enclose,E=m.cap===0?0:m.cap||C.a.CAP_ALL,D=m.arc&&(m.arc<=0||m.arc>1)?1:m.arc||1,w=m.sideOrientation===0?0:m.sideOrientation||u.a.DEFAULTSIDE,N=m.faceUV||new Array(3),I=m.faceColors,V=2+(1+(D!==1&&v?2:0))*(h?l:1);for(S=0;S<V;S++)I&&I[S]===void 0&&(I[S]=new _.b(1,1,1,1));for(S=0;S<V;S++)N&&N[S]===void 0&&(N[S]=new U.f(0,0,1,1));var X,j,ne,te,de,pe,ae=new Array,ee=new Array,K=new Array,$=new Array,L=new Array,G=2*Math.PI*D/g,Q=(A-T)/2/c,oe=U.e.Zero(),re=U.e.Zero(),Y=U.e.Zero(),k=U.e.Zero(),H=U.e.Zero(),Z=R.a.Y,W=1,q=1,he=0,ge=0;for(te=0;te<=l;te++)for(ne=((j=te/l)*(T-A)+A)/2,W=h&&te!==0&&te!==l?2:1,pe=0;pe<W;pe++){for(h&&(q+=pe),v&&(q+=2*pe),de=0;de<=g;de++)X=de*G,oe.x=Math.cos(-X)*ne,oe.y=-c/2+j*c,oe.z=Math.sin(-X)*ne,T===0&&te===l?(re.x=K[K.length-3*(g+1)],re.y=K[K.length-3*(g+1)+1],re.z=K[K.length-3*(g+1)+2]):(re.x=oe.x,re.z=oe.z,re.y=Math.sqrt(re.x*re.x+re.z*re.z)*Q,re.normalize()),de===0&&(Y.copyFrom(oe),k.copyFrom(re)),ee.push(oe.x,oe.y,oe.z),K.push(re.x,re.y,re.z),ge=h?he!==q?N[q].y:N[q].w:N[q].y+(N[q].w-N[q].y)*j,$.push(N[q].x+(N[q].z-N[q].x)*de/g,ge),I&&L.push(I[q].r,I[q].g,I[q].b,I[q].a);D!==1&&v&&(ee.push(oe.x,oe.y,oe.z),ee.push(0,oe.y,0),ee.push(0,oe.y,0),ee.push(Y.x,Y.y,Y.z),U.e.CrossToRef(Z,re,H),H.normalize(),K.push(H.x,H.y,H.z,H.x,H.y,H.z),U.e.CrossToRef(k,Z,H),H.normalize(),K.push(H.x,H.y,H.z,H.x,H.y,H.z),ge=h?he!==q?N[q+1].y:N[q+1].w:N[q+1].y+(N[q+1].w-N[q+1].y)*j,$.push(N[q+1].x,ge),$.push(N[q+1].z,ge),ge=h?he!==q?N[q+2].y:N[q+2].w:N[q+2].y+(N[q+2].w-N[q+2].y)*j,$.push(N[q+2].x,ge),$.push(N[q+2].z,ge),I&&(L.push(I[q+1].r,I[q+1].g,I[q+1].b,I[q+1].a),L.push(I[q+1].r,I[q+1].g,I[q+1].b,I[q+1].a),L.push(I[q+2].r,I[q+2].g,I[q+2].b,I[q+2].a),L.push(I[q+2].r,I[q+2].g,I[q+2].b,I[q+2].a))),he!==q&&(he=q)}var me=D!==1&&v?g+4:g;for(te=0,q=0;q<l;q++){var _e=0,be=0,Pe=0,ye=0;for(de=0;de<g;de++)_e=te*(me+1)+de,be=(te+1)*(me+1)+de,Pe=te*(me+1)+(de+1),ye=(te+1)*(me+1)+(de+1),ae.push(_e,be,Pe),ae.push(ye,Pe,be);D!==1&&v&&(ae.push(_e+2,be+2,Pe+2),ae.push(ye+2,Pe+2,be+2),ae.push(_e+4,be+4,Pe+4),ae.push(ye+4,Pe+4,be+4)),te=h?te+2:te+1}var Be=function(We){var je=We?T/2:A/2;if(je!==0){var He,qe,Ge,nt=We?N[V-1]:N[0],$e=null;I&&($e=We?I[V-1]:I[0]);var lt=ee.length/3,st=We?c/2:-c/2,mt=new U.e(0,st,0);ee.push(mt.x,mt.y,mt.z),K.push(0,We?1:-1,0),$.push(nt.x+.5*(nt.z-nt.x),nt.y+.5*(nt.w-nt.y)),$e&&L.push($e.r,$e.g,$e.b,$e.a);var St=new U.d(.5,.5);for(Ge=0;Ge<=g;Ge++){He=2*Math.PI*Ge*D/g;var wt=Math.cos(-He),It=Math.sin(-He);qe=new U.e(wt*je,st,It*je);var Pt=new U.d(wt*St.x+.5,It*St.y+.5);ee.push(qe.x,qe.y,qe.z),K.push(0,We?1:-1,0),$.push(nt.x+(nt.z-nt.x)*Pt.x,nt.y+(nt.w-nt.y)*Pt.y),$e&&L.push($e.r,$e.g,$e.b,$e.a)}for(Ge=0;Ge<g;Ge++)We?(ae.push(lt),ae.push(lt+(Ge+2)),ae.push(lt+(Ge+1))):(ae.push(lt),ae.push(lt+(Ge+1)),ae.push(lt+(Ge+2)))}};E!==C.a.CAP_START&&E!==C.a.CAP_ALL||Be(!1),E!==C.a.CAP_END&&E!==C.a.CAP_ALL||Be(!0),u.a._ComputeSides(w,ee,ae,K,$,m.frontUVs,m.backUVs);var ke=new u.a;return ke.indices=ae,ke.positions=ee,ke.normals=K,ke.uvs=$,I&&(ke.colors=L),ke},C.a.CreateCylinder=function(m,c,T,A,S,g,l,h,v){l!==void 0&&l instanceof M.a||(l!==void 0&&(v=h||C.a.DEFAULTSIDE,h=l),l=g,g=1);var E={height:c,diameterTop:T,diameterBottom:A,tessellation:S,subdivisions:g,sideOrientation:v,updatable:h};return x.CreateCylinder(m,E,l)};var x=function(){function m(){}return m.CreateCylinder=function(c,T,A){var S=new C.a(c,A);return 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c=this.pickedMesh.getVerticesData(_.b.NormalKind),T=U.e.FromArray(c,3*m[3*this.faceId]),A=U.e.FromArray(c,3*m[3*this.faceId+1]),S=U.e.FromArray(c,3*m[3*this.faceId+2]);T=T.scale(this.bu),A=A.scale(this.bv),S=S.scale(1-this.bu-this.bv),x=new U.e(T.x+A.x+S.x,T.y+A.y+S.y,T.z+A.z+S.z)}else{var g=this.pickedMesh.getVerticesData(_.b.PositionKind),l=U.e.FromArray(g,3*m[3*this.faceId]),h=U.e.FromArray(g,3*m[3*this.faceId+1]),v=U.e.FromArray(g,3*m[3*this.faceId+2]),E=l.subtract(h),D=v.subtract(h);x=U.e.Cross(E,D)}if(M){var w=this.pickedMesh.getWorldMatrix();this.pickedMesh.nonUniformScaling&&(U.c.Matrix[0].copyFrom(w),(w=U.c.Matrix[0]).setTranslationFromFloats(0,0,0),w.invert(),w.transposeToRef(U.c.Matrix[1]),w=U.c.Matrix[1]),x=U.e.TransformNormal(x,w)}return x.normalize(),x},u.prototype.getTextureCoordinates=function(){if(!this.pickedMesh||!this.pickedMesh.isVerticesDataPresent(_.b.UVKind))return null;var M=this.pickedMesh.getIndices();if(!M)return null;var R=this.pickedMesh.getVerticesData(_.b.UVKind);if(!R)return null;var x=U.d.FromArray(R,2*M[3*this.faceId]),m=U.d.FromArray(R,2*M[3*this.faceId+1]),c=U.d.FromArray(R,2*M[3*this.faceId+2]);return x=x.scale(this.bu),m=m.scale(this.bv),c=c.scale(1-this.bu-this.bv),new U.d(x.x+m.x+c.x,x.y+m.y+c.y)},u}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(57),_=function(){function C(){this._startMonitoringTime=0,this._min=0,this._max=0,this._average=0,this._lastSecAverage=0,this._current=0,this._totalValueCount=0,this._totalAccumulated=0,this._lastSecAccumulated=0,this._lastSecTime=0,this._lastSecValueCount=0}return Object.defineProperty(C.prototype,"min",{get:function(){return this._min},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"max",{get:function(){return this._max},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"average",{get:function(){return 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te=function(){X.src=I};if(I.substr(0,5)!=="data:"&&w&&w.enableTexturesOffline)w.open(function(){w&&w.loadImage(I,X)},te);else{if(I.indexOf("file:")!==-1){var de=decodeURIComponent(I.substring(5).toLowerCase());if(M.a.FilesToLoad[de]){try{var pe;try{pe=URL.createObjectURL(M.a.FilesToLoad[de])}catch{pe=URL.createObjectURL(M.a.FilesToLoad[de])}X.src=pe,V=!0}catch{X.src=""}return X}}te()}return X},h.ReadFile=function(v,E,D,w,N){var I=new FileReader,V={onCompleteObservable:new u.c,abort:function(){return I.abort()}};return I.onloadend=function(X){return V.onCompleteObservable.notifyObservers(V)},N&&(I.onerror=function(X){N(new g("Unable to read "+v.name,v))}),I.onload=function(X){E(X.target.result)},D&&(I.onprogress=D),w?I.readAsArrayBuffer(v):I.readAsText(v),V},h.LoadFile=function(v,E,D,w,N,I){if(v.indexOf("file:")!==-1){var V=decodeURIComponent(v.substring(5).toLowerCase());V.indexOf("./")===0&&(V=V.substring(2));var X=M.a.FilesToLoad[V];if(X)return h.ReadFile(X,E,D,N,I?function(j){return 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_});var U=f(38),_=function(){function C(){}return Object.defineProperty(C,"Now",{get:function(){return U.a.IsWindowObjectExist()&&window.performance&&window.performance.now?window.performance.now():Date.now()},enumerable:!1,configurable:!0}),C}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(C,u,M,R){this.x=C,this.y=u,this.width=M,this.height=R}return _.prototype.toGlobal=function(C,u){return new _(this.x*C,this.y*u,this.width*C,this.height*u)},_.prototype.toGlobalToRef=function(C,u,M){return M.x=this.x*C,M.y=this.y*u,M.width=this.width*C,M.height=this.height*u,this},_.prototype.clone=function(){return new _(this.x,this.y,this.width,this.height)},_}()},function(Me,y,f){var U="helperFunctions",_=`const float PI=3.1415926535897932384626433832795;
-const float HALF_MIN=5.96046448e-08;
-const float LinearEncodePowerApprox=2.2;
-const float GammaEncodePowerApprox=1.0/LinearEncodePowerApprox;
-const vec3 LuminanceEncodeApprox=vec3(0.2126,0.7152,0.0722);
-const float Epsilon=0.0000001;
-#define saturate(x) clamp(x,0.0,1.0)
-#define absEps(x) abs(x)+Epsilon
-#define maxEps(x) max(x,Epsilon)
-#define saturateEps(x) clamp(x,Epsilon,1.0)
-mat3 transposeMat3(mat3 inMatrix) {
-vec3 i0=inMatrix[0];
-vec3 i1=inMatrix[1];
-vec3 i2=inMatrix[2];
-mat3 outMatrix=mat3(
-vec3(i0.x,i1.x,i2.x),
-vec3(i0.y,i1.y,i2.y),
-vec3(i0.z,i1.z,i2.z)
-);
-return outMatrix;
-}
-
-mat3 inverseMat3(mat3 inMatrix) {
-float a00=inMatrix[0][0],a01=inMatrix[0][1],a02=inMatrix[0][2];
-float a10=inMatrix[1][0],a11=inMatrix[1][1],a12=inMatrix[1][2];
-float a20=inMatrix[2][0],a21=inMatrix[2][1],a22=inMatrix[2][2];
-float b01=a22*a11-a12*a21;
-float b11=-a22*a10+a12*a20;
-float b21=a21*a10-a11*a20;
-float det=a00*b01+a01*b11+a02*b21;
-return mat3(b01,(-a22*a01+a02*a21),(a12*a01-a02*a11),
-b11,(a22*a00-a02*a20),(-a12*a00+a02*a10),
-b21,(-a21*a00+a01*a20),(a11*a00-a01*a10))/det;
-}
-float toLinearSpace(float color)
-{
-return pow(color,LinearEncodePowerApprox);
-}
-vec3 toLinearSpace(vec3 color)
-{
-return pow(color,vec3(LinearEncodePowerApprox));
-}
-vec4 toLinearSpace(vec4 color)
-{
-return vec4(pow(color.rgb,vec3(LinearEncodePowerApprox)),color.a);
-}
-vec3 toGammaSpace(vec3 color)
-{
-return pow(color,vec3(GammaEncodePowerApprox));
-}
-vec4 toGammaSpace(vec4 color)
-{
-return vec4(pow(color.rgb,vec3(GammaEncodePowerApprox)),color.a);
-}
-float toGammaSpace(float color)
-{
-return pow(color,GammaEncodePowerApprox);
-}
-float square(float value)
-{
-return value*value;
-}
-float pow5(float value) {
-float sq=value*value;
-return sq*sq*value;
-}
-float getLuminance(vec3 color)
-{
-return clamp(dot(color,LuminanceEncodeApprox),0.,1.);
-}
-
-float getRand(vec2 seed) {
-return fract(sin(dot(seed.xy ,vec2(12.9898,78.233)))*43758.5453);
-}
-float dither(vec2 seed,float varianceAmount) {
-float rand=getRand(seed);
-float dither=mix(-varianceAmount/255.0,varianceAmount/255.0,rand);
-return dither;
-}
-
-const float rgbdMaxRange=255.0;
-vec4 toRGBD(vec3 color) {
-float maxRGB=maxEps(max(color.r,max(color.g,color.b)));
-float D=max(rgbdMaxRange/maxRGB,1.);
-D=clamp(floor(D)/255.0,0.,1.);
-
-vec3 rgb=color.rgb*D;
-
-rgb=toGammaSpace(rgb);
-return vec4(rgb,D);
-}
-vec3 fromRGBD(vec4 rgbd) {
-
-rgbd.rgb=toLinearSpace(rgbd.rgb);
-
-return rgbd.rgb/rgbd.a;
-}
-`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(0),_=function(){function C(){}return 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this._renderingMesh},x.prototype.getReplacementMesh=function(){return this._mesh._internalAbstractMeshDataInfo._actAsRegularMesh?this._mesh:null},x.prototype.getEffectiveMesh=function(){var m=this._mesh._internalAbstractMeshDataInfo._actAsRegularMesh?this._mesh:null;return m||this._renderingMesh},x.prototype.getMaterial=function(){var m=this._renderingMesh.material;if(m==null)return this._mesh.getScene().defaultMaterial;if(this._IsMultiMaterial(m)){var c=m.getSubMaterial(this.materialIndex);return this._currentMaterial!==c&&(this._currentMaterial=c,this._materialDefines=null),c}return m},x.prototype._IsMultiMaterial=function(m){return m.getSubMaterial!==void 0},x.prototype.refreshBoundingInfo=function(m){if(m===void 0&&(m=null),this._lastColliderWorldVertices=null,this.IsGlobal||!this._renderingMesh||!this._renderingMesh.geometry)return this;if(m||(m=this._renderingMesh.getVerticesData(U.b.PositionKind)),!m)return this._boundingInfo=this._mesh.getBoundingInfo(),this;var c,T=this._renderingMesh.getIndices();if(this.indexStart===0&&this.indexCount===T.length){var A=this._renderingMesh.getBoundingInfo();c={minimum:A.minimum.clone(),maximum:A.maximum.clone()}}else c=Object(M.b)(m,T,this.indexStart,this.indexCount,this._renderingMesh.geometry.boundingBias);return this._boundingInfo?this._boundingInfo.reConstruct(c.minimum,c.maximum):this._boundingInfo=new C.a(c.minimum,c.maximum),this},x.prototype._checkCollision=function(m){return this.getBoundingInfo()._checkCollision(m)},x.prototype.updateBoundingInfo=function(m){var c=this.getBoundingInfo();return c||(this.refreshBoundingInfo(),c=this.getBoundingInfo()),c&&c.update(m),this},x.prototype.isInFrustum=function(m){var c=this.getBoundingInfo();return!!c&&c.isInFrustum(m,this._mesh.cullingStrategy)},x.prototype.isCompletelyInFrustum=function(m){var c=this.getBoundingInfo();return!!c&&c.isCompletelyInFrustum(m)},x.prototype.render=function(m){return this._renderingMesh.render(this,m,this._mesh._internalAbstractMeshDataInfo._actAsRegularMesh?this._mesh:void 0),this},x.prototype._getLinesIndexBuffer=function(m,c){if(!this._linesIndexBuffer){for(var T=[],A=this.indexStart;A<this.indexStart+this.indexCount;A+=3)T.push(m[A],m[A+1],m[A+1],m[A+2],m[A+2],m[A]);this._linesIndexBuffer=c.createIndexBuffer(T),this._linesIndexCount=T.length}return this._linesIndexBuffer},x.prototype.canIntersects=function(m){var c=this.getBoundingInfo();return!!c&&m.intersectsBox(c.boundingBox)},x.prototype.intersects=function(m,c,T,A,S){var g=this.getMaterial();if(!g)return null;var l=3,h=!1;switch(g.fillMode){case u.a.MATERIAL_PointListDrawMode:case u.a.MATERIAL_LineListDrawMode:case u.a.MATERIAL_LineLoopDrawMode:case u.a.MATERIAL_LineStripDrawMode:case u.a.MATERIAL_TriangleFanDrawMode:return null;case u.a.MATERIAL_TriangleStripDrawMode:l=1,h=!0}return this._mesh.getClassName()==="InstancedLinesMesh"||this._mesh.getClassName()==="LinesMesh"?T.length?this._intersectLines(m,c,T,this._mesh.intersectionThreshold,A):this._intersectUnIndexedLines(m,c,T,this._mesh.intersectionThreshold,A):!T.length&&this._mesh._unIndexed?this._intersectUnIndexedTriangles(m,c,T,A,S):this._intersectTriangles(m,c,T,l,h,A,S)},x.prototype._intersectLines=function(m,c,T,A,S){for(var g=null,l=this.indexStart;l<this.indexStart+this.indexCount;l+=2){var h=c[T[l]],v=c[T[l+1]],E=m.intersectionSegment(h,v,A);if(!(E<0)&&(S||!g||E<g.distance)&&((g=new _.a(null,null,E)).faceId=l/2,S))break}return g},x.prototype._intersectUnIndexedLines=function(m,c,T,A,S){for(var g=null,l=this.verticesStart;l<this.verticesStart+this.verticesCount;l+=2){var h=c[l],v=c[l+1],E=m.intersectionSegment(h,v,A);if(!(E<0)&&(S||!g||E<g.distance)&&((g=new _.a(null,null,E)).faceId=l/2,S))break}return g},x.prototype._intersectTriangles=function(m,c,T,A,S,g,l){for(var 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v;T.getContext?(v._canvas=T,v._texture=E.createDynamicTexture(T.width,T.height,S,g)):(v._canvas=M.a.CreateCanvas(1,1),T.width||T.width===0?v._texture=E.createDynamicTexture(T.width,T.height,S,g):v._texture=E.createDynamicTexture(T,T,S,g));var D=v.getSize();return v._canvas.width=D.width,v._canvas.height=D.height,v._context=v._canvas.getContext("2d"),v}return Object(U.d)(m,x),m.prototype.getClassName=function(){return"DynamicTexture"},Object.defineProperty(m.prototype,"canRescale",{get:function(){return!0},enumerable:!1,configurable:!0}),m.prototype._recreate=function(c){this._canvas.width=c.width,this._canvas.height=c.height,this.releaseInternalTexture(),this._texture=this._getEngine().createDynamicTexture(c.width,c.height,this._generateMipMaps,this.samplingMode)},m.prototype.scale=function(c){var T=this.getSize();T.width*=c,T.height*=c,this._recreate(T)},m.prototype.scaleTo=function(c,T){var A=this.getSize();A.width=c,A.height=T,this._recreate(A)},m.prototype.getContext=function(){return this._context},m.prototype.clear=function(){var c=this.getSize();this._context.fillRect(0,0,c.width,c.height)},m.prototype.update=function(c,T){T===void 0&&(T=!1),this._getEngine().updateDynamicTexture(this._texture,this._canvas,c===void 0||c,T,this._format||void 0)},m.prototype.drawText=function(c,T,A,S,g,l,h,v){v===void 0&&(v=!0);var E=this.getSize();if(l&&(this._context.fillStyle=l,this._context.fillRect(0,0,E.width,E.height)),this._context.font=S,T==null){var D=this._context.measureText(c);T=(E.width-D.width)/2}if(A==null){var w=parseInt(S.replace(/\D/g,""));A=E.height/2+w/3.65}this._context.fillStyle=g||"",this._context.fillText(c,T,A),v&&this.update(h)},m.prototype.clone=function(){var c=this.getScene();if(!c)return this;var T=this.getSize(),A=new m(this.name,T,c,this._generateMipMaps);return A.hasAlpha=this.hasAlpha,A.level=this.level,A.wrapU=this.wrapU,A.wrapV=this.wrapV,A},m.prototype.serialize=function(){var c=this.getScene();c&&!c.isReady()&&_.a.Warn("The scene must be ready before serializing the dynamic texture");var T=x.prototype.serialize.call(this);return this._IsCanvasElement(this._canvas)&&(T.base64String=this._canvas.toDataURL()),T.invertY=this._invertY,T.samplingMode=this.samplingMode,T},m.prototype._IsCanvasElement=function(c){return c.toDataURL!==void 0},m.prototype._rebuild=function(){this.update()},m}(C.a)},function(Me,y,f){f.d(y,"a",function(){return M});var U=f(0),_=f(9),C=f(7),u=f(16);u.a.CreateBox=function(R){var x,m=[0,1,2,0,2,3,4,5,6,4,6,7,8,9,10,8,10,11,12,13,14,12,14,15,16,17,18,16,18,19,20,21,22,20,22,23],c=[0,0,1,0,0,1,0,0,1,0,0,1,0,0,-1,0,0,-1,0,0,-1,0,0,-1,1,0,0,1,0,0,1,0,0,1,0,0,-1,0,0,-1,0,0,-1,0,0,-1,0,0,0,1,0,0,1,0,0,1,0,0,1,0,0,-1,0,0,-1,0,0,-1,0,0,-1,0],T=[],A=R.width||R.size||1,S=R.height||R.size||1,g=R.depth||R.size||1,l=R.wrap||!1,h=R.topBaseAt===void 0?1:R.topBaseAt,v=R.bottomBaseAt===void 0?0:R.bottomBaseAt,E=[2,0,3,1][h=(h+4)%4],D=[2,0,1,3][v=(v+4)%4],w=[1,-1,1,-1,-1,1,-1,1,1,1,1,1,1,1,-1,-1,1,-1,-1,-1,-1,1,-1,-1,1,1,-1,1,-1,-1,1,-1,1,1,1,1,-1,1,1,-1,-1,1,-1,-1,-1,-1,1,-1,-1,1,1,-1,1,-1,1,1,-1,1,1,1,1,-1,1,1,-1,-1,-1,-1,-1,-1,-1,1];if(l){m=[2,3,0,2,0,1,4,5,6,4,6,7,9,10,11,9,11,8,12,14,15,12,13,14],w=[-1,1,1,1,1,1,1,-1,1,-1,-1,1,1,1,-1,-1,1,-1,-1,-1,-1,1,-1,-1,1,1,1,1,1,-1,1,-1,-1,1,-1,1,-1,1,-1,-1,1,1,-1,-1,1,-1,-1,-1];for(var N=[[1,1,1],[-1,1,1],[-1,1,-1],[1,1,-1]],I=[[-1,-1,1],[1,-1,1],[1,-1,-1],[-1,-1,-1]],V=[17,18,19,16],X=[22,23,20,21];E>0;)N.unshift(N.pop()),V.unshift(V.pop()),E--;for(;D>0;)I.unshift(I.pop()),X.unshift(X.pop()),D--;N=N.flat(),I=I.flat(),w=w.concat(N).concat(I),m.push(V[0],V[2],V[3],V[0],V[1],V[2]),m.push(X[0],X[2],X[3],X[0],X[1],X[2])}var j=[A/2,S/2,g/2];x=w.reduce(function(G,Q,oe){return G.concat(Q*j[oe%3])},[]);for(var ne=R.sideOrientation===0?0:R.sideOrientation||u.a.DEFAULTSIDE,te=R.faceUV||new Array(6),de=R.faceColors,pe=[],ae=0;ae<6;ae++)te[ae]===void 0&&(te[ae]=new U.f(0,0,1,1)),de&&de[ae]===void 0&&(de[ae]=new _.b(1,1,1,1));for(var ee=0;ee<6;ee++)if(T.push(te[ee].z,te[ee].w),T.push(te[ee].x,te[ee].w),T.push(te[ee].x,te[ee].y),T.push(te[ee].z,te[ee].y),de)for(var K=0;K<4;K++)pe.push(de[ee].r,de[ee].g,de[ee].b,de[ee].a);u.a._ComputeSides(ne,x,m,c,T,R.frontUVs,R.backUVs);var $=new u.a;if($.indices=m,$.positions=x,$.normals=c,$.uvs=T,de){var L=ne===u.a.DOUBLESIDE?pe.concat(pe):pe;$.colors=L}return $},C.a.CreateBox=function(R,x,m,c,T){m===void 0&&(m=null);var A={size:x,sideOrientation:T,updatable:c};return M.CreateBox(R,A,m)};var M=function(){function R(){}return R.CreateBox=function(x,m,c){c===void 0&&(c=null);var T=new C.a(x,c);return m.sideOrientation=C.a._GetDefaultSideOrientation(m.sideOrientation),T._originalBuilderSideOrientation=m.sideOrientation,u.a.CreateBox(m).applyToMesh(T,m.updatable),T},R}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(0),_=function(){function C(u,M,R,x){this.normal=new U.e(u,M,R),this.d=x}return C.prototype.asArray=function(){return[this.normal.x,this.normal.y,this.normal.z,this.d]},C.prototype.clone=function(){return new C(this.normal.x,this.normal.y,this.normal.z,this.d)},C.prototype.getClassName=function(){return"Plane"},C.prototype.getHashCode=function(){var u=this.normal.getHashCode();return u=397*u^(0|this.d)},C.prototype.normalize=function(){var u=Math.sqrt(this.normal.x*this.normal.x+this.normal.y*this.normal.y+this.normal.z*this.normal.z),M=0;return u!==0&&(M=1/u),this.normal.x*=M,this.normal.y*=M,this.normal.z*=M,this.d*=M,this},C.prototype.transform=function(u){var M=C._TmpMatrix;u.invertToRef(M);var R=M.m,x=this.normal.x,m=this.normal.y,c=this.normal.z,T=this.d;return new C(x*R[0]+m*R[1]+c*R[2]+T*R[3],x*R[4]+m*R[5]+c*R[6]+T*R[7],x*R[8]+m*R[9]+c*R[10]+T*R[11],x*R[12]+m*R[13]+c*R[14]+T*R[15])},C.prototype.dotCoordinate=function(u){return this.normal.x*u.x+this.normal.y*u.y+this.normal.z*u.z+this.d},C.prototype.copyFromPoints=function(u,M,R){var x,m=M.x-u.x,c=M.y-u.y,T=M.z-u.z,A=R.x-u.x,S=R.y-u.y,g=R.z-u.z,l=c*g-T*S,h=T*A-m*g,v=m*S-c*A,E=Math.sqrt(l*l+h*h+v*v);return x=E!==0?1/E:0,this.normal.x=l*x,this.normal.y=h*x,this.normal.z=v*x,this.d=-(this.normal.x*u.x+this.normal.y*u.y+this.normal.z*u.z),this},C.prototype.isFrontFacingTo=function(u,M){return U.e.Dot(this.normal,u)<=M},C.prototype.signedDistanceTo=function(u){return U.e.Dot(u,this.normal)+this.d},C.FromArray=function(u){return new C(u[0],u[1],u[2],u[3])},C.FromPoints=function(u,M,R){var x=new C(0,0,0,0);return x.copyFromPoints(u,M,R),x},C.FromPositionAndNormal=function(u,M){var R=new C(0,0,0,0);return M.normalize(),R.normal=M,R.d=-(M.x*u.x+M.y*u.y+M.z*u.z),R},C.SignedDistanceToPlaneFromPositionAndNormal=function(u,M,R){var x=-(M.x*u.x+M.y*u.y+M.z*u.z);return U.e.Dot(R,M)+x},C._TmpMatrix=U.a.Identity(),C}()},function(Me,y,f){f.d(y,"a",function(){return m});var U=f(7),_=f(20),C=f(6),u=f(0),M=f(18),R=f(39),x=f(60),m=(f(84),function(){function c(T){this._useAlternatePickedPointAboveMaxDragAngleDragSpeed=-1.1,this.maxDragAngle=0,this._useAlternatePickedPointAboveMaxDragAngle=!1,this.currentDraggingPointerID=-1,this.dragging=!1,this.dragDeltaRatio=.2,this.updateDragPlane=!0,this._debugMode=!1,this._moving=!1,this.onDragObservable=new C.c,this.onDragStartObservable=new C.c,this.onDragEndObservable=new C.c,this.moveAttached=!0,this.enabled=!0,this.startAndReleaseDragOnPointerEvents=!0,this.detachCameraControls=!0,this.useObjectOrientationForDragging=!0,this.validateDrag=function(S){return!0},this._tmpVector=new u.e(0,0,0),this._alternatePickedPoint=new u.e(0,0,0),this._worldDragAxis=new u.e(0,0,0),this._targetPosition=new u.e(0,0,0),this._attachedToElement=!1,this._startDragRay=new R.a(new u.e,new u.e),this._lastPointerRay={},this._dragDelta=new u.e,this._pointA=new u.e(0,0,0),this._pointC=new u.e(0,0,0),this._localAxis=new u.e(0,0,0),this._lookAt=new u.e(0,0,0),this._options=T||{};var A=0;if(this._options.dragAxis&&A++,this._options.dragPlaneNormal&&A++,A>1)throw"Multiple drag modes specified in dragBehavior options. 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S.attachedNode==l||l.isDescendantOf(S.attachedNode)};this._pointerObserver=this._scene.onPointerObservable.add(function(l,h){if(S.enabled){if(l.type==M.a.POINTERDOWN)S.startAndReleaseDragOnPointerEvents&&!S.dragging&&l.pickInfo&&l.pickInfo.hit&&l.pickInfo.pickedMesh&&l.pickInfo.pickedPoint&&l.pickInfo.ray&&g(l.pickInfo.pickedMesh)&&S._startDrag(l.event.pointerId,l.pickInfo.ray,l.pickInfo.pickedPoint);else if(l.type==M.a.POINTERUP)S.startAndReleaseDragOnPointerEvents&&S.currentDraggingPointerID==l.event.pointerId&&S.releaseDrag();else if(l.type==M.a.POINTERMOVE){var v=l.event.pointerId;if(S.currentDraggingPointerID===c._AnyMouseID&&v!==c._AnyMouseID){var E=l.event;(E.pointerType==="mouse"||!S._scene.getEngine().hostInformation.isMobile&&E instanceof MouseEvent)&&(S._lastPointerRay[S.currentDraggingPointerID]&&(S._lastPointerRay[v]=S._lastPointerRay[S.currentDraggingPointerID],delete S._lastPointerRay[S.currentDraggingPointerID]),S.currentDraggingPointerID=v)}S._lastPointerRay[v]||(S._lastPointerRay[v]=new R.a(new u.e,new u.e)),l.pickInfo&&l.pickInfo.ray&&(S._lastPointerRay[v].origin.copyFrom(l.pickInfo.ray.origin),S._lastPointerRay[v].direction.copyFrom(l.pickInfo.ray.direction),S.currentDraggingPointerID==v&&S.dragging&&S._moveDrag(l.pickInfo.ray))}}}),this._beforeRenderObserver=this._scene.onBeforeRenderObservable.add(function(){S._moving&&S.moveAttached&&(x.a._RemoveAndStorePivotPoint(S.attachedNode),S._targetPosition.subtractToRef(S.attachedNode.absolutePosition,S._tmpVector),S._tmpVector.scaleInPlace(S.dragDeltaRatio),S.attachedNode.getAbsolutePosition().addToRef(S._tmpVector,S._tmpVector),S.validateDrag(S._tmpVector)&&S.attachedNode.setAbsolutePosition(S._tmpVector),x.a._RestorePivotPoint(S.attachedNode))})},c.prototype.releaseDrag=function(){if(this.dragging&&(this.dragging=!1,this.onDragEndObservable.notifyObservers({dragPlanePoint:this.lastDragPosition,pointerId:this.currentDraggingPointerID})),this.currentDraggingPointerID=-1,this._moving=!1,this.detachCameraControls&&this._attachedToElement&&this._scene.activeCamera&&!this._scene.activeCamera.leftCamera){if(this._scene.activeCamera.getClassName()==="ArcRotateCamera"){var T=this._scene.activeCamera;T.attachControl(!T.inputs||T.inputs.noPreventDefault,T._useCtrlForPanning,T._panningMouseButton)}else this._scene.activeCamera.attachControl(!this._scene.activeCamera.inputs||this._scene.activeCamera.inputs.noPreventDefault);this._attachedToElement=!1}},c.prototype.startDrag=function(T,A,S){T===void 0&&(T=c._AnyMouseID),this._startDrag(T,A,S);var g=this._lastPointerRay[T];T===c._AnyMouseID&&(g=this._lastPointerRay[Object.keys(this._lastPointerRay)[0]]),g&&this._moveDrag(g)},c.prototype._startDrag=function(T,A,S){if(this._scene.activeCamera&&!this.dragging&&this.attachedNode){x.a._RemoveAndStorePivotPoint(this.attachedNode),A?(this._startDragRay.direction.copyFrom(A.direction),this._startDragRay.origin.copyFrom(A.origin)):(this._startDragRay.origin.copyFrom(this._scene.activeCamera.position),this.attachedNode.getWorldMatrix().getTranslationToRef(this._tmpVector),this._tmpVector.subtractToRef(this._scene.activeCamera.position,this._startDragRay.direction)),this._updateDragPlanePosition(this._startDragRay,S||this._tmpVector);var g=this._pickWithRayOnDragPlane(this._startDragRay);g&&(this.dragging=!0,this.currentDraggingPointerID=T,this.lastDragPosition.copyFrom(g),this.onDragStartObservable.notifyObservers({dragPlanePoint:g,pointerId:this.currentDraggingPointerID}),this._targetPosition.copyFrom(this.attachedNode.absolutePosition),this.detachCameraControls&&this._scene.activeCamera&&this._scene.activeCamera.inputs&&!this._scene.activeCamera.leftCamera&&(this._scene.activeCamera.inputs.attachedToElement?(this._scene.activeCamera.detachControl(),this._attachedToElement=!0):this._attachedToElement=!1)),x.a._RestorePivotPoint(this.attachedNode)}},c.prototype._moveDrag=function(T){this._moving=!0;var A=this._pickWithRayOnDragPlane(T);if(A){this.updateDragPlane&&this._updateDragPlanePosition(T,A);var S=0;this._options.dragAxis?(this.useObjectOrientationForDragging?u.e.TransformCoordinatesToRef(this._options.dragAxis,this.attachedNode.getWorldMatrix().getRotationMatrix(),this._worldDragAxis):this._worldDragAxis.copyFrom(this._options.dragAxis),A.subtractToRef(this.lastDragPosition,this._tmpVector),S=u.e.Dot(this._tmpVector,this._worldDragAxis),this._worldDragAxis.scaleToRef(S,this._dragDelta)):(S=this._dragDelta.length(),A.subtractToRef(this.lastDragPosition,this._dragDelta)),this._targetPosition.addInPlace(this._dragDelta),this.onDragObservable.notifyObservers({dragDistance:S,delta:this._dragDelta,dragPlanePoint:A,dragPlaneNormal:this._dragPlane.forward,pointerId:this.currentDraggingPointerID}),this.lastDragPosition.copyFrom(A)}},c.prototype._pickWithRayOnDragPlane=function(T){var A=this;if(!T)return null;var S=Math.acos(u.e.Dot(this._dragPlane.forward,T.direction));if(S>Math.PI/2&&(S=Math.PI-S),this.maxDragAngle>0&&S>this.maxDragAngle){if(this._useAlternatePickedPointAboveMaxDragAngle){this._tmpVector.copyFrom(T.direction),this.attachedNode.absolutePosition.subtractToRef(T.origin,this._alternatePickedPoint),this._alternatePickedPoint.normalize(),this._alternatePickedPoint.scaleInPlace(this._useAlternatePickedPointAboveMaxDragAngleDragSpeed*u.e.Dot(this._alternatePickedPoint,this._tmpVector)),this._tmpVector.addInPlace(this._alternatePickedPoint);var g=u.e.Dot(this._dragPlane.forward,this._tmpVector);return this._dragPlane.forward.scaleToRef(-g,this._alternatePickedPoint),this._alternatePickedPoint.addInPlace(this._tmpVector),this._alternatePickedPoint.addInPlace(this.attachedNode.absolutePosition),this._alternatePickedPoint}return null}var l=c._planeScene.pickWithRay(T,function(h){return h==A._dragPlane});return l&&l.hit&&l.pickedMesh&&l.pickedPoint?l.pickedPoint:null},c.prototype._updateDragPlanePosition=function(T,A){this._pointA.copyFrom(A),this._options.dragAxis?(this.useObjectOrientationForDragging?u.e.TransformCoordinatesToRef(this._options.dragAxis,this.attachedNode.getWorldMatrix().getRotationMatrix(),this._localAxis):this._localAxis.copyFrom(this._options.dragAxis),T.origin.subtractToRef(this._pointA,this._pointC),this._pointC.normalize(),Math.abs(u.e.Dot(this._localAxis,this._pointC))>.999?Math.abs(u.e.Dot(u.e.UpReadOnly,this._pointC))>.999?this._lookAt.copyFrom(u.e.Right()):this._lookAt.copyFrom(u.e.UpReadOnly):(u.e.CrossToRef(this._localAxis,this._pointC,this._lookAt),u.e.CrossToRef(this._localAxis,this._lookAt,this._lookAt),this._lookAt.normalize()),this._dragPlane.position.copyFrom(this._pointA),this._pointA.addToRef(this._lookAt,this._lookAt),this._dragPlane.lookAt(this._lookAt)):this._options.dragPlaneNormal?(this.useObjectOrientationForDragging?u.e.TransformCoordinatesToRef(this._options.dragPlaneNormal,this.attachedNode.getWorldMatrix().getRotationMatrix(),this._localAxis):this._localAxis.copyFrom(this._options.dragPlaneNormal),this._dragPlane.position.copyFrom(this._pointA),this._pointA.addToRef(this._localAxis,this._lookAt),this._dragPlane.lookAt(this._lookAt)):(this._dragPlane.position.copyFrom(this._pointA),this._dragPlane.lookAt(T.origin)),this._dragPlane.position.copyFrom(this.attachedNode.absolutePosition),this._dragPlane.computeWorldMatrix(!0)},c.prototype.detach=function(){this._pointerObserver&&this._scene.onPointerObservable.remove(this._pointerObserver),this._beforeRenderObserver&&this._scene.onBeforeRenderObservable.remove(this._beforeRenderObserver),this.releaseDrag()},c._AnyMouseID=-2,c}())},function(Me,y,f){f.d(y,"a",function(){return _}),f.d(y,"b",function(){return C}),f.d(y,"c",function(){return u});var U=f(1),_=function(){function M(){}return M.KEYDOWN=1,M.KEYUP=2,M}(),C=function(M,R){this.type=M,this.event=R},u=function(M){function R(x,m){var c=M.call(this,x,m)||this;return c.type=x,c.event=m,c.skipOnPointerObservable=!1,c}return Object(U.d)(R,M),R}(C)},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){this._defines={},this._currentRank=32,this._maxRank=-1,this._mesh=null}return _.prototype.unBindMesh=function(){this._mesh=null},_.prototype.addFallback=function(C,u){this._defines[C]||(C<this._currentRank&&(this._currentRank=C),C>this._maxRank&&(this._maxRank=C),this._defines[C]=new Array),this._defines[C].push(u)},_.prototype.addCPUSkinningFallback=function(C,u){this._mesh=u,C<this._currentRank&&(this._currentRank=C),C>this._maxRank&&(this._maxRank=C)},Object.defineProperty(_.prototype,"hasMoreFallbacks",{get:function(){return this._currentRank<=this._maxRank},enumerable:!1,configurable:!0}),_.prototype.reduce=function(C,u){if(this._mesh&&this._mesh.computeBonesUsingShaders&&this._mesh.numBoneInfluencers>0){this._mesh.computeBonesUsingShaders=!1,C=C.replace("#define NUM_BONE_INFLUENCERS "+this._mesh.numBoneInfluencers,"#define NUM_BONE_INFLUENCERS 0"),u._bonesComputationForcedToCPU=!0;for(var M=this._mesh.getScene(),R=0;R<M.meshes.length;R++){var x=M.meshes[R];if(x.material){if(x.computeBonesUsingShaders&&x.numBoneInfluencers!==0){if(x.material.getEffect()===u)x.computeBonesUsingShaders=!1;else if(x.subMeshes){for(var m=0,c=x.subMeshes;m<c.length;m++)if(c[m].effect===u){x.computeBonesUsingShaders=!1;break}}}}else!this._mesh.material&&x.computeBonesUsingShaders&&x.numBoneInfluencers>0&&(x.computeBonesUsingShaders=!1)}}else{var T=this._defines[this._currentRank];if(T)for(R=0;R<T.length;R++)C=C.replace("#define "+T[R],"");this._currentRank++}return C},_}()},function(Me,y,f){f.d(y,"a",function(){return M});var U=f(1),_=f(25),C=f(37),u=f(11),M=function(R){function x(m,c){var T=R.call(this,m,c,!0)||this;return c.multiMaterials.push(T),T.subMaterials=new Array,T._storeEffectOnSubMeshes=!0,T}return Object(U.d)(x,R),Object.defineProperty(x.prototype,"subMaterials",{get:function(){return this._subMaterials},set:function(m){this._subMaterials=m,this._hookArray(m)},enumerable:!1,configurable:!0}),x.prototype.getChildren=function(){return this.subMaterials},x.prototype._hookArray=function(m){var c=this,T=m.push;m.push=function(){for(var S=[],g=0;g<arguments.length;g++)S[g]=arguments[g];var l=T.apply(m,S);return c._markAllSubMeshesAsTexturesDirty(),l};var A=m.splice;m.splice=function(S,g){var l=A.apply(m,[S,g]);return c._markAllSubMeshesAsTexturesDirty(),l}},x.prototype.getSubMaterial=function(m){return m<0||m>=this.subMaterials.length?this.getScene().defaultMaterial:this.subMaterials[m]},x.prototype.getActiveTextures=function(){var m;return(m=R.prototype.getActiveTextures.call(this)).concat.apply(m,this.subMaterials.map(function(c){return c?c.getActiveTextures():[]}))},x.prototype.hasTexture=function(m){var c;if(R.prototype.hasTexture.call(this,m))return!0;for(var T=0;T<this.subMaterials.length;T++)if(!((c=this.subMaterials[T])===null||c===void 0)&&c.hasTexture(m))return!0;return!1},x.prototype.getClassName=function(){return"MultiMaterial"},x.prototype.isReadyForSubMesh=function(m,c,T){for(var A=0;A<this.subMaterials.length;A++){var S=this.subMaterials[A];if(S){if(S._storeEffectOnSubMeshes){if(!S.isReadyForSubMesh(m,c,T))return!1;continue}if(!S.isReady(m))return!1}}return!0},x.prototype.clone=function(m,c){for(var T=new x(m,this.getScene()),A=0;A<this.subMaterials.length;A++){var S=null,g=this.subMaterials[A];S=c&&g?g.clone(m+"-"+g.name):this.subMaterials[A],T.subMaterials.push(S)}return T},x.prototype.serialize=function(){var m={};m.name=this.name,m.id=this.id,C.a&&(m.tags=C.a.GetTags(this)),m.materials=[];for(var c=0;c<this.subMaterials.length;c++){var T=this.subMaterials[c];T?m.materials.push(T.id):m.materials.push(null)}return m},x.prototype.dispose=function(m,c,T){var A=this.getScene();if(A){if(T)for(var S=0;S<this.subMaterials.length;S++){var g=this.subMaterials[S];g&&g.dispose(m,c)}(S=A.multiMaterials.indexOf(this))>=0&&A.multiMaterials.splice(S,1),R.prototype.dispose.call(this,m,c)}},x.ParseMultiMaterial=function(m,c){var T=new x(m.name,c);T.id=m.id,C.a&&C.a.AddTagsTo(T,m.tags);for(var A=0;A<m.materials.length;A++){var S=m.materials[A];S?T.subMaterials.push(c.getLastMaterialByID(S)):T.subMaterials.push(null)}return T},x}(_.a);u.a.RegisteredTypes["BABYLON.MultiMaterial"]=M},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(2),_=function(){function C(){}return Object.defineProperty(C,"ForceFullSceneLoadingForIncremental",{get:function(){return C._ForceFullSceneLoadingForIncremental},set:function(u){C._ForceFullSceneLoadingForIncremental=u},enumerable:!1,configurable:!0}),Object.defineProperty(C,"ShowLoadingScreen",{get:function(){return C._ShowLoadingScreen},set:function(u){C._ShowLoadingScreen=u},enumerable:!1,configurable:!0}),Object.defineProperty(C,"loggingLevel",{get:function(){return C._loggingLevel},set:function(u){C._loggingLevel=u},enumerable:!1,configurable:!0}),Object.defineProperty(C,"CleanBoneMatrixWeights",{get:function(){return C._CleanBoneMatrixWeights},set:function(u){C._CleanBoneMatrixWeights=u},enumerable:!1,configurable:!0}),C._ForceFullSceneLoadingForIncremental=!1,C._ShowLoadingScreen=!0,C._CleanBoneMatrixWeights=!1,C._loggingLevel=U.a.SCENELOADER_NO_LOGGING,C}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.CreateCanvas=function(C,u){if(typeof document>"u")return new OffscreenCanvas(C,u);var M=document.createElement("canvas");return M.width=C,M.height=u,M},_}()},function(Me,y,f){f.d(y,"a",function(){return S});var U=f(0),_=f(9),C=f(16),u=f(4),M=f(61),R=f(69),x=f(43),m=f(2),c=f(12),T=f(37),A=f(101),S=function(){function g(l,h,v,E,D){E===void 0&&(E=!1),D===void 0&&(D=null),this.delayLoadState=m.a.DELAYLOADSTATE_NONE,this._totalVertices=0,this._isDisposed=!1,this._indexBufferIsUpdatable=!1,this._positionsCache=[],this.useBoundingInfoFromGeometry=!1,this.id=l,this.uniqueId=h.getUniqueId(),this._engine=h.getEngine(),this._meshes=[],this._scene=h,this._vertexBuffers={},this._indices=[],this._updatable=E,v?this.setAllVerticesData(v,E):(this._totalVertices=0,this._indices=[]),this._engine.getCaps().vertexArrayObject&&(this._vertexArrayObjects={}),D&&(this.applyToMesh(D),D.computeWorldMatrix(!0))}return Object.defineProperty(g.prototype,"boundingBias",{get:function(){return this._boundingBias},set:function(l){this._boundingBias?this._boundingBias.copyFrom(l):this._boundingBias=l.clone(),this._updateBoundingInfo(!0,null)},enumerable:!1,configurable:!0}),g.CreateGeometryForMesh=function(l){var h=new g(g.RandomId(),l.getScene());return h.applyToMesh(l),h},Object.defineProperty(g.prototype,"meshes",{get:function(){return this._meshes},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"extend",{get:function(){return this._extend},enumerable:!1,configurable:!0}),g.prototype.getScene=function(){return this._scene},g.prototype.getEngine=function(){return this._engine},g.prototype.isReady=function(){return this.delayLoadState===m.a.DELAYLOADSTATE_LOADED||this.delayLoadState===m.a.DELAYLOADSTATE_NONE},Object.defineProperty(g.prototype,"doNotSerialize",{get:function(){for(var l=0;l<this._meshes.length;l++)if(!this._meshes[l].doNotSerialize)return!1;return!0},enumerable:!1,configurable:!0}),g.prototype._rebuild=function(){for(var l in this._vertexArrayObjects&&(this._vertexArrayObjects={}),this._meshes.length!==0&&this._indices&&(this._indexBuffer=this._engine.createIndexBuffer(this._indices)),this._vertexBuffers)this._vertexBuffers[l]._rebuild()},g.prototype.setAllVerticesData=function(l,h){l.applyToGeometry(this,h),this.notifyUpdate()},g.prototype.setVerticesData=function(l,h,v,E){v===void 0&&(v=!1),v&&Array.isArray(h)&&(h=new Float32Array(h));var D=new u.b(this._engine,h,l,v,this._meshes.length===0,E);this.setVerticesBuffer(D)},g.prototype.removeVerticesData=function(l){this._vertexBuffers[l]&&(this._vertexBuffers[l].dispose(),delete this._vertexBuffers[l])},g.prototype.setVerticesBuffer=function(l,h){h===void 0&&(h=null);var v=l.getKind();if(this._vertexBuffers[v]&&this._vertexBuffers[v].dispose(),this._vertexBuffers[v]=l,v===u.b.PositionKind){var E=l.getData();h!=null?this._totalVertices=h:E!=null&&(this._totalVertices=E.length/(l.byteStride/4)),this._updateExtend(E),this._resetPointsArrayCache();for(var D=this._meshes,w=D.length,N=0;N<w;N++){var I=D[N];I._boundingInfo=new x.a(this._extend.minimum,this._extend.maximum),I._createGlobalSubMesh(!1),I.computeWorldMatrix(!0)}}this.notifyUpdate(v),this._vertexArrayObjects&&(this._disposeVertexArrayObjects(),this._vertexArrayObjects={})},g.prototype.updateVerticesDataDirectly=function(l,h,v,E){E===void 0&&(E=!1);var D=this.getVertexBuffer(l);D&&(D.updateDirectly(h,v,E),this.notifyUpdate(l))},g.prototype.updateVerticesData=function(l,h,v){v===void 0&&(v=!1);var E=this.getVertexBuffer(l);E&&(E.update(h),l===u.b.PositionKind&&this._updateBoundingInfo(v,h),this.notifyUpdate(l))},g.prototype._updateBoundingInfo=function(l,h){if(l&&this._updateExtend(h),this._resetPointsArrayCache(),l)for(var v=0,E=this._meshes;v<E.length;v++){var D=E[v];D._boundingInfo?D._boundingInfo.reConstruct(this._extend.minimum,this._extend.maximum):D._boundingInfo=new x.a(this._extend.minimum,this._extend.maximum);for(var w=0,N=D.subMeshes;w<N.length;w++)N[w].refreshBoundingInfo()}},g.prototype._bind=function(l,h){if(l){h===void 0&&(h=this._indexBuffer);var v=this.getVertexBuffers();v&&(h==this._indexBuffer&&this._vertexArrayObjects?(this._vertexArrayObjects[l.key]||(this._vertexArrayObjects[l.key]=this._engine.recordVertexArrayObject(v,h,l)),this._engine.bindVertexArrayObject(this._vertexArrayObjects[l.key],h)):this._engine.bindBuffers(v,h,l))}},g.prototype.getTotalVertices=function(){return this.isReady()?this._totalVertices:0},g.prototype.getVerticesData=function(l,h,v){var E=this.getVertexBuffer(l);if(!E)return null;var D=E.getData();if(!D)return null;var w=E.getSize()*u.b.GetTypeByteLength(E.type),N=this._totalVertices*E.getSize();if(E.type!==u.b.FLOAT||E.byteStride!==w){var I=[];return E.forEach(N,function(te){return I.push(te)}),I}if(!(D instanceof Array||D instanceof Float32Array)||E.byteOffset!==0||D.length!==N){if(D instanceof Array){var V=E.byteOffset/4;return c.b.Slice(D,V,V+N)}if(D instanceof ArrayBuffer)return new Float32Array(D,E.byteOffset,N);if(V=D.byteOffset+E.byteOffset,v||h&&this._meshes.length!==1){var X=new Float32Array(N),j=new Float32Array(D.buffer,V,N);return X.set(j),X}var ne=V%4;return ne&&(V=Math.max(0,V-ne)),new Float32Array(D.buffer,V,N)}return v||h&&this._meshes.length!==1?c.b.Slice(D):D},g.prototype.isVertexBufferUpdatable=function(l){var h=this._vertexBuffers[l];return!!h&&h.isUpdatable()},g.prototype.getVertexBuffer=function(l){return this.isReady()?this._vertexBuffers[l]:null},g.prototype.getVertexBuffers=function(){return this.isReady()?this._vertexBuffers:null},g.prototype.isVerticesDataPresent=function(l){return this._vertexBuffers?this._vertexBuffers[l]!==void 0:!!this._delayInfo&&this._delayInfo.indexOf(l)!==-1},g.prototype.getVerticesDataKinds=function(){var l,h=[];if(!this._vertexBuffers&&this._delayInfo)for(l in this._delayInfo)h.push(l);else for(l in this._vertexBuffers)h.push(l);return h},g.prototype.updateIndices=function(l,h,v){if(v===void 0&&(v=!1),this._indexBuffer)if(this._indexBufferIsUpdatable){var E=l.length!==this._indices.length;if(v||(this._indices=l.slice()),this._engine.updateDynamicIndexBuffer(this._indexBuffer,l,h),E)for(var D=0,w=this._meshes;D<w.length;D++)w[D]._createGlobalSubMesh(!0)}else this.setIndices(l,null,!0)},g.prototype.setIndices=function(l,h,v){h===void 0&&(h=null),v===void 0&&(v=!1),this._indexBuffer&&this._engine._releaseBuffer(this._indexBuffer),this._disposeVertexArrayObjects(),this._indices=l,this._indexBufferIsUpdatable=v,this._meshes.length!==0&&this._indices&&(this._indexBuffer=this._engine.createIndexBuffer(this._indices,v)),h!=null&&(this._totalVertices=h);for(var E=0,D=this._meshes;E<D.length;E++)D[E]._createGlobalSubMesh(!0);this.notifyUpdate()},g.prototype.getTotalIndices=function(){return this.isReady()?this._indices.length:0},g.prototype.getIndices=function(l,h){if(!this.isReady())return null;var v=this._indices;if(h||l&&this._meshes.length!==1){for(var E=v.length,D=[],w=0;w<E;w++)D.push(v[w]);return D}return v},g.prototype.getIndexBuffer=function(){return this.isReady()?this._indexBuffer:null},g.prototype._releaseVertexArrayObject=function(l){l===void 0&&(l=null),l&&this._vertexArrayObjects&&this._vertexArrayObjects[l.key]&&(this._engine.releaseVertexArrayObject(this._vertexArrayObjects[l.key]),delete this._vertexArrayObjects[l.key])},g.prototype.releaseForMesh=function(l,h){var v=this._meshes,E=v.indexOf(l);E!==-1&&(v.splice(E,1),l._geometry=null,v.length===0&&h&&this.dispose())},g.prototype.applyToMesh=function(l){if(l._geometry!==this){var h=l._geometry;h&&h.releaseForMesh(l);var v=this._meshes;l._geometry=this,this._scene.pushGeometry(this),v.push(l),this.isReady()?this._applyToMesh(l):l._boundingInfo=this._boundingInfo}},g.prototype._updateExtend=function(l){l===void 0&&(l=null),this.useBoundingInfoFromGeometry&&this._boundingInfo?this._extend={minimum:this._boundingInfo.minimum.clone(),maximum:this._boundingInfo.maximum.clone()}:(l||(l=this.getVerticesData(u.b.PositionKind)),this._extend=Object(A.a)(l,0,this._totalVertices,this.boundingBias,3))},g.prototype._applyToMesh=function(l){var h=this._meshes.length;for(var v in this._vertexBuffers){h===1&&this._vertexBuffers[v].create();var E=this._vertexBuffers[v].getBuffer();E&&(E.references=h),v===u.b.PositionKind&&(this._extend||this._updateExtend(),l._boundingInfo=new x.a(this._extend.minimum,this._extend.maximum),l._createGlobalSubMesh(!1),l._updateBoundingInfo())}h===1&&this._indices&&this._indices.length>0&&(this._indexBuffer=this._engine.createIndexBuffer(this._indices)),this._indexBuffer&&(this._indexBuffer.references=h),l._syncGeometryWithMorphTargetManager(),l.synchronizeInstances()},g.prototype.notifyUpdate=function(l){this.onGeometryUpdated&&this.onGeometryUpdated(this,l);for(var h=0,v=this._meshes;h<v.length;h++)v[h]._markSubMeshesAsAttributesDirty()},g.prototype.load=function(l,h){this.delayLoadState!==m.a.DELAYLOADSTATE_LOADING&&(this.isReady()?h&&h():(this.delayLoadState=m.a.DELAYLOADSTATE_LOADING,this._queueLoad(l,h)))},g.prototype._queueLoad=function(l,h){var v=this;this.delayLoadingFile&&(l._addPendingData(this),l._loadFile(this.delayLoadingFile,function(E){if(v._delayLoadingFunction){v._delayLoadingFunction(JSON.parse(E),v),v.delayLoadState=m.a.DELAYLOADSTATE_LOADED,v._delayInfo=[],l._removePendingData(v);for(var D=v._meshes,w=D.length,N=0;N<w;N++)v._applyToMesh(D[N]);h&&h()}},void 0,!0))},g.prototype.toLeftHanded=function(){var l=this.getIndices(!1);if(l!=null&&l.length>0){for(var h=0;h<l.length;h+=3){var v=l[h+0];l[h+0]=l[h+2],l[h+2]=v}this.setIndices(l)}var E=this.getVerticesData(u.b.PositionKind,!1);if(E!=null&&E.length>0){for(h=0;h<E.length;h+=3)E[h+2]=-E[h+2];this.setVerticesData(u.b.PositionKind,E,!1)}var D=this.getVerticesData(u.b.NormalKind,!1);if(D!=null&&D.length>0){for(h=0;h<D.length;h+=3)D[h+2]=-D[h+2];this.setVerticesData(u.b.NormalKind,D,!1)}},g.prototype._resetPointsArrayCache=function(){this._positions=null},g.prototype._generatePointsArray=function(){if(this._positions)return!0;var l=this.getVerticesData(u.b.PositionKind);if(!l||l.length===0)return!1;for(var h=3*this._positionsCache.length,v=this._positionsCache.length;h<l.length;h+=3,++v)this._positionsCache[v]=U.e.FromArray(l,h);for(h=0,v=0;h<l.length;h+=3,++v)this._positionsCache[v].set(l[0+h],l[1+h],l[2+h]);return this._positionsCache.length=l.length/3,this._positions=this._positionsCache,!0},g.prototype.isDisposed=function(){return this._isDisposed},g.prototype._disposeVertexArrayObjects=function(){if(this._vertexArrayObjects){for(var l in this._vertexArrayObjects)this._engine.releaseVertexArrayObject(this._vertexArrayObjects[l]);this._vertexArrayObjects={}}},g.prototype.dispose=function(){var l,h=this._meshes,v=h.length;for(l=0;l<v;l++)this.releaseForMesh(h[l]);for(var E in this._meshes=[],this._disposeVertexArrayObjects(),this._vertexBuffers)this._vertexBuffers[E].dispose();this._vertexBuffers={},this._totalVertices=0,this._indexBuffer&&this._engine._releaseBuffer(this._indexBuffer),this._indexBuffer=null,this._indices=[],this.delayLoadState=m.a.DELAYLOADSTATE_NONE,this.delayLoadingFile=null,this._delayLoadingFunction=null,this._delayInfo=[],this._boundingInfo=null,this._scene.removeGeometry(this),this._isDisposed=!0},g.prototype.copy=function(l){var h=new C.a;h.indices=[];var v=this.getIndices();if(v)for(var E=0;E<v.length;E++)h.indices.push(v[E]);var D,w=!1,N=!1;for(D in this._vertexBuffers){var I=this.getVerticesData(D);if(I&&(I instanceof Float32Array?h.set(new Float32Array(I),D):h.set(I.slice(0),D),!N)){var V=this.getVertexBuffer(D);V&&(N=!(w=V.isUpdatable()))}}var X=new g(l,this._scene,h,w);for(D in X.delayLoadState=this.delayLoadState,X.delayLoadingFile=this.delayLoadingFile,X._delayLoadingFunction=this._delayLoadingFunction,this._delayInfo)X._delayInfo=X._delayInfo||[],X._delayInfo.push(D);return X._boundingInfo=new x.a(this._extend.minimum,this._extend.maximum),X},g.prototype.serialize=function(){var l={};return l.id=this.id,l.updatable=this._updatable,T.a&&T.a.HasTags(this)&&(l.tags=T.a.GetTags(this)),l},g.prototype.toNumberArray=function(l){return Array.isArray(l)?l:Array.prototype.slice.call(l)},g.prototype.serializeVerticeData=function(){var l=this.serialize();return this.isVerticesDataPresent(u.b.PositionKind)&&(l.positions=this.toNumberArray(this.getVerticesData(u.b.PositionKind)),this.isVertexBufferUpdatable(u.b.PositionKind)&&(l.positions._updatable=!0)),this.isVerticesDataPresent(u.b.NormalKind)&&(l.normals=this.toNumberArray(this.getVerticesData(u.b.NormalKind)),this.isVertexBufferUpdatable(u.b.NormalKind)&&(l.normals._updatable=!0)),this.isVerticesDataPresent(u.b.TangentKind)&&(l.tangets=this.toNumberArray(this.getVerticesData(u.b.TangentKind)),this.isVertexBufferUpdatable(u.b.TangentKind)&&(l.tangets._updatable=!0)),this.isVerticesDataPresent(u.b.UVKind)&&(l.uvs=this.toNumberArray(this.getVerticesData(u.b.UVKind)),this.isVertexBufferUpdatable(u.b.UVKind)&&(l.uvs._updatable=!0)),this.isVerticesDataPresent(u.b.UV2Kind)&&(l.uv2s=this.toNumberArray(this.getVerticesData(u.b.UV2Kind)),this.isVertexBufferUpdatable(u.b.UV2Kind)&&(l.uv2s._updatable=!0)),this.isVerticesDataPresent(u.b.UV3Kind)&&(l.uv3s=this.toNumberArray(this.getVerticesData(u.b.UV3Kind)),this.isVertexBufferUpdatable(u.b.UV3Kind)&&(l.uv3s._updatable=!0)),this.isVerticesDataPresent(u.b.UV4Kind)&&(l.uv4s=this.toNumberArray(this.getVerticesData(u.b.UV4Kind)),this.isVertexBufferUpdatable(u.b.UV4Kind)&&(l.uv4s._updatable=!0)),this.isVerticesDataPresent(u.b.UV5Kind)&&(l.uv5s=this.toNumberArray(this.getVerticesData(u.b.UV5Kind)),this.isVertexBufferUpdatable(u.b.UV5Kind)&&(l.uv5s._updatable=!0)),this.isVerticesDataPresent(u.b.UV6Kind)&&(l.uv6s=this.toNumberArray(this.getVerticesData(u.b.UV6Kind)),this.isVertexBufferUpdatable(u.b.UV6Kind)&&(l.uv6s._updatable=!0)),this.isVerticesDataPresent(u.b.ColorKind)&&(l.colors=this.toNumberArray(this.getVerticesData(u.b.ColorKind)),this.isVertexBufferUpdatable(u.b.ColorKind)&&(l.colors._updatable=!0)),this.isVerticesDataPresent(u.b.MatricesIndicesKind)&&(l.matricesIndices=this.toNumberArray(this.getVerticesData(u.b.MatricesIndicesKind)),l.matricesIndices._isExpanded=!0,this.isVertexBufferUpdatable(u.b.MatricesIndicesKind)&&(l.matricesIndices._updatable=!0)),this.isVerticesDataPresent(u.b.MatricesWeightsKind)&&(l.matricesWeights=this.toNumberArray(this.getVerticesData(u.b.MatricesWeightsKind)),this.isVertexBufferUpdatable(u.b.MatricesWeightsKind)&&(l.matricesWeights._updatable=!0)),l.indices=this.toNumberArray(this.getIndices()),l},g.ExtractFromMesh=function(l,h){var v=l._geometry;return v?v.copy(h):null},g.RandomId=function(){return c.b.RandomId()},g._ImportGeometry=function(l,h){var v=h.getScene(),E=l.geometryId;if(E){var D=v.getGeometryByID(E);D&&D.applyToMesh(h)}else if(l instanceof ArrayBuffer){var w=h._binaryInfo;if(w.positionsAttrDesc&&w.positionsAttrDesc.count>0){var N=new Float32Array(l,w.positionsAttrDesc.offset,w.positionsAttrDesc.count);h.setVerticesData(u.b.PositionKind,N,!1)}if(w.normalsAttrDesc&&w.normalsAttrDesc.count>0){var I=new Float32Array(l,w.normalsAttrDesc.offset,w.normalsAttrDesc.count);h.setVerticesData(u.b.NormalKind,I,!1)}if(w.tangetsAttrDesc&&w.tangetsAttrDesc.count>0){var V=new Float32Array(l,w.tangetsAttrDesc.offset,w.tangetsAttrDesc.count);h.setVerticesData(u.b.TangentKind,V,!1)}if(w.uvsAttrDesc&&w.uvsAttrDesc.count>0){var X=new Float32Array(l,w.uvsAttrDesc.offset,w.uvsAttrDesc.count);h.setVerticesData(u.b.UVKind,X,!1)}if(w.uvs2AttrDesc&&w.uvs2AttrDesc.count>0){var j=new Float32Array(l,w.uvs2AttrDesc.offset,w.uvs2AttrDesc.count);h.setVerticesData(u.b.UV2Kind,j,!1)}if(w.uvs3AttrDesc&&w.uvs3AttrDesc.count>0){var ne=new Float32Array(l,w.uvs3AttrDesc.offset,w.uvs3AttrDesc.count);h.setVerticesData(u.b.UV3Kind,ne,!1)}if(w.uvs4AttrDesc&&w.uvs4AttrDesc.count>0){var te=new Float32Array(l,w.uvs4AttrDesc.offset,w.uvs4AttrDesc.count);h.setVerticesData(u.b.UV4Kind,te,!1)}if(w.uvs5AttrDesc&&w.uvs5AttrDesc.count>0){var de=new Float32Array(l,w.uvs5AttrDesc.offset,w.uvs5AttrDesc.count);h.setVerticesData(u.b.UV5Kind,de,!1)}if(w.uvs6AttrDesc&&w.uvs6AttrDesc.count>0){var pe=new Float32Array(l,w.uvs6AttrDesc.offset,w.uvs6AttrDesc.count);h.setVerticesData(u.b.UV6Kind,pe,!1)}if(w.colorsAttrDesc&&w.colorsAttrDesc.count>0){var ae=new Float32Array(l,w.colorsAttrDesc.offset,w.colorsAttrDesc.count);h.setVerticesData(u.b.ColorKind,ae,!1,w.colorsAttrDesc.stride)}if(w.matricesIndicesAttrDesc&&w.matricesIndicesAttrDesc.count>0){for(var ee=new Int32Array(l,w.matricesIndicesAttrDesc.offset,w.matricesIndicesAttrDesc.count),K=[],$=0;$<ee.length;$++){var L=ee[$];K.push(255&L),K.push((65280&L)>>8),K.push((16711680&L)>>16),K.push(L>>24&255)}h.setVerticesData(u.b.MatricesIndicesKind,K,!1)}if(w.matricesIndicesExtraAttrDesc&&w.matricesIndicesExtraAttrDesc.count>0){for(ee=new Int32Array(l,w.matricesIndicesExtraAttrDesc.offset,w.matricesIndicesExtraAttrDesc.count),K=[],$=0;$<ee.length;$++)L=ee[$],K.push(255&L),K.push((65280&L)>>8),K.push((16711680&L)>>16),K.push(L>>24&255);h.setVerticesData(u.b.MatricesIndicesExtraKind,K,!1)}if(w.matricesWeightsAttrDesc&&w.matricesWeightsAttrDesc.count>0){var G=new Float32Array(l,w.matricesWeightsAttrDesc.offset,w.matricesWeightsAttrDesc.count);h.setVerticesData(u.b.MatricesWeightsKind,G,!1)}if(w.indicesAttrDesc&&w.indicesAttrDesc.count>0){var Q=new Int32Array(l,w.indicesAttrDesc.offset,w.indicesAttrDesc.count);h.setIndices(Q,null)}if(w.subMeshesAttrDesc&&w.subMeshesAttrDesc.count>0){var oe=new Int32Array(l,w.subMeshesAttrDesc.offset,5*w.subMeshesAttrDesc.count);for(h.subMeshes=[],$=0;$<w.subMeshesAttrDesc.count;$++){var re=oe[5*$+0],Y=oe[5*$+1],k=oe[5*$+2],H=oe[5*$+3],Z=oe[5*$+4];M.a.AddToMesh(re,Y,k,H,Z,h)}}}else if(l.positions&&l.normals&&l.indices){if(h.setVerticesData(u.b.PositionKind,l.positions,l.positions._updatable),h.setVerticesData(u.b.NormalKind,l.normals,l.normals._updatable),l.tangents&&h.setVerticesData(u.b.TangentKind,l.tangents,l.tangents._updatable),l.uvs&&h.setVerticesData(u.b.UVKind,l.uvs,l.uvs._updatable),l.uvs2&&h.setVerticesData(u.b.UV2Kind,l.uvs2,l.uvs2._updatable),l.uvs3&&h.setVerticesData(u.b.UV3Kind,l.uvs3,l.uvs3._updatable),l.uvs4&&h.setVerticesData(u.b.UV4Kind,l.uvs4,l.uvs4._updatable),l.uvs5&&h.setVerticesData(u.b.UV5Kind,l.uvs5,l.uvs5._updatable),l.uvs6&&h.setVerticesData(u.b.UV6Kind,l.uvs6,l.uvs6._updatable),l.colors&&h.setVerticesData(u.b.ColorKind,_.b.CheckColors4(l.colors,l.positions.length/3),l.colors._updatable),l.matricesIndices)if(l.matricesIndices._isExpanded)delete l.matricesIndices._isExpanded,h.setVerticesData(u.b.MatricesIndicesKind,l.matricesIndices,l.matricesIndices._updatable);else{for(K=[],$=0;$<l.matricesIndices.length;$++){var W=l.matricesIndices[$];K.push(255&W),K.push((65280&W)>>8),K.push((16711680&W)>>16),K.push(W>>24&255)}h.setVerticesData(u.b.MatricesIndicesKind,K,l.matricesIndices._updatable)}if(l.matricesIndicesExtra)if(l.matricesIndicesExtra._isExpanded)delete l.matricesIndices._isExpanded,h.setVerticesData(u.b.MatricesIndicesExtraKind,l.matricesIndicesExtra,l.matricesIndicesExtra._updatable);else{for(K=[],$=0;$<l.matricesIndicesExtra.length;$++)W=l.matricesIndicesExtra[$],K.push(255&W),K.push((65280&W)>>8),K.push((16711680&W)>>16),K.push(W>>24&255);h.setVerticesData(u.b.MatricesIndicesExtraKind,K,l.matricesIndicesExtra._updatable)}l.matricesWeights&&(g._CleanMatricesWeights(l,h),h.setVerticesData(u.b.MatricesWeightsKind,l.matricesWeights,l.matricesWeights._updatable)),l.matricesWeightsExtra&&h.setVerticesData(u.b.MatricesWeightsExtraKind,l.matricesWeightsExtra,l.matricesWeights._updatable),h.setIndices(l.indices,null)}if(l.subMeshes){h.subMeshes=[];for(var q=0;q<l.subMeshes.length;q++){var he=l.subMeshes[q];M.a.AddToMesh(he.materialIndex,he.verticesStart,he.verticesCount,he.indexStart,he.indexCount,h)}}h._shouldGenerateFlatShading&&(h.convertToFlatShadedMesh(),h._shouldGenerateFlatShading=!1),h.computeWorldMatrix(!0),v.onMeshImportedObservable.notifyObservers(h)},g._CleanMatricesWeights=function(l,h){if(R.a.CleanBoneMatrixWeights){var v=0;if(l.skeletonId>-1){var E=h.getScene().getLastSkeletonByID(l.skeletonId);if(E){v=E.bones.length;for(var D=h.getVerticesData(u.b.MatricesIndicesKind),w=h.getVerticesData(u.b.MatricesIndicesExtraKind),N=l.matricesWeights,I=l.matricesWeightsExtra,V=l.numBoneInfluencer,X=N.length,j=0;j<X;j+=4){for(var ne=0,te=-1,de=0;de<4;de++)ne+=pe=N[j+de],pe<.001&&te<0&&(te=de);if(I)for(de=0;de<4;de++){var pe;ne+=pe=I[j+de],pe<.001&&te<0&&(te=de+4)}if((te<0||te>V-1)&&(te=V-1),ne>.001){var ae=1/ne;for(de=0;de<4;de++)N[j+de]*=ae;if(I)for(de=0;de<4;de++)I[j+de]*=ae}else te>=4?(I[j+te-4]=1-ne,w[j+te-4]=v):(N[j+te]=1-ne,D[j+te]=v)}h.setVerticesData(u.b.MatricesIndicesKind,D),l.matricesWeightsExtra&&h.setVerticesData(u.b.MatricesIndicesExtraKind,w)}}}},g.Parse=function(l,h,v){if(h.getGeometryByID(l.id))return null;var E=new g(l.id,h,void 0,l.updatable);return T.a&&T.a.AddTagsTo(E,l.tags),l.delayLoadingFile?(E.delayLoadState=m.a.DELAYLOADSTATE_NOTLOADED,E.delayLoadingFile=v+l.delayLoadingFile,E._boundingInfo=new x.a(U.e.FromArray(l.boundingBoxMinimum),U.e.FromArray(l.boundingBoxMaximum)),E._delayInfo=[],l.hasUVs&&E._delayInfo.push(u.b.UVKind),l.hasUVs2&&E._delayInfo.push(u.b.UV2Kind),l.hasUVs3&&E._delayInfo.push(u.b.UV3Kind),l.hasUVs4&&E._delayInfo.push(u.b.UV4Kind),l.hasUVs5&&E._delayInfo.push(u.b.UV5Kind),l.hasUVs6&&E._delayInfo.push(u.b.UV6Kind),l.hasColors&&E._delayInfo.push(u.b.ColorKind),l.hasMatricesIndices&&E._delayInfo.push(u.b.MatricesIndicesKind),l.hasMatricesWeights&&E._delayInfo.push(u.b.MatricesWeightsKind),E._delayLoadingFunction=C.a.ImportVertexData):C.a.ImportVertexData(l,E),h.pushGeometry(E,!0),E},g}()},function(Me,y,f){f.d(y,"e",function(){return U}),f.d(y,"c",function(){return M}),f.d(y,"a",function(){return R}),f.d(y,"b",function(){return x}),f.d(y,"f",function(){return m}),f.d(y,"g",function(){return c}),f.d(y,"d",function(){return T});var U,_=f(14),C=f(0),u=f(28);(function(A){A[A.CW=0]="CW",A[A.CCW=1]="CCW"})(U||(U={}));var M=function(){function A(){}return A.Interpolate=function(S,g,l,h,v){for(var E=1-3*h+3*g,D=3*h-6*g,w=3*g,N=S,I=0;I<5;I++){var V=N*N;N-=(E*(V*N)+D*V+w*N-S)*(1/(3*E*V+2*D*N+w)),N=Math.min(1,Math.max(0,N))}return 3*Math.pow(1-N,2)*N*l+3*(1-N)*Math.pow(N,2)*v+Math.pow(N,3)},A}(),R=function(){function A(S){this._radians=S,this._radians<0&&(this._radians+=2*Math.PI)}return A.prototype.degrees=function(){return 180*this._radians/Math.PI},A.prototype.radians=function(){return this._radians},A.BetweenTwoPoints=function(S,g){var l=g.subtract(S);return new A(Math.atan2(l.y,l.x))},A.FromRadians=function(S){return new A(S)},A.FromDegrees=function(S){return new A(S*Math.PI/180)},A}(),x=function(A,S,g){this.startPoint=A,this.midPoint=S,this.endPoint=g;var l=Math.pow(S.x,2)+Math.pow(S.y,2),h=(Math.pow(A.x,2)+Math.pow(A.y,2)-l)/2,v=(l-Math.pow(g.x,2)-Math.pow(g.y,2))/2,E=(A.x-S.x)*(S.y-g.y)-(S.x-g.x)*(A.y-S.y);this.centerPoint=new C.d((h*(S.y-g.y)-v*(A.y-S.y))/E,((A.x-S.x)*v-(S.x-g.x)*h)/E),this.radius=this.centerPoint.subtract(this.startPoint).length(),this.startAngle=R.BetweenTwoPoints(this.centerPoint,this.startPoint);var D=this.startAngle.degrees(),w=R.BetweenTwoPoints(this.centerPoint,this.midPoint).degrees(),N=R.BetweenTwoPoints(this.centerPoint,this.endPoint).degrees();w-D>180&&(w-=360),w-D<-180&&(w+=360),N-w>180&&(N-=360),N-w<-180&&(N+=360),this.orientation=w-D<0?U.CW:U.CCW,this.angle=R.FromDegrees(this.orientation===U.CW?D-N:N-D)},m=function(){function A(S,g){this._points=new Array,this._length=0,this.closed=!1,this._points.push(new C.d(S,g))}return A.prototype.addLineTo=function(S,g){if(this.closed)return this;var l=new C.d(S,g),h=this._points[this._points.length-1];return this._points.push(l),this._length+=l.subtract(h).length(),this},A.prototype.addArcTo=function(S,g,l,h,v){if(v===void 0&&(v=36),this.closed)return this;var E=this._points[this._points.length-1],D=new C.d(S,g),w=new C.d(l,h),N=new x(E,D,w),I=N.angle.radians()/v;N.orientation===U.CW&&(I*=-1);for(var V=N.startAngle.radians()+I,X=0;X<v;X++){var j=Math.cos(V)*N.radius+N.centerPoint.x,ne=Math.sin(V)*N.radius+N.centerPoint.y;this.addLineTo(j,ne),V+=I}return this},A.prototype.close=function(){return this.closed=!0,this},A.prototype.length=function(){var S=this._length;if(this.closed){var g=this._points[this._points.length-1];S+=this._points[0].subtract(g).length()}return S},A.prototype.getPoints=function(){return this._points},A.prototype.getPointAtLengthPosition=function(S){if(S<0||S>1)return C.d.Zero();for(var g=S*this.length(),l=0,h=0;h<this._points.length;h++){var v=(h+1)%this._points.length,E=this._points[h],D=this._points[v].subtract(E),w=D.length()+l;if(g>=l&&g<=w){var N=D.normalize(),I=g-l;return new C.d(E.x+N.x*I,E.y+N.y*I)}l=w}return C.d.Zero()},A.StartingAt=function(S,g){return new A(S,g)},A}(),c=function(){function A(S,g,l,h){g===void 0&&(g=null),h===void 0&&(h=!1),this.path=S,this._curve=new Array,this._distances=new Array,this._tangents=new Array,this._normals=new Array,this._binormals=new Array,this._pointAtData={id:0,point:C.e.Zero(),previousPointArrayIndex:0,position:0,subPosition:0,interpolateReady:!1,interpolationMatrix:C.a.Identity()};for(var v=0;v<S.length;v++)this._curve[v]=S[v].clone();this._raw=l||!1,this._alignTangentsWithPath=h,this._compute(g,h)}return A.prototype.getCurve=function(){return this._curve},A.prototype.getPoints=function(){return this._curve},A.prototype.length=function(){return this._distances[this._distances.length-1]},A.prototype.getTangents=function(){return this._tangents},A.prototype.getNormals=function(){return this._normals},A.prototype.getBinormals=function(){return this._binormals},A.prototype.getDistances=function(){return this._distances},A.prototype.getPointAt=function(S){return this._updatePointAtData(S).point},A.prototype.getTangentAt=function(S,g){return g===void 0&&(g=!1),this._updatePointAtData(S,g),g?C.e.TransformCoordinates(C.e.Forward(),this._pointAtData.interpolationMatrix):this._tangents[this._pointAtData.previousPointArrayIndex]},A.prototype.getNormalAt=function(S,g){return g===void 0&&(g=!1),this._updatePointAtData(S,g),g?C.e.TransformCoordinates(C.e.Right(),this._pointAtData.interpolationMatrix):this._normals[this._pointAtData.previousPointArrayIndex]},A.prototype.getBinormalAt=function(S,g){return g===void 0&&(g=!1),this._updatePointAtData(S,g),g?C.e.TransformCoordinates(C.e.UpReadOnly,this._pointAtData.interpolationMatrix):this._binormals[this._pointAtData.previousPointArrayIndex]},A.prototype.getDistanceAt=function(S){return this.length()*S},A.prototype.getPreviousPointIndexAt=function(S){return this._updatePointAtData(S),this._pointAtData.previousPointArrayIndex},A.prototype.getSubPositionAt=function(S){return this._updatePointAtData(S),this._pointAtData.subPosition},A.prototype.getClosestPositionTo=function(S){for(var g=Number.MAX_VALUE,l=0,h=0;h<this._curve.length-1;h++){var v=this._curve[h+0],E=this._curve[h+1].subtract(v).normalize(),D=this._distances[h+1]-this._distances[h+0],w=Math.min(Math.max(C.e.Dot(E,S.subtract(v).normalize()),0)*C.e.Distance(v,S)/D,1),N=C.e.Distance(v.add(E.scale(w*D)),S);N<g&&(g=N,l=(this._distances[h+0]+D*w)/this.length())}return l},A.prototype.slice=function(S,g){if(S===void 0&&(S=0),g===void 0&&(g=1),S<0&&(S=1- -1*S%1),g<0&&(g=1- -1*g%1),S>g){var l=S;S=g,g=l}var h=this.getCurve(),v=this.getPointAt(S),E=this.getPreviousPointIndexAt(S),D=this.getPointAt(g),w=this.getPreviousPointIndexAt(g)+1,N=[];return S!==0&&(E++,N.push(v)),N.push.apply(N,h.slice(E,w)),g===1&&S!==1||N.push(D),new A(N,this.getNormalAt(S),this._raw,this._alignTangentsWithPath)},A.prototype.update=function(S,g,l){g===void 0&&(g=null),l===void 0&&(l=!1);for(var h=0;h<S.length;h++)this._curve[h].x=S[h].x,this._curve[h].y=S[h].y,this._curve[h].z=S[h].z;return this._compute(g,l),this},A.prototype._compute=function(S,g){g===void 0&&(g=!1);var l=this._curve.length;if(!(l<2)){this._tangents[0]=this._getFirstNonNullVector(0),this._raw||this._tangents[0].normalize(),this._tangents[l-1]=this._curve[l-1].subtract(this._curve[l-2]),this._raw||this._tangents[l-1].normalize();var h,v,E,D,w,N=this._tangents[0],I=this._normalVector(N,S);this._normals[0]=I,this._raw||this._normals[0].normalize(),this._binormals[0]=C.e.Cross(N,this._normals[0]),this._raw||this._binormals[0].normalize(),this._distances[0]=0;for(var V=1;V<l;V++)h=this._getLastNonNullVector(V),V<l-1&&(v=this._getFirstNonNullVector(V),this._tangents[V]=g?v:h.add(v),this._tangents[V].normalize()),this._distances[V]=this._distances[V-1]+this._curve[V].subtract(this._curve[V-1]).length(),E=this._tangents[V],w=this._binormals[V-1],this._normals[V]=C.e.Cross(w,E),this._raw||(this._normals[V].length()===0?(D=this._normals[V-1],this._normals[V]=D.clone()):this._normals[V].normalize()),this._binormals[V]=C.e.Cross(E,this._normals[V]),this._raw||this._binormals[V].normalize();this._pointAtData.id=NaN}},A.prototype._getFirstNonNullVector=function(S){for(var g=1,l=this._curve[S+g].subtract(this._curve[S]);l.length()===0&&S+g+1<this._curve.length;)g++,l=this._curve[S+g].subtract(this._curve[S]);return l},A.prototype._getLastNonNullVector=function(S){for(var g=1,l=this._curve[S].subtract(this._curve[S-g]);l.length()===0&&S>g+1;)g++,l=this._curve[S].subtract(this._curve[S-g]);return l},A.prototype._normalVector=function(S,g){var l,h,v=S.length();return v===0&&(v=1),g==null?(h=_.a.WithinEpsilon(Math.abs(S.y)/v,1,u.a)?_.a.WithinEpsilon(Math.abs(S.x)/v,1,u.a)?_.a.WithinEpsilon(Math.abs(S.z)/v,1,u.a)?C.e.Zero():new C.e(0,0,1):new C.e(1,0,0):new C.e(0,-1,0),l=C.e.Cross(S,h)):(l=C.e.Cross(S,g),C.e.CrossToRef(l,S,l)),l.normalize(),l},A.prototype._updatePointAtData=function(S,g){if(g===void 0&&(g=!1),this._pointAtData.id===S)return this._pointAtData.interpolateReady||this._updateInterpolationMatrix(),this._pointAtData;this._pointAtData.id=S;var l=this.getPoints();if(S<=0)return this._setPointAtData(0,0,l[0],0,g);if(S>=1)return this._setPointAtData(1,1,l[l.length-1],l.length-1,g);for(var h,v=l[0],E=0,D=S*this.length(),w=1;w<l.length;w++){h=l[w];var N=C.e.Distance(v,h);if((E+=N)===D)return this._setPointAtData(S,1,h,w,g);if(E>D){var I=(E-D)/N,V=v.subtract(h),X=h.add(V.scaleInPlace(I));return this._setPointAtData(S,1-I,X,w-1,g)}v=h}return this._pointAtData},A.prototype._setPointAtData=function(S,g,l,h,v){return this._pointAtData.point=l,this._pointAtData.position=S,this._pointAtData.subPosition=g,this._pointAtData.previousPointArrayIndex=h,this._pointAtData.interpolateReady=v,v&&this._updateInterpolationMatrix(),this._pointAtData},A.prototype._updateInterpolationMatrix=function(){this._pointAtData.interpolationMatrix=C.a.Identity();var S=this._pointAtData.previousPointArrayIndex;if(S!==this._tangents.length-1){var g=S+1,l=this._tangents[S].clone(),h=this._normals[S].clone(),v=this._binormals[S].clone(),E=this._tangents[g].clone(),D=this._normals[g].clone(),w=this._binormals[g].clone(),N=C.b.RotationQuaternionFromAxis(h,v,l),I=C.b.RotationQuaternionFromAxis(D,w,E);C.b.Slerp(N,I,this._pointAtData.subPosition).toRotationMatrix(this._pointAtData.interpolationMatrix)}},A}(),T=function(){function A(S){this._length=0,this._points=S,this._length=this._computeLength(S)}return A.CreateQuadraticBezier=function(S,g,l,h){h=h>2?h:3;for(var v=new Array,E=function(w,N,I,V){return(1-w)*(1-w)*N+2*w*(1-w)*I+w*w*V},D=0;D<=h;D++)v.push(new C.e(E(D/h,S.x,g.x,l.x),E(D/h,S.y,g.y,l.y),E(D/h,S.z,g.z,l.z)));return new A(v)},A.CreateCubicBezier=function(S,g,l,h,v){v=v>3?v:4;for(var E=new Array,D=function(N,I,V,X,j){return(1-N)*(1-N)*(1-N)*I+3*N*(1-N)*(1-N)*V+3*N*N*(1-N)*X+N*N*N*j},w=0;w<=v;w++)E.push(new C.e(D(w/v,S.x,g.x,l.x,h.x),D(w/v,S.y,g.y,l.y,h.y),D(w/v,S.z,g.z,l.z,h.z)));return new A(E)},A.CreateHermiteSpline=function(S,g,l,h,v){for(var E=new Array,D=1/v,w=0;w<=v;w++)E.push(C.e.Hermite(S,g,l,h,w*D));return new A(E)},A.CreateCatmullRomSpline=function(S,g,l){var h=new Array,v=1/g,E=0;if(l){for(var D=S.length,w=0;w<D;w++){E=0;for(var N=0;N<g;N++)h.push(C.e.CatmullRom(S[w%D],S[(w+1)%D],S[(w+2)%D],S[(w+3)%D],E)),E+=v}h.push(h[0])}else{var I=new Array;for(I.push(S[0].clone()),Array.prototype.push.apply(I,S),I.push(S[S.length-1].clone()),w=0;w<I.length-3;w++)for(E=0,N=0;N<g;N++)h.push(C.e.CatmullRom(I[w],I[w+1],I[w+2],I[w+3],E)),E+=v;w--,h.push(C.e.CatmullRom(I[w],I[w+1],I[w+2],I[w+3],E))}return new A(h)},A.prototype.getPoints=function(){return this._points},A.prototype.length=function(){return this._length},A.prototype.continue=function(S){for(var g=this._points[this._points.length-1],l=this._points.slice(),h=S.getPoints(),v=1;v<h.length;v++)l.push(h[v].subtract(h[0]).add(g));return new A(l)},A.prototype._computeLength=function(S){for(var g=0,l=1;l<S.length;l++)g+=S[l].subtract(S[l-1]).length();return g},A}()},function(Me,y,f){f.d(y,"a",function(){return l});var U=f(1),_=f(3),C=f(0),u=f(4),M=f(10),R=f(15),x=f(25),m=f(11),c=f(9),T=f(67),A=f(49),S=f(13),g={effect:null,subMesh:null},l=function(h){function v(E,D,w,N){N===void 0&&(N={});var I=h.call(this,E,D)||this;return I._textures={},I._textureArrays={},I._floats={},I._ints={},I._floatsArrays={},I._colors3={},I._colors3Arrays={},I._colors4={},I._colors4Arrays={},I._vectors2={},I._vectors3={},I._vectors4={},I._matrices={},I._matrixArrays={},I._matrices3x3={},I._matrices2x2={},I._vectors2Arrays={},I._vectors3Arrays={},I._vectors4Arrays={},I._cachedWorldViewMatrix=new C.a,I._cachedWorldViewProjectionMatrix=new C.a,I._multiview=!1,I._shaderPath=w,I._options=Object(U.a)({needAlphaBlending:!1,needAlphaTesting:!1,attributes:["position","normal","uv"],uniforms:["worldViewProjection"],uniformBuffers:[],samplers:[],defines:[]},N),I}return Object(U.d)(v,h),Object.defineProperty(v.prototype,"shaderPath",{get:function(){return this._shaderPath},set:function(E){this._shaderPath=E},enumerable:!1,configurable:!0}),Object.defineProperty(v.prototype,"options",{get:function(){return this._options},enumerable:!1,configurable:!0}),v.prototype.getClassName=function(){return"ShaderMaterial"},v.prototype.needAlphaBlending=function(){return this.alpha<1||this._options.needAlphaBlending},v.prototype.needAlphaTesting=function(){return this._options.needAlphaTesting},v.prototype._checkUniform=function(E){this._options.uniforms.indexOf(E)===-1&&this._options.uniforms.push(E)},v.prototype.setTexture=function(E,D){return this._options.samplers.indexOf(E)===-1&&this._options.samplers.push(E),this._textures[E]=D,this},v.prototype.setTextureArray=function(E,D){return this._options.samplers.indexOf(E)===-1&&this._options.samplers.push(E),this._checkUniform(E),this._textureArrays[E]=D,this},v.prototype.setFloat=function(E,D){return this._checkUniform(E),this._floats[E]=D,this},v.prototype.setInt=function(E,D){return this._checkUniform(E),this._ints[E]=D,this},v.prototype.setFloats=function(E,D){return this._checkUniform(E),this._floatsArrays[E]=D,this},v.prototype.setColor3=function(E,D){return this._checkUniform(E),this._colors3[E]=D,this},v.prototype.setColor3Array=function(E,D){return this._checkUniform(E),this._colors3Arrays[E]=D.reduce(function(w,N){return N.toArray(w,w.length),w},[]),this},v.prototype.setColor4=function(E,D){return this._checkUniform(E),this._colors4[E]=D,this},v.prototype.setColor4Array=function(E,D){return this._checkUniform(E),this._colors4Arrays[E]=D.reduce(function(w,N){return N.toArray(w,w.length),w},[]),this},v.prototype.setVector2=function(E,D){return this._checkUniform(E),this._vectors2[E]=D,this},v.prototype.setVector3=function(E,D){return this._checkUniform(E),this._vectors3[E]=D,this},v.prototype.setVector4=function(E,D){return this._checkUniform(E),this._vectors4[E]=D,this},v.prototype.setMatrix=function(E,D){return this._checkUniform(E),this._matrices[E]=D,this},v.prototype.setMatrices=function(E,D){this._checkUniform(E);for(var w=new Float32Array(16*D.length),N=0;N<D.length;N++)D[N].copyToArray(w,16*N);return this._matrixArrays[E]=w,this},v.prototype.setMatrix3x3=function(E,D){return this._checkUniform(E),this._matrices3x3[E]=D,this},v.prototype.setMatrix2x2=function(E,D){return this._checkUniform(E),this._matrices2x2[E]=D,this},v.prototype.setArray2=function(E,D){return this._checkUniform(E),this._vectors2Arrays[E]=D,this},v.prototype.setArray3=function(E,D){return this._checkUniform(E),this._vectors3Arrays[E]=D,this},v.prototype.setArray4=function(E,D){return this._checkUniform(E),this._vectors4Arrays[E]=D,this},v.prototype._checkCache=function(E,D){return!E||!this._effect||this._effect.defines.indexOf("#define INSTANCES")!==-1===D},v.prototype.isReadyForSubMesh=function(E,D,w){return this.isReady(E,w)},v.prototype.isReady=function(E,D){var w,N;if(this._effect&&this.isFrozen&&this._effect._wasPreviouslyReady)return!0;var I=this.getScene(),V=I.getEngine();if(!this.checkReadyOnEveryCall&&this._renderId===I.getRenderId()&&this._checkCache(E,D))return!0;var X=[],j=[],ne=new T.a;V.getCaps().multiview&&I.activeCamera&&I.activeCamera.outputRenderTarget&&I.activeCamera.outputRenderTarget.getViewCount()>1&&(this._multiview=!0,X.push("#define MULTIVIEW"),this._options.uniforms.indexOf("viewProjection")!==-1&&this._options.uniforms.push("viewProjectionR")===-1&&this._options.uniforms.push("viewProjectionR"));for(var te=0;te<this._options.defines.length;te++)X.push(this._options.defines[te]);for(te=0;te<this._options.attributes.length;te++)j.push(this._options.attributes[te]);E&&E.isVerticesDataPresent(u.b.ColorKind)&&(j.push(u.b.ColorKind),X.push("#define VERTEXCOLOR")),D&&(X.push("#define INSTANCES"),R.a.PushAttributesForInstances(j),E?.hasThinInstances&&X.push("#define THIN_INSTANCES"));var de=0;if(E&&E.useBones&&E.computeBonesUsingShaders&&E.skeleton){j.push(u.b.MatricesIndicesKind),j.push(u.b.MatricesWeightsKind),E.numBoneInfluencers>4&&(j.push(u.b.MatricesIndicesExtraKind),j.push(u.b.MatricesWeightsExtraKind));var pe=E.skeleton;de=E.numBoneInfluencers,X.push("#define NUM_BONE_INFLUENCERS "+de),ne.addCPUSkinningFallback(0,E),pe.isUsingTextureForMatrices?(X.push("#define BONETEXTURE"),this._options.uniforms.indexOf("boneTextureWidth")===-1&&this._options.uniforms.push("boneTextureWidth"),this._options.samplers.indexOf("boneSampler")===-1&&this._options.samplers.push("boneSampler")):(X.push("#define BonesPerMesh "+(pe.bones.length+1)),this._options.uniforms.indexOf("mBones")===-1&&this._options.uniforms.push("mBones"))}else X.push("#define NUM_BONE_INFLUENCERS 0");for(var ae in this._textures)if(!this._textures[ae].isReady())return!1;E&&this._shouldTurnAlphaTestOn(E)&&X.push("#define ALPHATEST");var ee=this._shaderPath,K=this._options.uniforms,$=this._options.uniformBuffers,L=this._options.samplers;this.customShaderNameResolve&&(K=K.slice(),$=$.slice(),L=L.slice(),ee=this.customShaderNameResolve(ee,K,$,L,X,j));var G=this._effect,Q=X.join(`
-`);return this._cachedDefines!==Q&&(this._cachedDefines=Q,this._effect=V.createEffect(ee,{attributes:j,uniformsNames:K,uniformBuffersNames:$,samplers:L,defines:Q,fallbacks:ne,onCompiled:this.onCompiled,onError:this.onError,indexParameters:{maxSimultaneousMorphTargets:de}},V),this._onEffectCreatedObservable&&(g.effect=this._effect,this._onEffectCreatedObservable.notifyObservers(g))),(N=!(!((w=this._effect)===null||w===void 0)&&w.isReady()))!==null&&N!==void 0&&!N&&(G!==this._effect&&I.resetCachedMaterial(),this._renderId=I.getRenderId(),this._effect._wasPreviouslyReady=!0,!0)},v.prototype.bindOnlyWorldMatrix=function(E,D){var w=this.getScene(),N=D??this._effect;N&&(this._options.uniforms.indexOf("world")!==-1&&N.setMatrix("world",E),this._options.uniforms.indexOf("worldView")!==-1&&(E.multiplyToRef(w.getViewMatrix(),this._cachedWorldViewMatrix),N.setMatrix("worldView",this._cachedWorldViewMatrix)),this._options.uniforms.indexOf("worldViewProjection")!==-1&&(E.multiplyToRef(w.getTransformMatrix(),this._cachedWorldViewProjectionMatrix),N.setMatrix("worldViewProjection",this._cachedWorldViewProjectionMatrix)))},v.prototype.bindForSubMesh=function(E,D,w){this.bind(E,D,w._effectOverride)},v.prototype.bind=function(E,D,w){this.bindOnlyWorldMatrix(E,w);var N=w??this._effect;if(N&&this.getScene().getCachedMaterial()!==this){var I;for(I in this._options.uniforms.indexOf("view")!==-1&&N.setMatrix("view",this.getScene().getViewMatrix()),this._options.uniforms.indexOf("projection")!==-1&&N.setMatrix("projection",this.getScene().getProjectionMatrix()),this._options.uniforms.indexOf("viewProjection")!==-1&&(N.setMatrix("viewProjection",this.getScene().getTransformMatrix()),this._multiview&&N.setMatrix("viewProjectionR",this.getScene()._transformMatrixR)),this.getScene().activeCamera&&this._options.uniforms.indexOf("cameraPosition")!==-1&&N.setVector3("cameraPosition",this.getScene().activeCamera.globalPosition),R.a.BindBonesParameters(D,N),this._textures)N.setTexture(I,this._textures[I]);for(I in this._textureArrays)N.setTextureArray(I,this._textureArrays[I]);for(I in this._ints)N.setInt(I,this._ints[I]);for(I in this._floats)N.setFloat(I,this._floats[I]);for(I in this._floatsArrays)N.setArray(I,this._floatsArrays[I]);for(I in this._colors3)N.setColor3(I,this._colors3[I]);for(I in this._colors3Arrays)N.setArray3(I,this._colors3Arrays[I]);for(I in this._colors4){var V=this._colors4[I];N.setFloat4(I,V.r,V.g,V.b,V.a)}for(I in this._colors4Arrays)N.setArray4(I,this._colors4Arrays[I]);for(I in this._vectors2)N.setVector2(I,this._vectors2[I]);for(I in this._vectors3)N.setVector3(I,this._vectors3[I]);for(I in this._vectors4)N.setVector4(I,this._vectors4[I]);for(I in this._matrices)N.setMatrix(I,this._matrices[I]);for(I in this._matrixArrays)N.setMatrices(I,this._matrixArrays[I]);for(I in this._matrices3x3)N.setMatrix3x3(I,this._matrices3x3[I]);for(I in this._matrices2x2)N.setMatrix2x2(I,this._matrices2x2[I]);for(I in this._vectors2Arrays)N.setArray2(I,this._vectors2Arrays[I]);for(I in this._vectors3Arrays)N.setArray3(I,this._vectors3Arrays[I]);for(I in this._vectors4Arrays)N.setArray4(I,this._vectors4Arrays[I])}var X=this._effect;this._effect=N,this._afterBind(D),this._effect=X},v.prototype._afterBind=function(E){h.prototype._afterBind.call(this,E),this.getScene()._cachedEffect=this._effect},v.prototype.getActiveTextures=function(){var E=h.prototype.getActiveTextures.call(this);for(var D in this._textures)E.push(this._textures[D]);for(var D in this._textureArrays)for(var w=this._textureArrays[D],N=0;N<w.length;N++)E.push(w[N]);return E},v.prototype.hasTexture=function(E){if(h.prototype.hasTexture.call(this,E))return!0;for(var D in this._textures)if(this._textures[D]===E)return!0;for(var D in this._textureArrays)for(var w=this._textureArrays[D],N=0;N<w.length;N++)if(w[N]===E)return!0;return!1},v.prototype.clone=function(E){var D=this,w=_.a.Clone(function(){return new v(E,D.getScene(),D._shaderPath,D._options)},this);for(var N in w.name=E,w.id=E,typeof w._shaderPath=="object"&&(w._shaderPath=Object(U.a)({},w._shaderPath)),this._options=Object(U.a)({},this._options),Object.keys(this._options).forEach(function(I){var V=D._options[I];Array.isArray(V)&&(D._options[I]=V.slice(0))}),this._textures)w.setTexture(N,this._textures[N]);for(var N in this._floats)w.setFloat(N,this._floats[N]);for(var N in this._floatsArrays)w.setFloats(N,this._floatsArrays[N]);for(var N in this._colors3)w.setColor3(N,this._colors3[N]);for(var N in this._colors4)w.setColor4(N,this._colors4[N]);for(var N in this._vectors2)w.setVector2(N,this._vectors2[N]);for(var N in this._vectors3)w.setVector3(N,this._vectors3[N]);for(var N in this._vectors4)w.setVector4(N,this._vectors4[N]);for(var N in this._matrices)w.setMatrix(N,this._matrices[N]);for(var N in this._matrices3x3)w.setMatrix3x3(N,this._matrices3x3[N]);for(var N in this._matrices2x2)w.setMatrix2x2(N,this._matrices2x2[N]);return w},v.prototype.dispose=function(E,D,w){if(D){var N;for(N in 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H,Z,W=null,q=null;for(v=0;v<l+k;v++){for(pe[v]=0,te[v]=[0],h=0;h<m.length-1;h++)oe=m[h],re=m[h+1],v===l?(W=oe[0],q=re[0]):(W=oe[v],q=re[v]),Q=q.subtract(W).length()+pe[v],te[v].push(Q),pe[v]=Q;c&&q&&W&&(oe=m[h],re=m[0],v===l&&(q=re[0]),Q=q.subtract(W).length()+pe[v],pe[v]=Q)}if(w)for(h=0;h<w.length;h++)j.push(w[h].x,w[h].y);else for(h=0;h<m.length;h++)for(v=0;v<l+k;v++)H=de[h]!=0?ne[h][v]/de[h]:0,Z=pe[v]!=0?te[v][h]/pe[v]:0,A?j.push(Z,H):j.push(H,Z);for(var he=0,ge=ae[h=0]-1,me=ae[h+1]-1,_e=ge<me?ge:me,be=ee[1]-ee[0],Pe=c?ae.length:ae.length-1;he<=_e&&h<Pe;)V.push(he,he+be,he+1),V.push(he+be+1,he+1,he+be),(he+=1)===_e&&(++h===ae.length-1?(be=ee[0]-ee[h],ge=ae[h]-1,me=ae[0]-1):(be=ee[h+1]-ee[h],ge=ae[h]-1,me=ae[h+1]-1),he=ee[h],_e=ge<me?ge+he:me+he);if(u.a.ComputeNormals(I,V,X),T){var ye=0,Be=0;for(h=0;h<m.length;h++)ye=3*ee[h],Be=h+1<m.length?3*(ee[h+1]-1):X.length-3,X[ye]=.5*(X[ye]+X[Be]),X[ye+1]=.5*(X[ye+1]+X[Be+1]),X[ye+2]=.5*(X[ye+2]+X[Be+2]),X[Be]=X[ye],X[Be+1]=X[ye+1],X[Be+2]=X[ye+2]}u.a._ComputeSides(D,I,V,X,j,x.frontUVs,x.backUVs);var ke=null;if(N){ke=new Float32Array(4*N.length);for(var We=0;We<N.length;We++)ke[4*We]=N[We].r,ke[4*We+1]=N[We].g,ke[4*We+2]=N[We].b,ke[4*We+3]=N[We].a}var je=new u.a,He=new Float32Array(I),qe=new Float32Array(X),Ge=new Float32Array(j);return je.indices=V,je.positions=He,je.normals=qe,je.uvs=Ge,ke&&je.set(ke,C.b.ColorKind),T&&(je._idx=ee),je},_.a.CreateRibbon=function(x,m,c,T,A,S,g,l,h){return c===void 0&&(c=!1),g===void 0&&(g=!1),R.CreateRibbon(x,{pathArray:m,closeArray:c,closePath:T,offset:A,updatable:g,sideOrientation:l,instance:h},S)};var R=function(){function x(){}return x.CreateRibbon=function(m,c,T){T===void 0&&(T=null);var A=c.pathArray,S=c.closeArray,g=c.closePath,l=_.a._GetDefaultSideOrientation(c.sideOrientation),h=c.instance,v=c.updatable;if(h){var E=U.c.Vector3[0].setAll(Number.MAX_VALUE),D=U.c.Vector3[1].setAll(-Number.MAX_VALUE),w=h.getVerticesData(C.b.PositionKind);if(function(G){for(var Q=A[0].length,oe=h,re=0,Y=oe._originalBuilderSideOrientation===_.a.DOUBLESIDE?2:1,k=1;k<=Y;++k)for(var H=0;H<A.length;++H){var Z=A[H],W=Z.length;Q=Q<W?Q:W;for(var q=0;q<Q;++q){var he=Z[q];G[re]=he.x,G[re+1]=he.y,G[re+2]=he.z,E.minimizeInPlaceFromFloats(he.x,he.y,he.z),D.maximizeInPlaceFromFloats(he.x,he.y,he.z),re+=3}oe._creationDataStorage&&oe._creationDataStorage.closePath&&(he=Z[0],G[re]=he.x,G[re+1]=he.y,G[re+2]=he.z,re+=3)}}(w),h._boundingInfo?h._boundingInfo.reConstruct(E,D,h._worldMatrix):h._boundingInfo=new M.a(E,D,h._worldMatrix),h.updateVerticesData(C.b.PositionKind,w,!1,!1),c.colors){for(var N=h.getVerticesData(C.b.ColorKind),I=0,V=0;I<c.colors.length;I++,V+=4){var X=c.colors[I];N[V]=X.r,N[V+1]=X.g,N[V+2]=X.b,N[V+3]=X.a}h.updateVerticesData(C.b.ColorKind,N,!1,!1)}if(c.uvs){for(var j=h.getVerticesData(C.b.UVKind),ne=0;ne<c.uvs.length;ne++)j[2*ne]=c.uvs[ne].x,j[2*ne+1]=c.uvs[ne].y;h.updateVerticesData(C.b.UVKind,j,!1,!1)}if(!h.areNormalsFrozen||h.isFacetDataEnabled){var te=h.getIndices(),de=h.getVerticesData(C.b.NormalKind),pe=h.isFacetDataEnabled?h.getFacetDataParameters():null;if(u.a.ComputeNormals(w,te,de,pe),h._creationDataStorage&&h._creationDataStorage.closePath)for(var ae=0,ee=0,K=0;K<A.length;K++)ae=3*h._creationDataStorage.idx[K],ee=K+1<A.length?3*(h._creationDataStorage.idx[K+1]-1):de.length-3,de[ae]=.5*(de[ae]+de[ee]),de[ae+1]=.5*(de[ae+1]+de[ee+1]),de[ae+2]=.5*(de[ae+2]+de[ee+2]),de[ee]=de[ae],de[ee+1]=de[ae+1],de[ee+2]=de[ae+2];h.areNormalsFrozen||h.updateVerticesData(C.b.NormalKind,de,!1,!1)}return h}var $=new _.a(m,T);$._originalBuilderSideOrientation=l,$._creationDataStorage=new _.b;var L=u.a.CreateRibbon(c);return g&&($._creationDataStorage.idx=L._idx),$._creationDataStorage.closePath=g,$._creationDataStorage.closeArray=S,L.applyToMesh($,v),$},x}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.FilesToLoad={},_}()},function(Me,y,f){f.d(y,"a",function(){return C});var U=f(7),_=f(16);_.a.CreatePlane=function(u){var M=[],R=[],x=[],m=[],c=u.width||u.size||1,T=u.height||u.size||1,A=u.sideOrientation===0?0:u.sideOrientation||_.a.DEFAULTSIDE,S=c/2,g=T/2;R.push(-S,-g,0),x.push(0,0,-1),m.push(0,0),R.push(S,-g,0),x.push(0,0,-1),m.push(1,0),R.push(S,g,0),x.push(0,0,-1),m.push(1,1),R.push(-S,g,0),x.push(0,0,-1),m.push(0,1),M.push(0),M.push(1),M.push(2),M.push(0),M.push(2),M.push(3),_.a._ComputeSides(A,R,M,x,m,u.frontUVs,u.backUVs);var l=new _.a;return l.indices=M,l.positions=R,l.normals=x,l.uvs=m,l},U.a.CreatePlane=function(u,M,R,x,m){var c={size:M,width:M,height:M,sideOrientation:m,updatable:x};return C.CreatePlane(u,c,R)};var C=function(){function u(){}return u.CreatePlane=function(M,R,x){x===void 0&&(x=null);var m=new U.a(M,x);return R.sideOrientation=U.a._GetDefaultSideOrientation(R.sideOrientation),m._originalBuilderSideOrientation=R.sideOrientation,_.a.CreatePlane(R).applyToMesh(m,R.updatable),R.sourcePlane&&(m.translate(R.sourcePlane.normal,-R.sourcePlane.d),m.setDirection(R.sourcePlane.normal.scale(-1))),m},u}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(8),_=(f(153),function(){function C(u,M,R){this._alreadyBound=!1,this._valueCache={},this._engine=u,this._noUBO=!u.supportsUniformBuffers,this._dynamic=R,this._data=M||[],this._uniformLocations={},this._uniformSizes={},this._uniformLocationPointer=0,this._needSync=!1,this._noUBO?(this.updateMatrix3x3=this._updateMatrix3x3ForEffect,this.updateMatrix2x2=this._updateMatrix2x2ForEffect,this.updateFloat=this._updateFloatForEffect,this.updateFloat2=this._updateFloat2ForEffect,this.updateFloat3=this._updateFloat3ForEffect,this.updateFloat4=this._updateFloat4ForEffect,this.updateMatrix=this._updateMatrixForEffect,this.updateVector3=this._updateVector3ForEffect,this.updateVector4=this._updateVector4ForEffect,this.updateColor3=this._updateColor3ForEffect,this.updateColor4=this._updateColor4ForEffect):(this._engine._uniformBuffers.push(this),this.updateMatrix3x3=this._updateMatrix3x3ForUniform,this.updateMatrix2x2=this._updateMatrix2x2ForUniform,this.updateFloat=this._updateFloatForUniform,this.updateFloat2=this._updateFloat2ForUniform,this.updateFloat3=this._updateFloat3ForUniform,this.updateFloat4=this._updateFloat4ForUniform,this.updateMatrix=this._updateMatrixForUniform,this.updateVector3=this._updateVector3ForUniform,this.updateVector4=this._updateVector4ForUniform,this.updateColor3=this._updateColor3ForUniform,this.updateColor4=this._updateColor4ForUniform)}return Object.defineProperty(C.prototype,"useUbo",{get:function(){return!this._noUBO},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"isSync",{get:function(){return!this._needSync},enumerable:!1,configurable:!0}),C.prototype.isDynamic=function(){return this._dynamic!==void 0},C.prototype.getData=function(){return this._bufferData},C.prototype.getBuffer=function(){return this._buffer},C.prototype._fillAlignment=function(u){var M;if(M=u<=2?u:4,this._uniformLocationPointer%M!=0){var R=this._uniformLocationPointer;this._uniformLocationPointer+=M-this._uniformLocationPointer%M;for(var x=this._uniformLocationPointer-R,m=0;m<x;m++)this._data.push(0)}},C.prototype.addUniform=function(u,M){if(!this._noUBO&&this._uniformLocations[u]===void 0){var R;if(M instanceof Array)M=(R=M).length;else{M=M,R=[];for(var x=0;x<M;x++)R.push(0)}for(this._fillAlignment(M),this._uniformSizes[u]=M,this._uniformLocations[u]=this._uniformLocationPointer,this._uniformLocationPointer+=M,x=0;x<M;x++)this._data.push(R[x]);this._needSync=!0}},C.prototype.addMatrix=function(u,M){this.addUniform(u,Array.prototype.slice.call(M.toArray()))},C.prototype.addFloat2=function(u,M,R){var x=[M,R];this.addUniform(u,x)},C.prototype.addFloat3=function(u,M,R,x){var m=[M,R,x];this.addUniform(u,m)},C.prototype.addColor3=function(u,M){var R=new Array;M.toArray(R),this.addUniform(u,R)},C.prototype.addColor4=function(u,M,R){var x=new Array;M.toArray(x),x.push(R),this.addUniform(u,x)},C.prototype.addVector3=function(u,M){var R=new Array;M.toArray(R),this.addUniform(u,R)},C.prototype.addMatrix3x3=function(u){this.addUniform(u,12)},C.prototype.addMatrix2x2=function(u){this.addUniform(u,8)},C.prototype.create=function(){this._noUBO||this._buffer||(this._fillAlignment(4),this._bufferData=new Float32Array(this._data),this._rebuild(),this._needSync=!0)},C.prototype._rebuild=function(){!this._noUBO&&this._bufferData&&(this._dynamic?this._buffer=this._engine.createDynamicUniformBuffer(this._bufferData):this._buffer=this._engine.createUniformBuffer(this._bufferData))},C.prototype.update=function(){this._buffer?(this._dynamic||this._needSync)&&(this._engine.updateUniformBuffer(this._buffer,this._bufferData),this._needSync=!1):this.create()},C.prototype.updateUniform=function(u,M,R){var x=this._uniformLocations[u];if(x===void 0){if(this._buffer)return void U.a.Error("Cannot add an uniform after UBO has been created.");this.addUniform(u,R),x=this._uniformLocations[u]}if(this._buffer||this.create(),this._dynamic)for(c=0;c<R;c++)this._bufferData[x+c]=M[c];else{for(var m=!1,c=0;c<R;c++)R!==16&&this._bufferData[x+c]===M[c]||(m=!0,this._bufferData[x+c]=M[c]);this._needSync=this._needSync||m}},C.prototype._cacheMatrix=function(u,M){var R=this._valueCache[u],x=M.updateFlag;return(R===void 0||R!==x)&&(this._valueCache[u]=x,!0)},C.prototype._updateMatrix3x3ForUniform=function(u,M){for(var R=0;R<3;R++)C._tempBuffer[4*R]=M[3*R],C._tempBuffer[4*R+1]=M[3*R+1],C._tempBuffer[4*R+2]=M[3*R+2],C._tempBuffer[4*R+3]=0;this.updateUniform(u,C._tempBuffer,12)},C.prototype._updateMatrix3x3ForEffect=function(u,M){this._currentEffect.setMatrix3x3(u,M)},C.prototype._updateMatrix2x2ForEffect=function(u,M){this._currentEffect.setMatrix2x2(u,M)},C.prototype._updateMatrix2x2ForUniform=function(u,M){for(var R=0;R<2;R++)C._tempBuffer[4*R]=M[2*R],C._tempBuffer[4*R+1]=M[2*R+1],C._tempBuffer[4*R+2]=0,C._tempBuffer[4*R+3]=0;this.updateUniform(u,C._tempBuffer,8)},C.prototype._updateFloatForEffect=function(u,M){this._currentEffect.setFloat(u,M)},C.prototype._updateFloatForUniform=function(u,M){C._tempBuffer[0]=M,this.updateUniform(u,C._tempBuffer,1)},C.prototype._updateFloat2ForEffect=function(u,M,R,x){x===void 0&&(x=""),this._currentEffect.setFloat2(u+x,M,R)},C.prototype._updateFloat2ForUniform=function(u,M,R){C._tempBuffer[0]=M,C._tempBuffer[1]=R,this.updateUniform(u,C._tempBuffer,2)},C.prototype._updateFloat3ForEffect=function(u,M,R,x,m){m===void 0&&(m=""),this._currentEffect.setFloat3(u+m,M,R,x)},C.prototype._updateFloat3ForUniform=function(u,M,R,x){C._tempBuffer[0]=M,C._tempBuffer[1]=R,C._tempBuffer[2]=x,this.updateUniform(u,C._tempBuffer,3)},C.prototype._updateFloat4ForEffect=function(u,M,R,x,m,c){c===void 0&&(c=""),this._currentEffect.setFloat4(u+c,M,R,x,m)},C.prototype._updateFloat4ForUniform=function(u,M,R,x,m){C._tempBuffer[0]=M,C._tempBuffer[1]=R,C._tempBuffer[2]=x,C._tempBuffer[3]=m,this.updateUniform(u,C._tempBuffer,4)},C.prototype._updateMatrixForEffect=function(u,M){this._currentEffect.setMatrix(u,M)},C.prototype._updateMatrixForUniform=function(u,M){this._cacheMatrix(u,M)&&this.updateUniform(u,M.toArray(),16)},C.prototype._updateVector3ForEffect=function(u,M){this._currentEffect.setVector3(u,M)},C.prototype._updateVector3ForUniform=function(u,M){M.toArray(C._tempBuffer),this.updateUniform(u,C._tempBuffer,3)},C.prototype._updateVector4ForEffect=function(u,M){this._currentEffect.setVector4(u,M)},C.prototype._updateVector4ForUniform=function(u,M){M.toArray(C._tempBuffer),this.updateUniform(u,C._tempBuffer,4)},C.prototype._updateColor3ForEffect=function(u,M,R){R===void 0&&(R=""),this._currentEffect.setColor3(u+R,M)},C.prototype._updateColor3ForUniform=function(u,M){M.toArray(C._tempBuffer),this.updateUniform(u,C._tempBuffer,3)},C.prototype._updateColor4ForEffect=function(u,M,R,x){x===void 0&&(x=""),this._currentEffect.setColor4(u+x,M,R)},C.prototype._updateColor4ForUniform=function(u,M,R){M.toArray(C._tempBuffer),C._tempBuffer[3]=R,this.updateUniform(u,C._tempBuffer,4)},C.prototype.setTexture=function(u,M){this._currentEffect.setTexture(u,M)},C.prototype.updateUniformDirectly=function(u,M){this.updateUniform(u,M,M.length),this.update()},C.prototype.bindToEffect=function(u,M){this._currentEffect=u,!this._noUBO&&this._buffer&&(this._alreadyBound=!0,u.bindUniformBuffer(this._buffer,M))},C.prototype.dispose=function(){if(!this._noUBO){var u=this._engine._uniformBuffers,M=u.indexOf(this);M!==-1&&(u[M]=u[u.length-1],u.pop()),this._buffer&&this._engine._releaseBuffer(this._buffer)&&(this._buffer=null)}},C._MAX_UNIFORM_SIZE=256,C._tempBuffer=new Float32Array(C._MAX_UNIFORM_SIZE),C}())},function(Me,y,f){f.d(y,"a",function(){return x});var U=f(1),_=f(3),C=f(0),u=f(9),M=f(29),R=f(48);M.a.AddNodeConstructor("Light_Type_3",function(m,c){return function(){return new x(m,C.e.Zero(),c)}});var x=function(m){function c(T,A,S){var g=m.call(this,T,S)||this;return g.groundColor=new u.a(0,0,0),g.direction=A||C.e.Up(),g}return Object(U.d)(c,m),c.prototype._buildUniformLayout=function(){this._uniformBuffer.addUniform("vLightData",4),this._uniformBuffer.addUniform("vLightDiffuse",4),this._uniformBuffer.addUniform("vLightSpecular",4),this._uniformBuffer.addUniform("vLightGround",3),this._uniformBuffer.addUniform("shadowsInfo",3),this._uniformBuffer.addUniform("depthValues",2),this._uniformBuffer.create()},c.prototype.getClassName=function(){return"HemisphericLight"},c.prototype.setDirectionToTarget=function(T){return this.direction=C.e.Normalize(T.subtract(C.e.Zero())),this.direction},c.prototype.getShadowGenerator=function(){return null},c.prototype.transferToEffect=function(T,A){var S=C.e.Normalize(this.direction);return this._uniformBuffer.updateFloat4("vLightData",S.x,S.y,S.z,0,A),this._uniformBuffer.updateColor3("vLightGround",this.groundColor.scale(this.intensity),A),this},c.prototype.transferToNodeMaterialEffect=function(T,A){var S=C.e.Normalize(this.direction);return T.setFloat3(A,S.x,S.y,S.z),this},c.prototype.computeWorldMatrix=function(){return this._worldMatrix||(this._worldMatrix=C.a.Identity()),this._worldMatrix},c.prototype.getTypeID=function(){return R.a.LIGHTTYPEID_HEMISPHERICLIGHT},c.prototype.prepareLightSpecificDefines=function(T,A){T["HEMILIGHT"+A]=!0},Object(U.c)([Object(_.e)()],c.prototype,"groundColor",void 0),Object(U.c)([Object(_.o)()],c.prototype,"direction",void 0),c}(R.a)},function(Me,y,f){f.d(y,"a",function(){return C});var U=f(1),_=f(0),C=function(u){function M(R,x){var m=u.call(this,R,x)||this;return m._normalMatrix=new _.a,m._storeEffectOnSubMeshes=!0,m}return Object(U.d)(M,u),M.prototype.getEffect=function(){return this._activeEffect},M.prototype.isReady=function(R,x){return!!R&&(!R.subMeshes||R.subMeshes.length===0||this.isReadyForSubMesh(R,R.subMeshes[0],x))},M.prototype._isReadyForSubMesh=function(R){var x=R._materialDefines;return!(this.checkReadyOnEveryCall||!R.effect||!x||x._renderId!==this.getScene().getRenderId())},M.prototype.bindOnlyWorldMatrix=function(R){this._activeEffect.setMatrix("world",R)},M.prototype.bindOnlyNormalMatrix=function(R){this._activeEffect.setMatrix("normalMatrix",R)},M.prototype.bind=function(R,x){x&&this.bindForSubMesh(R,x,x.subMeshes[0])},M.prototype._afterBind=function(R,x){x===void 0&&(x=null),u.prototype._afterBind.call(this,R),this.getScene()._cachedEffect=x},M.prototype._mustRebind=function(R,x,m){return m===void 0&&(m=1),R.isCachedMaterialInvalid(this,x,m)},M}(f(25).a)},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(1),_=function(C){function u(M){var R=C.call(this)||this;return R._buffer=M,R}return Object(U.d)(u,C),Object.defineProperty(u.prototype,"underlyingResource",{get:function(){return this._buffer},enumerable:!1,configurable:!0}),u}(f(89).a)},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){this.references=0,this.capacity=0,this.is32Bits=!1}return Object.defineProperty(_.prototype,"underlyingResource",{get:function(){return null},enumerable:!1,configurable:!0}),_}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(64),_=function(){function C(){}return C.GetPlanes=function(u){for(var M=[],R=0;R<6;R++)M.push(new U.a(0,0,0,0));return C.GetPlanesToRef(u,M),M},C.GetNearPlaneToRef=function(u,M){var R=u.m;M.normal.x=R[3]+R[2],M.normal.y=R[7]+R[6],M.normal.z=R[11]+R[10],M.d=R[15]+R[14],M.normalize()},C.GetFarPlaneToRef=function(u,M){var R=u.m;M.normal.x=R[3]-R[2],M.normal.y=R[7]-R[6],M.normal.z=R[11]-R[10],M.d=R[15]-R[14],M.normalize()},C.GetLeftPlaneToRef=function(u,M){var R=u.m;M.normal.x=R[3]+R[0],M.normal.y=R[7]+R[4],M.normal.z=R[11]+R[8],M.d=R[15]+R[12],M.normalize()},C.GetRightPlaneToRef=function(u,M){var R=u.m;M.normal.x=R[3]-R[0],M.normal.y=R[7]-R[4],M.normal.z=R[11]-R[8],M.d=R[15]-R[12],M.normalize()},C.GetTopPlaneToRef=function(u,M){var R=u.m;M.normal.x=R[3]-R[1],M.normal.y=R[7]-R[5],M.normal.z=R[11]-R[9],M.d=R[15]-R[13],M.normalize()},C.GetBottomPlaneToRef=function(u,M){var R=u.m;M.normal.x=R[3]+R[1],M.normal.y=R[7]+R[5],M.normal.z=R[11]+R[9],M.d=R[15]+R[13],M.normalize()},C.GetPlanesToRef=function(u,M){C.GetNearPlaneToRef(u,M[0]),C.GetFarPlaneToRef(u,M[1]),C.GetLeftPlaneToRef(u,M[2]),C.GetRightPlaneToRef(u,M[3]),C.GetTopPlaneToRef(u,M[4]),C.GetBottomPlaneToRef(u,M[5])},C}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(2),_=function(){function C(){this.hoverCursor="",this.actions=new Array,this.isRecursive=!1}return Object.defineProperty(C,"HasTriggers",{get:function(){for(var u in C.Triggers)if(C.Triggers.hasOwnProperty(u))return!0;return!1},enumerable:!1,configurable:!0}),Object.defineProperty(C,"HasPickTriggers",{get:function(){for(var u in C.Triggers)if(C.Triggers.hasOwnProperty(u)){var M=parseInt(u);if(M>=U.a.ACTION_OnPickTrigger&&M<=U.a.ACTION_OnPickUpTrigger)return!0}return!1},enumerable:!1,configurable:!0}),C.HasSpecificTrigger=function(u){for(var M in C.Triggers)if(C.Triggers.hasOwnProperty(M)&&parseInt(M)===u)return!0;return!1},C.Triggers={},C}()},function(Me,y,f){f.d(y,"a",function(){return R});var U=f(1),_=f(25),C=f(3),u=f(19),M=f(15),R=function(){function x(m){this._texture=null,this.diffuseBlendLevel=1,this.roughnessBlendLevel=1,this.bumpLevel=1,this._normalBlendMethod=_.a.MATERIAL_NORMALBLENDMETHOD_WHITEOUT,this._isEnabled=!1,this.isEnabled=!1,this._internalMarkAllSubMeshesAsTexturesDirty=m}return x.prototype._markAllSubMeshesAsTexturesDirty=function(){this._internalMarkAllSubMeshesAsTexturesDirty()},x.prototype.isReadyForSubMesh=function(m,c){var T=c.getEngine();return!(m._areTexturesDirty&&c.texturesEnabled&&T.getCaps().standardDerivatives&&this._texture&&u.a.DetailTextureEnabled&&!this._texture.isReady())},x.prototype.prepareDefines=function(m,c){if(this._isEnabled){m.DETAIL_NORMALBLENDMETHOD=this._normalBlendMethod;var T=c.getEngine();m._areTexturesDirty&&(T.getCaps().standardDerivatives&&this._texture&&u.a.DetailTextureEnabled&&this._isEnabled?(M.a.PrepareDefinesForMergedUV(this._texture,m,"DETAIL"),m.DETAIL_NORMALBLENDMETHOD=this._normalBlendMethod):m.DETAIL=!1)}else m.DETAIL=!1},x.prototype.bindForSubMesh=function(m,c,T){this._isEnabled&&(m.useUbo&&T&&m.isSync||this._texture&&u.a.DetailTextureEnabled&&(m.updateFloat4("vDetailInfos",this._texture.coordinatesIndex,this.diffuseBlendLevel,this.bumpLevel,this.roughnessBlendLevel),M.a.BindTextureMatrix(this._texture,m,"detail")),c.texturesEnabled&&this._texture&&u.a.DetailTextureEnabled&&m.setTexture("detailSampler",this._texture))},x.prototype.hasTexture=function(m){return this._texture===m},x.prototype.getActiveTextures=function(m){this._texture&&m.push(this._texture)},x.prototype.getAnimatables=function(m){this._texture&&this._texture.animations&&this._texture.animations.length>0&&m.push(this._texture)},x.prototype.dispose=function(m){var c;m&&((c=this._texture)===null||c===void 0||c.dispose())},x.prototype.getClassName=function(){return"DetailMap"},x.AddUniforms=function(m){m.push("vDetailInfos")},x.AddSamplers=function(m){m.push("detailSampler")},x.PrepareUniformBuffer=function(m){m.addUniform("vDetailInfos",4),m.addUniform("detailMatrix",16)},x.prototype.copyTo=function(m){C.a.Clone(function(){return m},this)},x.prototype.serialize=function(){return C.a.Serialize(this)},x.prototype.parse=function(m,c,T){var A=this;C.a.Parse(function(){return A},m,c,T)},Object(U.c)([Object(C.m)("detailTexture"),Object(C.b)("_markAllSubMeshesAsTexturesDirty")],x.prototype,"texture",void 0),Object(U.c)([Object(C.c)()],x.prototype,"diffuseBlendLevel",void 0),Object(U.c)([Object(C.c)()],x.prototype,"roughnessBlendLevel",void 0),Object(U.c)([Object(C.c)()],x.prototype,"bumpLevel",void 0),Object(U.c)([Object(C.c)(),Object(C.b)("_markAllSubMeshesAsTexturesDirty")],x.prototype,"normalBlendMethod",void 0),Object(U.c)([Object(C.c)(),Object(C.b)("_markAllSubMeshesAsTexturesDirty")],x.prototype,"isEnabled",void 0),x}()},function(Me,y,f){var U="morphTargetsVertexGlobalDeclaration",_=`#ifdef MORPHTARGETS
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-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="morphTargetsVertexDeclaration",_=`#ifdef MORPHTARGETS
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-#ifdef MORPHTARGETS_NORMAL
-attribute vec3 normal{X};
-#endif
-#ifdef MORPHTARGETS_TANGENT
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-#ifdef MORPHTARGETS_UV
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c!=null}))||x.length===0||!this._scene.postProcessesEnabled)&&(x[0].activate(m,R,x!=null),!0)},M.prototype.directRender=function(R,x,m,c,T,A){x===void 0&&(x=null),m===void 0&&(m=!1),c===void 0&&(c=0),T===void 0&&(T=0),A===void 0&&(A=!1);for(var S=this._scene.getEngine(),g=0;g<R.length;g++){g<R.length-1?R[g+1].activate(this._scene.activeCamera,x):x?S.bindFramebuffer(x,c,void 0,void 0,m,T):A||S.restoreDefaultFramebuffer();var l=R[g],h=l.apply();h&&(l.onBeforeRenderObservable.notifyObservers(h),this._prepareBuffers(),S.bindBuffers(this._vertexBuffers,this._indexBuffer,h),S.drawElementsType(U.a.TriangleFillMode,0,6),l.onAfterRenderObservable.notifyObservers(h))}S.setDepthBuffer(!0),S.setDepthWrite(!0)},M.prototype._finalizeFrame=function(R,x,m,c,T){T===void 0&&(T=!1);var A=this._scene.activeCamera;if(A&&(c=c||A._postProcesses.filter(function(E){return E!=null})).length!==0&&this._scene.postProcessesEnabled){for(var S=this._scene.getEngine(),g=0,l=c.length;g<l;g++){var h=c[g];if(g<l-1?h._outputTexture=c[g+1].activate(A,x):x?(S.bindFramebuffer(x,m,void 0,void 0,T),h._outputTexture=x):(S.restoreDefaultFramebuffer(),h._outputTexture=null),R)break;var v=h.apply();v&&(h.onBeforeRenderObservable.notifyObservers(v),this._prepareBuffers(),S.bindBuffers(this._vertexBuffers,this._indexBuffer,v),S.drawElementsType(U.a.TriangleFillMode,0,6),h.onAfterRenderObservable.notifyObservers(v))}S.setDepthBuffer(!0),S.setDepthWrite(!0),S.setAlphaMode(C.a.ALPHA_DISABLE)}},M.prototype.dispose=function(){var R=this._vertexBuffers[_.b.PositionKind];R&&(R.dispose(),this._vertexBuffers[_.b.PositionKind]=null),this._indexBuffer&&(this._scene.getEngine()._releaseBuffer(this._indexBuffer),this._indexBuffer=null)},M}()},function(Me,y,f){f.d(y,"a",function(){return _}),f.d(y,"b",function(){return C});var U=f(148),_=function(){},C=function(){function u(M){this._useSceneAutoClearSetup=!1,this._renderingGroups=new Array,this._autoClearDepthStencil={},this._customOpaqueSortCompareFn={},this._customAlphaTestSortCompareFn={},this._customTransparentSortCompareFn={},this._renderingGroupInfo=new _,this._scene=M;for(var R=u.MIN_RENDERINGGROUPS;R<u.MAX_RENDERINGGROUPS;R++)this._autoClearDepthStencil[R]={autoClear:!0,depth:!0,stencil:!0}}return u.prototype._clearDepthStencilBuffer=function(M,R){M===void 0&&(M=!0),R===void 0&&(R=!0),this._depthStencilBufferAlreadyCleaned||(this._scene.getEngine().clear(null,!1,M,R),this._depthStencilBufferAlreadyCleaned=!0)},u.prototype.render=function(M,R,x,m){var c=this._renderingGroupInfo;if(c.scene=this._scene,c.camera=this._scene.activeCamera,this._scene.spriteManagers&&m)for(var T=0;T<this._scene.spriteManagers.length;T++){var A=this._scene.spriteManagers[T];this.dispatchSprites(A)}for(T=u.MIN_RENDERINGGROUPS;T<u.MAX_RENDERINGGROUPS;T++){this._depthStencilBufferAlreadyCleaned=T===u.MIN_RENDERINGGROUPS;var S=this._renderingGroups[T];if(S){var g=Math.pow(2,T);if(c.renderingGroupId=T,this._scene.onBeforeRenderingGroupObservable.notifyObservers(c,g),u.AUTOCLEAR){var l=this._useSceneAutoClearSetup?this._scene.getAutoClearDepthStencilSetup(T):this._autoClearDepthStencil[T];l&&l.autoClear&&this._clearDepthStencilBuffer(l.depth,l.stencil)}for(var h=0,v=this._scene._beforeRenderingGroupDrawStage;h<v.length;h++)v[h].action(T);S.render(M,m,x,R);for(var E=0,D=this._scene._afterRenderingGroupDrawStage;E<D.length;E++)D[E].action(T);this._scene.onAfterRenderingGroupObservable.notifyObservers(c,g)}}},u.prototype.reset=function(){for(var M=u.MIN_RENDERINGGROUPS;M<u.MAX_RENDERINGGROUPS;M++){var R=this._renderingGroups[M];R&&R.prepare()}},u.prototype.dispose=function(){this.freeRenderingGroups(),this._renderingGroups.length=0,this._renderingGroupInfo=null},u.prototype.freeRenderingGroups=function(){for(var M=u.MIN_RENDERINGGROUPS;M<u.MAX_RENDERINGGROUPS;M++){var R=this._renderingGroups[M];R&&R.dispose()}},u.prototype._prepareRenderingGroup=function(M){this._renderingGroups[M]===void 0&&(this._renderingGroups[M]=new U.a(M,this._scene,this._customOpaqueSortCompareFn[M],this._customAlphaTestSortCompareFn[M],this._customTransparentSortCompareFn[M]))},u.prototype.dispatchSprites=function(M){var R=M.renderingGroupId||0;this._prepareRenderingGroup(R),this._renderingGroups[R].dispatchSprites(M)},u.prototype.dispatchParticles=function(M){var R=M.renderingGroupId||0;this._prepareRenderingGroup(R),this._renderingGroups[R].dispatchParticles(M)},u.prototype.dispatch=function(M,R,x){R===void 0&&(R=M.getMesh());var m=R.renderingGroupId||0;this._prepareRenderingGroup(m),this._renderingGroups[m].dispatch(M,R,x)},u.prototype.setRenderingOrder=function(M,R,x,m){if(R===void 0&&(R=null),x===void 0&&(x=null),m===void 0&&(m=null),this._customOpaqueSortCompareFn[M]=R,this._customAlphaTestSortCompareFn[M]=x,this._customTransparentSortCompareFn[M]=m,this._renderingGroups[M]){var c=this._renderingGroups[M];c.opaqueSortCompareFn=this._customOpaqueSortCompareFn[M],c.alphaTestSortCompareFn=this._customAlphaTestSortCompareFn[M],c.transparentSortCompareFn=this._customTransparentSortCompareFn[M]}},u.prototype.setRenderingAutoClearDepthStencil=function(M,R,x,m){x===void 0&&(x=!0),m===void 0&&(m=!0),this._autoClearDepthStencil[M]={autoClear:R,depth:x,stencil:m}},u.prototype.getAutoClearDepthStencilSetup=function(M){return this._autoClearDepthStencil[M]},u.MAX_RENDERINGGROUPS=4,u.MIN_RENDERINGGROUPS=0,u.AUTOCLEAR=!0,u}()},function(Me,y,f){f.d(y,"a",function(){return M});var U=f(0),_=f(7),C=f(82),u=f(72);_.a.ExtrudeShape=function(R,x,m,c,T,A,S,g,l,h){S===void 0&&(S=null);var v={shape:x,path:m,scale:c,rotation:T,cap:A===0?0:A||_.a.NO_CAP,sideOrientation:l,instance:h,updatable:g};return M.ExtrudeShape(R,v,S)},_.a.ExtrudeShapeCustom=function(R,x,m,c,T,A,S,g,l,h,v,E){var D={shape:x,path:m,scaleFunction:c,rotationFunction:T,ribbonCloseArray:A,ribbonClosePath:S,cap:g===0?0:g||_.a.NO_CAP,sideOrientation:v,instance:E,updatable:h};return M.ExtrudeShapeCustom(R,D,l)};var M=function(){function R(){}return R.ExtrudeShape=function(x,m,c){c===void 0&&(c=null);var T=m.path,A=m.shape,S=m.scale||1,g=m.rotation||0,l=m.cap===0?0:m.cap||_.a.NO_CAP,h=m.updatable,v=_.a._GetDefaultSideOrientation(m.sideOrientation),E=m.instance||null,D=m.invertUV||!1;return R._ExtrudeShapeGeneric(x,A,T,S,g,null,null,!1,!1,l,!1,c,!!h,v,E,D,m.frontUVs||null,m.backUVs||null)},R.ExtrudeShapeCustom=function(x,m,c){c===void 0&&(c=null);var T=m.path,A=m.shape,S=m.scaleFunction||function(){return 1},g=m.rotationFunction||function(){return 0},l=m.ribbonCloseArray||!1,h=m.ribbonClosePath||!1,v=m.cap===0?0:m.cap||_.a.NO_CAP,E=m.updatable,D=_.a._GetDefaultSideOrientation(m.sideOrientation),w=m.instance,N=m.invertUV||!1;return R._ExtrudeShapeGeneric(x,A,T,null,null,S,g,l,h,v,!0,c,!!E,D,w||null,N,m.frontUVs||null,m.backUVs||null)},R._ExtrudeShapeGeneric=function(x,m,c,T,A,S,g,l,h,v,E,D,w,N,I,V,X,j){var ne,te,de=function(ee,K,$,L,G,Q,oe,re,Y,k){for(var H=$.getTangents(),Z=$.getNormals(),W=$.getBinormals(),q=$.getDistances(),he=0,ge=k&&re?re:function(){return Q!==null?Q:0},me=k&&oe?oe:function(){return G!==null?G:1},_e=Y===_.a.NO_CAP||Y===_.a.CAP_END?0:2,be=U.c.Matrix[0],Pe=0;Pe<K.length;Pe++){for(var ye=new Array,Be=ge(Pe,q[Pe]),ke=me(Pe,q[Pe]),We=0;We<ee.length;We++){U.a.RotationAxisToRef(H[Pe],he,be);var je=H[Pe].scale(ee[We].z).add(Z[Pe].scale(ee[We].x)).add(W[Pe].scale(ee[We].y)),He=ye[We]?ye[We]:U.e.Zero();U.e.TransformCoordinatesToRef(je,be,He),He.scaleInPlace(ke).addInPlace(K[Pe]),ye[We]=He}L[_e]=ye,he+=Be,_e++}var qe=function(Ge){var nt,$e=Array(),lt=U.e.Zero();for(nt=0;nt<Ge.length;nt++)lt.addInPlace(Ge[nt]);for(lt.scaleInPlace(1/Ge.length),nt=0;nt<Ge.length;nt++)$e.push(lt);return $e};switch(Y){case _.a.NO_CAP:break;case _.a.CAP_START:L[0]=qe(L[2]),L[1]=L[2];break;case _.a.CAP_END:L[_e]=L[_e-1],L[_e+1]=qe(L[_e-1]);break;case _.a.CAP_ALL:L[0]=qe(L[2]),L[1]=L[2],L[_e]=L[_e-1],L[_e+1]=qe(L[_e-1])}return L};if(I){var pe=I._creationDataStorage;return ne=pe.path3D.update(c),te=de(m,c,pe.path3D,pe.pathArray,T,A,S,g,pe.cap,E),I=_.a.CreateRibbon("",te,!1,!1,0,D||void 0,!1,0,I)}te=de(m,c,ne=new u.g(c),new Array,T,A,S,g,v=v<0||v>3?0:v,E);var ae=C.a.CreateRibbon(x,{pathArray:te,closeArray:l,closePath:h,updatable:w,sideOrientation:N,invertUV:V,frontUVs:X||void 0,backUVs:j||void 0},D);return ae._creationDataStorage.pathArray=te,ae._creationDataStorage.path3D=ne,ae._creationDataStorage.cap=v,ae},R}()},function(Me,y,f){f.d(y,"b",function(){return c}),f.d(y,"a",function(){return T});var U=f(1),_=f(9),C=f(4),u=f(7),M=f(151),R=f(25),x=f(73),m=f(15),c=(f(166),f(167),function(A){function S(g,l,h,v,E,D,w){l===void 0&&(l=null),h===void 0&&(h=null),v===void 0&&(v=null);var N=A.call(this,g,l,h,v,E)||this;N.useVertexColor=D,N.useVertexAlpha=w,N.color=new _.a(1,1,1),N.alpha=1,v&&(N.color=v.color.clone(),N.alpha=v.alpha,N.useVertexColor=v.useVertexColor,N.useVertexAlpha=v.useVertexAlpha),N.intersectionThreshold=.1;var I={attributes:[C.b.PositionKind,"world0","world1","world2","world3"],uniforms:["vClipPlane","vClipPlane2","vClipPlane3","vClipPlane4","vClipPlane5","vClipPlane6","world","viewProjection"],needAlphaBlending:!0,defines:[]};return w===!1&&(I.needAlphaBlending=!1),D?(I.defines.push("#define VERTEXCOLOR"),I.attributes.push(C.b.ColorKind)):(I.uniforms.push("color"),N.color4=new _.b),N._colorShader=new x.a("colorShader",N.getScene(),"color",I),N}return Object(U.d)(S,A),S.prototype._addClipPlaneDefine=function(g){var l="#define "+g;this._colorShader.options.defines.indexOf(l)===-1&&this._colorShader.options.defines.push(l)},S.prototype._removeClipPlaneDefine=function(g){var l="#define "+g,h=this._colorShader.options.defines.indexOf(l);h!==-1&&this._colorShader.options.defines.splice(h,1)},S.prototype.isReady=function(){var g=this.getScene();return g.clipPlane?this._addClipPlaneDefine("CLIPPLANE"):this._removeClipPlaneDefine("CLIPPLANE"),g.clipPlane2?this._addClipPlaneDefine("CLIPPLANE2"):this._removeClipPlaneDefine("CLIPPLANE2"),g.clipPlane3?this._addClipPlaneDefine("CLIPPLANE3"):this._removeClipPlaneDefine("CLIPPLANE3"),g.clipPlane4?this._addClipPlaneDefine("CLIPPLANE4"):this._removeClipPlaneDefine("CLIPPLANE4"),g.clipPlane5?this._addClipPlaneDefine("CLIPPLANE5"):this._removeClipPlaneDefine("CLIPPLANE5"),g.clipPlane6?this._addClipPlaneDefine("CLIPPLANE6"):this._removeClipPlaneDefine("CLIPPLANE6"),!!this._colorShader.isReady(this)&&A.prototype.isReady.call(this)},S.prototype.getClassName=function(){return"LinesMesh"},Object.defineProperty(S.prototype,"material",{get:function(){return this._colorShader},set:function(g){},enumerable:!1,configurable:!0}),Object.defineProperty(S.prototype,"checkCollisions",{get:function(){return!1},enumerable:!1,configurable:!0}),S.prototype._bind=function(g,l,h){if(!this._geometry)return this;var v=this._colorShader.getEffect(),E=this.isUnIndexed?null:this._geometry.getIndexBuffer();if(this._geometry._bind(v,E),!this.useVertexColor){var D=this.color,w=D.r,N=D.g,I=D.b;this.color4.set(w,N,I,this.alpha),this._colorShader.setColor4("color",this.color4)}return m.a.BindClipPlane(v,this.getScene()),this},S.prototype._draw=function(g,l,h){if(!this._geometry||!this._geometry.getVertexBuffers()||!this._unIndexed&&!this._geometry.getIndexBuffer())return this;var v=this.getScene().getEngine();return this._unIndexed?v.drawArraysType(R.a.LineListDrawMode,g.verticesStart,g.verticesCount,h):v.drawElementsType(R.a.LineListDrawMode,g.indexStart,g.indexCount,h),this},S.prototype.dispose=function(g){this._colorShader.dispose(!1,!1,!0),A.prototype.dispose.call(this,g)},S.prototype.clone=function(g,l,h){return l===void 0&&(l=null),new S(g,this.getScene(),l,this,h)},S.prototype.createInstance=function(g){return new T(g,this)},S}(u.a)),T=function(A){function S(g,l){var h=A.call(this,g,l)||this;return h.intersectionThreshold=l.intersectionThreshold,h}return Object(U.d)(S,A),S.prototype.getClassName=function(){return"InstancedLinesMesh"},S}(M.a)},function(Me,y,f){f.r(y),f.d(y,"AxesViewer",function(){return R}),f.d(y,"BoneAxesViewer",function(){return c}),f.d(y,"DebugLayerTab",function(){return U}),f.d(y,"DebugLayer",function(){return l}),f.d(y,"PhysicsViewer",function(){return V}),f.d(y,"RayHelper",function(){return j}),f.d(y,"SkeletonViewer",function(){return K});var U,_=f(0),C=f(30),u=f(75),M=f(9),R=function(){function $(L,G,Q,oe,re,Y){if(G===void 0&&(G=1),Q===void 0&&(Q=2),this._scaleLinesFactor=4,this._instanced=!1,this.scene=null,this.scaleLines=1,this.scaleLines=G,!oe){var k=new C.a("",L);k.disableLighting=!0,k.emissiveColor=M.a.Red().scale(.5),oe=u.a._CreateArrow(L,k)}if(!re){var H=new C.a("",L);H.disableLighting=!0,H.emissiveColor=M.a.Green().scale(.5),re=u.a._CreateArrow(L,H)}if(!Y){var Z=new C.a("",L);Z.disableLighting=!0,Z.emissiveColor=M.a.Blue().scale(.5),Y=u.a._CreateArrow(L,Z)}this._xAxis=oe,this._xAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor),this._yAxis=re,this._yAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor),this._zAxis=Y,this._zAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor),Q!=null&&($._SetRenderingGroupId(this._xAxis,Q),$._SetRenderingGroupId(this._yAxis,Q),$._SetRenderingGroupId(this._zAxis,Q)),this.scene=L,this.update(new _.e,_.e.Right(),_.e.Up(),_.e.Forward())}return Object.defineProperty($.prototype,"xAxis",{get:function(){return this._xAxis},enumerable:!1,configurable:!0}),Object.defineProperty($.prototype,"yAxis",{get:function(){return this._yAxis},enumerable:!1,configurable:!0}),Object.defineProperty($.prototype,"zAxis",{get:function(){return this._zAxis},enumerable:!1,configurable:!0}),$.prototype.update=function(L,G,Q,oe){this._xAxis.position.copyFrom(L),this._xAxis.setDirection(G),this._xAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor),this._yAxis.position.copyFrom(L),this._yAxis.setDirection(Q),this._yAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor),this._zAxis.position.copyFrom(L),this._zAxis.setDirection(oe),this._zAxis.scaling.setAll(this.scaleLines*this._scaleLinesFactor)},$.prototype.createInstance=function(){var L=u.a._CreateArrowInstance(this.scene,this._xAxis),G=u.a._CreateArrowInstance(this.scene,this._yAxis),Q=u.a._CreateArrowInstance(this.scene,this._zAxis),oe=new $(this.scene,this.scaleLines,null,L,G,Q);return oe._instanced=!0,oe},$.prototype.dispose=function(){this._xAxis&&this._xAxis.dispose(!1,!this._instanced),this._yAxis&&this._yAxis.dispose(!1,!this._instanced),this._zAxis&&this._zAxis.dispose(!1,!this._instanced),this.scene=null},$._SetRenderingGroupId=function(L,G){L.getChildMeshes().forEach(function(Q){Q.renderingGroupId=G})},$}(),x=f(1),m=f(23),c=function($){function L(G,Q,oe,re){re===void 0&&(re=1);var Y=$.call(this,G,re)||this;return Y.pos=_.e.Zero(),Y.xaxis=_.e.Zero(),Y.yaxis=_.e.Zero(),Y.zaxis=_.e.Zero(),Y.mesh=oe,Y.bone=Q,Y}return Object(x.d)(L,$),L.prototype.update=function(){if(this.mesh&&this.bone){var G=this.bone;G._markAsDirtyAndCompose(),G.getAbsolutePositionToRef(this.mesh,this.pos),G.getDirectionToRef(m.a.X,this.mesh,this.xaxis),G.getDirectionToRef(m.a.Y,this.mesh,this.yaxis),G.getDirectionToRef(m.a.Z,this.mesh,this.zaxis),$.prototype.update.call(this,this.pos,this.xaxis,this.yaxis,this.zaxis)}},L.prototype.dispose=function(){this.mesh&&(this.mesh=null,this.bone=null,$.prototype.dispose.call(this))},L}(R),T=f(12),A=f(6),S=f(20),g=f(13);Object.defineProperty(S.a.prototype,"debugLayer",{get:function(){return this._debugLayer||(this._debugLayer=new l(this)),this._debugLayer},enumerable:!0,configurable:!0}),function($){$[$.Properties=0]="Properties",$[$.Debug=1]="Debug",$[$.Statistics=2]="Statistics",$[$.Tools=3]="Tools",$[$.Settings=4]="Settings"}(U||(U={}));var l=function(){function $(L){var G=this;this.BJSINSPECTOR=this._getGlobalInspector(),this._scene=L,this._scene.onDisposeObservable.add(function(){G._scene._debugLayer&&G._scene._debugLayer.hide()})}return Object.defineProperty($.prototype,"onPropertyChangedObservable",{get:function(){return this.BJSINSPECTOR&&this.BJSINSPECTOR.Inspector?this.BJSINSPECTOR.Inspector.OnPropertyChangedObservable:(this._onPropertyChangedObservable||(this._onPropertyChangedObservable=new A.c),this._onPropertyChangedObservable)},enumerable:!1,configurable:!0}),$.prototype._createInspector=function(L){if(!this.isVisible()){if(this._onPropertyChangedObservable){for(var G=0,Q=this._onPropertyChangedObservable.observers;G<Q.length;G++){var oe=Q[G];this.BJSINSPECTOR.Inspector.OnPropertyChangedObservable.add(oe)}this._onPropertyChangedObservable.clear(),this._onPropertyChangedObservable=void 0}var re=Object(x.a)({overlay:!1,showExplorer:!0,showInspector:!0,embedMode:!1,handleResize:!0,enablePopup:!0},L);this.BJSINSPECTOR=this.BJSINSPECTOR||this._getGlobalInspector(),this.BJSINSPECTOR.Inspector.Show(this._scene,re)}},$.prototype.select=function(L,G){this.BJSINSPECTOR&&(G&&(Object.prototype.toString.call(G)=="[object String]"?this.BJSINSPECTOR.Inspector.MarkLineContainerTitleForHighlighting(G):this.BJSINSPECTOR.Inspector.MarkMultipleLineContainerTitlesForHighlighting(G)),this.BJSINSPECTOR.Inspector.OnSelectionChangeObservable.notifyObservers(L))},$.prototype._getGlobalInspector=function(){return typeof INSPECTOR<"u"?INSPECTOR:typeof BABYLON<"u"&&BABYLON.Inspector!==void 0?BABYLON:void 0},$.prototype.isVisible=function(){return this.BJSINSPECTOR&&this.BJSINSPECTOR.Inspector.IsVisible},$.prototype.hide=function(){this.BJSINSPECTOR&&this.BJSINSPECTOR.Inspector.Hide()},$.prototype.setAsActiveScene=function(){this.BJSINSPECTOR&&this.BJSINSPECTOR.Inspector._SetNewScene(this._scene)},$.prototype.show=function(L){var G=this;return new Promise(function(Q,oe){if(G.BJSINSPECTOR===void 0){var re=L&&L.inspectorURL?L.inspectorURL:$.InspectorURL;T.b.LoadScript(re,function(){G._createInspector(L),Q(G)})}else G._createInspector(L),Q(G)})},$.InspectorURL="https://unpkg.com/babylonjs-inspector@"+g.a.Version+"/babylon.inspector.bundle.js",$}(),h=f(7),v=f(63),E=f(45),D=f(22),w=f(32),N=f(36),I=f(53),V=function(){function $(L){this._impostors=[],this._meshes=[],this._numMeshes=0,this._debugMeshMeshes=new Array,this._scene=L||D.a.LastCreatedScene;var G=this._scene.getPhysicsEngine();G&&(this._physicsEnginePlugin=G.getPhysicsPlugin()),this._utilityLayer=new N.a(this._scene,!1),this._utilityLayer.pickUtilitySceneFirst=!1,this._utilityLayer.utilityLayerScene.autoClearDepthAndStencil=!0}return $.prototype._updateDebugMeshes=function(){for(var L=this._physicsEnginePlugin,G=0;G<this._numMeshes;G++){var Q=this._impostors[G];if(Q)if(Q.isDisposed)this.hideImpostor(this._impostors[G--]);else{if(Q.type===w.a.MeshImpostor)continue;var oe=this._meshes[G];oe&&L&&L.syncMeshWithImpostor(oe,Q)}}},$.prototype.showImpostor=function(L,G){if(!this._scene)return null;for(var Q=0;Q<this._numMeshes;Q++)if(this._impostors[Q]==L)return null;var oe=this._getDebugMesh(L,G);return oe&&(this._impostors[this._numMeshes]=L,this._meshes[this._numMeshes]=oe,this._numMeshes===0&&(this._renderFunction=this._updateDebugMeshes.bind(this),this._scene.registerBeforeRender(this._renderFunction)),this._numMeshes++),oe},$.prototype.hideImpostor=function(L){if(L&&this._scene&&this._utilityLayer){for(var G=!1,Q=this._utilityLayer.utilityLayerScene,oe=0;oe<this._numMeshes;oe++)if(this._impostors[oe]==L){var re=this._meshes[oe];if(!re)continue;Q.removeMesh(re),re.dispose();var Y=this._debugMeshMeshes.indexOf(re);Y>-1&&this._debugMeshMeshes.splice(Y,1),this._numMeshes--,this._numMeshes>0?(this._meshes[oe]=this._meshes[this._numMeshes],this._impostors[oe]=this._impostors[this._numMeshes],this._meshes[this._numMeshes]=null,this._impostors[this._numMeshes]=null):(this._meshes[0]=null,this._impostors[0]=null),G=!0;break}G&&this._numMeshes===0&&this._scene.unregisterBeforeRender(this._renderFunction)}},$.prototype._getDebugMaterial=function(L){return this._debugMaterial||(this._debugMaterial=new C.a("",L),this._debugMaterial.wireframe=!0,this._debugMaterial.emissiveColor=M.a.White(),this._debugMaterial.disableLighting=!0),this._debugMaterial},$.prototype._getDebugBoxMesh=function(L){return this._debugBoxMesh||(this._debugBoxMesh=v.a.CreateBox("physicsBodyBoxViewMesh",{size:1},L),this._debugBoxMesh.rotationQuaternion=_.b.Identity(),this._debugBoxMesh.material=this._getDebugMaterial(L),this._debugBoxMesh.setEnabled(!1)),this._debugBoxMesh.createInstance("physicsBodyBoxViewInstance")},$.prototype._getDebugSphereMesh=function(L){return this._debugSphereMesh||(this._debugSphereMesh=E.a.CreateSphere("physicsBodySphereViewMesh",{diameter:1},L),this._debugSphereMesh.rotationQuaternion=_.b.Identity(),this._debugSphereMesh.material=this._getDebugMaterial(L),this._debugSphereMesh.setEnabled(!1)),this._debugSphereMesh.createInstance("physicsBodyBoxViewInstance")},$.prototype._getDebugCylinderMesh=function(L){return this._debugCylinderMesh||(this._debugCylinderMesh=I.a.CreateCylinder("physicsBodyCylinderViewMesh",{diameterTop:1,diameterBottom:1,height:1},L),this._debugCylinderMesh.rotationQuaternion=_.b.Identity(),this._debugCylinderMesh.material=this._getDebugMaterial(L),this._debugCylinderMesh.setEnabled(!1)),this._debugCylinderMesh.createInstance("physicsBodyBoxViewInstance")},$.prototype._getDebugMeshMesh=function(L,G){var Q=new h.a(L.name,G,null,L);return Q.position=_.e.Zero(),Q.setParent(L),Q.material=this._getDebugMaterial(G),this._debugMeshMeshes.push(Q),Q},$.prototype._getDebugMesh=function(L,G){var Q=this;if(!this._utilityLayer||G&&G.parent&&G.parent.physicsImpostor)return null;var oe=null,re=this._utilityLayer.utilityLayerScene;switch(L.type){case w.a.BoxImpostor:oe=this._getDebugBoxMesh(re),L.getBoxSizeToRef(oe.scaling);break;case w.a.SphereImpostor:oe=this._getDebugSphereMesh(re);var Y=L.getRadius();oe.scaling.x=2*Y,oe.scaling.y=2*Y,oe.scaling.z=2*Y;break;case w.a.MeshImpostor:G&&(oe=this._getDebugMeshMesh(G,re));break;case w.a.NoImpostor:G&&G.getChildMeshes().filter(function(H){return H.physicsImpostor?1:0}).forEach(function(H){Q._getDebugBoxMesh(re).parent=H});break;case w.a.CylinderImpostor:oe=this._getDebugCylinderMesh(re);var k=L.object.getBoundingInfo();oe.scaling.x=k.boundingBox.maximum.x-k.boundingBox.minimum.x,oe.scaling.y=k.boundingBox.maximum.y-k.boundingBox.minimum.y,oe.scaling.z=k.boundingBox.maximum.z-k.boundingBox.minimum.z}return oe},$.prototype.dispose=function(){for(var L=this._numMeshes,G=0;G<L;G++)this.hideImpostor(this._impostors[0]);this._debugBoxMesh&&this._debugBoxMesh.dispose(),this._debugSphereMesh&&this._debugSphereMesh.dispose(),this._debugCylinderMesh&&this._debugCylinderMesh.dispose(),this._debugMaterial&&this._debugMaterial.dispose(),this._impostors.length=0,this._scene=null,this._physicsEnginePlugin=null,this._utilityLayer&&(this._utilityLayer.dispose(),this._utilityLayer=null)},$}(),X=f(40),j=function(){function $(L){this.ray=L}return $.CreateAndShow=function(L,G,Q){var oe=new $(L);return oe.show(G,Q),oe},$.prototype.show=function(L,G){if(!this._renderFunction&&this.ray){var Q=this.ray;this._renderFunction=this._render.bind(this),this._scene=L,this._renderPoints=[Q.origin,Q.origin.add(Q.direction.scale(Q.length))],this._renderLine=h.a.CreateLines("ray",this._renderPoints,L,!0),this._renderLine.isPickable=!1,this._renderFunction&&this._scene.registerBeforeRender(this._renderFunction)}G&&this._renderLine&&this._renderLine.color.copyFrom(G)},$.prototype.hide=function(){this._renderFunction&&this._scene&&(this._scene.unregisterBeforeRender(this._renderFunction),this._scene=null,this._renderFunction=null,this._renderLine&&(this._renderLine.dispose(),this._renderLine=null),this._renderPoints=[])},$.prototype._render=function(){var L=this.ray;if(L){var G=this._renderPoints[1],Q=Math.min(L.length,1e6);G.copyFrom(L.direction),G.scaleInPlace(Q),G.addInPlace(L.origin),this._renderPoints[0].copyFrom(L.origin),h.a.CreateLines("ray",this._renderPoints,this._scene,!0,this._renderLine)}},$.prototype.attachToMesh=function(L,G,Q,oe){var re=this;this._attachedToMesh=L;var Y=this.ray;Y&&(Y.direction||(Y.direction=_.e.Zero()),Y.origin||(Y.origin=_.e.Zero()),oe&&(Y.length=oe),Q||(Q=_.e.Zero()),G||(G=new _.e(0,0,-1)),this._scene||(this._scene=L.getScene()),this._meshSpaceDirection?(this._meshSpaceDirection.copyFrom(G),this._meshSpaceOrigin.copyFrom(Q)):(this._meshSpaceDirection=G.clone(),this._meshSpaceOrigin=Q.clone()),this._onAfterRenderObserver||(this._onAfterRenderObserver=this._scene.onBeforeRenderObservable.add(function(){return re._updateToMesh()}),this._onAfterStepObserver=this._scene.onAfterStepObservable.add(function(){return re._updateToMesh()})),this._attachedToMesh.computeWorldMatrix(!0),this._updateToMesh())},$.prototype.detachFromMesh=function(){this._attachedToMesh&&this._scene&&(this._onAfterRenderObserver&&(this._scene.onBeforeRenderObservable.remove(this._onAfterRenderObserver),this._scene.onAfterStepObservable.remove(this._onAfterStepObserver)),this._attachedToMesh=null,this._onAfterRenderObserver=null,this._onAfterStepObserver=null,this._scene=null)},$.prototype._updateToMesh=function(){var L=this.ray;this._attachedToMesh&&L&&(this._attachedToMesh._isDisposed?this.detachFromMesh():(this._attachedToMesh.getDirectionToRef(this._meshSpaceDirection,L.direction),_.e.TransformCoordinatesToRef(this._meshSpaceOrigin,this._attachedToMesh.getWorldMatrix(),L.origin)))},$.prototype.dispose=function(){this.hide(),this.detachFromMesh(),this.ray=null},$}(),ne=f(25),te=f(73),de=f(62),pe=f(4),ae=f(5),ee=f(97),K=function(){function $(L,G,Q,oe,re,Y){var k,H,Z,W,q,he,ge,me,_e,be,Pe,ye,Be,ke;oe===void 0&&(oe=!0),re===void 0&&(re=3),Y===void 0&&(Y={}),this.skeleton=L,this.mesh=G,this.autoUpdateBonesMatrices=oe,this.renderingGroupId=re,this.options=Y,this.color=M.a.White(),this._debugLines=new Array,this._localAxes=null,this._isEnabled=!1,this._obs=null,this._scene=Q,this._ready=!1,Y.pauseAnimations=(k=Y.pauseAnimations)===null||k===void 0||k,Y.returnToRest=(H=Y.returnToRest)!==null&&H!==void 0&&H,Y.displayMode=(Z=Y.displayMode)!==null&&Z!==void 0?Z:$.DISPLAY_LINES,Y.displayOptions=(W=Y.displayOptions)!==null&&W!==void 0?W:{},Y.displayOptions.midStep=(q=Y.displayOptions.midStep)!==null&&q!==void 0?q:.235,Y.displayOptions.midStepFactor=(he=Y.displayOptions.midStepFactor)!==null&&he!==void 0?he:.155,Y.displayOptions.sphereBaseSize=(ge=Y.displayOptions.sphereBaseSize)!==null&&ge!==void 0?ge:.15,Y.displayOptions.sphereScaleUnit=(me=Y.displayOptions.sphereScaleUnit)!==null&&me!==void 0?me:2,Y.displayOptions.sphereFactor=(_e=Y.displayOptions.sphereFactor)!==null&&_e!==void 0?_e:.865,Y.displayOptions.spurFollowsChild=(be=Y.displayOptions.spurFollowsChild)!==null&&be!==void 0&&be,Y.displayOptions.showLocalAxes=(Pe=Y.displayOptions.showLocalAxes)!==null&&Pe!==void 0&&Pe,Y.displayOptions.localAxesSize=(ye=Y.displayOptions.localAxesSize)!==null&&ye!==void 0?ye:.075,Y.computeBonesUsingShaders=(Be=Y.computeBonesUsingShaders)===null||Be===void 0||Be,Y.useAllBones=(ke=Y.useAllBones)===null||ke===void 0||ke;var We=G.getVerticesData(pe.b.MatricesIndicesKind),je=G.getVerticesData(pe.b.MatricesWeightsKind);if(this._boneIndices=new Set,!Y.useAllBones&&We&&je)for(var He=0;He<We.length;++He){var qe=We[He];je[He]!==0&&this._boneIndices.add(qe)}this._utilityLayer=new N.a(this._scene,!1),this._utilityLayer.pickUtilitySceneFirst=!1,this._utilityLayer.utilityLayerScene.autoClearDepthAndStencil=!0;var Ge=this.options.displayMode||0;Ge>$.DISPLAY_SPHERE_AND_SPURS&&(Ge=$.DISPLAY_LINES),this.displayMode=Ge,this.update(),this._bindObs()}return $.CreateBoneWeightShader=function(L,G){var Q,oe,re,Y,k,H,Z=L.skeleton,W=(Q=L.colorBase)!==null&&Q!==void 0?Q:M.a.Black(),q=(oe=L.colorZero)!==null&&oe!==void 0?oe:M.a.Blue(),he=(re=L.colorQuarter)!==null&&re!==void 0?re:M.a.Green(),ge=(Y=L.colorHalf)!==null&&Y!==void 0?Y:M.a.Yellow(),me=(k=L.colorFull)!==null&&k!==void 0?k:M.a.Red(),_e=(H=L.targetBoneIndex)!==null&&H!==void 0?H:0;ae.a.ShadersStore["boneWeights:"+Z.name+"VertexShader"]=`precision highp float;
-
-        attribute vec3 position;
-        attribute vec2 uv;
-
-        uniform mat4 view;
-        uniform mat4 projection;
-        uniform mat4 worldViewProjection;
-
-        #include<bonesDeclaration>
-        #if NUM_BONE_INFLUENCERS == 0
-            attribute vec4 matricesIndices;
-            attribute vec4 matricesWeights;
-        #endif
-
-        #include<instancesDeclaration>
-
-        varying vec3 vColor;
-
-        uniform vec3 colorBase;
-        uniform vec3 colorZero;
-        uniform vec3 colorQuarter;
-        uniform vec3 colorHalf;
-        uniform vec3 colorFull;
-
-        uniform float targetBoneIndex;
-
-        void main() {
-            vec3 positionUpdated = position;
-
-            #include<instancesVertex>
-            #include<bonesVertex>
-
-            vec4 worldPos = finalWorld * vec4(positionUpdated, 1.0);
-
-            vec3 color = colorBase;
-            float totalWeight = 0.;
-            if(matricesIndices[0] == targetBoneIndex && matricesWeights[0] > 0.){
-                totalWeight += matricesWeights[0];
-            }
-            if(matricesIndices[1] == targetBoneIndex && matricesWeights[1] > 0.){
-                totalWeight += matricesWeights[1];
-            }
-            if(matricesIndices[2] == targetBoneIndex && matricesWeights[2] > 0.){
-                totalWeight += matricesWeights[2];
-            }
-            if(matricesIndices[3] == targetBoneIndex && matricesWeights[3] > 0.){
-                totalWeight += matricesWeights[3];
-            }
-
-            color = mix(color, colorZero, smoothstep(0., 0.25, totalWeight));
-            color = mix(color, colorQuarter, smoothstep(0.25, 0.5, totalWeight));
-            color = mix(color, colorHalf, smoothstep(0.5, 0.75, totalWeight));
-            color = mix(color, colorFull, smoothstep(0.75, 1.0, totalWeight));
-            vColor = color;
-
-        gl_Position = projection * view * worldPos;
-        }`,ae.a.ShadersStore["boneWeights:"+Z.name+"FragmentShader"]=`
-            precision highp float;
-            varying vec3 vPosition;
-
-            varying vec3 vColor;
-
-            void main() {
-                vec4 color = vec4(vColor, 1.0);
-                gl_FragColor = color;
-            }
-        `;var be=new te.a("boneWeight:"+Z.name,G,{vertex:"boneWeights:"+Z.name,fragment:"boneWeights:"+Z.name},{attributes:["position","normal","matricesIndices","matricesWeights"],uniforms:["world","worldView","worldViewProjection","view","projection","viewProjection","colorBase","colorZero","colorQuarter","colorHalf","colorFull","targetBoneIndex"]});return be.setColor3("colorBase",W),be.setColor3("colorZero",q),be.setColor3("colorQuarter",he),be.setColor3("colorHalf",ge),be.setColor3("colorFull",me),be.setFloat("targetBoneIndex",_e),be.getClassName=function(){return"BoneWeightShader"},be.transparencyMode=ne.a.MATERIAL_OPAQUE,be},$.CreateSkeletonMapShader=function(L,G){var Q,oe=L.skeleton,re=(Q=L.colorMap)!==null&&Q!==void 0?Q:[{color:new M.a(1,.38,.18),location:0},{color:new M.a(.59,.18,1),location:.2},{color:new M.a(.59,1,.18),location:.4},{color:new M.a(1,.87,.17),location:.6},{color:new M.a(1,.17,.42),location:.8},{color:new M.a(.17,.68,1),location:1}],Y=oe.bones.length+1,k=$._CreateBoneMapColorBuffer(Y,re,G),H=new te.a("boneWeights:"+oe.name,G,{vertexSource:`precision highp float;
-
-            attribute vec3 position;
-            attribute vec2 uv;
-
-            uniform mat4 view;
-            uniform mat4 projection;
-            uniform mat4 worldViewProjection;
-            uniform float colorMap[`+4*oe.bones.length+`];
-
-            #include<bonesDeclaration>
-            #if NUM_BONE_INFLUENCERS == 0
-                attribute vec4 matricesIndices;
-                attribute vec4 matricesWeights;
-            #endif
-            #include<instancesDeclaration>
-
-            varying vec3 vColor;
-
-            void main() {
-                vec3 positionUpdated = position;
-
-                #include<instancesVertex>
-                #include<bonesVertex>
-
-                vec3 color = vec3(0.);
-                bool first = true;
-
-                for (int i = 0; i < 4; i++) {
-                    int boneIdx = int(matricesIndices[i]);
-                    float boneWgt = matricesWeights[i];
-
-                    vec3 c = vec3(colorMap[boneIdx * 4 + 0], colorMap[boneIdx * 4 + 1], colorMap[boneIdx * 4 + 2]);
-
-                    if (boneWgt > 0.) {
-                        if (first) {
-                            first = false;
-                            color = c;
-                        } else {
-                            color = mix(color, c, boneWgt);
-                        }
-                    }
-                }
-
-                vColor = color;
-
-                vec4 worldPos = finalWorld * vec4(positionUpdated, 1.0);
-
-                gl_Position = projection * view * worldPos;
-            }`,fragmentSource:`
-            precision highp float;
-            varying vec3 vColor;
-
-            void main() {
-                vec4 color = vec4( vColor, 1.0 );
-                gl_FragColor = color;
-            }
-            `},{attributes:["position","normal","matricesIndices","matricesWeights"],uniforms:["world","worldView","worldViewProjection","view","projection","viewProjection","colorMap"]});return H.setFloats("colorMap",k),H.getClassName=function(){return"SkeletonMapShader"},H.transparencyMode=ne.a.MATERIAL_OPAQUE,H},$._CreateBoneMapColorBuffer=function(L,G,Q){var oe=new de.a("temp",{width:L,height:1},Q,!1),re=oe.getContext(),Y=re.createLinearGradient(0,0,L,0);G.forEach(function(W){Y.addColorStop(W.location,W.color.toHexString())}),re.fillStyle=Y,re.fillRect(0,0,L,1),oe.update();for(var k=[],H=re.getImageData(0,0,L,1).data,Z=0;Z<H.length;Z++)k.push(H[Z]*(1/255));return oe.dispose(),k},Object.defineProperty($.prototype,"scene",{get:function(){return this._scene},enumerable:!1,configurable:!0}),Object.defineProperty($.prototype,"utilityLayer",{get:function(){return this._utilityLayer},enumerable:!1,configurable:!0}),Object.defineProperty($.prototype,"isReady",{get:function(){return this._ready},enumerable:!1,configurable:!0}),Object.defineProperty($.prototype,"ready",{set:function(L){this._ready=L},enumerable:!1,configurable:!0}),Object.defineProperty($.prototype,"debugMesh",{get:function(){return this._debugMesh},set:function(L){this._debugMesh=L},enumerable:!1,configurable:!0}),Object.defineProperty($.prototype,"displayMode",{get:function(){return this.options.displayMode||$.DISPLAY_LINES},set:function(L){L>$.DISPLAY_SPHERE_AND_SPURS&&(L=$.DISPLAY_LINES),this.options.displayMode=L},enumerable:!1,configurable:!0}),$.prototype._bindObs=function(){var L=this;switch(this.displayMode){case $.DISPLAY_LINES:this._obs=this.scene.onBeforeRenderObservable.add(function(){L._displayLinesUpdate()})}},$.prototype.update=function(){switch(this.displayMode){case $.DISPLAY_LINES:this._displayLinesUpdate();break;case $.DISPLAY_SPHERES:this._buildSpheresAndSpurs(!0);break;case $.DISPLAY_SPHERE_AND_SPURS:this._buildSpheresAndSpurs(!1)}this._buildLocalAxes()},Object.defineProperty($.prototype,"isEnabled",{get:function(){return this._isEnabled},set:function(L){this.isEnabled!==L&&(this._isEnabled=L,this.debugMesh&&this.debugMesh.setEnabled(L),L&&!this._obs?this._bindObs():!L&&this._obs&&(this.scene.onBeforeRenderObservable.remove(this._obs),this._obs=null))},enumerable:!1,configurable:!0}),$.prototype._getBonePosition=function(L,G,Q,oe,re,Y){oe===void 0&&(oe=0),re===void 0&&(re=0),Y===void 0&&(Y=0);var k=_.c.Matrix[0],H=G.getParent();if(k.copyFrom(G.getLocalMatrix()),oe!==0||re!==0||Y!==0){var Z=_.c.Matrix[1];_.a.IdentityToRef(Z),Z.setTranslationFromFloats(oe,re,Y),Z.multiplyToRef(k,k)}H&&k.multiplyToRef(H.getAbsoluteTransform(),k),k.multiplyToRef(Q,k),L.x=k.m[12],L.y=k.m[13],L.z=k.m[14]},$.prototype._getLinesForBonesWithLength=function(L,G){for(var Q=L.length,oe=this.mesh._effectiveMesh.position,re=0,Y=0;Y<Q;Y++){var k=L[Y],H=this._debugLines[re];k._index!==-1&&(this._boneIndices.has(k.getIndex())||this.options.useAllBones)&&(H||(H=[_.e.Zero(),_.e.Zero()],this._debugLines[re]=H),this._getBonePosition(H[0],k,G),this._getBonePosition(H[1],k,G,0,k.length,0),H[0].subtractInPlace(oe),H[1].subtractInPlace(oe),re++)}},$.prototype._getLinesForBonesNoLength=function(L){for(var G=L.length,Q=0,oe=this.mesh._effectiveMesh,re=oe.position,Y=G-1;Y>=0;Y--){var k=L[Y],H=k.getParent();if(H&&(this._boneIndices.has(k.getIndex())||this.options.useAllBones)){var Z=this._debugLines[Q];Z||(Z=[_.e.Zero(),_.e.Zero()],this._debugLines[Q]=Z),k.getAbsolutePositionToRef(oe,Z[0]),H.getAbsolutePositionToRef(oe,Z[1]),Z[0].subtractInPlace(re),Z[1].subtractInPlace(re),Q++}}},$.prototype._revert=function(L){this.options.pauseAnimations&&(this.scene.animationsEnabled=L,this.utilityLayer.utilityLayerScene.animationsEnabled=L)},$.prototype._getAbsoluteBindPoseToRef=function(L,G){L!==null&&L._index!==-1?(this._getAbsoluteBindPoseToRef(L.getParent(),G),L.getBindPose().multiplyToRef(G,G)):G.copyFrom(_.a.Identity())},$.prototype._buildSpheresAndSpurs=function(L){var G,Q;L===void 0&&(L=!0),this._debugMesh&&(this._debugMesh.dispose(),this._debugMesh=null,this.ready=!1),this._ready=!1;var oe=(G=this.utilityLayer)===null||G===void 0?void 0:G.utilityLayerScene,re=this.skeleton.bones,Y=[],k=[],H=this.scene.animationsEnabled;try{this.options.pauseAnimations&&(this.scene.animationsEnabled=!1,oe.animationsEnabled=!1),this.options.returnToRest&&this.skeleton.returnToRest(),this.autoUpdateBonesMatrices&&this.skeleton.computeAbsoluteTransforms();for(var Z=Number.NEGATIVE_INFINITY,W=this.options.displayOptions||{},q=function(He){var qe=re[He];if(qe._index===-1||!he._boneIndices.has(qe.getIndex())&&!he.options.useAllBones)return"continue";var Ge=new _.a;he._getAbsoluteBindPoseToRef(qe,Ge);var nt=new _.e;Ge.decompose(void 0,void 0,nt),qe.children.forEach(function(It,Pt){var Ot=new _.a;It.getBindPose().multiplyToRef(Ge,Ot);var on=new _.e;Ot.decompose(void 0,void 0,on);var Zt=_.e.Distance(nt,on);if(Zt>Z&&(Z=Zt),!L){for(var tn=on.clone().subtract(nt.clone()),De=tn.length(),Pn=tn.normalize().scale(De),nn=W.midStep||.165,xn=W.midStepFactor||.215,Ue=Pn.scale(nn),Cn=ee.a.ExtrudeShapeCustom("skeletonViewer",{shape:[new _.e(1,-1,0),new _.e(1,1,0),new _.e(-1,1,0),new _.e(-1,-1,0),new _.e(1,-1,0)],path:[_.e.Zero(),Ue,Pn],scaleFunction:function(Lo){switch(Lo){case 0:case 2:return 0;case 1:return De*xn}return 0},sideOrientation:h.a.DEFAULTSIDE,updatable:!1},oe),dr=Cn.getTotalVertices(),Xe=[],An=[],ei=0;ei<dr;ei++)Xe.push(1,0,0,0),W.spurFollowsChild&&ei>9?An.push(It.getIndex(),0,0,0):An.push(qe.getIndex(),0,0,0);Cn.position=nt.clone(),Cn.setVerticesData(pe.b.MatricesWeightsKind,Xe,!1),Cn.setVerticesData(pe.b.MatricesIndicesKind,An,!1),Cn.convertToFlatShadedMesh(),k.push(Cn)}});for(var $e=W.sphereBaseSize||.2,lt=E.a.CreateSphere("skeletonViewer",{segments:6,diameter:$e,updatable:!0},oe),st=lt.getTotalVertices(),mt=[],St=[],wt=0;wt<st;wt++)mt.push(1,0,0,0),St.push(qe.getIndex(),0,0,0);lt.setVerticesData(pe.b.MatricesWeightsKind,mt,!1),lt.setVerticesData(pe.b.MatricesIndicesKind,St,!1),lt.position=nt.clone(),Y.push([lt,qe])},he=this,ge=0;ge<re.length;ge++)q(ge);var me=W.sphereScaleUnit||2,_e=W.sphereFactor||.85,be=[];for(ge=0;ge<Y.length;ge++){for(var Pe=Y[ge],ye=Pe[0],Be=Pe[1],ke=1/(me/Z),We=0,je=Be;je.getParent()&&je.getParent().getIndex()!==-1;)We++,je=je.getParent();ye.scaling.scaleInPlace(ke*Math.pow(_e,We)),be.push(ye)}this.debugMesh=h.a.MergeMeshes(be.concat(k),!0,!0),this.debugMesh&&(this.debugMesh.renderingGroupId=this.renderingGroupId,this.debugMesh.skeleton=this.skeleton,this.debugMesh.parent=this.mesh,this.debugMesh.computeBonesUsingShaders=(Q=this.options.computeBonesUsingShaders)===null||Q===void 0||Q,this.debugMesh.alwaysSelectAsActiveMesh=!0),this.utilityLayer._getSharedGizmoLight().intensity=.7,this._revert(H),this.ready=!0}catch(He){console.error(He),this._revert(H),this.dispose()}},$.prototype._buildLocalAxes=function(){var L;this._localAxes&&this._localAxes.dispose(),this._localAxes=null;var G=this.options.displayOptions||{};if(G.showLocalAxes){var Q=this._utilityLayer.utilityLayerScene,oe=G.localAxesSize||.075,re=[],Y=[],k=new M.b(1,0,0,1),H=new M.b(0,1,0,1),Z=new M.b(0,0,1,1),W=[],q=[];for(var he in this.skeleton.bones){var ge=this.skeleton.bones[he];if(ge._index!==-1&&(this._boneIndices.has(ge.getIndex())||this.options.useAllBones)){var me=new _.a,_e=new _.e;this._getAbsoluteBindPoseToRef(ge,me),me.decompose(void 0,void 0,_e);var be=ge.getBindPose().getRotationMatrix(),Pe=_.e.TransformCoordinates(new _.e(0+oe,0,0),be),ye=_.e.TransformCoordinates(new _.e(0,0+oe,0),be),Be=_.e.TransformCoordinates(new _.e(0,0,0+oe),be),ke=[[_e,_e.add(Pe)],[_e,_e.add(ye)],[_e,_e.add(Be)]],We=[[k,k],[H,H],[Z,Z]];re.push.apply(re,ke),Y.push.apply(Y,We);for(var je=0;je<6;je++)W.push(1,0,0,0),q.push(ge.getIndex(),0,0,0)}}this._localAxes=X.a.CreateLineSystem("localAxes",{lines:re,colors:Y,updatable:!0},Q),this._localAxes.setVerticesData(pe.b.MatricesWeightsKind,W,!1),this._localAxes.setVerticesData(pe.b.MatricesIndicesKind,q,!1),this._localAxes.skeleton=this.skeleton,this._localAxes.renderingGroupId=this.renderingGroupId,this._localAxes.parent=this.mesh,this._localAxes.computeBonesUsingShaders=(L=this.options.computeBonesUsingShaders)===null||L===void 0||L}},$.prototype._displayLinesUpdate=function(){if(this._utilityLayer){this.autoUpdateBonesMatrices&&this.skeleton.computeAbsoluteTransforms();var L=this.mesh._effectiveMesh;this.skeleton.bones[0].length===void 0?this._getLinesForBonesNoLength(this.skeleton.bones):this._getLinesForBonesWithLength(this.skeleton.bones,L.getWorldMatrix());var G=this._utilityLayer.utilityLayerScene;G&&(this._debugMesh?X.a.CreateLineSystem("",{lines:this._debugLines,updatable:!0,instance:this._debugMesh},G):(this._debugMesh=X.a.CreateLineSystem("",{lines:this._debugLines,updatable:!0,instance:null},G),this._debugMesh.renderingGroupId=this.renderingGroupId),this._debugMesh.position.copyFrom(this.mesh.position),this._debugMesh.color=this.color)}},$.prototype.changeDisplayMode=function(L){var G=!!this.isEnabled;this.displayMode!==L&&(this.isEnabled=!1,this._debugMesh&&(this._debugMesh.dispose(),this._debugMesh=null,this.ready=!1),this.displayMode=L,this.update(),this._bindObs(),this.isEnabled=G)},$.prototype.changeDisplayOptions=function(L,G){var Q=!!this.isEnabled;this.options.displayOptions[L]=G,this.isEnabled=!1,this._debugMesh&&(this._debugMesh.dispose(),this._debugMesh=null,this.ready=!1),this.update(),this._bindObs(),this.isEnabled=Q},$.prototype.dispose=function(){this.isEnabled=!1,this._debugMesh&&(this._debugMesh.dispose(),this._debugMesh=null),this._utilityLayer&&(this._utilityLayer.dispose(),this._utilityLayer=null),this.ready=!1},$.DISPLAY_LINES=0,$.DISPLAY_SPHERES=1,$.DISPLAY_SPHERE_AND_SPURS=2,$}()},function(Me,y,f){var U="morphTargetsVertex",_=`#ifdef MORPHTARGETS
-positionUpdated+=(position{X}-position)*morphTargetInfluences[{X}];
-#ifdef MORPHTARGETS_NORMAL
-normalUpdated+=(normal{X}-normal)*morphTargetInfluences[{X}];
-#endif
-#ifdef MORPHTARGETS_TANGENT
-tangentUpdated.xyz+=(tangent{X}-tangent.xyz)*morphTargetInfluences[{X}];
-#endif
-#ifdef MORPHTARGETS_UV
-uvUpdated+=(uv_{X}-uv)*morphTargetInfluences[{X}];
-#endif
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){f.d(y,"b",function(){return _}),f.d(y,"a",function(){return C});var U=f(0);function _(u,M,R,x,m){m===void 0&&(m=null);for(var c=new U.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),T=new U.e(-Number.MAX_VALUE,-Number.MAX_VALUE,-Number.MAX_VALUE),A=R;A<R+x;A++){var S=3*M[A],g=u[S],l=u[S+1],h=u[S+2];c.minimizeInPlaceFromFloats(g,l,h),T.maximizeInPlaceFromFloats(g,l,h)}return m&&(c.x-=c.x*m.x+m.y,c.y-=c.y*m.x+m.y,c.z-=c.z*m.x+m.y,T.x+=T.x*m.x+m.y,T.y+=T.y*m.x+m.y,T.z+=T.z*m.x+m.y),{minimum:c,maximum:T}}function C(u,M,R,x,m){x===void 0&&(x=null);var c=new U.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),T=new U.e(-Number.MAX_VALUE,-Number.MAX_VALUE,-Number.MAX_VALUE);m||(m=3);for(var A=M,S=M*m;A<M+R;A++,S+=m){var g=u[S],l=u[S+1],h=u[S+2];c.minimizeInPlaceFromFloats(g,l,h),T.maximizeInPlaceFromFloats(g,l,h)}return x&&(c.x-=c.x*x.x+x.y,c.y-=c.y*x.x+x.y,c.z-=c.z*x.x+x.y,T.x+=T.x*x.x+x.y,T.y+=T.y*x.x+x.y,T.z+=T.z*x.x+x.y),{minimum:c,maximum:T}}},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){}},function(Me,y,f){f.d(y,"a",function(){return u});var U=f(44),_=f(0),C=f(28),u=function(){function M(R,x,m){this.vectors=U.a.BuildArray(8,_.e.Zero),this.center=_.e.Zero(),this.centerWorld=_.e.Zero(),this.extendSize=_.e.Zero(),this.extendSizeWorld=_.e.Zero(),this.directions=U.a.BuildArray(3,_.e.Zero),this.vectorsWorld=U.a.BuildArray(8,_.e.Zero),this.minimumWorld=_.e.Zero(),this.maximumWorld=_.e.Zero(),this.minimum=_.e.Zero(),this.maximum=_.e.Zero(),this.reConstruct(R,x,m)}return M.prototype.reConstruct=function(R,x,m){var c=R.x,T=R.y,A=R.z,S=x.x,g=x.y,l=x.z,h=this.vectors;this.minimum.copyFromFloats(c,T,A),this.maximum.copyFromFloats(S,g,l),h[0].copyFromFloats(c,T,A),h[1].copyFromFloats(S,g,l),h[2].copyFromFloats(S,T,A),h[3].copyFromFloats(c,g,A),h[4].copyFromFloats(c,T,l),h[5].copyFromFloats(S,g,A),h[6].copyFromFloats(c,g,l),h[7].copyFromFloats(S,T,l),x.addToRef(R,this.center).scaleInPlace(.5),x.subtractToRef(R,this.extendSize).scaleInPlace(.5),this._worldMatrix=m||_.a.IdentityReadOnly,this._update(this._worldMatrix)},M.prototype.scale=function(R){var x=M.TmpVector3,m=this.maximum.subtractToRef(this.minimum,x[0]),c=m.length();m.normalizeFromLength(c);var T=c*R,A=m.scaleInPlace(.5*T),S=this.center.subtractToRef(A,x[1]),g=this.center.addToRef(A,x[2]);return this.reConstruct(S,g,this._worldMatrix),this},M.prototype.getWorldMatrix=function(){return this._worldMatrix},M.prototype._update=function(R){var x=this.minimumWorld,m=this.maximumWorld,c=this.directions,T=this.vectorsWorld,A=this.vectors;if(R.isIdentity()){for(x.copyFrom(this.minimum),m.copyFrom(this.maximum),S=0;S<8;++S)T[S].copyFrom(A[S]);this.extendSizeWorld.copyFrom(this.extendSize),this.centerWorld.copyFrom(this.center)}else{x.setAll(Number.MAX_VALUE),m.setAll(-Number.MAX_VALUE);for(var S=0;S<8;++S){var g=T[S];_.e.TransformCoordinatesToRef(A[S],R,g),x.minimizeInPlace(g),m.maximizeInPlace(g)}m.subtractToRef(x,this.extendSizeWorld).scaleInPlace(.5),m.addToRef(x,this.centerWorld).scaleInPlace(.5)}_.e.FromArrayToRef(R.m,0,c[0]),_.e.FromArrayToRef(R.m,4,c[1]),_.e.FromArrayToRef(R.m,8,c[2]),this._worldMatrix=R},M.prototype.isInFrustum=function(R){return M.IsInFrustum(this.vectorsWorld,R)},M.prototype.isCompletelyInFrustum=function(R){return M.IsCompletelyInFrustum(this.vectorsWorld,R)},M.prototype.intersectsPoint=function(R){var x=this.minimumWorld,m=this.maximumWorld,c=x.x,T=x.y,A=x.z,S=m.x,g=m.y,l=m.z,h=R.x,v=R.y,E=R.z,D=-C.a;return!(S-h<D||D>h-c)&&!(g-v<D||D>v-T)&&!(l-E<D||D>E-A)},M.prototype.intersectsSphere=function(R){return M.IntersectsSphere(this.minimumWorld,this.maximumWorld,R.centerWorld,R.radiusWorld)},M.prototype.intersectsMinMax=function(R,x){var m=this.minimumWorld,c=this.maximumWorld,T=m.x,A=m.y,S=m.z,g=c.x,l=c.y,h=c.z,v=R.x,E=R.y,D=R.z,w=x.x,N=x.y,I=x.z;return!(g<v||T>w)&&!(l<E||A>N)&&!(h<D||S>I)},M.Intersects=function(R,x){return R.intersectsMinMax(x.minimumWorld,x.maximumWorld)},M.IntersectsSphere=function(R,x,m,c){var T=M.TmpVector3[0];return _.e.ClampToRef(m,R,x,T),_.e.DistanceSquared(m,T)<=c*c},M.IsCompletelyInFrustum=function(R,x){for(var m=0;m<6;++m)for(var c=x[m],T=0;T<8;++T)if(c.dotCoordinate(R[T])<0)return!1;return!0},M.IsInFrustum=function(R,x){for(var m=0;m<6;++m){for(var c=!0,T=x[m],A=0;A<8;++A)if(T.dotCoordinate(R[A])>=0){c=!1;break}if(c)return!1}return!0},M.TmpVector3=U.a.BuildArray(3,_.e.Zero),M}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(38),_=function(){function C(){}return C.SetImmediate=function(u){U.a.IsWindowObjectExist()&&window.setImmediate?window.setImmediate(u):setTimeout(u,1)},C}()},function(Me,y,f){f.d(y,"a",function(){return C});var U=f(0),_=f(2),C=function(){function u(){this.previousWorldMatrices={},this.previousBones={}}return u.AddUniforms=function(M){M.push("previousWorld","previousViewProjection")},u.AddSamplers=function(M){},u.prototype.bindForSubMesh=function(M,R,x,m,c){R.prePassRenderer&&R.prePassRenderer.enabled&&R.prePassRenderer.getIndex(_.a.PREPASS_VELOCITY_TEXTURE_TYPE)!==-1&&(this.previousWorldMatrices[x.uniqueId]||(this.previousWorldMatrices[x.uniqueId]=U.a.Identity()),this.previousViewProjection||(this.previousViewProjection=R.getTransformMatrix()),M.setMatrix("previousWorld",this.previousWorldMatrices[x.uniqueId]),M.setMatrix("previousViewProjection",this.previousViewProjection),this.previousWorldMatrices[x.uniqueId]=m.clone(),this.previousViewProjection=R.getTransformMatrix().clone())},u}()},function(Me,y,f){var U="lightFragmentDeclaration",_=`#ifdef LIGHT{X}
-uniform vec4 vLightData{X};
-uniform vec4 vLightDiffuse{X};
-#ifdef SPECULARTERM
-uniform vec4 vLightSpecular{X};
-#else
-vec4 vLightSpecular{X}=vec4(0.);
-#endif
-#ifdef SHADOW{X}
-#ifdef SHADOWCSM{X}
-uniform mat4 lightMatrix{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float viewFrustumZ{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float frustumLengths{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float cascadeBlendFactor{X};
-varying vec4 vPositionFromLight{X}[SHADOWCSMNUM_CASCADES{X}];
-varying float vDepthMetric{X}[SHADOWCSMNUM_CASCADES{X}];
-varying vec4 vPositionFromCamera{X};
-#if defined(SHADOWPCSS{X})
-uniform highp sampler2DArrayShadow shadowSampler{X};
-uniform highp sampler2DArray depthSampler{X};
-uniform vec2 lightSizeUVCorrection{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float depthCorrection{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float penumbraDarkness{X};
-#elif defined(SHADOWPCF{X})
-uniform highp sampler2DArrayShadow shadowSampler{X};
-#else
-uniform highp sampler2DArray shadowSampler{X};
-#endif
-#ifdef SHADOWCSMDEBUG{X}
-const vec3 vCascadeColorsMultiplier{X}[8]=vec3[8]
-(
-vec3 ( 1.5,0.0,0.0 ),
-vec3 ( 0.0,1.5,0.0 ),
-vec3 ( 0.0,0.0,5.5 ),
-vec3 ( 1.5,0.0,5.5 ),
-vec3 ( 1.5,1.5,0.0 ),
-vec3 ( 1.0,1.0,1.0 ),
-vec3 ( 0.0,1.0,5.5 ),
-vec3 ( 0.5,3.5,0.75 )
-);
-vec3 shadowDebug{X};
-#endif
-#ifdef SHADOWCSMUSESHADOWMAXZ{X}
-int index{X}=-1;
-#else
-int index{X}=SHADOWCSMNUM_CASCADES{X}-1;
-#endif
-float diff{X}=0.;
-#elif defined(SHADOWCUBE{X})
-uniform samplerCube shadowSampler{X};
-#else
-varying vec4 vPositionFromLight{X};
-varying float vDepthMetric{X};
-#if defined(SHADOWPCSS{X})
-uniform highp sampler2DShadow shadowSampler{X};
-uniform highp sampler2D depthSampler{X};
-#elif defined(SHADOWPCF{X})
-uniform highp sampler2DShadow shadowSampler{X};
-#else
-uniform sampler2D shadowSampler{X};
-#endif
-uniform mat4 lightMatrix{X};
-#endif
-uniform vec4 shadowsInfo{X};
-uniform vec2 depthValues{X};
-#endif
-#ifdef SPOTLIGHT{X}
-uniform vec4 vLightDirection{X};
-uniform vec4 vLightFalloff{X};
-#elif defined(POINTLIGHT{X})
-uniform vec4 vLightFalloff{X};
-#elif defined(HEMILIGHT{X})
-uniform vec3 vLightGround{X};
-#endif
-#ifdef PROJECTEDLIGHTTEXTURE{X}
-uniform mat4 textureProjectionMatrix{X};
-uniform sampler2D projectionLightSampler{X};
-#endif
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="lightUboDeclaration",_=`#ifdef LIGHT{X}
-uniform Light{X}
-{
-vec4 vLightData;
-vec4 vLightDiffuse;
-vec4 vLightSpecular;
-#ifdef SPOTLIGHT{X}
-vec4 vLightDirection;
-vec4 vLightFalloff;
-#elif defined(POINTLIGHT{X})
-vec4 vLightFalloff;
-#elif defined(HEMILIGHT{X})
-vec3 vLightGround;
-#endif
-vec4 shadowsInfo;
-vec2 depthValues;
-} light{X};
-#ifdef PROJECTEDLIGHTTEXTURE{X}
-uniform mat4 textureProjectionMatrix{X};
-uniform sampler2D projectionLightSampler{X};
-#endif
-#ifdef SHADOW{X}
-#ifdef SHADOWCSM{X}
-uniform mat4 lightMatrix{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float viewFrustumZ{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float frustumLengths{X}[SHADOWCSMNUM_CASCADES{X}];
-uniform float cascadeBlendFactor{X};
-varying vec4 vPositionFromLight{X}[SHADOWCSMNUM_CASCADES{X}];
-varying float vDepthMetric{X}[SHADOWCSMNUM_CASCADES{X}];
-varying vec4 vPositionFromCamera{X};
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o=new r(t+"Animation",t,n,e,r.ANIMATIONLOOPMODE_CONSTANT);return o.setEasingFunction(i),o},r.CreateAndStartAnimation=function(t,e,n,i,o,a,s,d,p,b){var P=r._PrepareAnimation(t,n,i,o,a,s,d,p);return P?e.getScene().beginDirectAnimation(e,[P],0,o,P.loopMode===1,1,b):null},r.CreateAndStartHierarchyAnimation=function(t,e,n,i,o,a,s,d,p,b,P){var O=r._PrepareAnimation(t,i,o,a,s,d,p,b);return O?e.getScene().beginDirectHierarchyAnimation(e,n,[O],0,a,O.loopMode===1,1,P):null},r.CreateMergeAndStartAnimation=function(t,e,n,i,o,a,s,d,p,b){var P=r._PrepareAnimation(t,n,i,o,a,s,d,p);return P?(e.animations.push(P),e.getScene().beginAnimation(e,0,o,P.loopMode===1,1,b)):null},r.MakeAnimationAdditive=function(t,e,n,i,o){e===void 0&&(e=0),i===void 0&&(i=!1);var a=t;if(i&&((a=t.clone()).name=o||a.name),!a._keys.length)return a;e=e>=0?e:0;var 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r.ANIMATIONTYPE_MATRIX:Te.value.decompose(P.keyScaling,P.keyQuaternion,P.keyPosition),P.keyPosition.subtractInPlace(P.referencePosition),P.keyScaling.divideInPlace(P.referenceScaling),P.referenceQuaternion.multiplyToRef(P.keyQuaternion,P.keyQuaternion),u.a.ComposeToRef(P.keyScaling,P.keyQuaternion,P.keyPosition,Te.value);break;case r.ANIMATIONTYPE_QUATERNION:P.referenceValue.multiplyToRef(Te.value,Te.value);break;case r.ANIMATIONTYPE_VECTOR2:case r.ANIMATIONTYPE_VECTOR3:case r.ANIMATIONTYPE_COLOR3:case r.ANIMATIONTYPE_COLOR4:Te.value.subtractToRef(P.referenceValue,Te.value);break;case r.ANIMATIONTYPE_SIZE:Te.value.width-=P.referenceValue.width,Te.value.height-=P.referenceValue.height;break;default:Te.value-=P.referenceValue}return a},r.TransitionTo=function(t,e,n,i,o,a,s,d){if(d===void 0&&(d=null),s<=0)return n[t]=e,d&&d(),null;var p=o*(s/1e3);a.setKeys([{frame:0,value:n[t].clone?n[t].clone():n[t]},{frame:p,value:e}]),n.animations||(n.animations=[]),n.animations.push(a);var 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t=="function"?t():t},r.prototype._interpolate=function(t,e){if(e.loopMode===r.ANIMATIONLOOPMODE_CONSTANT&&e.repeatCount>0)return e.highLimitValue.clone?e.highLimitValue.clone():e.highLimitValue;var n=this._keys;if(n.length===1)return this._getKeyValue(n[0].value);var i=e.key;if(n[i].frame>=t)for(;i-1>=0&&n[i].frame>=t;)i--;for(var o=i;o<n.length;o++){var a=n[o+1];if(a.frame>=t){e.key=o;var s=n[o],d=this._getKeyValue(s.value);if(s.interpolation===K.STEP)return d;var p=this._getKeyValue(a.value),b=s.outTangent!==void 0&&a.inTangent!==void 0,P=a.frame-s.frame,O=(t-s.frame)/P,B=this.getEasingFunction();switch(B!=null&&(O=B.ease(O)),this.dataType){case r.ANIMATIONTYPE_FLOAT:var F=b?this.floatInterpolateFunctionWithTangents(d,s.outTangent*P,p,a.inTangent*P,O):this.floatInterpolateFunction(d,p,O);switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:return F;case r.ANIMATIONLOOPMODE_RELATIVE:return e.offsetValue*e.repeatCount+F}break;case r.ANIMATIONTYPE_QUATERNION:var z=b?this.quaternionInterpolateFunctionWithTangents(d,s.outTangent.scale(P),p,a.inTangent.scale(P),O):this.quaternionInterpolateFunction(d,p,O);switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:return z;case r.ANIMATIONLOOPMODE_RELATIVE:return z.addInPlace(e.offsetValue.scale(e.repeatCount))}return z;case r.ANIMATIONTYPE_VECTOR3:var J=b?this.vector3InterpolateFunctionWithTangents(d,s.outTangent.scale(P),p,a.inTangent.scale(P),O):this.vector3InterpolateFunction(d,p,O);switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:return J;case r.ANIMATIONLOOPMODE_RELATIVE:return J.add(e.offsetValue.scale(e.repeatCount))}case r.ANIMATIONTYPE_VECTOR2:var ie=b?this.vector2InterpolateFunctionWithTangents(d,s.outTangent.scale(P),p,a.inTangent.scale(P),O):this.vector2InterpolateFunction(d,p,O);switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:return ie;case r.ANIMATIONLOOPMODE_RELATIVE:return ie.add(e.offsetValue.scale(e.repeatCount))}case r.ANIMATIONTYPE_SIZE:switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:return this.sizeInterpolateFunction(d,p,O);case r.ANIMATIONLOOPMODE_RELATIVE:return this.sizeInterpolateFunction(d,p,O).add(e.offsetValue.scale(e.repeatCount))}case r.ANIMATIONTYPE_COLOR3:switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:return this.color3InterpolateFunction(d,p,O);case r.ANIMATIONLOOPMODE_RELATIVE:return this.color3InterpolateFunction(d,p,O).add(e.offsetValue.scale(e.repeatCount))}case r.ANIMATIONTYPE_COLOR4:switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:return this.color4InterpolateFunction(d,p,O);case r.ANIMATIONLOOPMODE_RELATIVE:return this.color4InterpolateFunction(d,p,O).add(e.offsetValue.scale(e.repeatCount))}case r.ANIMATIONTYPE_MATRIX:switch(e.loopMode){case r.ANIMATIONLOOPMODE_CYCLE:case r.ANIMATIONLOOPMODE_CONSTANT:if(r.AllowMatricesInterpolation)return this.matrixInterpolateFunction(d,p,O,e.workValue);case r.ANIMATIONLOOPMODE_RELATIVE:return d}}break}}return this._getKeyValue(n[n.length-1].value)},r.prototype.matrixInterpolateFunction=function(t,e,n,i){return r.AllowMatrixDecomposeForInterpolation?i?(u.a.DecomposeLerpToRef(t,e,n,i),i):u.a.DecomposeLerp(t,e,n):i?(u.a.LerpToRef(t,e,n,i),i):u.a.Lerp(t,e,n)},r.prototype.clone=function(){var t=new r(this.name,this.targetPropertyPath.join("."),this.framePerSecond,this.dataType,this.loopMode);if(t.enableBlending=this.enableBlending,t.blendingSpeed=this.blendingSpeed,this._keys&&t.setKeys(this._keys),this._ranges)for(var e in t._ranges={},this._ranges){var n=this._ranges[e];n&&(t._ranges[e]=n.clone())}return t},r.prototype.setKeys=function(t){this._keys=t.slice(0)},r.prototype.serialize=function(){var t={};t.name=this.name,t.property=this.targetProperty,t.framePerSecond=this.framePerSecond,t.dataType=this.dataType,t.loopBehavior=this.loopMode,t.enableBlending=this.enableBlending,t.blendingSpeed=this.blendingSpeed;var e=this.dataType;t.keys=[];for(var n=this.getKeys(),i=0;i<n.length;i++){var o=n[i],a={};switch(a.frame=o.frame,e){case r.ANIMATIONTYPE_FLOAT:a.values=[o.value],o.inTangent!==void 0&&a.values.push(o.inTangent),o.outTangent!==void 0&&(o.inTangent===void 0&&a.values.push(void 0),a.values.push(o.outTangent));break;case r.ANIMATIONTYPE_QUATERNION:case r.ANIMATIONTYPE_MATRIX:case r.ANIMATIONTYPE_VECTOR3:case r.ANIMATIONTYPE_COLOR3:case r.ANIMATIONTYPE_COLOR4:a.values=o.value.asArray(),o.inTangent!=null&&a.values.push(o.inTangent.asArray()),o.outTangent!=null&&(o.inTangent===void 0&&a.values.push(void 0),a.values.push(o.outTangent.asArray()))}t.keys.push(a)}for(var s in t.ranges=[],this._ranges){var d=this._ranges[s];if(d){var p={};p.name=s,p.from=d.from,p.to=d.to,t.ranges.push(p)}}return t},r._UniversalLerp=function(t,e,n){var i=t.constructor;return i.Lerp?i.Lerp(t,e,n):i.Slerp?i.Slerp(t,e,n):t.toFixed?t*(1-n)+n*e:e},r.Parse=function(t){var e,n,i=new r(t.name,t.property,t.framePerSecond,t.dataType,t.loopBehavior),o=t.dataType,a=[];for(t.enableBlending&&(i.enableBlending=t.enableBlending),t.blendingSpeed&&(i.blendingSpeed=t.blendingSpeed),n=0;n<t.keys.length;n++){var s,d,p=t.keys[n];switch(o){case r.ANIMATIONTYPE_FLOAT:e=p.values[0],p.values.length>=1&&(s=p.values[1]),p.values.length>=2&&(d=p.values[2]);break;case r.ANIMATIONTYPE_QUATERNION:if(e=u.b.FromArray(p.values),p.values.length>=8){var b=u.b.FromArray(p.values.slice(4,8));b.equals(u.b.Zero())||(s=b)}if(p.values.length>=12){var P=u.b.FromArray(p.values.slice(8,12));P.equals(u.b.Zero())||(d=P)}break;case r.ANIMATIONTYPE_MATRIX:e=u.a.FromArray(p.values);break;case r.ANIMATIONTYPE_COLOR3:e=M.a.FromArray(p.values);break;case r.ANIMATIONTYPE_COLOR4:e=M.b.FromArray(p.values);break;case r.ANIMATIONTYPE_VECTOR3:default:e=u.e.FromArray(p.values)}var O={};O.frame=p.frame,O.value=e,s!=null&&(O.inTangent=s),d!=null&&(O.outTangent=d),a.push(O)}if(i.setKeys(a),t.ranges)for(n=0;n<t.ranges.length;n++)e=t.ranges[n],i.createRange(e.name,e.from,e.to);return i},r.AppendSerializedAnimations=function(t,e){L.a.AppendSerializedAnimations(t,e)},r.ParseFromFileAsync=function(t,e){var n=this;return new Promise(function(i,o){var a=new re.a;a.addEventListener("readystatechange",function(){if(a.readyState==4)if(a.status==200){var s=JSON.parse(a.responseText);if(s.length){for(var d=new Array,p=0,b=s;p<b.length;p++){var P=b[p];d.push(n.Parse(P))}i(d)}else d=n.Parse(s),t&&(d.name=t),i(d)}else o("Unable to load the animation")}),a.open("GET",e),a.send()})},r.CreateFromSnippetAsync=function(t){var e=this;return new Promise(function(n,i){var o=new re.a;o.addEventListener("readystatechange",function(){if(o.readyState==4)if(o.status==200){var a=JSON.parse(JSON.parse(o.responseText).jsonPayload);if(a.animations){for(var s=JSON.parse(a.animations),d=new Array,p=0,b=s;p<b.length;p++){var P=b[p];d.push(e.Parse(P))}n(d)}else s=JSON.parse(a.animation),(d=e.Parse(s)).snippetId=t,n(d)}else i("Unable to load the snippet "+t)}),o.open("GET",e.SnippetUrl+"/"+t.replace(/#/g,"/")),o.send()})},r.AllowMatricesInterpolation=!1,r.AllowMatrixDecomposeForInterpolation=!0,r.SnippetUrl="https://snippet.babylonjs.com",r.ANIMATIONTYPE_FLOAT=0,r.ANIMATIONTYPE_VECTOR3=1,r.ANIMATIONTYPE_QUATERNION=2,r.ANIMATIONTYPE_MATRIX=3,r.ANIMATIONTYPE_COLOR3=4,r.ANIMATIONTYPE_COLOR4=7,r.ANIMATIONTYPE_VECTOR2=5,r.ANIMATIONTYPE_SIZE=6,r.ANIMATIONLOOPMODE_RELATIVE=0,r.ANIMATIONLOOPMODE_CYCLE=1,r.ANIMATIONLOOPMODE_CONSTANT=2,r}();R.a.RegisteredTypes["BABYLON.Animation"]=k,Q.a._AnimationRangeFactory=function(r,t,e){return new G(r,t,e)};var H=function(r){function t(e,n,i,o,a,s,d,p){a===void 0&&(a=1e3);var b=r.call(this,e,s)||this;return b.duration=1e3,b.onInterpolationDoneObservable=new C.c,b.propertyPath=i,b.value=o,b.duration=a,b.stopOtherAnimations=d,b.onInterpolationDone=p,b._target=b._effectiveTarget=n,b}return Object(c.d)(t,r),t.prototype._prepare=function(){this._effectiveTarget=this._getEffectiveTarget(this._effectiveTarget,this.propertyPath),this._property=this._getProperty(this.propertyPath)},t.prototype.execute=function(){var e,n=this,i=this._actionManager.getScene(),o=[{frame:0,value:this._effectiveTarget[this._property]},{frame:100,value:this.value}];if(typeof this.value=="number")e=k.ANIMATIONTYPE_FLOAT;else if(this.value instanceof M.a)e=k.ANIMATIONTYPE_COLOR3;else if(this.value instanceof u.e)e=k.ANIMATIONTYPE_VECTOR3;else if(this.value instanceof u.a)e=k.ANIMATIONTYPE_MATRIX;else{if(!(this.value instanceof u.b))return void l.a.Warn("InterpolateValueAction: Unsupported type ("+typeof this.value+")");e=k.ANIMATIONTYPE_QUATERNION}var a=new k("InterpolateValueAction",this._property,1e3/this.duration*100,e,k.ANIMATIONLOOPMODE_CONSTANT);a.setKeys(o),this.stopOtherAnimations&&i.stopAnimation(this._effectiveTarget),i.beginDirectAnimation(this._effectiveTarget,[a],0,100,!1,1,function(){n.onInterpolationDoneObservable.notifyObservers(n),n.onInterpolationDone&&n.onInterpolationDone()})},t.prototype.serialize=function(e){return r.prototype._serialize.call(this,{name:"InterpolateValueAction",properties:[x._GetTargetProperty(this._target),{name:"propertyPath",value:this.propertyPath},{name:"value",value:x._SerializeValueAsString(this.value)},{name:"duration",value:x._SerializeValueAsString(this.duration)},{name:"stopOtherAnimations",value:x._SerializeValueAsString(this.stopOtherAnimations)||!1}]},e)},t}(x);R.a.RegisteredTypes["BABYLON.InterpolateValueAction"]=H;var Z=Object.freeze(new u.b(0,0,0,0)),W=Object.freeze(u.e.Zero()),q=Object.freeze(u.d.Zero()),he=Object.freeze(oe.a.Zero()),ge=Object.freeze(M.a.Black()),me=function(){function r(t,e,n,i){var o=this;if(this._events=new Array,this._currentFrame=0,this._originalValue=new Array,this._originalBlendValue=null,this._offsetsCache={},this._highLimitsCache={},this._stopped=!1,this._blendingFactor=0,this._currentValue=null,this._currentActiveTarget=null,this._directTarget=null,this._targetPath="",this._weight=1,this._ratioOffset=0,this._previousDelay=0,this._previousRatio=0,this._targetIsArray=!1,this._animation=e,this._target=t,this._scene=n,this._host=i,this._activeTargets=[],e._runtimeAnimations.push(this),this._animationState={key:0,repeatCount:0,loopMode:this._getCorrectLoopMode()},this._animation.dataType===k.ANIMATIONTYPE_MATRIX&&(this._animationState.workValue=u.a.Zero()),this._keys=this._animation.getKeys(),this._minFrame=this._keys[0].frame,this._maxFrame=this._keys[this._keys.length-1].frame,this._minValue=this._keys[0].value,this._maxValue=this._keys[this._keys.length-1].value,this._minFrame!==0){var a={frame:0,value:this._minValue};this._keys.splice(0,0,a)}if(this._target instanceof Array){for(var s=0,d=0,p=this._target;d<p.length;d++){var b=p[d];this._preparePath(b,s),this._getOriginalValues(s),s++}this._targetIsArray=!0}else this._preparePath(this._target),this._getOriginalValues(),this._targetIsArray=!1,this._directTarget=this._activeTargets[0];var P=e.getEvents();P&&P.length>0&&P.forEach(function(O){o._events.push(O._clone())}),this._enableBlending=t&&t.animationPropertiesOverride?t.animationPropertiesOverride.enableBlending:this._animation.enableBlending}return Object.defineProperty(r.prototype,"currentFrame",{get:function(){return this._currentFrame},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"weight",{get:function(){return this._weight},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"currentValue",{get:function(){return this._currentValue},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"targetPath",{get:function(){return this._targetPath},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"target",{get:function(){return this._currentActiveTarget},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isAdditive",{get:function(){return this._host&&this._host.isAdditive},enumerable:!1,configurable:!0}),r.prototype._preparePath=function(t,e){e===void 0&&(e=0);var n=this._animation.targetPropertyPath;if(n.length>1){for(var i=t[n[0]],o=1;o<n.length-1;o++)i=i[n[o]];this._targetPath=n[n.length-1],this._activeTargets[e]=i}else this._targetPath=n[0],this._activeTargets[e]=t},Object.defineProperty(r.prototype,"animation",{get:function(){return this._animation},enumerable:!1,configurable:!0}),r.prototype.reset=function(t){if(t===void 0&&(t=!1),t)if(this._target instanceof Array)for(var e=0,n=0,i=this._target;n<i.length;n++){var o=i[n];this._originalValue[e]!==void 0&&this._setValue(o,this._activeTargets[e],this._originalValue[e],-1,e),e++}else this._originalValue[0]!==void 0&&this._setValue(this._target,this._directTarget,this._originalValue[0],-1,0);for(this._offsetsCache={},this._highLimitsCache={},this._currentFrame=0,this._blendingFactor=0,e=0;e<this._events.length;e++)this._events[e].isDone=!1},r.prototype.isStopped=function(){return this._stopped},r.prototype.dispose=function(){var t=this._animation.runtimeAnimations.indexOf(this);t>-1&&this._animation.runtimeAnimations.splice(t,1)},r.prototype.setValue=function(t,e){if(this._targetIsArray)for(var n=0;n<this._target.length;n++){var i=this._target[n];this._setValue(i,this._activeTargets[n],t,e,n)}else this._setValue(this._target,this._directTarget,t,e,0)},r.prototype._getOriginalValues=function(t){var e;t===void 0&&(t=0);var n=this._activeTargets[t];(e=n.getRestPose&&this._targetPath==="_matrix"?n.getRestPose():n[this._targetPath])&&e.clone?this._originalValue[t]=e.clone():this._originalValue[t]=e},r.prototype._setValue=function(t,e,n,i,o){if(this._currentActiveTarget=e,this._weight=i,this._enableBlending&&this._blendingFactor<=1){if(!this._originalBlendValue){var a=e[this._targetPath];a.clone?this._originalBlendValue=a.clone():this._originalBlendValue=a}this._originalBlendValue.m?k.AllowMatrixDecomposeForInterpolation?this._currentValue?u.a.DecomposeLerpToRef(this._originalBlendValue,n,this._blendingFactor,this._currentValue):this._currentValue=u.a.DecomposeLerp(this._originalBlendValue,n,this._blendingFactor):this._currentValue?u.a.LerpToRef(this._originalBlendValue,n,this._blendingFactor,this._currentValue):this._currentValue=u.a.Lerp(this._originalBlendValue,n,this._blendingFactor):this._currentValue=k._UniversalLerp(this._originalBlendValue,n,this._blendingFactor);var s=t&&t.animationPropertiesOverride?t.animationPropertiesOverride.blendingSpeed:this._animation.blendingSpeed;this._blendingFactor+=s}else this._currentValue=n;i!==-1?this._scene._registerTargetForLateAnimationBinding(this,this._originalValue[o]):e[this._targetPath]=this._currentValue,t.markAsDirty&&t.markAsDirty(this._animation.targetProperty)},r.prototype._getCorrectLoopMode=function(){return this._target&&this._target.animationPropertiesOverride?this._target.animationPropertiesOverride.loopMode:this._animation.loopMode},r.prototype.goToFrame=function(t){var e=this._animation.getKeys();t<e[0].frame?t=e[0].frame:t>e[e.length-1].frame&&(t=e[e.length-1].frame);var n=this._events;if(n.length)for(var i=0;i<n.length;i++)n[i].onlyOnce||(n[i].isDone=n[i].frame<t);this._currentFrame=t;var o=this._animation._interpolate(t,this._animationState);this.setValue(o,-1)},r.prototype._prepareForSpeedRatioChange=function(t){var e=this._previousDelay*(this._animation.framePerSecond*t)/1e3;this._ratioOffset=this._previousRatio-e},r.prototype.animate=function(t,e,n,i,o,a){a===void 0&&(a=-1);var s=this._animation,d=s.targetPropertyPath;if(!d||d.length<1)return this._stopped=!0,!1;var p=!0;(e<this._minFrame||e>this._maxFrame)&&(e=this._minFrame),(n<this._minFrame||n>this._maxFrame)&&(n=this._maxFrame);var b,P,O=n-e,B=t*(s.framePerSecond*o)/1e3+this._ratioOffset,F=0;if(this._previousDelay=t,this._previousRatio=B,!i&&n>=e&&B>=O)p=!1,F=s._getKeyValue(this._maxValue);else if(!i&&e>=n&&B<=O)p=!1,F=s._getKeyValue(this._minValue);else if(this._animationState.loopMode!==k.ANIMATIONLOOPMODE_CYCLE){var z=n.toString()+e.toString();if(!this._offsetsCache[z]){this._animationState.repeatCount=0,this._animationState.loopMode=k.ANIMATIONLOOPMODE_CYCLE;var J=s._interpolate(e,this._animationState),ie=s._interpolate(n,this._animationState);switch(this._animationState.loopMode=this._getCorrectLoopMode(),s.dataType){case k.ANIMATIONTYPE_FLOAT:this._offsetsCache[z]=ie-J;break;case k.ANIMATIONTYPE_QUATERNION:this._offsetsCache[z]=ie.subtract(J);break;case k.ANIMATIONTYPE_VECTOR3:this._offsetsCache[z]=ie.subtract(J);case k.ANIMATIONTYPE_VECTOR2:this._offsetsCache[z]=ie.subtract(J);case k.ANIMATIONTYPE_SIZE:this._offsetsCache[z]=ie.subtract(J);case k.ANIMATIONTYPE_COLOR3:this._offsetsCache[z]=ie.subtract(J)}this._highLimitsCache[z]=ie}F=this._highLimitsCache[z],b=this._offsetsCache[z]}if(b===void 0)switch(s.dataType){case k.ANIMATIONTYPE_FLOAT:b=0;break;case k.ANIMATIONTYPE_QUATERNION:b=Z;break;case k.ANIMATIONTYPE_VECTOR3:b=W;break;case k.ANIMATIONTYPE_VECTOR2:b=q;break;case k.ANIMATIONTYPE_SIZE:b=he;break;case k.ANIMATIONTYPE_COLOR3:b=ge}if(this._host&&this._host.syncRoot){var se=this._host.syncRoot;P=e+(n-e)*((se.masterFrame-se.fromFrame)/(se.toFrame-se.fromFrame))}else P=p&&O!==0?e+B%O:n;var ce=this._events;if((O>0&&this.currentFrame>P||O<0&&this.currentFrame<P)&&(this._onLoop(),ce.length))for(var ue=0;ue<ce.length;ue++)ce[ue].onlyOnce||(ce[ue].isDone=!1);this._currentFrame=P,this._animationState.repeatCount=O===0?0:B/O>>0,this._animationState.highLimitValue=F,this._animationState.offsetValue=b;var fe=s._interpolate(P,this._animationState);if(this.setValue(fe,a),ce.length){for(ue=0;ue<ce.length;ue++)if(O>0&&P>=ce[ue].frame&&ce[ue].frame>=e||O<0&&P<=ce[ue].frame&&ce[ue].frame<=e){var ve=ce[ue];ve.isDone||(ve.onlyOnce&&(ce.splice(ue,1),ue--),ve.isDone=!0,ve.action(P))}}return p||(this._stopped=!0),p},r}(),_e=f(20),be=f(57),Pe=f(44),ye=f(23),Be=function(r){function t(e,n,i,o,a,s,d){i===void 0&&(i=null),o===void 0&&(o=null),a===void 0&&(a=null),s===void 0&&(s=null),d===void 0&&(d=null);var p=r.call(this,e,n.getScene())||this;return p.name=e,p.children=new Array,p.animations=new Array,p._index=null,p._absoluteTransform=new u.a,p._invertedAbsoluteTransform=new u.a,p._scalingDeterminant=1,p._worldTransform=new u.a,p._needToDecompose=!0,p._needToCompose=!1,p._linkedTransformNode=null,p._waitingTransformNodeId=null,p._skeleton=n,p._localMatrix=o?o.clone():u.a.Identity(),p._restPose=a||p._localMatrix.clone(),p._bindPose=p._localMatrix.clone(),p._baseMatrix=s||p._localMatrix.clone(),p._index=d,n.bones.push(p),p.setParent(i,!1),(s||o)&&p._updateDifferenceMatrix(),p}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"_matrix",{get:function(){return this._compose(),this._localMatrix},set:function(e){this._localMatrix.copyFrom(e),this._needToDecompose=!0},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"Bone"},t.prototype.getSkeleton=function(){return this._skeleton},t.prototype.getParent=function(){return this._parent},t.prototype.getChildren=function(){return this.children},t.prototype.getIndex=function(){return this._index===null?this.getSkeleton().bones.indexOf(this):this._index},t.prototype.setParent=function(e,n){if(n===void 0&&(n=!0),this._parent!==e){if(this._parent){var i=this._parent.children.indexOf(this);i!==-1&&this._parent.children.splice(i,1)}this._parent=e,this._parent&&this._parent.children.push(this),n&&this._updateDifferenceMatrix(),this.markAsDirty()}},t.prototype.getLocalMatrix=function(){return this._compose(),this._localMatrix},t.prototype.getBaseMatrix=function(){return this._baseMatrix},t.prototype.getRestPose=function(){return this._restPose},t.prototype.setRestPose=function(e){this._restPose.copyFrom(e)},t.prototype.getBindPose=function(){return this._bindPose},t.prototype.setBindPose=function(e){this._bindPose.copyFrom(e)},t.prototype.getWorldMatrix=function(){return this._worldTransform},t.prototype.returnToRest=function(){this._skeleton._numBonesWithLinkedTransformNode>0?this.updateMatrix(this._restPose,!1,!1):this.updateMatrix(this._restPose,!1,!0)},t.prototype.getInvertedAbsoluteTransform=function(){return this._invertedAbsoluteTransform},t.prototype.getAbsoluteTransform=function(){return this._absoluteTransform},t.prototype.linkTransformNode=function(e){this._linkedTransformNode&&this._skeleton._numBonesWithLinkedTransformNode--,this._linkedTransformNode=e,this._linkedTransformNode&&this._skeleton._numBonesWithLinkedTransformNode++},t.prototype.getTransformNode=function(){return this._linkedTransformNode},Object.defineProperty(t.prototype,"position",{get:function(){return this._decompose(),this._localPosition},set:function(e){this._decompose(),this._localPosition.copyFrom(e),this._markAsDirtyAndCompose()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rotation",{get:function(){return this.getRotation()},set:function(e){this.setRotation(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rotationQuaternion",{get:function(){return this._decompose(),this._localRotation},set:function(e){this.setRotationQuaternion(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"scaling",{get:function(){return this.getScale()},set:function(e){this.setScale(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"animationPropertiesOverride",{get:function(){return this._skeleton.animationPropertiesOverride},enumerable:!1,configurable:!0}),t.prototype._decompose=function(){this._needToDecompose&&(this._needToDecompose=!1,this._localScaling||(this._localScaling=u.e.Zero(),this._localRotation=u.b.Zero(),this._localPosition=u.e.Zero()),this._localMatrix.decompose(this._localScaling,this._localRotation,this._localPosition))},t.prototype._compose=function(){this._needToCompose&&(this._localScaling?(this._needToCompose=!1,u.a.ComposeToRef(this._localScaling,this._localRotation,this._localPosition,this._localMatrix)):this._needToCompose=!1)},t.prototype.updateMatrix=function(e,n,i){n===void 0&&(n=!0),i===void 0&&(i=!0),this._baseMatrix.copyFrom(e),n&&this._updateDifferenceMatrix(),i?(this._needToCompose=!1,this._localMatrix.copyFrom(e),this._markAsDirtyAndDecompose()):this.markAsDirty()},t.prototype._updateDifferenceMatrix=function(e,n){if(n===void 0&&(n=!0),e||(e=this._baseMatrix),this._parent?e.multiplyToRef(this._parent._absoluteTransform,this._absoluteTransform):this._absoluteTransform.copyFrom(e),this._absoluteTransform.invertToRef(this._invertedAbsoluteTransform),n)for(var i=0;i<this.children.length;i++)this.children[i]._updateDifferenceMatrix();this._scalingDeterminant=this._absoluteTransform.determinant()<0?-1:1},t.prototype.markAsDirty=function(){this._currentRenderId++,this._childUpdateId++,this._skeleton._markAsDirty()},t.prototype._markAsDirtyAndCompose=function(){this.markAsDirty(),this._needToCompose=!0},t.prototype._markAsDirtyAndDecompose=function(){this.markAsDirty(),this._needToDecompose=!0},t.prototype.translate=function(e,n,i){n===void 0&&(n=ye.c.LOCAL);var o=this.getLocalMatrix();if(n==ye.c.LOCAL)o.addAtIndex(12,e.x),o.addAtIndex(13,e.y),o.addAtIndex(14,e.z);else{var a=null;i&&(a=i.getWorldMatrix()),this._skeleton.computeAbsoluteTransforms();var s=t._tmpMats[0],d=t._tmpVecs[0];this._parent?i&&a?(s.copyFrom(this._parent.getAbsoluteTransform()),s.multiplyToRef(a,s)):s.copyFrom(this._parent.getAbsoluteTransform()):u.a.IdentityToRef(s),s.setTranslationFromFloats(0,0,0),s.invert(),u.e.TransformCoordinatesToRef(e,s,d),o.addAtIndex(12,d.x),o.addAtIndex(13,d.y),o.addAtIndex(14,d.z)}this._markAsDirtyAndDecompose()},t.prototype.setPosition=function(e,n,i){n===void 0&&(n=ye.c.LOCAL);var o=this.getLocalMatrix();if(n==ye.c.LOCAL)o.setTranslationFromFloats(e.x,e.y,e.z);else{var a=null;i&&(a=i.getWorldMatrix()),this._skeleton.computeAbsoluteTransforms();var s=t._tmpMats[0],d=t._tmpVecs[0];this._parent?(i&&a?(s.copyFrom(this._parent.getAbsoluteTransform()),s.multiplyToRef(a,s)):s.copyFrom(this._parent.getAbsoluteTransform()),s.invert()):u.a.IdentityToRef(s),u.e.TransformCoordinatesToRef(e,s,d),o.setTranslationFromFloats(d.x,d.y,d.z)}this._markAsDirtyAndDecompose()},t.prototype.setAbsolutePosition=function(e,n){this.setPosition(e,ye.c.WORLD,n)},t.prototype.scale=function(e,n,i,o){o===void 0&&(o=!1);var a=this.getLocalMatrix(),s=t._tmpMats[0];u.a.ScalingToRef(e,n,i,s),s.multiplyToRef(a,a),s.invert();for(var d=0,p=this.children;d<p.length;d++){var b=(B=p[d]).getLocalMatrix();b.multiplyToRef(s,b),b.multiplyAtIndex(12,e),b.multiplyAtIndex(13,n),b.multiplyAtIndex(14,i),B._markAsDirtyAndDecompose()}if(this._markAsDirtyAndDecompose(),o)for(var P=0,O=this.children;P<O.length;P++){var B;(B=O[P]).scale(e,n,i,o)}},t.prototype.setScale=function(e){this._decompose(),this._localScaling.copyFrom(e),this._markAsDirtyAndCompose()},t.prototype.getScale=function(){return this._decompose(),this._localScaling},t.prototype.getScaleToRef=function(e){this._decompose(),e.copyFrom(this._localScaling)},t.prototype.setYawPitchRoll=function(e,n,i,o,a){if(o===void 0&&(o=ye.c.LOCAL),o===ye.c.LOCAL){var s=t._tmpQuat;return u.b.RotationYawPitchRollToRef(e,n,i,s),void this.setRotationQuaternion(s,o,a)}var d=t._tmpMats[0];if(this._getNegativeRotationToRef(d,a)){var p=t._tmpMats[1];u.a.RotationYawPitchRollToRef(e,n,i,p),d.multiplyToRef(p,p),this._rotateWithMatrix(p,o,a)}},t.prototype.rotate=function(e,n,i,o){i===void 0&&(i=ye.c.LOCAL);var a=t._tmpMats[0];a.setTranslationFromFloats(0,0,0),u.a.RotationAxisToRef(e,n,a),this._rotateWithMatrix(a,i,o)},t.prototype.setAxisAngle=function(e,n,i,o){if(i===void 0&&(i=ye.c.LOCAL),i===ye.c.LOCAL){var a=t._tmpQuat;return u.b.RotationAxisToRef(e,n,a),void this.setRotationQuaternion(a,i,o)}var s=t._tmpMats[0];if(this._getNegativeRotationToRef(s,o)){var d=t._tmpMats[1];u.a.RotationAxisToRef(e,n,d),s.multiplyToRef(d,d),this._rotateWithMatrix(d,i,o)}},t.prototype.setRotation=function(e,n,i){n===void 0&&(n=ye.c.LOCAL),this.setYawPitchRoll(e.y,e.x,e.z,n,i)},t.prototype.setRotationQuaternion=function(e,n,i){if(n===void 0&&(n=ye.c.LOCAL),n===ye.c.LOCAL)return this._decompose(),this._localRotation.copyFrom(e),void this._markAsDirtyAndCompose();var o=t._tmpMats[0];if(this._getNegativeRotationToRef(o,i)){var a=t._tmpMats[1];u.a.FromQuaternionToRef(e,a),o.multiplyToRef(a,a),this._rotateWithMatrix(a,n,i)}},t.prototype.setRotationMatrix=function(e,n,i){if(n===void 0&&(n=ye.c.LOCAL),n===ye.c.LOCAL){var o=t._tmpQuat;return u.b.FromRotationMatrixToRef(e,o),void this.setRotationQuaternion(o,n,i)}var a=t._tmpMats[0];if(this._getNegativeRotationToRef(a,i)){var s=t._tmpMats[1];s.copyFrom(e),a.multiplyToRef(e,s),this._rotateWithMatrix(s,n,i)}},t.prototype._rotateWithMatrix=function(e,n,i){n===void 0&&(n=ye.c.LOCAL);var o=this.getLocalMatrix(),a=o.m[12],s=o.m[13],d=o.m[14],p=this.getParent(),b=t._tmpMats[3],P=t._tmpMats[4];p&&n==ye.c.WORLD?(i?(b.copyFrom(i.getWorldMatrix()),p.getAbsoluteTransform().multiplyToRef(b,b)):b.copyFrom(p.getAbsoluteTransform()),P.copyFrom(b),P.invert(),o.multiplyToRef(b,o),o.multiplyToRef(e,o),o.multiplyToRef(P,o)):n==ye.c.WORLD&&i?(b.copyFrom(i.getWorldMatrix()),P.copyFrom(b),P.invert(),o.multiplyToRef(b,o),o.multiplyToRef(e,o),o.multiplyToRef(P,o)):o.multiplyToRef(e,o),o.setTranslationFromFloats(a,s,d),this.computeAbsoluteTransforms(),this._markAsDirtyAndDecompose()},t.prototype._getNegativeRotationToRef=function(e,n){var i=t._tmpMats[2];return e.copyFrom(this.getAbsoluteTransform()),n&&(e.multiplyToRef(n.getWorldMatrix(),e),u.a.ScalingToRef(n.scaling.x,n.scaling.y,n.scaling.z,i)),e.invert(),!isNaN(e.m[0])&&(i.multiplyAtIndex(0,this._scalingDeterminant),e.multiplyToRef(i,e),!0)},t.prototype.getPosition=function(e,n){e===void 0&&(e=ye.c.LOCAL),n===void 0&&(n=null);var i=u.e.Zero();return this.getPositionToRef(e,n,i),i},t.prototype.getPositionToRef=function(e,n,i){if(e===void 0&&(e=ye.c.LOCAL),e==ye.c.LOCAL){var o=this.getLocalMatrix();i.x=o.m[12],i.y=o.m[13],i.z=o.m[14]}else{var a=null;n&&(a=n.getWorldMatrix()),this._skeleton.computeAbsoluteTransforms();var s=t._tmpMats[0];n&&a?(s.copyFrom(this.getAbsoluteTransform()),s.multiplyToRef(a,s)):s=this.getAbsoluteTransform(),i.x=s.m[12],i.y=s.m[13],i.z=s.m[14]}},t.prototype.getAbsolutePosition=function(e){e===void 0&&(e=null);var n=u.e.Zero();return this.getPositionToRef(ye.c.WORLD,e,n),n},t.prototype.getAbsolutePositionToRef=function(e,n){this.getPositionToRef(ye.c.WORLD,e,n)},t.prototype.computeAbsoluteTransforms=function(){if(this._compose(),this._parent)this._localMatrix.multiplyToRef(this._parent._absoluteTransform,this._absoluteTransform);else{this._absoluteTransform.copyFrom(this._localMatrix);var e=this._skeleton.getPoseMatrix();e&&this._absoluteTransform.multiplyToRef(e,this._absoluteTransform)}for(var n=this.children,i=n.length,o=0;o<i;o++)n[o].computeAbsoluteTransforms()},t.prototype.getDirection=function(e,n){n===void 0&&(n=null);var i=u.e.Zero();return this.getDirectionToRef(e,n,i),i},t.prototype.getDirectionToRef=function(e,n,i){n===void 0&&(n=null);var o=null;n&&(o=n.getWorldMatrix()),this._skeleton.computeAbsoluteTransforms();var a=t._tmpMats[0];a.copyFrom(this.getAbsoluteTransform()),n&&o&&a.multiplyToRef(o,a),u.e.TransformNormalToRef(e,a,i),i.normalize()},t.prototype.getRotation=function(e,n){e===void 0&&(e=ye.c.LOCAL),n===void 0&&(n=null);var i=u.e.Zero();return this.getRotationToRef(e,n,i),i},t.prototype.getRotationToRef=function(e,n,i){e===void 0&&(e=ye.c.LOCAL),n===void 0&&(n=null);var o=t._tmpQuat;this.getRotationQuaternionToRef(e,n,o),o.toEulerAnglesToRef(i)},t.prototype.getRotationQuaternion=function(e,n){e===void 0&&(e=ye.c.LOCAL),n===void 0&&(n=null);var i=u.b.Identity();return this.getRotationQuaternionToRef(e,n,i),i},t.prototype.getRotationQuaternionToRef=function(e,n,i){if(e===void 0&&(e=ye.c.LOCAL),n===void 0&&(n=null),e==ye.c.LOCAL)this._decompose(),i.copyFrom(this._localRotation);else{var o=t._tmpMats[0],a=this.getAbsoluteTransform();n?a.multiplyToRef(n.getWorldMatrix(),o):o.copyFrom(a),o.multiplyAtIndex(0,this._scalingDeterminant),o.multiplyAtIndex(1,this._scalingDeterminant),o.multiplyAtIndex(2,this._scalingDeterminant),o.decompose(void 0,i,void 0)}},t.prototype.getRotationMatrix=function(e,n){e===void 0&&(e=ye.c.LOCAL);var i=u.a.Identity();return this.getRotationMatrixToRef(e,n,i),i},t.prototype.getRotationMatrixToRef=function(e,n,i){if(e===void 0&&(e=ye.c.LOCAL),e==ye.c.LOCAL)this.getLocalMatrix().getRotationMatrixToRef(i);else{var o=t._tmpMats[0],a=this.getAbsoluteTransform();n?a.multiplyToRef(n.getWorldMatrix(),o):o.copyFrom(a),o.multiplyAtIndex(0,this._scalingDeterminant),o.multiplyAtIndex(1,this._scalingDeterminant),o.multiplyAtIndex(2,this._scalingDeterminant),o.getRotationMatrixToRef(i)}},t.prototype.getAbsolutePositionFromLocal=function(e,n){n===void 0&&(n=null);var i=u.e.Zero();return this.getAbsolutePositionFromLocalToRef(e,n,i),i},t.prototype.getAbsolutePositionFromLocalToRef=function(e,n,i){n===void 0&&(n=null);var o=null;n&&(o=n.getWorldMatrix()),this._skeleton.computeAbsoluteTransforms();var a=t._tmpMats[0];n&&o?(a.copyFrom(this.getAbsoluteTransform()),a.multiplyToRef(o,a)):a=this.getAbsoluteTransform(),u.e.TransformCoordinatesToRef(e,a,i)},t.prototype.getLocalPositionFromAbsolute=function(e,n){n===void 0&&(n=null);var i=u.e.Zero();return this.getLocalPositionFromAbsoluteToRef(e,n,i),i},t.prototype.getLocalPositionFromAbsoluteToRef=function(e,n,i){n===void 0&&(n=null);var o=null;n&&(o=n.getWorldMatrix()),this._skeleton.computeAbsoluteTransforms();var a=t._tmpMats[0];a.copyFrom(this.getAbsoluteTransform()),n&&o&&a.multiplyToRef(o,a),a.invert(),u.e.TransformCoordinatesToRef(e,a,i)},t.prototype.setCurrentPoseAsRest=function(){this.setRestPose(this.getLocalMatrix())},t._tmpVecs=Pe.a.BuildArray(2,u.e.Zero),t._tmpQuat=u.b.Identity(),t._tmpMats=Pe.a.BuildArray(5,u.a.Identity),t}(Q.a),ke=function(){function r(t,e,n,i,o,a,s,d,p,b){n===void 0&&(n=0),i===void 0&&(i=100),o===void 0&&(o=!1),a===void 0&&(a=1),b===void 0&&(b=!1),this.target=e,this.fromFrame=n,this.toFrame=i,this.loopAnimation=o,this.onAnimationEnd=s,this.onAnimationLoop=p,this.isAdditive=b,this._localDelayOffset=null,this._pausedDelay=null,this._runtimeAnimations=new Array,this._paused=!1,this._speedRatio=1,this._weight=-1,this._syncRoot=null,this.disposeOnEnd=!0,this.animationStarted=!1,this.onAnimationEndObservable=new C.c,this.onAnimationLoopObservable=new C.c,this._scene=t,d&&this.appendAnimations(e,d),this._speedRatio=a,t._activeAnimatables.push(this)}return Object.defineProperty(r.prototype,"syncRoot",{get:function(){return this._syncRoot},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"masterFrame",{get:function(){return this._runtimeAnimations.length===0?0:this._runtimeAnimations[0].currentFrame},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"weight",{get:function(){return this._weight},set:function(t){this._weight=t!==-1?Math.min(Math.max(t,0),1):-1},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"speedRatio",{get:function(){return this._speedRatio},set:function(t){for(var e=0;e<this._runtimeAnimations.length;e++)this._runtimeAnimations[e]._prepareForSpeedRatioChange(t);this._speedRatio=t},enumerable:!1,configurable:!0}),r.prototype.syncWith=function(t){if(this._syncRoot=t,t){var e=this._scene._activeAnimatables.indexOf(this);e>-1&&(this._scene._activeAnimatables.splice(e,1),this._scene._activeAnimatables.push(this))}return this},r.prototype.getAnimations=function(){return this._runtimeAnimations},r.prototype.appendAnimations=function(t,e){for(var n=this,i=0;i<e.length;i++){var o=e[i],a=new me(t,o,this._scene,this);a._onLoop=function(){n.onAnimationLoopObservable.notifyObservers(n),n.onAnimationLoop&&n.onAnimationLoop()},this._runtimeAnimations.push(a)}},r.prototype.getAnimationByTargetProperty=function(t){for(var e=this._runtimeAnimations,n=0;n<e.length;n++)if(e[n].animation.targetProperty===t)return e[n].animation;return null},r.prototype.getRuntimeAnimationByTargetProperty=function(t){for(var e=this._runtimeAnimations,n=0;n<e.length;n++)if(e[n].animation.targetProperty===t)return e[n];return null},r.prototype.reset=function(){for(var t=this._runtimeAnimations,e=0;e<t.length;e++)t[e].reset(!0);this._localDelayOffset=null,this._pausedDelay=null},r.prototype.enableBlending=function(t){for(var e=this._runtimeAnimations,n=0;n<e.length;n++)e[n].animation.enableBlending=!0,e[n].animation.blendingSpeed=t},r.prototype.disableBlending=function(){for(var t=this._runtimeAnimations,e=0;e<t.length;e++)t[e].animation.enableBlending=!1},r.prototype.goToFrame=function(t){var e=this._runtimeAnimations;if(e[0]){var n=e[0].animation.framePerSecond,i=e[0].currentFrame,o=this.speedRatio===0?0:(t-i)/n*1e3/this.speedRatio;this._localDelayOffset===null&&(this._localDelayOffset=0),this._localDelayOffset-=o}for(var a=0;a<e.length;a++)e[a].goToFrame(t)},r.prototype.pause=function(){this._paused||(this._paused=!0)},r.prototype.restart=function(){this._paused=!1},r.prototype._raiseOnAnimationEnd=function(){this.onAnimationEnd&&this.onAnimationEnd(),this.onAnimationEndObservable.notifyObservers(this)},r.prototype.stop=function(t,e){if(t||e){var n=this._scene._activeAnimatables.indexOf(this);if(n>-1){for(var i=(a=this._runtimeAnimations).length-1;i>=0;i--){var o=a[i];t&&o.animation.name!=t||e&&!e(o.target)||(o.dispose(),a.splice(i,1))}a.length==0&&(this._scene._activeAnimatables.splice(n,1),this._raiseOnAnimationEnd())}}else if((i=this._scene._activeAnimatables.indexOf(this))>-1){this._scene._activeAnimatables.splice(i,1);var a=this._runtimeAnimations;for(i=0;i<a.length;i++)a[i].dispose();this._raiseOnAnimationEnd()}},r.prototype.waitAsync=function(){var t=this;return new Promise(function(e,n){t.onAnimationEndObservable.add(function(){e(t)},void 0,void 0,t,!0)})},r.prototype._animate=function(t){if(this._paused)return this.animationStarted=!1,this._pausedDelay===null&&(this._pausedDelay=t),!0;if(this._localDelayOffset===null?(this._localDelayOffset=t,this._pausedDelay=null):this._pausedDelay!==null&&(this._localDelayOffset+=t-this._pausedDelay,this._pausedDelay=null),this._weight===0)return!0;var e,n=!1,i=this._runtimeAnimations;for(e=0;e<i.length;e++){var o=i[e].animate(t-this._localDelayOffset,this.fromFrame,this.toFrame,this.loopAnimation,this._speedRatio,this._weight);n=n||o}if(this.animationStarted=n,!n){if(this.disposeOnEnd)for(e=this._scene._activeAnimatables.indexOf(this),this._scene._activeAnimatables.splice(e,1),e=0;e<i.length;e++)i[e].dispose();this._raiseOnAnimationEnd(),this.disposeOnEnd&&(this.onAnimationEnd=null,this.onAnimationLoop=null,this.onAnimationLoopObservable.clear(),this.onAnimationEndObservable.clear())}return n},r}();_e.a.prototype._animate=function(){if(this.animationsEnabled){var r=be.a.Now;if(!this._animationTimeLast){if(this._pendingData.length>0)return;this._animationTimeLast=r}this.deltaTime=this.useConstantAnimationDeltaTime?16:(r-this._animationTimeLast)*this.animationTimeScale,this._animationTimeLast=r;var t=this._activeAnimatables;if(t.length!==0){this._animationTime+=this.deltaTime;for(var e=this._animationTime,n=0;n<t.length;n++){var i=t[n];!i._animate(e)&&i.disposeOnEnd&&n--}this._processLateAnimationBindings()}}},_e.a.prototype.beginWeightedAnimation=function(r,t,e,n,i,o,a,s,d,p,b){n===void 0&&(n=1),o===void 0&&(o=1),b===void 0&&(b=!1);var P=this.beginAnimation(r,t,e,i,o,a,s,!1,d,p,b);return P.weight=n,P},_e.a.prototype.beginAnimation=function(r,t,e,n,i,o,a,s,d,p,b){i===void 0&&(i=1),s===void 0&&(s=!0),b===void 0&&(b=!1),t>e&&i>0&&(i*=-1),s&&this.stopAnimation(r,void 0,d),a||(a=new ke(this,r,t,e,n,i,o,void 0,p,b));var P=!d||d(r);if(r.animations&&P&&a.appendAnimations(r,r.animations),r.getAnimatables)for(var O=r.getAnimatables(),B=0;B<O.length;B++)this.beginAnimation(O[B],t,e,n,i,o,a,s,d,p);return a.reset(),a},_e.a.prototype.beginHierarchyAnimation=function(r,t,e,n,i,o,a,s,d,p,b,P){o===void 0&&(o=1),d===void 0&&(d=!0),P===void 0&&(P=!1);var O=r.getDescendants(t),B=[];B.push(this.beginAnimation(r,e,n,i,o,a,s,d,p,void 0,P));for(var F=0,z=O;F<z.length;F++){var J=z[F];B.push(this.beginAnimation(J,e,n,i,o,a,s,d,p,void 0,P))}return B},_e.a.prototype.beginDirectAnimation=function(r,t,e,n,i,o,a,s,d){return d===void 0&&(d=!1),o===void 0&&(o=1),e>n&&o>0&&(o*=-1),new ke(this,r,e,n,i,o,a,t,s,d)},_e.a.prototype.beginDirectHierarchyAnimation=function(r,t,e,n,i,o,a,s,d,p){p===void 0&&(p=!1);var b=r.getDescendants(t),P=[];P.push(this.beginDirectAnimation(r,e,n,i,o,a,s,d,p));for(var O=0,B=b;O<B.length;O++){var F=B[O];P.push(this.beginDirectAnimation(F,e,n,i,o,a,s,d,p))}return P},_e.a.prototype.getAnimatableByTarget=function(r){for(var t=0;t<this._activeAnimatables.length;t++)if(this._activeAnimatables[t].target===r)return this._activeAnimatables[t];return null},_e.a.prototype.getAllAnimatablesByTarget=function(r){for(var t=[],e=0;e<this._activeAnimatables.length;e++)this._activeAnimatables[e].target===r&&t.push(this._activeAnimatables[e]);return t},_e.a.prototype.stopAnimation=function(r,t,e){for(var n=0,i=this.getAllAnimatablesByTarget(r);n<i.length;n++)i[n].stop(t,e)},_e.a.prototype.stopAllAnimations=function(){if(this._activeAnimatables){for(var r=0;r<this._activeAnimatables.length;r++)this._activeAnimatables[r].stop();this._activeAnimatables=[]}for(var t=0,e=this.animationGroups;t<e.length;t++)e[t].stop()},_e.a.prototype._registerTargetForLateAnimationBinding=function(r,t){var e=r.target;this._registeredForLateAnimationBindings.pushNoDuplicate(e),e._lateAnimationHolders||(e._lateAnimationHolders={}),e._lateAnimationHolders[r.targetPath]||(e._lateAnimationHolders[r.targetPath]={totalWeight:0,totalAdditiveWeight:0,animations:[],additiveAnimations:[],originalValue:t}),r.isAdditive?(e._lateAnimationHolders[r.targetPath].additiveAnimations.push(r),e._lateAnimationHolders[r.targetPath].totalAdditiveWeight+=r.weight):(e._lateAnimationHolders[r.targetPath].animations.push(r),e._lateAnimationHolders[r.targetPath].totalWeight+=r.weight)},_e.a.prototype._processLateAnimationBindingsForMatrices=function(r){if(r.totalWeight===0&&r.totalAdditiveWeight===0)return r.originalValue;var t=1,e=u.c.Vector3[0],n=u.c.Vector3[1],i=u.c.Quaternion[0],o=0,a=r.animations[0],s=r.originalValue,d=1,p=!1;if(r.totalWeight<1)d=1-r.totalWeight,s.decompose(n,i,e);else{if(o=1,t=r.totalWeight,(d=a.weight/t)==1){if(!r.totalAdditiveWeight)return a.currentValue;p=!0}a.currentValue.decompose(n,i,e)}if(!p){n.scaleInPlace(d),e.scaleInPlace(d),i.scaleInPlace(d);for(var b=o;b<r.animations.length;b++)if((z=r.animations[b]).weight!==0){d=z.weight/t;var P=u.c.Vector3[2],O=u.c.Vector3[3],B=u.c.Quaternion[1];z.currentValue.decompose(O,B,P),O.scaleAndAddToRef(d,n),B.scaleAndAddToRef(d,i),P.scaleAndAddToRef(d,e)}}for(var F=0;F<r.additiveAnimations.length;F++){var z;(z=r.additiveAnimations[F]).weight!==0&&(P=u.c.Vector3[2],O=u.c.Vector3[3],B=u.c.Quaternion[1],z.currentValue.decompose(O,B,P),O.multiplyToRef(n,O),u.e.LerpToRef(n,O,z.weight,n),i.multiplyToRef(B,B),u.b.SlerpToRef(i,B,z.weight,i),P.scaleAndAddToRef(z.weight,e))}var J=a?a._animationState.workValue:u.c.Matrix[0].clone();return u.a.ComposeToRef(n,i,e,J),J},_e.a.prototype._processLateAnimationBindingsForQuaternions=function(r,t){if(r.totalWeight===0&&r.totalAdditiveWeight===0)return t;var e=r.animations[0],n=r.originalValue,i=t;if(r.totalWeight===0&&r.totalAdditiveWeight>0)i.copyFrom(n);else if(r.animations.length===1){if(u.b.SlerpToRef(n,e.currentValue,Math.min(1,r.totalWeight),i),r.totalAdditiveWeight===0)return i}else if(r.animations.length>1){var o=1,a=void 0,s=void 0;if(r.totalWeight<1){var d=1-r.totalWeight;s=[],(a=[]).push(n),s.push(d)}else{if(r.animations.length===2&&(u.b.SlerpToRef(r.animations[0].currentValue,r.animations[1].currentValue,r.animations[1].weight/r.totalWeight,t),r.totalAdditiveWeight===0))return t;a=[],s=[],o=r.totalWeight}for(var p=0;p<r.animations.length;p++){var b=r.animations[p];a.push(b.currentValue),s.push(b.weight/o)}for(var P=0,O=0;O<a.length;)O?(P+=s[O],u.b.SlerpToRef(i,a[O],s[O]/P,i),O++):(u.b.SlerpToRef(a[O],a[O+1],s[O+1]/(s[O]+s[O+1]),t),i=t,P=s[O]+s[O+1],O+=2)}for(var B=0;B<r.additiveAnimations.length;B++)(b=r.additiveAnimations[B]).weight!==0&&(i.multiplyToRef(b.currentValue,u.c.Quaternion[0]),u.b.SlerpToRef(i,u.c.Quaternion[0],b.weight,i));return i},_e.a.prototype._processLateAnimationBindings=function(){if(this._registeredForLateAnimationBindings.length){for(var r=0;r<this._registeredForLateAnimationBindings.length;r++){var t=this._registeredForLateAnimationBindings.data[r];for(var e in t._lateAnimationHolders){var n=t._lateAnimationHolders[e],i=n.animations[0],o=n.originalValue,a=k.AllowMatrixDecomposeForInterpolation&&o.m,s=t[e];if(a)s=this._processLateAnimationBindingsForMatrices(n);else if(o.w!==void 0)s=this._processLateAnimationBindingsForQuaternions(n,s||u.b.Identity());else{var d=0,p=1;if(n.totalWeight<1)s=i&&o.scale?o.scale(1-n.totalWeight):i?o*(1-n.totalWeight):o.clone?o.clone():o;else if(i){p=n.totalWeight;var b=i.weight/p;s=b!==1?i.currentValue.scale?i.currentValue.scale(b):i.currentValue*b:i.currentValue,d=1}for(var P=d;P<n.animations.length;P++)(F=(B=n.animations[P]).weight/p)&&(B.currentValue.scaleAndAddToRef?B.currentValue.scaleAndAddToRef(F,s):s+=B.currentValue*F);for(var O=0;O<n.additiveAnimations.length;O++){var B,F;(F=(B=n.additiveAnimations[O]).weight)&&(B.currentValue.scaleAndAddToRef?B.currentValue.scaleAndAddToRef(F,s):s+=B.currentValue*F)}}t[e]=s}t._lateAnimationHolders={}}this._registeredForLateAnimationBindings.reset()}},Be.prototype.copyAnimationRange=function(r,t,e,n,i){n===void 0&&(n=!1),i===void 0&&(i=null),this.animations.length===0&&(this.animations.push(new k(this.name,"_matrix",r.animations[0].framePerSecond,k.ANIMATIONTYPE_MATRIX,0)),this.animations[0].setKeys([]));var o=r.animations[0].getRange(t);if(!o)return!1;for(var a,s,d,p=o.from,b=o.to,P=r.animations[0].getKeys(),O=r.length,B=r.getParent(),F=this.getParent(),z=n&&B&&O&&this.length&&O!==this.length,J=z&&F&&B?F.length/B.length:1,ie=n&&!F&&i&&(i.x!==1||i.y!==1||i.z!==1),se=this.animations[0].getKeys(),ce=0,ue=P.length;ce<ue;ce++)(a=P[ce]).frame>=p&&a.frame<=b&&(n?(d=a.value.clone(),z?(s=d.getTranslation(),d.setTranslation(s.scaleInPlace(J))):ie&&i?(s=d.getTranslation(),d.setTranslation(s.multiplyInPlace(i))):d=a.value):d=a.value,se.push({frame:a.frame+e,value:d}));return this.animations[0].createRange(t,p+e,b+e),!0};var We=function(){function r(){}return r.prototype.getClassName=function(){return"TargetedAnimation"},r.prototype.serialize=function(){var t={};return t.animation=this.animation.serialize(),t.targetId=this.target.id,t},r}(),je=function(){function r(t,e){e===void 0&&(e=null),this.name=t,this._targetedAnimations=new Array,this._animatables=new Array,this._from=Number.MAX_VALUE,this._to=-Number.MAX_VALUE,this._speedRatio=1,this._loopAnimation=!1,this._isAdditive=!1,this.onAnimationEndObservable=new C.c,this.onAnimationLoopObservable=new C.c,this.onAnimationGroupLoopObservable=new C.c,this.onAnimationGroupEndObservable=new C.c,this.onAnimationGroupPauseObservable=new C.c,this.onAnimationGroupPlayObservable=new C.c,this._scene=e||te.a.LastCreatedScene,this.uniqueId=this._scene.getUniqueId(),this._scene.addAnimationGroup(this)}return Object.defineProperty(r.prototype,"from",{get:function(){return this._from},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"to",{get:function(){return this._to},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isStarted",{get:function(){return this._isStarted},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isPlaying",{get:function(){return this._isStarted&&!this._isPaused},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"speedRatio",{get:function(){return this._speedRatio},set:function(t){if(this._speedRatio!==t){this._speedRatio=t;for(var e=0;e<this._animatables.length;e++)this._animatables[e].speedRatio=this._speedRatio}},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"loopAnimation",{get:function(){return this._loopAnimation},set:function(t){if(this._loopAnimation!==t){this._loopAnimation=t;for(var e=0;e<this._animatables.length;e++)this._animatables[e].loopAnimation=this._loopAnimation}},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isAdditive",{get:function(){return this._isAdditive},set:function(t){if(this._isAdditive!==t){this._isAdditive=t;for(var e=0;e<this._animatables.length;e++)this._animatables[e].isAdditive=this._isAdditive}},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"targetedAnimations",{get:function(){return this._targetedAnimations},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"animatables",{get:function(){return this._animatables},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"children",{get:function(){return this._targetedAnimations},enumerable:!1,configurable:!0}),r.prototype.addTargetedAnimation=function(t,e){var n=new We;n.animation=t,n.target=e;var i=t.getKeys();return this._from>i[0].frame&&(this._from=i[0].frame),this._to<i[i.length-1].frame&&(this._to=i[i.length-1].frame),this._targetedAnimations.push(n),n},r.prototype.normalize=function(t,e){t===void 0&&(t=null),e===void 0&&(e=null),t==null&&(t=this._from),e==null&&(e=this._to);for(var n=0;n<this._targetedAnimations.length;n++){var i=this._targetedAnimations[n].animation.getKeys(),o=i[0],a=i[i.length-1];if(o.frame>t){var s={frame:t,value:o.value,inTangent:o.inTangent,outTangent:o.outTangent,interpolation:o.interpolation};i.splice(0,0,s)}a.frame<e&&(s={frame:e,value:a.value,inTangent:a.inTangent,outTangent:a.outTangent,interpolation:a.interpolation},i.push(s))}return this._from=t,this._to=e,this},r.prototype._processLoop=function(t,e,n){var i=this;t.onAnimationLoop=function(){i.onAnimationLoopObservable.notifyObservers(e),i._animationLoopFlags[n]||(i._animationLoopFlags[n]=!0,i._animationLoopCount++,i._animationLoopCount===i._targetedAnimations.length&&(i.onAnimationGroupLoopObservable.notifyObservers(i),i._animationLoopCount=0,i._animationLoopFlags=[]))}},r.prototype.start=function(t,e,n,i,o){var a=this;if(t===void 0&&(t=!1),e===void 0&&(e=1),this._isStarted||this._targetedAnimations.length===0)return this;this._loopAnimation=t,this._animationLoopCount=0,this._animationLoopFlags=[];for(var s=function(){var P=d._targetedAnimations[p],O=d._scene.beginDirectAnimation(P.target,[P.animation],n!==void 0?n:d._from,i!==void 0?i:d._to,t,e,void 0,void 0,o!==void 0?o:d._isAdditive);O.onAnimationEnd=function(){a.onAnimationEndObservable.notifyObservers(P),a._checkAnimationGroupEnded(O)},d._processLoop(O,P,p),d._animatables.push(O)},d=this,p=0;p<this._targetedAnimations.length;p++)s();if(this._speedRatio=e,n!==void 0&&i!==void 0)if(n<i&&this._speedRatio<0){var b=i;i=n,n=b}else n>i&&this._speedRatio>0&&(this._speedRatio=-e);return this._isStarted=!0,this._isPaused=!1,this.onAnimationGroupPlayObservable.notifyObservers(this),this},r.prototype.pause=function(){if(!this._isStarted)return this;this._isPaused=!0;for(var t=0;t<this._animatables.length;t++)this._animatables[t].pause();return this.onAnimationGroupPauseObservable.notifyObservers(this),this},r.prototype.play=function(t){return this.isStarted&&this._animatables.length===this._targetedAnimations.length?(t!==void 0&&(this.loopAnimation=t),this.restart()):(this.stop(),this.start(t,this._speedRatio)),this._isPaused=!1,this},r.prototype.reset=function(){if(!this._isStarted)return this.play(),this.goToFrame(0),this.stop(),this;for(var t=0;t<this._animatables.length;t++)this._animatables[t].reset();return this},r.prototype.restart=function(){if(!this._isStarted)return this;for(var t=0;t<this._animatables.length;t++)this._animatables[t].restart();return this.onAnimationGroupPlayObservable.notifyObservers(this),this},r.prototype.stop=function(){if(!this._isStarted)return this;for(var t=this._animatables.slice(),e=0;e<t.length;e++)t[e].stop();return this._isStarted=!1,this},r.prototype.setWeightForAllAnimatables=function(t){for(var e=0;e<this._animatables.length;e++)this._animatables[e].weight=t;return this},r.prototype.syncAllAnimationsWith=function(t){for(var e=0;e<this._animatables.length;e++)this._animatables[e].syncWith(t);return this},r.prototype.goToFrame=function(t){if(!this._isStarted)return this;for(var e=0;e<this._animatables.length;e++)this._animatables[e].goToFrame(t);return this},r.prototype.dispose=function(){this._targetedAnimations=[],this._animatables=[];var t=this._scene.animationGroups.indexOf(this);t>-1&&this._scene.animationGroups.splice(t,1),this.onAnimationEndObservable.clear(),this.onAnimationGroupEndObservable.clear(),this.onAnimationGroupPauseObservable.clear(),this.onAnimationGroupPlayObservable.clear(),this.onAnimationLoopObservable.clear(),this.onAnimationGroupLoopObservable.clear()},r.prototype._checkAnimationGroupEnded=function(t){var e=this._animatables.indexOf(t);e>-1&&this._animatables.splice(e,1),this._animatables.length===0&&(this._isStarted=!1,this.onAnimationGroupEndObservable.notifyObservers(this))},r.prototype.clone=function(t,e){for(var n=new r(t||this.name,this._scene),i=0,o=this._targetedAnimations;i<o.length;i++){var a=o[i];n.addTargetedAnimation(a.animation.clone(),e?e(a.target):a.target)}return n},r.prototype.serialize=function(){var t={};t.name=this.name,t.from=this.from,t.to=this.to,t.targetedAnimations=[];for(var e=0;e<this.targetedAnimations.length;e++){var n=this.targetedAnimations[e];t.targetedAnimations[e]=n.serialize()}return t},r.Parse=function(t,e){for(var n=new r(t.name,e),i=0;i<t.targetedAnimations.length;i++){var o=t.targetedAnimations[i],a=k.Parse(o.animation),s=o.targetId;if(o.animation.property==="influence"){var d=e.getMorphTargetById(s);d&&n.addTargetedAnimation(a,d)}else{var p=e.getNodeByID(s);p!=null&&n.addTargetedAnimation(a,p)}}return t.from!==null&&t.to!==null&&n.normalize(t.from,t.to),n},r.MakeAnimationAdditive=function(t,e,n,i,o){e===void 0&&(e=0),i===void 0&&(i=!1);var a=t;i&&(a=t.clone(o||a.name));for(var s=a.targetedAnimations,d=0;d<s.length;d++){var p=s[d];k.MakeAnimationAdditive(p.animation,e,n)}return a.isAdditive=!0,a},r.prototype.getClassName=function(){return"AnimationGroup"},r.prototype.toString=function(t){var e="Name: "+this.name;return e+=", type: "+this.getClassName(),t&&(e+=", from: "+this._from,e+=", to: "+this._to,e+=", isStarted: "+this._isStarted,e+=", speedRatio: "+this._speedRatio,e+=", targetedAnimations length: "+this._targetedAnimations.length,e+=", animatables length: "+this._animatables),e},r}(),He=function(){this.enableBlending=!1,this.blendingSpeed=.01,this.loopMode=k.ANIMATIONLOOPMODE_CYCLE},qe=f(72),Ge=function(){function r(){this._easingMode=r.EASINGMODE_EASEIN}return r.prototype.setEasingMode=function(t){var e=Math.min(Math.max(t,0),2);this._easingMode=e},r.prototype.getEasingMode=function(){return this._easingMode},r.prototype.easeInCore=function(t){throw new Error("You must implement this method")},r.prototype.ease=function(t){switch(this._easingMode){case r.EASINGMODE_EASEIN:return this.easeInCore(t);case r.EASINGMODE_EASEOUT:return 1-this.easeInCore(1-t)}return t>=.5?.5*(1-this.easeInCore(2*(1-t)))+.5:.5*this.easeInCore(2*t)},r.EASINGMODE_EASEIN=0,r.EASINGMODE_EASEOUT=1,r.EASINGMODE_EASEINOUT=2,r}(),nt=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return e=Math.max(0,Math.min(1,e)),1-Math.sqrt(1-e*e)},t}(Ge),$e=function(r){function t(e){e===void 0&&(e=1);var n=r.call(this)||this;return n.amplitude=e,n}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){var n=Math.max(0,this.amplitude);return Math.pow(e,3)-e*n*Math.sin(3.141592653589793*e)},t}(Ge),lt=function(r){function t(e,n){e===void 0&&(e=3),n===void 0&&(n=2);var i=r.call(this)||this;return i.bounces=e,i.bounciness=n,i}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){var n=Math.max(0,this.bounces),i=this.bounciness;i<=1&&(i=1.001);var o=Math.pow(i,n),a=1-i,s=(1-o)/a+.5*o,d=e*s,p=Math.log(-d*(1-i)+1)/Math.log(i),b=Math.floor(p),P=b+1,O=(1-Math.pow(i,b))/(a*s),B=.5*(O+(1-Math.pow(i,P))/(a*s)),F=e-B,z=B-O;return-Math.pow(1/i,n-b)/(z*z)*(F-z)*(F+z)},t}(Ge),st=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return e*e*e},t}(Ge),mt=function(r){function t(e,n){e===void 0&&(e=3),n===void 0&&(n=3);var i=r.call(this)||this;return i.oscillations=e,i.springiness=n,i}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){var n=Math.max(0,this.oscillations),i=Math.max(0,this.springiness);return(i==0?e:(Math.exp(i*e)-1)/(Math.exp(i)-1))*Math.sin((6.283185307179586*n+1.5707963267948966)*e)},t}(Ge),St=function(r){function t(e){e===void 0&&(e=2);var n=r.call(this)||this;return n.exponent=e,n}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return this.exponent<=0?e:(Math.exp(this.exponent*e)-1)/(Math.exp(this.exponent)-1)},t}(Ge),wt=function(r){function t(e){e===void 0&&(e=2);var n=r.call(this)||this;return n.power=e,n}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){var n=Math.max(0,this.power);return Math.pow(e,n)},t}(Ge),It=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return e*e},t}(Ge),Pt=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return e*e*e*e},t}(Ge),Ot=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return e*e*e*e*e},t}(Ge),on=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return 1-Math.sin(1.5707963267948966*(1-e))},t}(Ge),Zt=function(r){function t(e,n,i,o){e===void 0&&(e=0),n===void 0&&(n=0),i===void 0&&(i=1),o===void 0&&(o=1);var a=r.call(this)||this;return a.x1=e,a.y1=n,a.x2=i,a.y2=o,a}return Object(c.d)(t,r),t.prototype.easeInCore=function(e){return qe.c.Interpolate(e,this.x1,this.y1,this.x2,this.y2)},t}(Ge),tn=function(){function r(t,e,n){this.frame=t,this.action=e,this.onlyOnce=n,this.isDone=!1}return r.prototype._clone=function(){return new r(this.frame,this.action,this.onlyOnce)},r}(),De=f(7),Pn=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t}(U.a),nn=function(){this.rootNodes=[],this.skeletons=[],this.animationGroups=[]},xn=function(r){function t(e){var n=r.call(this)||this;return n._wasAddedToScene=!1,n.scene=e,n.sounds=[],n.effectLayers=[],n.layers=[],n.lensFlareSystems=[],n.proceduralTextures=[],n.reflectionProbes=[],e.onDisposeObservable.add(function(){n._wasAddedToScene||n.dispose()}),n}return Object(c.d)(t,r),t.prototype.instantiateModelsToScene=function(e,n){var i=this;n===void 0&&(n=!1);var o={},a={},s=new nn,d=[],p=[],b={doNotInstantiate:!0},P=function(O,B){if(o[O.uniqueId]=B.uniqueId,a[B.uniqueId]=B,e&&(B.name=e(O.name)),B instanceof De.a){var F=B;if(F.morphTargetManager){var z=O.morphTargetManager;F.morphTargetManager=z.clone();for(var J=0;J<z.numTargets;J++){var ie=z.getTarget(J),se=F.morphTargetManager.getTarget(J);o[ie.uniqueId]=se.uniqueId,a[se.uniqueId]=se}}}};return this.transformNodes.forEach(function(O){if(!O.parent){var B=O.instantiateHierarchy(null,b,function(F,z){P(F,z)});B&&s.rootNodes.push(B)}}),this.meshes.forEach(function(O){if(!O.parent){var B=O.instantiateHierarchy(null,b,function(F,z){if(P(F,z),z.material){var J=z;if(J.material)if(n){var ie=F.material;if(p.indexOf(ie)===-1){var se=ie.clone(e?e(ie.name):"Clone of "+ie.name);if(p.push(ie),o[ie.uniqueId]=se.uniqueId,a[se.uniqueId]=se,ie.getClassName()==="MultiMaterial"){for(var ce=ie,ue=0,fe=ce.subMaterials;ue<fe.length;ue++){var ve=fe[ue];ve&&(se=ve.clone(e?e(ve.name):"Clone of 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a[o[F.uniqueId]]||F});s.animationGroups.push(B)}),s},t.prototype.addAllToScene=function(){var e=this;this._wasAddedToScene=!0,this.cameras.forEach(function(o){e.scene.addCamera(o)}),this.lights.forEach(function(o){e.scene.addLight(o)}),this.meshes.forEach(function(o){e.scene.addMesh(o)}),this.skeletons.forEach(function(o){e.scene.addSkeleton(o)}),this.animations.forEach(function(o){e.scene.addAnimation(o)}),this.animationGroups.forEach(function(o){e.scene.addAnimationGroup(o)}),this.multiMaterials.forEach(function(o){e.scene.addMultiMaterial(o)}),this.materials.forEach(function(o){e.scene.addMaterial(o)}),this.morphTargetManagers.forEach(function(o){e.scene.addMorphTargetManager(o)}),this.geometries.forEach(function(o){e.scene.addGeometry(o)}),this.transformNodes.forEach(function(o){e.scene.addTransformNode(o)}),this.actionManagers.forEach(function(o){e.scene.addActionManager(o)}),this.textures.forEach(function(o){e.scene.addTexture(o)}),this.reflectionProbes.forEach(function(o){e.scene.addReflectionProbe(o)}),this.environmentTexture&&(this.scene.environmentTexture=this.environmentTexture);for(var n=0,i=this.scene._serializableComponents;n<i.length;n++)i[n].addFromContainer(this)},t.prototype.removeAllFromScene=function(){var e=this;this._wasAddedToScene=!1,this.cameras.forEach(function(o){e.scene.removeCamera(o)}),this.lights.forEach(function(o){e.scene.removeLight(o)}),this.meshes.forEach(function(o){e.scene.removeMesh(o)}),this.skeletons.forEach(function(o){e.scene.removeSkeleton(o)}),this.animations.forEach(function(o){e.scene.removeAnimation(o)}),this.animationGroups.forEach(function(o){e.scene.removeAnimationGroup(o)}),this.multiMaterials.forEach(function(o){e.scene.removeMultiMaterial(o)}),this.materials.forEach(function(o){e.scene.removeMaterial(o)}),this.morphTargetManagers.forEach(function(o){e.scene.removeMorphTargetManager(o)}),this.geometries.forEach(function(o){e.scene.removeGeometry(o)}),this.transformNodes.forEach(function(o){e.scene.removeTransformNode(o)}),this.actionManagers.forEach(function(o){e.scene.removeActionManager(o)}),this.textures.forEach(function(o){e.scene.removeTexture(o)}),this.reflectionProbes.forEach(function(o){e.scene.removeReflectionProbe(o)}),this.environmentTexture===this.scene.environmentTexture&&(this.scene.environmentTexture=null);for(var n=0,i=this.scene._serializableComponents;n<i.length;n++)i[n].removeFromContainer(this)},t.prototype.dispose=function(){this.cameras.forEach(function(i){i.dispose()}),this.cameras=[],this.lights.forEach(function(i){i.dispose()}),this.lights=[],this.meshes.forEach(function(i){i.dispose()}),this.meshes=[],this.skeletons.forEach(function(i){i.dispose()}),this.skeletons=[],this.animationGroups.forEach(function(i){i.dispose()}),this.animationGroups=[],this.multiMaterials.forEach(function(i){i.dispose()}),this.multiMaterials=[],this.materials.forEach(function(i){i.dispose()}),this.materials=[],this.geometries.forEach(function(i){i.dispose()}),this.geometries=[],this.transformNodes.forEach(function(i){i.dispose()}),this.transformNodes=[],this.actionManagers.forEach(function(i){i.dispose()}),this.actionManagers=[],this.textures.forEach(function(i){i.dispose()}),this.textures=[],this.reflectionProbes.forEach(function(i){i.dispose()}),this.reflectionProbes=[],this.environmentTexture&&(this.environmentTexture.dispose(),this.environmentTexture=null);for(var e=0,n=this.scene._serializableComponents;e<n.length;e++)n[e].removeFromContainer(this,!0)},t.prototype._moveAssets=function(e,n,i){if(e)for(var o=0,a=e;o<a.length;o++){var s=a[o],d=!0;if(i){for(var p=0,b=i;p<b.length;p++)if(s===b[p]){d=!1;break}}d&&n.push(s)}},t.prototype.moveAllFromScene=function(e){for(var n in this._wasAddedToScene=!1,e===void 0&&(e=new Pn),this)this.hasOwnProperty(n)&&(this[n]=this[n]||(n==="environmentTexture"?null:[]),this._moveAssets(this.scene[n],this[n],e[n]));this.environmentTexture=this.scene.environmentTexture,this.removeAllFromScene()},t.prototype.createRootMesh=function(){var e=new De.a("assetContainerRootMesh",this.scene);return this.meshes.forEach(function(n){n.parent||e.addChild(n)}),this.meshes.unshift(e),e},t.prototype.mergeAnimationsTo=function(e,n,i){if(e===void 0&&(e=te.a.LastCreatedScene),i===void 0&&(i=null),!e)return l.a.Error("No scene available to merge animations to"),[];var o=i||function(s){var d=null,p=s.animations.length?s.animations[0].targetProperty:"",b=s.name.split(".").join("").split("_primitive")[0];switch(p){case"position":case"rotationQuaternion":d=e.getTransformNodeByName(s.name)||e.getTransformNodeByName(b);break;case"influence":d=e.getMorphTargetByName(s.name)||e.getMorphTargetByName(b);break;default:d=e.getNodeByName(s.name)||e.getNodeByName(b)}return d};this.getNodes().forEach(function(s){var d=o(s);if(d!==null){for(var p=function(O){for(var B=0,F=d.animations.filter(function(ie){return ie.targetProperty===O.targetProperty});B<F.length;B++){var z=F[B],J=d.animations.indexOf(z,0);J>-1&&d.animations.splice(J,1)}},b=0,P=s.animations;b<P.length;b++)p(P[b]);d.animations=d.animations.concat(s.animations)}});var a=new Array;return this.animationGroups.slice().forEach(function(s){a.push(s.clone(s.name,o)),s.animatables.forEach(function(d){d.stop()})}),n.forEach(function(s){var d=o(s.target);d&&(e.beginAnimation(d,s.fromFrame,s.toFrame,s.loopAnimation,s.speedRatio,s.onAnimationEnd?s.onAnimationEnd:void 0,void 0,!0,void 0,s.onAnimationLoop?s.onAnimationLoop:void 0),e.stopAnimation(s.target))}),a},t}(U.a),Ue=f(13),Cn=function(){function r(t){this.SMOOTHING=.75,this.FFT_SIZE=512,this.BARGRAPHAMPLITUDE=256,this.DEBUGCANVASPOS={x:20,y:20},this.DEBUGCANVASSIZE={width:320,height:200},this._scene=t,this._audioEngine=Ue.a.audioEngine,this._audioEngine.canUseWebAudio&&this._audioEngine.audioContext&&(this._webAudioAnalyser=this._audioEngine.audioContext.createAnalyser(),this._webAudioAnalyser.minDecibels=-140,this._webAudioAnalyser.maxDecibels=0,this._byteFreqs=new Uint8Array(this._webAudioAnalyser.frequencyBinCount),this._byteTime=new Uint8Array(this._webAudioAnalyser.frequencyBinCount),this._floatFreqs=new Float32Array(this._webAudioAnalyser.frequencyBinCount))}return r.prototype.getFrequencyBinCount=function(){return this._audioEngine.canUseWebAudio?this._webAudioAnalyser.frequencyBinCount:0},r.prototype.getByteFrequencyData=function(){return this._audioEngine.canUseWebAudio&&(this._webAudioAnalyser.smoothingTimeConstant=this.SMOOTHING,this._webAudioAnalyser.fftSize=this.FFT_SIZE,this._webAudioAnalyser.getByteFrequencyData(this._byteFreqs)),this._byteFreqs},r.prototype.getByteTimeDomainData=function(){return this._audioEngine.canUseWebAudio&&(this._webAudioAnalyser.smoothingTimeConstant=this.SMOOTHING,this._webAudioAnalyser.fftSize=this.FFT_SIZE,this._webAudioAnalyser.getByteTimeDomainData(this._byteTime)),this._byteTime},r.prototype.getFloatFrequencyData=function(){return this._audioEngine.canUseWebAudio&&(this._webAudioAnalyser.smoothingTimeConstant=this.SMOOTHING,this._webAudioAnalyser.fftSize=this.FFT_SIZE,this._webAudioAnalyser.getFloatFrequencyData(this._floatFreqs)),this._floatFreqs},r.prototype.drawDebugCanvas=function(){var t=this;if(this._audioEngine.canUseWebAudio&&(this._debugCanvas||(this._debugCanvas=document.createElement("canvas"),this._debugCanvas.width=this.DEBUGCANVASSIZE.width,this._debugCanvas.height=this.DEBUGCANVASSIZE.height,this._debugCanvas.style.position="absolute",this._debugCanvas.style.top=this.DEBUGCANVASPOS.y+"px",this._debugCanvas.style.left=this.DEBUGCANVASPOS.x+"px",this._debugCanvasContext=this._debugCanvas.getContext("2d"),document.body.appendChild(this._debugCanvas),this._registerFunc=function(){t.drawDebugCanvas()},this._scene.registerBeforeRender(this._registerFunc)),this._registerFunc&&this._debugCanvasContext)){var e=this.getByteFrequencyData();this._debugCanvasContext.fillStyle="rgb(0, 0, 0)",this._debugCanvasContext.fillRect(0,0,this.DEBUGCANVASSIZE.width,this.DEBUGCANVASSIZE.height);for(var n=0;n<this.getFrequencyBinCount();n++){var i=e[n]/this.BARGRAPHAMPLITUDE,o=this.DEBUGCANVASSIZE.height*i,a=this.DEBUGCANVASSIZE.height-o-1,s=this.DEBUGCANVASSIZE.width/this.getFrequencyBinCount(),d=n/this.getFrequencyBinCount()*360;this._debugCanvasContext.fillStyle="hsl("+d+", 100%, 50%)",this._debugCanvasContext.fillRect(n*s,a,s,o)}}},r.prototype.stopDebugCanvas=function(){this._debugCanvas&&(this._registerFunc&&(this._scene.unregisterBeforeRender(this._registerFunc),this._registerFunc=null),document.body.removeChild(this._debugCanvas),this._debugCanvas=null,this._debugCanvasContext=null)},r.prototype.connectAudioNodes=function(t,e){this._audioEngine.canUseWebAudio&&(t.connect(this._webAudioAnalyser),this._webAudioAnalyser.connect(e))},r.prototype.dispose=function(){this._audioEngine.canUseWebAudio&&this._webAudioAnalyser.disconnect()},r}();Ue.a.AudioEngineFactory=function(r){return new dr(r)};var dr=function(){function r(t){var e=this;t===void 0&&(t=null),this._audioContext=null,this._audioContextInitialized=!1,this._muteButton=null,this.canUseWebAudio=!1,this.WarnedWebAudioUnsupported=!1,this.isMP3supported=!1,this.isOGGsupported=!1,this.unlocked=!0,this.useCustomUnlockedButton=!1,this.onAudioUnlockedObservable=new C.c,this.onAudioLockedObservable=new C.c,this._tryToRun=!1,this._onResize=function(){e._moveButtonToTopLeft()},window.AudioContext===void 0&&window.webkitAudioContext===void 0||(window.AudioContext=window.AudioContext||window.webkitAudioContext,this.canUseWebAudio=!0);var n=document.createElement("audio");this._hostElement=t;try{n&&n.canPlayType&&(n.canPlayType('audio/mpeg; codecs="mp3"').replace(/^no$/,"")||n.canPlayType("audio/mp3").replace(/^no$/,""))&&(this.isMP3supported=!0)}catch{}try{n&&n.canPlayType&&n.canPlayType('audio/ogg; codecs="vorbis"').replace(/^no$/,"")&&(this.isOGGsupported=!0)}catch{}}return Object.defineProperty(r.prototype,"audioContext",{get:function(){return this._audioContextInitialized?this.unlocked||this._muteButton||this._displayMuteButton():this._initializeAudioContext(),this._audioContext},enumerable:!1,configurable:!0}),r.prototype.lock=function(){this._triggerSuspendedState()},r.prototype.unlock=function(){this._triggerRunningState()},r.prototype._resumeAudioContext=function(){var t;return this._audioContext.resume!==void 0&&(t=this._audioContext.resume()),t||Promise.resolve()},r.prototype._initializeAudioContext=function(){try{this.canUseWebAudio&&(this._audioContext=new AudioContext,this.masterGain=this._audioContext.createGain(),this.masterGain.gain.value=1,this.masterGain.connect(this._audioContext.destination),this._audioContextInitialized=!0,this._audioContext.state==="running"&&this._triggerRunningState())}catch(t){this.canUseWebAudio=!1,l.a.Error("Web Audio: "+t.message)}},r.prototype._triggerRunningState=function(){var t=this;this._tryToRun||(this._tryToRun=!0,this._resumeAudioContext().then(function(){t._tryToRun=!1,t._muteButton&&t._hideMuteButton(),t.unlocked=!0,t.onAudioUnlockedObservable.notifyObservers(t)}).catch(function(){t._tryToRun=!1,t.unlocked=!1}))},r.prototype._triggerSuspendedState=function(){this.unlocked=!1,this.onAudioLockedObservable.notifyObservers(this),this._displayMuteButton()},r.prototype._displayMuteButton=function(){var t=this;if(!this.useCustomUnlockedButton&&!this._muteButton){this._muteButton=document.createElement("BUTTON"),this._muteButton.className="babylonUnmuteIcon",this._muteButton.id="babylonUnmuteIconBtn",this._muteButton.title="Unmute";var e=".babylonUnmuteIcon { position: absolute; left: 20px; top: 20px; height: 40px; width: 60px; background-color: rgba(51,51,51,0.7); background-image: url("+(window.SVGSVGElement?"data:image/svg+xml;charset=UTF-8,%3Csvg%20version%3D%221.1%22%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20width%3D%2239%22%20height%3D%2232%22%20viewBox%3D%220%200%2039%2032%22%3E%3Cpath%20fill%3D%22white%22%20d%3D%22M9.625%2018.938l-0.031%200.016h-4.953q-0.016%200-0.031-0.016v-12.453q0-0.016%200.031-0.016h4.953q0.031%200%200.031%200.016v12.453zM12.125%207.688l8.719-8.703v27.453l-8.719-8.719-0.016-0.047v-9.938zM23.359%207.875l1.406-1.406%204.219%204.203%204.203-4.203%201.422%201.406-4.219%204.219%204.219%204.203-1.484%201.359-4.141-4.156-4.219%204.219-1.406-1.422%204.219-4.203z%22%3E%3C%2Fpath%3E%3C%2Fsvg%3E":"https://cdn.babylonjs.com/Assets/audio.png")+");  background-size: 80%; background-repeat:no-repeat; background-position: center; background-position-y: 4px; border: none; outline: none; transition: transform 0.125s ease-out; cursor: pointer; z-index: 9999; } .babylonUnmuteIcon:hover { transform: scale(1.05) } .babylonUnmuteIcon:active { background-color: rgba(51,51,51,1) }",n=document.createElement("style");n.appendChild(document.createTextNode(e)),document.getElementsByTagName("head")[0].appendChild(n),document.body.appendChild(this._muteButton),this._moveButtonToTopLeft(),this._muteButton.addEventListener("touchend",function(){t._triggerRunningState()},!0),this._muteButton.addEventListener("click",function(){t._triggerRunningState()},!0),window.addEventListener("resize",this._onResize)}},r.prototype._moveButtonToTopLeft=function(){this._hostElement&&this._muteButton&&(this._muteButton.style.top=this._hostElement.offsetTop+20+"px",this._muteButton.style.left=this._hostElement.offsetLeft+20+"px")},r.prototype._hideMuteButton=function(){this._muteButton&&(document.body.removeChild(this._muteButton),this._muteButton=null)},r.prototype.dispose=function(){this.canUseWebAudio&&this._audioContextInitialized&&(this._connectedAnalyser&&this._audioContext&&(this._connectedAnalyser.stopDebugCanvas(),this._connectedAnalyser.dispose(),this.masterGain.disconnect(),this.masterGain.connect(this._audioContext.destination),this._connectedAnalyser=null),this.masterGain.gain.value=1),this.WarnedWebAudioUnsupported=!1,this._hideMuteButton(),window.removeEventListener("resize",this._onResize),this.onAudioUnlockedObservable.clear(),this.onAudioLockedObservable.clear()},r.prototype.getGlobalVolume=function(){return this.canUseWebAudio&&this._audioContextInitialized?this.masterGain.gain.value:-1},r.prototype.setGlobalVolume=function(t){this.canUseWebAudio&&this._audioContextInitialized&&(this.masterGain.gain.value=t)},r.prototype.connectToAnalyser=function(t){this._connectedAnalyser&&this._connectedAnalyser.stopDebugCanvas(),this.canUseWebAudio&&this._audioContextInitialized&&this._audioContext&&(this._connectedAnalyser=t,this.masterGain.disconnect(),this._connectedAnalyser.connectAudioNodes(this.masterGain,this._audioContext.destination))},r}(),Xe=f(12),An=f(21),ei=function(){function r(t,e,n,i,o){var a,s,d,p,b=this;if(i===void 0&&(i=null),this.autoplay=!1,this.loop=!1,this.useCustomAttenuation=!1,this.isPlaying=!1,this.isPaused=!1,this.spatialSound=!1,this.refDistance=1,this.rolloffFactor=1,this.maxDistance=100,this.distanceModel="linear",this.metadata=null,this.onEndedObservable=new C.c,this._panningModel="equalpower",this._playbackRate=1,this._streaming=!1,this._startTime=0,this._startOffset=0,this._position=u.e.Zero(),this._positionInEmitterSpace=!1,this._localDirection=new u.e(1,0,0),this._volume=1,this._isReadyToPlay=!1,this._isDirectional=!1,this._coneInnerAngle=360,this._coneOuterAngle=360,this._coneOuterGain=0,this._isOutputConnected=!1,this._urlType="Unknown",this.name=t,this._scene=n,r._SceneComponentInitialization(n),this._readyToPlayCallback=i,this._customAttenuationFunction=function(J,ie,se,ce,ue){return ie<se?J*(1-ie/se):0},o&&(this.autoplay=o.autoplay||!1,this.loop=o.loop||!1,o.volume!==void 0&&(this._volume=o.volume),this.spatialSound=(a=o.spatialSound)!==null&&a!==void 0&&a,this.maxDistance=(s=o.maxDistance)!==null&&s!==void 0?s:100,this.useCustomAttenuation=(d=o.useCustomAttenuation)!==null&&d!==void 0&&d,this.rolloffFactor=o.rolloffFactor||1,this.refDistance=o.refDistance||1,this.distanceModel=o.distanceModel||"linear",this._playbackRate=o.playbackRate||1,this._streaming=(p=o.streaming)!==null&&p!==void 0&&p,this._length=o.length,this._offset=o.offset),Ue.a.audioEngine.canUseWebAudio&&Ue.a.audioEngine.audioContext){this._soundGain=Ue.a.audioEngine.audioContext.createGain(),this._soundGain.gain.value=this._volume,this._inputAudioNode=this._soundGain,this._outputAudioNode=this._soundGain,this.spatialSound&&this._createSpatialParameters(),this._scene.mainSoundTrack.addSound(this);var P=!0;if(e)try{typeof e=="string"?this._urlType="String":e instanceof ArrayBuffer?this._urlType="ArrayBuffer":e instanceof MediaStream?this._urlType="MediaStream":Array.isArray(e)&&(this._urlType="Array");var O=[],B=!1;switch(this._urlType){case"MediaStream":this._streaming=!0,this._isReadyToPlay=!0,this._streamingSource=Ue.a.audioEngine.audioContext.createMediaStreamSource(e),this.autoplay&&this.play(0,this._offset,this._length),this._readyToPlayCallback&&this._readyToPlayCallback();break;case"ArrayBuffer":e.byteLength>0&&(B=!0,this._soundLoaded(e));break;case"String":O.push(e);case"Array":O.length===0&&(O=e);for(var F=0;F<O.length;F++){var z=O[F];if(B=o&&o.skipCodecCheck||z.indexOf(".mp3",z.length-4)!==-1&&Ue.a.audioEngine.isMP3supported||z.indexOf(".ogg",z.length-4)!==-1&&Ue.a.audioEngine.isOGGsupported||z.indexOf(".wav",z.length-4)!==-1||z.indexOf(".m4a",z.length-4)!==-1||z.indexOf("blob:")!==-1){this._streaming?(this._htmlAudioElement=new Audio(z),this._htmlAudioElement.controls=!1,this._htmlAudioElement.loop=this.loop,Xe.b.SetCorsBehavior(z,this._htmlAudioElement),this._htmlAudioElement.preload="auto",this._htmlAudioElement.addEventListener("canplaythrough",function(){b._isReadyToPlay=!0,b.autoplay&&b.play(0,b._offset,b._length),b._readyToPlayCallback&&b._readyToPlayCallback()}),document.body.appendChild(this._htmlAudioElement),this._htmlAudioElement.load()):this._scene._loadFile(z,function(J){b._soundLoaded(J)},void 0,!0,!0,function(J){J&&l.a.Error("XHR "+J.status+" error on: "+z+"."),l.a.Error("Sound creation aborted."),b._scene.mainSoundTrack.removeSound(b)});break}}break;default:P=!1}P?B||(this._isReadyToPlay=!0,this._readyToPlayCallback&&window.setTimeout(function(){b._readyToPlayCallback&&b._readyToPlayCallback()},1e3)):l.a.Error("Parameter must be a URL to the sound, an Array of URLs (.mp3 & .ogg) or an ArrayBuffer of the sound.")}catch{l.a.Error("Unexpected error. Sound creation aborted."),this._scene.mainSoundTrack.removeSound(this)}}else this._scene.mainSoundTrack.addSound(this),Ue.a.audioEngine.WarnedWebAudioUnsupported||(l.a.Error("Web Audio is not supported by your browser."),Ue.a.audioEngine.WarnedWebAudioUnsupported=!0),this._readyToPlayCallback&&window.setTimeout(function(){b._readyToPlayCallback&&b._readyToPlayCallback()},1e3)}return Object.defineProperty(r.prototype,"currentTime",{get:function(){if(this._htmlAudioElement)return this._htmlAudioElement.currentTime;var t=this._startOffset;return this.isPlaying&&Ue.a.audioEngine.audioContext&&(t+=Ue.a.audioEngine.audioContext.currentTime-this._startTime),t},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){Ue.a.audioEngine.canUseWebAudio&&(this.isPlaying&&this.stop(),this._isReadyToPlay=!1,this.soundTrackId===-1?this._scene.mainSoundTrack.removeSound(this):this._scene.soundTracks&&this._scene.soundTracks[this.soundTrackId].removeSound(this),this._soundGain&&(this._soundGain.disconnect(),this._soundGain=null),this._soundPanner&&(this._soundPanner.disconnect(),this._soundPanner=null),this._soundSource&&(this._soundSource.disconnect(),this._soundSource=null),this._audioBuffer=null,this._htmlAudioElement&&(this._htmlAudioElement.pause(),this._htmlAudioElement.src="",document.body.removeChild(this._htmlAudioElement)),this._streamingSource&&this._streamingSource.disconnect(),this._connectedTransformNode&&this._registerFunc&&(this._connectedTransformNode.unregisterAfterWorldMatrixUpdate(this._registerFunc),this._connectedTransformNode=null))},r.prototype.isReady=function(){return this._isReadyToPlay},r.prototype._soundLoaded=function(t){var e=this;Ue.a.audioEngine.audioContext&&Ue.a.audioEngine.audioContext.decodeAudioData(t,function(n){e._audioBuffer=n,e._isReadyToPlay=!0,e.autoplay&&e.play(0,e._offset,e._length),e._readyToPlayCallback&&e._readyToPlayCallback()},function(n){l.a.Error("Error while decoding audio data for: "+e.name+" / Error: "+n)})},r.prototype.setAudioBuffer=function(t){Ue.a.audioEngine.canUseWebAudio&&(this._audioBuffer=t,this._isReadyToPlay=!0)},r.prototype.updateOptions=function(t){var e,n,i,o,a,s,d,p,b;t&&(this.loop=(e=t.loop)!==null&&e!==void 0?e:this.loop,this.maxDistance=(n=t.maxDistance)!==null&&n!==void 0?n:this.maxDistance,this.useCustomAttenuation=(i=t.useCustomAttenuation)!==null&&i!==void 0?i:this.useCustomAttenuation,this.rolloffFactor=(o=t.rolloffFactor)!==null&&o!==void 0?o:this.rolloffFactor,this.refDistance=(a=t.refDistance)!==null&&a!==void 0?a:this.refDistance,this.distanceModel=(s=t.distanceModel)!==null&&s!==void 0?s:this.distanceModel,this._playbackRate=(d=t.playbackRate)!==null&&d!==void 0?d:this._playbackRate,this._length=(p=t.length)!==null&&p!==void 0?p:void 0,this._offset=(b=t.offset)!==null&&b!==void 0?b:void 0,this._updateSpatialParameters(),this.isPlaying&&(this._streaming&&this._htmlAudioElement?(this._htmlAudioElement.playbackRate=this._playbackRate,this._htmlAudioElement.loop!==this.loop&&(this._htmlAudioElement.loop=this.loop)):this._soundSource&&(this._soundSource.playbackRate.value=this._playbackRate,this._soundSource.loop!==this.loop&&(this._soundSource.loop=this.loop),this._offset!==void 0&&this._soundSource.loopStart!==this._offset&&(this._soundSource.loopStart=this._offset),this._length!==void 0&&this._length!==this._soundSource.loopEnd&&(this._soundSource.loopEnd=(0|this._offset)+this._length))))},r.prototype._createSpatialParameters=function(){Ue.a.audioEngine.canUseWebAudio&&Ue.a.audioEngine.audioContext&&(this._scene.headphone&&(this._panningModel="HRTF"),this._soundPanner=Ue.a.audioEngine.audioContext.createPanner(),this._soundPanner&&this._outputAudioNode&&(this._updateSpatialParameters(),this._soundPanner.connect(this._outputAudioNode),this._inputAudioNode=this._soundPanner))},r.prototype._updateSpatialParameters=function(){this.spatialSound&&this._soundPanner&&(this.useCustomAttenuation?(this._soundPanner.distanceModel="linear",this._soundPanner.maxDistance=Number.MAX_VALUE,this._soundPanner.refDistance=1,this._soundPanner.rolloffFactor=1,this._soundPanner.panningModel=this._panningModel):(this._soundPanner.distanceModel=this.distanceModel,this._soundPanner.maxDistance=this.maxDistance,this._soundPanner.refDistance=this.refDistance,this._soundPanner.rolloffFactor=this.rolloffFactor,this._soundPanner.panningModel=this._panningModel))},r.prototype.switchPanningModelToHRTF=function(){this._panningModel="HRTF",this._switchPanningModel()},r.prototype.switchPanningModelToEqualPower=function(){this._panningModel="equalpower",this._switchPanningModel()},r.prototype._switchPanningModel=function(){Ue.a.audioEngine.canUseWebAudio&&this.spatialSound&&this._soundPanner&&(this._soundPanner.panningModel=this._panningModel)},r.prototype.connectToSoundTrackAudioNode=function(t){Ue.a.audioEngine.canUseWebAudio&&this._outputAudioNode&&(this._isOutputConnected&&this._outputAudioNode.disconnect(),this._outputAudioNode.connect(t),this._isOutputConnected=!0)},r.prototype.setDirectionalCone=function(t,e,n){e<t?l.a.Error("setDirectionalCone(): outer angle of the cone must be superior or equal to the inner angle."):(this._coneInnerAngle=t,this._coneOuterAngle=e,this._coneOuterGain=n,this._isDirectional=!0,this.isPlaying&&this.loop&&(this.stop(),this.play(0,this._offset,this._length)))},Object.defineProperty(r.prototype,"directionalConeInnerAngle",{get:function(){return this._coneInnerAngle},set:function(t){if(t!=this._coneInnerAngle){if(this._coneOuterAngle<t)return void l.a.Error("directionalConeInnerAngle: outer angle of the cone must be superior or equal to the inner angle.");this._coneInnerAngle=t,Ue.a.audioEngine.canUseWebAudio&&this.spatialSound&&this._soundPanner&&(this._soundPanner.coneInnerAngle=this._coneInnerAngle)}},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"directionalConeOuterAngle",{get:function(){return this._coneOuterAngle},set:function(t){if(t!=this._coneOuterAngle){if(t<this._coneInnerAngle)return void l.a.Error("directionalConeOuterAngle: outer angle of the cone must be superior or equal to the inner angle.");this._coneOuterAngle=t,Ue.a.audioEngine.canUseWebAudio&&this.spatialSound&&this._soundPanner&&(this._soundPanner.coneOuterAngle=this._coneOuterAngle)}},enumerable:!1,configurable:!0}),r.prototype.setPosition=function(t){this._position=t,Ue.a.audioEngine.canUseWebAudio&&this.spatialSound&&this._soundPanner&&!isNaN(this._position.x)&&!isNaN(this._position.y)&&!isNaN(this._position.z)&&this._soundPanner.setPosition(this._position.x,this._position.y,this._position.z)},r.prototype.setLocalDirectionToMesh=function(t){this._localDirection=t,Ue.a.audioEngine.canUseWebAudio&&this._connectedTransformNode&&this.isPlaying&&this._updateDirection()},r.prototype._updateDirection=function(){if(this._connectedTransformNode&&this._soundPanner){var t=this._connectedTransformNode.getWorldMatrix(),e=u.e.TransformNormal(this._localDirection,t);e.normalize(),this._soundPanner.setOrientation(e.x,e.y,e.z)}},r.prototype.updateDistanceFromListener=function(){if(Ue.a.audioEngine.canUseWebAudio&&this._connectedTransformNode&&this.useCustomAttenuation&&this._soundGain&&this._scene.activeCamera){var t=this._connectedTransformNode.getDistanceToCamera(this._scene.activeCamera);this._soundGain.gain.value=this._customAttenuationFunction(this._volume,t,this.maxDistance,this.refDistance,this.rolloffFactor)}},r.prototype.setAttenuationFunction=function(t){this._customAttenuationFunction=t},r.prototype.play=function(t,e,n){var i=this;if(this._isReadyToPlay&&this._scene.audioEnabled&&Ue.a.audioEngine.audioContext)try{this._startOffset<0&&(t=-this._startOffset,this._startOffset=0);var o=t?Ue.a.audioEngine.audioContext.currentTime+t:Ue.a.audioEngine.audioContext.currentTime;if(this._soundSource&&this._streamingSource||this.spatialSound&&this._soundPanner&&(isNaN(this._position.x)||isNaN(this._position.y)||isNaN(this._position.z)||this._soundPanner.setPosition(this._position.x,this._position.y,this._position.z),this._isDirectional&&(this._soundPanner.coneInnerAngle=this._coneInnerAngle,this._soundPanner.coneOuterAngle=this._coneOuterAngle,this._soundPanner.coneOuterGain=this._coneOuterGain,this._connectedTransformNode?this._updateDirection():this._soundPanner.setOrientation(this._localDirection.x,this._localDirection.y,this._localDirection.z))),this._streaming)this._streamingSource||(this._streamingSource=Ue.a.audioEngine.audioContext.createMediaElementSource(this._htmlAudioElement),this._htmlAudioElement.onended=function(){i._onended()},this._htmlAudioElement.playbackRate=this._playbackRate),this._streamingSource.disconnect(),this._inputAudioNode&&this._streamingSource.connect(this._inputAudioNode),this._htmlAudioElement&&(a=function(){if(Ue.a.audioEngine.unlocked){var s=i._htmlAudioElement.play();s!==void 0&&s.catch(function(d){Ue.a.audioEngine.lock(),(i.loop||i.autoplay)&&Ue.a.audioEngine.onAudioUnlockedObservable.addOnce(function(){a()})})}else(i.loop||i.autoplay)&&Ue.a.audioEngine.onAudioUnlockedObservable.addOnce(function(){a()})})();else{var a=function(){if(Ue.a.audioEngine.audioContext){if(n=n||i._length,e=e||i._offset,i._soundSource){var s=i._soundSource;s.onended=function(){s.disconnect()}}if(i._soundSource=Ue.a.audioEngine.audioContext.createBufferSource(),i._soundSource&&i._inputAudioNode){i._soundSource.buffer=i._audioBuffer,i._soundSource.connect(i._inputAudioNode),i._soundSource.loop=i.loop,e!==void 0&&(i._soundSource.loopStart=e),n!==void 0&&(i._soundSource.loopEnd=(0|e)+n),i._soundSource.playbackRate.value=i._playbackRate,i._soundSource.onended=function(){i._onended()},o=t?Ue.a.audioEngine.audioContext.currentTime+t:Ue.a.audioEngine.audioContext.currentTime;var d=i.isPaused?i._startOffset%i._soundSource.buffer.duration:e||0;i._soundSource.start(o,d,i.loop?void 0:n)}}};Ue.a.audioEngine.audioContext.state==="suspended"?setTimeout(function(){Ue.a.audioEngine.audioContext.state==="suspended"?(Ue.a.audioEngine.lock(),(i.loop||i.autoplay)&&Ue.a.audioEngine.onAudioUnlockedObservable.addOnce(function(){a()})):a()},500):a()}this._startTime=o,this.isPlaying=!0,this.isPaused=!1}catch(s){l.a.Error("Error while trying to play audio: "+this.name+", "+s.message)}},r.prototype._onended=function(){this.isPlaying=!1,this._startOffset=0,this.onended&&this.onended(),this.onEndedObservable.notifyObservers(this)},r.prototype.stop=function(t){var e=this;if(this.isPlaying){if(this._streaming)this._htmlAudioElement?(this._htmlAudioElement.pause(),this._htmlAudioElement.currentTime>0&&(this._htmlAudioElement.currentTime=0)):this._streamingSource.disconnect(),this.isPlaying=!1;else if(Ue.a.audioEngine.audioContext&&this._soundSource){var n=t?Ue.a.audioEngine.audioContext.currentTime+t:Ue.a.audioEngine.audioContext.currentTime;this._soundSource.stop(n),this._soundSource.onended=function(){e.isPlaying=!1},this.isPaused||(this._startOffset=0)}}},r.prototype.pause=function(){this.isPlaying&&(this.isPaused=!0,this._streaming?this._htmlAudioElement?this._htmlAudioElement.pause():this._streamingSource.disconnect():Ue.a.audioEngine.audioContext&&(this.stop(0),this._startOffset+=Ue.a.audioEngine.audioContext.currentTime-this._startTime))},r.prototype.setVolume=function(t,e){Ue.a.audioEngine.canUseWebAudio&&this._soundGain&&(e&&Ue.a.audioEngine.audioContext?(this._soundGain.gain.cancelScheduledValues(Ue.a.audioEngine.audioContext.currentTime),this._soundGain.gain.setValueAtTime(this._soundGain.gain.value,Ue.a.audioEngine.audioContext.currentTime),this._soundGain.gain.linearRampToValueAtTime(t,Ue.a.audioEngine.audioContext.currentTime+e)):this._soundGain.gain.value=t),this._volume=t},r.prototype.setPlaybackRate=function(t){this._playbackRate=t,this.isPlaying&&(this._streaming&&this._htmlAudioElement?this._htmlAudioElement.playbackRate=this._playbackRate:this._soundSource&&(this._soundSource.playbackRate.value=this._playbackRate))},r.prototype.getVolume=function(){return this._volume},r.prototype.attachToMesh=function(t){var e=this;this._connectedTransformNode&&this._registerFunc&&(this._connectedTransformNode.unregisterAfterWorldMatrixUpdate(this._registerFunc),this._registerFunc=null),this._connectedTransformNode=t,this.spatialSound||(this.spatialSound=!0,this._createSpatialParameters(),this.isPlaying&&this.loop&&(this.stop(),this.play(0,this._offset,this._length))),this._onRegisterAfterWorldMatrixUpdate(this._connectedTransformNode),this._registerFunc=function(n){return e._onRegisterAfterWorldMatrixUpdate(n)},this._connectedTransformNode.registerAfterWorldMatrixUpdate(this._registerFunc)},r.prototype.detachFromMesh=function(){this._connectedTransformNode&&this._registerFunc&&(this._connectedTransformNode.unregisterAfterWorldMatrixUpdate(this._registerFunc),this._registerFunc=null,this._connectedTransformNode=null)},r.prototype._onRegisterAfterWorldMatrixUpdate=function(t){if(this._positionInEmitterSpace)t.worldMatrixFromCache.invertToRef(u.c.Matrix[0]),this.setPosition(u.c.Matrix[0].getTranslation());else if(t.getBoundingInfo){var e=t.getBoundingInfo();this.setPosition(e.boundingSphere.centerWorld)}else this.setPosition(t.absolutePosition);Ue.a.audioEngine.canUseWebAudio&&this._isDirectional&&this.isPlaying&&this._updateDirection()},r.prototype.clone=function(){var t=this;if(this._streaming)return null;var e=function(){t._isReadyToPlay?(i._audioBuffer=t.getAudioBuffer(),i._isReadyToPlay=!0,i.autoplay&&i.play(0,t._offset,t._length)):window.setTimeout(e,300)},n={autoplay:this.autoplay,loop:this.loop,volume:this._volume,spatialSound:this.spatialSound,maxDistance:this.maxDistance,useCustomAttenuation:this.useCustomAttenuation,rolloffFactor:this.rolloffFactor,refDistance:this.refDistance,distanceModel:this.distanceModel},i=new r(this.name+"_cloned",new ArrayBuffer(0),this._scene,null,n);return this.useCustomAttenuation&&i.setAttenuationFunction(this._customAttenuationFunction),i.setPosition(this._position),i.setPlaybackRate(this._playbackRate),e(),i},r.prototype.getAudioBuffer=function(){return this._audioBuffer},r.prototype.getSoundSource=function(){return this._soundSource},r.prototype.getSoundGain=function(){return this._soundGain},r.prototype.serialize=function(){var t={name:this.name,url:this.name,autoplay:this.autoplay,loop:this.loop,volume:this._volume,spatialSound:this.spatialSound,maxDistance:this.maxDistance,rolloffFactor:this.rolloffFactor,refDistance:this.refDistance,distanceModel:this.distanceModel,playbackRate:this._playbackRate,panningModel:this._panningModel,soundTrackId:this.soundTrackId,metadata:this.metadata};return this.spatialSound&&(this._connectedTransformNode&&(t.connectedMeshId=this._connectedTransformNode.id),t.position=this._position.asArray(),t.refDistance=this.refDistance,t.distanceModel=this.distanceModel,t.isDirectional=this._isDirectional,t.localDirectionToMesh=this._localDirection.asArray(),t.coneInnerAngle=this._coneInnerAngle,t.coneOuterAngle=this._coneOuterAngle,t.coneOuterGain=this._coneOuterGain),t},r.Parse=function(t,e,n,i){var o,a=t.name;o=t.url?n+t.url:n+a;var s,d={autoplay:t.autoplay,loop:t.loop,volume:t.volume,spatialSound:t.spatialSound,maxDistance:t.maxDistance,rolloffFactor:t.rolloffFactor,refDistance:t.refDistance,distanceModel:t.distanceModel,playbackRate:t.playbackRate};if(i){var p=function(){i._isReadyToPlay?(s._audioBuffer=i.getAudioBuffer(),s._isReadyToPlay=!0,s.autoplay&&s.play(0,s._offset,s._length)):window.setTimeout(p,300)};s=new r(a,new ArrayBuffer(0),e,null,d),p()}else s=new r(a,o,e,function(){e._removePendingData(s)},d),e._addPendingData(s);if(t.position){var b=u.e.FromArray(t.position);s.setPosition(b)}if(t.isDirectional&&(s.setDirectionalCone(t.coneInnerAngle||360,t.coneOuterAngle||360,t.coneOuterGain||0),t.localDirectionToMesh)){var P=u.e.FromArray(t.localDirectionToMesh);s.setLocalDirectionToMesh(P)}if(t.connectedMeshId){var O=e.getMeshByID(t.connectedMeshId);O&&s.attachToMesh(O)}return t.metadata&&(s.metadata=t.metadata),s},r._SceneComponentInitialization=function(t){throw An.a.WarnImport("AudioSceneComponent")},r}(),Lo=function(){function r(t,e){e===void 0&&(e={}),this.id=-1,this._isInitialized=!1,this._scene=t,this.soundCollection=new Array,this._options=e,!this._options.mainTrack&&this._scene.soundTracks&&(this._scene.soundTracks.push(this),this.id=this._scene.soundTracks.length-1)}return r.prototype._initializeSoundTrackAudioGraph=function(){Ue.a.audioEngine.canUseWebAudio&&Ue.a.audioEngine.audioContext&&(this._outputAudioNode=Ue.a.audioEngine.audioContext.createGain(),this._outputAudioNode.connect(Ue.a.audioEngine.masterGain),this._options&&this._options.volume&&(this._outputAudioNode.gain.value=this._options.volume),this._isInitialized=!0)},r.prototype.dispose=function(){if(Ue.a.audioEngine&&Ue.a.audioEngine.canUseWebAudio){for(this._connectedAnalyser&&this._connectedAnalyser.stopDebugCanvas();this.soundCollection.length;)this.soundCollection[0].dispose();this._outputAudioNode&&this._outputAudioNode.disconnect(),this._outputAudioNode=null}},r.prototype.addSound=function(t){this._isInitialized||this._initializeSoundTrackAudioGraph(),Ue.a.audioEngine.canUseWebAudio&&this._outputAudioNode&&t.connectToSoundTrackAudioNode(this._outputAudioNode),t.soundTrackId&&(t.soundTrackId===-1?this._scene.mainSoundTrack.removeSound(t):this._scene.soundTracks&&this._scene.soundTracks[t.soundTrackId].removeSound(t)),this.soundCollection.push(t),t.soundTrackId=this.id},r.prototype.removeSound=function(t){var e=this.soundCollection.indexOf(t);e!==-1&&this.soundCollection.splice(e,1)},r.prototype.setVolume=function(t){Ue.a.audioEngine.canUseWebAudio&&this._outputAudioNode&&(this._outputAudioNode.gain.value=t)},r.prototype.switchPanningModelToHRTF=function(){if(Ue.a.audioEngine.canUseWebAudio)for(var t=0;t<this.soundCollection.length;t++)this.soundCollection[t].switchPanningModelToHRTF()},r.prototype.switchPanningModelToEqualPower=function(){if(Ue.a.audioEngine.canUseWebAudio)for(var t=0;t<this.soundCollection.length;t++)this.soundCollection[t].switchPanningModelToEqualPower()},r.prototype.connectToAnalyser=function(t){this._connectedAnalyser&&this._connectedAnalyser.stopDebugCanvas(),this._connectedAnalyser=t,Ue.a.audioEngine.canUseWebAudio&&this._outputAudioNode&&(this._outputAudioNode.disconnect(),this._connectedAnalyser.connectAudioNodes(this._outputAudioNode,Ue.a.audioEngine.masterGain))},r}(),at=f(17);U.a.AddParser(at.a.NAME_AUDIO,function(r,t,e,n){var i,o=[];if(e.sounds=e.sounds||[],r.sounds!==void 0&&r.sounds!==null)for(var a=0,s=r.sounds.length;a<s;a++){var d=r.sounds[a];Ue.a.audioEngine.canUseWebAudio?(d.url||(d.url=d.name),o[d.url]?e.sounds.push(ei.Parse(d,t,n,o[d.url])):(i=ei.Parse(d,t,n),o[d.url]=i,e.sounds.push(i))):e.sounds.push(new ei(d.name,null,t))}o=[]}),Object.defineProperty(_e.a.prototype,"mainSoundTrack",{get:function(){var r=this._getComponent(at.a.NAME_AUDIO);return r||(r=new ti(this),this._addComponent(r)),this._mainSoundTrack||(this._mainSoundTrack=new Lo(this,{mainTrack:!0})),this._mainSoundTrack},enumerable:!0,configurable:!0}),_e.a.prototype.getSoundByName=function(r){var t;for(t=0;t<this.mainSoundTrack.soundCollection.length;t++)if(this.mainSoundTrack.soundCollection[t].name===r)return this.mainSoundTrack.soundCollection[t];if(this.soundTracks){for(var e=0;e<this.soundTracks.length;e++)for(t=0;t<this.soundTracks[e].soundCollection.length;t++)if(this.soundTracks[e].soundCollection[t].name===r)return this.soundTracks[e].soundCollection[t]}return null},Object.defineProperty(_e.a.prototype,"audioEnabled",{get:function(){var r=this._getComponent(at.a.NAME_AUDIO);return r||(r=new ti(this),this._addComponent(r)),r.audioEnabled},set:function(r){var t=this._getComponent(at.a.NAME_AUDIO);t||(t=new ti(this),this._addComponent(t)),r?t.enableAudio():t.disableAudio()},enumerable:!0,configurable:!0}),Object.defineProperty(_e.a.prototype,"headphone",{get:function(){var r=this._getComponent(at.a.NAME_AUDIO);return r||(r=new ti(this),this._addComponent(r)),r.headphone},set:function(r){var t=this._getComponent(at.a.NAME_AUDIO);t||(t=new ti(this),this._addComponent(t)),r?t.switchAudioModeForHeadphones():t.switchAudioModeForNormalSpeakers()},enumerable:!0,configurable:!0}),Object.defineProperty(_e.a.prototype,"audioListenerPositionProvider",{get:function(){var r=this._getComponent(at.a.NAME_AUDIO);return r||(r=new ti(this),this._addComponent(r)),r.audioListenerPositionProvider},set:function(r){var t=this._getComponent(at.a.NAME_AUDIO);if(t||(t=new ti(this),this._addComponent(t)),typeof r!="function")throw new Error("The value passed to [Scene.audioListenerPositionProvider] must be a function that returns a Vector3");t.audioListenerPositionProvider=r},enumerable:!0,configurable:!0}),Object.defineProperty(_e.a.prototype,"audioPositioningRefreshRate",{get:function(){var r=this._getComponent(at.a.NAME_AUDIO);return r||(r=new ti(this),this._addComponent(r)),r.audioPositioningRefreshRate},set:function(r){var t=this._getComponent(at.a.NAME_AUDIO);t||(t=new ti(this),this._addComponent(t)),t.audioPositioningRefreshRate=r},enumerable:!0,configurable:!0});var ti=function(){function r(t){this.name=at.a.NAME_AUDIO,this._audioEnabled=!0,this._headphone=!1,this.audioPositioningRefreshRate=500,this._audioListenerPositionProvider=null,this._cachedCameraDirection=new u.e,this._cachedCameraPosition=new u.e,this._lastCheck=0,this.scene=t,t.soundTracks=new Array,t.sounds=new Array}return Object.defineProperty(r.prototype,"audioEnabled",{get:function(){return this._audioEnabled},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"headphone",{get:function(){return this._headphone},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"audioListenerPositionProvider",{get:function(){return this._audioListenerPositionProvider},set:function(t){this._audioListenerPositionProvider=t},enumerable:!1,configurable:!0}),r.prototype.register=function(){this.scene._afterRenderStage.registerStep(at.a.STEP_AFTERRENDER_AUDIO,this,this._afterRender)},r.prototype.rebuild=function(){},r.prototype.serialize=function(t){if(t.sounds=[],this.scene.soundTracks)for(var e=0;e<this.scene.soundTracks.length;e++)for(var n=this.scene.soundTracks[e],i=0;i<n.soundCollection.length;i++)t.sounds.push(n.soundCollection[i].serialize())},r.prototype.addFromContainer=function(t){var e=this;t.sounds&&t.sounds.forEach(function(n){n.play(),n.autoplay=!0,e.scene.mainSoundTrack.addSound(n)})},r.prototype.removeFromContainer=function(t,e){var n=this;e===void 0&&(e=!1),t.sounds&&t.sounds.forEach(function(i){i.stop(),i.autoplay=!1,n.scene.mainSoundTrack.removeSound(i),e&&i.dispose()})},r.prototype.dispose=function(){var t=this.scene;if(t._mainSoundTrack&&t.mainSoundTrack.dispose(),t.soundTracks)for(var e=0;e<t.soundTracks.length;e++)t.soundTracks[e].dispose()},r.prototype.disableAudio=function(){var t,e=this.scene;for(this._audioEnabled=!1,Ue.a.audioEngine&&Ue.a.audioEngine.audioContext&&Ue.a.audioEngine.audioContext.suspend(),t=0;t<e.mainSoundTrack.soundCollection.length;t++)e.mainSoundTrack.soundCollection[t].pause();if(e.soundTracks)for(t=0;t<e.soundTracks.length;t++)for(var n=0;n<e.soundTracks[t].soundCollection.length;n++)e.soundTracks[t].soundCollection[n].pause()},r.prototype.enableAudio=function(){var t,e=this.scene;for(this._audioEnabled=!0,Ue.a.audioEngine&&Ue.a.audioEngine.audioContext&&Ue.a.audioEngine.audioContext.resume(),t=0;t<e.mainSoundTrack.soundCollection.length;t++)e.mainSoundTrack.soundCollection[t].isPaused&&e.mainSoundTrack.soundCollection[t].play();if(e.soundTracks)for(t=0;t<e.soundTracks.length;t++)for(var n=0;n<e.soundTracks[t].soundCollection.length;n++)e.soundTracks[t].soundCollection[n].isPaused&&e.soundTracks[t].soundCollection[n].play()},r.prototype.switchAudioModeForHeadphones=function(){var t=this.scene;if(this._headphone=!0,t.mainSoundTrack.switchPanningModelToHRTF(),t.soundTracks)for(var e=0;e<t.soundTracks.length;e++)t.soundTracks[e].switchPanningModelToHRTF()},r.prototype.switchAudioModeForNormalSpeakers=function(){var t=this.scene;if(this._headphone=!1,t.mainSoundTrack.switchPanningModelToEqualPower(),t.soundTracks)for(var e=0;e<t.soundTracks.length;e++)t.soundTracks[e].switchPanningModelToEqualPower()},r.prototype._afterRender=function(){var t=be.a.Now;if(!(this._lastCheck&&t-this._lastCheck<this.audioPositioningRefreshRate)){this._lastCheck=t;var e=this.scene;if(this._audioEnabled&&e._mainSoundTrack&&e.soundTracks&&(e._mainSoundTrack.soundCollection.length!==0||e.soundTracks.length!==1)){var n=Ue.a.audioEngine;if(n&&n.audioContext){if(this._audioListenerPositionProvider){var i=this._audioListenerPositionProvider();i.x=i.x||0,i.y=i.y||0,i.z=i.z||0,n.audioContext.listener.setPosition(i.x,i.y,i.z)}else{var o;if(o=e.activeCameras&&e.activeCameras.length>0?e.activeCameras[0]:e.activeCamera){this._cachedCameraPosition.equals(o.globalPosition)||(this._cachedCameraPosition.copyFrom(o.globalPosition),n.audioContext.listener.setPosition(o.globalPosition.x,o.globalPosition.y,o.globalPosition.z)),o.rigCameras&&o.rigCameras.length>0&&(o=o.rigCameras[0]);var a=u.a.Invert(o.getViewMatrix()),s=u.e.TransformNormal(e.useRightHandedSystem?r._CameraDirectionRH:r._CameraDirectionLH,a);s.normalize(),isNaN(s.x)||isNaN(s.y)||isNaN(s.z)||this._cachedCameraDirection.equals(s)||(this._cachedCameraDirection.copyFrom(s),n.audioContext.listener.setOrientation(s.x,s.y,s.z,0,1,0))}else n.audioContext.listener.setPosition(0,0,0)}var d;for(d=0;d<e.mainSoundTrack.soundCollection.length;d++){var p=e.mainSoundTrack.soundCollection[d];p.useCustomAttenuation&&p.updateDistanceFromListener()}if(e.soundTracks)for(d=0;d<e.soundTracks.length;d++)for(var b=0;b<e.soundTracks[d].soundCollection.length;b++)(p=e.soundTracks[d].soundCollection[b]).useCustomAttenuation&&p.updateDistanceFromListener()}}}},r._CameraDirectionLH=new u.e(0,0,-1),r._CameraDirectionRH=new u.e(0,0,1),r}();ei._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_AUDIO);t||(t=new ti(r),r._addComponent(t))};var Df=function(){function r(t,e,n){var i=this;if(this.loop=!1,this._coneInnerAngle=360,this._coneOuterAngle=360,this._volume=1,this.isPlaying=!1,this.isPaused=!1,this._sounds=[],this._weights=[],e.length!==n.length)throw new Error("Sounds length does not equal weights length");this.loop=t,this._weights=n;for(var o=0,a=0,s=n;a<s.length;a++)o+=s[a];for(var d=o>0?1/o:0,p=0;p<this._weights.length;p++)this._weights[p]*=d;this._sounds=e;for(var b=0,P=this._sounds;b<P.length;b++)P[b].onEndedObservable.add(function(){i._onended()})}return Object.defineProperty(r.prototype,"directionalConeInnerAngle",{get:function(){return this._coneInnerAngle},set:function(t){if(t!==this._coneInnerAngle){if(this._coneOuterAngle<t)return void l.a.Error("directionalConeInnerAngle: outer angle of the cone must be superior or equal to the inner angle.");this._coneInnerAngle=t;for(var e=0,n=this._sounds;e<n.length;e++)n[e].directionalConeInnerAngle=t}},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"directionalConeOuterAngle",{get:function(){return this._coneOuterAngle},set:function(t){if(t!==this._coneOuterAngle){if(t<this._coneInnerAngle)return void l.a.Error("directionalConeOuterAngle: outer angle of the cone must be superior or equal to the inner angle.");this._coneOuterAngle=t;for(var e=0,n=this._sounds;e<n.length;e++)n[e].directionalConeOuterAngle=t}},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"volume",{get:function(){return this._volume},set:function(t){if(t!==this._volume)for(var e=0,n=this._sounds;e<n.length;e++)n[e].setVolume(t)},enumerable:!1,configurable:!0}),r.prototype._onended=function(){this._currentIndex!==void 0&&(this._sounds[this._currentIndex].autoplay=!1),this.loop&&this.isPlaying?this.play():this.isPlaying=!1},r.prototype.pause=function(){this.isPaused=!0,this._currentIndex!==void 0&&this._sounds[this._currentIndex].pause()},r.prototype.stop=function(){this.isPlaying=!1,this._currentIndex!==void 0&&this._sounds[this._currentIndex].stop()},r.prototype.play=function(t){if(!this.isPaused){this.stop();for(var e=Math.random(),n=0,i=0;i<this._weights.length;i++)if(e<=(n+=this._weights[i])){this._currentIndex=i;break}}var o=this._sounds[this._currentIndex];o.isReady()?o.play(0,this.isPaused?void 0:t):o.autoplay=!0,this.isPlaying=!0,this.isPaused=!1},r}(),Tt=f(18),pl=function(){function r(){this._zoomStopsAnimation=!1,this._idleRotationSpeed=.05,this._idleRotationWaitTime=2e3,this._idleRotationSpinupTime=2e3,this._isPointerDown=!1,this._lastFrameTime=null,this._lastInteractionTime=-1/0,this._cameraRotationSpeed=0,this._lastFrameRadius=0}return Object.defineProperty(r.prototype,"name",{get:function(){return"AutoRotation"},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"zoomStopsAnimation",{get:function(){return this._zoomStopsAnimation},set:function(t){this._zoomStopsAnimation=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"idleRotationSpeed",{get:function(){return this._idleRotationSpeed},set:function(t){this._idleRotationSpeed=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"idleRotationWaitTime",{get:function(){return this._idleRotationWaitTime},set:function(t){this._idleRotationWaitTime=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"idleRotationSpinupTime",{get:function(){return this._idleRotationSpinupTime},set:function(t){this._idleRotationSpinupTime=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rotationInProgress",{get:function(){return Math.abs(this._cameraRotationSpeed)>0},enumerable:!1,configurable:!0}),r.prototype.init=function(){},r.prototype.attach=function(t){var e=this;this._attachedCamera=t;var n=this._attachedCamera.getScene();this._onPrePointerObservableObserver=n.onPrePointerObservable.add(function(i){i.type!==Tt.a.POINTERDOWN?i.type===Tt.a.POINTERUP&&(e._isPointerDown=!1):e._isPointerDown=!0}),this._onAfterCheckInputsObserver=t.onAfterCheckInputsObservable.add(function(){var i=be.a.Now,o=0;e._lastFrameTime!=null&&(o=i-e._lastFrameTime),e._lastFrameTime=i,e._applyUserInteraction();var a=i-e._lastInteractionTime-e._idleRotationWaitTime,s=Math.max(Math.min(a/e._idleRotationSpinupTime,1),0);e._cameraRotationSpeed=e._idleRotationSpeed*s,e._attachedCamera&&(e._attachedCamera.alpha-=e._cameraRotationSpeed*(o/1e3))})},r.prototype.detach=function(){if(this._attachedCamera){var t=this._attachedCamera.getScene();this._onPrePointerObservableObserver&&t.onPrePointerObservable.remove(this._onPrePointerObservableObserver),this._attachedCamera.onAfterCheckInputsObservable.remove(this._onAfterCheckInputsObserver),this._attachedCamera=null}},r.prototype._userIsZooming=function(){return!!this._attachedCamera&&this._attachedCamera.inertialRadiusOffset!==0},r.prototype._shouldAnimationStopForInteraction=function(){if(!this._attachedCamera)return!1;var t=!1;return this._lastFrameRadius===this._attachedCamera.radius&&this._attachedCamera.inertialRadiusOffset!==0&&(t=!0),this._lastFrameRadius=this._attachedCamera.radius,this._zoomStopsAnimation?t:this._userIsZooming()},r.prototype._applyUserInteraction=function(){this._userIsMoving()&&!this._shouldAnimationStopForInteraction()&&(this._lastInteractionTime=be.a.Now)},r.prototype._userIsMoving=function(){return!!this._attachedCamera&&(this._attachedCamera.inertialAlphaOffset!==0||this._attachedCamera.inertialBetaOffset!==0||this._attachedCamera.inertialRadiusOffset!==0||this._attachedCamera.inertialPanningX!==0||this._attachedCamera.inertialPanningY!==0||this._isPointerDown)},r}(),_l=function(){function r(){this.transitionDuration=450,this.lowerRadiusTransitionRange=2,this.upperRadiusTransitionRange=-2,this._autoTransitionRange=!1,this._radiusIsAnimating=!1,this._radiusBounceTransition=null,this._animatables=new Array}return Object.defineProperty(r.prototype,"name",{get:function(){return"Bouncing"},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"autoTransitionRange",{get:function(){return this._autoTransitionRange},set:function(t){var e=this;if(this._autoTransitionRange!==t){this._autoTransitionRange=t;var n=this._attachedCamera;n&&(t?this._onMeshTargetChangedObserver=n.onMeshTargetChangedObservable.add(function(i){if(i){i.computeWorldMatrix(!0);var o=i.getBoundingInfo().diagonalLength;e.lowerRadiusTransitionRange=.05*o,e.upperRadiusTransitionRange=.05*o}}):this._onMeshTargetChangedObserver&&n.onMeshTargetChangedObservable.remove(this._onMeshTargetChangedObserver))}},enumerable:!1,configurable:!0}),r.prototype.init=function(){},r.prototype.attach=function(t){var e=this;this._attachedCamera=t,this._onAfterCheckInputsObserver=t.onAfterCheckInputsObservable.add(function(){e._attachedCamera&&(e._isRadiusAtLimit(e._attachedCamera.lowerRadiusLimit)&&e._applyBoundRadiusAnimation(e.lowerRadiusTransitionRange),e._isRadiusAtLimit(e._attachedCamera.upperRadiusLimit)&&e._applyBoundRadiusAnimation(e.upperRadiusTransitionRange))})},r.prototype.detach=function(){this._attachedCamera&&(this._onAfterCheckInputsObserver&&this._attachedCamera.onAfterCheckInputsObservable.remove(this._onAfterCheckInputsObserver),this._onMeshTargetChangedObserver&&this._attachedCamera.onMeshTargetChangedObservable.remove(this._onMeshTargetChangedObserver),this._attachedCamera=null)},r.prototype._isRadiusAtLimit=function(t){return!!this._attachedCamera&&this._attachedCamera.radius===t&&!this._radiusIsAnimating},r.prototype._applyBoundRadiusAnimation=function(t){var e=this;if(this._attachedCamera){this._radiusBounceTransition||(r.EasingFunction.setEasingMode(r.EasingMode),this._radiusBounceTransition=k.CreateAnimation("radius",k.ANIMATIONTYPE_FLOAT,60,r.EasingFunction)),this._cachedWheelPrecision=this._attachedCamera.wheelPrecision,this._attachedCamera.wheelPrecision=1/0,this._attachedCamera.inertialRadiusOffset=0,this.stopAllAnimations(),this._radiusIsAnimating=!0;var n=k.TransitionTo("radius",this._attachedCamera.radius+t,this._attachedCamera,this._attachedCamera.getScene(),60,this._radiusBounceTransition,this.transitionDuration,function(){return e._clearAnimationLocks()});n&&this._animatables.push(n)}},r.prototype._clearAnimationLocks=function(){this._radiusIsAnimating=!1,this._attachedCamera&&(this._attachedCamera.wheelPrecision=this._cachedWheelPrecision)},r.prototype.stopAllAnimations=function(){for(this._attachedCamera&&(this._attachedCamera.animations=[]);this._animatables.length;)this._animatables[0].onAnimationEnd=null,this._animatables[0].stop(),this._animatables.shift()},r.EasingFunction=new $e(.3),r.EasingMode=Ge.EASINGMODE_EASEOUT,r}(),ml=function(){function r(){this._mode=r.FitFrustumSidesMode,this._radiusScale=1,this._positionScale=.5,this._defaultElevation=.3,this._elevationReturnTime=1500,this._elevationReturnWaitTime=1e3,this._zoomStopsAnimation=!1,this._framingTime=1500,this.autoCorrectCameraLimitsAndSensibility=!0,this._isPointerDown=!1,this._lastInteractionTime=-1/0,this._animatables=new Array,this._betaIsAnimating=!1}return Object.defineProperty(r.prototype,"name",{get:function(){return"Framing"},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"mode",{get:function(){return this._mode},set:function(t){this._mode=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"radiusScale",{get:function(){return this._radiusScale},set:function(t){this._radiusScale=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"positionScale",{get:function(){return this._positionScale},set:function(t){this._positionScale=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"defaultElevation",{get:function(){return this._defaultElevation},set:function(t){this._defaultElevation=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"elevationReturnTime",{get:function(){return this._elevationReturnTime},set:function(t){this._elevationReturnTime=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"elevationReturnWaitTime",{get:function(){return this._elevationReturnWaitTime},set:function(t){this._elevationReturnWaitTime=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"zoomStopsAnimation",{get:function(){return this._zoomStopsAnimation},set:function(t){this._zoomStopsAnimation=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"framingTime",{get:function(){return this._framingTime},set:function(t){this._framingTime=t},enumerable:!1,configurable:!0}),r.prototype.init=function(){},r.prototype.attach=function(t){var e=this;this._attachedCamera=t;var n=this._attachedCamera.getScene();r.EasingFunction.setEasingMode(r.EasingMode),this._onPrePointerObservableObserver=n.onPrePointerObservable.add(function(i){i.type!==Tt.a.POINTERDOWN?i.type===Tt.a.POINTERUP&&(e._isPointerDown=!1):e._isPointerDown=!0}),this._onMeshTargetChangedObserver=t.onMeshTargetChangedObservable.add(function(i){i&&e.zoomOnMesh(i)}),this._onAfterCheckInputsObserver=t.onAfterCheckInputsObservable.add(function(){e._applyUserInteraction(),e._maintainCameraAboveGround()})},r.prototype.detach=function(){if(this._attachedCamera){var t=this._attachedCamera.getScene();this._onPrePointerObservableObserver&&t.onPrePointerObservable.remove(this._onPrePointerObservableObserver),this._onAfterCheckInputsObserver&&this._attachedCamera.onAfterCheckInputsObservable.remove(this._onAfterCheckInputsObserver),this._onMeshTargetChangedObserver&&this._attachedCamera.onMeshTargetChangedObservable.remove(this._onMeshTargetChangedObserver),this._attachedCamera=null}},r.prototype.zoomOnMesh=function(t,e,n){e===void 0&&(e=!1),n===void 0&&(n=null),t.computeWorldMatrix(!0);var i=t.getBoundingInfo().boundingBox;this.zoomOnBoundingInfo(i.minimumWorld,i.maximumWorld,e,n)},r.prototype.zoomOnMeshHierarchy=function(t,e,n){e===void 0&&(e=!1),n===void 0&&(n=null),t.computeWorldMatrix(!0);var i=t.getHierarchyBoundingVectors(!0);this.zoomOnBoundingInfo(i.min,i.max,e,n)},r.prototype.zoomOnMeshesHierarchy=function(t,e,n){e===void 0&&(e=!1),n===void 0&&(n=null);for(var i=new u.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),o=new u.e(-Number.MAX_VALUE,-Number.MAX_VALUE,-Number.MAX_VALUE),a=0;a<t.length;a++){var s=t[a].getHierarchyBoundingVectors(!0);u.e.CheckExtends(s.min,i,o),u.e.CheckExtends(s.max,i,o)}this.zoomOnBoundingInfo(i,o,e,n)},r.prototype.zoomOnBoundingInfo=function(t,e,n,i){var o,a=this;if(n===void 0&&(n=!1),i===void 0&&(i=null),this._attachedCamera){var s=t.y,d=s+(e.y-s)*this._positionScale,p=e.subtract(t).scale(.5);if(n)o=new u.e(0,d,0);else{var b=t.add(p);o=new u.e(b.x,d,b.z)}this._vectorTransition||(this._vectorTransition=k.CreateAnimation("target",k.ANIMATIONTYPE_VECTOR3,60,r.EasingFunction)),this._betaIsAnimating=!0;var P=k.TransitionTo("target",o,this._attachedCamera,this._attachedCamera.getScene(),60,this._vectorTransition,this._framingTime);P&&this._animatables.push(P);var O=0;if(this._mode===r.FitFrustumSidesMode){var B=this._calculateLowerRadiusFromModelBoundingSphere(t,e);this.autoCorrectCameraLimitsAndSensibility&&(this._attachedCamera.lowerRadiusLimit=p.length()+this._attachedCamera.minZ),O=B}else this._mode===r.IgnoreBoundsSizeMode&&(O=this._calculateLowerRadiusFromModelBoundingSphere(t,e),this.autoCorrectCameraLimitsAndSensibility&&this._attachedCamera.lowerRadiusLimit===null&&(this._attachedCamera.lowerRadiusLimit=this._attachedCamera.minZ));if(this.autoCorrectCameraLimitsAndSensibility){var F=e.subtract(t).length();this._attachedCamera.panningSensibility=5e3/F,this._attachedCamera.wheelPrecision=100/O}this._radiusTransition||(this._radiusTransition=k.CreateAnimation("radius",k.ANIMATIONTYPE_FLOAT,60,r.EasingFunction)),(P=k.TransitionTo("radius",O,this._attachedCamera,this._attachedCamera.getScene(),60,this._radiusTransition,this._framingTime,function(){a.stopAllAnimations(),i&&i(),a._attachedCamera&&a._attachedCamera.useInputToRestoreState&&a._attachedCamera.storeState()}))&&this._animatables.push(P)}},r.prototype._calculateLowerRadiusFromModelBoundingSphere=function(t,e){var n=e.subtract(t).length(),i=this._getFrustumSlope(),o=.5*n*this._radiusScale,a=o*Math.sqrt(1+1/(i.x*i.x)),s=o*Math.sqrt(1+1/(i.y*i.y)),d=Math.max(a,s),p=this._attachedCamera;return p?(p.lowerRadiusLimit&&this._mode===r.IgnoreBoundsSizeMode&&(d=d<p.lowerRadiusLimit?p.lowerRadiusLimit:d),p.upperRadiusLimit&&(d=d>p.upperRadiusLimit?p.upperRadiusLimit:d),d):0},r.prototype._maintainCameraAboveGround=function(){var t=this;if(!(this._elevationReturnTime<0)){var e=be.a.Now-this._lastInteractionTime,n=.5*Math.PI-this._defaultElevation,i=.5*Math.PI;if(this._attachedCamera&&!this._betaIsAnimating&&this._attachedCamera.beta>i&&e>=this._elevationReturnWaitTime){this._betaIsAnimating=!0,this.stopAllAnimations(),this._betaTransition||(this._betaTransition=k.CreateAnimation("beta",k.ANIMATIONTYPE_FLOAT,60,r.EasingFunction));var o=k.TransitionTo("beta",n,this._attachedCamera,this._attachedCamera.getScene(),60,this._betaTransition,this._elevationReturnTime,function(){t._clearAnimationLocks(),t.stopAllAnimations()});o&&this._animatables.push(o)}}},r.prototype._getFrustumSlope=function(){var t=this._attachedCamera;if(!t)return u.d.Zero();var e=t.getScene().getEngine().getAspectRatio(t),n=Math.tan(t.fov/2),i=n*e;return new u.d(i,n)},r.prototype._clearAnimationLocks=function(){this._betaIsAnimating=!1},r.prototype._applyUserInteraction=function(){this.isUserIsMoving&&(this._lastInteractionTime=be.a.Now,this.stopAllAnimations(),this._clearAnimationLocks())},r.prototype.stopAllAnimations=function(){for(this._attachedCamera&&(this._attachedCamera.animations=[]);this._animatables.length;)this._animatables[0]&&(this._animatables[0].onAnimationEnd=null,this._animatables[0].stop()),this._animatables.shift()},Object.defineProperty(r.prototype,"isUserIsMoving",{get:function(){return!!this._attachedCamera&&(this._attachedCamera.inertialAlphaOffset!==0||this._attachedCamera.inertialBetaOffset!==0||this._attachedCamera.inertialRadiusOffset!==0||this._attachedCamera.inertialPanningX!==0||this._attachedCamera.inertialPanningY!==0||this._isPointerDown)},enumerable:!1,configurable:!0}),r.EasingFunction=new St,r.EasingMode=Ge.EASINGMODE_EASEINOUT,r.IgnoreBoundsSizeMode=0,r.FitFrustumSidesMode=1,r}(),fr=function(r,t,e,n){t===void 0&&(t=new u.e),e===void 0&&(e=0),n===void 0&&(n=!1),this.direction=r,this.rotatedDirection=t,this.diff=e,this.ignore=n},Lf=function(){function r(t){this.ui=t,this.name="AttachToBoxBehavior",this.distanceAwayFromFace=.15,this.distanceAwayFromBottomOfFace=.15,this._faceVectors=[new fr(u.e.Up()),new fr(u.e.Down()),new fr(u.e.Left()),new fr(u.e.Right()),new fr(u.e.Forward()),new fr(u.e.Forward().scaleInPlace(-1))],this._tmpMatrix=new u.a,this._tmpVector=new u.e,this._zeroVector=u.e.Zero(),this._lookAtTmpMatrix=new u.a}return r.prototype.init=function(){},r.prototype._closestFace=function(t){var e=this;return this._faceVectors.forEach(function(n){e._target.rotationQuaternion||(e._target.rotationQuaternion=u.b.RotationYawPitchRoll(e._target.rotation.y,e._target.rotation.x,e._target.rotation.z)),e._target.rotationQuaternion.toRotationMatrix(e._tmpMatrix),u.e.TransformCoordinatesToRef(n.direction,e._tmpMatrix,n.rotatedDirection),n.diff=u.e.GetAngleBetweenVectors(n.rotatedDirection,t,u.e.Cross(n.rotatedDirection,t))}),this._faceVectors.reduce(function(n,i){return n.ignore?i:i.ignore||n.diff<i.diff?n:i},this._faceVectors[0])},r.prototype._lookAtToRef=function(t,e,n){e===void 0&&(e=new u.e(0,1,0)),u.a.LookAtLHToRef(this._zeroVector,t,e,this._lookAtTmpMatrix),this._lookAtTmpMatrix.invert(),u.b.FromRotationMatrixToRef(this._lookAtTmpMatrix,n)},r.prototype.attach=function(t){var e=this;this._target=t,this._scene=this._target.getScene(),this._onRenderObserver=this._scene.onBeforeRenderObservable.add(function(){if(e._scene.activeCamera){var n=e._scene.activeCamera.position;e._scene.activeCamera.devicePosition&&(n=e._scene.activeCamera.devicePosition);var i=e._closestFace(n.subtract(t.position));e._scene.activeCamera.leftCamera?e._scene.activeCamera.leftCamera.computeWorldMatrix().getRotationMatrixToRef(e._tmpMatrix):e._scene.activeCamera.computeWorldMatrix().getRotationMatrixToRef(e._tmpMatrix),u.e.TransformCoordinatesToRef(u.e.Up(),e._tmpMatrix,e._tmpVector),e._faceVectors.forEach(function(a){i.direction.x&&a.direction.x&&(a.ignore=!0),i.direction.y&&a.direction.y&&(a.ignore=!0),i.direction.z&&a.direction.z&&(a.ignore=!0)});var o=e._closestFace(e._tmpVector);e._faceVectors.forEach(function(a){a.ignore=!1}),e.ui.position.copyFrom(t.position),i.direction.x&&(i.rotatedDirection.scaleToRef(t.scaling.x/2+e.distanceAwayFromFace,e._tmpVector),e.ui.position.addInPlace(e._tmpVector)),i.direction.y&&(i.rotatedDirection.scaleToRef(t.scaling.y/2+e.distanceAwayFromFace,e._tmpVector),e.ui.position.addInPlace(e._tmpVector)),i.direction.z&&(i.rotatedDirection.scaleToRef(t.scaling.z/2+e.distanceAwayFromFace,e._tmpVector),e.ui.position.addInPlace(e._tmpVector)),e.ui.rotationQuaternion||(e.ui.rotationQuaternion=u.b.RotationYawPitchRoll(e.ui.rotation.y,e.ui.rotation.x,e.ui.rotation.z)),i.rotatedDirection.scaleToRef(-1,e._tmpVector),e._lookAtToRef(e._tmpVector,o.rotatedDirection,e.ui.rotationQuaternion),o.direction.x&&e.ui.up.scaleToRef(e.distanceAwayFromBottomOfFace-t.scaling.x/2,e._tmpVector),o.direction.y&&e.ui.up.scaleToRef(e.distanceAwayFromBottomOfFace-t.scaling.y/2,e._tmpVector),o.direction.z&&e.ui.up.scaleToRef(e.distanceAwayFromBottomOfFace-t.scaling.z/2,e._tmpVector),e.ui.position.addInPlace(e._tmpVector)}})},r.prototype.detach=function(){this._scene.onBeforeRenderObservable.remove(this._onRenderObserver)},r}(),Nf=function(){function r(){var t=this;this.delay=0,this.fadeInTime=300,this._millisecondsPerFrame=1e3/60,this._hovered=!1,this._hoverValue=0,this._ownerNode=null,this._update=function(){if(t._ownerNode){if(t._hoverValue+=t._hovered?t._millisecondsPerFrame:-t._millisecondsPerFrame,t._setAllVisibility(t._ownerNode,(t._hoverValue-t.delay)/t.fadeInTime),t._ownerNode.visibility>1)return t._setAllVisibility(t._ownerNode,1),void(t._hoverValue=t.fadeInTime+t.delay);if(t._ownerNode.visibility<0&&(t._setAllVisibility(t._ownerNode,0),t._hoverValue<0))return void(t._hoverValue=0);setTimeout(t._update,t._millisecondsPerFrame)}}}return Object.defineProperty(r.prototype,"name",{get:function(){return"FadeInOut"},enumerable:!1,configurable:!0}),r.prototype.init=function(){},r.prototype.attach=function(t){this._ownerNode=t,this._setAllVisibility(this._ownerNode,0)},r.prototype.detach=function(){this._ownerNode=null},r.prototype.fadeIn=function(t){this._hovered=t,this._update()},r.prototype._setAllVisibility=function(t,e){var n=this;t.visibility=e,t.getChildMeshes().forEach(function(i){n._setAllVisibility(i,e)})},r}(),yi=f(65),wf=function(){function r(){this._startDistance=0,this._initialScale=new u.e(0,0,0),this._targetScale=new u.e(0,0,0),this._sceneRenderObserver=null,this._dragBehaviorA=new yi.a({}),this._dragBehaviorA.moveAttached=!1,this._dragBehaviorB=new yi.a({}),this._dragBehaviorB.moveAttached=!1}return Object.defineProperty(r.prototype,"name",{get:function(){return"MultiPointerScale"},enumerable:!1,configurable:!0}),r.prototype.init=function(){},r.prototype._getCurrentDistance=function(){return this._dragBehaviorA.lastDragPosition.subtract(this._dragBehaviorB.lastDragPosition).length()},r.prototype.attach=function(t){var e=this;this._ownerNode=t,this._dragBehaviorA.onDragStartObservable.add(function(n){e._dragBehaviorA.dragging&&e._dragBehaviorB.dragging&&(e._dragBehaviorA.currentDraggingPointerID==e._dragBehaviorB.currentDraggingPointerID?e._dragBehaviorA.releaseDrag():(e._initialScale.copyFrom(t.scaling),e._startDistance=e._getCurrentDistance()))}),this._dragBehaviorB.onDragStartObservable.add(function(n){e._dragBehaviorA.dragging&&e._dragBehaviorB.dragging&&(e._dragBehaviorA.currentDraggingPointerID==e._dragBehaviorB.currentDraggingPointerID?e._dragBehaviorB.releaseDrag():(e._initialScale.copyFrom(t.scaling),e._startDistance=e._getCurrentDistance()))}),[this._dragBehaviorA,this._dragBehaviorB].forEach(function(n){n.onDragObservable.add(function(){if(e._dragBehaviorA.dragging&&e._dragBehaviorB.dragging){var i=e._getCurrentDistance()/e._startDistance;e._initialScale.scaleToRef(i,e._targetScale)}})}),t.addBehavior(this._dragBehaviorA),t.addBehavior(this._dragBehaviorB),this._sceneRenderObserver=t.getScene().onBeforeRenderObservable.add(function(){if(e._dragBehaviorA.dragging&&e._dragBehaviorB.dragging){var n=e._targetScale.subtract(t.scaling).scaleInPlace(.1);n.length()>.01&&t.scaling.addInPlace(n)}})},r.prototype.detach=function(){var t=this;this._ownerNode.getScene().onBeforeRenderObservable.remove(this._sceneRenderObserver),[this._dragBehaviorA,this._dragBehaviorB].forEach(function(e){e.onDragStartObservable.clear(),e.onDragObservable.clear(),t._ownerNode.removeBehavior(e)})},r}(),Dt=f(31),gt=f(24),kn=f(60),gl=function(){function r(){this._sceneRenderObserver=null,this._targetPosition=new u.e(0,0,0),this._moving=!1,this._startingOrientation=new u.b,this._attachedToElement=!1,this.zDragFactor=3,this.rotateDraggedObject=!0,this.dragging=!1,this.dragDeltaRatio=.2,this.currentDraggingPointerID=-1,this.detachCameraControls=!0,this.onDragStartObservable=new C.c,this.onDragObservable=new C.c,this.onDragEndObservable=new C.c}return Object.defineProperty(r.prototype,"name",{get:function(){return"SixDofDrag"},enumerable:!1,configurable:!0}),r.prototype.init=function(){},Object.defineProperty(r.prototype,"_pointerCamera",{get:function(){return this._scene.cameraToUseForPointers?this._scene.cameraToUseForPointers:this._scene.activeCamera},enumerable:!1,configurable:!0}),r.prototype.attach=function(t){var e=this;this._ownerNode=t,this._scene=this._ownerNode.getScene(),r._virtualScene||(r._virtualScene=new _e.a(this._scene.getEngine(),{virtual:!0}),r._virtualScene.detachControl(),this._scene.getEngine().scenes.pop());var n=null,i=new u.e(0,0,0);this._virtualOriginMesh=new Dt.a("",r._virtualScene),this._virtualOriginMesh.rotationQuaternion=new u.b,this._virtualDragMesh=new Dt.a("",r._virtualScene),this._virtualDragMesh.rotationQuaternion=new u.b,this._pointerObserver=this._scene.onPointerObservable.add(function(a,s){if(a.type==Tt.a.POINTERDOWN){if(!e.dragging&&a.pickInfo&&a.pickInfo.hit&&a.pickInfo.pickedMesh&&a.pickInfo.ray&&(O=a.pickInfo.pickedMesh,e._ownerNode==O||O.isDescendantOf(e._ownerNode))){e._pointerCamera&&e._pointerCamera.cameraRigMode==gt.a.RIG_MODE_NONE&&a.pickInfo.ray.origin.copyFrom(e._pointerCamera.globalPosition),n=e._ownerNode,kn.a._RemoveAndStorePivotPoint(n),i.copyFrom(a.pickInfo.ray.origin),e._virtualOriginMesh.position.copyFrom(a.pickInfo.ray.origin),e._virtualOriginMesh.lookAt(a.pickInfo.ray.origin.add(a.pickInfo.ray.direction)),e._virtualOriginMesh.removeChild(e._virtualDragMesh),n.computeWorldMatrix(),e._virtualDragMesh.position.copyFrom(n.absolutePosition),n.rotationQuaternion||(n.rotationQuaternion=u.b.RotationYawPitchRoll(n.rotation.y,n.rotation.x,n.rotation.z));var d=n.parent;n.setParent(null),e._virtualDragMesh.rotationQuaternion.copyFrom(n.rotationQuaternion),n.setParent(d),e._virtualOriginMesh.addChild(e._virtualDragMesh),e._targetPosition.copyFrom(e._virtualDragMesh.absolutePosition),e.dragging=!0,e.currentDraggingPointerID=a.event.pointerId,e.detachCameraControls&&e._pointerCamera&&!e._pointerCamera.leftCamera&&(e._pointerCamera.inputs.attachedToElement?(e._pointerCamera.detachControl(),e._attachedToElement=!0):e._attachedToElement=!1),kn.a._RestorePivotPoint(n),e.onDragStartObservable.notifyObservers({})}}else if(a.type==Tt.a.POINTERUP||a.type==Tt.a.POINTERDOUBLETAP)e.currentDraggingPointerID==a.event.pointerId&&(e.dragging=!1,e._moving=!1,e.currentDraggingPointerID=-1,n=null,e._virtualOriginMesh.removeChild(e._virtualDragMesh),e.detachCameraControls&&e._attachedToElement&&e._pointerCamera&&!e._pointerCamera.leftCamera&&(e._pointerCamera.attachControl(!0),e._attachedToElement=!1),e.onDragEndObservable.notifyObservers({}));else if(a.type==Tt.a.POINTERMOVE&&e.currentDraggingPointerID==a.event.pointerId&&e.dragging&&a.pickInfo&&a.pickInfo.ray&&n){var p=e.zDragFactor;e._pointerCamera&&e._pointerCamera.cameraRigMode==gt.a.RIG_MODE_NONE&&(a.pickInfo.ray.origin.copyFrom(e._pointerCamera.globalPosition),p=0);var b=a.pickInfo.ray.origin.subtract(i);i.copyFrom(a.pickInfo.ray.origin);var P=-u.e.Dot(b,a.pickInfo.ray.direction);e._virtualOriginMesh.addChild(e._virtualDragMesh),e._virtualDragMesh.position.z-=e._virtualDragMesh.position.z<1?P*e.zDragFactor:P*p*e._virtualDragMesh.position.z,e._virtualDragMesh.position.z<0&&(e._virtualDragMesh.position.z=0),e._virtualOriginMesh.position.copyFrom(a.pickInfo.ray.origin),e._virtualOriginMesh.lookAt(a.pickInfo.ray.origin.add(a.pickInfo.ray.direction)),e._virtualOriginMesh.removeChild(e._virtualDragMesh),e._targetPosition.copyFrom(e._virtualDragMesh.absolutePosition),n.parent&&u.e.TransformCoordinatesToRef(e._targetPosition,u.a.Invert(n.parent.getWorldMatrix()),e._targetPosition),e._moving||e._startingOrientation.copyFrom(e._virtualDragMesh.rotationQuaternion),e._moving=!0}var O});var o=new u.b;this._sceneRenderObserver=t.getScene().onBeforeRenderObservable.add(function(){if(e.dragging&&e._moving&&n){if(kn.a._RemoveAndStorePivotPoint(n),n.position.addInPlace(e._targetPosition.subtract(n.position).scale(e.dragDeltaRatio)),e.rotateDraggedObject){o.copyFrom(e._startingOrientation),o.x=-o.x,o.y=-o.y,o.z=-o.z,e._virtualDragMesh.rotationQuaternion.multiplyToRef(o,o),u.b.RotationYawPitchRollToRef(o.toEulerAngles("xyz").y,0,0,o),o.multiplyToRef(e._startingOrientation,o);var a=n.parent;(!a||a.scaling&&!a.scaling.isNonUniformWithinEpsilon(.001))&&(n.setParent(null),u.b.SlerpToRef(n.rotationQuaternion,o,e.dragDeltaRatio,n.rotationQuaternion),n.setParent(a))}kn.a._RestorePivotPoint(n),e.onDragObservable.notifyObservers()}})},r.prototype.detach=function(){this._scene&&(this.detachCameraControls&&this._attachedToElement&&this._pointerCamera&&!this._pointerCamera.leftCamera&&(this._pointerCamera.attachControl(!0),this._attachedToElement=!1),this._scene.onPointerObservable.remove(this._pointerObserver)),this._ownerNode&&this._ownerNode.getScene().onBeforeRenderObservable.remove(this._sceneRenderObserver),this._virtualOriginMesh&&this._virtualOriginMesh.dispose(),this._virtualDragMesh&&this._virtualDragMesh.dispose(),this.onDragEndObservable.clear(),this.onDragObservable.clear(),this.onDragStartObservable.clear()},r}(),Ff=function(){function r(t,e,n){if(this.targetPosition=u.e.Zero(),this.poleTargetPosition=u.e.Zero(),this.poleTargetLocalOffset=u.e.Zero(),this.poleAngle=0,this.slerpAmount=1,this._bone1Quat=u.b.Identity(),this._bone1Mat=u.a.Identity(),this._bone2Ang=Math.PI,this._maxAngle=Math.PI,this._rightHandedSystem=!1,this._bendAxis=u.e.Right(),this._slerping=!1,this._adjustRoll=0,this._bone2=e,this._bone1=e.getParent(),this._bone1){this.mesh=t;var i=e.getPosition();if(e.getAbsoluteTransform().determinant()>0&&(this._rightHandedSystem=!0,this._bendAxis.x=0,this._bendAxis.y=0,this._bendAxis.z=-1,i.x>i.y&&i.x>i.z&&(this._adjustRoll=.5*Math.PI,this._bendAxis.z=1)),this._bone1.length){var o=this._bone1.getScale(),a=this._bone2.getScale();this._bone1Length=this._bone1.length*o.y*this.mesh.scaling.y,this._bone2Length=this._bone2.length*a.y*this.mesh.scaling.y}else if(this._bone1.children[0]){t.computeWorldMatrix(!0);var s=this._bone2.children[0].getAbsolutePosition(t),d=this._bone2.getAbsolutePosition(t),p=this._bone1.getAbsolutePosition(t);this._bone1Length=u.e.Distance(s,d),this._bone2Length=u.e.Distance(d,p)}this._bone1.getRotationMatrixToRef(ye.c.WORLD,t,this._bone1Mat),this.maxAngle=Math.PI,n&&(n.targetMesh&&(this.targetMesh=n.targetMesh,this.targetMesh.computeWorldMatrix(!0)),n.poleTargetMesh?(this.poleTargetMesh=n.poleTargetMesh,this.poleTargetMesh.computeWorldMatrix(!0)):n.poleTargetBone?this.poleTargetBone=n.poleTargetBone:this._bone1.getParent()&&(this.poleTargetBone=this._bone1.getParent()),n.poleTargetLocalOffset&&this.poleTargetLocalOffset.copyFrom(n.poleTargetLocalOffset),n.poleAngle&&(this.poleAngle=n.poleAngle),n.bendAxis&&this._bendAxis.copyFrom(n.bendAxis),n.maxAngle&&(this.maxAngle=n.maxAngle),n.slerpAmount&&(this.slerpAmount=n.slerpAmount))}}return Object.defineProperty(r.prototype,"maxAngle",{get:function(){return this._maxAngle},set:function(t){this._setMaxAngle(t)},enumerable:!1,configurable:!0}),r.prototype._setMaxAngle=function(t){t<0&&(t=0),(t>Math.PI||t==null)&&(t=Math.PI),this._maxAngle=t;var e=this._bone1Length,n=this._bone2Length;this._maxReach=Math.sqrt(e*e+n*n-2*e*n*Math.cos(t))},r.prototype.update=function(){var t=this._bone1;if(t){var e=this.targetPosition,n=this.poleTargetPosition,i=r._tmpMats[0],o=r._tmpMats[1];this.targetMesh&&e.copyFrom(this.targetMesh.getAbsolutePosition()),this.poleTargetBone?this.poleTargetBone.getAbsolutePositionFromLocalToRef(this.poleTargetLocalOffset,this.mesh,n):this.poleTargetMesh&&u.e.TransformCoordinatesToRef(this.poleTargetLocalOffset,this.poleTargetMesh.getWorldMatrix(),n);var a=r._tmpVecs[0],s=r._tmpVecs[1],d=r._tmpVecs[2],p=r._tmpVecs[3],b=r._tmpVecs[4],P=r._tmpQuat;t.getAbsolutePositionToRef(this.mesh,a),n.subtractToRef(a,b),b.x==0&&b.y==0&&b.z==0?b.y=1:b.normalize(),e.subtractToRef(a,p),p.normalize(),u.e.CrossToRef(p,b,s),s.normalize(),u.e.CrossToRef(p,s,d),d.normalize(),u.a.FromXYZAxesToRef(d,p,s,i);var O=this._bone1Length,B=this._bone2Length,F=u.e.Distance(a,e);this._maxReach>0&&(F=Math.min(this._maxReach,F));var z=(B*B+F*F-O*O)/(2*B*F),J=(F*F+O*O-B*B)/(2*F*O);z>1&&(z=1),J>1&&(J=1),z<-1&&(z=-1),J<-1&&(J=-1);var ie=Math.acos(z),se=Math.acos(J),ce=-ie-se;if(this._rightHandedSystem)u.a.RotationYawPitchRollToRef(0,0,this._adjustRoll,o),o.multiplyToRef(i,i),u.a.RotationAxisToRef(this._bendAxis,se,o),o.multiplyToRef(i,i);else{var ue=r._tmpVecs[5];ue.copyFrom(this._bendAxis),ue.x*=-1,u.a.RotationAxisToRef(ue,-se,o),o.multiplyToRef(i,i)}this.poleAngle&&(u.a.RotationAxisToRef(p,this.poleAngle,o),i.multiplyToRef(o,i)),this._bone1&&(this.slerpAmount<1?(this._slerping||u.b.FromRotationMatrixToRef(this._bone1Mat,this._bone1Quat),u.b.FromRotationMatrixToRef(i,P),u.b.SlerpToRef(this._bone1Quat,P,this.slerpAmount,this._bone1Quat),ce=this._bone2Ang*(1-this.slerpAmount)+ce*this.slerpAmount,this._bone1.setRotationQuaternion(this._bone1Quat,ye.c.WORLD,this.mesh),this._slerping=!0):(this._bone1.setRotationMatrix(i,ye.c.WORLD,this.mesh),this._bone1Mat.copyFrom(i),this._slerping=!1)),this._bone2.setAxisAngle(this._bendAxis,ce,ye.c.LOCAL),this._bone2Ang=ce}},r._tmpVecs=[u.e.Zero(),u.e.Zero(),u.e.Zero(),u.e.Zero(),u.e.Zero(),u.e.Zero()],r._tmpQuat=u.b.Identity(),r._tmpMats=[u.a.Identity(),u.a.Identity()],r}(),Bf=function(){function r(t,e,n,i){if(this.upAxis=u.e.Up(),this.upAxisSpace=ye.c.LOCAL,this.adjustYaw=0,this.adjustPitch=0,this.adjustRoll=0,this.slerpAmount=1,this._boneQuat=u.b.Identity(),this._slerping=!1,this._firstFrameSkipped=!1,this._fowardAxis=u.e.Forward(),this.mesh=t,this.bone=e,this.target=n,i&&(i.adjustYaw&&(this.adjustYaw=i.adjustYaw),i.adjustPitch&&(this.adjustPitch=i.adjustPitch),i.adjustRoll&&(this.adjustRoll=i.adjustRoll),i.maxYaw!=null?this.maxYaw=i.maxYaw:this.maxYaw=Math.PI,i.minYaw!=null?this.minYaw=i.minYaw:this.minYaw=-Math.PI,i.maxPitch!=null?this.maxPitch=i.maxPitch:this.maxPitch=Math.PI,i.minPitch!=null?this.minPitch=i.minPitch:this.minPitch=-Math.PI,i.slerpAmount!=null&&(this.slerpAmount=i.slerpAmount),i.upAxis!=null&&(this.upAxis=i.upAxis),i.upAxisSpace!=null&&(this.upAxisSpace=i.upAxisSpace),i.yawAxis!=null||i.pitchAxis!=null)){var o=ye.a.Y,a=ye.a.X;i.yawAxis!=null&&(o=i.yawAxis.clone()).normalize(),i.pitchAxis!=null&&(a=i.pitchAxis.clone()).normalize();var s=u.e.Cross(a,o);this._transformYawPitch=u.a.Identity(),u.a.FromXYZAxesToRef(a,o,s,this._transformYawPitch),this._transformYawPitchInv=this._transformYawPitch.clone(),this._transformYawPitch.invert()}e.getParent()||this.upAxisSpace!=ye.c.BONE||(this.upAxisSpace=ye.c.LOCAL)}return Object.defineProperty(r.prototype,"minYaw",{get:function(){return this._minYaw},set:function(t){this._minYaw=t,this._minYawSin=Math.sin(t),this._minYawCos=Math.cos(t),this._maxYaw!=null&&(this._midYawConstraint=.5*this._getAngleDiff(this._minYaw,this._maxYaw)+this._minYaw,this._yawRange=this._maxYaw-this._minYaw)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"maxYaw",{get:function(){return this._maxYaw},set:function(t){this._maxYaw=t,this._maxYawSin=Math.sin(t),this._maxYawCos=Math.cos(t),this._minYaw!=null&&(this._midYawConstraint=.5*this._getAngleDiff(this._minYaw,this._maxYaw)+this._minYaw,this._yawRange=this._maxYaw-this._minYaw)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"minPitch",{get:function(){return this._minPitch},set:function(t){this._minPitch=t,this._minPitchTan=Math.tan(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"maxPitch",{get:function(){return this._maxPitch},set:function(t){this._maxPitch=t,this._maxPitchTan=Math.tan(t)},enumerable:!1,configurable:!0}),r.prototype.update=function(){if(this.slerpAmount<1&&!this._firstFrameSkipped)this._firstFrameSkipped=!0;else{var t=this.bone,e=r._tmpVecs[0];t.getAbsolutePositionToRef(this.mesh,e);var n=this.target,i=r._tmpMats[0],o=r._tmpMats[1],a=this.mesh,s=t.getParent(),d=r._tmpVecs[1];d.copyFrom(this.upAxis),this.upAxisSpace==ye.c.BONE&&s?(this._transformYawPitch&&u.e.TransformCoordinatesToRef(d,this._transformYawPitchInv,d),s.getDirectionToRef(d,this.mesh,d)):this.upAxisSpace==ye.c.LOCAL&&(a.getDirectionToRef(d,d),a.scaling.x==1&&a.scaling.y==1&&a.scaling.z==1||d.normalize());var p=!1,b=!1;if(this._maxYaw==Math.PI&&this._minYaw==-Math.PI||(p=!0),this._maxPitch==Math.PI&&this._minPitch==-Math.PI||(b=!0),p||b){var P=r._tmpMats[2],O=r._tmpMats[3];if(this.upAxisSpace==ye.c.BONE&&d.y==1&&s)s.getRotationMatrixToRef(ye.c.WORLD,this.mesh,P);else if(this.upAxisSpace!=ye.c.LOCAL||d.y!=1||s){(F=r._tmpVecs[2]).copyFrom(this._fowardAxis),this._transformYawPitch&&u.e.TransformCoordinatesToRef(F,this._transformYawPitchInv,F),s?s.getDirectionToRef(F,this.mesh,F):a.getDirectionToRef(F,F);var B=u.e.Cross(d,F);B.normalize();var F=u.e.Cross(B,d);u.a.FromXYZAxesToRef(B,d,F,P)}else P.copyFrom(a.getWorldMatrix());P.invertToRef(O);var z=null;if(b){var J=r._tmpVecs[3];n.subtractToRef(e,J),u.e.TransformCoordinatesToRef(J,O,J),z=Math.sqrt(J.x*J.x+J.z*J.z);var ie=Math.atan2(J.y,z),se=ie;ie>this._maxPitch?(J.y=this._maxPitchTan*z,se=this._maxPitch):ie<this._minPitch&&(J.y=this._minPitchTan*z,se=this._minPitch),ie!=se&&(u.e.TransformCoordinatesToRef(J,P,J),J.addInPlace(e),n=J)}if(p){J=r._tmpVecs[4],n.subtractToRef(e,J),u.e.TransformCoordinatesToRef(J,O,J);var ce=Math.atan2(J.x,J.z),ue=ce;if((ce>this._maxYaw||ce<this._minYaw)&&(z==null&&(z=Math.sqrt(J.x*J.x+J.z*J.z)),this._yawRange>Math.PI?this._isAngleBetween(ce,this._maxYaw,this._midYawConstraint)?(J.z=this._maxYawCos*z,J.x=this._maxYawSin*z,ue=this._maxYaw):this._isAngleBetween(ce,this._midYawConstraint,this._minYaw)&&(J.z=this._minYawCos*z,J.x=this._minYawSin*z,ue=this._minYaw):ce>this._maxYaw?(J.z=this._maxYawCos*z,J.x=this._maxYawSin*z,ue=this._maxYaw):ce<this._minYaw&&(J.z=this._minYawCos*z,J.x=this._minYawSin*z,ue=this._minYaw)),this._slerping&&this._yawRange>Math.PI){var fe=r._tmpVecs[8];fe.copyFrom(ye.a.Z),this._transformYawPitch&&u.e.TransformCoordinatesToRef(fe,this._transformYawPitchInv,fe);var ve=r._tmpMats[4];this._boneQuat.toRotationMatrix(ve),this.mesh.getWorldMatrix().multiplyToRef(ve,ve),u.e.TransformCoordinatesToRef(fe,ve,fe),u.e.TransformCoordinatesToRef(fe,O,fe);var Te=Math.atan2(fe.x,fe.z);if(this._getAngleBetween(Te,ce)>this._getAngleBetween(Te,this._midYawConstraint)){z==null&&(z=Math.sqrt(J.x*J.x+J.z*J.z));var Re=this._getAngleBetween(Te,this._maxYaw);this._getAngleBetween(Te,this._minYaw)<Re?(ue=Te+.75*Math.PI,J.z=Math.cos(ue)*z,J.x=Math.sin(ue)*z):(ue=Te-.75*Math.PI,J.z=Math.cos(ue)*z,J.x=Math.sin(ue)*z)}}ce!=ue&&(u.e.TransformCoordinatesToRef(J,P,J),J.addInPlace(e),n=J)}}var Ae=r._tmpVecs[5],Ee=r._tmpVecs[6],Se=r._tmpVecs[7],Le=r._tmpQuat;n.subtractToRef(e,Ae),Ae.normalize(),u.e.CrossToRef(d,Ae,Ee),Ee.normalize(),u.e.CrossToRef(Ae,Ee,Se),Se.normalize(),u.a.FromXYZAxesToRef(Ee,Se,Ae,i),Ee.x===0&&Ee.y===0&&Ee.z===0||Se.x===0&&Se.y===0&&Se.z===0||Ae.x===0&&Ae.y===0&&Ae.z===0||((this.adjustYaw||this.adjustPitch||this.adjustRoll)&&(u.a.RotationYawPitchRollToRef(this.adjustYaw,this.adjustPitch,this.adjustRoll,o),o.multiplyToRef(i,i)),this.slerpAmount<1?(this._slerping||this.bone.getRotationQuaternionToRef(ye.c.WORLD,this.mesh,this._boneQuat),this._transformYawPitch&&this._transformYawPitch.multiplyToRef(i,i),u.b.FromRotationMatrixToRef(i,Le),u.b.SlerpToRef(this._boneQuat,Le,this.slerpAmount,this._boneQuat),this.bone.setRotationQuaternion(this._boneQuat,ye.c.WORLD,this.mesh),this._slerping=!0):(this._transformYawPitch&&this._transformYawPitch.multiplyToRef(i,i),this.bone.setRotationMatrix(i,ye.c.WORLD,this.mesh),this._slerping=!1))}},r.prototype._getAngleDiff=function(t,e){var n=e-t;return(n%=2*Math.PI)>Math.PI?n-=2*Math.PI:n<-Math.PI&&(n+=2*Math.PI),n},r.prototype._getAngleBetween=function(t,e){var n=0;return(n=(t=(t%=2*Math.PI)<0?t+2*Math.PI:t)<(e=(e%=2*Math.PI)<0?e+2*Math.PI:e)?e-t:t-e)>Math.PI&&(n=2*Math.PI-n),n},r.prototype._isAngleBetween=function(t,e,n){if(t=(t%=2*Math.PI)<0?t+2*Math.PI:t,(e=(e%=2*Math.PI)<0?e+2*Math.PI:e)<(n=(n%=2*Math.PI)<0?n+2*Math.PI:n)){if(t>e&&t<n)return!0}else if(t>n&&t<e)return!0;return!1},r._tmpVecs=Pe.a.BuildArray(10,u.e.Zero),r._tmpQuat=u.b.Identity(),r._tmpMats=Pe.a.BuildArray(5,u.a.Identity),r}(),we=f(10),Ct=f(27),Bt=f(26);function vl(r,t,e,n){var i;i=n===h.a.TEXTURETYPE_FLOAT?new Float32Array(t*e*4):new Uint32Array(t*e*4);for(var o=0;o<t;o++)for(var a=0;a<e;a++){var s=3*(a*t+o),d=4*(a*t+o);i[d+0]=r[s+0],i[d+1]=r[s+1],i[d+2]=r[s+2],i[d+3]=1}return i}function bl(r){return function(t,e,n,i,o,a,s,d,p,b){p===void 0&&(p=null),b===void 0&&(b=h.a.TEXTURETYPE_UNSIGNED_INT);var P=r?this._gl.TEXTURE_3D:this._gl.TEXTURE_2D_ARRAY,O=r?Ct.b.Raw3D:Ct.b.Raw2DArray,B=new Ct.a(this,O);B.baseWidth=e,B.baseHeight=n,B.baseDepth=i,B.width=e,B.height=n,B.depth=i,B.format=o,B.type=b,B.generateMipMaps=a,B.samplingMode=d,r?B.is3D=!0:B.is2DArray=!0,this._doNotHandleContextLost||(B._bufferView=t),r?this.updateRawTexture3D(B,t,o,s,p,b):this.updateRawTexture2DArray(B,t,o,s,p,b),this._bindTextureDirectly(P,B,!0);var F=this._getSamplingParameters(d,a);return this._gl.texParameteri(P,this._gl.TEXTURE_MAG_FILTER,F.mag),this._gl.texParameteri(P,this._gl.TEXTURE_MIN_FILTER,F.min),a&&this._gl.generateMipmap(P),this._bindTextureDirectly(P,null),this._internalTexturesCache.push(B),B}}function yl(r){return function(t,e,n,i,o,a){o===void 0&&(o=null),a===void 0&&(a=h.a.TEXTURETYPE_UNSIGNED_INT);var s=r?this._gl.TEXTURE_3D:this._gl.TEXTURE_2D_ARRAY,d=this._getWebGLTextureType(a),p=this._getInternalFormat(n),b=this._getRGBABufferInternalSizedFormat(a,n);this._bindTextureDirectly(s,t,!0),this._unpackFlipY(i===void 0||!!i),this._doNotHandleContextLost||(t._bufferView=e,t.format=n,t.invertY=i,t._compression=o),t.width%4!=0&&this._gl.pixelStorei(this._gl.UNPACK_ALIGNMENT,1),o&&e?this._gl.compressedTexImage3D(s,0,this.getCaps().s3tc[o],t.width,t.height,t.depth,0,e):this._gl.texImage3D(s,0,b,t.width,t.height,t.depth,0,p,d,e),t.generateMipMaps&&this._gl.generateMipmap(s),this._bindTextureDirectly(s,null),t.isReady=!0}}Bt.a.prototype.updateRawTexture=function(r,t,e,n,i,o){if(i===void 0&&(i=null),o===void 0&&(o=h.a.TEXTURETYPE_UNSIGNED_INT),r){var a=this._getRGBABufferInternalSizedFormat(o,e),s=this._getInternalFormat(e),d=this._getWebGLTextureType(o);this._bindTextureDirectly(this._gl.TEXTURE_2D,r,!0),this._unpackFlipY(n===void 0||!!n),this._doNotHandleContextLost||(r._bufferView=t,r.format=e,r.type=o,r.invertY=n,r._compression=i),r.width%4!=0&&this._gl.pixelStorei(this._gl.UNPACK_ALIGNMENT,1),i&&t?this._gl.compressedTexImage2D(this._gl.TEXTURE_2D,0,this.getCaps().s3tc[i],r.width,r.height,0,t):this._gl.texImage2D(this._gl.TEXTURE_2D,0,a,r.width,r.height,0,s,d,t),r.generateMipMaps&&this._gl.generateMipmap(this._gl.TEXTURE_2D),this._bindTextureDirectly(this._gl.TEXTURE_2D,null),r.isReady=!0}},Bt.a.prototype.createRawTexture=function(r,t,e,n,i,o,a,s,d){s===void 0&&(s=null),d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT);var p=new Ct.a(this,Ct.b.Raw);p.baseWidth=t,p.baseHeight=e,p.width=t,p.height=e,p.format=n,p.generateMipMaps=i,p.samplingMode=a,p.invertY=o,p._compression=s,p.type=d,this._doNotHandleContextLost||(p._bufferView=r),this.updateRawTexture(p,r,n,o,s,d),this._bindTextureDirectly(this._gl.TEXTURE_2D,p,!0);var b=this._getSamplingParameters(a,i);return this._gl.texParameteri(this._gl.TEXTURE_2D,this._gl.TEXTURE_MAG_FILTER,b.mag),this._gl.texParameteri(this._gl.TEXTURE_2D,this._gl.TEXTURE_MIN_FILTER,b.min),i&&this._gl.generateMipmap(this._gl.TEXTURE_2D),this._bindTextureDirectly(this._gl.TEXTURE_2D,null),this._internalTexturesCache.push(p),p},Bt.a.prototype.createRawCubeTexture=function(r,t,e,n,i,o,a,s){s===void 0&&(s=null);var d=this._gl,p=new Ct.a(this,Ct.b.CubeRaw);p.isCube=!0,p.format=e,p.type=n,this._doNotHandleContextLost||(p._bufferViewArray=r);var b=this._getWebGLTextureType(n),P=this._getInternalFormat(e);P===d.RGB&&(P=d.RGBA),b!==d.FLOAT||this._caps.textureFloatLinearFiltering?b!==this._gl.HALF_FLOAT_OES||this._caps.textureHalfFloatLinearFiltering?b!==d.FLOAT||this._caps.textureFloatRender?b!==d.HALF_FLOAT||this._caps.colorBufferFloat||(i=!1,l.a.Warn("Render to half float textures is not supported. Mipmap generation forced to false.")):(i=!1,l.a.Warn("Render to float textures is not supported. Mipmap generation forced to false.")):(i=!1,a=h.a.TEXTURE_NEAREST_SAMPLINGMODE,l.a.Warn("Half float texture filtering is not supported. Mipmap generation and sampling mode are forced to false and TEXTURE_NEAREST_SAMPLINGMODE, respectively.")):(i=!1,a=h.a.TEXTURE_NEAREST_SAMPLINGMODE,l.a.Warn("Float texture filtering is not supported. Mipmap generation and sampling mode are forced to false and TEXTURE_NEAREST_SAMPLINGMODE, respectively."));var O=t,B=O;p.width=O,p.height=B,!this.needPOTTextures||Xe.b.IsExponentOfTwo(p.width)&&Xe.b.IsExponentOfTwo(p.height)||(i=!1),r&&this.updateRawCubeTexture(p,r,e,n,o,s),this._bindTextureDirectly(this._gl.TEXTURE_CUBE_MAP,p,!0),r&&i&&this._gl.generateMipmap(this._gl.TEXTURE_CUBE_MAP);var F=this._getSamplingParameters(a,i);return d.texParameteri(d.TEXTURE_CUBE_MAP,d.TEXTURE_MAG_FILTER,F.mag),d.texParameteri(d.TEXTURE_CUBE_MAP,d.TEXTURE_MIN_FILTER,F.min),d.texParameteri(d.TEXTURE_CUBE_MAP,d.TEXTURE_WRAP_S,d.CLAMP_TO_EDGE),d.texParameteri(d.TEXTURE_CUBE_MAP,d.TEXTURE_WRAP_T,d.CLAMP_TO_EDGE),this._bindTextureDirectly(d.TEXTURE_CUBE_MAP,null),p.generateMipMaps=i,p},Bt.a.prototype.updateRawCubeTexture=function(r,t,e,n,i,o,a){o===void 0&&(o=null),a===void 0&&(a=0),r._bufferViewArray=t,r.format=e,r.type=n,r.invertY=i,r._compression=o;var s=this._gl,d=this._getWebGLTextureType(n),p=this._getInternalFormat(e),b=this._getRGBABufferInternalSizedFormat(n),P=!1;p===s.RGB&&(p=s.RGBA,P=!0),this._bindTextureDirectly(s.TEXTURE_CUBE_MAP,r,!0),this._unpackFlipY(i===void 0||!!i),r.width%4!=0&&s.pixelStorei(s.UNPACK_ALIGNMENT,1);for(var O=0;O<6;O++){var B=t[O];o?s.compressedTexImage2D(s.TEXTURE_CUBE_MAP_POSITIVE_X+O,a,this.getCaps().s3tc[o],r.width,r.height,0,B):(P&&(B=vl(B,r.width,r.height,n)),s.texImage2D(s.TEXTURE_CUBE_MAP_POSITIVE_X+O,a,b,r.width,r.height,0,p,d,B))}(!this.needPOTTextures||Xe.b.IsExponentOfTwo(r.width)&&Xe.b.IsExponentOfTwo(r.height))&&r.generateMipMaps&&a===0&&this._gl.generateMipmap(this._gl.TEXTURE_CUBE_MAP),this._bindTextureDirectly(this._gl.TEXTURE_CUBE_MAP,null),r.isReady=!0},Bt.a.prototype.createRawCubeTextureFromUrl=function(r,t,e,n,i,o,a,s,d,p,b,P){var O=this;d===void 0&&(d=null),p===void 0&&(p=null),b===void 0&&(b=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),P===void 0&&(P=!1);var B=this._gl,F=this.createRawCubeTexture(null,e,n,i,!o,P,b,null);return t?._addPendingData(F),F.url=r,this._internalTexturesCache.push(F),this._loadFile(r,function(z){(function(J){var ie=F.width,se=a(J);if(se){if(s){var ce=O._getWebGLTextureType(i),ue=O._getInternalFormat(n),fe=O._getRGBABufferInternalSizedFormat(i),ve=!1;ue===B.RGB&&(ue=B.RGBA,ve=!0),O._bindTextureDirectly(B.TEXTURE_CUBE_MAP,F,!0),O._unpackFlipY(!1);for(var Te=s(se),Re=0;Re<Te.length;Re++)for(var Ae=ie>>Re,Ee=0;Ee<6;Ee++){var Se=Te[Re][Ee];ve&&(Se=vl(Se,Ae,Ae,i)),B.texImage2D(Ee,Re,fe,Ae,Ae,0,ue,ce,Se)}O._bindTextureDirectly(B.TEXTURE_CUBE_MAP,null)}else O.updateRawCubeTexture(F,se,n,i,P);F.isReady=!0,t?._removePendingData(F),d&&d()}})(z)},void 0,t?.offlineProvider,!0,function(z,J){t?._removePendingData(F),p&&z&&p(z.status+" "+z.statusText,J)}),F},Bt.a.prototype.createRawTexture2DArray=bl(!1),Bt.a.prototype.createRawTexture3D=bl(!0),Bt.a.prototype.updateRawTexture2DArray=yl(!1),Bt.a.prototype.updateRawTexture3D=yl(!0);var ni=function(r){function t(e,n,i,o,a,s,d,p,b){s===void 0&&(s=!0),d===void 0&&(d=!1),p===void 0&&(p=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),b===void 0&&(b=h.a.TEXTURETYPE_UNSIGNED_INT);var P=r.call(this,null,a,!s,d)||this;return P.format=o,P._engine&&(P._texture=P._engine.createRawTexture(e,n,i,o,s,d,p,null,b),P.wrapU=we.a.CLAMP_ADDRESSMODE,P.wrapV=we.a.CLAMP_ADDRESSMODE),P}return Object(c.d)(t,r),t.prototype.update=function(e){this._getEngine().updateRawTexture(this._texture,e,this._texture.format,this._texture.invertY,null,this._texture.type)},t.CreateLuminanceTexture=function(e,n,i,o,a,s,d){return a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),new t(e,n,i,h.a.TEXTUREFORMAT_LUMINANCE,o,a,s,d)},t.CreateLuminanceAlphaTexture=function(e,n,i,o,a,s,d){return a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),new t(e,n,i,h.a.TEXTUREFORMAT_LUMINANCE_ALPHA,o,a,s,d)},t.CreateAlphaTexture=function(e,n,i,o,a,s,d){return a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),new t(e,n,i,h.a.TEXTUREFORMAT_ALPHA,o,a,s,d)},t.CreateRGBTexture=function(e,n,i,o,a,s,d,p){return a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT),new t(e,n,i,h.a.TEXTUREFORMAT_RGB,o,a,s,d,p)},t.CreateRGBATexture=function(e,n,i,o,a,s,d,p){return a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT),new t(e,n,i,h.a.TEXTUREFORMAT_RGBA,o,a,s,d,p)},t.CreateRTexture=function(e,n,i,o,a,s,d,p){return a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=we.a.TRILINEAR_SAMPLINGMODE),p===void 0&&(p=h.a.TEXTURETYPE_FLOAT),new t(e,n,i,h.a.TEXTUREFORMAT_R,o,a,s,d,p)},t}(we.a),No=function(){function r(t,e,n){this.name=t,this.id=e,this.bones=new Array,this.needInitialSkinMatrix=!1,this.overrideMesh=null,this._isDirty=!0,this._meshesWithPoseMatrix=new Array,this._identity=u.a.Identity(),this._ranges={},this._lastAbsoluteTransformsUpdateId=-1,this._canUseTextureForBones=!1,this._uniqueId=0,this._numBonesWithLinkedTransformNode=0,this._hasWaitingData=null,this._waitingOverrideMeshId=null,this.doNotSerialize=!1,this._useTextureToStoreBoneMatrices=!0,this._animationPropertiesOverride=null,this.onBeforeComputeObservable=new C.c,this.bones=[],this._scene=n||te.a.LastCreatedScene,this._uniqueId=this._scene.getUniqueId(),this._scene.addSkeleton(this),this._isDirty=!0;var i=this._scene.getEngine().getCaps();this._canUseTextureForBones=i.textureFloat&&i.maxVertexTextureImageUnits>0}return Object.defineProperty(r.prototype,"useTextureToStoreBoneMatrices",{get:function(){return this._useTextureToStoreBoneMatrices},set:function(t){this._useTextureToStoreBoneMatrices=t,this._markAsDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"animationPropertiesOverride",{get:function(){return this._animationPropertiesOverride?this._animationPropertiesOverride:this._scene.animationPropertiesOverride},set:function(t){this._animationPropertiesOverride=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isUsingTextureForMatrices",{get:function(){return this.useTextureToStoreBoneMatrices&&this._canUseTextureForBones},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"uniqueId",{get:function(){return this._uniqueId},enumerable:!1,configurable:!0}),r.prototype.getClassName=function(){return"Skeleton"},r.prototype.getChildren=function(){return this.bones.filter(function(t){return!t.getParent()})},r.prototype.getTransformMatrices=function(t){return this.needInitialSkinMatrix&&t._bonesTransformMatrices?t._bonesTransformMatrices:(this._transformMatrices||this.prepare(),this._transformMatrices)},r.prototype.getTransformMatrixTexture=function(t){return this.needInitialSkinMatrix&&t._transformMatrixTexture?t._transformMatrixTexture:this._transformMatrixTexture},r.prototype.getScene=function(){return this._scene},r.prototype.toString=function(t){var e="Name: "+this.name+", nBones: "+this.bones.length;if(e+=", nAnimationRanges: "+(this._ranges?Object.keys(this._ranges).length:"none"),t){e+=", Ranges: {";var n=!0;for(var i in this._ranges)n&&(e+=", ",n=!1),e+=i;e+="}"}return e},r.prototype.getBoneIndexByName=function(t){for(var e=0,n=this.bones.length;e<n;e++)if(this.bones[e].name===t)return e;return-1},r.prototype.createAnimationRange=function(t,e,n){if(!this._ranges[t]){this._ranges[t]=new G(t,e,n);for(var i=0,o=this.bones.length;i<o;i++)this.bones[i].animations[0]&&this.bones[i].animations[0].createRange(t,e,n)}},r.prototype.deleteAnimationRange=function(t,e){e===void 0&&(e=!0);for(var n=0,i=this.bones.length;n<i;n++)this.bones[n].animations[0]&&this.bones[n].animations[0].deleteRange(t,e);this._ranges[t]=null},r.prototype.getAnimationRange=function(t){return this._ranges[t]||null},r.prototype.getAnimationRanges=function(){var t,e=[];for(t in this._ranges)e.push(this._ranges[t]);return e},r.prototype.copyAnimationRange=function(t,e,n){if(n===void 0&&(n=!1),this._ranges[e]||!t.getAnimationRange(e))return!1;var i,o,a=!0,s=this._getHighestAnimationFrame()+1,d={},p=t.bones;for(o=0,i=p.length;o<i;o++)d[p[o].name]=p[o];this.bones.length!==p.length&&(l.a.Warn("copyAnimationRange: this rig has "+this.bones.length+" bones, while source as "+p.length),a=!1);var b=n&&this.dimensionsAtRest&&t.dimensionsAtRest?this.dimensionsAtRest.divide(t.dimensionsAtRest):null;for(o=0,i=this.bones.length;o<i;o++){var P=this.bones[o].name,O=d[P];O?a=a&&this.bones[o].copyAnimationRange(O,e,s,n,b):(l.a.Warn("copyAnimationRange: not same rig, missing source bone "+P),a=!1)}var B=t.getAnimationRange(e);return B&&(this._ranges[e]=new G(e,B.from+s,B.to+s)),a},r.prototype.returnToRest=function(){for(var t=u.c.Vector3[0],e=u.c.Quaternion[0],n=u.c.Vector3[1],i=0;i<this.bones.length;i++){var o=this.bones[i];o._index!==-1&&(o.returnToRest(),o._linkedTransformNode&&(o.getRestPose().decompose(t,e,n),o._linkedTransformNode.position=n.clone(),o._linkedTransformNode.rotationQuaternion=e.clone(),o._linkedTransformNode.scaling=t.clone()))}},r.prototype._getHighestAnimationFrame=function(){for(var t=0,e=0,n=this.bones.length;e<n;e++)if(this.bones[e].animations[0]){var i=this.bones[e].animations[0].getHighestFrame();t<i&&(t=i)}return t},r.prototype.beginAnimation=function(t,e,n,i){var o=this.getAnimationRange(t);return o?this._scene.beginAnimation(this,o.from,o.to,e,n,i):null},r.MakeAnimationAdditive=function(t,e,n){e===void 0&&(e=0);var i=t.getAnimationRange(n);if(!i)return null;for(var o=t._scene.getAllAnimatablesByTarget(t),a=null,s=0;s<o.length;s++){var d=o[s];if(d.fromFrame===i?.from&&d.toFrame===i?.to){a=d;break}}var p=t.getAnimatables();for(s=0;s<p.length;s++){var b=p[s].animations;if(b)for(var P=0;P<b.length;P++)k.MakeAnimationAdditive(b[P],e,n)}return a&&(a.isAdditive=!0),t},r.prototype._markAsDirty=function(){this._isDirty=!0},r.prototype._registerMeshWithPoseMatrix=function(t){this._meshesWithPoseMatrix.push(t)},r.prototype._unregisterMeshWithPoseMatrix=function(t){var e=this._meshesWithPoseMatrix.indexOf(t);e>-1&&this._meshesWithPoseMatrix.splice(e,1)},r.prototype._computeTransformMatrices=function(t,e){this.onBeforeComputeObservable.notifyObservers(this);for(var n=0;n<this.bones.length;n++){var i=this.bones[n];i._childUpdateId++;var o=i.getParent();if(o?i.getLocalMatrix().multiplyToRef(o.getWorldMatrix(),i.getWorldMatrix()):e?i.getLocalMatrix().multiplyToRef(e,i.getWorldMatrix()):i.getWorldMatrix().copyFrom(i.getLocalMatrix()),i._index!==-1){var a=i._index===null?n:i._index;i.getInvertedAbsoluteTransform().multiplyToArray(i.getWorldMatrix(),t,16*a)}}this._identity.copyToArray(t,16*this.bones.length)},r.prototype.prepare=function(){if(this._numBonesWithLinkedTransformNode>0)for(var t=0,e=this.bones;t<e.length;t++){var n=e[t];n._linkedTransformNode&&(n._linkedTransformNode.computeWorldMatrix(),n._matrix=n._linkedTransformNode._localMatrix,n.markAsDirty())}if(this._isDirty){if(this.needInitialSkinMatrix)for(var i=0;i<this._meshesWithPoseMatrix.length;i++){var o=this._meshesWithPoseMatrix[i],a=o.getPoseMatrix();if(o._bonesTransformMatrices&&o._bonesTransformMatrices.length===16*(this.bones.length+1)||(o._bonesTransformMatrices=new Float32Array(16*(this.bones.length+1))),this._synchronizedWithMesh!==o){this._synchronizedWithMesh=o;for(var s=0;s<this.bones.length;s++){var d=this.bones[s];d.getParent()||(d.getBaseMatrix().multiplyToRef(a,u.c.Matrix[1]),d._updateDifferenceMatrix(u.c.Matrix[1]))}if(this.isUsingTextureForMatrices){var p=4*(this.bones.length+1);o._transformMatrixTexture&&o._transformMatrixTexture.getSize().width===p||(o._transformMatrixTexture&&o._transformMatrixTexture.dispose(),o._transformMatrixTexture=ni.CreateRGBATexture(o._bonesTransformMatrices,4*(this.bones.length+1),1,this._scene,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE,h.a.TEXTURETYPE_FLOAT))}}this._computeTransformMatrices(o._bonesTransformMatrices,a),this.isUsingTextureForMatrices&&o._transformMatrixTexture&&o._transformMatrixTexture.update(o._bonesTransformMatrices)}else this._transformMatrices&&this._transformMatrices.length===16*(this.bones.length+1)||(this._transformMatrices=new Float32Array(16*(this.bones.length+1)),this.isUsingTextureForMatrices&&(this._transformMatrixTexture&&this._transformMatrixTexture.dispose(),this._transformMatrixTexture=ni.CreateRGBATexture(this._transformMatrices,4*(this.bones.length+1),1,this._scene,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE,h.a.TEXTURETYPE_FLOAT))),this._computeTransformMatrices(this._transformMatrices,null),this.isUsingTextureForMatrices&&this._transformMatrixTexture&&this._transformMatrixTexture.update(this._transformMatrices);this._isDirty=!1,this._scene._activeBones.addCount(this.bones.length,!1)}},r.prototype.getAnimatables=function(){if(!this._animatables||this._animatables.length!==this.bones.length){this._animatables=[];for(var t=0;t<this.bones.length;t++)this._animatables.push(this.bones[t])}return this._animatables},r.prototype.clone=function(t,e){var n=new r(t,e||t,this._scene);n.needInitialSkinMatrix=this.needInitialSkinMatrix,n.overrideMesh=this.overrideMesh;for(var i=0;i<this.bones.length;i++){var o=this.bones[i],a=null,s=o.getParent();if(s){var d=this.bones.indexOf(s);a=n.bones[d]}var p=new Be(o.name,n,a,o.getBaseMatrix().clone(),o.getRestPose().clone());p._index=o._index,o._linkedTransformNode&&p.linkTransformNode(o._linkedTransformNode),de.a.DeepCopy(o.animations,p.animations)}if(this._ranges)for(var b in n._ranges={},this._ranges){var P=this._ranges[b];P&&(n._ranges[b]=P.clone())}return this._isDirty=!0,n},r.prototype.enableBlending=function(t){t===void 0&&(t=.01),this.bones.forEach(function(e){e.animations.forEach(function(n){n.enableBlending=!0,n.blendingSpeed=t})})},r.prototype.dispose=function(){this._meshesWithPoseMatrix=[],this.getScene().stopAnimation(this),this.getScene().removeSkeleton(this),this._transformMatrixTexture&&(this._transformMatrixTexture.dispose(),this._transformMatrixTexture=null)},r.prototype.serialize=function(){var t,e,n={};n.name=this.name,n.id=this.id,this.dimensionsAtRest&&(n.dimensionsAtRest=this.dimensionsAtRest.asArray()),n.bones=[],n.needInitialSkinMatrix=this.needInitialSkinMatrix,n.overrideMeshId=(t=this.overrideMesh)===null||t===void 0?void 0:t.id;for(var i=0;i<this.bones.length;i++){var o=this.bones[i],a=o.getParent(),s={parentBoneIndex:a?this.bones.indexOf(a):-1,index:o.getIndex(),name:o.name,matrix:o.getBaseMatrix().toArray(),rest:o.getRestPose().toArray(),linkedTransformNodeId:(e=o.getTransformNode())===null||e===void 0?void 0:e.id};for(var d in n.bones.push(s),o.length&&(s.length=o.length),o.metadata&&(s.metadata=o.metadata),o.animations&&o.animations.length>0&&(s.animation=o.animations[0].serialize()),n.ranges=[],this._ranges){var p=this._ranges[d];if(p){var b={};b.name=d,b.from=p.from,b.to=p.to,n.ranges.push(b)}}}return n},r.Parse=function(t,e){var n,i=new r(t.name,t.id,e);for(t.dimensionsAtRest&&(i.dimensionsAtRest=u.e.FromArray(t.dimensionsAtRest)),i.needInitialSkinMatrix=t.needInitialSkinMatrix,t.overrideMeshId&&(i._hasWaitingData=!0,i._waitingOverrideMeshId=t.overrideMeshId),n=0;n<t.bones.length;n++){var o=t.bones[n],a=t.bones[n].index,s=null;o.parentBoneIndex>-1&&(s=i.bones[o.parentBoneIndex]);var d=o.rest?u.a.FromArray(o.rest):null,p=new Be(o.name,i,s,u.a.FromArray(o.matrix),d,null,a);o.id!==void 0&&o.id!==null&&(p.id=o.id),o.length&&(p.length=o.length),o.metadata&&(p.metadata=o.metadata),o.animation&&p.animations.push(k.Parse(o.animation)),o.linkedTransformNodeId!==void 0&&o.linkedTransformNodeId!==null&&(i._hasWaitingData=!0,p._waitingTransformNodeId=o.linkedTransformNodeId)}if(t.ranges)for(n=0;n<t.ranges.length;n++){var b=t.ranges[n];i.createAnimationRange(b.name,b.from,b.to)}return i},r.prototype.computeAbsoluteTransforms=function(t){t===void 0&&(t=!1);var e=this._scene.getRenderId();(this._lastAbsoluteTransformsUpdateId!=e||t)&&(this.bones[0].computeAbsoluteTransforms(),this._lastAbsoluteTransformsUpdateId=e)},r.prototype.getPoseMatrix=function(){var t=null;return this._meshesWithPoseMatrix.length>0&&(t=this._meshesWithPoseMatrix[0].getPoseMatrix()),t},r.prototype.sortBones=function(){for(var t=new Array,e=new Array(this.bones.length),n=0;n<this.bones.length;n++)this._sortBones(n,t,e);this.bones=t},r.prototype._sortBones=function(t,e,n){if(!n[t]){n[t]=!0;var i=this.bones[t];i._index===void 0&&(i._index=t);var o=i.getParent();o&&this._sortBones(this.bones.indexOf(o),e,n),e.push(i)}},r.prototype.setCurrentPoseAsRest=function(){this.bones.forEach(function(t){t.setCurrentPoseAsRest()})},r}(),hn={},$r=function(){function r(t){this.attachedToElement=!1,this.attached={},this.camera=t,this.checkInputs=function(){}}return r.prototype.add=function(t){var e=t.getSimpleName();this.attached[e]?l.a.Warn("camera input of type "+e+" already exists on camera"):(this.attached[e]=t,t.camera=this.camera,t.checkInputs&&(this.checkInputs=this._addCheckInputs(t.checkInputs.bind(t))),this.attachedToElement&&t.attachControl())},r.prototype.remove=function(t){for(var e in this.attached){var n=this.attached[e];n===t&&(n.detachControl(),n.camera=null,delete this.attached[e],this.rebuildInputCheck())}},r.prototype.removeByType=function(t){for(var e in this.attached){var n=this.attached[e];n.getClassName()===t&&(n.detachControl(),n.camera=null,delete this.attached[e],this.rebuildInputCheck())}},r.prototype._addCheckInputs=function(t){var e=this.checkInputs;return function(){e(),t()}},r.prototype.attachInput=function(t){this.attachedToElement&&t.attachControl(this.noPreventDefault)},r.prototype.attachElement=function(t){if(t===void 0&&(t=!1),!this.attachedToElement)for(var e in t=!gt.a.ForceAttachControlToAlwaysPreventDefault&&t,this.attachedToElement=!0,this.noPreventDefault=t,this.attached)this.attached[e].attachControl(t)},r.prototype.detachElement=function(t){for(var e in t===void 0&&(t=!1),this.attached)this.attached[e].detachControl(),t&&(this.attached[e].camera=null);this.attachedToElement=!1},r.prototype.rebuildInputCheck=function(){for(var t in this.checkInputs=function(){},this.attached){var e=this.attached[t];e.checkInputs&&(this.checkInputs=this._addCheckInputs(e.checkInputs.bind(e)))}},r.prototype.clear=function(){this.attachedToElement&&this.detachElement(!0),this.attached={},this.attachedToElement=!1,this.checkInputs=function(){}},r.prototype.serialize=function(t){var e={};for(var n in this.attached){var i=this.attached[n],o=L.a.Serialize(i);e[i.getClassName()]=o}t.inputsmgr=e},r.prototype.parse=function(t){var e=t.inputsmgr;if(e){for(var n in this.clear(),e)if(a=hn[n]){var i=e[n],o=L.a.Parse(function(){return new a},i,null);this.add(o)}}else for(var n in this.attached){var a;(a=hn[this.attached[n].getClassName()])&&(o=L.a.Parse(function(){return new a},t,null),this.remove(this.attached[n]),this.add(o))}},r}(),Uf=function(r,t){this.x=r,this.y=t},dn=function(){function r(t,e,n,i,o,a,s){i===void 0&&(i=0),o===void 0&&(o=1),a===void 0&&(a=2),s===void 0&&(s=3),this.id=t,this.index=e,this.browserGamepad=n,this._leftStick={x:0,y:0},this._rightStick={x:0,y:0},this._isConnected=!0,this._invertLeftStickY=!1,this.type=r.GAMEPAD,this._leftStickAxisX=i,this._leftStickAxisY=o,this._rightStickAxisX=a,this._rightStickAxisY=s,this.browserGamepad.axes.length>=2&&(this._leftStick={x:this.browserGamepad.axes[this._leftStickAxisX],y:this.browserGamepad.axes[this._leftStickAxisY]}),this.browserGamepad.axes.length>=4&&(this._rightStick={x:this.browserGamepad.axes[this._rightStickAxisX],y:this.browserGamepad.axes[this._rightStickAxisY]})}return Object.defineProperty(r.prototype,"isConnected",{get:function(){return this._isConnected},enumerable:!1,configurable:!0}),r.prototype.onleftstickchanged=function(t){this._onleftstickchanged=t},r.prototype.onrightstickchanged=function(t){this._onrightstickchanged=t},Object.defineProperty(r.prototype,"leftStick",{get:function(){return this._leftStick},set:function(t){!this._onleftstickchanged||this._leftStick.x===t.x&&this._leftStick.y===t.y||this._onleftstickchanged(t),this._leftStick=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rightStick",{get:function(){return this._rightStick},set:function(t){!this._onrightstickchanged||this._rightStick.x===t.x&&this._rightStick.y===t.y||this._onrightstickchanged(t),this._rightStick=t},enumerable:!1,configurable:!0}),r.prototype.update=function(){this._leftStick&&(this.leftStick={x:this.browserGamepad.axes[this._leftStickAxisX],y:this.browserGamepad.axes[this._leftStickAxisY]},this._invertLeftStickY&&(this.leftStick.y*=-1)),this._rightStick&&(this.rightStick={x:this.browserGamepad.axes[this._rightStickAxisX],y:this.browserGamepad.axes[this._rightStickAxisY]})},r.prototype.dispose=function(){},r.GAMEPAD=0,r.GENERIC=1,r.XBOX=2,r.POSE_ENABLED=3,r.DUALSHOCK=4,r}(),Tl=function(r){function t(e,n,i){var o=r.call(this,e,n,i)||this;return o.onButtonDownObservable=new C.c,o.onButtonUpObservable=new C.c,o.type=dn.GENERIC,o._buttons=new Array(i.buttons.length),o}return Object(c.d)(t,r),t.prototype.onbuttondown=function(e){this._onbuttondown=e},t.prototype.onbuttonup=function(e){this._onbuttonup=e},t.prototype._setButtonValue=function(e,n,i){return e!==n&&(e===1&&(this._onbuttondown&&this._onbuttondown(i),this.onButtonDownObservable.notifyObservers(i)),e===0&&(this._onbuttonup&&this._onbuttonup(i),this.onButtonUpObservable.notifyObservers(i))),e},t.prototype.update=function(){r.prototype.update.call(this);for(var e=0;e<this._buttons.length;e++)this._buttons[e]=this._setButtonValue(this.browserGamepad.buttons[e].value,this._buttons[e],e)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onButtonDownObservable.clear(),this.onButtonUpObservable.clear()},t}(dn),Wa=function(){function r(){this.gamepadRotationSensibility=80,this.gamepadMoveSensibility=40,this._yAxisScale=1}return Object.defineProperty(r.prototype,"invertYAxis",{get:function(){return this._yAxisScale!==1},set:function(t){this._yAxisScale=t?-1:1},enumerable:!1,configurable:!0}),r.prototype.attachControl=function(){var t=this,e=this.camera.getScene().gamepadManager;this._onGamepadConnectedObserver=e.onGamepadConnectedObservable.add(function(n){n.type!==dn.POSE_ENABLED&&(t.gamepad&&n.type!==dn.XBOX||(t.gamepad=n))}),this._onGamepadDisconnectedObserver=e.onGamepadDisconnectedObservable.add(function(n){t.gamepad===n&&(t.gamepad=null)}),this.gamepad=e.getGamepadByType(dn.XBOX)},r.prototype.detachControl=function(t){this.camera.getScene().gamepadManager.onGamepadConnectedObservable.remove(this._onGamepadConnectedObserver),this.camera.getScene().gamepadManager.onGamepadDisconnectedObservable.remove(this._onGamepadDisconnectedObserver),this.gamepad=null},r.prototype.checkInputs=function(){if(this.gamepad){var t=this.camera,e=this.gamepad.rightStick;if(e){if(e.x!=0){var n=e.x/this.gamepadRotationSensibility;n!=0&&Math.abs(n)>.005&&(t.inertialAlphaOffset+=n)}if(e.y!=0){var i=e.y/this.gamepadRotationSensibility*this._yAxisScale;i!=0&&Math.abs(i)>.005&&(t.inertialBetaOffset+=i)}}var o=this.gamepad.leftStick;if(o&&o.y!=0){var a=o.y/this.gamepadMoveSensibility;a!=0&&Math.abs(a)>.005&&(this.camera.inertialRadiusOffset-=a)}}},r.prototype.getClassName=function(){return"ArcRotateCameraGamepadInput"},r.prototype.getSimpleName=function(){return"gamepad"},Object(c.c)([Object(L.c)()],r.prototype,"gamepadRotationSensibility",void 0),Object(c.c)([Object(L.c)()],r.prototype,"gamepadMoveSensibility",void 0),r}();hn.ArcRotateCameraGamepadInput=Wa;var Zi=f(66),Xa=function(){function r(){this.keysUp=[38],this.keysDown=[40],this.keysLeft=[37],this.keysRight=[39],this.keysReset=[220],this.panningSensibility=50,this.zoomingSensibility=25,this.useAltToZoom=!0,this.angularSpeed=.01,this._keys=new Array}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._onCanvasBlurObserver||(this._scene=this.camera.getScene(),this._engine=this._scene.getEngine(),this._onCanvasBlurObserver=this._engine.onCanvasBlurObservable.add(function(){e._keys=[]}),this._onKeyboardObserver=this._scene.onKeyboardObservable.add(function(n){var i,o=n.event;o.metaKey||(n.type===Zi.a.KEYDOWN?(e._ctrlPressed=o.ctrlKey,e._altPressed=o.altKey,(e.keysUp.indexOf(o.keyCode)!==-1||e.keysDown.indexOf(o.keyCode)!==-1||e.keysLeft.indexOf(o.keyCode)!==-1||e.keysRight.indexOf(o.keyCode)!==-1||e.keysReset.indexOf(o.keyCode)!==-1)&&((i=e._keys.indexOf(o.keyCode))===-1&&e._keys.push(o.keyCode),o.preventDefault&&(t||o.preventDefault()))):e.keysUp.indexOf(o.keyCode)===-1&&e.keysDown.indexOf(o.keyCode)===-1&&e.keysLeft.indexOf(o.keyCode)===-1&&e.keysRight.indexOf(o.keyCode)===-1&&e.keysReset.indexOf(o.keyCode)===-1||((i=e._keys.indexOf(o.keyCode))>=0&&e._keys.splice(i,1),o.preventDefault&&(t||o.preventDefault())))}))},r.prototype.detachControl=function(t){this._scene&&(this._onKeyboardObserver&&this._scene.onKeyboardObservable.remove(this._onKeyboardObserver),this._onCanvasBlurObserver&&this._engine.onCanvasBlurObservable.remove(this._onCanvasBlurObserver),this._onKeyboardObserver=null,this._onCanvasBlurObserver=null),this._keys=[]},r.prototype.checkInputs=function(){if(this._onKeyboardObserver)for(var t=this.camera,e=0;e<this._keys.length;e++){var n=this._keys[e];this.keysLeft.indexOf(n)!==-1?this._ctrlPressed&&this.camera._useCtrlForPanning?t.inertialPanningX-=1/this.panningSensibility:t.inertialAlphaOffset-=this.angularSpeed:this.keysUp.indexOf(n)!==-1?this._ctrlPressed&&this.camera._useCtrlForPanning?t.inertialPanningY+=1/this.panningSensibility:this._altPressed&&this.useAltToZoom?t.inertialRadiusOffset+=1/this.zoomingSensibility:t.inertialBetaOffset-=this.angularSpeed:this.keysRight.indexOf(n)!==-1?this._ctrlPressed&&this.camera._useCtrlForPanning?t.inertialPanningX+=1/this.panningSensibility:t.inertialAlphaOffset+=this.angularSpeed:this.keysDown.indexOf(n)!==-1?this._ctrlPressed&&this.camera._useCtrlForPanning?t.inertialPanningY-=1/this.panningSensibility:this._altPressed&&this.useAltToZoom?t.inertialRadiusOffset-=1/this.zoomingSensibility:t.inertialBetaOffset+=this.angularSpeed:this.keysReset.indexOf(n)!==-1&&t.useInputToRestoreState&&t.restoreState()}},r.prototype.getClassName=function(){return"ArcRotateCameraKeyboardMoveInput"},r.prototype.getSimpleName=function(){return"keyboard"},Object(c.c)([Object(L.c)()],r.prototype,"keysUp",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysDown",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysLeft",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRight",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysReset",void 0),Object(c.c)([Object(L.c)()],r.prototype,"panningSensibility",void 0),Object(c.c)([Object(L.c)()],r.prototype,"zoomingSensibility",void 0),Object(c.c)([Object(L.c)()],r.prototype,"useAltToZoom",void 0),Object(c.c)([Object(L.c)()],r.prototype,"angularSpeed",void 0),r}();hn.ArcRotateCameraKeyboardMoveInput=Xa;var Ya=function(){function r(){this.wheelPrecision=3,this.wheelDeltaPercentage=0}return r.prototype.computeDeltaFromMouseWheelLegacyEvent=function(t,e){var n=.01*t*this.wheelDeltaPercentage*e;return t>0?n/(1+this.wheelDeltaPercentage):n*(1+this.wheelDeltaPercentage)},r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._wheel=function(n,i){if(n.type===Tt.a.POINTERWHEEL){var o=n.event,a=0,s=o,d=0;if(d=s.wheelDelta?s.wheelDelta:60*-(o.deltaY||o.detail),e.wheelDeltaPercentage){if((a=e.computeDeltaFromMouseWheelLegacyEvent(d,e.camera.radius))>0){for(var p=e.camera.radius,b=e.camera.inertialRadiusOffset+a,P=0;P<20&&Math.abs(b)>.001;P++)p-=b,b*=e.camera.inertia;p=$.a.Clamp(p,0,Number.MAX_VALUE),a=e.computeDeltaFromMouseWheelLegacyEvent(d,p)}}else a=d/(40*e.wheelPrecision);a&&(e.camera.inertialRadiusOffset+=a),o.preventDefault&&(t||o.preventDefault())}},this._observer=this.camera.getScene().onPointerObservable.add(this._wheel,Tt.a.POINTERWHEEL)},r.prototype.detachControl=function(t){this._observer&&(this.camera.getScene().onPointerObservable.remove(this._observer),this._observer=null,this._wheel=null)},r.prototype.getClassName=function(){return"ArcRotateCameraMouseWheelInput"},r.prototype.getSimpleName=function(){return"mousewheel"},Object(c.c)([Object(L.c)()],r.prototype,"wheelPrecision",void 0),Object(c.c)([Object(L.c)()],r.prototype,"wheelDeltaPercentage",void 0),r}();hn.ArcRotateCameraMouseWheelInput=Ya;var El=function(){function r(){this.buttons=[0,1,2]}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments);var n=this.camera.getEngine(),i=n.getInputElement(),o=0,a=null;this.pointA=null,this.pointB=null,this._altKey=!1,this._ctrlKey=!1,this._metaKey=!1,this._shiftKey=!1,this._buttonsPressed=0,this._pointerInput=function(d,p){var b=d.event,P=b.pointerType==="touch";if(!n.isInVRExclusivePointerMode&&(d.type===Tt.a.POINTERMOVE||e.buttons.indexOf(b.button)!==-1)){var O=b.srcElement||b.target;if(e._altKey=b.altKey,e._ctrlKey=b.ctrlKey,e._metaKey=b.metaKey,e._shiftKey=b.shiftKey,e._buttonsPressed=b.buttons,n.isPointerLock){var B=b.movementX||b.mozMovementX||b.webkitMovementX||b.msMovementX||0,F=b.movementY||b.mozMovementY||b.webkitMovementY||b.msMovementY||0;e.onTouch(null,B,F),e.pointA=null,e.pointB=null}else if(d.type===Tt.a.POINTERDOWN&&O){try{O.setPointerCapture(b.pointerId)}catch{}e.pointA===null?e.pointA={x:b.clientX,y:b.clientY,pointerId:b.pointerId,type:b.pointerType}:e.pointB===null&&(e.pointB={x:b.clientX,y:b.clientY,pointerId:b.pointerId,type:b.pointerType}),e.onButtonDown(b),t||(b.preventDefault(),i&&i.focus())}else if(d.type===Tt.a.POINTERDOUBLETAP)e.onDoubleTap(b.pointerType);else if(d.type===Tt.a.POINTERUP&&O){try{O.releasePointerCapture(b.pointerId)}catch{}P||(e.pointB=null),n._badOS?e.pointA=e.pointB=null:e.pointB&&e.pointA&&e.pointA.pointerId==b.pointerId?(e.pointA=e.pointB,e.pointB=null):e.pointA&&e.pointB&&e.pointB.pointerId==b.pointerId?e.pointB=null:e.pointA=e.pointB=null,(o!==0||a)&&(e.onMultiTouch(e.pointA,e.pointB,o,0,a,null),o=0,a=null),e.onButtonUp(b),t||b.preventDefault()}else if(d.type===Tt.a.POINTERMOVE){if(t||b.preventDefault(),e.pointA&&e.pointB===null)B=b.clientX-e.pointA.x,F=b.clientY-e.pointA.y,e.onTouch(e.pointA,B,F),e.pointA.x=b.clientX,e.pointA.y=b.clientY;else if(e.pointA&&e.pointB){var z=e.pointA.pointerId===b.pointerId?e.pointA:e.pointB;z.x=b.clientX,z.y=b.clientY;var J=e.pointA.x-e.pointB.x,ie=e.pointA.y-e.pointB.y,se=J*J+ie*ie,ce={x:(e.pointA.x+e.pointB.x)/2,y:(e.pointA.y+e.pointB.y)/2,pointerId:b.pointerId,type:d.type};e.onMultiTouch(e.pointA,e.pointB,o,se,a,ce),a=ce,o=se}}}},this._observer=this.camera.getScene().onPointerObservable.add(this._pointerInput,Tt.a.POINTERDOWN|Tt.a.POINTERUP|Tt.a.POINTERMOVE),this._onLostFocus=function(){e.pointA=e.pointB=null,o=0,a=null,e.onLostFocus()},i&&i.addEventListener("contextmenu",this.onContextMenu.bind(this),!1);var s=this.camera.getScene().getEngine().getHostWindow();s&&Xe.b.RegisterTopRootEvents(s,[{name:"blur",handler:this._onLostFocus}])},r.prototype.detachControl=function(t){if(this._onLostFocus){var e=this.camera.getScene().getEngine().getHostWindow();e&&Xe.b.UnregisterTopRootEvents(e,[{name:"blur",handler:this._onLostFocus}])}if(this._observer){if(this.camera.getScene().onPointerObservable.remove(this._observer),this._observer=null,this.onContextMenu){var n=this.camera.getScene().getEngine().getInputElement();n&&n.removeEventListener("contextmenu",this.onContextMenu)}this._onLostFocus=null}this._altKey=!1,this._ctrlKey=!1,this._metaKey=!1,this._shiftKey=!1,this._buttonsPressed=0},r.prototype.getClassName=function(){return"BaseCameraPointersInput"},r.prototype.getSimpleName=function(){return"pointers"},r.prototype.onDoubleTap=function(t){},r.prototype.onTouch=function(t,e,n){},r.prototype.onMultiTouch=function(t,e,n,i,o,a){},r.prototype.onContextMenu=function(t){t.preventDefault()},r.prototype.onButtonDown=function(t){},r.prototype.onButtonUp=function(t){},r.prototype.onLostFocus=function(){},Object(c.c)([Object(L.c)()],r.prototype,"buttons",void 0),r}(),Ka=function(r){function t(){var e=r!==null&&r.apply(this,arguments)||this;return e.buttons=[0,1,2],e.angularSensibilityX=1e3,e.angularSensibilityY=1e3,e.pinchPrecision=12,e.pinchDeltaPercentage=0,e.useNaturalPinchZoom=!1,e.panningSensibility=1e3,e.multiTouchPanning=!0,e.multiTouchPanAndZoom=!0,e.pinchInwards=!0,e._isPanClick=!1,e._twoFingerActivityCount=0,e._isPinching=!1,e}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ArcRotateCameraPointersInput"},t.prototype.onTouch=function(e,n,i){this.panningSensibility!==0&&(this._ctrlKey&&this.camera._useCtrlForPanning||this._isPanClick)?(this.camera.inertialPanningX+=-n/this.panningSensibility,this.camera.inertialPanningY+=i/this.panningSensibility):(this.camera.inertialAlphaOffset-=n/this.angularSensibilityX,this.camera.inertialBetaOffset-=i/this.angularSensibilityY)},t.prototype.onDoubleTap=function(e){this.camera.useInputToRestoreState&&this.camera.restoreState()},t.prototype.onMultiTouch=function(e,n,i,o,a,s){if(!(i===0&&a===null||o===0&&s===null)){var d=this.pinchInwards?1:-1;if(this.multiTouchPanAndZoom){if(this.useNaturalPinchZoom?this.camera.radius=this.camera.radius*Math.sqrt(i)/Math.sqrt(o):this.pinchDeltaPercentage?this.camera.inertialRadiusOffset+=.001*(o-i)*this.camera.radius*this.pinchDeltaPercentage:this.camera.inertialRadiusOffset+=(o-i)/(this.pinchPrecision*d*(this.angularSensibilityX+this.angularSensibilityY)/2),this.panningSensibility!==0&&a&&s){var p=s.x-a.x,b=s.y-a.y;this.camera.inertialPanningX+=-p/this.panningSensibility,this.camera.inertialPanningY+=b/this.panningSensibility}}else{this._twoFingerActivityCount++;var P=Math.sqrt(i),O=Math.sqrt(o);this._isPinching||this._twoFingerActivityCount<20&&Math.abs(O-P)>this.camera.pinchToPanMaxDistance?(this.pinchDeltaPercentage?this.camera.inertialRadiusOffset+=.001*(o-i)*this.camera.radius*this.pinchDeltaPercentage:this.camera.inertialRadiusOffset+=(o-i)/(this.pinchPrecision*d*(this.angularSensibilityX+this.angularSensibilityY)/2),this._isPinching=!0):this.panningSensibility!==0&&this.multiTouchPanning&&s&&a&&(p=s.x-a.x,b=s.y-a.y,this.camera.inertialPanningX+=-p/this.panningSensibility,this.camera.inertialPanningY+=b/this.panningSensibility)}}},t.prototype.onButtonDown=function(e){this._isPanClick=e.button===this.camera._panningMouseButton},t.prototype.onButtonUp=function(e){this._twoFingerActivityCount=0,this._isPinching=!1},t.prototype.onLostFocus=function(){this._isPanClick=!1,this._twoFingerActivityCount=0,this._isPinching=!1},Object(c.c)([Object(L.c)()],t.prototype,"buttons",void 0),Object(c.c)([Object(L.c)()],t.prototype,"angularSensibilityX",void 0),Object(c.c)([Object(L.c)()],t.prototype,"angularSensibilityY",void 0),Object(c.c)([Object(L.c)()],t.prototype,"pinchPrecision",void 0),Object(c.c)([Object(L.c)()],t.prototype,"pinchDeltaPercentage",void 0),Object(c.c)([Object(L.c)()],t.prototype,"useNaturalPinchZoom",void 0),Object(c.c)([Object(L.c)()],t.prototype,"panningSensibility",void 0),Object(c.c)([Object(L.c)()],t.prototype,"multiTouchPanning",void 0),Object(c.c)([Object(L.c)()],t.prototype,"multiTouchPanAndZoom",void 0),t}(El);hn.ArcRotateCameraPointersInput=Ka;var wo=function(r){function t(e){return r.call(this,e)||this}return Object(c.d)(t,r),t.prototype.addMouseWheel=function(){return this.add(new Ya),this},t.prototype.addPointers=function(){return this.add(new Ka),this},t.prototype.addKeyboard=function(){return this.add(new Xa),this},t}($r);wo.prototype.addVRDeviceOrientation=function(){return this.add(new Qa),this};var Qa=function(){function r(){this.alphaCorrection=1,this.gammaCorrection=1,this._alpha=0,this._gamma=0,this._dirty=!1,this._deviceOrientationHandler=this._onOrientationEvent.bind(this)}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this.camera.attachControl(t);var n=this.camera.getScene().getEngine().getHostWindow();n&&(typeof DeviceOrientationEvent<"u"&&typeof DeviceOrientationEvent.requestPermission=="function"?DeviceOrientationEvent.requestPermission().then(function(i){i==="granted"?n.addEventListener("deviceorientation",e._deviceOrientationHandler):Xe.b.Warn("Permission not granted.")}).catch(function(i){Xe.b.Error(i)}):n.addEventListener("deviceorientation",this._deviceOrientationHandler))},r.prototype._onOrientationEvent=function(t){t.alpha!==null&&(this._alpha=(0|+t.alpha)*this.alphaCorrection),t.gamma!==null&&(this._gamma=(0|+t.gamma)*this.gammaCorrection),this._dirty=!0},r.prototype.checkInputs=function(){this._dirty&&(this._dirty=!1,this._gamma<0&&(this._gamma=180+this._gamma),this.camera.alpha=-this._alpha/180*Math.PI%Math.PI*2,this.camera.beta=this._gamma/180*Math.PI)},r.prototype.detachControl=function(t){window.removeEventListener("deviceorientation",this._deviceOrientationHandler)},r.prototype.getClassName=function(){return"ArcRotateCameraVRDeviceOrientationInput"},r.prototype.getSimpleName=function(){return"VRDeviceOrientation"},r}();hn.ArcRotateCameraVRDeviceOrientationInput=Qa;var qa=function(){function r(){this.keysForward=[87],this.keysBackward=[83],this.keysUp=[69],this.keysDown=[81],this.keysRight=[68],this.keysLeft=[65],this._keys=new Array}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._onCanvasBlurObserver||(this._scene=this.camera.getScene(),this._engine=this._scene.getEngine(),this._onCanvasBlurObserver=this._engine.onCanvasBlurObservable.add(function(){e._keys=[]}),this._onKeyboardObserver=this._scene.onKeyboardObservable.add(function(n){var i,o=n.event;n.type===Zi.a.KEYDOWN?e.keysForward.indexOf(o.keyCode)===-1&&e.keysBackward.indexOf(o.keyCode)===-1&&e.keysUp.indexOf(o.keyCode)===-1&&e.keysDown.indexOf(o.keyCode)===-1&&e.keysLeft.indexOf(o.keyCode)===-1&&e.keysRight.indexOf(o.keyCode)===-1||((i=e._keys.indexOf(o.keyCode))===-1&&e._keys.push(o.keyCode),t||o.preventDefault()):e.keysForward.indexOf(o.keyCode)===-1&&e.keysBackward.indexOf(o.keyCode)===-1&&e.keysUp.indexOf(o.keyCode)===-1&&e.keysDown.indexOf(o.keyCode)===-1&&e.keysLeft.indexOf(o.keyCode)===-1&&e.keysRight.indexOf(o.keyCode)===-1||((i=e._keys.indexOf(o.keyCode))>=0&&e._keys.splice(i,1),t||o.preventDefault())}))},r.prototype.detachControl=function(t){this._scene&&(this._onKeyboardObserver&&this._scene.onKeyboardObservable.remove(this._onKeyboardObserver),this._onCanvasBlurObserver&&this._engine.onCanvasBlurObservable.remove(this._onCanvasBlurObserver),this._onKeyboardObserver=null,this._onCanvasBlurObserver=null),this._keys=[]},r.prototype.getClassName=function(){return"FlyCameraKeyboardInput"},r.prototype._onLostFocus=function(t){this._keys=[]},r.prototype.getSimpleName=function(){return"keyboard"},r.prototype.checkInputs=function(){if(this._onKeyboardObserver)for(var t=this.camera,e=0;e<this._keys.length;e++){var n=this._keys[e],i=t._computeLocalCameraSpeed();this.keysForward.indexOf(n)!==-1?t._localDirection.copyFromFloats(0,0,i):this.keysBackward.indexOf(n)!==-1?t._localDirection.copyFromFloats(0,0,-i):this.keysUp.indexOf(n)!==-1?t._localDirection.copyFromFloats(0,i,0):this.keysDown.indexOf(n)!==-1?t._localDirection.copyFromFloats(0,-i,0):this.keysRight.indexOf(n)!==-1?t._localDirection.copyFromFloats(i,0,0):this.keysLeft.indexOf(n)!==-1&&t._localDirection.copyFromFloats(-i,0,0),t.getScene().useRightHandedSystem&&(t._localDirection.z*=-1),t.getViewMatrix().invertToRef(t._cameraTransformMatrix),u.e.TransformNormalToRef(t._localDirection,t._cameraTransformMatrix,t._transformedDirection),t.cameraDirection.addInPlace(t._transformedDirection)}},Object(c.c)([Object(L.c)()],r.prototype,"keysForward",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysBackward",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysUp",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysDown",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRight",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysLeft",void 0),r}();hn.FlyCameraKeyboardInput=qa;var Za=function(){function r(t){this.buttons=[0,1,2],this.buttonsYaw=[-1,0,1],this.buttonsPitch=[-1,0,1],this.buttonsRoll=[2],this.activeButton=-1,this.angularSensibility=1e3,this.previousPosition=null}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this.noPreventDefault=t,this._observer=this.camera.getScene().onPointerObservable.add(function(n,i){e._pointerInput(n,i)},Tt.a.POINTERDOWN|Tt.a.POINTERUP|Tt.a.POINTERMOVE),this._rollObserver=this.camera.getScene().onBeforeRenderObservable.add(function(){e.camera.rollCorrect&&e.camera.restoreRoll(e.camera.rollCorrect)})},r.prototype.detachControl=function(t){this._observer&&(this.camera.getScene().onPointerObservable.remove(this._observer),this.camera.getScene().onBeforeRenderObservable.remove(this._rollObserver),this._observer=null,this._rollObserver=null,this.previousPosition=null,this.noPreventDefault=void 0)},r.prototype.getClassName=function(){return"FlyCameraMouseInput"},r.prototype.getSimpleName=function(){return"mouse"},r.prototype._pointerInput=function(t,e){var n=t.event,i=this.camera.getEngine();if(!i.isInVRExclusivePointerMode&&(this.touchEnabled||n.pointerType!=="touch")&&(t.type===Tt.a.POINTERMOVE||this.buttons.indexOf(n.button)!==-1)){var o=n.srcElement||n.target;if(t.type===Tt.a.POINTERDOWN&&o){try{o.setPointerCapture(n.pointerId)}catch{}this.previousPosition={x:n.clientX,y:n.clientY},this.activeButton=n.button,this.noPreventDefault||(n.preventDefault(),this.element.focus()),i.isPointerLock&&this._onMouseMove(t.event)}else if(t.type===Tt.a.POINTERUP&&o){try{o.releasePointerCapture(n.pointerId)}catch{}this.activeButton=-1,this.previousPosition=null,this.noPreventDefault||n.preventDefault()}else if(t.type===Tt.a.POINTERMOVE){if(!this.previousPosition)return void(i.isPointerLock&&this._onMouseMove(t.event));var a=n.clientX-this.previousPosition.x,s=n.clientY-this.previousPosition.y;this.rotateCamera(a,s),this.previousPosition={x:n.clientX,y:n.clientY},this.noPreventDefault||n.preventDefault()}}},r.prototype._onMouseMove=function(t){var e=this.camera.getEngine();if(e.isPointerLock&&!e.isInVRExclusivePointerMode){var n=t.movementX||t.mozMovementX||t.webkitMovementX||t.msMovementX||0,i=t.movementY||t.mozMovementY||t.webkitMovementY||t.msMovementY||0;this.rotateCamera(n,i),this.previousPosition=null,this.noPreventDefault||t.preventDefault()}},r.prototype.rotateCamera=function(t,e){var n=this,i=this.camera;this.camera.getScene().useRightHandedSystem&&(t*=-1),i.parent&&i.parent._getWorldMatrixDeterminant()<0&&(t*=-1);var o,a=t/this.angularSensibility,s=e/this.angularSensibility,d=u.b.RotationYawPitchRoll(i.rotation.y,i.rotation.x,i.rotation.z);if(this.buttonsPitch.some(function(P){return P===n.activeButton})&&(o=u.b.RotationAxis(ye.a.X,s),d.multiplyInPlace(o)),this.buttonsYaw.some(function(P){return P===n.activeButton})){o=u.b.RotationAxis(ye.a.Y,a),d.multiplyInPlace(o);var p=i.bankedTurnLimit+i._trackRoll;if(i.bankedTurn&&-p<i.rotation.z&&i.rotation.z<p){var b=i.bankedTurnMultiplier*-a;o=u.b.RotationAxis(ye.a.Z,b),d.multiplyInPlace(o)}}this.buttonsRoll.some(function(P){return P===n.activeButton})&&(o=u.b.RotationAxis(ye.a.Z,-a),i._trackRoll-=a,d.multiplyInPlace(o)),d.toEulerAnglesToRef(i.rotation)},Object(c.c)([Object(L.c)()],r.prototype,"buttons",void 0),Object(c.c)([Object(L.c)()],r.prototype,"angularSensibility",void 0),r}();hn.FlyCameraMouseInput=Za;var Ja=function(){function r(){this.keysHeightOffsetIncr=[38],this.keysHeightOffsetDecr=[40],this.keysHeightOffsetModifierAlt=!1,this.keysHeightOffsetModifierCtrl=!1,this.keysHeightOffsetModifierShift=!1,this.keysRotationOffsetIncr=[37],this.keysRotationOffsetDecr=[39],this.keysRotationOffsetModifierAlt=!1,this.keysRotationOffsetModifierCtrl=!1,this.keysRotationOffsetModifierShift=!1,this.keysRadiusIncr=[40],this.keysRadiusDecr=[38],this.keysRadiusModifierAlt=!0,this.keysRadiusModifierCtrl=!1,this.keysRadiusModifierShift=!1,this.heightSensibility=1,this.rotationSensibility=1,this.radiusSensibility=1,this._keys=new Array}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._onCanvasBlurObserver||(this._scene=this.camera.getScene(),this._engine=this._scene.getEngine(),this._onCanvasBlurObserver=this._engine.onCanvasBlurObservable.add(function(){e._keys=[]}),this._onKeyboardObserver=this._scene.onKeyboardObservable.add(function(n){var i,o=n.event;o.metaKey||(n.type===Zi.a.KEYDOWN?(e._ctrlPressed=o.ctrlKey,e._altPressed=o.altKey,e._shiftPressed=o.shiftKey,(e.keysHeightOffsetIncr.indexOf(o.keyCode)!==-1||e.keysHeightOffsetDecr.indexOf(o.keyCode)!==-1||e.keysRotationOffsetIncr.indexOf(o.keyCode)!==-1||e.keysRotationOffsetDecr.indexOf(o.keyCode)!==-1||e.keysRadiusIncr.indexOf(o.keyCode)!==-1||e.keysRadiusDecr.indexOf(o.keyCode)!==-1)&&((i=e._keys.indexOf(o.keyCode))===-1&&e._keys.push(o.keyCode),o.preventDefault&&(t||o.preventDefault()))):e.keysHeightOffsetIncr.indexOf(o.keyCode)===-1&&e.keysHeightOffsetDecr.indexOf(o.keyCode)===-1&&e.keysRotationOffsetIncr.indexOf(o.keyCode)===-1&&e.keysRotationOffsetDecr.indexOf(o.keyCode)===-1&&e.keysRadiusIncr.indexOf(o.keyCode)===-1&&e.keysRadiusDecr.indexOf(o.keyCode)===-1||((i=e._keys.indexOf(o.keyCode))>=0&&e._keys.splice(i,1),o.preventDefault&&(t||o.preventDefault())))}))},r.prototype.detachControl=function(t){this._scene&&(this._onKeyboardObserver&&this._scene.onKeyboardObservable.remove(this._onKeyboardObserver),this._onCanvasBlurObserver&&this._engine.onCanvasBlurObservable.remove(this._onCanvasBlurObserver),this._onKeyboardObserver=null,this._onCanvasBlurObserver=null),this._keys=[]},r.prototype.checkInputs=function(){var t=this;this._onKeyboardObserver&&this._keys.forEach(function(e){t.keysHeightOffsetIncr.indexOf(e)!==-1&&t._modifierHeightOffset()?t.camera.heightOffset+=t.heightSensibility:t.keysHeightOffsetDecr.indexOf(e)!==-1&&t._modifierHeightOffset()?t.camera.heightOffset-=t.heightSensibility:t.keysRotationOffsetIncr.indexOf(e)!==-1&&t._modifierRotationOffset()?(t.camera.rotationOffset+=t.rotationSensibility,t.camera.rotationOffset%=360):t.keysRotationOffsetDecr.indexOf(e)!==-1&&t._modifierRotationOffset()?(t.camera.rotationOffset-=t.rotationSensibility,t.camera.rotationOffset%=360):t.keysRadiusIncr.indexOf(e)!==-1&&t._modifierRadius()?t.camera.radius+=t.radiusSensibility:t.keysRadiusDecr.indexOf(e)!==-1&&t._modifierRadius()&&(t.camera.radius-=t.radiusSensibility)})},r.prototype.getClassName=function(){return"FollowCameraKeyboardMoveInput"},r.prototype.getSimpleName=function(){return"keyboard"},r.prototype._modifierHeightOffset=function(){return this.keysHeightOffsetModifierAlt===this._altPressed&&this.keysHeightOffsetModifierCtrl===this._ctrlPressed&&this.keysHeightOffsetModifierShift===this._shiftPressed},r.prototype._modifierRotationOffset=function(){return this.keysRotationOffsetModifierAlt===this._altPressed&&this.keysRotationOffsetModifierCtrl===this._ctrlPressed&&this.keysRotationOffsetModifierShift===this._shiftPressed},r.prototype._modifierRadius=function(){return this.keysRadiusModifierAlt===this._altPressed&&this.keysRadiusModifierCtrl===this._ctrlPressed&&this.keysRadiusModifierShift===this._shiftPressed},Object(c.c)([Object(L.c)()],r.prototype,"keysHeightOffsetIncr",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysHeightOffsetDecr",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysHeightOffsetModifierAlt",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysHeightOffsetModifierCtrl",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysHeightOffsetModifierShift",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRotationOffsetIncr",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRotationOffsetDecr",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRotationOffsetModifierAlt",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRotationOffsetModifierCtrl",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRotationOffsetModifierShift",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRadiusIncr",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRadiusDecr",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRadiusModifierAlt",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRadiusModifierCtrl",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRadiusModifierShift",void 0),Object(c.c)([Object(L.c)()],r.prototype,"heightSensibility",void 0),Object(c.c)([Object(L.c)()],r.prototype,"rotationSensibility",void 0),Object(c.c)([Object(L.c)()],r.prototype,"radiusSensibility",void 0),r}();hn.FollowCameraKeyboardMoveInput=Ja;var $a=function(){function r(){this.axisControlRadius=!0,this.axisControlHeight=!1,this.axisControlRotation=!1,this.wheelPrecision=3,this.wheelDeltaPercentage=0}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._wheel=function(n,i){if(n.type===Tt.a.POINTERWHEEL){var o=n.event,a=0,s=Math.max(-1,Math.min(1,o.deltaY||o.wheelDelta||-o.detail));e.wheelDeltaPercentage?(console.assert(e.axisControlRadius+e.axisControlHeight+e.axisControlRotation<=1,"wheelDeltaPercentage only usable when mouse wheel controlls ONE axis. Currently enabled: axisControlRadius: "+e.axisControlRadius+", axisControlHeightOffset: "+e.axisControlHeight+", axisControlRotationOffset: "+e.axisControlRotation),e.axisControlRadius?a=.01*s*e.wheelDeltaPercentage*e.camera.radius:e.axisControlHeight?a=.01*s*e.wheelDeltaPercentage*e.camera.heightOffset:e.axisControlRotation&&(a=.01*s*e.wheelDeltaPercentage*e.camera.rotationOffset)):a=s*e.wheelPrecision,a&&(e.axisControlRadius?e.camera.radius+=a:e.axisControlHeight?e.camera.heightOffset-=a:e.axisControlRotation&&(e.camera.rotationOffset-=a)),o.preventDefault&&(t||o.preventDefault())}},this._observer=this.camera.getScene().onPointerObservable.add(this._wheel,Tt.a.POINTERWHEEL)},r.prototype.detachControl=function(t){this._observer&&(this.camera.getScene().onPointerObservable.remove(this._observer),this._observer=null,this._wheel=null)},r.prototype.getClassName=function(){return"ArcRotateCameraMouseWheelInput"},r.prototype.getSimpleName=function(){return"mousewheel"},Object(c.c)([Object(L.c)()],r.prototype,"axisControlRadius",void 0),Object(c.c)([Object(L.c)()],r.prototype,"axisControlHeight",void 0),Object(c.c)([Object(L.c)()],r.prototype,"axisControlRotation",void 0),Object(c.c)([Object(L.c)()],r.prototype,"wheelPrecision",void 0),Object(c.c)([Object(L.c)()],r.prototype,"wheelDeltaPercentage",void 0),r}();hn.FollowCameraMouseWheelInput=$a;var es=function(r){function t(){var e=r!==null&&r.apply(this,arguments)||this;return e.angularSensibilityX=1,e.angularSensibilityY=1,e.pinchPrecision=1e4,e.pinchDeltaPercentage=0,e.axisXControlRadius=!1,e.axisXControlHeight=!1,e.axisXControlRotation=!0,e.axisYControlRadius=!1,e.axisYControlHeight=!0,e.axisYControlRotation=!1,e.axisPinchControlRadius=!0,e.axisPinchControlHeight=!1,e.axisPinchControlRotation=!1,e.warningEnable=!0,e._warningCounter=0,e}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FollowCameraPointersInput"},t.prototype.onTouch=function(e,n,i){this._warning(),this.axisXControlRotation?this.camera.rotationOffset+=n/this.angularSensibilityX:this.axisYControlRotation&&(this.camera.rotationOffset+=i/this.angularSensibilityX),this.axisXControlHeight?this.camera.heightOffset+=n/this.angularSensibilityY:this.axisYControlHeight&&(this.camera.heightOffset+=i/this.angularSensibilityY),this.axisXControlRadius?this.camera.radius-=n/this.angularSensibilityY:this.axisYControlRadius&&(this.camera.radius-=i/this.angularSensibilityY)},t.prototype.onMultiTouch=function(e,n,i,o,a,s){if(!(i===0&&a===null||o===0&&s===null)){var d=(o-i)/(this.pinchPrecision*(this.angularSensibilityX+this.angularSensibilityY)/2);this.pinchDeltaPercentage?(d*=.01*this.pinchDeltaPercentage,this.axisPinchControlRotation&&(this.camera.rotationOffset+=d*this.camera.rotationOffset),this.axisPinchControlHeight&&(this.camera.heightOffset+=d*this.camera.heightOffset),this.axisPinchControlRadius&&(this.camera.radius-=d*this.camera.radius)):(this.axisPinchControlRotation&&(this.camera.rotationOffset+=d),this.axisPinchControlHeight&&(this.camera.heightOffset+=d),this.axisPinchControlRadius&&(this.camera.radius-=d))}},t.prototype._warning=function(){if(this.warningEnable&&this._warningCounter++%100==0){var e="It probably only makes sense to control ONE camera property with each pointer axis. Set 'warningEnable = false' if you are sure. Currently enabled: ";console.assert(this.axisXControlRotation+this.axisXControlHeight+this.axisXControlRadius<=1,e+"axisXControlRotation: "+this.axisXControlRotation+", axisXControlHeight: "+this.axisXControlHeight+", axisXControlRadius: "+this.axisXControlRadius),console.assert(this.axisYControlRotation+this.axisYControlHeight+this.axisYControlRadius<=1,e+"axisYControlRotation: "+this.axisYControlRotation+", axisYControlHeight: "+this.axisYControlHeight+", axisYControlRadius: "+this.axisYControlRadius),console.assert(this.axisPinchControlRotation+this.axisPinchControlHeight+this.axisPinchControlRadius<=1,e+"axisPinchControlRotation: "+this.axisPinchControlRotation+", axisPinchControlHeight: "+this.axisPinchControlHeight+", axisPinchControlRadius: "+this.axisPinchControlRadius)}},Object(c.c)([Object(L.c)()],t.prototype,"angularSensibilityX",void 0),Object(c.c)([Object(L.c)()],t.prototype,"angularSensibilityY",void 0),Object(c.c)([Object(L.c)()],t.prototype,"pinchPrecision",void 0),Object(c.c)([Object(L.c)()],t.prototype,"pinchDeltaPercentage",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisXControlRadius",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisXControlHeight",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisXControlRotation",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisYControlRadius",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisYControlHeight",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisYControlRotation",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisPinchControlRadius",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisPinchControlHeight",void 0),Object(c.c)([Object(L.c)()],t.prototype,"axisPinchControlRotation",void 0),t}(El);hn.FollowCameraPointersInput=es;var ts=function(){function r(){this.keysUp=[38],this.keysUpward=[33],this.keysDown=[40],this.keysDownward=[34],this.keysLeft=[37],this.keysRight=[39],this._keys=new Array}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._onCanvasBlurObserver||(this._scene=this.camera.getScene(),this._engine=this._scene.getEngine(),this._onCanvasBlurObserver=this._engine.onCanvasBlurObservable.add(function(){e._keys=[]}),this._onKeyboardObserver=this._scene.onKeyboardObservable.add(function(n){var i,o=n.event;o.metaKey||(n.type===Zi.a.KEYDOWN?e.keysUp.indexOf(o.keyCode)===-1&&e.keysDown.indexOf(o.keyCode)===-1&&e.keysLeft.indexOf(o.keyCode)===-1&&e.keysRight.indexOf(o.keyCode)===-1&&e.keysUpward.indexOf(o.keyCode)===-1&&e.keysDownward.indexOf(o.keyCode)===-1||((i=e._keys.indexOf(o.keyCode))===-1&&e._keys.push(o.keyCode),t||o.preventDefault()):e.keysUp.indexOf(o.keyCode)===-1&&e.keysDown.indexOf(o.keyCode)===-1&&e.keysLeft.indexOf(o.keyCode)===-1&&e.keysRight.indexOf(o.keyCode)===-1&&e.keysUpward.indexOf(o.keyCode)===-1&&e.keysDownward.indexOf(o.keyCode)===-1||((i=e._keys.indexOf(o.keyCode))>=0&&e._keys.splice(i,1),t||o.preventDefault()))}))},r.prototype.detachControl=function(t){this._scene&&(this._onKeyboardObserver&&this._scene.onKeyboardObservable.remove(this._onKeyboardObserver),this._onCanvasBlurObserver&&this._engine.onCanvasBlurObservable.remove(this._onCanvasBlurObserver),this._onKeyboardObserver=null,this._onCanvasBlurObserver=null),this._keys=[]},r.prototype.checkInputs=function(){if(this._onKeyboardObserver)for(var t=this.camera,e=0;e<this._keys.length;e++){var n=this._keys[e],i=t._computeLocalCameraSpeed();this.keysLeft.indexOf(n)!==-1?t._localDirection.copyFromFloats(-i,0,0):this.keysUp.indexOf(n)!==-1?t._localDirection.copyFromFloats(0,0,i):this.keysRight.indexOf(n)!==-1?t._localDirection.copyFromFloats(i,0,0):this.keysDown.indexOf(n)!==-1?t._localDirection.copyFromFloats(0,0,-i):this.keysUpward.indexOf(n)!==-1?t._localDirection.copyFromFloats(0,i,0):this.keysDownward.indexOf(n)!==-1&&t._localDirection.copyFromFloats(0,-i,0),t.getScene().useRightHandedSystem&&(t._localDirection.z*=-1),t.getViewMatrix().invertToRef(t._cameraTransformMatrix),u.e.TransformNormalToRef(t._localDirection,t._cameraTransformMatrix,t._transformedDirection),t.cameraDirection.addInPlace(t._transformedDirection)}},r.prototype.getClassName=function(){return"FreeCameraKeyboardMoveInput"},r.prototype._onLostFocus=function(){this._keys=[]},r.prototype.getSimpleName=function(){return"keyboard"},Object(c.c)([Object(L.c)()],r.prototype,"keysUp",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysUpward",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysDown",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysDownward",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysLeft",void 0),Object(c.c)([Object(L.c)()],r.prototype,"keysRight",void 0),r}();hn.FreeCameraKeyboardMoveInput=ts;var ns=function(){function r(t){t===void 0&&(t=!0),this.touchEnabled=t,this.buttons=[0,1,2],this.angularSensibility=2e3,this.previousPosition=null,this.onPointerMovedObservable=new C.c,this._allowCameraRotation=!0}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments);var n=this.camera.getEngine(),i=n.getInputElement();this._pointerInput||(this._pointerInput=function(o){var a=o.event;if(!n.isInVRExclusivePointerMode&&(e.touchEnabled||a.pointerType!=="touch")&&(o.type===Tt.a.POINTERMOVE||e.buttons.indexOf(a.button)!==-1)){var s=a.srcElement||a.target;if(o.type===Tt.a.POINTERDOWN&&s){try{s.setPointerCapture(a.pointerId)}catch{}e.previousPosition={x:a.clientX,y:a.clientY},t||(a.preventDefault(),i&&i.focus()),n.isPointerLock&&e._onMouseMove&&e._onMouseMove(o.event)}else if(o.type===Tt.a.POINTERUP&&s){try{s.releasePointerCapture(a.pointerId)}catch{}e.previousPosition=null,t||a.preventDefault()}else if(o.type===Tt.a.POINTERMOVE){if(!e.previousPosition)return void(n.isPointerLock&&e._onMouseMove&&e._onMouseMove(o.event));var d=a.clientX-e.previousPosition.x,p=a.clientY-e.previousPosition.y;e.camera.getScene().useRightHandedSystem&&(d*=-1),e.camera.parent&&e.camera.parent._getWorldMatrixDeterminant()<0&&(d*=-1),e._allowCameraRotation&&(e.camera.cameraRotation.y+=d/e.angularSensibility,e.camera.cameraRotation.x+=p/e.angularSensibility),e.onPointerMovedObservable.notifyObservers({offsetX:d,offsetY:p}),e.previousPosition={x:a.clientX,y:a.clientY},t||a.preventDefault()}}}),this._onMouseMove=function(o){if(n.isPointerLock&&!n.isInVRExclusivePointerMode){var a=o.movementX||o.mozMovementX||o.webkitMovementX||o.msMovementX||0;e.camera.getScene().useRightHandedSystem&&(a*=-1),e.camera.parent&&e.camera.parent._getWorldMatrixDeterminant()<0&&(a*=-1),e.camera.cameraRotation.y+=a/e.angularSensibility;var s=o.movementY||o.mozMovementY||o.webkitMovementY||o.msMovementY||0;e.camera.cameraRotation.x+=s/e.angularSensibility,e.previousPosition=null,t||o.preventDefault()}},this._observer=this.camera.getScene().onPointerObservable.add(this._pointerInput,Tt.a.POINTERDOWN|Tt.a.POINTERUP|Tt.a.POINTERMOVE),i&&i.addEventListener("contextmenu",this.onContextMenu.bind(this),!1)},r.prototype.onContextMenu=function(t){t.preventDefault()},r.prototype.detachControl=function(t){if(this._observer){if(this.camera.getScene().onPointerObservable.remove(this._observer),this.onContextMenu){var e=this.camera.getEngine().getInputElement();e&&e.removeEventListener("contextmenu",this.onContextMenu)}this.onPointerMovedObservable&&this.onPointerMovedObservable.clear(),this._observer=null,this._onMouseMove=null,this.previousPosition=null}},r.prototype.getClassName=function(){return"FreeCameraMouseInput"},r.prototype.getSimpleName=function(){return"mouse"},Object(c.c)([Object(L.c)()],r.prototype,"buttons",void 0),Object(c.c)([Object(L.c)()],r.prototype,"angularSensibility",void 0),r}();hn.FreeCameraMouseInput=ns;var kt,Vf=function(){function r(){this.wheelPrecisionX=3,this.wheelPrecisionY=3,this.wheelPrecisionZ=3,this.onChangedObservable=new C.c,this._wheelDeltaX=0,this._wheelDeltaY=0,this._wheelDeltaZ=0,this._ffMultiplier=12,this._normalize=120}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._wheel=function(n){if(n.type===Tt.a.POINTERWHEEL){var i=n.event,o=i.deltaMode===WheelEvent.DOM_DELTA_LINE?e._ffMultiplier:1;i.deltaY!==void 0?(e._wheelDeltaX+=e.wheelPrecisionX*o*i.deltaX/e._normalize,e._wheelDeltaY-=e.wheelPrecisionY*o*i.deltaY/e._normalize,e._wheelDeltaZ+=e.wheelPrecisionZ*o*i.deltaZ/e._normalize):i.wheelDeltaY!==void 0?(e._wheelDeltaX+=e.wheelPrecisionX*o*i.wheelDeltaX/e._normalize,e._wheelDeltaY-=e.wheelPrecisionY*o*i.wheelDeltaY/e._normalize,e._wheelDeltaZ+=e.wheelPrecisionZ*o*i.wheelDeltaZ/e._normalize):i.wheelDelta&&(e._wheelDeltaY-=e.wheelPrecisionY*i.wheelDelta/e._normalize),i.preventDefault&&(t||i.preventDefault())}},this._observer=this.camera.getScene().onPointerObservable.add(this._wheel,Tt.a.POINTERWHEEL)},r.prototype.detachControl=function(t){this._observer&&(this.camera.getScene().onPointerObservable.remove(this._observer),this._observer=null,this._wheel=null),this.onChangedObservable&&this.onChangedObservable.clear()},r.prototype.checkInputs=function(){this.onChangedObservable.notifyObservers({wheelDeltaX:this._wheelDeltaX,wheelDeltaY:this._wheelDeltaY,wheelDeltaZ:this._wheelDeltaZ}),this._wheelDeltaX=0,this._wheelDeltaY=0,this._wheelDeltaZ=0},r.prototype.getClassName=function(){return"BaseCameraMouseWheelInput"},r.prototype.getSimpleName=function(){return"mousewheel"},Object(c.c)([Object(L.c)()],r.prototype,"wheelPrecisionX",void 0),Object(c.c)([Object(L.c)()],r.prototype,"wheelPrecisionY",void 0),Object(c.c)([Object(L.c)()],r.prototype,"wheelPrecisionZ",void 0),r}();(function(r){r[r.MoveRelative=0]="MoveRelative",r[r.RotateRelative=1]="RotateRelative",r[r.MoveScene=2]="MoveScene"})(kt||(kt={}));var is=function(r){function t(){var e=r!==null&&r.apply(this,arguments)||this;return e._moveRelative=u.e.Zero(),e._rotateRelative=u.e.Zero(),e._moveScene=u.e.Zero(),e._wheelXAction=kt.MoveRelative,e._wheelXActionCoordinate=ye.b.X,e._wheelYAction=kt.MoveRelative,e._wheelYActionCoordinate=ye.b.Z,e._wheelZAction=null,e._wheelZActionCoordinate=null,e}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FreeCameraMouseWheelInput"},Object.defineProperty(t.prototype,"wheelXMoveRelative",{get:function(){return this._wheelXAction!==kt.MoveRelative?null:this._wheelXActionCoordinate},set:function(e){e===null&&this._wheelXAction!==kt.MoveRelative||(this._wheelXAction=kt.MoveRelative,this._wheelXActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelYMoveRelative",{get:function(){return this._wheelYAction!==kt.MoveRelative?null:this._wheelYActionCoordinate},set:function(e){e===null&&this._wheelYAction!==kt.MoveRelative||(this._wheelYAction=kt.MoveRelative,this._wheelYActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelZMoveRelative",{get:function(){return this._wheelZAction!==kt.MoveRelative?null:this._wheelZActionCoordinate},set:function(e){e===null&&this._wheelZAction!==kt.MoveRelative||(this._wheelZAction=kt.MoveRelative,this._wheelZActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelXRotateRelative",{get:function(){return this._wheelXAction!==kt.RotateRelative?null:this._wheelXActionCoordinate},set:function(e){e===null&&this._wheelXAction!==kt.RotateRelative||(this._wheelXAction=kt.RotateRelative,this._wheelXActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelYRotateRelative",{get:function(){return this._wheelYAction!==kt.RotateRelative?null:this._wheelYActionCoordinate},set:function(e){e===null&&this._wheelYAction!==kt.RotateRelative||(this._wheelYAction=kt.RotateRelative,this._wheelYActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelZRotateRelative",{get:function(){return this._wheelZAction!==kt.RotateRelative?null:this._wheelZActionCoordinate},set:function(e){e===null&&this._wheelZAction!==kt.RotateRelative||(this._wheelZAction=kt.RotateRelative,this._wheelZActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelXMoveScene",{get:function(){return this._wheelXAction!==kt.MoveScene?null:this._wheelXActionCoordinate},set:function(e){e===null&&this._wheelXAction!==kt.MoveScene||(this._wheelXAction=kt.MoveScene,this._wheelXActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelYMoveScene",{get:function(){return this._wheelYAction!==kt.MoveScene?null:this._wheelYActionCoordinate},set:function(e){e===null&&this._wheelYAction!==kt.MoveScene||(this._wheelYAction=kt.MoveScene,this._wheelYActionCoordinate=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelZMoveScene",{get:function(){return this._wheelZAction!==kt.MoveScene?null:this._wheelZActionCoordinate},set:function(e){e===null&&this._wheelZAction!==kt.MoveScene||(this._wheelZAction=kt.MoveScene,this._wheelZActionCoordinate=e)},enumerable:!1,configurable:!0}),t.prototype.checkInputs=function(){if(this._wheelDeltaX!==0||this._wheelDeltaY!==0||this._wheelDeltaZ!=0){this._moveRelative.setAll(0),this._rotateRelative.setAll(0),this._moveScene.setAll(0),this._updateCamera(),this.camera.getScene().useRightHandedSystem&&(this._moveRelative.z*=-1);var e=u.a.Zero();this.camera.getViewMatrix().invertToRef(e);var n=u.e.Zero();u.e.TransformNormalToRef(this._moveRelative,e,n),this.camera.cameraRotation.x+=this._rotateRelative.x/200,this.camera.cameraRotation.y+=this._rotateRelative.y/200,this.camera.cameraDirection.addInPlace(n),this.camera.cameraDirection.addInPlace(this._moveScene),r.prototype.checkInputs.call(this)}},t.prototype._updateCamera=function(){var e=this._moveRelative,n=this._rotateRelative,i=this._moveScene,o=function(a,s,d){if(a!==0&&s!==null&&d!==null){var p=null;switch(s){case kt.MoveRelative:p=e;break;case kt.RotateRelative:p=n;break;case kt.MoveScene:p=i}switch(d){case ye.b.X:p.set(a,0,0);break;case ye.b.Y:p.set(0,a,0);break;case ye.b.Z:p.set(0,0,a)}}};o(this._wheelDeltaX,this._wheelXAction,this._wheelXActionCoordinate),o(this._wheelDeltaY,this._wheelYAction,this._wheelYActionCoordinate),o(this._wheelDeltaZ,this._wheelZAction,this._wheelZActionCoordinate)},Object(c.c)([Object(L.c)()],t.prototype,"wheelXMoveRelative",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelYMoveRelative",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelZMoveRelative",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelXRotateRelative",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelYRotateRelative",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelZRotateRelative",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelXMoveScene",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelYMoveScene",null),Object(c.c)([Object(L.c)()],t.prototype,"wheelZMoveScene",null),t}(Vf);hn.FreeCameraMouseWheelInput=is;var rs=function(){function r(t){t===void 0&&(t=!1),this.allowMouse=t,this.touchAngularSensibility=2e5,this.touchMoveSensibility=250,this._offsetX=null,this._offsetY=null,this._pointerPressed=new Array}return r.prototype.attachControl=function(t){var e=this;t=Xe.b.BackCompatCameraNoPreventDefault(arguments);var n=null;if(this._pointerInput===void 0&&(this._onLostFocus=function(){e._offsetX=null,e._offsetY=null},this._pointerInput=function(a){var s=a.event,d=!e.camera.getEngine().hostInformation.isMobile&&s instanceof MouseEvent;if(e.allowMouse||s.pointerType!=="mouse"&&!d){if(a.type===Tt.a.POINTERDOWN){if(t||s.preventDefault(),e._pointerPressed.push(s.pointerId),e._pointerPressed.length!==1)return;n={x:s.clientX,y:s.clientY}}else if(a.type===Tt.a.POINTERUP){if(t||s.preventDefault(),(p=e._pointerPressed.indexOf(s.pointerId))===-1||(e._pointerPressed.splice(p,1),p!=0))return;n=null,e._offsetX=null,e._offsetY=null}else if(a.type===Tt.a.POINTERMOVE){if(t||s.preventDefault(),!n)return;var p;if((p=e._pointerPressed.indexOf(s.pointerId))!=0)return;e._offsetX=s.clientX-n.x,e._offsetY=-(s.clientY-n.y)}}}),this._observer=this.camera.getScene().onPointerObservable.add(this._pointerInput,Tt.a.POINTERDOWN|Tt.a.POINTERUP|Tt.a.POINTERMOVE),this._onLostFocus){var i=this.camera.getEngine(),o=i.getInputElement();o&&o.addEventListener("blur",this._onLostFocus)}},r.prototype.detachControl=function(t){if(this._pointerInput){if(this._observer&&(this.camera.getScene().onPointerObservable.remove(this._observer),this._observer=null),this._onLostFocus){var e=this.camera.getEngine().getInputElement();e&&e.removeEventListener("blur",this._onLostFocus),this._onLostFocus=null}this._pointerPressed=[],this._offsetX=null,this._offsetY=null}},r.prototype.checkInputs=function(){if(this._offsetX!==null&&this._offsetY!==null&&(this._offsetX!==0||this._offsetY!==0)){var t=this.camera;if(t.cameraRotation.y=this._offsetX/this.touchAngularSensibility,this._pointerPressed.length>1)t.cameraRotation.x=-this._offsetY/this.touchAngularSensibility;else{var e=t._computeLocalCameraSpeed(),n=new u.e(0,0,e*this._offsetY/this.touchMoveSensibility);u.a.RotationYawPitchRollToRef(t.rotation.y,t.rotation.x,0,t._cameraRotationMatrix),t.cameraDirection.addInPlace(u.e.TransformCoordinates(n,t._cameraRotationMatrix))}}},r.prototype.getClassName=function(){return"FreeCameraTouchInput"},r.prototype.getSimpleName=function(){return"touch"},Object(c.c)([Object(L.c)()],r.prototype,"touchAngularSensibility",void 0),Object(c.c)([Object(L.c)()],r.prototype,"touchMoveSensibility",void 0),r}();hn.FreeCameraTouchInput=rs;var eo=function(r){function t(e){var n=r.call(this,e)||this;return n._mouseInput=null,n._mouseWheelInput=null,n}return Object(c.d)(t,r),t.prototype.addKeyboard=function(){return this.add(new ts),this},t.prototype.addMouse=function(e){return e===void 0&&(e=!0),this._mouseInput||(this._mouseInput=new ns(e),this.add(this._mouseInput)),this},t.prototype.removeMouse=function(){return this._mouseInput&&this.remove(this._mouseInput),this},t.prototype.addMouseWheel=function(){return this._mouseWheelInput||(this._mouseWheelInput=new is,this.add(this._mouseWheelInput)),this},t.prototype.removeMouseWheel=function(){return this._mouseWheelInput&&this.remove(this._mouseWheelInput),this},t.prototype.addTouch=function(){return this.add(new rs),this},t.prototype.clear=function(){r.prototype.clear.call(this),this._mouseInput=null},t}($r);eo.prototype.addDeviceOrientation=function(){return this._deviceOrientationInput||(this._deviceOrientationInput=new os,this.add(this._deviceOrientationInput)),this};var os=function(){function r(){var t=this;this._screenOrientationAngle=0,this._screenQuaternion=new u.b,this._alpha=0,this._beta=0,this._gamma=0,this._onDeviceOrientationChangedObservable=new C.c,this._orientationChanged=function(){t._screenOrientationAngle=window.orientation!==void 0?+window.orientation:window.screen.orientation&&window.screen.orientation.angle?window.screen.orientation.angle:0,t._screenOrientationAngle=-Xe.b.ToRadians(t._screenOrientationAngle/2),t._screenQuaternion.copyFromFloats(0,Math.sin(t._screenOrientationAngle),0,Math.cos(t._screenOrientationAngle))},this._deviceOrientation=function(e){t._alpha=e.alpha!==null?e.alpha:0,t._beta=e.beta!==null?e.beta:0,t._gamma=e.gamma!==null?e.gamma:0,e.alpha!==null&&t._onDeviceOrientationChangedObservable.notifyObservers()},this._constantTranform=new u.b(-Math.sqrt(.5),0,0,Math.sqrt(.5)),this._orientationChanged()}return r.WaitForOrientationChangeAsync=function(t){return new Promise(function(e,n){var i=!1,o=function(){window.removeEventListener("deviceorientation",o),i=!0,e()};t&&setTimeout(function(){i||(window.removeEventListener("deviceorientation",o),n("WaitForOrientationChangeAsync timed out"))},t),typeof DeviceOrientationEvent<"u"&&typeof DeviceOrientationEvent.requestPermission=="function"?DeviceOrientationEvent.requestPermission().then(function(a){a=="granted"?window.addEventListener("deviceorientation",o):Xe.b.Warn("Permission not granted.")}).catch(function(a){Xe.b.Error(a)}):window.addEventListener("deviceorientation",o)})},Object.defineProperty(r.prototype,"camera",{get:function(){return this._camera},set:function(t){var e=this;this._camera=t,this._camera==null||this._camera.rotationQuaternion||(this._camera.rotationQuaternion=new u.b),this._camera&&this._camera.onDisposeObservable.add(function(){e._onDeviceOrientationChangedObservable.clear()})},enumerable:!1,configurable:!0}),r.prototype.attachControl=function(){var t=this,e=this.camera.getScene().getEngine().getHostWindow();if(e){var n=function(){e.addEventListener("orientationchange",t._orientationChanged),e.addEventListener("deviceorientation",t._deviceOrientation),t._orientationChanged()};typeof DeviceOrientationEvent<"u"&&typeof DeviceOrientationEvent.requestPermission=="function"?DeviceOrientationEvent.requestPermission().then(function(i){i==="granted"?n():Xe.b.Warn("Permission not granted.")}).catch(function(i){Xe.b.Error(i)}):n()}},r.prototype.detachControl=function(t){window.removeEventListener("orientationchange",this._orientationChanged),window.removeEventListener("deviceorientation",this._deviceOrientation),this._alpha=0},r.prototype.checkInputs=function(){this._alpha&&(u.b.RotationYawPitchRollToRef(Xe.b.ToRadians(this._alpha),Xe.b.ToRadians(this._beta),-Xe.b.ToRadians(this._gamma),this.camera.rotationQuaternion),this._camera.rotationQuaternion.multiplyInPlace(this._screenQuaternion),this._camera.rotationQuaternion.multiplyInPlace(this._constantTranform),this._camera.rotationQuaternion.z*=-1,this._camera.rotationQuaternion.w*=-1)},r.prototype.getClassName=function(){return"FreeCameraDeviceOrientationInput"},r.prototype.getSimpleName=function(){return"deviceOrientation"},r}();hn.FreeCameraDeviceOrientationInput=os;var as=function(){function r(){this.gamepadAngularSensibility=200,this.gamepadMoveSensibility=40,this._yAxisScale=1,this._cameraTransform=u.a.Identity(),this._deltaTransform=u.e.Zero(),this._vector3=u.e.Zero(),this._vector2=u.d.Zero()}return Object.defineProperty(r.prototype,"invertYAxis",{get:function(){return this._yAxisScale!==1},set:function(t){this._yAxisScale=t?-1:1},enumerable:!1,configurable:!0}),r.prototype.attachControl=function(){var t=this,e=this.camera.getScene().gamepadManager;this._onGamepadConnectedObserver=e.onGamepadConnectedObservable.add(function(n){n.type!==dn.POSE_ENABLED&&(t.gamepad&&n.type!==dn.XBOX||(t.gamepad=n))}),this._onGamepadDisconnectedObserver=e.onGamepadDisconnectedObservable.add(function(n){t.gamepad===n&&(t.gamepad=null)}),this.gamepad=e.getGamepadByType(dn.XBOX),!this.gamepad&&e.gamepads.length&&(this.gamepad=e.gamepads[0])},r.prototype.detachControl=function(t){this.camera.getScene().gamepadManager.onGamepadConnectedObservable.remove(this._onGamepadConnectedObserver),this.camera.getScene().gamepadManager.onGamepadDisconnectedObservable.remove(this._onGamepadDisconnectedObserver),this.gamepad=null},r.prototype.checkInputs=function(){if(this.gamepad&&this.gamepad.leftStick){var t=this.camera,e=this.gamepad.leftStick,n=e.x/this.gamepadMoveSensibility,i=e.y/this.gamepadMoveSensibility;e.x=Math.abs(n)>.005?0+n:0,e.y=Math.abs(i)>.005?0+i:0;var o=this.gamepad.rightStick;if(o){var a=o.x/this.gamepadAngularSensibility,s=o.y/this.gamepadAngularSensibility*this._yAxisScale;o.x=Math.abs(a)>.001?0+a:0,o.y=Math.abs(s)>.001?0+s:0}else o={x:0,y:0};t.rotationQuaternion?t.rotationQuaternion.toRotationMatrix(this._cameraTransform):u.a.RotationYawPitchRollToRef(t.rotation.y,t.rotation.x,0,this._cameraTransform);var d=50*t._computeLocalCameraSpeed();this._vector3.copyFromFloats(e.x*d,0,-e.y*d),u.e.TransformCoordinatesToRef(this._vector3,this._cameraTransform,this._deltaTransform),t.cameraDirection.addInPlace(this._deltaTransform),this._vector2.copyFromFloats(o.y,o.x),t.cameraRotation.addInPlace(this._vector2)}},r.prototype.getClassName=function(){return"FreeCameraGamepadInput"},r.prototype.getSimpleName=function(){return"gamepad"},Object(c.c)([Object(L.c)()],r.prototype,"gamepadAngularSensibility",void 0),Object(c.c)([Object(L.c)()],r.prototype,"gamepadMoveSensibility",void 0),r}();hn.FreeCameraGamepadInput=as;var an,Sl=f(112);(function(r){r[r.X=0]="X",r[r.Y=1]="Y",r[r.Z=2]="Z"})(an||(an={}));var ss=function(){function r(t,e){var n=this,i=Object(c.a)(Object(c.a)({},r._GetDefaultOptions()),e);if(this._leftJoystick=!!t,r._globalJoystickIndex++,this._axisTargetedByLeftAndRight=an.X,this._axisTargetedByUpAndDown=an.Y,this.reverseLeftRight=!1,this.reverseUpDown=!1,this._touches=new Sl.a,this.deltaPosition=u.e.Zero(),this._joystickSensibility=25,this._inversedSensibility=1/(this._joystickSensibility/1e3),this._onResize=function(a){r.vjCanvasWidth=window.innerWidth,r.vjCanvasHeight=window.innerHeight,r.Canvas&&(r.Canvas.width=r.vjCanvasWidth,r.Canvas.height=r.vjCanvasHeight),r.halfWidth=r.vjCanvasWidth/2},!r.Canvas){window.addEventListener("resize",this._onResize,!1),r.Canvas=document.createElement("canvas"),r.vjCanvasWidth=window.innerWidth,r.vjCanvasHeight=window.innerHeight,r.Canvas.width=window.innerWidth,r.Canvas.height=window.innerHeight,r.Canvas.style.width="100%",r.Canvas.style.height="100%",r.Canvas.style.position="absolute",r.Canvas.style.backgroundColor="transparent",r.Canvas.style.top="0px",r.Canvas.style.left="0px",r.Canvas.style.zIndex="5",r.Canvas.style.msTouchAction="none",r.Canvas.style.touchAction="none",r.Canvas.setAttribute("touch-action","none");var o=r.Canvas.getContext("2d");if(!o)throw new Error("Unable to create canvas for virtual joystick");r.vjCanvasContext=o,r.vjCanvasContext.strokeStyle="#ffffff",r.vjCanvasContext.lineWidth=2,document.body.appendChild(r.Canvas)}r.halfWidth=r.Canvas.width/2,this.pressed=!1,this.limitToContainer=i.limitToContainer,this._joystickColor=i.color,this.containerSize=i.containerSize,this.puckSize=i.puckSize,i.position&&this.setPosition(i.position.x,i.position.y),i.puckImage&&this.setPuckImage(i.puckImage),i.containerImage&&this.setContainerImage(i.containerImage),i.alwaysVisible&&r._alwaysVisibleSticks++,this.alwaysVisible=i.alwaysVisible,this._joystickPointerID=-1,this._joystickPointerPos=new u.d(0,0),this._joystickPreviousPointerPos=new u.d(0,0),this._joystickPointerStartPos=new u.d(0,0),this._deltaJoystickVector=new u.d(0,0),this._onPointerDownHandlerRef=function(a){n._onPointerDown(a)},this._onPointerMoveHandlerRef=function(a){n._onPointerMove(a)},this._onPointerUpHandlerRef=function(a){n._onPointerUp(a)},r.Canvas.addEventListener("pointerdown",this._onPointerDownHandlerRef,!1),r.Canvas.addEventListener("pointermove",this._onPointerMoveHandlerRef,!1),r.Canvas.addEventListener("pointerup",this._onPointerUpHandlerRef,!1),r.Canvas.addEventListener("pointerout",this._onPointerUpHandlerRef,!1),r.Canvas.addEventListener("contextmenu",function(a){a.preventDefault()},!1),requestAnimationFrame(function(){n._drawVirtualJoystick()})}return r._GetDefaultOptions=function(){return{puckSize:40,containerSize:60,color:"cyan",puckImage:void 0,containerImage:void 0,position:void 0,alwaysVisible:!1,limitToContainer:!1}},r.prototype.setJoystickSensibility=function(t){this._joystickSensibility=t,this._inversedSensibility=1/(this._joystickSensibility/1e3)},r.prototype._onPointerDown=function(t){t.preventDefault(),(this._leftJoystick===!0?t.clientX<r.halfWidth:t.clientX>r.halfWidth)&&this._joystickPointerID<0?(this._joystickPointerID=t.pointerId,this._joystickPosition?(this._joystickPointerStartPos=this._joystickPosition.clone(),this._joystickPointerPos=this._joystickPosition.clone(),this._joystickPreviousPointerPos=this._joystickPosition.clone(),this._onPointerMove(t)):(this._joystickPointerStartPos.x=t.clientX,this._joystickPointerStartPos.y=t.clientY,this._joystickPointerPos=this._joystickPointerStartPos.clone(),this._joystickPreviousPointerPos=this._joystickPointerStartPos.clone()),this._deltaJoystickVector.x=0,this._deltaJoystickVector.y=0,this.pressed=!0,this._touches.add(t.pointerId.toString(),t)):r._globalJoystickIndex<2&&this._action&&(this._action(),this._touches.add(t.pointerId.toString(),{x:t.clientX,y:t.clientY,prevX:t.clientX,prevY:t.clientY}))},r.prototype._onPointerMove=function(t){if(this._joystickPointerID==t.pointerId){if(this.limitToContainer){var e=new u.d(t.clientX-this._joystickPointerStartPos.x,t.clientY-this._joystickPointerStartPos.y),n=e.length();n>this.containerSize&&e.scaleInPlace(this.containerSize/n),this._joystickPointerPos.x=this._joystickPointerStartPos.x+e.x,this._joystickPointerPos.y=this._joystickPointerStartPos.y+e.y}else this._joystickPointerPos.x=t.clientX,this._joystickPointerPos.y=t.clientY;this._deltaJoystickVector=this._joystickPointerPos.clone(),this._deltaJoystickVector=this._deltaJoystickVector.subtract(this._joystickPointerStartPos),0<r._alwaysVisibleSticks&&(this._leftJoystick?this._joystickPointerPos.x=Math.min(r.halfWidth,this._joystickPointerPos.x):this._joystickPointerPos.x=Math.max(r.halfWidth,this._joystickPointerPos.x));var i=(this.reverseLeftRight?-1:1)*this._deltaJoystickVector.x/this._inversedSensibility;switch(this._axisTargetedByLeftAndRight){case an.X:this.deltaPosition.x=Math.min(1,Math.max(-1,i));break;case an.Y:this.deltaPosition.y=Math.min(1,Math.max(-1,i));break;case an.Z:this.deltaPosition.z=Math.min(1,Math.max(-1,i))}var o=(this.reverseUpDown?1:-1)*this._deltaJoystickVector.y/this._inversedSensibility;switch(this._axisTargetedByUpAndDown){case an.X:this.deltaPosition.x=Math.min(1,Math.max(-1,o));break;case an.Y:this.deltaPosition.y=Math.min(1,Math.max(-1,o));break;case an.Z:this.deltaPosition.z=Math.min(1,Math.max(-1,o))}}else{var a=this._touches.get(t.pointerId.toString());a&&(a.x=t.clientX,a.y=t.clientY)}},r.prototype._onPointerUp=function(t){if(this._joystickPointerID==t.pointerId)this._clearPreviousDraw(),this._joystickPointerID=-1,this.pressed=!1;else{var e=this._touches.get(t.pointerId.toString());e&&r.vjCanvasContext.clearRect(e.prevX-44,e.prevY-44,88,88)}this._deltaJoystickVector.x=0,this._deltaJoystickVector.y=0,this._touches.remove(t.pointerId.toString())},r.prototype.setJoystickColor=function(t){this._joystickColor=t},Object.defineProperty(r.prototype,"containerSize",{get:function(){return this._joystickContainerSize},set:function(t){this._joystickContainerSize=t,this._clearContainerSize=~~(2.1*this._joystickContainerSize),this._clearContainerSizeOffset=~~(this._clearContainerSize/2)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"puckSize",{get:function(){return this._joystickPuckSize},set:function(t){this._joystickPuckSize=t,this._clearPuckSize=~~(2.1*this._joystickPuckSize),this._clearPuckSizeOffset=~~(this._clearPuckSize/2)},enumerable:!1,configurable:!0}),r.prototype.clearPosition=function(){this.alwaysVisible=!1,this._joystickPosition=null},Object.defineProperty(r.prototype,"alwaysVisible",{get:function(){return this._alwaysVisible},set:function(t){this._alwaysVisible!==t&&(t&&this._joystickPosition?(r._alwaysVisibleSticks++,this._alwaysVisible=!0):(r._alwaysVisibleSticks--,this._alwaysVisible=!1))},enumerable:!1,configurable:!0}),r.prototype.setPosition=function(t,e){this._joystickPointerStartPos&&this._clearPreviousDraw(),this._joystickPosition=new u.d(t,e)},r.prototype.setActionOnTouch=function(t){this._action=t},r.prototype.setAxisForLeftRight=function(t){switch(t){case an.X:case an.Y:case an.Z:this._axisTargetedByLeftAndRight=t;break;default:this._axisTargetedByLeftAndRight=an.X}},r.prototype.setAxisForUpDown=function(t){switch(t){case an.X:case an.Y:case an.Z:this._axisTargetedByUpAndDown=t;break;default:this._axisTargetedByUpAndDown=an.Y}},r.prototype._clearPreviousDraw=function(){var t=this._joystickPosition||this._joystickPointerStartPos;r.vjCanvasContext.clearRect(t.x-this._clearContainerSizeOffset,t.y-this._clearContainerSizeOffset,this._clearContainerSize,this._clearContainerSize),r.vjCanvasContext.clearRect(this._joystickPreviousPointerPos.x-this._clearPuckSizeOffset,this._joystickPreviousPointerPos.y-this._clearPuckSizeOffset,this._clearPuckSize,this._clearPuckSize)},r.prototype.setContainerImage=function(t){var e=this,n=new Image;n.src=t,n.onload=function(){return e._containerImage=n}},r.prototype.setPuckImage=function(t){var e=this,n=new Image;n.src=t,n.onload=function(){return e._puckImage=n}},r.prototype._drawContainer=function(){var t=this._joystickPosition||this._joystickPointerStartPos;this._clearPreviousDraw(),this._containerImage?r.vjCanvasContext.drawImage(this._containerImage,t.x-this.containerSize,t.y-this.containerSize,2*this.containerSize,2*this.containerSize):(r.vjCanvasContext.beginPath(),r.vjCanvasContext.strokeStyle=this._joystickColor,r.vjCanvasContext.lineWidth=2,r.vjCanvasContext.arc(t.x,t.y,this.containerSize,0,2*Math.PI,!0),r.vjCanvasContext.stroke(),r.vjCanvasContext.closePath(),r.vjCanvasContext.beginPath(),r.vjCanvasContext.lineWidth=6,r.vjCanvasContext.strokeStyle=this._joystickColor,r.vjCanvasContext.arc(t.x,t.y,this.puckSize,0,2*Math.PI,!0),r.vjCanvasContext.stroke(),r.vjCanvasContext.closePath())},r.prototype._drawPuck=function(){this._puckImage?r.vjCanvasContext.drawImage(this._puckImage,this._joystickPointerPos.x-this.puckSize,this._joystickPointerPos.y-this.puckSize,2*this.puckSize,2*this.puckSize):(r.vjCanvasContext.beginPath(),r.vjCanvasContext.strokeStyle=this._joystickColor,r.vjCanvasContext.lineWidth=2,r.vjCanvasContext.arc(this._joystickPointerPos.x,this._joystickPointerPos.y,this.puckSize,0,2*Math.PI,!0),r.vjCanvasContext.stroke(),r.vjCanvasContext.closePath())},r.prototype._drawVirtualJoystick=function(){var t=this;this.alwaysVisible&&this._drawContainer(),this.pressed&&this._touches.forEach(function(e,n){n.pointerId===t._joystickPointerID?(t.alwaysVisible||t._drawContainer(),t._drawPuck(),t._joystickPreviousPointerPos=t._joystickPointerPos.clone()):(r.vjCanvasContext.clearRect(n.prevX-44,n.prevY-44,88,88),r.vjCanvasContext.beginPath(),r.vjCanvasContext.fillStyle="white",r.vjCanvasContext.beginPath(),r.vjCanvasContext.strokeStyle="red",r.vjCanvasContext.lineWidth=6,r.vjCanvasContext.arc(n.x,n.y,40,0,2*Math.PI,!0),r.vjCanvasContext.stroke(),r.vjCanvasContext.closePath(),n.prevX=n.x,n.prevY=n.y)}),requestAnimationFrame(function(){t._drawVirtualJoystick()})},r.prototype.releaseCanvas=function(){r.Canvas&&(r.Canvas.removeEventListener("pointerdown",this._onPointerDownHandlerRef),r.Canvas.removeEventListener("pointermove",this._onPointerMoveHandlerRef),r.Canvas.removeEventListener("pointerup",this._onPointerUpHandlerRef),r.Canvas.removeEventListener("pointerout",this._onPointerUpHandlerRef),window.removeEventListener("resize",this._onResize),document.body.removeChild(r.Canvas),r.Canvas=null)},r._globalJoystickIndex=0,r._alwaysVisibleSticks=0,r}();eo.prototype.addVirtualJoystick=function(){return this.add(new cs),this};var cs=function(){function r(){}return r.prototype.getLeftJoystick=function(){return this._leftjoystick},r.prototype.getRightJoystick=function(){return this._rightjoystick},r.prototype.checkInputs=function(){if(this._leftjoystick){var t=this.camera,e=50*t._computeLocalCameraSpeed(),n=u.a.RotationYawPitchRoll(t.rotation.y,t.rotation.x,0),i=u.e.TransformCoordinates(new u.e(this._leftjoystick.deltaPosition.x*e,this._leftjoystick.deltaPosition.y*e,this._leftjoystick.deltaPosition.z*e),n);t.cameraDirection=t.cameraDirection.add(i),t.cameraRotation=t.cameraRotation.addVector3(this._rightjoystick.deltaPosition),this._leftjoystick.pressed||(this._leftjoystick.deltaPosition=this._leftjoystick.deltaPosition.scale(.9)),this._rightjoystick.pressed||(this._rightjoystick.deltaPosition=this._rightjoystick.deltaPosition.scale(.9))}},r.prototype.attachControl=function(){this._leftjoystick=new ss(!0),this._leftjoystick.setAxisForUpDown(an.Z),this._leftjoystick.setAxisForLeftRight(an.X),this._leftjoystick.setJoystickSensibility(.15),this._rightjoystick=new ss(!1),this._rightjoystick.setAxisForUpDown(an.X),this._rightjoystick.setAxisForLeftRight(an.Y),this._rightjoystick.reverseUpDown=!0,this._rightjoystick.setJoystickSensibility(.05),this._rightjoystick.setJoystickColor("yellow")},r.prototype.detachControl=function(t){this._leftjoystick.releaseCanvas(),this._rightjoystick.releaseCanvas()},r.prototype.getClassName=function(){return"FreeCameraVirtualJoystickInput"},r.prototype.getSimpleName=function(){return"virtualJoystick"},r}();hn.FreeCameraVirtualJoystickInput=cs;var Gt=f(28),Ni=function(r){function t(e,n,i,o){o===void 0&&(o=!0);var a=r.call(this,e,n,i,o)||this;return a._tmpUpVector=u.e.Zero(),a._tmpTargetVector=u.e.Zero(),a.cameraDirection=new u.e(0,0,0),a.cameraRotation=new u.d(0,0),a.ignoreParentScaling=!1,a.updateUpVectorFromRotation=!1,a._tmpQuaternion=new u.b,a.rotation=new u.e(0,0,0),a.speed=2,a.noRotationConstraint=!1,a.invertRotation=!1,a.inverseRotationSpeed=.2,a.lockedTarget=null,a._currentTarget=u.e.Zero(),a._initialFocalDistance=1,a._viewMatrix=u.a.Zero(),a._camMatrix=u.a.Zero(),a._cameraTransformMatrix=u.a.Zero(),a._cameraRotationMatrix=u.a.Zero(),a._referencePoint=new u.e(0,0,1),a._transformedReferencePoint=u.e.Zero(),a._defaultUp=u.e.Up(),a._cachedRotationZ=0,a._cachedQuaternionRotationZ=0,a}return Object(c.d)(t,r),t.prototype.getFrontPosition=function(e){this.getWorldMatrix();var n=this.getTarget().subtract(this.position);return n.normalize(),n.scaleInPlace(e),this.globalPosition.add(n)},t.prototype._getLockedTargetPosition=function(){return this.lockedTarget?(this.lockedTarget.absolutePosition&&this.lockedTarget.computeWorldMatrix(),this.lockedTarget.absolutePosition||this.lockedTarget):null},t.prototype.storeState=function(){return this._storedPosition=this.position.clone(),this._storedRotation=this.rotation.clone(),this.rotationQuaternion&&(this._storedRotationQuaternion=this.rotationQuaternion.clone()),r.prototype.storeState.call(this)},t.prototype._restoreStateValues=function(){return!!r.prototype._restoreStateValues.call(this)&&(this.position=this._storedPosition.clone(),this.rotation=this._storedRotation.clone(),this.rotationQuaternion&&(this.rotationQuaternion=this._storedRotationQuaternion.clone()),this.cameraDirection.copyFromFloats(0,0,0),this.cameraRotation.copyFromFloats(0,0),!0)},t.prototype._initCache=function(){r.prototype._initCache.call(this),this._cache.lockedTarget=new u.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._cache.rotation=new u.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._cache.rotationQuaternion=new u.b(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE)},t.prototype._updateCache=function(e){e||r.prototype._updateCache.call(this);var n=this._getLockedTargetPosition();n?this._cache.lockedTarget?this._cache.lockedTarget.copyFrom(n):this._cache.lockedTarget=n.clone():this._cache.lockedTarget=null,this._cache.rotation.copyFrom(this.rotation),this.rotationQuaternion&&this._cache.rotationQuaternion.copyFrom(this.rotationQuaternion)},t.prototype._isSynchronizedViewMatrix=function(){if(!r.prototype._isSynchronizedViewMatrix.call(this))return!1;var e=this._getLockedTargetPosition();return(this._cache.lockedTarget?this._cache.lockedTarget.equals(e):!e)&&(this.rotationQuaternion?this.rotationQuaternion.equals(this._cache.rotationQuaternion):this._cache.rotation.equals(this.rotation))},t.prototype._computeLocalCameraSpeed=function(){var e=this.getEngine();return this.speed*Math.sqrt(e.getDeltaTime()/(100*e.getFps()))},t.prototype.setTarget=function(e){this.upVector.normalize(),this._initialFocalDistance=e.subtract(this.position).length(),this.position.z===e.z&&(this.position.z+=Gt.a),this._referencePoint.normalize().scaleInPlace(this._initialFocalDistance),u.a.LookAtLHToRef(this.position,e,this._defaultUp,this._camMatrix),this._camMatrix.invert(),this.rotation.x=Math.atan(this._camMatrix.m[6]/this._camMatrix.m[10]);var n=e.subtract(this.position);n.x>=0?this.rotation.y=-Math.atan(n.z/n.x)+Math.PI/2:this.rotation.y=-Math.atan(n.z/n.x)-Math.PI/2,this.rotation.z=0,isNaN(this.rotation.x)&&(this.rotation.x=0),isNaN(this.rotation.y)&&(this.rotation.y=0),isNaN(this.rotation.z)&&(this.rotation.z=0),this.rotationQuaternion&&u.b.RotationYawPitchRollToRef(this.rotation.y,this.rotation.x,this.rotation.z,this.rotationQuaternion)},Object.defineProperty(t.prototype,"target",{get:function(){return this.getTarget()},set:function(e){this.setTarget(e)},enumerable:!1,configurable:!0}),t.prototype.getTarget=function(){return this._currentTarget},t.prototype._decideIfNeedsToMove=function(){return Math.abs(this.cameraDirection.x)>0||Math.abs(this.cameraDirection.y)>0||Math.abs(this.cameraDirection.z)>0},t.prototype._updatePosition=function(){if(this.parent)return this.parent.getWorldMatrix().invertToRef(u.c.Matrix[0]),u.e.TransformNormalToRef(this.cameraDirection,u.c.Matrix[0],u.c.Vector3[0]),void this.position.addInPlace(u.c.Vector3[0]);this.position.addInPlace(this.cameraDirection)},t.prototype._checkInputs=function(){var e=this.invertRotation?-this.inverseRotationSpeed:1,n=this._decideIfNeedsToMove(),i=Math.abs(this.cameraRotation.x)>0||Math.abs(this.cameraRotation.y)>0;n&&this._updatePosition(),i&&(this.rotationQuaternion&&this.rotationQuaternion.toEulerAnglesToRef(this.rotation),this.rotation.x+=this.cameraRotation.x*e,this.rotation.y+=this.cameraRotation.y*e,!this.noRotationConstraint&&(this.rotation.x>1.570796&&(this.rotation.x=1.570796),this.rotation.x<-1.570796&&(this.rotation.x=-1.570796)),this.rotationQuaternion&&this.rotation.lengthSquared()&&u.b.RotationYawPitchRollToRef(this.rotation.y,this.rotation.x,this.rotation.z,this.rotationQuaternion)),n&&(Math.abs(this.cameraDirection.x)<this.speed*Gt.a&&(this.cameraDirection.x=0),Math.abs(this.cameraDirection.y)<this.speed*Gt.a&&(this.cameraDirection.y=0),Math.abs(this.cameraDirection.z)<this.speed*Gt.a&&(this.cameraDirection.z=0),this.cameraDirection.scaleInPlace(this.inertia)),i&&(Math.abs(this.cameraRotation.x)<this.speed*Gt.a&&(this.cameraRotation.x=0),Math.abs(this.cameraRotation.y)<this.speed*Gt.a&&(this.cameraRotation.y=0),this.cameraRotation.scaleInPlace(this.inertia)),r.prototype._checkInputs.call(this)},t.prototype._updateCameraRotationMatrix=function(){this.rotationQuaternion?this.rotationQuaternion.toRotationMatrix(this._cameraRotationMatrix):u.a.RotationYawPitchRollToRef(this.rotation.y,this.rotation.x,this.rotation.z,this._cameraRotationMatrix)},t.prototype._rotateUpVectorWithCameraRotationMatrix=function(){return u.e.TransformNormalToRef(this._defaultUp,this._cameraRotationMatrix,this.upVector),this},t.prototype._getViewMatrix=function(){return this.lockedTarget&&this.setTarget(this._getLockedTargetPosition()),this._updateCameraRotationMatrix(),this.rotationQuaternion&&this._cachedQuaternionRotationZ!=this.rotationQuaternion.z?(this._rotateUpVectorWithCameraRotationMatrix(),this._cachedQuaternionRotationZ=this.rotationQuaternion.z):this._cachedRotationZ!=this.rotation.z&&(this._rotateUpVectorWithCameraRotationMatrix(),this._cachedRotationZ=this.rotation.z),u.e.TransformCoordinatesToRef(this._referencePoint,this._cameraRotationMatrix,this._transformedReferencePoint),this.position.addToRef(this._transformedReferencePoint,this._currentTarget),this.updateUpVectorFromRotation&&(this.rotationQuaternion?ye.a.Y.rotateByQuaternionToRef(this.rotationQuaternion,this.upVector):(u.b.FromEulerVectorToRef(this.rotation,this._tmpQuaternion),ye.a.Y.rotateByQuaternionToRef(this._tmpQuaternion,this.upVector))),this._computeViewMatrix(this.position,this._currentTarget,this.upVector),this._viewMatrix},t.prototype._computeViewMatrix=function(e,n,i){if(this.ignoreParentScaling){if(this.parent){var o=this.parent.getWorldMatrix();u.e.TransformCoordinatesToRef(e,o,this._globalPosition),u.e.TransformCoordinatesToRef(n,o,this._tmpTargetVector),u.e.TransformNormalToRef(i,o,this._tmpUpVector),this._markSyncedWithParent()}else this._globalPosition.copyFrom(e),this._tmpTargetVector.copyFrom(n),this._tmpUpVector.copyFrom(i);this.getScene().useRightHandedSystem?u.a.LookAtRHToRef(this._globalPosition,this._tmpTargetVector,this._tmpUpVector,this._viewMatrix):u.a.LookAtLHToRef(this._globalPosition,this._tmpTargetVector,this._tmpUpVector,this._viewMatrix)}else this.getScene().useRightHandedSystem?u.a.LookAtRHToRef(e,n,i,this._viewMatrix):u.a.LookAtLHToRef(e,n,i,this._viewMatrix),this.parent?(o=this.parent.getWorldMatrix(),this._viewMatrix.invert(),this._viewMatrix.multiplyToRef(o,this._viewMatrix),this._viewMatrix.getTranslationToRef(this._globalPosition),this._viewMatrix.invert(),this._markSyncedWithParent()):this._globalPosition.copyFrom(e)},t.prototype.createRigCamera=function(e,n){if(this.cameraRigMode!==gt.a.RIG_MODE_NONE){var i=new t(e,this.position.clone(),this.getScene());return i.isRigCamera=!0,i.rigParent=this,this.cameraRigMode!==gt.a.RIG_MODE_VR&&this.cameraRigMode!==gt.a.RIG_MODE_WEBVR||(this.rotationQuaternion||(this.rotationQuaternion=new u.b),i._cameraRigParams={},i.rotationQuaternion=new u.b),i}return null},t.prototype._updateRigCameras=function(){var e=this._rigCameras[0],n=this._rigCameras[1];switch(this.computeWorldMatrix(),this.cameraRigMode){case gt.a.RIG_MODE_STEREOSCOPIC_ANAGLYPH:case gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:case gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED:case gt.a.RIG_MODE_STEREOSCOPIC_OVERUNDER:case gt.a.RIG_MODE_STEREOSCOPIC_INTERLACED:var i=this.cameraRigMode===gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED?1:-1,o=this.cameraRigMode===gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED?-1:1;this._getRigCamPositionAndTarget(this._cameraRigParams.stereoHalfAngle*i,e),this._getRigCamPositionAndTarget(this._cameraRigParams.stereoHalfAngle*o,n);break;case gt.a.RIG_MODE_VR:e.rotationQuaternion?(e.rotationQuaternion.copyFrom(this.rotationQuaternion),n.rotationQuaternion.copyFrom(this.rotationQuaternion)):(e.rotation.copyFrom(this.rotation),n.rotation.copyFrom(this.rotation)),e.position.copyFrom(this.position),n.position.copyFrom(this.position)}r.prototype._updateRigCameras.call(this)},t.prototype._getRigCamPositionAndTarget=function(e,n){this.getTarget().subtractToRef(this.position,t._TargetFocalPoint),t._TargetFocalPoint.normalize().scaleInPlace(this._initialFocalDistance);var i=t._TargetFocalPoint.addInPlace(this.position);u.a.TranslationToRef(-i.x,-i.y,-i.z,t._TargetTransformMatrix),t._TargetTransformMatrix.multiplyToRef(u.a.RotationAxis(n.upVector,e),t._RigCamTransformMatrix),u.a.TranslationToRef(i.x,i.y,i.z,t._TargetTransformMatrix),t._RigCamTransformMatrix.multiplyToRef(t._TargetTransformMatrix,t._RigCamTransformMatrix),u.e.TransformCoordinatesToRef(this.position,t._RigCamTransformMatrix,n.position),n.setTarget(i)},t.prototype.getClassName=function(){return"TargetCamera"},t._RigCamTransformMatrix=new u.a,t._TargetTransformMatrix=new u.a,t._TargetFocalPoint=new u.e,Object(c.c)([Object(L.o)()],t.prototype,"rotation",void 0),Object(c.c)([Object(L.c)()],t.prototype,"speed",void 0),Object(c.c)([Object(L.k)("lockedTargetId")],t.prototype,"lockedTarget",void 0),t}(gt.a),Yn=function(r){function t(e,n,i,o){o===void 0&&(o=!0);var a=r.call(this,e,n,i,o)||this;return a.ellipsoid=new u.e(.5,1,.5),a.ellipsoidOffset=new u.e(0,0,0),a.checkCollisions=!1,a.applyGravity=!1,a._needMoveForGravity=!1,a._oldPosition=u.e.Zero(),a._diffPosition=u.e.Zero(),a._newPosition=u.e.Zero(),a._collisionMask=-1,a._onCollisionPositionChange=function(s,d,p){p===void 0&&(p=null);var b;b=d,a._newPosition.copyFrom(b),a._newPosition.subtractToRef(a._oldPosition,a._diffPosition),a._diffPosition.length()>Ue.a.CollisionsEpsilon&&(a.position.addInPlace(a._diffPosition),a.onCollide&&p&&a.onCollide(p))},a.inputs=new eo(a),a.inputs.addKeyboard().addMouse(),a}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"angularSensibility",{get:function(){var e=this.inputs.attached.mouse;return e?e.angularSensibility:0},set:function(e){var n=this.inputs.attached.mouse;n&&(n.angularSensibility=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysUp",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysUp:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysUp=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysUpward",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysUpward:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysUpward=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysDown",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysDown:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysDown=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysDownward",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysDownward:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysDownward=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysLeft",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysLeft:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysLeft=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysRight",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysRight:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysRight=e)},enumerable:!1,configurable:!0}),t.prototype.attachControl=function(e,n){n=Xe.b.BackCompatCameraNoPreventDefault(arguments),this.inputs.attachElement(n)},t.prototype.detachControl=function(e){this.inputs.detachElement(),this.cameraDirection=new u.e(0,0,0),this.cameraRotation=new u.d(0,0)},Object.defineProperty(t.prototype,"collisionMask",{get:function(){return this._collisionMask},set:function(e){this._collisionMask=isNaN(e)?-1:e},enumerable:!1,configurable:!0}),t.prototype._collideWithWorld=function(e){(this.parent?u.e.TransformCoordinates(this.position,this.parent.getWorldMatrix()):this.position).subtractFromFloatsToRef(0,this.ellipsoid.y,0,this._oldPosition),this._oldPosition.addInPlace(this.ellipsoidOffset);var n=this.getScene().collisionCoordinator;this._collider||(this._collider=n.createCollider()),this._collider._radius=this.ellipsoid,this._collider.collisionMask=this._collisionMask;var i=e;this.applyGravity&&(i=e.add(this.getScene().gravity)),n.getNewPosition(this._oldPosition,i,this._collider,3,null,this._onCollisionPositionChange,this.uniqueId)},t.prototype._checkInputs=function(){this._localDirection||(this._localDirection=u.e.Zero(),this._transformedDirection=u.e.Zero()),this.inputs.checkInputs(),r.prototype._checkInputs.call(this)},t.prototype._decideIfNeedsToMove=function(){return this._needMoveForGravity||Math.abs(this.cameraDirection.x)>0||Math.abs(this.cameraDirection.y)>0||Math.abs(this.cameraDirection.z)>0},t.prototype._updatePosition=function(){this.checkCollisions&&this.getScene().collisionsEnabled?this._collideWithWorld(this.cameraDirection):r.prototype._updatePosition.call(this)},t.prototype.dispose=function(){this.inputs.clear(),r.prototype.dispose.call(this)},t.prototype.getClassName=function(){return"FreeCamera"},Object(c.c)([Object(L.o)()],t.prototype,"ellipsoid",void 0),Object(c.c)([Object(L.o)()],t.prototype,"ellipsoidOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"checkCollisions",void 0),Object(c.c)([Object(L.c)()],t.prototype,"applyGravity",void 0),t}(Ni);Q.a.AddNodeConstructor("TouchCamera",function(r,t){return function(){return new ls(r,u.e.Zero(),t)}});var ls=function(r){function t(e,n,i){var o=r.call(this,e,n,i)||this;return o.inputs.addTouch(),o._setupInputs(),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"touchAngularSensibility",{get:function(){var e=this.inputs.attached.touch;return e?e.touchAngularSensibility:0},set:function(e){var n=this.inputs.attached.touch;n&&(n.touchAngularSensibility=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"touchMoveSensibility",{get:function(){var e=this.inputs.attached.touch;return e?e.touchMoveSensibility:0},set:function(e){var n=this.inputs.attached.touch;n&&(n.touchMoveSensibility=e)},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"TouchCamera"},t.prototype._setupInputs=function(){var e=this.inputs.attached.touch,n=this.inputs.attached.mouse;n?n.touchEnabled=!1:e.allowMouse=!0},t}(Yn);Q.a.AddNodeConstructor("ArcRotateCamera",function(r,t){return function(){return new Ji(r,0,0,1,u.e.Zero(),t)}});var Ji=function(r){function t(e,n,i,o,a,s,d){d===void 0&&(d=!0);var p=r.call(this,e,u.e.Zero(),s,d)||this;return p.inertialAlphaOffset=0,p.inertialBetaOffset=0,p.inertialRadiusOffset=0,p.lowerAlphaLimit=null,p.upperAlphaLimit=null,p.lowerBetaLimit=.01,p.upperBetaLimit=Math.PI-.01,p.lowerRadiusLimit=null,p.upperRadiusLimit=null,p.inertialPanningX=0,p.inertialPanningY=0,p.pinchToPanMaxDistance=20,p.panningDistanceLimit=null,p.panningOriginTarget=u.e.Zero(),p.panningInertia=.9,p.zoomOnFactor=1,p.targetScreenOffset=u.d.Zero(),p.allowUpsideDown=!0,p.useInputToRestoreState=!0,p._viewMatrix=new u.a,p.panningAxis=new u.e(1,1,0),p.onMeshTargetChangedObservable=new C.c,p.checkCollisions=!1,p.collisionRadius=new u.e(.5,.5,.5),p._previousPosition=u.e.Zero(),p._collisionVelocity=u.e.Zero(),p._newPosition=u.e.Zero(),p._computationVector=u.e.Zero(),p._onCollisionPositionChange=function(b,P,O){O===void 0&&(O=null),O?(p.setPosition(P),p.onCollide&&p.onCollide(O)):p._previousPosition.copyFrom(p._position);var B=Math.cos(p.alpha),F=Math.sin(p.alpha),z=Math.cos(p.beta),J=Math.sin(p.beta);J===0&&(J=1e-4);var ie=p._getTargetPosition();p._computationVector.copyFromFloats(p.radius*B*J,p.radius*z,p.radius*F*J),ie.addToRef(p._computationVector,p._newPosition),p._position.copyFrom(p._newPosition);var se=p.upVector;p.allowUpsideDown&&p.beta<0&&(se=(se=se.clone()).negate()),p._computeViewMatrix(p._position,ie,se),p._viewMatrix.addAtIndex(12,p.targetScreenOffset.x),p._viewMatrix.addAtIndex(13,p.targetScreenOffset.y),p._collisionTriggered=!1},p._target=u.e.Zero(),a&&p.setTarget(a),p.alpha=n,p.beta=i,p.radius=o,p.getViewMatrix(),p.inputs=new wo(p),p.inputs.addKeyboard().addMouseWheel().addPointers(),p}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"target",{get:function(){return this._target},set:function(e){this.setTarget(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"position",{get:function(){return this._position},set:function(e){this.setPosition(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"upVector",{get:function(){return this._upVector},set:function(e){this._upToYMatrix||(this._YToUpMatrix=new u.a,this._upToYMatrix=new u.a,this._upVector=u.e.Zero()),e.normalize(),this._upVector.copyFrom(e),this.setMatUp()},enumerable:!1,configurable:!0}),t.prototype.setMatUp=function(){u.a.RotationAlignToRef(u.e.UpReadOnly,this._upVector,this._YToUpMatrix),u.a.RotationAlignToRef(this._upVector,u.e.UpReadOnly,this._upToYMatrix)},Object.defineProperty(t.prototype,"angularSensibilityX",{get:function(){var e=this.inputs.attached.pointers;return e?e.angularSensibilityX:0},set:function(e){var n=this.inputs.attached.pointers;n&&(n.angularSensibilityX=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"angularSensibilityY",{get:function(){var e=this.inputs.attached.pointers;return e?e.angularSensibilityY:0},set:function(e){var n=this.inputs.attached.pointers;n&&(n.angularSensibilityY=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"pinchPrecision",{get:function(){var e=this.inputs.attached.pointers;return e?e.pinchPrecision:0},set:function(e){var n=this.inputs.attached.pointers;n&&(n.pinchPrecision=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"pinchDeltaPercentage",{get:function(){var e=this.inputs.attached.pointers;return e?e.pinchDeltaPercentage:0},set:function(e){var n=this.inputs.attached.pointers;n&&(n.pinchDeltaPercentage=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"useNaturalPinchZoom",{get:function(){var e=this.inputs.attached.pointers;return!!e&&e.useNaturalPinchZoom},set:function(e){var n=this.inputs.attached.pointers;n&&(n.useNaturalPinchZoom=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"panningSensibility",{get:function(){var e=this.inputs.attached.pointers;return e?e.panningSensibility:0},set:function(e){var n=this.inputs.attached.pointers;n&&(n.panningSensibility=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysUp",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysUp:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysUp=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysDown",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysDown:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysDown=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysLeft",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysLeft:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysLeft=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysRight",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysRight:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysRight=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelPrecision",{get:function(){var e=this.inputs.attached.mousewheel;return e?e.wheelPrecision:0},set:function(e){var n=this.inputs.attached.mousewheel;n&&(n.wheelPrecision=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wheelDeltaPercentage",{get:function(){var e=this.inputs.attached.mousewheel;return e?e.wheelDeltaPercentage:0},set:function(e){var n=this.inputs.attached.mousewheel;n&&(n.wheelDeltaPercentage=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"bouncingBehavior",{get:function(){return this._bouncingBehavior},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"useBouncingBehavior",{get:function(){return this._bouncingBehavior!=null},set:function(e){e!==this.useBouncingBehavior&&(e?(this._bouncingBehavior=new _l,this.addBehavior(this._bouncingBehavior)):this._bouncingBehavior&&(this.removeBehavior(this._bouncingBehavior),this._bouncingBehavior=null))},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"framingBehavior",{get:function(){return this._framingBehavior},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"useFramingBehavior",{get:function(){return this._framingBehavior!=null},set:function(e){e!==this.useFramingBehavior&&(e?(this._framingBehavior=new ml,this.addBehavior(this._framingBehavior)):this._framingBehavior&&(this.removeBehavior(this._framingBehavior),this._framingBehavior=null))},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"autoRotationBehavior",{get:function(){return this._autoRotationBehavior},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"useAutoRotationBehavior",{get:function(){return this._autoRotationBehavior!=null},set:function(e){e!==this.useAutoRotationBehavior&&(e?(this._autoRotationBehavior=new pl,this.addBehavior(this._autoRotationBehavior)):this._autoRotationBehavior&&(this.removeBehavior(this._autoRotationBehavior),this._autoRotationBehavior=null))},enumerable:!1,configurable:!0}),t.prototype._initCache=function(){r.prototype._initCache.call(this),this._cache._target=new u.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._cache.alpha=void 0,this._cache.beta=void 0,this._cache.radius=void 0,this._cache.targetScreenOffset=u.d.Zero()},t.prototype._updateCache=function(e){e||r.prototype._updateCache.call(this),this._cache._target.copyFrom(this._getTargetPosition()),this._cache.alpha=this.alpha,this._cache.beta=this.beta,this._cache.radius=this.radius,this._cache.targetScreenOffset.copyFrom(this.targetScreenOffset)},t.prototype._getTargetPosition=function(){if(this._targetHost&&this._targetHost.getAbsolutePosition){var e=this._targetHost.absolutePosition;this._targetBoundingCenter?e.addToRef(this._targetBoundingCenter,this._target):this._target.copyFrom(e)}var n=this._getLockedTargetPosition();return n||this._target},t.prototype.storeState=function(){return this._storedAlpha=this.alpha,this._storedBeta=this.beta,this._storedRadius=this.radius,this._storedTarget=this._getTargetPosition().clone(),this._storedTargetScreenOffset=this.targetScreenOffset.clone(),r.prototype.storeState.call(this)},t.prototype._restoreStateValues=function(){return!!r.prototype._restoreStateValues.call(this)&&(this.setTarget(this._storedTarget.clone()),this.alpha=this._storedAlpha,this.beta=this._storedBeta,this.radius=this._storedRadius,this.targetScreenOffset=this._storedTargetScreenOffset.clone(),this.inertialAlphaOffset=0,this.inertialBetaOffset=0,this.inertialRadiusOffset=0,this.inertialPanningX=0,this.inertialPanningY=0,!0)},t.prototype._isSynchronizedViewMatrix=function(){return!!r.prototype._isSynchronizedViewMatrix.call(this)&&this._cache._target.equals(this._getTargetPosition())&&this._cache.alpha===this.alpha&&this._cache.beta===this.beta&&this._cache.radius===this.radius&&this._cache.targetScreenOffset.equals(this.targetScreenOffset)},t.prototype.attachControl=function(e,n,i,o){var a=this;i===void 0&&(i=!0),o===void 0&&(o=2),n=Xe.b.BackCompatCameraNoPreventDefault(arguments),this._useCtrlForPanning=i,this._panningMouseButton=o,typeof arguments[0]=="boolean"&&(arguments.length>1&&(this._useCtrlForPanning=arguments[1]),arguments.length>2&&(this._panningMouseButton=arguments[2])),this.inputs.attachElement(n),this._reset=function(){a.inertialAlphaOffset=0,a.inertialBetaOffset=0,a.inertialRadiusOffset=0,a.inertialPanningX=0,a.inertialPanningY=0}},t.prototype.detachControl=function(e){this.inputs.detachElement(),this._reset&&this._reset()},t.prototype._checkInputs=function(){if(!this._collisionTriggered){if(this.inputs.checkInputs(),this.inertialAlphaOffset!==0||this.inertialBetaOffset!==0||this.inertialRadiusOffset!==0){var e=this.inertialAlphaOffset;this.beta<=0&&(e*=-1),this.getScene().useRightHandedSystem&&(e*=-1),this.parent&&this.parent._getWorldMatrixDeterminant()<0&&(e*=-1),this.alpha+=e,this.beta+=this.inertialBetaOffset,this.radius-=this.inertialRadiusOffset,this.inertialAlphaOffset*=this.inertia,this.inertialBetaOffset*=this.inertia,this.inertialRadiusOffset*=this.inertia,Math.abs(this.inertialAlphaOffset)<Gt.a&&(this.inertialAlphaOffset=0),Math.abs(this.inertialBetaOffset)<Gt.a&&(this.inertialBetaOffset=0),Math.abs(this.inertialRadiusOffset)<this.speed*Gt.a&&(this.inertialRadiusOffset=0)}(this.inertialPanningX!==0||this.inertialPanningY!==0)&&(this._localDirection||(this._localDirection=u.e.Zero(),this._transformedDirection=u.e.Zero()),this._localDirection.copyFromFloats(this.inertialPanningX,this.inertialPanningY,this.inertialPanningY),this._localDirection.multiplyInPlace(this.panningAxis),this._viewMatrix.invertToRef(this._cameraTransformMatrix),u.e.TransformNormalToRef(this._localDirection,this._cameraTransformMatrix,this._transformedDirection),this.panningAxis.y||(this._transformedDirection.y=0),!this._targetHost&&(this.panningDistanceLimit?(this._transformedDirection.addInPlace(this._target),u.e.DistanceSquared(this._transformedDirection,this.panningOriginTarget)<=this.panningDistanceLimit*this.panningDistanceLimit&&this._target.copyFrom(this._transformedDirection)):this._target.addInPlace(this._transformedDirection)),this.inertialPanningX*=this.panningInertia,this.inertialPanningY*=this.panningInertia,Math.abs(this.inertialPanningX)<this.speed*Gt.a&&(this.inertialPanningX=0),Math.abs(this.inertialPanningY)<this.speed*Gt.a&&(this.inertialPanningY=0)),this._checkLimits(),r.prototype._checkInputs.call(this)}},t.prototype._checkLimits=function(){this.lowerBetaLimit===null||this.lowerBetaLimit===void 0?this.allowUpsideDown&&this.beta>Math.PI&&(this.beta=this.beta-2*Math.PI):this.beta<this.lowerBetaLimit&&(this.beta=this.lowerBetaLimit),this.upperBetaLimit===null||this.upperBetaLimit===void 0?this.allowUpsideDown&&this.beta<-Math.PI&&(this.beta=this.beta+2*Math.PI):this.beta>this.upperBetaLimit&&(this.beta=this.upperBetaLimit),this.lowerAlphaLimit!==null&&this.alpha<this.lowerAlphaLimit&&(this.alpha=this.lowerAlphaLimit),this.upperAlphaLimit!==null&&this.alpha>this.upperAlphaLimit&&(this.alpha=this.upperAlphaLimit),this.lowerRadiusLimit!==null&&this.radius<this.lowerRadiusLimit&&(this.radius=this.lowerRadiusLimit,this.inertialRadiusOffset=0),this.upperRadiusLimit!==null&&this.radius>this.upperRadiusLimit&&(this.radius=this.upperRadiusLimit,this.inertialRadiusOffset=0)},t.prototype.rebuildAnglesAndRadius=function(){this._position.subtractToRef(this._getTargetPosition(),this._computationVector),this._upVector.x===0&&this._upVector.y===1&&this._upVector.z===0||u.e.TransformCoordinatesToRef(this._computationVector,this._upToYMatrix,this._computationVector),this.radius=this._computationVector.length(),this.radius===0&&(this.radius=1e-4);var e=this.alpha;this._computationVector.x===0&&this._computationVector.z===0?this.alpha=Math.PI/2:this.alpha=Math.acos(this._computationVector.x/Math.sqrt(Math.pow(this._computationVector.x,2)+Math.pow(this._computationVector.z,2))),this._computationVector.z<0&&(this.alpha=2*Math.PI-this.alpha);var n=Math.round((e-this.alpha)/(2*Math.PI));this.alpha+=2*n*Math.PI,this.beta=Math.acos(this._computationVector.y/this.radius),this._checkLimits()},t.prototype.setPosition=function(e){this._position.equals(e)||(this._position.copyFrom(e),this.rebuildAnglesAndRadius())},t.prototype.setTarget=function(e,n,i){if(n===void 0&&(n=!1),i===void 0&&(i=!1),e.getBoundingInfo)this._targetBoundingCenter=n?e.getBoundingInfo().boundingBox.centerWorld.clone():null,e.computeWorldMatrix(),this._targetHost=e,this._target=this._getTargetPosition(),this.onMeshTargetChangedObservable.notifyObservers(this._targetHost);else{var o=e,a=this._getTargetPosition();if(a&&!i&&a.equals(o))return;this._targetHost=null,this._target=o,this._targetBoundingCenter=null,this.onMeshTargetChangedObservable.notifyObservers(null)}this.rebuildAnglesAndRadius()},t.prototype._getViewMatrix=function(){var e=Math.cos(this.alpha),n=Math.sin(this.alpha),i=Math.cos(this.beta),o=Math.sin(this.beta);o===0&&(o=1e-4),this.radius===0&&(this.radius=1e-4);var a=this._getTargetPosition();if(this._computationVector.copyFromFloats(this.radius*e*o,this.radius*i,this.radius*n*o),this._upVector.x===0&&this._upVector.y===1&&this._upVector.z===0||u.e.TransformCoordinatesToRef(this._computationVector,this._YToUpMatrix,this._computationVector),a.addToRef(this._computationVector,this._newPosition),this.getScene().collisionsEnabled&&this.checkCollisions){var s=this.getScene().collisionCoordinator;this._collider||(this._collider=s.createCollider()),this._collider._radius=this.collisionRadius,this._newPosition.subtractToRef(this._position,this._collisionVelocity),this._collisionTriggered=!0,s.getNewPosition(this._position,this._collisionVelocity,this._collider,3,null,this._onCollisionPositionChange,this.uniqueId)}else{this._position.copyFrom(this._newPosition);var d=this.upVector;this.allowUpsideDown&&o<0&&(d=d.negate()),this._computeViewMatrix(this._position,a,d),this._viewMatrix.addAtIndex(12,this.targetScreenOffset.x),this._viewMatrix.addAtIndex(13,this.targetScreenOffset.y)}return this._currentTarget=a,this._viewMatrix},t.prototype.zoomOn=function(e,n){n===void 0&&(n=!1),e=e||this.getScene().meshes;var i=De.a.MinMax(e),o=u.e.Distance(i.min,i.max);this.radius=o*this.zoomOnFactor,this.focusOn({min:i.min,max:i.max,distance:o},n)},t.prototype.focusOn=function(e,n){var i,o;if(n===void 0&&(n=!1),e.min===void 0){var a=e||this.getScene().meshes;i=De.a.MinMax(a),o=u.e.Distance(i.min,i.max)}else i=e,o=e.distance;this._target=De.a.Center(i),n||(this.maxZ=2*o)},t.prototype.createRigCamera=function(e,n){var i=0;switch(this.cameraRigMode){case gt.a.RIG_MODE_STEREOSCOPIC_ANAGLYPH:case gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:case gt.a.RIG_MODE_STEREOSCOPIC_OVERUNDER:case gt.a.RIG_MODE_STEREOSCOPIC_INTERLACED:case gt.a.RIG_MODE_VR:i=this._cameraRigParams.stereoHalfAngle*(n===0?1:-1);break;case gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED:i=this._cameraRigParams.stereoHalfAngle*(n===0?-1:1)}var o=new t(e,this.alpha+i,this.beta,this.radius,this._target,this.getScene());return o._cameraRigParams={},o.isRigCamera=!0,o.rigParent=this,o.upVector=this.upVector,o},t.prototype._updateRigCameras=function(){var e=this._rigCameras[0],n=this._rigCameras[1];switch(e.beta=n.beta=this.beta,this.cameraRigMode){case gt.a.RIG_MODE_STEREOSCOPIC_ANAGLYPH:case gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:case gt.a.RIG_MODE_STEREOSCOPIC_OVERUNDER:case gt.a.RIG_MODE_STEREOSCOPIC_INTERLACED:case gt.a.RIG_MODE_VR:e.alpha=this.alpha-this._cameraRigParams.stereoHalfAngle,n.alpha=this.alpha+this._cameraRigParams.stereoHalfAngle;break;case gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED:e.alpha=this.alpha+this._cameraRigParams.stereoHalfAngle,n.alpha=this.alpha-this._cameraRigParams.stereoHalfAngle}r.prototype._updateRigCameras.call(this)},t.prototype.dispose=function(){this.inputs.clear(),r.prototype.dispose.call(this)},t.prototype.getClassName=function(){return"ArcRotateCamera"},Object(c.c)([Object(L.c)()],t.prototype,"alpha",void 0),Object(c.c)([Object(L.c)()],t.prototype,"beta",void 0),Object(c.c)([Object(L.c)()],t.prototype,"radius",void 0),Object(c.c)([Object(L.o)("target")],t.prototype,"_target",void 0),Object(c.c)([Object(L.c)()],t.prototype,"inertialAlphaOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"inertialBetaOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"inertialRadiusOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lowerAlphaLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"upperAlphaLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lowerBetaLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"upperBetaLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lowerRadiusLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"upperRadiusLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"inertialPanningX",void 0),Object(c.c)([Object(L.c)()],t.prototype,"inertialPanningY",void 0),Object(c.c)([Object(L.c)()],t.prototype,"pinchToPanMaxDistance",void 0),Object(c.c)([Object(L.c)()],t.prototype,"panningDistanceLimit",void 0),Object(c.c)([Object(L.o)()],t.prototype,"panningOriginTarget",void 0),Object(c.c)([Object(L.c)()],t.prototype,"panningInertia",void 0),Object(c.c)([Object(L.c)()],t.prototype,"zoomOnFactor",void 0),Object(c.c)([Object(L.c)()],t.prototype,"targetScreenOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"allowUpsideDown",void 0),Object(c.c)([Object(L.c)()],t.prototype,"useInputToRestoreState",void 0),t}(Ni);Q.a.AddNodeConstructor("DeviceOrientationCamera",function(r,t){return function(){return new Fo(r,u.e.Zero(),t)}});var Fo=function(r){function t(e,n,i){var o=r.call(this,e,n,i)||this;return o._tmpDragQuaternion=new u.b,o._disablePointerInputWhenUsingDeviceOrientation=!0,o._dragFactor=0,o._quaternionCache=new u.b,o.inputs.addDeviceOrientation(),o.inputs._deviceOrientationInput&&o.inputs._deviceOrientationInput._onDeviceOrientationChangedObservable.addOnce(function(){o._disablePointerInputWhenUsingDeviceOrientation&&o.inputs._mouseInput&&(o.inputs._mouseInput._allowCameraRotation=!1,o.inputs._mouseInput.onPointerMovedObservable.add(function(a){o._dragFactor!=0&&(o._initialQuaternion||(o._initialQuaternion=new u.b),u.b.FromEulerAnglesToRef(0,a.offsetX*o._dragFactor,0,o._tmpDragQuaternion),o._initialQuaternion.multiplyToRef(o._tmpDragQuaternion,o._initialQuaternion))}))}),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"disablePointerInputWhenUsingDeviceOrientation",{get:function(){return this._disablePointerInputWhenUsingDeviceOrientation},set:function(e){this._disablePointerInputWhenUsingDeviceOrientation=e},enumerable:!1,configurable:!0}),t.prototype.enableHorizontalDragging=function(e){e===void 0&&(e=1/300),this._dragFactor=e},t.prototype.getClassName=function(){return"DeviceOrientationCamera"},t.prototype._checkInputs=function(){r.prototype._checkInputs.call(this),this._quaternionCache.copyFrom(this.rotationQuaternion),this._initialQuaternion&&this._initialQuaternion.multiplyToRef(this.rotationQuaternion,this.rotationQuaternion)},t.prototype.resetToCurrentRotation=function(e){var n=this;e===void 0&&(e=ye.a.Y),this.rotationQuaternion&&(this._initialQuaternion||(this._initialQuaternion=new u.b),this._initialQuaternion.copyFrom(this._quaternionCache||this.rotationQuaternion),["x","y","z"].forEach(function(i){e[i]?n._initialQuaternion[i]*=-1:n._initialQuaternion[i]=0}),this._initialQuaternion.normalize(),this._initialQuaternion.multiplyToRef(this.rotationQuaternion,this.rotationQuaternion))},t}(Yn),Al=function(r){function t(e){return r.call(this,e)||this}return Object(c.d)(t,r),t.prototype.addKeyboard=function(){return this.add(new qa),this},t.prototype.addMouse=function(e){return e===void 0&&(e=!0),this.add(new Za(e)),this},t}($r),kf=function(r){function t(e,n,i,o){o===void 0&&(o=!0);var a=r.call(this,e,n,i,o)||this;return a.ellipsoid=new u.e(1,1,1),a.ellipsoidOffset=new u.e(0,0,0),a.checkCollisions=!1,a.applyGravity=!1,a.cameraDirection=u.e.Zero(),a._trackRoll=0,a.rollCorrect=100,a.bankedTurn=!1,a.bankedTurnLimit=Math.PI/2,a.bankedTurnMultiplier=1,a._needMoveForGravity=!1,a._oldPosition=u.e.Zero(),a._diffPosition=u.e.Zero(),a._newPosition=u.e.Zero(),a._collisionMask=-1,a._onCollisionPositionChange=function(s,d,p){p===void 0&&(p=null);var b;b=d,a._newPosition.copyFrom(b),a._newPosition.subtractToRef(a._oldPosition,a._diffPosition),a._diffPosition.length()>Ue.a.CollisionsEpsilon&&(a.position.addInPlace(a._diffPosition),a.onCollide&&p&&a.onCollide(p))},a.inputs=new Al(a),a.inputs.addKeyboard().addMouse(),a}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"angularSensibility",{get:function(){var e=this.inputs.attached.mouse;return e?e.angularSensibility:0},set:function(e){var n=this.inputs.attached.mouse;n&&(n.angularSensibility=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysForward",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysForward:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysForward=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysBackward",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysBackward:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysBackward=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysUp",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysUp:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysUp=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysDown",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysDown:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysDown=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysLeft",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysLeft:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysLeft=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"keysRight",{get:function(){var e=this.inputs.attached.keyboard;return e?e.keysRight:[]},set:function(e){var n=this.inputs.attached.keyboard;n&&(n.keysRight=e)},enumerable:!1,configurable:!0}),t.prototype.attachControl=function(e,n){n=Xe.b.BackCompatCameraNoPreventDefault(arguments),this.inputs.attachElement(n)},t.prototype.detachControl=function(){this.inputs.detachElement(),this.cameraDirection=new u.e(0,0,0)},Object.defineProperty(t.prototype,"collisionMask",{get:function(){return this._collisionMask},set:function(e){this._collisionMask=isNaN(e)?-1:e},enumerable:!1,configurable:!0}),t.prototype._collideWithWorld=function(e){(this.parent?u.e.TransformCoordinates(this.position,this.parent.getWorldMatrix()):this.position).subtractFromFloatsToRef(0,this.ellipsoid.y,0,this._oldPosition),this._oldPosition.addInPlace(this.ellipsoidOffset);var n=this.getScene().collisionCoordinator;this._collider||(this._collider=n.createCollider()),this._collider._radius=this.ellipsoid,this._collider.collisionMask=this._collisionMask;var i=e;this.applyGravity&&(i=e.add(this.getScene().gravity)),n.getNewPosition(this._oldPosition,i,this._collider,3,null,this._onCollisionPositionChange,this.uniqueId)},t.prototype._checkInputs=function(){this._localDirection||(this._localDirection=u.e.Zero(),this._transformedDirection=u.e.Zero()),this.inputs.checkInputs(),r.prototype._checkInputs.call(this)},t.prototype._decideIfNeedsToMove=function(){return this._needMoveForGravity||Math.abs(this.cameraDirection.x)>0||Math.abs(this.cameraDirection.y)>0||Math.abs(this.cameraDirection.z)>0},t.prototype._updatePosition=function(){this.checkCollisions&&this.getScene().collisionsEnabled?this._collideWithWorld(this.cameraDirection):r.prototype._updatePosition.call(this)},t.prototype.restoreRoll=function(e){var n=this._trackRoll,i=n-this.rotation.z;Math.abs(i)>=.001&&(this.rotation.z+=i/e,Math.abs(n-this.rotation.z)<=.001&&(this.rotation.z=n))},t.prototype.dispose=function(){this.inputs.clear(),r.prototype.dispose.call(this)},t.prototype.getClassName=function(){return"FlyCamera"},Object(c.c)([Object(L.o)()],t.prototype,"ellipsoid",void 0),Object(c.c)([Object(L.o)()],t.prototype,"ellipsoidOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"checkCollisions",void 0),Object(c.c)([Object(L.c)()],t.prototype,"applyGravity",void 0),t}(Ni),Pl=function(r){function t(e){return r.call(this,e)||this}return Object(c.d)(t,r),t.prototype.addKeyboard=function(){return this.add(new Ja),this},t.prototype.addMouseWheel=function(){return this.add(new $a),this},t.prototype.addPointers=function(){return this.add(new es),this},t.prototype.addVRDeviceOrientation=function(){return console.warn("DeviceOrientation support not yet implemented for FollowCamera."),this},t}($r);Q.a.AddNodeConstructor("FollowCamera",function(r,t){return function(){return new xl(r,u.e.Zero(),t)}}),Q.a.AddNodeConstructor("ArcFollowCamera",function(r,t){return function(){return new Cl(r,0,0,1,null,t)}});var ii,xl=function(r){function t(e,n,i,o){o===void 0&&(o=null);var a=r.call(this,e,n,i)||this;return a.radius=12,a.lowerRadiusLimit=null,a.upperRadiusLimit=null,a.rotationOffset=0,a.lowerRotationOffsetLimit=null,a.upperRotationOffsetLimit=null,a.heightOffset=4,a.lowerHeightOffsetLimit=null,a.upperHeightOffsetLimit=null,a.cameraAcceleration=.05,a.maxCameraSpeed=20,a.lockedTarget=o,a.inputs=new Pl(a),a.inputs.addKeyboard().addMouseWheel().addPointers(),a}return Object(c.d)(t,r),t.prototype._follow=function(e){if(e){var n;if(e.rotationQuaternion){var i=new u.a;e.rotationQuaternion.toRotationMatrix(i),n=Math.atan2(i.m[8],i.m[10])}else n=e.rotation.y;var o=Xe.b.ToRadians(this.rotationOffset)+n,a=e.getAbsolutePosition(),s=a.x+Math.sin(o)*this.radius,d=a.z+Math.cos(o)*this.radius,p=s-this.position.x,b=a.y+this.heightOffset-this.position.y,P=d-this.position.z,O=p*this.cameraAcceleration*2,B=b*this.cameraAcceleration,F=P*this.cameraAcceleration*2;(O>this.maxCameraSpeed||O<-this.maxCameraSpeed)&&(O=O<1?-this.maxCameraSpeed:this.maxCameraSpeed),(B>this.maxCameraSpeed||B<-this.maxCameraSpeed)&&(B=B<1?-this.maxCameraSpeed:this.maxCameraSpeed),(F>this.maxCameraSpeed||F<-this.maxCameraSpeed)&&(F=F<1?-this.maxCameraSpeed:this.maxCameraSpeed),this.position=new u.e(this.position.x+O,this.position.y+B,this.position.z+F),this.setTarget(a)}},t.prototype.attachControl=function(e,n){n=Xe.b.BackCompatCameraNoPreventDefault(arguments),this.inputs.attachElement(n),this._reset=function(){}},t.prototype.detachControl=function(e){this.inputs.detachElement(),this._reset&&this._reset()},t.prototype._checkInputs=function(){this.inputs.checkInputs(),this._checkLimits(),r.prototype._checkInputs.call(this),this.lockedTarget&&this._follow(this.lockedTarget)},t.prototype._checkLimits=function(){this.lowerRadiusLimit!==null&&this.radius<this.lowerRadiusLimit&&(this.radius=this.lowerRadiusLimit),this.upperRadiusLimit!==null&&this.radius>this.upperRadiusLimit&&(this.radius=this.upperRadiusLimit),this.lowerHeightOffsetLimit!==null&&this.heightOffset<this.lowerHeightOffsetLimit&&(this.heightOffset=this.lowerHeightOffsetLimit),this.upperHeightOffsetLimit!==null&&this.heightOffset>this.upperHeightOffsetLimit&&(this.heightOffset=this.upperHeightOffsetLimit),this.lowerRotationOffsetLimit!==null&&this.rotationOffset<this.lowerRotationOffsetLimit&&(this.rotationOffset=this.lowerRotationOffsetLimit),this.upperRotationOffsetLimit!==null&&this.rotationOffset>this.upperRotationOffsetLimit&&(this.rotationOffset=this.upperRotationOffsetLimit)},t.prototype.getClassName=function(){return"FollowCamera"},Object(c.c)([Object(L.c)()],t.prototype,"radius",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lowerRadiusLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"upperRadiusLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"rotationOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lowerRotationOffsetLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"upperRotationOffsetLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"heightOffset",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lowerHeightOffsetLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"upperHeightOffsetLimit",void 0),Object(c.c)([Object(L.c)()],t.prototype,"cameraAcceleration",void 0),Object(c.c)([Object(L.c)()],t.prototype,"maxCameraSpeed",void 0),Object(c.c)([Object(L.k)("lockedTargetId")],t.prototype,"lockedTarget",void 0),t}(Ni),Cl=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,u.e.Zero(),s)||this;return d.alpha=n,d.beta=i,d.radius=o,d._cartesianCoordinates=u.e.Zero(),d._meshTarget=a,d._follow(),d}return Object(c.d)(t,r),t.prototype._follow=function(){if(this._meshTarget){this._cartesianCoordinates.x=this.radius*Math.cos(this.alpha)*Math.cos(this.beta),this._cartesianCoordinates.y=this.radius*Math.sin(this.beta),this._cartesianCoordinates.z=this.radius*Math.sin(this.alpha)*Math.cos(this.beta);var e=this._meshTarget.getAbsolutePosition();this.position=e.add(this._cartesianCoordinates),this.setTarget(e)}},t.prototype._checkInputs=function(){r.prototype._checkInputs.call(this),this._follow()},t.prototype.getClassName=function(){return"ArcFollowCamera"},t}(Ni),us=f(38),fn=f(39);(function(r){r[r.VIVE=0]="VIVE",r[r.OCULUS=1]="OCULUS",r[r.WINDOWS=2]="WINDOWS",r[r.GEAR_VR=3]="GEAR_VR",r[r.DAYDREAM=4]="DAYDREAM",r[r.GENERIC=5]="GENERIC"})(ii||(ii={}));var Rn,$i,wi=function(){function r(){}return r.InitiateController=function(t){for(var e=0,n=this._ControllerFactories;e<n.length;e++){var i=n[e];if(i.canCreate(t))return i.create(t)}if(this._DefaultControllerFactory)return this._DefaultControllerFactory(t);throw"The type of gamepad you are trying to load needs to be imported first or is not supported."},r._ControllerFactories=[],r._DefaultControllerFactory=null,r}(),pr=function(r){function t(e){var n=r.call(this,e.id,e.index,e)||this;return n.isXR=!1,n._deviceRoomPosition=u.e.Zero(),n._deviceRoomRotationQuaternion=new u.b,n.devicePosition=u.e.Zero(),n.deviceRotationQuaternion=new u.b,n.deviceScaleFactor=1,n._trackPosition=!0,n._maxRotationDistFromHeadset=Math.PI/5,n._draggedRoomRotation=0,n._leftHandSystemQuaternion=new u.b,n._deviceToWorld=u.a.Identity(),n._pointingPoseNode=null,n._workingMatrix=u.a.Identity(),n._meshAttachedObservable=new C.c,n.type=dn.POSE_ENABLED,n.controllerType=ii.GENERIC,n.position=u.e.Zero(),n.rotationQuaternion=new u.b,n._calculatedPosition=u.e.Zero(),n._calculatedRotation=new u.b,u.b.RotationYawPitchRollToRef(Math.PI,0,0,n._leftHandSystemQuaternion),n}return Object(c.d)(t,r),t.prototype._disableTrackPosition=function(e){this._trackPosition&&(this._calculatedPosition.copyFrom(e),this._trackPosition=!1)},t.prototype.update=function(){r.prototype.update.call(this),this._updatePoseAndMesh()},t.prototype._updatePoseAndMesh=function(){if(!this.isXR){var e=this.browserGamepad.pose;if(this.updateFromDevice(e),!this._trackPosition&&te.a.LastCreatedScene&&te.a.LastCreatedScene.activeCamera&&te.a.LastCreatedScene.activeCamera.devicePosition&&((n=te.a.LastCreatedScene.activeCamera)._computeDevicePosition(),this._deviceToWorld.setTranslation(n.devicePosition),n.deviceRotationQuaternion)){var n;(n=n)._deviceRoomRotationQuaternion.toEulerAnglesToRef(u.c.Vector3[0]);var i=Math.atan2(Math.sin(u.c.Vector3[0].y-this._draggedRoomRotation),Math.cos(u.c.Vector3[0].y-this._draggedRoomRotation));if(Math.abs(i)>this._maxRotationDistFromHeadset){var o=i-(i<0?-this._maxRotationDistFromHeadset:this._maxRotationDistFromHeadset);this._draggedRoomRotation+=o;var a=Math.sin(-o),s=Math.cos(-o);this._calculatedPosition.x=this._calculatedPosition.x*s-this._calculatedPosition.z*a,this._calculatedPosition.z=this._calculatedPosition.x*a+this._calculatedPosition.z*s}}u.e.TransformCoordinatesToRef(this._calculatedPosition,this._deviceToWorld,this.devicePosition),this._deviceToWorld.getRotationMatrixToRef(this._workingMatrix),u.b.FromRotationMatrixToRef(this._workingMatrix,this.deviceRotationQuaternion),this.deviceRotationQuaternion.multiplyInPlace(this._calculatedRotation),this._mesh&&(this._mesh.position.copyFrom(this.devicePosition),this._mesh.rotationQuaternion&&this._mesh.rotationQuaternion.copyFrom(this.deviceRotationQuaternion))}},t.prototype.updateFromDevice=function(e){if(!this.isXR&&e){this.rawPose=e,e.position&&(this._deviceRoomPosition.copyFromFloats(e.position[0],e.position[1],-e.position[2]),this._mesh&&this._mesh.getScene().useRightHandedSystem&&(this._deviceRoomPosition.z*=-1),this._trackPosition&&this._deviceRoomPosition.scaleToRef(this.deviceScaleFactor,this._calculatedPosition),this._calculatedPosition.addInPlace(this.position));var n=this.rawPose;e.orientation&&n.orientation&&n.orientation.length===4&&(this._deviceRoomRotationQuaternion.copyFromFloats(n.orientation[0],n.orientation[1],-n.orientation[2],-n.orientation[3]),this._mesh&&(this._mesh.getScene().useRightHandedSystem?(this._deviceRoomRotationQuaternion.z*=-1,this._deviceRoomRotationQuaternion.w*=-1):this._deviceRoomRotationQuaternion.multiplyToRef(this._leftHandSystemQuaternion,this._deviceRoomRotationQuaternion)),this._deviceRoomRotationQuaternion.multiplyToRef(this.rotationQuaternion,this._calculatedRotation))}},t.prototype.attachToMesh=function(e){if(this._mesh&&(this._mesh.parent=null),this._mesh=e,this._poseControlledCamera&&(this._mesh.parent=this._poseControlledCamera),this._mesh.rotationQuaternion||(this._mesh.rotationQuaternion=new u.b),!this.isXR&&(this._updatePoseAndMesh(),this._pointingPoseNode)){for(var n=[],i=this._pointingPoseNode;i.parent;)n.push(i.parent),i=i.parent;n.reverse().forEach(function(o){o.computeWorldMatrix(!0)})}this._meshAttachedObservable.notifyObservers(e)},t.prototype.attachToPoseControlledCamera=function(e){this._poseControlledCamera=e,this._mesh&&(this._mesh.parent=this._poseControlledCamera)},t.prototype.dispose=function(){this._mesh&&this._mesh.dispose(),this._mesh=null,r.prototype.dispose.call(this)},Object.defineProperty(t.prototype,"mesh",{get:function(){return this._mesh},enumerable:!1,configurable:!0}),t.prototype.getForwardRay=function(e){if(e===void 0&&(e=100),!this.mesh)return new fn.a(u.e.Zero(),new u.e(0,0,1),e);var n=this._pointingPoseNode?this._pointingPoseNode.getWorldMatrix():this.mesh.getWorldMatrix(),i=n.getTranslation(),o=new u.e(0,0,-1),a=u.e.TransformNormal(o,n),s=u.e.Normalize(a);return new fn.a(i,s,e)},t.POINTING_POSE="POINTING_POSE",t}(dn);(function(r){r[r.A=0]="A",r[r.B=1]="B",r[r.X=2]="X",r[r.Y=3]="Y",r[r.LB=4]="LB",r[r.RB=5]="RB",r[r.Back=8]="Back",r[r.Start=9]="Start",r[r.LeftStick=10]="LeftStick",r[r.RightStick=11]="RightStick"})(Rn||(Rn={})),function(r){r[r.Up=12]="Up",r[r.Down=13]="Down",r[r.Left=14]="Left",r[r.Right=15]="Right"}($i||($i={}));var Gn,er,Rl=function(r){function t(e,n,i,o){o===void 0&&(o=!1);var a=r.call(this,e,n,i,0,1,2,3)||this;return a._leftTrigger=0,a._rightTrigger=0,a.onButtonDownObservable=new C.c,a.onButtonUpObservable=new C.c,a.onPadDownObservable=new C.c,a.onPadUpObservable=new C.c,a._buttonA=0,a._buttonB=0,a._buttonX=0,a._buttonY=0,a._buttonBack=0,a._buttonStart=0,a._buttonLB=0,a._buttonRB=0,a._buttonLeftStick=0,a._buttonRightStick=0,a._dPadUp=0,a._dPadDown=0,a._dPadLeft=0,a._dPadRight=0,a._isXboxOnePad=!1,a.type=dn.XBOX,a._isXboxOnePad=o,a}return Object(c.d)(t,r),t.prototype.onlefttriggerchanged=function(e){this._onlefttriggerchanged=e},t.prototype.onrighttriggerchanged=function(e){this._onrighttriggerchanged=e},Object.defineProperty(t.prototype,"leftTrigger",{get:function(){return this._leftTrigger},set:function(e){this._onlefttriggerchanged&&this._leftTrigger!==e&&this._onlefttriggerchanged(e),this._leftTrigger=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rightTrigger",{get:function(){return this._rightTrigger},set:function(e){this._onrighttriggerchanged&&this._rightTrigger!==e&&this._onrighttriggerchanged(e),this._rightTrigger=e},enumerable:!1,configurable:!0}),t.prototype.onbuttondown=function(e){this._onbuttondown=e},t.prototype.onbuttonup=function(e){this._onbuttonup=e},t.prototype.ondpaddown=function(e){this._ondpaddown=e},t.prototype.ondpadup=function(e){this._ondpadup=e},t.prototype._setButtonValue=function(e,n,i){return e!==n&&(e===1&&(this._onbuttondown&&this._onbuttondown(i),this.onButtonDownObservable.notifyObservers(i)),e===0&&(this._onbuttonup&&this._onbuttonup(i),this.onButtonUpObservable.notifyObservers(i))),e},t.prototype._setDPadValue=function(e,n,i){return e!==n&&(e===1&&(this._ondpaddown&&this._ondpaddown(i),this.onPadDownObservable.notifyObservers(i)),e===0&&(this._ondpadup&&this._ondpadup(i),this.onPadUpObservable.notifyObservers(i))),e},Object.defineProperty(t.prototype,"buttonA",{get:function(){return this._buttonA},set:function(e){this._buttonA=this._setButtonValue(e,this._buttonA,Rn.A)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonB",{get:function(){return this._buttonB},set:function(e){this._buttonB=this._setButtonValue(e,this._buttonB,Rn.B)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonX",{get:function(){return this._buttonX},set:function(e){this._buttonX=this._setButtonValue(e,this._buttonX,Rn.X)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonY",{get:function(){return this._buttonY},set:function(e){this._buttonY=this._setButtonValue(e,this._buttonY,Rn.Y)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonStart",{get:function(){return this._buttonStart},set:function(e){this._buttonStart=this._setButtonValue(e,this._buttonStart,Rn.Start)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonBack",{get:function(){return this._buttonBack},set:function(e){this._buttonBack=this._setButtonValue(e,this._buttonBack,Rn.Back)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonLB",{get:function(){return this._buttonLB},set:function(e){this._buttonLB=this._setButtonValue(e,this._buttonLB,Rn.LB)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonRB",{get:function(){return this._buttonRB},set:function(e){this._buttonRB=this._setButtonValue(e,this._buttonRB,Rn.RB)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonLeftStick",{get:function(){return this._buttonLeftStick},set:function(e){this._buttonLeftStick=this._setButtonValue(e,this._buttonLeftStick,Rn.LeftStick)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonRightStick",{get:function(){return this._buttonRightStick},set:function(e){this._buttonRightStick=this._setButtonValue(e,this._buttonRightStick,Rn.RightStick)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadUp",{get:function(){return this._dPadUp},set:function(e){this._dPadUp=this._setDPadValue(e,this._dPadUp,$i.Up)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadDown",{get:function(){return this._dPadDown},set:function(e){this._dPadDown=this._setDPadValue(e,this._dPadDown,$i.Down)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadLeft",{get:function(){return this._dPadLeft},set:function(e){this._dPadLeft=this._setDPadValue(e,this._dPadLeft,$i.Left)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadRight",{get:function(){return this._dPadRight},set:function(e){this._dPadRight=this._setDPadValue(e,this._dPadRight,$i.Right)},enumerable:!1,configurable:!0}),t.prototype.update=function(){r.prototype.update.call(this),this._isXboxOnePad,this.buttonA=this.browserGamepad.buttons[0].value,this.buttonB=this.browserGamepad.buttons[1].value,this.buttonX=this.browserGamepad.buttons[2].value,this.buttonY=this.browserGamepad.buttons[3].value,this.buttonLB=this.browserGamepad.buttons[4].value,this.buttonRB=this.browserGamepad.buttons[5].value,this.leftTrigger=this.browserGamepad.buttons[6].value,this.rightTrigger=this.browserGamepad.buttons[7].value,this.buttonBack=this.browserGamepad.buttons[8].value,this.buttonStart=this.browserGamepad.buttons[9].value,this.buttonLeftStick=this.browserGamepad.buttons[10].value,this.buttonRightStick=this.browserGamepad.buttons[11].value,this.dPadUp=this.browserGamepad.buttons[12].value,this.dPadDown=this.browserGamepad.buttons[13].value,this.dPadLeft=this.browserGamepad.buttons[14].value,this.dPadRight=this.browserGamepad.buttons[15].value},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onButtonDownObservable.clear(),this.onButtonUpObservable.clear(),this.onPadDownObservable.clear(),this.onPadUpObservable.clear()},t}(dn);(function(r){r[r.Cross=0]="Cross",r[r.Circle=1]="Circle",r[r.Square=2]="Square",r[r.Triangle=3]="Triangle",r[r.L1=4]="L1",r[r.R1=5]="R1",r[r.Share=8]="Share",r[r.Options=9]="Options",r[r.LeftStick=10]="LeftStick",r[r.RightStick=11]="RightStick"})(Gn||(Gn={})),function(r){r[r.Up=12]="Up",r[r.Down=13]="Down",r[r.Left=14]="Left",r[r.Right=15]="Right"}(er||(er={}));var Ol=function(r){function t(e,n,i){var o=r.call(this,e.replace("STANDARD GAMEPAD","SONY PLAYSTATION DUALSHOCK"),n,i,0,1,2,3)||this;return o._leftTrigger=0,o._rightTrigger=0,o.onButtonDownObservable=new C.c,o.onButtonUpObservable=new C.c,o.onPadDownObservable=new C.c,o.onPadUpObservable=new C.c,o._buttonCross=0,o._buttonCircle=0,o._buttonSquare=0,o._buttonTriangle=0,o._buttonShare=0,o._buttonOptions=0,o._buttonL1=0,o._buttonR1=0,o._buttonLeftStick=0,o._buttonRightStick=0,o._dPadUp=0,o._dPadDown=0,o._dPadLeft=0,o._dPadRight=0,o.type=dn.DUALSHOCK,o}return Object(c.d)(t,r),t.prototype.onlefttriggerchanged=function(e){this._onlefttriggerchanged=e},t.prototype.onrighttriggerchanged=function(e){this._onrighttriggerchanged=e},Object.defineProperty(t.prototype,"leftTrigger",{get:function(){return this._leftTrigger},set:function(e){this._onlefttriggerchanged&&this._leftTrigger!==e&&this._onlefttriggerchanged(e),this._leftTrigger=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rightTrigger",{get:function(){return this._rightTrigger},set:function(e){this._onrighttriggerchanged&&this._rightTrigger!==e&&this._onrighttriggerchanged(e),this._rightTrigger=e},enumerable:!1,configurable:!0}),t.prototype.onbuttondown=function(e){this._onbuttondown=e},t.prototype.onbuttonup=function(e){this._onbuttonup=e},t.prototype.ondpaddown=function(e){this._ondpaddown=e},t.prototype.ondpadup=function(e){this._ondpadup=e},t.prototype._setButtonValue=function(e,n,i){return e!==n&&(e===1&&(this._onbuttondown&&this._onbuttondown(i),this.onButtonDownObservable.notifyObservers(i)),e===0&&(this._onbuttonup&&this._onbuttonup(i),this.onButtonUpObservable.notifyObservers(i))),e},t.prototype._setDPadValue=function(e,n,i){return e!==n&&(e===1&&(this._ondpaddown&&this._ondpaddown(i),this.onPadDownObservable.notifyObservers(i)),e===0&&(this._ondpadup&&this._ondpadup(i),this.onPadUpObservable.notifyObservers(i))),e},Object.defineProperty(t.prototype,"buttonCross",{get:function(){return this._buttonCross},set:function(e){this._buttonCross=this._setButtonValue(e,this._buttonCross,Gn.Cross)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonCircle",{get:function(){return this._buttonCircle},set:function(e){this._buttonCircle=this._setButtonValue(e,this._buttonCircle,Gn.Circle)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonSquare",{get:function(){return this._buttonSquare},set:function(e){this._buttonSquare=this._setButtonValue(e,this._buttonSquare,Gn.Square)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonTriangle",{get:function(){return this._buttonTriangle},set:function(e){this._buttonTriangle=this._setButtonValue(e,this._buttonTriangle,Gn.Triangle)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonOptions",{get:function(){return this._buttonOptions},set:function(e){this._buttonOptions=this._setButtonValue(e,this._buttonOptions,Gn.Options)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonShare",{get:function(){return this._buttonShare},set:function(e){this._buttonShare=this._setButtonValue(e,this._buttonShare,Gn.Share)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonL1",{get:function(){return this._buttonL1},set:function(e){this._buttonL1=this._setButtonValue(e,this._buttonL1,Gn.L1)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonR1",{get:function(){return this._buttonR1},set:function(e){this._buttonR1=this._setButtonValue(e,this._buttonR1,Gn.R1)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonLeftStick",{get:function(){return this._buttonLeftStick},set:function(e){this._buttonLeftStick=this._setButtonValue(e,this._buttonLeftStick,Gn.LeftStick)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buttonRightStick",{get:function(){return this._buttonRightStick},set:function(e){this._buttonRightStick=this._setButtonValue(e,this._buttonRightStick,Gn.RightStick)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadUp",{get:function(){return this._dPadUp},set:function(e){this._dPadUp=this._setDPadValue(e,this._dPadUp,er.Up)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadDown",{get:function(){return this._dPadDown},set:function(e){this._dPadDown=this._setDPadValue(e,this._dPadDown,er.Down)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadLeft",{get:function(){return this._dPadLeft},set:function(e){this._dPadLeft=this._setDPadValue(e,this._dPadLeft,er.Left)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dPadRight",{get:function(){return this._dPadRight},set:function(e){this._dPadRight=this._setDPadValue(e,this._dPadRight,er.Right)},enumerable:!1,configurable:!0}),t.prototype.update=function(){r.prototype.update.call(this),this.buttonCross=this.browserGamepad.buttons[0].value,this.buttonCircle=this.browserGamepad.buttons[1].value,this.buttonSquare=this.browserGamepad.buttons[2].value,this.buttonTriangle=this.browserGamepad.buttons[3].value,this.buttonL1=this.browserGamepad.buttons[4].value,this.buttonR1=this.browserGamepad.buttons[5].value,this.leftTrigger=this.browserGamepad.buttons[6].value,this.rightTrigger=this.browserGamepad.buttons[7].value,this.buttonShare=this.browserGamepad.buttons[8].value,this.buttonOptions=this.browserGamepad.buttons[9].value,this.buttonLeftStick=this.browserGamepad.buttons[10].value,this.buttonRightStick=this.browserGamepad.buttons[11].value,this.dPadUp=this.browserGamepad.buttons[12].value,this.dPadDown=this.browserGamepad.buttons[13].value,this.dPadLeft=this.browserGamepad.buttons[14].value,this.dPadRight=this.browserGamepad.buttons[15].value},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onButtonDownObservable.clear(),this.onButtonUpObservable.clear(),this.onPadDownObservable.clear(),this.onPadUpObservable.clear()},t}(dn),Ml=function(){function r(t){var e=this;if(this._scene=t,this._babylonGamepads=[],this._oneGamepadConnected=!1,this._isMonitoring=!1,this.onGamepadDisconnectedObservable=new C.c,us.a.IsWindowObjectExist()?(this._gamepadEventSupported="GamepadEvent"in window,this._gamepadSupport=navigator.getGamepads||navigator.webkitGetGamepads||navigator.msGetGamepads||navigator.webkitGamepads):this._gamepadEventSupported=!1,this.onGamepadConnectedObservable=new C.c(function(i){for(var o in e._babylonGamepads){var a=e._babylonGamepads[o];a&&a._isConnected&&e.onGamepadConnectedObservable.notifyObserver(i,a)}}),this._onGamepadConnectedEvent=function(i){var o,a=i.gamepad;a.index in e._babylonGamepads&&e._babylonGamepads[a.index].isConnected||(e._babylonGamepads[a.index]?((o=e._babylonGamepads[a.index]).browserGamepad=a,o._isConnected=!0):o=e._addNewGamepad(a),e.onGamepadConnectedObservable.notifyObservers(o),e._startMonitoringGamepads())},this._onGamepadDisconnectedEvent=function(i){var o=i.gamepad;for(var a in e._babylonGamepads)if(e._babylonGamepads[a].index===o.index){var s=e._babylonGamepads[a];s._isConnected=!1,e.onGamepadDisconnectedObservable.notifyObservers(s),s.dispose&&s.dispose();break}},this._gamepadSupport)if(this._updateGamepadObjects(),this._babylonGamepads.length&&this._startMonitoringGamepads(),this._gamepadEventSupported){var n=this._scene?this._scene.getEngine().getHostWindow():window;n&&(n.addEventListener("gamepadconnected",this._onGamepadConnectedEvent,!1),n.addEventListener("gamepaddisconnected",this._onGamepadDisconnectedEvent,!1))}else this._startMonitoringGamepads()}return Object.defineProperty(r.prototype,"gamepads",{get:function(){return this._babylonGamepads},enumerable:!1,configurable:!0}),r.prototype.getGamepadByType=function(t){t===void 0&&(t=dn.XBOX);for(var e=0,n=this._babylonGamepads;e<n.length;e++){var i=n[e];if(i&&i.type===t)return i}return null},r.prototype.dispose=function(){this._gamepadEventSupported&&(this._onGamepadConnectedEvent&&window.removeEventListener("gamepadconnected",this._onGamepadConnectedEvent),this._onGamepadDisconnectedEvent&&window.removeEventListener("gamepaddisconnected",this._onGamepadDisconnectedEvent),this._onGamepadConnectedEvent=null,this._onGamepadDisconnectedEvent=null),this._babylonGamepads.forEach(function(t){t.dispose()}),this.onGamepadConnectedObservable.clear(),this.onGamepadDisconnectedObservable.clear(),this._oneGamepadConnected=!1,this._stopMonitoringGamepads(),this._babylonGamepads=[]},r.prototype._addNewGamepad=function(t){var e;this._oneGamepadConnected||(this._oneGamepadConnected=!0);var n=t.id.search("054c")!==-1,i=t.id.search("Xbox One")!==-1;return e=i||t.id.search("Xbox 360")!==-1||t.id.search("xinput")!==-1?new Rl(t.id,t.index,t,i):n?new Ol(t.id,t.index,t):t.pose?wi.InitiateController(t):new Tl(t.id,t.index,t),this._babylonGamepads[e.index]=e,e},r.prototype._startMonitoringGamepads=function(){this._isMonitoring||(this._isMonitoring=!0,this._scene||this._checkGamepadsStatus())},r.prototype._stopMonitoringGamepads=function(){this._isMonitoring=!1},r.prototype._checkGamepadsStatus=function(){var t=this;for(var e in this._updateGamepadObjects(),this._babylonGamepads){var n=this._babylonGamepads[e];n&&n.isConnected&&n.update()}this._isMonitoring&&!this._scene&&Ue.a.QueueNewFrame(function(){t._checkGamepadsStatus()})},r.prototype._updateGamepadObjects=function(){for(var t=navigator.getGamepads?navigator.getGamepads():navigator.webkitGetGamepads?navigator.webkitGetGamepads():[],e=0;e<t.length;e++){var n=t[e];if(n)if(this._babylonGamepads[n.index])this._babylonGamepads[e].browserGamepad=n,this._babylonGamepads[e].isConnected||(this._babylonGamepads[e]._isConnected=!0,this.onGamepadConnectedObservable.notifyObservers(this._babylonGamepads[e]));else{var i=this._addNewGamepad(n);this.onGamepadConnectedObservable.notifyObservers(i)}}},r}();Object.defineProperty(_e.a.prototype,"gamepadManager",{get:function(){if(!this._gamepadManager){this._gamepadManager=new Ml(this);var r=this._getComponent(at.a.NAME_GAMEPAD);r||(r=new Il(this),this._addComponent(r))}return this._gamepadManager},enumerable:!0,configurable:!0}),eo.prototype.addGamepad=function(){return this.add(new as),this},wo.prototype.addGamepad=function(){return this.add(new Wa),this};var Il=function(){function r(t){this.name=at.a.NAME_GAMEPAD,this.scene=t}return r.prototype.register=function(){this.scene._beforeCameraUpdateStage.registerStep(at.a.STEP_BEFORECAMERAUPDATE_GAMEPAD,this,this._beforeCameraUpdate)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){var t=this.scene._gamepadManager;t&&(t.dispose(),this.scene._gamepadManager=null)},r.prototype._beforeCameraUpdate=function(){var t=this.scene._gamepadManager;t&&t._isMonitoring&&t._checkGamepadsStatus()},r}();Q.a.AddNodeConstructor("FreeCamera",function(r,t){return function(){return new _r(r,u.e.Zero(),t)}});var _r=function(r){function t(e,n,i){var o=r.call(this,e,n,i)||this;return o.inputs.addGamepad(),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"gamepadAngularSensibility",{get:function(){var e=this.inputs.attached.gamepad;return e?e.gamepadAngularSensibility:0},set:function(e){var n=this.inputs.attached.gamepad;n&&(n.gamepadAngularSensibility=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"gamepadMoveSensibility",{get:function(){var e=this.inputs.attached.gamepad;return e?e.gamepadMoveSensibility:0},set:function(e){var n=this.inputs.attached.gamepad;n&&(n.gamepadMoveSensibility=e)},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"UniversalCamera"},t}(ls);gt.a._createDefaultParsedCamera=function(r,t){return new _r(r,u.e.Zero(),t)},Q.a.AddNodeConstructor("GamepadCamera",function(r,t){return function(){return new Bo(r,u.e.Zero(),t)}});var Bo=function(r){function t(e,n,i){return r.call(this,e,n,i)||this}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"GamepadCamera"},t}(_r),fi=f(33),ze=f(5),Gf=`
-attribute vec2 position;
-uniform vec2 scale;
-
-varying vec2 vUV;
-const vec2 madd=vec2(0.5,0.5);
-void main(void) {
-vUV=(position*madd+madd)*scale;
-gl_Position=vec4(position,0.0,1.0);
-}`;ze.a.ShadersStore.postprocessVertexShader=Gf;var Dl=f(102);Bt.a.prototype.createRenderTargetTexture=function(r,t){var e=new Dl.a;t!==void 0&&typeof t=="object"?(e.generateMipMaps=t.generateMipMaps,e.generateDepthBuffer=!!t.generateDepthBuffer,e.generateStencilBuffer=!!t.generateStencilBuffer,e.type=t.type===void 0?h.a.TEXTURETYPE_UNSIGNED_INT:t.type,e.samplingMode=t.samplingMode===void 0?h.a.TEXTURE_TRILINEAR_SAMPLINGMODE:t.samplingMode,e.format=t.format===void 0?h.a.TEXTUREFORMAT_RGBA:t.format):(e.generateMipMaps=t,e.generateDepthBuffer=!0,e.generateStencilBuffer=!1,e.type=h.a.TEXTURETYPE_UNSIGNED_INT,e.samplingMode=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,e.format=h.a.TEXTUREFORMAT_RGBA),(e.type!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloatLinearFiltering)&&(e.type!==h.a.TEXTURETYPE_HALF_FLOAT||this._caps.textureHalfFloatLinearFiltering)||(e.samplingMode=h.a.TEXTURE_NEAREST_SAMPLINGMODE),e.type!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloat||(e.type=h.a.TEXTURETYPE_UNSIGNED_INT,l.a.Warn("Float textures are not supported. Render target forced to TEXTURETYPE_UNSIGNED_BYTE type"));var n=this._gl,i=new Ct.a(this,Ct.b.RenderTarget),o=r.width||r,a=r.height||r,s=r.layers||0,d=this._getSamplingParameters(e.samplingMode,!!e.generateMipMaps),p=s!==0?n.TEXTURE_2D_ARRAY:n.TEXTURE_2D,b=this._getRGBABufferInternalSizedFormat(e.type,e.format),P=this._getInternalFormat(e.format),O=this._getWebGLTextureType(e.type);this._bindTextureDirectly(p,i),s!==0?(i.is2DArray=!0,n.texImage3D(p,0,b,o,a,s,0,P,O,null)):n.texImage2D(p,0,b,o,a,0,P,O,null),n.texParameteri(p,n.TEXTURE_MAG_FILTER,d.mag),n.texParameteri(p,n.TEXTURE_MIN_FILTER,d.min),n.texParameteri(p,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(p,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),e.generateMipMaps&&this._gl.generateMipmap(p),this._bindTextureDirectly(p,null);var B=this._currentFramebuffer,F=n.createFramebuffer();return this._bindUnboundFramebuffer(F),i._depthStencilBuffer=this._setupFramebufferDepthAttachments(!!e.generateStencilBuffer,e.generateDepthBuffer,o,a),i.is2DArray||n.framebufferTexture2D(n.FRAMEBUFFER,n.COLOR_ATTACHMENT0,n.TEXTURE_2D,i._webGLTexture,0),this._bindUnboundFramebuffer(B),i._framebuffer=F,i.baseWidth=o,i.baseHeight=a,i.width=o,i.height=a,i.depth=s,i.isReady=!0,i.samples=1,i.generateMipMaps=!!e.generateMipMaps,i.samplingMode=e.samplingMode,i.type=e.type,i.format=e.format,i._generateDepthBuffer=e.generateDepthBuffer,i._generateStencilBuffer=!!e.generateStencilBuffer,this._internalTexturesCache.push(i),i},Bt.a.prototype.createDepthStencilTexture=function(r,t){if(t.isCube){var e=r.width||r;return this._createDepthStencilCubeTexture(e,t)}return this._createDepthStencilTexture(r,t)},Bt.a.prototype._createDepthStencilTexture=function(r,t){var e=this._gl,n=r.layers||0,i=n!==0?e.TEXTURE_2D_ARRAY:e.TEXTURE_2D,o=new Ct.a(this,Ct.b.Depth);if(!this._caps.depthTextureExtension)return l.a.Error("Depth texture is not supported by your browser or hardware."),o;var a=Object(c.a)({bilinearFiltering:!1,comparisonFunction:0,generateStencil:!1},t);this._bindTextureDirectly(i,o,!0),this._setupDepthStencilTexture(o,r,a.generateStencil,a.bilinearFiltering,a.comparisonFunction);var s=a.generateStencil?e.UNSIGNED_INT_24_8:e.UNSIGNED_INT,d=a.generateStencil?e.DEPTH_STENCIL:e.DEPTH_COMPONENT,p=d;return this.webGLVersion>1&&(p=a.generateStencil?e.DEPTH24_STENCIL8:e.DEPTH_COMPONENT24),o.is2DArray?e.texImage3D(i,0,p,o.width,o.height,n,0,d,s,null):e.texImage2D(i,0,p,o.width,o.height,0,d,s,null),this._bindTextureDirectly(i,null),o};var _t=function(){function r(t,e,n,i,o,a,s,d,p,b,P,O,B,F,z){s===void 0&&(s=h.a.TEXTURE_NEAREST_SAMPLINGMODE),b===void 0&&(b=null),P===void 0&&(P=h.a.TEXTURETYPE_UNSIGNED_INT),O===void 0&&(O="postprocess"),F===void 0&&(F=!1),z===void 0&&(z=h.a.TEXTUREFORMAT_RGBA),this.width=-1,this.height=-1,this.nodeMaterialSource=null,this._outputTexture=null,this.autoClear=!0,this.alphaMode=h.a.ALPHA_DISABLE,this.animations=new Array,this.enablePixelPerfectMode=!1,this.forceFullscreenViewport=!0,this.scaleMode=h.a.SCALEMODE_FLOOR,this.alwaysForcePOT=!1,this._samples=1,this.adaptScaleToCurrentViewport=!1,this._reusable=!1,this._textures=new fi.a(2),this._currentRenderTextureInd=0,this._scaleRatio=new u.d(1,1),this._texelSize=u.d.Zero(),this.onActivateObservable=new C.c,this.onSizeChangedObservable=new C.c,this.onApplyObservable=new C.c,this.onBeforeRenderObservable=new C.c,this.onAfterRenderObservable=new C.c,this.name=t,a!=null?(this._camera=a,this._scene=a.getScene(),a.attachPostProcess(this),this._engine=this._scene.getEngine(),this._scene.postProcesses.push(this),this.uniqueId=this._scene.getUniqueId()):d&&(this._engine=d,this._engine.postProcesses.push(this)),this._options=o,this.renderTargetSamplingMode=s||h.a.TEXTURE_NEAREST_SAMPLINGMODE,this._reusable=p||!1,this._textureType=P,this._textureFormat=z,this._samplers=i||[],this._samplers.push("textureSampler"),this._fragmentUrl=e,this._vertexUrl=O,this._parameters=n||[],this._parameters.push("scale"),this._indexParameters=B,F||this.updateEffect(b)}return Object.defineProperty(r.prototype,"samples",{get:function(){return this._samples},set:function(t){var e=this;this._samples=Math.min(t,this._engine.getCaps().maxMSAASamples),this._textures.forEach(function(n){n.samples!==e._samples&&e._engine.updateRenderTargetTextureSampleCount(n,e._samples)})},enumerable:!1,configurable:!0}),r.prototype.getEffectName=function(){return this._fragmentUrl},Object.defineProperty(r.prototype,"onActivate",{set:function(t){this._onActivateObserver&&this.onActivateObservable.remove(this._onActivateObserver),t&&(this._onActivateObserver=this.onActivateObservable.add(t))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onSizeChanged",{set:function(t){this._onSizeChangedObserver&&this.onSizeChangedObservable.remove(this._onSizeChangedObserver),this._onSizeChangedObserver=this.onSizeChangedObservable.add(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onApply",{set:function(t){this._onApplyObserver&&this.onApplyObservable.remove(this._onApplyObserver),this._onApplyObserver=this.onApplyObservable.add(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onBeforeRender",{set:function(t){this._onBeforeRenderObserver&&this.onBeforeRenderObservable.remove(this._onBeforeRenderObserver),this._onBeforeRenderObserver=this.onBeforeRenderObservable.add(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onAfterRender",{set:function(t){this._onAfterRenderObserver&&this.onAfterRenderObservable.remove(this._onAfterRenderObserver),this._onAfterRenderObserver=this.onAfterRenderObservable.add(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"inputTexture",{get:function(){return this._textures.data[this._currentRenderTextureInd]},set:function(t){this._forcedOutputTexture=t},enumerable:!1,configurable:!0}),r.prototype.restoreDefaultInputTexture=function(){this._forcedOutputTexture=null},r.prototype.getCamera=function(){return this._camera},Object.defineProperty(r.prototype,"texelSize",{get:function(){return this._shareOutputWithPostProcess?this._shareOutputWithPostProcess.texelSize:(this._forcedOutputTexture&&this._texelSize.copyFromFloats(1/this._forcedOutputTexture.width,1/this._forcedOutputTexture.height),this._texelSize)},enumerable:!1,configurable:!0}),r.prototype.getClassName=function(){return"PostProcess"},r.prototype.getEngine=function(){return this._engine},r.prototype.getEffect=function(){return this._effect},r.prototype.shareOutputWith=function(t){return this._disposeTextures(),this._shareOutputWithPostProcess=t,this},r.prototype.useOwnOutput=function(){this._textures.length==0&&(this._textures=new fi.a(2)),this._shareOutputWithPostProcess=null},r.prototype.updateEffect=function(t,e,n,i,o,a,s,d){t===void 0&&(t=null),e===void 0&&(e=null),n===void 0&&(n=null),this._effect=this._engine.createEffect({vertex:s??this._vertexUrl,fragment:d??this._fragmentUrl},["position"],e||this._parameters,n||this._samplers,t!==null?t:"",void 0,o,a,i||this._indexParameters)},r.prototype.isReusable=function(){return this._reusable},r.prototype.markTextureDirty=function(){this.width=-1},r.prototype.activate=function(t,e,n){var i=this;e===void 0&&(e=null);var o=(t=t||this._camera).getScene(),a=o.getEngine(),s=a.getCaps().maxTextureSize,d=(e?e.width:this._engine.getRenderWidth(!0))*this._options|0,p=(e?e.height:this._engine.getRenderHeight(!0))*this._options|0,b=t.parent;!b||b.leftCamera!=t&&b.rightCamera!=t||(d/=2);var P,O=this._options.width||d,B=this._options.height||p,F=this.renderTargetSamplingMode!==h.a.TEXTURE_NEAREST_LINEAR&&this.renderTargetSamplingMode!==h.a.TEXTURE_NEAREST_NEAREST&&this.renderTargetSamplingMode!==h.a.TEXTURE_LINEAR_LINEAR;if(!this._shareOutputWithPostProcess&&!this._forcedOutputTexture){if(this.adaptScaleToCurrentViewport){var z=a.currentViewport;z&&(O*=z.width,B*=z.height)}if((F||this.alwaysForcePOT)&&(this._options.width||(O=a.needPOTTextures?Ue.a.GetExponentOfTwo(O,s,this.scaleMode):O),this._options.height||(B=a.needPOTTextures?Ue.a.GetExponentOfTwo(B,s,this.scaleMode):B)),this.width!==O||this.height!==B){if(this._textures.length>0){for(var J=0;J<this._textures.length;J++)this._engine._releaseTexture(this._textures.data[J]);this._textures.reset()}this.width=O,this.height=B;var ie={width:this.width,height:this.height},se={generateMipMaps:F,generateDepthBuffer:n||t._postProcesses.indexOf(this)===0,generateStencilBuffer:(n||t._postProcesses.indexOf(this)===0)&&this._engine.isStencilEnable,samplingMode:this.renderTargetSamplingMode,type:this._textureType,format:this._textureFormat};this._textures.push(this._engine.createRenderTargetTexture(ie,se)),this._reusable&&this._textures.push(this._engine.createRenderTargetTexture(ie,se)),this._texelSize.copyFromFloats(1/this.width,1/this.height),this.onSizeChangedObservable.notifyObservers(this)}this._textures.forEach(function(ce){ce.samples!==i.samples&&i._engine.updateRenderTargetTextureSampleCount(ce,i.samples)})}return this._shareOutputWithPostProcess?P=this._shareOutputWithPostProcess.inputTexture:this._forcedOutputTexture?(P=this._forcedOutputTexture,this.width=this._forcedOutputTexture.width,this.height=this._forcedOutputTexture.height):P=this.inputTexture,this.enablePixelPerfectMode?(this._scaleRatio.copyFromFloats(d/O,p/B),this._engine.bindFramebuffer(P,0,d,p,this.forceFullscreenViewport)):(this._scaleRatio.copyFromFloats(1,1),this._engine.bindFramebuffer(P,0,void 0,void 0,this.forceFullscreenViewport)),this.onActivateObservable.notifyObservers(t),this.autoClear&&this.alphaMode===h.a.ALPHA_DISABLE&&this._engine.clear(this.clearColor?this.clearColor:o.clearColor,o._allowPostProcessClearColor,!0,!0),this._reusable&&(this._currentRenderTextureInd=(this._currentRenderTextureInd+1)%2),P},Object.defineProperty(r.prototype,"isSupported",{get:function(){return this._effect.isSupported},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"aspectRatio",{get:function(){return this._shareOutputWithPostProcess?this._shareOutputWithPostProcess.aspectRatio:this._forcedOutputTexture?this._forcedOutputTexture.width/this._forcedOutputTexture.height:this.width/this.height},enumerable:!1,configurable:!0}),r.prototype.isReady=function(){return this._effect&&this._effect.isReady()},r.prototype.apply=function(){return this._effect&&this._effect.isReady()?(this._engine.enableEffect(this._effect),this._engine.setState(!1),this._engine.setDepthBuffer(!1),this._engine.setDepthWrite(!1),this._engine.setAlphaMode(this.alphaMode),this.alphaConstants&&this.getEngine().setAlphaConstants(this.alphaConstants.r,this.alphaConstants.g,this.alphaConstants.b,this.alphaConstants.a),t=this._shareOutputWithPostProcess?this._shareOutputWithPostProcess.inputTexture:this._forcedOutputTexture?this._forcedOutputTexture:this.inputTexture,this._effect._bindTexture("textureSampler",t),this._effect.setVector2("scale",this._scaleRatio),this.onApplyObservable.notifyObservers(this._effect),this._effect):null;var t},r.prototype._disposeTextures=function(){if(!this._shareOutputWithPostProcess&&!this._forcedOutputTexture){if(this._textures.length>0)for(var t=0;t<this._textures.length;t++)this._engine._releaseTexture(this._textures.data[t]);this._textures.dispose()}},r.prototype.setPrePassRenderer=function(t){return!!this._prePassEffectConfiguration&&(this._prePassEffectConfiguration=t.addEffectConfiguration(this._prePassEffectConfiguration),this._prePassEffectConfiguration.enabled=!0,!0)},r.prototype.dispose=function(t){var e;if(t=t||this._camera,this._disposeTextures(),this._scene&&(e=this._scene.postProcesses.indexOf(this))!==-1&&this._scene.postProcesses.splice(e,1),(e=this._engine.postProcesses.indexOf(this))!==-1&&this._engine.postProcesses.splice(e,1),t){if(t.detachPostProcess(this),(e=t._postProcesses.indexOf(this))===0&&t._postProcesses.length>0){var n=this._camera._getFirstPostProcess();n&&n.markTextureDirty()}this.onActivateObservable.clear(),this.onAfterRenderObservable.clear(),this.onApplyObservable.clear(),this.onBeforeRenderObservable.clear(),this.onSizeChangedObservable.clear()}},r.prototype.serialize=function(){var t=L.a.Serialize(this);return t.customType="BABYLON."+this.getClassName(),t.cameraId=this.getCamera().id,t.reusable=this._reusable,t.options=this._options,t.textureType=this._textureType,t},r.Parse=function(t,e,n){var i=R.a.GetClass(t.customType);if(!i||!i._Parse)return null;var o=e.getCameraByID(t.cameraId);return o?i._Parse(t,o,e,n):null},Object(c.c)([Object(L.c)()],r.prototype,"uniqueId",void 0),Object(c.c)([Object(L.c)()],r.prototype,"name",void 0),Object(c.c)([Object(L.c)()],r.prototype,"width",void 0),Object(c.c)([Object(L.c)()],r.prototype,"height",void 0),Object(c.c)([Object(L.c)()],r.prototype,"renderTargetSamplingMode",void 0),Object(c.c)([Object(L.f)()],r.prototype,"clearColor",void 0),Object(c.c)([Object(L.c)()],r.prototype,"autoClear",void 0),Object(c.c)([Object(L.c)()],r.prototype,"alphaMode",void 0),Object(c.c)([Object(L.c)()],r.prototype,"alphaConstants",void 0),Object(c.c)([Object(L.c)()],r.prototype,"enablePixelPerfectMode",void 0),Object(c.c)([Object(L.c)()],r.prototype,"forceFullscreenViewport",void 0),Object(c.c)([Object(L.c)()],r.prototype,"scaleMode",void 0),Object(c.c)([Object(L.c)()],r.prototype,"alwaysForcePOT",void 0),Object(c.c)([Object(L.c)("samples")],r.prototype,"_samples",void 0),Object(c.c)([Object(L.c)()],r.prototype,"adaptScaleToCurrentViewport",void 0),r}();R.a.RegisteredTypes["BABYLON.PostProcess"]=_t;var zf=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-void main(void)
-{
-gl_FragColor=texture2D(textureSampler,vUV);
-}`;ze.a.ShadersStore.passPixelShader=zf;var jf=`
-varying vec2 vUV;
-uniform samplerCube textureSampler;
-void main(void)
-{
-vec2 uv=vUV*2.0-1.0;
-#ifdef POSITIVEX
-gl_FragColor=textureCube(textureSampler,vec3(1.001,uv.y,uv.x));
-#endif
-#ifdef NEGATIVEX
-gl_FragColor=textureCube(textureSampler,vec3(-1.001,uv.y,uv.x));
-#endif
-#ifdef POSITIVEY
-gl_FragColor=textureCube(textureSampler,vec3(uv.y,1.001,uv.x));
-#endif
-#ifdef NEGATIVEY
-gl_FragColor=textureCube(textureSampler,vec3(uv.y,-1.001,uv.x));
-#endif
-#ifdef POSITIVEZ
-gl_FragColor=textureCube(textureSampler,vec3(uv,1.001));
-#endif
-#ifdef NEGATIVEZ
-gl_FragColor=textureCube(textureSampler,vec3(uv,-1.001));
-#endif
-}`;ze.a.ShadersStore.passCubePixelShader=jf;var Fi=function(r){function t(e,n,i,o,a,s,d,p){return i===void 0&&(i=null),d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT),p===void 0&&(p=!1),r.call(this,e,"pass",null,null,n,i,o,a,s,void 0,d,void 0,null,p)||this}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"PassPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},t}(_t);R.a.RegisteredTypes["BABYLON.PassPostProcess"]=Fi;var Hf=function(r){function t(e,n,i,o,a,s,d,p){i===void 0&&(i=null),d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT),p===void 0&&(p=!1);var b=r.call(this,e,"passCube",null,null,n,i,o,a,s,"#define POSITIVEX",d,void 0,null,p)||this;return b._face=0,b}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"face",{get:function(){return this._face},set:function(e){if(!(e<0||e>5))switch(this._face=e,this._face){case 0:this.updateEffect("#define POSITIVEX");break;case 1:this.updateEffect("#define NEGATIVEX");break;case 2:this.updateEffect("#define POSITIVEY");break;case 3:this.updateEffect("#define NEGATIVEY");break;case 4:this.updateEffect("#define POSITIVEZ");break;case 5:this.updateEffect("#define NEGATIVEZ")}},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"PassCubePostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},t}(_t);Ue.a._RescalePostProcessFactory=function(r){return new Fi("rescale",1,null,h.a.TEXTURE_BILINEAR_SAMPLINGMODE,r,!1,h.a.TEXTURETYPE_UNSIGNED_INT)};var Wf=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform sampler2D leftSampler;
-void main(void)
-{
-vec4 leftFrag=texture2D(leftSampler,vUV);
-leftFrag=vec4(1.0,leftFrag.g,leftFrag.b,1.0);
-vec4 rightFrag=texture2D(textureSampler,vUV);
-rightFrag=vec4(rightFrag.r,1.0,1.0,1.0);
-gl_FragColor=vec4(rightFrag.rgb*leftFrag.rgb,1.0);
-}`;ze.a.ShadersStore.anaglyphPixelShader=Wf;var hs=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,"anaglyph",null,["leftSampler"],n,i[1],o,a,s)||this;return d._passedProcess=i[0]._rigPostProcess,d.onApplyObservable.add(function(p){p.setTextureFromPostProcess("leftSampler",d._passedProcess)}),d}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"AnaglyphPostProcess"},t}(_t);R.a.RegisteredTypes["BABYLON.AnaglyphPostProcess"]=hs,gt.a._setStereoscopicAnaglyphRigMode=function(r){r._rigCameras[0]._rigPostProcess=new Fi(r.name+"_passthru",1,r._rigCameras[0]),r._rigCameras[1]._rigPostProcess=new hs(r.name+"_anaglyph",1,r._rigCameras)},Q.a.AddNodeConstructor("AnaglyphArcRotateCamera",function(r,t,e){return function(){return new Ll(r,0,0,1,u.e.Zero(),e.interaxial_distance,t)}});var Ll=function(r){function t(e,n,i,o,a,s,d){var p=r.call(this,e,n,i,o,a,d)||this;return p.interaxialDistance=s,p.setCameraRigMode(gt.a.RIG_MODE_STEREOSCOPIC_ANAGLYPH,{interaxialDistance:s}),p}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"AnaglyphArcRotateCamera"},t}(Ji);Q.a.AddNodeConstructor("AnaglyphFreeCamera",function(r,t,e){return function(){return new Nl(r,u.e.Zero(),e.interaxial_distance,t)}});var Nl=function(r){function t(e,n,i,o){var a=r.call(this,e,n,o)||this;return a.interaxialDistance=i,a.setCameraRigMode(gt.a.RIG_MODE_STEREOSCOPIC_ANAGLYPH,{interaxialDistance:i}),a}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"AnaglyphFreeCamera"},t}(Yn);Q.a.AddNodeConstructor("AnaglyphGamepadCamera",function(r,t,e){return function(){return new wl(r,u.e.Zero(),e.interaxial_distance,t)}});var wl=function(r){function t(e,n,i,o){var a=r.call(this,e,n,o)||this;return a.interaxialDistance=i,a.setCameraRigMode(gt.a.RIG_MODE_STEREOSCOPIC_ANAGLYPH,{interaxialDistance:i}),a}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"AnaglyphGamepadCamera"},t}(Bo);Q.a.AddNodeConstructor("AnaglyphUniversalCamera",function(r,t,e){return function(){return new Fl(r,u.e.Zero(),e.interaxial_distance,t)}});var Fl=function(r){function t(e,n,i,o){var a=r.call(this,e,n,o)||this;return a.interaxialDistance=i,a.setCameraRigMode(gt.a.RIG_MODE_STEREOSCOPIC_ANAGLYPH,{interaxialDistance:i}),a}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"AnaglyphUniversalCamera"},t}(_r),Kn=f(58);gt.a._setStereoscopicRigMode=function(r){var t=r.cameraRigMode===gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL||r.cameraRigMode===gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED,e=r.cameraRigMode===gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_CROSSEYED;r._rigCameras[e?1:0].viewport=new Kn.a(0,0,t?.5:1,t?1:.5),r._rigCameras[e?0:1].viewport=new Kn.a(t?.5:0,t?0:.5,t?.5:1,t?1:.5)},Q.a.AddNodeConstructor("StereoscopicArcRotateCamera",function(r,t,e){return function(){return new Bl(r,0,0,1,u.e.Zero(),e.interaxial_distance,e.isStereoscopicSideBySide,t)}});var Bl=function(r){function t(e,n,i,o,a,s,d,p){var b=r.call(this,e,n,i,o,a,p)||this;return b.interaxialDistance=s,b.isStereoscopicSideBySide=d,b.setCameraRigMode(d?gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:gt.a.RIG_MODE_STEREOSCOPIC_OVERUNDER,{interaxialDistance:s}),b}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"StereoscopicArcRotateCamera"},t}(Ji);Q.a.AddNodeConstructor("StereoscopicFreeCamera",function(r,t,e){return function(){return new Ul(r,u.e.Zero(),e.interaxial_distance,e.isStereoscopicSideBySide,t)}});var Ul=function(r){function t(e,n,i,o,a){var s=r.call(this,e,n,a)||this;return s.interaxialDistance=i,s.isStereoscopicSideBySide=o,s.setCameraRigMode(o?gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:gt.a.RIG_MODE_STEREOSCOPIC_OVERUNDER,{interaxialDistance:i}),s}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"StereoscopicFreeCamera"},t}(Yn);Q.a.AddNodeConstructor("StereoscopicGamepadCamera",function(r,t,e){return function(){return new Vl(r,u.e.Zero(),e.interaxial_distance,e.isStereoscopicSideBySide,t)}});var Vl=function(r){function t(e,n,i,o,a){var s=r.call(this,e,n,a)||this;return s.interaxialDistance=i,s.isStereoscopicSideBySide=o,s.setCameraRigMode(o?gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:gt.a.RIG_MODE_STEREOSCOPIC_OVERUNDER,{interaxialDistance:i}),s}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"StereoscopicGamepadCamera"},t}(Bo);Q.a.AddNodeConstructor("StereoscopicFreeCamera",function(r,t,e){return function(){return new kl(r,u.e.Zero(),e.interaxial_distance,e.isStereoscopicSideBySide,t)}});var kl=function(r){function t(e,n,i,o,a){var s=r.call(this,e,n,a)||this;return s.interaxialDistance=i,s.isStereoscopicSideBySide=o,s.setCameraRigMode(o?gt.a.RIG_MODE_STEREOSCOPIC_SIDEBYSIDE_PARALLEL:gt.a.RIG_MODE_STEREOSCOPIC_OVERUNDER,{interaxialDistance:i}),s}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"StereoscopicUniversalCamera"},t}(_r);Q.a.AddNodeConstructor("VirtualJoysticksCamera",function(r,t){return function(){return new Gl(r,u.e.Zero(),t)}});var Gl=function(r){function t(e,n,i){var o=r.call(this,e,n,i)||this;return o.inputs.addVirtualJoystick(),o}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VirtualJoysticksCamera"},t}(Yn),mr=function(){function r(){this.compensateDistortion=!0,this.multiviewEnabled=!1}return Object.defineProperty(r.prototype,"aspectRatio",{get:function(){return this.hResolution/(2*this.vResolution)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"aspectRatioFov",{get:function(){return 2*Math.atan(this.postProcessScaleFactor*this.vScreenSize/(2*this.eyeToScreenDistance))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"leftHMatrix",{get:function(){var t=4*(this.hScreenSize/4-this.lensSeparationDistance/2)/this.hScreenSize;return u.a.Translation(t,0,0)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rightHMatrix",{get:function(){var t=4*(this.hScreenSize/4-this.lensSeparationDistance/2)/this.hScreenSize;return u.a.Translation(-t,0,0)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"leftPreViewMatrix",{get:function(){return u.a.Translation(.5*this.interpupillaryDistance,0,0)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rightPreViewMatrix",{get:function(){return u.a.Translation(-.5*this.interpupillaryDistance,0,0)},enumerable:!1,configurable:!0}),r.GetDefault=function(){var t=new r;return t.hResolution=1280,t.vResolution=800,t.hScreenSize=.149759993,t.vScreenSize=.0935999975,t.vScreenCenter=.0467999987,t.eyeToScreenDistance=.0410000011,t.lensSeparationDistance=.063500002,t.interpupillaryDistance=.064000003,t.distortionK=[1,.219999999,.239999995,0],t.chromaAbCorrection=[.995999992,-.00400000019,1.01400006,0],t.postProcessScaleFactor=1.714605507808412,t.lensCenterOffset=.151976421,t},r}(),Xf=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform vec2 LensCenter;
-uniform vec2 Scale;
-uniform vec2 ScaleIn;
-uniform vec4 HmdWarpParam;
-vec2 HmdWarp(vec2 in01) {
-vec2 theta=(in01-LensCenter)*ScaleIn;
-float rSq=theta.x*theta.x+theta.y*theta.y;
-vec2 rvector=theta*(HmdWarpParam.x+HmdWarpParam.y*rSq+HmdWarpParam.z*rSq*rSq+HmdWarpParam.w*rSq*rSq*rSq);
-return LensCenter+Scale*rvector;
-}
-void main(void)
-{
-vec2 tc=HmdWarp(vUV);
-if (tc.x <0.0 || tc.x>1.0 || tc.y<0.0 || tc.y>1.0)
-gl_FragColor=vec4(0.0,0.0,0.0,0.0);
-else{
-gl_FragColor=texture2D(textureSampler,tc);
-}
-}`;ze.a.ShadersStore.vrDistortionCorrectionPixelShader=Xf;var ds=function(r){function t(e,n,i,o){var a=r.call(this,e,"vrDistortionCorrection",["LensCenter","Scale","ScaleIn","HmdWarpParam"],null,o.postProcessScaleFactor,n,we.a.BILINEAR_SAMPLINGMODE)||this;return a._isRightEye=i,a._distortionFactors=o.distortionK,a._postProcessScaleFactor=o.postProcessScaleFactor,a._lensCenterOffset=o.lensCenterOffset,a.adaptScaleToCurrentViewport=!0,a.onSizeChangedObservable.add(function(){a._scaleIn=new u.d(2,2/a.aspectRatio),a._scaleFactor=new u.d(1/a._postProcessScaleFactor*.5,1/a._postProcessScaleFactor*.5*a.aspectRatio),a._lensCenter=new u.d(a._isRightEye?.5-.5*a._lensCenterOffset:.5+.5*a._lensCenterOffset,.5)}),a.onApplyObservable.add(function(s){s.setFloat2("LensCenter",a._lensCenter.x,a._lensCenter.y),s.setFloat2("Scale",a._scaleFactor.x,a._scaleFactor.y),s.setFloat2("ScaleIn",a._scaleIn.x,a._scaleIn.y),s.setFloat4("HmdWarpParam",a._distortionFactors[0],a._distortionFactors[1],a._distortionFactors[2],a._distortionFactors[3])}),a}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VRDistortionCorrectionPostProcess"},t}(_t),Yf=`precision mediump sampler2DArray;
-varying vec2 vUV;
-uniform sampler2DArray multiviewSampler;
-uniform int imageIndex;
-void main(void)
-{
-gl_FragColor=texture(multiviewSampler,vec3(vUV,imageIndex));
-}`;ze.a.ShadersStore.vrMultiviewToSingleviewPixelShader=Yf;var zl=f(85),fs=f(95),to=f(96);Bt.a.prototype.createRenderTargetCubeTexture=function(r,t){var e=Object(c.a)({generateMipMaps:!0,generateDepthBuffer:!0,generateStencilBuffer:!1,type:h.a.TEXTURETYPE_UNSIGNED_INT,samplingMode:h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,format:h.a.TEXTUREFORMAT_RGBA},t);e.generateStencilBuffer=e.generateDepthBuffer&&e.generateStencilBuffer,(e.type!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloatLinearFiltering)&&(e.type!==h.a.TEXTURETYPE_HALF_FLOAT||this._caps.textureHalfFloatLinearFiltering)||(e.samplingMode=h.a.TEXTURE_NEAREST_SAMPLINGMODE);var n=this._gl,i=new Ct.a(this,Ct.b.RenderTarget);this._bindTextureDirectly(n.TEXTURE_CUBE_MAP,i,!0);var o=this._getSamplingParameters(e.samplingMode,e.generateMipMaps);e.type!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloat||(e.type=h.a.TEXTURETYPE_UNSIGNED_INT,l.a.Warn("Float textures are not supported. Cube render target forced to TEXTURETYPE_UNESIGNED_BYTE type")),n.texParameteri(n.TEXTURE_CUBE_MAP,n.TEXTURE_MAG_FILTER,o.mag),n.texParameteri(n.TEXTURE_CUBE_MAP,n.TEXTURE_MIN_FILTER,o.min),n.texParameteri(n.TEXTURE_CUBE_MAP,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_CUBE_MAP,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE);for(var a=0;a<6;a++)n.texImage2D(n.TEXTURE_CUBE_MAP_POSITIVE_X+a,0,this._getRGBABufferInternalSizedFormat(e.type,e.format),r,r,0,this._getInternalFormat(e.format),this._getWebGLTextureType(e.type),null);var s=n.createFramebuffer();return this._bindUnboundFramebuffer(s),i._depthStencilBuffer=this._setupFramebufferDepthAttachments(e.generateStencilBuffer,e.generateDepthBuffer,r,r),e.generateMipMaps&&n.generateMipmap(n.TEXTURE_CUBE_MAP),this._bindTextureDirectly(n.TEXTURE_CUBE_MAP,null),this._bindUnboundFramebuffer(null),i._framebuffer=s,i.width=r,i.height=r,i.isReady=!0,i.isCube=!0,i.samples=1,i.generateMipMaps=e.generateMipMaps,i.samplingMode=e.samplingMode,i.type=e.type,i.format=e.format,i._generateDepthBuffer=e.generateDepthBuffer,i._generateStencilBuffer=e.generateStencilBuffer,this._internalTexturesCache.push(i),i};var sn=function(r){function t(e,n,i,o,a,s,d,p,b,P,O,B,F){a===void 0&&(a=!0),s===void 0&&(s=h.a.TEXTURETYPE_UNSIGNED_INT),d===void 0&&(d=!1),p===void 0&&(p=we.a.TRILINEAR_SAMPLINGMODE),b===void 0&&(b=!0),P===void 0&&(P=!1),O===void 0&&(O=!1),B===void 0&&(B=h.a.TEXTUREFORMAT_RGBA),F===void 0&&(F=!1);var z=r.call(this,null,i,!o)||this;return z.renderParticles=!0,z.renderSprites=!1,z.ignoreCameraViewport=!1,z.onBeforeBindObservable=new C.c,z.onAfterUnbindObservable=new C.c,z.onBeforeRenderObservable=new C.c,z.onAfterRenderObservable=new C.c,z.onClearObservable=new C.c,z.onResizeObservable=new C.c,z._currentRefreshId=-1,z._refreshRate=1,z._samples=1,z.boundingBoxPosition=u.e.Zero(),(i=z.getScene())&&(z._coordinatesMode=we.a.PROJECTION_MODE,z.renderList=new Array,z.name=e,z.isRenderTarget=!0,z._initialSizeParameter=n,z._processSizeParameter(n),z._resizeObserver=z.getScene().getEngine().onResizeObservable.add(function(){}),z._generateMipMaps=!!o,z._doNotChangeAspectRatio=a,z._renderingManager=new to.b(i),z._renderingManager._useSceneAutoClearSetup=!0,O||(z._renderTargetOptions={generateMipMaps:o,type:s,format:B,samplingMode:p,generateDepthBuffer:b,generateStencilBuffer:P},p===we.a.NEAREST_SAMPLINGMODE&&(z.wrapU=we.a.CLAMP_ADDRESSMODE,z.wrapV=we.a.CLAMP_ADDRESSMODE),F||(d?(z._texture=i.getEngine().createRenderTargetCubeTexture(z.getRenderSize(),z._renderTargetOptions),z.coordinatesMode=we.a.INVCUBIC_MODE,z._textureMatrix=u.a.Identity()):z._texture=i.getEngine().createRenderTargetTexture(z._size,z._renderTargetOptions)))),z}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"renderList",{get:function(){return this._renderList},set:function(e){this._renderList=e,this._renderList&&this._hookArray(this._renderList)},enumerable:!1,configurable:!0}),t.prototype._hookArray=function(e){var n=this,i=e.push;e.push=function(){for(var a=[],s=0;s<arguments.length;s++)a[s]=arguments[s];var d=e.length===0,p=i.apply(e,a);return d&&n.getScene()&&n.getScene().meshes.forEach(function(b){b._markSubMeshesAsLightDirty()}),p};var o=e.splice;e.splice=function(a,s){var d=o.apply(e,[a,s]);return e.length===0&&n.getScene().meshes.forEach(function(p){p._markSubMeshesAsLightDirty()}),d}},Object.defineProperty(t.prototype,"onAfterUnbind",{set:function(e){this._onAfterUnbindObserver&&this.onAfterUnbindObservable.remove(this._onAfterUnbindObserver),this._onAfterUnbindObserver=this.onAfterUnbindObservable.add(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onBeforeRender",{set:function(e){this._onBeforeRenderObserver&&this.onBeforeRenderObservable.remove(this._onBeforeRenderObserver),this._onBeforeRenderObserver=this.onBeforeRenderObservable.add(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onAfterRender",{set:function(e){this._onAfterRenderObserver&&this.onAfterRenderObservable.remove(this._onAfterRenderObserver),this._onAfterRenderObserver=this.onAfterRenderObservable.add(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onClear",{set:function(e){this._onClearObserver&&this.onClearObservable.remove(this._onClearObserver),this._onClearObserver=this.onClearObservable.add(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"renderTargetOptions",{get:function(){return this._renderTargetOptions},enumerable:!1,configurable:!0}),t.prototype._onRatioRescale=function(){this._sizeRatio&&this.resize(this._initialSizeParameter)},Object.defineProperty(t.prototype,"boundingBoxSize",{get:function(){return this._boundingBoxSize},set:function(e){if(!this._boundingBoxSize||!this._boundingBoxSize.equals(e)){this._boundingBoxSize=e;var n=this.getScene();n&&n.markAllMaterialsAsDirty(h.a.MATERIAL_TextureDirtyFlag)}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"depthStencilTexture",{get:function(){var e;return((e=this.getInternalTexture())===null||e===void 0?void 0:e._depthStencilTexture)||null},enumerable:!1,configurable:!0}),t.prototype.createDepthStencilTexture=function(e,n,i){e===void 0&&(e=0),n===void 0&&(n=!0),i===void 0&&(i=!1);var o=this.getInternalTexture();if(this.getScene()&&o){var a=this.getScene().getEngine();o._depthStencilTexture=a.createDepthStencilTexture(this._size,{bilinearFiltering:n,comparisonFunction:e,generateStencil:i,isCube:this.isCube})}},t.prototype._processSizeParameter=function(e){if(e.ratio){this._sizeRatio=e.ratio;var n=this._getEngine();this._size={width:this._bestReflectionRenderTargetDimension(n.getRenderWidth(),this._sizeRatio),height:this._bestReflectionRenderTargetDimension(n.getRenderHeight(),this._sizeRatio)}}else this._size=e},Object.defineProperty(t.prototype,"samples",{get:function(){return this._samples},set:function(e){if(this._samples!==e){var n=this.getScene();n&&(this._samples=n.getEngine().updateRenderTargetTextureSampleCount(this._texture,e))}},enumerable:!1,configurable:!0}),t.prototype.resetRefreshCounter=function(){this._currentRefreshId=-1},Object.defineProperty(t.prototype,"refreshRate",{get:function(){return this._refreshRate},set:function(e){this._refreshRate=e,this.resetRefreshCounter()},enumerable:!1,configurable:!0}),t.prototype.addPostProcess=function(e){if(!this._postProcessManager){var n=this.getScene();if(!n)return;this._postProcessManager=new fs.a(n),this._postProcesses=new Array}this._postProcesses.push(e),this._postProcesses[0].autoClear=!1},t.prototype.clearPostProcesses=function(e){if(e===void 0&&(e=!1),this._postProcesses){if(e)for(var n=0,i=this._postProcesses;n<i.length;n++)i[n].dispose();this._postProcesses=[]}},t.prototype.removePostProcess=function(e){if(this._postProcesses){var n=this._postProcesses.indexOf(e);n!==-1&&(this._postProcesses.splice(n,1),this._postProcesses.length>0&&(this._postProcesses[0].autoClear=!1))}},t.prototype._shouldRender=function(){return this._currentRefreshId===-1||this.refreshRate===this._currentRefreshId?(this._currentRefreshId=1,!0):(this._currentRefreshId++,!1)},t.prototype.getRenderSize=function(){return this.getRenderWidth()},t.prototype.getRenderWidth=function(){return this._size.width?this._size.width:this._size},t.prototype.getRenderHeight=function(){return this._size.width?this._size.height:this._size},t.prototype.getRenderLayers=function(){var e=this._size.layers;return e||0},Object.defineProperty(t.prototype,"canRescale",{get:function(){return!0},enumerable:!1,configurable:!0}),t.prototype.scale=function(e){var n=Math.max(1,this.getRenderSize()*e);this.resize(n)},t.prototype.getReflectionTextureMatrix=function(){return this.isCube?this._textureMatrix:r.prototype.getReflectionTextureMatrix.call(this)},t.prototype.resize=function(e){var n=this.isCube;this.releaseInternalTexture();var i=this.getScene();i&&(this._processSizeParameter(e),this._texture=n?i.getEngine().createRenderTargetCubeTexture(this.getRenderSize(),this._renderTargetOptions):i.getEngine().createRenderTargetTexture(this._size,this._renderTargetOptions),this.onResizeObservable.hasObservers()&&this.onResizeObservable.notifyObservers(this))},t.prototype.render=function(e,n){if(e===void 0&&(e=!1),n===void 0&&(n=!1),p=this.getScene()){var i,o=p.getEngine();if(this.useCameraPostProcesses!==void 0&&(e=this.useCameraPostProcesses),this._waitingRenderList){this.renderList=[];for(var a=0;a<this._waitingRenderList.length;a++){var s=this._waitingRenderList[a],d=p.getMeshByID(s);d&&this.renderList.push(d)}this._waitingRenderList=void 0}if(this.renderListPredicate){var p;if(this.renderList?this.renderList.length=0:this.renderList=[],!(p=this.getScene()))return;var b=p.meshes;for(a=0;a<b.length;a++){var P=b[a];this.renderListPredicate(P)&&this.renderList.push(P)}}if(this.onBeforeBindObservable.notifyObservers(this),this.activeCamera?(i=this.activeCamera,o.setViewport(this.activeCamera.viewport,this.getRenderWidth(),this.getRenderHeight()),this.activeCamera!==p.activeCamera&&p.setTransformMatrix(this.activeCamera.getViewMatrix(),this.activeCamera.getProjectionMatrix(!0))):(i=p.activeCamera)&&o.setViewport(i.viewport,this.getRenderWidth(),this.getRenderHeight()),this._defaultRenderListPrepared=!1,this.is2DArray)for(var O=0;O<this.getRenderLayers();O++)this.renderToTarget(0,e,n,O,i),p.incrementRenderId(),p.resetCachedMaterial();else if(this.isCube)for(var B=0;B<6;B++)this.renderToTarget(B,e,n,void 0,i),p.incrementRenderId(),p.resetCachedMaterial();else this.renderToTarget(0,e,n,void 0,i);this.onAfterUnbindObservable.notifyObservers(this),p.activeCamera&&((p.getEngine().scenes.length>1||this.activeCamera&&this.activeCamera!==p.activeCamera)&&p.setTransformMatrix(p.activeCamera.getViewMatrix(),p.activeCamera.getProjectionMatrix(!0)),o.setViewport(p.activeCamera.viewport)),p.resetCachedMaterial()}},t.prototype._bestReflectionRenderTargetDimension=function(e,n){var i=e*n,o=Ue.a.NearestPOT(i+16384/(128+i));return Math.min(Ue.a.FloorPOT(e),o)},t.prototype._prepareRenderingManager=function(e,n,i,o){var a=this.getScene();if(a){this._renderingManager.reset();for(var s=a.getRenderId(),d=0;d<n;d++){var p=e[d];if(p&&!p.isBlocked){if(this.customIsReadyFunction){if(!this.customIsReadyFunction(p,this.refreshRate)){this.resetRefreshCounter();continue}}else if(!p.isReady(this.refreshRate===0)){this.resetRefreshCounter();continue}if(!p._internalAbstractMeshDataInfo._currentLODIsUpToDate&&a.activeCamera&&(p._internalAbstractMeshDataInfo._currentLOD=a.customLODSelector?a.customLODSelector(p,a.activeCamera):p.getLOD(a.activeCamera),p._internalAbstractMeshDataInfo._currentLODIsUpToDate=!0),!p._internalAbstractMeshDataInfo._currentLOD)continue;var b=p._internalAbstractMeshDataInfo._currentLOD;b._preActivateForIntermediateRendering(s);var P=void 0;if(P=!(!o||!i)&&(p.layerMask&i.layerMask)==0,p.isEnabled()&&p.isVisible&&p.subMeshes&&!P&&(b!==p&&b._activate(s,!0),p._activate(s,!0)&&p.subMeshes.length)){p.isAnInstance?p._internalAbstractMeshDataInfo._actAsRegularMesh&&(b=p):b._internalAbstractMeshDataInfo._onlyForInstancesIntermediate=!1,b._internalAbstractMeshDataInfo._isActiveIntermediate=!0;for(var O=0;O<b.subMeshes.length;O++){var B=b.subMeshes[O];this._renderingManager.dispatch(B,b)}}}}for(var F=0;F<a.particleSystems.length;F++){var z=a.particleSystems[F],J=z.emitter;z.isStarted()&&J&&J.position&&J.isEnabled()&&e.indexOf(J)>=0&&this._renderingManager.dispatchParticles(z)}}},t.prototype._bindFrameBuffer=function(e,n){e===void 0&&(e=0),n===void 0&&(n=0);var i=this.getScene();if(i){var o=i.getEngine();this._texture&&o.bindFramebuffer(this._texture,this.isCube?e:void 0,void 0,void 0,this.ignoreCameraViewport,0,n)}},t.prototype.unbindFrameBuffer=function(e,n){var i=this;this._texture&&e.unBindFramebuffer(this._texture,this.isCube,function(){i.onAfterRenderObservable.notifyObservers(n)})},t.prototype.renderToTarget=function(e,n,i,o,a){o===void 0&&(o=0),a===void 0&&(a=null);var s=this.getScene();if(s){var d=s.getEngine();if(this._texture){this._postProcessManager?this._postProcessManager._prepareFrame(this._texture,this._postProcesses):n&&s.postProcessManager._prepareFrame(this._texture)||this._bindFrameBuffer(e,o),this.is2DArray?this.onBeforeRenderObservable.notifyObservers(o):this.onBeforeRenderObservable.notifyObservers(e);var p=null,b=this.renderList?this.renderList:s.getActiveMeshes().data,P=this.renderList?this.renderList.length:s.getActiveMeshes().length;this.getCustomRenderList&&(p=this.getCustomRenderList(this.is2DArray?o:e,b,P)),p?this._prepareRenderingManager(p,p.length,a,!1):(this._defaultRenderListPrepared||(this._prepareRenderingManager(b,P,a,!this.renderList),this._defaultRenderListPrepared=!0),p=b),this.onClearObservable.hasObservers()?this.onClearObservable.notifyObservers(d):d.clear(this.clearColor||s.clearColor,!0,!0,!0),this._doNotChangeAspectRatio||s.updateTransformMatrix(!0);for(var O=0,B=s._beforeRenderTargetDrawStage;O<B.length;O++)B[O].action(this);this._renderingManager.render(this.customRenderFunction,p,this.renderParticles,this.renderSprites);for(var F=0,z=s._afterRenderTargetDrawStage;F<z.length;F++)z[F].action(this);this._postProcessManager?this._postProcessManager._finalizeFrame(!1,this._texture,e,this._postProcesses,this.ignoreCameraViewport):n&&s.postProcessManager._finalizeFrame(!1,this._texture,e),this._doNotChangeAspectRatio||s.updateTransformMatrix(!0),i&&Xe.b.DumpFramebuffer(this.getRenderWidth(),this.getRenderHeight(),d),this.isCube&&e!==5?this.onAfterRenderObservable.notifyObservers(e):(this.isCube&&e===5&&d.generateMipMapsForCubemap(this._texture),this.unbindFrameBuffer(d,e))}}},t.prototype.setRenderingOrder=function(e,n,i,o){n===void 0&&(n=null),i===void 0&&(i=null),o===void 0&&(o=null),this._renderingManager.setRenderingOrder(e,n,i,o)},t.prototype.setRenderingAutoClearDepthStencil=function(e,n){this._renderingManager.setRenderingAutoClearDepthStencil(e,n),this._renderingManager._useSceneAutoClearSetup=!1},t.prototype.clone=function(){var e=this.getSize(),n=new t(this.name,e,this.getScene(),this._renderTargetOptions.generateMipMaps,this._doNotChangeAspectRatio,this._renderTargetOptions.type,this.isCube,this._renderTargetOptions.samplingMode,this._renderTargetOptions.generateDepthBuffer,this._renderTargetOptions.generateStencilBuffer);return n.hasAlpha=this.hasAlpha,n.level=this.level,n.coordinatesMode=this.coordinatesMode,this.renderList&&(n.renderList=this.renderList.slice(0)),n},t.prototype.serialize=function(){if(!this.name)return null;var e=r.prototype.serialize.call(this);if(e.renderTargetSize=this.getRenderSize(),e.renderList=[],this.renderList)for(var n=0;n<this.renderList.length;n++)e.renderList.push(this.renderList[n].id);return e},t.prototype.disposeFramebufferObjects=function(){var e=this.getInternalTexture(),n=this.getScene();e&&n&&n.getEngine()._releaseFramebufferObjects(e)},t.prototype.dispose=function(){this.onResizeObservable.clear(),this.onClearObservable.clear(),this.onAfterRenderObservable.clear(),this.onAfterUnbindObservable.clear(),this.onBeforeBindObservable.clear(),this.onBeforeRenderObservable.clear(),this._postProcessManager&&(this._postProcessManager.dispose(),this._postProcessManager=null),this.clearPostProcesses(!0),this._resizeObserver&&(this.getScene().getEngine().onResizeObservable.remove(this._resizeObserver),this._resizeObserver=null),this.renderList=null;var e=this.getScene();if(e){var n=e.customRenderTargets.indexOf(this);n>=0&&e.customRenderTargets.splice(n,1);for(var i=0,o=e.cameras;i<o.length;i++){var a=o[i];(n=a.customRenderTargets.indexOf(this))>=0&&a.customRenderTargets.splice(n,1)}this.depthStencilTexture&&this.getScene().getEngine()._releaseTexture(this.depthStencilTexture),r.prototype.dispose.call(this)}},t.prototype._rebuild=function(){this.refreshRate===t.REFRESHRATE_RENDER_ONCE&&(this.refreshRate=t.REFRESHRATE_RENDER_ONCE),this._postProcessManager&&this._postProcessManager._rebuild()},t.prototype.freeRenderingGroups=function(){this._renderingManager&&this._renderingManager.freeRenderingGroups()},t.prototype.getViewCount=function(){return 1},t.REFRESHRATE_RENDER_ONCE=0,t.REFRESHRATE_RENDER_ONEVERYFRAME=1,t.REFRESHRATE_RENDER_ONEVERYTWOFRAMES=2,t}(we.a);we.a._CreateRenderTargetTexture=function(r,t,e,n){return new sn(r,t,e,n)};var jl=function(r){function t(e,n){n===void 0&&(n=512);var i=r.call(this,"multiview rtt",n,e,!1,!0,Ct.b.Unknown,!1,void 0,!1,!1,!0,void 0,!0)||this,o=e.getEngine().createMultiviewRenderTargetTexture(i.getRenderWidth(),i.getRenderHeight());return o.isMultiview=!0,o.format=h.a.TEXTUREFORMAT_RGBA,i._texture=o,i.samples=i._getEngine().getCaps().maxSamples||i.samples,i}return Object(c.d)(t,r),t.prototype._bindFrameBuffer=function(e){this._texture&&this.getScene().getEngine().bindMultiviewFramebuffer(this._texture)},t.prototype.getViewCount=function(){return 2},t}(sn),Hl=f(90);Ue.a.prototype.createMultiviewRenderTargetTexture=function(r,t){var e=this._gl;if(!this.getCaps().multiview)throw"Multiview is not supported";var n=new Ct.a(this,Ct.b.Unknown,!0);return n.width=r,n.height=t,n._framebuffer=e.createFramebuffer(),n._colorTextureArray=e.createTexture(),e.bindTexture(e.TEXTURE_2D_ARRAY,n._colorTextureArray),e.texStorage3D(e.TEXTURE_2D_ARRAY,1,e.RGBA8,r,t,2),n._depthStencilTextureArray=e.createTexture(),e.bindTexture(e.TEXTURE_2D_ARRAY,n._depthStencilTextureArray),e.texStorage3D(e.TEXTURE_2D_ARRAY,1,e.DEPTH32F_STENCIL8,r,t,2),n.isReady=!0,n},Ue.a.prototype.bindMultiviewFramebuffer=function(r){var t=this._gl,e=this.getCaps().oculusMultiview||this.getCaps().multiview;if(this.bindFramebuffer(r,void 0,void 0,void 0,!0),t.bindFramebuffer(t.DRAW_FRAMEBUFFER,r._framebuffer),!r._colorTextureArray||!r._depthStencilTextureArray)throw"Invalid multiview frame buffer";this.getCaps().oculusMultiview?(e.framebufferTextureMultisampleMultiviewOVR(t.DRAW_FRAMEBUFFER,t.COLOR_ATTACHMENT0,r._colorTextureArray,0,r.samples,0,2),e.framebufferTextureMultisampleMultiviewOVR(t.DRAW_FRAMEBUFFER,t.DEPTH_STENCIL_ATTACHMENT,r._depthStencilTextureArray,0,r.samples,0,2)):(e.framebufferTextureMultiviewOVR(t.DRAW_FRAMEBUFFER,t.COLOR_ATTACHMENT0,r._colorTextureArray,0,0,2),e.framebufferTextureMultiviewOVR(t.DRAW_FRAMEBUFFER,t.DEPTH_STENCIL_ATTACHMENT,r._depthStencilTextureArray,0,0,2))},gt.a.prototype._useMultiviewToSingleView=!1,gt.a.prototype._multiviewTexture=null,gt.a.prototype._resizeOrCreateMultiviewTexture=function(r,t){this._multiviewTexture?this._multiviewTexture.getRenderWidth()==r&&this._multiviewTexture.getRenderHeight()==t||(this._multiviewTexture.dispose(),this._multiviewTexture=new jl(this.getScene(),{width:r,height:t})):this._multiviewTexture=new jl(this.getScene(),{width:r,height:t})},_e.a.prototype._transformMatrixR=u.a.Zero(),_e.a.prototype._multiviewSceneUbo=null,_e.a.prototype._createMultiviewUbo=function(){this._multiviewSceneUbo=new zl.a(this.getEngine(),void 0,!0),this._multiviewSceneUbo.addUniform("viewProjection",16),this._multiviewSceneUbo.addUniform("viewProjectionR",16),this._multiviewSceneUbo.addUniform("view",16)},_e.a.prototype._updateMultiviewUbo=function(r,t){r&&t&&r.multiplyToRef(t,this._transformMatrixR),r&&t&&(r.multiplyToRef(t,u.c.Matrix[0]),Hl.a.GetRightPlaneToRef(u.c.Matrix[0],this._frustumPlanes[3])),this._multiviewSceneUbo&&(this._multiviewSceneUbo.updateMatrix("viewProjection",this.getTransformMatrix()),this._multiviewSceneUbo.updateMatrix("viewProjectionR",this._transformMatrixR),this._multiviewSceneUbo.updateMatrix("view",this._viewMatrix),this._multiviewSceneUbo.update())},_e.a.prototype._renderMultiviewToSingleView=function(r){r._resizeOrCreateMultiviewTexture(r._rigPostProcess&&r._rigPostProcess&&r._rigPostProcess.width>0?r._rigPostProcess.width:this.getEngine().getRenderWidth(!0),r._rigPostProcess&&r._rigPostProcess&&r._rigPostProcess.height>0?r._rigPostProcess.height:this.getEngine().getRenderHeight(!0)),this._multiviewSceneUbo||this._createMultiviewUbo(),r.outputRenderTarget=r._multiviewTexture,this._renderForCamera(r),r.outputRenderTarget=null;for(var t=0;t<r._rigCameras.length;t++){var e=this.getEngine();this._activeCamera=r._rigCameras[t],e.setViewport(this._activeCamera.viewport),this.postProcessManager&&(this.postProcessManager._prepareFrame(),this.postProcessManager._finalizeFrame(this._activeCamera.isIntermediate))}};var ps=function(r){function t(e,n,i){var o=r.call(this,e,"vrMultiviewToSingleview",["imageIndex"],["multiviewSampler"],i,n,we.a.BILINEAR_SAMPLINGMODE)||this;return o.onSizeChangedObservable.add(function(){}),o.onApplyObservable.add(function(a){n._scene.activeCamera&&n._scene.activeCamera.isLeftCamera?a.setInt("imageIndex",0):a.setInt("imageIndex",1),a.setTexture("multiviewSampler",n._multiviewTexture)}),o}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VRMultiviewToSingleviewPostProcess"},t}(_t);gt.a._setVRRigMode=function(r,t){var e=t.vrCameraMetrics||mr.GetDefault();r._rigCameras[0]._cameraRigParams.vrMetrics=e,r._rigCameras[0].viewport=new Kn.a(0,0,.5,1),r._rigCameras[0]._cameraRigParams.vrWorkMatrix=new u.a,r._rigCameras[0]._cameraRigParams.vrHMatrix=e.leftHMatrix,r._rigCameras[0]._cameraRigParams.vrPreViewMatrix=e.leftPreViewMatrix,r._rigCameras[0].getProjectionMatrix=r._rigCameras[0]._getVRProjectionMatrix,r._rigCameras[1]._cameraRigParams.vrMetrics=e,r._rigCameras[1].viewport=new Kn.a(.5,0,.5,1),r._rigCameras[1]._cameraRigParams.vrWorkMatrix=new u.a,r._rigCameras[1]._cameraRigParams.vrHMatrix=e.rightHMatrix,r._rigCameras[1]._cameraRigParams.vrPreViewMatrix=e.rightPreViewMatrix,r._rigCameras[1].getProjectionMatrix=r._rigCameras[1]._getVRProjectionMatrix,e.multiviewEnabled&&(r.getScene().getEngine().getCaps().multiview?(r._useMultiviewToSingleView=!0,r._rigPostProcess=new ps("VRMultiviewToSingleview",r,e.postProcessScaleFactor)):(l.a.Warn("Multiview is not supported, falling back to standard rendering"),e.multiviewEnabled=!1)),e.compensateDistortion&&(r._rigCameras[0]._rigPostProcess=new ds("VR_Distort_Compensation_Left",r._rigCameras[0],!1,e),r._rigCameras[1]._rigPostProcess=new ds("VR_Distort_Compensation_Right",r._rigCameras[1],!0,e))},Q.a.AddNodeConstructor("VRDeviceOrientationFreeCamera",function(r,t){return function(){return new Wl(r,0,0,1,u.e.Zero(),t)}});var Wl=function(r){function t(e,n,i,o,a,s,d,p){d===void 0&&(d=!0),p===void 0&&(p=mr.GetDefault());var b=r.call(this,e,n,i,o,a,s)||this;return p.compensateDistortion=d,b.setCameraRigMode(gt.a.RIG_MODE_VR,{vrCameraMetrics:p}),b.inputs.addVRDeviceOrientation(),b}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VRDeviceOrientationArcRotateCamera"},t}(Ji);Q.a.AddNodeConstructor("VRDeviceOrientationFreeCamera",function(r,t){return function(){return new Uo(r,u.e.Zero(),t)}});var Uo=function(r){function t(e,n,i,o,a){o===void 0&&(o=!0),a===void 0&&(a=mr.GetDefault());var s=r.call(this,e,n,i)||this;return a.compensateDistortion=o,s.setCameraRigMode(gt.a.RIG_MODE_VR,{vrCameraMetrics:a}),s}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VRDeviceOrientationFreeCamera"},t}(Fo);Q.a.AddNodeConstructor("VRDeviceOrientationGamepadCamera",function(r,t){return function(){return new Xl(r,u.e.Zero(),t)}});var Xl=function(r){function t(e,n,i,o,a){o===void 0&&(o=!0),a===void 0&&(a=mr.GetDefault());var s=r.call(this,e,n,i,o,a)||this;return s.inputs.addGamepad(),s}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VRDeviceOrientationGamepadCamera"},t}(Uo),Vo=f(86);gt.a._setWebVRRigMode=function(r,t){if(t.vrDisplay){var e=t.vrDisplay.getEyeParameters("left"),n=t.vrDisplay.getEyeParameters("right");r._rigCameras[0].viewport=new Kn.a(0,0,.5,1),r._rigCameras[0].setCameraRigParameter("left",!0),r._rigCameras[0].setCameraRigParameter("specs",t.specs),r._rigCameras[0].setCameraRigParameter("eyeParameters",e),r._rigCameras[0].setCameraRigParameter("frameData",t.frameData),r._rigCameras[0].setCameraRigParameter("parentCamera",t.parentCamera),r._rigCameras[0]._cameraRigParams.vrWorkMatrix=new u.a,r._rigCameras[0].getProjectionMatrix=r._getWebVRProjectionMatrix,r._rigCameras[0].parent=r,r._rigCameras[0]._getViewMatrix=r._getWebVRViewMatrix,r._rigCameras[1].viewport=new Kn.a(.5,0,.5,1),r._rigCameras[1].setCameraRigParameter("eyeParameters",n),r._rigCameras[1].setCameraRigParameter("specs",t.specs),r._rigCameras[1].setCameraRigParameter("frameData",t.frameData),r._rigCameras[1].setCameraRigParameter("parentCamera",t.parentCamera),r._rigCameras[1]._cameraRigParams.vrWorkMatrix=new u.a,r._rigCameras[1].getProjectionMatrix=r._getWebVRProjectionMatrix,r._rigCameras[1].parent=r,r._rigCameras[1]._getViewMatrix=r._getWebVRViewMatrix}},Object.defineProperty(Ue.a.prototype,"isInVRExclusivePointerMode",{get:function(){return this._vrExclusivePointerMode},enumerable:!0,configurable:!0}),Ue.a.prototype._prepareVRComponent=function(){this._vrSupported=!1,this._vrExclusivePointerMode=!1,this.onVRDisplayChangedObservable=new C.c,this.onVRRequestPresentComplete=new C.c,this.onVRRequestPresentStart=new C.c},Ue.a.prototype.isVRDevicePresent=function(){return!!this._vrDisplay},Ue.a.prototype.getVRDevice=function(){return this._vrDisplay},Ue.a.prototype.initWebVR=function(){return this.initWebVRAsync(),this.onVRDisplayChangedObservable},Ue.a.prototype.initWebVRAsync=function(){var r=this,t=function(){var n={vrDisplay:r._vrDisplay,vrSupported:r._vrSupported};r.onVRDisplayChangedObservable.notifyObservers(n),r._webVRInitPromise=new Promise(function(i){i(n)})};if(!this._onVrDisplayConnect){this._onVrDisplayConnect=function(n){r._vrDisplay=n.display,t()},this._onVrDisplayDisconnect=function(){r._vrDisplay.cancelAnimationFrame(r._frameHandler),r._vrDisplay=void 0,r._frameHandler=Ue.a.QueueNewFrame(r._boundRenderFunction),t()},this._onVrDisplayPresentChange=function(){r._vrExclusivePointerMode=r._vrDisplay&&r._vrDisplay.isPresenting};var e=this.getHostWindow();e&&(e.addEventListener("vrdisplayconnect",this._onVrDisplayConnect),e.addEventListener("vrdisplaydisconnect",this._onVrDisplayDisconnect),e.addEventListener("vrdisplaypresentchange",this._onVrDisplayPresentChange))}return this._webVRInitPromise=this._webVRInitPromise||this._getVRDisplaysAsync(),this._webVRInitPromise.then(t),this._webVRInitPromise},Ue.a.prototype._getVRDisplaysAsync=function(){var r=this;return new Promise(function(t){navigator.getVRDisplays?navigator.getVRDisplays().then(function(e){r._vrSupported=!0,r._vrDisplay=e[0],t({vrDisplay:r._vrDisplay,vrSupported:r._vrSupported})}):(r._vrDisplay=void 0,r._vrSupported=!1,t({vrDisplay:r._vrDisplay,vrSupported:r._vrSupported}))})},Ue.a.prototype.enableVR=function(r){var t=this;if(this._vrDisplay&&!this._vrDisplay.isPresenting){this.onVRRequestPresentStart.notifyObservers(this);var e={highRefreshRate:!!this.vrPresentationAttributes&&this.vrPresentationAttributes.highRefreshRate,foveationLevel:this.vrPresentationAttributes?this.vrPresentationAttributes.foveationLevel:1,multiview:(this.getCaps().multiview||this.getCaps().oculusMultiview)&&r.useMultiview};this._vrDisplay.requestPresent([Object(c.a)({source:this.getRenderingCanvas(),attributes:e},e)]).then(function(){t.onVRRequestPresentComplete.notifyObservers(!0),t._onVRFullScreenTriggered()}).catch(function(){t.onVRRequestPresentComplete.notifyObservers(!1)})}},Ue.a.prototype._onVRFullScreenTriggered=function(){if(this._vrDisplay&&this._vrDisplay.isPresenting){this._oldSize=new oe.a(this.getRenderWidth(),this.getRenderHeight()),this._oldHardwareScaleFactor=this.getHardwareScalingLevel();var r=this._vrDisplay.getEyeParameters("left");this.setHardwareScalingLevel(1),this.setSize(2*r.renderWidth,r.renderHeight)}else this.setHardwareScalingLevel(this._oldHardwareScaleFactor),this.setSize(this._oldSize.width,this._oldSize.height)},Ue.a.prototype.disableVR=function(){var r=this;this._vrDisplay&&this._vrDisplay.isPresenting&&this._vrDisplay.exitPresent().then(function(){return r._onVRFullScreenTriggered()}).catch(function(){return r._onVRFullScreenTriggered()}),us.a.IsWindowObjectExist()&&(window.removeEventListener("vrdisplaypointerrestricted",this._onVRDisplayPointerRestricted),window.removeEventListener("vrdisplaypointerunrestricted",this._onVRDisplayPointerUnrestricted),this._onVrDisplayConnect&&(window.removeEventListener("vrdisplayconnect",this._onVrDisplayConnect),this._onVrDisplayDisconnect&&window.removeEventListener("vrdisplaydisconnect",this._onVrDisplayDisconnect),this._onVrDisplayPresentChange&&window.removeEventListener("vrdisplaypresentchange",this._onVrDisplayPresentChange),this._onVrDisplayConnect=null,this._onVrDisplayDisconnect=null))},Ue.a.prototype._connectVREvents=function(r,t){var e=this;if(this._onVRDisplayPointerRestricted=function(){r&&r.requestPointerLock()},this._onVRDisplayPointerUnrestricted=function(){if(t)t.exitPointerLock&&t.exitPointerLock();else{var i=e.getHostWindow();i.document&&i.document.exitPointerLock&&i.document.exitPointerLock()}},us.a.IsWindowObjectExist()){var n=this.getHostWindow();n.addEventListener("vrdisplaypointerrestricted",this._onVRDisplayPointerRestricted,!1),n.addEventListener("vrdisplaypointerunrestricted",this._onVRDisplayPointerUnrestricted,!1)}},Ue.a.prototype._submitVRFrame=function(){if(this._vrDisplay&&this._vrDisplay.isPresenting)try{this._vrDisplay.submitFrame()}catch(r){Xe.b.Warn("webVR submitFrame has had an unexpected failure: "+r)}},Ue.a.prototype.isVRPresenting=function(){return this._vrDisplay&&this._vrDisplay.isPresenting},Ue.a.prototype._requestVRFrame=function(){this._frameHandler=Ue.a.QueueNewFrame(this._boundRenderFunction,this._vrDisplay)},Q.a.AddNodeConstructor("WebVRFreeCamera",function(r,t){return function(){return new ko(r,u.e.Zero(),t)}}),Q.a.AddNodeConstructor("WebVRGamepadCamera",function(r,t){return function(){return new ko(r,u.e.Zero(),t)}});var ko=function(r){function t(e,n,i,o){o===void 0&&(o={});var a=r.call(this,e,n,i)||this;a.webVROptions=o,a._vrDevice=null,a.rawPose=null,a._specsVersion="1.1",a._attached=!1,a._descendants=[],a._deviceRoomPosition=u.e.Zero(),a._deviceRoomRotationQuaternion=u.b.Identity(),a._standingMatrix=null,a.devicePosition=u.e.Zero(),a.deviceRotationQuaternion=u.b.Identity(),a.deviceScaleFactor=1,a._deviceToWorld=u.a.Identity(),a._worldToDevice=u.a.Identity(),a.controllers=[],a.onControllersAttachedObservable=new C.c,a.onControllerMeshLoadedObservable=new C.c,a.onPoseUpdatedFromDeviceObservable=new C.c,a._poseSet=!1,a.rigParenting=!0,a._defaultHeight=void 0,a._detachIfAttached=function(){var d=a.getEngine().getVRDevice();d&&!d.isPresenting&&a.detachControl()},a._workingVector=u.e.Zero(),a._oneVector=u.e.One(),a._workingMatrix=u.a.Identity(),a._tmpMatrix=new u.a,a._cache.position=u.e.Zero(),o.defaultHeight&&(a._defaultHeight=o.defaultHeight,a.position.y=a._defaultHeight),a.minZ=.1,arguments.length===5&&(a.webVROptions=arguments[4]),a.webVROptions.trackPosition==null&&(a.webVROptions.trackPosition=!0),a.webVROptions.controllerMeshes==null&&(a.webVROptions.controllerMeshes=!0),a.webVROptions.defaultLightingOnControllers==null&&(a.webVROptions.defaultLightingOnControllers=!0),a.rotationQuaternion=new u.b,a.webVROptions&&a.webVROptions.positionScale&&(a.deviceScaleFactor=a.webVROptions.positionScale);var s=a.getEngine();return a._onVREnabled=function(d){d&&a.initControllers()},s.onVRRequestPresentComplete.add(a._onVREnabled),s.initWebVR().add(function(d){d.vrDisplay&&a._vrDevice!==d.vrDisplay&&(a._vrDevice=d.vrDisplay,a.setCameraRigMode(gt.a.RIG_MODE_WEBVR,{parentCamera:a,vrDisplay:a._vrDevice,frameData:a._frameData,specs:a._specsVersion}),a._attached&&a.getEngine().enableVR(a.webVROptions))}),typeof VRFrameData<"u"&&(a._frameData=new VRFrameData),o.useMultiview&&(a.getScene().getEngine().getCaps().multiview?(a._useMultiviewToSingleView=!0,a._rigPostProcess=new ps("VRMultiviewToSingleview",a,1)):(l.a.Warn("Multiview is not supported, falling back to standard rendering"),a._useMultiviewToSingleView=!1)),i.onBeforeCameraRenderObservable.add(function(d){d.parent===a&&a.rigParenting&&(a._descendants=a.getDescendants(!0,function(p){var b=a.controllers.some(function(O){return O._mesh===p}),P=a._rigCameras.indexOf(p)!==-1;return!b&&!P}),a._descendants.forEach(function(p){p.parent=d}))}),i.onAfterCameraRenderObservable.add(function(d){d.parent===a&&a.rigParenting&&a._descendants.forEach(function(p){p.parent=a})}),a}return Object(c.d)(t,r),t.prototype.deviceDistanceToRoomGround=function(){return this._standingMatrix?(this._standingMatrix.getTranslationToRef(this._workingVector),this._deviceRoomPosition.y+this._workingVector.y):this._defaultHeight||0},t.prototype.useStandingMatrix=function(e){var n=this;e===void 0&&(e=function(i){}),this.getEngine().initWebVRAsync().then(function(i){i.vrDisplay&&i.vrDisplay.stageParameters&&i.vrDisplay.stageParameters.sittingToStandingTransform&&n.webVROptions.trackPosition?(n._standingMatrix=new u.a,u.a.FromFloat32ArrayToRefScaled(i.vrDisplay.stageParameters.sittingToStandingTransform,0,1,n._standingMatrix),n.getScene().useRightHandedSystem||n._standingMatrix&&n._standingMatrix.toggleModelMatrixHandInPlace(),e(!0)):e(!1)})},t.prototype.useStandingMatrixAsync=function(){var e=this;return new Promise(function(n){e.useStandingMatrix(function(i){n(i)})})},t.prototype.dispose=function(){this._detachIfAttached(),this.getEngine().onVRRequestPresentComplete.removeCallback(this._onVREnabled),this._updateCacheWhenTrackingDisabledObserver&&this._scene.onBeforeRenderObservable.remove(this._updateCacheWhenTrackingDisabledObserver),r.prototype.dispose.call(this)},t.prototype.getControllerByName=function(e){for(var n=0,i=this.controllers;n<i.length;n++){var o=i[n];if(o.hand===e)return o}return null},Object.defineProperty(t.prototype,"leftController",{get:function(){return this._leftController||(this._leftController=this.getControllerByName("left")),this._leftController},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rightController",{get:function(){return this._rightController||(this._rightController=this.getControllerByName("right")),this._rightController},enumerable:!1,configurable:!0}),t.prototype.getForwardRay=function(e){return e===void 0&&(e=100),this.leftCamera?r.prototype.getForwardRay.call(this,e,this.leftCamera.getWorldMatrix(),this.leftCamera.globalPosition):r.prototype.getForwardRay.call(this,e)},t.prototype._checkInputs=function(){this._vrDevice&&this._vrDevice.isPresenting&&(this._vrDevice.getFrameData(this._frameData),this.updateFromDevice(this._frameData.pose)),r.prototype._checkInputs.call(this)},t.prototype.updateFromDevice=function(e){e&&e.orientation&&e.orientation.length===4&&(this.rawPose=e,this._deviceRoomRotationQuaternion.copyFromFloats(e.orientation[0],e.orientation[1],-e.orientation[2],-e.orientation[3]),this.getScene().useRightHandedSystem&&(this._deviceRoomRotationQuaternion.z*=-1,this._deviceRoomRotationQuaternion.w*=-1),this.webVROptions.trackPosition&&this.rawPose.position&&(this._deviceRoomPosition.copyFromFloats(this.rawPose.position[0],this.rawPose.position[1],-this.rawPose.position[2]),this.getScene().useRightHandedSystem&&(this._deviceRoomPosition.z*=-1)),this._poseSet=!0)},t.prototype.attachControl=function(e){e=Xe.b.BackCompatCameraNoPreventDefault(arguments),r.prototype.attachControl.call(this,e),this._attached=!0,e=!gt.a.ForceAttachControlToAlwaysPreventDefault&&e,this._vrDevice&&this.getEngine().enableVR(this.webVROptions);var n=this._scene.getEngine().getHostWindow();n&&n.addEventListener("vrdisplaypresentchange",this._detachIfAttached)},t.prototype.detachControl=function(e){this.getScene().gamepadManager.onGamepadConnectedObservable.remove(this._onGamepadConnectedObserver),this.getScene().gamepadManager.onGamepadDisconnectedObservable.remove(this._onGamepadDisconnectedObserver),r.prototype.detachControl.call(this),this._attached=!1,this.getEngine().disableVR(),window.removeEventListener("vrdisplaypresentchange",this._detachIfAttached)},t.prototype.getClassName=function(){return"WebVRFreeCamera"},t.prototype.resetToCurrentRotation=function(){this._vrDevice.resetPose()},t.prototype._updateRigCameras=function(){var e=this._rigCameras[0],n=this._rigCameras[1];e.rotationQuaternion.copyFrom(this._deviceRoomRotationQuaternion),n.rotationQuaternion.copyFrom(this._deviceRoomRotationQuaternion),e.position.copyFrom(this._deviceRoomPosition),n.position.copyFrom(this._deviceRoomPosition)},t.prototype._correctPositionIfNotTrackPosition=function(e,n){n===void 0&&(n=!1),this.rawPose&&this.rawPose.position&&!this.webVROptions.trackPosition&&(u.a.TranslationToRef(this.rawPose.position[0],this.rawPose.position[1],-this.rawPose.position[2],this._tmpMatrix),n||this._tmpMatrix.invert(),this._tmpMatrix.multiplyToRef(e,e))},t.prototype._updateCache=function(e){var n=this;this.rotationQuaternion.equals(this._cache.rotationQuaternion)&&this.position.equals(this._cache.position)||(this.updateCacheCalled||(this.updateCacheCalled=!0,this.update()),this.rotationQuaternion.toRotationMatrix(this._workingMatrix),u.e.TransformCoordinatesToRef(this._deviceRoomPosition,this._workingMatrix,this._workingVector),this.devicePosition.subtractToRef(this._workingVector,this._workingVector),u.a.ComposeToRef(this._oneVector,this.rotationQuaternion,this._workingVector,this._deviceToWorld),this._deviceToWorld.getTranslationToRef(this._workingVector),this._workingVector.addInPlace(this.position),this._workingVector.subtractInPlace(this._cache.position),this._deviceToWorld.setTranslation(this._workingVector),this._deviceToWorld.invertToRef(this._worldToDevice),this.controllers.forEach(function(i){i._deviceToWorld.copyFrom(n._deviceToWorld),n._correctPositionIfNotTrackPosition(i._deviceToWorld),i.update()})),e||r.prototype._updateCache.call(this),this.updateCacheCalled=!1},t.prototype._computeDevicePosition=function(){u.e.TransformCoordinatesToRef(this._deviceRoomPosition,this._deviceToWorld,this.devicePosition)},t.prototype.update=function(){this._computeDevicePosition(),u.a.FromQuaternionToRef(this._deviceRoomRotationQuaternion,this._workingMatrix),this._workingMatrix.multiplyToRef(this._deviceToWorld,this._workingMatrix),u.b.FromRotationMatrixToRef(this._workingMatrix,this.deviceRotationQuaternion),this._poseSet&&this.onPoseUpdatedFromDeviceObservable.notifyObservers(null),r.prototype.update.call(this)},t.prototype._getViewMatrix=function(){return u.a.Identity()},t.prototype._getWebVRViewMatrix=function(){var e=this._cameraRigParams.parentCamera;e._updateCache();var n=this._cameraRigParams.left?this._cameraRigParams.frameData.leftViewMatrix:this._cameraRigParams.frameData.rightViewMatrix;return u.a.FromArrayToRef(n,0,this._webvrViewMatrix),this.getScene().useRightHandedSystem||this._webvrViewMatrix.toggleModelMatrixHandInPlace(),this._webvrViewMatrix.getRotationMatrixToRef(this._cameraRotationMatrix),u.e.TransformCoordinatesToRef(this._referencePoint,this._cameraRotationMatrix,this._transformedReferencePoint),this.position.addToRef(this._transformedReferencePoint,this._currentTarget),e.deviceScaleFactor!==1&&(this._webvrViewMatrix.invert(),e.deviceScaleFactor&&(this._webvrViewMatrix.multiplyAtIndex(12,e.deviceScaleFactor),this._webvrViewMatrix.multiplyAtIndex(13,e.deviceScaleFactor),this._webvrViewMatrix.multiplyAtIndex(14,e.deviceScaleFactor)),this._webvrViewMatrix.invert()),e._correctPositionIfNotTrackPosition(this._webvrViewMatrix,!0),e._worldToDevice.multiplyToRef(this._webvrViewMatrix,this._webvrViewMatrix),this._workingMatrix=this._workingMatrix||u.a.Identity(),this._webvrViewMatrix.invertToRef(this._workingMatrix),this._workingMatrix.multiplyToRef(e.getWorldMatrix(),this._workingMatrix),this._workingMatrix.getTranslationToRef(this._globalPosition),this._markSyncedWithParent(),this._webvrViewMatrix},t.prototype._getWebVRProjectionMatrix=function(){var e=this.parent;e._vrDevice.depthNear=e.minZ,e._vrDevice.depthFar=e.maxZ;var n=this._cameraRigParams.left?this._cameraRigParams.frameData.leftProjectionMatrix:this._cameraRigParams.frameData.rightProjectionMatrix;return u.a.FromArrayToRef(n,0,this._projectionMatrix),this.getScene().useRightHandedSystem||this._projectionMatrix.toggleProjectionMatrixHandInPlace(),this._projectionMatrix},t.prototype.initControllers=function(){var e=this;this.controllers=[];var n=this.getScene().gamepadManager;this._onGamepadDisconnectedObserver=n.onGamepadDisconnectedObservable.add(function(i){if(i.type===dn.POSE_ENABLED){var o=i;o.defaultModel&&o.defaultModel.setEnabled(!1),o.hand==="right"&&(e._rightController=null),o.hand==="left"&&(e._leftController=null);var a=e.controllers.indexOf(o);a!==-1&&e.controllers.splice(a,1)}}),this._onGamepadConnectedObserver=n.onGamepadConnectedObservable.add(function(i){if(i.type===dn.POSE_ENABLED){var o=i;if(e.webVROptions.trackPosition||(o._disableTrackPosition(new u.e(o.hand=="left"?-.15:.15,-.5,.25)),e._updateCacheWhenTrackingDisabledObserver||(e._updateCacheWhenTrackingDisabledObserver=e._scene.onBeforeRenderObservable.add(function(){e._updateCache()}))),o.deviceScaleFactor=e.deviceScaleFactor,o._deviceToWorld.copyFrom(e._deviceToWorld),e._correctPositionIfNotTrackPosition(o._deviceToWorld),e.webVROptions.controllerMeshes&&(o.defaultModel?o.defaultModel.setEnabled(!0):o.initControllerMesh(e.getScene(),function(d){if(d.scaling.scaleInPlace(e.deviceScaleFactor),e.onControllerMeshLoadedObservable.notifyObservers(o),e.webVROptions.defaultLightingOnControllers){e._lightOnControllers||(e._lightOnControllers=new Vo.a("vrControllersLight",new u.e(0,1,0),e.getScene()));var p=function(b,P){var O=b.getChildren();O&&O.length!==0&&O.forEach(function(B){P.includedOnlyMeshes.push(B),p(B,P)})};e._lightOnControllers.includedOnlyMeshes.push(d),p(d,e._lightOnControllers)}})),o.attachToPoseControlledCamera(e),e.controllers.indexOf(o)===-1){e.controllers.push(o);for(var a=!1,s=0;s<e.controllers.length;s++)e.controllers[s].controllerType===ii.VIVE&&(a?e.controllers[s].hand="right":(a=!0,e.controllers[s].hand="left"));e.controllers.length>=2&&e.onControllersAttachedObservable.notifyObservers(e.controllers)}}})},t}(Yn),Bi=function(r){function t(e){var n=r.call(this,e)||this;return n.onTriggerStateChangedObservable=new C.c,n.onMainButtonStateChangedObservable=new C.c,n.onSecondaryButtonStateChangedObservable=new C.c,n.onPadStateChangedObservable=new C.c,n.onPadValuesChangedObservable=new C.c,n.pad={x:0,y:0},n._changes={pressChanged:!1,touchChanged:!1,valueChanged:!1,changed:!1},n._buttons=new Array(e.buttons.length),n.hand=e.hand,n}return Object(c.d)(t,r),t.prototype.onButtonStateChange=function(e){this._onButtonStateChange=e},Object.defineProperty(t.prototype,"defaultModel",{get:function(){return this._defaultModel},enumerable:!1,configurable:!0}),t.prototype.update=function(){r.prototype.update.call(this);for(var e=0;e<this._buttons.length;e++)this._setButtonValue(this.browserGamepad.buttons[e],this._buttons[e],e);this.leftStick.x===this.pad.x&&this.leftStick.y===this.pad.y||(this.pad.x=this.leftStick.x,this.pad.y=this.leftStick.y,this.onPadValuesChangedObservable.notifyObservers(this.pad))},t.prototype._setButtonValue=function(e,n,i){e||(e={pressed:!1,touched:!1,value:0}),n?(this._checkChanges(e,n),this._changes.changed&&(this._onButtonStateChange&&this._onButtonStateChange(this.index,i,e),this._handleButtonChange(i,e,this._changes)),this._buttons[i].pressed=e.pressed,this._buttons[i].touched=e.touched,this._buttons[i].value=e.value<1e-8?0:e.value):this._buttons[i]={pressed:e.pressed,touched:e.touched,value:e.value}},t.prototype._checkChanges=function(e,n){return this._changes.pressChanged=e.pressed!==n.pressed,this._changes.touchChanged=e.touched!==n.touched,this._changes.valueChanged=e.value!==n.value,this._changes.changed=this._changes.pressChanged||this._changes.touchChanged||this._changes.valueChanged,this._changes},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._defaultModel=null,this.onTriggerStateChangedObservable.clear(),this.onMainButtonStateChangedObservable.clear(),this.onSecondaryButtonStateChangedObservable.clear(),this.onPadStateChangedObservable.clear(),this.onPadValuesChangedObservable.clear()},t}(pr),yn=f(42),Ft=f(30),Ti=f(62),Kf=(f(108),f(59),f(109),`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-#include<imageProcessingDeclaration>
-#include<helperFunctions>
-#include<imageProcessingFunctions>
-void main(void)
-{
-vec4 result=texture2D(textureSampler,vUV);
-#ifdef IMAGEPROCESSING
-#ifndef FROMLINEARSPACE
-
-result.rgb=toLinearSpace(result.rgb);
-#endif
-result=applyImageProcessing(result);
-#else
-
-#ifdef FROMLINEARSPACE
-result=applyImageProcessing(result);
-#endif
-#endif
-gl_FragColor=result;
-}`);ze.a.ShadersStore.imageProcessingPixelShader=Kf;var Go=function(r){function t(e,n,i,o,a,s,d,p){i===void 0&&(i=null),d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT);var b=r.call(this,e,"imageProcessing",[],[],n,i,o,a,s,null,d,"postprocess",null,!0)||this;return b._fromLinearSpace=!0,b._defines={IMAGEPROCESSING:!1,VIGNETTE:!1,VIGNETTEBLENDMODEMULTIPLY:!1,VIGNETTEBLENDMODEOPAQUE:!1,TONEMAPPING:!1,TONEMAPPING_ACES:!1,CONTRAST:!1,COLORCURVES:!1,COLORGRADING:!1,COLORGRADING3D:!1,FROMLINEARSPACE:!1,SAMPLER3DGREENDEPTH:!1,SAMPLER3DBGRMAP:!1,IMAGEPROCESSINGPOSTPROCESS:!1,EXPOSURE:!1},p?(p.applyByPostProcess=!0,b._attachImageProcessingConfiguration(p,!0),b.fromLinearSpace=!1):(b._attachImageProcessingConfiguration(null,!0),b.imageProcessingConfiguration.applyByPostProcess=!0),b.onApply=function(P){b.imageProcessingConfiguration.bind(P,b.aspectRatio)},b}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"imageProcessingConfiguration",{get:function(){return this._imageProcessingConfiguration},set:function(e){e.applyByPostProcess=!0,this._attachImageProcessingConfiguration(e)},enumerable:!1,configurable:!0}),t.prototype._attachImageProcessingConfiguration=function(e,n){var i=this;if(n===void 0&&(n=!1),e!==this._imageProcessingConfiguration){if(this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),e)this._imageProcessingConfiguration=e;else{var o=null,a=this.getEngine(),s=this.getCamera();if(s)o=s.getScene();else if(a&&a.scenes){var d=a.scenes;o=d[d.length-1]}else o=te.a.LastCreatedScene;this._imageProcessingConfiguration=o?o.imageProcessingConfiguration:new yn.a}this._imageProcessingConfiguration&&(this._imageProcessingObserver=this._imageProcessingConfiguration.onUpdateParameters.add(function(){i._updateParameters()})),n||this._updateParameters()}},Object.defineProperty(t.prototype,"isSupported",{get:function(){var e=this.getEffect();return!e||e.isSupported},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"colorCurves",{get:function(){return this.imageProcessingConfiguration.colorCurves},set:function(e){this.imageProcessingConfiguration.colorCurves=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"colorCurvesEnabled",{get:function(){return this.imageProcessingConfiguration.colorCurvesEnabled},set:function(e){this.imageProcessingConfiguration.colorCurvesEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"colorGradingTexture",{get:function(){return this.imageProcessingConfiguration.colorGradingTexture},set:function(e){this.imageProcessingConfiguration.colorGradingTexture=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"colorGradingEnabled",{get:function(){return this.imageProcessingConfiguration.colorGradingEnabled},set:function(e){this.imageProcessingConfiguration.colorGradingEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"exposure",{get:function(){return this.imageProcessingConfiguration.exposure},set:function(e){this.imageProcessingConfiguration.exposure=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"toneMappingEnabled",{get:function(){return this._imageProcessingConfiguration.toneMappingEnabled},set:function(e){this._imageProcessingConfiguration.toneMappingEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"toneMappingType",{get:function(){return this._imageProcessingConfiguration.toneMappingType},set:function(e){this._imageProcessingConfiguration.toneMappingType=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"contrast",{get:function(){return this.imageProcessingConfiguration.contrast},set:function(e){this.imageProcessingConfiguration.contrast=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteStretch",{get:function(){return this.imageProcessingConfiguration.vignetteStretch},set:function(e){this.imageProcessingConfiguration.vignetteStretch=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteCentreX",{get:function(){return this.imageProcessingConfiguration.vignetteCentreX},set:function(e){this.imageProcessingConfiguration.vignetteCentreX=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteCentreY",{get:function(){return this.imageProcessingConfiguration.vignetteCentreY},set:function(e){this.imageProcessingConfiguration.vignetteCentreY=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteWeight",{get:function(){return this.imageProcessingConfiguration.vignetteWeight},set:function(e){this.imageProcessingConfiguration.vignetteWeight=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteColor",{get:function(){return this.imageProcessingConfiguration.vignetteColor},set:function(e){this.imageProcessingConfiguration.vignetteColor=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteCameraFov",{get:function(){return this.imageProcessingConfiguration.vignetteCameraFov},set:function(e){this.imageProcessingConfiguration.vignetteCameraFov=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteBlendMode",{get:function(){return this.imageProcessingConfiguration.vignetteBlendMode},set:function(e){this.imageProcessingConfiguration.vignetteBlendMode=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vignetteEnabled",{get:function(){return this.imageProcessingConfiguration.vignetteEnabled},set:function(e){this.imageProcessingConfiguration.vignetteEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"fromLinearSpace",{get:function(){return this._fromLinearSpace},set:function(e){this._fromLinearSpace!==e&&(this._fromLinearSpace=e,this._updateParameters())},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"ImageProcessingPostProcess"},t.prototype._updateParameters=function(){this._defines.FROMLINEARSPACE=this._fromLinearSpace,this.imageProcessingConfiguration.prepareDefines(this._defines,!0);var e="";for(var n in this._defines)this._defines[n]&&(e+="#define "+n+`;\r
-`);var i=["textureSampler"],o=["scale"];yn.a&&(yn.a.PrepareSamplers(i,this._defines),yn.a.PrepareUniforms(o,this._defines)),this.updateEffect(e,o,i)},t.prototype.dispose=function(e){r.prototype.dispose.call(this,e),this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),this._imageProcessingConfiguration&&(this.imageProcessingConfiguration.applyByPostProcess=!1)},Object(c.c)([Object(L.c)()],t.prototype,"_fromLinearSpace",void 0),t}(_t),ft=f(16),Oe=f(4);De.a._GroundMeshParser=function(r,t){return zo.Parse(r,t)};var zo=function(r){function t(e,n){var i=r.call(this,e,n)||this;return i.generateOctree=!1,i}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"GroundMesh"},Object.defineProperty(t.prototype,"subdivisions",{get:function(){return Math.min(this._subdivisionsX,this._subdivisionsY)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"subdivisionsX",{get:function(){return this._subdivisionsX},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"subdivisionsY",{get:function(){return this._subdivisionsY},enumerable:!1,configurable:!0}),t.prototype.optimize=function(e,n){n===void 0&&(n=32),this._subdivisionsX=e,this._subdivisionsY=e,this.subdivide(e),this.createOrUpdateSubmeshesOctree&&this.createOrUpdateSubmeshesOctree(n)},t.prototype.getHeightAtCoordinates=function(e,n){var i=this.getWorldMatrix(),o=u.c.Matrix[5];i.invertToRef(o);var a=u.c.Vector3[8];if(u.e.TransformCoordinatesFromFloatsToRef(e,0,n,o,a),e=a.x,n=a.z,e<this._minX||e>this._maxX||n<this._minZ||n>this._maxZ)return this.position.y;this._heightQuads&&this._heightQuads.length!=0||(this._initHeightQuads(),this._computeHeightQuads());var s=this._getFacetAt(e,n),d=-(s.x*e+s.z*n+s.w)/s.y;return u.e.TransformCoordinatesFromFloatsToRef(0,d,0,i,a),a.y},t.prototype.getNormalAtCoordinates=function(e,n){var i=new u.e(0,1,0);return this.getNormalAtCoordinatesToRef(e,n,i),i},t.prototype.getNormalAtCoordinatesToRef=function(e,n,i){var o=this.getWorldMatrix(),a=u.c.Matrix[5];o.invertToRef(a);var s=u.c.Vector3[8];if(u.e.TransformCoordinatesFromFloatsToRef(e,0,n,a,s),e=s.x,n=s.z,e<this._minX||e>this._maxX||n<this._minZ||n>this._maxZ)return this;this._heightQuads&&this._heightQuads.length!=0||(this._initHeightQuads(),this._computeHeightQuads());var d=this._getFacetAt(e,n);return u.e.TransformNormalFromFloatsToRef(d.x,d.y,d.z,o,i),this},t.prototype.updateCoordinateHeights=function(){return this._heightQuads&&this._heightQuads.length!=0||this._initHeightQuads(),this._computeHeightQuads(),this},t.prototype._getFacetAt=function(e,n){var i=Math.floor((e+this._maxX)*this._subdivisionsX/this._width),o=Math.floor(-(n+this._maxZ)*this._subdivisionsY/this._height+this._subdivisionsY),a=this._heightQuads[o*this._subdivisionsX+i];return n<a.slope.x*e+a.slope.y?a.facet1:a.facet2},t.prototype._initHeightQuads=function(){var e=this._subdivisionsX,n=this._subdivisionsY;this._heightQuads=new Array;for(var i=0;i<n;i++)for(var o=0;o<e;o++){var a={slope:u.d.Zero(),facet1:new u.f(0,0,0,0),facet2:new u.f(0,0,0,0)};this._heightQuads[i*e+o]=a}return this},t.prototype._computeHeightQuads=function(){var e=this.getVerticesData(Oe.b.PositionKind);if(!e)return this;for(var n=u.c.Vector3[3],i=u.c.Vector3[2],o=u.c.Vector3[1],a=u.c.Vector3[0],s=u.c.Vector3[4],d=u.c.Vector3[5],p=u.c.Vector3[6],b=u.c.Vector3[7],P=u.c.Vector3[8],O=0,B=0,F=0,z=0,J=0,ie=0,se=0,ce=this._subdivisionsX,ue=this._subdivisionsY,fe=0;fe<ue;fe++)for(var ve=0;ve<ce;ve++){O=3*ve,B=fe*(ce+1)*3,F=(fe+1)*(ce+1)*3,n.x=e[B+O],n.y=e[B+O+1],n.z=e[B+O+2],i.x=e[B+O+3],i.y=e[B+O+4],i.z=e[B+O+5],o.x=e[F+O],o.y=e[F+O+1],o.z=e[F+O+2],a.x=e[F+O+3],a.y=e[F+O+4],a.z=e[F+O+5],z=(a.z-n.z)/(a.x-n.x),J=n.z-z*n.x,i.subtractToRef(n,s),o.subtractToRef(n,d),a.subtractToRef(n,p),u.e.CrossToRef(p,d,b),u.e.CrossToRef(s,p,P),b.normalize(),P.normalize(),ie=-(b.x*n.x+b.y*n.y+b.z*n.z),se=-(P.x*i.x+P.y*i.y+P.z*i.z);var Te=this._heightQuads[fe*ce+ve];Te.slope.copyFromFloats(z,J),Te.facet1.copyFromFloats(b.x,b.y,b.z,ie),Te.facet2.copyFromFloats(P.x,P.y,P.z,se)}return this},t.prototype.serialize=function(e){r.prototype.serialize.call(this,e),e.subdivisionsX=this._subdivisionsX,e.subdivisionsY=this._subdivisionsY,e.minX=this._minX,e.maxX=this._maxX,e.minZ=this._minZ,e.maxZ=this._maxZ,e.width=this._width,e.height=this._height},t.Parse=function(e,n){var i=new t(e.name,n);return i._subdivisionsX=e.subdivisionsX||1,i._subdivisionsY=e.subdivisionsY||1,i._minX=e.minX,i._maxX=e.maxX,i._minZ=e.minZ,i._maxZ=e.maxZ,i._width=e.width,i._height=e.height,i},t}(De.a),_s=f(70);ft.a.CreateGround=function(r){var t,e,n=[],i=[],o=[],a=[],s=r.width||1,d=r.height||1,p=r.subdivisionsX||r.subdivisions||1,b=r.subdivisionsY||r.subdivisions||1;for(t=0;t<=b;t++)for(e=0;e<=p;e++){var P=new u.e(e*s/p-s/2,0,(b-t)*d/b-d/2),O=new u.e(0,1,0);i.push(P.x,P.y,P.z),o.push(O.x,O.y,O.z),a.push(e/p,1-t/b)}for(t=0;t<b;t++)for(e=0;e<p;e++)n.push(e+1+(t+1)*(p+1)),n.push(e+1+t*(p+1)),n.push(e+t*(p+1)),n.push(e+(t+1)*(p+1)),n.push(e+1+(t+1)*(p+1)),n.push(e+t*(p+1));var B=new ft.a;return B.indices=n,B.positions=i,B.normals=o,B.uvs=a,B},ft.a.CreateTiledGround=function(r){var t,e,n,i,o=r.xmin!==void 0&&r.xmin!==null?r.xmin:-1,a=r.zmin!==void 0&&r.zmin!==null?r.zmin:-1,s=r.xmax!==void 0&&r.xmax!==null?r.xmax:1,d=r.zmax!==void 0&&r.zmax!==null?r.zmax:1,p=r.subdivisions||{w:1,h:1},b=r.precision||{w:1,h:1},P=new Array,O=new Array,B=new Array,F=new Array;p.h=p.h<1?1:p.h,p.w=p.w<1?1:p.w,b.w=b.w<1?1:b.w,b.h=b.h<1?1:b.h;var z=(s-o)/p.w,J=(d-a)/p.h;function ie(ce,ue,fe,ve){var Te=O.length/3,Re=b.w+1;for(t=0;t<b.h;t++)for(e=0;e<b.w;e++){var Ae=[Te+e+t*Re,Te+(e+1)+t*Re,Te+(e+1)+(t+1)*Re,Te+e+(t+1)*Re];P.push(Ae[1]),P.push(Ae[2]),P.push(Ae[3]),P.push(Ae[0]),P.push(Ae[1]),P.push(Ae[3])}var Ee=u.e.Zero(),Se=new u.e(0,1,0);for(t=0;t<=b.h;t++)for(Ee.z=t*(ve-ue)/b.h+ue,e=0;e<=b.w;e++)Ee.x=e*(fe-ce)/b.w+ce,Ee.y=0,O.push(Ee.x,Ee.y,Ee.z),B.push(Se.x,Se.y,Se.z),F.push(e/b.w,t/b.h)}for(n=0;n<p.h;n++)for(i=0;i<p.w;i++)ie(o+i*z,a+n*J,o+(i+1)*z,a+(n+1)*J);var se=new ft.a;return se.indices=P,se.positions=O,se.normals=B,se.uvs=F,se},ft.a.CreateGroundFromHeightMap=function(r){var t,e,n=[],i=[],o=[],a=[],s=r.colorFilter||new M.a(.3,.59,.11),d=r.alphaFilter||0,p=!1;if(r.minHeight>r.maxHeight){p=!0;var b=r.maxHeight;r.maxHeight=r.minHeight,r.minHeight=b}for(t=0;t<=r.subdivisions;t++)for(e=0;e<=r.subdivisions;e++){var P=new u.e(e*r.width/r.subdivisions-r.width/2,0,(r.subdivisions-t)*r.height/r.subdivisions-r.height/2),O=4*(((P.x+r.width/2)/r.width*(r.bufferWidth-1)|0)+((1-(P.z+r.height/2)/r.height)*(r.bufferHeight-1)|0)*r.bufferWidth),B=r.buffer[O]/255,F=r.buffer[O+1]/255,z=r.buffer[O+2]/255,J=r.buffer[O+3]/255;p&&(B=1-B,F=1-F,z=1-z);var ie=B*s.r+F*s.g+z*s.b;P.y=J>=d?r.minHeight+(r.maxHeight-r.minHeight)*ie:r.minHeight-Gt.a,i.push(P.x,P.y,P.z),o.push(0,0,0),a.push(e/r.subdivisions,1-t/r.subdivisions)}for(t=0;t<r.subdivisions;t++)for(e=0;e<r.subdivisions;e++){var se=e+1+(t+1)*(r.subdivisions+1),ce=e+1+t*(r.subdivisions+1),ue=e+t*(r.subdivisions+1),fe=e+(t+1)*(r.subdivisions+1),ve=i[3*se+1]>=r.minHeight,Te=i[3*ce+1]>=r.minHeight,Re=i[3*ue+1]>=r.minHeight;ve&&Te&&Re&&(n.push(se),n.push(ce),n.push(ue)),i[3*fe+1]>=r.minHeight&&ve&&Re&&(n.push(fe),n.push(se),n.push(ue))}ft.a.ComputeNormals(i,n,o);var Ae=new ft.a;return Ae.indices=n,Ae.positions=i,Ae.normals=o,Ae.uvs=a,Ae},De.a.CreateGround=function(r,t,e,n,i,o){var a={width:t,height:e,subdivisions:n,updatable:o};return Ui.CreateGround(r,a,i)},De.a.CreateTiledGround=function(r,t,e,n,i,o,a,s,d){var p={xmin:t,zmin:e,xmax:n,zmax:i,subdivisions:o,precision:a,updatable:d};return Ui.CreateTiledGround(r,p,s)},De.a.CreateGroundFromHeightMap=function(r,t,e,n,i,o,a,s,d,p,b){var P={width:e,height:n,subdivisions:i,minHeight:o,maxHeight:a,updatable:d,onReady:p,alphaFilter:b};return Ui.CreateGroundFromHeightMap(r,t,P,s)};var Ui=function(){function r(){}return r.CreateGround=function(t,e,n){var i=new zo(t,n);return i._setReady(!1),i._subdivisionsX=e.subdivisionsX||e.subdivisions||1,i._subdivisionsY=e.subdivisionsY||e.subdivisions||1,i._width=e.width||1,i._height=e.height||1,i._maxX=i._width/2,i._maxZ=i._height/2,i._minX=-i._maxX,i._minZ=-i._maxZ,ft.a.CreateGround(e).applyToMesh(i,e.updatable),i._setReady(!0),i},r.CreateTiledGround=function(t,e,n){n===void 0&&(n=null);var i=new De.a(t,n);return ft.a.CreateTiledGround(e).applyToMesh(i,e.updatable),i},r.CreateGroundFromHeightMap=function(t,e,n,i){i===void 0&&(i=null);var o=n.width||10,a=n.height||10,s=n.subdivisions||1,d=n.minHeight||0,p=n.maxHeight||1,b=n.colorFilter||new M.a(.3,.59,.11),P=n.alphaFilter||0,O=n.updatable,B=n.onReady;i=i||te.a.LastCreatedScene;var F=new zo(t,i);return F._subdivisionsX=s,F._subdivisionsY=s,F._width=o,F._height=a,F._maxX=F._width/2,F._maxZ=F._height/2,F._minX=-F._maxX,F._minZ=-F._maxZ,F._setReady(!1),Xe.b.LoadImage(e,function(z){var J=z.width,ie=z.height,se=_s.a.CreateCanvas(J,ie).getContext("2d");if(!se)throw new Error("Unable to get 2d context for CreateGroundFromHeightMap");if(!i.isDisposed){se.drawImage(z,0,0);var ce=se.getImageData(0,0,J,ie).data;ft.a.CreateGroundFromHeightMap({width:o,height:a,subdivisions:s,minHeight:d,maxHeight:p,colorFilter:b,buffer:ce,bufferWidth:J,bufferHeight:ie,alphaFilter:P}).applyToMesh(F,O),B&&B(F),F._setReady(!0)}},function(){},i.offlineProvider),F},r}();ft.a.CreateTorus=function(r){for(var t=[],e=[],n=[],i=[],o=r.diameter||1,a=r.thickness||.5,s=r.tessellation||16,d=r.sideOrientation===0?0:r.sideOrientation||ft.a.DEFAULTSIDE,p=s+1,b=0;b<=s;b++)for(var P=b/s,O=b*Math.PI*2/s-Math.PI/2,B=u.a.Translation(o/2,0,0).multiply(u.a.RotationY(O)),F=0;F<=s;F++){var z=1-F/s,J=F*Math.PI*2/s+Math.PI,ie=Math.cos(J),se=Math.sin(J),ce=new u.e(ie,se,0),ue=ce.scale(a/2),fe=new u.d(P,z);ue=u.e.TransformCoordinates(ue,B),ce=u.e.TransformNormal(ce,B),e.push(ue.x,ue.y,ue.z),n.push(ce.x,ce.y,ce.z),i.push(fe.x,fe.y);var ve=(b+1)%p,Te=(F+1)%p;t.push(b*p+F),t.push(b*p+Te),t.push(ve*p+F),t.push(b*p+Te),t.push(ve*p+Te),t.push(ve*p+F)}ft.a._ComputeSides(d,e,t,n,i,r.frontUVs,r.backUVs);var Re=new ft.a;return Re.indices=t,Re.positions=e,Re.normals=n,Re.uvs=i,Re},De.a.CreateTorus=function(r,t,e,n,i,o,a){var s={diameter:t,thickness:e,tessellation:n,sideOrientation:a,updatable:o};return gr.CreateTorus(r,s,i)};var pn,tr,gr=function(){function r(){}return r.CreateTorus=function(t,e,n){var i=new De.a(t,n);return e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation),i._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreateTorus(e).applyToMesh(i,e.updatable),i},r}(),pi=f(53),ms=function(){function r(){}return r.GetDefaults=function(t){var e=new r;return e.canvasOptions={antialias:!0,depth:!0,stencil:!t||t.isStencilEnable,alpha:!0,multiview:!1,framebufferScaleFactor:1},e.newCanvasCssStyle="position:absolute; bottom:0px;right:0px;z-index:10;width:90%;height:100%;background-color: #000000;",e},r}(),Yl=function(){function r(t,e){var n=this;if(e===void 0&&(e=ms.GetDefaults()),this._options=e,this._canvas=null,this.xrLayer=null,this.onXRLayerInitObservable=new C.c,this._engine=t.scene.getEngine(),e.canvasElement)this._setManagedOutputCanvas(e.canvasElement);else{var i=document.createElement("canvas");i.style.cssText=this._options.newCanvasCssStyle||"position:absolute; bottom:0px;right:0px;",this._setManagedOutputCanvas(i)}t.onXRSessionInit.add(function(){n._addCanvas()}),t.onXRSessionEnded.add(function(){n._removeCanvas()})}return r.prototype.dispose=function(){this._removeCanvas(),this._setManagedOutputCanvas(null)},r.prototype.initializeXRLayerAsync=function(t){var e=this,n=function(){var i=new XRWebGLLayer(t,e.canvasContext,e._options.canvasOptions);return e.onXRLayerInitObservable.notifyObservers(i),i};return this.canvasContext.makeXRCompatible?this.canvasContext.makeXRCompatible().then(function(){return e.xrLayer=n(),e.xrLayer}):(this.xrLayer=n(),Promise.resolve(this.xrLayer))},r.prototype._addCanvas=function(){var t=this;this._canvas&&this._canvas!==this._engine.getRenderingCanvas()&&document.body.appendChild(this._canvas),this.xrLayer?this._setCanvasSize(!0):this.onXRLayerInitObservable.addOnce(function(e){t._setCanvasSize(!0,e)})},r.prototype._removeCanvas=function(){this._canvas&&document.body.contains(this._canvas)&&this._canvas!==this._engine.getRenderingCanvas()&&document.body.removeChild(this._canvas),this._setCanvasSize(!1)},r.prototype._setCanvasSize=function(t,e){t===void 0&&(t=!0),e===void 0&&(e=this.xrLayer),this._canvas&&(t?e&&(this._canvas!==this._engine.getRenderingCanvas()?(this._canvas.style.width=e.framebufferWidth+"px",this._canvas.style.height=e.framebufferHeight+"px"):this._engine.setSize(e.framebufferWidth,e.framebufferHeight)):this._originalCanvasSize&&(this._canvas!==this._engine.getRenderingCanvas()?(this._canvas.style.width=this._originalCanvasSize.width+"px",this._canvas.style.height=this._originalCanvasSize.height+"px"):this._engine.setSize(this._originalCanvasSize.width,this._originalCanvasSize.height)))},r.prototype._setManagedOutputCanvas=function(t){this._removeCanvas(),t?(this._originalCanvasSize={width:t.offsetWidth,height:t.offsetHeight},this._canvas=t,this.canvasContext=this._canvas.getContext("webgl2"),this.canvasContext||(this.canvasContext=this._canvas.getContext("webgl"))):(this._canvas=null,this.canvasContext=null)},r}(),gs=function(){function r(t){this.scene=t,this._sessionEnded=!1,this.baseLayer=null,this.currentTimestamp=-1,this.defaultHeightCompensation=1.7,this.onXRFrameObservable=new C.c,this.onXRReferenceSpaceChanged=new C.c,this.onXRSessionEnded=new C.c,this.onXRSessionInit=new C.c}return Object.defineProperty(r.prototype,"referenceSpace",{get:function(){return this._referenceSpace},set:function(t){this._referenceSpace=t,this.onXRReferenceSpaceChanged.notifyObservers(this._referenceSpace)},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this._sessionEnded||this.exitXRAsync(),this.onXRFrameObservable.clear(),this.onXRSessionEnded.clear(),this.onXRReferenceSpaceChanged.clear(),this.onXRSessionInit.clear()},r.prototype.exitXRAsync=function(){return this.session&&!this._sessionEnded?(this._sessionEnded=!0,this.session.end().catch(function(t){l.a.Warn("Could not end XR session.")})):Promise.resolve()},r.prototype.getRenderTargetTextureForEye=function(t){return this._rttProvider.getRenderTargetForEye(t)},r.prototype.getWebXRRenderTarget=function(t){var e=this.scene.getEngine();return this._xrNavigator.xr.native?this._xrNavigator.xr.getWebXRRenderTarget(e):((t=t||ms.GetDefaults(e)).canvasElement=e.getRenderingCanvas()||void 0,new Yl(this,t))},r.prototype.initializeAsync=function(){return this._xrNavigator=navigator,this._xrNavigator.xr?Promise.resolve():Promise.reject("WebXR not available")},r.prototype.initializeSessionAsync=function(t,e){var n=this;return t===void 0&&(t="immersive-vr"),e===void 0&&(e={}),this._xrNavigator.xr.requestSession(t,e).then(function(i){return n.session=i,n.onXRSessionInit.notifyObservers(i),n._sessionEnded=!1,n.session.addEventListener("end",function(){var o=n.scene.getEngine();n._sessionEnded=!0,n._rttProvider=null,o.framebufferDimensionsObject=null,o.restoreDefaultFramebuffer(),o.customAnimationFrameRequester=null,n.onXRSessionEnded.notifyObservers(null),o._renderLoop()},{once:!0}),n.session})},r.prototype.isSessionSupportedAsync=function(t){return r.IsSessionSupportedAsync(t)},r.prototype.resetReferenceSpace=function(){this.referenceSpace=this.baseReferenceSpace},r.prototype.runXRRenderLoop=function(){var t=this,e=this.scene.getEngine();if(e.customAnimationFrameRequester={requestAnimationFrame:this.session.requestAnimationFrame.bind(this.session),renderFunction:function(i,o){t._sessionEnded||(t.currentFrame=o,t.currentTimestamp=i,o&&(e.framebufferDimensionsObject=t.baseLayer,t.onXRFrameObservable.notifyObservers(o),e._renderLoop(),e.framebufferDimensionsObject=null))}},this._xrNavigator.xr.native)this._rttProvider=this._xrNavigator.xr.getNativeRenderTargetProvider(this.session,this._createRenderTargetTexture.bind(this));else{var n=this._createRenderTargetTexture(this.baseLayer.framebufferWidth,this.baseLayer.framebufferHeight,this.baseLayer.framebuffer);this._rttProvider={getRenderTargetForEye:function(){return n}},e.framebufferDimensionsObject=this.baseLayer}typeof window<"u"&&window.cancelAnimationFrame&&window.cancelAnimationFrame(e._frameHandler),e._renderLoop()},r.prototype.setReferenceSpaceTypeAsync=function(t){var e=this;return t===void 0&&(t="local-floor"),this.session.requestReferenceSpace(t).then(function(n){return n},function(n){return l.a.Error("XR.requestReferenceSpace failed for the following reason: "),l.a.Error(n),l.a.Log('Defaulting to universally-supported "viewer" reference space type.'),e.session.requestReferenceSpace("viewer").then(function(i){var o=new XRRigidTransform({x:0,y:-e.defaultHeightCompensation,z:0});return i.getOffsetReferenceSpace(o)},function(i){throw l.a.Error(i),'XR initialization failed: required "viewer" reference space type not supported.'})}).then(function(n){return e.session.requestReferenceSpace("viewer").then(function(i){return e.viewerReferenceSpace=i,n})}).then(function(n){return e.referenceSpace=e.baseReferenceSpace=n,e.referenceSpace})},r.prototype.updateRenderStateAsync=function(t){return t.baseLayer&&(this.baseLayer=t.baseLayer),this.session.updateRenderState(t)},r.IsSessionSupportedAsync=function(t){if(!navigator.xr)return Promise.resolve(!1);var e=navigator.xr.isSessionSupported||navigator.xr.supportsSession;return e?e.call(navigator.xr,t).then(function(n){var i=n===void 0||n;return Promise.resolve(i)}).catch(function(n){return l.a.Warn(n),Promise.resolve(!1)}):Promise.resolve(!1)},r.prototype._createRenderTargetTexture=function(t,e,n){n===void 0&&(n=null);var i=new Ct.a(this.scene.getEngine(),Ct.b.Unknown,!0);i.width=t,i.height=e,i._framebuffer=n;var o=new sn("XR renderTargetTexture",{width:t,height:e},this.scene,void 0,void 0,void 0,void 0,void 0,void 0,void 0,void 0,void 0,!0);return o._texture=i,o},r}();(function(r){r[r.ENTERING_XR=0]="ENTERING_XR",r[r.EXITING_XR=1]="EXITING_XR",r[r.IN_XR=2]="IN_XR",r[r.NOT_IN_XR=3]="NOT_IN_XR"})(pn||(pn={})),function(r){r[r.NOT_TRACKING=0]="NOT_TRACKING",r[r.TRACKING_LOST=1]="TRACKING_LOST",r[r.TRACKING=2]="TRACKING"}(tr||(tr={}));var ri,Kl=function(){function r(t,e){if(e===void 0&&(e=null),this.scene=t,this._pointerDownOnMeshAsked=!1,this._isActionableMesh=!1,this._teleportationRequestInitiated=!1,this._teleportationBackRequestInitiated=!1,this._rotationRightAsked=!1,this._rotationLeftAsked=!1,this._dpadPressed=!0,this._activePointer=!1,this._id=r._idCounter++,e)this._gazeTracker=e.clone("gazeTracker");else{this._gazeTracker=De.a.CreateTorus("gazeTracker",.0035,.0025,20,t,!1),this._gazeTracker.bakeCurrentTransformIntoVertices(),this._gazeTracker.isPickable=!1,this._gazeTracker.isVisible=!1;var n=new Ft.a("targetMat",t);n.specularColor=M.a.Black(),n.emissiveColor=new M.a(.7,.7,.7),n.backFaceCulling=!1,this._gazeTracker.material=n}}return r.prototype._getForwardRay=function(t){return new fn.a(u.e.Zero(),new u.e(0,0,t))},r.prototype._selectionPointerDown=function(){this._pointerDownOnMeshAsked=!0,this._currentHit&&this.scene.simulatePointerDown(this._currentHit,{pointerId:this._id})},r.prototype._selectionPointerUp=function(){this._currentHit&&this.scene.simulatePointerUp(this._currentHit,{pointerId:this._id}),this._pointerDownOnMeshAsked=!1},r.prototype._activatePointer=function(){this._activePointer=!0},r.prototype._deactivatePointer=function(){this._activePointer=!1},r.prototype._updatePointerDistance=function(t){},r.prototype.dispose=function(){this._interactionsEnabled=!1,this._teleportationEnabled=!1,this._gazeTracker&&this._gazeTracker.dispose()},r._idCounter=0,r}(),Qf=function(r){function t(e,n,i){var o=r.call(this,n,i)||this;o.webVRController=e,o._laserPointer=De.a.CreateCylinder("laserPointer",1,.004,2e-4,20,1,n,!1);var a=new Ft.a("laserPointerMat",n);if(a.emissiveColor=new M.a(.7,.7,.7),a.alpha=.6,o._laserPointer.material=a,o._laserPointer.rotation.x=Math.PI/2,o._laserPointer.position.z=-.5,o._laserPointer.isVisible=!1,o._laserPointer.isPickable=!1,!e.mesh){var s=new De.a("preloadControllerMesh",n),d=new De.a(pr.POINTING_POSE,n);d.rotation.x=-.7,s.addChild(d),e.attachToMesh(s)}return o._setLaserPointerParent(e.mesh),o._meshAttachedObserver=e._meshAttachedObservable.add(function(p){o._setLaserPointerParent(p)}),o}return Object(c.d)(t,r),t.prototype._getForwardRay=function(e){return this.webVRController.getForwardRay(e)},t.prototype._activatePointer=function(){r.prototype._activatePointer.call(this),this._laserPointer.isVisible=!0},t.prototype._deactivatePointer=function(){r.prototype._deactivatePointer.call(this),this._laserPointer.isVisible=!1},t.prototype._setLaserPointerColor=function(e){this._laserPointer.material.emissiveColor=e},t.prototype._setLaserPointerLightingDisabled=function(e){this._laserPointer.material.disableLighting=e},t.prototype._setLaserPointerParent=function(e){var n=function(s){s.isPickable=!1,s.getChildMeshes().forEach(function(d){n(d)})};n(e);var i=e.getChildren(void 0,!1),o=e;this.webVRController._pointingPoseNode=null;for(var a=0;a<i.length;a++)if(i[a].name&&i[a].name.indexOf(pr.POINTING_POSE)>=0){o=i[a],this.webVRController._pointingPoseNode=o;break}this._laserPointer.parent=o},t.prototype._updatePointerDistance=function(e){e===void 0&&(e=100),this._laserPointer.scaling.y=e,this._laserPointer.position.z=-e/2},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._laserPointer.dispose(),this._meshAttachedObserver&&this.webVRController._meshAttachedObservable.remove(this._meshAttachedObserver)},t}(Kl),Ql=function(r){function t(e,n){var i=r.call(this,n)||this;return i.getCamera=e,i}return Object(c.d)(t,r),t.prototype._getForwardRay=function(e){var n=this.getCamera();return n?n.getForwardRay(e):new fn.a(u.e.Zero(),u.e.Forward())},t}(Kl),qf=function(){},ql=function(){function r(t,e){var n=this;if(e===void 0&&(e={}),this.webVROptions=e,this._webVRsupported=!1,this._webVRready=!1,this._webVRrequesting=!1,this._webVRpresenting=!1,this._fullscreenVRpresenting=!1,this.enableGazeEvenWhenNoPointerLock=!1,this.exitVROnDoubleTap=!0,this.onEnteringVRObservable=new C.c,this.onAfterEnteringVRObservable=new C.c,this.onExitingVRObservable=new C.c,this.onControllerMeshLoadedObservable=new C.c,this._useCustomVRButton=!1,this._teleportationRequested=!1,this._teleportActive=!1,this._floorMeshesCollection=[],this._teleportationMode=r.TELEPORTATIONMODE_CONSTANTTIME,this._teleportationTime=122,this._teleportationSpeed=20,this._rotationAllowed=!0,this._teleportBackwardsVector=new u.e(0,-1,-1),this._isDefaultTeleportationTarget=!0,this._teleportationFillColor="#444444",this._teleportationBorderColor="#FFFFFF",this._rotationAngle=0,this._haloCenter=new u.e(0,0,0),this._padSensibilityUp=.65,this._padSensibilityDown=.35,this._leftController=null,this._rightController=null,this._gazeColor=new M.a(.7,.7,.7),this._laserColor=new M.a(.7,.7,.7),this._pickedLaserColor=new M.a(.2,.2,1),this._pickedGazeColor=new M.a(0,0,1),this.onNewMeshSelected=new C.c,this.onMeshSelectedWithController=new C.c,this.onNewMeshPicked=new C.c,this.onBeforeCameraTeleport=new C.c,this.onAfterCameraTeleport=new C.c,this.onSelectedMeshUnselected=new C.c,this.teleportationEnabled=!0,this._teleportationInitialized=!1,this._interactionsEnabled=!1,this._interactionsRequested=!1,this._displayGaze=!0,this._displayLaserPointer=!0,this.updateGazeTrackerScale=!0,this.updateGazeTrackerColor=!0,this.updateControllerLaserColor=!0,this.requestPointerLockOnFullScreen=!0,this.xrTestDone=!1,this._onResize=function(){n.moveButtonToBottomRight(),n._fullscreenVRpresenting&&n._webVRready&&n.exitVR()},this._onFullscreenChange=function(){var o=document;o.fullscreen!==void 0?n._fullscreenVRpresenting=document.fullscreen:o.mozFullScreen!==void 0?n._fullscreenVRpresenting=o.mozFullScreen:o.webkitIsFullScreen!==void 0?n._fullscreenVRpresenting=o.webkitIsFullScreen:o.msIsFullScreen!==void 0?n._fullscreenVRpresenting=o.msIsFullScreen:document.msFullscreenElement!==void 0&&(n._fullscreenVRpresenting=document.msFullscreenElement),!n._fullscreenVRpresenting&&n._inputElement&&(n.exitVR(),!n._useCustomVRButton&&n._btnVR&&(n._btnVR.style.top=n._inputElement.offsetTop+n._inputElement.offsetHeight-70+"px",n._btnVR.style.left=n._inputElement.offsetLeft+n._inputElement.offsetWidth-100+"px",n.updateButtonVisibility()))},this._cachedAngularSensibility={angularSensibilityX:null,angularSensibilityY:null,angularSensibility:null},this.beforeRender=function(){n._leftController&&n._leftController._activePointer&&n._castRayAndSelectObject(n._leftController),n._rightController&&n._rightController._activePointer&&n._castRayAndSelectObject(n._rightController),n._noControllerIsActive&&(n._scene.getEngine().isPointerLock||n.enableGazeEvenWhenNoPointerLock)?n._castRayAndSelectObject(n._cameraGazer):n._cameraGazer._gazeTracker.isVisible=!1},this._onNewGamepadConnected=function(o){if(o.type!==dn.POSE_ENABLED)o.leftStick&&o.onleftstickchanged(function(d){n._teleportationInitialized&&n.teleportationEnabled&&(!n._leftController&&!n._rightController||n._leftController&&!n._leftController._activePointer&&n._rightController&&!n._rightController._activePointer)&&(n._checkTeleportWithRay(d,n._cameraGazer),n._checkTeleportBackwards(d,n._cameraGazer))}),o.rightStick&&o.onrightstickchanged(function(d){n._teleportationInitialized&&n._checkRotate(d,n._cameraGazer)}),o.type===dn.XBOX&&(o.onbuttondown(function(d){n._interactionsEnabled&&d===Rn.A&&n._cameraGazer._selectionPointerDown()}),o.onbuttonup(function(d){n._interactionsEnabled&&d===Rn.A&&n._cameraGazer._selectionPointerUp()}));else{var a=o,s=new Qf(a,n._scene,n._cameraGazer._gazeTracker);a.hand==="right"||n._leftController&&n._leftController.webVRController!=a?n._rightController=s:n._leftController=s,n._tryEnableInteractionOnController(s)}},this._tryEnableInteractionOnController=function(o){n._interactionsRequested&&!o._interactionsEnabled&&n._enableInteractionOnController(o),n._teleportationRequested&&!o._teleportationEnabled&&n._enableTeleportationOnController(o)},this._onNewGamepadDisconnected=function(o){o instanceof Bi&&(o.hand==="left"&&n._leftController!=null&&(n._leftController.dispose(),n._leftController=null),o.hand==="right"&&n._rightController!=null&&(n._rightController.dispose(),n._rightController=null))},this._workingVector=u.e.Zero(),this._workingQuaternion=u.b.Identity(),this._workingMatrix=u.a.Identity(),this._scene=t,this._inputElement=t.getEngine().getInputElement(),"getVRDisplays"in navigator||(e.useXR=!0),e.createFallbackVRDeviceOrientationFreeCamera===void 0&&(e.createFallbackVRDeviceOrientationFreeCamera=!0),e.createDeviceOrientationCamera===void 0&&(e.createDeviceOrientationCamera=!0),e.laserToggle===void 0&&(e.laserToggle=!0),e.defaultHeight===void 0&&(e.defaultHeight=1.7),e.useCustomVRButton&&(this._useCustomVRButton=!0,e.customVRButton&&(this._btnVR=e.customVRButton)),e.rayLength&&(this._rayLength=e.rayLength),this._defaultHeight=e.defaultHeight,e.positionScale&&(this._rayLength*=e.positionScale,this._defaultHeight*=e.positionScale),this._hasEnteredVR=!1,this._scene.activeCamera?this._position=this._scene.activeCamera.position.clone():this._position=new u.e(0,this._defaultHeight,0),e.createDeviceOrientationCamera||!this._scene.activeCamera){if(this._deviceOrientationCamera=new Fo("deviceOrientationVRHelper",this._position.clone(),t),this._scene.activeCamera&&(this._deviceOrientationCamera.minZ=this._scene.activeCamera.minZ,this._deviceOrientationCamera.maxZ=this._scene.activeCamera.maxZ,this._scene.activeCamera instanceof Ni&&this._scene.activeCamera.rotation)){var i=this._scene.activeCamera;i.rotationQuaternion?this._deviceOrientationCamera.rotationQuaternion.copyFrom(i.rotationQuaternion):this._deviceOrientationCamera.rotationQuaternion.copyFrom(u.b.RotationYawPitchRoll(i.rotation.y,i.rotation.x,i.rotation.z)),this._deviceOrientationCamera.rotation=i.rotation.clone()}this._scene.activeCamera=this._deviceOrientationCamera,this._inputElement&&this._scene.activeCamera.attachControl()}else this._existingCamera=this._scene.activeCamera;this.webVROptions.useXR&&navigator.xr?gs.IsSessionSupportedAsync("immersive-vr").then(function(o){o?(l.a.Log("Using WebXR. It is recommended to use the WebXRDefaultExperience directly"),t.createDefaultXRExperienceAsync({floorMeshes:e.floorMeshes||[]}).then(function(a){n.xr=a,n.xrTestDone=!0,n._cameraGazer=new Ql(function(){return n.xr.baseExperience.camera},t),n.xr.baseExperience.onStateChangedObservable.add(function(s){switch(s){case pn.ENTERING_XR:n.onEnteringVRObservable.notifyObservers(n),n._interactionsEnabled||n.xr.pointerSelection.detach(),n.xr.pointerSelection.displayLaserPointer=n._displayLaserPointer;break;case pn.EXITING_XR:n.onExitingVRObservable.notifyObservers(n),n._scene.getEngine().resize();break;case pn.IN_XR:n._hasEnteredVR=!0;break;case pn.NOT_IN_XR:n._hasEnteredVR=!1}})})):n.completeVRInit(t,e)}):this.completeVRInit(t,e)}return Object.defineProperty(r.prototype,"onEnteringVR",{get:function(){return this.onEnteringVRObservable},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onExitingVR",{get:function(){return this.onExitingVRObservable},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onControllerMeshLoaded",{get:function(){return this.onControllerMeshLoadedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"teleportationTarget",{get:function(){return this._teleportationTarget},set:function(t){t&&(t.name="teleportationTarget",this._isDefaultTeleportationTarget=!1,this._teleportationTarget=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"gazeTrackerMesh",{get:function(){return this._cameraGazer._gazeTracker},set:function(t){t&&(this._cameraGazer._gazeTracker&&this._cameraGazer._gazeTracker.dispose(),this._leftController&&this._leftController._gazeTracker&&this._leftController._gazeTracker.dispose(),this._rightController&&this._rightController._gazeTracker&&this._rightController._gazeTracker.dispose(),this._cameraGazer._gazeTracker=t,this._cameraGazer._gazeTracker.bakeCurrentTransformIntoVertices(),this._cameraGazer._gazeTracker.isPickable=!1,this._cameraGazer._gazeTracker.isVisible=!1,this._cameraGazer._gazeTracker.name="gazeTracker",this._leftController&&(this._leftController._gazeTracker=this._cameraGazer._gazeTracker.clone("gazeTracker")),this._rightController&&(this._rightController._gazeTracker=this._cameraGazer._gazeTracker.clone("gazeTracker")))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"leftControllerGazeTrackerMesh",{get:function(){return this._leftController?this._leftController._gazeTracker:null},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rightControllerGazeTrackerMesh",{get:function(){return this._rightController?this._rightController._gazeTracker:null},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"displayGaze",{get:function(){return this._displayGaze},set:function(t){this._displayGaze=t,t||(this._cameraGazer._gazeTracker.isVisible=!1,this._leftController&&(this._leftController._gazeTracker.isVisible=!1),this._rightController&&(this._rightController._gazeTracker.isVisible=!1))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"displayLaserPointer",{get:function(){return this._displayLaserPointer},set:function(t){this._displayLaserPointer=t,t?(this._rightController&&this._rightController._activatePointer(),this._leftController&&this._leftController._activatePointer()):(this._rightController&&(this._rightController._deactivatePointer(),this._rightController._gazeTracker.isVisible=!1),this._leftController&&(this._leftController._deactivatePointer(),this._leftController._gazeTracker.isVisible=!1))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"deviceOrientationCamera",{get:function(){return this._deviceOrientationCamera},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"currentVRCamera",{get:function(){return this._webVRready?this._webVRCamera:this._scene.activeCamera},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"webVRCamera",{get:function(){return this._webVRCamera},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"vrDeviceOrientationCamera",{get:function(){return this._vrDeviceOrientationCamera},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"vrButton",{get:function(){return this._btnVR},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"_teleportationRequestInitiated",{get:function(){return this._cameraGazer._teleportationRequestInitiated||this._leftController!==null&&this._leftController._teleportationRequestInitiated||this._rightController!==null&&this._rightController._teleportationRequestInitiated},enumerable:!1,configurable:!0}),r.prototype.completeVRInit=function(t,e){var n=this;if(this.xrTestDone=!0,e.createFallbackVRDeviceOrientationFreeCamera&&(e.useMultiview&&(e.vrDeviceOrientationCameraMetrics||(e.vrDeviceOrientationCameraMetrics=mr.GetDefault()),e.vrDeviceOrientationCameraMetrics.multiviewEnabled=!0),this._vrDeviceOrientationCamera=new Uo("VRDeviceOrientationVRHelper",this._position,this._scene,!0,e.vrDeviceOrientationCameraMetrics),this._vrDeviceOrientationCamera.angularSensibility=Number.MAX_VALUE),this._webVRCamera=new ko("WebVRHelper",this._position,this._scene,e),this._webVRCamera.useStandingMatrix(),this._cameraGazer=new Ql(function(){return n.currentVRCamera},t),!this._useCustomVRButton){this._btnVR=document.createElement("BUTTON"),this._btnVR.className="babylonVRicon",this._btnVR.id="babylonVRiconbtn",this._btnVR.title="Click to switch to VR";var i=".babylonVRicon { position: absolute; right: 20px; height: 50px; width: 80px; background-color: rgba(51,51,51,0.7); background-image: url("+(window.SVGSVGElement?"data:image/svg+xml;charset=UTF-8,%3Csvg%20xmlns%3D%22http%3A//www.w3.org/2000/svg%22%20width%3D%222048%22%20height%3D%221152%22%20viewBox%3D%220%200%202048%201152%22%20version%3D%221.1%22%3E%3Cpath%20transform%3D%22rotate%28180%201024%2C576.0000000000001%29%22%20d%3D%22m1109%2C896q17%2C0%2030%2C-12t13%2C-30t-12.5%2C-30.5t-30.5%2C-12.5l-170%2C0q-18%2C0%20-30.5%2C12.5t-12.5%2C30.5t13%2C30t30%2C12l170%2C0zm-85%2C256q59%2C0%20132.5%2C-1.5t154.5%2C-5.5t164.5%2C-11.5t163%2C-20t150%2C-30t124.5%2C-41.5q23%2C-11%2042%2C-24t38%2C-30q27%2C-25%2041%2C-61.5t14%2C-72.5l0%2C-257q0%2C-123%20-47%2C-232t-128%2C-190t-190%2C-128t-232%2C-47l-81%2C0q-37%2C0%20-68.5%2C14t-60.5%2C34.5t-55.5%2C45t-53%2C45t-53%2C34.5t-55.5%2C14t-55.5%2C-14t-53%2C-34.5t-53%2C-45t-55.5%2C-45t-60.5%2C-34.5t-68.5%2C-14l-81%2C0q-123%2C0%20-232%2C47t-190%2C128t-128%2C190t-47%2C232l0%2C257q0%2C68%2038%2C115t97%2C73q54%2C24%20124.5%2C41.5t150%2C30t163%2C20t164.5%2C11.5t154.5%2C5.5t132.5%2C1.5zm939%2C-298q0%2C39%20-24.5%2C67t-58.5%2C42q-54%2C23%20-122%2C39.5t-143.5%2C28t-155.5%2C19t-157%2C11t-148.5%2C5t-129.5%2C1.5q-59%2C0%20-130%2C-1.5t-148%2C-5t-157%2C-11t-155.5%2C-19t-143.5%2C-28t-122%2C-39.5q-34%2C-14%20-58.5%2C-42t-24.5%2C-67l0%2C-257q0%2C-106%2040.5%2C-199t110%2C-162.5t162.5%2C-109.5t199%2C-40l81%2C0q27%2C0%2052%2C14t50%2C34.5t51%2C44.5t55.5%2C44.5t63.5%2C34.5t74%2C14t74%2C-14t63.5%2C-34.5t55.5%2C-44.5t51%2C-44.5t50%2C-34.5t52%2C-14l14%2C0q37%2C0%2070%2C0.5t64.5%2C4.5t63.5%2C12t68%2C23q71%2C30%20128.5%2C78.5t98.5%2C110t63.5%2C133.5t22.5%2C149l0%2C257z%22%20fill%3D%22white%22%20/%3E%3C/svg%3E%0A":"https://cdn.babylonjs.com/Assets/vrButton.png")+"); background-size: 80%; background-repeat:no-repeat; background-position: center; border: none; outline: none; transition: transform 0.125s ease-out } .babylonVRicon:hover { transform: scale(1.05) } .babylonVRicon:active {background-color: rgba(51,51,51,1) } .babylonVRicon:focus {background-color: rgba(51,51,51,1) }";i+=".babylonVRicon.vrdisplaypresenting { display: none; }";var o=document.createElement("style");o.appendChild(document.createTextNode(i)),document.getElementsByTagName("head")[0].appendChild(o),this.moveButtonToBottomRight()}this._btnVR&&this._btnVR.addEventListener("click",function(){n.isInVRMode?n._scene.getEngine().disableVR():n.enterVR()});var a=this._scene.getEngine().getHostWindow();a&&(a.addEventListener("resize",this._onResize),document.addEventListener("fullscreenchange",this._onFullscreenChange,!1),document.addEventListener("mozfullscreenchange",this._onFullscreenChange,!1),document.addEventListener("webkitfullscreenchange",this._onFullscreenChange,!1),document.addEventListener("msfullscreenchange",this._onFullscreenChange,!1),document.onmsfullscreenchange=this._onFullscreenChange,e.createFallbackVRDeviceOrientationFreeCamera?this.displayVRButton():this._scene.getEngine().onVRDisplayChangedObservable.add(function(s){s.vrDisplay&&n.displayVRButton()}),this._onKeyDown=function(s){s.keyCode===27&&n.isInVRMode&&n.exitVR()},document.addEventListener("keydown",this._onKeyDown),this._scene.onPrePointerObservable.add(function(){n._hasEnteredVR&&n.exitVROnDoubleTap&&(n.exitVR(),n._fullscreenVRpresenting&&n._scene.getEngine().exitFullscreen())},Tt.a.POINTERDOUBLETAP,!1),this._onVRDisplayChanged=function(s){return n.onVRDisplayChanged(s)},this._onVrDisplayPresentChange=function(){return n.onVrDisplayPresentChange()},this._onVRRequestPresentStart=function(){n._webVRrequesting=!0,n.updateButtonVisibility()},this._onVRRequestPresentComplete=function(){n._webVRrequesting=!1,n.updateButtonVisibility()},t.getEngine().onVRDisplayChangedObservable.add(this._onVRDisplayChanged),t.getEngine().onVRRequestPresentStart.add(this._onVRRequestPresentStart),t.getEngine().onVRRequestPresentComplete.add(this._onVRRequestPresentComplete),a.addEventListener("vrdisplaypresentchange",this._onVrDisplayPresentChange),t.onDisposeObservable.add(function(){n.dispose()}),this._webVRCamera.onControllerMeshLoadedObservable.add(function(s){return n._onDefaultMeshLoaded(s)}),this._scene.gamepadManager.onGamepadConnectedObservable.add(this._onNewGamepadConnected),this._scene.gamepadManager.onGamepadDisconnectedObservable.add(this._onNewGamepadDisconnected),this.updateButtonVisibility(),this._circleEase=new nt,this._circleEase.setEasingMode(Ge.EASINGMODE_EASEINOUT),this._teleportationEasing=this._circleEase,t.onPointerObservable.add(function(s){n._interactionsEnabled&&t.activeCamera===n.vrDeviceOrientationCamera&&s.event.pointerType==="mouse"&&(s.type===Tt.a.POINTERDOWN?n._cameraGazer._selectionPointerDown():s.type===Tt.a.POINTERUP&&n._cameraGazer._selectionPointerUp())}),this.webVROptions.floorMeshes&&this.enableTeleportation({floorMeshes:this.webVROptions.floorMeshes}))},r.prototype._onDefaultMeshLoaded=function(t){this._leftController&&this._leftController.webVRController==t&&t.mesh&&this._leftController._setLaserPointerParent(t.mesh),this._rightController&&this._rightController.webVRController==t&&t.mesh&&this._rightController._setLaserPointerParent(t.mesh);try{this.onControllerMeshLoadedObservable.notifyObservers(t)}catch(e){l.a.Warn("Error in your custom logic onControllerMeshLoaded: "+e)}},Object.defineProperty(r.prototype,"isInVRMode",{get:function(){return this.xr&&this.webVROptions.useXR&&this.xr.baseExperience.state===pn.IN_XR||this._webVRpresenting||this._fullscreenVRpresenting},enumerable:!1,configurable:!0}),r.prototype.onVrDisplayPresentChange=function(){var t=this._scene.getEngine().getVRDevice();if(t){var e=this._webVRpresenting;this._webVRpresenting=t.isPresenting,e&&!this._webVRpresenting&&this.exitVR()}else l.a.Warn("Detected VRDisplayPresentChange on an unknown VRDisplay. Did you can enterVR on the vrExperienceHelper?");this.updateButtonVisibility()},r.prototype.onVRDisplayChanged=function(t){this._webVRsupported=t.vrSupported,this._webVRready=!!t.vrDisplay,this._webVRpresenting=t.vrDisplay&&t.vrDisplay.isPresenting,this.updateButtonVisibility()},r.prototype.moveButtonToBottomRight=function(){if(this._inputElement&&!this._useCustomVRButton&&this._btnVR){var t=this._inputElement.getBoundingClientRect();this._btnVR.style.top=t.top+t.height-70+"px",this._btnVR.style.left=t.left+t.width-100+"px"}},r.prototype.displayVRButton=function(){this._useCustomVRButton||this._btnVRDisplayed||!this._btnVR||(document.body.appendChild(this._btnVR),this._btnVRDisplayed=!0)},r.prototype.updateButtonVisibility=function(){this._btnVR&&!this._useCustomVRButton&&(this._btnVR.className="babylonVRicon",this.isInVRMode?this._btnVR.className+=" vrdisplaypresenting":(this._webVRready&&(this._btnVR.className+=" vrdisplayready"),this._webVRsupported&&(this._btnVR.className+=" vrdisplaysupported"),this._webVRrequesting&&(this._btnVR.className+=" vrdisplayrequesting")))},r.prototype.enterVR=function(){var t=this;if(this.xr)this.xr.baseExperience.enterXRAsync("immersive-vr","local-floor",this.xr.renderTarget);else{if(this.onEnteringVRObservable)try{this.onEnteringVRObservable.notifyObservers(this)}catch(o){l.a.Warn("Error in your custom logic onEnteringVR: "+o)}if(this._scene.activeCamera){if(this._position=this._scene.activeCamera.position.clone(),this.vrDeviceOrientationCamera&&(this.vrDeviceOrientationCamera.rotation=u.b.FromRotationMatrix(this._scene.activeCamera.getWorldMatrix().getRotationMatrix()).toEulerAngles(),this.vrDeviceOrientationCamera.angularSensibility=2e3),this.webVRCamera){var e=this.webVRCamera.deviceRotationQuaternion.toEulerAngles().y,n=u.b.FromRotationMatrix(this._scene.activeCamera.getWorldMatrix().getRotationMatrix()).toEulerAngles().y-e,i=this.webVRCamera.rotationQuaternion.toEulerAngles().y;this.webVRCamera.rotationQuaternion=u.b.FromEulerAngles(0,i+n,0)}this._existingCamera=this._scene.activeCamera,this._existingCamera.angularSensibilityX&&(this._cachedAngularSensibility.angularSensibilityX=this._existingCamera.angularSensibilityX,this._existingCamera.angularSensibilityX=Number.MAX_VALUE),this._existingCamera.angularSensibilityY&&(this._cachedAngularSensibility.angularSensibilityY=this._existingCamera.angularSensibilityY,this._existingCamera.angularSensibilityY=Number.MAX_VALUE),this._existingCamera.angularSensibility&&(this._cachedAngularSensibility.angularSensibility=this._existingCamera.angularSensibility,this._existingCamera.angularSensibility=Number.MAX_VALUE)}this._webVRrequesting||(this._webVRready?this._webVRpresenting||(this._scene.getEngine().onVRRequestPresentComplete.addOnce(function(o){t.onAfterEnteringVRObservable.notifyObservers({success:o})}),this._webVRCamera.position=this._position,this._scene.activeCamera=this._webVRCamera):this._vrDeviceOrientationCamera&&(this._vrDeviceOrientationCamera.position=this._position,this._scene.activeCamera&&(this._vrDeviceOrientationCamera.minZ=this._scene.activeCamera.minZ),this._scene.activeCamera=this._vrDeviceOrientationCamera,this._scene.getEngine().enterFullscreen(this.requestPointerLockOnFullScreen),this.updateButtonVisibility(),this._vrDeviceOrientationCamera.onViewMatrixChangedObservable.addOnce(function(){t.onAfterEnteringVRObservable.notifyObservers({success:!0})})),this._scene.activeCamera&&this._inputElement&&this._scene.activeCamera.attachControl(),this._interactionsEnabled&&this._scene.registerBeforeRender(this.beforeRender),this._displayLaserPointer&&[this._leftController,this._rightController].forEach(function(o){o&&o._activatePointer()}),this._hasEnteredVR=!0)}},r.prototype.exitVR=function(){if(this.xr)this.xr.baseExperience.exitXRAsync();else if(this._hasEnteredVR){if(this.onExitingVRObservable)try{this.onExitingVRObservable.notifyObservers(this)}catch(e){l.a.Warn("Error in your custom logic onExitingVR: "+e)}this._webVRpresenting&&this._scene.getEngine().disableVR(),this._scene.activeCamera&&(this._position=this._scene.activeCamera.position.clone()),this.vrDeviceOrientationCamera&&(this.vrDeviceOrientationCamera.angularSensibility=Number.MAX_VALUE),this._deviceOrientationCamera?(this._deviceOrientationCamera.position=this._position,this._scene.activeCamera=this._deviceOrientationCamera,this._cachedAngularSensibility.angularSensibilityX&&(this._deviceOrientationCamera.angularSensibilityX=this._cachedAngularSensibility.angularSensibilityX,this._cachedAngularSensibility.angularSensibilityX=null),this._cachedAngularSensibility.angularSensibilityY&&(this._deviceOrientationCamera.angularSensibilityY=this._cachedAngularSensibility.angularSensibilityY,this._cachedAngularSensibility.angularSensibilityY=null),this._cachedAngularSensibility.angularSensibility&&(this._deviceOrientationCamera.angularSensibility=this._cachedAngularSensibility.angularSensibility,this._cachedAngularSensibility.angularSensibility=null)):this._existingCamera&&(this._existingCamera.position=this._position,this._scene.activeCamera=this._existingCamera,this._inputElement&&this._scene.activeCamera.attachControl(),this._cachedAngularSensibility.angularSensibilityX&&(this._existingCamera.angularSensibilityX=this._cachedAngularSensibility.angularSensibilityX,this._cachedAngularSensibility.angularSensibilityX=null),this._cachedAngularSensibility.angularSensibilityY&&(this._existingCamera.angularSensibilityY=this._cachedAngularSensibility.angularSensibilityY,this._cachedAngularSensibility.angularSensibilityY=null),this._cachedAngularSensibility.angularSensibility&&(this._existingCamera.angularSensibility=this._cachedAngularSensibility.angularSensibility,this._cachedAngularSensibility.angularSensibility=null)),this.updateButtonVisibility(),this._interactionsEnabled&&(this._scene.unregisterBeforeRender(this.beforeRender),this._cameraGazer._gazeTracker.isVisible=!1,this._leftController&&(this._leftController._gazeTracker.isVisible=!1),this._rightController&&(this._rightController._gazeTracker.isVisible=!1)),this._scene.getEngine().resize(),[this._leftController,this._rightController].forEach(function(e){e&&e._deactivatePointer()}),this._hasEnteredVR=!1;var t=this._scene.getEngine();t._onVrDisplayPresentChange&&t._onVrDisplayPresentChange()}},Object.defineProperty(r.prototype,"position",{get:function(){return this._position},set:function(t){this._position=t,this._scene.activeCamera&&(this._scene.activeCamera.position=t)},enumerable:!1,configurable:!0}),r.prototype.enableInteractions=function(){var t=this;if(!this._interactionsEnabled){if(this._interactionsRequested=!0,this.xr)return void(this.xr.baseExperience.state===pn.IN_XR&&this.xr.pointerSelection.attach());this._leftController&&this._enableInteractionOnController(this._leftController),this._rightController&&this._enableInteractionOnController(this._rightController),this.raySelectionPredicate=function(e){return e.isVisible&&(e.isPickable||e.name===t._floorMeshName)},this.meshSelectionPredicate=function(){return!0},this._raySelectionPredicate=function(e){return!!(t._isTeleportationFloor(e)||e.name.indexOf("gazeTracker")===-1&&e.name.indexOf("teleportationTarget")===-1&&e.name.indexOf("torusTeleportation")===-1)&&t.raySelectionPredicate(e)},this._interactionsEnabled=!0}},Object.defineProperty(r.prototype,"_noControllerIsActive",{get:function(){return!(this._leftController&&this._leftController._activePointer||this._rightController&&this._rightController._activePointer)},enumerable:!1,configurable:!0}),r.prototype._isTeleportationFloor=function(t){for(var e=0;e<this._floorMeshesCollection.length;e++)if(this._floorMeshesCollection[e].id===t.id)return!0;return!(!this._floorMeshName||t.name!==this._floorMeshName)},r.prototype.addFloorMesh=function(t){this._floorMeshesCollection&&(this._floorMeshesCollection.indexOf(t)>-1||this._floorMeshesCollection.push(t))},r.prototype.removeFloorMesh=function(t){if(this._floorMeshesCollection){var e=this._floorMeshesCollection.indexOf(t);e!==-1&&this._floorMeshesCollection.splice(e,1)}},r.prototype.enableTeleportation=function(t){var e=this;if(t===void 0&&(t={}),!this._teleportationInitialized){if(this._teleportationRequested=!0,this.enableInteractions(),this.webVROptions.useXR&&(t.floorMeshes||t.floorMeshName)){var n=t.floorMeshes||[];if(!n.length){var i=this._scene.getMeshByName(t.floorMeshName);i&&n.push(i)}if(this.xr)return n.forEach(function(s){e.xr.teleportation.addFloorMesh(s)}),void(this.xr.teleportation.attached||this.xr.teleportation.attach());if(!this.xrTestDone){var o=function(){e.xrTestDone&&(e._scene.unregisterBeforeRender(o),e.xr?e.xr.teleportation.attached||e.xr.teleportation.attach():e.enableTeleportation(t))};return void this._scene.registerBeforeRender(o)}}t.floorMeshName&&(this._floorMeshName=t.floorMeshName),t.floorMeshes&&(this._floorMeshesCollection=t.floorMeshes),t.teleportationMode&&(this._teleportationMode=t.teleportationMode),t.teleportationTime&&t.teleportationTime>0&&(this._teleportationTime=t.teleportationTime),t.teleportationSpeed&&t.teleportationSpeed>0&&(this._teleportationSpeed=t.teleportationSpeed),t.easingFunction!==void 0&&(this._teleportationEasing=t.easingFunction),this._leftController!=null&&this._enableTeleportationOnController(this._leftController),this._rightController!=null&&this._enableTeleportationOnController(this._rightController);var a=new yn.a;a.vignetteColor=new M.b(0,0,0,0),a.vignetteEnabled=!0,this._postProcessMove=new Go("postProcessMove",1,this._webVRCamera,void 0,void 0,void 0,void 0,a),this._webVRCamera.detachPostProcess(this._postProcessMove),this._teleportationInitialized=!0,this._isDefaultTeleportationTarget&&(this._createTeleportationCircles(),this._teleportationTarget.scaling.scaleInPlace(this._webVRCamera.deviceScaleFactor))}},r.prototype._enableInteractionOnController=function(t){var e=this;t.webVRController.mesh&&(t._interactionsEnabled=!0,this.isInVRMode&&this._displayLaserPointer&&t._activatePointer(),this.webVROptions.laserToggle&&t.webVRController.onMainButtonStateChangedObservable.add(function(n){e._displayLaserPointer&&n.value===1&&(t._activePointer?t._deactivatePointer():t._activatePointer(),e.displayGaze&&(t._gazeTracker.isVisible=t._activePointer))}),t.webVRController.onTriggerStateChangedObservable.add(function(n){var i=t;e._noControllerIsActive&&(i=e._cameraGazer),i._pointerDownOnMeshAsked?n.value<e._padSensibilityDown&&i._selectionPointerUp():n.value>e._padSensibilityUp&&i._selectionPointerDown()}))},r.prototype._checkTeleportWithRay=function(t,e){this._teleportationRequestInitiated&&!e._teleportationRequestInitiated||(e._teleportationRequestInitiated?Math.sqrt(t.y*t.y+t.x*t.x)<this._padSensibilityDown&&(this._teleportActive&&this.teleportCamera(this._haloCenter),e._teleportationRequestInitiated=!1):t.y<-this._padSensibilityUp&&e._dpadPressed&&(e._activatePointer(),e._teleportationRequestInitiated=!0))},r.prototype._checkRotate=function(t,e){e._teleportationRequestInitiated||(e._rotationLeftAsked?t.x>-this._padSensibilityDown&&(e._rotationLeftAsked=!1):t.x<-this._padSensibilityUp&&e._dpadPressed&&(e._rotationLeftAsked=!0,this._rotationAllowed&&this._rotateCamera(!1)),e._rotationRightAsked?t.x<this._padSensibilityDown&&(e._rotationRightAsked=!1):t.x>this._padSensibilityUp&&e._dpadPressed&&(e._rotationRightAsked=!0,this._rotationAllowed&&this._rotateCamera(!0)))},r.prototype._checkTeleportBackwards=function(t,e){if(!e._teleportationRequestInitiated)if(t.y>this._padSensibilityUp&&e._dpadPressed){if(!e._teleportationBackRequestInitiated){if(!this.currentVRCamera)return;var n=u.b.FromRotationMatrix(this.currentVRCamera.getWorldMatrix().getRotationMatrix()),i=this.currentVRCamera.position;this.currentVRCamera.devicePosition&&this.currentVRCamera.deviceRotationQuaternion&&(n=this.currentVRCamera.deviceRotationQuaternion,i=this.currentVRCamera.devicePosition),n.toEulerAnglesToRef(this._workingVector),this._workingVector.z=0,this._workingVector.x=0,u.b.RotationYawPitchRollToRef(this._workingVector.y,this._workingVector.x,this._workingVector.z,this._workingQuaternion),this._workingQuaternion.toRotationMatrix(this._workingMatrix),u.e.TransformCoordinatesToRef(this._teleportBackwardsVector,this._workingMatrix,this._workingVector);var o=new fn.a(i,this._workingVector),a=this._scene.pickWithRay(o,this._raySelectionPredicate);a&&a.pickedPoint&&a.pickedMesh&&this._isTeleportationFloor(a.pickedMesh)&&a.distance<5&&this.teleportCamera(a.pickedPoint),e._teleportationBackRequestInitiated=!0}}else e._teleportationBackRequestInitiated=!1},r.prototype._enableTeleportationOnController=function(t){var e=this;t.webVRController.mesh&&(t._interactionsEnabled||this._enableInteractionOnController(t),t._interactionsEnabled=!0,t._teleportationEnabled=!0,t.webVRController.controllerType===ii.VIVE&&(t._dpadPressed=!1,t.webVRController.onPadStateChangedObservable.add(function(n){t._dpadPressed=n.pressed,t._dpadPressed||(t._rotationLeftAsked=!1,t._rotationRightAsked=!1,t._teleportationBackRequestInitiated=!1)})),t.webVRController.onPadValuesChangedObservable.add(function(n){e.teleportationEnabled&&(e._checkTeleportBackwards(n,t),e._checkTeleportWithRay(n,t)),e._checkRotate(n,t)}))},r.prototype._createTeleportationCircles=function(){this._teleportationTarget=De.a.CreateGround("teleportationTarget",2,2,2,this._scene),this._teleportationTarget.isPickable=!1;var t=new Ti.a("DynamicTexture",512,this._scene,!0);t.hasAlpha=!0;var e=t.getContext();e.beginPath(),e.arc(256,256,200,0,2*Math.PI,!1),e.fillStyle=this._teleportationFillColor,e.fill(),e.lineWidth=10,e.strokeStyle=this._teleportationBorderColor,e.stroke(),e.closePath(),t.update();var n=new Ft.a("TextPlaneMaterial",this._scene);n.diffuseTexture=t,this._teleportationTarget.material=n;var i=De.a.CreateTorus("torusTeleportation",.75,.1,25,this._scene,!1);i.isPickable=!1,i.parent=this._teleportationTarget;var o=new k("animationInnerCircle","position.y",30,k.ANIMATIONTYPE_FLOAT,k.ANIMATIONLOOPMODE_CYCLE),a=[];a.push({frame:0,value:0}),a.push({frame:30,value:.4}),a.push({frame:60,value:0}),o.setKeys(a);var s=new on;s.setEasingMode(Ge.EASINGMODE_EASEINOUT),o.setEasingFunction(s),i.animations=[],i.animations.push(o),this._scene.beginAnimation(i,0,60,!0),this._hideTeleportationTarget()},r.prototype._displayTeleportationTarget=function(){this._teleportActive=!0,this._teleportationInitialized&&(this._teleportationTarget.isVisible=!0,this._isDefaultTeleportationTarget&&(this._teleportationTarget.getChildren()[0].isVisible=!0))},r.prototype._hideTeleportationTarget=function(){this._teleportActive=!1,this._teleportationInitialized&&(this._teleportationTarget.isVisible=!1,this._isDefaultTeleportationTarget&&(this._teleportationTarget.getChildren()[0].isVisible=!1))},r.prototype._rotateCamera=function(t){var e=this;if(this.currentVRCamera instanceof Yn){t?this._rotationAngle++:this._rotationAngle--,this.currentVRCamera.animations=[];var n=u.b.FromRotationMatrix(u.a.RotationY(Math.PI/4*this._rotationAngle)),i=new k("animationRotation","rotationQuaternion",90,k.ANIMATIONTYPE_QUATERNION,k.ANIMATIONLOOPMODE_CONSTANT),o=[];o.push({frame:0,value:this.currentVRCamera.rotationQuaternion}),o.push({frame:6,value:n}),i.setKeys(o),i.setEasingFunction(this._circleEase),this.currentVRCamera.animations.push(i),this._postProcessMove.animations=[];var a=new k("animationPP","vignetteWeight",90,k.ANIMATIONTYPE_FLOAT,k.ANIMATIONLOOPMODE_CONSTANT),s=[];s.push({frame:0,value:0}),s.push({frame:3,value:4}),s.push({frame:6,value:0}),a.setKeys(s),a.setEasingFunction(this._circleEase),this._postProcessMove.animations.push(a);var d=new k("animationPP2","vignetteStretch",90,k.ANIMATIONTYPE_FLOAT,k.ANIMATIONLOOPMODE_CONSTANT),p=[];p.push({frame:0,value:0}),p.push({frame:3,value:10}),p.push({frame:6,value:0}),d.setKeys(p),d.setEasingFunction(this._circleEase),this._postProcessMove.animations.push(d),this._postProcessMove.imageProcessingConfiguration.vignetteWeight=0,this._postProcessMove.imageProcessingConfiguration.vignetteStretch=0,this._postProcessMove.samples=4,this._webVRCamera.attachPostProcess(this._postProcessMove),this._scene.beginAnimation(this._postProcessMove,0,6,!1,1,function(){e._webVRCamera.detachPostProcess(e._postProcessMove)}),this._scene.beginAnimation(this.currentVRCamera,0,6,!1,1)}},r.prototype._moveTeleportationSelectorTo=function(t,e,n){if(t.pickedPoint){e._teleportationRequestInitiated&&(this._displayTeleportationTarget(),this._haloCenter.copyFrom(t.pickedPoint),this._teleportationTarget.position.copyFrom(t.pickedPoint));var i=this._convertNormalToDirectionOfRay(t.getNormal(!0,!1),n);if(i){var o=u.e.Cross(ye.a.Y,i),a=u.e.Cross(i,o);u.e.RotationFromAxisToRef(a,i,o,this._teleportationTarget.rotation)}this._teleportationTarget.position.y+=.1}},r.prototype.teleportCamera=function(t){var e=this;if(this.currentVRCamera instanceof Yn){this.webVRCamera.leftCamera?(this._workingVector.copyFrom(this.webVRCamera.leftCamera.globalPosition),this._workingVector.subtractInPlace(this.webVRCamera.position),t.subtractToRef(this._workingVector,this._workingVector)):this._workingVector.copyFrom(t),this.isInVRMode?this._workingVector.y+=this.webVRCamera.deviceDistanceToRoomGround()*this._webVRCamera.deviceScaleFactor:this._workingVector.y+=this._defaultHeight,this.onBeforeCameraTeleport.notifyObservers(this._workingVector);var n,i;if(this._teleportationMode==r.TELEPORTATIONMODE_CONSTANTSPEED){i=90;var o=u.e.Distance(this.currentVRCamera.position,this._workingVector);n=this._teleportationSpeed/o}else i=Math.round(90*this._teleportationTime/1e3),n=1;this.currentVRCamera.animations=[];var a=new k("animationCameraTeleportation","position",90,k.ANIMATIONTYPE_VECTOR3,k.ANIMATIONLOOPMODE_CONSTANT),s=[{frame:0,value:this.currentVRCamera.position},{frame:i,value:this._workingVector}];a.setKeys(s),a.setEasingFunction(this._teleportationEasing),this.currentVRCamera.animations.push(a),this._postProcessMove.animations=[];var d=Math.round(i/2),p=new k("animationPP","vignetteWeight",90,k.ANIMATIONTYPE_FLOAT,k.ANIMATIONLOOPMODE_CONSTANT),b=[];b.push({frame:0,value:0}),b.push({frame:d,value:8}),b.push({frame:i,value:0}),p.setKeys(b),this._postProcessMove.animations.push(p);var P=new k("animationPP2","vignetteStretch",90,k.ANIMATIONTYPE_FLOAT,k.ANIMATIONLOOPMODE_CONSTANT),O=[];O.push({frame:0,value:0}),O.push({frame:d,value:10}),O.push({frame:i,value:0}),P.setKeys(O),this._postProcessMove.animations.push(P),this._postProcessMove.imageProcessingConfiguration.vignetteWeight=0,this._postProcessMove.imageProcessingConfiguration.vignetteStretch=0,this._webVRCamera.attachPostProcess(this._postProcessMove),this._scene.beginAnimation(this._postProcessMove,0,i,!1,n,function(){e._webVRCamera.detachPostProcess(e._postProcessMove)}),this._scene.beginAnimation(this.currentVRCamera,0,i,!1,n,function(){e.onAfterCameraTeleport.notifyObservers(e._workingVector)}),this._hideTeleportationTarget()}},r.prototype._convertNormalToDirectionOfRay=function(t,e){return t&&Math.acos(u.e.Dot(t,e.direction))<Math.PI/2&&t.scaleInPlace(-1),t},r.prototype._castRayAndSelectObject=function(t){if(this.currentVRCamera instanceof Yn){var e=t._getForwardRay(this._rayLength),n=this._scene.pickWithRay(e,this._raySelectionPredicate);if(n&&(t._laserPointer&&(n.originMesh=t._laserPointer.parent),this._scene.simulatePointerMove(n,{pointerId:t._id})),t._currentHit=n,n&&n.pickedPoint){if(this._displayGaze){var i=1;t._gazeTracker.isVisible=!0,t._isActionableMesh&&(i=3),this.updateGazeTrackerScale&&(t._gazeTracker.scaling.x=n.distance*i,t._gazeTracker.scaling.y=n.distance*i,t._gazeTracker.scaling.z=n.distance*i);var o=this._convertNormalToDirectionOfRay(n.getNormal(),e);if(o){var a=u.e.Cross(ye.a.Y,o),s=u.e.Cross(o,a);u.e.RotationFromAxisToRef(s,o,a,t._gazeTracker.rotation)}t._gazeTracker.position.copyFrom(n.pickedPoint),t._gazeTracker.position.x<0?t._gazeTracker.position.x+=.002:t._gazeTracker.position.x-=.002,t._gazeTracker.position.y<0?t._gazeTracker.position.y+=.002:t._gazeTracker.position.y-=.002,t._gazeTracker.position.z<0?t._gazeTracker.position.z+=.002:t._gazeTracker.position.z-=.002}t._updatePointerDistance(n.distance)}else t._updatePointerDistance(),t._gazeTracker.isVisible=!1;if(n&&n.pickedMesh){if(this._teleportationInitialized&&this._isTeleportationFloor(n.pickedMesh)&&n.pickedPoint)return t._currentMeshSelected&&!this._isTeleportationFloor(t._currentMeshSelected)&&this._notifySelectedMeshUnselected(t._currentMeshSelected),t._currentMeshSelected=null,void(t._teleportationRequestInitiated&&this._moveTeleportationSelectorTo(n,t,e));if(n.pickedMesh!==t._currentMeshSelected)if(this.meshSelectionPredicate(n.pickedMesh)){this.onNewMeshPicked.notifyObservers(n),t._currentMeshSelected=n.pickedMesh,n.pickedMesh.isPickable&&n.pickedMesh.actionManager?(this.changeGazeColor(this._pickedGazeColor),this.changeLaserColor(this._pickedLaserColor),t._isActionableMesh=!0):(this.changeGazeColor(this._gazeColor),this.changeLaserColor(this._laserColor),t._isActionableMesh=!1);try{this.onNewMeshSelected.notifyObservers(n.pickedMesh);var d=t;d.webVRController&&this.onMeshSelectedWithController.notifyObservers({mesh:n.pickedMesh,controller:d.webVRController})}catch(p){l.a.Warn("Error while raising onNewMeshSelected or onMeshSelectedWithController: "+p)}}else this._notifySelectedMeshUnselected(t._currentMeshSelected),t._currentMeshSelected=null,this.changeGazeColor(this._gazeColor),this.changeLaserColor(this._laserColor)}else this._notifySelectedMeshUnselected(t._currentMeshSelected),t._currentMeshSelected=null,this.changeGazeColor(this._gazeColor),this.changeLaserColor(this._laserColor)}},r.prototype._notifySelectedMeshUnselected=function(t){t&&this.onSelectedMeshUnselected.notifyObservers(t)},r.prototype.setLaserColor=function(t,e){e===void 0&&(e=this._pickedLaserColor),this._laserColor=t,this._pickedLaserColor=e},r.prototype.setLaserLightingState=function(t){t===void 0&&(t=!0),this._leftController&&this._leftController._setLaserPointerLightingDisabled(!t),this._rightController&&this._rightController._setLaserPointerLightingDisabled(!t)},r.prototype.setGazeColor=function(t,e){e===void 0&&(e=this._pickedGazeColor),this._gazeColor=t,this._pickedGazeColor=e},r.prototype.changeLaserColor=function(t){this.updateControllerLaserColor&&(this._leftController&&this._leftController._setLaserPointerColor(t),this._rightController&&this._rightController._setLaserPointerColor(t))},r.prototype.changeGazeColor=function(t){this.updateGazeTrackerColor&&this._cameraGazer._gazeTracker.material&&(this._cameraGazer._gazeTracker.material.emissiveColor=t,this._leftController&&(this._leftController._gazeTracker.material.emissiveColor=t),this._rightController&&(this._rightController._gazeTracker.material.emissiveColor=t))},r.prototype.dispose=function(){this.isInVRMode&&this.exitVR(),this._postProcessMove&&this._postProcessMove.dispose(),this._webVRCamera&&this._webVRCamera.dispose(),this._vrDeviceOrientationCamera&&this._vrDeviceOrientationCamera.dispose(),!this._useCustomVRButton&&this._btnVR&&this._btnVR.parentNode&&document.body.removeChild(this._btnVR),this._deviceOrientationCamera&&this._scene.activeCamera!=this._deviceOrientationCamera&&this._deviceOrientationCamera.dispose(),this._cameraGazer&&this._cameraGazer.dispose(),this._leftController&&this._leftController.dispose(),this._rightController&&this._rightController.dispose(),this._teleportationTarget&&this._teleportationTarget.dispose(),this.xr&&this.xr.dispose(),this._floorMeshesCollection=[],document.removeEventListener("keydown",this._onKeyDown),window.removeEventListener("vrdisplaypresentchange",this._onVrDisplayPresentChange),window.removeEventListener("resize",this._onResize),document.removeEventListener("fullscreenchange",this._onFullscreenChange),document.removeEventListener("mozfullscreenchange",this._onFullscreenChange),document.removeEventListener("webkitfullscreenchange",this._onFullscreenChange),document.removeEventListener("msfullscreenchange",this._onFullscreenChange),document.onmsfullscreenchange=null,this._scene.getEngine().onVRDisplayChangedObservable.removeCallback(this._onVRDisplayChanged),this._scene.getEngine().onVRRequestPresentStart.removeCallback(this._onVRRequestPresentStart),this._scene.getEngine().onVRRequestPresentComplete.removeCallback(this._onVRRequestPresentComplete),window.removeEventListener("vrdisplaypresentchange",this._onVrDisplayPresentChange),this._scene.gamepadManager.onGamepadConnectedObservable.removeCallback(this._onNewGamepadConnected),this._scene.gamepadManager.onGamepadDisconnectedObservable.removeCallback(this._onNewGamepadDisconnected),this._scene.unregisterBeforeRender(this.beforeRender)},r.prototype.getClassName=function(){return"VRExperienceHelper"},r.TELEPORTATIONMODE_CONSTANTTIME=0,r.TELEPORTATIONMODE_CONSTANTSPEED=1,r}(),vr=f(64),br=(ri={root:0,found:!1},function(r,t,e,n){ri.root=0,ri.found=!1;var i=t*t-4*r*e;if(i<0)return ri;var o=Math.sqrt(i),a=(-t-o)/(2*r),s=(-t+o)/(2*r);if(a>s){var d=s;s=a,a=d}return a>0&&a<n?(ri.root=a,ri.found=!0,ri):(s>0&&s<n&&(ri.root=s,ri.found=!0),ri)}),Zl=function(){function r(){this._collisionPoint=u.e.Zero(),this._planeIntersectionPoint=u.e.Zero(),this._tempVector=u.e.Zero(),this._tempVector2=u.e.Zero(),this._tempVector3=u.e.Zero(),this._tempVector4=u.e.Zero(),this._edge=u.e.Zero(),this._baseToVertex=u.e.Zero(),this._destinationPoint=u.e.Zero(),this._slidePlaneNormal=u.e.Zero(),this._displacementVector=u.e.Zero(),this._radius=u.e.One(),this._retry=0,this._basePointWorld=u.e.Zero(),this._velocityWorld=u.e.Zero(),this._normalizedVelocity=u.e.Zero(),this._collisionMask=-1}return Object.defineProperty(r.prototype,"collisionMask",{get:function(){return this._collisionMask},set:function(t){this._collisionMask=isNaN(t)?-1:t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"slidePlaneNormal",{get:function(){return this._slidePlaneNormal},enumerable:!1,configurable:!0}),r.prototype._initialize=function(t,e,n){this._velocity=e,u.e.NormalizeToRef(e,this._normalizedVelocity),this._basePoint=t,t.multiplyToRef(this._radius,this._basePointWorld),e.multiplyToRef(this._radius,this._velocityWorld),this._velocityWorldLength=this._velocityWorld.length(),this._epsilon=n,this.collisionFound=!1},r.prototype._checkPointInTriangle=function(t,e,n,i,o){e.subtractToRef(t,this._tempVector),n.subtractToRef(t,this._tempVector2),u.e.CrossToRef(this._tempVector,this._tempVector2,this._tempVector4);var a=u.e.Dot(this._tempVector4,o);return!(a<0)&&(i.subtractToRef(t,this._tempVector3),u.e.CrossToRef(this._tempVector2,this._tempVector3,this._tempVector4),!((a=u.e.Dot(this._tempVector4,o))<0)&&(u.e.CrossToRef(this._tempVector3,this._tempVector,this._tempVector4),(a=u.e.Dot(this._tempVector4,o))>=0))},r.prototype._canDoCollision=function(t,e,n,i){var o=u.e.Distance(this._basePointWorld,t),a=Math.max(this._radius.x,this._radius.y,this._radius.z);return!(o>this._velocityWorldLength+a+e)&&!!function(s,d,p,b){return!(s.x>p.x+b)&&!(p.x-b>d.x)&&!(s.y>p.y+b)&&!(p.y-b>d.y)&&!(s.z>p.z+b)&&!(p.z-b>d.z)}(n,i,this._basePointWorld,this._velocityWorldLength+a)},r.prototype._testTriangle=function(t,e,n,i,o,a,s){var d,p=!1;e||(e=[]),e[t]||(e[t]=new vr.a(0,0,0,0),e[t].copyFromPoints(n,i,o));var b=e[t];if(a||b.isFrontFacingTo(this._normalizedVelocity,0)){var P=b.signedDistanceTo(this._basePoint),O=u.e.Dot(b.normal,this._velocity);if(O==0){if(Math.abs(P)>=1)return;p=!0,d=0}else{var B=(1-P)/O;if((d=(-1-P)/O)>B){var F=B;B=d,d=F}if(d>1||B<0)return;d<0&&(d=0),d>1&&(d=1)}this._collisionPoint.copyFromFloats(0,0,0);var z=!1,J=1;if(p||(this._basePoint.subtractToRef(b.normal,this._planeIntersectionPoint),this._velocity.scaleToRef(d,this._tempVector),this._planeIntersectionPoint.addInPlace(this._tempVector),this._checkPointInTriangle(this._planeIntersectionPoint,n,i,o,b.normal)&&(z=!0,J=d,this._collisionPoint.copyFrom(this._planeIntersectionPoint))),!z){var ie=this._velocity.lengthSquared(),se=ie;this._basePoint.subtractToRef(n,this._tempVector);var ce=2*u.e.Dot(this._velocity,this._tempVector),ue=this._tempVector.lengthSquared()-1,fe=br(se,ce,ue,J);fe.found&&(J=fe.root,z=!0,this._collisionPoint.copyFrom(n)),this._basePoint.subtractToRef(i,this._tempVector),ce=2*u.e.Dot(this._velocity,this._tempVector),ue=this._tempVector.lengthSquared()-1,(fe=br(se,ce,ue,J)).found&&(J=fe.root,z=!0,this._collisionPoint.copyFrom(i)),this._basePoint.subtractToRef(o,this._tempVector),ce=2*u.e.Dot(this._velocity,this._tempVector),ue=this._tempVector.lengthSquared()-1,(fe=br(se,ce,ue,J)).found&&(J=fe.root,z=!0,this._collisionPoint.copyFrom(o)),i.subtractToRef(n,this._edge),n.subtractToRef(this._basePoint,this._baseToVertex);var ve=this._edge.lengthSquared(),Te=u.e.Dot(this._edge,this._velocity),Re=u.e.Dot(this._edge,this._baseToVertex);if(se=ve*-ie+Te*Te,ce=ve*(2*u.e.Dot(this._velocity,this._baseToVertex))-2*Te*Re,ue=ve*(1-this._baseToVertex.lengthSquared())+Re*Re,(fe=br(se,ce,ue,J)).found){var Ae=(Te*fe.root-Re)/ve;Ae>=0&&Ae<=1&&(J=fe.root,z=!0,this._edge.scaleInPlace(Ae),n.addToRef(this._edge,this._collisionPoint))}o.subtractToRef(i,this._edge),i.subtractToRef(this._basePoint,this._baseToVertex),ve=this._edge.lengthSquared(),Te=u.e.Dot(this._edge,this._velocity),Re=u.e.Dot(this._edge,this._baseToVertex),se=ve*-ie+Te*Te,ce=ve*(2*u.e.Dot(this._velocity,this._baseToVertex))-2*Te*Re,ue=ve*(1-this._baseToVertex.lengthSquared())+Re*Re,(fe=br(se,ce,ue,J)).found&&(Ae=(Te*fe.root-Re)/ve)>=0&&Ae<=1&&(J=fe.root,z=!0,this._edge.scaleInPlace(Ae),i.addToRef(this._edge,this._collisionPoint)),n.subtractToRef(o,this._edge),o.subtractToRef(this._basePoint,this._baseToVertex),ve=this._edge.lengthSquared(),Te=u.e.Dot(this._edge,this._velocity),Re=u.e.Dot(this._edge,this._baseToVertex),se=ve*-ie+Te*Te,ce=ve*(2*u.e.Dot(this._velocity,this._baseToVertex))-2*Te*Re,ue=ve*(1-this._baseToVertex.lengthSquared())+Re*Re,(fe=br(se,ce,ue,J)).found&&(Ae=(Te*fe.root-Re)/ve)>=0&&Ae<=1&&(J=fe.root,z=!0,this._edge.scaleInPlace(Ae),o.addToRef(this._edge,this._collisionPoint))}if(z){var Ee=J*this._velocity.length();(!this.collisionFound||Ee<this._nearestDistance)&&(s.collisionResponse&&(this.intersectionPoint?this.intersectionPoint.copyFrom(this._collisionPoint):this.intersectionPoint=this._collisionPoint.clone(),this._nearestDistance=Ee,this.collisionFound=!0),this.collidedMesh=s)}}},r.prototype._collide=function(t,e,n,i,o,a,s,d){if(n&&n.length!==0)for(p=i;p<o;p+=3)b=e[n[p]-a],P=e[n[p+1]-a],O=e[n[p+2]-a],this._testTriangle(p,t,O,P,b,s,d);else for(var p=0;p<e.length;p+=3){var b=e[p],P=e[p+1],O=e[p+2];this._testTriangle(p,t,O,P,b,s,d)}},r.prototype._getResponse=function(t,e){t.addToRef(e,this._destinationPoint),e.scaleInPlace(this._nearestDistance/e.length()),this._basePoint.addToRef(e,t),t.subtractToRef(this.intersectionPoint,this._slidePlaneNormal),this._slidePlaneNormal.normalize(),this._slidePlaneNormal.scaleToRef(this._epsilon,this._displacementVector),t.addInPlace(this._displacementVector),this.intersectionPoint.addInPlace(this._displacementVector),this._slidePlaneNormal.scaleInPlace(vr.a.SignedDistanceToPlaneFromPositionAndNormal(this.intersectionPoint,this._slidePlaneNormal,this._destinationPoint)),this._destinationPoint.subtractInPlace(this._slidePlaneNormal),this._destinationPoint.subtractToRef(this.intersectionPoint,e)},r}(),Jl=function(){function r(){this._scaledPosition=u.e.Zero(),this._scaledVelocity=u.e.Zero(),this._finalPosition=u.e.Zero()}return r.prototype.getNewPosition=function(t,e,n,i,o,a,s){t.divideToRef(n._radius,this._scaledPosition),e.divideToRef(n._radius,this._scaledVelocity),n.collidedMesh=null,n._retry=0,n._initialVelocity=this._scaledVelocity,n._initialPosition=this._scaledPosition,this._collideWithWorld(this._scaledPosition,this._scaledVelocity,n,i,this._finalPosition,o),this._finalPosition.multiplyInPlace(n._radius),a(s,this._finalPosition,n.collidedMesh)},r.prototype.createCollider=function(){return new Zl},r.prototype.init=function(t){this._scene=t},r.prototype._collideWithWorld=function(t,e,n,i,o,a){a===void 0&&(a=null);var s=10*Ue.a.CollisionsEpsilon;if(n._retry>=i)o.copyFrom(t);else{var d=a?a.collisionMask:n.collisionMask;n._initialize(t,e,s);for(var p=a&&a.surroundingMeshes||this._scene.meshes,b=0;b<p.length;b++){var P=p[b];P.isEnabled()&&P.checkCollisions&&P.subMeshes&&P!==a&&d&P.collisionGroup&&P._checkCollision(n)}n.collisionFound?(e.x===0&&e.y===0&&e.z===0||n._getResponse(t,e),e.length()<=s?o.copyFrom(t):(n._retry++,this._collideWithWorld(t,e,n,i,o,a))):t.addToRef(e,o)}},r}();_e.a.CollisionCoordinatorFactory=function(){return new Jl};var nr=f(54),Zf=f(114),Jf=f(147),vs=f(103),Vi=f(43),$l=f(113),eu=function(){function r(t,e,n,i,o,a){this.entries=new Array,this._boundingVectors=new Array,this._capacity=n,this._depth=i,this._maxDepth=o,this._creationFunc=a,this._minPoint=t,this._maxPoint=e,this._boundingVectors.push(t.clone()),this._boundingVectors.push(e.clone()),this._boundingVectors.push(t.clone()),this._boundingVectors[2].x=e.x,this._boundingVectors.push(t.clone()),this._boundingVectors[3].y=e.y,this._boundingVectors.push(t.clone()),this._boundingVectors[4].z=e.z,this._boundingVectors.push(e.clone()),this._boundingVectors[5].z=t.z,this._boundingVectors.push(e.clone()),this._boundingVectors[6].x=t.x,this._boundingVectors.push(e.clone()),this._boundingVectors[7].y=t.y}return Object.defineProperty(r.prototype,"capacity",{get:function(){return this._capacity},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"minPoint",{get:function(){return this._minPoint},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"maxPoint",{get:function(){return this._maxPoint},enumerable:!1,configurable:!0}),r.prototype.addEntry=function(t){if(this.blocks)for(var e=0;e<this.blocks.length;e++)this.blocks[e].addEntry(t);else this._creationFunc(t,this),this.entries.length>this.capacity&&this._depth<this._maxDepth&&this.createInnerBlocks()},r.prototype.removeEntry=function(t){if(this.blocks)for(var e=0;e<this.blocks.length;e++)this.blocks[e].removeEntry(t);else{var n=this.entries.indexOf(t);n>-1&&this.entries.splice(n,1)}},r.prototype.addEntries=function(t){for(var e=0;e<t.length;e++){var n=t[e];this.addEntry(n)}},r.prototype.select=function(t,e,n){if(vs.a.IsInFrustum(this._boundingVectors,t)){if(this.blocks){for(var i=0;i<this.blocks.length;i++)this.blocks[i].select(t,e,n);return}n?e.concat(this.entries):e.concatWithNoDuplicate(this.entries)}},r.prototype.intersects=function(t,e,n,i){if(vs.a.IntersectsSphere(this._minPoint,this._maxPoint,t,e)){if(this.blocks){for(var o=0;o<this.blocks.length;o++)this.blocks[o].intersects(t,e,n,i);return}i?n.concat(this.entries):n.concatWithNoDuplicate(this.entries)}},r.prototype.intersectsRay=function(t,e){if(t.intersectsBoxMinMax(this._minPoint,this._maxPoint)){if(this.blocks){for(var n=0;n<this.blocks.length;n++)this.blocks[n].intersectsRay(t,e);return}e.concatWithNoDuplicate(this.entries)}},r.prototype.createInnerBlocks=function(){r._CreateBlocks(this._minPoint,this._maxPoint,this.entries,this._capacity,this._depth,this._maxDepth,this,this._creationFunc)},r._CreateBlocks=function(t,e,n,i,o,a,s,d){s.blocks=new Array;for(var p=new u.e((e.x-t.x)/2,(e.y-t.y)/2,(e.z-t.z)/2),b=0;b<2;b++)for(var P=0;P<2;P++)for(var O=0;O<2;O++){var B=new r(t.add(p.multiplyByFloats(b,P,O)),t.add(p.multiplyByFloats(b+1,P+1,O+1)),i,o+1,a,d);B.addEntries(n),s.blocks.push(B)}},r}(),no=function(){function r(t,e,n){n===void 0&&(n=2),this.maxDepth=n,this.dynamicContent=new Array,this._maxBlockCapacity=e||64,this._selectionContent=new fi.b(1024),this._creationFunc=t}return r.prototype.update=function(t,e,n){eu._CreateBlocks(t,e,n,this._maxBlockCapacity,0,this.maxDepth,this,this._creationFunc)},r.prototype.addMesh=function(t){for(var e=0;e<this.blocks.length;e++)this.blocks[e].addEntry(t)},r.prototype.removeMesh=function(t){for(var e=0;e<this.blocks.length;e++)this.blocks[e].removeEntry(t)},r.prototype.select=function(t,e){this._selectionContent.reset();for(var n=0;n<this.blocks.length;n++)this.blocks[n].select(t,this._selectionContent,e);return e?this._selectionContent.concat(this.dynamicContent):this._selectionContent.concatWithNoDuplicate(this.dynamicContent),this._selectionContent},r.prototype.intersects=function(t,e,n){this._selectionContent.reset();for(var i=0;i<this.blocks.length;i++)this.blocks[i].intersects(t,e,this._selectionContent,n);return n?this._selectionContent.concat(this.dynamicContent):this._selectionContent.concatWithNoDuplicate(this.dynamicContent),this._selectionContent},r.prototype.intersectsRay=function(t){this._selectionContent.reset();for(var e=0;e<this.blocks.length;e++)this.blocks[e].intersectsRay(t,this._selectionContent);return this._selectionContent.concatWithNoDuplicate(this.dynamicContent),this._selectionContent},r.CreationFuncForMeshes=function(t,e){var n=t.getBoundingInfo();!t.isBlocked&&n.boundingBox.intersectsMinMax(e.minPoint,e.maxPoint)&&e.entries.push(t)},r.CreationFuncForSubMeshes=function(t,e){t.getBoundingInfo().boundingBox.intersectsMinMax(e.minPoint,e.maxPoint)&&e.entries.push(t)},r}();_e.a.prototype.createOrUpdateSelectionOctree=function(r,t){r===void 0&&(r=64),t===void 0&&(t=2);var e=this._getComponent(at.a.NAME_OCTREE);e||(e=new Ss(this),this._addComponent(e)),this._selectionOctree||(this._selectionOctree=new no(no.CreationFuncForMeshes,r,t));var n=this.getWorldExtends();return this._selectionOctree.update(n.min,n.max,this.meshes),this._selectionOctree},Object.defineProperty(_e.a.prototype,"selectionOctree",{get:function(){return this._selectionOctree},enumerable:!0,configurable:!0}),Dt.a.prototype.createOrUpdateSubmeshesOctree=function(r,t){r===void 0&&(r=64),t===void 0&&(t=2);var e=this.getScene(),n=e._getComponent(at.a.NAME_OCTREE);n||(n=new Ss(e),e._addComponent(n)),this._submeshesOctree||(this._submeshesOctree=new no(no.CreationFuncForSubMeshes,r,t)),this.computeWorldMatrix(!0);var i=this.getBoundingInfo().boundingBox;return this._submeshesOctree.update(i.minimumWorld,i.maximumWorld,this.subMeshes),this._submeshesOctree};var Kt,bs,ys,Ts,Es,Ss=function(){function r(t){this.name=at.a.NAME_OCTREE,this.checksIsEnabled=!0,this._tempRay=new fn.a(u.e.Zero(),new u.e(1,1,1)),this.scene=t,this.scene.getActiveMeshCandidates=this.getActiveMeshCandidates.bind(this),this.scene.getActiveSubMeshCandidates=this.getActiveSubMeshCandidates.bind(this),this.scene.getCollidingSubMeshCandidates=this.getCollidingSubMeshCandidates.bind(this),this.scene.getIntersectingSubMeshCandidates=this.getIntersectingSubMeshCandidates.bind(this)}return r.prototype.register=function(){var t=this;this.scene.onMeshRemovedObservable.add(function(e){var n=t.scene.selectionOctree;if(n!=null){var i=n.dynamicContent.indexOf(e);i!==-1&&n.dynamicContent.splice(i,1)}}),this.scene.onMeshImportedObservable.add(function(e){var n=t.scene.selectionOctree;n?.addMesh(e)})},r.prototype.getActiveMeshCandidates=function(){return this.scene._selectionOctree?this.scene._selectionOctree.select(this.scene.frustumPlanes):this.scene._getDefaultMeshCandidates()},r.prototype.getActiveSubMeshCandidates=function(t){return t._submeshesOctree&&t.useOctreeForRenderingSelection?t._submeshesOctree.select(this.scene.frustumPlanes):this.scene._getDefaultSubMeshCandidates(t)},r.prototype.getIntersectingSubMeshCandidates=function(t,e){return t._submeshesOctree&&t.useOctreeForPicking?(fn.a.TransformToRef(e,t.getWorldMatrix(),this._tempRay),t._submeshesOctree.intersectsRay(this._tempRay)):this.scene._getDefaultSubMeshCandidates(t)},r.prototype.getCollidingSubMeshCandidates=function(t,e){if(t._submeshesOctree&&t.useOctreeForCollisions){var n=e._velocityWorldLength+Math.max(e._radius.x,e._radius.y,e._radius.z);return t._submeshesOctree.intersects(e._basePointWorld,n)}return this.scene._getDefaultSubMeshCandidates(t)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){},r}(),ir=f(99);(function(r){r[r.Generic=0]="Generic",r[r.Keyboard=1]="Keyboard",r[r.Mouse=2]="Mouse",r[r.Touch=3]="Touch",r[r.DualShock=4]="DualShock",r[r.Xbox=5]="Xbox",r[r.Switch=6]="Switch"})(Kt||(Kt={})),function(r){r[r.Horizontal=0]="Horizontal",r[r.Vertical=1]="Vertical",r[r.LeftClick=2]="LeftClick",r[r.MiddleClick=3]="MiddleClick",r[r.RightClick=4]="RightClick",r[r.BrowserBack=5]="BrowserBack",r[r.BrowserForward=6]="BrowserForward"}(bs||(bs={})),function(r){r[r.Cross=0]="Cross",r[r.Circle=1]="Circle",r[r.Square=2]="Square",r[r.Triangle=3]="Triangle",r[r.L1=4]="L1",r[r.R1=5]="R1",r[r.L2=6]="L2",r[r.R2=7]="R2",r[r.Share=8]="Share",r[r.Options=9]="Options",r[r.L3=10]="L3",r[r.R3=11]="R3",r[r.DPadUp=12]="DPadUp",r[r.DPadDown=13]="DPadDown",r[r.DPadLeft=14]="DPadLeft",r[r.DPadRight=15]="DPadRight",r[r.Home=16]="Home",r[r.TouchPad=17]="TouchPad",r[r.LStickXAxis=18]="LStickXAxis",r[r.LStickYAxis=19]="LStickYAxis",r[r.RStickXAxis=20]="RStickXAxis",r[r.RStickYAxis=21]="RStickYAxis"}(ys||(ys={})),function(r){r[r.A=0]="A",r[r.B=1]="B",r[r.X=2]="X",r[r.Y=3]="Y",r[r.LB=4]="LB",r[r.RB=5]="RB",r[r.LT=6]="LT",r[r.RT=7]="RT",r[r.Back=8]="Back",r[r.Start=9]="Start",r[r.LS=10]="LS",r[r.RS=11]="RS",r[r.DPadUp=12]="DPadUp",r[r.DPadDown=13]="DPadDown",r[r.DPadLeft=14]="DPadLeft",r[r.DPadRight=15]="DPadRight",r[r.Home=16]="Home",r[r.LStickXAxis=17]="LStickXAxis",r[r.LStickYAxis=18]="LStickYAxis",r[r.RStickXAxis=19]="RStickXAxis",r[r.RStickYAxis=20]="RStickYAxis"}(Ts||(Ts={})),function(r){r[r.B=0]="B",r[r.A=1]="A",r[r.Y=2]="Y",r[r.X=3]="X",r[r.L=4]="L",r[r.R=5]="R",r[r.ZL=6]="ZL",r[r.ZR=7]="ZR",r[r.Minus=8]="Minus",r[r.Plus=9]="Plus",r[r.LS=10]="LS",r[r.RS=11]="RS",r[r.DPadUp=12]="DPadUp",r[r.DPadDown=13]="DPadDown",r[r.DPadLeft=14]="DPadLeft",r[r.DPadRight=15]="DPadRight",r[r.Home=16]="Home",r[r.Capture=17]="Capture",r[r.LStickXAxis=18]="LStickXAxis",r[r.LStickYAxis=19]="LStickYAxis",r[r.RStickXAxis=20]="RStickXAxis",r[r.RStickYAxis=21]="RStickYAxis"}(Es||(Es={}));var tu=function(){function r(t){this.onDeviceDisconnected=function(){},this._inputs=[],this._keyboardActive=!1,this._pointerActive=!1,this._keyboardDownEvent=function(n){},this._keyboardUpEvent=function(n){},this._pointerMoveEvent=function(n){},this._pointerDownEvent=function(n){},this._pointerUpEvent=function(n){},this._gamepadConnectedEvent=function(n){},this._gamepadDisconnectedEvent=function(n){},this._onDeviceConnected=function(){};var e=t.getInputElement();e&&(this._elementToAttachTo=e,this._handleKeyActions(),this._handlePointerActions(),this._handleGamepadActions(),this._checkForConnectedDevices())}return Object.defineProperty(r.prototype,"onDeviceConnected",{get:function(){return this._onDeviceConnected},set:function(t){this._onDeviceConnected=t;for(var e=0;e<this._inputs.length;e++)if(this._inputs[e])for(var n=0;n<this._inputs[e].length;n++)this._inputs[e][n]&&this._onDeviceConnected(e,n)},enumerable:!1,configurable:!0}),r.Create=function(t){return typeof _native<"u"&&_native.DeviceInputSystem?new _native.DeviceInputSystem(t):new r(t)},r.prototype.pollInput=function(t,e,n){var i=this._inputs[t][e];if(!i)throw"Unable to find device "+Kt[t];if(this._updateDevice(t,e,n),i[n]===void 0)throw"Unable to find input "+n+" for device "+Kt[t]+" in slot "+e;return i[n]},r.prototype.dispose=function(){this._keyboardActive&&(window.removeEventListener("keydown",this._keyboardDownEvent),window.removeEventListener("keyup",this._keyboardUpEvent)),this._pointerActive&&(this._elementToAttachTo.removeEventListener("pointermove",this._pointerMoveEvent),this._elementToAttachTo.removeEventListener("pointerdown",this._pointerDownEvent),this._elementToAttachTo.removeEventListener("pointerup",this._pointerUpEvent)),window.removeEventListener("gamepadconnected",this._gamepadConnectedEvent),window.removeEventListener("gamepaddisconnected",this._gamepadDisconnectedEvent)},r.prototype._checkForConnectedDevices=function(){for(var t=0,e=navigator.getGamepads();t<e.length;t++){var n=e[t];n&&this._addGamePad(n)}matchMedia("(pointer:fine)").matches&&this._addPointerDevice(Kt.Mouse,0,0,0)},r.prototype._addGamePad=function(t){var e=this._getGamepadDeviceType(t.id),n=t.index;this._registerDevice(e,n,t.buttons.length+t.axes.length),this._gamepads=this._gamepads||new Array(t.index+1),this._gamepads[n]=e},r.prototype._addPointerDevice=function(t,e,n,i){this._pointerActive=!0,this._registerDevice(t,e,r._MAX_POINTER_INPUTS);var o=this._inputs[t][e];o[0]=n,o[1]=i},r.prototype._registerDevice=function(t,e,n){if(this._inputs[t]||(this._inputs[t]=[]),!this._inputs[t][e]){for(var i=new Array(n),o=0;o<n;o++)i[o]=0;this._inputs[t][e]=i,this.onDeviceConnected(t,e)}},r.prototype._unregisterDevice=function(t,e){this._inputs[t][e]&&(delete this._inputs[t][e],this.onDeviceDisconnected(t,e))},r.prototype._handleKeyActions=function(){var t=this;this._keyboardDownEvent=function(e){t._keyboardActive||(t._keyboardActive=!0,t._registerDevice(Kt.Keyboard,0,r._MAX_KEYCODES));var n=t._inputs[Kt.Keyboard][0];n&&(t.onInputChanged&&t.onInputChanged(Kt.Keyboard,0,e.keyCode,n[e.keyCode],1),n[e.keyCode]=1)},this._keyboardUpEvent=function(e){var n=t._inputs[Kt.Keyboard][0];n&&(t.onInputChanged&&t.onInputChanged(Kt.Keyboard,0,e.keyCode,n[e.keyCode],0),n[e.keyCode]=0)},window.addEventListener("keydown",this._keyboardDownEvent),window.addEventListener("keyup",this._keyboardUpEvent)},r.prototype._handlePointerActions=function(){var t=this;this._pointerMoveEvent=function(e){var n=e.pointerType=="mouse"?Kt.Mouse:Kt.Touch,i=e.pointerType=="mouse"?0:e.pointerId;t._inputs[n]||(t._inputs[n]=[]),t._inputs[n][i]||t._addPointerDevice(n,i,e.clientX,e.clientY);var o=t._inputs[n][i];o&&(t.onInputChanged&&(t.onInputChanged(n,i,0,o[0],e.clientX),t.onInputChanged(n,i,1,o[1],e.clientY)),o[0]=e.clientX,o[1]=e.clientY)},this._pointerDownEvent=function(e){var n=e.pointerType=="mouse"?Kt.Mouse:Kt.Touch,i=e.pointerType=="mouse"?0:e.pointerId;t._inputs[n]||(t._inputs[n]=[]),t._inputs[n][i]||t._addPointerDevice(n,i,e.clientX,e.clientY);var o=t._inputs[n][i];o&&(t.onInputChanged&&(t.onInputChanged(n,i,0,o[0],e.clientX),t.onInputChanged(n,i,1,o[1],e.clientY),t.onInputChanged(n,i,e.button+2,o[e.button+2],1)),o[0]=e.clientX,o[1]=e.clientY,o[e.button+2]=1)},this._pointerUpEvent=function(e){var n=e.pointerType=="mouse"?Kt.Mouse:Kt.Touch,i=e.pointerType=="mouse"?0:e.pointerId,o=t._inputs[n][i];o&&(t.onInputChanged&&t.onInputChanged(n,i,e.button+2,o[e.button+2],0),o[0]=e.clientX,o[1]=e.clientY,o[e.button+2]=0),e.pointerType!="mouse"&&t._unregisterDevice(n,i)},this._elementToAttachTo.addEventListener("pointermove",this._pointerMoveEvent),this._elementToAttachTo.addEventListener("pointerdown",this._pointerDownEvent),this._elementToAttachTo.addEventListener("pointerup",this._pointerUpEvent)},r.prototype._handleGamepadActions=function(){var t=this;this._gamepadConnectedEvent=function(e){t._addGamePad(e.gamepad)},this._gamepadDisconnectedEvent=function(e){if(t._gamepads){var n=t._getGamepadDeviceType(e.gamepad.id),i=e.gamepad.index;t._unregisterDevice(n,i),delete t._gamepads[i]}},window.addEventListener("gamepadconnected",this._gamepadConnectedEvent),window.addEventListener("gamepaddisconnected",this._gamepadDisconnectedEvent)},r.prototype._updateDevice=function(t,e,n){var i=navigator.getGamepads()[e];if(i&&t==this._gamepads[e]){var o=this._inputs[t][e];n>=i.buttons.length?o[n]=i.axes[n-i.buttons.length].valueOf():o[n]=i.buttons[n].value}},r.prototype._getGamepadDeviceType=function(t){return t.indexOf("054c")!==-1?Kt.DualShock:t.indexOf("Xbox One")!==-1||t.search("Xbox 360")!==-1||t.search("xinput")!==-1?Kt.Xbox:t.indexOf("057e")!==-1?Kt.Switch:Kt.Generic},r._MAX_KEYCODES=255,r._MAX_POINTER_INPUTS=7,r}(),nu=function(){function r(t,e,n){n===void 0&&(n=0),this.deviceType=e,this.deviceSlot=n,this.onInputChangedObservable=new C.c,this._deviceInputSystem=t}return r.prototype.getInput=function(t){return this._deviceInputSystem.pollInput(this.deviceType,this.deviceSlot,t)},r}(),$f=function(){function r(t){var e=this;this.onDeviceConnectedObservable=new C.c(function(i){e.getDevices().forEach(function(o){e.onDeviceConnectedObservable.notifyObserver(i,o)})}),this.onDeviceDisconnectedObservable=new C.c;var n=Object.keys(Kt).length/2;this._devices=new Array(n),this._firstDevice=new Array(n),this._deviceInputSystem=tu.Create(t),this._deviceInputSystem.onDeviceConnected=function(i,o){e._addDevice(i,o),e.onDeviceConnectedObservable.notifyObservers(e.getDeviceSource(i,o))},this._deviceInputSystem.onDeviceDisconnected=function(i,o){var a=e.getDeviceSource(i,o);e._removeDevice(i,o),e.onDeviceDisconnectedObservable.notifyObservers(a)},this._deviceInputSystem.onInputChanged||(this._deviceInputSystem.onInputChanged=function(i,o,a,s,d){var p;(p=e.getDeviceSource(i,o))===null||p===void 0||p.onInputChangedObservable.notifyObservers({inputIndex:a,previousState:s,currentState:d})})}return r.prototype.getDeviceSource=function(t,e){if(e===void 0){if(this._firstDevice[t]===void 0)return null;e=this._firstDevice[t]}return this._devices[t]&&this._devices[t][e]!==void 0?this._devices[t][e]:null},r.prototype.getDeviceSources=function(t){return this._devices[t].filter(function(e){return!!e})},r.prototype.getDevices=function(){var t=new Array;return this._devices.forEach(function(e){t.push.apply(t,e)}),t},r.prototype.dispose=function(){this.onDeviceConnectedObservable.clear(),this.onDeviceDisconnectedObservable.clear(),this._deviceInputSystem.dispose()},r.prototype._addDevice=function(t,e){this._devices[t]||(this._devices[t]=new Array),this._devices[t][e]||(this._devices[t][e]=new nu(this._deviceInputSystem,t,e),this._updateFirstDevices(t))},r.prototype._removeDevice=function(t,e){delete this._devices[t][e],this._updateFirstDevices(t)},r.prototype._updateFirstDevices=function(t){switch(t){case Kt.Keyboard:case Kt.Mouse:this._firstDevice[t]=0;break;case Kt.Touch:case Kt.DualShock:case Kt.Xbox:case Kt.Switch:case Kt.Generic:var e=this._devices[t];delete this._firstDevice[t];for(var n=0;n<e.length;n++)if(e[n]){this._firstDevice[t]=n;break}}},r}(),iu=f(168),ru=(f(123),function(){this._timeElapsedQueryEnded=!1}),ou=function(){this.occlusionInternalRetryCounter=0,this.isOcclusionQueryInProgress=!1,this.isOccluded=!1,this.occlusionRetryCount=-1,this.occlusionType=Dt.a.OCCLUSION_TYPE_NONE,this.occlusionQueryAlgorithmType=Dt.a.OCCLUSION_ALGORITHM_TYPE_CONSERVATIVE};Ue.a.prototype.createQuery=function(){return this._gl.createQuery()},Ue.a.prototype.deleteQuery=function(r){return this._gl.deleteQuery(r),this},Ue.a.prototype.isQueryResultAvailable=function(r){return this._gl.getQueryParameter(r,this._gl.QUERY_RESULT_AVAILABLE)},Ue.a.prototype.getQueryResult=function(r){return this._gl.getQueryParameter(r,this._gl.QUERY_RESULT)},Ue.a.prototype.beginOcclusionQuery=function(r,t){var e=this._getGlAlgorithmType(r);return this._gl.beginQuery(e,t),this},Ue.a.prototype.endOcclusionQuery=function(r){var t=this._getGlAlgorithmType(r);return this._gl.endQuery(t),this},Ue.a.prototype._createTimeQuery=function(){var r=this.getCaps().timerQuery;return r.createQueryEXT?r.createQueryEXT():this.createQuery()},Ue.a.prototype._deleteTimeQuery=function(r){var t=this.getCaps().timerQuery;t.deleteQueryEXT?t.deleteQueryEXT(r):this.deleteQuery(r)},Ue.a.prototype._getTimeQueryResult=function(r){var t=this.getCaps().timerQuery;return t.getQueryObjectEXT?t.getQueryObjectEXT(r,t.QUERY_RESULT_EXT):this.getQueryResult(r)},Ue.a.prototype._getTimeQueryAvailability=function(r){var t=this.getCaps().timerQuery;return t.getQueryObjectEXT?t.getQueryObjectEXT(r,t.QUERY_RESULT_AVAILABLE_EXT):this.isQueryResultAvailable(r)},Ue.a.prototype.startTimeQuery=function(){var r=this.getCaps(),t=r.timerQuery;if(!t)return null;var e=new ru;if(this._gl.getParameter(t.GPU_DISJOINT_EXT),r.canUseTimestampForTimerQuery)e._startTimeQuery=this._createTimeQuery(),t.queryCounterEXT(e._startTimeQuery,t.TIMESTAMP_EXT);else{if(this._currentNonTimestampToken)return this._currentNonTimestampToken;e._timeElapsedQuery=this._createTimeQuery(),t.beginQueryEXT?t.beginQueryEXT(t.TIME_ELAPSED_EXT,e._timeElapsedQuery):this._gl.beginQuery(t.TIME_ELAPSED_EXT,e._timeElapsedQuery),this._currentNonTimestampToken=e}return e},Ue.a.prototype.endTimeQuery=function(r){var t=this.getCaps(),e=t.timerQuery;if(!e||!r)return-1;if(t.canUseTimestampForTimerQuery){if(!r._startTimeQuery)return-1;r._endTimeQuery||(r._endTimeQuery=this._createTimeQuery(),e.queryCounterEXT(r._endTimeQuery,e.TIMESTAMP_EXT))}else if(!r._timeElapsedQueryEnded){if(!r._timeElapsedQuery)return-1;e.endQueryEXT?e.endQueryEXT(e.TIME_ELAPSED_EXT):this._gl.endQuery(e.TIME_ELAPSED_EXT),r._timeElapsedQueryEnded=!0}var n=this._gl.getParameter(e.GPU_DISJOINT_EXT),i=!1;if(r._endTimeQuery?i=this._getTimeQueryAvailability(r._endTimeQuery):r._timeElapsedQuery&&(i=this._getTimeQueryAvailability(r._timeElapsedQuery)),i&&!n){var o=0;if(t.canUseTimestampForTimerQuery){if(!r._startTimeQuery||!r._endTimeQuery)return-1;var a=this._getTimeQueryResult(r._startTimeQuery);o=this._getTimeQueryResult(r._endTimeQuery)-a,this._deleteTimeQuery(r._startTimeQuery),this._deleteTimeQuery(r._endTimeQuery),r._startTimeQuery=null,r._endTimeQuery=null}else{if(!r._timeElapsedQuery)return-1;o=this._getTimeQueryResult(r._timeElapsedQuery),this._deleteTimeQuery(r._timeElapsedQuery),r._timeElapsedQuery=null,r._timeElapsedQueryEnded=!1,this._currentNonTimestampToken=null}return o}return-1},Ue.a.prototype._getGlAlgorithmType=function(r){return r===Dt.a.OCCLUSION_ALGORITHM_TYPE_CONSERVATIVE?this._gl.ANY_SAMPLES_PASSED_CONSERVATIVE:this._gl.ANY_SAMPLES_PASSED},Object.defineProperty(Dt.a.prototype,"isOcclusionQueryInProgress",{get:function(){return this._occlusionDataStorage.isOcclusionQueryInProgress},set:function(r){this._occlusionDataStorage.isOcclusionQueryInProgress=r},enumerable:!1,configurable:!0}),Object.defineProperty(Dt.a.prototype,"_occlusionDataStorage",{get:function(){return this.__occlusionDataStorage||(this.__occlusionDataStorage=new ou),this.__occlusionDataStorage},enumerable:!1,configurable:!0}),Object.defineProperty(Dt.a.prototype,"isOccluded",{get:function(){return this._occlusionDataStorage.isOccluded},set:function(r){this._occlusionDataStorage.isOccluded=r},enumerable:!0,configurable:!0}),Object.defineProperty(Dt.a.prototype,"occlusionQueryAlgorithmType",{get:function(){return this._occlusionDataStorage.occlusionQueryAlgorithmType},set:function(r){this._occlusionDataStorage.occlusionQueryAlgorithmType=r},enumerable:!0,configurable:!0}),Object.defineProperty(Dt.a.prototype,"occlusionType",{get:function(){return this._occlusionDataStorage.occlusionType},set:function(r){this._occlusionDataStorage.occlusionType=r},enumerable:!0,configurable:!0}),Object.defineProperty(Dt.a.prototype,"occlusionRetryCount",{get:function(){return this._occlusionDataStorage.occlusionRetryCount},set:function(r){this._occlusionDataStorage.occlusionRetryCount=r},enumerable:!0,configurable:!0}),Dt.a.prototype._checkOcclusionQuery=function(){var r=this._occlusionDataStorage;if(r.occlusionType===Dt.a.OCCLUSION_TYPE_NONE)return r.isOccluded=!1,!1;var t=this.getEngine();if(t.webGLVersion<2||!t.isQueryResultAvailable)return r.isOccluded=!1,!1;if(this.isOcclusionQueryInProgress&&this._occlusionQuery)if(t.isQueryResultAvailable(this._occlusionQuery)){var e=t.getQueryResult(this._occlusionQuery);r.isOcclusionQueryInProgress=!1,r.occlusionInternalRetryCounter=0,r.isOccluded=e!==1}else{if(r.occlusionInternalRetryCounter++,!(r.occlusionRetryCount!==-1&&r.occlusionInternalRetryCounter>r.occlusionRetryCount))return!1;r.isOcclusionQueryInProgress=!1,r.occlusionInternalRetryCounter=0,r.isOccluded=r.occlusionType!==Dt.a.OCCLUSION_TYPE_OPTIMISTIC&&r.isOccluded}var n=this.getScene();if(n.getBoundingBoxRenderer){var i=n.getBoundingBoxRenderer();this._occlusionQuery||(this._occlusionQuery=t.createQuery()),t.beginOcclusionQuery(r.occlusionQueryAlgorithmType,this._occlusionQuery),i.renderOcclusionBoundingBox(this),t.endOcclusionQuery(r.occlusionQueryAlgorithmType),this._occlusionDataStorage.isOcclusionQueryInProgress=!0}return r.isOccluded};var ep=!0;Ue.a.prototype.createTransformFeedback=function(){return this._gl.createTransformFeedback()},Ue.a.prototype.deleteTransformFeedback=function(r){this._gl.deleteTransformFeedback(r)},Ue.a.prototype.bindTransformFeedback=function(r){this._gl.bindTransformFeedback(this._gl.TRANSFORM_FEEDBACK,r)},Ue.a.prototype.beginTransformFeedback=function(r){r===void 0&&(r=!0),this._gl.beginTransformFeedback(r?this._gl.POINTS:this._gl.TRIANGLES)},Ue.a.prototype.endTransformFeedback=function(){this._gl.endTransformFeedback()},Ue.a.prototype.setTranformFeedbackVaryings=function(r,t){this._gl.transformFeedbackVaryings(r,t,this._gl.INTERLEAVED_ATTRIBS)},Ue.a.prototype.bindTransformFeedbackBuffer=function(r){this._gl.bindBufferBase(this._gl.TRANSFORM_FEEDBACK_BUFFER,0,r?r.underlyingResource:null)},f(126),Bt.a.prototype.updateVideoTexture=function(r,t,e){if(r&&!r._isDisabled){var n=this._bindTextureDirectly(this._gl.TEXTURE_2D,r,!0);this._unpackFlipY(!e);try{if(this._videoTextureSupported===void 0&&(this._gl.getError(),this._gl.texImage2D(this._gl.TEXTURE_2D,0,this._gl.RGBA,this._gl.RGBA,this._gl.UNSIGNED_BYTE,t),this._gl.getError()!==0?this._videoTextureSupported=!1:this._videoTextureSupported=!0),this._videoTextureSupported)this._gl.texImage2D(this._gl.TEXTURE_2D,0,this._gl.RGBA,this._gl.RGBA,this._gl.UNSIGNED_BYTE,t);else{if(!r._workingCanvas){r._workingCanvas=_s.a.CreateCanvas(r.width,r.height);var i=r._workingCanvas.getContext("2d");if(!i)throw new Error("Unable to get 2d context");r._workingContext=i,r._workingCanvas.width=r.width,r._workingCanvas.height=r.height}r._workingContext.clearRect(0,0,r.width,r.height),r._workingContext.drawImage(t,0,0,t.videoWidth,t.videoHeight,0,0,r.width,r.height),this._gl.texImage2D(this._gl.TEXTURE_2D,0,this._gl.RGBA,this._gl.RGBA,this._gl.UNSIGNED_BYTE,r._workingCanvas)}r.generateMipMaps&&this._gl.generateMipmap(this._gl.TEXTURE_2D),n||this._bindTextureDirectly(this._gl.TEXTURE_2D,null),r.isReady=!0}catch{r._isDisabled=!0}}},Bt.a.prototype.restoreSingleAttachment=function(){var r=this._gl;this.bindAttachments([r.BACK])},Bt.a.prototype.buildTextureLayout=function(r){for(var t=this._gl,e=[],n=0;n<r.length;n++)r[n]?e.push(t["COLOR_ATTACHMENT"+n]):e.push(t.NONE);return e},Bt.a.prototype.bindAttachments=function(r){this._gl.drawBuffers(r)},Bt.a.prototype.unBindMultiColorAttachmentFramebuffer=function(r,t,e){t===void 0&&(t=!1),this._currentRenderTarget=null;var n=this._gl,i=r[0]._attachments,o=i.length;if(r[0]._MSAAFramebuffer){n.bindFramebuffer(n.READ_FRAMEBUFFER,r[0]._MSAAFramebuffer),n.bindFramebuffer(n.DRAW_FRAMEBUFFER,r[0]._framebuffer);for(var a=0;a<o;a++){for(var s=r[a],d=0;d<o;d++)i[d]=n.NONE;i[a]=n[this.webGLVersion>1?"COLOR_ATTACHMENT"+a:"COLOR_ATTACHMENT"+a+"_WEBGL"],n.readBuffer(i[a]),n.drawBuffers(i),n.blitFramebuffer(0,0,s.width,s.height,0,0,s.width,s.height,n.COLOR_BUFFER_BIT,n.NEAREST)}for(a=0;a<o;a++)i[a]=n[this.webGLVersion>1?"COLOR_ATTACHMENT"+a:"COLOR_ATTACHMENT"+a+"_WEBGL"];n.drawBuffers(i)}for(a=0;a<o;a++)!(s=r[a]).generateMipMaps||t||s.isCube||(this._bindTextureDirectly(n.TEXTURE_2D,s,!0),n.generateMipmap(n.TEXTURE_2D),this._bindTextureDirectly(n.TEXTURE_2D,null));e&&(r[0]._MSAAFramebuffer&&this._bindUnboundFramebuffer(r[0]._framebuffer),e()),this._bindUnboundFramebuffer(null)},Bt.a.prototype.createMultipleRenderTarget=function(r,t){var e=!1,n=!0,i=!1,o=!1,a=1,s=h.a.TEXTURETYPE_UNSIGNED_INT,d=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,p=new Array,b=new Array;t!==void 0&&(e=t.generateMipMaps!==void 0&&t.generateMipMaps,n=t.generateDepthBuffer===void 0||t.generateDepthBuffer,i=t.generateStencilBuffer!==void 0&&t.generateStencilBuffer,o=t.generateDepthTexture!==void 0&&t.generateDepthTexture,a=t.textureCount||1,t.types&&(p=t.types),t.samplingModes&&(b=t.samplingModes));var P=this._gl,O=P.createFramebuffer();this._bindUnboundFramebuffer(O);for(var B=r.width||r,F=r.height||r,z=[],J=[],ie=this._setupFramebufferDepthAttachments(i,n,B,F),se=0;se<a;se++){var ce=b[se]||d,ue=p[se]||s;(ue!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloatLinearFiltering)&&(ue!==h.a.TEXTURETYPE_HALF_FLOAT||this._caps.textureHalfFloatLinearFiltering)||(ce=h.a.TEXTURE_NEAREST_SAMPLINGMODE);var fe=this._getSamplingParameters(ce,e);ue!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloat||(ue=h.a.TEXTURETYPE_UNSIGNED_INT,l.a.Warn("Float textures are not supported. Render target forced to TEXTURETYPE_UNSIGNED_BYTE type"));var ve=new Ct.a(this,Ct.b.MultiRenderTarget),Te=P[this.webGLVersion>1?"COLOR_ATTACHMENT"+se:"COLOR_ATTACHMENT"+se+"_WEBGL"];z.push(ve),J.push(Te),P.activeTexture(P["TEXTURE"+se]),P.bindTexture(P.TEXTURE_2D,ve._webGLTexture),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_MAG_FILTER,fe.mag),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_MIN_FILTER,fe.min),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_WRAP_S,P.CLAMP_TO_EDGE),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_WRAP_T,P.CLAMP_TO_EDGE),P.texImage2D(P.TEXTURE_2D,0,this._getRGBABufferInternalSizedFormat(ue),B,F,0,P.RGBA,this._getWebGLTextureType(ue),null),P.framebufferTexture2D(P.DRAW_FRAMEBUFFER,Te,P.TEXTURE_2D,ve._webGLTexture,0),e&&this._gl.generateMipmap(this._gl.TEXTURE_2D),this._bindTextureDirectly(P.TEXTURE_2D,null),ve._framebuffer=O,ve._depthStencilBuffer=ie,ve.baseWidth=B,ve.baseHeight=F,ve.width=B,ve.height=F,ve.isReady=!0,ve.samples=1,ve.generateMipMaps=e,ve.samplingMode=ce,ve.type=ue,ve._generateDepthBuffer=n,ve._generateStencilBuffer=i,ve._attachments=J,ve._textureArray=z,this._internalTexturesCache.push(ve)}if(o&&this._caps.depthTextureExtension){var Re=new Ct.a(this,Ct.b.MultiRenderTarget);P.activeTexture(P.TEXTURE0),P.bindTexture(P.TEXTURE_2D,Re._webGLTexture),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_MAG_FILTER,P.NEAREST),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_MIN_FILTER,P.NEAREST),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_WRAP_S,P.CLAMP_TO_EDGE),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_WRAP_T,P.CLAMP_TO_EDGE),P.texImage2D(P.TEXTURE_2D,0,this.webGLVersion<2?P.DEPTH_COMPONENT:P.DEPTH_COMPONENT16,B,F,0,P.DEPTH_COMPONENT,P.UNSIGNED_SHORT,null),P.framebufferTexture2D(P.FRAMEBUFFER,P.DEPTH_ATTACHMENT,P.TEXTURE_2D,Re._webGLTexture,0),Re._framebuffer=O,Re.baseWidth=B,Re.baseHeight=F,Re.width=B,Re.height=F,Re.isReady=!0,Re.samples=1,Re.generateMipMaps=e,Re.samplingMode=P.NEAREST,Re._generateDepthBuffer=n,Re._generateStencilBuffer=i,z.push(Re),this._internalTexturesCache.push(Re)}return P.drawBuffers(J),this._bindUnboundFramebuffer(null),this.resetTextureCache(),z},Bt.a.prototype.updateMultipleRenderTargetTextureSampleCount=function(r,t){if(this.webGLVersion<2||!r)return 1;if(r[0].samples===t)return t;var e=r[0]._attachments.length;if(e===0)return 1;var n=this._gl;t=Math.min(t,this.getCaps().maxMSAASamples),r[0]._depthStencilBuffer&&(n.deleteRenderbuffer(r[0]._depthStencilBuffer),r[0]._depthStencilBuffer=null),r[0]._MSAAFramebuffer&&(n.deleteFramebuffer(r[0]._MSAAFramebuffer),r[0]._MSAAFramebuffer=null);for(var i=0;i<e;i++)r[i]._MSAARenderBuffer&&(n.deleteRenderbuffer(r[i]._MSAARenderBuffer),r[i]._MSAARenderBuffer=null);if(t>1&&n.renderbufferStorageMultisample){var o=n.createFramebuffer();if(!o)throw new Error("Unable to create multi sampled framebuffer");this._bindUnboundFramebuffer(o);var a=this._setupFramebufferDepthAttachments(r[0]._generateStencilBuffer,r[0]._generateDepthBuffer,r[0].width,r[0].height,t),s=[];for(i=0;i<e;i++){var d=r[i],p=n[this.webGLVersion>1?"COLOR_ATTACHMENT"+i:"COLOR_ATTACHMENT"+i+"_WEBGL"],b=n.createRenderbuffer();if(!b)throw new Error("Unable to create multi sampled framebuffer");n.bindRenderbuffer(n.RENDERBUFFER,b),n.renderbufferStorageMultisample(n.RENDERBUFFER,t,this._getRGBAMultiSampleBufferFormat(d.type),d.width,d.height),n.framebufferRenderbuffer(n.FRAMEBUFFER,p,n.RENDERBUFFER,b),d._MSAAFramebuffer=o,d._MSAARenderBuffer=b,d.samples=t,d._depthStencilBuffer=a,n.bindRenderbuffer(n.RENDERBUFFER,null),s.push(p)}n.drawBuffers(s)}else this._bindUnboundFramebuffer(r[0]._framebuffer);return this._bindUnboundFramebuffer(null),t};var io=f(56);Bt.a.prototype._createDepthStencilCubeTexture=function(r,t){var e=new Ct.a(this,Ct.b.Unknown);if(e.isCube=!0,this.webGLVersion===1)return l.a.Error("Depth cube texture is not supported by WebGL 1."),e;var n=Object(c.a)({bilinearFiltering:!1,comparisonFunction:0,generateStencil:!1},t),i=this._gl;this._bindTextureDirectly(i.TEXTURE_CUBE_MAP,e,!0),this._setupDepthStencilTexture(e,r,n.generateStencil,n.bilinearFiltering,n.comparisonFunction);for(var o=0;o<6;o++)n.generateStencil?i.texImage2D(i.TEXTURE_CUBE_MAP_POSITIVE_X+o,0,i.DEPTH24_STENCIL8,r,r,0,i.DEPTH_STENCIL,i.UNSIGNED_INT_24_8,null):i.texImage2D(i.TEXTURE_CUBE_MAP_POSITIVE_X+o,0,i.DEPTH_COMPONENT24,r,r,0,i.DEPTH_COMPONENT,i.UNSIGNED_INT,null);return this._bindTextureDirectly(i.TEXTURE_CUBE_MAP,null),e},Bt.a.prototype._partialLoadFile=function(r,t,e,n,i){i===void 0&&(i=null),this._loadFile(r,function(o){e[t]=o,e._internalCount++,e._internalCount===6&&n(e)},void 0,void 0,!0,function(o,a){i&&o&&i(o.status+" "+o.statusText,a)})},Bt.a.prototype._cascadeLoadFiles=function(r,t,e,n){n===void 0&&(n=null);var i=[];i._internalCount=0;for(var o=0;o<6;o++)this._partialLoadFile(e[o],o,i,t,n)},Bt.a.prototype._cascadeLoadImgs=function(r,t,e,n,i){n===void 0&&(n=null);var o=[];o._internalCount=0;for(var a=0;a<6;a++)this._partialLoadImg(e[a],a,o,r,t,n,i)},Bt.a.prototype._partialLoadImg=function(r,t,e,n,i,o,a){var s;o===void 0&&(o=null),s=io.a.LoadImage(r,function(){s&&(e[t]=s,e._internalCount++,n&&n._removePendingData(s)),e._internalCount===6&&i(e)},function(d,p){n&&n._removePendingData(s),o&&o(d,p)},n?n.offlineProvider:null,a),n&&s&&n._addPendingData(s)},Bt.a.prototype._setCubeMapTextureParams=function(r,t){var e=this._gl;e.texParameteri(e.TEXTURE_CUBE_MAP,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_CUBE_MAP,e.TEXTURE_MIN_FILTER,t?e.LINEAR_MIPMAP_LINEAR:e.LINEAR),e.texParameteri(e.TEXTURE_CUBE_MAP,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE),e.texParameteri(e.TEXTURE_CUBE_MAP,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE),r.samplingMode=t?h.a.TEXTURE_TRILINEAR_SAMPLINGMODE:h.a.TEXTURE_LINEAR_LINEAR,this._bindTextureDirectly(e.TEXTURE_CUBE_MAP,null)},Bt.a.prototype.createCubeTexture=function(r,t,e,n,i,o,a,s,d,p,b,P,O){var B=this;i===void 0&&(i=null),o===void 0&&(o=null),s===void 0&&(s=null),d===void 0&&(d=!1),p===void 0&&(p=0),b===void 0&&(b=0),P===void 0&&(P=null);var F=this._gl,z=P||new Ct.a(this,Ct.b.Cube);z.isCube=!0,z.url=r,z.generateMipMaps=!n,z._lodGenerationScale=p,z._lodGenerationOffset=b,this._doNotHandleContextLost||(z._extension=s,z._files=e);var J=r;this._transformTextureUrl&&!P&&(r=this._transformTextureUrl(r));for(var ie=r.lastIndexOf("."),se=s||(ie>-1?r.substring(ie).toLowerCase():""),ce=null,ue=0,fe=Bt.a._TextureLoaders;ue<fe.length;ue++){var ve=fe[ue];if(ve.canLoad(se)){ce=ve;break}}if(ce){var Te=function(Re){B._bindTextureDirectly(F.TEXTURE_CUBE_MAP,z,!0),ce.loadCubeData(Re,z,d,i,o)};e&&e.length===6?ce.supportCascades?this._cascadeLoadFiles(t,function(Re){return Te(Re.map(function(Ae){return new Uint8Array(Ae)}))},e,o):o?o("Textures type does not support cascades."):l.a.Warn("Texture loader does not support cascades."):this._loadFile(r,function(Re){return Te(new Uint8Array(Re))},void 0,void 0,!0,function(Re,Ae){r===J?o&&Re&&o(Re.status+" "+Re.statusText,Ae):(l.a.Warn("Failed to load "+r+", falling back to the "+J),B.createCubeTexture(J,t,e,n,i,o,a,s,d,p,b,z,O))})}else{if(!e)throw new Error("Cannot load cubemap because files were not defined");this._cascadeLoadImgs(t,function(Re){var Ae=B.needPOTTextures?Bt.a.GetExponentOfTwo(Re[0].width,B._caps.maxCubemapTextureSize):Re[0].width,Ee=Ae,Se=[F.TEXTURE_CUBE_MAP_POSITIVE_X,F.TEXTURE_CUBE_MAP_POSITIVE_Y,F.TEXTURE_CUBE_MAP_POSITIVE_Z,F.TEXTURE_CUBE_MAP_NEGATIVE_X,F.TEXTURE_CUBE_MAP_NEGATIVE_Y,F.TEXTURE_CUBE_MAP_NEGATIVE_Z];B._bindTextureDirectly(F.TEXTURE_CUBE_MAP,z,!0),B._unpackFlipY(!1);for(var Le=a?B._getInternalFormat(a):B._gl.RGBA,xe=0;xe<Se.length;xe++)if(Re[xe].width!==Ae||Re[xe].height!==Ee){if(B._prepareWorkingCanvas(),!B._workingCanvas||!B._workingContext)return void l.a.Warn("Cannot create canvas to resize texture.");B._workingCanvas.width=Ae,B._workingCanvas.height=Ee,B._workingContext.drawImage(Re[xe],0,0,Re[xe].width,Re[xe].height,0,0,Ae,Ee),F.texImage2D(Se[xe],0,Le,Le,F.UNSIGNED_BYTE,B._workingCanvas)}else F.texImage2D(Se[xe],0,Le,Le,F.UNSIGNED_BYTE,Re[xe]);n||F.generateMipmap(F.TEXTURE_CUBE_MAP),B._setCubeMapTextureParams(z,!n),z.width=Ae,z.height=Ee,z.isReady=!0,a&&(z.format=a),z.onLoadedObservable.notifyObservers(z),z.onLoadedObservable.clear(),i&&i()},e,o)}return this._internalTexturesCache.push(z),z},f(153),f(124);var tp=function(){};Ue.a.prototype.getInputElement=function(){return this.inputElement||this.getRenderingCanvas()},Ue.a.prototype.registerView=function(r,t){var e=this;this.views||(this.views=[]);for(var n=0,i=this.views;n<i.length;n++){var o=i[n];if(o.target===r)return o}var a=this.getRenderingCanvas();a&&(r.width=a.width,r.height=a.height);var s={target:r,camera:t};return this.views.push(s),t&&t.onDisposeObservable.add(function(){e.unRegisterView(r)}),s},Ue.a.prototype.unRegisterView=function(r){if(!this.views)return this;for(var t=0,e=this.views;t<e.length;t++){var n=e[t];if(n.target===r){var i=this.views.indexOf(n);i!==-1&&this.views.splice(i,1);break}}return this},Ue.a.prototype._renderViews=function(){if(!this.views)return!1;var r=this.getRenderingCanvas();if(!r)return!1;for(var t=0,e=this.views;t<e.length;t++){var n=e[t],i=n.target,o=i.getContext("2d");if(o){var a=n.camera,s=null,d=null;if(a){if((d=a.getScene()).activeCameras&&d.activeCameras.length)continue;this.activeView=n,s=d.activeCamera,d.activeCamera=a}var p=i.width!==i.clientWidth||i.height!==i.clientHeight;if(i.clientWidth&&i.clientHeight&&p&&(i.width=i.clientWidth,i.height=i.clientHeight,r.width=i.clientWidth,r.height=i.clientHeight,this.resize()),!r.width||!r.height)return!1;this._renderFrame(),o.drawImage(r,0,0),s&&d&&(d.activeCamera=s)}}return this.activeView=null,!0},f(129);function np(r){if(this._excludedCompressedTextures&&this._excludedCompressedTextures.some(function(i){var o="\\b"+i+"\\b";return r&&(r===i||r.match(new RegExp(o,"g")))}))return r;var t=r.lastIndexOf("."),e=r.lastIndexOf("?"),n=e>-1?r.substring(e,r.length):"";return(t>-1?r.substring(0,t):r)+this._textureFormatInUse+n}Object.defineProperty(Ue.a.prototype,"texturesSupported",{get:function(){var r=new Array;return this._caps.astc&&r.push("-astc.ktx"),this._caps.s3tc&&r.push("-dxt.ktx"),this._caps.pvrtc&&r.push("-pvrtc.ktx"),this._caps.etc2&&r.push("-etc2.ktx"),this._caps.etc1&&r.push("-etc1.ktx"),r},enumerable:!0,configurable:!0}),Object.defineProperty(Ue.a.prototype,"textureFormatInUse",{get:function(){return this._textureFormatInUse||null},enumerable:!0,configurable:!0}),Ue.a.prototype.setCompressedTextureExclusions=function(r){this._excludedCompressedTextures=r},Ue.a.prototype.setTextureFormatToUse=function(r){for(var t=this.texturesSupported,e=0,n=t.length;e<n;e++)for(var i=0,o=r.length;i<o;i++)if(t[e]===r[i].toLowerCase())return this._transformTextureUrl=np.bind(this),this._textureFormatInUse=t[e];return this._textureFormatInUse="",this._transformTextureUrl=null,null};var ip=f(144),au=f(118),su=f(89),_i=[Math.sqrt(1/(4*Math.PI)),-Math.sqrt(3/(4*Math.PI)),Math.sqrt(3/(4*Math.PI)),-Math.sqrt(3/(4*Math.PI)),Math.sqrt(15/(4*Math.PI)),-Math.sqrt(15/(4*Math.PI)),Math.sqrt(5/(16*Math.PI)),-Math.sqrt(15/(4*Math.PI)),Math.sqrt(15/(16*Math.PI))],rp=[function(r){return 1},function(r){return r.y},function(r){return r.z},function(r){return r.x},function(r){return r.x*r.y},function(r){return r.y*r.z},function(r){return 3*r.z*r.z-1},function(r){return r.x*r.z},function(r){return r.x*r.x-r.y*r.y}],Ei=function(r,t){return _i[r]*rp[r](t)},Si=[Math.PI,2*Math.PI/3,2*Math.PI/3,2*Math.PI/3,Math.PI/4,Math.PI/4,Math.PI/4,Math.PI/4,Math.PI/4],As=function(){function r(){this.preScaled=!1,this.l00=u.e.Zero(),this.l1_1=u.e.Zero(),this.l10=u.e.Zero(),this.l11=u.e.Zero(),this.l2_2=u.e.Zero(),this.l2_1=u.e.Zero(),this.l20=u.e.Zero(),this.l21=u.e.Zero(),this.l22=u.e.Zero()}return r.prototype.addLight=function(t,e,n){var i=new u.e(e.r,e.g,e.b).scale(n);this.l00=this.l00.add(i.scale(Ei(0,t))),this.l1_1=this.l1_1.add(i.scale(Ei(1,t))),this.l10=this.l10.add(i.scale(Ei(2,t))),this.l11=this.l11.add(i.scale(Ei(3,t))),this.l2_2=this.l2_2.add(i.scale(Ei(4,t))),this.l2_1=this.l2_1.add(i.scale(Ei(5,t))),this.l20=this.l20.add(i.scale(Ei(6,t))),this.l21=this.l21.add(i.scale(Ei(7,t))),this.l22=this.l22.add(i.scale(Ei(8,t)))},r.prototype.scaleInPlace=function(t){this.l00.scaleInPlace(t),this.l1_1.scaleInPlace(t),this.l10.scaleInPlace(t),this.l11.scaleInPlace(t),this.l2_2.scaleInPlace(t),this.l2_1.scaleInPlace(t),this.l20.scaleInPlace(t),this.l21.scaleInPlace(t),this.l22.scaleInPlace(t)},r.prototype.convertIncidentRadianceToIrradiance=function(){this.l00.scaleInPlace(Si[0]),this.l1_1.scaleInPlace(Si[1]),this.l10.scaleInPlace(Si[2]),this.l11.scaleInPlace(Si[3]),this.l2_2.scaleInPlace(Si[4]),this.l2_1.scaleInPlace(Si[5]),this.l20.scaleInPlace(Si[6]),this.l21.scaleInPlace(Si[7]),this.l22.scaleInPlace(Si[8])},r.prototype.convertIrradianceToLambertianRadiance=function(){this.scaleInPlace(1/Math.PI)},r.prototype.preScaleForRendering=function(){this.preScaled=!0,this.l00.scaleInPlace(_i[0]),this.l1_1.scaleInPlace(_i[1]),this.l10.scaleInPlace(_i[2]),this.l11.scaleInPlace(_i[3]),this.l2_2.scaleInPlace(_i[4]),this.l2_1.scaleInPlace(_i[5]),this.l20.scaleInPlace(_i[6]),this.l21.scaleInPlace(_i[7]),this.l22.scaleInPlace(_i[8])},r.FromArray=function(t){var e=new r;return u.e.FromArrayToRef(t[0],0,e.l00),u.e.FromArrayToRef(t[1],0,e.l1_1),u.e.FromArrayToRef(t[2],0,e.l10),u.e.FromArrayToRef(t[3],0,e.l11),u.e.FromArrayToRef(t[4],0,e.l2_2),u.e.FromArrayToRef(t[5],0,e.l2_1),u.e.FromArrayToRef(t[6],0,e.l20),u.e.FromArrayToRef(t[7],0,e.l21),u.e.FromArrayToRef(t[8],0,e.l22),e},r.FromPolynomial=function(t){var e=new r;return e.l00=t.xx.scale(.376127).add(t.yy.scale(.376127)).add(t.zz.scale(.376126)),e.l1_1=t.y.scale(.977204),e.l10=t.z.scale(.977204),e.l11=t.x.scale(.977204),e.l2_2=t.xy.scale(1.16538),e.l2_1=t.yz.scale(1.16538),e.l20=t.zz.scale(1.34567).subtract(t.xx.scale(.672834)).subtract(t.yy.scale(.672834)),e.l21=t.zx.scale(1.16538),e.l22=t.xx.scale(1.16538).subtract(t.yy.scale(1.16538)),e.l1_1.scaleInPlace(-1),e.l11.scaleInPlace(-1),e.l2_1.scaleInPlace(-1),e.l21.scaleInPlace(-1),e.scaleInPlace(Math.PI),e},r}(),ro=function(){function r(){this.x=u.e.Zero(),this.y=u.e.Zero(),this.z=u.e.Zero(),this.xx=u.e.Zero(),this.yy=u.e.Zero(),this.zz=u.e.Zero(),this.xy=u.e.Zero(),this.yz=u.e.Zero(),this.zx=u.e.Zero()}return Object.defineProperty(r.prototype,"preScaledHarmonics",{get:function(){return this._harmonics||(this._harmonics=As.FromPolynomial(this)),this._harmonics.preScaled||this._harmonics.preScaleForRendering(),this._harmonics},enumerable:!1,configurable:!0}),r.prototype.addAmbient=function(t){var e=new u.e(t.r,t.g,t.b);this.xx=this.xx.add(e),this.yy=this.yy.add(e),this.zz=this.zz.add(e)},r.prototype.scaleInPlace=function(t){this.x.scaleInPlace(t),this.y.scaleInPlace(t),this.z.scaleInPlace(t),this.xx.scaleInPlace(t),this.yy.scaleInPlace(t),this.zz.scaleInPlace(t),this.yz.scaleInPlace(t),this.zx.scaleInPlace(t),this.xy.scaleInPlace(t)},r.FromHarmonics=function(t){var e=new r;return e._harmonics=t,e.x=t.l11.scale(1.02333).scale(-1),e.y=t.l1_1.scale(1.02333).scale(-1),e.z=t.l10.scale(1.02333),e.xx=t.l00.scale(.886277).subtract(t.l20.scale(.247708)).add(t.l22.scale(.429043)),e.yy=t.l00.scale(.886277).subtract(t.l20.scale(.247708)).subtract(t.l22.scale(.429043)),e.zz=t.l00.scale(.886277).add(t.l20.scale(.495417)),e.yz=t.l2_1.scale(.858086).scale(-1),e.zx=t.l21.scale(.858086).scale(-1),e.xy=t.l2_2.scale(.858086),e.scaleInPlace(1/Math.PI),e},r.FromArray=function(t){var e=new r;return u.e.FromArrayToRef(t[0],0,e.x),u.e.FromArrayToRef(t[1],0,e.y),u.e.FromArrayToRef(t[2],0,e.z),u.e.FromArrayToRef(t[3],0,e.xx),u.e.FromArrayToRef(t[4],0,e.yy),u.e.FromArrayToRef(t[5],0,e.zz),u.e.FromArrayToRef(t[6],0,e.yz),u.e.FromArrayToRef(t[7],0,e.zx),u.e.FromArrayToRef(t[8],0,e.xy),e},r}(),zn=f(52),yr=function(r,t,e,n){this.name=r,this.worldAxisForNormal=t,this.worldAxisForFileX=e,this.worldAxisForFileY=n},jo=function(){function r(){}return r.ConvertCubeMapTextureToSphericalPolynomial=function(t){if(!t.isCube)return null;var e,n,i=t.getSize().width,o=t.readPixels(0),a=t.readPixels(1);t.isRenderTarget?(e=t.readPixels(3),n=t.readPixels(2)):(e=t.readPixels(2),n=t.readPixels(3));var s=t.readPixels(4),d=t.readPixels(5),p=t.gammaSpace,b=h.a.TEXTUREFORMAT_RGBA,P=h.a.TEXTURETYPE_UNSIGNED_INT;t.textureType!=h.a.TEXTURETYPE_FLOAT&&t.textureType!=h.a.TEXTURETYPE_HALF_FLOAT||(P=h.a.TEXTURETYPE_FLOAT);var O={size:i,right:o,left:a,up:e,down:n,front:s,back:d,format:b,type:P,gammaSpace:p};return this.ConvertCubeMapToSphericalPolynomial(O)},r.ConvertCubeMapToSphericalPolynomial=function(t){for(var e=new As,n=0,i=2/t.size,o=i,a=.5*i-1,s=0;s<6;s++)for(var d=this.FileFaces[s],p=t[d.name],b=a,P=t.format===h.a.TEXTUREFORMAT_RGBA?4:3,O=0;O<t.size;O++){for(var B=a,F=0;F<t.size;F++){var z=d.worldAxisForFileX.scale(B).add(d.worldAxisForFileY.scale(b)).add(d.worldAxisForNormal);z.normalize();var 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-varying vec2 vUV;
-uniform sampler2D textureSampler;
-#include<helperFunctions>
-void main(void)
-{
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Promise.reject("Env texture can only be created when the engine is associated to a canvas.");var a=h.a.TEXTURETYPE_FLOAT;if(!i.getCaps().textureFloatRender&&(a=h.a.TEXTURETYPE_HALF_FLOAT,!i.getCaps().textureHalfFloatRender))return Promise.reject("Env texture can only be created when the browser supports half float or full float rendering.");var s=n.width,d=new _e.a(i),p={},b=[],P=$.a.Log2(n.width);P=Math.round(P);for(var O=function(F){for(var z=Math.pow(2,P-F),J=function(se){var ce=t.readPixels(se,F),ue=i.createRawTexture(ce,z,z,h.a.TEXTUREFORMAT_RGBA,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE,null,a),fe=new Promise(function(ve,Te){var Re=new _t("rgbdEncode","rgbdEncode",null,null,1,null,h.a.TEXTURE_NEAREST_SAMPLINGMODE,i,!1,void 0,h.a.TEXTURETYPE_UNSIGNED_INT,void 0,null,!1);Re.getEffect().executeWhenCompiled(function(){Re.onApply=function(Se){Se._bindTexture("textureSampler",ue)};var Ae=i.getRenderWidth(),Ee=i.getRenderHeight();i.setSize(z,z),d.postProcessManager.directRender([Re],null),Xe.b.ToBlob(o,function(Se){var Le=new FileReader;Le.onload=function(xe){var Ne=xe.target.result;p[6*F+se]=Ne,ve()},Le.readAsArrayBuffer(Se)}),i.setSize(Ae,Ee)})});b.push(fe)},ie=0;ie<6;ie++)J(ie)},B=0;B<=P;B++)O(B);return Promise.all(b).then(function(){d.dispose();for(var F={version:1,width:s,irradiance:e._CreateEnvTextureIrradiance(t),specular:{mipmaps:[],lodGenerationScale:t.lodGenerationScale}},z=0,J=0;J<=P;J++)for(var ie=0;ie<6;ie++){var se=p[6*J+ie].byteLength;F.specular.mipmaps.push({length:se,position:z}),z+=se}for(var ce=JSON.stringify(F),ue=new ArrayBuffer(ce.length+1),fe=new Uint8Array(ue),ve=(J=0,ce.length);J<ve;J++)fe[J]=ce.charCodeAt(J);fe[ce.length]=0;var Te=r._MagicBytes.length+z+ue.byteLength,Re=new ArrayBuffer(Te),Ae=new Uint8Array(Re),Ee=new DataView(Re),Se=0;for(J=0;J<r._MagicBytes.length;J++)Ee.setUint8(Se++,r._MagicBytes[J]);for(Ae.set(new Uint8Array(ue),Se),Se+=ue.byteLength,J=0;J<=P;J++)for(ie=0;ie<6;ie++){var Le=p[6*J+ie];Ae.set(new Uint8Array(Le),Se),Se+=Le.byteLength}return Re})},r._CreateEnvTextureIrradiance=function(t){var e=t.sphericalPolynomial;return e==null?null:{x:[e.x.x,e.x.y,e.x.z],y:[e.y.x,e.y.y,e.y.z],z:[e.z.x,e.z.y,e.z.z],xx:[e.xx.x,e.xx.y,e.xx.z],yy:[e.yy.x,e.yy.y,e.yy.z],zz:[e.zz.x,e.zz.y,e.zz.z],yz:[e.yz.x,e.yz.y,e.yz.z],zx:[e.zx.x,e.zx.y,e.zx.z],xy:[e.xy.x,e.xy.y,e.xy.z]}},r.CreateImageDataArrayBufferViews=function(t,e){if(e.version!==1)throw new Error('Unsupported babylon environment map version "'+e.version+'"');var n=e.specular,i=$.a.Log2(e.width);if(i=Math.round(i)+1,n.mipmaps.length!==6*i)throw new Error('Unsupported specular mipmaps number "'+n.mipmaps.length+'"');for(var o=new Array(i),a=0;a<i;a++){o[a]=new Array(6);for(var s=0;s<6;s++){var d=n.mipmaps[6*a+s];o[a][s]=new Uint8Array(t.buffer,t.byteOffset+n.specularDataPosition+d.position,d.length)}}return o},r.UploadEnvLevelsAsync=function(t,e,n){if(n.version!==1)throw new Error('Unsupported babylon environment map version "'+n.version+'"');var i=n.specular;if(!i)return Promise.resolve();t._lodGenerationScale=i.lodGenerationScale;var o=r.CreateImageDataArrayBufferViews(e,n);return r.UploadLevelsAsync(t,o)},r._OnImageReadyAsync=function(t,e,n,i,o,a,s,d,p,b,P){return new Promise(function(O,B){if(n){var F=e.createTexture(null,!0,!0,null,h.a.TEXTURE_NEAREST_SAMPLINGMODE,null,function(J){B(J)},t);i.getEffect().executeWhenCompiled(function(){i.onApply=function(J){J._bindTexture("textureSampler",F),J.setFloat2("scale",1,1)},e.scenes[0].postProcessManager.directRender([i],b,!0,a,s),e.restoreDefaultFramebuffer(),F.dispose(),URL.revokeObjectURL(o),O()})}else{if(e._uploadImageToTexture(P,t,a,s),d){var z=p[s];z&&e._uploadImageToTexture(z._texture,t,a,0)}O()}})},r.UploadLevelsAsync=function(t,e){var n=this;if(!Xe.b.IsExponentOfTwo(t.width))throw new Error("Texture size must be a power of two");var 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z=(i-1)*O+B,J=B+(z-B)*(1-F/2),ie=Math.round(Math.min(Math.max(J,0),z)),se=new Ct.a(o,Ct.b.Temp);se.isCube=!0,se.invertY=!0,se.generateMipMaps=!1,o.updateTextureSamplingMode(h.a.TEXTURE_LINEAR_LINEAR,se);var ce=new zn.a(null);switch(ce.isCube=!0,ce._texture=se,b[ie]=ce,F){case 0:t._lodTextureLow=ce;break;case 1:t._lodTextureMid=ce;break;case 2:t._lodTextureHigh=ce}}var ue=[],fe=function(Ee){for(var Se=function(xe){var Ne=e[Ee][xe],Ie=new Blob([Ne],{type:"image/png"}),Fe=URL.createObjectURL(Ie),Ye=void 0;if(typeof Image>"u")Ye=createImageBitmap(Ie).then(function(it){return n._OnImageReadyAsync(it,o,a,d,Fe,xe,Ee,s,b,p,t)});else{var tt=new Image;tt.src=Fe,Ye=new Promise(function(it,ut){tt.onload=function(){n._OnImageReadyAsync(tt,o,a,d,Fe,xe,Ee,s,b,p,t).then(function(){return it()}).catch(function(Qe){ut(Qe)})},tt.onerror=function(Qe){ut(Qe)}})}ue.push(Ye)},Le=0;Le<6;Le++)Se(Le)};for(F=0;F<e.length;F++)fe(F);if(e.length<i){var ve=void 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ro;u.e.FromArrayToRef(n.x,0,i.x),u.e.FromArrayToRef(n.y,0,i.y),u.e.FromArrayToRef(n.z,0,i.z),u.e.FromArrayToRef(n.xx,0,i.xx),u.e.FromArrayToRef(n.yy,0,i.yy),u.e.FromArrayToRef(n.zz,0,i.zz),u.e.FromArrayToRef(n.yz,0,i.yz),u.e.FromArrayToRef(n.zx,0,i.zx),u.e.FromArrayToRef(n.xy,0,i.xy),t._sphericalPolynomial=i}},r._UpdateRGBDAsync=function(t,e,n,i,o){return t._source=Ct.b.CubeRawRGBD,t._bufferViewArrayArray=e,t._lodGenerationScale=i,t._lodGenerationOffset=o,t._sphericalPolynomial=n,r.UploadLevelsAsync(t,e).then(function(){t.isReady=!0})},r._MagicBytes=[134,22,135,150,246,214,150,54],r}();Ct.a._UpdateRGBDAsync=Ai._UpdateRGBDAsync;var Pi,Ps=function(){function r(t,e){e===void 0&&(e=20),this.debug=!1,this._sourceCode=t,this._numMaxIterations=e,this._functionDescr=[],this.inlineToken="#define inline"}return Object.defineProperty(r.prototype,"code",{get:function(){return this._sourceCode},enumerable:!1,configurable:!0}),r.prototype.processCode=function(){this.debug&&console.log("Start 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p=this._sourceCode.substring(n+1,d),b=this._skipWhitespaces(this._sourceCode,d+1);if(b!==this._sourceCode.length){var P=this._extractBetweenMarkers("{","}",this._sourceCode,b);if(P<0)this.debug&&console.warn("Could not extract the body of the function '"+s+"' (type="+a+"). funcBodyStartIndex="+b),t=e+this.inlineToken.length;else{for(var O=this._sourceCode.substring(b,P+1),B=this._removeComments(p).split(","),F=[],z=0;z<B.length;++z){var J=B[z].trim(),ie=J.lastIndexOf(" ");ie>=0&&F.push(J.substring(ie+1))}a!=="void"&&F.push("return"),this._functionDescr.push({name:s,type:a,parameters:F,body:O,callIndex:0}),t=P+1;var se=e>0?this._sourceCode.substring(0,e):"",ce=P+1<this._sourceCode.length-1?this._sourceCode.substring(P+1):"";this._sourceCode=se+ce,t-=P+1-e}}else this.debug&&console.warn("Could not extract the body of the function '"+s+"' (type="+a+"). funcParamsEndIndex="+d),t=e+this.inlineToken.length}}else this.debug&&console.warn("Could not extract the name/type of the function from: 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launched"),Xe.b.LoadScript=function(n,i,o,a){Xe.b.LoadFile(n,function(s){Function(s).apply(null),i&&i()},void 0,void 0,!1,function(s,d){o&&o("LoadScript Error",d)})},typeof URL>"u"&&(window.URL={createObjectURL:function(){},revokeObjectURL:function(){}}),typeof Blob>"u"&&(window.Blob=function(){}),e._shaderProcessor=new au.a,e}return Object(c.d)(t,r),t.prototype.getHardwareScalingLevel=function(){return 1},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._boundBuffersVertexArray&&this._native.deleteVertexArray(this._boundBuffersVertexArray),this._native.dispose()},t.prototype._queueNewFrame=function(e,n){return n.requestAnimationFrame&&n!==window?n.requestAnimationFrame(e):this._native.requestAnimationFrame(e),0},t.prototype._bindUnboundFramebuffer=function(e){this._currentFramebuffer!==e&&(this._currentFramebuffer&&this._native.unbindFramebuffer(this._currentFramebuffer),e&&this._native.bindFramebuffer(e),this._currentFramebuffer=e)},t.prototype.getHostDocument=function(){return null},t.prototype.clear=function(e,n,i,o){o===void 0&&(o=!1);var a=0;n&&e&&(this._native.clearColor(e.r,e.g,e.b,e.a!==void 0?e.a:1),a|=this._native.CLEAR_FLAG_COLOR),i&&(this._native.clearDepth(1),a|=this._native.CLEAR_FLAG_DEPTH),o&&(this._native.clearStencil(0),a|=this._native.CLEAR_FLAG_STENCIL),this._native.clear(a)},t.prototype.createIndexBuffer=function(e,n){var i=this._normalizeIndexData(e),o=new cu;if(o.references=1,o.is32Bits=i.BYTES_PER_ELEMENT===4,i.length){if(o.nativeIndexBuffer=this._native.createIndexBuffer(i,n!=null&&n),o.nativeVertexBuffer===this.INVALID_HANDLE)throw new Error("Could not create a native index buffer.")}else o.nativeVertexBuffer=this.INVALID_HANDLE;return o},t.prototype.createVertexBuffer=function(e,n){var i=new cu;if(i.references=1,i.nativeVertexBuffer=this._native.createVertexBuffer(ArrayBuffer.isView(e)?e:new Float32Array(e),n!=null&&n),i.nativeVertexBuffer===this.INVALID_HANDLE)throw new Error("Could not create a native vertex buffer.");return i},t.prototype._recordVertexArrayObject=function(e,n,i,o){i&&this._native.recordIndexBuffer(e,i.nativeIndexBuffer);for(var a=o.getAttributesNames(),s=0;s<a.length;s++){var d=o.getAttributeLocation(s);if(d>=0){var p=n[a[s]];if(p){var b=p.getBuffer();b&&this._native.recordVertexBuffer(e,b.nativeVertexBuffer,d,p.byteOffset,p.byteStride,p.getSize(),this._getNativeAttribType(p.type),p.normalized)}}}},t.prototype.bindBuffers=function(e,n,i){this._boundBuffersVertexArray&&this._native.deleteVertexArray(this._boundBuffersVertexArray),this._boundBuffersVertexArray=this._native.createVertexArray(),this._recordVertexArrayObject(this._boundBuffersVertexArray,e,n,i),this._native.bindVertexArray(this._boundBuffersVertexArray)},t.prototype.recordVertexArrayObject=function(e,n,i){var o=this._native.createVertexArray();return this._recordVertexArrayObject(o,e,n,i),o},t.prototype.bindVertexArrayObject=function(e){this._native.bindVertexArray(e)},t.prototype.releaseVertexArrayObject=function(e){this._native.deleteVertexArray(e)},t.prototype.getAttributes=function(e,n){var i=e;return this._native.getAttributes(i.nativeProgram,n)},t.prototype.drawElementsType=function(e,n,i,o){this._drawCalls.addCount(1,!1),this._native.drawIndexed(e,n,i)},t.prototype.drawArraysType=function(e,n,i,o){this._drawCalls.addCount(1,!1),this._native.draw(e,n,i)},t.prototype.createPipelineContext=function(){return new sp},t.prototype._preparePipelineContext=function(e,n,i,o,a,s,d){var p=e;p.nativeProgram=o?this.createRawShaderProgram(e,n,i,void 0,d):this.createShaderProgram(e,n,i,s,void 0,d)},t.prototype._isRenderingStateCompiled=function(e){return!0},t.prototype._executeWhenRenderingStateIsCompiled=function(e,n){n()},t.prototype.createRawShaderProgram=function(e,n,i,o,a){throw new Error("Not Supported")},t.prototype.createShaderProgram=function(e,n,i,o,a,s){this.onBeforeShaderCompilationObservable.notifyObservers(this);var d=new Ps(n);d.processCode(),n=d.code;var p=new Ps(i);p.processCode(),i=p.code,n=Bt.a._ConcatenateShader(n,o),i=Bt.a._ConcatenateShader(i,o);var b=this._native.createProgram(n,i);return this.onAfterShaderCompilationObservable.notifyObservers(this),b},t.prototype._setProgram=function(e){this._currentProgram!==e&&(this._native.setProgram(e),this._currentProgram=e)},t.prototype._releaseEffect=function(e){},t.prototype._deletePipelineContext=function(e){},t.prototype.getUniforms=function(e,n){var i=e;return this._native.getUniforms(i.nativeProgram,n)},t.prototype.bindUniformBlock=function(e,n,i){throw new Error("Not Implemented")},t.prototype.bindSamplers=function(e){var n=e.getPipelineContext();this._setProgram(n.nativeProgram);for(var i=e.getSamplers(),o=0;o<i.length;o++){var a=e.getUniform(i[o]);a&&(this._boundUniforms[o]=a)}this._currentEffect=null},t.prototype.setMatrix=function(e,n){e&&this._native.setMatrix(e,n.toArray())},t.prototype.getRenderWidth=function(e){return e===void 0&&(e=!1),!e&&this._currentRenderTarget?this._currentRenderTarget.width:this._native.getRenderWidth()},t.prototype.getRenderHeight=function(e){return e===void 0&&(e=!1),!e&&this._currentRenderTarget?this._currentRenderTarget.height:this._native.getRenderHeight()},t.prototype.setViewport=function(e,n,i){this._cachedViewport=e,this._native.setViewPort(e.x,e.y,e.width,e.height)},t.prototype.setState=function(e,n,i,o){n===void 0&&(n=0),o===void 0&&(o=!1),this._native.setState(e,n,o)},t.prototype.setZOffset=function(e){this._native.setZOffset(e)},t.prototype.getZOffset=function(){return this._native.getZOffset()},t.prototype.setDepthBuffer=function(e){this._native.setDepthTest(e?this._currentDepthTest:this._native.DEPTH_TEST_ALWAYS)},t.prototype.getDepthWrite=function(){return this._native.getDepthWrite()},t.prototype.setDepthFunctionToGreater=function(){this._currentDepthTest=this._native.DEPTH_TEST_GREATER,this._native.setDepthTest(this._currentDepthTest)},t.prototype.setDepthFunctionToGreaterOrEqual=function(){this._currentDepthTest=this._native.DEPTH_TEST_GEQUAL,this._native.setDepthTest(this._currentDepthTest)},t.prototype.setDepthFunctionToLess=function(){this._currentDepthTest=this._native.DEPTH_TEST_LESS,this._native.setDepthTest(this._currentDepthTest)},t.prototype.setDepthFunctionToLessOrEqual=function(){this._currentDepthTest=this._native.DEPTH_TEST_LEQUAL,this._native.setDepthTest(this._currentDepthTest)},t.prototype.setDepthWrite=function(e){this._native.setDepthWrite(e)},t.prototype.setColorWrite=function(e){this._native.setColorWrite(e),this._colorWrite=e},t.prototype.getColorWrite=function(){return this._colorWrite},t.prototype.setAlphaConstants=function(e,n,i,o){throw new Error("Setting alpha blend constant color not yet implemented.")},t.prototype.setAlphaMode=function(e,n){n===void 0&&(n=!1),this._alphaMode!==e&&(e=this._getNativeAlphaMode(e),this._native.setBlendMode(e),n||this.setDepthWrite(e===h.a.ALPHA_DISABLE),this._alphaMode=e)},t.prototype.getAlphaMode=function(){return this._alphaMode},t.prototype.setInt=function(e,n){return!!e&&(this._native.setInt(e,n),!0)},t.prototype.setIntArray=function(e,n){return!!e&&(this._native.setIntArray(e,n),!0)},t.prototype.setIntArray2=function(e,n){return!!e&&(this._native.setIntArray2(e,n),!0)},t.prototype.setIntArray3=function(e,n){return!!e&&(this._native.setIntArray3(e,n),!0)},t.prototype.setIntArray4=function(e,n){return!!e&&(this._native.setIntArray4(e,n),!0)},t.prototype.setFloatArray=function(e,n){return!!e&&(this._native.setFloatArray(e,n),!0)},t.prototype.setFloatArray2=function(e,n){return!!e&&(this._native.setFloatArray2(e,n),!0)},t.prototype.setFloatArray3=function(e,n){return!!e&&(this._native.setFloatArray3(e,n),!0)},t.prototype.setFloatArray4=function(e,n){return!!e&&(this._native.setFloatArray4(e,n),!0)},t.prototype.setArray=function(e,n){return!!e&&(this._native.setFloatArray(e,n),!0)},t.prototype.setArray2=function(e,n){return!!e&&(this._native.setFloatArray2(e,n),!0)},t.prototype.setArray3=function(e,n){return!!e&&(this._native.setFloatArray3(e,n),!0)},t.prototype.setArray4=function(e,n){return!!e&&(this._native.setFloatArray4(e,n),!0)},t.prototype.setMatrices=function(e,n){return!!e&&(this._native.setMatrices(e,n),!0)},t.prototype.setMatrix3x3=function(e,n){return!!e&&(this._native.setMatrix3x3(e,n),!0)},t.prototype.setMatrix2x2=function(e,n){return!!e&&(this._native.setMatrix2x2(e,n),!0)},t.prototype.setFloat=function(e,n){return!!e&&(this._native.setFloat(e,n),!0)},t.prototype.setFloat2=function(e,n,i){return!!e&&(this._native.setFloat2(e,n,i),!0)},t.prototype.setFloat3=function(e,n,i,o){return!!e&&(this._native.setFloat3(e,n,i,o),!0)},t.prototype.setFloat4=function(e,n,i,o,a){return!!e&&(this._native.setFloat4(e,n,i,o,a),!0)},t.prototype.setColor3=function(e,n){return!!e&&(this._native.setFloat3(e,n.r,n.g,n.b),!0)},t.prototype.setColor4=function(e,n,i){return!!e&&(this._native.setFloat4(e,n.r,n.g,n.b,i),!0)},t.prototype.wipeCaches=function(e){this.preventCacheWipeBetweenFrames||(this.resetTextureCache(),this._currentEffect=null,e&&(this._currentProgram=null,this._stencilState.reset(),this._depthCullingState.reset(),this._alphaState.reset()),this._cachedVertexBuffers=null,this._cachedIndexBuffer=null,this._cachedEffectForVertexBuffers=null)},t.prototype._createTexture=function(){return this._native.createTexture()},t.prototype._deleteTexture=function(e){this._native.deleteTexture(e)},t.prototype.updateDynamicTexture=function(e,n,i,o,a){this.createTexture("data:my_image_name",!0,i,null,we.a.BILINEAR_SAMPLINGMODE,void 0,void 0,"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAgAAAAICAYAAADED76LAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAAYSURBVChTY/z//z8DPsAEpXGC4aCAgQEAGGMDDWwwgqsAAAAASUVORK5CYII=",e,t.TEXTUREFORMAT_RGBA,null,void 0)},t.prototype.createTexture=function(e,n,i,o,a,s,d,p,b,P,O,B,F){var z=this;a===void 0&&(a=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),s===void 0&&(s=null),d===void 0&&(d=null),p===void 0&&(p=null),b===void 0&&(b=null),P===void 0&&(P=null),O===void 0&&(O=null);var J=(e=e||"").substr(0,5)==="data:",ie=J&&e.indexOf(";base64,")!==-1,se=b||new Ct.a(this,Ct.b.Url),ce=e;!this._transformTextureUrl||ie||b||p||(e=this._transformTextureUrl(e));for(var ue=e.lastIndexOf("."),fe=O||(ue>-1?e.substring(ue).toLowerCase():""),ve=null,Te=0,Re=Ue.a._TextureLoaders;Te<Re.length;Te++){var Ae=Re[Te];if(Ae.canLoad(fe)){ve=Ae;break}}o&&o._addPendingData(se),se.url=e,se.generateMipMaps=!n,se.samplingMode=a,se.invertY=i,this.doNotHandleContextLost||(se._buffer=p);var Ee=null;if(s&&!b&&(Ee=se.onLoadedObservable.add(s)),b||this._internalTexturesCache.push(se),ve)throw new Error("Loading textures from IInternalTextureLoader not yet implemented.");var Se=function(Le){var xe=se._webGLTexture;xe?z._native.loadTexture(xe,Le,!n,i,function(){se.baseWidth=z._native.getTextureWidth(xe),se.baseHeight=z._native.getTextureHeight(xe),se.width=se.baseWidth,se.height=se.baseHeight,se.isReady=!0;var Ne=z._getNativeSamplingMode(a);z._native.setTextureSampling(xe,Ne),o&&o._removePendingData(se),se.onLoadedObservable.notifyObservers(se),se.onLoadedObservable.clear()},function(){throw new Error("Could not load a native texture.")}):o&&o._removePendingData(se)};if(J)if(p instanceof ArrayBuffer)Se(new Uint8Array(p));else if(ArrayBuffer.isView(p))Se(p);else{if(typeof p!="string")throw new Error("Unsupported buffer type");Se(new Uint8Array(Xe.b.DecodeBase64(p)))}else ie?Se(new Uint8Array(Xe.b.DecodeBase64(e))):this._loadFile(e,function(Le){return Se(new Uint8Array(Le))},void 0,void 0,!0,function(Le,xe){(function(Ne,Ie){o&&o._removePendingData(se),e===ce?(Ee&&se.onLoadedObservable.remove(Ee),te.a.UseFallbackTexture&&z.createTexture(te.a.FallbackTexture,n,se.invertY,o,a,null,d,p,se),d&&d((Ne||"Unknown error")+(te.a.UseFallbackTexture?" - Fallback texture was used":""),Ie)):(l.a.Warn("Failed to load "+e+", falling back to "+ce),z.createTexture(ce,n,se.invertY,o,a,s,d,p,se,P,O,B,F))})("Unable to load "+(Le&&Le.responseURL,xe))});return se},t.prototype._createDepthStencilTexture=function(e,n){var i=new lu(this,Ct.b.Depth),o=e.width||e,a=e.height||e,s=this._native.createDepthTexture(i._webGLTexture,o,a);return i._framebuffer=s,i},t.prototype._releaseFramebufferObjects=function(e){},t.prototype.createCubeTexture=function(e,n,i,o,a,s,d,p,b,P,O,B){var F=this;a===void 0&&(a=null),s===void 0&&(s=null),p===void 0&&(p=null),P===void 0&&(P=0),O===void 0&&(O=0),B===void 0&&(B=null);var z=B||new Ct.a(this,Ct.b.Cube);z.isCube=!0,z.url=e,z.generateMipMaps=!o,z._lodGenerationScale=P,z._lodGenerationOffset=O,this._doNotHandleContextLost||(z._extension=p,z._files=i);var J=e.lastIndexOf(".");if((p||(J>-1?e.substring(J).toLowerCase():""))===".env"){if(i&&i.length===6)throw new Error("Multi-file loading not allowed on env files.");this._loadFile(e,function(se){return function(ce){var ue=Ai.GetEnvInfo(ce);if(z.width=ue.width,z.height=ue.width,Ai.UploadEnvSpherical(z,ue),ue.version!==1)throw new Error('Unsupported babylon environment map version "'+ue.version+'"');var fe=ue.specular;if(!fe)throw new Error("Nothing else parsed so far");z._lodGenerationScale=fe.lodGenerationScale;var ve=Ai.CreateImageDataArrayBufferViews(ce,ue);z.format=h.a.TEXTUREFORMAT_RGBA,z.type=h.a.TEXTURETYPE_UNSIGNED_INT,z.generateMipMaps=!0,z.getEngine().updateTextureSamplingMode(we.a.TRILINEAR_SAMPLINGMODE,z),z._isRGBD=!0,z.invertY=!0,F._native.loadCubeTextureWithMips(z._webGLTexture,ve,function(){z.isReady=!0,a&&a()},function(){throw new Error("Could not load a native cube texture.")})}(new Uint8Array(se))},void 0,void 0,!0,function(se,ce){s&&se&&s(se.status+" "+se.statusText,ce)})}else{if(!i||i.length!==6)throw new Error("Cannot load cubemap because 6 files were not defined");var ie=[i[0],i[3],i[1],i[4],i[2],i[5]];Promise.all(ie.map(function(se){return Xe.b.LoadFileAsync(se).then(function(ce){return new Uint8Array(ce)})})).then(function(se){return new Promise(function(ce,ue){F._native.loadCubeTexture(z._webGLTexture,se,!o,ce,ue)})}).then(function(){z.isReady=!0,a&&a()},function(se){s&&s("Failed to load cubemap: "+se.message,se)})}return this._internalTexturesCache.push(z),z},t.prototype.createRenderTargetTexture=function(e,n){var i=new Dl.a;n!==void 0&&typeof n=="object"?(i.generateMipMaps=n.generateMipMaps,i.generateDepthBuffer=n.generateDepthBuffer===void 0||n.generateDepthBuffer,i.generateStencilBuffer=i.generateDepthBuffer&&n.generateStencilBuffer,i.type=n.type===void 0?h.a.TEXTURETYPE_UNSIGNED_INT:n.type,i.samplingMode=n.samplingMode===void 0?h.a.TEXTURE_TRILINEAR_SAMPLINGMODE:n.samplingMode,i.format=n.format===void 0?h.a.TEXTUREFORMAT_RGBA:n.format):(i.generateMipMaps=n,i.generateDepthBuffer=!0,i.generateStencilBuffer=!1,i.type=h.a.TEXTURETYPE_UNSIGNED_INT,i.samplingMode=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,i.format=h.a.TEXTUREFORMAT_RGBA),(i.type!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloatLinearFiltering)&&(i.type!==h.a.TEXTURETYPE_HALF_FLOAT||this._caps.textureHalfFloatLinearFiltering)||(i.samplingMode=h.a.TEXTURE_NEAREST_SAMPLINGMODE);var o=new lu(this,Ct.b.RenderTarget),a=e.width||e,s=e.height||e;i.type!==h.a.TEXTURETYPE_FLOAT||this._caps.textureFloat||(i.type=h.a.TEXTURETYPE_UNSIGNED_INT,l.a.Warn("Float textures are not supported. Render target forced to TEXTURETYPE_UNSIGNED_BYTE type"));var d=this._native.createFramebuffer(o._webGLTexture,a,s,this._getNativeTextureFormat(i.format,i.type),i.samplingMode,!!i.generateStencilBuffer,i.generateDepthBuffer,!!i.generateMipMaps);return o._framebuffer=d,o.baseWidth=a,o.baseHeight=s,o.width=a,o.height=s,o.isReady=!0,o.samples=1,o.generateMipMaps=!!i.generateMipMaps,o.samplingMode=i.samplingMode,o.type=i.type,o.format=i.format,o._generateDepthBuffer=i.generateDepthBuffer,o._generateStencilBuffer=!!i.generateStencilBuffer,this._internalTexturesCache.push(o),o},t.prototype.updateTextureSamplingMode=function(e,n){if(n._webGLTexture){var i=this._getNativeSamplingMode(e);this._native.setTextureSampling(n._webGLTexture,i)}n.samplingMode=e},t.prototype.bindFramebuffer=function(e,n,i,o,a){if(n)throw new Error("Cuboid frame buffers are not yet supported in NativeEngine.");if(i||o)throw new Error("Required width/height for frame buffers not yet supported in NativeEngine.");e._depthStencilTexture?this._bindUnboundFramebuffer(e._depthStencilTexture._framebuffer):this._bindUnboundFramebuffer(e._framebuffer)},t.prototype.unBindFramebuffer=function(e,n,i){n===void 0&&(n=!1),n&&l.a.Warn("Disabling mipmap generation not yet supported in NativeEngine. Ignoring."),i&&i(),this._bindUnboundFramebuffer(null)},t.prototype.createDynamicVertexBuffer=function(e){return this.createVertexBuffer(e,!0)},t.prototype.updateDynamicIndexBuffer=function(e,n,i){i===void 0&&(i=0);var o=e,a=this._normalizeIndexData(n);o.is32Bits=a.BYTES_PER_ELEMENT===4,this._native.updateDynamicIndexBuffer(o.nativeIndexBuffer,a,i)},t.prototype.updateDynamicVertexBuffer=function(e,n,i,o){var a=e,s=ArrayBuffer.isView(n)?n:new Float32Array(n);this._native.updateDynamicVertexBuffer(a.nativeVertexBuffer,s,i??0,o??s.byteLength)},t.prototype._setTexture=function(e,n,i,o){o===void 0&&(o=!1);var a,s=this._boundUniforms[e];if(!s)return!1;if(!n)return this._boundTexturesCache[e]!=null&&(this._activeChannel=e,this._native.setTexture(s,null)),!1;if(n.video)this._activeChannel=e,n.update();else if(n.delayLoadState===h.a.DELAYLOADSTATE_NOTLOADED)return n.delayLoad(),!1;return a=o?n.depthStencilTexture:n.isReady()?n.getInternalTexture():n.isCube?this.emptyCubeTexture:n.is3D?this.emptyTexture3D:n.is2DArray?this.emptyTexture2DArray:this.emptyTexture,this._activeChannel=e,!(!a||!a._webGLTexture)&&(this._native.setTextureWrapMode(a._webGLTexture,this._getAddressMode(n.wrapU),this._getAddressMode(n.wrapV),this._getAddressMode(n.wrapR)),this._updateAnisotropicLevel(n),this._native.setTexture(s,a._webGLTexture),!0)},t.prototype._updateAnisotropicLevel=function(e){var n=e.getInternalTexture(),i=e.anisotropicFilteringLevel;n&&n._webGLTexture&&n._cachedAnisotropicFilteringLevel!==i&&(this._native.setTextureAnisotropicLevel(n._webGLTexture,i),n._cachedAnisotropicFilteringLevel=i)},t.prototype._getAddressMode=function(e){switch(e){case h.a.TEXTURE_WRAP_ADDRESSMODE:return this._native.ADDRESS_MODE_WRAP;case h.a.TEXTURE_CLAMP_ADDRESSMODE:return this._native.ADDRESS_MODE_CLAMP;case h.a.TEXTURE_MIRROR_ADDRESSMODE:return this._native.ADDRESS_MODE_MIRROR;default:throw new Error("Unexpected wrap mode: "+e+".")}},t.prototype._bindTexture=function(e,n){var i=this._boundUniforms[e];i&&this._native.setTexture(i,n._webGLTexture)},t.prototype._deleteBuffer=function(e){e.nativeIndexBuffer&&(this._native.deleteIndexBuffer(e.nativeIndexBuffer),delete e.nativeIndexBuffer),e.nativeVertexBuffer&&(this._native.deleteVertexBuffer(e.nativeVertexBuffer),delete e.nativeVertexBuffer)},t.prototype.releaseEffects=function(){},t.prototype._uploadCompressedDataToTextureDirectly=function(e,n,i,o,a,s,d){throw new Error("_uploadCompressedDataToTextureDirectly not implemented.")},t.prototype._uploadDataToTextureDirectly=function(e,n,i,o){throw new Error("_uploadDataToTextureDirectly not implemented.")},t.prototype._uploadArrayBufferViewToTexture=function(e,n,i,o){throw new Error("_uploadArrayBufferViewToTexture not implemented.")},t.prototype._uploadImageToTexture=function(e,n,i,o){throw new Error("_uploadArrayBufferViewToTexture not 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Object(c.d)(t,r),t.prototype.initControllerMesh=function(e,n){var i,o=this;i=this.hand==="left"?t.MODEL_LEFT_FILENAME:t.MODEL_RIGHT_FILENAME,Ut.ImportMesh("",t._IsQuest?t.QUEST_MODEL_BASE_URL:t.MODEL_BASE_URL,i,e,function(a){o._defaultModel=t._IsQuest?a[0]:a[1],o.attachToMesh(o._defaultModel),n&&n(o._defaultModel)})},Object.defineProperty(t.prototype,"onAButtonStateChangedObservable",{get:function(){if(this.hand==="right")return this.onMainButtonStateChangedObservable;throw new Error("No A button on left hand")},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onBButtonStateChangedObservable",{get:function(){if(this.hand==="right")return this.onSecondaryButtonStateChangedObservable;throw new Error("No B button on left hand")},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onXButtonStateChangedObservable",{get:function(){if(this.hand==="left")return this.onMainButtonStateChangedObservable;throw new Error("No X button on right hand")},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onYButtonStateChangedObservable",{get:function(){if(this.hand==="left")return this.onSecondaryButtonStateChangedObservable;throw new Error("No Y button on right hand")},enumerable:!1,configurable:!0}),t.prototype._handleButtonChange=function(e,n,i){var o=n,a=this.hand==="right"?-1:1;switch(e){case 0:return void this.onPadStateChangedObservable.notifyObservers(o);case 1:return!t._IsQuest&&this._defaultModel&&(this._defaultModel.getChildren()[3].rotation.x=.2*-o.value,this._defaultModel.getChildren()[3].position.y=.005*-o.value,this._defaultModel.getChildren()[3].position.z=.005*-o.value),void this.onTriggerStateChangedObservable.notifyObservers(o);case 2:return!t._IsQuest&&this._defaultModel&&(this._defaultModel.getChildren()[4].position.x=a*o.value*.0035),void this.onSecondaryTriggerStateChangedObservable.notifyObservers(o);case 3:return!t._IsQuest&&this._defaultModel&&(o.pressed?this._defaultModel.getChildren()[1].position.y=-.001:this._defaultModel.getChildren()[1].position.y=0),void this.onMainButtonStateChangedObservable.notifyObservers(o);case 4:return!t._IsQuest&&this._defaultModel&&(o.pressed?this._defaultModel.getChildren()[2].position.y=-.001:this._defaultModel.getChildren()[2].position.y=0),void this.onSecondaryButtonStateChangedObservable.notifyObservers(o);case 5:return void this.onThumbRestChangedObservable.notifyObservers(o)}},t.MODEL_BASE_URL="https://controllers.babylonjs.com/oculus/",t.MODEL_LEFT_FILENAME="left.babylon",t.MODEL_RIGHT_FILENAME="right.babylon",t.QUEST_MODEL_BASE_URL="https://controllers.babylonjs.com/oculusQuest/",t._IsQuest=!1,t}(Bi);wi._ControllerFactories.push({canCreate:function(r){return Ue.a.LastCreatedEngine&&Ue.a.LastCreatedEngine._vrDisplay&&Ue.a.LastCreatedEngine._vrDisplay.displayName==="Oculus Quest"&&(Os._IsQuest=!0),r.id.indexOf("Oculus Touch")!==-1},create:function(r){return new Os(r)}});var uu=function(r){function t(e){var n=r.call(this,e)||this;return n.controllerType=ii.VIVE,n._invertLeftStickY=!0,n}return Object(c.d)(t,r),t.prototype.initControllerMesh=function(e,n){var i=this;Ut.ImportMesh("",t.MODEL_BASE_URL,t.MODEL_FILENAME,e,function(o){i._defaultModel=o[1],i.attachToMesh(i._defaultModel),n&&n(i._defaultModel)})},Object.defineProperty(t.prototype,"onLeftButtonStateChangedObservable",{get:function(){return this.onMainButtonStateChangedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onRightButtonStateChangedObservable",{get:function(){return this.onMainButtonStateChangedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onMenuButtonStateChangedObservable",{get:function(){return this.onSecondaryButtonStateChangedObservable},enumerable:!1,configurable:!0}),t.prototype._handleButtonChange=function(e,n,i){var o=n;switch(e){case 0:return void this.onPadStateChangedObservable.notifyObservers(o);case 1:return this._defaultModel&&(this._defaultModel.getChildren()[6].rotation.x=.15*-o.value),void this.onTriggerStateChangedObservable.notifyObservers(o);case 2:return void this.onMainButtonStateChangedObservable.notifyObservers(o);case 3:return this._defaultModel&&(o.pressed?this._defaultModel.getChildren()[2].position.y=-.001:this._defaultModel.getChildren()[2].position.y=0),void this.onSecondaryButtonStateChangedObservable.notifyObservers(o)}},t.MODEL_BASE_URL="https://controllers.babylonjs.com/vive/",t.MODEL_FILENAME="wand.babylon",t}(Bi);wi._ControllerFactories.push({canCreate:function(r){return r.id.toLowerCase().indexOf("openvr")!==-1},create:function(r){return new uu(r)}});var hp=function(){this.buttonMeshes={},this.axisMeshes={}},Xo=function(r){function t(e){var n=r.call(this,e)||this;return n._mapping={buttons:["thumbstick","trigger","grip","menu","trackpad"],buttonMeshNames:{trigger:"SELECT",menu:"MENU",grip:"GRASP",thumbstick:"THUMBSTICK_PRESS",trackpad:"TOUCHPAD_PRESS"},buttonObservableNames:{trigger:"onTriggerStateChangedObservable",menu:"onSecondaryButtonStateChangedObservable",grip:"onMainButtonStateChangedObservable",thumbstick:"onPadStateChangedObservable",trackpad:"onTrackpadChangedObservable"},axisMeshNames:["THUMBSTICK_X","THUMBSTICK_Y","TOUCHPAD_TOUCH_X","TOUCHPAD_TOUCH_Y"],pointingPoseMeshName:pr.POINTING_POSE},n.onTrackpadChangedObservable=new C.c,n.onTrackpadValuesChangedObservable=new C.c,n.trackpad={x:0,y:0},n.controllerType=ii.WINDOWS,n._loadedMeshInfo=null,n}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"onTriggerButtonStateChangedObservable",{get:function(){return this.onTriggerStateChangedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onMenuButtonStateChangedObservable",{get:function(){return this.onSecondaryButtonStateChangedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onGripButtonStateChangedObservable",{get:function(){return this.onMainButtonStateChangedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onThumbstickButtonStateChangedObservable",{get:function(){return this.onPadStateChangedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onTouchpadButtonStateChangedObservable",{get:function(){return this.onTrackpadChangedObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onTouchpadValuesChangedObservable",{get:function(){return this.onTrackpadValuesChangedObservable},enumerable:!1,configurable:!0}),t.prototype._updateTrackpad=function(){!this.browserGamepad.axes||this.browserGamepad.axes[2]==this.trackpad.x&&this.browserGamepad.axes[3]==this.trackpad.y||(this.trackpad.x=this.browserGamepad.axes[this._mapping.axisMeshNames.indexOf("TOUCHPAD_TOUCH_X")],this.trackpad.y=this.browserGamepad.axes[this._mapping.axisMeshNames.indexOf("TOUCHPAD_TOUCH_Y")],this.onTrackpadValuesChangedObservable.notifyObservers(this.trackpad))},t.prototype.update=function(){if(r.prototype.update.call(this),this.browserGamepad.axes&&(this._updateTrackpad(),this._loadedMeshInfo))for(var e=0;e<this._mapping.axisMeshNames.length;e++)this._lerpAxisTransform(e,this.browserGamepad.axes[e])},t.prototype._handleButtonChange=function(e,n,i){var o=this._mapping.buttons[e];if(o){this._updateTrackpad();var a=this[this._mapping.buttonObservableNames[o]];a&&a.notifyObservers(n),this._lerpButtonTransform(o,n.value)}},t.prototype._lerpButtonTransform=function(e,n){if(this._loadedMeshInfo){var i=this._loadedMeshInfo.buttonMeshes[e];i&&i.unpressed.rotationQuaternion&&i.pressed.rotationQuaternion&&i.value.rotationQuaternion&&(u.b.SlerpToRef(i.unpressed.rotationQuaternion,i.pressed.rotationQuaternion,n,i.value.rotationQuaternion),u.e.LerpToRef(i.unpressed.position,i.pressed.position,n,i.value.position))}},t.prototype._lerpAxisTransform=function(e,n){if(this._loadedMeshInfo){var i=this._loadedMeshInfo.axisMeshes[e];if(i&&i.min.rotationQuaternion&&i.max.rotationQuaternion&&i.value.rotationQuaternion){var o=.5*n+.5;u.b.SlerpToRef(i.min.rotationQuaternion,i.max.rotationQuaternion,o,i.value.rotationQuaternion),u.e.LerpToRef(i.min.position,i.max.position,o,i.value.position)}}},t.prototype.initControllerMesh=function(e,n,i){var o,a,s=this;if(i===void 0&&(i=!1),Ut.IsPluginForExtensionAvailable(".glb")){var d="default";if(this.id&&!i){var p=this.id.match(t.GAMEPAD_ID_PATTERN);d=p&&p[0]||d}a=this.hand==="left"?t.MODEL_LEFT_FILENAME:t.MODEL_RIGHT_FILENAME,o=t.MODEL_BASE_URL+d+"/"}else l.a.Warn("You need to reference GLTF loader to load Windows Motion Controllers model. Falling back to generic models"),o=Wo.MODEL_BASE_URL,a=Wo.MODEL_FILENAME;Ut.ImportMesh("",o,a,e,function(b){s._loadedMeshInfo=s.processModel(e,b),s._loadedMeshInfo&&(s._defaultModel=s._loadedMeshInfo.rootNode,s.attachToMesh(s._defaultModel),n&&n(s._defaultModel))},null,function(b,P){l.a.Log(P),l.a.Warn("Failed to retrieve controller model from the remote server: "+o+a),i||s.initControllerMesh(b,n,!0)})},t.prototype.processModel=function(e,n){for(var i=null,o=new De.a(this.id+" "+this.hand,e),a=null,s=0;s<n.length;s++){var d=n[s];if(!d.parent){d.isPickable=!1,a=d;break}}return a?(a.setParent(o),i=this.createMeshInfo(o)):l.a.Warn("Could not find root node in model file."),i},t.prototype.createMeshInfo=function(e){var n,i=new hp;for(i.rootNode=e,i.buttonMeshes={},i.axisMeshes={},n=0;n<this._mapping.buttons.length;n++){var o=this._mapping.buttonMeshNames[this._mapping.buttons[n]];if(o){var a=P(e,o);if(a){var s={index:n,value:O(a,"VALUE"),pressed:O(a,"PRESSED"),unpressed:O(a,"UNPRESSED")};s.value&&s.pressed&&s.unpressed?i.buttonMeshes[this._mapping.buttons[n]]=s:l.a.Warn("Missing button submesh under mesh with name: "+o+"(VALUE: "+!!s.value+", PRESSED: "+!!s.pressed+", UNPRESSED:"+!!s.unpressed+")")}else l.a.Warn("Missing button mesh with name: "+o)}else l.a.Log("Skipping unknown button at index: "+n+" with mapped name: "+this._mapping.buttons[n])}for(n=0;n<this._mapping.axisMeshNames.length;n++){var d=this._mapping.axisMeshNames[n];if(d){var p=P(e,d);if(p){var b={index:n,value:O(p,"VALUE"),min:O(p,"MIN"),max:O(p,"MAX")};b.value&&b.min&&b.max?i.axisMeshes[n]=b:l.a.Warn("Missing axis submesh under mesh with name: "+d+"(VALUE: "+!!b.value+", MIN: "+!!b.min+", MAX:"+!!b.max+")")}else l.a.Warn("Missing axis mesh with name: "+d)}else l.a.Log("Skipping unknown axis at index: "+n)}return i.pointingPoseNode=P(e,this._mapping.pointingPoseMeshName),i.pointingPoseNode?this._pointingPoseNode=i.pointingPoseNode:l.a.Warn("Missing pointing pose mesh with name: "+this._mapping.pointingPoseMeshName),i;function P(B,F){return B.getChildren(function(z){return z.name===F},!1)[0]}function O(B,F){return B.getChildren(function(z){return z.name==F},!0)[0]}},t.prototype.getForwardRay=function(e){if(e===void 0&&(e=100),!this._loadedMeshInfo||!this._loadedMeshInfo.pointingPoseNode)return r.prototype.getForwardRay.call(this,e);var n=this._loadedMeshInfo.pointingPoseNode.getWorldMatrix(),i=n.getTranslation(),o=new u.e(0,0,-1),a=u.e.TransformNormal(o,n),s=u.e.Normalize(a);return new fn.a(i,s,e)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onTrackpadChangedObservable.clear(),this.onTrackpadValuesChangedObservable.clear()},t.MODEL_BASE_URL="https://controllers.babylonjs.com/microsoft/",t.MODEL_LEFT_FILENAME="left.glb",t.MODEL_RIGHT_FILENAME="right.glb",t.GAMEPAD_ID_PREFIX="Spatial Controller (Spatial Interaction Source) ",t.GAMEPAD_ID_PATTERN=/([0-9a-zA-Z]+-[0-9a-zA-Z]+)$/,t}(Bi),dp=function(r){function t(e){var n=r.call(this,e)||this;return n._mapping={buttons:["trigger","grip","trackpad","thumbstick","menu"],buttonMeshNames:{trigger:"SELECT",menu:"MENU",grip:"GRASP",thumbstick:"THUMBSTICK_PRESS",trackpad:"TOUCHPAD_PRESS"},buttonObservableNames:{trigger:"onTriggerStateChangedObservable",menu:"onSecondaryButtonStateChangedObservable",grip:"onMainButtonStateChangedObservable",thumbstick:"onThumbstickStateChangedObservable",trackpad:"onTrackpadChangedObservable"},axisMeshNames:["TOUCHPAD_TOUCH_X","TOUCHPAD_TOUCH_Y","THUMBSTICK_X","THUMBSTICK_Y"],pointingPoseMeshName:pr.POINTING_POSE},n.thumbstickValues={x:0,y:0},n.onThumbstickStateChangedObservable=new C.c,n.onThumbstickValuesChangedObservable=new C.c,n.onTrackpadChangedObservable=n.onPadStateChangedObservable,n.onTrackpadValuesChangedObservable=n.onPadValuesChangedObservable,n}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"onThumbstickButtonStateChangedObservable",{get:function(){return this.onThumbstickStateChangedObservable},enumerable:!1,configurable:!0}),t.prototype._updateTrackpad=function(){!this.browserGamepad.axes||this.browserGamepad.axes[2]==this.thumbstickValues.x&&this.browserGamepad.axes[3]==this.thumbstickValues.y||(this.trackpad.x=this.browserGamepad.axes[2],this.trackpad.y=this.browserGamepad.axes[3],this.onThumbstickValuesChangedObservable.notifyObservers(this.trackpad))},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onThumbstickStateChangedObservable.clear(),this.onThumbstickValuesChangedObservable.clear()},t}(Xo);wi._ControllerFactories.push({canCreate:function(r){return r.id.indexOf(Xo.GAMEPAD_ID_PREFIX)===0},create:function(r){return new Xo(r)}});var Yo=f(75),Tr=f(63),wn=f(51),On=f(36),oo=function(r){function t(e,n,i,o,a){var s,d,p,b,P,O,B;n===void 0&&(n=M.a.Gray()),i===void 0&&(i=On.a.DefaultUtilityLayer),o===void 0&&(o=null),a===void 0&&(a=1);var F=r.call(this,i)||this;F._pointerObserver=null,F.snapDistance=0,F.onSnapObservable=new C.c,F.uniformScaling=!1,F.sensitivity=1,F._isEnabled=!0,F._parent=null,F._dragging=!1,F._tmpVector=new u.e,F._tmpMatrix=new u.a,F._tmpMatrix2=new u.a,F._parent=o,F._coloredMaterial=new Ft.a("",i.utilityLayerScene),F._coloredMaterial.diffuseColor=n,F._coloredMaterial.specularColor=n.subtract(new M.a(.1,.1,.1)),F._hoverMaterial=new Ft.a("",i.utilityLayerScene),F._hoverMaterial.diffuseColor=M.a.Yellow(),F._disableMaterial=new Ft.a("",i.utilityLayerScene),F._disableMaterial.diffuseColor=M.a.Gray(),F._disableMaterial.alpha=.4,F._gizmoMesh=new De.a("axis",i.utilityLayerScene);var z=F._createGizmoMesh(F._gizmoMesh,a),J=z.arrowMesh,ie=z.arrowTail,se=F._createGizmoMesh(F._gizmoMesh,a+4,!0);F._gizmoMesh.lookAt(F._rootMesh.position.add(e)),F._rootMesh.addChild(F._gizmoMesh),F._gizmoMesh.scaling.scaleInPlace(1/3);var ce=J.position.clone(),ue=ie.position.clone(),fe=ie.scaling.clone(),ve=function(xe){var Ne=xe*(3/F._rootMesh.scaling.length())*6;J.position.z+=Ne/3.5,ie.scaling.y+=Ne,ie.position.z=J.position.z/2},Te=function(){J.position.set(ce.x,ce.y,ce.z),ie.position.set(ue.x,ue.y,ue.z),ie.scaling.set(fe.x,fe.y,fe.z),F._dragging=!1};F.dragBehavior=new yi.a({dragAxis:e}),F.dragBehavior.moveAttached=!1,F._rootMesh.addBehavior(F.dragBehavior);var Re=0,Ae=new u.e,Ee={snapDistance:0};F.dragBehavior.onDragObservable.add(function(xe){if(F.attachedNode){var Ne=F.sensitivity*xe.dragDistance*(3*F.scaleRatio/F._rootMesh.scaling.length()),Ie=!1,Fe=0;F.uniformScaling?(F.attachedNode.getWorldMatrix().decompose(Ae),Ae.normalize(),Ae.y<0&&Ae.scaleInPlace(-1)):Ae.copyFrom(e),F.snapDistance==0?Ae.scaleToRef(Ne,Ae):(Re+=Ne,Math.abs(Re)>F.snapDistance?(Fe=Math.floor(Math.abs(Re)/F.snapDistance),Re<0&&(Fe*=-1),Re%=F.snapDistance,Ae.scaleToRef(F.snapDistance*Fe,Ae),Ie=!0):Ae.scaleInPlace(0)),u.a.ScalingToRef(1+Ae.x,1+Ae.y,1+Ae.z,F._tmpMatrix2),F._tmpMatrix2.multiplyToRef(F.attachedNode.getWorldMatrix(),F._tmpMatrix),F._tmpMatrix.decompose(F._tmpVector),Math.abs(F._tmpVector.x)<1e5&&Math.abs(F._tmpVector.y)<1e5&&Math.abs(F._tmpVector.z)<1e5&&F.attachedNode.getWorldMatrix().copyFrom(F._tmpMatrix),Ie&&(Ee.snapDistance=F.snapDistance*Fe,F.onSnapObservable.notifyObservers(Ee)),F._matrixChanged()}}),F.dragBehavior.onDragStartObservable.add(function(){F._dragging=!0}),F.dragBehavior.onDragObservable.add(function(xe){return ve(xe.dragDistance)}),F.dragBehavior.onDragEndObservable.add(Te),(p=(d=(s=o?.uniformScaleGizmo)===null||s===void 0?void 0:s.dragBehavior)===null||d===void 0?void 0:d.onDragObservable)===null||p===void 0||p.add(function(xe){return ve(xe.delta.y)}),(O=(P=(b=o?.uniformScaleGizmo)===null||b===void 0?void 0:b.dragBehavior)===null||P===void 0?void 0:P.onDragEndObservable)===null||O===void 0||O.add(Te);var Se={gizmoMeshes:[J,ie],colliderMeshes:[se.arrowMesh,se.arrowTail],material:F._coloredMaterial,hoverMaterial:F._hoverMaterial,disableMaterial:F._disableMaterial,active:!1};(B=F._parent)===null||B===void 0||B.addToAxisCache(F._gizmoMesh,Se),F._pointerObserver=i.utilityLayerScene.onPointerObservable.add(function(xe){var Ne;if(!F._customMeshSet&&(F._isHovered=Se.colliderMeshes.indexOf((Ne=xe?.pickInfo)===null||Ne===void 0?void 0:Ne.pickedMesh)!=-1,!F._parent)){var Ie=F._isHovered||F._dragging?F._hoverMaterial:F._coloredMaterial;Se.gizmoMeshes.forEach(function(Fe){Fe.material=Ie,Fe.color&&(Fe.color=Ie.diffuseColor)})}});var Le=i._getSharedGizmoLight();return Le.includedOnlyMeshes=Le.includedOnlyMeshes.concat(F._rootMesh.getChildMeshes()),F}return Object(c.d)(t,r),t.prototype._createGizmoMesh=function(e,n,i){i===void 0&&(i=!1);var o=Tr.a.CreateBox("yPosMesh",{size:.4*(1+(n-1)/4)},this.gizmoLayer.utilityLayerScene),a=pi.a.CreateCylinder("cylinder",{diameterTop:.005*n,height:.275,diameterBottom:.005*n,tessellation:96},this.gizmoLayer.utilityLayerScene);return o.scaling.scaleInPlace(.1),o.material=this._coloredMaterial,o.rotation.x=Math.PI/2,o.position.z+=.3,a.material=this._coloredMaterial,a.position.z+=.1375,a.rotation.x=Math.PI/2,i&&(o.visibility=0,a.visibility=0),e.addChild(o),e.addChild(a),{arrowMesh:o,arrowTail:a}},t.prototype._attachedNodeChanged=function(e){this.dragBehavior&&(this.dragBehavior.enabled=!!e)},Object.defineProperty(t.prototype,"isEnabled",{get:function(){return this._isEnabled},set:function(e){this._isEnabled=e,e?this._parent&&(this.attachedMesh=this._parent.attachedMesh,this.attachedNode=this._parent.attachedNode):(this.attachedMesh=null,this.attachedNode=null)},enumerable:!1,configurable:!0}),t.prototype.dispose=function(){this.onSnapObservable.clear(),this.gizmoLayer.utilityLayerScene.onPointerObservable.remove(this._pointerObserver),this.dragBehavior.detach(),this._gizmoMesh&&this._gizmoMesh.dispose(),[this._coloredMaterial,this._hoverMaterial,this._disableMaterial].forEach(function(e){e&&e.dispose()}),r.prototype.dispose.call(this)},t.prototype.setCustomMesh=function(e,n){var i=this;n===void 0&&(n=!1),r.prototype.setCustomMesh.call(this,e),n&&(this._rootMesh.getChildMeshes().forEach(function(o){o.material=i._coloredMaterial,o.color&&(o.color=i._coloredMaterial.diffuseColor)}),this._customMeshSet=!1)},t}(wn.a),Fn=f(45),cn=f(40),hu=function(r){function t(e,n){e===void 0&&(e=M.a.Gray()),n===void 0&&(n=On.a.DefaultKeepDepthUtilityLayer);var i=r.call(this,n)||this;i._boundingDimensions=new u.e(1,1,1),i._renderObserver=null,i._pointerObserver=null,i._scaleDragSpeed=.2,i._tmpQuaternion=new u.b,i._tmpVector=new u.e(0,0,0),i._tmpRotationMatrix=new u.a,i.ignoreChildren=!1,i.includeChildPredicate=null,i.rotationSphereSize=.1,i.scaleBoxSize=.1,i.fixedDragMeshScreenSize=!1,i.fixedDragMeshBoundsSize=!1,i.fixedDragMeshScreenSizeDistanceFactor=10,i.onDragStartObservable=new C.c,i.onScaleBoxDragObservable=new C.c,i.onScaleBoxDragEndObservable=new C.c,i.onRotationSphereDragObservable=new C.c,i.onRotationSphereDragEndObservable=new C.c,i.scalePivot=null,i._existingMeshScale=new u.e,i._dragMesh=null,i.pointerDragBehavior=new yi.a,i.updateScale=!1,i._anchorMesh=new Dt.a("anchor",n.utilityLayerScene),i.coloredMaterial=new Ft.a("",n.utilityLayerScene),i.coloredMaterial.disableLighting=!0,i.hoverColoredMaterial=new Ft.a("",n.utilityLayerScene),i.hoverColoredMaterial.disableLighting=!0,i._lineBoundingBox=new Dt.a("",n.utilityLayerScene),i._lineBoundingBox.rotationQuaternion=new u.b;var o=[];o.push(cn.a.CreateLines("lines",{points:[new u.e(0,0,0),new u.e(i._boundingDimensions.x,0,0)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(0,0,0),new u.e(0,i._boundingDimensions.y,0)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(0,0,0),new u.e(0,0,i._boundingDimensions.z)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(i._boundingDimensions.x,0,0),new u.e(i._boundingDimensions.x,i._boundingDimensions.y,0)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(i._boundingDimensions.x,0,0),new u.e(i._boundingDimensions.x,0,i._boundingDimensions.z)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(0,i._boundingDimensions.y,0),new u.e(i._boundingDimensions.x,i._boundingDimensions.y,0)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(0,i._boundingDimensions.y,0),new u.e(0,i._boundingDimensions.y,i._boundingDimensions.z)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(0,0,i._boundingDimensions.z),new u.e(i._boundingDimensions.x,0,i._boundingDimensions.z)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(0,0,i._boundingDimensions.z),new u.e(0,i._boundingDimensions.y,i._boundingDimensions.z)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(i._boundingDimensions.x,i._boundingDimensions.y,i._boundingDimensions.z),new u.e(0,i._boundingDimensions.y,i._boundingDimensions.z)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(i._boundingDimensions.x,i._boundingDimensions.y,i._boundingDimensions.z),new u.e(i._boundingDimensions.x,0,i._boundingDimensions.z)]},n.utilityLayerScene)),o.push(cn.a.CreateLines("lines",{points:[new u.e(i._boundingDimensions.x,i._boundingDimensions.y,i._boundingDimensions.z),new u.e(i._boundingDimensions.x,i._boundingDimensions.y,0)]},n.utilityLayerScene)),o.forEach(function(J){J.color=e,J.position.addInPlace(new u.e(-i._boundingDimensions.x/2,-i._boundingDimensions.y/2,-i._boundingDimensions.z/2)),J.isPickable=!1,i._lineBoundingBox.addChild(J)}),i._rootMesh.addChild(i._lineBoundingBox),i.setColor(e),i._rotateSpheresParent=new Dt.a("",n.utilityLayerScene),i._rotateSpheresParent.rotationQuaternion=new u.b;for(var a=function(J){var ie=Fn.a.CreateSphere("",{diameter:1},n.utilityLayerScene);ie.rotationQuaternion=new u.b,ie.material=s.coloredMaterial,(P=new yi.a({})).moveAttached=!1,P.updateDragPlane=!1,ie.addBehavior(P);var se=new u.e(1,0,0),ce=0;P.onDragStartObservable.add(function(){se.copyFrom(ie.forward),ce=0}),P.onDragObservable.add(function(ue){if(i.onRotationSphereDragObservable.notifyObservers({}),i.attachedMesh){var fe=i.attachedMesh.parent;if(fe&&fe.scaling&&fe.scaling.isNonUniformWithinEpsilon(.001))return void l.a.Warn("BoundingBoxGizmo controls are not supported on child meshes with non-uniform parent scaling");kn.a._RemoveAndStorePivotPoint(i.attachedMesh);var ve=se,Te=ue.dragPlaneNormal.scale(u.e.Dot(ue.dragPlaneNormal,ve)),Re=ve.subtract(Te).normalizeToNew(),Ae=u.e.Dot(Re,ue.delta)<0?Math.abs(ue.delta.length()):-Math.abs(ue.delta.length());Ae=Ae/i._boundingDimensions.length()*i._anchorMesh.scaling.length(),i.attachedMesh.rotationQuaternion||(i.attachedMesh.rotationQuaternion=u.b.RotationYawPitchRoll(i.attachedMesh.rotation.y,i.attachedMesh.rotation.x,i.attachedMesh.rotation.z)),i._anchorMesh.rotationQuaternion||(i._anchorMesh.rotationQuaternion=u.b.RotationYawPitchRoll(i._anchorMesh.rotation.y,i._anchorMesh.rotation.x,i._anchorMesh.rotation.z)),ce+=Ae,Math.abs(ce)<=2*Math.PI&&(J>=8?u.b.RotationYawPitchRollToRef(0,0,Ae,i._tmpQuaternion):J>=4?u.b.RotationYawPitchRollToRef(Ae,0,0,i._tmpQuaternion):u.b.RotationYawPitchRollToRef(0,Ae,0,i._tmpQuaternion),i._anchorMesh.addChild(i.attachedMesh),i._anchorMesh.rotationQuaternion.multiplyToRef(i._tmpQuaternion,i._anchorMesh.rotationQuaternion),i._anchorMesh.removeChild(i.attachedMesh),i.attachedMesh.setParent(fe)),i.updateBoundingBox(),kn.a._RestorePivotPoint(i.attachedMesh)}i._updateDummy()}),P.onDragStartObservable.add(function(){i.onDragStartObservable.notifyObservers({}),i._selectNode(ie)}),P.onDragEndObservable.add(function(){i.onRotationSphereDragEndObservable.notifyObservers({}),i._selectNode(null),i._updateDummy()}),s._rotateSpheresParent.addChild(ie)},s=this,d=0;d<12;d++)a(d);i._rootMesh.addChild(i._rotateSpheresParent),i._scaleBoxesParent=new Dt.a("",n.utilityLayerScene),i._scaleBoxesParent.rotationQuaternion=new u.b;for(var p=0;p<3;p++)for(var b=0;b<3;b++)for(var P,O=function(){var J=(p===1?1:0)+(b===1?1:0)+(F===1?1:0);if(J===1||J===3)return"continue";var ie=Tr.a.CreateBox("",{size:1},n.utilityLayerScene);ie.material=B.coloredMaterial,ie.metadata=J===2;var se=new u.e(p-1,b-1,F-1).normalize();(P=new yi.a({dragAxis:se})).updateDragPlane=!1,P.moveAttached=!1,ie.addBehavior(P),P.onDragObservable.add(function(ce){if(i.onScaleBoxDragObservable.notifyObservers({}),i.attachedMesh){var ue=i.attachedMesh.parent;if(ue&&ue.scaling&&ue.scaling.isNonUniformWithinEpsilon(.001))return void l.a.Warn("BoundingBoxGizmo controls are not supported on child meshes with non-uniform parent scaling");kn.a._RemoveAndStorePivotPoint(i.attachedMesh);var fe=ce.dragDistance/i._boundingDimensions.length()*i._anchorMesh.scaling.length(),ve=new u.e(fe,fe,fe);J===2&&(ve.x*=Math.abs(se.x),ve.y*=Math.abs(se.y),ve.z*=Math.abs(se.z)),ve.scaleInPlace(i._scaleDragSpeed),i.updateBoundingBox(),i.scalePivot?(i.attachedMesh.getWorldMatrix().getRotationMatrixToRef(i._tmpRotationMatrix),i._boundingDimensions.scaleToRef(.5,i._tmpVector),u.e.TransformCoordinatesToRef(i._tmpVector,i._tmpRotationMatrix,i._tmpVector),i._anchorMesh.position.subtractInPlace(i._tmpVector),i._boundingDimensions.multiplyToRef(i.scalePivot,i._tmpVector),u.e.TransformCoordinatesToRef(i._tmpVector,i._tmpRotationMatrix,i._tmpVector),i._anchorMesh.position.addInPlace(i._tmpVector)):(ie.absolutePosition.subtractToRef(i._anchorMesh.position,i._tmpVector),i._anchorMesh.position.subtractInPlace(i._tmpVector)),i._anchorMesh.addChild(i.attachedMesh),i._anchorMesh.scaling.addInPlace(ve),(i._anchorMesh.scaling.x<0||i._anchorMesh.scaling.y<0||i._anchorMesh.scaling.z<0)&&i._anchorMesh.scaling.subtractInPlace(ve),i._anchorMesh.removeChild(i.attachedMesh),i.attachedMesh.setParent(ue),kn.a._RestorePivotPoint(i.attachedMesh)}i._updateDummy()}),P.onDragStartObservable.add(function(){i.onDragStartObservable.notifyObservers({}),i._selectNode(ie)}),P.onDragEndObservable.add(function(){i.onScaleBoxDragEndObservable.notifyObservers({}),i._selectNode(null),i._updateDummy()}),B._scaleBoxesParent.addChild(ie)},B=this,F=0;F<3;F++)O();i._rootMesh.addChild(i._scaleBoxesParent);var z=new Array;return i._pointerObserver=n.utilityLayerScene.onPointerObservable.add(function(J){z[J.event.pointerId]?J.pickInfo&&J.pickInfo.pickedMesh!=z[J.event.pointerId]&&(z[J.event.pointerId].material=i.coloredMaterial,delete z[J.event.pointerId]):i._rotateSpheresParent.getChildMeshes().concat(i._scaleBoxesParent.getChildMeshes()).forEach(function(ie){J.pickInfo&&J.pickInfo.pickedMesh==ie&&(z[J.event.pointerId]=ie,ie.material=i.hoverColoredMaterial)})}),i._renderObserver=i.gizmoLayer.originalScene.onBeforeRenderObservable.add(function(){i.attachedMesh&&!i._existingMeshScale.equals(i.attachedMesh.scaling)?i.updateBoundingBox():(i.fixedDragMeshScreenSize||i.fixedDragMeshBoundsSize)&&(i._updateRotationSpheres(),i._updateScaleBoxes()),i._dragMesh&&i.attachedMesh&&i.pointerDragBehavior.dragging&&(i._lineBoundingBox.position.rotateByQuaternionToRef(i._rootMesh.rotationQuaternion,i._tmpVector),i.attachedMesh.setAbsolutePosition(i._dragMesh.position.add(i._tmpVector.scale(-1))))}),i.updateBoundingBox(),i}return Object(c.d)(t,r),t.prototype.setColor=function(e){this.coloredMaterial.emissiveColor=e,this.hoverColoredMaterial.emissiveColor=e.clone().add(new M.a(.3,.3,.3)),this._lineBoundingBox.getChildren().forEach(function(n){n.color&&(n.color=e)})},t.prototype._attachedNodeChanged=function(e){var n=this;if(e){kn.a._RemoveAndStorePivotPoint(e);var i=e.parent;this._anchorMesh.addChild(e),this._anchorMesh.removeChild(e),e.setParent(i),kn.a._RestorePivotPoint(e),this.updateBoundingBox(),e.getChildMeshes(!1).forEach(function(o){o.markAsDirty("scaling")}),this.gizmoLayer.utilityLayerScene.onAfterRenderObservable.addOnce(function(){n._updateDummy()})}},t.prototype._selectNode=function(e){this._rotateSpheresParent.getChildMeshes().concat(this._scaleBoxesParent.getChildMeshes()).forEach(function(n){n.isVisible=!e||n==e})},t.prototype.updateBoundingBox=function(){if(this.attachedMesh){kn.a._RemoveAndStorePivotPoint(this.attachedMesh);var e=this.attachedMesh.parent;this.attachedMesh.setParent(null);var n=null;this.attachedMesh.skeleton&&(n=this.attachedMesh.skeleton.overrideMesh,this.attachedMesh.skeleton.overrideMesh=null),this._update(),this.attachedMesh.rotationQuaternion||(this.attachedMesh.rotationQuaternion=u.b.RotationYawPitchRoll(this.attachedMesh.rotation.y,this.attachedMesh.rotation.x,this.attachedMesh.rotation.z)),this._anchorMesh.rotationQuaternion||(this._anchorMesh.rotationQuaternion=u.b.RotationYawPitchRoll(this._anchorMesh.rotation.y,this._anchorMesh.rotation.x,this._anchorMesh.rotation.z)),this._anchorMesh.rotationQuaternion.copyFrom(this.attachedMesh.rotationQuaternion),this._tmpQuaternion.copyFrom(this.attachedMesh.rotationQuaternion),this._tmpVector.copyFrom(this.attachedMesh.position),this.attachedMesh.rotationQuaternion.set(0,0,0,1),this.attachedMesh.position.set(0,0,0);var i=this.attachedMesh.getHierarchyBoundingVectors(!this.ignoreChildren,this.includeChildPredicate);i.max.subtractToRef(i.min,this._boundingDimensions),this._lineBoundingBox.scaling.copyFrom(this._boundingDimensions),this._lineBoundingBox.position.set((i.max.x+i.min.x)/2,(i.max.y+i.min.y)/2,(i.max.z+i.min.z)/2),this._rotateSpheresParent.position.copyFrom(this._lineBoundingBox.position),this._scaleBoxesParent.position.copyFrom(this._lineBoundingBox.position),this._lineBoundingBox.computeWorldMatrix(),this._anchorMesh.position.copyFrom(this._lineBoundingBox.absolutePosition),this.attachedMesh.rotationQuaternion.copyFrom(this._tmpQuaternion),this.attachedMesh.position.copyFrom(this._tmpVector),this.attachedMesh.setParent(e),this.attachedMesh.skeleton&&(this.attachedMesh.skeleton.overrideMesh=n)}this._updateRotationSpheres(),this._updateScaleBoxes(),this.attachedMesh&&(this._existingMeshScale.copyFrom(this.attachedMesh.scaling),kn.a._RestorePivotPoint(this.attachedMesh))},t.prototype._updateRotationSpheres=function(){for(var e=this._rotateSpheresParent.getChildMeshes(),n=0;n<3;n++)for(var i=0;i<2;i++)for(var o=0;o<2;o++){var a=4*n+2*i+o;if(n==0&&(e[a].position.set(this._boundingDimensions.x/2,this._boundingDimensions.y*i,this._boundingDimensions.z*o),e[a].position.addInPlace(new u.e(-this._boundingDimensions.x/2,-this._boundingDimensions.y/2,-this._boundingDimensions.z/2)),e[a].lookAt(u.e.Cross(e[a].position.normalizeToNew(),u.e.Right()).normalizeToNew().add(e[a].position))),n==1&&(e[a].position.set(this._boundingDimensions.x*i,this._boundingDimensions.y/2,this._boundingDimensions.z*o),e[a].position.addInPlace(new u.e(-this._boundingDimensions.x/2,-this._boundingDimensions.y/2,-this._boundingDimensions.z/2)),e[a].lookAt(u.e.Cross(e[a].position.normalizeToNew(),u.e.Up()).normalizeToNew().add(e[a].position))),n==2&&(e[a].position.set(this._boundingDimensions.x*i,this._boundingDimensions.y*o,this._boundingDimensions.z/2),e[a].position.addInPlace(new u.e(-this._boundingDimensions.x/2,-this._boundingDimensions.y/2,-this._boundingDimensions.z/2)),e[a].lookAt(u.e.Cross(e[a].position.normalizeToNew(),u.e.Forward()).normalizeToNew().add(e[a].position))),this.fixedDragMeshScreenSize&&this.gizmoLayer.utilityLayerScene.activeCamera){e[a].absolutePosition.subtractToRef(this.gizmoLayer.utilityLayerScene.activeCamera.position,this._tmpVector);var s=this.rotationSphereSize*this._tmpVector.length()/this.fixedDragMeshScreenSizeDistanceFactor;e[a].scaling.set(s,s,s)}else this.fixedDragMeshBoundsSize?e[a].scaling.set(this.rotationSphereSize*this._boundingDimensions.x,this.rotationSphereSize*this._boundingDimensions.y,this.rotationSphereSize*this._boundingDimensions.z):e[a].scaling.set(this.rotationSphereSize,this.rotationSphereSize,this.rotationSphereSize)}},t.prototype._updateScaleBoxes=function(){for(var e=this._scaleBoxesParent.getChildMeshes(),n=0,i=0;i<3;i++)for(var o=0;o<3;o++)for(var a=0;a<3;a++){var s=(i===1?1:0)+(o===1?1:0)+(a===1?1:0);if(s!==1&&s!==3){if(e[n])if(e[n].position.set(this._boundingDimensions.x*(i/2),this._boundingDimensions.y*(o/2),this._boundingDimensions.z*(a/2)),e[n].position.addInPlace(new u.e(-this._boundingDimensions.x/2,-this._boundingDimensions.y/2,-this._boundingDimensions.z/2)),this.fixedDragMeshScreenSize&&this.gizmoLayer.utilityLayerScene.activeCamera){e[n].absolutePosition.subtractToRef(this.gizmoLayer.utilityLayerScene.activeCamera.position,this._tmpVector);var d=this.scaleBoxSize*this._tmpVector.length()/this.fixedDragMeshScreenSizeDistanceFactor;e[n].scaling.set(d,d,d)}else this.fixedDragMeshBoundsSize?e[n].scaling.set(this.scaleBoxSize*this._boundingDimensions.x,this.scaleBoxSize*this._boundingDimensions.y,this.scaleBoxSize*this._boundingDimensions.z):e[n].scaling.set(this.scaleBoxSize,this.scaleBoxSize,this.scaleBoxSize);n++}}},t.prototype.setEnabledRotationAxis=function(e){this._rotateSpheresParent.getChildMeshes().forEach(function(n,i){i<4?n.setEnabled(e.indexOf("x")!=-1):i<8?n.setEnabled(e.indexOf("y")!=-1):n.setEnabled(e.indexOf("z")!=-1)})},t.prototype.setEnabledScaling=function(e,n){n===void 0&&(n=!1),this._scaleBoxesParent.getChildMeshes().forEach(function(i,o){var a=e;n&&i.metadata===!0&&(a=!1),i.setEnabled(a)})},t.prototype._updateDummy=function(){this._dragMesh&&(this._dragMesh.position.copyFrom(this._lineBoundingBox.getAbsolutePosition()),this._dragMesh.scaling.copyFrom(this._lineBoundingBox.scaling),this._dragMesh.rotationQuaternion.copyFrom(this._rootMesh.rotationQuaternion))},t.prototype.enableDragBehavior=function(){this._dragMesh=De.a.CreateBox("dummy",1,this.gizmoLayer.utilityLayerScene),this._dragMesh.visibility=0,this._dragMesh.rotationQuaternion=new u.b,this.pointerDragBehavior.useObjectOrientationForDragging=!1,this._dragMesh.addBehavior(this.pointerDragBehavior)},t.prototype.dispose=function(){this.gizmoLayer.utilityLayerScene.onPointerObservable.remove(this._pointerObserver),this.gizmoLayer.originalScene.onBeforeRenderObservable.remove(this._renderObserver),this._lineBoundingBox.dispose(),this._rotateSpheresParent.dispose(),this._scaleBoxesParent.dispose(),this._dragMesh&&this._dragMesh.dispose(),r.prototype.dispose.call(this)},t.MakeNotPickableAndWrapInBoundingBox=function(e){var n=function(d){d.isPickable=!1,d.getChildMeshes().forEach(function(p){n(p)})};n(e),e.rotationQuaternion||(e.rotationQuaternion=u.b.RotationYawPitchRoll(e.rotation.y,e.rotation.x,e.rotation.z));var i=e.position.clone(),o=e.rotationQuaternion.clone();e.rotationQuaternion.set(0,0,0,1),e.position.set(0,0,0);var a=Tr.a.CreateBox("box",{size:1},e.getScene()),s=e.getHierarchyBoundingVectors();return s.max.subtractToRef(s.min,a.scaling),a.scaling.y===0&&(a.scaling.y=Gt.a),a.scaling.x===0&&(a.scaling.x=Gt.a),a.scaling.z===0&&(a.scaling.z=Gt.a),a.position.set((s.max.x+s.min.x)/2,(s.max.y+s.min.y)/2,(s.max.z+s.min.z)/2),e.addChild(a),e.rotationQuaternion.copyFrom(o),e.position.copyFrom(i),e.removeChild(a),a.addChild(e),a.visibility=0,a},t.prototype.setCustomMesh=function(e){l.a.Error("Custom meshes are not supported on this gizmo")},t}(wn.a),Ko=function(r){function t(e,n,i,o,a,s,d){var p;n===void 0&&(n=M.a.Gray()),i===void 0&&(i=On.a.DefaultUtilityLayer),o===void 0&&(o=32),a===void 0&&(a=null),d===void 0&&(d=1);var b=r.call(this,i)||this;b._pointerObserver=null,b.snapDistance=0,b.onSnapObservable=new C.c,b._isEnabled=!0,b._parent=null,b._dragging=!1,b._parent=a,b._coloredMaterial=new Ft.a("",i.utilityLayerScene),b._coloredMaterial.diffuseColor=n,b._coloredMaterial.specularColor=n.subtract(new M.a(.1,.1,.1)),b._hoverMaterial=new Ft.a("",i.utilityLayerScene),b._hoverMaterial.diffuseColor=M.a.Yellow(),b._disableMaterial=new Ft.a("",i.utilityLayerScene),b._disableMaterial.diffuseColor=M.a.Gray(),b._disableMaterial.alpha=.4,b._gizmoMesh=new De.a("",i.utilityLayerScene);var P=b._createGizmoMesh(b._gizmoMesh,d,o),O=P.rotationMesh,B=P.collider,F=[];b._rotationCircle=b.setupRotationCircle(F,b._gizmoMesh),b._gizmoMesh.lookAt(b._rootMesh.position.add(e)),b._rootMesh.addChild(b._gizmoMesh),b._gizmoMesh.scaling.scaleInPlace(1/3),b.dragBehavior=new yi.a({dragPlaneNormal:e}),b.dragBehavior.moveAttached=!1,b.dragBehavior.maxDragAngle=9*Math.PI/20,b.dragBehavior._useAlternatePickedPointAboveMaxDragAngle=!0,b._rootMesh.addBehavior(b.dragBehavior);var z=0,J=new u.e,ie=new u.e,se=new u.a,ce=new u.e,ue=new u.e;b.dragBehavior.onDragStartObservable.add(function(Se){if(b.attachedNode){J.copyFrom(Se.dragPlanePoint);var Le=new u.e(0,0,1),xe=b._rotationCircle.getDirection(Le);xe.normalize(),b._gizmoMesh.removeChild(b._rotationCircle),J.copyFrom(Se.dragPlanePoint),ie=Se.dragPlanePoint;var Ne=b._rotationCircle.getAbsolutePosition().clone(),Ie=b._rotationCircle.getAbsolutePosition().clone().addInPlace(xe),Fe=Se.dragPlanePoint,Ye=u.e.GetAngleBetweenVectors(Ie.subtract(Ne),Fe.subtract(Ne),b._rotationCircle.up);b._rotationCircle.addRotation(0,Ye,0),b._dragging=!0}}),b.dragBehavior.onDragEndObservable.add(function(){z=0,b.updateRotationCircle(b._rotationCircle,F,z,ie),b._gizmoMesh.addChild(b._rotationCircle),b._dragging=!1});var fe={snapDistance:0},ve=0,Te=new u.a,Re=new u.b;b.dragBehavior.onDragObservable.add(function(Se){if(b.attachedNode){var Le=new u.e(1,1,1),xe=new u.b(0,0,0,1),Ne=new u.e(0,0,0);b.attachedNode.getWorldMatrix().decompose(Le,xe,Ne);var Ie=Se.dragPlanePoint.subtract(Ne).normalize(),Fe=J.subtract(Ne).normalize(),Ye=u.e.Cross(Ie,Fe),tt=u.e.Dot(Ie,Fe),it=Math.atan2(Ye.length(),tt);ce.copyFrom(e),ue.copyFrom(e),b.updateGizmoRotationToMatchAttachedMesh&&(xe.toRotationMatrix(se),ue=u.e.TransformCoordinates(ce,se));var ut=!1;if(i.utilityLayerScene.activeCamera){var Qe=i.utilityLayerScene.activeCamera.position.subtract(Ne);u.e.Dot(Qe,ue)>0&&(ce.scaleInPlace(-1),ue.scaleInPlace(-1),ut=!0)}u.e.Dot(ue,Ye)>0&&(it=-it);var ot=!1;if(b.snapDistance!=0)if(ve+=it,Math.abs(ve)>b.snapDistance){var rt=Math.floor(Math.abs(ve)/b.snapDistance);ve<0&&(rt*=-1),ve%=b.snapDistance,it=b.snapDistance*rt,ot=!0}else it=0;z+=ut?-it:it,b.updateRotationCircle(b._rotationCircle,F,z,ie);var Ze=Math.sin(it/2);if(Re.set(ce.x*Ze,ce.y*Ze,ce.z*Ze,Math.cos(it/2)),Te.determinant()>0){var dt=new u.e;Re.toEulerAnglesToRef(dt),u.b.RotationYawPitchRollToRef(dt.y,-dt.x,-dt.z,Re)}b.updateGizmoRotationToMatchAttachedMesh?xe.multiplyToRef(Re,xe):Re.multiplyToRef(xe,xe),b.attachedNode.getWorldMatrix().copyFrom(u.a.Compose(Le,xe,Ne)),J.copyFrom(Se.dragPlanePoint),ot&&(fe.snapDistance=it,b.onSnapObservable.notifyObservers(fe)),b._matrixChanged()}});var Ae=i._getSharedGizmoLight();Ae.includedOnlyMeshes=Ae.includedOnlyMeshes.concat(b._rootMesh.getChildMeshes(!1));var Ee={colliderMeshes:[B],gizmoMeshes:[O],material:b._coloredMaterial,hoverMaterial:b._hoverMaterial,disableMaterial:b._disableMaterial,active:!1};return(p=b._parent)===null||p===void 0||p.addToAxisCache(b._gizmoMesh,Ee),b._pointerObserver=i.utilityLayerScene.onPointerObservable.add(function(Se){var Le;if(!b._customMeshSet&&(b._isHovered=Ee.colliderMeshes.indexOf((Le=Se?.pickInfo)===null||Le===void 0?void 0:Le.pickedMesh)!=-1,!b._parent)){var xe=b._isHovered||b._dragging?b._hoverMaterial:b._coloredMaterial;Ee.gizmoMeshes.forEach(function(Ne){Ne.material=xe,Ne.color&&(Ne.color=xe.diffuseColor)})}}),b}return Object(c.d)(t,r),t.prototype._createGizmoMesh=function(e,n,i){var o=De.a.CreateTorus("ignore",.6,.03*n,i,this.gizmoLayer.utilityLayerScene);o.visibility=0;var a=De.a.CreateTorus("",.6,.005*n,i,this.gizmoLayer.utilityLayerScene);return a.material=this._coloredMaterial,a.rotation.x=Math.PI/2,o.rotation.x=Math.PI/2,e.addChild(a),e.addChild(o),{rotationMesh:a,collider:o}},t.prototype._attachedNodeChanged=function(e){this.dragBehavior&&(this.dragBehavior.enabled=!!e)},t.prototype.setupRotationCircle=function(e,n){for(var i=t._CircleConstants.pi2/t._CircleConstants.tessellation,o=-Math.PI/2;o<Math.PI/2-1.5;o+=i/2){for(var a=[],s=0;s<t._CircleConstants.pi2*t._CircleConstants.rotationCircleRange+.01;s+=i)if(s<0){var d=t._CircleConstants.radius*Math.sin(s)*Math.cos(o),p=t._CircleConstants.radius*Math.cos(s)*Math.cos(o);a.push(new u.e(d,0,p))}else a.push(new u.e(0,0,0));e.push(a)}var b=new Ft.a("",this.gizmoLayer.utilityLayerScene);b.diffuseColor=M.a.Yellow(),b.backFaceCulling=!1;var P=De.a.CreateRibbon("rotationCircle",e,!1,!1,0,this.gizmoLayer.utilityLayerScene,!0);return P.material=b,P.material.alpha=.25,P.rotation.x=Math.PI/2,n.addChild(P),P},t.prototype.updateRotationPath=function(e,n){for(var i=t._CircleConstants.pi2/t._CircleConstants.tessellation,o=0,a=-Math.PI/2;a<Math.PI/2-1.5;a+=i/2){var s=e[o];if(s)for(var d=0,p=0;p<t._CircleConstants.pi2*t._CircleConstants.rotationCircleRange+.01;p+=i){if(s[d])if(p<Math.abs(n)){var b=n>0?p:-1*p,P=n>0?a:-1*a;s[d].set(t._CircleConstants.radius*Math.sin(b)*Math.cos(P),0,t._CircleConstants.radius*Math.cos(b)*Math.cos(P))}else s[d].set(0,0,0);d++}o++}},t.prototype.updateRotationCircle=function(e,n,i,o){this.updateRotationPath(n,i),De.a.CreateRibbon("rotationCircle",n,!1,!1,0,this.gizmoLayer.utilityLayerScene,void 0,void 0,e.geometry?e:void 0)},Object.defineProperty(t.prototype,"isEnabled",{get:function(){return this._isEnabled},set:function(e){this._isEnabled=e,e?this._parent&&(this.attachedMesh=this._parent.attachedMesh):this.attachedMesh=null},enumerable:!1,configurable:!0}),t.prototype.dispose=function(){this.onSnapObservable.clear(),this.gizmoLayer.utilityLayerScene.onPointerObservable.remove(this._pointerObserver),this.dragBehavior.detach(),this._gizmoMesh&&this._gizmoMesh.dispose(),this._rotationCircle&&this._rotationCircle.dispose(),[this._coloredMaterial,this._hoverMaterial,this._disableMaterial].forEach(function(e){e&&e.dispose()}),r.prototype.dispose.call(this)},t._CircleConstants={radius:.3,pi2:2*Math.PI,tessellation:70,rotationCircleRange:4},t}(wn.a),du=function(r){function t(e,n,i,o,a){e===void 0&&(e=On.a.DefaultUtilityLayer),n===void 0&&(n=32),i===void 0&&(i=!1),o===void 0&&(o=1);var s=r.call(this,e)||this;return s.onDragStartObservable=new C.c,s.onDragEndObservable=new C.c,s._observables=[],s._gizmoAxisCache=new Map,s.xGizmo=new Ko(new u.e(1,0,0),M.a.Red().scale(.5),e,n,s,i,o),s.yGizmo=new Ko(new u.e(0,1,0),M.a.Green().scale(.5),e,n,s,i,o),s.zGizmo=new Ko(new u.e(0,0,1),M.a.Blue().scale(.5),e,n,s,i,o),[s.xGizmo,s.yGizmo,s.zGizmo].forEach(function(d){d.dragBehavior.onDragStartObservable.add(function(){s.onDragStartObservable.notifyObservers({})}),d.dragBehavior.onDragEndObservable.add(function(){s.onDragEndObservable.notifyObservers({})})}),s.attachedMesh=null,s.attachedNode=null,a?a.addToAxisCache(s._gizmoAxisCache):wn.a.GizmoAxisPointerObserver(e,s._gizmoAxisCache),s}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"attachedMesh",{get:function(){return this._meshAttached},set:function(e){this._meshAttached=e,this._nodeAttached=e,this._checkBillboardTransform(),[this.xGizmo,this.yGizmo,this.zGizmo].forEach(function(n){n.isEnabled?n.attachedMesh=e:n.attachedMesh=null})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"attachedNode",{get:function(){return this._nodeAttached},set:function(e){this._meshAttached=null,this._nodeAttached=e,this._checkBillboardTransform(),[this.xGizmo,this.yGizmo,this.zGizmo].forEach(function(n){n.isEnabled?n.attachedNode=e:n.attachedNode=null})},enumerable:!1,configurable:!0}),t.prototype._checkBillboardTransform=function(){this._nodeAttached&&this._nodeAttached.billboardMode&&console.log("Rotation Gizmo will not work with transforms in billboard mode.")},Object.defineProperty(t.prototype,"isHovered",{get:function(){var e=!1;return[this.xGizmo,this.yGizmo,this.zGizmo].forEach(function(n){e=e||n.isHovered}),e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"updateGizmoRotationToMatchAttachedMesh",{get:function(){return this.xGizmo.updateGizmoRotationToMatchAttachedMesh},set:function(e){this.xGizmo&&(this.xGizmo.updateGizmoRotationToMatchAttachedMesh=e,this.yGizmo.updateGizmoRotationToMatchAttachedMesh=e,this.zGizmo.updateGizmoRotationToMatchAttachedMesh=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"snapDistance",{get:function(){return this.xGizmo.snapDistance},set:function(e){this.xGizmo&&(this.xGizmo.snapDistance=e,this.yGizmo.snapDistance=e,this.zGizmo.snapDistance=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"scaleRatio",{get:function(){return this.xGizmo.scaleRatio},set:function(e){this.xGizmo&&(this.xGizmo.scaleRatio=e,this.yGizmo.scaleRatio=e,this.zGizmo.scaleRatio=e)},enumerable:!1,configurable:!0}),t.prototype.addToAxisCache=function(e,n){this._gizmoAxisCache.set(e,n)},t.prototype.dispose=function(){var e=this;this.xGizmo.dispose(),this.yGizmo.dispose(),this.zGizmo.dispose(),this.onDragStartObservable.clear(),this.onDragEndObservable.clear(),this._observables.forEach(function(n){e.gizmoLayer.utilityLayerScene.onPointerObservable.remove(n)})},t.prototype.setCustomMesh=function(e){l.a.Error("Custom meshes are not supported on this gizmo, please set the custom meshes on the gizmos contained within this one (gizmo.xGizmo, gizmo.yGizmo, gizmo.zGizmo)")},t}(wn.a),Er=f(46),Ms=f(84),Qo=function(r){function t(e,n,i,o){var a;n===void 0&&(n=M.a.Gray()),i===void 0&&(i=On.a.DefaultUtilityLayer),o===void 0&&(o=null);var s=r.call(this,i)||this;s._pointerObserver=null,s.snapDistance=0,s.onSnapObservable=new C.c,s._isEnabled=!1,s._parent=null,s._dragging=!1,s._parent=o,s._coloredMaterial=new Ft.a("",i.utilityLayerScene),s._coloredMaterial.diffuseColor=n,s._coloredMaterial.specularColor=n.subtract(new M.a(.1,.1,.1)),s._hoverMaterial=new Ft.a("",i.utilityLayerScene),s._hoverMaterial.diffuseColor=M.a.Yellow(),s._disableMaterial=new Ft.a("",i.utilityLayerScene),s._disableMaterial.diffuseColor=M.a.Gray(),s._disableMaterial.alpha=.4,s._gizmoMesh=t._CreatePlane(i.utilityLayerScene,s._coloredMaterial),s._gizmoMesh.lookAt(s._rootMesh.position.add(e)),s._gizmoMesh.scaling.scaleInPlace(1/3),s._gizmoMesh.parent=s._rootMesh;var d=0,p=new u.e,b={snapDistance:0};s.dragBehavior=new yi.a({dragPlaneNormal:e}),s.dragBehavior.moveAttached=!1,s._rootMesh.addBehavior(s.dragBehavior),s.dragBehavior.onDragObservable.add(function(B){if(s.attachedNode){if(s.snapDistance==0)s.attachedNode.getWorldMatrix().addTranslationFromFloats(B.delta.x,B.delta.y,B.delta.z);else if(d+=B.dragDistance,Math.abs(d)>s.snapDistance){var F=Math.floor(Math.abs(d)/s.snapDistance);d%=s.snapDistance,B.delta.normalizeToRef(p),p.scaleInPlace(s.snapDistance*F),s.attachedNode.getWorldMatrix().addTranslationFromFloats(p.x,p.y,p.z),b.snapDistance=s.snapDistance*F,s.onSnapObservable.notifyObservers(b)}s._matrixChanged()}}),s.dragBehavior.onDragStartObservable.add(function(){s._dragging=!0}),s.dragBehavior.onDragEndObservable.add(function(){s._dragging=!1});var P=i._getSharedGizmoLight();P.includedOnlyMeshes=P.includedOnlyMeshes.concat(s._rootMesh.getChildMeshes(!1));var O={gizmoMeshes:s._gizmoMesh.getChildMeshes(),colliderMeshes:s._gizmoMesh.getChildMeshes(),material:s._coloredMaterial,hoverMaterial:s._hoverMaterial,disableMaterial:s._disableMaterial,active:!1};return(a=s._parent)===null||a===void 0||a.addToAxisCache(s._gizmoMesh,O),s._pointerObserver=i.utilityLayerScene.onPointerObservable.add(function(B){var F;if(!s._customMeshSet&&(s._isHovered=O.colliderMeshes.indexOf((F=B?.pickInfo)===null||F===void 0?void 0:F.pickedMesh)!=-1,!s._parent)){var z=s._isHovered||s._dragging?s._hoverMaterial:s._coloredMaterial;O.gizmoMeshes.forEach(function(J){J.material=z})}}),s}return Object(c.d)(t,r),t._CreatePlane=function(e,n){var i=new Er.a("plane",e),o=Ms.a.CreatePlane("dragPlane",{width:.1375,height:.1375,sideOrientation:2},e);return o.material=n,o.parent=i,i},t.prototype._attachedNodeChanged=function(e){this.dragBehavior&&(this.dragBehavior.enabled=!!e)},Object.defineProperty(t.prototype,"isEnabled",{get:function(){return this._isEnabled},set:function(e){this._isEnabled=e,e?this._parent&&(this.attachedNode=this._parent.attachedNode):this.attachedNode=null},enumerable:!1,configurable:!0}),t.prototype.dispose=function(){this.onSnapObservable.clear(),this.gizmoLayer.utilityLayerScene.onPointerObservable.remove(this._pointerObserver),this.dragBehavior.detach(),r.prototype.dispose.call(this),this._gizmoMesh&&this._gizmoMesh.dispose(),[this._coloredMaterial,this._hoverMaterial,this._disableMaterial].forEach(function(e){e&&e.dispose()})},t}(wn.a),fu=function(r){function t(e,n,i){e===void 0&&(e=On.a.DefaultUtilityLayer),n===void 0&&(n=1);var o=r.call(this,e)||this;return o._meshAttached=null,o._nodeAttached=null,o._observables=[],o._gizmoAxisCache=new Map,o.onDragStartObservable=new C.c,o.onDragEndObservable=new C.c,o._planarGizmoEnabled=!1,o.xGizmo=new Yo.a(new u.e(1,0,0),M.a.Red().scale(.5),e,o,n),o.yGizmo=new Yo.a(new u.e(0,1,0),M.a.Green().scale(.5),e,o,n),o.zGizmo=new Yo.a(new u.e(0,0,1),M.a.Blue().scale(.5),e,o,n),o.xPlaneGizmo=new Qo(new u.e(1,0,0),M.a.Red().scale(.5),o.gizmoLayer,o),o.yPlaneGizmo=new Qo(new u.e(0,1,0),M.a.Green().scale(.5),o.gizmoLayer,o),o.zPlaneGizmo=new Qo(new u.e(0,0,1),M.a.Blue().scale(.5),o.gizmoLayer,o),[o.xGizmo,o.yGizmo,o.zGizmo,o.xPlaneGizmo,o.yPlaneGizmo,o.zPlaneGizmo].forEach(function(a){a.dragBehavior.onDragStartObservable.add(function(){o.onDragStartObservable.notifyObservers({})}),a.dragBehavior.onDragEndObservable.add(function(){o.onDragEndObservable.notifyObservers({})})}),o.attachedMesh=null,i?i.addToAxisCache(o._gizmoAxisCache):wn.a.GizmoAxisPointerObserver(e,o._gizmoAxisCache),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"attachedMesh",{get:function(){return this._meshAttached},set:function(e){this._meshAttached=e,this._nodeAttached=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(n){n.isEnabled?n.attachedMesh=e:n.attachedMesh=null})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"attachedNode",{get:function(){return this._nodeAttached},set:function(e){this._meshAttached=null,this._nodeAttached=null,[this.xGizmo,this.yGizmo,this.zGizmo,this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(n){n.isEnabled?n.attachedNode=e:n.attachedNode=null})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isHovered",{get:function(){var e=!1;return[this.xGizmo,this.yGizmo,this.zGizmo,this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(n){e=e||n.isHovered}),e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"planarGizmoEnabled",{get:function(){return this._planarGizmoEnabled},set:function(e){var n=this;this._planarGizmoEnabled=e,[this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(i){i&&(i.isEnabled=e,e&&(i.attachedMesh?i.attachedMesh=n.attachedMesh:i.attachedNode=n.attachedNode))},this)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"updateGizmoRotationToMatchAttachedMesh",{get:function(){return this._updateGizmoRotationToMatchAttachedMesh},set:function(e){this._updateGizmoRotationToMatchAttachedMesh=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(n){n&&(n.updateGizmoRotationToMatchAttachedMesh=e)})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"snapDistance",{get:function(){return this._snapDistance},set:function(e){this._snapDistance=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(n){n&&(n.snapDistance=e)})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"scaleRatio",{get:function(){return this._scaleRatio},set:function(e){this._scaleRatio=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(n){n&&(n.scaleRatio=e)})},enumerable:!1,configurable:!0}),t.prototype.addToAxisCache=function(e,n){this._gizmoAxisCache.set(e,n)},t.prototype.dispose=function(){var e=this;[this.xGizmo,this.yGizmo,this.zGizmo,this.xPlaneGizmo,this.yPlaneGizmo,this.zPlaneGizmo].forEach(function(n){n&&n.dispose()}),this._observables.forEach(function(n){e.gizmoLayer.utilityLayerScene.onPointerObservable.remove(n)}),this.onDragStartObservable.clear(),this.onDragEndObservable.clear()},t.prototype.setCustomMesh=function(e){l.a.Error("Custom meshes are not supported on this gizmo, please set the custom meshes on the gizmos contained within this one (gizmo.xGizmo, gizmo.yGizmo, gizmo.zGizmo,gizmo.xPlaneGizmo, gizmo.yPlaneGizmo, gizmo.zPlaneGizmo)")},t}(wn.a);ft.a.CreatePolyhedron=function(r){var t=[];t[0]={vertex:[[0,0,1.732051],[1.632993,0,-.5773503],[-.8164966,1.414214,-.5773503],[-.8164966,-1.414214,-.5773503]],face:[[0,1,2],[0,2,3],[0,3,1],[1,3,2]]},t[1]={vertex:[[0,0,1.414214],[1.414214,0,0],[0,1.414214,0],[-1.414214,0,0],[0,-1.414214,0],[0,0,-1.414214]],face:[[0,1,2],[0,2,3],[0,3,4],[0,4,1],[1,4,5],[1,5,2],[2,5,3],[3,5,4]]},t[2]={vertex:[[0,0,1.070466],[.7136442,0,.7978784],[-.3568221,.618034,.7978784],[-.3568221,-.618034,.7978784],[.7978784,.618034,.3568221],[.7978784,-.618034,.3568221],[-.9341724,.381966,.3568221],[.1362939,1,.3568221],[.1362939,-1,.3568221],[-.9341724,-.381966,.3568221],[.9341724,.381966,-.3568221],[.9341724,-.381966,-.3568221],[-.7978784,.618034,-.3568221],[-.1362939,1,-.3568221],[-.1362939,-1,-.3568221],[-.7978784,-.618034,-.3568221],[.3568221,.618034,-.7978784],[.3568221,-.618034,-.7978784],[-.7136442,0,-.7978784],[0,0,-1.070466]],face:[[0,1,4,7,2],[0,2,6,9,3],[0,3,8,5,1],[1,5,11,10,4],[2,7,13,12,6],[3,9,15,14,8],[4,10,16,13,7],[5,8,14,17,11],[6,12,18,15,9],[10,11,17,19,16],[12,13,16,19,18],[14,15,18,19,17]]},t[3]={vertex:[[0,0,1.175571],[1.051462,0,.5257311],[.3249197,1,.5257311],[-.8506508,.618034,.5257311],[-.8506508,-.618034,.5257311],[.3249197,-1,.5257311],[.8506508,.618034,-.5257311],[.8506508,-.618034,-.5257311],[-.3249197,1,-.5257311],[-1.051462,0,-.5257311],[-.3249197,-1,-.5257311],[0,0,-1.175571]],face:[[0,1,2],[0,2,3],[0,3,4],[0,4,5],[0,5,1],[1,5,7],[1,7,6],[1,6,2],[2,6,8],[2,8,3],[3,8,9],[3,9,4],[4,9,10],[4,10,5],[5,10,7],[6,7,11],[6,11,8],[7,10,11],[8,11,9],[9,11,10]]},t[4]={vertex:[[0,0,1.070722],[.7148135,0,.7971752],[-.104682,.7071068,.7971752],[-.6841528,.2071068,.7971752],[-.104682,-.7071068,.7971752],[.6101315,.7071068,.5236279],[1.04156,.2071068,.1367736],[.6101315,-.7071068,.5236279],[-.3574067,1,.1367736],[-.7888348,-.5,.5236279],[-.9368776,.5,.1367736],[-.3574067,-1,.1367736],[.3574067,1,-.1367736],[.9368776,-.5,-.1367736],[.7888348,.5,-.5236279],[.3574067,-1,-.1367736],[-.6101315,.7071068,-.5236279],[-1.04156,-.2071068,-.1367736],[-.6101315,-.7071068,-.5236279],[.104682,.7071068,-.7971752],[.6841528,-.2071068,-.7971752],[.104682,-.7071068,-.7971752],[-.7148135,0,-.7971752],[0,0,-1.070722]],face:[[0,2,3],[1,6,5],[4,9,11],[7,15,13],[8,16,10],[12,14,19],[17,22,18],[20,21,23],[0,1,5,2],[0,3,9,4],[0,4,7,1],[1,7,13,6],[2,5,12,8],[2,8,10,3],[3,10,17,9],[4,11,15,7],[5,6,14,12],[6,13,20,14],[8,12,19,16],[9,17,18,11],[10,16,22,17],[11,18,21,15],[13,15,21,20],[14,20,23,19],[16,19,23,22],[18,22,23,21]]},t[5]={vertex:[[0,0,1.322876],[1.309307,0,.1889822],[-.9819805,.8660254,.1889822],[.1636634,-1.299038,.1889822],[.3273268,.8660254,-.9449112],[-.8183171,-.4330127,-.9449112]],face:[[0,3,1],[2,4,5],[0,1,4,2],[0,2,5,3],[1,3,5,4]]},t[6]={vertex:[[0,0,1.159953],[1.013464,0,.5642542],[-.3501431,.9510565,.5642542],[-.7715208,-.6571639,.5642542],[.6633206,.9510565,-.03144481],[.8682979,-.6571639,-.3996071],[-1.121664,.2938926,-.03144481],[-.2348831,-1.063314,-.3996071],[.5181548,.2938926,-.9953061],[-.5850262,-.112257,-.9953061]],face:[[0,1,4,2],[0,2,6,3],[1,5,8,4],[3,6,9,7],[5,7,9,8],[0,3,7,5,1],[2,4,8,9,6]]},t[7]={vertex:[[0,0,1.118034],[.8944272,0,.6708204],[-.2236068,.8660254,.6708204],[-.7826238,-.4330127,.6708204],[.6708204,.8660254,.2236068],[1.006231,-.4330127,-.2236068],[-1.006231,.4330127,.2236068],[-.6708204,-.8660254,-.2236068],[.7826238,.4330127,-.6708204],[.2236068,-.8660254,-.6708204],[-.8944272,0,-.6708204],[0,0,-1.118034]],face:[[0,1,4,2],[0,2,6,3],[1,5,8,4],[3,6,10,7],[5,9,11,8],[7,10,11,9],[0,3,7,9,5,1],[2,4,8,11,10,6]]},t[8]={vertex:[[-.729665,.670121,.319155],[-.655235,-.29213,-.754096],[-.093922,-.607123,.537818],[.702196,.595691,.485187],[.776626,-.36656,-.588064]],face:[[1,4,2],[0,1,2],[3,0,2],[4,3,2],[4,1,0,3]]},t[9]={vertex:[[-.868849,-.100041,.61257],[-.329458,.976099,.28078],[-.26629,-.013796,-.477654],[-.13392,-1.034115,.229829],[.738834,.707117,-.307018],[.859683,-.535264,-.338508]],face:[[3,0,2],[5,3,2],[4,5,2],[1,4,2],[0,1,2],[0,3,5,4,1]]},t[10]={vertex:[[-.610389,.243975,.531213],[-.187812,-.48795,-.664016],[-.187812,.9759,-.664016],[.187812,-.9759,.664016],[.798201,.243975,.132803]],face:[[1,3,0],[3,4,0],[3,1,4],[0,2,1],[0,4,2],[2,4,1]]},t[11]={vertex:[[-1.028778,.392027,-.048786],[-.640503,-.646161,.621837],[-.125162,-.395663,-.540059],[.004683,.888447,-.651988],[.125161,.395663,.540059],[.632925,-.791376,.433102],[1.031672,.157063,-.354165]],face:[[3,2,0],[2,1,0],[2,5,1],[0,4,3],[0,1,4],[4,1,5],[2,3,6],[3,4,6],[5,2,6],[4,5,6]]},t[12]={vertex:[[-.669867,.334933,-.529576],[-.669867,.334933,.529577],[-.4043,1.212901,0],[-.334933,-.669867,-.529576],[-.334933,-.669867,.529577],[.334933,.669867,-.529576],[.334933,.669867,.529577],[.4043,-1.212901,0],[.669867,-.334933,-.529576],[.669867,-.334933,.529577]],face:[[8,9,7],[6,5,2],[3,8,7],[5,0,2],[4,3,7],[0,1,2],[9,4,7],[1,6,2],[9,8,5,6],[8,3,0,5],[3,4,1,0],[4,9,6,1]]},t[13]={vertex:[[-.931836,.219976,-.264632],[-.636706,.318353,.692816],[-.613483,-.735083,-.264632],[-.326545,.979634,0],[-.318353,-.636706,.692816],[-.159176,.477529,-.856368],[.159176,-.477529,-.856368],[.318353,.636706,.692816],[.326545,-.979634,0],[.613482,.735082,-.264632],[.636706,-.318353,.692816],[.931835,-.219977,-.264632]],face:[[11,10,8],[7,9,3],[6,11,8],[9,5,3],[2,6,8],[5,0,3],[4,2,8],[0,1,3],[10,4,8],[1,7,3],[10,11,9,7],[11,6,5,9],[6,2,0,5],[2,4,1,0],[4,10,7,1]]},t[14]={vertex:[[-.93465,.300459,-.271185],[-.838689,-.260219,-.516017],[-.711319,.717591,.128359],[-.710334,-.156922,.080946],[-.599799,.556003,-.725148],[-.503838,-.004675,-.969981],[-.487004,.26021,.48049],[-.460089,-.750282,-.512622],[-.376468,.973135,-.325605],[-.331735,-.646985,.084342],[-.254001,.831847,.530001],[-.125239,-.494738,-.966586],[.029622,.027949,.730817],[.056536,-.982543,-.262295],[.08085,1.087391,.076037],[.125583,-.532729,.485984],[.262625,.599586,.780328],[.391387,-.726999,-.716259],[.513854,-.868287,.139347],[.597475,.85513,.326364],[.641224,.109523,.783723],[.737185,-.451155,.538891],[.848705,-.612742,-.314616],[.976075,.365067,.32976],[1.072036,-.19561,.084927]],face:[[15,18,21],[12,20,16],[6,10,2],[3,0,1],[9,7,13],[2,8,4,0],[0,4,5,1],[1,5,11,7],[7,11,17,13],[13,17,22,18],[18,22,24,21],[21,24,23,20],[20,23,19,16],[16,19,14,10],[10,14,8,2],[15,9,13,18],[12,15,21,20],[6,12,16,10],[3,6,2,0],[9,3,1,7],[9,15,12,6,3],[22,17,11,5,4,8,14,19,23,24]]};var e,n,i,o,a,s,d=r.type&&(r.type<0||r.type>=t.length)?0:r.type||0,p=r.size,b=r.sizeX||p||1,P=r.sizeY||p||1,O=r.sizeZ||p||1,B=r.custom||t[d],F=B.face.length,z=r.faceUV||new Array(F),J=r.faceColors,ie=r.flat===void 0||r.flat,se=r.sideOrientation===0?0:r.sideOrientation||ft.a.DEFAULTSIDE,ce=new Array,ue=new Array,fe=new Array,ve=new Array,Te=new Array,Re=0,Ae=0,Ee=new Array,Se=0,Le=0;if(ie)for(Le=0;Le<F;Le++)J&&J[Le]===void 0&&(J[Le]=new M.b(1,1,1,1)),z&&z[Le]===void 0&&(z[Le]=new u.f(0,0,1,1));if(ie)for(Le=0;Le<F;Le++){var xe=B.face[Le].length;for(i=2*Math.PI/xe,o=.5*Math.tan(i/2),a=.5,Se=0;Se<xe;Se++)ce.push(B.vertex[B.face[Le][Se]][0]*b,B.vertex[B.face[Le][Se]][1]*P,B.vertex[B.face[Le][Se]][2]*O),Ee.push(Re),Re++,e=z[Le].x+(z[Le].z-z[Le].x)*(.5+o),n=z[Le].y+(z[Le].w-z[Le].y)*(a-.5),ve.push(e,n),s=o*Math.cos(i)-a*Math.sin(i),a=o*Math.sin(i)+a*Math.cos(i),o=s,J&&Te.push(J[Le].r,J[Le].g,J[Le].b,J[Le].a);for(Se=0;Se<xe-2;Se++)ue.push(Ee[0+Ae],Ee[Se+2+Ae],Ee[Se+1+Ae]);Ae+=xe}else{for(Se=0;Se<B.vertex.length;Se++)ce.push(B.vertex[Se][0]*b,B.vertex[Se][1]*P,B.vertex[Se][2]*O),ve.push(0,0);for(Le=0;Le<F;Le++)for(Se=0;Se<B.face[Le].length-2;Se++)ue.push(B.face[Le][0],B.face[Le][Se+2],B.face[Le][Se+1])}ft.a.ComputeNormals(ce,ue,fe),ft.a._ComputeSides(se,ce,ue,fe,ve,r.frontUVs,r.backUVs);var Ne=new ft.a;return Ne.positions=ce,Ne.indices=ue,Ne.normals=fe,Ne.uvs=ve,J&&ie&&(Ne.colors=Te),Ne},De.a.CreatePolyhedron=function(r,t,e){return ao.CreatePolyhedron(r,t,e)};var ao=function(){function r(){}return r.CreatePolyhedron=function(t,e,n){n===void 0&&(n=null);var i=new De.a(t,n);return e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation),i._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreatePolyhedron(e).applyToMesh(i,e.updatable),i},r}(),pu=function(r){function t(e,n,i){e===void 0&&(e=On.a.DefaultUtilityLayer),n===void 0&&(n=1);var o=r.call(this,e)||this;return o._meshAttached=null,o._nodeAttached=null,o._sensitivity=1,o._observables=[],o._gizmoAxisCache=new Map,o.onDragStartObservable=new C.c,o.onDragEndObservable=new C.c,o.uniformScaleGizmo=o._createUniformScaleMesh(),o.xGizmo=new oo(new u.e(1,0,0),M.a.Red().scale(.5),e,o,n),o.yGizmo=new oo(new u.e(0,1,0),M.a.Green().scale(.5),e,o,n),o.zGizmo=new oo(new u.e(0,0,1),M.a.Blue().scale(.5),e,o,n),[o.xGizmo,o.yGizmo,o.zGizmo,o.uniformScaleGizmo].forEach(function(a){a.dragBehavior.onDragStartObservable.add(function(){o.onDragStartObservable.notifyObservers({})}),a.dragBehavior.onDragEndObservable.add(function(){o.onDragEndObservable.notifyObservers({})})}),o.attachedMesh=null,o.attachedNode=null,i?i.addToAxisCache(o._gizmoAxisCache):wn.a.GizmoAxisPointerObserver(e,o._gizmoAxisCache),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"attachedMesh",{get:function(){return this._meshAttached},set:function(e){this._meshAttached=e,this._nodeAttached=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.uniformScaleGizmo].forEach(function(n){n.isEnabled?n.attachedMesh=e:n.attachedMesh=null})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"attachedNode",{get:function(){return this._nodeAttached},set:function(e){this._meshAttached=null,this._nodeAttached=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.uniformScaleGizmo].forEach(function(n){n.isEnabled?n.attachedNode=e:n.attachedNode=null})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isHovered",{get:function(){var e=!1;return[this.xGizmo,this.yGizmo,this.zGizmo].forEach(function(n){e=e||n.isHovered}),e},enumerable:!1,configurable:!0}),t.prototype._createUniformScaleMesh=function(){this._coloredMaterial=new Ft.a("",this.gizmoLayer.utilityLayerScene),this._coloredMaterial.diffuseColor=M.a.Gray(),this._hoverMaterial=new Ft.a("",this.gizmoLayer.utilityLayerScene),this._hoverMaterial.diffuseColor=M.a.Yellow(),this._disableMaterial=new Ft.a("",this.gizmoLayer.utilityLayerScene),this._disableMaterial.diffuseColor=M.a.Gray(),this._disableMaterial.alpha=.4;var e=new oo(new u.e(0,1,0),M.a.Gray().scale(.5),this.gizmoLayer,this);e.updateGizmoRotationToMatchAttachedMesh=!1,e.uniformScaling=!0,this._uniformScalingMesh=ao.CreatePolyhedron("uniform",{type:1},e.gizmoLayer.utilityLayerScene),this._uniformScalingMesh.scaling.scaleInPlace(.01),this._uniformScalingMesh.visibility=0,this._octahedron=ao.CreatePolyhedron("",{type:1},e.gizmoLayer.utilityLayerScene),this._octahedron.scaling.scaleInPlace(.007),this._uniformScalingMesh.addChild(this._octahedron),e.setCustomMesh(this._uniformScalingMesh,!0);var n=this.gizmoLayer._getSharedGizmoLight();n.includedOnlyMeshes=n.includedOnlyMeshes.concat(this._octahedron);var i={gizmoMeshes:[this._octahedron,this._uniformScalingMesh],colliderMeshes:[this._uniformScalingMesh],material:this._coloredMaterial,hoverMaterial:this._hoverMaterial,disableMaterial:this._disableMaterial,active:!1};return this.addToAxisCache(e._rootMesh,i),e},Object.defineProperty(t.prototype,"updateGizmoRotationToMatchAttachedMesh",{get:function(){return this._updateGizmoRotationToMatchAttachedMesh},set:function(e){e?(this._updateGizmoRotationToMatchAttachedMesh=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.uniformScaleGizmo].forEach(function(n){n&&(n.updateGizmoRotationToMatchAttachedMesh=e)})):l.a.Warn("Setting updateGizmoRotationToMatchAttachedMesh = false on scaling gizmo is not supported.")},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"snapDistance",{get:function(){return this._snapDistance},set:function(e){this._snapDistance=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.uniformScaleGizmo].forEach(function(n){n&&(n.snapDistance=e)})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"scaleRatio",{get:function(){return this._scaleRatio},set:function(e){this._scaleRatio=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.uniformScaleGizmo].forEach(function(n){n&&(n.scaleRatio=e)})},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sensitivity",{get:function(){return this._sensitivity},set:function(e){this._sensitivity=e,[this.xGizmo,this.yGizmo,this.zGizmo,this.uniformScaleGizmo].forEach(function(n){n&&(n.sensitivity=e)})},enumerable:!1,configurable:!0}),t.prototype.addToAxisCache=function(e,n){this._gizmoAxisCache.set(e,n)},t.prototype.dispose=function(){var e=this;[this.xGizmo,this.yGizmo,this.zGizmo,this.uniformScaleGizmo].forEach(function(n){n&&n.dispose()}),this._observables.forEach(function(n){e.gizmoLayer.utilityLayerScene.onPointerObservable.remove(n)}),this.onDragStartObservable.clear(),this.onDragEndObservable.clear(),[this._uniformScalingMesh,this._octahedron].forEach(function(n){n&&n.dispose()}),[this._coloredMaterial,this._hoverMaterial,this._disableMaterial].forEach(function(n){n&&n.dispose()})},t}(wn.a),fp=function(){function r(t,e,n,i){e===void 0&&(e=1),n===void 0&&(n=On.a.DefaultUtilityLayer),i===void 0&&(i=On.a.DefaultKeepDepthUtilityLayer),this.scene=t,this.clearGizmoOnEmptyPointerEvent=!1,this.onAttachedToMeshObservable=new C.c,this.onAttachedToNodeObservable=new C.c,this._gizmosEnabled={positionGizmo:!1,rotationGizmo:!1,scaleGizmo:!1,boundingBoxGizmo:!1},this._pointerObservers=[],this._attachedMesh=null,this._attachedNode=null,this._boundingBoxColor=M.a.FromHexString("#0984e3"),this._thickness=1,this._gizmoAxisCache=new Map,this.boundingBoxDragBehavior=new gl,this.attachableMeshes=null,this.attachableNodes=null,this.usePointerToAttachGizmos=!0,this._defaultUtilityLayer=n,this._defaultKeepDepthUtilityLayer=i,this._defaultKeepDepthUtilityLayer.utilityLayerScene.autoClearDepthAndStencil=!1,this._thickness=e,this.gizmos={positionGizmo:null,rotationGizmo:null,scaleGizmo:null,boundingBoxGizmo:null};var o=this._attachToMeshPointerObserver(t),a=wn.a.GizmoAxisPointerObserver(this._defaultUtilityLayer,this._gizmoAxisCache);this._pointerObservers=[o,a]}return Object.defineProperty(r.prototype,"keepDepthUtilityLayer",{get:function(){return this._defaultKeepDepthUtilityLayer},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"utilityLayer",{get:function(){return this._defaultUtilityLayer},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isHovered",{get:function(){var t=!1;for(var e in this.gizmos){var n=this.gizmos[e];if(n&&n.isHovered){t=!0;break}}return t},enumerable:!1,configurable:!0}),r.prototype._attachToMeshPointerObserver=function(t){var e=this;return t.onPointerObservable.add(function(n){if(e.usePointerToAttachGizmos&&n.type==Tt.a.POINTERDOWN)if(n.pickInfo&&n.pickInfo.pickedMesh){var i=n.pickInfo.pickedMesh;if(e.attachableMeshes==null)for(;i&&i.parent!=null;)i=i.parent;else{var o=!1;e.attachableMeshes.forEach(function(a){i&&(i==a||i.isDescendantOf(a))&&(i=a,o=!0)}),o||(i=null)}i instanceof Dt.a?e._attachedMesh!=i&&e.attachToMesh(i):e.clearGizmoOnEmptyPointerEvent&&e.attachToMesh(null)}else e.clearGizmoOnEmptyPointerEvent&&e.attachToMesh(null)})},r.prototype.attachToMesh=function(t){for(var e in this._attachedMesh&&this._attachedMesh.removeBehavior(this.boundingBoxDragBehavior),this._attachedNode&&this._attachedNode.removeBehavior(this.boundingBoxDragBehavior),this._attachedMesh=t,this._attachedNode=null,this.gizmos){var n=this.gizmos[e];n&&this._gizmosEnabled[e]&&(n.attachedMesh=t)}this.boundingBoxGizmoEnabled&&this._attachedMesh&&this._attachedMesh.addBehavior(this.boundingBoxDragBehavior),this.onAttachedToMeshObservable.notifyObservers(t)},r.prototype.attachToNode=function(t){for(var e in this._attachedMesh&&this._attachedMesh.removeBehavior(this.boundingBoxDragBehavior),this._attachedNode&&this._attachedNode.removeBehavior(this.boundingBoxDragBehavior),this._attachedMesh=null,this._attachedNode=t,this.gizmos){var n=this.gizmos[e];n&&this._gizmosEnabled[e]&&(n.attachedNode=t)}this.boundingBoxGizmoEnabled&&this._attachedNode&&this._attachedNode.addBehavior(this.boundingBoxDragBehavior),this.onAttachedToNodeObservable.notifyObservers(t)},Object.defineProperty(r.prototype,"positionGizmoEnabled",{get:function(){return this._gizmosEnabled.positionGizmo},set:function(t){t?(this.gizmos.positionGizmo||(this.gizmos.positionGizmo=new fu(this._defaultUtilityLayer,this._thickness,this)),this._attachedNode?this.gizmos.positionGizmo.attachedNode=this._attachedNode:this.gizmos.positionGizmo.attachedMesh=this._attachedMesh):this.gizmos.positionGizmo&&(this.gizmos.positionGizmo.attachedNode=null),this._gizmosEnabled.positionGizmo=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rotationGizmoEnabled",{get:function(){return this._gizmosEnabled.rotationGizmo},set:function(t){t?(this.gizmos.rotationGizmo||(this.gizmos.rotationGizmo=new du(this._defaultUtilityLayer,32,!1,this._thickness,this)),this._attachedNode?this.gizmos.rotationGizmo.attachedNode=this._attachedNode:this.gizmos.rotationGizmo.attachedMesh=this._attachedMesh):this.gizmos.rotationGizmo&&(this.gizmos.rotationGizmo.attachedNode=null),this._gizmosEnabled.rotationGizmo=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"scaleGizmoEnabled",{get:function(){return this._gizmosEnabled.scaleGizmo},set:function(t){t?(this.gizmos.scaleGizmo=this.gizmos.scaleGizmo||new pu(this._defaultUtilityLayer,this._thickness,this),this._attachedNode?this.gizmos.scaleGizmo.attachedNode=this._attachedNode:this.gizmos.scaleGizmo.attachedMesh=this._attachedMesh):this.gizmos.scaleGizmo&&(this.gizmos.scaleGizmo.attachedNode=null),this._gizmosEnabled.scaleGizmo=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"boundingBoxGizmoEnabled",{get:function(){return this._gizmosEnabled.boundingBoxGizmo},set:function(t){t?(this.gizmos.boundingBoxGizmo=this.gizmos.boundingBoxGizmo||new hu(this._boundingBoxColor,this._defaultKeepDepthUtilityLayer),this._attachedMesh?this.gizmos.boundingBoxGizmo.attachedMesh=this._attachedMesh:this.gizmos.boundingBoxGizmo.attachedNode=this._attachedNode,this._attachedMesh?(this._attachedMesh.removeBehavior(this.boundingBoxDragBehavior),this._attachedMesh.addBehavior(this.boundingBoxDragBehavior)):this._attachedNode&&(this._attachedNode.removeBehavior(this.boundingBoxDragBehavior),this._attachedNode.addBehavior(this.boundingBoxDragBehavior))):this.gizmos.boundingBoxGizmo&&(this._attachedMesh?this._attachedMesh.removeBehavior(this.boundingBoxDragBehavior):this._attachedNode&&this._attachedNode.removeBehavior(this.boundingBoxDragBehavior),this.gizmos.boundingBoxGizmo.attachedNode=null),this._gizmosEnabled.boundingBoxGizmo=t},enumerable:!1,configurable:!0}),r.prototype.addToAxisCache=function(t){var e=this;t.size>0&&t.forEach(function(n,i){e._gizmoAxisCache.set(i,n)})},r.prototype.dispose=function(){var t=this;for(var e in this._pointerObservers.forEach(function(i){t.scene.onPointerObservable.remove(i)}),this.gizmos){var n=this.gizmos[e];n&&n.dispose()}this._defaultKeepDepthUtilityLayer.dispose(),this._defaultUtilityLayer.dispose(),this.boundingBoxDragBehavior.detach(),this.onAttachedToMeshObservable.clear()},r}(),Ci=f(48),qo=function(r){function t(){var e=r!==null&&r.apply(this,arguments)||this;return e._needProjectionMatrixCompute=!0,e}return Object(c.d)(t,r),t.prototype._setPosition=function(e){this._position=e},Object.defineProperty(t.prototype,"position",{get:function(){return this._position},set:function(e){this._setPosition(e)},enumerable:!1,configurable:!0}),t.prototype._setDirection=function(e){this._direction=e},Object.defineProperty(t.prototype,"direction",{get:function(){return this._direction},set:function(e){this._setDirection(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"shadowMinZ",{get:function(){return this._shadowMinZ},set:function(e){this._shadowMinZ=e,this.forceProjectionMatrixCompute()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"shadowMaxZ",{get:function(){return this._shadowMaxZ},set:function(e){this._shadowMaxZ=e,this.forceProjectionMatrixCompute()},enumerable:!1,configurable:!0}),t.prototype.computeTransformedInformation=function(){return!(!this.parent||!this.parent.getWorldMatrix)&&(this.transformedPosition||(this.transformedPosition=u.e.Zero()),u.e.TransformCoordinatesToRef(this.position,this.parent.getWorldMatrix(),this.transformedPosition),this.direction&&(this.transformedDirection||(this.transformedDirection=u.e.Zero()),u.e.TransformNormalToRef(this.direction,this.parent.getWorldMatrix(),this.transformedDirection)),!0)},t.prototype.getDepthScale=function(){return 50},t.prototype.getShadowDirection=function(e){return this.transformedDirection?this.transformedDirection:this.direction},t.prototype.getAbsolutePosition=function(){return this.transformedPosition?this.transformedPosition:this.position},t.prototype.setDirectionToTarget=function(e){return this.direction=u.e.Normalize(e.subtract(this.position)),this.direction},t.prototype.getRotation=function(){this.direction.normalize();var e=u.e.Cross(this.direction,ye.a.Y),n=u.e.Cross(e,this.direction);return u.e.RotationFromAxis(e,n,this.direction)},t.prototype.needCube=function(){return!1},t.prototype.needProjectionMatrixCompute=function(){return this._needProjectionMatrixCompute},t.prototype.forceProjectionMatrixCompute=function(){this._needProjectionMatrixCompute=!0},t.prototype._initCache=function(){r.prototype._initCache.call(this),this._cache.position=u.e.Zero()},t.prototype._isSynchronized=function(){return!!this._cache.position.equals(this.position)},t.prototype.computeWorldMatrix=function(e){return!e&&this.isSynchronized()?(this._currentRenderId=this.getScene().getRenderId(),this._worldMatrix):(this._updateCache(),this._cache.position.copyFrom(this.position),this._worldMatrix||(this._worldMatrix=u.a.Identity()),u.a.TranslationToRef(this.position.x,this.position.y,this.position.z,this._worldMatrix),this.parent&&this.parent.getWorldMatrix&&(this._worldMatrix.multiplyToRef(this.parent.getWorldMatrix(),this._worldMatrix),this._markSyncedWithParent()),this._worldMatrixDeterminantIsDirty=!0,this._worldMatrix)},t.prototype.getDepthMinZ=function(e){return this.shadowMinZ!==void 0?this.shadowMinZ:e.minZ},t.prototype.getDepthMaxZ=function(e){return this.shadowMaxZ!==void 0?this.shadowMaxZ:e.maxZ},t.prototype.setShadowProjectionMatrix=function(e,n,i){return this.customProjectionMatrixBuilder?this.customProjectionMatrixBuilder(n,i,e):this._setDefaultShadowProjectionMatrix(e,n,i),this},Object(c.c)([Object(L.o)()],t.prototype,"position",null),Object(c.c)([Object(L.o)()],t.prototype,"direction",null),Object(c.c)([Object(L.c)()],t.prototype,"shadowMinZ",null),Object(c.c)([Object(L.c)()],t.prototype,"shadowMaxZ",null),t}(Ci.a);Q.a.AddNodeConstructor("Light_Type_1",function(r,t){return function(){return new Is(r,u.e.Zero(),t)}});var Is=function(r){function t(e,n,i){var o=r.call(this,e,i)||this;return o._shadowFrustumSize=0,o._shadowOrthoScale=.1,o.autoUpdateExtends=!0,o.autoCalcShadowZBounds=!1,o._orthoLeft=Number.MAX_VALUE,o._orthoRight=Number.MIN_VALUE,o._orthoTop=Number.MIN_VALUE,o._orthoBottom=Number.MAX_VALUE,o.position=n.scale(-1),o.direction=n,o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"shadowFrustumSize",{get:function(){return this._shadowFrustumSize},set:function(e){this._shadowFrustumSize=e,this.forceProjectionMatrixCompute()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"shadowOrthoScale",{get:function(){return this._shadowOrthoScale},set:function(e){this._shadowOrthoScale=e,this.forceProjectionMatrixCompute()},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"DirectionalLight"},t.prototype.getTypeID=function(){return Ci.a.LIGHTTYPEID_DIRECTIONALLIGHT},t.prototype._setDefaultShadowProjectionMatrix=function(e,n,i){this.shadowFrustumSize>0?this._setDefaultFixedFrustumShadowProjectionMatrix(e):this._setDefaultAutoExtendShadowProjectionMatrix(e,n,i)},t.prototype._setDefaultFixedFrustumShadowProjectionMatrix=function(e){var n=this.getScene().activeCamera;n&&u.a.OrthoLHToRef(this.shadowFrustumSize,this.shadowFrustumSize,this.shadowMinZ!==void 0?this.shadowMinZ:n.minZ,this.shadowMaxZ!==void 0?this.shadowMaxZ:n.maxZ,e)},t.prototype._setDefaultAutoExtendShadowProjectionMatrix=function(e,n,i){var o=this.getScene().activeCamera;if(o){if(this.autoUpdateExtends||this._orthoLeft===Number.MAX_VALUE){var a=u.e.Zero();this._orthoLeft=Number.MAX_VALUE,this._orthoRight=Number.MIN_VALUE,this._orthoTop=Number.MIN_VALUE,this._orthoBottom=Number.MAX_VALUE;for(var s=Number.MAX_VALUE,d=Number.MIN_VALUE,p=0;p<i.length;p++){var b=i[p];if(b)for(var P=b.getBoundingInfo().boundingBox,O=0;O<P.vectorsWorld.length;O++)u.e.TransformCoordinatesToRef(P.vectorsWorld[O],n,a),a.x<this._orthoLeft&&(this._orthoLeft=a.x),a.y<this._orthoBottom&&(this._orthoBottom=a.y),a.x>this._orthoRight&&(this._orthoRight=a.x),a.y>this._orthoTop&&(this._orthoTop=a.y),this.autoCalcShadowZBounds&&(a.z<s&&(s=a.z),a.z>d&&(d=a.z))}this.autoCalcShadowZBounds&&(this._shadowMinZ=s,this._shadowMaxZ=d)}var B=this._orthoRight-this._orthoLeft,F=this._orthoTop-this._orthoBottom;u.a.OrthoOffCenterLHToRef(this._orthoLeft-B*this.shadowOrthoScale,this._orthoRight+B*this.shadowOrthoScale,this._orthoBottom-F*this.shadowOrthoScale,this._orthoTop+F*this.shadowOrthoScale,this.shadowMinZ!==void 0?this.shadowMinZ:o.minZ,this.shadowMaxZ!==void 0?this.shadowMaxZ:o.maxZ,e)}},t.prototype._buildUniformLayout=function(){this._uniformBuffer.addUniform("vLightData",4),this._uniformBuffer.addUniform("vLightDiffuse",4),this._uniformBuffer.addUniform("vLightSpecular",4),this._uniformBuffer.addUniform("shadowsInfo",3),this._uniformBuffer.addUniform("depthValues",2),this._uniformBuffer.create()},t.prototype.transferToEffect=function(e,n){return this.computeTransformedInformation()?(this._uniformBuffer.updateFloat4("vLightData",this.transformedDirection.x,this.transformedDirection.y,this.transformedDirection.z,1,n),this):(this._uniformBuffer.updateFloat4("vLightData",this.direction.x,this.direction.y,this.direction.z,1,n),this)},t.prototype.transferToNodeMaterialEffect=function(e,n){return this.computeTransformedInformation()?(e.setFloat3(n,this.transformedDirection.x,this.transformedDirection.y,this.transformedDirection.z),this):(e.setFloat3(n,this.direction.x,this.direction.y,this.direction.z),this)},t.prototype.getDepthMinZ=function(e){return 1},t.prototype.getDepthMaxZ=function(e){return 1},t.prototype.prepareLightSpecificDefines=function(e,n){e["DIRLIGHT"+n]=!0},Object(c.c)([Object(L.c)()],t.prototype,"shadowFrustumSize",null),Object(c.c)([Object(L.c)()],t.prototype,"shadowOrthoScale",null),Object(c.c)([Object(L.c)()],t.prototype,"autoUpdateExtends",void 0),Object(c.c)([Object(L.c)()],t.prototype,"autoCalcShadowZBounds",void 0),t}(qo);De.a.CreateHemisphere=function(r,t,e,n){var i={segments:t,diameter:e};return Zo.CreateHemisphere(r,i,n)};var Zo=function(){function r(){}return r.CreateHemisphere=function(t,e,n){e.diameter||(e.diameter=1),e.segments||(e.segments=16);var i=Fn.a.CreateSphere("",{slice:.5,diameter:e.diameter,segments:e.segments},n),o=De.a.CreateDisc("",e.diameter/2,3*e.segments+(4-e.segments),n);o.rotation.x=-Math.PI/2,o.parent=i;var a=De.a.MergeMeshes([o,i],!0);return a.name=t,a},r}();Q.a.AddNodeConstructor("Light_Type_2",function(r,t){return function(){return new Ds(r,u.e.Zero(),u.e.Zero(),0,0,t)}});var Ds=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,s)||this;return d._innerAngle=0,d._projectionTextureMatrix=u.a.Zero(),d._projectionTextureLightNear=1e-6,d._projectionTextureLightFar=1e3,d._projectionTextureUpDirection=u.e.Up(),d._projectionTextureViewLightDirty=!0,d._projectionTextureProjectionLightDirty=!0,d._projectionTextureDirty=!0,d._projectionTextureViewTargetVector=u.e.Zero(),d._projectionTextureViewLightMatrix=u.a.Zero(),d._projectionTextureProjectionLightMatrix=u.a.Zero(),d._projectionTextureScalingMatrix=u.a.FromValues(.5,0,0,0,0,.5,0,0,0,0,.5,0,.5,.5,.5,1),d.position=n,d.direction=i,d.angle=o,d.exponent=a,d}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"angle",{get:function(){return this._angle},set:function(e){this._angle=e,this._cosHalfAngle=Math.cos(.5*e),this._projectionTextureProjectionLightDirty=!0,this.forceProjectionMatrixCompute(),this._computeAngleValues()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"innerAngle",{get:function(){return this._innerAngle},set:function(e){this._innerAngle=e,this._computeAngleValues()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"shadowAngleScale",{get:function(){return this._shadowAngleScale},set:function(e){this._shadowAngleScale=e,this.forceProjectionMatrixCompute()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"projectionTextureMatrix",{get:function(){return this._projectionTextureMatrix},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"projectionTextureLightNear",{get:function(){return this._projectionTextureLightNear},set:function(e){this._projectionTextureLightNear=e,this._projectionTextureProjectionLightDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"projectionTextureLightFar",{get:function(){return this._projectionTextureLightFar},set:function(e){this._projectionTextureLightFar=e,this._projectionTextureProjectionLightDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"projectionTextureUpDirection",{get:function(){return this._projectionTextureUpDirection},set:function(e){this._projectionTextureUpDirection=e,this._projectionTextureProjectionLightDirty=!0},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"projectionTexture",{get:function(){return this._projectionTexture},set:function(e){var n=this;this._projectionTexture!==e&&(this._projectionTexture=e,this._projectionTextureDirty=!0,this._projectionTexture&&!this._projectionTexture.isReady()&&(t._IsProceduralTexture(this._projectionTexture)?this._projectionTexture.getEffect().executeWhenCompiled(function(){n._markMeshesAsLightDirty()}):t._IsTexture(this._projectionTexture)&&this._projectionTexture.onLoadObservable.addOnce(function(){n._markMeshesAsLightDirty()})))},enumerable:!1,configurable:!0}),t._IsProceduralTexture=function(e){return e.onGeneratedObservable!==void 0},t._IsTexture=function(e){return e.onLoadObservable!==void 0},t.prototype.getClassName=function(){return"SpotLight"},t.prototype.getTypeID=function(){return Ci.a.LIGHTTYPEID_SPOTLIGHT},t.prototype._setDirection=function(e){r.prototype._setDirection.call(this,e),this._projectionTextureViewLightDirty=!0},t.prototype._setPosition=function(e){r.prototype._setPosition.call(this,e),this._projectionTextureViewLightDirty=!0},t.prototype._setDefaultShadowProjectionMatrix=function(e,n,i){var o=this.getScene().activeCamera;if(o){this._shadowAngleScale=this._shadowAngleScale||1;var a=this._shadowAngleScale*this._angle;u.a.PerspectiveFovLHToRef(a,1,this.getDepthMinZ(o),this.getDepthMaxZ(o),e)}},t.prototype._computeProjectionTextureViewLightMatrix=function(){this._projectionTextureViewLightDirty=!1,this._projectionTextureDirty=!0,this.position.addToRef(this.direction,this._projectionTextureViewTargetVector),u.a.LookAtLHToRef(this.position,this._projectionTextureViewTargetVector,this._projectionTextureUpDirection,this._projectionTextureViewLightMatrix)},t.prototype._computeProjectionTextureProjectionLightMatrix=function(){this._projectionTextureProjectionLightDirty=!1,this._projectionTextureDirty=!0;var e=this.projectionTextureLightFar,n=this.projectionTextureLightNear,i=e/(e-n),o=-i*n,a=1/Math.tan(this._angle/2);u.a.FromValuesToRef(a/1,0,0,0,0,a,0,0,0,0,i,1,0,0,o,0,this._projectionTextureProjectionLightMatrix)},t.prototype._computeProjectionTextureMatrix=function(){if(this._projectionTextureDirty=!1,this._projectionTextureViewLightMatrix.multiplyToRef(this._projectionTextureProjectionLightMatrix,this._projectionTextureMatrix),this._projectionTexture instanceof we.a){var e=this._projectionTexture.uScale/2,n=this._projectionTexture.vScale/2;u.a.FromValuesToRef(e,0,0,0,0,n,0,0,0,0,.5,0,.5,.5,.5,1,this._projectionTextureScalingMatrix)}this._projectionTextureMatrix.multiplyToRef(this._projectionTextureScalingMatrix,this._projectionTextureMatrix)},t.prototype._buildUniformLayout=function(){this._uniformBuffer.addUniform("vLightData",4),this._uniformBuffer.addUniform("vLightDiffuse",4),this._uniformBuffer.addUniform("vLightSpecular",4),this._uniformBuffer.addUniform("vLightDirection",3),this._uniformBuffer.addUniform("vLightFalloff",4),this._uniformBuffer.addUniform("shadowsInfo",3),this._uniformBuffer.addUniform("depthValues",2),this._uniformBuffer.create()},t.prototype._computeAngleValues=function(){this._lightAngleScale=1/Math.max(.001,Math.cos(.5*this._innerAngle)-this._cosHalfAngle),this._lightAngleOffset=-this._cosHalfAngle*this._lightAngleScale},t.prototype.transferTexturesToEffect=function(e,n){return this.projectionTexture&&this.projectionTexture.isReady()&&(this._projectionTextureViewLightDirty&&this._computeProjectionTextureViewLightMatrix(),this._projectionTextureProjectionLightDirty&&this._computeProjectionTextureProjectionLightMatrix(),this._projectionTextureDirty&&this._computeProjectionTextureMatrix(),e.setMatrix("textureProjectionMatrix"+n,this._projectionTextureMatrix),e.setTexture("projectionLightSampler"+n,this.projectionTexture)),this},t.prototype.transferToEffect=function(e,n){var i;return this.computeTransformedInformation()?(this._uniformBuffer.updateFloat4("vLightData",this.transformedPosition.x,this.transformedPosition.y,this.transformedPosition.z,this.exponent,n),i=u.e.Normalize(this.transformedDirection)):(this._uniformBuffer.updateFloat4("vLightData",this.position.x,this.position.y,this.position.z,this.exponent,n),i=u.e.Normalize(this.direction)),this._uniformBuffer.updateFloat4("vLightDirection",i.x,i.y,i.z,this._cosHalfAngle,n),this._uniformBuffer.updateFloat4("vLightFalloff",this.range,this._inverseSquaredRange,this._lightAngleScale,this._lightAngleOffset,n),this},t.prototype.transferToNodeMaterialEffect=function(e,n){var i;return i=this.computeTransformedInformation()?u.e.Normalize(this.transformedDirection):u.e.Normalize(this.direction),this.getScene().useRightHandedSystem?e.setFloat3(n,-i.x,-i.y,-i.z):e.setFloat3(n,i.x,i.y,i.z),this},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._projectionTexture&&this._projectionTexture.dispose()},t.prototype.prepareLightSpecificDefines=function(e,n){e["SPOTLIGHT"+n]=!0,e["PROJECTEDLIGHTTEXTURE"+n]=!(!this.projectionTexture||!this.projectionTexture.isReady())},Object(c.c)([Object(L.c)()],t.prototype,"angle",null),Object(c.c)([Object(L.c)()],t.prototype,"innerAngle",null),Object(c.c)([Object(L.c)()],t.prototype,"shadowAngleScale",null),Object(c.c)([Object(L.c)()],t.prototype,"exponent",void 0),Object(c.c)([Object(L.c)()],t.prototype,"projectionTextureLightNear",null),Object(c.c)([Object(L.c)()],t.prototype,"projectionTextureLightFar",null),Object(c.c)([Object(L.c)()],t.prototype,"projectionTextureUpDirection",null),Object(c.c)([Object(L.m)("projectedLightTexture")],t.prototype,"_projectionTexture",void 0),t}(qo),pp=function(r){function t(e){e===void 0&&(e=On.a.DefaultUtilityLayer);var n=r.call(this,e)||this;return n._cachedPosition=new u.e,n._cachedForward=new u.e(0,0,1),n._pointerObserver=null,n.onClickedObservable=new C.c,n._light=null,n.attachedMesh=new Dt.a("",n.gizmoLayer.utilityLayerScene),n._attachedMeshParent=new Er.a("parent",n.gizmoLayer.utilityLayerScene),n.attachedMesh.parent=n._attachedMeshParent,n._material=new Ft.a("light",n.gizmoLayer.utilityLayerScene),n._material.diffuseColor=new M.a(.5,.5,.5),n._material.specularColor=new M.a(.1,.1,.1),n._pointerObserver=e.utilityLayerScene.onPointerObservable.add(function(i){n._light&&(n._isHovered=!(!i.pickInfo||n._rootMesh.getChildMeshes().indexOf(i.pickInfo.pickedMesh)==-1),n._isHovered&&i.event.button===0&&n.onClickedObservable.notifyObservers(n._light))},Tt.a.POINTERDOWN),n}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"light",{get:function(){return this._light},set:function(e){var n=this;if(this._light=e,e){this._lightMesh&&this._lightMesh.dispose(),e instanceof Vo.a?this._lightMesh=t._CreateHemisphericLightMesh(this.gizmoLayer.utilityLayerScene):this._lightMesh=e instanceof Is?t._CreateDirectionalLightMesh(this.gizmoLayer.utilityLayerScene):e instanceof Ds?t._CreateSpotLightMesh(this.gizmoLayer.utilityLayerScene):t._CreatePointLightMesh(this.gizmoLayer.utilityLayerScene),this._lightMesh.getChildMeshes(!1).forEach(function(o){o.material=n._material}),this._lightMesh.parent=this._rootMesh;var i=this.gizmoLayer._getSharedGizmoLight();i.includedOnlyMeshes=i.includedOnlyMeshes.concat(this._lightMesh.getChildMeshes(!1)),this._lightMesh.rotationQuaternion=new u.b,this.attachedMesh.reservedDataStore||(this.attachedMesh.reservedDataStore={}),this.attachedMesh.reservedDataStore.lightGizmo=this,e.parent&&this._attachedMeshParent.freezeWorldMatrix(e.parent.getWorldMatrix()),e.position&&(this.attachedMesh.position.copyFrom(e.position),this.attachedMesh.computeWorldMatrix(!0),this._cachedPosition.copyFrom(this.attachedMesh.position)),e.direction&&(this.attachedMesh.setDirection(e.direction),this.attachedMesh.computeWorldMatrix(!0),this._cachedForward.copyFrom(this.attachedMesh.forward)),this._update()}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"material",{get:function(){return this._material},enumerable:!1,configurable:!0}),t.prototype._update=function(){r.prototype._update.call(this),this._light&&(this._light.parent&&this._attachedMeshParent.freezeWorldMatrix(this._light.parent.getWorldMatrix()),this._light.position&&(this.attachedMesh.position.equals(this._cachedPosition)?(this.attachedMesh.position.copyFrom(this._light.position),this.attachedMesh.computeWorldMatrix(!0),this._cachedPosition.copyFrom(this.attachedMesh.position)):(this._light.position.copyFrom(this.attachedMesh.position),this._cachedPosition.copyFrom(this.attachedMesh.position))),this._light.direction&&(u.e.DistanceSquared(this.attachedMesh.forward,this._cachedForward)>1e-4?(this._light.direction.copyFrom(this.attachedMesh.forward),this._cachedForward.copyFrom(this.attachedMesh.forward)):u.e.DistanceSquared(this.attachedMesh.forward,this._light.direction)>1e-4&&(this.attachedMesh.setDirection(this._light.direction),this.attachedMesh.computeWorldMatrix(!0),this._cachedForward.copyFrom(this.attachedMesh.forward))))},t.prototype.dispose=function(){this.onClickedObservable.clear(),this.gizmoLayer.utilityLayerScene.onPointerObservable.remove(this._pointerObserver),this._material.dispose(),r.prototype.dispose.call(this),this._attachedMeshParent.dispose()},t._CreateHemisphericLightMesh=function(e){var n=new De.a("hemisphereLight",e),i=Zo.CreateHemisphere(n.name,{segments:10,diameter:1},e);i.position.z=-.15,i.rotation.x=Math.PI/2,i.parent=n;var o=this._CreateLightLines(3,e);return o.parent=n,o.position.z,n.scaling.scaleInPlace(t._Scale),n.rotation.x=Math.PI/2,n},t._CreatePointLightMesh=function(e){var n=new De.a("pointLight",e),i=Fn.a.CreateSphere(n.name,{segments:10,diameter:1},e);return i.rotation.x=Math.PI/2,i.parent=n,this._CreateLightLines(5,e).parent=n,n.scaling.scaleInPlace(t._Scale),n.rotation.x=Math.PI/2,n},t._CreateSpotLightMesh=function(e){var n=new De.a("spotLight",e);Fn.a.CreateSphere(n.name,{segments:10,diameter:1},e).parent=n;var i=Zo.CreateHemisphere(n.name,{segments:10,diameter:2},e);return i.parent=n,i.rotation.x=-Math.PI/2,this._CreateLightLines(2,e).parent=n,n.scaling.scaleInPlace(t._Scale),n.rotation.x=Math.PI/2,n},t._CreateDirectionalLightMesh=function(e){var n=new De.a("directionalLight",e),i=new De.a(n.name,e);i.parent=n,Fn.a.CreateSphere(n.name,{diameter:1.2,segments:10},e).parent=i;var o=De.a.CreateCylinder(n.name,6,.3,.3,6,1,e);o.parent=i,(a=o.clone(n.name)).scaling.y=.5,a.position.x+=1.25,(s=o.clone(n.name)).scaling.y=.5,s.position.x+=-1.25;var a,s,d=De.a.CreateCylinder(n.name,1,0,.6,6,1,e);return d.position.y+=3,d.parent=i,(a=d.clone(n.name)).position.y=1.5,a.position.x+=1.25,(s=d.clone(n.name)).position.y=1.5,s.position.x+=-1.25,i.scaling.scaleInPlace(t._Scale),i.rotation.z=Math.PI/2,i.rotation.y=Math.PI/2,n},t._Scale=.007,t._CreateLightLines=function(e,n){var i=new De.a("root",n);i.rotation.x=Math.PI/2;var o=new De.a("linePivot",n);o.parent=i;var a=De.a.CreateCylinder("line",2,.2,.3,6,1,n);if(a.position.y=a.scaling.y/2+1.2,a.parent=o,e<2)return o;for(var s=0;s<4;s++)(d=o.clone("lineParentClone")).rotation.z=Math.PI/4,d.rotation.y=Math.PI/2+Math.PI/2*s,d.getChildMeshes()[0].scaling.y=.5,d.getChildMeshes()[0].scaling.x=d.getChildMeshes()[0].scaling.z=.8,d.getChildMeshes()[0].position.y=d.getChildMeshes()[0].scaling.y/2+1.2;if(e<3)return i;for(s=0;s<4;s++)(d=o.clone("linePivotClone")).rotation.z=Math.PI/2,d.rotation.y=Math.PI/2*s;if(e<4)return i;for(s=0;s<4;s++){var d;(d=o.clone("linePivotClone")).rotation.z=Math.PI+Math.PI/4,d.rotation.y=Math.PI/2+Math.PI/2*s,d.getChildMeshes()[0].scaling.y=.5,d.getChildMeshes()[0].scaling.x=d.getChildMeshes()[0].scaling.z=.8,d.getChildMeshes()[0].position.y=d.getChildMeshes()[0].scaling.y/2+1.2}return e<5||((d=o.clone("linePivotClone")).rotation.z=Math.PI),i},t}(wn.a),Ls=function(){function r(t,e){t===void 0&&(t=u.e.Zero()),e===void 0&&(e=u.e.Up()),this.position=t,this.normal=e}return r.prototype.clone=function(){return new r(this.position.clone(),this.normal.clone())},r}(),_p=function(){function r(t,e,n){t===void 0&&(t=u.e.Zero()),e===void 0&&(e=u.e.Up()),n===void 0&&(n=u.d.Zero()),this.position=t,this.normal=e,this.uv=n}return r.prototype.clone=function(){return new r(this.position.clone(),this.normal.clone(),this.uv.clone())},r}(),mp=function(r){function t(e){e===void 0&&(e=On.a.DefaultUtilityLayer);var n=r.call(this,e)||this;return n._pointerObserver=null,n.onClickedObservable=new C.c,n._camera=null,n._invProjection=new u.a,n._material=new Ft.a("cameraGizmoMaterial",n.gizmoLayer.utilityLayerScene),n._material.diffuseColor=new M.a(.5,.5,.5),n._material.specularColor=new M.a(.1,.1,.1),n._pointerObserver=e.utilityLayerScene.onPointerObservable.add(function(i){n._camera&&(n._isHovered=!(!i.pickInfo||n._rootMesh.getChildMeshes().indexOf(i.pickInfo.pickedMesh)==-1),n._isHovered&&i.event.button===0&&n.onClickedObservable.notifyObservers(n._camera))},Tt.a.POINTERDOWN),n}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"displayFrustum",{get:function(){return this._cameraLinesMesh.isEnabled()},set:function(e){this._cameraLinesMesh.setEnabled(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"camera",{get:function(){return this._camera},set:function(e){var n=this;if(this._camera=e,this.attachedNode=e,e){this._cameraMesh&&this._cameraMesh.dispose(),this._cameraLinesMesh&&this._cameraLinesMesh.dispose(),this._cameraMesh=t._CreateCameraMesh(this.gizmoLayer.utilityLayerScene),this._cameraLinesMesh=t._CreateCameraFrustum(this.gizmoLayer.utilityLayerScene),this._cameraMesh.getChildMeshes(!1).forEach(function(o){o.material=n._material}),this._cameraMesh.parent=this._rootMesh,this._cameraLinesMesh.parent=this._rootMesh,this.gizmoLayer.utilityLayerScene.activeCamera&&this.gizmoLayer.utilityLayerScene.activeCamera.maxZ<1.5*e.maxZ&&(this.gizmoLayer.utilityLayerScene.activeCamera.maxZ=1.5*e.maxZ),this.attachedNode.reservedDataStore||(this.attachedNode.reservedDataStore={}),this.attachedNode.reservedDataStore.cameraGizmo=this;var i=this.gizmoLayer._getSharedGizmoLight();i.includedOnlyMeshes=i.includedOnlyMeshes.concat(this._cameraMesh.getChildMeshes(!1)),this._update()}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"material",{get:function(){return this._material},enumerable:!1,configurable:!0}),t.prototype._update=function(){r.prototype._update.call(this),this._camera&&(this._camera.getProjectionMatrix().invertToRef(this._invProjection),this._cameraLinesMesh.setPivotMatrix(this._invProjection,!1),this._cameraLinesMesh.scaling.x=1/this._rootMesh.scaling.x,this._cameraLinesMesh.scaling.y=1/this._rootMesh.scaling.y,this._cameraLinesMesh.scaling.z=1/this._rootMesh.scaling.z,this._cameraMesh.parent=null,this._cameraMesh.rotation.y=.5*Math.PI*(this._camera.getScene().useRightHandedSystem?1:-1),this._cameraMesh.parent=this._rootMesh)},t.prototype.dispose=function(){this.onClickedObservable.clear(),this.gizmoLayer.utilityLayerScene.onPointerObservable.remove(this._pointerObserver),this._cameraMesh&&this._cameraMesh.dispose(),this._cameraLinesMesh&&this._cameraLinesMesh.dispose(),this._material.dispose(),r.prototype.dispose.call(this)},t._CreateCameraMesh=function(e){var n=new De.a("rootCameraGizmo",e),i=new De.a(n.name,e);i.parent=n,Tr.a.CreateBox(n.name,{width:1,height:.8,depth:.5},e).parent=i;var o=pi.a.CreateCylinder(n.name,{height:.5,diameterTop:.8,diameterBottom:.8},e);o.parent=i,o.position.y=.3,o.position.x=-.6,o.rotation.x=.5*Math.PI;var a=pi.a.CreateCylinder(n.name,{height:.5,diameterTop:.6,diameterBottom:.6},e);a.parent=i,a.position.y=.5,a.position.x=.4,a.rotation.x=.5*Math.PI;var s=pi.a.CreateCylinder(n.name,{height:.5,diameterTop:.5,diameterBottom:.5},e);return s.parent=i,s.position.y=0,s.position.x=.6,s.rotation.z=.5*Math.PI,n.scaling.scaleInPlace(t._Scale),i.position.x=-.9,n},t._CreateCameraFrustum=function(e){var n=new De.a("rootCameraGizmo",e),i=new De.a(n.name,e);i.parent=n;for(var o=0;o<4;o+=2)for(var a=0;a<4;a+=2){var s;(s=cn.a.CreateLines("lines",{points:[new u.e(-1+a,-1+o,-1),new u.e(-1+a,-1+o,1)]},e)).parent=i,s.alwaysSelectAsActiveMesh=!0,s.isPickable=!1,(s=cn.a.CreateLines("lines",{points:[new u.e(-1,-1+a,-1+o),new u.e(1,-1+a,-1+o)]},e)).parent=i,s.alwaysSelectAsActiveMesh=!0,s.isPickable=!1,(s=cn.a.CreateLines("lines",{points:[new u.e(-1+a,-1,-1+o),new u.e(-1+a,1,-1+o)]},e)).parent=i,s.alwaysSelectAsActiveMesh=!0,s.isPickable=!1}return n},t._Scale=.05,t}(wn.a);ze.a.IncludesShadersStore.kernelBlurVaryingDeclaration="varying vec2 sampleCoord{X};";var gp=`vec4 pack(float depth)
-{
-const vec4 bit_shift=vec4(255.0*255.0*255.0,255.0*255.0,255.0,1.0);
-const vec4 bit_mask=vec4(0.0,1.0/255.0,1.0/255.0,1.0/255.0);
-vec4 res=fract(depth*bit_shift);
-res-=res.xxyz*bit_mask;
-return res;
-}
-float unpack(vec4 color)
-{
-const vec4 bit_shift=vec4(1.0/(255.0*255.0*255.0),1.0/(255.0*255.0),1.0/255.0,1.0);
-return dot(color,bit_shift);
-}`;ze.a.IncludesShadersStore.packingFunctions=gp;var vp=`#ifdef DOF
-factor=sampleCoC(sampleCoord{X});
-computedWeight=KERNEL_WEIGHT{X}*factor;
-sumOfWeights+=computedWeight;
-#else
-computedWeight=KERNEL_WEIGHT{X};
-#endif
-#ifdef PACKEDFLOAT
-blend+=unpack(texture2D(textureSampler,sampleCoord{X}))*computedWeight;
-#else
-blend+=texture2D(textureSampler,sampleCoord{X})*computedWeight;
-#endif`;ze.a.IncludesShadersStore.kernelBlurFragment=vp;var bp=`#ifdef DOF
-factor=sampleCoC(sampleCenter+delta*KERNEL_DEP_OFFSET{X});
-computedWeight=KERNEL_DEP_WEIGHT{X}*factor;
-sumOfWeights+=computedWeight;
-#else
-computedWeight=KERNEL_DEP_WEIGHT{X};
-#endif
-#ifdef PACKEDFLOAT
-blend+=unpack(texture2D(textureSampler,sampleCenter+delta*KERNEL_DEP_OFFSET{X}))*computedWeight;
-#else
-blend+=texture2D(textureSampler,sampleCenter+delta*KERNEL_DEP_OFFSET{X})*computedWeight;
-#endif`;ze.a.IncludesShadersStore.kernelBlurFragment2=bp;var yp=`
-uniform sampler2D textureSampler;
-uniform vec2 delta;
-
-varying vec2 sampleCenter;
-#ifdef DOF
-uniform sampler2D circleOfConfusionSampler;
-uniform vec2 cameraMinMaxZ;
-float sampleDistance(const in vec2 offset) {
-float depth=texture2D(circleOfConfusionSampler,offset).g;
-return cameraMinMaxZ.x+(cameraMinMaxZ.y-cameraMinMaxZ.x)*depth;
-}
-float sampleCoC(const in vec2 offset) {
-float coc=texture2D(circleOfConfusionSampler,offset).r;
-return coc;
-}
-#endif
-#include<kernelBlurVaryingDeclaration>[0..varyingCount]
-#ifdef PACKEDFLOAT
-#include<packingFunctions>
-#endif
-void main(void)
-{
-float computedWeight=0.0;
-#ifdef PACKEDFLOAT
-float blend=0.;
-#else
-vec4 blend=vec4(0.);
-#endif
-#ifdef DOF
-float sumOfWeights=CENTER_WEIGHT;
-float factor=0.0;
-
-#ifdef PACKEDFLOAT
-blend+=unpack(texture2D(textureSampler,sampleCenter))*CENTER_WEIGHT;
-#else
-blend+=texture2D(textureSampler,sampleCenter)*CENTER_WEIGHT;
-#endif
-#endif
-#include<kernelBlurFragment>[0..varyingCount]
-#include<kernelBlurFragment2>[0..depCount]
-#ifdef PACKEDFLOAT
-gl_FragColor=pack(blend);
-#else
-gl_FragColor=blend;
-#endif
-#ifdef DOF
-gl_FragColor/=sumOfWeights;
-#endif
-}`;ze.a.ShadersStore.kernelBlurPixelShader=yp,ze.a.IncludesShadersStore.kernelBlurVertex="sampleCoord{X}=sampleCenter+delta*KERNEL_OFFSET{X};";var Tp=`
-attribute vec2 position;
-
-uniform vec2 delta;
-
-varying vec2 sampleCenter;
-#include<kernelBlurVaryingDeclaration>[0..varyingCount]
-const vec2 madd=vec2(0.5,0.5);
-void main(void) {
-sampleCenter=(position*madd+madd);
-#include<kernelBlurVertex>[0..varyingCount]
-gl_Position=vec4(position,0.0,1.0);
-}`;ze.a.ShadersStore.kernelBlurVertexShader=Tp;var gn=function(r){function t(e,n,i,o,a,s,d,p,b,P,O){s===void 0&&(s=we.a.BILINEAR_SAMPLINGMODE),b===void 0&&(b=h.a.TEXTURETYPE_UNSIGNED_INT),P===void 0&&(P=""),O===void 0&&(O=!1);var B=r.call(this,e,"kernelBlur",["delta","direction","cameraMinMaxZ"],["circleOfConfusionSampler"],o,a,s,d,p,null,b,"kernelBlur",{varyingCount:0,depCount:0},!0)||this;return B.blockCompilation=O,B._packedFloat=!1,B._staticDefines="",B._staticDefines=P,B.direction=n,B.onApplyObservable.add(function(F){B._outputTexture?F.setFloat2("delta",1/B._outputTexture.width*B.direction.x,1/B._outputTexture.height*B.direction.y):F.setFloat2("delta",1/B.width*B.direction.x,1/B.height*B.direction.y)}),B.kernel=i,B}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"kernel",{get:function(){return this._idealKernel},set:function(e){this._idealKernel!==e&&(e=Math.max(e,1),this._idealKernel=e,this._kernel=this._nearestBestKernel(e),this.blockCompilation||this._updateParameters())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"packedFloat",{get:function(){return this._packedFloat},set:function(e){this._packedFloat!==e&&(this._packedFloat=e,this.blockCompilation||this._updateParameters())},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"BlurPostProcess"},t.prototype.updateEffect=function(e,n,i,o,a,s){this._updateParameters(a,s)},t.prototype._updateParameters=function(e,n){for(var i=this._kernel,o=(i-1)/2,a=[],s=[],d=0,p=0;p<i;p++){var b=p/(i-1),P=this._gaussianWeight(2*b-1);a[p]=p-o,s[p]=P,d+=P}for(p=0;p<s.length;p++)s[p]/=d;var O=[],B=[],F=[];for(p=0;p<=o;p+=2){var z=Math.min(p+1,Math.floor(o));if(p===z)F.push({o:a[p],w:s[p]});else{var J=z===o,ie=s[p]+s[z]*(J?.5:1),se=a[p]+1/(1+s[p]/s[z]);se===0?(F.push({o:a[p],w:s[p]}),F.push({o:a[p+1],w:s[p+1]})):(F.push({o:se,w:ie}),F.push({o:-se,w:ie}))}}for(p=0;p<F.length;p++)B[p]=F[p].o,O[p]=F[p].w;a=B,s=O;var ce=this.getEngine().getCaps().maxVaryingVectors,ue=Math.max(ce,0)-1,fe=Math.min(a.length,ue),ve="";for(ve+=this._staticDefines,this._staticDefines.indexOf("DOF")!=-1&&(ve+="#define CENTER_WEIGHT "+this._glslFloat(s[fe-1])+`\r
-`,fe--),p=0;p<fe;p++)ve+="#define KERNEL_OFFSET"+p+" "+this._glslFloat(a[p])+`\r
-`,ve+="#define KERNEL_WEIGHT"+p+" "+this._glslFloat(s[p])+`\r
-`;var Te=0;for(p=ue;p<a.length;p++)ve+="#define KERNEL_DEP_OFFSET"+Te+" "+this._glslFloat(a[p])+`\r
-`,ve+="#define KERNEL_DEP_WEIGHT"+Te+" "+this._glslFloat(s[p])+`\r
-`,Te++;this.packedFloat&&(ve+="#define PACKEDFLOAT 1"),this.blockCompilation=!1,r.prototype.updateEffect.call(this,ve,null,null,{varyingCount:fe,depCount:Te},e,n)},t.prototype._nearestBestKernel=function(e){for(var n=Math.round(e),i=0,o=[n,n-1,n+1,n-2,n+2];i<o.length;i++){var a=o[i];if(a%2!=0&&Math.floor(a/2)%2==0&&a>0)return Math.max(a,3)}return Math.max(n,3)},t.prototype._gaussianWeight=function(e){var n=-e*e/.2222222222222222;return 1/(Math.sqrt(2*Math.PI)*(1/3))*Math.exp(n)},t.prototype._glslFloat=function(e,n){return n===void 0&&(n=8),e.toFixed(n).replace(/0+$/,"")},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.direction,e.kernel,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable,e.textureType,void 0,!1)},e,i,o)},Object(c.c)([Object(L.c)("kernel")],t.prototype,"_kernel",void 0),Object(c.c)([Object(L.c)("packedFloat")],t.prototype,"_packedFloat",void 0),Object(c.c)([Object(L.n)()],t.prototype,"direction",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.BlurPostProcess"]=gn;var Ns=function(r){function t(e,n,i,o,a,s,d){a===void 0&&(a=h.a.TEXTURETYPE_UNSIGNED_INT),s===void 0&&(s=we.a.BILINEAR_SAMPLINGMODE),d===void 0&&(d=!0);var p=r.call(this,e,n,i,o,!0,a,!1,s,d)||this;return p.scene=i,p.mirrorPlane=new vr.a(0,1,0,1),p._transformMatrix=u.a.Zero(),p._mirrorMatrix=u.a.Zero(),p._adaptiveBlurKernel=0,p._blurKernelX=0,p._blurKernelY=0,p._blurRatio=1,p.ignoreCameraViewport=!0,p._updateGammaSpace(),p._imageProcessingConfigChangeObserver=i.imageProcessingConfiguration.onUpdateParameters.add(function(){p._updateGammaSpace}),p.onBeforeRenderObservable.add(function(){u.a.ReflectionToRef(p.mirrorPlane,p._mirrorMatrix),p._savedViewMatrix=i.getViewMatrix(),p._mirrorMatrix.multiplyToRef(p._savedViewMatrix,p._transformMatrix),i.setTransformMatrix(p._transformMatrix,i.getProjectionMatrix()),i.clipPlane=p.mirrorPlane,i.getEngine().cullBackFaces=!1,i._mirroredCameraPosition=u.e.TransformCoordinates(i.activeCamera.globalPosition,p._mirrorMatrix)}),p.onAfterRenderObservable.add(function(){i.setTransformMatrix(p._savedViewMatrix,i.getProjectionMatrix()),i.getEngine().cullBackFaces=!0,i._mirroredCameraPosition=null,i.clipPlane=null}),p}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"blurRatio",{get:function(){return this._blurRatio},set:function(e){this._blurRatio!==e&&(this._blurRatio=e,this._preparePostProcesses())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"adaptiveBlurKernel",{set:function(e){this._adaptiveBlurKernel=e,this._autoComputeBlurKernel()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"blurKernel",{set:function(e){this.blurKernelX=e,this.blurKernelY=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"blurKernelX",{get:function(){return this._blurKernelX},set:function(e){this._blurKernelX!==e&&(this._blurKernelX=e,this._preparePostProcesses())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"blurKernelY",{get:function(){return this._blurKernelY},set:function(e){this._blurKernelY!==e&&(this._blurKernelY=e,this._preparePostProcesses())},enumerable:!1,configurable:!0}),t.prototype._autoComputeBlurKernel=function(){var e=this.getScene().getEngine(),n=this.getRenderWidth()/e.getRenderWidth(),i=this.getRenderHeight()/e.getRenderHeight();this.blurKernelX=this._adaptiveBlurKernel*n,this.blurKernelY=this._adaptiveBlurKernel*i},t.prototype._onRatioRescale=function(){this._sizeRatio&&(this.resize(this._initialSizeParameter),this._adaptiveBlurKernel||this._preparePostProcesses()),this._adaptiveBlurKernel&&this._autoComputeBlurKernel()},t.prototype._updateGammaSpace=function(){this.gammaSpace=!this.scene.imageProcessingConfiguration.isEnabled||!this.scene.imageProcessingConfiguration.applyByPostProcess},t.prototype._preparePostProcesses=function(){if(this.clearPostProcesses(!0),this._blurKernelX&&this._blurKernelY){var e=this.getScene().getEngine(),n=e.getCaps().textureFloatRender?h.a.TEXTURETYPE_FLOAT:h.a.TEXTURETYPE_HALF_FLOAT;this._blurX=new gn("horizontal blur",new u.d(1,0),this._blurKernelX,this._blurRatio,null,we.a.BILINEAR_SAMPLINGMODE,e,!1,n),this._blurX.autoClear=!1,this._blurRatio===1&&this.samples<2&&this._texture?this._blurX.inputTexture=this._texture:this._blurX.alwaysForcePOT=!0,this._blurY=new gn("vertical blur",new u.d(0,1),this._blurKernelY,this._blurRatio,null,we.a.BILINEAR_SAMPLINGMODE,e,!1,n),this._blurY.autoClear=!1,this._blurY.alwaysForcePOT=this._blurRatio!==1,this.addPostProcess(this._blurX),this.addPostProcess(this._blurY)}else this._blurY&&(this.removePostProcess(this._blurY),this._blurY.dispose(),this._blurY=null),this._blurX&&(this.removePostProcess(this._blurX),this._blurX.dispose(),this._blurX=null)},t.prototype.clone=function(){var e=this.getScene();if(!e)return this;var n=this.getSize(),i=new t(this.name,n.width,e,this._renderTargetOptions.generateMipMaps,this._renderTargetOptions.type,this._renderTargetOptions.samplingMode,this._renderTargetOptions.generateDepthBuffer);return i.hasAlpha=this.hasAlpha,i.level=this.level,i.mirrorPlane=this.mirrorPlane.clone(),this.renderList&&(i.renderList=this.renderList.slice(0)),i},t.prototype.serialize=function(){if(!this.name)return null;var e=r.prototype.serialize.call(this);return e.mirrorPlane=this.mirrorPlane.asArray(),e},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.scene.imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingConfigChangeObserver)},t}(sn);we.a._CreateMirror=function(r,t,e,n){return new Ns(r,t,e,n)};var Qn=f(34),oi=function(r){function t(e,n,i,o,a,s,d,p,b,P,O,B,F,z){var J;i===void 0&&(i=null),o===void 0&&(o=!1),a===void 0&&(a=null),s===void 0&&(s=null),d===void 0&&(d=null),p===void 0&&(p=h.a.TEXTUREFORMAT_RGBA),b===void 0&&(b=!1),P===void 0&&(P=null),O===void 0&&(O=!1),B===void 0&&(B=.8),F===void 0&&(F=0);var ie=r.call(this,n)||this;if(ie.onLoadObservable=new C.c,ie.boundingBoxPosition=u.e.Zero(),ie._rotationY=0,ie._files=null,ie._forcedExtension=null,ie._extensions=null,ie.name=e,ie.url=e,ie._noMipmap=o,ie.hasAlpha=!1,ie._format=p,ie.isCube=!0,ie._textureMatrix=u.a.Identity(),ie._createPolynomials=O,ie.coordinatesMode=we.a.CUBIC_MODE,ie._extensions=i,ie._files=a,ie._forcedExtension=P,ie._loaderOptions=z,!e&&!a)return ie;var se=e.lastIndexOf("."),ce=P||(se>-1?e.substring(se).toLowerCase():""),ue=ce===".dds",fe=ce===".env";if(fe?(ie.gammaSpace=!1,ie._prefiltered=!1,ie.anisotropicFilteringLevel=1):(ie._prefiltered=b,b&&(ie.gammaSpace=!1,ie.anisotropicFilteringLevel=1)),ie._texture=ie._getFromCache(e,o),!a&&(fe||ue||i||(i=["_px.jpg","_py.jpg","_pz.jpg","_nx.jpg","_ny.jpg","_nz.jpg"]),a=[],i))for(var ve=0;ve<i.length;ve++)a.push(e+i[ve]);ie._files=a;var Te=function(){ie.onLoadObservable.notifyObservers(ie),s&&s()};if(ie._texture)ie._texture.isReady?Xe.b.SetImmediate(function(){return Te()}):ie._texture.onLoadedObservable.add(function(){return Te()});else{var Re=ie.getScene();Re?.useDelayedTextureLoading?ie.delayLoadState=h.a.DELAYLOADSTATE_NOTLOADED:(ie._texture=b?ie._getEngine().createPrefilteredCubeTexture(e,Re,B,F,s,d,p,P,ie._createPolynomials):ie._getEngine().createCubeTexture(e,Re,a,o,s,d,ie._format,P,!1,B,F,null,z),(J=ie._texture)===null||J===void 0||J.onLoadedObservable.add(function(){return ie.onLoadObservable.notifyObservers(ie)}))}return ie}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"boundingBoxSize",{get:function(){return this._boundingBoxSize},set:function(e){if(!this._boundingBoxSize||!this._boundingBoxSize.equals(e)){this._boundingBoxSize=e;var n=this.getScene();n&&n.markAllMaterialsAsDirty(h.a.MATERIAL_TextureDirtyFlag)}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rotationY",{get:function(){return this._rotationY},set:function(e){this._rotationY=e,this.setReflectionTextureMatrix(u.a.RotationY(this._rotationY))},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"noMipmap",{get:function(){return this._noMipmap},enumerable:!1,configurable:!0}),t.CreateFromImages=function(e,n,i){var o="";return e.forEach(function(a){return o+=a}),new t(o,n,null,i,e)},t.CreateFromPrefilteredData=function(e,n,i,o){i===void 0&&(i=null),o===void 0&&(o=!0);var a=n.useDelayedTextureLoading;n.useDelayedTextureLoading=!1;var s=new t(e,n,null,!1,null,null,null,void 0,!0,i,o);return n.useDelayedTextureLoading=a,s},t.prototype.getClassName=function(){return"CubeTexture"},t.prototype.updateURL=function(e,n,i,o){var a;o===void 0&&(o=!1),this.url&&(this.releaseInternalTexture(),(a=this.getScene())===null||a===void 0||a.markAllMaterialsAsDirty(h.a.MATERIAL_TextureDirtyFlag)),this.name&&!Qn.a.StartsWith(this.name,"data:")||(this.name=e),this.url=e,this.delayLoadState=h.a.DELAYLOADSTATE_NOTLOADED,this._prefiltered=o,this._prefiltered&&(this.gammaSpace=!1,this.anisotropicFilteringLevel=1),this._forcedExtension=n||null,i&&(this._delayedOnLoad=i),this.delayLoad(n)},t.prototype.delayLoad=function(e){var n,i=this;if(this.delayLoadState===h.a.DELAYLOADSTATE_NOTLOADED&&(this.delayLoadState=h.a.DELAYLOADSTATE_LOADED,this._texture=this._getFromCache(this.url,this._noMipmap),!this._texture)){var o=this.getScene();this._prefiltered?this._texture=this._getEngine().createPrefilteredCubeTexture(this.url,o,.8,0,this._delayedOnLoad,void 0,this._format,e,this._createPolynomials):this._texture=this._getEngine().createCubeTexture(this.url,o,this._files,this._noMipmap,this._delayedOnLoad,null,this._format,e,!1,0,0,null,this._loaderOptions),(n=this._texture)===null||n===void 0||n.onLoadedObservable.add(function(){return i.onLoadObservable.notifyObservers(i)})}},t.prototype.getReflectionTextureMatrix=function(){return this._textureMatrix},t.prototype.setReflectionTextureMatrix=function(e){var n,i=this;e.updateFlag!==this._textureMatrix.updateFlag&&(e.isIdentity()!==this._textureMatrix.isIdentity()&&((n=this.getScene())===null||n===void 0||n.markAllMaterialsAsDirty(h.a.MATERIAL_TextureDirtyFlag,function(o){return o.getActiveTextures().indexOf(i)!==-1})),this._textureMatrix=e)},t.Parse=function(e,n,i){var o=L.a.Parse(function(){var p=!1;return e.prefiltered&&(p=e.prefiltered),new t(i+e.name,n,e.extensions,!1,e.files||null,null,null,void 0,p,e.forcedExtension)},e,n);if(e.boundingBoxPosition&&(o.boundingBoxPosition=u.e.FromArray(e.boundingBoxPosition)),e.boundingBoxSize&&(o.boundingBoxSize=u.e.FromArray(e.boundingBoxSize)),e.animations)for(var a=0;a<e.animations.length;a++){var s=e.animations[a],d=R.a.GetClass("BABYLON.Animation");d&&o.animations.push(d.Parse(s))}return o},t.prototype.clone=function(){var e=this,n=0,i=L.a.Clone(function(){var o=new t(e.url,e.getScene()||e._getEngine(),e._extensions,e._noMipmap,e._files);return n=o.uniqueId,o},this);return i.uniqueId=n,i},Object(c.c)([Object(L.c)()],t.prototype,"url",void 0),Object(c.c)([Object(L.c)("rotationY")],t.prototype,"rotationY",null),Object(c.c)([Object(L.c)("files")],t.prototype,"_files",void 0),Object(c.c)([Object(L.c)("forcedExtension")],t.prototype,"_forcedExtension",void 0),Object(c.c)([Object(L.c)("extensions")],t.prototype,"_extensions",void 0),Object(c.c)([Object(L.j)("textureMatrix")],t.prototype,"_textureMatrix",void 0),t}(zn.a);we.a._CubeTextureParser=oi.Parse,R.a.RegisteredTypes["BABYLON.CubeTexture"]=oi;var et=f(15),Jo=f(76),$o=f(87),ht=f(19),Ep=` uniform vec4 vPrimaryColor;
-#ifdef USEHIGHLIGHTANDSHADOWCOLORS
-uniform vec4 vPrimaryColorShadow;
-#endif
-uniform float shadowLevel;
-uniform float alpha;
-#ifdef DIFFUSE
-uniform vec2 vDiffuseInfos;
-#endif
-#ifdef REFLECTION
-uniform vec2 vReflectionInfos;
-uniform mat4 reflectionMatrix;
-uniform vec3 vReflectionMicrosurfaceInfos;
-#endif
-#if defined(REFLECTIONFRESNEL) || defined(OPACITYFRESNEL)
-uniform vec3 vBackgroundCenter;
-#endif
-#ifdef REFLECTIONFRESNEL
-uniform vec4 vReflectionControl;
-#endif
-#if defined(REFLECTIONMAP_SPHERICAL) || defined(REFLECTIONMAP_PROJECTION) || defined(REFRACTION)
-uniform mat4 view;
-#endif`;ze.a.IncludesShadersStore.backgroundFragmentDeclaration=Ep;var Sp=`layout(std140,column_major) uniform;
-uniform Material
-{
-uniform vec4 vPrimaryColor;
-uniform vec4 vPrimaryColorShadow;
-uniform vec2 vDiffuseInfos;
-uniform vec2 vReflectionInfos;
-uniform mat4 diffuseMatrix;
-uniform mat4 reflectionMatrix;
-uniform vec3 vReflectionMicrosurfaceInfos;
-uniform float fFovMultiplier;
-uniform float pointSize;
-uniform float shadowLevel;
-uniform float alpha;
-#if defined(REFLECTIONFRESNEL) || defined(OPACITYFRESNEL)
-uniform vec3 vBackgroundCenter;
-#endif
-#ifdef REFLECTIONFRESNEL
-uniform vec4 vReflectionControl;
-#endif
-};
-uniform Scene {
-mat4 viewProjection;
-#ifdef MULTIVIEW
-mat4 viewProjectionR;
-#endif
-mat4 view;
-};`;ze.a.IncludesShadersStore.backgroundUboDeclaration=Sp,f(131),f(106),f(107),f(154),f(130),f(115),f(125),f(110),f(135),f(136);var Ap=`#ifdef TEXTURELODSUPPORT
-#extension GL_EXT_shader_texture_lod : enable
-#endif
-precision highp float;
-#include<__decl__backgroundFragment>
-#define RECIPROCAL_PI2 0.15915494
-
-uniform vec3 vEyePosition;
-
-varying vec3 vPositionW;
-#ifdef MAINUV1
-varying vec2 vMainUV1;
-#endif
-#ifdef MAINUV2
-varying vec2 vMainUV2;
-#endif
-#ifdef NORMAL
-varying vec3 vNormalW;
-#endif
-#ifdef DIFFUSE
-#if DIFFUSEDIRECTUV == 1
-#define vDiffuseUV vMainUV1
-#elif DIFFUSEDIRECTUV == 2
-#define vDiffuseUV vMainUV2
-#else
-varying vec2 vDiffuseUV;
-#endif
-uniform sampler2D diffuseSampler;
-#endif
-
-#ifdef REFLECTION
-#ifdef REFLECTIONMAP_3D
-#define sampleReflection(s,c) textureCube(s,c)
-uniform samplerCube reflectionSampler;
-#ifdef TEXTURELODSUPPORT
-#define sampleReflectionLod(s,c,l) textureCubeLodEXT(s,c,l)
-#else
-uniform samplerCube reflectionSamplerLow;
-uniform samplerCube reflectionSamplerHigh;
-#endif
-#else
-#define sampleReflection(s,c) texture2D(s,c)
-uniform sampler2D reflectionSampler;
-#ifdef TEXTURELODSUPPORT
-#define sampleReflectionLod(s,c,l) texture2DLodEXT(s,c,l)
-#else
-uniform samplerCube reflectionSamplerLow;
-uniform samplerCube reflectionSamplerHigh;
-#endif
-#endif
-#ifdef REFLECTIONMAP_SKYBOX
-varying vec3 vPositionUVW;
-#else
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-varying vec3 vDirectionW;
-#endif
-#endif
-#include<reflectionFunction>
-#endif
-
-#ifndef FROMLINEARSPACE
-#define FROMLINEARSPACE;
-#endif
-
-#ifndef SHADOWONLY
-#define SHADOWONLY;
-#endif
-#include<imageProcessingDeclaration>
-
-#include<__decl__lightFragment>[0..maxSimultaneousLights]
-#include<helperFunctions>
-#include<lightsFragmentFunctions>
-#include<shadowsFragmentFunctions>
-#include<imageProcessingFunctions>
-#include<clipPlaneFragmentDeclaration>
-
-#include<fogFragmentDeclaration>
-#ifdef REFLECTIONFRESNEL
-#define FRESNEL_MAXIMUM_ON_ROUGH 0.25
-vec3 fresnelSchlickEnvironmentGGX(float VdotN,vec3 reflectance0,vec3 reflectance90,float smoothness)
-{
-
-float weight=mix(FRESNEL_MAXIMUM_ON_ROUGH,1.0,smoothness);
-return reflectance0+weight*(reflectance90-reflectance0)*pow5(saturate(1.0-VdotN));
-}
-#endif
-void main(void) {
-#include<clipPlaneFragment>
-vec3 viewDirectionW=normalize(vEyePosition-vPositionW);
-
-#ifdef NORMAL
-vec3 normalW=normalize(vNormalW);
-#else
-vec3 normalW=vec3(0.0,1.0,0.0);
-#endif
-
-float shadow=1.;
-float globalShadow=0.;
-float shadowLightCount=0.;
-#include<lightFragment>[0..maxSimultaneousLights]
-#ifdef SHADOWINUSE
-globalShadow/=shadowLightCount;
-#else
-globalShadow=1.0;
-#endif
-#ifndef BACKMAT_SHADOWONLY
-
-vec4 reflectionColor=vec4(1.,1.,1.,1.);
-#ifdef REFLECTION
-vec3 reflectionVector=computeReflectionCoords(vec4(vPositionW,1.0),normalW);
-#ifdef REFLECTIONMAP_OPPOSITEZ
-reflectionVector.z*=-1.0;
-#endif
-
-#ifdef REFLECTIONMAP_3D
-vec3 reflectionCoords=reflectionVector;
-#else
-vec2 reflectionCoords=reflectionVector.xy;
-#ifdef REFLECTIONMAP_PROJECTION
-reflectionCoords/=reflectionVector.z;
-#endif
-reflectionCoords.y=1.0-reflectionCoords.y;
-#endif
-#ifdef REFLECTIONBLUR
-float reflectionLOD=vReflectionInfos.y;
-#ifdef TEXTURELODSUPPORT
-
-reflectionLOD=reflectionLOD*log2(vReflectionMicrosurfaceInfos.x)*vReflectionMicrosurfaceInfos.y+vReflectionMicrosurfaceInfos.z;
-reflectionColor=sampleReflectionLod(reflectionSampler,reflectionCoords,reflectionLOD);
-#else
-float lodReflectionNormalized=saturate(reflectionLOD);
-float lodReflectionNormalizedDoubled=lodReflectionNormalized*2.0;
-vec4 reflectionSpecularMid=sampleReflection(reflectionSampler,reflectionCoords);
-if(lodReflectionNormalizedDoubled<1.0){
-reflectionColor=mix(
-sampleReflection(reflectionSamplerHigh,reflectionCoords),
-reflectionSpecularMid,
-lodReflectionNormalizedDoubled
-);
-} else {
-reflectionColor=mix(
-reflectionSpecularMid,
-sampleReflection(reflectionSamplerLow,reflectionCoords),
-lodReflectionNormalizedDoubled-1.0
-);
-}
-#endif
-#else
-vec4 reflectionSample=sampleReflection(reflectionSampler,reflectionCoords);
-reflectionColor=reflectionSample;
-#endif
-#ifdef RGBDREFLECTION
-reflectionColor.rgb=fromRGBD(reflectionColor);
-#endif
-#ifdef GAMMAREFLECTION
-reflectionColor.rgb=toLinearSpace(reflectionColor.rgb);
-#endif
-#ifdef REFLECTIONBGR
-reflectionColor.rgb=reflectionColor.bgr;
-#endif
-
-reflectionColor.rgb*=vReflectionInfos.x;
-#endif
-
-vec3 diffuseColor=vec3(1.,1.,1.);
-float finalAlpha=alpha;
-#ifdef DIFFUSE
-vec4 diffuseMap=texture2D(diffuseSampler,vDiffuseUV);
-#ifdef GAMMADIFFUSE
-diffuseMap.rgb=toLinearSpace(diffuseMap.rgb);
-#endif
-
-diffuseMap.rgb*=vDiffuseInfos.y;
-#ifdef DIFFUSEHASALPHA
-finalAlpha*=diffuseMap.a;
-#endif
-diffuseColor=diffuseMap.rgb;
-#endif
-
-#ifdef REFLECTIONFRESNEL
-vec3 colorBase=diffuseColor;
-#else
-vec3 colorBase=reflectionColor.rgb*diffuseColor;
-#endif
-colorBase=max(colorBase,0.0);
-
-#ifdef USERGBCOLOR
-vec3 finalColor=colorBase;
-#else
-#ifdef USEHIGHLIGHTANDSHADOWCOLORS
-vec3 mainColor=mix(vPrimaryColorShadow.rgb,vPrimaryColor.rgb,colorBase);
-#else
-vec3 mainColor=vPrimaryColor.rgb;
-#endif
-vec3 finalColor=colorBase*mainColor;
-#endif
-
-#ifdef REFLECTIONFRESNEL
-vec3 reflectionAmount=vReflectionControl.xxx;
-vec3 reflectionReflectance0=vReflectionControl.yyy;
-vec3 reflectionReflectance90=vReflectionControl.zzz;
-float VdotN=dot(normalize(vEyePosition),normalW);
-vec3 planarReflectionFresnel=fresnelSchlickEnvironmentGGX(saturate(VdotN),reflectionReflectance0,reflectionReflectance90,1.0);
-reflectionAmount*=planarReflectionFresnel;
-#ifdef REFLECTIONFALLOFF
-float reflectionDistanceFalloff=1.0-saturate(length(vPositionW.xyz-vBackgroundCenter)*vReflectionControl.w);
-reflectionDistanceFalloff*=reflectionDistanceFalloff;
-reflectionAmount*=reflectionDistanceFalloff;
-#endif
-finalColor=mix(finalColor,reflectionColor.rgb,saturate(reflectionAmount));
-#endif
-#ifdef OPACITYFRESNEL
-float viewAngleToFloor=dot(normalW,normalize(vEyePosition-vBackgroundCenter));
-
-const float startAngle=0.1;
-float fadeFactor=saturate(viewAngleToFloor/startAngle);
-finalAlpha*=fadeFactor*fadeFactor;
-#endif
-
-#ifdef SHADOWINUSE
-finalColor=mix(finalColor*shadowLevel,finalColor,globalShadow);
-#endif
-
-vec4 color=vec4(finalColor,finalAlpha);
-#else
-vec4 color=vec4(vPrimaryColor.rgb,(1.0-clamp(globalShadow,0.,1.))*alpha);
-#endif
-#include<fogFragment>
-#ifdef IMAGEPROCESSINGPOSTPROCESS
-
-
-color.rgb=clamp(color.rgb,0.,30.0);
-#else
-
-color=applyImageProcessing(color);
-#endif
-#ifdef PREMULTIPLYALPHA
-
-color.rgb*=color.a;
-#endif
-#ifdef NOISE
-color.rgb+=dither(vPositionW.xy,0.5);
-color=max(color,0.0);
-#endif
-gl_FragColor=color;
-}
-`;ze.a.ShadersStore.backgroundPixelShader=Ap;var Pp=`uniform mat4 view;
-uniform mat4 viewProjection;
-uniform float shadowLevel;
-#ifdef DIFFUSE
-uniform mat4 diffuseMatrix;
-uniform vec2 vDiffuseInfos;
-#endif
-#ifdef REFLECTION
-uniform vec2 vReflectionInfos;
-uniform mat4 reflectionMatrix;
-uniform vec3 vReflectionMicrosurfaceInfos;
-uniform float fFovMultiplier;
-#endif
-#ifdef POINTSIZE
-uniform float pointSize;
-#endif`;ze.a.IncludesShadersStore.backgroundVertexDeclaration=Pp,f(78),f(79),f(117),f(137),f(80),f(81),f(111),f(157),f(138);var xp=`precision highp float;
-#include<__decl__backgroundVertex>
-#include<helperFunctions>
-
-attribute vec3 position;
-#ifdef NORMAL
-attribute vec3 normal;
-#endif
-#include<bonesDeclaration>
-
-#include<instancesDeclaration>
-
-varying vec3 vPositionW;
-#ifdef NORMAL
-varying vec3 vNormalW;
-#endif
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#ifdef MAINUV1
-varying vec2 vMainUV1;
-#endif
-#ifdef MAINUV2
-varying vec2 vMainUV2;
-#endif
-#if defined(DIFFUSE) && DIFFUSEDIRECTUV == 0
-varying vec2 vDiffuseUV;
-#endif
-#include<clipPlaneVertexDeclaration>
-#include<fogVertexDeclaration>
-#include<__decl__lightFragment>[0..maxSimultaneousLights]
-#ifdef REFLECTIONMAP_SKYBOX
-varying vec3 vPositionUVW;
-#endif
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-varying vec3 vDirectionW;
-#endif
-void main(void) {
-#ifdef REFLECTIONMAP_SKYBOX
-vPositionUVW=position;
-#endif
-#include<instancesVertex>
-#include<bonesVertex>
-#ifdef MULTIVIEW
-if (gl_ViewID_OVR == 0u) {
-gl_Position=viewProjection*finalWorld*vec4(position,1.0);
-} else {
-gl_Position=viewProjectionR*finalWorld*vec4(position,1.0);
-}
-#else
-gl_Position=viewProjection*finalWorld*vec4(position,1.0);
-#endif
-vec4 worldPos=finalWorld*vec4(position,1.0);
-vPositionW=vec3(worldPos);
-#ifdef NORMAL
-mat3 normalWorld=mat3(finalWorld);
-#ifdef NONUNIFORMSCALING
-normalWorld=transposeMat3(inverseMat3(normalWorld));
-#endif
-vNormalW=normalize(normalWorld*normal);
-#endif
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-vDirectionW=normalize(vec3(finalWorld*vec4(position,0.0)));
-#ifdef EQUIRECTANGULAR_RELFECTION_FOV
-mat3 screenToWorld=inverseMat3(mat3(finalWorld*viewProjection));
-vec3 segment=mix(vDirectionW,screenToWorld*vec3(0.0,0.0,1.0),abs(fFovMultiplier-1.0));
-if (fFovMultiplier<=1.0) {
-vDirectionW=normalize(segment);
-} else {
-vDirectionW=normalize(vDirectionW+(vDirectionW-segment));
-}
-#endif
-#endif
-#ifndef UV1
-vec2 uv=vec2(0.,0.);
-#endif
-#ifndef UV2
-vec2 uv2=vec2(0.,0.);
-#endif
-#ifdef MAINUV1
-vMainUV1=uv;
-#endif
-#ifdef MAINUV2
-vMainUV2=uv2;
-#endif
-#if defined(DIFFUSE) && DIFFUSEDIRECTUV == 0
-if (vDiffuseInfos.x == 0.)
-{
-vDiffuseUV=vec2(diffuseMatrix*vec4(uv,1.0,0.0));
-}
-else
-{
-vDiffuseUV=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-
-#include<clipPlaneVertex>
-
-#include<fogVertex>
-
-#include<shadowsVertex>[0..maxSimultaneousLights]
-
-#ifdef VERTEXCOLOR
-vColor=color;
-#endif
-
-#ifdef POINTSIZE
-gl_PointSize=pointSize;
-#endif
-}
-`;ze.a.ShadersStore.backgroundVertexShader=xp;var Sr=f(67),Cp=function(r){function t(){var e=r.call(this)||this;return e.DIFFUSE=!1,e.DIFFUSEDIRECTUV=0,e.GAMMADIFFUSE=!1,e.DIFFUSEHASALPHA=!1,e.OPACITYFRESNEL=!1,e.REFLECTIONBLUR=!1,e.REFLECTIONFRESNEL=!1,e.REFLECTIONFALLOFF=!1,e.TEXTURELODSUPPORT=!1,e.PREMULTIPLYALPHA=!1,e.USERGBCOLOR=!1,e.USEHIGHLIGHTANDSHADOWCOLORS=!1,e.BACKMAT_SHADOWONLY=!1,e.NOISE=!1,e.REFLECTIONBGR=!1,e.IMAGEPROCESSING=!1,e.VIGNETTE=!1,e.VIGNETTEBLENDMODEMULTIPLY=!1,e.VIGNETTEBLENDMODEOPAQUE=!1,e.TONEMAPPING=!1,e.TONEMAPPING_ACES=!1,e.CONTRAST=!1,e.COLORCURVES=!1,e.COLORGRADING=!1,e.COLORGRADING3D=!1,e.SAMPLER3DGREENDEPTH=!1,e.SAMPLER3DBGRMAP=!1,e.IMAGEPROCESSINGPOSTPROCESS=!1,e.EXPOSURE=!1,e.MULTIVIEW=!1,e.REFLECTION=!1,e.REFLECTIONMAP_3D=!1,e.REFLECTIONMAP_SPHERICAL=!1,e.REFLECTIONMAP_PLANAR=!1,e.REFLECTIONMAP_CUBIC=!1,e.REFLECTIONMAP_PROJECTION=!1,e.REFLECTIONMAP_SKYBOX=!1,e.REFLECTIONMAP_EXPLICIT=!1,e.REFLECTIONMAP_EQUIRECTANGULAR=!1,e.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!1,e.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!1,e.INVERTCUBICMAP=!1,e.REFLECTIONMAP_OPPOSITEZ=!1,e.LODINREFLECTIONALPHA=!1,e.GAMMAREFLECTION=!1,e.RGBDREFLECTION=!1,e.EQUIRECTANGULAR_RELFECTION_FOV=!1,e.MAINUV1=!1,e.MAINUV2=!1,e.UV1=!1,e.UV2=!1,e.CLIPPLANE=!1,e.CLIPPLANE2=!1,e.CLIPPLANE3=!1,e.CLIPPLANE4=!1,e.CLIPPLANE5=!1,e.CLIPPLANE6=!1,e.POINTSIZE=!1,e.FOG=!1,e.NORMAL=!1,e.NUM_BONE_INFLUENCERS=0,e.BonesPerMesh=0,e.INSTANCES=!1,e.SHADOWFLOAT=!1,e.rebuild(),e}return Object(c.d)(t,r),t}(Jo.a),so=function(r){function t(e,n){var i=r.call(this,e,n)||this;return i.primaryColor=M.a.White(),i._primaryColorShadowLevel=0,i._primaryColorHighlightLevel=0,i.reflectionTexture=null,i.reflectionBlur=0,i.diffuseTexture=null,i._shadowLights=null,i.shadowLights=null,i.shadowLevel=0,i.sceneCenter=u.e.Zero(),i.opacityFresnel=!0,i.reflectionFresnel=!1,i.reflectionFalloffDistance=0,i.reflectionAmount=1,i.reflectionReflectance0=.05,i.reflectionReflectance90=.5,i.useRGBColor=!0,i.enableNoise=!1,i._fovMultiplier=1,i.useEquirectangularFOV=!1,i._maxSimultaneousLights=4,i.maxSimultaneousLights=4,i._shadowOnly=!1,i.shadowOnly=!1,i._imageProcessingObserver=null,i.switchToBGR=!1,i._renderTargets=new fi.a(16),i._reflectionControls=u.f.Zero(),i._white=M.a.White(),i._primaryShadowColor=M.a.Black(),i._primaryHighlightColor=M.a.Black(),i._attachImageProcessingConfiguration(null),i.getRenderTargetTextures=function(){return i._renderTargets.reset(),i._diffuseTexture&&i._diffuseTexture.isRenderTarget&&i._renderTargets.push(i._diffuseTexture),i._reflectionTexture&&i._reflectionTexture.isRenderTarget&&i._renderTargets.push(i._reflectionTexture),i._renderTargets},i}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"_perceptualColor",{get:function(){return this.__perceptualColor},set:function(e){this.__perceptualColor=e,this._computePrimaryColorFromPerceptualColor(),this._markAllSubMeshesAsLightsDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"primaryColorShadowLevel",{get:function(){return this._primaryColorShadowLevel},set:function(e){this._primaryColorShadowLevel=e,this._computePrimaryColors(),this._markAllSubMeshesAsLightsDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"primaryColorHighlightLevel",{get:function(){return this._primaryColorHighlightLevel},set:function(e){this._primaryColorHighlightLevel=e,this._computePrimaryColors(),this._markAllSubMeshesAsLightsDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"reflectionStandardFresnelWeight",{set:function(e){var n=e;n<.5?(n*=2,this.reflectionReflectance0=t.StandardReflectance0*n,this.reflectionReflectance90=t.StandardReflectance90*n):(n=2*n-1,this.reflectionReflectance0=t.StandardReflectance0+(1-t.StandardReflectance0)*n,this.reflectionReflectance90=t.StandardReflectance90+(1-t.StandardReflectance90)*n)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"fovMultiplier",{get:function(){return this._fovMultiplier},set:function(e){isNaN(e)&&(e=1),this._fovMultiplier=Math.max(0,Math.min(2,e))},enumerable:!1,configurable:!0}),t.prototype._attachImageProcessingConfiguration=function(e){var n=this;e!==this._imageProcessingConfiguration&&(this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),this._imageProcessingConfiguration=e||this.getScene().imageProcessingConfiguration,this._imageProcessingConfiguration&&(this._imageProcessingObserver=this._imageProcessingConfiguration.onUpdateParameters.add(function(){n._computePrimaryColorFromPerceptualColor(),n._markAllSubMeshesAsImageProcessingDirty()})))},Object.defineProperty(t.prototype,"imageProcessingConfiguration",{get:function(){return this._imageProcessingConfiguration},set:function(e){this._attachImageProcessingConfiguration(e),this._markAllSubMeshesAsTexturesDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorCurvesEnabled",{get:function(){return this.imageProcessingConfiguration.colorCurvesEnabled},set:function(e){this.imageProcessingConfiguration.colorCurvesEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorGradingEnabled",{get:function(){return this.imageProcessingConfiguration.colorGradingEnabled},set:function(e){this.imageProcessingConfiguration.colorGradingEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraToneMappingEnabled",{get:function(){return this._imageProcessingConfiguration.toneMappingEnabled},set:function(e){this._imageProcessingConfiguration.toneMappingEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraExposure",{get:function(){return this._imageProcessingConfiguration.exposure},set:function(e){this._imageProcessingConfiguration.exposure=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraContrast",{get:function(){return this._imageProcessingConfiguration.contrast},set:function(e){this._imageProcessingConfiguration.contrast=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorGradingTexture",{get:function(){return this._imageProcessingConfiguration.colorGradingTexture},set:function(e){this.imageProcessingConfiguration.colorGradingTexture=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorCurves",{get:function(){return this.imageProcessingConfiguration.colorCurves},set:function(e){this.imageProcessingConfiguration.colorCurves=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"hasRenderTargetTextures",{get:function(){return!(!this._diffuseTexture||!this._diffuseTexture.isRenderTarget)||!(!this._reflectionTexture||!this._reflectionTexture.isRenderTarget)},enumerable:!1,configurable:!0}),t.prototype.needAlphaTesting=function(){return!0},t.prototype.needAlphaBlending=function(){return this.alpha<1||this._diffuseTexture!=null&&this._diffuseTexture.hasAlpha||this._shadowOnly},t.prototype.isReadyForSubMesh=function(e,n,i){var o=this;if(i===void 0&&(i=!1),n.effect&&this.isFrozen&&n.effect._wasPreviouslyReady)return!0;n._materialDefines||(n._materialDefines=new Cp);var a=this.getScene(),s=n._materialDefines;if(this._isReadyForSubMesh(n))return!0;var d=a.getEngine();if(et.a.PrepareDefinesForLights(a,e,s,!1,this._maxSimultaneousLights),s._needNormals=!0,et.a.PrepareDefinesForMultiview(a,s),s._areTexturesDirty){if(s._needUVs=!1,a.texturesEnabled){if(a.getEngine().getCaps().textureLOD&&(s.TEXTURELODSUPPORT=!0),this._diffuseTexture&&ht.a.DiffuseTextureEnabled){if(!this._diffuseTexture.isReadyOrNotBlocking())return!1;et.a.PrepareDefinesForMergedUV(this._diffuseTexture,s,"DIFFUSE"),s.DIFFUSEHASALPHA=this._diffuseTexture.hasAlpha,s.GAMMADIFFUSE=this._diffuseTexture.gammaSpace,s.OPACITYFRESNEL=this._opacityFresnel}else s.DIFFUSE=!1,s.DIFFUSEHASALPHA=!1,s.GAMMADIFFUSE=!1,s.OPACITYFRESNEL=!1;var p=this._reflectionTexture;if(p&&ht.a.ReflectionTextureEnabled){if(!p.isReadyOrNotBlocking())return!1;switch(s.REFLECTION=!0,s.GAMMAREFLECTION=p.gammaSpace,s.RGBDREFLECTION=p.isRGBD,s.REFLECTIONBLUR=this._reflectionBlur>0,s.REFLECTIONMAP_OPPOSITEZ=this.getScene().useRightHandedSystem?!p.invertZ:p.invertZ,s.LODINREFLECTIONALPHA=p.lodLevelInAlpha,s.EQUIRECTANGULAR_RELFECTION_FOV=this.useEquirectangularFOV,s.REFLECTIONBGR=this.switchToBGR,p.coordinatesMode===we.a.INVCUBIC_MODE&&(s.INVERTCUBICMAP=!0),s.REFLECTIONMAP_3D=p.isCube,p.coordinatesMode){case we.a.EXPLICIT_MODE:s.REFLECTIONMAP_EXPLICIT=!0;break;case we.a.PLANAR_MODE:s.REFLECTIONMAP_PLANAR=!0;break;case we.a.PROJECTION_MODE:s.REFLECTIONMAP_PROJECTION=!0;break;case we.a.SKYBOX_MODE:s.REFLECTIONMAP_SKYBOX=!0;break;case we.a.SPHERICAL_MODE:s.REFLECTIONMAP_SPHERICAL=!0;break;case we.a.EQUIRECTANGULAR_MODE:s.REFLECTIONMAP_EQUIRECTANGULAR=!0;break;case we.a.FIXED_EQUIRECTANGULAR_MODE:s.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!0;break;case we.a.FIXED_EQUIRECTANGULAR_MIRRORED_MODE:s.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!0;break;case we.a.CUBIC_MODE:case we.a.INVCUBIC_MODE:default:s.REFLECTIONMAP_CUBIC=!0}this.reflectionFresnel?(s.REFLECTIONFRESNEL=!0,s.REFLECTIONFALLOFF=this.reflectionFalloffDistance>0,this._reflectionControls.x=this.reflectionAmount,this._reflectionControls.y=this.reflectionReflectance0,this._reflectionControls.z=this.reflectionReflectance90,this._reflectionControls.w=1/this.reflectionFalloffDistance):(s.REFLECTIONFRESNEL=!1,s.REFLECTIONFALLOFF=!1)}else s.REFLECTION=!1,s.REFLECTIONFRESNEL=!1,s.REFLECTIONFALLOFF=!1,s.REFLECTIONBLUR=!1,s.REFLECTIONMAP_3D=!1,s.REFLECTIONMAP_SPHERICAL=!1,s.REFLECTIONMAP_PLANAR=!1,s.REFLECTIONMAP_CUBIC=!1,s.REFLECTIONMAP_PROJECTION=!1,s.REFLECTIONMAP_SKYBOX=!1,s.REFLECTIONMAP_EXPLICIT=!1,s.REFLECTIONMAP_EQUIRECTANGULAR=!1,s.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!1,s.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!1,s.INVERTCUBICMAP=!1,s.REFLECTIONMAP_OPPOSITEZ=!1,s.LODINREFLECTIONALPHA=!1,s.GAMMAREFLECTION=!1,s.RGBDREFLECTION=!1}s.PREMULTIPLYALPHA=this.alphaMode===h.a.ALPHA_PREMULTIPLIED||this.alphaMode===h.a.ALPHA_PREMULTIPLIED_PORTERDUFF,s.USERGBCOLOR=this._useRGBColor,s.NOISE=this._enableNoise}if(s._areLightsDirty&&(s.USEHIGHLIGHTANDSHADOWCOLORS=!this._useRGBColor&&(this._primaryColorShadowLevel!==0||this._primaryColorHighlightLevel!==0),s.BACKMAT_SHADOWONLY=this._shadowOnly),s._areImageProcessingDirty&&this._imageProcessingConfiguration){if(!this._imageProcessingConfiguration.isReady())return!1;this._imageProcessingConfiguration.prepareDefines(s)}if(et.a.PrepareDefinesForMisc(e,a,!1,this.pointsCloud,this.fogEnabled,this._shouldTurnAlphaTestOn(e),s),et.a.PrepareDefinesForFrameBoundValues(a,d,s,i,null,n.getRenderingMesh().hasThinInstances),et.a.PrepareDefinesForAttributes(e,s,!1,!0,!1)&&e&&(a.getEngine().getCaps().standardDerivatives||e.isVerticesDataPresent(Oe.b.NormalKind)||(e.createNormals(!0),l.a.Warn("BackgroundMaterial: Normals have been created for the mesh: "+e.name))),s.isDirty){s.markAsProcessed(),a.resetCachedMaterial();var b=new Sr.a;s.FOG&&b.addFallback(0,"FOG"),s.POINTSIZE&&b.addFallback(1,"POINTSIZE"),s.MULTIVIEW&&b.addFallback(0,"MULTIVIEW"),et.a.HandleFallbacksForShadows(s,b,this._maxSimultaneousLights);var P=[Oe.b.PositionKind];s.NORMAL&&P.push(Oe.b.NormalKind),s.UV1&&P.push(Oe.b.UVKind),s.UV2&&P.push(Oe.b.UV2Kind),et.a.PrepareAttributesForBones(P,e,s,b),et.a.PrepareAttributesForInstances(P,s);var O=["world","view","viewProjection","vEyePosition","vLightsType","vFogInfos","vFogColor","pointSize","vClipPlane","vClipPlane2","vClipPlane3","vClipPlane4","vClipPlane5","vClipPlane6","mBones","vPrimaryColor","vPrimaryColorShadow","vReflectionInfos","reflectionMatrix","vReflectionMicrosurfaceInfos","fFovMultiplier","shadowLevel","alpha","vBackgroundCenter","vReflectionControl","vDiffuseInfos","diffuseMatrix"],B=["diffuseSampler","reflectionSampler","reflectionSamplerLow","reflectionSamplerHigh"],F=["Material","Scene"];yn.a&&(yn.a.PrepareUniforms(O,s),yn.a.PrepareSamplers(B,s)),et.a.PrepareUniformsAndSamplersList({uniformsNames:O,uniformBuffersNames:F,samplers:B,defines:s,maxSimultaneousLights:this._maxSimultaneousLights});var z=s.toString();n.setEffect(a.getEngine().createEffect("background",{attributes:P,uniformsNames:O,uniformBuffersNames:F,samplers:B,defines:z,fallbacks:b,onCompiled:function(J){o.onCompiled&&o.onCompiled(J),o.bindSceneUniformBuffer(J,a.getSceneUniformBuffer())},onError:this.onError,indexParameters:{maxSimultaneousLights:this._maxSimultaneousLights}},d),s),this.buildUniformLayout()}return!(!n.effect||!n.effect.isReady())&&(s._renderId=a.getRenderId(),n.effect._wasPreviouslyReady=!0,!0)},t.prototype._computePrimaryColorFromPerceptualColor=function(){this.__perceptualColor&&(this._primaryColor.copyFrom(this.__perceptualColor),this._primaryColor.toLinearSpaceToRef(this._primaryColor),this._imageProcessingConfiguration&&this._primaryColor.scaleToRef(1/this._imageProcessingConfiguration.exposure,this._primaryColor),this._computePrimaryColors())},t.prototype._computePrimaryColors=function(){this._primaryColorShadowLevel===0&&this._primaryColorHighlightLevel===0||(this._primaryColor.scaleToRef(this._primaryColorShadowLevel,this._primaryShadowColor),this._primaryColor.subtractToRef(this._primaryShadowColor,this._primaryShadowColor),this._white.subtractToRef(this._primaryColor,this._primaryHighlightColor),this._primaryHighlightColor.scaleToRef(this._primaryColorHighlightLevel,this._primaryHighlightColor),this._primaryColor.addToRef(this._primaryHighlightColor,this._primaryHighlightColor))},t.prototype.buildUniformLayout=function(){this._uniformBuffer.addUniform("vPrimaryColor",4),this._uniformBuffer.addUniform("vPrimaryColorShadow",4),this._uniformBuffer.addUniform("vDiffuseInfos",2),this._uniformBuffer.addUniform("vReflectionInfos",2),this._uniformBuffer.addUniform("diffuseMatrix",16),this._uniformBuffer.addUniform("reflectionMatrix",16),this._uniformBuffer.addUniform("vReflectionMicrosurfaceInfos",3),this._uniformBuffer.addUniform("fFovMultiplier",1),this._uniformBuffer.addUniform("pointSize",1),this._uniformBuffer.addUniform("shadowLevel",1),this._uniformBuffer.addUniform("alpha",1),this._uniformBuffer.addUniform("vBackgroundCenter",3),this._uniformBuffer.addUniform("vReflectionControl",4),this._uniformBuffer.create()},t.prototype.unbind=function(){this._diffuseTexture&&this._diffuseTexture.isRenderTarget&&this._uniformBuffer.setTexture("diffuseSampler",null),this._reflectionTexture&&this._reflectionTexture.isRenderTarget&&this._uniformBuffer.setTexture("reflectionSampler",null),r.prototype.unbind.call(this)},t.prototype.bindOnlyWorldMatrix=function(e){this._activeEffect.setMatrix("world",e)},t.prototype.bindForSubMesh=function(e,n,i){var o=this.getScene(),a=i._materialDefines;if(a){var s=i.effect;if(s){this._activeEffect=s,this.bindOnlyWorldMatrix(e),et.a.BindBonesParameters(n,this._activeEffect);var d=this._mustRebind(o,s,n.visibility);if(d){this._uniformBuffer.bindToEffect(s,"Material"),this.bindViewProjection(s);var p=this._reflectionTexture;this._uniformBuffer.useUbo&&this.isFrozen&&this._uniformBuffer.isSync||(o.texturesEnabled&&(this._diffuseTexture&&ht.a.DiffuseTextureEnabled&&(this._uniformBuffer.updateFloat2("vDiffuseInfos",this._diffuseTexture.coordinatesIndex,this._diffuseTexture.level),et.a.BindTextureMatrix(this._diffuseTexture,this._uniformBuffer,"diffuse")),p&&ht.a.ReflectionTextureEnabled&&(this._uniformBuffer.updateMatrix("reflectionMatrix",p.getReflectionTextureMatrix()),this._uniformBuffer.updateFloat2("vReflectionInfos",p.level,this._reflectionBlur),this._uniformBuffer.updateFloat3("vReflectionMicrosurfaceInfos",p.getSize().width,p.lodGenerationScale,p.lodGenerationOffset))),this.shadowLevel>0&&this._uniformBuffer.updateFloat("shadowLevel",this.shadowLevel),this._uniformBuffer.updateFloat("alpha",this.alpha),this.pointsCloud&&this._uniformBuffer.updateFloat("pointSize",this.pointSize),a.USEHIGHLIGHTANDSHADOWCOLORS?(this._uniformBuffer.updateColor4("vPrimaryColor",this._primaryHighlightColor,1),this._uniformBuffer.updateColor4("vPrimaryColorShadow",this._primaryShadowColor,1)):this._uniformBuffer.updateColor4("vPrimaryColor",this._primaryColor,1)),this._uniformBuffer.updateFloat("fFovMultiplier",this._fovMultiplier),o.texturesEnabled&&(this._diffuseTexture&&ht.a.DiffuseTextureEnabled&&this._uniformBuffer.setTexture("diffuseSampler",this._diffuseTexture),p&&ht.a.ReflectionTextureEnabled&&(a.REFLECTIONBLUR&&a.TEXTURELODSUPPORT?this._uniformBuffer.setTexture("reflectionSampler",p):a.REFLECTIONBLUR?(this._uniformBuffer.setTexture("reflectionSampler",p._lodTextureMid||p),this._uniformBuffer.setTexture("reflectionSamplerLow",p._lodTextureLow||p),this._uniformBuffer.setTexture("reflectionSamplerHigh",p._lodTextureHigh||p)):this._uniformBuffer.setTexture("reflectionSampler",p),a.REFLECTIONFRESNEL&&(this._uniformBuffer.updateFloat3("vBackgroundCenter",this.sceneCenter.x,this.sceneCenter.y,this.sceneCenter.z),this._uniformBuffer.updateFloat4("vReflectionControl",this._reflectionControls.x,this._reflectionControls.y,this._reflectionControls.z,this._reflectionControls.w)))),et.a.BindClipPlane(this._activeEffect,o),et.a.BindEyePosition(s,o)}!d&&this.isFrozen||(o.lightsEnabled&&et.a.BindLights(o,n,this._activeEffect,a,this._maxSimultaneousLights,!1),this.bindView(s),et.a.BindFogParameters(o,n,this._activeEffect,!0),this._imageProcessingConfiguration&&this._imageProcessingConfiguration.bind(this._activeEffect)),this._uniformBuffer.update(),this._afterBind(n,this._activeEffect)}}},t.prototype.hasTexture=function(e){return!!r.prototype.hasTexture.call(this,e)||this._reflectionTexture===e||this._diffuseTexture===e},t.prototype.dispose=function(e,n){e===void 0&&(e=!1),n===void 0&&(n=!1),n&&(this.diffuseTexture&&this.diffuseTexture.dispose(),this.reflectionTexture&&this.reflectionTexture.dispose()),this._renderTargets.dispose(),this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),r.prototype.dispose.call(this,e)},t.prototype.clone=function(e){var n=this;return L.a.Clone(function(){return new t(e,n.getScene())},this)},t.prototype.serialize=function(){var e=L.a.Serialize(this);return e.customType="BABYLON.BackgroundMaterial",e},t.prototype.getClassName=function(){return"BackgroundMaterial"},t.Parse=function(e,n,i){return L.a.Parse(function(){return new t(e.name,n)},e,n,i)},t.StandardReflectance0=.05,t.StandardReflectance90=.5,Object(c.c)([Object(L.e)()],t.prototype,"_primaryColor",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsLightsDirty")],t.prototype,"primaryColor",void 0),Object(c.c)([Object(L.e)()],t.prototype,"__perceptualColor",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_primaryColorShadowLevel",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_primaryColorHighlightLevel",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsLightsDirty")],t.prototype,"primaryColorHighlightLevel",null),Object(c.c)([Object(L.m)()],t.prototype,"_reflectionTexture",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionTexture",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_reflectionBlur",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionBlur",void 0),Object(c.c)([Object(L.m)()],t.prototype,"_diffuseTexture",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"diffuseTexture",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"shadowLights",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_shadowLevel",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"shadowLevel",void 0),Object(c.c)([Object(L.o)()],t.prototype,"_sceneCenter",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"sceneCenter",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_opacityFresnel",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"opacityFresnel",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_reflectionFresnel",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionFresnel",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_reflectionFalloffDistance",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionFalloffDistance",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_reflectionAmount",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionAmount",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_reflectionReflectance0",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionReflectance0",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_reflectionReflectance90",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionReflectance90",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_useRGBColor",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useRGBColor",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_enableNoise",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"enableNoise",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_maxSimultaneousLights",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"maxSimultaneousLights",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_shadowOnly",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsLightsDirty")],t.prototype,"shadowOnly",void 0),Object(c.c)([Object(L.i)()],t.prototype,"_imageProcessingConfiguration",void 0),t}($o.a);R.a.RegisteredTypes["BABYLON.BackgroundMaterial"]=so;var ws=function(){function r(t,e){var n=this;this._errorHandler=function(i,o){n.onErrorObservable.notifyObservers({message:i,exception:o})},this._options=Object(c.a)(Object(c.a)({},r._getDefaultOptions()),t),this._scene=e,this.onErrorObservable=new C.c,this._setupBackground(),this._setupImageProcessing()}return r._getDefaultOptions=function(){return{createGround:!0,groundSize:15,groundTexture:this._groundTextureCDNUrl,groundColor:new M.a(.2,.2,.3).toLinearSpace().scale(3),groundOpacity:.9,enableGroundShadow:!0,groundShadowLevel:.5,enableGroundMirror:!1,groundMirrorSizeRatio:.3,groundMirrorBlurKernel:64,groundMirrorAmount:1,groundMirrorFresnelWeight:1,groundMirrorFallOffDistance:0,groundMirrorTextureType:h.a.TEXTURETYPE_UNSIGNED_INT,groundYBias:1e-5,createSkybox:!0,skyboxSize:20,skyboxTexture:this._skyboxTextureCDNUrl,skyboxColor:new M.a(.2,.2,.3).toLinearSpace().scale(3),backgroundYRotation:0,sizeAuto:!0,rootPosition:u.e.Zero(),setupImageProcessing:!0,environmentTexture:this._environmentTextureCDNUrl,cameraExposure:.8,cameraContrast:1.2,toneMappingEnabled:!0}},Object.defineProperty(r.prototype,"rootMesh",{get:function(){return this._rootMesh},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"skybox",{get:function(){return this._skybox},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"skyboxTexture",{get:function(){return this._skyboxTexture},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"skyboxMaterial",{get:function(){return this._skyboxMaterial},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"ground",{get:function(){return this._ground},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"groundTexture",{get:function(){return this._groundTexture},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"groundMirror",{get:function(){return this._groundMirror},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"groundMirrorRenderList",{get:function(){return this._groundMirror?this._groundMirror.renderList:null},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"groundMaterial",{get:function(){return this._groundMaterial},enumerable:!1,configurable:!0}),r.prototype.updateOptions=function(t){var e=Object(c.a)(Object(c.a)({},this._options),t);this._ground&&!e.createGround&&(this._ground.dispose(),this._ground=null),this._groundMaterial&&!e.createGround&&(this._groundMaterial.dispose(),this._groundMaterial=null),this._groundTexture&&this._options.groundTexture!=e.groundTexture&&(this._groundTexture.dispose(),this._groundTexture=null),this._skybox&&!e.createSkybox&&(this._skybox.dispose(),this._skybox=null),this._skyboxMaterial&&!e.createSkybox&&(this._skyboxMaterial.dispose(),this._skyboxMaterial=null),this._skyboxTexture&&this._options.skyboxTexture!=e.skyboxTexture&&(this._skyboxTexture.dispose(),this._skyboxTexture=null),this._groundMirror&&!e.enableGroundMirror&&(this._groundMirror.dispose(),this._groundMirror=null),this._scene.environmentTexture&&this._options.environmentTexture!=e.environmentTexture&&this._scene.environmentTexture.dispose(),this._options=e,this._setupBackground(),this._setupImageProcessing()},r.prototype.setMainColor=function(t){this.groundMaterial&&(this.groundMaterial.primaryColor=t),this.skyboxMaterial&&(this.skyboxMaterial.primaryColor=t),this.groundMirror&&(this.groundMirror.clearColor=new M.b(t.r,t.g,t.b,1))},r.prototype._setupImageProcessing=function(){this._options.setupImageProcessing&&(this._scene.imageProcessingConfiguration.contrast=this._options.cameraContrast,this._scene.imageProcessingConfiguration.exposure=this._options.cameraExposure,this._scene.imageProcessingConfiguration.toneMappingEnabled=this._options.toneMappingEnabled,this._setupEnvironmentTexture())},r.prototype._setupEnvironmentTexture=function(){if(!this._scene.environmentTexture)if(this._options.environmentTexture instanceof zn.a)this._scene.environmentTexture=this._options.environmentTexture;else{var t=oi.CreateFromPrefilteredData(this._options.environmentTexture,this._scene);this._scene.environmentTexture=t}},r.prototype._setupBackground=function(){this._rootMesh||(this._rootMesh=new De.a("BackgroundHelper",this._scene)),this._rootMesh.rotation.y=this._options.backgroundYRotation;var t=this._getSceneSize();this._options.createGround&&(this._setupGround(t),this._setupGroundMaterial(),this._setupGroundDiffuseTexture(),this._options.enableGroundMirror&&this._setupGroundMirrorTexture(t),this._setupMirrorInGroundMaterial()),this._options.createSkybox&&(this._setupSkybox(t),this._setupSkyboxMaterial(),this._setupSkyboxReflectionTexture()),this._rootMesh.position.x=t.rootPosition.x,this._rootMesh.position.z=t.rootPosition.z,this._rootMesh.position.y=t.rootPosition.y},r.prototype._getSceneSize=function(){var t=this,e=this._options.groundSize,n=this._options.skyboxSize,i=this._options.rootPosition;if(!this._scene.meshes||this._scene.meshes.length===1)return{groundSize:e,skyboxSize:n,rootPosition:i};var o=this._scene.getWorldExtends(function(d){return d!==t._ground&&d!==t._rootMesh&&d!==t._skybox}),a=o.max.subtract(o.min);if(this._options.sizeAuto){this._scene.activeCamera instanceof Ji&&this._scene.activeCamera.upperRadiusLimit&&(n=e=2*this._scene.activeCamera.upperRadiusLimit);var s=a.length();s>e&&(n=e=2*s),e*=1.1,n*=1.5,(i=o.min.add(a.scale(.5))).y=o.min.y-this._options.groundYBias}return{groundSize:e,skyboxSize:n,rootPosition:i}},r.prototype._setupGround=function(t){var e=this;this._ground&&!this._ground.isDisposed()||(this._ground=De.a.CreatePlane("BackgroundPlane",t.groundSize,this._scene),this._ground.rotation.x=Math.PI/2,this._ground.parent=this._rootMesh,this._ground.onDisposeObservable.add(function(){e._ground=null})),this._ground.receiveShadows=this._options.enableGroundShadow},r.prototype._setupGroundMaterial=function(){this._groundMaterial||(this._groundMaterial=new so("BackgroundPlaneMaterial",this._scene)),this._groundMaterial.alpha=this._options.groundOpacity,this._groundMaterial.alphaMode=h.a.ALPHA_PREMULTIPLIED_PORTERDUFF,this._groundMaterial.shadowLevel=this._options.groundShadowLevel,this._groundMaterial.primaryColor=this._options.groundColor,this._groundMaterial.useRGBColor=!1,this._groundMaterial.enableNoise=!0,this._ground&&(this._ground.material=this._groundMaterial)},r.prototype._setupGroundDiffuseTexture=function(){this._groundMaterial&&(this._groundTexture||(this._options.groundTexture instanceof zn.a?this._groundMaterial.diffuseTexture=this._options.groundTexture:(this._groundTexture=new we.a(this._options.groundTexture,this._scene,void 0,void 0,void 0,void 0,this._errorHandler),this._groundTexture.gammaSpace=!1,this._groundTexture.hasAlpha=!0,this._groundMaterial.diffuseTexture=this._groundTexture)))},r.prototype._setupGroundMirrorTexture=function(t){var e=we.a.CLAMP_ADDRESSMODE;if(!this._groundMirror&&(this._groundMirror=new Ns("BackgroundPlaneMirrorTexture",{ratio:this._options.groundMirrorSizeRatio},this._scene,!1,this._options.groundMirrorTextureType,we.a.BILINEAR_SAMPLINGMODE,!0),this._groundMirror.mirrorPlane=new vr.a(0,-1,0,t.rootPosition.y),this._groundMirror.anisotropicFilteringLevel=1,this._groundMirror.wrapU=e,this._groundMirror.wrapV=e,this._groundMirror.gammaSpace=!1,this._groundMirror.renderList))for(var n=0;n<this._scene.meshes.length;n++){var i=this._scene.meshes[n];i!==this._ground&&i!==this._skybox&&i!==this._rootMesh&&this._groundMirror.renderList.push(i)}this._groundMirror.clearColor=new M.b(this._options.groundColor.r,this._options.groundColor.g,this._options.groundColor.b,1),this._groundMirror.adaptiveBlurKernel=this._options.groundMirrorBlurKernel},r.prototype._setupMirrorInGroundMaterial=function(){this._groundMaterial&&(this._groundMaterial.reflectionTexture=this._groundMirror,this._groundMaterial.reflectionFresnel=!0,this._groundMaterial.reflectionAmount=this._options.groundMirrorAmount,this._groundMaterial.reflectionStandardFresnelWeight=this._options.groundMirrorFresnelWeight,this._groundMaterial.reflectionFalloffDistance=this._options.groundMirrorFallOffDistance)},r.prototype._setupSkybox=function(t){var e=this;this._skybox&&!this._skybox.isDisposed()||(this._skybox=De.a.CreateBox("BackgroundSkybox",t.skyboxSize,this._scene,void 0,De.a.BACKSIDE),this._skybox.onDisposeObservable.add(function(){e._skybox=null})),this._skybox.parent=this._rootMesh},r.prototype._setupSkyboxMaterial=function(){this._skybox&&(this._skyboxMaterial||(this._skyboxMaterial=new so("BackgroundSkyboxMaterial",this._scene)),this._skyboxMaterial.useRGBColor=!1,this._skyboxMaterial.primaryColor=this._options.skyboxColor,this._skyboxMaterial.enableNoise=!0,this._skybox.material=this._skyboxMaterial)},r.prototype._setupSkyboxReflectionTexture=function(){this._skyboxMaterial&&(this._skyboxTexture||(this._options.skyboxTexture instanceof zn.a?this._skyboxMaterial.reflectionTexture=this._options.skyboxTexture:(this._skyboxTexture=new oi(this._options.skyboxTexture,this._scene,void 0,void 0,void 0,void 0,this._errorHandler),this._skyboxTexture.coordinatesMode=we.a.SKYBOX_MODE,this._skyboxTexture.gammaSpace=!1,this._skyboxMaterial.reflectionTexture=this._skyboxTexture)))},r.prototype.dispose=function(){this._groundMaterial&&this._groundMaterial.dispose(!0,!0),this._skyboxMaterial&&this._skyboxMaterial.dispose(!0,!0),this._rootMesh.dispose(!1)},r._groundTextureCDNUrl="https://assets.babylonjs.com/environments/backgroundGround.png",r._skyboxTextureCDNUrl="https://assets.babylonjs.com/environments/backgroundSkybox.dds",r._environmentTextureCDNUrl="https://assets.babylonjs.com/environments/environmentSpecular.env",r}(),ki=function(r){function t(e,n,i,o,a){a===void 0&&(a=null);var s=r.call(this,e,o)||this;s.onError=a,s._halfDome=!1,s._crossEye=!1,s._useDirectMapping=!1,s._textureMode=t.MODE_MONOSCOPIC,s._onBeforeCameraRenderObserver=null,s.onLoadErrorObservable=new C.c,o=s.getScene(),e=e||"textureDome",i.resolution=0|Math.abs(i.resolution)||32,i.clickToPlay=!!i.clickToPlay,i.autoPlay=i.autoPlay===void 0||!!i.autoPlay,i.loop=i.loop===void 0||!!i.loop,i.size=Math.abs(i.size)||(o.activeCamera?.48*o.activeCamera.maxZ:1e3),i.useDirectMapping===void 0?s._useDirectMapping=!0:s._useDirectMapping=i.useDirectMapping,i.faceForward===void 0&&(i.faceForward=!0),s._setReady(!1),s._mesh=De.a.CreateSphere(e+"_mesh",i.resolution,i.size,o,!1,De.a.BACKSIDE);var d=s._material=new so(e+"_material",o);d.useEquirectangularFOV=!0,d.fovMultiplier=1,d.opacityFresnel=!1;var p=s._initTexture(n,o,i);if(s.texture=p,s._mesh.material=d,s._mesh.parent=s,s._halfDomeMask=Fn.a.CreateSphere("",{slice:.5,diameter:.98*i.size,segments:2*i.resolution,sideOrientation:De.a.BACKSIDE},o),s._halfDomeMask.rotate(ye.a.X,-Math.PI/2),s._halfDomeMask.parent=s._mesh,s._halfDome=!!i.halfDomeMode,s._halfDomeMask.setEnabled(s._halfDome),s._crossEye=!!i.crossEyeMode,s._texture.anisotropicFilteringLevel=1,s._texture.onLoadObservable.addOnce(function(){s._setReady(!0)}),i.faceForward&&o.activeCamera){var b=o.activeCamera,P=u.e.Forward(),O=u.e.TransformNormal(P,b.getViewMatrix());O.normalize(),s.rotation.y=Math.acos(u.e.Dot(P,O))}return s._changeTextureMode(s._textureMode),s}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"texture",{get:function(){return this._texture},set:function(e){this._texture!==e&&(this._texture=e,this._useDirectMapping?(this._texture.wrapU=we.a.CLAMP_ADDRESSMODE,this._texture.wrapV=we.a.CLAMP_ADDRESSMODE,this._material.diffuseTexture=this._texture):(this._texture.coordinatesMode=we.a.FIXED_EQUIRECTANGULAR_MIRRORED_MODE,this._texture.wrapV=we.a.CLAMP_ADDRESSMODE,this._material.reflectionTexture=this._texture),this._changeTextureMode(this._textureMode))},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"mesh",{get:function(){return this._mesh},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"fovMultiplier",{get:function(){return this._material.fovMultiplier},set:function(e){this._material.fovMultiplier=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"textureMode",{get:function(){return this._textureMode},set:function(e){this._textureMode!==e&&this._changeTextureMode(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"halfDome",{get:function(){return this._halfDome},set:function(e){this._halfDome=e,this._halfDomeMask.setEnabled(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"crossEye",{get:function(){return this._crossEye},set:function(e){this._crossEye=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"material",{get:function(){return this._material},enumerable:!1,configurable:!0}),t.prototype._changeTextureMode=function(e){var n=this;switch(this._scene.onBeforeCameraRenderObservable.remove(this._onBeforeCameraRenderObserver),this._textureMode=e,this._texture.uScale=1,this._texture.vScale=1,this._texture.uOffset=0,this._texture.vOffset=0,this._texture.vAng=0,e){case t.MODE_MONOSCOPIC:this._halfDome&&(this._texture.uScale=2,this._texture.uOffset=-1);break;case t.MODE_SIDEBYSIDE:this._texture.uScale=this._halfDome?.99999:.5;var i=this._halfDome?0:.5,o=this._halfDome?-.5:0;this._onBeforeCameraRenderObserver=this._scene.onBeforeCameraRenderObservable.add(function(a){var s=a.isRightCamera;n._crossEye&&(s=!s),n._texture.uOffset=s?i:o});break;case t.MODE_TOPBOTTOM:this._texture.vScale=this._halfDome?.99999:.5,this._onBeforeCameraRenderObserver=this._scene.onBeforeCameraRenderObservable.add(function(a){var s=a.isRightCamera;n._crossEye&&(s=!s),n._texture.vOffset=s?.5:0})}},t.prototype.dispose=function(e,n){n===void 0&&(n=!1),this._texture.dispose(),this._mesh.dispose(),this._material.dispose(),this._scene.onBeforeCameraRenderObservable.remove(this._onBeforeCameraRenderObserver),this.onLoadErrorObservable.clear(),r.prototype.dispose.call(this,e,n)},t.MODE_MONOSCOPIC=0,t.MODE_TOPBOTTOM=1,t.MODE_SIDEBYSIDE=2,t}(Er.a),Rp=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"photoTexture",{get:function(){return this.texture},set:function(e){this.texture=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"imageMode",{get:function(){return this.textureMode},set:function(e){this.textureMode=e},enumerable:!1,configurable:!0}),t.prototype._initTexture=function(e,n,i){var o=this;return new we.a(e,n,!i.generateMipMaps,!this._useDirectMapping,void 0,void 0,function(a,s){o.onLoadErrorObservable.notifyObservers(a||"Unknown error occured"),o.onError&&o.onError(a,s)})},t.MODE_MONOSCOPIC=ki.MODE_MONOSCOPIC,t.MODE_TOPBOTTOM=ki.MODE_TOPBOTTOM,t.MODE_SIDEBYSIDE=ki.MODE_SIDEBYSIDE,t}(ki),_u=function(){function r(){}return r.ExpandRGBDTexture=function(t){var e=t._texture;if(e&&t.isRGBD){var n=e.getEngine(),i=n.getCaps(),o=!1;i.textureHalfFloatRender&&i.textureHalfFloatLinearFiltering?(o=!0,e.type=h.a.TEXTURETYPE_HALF_FLOAT):i.textureFloatRender&&i.textureFloatLinearFiltering&&(o=!0,e.type=h.a.TEXTURETYPE_FLOAT),o&&(e.isReady=!1,e._isRGBD=!1,e.invertY=!1),t.onLoadObservable.addOnce(function(){if(o){var a=new _t("rgbdDecode","rgbdDecode",null,null,1,null,h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,n,!1,void 0,e.type,void 0,null,!1),s=n.createRenderTargetTexture(e.width,{generateDepthBuffer:!1,generateMipMaps:!1,generateStencilBuffer:!1,samplingMode:e.samplingMode,type:e.type,format:h.a.TEXTUREFORMAT_RGBA});a.getEffect().executeWhenCompiled(function(){a.onApply=function(d){d._bindTexture("textureSampler",e),d.setFloat2("scale",1,1)},t.getScene().postProcessManager.directRender([a],s,!0),n.restoreDefaultFramebuffer(),n._releaseTexture(e),n._releaseFramebufferObjects(s),a&&a.dispose(),s._swapAndDie(e),e.isReady=!0})}})}},r}(),ea=function(){function r(){}return r.GetEnvironmentBRDFTexture=function(t){if(!t.environmentBRDFTexture){var e=t.useDelayedTextureLoading;t.useDelayedTextureLoading=!1;var n=t._blockEntityCollection;t._blockEntityCollection=!1;var i=we.a.CreateFromBase64String(this._environmentBRDFBase64Texture,"EnvironmentBRDFTexture"+this._instanceNumber++,t,!0,!1,we.a.BILINEAR_SAMPLINGMODE);t._blockEntityCollection=n;var o=t.getEngine().getLoadedTexturesCache(),a=o.indexOf(i.getInternalTexture());a!==-1&&o.splice(a,1),i.isRGBD=!0,i.wrapU=we.a.CLAMP_ADDRESSMODE,i.wrapV=we.a.CLAMP_ADDRESSMODE,t.environmentBRDFTexture=i,t.useDelayedTextureLoading=e,_u.ExpandRGBDTexture(i)}return 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",r}(),Ar=function(){function r(t){this._isEnabled=!1,this.isEnabled=!1,this.intensity=1,this.roughness=0,this._indexOfRefraction=r._DefaultIndexOfRefraction,this.indexOfRefraction=r._DefaultIndexOfRefraction,this._texture=null,this.texture=null,this._useRoughnessFromMainTexture=!0,this.useRoughnessFromMainTexture=!0,this._textureRoughness=null,this.textureRoughness=null,this._remapF0OnInterfaceChange=!0,this.remapF0OnInterfaceChange=!0,this._bumpTexture=null,this.bumpTexture=null,this._isTintEnabled=!1,this.isTintEnabled=!1,this.tintColor=M.a.White(),this.tintColorAtDistance=1,this.tintThickness=1,this._tintTexture=null,this.tintTexture=null,this._internalMarkAllSubMeshesAsTexturesDirty=t}return r.prototype._markAllSubMeshesAsTexturesDirty=function(){this._internalMarkAllSubMeshesAsTexturesDirty()},r.prototype.isReadyForSubMesh=function(t,e,n,i){return!(t._areTexturesDirty&&e.texturesEnabled&&(this._texture&&ht.a.ClearCoatTextureEnabled&&!this._texture.isReadyOrNotBlocking()||this._textureRoughness&&ht.a.ClearCoatTextureEnabled&&!this._textureRoughness.isReadyOrNotBlocking()||n.getCaps().standardDerivatives&&this._bumpTexture&&ht.a.ClearCoatBumpTextureEnabled&&!i&&!this._bumpTexture.isReady()||this._isTintEnabled&&this._tintTexture&&ht.a.ClearCoatTintTextureEnabled&&!this._tintTexture.isReadyOrNotBlocking()))},r.prototype.prepareDefines=function(t,e){var n;this._isEnabled?(t.CLEARCOAT=!0,t.CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE=this._useRoughnessFromMainTexture,t.CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL=this._texture!==null&&this._texture._texture===((n=this._textureRoughness)===null||n===void 0?void 0:n._texture)&&this._texture.checkTransformsAreIdentical(this._textureRoughness),t.CLEARCOAT_REMAP_F0=this._remapF0OnInterfaceChange,t._areTexturesDirty&&e.texturesEnabled&&(this._texture&&ht.a.ClearCoatTextureEnabled?et.a.PrepareDefinesForMergedUV(this._texture,t,"CLEARCOAT_TEXTURE"):t.CLEARCOAT_TEXTURE=!1,this._textureRoughness&&ht.a.ClearCoatTextureEnabled?et.a.PrepareDefinesForMergedUV(this._textureRoughness,t,"CLEARCOAT_TEXTURE_ROUGHNESS"):t.CLEARCOAT_TEXTURE_ROUGHNESS=!1,this._bumpTexture&&ht.a.ClearCoatBumpTextureEnabled?et.a.PrepareDefinesForMergedUV(this._bumpTexture,t,"CLEARCOAT_BUMP"):t.CLEARCOAT_BUMP=!1,t.CLEARCOAT_DEFAULTIOR=this._indexOfRefraction===r._DefaultIndexOfRefraction,this._isTintEnabled?(t.CLEARCOAT_TINT=!0,this._tintTexture&&ht.a.ClearCoatTintTextureEnabled?et.a.PrepareDefinesForMergedUV(this._tintTexture,t,"CLEARCOAT_TINT_TEXTURE"):t.CLEARCOAT_TINT_TEXTURE=!1):(t.CLEARCOAT_TINT=!1,t.CLEARCOAT_TINT_TEXTURE=!1))):(t.CLEARCOAT=!1,t.CLEARCOAT_TEXTURE=!1,t.CLEARCOAT_TEXTURE_ROUGHNESS=!1,t.CLEARCOAT_BUMP=!1,t.CLEARCOAT_TINT=!1,t.CLEARCOAT_TINT_TEXTURE=!1,t.CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE=!1,t.CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL=!1)},r.prototype.bindForSubMesh=function(t,e,n,i,o,a,s,d){var p,b,P,O,B,F,z,J,ie=d._materialDefines,se=ie.CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL;if(!t.useUbo||!o||!t.isSync){se&&ht.a.ClearCoatTextureEnabled?(t.updateFloat4("vClearCoatInfos",this._texture.coordinatesIndex,this._texture.level,-1,-1),et.a.BindTextureMatrix(this._texture,t,"clearCoat")):(this._texture||this._textureRoughness)&&ht.a.ClearCoatTextureEnabled&&(t.updateFloat4("vClearCoatInfos",(b=(p=this._texture)===null||p===void 0?void 0:p.coordinatesIndex)!==null&&b!==void 0?b:0,(O=(P=this._texture)===null||P===void 0?void 0:P.level)!==null&&O!==void 0?O:0,(F=(B=this._textureRoughness)===null||B===void 0?void 0:B.coordinatesIndex)!==null&&F!==void 0?F:0,(J=(z=this._textureRoughness)===null||z===void 0?void 0:z.level)!==null&&J!==void 0?J:0),this._texture&&et.a.BindTextureMatrix(this._texture,t,"clearCoat"),!this._textureRoughness||se||ie.CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE||et.a.BindTextureMatrix(this._textureRoughness,t,"clearCoatRoughness")),this._bumpTexture&&n.getCaps().standardDerivatives&&ht.a.ClearCoatTextureEnabled&&!i&&(t.updateFloat2("vClearCoatBumpInfos",this._bumpTexture.coordinatesIndex,this._bumpTexture.level),et.a.BindTextureMatrix(this._bumpTexture,t,"clearCoatBump"),e._mirroredCameraPosition?t.updateFloat2("vClearCoatTangentSpaceParams",a?1:-1,s?1:-1):t.updateFloat2("vClearCoatTangentSpaceParams",a?-1:1,s?-1:1)),this._tintTexture&&ht.a.ClearCoatTintTextureEnabled&&(t.updateFloat2("vClearCoatTintInfos",this._tintTexture.coordinatesIndex,this._tintTexture.level),et.a.BindTextureMatrix(this._tintTexture,t,"clearCoatTint")),t.updateFloat2("vClearCoatParams",this.intensity,this.roughness);var ce=1-this._indexOfRefraction,ue=1+this._indexOfRefraction,fe=Math.pow(-ce/ue,2),ve=1/this._indexOfRefraction;t.updateFloat4("vClearCoatRefractionParams",fe,ve,ce,ue),this._isTintEnabled&&(t.updateFloat4("vClearCoatTintParams",this.tintColor.r,this.tintColor.g,this.tintColor.b,Math.max(1e-5,this.tintThickness)),t.updateFloat("clearCoatColorAtDistance",Math.max(1e-5,this.tintColorAtDistance)))}e.texturesEnabled&&(this._texture&&ht.a.ClearCoatTextureEnabled&&t.setTexture("clearCoatSampler",this._texture),this._textureRoughness&&!se&&!ie.CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE&&ht.a.ClearCoatTextureEnabled&&t.setTexture("clearCoatRoughnessSampler",this._textureRoughness),this._bumpTexture&&n.getCaps().standardDerivatives&&ht.a.ClearCoatBumpTextureEnabled&&!i&&t.setTexture("clearCoatBumpSampler",this._bumpTexture),this._isTintEnabled&&this._tintTexture&&ht.a.ClearCoatTintTextureEnabled&&t.setTexture("clearCoatTintSampler",this._tintTexture))},r.prototype.hasTexture=function(t){return this._texture===t||this._textureRoughness===t||this._bumpTexture===t||this._tintTexture===t},r.prototype.getActiveTextures=function(t){this._texture&&t.push(this._texture),this._textureRoughness&&t.push(this._textureRoughness),this._bumpTexture&&t.push(this._bumpTexture),this._tintTexture&&t.push(this._tintTexture)},r.prototype.getAnimatables=function(t){this._texture&&this._texture.animations&&this._texture.animations.length>0&&t.push(this._texture),this._textureRoughness&&this._textureRoughness.animations&&this._textureRoughness.animations.length>0&&t.push(this._textureRoughness),this._bumpTexture&&this._bumpTexture.animations&&this._bumpTexture.animations.length>0&&t.push(this._bumpTexture),this._tintTexture&&this._tintTexture.animations&&this._tintTexture.animations.length>0&&t.push(this._tintTexture)},r.prototype.dispose=function(t){var e,n,i,o;t&&((e=this._texture)===null||e===void 0||e.dispose(),(n=this._textureRoughness)===null||n===void 0||n.dispose(),(i=this._bumpTexture)===null||i===void 0||i.dispose(),(o=this._tintTexture)===null||o===void 0||o.dispose())},r.prototype.getClassName=function(){return"PBRClearCoatConfiguration"},r.AddFallbacks=function(t,e,n){return t.CLEARCOAT_BUMP&&e.addFallback(n++,"CLEARCOAT_BUMP"),t.CLEARCOAT_TINT&&e.addFallback(n++,"CLEARCOAT_TINT"),t.CLEARCOAT&&e.addFallback(n++,"CLEARCOAT"),n},r.AddUniforms=function(t){t.push("vClearCoatTangentSpaceParams","vClearCoatParams","vClearCoatRefractionParams","vClearCoatTintParams","clearCoatColorAtDistance","clearCoatMatrix","clearCoatRoughnessMatrix","clearCoatBumpMatrix","clearCoatTintMatrix","vClearCoatInfos","vClearCoatBumpInfos","vClearCoatTintInfos")},r.AddSamplers=function(t){t.push("clearCoatSampler","clearCoatRoughnessSampler","clearCoatBumpSampler","clearCoatTintSampler")},r.PrepareUniformBuffer=function(t){t.addUniform("vClearCoatParams",2),t.addUniform("vClearCoatRefractionParams",4),t.addUniform("vClearCoatInfos",4),t.addUniform("clearCoatMatrix",16),t.addUniform("clearCoatRoughnessMatrix",16),t.addUniform("vClearCoatBumpInfos",2),t.addUniform("vClearCoatTangentSpaceParams",2),t.addUniform("clearCoatBumpMatrix",16),t.addUniform("vClearCoatTintParams",4),t.addUniform("clearCoatColorAtDistance",1),t.addUniform("vClearCoatTintInfos",2),t.addUniform("clearCoatTintMatrix",16)},r.prototype.copyTo=function(t){L.a.Clone(function(){return t},this)},r.prototype.serialize=function(){return L.a.Serialize(this)},r.prototype.parse=function(t,e,n){var i=this;L.a.Parse(function(){return i},t,e,n)},r._DefaultIndexOfRefraction=1.5,Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"isEnabled",void 0),Object(c.c)([Object(L.c)()],r.prototype,"intensity",void 0),Object(c.c)([Object(L.c)()],r.prototype,"roughness",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"indexOfRefraction",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"texture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"useRoughnessFromMainTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"textureRoughness",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"remapF0OnInterfaceChange",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"bumpTexture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"isTintEnabled",void 0),Object(c.c)([Object(L.e)()],r.prototype,"tintColor",void 0),Object(c.c)([Object(L.c)()],r.prototype,"tintColorAtDistance",void 0),Object(c.c)([Object(L.c)()],r.prototype,"tintThickness",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"tintTexture",void 0),r}(),Pr=function(){function r(t){this._isEnabled=!1,this.isEnabled=!1,this.intensity=1,this.direction=new u.d(1,0),this._texture=null,this.texture=null,this._internalMarkAllSubMeshesAsTexturesDirty=t}return r.prototype._markAllSubMeshesAsTexturesDirty=function(){this._internalMarkAllSubMeshesAsTexturesDirty()},r.prototype.isReadyForSubMesh=function(t,e){return!(t._areTexturesDirty&&e.texturesEnabled&&this._texture&&ht.a.AnisotropicTextureEnabled&&!this._texture.isReadyOrNotBlocking())},r.prototype.prepareDefines=function(t,e,n){this._isEnabled?(t.ANISOTROPIC=this._isEnabled,this._isEnabled&&!e.isVerticesDataPresent(Oe.b.TangentKind)&&(t._needUVs=!0,t.MAINUV1=!0),t._areTexturesDirty&&n.texturesEnabled&&(this._texture&&ht.a.AnisotropicTextureEnabled?et.a.PrepareDefinesForMergedUV(this._texture,t,"ANISOTROPIC_TEXTURE"):t.ANISOTROPIC_TEXTURE=!1)):(t.ANISOTROPIC=!1,t.ANISOTROPIC_TEXTURE=!1)},r.prototype.bindForSubMesh=function(t,e,n){t.useUbo&&n&&t.isSync||(this._texture&&ht.a.AnisotropicTextureEnabled&&(t.updateFloat2("vAnisotropyInfos",this._texture.coordinatesIndex,this._texture.level),et.a.BindTextureMatrix(this._texture,t,"anisotropy")),t.updateFloat3("vAnisotropy",this.direction.x,this.direction.y,this.intensity)),e.texturesEnabled&&this._texture&&ht.a.AnisotropicTextureEnabled&&t.setTexture("anisotropySampler",this._texture)},r.prototype.hasTexture=function(t){return this._texture===t},r.prototype.getActiveTextures=function(t){this._texture&&t.push(this._texture)},r.prototype.getAnimatables=function(t){this._texture&&this._texture.animations&&this._texture.animations.length>0&&t.push(this._texture)},r.prototype.dispose=function(t){t&&this._texture&&this._texture.dispose()},r.prototype.getClassName=function(){return"PBRAnisotropicConfiguration"},r.AddFallbacks=function(t,e,n){return t.ANISOTROPIC&&e.addFallback(n++,"ANISOTROPIC"),n},r.AddUniforms=function(t){t.push("vAnisotropy","vAnisotropyInfos","anisotropyMatrix")},r.PrepareUniformBuffer=function(t){t.addUniform("vAnisotropy",3),t.addUniform("vAnisotropyInfos",2),t.addUniform("anisotropyMatrix",16)},r.AddSamplers=function(t){t.push("anisotropySampler")},r.prototype.copyTo=function(t){L.a.Clone(function(){return t},this)},r.prototype.serialize=function(){return L.a.Serialize(this)},r.prototype.parse=function(t,e,n){var i=this;L.a.Parse(function(){return i},t,e,n)},Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"isEnabled",void 0),Object(c.c)([Object(L.c)()],r.prototype,"intensity",void 0),Object(c.c)([Object(L.n)()],r.prototype,"direction",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"texture",void 0),r}(),Op=function(){function r(t){this._useEnergyConservation=r.DEFAULT_USE_ENERGY_CONSERVATION,this.useEnergyConservation=r.DEFAULT_USE_ENERGY_CONSERVATION,this._useSmithVisibilityHeightCorrelated=r.DEFAULT_USE_SMITH_VISIBILITY_HEIGHT_CORRELATED,this.useSmithVisibilityHeightCorrelated=r.DEFAULT_USE_SMITH_VISIBILITY_HEIGHT_CORRELATED,this._useSphericalHarmonics=r.DEFAULT_USE_SPHERICAL_HARMONICS,this.useSphericalHarmonics=r.DEFAULT_USE_SPHERICAL_HARMONICS,this._useSpecularGlossinessInputEnergyConservation=r.DEFAULT_USE_SPECULAR_GLOSSINESS_INPUT_ENERGY_CONSERVATION,this.useSpecularGlossinessInputEnergyConservation=r.DEFAULT_USE_SPECULAR_GLOSSINESS_INPUT_ENERGY_CONSERVATION,this._internalMarkAllSubMeshesAsMiscDirty=t}return r.prototype._markAllSubMeshesAsMiscDirty=function(){this._internalMarkAllSubMeshesAsMiscDirty()},r.prototype.prepareDefines=function(t){t.BRDF_V_HEIGHT_CORRELATED=this._useSmithVisibilityHeightCorrelated,t.MS_BRDF_ENERGY_CONSERVATION=this._useEnergyConservation&&this._useSmithVisibilityHeightCorrelated,t.SPHERICAL_HARMONICS=this._useSphericalHarmonics,t.SPECULAR_GLOSSINESS_ENERGY_CONSERVATION=this._useSpecularGlossinessInputEnergyConservation},r.prototype.getClassName=function(){return"PBRBRDFConfiguration"},r.prototype.copyTo=function(t){L.a.Clone(function(){return t},this)},r.prototype.serialize=function(){return L.a.Serialize(this)},r.prototype.parse=function(t,e,n){var i=this;L.a.Parse(function(){return i},t,e,n)},r.DEFAULT_USE_ENERGY_CONSERVATION=!0,r.DEFAULT_USE_SMITH_VISIBILITY_HEIGHT_CORRELATED=!0,r.DEFAULT_USE_SPHERICAL_HARMONICS=!0,r.DEFAULT_USE_SPECULAR_GLOSSINESS_INPUT_ENERGY_CONSERVATION=!0,Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsMiscDirty")],r.prototype,"useEnergyConservation",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsMiscDirty")],r.prototype,"useSmithVisibilityHeightCorrelated",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsMiscDirty")],r.prototype,"useSphericalHarmonics",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsMiscDirty")],r.prototype,"useSpecularGlossinessInputEnergyConservation",void 0),r}(),co=function(){function r(t){this._isEnabled=!1,this.isEnabled=!1,this._linkSheenWithAlbedo=!1,this.linkSheenWithAlbedo=!1,this.intensity=1,this.color=M.a.White(),this._texture=null,this.texture=null,this._useRoughnessFromMainTexture=!0,this.useRoughnessFromMainTexture=!0,this._roughness=null,this.roughness=null,this._textureRoughness=null,this.textureRoughness=null,this._albedoScaling=!1,this.albedoScaling=!1,this._internalMarkAllSubMeshesAsTexturesDirty=t}return r.prototype._markAllSubMeshesAsTexturesDirty=function(){this._internalMarkAllSubMeshesAsTexturesDirty()},r.prototype.isReadyForSubMesh=function(t,e){return!(t._areTexturesDirty&&e.texturesEnabled&&(this._texture&&ht.a.SheenTextureEnabled&&!this._texture.isReadyOrNotBlocking()||this._textureRoughness&&ht.a.SheenTextureEnabled&&!this._textureRoughness.isReadyOrNotBlocking()))},r.prototype.prepareDefines=function(t,e){var n;this._isEnabled?(t.SHEEN=this._isEnabled,t.SHEEN_LINKWITHALBEDO=this._linkSheenWithAlbedo,t.SHEEN_ROUGHNESS=this._roughness!==null,t.SHEEN_ALBEDOSCALING=this._albedoScaling,t.SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE=this._useRoughnessFromMainTexture,t.SHEEN_TEXTURE_ROUGHNESS_IDENTICAL=this._texture!==null&&this._texture._texture===((n=this._textureRoughness)===null||n===void 0?void 0:n._texture)&&this._texture.checkTransformsAreIdentical(this._textureRoughness),t._areTexturesDirty&&e.texturesEnabled&&(this._texture&&ht.a.SheenTextureEnabled?et.a.PrepareDefinesForMergedUV(this._texture,t,"SHEEN_TEXTURE"):t.SHEEN_TEXTURE=!1,this._textureRoughness&&ht.a.SheenTextureEnabled?et.a.PrepareDefinesForMergedUV(this._textureRoughness,t,"SHEEN_TEXTURE_ROUGHNESS"):t.SHEEN_TEXTURE_ROUGHNESS=!1)):(t.SHEEN=!1,t.SHEEN_TEXTURE=!1,t.SHEEN_TEXTURE_ROUGHNESS=!1,t.SHEEN_LINKWITHALBEDO=!1,t.SHEEN_ROUGHNESS=!1,t.SHEEN_ALBEDOSCALING=!1,t.SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE=!1,t.SHEEN_TEXTURE_ROUGHNESS_IDENTICAL=!1)},r.prototype.bindForSubMesh=function(t,e,n,i){var o,a,s,d,p,b,P,O,B=i._materialDefines,F=B.SHEEN_TEXTURE_ROUGHNESS_IDENTICAL;t.useUbo&&n&&t.isSync||(F&&ht.a.SheenTextureEnabled?(t.updateFloat4("vSheenInfos",this._texture.coordinatesIndex,this._texture.level,-1,-1),et.a.BindTextureMatrix(this._texture,t,"sheen")):(this._texture||this._textureRoughness)&&ht.a.SheenTextureEnabled&&(t.updateFloat4("vSheenInfos",(a=(o=this._texture)===null||o===void 0?void 0:o.coordinatesIndex)!==null&&a!==void 0?a:0,(d=(s=this._texture)===null||s===void 0?void 0:s.level)!==null&&d!==void 0?d:0,(b=(p=this._textureRoughness)===null||p===void 0?void 0:p.coordinatesIndex)!==null&&b!==void 0?b:0,(O=(P=this._textureRoughness)===null||P===void 0?void 0:P.level)!==null&&O!==void 0?O:0),this._texture&&et.a.BindTextureMatrix(this._texture,t,"sheen"),!this._textureRoughness||F||B.SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE||et.a.BindTextureMatrix(this._textureRoughness,t,"sheenRoughness")),t.updateFloat4("vSheenColor",this.color.r,this.color.g,this.color.b,this.intensity),this._roughness!==null&&t.updateFloat("vSheenRoughness",this._roughness)),e.texturesEnabled&&(this._texture&&ht.a.SheenTextureEnabled&&t.setTexture("sheenSampler",this._texture),this._textureRoughness&&!F&&!B.SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE&&ht.a.SheenTextureEnabled&&t.setTexture("sheenRoughnessSampler",this._textureRoughness))},r.prototype.hasTexture=function(t){return this._texture===t||this._textureRoughness===t},r.prototype.getActiveTextures=function(t){this._texture&&t.push(this._texture),this._textureRoughness&&t.push(this._textureRoughness)},r.prototype.getAnimatables=function(t){this._texture&&this._texture.animations&&this._texture.animations.length>0&&t.push(this._texture),this._textureRoughness&&this._textureRoughness.animations&&this._textureRoughness.animations.length>0&&t.push(this._textureRoughness)},r.prototype.dispose=function(t){var e,n;t&&((e=this._texture)===null||e===void 0||e.dispose(),(n=this._textureRoughness)===null||n===void 0||n.dispose())},r.prototype.getClassName=function(){return"PBRSheenConfiguration"},r.AddFallbacks=function(t,e,n){return t.SHEEN&&e.addFallback(n++,"SHEEN"),n},r.AddUniforms=function(t){t.push("vSheenColor","vSheenRoughness","vSheenInfos","sheenMatrix","sheenRoughnessMatrix")},r.PrepareUniformBuffer=function(t){t.addUniform("vSheenColor",4),t.addUniform("vSheenRoughness",1),t.addUniform("vSheenInfos",4),t.addUniform("sheenMatrix",16),t.addUniform("sheenRoughnessMatrix",16)},r.AddSamplers=function(t){t.push("sheenSampler"),t.push("sheenRoughnessSampler")},r.prototype.copyTo=function(t){L.a.Clone(function(){return t},this)},r.prototype.serialize=function(){return L.a.Serialize(this)},r.prototype.parse=function(t,e,n){var i=this;L.a.Parse(function(){return i},t,e,n)},Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"isEnabled",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"linkSheenWithAlbedo",void 0),Object(c.c)([Object(L.c)()],r.prototype,"intensity",void 0),Object(c.c)([Object(L.e)()],r.prototype,"color",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"texture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"useRoughnessFromMainTexture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"roughness",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"textureRoughness",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"albedoScaling",void 0),r}(),lo=function(){function r(t,e,n){this._isRefractionEnabled=!1,this.isRefractionEnabled=!1,this._isTranslucencyEnabled=!1,this.isTranslucencyEnabled=!1,this._isScatteringEnabled=!1,this.isScatteringEnabled=!1,this._scatteringDiffusionProfileIndex=0,this.refractionIntensity=1,this.translucencyIntensity=1,this.useAlbedoToTintRefraction=!1,this._thicknessTexture=null,this.thicknessTexture=null,this._refractionTexture=null,this.refractionTexture=null,this._indexOfRefraction=1.5,this.indexOfRefraction=1.5,this._volumeIndexOfRefraction=-1,this._invertRefractionY=!1,this.invertRefractionY=!1,this._linkRefractionWithTransparency=!1,this.linkRefractionWithTransparency=!1,this.minimumThickness=0,this.maximumThickness=1,this.tintColor=M.a.White(),this.tintColorAtDistance=1,this.diffusionDistance=M.a.White(),this._useMaskFromThicknessTexture=!1,this.useMaskFromThicknessTexture=!1,this._useMaskFromThicknessTextureGltf=!1,this.useMaskFromThicknessTextureGltf=!1,this._internalMarkAllSubMeshesAsTexturesDirty=t,this._internalMarkScenePrePassDirty=e,this._scene=n}return Object.defineProperty(r.prototype,"scatteringDiffusionProfile",{get:function(){return this._scene.subSurfaceConfiguration?this._scene.subSurfaceConfiguration.ssDiffusionProfileColors[this._scatteringDiffusionProfileIndex]:null},set:function(t){this._scene.enableSubSurfaceForPrePass()&&t&&(this._scatteringDiffusionProfileIndex=this._scene.subSurfaceConfiguration.addDiffusionProfile(t))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"volumeIndexOfRefraction",{get:function(){return this._volumeIndexOfRefraction>=1?this._volumeIndexOfRefraction:this._indexOfRefraction},set:function(t){this._volumeIndexOfRefraction=t>=1?t:-1},enumerable:!1,configurable:!0}),r.prototype._markAllSubMeshesAsTexturesDirty=function(){this._internalMarkAllSubMeshesAsTexturesDirty()},r.prototype._markScenePrePassDirty=function(){this._internalMarkAllSubMeshesAsTexturesDirty(),this._internalMarkScenePrePassDirty()},r.prototype.isReadyForSubMesh=function(t,e){if(t._areTexturesDirty&&e.texturesEnabled){if(this._thicknessTexture&&ht.a.ThicknessTextureEnabled&&!this._thicknessTexture.isReadyOrNotBlocking())return!1;var n=this._getRefractionTexture(e);if(n&&ht.a.RefractionTextureEnabled&&!n.isReadyOrNotBlocking())return!1}return!0},r.prototype.prepareDefines=function(t,e){if(t._areTexturesDirty&&(t.SUBSURFACE=!1,t.SS_TRANSLUCENCY=this._isTranslucencyEnabled,t.SS_SCATTERING=this._isScatteringEnabled,t.SS_THICKNESSANDMASK_TEXTURE=!1,t.SS_MASK_FROM_THICKNESS_TEXTURE=!1,t.SS_MASK_FROM_THICKNESS_TEXTURE_GLTF=!1,t.SS_REFRACTION=!1,t.SS_REFRACTIONMAP_3D=!1,t.SS_GAMMAREFRACTION=!1,t.SS_RGBDREFRACTION=!1,t.SS_LINEARSPECULARREFRACTION=!1,t.SS_REFRACTIONMAP_OPPOSITEZ=!1,t.SS_LODINREFRACTIONALPHA=!1,t.SS_LINKREFRACTIONTOTRANSPARENCY=!1,t.SS_ALBEDOFORREFRACTIONTINT=!1,(this._isRefractionEnabled||this._isTranslucencyEnabled||this._isScatteringEnabled)&&(t.SUBSURFACE=!0,t._areTexturesDirty&&e.texturesEnabled&&this._thicknessTexture&&ht.a.ThicknessTextureEnabled&&et.a.PrepareDefinesForMergedUV(this._thicknessTexture,t,"SS_THICKNESSANDMASK_TEXTURE"),t.SS_MASK_FROM_THICKNESS_TEXTURE=this._useMaskFromThicknessTexture,t.SS_MASK_FROM_THICKNESS_TEXTURE_GLTF=this._useMaskFromThicknessTextureGltf),this._isRefractionEnabled&&e.texturesEnabled)){var n=this._getRefractionTexture(e);n&&ht.a.RefractionTextureEnabled&&(t.SS_REFRACTION=!0,t.SS_REFRACTIONMAP_3D=n.isCube,t.SS_GAMMAREFRACTION=n.gammaSpace,t.SS_RGBDREFRACTION=n.isRGBD,t.SS_LINEARSPECULARREFRACTION=n.linearSpecularLOD,t.SS_REFRACTIONMAP_OPPOSITEZ=n.invertZ,t.SS_LODINREFRACTIONALPHA=n.lodLevelInAlpha,t.SS_LINKREFRACTIONTOTRANSPARENCY=this._linkRefractionWithTransparency,t.SS_ALBEDOFORREFRACTIONTINT=this.useAlbedoToTintRefraction)}},r.prototype.bindForSubMesh=function(t,e,n,i,o,a){var s=this._getRefractionTexture(e);if(!t.useUbo||!i||!t.isSync){if(this._thicknessTexture&&ht.a.ThicknessTextureEnabled&&(t.updateFloat2("vThicknessInfos",this._thicknessTexture.coordinatesIndex,this._thicknessTexture.level),et.a.BindTextureMatrix(this._thicknessTexture,t,"thickness")),t.updateFloat2("vThicknessParam",this.minimumThickness,this.maximumThickness-this.minimumThickness),s&&ht.a.RefractionTextureEnabled){t.updateMatrix("refractionMatrix",s.getReflectionTextureMatrix());var d=1;s.isCube||s.depth&&(d=s.depth);var p=s.getSize().width,b=this.volumeIndexOfRefraction;t.updateFloat4("vRefractionInfos",s.level,1/b,d,this._invertRefractionY?-1:1),t.updateFloat3("vRefractionMicrosurfaceInfos",p,s.lodGenerationScale,s.lodGenerationOffset),a&&t.updateFloat2("vRefractionFilteringInfo",p,$.a.Log2(p))}this.isScatteringEnabled&&t.updateFloat("scatteringDiffusionProfile",this._scatteringDiffusionProfileIndex),t.updateColor3("vDiffusionDistance",this.diffusionDistance),t.updateFloat4("vTintColor",this.tintColor.r,this.tintColor.g,this.tintColor.b,this.tintColorAtDistance),t.updateFloat3("vSubSurfaceIntensity",this.refractionIntensity,this.translucencyIntensity,0)}e.texturesEnabled&&(this._thicknessTexture&&ht.a.ThicknessTextureEnabled&&t.setTexture("thicknessSampler",this._thicknessTexture),s&&ht.a.RefractionTextureEnabled&&(o?t.setTexture("refractionSampler",s):(t.setTexture("refractionSampler",s._lodTextureMid||s),t.setTexture("refractionSamplerLow",s._lodTextureLow||s),t.setTexture("refractionSamplerHigh",s._lodTextureHigh||s))))},r.prototype.unbind=function(t){return!(!this._refractionTexture||!this._refractionTexture.isRenderTarget)&&(t.setTexture("refractionSampler",null),!0)},r.prototype._getRefractionTexture=function(t){return this._refractionTexture?this._refractionTexture:this._isRefractionEnabled?t.environmentTexture:null},Object.defineProperty(r.prototype,"disableAlphaBlending",{get:function(){return this.isRefractionEnabled&&this._linkRefractionWithTransparency},enumerable:!1,configurable:!0}),r.prototype.fillRenderTargetTextures=function(t){ht.a.RefractionTextureEnabled&&this._refractionTexture&&this._refractionTexture.isRenderTarget&&t.push(this._refractionTexture)},r.prototype.hasTexture=function(t){return this._thicknessTexture===t||this._refractionTexture===t},r.prototype.hasRenderTargetTextures=function(){return!!(ht.a.RefractionTextureEnabled&&this._refractionTexture&&this._refractionTexture.isRenderTarget)},r.prototype.getActiveTextures=function(t){this._thicknessTexture&&t.push(this._thicknessTexture),this._refractionTexture&&t.push(this._refractionTexture)},r.prototype.getAnimatables=function(t){this._thicknessTexture&&this._thicknessTexture.animations&&this._thicknessTexture.animations.length>0&&t.push(this._thicknessTexture),this._refractionTexture&&this._refractionTexture.animations&&this._refractionTexture.animations.length>0&&t.push(this._refractionTexture)},r.prototype.dispose=function(t){t&&(this._thicknessTexture&&this._thicknessTexture.dispose(),this._refractionTexture&&this._refractionTexture.dispose())},r.prototype.getClassName=function(){return"PBRSubSurfaceConfiguration"},r.AddFallbacks=function(t,e,n){return t.SS_SCATTERING&&e.addFallback(n++,"SS_SCATTERING"),t.SS_TRANSLUCENCY&&e.addFallback(n++,"SS_TRANSLUCENCY"),n},r.AddUniforms=function(t){t.push("vDiffusionDistance","vTintColor","vSubSurfaceIntensity","vRefractionMicrosurfaceInfos","vRefractionFilteringInfo","vRefractionInfos","vThicknessInfos","vThicknessParam","refractionMatrix","thicknessMatrix","scatteringDiffusionProfile")},r.AddSamplers=function(t){t.push("thicknessSampler","refractionSampler","refractionSamplerLow","refractionSamplerHigh")},r.PrepareUniformBuffer=function(t){t.addUniform("vRefractionMicrosurfaceInfos",3),t.addUniform("vRefractionFilteringInfo",2),t.addUniform("vRefractionInfos",4),t.addUniform("refractionMatrix",16),t.addUniform("vThicknessInfos",2),t.addUniform("thicknessMatrix",16),t.addUniform("vThicknessParam",2),t.addUniform("vDiffusionDistance",3),t.addUniform("vTintColor",4),t.addUniform("vSubSurfaceIntensity",3),t.addUniform("scatteringDiffusionProfile",1)},r.prototype.copyTo=function(t){L.a.Clone(function(){return t},this)},r.prototype.serialize=function(){return L.a.Serialize(this)},r.prototype.parse=function(t,e,n){var i=this;L.a.Parse(function(){return i},t,e,n)},Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"isRefractionEnabled",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"isTranslucencyEnabled",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markScenePrePassDirty")],r.prototype,"isScatteringEnabled",void 0),Object(c.c)([Object(L.c)()],r.prototype,"_scatteringDiffusionProfileIndex",void 0),Object(c.c)([Object(L.c)()],r.prototype,"refractionIntensity",void 0),Object(c.c)([Object(L.c)()],r.prototype,"translucencyIntensity",void 0),Object(c.c)([Object(L.c)()],r.prototype,"useAlbedoToTintRefraction",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],r.prototype,"thicknessTexture",void 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-uniform vec4 vAlbedoColor;
-
-uniform vec4 vLightingIntensity;
-uniform vec4 vReflectivityColor;
-uniform vec4 vMetallicReflectanceFactors;
-uniform vec3 vEmissiveColor;
-uniform float visibility;
-
-#ifdef ALBEDO
-uniform vec2 vAlbedoInfos;
-#endif
-#ifdef AMBIENT
-uniform vec4 vAmbientInfos;
-#endif
-#ifdef BUMP
-uniform vec3 vBumpInfos;
-uniform vec2 vTangentSpaceParams;
-#endif
-#ifdef OPACITY
-uniform vec2 vOpacityInfos;
-#endif
-#ifdef EMISSIVE
-uniform vec2 vEmissiveInfos;
-#endif
-#ifdef LIGHTMAP
-uniform vec2 vLightmapInfos;
-#endif
-#ifdef REFLECTIVITY
-uniform vec3 vReflectivityInfos;
-#endif
-#ifdef MICROSURFACEMAP
-uniform vec2 vMicroSurfaceSamplerInfos;
-#endif
-
-#if defined(REFLECTIONMAP_SPHERICAL) || defined(REFLECTIONMAP_PROJECTION) || defined(SS_REFRACTION)
-uniform mat4 view;
-#endif
-
-#ifdef REFLECTION
-uniform vec2 vReflectionInfos;
-#ifdef REALTIME_FILTERING
-uniform vec2 vReflectionFilteringInfo;
-#endif
-uniform mat4 reflectionMatrix;
-uniform vec3 vReflectionMicrosurfaceInfos;
-#if defined(USE_LOCAL_REFLECTIONMAP_CUBIC) && defined(REFLECTIONMAP_CUBIC)
-uniform vec3 vReflectionPosition;
-uniform vec3 vReflectionSize;
-#endif
-#endif
-
-#ifdef CLEARCOAT
-uniform vec2 vClearCoatParams;
-uniform vec4 vClearCoatRefractionParams;
-#if defined(CLEARCOAT_TEXTURE) || defined(CLEARCOAT_TEXTURE_ROUGHNESS)
-uniform vec4 vClearCoatInfos;
-#endif
-#ifdef CLEARCOAT_TEXTURE
-uniform mat4 clearCoatMatrix;
-#endif
-#ifdef CLEARCOAT_TEXTURE_ROUGHNESS
-uniform mat4 clearCoatRoughnessMatrix;
-#endif
-#ifdef CLEARCOAT_BUMP
-uniform vec2 vClearCoatBumpInfos;
-uniform vec2 vClearCoatTangentSpaceParams;
-uniform mat4 clearCoatBumpMatrix;
-#endif
-#ifdef CLEARCOAT_TINT
-uniform vec4 vClearCoatTintParams;
-uniform float clearCoatColorAtDistance;
-#ifdef CLEARCOAT_TINT_TEXTURE
-uniform vec2 vClearCoatTintInfos;
-uniform mat4 clearCoatTintMatrix;
-#endif
-#endif
-#endif
-
-#ifdef ANISOTROPIC
-uniform vec3 vAnisotropy;
-#ifdef ANISOTROPIC_TEXTURE
-uniform vec2 vAnisotropyInfos;
-uniform mat4 anisotropyMatrix;
-#endif
-#endif
-
-#ifdef SHEEN
-uniform vec4 vSheenColor;
-#ifdef SHEEN_ROUGHNESS
-uniform float vSheenRoughness;
-#endif
-#if defined(SHEEN_TEXTURE) || defined(SHEEN_TEXTURE_ROUGHNESS)
-uniform vec4 vSheenInfos;
-#endif
-#ifdef SHEEN_TEXTURE
-uniform mat4 sheenMatrix;
-#endif
-#ifdef SHEEN_TEXTURE_ROUGHNESS
-uniform mat4 sheenRoughnessMatrix;
-#endif
-#endif
-
-#ifdef SUBSURFACE
-#ifdef SS_REFRACTION
-uniform vec3 vRefractionMicrosurfaceInfos;
-uniform vec4 vRefractionInfos;
-uniform mat4 refractionMatrix;
-#ifdef REALTIME_FILTERING
-uniform vec2 vRefractionFilteringInfo;
-#endif
-#endif
-#ifdef SS_THICKNESSANDMASK_TEXTURE
-uniform vec2 vThicknessInfos;
-uniform mat4 thicknessMatrix;
-#endif
-uniform vec2 vThicknessParam;
-uniform vec3 vDiffusionDistance;
-uniform vec4 vTintColor;
-uniform vec3 vSubSurfaceIntensity;
-#endif
-#ifdef PREPASS
-#ifdef PREPASS_IRRADIANCE
-uniform float scatteringDiffusionProfile;
-#endif
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-uniform Material
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-uniform vec2 vAlbedoInfos;
-uniform vec4 vAmbientInfos;
-uniform vec2 vOpacityInfos;
-uniform vec2 vEmissiveInfos;
-uniform vec2 vLightmapInfos;
-uniform vec3 vReflectivityInfos;
-uniform vec2 vMicroSurfaceSamplerInfos;
-uniform vec2 vReflectionInfos;
-uniform vec2 vReflectionFilteringInfo;
-uniform vec3 vReflectionPosition;
-uniform vec3 vReflectionSize;
-uniform vec3 vBumpInfos;
-uniform mat4 albedoMatrix;
-uniform mat4 ambientMatrix;
-uniform mat4 opacityMatrix;
-uniform mat4 emissiveMatrix;
-uniform mat4 lightmapMatrix;
-uniform mat4 reflectivityMatrix;
-uniform mat4 microSurfaceSamplerMatrix;
-uniform mat4 bumpMatrix;
-uniform vec2 vTangentSpaceParams;
-uniform mat4 reflectionMatrix;
-uniform vec3 vReflectionColor;
-uniform vec4 vAlbedoColor;
-uniform vec4 vLightingIntensity;
-uniform vec3 vReflectionMicrosurfaceInfos;
-uniform float pointSize;
-uniform vec4 vReflectivityColor;
-uniform vec3 vEmissiveColor;
-uniform float visibility;
-uniform vec4 vMetallicReflectanceFactors;
-uniform vec2 vMetallicReflectanceInfos;
-uniform mat4 metallicReflectanceMatrix;
-uniform vec2 vClearCoatParams;
-uniform vec4 vClearCoatRefractionParams;
-uniform vec4 vClearCoatInfos;
-uniform mat4 clearCoatMatrix;
-uniform mat4 clearCoatRoughnessMatrix;
-uniform vec2 vClearCoatBumpInfos;
-uniform vec2 vClearCoatTangentSpaceParams;
-uniform mat4 clearCoatBumpMatrix;
-uniform vec4 vClearCoatTintParams;
-uniform float clearCoatColorAtDistance;
-uniform vec2 vClearCoatTintInfos;
-uniform mat4 clearCoatTintMatrix;
-uniform vec3 vAnisotropy;
-uniform vec2 vAnisotropyInfos;
-uniform mat4 anisotropyMatrix;
-uniform vec4 vSheenColor;
-uniform float vSheenRoughness;
-uniform vec4 vSheenInfos;
-uniform mat4 sheenMatrix;
-uniform mat4 sheenRoughnessMatrix;
-uniform vec3 vRefractionMicrosurfaceInfos;
-uniform vec2 vRefractionFilteringInfo;
-uniform vec4 vRefractionInfos;
-uniform mat4 refractionMatrix;
-uniform vec2 vThicknessInfos;
-uniform mat4 thicknessMatrix;
-uniform vec2 vThicknessParam;
-uniform vec3 vDiffusionDistance;
-uniform vec4 vTintColor;
-uniform vec3 vSubSurfaceIntensity;
-uniform float scatteringDiffusionProfile;
-uniform vec4 vDetailInfos;
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-#endif
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-#endif
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-#define vAmbientUV vMainUV2
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-#ifdef REFLECTIVITY
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-#define vReflectivityUV vMainUV2
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-uniform sampler2D reflectivitySampler;
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-#ifdef MICROSURFACEMAP
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-uniform sampler2D microSurfaceSampler;
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-#ifdef METALLIC_REFLECTANCE
-#if METALLIC_REFLECTANCEDIRECTUV == 1
-#define vMetallicReflectanceUV vMainUV1
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-#define vMetallicReflectanceUV vMainUV2
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-#endif
-#ifdef CLEARCOAT
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-#if CLEARCOAT_TEXTUREDIRECTUV == 1
-#define vClearCoatUV vMainUV1
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-#define vClearCoatUV vMainUV2
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-#endif
-#endif
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-#define vClearCoatRoughnessUV vMainUV2
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-#endif
-#endif
-#ifdef CLEARCOAT_TEXTURE
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-#endif
-#ifdef CLEARCOAT_BUMP
-#if CLEARCOAT_BUMPDIRECTUV == 1
-#define vClearCoatBumpUV vMainUV1
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-#define vClearCoatBumpUV vMainUV2
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-#endif
-uniform sampler2D clearCoatBumpSampler;
-#endif
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-#define vClearCoatTintUV vMainUV1
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-#define vClearCoatTintUV vMainUV2
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-#define vSheenRoughnessUV vMainUV1
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-#ifdef USEIRRADIANCEMAP
-uniform samplerCube irradianceSampler;
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-#else
-#define sampleReflection(s,c) texture2D(s,c)
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-#ifdef LODBASEDMICROSFURACE
-#define sampleReflectionLod(s,c,l) texture2DLodEXT(s,c,l)
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-uniform sampler2D reflectionSamplerLow;
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-#endif
-#ifdef USEIRRADIANCEMAP
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-#endif
-#endif
-#ifdef REFLECTIONMAP_SKYBOX
-varying vec3 vPositionUVW;
-#else
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-varying vec3 vDirectionW;
-#endif
-#endif
-#endif
-#ifdef ENVIRONMENTBRDF
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-
-#ifdef SUBSURFACE
-#ifdef SS_REFRACTION
-#ifdef SS_REFRACTIONMAP_3D
-#define sampleRefraction(s,c) textureCube(s,c)
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-#ifdef LODBASEDMICROSFURACE
-#define sampleRefractionLod(s,c,l) textureCubeLodEXT(s,c,l)
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-#define sampleRefraction(s,c) texture2D(s,c)
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-#ifdef LODBASEDMICROSFURACE
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-#ifdef SS_THICKNESSANDMASK_TEXTURE
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-{
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-return square(roughness)+MINIMUMVARIANCE;
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-
-
-float reflectance90=saturate(reflectance0*25.0);
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-
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-
-vec2 getAnisotropicRoughness(float alphaG,float anisotropy) {
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-
-vec3 getAnisotropicBentNormals(const vec3 T,const vec3 B,const vec3 N,const vec3 V,float anisotropy) {
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-vec3 anisotropicFrameNormal=cross(anisotropicFrameTangent,anisotropicFrameDirection);
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-vec3 cocaLambert(float NdotVRefract,float NdotLRefract,vec3 alpha,float thickness) {
-return cocaLambert(alpha,(thickness*((NdotLRefract+NdotVRefract)/(NdotLRefract*NdotVRefract))));
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-
-vec3 computeColorAtDistanceInMedia(vec3 color,float distance) {
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-vec3 clearCoatAbsorption=mix(vec3(1.0),
-cocaLambert(NdotVRefract,NdotLRefract,clearCoatColor,clearCoatThickness),
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-#endif
-
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-#ifdef MICROSURFACEAUTOMATIC
-float computeDefaultMicroSurface(float microSurface,vec3 reflectivityColor)
-{
-const float kReflectivityNoAlphaWorkflow_SmoothnessMax=0.95;
-float reflectivityLuminance=getLuminance(reflectivityColor);
-float reflectivityLuma=sqrt(reflectivityLuminance);
-microSurface=reflectivityLuma*kReflectivityNoAlphaWorkflow_SmoothnessMax;
-return microSurface;
-}
-#endif`;ze.a.IncludesShadersStore.pbrHelperFunctions=wp;var Fp=`#ifdef USESPHERICALFROMREFLECTIONMAP
-#ifdef SPHERICAL_HARMONICS
-uniform vec3 vSphericalL00;
-uniform vec3 vSphericalL1_1;
-uniform vec3 vSphericalL10;
-uniform vec3 vSphericalL11;
-uniform vec3 vSphericalL2_2;
-uniform vec3 vSphericalL2_1;
-uniform vec3 vSphericalL20;
-uniform vec3 vSphericalL21;
-uniform vec3 vSphericalL22;
-
-
-
-
-
-
-
-vec3 computeEnvironmentIrradiance(vec3 normal) {
-return vSphericalL00
-+vSphericalL1_1*(normal.y)
-+vSphericalL10*(normal.z)
-+vSphericalL11*(normal.x)
-+vSphericalL2_2*(normal.y*normal.x)
-+vSphericalL2_1*(normal.y*normal.z)
-+vSphericalL20*((3.0*normal.z*normal.z)-1.0)
-+vSphericalL21*(normal.z*normal.x)
-+vSphericalL22*(normal.x*normal.x-(normal.y*normal.y));
-}
-#else
-uniform vec3 vSphericalX;
-uniform vec3 vSphericalY;
-uniform vec3 vSphericalZ;
-uniform vec3 vSphericalXX_ZZ;
-uniform vec3 vSphericalYY_ZZ;
-uniform vec3 vSphericalZZ;
-uniform vec3 vSphericalXY;
-uniform vec3 vSphericalYZ;
-uniform vec3 vSphericalZX;
-
-vec3 computeEnvironmentIrradiance(vec3 normal) {
-
-
-
-
-
-
-
-
-
-float Nx=normal.x;
-float Ny=normal.y;
-float Nz=normal.z;
-vec3 C1=vSphericalZZ.rgb;
-vec3 Cx=vSphericalX.rgb;
-vec3 Cy=vSphericalY.rgb;
-vec3 Cz=vSphericalZ.rgb;
-vec3 Cxx_zz=vSphericalXX_ZZ.rgb;
-vec3 Cyy_zz=vSphericalYY_ZZ.rgb;
-vec3 Cxy=vSphericalXY.rgb;
-vec3 Cyz=vSphericalYZ.rgb;
-vec3 Czx=vSphericalZX.rgb;
-vec3 a1=Cyy_zz*Ny+Cy;
-vec3 a2=Cyz*Nz+a1;
-vec3 b1=Czx*Nz+Cx;
-vec3 b2=Cxy*Ny+b1;
-vec3 b3=Cxx_zz*Nx+b2;
-vec3 t1=Cz*Nz+C1;
-vec3 t2=a2*Ny+t1;
-vec3 t3=b3*Nx+t2;
-return t3;
-}
-#endif
-#endif`;ze.a.IncludesShadersStore.harmonicsFunctions=Fp;var Bp=`
-struct preLightingInfo
-{
-
-vec3 lightOffset;
-float lightDistanceSquared;
-float lightDistance;
-
-float attenuation;
-
-vec3 L;
-vec3 H;
-float NdotV;
-float NdotLUnclamped;
-float NdotL;
-float VdotH;
-float roughness;
-};
-preLightingInfo computePointAndSpotPreLightingInfo(vec4 lightData,vec3 V,vec3 N) {
-preLightingInfo result;
-
-result.lightOffset=lightData.xyz-vPositionW;
-result.lightDistanceSquared=dot(result.lightOffset,result.lightOffset);
-
-result.lightDistance=sqrt(result.lightDistanceSquared);
-
-result.L=normalize(result.lightOffset);
-result.H=normalize(V+result.L);
-result.VdotH=saturate(dot(V,result.H));
-result.NdotLUnclamped=dot(N,result.L);
-result.NdotL=saturateEps(result.NdotLUnclamped);
-return result;
-}
-preLightingInfo computeDirectionalPreLightingInfo(vec4 lightData,vec3 V,vec3 N) {
-preLightingInfo result;
-
-result.lightDistance=length(-lightData.xyz);
-
-result.L=normalize(-lightData.xyz);
-result.H=normalize(V+result.L);
-result.VdotH=saturate(dot(V,result.H));
-result.NdotLUnclamped=dot(N,result.L);
-result.NdotL=saturateEps(result.NdotLUnclamped);
-return result;
-}
-preLightingInfo computeHemisphericPreLightingInfo(vec4 lightData,vec3 V,vec3 N) {
-preLightingInfo result;
-
-
-result.NdotL=dot(N,lightData.xyz)*0.5+0.5;
-result.NdotL=saturateEps(result.NdotL);
-result.NdotLUnclamped=result.NdotL;
-#ifdef SPECULARTERM
-result.L=normalize(lightData.xyz);
-result.H=normalize(V+result.L);
-result.VdotH=saturate(dot(V,result.H));
-#endif
-return result;
-}`;ze.a.IncludesShadersStore.pbrDirectLightingSetupFunctions=Bp;var Up=`float computeDistanceLightFalloff_Standard(vec3 lightOffset,float range)
-{
-return max(0.,1.0-length(lightOffset)/range);
-}
-float computeDistanceLightFalloff_Physical(float lightDistanceSquared)
-{
-return 1.0/maxEps(lightDistanceSquared);
-}
-float computeDistanceLightFalloff_GLTF(float lightDistanceSquared,float inverseSquaredRange)
-{
-float lightDistanceFalloff=1.0/maxEps(lightDistanceSquared);
-float factor=lightDistanceSquared*inverseSquaredRange;
-float attenuation=saturate(1.0-factor*factor);
-attenuation*=attenuation;
-
-lightDistanceFalloff*=attenuation;
-return lightDistanceFalloff;
-}
-float computeDistanceLightFalloff(vec3 lightOffset,float lightDistanceSquared,float range,float inverseSquaredRange)
-{
-#ifdef USEPHYSICALLIGHTFALLOFF
-return computeDistanceLightFalloff_Physical(lightDistanceSquared);
-#elif defined(USEGLTFLIGHTFALLOFF)
-return computeDistanceLightFalloff_GLTF(lightDistanceSquared,inverseSquaredRange);
-#else
-return computeDistanceLightFalloff_Standard(lightOffset,range);
-#endif
-}
-float computeDirectionalLightFalloff_Standard(vec3 lightDirection,vec3 directionToLightCenterW,float cosHalfAngle,float exponent)
-{
-float falloff=0.0;
-float cosAngle=maxEps(dot(-lightDirection,directionToLightCenterW));
-if (cosAngle>=cosHalfAngle)
-{
-falloff=max(0.,pow(cosAngle,exponent));
-}
-return falloff;
-}
-float computeDirectionalLightFalloff_Physical(vec3 lightDirection,vec3 directionToLightCenterW,float cosHalfAngle)
-{
-const float kMinusLog2ConeAngleIntensityRatio=6.64385618977;
-
-
-
-
-
-float concentrationKappa=kMinusLog2ConeAngleIntensityRatio/(1.0-cosHalfAngle);
-
-
-vec4 lightDirectionSpreadSG=vec4(-lightDirection*concentrationKappa,-concentrationKappa);
-float falloff=exp2(dot(vec4(directionToLightCenterW,1.0),lightDirectionSpreadSG));
-return falloff;
-}
-float computeDirectionalLightFalloff_GLTF(vec3 lightDirection,vec3 directionToLightCenterW,float lightAngleScale,float lightAngleOffset)
-{
-
-
-
-float cd=dot(-lightDirection,directionToLightCenterW);
-float falloff=saturate(cd*lightAngleScale+lightAngleOffset);
-
-falloff*=falloff;
-return falloff;
-}
-float computeDirectionalLightFalloff(vec3 lightDirection,vec3 directionToLightCenterW,float cosHalfAngle,float exponent,float lightAngleScale,float lightAngleOffset)
-{
-#ifdef USEPHYSICALLIGHTFALLOFF
-return computeDirectionalLightFalloff_Physical(lightDirection,directionToLightCenterW,cosHalfAngle);
-#elif defined(USEGLTFLIGHTFALLOFF)
-return computeDirectionalLightFalloff_GLTF(lightDirection,directionToLightCenterW,lightAngleScale,lightAngleOffset);
-#else
-return computeDirectionalLightFalloff_Standard(lightDirection,directionToLightCenterW,cosHalfAngle,exponent);
-#endif
-}`;ze.a.IncludesShadersStore.pbrDirectLightingFalloffFunctions=Up;var Vp=`
-#define FRESNEL_MAXIMUM_ON_ROUGH 0.25
-
-
-
-
-#ifdef MS_BRDF_ENERGY_CONSERVATION
-
-
-vec3 getEnergyConservationFactor(const vec3 specularEnvironmentR0,const vec3 environmentBrdf) {
-return 1.0+specularEnvironmentR0*(1.0/environmentBrdf.y-1.0);
-}
-#endif
-#ifdef ENVIRONMENTBRDF
-vec3 getBRDFLookup(float NdotV,float perceptualRoughness) {
-
-vec2 UV=vec2(NdotV,perceptualRoughness);
-
-vec4 brdfLookup=texture2D(environmentBrdfSampler,UV);
-#ifdef ENVIRONMENTBRDF_RGBD
-brdfLookup.rgb=fromRGBD(brdfLookup.rgba);
-#endif
-return brdfLookup.rgb;
-}
-vec3 getReflectanceFromBRDFLookup(const vec3 specularEnvironmentR0,const vec3 specularEnvironmentR90,const vec3 environmentBrdf) {
-#ifdef BRDF_V_HEIGHT_CORRELATED
-vec3 reflectance=(specularEnvironmentR90-specularEnvironmentR0)*environmentBrdf.x+specularEnvironmentR0*environmentBrdf.y;
-
-#else
-vec3 reflectance=specularEnvironmentR0*environmentBrdf.x+specularEnvironmentR90*environmentBrdf.y;
-#endif
-return reflectance;
-}
-vec3 getReflectanceFromBRDFLookup(const vec3 specularEnvironmentR0,const vec3 environmentBrdf) {
-#ifdef BRDF_V_HEIGHT_CORRELATED
-vec3 reflectance=mix(environmentBrdf.xxx,environmentBrdf.yyy,specularEnvironmentR0);
-#else
-vec3 reflectance=specularEnvironmentR0*environmentBrdf.x+environmentBrdf.y;
-#endif
-return reflectance;
-}
-#endif
-
-#if !defined(ENVIRONMENTBRDF) || defined(REFLECTIONMAP_SKYBOX) || defined(ALPHAFRESNEL)
-vec3 getReflectanceFromAnalyticalBRDFLookup_Jones(float VdotN,vec3 reflectance0,vec3 reflectance90,float smoothness)
-{
-
-float weight=mix(FRESNEL_MAXIMUM_ON_ROUGH,1.0,smoothness);
-return reflectance0+weight*(reflectance90-reflectance0)*pow5(saturate(1.0-VdotN));
-}
-#endif
-#if defined(SHEEN) && defined(ENVIRONMENTBRDF)
-
-vec3 getSheenReflectanceFromBRDFLookup(const vec3 reflectance0,const vec3 environmentBrdf) {
-vec3 sheenEnvironmentReflectance=reflectance0*environmentBrdf.b;
-return sheenEnvironmentReflectance;
-}
-#endif
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-vec3 fresnelSchlickGGX(float VdotH,vec3 reflectance0,vec3 reflectance90)
-{
-return reflectance0+(reflectance90-reflectance0)*pow5(1.0-VdotH);
-}
-float fresnelSchlickGGX(float VdotH,float reflectance0,float reflectance90)
-{
-return reflectance0+(reflectance90-reflectance0)*pow5(1.0-VdotH);
-}
-#ifdef CLEARCOAT
-
-
-
-
-
-vec3 getR0RemappedForClearCoat(vec3 f0) {
-#ifdef CLEARCOAT_DEFAULTIOR
-#ifdef MOBILE
-return saturate(f0*(f0*0.526868+0.529324)-0.0482256);
-#else
-return saturate(f0*(f0*(0.941892-0.263008*f0)+0.346479)-0.0285998);
-#endif
-#else
-vec3 s=sqrt(f0);
-vec3 t=(vClearCoatRefractionParams.z+vClearCoatRefractionParams.w*s)/(vClearCoatRefractionParams.w+vClearCoatRefractionParams.z*s);
-return t*t;
-#endif
-}
-#endif
-
-
-
-
-
-
-float normalDistributionFunction_TrowbridgeReitzGGX(float NdotH,float alphaG)
-{
-
-
-
-float a2=square(alphaG);
-float d=NdotH*NdotH*(a2-1.0)+1.0;
-return a2/(PI*d*d);
-}
-#ifdef SHEEN
-
-
-float normalDistributionFunction_CharlieSheen(float NdotH,float alphaG)
-{
-float invR=1./alphaG;
-float cos2h=NdotH*NdotH;
-float sin2h=1.-cos2h;
-return (2.+invR)*pow(sin2h,invR*.5)/(2.*PI);
-}
-#endif
-#ifdef ANISOTROPIC
-
-
-float normalDistributionFunction_BurleyGGX_Anisotropic(float NdotH,float TdotH,float BdotH,const vec2 alphaTB) {
-float a2=alphaTB.x*alphaTB.y;
-vec3 v=vec3(alphaTB.y*TdotH,alphaTB.x*BdotH,a2*NdotH);
-float v2=dot(v,v);
-float w2=a2/v2;
-return a2*w2*w2*RECIPROCAL_PI;
-}
-#endif
-
-
-
-
-#ifdef BRDF_V_HEIGHT_CORRELATED
-
-
-
-float smithVisibility_GGXCorrelated(float NdotL,float NdotV,float alphaG) {
-#ifdef MOBILE
-
-float GGXV=NdotL*(NdotV*(1.0-alphaG)+alphaG);
-float GGXL=NdotV*(NdotL*(1.0-alphaG)+alphaG);
-return 0.5/(GGXV+GGXL);
-#else
-float a2=alphaG*alphaG;
-float GGXV=NdotL*sqrt(NdotV*(NdotV-a2*NdotV)+a2);
-float GGXL=NdotV*sqrt(NdotL*(NdotL-a2*NdotL)+a2);
-return 0.5/(GGXV+GGXL);
-#endif
-}
-#else
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-float smithVisibilityG1_TrowbridgeReitzGGXFast(float dot,float alphaG)
-{
-#ifdef MOBILE
-
-return 1.0/(dot+alphaG+(1.0-alphaG)*dot ));
-#else
-float alphaSquared=alphaG*alphaG;
-return 1.0/(dot+sqrt(alphaSquared+(1.0-alphaSquared)*dot*dot));
-#endif
-}
-float smithVisibility_TrowbridgeReitzGGXFast(float NdotL,float NdotV,float alphaG)
-{
-float visibility=smithVisibilityG1_TrowbridgeReitzGGXFast(NdotL,alphaG)*smithVisibilityG1_TrowbridgeReitzGGXFast(NdotV,alphaG);
-
-return visibility;
-}
-#endif
-#ifdef ANISOTROPIC
-
-
-float smithVisibility_GGXCorrelated_Anisotropic(float NdotL,float NdotV,float TdotV,float BdotV,float TdotL,float BdotL,const vec2 alphaTB) {
-float lambdaV=NdotL*length(vec3(alphaTB.x*TdotV,alphaTB.y*BdotV,NdotV));
-float lambdaL=NdotV*length(vec3(alphaTB.x*TdotL,alphaTB.y*BdotL,NdotL));
-float v=0.5/(lambdaV+lambdaL);
-return v;
-}
-#endif
-#ifdef CLEARCOAT
-float visibility_Kelemen(float VdotH) {
-
-
-
-return 0.25/(VdotH*VdotH);
-}
-#endif
-#ifdef SHEEN
-
-
-
-float visibility_Ashikhmin(float NdotL,float NdotV)
-{
-return 1./(4.*(NdotL+NdotV-NdotL*NdotV));
-}
-
-#endif
-
-
-
-
-
-
-
-float diffuseBRDF_Burley(float NdotL,float NdotV,float VdotH,float roughness) {
-
-
-float diffuseFresnelNV=pow5(saturateEps(1.0-NdotL));
-float diffuseFresnelNL=pow5(saturateEps(1.0-NdotV));
-float diffuseFresnel90=0.5+2.0*VdotH*VdotH*roughness;
-float fresnel =
-(1.0+(diffuseFresnel90-1.0)*diffuseFresnelNL) *
-(1.0+(diffuseFresnel90-1.0)*diffuseFresnelNV);
-return fresnel/PI;
-}
-#ifdef SS_TRANSLUCENCY
-
-
-vec3 transmittanceBRDF_Burley(const vec3 tintColor,const vec3 diffusionDistance,float thickness) {
-vec3 S=1./maxEps(diffusionDistance);
-vec3 temp=exp((-0.333333333*thickness)*S);
-return tintColor.rgb*0.25*(temp*temp*temp+3.0*temp);
-}
-
-
-float computeWrappedDiffuseNdotL(float NdotL,float w) {
-float t=1.0+w;
-float invt2=1.0/square(t);
-return saturate((NdotL+w)*invt2);
-}
-#endif
-`;ze.a.IncludesShadersStore.pbrBRDFFunctions=Vp;var kp=`#ifdef NUM_SAMPLES
-#if NUM_SAMPLES>0
-#ifdef WEBGL2
-
-
-float radicalInverse_VdC(uint bits)
-{
-bits=(bits << 16u) | (bits >> 16u);
-bits=((bits & 0x55555555u) << 1u) | ((bits & 0xAAAAAAAAu) >> 1u);
-bits=((bits & 0x33333333u) << 2u) | ((bits & 0xCCCCCCCCu) >> 2u);
-bits=((bits & 0x0F0F0F0Fu) << 4u) | ((bits & 0xF0F0F0F0u) >> 4u);
-bits=((bits & 0x00FF00FFu) << 8u) | ((bits & 0xFF00FF00u) >> 8u);
-return float(bits)*2.3283064365386963e-10;
-}
-vec2 hammersley(uint i,uint N)
-{
-return vec2(float(i)/float(N),radicalInverse_VdC(i));
-}
-#else
-float vanDerCorpus(int n,int base)
-{
-float invBase=1.0/float(base);
-float denom=1.0;
-float result=0.0;
-for(int i=0; i<32; ++i)
-{
-if(n>0)
-{
-denom=mod(float(n),2.0);
-result+=denom*invBase;
-invBase=invBase/2.0;
-n=int(float(n)/2.0);
-}
-}
-return result;
-}
-vec2 hammersley(int i,int N)
-{
-return vec2(float(i)/float(N),vanDerCorpus(i,2));
-}
-#endif
-float log4(float x) {
-return log2(x)/2.;
-}
-const float NUM_SAMPLES_FLOAT=float(NUM_SAMPLES);
-const float NUM_SAMPLES_FLOAT_INVERSED=1./NUM_SAMPLES_FLOAT;
-const float K=4.;
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
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-
-
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-
-
-
-
-
-
-
-
-
-
-
-
-#define inline
-vec3 irradiance(samplerCube inputTexture,vec3 inputN,vec2 filteringInfo)
-{
-vec3 n=normalize(inputN);
-vec3 result=vec3(0.0);
-vec3 tangent=abs(n.z)<0.999 ? vec3(0.,0.,1.) : vec3(1.,0.,0.);
-tangent=normalize(cross(tangent,n));
-vec3 bitangent=cross(n,tangent);
-mat3 tbn=mat3(tangent,bitangent,n);
-float maxLevel=filteringInfo.y;
-float dim0=filteringInfo.x;
-float omegaP=(4.*PI)/(6.*dim0*dim0);
-#ifdef WEBGL2
-for(uint i=0u; i<NUM_SAMPLES; ++i)
-#else
-for(int i=0; i<NUM_SAMPLES; ++i)
-#endif
-{
-vec2 Xi=hammersley(i,NUM_SAMPLES);
-vec3 Ls=hemisphereCosSample(Xi);
-Ls=normalize(Ls);
-vec3 Ns=vec3(0.,0.,1.);
-float NoL=dot(Ns,Ls);
-if (NoL>0.) {
-float pdf_inversed=PI/NoL;
-float omegaS=NUM_SAMPLES_FLOAT_INVERSED*pdf_inversed;
-float l=log4(omegaS)-log4(omegaP)+log4(K);
-float mipLevel=clamp(l,0.0,maxLevel);
-vec3 c=textureCubeLodEXT(inputTexture,tbn*Ls,mipLevel).rgb;
-#ifdef GAMMA_INPUT
-c=toLinearSpace(c);
-#endif
-result+=c;
-}
-}
-result=result*NUM_SAMPLES_FLOAT_INVERSED;
-return result;
-}
-#define inline
-vec3 radiance(float alphaG,samplerCube inputTexture,vec3 inputN,vec2 filteringInfo)
-{
-vec3 n=normalize(inputN);
-if (alphaG == 0.) {
-vec3 c=textureCube(inputTexture,n).rgb;
-#ifdef GAMMA_INPUT
-c=toLinearSpace(c);
-#endif
-return c;
-}
-vec3 result=vec3(0.);
-vec3 tangent=abs(n.z)<0.999 ? vec3(0.,0.,1.) : vec3(1.,0.,0.);
-tangent=normalize(cross(tangent,n));
-vec3 bitangent=cross(n,tangent);
-mat3 tbn=mat3(tangent,bitangent,n);
-float maxLevel=filteringInfo.y;
-float dim0=filteringInfo.x;
-float omegaP=(4.*PI)/(6.*dim0*dim0);
-float weight=0.;
-#ifdef WEBGL2
-for(uint i=0u; i<NUM_SAMPLES; ++i)
-#else
-for(int i=0; i<NUM_SAMPLES; ++i)
-#endif
-{
-vec2 Xi=hammersley(i,NUM_SAMPLES);
-vec3 H=hemisphereImportanceSampleDggx(Xi,alphaG);
-float NoV=1.;
-float NoH=H.z;
-float NoH2=H.z*H.z;
-float NoL=2.*NoH2-1.;
-vec3 L=vec3(2.*NoH*H.x,2.*NoH*H.y,NoL);
-L=normalize(L);
-if (NoL>0.) {
-float pdf_inversed=4./normalDistributionFunction_TrowbridgeReitzGGX(NoH,alphaG);
-float omegaS=NUM_SAMPLES_FLOAT_INVERSED*pdf_inversed;
-float l=log4(omegaS)-log4(omegaP)+log4(K);
-float mipLevel=clamp(float(l),0.0,maxLevel);
-weight+=NoL;
-vec3 c=textureCubeLodEXT(inputTexture,tbn*L,mipLevel).rgb;
-#ifdef GAMMA_INPUT
-c=toLinearSpace(c);
-#endif
-result+=c*NoL;
-}
-}
-result=result/weight;
-return result;
-}
-#endif
-#endif`;ze.a.IncludesShadersStore.hdrFilteringFunctions=kp;var Gp=`#define CLEARCOATREFLECTANCE90 1.0
-
-struct lightingInfo
-{
-vec3 diffuse;
-#ifdef SPECULARTERM
-vec3 specular;
-#endif
-#ifdef CLEARCOAT
-
-
-vec4 clearCoat;
-#endif
-#ifdef SHEEN
-vec3 sheen;
-#endif
-};
-
-float adjustRoughnessFromLightProperties(float roughness,float lightRadius,float lightDistance) {
-#if defined(USEPHYSICALLIGHTFALLOFF) || defined(USEGLTFLIGHTFALLOFF)
-
-float lightRoughness=lightRadius/lightDistance;
-
-float totalRoughness=saturate(lightRoughness+roughness);
-return totalRoughness;
-#else
-return roughness;
-#endif
-}
-vec3 computeHemisphericDiffuseLighting(preLightingInfo info,vec3 lightColor,vec3 groundColor) {
-return mix(groundColor,lightColor,info.NdotL);
-}
-vec3 computeDiffuseLighting(preLightingInfo info,vec3 lightColor) {
-float diffuseTerm=diffuseBRDF_Burley(info.NdotL,info.NdotV,info.VdotH,info.roughness);
-return diffuseTerm*info.attenuation*info.NdotL*lightColor;
-}
-#define inline
-vec3 computeProjectionTextureDiffuseLighting(sampler2D projectionLightSampler,mat4 textureProjectionMatrix){
-vec4 strq=textureProjectionMatrix*vec4(vPositionW,1.0);
-strq/=strq.w;
-vec3 textureColor=texture2D(projectionLightSampler,strq.xy).rgb;
-return toLinearSpace(textureColor);
-}
-#ifdef SS_TRANSLUCENCY
-vec3 computeDiffuseAndTransmittedLighting(preLightingInfo info,vec3 lightColor,vec3 transmittance) {
-float NdotL=absEps(info.NdotLUnclamped);
-
-float wrapNdotL=computeWrappedDiffuseNdotL(NdotL,0.02);
-
-float trAdapt=step(0.,info.NdotLUnclamped);
-vec3 transmittanceNdotL=mix(transmittance*wrapNdotL,vec3(wrapNdotL),trAdapt);
-float diffuseTerm=diffuseBRDF_Burley(NdotL,info.NdotV,info.VdotH,info.roughness);
-return diffuseTerm*transmittanceNdotL*info.attenuation*lightColor;
-}
-#endif
-#ifdef SPECULARTERM
-vec3 computeSpecularLighting(preLightingInfo info,vec3 N,vec3 reflectance0,vec3 reflectance90,float geometricRoughnessFactor,vec3 lightColor) {
-float NdotH=saturateEps(dot(N,info.H));
-float roughness=max(info.roughness,geometricRoughnessFactor);
-float alphaG=convertRoughnessToAverageSlope(roughness);
-vec3 fresnel=fresnelSchlickGGX(info.VdotH,reflectance0,reflectance90);
-float distribution=normalDistributionFunction_TrowbridgeReitzGGX(NdotH,alphaG);
-#ifdef BRDF_V_HEIGHT_CORRELATED
-float smithVisibility=smithVisibility_GGXCorrelated(info.NdotL,info.NdotV,alphaG);
-#else
-float smithVisibility=smithVisibility_TrowbridgeReitzGGXFast(info.NdotL,info.NdotV,alphaG);
-#endif
-vec3 specTerm=fresnel*distribution*smithVisibility;
-return specTerm*info.attenuation*info.NdotL*lightColor;
-}
-#endif
-#ifdef ANISOTROPIC
-vec3 computeAnisotropicSpecularLighting(preLightingInfo info,vec3 V,vec3 N,vec3 T,vec3 B,float anisotropy,vec3 reflectance0,vec3 reflectance90,float geometricRoughnessFactor,vec3 lightColor) {
-float NdotH=saturateEps(dot(N,info.H));
-float TdotH=dot(T,info.H);
-float BdotH=dot(B,info.H);
-float TdotV=dot(T,V);
-float BdotV=dot(B,V);
-float TdotL=dot(T,info.L);
-float BdotL=dot(B,info.L);
-float alphaG=convertRoughnessToAverageSlope(info.roughness);
-vec2 alphaTB=getAnisotropicRoughness(alphaG,anisotropy);
-alphaTB=max(alphaTB,square(geometricRoughnessFactor));
-vec3 fresnel=fresnelSchlickGGX(info.VdotH,reflectance0,reflectance90);
-float distribution=normalDistributionFunction_BurleyGGX_Anisotropic(NdotH,TdotH,BdotH,alphaTB);
-float smithVisibility=smithVisibility_GGXCorrelated_Anisotropic(info.NdotL,info.NdotV,TdotV,BdotV,TdotL,BdotL,alphaTB);
-vec3 specTerm=fresnel*distribution*smithVisibility;
-return specTerm*info.attenuation*info.NdotL*lightColor;
-}
-#endif
-#ifdef CLEARCOAT
-vec4 computeClearCoatLighting(preLightingInfo info,vec3 Ncc,float geometricRoughnessFactor,float clearCoatIntensity,vec3 lightColor) {
-float NccdotL=saturateEps(dot(Ncc,info.L));
-float NccdotH=saturateEps(dot(Ncc,info.H));
-float clearCoatRoughness=max(info.roughness,geometricRoughnessFactor);
-float alphaG=convertRoughnessToAverageSlope(clearCoatRoughness);
-float fresnel=fresnelSchlickGGX(info.VdotH,vClearCoatRefractionParams.x,CLEARCOATREFLECTANCE90);
-fresnel*=clearCoatIntensity;
-float distribution=normalDistributionFunction_TrowbridgeReitzGGX(NccdotH,alphaG);
-float kelemenVisibility=visibility_Kelemen(info.VdotH);
-float clearCoatTerm=fresnel*distribution*kelemenVisibility;
-return vec4(
-clearCoatTerm*info.attenuation*NccdotL*lightColor,
-1.0-fresnel
-);
-}
-vec3 computeClearCoatLightingAbsorption(float NdotVRefract,vec3 L,vec3 Ncc,vec3 clearCoatColor,float clearCoatThickness,float clearCoatIntensity) {
-vec3 LRefract=-refract(L,Ncc,vClearCoatRefractionParams.y);
-float NdotLRefract=saturateEps(dot(Ncc,LRefract));
-vec3 absorption=computeClearCoatAbsorption(NdotVRefract,NdotLRefract,clearCoatColor,clearCoatThickness,clearCoatIntensity);
-return absorption;
-}
-#endif
-#ifdef SHEEN
-vec3 computeSheenLighting(preLightingInfo info,vec3 N,vec3 reflectance0,vec3 reflectance90,float geometricRoughnessFactor,vec3 lightColor) {
-float NdotH=saturateEps(dot(N,info.H));
-float roughness=max(info.roughness,geometricRoughnessFactor);
-float alphaG=convertRoughnessToAverageSlope(roughness);
-
-
-float fresnel=1.;
-float distribution=normalDistributionFunction_CharlieSheen(NdotH,alphaG);
-
-float visibility=visibility_Ashikhmin(info.NdotL,info.NdotV);
-
-float sheenTerm=fresnel*distribution*visibility;
-return sheenTerm*info.attenuation*info.NdotL*lightColor;
-}
-#endif
-`;ze.a.IncludesShadersStore.pbrDirectLightingFunctions=Gp;var zp=`#if defined(REFLECTION) || defined(SS_REFRACTION)
-float getLodFromAlphaG(float cubeMapDimensionPixels,float microsurfaceAverageSlope) {
-float microsurfaceAverageSlopeTexels=cubeMapDimensionPixels*microsurfaceAverageSlope;
-float lod=log2(microsurfaceAverageSlopeTexels);
-return lod;
-}
-float getLinearLodFromRoughness(float cubeMapDimensionPixels,float roughness) {
-float lod=log2(cubeMapDimensionPixels)*roughness;
-return lod;
-}
-#endif
-#if defined(ENVIRONMENTBRDF) && defined(RADIANCEOCCLUSION)
-float environmentRadianceOcclusion(float ambientOcclusion,float NdotVUnclamped) {
-
-
-float temp=NdotVUnclamped+ambientOcclusion;
-return saturate(square(temp)-1.0+ambientOcclusion);
-}
-#endif
-#if defined(ENVIRONMENTBRDF) && defined(HORIZONOCCLUSION)
-float environmentHorizonOcclusion(vec3 view,vec3 normal,vec3 geometricNormal) {
-
-vec3 reflection=reflect(view,normal);
-float temp=saturate(1.0+1.1*dot(reflection,geometricNormal));
-return square(temp);
-}
-#endif
-
-
-
-
-#if defined(LODINREFLECTIONALPHA) || defined(SS_LODINREFRACTIONALPHA)
-
-
-#define UNPACK_LOD(x) (1.0-x)*255.0
-float getLodFromAlphaG(float cubeMapDimensionPixels,float alphaG,float NdotV) {
-float microsurfaceAverageSlope=alphaG;
-
-
-
-
-
-
-microsurfaceAverageSlope*=sqrt(abs(NdotV));
-return getLodFromAlphaG(cubeMapDimensionPixels,microsurfaceAverageSlope);
-}
-#endif`;ze.a.IncludesShadersStore.pbrIBLFunctions=zp,f(132),f(133);var jp=`struct albedoOpacityOutParams
-{
-vec3 surfaceAlbedo;
-float alpha;
-};
-#define pbr_inline
-void albedoOpacityBlock(
-const in vec4 vAlbedoColor,
-#ifdef ALBEDO
-const in vec4 albedoTexture,
-const in vec2 albedoInfos,
-#endif
-#ifdef OPACITY
-const in vec4 opacityMap,
-const in vec2 vOpacityInfos,
-#endif
-#ifdef DETAIL
-const in vec4 detailColor,
-const in vec4 vDetailInfos,
-#endif
-out albedoOpacityOutParams outParams
-)
-{
-
-vec3 surfaceAlbedo=vAlbedoColor.rgb;
-float alpha=vAlbedoColor.a;
-#ifdef ALBEDO
-#if defined(ALPHAFROMALBEDO) || defined(ALPHATEST)
-alpha*=albedoTexture.a;
-#endif
-#ifdef GAMMAALBEDO
-surfaceAlbedo*=toLinearSpace(albedoTexture.rgb);
-#else
-surfaceAlbedo*=albedoTexture.rgb;
-#endif
-surfaceAlbedo*=albedoInfos.y;
-#endif
-#ifdef VERTEXCOLOR
-surfaceAlbedo*=vColor.rgb;
-#endif
-#ifdef DETAIL
-float detailAlbedo=2.0*mix(0.5,detailColor.r,vDetailInfos.y);
-surfaceAlbedo.rgb=surfaceAlbedo.rgb*detailAlbedo*detailAlbedo;
-#endif
-#define CUSTOM_FRAGMENT_UPDATE_ALBEDO
-
-#ifdef OPACITY
-#ifdef OPACITYRGB
-alpha=getLuminance(opacityMap.rgb);
-#else
-alpha*=opacityMap.a;
-#endif
-alpha*=vOpacityInfos.y;
-#endif
-#ifdef VERTEXALPHA
-alpha*=vColor.a;
-#endif
-#if !defined(SS_LINKREFRACTIONTOTRANSPARENCY) && !defined(ALPHAFRESNEL)
-#ifdef ALPHATEST
-if (alpha<ALPHATESTVALUE)
-discard;
-#ifndef ALPHABLEND
-
-alpha=1.0;
-#endif
-#endif
-#endif
-outParams.surfaceAlbedo=surfaceAlbedo;
-outParams.alpha=alpha;
-}
-`;ze.a.IncludesShadersStore.pbrBlockAlbedoOpacity=jp;var Hp=`struct reflectivityOutParams
-{
-float microSurface;
-float roughness;
-vec3 surfaceReflectivityColor;
-#ifdef METALLICWORKFLOW
-vec3 surfaceAlbedo;
-#endif
-#if defined(METALLICWORKFLOW) && defined(REFLECTIVITY) && defined(AOSTOREINMETALMAPRED)
-vec3 ambientOcclusionColor;
-#endif
-#if DEBUGMODE>0
-vec4 surfaceMetallicColorMap;
-vec4 surfaceReflectivityColorMap;
-vec2 metallicRoughness;
-vec3 metallicF0;
-#endif
-};
-#define pbr_inline
-void reflectivityBlock(
-const in vec4 vReflectivityColor,
-#ifdef METALLICWORKFLOW
-const in vec3 surfaceAlbedo,
-const in vec4 metallicReflectanceFactors,
-#endif
-#ifdef REFLECTIVITY
-const in vec3 reflectivityInfos,
-const in vec4 surfaceMetallicOrReflectivityColorMap,
-#endif
-#if defined(METALLICWORKFLOW) && defined(REFLECTIVITY) && defined(AOSTOREINMETALMAPRED)
-const in vec3 ambientOcclusionColorIn,
-#endif
-#ifdef MICROSURFACEMAP
-const in vec4 microSurfaceTexel,
-#endif
-#ifdef DETAIL
-const in vec4 detailColor,
-const in vec4 vDetailInfos,
-#endif
-out reflectivityOutParams outParams
-)
-{
-float microSurface=vReflectivityColor.a;
-vec3 surfaceReflectivityColor=vReflectivityColor.rgb;
-#ifdef METALLICWORKFLOW
-vec2 metallicRoughness=surfaceReflectivityColor.rg;
-#ifdef REFLECTIVITY
-#if DEBUGMODE>0
-outParams.surfaceMetallicColorMap=surfaceMetallicOrReflectivityColorMap;
-#endif
-#ifdef AOSTOREINMETALMAPRED
-vec3 aoStoreInMetalMap=vec3(surfaceMetallicOrReflectivityColorMap.r,surfaceMetallicOrReflectivityColorMap.r,surfaceMetallicOrReflectivityColorMap.r);
-outParams.ambientOcclusionColor=mix(ambientOcclusionColorIn,aoStoreInMetalMap,reflectivityInfos.z);
-#endif
-#ifdef METALLNESSSTOREINMETALMAPBLUE
-metallicRoughness.r*=surfaceMetallicOrReflectivityColorMap.b;
-#else
-metallicRoughness.r*=surfaceMetallicOrReflectivityColorMap.r;
-#endif
-#ifdef ROUGHNESSSTOREINMETALMAPALPHA
-metallicRoughness.g*=surfaceMetallicOrReflectivityColorMap.a;
-#else
-#ifdef ROUGHNESSSTOREINMETALMAPGREEN
-metallicRoughness.g*=surfaceMetallicOrReflectivityColorMap.g;
-#endif
-#endif
-#endif
-#ifdef DETAIL
-float detailRoughness=mix(0.5,detailColor.b,vDetailInfos.w);
-float loLerp=mix(0.,metallicRoughness.g,detailRoughness*2.);
-float hiLerp=mix(metallicRoughness.g,1.,(detailRoughness-0.5)*2.);
-metallicRoughness.g=mix(loLerp,hiLerp,step(detailRoughness,0.5));
-#endif
-#ifdef MICROSURFACEMAP
-metallicRoughness.g*=microSurfaceTexel.r;
-#endif
-#if DEBUGMODE>0
-outParams.metallicRoughness=metallicRoughness;
-#endif
-#define CUSTOM_FRAGMENT_UPDATE_METALLICROUGHNESS
-
-microSurface=1.0-metallicRoughness.g;
-
-vec3 baseColor=surfaceAlbedo;
-#ifdef FROSTBITE_REFLECTANCE
-
-
-
-
-
-
-outParams.surfaceAlbedo=baseColor.rgb*(1.0-metallicRoughness.r);
-
-surfaceReflectivityColor=mix(0.16*reflectance*reflectance,baseColor,metallicRoughness.r);
-#else
-vec3 metallicF0=metallicReflectanceFactors.rgb;
-#if DEBUGMODE>0
-outParams.metallicF0=metallicF0;
-#endif
-
-outParams.surfaceAlbedo=mix(baseColor.rgb*(1.0-metallicF0),vec3(0.,0.,0.),metallicRoughness.r);
-
-surfaceReflectivityColor=mix(metallicF0,baseColor,metallicRoughness.r);
-#endif
-#else
-#ifdef REFLECTIVITY
-surfaceReflectivityColor*=surfaceMetallicOrReflectivityColorMap.rgb;
-#if DEBUGMODE>0
-outParams.surfaceReflectivityColorMap=surfaceMetallicOrReflectivityColorMap;
-#endif
-#ifdef MICROSURFACEFROMREFLECTIVITYMAP
-microSurface*=surfaceMetallicOrReflectivityColorMap.a;
-microSurface*=reflectivityInfos.z;
-#else
-#ifdef MICROSURFACEAUTOMATIC
-microSurface*=computeDefaultMicroSurface(microSurface,surfaceReflectivityColor);
-#endif
-#ifdef MICROSURFACEMAP
-microSurface*=microSurfaceTexel.r;
-#endif
-#define CUSTOM_FRAGMENT_UPDATE_MICROSURFACE
-#endif
-#endif
-#endif
-
-microSurface=saturate(microSurface);
-
-float roughness=1.-microSurface;
-outParams.microSurface=microSurface;
-outParams.roughness=roughness;
-outParams.surfaceReflectivityColor=surfaceReflectivityColor;
-}
-`;ze.a.IncludesShadersStore.pbrBlockReflectivity=Hp;var Wp=`struct ambientOcclusionOutParams
-{
-vec3 ambientOcclusionColor;
-#if DEBUGMODE>0
-vec3 ambientOcclusionColorMap;
-#endif
-};
-#define pbr_inline
-void ambientOcclusionBlock(
-#ifdef AMBIENT
-const in vec3 ambientOcclusionColorMap_,
-const in vec4 vAmbientInfos,
-#endif
-out ambientOcclusionOutParams outParams
-)
-{
-vec3 ambientOcclusionColor=vec3(1.,1.,1.);
-#ifdef AMBIENT
-vec3 ambientOcclusionColorMap=ambientOcclusionColorMap_*vAmbientInfos.y;
-#ifdef AMBIENTINGRAYSCALE
-ambientOcclusionColorMap=vec3(ambientOcclusionColorMap.r,ambientOcclusionColorMap.r,ambientOcclusionColorMap.r);
-#endif
-ambientOcclusionColor=mix(ambientOcclusionColor,ambientOcclusionColorMap,vAmbientInfos.z);
-#if DEBUGMODE>0
-outParams.ambientOcclusionColorMap=ambientOcclusionColorMap;
-#endif
-#endif
-outParams.ambientOcclusionColor=ambientOcclusionColor;
-}
-`;ze.a.IncludesShadersStore.pbrBlockAmbientOcclusion=Wp;var Xp=`#ifdef ALPHAFRESNEL
-#if defined(ALPHATEST) || defined(ALPHABLEND)
-struct alphaFresnelOutParams
-{
-float alpha;
-};
-#define pbr_inline
-void alphaFresnelBlock(
-const in vec3 normalW,
-const in vec3 viewDirectionW,
-const in float alpha,
-const in float microSurface,
-out alphaFresnelOutParams outParams
-)
-{
-
-
-
-float opacityPerceptual=alpha;
-#ifdef LINEARALPHAFRESNEL
-float opacity0=opacityPerceptual;
-#else
-float opacity0=opacityPerceptual*opacityPerceptual;
-#endif
-float opacity90=fresnelGrazingReflectance(opacity0);
-vec3 normalForward=faceforward(normalW,-viewDirectionW,normalW);
-
-outParams.alpha=getReflectanceFromAnalyticalBRDFLookup_Jones(saturate(dot(viewDirectionW,normalForward)),vec3(opacity0),vec3(opacity90),sqrt(microSurface)).x;
-#ifdef ALPHATEST
-if (outParams.alpha<ALPHATESTVALUE)
-discard;
-#ifndef ALPHABLEND
-
-outParams.alpha=1.0;
-#endif
-#endif
-}
-#endif
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockAlphaFresnel=Xp;var Yp=`#ifdef ANISOTROPIC
-struct anisotropicOutParams
-{
-float anisotropy;
-vec3 anisotropicTangent;
-vec3 anisotropicBitangent;
-vec3 anisotropicNormal;
-#if DEBUGMODE>0
-vec3 anisotropyMapData;
-#endif
-};
-#define pbr_inline
-void anisotropicBlock(
-const in vec3 vAnisotropy,
-#ifdef ANISOTROPIC_TEXTURE
-const in vec3 anisotropyMapData,
-#endif
-const in mat3 TBN,
-const in vec3 normalW,
-const in vec3 viewDirectionW,
-out anisotropicOutParams outParams
-)
-{
-float anisotropy=vAnisotropy.b;
-vec3 anisotropyDirection=vec3(vAnisotropy.xy,0.);
-#ifdef ANISOTROPIC_TEXTURE
-anisotropy*=anisotropyMapData.b;
-anisotropyDirection.rg*=anisotropyMapData.rg*2.0-1.0;
-#if DEBUGMODE>0
-outParams.anisotropyMapData=anisotropyMapData;
-#endif
-#endif
-mat3 anisoTBN=mat3(normalize(TBN[0]),normalize(TBN[1]),normalize(TBN[2]));
-vec3 anisotropicTangent=normalize(anisoTBN*anisotropyDirection);
-vec3 anisotropicBitangent=normalize(cross(anisoTBN[2],anisotropicTangent));
-outParams.anisotropy=anisotropy;
-outParams.anisotropicTangent=anisotropicTangent;
-outParams.anisotropicBitangent=anisotropicBitangent;
-outParams.anisotropicNormal=getAnisotropicBentNormals(anisotropicTangent,anisotropicBitangent,normalW,viewDirectionW,anisotropy);
-}
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockAnisotropic=Yp;var Kp=`#ifdef REFLECTION
-struct reflectionOutParams
-{
-vec4 environmentRadiance;
-vec3 environmentIrradiance;
-#ifdef REFLECTIONMAP_3D
-vec3 reflectionCoords;
-#else
-vec2 reflectionCoords;
-#endif
-#ifdef SS_TRANSLUCENCY
-#ifdef USESPHERICALFROMREFLECTIONMAP
-#if !defined(NORMAL) || !defined(USESPHERICALINVERTEX)
-vec3 irradianceVector;
-#endif
-#endif
-#endif
-};
-#define pbr_inline
-void createReflectionCoords(
-const in vec3 vPositionW,
-const in vec3 normalW,
-#ifdef ANISOTROPIC
-const in anisotropicOutParams anisotropicOut,
-#endif
-#ifdef REFLECTIONMAP_3D
-out vec3 reflectionCoords
-#else
-out vec2 reflectionCoords
-#endif
-)
-{
-#ifdef ANISOTROPIC
-vec3 reflectionVector=computeReflectionCoords(vec4(vPositionW,1.0),anisotropicOut.anisotropicNormal);
-#else
-vec3 reflectionVector=computeReflectionCoords(vec4(vPositionW,1.0),normalW);
-#endif
-#ifdef REFLECTIONMAP_OPPOSITEZ
-reflectionVector.z*=-1.0;
-#endif
-
-#ifdef REFLECTIONMAP_3D
-reflectionCoords=reflectionVector;
-#else
-reflectionCoords=reflectionVector.xy;
-#ifdef REFLECTIONMAP_PROJECTION
-reflectionCoords/=reflectionVector.z;
-#endif
-reflectionCoords.y=1.0-reflectionCoords.y;
-#endif
-}
-#define pbr_inline
-#define inline
-void sampleReflectionTexture(
-const in float alphaG,
-const in vec3 vReflectionMicrosurfaceInfos,
-const in vec2 vReflectionInfos,
-const in vec3 vReflectionColor,
-#if defined(LODINREFLECTIONALPHA) && !defined(REFLECTIONMAP_SKYBOX)
-const in float NdotVUnclamped,
-#endif
-#ifdef LINEARSPECULARREFLECTION
-const in float roughness,
-#endif
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSampler,
-const vec3 reflectionCoords,
-#else
-const in sampler2D reflectionSampler,
-const vec2 reflectionCoords,
-#endif
-#ifndef LODBASEDMICROSFURACE
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSamplerLow,
-const in samplerCube reflectionSamplerHigh,
-#else
-const in sampler2D reflectionSamplerLow,
-const in sampler2D reflectionSamplerHigh,
-#endif
-#endif
-#ifdef REALTIME_FILTERING
-const in vec2 vReflectionFilteringInfo,
-#endif
-out vec4 environmentRadiance
-)
-{
-
-#if defined(LODINREFLECTIONALPHA) && !defined(REFLECTIONMAP_SKYBOX)
-float reflectionLOD=getLodFromAlphaG(vReflectionMicrosurfaceInfos.x,alphaG,NdotVUnclamped);
-#elif defined(LINEARSPECULARREFLECTION)
-float reflectionLOD=getLinearLodFromRoughness(vReflectionMicrosurfaceInfos.x,roughness);
-#else
-float reflectionLOD=getLodFromAlphaG(vReflectionMicrosurfaceInfos.x,alphaG);
-#endif
-#ifdef LODBASEDMICROSFURACE
-
-reflectionLOD=reflectionLOD*vReflectionMicrosurfaceInfos.y+vReflectionMicrosurfaceInfos.z;
-#ifdef LODINREFLECTIONALPHA
-
-
-
-
-
-
-
-
-
-float automaticReflectionLOD=UNPACK_LOD(sampleReflection(reflectionSampler,reflectionCoords).a);
-float requestedReflectionLOD=max(automaticReflectionLOD,reflectionLOD);
-#else
-float requestedReflectionLOD=reflectionLOD;
-#endif
-#ifdef REALTIME_FILTERING
-environmentRadiance=vec4(radiance(alphaG,reflectionSampler,reflectionCoords,vReflectionFilteringInfo),1.0);
-#else
-environmentRadiance=sampleReflectionLod(reflectionSampler,reflectionCoords,reflectionLOD);
-#endif
-#else
-float lodReflectionNormalized=saturate(reflectionLOD/log2(vReflectionMicrosurfaceInfos.x));
-float lodReflectionNormalizedDoubled=lodReflectionNormalized*2.0;
-vec4 environmentMid=sampleReflection(reflectionSampler,reflectionCoords);
-if (lodReflectionNormalizedDoubled<1.0){
-environmentRadiance=mix(
-sampleReflection(reflectionSamplerHigh,reflectionCoords),
-environmentMid,
-lodReflectionNormalizedDoubled
-);
-} else {
-environmentRadiance=mix(
-environmentMid,
-sampleReflection(reflectionSamplerLow,reflectionCoords),
-lodReflectionNormalizedDoubled-1.0
-);
-}
-#endif
-#ifdef RGBDREFLECTION
-environmentRadiance.rgb=fromRGBD(environmentRadiance);
-#endif
-#ifdef GAMMAREFLECTION
-environmentRadiance.rgb=toLinearSpace(environmentRadiance.rgb);
-#endif
-
-environmentRadiance.rgb*=vReflectionInfos.x;
-environmentRadiance.rgb*=vReflectionColor.rgb;
-}
-#define pbr_inline
-#define inline
-void reflectionBlock(
-const in vec3 vPositionW,
-const in vec3 normalW,
-const in float alphaG,
-const in vec3 vReflectionMicrosurfaceInfos,
-const in vec2 vReflectionInfos,
-const in vec3 vReflectionColor,
-#ifdef ANISOTROPIC
-const in anisotropicOutParams anisotropicOut,
-#endif
-#if defined(LODINREFLECTIONALPHA) && !defined(REFLECTIONMAP_SKYBOX)
-const in float NdotVUnclamped,
-#endif
-#ifdef LINEARSPECULARREFLECTION
-const in float roughness,
-#endif
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSampler,
-#else
-const in sampler2D reflectionSampler,
-#endif
-#if defined(NORMAL) && defined(USESPHERICALINVERTEX)
-const in vec3 vEnvironmentIrradiance,
-#endif
-#ifdef USESPHERICALFROMREFLECTIONMAP
-#if !defined(NORMAL) || !defined(USESPHERICALINVERTEX)
-const in mat4 reflectionMatrix,
-#endif
-#endif
-#ifdef USEIRRADIANCEMAP
-#ifdef REFLECTIONMAP_3D
-const in samplerCube irradianceSampler,
-#else
-const in sampler2D irradianceSampler,
-#endif
-#endif
-#ifndef LODBASEDMICROSFURACE
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSamplerLow,
-const in samplerCube reflectionSamplerHigh,
-#else
-const in sampler2D reflectionSamplerLow,
-const in sampler2D reflectionSamplerHigh,
-#endif
-#endif
-#ifdef REALTIME_FILTERING
-const in vec2 vReflectionFilteringInfo,
-#endif
-out reflectionOutParams outParams
-)
-{
-
-vec4 environmentRadiance=vec4(0.,0.,0.,0.);
-#ifdef REFLECTIONMAP_3D
-vec3 reflectionCoords=vec3(0.);
-#else
-vec2 reflectionCoords=vec2(0.);
-#endif
-createReflectionCoords(
-vPositionW,
-normalW,
-#ifdef ANISOTROPIC
-anisotropicOut,
-#endif
-reflectionCoords
-);
-sampleReflectionTexture(
-alphaG,
-vReflectionMicrosurfaceInfos,
-vReflectionInfos,
-vReflectionColor,
-#if defined(LODINREFLECTIONALPHA) && !defined(REFLECTIONMAP_SKYBOX)
-NdotVUnclamped,
-#endif
-#ifdef LINEARSPECULARREFLECTION
-roughness,
-#endif
-#ifdef REFLECTIONMAP_3D
-reflectionSampler,
-reflectionCoords,
-#else
-reflectionSampler,
-reflectionCoords,
-#endif
-#ifndef LODBASEDMICROSFURACE
-reflectionSamplerLow,
-reflectionSamplerHigh,
-#endif
-#ifdef REALTIME_FILTERING
-vReflectionFilteringInfo,
-#endif
-environmentRadiance
-);
-
-vec3 environmentIrradiance=vec3(0.,0.,0.);
-#ifdef USESPHERICALFROMREFLECTIONMAP
-#if defined(NORMAL) && defined(USESPHERICALINVERTEX)
-environmentIrradiance=vEnvironmentIrradiance;
-#else
-#ifdef ANISOTROPIC
-vec3 irradianceVector=vec3(reflectionMatrix*vec4(anisotropicOut.anisotropicNormal,0)).xyz;
-#else
-vec3 irradianceVector=vec3(reflectionMatrix*vec4(normalW,0)).xyz;
-#endif
-#ifdef REFLECTIONMAP_OPPOSITEZ
-irradianceVector.z*=-1.0;
-#endif
-#ifdef INVERTCUBICMAP
-irradianceVector.y*=-1.0;
-#endif
-#if defined(REALTIME_FILTERING)
-environmentIrradiance=irradiance(reflectionSampler,irradianceVector,vReflectionFilteringInfo);
-#else
-environmentIrradiance=computeEnvironmentIrradiance(irradianceVector);
-#endif
-#ifdef SS_TRANSLUCENCY
-outParams.irradianceVector=irradianceVector;
-#endif
-#endif
-#elif defined(USEIRRADIANCEMAP)
-vec4 environmentIrradiance4=sampleReflection(irradianceSampler,reflectionCoords);
-environmentIrradiance=environmentIrradiance4.rgb;
-#ifdef RGBDREFLECTION
-environmentIrradiance.rgb=fromRGBD(environmentIrradiance4);
-#endif
-#ifdef GAMMAREFLECTION
-environmentIrradiance.rgb=toLinearSpace(environmentIrradiance.rgb);
-#endif
-#endif
-environmentIrradiance*=vReflectionColor.rgb;
-outParams.environmentRadiance=environmentRadiance;
-outParams.environmentIrradiance=environmentIrradiance;
-outParams.reflectionCoords=reflectionCoords;
-}
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockReflection=Kp;var Qp=`#ifdef SHEEN
-struct sheenOutParams
-{
-float sheenIntensity;
-vec3 sheenColor;
-float sheenRoughness;
-#ifdef SHEEN_LINKWITHALBEDO
-vec3 surfaceAlbedo;
-#endif
-#if defined(ENVIRONMENTBRDF) && defined(SHEEN_ALBEDOSCALING)
-float sheenAlbedoScaling;
-#endif
-#if defined(REFLECTION) && defined(ENVIRONMENTBRDF)
-vec3 finalSheenRadianceScaled;
-#endif
-#if DEBUGMODE>0
-vec4 sheenMapData;
-vec3 sheenEnvironmentReflectance;
-#endif
-};
-#define pbr_inline
-#define inline
-void sheenBlock(
-const in vec4 vSheenColor,
-#ifdef SHEEN_ROUGHNESS
-const in float vSheenRoughness,
-#if defined(SHEEN_TEXTURE_ROUGHNESS) && !defined(SHEEN_TEXTURE_ROUGHNESS_IDENTICAL) && !defined(SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE)
-const in vec4 sheenMapRoughnessData,
-#endif
-#endif
-const in float roughness,
-#ifdef SHEEN_TEXTURE
-const in vec4 sheenMapData,
-#endif
-const in float reflectance,
-#ifdef SHEEN_LINKWITHALBEDO
-const in vec3 baseColor,
-const in vec3 surfaceAlbedo,
-#endif
-#ifdef ENVIRONMENTBRDF
-const in float NdotV,
-const in vec3 environmentBrdf,
-#endif
-#if defined(REFLECTION) && defined(ENVIRONMENTBRDF)
-const in vec2 AARoughnessFactors,
-const in vec3 vReflectionMicrosurfaceInfos,
-const in vec2 vReflectionInfos,
-const in vec3 vReflectionColor,
-const in vec4 vLightingIntensity,
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSampler,
-const in vec3 reflectionCoords,
-#else
-const in sampler2D reflectionSampler,
-const in vec2 reflectionCoords,
-#endif
-const in float NdotVUnclamped,
-#ifndef LODBASEDMICROSFURACE
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSamplerLow,
-const in samplerCube reflectionSamplerHigh,
-#else
-const in sampler2D reflectionSamplerLow,
-const in sampler2D reflectionSamplerHigh,
-#endif
-#endif
-#ifdef REALTIME_FILTERING
-const in vec2 vReflectionFilteringInfo,
-#endif
-#if !defined(REFLECTIONMAP_SKYBOX) && defined(RADIANCEOCCLUSION)
-const in float seo,
-#endif
-#if !defined(REFLECTIONMAP_SKYBOX) && defined(HORIZONOCCLUSION) && defined(BUMP) && defined(REFLECTIONMAP_3D)
-const in float eho,
-#endif
-#endif
-out sheenOutParams outParams
-)
-{
-float sheenIntensity=vSheenColor.a;
-#ifdef SHEEN_TEXTURE
-#if DEBUGMODE>0
-outParams.sheenMapData=sheenMapData;
-#endif
-#endif
-#ifdef SHEEN_LINKWITHALBEDO
-float sheenFactor=pow5(1.0-sheenIntensity);
-vec3 sheenColor=baseColor.rgb*(1.0-sheenFactor);
-float sheenRoughness=sheenIntensity;
-outParams.surfaceAlbedo=surfaceAlbedo*sheenFactor;
-#ifdef SHEEN_TEXTURE
-sheenIntensity*=sheenMapData.a;
-#endif
-#else
-vec3 sheenColor=vSheenColor.rgb;
-#ifdef SHEEN_TEXTURE
-sheenColor.rgb*=sheenMapData.rgb;
-#endif
-#ifdef SHEEN_ROUGHNESS
-float sheenRoughness=vSheenRoughness;
-#ifdef SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE
-#if defined(SHEEN_TEXTURE)
-sheenRoughness*=sheenMapData.a;
-#endif
-#elif defined(SHEEN_TEXTURE_ROUGHNESS)
-#ifdef SHEEN_TEXTURE_ROUGHNESS_IDENTICAL
-sheenRoughness*=sheenMapData.a;
-#else
-sheenRoughness*=sheenMapRoughnessData.a;
-#endif
-#endif
-#else
-float sheenRoughness=roughness;
-#ifdef SHEEN_TEXTURE
-sheenIntensity*=sheenMapData.a;
-#endif
-#endif
-
-#if !defined(SHEEN_ALBEDOSCALING)
-sheenIntensity*=(1.-reflectance);
-#endif
-
-sheenColor*=sheenIntensity;
-#endif
-
-#ifdef ENVIRONMENTBRDF
-
-#ifdef SHEEN_ROUGHNESS
-vec3 environmentSheenBrdf=getBRDFLookup(NdotV,sheenRoughness);
-#else
-vec3 environmentSheenBrdf=environmentBrdf;
-#endif
-
-#endif
-#if defined(REFLECTION) && defined(ENVIRONMENTBRDF)
-float sheenAlphaG=convertRoughnessToAverageSlope(sheenRoughness);
-#ifdef SPECULARAA
-
-sheenAlphaG+=AARoughnessFactors.y;
-#endif
-vec4 environmentSheenRadiance=vec4(0.,0.,0.,0.);
-sampleReflectionTexture(
-sheenAlphaG,
-vReflectionMicrosurfaceInfos,
-vReflectionInfos,
-vReflectionColor,
-#if defined(LODINREFLECTIONALPHA) && !defined(REFLECTIONMAP_SKYBOX)
-NdotVUnclamped,
-#endif
-#ifdef LINEARSPECULARREFLECTION
-sheenRoughness,
-#endif
-reflectionSampler,
-reflectionCoords,
-#ifndef LODBASEDMICROSFURACE
-reflectionSamplerLow,
-reflectionSamplerHigh,
-#endif
-#ifdef REALTIME_FILTERING
-vReflectionFilteringInfo,
-#endif
-environmentSheenRadiance
-);
-vec3 sheenEnvironmentReflectance=getSheenReflectanceFromBRDFLookup(sheenColor,environmentSheenBrdf);
-#if !defined(REFLECTIONMAP_SKYBOX) && defined(RADIANCEOCCLUSION)
-sheenEnvironmentReflectance*=seo;
-#endif
-#if !defined(REFLECTIONMAP_SKYBOX) && defined(HORIZONOCCLUSION) && defined(BUMP) && defined(REFLECTIONMAP_3D)
-sheenEnvironmentReflectance*=eho;
-#endif
-#if DEBUGMODE>0
-outParams.sheenEnvironmentReflectance=sheenEnvironmentReflectance;
-#endif
-outParams.finalSheenRadianceScaled=
-environmentSheenRadiance.rgb *
-sheenEnvironmentReflectance *
-vLightingIntensity.z;
-
-
-
-
-
-#endif
-#if defined(ENVIRONMENTBRDF) && defined(SHEEN_ALBEDOSCALING)
-
-
-
-outParams.sheenAlbedoScaling=1.0-sheenIntensity*max(max(sheenColor.r,sheenColor.g),sheenColor.b)*environmentSheenBrdf.b;
-#endif
-
-outParams.sheenIntensity=sheenIntensity;
-outParams.sheenColor=sheenColor;
-outParams.sheenRoughness=sheenRoughness;
-}
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockSheen=Qp;var qp=`struct clearcoatOutParams
-{
-vec3 specularEnvironmentR0;
-float conservationFactor;
-vec3 clearCoatNormalW;
-vec2 clearCoatAARoughnessFactors;
-float clearCoatIntensity;
-float clearCoatRoughness;
-#ifdef REFLECTION
-vec3 finalClearCoatRadianceScaled;
-#endif
-#ifdef CLEARCOAT_TINT
-vec3 absorption;
-float clearCoatNdotVRefract;
-vec3 clearCoatColor;
-float clearCoatThickness;
-#endif
-#if defined(ENVIRONMENTBRDF) && defined(MS_BRDF_ENERGY_CONSERVATION)
-vec3 energyConservationFactorClearCoat;
-#endif
-#if DEBUGMODE>0
-mat3 TBNClearCoat;
-vec2 clearCoatMapData;
-vec4 clearCoatTintMapData;
-vec4 environmentClearCoatRadiance;
-float clearCoatNdotV;
-vec3 clearCoatEnvironmentReflectance;
-#endif
-};
-#ifdef CLEARCOAT
-#define pbr_inline
-#define inline
-void clearcoatBlock(
-const in vec3 vPositionW,
-const in vec3 geometricNormalW,
-const in vec3 viewDirectionW,
-const in vec2 vClearCoatParams,
-#if defined(CLEARCOAT_TEXTURE_ROUGHNESS) && !defined(CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL) && !defined(CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE)
-const in vec4 clearCoatMapRoughnessData,
-#endif
-const in vec3 specularEnvironmentR0,
-#ifdef CLEARCOAT_TEXTURE
-const in vec2 clearCoatMapData,
-#endif
-#ifdef CLEARCOAT_TINT
-const in vec4 vClearCoatTintParams,
-const in float clearCoatColorAtDistance,
-const in vec4 vClearCoatRefractionParams,
-#ifdef CLEARCOAT_TINT_TEXTURE
-const in vec4 clearCoatTintMapData,
-#endif
-#endif
-#ifdef CLEARCOAT_BUMP
-const in vec2 vClearCoatBumpInfos,
-const in vec4 clearCoatBumpMapData,
-const in vec2 vClearCoatBumpUV,
-#if defined(TANGENT) && defined(NORMAL)
-const in mat3 vTBN,
-#else
-const in vec2 vClearCoatTangentSpaceParams,
-#endif
-#ifdef OBJECTSPACE_NORMALMAP
-const in mat4 normalMatrix,
-#endif
-#endif
-#if defined(FORCENORMALFORWARD) && defined(NORMAL)
-const in vec3 faceNormal,
-#endif
-#ifdef REFLECTION
-const in vec3 vReflectionMicrosurfaceInfos,
-const in vec2 vReflectionInfos,
-const in vec3 vReflectionColor,
-const in vec4 vLightingIntensity,
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSampler,
-#else
-const in sampler2D reflectionSampler,
-#endif
-#ifndef LODBASEDMICROSFURACE
-#ifdef REFLECTIONMAP_3D
-const in samplerCube reflectionSamplerLow,
-const in samplerCube reflectionSamplerHigh,
-#else
-const in sampler2D reflectionSamplerLow,
-const in sampler2D reflectionSamplerHigh,
-#endif
-#endif
-#ifdef REALTIME_FILTERING
-const in vec2 vReflectionFilteringInfo,
-#endif
-#endif
-#if defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-#ifdef RADIANCEOCCLUSION
-const in float ambientMonochrome,
-#endif
-#endif
-out clearcoatOutParams outParams
-)
-{
-
-float clearCoatIntensity=vClearCoatParams.x;
-float clearCoatRoughness=vClearCoatParams.y;
-#ifdef CLEARCOAT_TEXTURE
-clearCoatIntensity*=clearCoatMapData.x;
-#ifdef CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE
-clearCoatRoughness*=clearCoatMapData.y;
-#endif
-#if DEBUGMODE>0
-outParams.clearCoatMapData=clearCoatMapData;
-#endif
-#endif
-#if defined(CLEARCOAT_TEXTURE_ROUGHNESS) && !defined(CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE)
-#ifdef CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL
-clearCoatRoughness*=clearCoatMapData.y;
-#else
-clearCoatRoughness*=clearCoatMapRoughnessData.y;
-#endif
-#endif
-outParams.clearCoatIntensity=clearCoatIntensity;
-outParams.clearCoatRoughness=clearCoatRoughness;
-#ifdef CLEARCOAT_TINT
-vec3 clearCoatColor=vClearCoatTintParams.rgb;
-float clearCoatThickness=vClearCoatTintParams.a;
-#ifdef CLEARCOAT_TINT_TEXTURE
-clearCoatColor*=clearCoatTintMapData.rgb;
-clearCoatThickness*=clearCoatTintMapData.a;
-#if DEBUGMODE>0
-outParams.clearCoatTintMapData=clearCoatTintMapData;
-#endif
-#endif
-outParams.clearCoatColor=computeColorAtDistanceInMedia(clearCoatColor,clearCoatColorAtDistance);
-outParams.clearCoatThickness=clearCoatThickness;
-#endif
-
-
-
-
-#ifdef CLEARCOAT_REMAP_F0
-vec3 specularEnvironmentR0Updated=getR0RemappedForClearCoat(specularEnvironmentR0);
-#else
-vec3 specularEnvironmentR0Updated=specularEnvironmentR0;
-#endif
-outParams.specularEnvironmentR0=mix(specularEnvironmentR0,specularEnvironmentR0Updated,clearCoatIntensity);
-
-vec3 clearCoatNormalW=geometricNormalW;
-#ifdef CLEARCOAT_BUMP
-#ifdef NORMALXYSCALE
-float clearCoatNormalScale=1.0;
-#else
-float clearCoatNormalScale=vClearCoatBumpInfos.y;
-#endif
-#if defined(TANGENT) && defined(NORMAL)
-mat3 TBNClearCoat=vTBN;
-#else
-mat3 TBNClearCoat=cotangent_frame(clearCoatNormalW*clearCoatNormalScale,vPositionW,vClearCoatBumpUV,vClearCoatTangentSpaceParams);
-#endif
-#if DEBUGMODE>0
-outParams.TBNClearCoat=TBNClearCoat;
-#endif
-#ifdef OBJECTSPACE_NORMALMAP
-clearCoatNormalW=normalize(clearCoatBumpMapData.xyz*2.0-1.0);
-clearCoatNormalW=normalize(mat3(normalMatrix)*clearCoatNormalW);
-#else
-clearCoatNormalW=perturbNormal(TBNClearCoat,clearCoatBumpMapData.xyz,vClearCoatBumpInfos.y);
-#endif
-#endif
-#if defined(FORCENORMALFORWARD) && defined(NORMAL)
-clearCoatNormalW*=sign(dot(clearCoatNormalW,faceNormal));
-#endif
-#if defined(TWOSIDEDLIGHTING) && defined(NORMAL)
-clearCoatNormalW=gl_FrontFacing ? clearCoatNormalW : -clearCoatNormalW;
-#endif
-outParams.clearCoatNormalW=clearCoatNormalW;
-
-outParams.clearCoatAARoughnessFactors=getAARoughnessFactors(clearCoatNormalW.xyz);
-
-float clearCoatNdotVUnclamped=dot(clearCoatNormalW,viewDirectionW);
-
-float clearCoatNdotV=absEps(clearCoatNdotVUnclamped);
-#if DEBUGMODE>0
-outParams.clearCoatNdotV=clearCoatNdotV;
-#endif
-#ifdef CLEARCOAT_TINT
-
-vec3 clearCoatVRefract=-refract(vPositionW,clearCoatNormalW,vClearCoatRefractionParams.y);
-
-outParams.clearCoatNdotVRefract=absEps(dot(clearCoatNormalW,clearCoatVRefract));
-#endif
-#if defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-
-vec3 environmentClearCoatBrdf=getBRDFLookup(clearCoatNdotV,clearCoatRoughness);
-#endif
-
-#if defined(REFLECTION)
-float clearCoatAlphaG=convertRoughnessToAverageSlope(clearCoatRoughness);
-#ifdef SPECULARAA
-
-clearCoatAlphaG+=outParams.clearCoatAARoughnessFactors.y;
-#endif
-vec4 environmentClearCoatRadiance=vec4(0.,0.,0.,0.);
-vec3 clearCoatReflectionVector=computeReflectionCoords(vec4(vPositionW,1.0),clearCoatNormalW);
-#ifdef REFLECTIONMAP_OPPOSITEZ
-clearCoatReflectionVector.z*=-1.0;
-#endif
-
-#ifdef REFLECTIONMAP_3D
-vec3 clearCoatReflectionCoords=clearCoatReflectionVector;
-#else
-vec2 clearCoatReflectionCoords=clearCoatReflectionVector.xy;
-#ifdef REFLECTIONMAP_PROJECTION
-clearCoatReflectionCoords/=clearCoatReflectionVector.z;
-#endif
-clearCoatReflectionCoords.y=1.0-clearCoatReflectionCoords.y;
-#endif
-sampleReflectionTexture(
-clearCoatAlphaG,
-vReflectionMicrosurfaceInfos,
-vReflectionInfos,
-vReflectionColor,
-#if defined(LODINREFLECTIONALPHA) && !defined(REFLECTIONMAP_SKYBOX)
-clearCoatNdotVUnclamped,
-#endif
-#ifdef LINEARSPECULARREFLECTION
-clearCoatRoughness,
-#endif
-reflectionSampler,
-clearCoatReflectionCoords,
-#ifndef LODBASEDMICROSFURACE
-reflectionSamplerLow,
-reflectionSamplerHigh,
-#endif
-#ifdef REALTIME_FILTERING
-vReflectionFilteringInfo,
-#endif
-environmentClearCoatRadiance
-);
-#if DEBUGMODE>0
-outParams.environmentClearCoatRadiance=environmentClearCoatRadiance;
-#endif
-
-#if defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-vec3 clearCoatEnvironmentReflectance=getReflectanceFromBRDFLookup(vec3(vClearCoatRefractionParams.x),environmentClearCoatBrdf);
-#ifdef RADIANCEOCCLUSION
-float clearCoatSeo=environmentRadianceOcclusion(ambientMonochrome,clearCoatNdotVUnclamped);
-clearCoatEnvironmentReflectance*=clearCoatSeo;
-#endif
-#ifdef HORIZONOCCLUSION
-#ifdef BUMP
-#ifdef REFLECTIONMAP_3D
-float clearCoatEho=environmentHorizonOcclusion(-viewDirectionW,clearCoatNormalW,geometricNormalW);
-clearCoatEnvironmentReflectance*=clearCoatEho;
-#endif
-#endif
-#endif
-#else
-
-vec3 clearCoatEnvironmentReflectance=getReflectanceFromAnalyticalBRDFLookup_Jones(clearCoatNdotV,vec3(1.),vec3(1.),sqrt(1.-clearCoatRoughness));
-#endif
-clearCoatEnvironmentReflectance*=clearCoatIntensity;
-#if DEBUGMODE>0
-outParams.clearCoatEnvironmentReflectance=clearCoatEnvironmentReflectance;
-#endif
-outParams.finalClearCoatRadianceScaled=
-environmentClearCoatRadiance.rgb *
-clearCoatEnvironmentReflectance *
-vLightingIntensity.z;
-#endif
-#if defined(CLEARCOAT_TINT)
-
-outParams.absorption=computeClearCoatAbsorption(outParams.clearCoatNdotVRefract,outParams.clearCoatNdotVRefract,outParams.clearCoatColor,clearCoatThickness,clearCoatIntensity);
-#endif
-
-float fresnelIBLClearCoat=fresnelSchlickGGX(clearCoatNdotV,vClearCoatRefractionParams.x,CLEARCOATREFLECTANCE90);
-fresnelIBLClearCoat*=clearCoatIntensity;
-outParams.conservationFactor=(1.-fresnelIBLClearCoat);
-#if defined(ENVIRONMENTBRDF) && defined(MS_BRDF_ENERGY_CONSERVATION)
-outParams.energyConservationFactorClearCoat=getEnergyConservationFactor(outParams.specularEnvironmentR0,environmentClearCoatBrdf);
-#endif
-}
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockClearcoat=qp;var Zp=`struct subSurfaceOutParams
-{
-vec3 specularEnvironmentReflectance;
-#ifdef SS_REFRACTION
-vec3 finalRefraction;
-vec3 surfaceAlbedo;
-#ifdef SS_LINKREFRACTIONTOTRANSPARENCY
-float alpha;
-#endif
-#ifdef REFLECTION
-float refractionFactorForIrradiance;
-#endif
-#endif
-#ifdef SS_TRANSLUCENCY
-vec3 transmittance;
-float translucencyIntensity;
-#ifdef REFLECTION
-vec3 refractionIrradiance;
-#endif
-#endif
-#if DEBUGMODE>0
-vec4 thicknessMap;
-vec4 environmentRefraction;
-vec3 refractionTransmittance;
-#endif
-};
-#ifdef SUBSURFACE
-#define pbr_inline
-#define inline
-void subSurfaceBlock(
-const in vec3 vSubSurfaceIntensity,
-const in vec2 vThicknessParam,
-const in vec4 vTintColor,
-const in vec3 normalW,
-const in vec3 specularEnvironmentReflectance,
-#ifdef SS_THICKNESSANDMASK_TEXTURE
-const in vec4 thicknessMap,
-#endif
-#ifdef REFLECTION
-#ifdef SS_TRANSLUCENCY
-const in mat4 reflectionMatrix,
-#ifdef USESPHERICALFROMREFLECTIONMAP
-#if !defined(NORMAL) || !defined(USESPHERICALINVERTEX)
-const in vec3 irradianceVector_,
-#endif
-#if defined(REALTIME_FILTERING)
-const in samplerCube reflectionSampler,
-const in vec2 vReflectionFilteringInfo,
-#endif
-#endif
-#ifdef USEIRRADIANCEMAP
-#ifdef REFLECTIONMAP_3D
-const in samplerCube irradianceSampler,
-#else
-const in sampler2D irradianceSampler,
-#endif
-#endif
-#endif
-#endif
-#ifdef SS_REFRACTION
-const in vec3 vPositionW,
-const in vec3 viewDirectionW,
-const in mat4 view,
-const in vec3 surfaceAlbedo,
-const in vec4 vRefractionInfos,
-const in mat4 refractionMatrix,
-const in vec3 vRefractionMicrosurfaceInfos,
-const in vec4 vLightingIntensity,
-#ifdef SS_LINKREFRACTIONTOTRANSPARENCY
-const in float alpha,
-#endif
-#ifdef SS_LODINREFRACTIONALPHA
-const in float NdotVUnclamped,
-#endif
-#ifdef SS_LINEARSPECULARREFRACTION
-const in float roughness,
-#else
-const in float alphaG,
-#endif
-#ifdef SS_REFRACTIONMAP_3D
-const in samplerCube refractionSampler,
-#ifndef LODBASEDMICROSFURACE
-const in samplerCube refractionSamplerLow,
-const in samplerCube refractionSamplerHigh,
-#endif
-#else
-const in sampler2D refractionSampler,
-#ifndef LODBASEDMICROSFURACE
-const in sampler2D refractionSamplerLow,
-const in sampler2D refractionSamplerHigh,
-#endif
-#endif
-#ifdef ANISOTROPIC
-const in anisotropicOutParams anisotropicOut,
-#endif
-#ifdef REALTIME_FILTERING
-const in vec2 vRefractionFilteringInfo,
-#endif
-#endif
-#ifdef SS_TRANSLUCENCY
-const in vec3 vDiffusionDistance,
-#endif
-out subSurfaceOutParams outParams
-)
-{
-outParams.specularEnvironmentReflectance=specularEnvironmentReflectance;
-
-
-
-#ifdef SS_REFRACTION
-float refractionIntensity=vSubSurfaceIntensity.x;
-#ifdef SS_LINKREFRACTIONTOTRANSPARENCY
-refractionIntensity*=(1.0-alpha);
-
-outParams.alpha=1.0;
-#endif
-#endif
-#ifdef SS_TRANSLUCENCY
-float translucencyIntensity=vSubSurfaceIntensity.y;
-#endif
-#ifdef SS_THICKNESSANDMASK_TEXTURE
-float thickness=thicknessMap.r*vThicknessParam.y+vThicknessParam.x;
-#if DEBUGMODE>0
-outParams.thicknessMap=thicknessMap;
-#endif
-#ifdef SS_MASK_FROM_THICKNESS_TEXTURE
-#ifdef SS_REFRACTION
-refractionIntensity*=thicknessMap.g;
-#endif
-#ifdef SS_TRANSLUCENCY
-translucencyIntensity*=thicknessMap.b;
-#endif
-#elif defined(SS_MASK_FROM_THICKNESS_TEXTURE_GLTF)
-#ifdef SS_REFRACTION
-refractionIntensity*=thicknessMap.r;
-#elif defined(SS_TRANSLUCENCY)
-translucencyIntensity*=thicknessMap.r;
-#endif
-thickness=thicknessMap.g*vThicknessParam.y+vThicknessParam.x;
-#endif
-#else
-float thickness=vThicknessParam.y;
-#endif
-
-
-
-#ifdef SS_TRANSLUCENCY
-thickness=maxEps(thickness);
-vec3 transmittance=transmittanceBRDF_Burley(vTintColor.rgb,vDiffusionDistance,thickness);
-transmittance*=translucencyIntensity;
-outParams.transmittance=transmittance;
-outParams.translucencyIntensity=translucencyIntensity;
-#endif
-
-
-
-#ifdef SS_REFRACTION
-vec4 environmentRefraction=vec4(0.,0.,0.,0.);
-#ifdef ANISOTROPIC
-vec3 refractionVector=refract(-viewDirectionW,anisotropicOut.anisotropicNormal,vRefractionInfos.y);
-#else
-vec3 refractionVector=refract(-viewDirectionW,normalW,vRefractionInfos.y);
-#endif
-#ifdef SS_REFRACTIONMAP_OPPOSITEZ
-refractionVector.z*=-1.0;
-#endif
-
-#ifdef SS_REFRACTIONMAP_3D
-refractionVector.y=refractionVector.y*vRefractionInfos.w;
-vec3 refractionCoords=refractionVector;
-refractionCoords=vec3(refractionMatrix*vec4(refractionCoords,0));
-#else
-vec3 vRefractionUVW=vec3(refractionMatrix*(view*vec4(vPositionW+refractionVector*vRefractionInfos.z,1.0)));
-vec2 refractionCoords=vRefractionUVW.xy/vRefractionUVW.z;
-refractionCoords.y=1.0-refractionCoords.y;
-#endif
-#ifdef SS_LODINREFRACTIONALPHA
-float refractionLOD=getLodFromAlphaG(vRefractionMicrosurfaceInfos.x,alphaG,NdotVUnclamped);
-#elif defined(SS_LINEARSPECULARREFRACTION)
-float refractionLOD=getLinearLodFromRoughness(vRefractionMicrosurfaceInfos.x,roughness);
-#else
-float refractionLOD=getLodFromAlphaG(vRefractionMicrosurfaceInfos.x,alphaG);
-#endif
-#ifdef LODBASEDMICROSFURACE
-
-refractionLOD=refractionLOD*vRefractionMicrosurfaceInfos.y+vRefractionMicrosurfaceInfos.z;
-#ifdef SS_LODINREFRACTIONALPHA
-
-
-
-
-
-
-
-
-
-float automaticRefractionLOD=UNPACK_LOD(sampleRefraction(refractionSampler,refractionCoords).a);
-float requestedRefractionLOD=max(automaticRefractionLOD,refractionLOD);
-#else
-float requestedRefractionLOD=refractionLOD;
-#endif
-#ifdef REALTIME_FILTERING
-environmentRefraction=vec4(radiance(alphaG,refractionSampler,refractionCoords,vRefractionFilteringInfo),1.0);
-#else
-environmentRefraction=sampleRefractionLod(refractionSampler,refractionCoords,requestedRefractionLOD);
-#endif
-#else
-float lodRefractionNormalized=saturate(refractionLOD/log2(vRefractionMicrosurfaceInfos.x));
-float lodRefractionNormalizedDoubled=lodRefractionNormalized*2.0;
-vec4 environmentRefractionMid=sampleRefraction(refractionSampler,refractionCoords);
-if (lodRefractionNormalizedDoubled<1.0){
-environmentRefraction=mix(
-sampleRefraction(refractionSamplerHigh,refractionCoords),
-environmentRefractionMid,
-lodRefractionNormalizedDoubled
-);
-} else {
-environmentRefraction=mix(
-environmentRefractionMid,
-sampleRefraction(refractionSamplerLow,refractionCoords),
-lodRefractionNormalizedDoubled-1.0
-);
-}
-#endif
-#ifdef SS_RGBDREFRACTION
-environmentRefraction.rgb=fromRGBD(environmentRefraction);
-#endif
-#ifdef SS_GAMMAREFRACTION
-environmentRefraction.rgb=toLinearSpace(environmentRefraction.rgb);
-#endif
-
-environmentRefraction.rgb*=vRefractionInfos.x;
-#endif
-
-
-
-#ifdef SS_REFRACTION
-vec3 refractionTransmittance=vec3(refractionIntensity);
-#ifdef SS_THICKNESSANDMASK_TEXTURE
-vec3 volumeAlbedo=computeColorAtDistanceInMedia(vTintColor.rgb,vTintColor.w);
-
-
-
-
-
-refractionTransmittance*=cocaLambert(volumeAlbedo,thickness);
-#elif defined(SS_LINKREFRACTIONTOTRANSPARENCY)
-
-float maxChannel=max(max(surfaceAlbedo.r,surfaceAlbedo.g),surfaceAlbedo.b);
-vec3 volumeAlbedo=saturate(maxChannel*surfaceAlbedo);
-
-environmentRefraction.rgb*=volumeAlbedo;
-#else
-
-vec3 volumeAlbedo=computeColorAtDistanceInMedia(vTintColor.rgb,vTintColor.w);
-refractionTransmittance*=cocaLambert(volumeAlbedo,vThicknessParam.y);
-#endif
-#ifdef SS_ALBEDOFORREFRACTIONTINT
-
-environmentRefraction.rgb*=surfaceAlbedo.rgb;
-#endif
-
-outParams.surfaceAlbedo=surfaceAlbedo*(1.-refractionIntensity);
-#ifdef REFLECTION
-
-outParams.refractionFactorForIrradiance=(1.-refractionIntensity);
-
-#endif
-
-vec3 bounceSpecularEnvironmentReflectance=(2.0*specularEnvironmentReflectance)/(1.0+specularEnvironmentReflectance);
-outParams.specularEnvironmentReflectance=mix(bounceSpecularEnvironmentReflectance,specularEnvironmentReflectance,refractionIntensity);
-
-refractionTransmittance*=1.0-outParams.specularEnvironmentReflectance;
-#if DEBUGMODE>0
-outParams.refractionTransmittance=refractionTransmittance;
-#endif
-outParams.finalRefraction=environmentRefraction.rgb*refractionTransmittance*vLightingIntensity.z;
-#if DEBUGMODE>0
-outParams.environmentRefraction=environmentRefraction;
-#endif
-#endif
-
-
-
-#if defined(REFLECTION) && defined(SS_TRANSLUCENCY)
-#if defined(NORMAL) && defined(USESPHERICALINVERTEX) || !defined(USESPHERICALFROMREFLECTIONMAP)
-vec3 irradianceVector=vec3(reflectionMatrix*vec4(normalW,0)).xyz;
-#ifdef REFLECTIONMAP_OPPOSITEZ
-irradianceVector.z*=-1.0;
-#endif
-#ifdef INVERTCUBICMAP
-irradianceVector.y*=-1.0;
-#endif
-#else
-vec3 irradianceVector=irradianceVector_;
-#endif
-#if defined(USESPHERICALFROMREFLECTIONMAP)
-#if defined(REALTIME_FILTERING)
-vec3 refractionIrradiance=irradiance(reflectionSampler,-irradianceVector,vReflectionFilteringInfo);
-#else
-vec3 refractionIrradiance=computeEnvironmentIrradiance(-irradianceVector);
-#endif
-#elif defined(USEIRRADIANCEMAP)
-#ifdef REFLECTIONMAP_3D
-vec3 irradianceCoords=irradianceVector;
-#else
-vec2 irradianceCoords=irradianceVector.xy;
-#ifdef REFLECTIONMAP_PROJECTION
-irradianceCoords/=irradianceVector.z;
-#endif
-irradianceCoords.y=1.0-irradianceCoords.y;
-#endif
-vec4 refractionIrradiance=sampleReflection(irradianceSampler,-irradianceCoords);
-#ifdef RGBDREFLECTION
-refractionIrradiance.rgb=fromRGBD(refractionIrradiance);
-#endif
-#ifdef GAMMAREFLECTION
-refractionIrradiance.rgb=toLinearSpace(refractionIrradiance.rgb);
-#endif
-#else
-vec4 refractionIrradiance=vec4(0.);
-#endif
-refractionIrradiance.rgb*=transmittance;
-outParams.refractionIrradiance=refractionIrradiance.rgb;
-#endif
-}
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockSubSurface=Zp;var Jp=`vec3 viewDirectionW=normalize(vEyePosition.xyz-vPositionW);
-#ifdef NORMAL
-vec3 normalW=normalize(vNormalW);
-#else
-vec3 normalW=normalize(cross(dFdx(vPositionW),dFdy(vPositionW)))*vEyePosition.w;
-#endif
-vec3 geometricNormalW=normalW;
-#if defined(TWOSIDEDLIGHTING) && defined(NORMAL)
-geometricNormalW=gl_FrontFacing ? geometricNormalW : -geometricNormalW;
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockNormalGeometric=Jp,f(134);var $p=`#if defined(FORCENORMALFORWARD) && defined(NORMAL)
-vec3 faceNormal=normalize(cross(dFdx(vPositionW),dFdy(vPositionW)))*vEyePosition.w;
-#if defined(TWOSIDEDLIGHTING)
-faceNormal=gl_FrontFacing ? faceNormal : -faceNormal;
-#endif
-normalW*=sign(dot(normalW,faceNormal));
-#endif
-#if defined(TWOSIDEDLIGHTING) && defined(NORMAL)
-normalW=gl_FrontFacing ? normalW : -normalW;
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockNormalFinal=$p,f(162);var e_=`#ifdef LIGHTMAP
-vec4 lightmapColor=texture2D(lightmapSampler,vLightmapUV+uvOffset);
-#ifdef RGBDLIGHTMAP
-lightmapColor.rgb=fromRGBD(lightmapColor);
-#endif
-#ifdef GAMMALIGHTMAP
-lightmapColor.rgb=toLinearSpace(lightmapColor.rgb);
-#endif
-lightmapColor.rgb*=vLightmapInfos.y;
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockLightmapInit=e_;var t_=`float NdotVUnclamped=dot(normalW,viewDirectionW);
-
-float NdotV=absEps(NdotVUnclamped);
-float alphaG=convertRoughnessToAverageSlope(roughness);
-vec2 AARoughnessFactors=getAARoughnessFactors(normalW.xyz);
-#ifdef SPECULARAA
-
-alphaG+=AARoughnessFactors.y;
-#endif
-#if defined(ENVIRONMENTBRDF)
-
-vec3 environmentBrdf=getBRDFLookup(NdotV,roughness);
-#endif
-#if defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-#ifdef RADIANCEOCCLUSION
-#ifdef AMBIENTINGRAYSCALE
-float ambientMonochrome=aoOut.ambientOcclusionColor.r;
-#else
-float ambientMonochrome=getLuminance(aoOut.ambientOcclusionColor);
-#endif
-float seo=environmentRadianceOcclusion(ambientMonochrome,NdotVUnclamped);
-#endif
-#ifdef HORIZONOCCLUSION
-#ifdef BUMP
-#ifdef REFLECTIONMAP_3D
-float eho=environmentHorizonOcclusion(-viewDirectionW,normalW,geometricNormalW);
-#endif
-#endif
-#endif
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockGeometryInfo=t_;var n_=`float reflectance=max(max(reflectivityOut.surfaceReflectivityColor.r,reflectivityOut.surfaceReflectivityColor.g),reflectivityOut.surfaceReflectivityColor.b);
-vec3 specularEnvironmentR0=reflectivityOut.surfaceReflectivityColor.rgb;
-#ifdef METALLICWORKFLOW
-vec3 specularEnvironmentR90=vec3(metallicReflectanceFactors.a);
-#else
-vec3 specularEnvironmentR90=vec3(1.0,1.0,1.0);
-#endif
-
-#ifdef ALPHAFRESNEL
-float reflectance90=fresnelGrazingReflectance(reflectance);
-specularEnvironmentR90=specularEnvironmentR90*reflectance90;
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockReflectance0=n_;var i_=`#if defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-vec3 specularEnvironmentReflectance=getReflectanceFromBRDFLookup(clearcoatOut.specularEnvironmentR0,specularEnvironmentR90,environmentBrdf);
-#ifdef RADIANCEOCCLUSION
-specularEnvironmentReflectance*=seo;
-#endif
-#ifdef HORIZONOCCLUSION
-#ifdef BUMP
-#ifdef REFLECTIONMAP_3D
-specularEnvironmentReflectance*=eho;
-#endif
-#endif
-#endif
-#else
-
-vec3 specularEnvironmentReflectance=getReflectanceFromAnalyticalBRDFLookup_Jones(NdotV,clearcoatOut.specularEnvironmentR0,specularEnvironmentR90,sqrt(microSurface));
-#endif
-#ifdef CLEARCOAT
-specularEnvironmentReflectance*=clearcoatOut.conservationFactor;
-#if defined(CLEARCOAT_TINT)
-specularEnvironmentReflectance*=clearcoatOut.absorption;
-#endif
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockReflectance=i_;var r_=`vec3 diffuseBase=vec3(0.,0.,0.);
-#ifdef SPECULARTERM
-vec3 specularBase=vec3(0.,0.,0.);
-#endif
-#ifdef CLEARCOAT
-vec3 clearCoatBase=vec3(0.,0.,0.);
-#endif
-#ifdef SHEEN
-vec3 sheenBase=vec3(0.,0.,0.);
-#endif
-
-preLightingInfo preInfo;
-lightingInfo info;
-float shadow=1.;
-#if defined(CLEARCOAT) && defined(CLEARCOAT_TINT)
-vec3 absorption=vec3(0.);
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockDirectLighting=r_;var o_=`
-
-
-
-#if defined(ENVIRONMENTBRDF)
-#ifdef MS_BRDF_ENERGY_CONSERVATION
-vec3 energyConservationFactor=getEnergyConservationFactor(clearcoatOut.specularEnvironmentR0,environmentBrdf);
-#endif
-#endif
-#ifndef METALLICWORKFLOW
-#ifdef SPECULAR_GLOSSINESS_ENERGY_CONSERVATION
-surfaceAlbedo.rgb=(1.-reflectance)*surfaceAlbedo.rgb;
-#endif
-#endif
-#if defined(SHEEN) && defined(SHEEN_ALBEDOSCALING) && defined(ENVIRONMENTBRDF)
-surfaceAlbedo.rgb=sheenOut.sheenAlbedoScaling*surfaceAlbedo.rgb;
-#endif
-
-#ifdef REFLECTION
-vec3 finalIrradiance=reflectionOut.environmentIrradiance;
-#if defined(CLEARCOAT)
-finalIrradiance*=clearcoatOut.conservationFactor;
-#if defined(CLEARCOAT_TINT)
-finalIrradiance*=clearcoatOut.absorption;
-#endif
-#endif
-#if defined(SS_REFRACTION)
-finalIrradiance*=subSurfaceOut.refractionFactorForIrradiance;
-#endif
-#if defined(SS_TRANSLUCENCY)
-finalIrradiance*=(1.0-subSurfaceOut.translucencyIntensity);
-finalIrradiance+=subSurfaceOut.refractionIrradiance;
-#endif
-finalIrradiance*=surfaceAlbedo.rgb;
-finalIrradiance*=vLightingIntensity.z;
-finalIrradiance*=aoOut.ambientOcclusionColor;
-#endif
-
-#ifdef SPECULARTERM
-vec3 finalSpecular=specularBase;
-finalSpecular=max(finalSpecular,0.0);
-vec3 finalSpecularScaled=finalSpecular*vLightingIntensity.x*vLightingIntensity.w;
-#if defined(ENVIRONMENTBRDF) && defined(MS_BRDF_ENERGY_CONSERVATION)
-finalSpecularScaled*=energyConservationFactor;
-#endif
-#if defined(SHEEN) && defined(ENVIRONMENTBRDF) && defined(SHEEN_ALBEDOSCALING)
-finalSpecularScaled*=sheenOut.sheenAlbedoScaling;
-#endif
-#endif
-
-#ifdef REFLECTION
-vec3 finalRadiance=reflectionOut.environmentRadiance.rgb;
-finalRadiance*=subSurfaceOut.specularEnvironmentReflectance;
-vec3 finalRadianceScaled=finalRadiance*vLightingIntensity.z;
-#if defined(ENVIRONMENTBRDF) && defined(MS_BRDF_ENERGY_CONSERVATION)
-finalRadianceScaled*=energyConservationFactor;
-#endif
-#if defined(SHEEN) && defined(ENVIRONMENTBRDF) && defined(SHEEN_ALBEDOSCALING)
-finalRadianceScaled*=sheenOut.sheenAlbedoScaling;
-#endif
-#endif
-
-#ifdef SHEEN
-vec3 finalSheen=sheenBase*sheenOut.sheenColor;
-finalSheen=max(finalSheen,0.0);
-vec3 finalSheenScaled=finalSheen*vLightingIntensity.x*vLightingIntensity.w;
-#if defined(CLEARCOAT) && defined(REFLECTION) && defined(ENVIRONMENTBRDF)
-sheenOut.finalSheenRadianceScaled*=clearcoatOut.conservationFactor;
-#if defined(CLEARCOAT_TINT)
-sheenOut.finalSheenRadianceScaled*=clearcoatOut.absorption;
-#endif
-#endif
-#endif
-
-#ifdef CLEARCOAT
-vec3 finalClearCoat=clearCoatBase;
-finalClearCoat=max(finalClearCoat,0.0);
-vec3 finalClearCoatScaled=finalClearCoat*vLightingIntensity.x*vLightingIntensity.w;
-#if defined(ENVIRONMENTBRDF) && defined(MS_BRDF_ENERGY_CONSERVATION)
-finalClearCoatScaled*=clearcoatOut.energyConservationFactorClearCoat;
-#endif
-#ifdef SS_REFRACTION
-subSurfaceOut.finalRefraction*=clearcoatOut.conservationFactor;
-#ifdef CLEARCOAT_TINT
-subSurfaceOut.finalRefraction*=clearcoatOut.absorption;
-#endif
-#endif
-#endif
-
-#ifdef ALPHABLEND
-float luminanceOverAlpha=0.0;
-#if defined(REFLECTION) && defined(RADIANCEOVERALPHA)
-luminanceOverAlpha+=getLuminance(finalRadianceScaled);
-#if defined(CLEARCOAT)
-luminanceOverAlpha+=getLuminance(clearcoatOut.finalClearCoatRadianceScaled);
-#endif
-#endif
-#if defined(SPECULARTERM) && defined(SPECULAROVERALPHA)
-luminanceOverAlpha+=getLuminance(finalSpecularScaled);
-#endif
-#if defined(CLEARCOAT) && defined(CLEARCOATOVERALPHA)
-luminanceOverAlpha+=getLuminance(finalClearCoatScaled);
-#endif
-#if defined(RADIANCEOVERALPHA) || defined(SPECULAROVERALPHA) || defined(CLEARCOATOVERALPHA)
-alpha=saturate(alpha+luminanceOverAlpha*luminanceOverAlpha);
-#endif
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockFinalLitComponents=o_;var a_=`
-vec3 finalDiffuse=diffuseBase;
-finalDiffuse*=surfaceAlbedo.rgb;
-finalDiffuse=max(finalDiffuse,0.0);
-finalDiffuse*=vLightingIntensity.x;
-
-vec3 finalAmbient=vAmbientColor;
-finalAmbient*=surfaceAlbedo.rgb;
-
-vec3 finalEmissive=vEmissiveColor;
-#ifdef EMISSIVE
-vec3 emissiveColorTex=texture2D(emissiveSampler,vEmissiveUV+uvOffset).rgb;
-finalEmissive*=toLinearSpace(emissiveColorTex.rgb);
-finalEmissive*=vEmissiveInfos.y;
-#endif
-finalEmissive*=vLightingIntensity.y;
-
-#ifdef AMBIENT
-vec3 ambientOcclusionForDirectDiffuse=mix(vec3(1.),aoOut.ambientOcclusionColor,vAmbientInfos.w);
-#else
-vec3 ambientOcclusionForDirectDiffuse=aoOut.ambientOcclusionColor;
-#endif
-finalAmbient*=aoOut.ambientOcclusionColor;
-finalDiffuse*=ambientOcclusionForDirectDiffuse;
-`;ze.a.IncludesShadersStore.pbrBlockFinalUnlitComponents=a_;var s_=`vec4 finalColor=vec4(
-finalAmbient +
-finalDiffuse +
-#ifndef UNLIT
-#ifdef REFLECTION
-finalIrradiance +
-#endif
-#ifdef SPECULARTERM
-finalSpecularScaled +
-#endif
-#ifdef SHEEN
-finalSheenScaled +
-#endif
-#ifdef CLEARCOAT
-finalClearCoatScaled +
-#endif
-#ifdef REFLECTION
-finalRadianceScaled +
-#if defined(SHEEN) && defined(ENVIRONMENTBRDF)
-sheenOut.finalSheenRadianceScaled +
-#endif
-#ifdef CLEARCOAT
-clearcoatOut.finalClearCoatRadianceScaled +
-#endif
-#endif
-#ifdef SS_REFRACTION
-subSurfaceOut.finalRefraction +
-#endif
-#endif
-finalEmissive,
-alpha);
-
-#ifdef LIGHTMAP
-#ifndef LIGHTMAPEXCLUDED
-#ifdef USELIGHTMAPASSHADOWMAP
-finalColor.rgb*=lightmapColor.rgb;
-#else
-finalColor.rgb+=lightmapColor.rgb;
-#endif
-#endif
-#endif
-#define CUSTOM_FRAGMENT_BEFORE_FOG
-
-finalColor=max(finalColor,0.0);
-`;ze.a.IncludesShadersStore.pbrBlockFinalColorComposition=s_,f(155);var c_=`#ifdef IMAGEPROCESSINGPOSTPROCESS
-
-
-finalColor.rgb=clamp(finalColor.rgb,0.,30.0);
-#else
-
-finalColor=applyImageProcessing(finalColor);
-#endif
-finalColor.a*=visibility;
-#ifdef PREMULTIPLYALPHA
-
-finalColor.rgb*=finalColor.a;
-#endif
-`;ze.a.IncludesShadersStore.pbrBlockImageProcessing=c_;var l_=`#if DEBUGMODE>0
-if (vClipSpacePosition.x/vClipSpacePosition.w>=vDebugMode.x) {
-
-#if DEBUGMODE == 1
-gl_FragColor.rgb=vPositionW.rgb;
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 2 && defined(NORMAL)
-gl_FragColor.rgb=vNormalW.rgb;
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 3 && defined(BUMP) || DEBUGMODE == 3 && defined(PARALLAX) || DEBUGMODE == 3 && defined(ANISOTROPIC)
-
-gl_FragColor.rgb=TBN[0];
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 4 && defined(BUMP) || DEBUGMODE == 4 && defined(PARALLAX) || DEBUGMODE == 4 && defined(ANISOTROPIC)
-
-gl_FragColor.rgb=TBN[1];
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 5
-
-gl_FragColor.rgb=normalW;
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 6 && defined(MAINUV1)
-gl_FragColor.rgb=vec3(vMainUV1,0.0);
-#elif DEBUGMODE == 7 && defined(MAINUV2)
-gl_FragColor.rgb=vec3(vMainUV2,0.0);
-#elif DEBUGMODE == 8 && defined(CLEARCOAT) && defined(CLEARCOAT_BUMP)
-
-gl_FragColor.rgb=clearcoatOut.TBNClearCoat[0];
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 9 && defined(CLEARCOAT) && defined(CLEARCOAT_BUMP)
-
-gl_FragColor.rgb=clearcoatOut.TBNClearCoat[1];
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 10 && defined(CLEARCOAT)
-
-gl_FragColor.rgb=clearcoatOut.clearCoatNormalW;
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 11 && defined(ANISOTROPIC)
-gl_FragColor.rgb=anisotropicOut.anisotropicNormal;
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 12 && defined(ANISOTROPIC)
-gl_FragColor.rgb=anisotropicOut.anisotropicTangent;
-#define DEBUGMODE_NORMALIZE
-#elif DEBUGMODE == 13 && defined(ANISOTROPIC)
-gl_FragColor.rgb=anisotropicOut.anisotropicBitangent;
-#define DEBUGMODE_NORMALIZE
-
-#elif DEBUGMODE == 20 && defined(ALBEDO)
-gl_FragColor.rgb=albedoTexture.rgb;
-#elif DEBUGMODE == 21 && defined(AMBIENT)
-gl_FragColor.rgb=aoOut.ambientOcclusionColorMap.rgb;
-#elif DEBUGMODE == 22 && defined(OPACITY)
-gl_FragColor.rgb=opacityMap.rgb;
-#elif DEBUGMODE == 23 && defined(EMISSIVE)
-gl_FragColor.rgb=emissiveColorTex.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 24 && defined(LIGHTMAP)
-gl_FragColor.rgb=lightmapColor.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 25 && defined(REFLECTIVITY) && defined(METALLICWORKFLOW)
-gl_FragColor.rgb=reflectivityOut.surfaceMetallicColorMap.rgb;
-#elif DEBUGMODE == 26 && defined(REFLECTIVITY) && !defined(METALLICWORKFLOW)
-gl_FragColor.rgb=reflectivityOut.surfaceReflectivityColorMap.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 27 && defined(CLEARCOAT) && defined(CLEARCOAT_TEXTURE)
-gl_FragColor.rgb=vec3(clearcoatOut.clearCoatMapData.rg,0.0);
-#elif DEBUGMODE == 28 && defined(CLEARCOAT) && defined(CLEARCOAT_TINT) && defined(CLEARCOAT_TINT_TEXTURE)
-gl_FragColor.rgb=clearcoatOut.clearCoatTintMapData.rgb;
-#elif DEBUGMODE == 29 && defined(SHEEN) && defined(SHEEN_TEXTURE)
-gl_FragColor.rgb=sheenOut.sheenMapData.rgb;
-#elif DEBUGMODE == 30 && defined(ANISOTROPIC) && defined(ANISOTROPIC_TEXTURE)
-gl_FragColor.rgb=anisotropicOut.anisotropyMapData.rgb;
-#elif DEBUGMODE == 31 && defined(SUBSURFACE) && defined(SS_THICKNESSANDMASK_TEXTURE)
-gl_FragColor.rgb=subSurfaceOut.thicknessMap.rgb;
-
-#elif DEBUGMODE == 40 && defined(SS_REFRACTION)
-
-gl_FragColor.rgb=subSurfaceOut.environmentRefraction.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 41 && defined(REFLECTION)
-gl_FragColor.rgb=reflectionOut.environmentRadiance.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 42 && defined(CLEARCOAT) && defined(REFLECTION)
-gl_FragColor.rgb=clearcoatOut.environmentClearCoatRadiance.rgb;
-#define DEBUGMODE_GAMMA
-
-#elif DEBUGMODE == 50
-gl_FragColor.rgb=diffuseBase.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 51 && defined(SPECULARTERM)
-gl_FragColor.rgb=specularBase.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 52 && defined(CLEARCOAT)
-gl_FragColor.rgb=clearCoatBase.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 53 && defined(SHEEN)
-gl_FragColor.rgb=sheenBase.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 54 && defined(REFLECTION)
-gl_FragColor.rgb=reflectionOut.environmentIrradiance.rgb;
-#define DEBUGMODE_GAMMA
-
-#elif DEBUGMODE == 60
-gl_FragColor.rgb=surfaceAlbedo.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 61
-gl_FragColor.rgb=clearcoatOut.specularEnvironmentR0;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 62 && defined(METALLICWORKFLOW)
-gl_FragColor.rgb=vec3(reflectivityOut.metallicRoughness.r);
-#elif DEBUGMODE == 71 && defined(METALLICWORKFLOW)
-gl_FragColor.rgb=reflectivityOut.metallicF0;
-#elif DEBUGMODE == 63
-gl_FragColor.rgb=vec3(roughness);
-#elif DEBUGMODE == 64
-gl_FragColor.rgb=vec3(alphaG);
-#elif DEBUGMODE == 65
-gl_FragColor.rgb=vec3(NdotV);
-#elif DEBUGMODE == 66 && defined(CLEARCOAT) && defined(CLEARCOAT_TINT)
-gl_FragColor.rgb=clearcoatOut.clearCoatColor.rgb;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 67 && defined(CLEARCOAT)
-gl_FragColor.rgb=vec3(clearcoatOut.clearCoatRoughness);
-#elif DEBUGMODE == 68 && defined(CLEARCOAT)
-gl_FragColor.rgb=vec3(clearcoatOut.clearCoatNdotV);
-#elif DEBUGMODE == 69 && defined(SUBSURFACE) && defined(SS_TRANSLUCENCY)
-gl_FragColor.rgb=subSurfaceOut.transmittance;
-#elif DEBUGMODE == 70 && defined(SUBSURFACE) && defined(SS_REFRACTION)
-gl_FragColor.rgb=subSurfaceOut.refractionTransmittance;
-
-#elif DEBUGMODE == 80 && defined(RADIANCEOCCLUSION)
-gl_FragColor.rgb=vec3(seo);
-#elif DEBUGMODE == 81 && defined(HORIZONOCCLUSION)
-gl_FragColor.rgb=vec3(eho);
-#elif DEBUGMODE == 82 && defined(MS_BRDF_ENERGY_CONSERVATION)
-gl_FragColor.rgb=vec3(energyConservationFactor);
-#elif DEBUGMODE == 83 && defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-gl_FragColor.rgb=specularEnvironmentReflectance;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 84 && defined(CLEARCOAT) && defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-gl_FragColor.rgb=clearcoatOut.clearCoatEnvironmentReflectance;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 85 && defined(SHEEN) && defined(REFLECTION)
-gl_FragColor.rgb=sheenOut.sheenEnvironmentReflectance;
-#define DEBUGMODE_GAMMA
-#elif DEBUGMODE == 86 && defined(ALPHABLEND)
-gl_FragColor.rgb=vec3(luminanceOverAlpha);
-#elif DEBUGMODE == 87
-gl_FragColor.rgb=vec3(alpha);
-#endif
-gl_FragColor.rgb*=vDebugMode.y;
-#ifdef DEBUGMODE_NORMALIZE
-gl_FragColor.rgb=normalize(gl_FragColor.rgb)*0.5+0.5;
-#endif
-#ifdef DEBUGMODE_GAMMA
-gl_FragColor.rgb=toGammaSpace(gl_FragColor.rgb);
-#endif
-gl_FragColor.a=1.0;
-#ifdef PREPASS
-gl_FragData[0]=toLinearSpace(gl_FragColor);
-gl_FragData[1]=vec4(0.,0.,0.,0.);
-#endif
-return;
-}
-#endif`;ze.a.IncludesShadersStore.pbrDebug=l_;var u_=`#if defined(BUMP) || !defined(NORMAL) || defined(FORCENORMALFORWARD) || defined(SPECULARAA) || defined(CLEARCOAT_BUMP) || defined(ANISOTROPIC)
-#extension GL_OES_standard_derivatives : enable
-#endif
-#ifdef LODBASEDMICROSFURACE
-#extension GL_EXT_shader_texture_lod : enable
-#endif
-#define CUSTOM_FRAGMENT_BEGIN
-#ifdef LOGARITHMICDEPTH
-#extension GL_EXT_frag_depth : enable
-#endif
-#include<prePassDeclaration>[SCENE_MRT_COUNT]
-precision highp float;
-
-#ifndef FROMLINEARSPACE
-#define FROMLINEARSPACE
-#endif
-
-#include<__decl__pbrFragment>
-#include<pbrFragmentExtraDeclaration>
-#include<__decl__lightFragment>[0..maxSimultaneousLights]
-#include<pbrFragmentSamplersDeclaration>
-#include<imageProcessingDeclaration>
-#include<clipPlaneFragmentDeclaration>
-#include<logDepthDeclaration>
-#include<fogFragmentDeclaration>
-
-#include<helperFunctions>
-#include<subSurfaceScatteringFunctions>
-#include<importanceSampling>
-#include<pbrHelperFunctions>
-#include<imageProcessingFunctions>
-#include<shadowsFragmentFunctions>
-#include<harmonicsFunctions>
-#include<pbrDirectLightingSetupFunctions>
-#include<pbrDirectLightingFalloffFunctions>
-#include<pbrBRDFFunctions>
-#include<hdrFilteringFunctions>
-#include<pbrDirectLightingFunctions>
-#include<pbrIBLFunctions>
-#include<bumpFragmentMainFunctions>
-#include<bumpFragmentFunctions>
-#ifdef REFLECTION
-#include<reflectionFunction>
-#endif
-#define CUSTOM_FRAGMENT_DEFINITIONS
-#include<pbrBlockAlbedoOpacity>
-#include<pbrBlockReflectivity>
-#include<pbrBlockAmbientOcclusion>
-#include<pbrBlockAlphaFresnel>
-#include<pbrBlockAnisotropic>
-#include<pbrBlockReflection>
-#include<pbrBlockSheen>
-#include<pbrBlockClearcoat>
-#include<pbrBlockSubSurface>
-
-void main(void) {
-#define CUSTOM_FRAGMENT_MAIN_BEGIN
-#include<clipPlaneFragment>
-
-#include<pbrBlockNormalGeometric>
-#include<bumpFragment>
-#include<pbrBlockNormalFinal>
-
-albedoOpacityOutParams albedoOpacityOut;
-#ifdef ALBEDO
-vec4 albedoTexture=texture2D(albedoSampler,vAlbedoUV+uvOffset);
-#endif
-#ifdef OPACITY
-vec4 opacityMap=texture2D(opacitySampler,vOpacityUV+uvOffset);
-#endif
-albedoOpacityBlock(
-vAlbedoColor,
-#ifdef ALBEDO
-albedoTexture,
-vAlbedoInfos,
-#endif
-#ifdef OPACITY
-opacityMap,
-vOpacityInfos,
-#endif
-#ifdef DETAIL
-detailColor,
-vDetailInfos,
-#endif
-albedoOpacityOut
-);
-vec3 surfaceAlbedo=albedoOpacityOut.surfaceAlbedo;
-float alpha=albedoOpacityOut.alpha;
-#define CUSTOM_FRAGMENT_UPDATE_ALPHA
-#include<depthPrePass>
-#define CUSTOM_FRAGMENT_BEFORE_LIGHTS
-
-ambientOcclusionOutParams aoOut;
-#ifdef AMBIENT
-vec3 ambientOcclusionColorMap=texture2D(ambientSampler,vAmbientUV+uvOffset).rgb;
-#endif
-ambientOcclusionBlock(
-#ifdef AMBIENT
-ambientOcclusionColorMap,
-vAmbientInfos,
-#endif
-aoOut
-);
-#include<pbrBlockLightmapInit>
-#ifdef UNLIT
-vec3 diffuseBase=vec3(1.,1.,1.);
-#else
-
-vec3 baseColor=surfaceAlbedo;
-reflectivityOutParams reflectivityOut;
-#if defined(REFLECTIVITY)
-vec4 surfaceMetallicOrReflectivityColorMap=texture2D(reflectivitySampler,vReflectivityUV+uvOffset);
-vec4 baseReflectivity=surfaceMetallicOrReflectivityColorMap;
-#ifndef METALLICWORKFLOW
-surfaceMetallicOrReflectivityColorMap=toLinearSpace(surfaceMetallicOrReflectivityColorMap);
-surfaceMetallicOrReflectivityColorMap.rgb*=vReflectivityInfos.y;
-#endif
-#endif
-#if defined(MICROSURFACEMAP)
-vec4 microSurfaceTexel=texture2D(microSurfaceSampler,vMicroSurfaceSamplerUV+uvOffset)*vMicroSurfaceSamplerInfos.y;
-#endif
-#ifdef METALLICWORKFLOW
-vec4 metallicReflectanceFactors=vMetallicReflectanceFactors;
-#ifdef METALLIC_REFLECTANCE
-vec4 metallicReflectanceFactorsMap=texture2D(metallicReflectanceSampler,vMetallicReflectanceUV+uvOffset);
-metallicReflectanceFactorsMap=toLinearSpace(metallicReflectanceFactorsMap);
-metallicReflectanceFactors*=metallicReflectanceFactorsMap;
-#endif
-#endif
-reflectivityBlock(
-vReflectivityColor,
-#ifdef METALLICWORKFLOW
-surfaceAlbedo,
-metallicReflectanceFactors,
-#endif
-#ifdef REFLECTIVITY
-vReflectivityInfos,
-surfaceMetallicOrReflectivityColorMap,
-#endif
-#if defined(METALLICWORKFLOW) && defined(REFLECTIVITY) && defined(AOSTOREINMETALMAPRED)
-aoOut.ambientOcclusionColor,
-#endif
-#ifdef MICROSURFACEMAP
-microSurfaceTexel,
-#endif
-#ifdef DETAIL
-detailColor,
-vDetailInfos,
-#endif
-reflectivityOut
-);
-float microSurface=reflectivityOut.microSurface;
-float roughness=reflectivityOut.roughness;
-#ifdef METALLICWORKFLOW
-surfaceAlbedo=reflectivityOut.surfaceAlbedo;
-#endif
-#if defined(METALLICWORKFLOW) && defined(REFLECTIVITY) && defined(AOSTOREINMETALMAPRED)
-aoOut.ambientOcclusionColor=reflectivityOut.ambientOcclusionColor;
-#endif
-
-#ifdef ALPHAFRESNEL
-#if defined(ALPHATEST) || defined(ALPHABLEND)
-alphaFresnelOutParams alphaFresnelOut;
-alphaFresnelBlock(
-normalW,
-viewDirectionW,
-alpha,
-microSurface,
-alphaFresnelOut
-);
-alpha=alphaFresnelOut.alpha;
-#endif
-#endif
-
-#include<pbrBlockGeometryInfo>
-
-#ifdef ANISOTROPIC
-anisotropicOutParams anisotropicOut;
-#ifdef ANISOTROPIC_TEXTURE
-vec3 anisotropyMapData=texture2D(anisotropySampler,vAnisotropyUV+uvOffset).rgb*vAnisotropyInfos.y;
-#endif
-anisotropicBlock(
-vAnisotropy,
-#ifdef ANISOTROPIC_TEXTURE
-anisotropyMapData,
-#endif
-TBN,
-normalW,
-viewDirectionW,
-anisotropicOut
-);
-#endif
-
-#ifdef REFLECTION
-reflectionOutParams reflectionOut;
-reflectionBlock(
-vPositionW,
-normalW,
-alphaG,
-vReflectionMicrosurfaceInfos,
-vReflectionInfos,
-vReflectionColor,
-#ifdef ANISOTROPIC
-anisotropicOut,
-#endif
-#if defined(LODINREFLECTIONALPHA) && !defined(REFLECTIONMAP_SKYBOX)
-NdotVUnclamped,
-#endif
-#ifdef LINEARSPECULARREFLECTION
-roughness,
-#endif
-reflectionSampler,
-#if defined(NORMAL) && defined(USESPHERICALINVERTEX)
-vEnvironmentIrradiance,
-#endif
-#ifdef USESPHERICALFROMREFLECTIONMAP
-#if !defined(NORMAL) || !defined(USESPHERICALINVERTEX)
-reflectionMatrix,
-#endif
-#endif
-#ifdef USEIRRADIANCEMAP
-irradianceSampler,
-#endif
-#ifndef LODBASEDMICROSFURACE
-reflectionSamplerLow,
-reflectionSamplerHigh,
-#endif
-#ifdef REALTIME_FILTERING
-vReflectionFilteringInfo,
-#endif
-reflectionOut
-);
-#endif
-
-#include<pbrBlockReflectance0>
-
-#ifdef SHEEN
-sheenOutParams sheenOut;
-#ifdef SHEEN_TEXTURE
-vec4 sheenMapData=toLinearSpace(texture2D(sheenSampler,vSheenUV+uvOffset))*vSheenInfos.y;
-#endif
-#if defined(SHEEN_ROUGHNESS) && defined(SHEEN_TEXTURE_ROUGHNESS) && !defined(SHEEN_TEXTURE_ROUGHNESS_IDENTICAL) && !defined(SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE)
-vec4 sheenMapRoughnessData=texture2D(sheenRoughnessSampler,vSheenRoughnessUV+uvOffset)*vSheenInfos.w;
-#endif
-sheenBlock(
-vSheenColor,
-#ifdef SHEEN_ROUGHNESS
-vSheenRoughness,
-#if defined(SHEEN_TEXTURE_ROUGHNESS) && !defined(SHEEN_TEXTURE_ROUGHNESS_IDENTICAL) && !defined(SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE)
-sheenMapRoughnessData,
-#endif
-#endif
-roughness,
-#ifdef SHEEN_TEXTURE
-sheenMapData,
-#endif
-reflectance,
-#ifdef SHEEN_LINKWITHALBEDO
-baseColor,
-surfaceAlbedo,
-#endif
-#ifdef ENVIRONMENTBRDF
-NdotV,
-environmentBrdf,
-#endif
-#if defined(REFLECTION) && defined(ENVIRONMENTBRDF)
-AARoughnessFactors,
-vReflectionMicrosurfaceInfos,
-vReflectionInfos,
-vReflectionColor,
-vLightingIntensity,
-reflectionSampler,
-reflectionOut.reflectionCoords,
-NdotVUnclamped,
-#ifndef LODBASEDMICROSFURACE
-reflectionSamplerLow,
-reflectionSamplerHigh,
-#endif
-#ifdef REALTIME_FILTERING
-vReflectionFilteringInfo,
-#endif
-#if !defined(REFLECTIONMAP_SKYBOX) && defined(RADIANCEOCCLUSION)
-seo,
-#endif
-#if !defined(REFLECTIONMAP_SKYBOX) && defined(HORIZONOCCLUSION) && defined(BUMP) && defined(REFLECTIONMAP_3D)
-eho,
-#endif
-#endif
-sheenOut
-);
-#ifdef SHEEN_LINKWITHALBEDO
-surfaceAlbedo=sheenOut.surfaceAlbedo;
-#endif
-#endif
-
-clearcoatOutParams clearcoatOut;
-#ifdef CLEARCOAT
-#ifdef CLEARCOAT_TEXTURE
-vec2 clearCoatMapData=texture2D(clearCoatSampler,vClearCoatUV+uvOffset).rg*vClearCoatInfos.y;
-#endif
-#if defined(CLEARCOAT_TEXTURE_ROUGHNESS) && !defined(CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL) && !defined(CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE)
-vec4 clearCoatMapRoughnessData=texture2D(clearCoatRoughnessSampler,vClearCoatRoughnessUV+uvOffset)*vClearCoatInfos.w;
-#endif
-#if defined(CLEARCOAT_TINT) && defined(CLEARCOAT_TINT_TEXTURE)
-vec4 clearCoatTintMapData=toLinearSpace(texture2D(clearCoatTintSampler,vClearCoatTintUV+uvOffset));
-#endif
-#ifdef CLEARCOAT_BUMP
-vec4 clearCoatBumpMapData=texture2D(clearCoatBumpSampler,vClearCoatBumpUV+uvOffset);
-#endif
-clearcoatBlock(
-vPositionW,
-geometricNormalW,
-viewDirectionW,
-vClearCoatParams,
-#if defined(CLEARCOAT_TEXTURE_ROUGHNESS) && !defined(CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL) && !defined(CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE)
-clearCoatMapRoughnessData,
-#endif
-specularEnvironmentR0,
-#ifdef CLEARCOAT_TEXTURE
-clearCoatMapData,
-#endif
-#ifdef CLEARCOAT_TINT
-vClearCoatTintParams,
-clearCoatColorAtDistance,
-vClearCoatRefractionParams,
-#ifdef CLEARCOAT_TINT_TEXTURE
-clearCoatTintMapData,
-#endif
-#endif
-#ifdef CLEARCOAT_BUMP
-vClearCoatBumpInfos,
-clearCoatBumpMapData,
-vClearCoatBumpUV,
-#if defined(TANGENT) && defined(NORMAL)
-vTBN,
-#else
-vClearCoatTangentSpaceParams,
-#endif
-#ifdef OBJECTSPACE_NORMALMAP
-normalMatrix,
-#endif
-#endif
-#if defined(FORCENORMALFORWARD) && defined(NORMAL)
-faceNormal,
-#endif
-#ifdef REFLECTION
-vReflectionMicrosurfaceInfos,
-vReflectionInfos,
-vReflectionColor,
-vLightingIntensity,
-reflectionSampler,
-#ifndef LODBASEDMICROSFURACE
-reflectionSamplerLow,
-reflectionSamplerHigh,
-#endif
-#ifdef REALTIME_FILTERING
-vReflectionFilteringInfo,
-#endif
-#endif
-#if defined(ENVIRONMENTBRDF) && !defined(REFLECTIONMAP_SKYBOX)
-#ifdef RADIANCEOCCLUSION
-ambientMonochrome,
-#endif
-#endif
-clearcoatOut
-);
-#else
-clearcoatOut.specularEnvironmentR0=specularEnvironmentR0;
-#endif
-
-#include<pbrBlockReflectance>
-
-subSurfaceOutParams subSurfaceOut;
-#ifdef SUBSURFACE
-#ifdef SS_THICKNESSANDMASK_TEXTURE
-vec4 thicknessMap=texture2D(thicknessSampler,vThicknessUV+uvOffset);
-#endif
-subSurfaceBlock(
-vSubSurfaceIntensity,
-vThicknessParam,
-vTintColor,
-normalW,
-specularEnvironmentReflectance,
-#ifdef SS_THICKNESSANDMASK_TEXTURE
-thicknessMap,
-#endif
-#ifdef REFLECTION
-#ifdef SS_TRANSLUCENCY
-reflectionMatrix,
-#ifdef USESPHERICALFROMREFLECTIONMAP
-#if !defined(NORMAL) || !defined(USESPHERICALINVERTEX)
-reflectionOut.irradianceVector,
-#endif
-#if defined(REALTIME_FILTERING)
-reflectionSampler,
-vReflectionFilteringInfo,
-#endif
-#endif
-#ifdef USEIRRADIANCEMAP
-irradianceSampler,
-#endif
-#endif
-#endif
-#ifdef SS_REFRACTION
-vPositionW,
-viewDirectionW,
-view,
-surfaceAlbedo,
-vRefractionInfos,
-refractionMatrix,
-vRefractionMicrosurfaceInfos,
-vLightingIntensity,
-#ifdef SS_LINKREFRACTIONTOTRANSPARENCY
-alpha,
-#endif
-#ifdef SS_LODINREFRACTIONALPHA
-NdotVUnclamped,
-#endif
-#ifdef SS_LINEARSPECULARREFRACTION
-roughness,
-#else
-alphaG,
-#endif
-refractionSampler,
-#ifndef LODBASEDMICROSFURACE
-refractionSamplerLow,
-refractionSamplerHigh,
-#endif
-#ifdef ANISOTROPIC
-anisotropicOut,
-#endif
-#ifdef REALTIME_FILTERING
-vRefractionFilteringInfo,
-#endif
-#endif
-#ifdef SS_TRANSLUCENCY
-vDiffusionDistance,
-#endif
-subSurfaceOut
-);
-#ifdef SS_REFRACTION
-surfaceAlbedo=subSurfaceOut.surfaceAlbedo;
-#ifdef SS_LINKREFRACTIONTOTRANSPARENCY
-alpha=subSurfaceOut.alpha;
-#endif
-#endif
-#else
-subSurfaceOut.specularEnvironmentReflectance=specularEnvironmentReflectance;
-#endif
-
-#include<pbrBlockDirectLighting>
-#include<lightFragment>[0..maxSimultaneousLights]
-
-#include<pbrBlockFinalLitComponents>
-#endif
-#include<pbrBlockFinalUnlitComponents>
-#include<pbrBlockFinalColorComposition>
-#include<logDepthFragment>
-#include<fogFragment>(color,finalColor)
-#include<pbrBlockImageProcessing>
-#define CUSTOM_FRAGMENT_BEFORE_FRAGCOLOR
-#ifdef PREPASS
-#ifdef PREPASS_POSITION
-gl_FragData[PREPASS_POSITION_INDEX]=vec4(vPositionW,1.0);
-#endif
-#ifdef PREPASS_VELOCITY
-vec2 a=(vCurrentPosition.xy/vCurrentPosition.w)*0.5+0.5;
-vec2 b=(vPreviousPosition.xy/vPreviousPosition.w)*0.5+0.5;
-vec2 velocity=abs(a-b);
-velocity=vec2(pow(velocity.x,1.0/3.0),pow(velocity.y,1.0/3.0))*sign(a-b)*0.5+0.5;
-gl_FragData[PREPASS_VELOCITY_INDEX]=vec4(velocity,0.0,1.0);
-#endif
-#ifdef PREPASS_IRRADIANCE
-vec3 irradiance=finalDiffuse;
-#ifndef UNLIT
-#ifdef REFLECTION
-irradiance+=finalIrradiance;
-#endif
-#endif
-vec3 sqAlbedo=sqrt(surfaceAlbedo);
-#ifdef SS_SCATTERING
-gl_FragData[0]=vec4(finalColor.rgb-irradiance,finalColor.a);
-irradiance/=sqAlbedo;
-#else
-gl_FragData[0]=finalColor;
-float scatteringDiffusionProfile=255.;
-#endif
-gl_FragData[PREPASS_IRRADIANCE_INDEX]=vec4(irradiance,scatteringDiffusionProfile/255.);
-#else
-gl_FragData[0]=vec4(finalColor.rgb,finalColor.a);
-#endif
-#ifdef PREPASS_DEPTHNORMAL
-gl_FragData[PREPASS_DEPTHNORMAL_INDEX]=vec4(vViewPos.z,(view*vec4(normalW,0.0)).rgb);
-#endif
-#ifdef PREPASS_ALBEDO
-gl_FragData[PREPASS_ALBEDO_INDEX]=vec4(sqAlbedo,1.0);
-#endif
-#ifdef PREPASS_REFLECTIVITY
-#if defined(REFLECTIVITY)
-gl_FragData[PREPASS_REFLECTIVITY_INDEX]=vec4(baseReflectivity.rgb,1.0);
-#else
-gl_FragData[PREPASS_REFLECTIVITY_INDEX]=vec4(0.0,0.0,0.0,1.0);
-#endif
-#endif
-#endif
-#if !defined(PREPASS) || defined(WEBGL2)
-gl_FragColor=finalColor;
-#endif
-#include<pbrDebug>
-}
-`;ze.a.ShadersStore.pbrPixelShader=u_;var h_=`uniform mat4 view;
-uniform mat4 viewProjection;
-#ifdef ALBEDO
-uniform mat4 albedoMatrix;
-uniform vec2 vAlbedoInfos;
-#endif
-#ifdef AMBIENT
-uniform mat4 ambientMatrix;
-uniform vec4 vAmbientInfos;
-#endif
-#ifdef OPACITY
-uniform mat4 opacityMatrix;
-uniform vec2 vOpacityInfos;
-#endif
-#ifdef EMISSIVE
-uniform vec2 vEmissiveInfos;
-uniform mat4 emissiveMatrix;
-#endif
-#ifdef LIGHTMAP
-uniform vec2 vLightmapInfos;
-uniform mat4 lightmapMatrix;
-#endif
-#ifdef REFLECTIVITY
-uniform vec3 vReflectivityInfos;
-uniform mat4 reflectivityMatrix;
-#endif
-#ifdef METALLIC_REFLECTANCE
-uniform vec2 vMetallicReflectanceInfos;
-uniform mat4 metallicReflectanceMatrix;
-#endif
-#ifdef MICROSURFACEMAP
-uniform vec2 vMicroSurfaceSamplerInfos;
-uniform mat4 microSurfaceSamplerMatrix;
-#endif
-#ifdef BUMP
-uniform vec3 vBumpInfos;
-uniform mat4 bumpMatrix;
-#endif
-#ifdef POINTSIZE
-uniform float pointSize;
-#endif
-
-#ifdef REFLECTION
-uniform vec2 vReflectionInfos;
-uniform mat4 reflectionMatrix;
-#endif
-
-#ifdef CLEARCOAT
-#if defined(CLEARCOAT_TEXTURE) || defined(CLEARCOAT_TEXTURE_ROUGHNESS)
-uniform vec4 vClearCoatInfos;
-#endif
-#ifdef CLEARCOAT_TEXTURE
-uniform mat4 clearCoatMatrix;
-#endif
-#ifdef CLEARCOAT_TEXTURE_ROUGHNESS
-uniform mat4 clearCoatRoughnessMatrix;
-#endif
-#ifdef CLEARCOAT_BUMP
-uniform vec2 vClearCoatBumpInfos;
-uniform mat4 clearCoatBumpMatrix;
-#endif
-#ifdef CLEARCOAT_TINT_TEXTURE
-uniform vec2 vClearCoatTintInfos;
-uniform mat4 clearCoatTintMatrix;
-#endif
-#endif
-
-#ifdef ANISOTROPIC
-#ifdef ANISOTROPIC_TEXTURE
-uniform vec2 vAnisotropyInfos;
-uniform mat4 anisotropyMatrix;
-#endif
-#endif
-
-#ifdef SHEEN
-#if defined(SHEEN_TEXTURE) || defined(SHEEN_TEXTURE_ROUGHNESS)
-uniform vec4 vSheenInfos;
-#endif
-#ifdef SHEEN_TEXTURE
-uniform mat4 sheenMatrix;
-#endif
-#ifdef SHEEN_TEXTURE_ROUGHNESS
-uniform mat4 sheenRoughnessMatrix;
-#endif
-#endif
-
-#ifdef SUBSURFACE
-#ifdef SS_REFRACTION
-uniform vec4 vRefractionInfos;
-uniform mat4 refractionMatrix;
-#endif
-#ifdef SS_THICKNESSANDMASK_TEXTURE
-uniform vec2 vThicknessInfos;
-uniform mat4 thicknessMatrix;
-#endif
-#endif
-`;ze.a.IncludesShadersStore.pbrVertexDeclaration=h_,f(163),f(164),f(93),f(94),f(100),f(165),f(156),f(158);var d_=`precision highp float;
-#include<__decl__pbrVertex>
-#define CUSTOM_VERTEX_BEGIN
-
-attribute vec3 position;
-#ifdef NORMAL
-attribute vec3 normal;
-#endif
-#ifdef TANGENT
-attribute vec4 tangent;
-#endif
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#ifdef MAINUV1
-varying vec2 vMainUV1;
-#endif
-#ifdef MAINUV2
-varying vec2 vMainUV2;
-#endif
-#ifdef VERTEXCOLOR
-attribute vec4 color;
-#endif
-#include<helperFunctions>
-#include<bonesDeclaration>
-
-#include<instancesDeclaration>
-#include<prePassVertexDeclaration>
-#if defined(ALBEDO) && ALBEDODIRECTUV == 0
-varying vec2 vAlbedoUV;
-#endif
-#if defined(DETAIL) && DETAILDIRECTUV == 0
-varying vec2 vDetailUV;
-#endif
-#if defined(AMBIENT) && AMBIENTDIRECTUV == 0
-varying vec2 vAmbientUV;
-#endif
-#if defined(OPACITY) && OPACITYDIRECTUV == 0
-varying vec2 vOpacityUV;
-#endif
-#if defined(EMISSIVE) && EMISSIVEDIRECTUV == 0
-varying vec2 vEmissiveUV;
-#endif
-#if defined(LIGHTMAP) && LIGHTMAPDIRECTUV == 0
-varying vec2 vLightmapUV;
-#endif
-#if defined(REFLECTIVITY) && REFLECTIVITYDIRECTUV == 0
-varying vec2 vReflectivityUV;
-#endif
-#if defined(MICROSURFACEMAP) && MICROSURFACEMAPDIRECTUV == 0
-varying vec2 vMicroSurfaceSamplerUV;
-#endif
-#if defined(METALLIC_REFLECTANCE) && METALLIC_REFLECTANCEDIRECTUV == 0
-varying vec2 vMetallicReflectanceUV;
-#endif
-#if defined(BUMP) && BUMPDIRECTUV == 0
-varying vec2 vBumpUV;
-#endif
-#ifdef CLEARCOAT
-#if defined(CLEARCOAT_TEXTURE) && CLEARCOAT_TEXTUREDIRECTUV == 0
-varying vec2 vClearCoatUV;
-#endif
-#if defined(CLEARCOAT_TEXTURE_ROUGHNESS) && CLEARCOAT_TEXTURE_ROUGHNESSDIRECTUV == 0
-varying vec2 vClearCoatRoughnessUV;
-#endif
-#if defined(CLEARCOAT_BUMP) && CLEARCOAT_BUMPDIRECTUV == 0
-varying vec2 vClearCoatBumpUV;
-#endif
-#if defined(CLEARCOAT_TINT_TEXTURE) && CLEARCOAT_TINT_TEXTUREDIRECTUV == 0
-varying vec2 vClearCoatTintUV;
-#endif
-#endif
-#ifdef SHEEN
-#if defined(SHEEN_TEXTURE) && SHEEN_TEXTUREDIRECTUV == 0
-varying vec2 vSheenUV;
-#endif
-#if defined(SHEEN_TEXTURE_ROUGHNESS) && SHEEN_TEXTURE_ROUGHNESSDIRECTUV == 0
-varying vec2 vSheenRoughnessUV;
-#endif
-#endif
-#ifdef ANISOTROPIC
-#if defined(ANISOTROPIC_TEXTURE) && ANISOTROPIC_TEXTUREDIRECTUV == 0
-varying vec2 vAnisotropyUV;
-#endif
-#endif
-#ifdef SUBSURFACE
-#if defined(SS_THICKNESSANDMASK_TEXTURE) && SS_THICKNESSANDMASK_TEXTUREDIRECTUV == 0
-varying vec2 vThicknessUV;
-#endif
-#endif
-
-varying vec3 vPositionW;
-#if DEBUGMODE>0
-varying vec4 vClipSpacePosition;
-#endif
-#ifdef NORMAL
-varying vec3 vNormalW;
-#if defined(USESPHERICALFROMREFLECTIONMAP) && defined(USESPHERICALINVERTEX)
-varying vec3 vEnvironmentIrradiance;
-#include<harmonicsFunctions>
-#endif
-#endif
-#ifdef VERTEXCOLOR
-varying vec4 vColor;
-#endif
-#include<bumpVertexDeclaration>
-#include<clipPlaneVertexDeclaration>
-#include<fogVertexDeclaration>
-#include<__decl__lightFragment>[0..maxSimultaneousLights]
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-#ifdef REFLECTIONMAP_SKYBOX
-varying vec3 vPositionUVW;
-#endif
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-varying vec3 vDirectionW;
-#endif
-#include<logDepthDeclaration>
-#define CUSTOM_VERTEX_DEFINITIONS
-void main(void) {
-#define CUSTOM_VERTEX_MAIN_BEGIN
-vec3 positionUpdated=position;
-#ifdef NORMAL
-vec3 normalUpdated=normal;
-#endif
-#ifdef TANGENT
-vec4 tangentUpdated=tangent;
-#endif
-#ifdef UV1
-vec2 uvUpdated=uv;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-#ifdef REFLECTIONMAP_SKYBOX
-vPositionUVW=positionUpdated;
-#endif
-#define CUSTOM_VERTEX_UPDATE_POSITION
-#define CUSTOM_VERTEX_UPDATE_NORMAL
-#include<instancesVertex>
-#if defined(PREPASS) && defined(PREPASS_VELOCITY) && !defined(BONES_VELOCITY_ENABLED)
-
-vCurrentPosition=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-vPreviousPosition=previousViewProjection*previousWorld*vec4(positionUpdated,1.0);
-#endif
-#include<bonesVertex>
-vec4 worldPos=finalWorld*vec4(positionUpdated,1.0);
-vPositionW=vec3(worldPos);
-#include<prePassVertex>
-#ifdef NORMAL
-mat3 normalWorld=mat3(finalWorld);
-#if defined(INSTANCES) && defined(THIN_INSTANCES)
-vNormalW=normalUpdated/vec3(dot(normalWorld[0],normalWorld[0]),dot(normalWorld[1],normalWorld[1]),dot(normalWorld[2],normalWorld[2]));
-vNormalW=normalize(normalWorld*vNormalW);
-#else
-#ifdef NONUNIFORMSCALING
-normalWorld=transposeMat3(inverseMat3(normalWorld));
-#endif
-vNormalW=normalize(normalWorld*normalUpdated);
-#endif
-#if defined(USESPHERICALFROMREFLECTIONMAP) && defined(USESPHERICALINVERTEX)
-vec3 reflectionVector=vec3(reflectionMatrix*vec4(vNormalW,0)).xyz;
-#ifdef REFLECTIONMAP_OPPOSITEZ
-reflectionVector.z*=-1.0;
-#endif
-vEnvironmentIrradiance=computeEnvironmentIrradiance(reflectionVector);
-#endif
-#endif
-#define CUSTOM_VERTEX_UPDATE_WORLDPOS
-#ifdef MULTIVIEW
-if (gl_ViewID_OVR == 0u) {
-gl_Position=viewProjection*worldPos;
-} else {
-gl_Position=viewProjectionR*worldPos;
-}
-#else
-gl_Position=viewProjection*worldPos;
-#endif
-#if DEBUGMODE>0
-vClipSpacePosition=gl_Position;
-#endif
-#if defined(REFLECTIONMAP_EQUIRECTANGULAR_FIXED) || defined(REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED)
-vDirectionW=normalize(vec3(finalWorld*vec4(positionUpdated,0.0)));
-#endif
-
-#ifndef UV1
-vec2 uvUpdated=vec2(0.,0.);
-#endif
-#ifndef UV2
-vec2 uv2=vec2(0.,0.);
-#endif
-#ifdef MAINUV1
-vMainUV1=uvUpdated;
-#endif
-#ifdef MAINUV2
-vMainUV2=uv2;
-#endif
-#if defined(ALBEDO) && ALBEDODIRECTUV == 0
-if (vAlbedoInfos.x == 0.)
-{
-vAlbedoUV=vec2(albedoMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vAlbedoUV=vec2(albedoMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(DETAIL) && DETAILDIRECTUV == 0
-if (vDetailInfos.x == 0.)
-{
-vDetailUV=vec2(detailMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vDetailUV=vec2(detailMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(AMBIENT) && AMBIENTDIRECTUV == 0
-if (vAmbientInfos.x == 0.)
-{
-vAmbientUV=vec2(ambientMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vAmbientUV=vec2(ambientMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(OPACITY) && OPACITYDIRECTUV == 0
-if (vOpacityInfos.x == 0.)
-{
-vOpacityUV=vec2(opacityMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vOpacityUV=vec2(opacityMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(EMISSIVE) && EMISSIVEDIRECTUV == 0
-if (vEmissiveInfos.x == 0.)
-{
-vEmissiveUV=vec2(emissiveMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vEmissiveUV=vec2(emissiveMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(LIGHTMAP) && LIGHTMAPDIRECTUV == 0
-if (vLightmapInfos.x == 0.)
-{
-vLightmapUV=vec2(lightmapMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vLightmapUV=vec2(lightmapMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(REFLECTIVITY) && REFLECTIVITYDIRECTUV == 0
-if (vReflectivityInfos.x == 0.)
-{
-vReflectivityUV=vec2(reflectivityMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vReflectivityUV=vec2(reflectivityMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(MICROSURFACEMAP) && MICROSURFACEMAPDIRECTUV == 0
-if (vMicroSurfaceSamplerInfos.x == 0.)
-{
-vMicroSurfaceSamplerUV=vec2(microSurfaceSamplerMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vMicroSurfaceSamplerUV=vec2(microSurfaceSamplerMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(METALLIC_REFLECTANCE) && METALLIC_REFLECTANCEDIRECTUV == 0
-if (vMetallicReflectanceInfos.x == 0.)
-{
-vMetallicReflectanceUV=vec2(metallicReflectanceMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vMetallicReflectanceUV=vec2(metallicReflectanceMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(BUMP) && BUMPDIRECTUV == 0
-if (vBumpInfos.x == 0.)
-{
-vBumpUV=vec2(bumpMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vBumpUV=vec2(bumpMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#ifdef CLEARCOAT
-#if defined(CLEARCOAT_TEXTURE) && CLEARCOAT_TEXTUREDIRECTUV == 0
-if (vClearCoatInfos.x == 0.)
-{
-vClearCoatUV=vec2(clearCoatMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vClearCoatUV=vec2(clearCoatMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(CLEARCOAT_TEXTURE_ROUGHNESS) && CLEARCOAT_TEXTURE_ROUGHNESSDIRECTUV == 0
-if (vClearCoatInfos.z == 0.)
-{
-vClearCoatRoughnessUV=vec2(clearCoatRoughnessMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vClearCoatRoughnessUV=vec2(clearCoatRoughnessMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(CLEARCOAT_BUMP) && CLEARCOAT_BUMPDIRECTUV == 0
-if (vClearCoatBumpInfos.x == 0.)
-{
-vClearCoatBumpUV=vec2(clearCoatBumpMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vClearCoatBumpUV=vec2(clearCoatBumpMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(CLEARCOAT_TINT_TEXTURE) && CLEARCOAT_TINT_TEXTUREDIRECTUV == 0
-if (vClearCoatTintInfos.x == 0.)
-{
-vClearCoatTintUV=vec2(clearCoatTintMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vClearCoatTintUV=vec2(clearCoatTintMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#endif
-#ifdef SHEEN
-#if defined(SHEEN_TEXTURE) && SHEEN_TEXTUREDIRECTUV == 0
-if (vSheenInfos.x == 0.)
-{
-vSheenUV=vec2(sheenMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vSheenUV=vec2(sheenMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#if defined(SHEEN_TEXTURE_ROUGHNESS) && SHEEN_TEXTURE_ROUGHNESSDIRECTUV == 0
-if (vSheenInfos.z == 0.)
-{
-vSheenRoughnessUV=vec2(sheenRoughnessMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vSheenRoughnessUV=vec2(sheenRoughnessMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#endif
-#ifdef ANISOTROPIC
-#if defined(ANISOTROPIC_TEXTURE) && ANISOTROPIC_TEXTUREDIRECTUV == 0
-if (vAnisotropyInfos.x == 0.)
-{
-vAnisotropyUV=vec2(anisotropyMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vAnisotropyUV=vec2(anisotropyMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#endif
-#ifdef SUBSURFACE
-#if defined(SS_THICKNESSANDMASK_TEXTURE) && SS_THICKNESSANDMASK_TEXTUREDIRECTUV == 0
-if (vThicknessInfos.x == 0.)
-{
-vThicknessUV=vec2(thicknessMatrix*vec4(uvUpdated,1.0,0.0));
-}
-else
-{
-vThicknessUV=vec2(thicknessMatrix*vec4(uv2,1.0,0.0));
-}
-#endif
-#endif
-
-#include<bumpVertex>
-
-#include<clipPlaneVertex>
-
-#include<fogVertex>
-
-#include<shadowsVertex>[0..maxSimultaneousLights]
-
-#ifdef VERTEXCOLOR
-vColor=color;
-#endif
-
-#ifdef POINTSIZE
-gl_PointSize=pointSize;
-#endif
-
-#include<logDepthVertex>
-#define CUSTOM_VERTEX_MAIN_END
-}`;ze.a.ShadersStore.pbrVertexShader=d_;var ta=f(92),xr={effect:null,subMesh:null},Bs=function(r){function t(){var e=r.call(this)||this;return e.PBR=!0,e.NUM_SAMPLES="0",e.REALTIME_FILTERING=!1,e.MAINUV1=!1,e.MAINUV2=!1,e.UV1=!1,e.UV2=!1,e.ALBEDO=!1,e.GAMMAALBEDO=!1,e.ALBEDODIRECTUV=0,e.VERTEXCOLOR=!1,e.DETAIL=!1,e.DETAILDIRECTUV=0,e.DETAIL_NORMALBLENDMETHOD=0,e.AMBIENT=!1,e.AMBIENTDIRECTUV=0,e.AMBIENTINGRAYSCALE=!1,e.OPACITY=!1,e.VERTEXALPHA=!1,e.OPACITYDIRECTUV=0,e.OPACITYRGB=!1,e.ALPHATEST=!1,e.DEPTHPREPASS=!1,e.ALPHABLEND=!1,e.ALPHAFROMALBEDO=!1,e.ALPHATESTVALUE="0.5",e.SPECULAROVERALPHA=!1,e.RADIANCEOVERALPHA=!1,e.ALPHAFRESNEL=!1,e.LINEARALPHAFRESNEL=!1,e.PREMULTIPLYALPHA=!1,e.EMISSIVE=!1,e.EMISSIVEDIRECTUV=0,e.REFLECTIVITY=!1,e.REFLECTIVITYDIRECTUV=0,e.SPECULARTERM=!1,e.MICROSURFACEFROMREFLECTIVITYMAP=!1,e.MICROSURFACEAUTOMATIC=!1,e.LODBASEDMICROSFURACE=!1,e.MICROSURFACEMAP=!1,e.MICROSURFACEMAPDIRECTUV=0,e.METALLICWORKFLOW=!1,e.ROUGHNESSSTOREINMETALMAPALPHA=!1,e.ROUGHNESSSTOREINMETALMAPGREEN=!1,e.METALLNESSSTOREINMETALMAPBLUE=!1,e.AOSTOREINMETALMAPRED=!1,e.METALLIC_REFLECTANCE=!1,e.METALLIC_REFLECTANCEDIRECTUV=0,e.ENVIRONMENTBRDF=!1,e.ENVIRONMENTBRDF_RGBD=!1,e.NORMAL=!1,e.TANGENT=!1,e.BUMP=!1,e.BUMPDIRECTUV=0,e.OBJECTSPACE_NORMALMAP=!1,e.PARALLAX=!1,e.PARALLAXOCCLUSION=!1,e.NORMALXYSCALE=!0,e.LIGHTMAP=!1,e.LIGHTMAPDIRECTUV=0,e.USELIGHTMAPASSHADOWMAP=!1,e.GAMMALIGHTMAP=!1,e.RGBDLIGHTMAP=!1,e.REFLECTION=!1,e.REFLECTIONMAP_3D=!1,e.REFLECTIONMAP_SPHERICAL=!1,e.REFLECTIONMAP_PLANAR=!1,e.REFLECTIONMAP_CUBIC=!1,e.USE_LOCAL_REFLECTIONMAP_CUBIC=!1,e.REFLECTIONMAP_PROJECTION=!1,e.REFLECTIONMAP_SKYBOX=!1,e.REFLECTIONMAP_EXPLICIT=!1,e.REFLECTIONMAP_EQUIRECTANGULAR=!1,e.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!1,e.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!1,e.INVERTCUBICMAP=!1,e.USESPHERICALFROMREFLECTIONMAP=!1,e.USEIRRADIANCEMAP=!1,e.SPHERICAL_HARMONICS=!1,e.USESPHERICALINVERTEX=!1,e.REFLECTIONMAP_OPPOSITEZ=!1,e.LODINREFLECTIONALPHA=!1,e.GAMMAREFLECTION=!1,e.RGBDREFLECTION=!1,e.LINEARSPECULARREFLECTION=!1,e.RADIANCEOCCLUSION=!1,e.HORIZONOCCLUSION=!1,e.INSTANCES=!1,e.THIN_INSTANCES=!1,e.PREPASS=!1,e.PREPASS_IRRADIANCE=!1,e.PREPASS_IRRADIANCE_INDEX=-1,e.PREPASS_ALBEDO=!1,e.PREPASS_ALBEDO_INDEX=-1,e.PREPASS_DEPTHNORMAL=!1,e.PREPASS_DEPTHNORMAL_INDEX=-1,e.PREPASS_POSITION=!1,e.PREPASS_POSITION_INDEX=-1,e.PREPASS_VELOCITY=!1,e.PREPASS_VELOCITY_INDEX=-1,e.PREPASS_REFLECTIVITY=!1,e.PREPASS_REFLECTIVITY_INDEX=-1,e.SCENE_MRT_COUNT=0,e.NUM_BONE_INFLUENCERS=0,e.BonesPerMesh=0,e.BONETEXTURE=!1,e.BONES_VELOCITY_ENABLED=!1,e.NONUNIFORMSCALING=!1,e.MORPHTARGETS=!1,e.MORPHTARGETS_NORMAL=!1,e.MORPHTARGETS_TANGENT=!1,e.MORPHTARGETS_UV=!1,e.NUM_MORPH_INFLUENCERS=0,e.IMAGEPROCESSING=!1,e.VIGNETTE=!1,e.VIGNETTEBLENDMODEMULTIPLY=!1,e.VIGNETTEBLENDMODEOPAQUE=!1,e.TONEMAPPING=!1,e.TONEMAPPING_ACES=!1,e.CONTRAST=!1,e.COLORCURVES=!1,e.COLORGRADING=!1,e.COLORGRADING3D=!1,e.SAMPLER3DGREENDEPTH=!1,e.SAMPLER3DBGRMAP=!1,e.IMAGEPROCESSINGPOSTPROCESS=!1,e.EXPOSURE=!1,e.MULTIVIEW=!1,e.USEPHYSICALLIGHTFALLOFF=!1,e.USEGLTFLIGHTFALLOFF=!1,e.TWOSIDEDLIGHTING=!1,e.SHADOWFLOAT=!1,e.CLIPPLANE=!1,e.CLIPPLANE2=!1,e.CLIPPLANE3=!1,e.CLIPPLANE4=!1,e.CLIPPLANE5=!1,e.CLIPPLANE6=!1,e.POINTSIZE=!1,e.FOG=!1,e.LOGARITHMICDEPTH=!1,e.FORCENORMALFORWARD=!1,e.SPECULARAA=!1,e.CLEARCOAT=!1,e.CLEARCOAT_DEFAULTIOR=!1,e.CLEARCOAT_TEXTURE=!1,e.CLEARCOAT_TEXTURE_ROUGHNESS=!1,e.CLEARCOAT_TEXTUREDIRECTUV=0,e.CLEARCOAT_TEXTURE_ROUGHNESSDIRECTUV=0,e.CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE=!1,e.CLEARCOAT_TEXTURE_ROUGHNESS_IDENTICAL=!1,e.CLEARCOAT_BUMP=!1,e.CLEARCOAT_BUMPDIRECTUV=0,e.CLEARCOAT_REMAP_F0=!0,e.CLEARCOAT_TINT=!1,e.CLEARCOAT_TINT_TEXTURE=!1,e.CLEARCOAT_TINT_TEXTUREDIRECTUV=0,e.ANISOTROPIC=!1,e.ANISOTROPIC_TEXTURE=!1,e.ANISOTROPIC_TEXTUREDIRECTUV=0,e.BRDF_V_HEIGHT_CORRELATED=!1,e.MS_BRDF_ENERGY_CONSERVATION=!1,e.SPECULAR_GLOSSINESS_ENERGY_CONSERVATION=!1,e.SHEEN=!1,e.SHEEN_TEXTURE=!1,e.SHEEN_TEXTURE_ROUGHNESS=!1,e.SHEEN_TEXTUREDIRECTUV=0,e.SHEEN_TEXTURE_ROUGHNESSDIRECTUV=0,e.SHEEN_LINKWITHALBEDO=!1,e.SHEEN_ROUGHNESS=!1,e.SHEEN_ALBEDOSCALING=!1,e.SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE=!1,e.SHEEN_TEXTURE_ROUGHNESS_IDENTICAL=!1,e.SUBSURFACE=!1,e.SS_REFRACTION=!1,e.SS_TRANSLUCENCY=!1,e.SS_SCATTERING=!1,e.SS_THICKNESSANDMASK_TEXTURE=!1,e.SS_THICKNESSANDMASK_TEXTUREDIRECTUV=0,e.SS_REFRACTIONMAP_3D=!1,e.SS_REFRACTIONMAP_OPPOSITEZ=!1,e.SS_LODINREFRACTIONALPHA=!1,e.SS_GAMMAREFRACTION=!1,e.SS_RGBDREFRACTION=!1,e.SS_LINEARSPECULARREFRACTION=!1,e.SS_LINKREFRACTIONTOTRANSPARENCY=!1,e.SS_ALBEDOFORREFRACTIONTINT=!1,e.SS_MASK_FROM_THICKNESS_TEXTURE=!1,e.SS_MASK_FROM_THICKNESS_TEXTURE_GLTF=!1,e.UNLIT=!1,e.DEBUGMODE=0,e.rebuild(),e}return 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M.a(1,1,1),i._reflectionColor=new M.a(1,1,1),i._emissiveColor=new M.a(0,0,0),i._microSurface=.9,i._useLightmapAsShadowmap=!1,i._useHorizonOcclusion=!0,i._useRadianceOcclusion=!0,i._useAlphaFromAlbedoTexture=!1,i._useSpecularOverAlpha=!0,i._useMicroSurfaceFromReflectivityMapAlpha=!1,i._useRoughnessFromMetallicTextureAlpha=!0,i._useRoughnessFromMetallicTextureGreen=!1,i._useMetallnessFromMetallicTextureBlue=!1,i._useAmbientOcclusionFromMetallicTextureRed=!1,i._useAmbientInGrayScale=!1,i._useAutoMicroSurfaceFromReflectivityMap=!1,i._lightFalloff=t.LIGHTFALLOFF_PHYSICAL,i._useRadianceOverAlpha=!0,i._useObjectSpaceNormalMap=!1,i._useParallax=!1,i._useParallaxOcclusion=!1,i._parallaxScaleBias=.05,i._disableLighting=!1,i._maxSimultaneousLights=4,i._invertNormalMapX=!1,i._invertNormalMapY=!1,i._twoSidedLighting=!1,i._alphaCutOff=.4,i._forceAlphaTest=!1,i._useAlphaFresnel=!1,i._useLinearAlphaFresnel=!1,i._environmentBRDFTexture=null,i._forceIrradianceInFragment=!1,i._realTimeFiltering=!1,i._realTimeFilteringQuality=h.a.TEXTURE_FILTERING_QUALITY_LOW,i._forceNormalForward=!1,i._enableSpecularAntiAliasing=!1,i._imageProcessingObserver=null,i._renderTargets=new fi.a(16),i._globalAmbientColor=new M.a(0,0,0),i._useLogarithmicDepth=!1,i._unlit=!1,i._debugMode=0,i.debugMode=0,i.debugLimit=-1,i.debugFactor=1,i.clearCoat=new Ar(i._markAllSubMeshesAsTexturesDirty.bind(i)),i.anisotropy=new Pr(i._markAllSubMeshesAsTexturesDirty.bind(i)),i.brdf=new Op(i._markAllSubMeshesAsMiscDirty.bind(i)),i.sheen=new co(i._markAllSubMeshesAsTexturesDirty.bind(i)),i.detailMap=new ta.a(i._markAllSubMeshesAsTexturesDirty.bind(i)),i._rebuildInParallel=!1,i._attachImageProcessingConfiguration(null),i.getRenderTargetTextures=function(){return i._renderTargets.reset(),ht.a.ReflectionTextureEnabled&&i._reflectionTexture&&i._reflectionTexture.isRenderTarget&&i._renderTargets.push(i._reflectionTexture),i.subSurface.fillRenderTargetTextures(i._renderTargets),i._renderTargets},i._environmentBRDFTexture=ea.GetEnvironmentBRDFTexture(n),i.subSurface=new lo(i._markAllSubMeshesAsTexturesDirty.bind(i),i._markScenePrePassDirty.bind(i),n),i.prePassConfiguration=new Fs.a,i}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"realTimeFiltering",{get:function(){return this._realTimeFiltering},set:function(e){this._realTimeFiltering=e,this.markAsDirty(h.a.MATERIAL_TextureDirtyFlag)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"realTimeFilteringQuality",{get:function(){return this._realTimeFilteringQuality},set:function(e){this._realTimeFilteringQuality=e,this.markAsDirty(h.a.MATERIAL_TextureDirtyFlag)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"canRenderToMRT",{get:function(){return!0},enumerable:!1,configurable:!0}),t.prototype._attachImageProcessingConfiguration=function(e){var n=this;e!==this._imageProcessingConfiguration&&(this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),this._imageProcessingConfiguration=e||this.getScene().imageProcessingConfiguration,this._imageProcessingConfiguration&&(this._imageProcessingObserver=this._imageProcessingConfiguration.onUpdateParameters.add(function(){n._markAllSubMeshesAsImageProcessingDirty()})))},Object.defineProperty(t.prototype,"hasRenderTargetTextures",{get:function(){return!!(ht.a.ReflectionTextureEnabled&&this._reflectionTexture&&this._reflectionTexture.isRenderTarget)||this.subSurface.hasRenderTargetTextures()},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"PBRBaseMaterial"},Object.defineProperty(t.prototype,"useLogarithmicDepth",{get:function(){return this._useLogarithmicDepth},set:function(e){this._useLogarithmicDepth=e&&this.getScene().getEngine().getCaps().fragmentDepthSupported},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"_disableAlphaBlending",{get:function(){return this.subSurface.disableAlphaBlending||this._transparencyMode===t.PBRMATERIAL_OPAQUE||this._transparencyMode===t.PBRMATERIAL_ALPHATEST},enumerable:!1,configurable:!0}),t.prototype.needAlphaBlending=function(){return!this._disableAlphaBlending&&(this.alpha<1||this._opacityTexture!=null||this._shouldUseAlphaFromAlbedoTexture())},t.prototype.needAlphaTesting=function(){return!!this._forceAlphaTest||!this.subSurface.disableAlphaBlending&&this._hasAlphaChannel()&&(this._transparencyMode==null||this._transparencyMode===t.PBRMATERIAL_ALPHATEST)},t.prototype._shouldUseAlphaFromAlbedoTexture=function(){return this._albedoTexture!=null&&this._albedoTexture.hasAlpha&&this._useAlphaFromAlbedoTexture&&this._transparencyMode!==t.PBRMATERIAL_OPAQUE},t.prototype._hasAlphaChannel=function(){return this._albedoTexture!=null&&this._albedoTexture.hasAlpha||this._opacityTexture!=null},t.prototype.getAlphaTestTexture=function(){return this._albedoTexture},t.prototype.isReadyForSubMesh=function(e,n,i){if(n.effect&&this.isFrozen&&n.effect._wasPreviouslyReady)return!0;n._materialDefines||(n._materialDefines=new Bs);var o=n._materialDefines;if(this._isReadyForSubMesh(n))return!0;var a=this.getScene(),s=a.getEngine();if(o._areTexturesDirty&&a.texturesEnabled){if(this._albedoTexture&&ht.a.DiffuseTextureEnabled&&!this._albedoTexture.isReadyOrNotBlocking()||this._ambientTexture&&ht.a.AmbientTextureEnabled&&!this._ambientTexture.isReadyOrNotBlocking()||this._opacityTexture&&ht.a.OpacityTextureEnabled&&!this._opacityTexture.isReadyOrNotBlocking())return!1;var d=this._getReflectionTexture();if(d&&ht.a.ReflectionTextureEnabled&&(!d.isReadyOrNotBlocking()||d.irradianceTexture&&!d.irradianceTexture.isReadyOrNotBlocking())||this._lightmapTexture&&ht.a.LightmapTextureEnabled&&!this._lightmapTexture.isReadyOrNotBlocking()||this._emissiveTexture&&ht.a.EmissiveTextureEnabled&&!this._emissiveTexture.isReadyOrNotBlocking())return!1;if(ht.a.SpecularTextureEnabled){if(this._metallicTexture){if(!this._metallicTexture.isReadyOrNotBlocking())return!1}else if(this._reflectivityTexture&&!this._reflectivityTexture.isReadyOrNotBlocking())return!1;if(this._metallicReflectanceTexture&&!this._metallicReflectanceTexture.isReadyOrNotBlocking()||this._microSurfaceTexture&&!this._microSurfaceTexture.isReadyOrNotBlocking())return!1}if(s.getCaps().standardDerivatives&&this._bumpTexture&&ht.a.BumpTextureEnabled&&!this._disableBumpMap&&!this._bumpTexture.isReady()||this._environmentBRDFTexture&&ht.a.ReflectionTextureEnabled&&!this._environmentBRDFTexture.isReady())return!1}if(!(this.subSurface.isReadyForSubMesh(o,a)&&this.clearCoat.isReadyForSubMesh(o,a,s,this._disableBumpMap)&&this.sheen.isReadyForSubMesh(o,a)&&this.anisotropy.isReadyForSubMesh(o,a)&&this.detailMap.isReadyForSubMesh(o,a))||o._areImageProcessingDirty&&this._imageProcessingConfiguration&&!this._imageProcessingConfiguration.isReady())return!1;s.getCaps().standardDerivatives||e.isVerticesDataPresent(Oe.b.NormalKind)||(e.createNormals(!0),l.a.Warn("PBRMaterial: Normals have been created for the mesh: "+e.name));var p=n.effect,b=o._areLightsDisposed,P=this._prepareEffect(e,o,this.onCompiled,this.onError,i,null,n.getRenderingMesh().hasThinInstances);if(P)if(this._onEffectCreatedObservable&&(xr.effect=P,xr.subMesh=n,this._onEffectCreatedObservable.notifyObservers(xr)),this.allowShaderHotSwapping&&p&&!P.isReady()){if(P=p,this._rebuildInParallel=!0,o.markAsUnprocessed(),b)return o._areLightsDisposed=!0,!1}else this._rebuildInParallel=!1,a.resetCachedMaterial(),n.setEffect(P,o),this.buildUniformLayout();return!(!n.effect||!n.effect.isReady())&&(o._renderId=a.getRenderId(),n.effect._wasPreviouslyReady=!0,!0)},t.prototype.isMetallicWorkflow=function(){return!(this._metallic==null&&this._roughness==null&&!this._metallicTexture)},t.prototype._prepareEffect=function(e,n,i,o,a,s,d){if(i===void 0&&(i=null),o===void 0&&(o=null),a===void 0&&(a=null),s===void 0&&(s=null),this._prepareDefines(e,n,a,s,d),!n.isDirty)return null;n.markAsProcessed();var p=this.getScene().getEngine(),b=new Sr.a,P=0;n.USESPHERICALINVERTEX&&b.addFallback(P++,"USESPHERICALINVERTEX"),n.FOG&&b.addFallback(P,"FOG"),n.SPECULARAA&&b.addFallback(P,"SPECULARAA"),n.POINTSIZE&&b.addFallback(P,"POINTSIZE"),n.LOGARITHMICDEPTH&&b.addFallback(P,"LOGARITHMICDEPTH"),n.PARALLAX&&b.addFallback(P,"PARALLAX"),n.PARALLAXOCCLUSION&&b.addFallback(P++,"PARALLAXOCCLUSION"),P=Pr.AddFallbacks(n,b,P),P=Pr.AddFallbacks(n,b,P),P=lo.AddFallbacks(n,b,P),P=co.AddFallbacks(n,b,P),n.ENVIRONMENTBRDF&&b.addFallback(P++,"ENVIRONMENTBRDF"),n.TANGENT&&b.addFallback(P++,"TANGENT"),n.BUMP&&b.addFallback(P++,"BUMP"),P=et.a.HandleFallbacksForShadows(n,b,this._maxSimultaneousLights,P++),n.SPECULARTERM&&b.addFallback(P++,"SPECULARTERM"),n.USESPHERICALFROMREFLECTIONMAP&&b.addFallback(P++,"USESPHERICALFROMREFLECTIONMAP"),n.USEIRRADIANCEMAP&&b.addFallback(P++,"USEIRRADIANCEMAP"),n.LIGHTMAP&&b.addFallback(P++,"LIGHTMAP"),n.NORMAL&&b.addFallback(P++,"NORMAL"),n.AMBIENT&&b.addFallback(P++,"AMBIENT"),n.EMISSIVE&&b.addFallback(P++,"EMISSIVE"),n.VERTEXCOLOR&&b.addFallback(P++,"VERTEXCOLOR"),n.MORPHTARGETS&&b.addFallback(P++,"MORPHTARGETS"),n.MULTIVIEW&&b.addFallback(0,"MULTIVIEW");var O=[Oe.b.PositionKind];n.NORMAL&&O.push(Oe.b.NormalKind),n.TANGENT&&O.push(Oe.b.TangentKind),n.UV1&&O.push(Oe.b.UVKind),n.UV2&&O.push(Oe.b.UV2Kind),n.VERTEXCOLOR&&O.push(Oe.b.ColorKind),et.a.PrepareAttributesForBones(O,e,n,b),et.a.PrepareAttributesForInstances(O,n),et.a.PrepareAttributesForMorphTargets(O,e,n);var B="pbr",F=["world","view","viewProjection","vEyePosition","vLightsType","vAmbientColor","vAlbedoColor","vReflectivityColor","vMetallicReflectanceFactors","vEmissiveColor","visibility","vReflectionColor","vFogInfos","vFogColor","pointSize","vAlbedoInfos","vAmbientInfos","vOpacityInfos","vReflectionInfos","vReflectionPosition","vReflectionSize","vEmissiveInfos","vReflectivityInfos","vReflectionFilteringInfo","vMetallicReflectanceInfos","vMicroSurfaceSamplerInfos","vBumpInfos","vLightmapInfos","mBones","vClipPlane","vClipPlane2","vClipPlane3","vClipPlane4","vClipPlane5","vClipPlane6","albedoMatrix","ambientMatrix","opacityMatrix","reflectionMatrix","emissiveMatrix","reflectivityMatrix","normalMatrix","microSurfaceSamplerMatrix","bumpMatrix","lightmapMatrix","metallicReflectanceMatrix","vLightingIntensity","logarithmicDepthConstant","vSphericalX","vSphericalY","vSphericalZ","vSphericalXX_ZZ","vSphericalYY_ZZ","vSphericalZZ","vSphericalXY","vSphericalYZ","vSphericalZX","vSphericalL00","vSphericalL1_1","vSphericalL10","vSphericalL11","vSphericalL2_2","vSphericalL2_1","vSphericalL20","vSphericalL21","vSphericalL22","vReflectionMicrosurfaceInfos","vTangentSpaceParams","boneTextureWidth","vDebugMode"],z=["albedoSampler","reflectivitySampler","ambientSampler","emissiveSampler","bumpSampler","lightmapSampler","opacitySampler","reflectionSampler","reflectionSamplerLow","reflectionSamplerHigh","irradianceSampler","microSurfaceSampler","environmentBrdfSampler","boneSampler","metallicReflectanceSampler"],J=["Material","Scene"];ta.a.AddUniforms(F),ta.a.AddSamplers(z),lo.AddUniforms(F),lo.AddSamplers(z),Ar.AddUniforms(F),Ar.AddSamplers(z),Pr.AddUniforms(F),Pr.AddSamplers(z),co.AddUniforms(F),co.AddSamplers(z),Fs.a.AddUniforms(F),Fs.a.AddSamplers(F),yn.a&&(yn.a.PrepareUniforms(F,n),yn.a.PrepareSamplers(z,n)),et.a.PrepareUniformsAndSamplersList({uniformsNames:F,uniformBuffersNames:J,samplers:z,defines:n,maxSimultaneousLights:this._maxSimultaneousLights});var ie={};this.customShaderNameResolve&&(B=this.customShaderNameResolve(B,F,J,z,n,O,ie));var se=n.toString();return p.createEffect(B,{attributes:O,uniformsNames:F,uniformBuffersNames:J,samplers:z,defines:se,fallbacks:b,onCompiled:i,onError:o,indexParameters:{maxSimultaneousLights:this._maxSimultaneousLights,maxSimultaneousMorphTargets:n.NUM_MORPH_INFLUENCERS},processFinalCode:ie.processFinalCode,multiTarget:n.PREPASS},p)},t.prototype._prepareDefines=function(e,n,i,o,a){i===void 0&&(i=null),o===void 0&&(o=null),a===void 0&&(a=!1);var s=this.getScene(),d=s.getEngine();if(et.a.PrepareDefinesForLights(s,e,n,!0,this._maxSimultaneousLights,this._disableLighting),n._needNormals=!0,et.a.PrepareDefinesForMultiview(s,n),et.a.PrepareDefinesForPrePass(s,n,this.canRenderToMRT),n.METALLICWORKFLOW=this.isMetallicWorkflow(),n._areTexturesDirty){if(n._needUVs=!1,s.texturesEnabled){s.getEngine().getCaps().textureLOD&&(n.LODBASEDMICROSFURACE=!0),this._albedoTexture&&ht.a.DiffuseTextureEnabled?(et.a.PrepareDefinesForMergedUV(this._albedoTexture,n,"ALBEDO"),n.GAMMAALBEDO=this._albedoTexture.gammaSpace):n.ALBEDO=!1,this._ambientTexture&&ht.a.AmbientTextureEnabled?(et.a.PrepareDefinesForMergedUV(this._ambientTexture,n,"AMBIENT"),n.AMBIENTINGRAYSCALE=this._useAmbientInGrayScale):n.AMBIENT=!1,this._opacityTexture&&ht.a.OpacityTextureEnabled?(et.a.PrepareDefinesForMergedUV(this._opacityTexture,n,"OPACITY"),n.OPACITYRGB=this._opacityTexture.getAlphaFromRGB):n.OPACITY=!1;var p=this._getReflectionTexture();if(p&&ht.a.ReflectionTextureEnabled){switch(n.REFLECTION=!0,n.GAMMAREFLECTION=p.gammaSpace,n.RGBDREFLECTION=p.isRGBD,n.REFLECTIONMAP_OPPOSITEZ=this.getScene().useRightHandedSystem?!p.invertZ:p.invertZ,n.LODINREFLECTIONALPHA=p.lodLevelInAlpha,n.LINEARSPECULARREFLECTION=p.linearSpecularLOD,this.realTimeFiltering&&this.realTimeFilteringQuality>0?(n.NUM_SAMPLES=""+this.realTimeFilteringQuality,d.webGLVersion>1&&(n.NUM_SAMPLES=n.NUM_SAMPLES+"u"),n.REALTIME_FILTERING=!0):n.REALTIME_FILTERING=!1,p.coordinatesMode===we.a.INVCUBIC_MODE&&(n.INVERTCUBICMAP=!0),n.REFLECTIONMAP_3D=p.isCube,n.REFLECTIONMAP_CUBIC=!1,n.REFLECTIONMAP_EXPLICIT=!1,n.REFLECTIONMAP_PLANAR=!1,n.REFLECTIONMAP_PROJECTION=!1,n.REFLECTIONMAP_SKYBOX=!1,n.REFLECTIONMAP_SPHERICAL=!1,n.REFLECTIONMAP_EQUIRECTANGULAR=!1,n.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!1,n.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!1,p.coordinatesMode){case we.a.EXPLICIT_MODE:n.REFLECTIONMAP_EXPLICIT=!0;break;case we.a.PLANAR_MODE:n.REFLECTIONMAP_PLANAR=!0;break;case we.a.PROJECTION_MODE:n.REFLECTIONMAP_PROJECTION=!0;break;case we.a.SKYBOX_MODE:n.REFLECTIONMAP_SKYBOX=!0;break;case we.a.SPHERICAL_MODE:n.REFLECTIONMAP_SPHERICAL=!0;break;case we.a.EQUIRECTANGULAR_MODE:n.REFLECTIONMAP_EQUIRECTANGULAR=!0;break;case we.a.FIXED_EQUIRECTANGULAR_MODE:n.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!0;break;case we.a.FIXED_EQUIRECTANGULAR_MIRRORED_MODE:n.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!0;break;case we.a.CUBIC_MODE:case we.a.INVCUBIC_MODE:default:n.REFLECTIONMAP_CUBIC=!0,n.USE_LOCAL_REFLECTIONMAP_CUBIC=!!p.boundingBoxSize}p.coordinatesMode!==we.a.SKYBOX_MODE&&(p.irradianceTexture?(n.USEIRRADIANCEMAP=!0,n.USESPHERICALFROMREFLECTIONMAP=!1):p.isCube&&(n.USESPHERICALFROMREFLECTIONMAP=!0,n.USEIRRADIANCEMAP=!1,this._forceIrradianceInFragment||this.realTimeFiltering||s.getEngine().getCaps().maxVaryingVectors<=8?n.USESPHERICALINVERTEX=!1:n.USESPHERICALINVERTEX=!0))}else n.REFLECTION=!1,n.REFLECTIONMAP_3D=!1,n.REFLECTIONMAP_SPHERICAL=!1,n.REFLECTIONMAP_PLANAR=!1,n.REFLECTIONMAP_CUBIC=!1,n.USE_LOCAL_REFLECTIONMAP_CUBIC=!1,n.REFLECTIONMAP_PROJECTION=!1,n.REFLECTIONMAP_SKYBOX=!1,n.REFLECTIONMAP_EXPLICIT=!1,n.REFLECTIONMAP_EQUIRECTANGULAR=!1,n.REFLECTIONMAP_EQUIRECTANGULAR_FIXED=!1,n.REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED=!1,n.INVERTCUBICMAP=!1,n.USESPHERICALFROMREFLECTIONMAP=!1,n.USEIRRADIANCEMAP=!1,n.USESPHERICALINVERTEX=!1,n.REFLECTIONMAP_OPPOSITEZ=!1,n.LODINREFLECTIONALPHA=!1,n.GAMMAREFLECTION=!1,n.RGBDREFLECTION=!1,n.LINEARSPECULARREFLECTION=!1;this._lightmapTexture&&ht.a.LightmapTextureEnabled?(et.a.PrepareDefinesForMergedUV(this._lightmapTexture,n,"LIGHTMAP"),n.USELIGHTMAPASSHADOWMAP=this._useLightmapAsShadowmap,n.GAMMALIGHTMAP=this._lightmapTexture.gammaSpace,n.RGBDLIGHTMAP=this._lightmapTexture.isRGBD):n.LIGHTMAP=!1,this._emissiveTexture&&ht.a.EmissiveTextureEnabled?et.a.PrepareDefinesForMergedUV(this._emissiveTexture,n,"EMISSIVE"):n.EMISSIVE=!1,ht.a.SpecularTextureEnabled?(this._metallicTexture?(et.a.PrepareDefinesForMergedUV(this._metallicTexture,n,"REFLECTIVITY"),n.ROUGHNESSSTOREINMETALMAPALPHA=this._useRoughnessFromMetallicTextureAlpha,n.ROUGHNESSSTOREINMETALMAPGREEN=!this._useRoughnessFromMetallicTextureAlpha&&this._useRoughnessFromMetallicTextureGreen,n.METALLNESSSTOREINMETALMAPBLUE=this._useMetallnessFromMetallicTextureBlue,n.AOSTOREINMETALMAPRED=this._useAmbientOcclusionFromMetallicTextureRed):this._reflectivityTexture?(et.a.PrepareDefinesForMergedUV(this._reflectivityTexture,n,"REFLECTIVITY"),n.MICROSURFACEFROMREFLECTIVITYMAP=this._useMicroSurfaceFromReflectivityMapAlpha,n.MICROSURFACEAUTOMATIC=this._useAutoMicroSurfaceFromReflectivityMap):n.REFLECTIVITY=!1,this._metallicReflectanceTexture?et.a.PrepareDefinesForMergedUV(this._metallicReflectanceTexture,n,"METALLIC_REFLECTANCE"):n.METALLIC_REFLECTANCE=!1,this._microSurfaceTexture?et.a.PrepareDefinesForMergedUV(this._microSurfaceTexture,n,"MICROSURFACEMAP"):n.MICROSURFACEMAP=!1):(n.REFLECTIVITY=!1,n.MICROSURFACEMAP=!1),s.getEngine().getCaps().standardDerivatives&&this._bumpTexture&&ht.a.BumpTextureEnabled&&!this._disableBumpMap?(et.a.PrepareDefinesForMergedUV(this._bumpTexture,n,"BUMP"),this._useParallax&&this._albedoTexture&&ht.a.DiffuseTextureEnabled?(n.PARALLAX=!0,n.PARALLAXOCCLUSION=!!this._useParallaxOcclusion):n.PARALLAX=!1,n.OBJECTSPACE_NORMALMAP=this._useObjectSpaceNormalMap):n.BUMP=!1,this._environmentBRDFTexture&&ht.a.ReflectionTextureEnabled?(n.ENVIRONMENTBRDF=!0,n.ENVIRONMENTBRDF_RGBD=this._environmentBRDFTexture.isRGBD):(n.ENVIRONMENTBRDF=!1,n.ENVIRONMENTBRDF_RGBD=!1),this._shouldUseAlphaFromAlbedoTexture()?n.ALPHAFROMALBEDO=!0:n.ALPHAFROMALBEDO=!1}n.SPECULAROVERALPHA=this._useSpecularOverAlpha,this._lightFalloff===t.LIGHTFALLOFF_STANDARD?(n.USEPHYSICALLIGHTFALLOFF=!1,n.USEGLTFLIGHTFALLOFF=!1):this._lightFalloff===t.LIGHTFALLOFF_GLTF?(n.USEPHYSICALLIGHTFALLOFF=!1,n.USEGLTFLIGHTFALLOFF=!0):(n.USEPHYSICALLIGHTFALLOFF=!0,n.USEGLTFLIGHTFALLOFF=!1),n.RADIANCEOVERALPHA=this._useRadianceOverAlpha,!this.backFaceCulling&&this._twoSidedLighting?n.TWOSIDEDLIGHTING=!0:n.TWOSIDEDLIGHTING=!1,n.SPECULARAA=s.getEngine().getCaps().standardDerivatives&&this._enableSpecularAntiAliasing}(n._areTexturesDirty||n._areMiscDirty)&&(n.ALPHATESTVALUE=this._alphaCutOff+(this._alphaCutOff%1==0?".":""),n.PREMULTIPLYALPHA=this.alphaMode===h.a.ALPHA_PREMULTIPLIED||this.alphaMode===h.a.ALPHA_PREMULTIPLIED_PORTERDUFF,n.ALPHABLEND=this.needAlphaBlendingForMesh(e),n.ALPHAFRESNEL=this._useAlphaFresnel||this._useLinearAlphaFresnel,n.LINEARALPHAFRESNEL=this._useLinearAlphaFresnel),n._areImageProcessingDirty&&this._imageProcessingConfiguration&&this._imageProcessingConfiguration.prepareDefines(n),n.FORCENORMALFORWARD=this._forceNormalForward,n.RADIANCEOCCLUSION=this._useRadianceOcclusion,n.HORIZONOCCLUSION=this._useHorizonOcclusion,n._areMiscDirty&&(et.a.PrepareDefinesForMisc(e,s,this._useLogarithmicDepth,this.pointsCloud,this.fogEnabled,this._shouldTurnAlphaTestOn(e)||this._forceAlphaTest,n),n.UNLIT=this._unlit||(this.pointsCloud||this.wireframe)&&!e.isVerticesDataPresent(Oe.b.NormalKind),n.DEBUGMODE=this._debugMode),this.detailMap.prepareDefines(n,s),this.subSurface.prepareDefines(n,s),this.clearCoat.prepareDefines(n,s),this.anisotropy.prepareDefines(n,e,s),this.brdf.prepareDefines(n),this.sheen.prepareDefines(n,s),et.a.PrepareDefinesForFrameBoundValues(s,d,n,!!i,o,a),et.a.PrepareDefinesForAttributes(e,n,!0,!0,!0,this._transparencyMode!==t.PBRMATERIAL_OPAQUE)},t.prototype.forceCompilation=function(e,n,i){var o=this,a=Object(c.a)({clipPlane:!1,useInstances:!1},i),s=new Bs,d=this._prepareEffect(e,s,void 0,void 0,a.useInstances,a.clipPlane,e.hasThinInstances);this._onEffectCreatedObservable&&(xr.effect=d,xr.subMesh=null,this._onEffectCreatedObservable.notifyObservers(xr)),d.isReady()?n&&n(this):d.onCompileObservable.add(function(){n&&n(o)})},t.prototype.buildUniformLayout=function(){var e=this._uniformBuffer;e.addUniform("vAlbedoInfos",2),e.addUniform("vAmbientInfos",4),e.addUniform("vOpacityInfos",2),e.addUniform("vEmissiveInfos",2),e.addUniform("vLightmapInfos",2),e.addUniform("vReflectivityInfos",3),e.addUniform("vMicroSurfaceSamplerInfos",2),e.addUniform("vReflectionInfos",2),e.addUniform("vReflectionFilteringInfo",2),e.addUniform("vReflectionPosition",3),e.addUniform("vReflectionSize",3),e.addUniform("vBumpInfos",3),e.addUniform("albedoMatrix",16),e.addUniform("ambientMatrix",16),e.addUniform("opacityMatrix",16),e.addUniform("emissiveMatrix",16),e.addUniform("lightmapMatrix",16),e.addUniform("reflectivityMatrix",16),e.addUniform("microSurfaceSamplerMatrix",16),e.addUniform("bumpMatrix",16),e.addUniform("vTangentSpaceParams",2),e.addUniform("reflectionMatrix",16),e.addUniform("vReflectionColor",3),e.addUniform("vAlbedoColor",4),e.addUniform("vLightingIntensity",4),e.addUniform("vReflectionMicrosurfaceInfos",3),e.addUniform("pointSize",1),e.addUniform("vReflectivityColor",4),e.addUniform("vEmissiveColor",3),e.addUniform("visibility",1),e.addUniform("vMetallicReflectanceFactors",4),e.addUniform("vMetallicReflectanceInfos",2),e.addUniform("metallicReflectanceMatrix",16),Ar.PrepareUniformBuffer(e),Pr.PrepareUniformBuffer(e),co.PrepareUniformBuffer(e),lo.PrepareUniformBuffer(e),ta.a.PrepareUniformBuffer(e),e.create()},t.prototype.unbind=function(){if(this._activeEffect){var e=!1;this._reflectionTexture&&this._reflectionTexture.isRenderTarget&&(this._activeEffect.setTexture("reflection2DSampler",null),e=!0),this.subSurface.unbind(this._activeEffect)&&(e=!0),e&&this._markAllSubMeshesAsTexturesDirty()}r.prototype.unbind.call(this)},t.prototype.bindForSubMesh=function(e,n,i){var o=this.getScene(),a=i._materialDefines;if(a){var s=i.effect;if(s){this._activeEffect=s,a.INSTANCES&&!a.THIN_INSTANCES||this.bindOnlyWorldMatrix(e),this.prePassConfiguration.bindForSubMesh(this._activeEffect,o,n,e,this.isFrozen),a.OBJECTSPACE_NORMALMAP&&(e.toNormalMatrix(this._normalMatrix),this.bindOnlyNormalMatrix(this._normalMatrix));var d=this._mustRebind(o,s,n.visibility);et.a.BindBonesParameters(n,this._activeEffect,this.prePassConfiguration);var p=null,b=this._uniformBuffer;if(d){var P=o.getEngine();if(b.bindToEffect(s,"Material"),this.bindViewProjection(s),p=this._getReflectionTexture(),!b.useUbo||!this.isFrozen||!b.isSync){if(o.texturesEnabled){if(this._albedoTexture&&ht.a.DiffuseTextureEnabled&&(b.updateFloat2("vAlbedoInfos",this._albedoTexture.coordinatesIndex,this._albedoTexture.level),et.a.BindTextureMatrix(this._albedoTexture,b,"albedo")),this._ambientTexture&&ht.a.AmbientTextureEnabled&&(b.updateFloat4("vAmbientInfos",this._ambientTexture.coordinatesIndex,this._ambientTexture.level,this._ambientTextureStrength,this._ambientTextureImpactOnAnalyticalLights),et.a.BindTextureMatrix(this._ambientTexture,b,"ambient")),this._opacityTexture&&ht.a.OpacityTextureEnabled&&(b.updateFloat2("vOpacityInfos",this._opacityTexture.coordinatesIndex,this._opacityTexture.level),et.a.BindTextureMatrix(this._opacityTexture,b,"opacity")),p&&ht.a.ReflectionTextureEnabled){if(b.updateMatrix("reflectionMatrix",p.getReflectionTextureMatrix()),b.updateFloat2("vReflectionInfos",p.level,0),p.boundingBoxSize){var O=p;b.updateVector3("vReflectionPosition",O.boundingBoxPosition),b.updateVector3("vReflectionSize",O.boundingBoxSize)}if(this.realTimeFiltering){var B=p.getSize().width;b.updateFloat2("vReflectionFilteringInfo",B,$.a.Log2(B))}if(!a.USEIRRADIANCEMAP){var F=p.sphericalPolynomial;if(a.USESPHERICALFROMREFLECTIONMAP&&F)if(a.SPHERICAL_HARMONICS){var z=F.preScaledHarmonics;this._activeEffect.setVector3("vSphericalL00",z.l00),this._activeEffect.setVector3("vSphericalL1_1",z.l1_1),this._activeEffect.setVector3("vSphericalL10",z.l10),this._activeEffect.setVector3("vSphericalL11",z.l11),this._activeEffect.setVector3("vSphericalL2_2",z.l2_2),this._activeEffect.setVector3("vSphericalL2_1",z.l2_1),this._activeEffect.setVector3("vSphericalL20",z.l20),this._activeEffect.setVector3("vSphericalL21",z.l21),this._activeEffect.setVector3("vSphericalL22",z.l22)}else this._activeEffect.setFloat3("vSphericalX",F.x.x,F.x.y,F.x.z),this._activeEffect.setFloat3("vSphericalY",F.y.x,F.y.y,F.y.z),this._activeEffect.setFloat3("vSphericalZ",F.z.x,F.z.y,F.z.z),this._activeEffect.setFloat3("vSphericalXX_ZZ",F.xx.x-F.zz.x,F.xx.y-F.zz.y,F.xx.z-F.zz.z),this._activeEffect.setFloat3("vSphericalYY_ZZ",F.yy.x-F.zz.x,F.yy.y-F.zz.y,F.yy.z-F.zz.z),this._activeEffect.setFloat3("vSphericalZZ",F.zz.x,F.zz.y,F.zz.z),this._activeEffect.setFloat3("vSphericalXY",F.xy.x,F.xy.y,F.xy.z),this._activeEffect.setFloat3("vSphericalYZ",F.yz.x,F.yz.y,F.yz.z),this._activeEffect.setFloat3("vSphericalZX",F.zx.x,F.zx.y,F.zx.z)}b.updateFloat3("vReflectionMicrosurfaceInfos",p.getSize().width,p.lodGenerationScale,p.lodGenerationOffset)}this._emissiveTexture&&ht.a.EmissiveTextureEnabled&&(b.updateFloat2("vEmissiveInfos",this._emissiveTexture.coordinatesIndex,this._emissiveTexture.level),et.a.BindTextureMatrix(this._emissiveTexture,b,"emissive")),this._lightmapTexture&&ht.a.LightmapTextureEnabled&&(b.updateFloat2("vLightmapInfos",this._lightmapTexture.coordinatesIndex,this._lightmapTexture.level),et.a.BindTextureMatrix(this._lightmapTexture,b,"lightmap")),ht.a.SpecularTextureEnabled&&(this._metallicTexture?(b.updateFloat3("vReflectivityInfos",this._metallicTexture.coordinatesIndex,this._metallicTexture.level,this._ambientTextureStrength),et.a.BindTextureMatrix(this._metallicTexture,b,"reflectivity")):this._reflectivityTexture&&(b.updateFloat3("vReflectivityInfos",this._reflectivityTexture.coordinatesIndex,this._reflectivityTexture.level,1),et.a.BindTextureMatrix(this._reflectivityTexture,b,"reflectivity")),this._metallicReflectanceTexture&&(b.updateFloat2("vMetallicReflectanceInfos",this._metallicReflectanceTexture.coordinatesIndex,this._metallicReflectanceTexture.level),et.a.BindTextureMatrix(this._metallicReflectanceTexture,b,"metallicReflectance")),this._microSurfaceTexture&&(b.updateFloat2("vMicroSurfaceSamplerInfos",this._microSurfaceTexture.coordinatesIndex,this._microSurfaceTexture.level),et.a.BindTextureMatrix(this._microSurfaceTexture,b,"microSurfaceSampler"))),this._bumpTexture&&P.getCaps().standardDerivatives&&ht.a.BumpTextureEnabled&&!this._disableBumpMap&&(b.updateFloat3("vBumpInfos",this._bumpTexture.coordinatesIndex,this._bumpTexture.level,this._parallaxScaleBias),et.a.BindTextureMatrix(this._bumpTexture,b,"bump"),o._mirroredCameraPosition?b.updateFloat2("vTangentSpaceParams",this._invertNormalMapX?1:-1,this._invertNormalMapY?1:-1):b.updateFloat2("vTangentSpaceParams",this._invertNormalMapX?-1:1,this._invertNormalMapY?-1:1))}if(this.pointsCloud&&b.updateFloat("pointSize",this.pointSize),a.METALLICWORKFLOW){M.c.Color3[0].r=this._metallic===void 0||this._metallic===null?1:this._metallic,M.c.Color3[0].g=this._roughness===void 0||this._roughness===null?1:this._roughness,b.updateColor4("vReflectivityColor",M.c.Color3[0],1);var J=this.subSurface.indexOfRefraction,ie=Math.pow((J-1)/(J+1),2);this._metallicReflectanceColor.scaleToRef(ie*this._metallicF0Factor,M.c.Color3[0]);var se=this._metallicF0Factor;b.updateColor4("vMetallicReflectanceFactors",M.c.Color3[0],se)}else b.updateColor4("vReflectivityColor",this._reflectivityColor,this._microSurface);b.updateColor3("vEmissiveColor",ht.a.EmissiveTextureEnabled?this._emissiveColor:M.a.BlackReadOnly),b.updateColor3("vReflectionColor",this._reflectionColor),!a.SS_REFRACTION&&this.subSurface.linkRefractionWithTransparency?b.updateColor4("vAlbedoColor",this._albedoColor,1):b.updateColor4("vAlbedoColor",this._albedoColor,this.alpha),this._lightingInfos.x=this._directIntensity,this._lightingInfos.y=this._emissiveIntensity,this._lightingInfos.z=this._environmentIntensity*o.environmentIntensity,this._lightingInfos.w=this._specularIntensity,b.updateVector4("vLightingIntensity",this._lightingInfos)}b.updateFloat("visibility",n.visibility),o.texturesEnabled&&(this._albedoTexture&&ht.a.DiffuseTextureEnabled&&b.setTexture("albedoSampler",this._albedoTexture),this._ambientTexture&&ht.a.AmbientTextureEnabled&&b.setTexture("ambientSampler",this._ambientTexture),this._opacityTexture&&ht.a.OpacityTextureEnabled&&b.setTexture("opacitySampler",this._opacityTexture),p&&ht.a.ReflectionTextureEnabled&&(a.LODBASEDMICROSFURACE?b.setTexture("reflectionSampler",p):(b.setTexture("reflectionSampler",p._lodTextureMid||p),b.setTexture("reflectionSamplerLow",p._lodTextureLow||p),b.setTexture("reflectionSamplerHigh",p._lodTextureHigh||p)),a.USEIRRADIANCEMAP&&b.setTexture("irradianceSampler",p.irradianceTexture)),a.ENVIRONMENTBRDF&&b.setTexture("environmentBrdfSampler",this._environmentBRDFTexture),this._emissiveTexture&&ht.a.EmissiveTextureEnabled&&b.setTexture("emissiveSampler",this._emissiveTexture),this._lightmapTexture&&ht.a.LightmapTextureEnabled&&b.setTexture("lightmapSampler",this._lightmapTexture),ht.a.SpecularTextureEnabled&&(this._metallicTexture?b.setTexture("reflectivitySampler",this._metallicTexture):this._reflectivityTexture&&b.setTexture("reflectivitySampler",this._reflectivityTexture),this._metallicReflectanceTexture&&b.setTexture("metallicReflectanceSampler",this._metallicReflectanceTexture),this._microSurfaceTexture&&b.setTexture("microSurfaceSampler",this._microSurfaceTexture)),this._bumpTexture&&P.getCaps().standardDerivatives&&ht.a.BumpTextureEnabled&&!this._disableBumpMap&&b.setTexture("bumpSampler",this._bumpTexture)),this.detailMap.bindForSubMesh(b,o,this.isFrozen),this.subSurface.bindForSubMesh(b,o,P,this.isFrozen,a.LODBASEDMICROSFURACE,this.realTimeFiltering),this.clearCoat.bindForSubMesh(b,o,P,this._disableBumpMap,this.isFrozen,this._invertNormalMapX,this._invertNormalMapY,i),this.anisotropy.bindForSubMesh(b,o,this.isFrozen),this.sheen.bindForSubMesh(b,o,this.isFrozen,i),et.a.BindClipPlane(this._activeEffect,o),o.ambientColor.multiplyToRef(this._ambientColor,this._globalAmbientColor);var ce=o._forcedViewPosition?o._forcedViewPosition:o._mirroredCameraPosition?o._mirroredCameraPosition:o.activeCamera.globalPosition,ue=o.useRightHandedSystem===(o._mirroredCameraPosition!=null);s.setFloat4("vEyePosition",ce.x,ce.y,ce.z,ue?-1:1),s.setColor3("vAmbientColor",this._globalAmbientColor),s.setFloat2("vDebugMode",this.debugLimit,this.debugFactor)}!d&&this.isFrozen||(o.lightsEnabled&&!this._disableLighting&&et.a.BindLights(o,n,this._activeEffect,a,this._maxSimultaneousLights,this._rebuildInParallel),(o.fogEnabled&&n.applyFog&&o.fogMode!==_e.a.FOGMODE_NONE||p)&&this.bindView(s),et.a.BindFogParameters(o,n,this._activeEffect,!0),a.NUM_MORPH_INFLUENCERS&&et.a.BindMorphTargetParameters(n,this._activeEffect),this._imageProcessingConfiguration.bind(this._activeEffect),et.a.BindLogDepth(a,this._activeEffect,o)),b.update(),this._afterBind(n,this._activeEffect)}}},t.prototype.getAnimatables=function(){var e=[];return this._albedoTexture&&this._albedoTexture.animations&&this._albedoTexture.animations.length>0&&e.push(this._albedoTexture),this._ambientTexture&&this._ambientTexture.animations&&this._ambientTexture.animations.length>0&&e.push(this._ambientTexture),this._opacityTexture&&this._opacityTexture.animations&&this._opacityTexture.animations.length>0&&e.push(this._opacityTexture),this._reflectionTexture&&this._reflectionTexture.animations&&this._reflectionTexture.animations.length>0&&e.push(this._reflectionTexture),this._emissiveTexture&&this._emissiveTexture.animations&&this._emissiveTexture.animations.length>0&&e.push(this._emissiveTexture),this._metallicTexture&&this._metallicTexture.animations&&this._metallicTexture.animations.length>0?e.push(this._metallicTexture):this._reflectivityTexture&&this._reflectivityTexture.animations&&this._reflectivityTexture.animations.length>0&&e.push(this._reflectivityTexture),this._bumpTexture&&this._bumpTexture.animations&&this._bumpTexture.animations.length>0&&e.push(this._bumpTexture),this._lightmapTexture&&this._lightmapTexture.animations&&this._lightmapTexture.animations.length>0&&e.push(this._lightmapTexture),this.detailMap.getAnimatables(e),this.subSurface.getAnimatables(e),this.clearCoat.getAnimatables(e),this.sheen.getAnimatables(e),this.anisotropy.getAnimatables(e),e},t.prototype._getReflectionTexture=function(){return this._reflectionTexture?this._reflectionTexture:this.getScene().environmentTexture},t.prototype.getActiveTextures=function(){var e=r.prototype.getActiveTextures.call(this);return this._albedoTexture&&e.push(this._albedoTexture),this._ambientTexture&&e.push(this._ambientTexture),this._opacityTexture&&e.push(this._opacityTexture),this._reflectionTexture&&e.push(this._reflectionTexture),this._emissiveTexture&&e.push(this._emissiveTexture),this._reflectivityTexture&&e.push(this._reflectivityTexture),this._metallicTexture&&e.push(this._metallicTexture),this._metallicReflectanceTexture&&e.push(this._metallicReflectanceTexture),this._microSurfaceTexture&&e.push(this._microSurfaceTexture),this._bumpTexture&&e.push(this._bumpTexture),this._lightmapTexture&&e.push(this._lightmapTexture),this.detailMap.getActiveTextures(e),this.subSurface.getActiveTextures(e),this.clearCoat.getActiveTextures(e),this.sheen.getActiveTextures(e),this.anisotropy.getActiveTextures(e),e},t.prototype.hasTexture=function(e){return!!r.prototype.hasTexture.call(this,e)||this._albedoTexture===e||this._ambientTexture===e||this._opacityTexture===e||this._reflectionTexture===e||this._reflectivityTexture===e||this._metallicTexture===e||this._metallicReflectanceTexture===e||this._microSurfaceTexture===e||this._bumpTexture===e||this._lightmapTexture===e||this.detailMap.hasTexture(e)||this.subSurface.hasTexture(e)||this.clearCoat.hasTexture(e)||this.sheen.hasTexture(e)||this.anisotropy.hasTexture(e)},t.prototype.setPrePassRenderer=function(e){if(this.subSurface.isScatteringEnabled){var n=this.getScene().enableSubSurfaceForPrePass();return n&&(n.enabled=!0),!0}return!1},t.prototype.dispose=function(e,n){var i,o,a,s,d,p,b,P,O,B,F;n&&(this._environmentBRDFTexture&&this.getScene().environmentBRDFTexture!==this._environmentBRDFTexture&&this._environmentBRDFTexture.dispose(),(i=this._albedoTexture)===null||i===void 0||i.dispose(),(o=this._ambientTexture)===null||o===void 0||o.dispose(),(a=this._opacityTexture)===null||a===void 0||a.dispose(),(s=this._reflectionTexture)===null||s===void 0||s.dispose(),(d=this._emissiveTexture)===null||d===void 0||d.dispose(),(p=this._metallicTexture)===null||p===void 0||p.dispose(),(b=this._reflectivityTexture)===null||b===void 0||b.dispose(),(P=this._bumpTexture)===null||P===void 0||P.dispose(),(O=this._lightmapTexture)===null||O===void 0||O.dispose(),(B=this._metallicReflectanceTexture)===null||B===void 0||B.dispose(),(F=this._microSurfaceTexture)===null||F===void 0||F.dispose()),this.detailMap.dispose(n),this.subSurface.dispose(n),this.clearCoat.dispose(n),this.sheen.dispose(n),this.anisotropy.dispose(n),this._renderTargets.dispose(),this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),r.prototype.dispose.call(this,e,n)},t.PBRMATERIAL_OPAQUE=Ht.a.MATERIAL_OPAQUE,t.PBRMATERIAL_ALPHATEST=Ht.a.MATERIAL_ALPHATEST,t.PBRMATERIAL_ALPHABLEND=Ht.a.MATERIAL_ALPHABLEND,t.PBRMATERIAL_ALPHATESTANDBLEND=Ht.a.MATERIAL_ALPHATESTANDBLEND,t.DEFAULT_AO_ON_ANALYTICAL_LIGHTS=0,t.LIGHTFALLOFF_PHYSICAL=0,t.LIGHTFALLOFF_GLTF=1,t.LIGHTFALLOFF_STANDARD=2,Object(c.c)([Object(L.i)()],t.prototype,"_imageProcessingConfiguration",void 0),Object(c.c)([Object(L.b)("_markAllSubMeshesAsMiscDirty")],t.prototype,"debugMode",void 0),Object(c.c)([Object(L.c)()],t.prototype,"useLogarithmicDepth",null),t}($o.a),uo=function(r){function t(e,n){var i=r.call(this,e,n)||this;return i.directIntensity=1,i.emissiveIntensity=1,i.environmentIntensity=1,i.specularIntensity=1,i.disableBumpMap=!1,i.ambientTextureStrength=1,i.ambientTextureImpactOnAnalyticalLights=t.DEFAULT_AO_ON_ANALYTICAL_LIGHTS,i.metallicF0Factor=1,i.metallicReflectanceColor=M.a.White(),i.ambientColor=new M.a(0,0,0),i.albedoColor=new M.a(1,1,1),i.reflectivityColor=new M.a(1,1,1),i.reflectionColor=new M.a(1,1,1),i.emissiveColor=new M.a(0,0,0),i.microSurface=1,i.useLightmapAsShadowmap=!1,i.useAlphaFromAlbedoTexture=!1,i.forceAlphaTest=!1,i.alphaCutOff=.4,i.useSpecularOverAlpha=!0,i.useMicroSurfaceFromReflectivityMapAlpha=!1,i.useRoughnessFromMetallicTextureAlpha=!0,i.useRoughnessFromMetallicTextureGreen=!1,i.useMetallnessFromMetallicTextureBlue=!1,i.useAmbientOcclusionFromMetallicTextureRed=!1,i.useAmbientInGrayScale=!1,i.useAutoMicroSurfaceFromReflectivityMap=!1,i.useRadianceOverAlpha=!0,i.useObjectSpaceNormalMap=!1,i.useParallax=!1,i.useParallaxOcclusion=!1,i.parallaxScaleBias=.05,i.disableLighting=!1,i.forceIrradianceInFragment=!1,i.maxSimultaneousLights=4,i.invertNormalMapX=!1,i.invertNormalMapY=!1,i.twoSidedLighting=!1,i.useAlphaFresnel=!1,i.useLinearAlphaFresnel=!1,i.environmentBRDFTexture=null,i.forceNormalForward=!1,i.enableSpecularAntiAliasing=!1,i.useHorizonOcclusion=!0,i.useRadianceOcclusion=!0,i.unlit=!1,i._environmentBRDFTexture=ea.GetEnvironmentBRDFTexture(n),i}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"refractionTexture",{get:function(){return this.subSurface.refractionTexture},set:function(e){this.subSurface.refractionTexture=e,e?this.subSurface.isRefractionEnabled=!0:this.subSurface.linkRefractionWithTransparency||(this.subSurface.isRefractionEnabled=!1)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"indexOfRefraction",{get:function(){return this.subSurface.indexOfRefraction},set:function(e){this.subSurface.indexOfRefraction=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"invertRefractionY",{get:function(){return this.subSurface.invertRefractionY},set:function(e){this.subSurface.invertRefractionY=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"linkRefractionWithTransparency",{get:function(){return this.subSurface.linkRefractionWithTransparency},set:function(e){this.subSurface.linkRefractionWithTransparency=e,e&&(this.subSurface.isRefractionEnabled=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"usePhysicalLightFalloff",{get:function(){return this._lightFalloff===_n.LIGHTFALLOFF_PHYSICAL},set:function(e){e!==this.usePhysicalLightFalloff&&(this._markAllSubMeshesAsTexturesDirty(),this._lightFalloff=e?_n.LIGHTFALLOFF_PHYSICAL:_n.LIGHTFALLOFF_STANDARD)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"useGLTFLightFalloff",{get:function(){return this._lightFalloff===_n.LIGHTFALLOFF_GLTF},set:function(e){e!==this.useGLTFLightFalloff&&(this._markAllSubMeshesAsTexturesDirty(),this._lightFalloff=e?_n.LIGHTFALLOFF_GLTF:_n.LIGHTFALLOFF_STANDARD)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"imageProcessingConfiguration",{get:function(){return this._imageProcessingConfiguration},set:function(e){this._attachImageProcessingConfiguration(e),this._markAllSubMeshesAsTexturesDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorCurvesEnabled",{get:function(){return this.imageProcessingConfiguration.colorCurvesEnabled},set:function(e){this.imageProcessingConfiguration.colorCurvesEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorGradingEnabled",{get:function(){return this.imageProcessingConfiguration.colorGradingEnabled},set:function(e){this.imageProcessingConfiguration.colorGradingEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraToneMappingEnabled",{get:function(){return this._imageProcessingConfiguration.toneMappingEnabled},set:function(e){this._imageProcessingConfiguration.toneMappingEnabled=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraExposure",{get:function(){return this._imageProcessingConfiguration.exposure},set:function(e){this._imageProcessingConfiguration.exposure=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraContrast",{get:function(){return this._imageProcessingConfiguration.contrast},set:function(e){this._imageProcessingConfiguration.contrast=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorGradingTexture",{get:function(){return this._imageProcessingConfiguration.colorGradingTexture},set:function(e){this._imageProcessingConfiguration.colorGradingTexture=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraColorCurves",{get:function(){return this._imageProcessingConfiguration.colorCurves},set:function(e){this._imageProcessingConfiguration.colorCurves=e},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"PBRMaterial"},t.prototype.clone=function(e){var n=this,i=L.a.Clone(function(){return new t(e,n.getScene())},this);return i.id=e,i.name=e,this.clearCoat.copyTo(i.clearCoat),this.anisotropy.copyTo(i.anisotropy),this.brdf.copyTo(i.brdf),this.sheen.copyTo(i.sheen),this.subSurface.copyTo(i.subSurface),i},t.prototype.serialize=function(){var e=L.a.Serialize(this);return e.customType="BABYLON.PBRMaterial",e.clearCoat=this.clearCoat.serialize(),e.anisotropy=this.anisotropy.serialize(),e.brdf=this.brdf.serialize(),e.sheen=this.sheen.serialize(),e.subSurface=this.subSurface.serialize(),e},t.Parse=function(e,n,i){var o=L.a.Parse(function(){return new t(e.name,n)},e,n,i);return e.clearCoat&&o.clearCoat.parse(e.clearCoat,n,i),e.anisotropy&&o.anisotropy.parse(e.anisotropy,n,i),e.brdf&&o.brdf.parse(e.brdf,n,i),e.sheen&&o.sheen.parse(e.sheen,n,i),e.subSurface&&o.subSurface.parse(e.subSurface,n,i),o},t.PBRMATERIAL_OPAQUE=_n.PBRMATERIAL_OPAQUE,t.PBRMATERIAL_ALPHATEST=_n.PBRMATERIAL_ALPHATEST,t.PBRMATERIAL_ALPHABLEND=_n.PBRMATERIAL_ALPHABLEND,t.PBRMATERIAL_ALPHATESTANDBLEND=_n.PBRMATERIAL_ALPHATESTANDBLEND,t.DEFAULT_AO_ON_ANALYTICAL_LIGHTS=_n.DEFAULT_AO_ON_ANALYTICAL_LIGHTS,Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"directIntensity",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"emissiveIntensity",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"environmentIntensity",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"specularIntensity",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"disableBumpMap",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"albedoTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"ambientTexture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"ambientTextureStrength",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"ambientTextureImpactOnAnalyticalLights",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesAndMiscDirty")],t.prototype,"opacityTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"emissiveTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectivityTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"metallicTexture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"metallic",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"roughness",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"metallicF0Factor",void 0),Object(c.c)([Object(L.e)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"metallicReflectanceColor",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"metallicReflectanceTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"microSurfaceTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"bumpTexture",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty",null)],t.prototype,"lightmapTexture",void 0),Object(c.c)([Object(L.e)("ambient"),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"ambientColor",void 0),Object(c.c)([Object(L.e)("albedo"),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"albedoColor",void 0),Object(c.c)([Object(L.e)("reflectivity"),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectivityColor",void 0),Object(c.c)([Object(L.e)("reflection"),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"reflectionColor",void 0),Object(c.c)([Object(L.e)("emissive"),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"emissiveColor",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"microSurface",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useLightmapAsShadowmap",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesAndMiscDirty")],t.prototype,"useAlphaFromAlbedoTexture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesAndMiscDirty")],t.prototype,"forceAlphaTest",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesAndMiscDirty")],t.prototype,"alphaCutOff",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useSpecularOverAlpha",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useMicroSurfaceFromReflectivityMapAlpha",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useRoughnessFromMetallicTextureAlpha",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useRoughnessFromMetallicTextureGreen",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useMetallnessFromMetallicTextureBlue",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useAmbientOcclusionFromMetallicTextureRed",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useAmbientInGrayScale",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useAutoMicroSurfaceFromReflectivityMap",void 0),Object(c.c)([Object(L.c)()],t.prototype,"usePhysicalLightFalloff",null),Object(c.c)([Object(L.c)()],t.prototype,"useGLTFLightFalloff",null),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useRadianceOverAlpha",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useObjectSpaceNormalMap",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useParallax",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useParallaxOcclusion",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"parallaxScaleBias",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsLightsDirty")],t.prototype,"disableLighting",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"forceIrradianceInFragment",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsLightsDirty")],t.prototype,"maxSimultaneousLights",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"invertNormalMapX",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"invertNormalMapY",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"twoSidedLighting",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useAlphaFresnel",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useLinearAlphaFresnel",void 0),Object(c.c)([Object(L.m)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"environmentBRDFTexture",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"forceNormalForward",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"enableSpecularAntiAliasing",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useHorizonOcclusion",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty")],t.prototype,"useRadianceOcclusion",void 0),Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsMiscDirty")],t.prototype,"unlit",void 0),t}(_n);R.a.RegisteredTypes["BABYLON.PBRMaterial"]=uo;function na(r){return r.charCodeAt(0)+(r.charCodeAt(1)<<8)+(r.charCodeAt(2)<<16)+(r.charCodeAt(3)<<24)}var mu=na("DXT1"),gu=na("DXT3"),vu=na("DXT5"),Us=na("DX10"),Gi=function(){function r(){}return r.GetDDSInfo=function(t){var e=new Int32Array(t.buffer,t.byteOffset,31),n=new Int32Array(t.buffer,t.byteOffset,35),i=1;131072&e[2]&&(i=Math.max(1,e[7]));var o=e[21],a=o===Us?n[32]:0,s=h.a.TEXTURETYPE_UNSIGNED_INT;switch(o){case 113:s=h.a.TEXTURETYPE_HALF_FLOAT;break;case 116:s=h.a.TEXTURETYPE_FLOAT;break;case Us:if(a===10){s=h.a.TEXTURETYPE_HALF_FLOAT;break}if(a===2){s=h.a.TEXTURETYPE_FLOAT;break}}return{width:e[4],height:e[3],mipmapCount:i,isFourCC:(4&e[20])==4,isRGB:(64&e[20])==64,isLuminance:(131072&e[20])==131072,isCube:(512&e[28])==512,isCompressed:o===mu||o===gu||o===vu,dxgiFormat:a,textureType:s}},r._ToHalfFloat=function(t){r._FloatView||(r._FloatView=new Float32Array(1),r._Int32View=new Int32Array(r._FloatView.buffer)),r._FloatView[0]=t;var e=r._Int32View[0],n=e>>16&32768,i=e>>12&2047,o=e>>23&255;return o<103?n:o>142?(n|=31744,n|=(o==255?0:1)&&8388607&e):o<113?n|=((i|=2048)>>114-o)+(i>>113-o&1):(n|=o-112<<10|i>>1,n+=1&i)},r._FromHalfFloat=function(t){var e=(32768&t)>>15,n=(31744&t)>>10,i=1023&t;return n===0?(e?-1:1)*Math.pow(2,-14)*(i/Math.pow(2,10)):n==31?i?NaN:1/0*(e?-1:1):(e?-1:1)*Math.pow(2,n-15)*(1+i/Math.pow(2,10))},r._GetHalfFloatAsFloatRGBAArrayBuffer=function(t,e,n,i,o,a){for(var s=new Float32Array(i),d=new Uint16Array(o,n),p=0,b=0;b<e;b++)for(var P=0;P<t;P++){var O=4*(P+b*t);s[p]=r._FromHalfFloat(d[O]),s[p+1]=r._FromHalfFloat(d[O+1]),s[p+2]=r._FromHalfFloat(d[O+2]),r.StoreLODInAlphaChannel?s[p+3]=a:s[p+3]=r._FromHalfFloat(d[O+3]),p+=4}return s},r._GetHalfFloatRGBAArrayBuffer=function(t,e,n,i,o,a){if(r.StoreLODInAlphaChannel){for(var s=new Uint16Array(i),d=new Uint16Array(o,n),p=0,b=0;b<e;b++)for(var P=0;P<t;P++){var O=4*(P+b*t);s[p]=d[O],s[p+1]=d[O+1],s[p+2]=d[O+2],s[p+3]=r._ToHalfFloat(a),p+=4}return s}return new Uint16Array(o,n,i)},r._GetFloatRGBAArrayBuffer=function(t,e,n,i,o,a){if(r.StoreLODInAlphaChannel){for(var s=new Float32Array(i),d=new Float32Array(o,n),p=0,b=0;b<e;b++)for(var P=0;P<t;P++){var O=4*(P+b*t);s[p]=d[O],s[p+1]=d[O+1],s[p+2]=d[O+2],s[p+3]=a,p+=4}return s}return new Float32Array(o,n,i)},r._GetFloatAsUIntRGBAArrayBuffer=function(t,e,n,i,o,a){for(var s=new Uint8Array(i),d=new Float32Array(o,n),p=0,b=0;b<e;b++)for(var P=0;P<t;P++){var O=4*(P+b*t);s[p]=255*$.a.Clamp(d[O]),s[p+1]=255*$.a.Clamp(d[O+1]),s[p+2]=255*$.a.Clamp(d[O+2]),r.StoreLODInAlphaChannel?s[p+3]=a:s[p+3]=255*$.a.Clamp(d[O+3]),p+=4}return s},r._GetHalfFloatAsUIntRGBAArrayBuffer=function(t,e,n,i,o,a){for(var s=new Uint8Array(i),d=new Uint16Array(o,n),p=0,b=0;b<e;b++)for(var P=0;P<t;P++){var O=4*(P+b*t);s[p]=255*$.a.Clamp(r._FromHalfFloat(d[O])),s[p+1]=255*$.a.Clamp(r._FromHalfFloat(d[O+1])),s[p+2]=255*$.a.Clamp(r._FromHalfFloat(d[O+2])),r.StoreLODInAlphaChannel?s[p+3]=a:s[p+3]=255*$.a.Clamp(r._FromHalfFloat(d[O+3])),p+=4}return s},r._GetRGBAArrayBuffer=function(t,e,n,i,o,a,s,d,p){for(var b=new Uint8Array(i),P=new Uint8Array(o,n),O=0,B=0;B<e;B++)for(var F=0;F<t;F++){var z=4*(F+B*t);b[O]=P[z+a],b[O+1]=P[z+s],b[O+2]=P[z+d],b[O+3]=P[z+p],O+=4}return b},r._ExtractLongWordOrder=function(t){return t===0||t===255||t===-16777216?0:1+r._ExtractLongWordOrder(t>>8)},r._GetRGBArrayBuffer=function(t,e,n,i,o,a,s,d){for(var p=new Uint8Array(i),b=new Uint8Array(o,n),P=0,O=0;O<e;O++)for(var B=0;B<t;B++){var F=3*(B+O*t);p[P]=b[F+a],p[P+1]=b[F+s],p[P+2]=b[F+d],P+=3}return p},r._GetLuminanceArrayBuffer=function(t,e,n,i,o){for(var a=new Uint8Array(i),s=new Uint8Array(o,n),d=0,p=0;p<e;p++)for(var b=0;b<t;b++){var P=b+p*t;a[d]=s[P],d++}return a},r.UploadDDSLevels=function(t,e,n,i,o,a,s,d){s===void 0&&(s=-1);var p=null;i.sphericalPolynomial&&(p=new Array);var b,P,O,B,F,z,J,ie=t.getCaps().s3tc,se=new Int32Array(n.buffer,n.byteOffset,31),ce=0,ue=0,fe=1;if(se[0]===542327876)if(i.isFourCC||i.isRGB||i.isLuminance)if(!i.isCompressed||ie){var ve=se[22];B=se[1]+4;var Te,Re=!1;if(i.isFourCC)switch(b=se[21]){case mu:fe=8,ue=ie.COMPRESSED_RGBA_S3TC_DXT1_EXT;break;case gu:fe=16,ue=ie.COMPRESSED_RGBA_S3TC_DXT3_EXT;break;case vu:fe=16,ue=ie.COMPRESSED_RGBA_S3TC_DXT5_EXT;break;case 113:case 116:Re=!0;break;case Us:B+=20;var Ae=!1;switch(i.dxgiFormat){case 10:case 2:Re=!0,Ae=!0;break;case 88:i.isRGB=!0,i.isFourCC=!1,ve=32,Ae=!0}if(Ae)break;default:return void console.error("Unsupported FourCC code:",(Te=b,String.fromCharCode(255&Te,Te>>8&255,Te>>16&255,Te>>24&255)))}var Ee=r._ExtractLongWordOrder(se[23]),Se=r._ExtractLongWordOrder(se[24]),Le=r._ExtractLongWordOrder(se[25]),xe=r._ExtractLongWordOrder(se[26]);Re&&(ue=t._getRGBABufferInternalSizedFormat(i.textureType)),z=1,131072&se[2]&&o!==!1&&(z=Math.max(1,se[7]));for(var Ne=d||0;Ne<a;Ne++){for(P=se[4],O=se[3],J=0;J<z;++J){if(s===-1||s===J){var Ie=s===-1?J:0;if(!i.isCompressed&&i.isFourCC){e.format=h.a.TEXTUREFORMAT_RGBA,ce=P*O*4;var Fe=null;t._badOS||t._badDesktopOS||!t.getCaps().textureHalfFloat&&!t.getCaps().textureFloat?(ve===128?(Fe=r._GetFloatAsUIntRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ie),p&&Ie==0&&p.push(r._GetFloatRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ie))):ve===64&&(Fe=r._GetHalfFloatAsUIntRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ie),p&&Ie==0&&p.push(r._GetHalfFloatAsFloatRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ie))),e.type=h.a.TEXTURETYPE_UNSIGNED_INT):ve===128?(e.type=h.a.TEXTURETYPE_FLOAT,Fe=r._GetFloatRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ie),p&&Ie==0&&p.push(Fe)):ve!==64||t.getCaps().textureHalfFloat?(e.type=h.a.TEXTURETYPE_HALF_FLOAT,Fe=r._GetHalfFloatRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ie),p&&Ie==0&&p.push(r._GetHalfFloatAsFloatRGBAArrayBuffer(P,O,B,ce,n.buffer,Ie))):(e.type=h.a.TEXTURETYPE_FLOAT,Fe=r._GetHalfFloatAsFloatRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ie),p&&Ie==0&&p.push(Fe)),Fe&&t._uploadDataToTextureDirectly(e,Fe,Ne,Ie)}else if(i.isRGB)e.type=h.a.TEXTURETYPE_UNSIGNED_INT,ve===24?(e.format=h.a.TEXTUREFORMAT_RGB,ce=P*O*3,F=r._GetRGBArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ee,Se,Le),t._uploadDataToTextureDirectly(e,F,Ne,Ie)):(e.format=h.a.TEXTUREFORMAT_RGBA,ce=P*O*4,F=r._GetRGBAArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer,Ee,Se,Le,xe),t._uploadDataToTextureDirectly(e,F,Ne,Ie));else if(i.isLuminance){var Ye=t._getUnpackAlignement(),tt=P;ce=Math.floor((P+Ye-1)/Ye)*Ye*(O-1)+tt,F=r._GetLuminanceArrayBuffer(P,O,n.byteOffset+B,ce,n.buffer),e.format=h.a.TEXTUREFORMAT_LUMINANCE,e.type=h.a.TEXTURETYPE_UNSIGNED_INT,t._uploadDataToTextureDirectly(e,F,Ne,Ie)}else ce=Math.max(4,P)/4*Math.max(4,O)/4*fe,F=new Uint8Array(n.buffer,n.byteOffset+B,ce),e.type=h.a.TEXTURETYPE_UNSIGNED_INT,t._uploadCompressedDataToTextureDirectly(e,ue,P,O,F,Ne,Ie)}B+=ve?P*O*(ve/8):ce,P*=.5,O*=.5,P=Math.max(1,P),O=Math.max(1,O)}if(d!==void 0)break}p&&p.length>0?i.sphericalPolynomial=jo.ConvertCubeMapToSphericalPolynomial({size:se[4],right:p[0],left:p[1],up:p[2],down:p[3],front:p[4],back:p[5],format:h.a.TEXTUREFORMAT_RGBA,type:h.a.TEXTURETYPE_FLOAT,gammaSpace:!1}):i.sphericalPolynomial=void 0}else l.a.Error("Compressed textures are not supported on this platform.");else l.a.Error("Unsupported format, must contain a FourCC, RGB or LUMINANCE code");else l.a.Error("Invalid magic number in DDS header")},r.StoreLODInAlphaChannel=!1,r}();Bt.a.prototype.createPrefilteredCubeTexture=function(r,t,e,n,i,o,a,s,d){var p=this;return i===void 0&&(i=null),o===void 0&&(o=null),s===void 0&&(s=null),d===void 0&&(d=!0),this.createCubeTexture(r,t,null,!1,function(b){if(b){var P=b.texture;if(d?b.info.sphericalPolynomial&&(P._sphericalPolynomial=b.info.sphericalPolynomial):P._sphericalPolynomial=new ro,P._source=Ct.b.CubePrefiltered,p.getCaps().textureLOD)i&&i(P);else{var O=p._gl,B=b.width;if(B){for(var F=[],z=0;z<3;z++){var J=1-z/2,ie=n,se=$.a.Log2(B)*e+n,ce=ie+(se-ie)*J,ue=Math.round(Math.min(Math.max(ce,0),se)),fe=new Ct.a(p,Ct.b.Temp);if(fe.type=P.type,fe.format=P.format,fe.width=Math.pow(2,Math.max($.a.Log2(B)-ue,0)),fe.height=fe.width,fe.isCube=!0,p._bindTextureDirectly(O.TEXTURE_CUBE_MAP,fe,!0),fe.samplingMode=h.a.TEXTURE_LINEAR_LINEAR,O.texParameteri(O.TEXTURE_CUBE_MAP,O.TEXTURE_MAG_FILTER,O.LINEAR),O.texParameteri(O.TEXTURE_CUBE_MAP,O.TEXTURE_MIN_FILTER,O.LINEAR),O.texParameteri(O.TEXTURE_CUBE_MAP,O.TEXTURE_WRAP_S,O.CLAMP_TO_EDGE),O.texParameteri(O.TEXTURE_CUBE_MAP,O.TEXTURE_WRAP_T,O.CLAMP_TO_EDGE),b.isDDS){var ve=b.info,Te=b.data;p._unpackFlipY(ve.isCompressed),Gi.UploadDDSLevels(p,fe,Te,ve,!0,6,ue)}else l.a.Warn("DDS is the only prefiltered cube map supported so far.");p._bindTextureDirectly(O.TEXTURE_CUBE_MAP,null);var Re=new zn.a(t);Re.isCube=!0,Re._texture=fe,fe.isReady=!0,F.push(Re)}P._lodTextureHigh=F[2],P._lodTextureMid=F[1],P._lodTextureLow=F[0],i&&i(P)}}}else i&&i(null)},o,a,s,d,e,n)};var bu=function(){function r(){this.supportCascades=!0}return r.prototype.canLoad=function(t){return Qn.a.EndsWith(t,".dds")},r.prototype.loadCubeData=function(t,e,n,i,o){var a,s=e.getEngine(),d=!1;if(Array.isArray(t))for(var p=0;p<t.length;p++){var b=t[p];a=Gi.GetDDSInfo(b),e.width=a.width,e.height=a.height,d=(a.isRGB||a.isLuminance||a.mipmapCount>1)&&e.generateMipMaps,s._unpackFlipY(a.isCompressed),Gi.UploadDDSLevels(s,e,b,a,d,6,-1,p),a.isFourCC||a.mipmapCount!==1||s.generateMipMapsForCubemap(e)}else{var P=t;a=Gi.GetDDSInfo(P),e.width=a.width,e.height=a.height,n&&(a.sphericalPolynomial=new ro),d=(a.isRGB||a.isLuminance||a.mipmapCount>1)&&e.generateMipMaps,s._unpackFlipY(a.isCompressed),Gi.UploadDDSLevels(s,e,P,a,d,6),a.isFourCC||a.mipmapCount!==1||s.generateMipMapsForCubemap(e,!1)}s._setCubeMapTextureParams(e,d),e.isReady=!0,e.onLoadedObservable.notifyObservers(e),e.onLoadedObservable.clear(),i&&i({isDDS:!0,width:e.width,info:a,data:t,texture:e})},r.prototype.loadData=function(t,e,n){var i=Gi.GetDDSInfo(t),o=(i.isRGB||i.isLuminance||i.mipmapCount>1)&&e.generateMipMaps&&i.width>>i.mipmapCount-1==1;n(i.width,i.height,o,i.isFourCC,function(){Gi.UploadDDSLevels(e.getEngine(),e,t,i,o,1)})},r}();Ue.a._TextureLoaders.push(new bu);var yu=function(){function r(){this.supportCascades=!1}return r.prototype.canLoad=function(t){return Qn.a.EndsWith(t,".env")},r.prototype.loadCubeData=function(t,e,n,i,o){if(!Array.isArray(t)){var a=Ai.GetEnvInfo(t);a?(e.width=a.width,e.height=a.width,Ai.UploadEnvSpherical(e,a),Ai.UploadEnvLevelsAsync(e,t,a).then(function(){e.isReady=!0,e.onLoadedObservable.notifyObservers(e),e.onLoadedObservable.clear(),i&&i()})):o&&o("Can not parse the environment file",null)}},r.prototype.loadData=function(t,e,n){throw".env not supported in 2d."},r}();Ue.a._TextureLoaders.push(new yu);var ia=function(){function r(t,e,n,i){if(this.data=t,this.isInvalid=!1,!r.IsValid(t))return this.isInvalid=!0,void l.a.Error("texture missing KTX identifier");var o=Uint32Array.BYTES_PER_ELEMENT,a=new DataView(this.data.buffer,this.data.byteOffset+12,13*o),s=a.getUint32(0,!0)===67305985;this.glType=a.getUint32(1*o,s),this.glTypeSize=a.getUint32(2*o,s),this.glFormat=a.getUint32(3*o,s),this.glInternalFormat=a.getUint32(4*o,s),this.glBaseInternalFormat=a.getUint32(5*o,s),this.pixelWidth=a.getUint32(6*o,s),this.pixelHeight=a.getUint32(7*o,s),this.pixelDepth=a.getUint32(8*o,s),this.numberOfArrayElements=a.getUint32(9*o,s),this.numberOfFaces=a.getUint32(10*o,s),this.numberOfMipmapLevels=a.getUint32(11*o,s),this.bytesOfKeyValueData=a.getUint32(12*o,s),this.glType===0?(this.numberOfMipmapLevels=Math.max(1,this.numberOfMipmapLevels),this.pixelHeight!==0&&this.pixelDepth===0?this.numberOfArrayElements===0?this.numberOfFaces===e?this.loadType=r.COMPRESSED_2D:l.a.Error("number of faces expected"+e+", but found "+this.numberOfFaces):l.a.Error("texture arrays not currently supported"):l.a.Error("only 2D textures currently supported")):l.a.Error("only compressed formats currently supported")}return r.prototype.uploadLevels=function(t,e){switch(this.loadType){case r.COMPRESSED_2D:this._upload2DCompressedLevels(t,e);break}},r.prototype._upload2DCompressedLevels=function(t,e){for(var n=r.HEADER_LEN+this.bytesOfKeyValueData,i=this.pixelWidth,o=this.pixelHeight,a=e?this.numberOfMipmapLevels:1,s=0;s<a;s++){var d=new Int32Array(this.data.buffer,this.data.byteOffset+n,1)[0];n+=4;for(var p=0;p<this.numberOfFaces;p++){var b=new Uint8Array(this.data.buffer,this.data.byteOffset+n,d);t.getEngine()._uploadCompressedDataToTextureDirectly(t,this.glInternalFormat,i,o,b,p,s),n+=d,n+=3-(d+3)%4}i=Math.max(1,.5*i),o=Math.max(1,.5*o)}},r.IsValid=function(t){if(t.byteLength>=12){var e=new Uint8Array(t.buffer,t.byteOffset,12);if(e[0]===171&&e[1]===75&&e[2]===84&&e[3]===88&&e[4]===32&&e[5]===49&&e[6]===49&&e[7]===187&&e[8]===13&&e[9]===10&&e[10]===26&&e[11]===10)return!0}return!1},r.HEADER_LEN=64,r.COMPRESSED_2D=0,r.COMPRESSED_3D=1,r.TEX_2D=2,r.TEX_3D=3,r}(),Vs=function(){function r(t){this._pendingActions=new Array,this._workerInfos=t.map(function(e){return{worker:e,active:!1}})}return r.prototype.dispose=function(){for(var t=0,e=this._workerInfos;t<e.length;t++)e[t].worker.terminate();this._workerInfos=[],this._pendingActions=[]},r.prototype.push=function(t){for(var e=0,n=this._workerInfos;e<n.length;e++){var i=n[e];if(!i.active)return void this._execute(i,t)}this._pendingActions.push(t)},r.prototype._execute=function(t,e){var n=this;t.active=!0,e(t.worker,function(){t.active=!1;var i=n._pendingActions.shift();i&&n._execute(t,i)})},r}(),ks=function(){function r(t,e){e===void 0&&(e=r.DefaultNumWorkers),this._engine=t,r._Initialized||r._CreateWorkerPool(e)}return r.GetDefaultNumWorkers=function(){return typeof navigator=="object"&&navigator.hardwareConcurrency?Math.min(Math.floor(.5*navigator.hardwareConcurrency),4):1},r._CreateWorkerPool=function(t){this._Initialized=!0,t&&typeof Worker=="function"?r._WorkerPoolPromise=new Promise(function(e){for(var n="("+f_+")()",i=URL.createObjectURL(new Blob([n],{type:"application/javascript"})),o=new Array(t),a=0;a<o.length;a++)o[a]=new Promise(function(s,d){var p=new Worker(i),b=function(O){p.removeEventListener("error",b),p.removeEventListener("message",P),d(O)},P=function(O){O.data.action==="init"&&(p.removeEventListener("error",b),p.removeEventListener("message",P),s(p))};p.addEventListener("error",b),p.addEventListener("message",P),p.postMessage({action:"init",urls:r.URLConfig})});Promise.all(o).then(function(s){e(new Vs(s))})}):(KTX2DECODER.MSCTranscoder.UseFromWorkerThread=!1,KTX2DECODER.WASMMemoryManager.LoadBinariesFromCurrentThread=!0)},r.prototype.uploadAsync=function(t,e,n){var i=this,o=this._engine.getCaps(),a={astc:!!o.astc,bptc:!!o.bptc,s3tc:!!o.s3tc,pvrtc:!!o.pvrtc,etc2:!!o.etc2,etc1:!!o.etc1};return r._WorkerPoolPromise?r._WorkerPoolPromise.then(function(s){return new Promise(function(d,p){s.push(function(b,P){var O=function(F){b.removeEventListener("error",O),b.removeEventListener("message",B),p(F),P()},B=function(F){if(F.data.action==="decoded"){if(b.removeEventListener("error",O),b.removeEventListener("message",B),F.data.success)try{i._createTexture(F.data.decodedData,e,n),d()}catch(z){p({message:z})}else p({message:F.data.msg});P()}};b.addEventListener("error",O),b.addEventListener("message",B),b.postMessage({action:"decode",data:t,caps:a,options:n})})})}):new Promise(function(s,d){r._Ktx2Decoder||(r._Ktx2Decoder=new KTX2DECODER.KTX2Decoder),r._Ktx2Decoder.decode(t,o).then(function(p){i._createTexture(p,e),s()}).catch(function(p){d({message:p})})})},r.prototype.dispose=function(){r._WorkerPoolPromise&&r._WorkerPoolPromise.then(function(t){t.dispose()}),delete r._WorkerPoolPromise},r.prototype._createTexture=function(t,e,n){if(this._engine._bindTextureDirectly(this._engine._gl.TEXTURE_2D,e),n&&(n.transcodedFormat=t.transcodedFormat,n.isInGammaSpace=t.isInGammaSpace,n.transcoderName=t.transcoderName),t.transcodedFormat===32856?(e.type=h.a.TEXTURETYPE_UNSIGNED_BYTE,e.format=h.a.TEXTUREFORMAT_RGBA):e.format=t.transcodedFormat,e._gammaSpace=t.isInGammaSpace,t.errors)throw new Error("KTX2 container - could not transcode the data. "+t.errors);for(var i=0;i<t.mipmaps.length;++i){var o=t.mipmaps[i];if(!o||!o.data)throw new Error("KTX2 container - could not transcode one of the image");t.transcodedFormat===32856?(e.width=o.width,e.height=o.height,this._engine._uploadDataToTextureDirectly(e,o.data,0,i,void 0,!0)):this._engine._uploadCompressedDataToTextureDirectly(e,t.transcodedFormat,o.width,o.height,o.data,0,i)}e.width=t.mipmaps[0].width,e.height=t.mipmaps[0].height,e.generateMipMaps=t.mipmaps.length>1,e.isReady=!0,this._engine._bindTextureDirectly(this._engine._gl.TEXTURE_2D,null)},r.IsValid=function(t){if(t.byteLength>=12){var e=new Uint8Array(t.buffer,t.byteOffset,12);if(e[0]===171&&e[1]===75&&e[2]===84&&e[3]===88&&e[4]===32&&e[5]===50&&e[6]===48&&e[7]===187&&e[8]===13&&e[9]===10&&e[10]===26&&e[11]===10)return!0}return!1},r.URLConfig={jsDecoderModule:"https://preview.babylonjs.com/babylon.ktx2Decoder.js",wasmUASTCToASTC:null,wasmUASTCToBC7:null,wasmUASTCToRGBA_UNORM:null,wasmUASTCToRGBA_SRGB:null,jsMSCTranscoder:null,wasmMSCTranscoder:null},r.DefaultNumWorkers=r.GetDefaultNumWorkers(),r}();function f_(){var r;onmessage=function(t){switch(t.data.action){case"init":var e=t.data.urls;importScripts(e.jsDecoderModule),e.wasmUASTCToASTC!==null&&(KTX2DECODER.LiteTranscoder_UASTC_ASTC.WasmModuleURL=e.wasmUASTCToASTC),e.wasmUASTCToBC7!==null&&(KTX2DECODER.LiteTranscoder_UASTC_BC7.WasmModuleURL=e.wasmUASTCToBC7),e.wasmUASTCToRGBA_UNORM!==null&&(KTX2DECODER.LiteTranscoder_UASTC_RGBA_UNORM.WasmModuleURL=e.wasmUASTCToRGBA_UNORM),e.wasmUASTCToRGBA_SRGB!==null&&(KTX2DECODER.LiteTranscoder_UASTC_RGBA_SRGB.WasmModuleURL=e.wasmUASTCToRGBA_SRGB),e.jsMSCTranscoder!==null&&(KTX2DECODER.MSCTranscoder.JSModuleURL=e.jsMSCTranscoder),e.wasmMSCTranscoder!==null&&(KTX2DECODER.MSCTranscoder.WasmModuleURL=e.wasmMSCTranscoder),r=new KTX2DECODER.KTX2Decoder,postMessage({action:"init"});break;case"decode":r.decode(t.data.data,t.data.caps,t.data.options).then(function(n){for(var i=[],o=0;o<n.mipmaps.length;++o){var a=n.mipmaps[o];a&&a.data&&i.push(a.data.buffer)}postMessage({action:"decoded",success:!0,decodedData:n},i)}).catch(function(n){postMessage({action:"decoded",success:!1,msg:n})})}}}var Tu=function(){function r(){this.supportCascades=!1}return r.prototype.canLoad=function(t,e){return Qn.a.EndsWith(t,".ktx")||Qn.a.EndsWith(t,".ktx2")||e==="image/ktx"||e==="image/ktx2"},r.prototype.loadCubeData=function(t,e,n,i,o){if(!Array.isArray(t)){e._invertVScale=!e.invertY;var a=e.getEngine(),s=new ia(t,6),d=s.numberOfMipmapLevels>1&&e.generateMipMaps;a._unpackFlipY(!0),s.uploadLevels(e,e.generateMipMaps),e.width=s.pixelWidth,e.height=s.pixelHeight,a._setCubeMapTextureParams(e,d),e.isReady=!0,e.onLoadedObservable.notifyObservers(e),e.onLoadedObservable.clear(),i&&i()}},r.prototype.loadData=function(t,e,n,i){if(ia.IsValid(t)){e._invertVScale=!e.invertY;var o=new ia(t,1);n(o.pixelWidth,o.pixelHeight,e.generateMipMaps,!0,function(){o.uploadLevels(e,e.generateMipMaps)},o.isInvalid)}else ks.IsValid(t)?new ks(e.getEngine()).uploadAsync(t,e,i).then(function(){n(e.width,e.height,e.generateMipMaps,!0,function(){},!1)},function(a){l.a.Warn("Failed to load KTX2 texture data: "+a.message),n(0,0,!1,!1,function(){},!0)}):(l.a.Error("texture missing KTX identifier"),n(0,0,!1,!1,function(){},!0))},r}();Ue.a._TextureLoaders.unshift(new Tu);var Eu=function(r){function t(e,n,i){var o=r.call(this,e,u.e.Zero(),n)||this;return o._xrSessionManager=i,o._firstFrame=!1,o._referenceQuaternion=u.b.Identity(),o._referencedPosition=new u.e,o._xrInvPositionCache=new u.e,o._xrInvQuaternionCache=u.b.Identity(),o._trackingState=tr.NOT_TRACKING,o.onBeforeCameraTeleport=new C.c,o.onAfterCameraTeleport=new C.c,o.onTrackingStateChanged=new C.c,o.compensateOnFirstFrame=!0,o._rotate180=new u.b(0,1,0,0),o.minZ=.1,o.rotationQuaternion=new u.b,o.cameraRigMode=gt.a.RIG_MODE_CUSTOM,o.updateUpVectorFromRotation=!0,o._updateNumberOfRigCameras(1),o.freezeProjectionMatrix(),o._xrSessionManager.onXRSessionInit.add(function(){o._referencedPosition.copyFromFloats(0,0,0),o._referenceQuaternion.copyFromFloats(0,0,0,1),o._firstFrame=o.compensateOnFirstFrame}),o._xrSessionManager.onXRFrameObservable.add(function(a){o._firstFrame&&o._updateFromXRSession(),o._updateReferenceSpace(),o._updateFromXRSession()},void 0,!0),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"trackingState",{get:function(){return this._trackingState},enumerable:!1,configurable:!0}),t.prototype._setTrackingState=function(e){this._trackingState!==e&&(this._trackingState=e,this.onTrackingStateChanged.notifyObservers(e))},Object.defineProperty(t.prototype,"realWorldHeight",{get:function(){var e=this._xrSessionManager.currentFrame&&this._xrSessionManager.currentFrame.getViewerPose(this._xrSessionManager.baseReferenceSpace);return e&&e.transform?e.transform.position.y:0},enumerable:!1,configurable:!0}),t.prototype._updateForDualEyeDebugging=function(){this._updateNumberOfRigCameras(2),this.rigCameras[0].viewport=new Kn.a(0,0,.5,1),this.rigCameras[0].outputRenderTarget=null,this.rigCameras[1].viewport=new Kn.a(.5,0,.5,1),this.rigCameras[1].outputRenderTarget=null},t.prototype.setTransformationFromNonVRCamera=function(e,n){e===void 0&&(e=this.getScene().activeCamera),n===void 0&&(n=!0),e&&e!==this&&(e.computeWorldMatrix().decompose(void 0,this.rotationQuaternion,this.position),this.position.y=0,u.b.FromEulerAnglesToRef(0,this.rotationQuaternion.toEulerAngles().y,0,this.rotationQuaternion),this._firstFrame=!0,n&&this._xrSessionManager.resetReferenceSpace())},t.prototype.getClassName=function(){return"WebXRCamera"},t.prototype._updateFromXRSession=function(){var e=this,n=this._xrSessionManager.currentFrame&&this._xrSessionManager.currentFrame.getViewerPose(this._xrSessionManager.referenceSpace);if(n){var i=n.emulatedPosition?tr.TRACKING_LOST:tr.TRACKING;if(this._setTrackingState(i),n.transform){var o=n.transform.position;this._referencedPosition.set(o.x,o.y,o.z);var a=n.transform.orientation;this._referenceQuaternion.set(a.x,a.y,a.z,a.w),this._scene.useRightHandedSystem||(this._referencedPosition.z*=-1,this._referenceQuaternion.z*=-1,this._referenceQuaternion.w*=-1),this._firstFrame?(this._firstFrame=!1,this.position.y+=this._referencedPosition.y,this._referenceQuaternion.copyFromFloats(0,0,0,1)):(this.rotationQuaternion.copyFrom(this._referenceQuaternion),this.position.copyFrom(this._referencedPosition))}this.rigCameras.length!==n.views.length&&this._updateNumberOfRigCameras(n.views.length),n.views.forEach(function(s,d){var p=e.rigCameras[d];p.isLeftCamera||p.isRightCamera||(s.eye==="right"?p._isRightCamera=!0:s.eye==="left"&&(p._isLeftCamera=!0));var b=s.transform.position,P=s.transform.orientation;if(p.position.set(b.x,b.y,b.z),p.rotationQuaternion.set(P.x,P.y,P.z,P.w),e._scene.useRightHandedSystem?p.rotationQuaternion.multiplyInPlace(e._rotate180):(p.position.z*=-1,p.rotationQuaternion.z*=-1,p.rotationQuaternion.w*=-1),u.a.FromFloat32ArrayToRefScaled(s.projectionMatrix,0,1,p._projectionMatrix),e._scene.useRightHandedSystem||p._projectionMatrix.toggleProjectionMatrixHandInPlace(),d===0&&e._projectionMatrix.copyFrom(p._projectionMatrix),e._xrSessionManager.session.renderState.baseLayer){var O=e._xrSessionManager.session.renderState.baseLayer.getViewport(s),B=e._xrSessionManager.session.renderState.baseLayer.framebufferWidth,F=e._xrSessionManager.session.renderState.baseLayer.framebufferHeight;p.viewport.width=O.width/B,p.viewport.height=O.height/F,p.viewport.x=O.x/B,p.viewport.y=O.y/F}p.outputRenderTarget=e._xrSessionManager.getRenderTargetTextureForEye(s.eye)})}else this._setTrackingState(tr.NOT_TRACKING)},t.prototype._updateNumberOfRigCameras=function(e){for(e===void 0&&(e=1);this.rigCameras.length<e;){var n=new Ni("XR-RigCamera: "+this.rigCameras.length,u.e.Zero(),this.getScene());n.minZ=.1,n.rotationQuaternion=new u.b,n.updateUpVectorFromRotation=!0,n.isRigCamera=!0,n.rigParent=this,n.freezeProjectionMatrix(),this.rigCameras.push(n)}for(;this.rigCameras.length>e;){var i=this.rigCameras.pop();i&&i.dispose()}},t.prototype._updateReferenceSpace=function(){this.position.equals(this._referencedPosition)&&this.rotationQuaternion.equals(this._referenceQuaternion)||(this.position.subtractToRef(this._referencedPosition,this._referencedPosition),this._referenceQuaternion.conjugateInPlace(),this._referenceQuaternion.multiplyToRef(this.rotationQuaternion,this._referenceQuaternion),this._updateReferenceSpaceOffset(this._referencedPosition,this._referenceQuaternion.normalize()))},t.prototype._updateReferenceSpaceOffset=function(e,n,i){if(i===void 0&&(i=!1),this._xrSessionManager.referenceSpace&&this._xrSessionManager.currentFrame){this._xrInvPositionCache.copyFrom(e),n?this._xrInvQuaternionCache.copyFrom(n):this._xrInvQuaternionCache.copyFromFloats(0,0,0,1),this._scene.useRightHandedSystem||(this._xrInvPositionCache.z*=-1,this._xrInvQuaternionCache.z*=-1,this._xrInvQuaternionCache.w*=-1),this._xrInvPositionCache.negateInPlace(),this._xrInvQuaternionCache.conjugateInPlace(),this._xrInvPositionCache.rotateByQuaternionToRef(this._xrInvQuaternionCache,this._xrInvPositionCache),i&&(this._xrInvPositionCache.y=0);var o=new XRRigidTransform({x:this._xrInvPositionCache.x,y:this._xrInvPositionCache.y,z:this._xrInvPositionCache.z},{x:this._xrInvQuaternionCache.x,y:this._xrInvQuaternionCache.y,z:this._xrInvQuaternionCache.z,w:this._xrInvQuaternionCache.w}),a=this._xrSessionManager.referenceSpace.getOffsetReferenceSpace(o),s=this._xrSessionManager.currentFrame&&this._xrSessionManager.currentFrame.getViewerPose(a);if(s){var d=new u.e(s.transform.position.x,s.transform.position.y,s.transform.position.z);this._scene.useRightHandedSystem||(d.z*=-1),this.position.subtractToRef(d,d),this._scene.useRightHandedSystem||(d.z*=-1),d.negateInPlace();var p=new XRRigidTransform({x:d.x,y:d.y,z:d.z});this._xrSessionManager.referenceSpace=a.getOffsetReferenceSpace(p)}}},t}(Yn),ai=function(){function r(){}return r.ANCHOR_SYSTEM="xr-anchor-system",r.BACKGROUND_REMOVER="xr-background-remover",r.HIT_TEST="xr-hit-test",r.PHYSICS_CONTROLLERS="xr-physics-controller",r.PLANE_DETECTION="xr-plane-detection",r.POINTER_SELECTION="xr-controller-pointer-selection",r.TELEPORTATION="xr-controller-teleportation",r.FEATURE_POINTS="xr-feature-points",r.HAND_TRACKING="xr-hand-tracking",r}(),qn=function(){function r(t){var e=this;this._xrSessionManager=t,this._features={},this._xrSessionManager.onXRSessionInit.add(function(){e.getEnabledFeatures().forEach(function(n){var i=e._features[n];!i.enabled||i.featureImplementation.attached||i.featureImplementation.disableAutoAttach||e.attachFeature(n)})}),this._xrSessionManager.onXRSessionEnded.add(function(){e.getEnabledFeatures().forEach(function(n){var i=e._features[n];i.enabled&&i.featureImplementation.attached&&e.detachFeature(n)})})}return r.AddWebXRFeature=function(t,e,n,i){n===void 0&&(n=1),i===void 0&&(i=!1),this._AvailableFeatures[t]=this._AvailableFeatures[t]||{latest:n},n>this._AvailableFeatures[t].latest&&(this._AvailableFeatures[t].latest=n),i&&(this._AvailableFeatures[t].stable=n),this._AvailableFeatures[t][n]=e},r.ConstructFeature=function(t,e,n,i){e===void 0&&(e=1);var o=this._AvailableFeatures[t][e];if(!o)throw new Error("feature not found");return o(n,i)},r.GetAvailableFeatures=function(){return Object.keys(this._AvailableFeatures)},r.GetAvailableVersions=function(t){return Object.keys(this._AvailableFeatures[t])},r.GetLatestVersionOfFeature=function(t){return this._AvailableFeatures[t]&&this._AvailableFeatures[t].latest||-1},r.GetStableVersionOfFeature=function(t){return this._AvailableFeatures[t]&&this._AvailableFeatures[t].stable||-1},r.prototype.attachFeature=function(t){var e=this._features[t];e&&e.enabled&&!e.featureImplementation.attached&&e.featureImplementation.attach()},r.prototype.detachFeature=function(t){var e=this._features[t];e&&e.featureImplementation.attached&&e.featureImplementation.detach()},r.prototype.disableFeature=function(t){var e=typeof t=="string"?t:t.Name,n=this._features[e];return!(!n||!n.enabled)&&(n.enabled=!1,this.detachFeature(e),n.featureImplementation.dispose(),!0)},r.prototype.dispose=function(){var t=this;this.getEnabledFeatures().forEach(function(e){t.disableFeature(e),t._features[e].featureImplementation.dispose()})},r.prototype.enableFeature=function(t,e,n,i,o){var a=this;e===void 0&&(e="latest"),n===void 0&&(n={}),i===void 0&&(i=!0),o===void 0&&(o=!0);var s=typeof t=="string"?t:t.Name,d=0;if(typeof e=="string"){if(!e)throw new Error("Error in provided version - "+s+" ("+e+")");if((d=e==="stable"?r.GetStableVersionOfFeature(s):e==="latest"?r.GetLatestVersionOfFeature(s):+e)===-1||isNaN(d))throw new Error("feature not found - "+s+" ("+e+")")}else d=e;var p=this._features[s],b=r.ConstructFeature(s,d,this._xrSessionManager,n);if(!b)throw new Error("feature not found - "+s);p&&this.disableFeature(s);var P=b();if(P.dependsOn&&!P.dependsOn.every(function(O){return!!a._features[O]}))throw new Error("Dependant features missing. Make sure the following features are enabled - "+P.dependsOn.join(", "));if(P.isCompatible())return this._features[s]={featureImplementation:P,enabled:!0,version:d,required:o},i?this._xrSessionManager.session&&!this._features[s].featureImplementation.attached&&this.attachFeature(s):this._features[s].featureImplementation.disableAutoAttach=!0,this._features[s].featureImplementation;if(o)throw new Error("required feature not compatible");return Xe.b.Warn("Feature "+s+" not compatible with the current environment/browser and was not enabled."),P},r.prototype.getEnabledFeature=function(t){return this._features[t]&&this._features[t].featureImplementation},r.prototype.getEnabledFeatures=function(){return Object.keys(this._features)},r.prototype.extendXRSessionInitObject=function(t){var e=this;return this.getEnabledFeatures().forEach(function(n){var i=e._features[n],o=i.featureImplementation.xrNativeFeatureName;o&&(i.required?(t.requiredFeatures=t.requiredFeatures||[],t.requiredFeatures.indexOf(o)===-1&&t.requiredFeatures.push(o)):(t.optionalFeatures=t.optionalFeatures||[],t.optionalFeatures.indexOf(o)===-1&&t.optionalFeatures.push(o)))}),t},r._AvailableFeatures={},r}(),Su=function(){function r(t){var e=this;this.scene=t,this._nonVRCamera=null,this._originalSceneAutoClear=!0,this._supported=!1,this.onInitialXRPoseSetObservable=new C.c,this.onStateChangedObservable=new C.c,this.state=pn.NOT_IN_XR,this.sessionManager=new gs(t),this.camera=new Eu("",t,this.sessionManager),this.featuresManager=new qn(this.sessionManager),t.onDisposeObservable.add(function(){e.exitXRAsync()})}return r.CreateAsync=function(t){var e=new r(t);return e.sessionManager.initializeAsync().then(function(){return e._supported=!0,e}).catch(function(n){throw e._setState(pn.NOT_IN_XR),e.dispose(),n})},r.prototype.dispose=function(){this.camera.dispose(),this.onStateChangedObservable.clear(),this.onInitialXRPoseSetObservable.clear(),this.sessionManager.dispose(),this._nonVRCamera&&(this.scene.activeCamera=this._nonVRCamera)},r.prototype.enterXRAsync=function(t,e,n,i){var o=this;if(n===void 0&&(n=this.sessionManager.getWebXRRenderTarget()),i===void 0&&(i={}),!this._supported)throw"WebXR not supported in this browser or environment";return this._setState(pn.ENTERING_XR),e!=="viewer"&&e!=="local"&&(i.optionalFeatures=i.optionalFeatures||[],i.optionalFeatures.push(e)),this.featuresManager.extendXRSessionInitObject(i),t==="immersive-ar"&&e!=="unbounded"&&l.a.Warn("We recommend using 'unbounded' reference space type when using 'immersive-ar' session mode"),this.sessionManager.initializeSessionAsync(t,i).then(function(){return o.sessionManager.setReferenceSpaceTypeAsync(e)}).then(function(){return n.initializeXRLayerAsync(o.sessionManager.session)}).then(function(){return o.sessionManager.updateRenderStateAsync({depthFar:o.camera.maxZ,depthNear:o.camera.minZ,baseLayer:n.xrLayer})}).then(function(){return o.sessionManager.runXRRenderLoop(),o._originalSceneAutoClear=o.scene.autoClear,o._nonVRCamera=o.scene.activeCamera,o.scene.activeCamera=o.camera,t!=="immersive-ar"?o._nonXRToXRCamera():(o.scene.autoClear=!1,o.camera.compensateOnFirstFrame=!1),o.sessionManager.onXRSessionEnded.addOnce(function(){o.camera.rigCameras.forEach(function(a){a.outputRenderTarget=null}),o.scene.autoClear=o._originalSceneAutoClear,o.scene.activeCamera=o._nonVRCamera,t!=="immersive-ar"&&o.camera.compensateOnFirstFrame&&(o._nonVRCamera.setPosition?o._nonVRCamera.setPosition(o.camera.position):o._nonVRCamera.position.copyFrom(o.camera.position)),o._setState(pn.NOT_IN_XR)}),o.sessionManager.onXRFrameObservable.addOnce(function(){o._setState(pn.IN_XR)}),o.sessionManager}).catch(function(a){throw console.log(a),console.log(a.message),o._setState(pn.NOT_IN_XR),a})},r.prototype.exitXRAsync=function(){return this.state!==pn.IN_XR?Promise.resolve():(this._setState(pn.EXITING_XR),this.sessionManager.exitXRAsync())},r.prototype._nonXRToXRCamera=function(){this.camera.setTransformationFromNonVRCamera(this._nonVRCamera),this.onInitialXRPoseSetObservable.notifyObservers(this.camera)},r.prototype._setState=function(t){this.state!==t&&(this.state=t,this.onStateChangedObservable.notifyObservers(this.state))},r}(),Cr=function(){function r(t,e,n,i){n===void 0&&(n=-1),i===void 0&&(i=[]),this.id=t,this.type=e,this._buttonIndex=n,this._axesIndices=i,this._axes={x:0,y:0},this._changes={},this._currentValue=0,this._hasChanges=!1,this._pressed=!1,this._touched=!1,this.onAxisValueChangedObservable=new C.c,this.onButtonStateChangedObservable=new C.c}return Object.defineProperty(r.prototype,"axes",{get:function(){return this._axes},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"changes",{get:function(){return this._changes},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hasChanges",{get:function(){return this._hasChanges},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"pressed",{get:function(){return this._pressed},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"touched",{get:function(){return this._touched},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"value",{get:function(){return this._currentValue},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this.onAxisValueChangedObservable.clear(),this.onButtonStateChangedObservable.clear()},r.prototype.isAxes=function(){return this._axesIndices.length!==0},r.prototype.isButton=function(){return this._buttonIndex!==-1},r.prototype.update=function(t){var e=!1,n=!1;if(this._hasChanges=!1,this._changes={},this.isButton()){var i=t.buttons[this._buttonIndex];if(!i)return;this._currentValue!==i.value&&(this.changes.value={current:i.value,previous:this._currentValue},e=!0,this._currentValue=i.value),this._touched!==i.touched&&(this.changes.touched={current:i.touched,previous:this._touched},e=!0,this._touched=i.touched),this._pressed!==i.pressed&&(this.changes.pressed={current:i.pressed,previous:this._pressed},e=!0,this._pressed=i.pressed)}this.isAxes()&&(this._axes.x!==t.axes[this._axesIndices[0]]&&(this.changes.axes={current:{x:t.axes[this._axesIndices[0]],y:this._axes.y},previous:{x:this._axes.x,y:this._axes.y}},this._axes.x=t.axes[this._axesIndices[0]],n=!0),this._axes.y!==t.axes[this._axesIndices[1]]&&(this.changes.axes?this.changes.axes.current.y=t.axes[this._axesIndices[1]]:this.changes.axes={current:{x:this._axes.x,y:t.axes[this._axesIndices[1]]},previous:{x:this._axes.x,y:this._axes.y}},this._axes.y=t.axes[this._axesIndices[1]],n=!0)),e&&(this._hasChanges=!0,this.onButtonStateChangedObservable.notifyObservers(this)),n&&(this._hasChanges=!0,this.onAxisValueChangedObservable.notifyObservers(this._axes))},r.BUTTON_TYPE="button",r.SQUEEZE_TYPE="squeeze",r.THUMBSTICK_TYPE="thumbstick",r.TOUCHPAD_TYPE="touchpad",r.TRIGGER_TYPE="trigger",r}(),Rr=function(){function r(t,e,n,i,o){var a=this;this.scene=t,this.layout=e,this.gamepadObject=n,this.handedness=i,this._initComponent=function(s){if(s){var d=a.layout.components[s],p=d.type,b=d.gamepadIndices.button,P=[];d.gamepadIndices.xAxis!==void 0&&d.gamepadIndices.yAxis!==void 0&&P.push(d.gamepadIndices.xAxis,d.gamepadIndices.yAxis),a.components[s]=new Cr(s,p,b,P)}},this._modelReady=!1,this.components={},this.disableAnimation=!1,this.onModelLoadedObservable=new C.c,e.components&&Object.keys(e.components).forEach(this._initComponent)}return r.prototype.dispose=function(){var t=this;this.getComponentIds().forEach(function(e){return t.getComponent(e).dispose()}),this.rootMesh&&this.rootMesh.dispose()},r.prototype.getAllComponentsOfType=function(t){var e=this;return this.getComponentIds().map(function(n){return e.components[n]}).filter(function(n){return n.type===t})},r.prototype.getComponent=function(t){return this.components[t]},r.prototype.getComponentIds=function(){return Object.keys(this.components)},r.prototype.getComponentOfType=function(t){return this.getAllComponentsOfType(t)[0]||null},r.prototype.getMainComponent=function(){return this.getComponent(this.layout.selectComponentId)},r.prototype.loadModel=function(){return Object(c.b)(this,void 0,void 0,function(){var t,e,n=this;return Object(c.e)(this,function(i){return t=!this._getModelLoadingConstraints(),e=this._getGenericFilenameAndPath(),t?l.a.Warn("Falling back to generic models"):e=this._getFilenameAndPath(),[2,new Promise(function(o,a){Ut.ImportMesh("",e.path,e.filename,n.scene,function(s){t?n._getGenericParentMesh(s):n._setRootMesh(s),n._processLoadedModel(s),n._modelReady=!0,n.onModelLoadedObservable.notifyObservers(n),o(!0)},null,function(s,d){l.a.Log(d),l.a.Warn("Failed to retrieve controller model of type "+n.profileId+" from the remote server: "+e.path+e.filename),a(d)})})]})})},r.prototype.updateFromXRFrame=function(t){var e=this;this.getComponentIds().forEach(function(n){return e.getComponent(n).update(e.gamepadObject)}),this.updateModel(t)},Object.defineProperty(r.prototype,"handness",{get:function(){return this.handedness},enumerable:!1,configurable:!0}),r.prototype.pulse=function(t,e,n){return n===void 0&&(n=0),this.gamepadObject.hapticActuators&&this.gamepadObject.hapticActuators[n]?this.gamepadObject.hapticActuators[n].pulse(t,e):Promise.resolve(!1)},r.prototype._getChildByName=function(t,e){return t.getChildren(function(n){return n.name===e},!1)[0]},r.prototype._getImmediateChildByName=function(t,e){return t.getChildren(function(n){return n.name==e},!0)[0]},r.prototype._lerpTransform=function(t,e,n){if(t.minMesh&&t.maxMesh&&t.valueMesh&&t.minMesh.rotationQuaternion&&t.maxMesh.rotationQuaternion&&t.valueMesh.rotationQuaternion){var i=n?.5*e+.5:e;u.b.SlerpToRef(t.minMesh.rotationQuaternion,t.maxMesh.rotationQuaternion,i,t.valueMesh.rotationQuaternion),u.e.LerpToRef(t.minMesh.position,t.maxMesh.position,i,t.valueMesh.position)}},r.prototype.updateModel=function(t){this._modelReady&&this._updateModel(t)},r.prototype._getGenericFilenameAndPath=function(){return{filename:"generic.babylon",path:"https://controllers.babylonjs.com/generic/"}},r.prototype._getGenericParentMesh=function(t){var e=this;this.rootMesh=new De.a(this.profileId+" "+this.handedness,this.scene),t.forEach(function(n){n.parent||(n.isPickable=!1,n.setParent(e.rootMesh))}),this.rootMesh.rotationQuaternion=u.b.FromEulerAngles(0,Math.PI,0)},r}(),Gs=function(r){function t(e,n,i){var o=r.call(this,e,p_[i],n,i)||this;return o.profileId=t.ProfileId,o}return Object(c.d)(t,r),t.prototype._getFilenameAndPath=function(){return{filename:"generic.babylon",path:"https://controllers.babylonjs.com/generic/"}},t.prototype._getModelLoadingConstraints=function(){return!0},t.prototype._processLoadedModel=function(e){},t.prototype._setRootMesh=function(e){var n=this;this.rootMesh=new De.a(this.profileId+" "+this.handedness,this.scene),e.forEach(function(i){i.isPickable=!1,i.parent||i.setParent(n.rootMesh)}),this.rootMesh.rotationQuaternion=u.b.FromEulerAngles(0,Math.PI,0)},t.prototype._updateModel=function(){},t.ProfileId="generic-trigger",t}(Rr),p_={left:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"generic-trigger-left",assetPath:"left.glb"},right:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"generic-trigger-right",assetPath:"right.glb"},none:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"generic-trigger-none",assetPath:"none.glb"}},Au=function(r){function t(e,n,i,o){var a=r.call(this,e,i.layouts[n.handedness||"none"],n.gamepad,n.handedness)||this;return a._repositoryUrl=o,a._buttonMeshMapping={},a._touchDots={},a.profileId=i.profileId,a}return Object(c.d)(t,r),t.prototype.dispose=function(){var e=this;r.prototype.dispose.call(this),Object.keys(this._touchDots).forEach(function(n){e._touchDots[n].dispose()})},t.prototype._getFilenameAndPath=function(){return{filename:this.layout.assetPath,path:this._repositoryUrl+"/profiles/"+this.profileId+"/"}},t.prototype._getModelLoadingConstraints=function(){var e=Ut.IsPluginForExtensionAvailable(".glb");return e||l.a.Warn("glTF / glb loaded was not registered, using generic controller instead"),e},t.prototype._processLoadedModel=function(e){var n=this;this.getComponentIds().forEach(function(i){var o=n.layout.components[i];n._buttonMeshMapping[i]={mainMesh:n._getChildByName(n.rootMesh,o.rootNodeName),states:{}},Object.keys(o.visualResponses).forEach(function(a){var s=o.visualResponses[a];if(s.valueNodeProperty==="transform")n._buttonMeshMapping[i].states[a]={valueMesh:n._getChildByName(n.rootMesh,s.valueNodeName),minMesh:n._getChildByName(n.rootMesh,s.minNodeName),maxMesh:n._getChildByName(n.rootMesh,s.maxNodeName)};else{var d=o.type===Cr.TOUCHPAD_TYPE&&o.touchPointNodeName?o.touchPointNodeName:s.valueNodeName;if(n._buttonMeshMapping[i].states[a]={valueMesh:n._getChildByName(n.rootMesh,d)},o.type===Cr.TOUCHPAD_TYPE&&!n._touchDots[a]){var p=Fn.a.CreateSphere(a+"dot",{diameter:.0015,segments:8},n.scene);p.material=new Ft.a(a+"mat",n.scene),p.material.diffuseColor=M.a.Red(),p.parent=n._buttonMeshMapping[i].states[a].valueMesh||null,p.isVisible=!1,n._touchDots[a]=p}}})})},t.prototype._setRootMesh=function(e){var n;this.rootMesh=new De.a(this.profileId+"-"+this.handedness,this.scene),this.rootMesh.isPickable=!1;for(var i=0;i<e.length;i++){var o=e[i];o.isPickable=!1,o.parent||(n=o)}n&&n.setParent(this.rootMesh),this.scene.useRightHandedSystem||this.rootMesh.rotate(ye.a.Y,Math.PI,ye.c.WORLD)},t.prototype._updateModel=function(e){var n=this;this.disableAnimation||this.getComponentIds().forEach(function(i){var o=n.getComponent(i);if(o.hasChanges){var a=n._buttonMeshMapping[i],s=n.layout.components[i];Object.keys(s.visualResponses).forEach(function(d){var p=s.visualResponses[d],b=o.value;if(p.componentProperty==="xAxis"?b=o.axes.x:p.componentProperty==="yAxis"&&(b=o.axes.y),p.valueNodeProperty==="transform")n._lerpTransform(a.states[d],b,p.componentProperty!=="button");else{var P=a.states[d].valueMesh;P&&(P.isVisible=o.touched||o.pressed),n._touchDots[d]&&(n._touchDots[d].isVisible=o.touched||o.pressed)}})}})},t}(Rr),Bn=function(){function r(){}return r.ClearProfilesCache=function(){this._ProfilesList=null,this._ProfileLoadingPromises={}},r.DefaultFallbacks=function(){this.RegisterFallbacksForProfileId("google-daydream",["generic-touchpad"]),this.RegisterFallbacksForProfileId("htc-vive-focus",["generic-trigger-touchpad"]),this.RegisterFallbacksForProfileId("htc-vive",["generic-trigger-squeeze-touchpad"]),this.RegisterFallbacksForProfileId("magicleap-one",["generic-trigger-squeeze-touchpad"]),this.RegisterFallbacksForProfileId("windows-mixed-reality",["generic-trigger-squeeze-touchpad-thumbstick"]),this.RegisterFallbacksForProfileId("microsoft-mixed-reality",["windows-mixed-reality","generic-trigger-squeeze-touchpad-thumbstick"]),this.RegisterFallbacksForProfileId("oculus-go",["generic-trigger-touchpad"]),this.RegisterFallbacksForProfileId("oculus-touch-v2",["oculus-touch","generic-trigger-squeeze-thumbstick"]),this.RegisterFallbacksForProfileId("oculus-touch",["generic-trigger-squeeze-thumbstick"]),this.RegisterFallbacksForProfileId("samsung-gearvr",["windows-mixed-reality","generic-trigger-squeeze-touchpad-thumbstick"]),this.RegisterFallbacksForProfileId("samsung-odyssey",["generic-touchpad"]),this.RegisterFallbacksForProfileId("valve-index",["generic-trigger-squeeze-touchpad-thumbstick"])},r.FindFallbackWithProfileId=function(t){var e=this._Fallbacks[t]||[];return e.unshift(t),e},r.GetMotionControllerWithXRInput=function(t,e,n){var i=this,o=[];if(n&&o.push(n),o.push.apply(o,t.profiles||[]),o.length&&!o[0]&&o.pop(),t.gamepad&&t.gamepad.id)switch(t.gamepad.id){case(t.gamepad.id.match(/oculus touch/gi)?t.gamepad.id:void 0):o.push("oculus-touch-v2")}var a=o.indexOf("windows-mixed-reality");if(a!==-1&&o.splice(a,0,"microsoft-mixed-reality"),o.length||o.push("generic-trigger"),this.UseOnlineRepository){var s=this.PrioritizeOnlineRepository?this._LoadProfileFromRepository:this._LoadProfilesFromAvailableControllers,d=this.PrioritizeOnlineRepository?this._LoadProfilesFromAvailableControllers:this._LoadProfileFromRepository;return s.call(this,o,t,e).catch(function(){return d.call(i,o,t,e)})}return this._LoadProfilesFromAvailableControllers(o,t,e)},r.RegisterController=function(t,e){this._AvailableControllers[t]=e},r.RegisterFallbacksForProfileId=function(t,e){var n;this._Fallbacks[t]?(n=this._Fallbacks[t]).push.apply(n,e):this._Fallbacks[t]=e},r.UpdateProfilesList=function(){return this._ProfilesList=Xe.b.LoadFileAsync(this.BaseRepositoryUrl+"/profiles/profilesList.json",!1).then(function(t){return JSON.parse(t.toString())}),this._ProfilesList},r._LoadProfileFromRepository=function(t,e,n){var i=this;return Promise.resolve().then(function(){return i._ProfilesList?i._ProfilesList:i.UpdateProfilesList()}).then(function(o){for(var a=0;a<t.length;++a)if(t[a]&&o[t[a]])return t[a];throw new Error("neither controller "+t[0]+" nor all fallbacks were found in the repository,")}).then(function(o){return i._ProfileLoadingPromises[o]||(i._ProfileLoadingPromises[o]=Xe.b.LoadFileAsync(i.BaseRepositoryUrl+"/profiles/"+o+"/profile.json",!1).then(function(a){return JSON.parse(a)})),i._ProfileLoadingPromises[o]}).then(function(o){return new Au(n,e,o,i.BaseRepositoryUrl)})},r._LoadProfilesFromAvailableControllers=function(t,e,n){for(var i=0;i<t.length;++i)if(t[i])for(var o=this.FindFallbackWithProfileId(t[i]),a=0;a<o.length;++a){var s=this._AvailableControllers[o[a]];if(s)return Promise.resolve(s(e,n))}throw new Error("no controller requested was found in the available controllers list")},r._AvailableControllers={},r._Fallbacks={},r._ProfileLoadingPromises={},r.BaseRepositoryUrl="https://immersive-web.github.io/webxr-input-profiles/packages/viewer/dist",r.PrioritizeOnlineRepository=!0,r.UseOnlineRepository=!0,r}();Bn.RegisterController(Gs.ProfileId,function(r,t){return new Gs(t,r.gamepad,r.handedness)}),Bn.DefaultFallbacks();var __=0,Pu=function(){function r(t,e,n){var i=this;n===void 0&&(n={}),this._scene=t,this.inputSource=e,this._options=n,this._tmpVector=new u.e,this._disposed=!1,this.onDisposeObservable=new C.c,this.onMeshLoadedObservable=new C.c,this.onMotionControllerInitObservable=new C.c,this._uniqueId="controller-"+__+++"-"+e.targetRayMode+"-"+e.handedness,this.pointer=new Dt.a(this._uniqueId+"-pointer",t),this.pointer.rotationQuaternion=new u.b,this.inputSource.gripSpace&&(this.grip=new Dt.a(this._uniqueId+"-grip",this._scene),this.grip.rotationQuaternion=new u.b),this._tmpVector.set(0,0,this._scene.useRightHandedSystem?-1:1),this.inputSource.gamepad&&Bn.GetMotionControllerWithXRInput(e,t,this._options.forceControllerProfile).then(function(o){i.motionController=o,i.onMotionControllerInitObservable.notifyObservers(o),i._options.doNotLoadControllerMesh||i.motionController.loadModel().then(function(a){var s;a&&i.motionController&&i.motionController.rootMesh&&(i._options.renderingGroupId&&(i.motionController.rootMesh.renderingGroupId=i._options.renderingGroupId,i.motionController.rootMesh.getChildMeshes(!1).forEach(function(d){return d.renderingGroupId=i._options.renderingGroupId})),i.onMeshLoadedObservable.notifyObservers(i.motionController.rootMesh),i.motionController.rootMesh.parent=i.grip||i.pointer,i.motionController.disableAnimation=!!i._options.disableMotionControllerAnimation),i._disposed&&((s=i.motionController)===null||s===void 0||s.dispose())})},function(){Xe.b.Warn("Could not find a matching motion controller for the registered input source")})}return Object.defineProperty(r.prototype,"uniqueId",{get:function(){return this._uniqueId},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this.grip&&this.grip.dispose(),this.motionController&&this.motionController.dispose(),this.pointer.dispose(),this.onMotionControllerInitObservable.clear(),this.onMeshLoadedObservable.clear(),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear(),this._disposed=!0},r.prototype.getWorldPointerRayToRef=function(t,e){e===void 0&&(e=!1);var n=e&&this.grip?this.grip:this.pointer;u.e.TransformNormalToRef(this._tmpVector,n.getWorldMatrix(),t.direction),t.direction.normalize(),t.origin.copyFrom(n.absolutePosition),t.length=1e3},r.prototype.updateFromXRFrame=function(t,e){var n=t.getPose(this.inputSource.targetRaySpace,e);if(n){var i=n.transform.position;this.pointer.position.set(i.x,i.y,i.z);var o=n.transform.orientation;this.pointer.rotationQuaternion.set(o.x,o.y,o.z,o.w),this._scene.useRightHandedSystem||(this.pointer.position.z*=-1,this.pointer.rotationQuaternion.z*=-1,this.pointer.rotationQuaternion.w*=-1)}if(this.inputSource.gripSpace&&this.grip){var a=t.getPose(this.inputSource.gripSpace,e);if(a){i=a.transform.position;var s=a.transform.orientation;this.grip.position.set(i.x,i.y,i.z),this.grip.rotationQuaternion.set(s.x,s.y,s.z,s.w),this._scene.useRightHandedSystem||(this.grip.position.z*=-1,this.grip.rotationQuaternion.z*=-1,this.grip.rotationQuaternion.w*=-1)}}this.motionController&&this.motionController.updateFromXRFrame(t)},r}(),xu=function(){function r(t,e,n){var i=this;if(n===void 0&&(n={}),this.xrSessionManager=t,this.xrCamera=e,this.options=n,this.controllers=[],this.onControllerAddedObservable=new C.c,this.onControllerRemovedObservable=new C.c,this._onInputSourcesChange=function(o){i._addAndRemoveControllers(o.added,o.removed)},this._sessionEndedObserver=this.xrSessionManager.onXRSessionEnded.add(function(){i._addAndRemoveControllers([],i.controllers.map(function(o){return o.inputSource}))}),this._sessionInitObserver=this.xrSessionManager.onXRSessionInit.add(function(o){o.addEventListener("inputsourceschange",i._onInputSourcesChange)}),this._frameObserver=this.xrSessionManager.onXRFrameObservable.add(function(o){i.controllers.forEach(function(a){a.updateFromXRFrame(o,i.xrSessionManager.referenceSpace)})}),this.options.customControllersRepositoryURL&&(Bn.BaseRepositoryUrl=this.options.customControllersRepositoryURL),Bn.UseOnlineRepository=!this.options.disableOnlineControllerRepository,Bn.UseOnlineRepository)try{Bn.UpdateProfilesList().catch(function(){Bn.UseOnlineRepository=!1})}catch{Bn.UseOnlineRepository=!1}}return r.prototype._addAndRemoveControllers=function(t,e){for(var n=this,i=this.controllers.map(function(P){return P.inputSource}),o=0,a=t;o<a.length;o++){var s=a[o];if(i.indexOf(s)===-1){var d=new Pu(this.xrSessionManager.scene,s,Object(c.a)(Object(c.a)({},this.options.controllerOptions||{}),{forceControllerProfile:this.options.forceInputProfile,doNotLoadControllerMesh:this.options.doNotLoadControllerMeshes,disableMotionControllerAnimation:this.options.disableControllerAnimation}));this.controllers.push(d),this.onControllerAddedObservable.notifyObservers(d)}}var p=[],b=[];this.controllers.forEach(function(P){e.indexOf(P.inputSource)===-1?p.push(P):b.push(P)}),this.controllers=p,b.forEach(function(P){n.onControllerRemovedObservable.notifyObservers(P),P.dispose()})},r.prototype.dispose=function(){this.controllers.forEach(function(t){t.dispose()}),this.xrSessionManager.onXRFrameObservable.remove(this._frameObserver),this.xrSessionManager.onXRSessionInit.remove(this._sessionInitObserver),this.xrSessionManager.onXRSessionEnded.remove(this._sessionEndedObserver),this.onControllerAddedObservable.clear(),this.onControllerRemovedObservable.clear()},r}(),si=function(){function r(t){this._xrSessionManager=t,this._attached=!1,this._removeOnDetach=[],this.isDisposed=!1,this.disableAutoAttach=!1,this.xrNativeFeatureName=""}return Object.defineProperty(r.prototype,"attached",{get:function(){return this._attached},enumerable:!1,configurable:!0}),r.prototype.attach=function(t){var e=this;if(this.isDisposed)return!1;if(t)this.attached&&this.detach();else if(this.attached)return!1;return this._attached=!0,this._addNewAttachObserver(this._xrSessionManager.onXRFrameObservable,function(n){return e._onXRFrame(n)}),!0},r.prototype.detach=function(){return this._attached?(this._attached=!1,this._removeOnDetach.forEach(function(t){t.observable.remove(t.observer)}),!0):(this.disableAutoAttach=!0,!1)},r.prototype.dispose=function(){this.detach(),this.isDisposed=!0},r.prototype.isCompatible=function(){return!0},r.prototype._addNewAttachObserver=function(t,e){this._removeOnDetach.push({observable:t,observer:t.add(e)})},r}(),ho=function(r){function t(e,n){var i=r.call(this,e)||this;return i._options=n,i._attachController=function(o){if(!i._controllers[o.uniqueId]){var a=i._generateNewMeshPair(o.pointer),s=a.laserPointer,d=a.selectionMesh;switch(i._controllers[o.uniqueId]={xrController:o,laserPointer:s,selectionMesh:d,meshUnderPointer:null,pick:null,tmpRay:new fn.a(new u.e,new u.e),id:t._idCounter++},i._attachedController?!i._options.enablePointerSelectionOnAllControllers&&i._options.preferredHandedness&&o.inputSource.handedness===i._options.preferredHandedness&&(i._attachedController=o.uniqueId):i._options.enablePointerSelectionOnAllControllers||(i._attachedController=o.uniqueId),o.inputSource.targetRayMode){case"tracked-pointer":return i._attachTrackedPointerRayMode(o);case"gaze":return i._attachGazeMode(o);case"screen":return i._attachScreenRayMode(o)}}},i._controllers={},i._tmpVectorForPickCompare=new u.e,i.disablePointerLighting=!0,i.disableSelectionMeshLighting=!0,i.displayLaserPointer=!0,i.displaySelectionMesh=!0,i.laserPointerPickedColor=new M.a(.9,.9,.9),i.laserPointerDefaultColor=new M.a(.7,.7,.7),i.selectionMeshDefaultColor=new M.a(.8,.8,.8),i.selectionMeshPickedColor=new M.a(.3,.3,1),i._identityMatrix=u.a.Identity(),i._screenCoordinatesRef=u.e.Zero(),i._viewportRef=new Kn.a(0,0,0,0),i._scene=i._xrSessionManager.scene,i}return Object(c.d)(t,r),t.prototype.attach=function(){var e=this;if(!r.prototype.attach.call(this))return!1;if(this._options.xrInput.controllers.forEach(this._attachController),this._addNewAttachObserver(this._options.xrInput.onControllerAddedObservable,this._attachController),this._addNewAttachObserver(this._options.xrInput.onControllerRemovedObservable,function(s){e._detachController(s.uniqueId)}),this._scene.constantlyUpdateMeshUnderPointer=!0,this._options.gazeCamera){var n=this._options.gazeCamera,i=this._generateNewMeshPair(n),o=i.laserPointer,a=i.selectionMesh;this._controllers.camera={webXRCamera:n,laserPointer:o,selectionMesh:a,meshUnderPointer:null,pick:null,tmpRay:new fn.a(new u.e,new u.e),id:t._idCounter++},this._attachGazeMode()}return!0},t.prototype.detach=function(){var e=this;return!!r.prototype.detach.call(this)&&(Object.keys(this._controllers).forEach(function(n){e._detachController(n)}),!0)},t.prototype.getMeshUnderPointer=function(e){return this._controllers[e]?this._controllers[e].meshUnderPointer:null},t.prototype.getXRControllerByPointerId=function(e){for(var n=Object.keys(this._controllers),i=0;i<n.length;++i)if(this._controllers[n[i]].id===e)return this._controllers[n[i]].xrController||null;return null},t.prototype._onXRFrame=function(e){var n=this;Object.keys(this._controllers).forEach(function(i){var o,a=n._controllers[i];if(!n._options.enablePointerSelectionOnAllControllers&&i!==n._attachedController)return a.selectionMesh.isVisible=!1,a.laserPointer.isVisible=!1,void(a.pick=null);if(a.laserPointer.isVisible=n.displayLaserPointer,a.xrController)o=a.xrController.pointer.position,a.xrController.getWorldPointerRayToRef(a.tmpRay);else{if(!a.webXRCamera)return;o=a.webXRCamera.position,a.webXRCamera.getForwardRayToRef(a.tmpRay)}if(n._options.maxPointerDistance&&(a.tmpRay.length=n._options.maxPointerDistance),!n._options.disableScenePointerVectorUpdate&&o){var s=n._xrSessionManager.scene,d=n._options.xrInput.xrCamera;d&&(d.viewport.toGlobalToRef(s.getEngine().getRenderWidth(),s.getEngine().getRenderHeight(),n._viewportRef),u.e.ProjectToRef(o,n._identityMatrix,s.getTransformMatrix(),n._viewportRef,n._screenCoordinatesRef),s.pointerX=n._screenCoordinatesRef.x,s.pointerY=n._screenCoordinatesRef.y)}a.pick=n._scene.pickWithRay(a.tmpRay,n._scene.pointerMovePredicate||n.raySelectionPredicate);var p=a.pick;if(p&&p.pickedPoint&&p.hit){n._updatePointerDistance(a.laserPointer,p.distance),a.selectionMesh.position.copyFrom(p.pickedPoint),a.selectionMesh.scaling.x=Math.sqrt(p.distance),a.selectionMesh.scaling.y=Math.sqrt(p.distance),a.selectionMesh.scaling.z=Math.sqrt(p.distance);var b=n._convertNormalToDirectionOfRay(p.getNormal(!0),a.tmpRay);if(a.selectionMesh.position.copyFrom(p.pickedPoint),b){var P=u.e.Cross(ye.a.Y,b),O=u.e.Cross(b,P);u.e.RotationFromAxisToRef(O,b,P,a.selectionMesh.rotation),a.selectionMesh.position.addInPlace(b.scale(.001))}a.selectionMesh.isVisible=n.displaySelectionMesh,a.meshUnderPointer=p.pickedMesh}else a.selectionMesh.isVisible=!1,n._updatePointerDistance(a.laserPointer,1),a.meshUnderPointer=null})},t.prototype._attachGazeMode=function(e){var n=this,i=this._controllers[e&&e.uniqueId||"camera"],o=this._options.timeToSelect||3e3,a=this._options.useUtilityLayer?this._options.customUtilityLayerScene||On.a.DefaultUtilityLayer.utilityLayerScene:this._scene,s=new nr.a,d=gr.CreateTorus("selection",{diameter:.0525,thickness:.015,tessellation:20},a);d.isVisible=!1,d.isPickable=!1,d.parent=i.selectionMesh;var p=0,b=!1;i.onFrameObserver=this._xrSessionManager.onXRFrameObservable.add(function(){if(i.pick){if(i.laserPointer.material.alpha=0,d.isVisible=!1,i.pick.hit)if(n._pickingMoved(s,i.pick))b&&(n._options.disablePointerUpOnTouchOut||n._scene.simulatePointerUp(i.pick,{pointerId:i.id})),b=!1,p=0;else if(p>o/10&&(d.isVisible=!0),(p+=n._scene.getEngine().getDeltaTime())>=o)n._scene.simulatePointerDown(i.pick,{pointerId:i.id}),b=!0,n._options.disablePointerUpOnTouchOut&&n._scene.simulatePointerUp(i.pick,{pointerId:i.id}),d.isVisible=!1;else{var P=1-p/o;d.scaling.set(P,P,P)}else b=!1,p=0;n._scene.simulatePointerMove(i.pick,{pointerId:i.id}),s=i.pick}}),this._options.renderingGroupId!==void 0&&(d.renderingGroupId=this._options.renderingGroupId),e&&e.onDisposeObservable.addOnce(function(){i.pick&&!n._options.disablePointerUpOnTouchOut&&b&&n._scene.simulatePointerUp(i.pick,{pointerId:i.id}),d.dispose()})},t.prototype._attachScreenRayMode=function(e){var n=this,i=this._controllers[e.uniqueId],o=!1;i.onFrameObserver=this._xrSessionManager.onXRFrameObservable.add(function(){!i.pick||n._options.disablePointerUpOnTouchOut&&o||(o?n._scene.simulatePointerMove(i.pick,{pointerId:i.id}):(n._scene.simulatePointerDown(i.pick,{pointerId:i.id}),o=!0,n._options.disablePointerUpOnTouchOut&&n._scene.simulatePointerUp(i.pick,{pointerId:i.id})))}),e.onDisposeObservable.addOnce(function(){i.pick&&o&&!n._options.disablePointerUpOnTouchOut&&n._scene.simulatePointerUp(i.pick,{pointerId:i.id})})},t.prototype._attachTrackedPointerRayMode=function(e){var n=this,i=this._controllers[e.uniqueId];if(this._options.forceGazeMode)return this._attachGazeMode(e);if(i.onFrameObserver=this._xrSessionManager.onXRFrameObservable.add(function(){i.laserPointer.material.disableLighting=n.disablePointerLighting,i.selectionMesh.material.disableLighting=n.disableSelectionMeshLighting,i.pick&&n._scene.simulatePointerMove(i.pick,{pointerId:i.id})}),e.inputSource.gamepad){var o=function(d){n._options.overrideButtonId&&(i.selectionComponent=d.getComponent(n._options.overrideButtonId)),i.selectionComponent||(i.selectionComponent=d.getMainComponent()),i.onButtonChangedObserver=i.selectionComponent.onButtonStateChangedObservable.add(function(p){if(p.changes.pressed){var b=p.changes.pressed.current;i.pick?(n._options.enablePointerSelectionOnAllControllers||e.uniqueId===n._attachedController)&&(b?(n._scene.simulatePointerDown(i.pick,{pointerId:i.id}),i.selectionMesh.material.emissiveColor=n.selectionMeshPickedColor,i.laserPointer.material.emissiveColor=n.laserPointerPickedColor):(n._scene.simulatePointerUp(i.pick,{pointerId:i.id}),i.selectionMesh.material.emissiveColor=n.selectionMeshDefaultColor,i.laserPointer.material.emissiveColor=n.laserPointerDefaultColor)):!b||n._options.enablePointerSelectionOnAllControllers||n._options.disableSwitchOnClick||(n._attachedController=e.uniqueId)}})};e.motionController?o(e.motionController):e.onMotionControllerInitObservable.add(o)}else{var a=function(d){i.xrController&&d.inputSource===i.xrController.inputSource&&i.pick&&(n._scene.simulatePointerDown(i.pick,{pointerId:i.id}),i.selectionMesh.material.emissiveColor=n.selectionMeshPickedColor,i.laserPointer.material.emissiveColor=n.laserPointerPickedColor)},s=function(d){i.xrController&&d.inputSource===i.xrController.inputSource&&i.pick&&(n._scene.simulatePointerUp(i.pick,{pointerId:i.id}),i.selectionMesh.material.emissiveColor=n.selectionMeshDefaultColor,i.laserPointer.material.emissiveColor=n.laserPointerDefaultColor)};i.eventListeners={selectend:s,selectstart:a},this._xrSessionManager.session.addEventListener("selectstart",a),this._xrSessionManager.session.addEventListener("selectend",s)}},t.prototype._convertNormalToDirectionOfRay=function(e,n){return e&&Math.acos(u.e.Dot(e,n.direction))<Math.PI/2&&e.scaleInPlace(-1),e},t.prototype._detachController=function(e){var n=this,i=this._controllers[e];if(i&&(i.selectionComponent&&i.onButtonChangedObserver&&i.selectionComponent.onButtonStateChangedObservable.remove(i.onButtonChangedObserver),i.onFrameObserver&&this._xrSessionManager.onXRFrameObservable.remove(i.onFrameObserver),i.eventListeners&&Object.keys(i.eventListeners).forEach(function(a){var s=i.eventListeners&&i.eventListeners[a];s&&n._xrSessionManager.session.removeEventListener(a,s)}),i.selectionMesh.dispose(),i.laserPointer.dispose(),delete this._controllers[e],this._attachedController===e)){var o=Object.keys(this._controllers);o.length?this._attachedController=o[0]:this._attachedController=""}},t.prototype._generateNewMeshPair=function(e){var n=this._options.useUtilityLayer?this._options.customUtilityLayerScene||On.a.DefaultUtilityLayer.utilityLayerScene:this._scene,i=pi.a.CreateCylinder("laserPointer",{height:1,diameterTop:2e-4,diameterBottom:.004,tessellation:20,subdivisions:1},n);i.parent=e;var o=new Ft.a("laserPointerMat",n);o.emissiveColor=this.laserPointerDefaultColor,o.alpha=.7,i.material=o,i.rotation.x=Math.PI/2,this._updatePointerDistance(i,1),i.isPickable=!1;var a=gr.CreateTorus("gazeTracker",{diameter:.0105,thickness:.0075,tessellation:20},n);a.bakeCurrentTransformIntoVertices(),a.isPickable=!1,a.isVisible=!1;var s=new Ft.a("targetMat",n);return s.specularColor=M.a.Black(),s.emissiveColor=this.selectionMeshDefaultColor,s.backFaceCulling=!1,a.material=s,this._options.renderingGroupId!==void 0&&(i.renderingGroupId=this._options.renderingGroupId,a.renderingGroupId=this._options.renderingGroupId),{laserPointer:i,selectionMesh:a}},t.prototype._pickingMoved=function(e,n){var i;if(!e.hit||!n.hit||!(e.pickedMesh&&e.pickedPoint&&n.pickedMesh&&n.pickedPoint)||e.pickedMesh!==n.pickedMesh)return!0;(i=e.pickedPoint)===null||i===void 0||i.subtractToRef(n.pickedPoint,this._tmpVectorForPickCompare),this._tmpVectorForPickCompare.set(Math.abs(this._tmpVectorForPickCompare.x),Math.abs(this._tmpVectorForPickCompare.y),Math.abs(this._tmpVectorForPickCompare.z));var o=.01*(this._options.gazeModePointerMovedFactor||1)*n.distance;return this._tmpVectorForPickCompare.length()>o},t.prototype._updatePointerDistance=function(e,n){n===void 0&&(n=100),e.scaling.y=n,this._scene.useRightHandedSystem&&(n*=-1),e.position.z=n/2+.05},Object.defineProperty(t.prototype,"lasterPointerDefaultColor",{get:function(){return this.laserPointerDefaultColor},enumerable:!1,configurable:!0}),t._idCounter=200,t.Name=ai.POINTER_SELECTION,t.Version=1,t}(si);qn.AddWebXRFeature(ho.Name,function(r,t){return function(){return new ho(r,t)}},ho.Version,!0);var zi,Cu=function(){function r(t,e,n){this.element=t,this.sessionMode=e,this.referenceSpaceType=n}return r.prototype.update=function(t){},r}(),m_=function(){},Ru=function(){function r(t,e){var n=this;if(this.scene=t,this.options=e,this._activeButton=null,this._buttons=[],this.activeButtonChangedObservable=new C.c,this.overlay=document.createElement("div"),this.overlay.classList.add("xr-button-overlay"),this.overlay.style.cssText="z-index:11;position: absolute; right: 20px;bottom: 50px;",typeof window<"u"&&window.location&&window.location.protocol==="http:"&&Xe.b.Warn("WebXR can only be served over HTTPS"),e.customButtons)this._buttons=e.customButtons;else{var i=e.sessionMode||"immersive-vr",o=e.referenceSpaceType||"local-floor",a=".babylonVRicon { color: #868686; border-color: #868686; border-style: solid; margin-left: 10px; height: 50px; width: 80px; background-color: rgba(51,51,51,0.7); background-image: url("+(typeof SVGSVGElement>"u"?"https://cdn.babylonjs.com/Assets/vrButton.png":"data:image/svg+xml;charset=UTF-8,%3Csvg%20xmlns%3D%22http%3A//www.w3.org/2000/svg%22%20width%3D%222048%22%20height%3D%221152%22%20viewBox%3D%220%200%202048%201152%22%20version%3D%221.1%22%3E%3Cpath%20transform%3D%22rotate%28180%201024%2C576.0000000000001%29%22%20d%3D%22m1109%2C896q17%2C0%2030%2C-12t13%2C-30t-12.5%2C-30.5t-30.5%2C-12.5l-170%2C0q-18%2C0%20-30.5%2C12.5t-12.5%2C30.5t13%2C30t30%2C12l170%2C0zm-85%2C256q59%2C0%20132.5%2C-1.5t154.5%2C-5.5t164.5%2C-11.5t163%2C-20t150%2C-30t124.5%2C-41.5q23%2C-11%2042%2C-24t38%2C-30q27%2C-25%2041%2C-61.5t14%2C-72.5l0%2C-257q0%2C-123%20-47%2C-232t-128%2C-190t-190%2C-128t-232%2C-47l-81%2C0q-37%2C0%20-68.5%2C14t-60.5%2C34.5t-55.5%2C45t-53%2C45t-53%2C34.5t-55.5%2C14t-55.5%2C-14t-53%2C-34.5t-53%2C-45t-55.5%2C-45t-60.5%2C-34.5t-68.5%2C-14l-81%2C0q-123%2C0%20-232%2C47t-190%2C128t-128%2C190t-47%2C232l0%2C257q0%2C68%2038%2C115t97%2C73q54%2C24%20124.5%2C41.5t150%2C30t163%2C20t164.5%2C11.5t154.5%2C5.5t132.5%2C1.5zm939%2C-298q0%2C39%20-24.5%2C67t-58.5%2C42q-54%2C23%20-122%2C39.5t-143.5%2C28t-155.5%2C19t-157%2C11t-148.5%2C5t-129.5%2C1.5q-59%2C0%20-130%2C-1.5t-148%2C-5t-157%2C-11t-155.5%2C-19t-143.5%2C-28t-122%2C-39.5q-34%2C-14%20-58.5%2C-42t-24.5%2C-67l0%2C-257q0%2C-106%2040.5%2C-199t110%2C-162.5t162.5%2C-109.5t199%2C-40l81%2C0q27%2C0%2052%2C14t50%2C34.5t51%2C44.5t55.5%2C44.5t63.5%2C34.5t74%2C14t74%2C-14t63.5%2C-34.5t55.5%2C-44.5t51%2C-44.5t50%2C-34.5t52%2C-14l14%2C0q37%2C0%2070%2C0.5t64.5%2C4.5t63.5%2C12t68%2C23q71%2C30%20128.5%2C78.5t98.5%2C110t63.5%2C133.5t22.5%2C149l0%2C257z%22%20fill%3D%22white%22%20/%3E%3C/svg%3E%0A")+"); background-size: 80%; background-repeat:no-repeat; background-position: center; border: none; outline: none; transition: transform 0.125s ease-out } .babylonVRicon:hover { transform: scale(1.05) } .babylonVRicon:active {background-color: rgba(51,51,51,1) } .babylonVRicon:focus {background-color: rgba(51,51,51,1) }";a+='.babylonVRicon.vrdisplaypresenting { background-image: none;} .vrdisplaypresenting::after { content: "EXIT"} .xr-error::after { content: "ERROR"}';var s=document.createElement("style");s.appendChild(document.createTextNode(a)),document.getElementsByTagName("head")[0].appendChild(s);var d=document.createElement("button");d.className="babylonVRicon",d.title=i+" - "+o,this._buttons.push(new Cu(d,i,o)),this._buttons[this._buttons.length-1].update=function(b){this.element.style.display=b===null||b===this?"":"none",d.className="babylonVRicon"+(b===this?" vrdisplaypresenting":"")},this._updateButtons(null)}var p=t.getEngine().getInputElement();p&&p.parentNode&&(p.parentNode.appendChild(this.overlay),t.onDisposeObservable.addOnce(function(){n.dispose()}))}return r.CreateAsync=function(t,e,n){var i=this,o=new r(t,n),a=o._buttons.map(function(s){return e.sessionManager.isSessionSupportedAsync(s.sessionMode)});return e.onStateChangedObservable.add(function(s){s==pn.NOT_IN_XR&&o._updateButtons(null)}),Promise.all(a).then(function(s){return s.forEach(function(d,p){d?(o.overlay.appendChild(o._buttons[p].element),o._buttons[p].element.onclick=function(){return Object(c.b)(i,void 0,void 0,function(){var b,P,O;return Object(c.e)(this,function(B){switch(B.label){case 0:return e.state!=pn.IN_XR?[3,2]:[4,e.exitXRAsync()];case 1:return B.sent(),o._updateButtons(null),[3,6];case 2:if(e.state!=pn.NOT_IN_XR)return[3,6];if(!n.renderTarget)return[3,6];B.label=3;case 3:return B.trys.push([3,5,,6]),[4,e.enterXRAsync(o._buttons[p].sessionMode,o._buttons[p].referenceSpaceType,n.renderTarget,{optionalFeatures:n.optionalFeatures,requiredFeatures:n.requiredFeatures})];case 4:return B.sent(),o._updateButtons(o._buttons[p]),[3,6];case 5:return b=B.sent(),o._updateButtons(null),P=o._buttons[p].element,O=P.title,P.title="Error entering XR session : "+O,P.classList.add("xr-error"),n.onError&&n.onError(b),[3,6];case 6:return[2]}})})}):Xe.b.Warn('Session mode "'+o._buttons[p].sessionMode+'" not supported in browser')}),o})},r.prototype.dispose=function(){var t=this.scene.getEngine().getInputElement();t&&t.parentNode&&t.parentNode.contains(this.overlay)&&t.parentNode.removeChild(this.overlay),this.activeButtonChangedObservable.clear()},r.prototype._updateButtons=function(t){var e=this;this._activeButton=t,this._buttons.forEach(function(n){n.update(e._activeButton)}),this.activeButtonChangedObservable.notifyObservers(this._activeButton)},r}();function zs(r){var t,e=0,n=Date.now();r.observableParameters=(t=r.observableParameters)!==null&&t!==void 0?t:{};var i=r.contextObservable.add(function(o){var a=Date.now(),s={startTime:n,currentTime:a,deltaTime:e=a-n,completeRate:e/r.timeout,payload:o};r.onTick&&r.onTick(s),r.breakCondition&&r.breakCondition()&&(r.contextObservable.remove(i),r.onAborted&&r.onAborted(s)),e>=r.timeout&&(r.contextObservable.remove(i),r.onEnded&&r.onEnded(s))},r.observableParameters.mask,r.observableParameters.insertFirst,r.observableParameters.scope);return i}(function(r){r[r.INIT=0]="INIT",r[r.STARTED=1]="STARTED",r[r.ENDED=2]="ENDED"})(zi||(zi={}));var g_=function(){function r(t){var e,n,i=this;this.onEachCountObservable=new C.c,this.onTimerAbortedObservable=new C.c,this.onTimerEndedObservable=new C.c,this.onStateChangedObservable=new C.c,this._observer=null,this._breakOnNextTick=!1,this._tick=function(o){var a=Date.now();i._timer=a-i._startTime;var s={startTime:i._startTime,currentTime:a,deltaTime:i._timer,completeRate:i._timer/i._timeToEnd,payload:o},d=i._breakOnNextTick||i._breakCondition(s);d||i._timer>=i._timeToEnd?i._stop(s,d):i.onEachCountObservable.notifyObservers(s)},this._setState(zi.INIT),this._contextObservable=t.contextObservable,this._observableParameters=(e=t.observableParameters)!==null&&e!==void 0?e:{},this._breakCondition=(n=t.breakCondition)!==null&&n!==void 0?n:function(){return!1},t.onEnded&&this.onTimerEndedObservable.add(t.onEnded),t.onTick&&this.onEachCountObservable.add(t.onTick),t.onAborted&&this.onTimerAbortedObservable.add(t.onAborted)}return Object.defineProperty(r.prototype,"breakCondition",{set:function(t){this._breakCondition=t},enumerable:!1,configurable:!0}),r.prototype.clearObservables=function(){this.onEachCountObservable.clear(),this.onTimerAbortedObservable.clear(),this.onTimerEndedObservable.clear(),this.onStateChangedObservable.clear()},r.prototype.start=function(t){if(t===void 0&&(t=this._timeToEnd),this._state===zi.STARTED)throw new Error("Timer already started. Please stop it before starting again");this._timeToEnd=t,this._startTime=Date.now(),this._timer=0,this._observer=this._contextObservable.add(this._tick,this._observableParameters.mask,this._observableParameters.insertFirst,this._observableParameters.scope),this._setState(zi.STARTED)},r.prototype.stop=function(){this._state===zi.STARTED&&(this._breakOnNextTick=!0)},r.prototype.dispose=function(){this._observer&&this._contextObservable.remove(this._observer),this.clearObservables()},r.prototype._setState=function(t){this._state=t,this.onStateChangedObservable.notifyObservers(this._state)},r.prototype._stop=function(t,e){e===void 0&&(e=!1),this._contextObservable.remove(this._observer),this._setState(zi.ENDED),e?this.onTimerAbortedObservable.notifyObservers(t):this.onTimerEndedObservable.notifyObservers(t)},r}(),fo=function(r){function t(e,n){var i=r.call(this,e)||this;return i._options=n,i._controllers={},i._snappedToPoint=!1,i._tmpRay=new fn.a(new u.e,new u.e),i._tmpVector=new u.e,i._tmpQuaternion=new u.b,i.backwardsMovementEnabled=!0,i.backwardsTeleportationDistance=.7,i.parabolicCheckRadius=5,i.parabolicRayEnabled=!0,i.straightRayEnabled=!0,i.rotationAngle=Math.PI/8,i._rotationEnabled=!0,i._attachController=function(o){if(!(i._controllers[o.uniqueId]||i._options.forceHandedness&&o.inputSource.handedness!==i._options.forceHandedness)){i._controllers[o.uniqueId]={xrController:o,teleportationState:{forward:!1,backwards:!1,rotating:!1,currentRotation:0,baseRotation:0}};var a=i._controllers[o.uniqueId];if(a.xrController.inputSource.targetRayMode==="tracked-pointer"&&a.xrController.inputSource.gamepad){var s=function(){if(o.motionController){var d=o.motionController.getComponentOfType(Cr.THUMBSTICK_TYPE)||o.motionController.getComponentOfType(Cr.TOUCHPAD_TYPE);if(!d||i._options.useMainComponentOnly){var p=o.motionController.getMainComponent();if(!p)return;a.teleportationComponent=p,a.onButtonChangedObserver=p.onButtonStateChangedObservable.add(function(){p.changes.pressed&&(p.changes.pressed.current?(a.teleportationState.forward=!0,i._currentTeleportationControllerId=a.xrController.uniqueId,a.teleportationState.baseRotation=i._options.xrInput.xrCamera.rotationQuaternion.toEulerAngles().y,a.teleportationState.currentRotation=0,zs({timeout:i._options.timeToTeleport||3e3,contextObservable:i._xrSessionManager.onXRFrameObservable,breakCondition:function(){return!p.pressed},onEnded:function(){i._currentTeleportationControllerId===a.xrController.uniqueId&&a.teleportationState.forward&&i._teleportForward(o.uniqueId)}})):(a.teleportationState.forward=!1,i._currentTeleportationControllerId=""))})}else a.teleportationComponent=d,a.onAxisChangedObserver=d.onAxisValueChangedObservable.add(function(b){if(b.y<=.7&&a.teleportationState.backwards&&(a.teleportationState.backwards=!1),b.y>.7&&!a.teleportationState.forward&&i.backwardsMovementEnabled&&!i.snapPointsOnly&&!a.teleportationState.backwards){a.teleportationState.backwards=!0,i._tmpQuaternion.copyFrom(i._options.xrInput.xrCamera.rotationQuaternion),i._tmpQuaternion.toEulerAnglesToRef(i._tmpVector),i._tmpVector.x=0,i._tmpVector.z=0,u.b.FromEulerVectorToRef(i._tmpVector,i._tmpQuaternion),i._tmpVector.set(0,0,i.backwardsTeleportationDistance*(i._xrSessionManager.scene.useRightHandedSystem?1:-1)),i._tmpVector.rotateByQuaternionToRef(i._tmpQuaternion,i._tmpVector),i._tmpVector.addInPlace(i._options.xrInput.xrCamera.position),i._tmpRay.origin.copyFrom(i._tmpVector),i._tmpRay.length=i._options.xrInput.xrCamera.realWorldHeight+.1,i._tmpRay.direction.set(0,-1,0);var P=i._xrSessionManager.scene.pickWithRay(i._tmpRay,function(B){return i._floorMeshes.indexOf(B)!==-1});P&&P.pickedPoint&&(i._options.xrInput.xrCamera.position.x=P.pickedPoint.x,i._options.xrInput.xrCamera.position.z=P.pickedPoint.z)}if(b.y<-.7&&!i._currentTeleportationControllerId&&!a.teleportationState.rotating&&(a.teleportationState.forward=!0,i._currentTeleportationControllerId=a.xrController.uniqueId,a.teleportationState.baseRotation=i._options.xrInput.xrCamera.rotationQuaternion.toEulerAngles().y),b.x){if(a.teleportationState.forward)i._currentTeleportationControllerId===a.xrController.uniqueId&&(i.rotationEnabled?setTimeout(function(){a.teleportationState.currentRotation=Math.atan2(b.x,b.y*(i._xrSessionManager.scene.useRightHandedSystem?1:-1))}):a.teleportationState.currentRotation=0);else if(!a.teleportationState.rotating&&Math.abs(b.x)>.7){a.teleportationState.rotating=!0;var O=i.rotationAngle*(b.x>0?1:-1)*(i._xrSessionManager.scene.useRightHandedSystem?-1:1);i._options.xrInput.xrCamera.rotationQuaternion.multiplyInPlace(u.b.FromEulerAngles(0,O,0))}}else a.teleportationState.rotating=!1;b.x===0&&b.y===0&&a.teleportationState.forward&&i._teleportForward(o.uniqueId)})}};o.motionController?s():o.onMotionControllerInitObservable.addOnce(function(){s()})}else i._xrSessionManager.scene.onPointerObservable.add(function(d){d.type===Tt.a.POINTERDOWN?(a.teleportationState.forward=!0,i._currentTeleportationControllerId=a.xrController.uniqueId,a.teleportationState.baseRotation=i._options.xrInput.xrCamera.rotationQuaternion.toEulerAngles().y,a.teleportationState.currentRotation=0,zs({timeout:i._options.timeToTeleport||3e3,contextObservable:i._xrSessionManager.onXRFrameObservable,onEnded:function(){i._currentTeleportationControllerId===a.xrController.uniqueId&&a.teleportationState.forward&&i._teleportForward(o.uniqueId)}})):d.type===Tt.a.POINTERUP&&(a.teleportationState.forward=!1,i._currentTeleportationControllerId="")})}},i._options.teleportationTargetMesh||i._createDefaultTargetMesh(),i._floorMeshes=i._options.floorMeshes||[],i._snapToPositions=i._options.snapPositions||[],i._setTargetMeshVisibility(!1),i}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"rotationEnabled",{get:function(){return this._rotationEnabled},set:function(e){if(this._rotationEnabled=e,this._options.teleportationTargetMesh){var n=this._options.teleportationTargetMesh.getChildMeshes(!1,function(i){return i.name==="rotationCone"});n[0]&&n[0].setEnabled(e)}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"teleportationTargetMesh",{get:function(){return this._options.teleportationTargetMesh||null},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"snapPointsOnly",{get:function(){return!!this._options.snapPointsOnly},set:function(e){this._options.snapPointsOnly=e},enumerable:!1,configurable:!0}),t.prototype.addFloorMesh=function(e){this._floorMeshes.push(e)},t.prototype.addSnapPoint=function(e){this._snapToPositions.push(e)},t.prototype.attach=function(){var e=this;return!!r.prototype.attach.call(this)&&(this._currentTeleportationControllerId="",this._options.xrInput.controllers.forEach(this._attachController),this._addNewAttachObserver(this._options.xrInput.onControllerAddedObservable,this._attachController),this._addNewAttachObserver(this._options.xrInput.onControllerRemovedObservable,function(n){e._detachController(n.uniqueId)}),!0)},t.prototype.detach=function(){var e=this;return!!r.prototype.detach.call(this)&&(Object.keys(this._controllers).forEach(function(n){e._detachController(n)}),this._setTargetMeshVisibility(!1),this._currentTeleportationControllerId="",this._controllers={},!0)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._options.teleportationTargetMesh&&this._options.teleportationTargetMesh.dispose(!1,!0)},t.prototype.removeFloorMesh=function(e){var n=this._floorMeshes.indexOf(e);n!==-1&&this._floorMeshes.splice(n,1)},t.prototype.removeFloorMeshByName=function(e){var n=this._xrSessionManager.scene.getMeshByName(e);n&&this.removeFloorMesh(n)},t.prototype.removeSnapPoint=function(e){var n=this._snapToPositions.indexOf(e);if(n===-1){for(var i=0;i<this._snapToPositions.length;++i)if(this._snapToPositions[i].equals(e)){n=i;break}}return n!==-1&&(this._snapToPositions.splice(n,1),!0)},t.prototype.setSelectionFeature=function(e){this._selectionFeature=e},t.prototype._onXRFrame=function(e){var n=this,i=this._xrSessionManager.currentFrame,o=this._xrSessionManager.scene;if(this.attach&&i){var a=this._options.teleportationTargetMesh;if(this._currentTeleportationControllerId){if(!a)return;a.rotationQuaternion=a.rotationQuaternion||new u.b;var s=this._controllers[this._currentTeleportationControllerId];if(s&&s.teleportationState.forward){u.b.RotationYawPitchRollToRef(s.teleportationState.currentRotation+s.teleportationState.baseRotation,0,0,a.rotationQuaternion);var d=!1;if(s.xrController.getWorldPointerRayToRef(this._tmpRay),this.straightRayEnabled){if((p=o.pickWithRay(this._tmpRay,function(B){if(n._options.pickBlockerMeshes&&n._options.pickBlockerMeshes.indexOf(B)!==-1)return!0;var F=n._floorMeshes.indexOf(B);return F!==-1&&n._floorMeshes[F].absolutePosition.y<n._options.xrInput.xrCamera.position.y}))&&p.pickedMesh&&this._options.pickBlockerMeshes&&this._options.pickBlockerMeshes.indexOf(p.pickedMesh)!==-1)return;p&&p.pickedPoint&&(d=!0,this._setTargetMeshPosition(p.pickedPoint),this._setTargetMeshVisibility(!0),this._showParabolicPath(p))}if(this.parabolicRayEnabled&&!d){var p,b=s.xrController.pointer.rotationQuaternion.toEulerAngles().x,P=Math.PI/2-Math.abs(b)+1,O=this.parabolicCheckRadius*P;if(this._tmpRay.origin.addToRef(this._tmpRay.direction.scale(2*O),this._tmpVector),this._tmpVector.y=this._tmpRay.origin.y,this._tmpRay.origin.addInPlace(this._tmpRay.direction.scale(O)),this._tmpVector.subtractToRef(this._tmpRay.origin,this._tmpRay.direction),this._tmpRay.direction.normalize(),(p=o.pickWithRay(this._tmpRay,function(B){return!(!n._options.pickBlockerMeshes||n._options.pickBlockerMeshes.indexOf(B)===-1)||n._floorMeshes.indexOf(B)!==-1}))&&p.pickedMesh&&this._options.pickBlockerMeshes&&this._options.pickBlockerMeshes.indexOf(p.pickedMesh)!==-1)return;p&&p.pickedPoint&&(d=!0,this._setTargetMeshPosition(p.pickedPoint),this._setTargetMeshVisibility(!0),this._showParabolicPath(p))}this._setTargetMeshVisibility(d)}else this._setTargetMeshVisibility(!1)}else this._setTargetMeshVisibility(!1)}},t.prototype._createDefaultTargetMesh=function(){this._options.defaultTargetMeshOptions=this._options.defaultTargetMeshOptions||{};var e=this._options.useUtilityLayer?this._options.customUtilityLayerScene||On.a.DefaultUtilityLayer.utilityLayerScene:this._xrSessionManager.scene,n=Ui.CreateGround("teleportationTarget",{width:2,height:2,subdivisions:2},e);n.isPickable=!1;var i=new Ti.a("teleportationPlaneDynamicTexture",512,e,!0);i.hasAlpha=!0;var o=i.getContext();o.beginPath(),o.arc(256,256,200,0,2*Math.PI,!1),o.fillStyle=this._options.defaultTargetMeshOptions.teleportationFillColor||"#444444",o.fill(),o.lineWidth=10,o.strokeStyle=this._options.defaultTargetMeshOptions.teleportationBorderColor||"#FFFFFF",o.stroke(),o.closePath(),i.update();var a=new Ft.a("teleportationPlaneMaterial",e);a.diffuseTexture=i,n.material=a;var s=gr.CreateTorus("torusTeleportation",{diameter:.75,thickness:.1,tessellation:20},e);if(s.isPickable=!1,s.parent=n,!this._options.defaultTargetMeshOptions.disableAnimation){var d=new k("animationInnerCircle","position.y",30,k.ANIMATIONTYPE_FLOAT,k.ANIMATIONLOOPMODE_CYCLE),p=[];p.push({frame:0,value:0}),p.push({frame:30,value:.4}),p.push({frame:60,value:0}),d.setKeys(p);var b=new on;b.setEasingMode(Ge.EASINGMODE_EASEINOUT),d.setEasingFunction(b),s.animations=[],s.animations.push(d),e.beginAnimation(s,0,60,!0)}var P=pi.a.CreateCylinder("rotationCone",{diameterTop:0,tessellation:4},e);if(P.isPickable=!1,P.scaling.set(.5,.12,.2),P.rotate(ye.a.X,Math.PI/2),P.position.z=.6,P.parent=s,this._options.defaultTargetMeshOptions.torusArrowMaterial)s.material=this._options.defaultTargetMeshOptions.torusArrowMaterial,P.material=this._options.defaultTargetMeshOptions.torusArrowMaterial;else{var O=new Ft.a("torusConsMat",e);O.disableLighting=!!this._options.defaultTargetMeshOptions.disableLighting,O.disableLighting?O.emissiveColor=new M.a(.3,.3,1):O.diffuseColor=new M.a(.3,.3,1),O.alpha=.9,s.material=O,P.material=O,this._teleportationRingMaterial=O}this._options.renderingGroupId!==void 0&&(n.renderingGroupId=this._options.renderingGroupId,s.renderingGroupId=this._options.renderingGroupId,P.renderingGroupId=this._options.renderingGroupId),this._options.teleportationTargetMesh=n},t.prototype._detachController=function(e){var n=this._controllers[e];n&&(n.teleportationComponent&&(n.onAxisChangedObserver&&n.teleportationComponent.onAxisValueChangedObservable.remove(n.onAxisChangedObserver),n.onButtonChangedObserver&&n.teleportationComponent.onButtonStateChangedObservable.remove(n.onButtonChangedObserver)),delete this._controllers[e])},t.prototype._findClosestSnapPointWithRadius=function(e,n){n===void 0&&(n=this._options.snapToPositionRadius||.8);var i=null,o=Number.MAX_VALUE;if(this._snapToPositions.length){var a=n*n;this._snapToPositions.forEach(function(s){var d=u.e.DistanceSquared(s,e);d<=a&&d<o&&(o=d,i=s)})}return i},t.prototype._setTargetMeshPosition=function(e){if(this._options.teleportationTargetMesh){var n=this._findClosestSnapPointWithRadius(e);this._snappedToPoint=!!n,this.snapPointsOnly&&!this._snappedToPoint&&this._teleportationRingMaterial?this._teleportationRingMaterial.diffuseColor.set(1,.3,.3):this.snapPointsOnly&&this._snappedToPoint&&this._teleportationRingMaterial&&this._teleportationRingMaterial.diffuseColor.set(.3,.3,1),this._options.teleportationTargetMesh.position.copyFrom(n||e),this._options.teleportationTargetMesh.position.y+=.01}},t.prototype._setTargetMeshVisibility=function(e){this._options.teleportationTargetMesh&&this._options.teleportationTargetMesh.isVisible!==e&&(this._options.teleportationTargetMesh.isVisible=e,this._options.teleportationTargetMesh.getChildren(void 0,!1).forEach(function(n){n.isVisible=e}),e?this._selectionFeature&&this._selectionFeature.detach():(this._quadraticBezierCurve&&(this._quadraticBezierCurve.dispose(),this._quadraticBezierCurve=null),this._selectionFeature&&this._selectionFeature.attach()))},t.prototype._showParabolicPath=function(e){if(e.pickedPoint){var n=this._controllers[this._currentTeleportationControllerId],i=qe.d.CreateQuadraticBezier(n.xrController.pointer.absolutePosition,e.ray.origin,e.pickedPoint,25);this._options.generateRayPathMesh?this._quadraticBezierCurve=this._options.generateRayPathMesh(i.getPoints()):this._quadraticBezierCurve=cn.a.CreateLines("teleportation path line",{points:i.getPoints(),instance:this._quadraticBezierCurve,updatable:!0}),this._quadraticBezierCurve.isPickable=!1}},t.prototype._teleportForward=function(e){var n=this._controllers[e];if(n&&n.teleportationState.forward&&(n.teleportationState.forward=!1,this._currentTeleportationControllerId="",(!this.snapPointsOnly||this._snappedToPoint)&&this._options.teleportationTargetMesh&&this._options.teleportationTargetMesh.isVisible)){var i=this._options.xrInput.xrCamera.realWorldHeight;this._options.xrInput.xrCamera.onBeforeCameraTeleport.notifyObservers(this._options.xrInput.xrCamera.position),this._options.xrInput.xrCamera.position.copyFrom(this._options.teleportationTargetMesh.position),this._options.xrInput.xrCamera.position.y+=i,this._options.xrInput.xrCamera.rotationQuaternion.multiplyInPlace(u.b.FromEulerAngles(0,n.teleportationState.currentRotation-(this._xrSessionManager.scene.useRightHandedSystem?Math.PI:0),0)),this._options.xrInput.xrCamera.onAfterCameraTeleport.notifyObservers(this._options.xrInput.xrCamera.position)}},t.Name=ai.TELEPORTATION,t.Version=1,t}(si);qn.AddWebXRFeature(fo.Name,function(r,t){return function(){return new fo(r,t)}},fo.Version,!0);var v_=function(){},Ou=function(){function r(){}return r.CreateAsync=function(t,e){e===void 0&&(e={});var n=new r;return Su.CreateAsync(t).then(function(i){if(n.baseExperience=i,e.ignoreNativeCameraTransformation&&(n.baseExperience.camera.compensateOnFirstFrame=!1),n.input=new xu(i.sessionManager,i.camera,Object(c.a)({controllerOptions:{renderingGroupId:e.renderingGroupId}},e.inputOptions||{})),n.pointerSelection=n.baseExperience.featuresManager.enableFeature(ho.Name,e.useStablePlugins?"stable":"latest",{xrInput:n.input,renderingGroupId:e.renderingGroupId}),e.disableTeleportation||(n.teleportation=n.baseExperience.featuresManager.enableFeature(fo.Name,e.useStablePlugins?"stable":"latest",{floorMeshes:e.floorMeshes,xrInput:n.input,renderingGroupId:e.renderingGroupId}),n.teleportation.setSelectionFeature(n.pointerSelection)),n.renderTarget=n.baseExperience.sessionManager.getWebXRRenderTarget(e.outputCanvasOptions),!e.disableDefaultUI){var o=Object(c.a)({renderTarget:n.renderTarget},e.uiOptions||{});return e.optionalFeatures&&(typeof e.optionalFeatures=="boolean"?o.optionalFeatures=["hit-test","anchors","plane-detection","hand-tracking"]:o.optionalFeatures=e.optionalFeatures),Ru.CreateAsync(t,n.baseExperience,o).then(function(a){n.enterExitUI=a})}}).then(function(){return n}).catch(function(i){return l.a.Error("Error initializing XR"),l.a.Error(i),n})},r.prototype.dispose=function(){this.baseExperience&&this.baseExperience.dispose(),this.input&&this.input.dispose(),this.enterExitUI&&this.enterExitUI.dispose(),this.renderTarget&&this.renderTarget.dispose()},r}(),b_=!0;_e.a.prototype.createDefaultLight=function(r){if(r===void 0&&(r=!1),r&&this.lights)for(var t=0;t<this.lights.length;t++)this.lights[t].dispose();this.lights.length===0&&new Vo.a("default light",u.e.Up(),this)},_e.a.prototype.createDefaultCamera=function(r,t,e){if(r===void 0&&(r=!1),t===void 0&&(t=!1),e===void 0&&(e=!1),t&&this.activeCamera&&(this.activeCamera.dispose(),this.activeCamera=null),!this.activeCamera){var n,i=this.getWorldExtends(function(P){return P.isVisible&&P.isEnabled()}),o=i.max.subtract(i.min),a=i.min.add(o.scale(.5)),s=1.5*o.length();if(isFinite(s)||(s=1,a.copyFromFloats(0,0,0)),r){var d=new Ji("default camera",-Math.PI/2,Math.PI/2,s,a,this);d.lowerRadiusLimit=.01*s,d.wheelPrecision=100/s,n=d}else{var p=new Yn("default camera",new u.e(a.x,a.y,-s),this);p.setTarget(a),n=p}n.minZ=.01*s,n.maxZ=1e3*s,n.speed=.2*s,this.activeCamera=n;var b=this.getEngine().getInputElement();e&&b&&n.attachControl()}},_e.a.prototype.createDefaultCameraOrLight=function(r,t,e){r===void 0&&(r=!1),t===void 0&&(t=!1),e===void 0&&(e=!1),this.createDefaultLight(t),this.createDefaultCamera(r,t,e)},_e.a.prototype.createDefaultSkybox=function(r,t,e,n,i){if(t===void 0&&(t=!1),e===void 0&&(e=1e3),n===void 0&&(n=0),i===void 0&&(i=!0),!r)return l.a.Warn("Can not create default skybox without environment texture."),null;i&&r&&(this.environmentTexture=r);var o=De.a.CreateBox("hdrSkyBox",e,this);if(t){var a=new uo("skyBox",this);a.backFaceCulling=!1,a.reflectionTexture=r.clone(),a.reflectionTexture&&(a.reflectionTexture.coordinatesMode=we.a.SKYBOX_MODE),a.microSurface=1-n,a.disableLighting=!0,a.twoSidedLighting=!0,o.infiniteDistance=!0,o.material=a}else{var s=new Ft.a("skyBox",this);s.backFaceCulling=!1,s.reflectionTexture=r.clone(),s.reflectionTexture&&(s.reflectionTexture.coordinatesMode=we.a.SKYBOX_MODE),s.disableLighting=!0,o.infiniteDistance=!0,o.material=s}return o.isPickable=!1,o},_e.a.prototype.createDefaultEnvironment=function(r){return ws?new ws(r,this):null},_e.a.prototype.createDefaultVRExperience=function(r){return r===void 0&&(r={}),new ql(this,r)},_e.a.prototype.createDefaultXRExperienceAsync=function(r){return r===void 0&&(r={}),Ou.CreateAsync(this,r).then(function(t){return t})};var Mu=function(r){function t(e,n,i,o,a,s,d){o===void 0&&(o=!1),a===void 0&&(a=!1),s===void 0&&(s=we.a.TRILINEAR_SAMPLINGMODE),d===void 0&&(d={autoPlay:!0,loop:!0,autoUpdateTexture:!0});var p=r.call(this,null,i,!o,a)||this;p._onUserActionRequestedObservable=null,p._stillImageCaptured=!1,p._displayingPosterTexture=!1,p._frameId=-1,p._currentSrc=null,p._createInternalTexture=function(){if(p._texture!=null){if(!p._displayingPosterTexture)return;p._texture.dispose(),p._displayingPosterTexture=!1}if(!p._getEngine().needPOTTextures||Xe.b.IsExponentOfTwo(p.video.videoWidth)&&Xe.b.IsExponentOfTwo(p.video.videoHeight)?(p.wrapU=we.a.WRAP_ADDRESSMODE,p.wrapV=we.a.WRAP_ADDRESSMODE):(p.wrapU=we.a.CLAMP_ADDRESSMODE,p.wrapV=we.a.CLAMP_ADDRESSMODE,p._generateMipMaps=!1),p._texture=p._getEngine().createDynamicTexture(p.video.videoWidth,p.video.videoHeight,p._generateMipMaps,p.samplingMode),p.video.autoplay||p._settings.poster)p._texture.isReady=!0,p._updateInternalTexture(),p.onLoadObservable.hasObservers()&&p.onLoadObservable.notifyObservers(p);else{var P=p.video.onplaying,O=!1,B=p.video.muted;p.video.muted=!0,p.video.onplaying=function(){p.video.muted=B,p.video.onplaying=P,p._texture.isReady=!0,p._updateInternalTexture(),O||p.video.pause(),p.onLoadObservable.hasObservers()&&p.onLoadObservable.notifyObservers(p)};var F=p.video.play();F?F.then(function(){}).catch(function(){O=!0,p._onUserActionRequestedObservable&&p._onUserActionRequestedObservable.hasObservers()&&p._onUserActionRequestedObservable.notifyObservers(p)}):(p.video.onplaying=P,p._texture.isReady=!0,p._updateInternalTexture(),p.onLoadObservable.hasObservers()&&p.onLoadObservable.notifyObservers(p))}},p.reset=function(){p._texture!=null&&(p._displayingPosterTexture||(p._texture.dispose(),p._texture=null))},p._updateInternalTexture=function(){if(p._texture!=null&&p._texture.isReady&&!(p.video.readyState<p.video.HAVE_CURRENT_DATA||p._displayingPosterTexture)){var P=p.getScene().getFrameId();p._frameId!==P&&(p._frameId=P,p._getEngine().updateVideoTexture(p._texture,p.video,p._invertY))}},p._generateMipMaps=o,p._initialSamplingMode=s,p.autoUpdateTexture=d.autoUpdateTexture,p._currentSrc=n,p.name=e||p._getName(n),p.video=p._getVideo(n),p._settings=d,d.poster&&(p.video.poster=d.poster),d.autoPlay!==void 0&&(p.video.autoplay=d.autoPlay),d.loop!==void 0&&(p.video.loop=d.loop),d.muted!==void 0&&(p.video.muted=d.muted),p.video.setAttribute("playsinline",""),p.video.addEventListener("paused",p._updateInternalTexture),p.video.addEventListener("seeked",p._updateInternalTexture),p.video.addEventListener("emptied",p.reset),p._createInternalTextureOnEvent=d.poster&&!d.autoPlay?"play":"canplay",p.video.addEventListener(p._createInternalTextureOnEvent,p._createInternalTexture),d.autoPlay&&p.video.play();var b=p.video.readyState>=p.video.HAVE_CURRENT_DATA;return!d.poster||d.autoPlay&&b?b&&p._createInternalTexture():(p._texture=p._getEngine().createTexture(d.poster,!1,!p.invertY,i),p._displayingPosterTexture=!0),p}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"onUserActionRequestedObservable",{get:function(){return this._onUserActionRequestedObservable||(this._onUserActionRequestedObservable=new C.c),this._onUserActionRequestedObservable},enumerable:!1,configurable:!0}),t.prototype._getName=function(e){return e instanceof HTMLVideoElement?e.currentSrc:typeof e=="object"?e.toString():e},t.prototype._getVideo=function(e){if(e instanceof HTMLVideoElement)return Xe.b.SetCorsBehavior(e.currentSrc,e),e;var n=document.createElement("video");return typeof e=="string"?(Xe.b.SetCorsBehavior(e,n),n.src=e):(Xe.b.SetCorsBehavior(e[0],n),e.forEach(function(i){var o=document.createElement("source");o.src=i,n.appendChild(o)})),n},t.prototype._rebuild=function(){this.update()},t.prototype.update=function(){this.autoUpdateTexture&&this.updateTexture(!0)},t.prototype.updateTexture=function(e){e&&(this.video.paused&&this._stillImageCaptured||(this._stillImageCaptured=!0,this._updateInternalTexture()))},t.prototype.updateURL=function(e){this.video.src=e,this._currentSrc=e},t.prototype.clone=function(){return new t(this.name,this._currentSrc,this.getScene(),this._generateMipMaps,this.invertY,this.samplingMode,this._settings)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._currentSrc=null,this._onUserActionRequestedObservable&&(this._onUserActionRequestedObservable.clear(),this._onUserActionRequestedObservable=null),this.video.removeEventListener(this._createInternalTextureOnEvent,this._createInternalTexture),this.video.removeEventListener("paused",this._updateInternalTexture),this.video.removeEventListener("seeked",this._updateInternalTexture),this.video.removeEventListener("emptied",this.reset),this.video.pause()},t.CreateFromStreamAsync=function(e,n){var i=document.createElement("video");return e.getEngine()._badOS&&(document.body.appendChild(i),i.style.transform="scale(0.0001, 0.0001)",i.style.opacity="0",i.style.position="fixed",i.style.bottom="0px",i.style.right="0px"),i.setAttribute("autoplay",""),i.setAttribute("muted","true"),i.setAttribute("playsinline",""),i.muted=!0,i.mozSrcObject!==void 0?i.mozSrcObject=n:typeof i.srcObject=="object"?i.srcObject=n:(window.URL=window.URL||window.webkitURL||window.mozURL||window.msURL,i.src=window.URL&&window.URL.createObjectURL(n)),new Promise(function(o){var a=function(){o(new t("video",i,e,!0,!0)),i.removeEventListener("playing",a)};i.addEventListener("playing",a),i.play()})},t.CreateFromWebCamAsync=function(e,n,i){var o,a=this;return i===void 0&&(i=!1),n&&n.deviceId&&(o={exact:n.deviceId}),navigator.mediaDevices?navigator.mediaDevices.getUserMedia({video:n,audio:i}).then(function(s){return a.CreateFromStreamAsync(e,s)}):(navigator.getUserMedia=navigator.getUserMedia||navigator.webkitGetUserMedia||navigator.mozGetUserMedia||navigator.msGetUserMedia,navigator.getUserMedia&&navigator.getUserMedia({video:{deviceId:o,width:{min:n&&n.minWidth||256,max:n&&n.maxWidth||640},height:{min:n&&n.minHeight||256,max:n&&n.maxHeight||480}},audio:i},function(s){return a.CreateFromStreamAsync(e,s)},function(s){l.a.Error(s.name)}),Promise.reject("No support for userMedia on this device"))},t.CreateFromWebCam=function(e,n,i,o){o===void 0&&(o=!1),this.CreateFromWebCamAsync(e,i,o).then(function(a){n&&n(a)}).catch(function(a){l.a.Error(a.name)})},t}(we.a),y_=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"videoTexture",{get:function(){return this._texture},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"videoMode",{get:function(){return this.textureMode},set:function(e){this.textureMode=e},enumerable:!1,configurable:!0}),t.prototype._initTexture=function(e,n,i){var o=this,a={loop:i.loop,autoPlay:i.autoPlay,autoUpdateTexture:!0,poster:i.poster},s=new Mu((this.name||"videoDome")+"_texture",e,n,i.generateMipMaps,this._useDirectMapping,we.a.TRILINEAR_SAMPLINGMODE,a);return i.clickToPlay&&(n.onPointerUp=function(){o._texture.video.play()}),s},t.MODE_MONOSCOPIC=ki.MODE_MONOSCOPIC,t.MODE_TOPBOTTOM=ki.MODE_TOPBOTTOM,t.MODE_SIDEBYSIDE=ki.MODE_SIDEBYSIDE,t}(ki),jn=f(55),T_=function(){function r(t){this.engine=t,this._captureGPUFrameTime=!1,this._gpuFrameTime=new jn.a,this._captureShaderCompilationTime=!1,this._shaderCompilationTime=new jn.a,this._onBeginFrameObserver=null,this._onEndFrameObserver=null,this._onBeforeShaderCompilationObserver=null,this._onAfterShaderCompilationObserver=null}return Object.defineProperty(r.prototype,"gpuFrameTimeCounter",{get:function(){return this._gpuFrameTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureGPUFrameTime",{get:function(){return this._captureGPUFrameTime},set:function(t){var e=this;t!==this._captureGPUFrameTime&&(this._captureGPUFrameTime=t,t?(this._onBeginFrameObserver=this.engine.onBeginFrameObservable.add(function(){e._gpuFrameTimeToken||(e._gpuFrameTimeToken=e.engine.startTimeQuery())}),this._onEndFrameObserver=this.engine.onEndFrameObservable.add(function(){if(e._gpuFrameTimeToken){var n=e.engine.endTimeQuery(e._gpuFrameTimeToken);n>-1&&(e._gpuFrameTimeToken=null,e._gpuFrameTime.fetchNewFrame(),e._gpuFrameTime.addCount(n,!0))}})):(this.engine.onBeginFrameObservable.remove(this._onBeginFrameObserver),this._onBeginFrameObserver=null,this.engine.onEndFrameObservable.remove(this._onEndFrameObserver),this._onEndFrameObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"shaderCompilationTimeCounter",{get:function(){return this._shaderCompilationTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureShaderCompilationTime",{get:function(){return this._captureShaderCompilationTime},set:function(t){var e=this;t!==this._captureShaderCompilationTime&&(this._captureShaderCompilationTime=t,t?(this._onBeforeShaderCompilationObserver=this.engine.onBeforeShaderCompilationObservable.add(function(){e._shaderCompilationTime.fetchNewFrame(),e._shaderCompilationTime.beginMonitoring()}),this._onAfterShaderCompilationObserver=this.engine.onAfterShaderCompilationObservable.add(function(){e._shaderCompilationTime.endMonitoring()})):(this.engine.onBeforeShaderCompilationObservable.remove(this._onBeforeShaderCompilationObserver),this._onBeforeShaderCompilationObserver=null,this.engine.onAfterShaderCompilationObservable.remove(this._onAfterShaderCompilationObserver),this._onAfterShaderCompilationObserver=null))},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this.engine.onBeginFrameObservable.remove(this._onBeginFrameObserver),this._onBeginFrameObserver=null,this.engine.onEndFrameObservable.remove(this._onEndFrameObserver),this._onEndFrameObserver=null,this.engine.onBeforeShaderCompilationObservable.remove(this._onBeforeShaderCompilationObserver),this._onBeforeShaderCompilationObserver=null,this.engine.onAfterShaderCompilationObservable.remove(this._onAfterShaderCompilationObserver),this._onAfterShaderCompilationObserver=null,this.engine=null},r}(),E_=function(){function r(t){var e=this;this.scene=t,this._captureActiveMeshesEvaluationTime=!1,this._activeMeshesEvaluationTime=new jn.a,this._captureRenderTargetsRenderTime=!1,this._renderTargetsRenderTime=new jn.a,this._captureFrameTime=!1,this._frameTime=new jn.a,this._captureRenderTime=!1,this._renderTime=new jn.a,this._captureInterFrameTime=!1,this._interFrameTime=new jn.a,this._captureParticlesRenderTime=!1,this._particlesRenderTime=new jn.a,this._captureSpritesRenderTime=!1,this._spritesRenderTime=new jn.a,this._capturePhysicsTime=!1,this._physicsTime=new jn.a,this._captureAnimationsTime=!1,this._animationsTime=new jn.a,this._captureCameraRenderTime=!1,this._cameraRenderTime=new jn.a,this._onBeforeActiveMeshesEvaluationObserver=null,this._onAfterActiveMeshesEvaluationObserver=null,this._onBeforeRenderTargetsRenderObserver=null,this._onAfterRenderTargetsRenderObserver=null,this._onAfterRenderObserver=null,this._onBeforeDrawPhaseObserver=null,this._onAfterDrawPhaseObserver=null,this._onBeforeAnimationsObserver=null,this._onBeforeParticlesRenderingObserver=null,this._onAfterParticlesRenderingObserver=null,this._onBeforeSpritesRenderingObserver=null,this._onAfterSpritesRenderingObserver=null,this._onBeforePhysicsObserver=null,this._onAfterPhysicsObserver=null,this._onAfterAnimationsObserver=null,this._onBeforeCameraRenderObserver=null,this._onAfterCameraRenderObserver=null,this._onBeforeAnimationsObserver=t.onBeforeAnimationsObservable.add(function(){e._captureActiveMeshesEvaluationTime&&e._activeMeshesEvaluationTime.fetchNewFrame(),e._captureRenderTargetsRenderTime&&e._renderTargetsRenderTime.fetchNewFrame(),e._captureFrameTime&&(Xe.b.StartPerformanceCounter("Scene rendering"),e._frameTime.beginMonitoring()),e._captureInterFrameTime&&e._interFrameTime.endMonitoring(),e._captureParticlesRenderTime&&e._particlesRenderTime.fetchNewFrame(),e._captureSpritesRenderTime&&e._spritesRenderTime.fetchNewFrame(),e._captureAnimationsTime&&e._animationsTime.beginMonitoring(),e.scene.getEngine()._drawCalls.fetchNewFrame()}),this._onAfterRenderObserver=t.onAfterRenderObservable.add(function(){e._captureFrameTime&&(Xe.b.EndPerformanceCounter("Scene rendering"),e._frameTime.endMonitoring()),e._captureRenderTime&&e._renderTime.endMonitoring(!1),e._captureInterFrameTime&&e._interFrameTime.beginMonitoring()})}return Object.defineProperty(r.prototype,"activeMeshesEvaluationTimeCounter",{get:function(){return this._activeMeshesEvaluationTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureActiveMeshesEvaluationTime",{get:function(){return this._captureActiveMeshesEvaluationTime},set:function(t){var e=this;t!==this._captureActiveMeshesEvaluationTime&&(this._captureActiveMeshesEvaluationTime=t,t?(this._onBeforeActiveMeshesEvaluationObserver=this.scene.onBeforeActiveMeshesEvaluationObservable.add(function(){Xe.b.StartPerformanceCounter("Active meshes evaluation"),e._activeMeshesEvaluationTime.beginMonitoring()}),this._onAfterActiveMeshesEvaluationObserver=this.scene.onAfterActiveMeshesEvaluationObservable.add(function(){Xe.b.EndPerformanceCounter("Active meshes evaluation"),e._activeMeshesEvaluationTime.endMonitoring()})):(this.scene.onBeforeActiveMeshesEvaluationObservable.remove(this._onBeforeActiveMeshesEvaluationObserver),this._onBeforeActiveMeshesEvaluationObserver=null,this.scene.onAfterActiveMeshesEvaluationObservable.remove(this._onAfterActiveMeshesEvaluationObserver),this._onAfterActiveMeshesEvaluationObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"renderTargetsRenderTimeCounter",{get:function(){return this._renderTargetsRenderTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureRenderTargetsRenderTime",{get:function(){return this._captureRenderTargetsRenderTime},set:function(t){var e=this;t!==this._captureRenderTargetsRenderTime&&(this._captureRenderTargetsRenderTime=t,t?(this._onBeforeRenderTargetsRenderObserver=this.scene.onBeforeRenderTargetsRenderObservable.add(function(){Xe.b.StartPerformanceCounter("Render targets rendering"),e._renderTargetsRenderTime.beginMonitoring()}),this._onAfterRenderTargetsRenderObserver=this.scene.onAfterRenderTargetsRenderObservable.add(function(){Xe.b.EndPerformanceCounter("Render targets rendering"),e._renderTargetsRenderTime.endMonitoring(!1)})):(this.scene.onBeforeRenderTargetsRenderObservable.remove(this._onBeforeRenderTargetsRenderObserver),this._onBeforeRenderTargetsRenderObserver=null,this.scene.onAfterRenderTargetsRenderObservable.remove(this._onAfterRenderTargetsRenderObserver),this._onAfterRenderTargetsRenderObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"particlesRenderTimeCounter",{get:function(){return this._particlesRenderTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureParticlesRenderTime",{get:function(){return this._captureParticlesRenderTime},set:function(t){var e=this;t!==this._captureParticlesRenderTime&&(this._captureParticlesRenderTime=t,t?(this._onBeforeParticlesRenderingObserver=this.scene.onBeforeParticlesRenderingObservable.add(function(){Xe.b.StartPerformanceCounter("Particles"),e._particlesRenderTime.beginMonitoring()}),this._onAfterParticlesRenderingObserver=this.scene.onAfterParticlesRenderingObservable.add(function(){Xe.b.EndPerformanceCounter("Particles"),e._particlesRenderTime.endMonitoring(!1)})):(this.scene.onBeforeParticlesRenderingObservable.remove(this._onBeforeParticlesRenderingObserver),this._onBeforeParticlesRenderingObserver=null,this.scene.onAfterParticlesRenderingObservable.remove(this._onAfterParticlesRenderingObserver),this._onAfterParticlesRenderingObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"spritesRenderTimeCounter",{get:function(){return this._spritesRenderTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureSpritesRenderTime",{get:function(){return this._captureSpritesRenderTime},set:function(t){var e=this;t!==this._captureSpritesRenderTime&&(this._captureSpritesRenderTime=t,this.scene.spriteManagers&&(t?(this._onBeforeSpritesRenderingObserver=this.scene.onBeforeSpritesRenderingObservable.add(function(){Xe.b.StartPerformanceCounter("Sprites"),e._spritesRenderTime.beginMonitoring()}),this._onAfterSpritesRenderingObserver=this.scene.onAfterSpritesRenderingObservable.add(function(){Xe.b.EndPerformanceCounter("Sprites"),e._spritesRenderTime.endMonitoring(!1)})):(this.scene.onBeforeSpritesRenderingObservable.remove(this._onBeforeSpritesRenderingObserver),this._onBeforeSpritesRenderingObserver=null,this.scene.onAfterSpritesRenderingObservable.remove(this._onAfterSpritesRenderingObserver),this._onAfterSpritesRenderingObserver=null)))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"physicsTimeCounter",{get:function(){return this._physicsTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"capturePhysicsTime",{get:function(){return this._capturePhysicsTime},set:function(t){var e=this;t!==this._capturePhysicsTime&&this.scene.onBeforePhysicsObservable&&(this._capturePhysicsTime=t,t?(this._onBeforePhysicsObserver=this.scene.onBeforePhysicsObservable.add(function(){Xe.b.StartPerformanceCounter("Physics"),e._physicsTime.beginMonitoring()}),this._onAfterPhysicsObserver=this.scene.onAfterPhysicsObservable.add(function(){Xe.b.EndPerformanceCounter("Physics"),e._physicsTime.endMonitoring()})):(this.scene.onBeforePhysicsObservable.remove(this._onBeforePhysicsObserver),this._onBeforePhysicsObserver=null,this.scene.onAfterPhysicsObservable.remove(this._onAfterPhysicsObserver),this._onAfterPhysicsObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"animationsTimeCounter",{get:function(){return this._animationsTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureAnimationsTime",{get:function(){return this._captureAnimationsTime},set:function(t){var e=this;t!==this._captureAnimationsTime&&(this._captureAnimationsTime=t,t?this._onAfterAnimationsObserver=this.scene.onAfterAnimationsObservable.add(function(){e._animationsTime.endMonitoring()}):(this.scene.onAfterAnimationsObservable.remove(this._onAfterAnimationsObserver),this._onAfterAnimationsObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"frameTimeCounter",{get:function(){return this._frameTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureFrameTime",{get:function(){return this._captureFrameTime},set:function(t){this._captureFrameTime=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"interFrameTimeCounter",{get:function(){return this._interFrameTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureInterFrameTime",{get:function(){return this._captureInterFrameTime},set:function(t){this._captureInterFrameTime=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"renderTimeCounter",{get:function(){return this._renderTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureRenderTime",{get:function(){return this._captureRenderTime},set:function(t){var e=this;t!==this._captureRenderTime&&(this._captureRenderTime=t,t?(this._onBeforeDrawPhaseObserver=this.scene.onBeforeDrawPhaseObservable.add(function(){e._renderTime.beginMonitoring(),Xe.b.StartPerformanceCounter("Main render")}),this._onAfterDrawPhaseObserver=this.scene.onAfterDrawPhaseObservable.add(function(){e._renderTime.endMonitoring(!1),Xe.b.EndPerformanceCounter("Main render")})):(this.scene.onBeforeDrawPhaseObservable.remove(this._onBeforeDrawPhaseObserver),this._onBeforeDrawPhaseObserver=null,this.scene.onAfterDrawPhaseObservable.remove(this._onAfterDrawPhaseObserver),this._onAfterDrawPhaseObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"cameraRenderTimeCounter",{get:function(){return this._cameraRenderTime},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"captureCameraRenderTime",{get:function(){return this._captureCameraRenderTime},set:function(t){var e=this;t!==this._captureCameraRenderTime&&(this._captureCameraRenderTime=t,t?(this._onBeforeCameraRenderObserver=this.scene.onBeforeCameraRenderObservable.add(function(n){e._cameraRenderTime.beginMonitoring(),Xe.b.StartPerformanceCounter("Rendering camera "+n.name)}),this._onAfterCameraRenderObserver=this.scene.onAfterCameraRenderObservable.add(function(n){e._cameraRenderTime.endMonitoring(!1),Xe.b.EndPerformanceCounter("Rendering camera "+n.name)})):(this.scene.onBeforeCameraRenderObservable.remove(this._onBeforeCameraRenderObserver),this._onBeforeCameraRenderObserver=null,this.scene.onAfterCameraRenderObservable.remove(this._onAfterCameraRenderObserver),this._onAfterCameraRenderObserver=null))},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"drawCallsCounter",{get:function(){return this.scene.getEngine()._drawCalls},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this.scene.onAfterRenderObservable.remove(this._onAfterRenderObserver),this._onAfterRenderObserver=null,this.scene.onBeforeActiveMeshesEvaluationObservable.remove(this._onBeforeActiveMeshesEvaluationObserver),this._onBeforeActiveMeshesEvaluationObserver=null,this.scene.onAfterActiveMeshesEvaluationObservable.remove(this._onAfterActiveMeshesEvaluationObserver),this._onAfterActiveMeshesEvaluationObserver=null,this.scene.onBeforeRenderTargetsRenderObservable.remove(this._onBeforeRenderTargetsRenderObserver),this._onBeforeRenderTargetsRenderObserver=null,this.scene.onAfterRenderTargetsRenderObservable.remove(this._onAfterRenderTargetsRenderObserver),this._onAfterRenderTargetsRenderObserver=null,this.scene.onBeforeAnimationsObservable.remove(this._onBeforeAnimationsObserver),this._onBeforeAnimationsObserver=null,this.scene.onBeforeParticlesRenderingObservable.remove(this._onBeforeParticlesRenderingObserver),this._onBeforeParticlesRenderingObserver=null,this.scene.onAfterParticlesRenderingObservable.remove(this._onAfterParticlesRenderingObserver),this._onAfterParticlesRenderingObserver=null,this._onBeforeSpritesRenderingObserver&&(this.scene.onBeforeSpritesRenderingObservable.remove(this._onBeforeSpritesRenderingObserver),this._onBeforeSpritesRenderingObserver=null),this._onAfterSpritesRenderingObserver&&(this.scene.onAfterSpritesRenderingObservable.remove(this._onAfterSpritesRenderingObserver),this._onAfterSpritesRenderingObserver=null),this.scene.onBeforeDrawPhaseObservable.remove(this._onBeforeDrawPhaseObserver),this._onBeforeDrawPhaseObserver=null,this.scene.onAfterDrawPhaseObservable.remove(this._onAfterDrawPhaseObserver),this._onAfterDrawPhaseObserver=null,this._onBeforePhysicsObserver&&(this.scene.onBeforePhysicsObservable.remove(this._onBeforePhysicsObserver),this._onBeforePhysicsObserver=null),this._onAfterPhysicsObserver&&(this.scene.onAfterPhysicsObservable.remove(this._onAfterPhysicsObserver),this._onAfterPhysicsObserver=null),this.scene.onAfterAnimationsObservable.remove(this._onAfterAnimationsObserver),this._onAfterAnimationsObserver=null,this.scene.onBeforeCameraRenderObservable.remove(this._onBeforeCameraRenderObserver),this._onBeforeCameraRenderObserver=null,this.scene.onAfterCameraRenderObservable.remove(this._onAfterCameraRenderObserver),this._onAfterCameraRenderObserver=null,this.scene=null},r}(),S_=`#ifdef DIFFUSE
-varying vec2 vUVDiffuse;
-uniform sampler2D diffuseSampler;
-#endif
-#ifdef OPACITY
-varying vec2 vUVOpacity;
-uniform sampler2D opacitySampler;
-uniform float opacityIntensity;
-#endif
-#ifdef EMISSIVE
-varying vec2 vUVEmissive;
-uniform sampler2D emissiveSampler;
-#endif
-#ifdef VERTEXALPHA
-varying vec4 vColor;
-#endif
-uniform vec4 glowColor;
-void main(void)
-{
-vec4 finalColor=glowColor;
-
-#ifdef DIFFUSE
-vec4 albedoTexture=texture2D(diffuseSampler,vUVDiffuse);
-#ifdef GLOW
-
-finalColor.a*=albedoTexture.a;
-#endif
-#ifdef HIGHLIGHT
-
-finalColor.a=albedoTexture.a;
-#endif
-#endif
-#ifdef OPACITY
-vec4 opacityMap=texture2D(opacitySampler,vUVOpacity);
-#ifdef OPACITYRGB
-finalColor.a*=getLuminance(opacityMap.rgb);
-#else
-finalColor.a*=opacityMap.a;
-#endif
-finalColor.a*=opacityIntensity;
-#endif
-#ifdef VERTEXALPHA
-finalColor.a*=vColor.a;
-#endif
-#ifdef ALPHATEST
-if (finalColor.a<ALPHATESTVALUE)
-discard;
-#endif
-#ifdef EMISSIVE
-gl_FragColor=texture2D(emissiveSampler,vUVEmissive)*finalColor;
-#else
-gl_FragColor=finalColor;
-#endif
-#ifdef HIGHLIGHT
-
-gl_FragColor.a=glowColor.a;
-#endif
-}`;ze.a.ShadersStore.glowMapGenerationPixelShader=S_;var A_=`
-attribute vec3 position;
-#include<bonesDeclaration>
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-
-#include<instancesDeclaration>
-uniform mat4 viewProjection;
-varying vec4 vPosition;
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#ifdef DIFFUSE
-varying vec2 vUVDiffuse;
-uniform mat4 diffuseMatrix;
-#endif
-#ifdef OPACITY
-varying vec2 vUVOpacity;
-uniform mat4 opacityMatrix;
-#endif
-#ifdef EMISSIVE
-varying vec2 vUVEmissive;
-uniform mat4 emissiveMatrix;
-#endif
-#ifdef VERTEXALPHA
-attribute vec4 color;
-varying vec4 vColor;
-#endif
-void main(void)
-{
-vec3 positionUpdated=position;
-#ifdef UV1
-vec2 uvUpdated=uv;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-#include<instancesVertex>
-#include<bonesVertex>
-#ifdef CUBEMAP
-vPosition=finalWorld*vec4(positionUpdated,1.0);
-gl_Position=viewProjection*finalWorld*vec4(position,1.0);
-#else
-vPosition=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-gl_Position=vPosition;
-#endif
-#ifdef DIFFUSE
-#ifdef DIFFUSEUV1
-vUVDiffuse=vec2(diffuseMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef DIFFUSEUV2
-vUVDiffuse=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-#ifdef OPACITY
-#ifdef OPACITYUV1
-vUVOpacity=vec2(opacityMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef OPACITYUV2
-vUVOpacity=vec2(opacityMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-#ifdef EMISSIVE
-#ifdef EMISSIVEUV1
-vUVEmissive=vec2(emissiveMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef EMISSIVEUV2
-vUVEmissive=vec2(emissiveMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-#ifdef VERTEXALPHA
-vColor=color;
-#endif
-}`;ze.a.ShadersStore.glowMapGenerationVertexShader=A_;var po=function(){function r(t,e){this._vertexBuffers={},this._maxSize=0,this._mainTextureDesiredSize={width:0,height:0},this._shouldRender=!0,this._postProcesses=[],this._textures=[],this._emissiveTextureAndColor={texture:null,color:new M.b},this.neutralColor=new M.b,this.isEnabled=!0,this.disableBoundingBoxesFromEffectLayer=!1,this.onDisposeObservable=new C.c,this.onBeforeRenderMainTextureObservable=new C.c,this.onBeforeComposeObservable=new C.c,this.onBeforeRenderMeshToEffect=new C.c,this.onAfterRenderMeshToEffect=new C.c,this.onAfterComposeObservable=new C.c,this.onSizeChangedObservable=new C.c,this.name=t,this._scene=e||te.a.LastCreatedScene,r._SceneComponentInitialization(this._scene),this._engine=this._scene.getEngine(),this._maxSize=this._engine.getCaps().maxTextureSize,this._scene.effectLayers.push(this),this._generateIndexBuffer(),this._generateVertexBuffer()}return Object.defineProperty(r.prototype,"camera",{get:function(){return this._effectLayerOptions.camera},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"renderingGroupId",{get:function(){return this._effectLayerOptions.renderingGroupId},set:function(t){this._effectLayerOptions.renderingGroupId=t},enumerable:!1,configurable:!0}),r.prototype._init=function(t){this._effectLayerOptions=Object(c.a)({mainTextureRatio:.5,alphaBlendingMode:h.a.ALPHA_COMBINE,camera:null,renderingGroupId:-1},t),this._setMainTextureSize(),this._createMainTexture(),this._createTextureAndPostProcesses(),this._mergeEffect=this._createMergeEffect()},r.prototype._generateIndexBuffer=function(){var t=[];t.push(0),t.push(1),t.push(2),t.push(0),t.push(2),t.push(3),this._indexBuffer=this._engine.createIndexBuffer(t)},r.prototype._generateVertexBuffer=function(){var t=[];t.push(1,1),t.push(-1,1),t.push(-1,-1),t.push(1,-1);var e=new Oe.b(this._engine,t,Oe.b.PositionKind,!1,!1,2);this._vertexBuffers[Oe.b.PositionKind]=e},r.prototype._setMainTextureSize=function(){this._effectLayerOptions.mainTextureFixedSize?(this._mainTextureDesiredSize.width=this._effectLayerOptions.mainTextureFixedSize,this._mainTextureDesiredSize.height=this._effectLayerOptions.mainTextureFixedSize):(this._mainTextureDesiredSize.width=this._engine.getRenderWidth()*this._effectLayerOptions.mainTextureRatio,this._mainTextureDesiredSize.height=this._engine.getRenderHeight()*this._effectLayerOptions.mainTextureRatio,this._mainTextureDesiredSize.width=this._engine.needPOTTextures?Ue.a.GetExponentOfTwo(this._mainTextureDesiredSize.width,this._maxSize):this._mainTextureDesiredSize.width,this._mainTextureDesiredSize.height=this._engine.needPOTTextures?Ue.a.GetExponentOfTwo(this._mainTextureDesiredSize.height,this._maxSize):this._mainTextureDesiredSize.height),this._mainTextureDesiredSize.width=Math.floor(this._mainTextureDesiredSize.width),this._mainTextureDesiredSize.height=Math.floor(this._mainTextureDesiredSize.height)},r.prototype._createMainTexture=function(){var t=this;this._mainTexture=new sn("HighlightLayerMainRTT",{width:this._mainTextureDesiredSize.width,height:this._mainTextureDesiredSize.height},this._scene,!1,!0,h.a.TEXTURETYPE_UNSIGNED_INT),this._mainTexture.activeCamera=this._effectLayerOptions.camera,this._mainTexture.wrapU=we.a.CLAMP_ADDRESSMODE,this._mainTexture.wrapV=we.a.CLAMP_ADDRESSMODE,this._mainTexture.anisotropicFilteringLevel=1,this._mainTexture.updateSamplingMode(we.a.BILINEAR_SAMPLINGMODE),this._mainTexture.renderParticles=!1,this._mainTexture.renderList=null,this._mainTexture.ignoreCameraViewport=!0,this._mainTexture.customRenderFunction=function(n,i,o,a){var s;t.onBeforeRenderMainTextureObservable.notifyObservers(t);var d=t._scene.getEngine();if(a.length){for(d.setColorWrite(!1),s=0;s<a.length;s++)t._renderSubMesh(a.data[s]);d.setColorWrite(!0)}for(s=0;s<n.length;s++)t._renderSubMesh(n.data[s]);for(s=0;s<i.length;s++)t._renderSubMesh(i.data[s]);var p=d.getAlphaMode();for(s=0;s<o.length;s++)t._renderSubMesh(o.data[s],!0);d.setAlphaMode(p)},this._mainTexture.onClearObservable.add(function(n){n.clear(t.neutralColor,!0,!0,!0)});var e=this._scene.getBoundingBoxRenderer().enabled;this._mainTexture.onBeforeBindObservable.add(function(){t._scene.getBoundingBoxRenderer().enabled=!t.disableBoundingBoxesFromEffectLayer&&e}),this._mainTexture.onAfterUnbindObservable.add(function(){t._scene.getBoundingBoxRenderer().enabled=e})},r.prototype._addCustomEffectDefines=function(t){},r.prototype._isReady=function(t,e,n){var i=t.getMaterial();if(!i||!i.isReadyForSubMesh(t.getMesh(),t,e))return!1;var o=[],a=[Oe.b.PositionKind],s=t.getMesh(),d=!1,p=!1;if(i){var b=i.needAlphaTesting(),P=i.getAlphaTestTexture(),O=P&&P.hasAlpha&&(i.useAlphaFromDiffuseTexture||i._useAlphaFromAlbedoTexture);P&&(b||O)&&(o.push("#define DIFFUSE"),s.isVerticesDataPresent(Oe.b.UV2Kind)&&P.coordinatesIndex===1?(o.push("#define DIFFUSEUV2"),p=!0):s.isVerticesDataPresent(Oe.b.UVKind)&&(o.push("#define DIFFUSEUV1"),d=!0),b&&(o.push("#define ALPHATEST"),o.push("#define ALPHATESTVALUE 0.4")));var B=i.opacityTexture;B&&(o.push("#define OPACITY"),s.isVerticesDataPresent(Oe.b.UV2Kind)&&B.coordinatesIndex===1?(o.push("#define OPACITYUV2"),p=!0):s.isVerticesDataPresent(Oe.b.UVKind)&&(o.push("#define OPACITYUV1"),d=!0))}n&&(o.push("#define EMISSIVE"),s.isVerticesDataPresent(Oe.b.UV2Kind)&&n.coordinatesIndex===1?(o.push("#define EMISSIVEUV2"),p=!0):s.isVerticesDataPresent(Oe.b.UVKind)&&(o.push("#define EMISSIVEUV1"),d=!0)),s.isVerticesDataPresent(Oe.b.ColorKind)&&s.hasVertexAlpha&&(a.push(Oe.b.ColorKind),o.push("#define VERTEXALPHA")),d&&(a.push(Oe.b.UVKind),o.push("#define UV1")),p&&(a.push(Oe.b.UV2Kind),o.push("#define UV2"));var F=new Sr.a;if(s.useBones&&s.computeBonesUsingShaders){a.push(Oe.b.MatricesIndicesKind),a.push(Oe.b.MatricesWeightsKind),s.numBoneInfluencers>4&&(a.push(Oe.b.MatricesIndicesExtraKind),a.push(Oe.b.MatricesWeightsExtraKind)),o.push("#define NUM_BONE_INFLUENCERS "+s.numBoneInfluencers);var z=s.skeleton;z&&z.isUsingTextureForMatrices?o.push("#define BONETEXTURE"):o.push("#define BonesPerMesh "+(z?z.bones.length+1:0)),s.numBoneInfluencers>0&&F.addCPUSkinningFallback(0,s)}else o.push("#define NUM_BONE_INFLUENCERS 0");var J=s.morphTargetManager,ie=0;J&&J.numInfluencers>0&&(o.push("#define MORPHTARGETS"),ie=J.numInfluencers,o.push("#define NUM_MORPH_INFLUENCERS "+ie),et.a.PrepareAttributesForMorphTargetsInfluencers(a,s,ie)),e&&(o.push("#define INSTANCES"),et.a.PushAttributesForInstances(a),t.getRenderingMesh().hasThinInstances&&o.push("#define THIN_INSTANCES")),this._addCustomEffectDefines(o);var se=o.join(`
-`);return this._cachedDefines!==se&&(this._cachedDefines=se,this._effectLayerMapGenerationEffect=this._scene.getEngine().createEffect("glowMapGeneration",a,["world","mBones","viewProjection","glowColor","morphTargetInfluences","boneTextureWidth","diffuseMatrix","emissiveMatrix","opacityMatrix","opacityIntensity"],["diffuseSampler","emissiveSampler","opacitySampler","boneSampler"],se,F,void 0,void 0,{maxSimultaneousMorphTargets:ie})),this._effectLayerMapGenerationEffect.isReady()},r.prototype.render=function(){var t=this._mergeEffect;if(t.isReady()){for(var e=0;e<this._postProcesses.length;e++)if(!this._postProcesses[e].isReady())return;var n=this._scene.getEngine();this.onBeforeComposeObservable.notifyObservers(this),n.enableEffect(t),n.setState(!1),n.bindBuffers(this._vertexBuffers,this._indexBuffer,t);var i=n.getAlphaMode();n.setAlphaMode(this._effectLayerOptions.alphaBlendingMode),this._internalRender(t),n.setAlphaMode(i),this.onAfterComposeObservable.notifyObservers(this);var o=this._mainTexture.getSize();this._setMainTextureSize(),o.width===this._mainTextureDesiredSize.width&&o.height===this._mainTextureDesiredSize.height||(this.onSizeChangedObservable.notifyObservers(this),this._disposeTextureAndPostProcesses(),this._createMainTexture(),this._createTextureAndPostProcesses())}},r.prototype.hasMesh=function(t){return this.renderingGroupId===-1||t.renderingGroupId===this.renderingGroupId},r.prototype.shouldRender=function(){return this.isEnabled&&this._shouldRender},r.prototype._shouldRenderMesh=function(t){return!0},r.prototype._canRenderMesh=function(t,e){return!e.needAlphaBlendingForMesh(t)},r.prototype._shouldRenderEmissiveTextureForMesh=function(){return!0},r.prototype._renderSubMesh=function(t,e){var n,i=this;if(e===void 0&&(e=!1),this.shouldRender()){var o=t.getMaterial(),a=t.getMesh(),s=t.getReplacementMesh(),d=t.getRenderingMesh(),p=t.getEffectiveMesh(),b=this._scene,P=b.getEngine();if(p._internalAbstractMeshDataInfo._isActiveIntermediate=!1,o&&this._canRenderMesh(d,o)){var O=(n=d.overrideMaterialSideOrientation)!==null&&n!==void 0?n:o.sideOrientation;d._getWorldMatrixDeterminant()<0&&(O=O===Ht.a.ClockWiseSideOrientation?Ht.a.CounterClockWiseSideOrientation:Ht.a.ClockWiseSideOrientation);var B=O===Ht.a.ClockWiseSideOrientation;P.setState(o.backFaceCulling,o.zOffset,void 0,B);var F=d._getInstancesRenderList(t._id,!!s);if(!F.mustReturn&&this._shouldRenderMesh(d)){var z=F.hardwareInstancedRendering[t._id]||d.hasThinInstances;if(this._setEmissiveTextureAndColor(d,t,o),this.onBeforeRenderMeshToEffect.notifyObservers(a),this._useMeshMaterial(d))d.render(t,z,s||void 0);else if(this._isReady(t,z,this._emissiveTextureAndColor.texture)){P.enableEffect(this._effectLayerMapGenerationEffect),d._bind(t,this._effectLayerMapGenerationEffect,Ht.a.TriangleFillMode),this._effectLayerMapGenerationEffect.setMatrix("viewProjection",b.getTransformMatrix()),this._effectLayerMapGenerationEffect.setMatrix("world",p.getWorldMatrix()),this._effectLayerMapGenerationEffect.setFloat4("glowColor",this._emissiveTextureAndColor.color.r,this._emissiveTextureAndColor.color.g,this._emissiveTextureAndColor.color.b,this._emissiveTextureAndColor.color.a);var J=o.needAlphaTesting(),ie=o.getAlphaTestTexture(),se=ie&&ie.hasAlpha&&(o.useAlphaFromDiffuseTexture||o._useAlphaFromAlbedoTexture);ie&&(J||se)&&(this._effectLayerMapGenerationEffect.setTexture("diffuseSampler",ie),(ce=ie.getTextureMatrix())&&this._effectLayerMapGenerationEffect.setMatrix("diffuseMatrix",ce));var ce,ue=o.opacityTexture;if(ue&&(this._effectLayerMapGenerationEffect.setTexture("opacitySampler",ue),this._effectLayerMapGenerationEffect.setFloat("opacityIntensity",ue.level),(ce=ue.getTextureMatrix())&&this._effectLayerMapGenerationEffect.setMatrix("opacityMatrix",ce)),this._emissiveTextureAndColor.texture&&(this._effectLayerMapGenerationEffect.setTexture("emissiveSampler",this._emissiveTextureAndColor.texture),this._effectLayerMapGenerationEffect.setMatrix("emissiveMatrix",this._emissiveTextureAndColor.texture.getTextureMatrix())),d.useBones&&d.computeBonesUsingShaders&&d.skeleton){var fe=d.skeleton;if(fe.isUsingTextureForMatrices){var ve=fe.getTransformMatrixTexture(d);if(!ve)return;this._effectLayerMapGenerationEffect.setTexture("boneSampler",ve),this._effectLayerMapGenerationEffect.setFloat("boneTextureWidth",4*(fe.bones.length+1))}else this._effectLayerMapGenerationEffect.setMatrices("mBones",fe.getTransformMatrices(d))}et.a.BindMorphTargetParameters(d,this._effectLayerMapGenerationEffect),e&&P.setAlphaMode(o.alphaMode),d._processRendering(p,t,this._effectLayerMapGenerationEffect,o.fillMode,F,z,function(Te,Re){return i._effectLayerMapGenerationEffect.setMatrix("world",Re)})}else this._mainTexture.resetRefreshCounter();this.onAfterRenderMeshToEffect.notifyObservers(a)}}}},r.prototype._useMeshMaterial=function(t){return!1},r.prototype._rebuild=function(){var t=this._vertexBuffers[Oe.b.PositionKind];t&&t._rebuild(),this._generateIndexBuffer()},r.prototype._disposeTextureAndPostProcesses=function(){this._mainTexture.dispose();for(var t=0;t<this._postProcesses.length;t++)this._postProcesses[t]&&this._postProcesses[t].dispose();for(this._postProcesses=[],t=0;t<this._textures.length;t++)this._textures[t]&&this._textures[t].dispose();this._textures=[]},r.prototype.dispose=function(){var t=this._vertexBuffers[Oe.b.PositionKind];t&&(t.dispose(),this._vertexBuffers[Oe.b.PositionKind]=null),this._indexBuffer&&(this._scene.getEngine()._releaseBuffer(this._indexBuffer),this._indexBuffer=null),this._disposeTextureAndPostProcesses();var e=this._scene.effectLayers.indexOf(this,0);e>-1&&this._scene.effectLayers.splice(e,1),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear(),this.onBeforeRenderMainTextureObservable.clear(),this.onBeforeComposeObservable.clear(),this.onBeforeRenderMeshToEffect.clear(),this.onAfterRenderMeshToEffect.clear(),this.onAfterComposeObservable.clear(),this.onSizeChangedObservable.clear()},r.prototype.getClassName=function(){return"EffectLayer"},r.Parse=function(t,e,n){return Xe.b.Instantiate(t.customType).Parse(t,e,n)},r._SceneComponentInitialization=function(t){throw An.a.WarnImport("EffectLayerSceneComponent")},Object(c.c)([Object(L.c)()],r.prototype,"name",void 0),Object(c.c)([Object(L.f)()],r.prototype,"neutralColor",void 0),Object(c.c)([Object(L.c)()],r.prototype,"isEnabled",void 0),Object(c.c)([Object(L.d)()],r.prototype,"camera",null),Object(c.c)([Object(L.c)()],r.prototype,"renderingGroupId",null),Object(c.c)([Object(L.c)()],r.prototype,"disableBoundingBoxesFromEffectLayer",void 0),r}();U.a.AddParser(at.a.NAME_EFFECTLAYER,function(r,t,e,n){if(r.effectLayers){e.effectLayers||(e.effectLayers=new Array);for(var i=0;i<r.effectLayers.length;i++){var o=po.Parse(r.effectLayers[i],t,n);e.effectLayers.push(o)}}}),U.a.prototype.removeEffectLayer=function(r){var t=this.effectLayers.indexOf(r);return t!==-1&&this.effectLayers.splice(t,1),t},U.a.prototype.addEffectLayer=function(r){this.effectLayers.push(r)};var Iu=function(){function r(t){this.name=at.a.NAME_EFFECTLAYER,this._renderEffects=!1,this._needStencil=!1,this._previousStencilState=!1,this.scene=t,this._engine=t.getEngine(),t.effectLayers=new Array}return r.prototype.register=function(){this.scene._isReadyForMeshStage.registerStep(at.a.STEP_ISREADYFORMESH_EFFECTLAYER,this,this._isReadyForMesh),this.scene._cameraDrawRenderTargetStage.registerStep(at.a.STEP_CAMERADRAWRENDERTARGET_EFFECTLAYER,this,this._renderMainTexture),this.scene._beforeCameraDrawStage.registerStep(at.a.STEP_BEFORECAMERADRAW_EFFECTLAYER,this,this._setStencil),this.scene._afterRenderingGroupDrawStage.registerStep(at.a.STEP_AFTERRENDERINGGROUPDRAW_EFFECTLAYER_DRAW,this,this._drawRenderingGroup),this.scene._afterCameraDrawStage.registerStep(at.a.STEP_AFTERCAMERADRAW_EFFECTLAYER,this,this._setStencilBack),this.scene._afterCameraDrawStage.registerStep(at.a.STEP_AFTERCAMERADRAW_EFFECTLAYER_DRAW,this,this._drawCamera)},r.prototype.rebuild=function(){for(var t=0,e=this.scene.effectLayers;t<e.length;t++)e[t]._rebuild()},r.prototype.serialize=function(t){t.effectLayers=[];for(var e=0,n=this.scene.effectLayers;e<n.length;e++){var i=n[e];i.serialize&&t.effectLayers.push(i.serialize())}},r.prototype.addFromContainer=function(t){var e=this;t.effectLayers&&t.effectLayers.forEach(function(n){e.scene.addEffectLayer(n)})},r.prototype.removeFromContainer=function(t,e){var n=this;t.effectLayers&&t.effectLayers.forEach(function(i){n.scene.removeEffectLayer(i),e&&i.dispose()})},r.prototype.dispose=function(){for(var t=this.scene.effectLayers;t.length;)t[0].dispose()},r.prototype._isReadyForMesh=function(t,e){for(var n=0,i=this.scene.effectLayers;n<i.length;n++){var o=i[n];if(o.hasMesh(t))for(var a=0,s=t.subMeshes;a<s.length;a++){var d=s[a];if(!o.isReady(d,e))return!1}}return!0},r.prototype._renderMainTexture=function(t){this._renderEffects=!1,this._needStencil=!1;var e=!1,n=this.scene.effectLayers;if(n&&n.length>0){this._previousStencilState=this._engine.getStencilBuffer();for(var i=0,o=n;i<o.length;i++){var a=o[i];if(a.shouldRender()&&(!a.camera||a.camera.cameraRigMode===gt.a.RIG_MODE_NONE&&t===a.camera||a.camera.cameraRigMode!==gt.a.RIG_MODE_NONE&&a.camera._rigCameras.indexOf(t)>-1)){this._renderEffects=!0,this._needStencil=this._needStencil||a.needStencil();var s=a._mainTexture;s._shouldRender()&&(this.scene.incrementRenderId(),s.render(!1,!1),e=!0)}}this.scene.incrementRenderId()}return e},r.prototype._setStencil=function(){this._needStencil&&this._engine.setStencilBuffer(!0)},r.prototype._setStencilBack=function(){this._needStencil&&this._engine.setStencilBuffer(this._previousStencilState)},r.prototype._draw=function(t){if(this._renderEffects){this._engine.setDepthBuffer(!1);for(var e=this.scene.effectLayers,n=0;n<e.length;n++){var i=e[n];i.renderingGroupId===t&&i.shouldRender()&&i.render()}this._engine.setDepthBuffer(!0)}},r.prototype._drawCamera=function(){this._renderEffects&&this._draw(-1)},r.prototype._drawRenderingGroup=function(t){!this.scene._isInIntermediateRendering()&&this._renderEffects&&this._draw(t)},r}();po._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_EFFECTLAYER);t||(t=new Iu(r),r._addComponent(t))};var P_=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-#ifdef EMISSIVE
-uniform sampler2D textureSampler2;
-#endif
-
-uniform float offset;
-void main(void) {
-vec4 baseColor=texture2D(textureSampler,vUV);
-#ifdef EMISSIVE
-baseColor+=texture2D(textureSampler2,vUV);
-baseColor*=offset;
-#else
-baseColor.a=abs(offset-baseColor.a);
-#ifdef STROKE
-float alpha=smoothstep(.0,.1,baseColor.a);
-baseColor.a=alpha;
-baseColor.rgb=baseColor.rgb*alpha;
-#endif
-#endif
-gl_FragColor=baseColor;
-}`;ze.a.ShadersStore.glowMapMergePixelShader=P_;var x_=`
-attribute vec2 position;
-
-varying vec2 vUV;
-const vec2 madd=vec2(0.5,0.5);
-void main(void) {
-vUV=position*madd+madd;
-gl_Position=vec4(position,0.0,1.0);
-}`;ze.a.ShadersStore.glowMapMergeVertexShader=x_,U.a.prototype.getGlowLayerByName=function(r){for(var t=0;t<this.effectLayers.length;t++)if(this.effectLayers[t].name===r&&this.effectLayers[t].getEffectName()===ra.EffectName)return this.effectLayers[t];return null};var ra=function(r){function t(e,n,i){var o=r.call(this,e,n)||this;return o._intensity=1,o._includedOnlyMeshes=[],o._excludedMeshes=[],o._meshesUsingTheirOwnMaterials=[],o.neutralColor=new M.b(0,0,0,1),o._options=Object(c.a)({mainTextureRatio:t.DefaultTextureRatio,blurKernelSize:32,mainTextureFixedSize:void 0,camera:null,mainTextureSamples:1,renderingGroupId:-1},i),o._init({alphaBlendingMode:h.a.ALPHA_ADD,camera:o._options.camera,mainTextureFixedSize:o._options.mainTextureFixedSize,mainTextureRatio:o._options.mainTextureRatio,renderingGroupId:o._options.renderingGroupId}),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"blurKernelSize",{get:function(){return this._horizontalBlurPostprocess1.kernel},set:function(e){this._horizontalBlurPostprocess1.kernel=e,this._verticalBlurPostprocess1.kernel=e,this._horizontalBlurPostprocess2.kernel=e,this._verticalBlurPostprocess2.kernel=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"intensity",{get:function(){return this._intensity},set:function(e){this._intensity=e},enumerable:!1,configurable:!0}),t.prototype.getEffectName=function(){return t.EffectName},t.prototype._createMergeEffect=function(){return this._engine.createEffect("glowMapMerge",[Oe.b.PositionKind],["offset"],["textureSampler","textureSampler2"],`#define EMISSIVE 
-`)},t.prototype._createTextureAndPostProcesses=function(){var e=this,n=this._mainTextureDesiredSize.width,i=this._mainTextureDesiredSize.height;n=this._engine.needPOTTextures?Ue.a.GetExponentOfTwo(n,this._maxSize):n,i=this._engine.needPOTTextures?Ue.a.GetExponentOfTwo(i,this._maxSize):i;var o=0;o=this._engine.getCaps().textureHalfFloatRender?h.a.TEXTURETYPE_HALF_FLOAT:h.a.TEXTURETYPE_UNSIGNED_INT,this._blurTexture1=new sn("GlowLayerBlurRTT",{width:n,height:i},this._scene,!1,!0,o),this._blurTexture1.wrapU=we.a.CLAMP_ADDRESSMODE,this._blurTexture1.wrapV=we.a.CLAMP_ADDRESSMODE,this._blurTexture1.updateSamplingMode(we.a.BILINEAR_SAMPLINGMODE),this._blurTexture1.renderParticles=!1,this._blurTexture1.ignoreCameraViewport=!0;var a=Math.floor(n/2),s=Math.floor(i/2);this._blurTexture2=new sn("GlowLayerBlurRTT2",{width:a,height:s},this._scene,!1,!0,o),this._blurTexture2.wrapU=we.a.CLAMP_ADDRESSMODE,this._blurTexture2.wrapV=we.a.CLAMP_ADDRESSMODE,this._blurTexture2.updateSamplingMode(we.a.BILINEAR_SAMPLINGMODE),this._blurTexture2.renderParticles=!1,this._blurTexture2.ignoreCameraViewport=!0,this._textures=[this._blurTexture1,this._blurTexture2],this._horizontalBlurPostprocess1=new gn("GlowLayerHBP1",new u.d(1,0),this._options.blurKernelSize/2,{width:n,height:i},null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,o),this._horizontalBlurPostprocess1.width=n,this._horizontalBlurPostprocess1.height=i,this._horizontalBlurPostprocess1.onApplyObservable.add(function(d){d.setTexture("textureSampler",e._mainTexture)}),this._verticalBlurPostprocess1=new gn("GlowLayerVBP1",new u.d(0,1),this._options.blurKernelSize/2,{width:n,height:i},null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,o),this._horizontalBlurPostprocess2=new gn("GlowLayerHBP2",new u.d(1,0),this._options.blurKernelSize/2,{width:a,height:s},null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,o),this._horizontalBlurPostprocess2.width=a,this._horizontalBlurPostprocess2.height=s,this._horizontalBlurPostprocess2.onApplyObservable.add(function(d){d.setTexture("textureSampler",e._blurTexture1)}),this._verticalBlurPostprocess2=new gn("GlowLayerVBP2",new u.d(0,1),this._options.blurKernelSize/2,{width:a,height:s},null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,o),this._postProcesses=[this._horizontalBlurPostprocess1,this._verticalBlurPostprocess1,this._horizontalBlurPostprocess2,this._verticalBlurPostprocess2],this._postProcesses1=[this._horizontalBlurPostprocess1,this._verticalBlurPostprocess1],this._postProcesses2=[this._horizontalBlurPostprocess2,this._verticalBlurPostprocess2],this._mainTexture.samples=this._options.mainTextureSamples,this._mainTexture.onAfterUnbindObservable.add(function(){var d=e._blurTexture1.getInternalTexture();if(d){e._scene.postProcessManager.directRender(e._postProcesses1,d,!0);var p=e._blurTexture2.getInternalTexture();p&&e._scene.postProcessManager.directRender(e._postProcesses2,p,!0),e._engine.unBindFramebuffer(p??d,!0)}}),this._postProcesses.map(function(d){d.autoClear=!1})},t.prototype.isReady=function(e,n){var i=e.getMaterial(),o=e.getRenderingMesh();if(!i||!o)return!1;var a=i.emissiveTexture;return r.prototype._isReady.call(this,e,n,a)},t.prototype.needStencil=function(){return!1},t.prototype._canRenderMesh=function(e,n){return!0},t.prototype._internalRender=function(e){e.setTexture("textureSampler",this._blurTexture1),e.setTexture("textureSampler2",this._blurTexture2),e.setFloat("offset",this._intensity);var n=this._engine,i=n.getStencilBuffer();n.setStencilBuffer(!1),n.drawElementsType(Ht.a.TriangleFillMode,0,6),n.setStencilBuffer(i)},t.prototype._setEmissiveTextureAndColor=function(e,n,i){var o=1;this.customEmissiveTextureSelector?this._emissiveTextureAndColor.texture=this.customEmissiveTextureSelector(e,n,i):i?(this._emissiveTextureAndColor.texture=i.emissiveTexture,this._emissiveTextureAndColor.texture&&(o=this._emissiveTextureAndColor.texture.level)):this._emissiveTextureAndColor.texture=null,this.customEmissiveColorSelector?this.customEmissiveColorSelector(e,n,i,this._emissiveTextureAndColor.color):i.emissiveColor?this._emissiveTextureAndColor.color.set(i.emissiveColor.r*o,i.emissiveColor.g*o,i.emissiveColor.b*o,i.alpha):this._emissiveTextureAndColor.color.set(this.neutralColor.r,this.neutralColor.g,this.neutralColor.b,this.neutralColor.a)},t.prototype._shouldRenderMesh=function(e){return this.hasMesh(e)},t.prototype._addCustomEffectDefines=function(e){e.push("#define GLOW")},t.prototype.addExcludedMesh=function(e){this._excludedMeshes.indexOf(e.uniqueId)===-1&&this._excludedMeshes.push(e.uniqueId)},t.prototype.removeExcludedMesh=function(e){var n=this._excludedMeshes.indexOf(e.uniqueId);n!==-1&&this._excludedMeshes.splice(n,1)},t.prototype.addIncludedOnlyMesh=function(e){this._includedOnlyMeshes.indexOf(e.uniqueId)===-1&&this._includedOnlyMeshes.push(e.uniqueId)},t.prototype.removeIncludedOnlyMesh=function(e){var n=this._includedOnlyMeshes.indexOf(e.uniqueId);n!==-1&&this._includedOnlyMeshes.splice(n,1)},t.prototype.hasMesh=function(e){return!!r.prototype.hasMesh.call(this,e)&&(this._includedOnlyMeshes.length?this._includedOnlyMeshes.indexOf(e.uniqueId)!==-1:!this._excludedMeshes.length||this._excludedMeshes.indexOf(e.uniqueId)===-1)},t.prototype._useMeshMaterial=function(e){return this._meshesUsingTheirOwnMaterials.length!=0&&this._meshesUsingTheirOwnMaterials.indexOf(e.uniqueId)>-1},t.prototype.referenceMeshToUseItsOwnMaterial=function(e){this._meshesUsingTheirOwnMaterials.push(e.uniqueId)},t.prototype.unReferenceMeshFromUsingItsOwnMaterial=function(e){for(var n=this._meshesUsingTheirOwnMaterials.indexOf(e.uniqueId);n>=0;)this._meshesUsingTheirOwnMaterials.splice(n,1),n=this._meshesUsingTheirOwnMaterials.indexOf(e.uniqueId)},t.prototype._disposeMesh=function(e){this.removeIncludedOnlyMesh(e),this.removeExcludedMesh(e)},t.prototype.getClassName=function(){return"GlowLayer"},t.prototype.serialize=function(){var e,n=L.a.Serialize(this);if(n.customType="BABYLON.GlowLayer",n.includedMeshes=[],this._includedOnlyMeshes.length)for(e=0;e<this._includedOnlyMeshes.length;e++)(i=this._scene.getMeshByUniqueID(this._includedOnlyMeshes[e]))&&n.includedMeshes.push(i.id);if(n.excludedMeshes=[],this._excludedMeshes.length)for(e=0;e<this._excludedMeshes.length;e++){var i;(i=this._scene.getMeshByUniqueID(this._excludedMeshes[e]))&&n.excludedMeshes.push(i.id)}return n},t.Parse=function(e,n,i){var o,a=L.a.Parse(function(){return new t(e.name,n,e.options)},e,n,i);for(o=0;o<e.excludedMeshes.length;o++)(s=n.getMeshByID(e.excludedMeshes[o]))&&a.addExcludedMesh(s);for(o=0;o<e.includedMeshes.length;o++){var s;(s=n.getMeshByID(e.includedMeshes[o]))&&a.addIncludedOnlyMesh(s)}return a},t.EffectName="GlowLayer",t.DefaultBlurKernelSize=32,t.DefaultTextureRatio=.5,Object(c.c)([Object(L.c)()],t.prototype,"blurKernelSize",null),Object(c.c)([Object(L.c)()],t.prototype,"intensity",null),Object(c.c)([Object(L.c)("options")],t.prototype,"_options",void 0),t}(po);R.a.RegisteredTypes["BABYLON.GlowLayer"]=ra;var C_=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-
-uniform vec2 screenSize;
-uniform vec2 direction;
-uniform float blurWidth;
-
-float getLuminance(vec3 color)
-{
-return dot(color,vec3(0.2126,0.7152,0.0722));
-}
-void main(void)
-{
-float weights[7];
-weights[0]=0.05;
-weights[1]=0.1;
-weights[2]=0.2;
-weights[3]=0.3;
-weights[4]=0.2;
-weights[5]=0.1;
-weights[6]=0.05;
-vec2 texelSize=vec2(1.0/screenSize.x,1.0/screenSize.y);
-vec2 texelStep=texelSize*direction*blurWidth;
-vec2 start=vUV-3.0*texelStep;
-vec4 baseColor=vec4(0.,0.,0.,0.);
-vec2 texelOffset=vec2(0.,0.);
-for (int i=0; i<7; i++)
-{
-
-vec4 texel=texture2D(textureSampler,start+texelOffset);
-baseColor.a+=texel.a*weights[i];
-
-float luminance=getLuminance(baseColor.rgb);
-float luminanceTexel=getLuminance(texel.rgb);
-float choice=step(luminanceTexel,luminance);
-baseColor.rgb=choice*baseColor.rgb+(1.0-choice)*texel.rgb;
-texelOffset+=texelStep;
-}
-gl_FragColor=baseColor;
-}`;ze.a.ShadersStore.glowBlurPostProcessPixelShader=C_,U.a.prototype.getHighlightLayerByName=function(r){for(var t=0;t<this.effectLayers.length;t++)if(this.effectLayers[t].name===r&&this.effectLayers[t].getEffectName()===js.EffectName)return this.effectLayers[t];return null};var Du=function(r){function t(e,n,i,o,a,s,d,p){s===void 0&&(s=we.a.BILINEAR_SAMPLINGMODE);var b=r.call(this,e,"glowBlurPostProcess",["screenSize","direction","blurWidth"],null,o,a,s,d,p)||this;return b.direction=n,b.kernel=i,b.onApplyObservable.add(function(P){P.setFloat2("screenSize",b.width,b.height),P.setVector2("direction",b.direction),P.setFloat("blurWidth",b.kernel)}),b}return Object(c.d)(t,r),t}(_t),js=function(r){function t(e,n,i){var o=r.call(this,e,n)||this;return o.name=e,o.innerGlow=!0,o.outerGlow=!0,o.onBeforeBlurObservable=new C.c,o.onAfterBlurObservable=new C.c,o._instanceGlowingMeshStencilReference=t.GlowingMeshStencilReference++,o._meshes={},o._excludedMeshes={},o.neutralColor=t.NeutralColor,o._engine.isStencilEnable||l.a.Warn("Rendering the Highlight Layer requires the stencil to be active on the canvas. var engine = new Engine(canvas, antialias, { stencil: true }"),o._options=Object(c.a)({mainTextureRatio:.5,blurTextureSizeRatio:.5,blurHorizontalSize:1,blurVerticalSize:1,alphaBlendingMode:h.a.ALPHA_COMBINE,camera:null,renderingGroupId:-1},i),o._init({alphaBlendingMode:o._options.alphaBlendingMode,camera:o._options.camera,mainTextureFixedSize:o._options.mainTextureFixedSize,mainTextureRatio:o._options.mainTextureRatio,renderingGroupId:o._options.renderingGroupId}),o._shouldRender=!1,o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"blurHorizontalSize",{get:function(){return this._horizontalBlurPostprocess.kernel},set:function(e){this._horizontalBlurPostprocess.kernel=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"blurVerticalSize",{get:function(){return this._verticalBlurPostprocess.kernel},set:function(e){this._verticalBlurPostprocess.kernel=e},enumerable:!1,configurable:!0}),t.prototype.getEffectName=function(){return t.EffectName},t.prototype._createMergeEffect=function(){return this._engine.createEffect("glowMapMerge",[Oe.b.PositionKind],["offset"],["textureSampler"],this._options.isStroke?`#define STROKE 
-`:void 0)},t.prototype._createTextureAndPostProcesses=function(){var e=this,n=this._mainTextureDesiredSize.width*this._options.blurTextureSizeRatio,i=this._mainTextureDesiredSize.height*this._options.blurTextureSizeRatio;n=this._engine.needPOTTextures?Ue.a.GetExponentOfTwo(n,this._maxSize):n,i=this._engine.needPOTTextures?Ue.a.GetExponentOfTwo(i,this._maxSize):i;var o=0;o=this._engine.getCaps().textureHalfFloatRender?h.a.TEXTURETYPE_HALF_FLOAT:h.a.TEXTURETYPE_UNSIGNED_INT,this._blurTexture=new sn("HighlightLayerBlurRTT",{width:n,height:i},this._scene,!1,!0,o),this._blurTexture.wrapU=we.a.CLAMP_ADDRESSMODE,this._blurTexture.wrapV=we.a.CLAMP_ADDRESSMODE,this._blurTexture.anisotropicFilteringLevel=16,this._blurTexture.updateSamplingMode(we.a.TRILINEAR_SAMPLINGMODE),this._blurTexture.renderParticles=!1,this._blurTexture.ignoreCameraViewport=!0,this._textures=[this._blurTexture],this._options.alphaBlendingMode===h.a.ALPHA_COMBINE?(this._downSamplePostprocess=new Fi("HighlightLayerPPP",this._options.blurTextureSizeRatio,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine()),this._downSamplePostprocess.onApplyObservable.add(function(a){a.setTexture("textureSampler",e._mainTexture)}),this._horizontalBlurPostprocess=new Du("HighlightLayerHBP",new u.d(1,0),this._options.blurHorizontalSize,1,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine()),this._horizontalBlurPostprocess.onApplyObservable.add(function(a){a.setFloat2("screenSize",n,i)}),this._verticalBlurPostprocess=new Du("HighlightLayerVBP",new u.d(0,1),this._options.blurVerticalSize,1,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine()),this._verticalBlurPostprocess.onApplyObservable.add(function(a){a.setFloat2("screenSize",n,i)}),this._postProcesses=[this._downSamplePostprocess,this._horizontalBlurPostprocess,this._verticalBlurPostprocess]):(this._horizontalBlurPostprocess=new gn("HighlightLayerHBP",new u.d(1,0),this._options.blurHorizontalSize/2,{width:n,height:i},null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,o),this._horizontalBlurPostprocess.width=n,this._horizontalBlurPostprocess.height=i,this._horizontalBlurPostprocess.onApplyObservable.add(function(a){a.setTexture("textureSampler",e._mainTexture)}),this._verticalBlurPostprocess=new gn("HighlightLayerVBP",new u.d(0,1),this._options.blurVerticalSize/2,{width:n,height:i},null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,o),this._postProcesses=[this._horizontalBlurPostprocess,this._verticalBlurPostprocess]),this._mainTexture.onAfterUnbindObservable.add(function(){e.onBeforeBlurObservable.notifyObservers(e);var a=e._blurTexture.getInternalTexture();a&&(e._scene.postProcessManager.directRender(e._postProcesses,a,!0),e._engine.unBindFramebuffer(a,!0)),e.onAfterBlurObservable.notifyObservers(e)}),this._postProcesses.map(function(a){a.autoClear=!1})},t.prototype.needStencil=function(){return!0},t.prototype.isReady=function(e,n){var i=e.getMaterial(),o=e.getRenderingMesh();if(!i||!o||!this._meshes)return!1;var a=null,s=this._meshes[o.uniqueId];return s&&s.glowEmissiveOnly&&i&&(a=i.emissiveTexture),r.prototype._isReady.call(this,e,n,a)},t.prototype._internalRender=function(e){e.setTexture("textureSampler",this._blurTexture);var n=this._engine;n.cacheStencilState(),n.setStencilOperationPass(h.a.REPLACE),n.setStencilOperationFail(h.a.KEEP),n.setStencilOperationDepthFail(h.a.KEEP),n.setStencilMask(0),n.setStencilBuffer(!0),n.setStencilFunctionReference(this._instanceGlowingMeshStencilReference),this.outerGlow&&(e.setFloat("offset",0),n.setStencilFunction(h.a.NOTEQUAL),n.drawElementsType(Ht.a.TriangleFillMode,0,6)),this.innerGlow&&(e.setFloat("offset",1),n.setStencilFunction(h.a.EQUAL),n.drawElementsType(Ht.a.TriangleFillMode,0,6)),n.restoreStencilState()},t.prototype.shouldRender=function(){return!!r.prototype.shouldRender.call(this)&&!!this._meshes},t.prototype._shouldRenderMesh=function(e){return(!this._excludedMeshes||!this._excludedMeshes[e.uniqueId])&&!!r.prototype.hasMesh.call(this,e)},t.prototype._canRenderMesh=function(e,n){return!0},t.prototype._addCustomEffectDefines=function(e){e.push("#define HIGHLIGHT")},t.prototype._setEmissiveTextureAndColor=function(e,n,i){var o=this._meshes[e.uniqueId];o?this._emissiveTextureAndColor.color.set(o.color.r,o.color.g,o.color.b,1):this._emissiveTextureAndColor.color.set(this.neutralColor.r,this.neutralColor.g,this.neutralColor.b,this.neutralColor.a),o&&o.glowEmissiveOnly&&i?(this._emissiveTextureAndColor.texture=i.emissiveTexture,this._emissiveTextureAndColor.color.set(1,1,1,1)):this._emissiveTextureAndColor.texture=null},t.prototype.addExcludedMesh=function(e){this._excludedMeshes&&(this._excludedMeshes[e.uniqueId]||(this._excludedMeshes[e.uniqueId]={mesh:e,beforeBind:e.onBeforeBindObservable.add(function(n){n.getEngine().setStencilBuffer(!1)}),afterRender:e.onAfterRenderObservable.add(function(n){n.getEngine().setStencilBuffer(!0)})}))},t.prototype.removeExcludedMesh=function(e){if(this._excludedMeshes){var n=this._excludedMeshes[e.uniqueId];n&&(n.beforeBind&&e.onBeforeBindObservable.remove(n.beforeBind),n.afterRender&&e.onAfterRenderObservable.remove(n.afterRender)),this._excludedMeshes[e.uniqueId]=null}},t.prototype.hasMesh=function(e){return!!this._meshes&&!!r.prototype.hasMesh.call(this,e)&&this._meshes[e.uniqueId]!==void 0&&this._meshes[e.uniqueId]!==null},t.prototype.addMesh=function(e,n,i){var o=this;if(i===void 0&&(i=!1),this._meshes){var a=this._meshes[e.uniqueId];a?a.color=n:(this._meshes[e.uniqueId]={mesh:e,color:n,observerHighlight:e.onBeforeBindObservable.add(function(s){o.isEnabled&&(o._excludedMeshes&&o._excludedMeshes[s.uniqueId]?o._defaultStencilReference(s):s.getScene().getEngine().setStencilFunctionReference(o._instanceGlowingMeshStencilReference))}),observerDefault:e.onAfterRenderObservable.add(function(s){o.isEnabled&&o._defaultStencilReference(s)}),glowEmissiveOnly:i},e.onDisposeObservable.add(function(){o._disposeMesh(e)})),this._shouldRender=!0}},t.prototype.removeMesh=function(e){if(this._meshes){var n=this._meshes[e.uniqueId];for(var i in n&&(n.observerHighlight&&e.onBeforeBindObservable.remove(n.observerHighlight),n.observerDefault&&e.onAfterRenderObservable.remove(n.observerDefault),delete this._meshes[e.uniqueId]),this._shouldRender=!1,this._meshes)if(this._meshes[i]){this._shouldRender=!0;break}}},t.prototype.removeAllMeshes=function(){if(this._meshes){for(var e in this._meshes)if(this._meshes.hasOwnProperty(e)){var n=this._meshes[e];n&&this.removeMesh(n.mesh)}}},t.prototype._defaultStencilReference=function(e){e.getScene().getEngine().setStencilFunctionReference(t.NormalMeshStencilReference)},t.prototype._disposeMesh=function(e){this.removeMesh(e),this.removeExcludedMesh(e)},t.prototype.dispose=function(){if(this._meshes){for(var e in this._meshes)(n=this._meshes[e])&&n.mesh&&(n.observerHighlight&&n.mesh.onBeforeBindObservable.remove(n.observerHighlight),n.observerDefault&&n.mesh.onAfterRenderObservable.remove(n.observerDefault));this._meshes=null}if(this._excludedMeshes){for(var e in this._excludedMeshes){var n;(n=this._excludedMeshes[e])&&(n.beforeBind&&n.mesh.onBeforeBindObservable.remove(n.beforeBind),n.afterRender&&n.mesh.onAfterRenderObservable.remove(n.afterRender))}this._excludedMeshes=null}r.prototype.dispose.call(this)},t.prototype.getClassName=function(){return"HighlightLayer"},t.prototype.serialize=function(){var e=L.a.Serialize(this);if(e.customType="BABYLON.HighlightLayer",e.meshes=[],this._meshes)for(var n in this._meshes){var i=this._meshes[n];i&&e.meshes.push({glowEmissiveOnly:i.glowEmissiveOnly,color:i.color.asArray(),meshId:i.mesh.id})}if(e.excludedMeshes=[],this._excludedMeshes)for(var o in this._excludedMeshes){var a=this._excludedMeshes[o];a&&e.excludedMeshes.push(a.mesh.id)}return e},t.Parse=function(e,n,i){var o,a=L.a.Parse(function(){return new t(e.name,n,e.options)},e,n,i);for(o=0;o<e.excludedMeshes.length;o++)(s=n.getMeshByID(e.excludedMeshes[o]))&&a.addExcludedMesh(s);for(o=0;o<e.meshes.length;o++){var s,d=e.meshes[o];(s=n.getMeshByID(d.meshId))&&a.addMesh(s,M.a.FromArray(d.color),d.glowEmissiveOnly)}return a},t.EffectName="HighlightLayer",t.NeutralColor=new M.b(0,0,0,0),t.GlowingMeshStencilReference=2,t.NormalMeshStencilReference=1,Object(c.c)([Object(L.c)()],t.prototype,"innerGlow",void 0),Object(c.c)([Object(L.c)()],t.prototype,"outerGlow",void 0),Object(c.c)([Object(L.c)()],t.prototype,"blurHorizontalSize",null),Object(c.c)([Object(L.c)()],t.prototype,"blurVerticalSize",null),Object(c.c)([Object(L.c)("options")],t.prototype,"_options",void 0),t}(po);R.a.RegisteredTypes["BABYLON.HighlightLayer"]=js;var Lu=function(){function r(t){this.name=at.a.NAME_LAYER,this.scene=t,this._engine=t.getEngine(),t.layers=new Array}return r.prototype.register=function(){this.scene._beforeCameraDrawStage.registerStep(at.a.STEP_BEFORECAMERADRAW_LAYER,this,this._drawCameraBackground),this.scene._afterCameraDrawStage.registerStep(at.a.STEP_AFTERCAMERADRAW_LAYER,this,this._drawCameraForeground),this.scene._beforeRenderTargetDrawStage.registerStep(at.a.STEP_BEFORERENDERTARGETDRAW_LAYER,this,this._drawRenderTargetBackground),this.scene._afterRenderTargetDrawStage.registerStep(at.a.STEP_AFTERRENDERTARGETDRAW_LAYER,this,this._drawRenderTargetForeground)},r.prototype.rebuild=function(){for(var t=0,e=this.scene.layers;t<e.length;t++)e[t]._rebuild()},r.prototype.dispose=function(){for(var t=this.scene.layers;t.length;)t[0].dispose()},r.prototype._draw=function(t){var e=this.scene.layers;if(e.length){this._engine.setDepthBuffer(!1);for(var n=0,i=e;n<i.length;n++){var o=i[n];t(o)&&o.render()}this._engine.setDepthBuffer(!0)}},r.prototype._drawCameraPredicate=function(t,e,n){return!t.renderOnlyInRenderTargetTextures&&t.isBackground===e&&(t.layerMask&n)!=0},r.prototype._drawCameraBackground=function(t){var e=this;this._draw(function(n){return e._drawCameraPredicate(n,!0,t.layerMask)})},r.prototype._drawCameraForeground=function(t){var e=this;this._draw(function(n){return e._drawCameraPredicate(n,!1,t.layerMask)})},r.prototype._drawRenderTargetPredicate=function(t,e,n,i){return t.renderTargetTextures.length>0&&t.isBackground===e&&t.renderTargetTextures.indexOf(i)>-1&&(t.layerMask&n)!=0},r.prototype._drawRenderTargetBackground=function(t){var e=this;this._draw(function(n){return e._drawRenderTargetPredicate(n,!0,e.scene.activeCamera.layerMask,t)})},r.prototype._drawRenderTargetForeground=function(t){var e=this;this._draw(function(n){return e._drawRenderTargetPredicate(n,!1,e.scene.activeCamera.layerMask,t)})},r.prototype.addFromContainer=function(t){var e=this;t.layers&&t.layers.forEach(function(n){e.scene.layers.push(n)})},r.prototype.removeFromContainer=function(t,e){var n=this;e===void 0&&(e=!1),t.layers&&t.layers.forEach(function(i){var o=n.scene.layers.indexOf(i);o!==-1&&n.scene.layers.splice(o,1),e&&i.dispose()})},r}(),R_=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-
-uniform vec4 color;
-
-#include<helperFunctions>
-void main(void) {
-vec4 baseColor=texture2D(textureSampler,vUV);
-#ifdef LINEAR
-baseColor.rgb=toGammaSpace(baseColor.rgb);
-#endif
-#ifdef ALPHATEST
-if (baseColor.a<0.4)
-discard;
-#endif
-gl_FragColor=baseColor*color;
-}`;ze.a.ShadersStore.layerPixelShader=R_;var O_=`
-attribute vec2 position;
-
-uniform vec2 scale;
-uniform vec2 offset;
-uniform mat4 textureMatrix;
-
-varying vec2 vUV;
-const vec2 madd=vec2(0.5,0.5);
-void main(void) {
-vec2 shiftedPosition=position*scale+offset;
-vUV=vec2(textureMatrix*vec4(shiftedPosition*madd+madd,1.0,0.0));
-gl_Position=vec4(shiftedPosition,0.0,1.0);
-}`;ze.a.ShadersStore.layerVertexShader=O_;var M_=function(){function r(t,e,n,i,o){this.name=t,this.scale=new u.d(1,1),this.offset=new u.d(0,0),this.alphaBlendingMode=h.a.ALPHA_COMBINE,this.layerMask=268435455,this.renderTargetTextures=[],this.renderOnlyInRenderTargetTextures=!1,this._vertexBuffers={},this.onDisposeObservable=new C.c,this.onBeforeRenderObservable=new C.c,this.onAfterRenderObservable=new C.c,this.texture=e?new we.a(e,n,!0):null,this.isBackground=i===void 0||i,this.color=o===void 0?new M.b(1,1,1,1):o,this._scene=n||te.a.LastCreatedScene;var a=this._scene._getComponent(at.a.NAME_LAYER);a||(a=new Lu(this._scene),this._scene._addComponent(a)),this._scene.layers.push(this);var s=this._scene.getEngine(),d=[];d.push(1,1),d.push(-1,1),d.push(-1,-1),d.push(1,-1);var p=new Oe.b(s,d,Oe.b.PositionKind,!1,!1,2);this._vertexBuffers[Oe.b.PositionKind]=p,this._createIndexBuffer()}return Object.defineProperty(r.prototype,"onDispose",{set:function(t){this._onDisposeObserver&&this.onDisposeObservable.remove(this._onDisposeObserver),this._onDisposeObserver=this.onDisposeObservable.add(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onBeforeRender",{set:function(t){this._onBeforeRenderObserver&&this.onBeforeRenderObservable.remove(this._onBeforeRenderObserver),this._onBeforeRenderObserver=this.onBeforeRenderObservable.add(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"onAfterRender",{set:function(t){this._onAfterRenderObserver&&this.onAfterRenderObservable.remove(this._onAfterRenderObserver),this._onAfterRenderObserver=this.onAfterRenderObservable.add(t)},enumerable:!1,configurable:!0}),r.prototype._createIndexBuffer=function(){var t=this._scene.getEngine(),e=[];e.push(0),e.push(1),e.push(2),e.push(0),e.push(2),e.push(3),this._indexBuffer=t.createIndexBuffer(e)},r.prototype._rebuild=function(){var t=this._vertexBuffers[Oe.b.PositionKind];t&&t._rebuild(),this._createIndexBuffer()},r.prototype.render=function(){var t=this._scene.getEngine(),e="";this.alphaTest&&(e="#define ALPHATEST"),this.texture&&!this.texture.gammaSpace&&(e+=`\r
-#define LINEAR`),this._previousDefines!==e&&(this._previousDefines=e,this._effect=t.createEffect("layer",[Oe.b.PositionKind],["textureMatrix","color","scale","offset"],["textureSampler"],e));var n=this._effect;n&&n.isReady()&&this.texture&&this.texture.isReady()&&(t=this._scene.getEngine(),this.onBeforeRenderObservable.notifyObservers(this),t.enableEffect(n),t.setState(!1),n.setTexture("textureSampler",this.texture),n.setMatrix("textureMatrix",this.texture.getTextureMatrix()),n.setFloat4("color",this.color.r,this.color.g,this.color.b,this.color.a),n.setVector2("offset",this.offset),n.setVector2("scale",this.scale),t.bindBuffers(this._vertexBuffers,this._indexBuffer,n),this.alphaTest?t.drawElementsType(Ht.a.TriangleFillMode,0,6):(t.setAlphaMode(this.alphaBlendingMode),t.drawElementsType(Ht.a.TriangleFillMode,0,6),t.setAlphaMode(h.a.ALPHA_DISABLE)),this.onAfterRenderObservable.notifyObservers(this))},r.prototype.dispose=function(){var t=this._vertexBuffers[Oe.b.PositionKind];t&&(t.dispose(),this._vertexBuffers[Oe.b.PositionKind]=null),this._indexBuffer&&(this._scene.getEngine()._releaseBuffer(this._indexBuffer),this._indexBuffer=null),this.texture&&(this.texture.dispose(),this.texture=null),this.renderTargetTextures=[];var e=this._scene.layers.indexOf(this);this._scene.layers.splice(e,1),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear(),this.onAfterRenderObservable.clear(),this.onBeforeRenderObservable.clear()},r}(),Nu=function(){function r(t,e,n,i,o){this.size=t,this.position=e,this.alphaMode=h.a.ALPHA_ONEONE,this.color=n||new M.a(1,1,1),this.texture=i?new we.a(i,o.getScene(),!0):null,this._system=o,o.lensFlares.push(this)}return r.AddFlare=function(t,e,n,i,o){return new r(t,e,n,i,o)},r.prototype.dispose=function(){this.texture&&this.texture.dispose();var t=this._system.lensFlares.indexOf(this);this._system.lensFlares.splice(t,1)},r}(),I_=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-
-uniform vec4 color;
-void main(void) {
-vec4 baseColor=texture2D(textureSampler,vUV);
-gl_FragColor=baseColor*color;
-}`;ze.a.ShadersStore.lensFlarePixelShader=I_;var D_=`
-attribute vec2 position;
-
-uniform mat4 viewportMatrix;
-
-varying vec2 vUV;
-const vec2 madd=vec2(0.5,0.5);
-void main(void) {
-vUV=position*madd+madd;
-gl_Position=viewportMatrix*vec4(position,0.0,1.0);
-}`;ze.a.ShadersStore.lensFlareVertexShader=D_;var Hs=function(){function r(t,e,n){this.name=t,this.lensFlares=new Array,this.borderLimit=300,this.viewportBorder=0,this.layerMask=268435455,this._vertexBuffers={},this._isEnabled=!0,this._scene=n||te.a.LastCreatedScene,r._SceneComponentInitialization(this._scene),this._emitter=e,this.id=t,n.lensFlareSystems.push(this),this.meshesSelectionPredicate=function(s){return n.activeCamera&&s.material&&s.isVisible&&s.isEnabled()&&s.isBlocker&&(s.layerMask&n.activeCamera.layerMask)!=0};var i=n.getEngine(),o=[];o.push(1,1),o.push(-1,1),o.push(-1,-1),o.push(1,-1),this._vertexBuffers[Oe.b.PositionKind]=new Oe.b(i,o,Oe.b.PositionKind,!1,!1,2);var a=[];a.push(0),a.push(1),a.push(2),a.push(0),a.push(2),a.push(3),this._indexBuffer=i.createIndexBuffer(a),this._effect=i.createEffect("lensFlare",[Oe.b.PositionKind],["color","viewportMatrix"],["textureSampler"],"")}return Object.defineProperty(r.prototype,"isEnabled",{get:function(){return this._isEnabled},set:function(t){this._isEnabled=t},enumerable:!1,configurable:!0}),r.prototype.getScene=function(){return this._scene},r.prototype.getEmitter=function(){return this._emitter},r.prototype.setEmitter=function(t){this._emitter=t},r.prototype.getEmitterPosition=function(){return this._emitter.getAbsolutePosition?this._emitter.getAbsolutePosition():this._emitter.position},r.prototype.computeEffectivePosition=function(t){var e=this.getEmitterPosition();return e=u.e.Project(e,u.a.Identity(),this._scene.getTransformMatrix(),t),this._positionX=e.x,this._positionY=e.y,e=u.e.TransformCoordinates(this.getEmitterPosition(),this._scene.getViewMatrix()),this.viewportBorder>0&&(t.x-=this.viewportBorder,t.y-=this.viewportBorder,t.width+=2*this.viewportBorder,t.height+=2*this.viewportBorder,e.x+=this.viewportBorder,e.y+=this.viewportBorder,this._positionX+=this.viewportBorder,this._positionY+=this.viewportBorder),e.z>0&&(this._positionX>t.x&&this._positionX<t.x+t.width&&this._positionY>t.y&&(this._positionY,t.y,t.height),!0)},r.prototype._isVisible=function(){if(!this._isEnabled||!this._scene.activeCamera)return!1;var t=this.getEmitterPosition().subtract(this._scene.activeCamera.globalPosition),e=t.length();t.normalize();var n=new fn.a(this._scene.activeCamera.globalPosition,t),i=this._scene.pickWithRay(n,this.meshesSelectionPredicate,!0);return!i||!i.hit||i.distance>e},r.prototype.render=function(){if(!this._effect.isReady()||!this._scene.activeCamera)return!1;var t,e,n=this._scene.getEngine(),i=this._scene.activeCamera.viewport.toGlobal(n.getRenderWidth(!0),n.getRenderHeight(!0));if(!this.computeEffectivePosition(i)||!this._isVisible())return!1;var o=(t=this._positionX<this.borderLimit+i.x?this.borderLimit+i.x-this._positionX:this._positionX>i.x+i.width-this.borderLimit?this._positionX-i.x-i.width+this.borderLimit:0)>(e=this._positionY<this.borderLimit+i.y?this.borderLimit+i.y-this._positionY:this._positionY>i.y+i.height-this.borderLimit?this._positionY-i.y-i.height+this.borderLimit:0)?t:e;(o-=this.viewportBorder)>this.borderLimit&&(o=this.borderLimit);var a=1-$.a.Clamp(o/this.borderLimit,0,1);if(a<0)return!1;a>1&&(a=1),this.viewportBorder>0&&(i.x+=this.viewportBorder,i.y+=this.viewportBorder,i.width-=2*this.viewportBorder,i.height-=2*this.viewportBorder,this._positionX-=this.viewportBorder,this._positionY-=this.viewportBorder);var s=i.x+i.width/2,d=i.y+i.height/2,p=s-this._positionX,b=d-this._positionY;n.enableEffect(this._effect),n.setState(!1),n.setDepthBuffer(!1),n.bindBuffers(this._vertexBuffers,this._indexBuffer,this._effect);for(var P=0;P<this.lensFlares.length;P++){var O=this.lensFlares[P];if(!O.texture||O.texture.isReady()){n.setAlphaMode(O.alphaMode);var B=s-p*O.position,F=d-b*O.position,z=O.size,J=O.size*n.getAspectRatio(this._scene.activeCamera,!0),ie=B/(i.width+2*i.x)*2-1,se=1-F/(i.height+2*i.y)*2,ce=u.a.FromValues(z/2,0,0,0,0,J/2,0,0,0,0,1,0,ie,se,0,1);this._effect.setMatrix("viewportMatrix",ce),this._effect.setTexture("textureSampler",O.texture),this._effect.setFloat4("color",O.color.r*a,O.color.g*a,O.color.b*a,1),n.drawElementsType(Ht.a.TriangleFillMode,0,6)}}return n.setDepthBuffer(!0),n.setAlphaMode(h.a.ALPHA_DISABLE),!0},r.prototype.dispose=function(){var t=this._vertexBuffers[Oe.b.PositionKind];for(t&&(t.dispose(),this._vertexBuffers[Oe.b.PositionKind]=null),this._indexBuffer&&(this._scene.getEngine()._releaseBuffer(this._indexBuffer),this._indexBuffer=null);this.lensFlares.length;)this.lensFlares[0].dispose();var e=this._scene.lensFlareSystems.indexOf(this);this._scene.lensFlareSystems.splice(e,1)},r.Parse=function(t,e,n){var i=e.getLastEntryByID(t.emitterId),o=t.name||"lensFlareSystem#"+t.emitterId,a=new r(o,i,e);a.id=t.id||o,a.borderLimit=t.borderLimit;for(var s=0;s<t.flares.length;s++){var d=t.flares[s];Nu.AddFlare(d.size,d.position,M.a.FromArray(d.color),d.textureName?n+d.textureName:"",a)}return a},r.prototype.serialize=function(){var t={};t.id=this.id,t.name=this.name,t.emitterId=this.getEmitter().id,t.borderLimit=this.borderLimit,t.flares=[];for(var e=0;e<this.lensFlares.length;e++){var n=this.lensFlares[e];t.flares.push({size:n.size,position:n.position,color:n.color.asArray(),textureName:Xe.b.GetFilename(n.texture?n.texture.name:"")})}return t},r._SceneComponentInitialization=function(t){throw An.a.WarnImport("LensFlareSystemSceneComponent")},r}();U.a.AddParser(at.a.NAME_LENSFLARESYSTEM,function(r,t,e,n){if(r.lensFlareSystems!==void 0&&r.lensFlareSystems!==null){e.lensFlareSystems||(e.lensFlareSystems=new Array);for(var i=0,o=r.lensFlareSystems.length;i<o;i++){var a=r.lensFlareSystems[i],s=Hs.Parse(a,t,n);e.lensFlareSystems.push(s)}}}),U.a.prototype.getLensFlareSystemByName=function(r){for(var t=0;t<this.lensFlareSystems.length;t++)if(this.lensFlareSystems[t].name===r)return this.lensFlareSystems[t];return null},U.a.prototype.getLensFlareSystemByID=function(r){for(var t=0;t<this.lensFlareSystems.length;t++)if(this.lensFlareSystems[t].id===r)return this.lensFlareSystems[t];return null},U.a.prototype.removeLensFlareSystem=function(r){var t=this.lensFlareSystems.indexOf(r);return t!==-1&&this.lensFlareSystems.splice(t,1),t},U.a.prototype.addLensFlareSystem=function(r){this.lensFlareSystems.push(r)};var wu=function(){function r(t){this.name=at.a.NAME_LENSFLARESYSTEM,this.scene=t,t.lensFlareSystems=new Array}return r.prototype.register=function(){this.scene._afterCameraDrawStage.registerStep(at.a.STEP_AFTERCAMERADRAW_LENSFLARESYSTEM,this,this._draw)},r.prototype.rebuild=function(){},r.prototype.addFromContainer=function(t){var e=this;t.lensFlareSystems&&t.lensFlareSystems.forEach(function(n){e.scene.addLensFlareSystem(n)})},r.prototype.removeFromContainer=function(t,e){var n=this;t.lensFlareSystems&&t.lensFlareSystems.forEach(function(i){n.scene.removeLensFlareSystem(i),e&&i.dispose()})},r.prototype.serialize=function(t){t.lensFlareSystems=[];for(var e=0,n=this.scene.lensFlareSystems;e<n.length;e++){var i=n[e];t.lensFlareSystems.push(i.serialize())}},r.prototype.dispose=function(){for(var t=this.scene.lensFlareSystems;t.length;)t[0].dispose()},r.prototype._draw=function(t){if(this.scene.lensFlaresEnabled){var e=this.scene.lensFlareSystems;Xe.b.StartPerformanceCounter("Lens flares",e.length>0);for(var n=0,i=e;n<i.length;n++){var o=i[n];t.layerMask&o.layerMask&&o.render()}Xe.b.EndPerformanceCounter("Lens flares",e.length>0)}},r}();Hs._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_LENSFLARESYSTEM);t||(t=new wu(r),r._addComponent(t))};var L_=`
-
-
-
-
-float bayerDither2(vec2 _P) {
-return mod(2.0*_P.y+_P.x+1.0,4.0);
-}
-
-
-float bayerDither4(vec2 _P) {
-vec2 P1=mod(_P,2.0);
-vec2 P2=floor(0.5*mod(_P,4.0));
-return 4.0*bayerDither2(P1)+bayerDither2(P2);
-}
-
-float bayerDither8(vec2 _P) {
-vec2 P1=mod(_P,2.0);
-vec2 P2=floor(0.5*mod(_P,4.0));
-vec2 P4=floor(0.25*mod(_P,8.0));
-return 4.0*(4.0*bayerDither2(P1)+bayerDither2(P2))+bayerDither2(P4);
-}
-`;ze.a.IncludesShadersStore.bayerDitherFunctions=L_;var N_=`#if SM_FLOAT == 0
-#include<packingFunctions>
-#endif
-#if SM_SOFTTRANSPARENTSHADOW == 1
-#include<bayerDitherFunctions>
-uniform float softTransparentShadowSM;
-#endif
-varying float vDepthMetricSM;
-#if SM_USEDISTANCE == 1
-uniform vec3 lightDataSM;
-varying vec3 vPositionWSM;
-#endif
-uniform vec3 biasAndScaleSM;
-uniform vec2 depthValuesSM;
-#if defined(SM_DEPTHCLAMP) && SM_DEPTHCLAMP == 1
-varying float zSM;
-#endif
-`;ze.a.IncludesShadersStore.shadowMapFragmentDeclaration=N_;var w_=` float depthSM=vDepthMetricSM;
-#if defined(SM_DEPTHCLAMP) && SM_DEPTHCLAMP == 1
-#if SM_USEDISTANCE == 1
-depthSM=clamp(((length(vPositionWSM-lightDataSM)+depthValuesSM.x)/(depthValuesSM.y))+biasAndScaleSM.x,0.0,1.0);
-#else
-depthSM=clamp(((zSM+depthValuesSM.x)/(depthValuesSM.y))+biasAndScaleSM.x,0.0,1.0);
-#endif
-gl_FragDepth=depthSM;
-#elif SM_USEDISTANCE == 1
-depthSM=(length(vPositionWSM-lightDataSM)+depthValuesSM.x)/(depthValuesSM.y)+biasAndScaleSM.x;
-#endif
-#if SM_ESM == 1
-depthSM=clamp(exp(-min(87.,biasAndScaleSM.z*depthSM)),0.,1.);
-#endif
-#if SM_FLOAT == 1
-gl_FragColor=vec4(depthSM,1.0,1.0,1.0);
-#else
-gl_FragColor=pack(depthSM);
-#endif
-return;`;ze.a.IncludesShadersStore.shadowMapFragment=w_;var F_=`#include<shadowMapFragmentDeclaration>
-#ifdef ALPHATEST
-varying vec2 vUV;
-uniform sampler2D diffuseSampler;
-#endif
-#include<clipPlaneFragmentDeclaration>
-void main(void)
-{
-#include<clipPlaneFragment>
-#ifdef ALPHATEST
-float alphaFromAlphaTexture=texture2D(diffuseSampler,vUV).a;
-if (alphaFromAlphaTexture<0.4)
-discard;
-#endif
-#if SM_SOFTTRANSPARENTSHADOW == 1
-#ifdef ALPHATEST
-if ((bayerDither8(floor(mod(gl_FragCoord.xy,8.0))))/64.0>=softTransparentShadowSM*alphaFromAlphaTexture) discard;
-#else
-if ((bayerDither8(floor(mod(gl_FragCoord.xy,8.0))))/64.0>=softTransparentShadowSM) discard;
-#endif
-#endif
-#include<shadowMapFragment>
-}`;ze.a.ShadersStore.shadowMapPixelShader=F_;var B_=`#if SM_NORMALBIAS == 1
-uniform vec3 lightDataSM;
-#endif
-uniform vec3 biasAndScaleSM;
-uniform vec2 depthValuesSM;
-varying float vDepthMetricSM;
-#if SM_USEDISTANCE == 1
-varying vec3 vPositionWSM;
-#endif
-#if defined(SM_DEPTHCLAMP) && SM_DEPTHCLAMP == 1
-varying float zSM;
-#endif
-`;ze.a.IncludesShadersStore.shadowMapVertexDeclaration=B_;var U_=`
-#if SM_NORMALBIAS == 1
-#if SM_DIRECTIONINLIGHTDATA == 1
-vec3 worldLightDirSM=normalize(-lightDataSM.xyz);
-#else
-vec3 directionToLightSM=lightDataSM.xyz-worldPos.xyz;
-vec3 worldLightDirSM=normalize(directionToLightSM);
-#endif
-float ndlSM=dot(vNormalW,worldLightDirSM);
-float sinNLSM=sqrt(1.0-ndlSM*ndlSM);
-float normalBiasSM=biasAndScaleSM.y*sinNLSM;
-worldPos.xyz-=vNormalW*normalBiasSM;
-#endif
-`;ze.a.IncludesShadersStore.shadowMapVertexNormalBias=U_;var V_=`#if SM_USEDISTANCE == 1
-vPositionWSM=worldPos.xyz;
-#endif
-#if SM_DEPTHTEXTURE == 1
-
-gl_Position.z+=biasAndScaleSM.x*gl_Position.w;
-#endif
-#if defined(SM_DEPTHCLAMP) && SM_DEPTHCLAMP == 1
-zSM=gl_Position.z;
-gl_Position.z=0.0;
-#elif SM_USEDISTANCE == 0
-
-vDepthMetricSM=((gl_Position.z+depthValuesSM.x)/(depthValuesSM.y))+biasAndScaleSM.x;
-#endif
-`;ze.a.IncludesShadersStore.shadowMapVertexMetric=V_;var k_=`
-attribute vec3 position;
-#ifdef NORMAL
-attribute vec3 normal;
-#endif
-#include<bonesDeclaration>
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-
-#include<instancesDeclaration>
-#include<helperFunctions>
-uniform mat4 viewProjection;
-#ifdef ALPHATEST
-varying vec2 vUV;
-uniform mat4 diffuseMatrix;
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#endif
-#include<shadowMapVertexDeclaration>
-#include<clipPlaneVertexDeclaration>
-void main(void)
-{
-vec3 positionUpdated=position;
-#ifdef UV1
-vec2 uvUpdated=uv;
-#endif
-#ifdef NORMAL
-vec3 normalUpdated=normal;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-#include<instancesVertex>
-#include<bonesVertex>
-vec4 worldPos=finalWorld*vec4(positionUpdated,1.0);
-#ifdef NORMAL
-mat3 normWorldSM=mat3(finalWorld);
-#if defined(INSTANCES) && defined(THIN_INSTANCES)
-vec3 vNormalW=normalUpdated/vec3(dot(normWorldSM[0],normWorldSM[0]),dot(normWorldSM[1],normWorldSM[1]),dot(normWorldSM[2],normWorldSM[2]));
-vNormalW=normalize(normWorldSM*vNormalW);
-#else
-#ifdef NONUNIFORMSCALING
-normWorldSM=transposeMat3(inverseMat3(normWorldSM));
-#endif
-vec3 vNormalW=normalize(normWorldSM*normalUpdated);
-#endif
-#endif
-#include<shadowMapVertexNormalBias>
-
-gl_Position=viewProjection*worldPos;
-#include<shadowMapVertexMetric>
-#ifdef ALPHATEST
-#ifdef UV1
-vUV=vec2(diffuseMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef UV2
-vUV=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-#include<clipPlaneVertex>
-}`;ze.a.ShadersStore.shadowMapVertexShader=k_;var G_=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-
-uniform vec2 screenSize;
-void main(void)
-{
-vec4 colorDepth=vec4(0.0);
-for (int x=-OFFSET; x<=OFFSET; x++)
-for (int y=-OFFSET; y<=OFFSET; y++)
-colorDepth+=texture2D(textureSampler,vUV+vec2(x,y)/screenSize);
-gl_FragColor=(colorDepth/float((OFFSET*2+1)*(OFFSET*2+1)));
-}`;ze.a.ShadersStore.depthBoxBlurPixelShader=G_;var z_=`#if SM_SOFTTRANSPARENTSHADOW == 1
-if ((bayerDither8(floor(mod(gl_FragCoord.xy,8.0))))/64.0>=softTransparentShadowSM*alpha) discard;
-#endif
-`;ze.a.IncludesShadersStore.shadowMapFragmentSoftTransparentShadow=z_;var Fu=new u.a,Bu=new u.a,Un=function(){function r(t,e,n){this.onBeforeShadowMapRenderObservable=new C.c,this.onAfterShadowMapRenderObservable=new C.c,this.onBeforeShadowMapRenderMeshObservable=new C.c,this.onAfterShadowMapRenderMeshObservable=new C.c,this._bias=5e-5,this._normalBias=0,this._blurBoxOffset=1,this._blurScale=2,this._blurKernel=1,this._useKernelBlur=!1,this._filter=r.FILTER_NONE,this._filteringQuality=r.QUALITY_HIGH,this._contactHardeningLightSizeUVRatio=.1,this._darkness=0,this._transparencyShadow=!1,this.enableSoftTransparentShadow=!1,this.frustumEdgeFalloff=0,this.forceBackFacesOnly=!1,this._lightDirection=u.e.Zero(),this._viewMatrix=u.a.Zero(),this._projectionMatrix=u.a.Zero(),this._transformMatrix=u.a.Zero(),this._cachedPosition=new u.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._cachedDirection=new u.e(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._currentFaceIndex=0,this._currentFaceIndexCache=0,this._defaultTextureMatrix=u.a.Identity(),this._mapSize=t,this._light=e,this._scene=e.getScene(),e._shadowGenerator=this,this.id=e.id,r._SceneComponentInitialization(this._scene);var i=this._scene.getEngine().getCaps();n?i.textureFloatRender&&i.textureFloatLinearFiltering?this._textureType=h.a.TEXTURETYPE_FLOAT:i.textureHalfFloatRender&&i.textureHalfFloatLinearFiltering?this._textureType=h.a.TEXTURETYPE_HALF_FLOAT:this._textureType=h.a.TEXTURETYPE_UNSIGNED_INT:i.textureHalfFloatRender&&i.textureHalfFloatLinearFiltering?this._textureType=h.a.TEXTURETYPE_HALF_FLOAT:i.textureFloatRender&&i.textureFloatLinearFiltering?this._textureType=h.a.TEXTURETYPE_FLOAT:this._textureType=h.a.TEXTURETYPE_UNSIGNED_INT,this._initializeGenerator(),this._applyFilterValues()}return Object.defineProperty(r.prototype,"bias",{get:function(){return this._bias},set:function(t){this._bias=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"normalBias",{get:function(){return this._normalBias},set:function(t){this._normalBias=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"blurBoxOffset",{get:function(){return this._blurBoxOffset},set:function(t){this._blurBoxOffset!==t&&(this._blurBoxOffset=t,this._disposeBlurPostProcesses())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"blurScale",{get:function(){return this._blurScale},set:function(t){this._blurScale!==t&&(this._blurScale=t,this._disposeBlurPostProcesses())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"blurKernel",{get:function(){return this._blurKernel},set:function(t){this._blurKernel!==t&&(this._blurKernel=t,this._disposeBlurPostProcesses())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useKernelBlur",{get:function(){return this._useKernelBlur},set:function(t){this._useKernelBlur!==t&&(this._useKernelBlur=t,this._disposeBlurPostProcesses())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"depthScale",{get:function(){return this._depthScale!==void 0?this._depthScale:this._light.getDepthScale()},set:function(t){this._depthScale=t},enumerable:!1,configurable:!0}),r.prototype._validateFilter=function(t){return t},Object.defineProperty(r.prototype,"filter",{get:function(){return this._filter},set:function(t){if(t=this._validateFilter(t),this._light.needCube()){if(t===r.FILTER_BLUREXPONENTIALSHADOWMAP)return void(this.useExponentialShadowMap=!0);if(t===r.FILTER_BLURCLOSEEXPONENTIALSHADOWMAP)return void(this.useCloseExponentialShadowMap=!0);if(t===r.FILTER_PCF||t===r.FILTER_PCSS)return void(this.usePoissonSampling=!0)}t!==r.FILTER_PCF&&t!==r.FILTER_PCSS||this._scene.getEngine().webGLVersion!==1?this._filter!==t&&(this._filter=t,this._disposeBlurPostProcesses(),this._applyFilterValues(),this._light._markMeshesAsLightDirty()):this.usePoissonSampling=!0},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"usePoissonSampling",{get:function(){return this.filter===r.FILTER_POISSONSAMPLING},set:function(t){var e=this._validateFilter(r.FILTER_POISSONSAMPLING);(t||this.filter===r.FILTER_POISSONSAMPLING)&&(this.filter=t?e:r.FILTER_NONE)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useExponentialShadowMap",{get:function(){return this.filter===r.FILTER_EXPONENTIALSHADOWMAP},set:function(t){var e=this._validateFilter(r.FILTER_EXPONENTIALSHADOWMAP);(t||this.filter===r.FILTER_EXPONENTIALSHADOWMAP)&&(this.filter=t?e:r.FILTER_NONE)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useBlurExponentialShadowMap",{get:function(){return this.filter===r.FILTER_BLUREXPONENTIALSHADOWMAP},set:function(t){var e=this._validateFilter(r.FILTER_BLUREXPONENTIALSHADOWMAP);(t||this.filter===r.FILTER_BLUREXPONENTIALSHADOWMAP)&&(this.filter=t?e:r.FILTER_NONE)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useCloseExponentialShadowMap",{get:function(){return this.filter===r.FILTER_CLOSEEXPONENTIALSHADOWMAP},set:function(t){var e=this._validateFilter(r.FILTER_CLOSEEXPONENTIALSHADOWMAP);(t||this.filter===r.FILTER_CLOSEEXPONENTIALSHADOWMAP)&&(this.filter=t?e:r.FILTER_NONE)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useBlurCloseExponentialShadowMap",{get:function(){return this.filter===r.FILTER_BLURCLOSEEXPONENTIALSHADOWMAP},set:function(t){var e=this._validateFilter(r.FILTER_BLURCLOSEEXPONENTIALSHADOWMAP);(t||this.filter===r.FILTER_BLURCLOSEEXPONENTIALSHADOWMAP)&&(this.filter=t?e:r.FILTER_NONE)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"usePercentageCloserFiltering",{get:function(){return this.filter===r.FILTER_PCF},set:function(t){var e=this._validateFilter(r.FILTER_PCF);(t||this.filter===r.FILTER_PCF)&&(this.filter=t?e:r.FILTER_NONE)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"filteringQuality",{get:function(){return this._filteringQuality},set:function(t){this._filteringQuality!==t&&(this._filteringQuality=t,this._disposeBlurPostProcesses(),this._applyFilterValues(),this._light._markMeshesAsLightDirty())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useContactHardeningShadow",{get:function(){return this.filter===r.FILTER_PCSS},set:function(t){var e=this._validateFilter(r.FILTER_PCSS);(t||this.filter===r.FILTER_PCSS)&&(this.filter=t?e:r.FILTER_NONE)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"contactHardeningLightSizeUVRatio",{get:function(){return this._contactHardeningLightSizeUVRatio},set:function(t){this._contactHardeningLightSizeUVRatio=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"darkness",{get:function(){return this._darkness},set:function(t){this.setDarkness(t)},enumerable:!1,configurable:!0}),r.prototype.getDarkness=function(){return this._darkness},r.prototype.setDarkness=function(t){return this._darkness=t>=1?1:t<=0?0:t,this},Object.defineProperty(r.prototype,"transparencyShadow",{get:function(){return this._transparencyShadow},set:function(t){this.setTransparencyShadow(t)},enumerable:!1,configurable:!0}),r.prototype.setTransparencyShadow=function(t){return this._transparencyShadow=t,this},r.prototype.getShadowMap=function(){return this._shadowMap},r.prototype.getShadowMapForRendering=function(){return this._shadowMap2?this._shadowMap2:this._shadowMap},r.prototype.getClassName=function(){return r.CLASSNAME},r.prototype.addShadowCaster=function(t,e){var n;return e===void 0&&(e=!0),this._shadowMap?(this._shadowMap.renderList||(this._shadowMap.renderList=[]),this._shadowMap.renderList.push(t),e&&(n=this._shadowMap.renderList).push.apply(n,t.getChildMeshes()),this):this},r.prototype.removeShadowCaster=function(t,e){if(e===void 0&&(e=!0),!this._shadowMap||!this._shadowMap.renderList)return this;var n=this._shadowMap.renderList.indexOf(t);if(n!==-1&&this._shadowMap.renderList.splice(n,1),e)for(var i=0,o=t.getChildren();i<o.length;i++){var a=o[i];this.removeShadowCaster(a)}return this},r.prototype.getLight=function(){return this._light},Object.defineProperty(r.prototype,"mapSize",{get:function(){return this._mapSize},set:function(t){this._mapSize=t,this._light._markMeshesAsLightDirty(),this.recreateShadowMap()},enumerable:!1,configurable:!0}),r.prototype._initializeGenerator=function(){this._light._markMeshesAsLightDirty(),this._initializeShadowMap()},r.prototype._createTargetRenderTexture=function(){this._scene.getEngine().webGLVersion>1?(this._shadowMap=new sn(this._light.name+"_shadowMap",this._mapSize,this._scene,!1,!0,this._textureType,this._light.needCube(),void 0,!1,!1),this._shadowMap.createDepthStencilTexture(h.a.LESS,!0)):this._shadowMap=new sn(this._light.name+"_shadowMap",this._mapSize,this._scene,!1,!0,this._textureType,this._light.needCube())},r.prototype._initializeShadowMap=function(){var t=this;if(this._createTargetRenderTexture(),this._shadowMap!==null){this._shadowMap.wrapU=we.a.CLAMP_ADDRESSMODE,this._shadowMap.wrapV=we.a.CLAMP_ADDRESSMODE,this._shadowMap.anisotropicFilteringLevel=1,this._shadowMap.updateSamplingMode(we.a.BILINEAR_SAMPLINGMODE),this._shadowMap.renderParticles=!1,this._shadowMap.ignoreCameraViewport=!0,this._storedUniqueId&&(this._shadowMap.uniqueId=this._storedUniqueId),this._shadowMap.customRenderFunction=this._renderForShadowMap.bind(this),this._shadowMap.customIsReadyFunction=function(a,s){return!0};var e=this._scene.getEngine();this._shadowMap.onBeforeRenderObservable.add(function(a){if(t._currentFaceIndex=a,t._filter===r.FILTER_PCF&&e.setColorWrite(!1),t._scene.getSceneUniformBuffer().useUbo){var s=t._scene.getSceneUniformBuffer();s.updateMatrix("viewProjection",t.getTransformMatrix()),s.updateMatrix("view",t._viewMatrix),s.update()}}),this._shadowMap.onAfterUnbindObservable.add(function(){if(t._scene.getSceneUniformBuffer().useUbo){var a=t._scene.getSceneUniformBuffer();a.updateMatrix("viewProjection",t._scene.getTransformMatrix()),a.updateMatrix("view",t._scene.getViewMatrix()),a.update()}if(t._filter===r.FILTER_PCF&&e.setColorWrite(!0),t.useBlurExponentialShadowMap||t.useBlurCloseExponentialShadowMap){var s=t.getShadowMapForRendering();if(s){var d=s.getInternalTexture();t._scene.postProcessManager.directRender(t._blurPostProcesses,d,!0),e.unBindFramebuffer(d,!0)}}});var n=new M.b(0,0,0,0),i=new M.b(1,1,1,1);this._shadowMap.onClearObservable.add(function(a){t._filter===r.FILTER_PCF?a.clear(i,!1,!0,!1):t.useExponentialShadowMap||t.useBlurExponentialShadowMap?a.clear(n,!0,!0,!1):a.clear(i,!0,!0,!1)}),this._shadowMap.onResizeObservable.add(function(a){t._storedUniqueId=t._shadowMap.uniqueId,t._mapSize=a.getRenderSize(),t._light._markMeshesAsLightDirty(),t.recreateShadowMap()});for(var o=to.b.MIN_RENDERINGGROUPS;o<to.b.MAX_RENDERINGGROUPS;o++)this._shadowMap.setRenderingAutoClearDepthStencil(o,!1)}},r.prototype._initializeBlurRTTAndPostProcesses=function(){var t=this,e=this._scene.getEngine(),n=this._mapSize/this.blurScale;this.useKernelBlur&&this.blurScale===1||(this._shadowMap2=new sn(this._light.name+"_shadowMap2",n,this._scene,!1,!0,this._textureType),this._shadowMap2.wrapU=we.a.CLAMP_ADDRESSMODE,this._shadowMap2.wrapV=we.a.CLAMP_ADDRESSMODE,this._shadowMap2.updateSamplingMode(we.a.BILINEAR_SAMPLINGMODE)),this.useKernelBlur?(this._kernelBlurXPostprocess=new gn(this._light.name+"KernelBlurX",new u.d(1,0),this.blurKernel,1,null,we.a.BILINEAR_SAMPLINGMODE,e,!1,this._textureType),this._kernelBlurXPostprocess.width=n,this._kernelBlurXPostprocess.height=n,this._kernelBlurXPostprocess.onApplyObservable.add(function(i){i.setTexture("textureSampler",t._shadowMap)}),this._kernelBlurYPostprocess=new gn(this._light.name+"KernelBlurY",new u.d(0,1),this.blurKernel,1,null,we.a.BILINEAR_SAMPLINGMODE,e,!1,this._textureType),this._kernelBlurXPostprocess.autoClear=!1,this._kernelBlurYPostprocess.autoClear=!1,this._textureType===h.a.TEXTURETYPE_UNSIGNED_INT&&(this._kernelBlurXPostprocess.packedFloat=!0,this._kernelBlurYPostprocess.packedFloat=!0),this._blurPostProcesses=[this._kernelBlurXPostprocess,this._kernelBlurYPostprocess]):(this._boxBlurPostprocess=new _t(this._light.name+"DepthBoxBlur","depthBoxBlur",["screenSize","boxOffset"],[],1,null,we.a.BILINEAR_SAMPLINGMODE,e,!1,"#define OFFSET "+this._blurBoxOffset,this._textureType),this._boxBlurPostprocess.onApplyObservable.add(function(i){i.setFloat2("screenSize",n,n),i.setTexture("textureSampler",t._shadowMap)}),this._boxBlurPostprocess.autoClear=!1,this._blurPostProcesses=[this._boxBlurPostprocess])},r.prototype._renderForShadowMap=function(t,e,n,i){var o,a=this._scene.getEngine(),s=a.getColorWrite();if(i.length){for(a.setColorWrite(!1),o=0;o<i.length;o++)this._renderSubMeshForShadowMap(i.data[o]);a.setColorWrite(s)}for(o=0;o<t.length;o++)this._renderSubMeshForShadowMap(t.data[o]);for(o=0;o<e.length;o++)this._renderSubMeshForShadowMap(e.data[o]);if(this._transparencyShadow)for(o=0;o<n.length;o++)this._renderSubMeshForShadowMap(n.data[o],!0);else for(o=0;o<n.length;o++)n.data[o].getEffectiveMesh()._internalAbstractMeshDataInfo._isActiveIntermediate=!1},r.prototype._bindCustomEffectForRenderSubMeshForShadowMap=function(t,e,n,i){var o,a,s,d,p,b;e.setMatrix((o=n?.viewProjection)!==null&&o!==void 0?o:"viewProjection",this.getTransformMatrix()),e.setMatrix((a=n?.view)!==null&&a!==void 0?a:"view",this._viewMatrix),e.setMatrix((s=n?.projection)!==null&&s!==void 0?s:"projection",this._projectionMatrix);var P=i.getWorldMatrix();e.setMatrix((d=n?.world)!==null&&d!==void 0?d:"world",P),P.multiplyToRef(this.getTransformMatrix(),Fu),e.setMatrix((p=n?.worldViewProjection)!==null&&p!==void 0?p:"worldViewProjection",Fu),P.multiplyToRef(this._viewMatrix,Bu),e.setMatrix((b=n?.worldView)!==null&&b!==void 0?b:"worldView",Bu)},r.prototype._renderSubMeshForShadowMap=function(t,e){var n,i;e===void 0&&(e=!1);var o=t.getRenderingMesh(),a=t.getEffectiveMesh(),s=this._scene,d=s.getEngine(),p=t.getMaterial();if(a._internalAbstractMeshDataInfo._isActiveIntermediate=!1,p&&t.verticesCount!==0&&t._renderId!==s.getRenderId()){d.setState(p.backFaceCulling);var b=o._getInstancesRenderList(t._id,!!t.getReplacementMesh());if(!b.mustReturn){var P=d.getCaps().instancedArrays&&(b.visibleInstances[t._id]!==null&&b.visibleInstances[t._id]!==void 0||o.hasThinInstances);if(!this.customAllowRendering||this.customAllowRendering(t))if(this.isReady(t,P,e)){t._renderId=s.getRenderId();var O=(n=o.material)===null||n===void 0?void 0:n.shadowDepthWrapper,B=(i=O?.getEffect(t,this))!==null&&i!==void 0?i:this._effect;if(d.enableEffect(B),o._bind(t,B,p.fillMode),this.getTransformMatrix(),B.setFloat3("biasAndScaleSM",this.bias,this.normalBias,this.depthScale),this.getLight().getTypeID()===Ci.a.LIGHTTYPEID_DIRECTIONALLIGHT?B.setVector3("lightDataSM",this._cachedDirection):B.setVector3("lightDataSM",this._cachedPosition),s.activeCamera&&B.setFloat2("depthValuesSM",this.getLight().getDepthMinZ(s.activeCamera),this.getLight().getDepthMinZ(s.activeCamera)+this.getLight().getDepthMaxZ(s.activeCamera)),e&&this.enableSoftTransparentShadow&&B.setFloat("softTransparentShadowSM",a.visibility),O)t._effectOverride=B,O.standalone?O.baseMaterial.bindForSubMesh(a.getWorldMatrix(),o,t):p.bindForSubMesh(a.getWorldMatrix(),o,t),t._effectOverride=null;else{if(B.setMatrix("viewProjection",this.getTransformMatrix()),p&&p.needAlphaTesting()){var F=p.getAlphaTestTexture();F&&(B.setTexture("diffuseSampler",F),B.setMatrix("diffuseMatrix",F.getTextureMatrix()||this._defaultTextureMatrix))}if(o.useBones&&o.computeBonesUsingShaders&&o.skeleton){var z=o.skeleton;if(z.isUsingTextureForMatrices){var J=z.getTransformMatrixTexture(o);if(!J)return;B.setTexture("boneSampler",J),B.setFloat("boneTextureWidth",4*(z.bones.length+1))}else B.setMatrices("mBones",z.getTransformMatrices(o))}et.a.BindMorphTargetParameters(o,B),et.a.BindClipPlane(B,s)}this._bindCustomEffectForRenderSubMeshForShadowMap(t,B,O?._matriceNames,a),this.forceBackFacesOnly&&d.setState(!0,0,!1,!0),this.onBeforeShadowMapRenderMeshObservable.notifyObservers(o),this.onBeforeShadowMapRenderObservable.notifyObservers(B),o._processRendering(a,t,B,p.fillMode,b,P,function(ie,se){return B.setMatrix("world",se)}),this.forceBackFacesOnly&&d.setState(!0,0,!1,!1),this.onAfterShadowMapRenderObservable.notifyObservers(B),this.onAfterShadowMapRenderMeshObservable.notifyObservers(o)}else this._shadowMap&&this._shadowMap.resetRefreshCounter()}}},r.prototype._applyFilterValues=function(){this._shadowMap&&(this.filter===r.FILTER_NONE||this.filter===r.FILTER_PCSS?this._shadowMap.updateSamplingMode(we.a.NEAREST_SAMPLINGMODE):this._shadowMap.updateSamplingMode(we.a.BILINEAR_SAMPLINGMODE))},r.prototype.forceCompilation=function(t,e){var n=this,i=Object(c.a)({useInstances:!1},e),o=this.getShadowMap();if(o){var a=o.renderList;if(a){for(var s=new Array,d=0,p=a;d<p.length;d++){var b=p[d];s.push.apply(s,b.subMeshes)}if(s.length!==0){var P=0,O=function(){var B,F;if(n._scene&&n._scene.getEngine()){for(;n.isReady(s[P],i.useInstances,(F=(B=s[P].getMaterial())===null||B===void 0?void 0:B.needAlphaBlendingForMesh(s[P].getMesh()))!==null&&F!==void 0&&F);)if(++P>=s.length)return void(t&&t(n));setTimeout(O,16)}};O()}else t&&t(this)}else t&&t(this)}else t&&t(this)},r.prototype.forceCompilationAsync=function(t){var e=this;return new Promise(function(n){e.forceCompilation(function(){n()},t)})},r.prototype._isReadyCustomDefines=function(t,e,n){},r.prototype._prepareShadowDefines=function(t,e,n,i){n.push("#define SM_FLOAT "+(this._textureType!==h.a.TEXTURETYPE_UNSIGNED_INT?"1":"0")),n.push("#define SM_ESM "+(this.useExponentialShadowMap||this.useBlurExponentialShadowMap?"1":"0")),n.push("#define SM_DEPTHTEXTURE "+(this.usePercentageCloserFiltering||this.useContactHardeningShadow?"1":"0"));var o=t.getMesh();return n.push("#define SM_NORMALBIAS "+(this.normalBias&&o.isVerticesDataPresent(Oe.b.NormalKind)?"1":"0")),n.push("#define SM_DIRECTIONINLIGHTDATA "+(this.getLight().getTypeID()===Ci.a.LIGHTTYPEID_DIRECTIONALLIGHT?"1":"0")),n.push("#define SM_USEDISTANCE "+(this._light.needCube()?"1":"0")),n.push("#define SM_SOFTTRANSPARENTSHADOW "+(this.enableSoftTransparentShadow&&i?"1":"0")),this._isReadyCustomDefines(n,t,e),n},r.prototype.isReady=function(t,e,n){var i=t.getMaterial(),o=i?.shadowDepthWrapper,a=[];if(this._prepareShadowDefines(t,e,a,n),o){if(!o.isReadyForSubMesh(t,a,this,e))return!1}else{var s=[Oe.b.PositionKind],d=t.getMesh();if(this.normalBias&&d.isVerticesDataPresent(Oe.b.NormalKind)&&(s.push(Oe.b.NormalKind),a.push("#define NORMAL"),d.nonUniformScaling&&a.push("#define NONUNIFORMSCALING")),i&&i.needAlphaTesting()){var p=i.getAlphaTestTexture();if(p){if(!p.isReady())return!1;a.push("#define ALPHATEST"),d.isVerticesDataPresent(Oe.b.UVKind)&&(s.push(Oe.b.UVKind),a.push("#define UV1")),d.isVerticesDataPresent(Oe.b.UV2Kind)&&p.coordinatesIndex===1&&(s.push(Oe.b.UV2Kind),a.push("#define UV2"))}}var b=new Sr.a;if(d.useBones&&d.computeBonesUsingShaders&&d.skeleton){s.push(Oe.b.MatricesIndicesKind),s.push(Oe.b.MatricesWeightsKind),d.numBoneInfluencers>4&&(s.push(Oe.b.MatricesIndicesExtraKind),s.push(Oe.b.MatricesWeightsExtraKind));var P=d.skeleton;a.push("#define NUM_BONE_INFLUENCERS "+d.numBoneInfluencers),d.numBoneInfluencers>0&&b.addCPUSkinningFallback(0,d),P.isUsingTextureForMatrices?a.push("#define BONETEXTURE"):a.push("#define BonesPerMesh "+(P.bones.length+1))}else a.push("#define NUM_BONE_INFLUENCERS 0");var O=d.morphTargetManager,B=0;O&&O.numInfluencers>0&&(a.push("#define MORPHTARGETS"),B=O.numInfluencers,a.push("#define NUM_MORPH_INFLUENCERS "+B),et.a.PrepareAttributesForMorphTargetsInfluencers(s,d,B));var F=this._scene;if(F.clipPlane&&a.push("#define CLIPPLANE"),F.clipPlane2&&a.push("#define CLIPPLANE2"),F.clipPlane3&&a.push("#define CLIPPLANE3"),F.clipPlane4&&a.push("#define CLIPPLANE4"),F.clipPlane5&&a.push("#define CLIPPLANE5"),F.clipPlane6&&a.push("#define CLIPPLANE6"),e&&(a.push("#define INSTANCES"),et.a.PushAttributesForInstances(s),t.getRenderingMesh().hasThinInstances&&a.push("#define THIN_INSTANCES")),this.customShaderOptions&&this.customShaderOptions.defines)for(var z=0,J=this.customShaderOptions.defines;z<J.length;z++){var ie=J[z];a.indexOf(ie)===-1&&a.push(ie)}var se=a.join(`
-`);if(this._cachedDefines!==se){this._cachedDefines=se;var ce="shadowMap",ue=["world","mBones","viewProjection","diffuseMatrix","lightDataSM","depthValuesSM","biasAndScaleSM","morphTargetInfluences","boneTextureWidth","vClipPlane","vClipPlane2","vClipPlane3","vClipPlane4","vClipPlane5","vClipPlane6","softTransparentShadowSM"],fe=["diffuseSampler","boneSampler"];if(this.customShaderOptions){if(ce=this.customShaderOptions.shaderName,this.customShaderOptions.attributes)for(var ve=0,Te=this.customShaderOptions.attributes;ve<Te.length;ve++){var Re=Te[ve];s.indexOf(Re)===-1&&s.push(Re)}if(this.customShaderOptions.uniforms)for(var Ae=0,Ee=this.customShaderOptions.uniforms;Ae<Ee.length;Ae++){var Se=Ee[Ae];ue.indexOf(Se)===-1&&ue.push(Se)}if(this.customShaderOptions.samplers)for(var Le=0,xe=this.customShaderOptions.samplers;Le<xe.length;Le++){var Ne=xe[Le];fe.indexOf(Ne)===-1&&fe.push(Ne)}}this._effect=this._scene.getEngine().createEffect(ce,s,ue,fe,se,b,void 0,void 0,{maxSimultaneousMorphTargets:B})}if(!this._effect.isReady())return!1}return(this.useBlurExponentialShadowMap||this.useBlurCloseExponentialShadowMap)&&(this._blurPostProcesses&&this._blurPostProcesses.length||this._initializeBlurRTTAndPostProcesses()),!(this._kernelBlurXPostprocess&&!this._kernelBlurXPostprocess.isReady())&&!(this._kernelBlurYPostprocess&&!this._kernelBlurYPostprocess.isReady())&&!(this._boxBlurPostprocess&&!this._boxBlurPostprocess.isReady())},r.prototype.prepareDefines=function(t,e){var n=this._scene,i=this._light;n.shadowsEnabled&&i.shadowEnabled&&(t["SHADOW"+e]=!0,this.useContactHardeningShadow?(t["SHADOWPCSS"+e]=!0,this._filteringQuality===r.QUALITY_LOW?t["SHADOWLOWQUALITY"+e]=!0:this._filteringQuality===r.QUALITY_MEDIUM&&(t["SHADOWMEDIUMQUALITY"+e]=!0)):this.usePercentageCloserFiltering?(t["SHADOWPCF"+e]=!0,this._filteringQuality===r.QUALITY_LOW?t["SHADOWLOWQUALITY"+e]=!0:this._filteringQuality===r.QUALITY_MEDIUM&&(t["SHADOWMEDIUMQUALITY"+e]=!0)):this.usePoissonSampling?t["SHADOWPOISSON"+e]=!0:this.useExponentialShadowMap||this.useBlurExponentialShadowMap?t["SHADOWESM"+e]=!0:(this.useCloseExponentialShadowMap||this.useBlurCloseExponentialShadowMap)&&(t["SHADOWCLOSEESM"+e]=!0),i.needCube()&&(t["SHADOWCUBE"+e]=!0))},r.prototype.bindShadowLight=function(t,e){var n=this._light,i=this._scene;if(i.shadowsEnabled&&n.shadowEnabled){var o=i.activeCamera;if(o){var a=this.getShadowMap();a&&(n.needCube()||e.setMatrix("lightMatrix"+t,this.getTransformMatrix()),this._filter===r.FILTER_PCF?(e.setDepthStencilTexture("shadowSampler"+t,this.getShadowMapForRendering()),n._uniformBuffer.updateFloat4("shadowsInfo",this.getDarkness(),a.getSize().width,1/a.getSize().width,this.frustumEdgeFalloff,t)):this._filter===r.FILTER_PCSS?(e.setDepthStencilTexture("shadowSampler"+t,this.getShadowMapForRendering()),e.setTexture("depthSampler"+t,this.getShadowMapForRendering()),n._uniformBuffer.updateFloat4("shadowsInfo",this.getDarkness(),1/a.getSize().width,this._contactHardeningLightSizeUVRatio*a.getSize().width,this.frustumEdgeFalloff,t)):(e.setTexture("shadowSampler"+t,this.getShadowMapForRendering()),n._uniformBuffer.updateFloat4("shadowsInfo",this.getDarkness(),this.blurScale/a.getSize().width,this.depthScale,this.frustumEdgeFalloff,t)),n._uniformBuffer.updateFloat2("depthValues",this.getLight().getDepthMinZ(o),this.getLight().getDepthMinZ(o)+this.getLight().getDepthMaxZ(o),t))}}},r.prototype.getTransformMatrix=function(){var t=this._scene;if(this._currentRenderID===t.getRenderId()&&this._currentFaceIndexCache===this._currentFaceIndex)return this._transformMatrix;this._currentRenderID=t.getRenderId(),this._currentFaceIndexCache=this._currentFaceIndex;var e=this._light.position;if(this._light.computeTransformedInformation()&&(e=this._light.transformedPosition),u.e.NormalizeToRef(this._light.getShadowDirection(this._currentFaceIndex),this._lightDirection),Math.abs(u.e.Dot(this._lightDirection,u.e.Up()))===1&&(this._lightDirection.z=1e-13),this._light.needProjectionMatrixCompute()||!this._cachedPosition||!this._cachedDirection||!e.equals(this._cachedPosition)||!this._lightDirection.equals(this._cachedDirection)){this._cachedPosition.copyFrom(e),this._cachedDirection.copyFrom(this._lightDirection),u.a.LookAtLHToRef(e,e.add(this._lightDirection),u.e.Up(),this._viewMatrix);var n=this.getShadowMap();if(n){var i=n.renderList;i&&this._light.setShadowProjectionMatrix(this._projectionMatrix,this._viewMatrix,i)}this._viewMatrix.multiplyToRef(this._projectionMatrix,this._transformMatrix)}return this._transformMatrix},r.prototype.recreateShadowMap=function(){var t=this._shadowMap;if(t){var e=t.renderList;this._disposeRTTandPostProcesses(),this._initializeGenerator(),this.filter=this.filter,this._applyFilterValues(),this._shadowMap.renderList=e}},r.prototype._disposeBlurPostProcesses=function(){this._shadowMap2&&(this._shadowMap2.dispose(),this._shadowMap2=null),this._boxBlurPostprocess&&(this._boxBlurPostprocess.dispose(),this._boxBlurPostprocess=null),this._kernelBlurXPostprocess&&(this._kernelBlurXPostprocess.dispose(),this._kernelBlurXPostprocess=null),this._kernelBlurYPostprocess&&(this._kernelBlurYPostprocess.dispose(),this._kernelBlurYPostprocess=null),this._blurPostProcesses=[]},r.prototype._disposeRTTandPostProcesses=function(){this._shadowMap&&(this._shadowMap.dispose(),this._shadowMap=null),this._disposeBlurPostProcesses()},r.prototype.dispose=function(){this._disposeRTTandPostProcesses(),this._light&&(this._light._shadowGenerator=null,this._light._markMeshesAsLightDirty()),this.onBeforeShadowMapRenderMeshObservable.clear(),this.onBeforeShadowMapRenderObservable.clear(),this.onAfterShadowMapRenderMeshObservable.clear(),this.onAfterShadowMapRenderObservable.clear()},r.prototype.serialize=function(){var t={},e=this.getShadowMap();if(!e)return t;if(t.className=this.getClassName(),t.lightId=this._light.id,t.id=this._light.id,t.mapSize=e.getRenderSize(),t.forceBackFacesOnly=this.forceBackFacesOnly,t.darkness=this.getDarkness(),t.transparencyShadow=this._transparencyShadow,t.frustumEdgeFalloff=this.frustumEdgeFalloff,t.bias=this.bias,t.normalBias=this.normalBias,t.usePercentageCloserFiltering=this.usePercentageCloserFiltering,t.useContactHardeningShadow=this.useContactHardeningShadow,t.contactHardeningLightSizeUVRatio=this.contactHardeningLightSizeUVRatio,t.filteringQuality=this.filteringQuality,t.useExponentialShadowMap=this.useExponentialShadowMap,t.useBlurExponentialShadowMap=this.useBlurExponentialShadowMap,t.useCloseExponentialShadowMap=this.useBlurExponentialShadowMap,t.useBlurCloseExponentialShadowMap=this.useBlurExponentialShadowMap,t.usePoissonSampling=this.usePoissonSampling,t.depthScale=this.depthScale,t.blurBoxOffset=this.blurBoxOffset,t.blurKernel=this.blurKernel,t.blurScale=this.blurScale,t.useKernelBlur=this.useKernelBlur,t.renderList=[],e.renderList)for(var n=0;n<e.renderList.length;n++){var i=e.renderList[n];t.renderList.push(i.id)}return t},r.Parse=function(t,e,n){for(var i=e.getLightByID(t.lightId),o=n?n(t.mapSize,i):new r(t.mapSize,i),a=o.getShadowMap(),s=0;s<t.renderList.length;s++)e.getMeshesByID(t.renderList[s]).forEach(function(d){a&&(a.renderList||(a.renderList=[]),a.renderList.push(d))});return t.id!==void 0&&(o.id=t.id),o.forceBackFacesOnly=!!t.forceBackFacesOnly,t.darkness!==void 0&&o.setDarkness(t.darkness),t.transparencyShadow&&o.setTransparencyShadow(!0),t.frustumEdgeFalloff!==void 0&&(o.frustumEdgeFalloff=t.frustumEdgeFalloff),t.bias!==void 0&&(o.bias=t.bias),t.normalBias!==void 0&&(o.normalBias=t.normalBias),t.usePercentageCloserFiltering?o.usePercentageCloserFiltering=!0:t.useContactHardeningShadow?o.useContactHardeningShadow=!0:t.usePoissonSampling?o.usePoissonSampling=!0:t.useExponentialShadowMap?o.useExponentialShadowMap=!0:t.useBlurExponentialShadowMap?o.useBlurExponentialShadowMap=!0:t.useCloseExponentialShadowMap?o.useCloseExponentialShadowMap=!0:t.useBlurCloseExponentialShadowMap?o.useBlurCloseExponentialShadowMap=!0:t.useVarianceShadowMap?o.useExponentialShadowMap=!0:t.useBlurVarianceShadowMap&&(o.useBlurExponentialShadowMap=!0),t.contactHardeningLightSizeUVRatio!==void 0&&(o.contactHardeningLightSizeUVRatio=t.contactHardeningLightSizeUVRatio),t.filteringQuality!==void 0&&(o.filteringQuality=t.filteringQuality),t.depthScale&&(o.depthScale=t.depthScale),t.blurScale&&(o.blurScale=t.blurScale),t.blurBoxOffset&&(o.blurBoxOffset=t.blurBoxOffset),t.useKernelBlur&&(o.useKernelBlur=t.useKernelBlur),t.blurKernel&&(o.blurKernel=t.blurKernel),o},r.CLASSNAME="ShadowGenerator",r.FILTER_NONE=0,r.FILTER_EXPONENTIALSHADOWMAP=1,r.FILTER_POISSONSAMPLING=2,r.FILTER_BLUREXPONENTIALSHADOWMAP=3,r.FILTER_CLOSEEXPONENTIALSHADOWMAP=4,r.FILTER_BLURCLOSEEXPONENTIALSHADOWMAP=5,r.FILTER_PCF=6,r.FILTER_PCSS=7,r.QUALITY_HIGH=0,r.QUALITY_MEDIUM=1,r.QUALITY_LOW=2,r._SceneComponentInitialization=function(t){throw An.a.WarnImport("ShadowGeneratorSceneComponent")},r}(),j_=`#ifdef ALPHATEST
-varying vec2 vUV;
-uniform sampler2D diffuseSampler;
-#endif
-varying float vDepthMetric;
-#ifdef PACKED
-#include<packingFunctions>
-#endif
-void main(void)
-{
-#ifdef ALPHATEST
-if (texture2D(diffuseSampler,vUV).a<0.4)
-discard;
-#endif
-#ifdef NONLINEARDEPTH
-#ifdef PACKED
-gl_FragColor=pack(gl_FragCoord.z);
-#else
-gl_FragColor=vec4(gl_FragCoord.z,0.0,0.0,0.0);
-#endif
-#else
-#ifdef PACKED
-gl_FragColor=pack(vDepthMetric);
-#else
-gl_FragColor=vec4(vDepthMetric,0.0,0.0,1.0);
-#endif
-#endif
-}`;ze.a.ShadersStore.depthPixelShader=j_;var H_=`
-attribute vec3 position;
-#include<bonesDeclaration>
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-
-#include<instancesDeclaration>
-uniform mat4 viewProjection;
-uniform vec2 depthValues;
-#if defined(ALPHATEST) || defined(NEED_UV)
-varying vec2 vUV;
-uniform mat4 diffuseMatrix;
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#endif
-varying float vDepthMetric;
-void main(void)
-{
-vec3 positionUpdated=position;
-#ifdef UV1
-vec2 uvUpdated=uv;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-#include<instancesVertex>
-#include<bonesVertex>
-gl_Position=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-vDepthMetric=((gl_Position.z+depthValues.x)/(depthValues.y));
-#if defined(ALPHATEST) || defined(BASIC_RENDER)
-#ifdef UV1
-vUV=vec2(diffuseMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef UV2
-vUV=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-}
-`;ze.a.ShadersStore.depthVertexShader=H_;var oa=function(){function r(t,e,n,i){var o=this;e===void 0&&(e=h.a.TEXTURETYPE_FLOAT),n===void 0&&(n=null),i===void 0&&(i=!1),this.enabled=!0,this.useOnlyInActiveCamera=!1,this._scene=t,this._storeNonLinearDepth=i,this.isPacked=e===h.a.TEXTURETYPE_UNSIGNED_BYTE,this.isPacked?this._clearColor=new M.b(1,1,1,1):this._clearColor=new M.b(1,0,0,1),r._SceneComponentInitialization(this._scene),this._camera=n;var a=t.getEngine(),s=this.isPacked||a.webGLVersion===1?h.a.TEXTUREFORMAT_RGBA:h.a.TEXTUREFORMAT_R;this._depthMap=new sn("depthMap",{width:a.getRenderWidth(),height:a.getRenderHeight()},this._scene,!1,!0,e,!1,void 0,void 0,void 0,void 0,s),this._depthMap.wrapU=we.a.CLAMP_ADDRESSMODE,this._depthMap.wrapV=we.a.CLAMP_ADDRESSMODE,this._depthMap.refreshRate=1,this._depthMap.renderParticles=!1,this._depthMap.renderList=null,this._depthMap.activeCamera=this._camera,this._depthMap.ignoreCameraViewport=!0,this._depthMap.useCameraPostProcesses=!1,this._depthMap.onClearObservable.add(function(p){p.clear(o._clearColor,!0,!0,!0)});var d=function(p){var b=p.getRenderingMesh(),P=p.getEffectiveMesh(),O=o._scene,B=O.getEngine(),F=p.getMaterial();if(P._internalAbstractMeshDataInfo._isActiveIntermediate=!1,F&&p.verticesCount!==0&&p._renderId!==O.getRenderId()){B.setState(F.backFaceCulling,0,!1,O.useRightHandedSystem);var z=b._getInstancesRenderList(p._id,!!p.getReplacementMesh());if(!z.mustReturn){var J=B.getCaps().instancedArrays&&(z.visibleInstances[p._id]!==null&&z.visibleInstances[p._id]!==void 0||b.hasThinInstances),ie=o._camera||O.activeCamera;if(o.isReady(p,J)&&ie){if(p._renderId=O.getRenderId(),B.enableEffect(o._effect),b._bind(p,o._effect,F.fillMode),o._effect.setMatrix("viewProjection",O.getTransformMatrix()),o._effect.setFloat2("depthValues",ie.minZ,ie.minZ+ie.maxZ),F&&F.needAlphaTesting()){var se=F.getAlphaTestTexture();se&&(o._effect.setTexture("diffuseSampler",se),o._effect.setMatrix("diffuseMatrix",se.getTextureMatrix()))}b.useBones&&b.computeBonesUsingShaders&&b.skeleton&&o._effect.setMatrices("mBones",b.skeleton.getTransformMatrices(b)),et.a.BindMorphTargetParameters(b,o._effect),b._processRendering(P,p,o._effect,F.fillMode,z,J,function(ce,ue){return o._effect.setMatrix("world",ue)})}}}};this._depthMap.customRenderFunction=function(p,b,P,O){var B;if(O.length){for(a.setColorWrite(!1),B=0;B<O.length;B++)d(O.data[B]);a.setColorWrite(!0)}for(B=0;B<p.length;B++)d(p.data[B]);for(B=0;B<b.length;B++)d(b.data[B])}}return r.prototype.isReady=function(t,e){var n=t.getMaterial();if(n.disableDepthWrite)return!1;var i=[],o=[Oe.b.PositionKind],a=t.getMesh();n&&n.needAlphaTesting()&&n.getAlphaTestTexture()&&(i.push("#define ALPHATEST"),a.isVerticesDataPresent(Oe.b.UVKind)&&(o.push(Oe.b.UVKind),i.push("#define UV1")),a.isVerticesDataPresent(Oe.b.UV2Kind)&&(o.push(Oe.b.UV2Kind),i.push("#define UV2"))),a.useBones&&a.computeBonesUsingShaders?(o.push(Oe.b.MatricesIndicesKind),o.push(Oe.b.MatricesWeightsKind),a.numBoneInfluencers>4&&(o.push(Oe.b.MatricesIndicesExtraKind),o.push(Oe.b.MatricesWeightsExtraKind)),i.push("#define NUM_BONE_INFLUENCERS "+a.numBoneInfluencers),i.push("#define BonesPerMesh "+(a.skeleton?a.skeleton.bones.length+1:0))):i.push("#define NUM_BONE_INFLUENCERS 0");var s=a.morphTargetManager,d=0;s&&s.numInfluencers>0&&(d=s.numInfluencers,i.push("#define MORPHTARGETS"),i.push("#define NUM_MORPH_INFLUENCERS "+d),et.a.PrepareAttributesForMorphTargetsInfluencers(o,a,d)),e&&(i.push("#define INSTANCES"),et.a.PushAttributesForInstances(o),t.getRenderingMesh().hasThinInstances&&i.push("#define THIN_INSTANCES")),this._storeNonLinearDepth&&i.push("#define NONLINEARDEPTH"),this.isPacked&&i.push("#define PACKED");var p=i.join(`
-`);return this._cachedDefines!==p&&(this._cachedDefines=p,this._effect=this._scene.getEngine().createEffect("depth",o,["world","mBones","viewProjection","diffuseMatrix","depthValues","morphTargetInfluences"],["diffuseSampler"],p,void 0,void 0,void 0,{maxSimultaneousMorphTargets:d})),this._effect.isReady()},r.prototype.getDepthMap=function(){return this._depthMap},r.prototype.dispose=function(){this._depthMap.dispose()},r._SceneComponentInitialization=function(t){throw An.a.WarnImport("DepthRendererSceneComponent")},r}(),W_=`attribute vec2 vUV;
-uniform sampler2D textureSampler;
-#if defined(INITIAL)
-uniform sampler2D sourceTexture;
-uniform vec2 texSize;
-void main(void)
-{
-ivec2 coord=ivec2(vUV*(texSize-1.0));
-float f1=texelFetch(sourceTexture,coord,0).r;
-float f2=texelFetch(sourceTexture,coord+ivec2(1,0),0).r;
-float f3=texelFetch(sourceTexture,coord+ivec2(1,1),0).r;
-float f4=texelFetch(sourceTexture,coord+ivec2(0,1),0).r;
-float minz=min(min(min(f1,f2),f3),f4);
-#ifdef DEPTH_REDUX
-float maxz=max(max(max(sign(1.0-f1)*f1,sign(1.0-f2)*f2),sign(1.0-f3)*f3),sign(1.0-f4)*f4);
-#else
-float maxz=max(max(max(f1,f2),f3),f4);
-#endif
-glFragColor=vec4(minz,maxz,0.,0.);
-}
-#elif defined(MAIN)
-uniform vec2 texSize;
-void main(void)
-{
-ivec2 coord=ivec2(vUV*(texSize-1.0));
-vec2 f1=texelFetch(textureSampler,coord,0).rg;
-vec2 f2=texelFetch(textureSampler,coord+ivec2(1,0),0).rg;
-vec2 f3=texelFetch(textureSampler,coord+ivec2(1,1),0).rg;
-vec2 f4=texelFetch(textureSampler,coord+ivec2(0,1),0).rg;
-float minz=min(min(min(f1.x,f2.x),f3.x),f4.x);
-float maxz=max(max(max(f1.y,f2.y),f3.y),f4.y);
-glFragColor=vec4(minz,maxz,0.,0.);
-}
-#elif defined(ONEBEFORELAST)
-uniform ivec2 texSize;
-void main(void)
-{
-ivec2 coord=ivec2(vUV*vec2(texSize-1));
-vec2 f1=texelFetch(textureSampler,coord % texSize,0).rg;
-vec2 f2=texelFetch(textureSampler,(coord+ivec2(1,0)) % texSize,0).rg;
-vec2 f3=texelFetch(textureSampler,(coord+ivec2(1,1)) % texSize,0).rg;
-vec2 f4=texelFetch(textureSampler,(coord+ivec2(0,1)) % texSize,0).rg;
-float minz=min(f1.x,f2.x);
-float maxz=max(f1.y,f2.y);
-glFragColor=vec4(minz,maxz,0.,0.);
-}
-#elif defined(LAST)
-void main(void)
-{
-discard;
-glFragColor=vec4(0.);
-}
-#endif
-`;ze.a.ShadersStore.minmaxReduxPixelShader=W_;var Uu=function(){function r(t){this.onAfterReductionPerformed=new C.c,this._forceFullscreenViewport=!0,this._activated=!1,this._camera=t,this._postProcessManager=new fs.a(t.getScene())}return Object.defineProperty(r.prototype,"sourceTexture",{get:function(){return this._sourceTexture},enumerable:!1,configurable:!0}),r.prototype.setSourceTexture=function(t,e,n,i){var o=this;if(n===void 0&&(n=h.a.TEXTURETYPE_HALF_FLOAT),i===void 0&&(i=!0),t!==this._sourceTexture){this.dispose(!1),this._sourceTexture=t,this._reductionSteps=[],this._forceFullscreenViewport=i;var a=this._camera.getScene(),s=new _t("Initial reduction phase","minmaxRedux",["texSize"],["sourceTexture"],1,null,h.a.TEXTURE_NEAREST_NEAREST,a.getEngine(),!1,"#define INITIAL"+(e?`
-#define DEPTH_REDUX`:""),n,void 0,void 0,void 0,h.a.TEXTUREFORMAT_RG);s.autoClear=!1,s.forceFullscreenViewport=i;var d=this._sourceTexture.getRenderWidth(),p=this._sourceTexture.getRenderHeight();s.onApply=function(O,B){return function(F){F.setTexture("sourceTexture",o._sourceTexture),F.setFloatArray2("texSize",new Float32Array([O,B]))}}(d,p),this._reductionSteps.push(s);for(var b=1;d>1||p>1;){d=Math.max(Math.round(d/2),1),p=Math.max(Math.round(p/2),1);var P=new _t("Reduction phase "+b,"minmaxRedux",["texSize"],null,{width:d,height:p},null,h.a.TEXTURE_NEAREST_NEAREST,a.getEngine(),!1,"#define "+(d==1&&p==1?"LAST":d==1||p==1?"ONEBEFORELAST":"MAIN"),n,void 0,void 0,void 0,h.a.TEXTUREFORMAT_RG);P.autoClear=!1,P.forceFullscreenViewport=i,P.onApply=function(O,B){return function(F){O==1||B==1?F.setIntArray2("texSize",new Int32Array([O,B])):F.setFloatArray2("texSize",new Float32Array([O,B]))}}(d,p),this._reductionSteps.push(P),b++,d==1&&p==1&&P.onAfterRenderObservable.add(function(O,B,F){var z=new Float32Array(4*O*B),J={min:0,max:0};return function(){a.getEngine()._readTexturePixels(F.inputTexture,O,B,-1,0,z),J.min=z[0],J.max=z[1],o.onAfterReductionPerformed.notifyObservers(J)}}(d,p,P))}}},Object.defineProperty(r.prototype,"refreshRate",{get:function(){return this._sourceTexture?this._sourceTexture.refreshRate:-1},set:function(t){this._sourceTexture&&(this._sourceTexture.refreshRate=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"activated",{get:function(){return this._activated},enumerable:!1,configurable:!0}),r.prototype.activate=function(){var t=this;!this._onAfterUnbindObserver&&this._sourceTexture&&(this._onAfterUnbindObserver=this._sourceTexture.onAfterUnbindObservable.add(function(){t._reductionSteps[0].activate(t._camera),t._postProcessManager.directRender(t._reductionSteps,t._reductionSteps[0].inputTexture,t._forceFullscreenViewport),t._camera.getScene().getEngine().unBindFramebuffer(t._reductionSteps[0].inputTexture,!1)}),this._activated=!0)},r.prototype.deactivate=function(){this._onAfterUnbindObserver&&this._sourceTexture&&(this._sourceTexture.onAfterUnbindObservable.remove(this._onAfterUnbindObserver),this._onAfterUnbindObserver=null,this._activated=!1)},r.prototype.dispose=function(t){if(t===void 0&&(t=!0),t&&this.onAfterReductionPerformed.clear(),this.deactivate(),this._reductionSteps){for(var e=0;e<this._reductionSteps.length;++e)this._reductionSteps[e].dispose();this._reductionSteps=null}this._postProcessManager&&t&&this._postProcessManager.dispose(),this._sourceTexture=null},r}(),Vu=function(r){function t(e){return r.call(this,e)||this}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"depthRenderer",{get:function(){return this._depthRenderer},enumerable:!1,configurable:!0}),t.prototype.setDepthRenderer=function(e,n,i){e===void 0&&(e=null),n===void 0&&(n=h.a.TEXTURETYPE_HALF_FLOAT),i===void 0&&(i=!0);var o=this._camera.getScene();this._depthRenderer&&(delete o._depthRenderer[this._depthRendererId],this._depthRenderer.dispose(),this._depthRenderer=null),e===null&&(o._depthRenderer||(o._depthRenderer={}),(e=this._depthRenderer=new oa(o,n,this._camera,!1)).enabled=!1,this._depthRendererId="minmax"+this._camera.id,o._depthRenderer[this._depthRendererId]=e),r.prototype.setSourceTexture.call(this,e.getDepthMap(),!0,n,i)},t.prototype.setSourceTexture=function(e,n,i,o){i===void 0&&(i=h.a.TEXTURETYPE_HALF_FLOAT),o===void 0&&(o=!0),r.prototype.setSourceTexture.call(this,e,n,i,o)},t.prototype.activate=function(){this._depthRenderer&&(this._depthRenderer.enabled=!0),r.prototype.activate.call(this)},t.prototype.deactivate=function(){r.prototype.deactivate.call(this),this._depthRenderer&&(this._depthRenderer.enabled=!1)},t.prototype.dispose=function(e){if(e===void 0&&(e=!0),r.prototype.dispose.call(this,e),this._depthRenderer&&e){var n=this._depthRenderer.getDepthMap().getScene();n&&delete n._depthRenderer[this._depthRendererId],this._depthRenderer.dispose(),this._depthRenderer=null}},t}(Uu),ku=u.e.Up(),X_=u.e.Zero(),vn=new u.e,Or=new u.e,Mr=new u.a,Gu=new u.a,Ws=function(r){function t(e,n,i){var o=this;if(t.IsSupported)return(o=r.call(this,e,n,i)||this).usePercentageCloserFiltering=!0,o;l.a.Error("CascadedShadowMap needs WebGL 2 support.")}return Object(c.d)(t,r),t.prototype._validateFilter=function(e){return e===Un.FILTER_NONE||e===Un.FILTER_PCF||e===Un.FILTER_PCSS?e:(console.error('Unsupported filter "'+e+'"!'),Un.FILTER_NONE)},Object.defineProperty(t.prototype,"numCascades",{get:function(){return this._numCascades},set:function(e){(e=Math.min(Math.max(e,t.MIN_CASCADES_COUNT),t.MAX_CASCADES_COUNT))!==this._numCascades&&(this._numCascades=e,this.recreateShadowMap())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"freezeShadowCastersBoundingInfo",{get:function(){return this._freezeShadowCastersBoundingInfo},set:function(e){this._freezeShadowCastersBoundingInfoObservable&&e&&(this._scene.onBeforeRenderObservable.remove(this._freezeShadowCastersBoundingInfoObservable),this._freezeShadowCastersBoundingInfoObservable=null),this._freezeShadowCastersBoundingInfoObservable||e||(this._freezeShadowCastersBoundingInfoObservable=this._scene.onBeforeRenderObservable.add(this._computeShadowCastersBoundingInfo.bind(this))),this._freezeShadowCastersBoundingInfo=e,e&&this._computeShadowCastersBoundingInfo()},enumerable:!1,configurable:!0}),t.prototype._computeShadowCastersBoundingInfo=function(){if(this._scbiMin.copyFromFloats(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._scbiMax.copyFromFloats(Number.MIN_VALUE,Number.MIN_VALUE,Number.MIN_VALUE),this._shadowMap&&this._shadowMap.renderList){for(var e=this._shadowMap.renderList,n=0;n<e.length;n++)if(a=e[n]){var i=a.getBoundingInfo().boundingBox;this._scbiMin.minimizeInPlace(i.minimumWorld),this._scbiMax.maximizeInPlace(i.maximumWorld)}var o=this._scene.meshes;for(n=0;n<o.length;n++){var a;(a=o[n])&&a.isVisible&&a.isEnabled&&a.receiveShadows&&(i=a.getBoundingInfo().boundingBox,this._scbiMin.minimizeInPlace(i.minimumWorld),this._scbiMax.maximizeInPlace(i.maximumWorld))}}this._shadowCastersBoundingInfo.reConstruct(this._scbiMin,this._scbiMax)},Object.defineProperty(t.prototype,"shadowCastersBoundingInfo",{get:function(){return this._shadowCastersBoundingInfo},set:function(e){this._shadowCastersBoundingInfo=e},enumerable:!1,configurable:!0}),t.prototype.setMinMaxDistance=function(e,n){this._minDistance===e&&this._maxDistance===n||(e>n&&(e=0,n=1),e<0&&(e=0),n>1&&(n=1),this._minDistance=e,this._maxDistance=n,this._breaksAreDirty=!0)},Object.defineProperty(t.prototype,"minDistance",{get:function(){return this._minDistance},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"maxDistance",{get:function(){return this._maxDistance},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return t.CLASSNAME},t.prototype.getCascadeMinExtents=function(e){return e>=0&&e<this._numCascades?this._cascadeMinExtents[e]:null},t.prototype.getCascadeMaxExtents=function(e){return e>=0&&e<this._numCascades?this._cascadeMaxExtents[e]:null},Object.defineProperty(t.prototype,"shadowMaxZ",{get:function(){return this._scene&&this._scene.activeCamera?this._shadowMaxZ:0},set:function(e){this._scene&&this._scene.activeCamera?this._shadowMaxZ===e||e<this._scene.activeCamera.minZ||e>this._scene.activeCamera.maxZ||(this._shadowMaxZ=e,this._light._markMeshesAsLightDirty(),this._breaksAreDirty=!0):this._shadowMaxZ=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"debug",{get:function(){return this._debug},set:function(e){this._debug=e,this._light._markMeshesAsLightDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"depthClamp",{get:function(){return this._depthClamp},set:function(e){this._depthClamp=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cascadeBlendPercentage",{get:function(){return this._cascadeBlendPercentage},set:function(e){this._cascadeBlendPercentage=e,this._light._markMeshesAsLightDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"lambda",{get:function(){return this._lambda},set:function(e){var n=Math.min(Math.max(e,0),1);this._lambda!=n&&(this._lambda=n,this._breaksAreDirty=!0)},enumerable:!1,configurable:!0}),t.prototype.getCascadeViewMatrix=function(e){return e>=0&&e<this._numCascades?this._viewMatrices[e]:null},t.prototype.getCascadeProjectionMatrix=function(e){return e>=0&&e<this._numCascades?this._projectionMatrices[e]:null},t.prototype.getCascadeTransformMatrix=function(e){return e>=0&&e<this._numCascades?this._transformMatrices[e]:null},t.prototype.setDepthRenderer=function(e){this._depthRenderer=e,this._depthReducer&&this._depthReducer.setDepthRenderer(this._depthRenderer)},Object.defineProperty(t.prototype,"autoCalcDepthBounds",{get:function(){return this._autoCalcDepthBounds},set:function(e){var n=this,i=this._scene.activeCamera;if(i){if(this._autoCalcDepthBounds=e,!e)return this._depthReducer&&this._depthReducer.deactivate(),void this.setMinMaxDistance(0,1);this._depthReducer||(this._depthReducer=new Vu(i),this._depthReducer.onAfterReductionPerformed.add(function(o){var a=o.min,s=o.max;a>=s&&(a=0,s=1),a==n._minDistance&&s==n._maxDistance||n.setMinMaxDistance(a,s)}),this._depthReducer.setDepthRenderer(this._depthRenderer)),this._depthReducer.activate()}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"autoCalcDepthBoundsRefreshRate",{get:function(){var e,n,i;return(i=(n=(e=this._depthReducer)===null||e===void 0?void 0:e.depthRenderer)===null||n===void 0?void 0:n.getDepthMap().refreshRate)!==null&&i!==void 0?i:-1},set:function(e){var n;!((n=this._depthReducer)===null||n===void 0)&&n.depthRenderer&&(this._depthReducer.depthRenderer.getDepthMap().refreshRate=e)},enumerable:!1,configurable:!0}),t.prototype.splitFrustum=function(){this._breaksAreDirty=!0},t.prototype._splitFrustum=function(){var e=this._scene.activeCamera;if(e){for(var n=e.minZ,i=e.maxZ,o=i-n,a=this._minDistance,s=n+a*o,d=n+(this._shadowMaxZ<i&&this._shadowMaxZ>=n?Math.min((this._shadowMaxZ-n)/(i-n),this._maxDistance):this._maxDistance)*o,p=d-s,b=d/s,P=0;P<this._cascades.length;++P){var O=(P+1)/this._numCascades,B=s*Math.pow(b,O),F=s+p*O,z=this._lambda*(B-F)+F;this._cascades[P].prevBreakDistance=P===0?a:this._cascades[P-1].breakDistance,this._cascades[P].breakDistance=(z-n)/o,this._viewSpaceFrustumsZ[P]=n+this._cascades[P].breakDistance*o,this._frustumLengths[P]=(this._cascades[P].breakDistance-this._cascades[P].prevBreakDistance)*o}this._breaksAreDirty=!1}},t.prototype._computeMatrices=function(){if(this._scene.activeCamera){u.e.NormalizeToRef(this._light.getShadowDirection(0),this._lightDirection),Math.abs(u.e.Dot(this._lightDirection,u.e.Up()))===1&&(this._lightDirection.z=1e-13),this._cachedDirection.copyFrom(this._lightDirection);for(var e=0;e<this._numCascades;++e){this._computeFrustumInWorldSpace(e),this._computeCascadeFrustum(e),this._cascadeMaxExtents[e].subtractToRef(this._cascadeMinExtents[e],vn),this._frustumCenter[e].addToRef(this._lightDirection.scale(this._cascadeMinExtents[e].z),this._shadowCameraPos[e]),u.a.LookAtLHToRef(this._shadowCameraPos[e],this._frustumCenter[e],ku,this._viewMatrices[e]);var n=0,i=vn.z,o=this._shadowCastersBoundingInfo;o.update(this._viewMatrices[e]),i=Math.min(i,o.boundingBox.maximumWorld.z),n=this._depthClamp&&this.filter!==Un.FILTER_PCSS?Math.max(n,o.boundingBox.minimumWorld.z):Math.min(n,o.boundingBox.minimumWorld.z),u.a.OrthoOffCenterLHToRef(this._cascadeMinExtents[e].x,this._cascadeMaxExtents[e].x,this._cascadeMinExtents[e].y,this._cascadeMaxExtents[e].y,n,i,this._projectionMatrices[e]),this._cascadeMinExtents[e].z=n,this._cascadeMaxExtents[e].z=i,this._viewMatrices[e].multiplyToRef(this._projectionMatrices[e],this._transformMatrices[e]),u.e.TransformCoordinatesToRef(X_,this._transformMatrices[e],vn),vn.scaleInPlace(this._mapSize/2),Or.copyFromFloats(Math.round(vn.x),Math.round(vn.y),Math.round(vn.z)),Or.subtractInPlace(vn).scaleInPlace(2/this._mapSize),u.a.TranslationToRef(Or.x,Or.y,0,Mr),this._projectionMatrices[e].multiplyToRef(Mr,this._projectionMatrices[e]),this._viewMatrices[e].multiplyToRef(this._projectionMatrices[e],this._transformMatrices[e]),this._transformMatrices[e].copyToArray(this._transformMatricesAsArray,16*e)}}},t.prototype._computeFrustumInWorldSpace=function(e){if(this._scene.activeCamera){var n=this._cascades[e].prevBreakDistance,i=this._cascades[e].breakDistance;this._scene.activeCamera.getViewMatrix();for(var o=u.a.Invert(this._scene.activeCamera.getTransformationMatrix()),a=0;a<t.frustumCornersNDCSpace.length;++a)u.e.TransformCoordinatesToRef(t.frustumCornersNDCSpace[a],o,this._frustumCornersWorldSpace[e][a]);for(a=0;a<t.frustumCornersNDCSpace.length/2;++a)vn.copyFrom(this._frustumCornersWorldSpace[e][a+4]).subtractInPlace(this._frustumCornersWorldSpace[e][a]),Or.copyFrom(vn).scaleInPlace(n),vn.scaleInPlace(i),vn.addInPlace(this._frustumCornersWorldSpace[e][a]),this._frustumCornersWorldSpace[e][a+4].copyFrom(vn),this._frustumCornersWorldSpace[e][a].addInPlace(Or)}},t.prototype._computeCascadeFrustum=function(e){if(this._cascadeMinExtents[e].copyFromFloats(Number.MAX_VALUE,Number.MAX_VALUE,Number.MAX_VALUE),this._cascadeMaxExtents[e].copyFromFloats(Number.MIN_VALUE,Number.MIN_VALUE,Number.MIN_VALUE),this._frustumCenter[e].copyFromFloats(0,0,0),this._scene.activeCamera){for(var n=0;n<this._frustumCornersWorldSpace[e].length;++n)this._frustumCenter[e].addInPlace(this._frustumCornersWorldSpace[e][n]);if(this._frustumCenter[e].scaleInPlace(1/this._frustumCornersWorldSpace[e].length),this.stabilizeCascades){var i=0;for(n=0;n<this._frustumCornersWorldSpace[e].length;++n){var o=this._frustumCornersWorldSpace[e][n].subtractToRef(this._frustumCenter[e],vn).length();i=Math.max(i,o)}i=Math.ceil(16*i)/16,this._cascadeMaxExtents[e].copyFromFloats(i,i,i),this._cascadeMinExtents[e].copyFromFloats(-i,-i,-i)}else{var a=this._frustumCenter[e];for(this._frustumCenter[e].addToRef(this._lightDirection,vn),u.a.LookAtLHToRef(a,vn,ku,Mr),n=0;n<this._frustumCornersWorldSpace[e].length;++n)u.e.TransformCoordinatesToRef(this._frustumCornersWorldSpace[e][n],Mr,vn),this._cascadeMinExtents[e].minimizeInPlace(vn),this._cascadeMaxExtents[e].maximizeInPlace(vn)}}},Object.defineProperty(t,"IsSupported",{get:function(){var e=te.a.LastCreatedEngine;return!!e&&e.webGLVersion!=1},enumerable:!1,configurable:!0}),t.prototype._initializeGenerator=function(){var e,n,i,o,a,s,d,p,b,P,O,B,F,z,J,ie,se,ce,ue,fe;this.penumbraDarkness=(e=this.penumbraDarkness)!==null&&e!==void 0?e:1,this._numCascades=(n=this._numCascades)!==null&&n!==void 0?n:t.DEFAULT_CASCADES_COUNT,this.stabilizeCascades=(i=this.stabilizeCascades)!==null&&i!==void 0&&i,this._freezeShadowCastersBoundingInfoObservable=(o=this._freezeShadowCastersBoundingInfoObservable)!==null&&o!==void 0?o:null,this.freezeShadowCastersBoundingInfo=(a=this.freezeShadowCastersBoundingInfo)!==null&&a!==void 0&&a,this._scbiMin=(s=this._scbiMin)!==null&&s!==void 0?s:new u.e(0,0,0),this._scbiMax=(d=this._scbiMax)!==null&&d!==void 0?d:new u.e(0,0,0),this._shadowCastersBoundingInfo=(p=this._shadowCastersBoundingInfo)!==null&&p!==void 0?p:new Vi.a(new u.e(0,0,0),new u.e(0,0,0)),this._breaksAreDirty=(b=this._breaksAreDirty)===null||b===void 0||b,this._minDistance=(P=this._minDistance)!==null&&P!==void 0?P:0,this._maxDistance=(O=this._maxDistance)!==null&&O!==void 0?O:1,this._currentLayer=(B=this._currentLayer)!==null&&B!==void 0?B:0,this._shadowMaxZ=(J=(F=this._shadowMaxZ)!==null&&F!==void 0?F:(z=this._scene.activeCamera)===null||z===void 0?void 0:z.maxZ)!==null&&J!==void 0?J:1e4,this._debug=(ie=this._debug)!==null&&ie!==void 0&&ie,this._depthClamp=(se=this._depthClamp)===null||se===void 0||se,this._cascadeBlendPercentage=(ce=this._cascadeBlendPercentage)!==null&&ce!==void 0?ce:.1,this._lambda=(ue=this._lambda)!==null&&ue!==void 0?ue:.5,this._autoCalcDepthBounds=(fe=this._autoCalcDepthBounds)!==null&&fe!==void 0&&fe,r.prototype._initializeGenerator.call(this)},t.prototype._createTargetRenderTexture=function(){var e={width:this._mapSize,height:this._mapSize,layers:this.numCascades};this._shadowMap=new sn(this._light.name+"_shadowMap",e,this._scene,!1,!0,this._textureType,!1,void 0,!1,!1,void 0),this._shadowMap.createDepthStencilTexture(h.a.LESS,!0)},t.prototype._initializeShadowMap=function(){var e=this;if(r.prototype._initializeShadowMap.call(this),this._shadowMap!==null){this._transformMatricesAsArray=new Float32Array(16*this._numCascades),this._viewSpaceFrustumsZ=new Array(this._numCascades),this._frustumLengths=new Array(this._numCascades),this._lightSizeUVCorrection=new Array(2*this._numCascades),this._depthCorrection=new Array(this._numCascades),this._cascades=[],this._viewMatrices=[],this._projectionMatrices=[],this._transformMatrices=[],this._cascadeMinExtents=[],this._cascadeMaxExtents=[],this._frustumCenter=[],this._shadowCameraPos=[],this._frustumCornersWorldSpace=[];for(var n=0;n<this._numCascades;++n){this._cascades[n]={prevBreakDistance:0,breakDistance:0},this._viewMatrices[n]=u.a.Zero(),this._projectionMatrices[n]=u.a.Zero(),this._transformMatrices[n]=u.a.Zero(),this._cascadeMinExtents[n]=new u.e,this._cascadeMaxExtents[n]=new u.e,this._frustumCenter[n]=new u.e,this._shadowCameraPos[n]=new u.e,this._frustumCornersWorldSpace[n]=new Array(t.frustumCornersNDCSpace.length);for(var i=0;i<t.frustumCornersNDCSpace.length;++i)this._frustumCornersWorldSpace[n][i]=new u.e}this._shadowMap.onBeforeRenderObservable.add(function(o){if(e._currentLayer=o,e._scene.getSceneUniformBuffer().useUbo){var a=e._scene.getSceneUniformBuffer();a.updateMatrix("viewProjection",e.getCascadeTransformMatrix(o)),a.updateMatrix("view",e.getCascadeViewMatrix(o)),a.update()}}),this._shadowMap.onBeforeBindObservable.add(function(){e._breaksAreDirty&&e._splitFrustum(),e._computeMatrices()}),this._splitFrustum()}},t.prototype._bindCustomEffectForRenderSubMeshForShadowMap=function(e,n,i,o){var a,s,d,p,b,P;n.setMatrix((a=i?.viewProjection)!==null&&a!==void 0?a:"viewProjection",this.getCascadeTransformMatrix(this._currentLayer)),n.setMatrix((s=i?.view)!==null&&s!==void 0?s:"view",this.getCascadeViewMatrix(this._currentLayer)),n.setMatrix((d=i?.projection)!==null&&d!==void 0?d:"projection",this.getCascadeProjectionMatrix(this._currentLayer));var O=o.getWorldMatrix();n.setMatrix((p=i?.world)!==null&&p!==void 0?p:"world",O),O.multiplyToRef(this.getCascadeTransformMatrix(this._currentLayer),Mr),n.setMatrix((b=i?.worldViewProjection)!==null&&b!==void 0?b:"worldViewProjection",Mr),O.multiplyToRef(this.getCascadeViewMatrix(this._currentLayer),Gu),n.setMatrix((P=i?.worldView)!==null&&P!==void 0?P:"worldView",Gu)},t.prototype._isReadyCustomDefines=function(e,n,i){e.push("#define SM_DEPTHCLAMP "+(this._depthClamp&&this._filter!==Un.FILTER_PCSS?"1":"0"))},t.prototype.prepareDefines=function(e,n){r.prototype.prepareDefines.call(this,e,n);var i=this._scene,o=this._light;if(i.shadowsEnabled&&o.shadowEnabled){e["SHADOWCSM"+n]=!0,e["SHADOWCSMDEBUG"+n]=this.debug,e["SHADOWCSMNUM_CASCADES"+n]=this.numCascades,e["SHADOWCSM_RIGHTHANDED"+n]=i.useRightHandedSystem;var a=i.activeCamera;a&&this._shadowMaxZ<a.maxZ&&(e["SHADOWCSMUSESHADOWMAXZ"+n]=!0),this.cascadeBlendPercentage===0&&(e["SHADOWCSMNOBLEND"+n]=!0)}},t.prototype.bindShadowLight=function(e,n){var i=this._light,o=this._scene;if(o.shadowsEnabled&&i.shadowEnabled){var a=o.activeCamera;if(a){var s=this.getShadowMap();if(s){var d=s.getSize().width;if(n.setMatrices("lightMatrix"+e,this._transformMatricesAsArray),n.setArray("viewFrustumZ"+e,this._viewSpaceFrustumsZ),n.setFloat("cascadeBlendFactor"+e,this.cascadeBlendPercentage===0?1e4:1/this.cascadeBlendPercentage),n.setArray("frustumLengths"+e,this._frustumLengths),this._filter===Un.FILTER_PCF)n.setDepthStencilTexture("shadowSampler"+e,s),i._uniformBuffer.updateFloat4("shadowsInfo",this.getDarkness(),d,1/d,this.frustumEdgeFalloff,e);else if(this._filter===Un.FILTER_PCSS){for(var p=0;p<this._numCascades;++p)this._lightSizeUVCorrection[2*p+0]=p===0?1:(this._cascadeMaxExtents[0].x-this._cascadeMinExtents[0].x)/(this._cascadeMaxExtents[p].x-this._cascadeMinExtents[p].x),this._lightSizeUVCorrection[2*p+1]=p===0?1:(this._cascadeMaxExtents[0].y-this._cascadeMinExtents[0].y)/(this._cascadeMaxExtents[p].y-this._cascadeMinExtents[p].y),this._depthCorrection[p]=p===0?1:(this._cascadeMaxExtents[p].z-this._cascadeMinExtents[p].z)/(this._cascadeMaxExtents[0].z-this._cascadeMinExtents[0].z);n.setDepthStencilTexture("shadowSampler"+e,s),n.setTexture("depthSampler"+e,s),n.setArray2("lightSizeUVCorrection"+e,this._lightSizeUVCorrection),n.setArray("depthCorrection"+e,this._depthCorrection),n.setFloat("penumbraDarkness"+e,this.penumbraDarkness),i._uniformBuffer.updateFloat4("shadowsInfo",this.getDarkness(),1/d,this._contactHardeningLightSizeUVRatio*d,this.frustumEdgeFalloff,e)}else n.setTexture("shadowSampler"+e,s),i._uniformBuffer.updateFloat4("shadowsInfo",this.getDarkness(),d,1/d,this.frustumEdgeFalloff,e);i._uniformBuffer.updateFloat2("depthValues",this.getLight().getDepthMinZ(a),this.getLight().getDepthMinZ(a)+this.getLight().getDepthMaxZ(a),e)}}}},t.prototype.getTransformMatrix=function(){return this.getCascadeTransformMatrix(0)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._freezeShadowCastersBoundingInfoObservable&&(this._scene.onBeforeRenderObservable.remove(this._freezeShadowCastersBoundingInfoObservable),this._freezeShadowCastersBoundingInfoObservable=null),this._depthReducer&&(this._depthReducer.dispose(),this._depthReducer=null)},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this),n=this.getShadowMap();if(!n)return e;if(e.numCascades=this._numCascades,e.debug=this._debug,e.stabilizeCascades=this.stabilizeCascades,e.lambda=this._lambda,e.cascadeBlendPercentage=this.cascadeBlendPercentage,e.depthClamp=this._depthClamp,e.autoCalcDepthBounds=this.autoCalcDepthBounds,e.shadowMaxZ=this._shadowMaxZ,e.penumbraDarkness=this.penumbraDarkness,e.freezeShadowCastersBoundingInfo=this._freezeShadowCastersBoundingInfo,e.minDistance=this.minDistance,e.maxDistance=this.maxDistance,e.renderList=[],n.renderList)for(var i=0;i<n.renderList.length;i++){var o=n.renderList[i];e.renderList.push(o.id)}return e},t.Parse=function(e,n){var i=Un.Parse(e,n,function(o,a){return new t(o,a)});return e.numCascades!==void 0&&(i.numCascades=e.numCascades),e.debug!==void 0&&(i.debug=e.debug),e.stabilizeCascades!==void 0&&(i.stabilizeCascades=e.stabilizeCascades),e.lambda!==void 0&&(i.lambda=e.lambda),e.cascadeBlendPercentage!==void 0&&(i.cascadeBlendPercentage=e.cascadeBlendPercentage),e.depthClamp!==void 0&&(i.depthClamp=e.depthClamp),e.autoCalcDepthBounds!==void 0&&(i.autoCalcDepthBounds=e.autoCalcDepthBounds),e.shadowMaxZ!==void 0&&(i.shadowMaxZ=e.shadowMaxZ),e.penumbraDarkness!==void 0&&(i.penumbraDarkness=e.penumbraDarkness),e.freezeShadowCastersBoundingInfo!==void 0&&(i.freezeShadowCastersBoundingInfo=e.freezeShadowCastersBoundingInfo),e.minDistance!==void 0&&e.maxDistance!==void 0&&i.setMinMaxDistance(e.minDistance,e.maxDistance),i},t.frustumCornersNDCSpace=[new u.e(-1,1,-1),new u.e(1,1,-1),new u.e(1,-1,-1),new u.e(-1,-1,-1),new u.e(-1,1,1),new u.e(1,1,1),new u.e(1,-1,1),new u.e(-1,-1,1)],t.CLASSNAME="CascadedShadowGenerator",t.DEFAULT_CASCADES_COUNT=4,t.MIN_CASCADES_COUNT=2,t.MAX_CASCADES_COUNT=4,t._SceneComponentInitialization=function(e){throw An.a.WarnImport("ShadowGeneratorSceneComponent")},t}(Un);U.a.AddParser(at.a.NAME_SHADOWGENERATOR,function(r,t){if(r.shadowGenerators!==void 0&&r.shadowGenerators!==null)for(var e=0,n=r.shadowGenerators.length;e<n;e++){var i=r.shadowGenerators[e];i.className===Ws.CLASSNAME?Ws.Parse(i,t):Un.Parse(i,t)}});var zu=function(){function r(t){this.name=at.a.NAME_SHADOWGENERATOR,this.scene=t}return r.prototype.register=function(){this.scene._gatherRenderTargetsStage.registerStep(at.a.STEP_GATHERRENDERTARGETS_SHADOWGENERATOR,this,this._gatherRenderTargets)},r.prototype.rebuild=function(){},r.prototype.serialize=function(t){t.shadowGenerators=[];for(var e=0,n=this.scene.lights;e<n.length;e++){var i=n[e].getShadowGenerator();i&&t.shadowGenerators.push(i.serialize())}},r.prototype.addFromContainer=function(t){},r.prototype.removeFromContainer=function(t,e){},r.prototype.dispose=function(){},r.prototype._gatherRenderTargets=function(t){var e=this.scene;if(this.scene.shadowsEnabled)for(var n=0;n<e.lights.length;n++){var i=e.lights[n],o=i.getShadowGenerator();if(i.isEnabled()&&i.shadowEnabled&&o){var a=o.getShadowMap();e.textures.indexOf(a)!==-1&&t.push(a)}}},r}();Un._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_SHADOWGENERATOR);t||(t=new zu(r),r._addComponent(t))},Q.a.AddNodeConstructor("Light_Type_0",function(r,t){return function(){return new Xs(r,u.e.Zero(),t)}});var Xs=function(r){function t(e,n,i){var o=r.call(this,e,i)||this;return o._shadowAngle=Math.PI/2,o.position=n,o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"shadowAngle",{get:function(){return this._shadowAngle},set:function(e){this._shadowAngle=e,this.forceProjectionMatrixCompute()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"direction",{get:function(){return this._direction},set:function(e){var n=this.needCube();this._direction=e,this.needCube()!==n&&this._shadowGenerator&&this._shadowGenerator.recreateShadowMap()},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"PointLight"},t.prototype.getTypeID=function(){return Ci.a.LIGHTTYPEID_POINTLIGHT},t.prototype.needCube=function(){return!this.direction},t.prototype.getShadowDirection=function(e){if(this.direction)return r.prototype.getShadowDirection.call(this,e);switch(e){case 0:return new u.e(1,0,0);case 1:return new u.e(-1,0,0);case 2:return new u.e(0,-1,0);case 3:return new u.e(0,1,0);case 4:return new u.e(0,0,1);case 5:return new u.e(0,0,-1)}return u.e.Zero()},t.prototype._setDefaultShadowProjectionMatrix=function(e,n,i){var o=this.getScene().activeCamera;o&&u.a.PerspectiveFovLHToRef(this.shadowAngle,1,this.getDepthMinZ(o),this.getDepthMaxZ(o),e)},t.prototype._buildUniformLayout=function(){this._uniformBuffer.addUniform("vLightData",4),this._uniformBuffer.addUniform("vLightDiffuse",4),this._uniformBuffer.addUniform("vLightSpecular",4),this._uniformBuffer.addUniform("vLightFalloff",4),this._uniformBuffer.addUniform("shadowsInfo",3),this._uniformBuffer.addUniform("depthValues",2),this._uniformBuffer.create()},t.prototype.transferToEffect=function(e,n){return this.computeTransformedInformation()?this._uniformBuffer.updateFloat4("vLightData",this.transformedPosition.x,this.transformedPosition.y,this.transformedPosition.z,0,n):this._uniformBuffer.updateFloat4("vLightData",this.position.x,this.position.y,this.position.z,0,n),this._uniformBuffer.updateFloat4("vLightFalloff",this.range,this._inverseSquaredRange,0,0,n),this},t.prototype.transferToNodeMaterialEffect=function(e,n){return this.computeTransformedInformation()?e.setFloat3(n,this.transformedPosition.x,this.transformedPosition.y,this.transformedPosition.z):e.setFloat3(n,this.position.x,this.position.y,this.position.z),this},t.prototype.prepareLightSpecificDefines=function(e,n){e["POINTLIGHT"+n]=!0},Object(c.c)([Object(L.c)()],t.prototype,"shadowAngle",null),t}(qo),ju=function(){function r(t,e,n){var i=this;e===void 0&&(e=""),n===void 0&&(n="black"),this._renderingCanvas=t,this._loadingText=e,this._loadingDivBackgroundColor=n,this._resizeLoadingUI=function(){var o=i._renderingCanvas.getBoundingClientRect(),a=window.getComputedStyle(i._renderingCanvas).position;i._loadingDiv&&(i._loadingDiv.style.position=a==="fixed"?"fixed":"absolute",i._loadingDiv.style.left=o.left+"px",i._loadingDiv.style.top=o.top+"px",i._loadingDiv.style.width=o.width+"px",i._loadingDiv.style.height=o.height+"px")}}return r.prototype.displayLoadingUI=function(){if(!this._loadingDiv){this._loadingDiv=document.createElement("div"),this._loadingDiv.id="babylonjsLoadingDiv",this._loadingDiv.style.opacity="0",this._loadingDiv.style.transition="opacity 1.5s ease",this._loadingDiv.style.pointerEvents="none",this._loadingDiv.style.display="grid",this._loadingDiv.style.gridTemplateRows="100%",this._loadingDiv.style.gridTemplateColumns="100%",this._loadingDiv.style.justifyItems="center",this._loadingDiv.style.alignItems="center",this._loadingTextDiv=document.createElement("div"),this._loadingTextDiv.style.position="absolute",this._loadingTextDiv.style.left="0",this._loadingTextDiv.style.top="50%",this._loadingTextDiv.style.marginTop="80px",this._loadingTextDiv.style.width="100%",this._loadingTextDiv.style.height="20px",this._loadingTextDiv.style.fontFamily="Arial",this._loadingTextDiv.style.fontSize="14px",this._loadingTextDiv.style.color="white",this._loadingTextDiv.style.textAlign="center",this._loadingTextDiv.style.zIndex="1",this._loadingTextDiv.innerHTML="Loading",this._loadingDiv.appendChild(this._loadingTextDiv),this._loadingTextDiv.innerHTML=this._loadingText;var t=document.createElement("style");t.type="text/css",t.innerHTML=`@-webkit-keyframes spin1 {                    0% { -webkit-transform: rotate(0deg);}
-                    100% { -webkit-transform: rotate(360deg);}
-                }                @keyframes spin1 {                    0% { transform: rotate(0deg);}
-                    100% { transform: rotate(360deg);}
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"+a.w/2+"vh)",n.style.top="calc(50% - "+a.h/2+"vh)",o.style.width=s.w+"vh",o.style.height=s.h+"vh",o.style.left="calc(50% - "+s.w/2+"vh)",o.style.top="calc(50% - "+s.h/2+"vh)"}i.appendChild(o),this._loadingDiv.appendChild(n),this._loadingDiv.appendChild(i),this._resizeLoadingUI(),window.addEventListener("resize",this._resizeLoadingUI),this._loadingDiv.style.backgroundColor=this._loadingDivBackgroundColor,document.body.appendChild(this._loadingDiv),this._loadingDiv.style.opacity="1"}},r.prototype.hideLoadingUI=function(){var t=this;this._loadingDiv&&(this._loadingDiv.style.opacity="0",this._loadingDiv.addEventListener("transitionend",function(){t._loadingDiv&&(t._loadingDiv.parentElement&&t._loadingDiv.parentElement.removeChild(t._loadingDiv),window.removeEventListener("resize",t._resizeLoadingUI),t._loadingDiv=null)}))},Object.defineProperty(r.prototype,"loadingUIText",{get:function(){return this._loadingText},set:function(t){this._loadingText=t,this._loadingTextDiv&&(this._loadingTextDiv.innerHTML=this._loadingText)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"loadingUIBackgroundColor",{get:function(){return this._loadingDivBackgroundColor},set:function(t){this._loadingDivBackgroundColor=t,this._loadingDiv&&(this._loadingDiv.style.backgroundColor=this._loadingDivBackgroundColor)},enumerable:!1,configurable:!0}),r.DefaultLogoUrl="",r.DefaultSpinnerUrl="",r}();Ue.a.DefaultLoadingScreenFactory=function(r){return new ju(r)};var Ys=f(71),rr=f(68),Ks=function(){function r(){}return r.ConvertPanoramaToCubemap=function(t,e,n,i){if(!t)throw"ConvertPanoramaToCubemap: input cannot be null";if(t.length!=e*n*3)throw"ConvertPanoramaToCubemap: input size is wrong";return{front:this.CreateCubemapTexture(i,this.FACE_FRONT,t,e,n),back:this.CreateCubemapTexture(i,this.FACE_BACK,t,e,n),left:this.CreateCubemapTexture(i,this.FACE_LEFT,t,e,n),right:this.CreateCubemapTexture(i,this.FACE_RIGHT,t,e,n),up:this.CreateCubemapTexture(i,this.FACE_UP,t,e,n),down:this.CreateCubemapTexture(i,this.FACE_DOWN,t,e,n),size:i,type:h.a.TEXTURETYPE_FLOAT,format:h.a.TEXTUREFORMAT_RGB,gammaSpace:!1}},r.CreateCubemapTexture=function(t,e,n,i,o){for(var a=new ArrayBuffer(t*t*4*3),s=new Float32Array(a),d=e[1].subtract(e[0]).scale(1/t),p=e[3].subtract(e[2]).scale(1/t),b=1/t,P=0,O=0;O<t;O++){for(var B=e[0],F=e[2],z=0;z<t;z++){var J=F.subtract(B).scale(P).add(B);J.normalize();var ie=this.CalcProjectionSpherical(J,n,i,o);s[O*t*3+3*z+0]=ie.r,s[O*t*3+3*z+1]=ie.g,s[O*t*3+3*z+2]=ie.b,B=B.add(d),F=F.add(p)}P+=b}return s},r.CalcProjectionSpherical=function(t,e,n,i){for(var o=Math.atan2(t.z,t.x),a=Math.acos(t.y);o<-Math.PI;)o+=2*Math.PI;for(;o>Math.PI;)o-=2*Math.PI;var s=o/Math.PI,d=a/Math.PI;s=.5*s+.5;var p=Math.round(s*n);p<0?p=0:p>=n&&(p=n-1);var b=Math.round(d*i);b<0?b=0:b>=i&&(b=i-1);var P=i-b-1;return{r:e[P*n*3+3*p+0],g:e[P*n*3+3*p+1],b:e[P*n*3+3*p+2]}},r.FACE_LEFT=[new u.e(-1,-1,-1),new u.e(1,-1,-1),new u.e(-1,1,-1),new u.e(1,1,-1)],r.FACE_RIGHT=[new u.e(1,-1,1),new u.e(-1,-1,1),new u.e(1,1,1),new u.e(-1,1,1)],r.FACE_FRONT=[new u.e(1,-1,-1),new u.e(1,-1,1),new u.e(1,1,-1),new u.e(1,1,1)],r.FACE_BACK=[new u.e(-1,-1,1),new u.e(-1,-1,-1),new u.e(-1,1,1),new u.e(-1,1,-1)],r.FACE_DOWN=[new u.e(1,1,-1),new u.e(1,1,1),new u.e(-1,1,-1),new u.e(-1,1,1)],r.FACE_UP=[new u.e(-1,-1,-1),new u.e(-1,-1,1),new u.e(1,-1,-1),new u.e(1,-1,1)],r}(),Hu=function(){function r(){}return r.Ldexp=function(t,e){return e>1023?t*Math.pow(2,1023)*Math.pow(2,e-1023):e<-1074?t*Math.pow(2,-1074)*Math.pow(2,e+1074):t*Math.pow(2,e)},r.Rgbe2float=function(t,e,n,i,o,a){o>0?(o=this.Ldexp(1,o-136),t[a+0]=e*o,t[a+1]=n*o,t[a+2]=i*o):(t[a+0]=0,t[a+1]=0,t[a+2]=0)},r.readStringLine=function(t,e){for(var n="",i="",o=e;o<t.length-e&&(i=String.fromCharCode(t[o]))!=`
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-`):"";t.useShaderStore?(e.fragment=e.fragmentSource,e.vertex||(e.vertex=e.vertexSource),delete e.fragmentSource,delete e.vertexSource,this.effect=t.engine.createEffect(e.spectorName,t.attributeNames||["position"],i,t.samplerNames,o,void 0,t.onCompiled)):this.effect=new ze.a(e,t.attributeNames||["position"],i,t.samplerNames,t.engine,o,void 0,t.onCompiled)}return r.prototype.dispose=function(){this.effect.dispose()},r}(),Y_=`
-attribute vec2 position;
-
-varying vec3 direction;
-
-uniform vec3 up;
-uniform vec3 right;
-uniform vec3 front;
-void main(void) {
-mat3 view=mat3(up,right,front);
-direction=view*vec3(position,1.0);
-gl_Position=vec4(position,0.0,1.0);
-}`;ze.a.ShadersStore.hdrFilteringVertexShader=Y_;var K_=`#include<helperFunctions>
-#include<importanceSampling>
-#include<pbrBRDFFunctions>
-#include<hdrFilteringFunctions>
-uniform float alphaG;
-uniform samplerCube inputTexture;
-uniform vec2 vFilteringInfo;
-uniform float hdrScale;
-varying vec3 direction;
-void main() {
-vec3 color=radiance(alphaG,inputTexture,direction,vFilteringInfo);
-gl_FragColor=vec4(color*hdrScale,1.0);
-}`;ze.a.ShadersStore.hdrFilteringPixelShader=K_;var Yu=function(){function r(t,e){e===void 0&&(e={}),this._lodGenerationOffset=0,this._lodGenerationScale=.8,this.quality=h.a.TEXTURE_FILTERING_QUALITY_OFFLINE,this.hdrScale=1,this._engine=t,this.hdrScale=e.hdrScale||this.hdrScale,this.quality=e.hdrScale||this.quality}return r.prototype._createRenderTarget=function(t){var e=h.a.TEXTURETYPE_UNSIGNED_BYTE;this._engine.getCaps().textureHalfFloatRender?e=h.a.TEXTURETYPE_HALF_FLOAT:this._engine.getCaps().textureFloatRender&&(e=h.a.TEXTURETYPE_FLOAT);var n=this._engine.createRenderTargetCubeTexture(t,{format:h.a.TEXTUREFORMAT_RGBA,type:e,generateMipMaps:!1,generateDepthBuffer:!1,generateStencilBuffer:!1,samplingMode:h.a.TEXTURE_NEAREST_SAMPLINGMODE});return this._engine.updateTextureWrappingMode(n,h.a.TEXTURE_CLAMP_ADDRESSMODE,h.a.TEXTURE_CLAMP_ADDRESSMODE,h.a.TEXTURE_CLAMP_ADDRESSMODE),this._engine.updateTextureSamplingMode(h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,n,!0),n},r.prototype._prefilterInternal=function(t){var e=t.getSize().width,n=Math.round($.a.Log2(e))+1,i=this._effectWrapper.effect,o=this._createRenderTarget(e);this._effectRenderer.setViewport();var a=t.getInternalTexture();a&&this._engine.updateTextureSamplingMode(h.a.TEXTURE_TRILINEAR_SAMPLINGMODE,a,!0),this._effectRenderer.applyEffectWrapper(this._effectWrapper);var s=[[new u.e(0,0,-1),new u.e(0,-1,0),new u.e(1,0,0)],[new u.e(0,0,1),new u.e(0,-1,0),new u.e(-1,0,0)],[new u.e(1,0,0),new u.e(0,0,1),new u.e(0,1,0)],[new u.e(1,0,0),new u.e(0,0,-1),new u.e(0,-1,0)],[new u.e(1,0,0),new u.e(0,-1,0),new u.e(0,0,1)],[new u.e(-1,0,0),new u.e(0,-1,0),new u.e(0,0,-1)]];i.setFloat("hdrScale",this.hdrScale),i.setFloat2("vFilteringInfo",t.getSize().width,n),i.setTexture("inputTexture",t);for(var d=0;d<6;d++){i.setVector3("up",s[d][0]),i.setVector3("right",s[d][1]),i.setVector3("front",s[d][2]);for(var p=0;p<n;p++){this._engine.bindFramebuffer(o,d,void 0,void 0,!0,p),this._effectRenderer.applyEffectWrapper(this._effectWrapper);var b=Math.pow(2,(p-this._lodGenerationOffset)/this._lodGenerationScale)/e;p===0&&(b=0),i.setFloat("alphaG",b),this._effectRenderer.draw()}}return this._effectRenderer.restoreStates(),this._engine.restoreDefaultFramebuffer(),this._engine._releaseFramebufferObjects(o),this._engine._releaseTexture(t._texture),o._swapAndDie(t._texture),t._prefiltered=!0,t},r.prototype._createEffect=function(t,e){var n=[];return t.gammaSpace&&n.push("#define GAMMA_INPUT"),n.push("#define NUM_SAMPLES "+this.quality+"u"),new Xu({engine:this._engine,name:"hdrFiltering",vertexShader:"hdrFiltering",fragmentShader:"hdrFiltering",samplerNames:["inputTexture"],uniformNames:["vSampleDirections","vWeights","up","right","front","vFilteringInfo","hdrScale","alphaG"],useShaderStore:!0,defines:n,onCompiled:e})},r.prototype.isReady=function(t){return t.isReady()&&this._effectWrapper.effect.isReady()},r.prototype.prefilter=function(t,e){var n=this;if(e===void 0&&(e=null),this._engine.webGLVersion!==1)return new Promise(function(i){n._effectRenderer=new Wu(n._engine),n._effectWrapper=n._createEffect(t),n._effectWrapper.effect.executeWhenCompiled(function(){n._prefilterInternal(t),n._effectRenderer.dispose(),n._effectWrapper.dispose(),i(),e&&e()})});l.a.Warn("HDR prefiltering is not available in WebGL 1., you can use real time filtering instead.")},r}(),aa=function(r){function t(e,n,i,o,a,s,d,p,b){var P;o===void 0&&(o=!1),a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=!1),p===void 0&&(p=null),b===void 0&&(b=null);var O=r.call(this,n)||this;return O._generateHarmonics=!0,O._onLoad=null,O._onError=null,O._isBlocking=!0,O._rotationY=0,O.boundingBoxPosition=u.e.Zero(),e&&(O._coordinatesMode=we.a.CUBIC_MODE,O.name=e,O.url=e,O.hasAlpha=!1,O.isCube=!0,O._textureMatrix=u.a.Identity(),O._prefilterOnLoad=d,O._onLoad=p,O._onError=b,O.gammaSpace=s,O._noMipmap=o,O._size=i,O._generateHarmonics=a,O._texture=O._getFromCache(e,O._noMipmap),O._texture?p&&(O._texture.isReady?Xe.b.SetImmediate(function(){return p()}):O._texture.onLoadedObservable.add(p)):!((P=O.getScene())===null||P===void 0)&&P.useDelayedTextureLoading?O.delayLoadState=h.a.DELAYLOADSTATE_NOTLOADED:O.loadTexture()),O}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"isBlocking",{get:function(){return this._isBlocking},set:function(e){this._isBlocking=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rotationY",{get:function(){return this._rotationY},set:function(e){this._rotationY=e,this.setReflectionTextureMatrix(u.a.RotationY(this._rotationY))},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"boundingBoxSize",{get:function(){return this._boundingBoxSize},set:function(e){if(!this._boundingBoxSize||!this._boundingBoxSize.equals(e)){this._boundingBoxSize=e;var n=this.getScene();n&&n.markAllMaterialsAsDirty(h.a.MATERIAL_TextureDirtyFlag)}},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"HDRCubeTexture"},t.prototype.loadTexture=function(){var e=this,n=this._getEngine();if(this._getEngine().webGLVersion>=2&&this._prefilterOnLoad){var i=this._onLoad,o=new Yu(n);this._onLoad=function(){o.prefilter(e,i)}}this._texture=n.createRawCubeTextureFromUrl(this.url,this.getScene(),this._size,h.a.TEXTUREFORMAT_RGB,n.getCaps().textureFloat?h.a.TEXTURETYPE_FLOAT:h.a.TEXTURETYPE_UNSIGNED_INT,this._noMipmap,function(a){e.lodGenerationOffset=0,e.lodGenerationScale=.8;var s=Hu.GetCubeMapTextureData(a,e._size);if(e._generateHarmonics){var d=jo.ConvertCubeMapToSphericalPolynomial(s);e.sphericalPolynomial=d}for(var p=[],b=null,P=0;P<6;P++){if(!n.getCaps().textureFloat){var O=new ArrayBuffer(e._size*e._size*3);b=new Uint8Array(O)}var B=s[t._facesMapping[P]];if(e.gammaSpace||b){for(var F=0;F<e._size*e._size;F++)if(e.gammaSpace&&(B[3*F+0]=Math.pow(B[3*F+0],Gt.b),B[3*F+1]=Math.pow(B[3*F+1],Gt.b),B[3*F+2]=Math.pow(B[3*F+2],Gt.b)),b){var z=Math.max(255*B[3*F+0],0),J=Math.max(255*B[3*F+1],0),ie=Math.max(255*B[3*F+2],0),se=Math.max(Math.max(z,J),ie);if(se>255){var ce=255/se;z*=ce,J*=ce,ie*=ce}b[3*F+0]=z,b[3*F+1]=J,b[3*F+2]=ie}}b?p.push(b):p.push(B)}return p},null,this._onLoad,this._onError)},t.prototype.clone=function(){var e=new t(this.url,this.getScene()||this._getEngine(),this._size,this._noMipmap,this._generateHarmonics,this.gammaSpace);return e.level=this.level,e.wrapU=this.wrapU,e.wrapV=this.wrapV,e.coordinatesIndex=this.coordinatesIndex,e.coordinatesMode=this.coordinatesMode,e},t.prototype.delayLoad=function(){this.delayLoadState===h.a.DELAYLOADSTATE_NOTLOADED&&(this.delayLoadState=h.a.DELAYLOADSTATE_LOADED,this._texture=this._getFromCache(this.url,this._noMipmap),this._texture||this.loadTexture())},t.prototype.getReflectionTextureMatrix=function(){return this._textureMatrix},t.prototype.setReflectionTextureMatrix=function(e){var n,i=this;this._textureMatrix=e,e.updateFlag!==this._textureMatrix.updateFlag&&e.isIdentity()!==this._textureMatrix.isIdentity()&&((n=this.getScene())===null||n===void 0||n.markAllMaterialsAsDirty(h.a.MATERIAL_TextureDirtyFlag,function(o){return o.getActiveTextures().indexOf(i)!==-1}))},t.Parse=function(e,n,i){var o=null;return e.name&&!e.isRenderTarget&&((o=new t(i+e.name,n,e.size,e.noMipmap,e.generateHarmonics,e.useInGammaSpace)).name=e.name,o.hasAlpha=e.hasAlpha,o.level=e.level,o.coordinatesMode=e.coordinatesMode,o.isBlocking=e.isBlocking),o&&(e.boundingBoxPosition&&(o.boundingBoxPosition=u.e.FromArray(e.boundingBoxPosition)),e.boundingBoxSize&&(o.boundingBoxSize=u.e.FromArray(e.boundingBoxSize)),e.rotationY&&(o.rotationY=e.rotationY)),o},t.prototype.serialize=function(){if(!this.name)return null;var e={};return e.name=this.name,e.hasAlpha=this.hasAlpha,e.isCube=!0,e.level=this.level,e.size=this._size,e.coordinatesMode=this.coordinatesMode,e.useInGammaSpace=this.gammaSpace,e.generateHarmonics=this._generateHarmonics,e.customType="BABYLON.HDRCubeTexture",e.noMipmap=this._noMipmap,e.isBlocking=this._isBlocking,e.rotationY=this._rotationY,e},t._facesMapping=["right","left","up","down","front","back"],t}(zn.a);R.a.RegisteredTypes["BABYLON.HDRCubeTexture"]=aa;var Ku=function(){function r(t,e,n){e===void 0&&(e=0),n===void 0&&(n=null),this.name=t,this.animations=new Array,this._positions=null,this._normals=null,this._tangents=null,this._uvs=null,this._uniqueId=0,this.onInfluenceChanged=new C.c,this._onDataLayoutChanged=new C.c,this._animationPropertiesOverride=null,this._scene=n||te.a.LastCreatedScene,this.influence=e,this._scene&&(this._uniqueId=this._scene.getUniqueId())}return Object.defineProperty(r.prototype,"influence",{get:function(){return this._influence},set:function(t){if(this._influence!==t){var e=this._influence;this._influence=t,this.onInfluenceChanged.hasObservers()&&this.onInfluenceChanged.notifyObservers(e===0||t===0)}},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"animationPropertiesOverride",{get:function(){return!this._animationPropertiesOverride&&this._scene?this._scene.animationPropertiesOverride:this._animationPropertiesOverride},set:function(t){this._animationPropertiesOverride=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"uniqueId",{get:function(){return this._uniqueId},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hasPositions",{get:function(){return!!this._positions},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hasNormals",{get:function(){return!!this._normals},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hasTangents",{get:function(){return!!this._tangents},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hasUVs",{get:function(){return!!this._uvs},enumerable:!1,configurable:!0}),r.prototype.setPositions=function(t){var e=this.hasPositions;this._positions=t,e!==this.hasPositions&&this._onDataLayoutChanged.notifyObservers(void 0)},r.prototype.getPositions=function(){return this._positions},r.prototype.setNormals=function(t){var e=this.hasNormals;this._normals=t,e!==this.hasNormals&&this._onDataLayoutChanged.notifyObservers(void 0)},r.prototype.getNormals=function(){return this._normals},r.prototype.setTangents=function(t){var e=this.hasTangents;this._tangents=t,e!==this.hasTangents&&this._onDataLayoutChanged.notifyObservers(void 0)},r.prototype.getTangents=function(){return this._tangents},r.prototype.setUVs=function(t){var e=this.hasUVs;this._uvs=t,e!==this.hasUVs&&this._onDataLayoutChanged.notifyObservers(void 0)},r.prototype.getUVs=function(){return this._uvs},r.prototype.clone=function(){var t=this,e=L.a.Clone(function(){return new r(t.name,t.influence,t._scene)},this);return e._positions=this._positions,e._normals=this._normals,e._tangents=this._tangents,e._uvs=this._uvs,e},r.prototype.serialize=function(){var t={};return t.name=this.name,t.influence=this.influence,t.positions=Array.prototype.slice.call(this.getPositions()),this.id!=null&&(t.id=this.id),this.hasNormals&&(t.normals=Array.prototype.slice.call(this.getNormals())),this.hasTangents&&(t.tangents=Array.prototype.slice.call(this.getTangents())),this.hasUVs&&(t.uvs=Array.prototype.slice.call(this.getUVs())),L.a.AppendSerializedAnimations(this,t),t},r.prototype.getClassName=function(){return"MorphTarget"},r.Parse=function(t){var e=new r(t.name,t.influence);if(e.setPositions(t.positions),t.id!=null&&(e.id=t.id),t.normals&&e.setNormals(t.normals),t.tangents&&e.setTangents(t.tangents),t.uvs&&e.setUVs(t.uvs),t.animations)for(var n=0;n<t.animations.length;n++){var i=t.animations[n],o=R.a.GetClass("BABYLON.Animation");o&&e.animations.push(o.Parse(i))}return e},r.FromMesh=function(t,e,n){e||(e=t.name);var i=new r(e,n,t.getScene());return i.setPositions(t.getVerticesData(Oe.b.PositionKind)),t.isVerticesDataPresent(Oe.b.NormalKind)&&i.setNormals(t.getVerticesData(Oe.b.NormalKind)),t.isVerticesDataPresent(Oe.b.TangentKind)&&i.setTangents(t.getVerticesData(Oe.b.TangentKind)),t.isVerticesDataPresent(Oe.b.UVKind)&&i.setUVs(t.getVerticesData(Oe.b.UVKind)),i},Object(c.c)([Object(L.c)()],r.prototype,"id",void 0),r}(),sa=function(){function r(t){t===void 0&&(t=null),this._targets=new Array,this._targetInfluenceChangedObservers=new Array,this._targetDataLayoutChangedObservers=new Array,this._activeTargets=new fi.a(16),this._supportsNormals=!1,this._supportsTangents=!1,this._supportsUVs=!1,this._vertexCount=0,this._uniqueId=0,this._tempInfluences=new Array,this.enableNormalMorphing=!0,this.enableTangentMorphing=!0,this.enableUVMorphing=!0,t||(t=te.a.LastCreatedScene),this._scene=t,this._scene&&(this._scene.morphTargetManagers.push(this),this._uniqueId=this._scene.getUniqueId())}return Object.defineProperty(r.prototype,"uniqueId",{get:function(){return this._uniqueId},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"vertexCount",{get:function(){return this._vertexCount},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"supportsNormals",{get:function(){return this._supportsNormals&&this.enableNormalMorphing},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"supportsTangents",{get:function(){return this._supportsTangents&&this.enableTangentMorphing},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"supportsUVs",{get:function(){return this._supportsUVs&&this.enableUVMorphing},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"numTargets",{get:function(){return this._targets.length},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"numInfluencers",{get:function(){return this._activeTargets.length},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"influences",{get:function(){return this._influences},enumerable:!1,configurable:!0}),r.prototype.getActiveTarget=function(t){return this._activeTargets.data[t]},r.prototype.getTarget=function(t){return this._targets[t]},r.prototype.addTarget=function(t){var e=this;this._targets.push(t),this._targetInfluenceChangedObservers.push(t.onInfluenceChanged.add(function(n){e._syncActiveTargets(n)})),this._targetDataLayoutChangedObservers.push(t._onDataLayoutChanged.add(function(){e._syncActiveTargets(!0)})),this._syncActiveTargets(!0)},r.prototype.removeTarget=function(t){var e=this._targets.indexOf(t);e>=0&&(this._targets.splice(e,1),t.onInfluenceChanged.remove(this._targetInfluenceChangedObservers.splice(e,1)[0]),t._onDataLayoutChanged.remove(this._targetDataLayoutChangedObservers.splice(e,1)[0]),this._syncActiveTargets(!0))},r.prototype.clone=function(){for(var t=new r(this._scene),e=0,n=this._targets;e<n.length;e++){var i=n[e];t.addTarget(i.clone())}return t.enableNormalMorphing=this.enableNormalMorphing,t.enableTangentMorphing=this.enableTangentMorphing,t.enableUVMorphing=this.enableUVMorphing,t},r.prototype.serialize=function(){var t={};t.id=this.uniqueId,t.targets=[];for(var e=0,n=this._targets;e<n.length;e++){var i=n[e];t.targets.push(i.serialize())}return t},r.prototype._syncActiveTargets=function(t){var e=0;this._activeTargets.reset(),this._supportsNormals=!0,this._supportsTangents=!0,this._supportsUVs=!0,this._vertexCount=0;for(var n=0,i=this._targets;n<i.length;n++){var o=i[n];if(o.influence!==0){this._activeTargets.push(o),this._tempInfluences[e++]=o.influence,this._supportsNormals=this._supportsNormals&&o.hasNormals,this._supportsTangents=this._supportsTangents&&o.hasTangents,this._supportsUVs=this._supportsUVs&&o.hasUVs;var a=o.getPositions();if(a){var s=a.length/3;if(this._vertexCount===0)this._vertexCount=s;else if(this._vertexCount!==s)return void l.a.Error("Incompatible target. Targets must all have the same vertices count.")}}}this._influences&&this._influences.length===e||(this._influences=new Float32Array(e));for(var d=0;d<e;d++)this._influences[d]=this._tempInfluences[d];t&&this.synchronize()},r.prototype.synchronize=function(){if(this._scene)for(var t=0,e=this._scene.meshes;t<e.length;t++){var n=e[t];n.morphTargetManager===this&&n._syncGeometryWithMorphTargetManager()}},r.Parse=function(t,e){var n=new r(e);n._uniqueId=t.id;for(var i=0,o=t.targets;i<o.length;i++){var a=o[i];n.addTarget(Ku.Parse(a))}return n},r}(),xt=f(32),en=f(50),Ir=function(){function r(t,e){if(e===void 0&&(e=r.DefaultPluginFactory()),this._physicsPlugin=e,this._impostors=[],this._joints=[],this._subTimeStep=0,!this._physicsPlugin.isSupported())throw new Error("Physics Engine "+this._physicsPlugin.name+" cannot be found. Please make sure it is included.");t=t||new u.e(0,-9.807,0),this.setGravity(t),this.setTimeStep()}return r.DefaultPluginFactory=function(){throw An.a.WarnImport("CannonJSPlugin")},r.prototype.setGravity=function(t){this.gravity=t,this._physicsPlugin.setGravity(this.gravity)},r.prototype.setTimeStep=function(t){t===void 0&&(t=1/60),this._physicsPlugin.setTimeStep(t)},r.prototype.getTimeStep=function(){return this._physicsPlugin.getTimeStep()},r.prototype.setSubTimeStep=function(t){t===void 0&&(t=0),this._subTimeStep=t},r.prototype.getSubTimeStep=function(){return this._subTimeStep},r.prototype.dispose=function(){this._impostors.forEach(function(t){t.dispose()}),this._physicsPlugin.dispose()},r.prototype.getPhysicsPluginName=function(){return this._physicsPlugin.name},r.prototype.addImpostor=function(t){t.uniqueId=this._impostors.push(t),t.parent||this._physicsPlugin.generatePhysicsBody(t)},r.prototype.removeImpostor=function(t){var e=this._impostors.indexOf(t);e>-1&&this._impostors.splice(e,1).length&&this.getPhysicsPlugin().removePhysicsBody(t)},r.prototype.addJoint=function(t,e,n){var i={mainImpostor:t,connectedImpostor:e,joint:n};n.physicsPlugin=this._physicsPlugin,this._joints.push(i),this._physicsPlugin.generateJoint(i)},r.prototype.removeJoint=function(t,e,n){var i=this._joints.filter(function(o){return o.connectedImpostor===e&&o.joint===n&&o.mainImpostor===t});i.length&&this._physicsPlugin.removeJoint(i[0])},r.prototype._step=function(t){var e=this;this._impostors.forEach(function(n){n.isBodyInitRequired()&&e._physicsPlugin.generatePhysicsBody(n)}),t>.1?t=.1:t<=0&&(t=1/60),this._physicsPlugin.executeStep(t,this._impostors)},r.prototype.getPhysicsPlugin=function(){return this._physicsPlugin},r.prototype.getImpostors=function(){return this._impostors},r.prototype.getImpostorForPhysicsObject=function(t){for(var e=0;e<this._impostors.length;++e)if(this._impostors[e].object===t)return this._impostors[e];return null},r.prototype.getImpostorWithPhysicsBody=function(t){for(var e=0;e<this._impostors.length;++e)if(this._impostors[e].physicsBody===t)return this._impostors[e];return null},r.prototype.raycast=function(t,e){return this._physicsPlugin.raycast(t,e)},r.Epsilon=.001,r}(),Qs=function(){function r(){this._hasHit=!1,this._hitDistance=0,this._hitNormalWorld=u.e.Zero(),this._hitPointWorld=u.e.Zero(),this._rayFromWorld=u.e.Zero(),this._rayToWorld=u.e.Zero()}return Object.defineProperty(r.prototype,"hasHit",{get:function(){return this._hasHit},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hitDistance",{get:function(){return this._hitDistance},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hitNormalWorld",{get:function(){return this._hitNormalWorld},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hitPointWorld",{get:function(){return this._hitPointWorld},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rayFromWorld",{get:function(){return this._rayFromWorld},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rayToWorld",{get:function(){return this._rayToWorld},enumerable:!1,configurable:!0}),r.prototype.setHitData=function(t,e){this._hasHit=!0,this._hitNormalWorld=new u.e(t.x,t.y,t.z),this._hitPointWorld=new u.e(e.x,e.y,e.z)},r.prototype.setHitDistance=function(t){this._hitDistance=t},r.prototype.calculateHitDistance=function(){this._hitDistance=u.e.Distance(this._rayFromWorld,this._hitPointWorld)},r.prototype.reset=function(t,e){t===void 0&&(t=u.e.Zero()),e===void 0&&(e=u.e.Zero()),this._rayFromWorld=t,this._rayToWorld=e,this._hasHit=!1,this._hitDistance=0,this._hitNormalWorld=u.e.Zero(),this._hitPointWorld=u.e.Zero()},r}(),qs=function(){function r(t,e,n){t===void 0&&(t=!0),e===void 0&&(e=10),n===void 0&&(n=CANNON),this._useDeltaForWorldStep=t,this.name="CannonJSPlugin",this._physicsMaterials=new Array,this._fixedTimeStep=1/60,this._physicsBodysToRemoveAfterStep=new Array,this._firstFrame=!0,this._minus90X=new u.b(-.7071067811865475,0,0,.7071067811865475),this._plus90X=new u.b(.7071067811865475,0,0,.7071067811865475),this._tmpPosition=u.e.Zero(),this._tmpDeltaPosition=u.e.Zero(),this._tmpUnityRotation=new u.b,this.BJSCANNON=n,this.isSupported()?(this._extendNamespace(),this.world=new this.BJSCANNON.World,this.world.broadphase=new this.BJSCANNON.NaiveBroadphase,this.world.solver.iterations=e,this._cannonRaycastResult=new this.BJSCANNON.RaycastResult,this._raycastResult=new Qs):l.a.Error("CannonJS is not available. Please make sure you included the js file.")}return r.prototype.setGravity=function(t){var e=t;this.world.gravity.set(e.x,e.y,e.z)},r.prototype.setTimeStep=function(t){this._fixedTimeStep=t},r.prototype.getTimeStep=function(){return this._fixedTimeStep},r.prototype.executeStep=function(t,e){if(this._firstFrame){this._firstFrame=!1;for(var n=0,i=e;n<i.length;n++){var o=i[n];o.type!=xt.a.HeightmapImpostor&&o.type!==xt.a.PlaneImpostor&&o.beforeStep()}}this.world.step(this._useDeltaForWorldStep?t:this._fixedTimeStep),this._removeMarkedPhysicsBodiesFromWorld()},r.prototype._removeMarkedPhysicsBodiesFromWorld=function(){var t=this;this._physicsBodysToRemoveAfterStep.length>0&&(this._physicsBodysToRemoveAfterStep.forEach(function(e){t.world.remove(e)}),this._physicsBodysToRemoveAfterStep=[])},r.prototype.applyImpulse=function(t,e,n){var i=new this.BJSCANNON.Vec3(n.x,n.y,n.z),o=new this.BJSCANNON.Vec3(e.x,e.y,e.z);t.physicsBody.applyImpulse(o,i)},r.prototype.applyForce=function(t,e,n){var i=new this.BJSCANNON.Vec3(n.x,n.y,n.z),o=new this.BJSCANNON.Vec3(e.x,e.y,e.z);t.physicsBody.applyForce(o,i)},r.prototype.generatePhysicsBody=function(t){if(this._removeMarkedPhysicsBodiesFromWorld(),t.parent)t.physicsBody&&(this.removePhysicsBody(t),t.forceUpdate());else{if(t.isBodyInitRequired()){var e=this._createShape(t),n=t.physicsBody;n&&this.removePhysicsBody(t);var i=this._addMaterial("mat-"+t.uniqueId,t.getParam("friction"),t.getParam("restitution")),o={mass:t.getParam("mass"),material:i},a=t.getParam("nativeOptions");for(var s in a)a.hasOwnProperty(s)&&(o[s]=a[s]);t.physicsBody=new this.BJSCANNON.Body(o),t.physicsBody.addEventListener("collide",t.onCollide),this.world.addEventListener("preStep",t.beforeStep),this.world.addEventListener("postStep",t.afterStep),t.physicsBody.addShape(e),this.world.add(t.physicsBody),n&&["force","torque","velocity","angularVelocity"].forEach(function(d){var p=n[d];t.physicsBody[d].set(p.x,p.y,p.z)}),this._processChildMeshes(t)}this._updatePhysicsBodyTransformation(t)}},r.prototype._processChildMeshes=function(t){var e=this,n=t.object.getChildMeshes?t.object.getChildMeshes(!0):[],i=t.object.rotationQuaternion;if(n.length){var o=function(a){if(i&&a.rotationQuaternion){var s=a.getPhysicsImpostor();if(s&&s.parent!==t){var d=a.getAbsolutePosition().subtract(a.parent.getAbsolutePosition()),p=a.rotationQuaternion;s.physicsBody&&(e.removePhysicsBody(s),s.physicsBody=null),s.parent=t,s.resetUpdateFlags(),t.physicsBody.addShape(e._createShape(s),new e.BJSCANNON.Vec3(d.x,d.y,d.z),new e.BJSCANNON.Quaternion(p.x,p.y,p.z,p.w)),t.physicsBody.mass+=s.getParam("mass")}i.multiplyInPlace(a.rotationQuaternion),a.getChildMeshes(!0).filter(function(b){return!!b.physicsImpostor}).forEach(o)}};n.filter(function(a){return!!a.physicsImpostor}).forEach(o)}},r.prototype.removePhysicsBody=function(t){t.physicsBody.removeEventListener("collide",t.onCollide),this.world.removeEventListener("preStep",t.beforeStep),this.world.removeEventListener("postStep",t.afterStep),this._physicsBodysToRemoveAfterStep.indexOf(t.physicsBody)===-1&&this._physicsBodysToRemoveAfterStep.push(t.physicsBody)},r.prototype.generateJoint=function(t){var e=t.mainImpostor.physicsBody,n=t.connectedImpostor.physicsBody;if(e&&n){var i,o=t.joint.jointData,a={pivotA:o.mainPivot?new this.BJSCANNON.Vec3().set(o.mainPivot.x,o.mainPivot.y,o.mainPivot.z):null,pivotB:o.connectedPivot?new this.BJSCANNON.Vec3().set(o.connectedPivot.x,o.connectedPivot.y,o.connectedPivot.z):null,axisA:o.mainAxis?new this.BJSCANNON.Vec3().set(o.mainAxis.x,o.mainAxis.y,o.mainAxis.z):null,axisB:o.connectedAxis?new this.BJSCANNON.Vec3().set(o.connectedAxis.x,o.connectedAxis.y,o.connectedAxis.z):null,maxForce:o.nativeParams.maxForce,collideConnected:!!o.collision};switch(t.joint.type){case en.e.HingeJoint:case en.e.Hinge2Joint:i=new this.BJSCANNON.HingeConstraint(e,n,a);break;case en.e.DistanceJoint:i=new this.BJSCANNON.DistanceConstraint(e,n,o.maxDistance||2);break;case en.e.SpringJoint:var s=o;i=new this.BJSCANNON.Spring(e,n,{restLength:s.length,stiffness:s.stiffness,damping:s.damping,localAnchorA:a.pivotA,localAnchorB:a.pivotB});break;case en.e.LockJoint:i=new this.BJSCANNON.LockConstraint(e,n,a);break;case en.e.PointToPointJoint:case en.e.BallAndSocketJoint:default:i=new this.BJSCANNON.PointToPointConstraint(e,a.pivotA,n,a.pivotB,a.maxForce)}i.collideConnected=!!o.collision,t.joint.physicsJoint=i,t.joint.type!==en.e.SpringJoint?this.world.addConstraint(i):(t.joint.jointData.forceApplicationCallback=t.joint.jointData.forceApplicationCallback||function(){i.applyForce()},t.mainImpostor.registerAfterPhysicsStep(t.joint.jointData.forceApplicationCallback))}},r.prototype.removeJoint=function(t){t.joint.type!==en.e.SpringJoint?this.world.removeConstraint(t.joint.physicsJoint):t.mainImpostor.unregisterAfterPhysicsStep(t.joint.jointData.forceApplicationCallback)},r.prototype._addMaterial=function(t,e,n){var i,o;for(i=0;i<this._physicsMaterials.length;i++)if((o=this._physicsMaterials[i]).friction===e&&o.restitution===n)return o;var a=new this.BJSCANNON.Material(t);return a.friction=e,a.restitution=n,this._physicsMaterials.push(a),a},r.prototype._checkWithEpsilon=function(t){return t<Ir.Epsilon?Ir.Epsilon:t},r.prototype._createShape=function(t){var e,n=t.object,i=t.getObjectExtendSize();switch(t.type){case xt.a.SphereImpostor:var o=i.x,a=i.y,s=i.z;e=new this.BJSCANNON.Sphere(Math.max(this._checkWithEpsilon(o),this._checkWithEpsilon(a),this._checkWithEpsilon(s))/2);break;case xt.a.CylinderImpostor:var d=t.getParam("nativeOptions");d||(d={});var p=d.radiusTop!==void 0?d.radiusTop:this._checkWithEpsilon(i.x)/2,b=d.radiusBottom!==void 0?d.radiusBottom:this._checkWithEpsilon(i.x)/2,P=d.height!==void 0?d.height:this._checkWithEpsilon(i.y),O=d.numSegments!==void 0?d.numSegments:16;e=new this.BJSCANNON.Cylinder(p,b,P,O);var B=new this.BJSCANNON.Quaternion;B.setFromAxisAngle(new this.BJSCANNON.Vec3(1,0,0),-Math.PI/2);var F=new this.BJSCANNON.Vec3(0,0,0);e.transformAllPoints(F,B);break;case xt.a.BoxImpostor:var z=i.scale(.5);e=new this.BJSCANNON.Box(new this.BJSCANNON.Vec3(this._checkWithEpsilon(z.x),this._checkWithEpsilon(z.y),this._checkWithEpsilon(z.z)));break;case xt.a.PlaneImpostor:l.a.Warn("Attention, PlaneImposter might not behave as you expect. Consider using BoxImposter instead"),e=new this.BJSCANNON.Plane;break;case xt.a.MeshImpostor:var J=n.getVerticesData?n.getVerticesData(Oe.b.PositionKind):[],ie=n.getIndices?n.getIndices():[];if(!J)return;var se=n.position.clone(),ce=n.rotation&&n.rotation.clone(),ue=n.rotationQuaternion&&n.rotationQuaternion.clone();n.position.copyFromFloats(0,0,0),n.rotation&&n.rotation.copyFromFloats(0,0,0),n.rotationQuaternion&&n.rotationQuaternion.copyFrom(t.getParentsRotation()),n.rotationQuaternion&&n.parent&&n.rotationQuaternion.conjugateInPlace();var fe,ve=n.computeWorldMatrix(!0),Te=new Array;for(fe=0;fe<J.length;fe+=3)u.e.TransformCoordinates(u.e.FromArray(J,fe),ve).toArray(Te,fe);l.a.Warn("MeshImpostor only collides against spheres."),e=new this.BJSCANNON.Trimesh(Te,ie),n.position.copyFrom(se),ce&&n.rotation&&n.rotation.copyFrom(ce),ue&&n.rotationQuaternion&&n.rotationQuaternion.copyFrom(ue);break;case xt.a.HeightmapImpostor:var Re=n.position.clone(),Ae=n.rotation&&n.rotation.clone(),Ee=n.rotationQuaternion&&n.rotationQuaternion.clone();n.position.copyFromFloats(0,0,0),n.rotation&&n.rotation.copyFromFloats(0,0,0),n.rotationQuaternion&&n.rotationQuaternion.copyFrom(t.getParentsRotation()),n.rotationQuaternion&&n.parent&&n.rotationQuaternion.conjugateInPlace(),n.rotationQuaternion&&n.rotationQuaternion.multiplyInPlace(this._minus90X),e=this._createHeightmap(n),n.position.copyFrom(Re),Ae&&n.rotation&&n.rotation.copyFrom(Ae),Ee&&n.rotationQuaternion&&n.rotationQuaternion.copyFrom(Ee),n.computeWorldMatrix(!0);break;case xt.a.ParticleImpostor:e=new this.BJSCANNON.Particle;break;case xt.a.NoImpostor:e=new this.BJSCANNON.Box(new this.BJSCANNON.Vec3(0,0,0))}return e},r.prototype._createHeightmap=function(t,e){var n,i=t.getVerticesData(Oe.b.PositionKind),o=t.computeWorldMatrix(!0),a=new Array;for(n=0;n<i.length;n+=3)u.e.TransformCoordinates(u.e.FromArray(i,n),o).toArray(a,n);i=a;for(var s=new Array,d=e||~~(Math.sqrt(i.length/3)-1),p=t.getBoundingInfo(),b=Math.min(p.boundingBox.extendSizeWorld.x,p.boundingBox.extendSizeWorld.y),P=p.boundingBox.extendSizeWorld.z,O=2*b/d,B=0;B<i.length;B+=3){var F=Math.round(i[B+0]/O+d/2),z=Math.round(-1*(i[B+1]/O-d/2)),J=-i[B+2]+P;s[F]||(s[F]=[]),s[F][z]||(s[F][z]=J),s[F][z]=Math.max(J,s[F][z])}for(F=0;F<=d;++F){if(!s[F]){for(var ie=1;!s[(F+ie)%d];)ie++;s[F]=s[(F+ie)%d].slice()}for(z=0;z<=d;++z)if(!s[F][z]){var se;for(ie=1;se===void 0;)se=s[F][(z+ie++)%d];s[F][z]=se}}var ce=new this.BJSCANNON.Heightfield(s,{elementSize:O});return ce.minY=P,ce},r.prototype._updatePhysicsBodyTransformation=function(t){var e=t.object;if(e.computeWorldMatrix&&e.computeWorldMatrix(!0),e.getBoundingInfo()){var n=t.getObjectCenter();this._tmpDeltaPosition.copyFrom(e.getAbsolutePivotPoint().subtract(n)),this._tmpDeltaPosition.divideInPlace(t.object.scaling),this._tmpPosition.copyFrom(n);var i=e.rotationQuaternion;if(i){if(t.type!==xt.a.PlaneImpostor&&t.type!==xt.a.HeightmapImpostor||(i=i.multiply(this._minus90X),t.setDeltaRotation(this._plus90X)),t.type===xt.a.HeightmapImpostor){var o=e,a=o.getBoundingInfo(),s=o.rotationQuaternion;o.rotationQuaternion=this._tmpUnityRotation,o.computeWorldMatrix(!0);var d=n.clone(),p=o.getPivotMatrix();p=p?p.clone():u.a.Identity();var b=u.a.Translation(a.boundingBox.extendSizeWorld.x,0,-a.boundingBox.extendSizeWorld.z);o.setPreTransformMatrix(b),o.computeWorldMatrix(!0);var P=a.boundingBox.centerWorld.subtract(n).subtract(o.position).negate();this._tmpPosition.copyFromFloats(P.x,P.y-a.boundingBox.extendSizeWorld.y,P.z),this._tmpDeltaPosition.copyFrom(a.boundingBox.centerWorld.subtract(d)),this._tmpDeltaPosition.y+=a.boundingBox.extendSizeWorld.y,o.rotationQuaternion=s,o.setPreTransformMatrix(p),o.computeWorldMatrix(!0)}else t.type===xt.a.MeshImpostor&&this._tmpDeltaPosition.copyFromFloats(0,0,0);t.setDeltaPosition(this._tmpDeltaPosition),t.physicsBody.position.set(this._tmpPosition.x,this._tmpPosition.y,this._tmpPosition.z),t.physicsBody.quaternion.set(i.x,i.y,i.z,i.w)}}},r.prototype.setTransformationFromPhysicsBody=function(t){if(t.object.position.set(t.physicsBody.position.x,t.physicsBody.position.y,t.physicsBody.position.z),t.object.rotationQuaternion){var e=t.physicsBody.quaternion;t.object.rotationQuaternion.set(e.x,e.y,e.z,e.w)}},r.prototype.setPhysicsBodyTransformation=function(t,e,n){t.physicsBody.position.set(e.x,e.y,e.z),t.physicsBody.quaternion.set(n.x,n.y,n.z,n.w)},r.prototype.isSupported=function(){return this.BJSCANNON!==void 0},r.prototype.setLinearVelocity=function(t,e){t.physicsBody.velocity.set(e.x,e.y,e.z)},r.prototype.setAngularVelocity=function(t,e){t.physicsBody.angularVelocity.set(e.x,e.y,e.z)},r.prototype.getLinearVelocity=function(t){var e=t.physicsBody.velocity;return e?new u.e(e.x,e.y,e.z):null},r.prototype.getAngularVelocity=function(t){var e=t.physicsBody.angularVelocity;return e?new u.e(e.x,e.y,e.z):null},r.prototype.setBodyMass=function(t,e){t.physicsBody.mass=e,t.physicsBody.updateMassProperties()},r.prototype.getBodyMass=function(t){return t.physicsBody.mass},r.prototype.getBodyFriction=function(t){return t.physicsBody.material.friction},r.prototype.setBodyFriction=function(t,e){t.physicsBody.material.friction=e},r.prototype.getBodyRestitution=function(t){return t.physicsBody.material.restitution},r.prototype.setBodyRestitution=function(t,e){t.physicsBody.material.restitution=e},r.prototype.sleepBody=function(t){t.physicsBody.sleep()},r.prototype.wakeUpBody=function(t){t.physicsBody.wakeUp()},r.prototype.updateDistanceJoint=function(t,e){t.physicsJoint.distance=e},r.prototype.setMotor=function(t,e,n,i){i||(t.physicsJoint.enableMotor(),t.physicsJoint.setMotorSpeed(e),n&&this.setLimit(t,n))},r.prototype.setLimit=function(t,e,n){t.physicsJoint.motorEquation.maxForce=e,t.physicsJoint.motorEquation.minForce=n===void 0?-e:n},r.prototype.syncMeshWithImpostor=function(t,e){var n=e.physicsBody;t.position.x=n.position.x,t.position.y=n.position.y,t.position.z=n.position.z,t.rotationQuaternion&&(t.rotationQuaternion.x=n.quaternion.x,t.rotationQuaternion.y=n.quaternion.y,t.rotationQuaternion.z=n.quaternion.z,t.rotationQuaternion.w=n.quaternion.w)},r.prototype.getRadius=function(t){return t.physicsBody.shapes[0].boundingSphereRadius},r.prototype.getBoxSizeToRef=function(t,e){var n=t.physicsBody.shapes[0];e.x=2*n.halfExtents.x,e.y=2*n.halfExtents.y,e.z=2*n.halfExtents.z},r.prototype.dispose=function(){},r.prototype._extendNamespace=function(){var t=new this.BJSCANNON.Vec3,e=this.BJSCANNON;this.BJSCANNON.World.prototype.step=function(n,i,o){if(o=o||10,(i=i||0)===0)this.internalStep(n),this.time+=n;else{var a=Math.floor((this.time+i)/n)-Math.floor(this.time/n);a=Math.min(a,o)||1;for(var s=performance.now(),d=0;d!==a&&(this.internalStep(n),!(performance.now()-s>1e3*n));d++);this.time+=i;for(var p=this.time%n/n,b=t,P=this.bodies,O=0;O!==P.length;O++){var B=P[O];B.type!==e.Body.STATIC&&B.sleepState!==e.Body.SLEEPING?(B.position.vsub(B.previousPosition,b),b.scale(p,b),B.position.vadd(b,B.interpolatedPosition)):(B.interpolatedPosition.set(B.position.x,B.position.y,B.position.z),B.interpolatedQuaternion.set(B.quaternion.x,B.quaternion.y,B.quaternion.z,B.quaternion.w))}}}},r.prototype.raycast=function(t,e){return this._cannonRaycastResult.reset(),this.world.raycastClosest(t,e,{},this._cannonRaycastResult),this._raycastResult.reset(t,e),this._cannonRaycastResult.hasHit&&(this._raycastResult.setHitData({x:this._cannonRaycastResult.hitNormalWorld.x,y:this._cannonRaycastResult.hitNormalWorld.y,z:this._cannonRaycastResult.hitNormalWorld.z},{x:this._cannonRaycastResult.hitPointWorld.x,y:this._cannonRaycastResult.hitPointWorld.y,z:this._cannonRaycastResult.hitPointWorld.z}),this._raycastResult.setHitDistance(this._cannonRaycastResult.distance)),this._raycastResult},r}();Ir.DefaultPluginFactory=function(){return new qs};var Qu=function(){function r(t,e,n){t===void 0&&(t=!0),n===void 0&&(n=OIMO),this._useDeltaForWorldStep=t,this.name="OimoJSPlugin",this._fixedTimeStep=1/60,this._tmpImpostorsArray=[],this._tmpPositionVector=u.e.Zero(),this.BJSOIMO=n,this.world=new this.BJSOIMO.World({iterations:e}),this.world.clear(),this._raycastResult=new Qs}return r.prototype.setGravity=function(t){this.world.gravity.set(t.x,t.y,t.z)},r.prototype.setTimeStep=function(t){this.world.timeStep=t},r.prototype.getTimeStep=function(){return this.world.timeStep},r.prototype.executeStep=function(t,e){var n=this;e.forEach(function(s){s.beforeStep()}),this.world.timeStep=this._useDeltaForWorldStep?t:this._fixedTimeStep,this.world.step(),e.forEach(function(s){s.afterStep(),n._tmpImpostorsArray[s.uniqueId]=s});for(var i=this.world.contacts;i!==null;)if(!i.touching||i.body1.sleeping||i.body2.sleeping){var o=this._tmpImpostorsArray[+i.body1.name],a=this._tmpImpostorsArray[+i.body2.name];o&&a&&(o.onCollide({body:a.physicsBody,point:null}),a.onCollide({body:o.physicsBody,point:null})),i=i.next}else i=i.next},r.prototype.applyImpulse=function(t,e,n){var i=t.physicsBody.mass;t.physicsBody.applyImpulse(n.scale(this.world.invScale),e.scale(this.world.invScale*i))},r.prototype.applyForce=function(t,e,n){l.a.Warn("Oimo doesn't support applying force. Using impule instead."),this.applyImpulse(t,e,n)},r.prototype.generatePhysicsBody=function(t){var e=this;if(t.parent)t.physicsBody&&(this.removePhysicsBody(t),t.forceUpdate());else{if(t.isBodyInitRequired()){var n={name:t.uniqueId,config:[t.getParam("mass")||.001,t.getParam("friction"),t.getParam("restitution")],size:[],type:[],pos:[],posShape:[],rot:[],rotShape:[],move:t.getParam("mass")!==0,density:t.getParam("mass"),friction:t.getParam("friction"),restitution:t.getParam("restitution"),world:this.world},i=[t];(s=t.object).getChildMeshes&&s.getChildMeshes().forEach(function(d){d.physicsImpostor&&i.push(d.physicsImpostor)});var o=function(d){return Math.max(d,Ir.Epsilon)},a=new u.b;i.forEach(function(d){if(d.object.rotationQuaternion){var p=d.object.rotationQuaternion;a.copyFrom(p),d.object.rotationQuaternion.set(0,0,0,1),d.object.computeWorldMatrix(!0);var b=a.toEulerAngles(),P=d.getObjectExtendSize();if(d===t){var O=t.getObjectCenter();t.object.getAbsolutePivotPoint().subtractToRef(O,e._tmpPositionVector),e._tmpPositionVector.divideInPlace(t.object.scaling),n.pos.push(O.x),n.pos.push(O.y),n.pos.push(O.z),n.posShape.push(0,0,0),n.rotShape.push(0,0,0)}else{var B=d.object.position.clone();n.posShape.push(B.x),n.posShape.push(B.y),n.posShape.push(B.z),n.rotShape.push(57.29577951308232*b.x,57.29577951308232*b.y,57.29577951308232*b.z)}switch(d.object.rotationQuaternion.copyFrom(a),d.type){case xt.a.ParticleImpostor:l.a.Warn("No Particle support in OIMO.js. using SphereImpostor instead");case xt.a.SphereImpostor:var F=P.x,z=P.y,J=P.z,ie=Math.max(o(F),o(z),o(J))/2;n.type.push("sphere"),n.size.push(ie),n.size.push(ie),n.size.push(ie);break;case xt.a.CylinderImpostor:var se=o(P.x)/2,ce=o(P.y);n.type.push("cylinder"),n.size.push(se),n.size.push(ce),n.size.push(ce);break;case xt.a.PlaneImpostor:case xt.a.BoxImpostor:default:se=o(P.x),ce=o(P.y);var ue=o(P.z);n.type.push("box"),n.size.push(se),n.size.push(ce),n.size.push(ue)}d.object.rotationQuaternion=p}}),t.physicsBody=this.world.add(n),t.physicsBody.resetQuaternion(a),t.physicsBody.updatePosition(0)}else this._tmpPositionVector.copyFromFloats(0,0,0);var s;t.setDeltaPosition(this._tmpPositionVector)}},r.prototype.removePhysicsBody=function(t){this.world.removeRigidBody(t.physicsBody)},r.prototype.generateJoint=function(t){var e=t.mainImpostor.physicsBody,n=t.connectedImpostor.physicsBody;if(e&&n){var i,o=t.joint.jointData,a=o.nativeParams||{},s={body1:e,body2:n,axe1:a.axe1||(o.mainAxis?o.mainAxis.asArray():null),axe2:a.axe2||(o.connectedAxis?o.connectedAxis.asArray():null),pos1:a.pos1||(o.mainPivot?o.mainPivot.asArray():null),pos2:a.pos2||(o.connectedPivot?o.connectedPivot.asArray():null),min:a.min,max:a.max,collision:a.collision||o.collision,spring:a.spring,world:this.world};switch(t.joint.type){case en.e.BallAndSocketJoint:i="jointBall";break;case en.e.SpringJoint:l.a.Warn("OIMO.js doesn't support Spring Constraint. Simulating using DistanceJoint instead");var d=o;s.min=d.length||s.min,s.max=Math.max(s.min,s.max);case en.e.DistanceJoint:i="jointDistance",s.max=o.maxDistance;break;case en.e.PrismaticJoint:i="jointPrisme";break;case en.e.SliderJoint:i="jointSlide";break;case en.e.WheelJoint:i="jointWheel";break;case en.e.HingeJoint:default:i="jointHinge"}s.type=i,t.joint.physicsJoint=this.world.add(s)}},r.prototype.removeJoint=function(t){try{this.world.removeJoint(t.joint.physicsJoint)}catch(e){l.a.Warn(e)}},r.prototype.isSupported=function(){return this.BJSOIMO!==void 0},r.prototype.setTransformationFromPhysicsBody=function(t){if(!t.physicsBody.sleeping){if(t.physicsBody.shapes.next){for(var e=t.physicsBody.shapes;e.next;)e=e.next;t.object.position.set(e.position.x,e.position.y,e.position.z)}else{var n=t.physicsBody.getPosition();t.object.position.set(n.x,n.y,n.z)}if(t.object.rotationQuaternion){var i=t.physicsBody.getQuaternion();t.object.rotationQuaternion.set(i.x,i.y,i.z,i.w)}}},r.prototype.setPhysicsBodyTransformation=function(t,e,n){var i=t.physicsBody;t.physicsBody.shapes.next||(i.position.set(e.x,e.y,e.z),i.orientation.set(n.x,n.y,n.z,n.w),i.syncShapes(),i.awake())},r.prototype.setLinearVelocity=function(t,e){t.physicsBody.linearVelocity.set(e.x,e.y,e.z)},r.prototype.setAngularVelocity=function(t,e){t.physicsBody.angularVelocity.set(e.x,e.y,e.z)},r.prototype.getLinearVelocity=function(t){var e=t.physicsBody.linearVelocity;return e?new u.e(e.x,e.y,e.z):null},r.prototype.getAngularVelocity=function(t){var e=t.physicsBody.angularVelocity;return e?new u.e(e.x,e.y,e.z):null},r.prototype.setBodyMass=function(t,e){var n=e===0;t.physicsBody.shapes.density=n?1:e,t.physicsBody.setupMass(n?2:1)},r.prototype.getBodyMass=function(t){return t.physicsBody.shapes.density},r.prototype.getBodyFriction=function(t){return t.physicsBody.shapes.friction},r.prototype.setBodyFriction=function(t,e){t.physicsBody.shapes.friction=e},r.prototype.getBodyRestitution=function(t){return t.physicsBody.shapes.restitution},r.prototype.setBodyRestitution=function(t,e){t.physicsBody.shapes.restitution=e},r.prototype.sleepBody=function(t){t.physicsBody.sleep()},r.prototype.wakeUpBody=function(t){t.physicsBody.awake()},r.prototype.updateDistanceJoint=function(t,e,n){t.physicsJoint.limitMotor.upperLimit=e,n!==void 0&&(t.physicsJoint.limitMotor.lowerLimit=n)},r.prototype.setMotor=function(t,e,n,i){n!==void 0?l.a.Warn("OimoJS plugin currently has unexpected behavior when using setMotor with force parameter"):n=1e6,e*=-1;var o=i?t.physicsJoint.rotationalLimitMotor2:t.physicsJoint.rotationalLimitMotor1||t.physicsJoint.rotationalLimitMotor||t.physicsJoint.limitMotor;o&&o.setMotor(e,n)},r.prototype.setLimit=function(t,e,n,i){var o=i?t.physicsJoint.rotationalLimitMotor2:t.physicsJoint.rotationalLimitMotor1||t.physicsJoint.rotationalLimitMotor||t.physicsJoint.limitMotor;o&&o.setLimit(e,n===void 0?-e:n)},r.prototype.syncMeshWithImpostor=function(t,e){var n=e.physicsBody;t.position.x=n.position.x,t.position.y=n.position.y,t.position.z=n.position.z,t.rotationQuaternion&&(t.rotationQuaternion.x=n.orientation.x,t.rotationQuaternion.y=n.orientation.y,t.rotationQuaternion.z=n.orientation.z,t.rotationQuaternion.w=n.orientation.s)},r.prototype.getRadius=function(t){return t.physicsBody.shapes.radius},r.prototype.getBoxSizeToRef=function(t,e){var n=t.physicsBody.shapes;e.x=2*n.halfWidth,e.y=2*n.halfHeight,e.z=2*n.halfDepth},r.prototype.dispose=function(){this.world.clear()},r.prototype.raycast=function(t,e){return l.a.Warn("raycast is not currently supported by the Oimo physics plugin"),this._raycastResult.reset(t,e),this._raycastResult},r}(),ca=f(97),qu=function(){function r(t,e,n){var i=this;t===void 0&&(t=!0),e===void 0&&(e=Ammo),n===void 0&&(n=null),this._useDeltaForWorldStep=t,this.bjsAMMO={},this.name="AmmoJSPlugin",this._timeStep=1/60,this._fixedTimeStep=1/60,this._maxSteps=5,this._tmpQuaternion=new u.b,this._tmpContactCallbackResult=!1,this._tmpContactPoint=new u.e,this._tmpMatrix=new u.a,typeof e=="function"?e(this.bjsAMMO):this.bjsAMMO=e,this.isSupported()?(this._collisionConfiguration=new this.bjsAMMO.btSoftBodyRigidBodyCollisionConfiguration,this._dispatcher=new this.bjsAMMO.btCollisionDispatcher(this._collisionConfiguration),this._overlappingPairCache=n||new this.bjsAMMO.btDbvtBroadphase,this._solver=new this.bjsAMMO.btSequentialImpulseConstraintSolver,this._softBodySolver=new this.bjsAMMO.btDefaultSoftBodySolver,this.world=new this.bjsAMMO.btSoftRigidDynamicsWorld(this._dispatcher,this._overlappingPairCache,this._solver,this._collisionConfiguration,this._softBodySolver),this._tmpAmmoConcreteContactResultCallback=new this.bjsAMMO.ConcreteContactResultCallback,this._tmpAmmoConcreteContactResultCallback.addSingleResult=function(o,a,s,d){var p=(o=i.bjsAMMO.wrapPointer(o,Ammo.btManifoldPoint)).getPositionWorldOnA();i._tmpContactPoint.x=p.x(),i._tmpContactPoint.y=p.y(),i._tmpContactPoint.z=p.z(),i._tmpContactCallbackResult=!0},this._raycastResult=new Qs,this._tmpAmmoTransform=new this.bjsAMMO.btTransform,this._tmpAmmoTransform.setIdentity(),this._tmpAmmoQuaternion=new this.bjsAMMO.btQuaternion(0,0,0,1),this._tmpAmmoVectorA=new this.bjsAMMO.btVector3(0,0,0),this._tmpAmmoVectorB=new this.bjsAMMO.btVector3(0,0,0),this._tmpAmmoVectorC=new this.bjsAMMO.btVector3(0,0,0),this._tmpAmmoVectorD=new this.bjsAMMO.btVector3(0,0,0)):l.a.Error("AmmoJS is not available. Please make sure you included the js file.")}return r.prototype.setGravity=function(t){this._tmpAmmoVectorA.setValue(t.x,t.y,t.z),this.world.setGravity(this._tmpAmmoVectorA),this.world.getWorldInfo().set_m_gravity(this._tmpAmmoVectorA)},r.prototype.setTimeStep=function(t){this._timeStep=t},r.prototype.setFixedTimeStep=function(t){this._fixedTimeStep=t},r.prototype.setMaxSteps=function(t){this._maxSteps=t},r.prototype.getTimeStep=function(){return this._timeStep},r.prototype._isImpostorInContact=function(t){return this._tmpContactCallbackResult=!1,this.world.contactTest(t.physicsBody,this._tmpAmmoConcreteContactResultCallback),this._tmpContactCallbackResult},r.prototype._isImpostorPairInContact=function(t,e){return this._tmpContactCallbackResult=!1,this.world.contactPairTest(t.physicsBody,e.physicsBody,this._tmpAmmoConcreteContactResultCallback),this._tmpContactCallbackResult},r.prototype._stepSimulation=function(t,e,n){if(t===void 0&&(t=1/60),e===void 0&&(e=10),n===void 0&&(n=1/60),e==0)this.world.stepSimulation(t,0);else for(;e>0&&t>0;)t-n<n?(this.world.stepSimulation(t,0),t=0):(t-=n,this.world.stepSimulation(n,0)),e--},r.prototype.executeStep=function(t,e){for(var n=0,i=e;n<i.length;n++){var o=i[n];o.soft||o.beforeStep()}this._stepSimulation(this._useDeltaForWorldStep?t:this._timeStep,this._maxSteps,this._fixedTimeStep);for(var a=0,s=e;a<s.length;a++){var d=s[a];if(d.soft?this._afterSoftStep(d):d.afterStep(),d._onPhysicsCollideCallbacks.length>0&&this._isImpostorInContact(d))for(var p=0,b=d._onPhysicsCollideCallbacks;p<b.length;p++)for(var P=0,O=b[p].otherImpostors;P<O.length;P++){var B=O[P];(d.physicsBody.isActive()||B.physicsBody.isActive())&&this._isImpostorPairInContact(d,B)&&(d.onCollide({body:B.physicsBody,point:this._tmpContactPoint}),B.onCollide({body:d.physicsBody,point:this._tmpContactPoint}))}}},r.prototype._afterSoftStep=function(t){t.type===xt.a.RopeImpostor?this._ropeStep(t):this._softbodyOrClothStep(t)},r.prototype._ropeStep=function(t){for(var e,n,i,o,a=t.physicsBody.get_m_nodes(),s=a.size(),d=new Array,p=0;p<s;p++)n=(e=a.at(p).get_m_x()).x(),i=e.y(),o=e.z(),d.push(new u.e(n,i,o));var b=t.object,P=t.getParam("shape");t._isFromLine?t.object=cn.a.CreateLines("lines",{points:d,instance:b}):t.object=ca.a.ExtrudeShape("ext",{shape:P,path:d,instance:b})},r.prototype._softbodyOrClothStep=function(t){var e=t.type===xt.a.ClothImpostor?1:-1,n=t.object,i=n.getVerticesData(Oe.b.PositionKind);i||(i=[]);var o=n.getVerticesData(Oe.b.NormalKind);o||(o=[]);for(var a,s,d,p,b,P,O,B,F=i.length/3,z=t.physicsBody.get_m_nodes(),J=0;J<F;J++){var ie;d=(s=(a=z.at(J)).get_m_x()).x(),p=s.y(),b=s.z()*e,P=(ie=a.get_m_n()).x(),O=ie.y(),B=ie.z()*e,i[3*J]=d,i[3*J+1]=p,i[3*J+2]=b,o[3*J]=P,o[3*J+1]=O,o[3*J+2]=B}var se=new ft.a;se.positions=i,se.normals=o,se.uvs=n.getVerticesData(Oe.b.UVKind),se.colors=n.getVerticesData(Oe.b.ColorKind),n&&n.getIndices&&(se.indices=n.getIndices()),se.applyToMesh(n)},r.prototype.applyImpulse=function(t,e,n){if(t.soft)l.a.Warn("Cannot be applied to a soft body");else{t.physicsBody.activate();var i=this._tmpAmmoVectorA,o=this._tmpAmmoVectorB;t.object&&t.object.getWorldMatrix&&n.subtractInPlace(t.object.getWorldMatrix().getTranslation()),i.setValue(n.x,n.y,n.z),o.setValue(e.x,e.y,e.z),t.physicsBody.applyImpulse(o,i)}},r.prototype.applyForce=function(t,e,n){if(t.soft)l.a.Warn("Cannot be applied to a soft body");else{t.physicsBody.activate();var i=this._tmpAmmoVectorA,o=this._tmpAmmoVectorB;t.object&&t.object.getWorldMatrix&&n.subtractInPlace(t.object.getWorldMatrix().getTranslation()),i.setValue(n.x,n.y,n.z),o.setValue(e.x,e.y,e.z),t.physicsBody.applyForce(o,i)}},r.prototype.generatePhysicsBody=function(t){if(t._pluginData.toDispose=[],t.parent)t.physicsBody&&(this.removePhysicsBody(t),t.forceUpdate());else if(t.isBodyInitRequired()){var e=this._createShape(t),n=t.getParam("mass");if(t._pluginData.mass=n,t.soft)e.get_m_cfg().set_collisions(17),e.get_m_cfg().set_kDP(t.getParam("damping")),this.bjsAMMO.castObject(e,this.bjsAMMO.btCollisionObject).getCollisionShape().setMargin(t.getParam("margin")),e.setActivationState(r.DISABLE_DEACTIVATION_FLAG),this.world.addSoftBody(e,1,-1),t.physicsBody=e,t._pluginData.toDispose.push(e),this.setBodyPressure(t,0),t.type===xt.a.SoftbodyImpostor&&this.setBodyPressure(t,t.getParam("pressure")),this.setBodyStiffness(t,t.getParam("stiffness")),this.setBodyVelocityIterations(t,t.getParam("velocityIterations")),this.setBodyPositionIterations(t,t.getParam("positionIterations"));else{var i=new this.bjsAMMO.btVector3(0,0,0),o=new this.bjsAMMO.btTransform;o.setIdentity(),n!==0&&e.calculateLocalInertia(n,i),this._tmpAmmoVectorA.setValue(t.object.position.x,t.object.position.y,t.object.position.z),this._tmpAmmoQuaternion.setValue(t.object.rotationQuaternion.x,t.object.rotationQuaternion.y,t.object.rotationQuaternion.z,t.object.rotationQuaternion.w),o.setOrigin(this._tmpAmmoVectorA),o.setRotation(this._tmpAmmoQuaternion);var a=new this.bjsAMMO.btDefaultMotionState(o),s=new this.bjsAMMO.btRigidBodyConstructionInfo(n,a,e,i),d=new this.bjsAMMO.btRigidBody(s);n===0&&(d.setCollisionFlags(d.getCollisionFlags()|r.KINEMATIC_FLAG),d.setActivationState(r.DISABLE_DEACTIVATION_FLAG)),t.type!=xt.a.NoImpostor||e.getChildShape||d.setCollisionFlags(d.getCollisionFlags()|r.DISABLE_COLLISION_FLAG);var p=t.getParam("group"),b=t.getParam("mask");p&&b?this.world.addRigidBody(d,p,b):this.world.addRigidBody(d),t.physicsBody=d,t._pluginData.toDispose=t._pluginData.toDispose.concat([d,s,a,o,i,e])}this.setBodyRestitution(t,t.getParam("restitution")),this.setBodyFriction(t,t.getParam("friction"))}},r.prototype.removePhysicsBody=function(t){var e=this;this.world&&(t.soft?this.world.removeSoftBody(t.physicsBody):this.world.removeRigidBody(t.physicsBody),t._pluginData&&(t._pluginData.toDispose.forEach(function(n){e.bjsAMMO.destroy(n)}),t._pluginData.toDispose=[]))},r.prototype.generateJoint=function(t){var e=t.mainImpostor.physicsBody,n=t.connectedImpostor.physicsBody;if(e&&n){var i,o=t.joint.jointData;switch(o.mainPivot||(o.mainPivot=new u.e(0,0,0)),o.connectedPivot||(o.connectedPivot=new u.e(0,0,0)),t.joint.type){case en.e.DistanceJoint:var a=o.maxDistance;a&&(o.mainPivot=new u.e(0,-a/2,0),o.connectedPivot=new u.e(0,a/2,0)),i=new this.bjsAMMO.btPoint2PointConstraint(e,n,new this.bjsAMMO.btVector3(o.mainPivot.x,o.mainPivot.y,o.mainPivot.z),new this.bjsAMMO.btVector3(o.connectedPivot.x,o.connectedPivot.y,o.connectedPivot.z));break;case en.e.HingeJoint:o.mainAxis||(o.mainAxis=new u.e(0,0,0)),o.connectedAxis||(o.connectedAxis=new u.e(0,0,0));var s=new this.bjsAMMO.btVector3(o.mainAxis.x,o.mainAxis.y,o.mainAxis.z),d=new this.bjsAMMO.btVector3(o.connectedAxis.x,o.connectedAxis.y,o.connectedAxis.z);i=new this.bjsAMMO.btHingeConstraint(e,n,new this.bjsAMMO.btVector3(o.mainPivot.x,o.mainPivot.y,o.mainPivot.z),new this.bjsAMMO.btVector3(o.connectedPivot.x,o.connectedPivot.y,o.connectedPivot.z),s,d);break;case en.e.BallAndSocketJoint:i=new this.bjsAMMO.btPoint2PointConstraint(e,n,new this.bjsAMMO.btVector3(o.mainPivot.x,o.mainPivot.y,o.mainPivot.z),new this.bjsAMMO.btVector3(o.connectedPivot.x,o.connectedPivot.y,o.connectedPivot.z));break;default:l.a.Warn("JointType not currently supported by the Ammo plugin, falling back to PhysicsJoint.BallAndSocketJoint"),i=new this.bjsAMMO.btPoint2PointConstraint(e,n,new this.bjsAMMO.btVector3(o.mainPivot.x,o.mainPivot.y,o.mainPivot.z),new this.bjsAMMO.btVector3(o.connectedPivot.x,o.connectedPivot.y,o.connectedPivot.z))}this.world.addConstraint(i,!t.joint.jointData.collision),t.joint.physicsJoint=i}},r.prototype.removeJoint=function(t){this.world&&this.world.removeConstraint(t.joint.physicsJoint)},r.prototype._addMeshVerts=function(t,e,n){var i=this,o=0;if(n&&n.getIndices&&n.getWorldMatrix&&n.getChildMeshes){var a=n.getIndices();a||(a=[]);var s=n.getVerticesData(Oe.b.PositionKind);s||(s=[]),n.computeWorldMatrix(!1);for(var d=a.length/3,p=0;p<d;p++){for(var b=[],P=0;P<3;P++){var O,B=new u.e(s[3*a[3*p+P]+0],s[3*a[3*p+P]+1],s[3*a[3*p+P]+2]);u.a.ScalingToRef(n.scaling.x,n.scaling.y,n.scaling.z,this._tmpMatrix),B=u.e.TransformCoordinates(B,this._tmpMatrix),(O=P==0?this._tmpAmmoVectorA:P==1?this._tmpAmmoVectorB:this._tmpAmmoVectorC).setValue(B.x,B.y,B.z),b.push(O)}t.addTriangle(b[0],b[1],b[2]),o++}n.getChildMeshes().forEach(function(F){o+=i._addMeshVerts(t,e,F)})}return o},r.prototype._softVertexData=function(t){var e=t.object;if(e&&e.getIndices&&e.getWorldMatrix&&e.getChildMeshes){e.getIndices();var n=e.getVerticesData(Oe.b.PositionKind);n||(n=[]);var i=e.getVerticesData(Oe.b.NormalKind);i||(i=[]),e.computeWorldMatrix(!1);for(var o=[],a=[],s=0;s<n.length;s+=3){var d=new u.e(n[s],n[s+1],n[s+2]),p=new u.e(i[s],i[s+1],i[s+2]);d=u.e.TransformCoordinates(d,e.getWorldMatrix()),p=u.e.TransformNormal(p,e.getWorldMatrix()),o.push(d.x,d.y,d.z),a.push(p.x,p.y,p.z)}var b=new ft.a;return b.positions=o,b.normals=a,b.uvs=e.getVerticesData(Oe.b.UVKind),b.colors=e.getVerticesData(Oe.b.ColorKind),e&&e.getIndices&&(b.indices=e.getIndices()),b.applyToMesh(e),e.position=u.e.Zero(),e.rotationQuaternion=null,e.rotation=u.e.Zero(),e.computeWorldMatrix(!0),b}return ft.a.ExtractFromMesh(e)},r.prototype._createSoftbody=function(t){var e=t.object;if(e&&e.getIndices){var n=e.getIndices();n||(n=[]);var i=this._softVertexData(t),o=i.positions,a=i.normals;if(o===null||a===null)return new this.bjsAMMO.btCompoundShape;for(var s=[],d=[],p=0;p<o.length;p+=3){var b=new u.e(o[p],o[p+1],o[p+2]),P=new u.e(a[p],a[p+1],a[p+2]);s.push(b.x,b.y,-b.z),d.push(P.x,P.y,-P.z)}var O=new this.bjsAMMO.btSoftBodyHelpers().CreateFromTriMesh(this.world.getWorldInfo(),s,e.getIndices(),n.length/3,!0),B=o.length/3,F=O.get_m_nodes();for(p=0;p<B;p++){var z;(z=F.at(p).get_m_n()).setX(d[3*p]),z.setY(d[3*p+1]),z.setZ(d[3*p+2])}return O}},r.prototype._createCloth=function(t){var e=t.object;if(e&&e.getIndices){e.getIndices();var n=this._softVertexData(t),i=n.positions,o=n.normals;if(i===null||o===null)return new this.bjsAMMO.btCompoundShape;var a=i.length,s=Math.sqrt(a/3);t.segments=s;var d=s-1;return this._tmpAmmoVectorA.setValue(i[0],i[1],i[2]),this._tmpAmmoVectorB.setValue(i[3*d],i[3*d+1],i[3*d+2]),this._tmpAmmoVectorD.setValue(i[a-3],i[a-2],i[a-1]),this._tmpAmmoVectorC.setValue(i[a-3-3*d],i[a-2-3*d],i[a-1-3*d]),new this.bjsAMMO.btSoftBodyHelpers().CreatePatch(this.world.getWorldInfo(),this._tmpAmmoVectorA,this._tmpAmmoVectorB,this._tmpAmmoVectorC,this._tmpAmmoVectorD,s,s,t.getParam("fixedPoints"),!0)}},r.prototype._createRope=function(t){var e,n,i=this._softVertexData(t),o=i.positions,a=i.normals;if(o===null||a===null)return new this.bjsAMMO.btCompoundShape;if(i.applyToMesh(t.object,!0),t._isFromLine=!0,a.map(function(b){return b*b}).reduce(function(b,P){return b+P})===0)n=(e=o.length)/3-1,this._tmpAmmoVectorA.setValue(o[0],o[1],o[2]),this._tmpAmmoVectorB.setValue(o[e-3],o[e-2],o[e-1]);else{t._isFromLine=!1;var s=t.getParam("path");if(t.getParam("shape")===null)return l.a.Warn("No shape available for extruded mesh"),new this.bjsAMMO.btCompoundShape;if(o.length%(3*s.length)!=0)return l.a.Warn("Path does not match extrusion"),new this.bjsAMMO.btCompoundShape;n=(e=s.length)-1,this._tmpAmmoVectorA.setValue(s[0].x,s[0].y,s[0].z),this._tmpAmmoVectorB.setValue(s[e-1].x,s[e-1].y,s[e-1].z)}t.segments=n;var d=t.getParam("fixedPoints");d=d>3?3:d;var p=new this.bjsAMMO.btSoftBodyHelpers().CreateRope(this.world.getWorldInfo(),this._tmpAmmoVectorA,this._tmpAmmoVectorB,n-1,d);return p.get_m_cfg().set_collisions(17),p},r.prototype._createCustom=function(t){var e=null;return this.onCreateCustomShape&&(e=this.onCreateCustomShape(t)),e==null&&(e=new this.bjsAMMO.btCompoundShape),e},r.prototype._addHullVerts=function(t,e,n){var i=this,o=0;if(n&&n.getIndices&&n.getWorldMatrix&&n.getChildMeshes){var a=n.getIndices();a||(a=[]);var s=n.getVerticesData(Oe.b.PositionKind);s||(s=[]),n.computeWorldMatrix(!1);for(var d=a.length/3,p=0;p<d;p++){for(var b=[],P=0;P<3;P++){var O,B=new u.e(s[3*a[3*p+P]+0],s[3*a[3*p+P]+1],s[3*a[3*p+P]+2]);u.a.ScalingToRef(n.scaling.x,n.scaling.y,n.scaling.z,this._tmpMatrix),B=u.e.TransformCoordinates(B,this._tmpMatrix),(O=P==0?this._tmpAmmoVectorA:P==1?this._tmpAmmoVectorB:this._tmpAmmoVectorC).setValue(B.x,B.y,B.z),b.push(O)}t.addPoint(b[0],!0),t.addPoint(b[1],!0),t.addPoint(b[2],!0),o++}n.getChildMeshes().forEach(function(F){o+=i._addHullVerts(t,e,F)})}return o},r.prototype._createShape=function(t,e){var n=this;e===void 0&&(e=!1);var i,o=t.object,a=t.getObjectExtendSize();if(!e){var s=t.object.getChildMeshes?t.object.getChildMeshes(!0):[];i=new this.bjsAMMO.btCompoundShape;var d=0;if(s.forEach(function(F){var z=F.getPhysicsImpostor();if(z){if(z.type==xt.a.MeshImpostor)throw"A child MeshImpostor is not supported. Only primitive impostors are supported as children (eg. box or sphere)";var J=n._createShape(z),ie=F.parent.getWorldMatrix().clone(),se=new u.e;ie.decompose(se),n._tmpAmmoTransform.getOrigin().setValue(F.position.x*se.x,F.position.y*se.y,F.position.z*se.z),n._tmpAmmoQuaternion.setValue(F.rotationQuaternion.x,F.rotationQuaternion.y,F.rotationQuaternion.z,F.rotationQuaternion.w),n._tmpAmmoTransform.setRotation(n._tmpAmmoQuaternion),i.addChildShape(n._tmpAmmoTransform,J),z.dispose(),d++}}),d>0){if(t.type!=xt.a.NoImpostor){var p=this._createShape(t,!0);p&&(this._tmpAmmoTransform.getOrigin().setValue(0,0,0),this._tmpAmmoQuaternion.setValue(0,0,0,1),this._tmpAmmoTransform.setRotation(this._tmpAmmoQuaternion),i.addChildShape(this._tmpAmmoTransform,p))}return i}this.bjsAMMO.destroy(i),i=null}switch(t.type){case xt.a.SphereImpostor:if($.a.WithinEpsilon(a.x,a.y,1e-4)&&$.a.WithinEpsilon(a.x,a.z,1e-4))i=new this.bjsAMMO.btSphereShape(a.x/2);else{var b=[new this.bjsAMMO.btVector3(0,0,0)];(i=new this.bjsAMMO.btMultiSphereShape(b,[1],1)).setLocalScaling(new this.bjsAMMO.btVector3(a.x/2,a.y/2,a.z/2))}break;case xt.a.CapsuleImpostor:i=new this.bjsAMMO.btCapsuleShape(a.x/2,a.y/2);break;case xt.a.CylinderImpostor:this._tmpAmmoVectorA.setValue(a.x/2,a.y/2,a.z/2),i=new this.bjsAMMO.btCylinderShape(this._tmpAmmoVectorA);break;case xt.a.PlaneImpostor:case xt.a.BoxImpostor:this._tmpAmmoVectorA.setValue(a.x/2,a.y/2,a.z/2),i=new this.bjsAMMO.btBoxShape(this._tmpAmmoVectorA);break;case xt.a.MeshImpostor:if(t.getParam("mass")==0){var P=new this.bjsAMMO.btTriangleMesh;t._pluginData.toDispose.push(P);var O=this._addMeshVerts(P,o,o);i=O==0?new this.bjsAMMO.btCompoundShape:new this.bjsAMMO.btBvhTriangleMeshShape(P);break}case xt.a.ConvexHullImpostor:var B=new this.bjsAMMO.btConvexHullShape;(O=this._addHullVerts(B,o,o))==0?(t._pluginData.toDispose.push(B),i=new this.bjsAMMO.btCompoundShape):i=B;break;case xt.a.NoImpostor:i=new this.bjsAMMO.btSphereShape(a.x/2);break;case xt.a.CustomImpostor:i=this._createCustom(t);break;case xt.a.SoftbodyImpostor:i=this._createSoftbody(t);break;case xt.a.ClothImpostor:i=this._createCloth(t);break;case xt.a.RopeImpostor:i=this._createRope(t);break;default:l.a.Warn("The impostor type is not currently supported by the ammo plugin.")}return i},r.prototype.setTransformationFromPhysicsBody=function(t){t.physicsBody.getMotionState().getWorldTransform(this._tmpAmmoTransform),t.object.position.set(this._tmpAmmoTransform.getOrigin().x(),this._tmpAmmoTransform.getOrigin().y(),this._tmpAmmoTransform.getOrigin().z()),t.object.rotationQuaternion?t.object.rotationQuaternion.set(this._tmpAmmoTransform.getRotation().x(),this._tmpAmmoTransform.getRotation().y(),this._tmpAmmoTransform.getRotation().z(),this._tmpAmmoTransform.getRotation().w()):t.object.rotation&&(this._tmpQuaternion.set(this._tmpAmmoTransform.getRotation().x(),this._tmpAmmoTransform.getRotation().y(),this._tmpAmmoTransform.getRotation().z(),this._tmpAmmoTransform.getRotation().w()),this._tmpQuaternion.toEulerAnglesToRef(t.object.rotation))},r.prototype.setPhysicsBodyTransformation=function(t,e,n){var i=t.physicsBody.getWorldTransform();if(Math.abs(i.getOrigin().x()-e.x)>Gt.a||Math.abs(i.getOrigin().y()-e.y)>Gt.a||Math.abs(i.getOrigin().z()-e.z)>Gt.a||Math.abs(i.getRotation().x()-n.x)>Gt.a||Math.abs(i.getRotation().y()-n.y)>Gt.a||Math.abs(i.getRotation().z()-n.z)>Gt.a||Math.abs(i.getRotation().w()-n.w)>Gt.a)if(this._tmpAmmoVectorA.setValue(e.x,e.y,e.z),i.setOrigin(this._tmpAmmoVectorA),this._tmpAmmoQuaternion.setValue(n.x,n.y,n.z,n.w),i.setRotation(this._tmpAmmoQuaternion),t.physicsBody.setWorldTransform(i),t.mass==0){var o=t.physicsBody.getMotionState();o&&o.setWorldTransform(i)}else t.physicsBody.activate()},r.prototype.isSupported=function(){return this.bjsAMMO!==void 0},r.prototype.setLinearVelocity=function(t,e){this._tmpAmmoVectorA.setValue(e.x,e.y,e.z),t.soft?t.physicsBody.linearVelocity(this._tmpAmmoVectorA):t.physicsBody.setLinearVelocity(this._tmpAmmoVectorA)},r.prototype.setAngularVelocity=function(t,e){this._tmpAmmoVectorA.setValue(e.x,e.y,e.z),t.soft?t.physicsBody.angularVelocity(this._tmpAmmoVectorA):t.physicsBody.setAngularVelocity(this._tmpAmmoVectorA)},r.prototype.getLinearVelocity=function(t){if(t.soft)var e=t.physicsBody.linearVelocity();else e=t.physicsBody.getLinearVelocity();if(!e)return null;var n=new u.e(e.x(),e.y(),e.z());return this.bjsAMMO.destroy(e),n},r.prototype.getAngularVelocity=function(t){if(t.soft)var e=t.physicsBody.angularVelocity();else e=t.physicsBody.getAngularVelocity();if(!e)return null;var n=new u.e(e.x(),e.y(),e.z());return this.bjsAMMO.destroy(e),n},r.prototype.setBodyMass=function(t,e){t.soft?t.physicsBody.setTotalMass(e,!1):t.physicsBody.setMassProps(e),t._pluginData.mass=e},r.prototype.getBodyMass=function(t){return t._pluginData.mass||0},r.prototype.getBodyFriction=function(t){return t._pluginData.friction||0},r.prototype.setBodyFriction=function(t,e){t.soft?t.physicsBody.get_m_cfg().set_kDF(e):t.physicsBody.setFriction(e),t._pluginData.friction=e},r.prototype.getBodyRestitution=function(t){return t._pluginData.restitution||0},r.prototype.setBodyRestitution=function(t,e){t.physicsBody.setRestitution(e),t._pluginData.restitution=e},r.prototype.getBodyPressure=function(t){return t.soft?t._pluginData.pressure||0:(l.a.Warn("Pressure is not a property of a rigid body"),0)},r.prototype.setBodyPressure=function(t,e){t.soft?t.type===xt.a.SoftbodyImpostor?(t.physicsBody.get_m_cfg().set_kPR(e),t._pluginData.pressure=e):(t.physicsBody.get_m_cfg().set_kPR(0),t._pluginData.pressure=0):l.a.Warn("Pressure can only be applied to a softbody")},r.prototype.getBodyStiffness=function(t){return t.soft?t._pluginData.stiffness||0:(l.a.Warn("Stiffness is not a property of a rigid body"),0)},r.prototype.setBodyStiffness=function(t,e){t.soft?(e=(e=e<0?0:e)>1?1:e,t.physicsBody.get_m_materials().at(0).set_m_kLST(e),t._pluginData.stiffness=e):l.a.Warn("Stiffness cannot be applied to a rigid body")},r.prototype.getBodyVelocityIterations=function(t){return t.soft?t._pluginData.velocityIterations||0:(l.a.Warn("Velocity iterations is not a property of a rigid body"),0)},r.prototype.setBodyVelocityIterations=function(t,e){t.soft?(e=e<0?0:e,t.physicsBody.get_m_cfg().set_viterations(e),t._pluginData.velocityIterations=e):l.a.Warn("Velocity iterations cannot be applied to a rigid body")},r.prototype.getBodyPositionIterations=function(t){return t.soft?t._pluginData.positionIterations||0:(l.a.Warn("Position iterations is not a property of a rigid body"),0)},r.prototype.setBodyPositionIterations=function(t,e){t.soft?(e=e<0?0:e,t.physicsBody.get_m_cfg().set_piterations(e),t._pluginData.positionIterations=e):l.a.Warn("Position iterations cannot be applied to a rigid body")},r.prototype.appendAnchor=function(t,e,n,i,o,a){o===void 0&&(o=1),a===void 0&&(a=!1);var s=t.segments,d=Math.round((s-1)*n)+s*(s-1-Math.round((s-1)*i));t.physicsBody.appendAnchor(d,e.physicsBody,a,o)},r.prototype.appendHook=function(t,e,n,i,o){i===void 0&&(i=1),o===void 0&&(o=!1);var a=Math.round(t.segments*n);t.physicsBody.appendAnchor(a,e.physicsBody,o,i)},r.prototype.sleepBody=function(t){l.a.Warn("sleepBody is not currently supported by the Ammo physics plugin")},r.prototype.wakeUpBody=function(t){t.physicsBody.activate()},r.prototype.updateDistanceJoint=function(t,e,n){l.a.Warn("updateDistanceJoint is not currently supported by the Ammo physics plugin")},r.prototype.setMotor=function(t,e,n,i){t.physicsJoint.enableAngularMotor(!0,e,n)},r.prototype.setLimit=function(t,e,n){l.a.Warn("setLimit is not currently supported by the Ammo physics plugin")},r.prototype.syncMeshWithImpostor=function(t,e){e.physicsBody.getMotionState().getWorldTransform(this._tmpAmmoTransform),t.position.x=this._tmpAmmoTransform.getOrigin().x(),t.position.y=this._tmpAmmoTransform.getOrigin().y(),t.position.z=this._tmpAmmoTransform.getOrigin().z(),t.rotationQuaternion&&(t.rotationQuaternion.x=this._tmpAmmoTransform.getRotation().x(),t.rotationQuaternion.y=this._tmpAmmoTransform.getRotation().y(),t.rotationQuaternion.z=this._tmpAmmoTransform.getRotation().z(),t.rotationQuaternion.w=this._tmpAmmoTransform.getRotation().w())},r.prototype.getRadius=function(t){return t.getObjectExtendSize().x/2},r.prototype.getBoxSizeToRef=function(t,e){var n=t.getObjectExtendSize();e.x=n.x,e.y=n.y,e.z=n.z},r.prototype.dispose=function(){this.bjsAMMO.destroy(this.world),this.bjsAMMO.destroy(this._solver),this.bjsAMMO.destroy(this._overlappingPairCache),this.bjsAMMO.destroy(this._dispatcher),this.bjsAMMO.destroy(this._collisionConfiguration),this.bjsAMMO.destroy(this._tmpAmmoVectorA),this.bjsAMMO.destroy(this._tmpAmmoVectorB),this.bjsAMMO.destroy(this._tmpAmmoVectorC),this.bjsAMMO.destroy(this._tmpAmmoTransform),this.bjsAMMO.destroy(this._tmpAmmoQuaternion),this.bjsAMMO.destroy(this._tmpAmmoConcreteContactResultCallback),this.world=null},r.prototype.raycast=function(t,e){this._tmpAmmoVectorRCA=new this.bjsAMMO.btVector3(t.x,t.y,t.z),this._tmpAmmoVectorRCB=new this.bjsAMMO.btVector3(e.x,e.y,e.z);var n=new this.bjsAMMO.ClosestRayResultCallback(this._tmpAmmoVectorRCA,this._tmpAmmoVectorRCB);return this.world.rayTest(this._tmpAmmoVectorRCA,this._tmpAmmoVectorRCB,n),this._raycastResult.reset(t,e),n.hasHit()&&(this._raycastResult.setHitData({x:n.get_m_hitNormalWorld().x(),y:n.get_m_hitNormalWorld().y(),z:n.get_m_hitNormalWorld().z()},{x:n.get_m_hitPointWorld().x(),y:n.get_m_hitPointWorld().y(),z:n.get_m_hitPointWorld().z()}),this._raycastResult.calculateHitDistance()),this.bjsAMMO.destroy(n),this.bjsAMMO.destroy(this._tmpAmmoVectorRCA),this.bjsAMMO.destroy(this._tmpAmmoVectorRCB),this._raycastResult},r.DISABLE_COLLISION_FLAG=4,r.KINEMATIC_FLAG=2,r.DISABLE_DEACTIVATION_FLAG=4,r}();U.a.prototype.removeReflectionProbe=function(r){if(!this.reflectionProbes)return-1;var t=this.reflectionProbes.indexOf(r);return t!==-1&&this.reflectionProbes.splice(t,1),t},U.a.prototype.addReflectionProbe=function(r){this.reflectionProbes||(this.reflectionProbes=[]),this.reflectionProbes.push(r)};var Zu=function(){function r(t,e,n,i,o){var a=this;i===void 0&&(i=!0),o===void 0&&(o=!1),this.name=t,this._viewMatrix=u.a.Identity(),this._target=u.e.Zero(),this._add=u.e.Zero(),this._invertYAxis=!1,this.position=u.e.Zero(),this._scene=n,this._scene.reflectionProbes||(this._scene.reflectionProbes=new Array),this._scene.reflectionProbes.push(this);var s=h.a.TEXTURETYPE_UNSIGNED_BYTE;if(o){var d=this._scene.getEngine().getCaps();d.textureHalfFloatRender?s=h.a.TEXTURETYPE_HALF_FLOAT:d.textureFloatRender&&(s=h.a.TEXTURETYPE_FLOAT)}this._renderTargetTexture=new sn(t,e,n,i,!0,s,!0),this._renderTargetTexture.onBeforeRenderObservable.add(function(p){switch(p){case 0:a._add.copyFromFloats(1,0,0);break;case 1:a._add.copyFromFloats(-1,0,0);break;case 2:a._add.copyFromFloats(0,a._invertYAxis?1:-1,0);break;case 3:a._add.copyFromFloats(0,a._invertYAxis?-1:1,0);break;case 4:a._add.copyFromFloats(0,0,1);break;case 5:a._add.copyFromFloats(0,0,-1)}a._attachedMesh&&a.position.copyFrom(a._attachedMesh.getAbsolutePosition()),a.position.addToRef(a._add,a._target),u.a.LookAtLHToRef(a.position,a._target,u.e.Up(),a._viewMatrix),n.activeCamera&&(a._projectionMatrix=u.a.PerspectiveFovLH(Math.PI/2,1,n.activeCamera.minZ,n.activeCamera.maxZ),n.setTransformMatrix(a._viewMatrix,a._projectionMatrix)),n._forcedViewPosition=a.position}),this._renderTargetTexture.onAfterUnbindObservable.add(function(){n._forcedViewPosition=null,n.updateTransformMatrix(!0)})}return Object.defineProperty(r.prototype,"samples",{get:function(){return this._renderTargetTexture.samples},set:function(t){this._renderTargetTexture.samples=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"refreshRate",{get:function(){return this._renderTargetTexture.refreshRate},set:function(t){this._renderTargetTexture.refreshRate=t},enumerable:!1,configurable:!0}),r.prototype.getScene=function(){return this._scene},Object.defineProperty(r.prototype,"cubeTexture",{get:function(){return this._renderTargetTexture},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"renderList",{get:function(){return this._renderTargetTexture.renderList},enumerable:!1,configurable:!0}),r.prototype.attachToMesh=function(t){this._attachedMesh=t},r.prototype.setRenderingAutoClearDepthStencil=function(t,e){this._renderTargetTexture.setRenderingAutoClearDepthStencil(t,e)},r.prototype.dispose=function(){var t=this._scene.reflectionProbes.indexOf(this);t!==-1&&this._scene.reflectionProbes.splice(t,1),this._renderTargetTexture&&(this._renderTargetTexture.dispose(),this._renderTargetTexture=null)},r.prototype.toString=function(t){var e="Name: "+this.name;return t&&(e+=", position: "+this.position.toString(),this._attachedMesh&&(e+=", attached mesh: "+this._attachedMesh.name)),e},r.prototype.getClassName=function(){return"ReflectionProbe"},r.prototype.serialize=function(){var t=L.a.Serialize(this,this._renderTargetTexture.serialize());return t.isReflectionProbe=!0,t},r.Parse=function(t,e,n){var i=null;if(e.reflectionProbes)for(var o=0;o<e.reflectionProbes.length;o++){var a=e.reflectionProbes[o];if(a.name===t.name){i=a;break}}return(i=L.a.Parse(function(){return i||new r(t.name,t.renderTargetSize,e,t._generateMipMaps)},t,e,n)).cubeTexture._waitingRenderList=t.renderList,t._attachedMesh&&i.attachToMesh(e.getMeshByID(t._attachedMesh)),i},Object(c.c)([Object(L.k)()],r.prototype,"_attachedMesh",void 0),Object(c.c)([Object(L.o)()],r.prototype,"position",void 0),r}(),Q_=!0,la=function(){function r(){}return r.LoaderInjectedPhysicsEngine=void 0,r}(),Ju=function(r,t,e,n){for(var i=0,o=t.materials.length;i<o;i++){var a=t.materials[i];if(a.id===r)return Ht.a.Parse(a,e,n)}return null},q_=function(r,t,e){for(var n in t)if(r.name===t[n])return e.push(r.id),!0;return!(!r.parentId||e.indexOf(r.parentId)===-1)&&(e.push(r.id),!0)},Dr=function(r,t){return r+" of "+(t?t.file+" from "+t.name+" version: "+t.version+", exporter version: "+t.exporter_version:"unknown")},$u=function(r,t){var e=t;if(t._waitingData.lods){if(t._waitingData.lods.ids&&t._waitingData.lods.ids.length>0){var n=t._waitingData.lods.ids,i=e.isEnabled(!1);if(t._waitingData.lods.distances){var o=t._waitingData.lods.distances;if(o.length>=n.length){var a=o.length>n.length?o[o.length-1]:0;e.setEnabled(!1);for(var s=0;s<n.length;s++){var d=n[s],p=r.getMeshByID(d);p!=null&&e.addLODLevel(o[s],p)}a>0&&e.addLODLevel(a,null),i===!0&&e.setEnabled(!0)}else Xe.b.Warn("Invalid level of detail distances for "+t.name)}}t._waitingData.lods=null}},eh=function(r,t,e,n,i){i===void 0&&(i=!1);var o=new xn(r),a="importScene has failed JSON parse";try{var s=JSON.parse(t);a="";var d,p,b=Ut.loggingLevel===Ut.DETAILED_LOGGING;if(s.environmentTexture!==void 0&&s.environmentTexture!==null){var P=s.isPBR===void 0||s.isPBR;if(s.environmentTextureType&&s.environmentTextureType==="BABYLON.HDRCubeTexture"){var O=s.environmentTextureSize?s.environmentTextureSize:128,B=new aa((s.environmentTexture.match(/https?:\/\//g)?"":e)+s.environmentTexture,r,O,!0,!P);s.environmentTextureRotationY&&(B.rotationY=s.environmentTextureRotationY),r.environmentTexture=B}else if(Qn.a.EndsWith(s.environmentTexture,".env")){var F=new oi((s.environmentTexture.match(/https?:\/\//g)?"":e)+s.environmentTexture,r);s.environmentTextureRotationY&&(F.rotationY=s.environmentTextureRotationY),r.environmentTexture=F}else{var z=oi.CreateFromPrefilteredData((s.environmentTexture.match(/https?:\/\//g)?"":e)+s.environmentTexture,r);s.environmentTextureRotationY&&(z.rotationY=s.environmentTextureRotationY),r.environmentTexture=z}if(s.createDefaultSkybox===!0){var J=r.activeCamera!==void 0&&r.activeCamera!==null?(r.activeCamera.maxZ-r.activeCamera.minZ)/2:1e3,ie=s.skyboxBlurLevel||0;r.createDefaultSkybox(r.environmentTexture,P,J,ie)}o.environmentTexture=r.environmentTexture}if(s.environmentIntensity!==void 0&&s.environmentIntensity!==null&&(r.environmentIntensity=s.environmentIntensity),s.lights!==void 0&&s.lights!==null)for(d=0,p=s.lights.length;d<p;d++){var se=s.lights[d],ce=Ci.a.Parse(se,r);ce&&(o.lights.push(ce),a+=d===0?`
-	Lights:`:"",a+=`
-		`+ce.toString(b))}if(s.reflectionProbes!==void 0&&s.reflectionProbes!==null)for(d=0,p=s.reflectionProbes.length;d<p;d++){var ue=s.reflectionProbes[d],fe=Zu.Parse(ue,r,e);fe&&(o.reflectionProbes.push(fe),a+=d===0?`
-	Reflection Probes:`:"",a+=`
-		`+fe.toString(b))}if(s.animations!==void 0&&s.animations!==null)for(d=0,p=s.animations.length;d<p;d++){var ve=s.animations[d],Te=R.a.GetClass("BABYLON.Animation");if(Te){var Re=Te.Parse(ve);r.animations.push(Re),o.animations.push(Re),a+=d===0?`
-	Animations:`:"",a+=`
-		`+Re.toString(b)}}if(s.materials!==void 0&&s.materials!==null)for(d=0,p=s.materials.length;d<p;d++){var Ae=s.materials[d],Ee=Ht.a.Parse(Ae,r,e);Ee&&(o.materials.push(Ee),a+=d===0?`
-	Materials:`:"",a+=`
-		`+Ee.toString(b),Ee.getActiveTextures().forEach(function(qt){o.textures.indexOf(qt)==-1&&o.textures.push(qt)}))}if(s.multiMaterials!==void 0&&s.multiMaterials!==null)for(d=0,p=s.multiMaterials.length;d<p;d++){var Se=s.multiMaterials[d],Le=rr.a.ParseMultiMaterial(Se,r);o.multiMaterials.push(Le),a+=d===0?`
-	MultiMaterials:`:"",a+=`
-		`+Le.toString(b),Le.getActiveTextures().forEach(function(qt){o.textures.indexOf(qt)==-1&&o.textures.push(qt)})}if(s.morphTargetManagers!==void 0&&s.morphTargetManagers!==null)for(var xe=0,Ne=s.morphTargetManagers;xe<Ne.length;xe++){var Ie=Ne[xe];o.morphTargetManagers.push(sa.Parse(Ie,r))}if(s.skeletons!==void 0&&s.skeletons!==null)for(d=0,p=s.skeletons.length;d<p;d++){var Fe=s.skeletons[d],Ye=No.Parse(Fe,r);o.skeletons.push(Ye),a+=d===0?`
-	Skeletons:`:"",a+=`
-		`+Ye.toString(b)}var tt=s.geometries;if(tt!=null){var it=new Array,ut=tt.vertexData;if(ut!=null)for(d=0,p=ut.length;d<p;d++){var Qe=ut[d];it.push(Ys.a.Parse(Qe,r,e))}it.forEach(function(qt){qt&&o.geometries.push(qt)})}if(s.transformNodes!==void 0&&s.transformNodes!==null)for(d=0,p=s.transformNodes.length;d<p;d++){var ot=s.transformNodes[d],rt=Er.a.Parse(ot,r,e);o.transformNodes.push(rt)}if(s.meshes!==void 0&&s.meshes!==null)for(d=0,p=s.meshes.length;d<p;d++){var Ze=s.meshes[d],dt=De.a.Parse(Ze,r,e);if(o.meshes.push(dt),dt.hasInstances)for(var Ve=0,Je=dt.instances;Ve<Je.length;Ve++){var yt=Je[Ve];o.meshes.push(yt)}a+=d===0?`
-	Meshes:`:"",a+=`
-		`+dt.toString(b)}if(s.cameras!==void 0&&s.cameras!==null)for(d=0,p=s.cameras.length;d<p;d++){var Wt=s.cameras[d],Nt=gt.a.Parse(Wt,r);o.cameras.push(Nt),a+=d===0?`
-	Cameras:`:"",a+=`
-		`+Nt.toString(b)}if(s.postProcesses!==void 0&&s.postProcesses!==null)for(d=0,p=s.postProcesses.length;d<p;d++){var Qt=s.postProcesses[d],vt=_t.Parse(Qt,r,e);vt&&(o.postProcesses.push(vt),a+=d===0?`
-Postprocesses:`:"",a+=`
-		`+vt.toString())}if(s.animationGroups!==void 0&&s.animationGroups!==null)for(d=0,p=s.animationGroups.length;d<p;d++){var Jt=s.animationGroups[d],Xt=je.Parse(Jt,r);o.animationGroups.push(Xt),a+=d===0?`
-	AnimationGroups:`:"",a+=`
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r({isEnabled:t.isEnabled,leftColor:M.a.FromArray(t.leftColor),rightColor:M.a.FromArray(t.rightColor),bias:t.bias,power:t.power||1})},r}();L.a._FresnelParametersParser=th.Parse;var nh=f(119),Zs=function(r){function t(e,n){var i=r.call(this,e,n)||this;return i.maxSimultaneousLights=4,i.disableLighting=!1,i.invertNormalMapX=!1,i.invertNormalMapY=!1,i.emissiveColor=new M.a(0,0,0),i.occlusionStrength=1,i.useLightmapAsShadowmap=!1,i._useAlphaFromAlbedoTexture=!0,i._useAmbientInGrayScale=!0,i}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"doubleSided",{get:function(){return this._twoSidedLighting},set:function(e){this._twoSidedLighting!==e&&(this._twoSidedLighting=e,this.backFaceCulling=!e,this._markAllSubMeshesAsTexturesDirty())},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"PBRBaseSimpleMaterial"},Object(c.c)([Object(L.c)(),Object(L.b)("_markAllSubMeshesAsLightsDirty")],t.prototype,"maxSimultaneousLights",void 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i.id=e,i.name=e,this.clearCoat.copyTo(i.clearCoat),this.anisotropy.copyTo(i.anisotropy),this.brdf.copyTo(i.brdf),this.sheen.copyTo(i.sheen),this.subSurface.copyTo(i.subSurface),i},t.prototype.serialize=function(){var e=L.a.Serialize(this);return e.customType="BABYLON.PBRMetallicRoughnessMaterial",e.clearCoat=this.clearCoat.serialize(),e.anisotropy=this.anisotropy.serialize(),e.brdf=this.brdf.serialize(),e.sheen=this.sheen.serialize(),e.subSurface=this.subSurface.serialize(),e},t.Parse=function(e,n,i){var o=L.a.Parse(function(){return new t(e.name,n)},e,n,i);return e.clearCoat&&o.clearCoat.parse(e.clearCoat,n,i),e.anisotropy&&o.anisotropy.parse(e.anisotropy,n,i),e.brdf&&o.brdf.parse(e.brdf,n,i),e.sheen&&o.sheen.parse(e.sheen,n,i),e.subSurface&&o.subSurface.parse(e.subSurface,n,i),o},Object(c.c)([Object(L.e)(),Object(L.b)("_markAllSubMeshesAsTexturesDirty","_albedoColor")],t.prototype,"baseColor",void 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n.level=this.level,n.wrapU=this.wrapU,n.wrapV=this.wrapV,n.coordinatesIndex=this.coordinatesIndex,n.coordinatesMode=this.coordinatesMode,n},t._FacesMapping=["right","left","up","down","front","back"],t}(zn.a),J_=function(r){function t(e,n,i){var o=r.call(this,i.scene||i.engine)||this;return n&&(i.engine||i.scene)&&(i=Object(c.a)(Object(c.a)({},t.DefaultOptions),i),o._generateMipMaps=i.generateMipMaps,o._samplingMode=i.samplingMode,o._textureMatrix=u.a.Identity(),o.name=e,o.element=n,o._isVideo=n instanceof HTMLVideoElement,o.anisotropicFilteringLevel=1,o._createInternalTexture()),o}return Object(c.d)(t,r),t.prototype._createInternalTexture=function(){var e=0,n=0;this._isVideo?(e=this.element.videoWidth,n=this.element.videoHeight):(e=this.element.width,n=this.element.height);var i=this._getEngine();i&&(this._texture=i.createDynamicTexture(e,n,this._generateMipMaps,this._samplingMode)),this.update()},t.prototype.getTextureMatrix=function(){return 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Te=r["_getImageData"+(d?"Grey":"")+i.pixel_size+"bits"](i,p,o,P,B,F,b,O,z);t.getEngine()._uploadDataToTextureDirectly(t,Te)}}},r._getImageData8bits=function(t,e,n,i,o,a,s,d,p){var b,P,O,B=n,F=e,z=t.width,J=t.height,ie=0,se=new Uint8Array(z*J*4);for(O=i;O!==a;O+=o)for(P=s;P!==p;P+=d,ie++)b=B[ie],se[4*(P+z*O)+3]=255,se[4*(P+z*O)+2]=F[3*b+0],se[4*(P+z*O)+1]=F[3*b+1],se[4*(P+z*O)+0]=F[3*b+2];return se},r._getImageData16bits=function(t,e,n,i,o,a,s,d,p){var b,P,O,B=n,F=t.width,z=t.height,J=0,ie=new Uint8Array(F*z*4);for(O=i;O!==a;O+=o)for(P=s;P!==p;P+=d,J+=2){var se=255*((31744&(b=B[J+0]+(B[J+1]<<8)))>>10)/31|0,ce=255*((992&b)>>5)/31|0,ue=255*(31&b)/31|0;ie[4*(P+F*O)+0]=se,ie[4*(P+F*O)+1]=ce,ie[4*(P+F*O)+2]=ue,ie[4*(P+F*O)+3]=32768&b?0:255}return ie},r._getImageData24bits=function(t,e,n,i,o,a,s,d,p){var b,P,O=n,B=t.width,F=t.height,z=0,J=new Uint8Array(B*F*4);for(P=i;P!==a;P+=o)for(b=s;b!==p;b+=d,z+=3)J[4*(b+B*P)+3]=255,J[4*(b+B*P)+2]=O[z+0],J[4*(b+B*P)+1]=O[z+1],J[4*(b+B*P)+0]=O[z+2];return 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r(){this.supportCascades=!1}return r.prototype.canLoad=function(t){return Qn.a.EndsWith(t,".tga")},r.prototype.loadCubeData=function(t,e,n,i,o){throw".env not supported in Cube."},r.prototype.loadData=function(t,e,n){var i=new Uint8Array(t.buffer,t.byteOffset,t.byteLength),o=ha.GetTGAHeader(i);n(o.width,o.height,e.generateMipMaps,!1,function(){ha.UploadContent(e,i)})},r}();Ue.a._TextureLoaders.push(new sh);var _o,$_=function(){};(function(r){r[r.cTFETC1=0]="cTFETC1",r[r.cTFBC1=1]="cTFBC1",r[r.cTFBC4=2]="cTFBC4",r[r.cTFPVRTC1_4_OPAQUE_ONLY=3]="cTFPVRTC1_4_OPAQUE_ONLY",r[r.cTFBC7_M6_OPAQUE_ONLY=4]="cTFBC7_M6_OPAQUE_ONLY",r[r.cTFETC2=5]="cTFETC2",r[r.cTFBC3=6]="cTFBC3",r[r.cTFBC5=7]="cTFBC5"})(_o||(_o={}));var mo=function(){function r(){}return r.GetInternalFormatFromBasisFormat=function(t){if(t===_o.cTFETC1)return 36196;if(t===_o.cTFBC1)return 33776;if(t===_o.cTFBC3)return 33779;throw"The chosen Basis transcoder format is not currently supported"},r._CreateWorkerAsync=function(){var t=this;return this._WorkerPromise||(this._WorkerPromise=new Promise(function(e){t._Worker?e(t._Worker):Xe.b.LoadFileAsync(r.WasmModuleURL).then(function(n){var i=URL.createObjectURL(new Blob(["("+em+")()"],{type:"application/javascript"}));t._Worker=new Worker(i);var o=function(a){a.data.action==="init"&&(t._Worker.removeEventListener("message",o),e(t._Worker))};t._Worker.addEventListener("message",o),t._Worker.postMessage({action:"init",url:r.JSModuleURL,wasmBinary:n})})})),this._WorkerPromise},r.TranscodeAsync=function(t,e){var n=this,i=t instanceof ArrayBuffer?new Uint8Array(t):t;return new Promise(function(o,a){n._CreateWorkerAsync().then(function(){var s=n._actionId++,d=function(b){b.data.action==="transcode"&&b.data.id===s&&(n._Worker.removeEventListener("message",d),b.data.success?o(b.data):a("Transcode is not supported on this device"))};n._Worker.addEventListener("message",d);var p=new Uint8Array(i.byteLength);p.set(new 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t._invertVScale=!t.invertY,t.width=n.width+3&-4,t.height=n.height+3&-4,i._uploadDataToTextureDirectly(t,n.transcodedPixels,a,0,h.a.TEXTUREFORMAT_RGB,!0);else t.width=n.width,t.height=n.height,e.fileInfo.images[a].levels.forEach(function(d,p){i._uploadCompressedDataToTextureDirectly(t,r.GetInternalFormatFromBasisFormat(e.format),d.width,d.height,d.transcodedPixels,a,p)}),i.webGLVersion<2&&($.a.Log2(t.width)%1!=0||$.a.Log2(t.height)%1!=0)&&(Xe.b.Warn("Loaded .basis texture width and height are not a power of two. 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Te=F+8*(fe*ce+ve);ie[0]=B[Te]|B[Te+1]<<8,ie[1]=B[Te+2]|B[Te+3]<<8,ie[2]=(2*(31&ie[0])+1*(31&ie[1]))/3|(2*(2016&ie[0])+1*(2016&ie[1]))/3&2016|(2*(63488&ie[0])+1*(63488&ie[1]))/3&63488,ie[3]=(2*(31&ie[1])+1*(31&ie[0]))/3|(2*(2016&ie[1])+1*(2016&ie[0]))/3&2016|(2*(63488&ie[1])+1*(63488&ie[0]))/3&63488;for(var Re=0;Re<4;Re++){var Ae=B[Te+4+Re],Ee=(4*fe+Re)*z+4*ve;se[Ee++]=ie[3&Ae],se[Ee++]=ie[Ae>>2&3],se[Ee++]=ie[Ae>>4&3],se[Ee++]=ie[Ae>>6&3]}}return se}(O,0,a.getImageWidth(s,d)+3&-4,a.getImageHeight(s,d)+3&-4)),O):null}onmessage=function(a){if(a.data.action==="init")i||(Module={wasmBinary:a.data.wasmBinary},importScripts(a.data.url),i=new Promise(function(fe){Module.onRuntimeInitialized=function(){Module.initializeBasis(),fe()}})),i.then(function(){postMessage({action:"init"})});else if(a.data.action==="transcode"){var s=a.data.config,d=a.data.imageData,p=new Module.BasisFile(d),b=function(fe){for(var ve=fe.getHasAlpha(),Te=fe.getNumImages(),Re=[],Ae=0;Ae<Te;Ae++){for(var Ee={levels:[]},Se=fe.getNumLevels(Ae),Le=0;Le<Se;Le++){var xe={width:fe.getImageWidth(Ae,Le),height:fe.getImageHeight(Ae,Le)};Ee.levels.push(xe)}Re.push(Ee)}return{hasAlpha:ve,images:Re}}(p),P=a.data.ignoreSupportedFormats?null:function(fe,ve){var Te=null;return fe.supportedCompressionFormats&&(fe.supportedCompressionFormats.etc1?Te=r:fe.supportedCompressionFormats.s3tc?Te=ve.hasAlpha?n:t:fe.supportedCompressionFormats.pvrtc||fe.supportedCompressionFormats.etc2&&(Te=e)),Te}(a.data.config,b),O=!1;P===null&&(O=!0,P=b.hasAlpha?n:t);var B=!0;p.startTranscoding()||(B=!1);for(var F=[],z=0;z<b.images.length&&B;z++){var J=b.images[z];if(s.loadSingleImage===void 0||s.loadSingleImage===z){var ie=J.levels.length;s.loadMipmapLevels===!1&&(ie=1);for(var se=0;se<ie;se++){var ce=J.levels[se],ue=o(p,z,se,P,O);if(!ue){B=!1;break}ce.transcodedPixels=ue,F.push(ce.transcodedPixels.buffer)}}}p.close(),p.delete(),O&&(P=-1),B?postMessage({action:"transcode",success:B,id:a.data.id,fileInfo:b,format:P},F):postMessage({action:"transcode",success:B,id:a.data.id})}}}var ch=function(){function r(){this.supportCascades=!1}return r.prototype.canLoad=function(t){return Qn.a.EndsWith(t,".basis")},r.prototype.loadCubeData=function(t,e,n,i,o){if(!Array.isArray(t)){var a=e.getEngine().getCaps(),s={supportedCompressionFormats:{etc1:!!a.etc1,s3tc:!!a.s3tc,pvrtc:!!a.pvrtc,etc2:!!a.etc2}};mo.TranscodeAsync(t,s).then(function(d){var p=d.fileInfo.images[0].levels.length>1&&e.generateMipMaps;mo.LoadTextureFromTranscodeResult(e,d),e.getEngine()._setCubeMapTextureParams(e,p),e.isReady=!0,e.onLoadedObservable.notifyObservers(e),e.onLoadedObservable.clear(),i&&i()}).catch(function(d){Xe.b.Warn("Failed to transcode Basis file, transcoding may not be supported on this device"),e.isReady=!0})}},r.prototype.loadData=function(t,e,n){var i=e.getEngine().getCaps(),o={supportedCompressionFormats:{etc1:!!i.etc1,s3tc:!!i.s3tc,pvrtc:!!i.pvrtc,etc2:!!i.etc2}};mo.TranscodeAsync(t,o).then(function(a){var s=a.fileInfo.images[0].levels[0],d=a.fileInfo.images[0].levels.length>1&&e.generateMipMaps;n(s.width,s.height,d,a.format!==-1,function(){mo.LoadTextureFromTranscodeResult(e,a)})}).catch(function(a){Xe.b.Warn("Failed to transcode Basis file, transcoding may not be supported on this device"),n(0,0,!1,!1,function(){})})},r}();Ue.a._TextureLoaders.push(new ch);var Js=function(r){function t(e,n,i,o,a){var s=this,d=!(!a||!a.generateMipMaps)&&a.generateMipMaps,p=!(!a||!a.generateDepthTexture)&&a.generateDepthTexture,b=!a||a.doNotChangeAspectRatio===void 0||a.doNotChangeAspectRatio;if((s=r.call(this,e,n,o,d,b)||this).isSupported){var P=[],O=[];s._initTypes(i,P,O,a);var B=!a||a.generateDepthBuffer===void 0||a.generateDepthBuffer,F=!(!a||a.generateStencilBuffer===void 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n=0;n<this._textures.length;n++)this._textures[n].wrapU=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"wrapV",{set:function(e){if(this._textures)for(var n=0;n<this._textures.length;n++)this._textures[n].wrapV=e},enumerable:!1,configurable:!0}),t.prototype._initTypes=function(e,n,i,o){for(var a=0;a<e;a++)o&&o.types&&o.types[a]!==void 0?n.push(o.types[a]):n.push(o&&o.defaultType?o.defaultType:h.a.TEXTURETYPE_UNSIGNED_INT),o&&o.samplingModes&&o.samplingModes[a]!==void 0?i.push(o.samplingModes[a]):i.push(we.a.BILINEAR_SAMPLINGMODE)},t.prototype._rebuild=function(e){e===void 0&&(e=!1),this.releaseInternalTextures(),this._createInternalTextures(),e&&this._createTextures();for(var n=0;n<this._internalTextures.length;n++)this._textures[n]._texture=this._internalTextures[n];this._texture=this._internalTextures[0],this.samples!==1&&this._getEngine().updateMultipleRenderTargetTextureSampleCount(this._internalTextures,this.samples)},t.prototype._createInternalTextures=function(){this._internalTextures=this._getEngine().createMultipleRenderTarget(this._size,this._multiRenderTargetOptions)},t.prototype._createTextures=function(){this._textures=[];for(var e=0;e<this._internalTextures.length;e++){var n=new we.a(null,this.getScene());n._texture=this._internalTextures[e],this._textures.push(n)}this._texture=this._internalTextures[0]},t.prototype.replaceTexture=function(e,n){e._texture&&(this._textures[n]=e,this._internalTextures[n]=e._texture)},Object.defineProperty(t.prototype,"samples",{get:function(){return this._samples},set:function(e){this._samples!==e&&(this._samples=this._getEngine().updateMultipleRenderTargetTextureSampleCount(this._internalTextures,e))},enumerable:!1,configurable:!0}),t.prototype.resize=function(e){this._size=e,this._rebuild()},t.prototype.updateCount=function(e,n){this._multiRenderTargetOptions.textureCount=e,this._count=e;var i=[],o=[];this._initTypes(e,i,o,n),this._multiRenderTargetOptions.types=i,this._multiRenderTargetOptions.samplingModes=o,this._rebuild(!0)},t.prototype.unbindFrameBuffer=function(e,n){var i=this;e.unBindMultiColorAttachmentFramebuffer(this._internalTextures,this.isCube,function(){i.onAfterRenderObservable.notifyObservers(n)})},t.prototype.dispose=function(){this.releaseInternalTextures(),r.prototype.dispose.call(this)},t.prototype.releaseInternalTextures=function(){if(this._internalTextures)for(var e=this._internalTextures.length-1;e>=0;e--)this._internalTextures[e]!==void 0&&(this._internalTextures[e].dispose(),this._internalTextures.splice(e,1))},t}(sn),$s=function(r,t,e){this.id=r,this.scale=t,this.offset=e},tm=function(){function r(t,e,n,i){var o,a,s,d,p,b,P,O,B,F,z,J,ie;return this.name=t,this.meshes=e,this.scene=i,this.options=n,this.options.map=(o=this.options.map)!==null&&o!==void 0?o:["ambientTexture","bumpTexture","diffuseTexture","emissiveTexture","lightmapTexture","opacityTexture","reflectionTexture","refractionTexture","specularTexture"],this.options.uvsIn=(a=this.options.uvsIn)!==null&&a!==void 0?a:Oe.b.UVKind,this.options.uvsOut=(s=this.options.uvsOut)!==null&&s!==void 0?s:Oe.b.UVKind,this.options.layout=(d=this.options.layout)!==null&&d!==void 0?d:r.LAYOUT_STRIP,this.options.layout===r.LAYOUT_COLNUM&&(this.options.colnum=(p=this.options.colnum)!==null&&p!==void 0?p:8),this.options.updateInputMeshes=(b=this.options.updateInputMeshes)===null||b===void 0||b,this.options.disposeSources=(P=this.options.disposeSources)===null||P===void 0||P,this._expecting=0,this.options.fillBlanks=(O=this.options.fillBlanks)===null||O===void 0||O,this.options.fillBlanks===!0&&(this.options.customFillColor=(B=this.options.customFillColor)!==null&&B!==void 0?B:"black"),this.options.frameSize=(F=this.options.frameSize)!==null&&F!==void 0?F:256,this.options.paddingRatio=(z=this.options.paddingRatio)!==null&&z!==void 0?z:.0115,this._paddingValue=Math.ceil(this.options.frameSize*this.options.paddingRatio),this._paddingValue%2!=0&&this._paddingValue++,this.options.paddingMode=(J=this.options.paddingMode)!==null&&J!==void 0?J:r.SUBUV_WRAP,this.options.paddingMode===r.SUBUV_COLOR&&(this.options.paddingColor=(ie=this.options.paddingColor)!==null&&ie!==void 0?ie:new M.b(0,0,0,1)),this.sets={},this.frames=[],this}return r.prototype._createFrames=function(t){for(var e=this,n=this._calculateSize(),i=new u.d(1,1).divide(n),o=0,a=this._expecting,s=this.meshes.length,d=Object.keys(this.sets),p=0;p<d.length;p++){var b=d[p],P=new Ti.a(this.name+".TexturePack."+b+"Set",{width:n.x,height:n.y},this.scene,!0,we.a.TRILINEAR_SAMPLINGMODE,Ue.a.TEXTUREFORMAT_RGBA),O=P.getContext();O.fillStyle="rgba(0,0,0,0)",O.fillRect(0,0,n.x,n.y),P.update(!1),this.sets[b]=P}var B=this.options.frameSize||256,F=this._paddingValue,z=B+2*F;for(p=0;p<s;p++)for(var J=this.meshes[p].material,ie=function(ue){var fe=new Ti.a("temp",z,se.scene,!0),ve=fe.getContext(),Te=se._getFrameOffset(p),Re=function(){o++,fe.update(!1);var Le=ve.getImageData(0,0,z,z),xe=e.sets[Ae];if(xe.getContext().putImageData(Le,n.x*Te.x,n.y*Te.y),fe.dispose(),xe.update(!1),o==a)return e._calculateMeshUVFrames(B,F,n,i,e.options.updateInputMeshes||!1),void t()},Ae=d[ue]||"_blank";if(J&&J[Ae]!==null){var Ee=J[Ae],Se=new Image;Ee instanceof Ti.a?Se.src=Ee.getContext().canvas.toDataURL("image/png"):Se.src=Ee.url,Xe.b.SetCorsBehavior(Se.src,Se),Se.onload=function(){ve.fillStyle="rgba(0,0,0,0)",ve.fillRect(0,0,z,z),fe.update(!1),ve.setTransform(1,0,0,-1,0,0);var Le=[0,0,1,0,1,1,0,1,-1,1,-1,0,-2,0,-1,1,-1];switch(e.options.paddingMode){case 0:for(var xe=0;xe<9;xe++)ve.drawImage(Se,0,0,Se.width,Se.height,F+B*Le[xe],F+B*Le[xe+1]-z,B,B);break;case 1:for(var Ne=0;Ne<F;Ne++)ve.drawImage(Se,0,0,Se.width,Se.height,Ne+B*Le[0],F-z,B,B),ve.drawImage(Se,0,0,Se.width,Se.height,2*F-Ne,F-z,B,B),ve.drawImage(Se,0,0,Se.width,Se.height,F,Ne-z,B,B),ve.drawImage(Se,0,0,Se.width,Se.height,F,2*F-Ne-z,B,B);ve.drawImage(Se,0,0,Se.width,Se.height,F+B*Le[0],F+B*Le[1]-z,B,B);break;case 2:ve.fillStyle=(e.options.paddingColor||M.a.Black()).toHexString(),ve.fillRect(0,0,z,-z),ve.clearRect(F,F,B,B),ve.drawImage(Se,0,0,Se.width,Se.height,F+B*Le[0],F+B*Le[1]-z,B,B)}ve.setTransform(1,0,0,1,0,0),Re()}}else ve.fillStyle="rgba(0,0,0,0)",se.options.fillBlanks&&(ve.fillStyle=se.options.customFillColor),ve.fillRect(0,0,z,z),Re()},se=this,ce=0;ce<d.length;ce++)ie(ce)},r.prototype._calculateSize=function(){var t=this.meshes.length||0,e=this.options.frameSize||0,n=this._paddingValue||0;switch(this.options.layout){case 0:return new u.d(e*t+2*n*t,e+2*n);case 1:var i=Math.max(2,Math.ceil(Math.sqrt(t))),o=e*i+2*n*i;return new u.d(o,o);case 2:var a=this.options.colnum||1,s=Math.max(1,Math.ceil(t/a));return new u.d(e*a+2*n*a,e*s+2*n*s)}return u.d.Zero()},r.prototype._calculateMeshUVFrames=function(t,e,n,i,o){for(var a=this.meshes.length,s=0;s<a;s++){var d=this.meshes[s],p=new u.d(t/n.x,t/n.y),b=i.clone().scale(e),P=this._getFrameOffset(s).add(b),O=new $s(s,p,P);this.frames.push(O),o&&(this._updateMeshUV(d,s),this._updateTextureReferences(d))}},r.prototype._getFrameOffset=function(t){var e,n,i,o=this.meshes.length;switch(this.options.layout){case 0:return e=1/o,new u.d(t*e,0);case 1:var a=Math.max(2,Math.ceil(Math.sqrt(o)));return i=t-(n=Math.floor(t/a))*a,e=1/a,new u.d(i*e,n*e);case 2:var s=this.options.colnum||1,d=Math.max(1,Math.ceil(o/s));return n=t-(i=Math.floor(t/d))*d,e=new u.d(1/s,1/d),new u.d(i*e.x,n*e.y)}return u.d.Zero()},r.prototype._updateMeshUV=function(t,e){var n=this.frames[e],i=t.getVerticesData(this.options.uvsIn||Oe.b.UVKind),o=[],a=0;i.length&&(a=i.length||0);for(var s=0;s<a;s+=2)o.push(i[s]*n.scale.x+n.offset.x,i[s+1]*n.scale.y+n.offset.y);t.setVerticesData(this.options.uvsOut||Oe.b.UVKind,o)},r.prototype._updateTextureReferences=function(t,e){e===void 0&&(e=!1);for(var n=t.material,i=Object.keys(this.sets),o=function(d){d.dispose&&d.dispose()},a=0;a<i.length;a++){var s=i[a];if(e)n[s]!==null&&o(n[s]),n[s]=this.sets[s];else{if(!n)return;n[s]!==null&&(o(n[s]),n[s]=this.sets[s])}}},r.prototype.setMeshToFrame=function(t,e,n){n===void 0&&(n=!1),this._updateMeshUV(t,e),n&&this._updateTextureReferences(t,!0)},r.prototype.processAsync=function(){var t=this;return new Promise(function(e,n){try{if(t.meshes.length===0)return void e();for(var i=0,o=function(d){var p=t.meshes[d],b=p.material;if(!b)return++i===t.meshes.length?{value:t._createFrames(e)}:"continue";b.forceCompilationAsync(p).then(function(){(function(P){if(i++,t.options.map){for(var O=0;O<t.options.map.length;O++)P[t.options.map[O]]!==null&&(t.sets[t.options.map[O]]||(t.sets[t.options.map[O]]=!0),t._expecting++);i===t.meshes.length&&t._createFrames(e)}})(b)})},a=0;a<t.meshes.length;a++){var s=o(a);if(typeof s=="object")return s.value}}catch(d){return n(d)}})},r.prototype.dispose=function(){for(var t=Object.keys(this.sets),e=0;e<t.length;e++){var n=t[e];this.sets[n].dispose()}},r.prototype.download=function(t,e){var n=this;t===void 0&&(t="png"),e===void 0&&(e=1),setTimeout(function(){var i={name:n.name,sets:{},options:{},frames:[]},o=Object.keys(n.sets),a=Object.keys(n.options);try{for(var s=0;s<o.length;s++){var d=o[s],p=n.sets[d];i.sets[d]=p.getContext().canvas.toDataURL("image/"+t,e)}for(s=0;s<a.length;s++){var b=a[s];i.options[b]=n.options[b]}for(s=0;s<n.frames.length;s++){var P=n.frames[s];i.frames.push(P.scale.x,P.scale.y,P.offset.x,P.offset.y)}}catch(F){return void l.a.Warn("Unable to download: "+F)}var O="data:text/json;charset=utf-8,"+encodeURIComponent(JSON.stringify(i,null,4)),B=document.createElement("a");B.setAttribute("href",O),B.setAttribute("download",n.name+"_texurePackage.json"),document.body.appendChild(B),B.click(),B.remove()},0)},r.prototype.updateFromJSON=function(t){try{var e=JSON.parse(t);this.name=e.name;for(var n=Object.keys(e.options),i=0;i<n.length;i++)this.options[n[i]]=e.options[n[i]];for(i=0;i<e.frames.length;i+=4){var o=new $s(i/4,new u.d(e.frames[i],e.frames[i+1]),new u.d(e.frames[i+2],e.frames[i+3]));this.frames.push(o)}var a=Object.keys(e.sets);for(i=0;i<a.length;i++){var s=new we.a(e.sets[a[i]],this.scene,!1,!1);this.sets[a[i]]=s}}catch(d){l.a.Warn("Unable to update from JSON: "+d)}},r.LAYOUT_STRIP=0,r.LAYOUT_POWER2=1,r.LAYOUT_COLNUM=2,r.SUBUV_WRAP=0,r.SUBUV_EXTEND=1,r.SUBUV_COLOR=2,r}(),lh=function(){function r(t){this.name=at.a.NAME_PROCEDURALTEXTURE,this.scene=t,this.scene.proceduralTextures=new Array}return r.prototype.register=function(){this.scene._beforeClearStage.registerStep(at.a.STEP_BEFORECLEAR_PROCEDURALTEXTURE,this,this._beforeClear)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){},r.prototype._beforeClear=function(){if(this.scene.proceduralTexturesEnabled){Xe.b.StartPerformanceCounter("Procedural textures",this.scene.proceduralTextures.length>0);for(var t=0;t<this.scene.proceduralTextures.length;t++){var e=this.scene.proceduralTextures[t];e._shouldRender()&&e.render()}Xe.b.EndPerformanceCounter("Procedural textures",this.scene.proceduralTextures.length>0)}},r}(),nm=`
-attribute vec2 position;
-
-varying vec2 vPosition;
-varying vec2 vUV;
-const vec2 madd=vec2(0.5,0.5);
-void main(void) {
-vPosition=position;
-vUV=position*madd+madd;
-gl_Position=vec4(position,0.0,1.0);
-}`;ze.a.ShadersStore.proceduralVertexShader=nm;var go=function(r){function t(e,n,i,o,a,s,d,p){a===void 0&&(a=null),s===void 0&&(s=!0),d===void 0&&(d=!1),p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT);var b=r.call(this,null,o,!s)||this;b.isEnabled=!0,b.autoClear=!0,b.onGeneratedObservable=new C.c,b.onBeforeGenerationObservable=new C.c,b.nodeMaterialSource=null,b._textures={},b._currentRefreshId=-1,b._frameId=-1,b._refreshRate=1,b._vertexBuffers={},b._uniforms=new Array,b._samplers=new Array,b._floats={},b._ints={},b._floatsArrays={},b._colors3={},b._colors4={},b._vectors2={},b._vectors3={},b._matrices={},b._fallbackTextureUsed=!1,b._cachedDefines="",b._contentUpdateId=-1;var P=(o=b.getScene()||te.a.LastCreatedScene)._getComponent(at.a.NAME_PROCEDURALTEXTURE);P||(P=new lh(o),o._addComponent(P)),o.proceduralTextures.push(b),b._fullEngine=o.getEngine(),b.name=e,b.isRenderTarget=!0,b._size=n,b._generateMipMaps=s,b.setFragment(i),b._fallbackTexture=a,d?(b._texture=b._fullEngine.createRenderTargetCubeTexture(n,{generateMipMaps:s,generateDepthBuffer:!1,generateStencilBuffer:!1,type:p}),b.setFloat("face",0)):b._texture=b._fullEngine.createRenderTargetTexture(n,{generateMipMaps:s,generateDepthBuffer:!1,generateStencilBuffer:!1,type:p});var O=[];return O.push(1,1),O.push(-1,1),O.push(-1,-1),O.push(1,-1),b._vertexBuffers[Oe.b.PositionKind]=new Oe.b(b._fullEngine,O,Oe.b.PositionKind,!1,!1,2),b._createIndexBuffer(),b}return Object(c.d)(t,r),t.prototype.getEffect=function(){return this._effect},t.prototype.getContent=function(){return this._contentData&&this._frameId===this._contentUpdateId||(this._contentData=this.readPixels(0,0,this._contentData),this._contentUpdateId=this._frameId),this._contentData},t.prototype._createIndexBuffer=function(){var e=this._fullEngine,n=[];n.push(0),n.push(1),n.push(2),n.push(0),n.push(2),n.push(3),this._indexBuffer=e.createIndexBuffer(n)},t.prototype._rebuild=function(){var e=this._vertexBuffers[Oe.b.PositionKind];e&&e._rebuild(),this._createIndexBuffer(),this.refreshRate===sn.REFRESHRATE_RENDER_ONCE&&(this.refreshRate=sn.REFRESHRATE_RENDER_ONCE)},t.prototype.reset=function(){this._effect!==void 0&&this._effect.dispose()},t.prototype._getDefines=function(){return""},t.prototype.isReady=function(){var e,n=this,i=this._fullEngine;if(this.nodeMaterialSource)return this._effect.isReady();if(!this._fragment)return!1;if(this._fallbackTextureUsed)return!0;var o=this._getDefines();return!(!this._effect||o!==this._cachedDefines||!this._effect.isReady())||(e=this._fragment.fragmentElement!==void 0?{vertex:"procedural",fragmentElement:this._fragment.fragmentElement}:{vertex:"procedural",fragment:this._fragment},this._cachedDefines=o,this._effect=i.createEffect(e,[Oe.b.PositionKind],this._uniforms,this._samplers,o,void 0,void 0,function(){n.releaseInternalTexture(),n._fallbackTexture&&(n._texture=n._fallbackTexture._texture,n._texture&&n._texture.incrementReferences()),n._fallbackTextureUsed=!0}),this._effect.isReady())},t.prototype.resetRefreshCounter=function(){this._currentRefreshId=-1},t.prototype.setFragment=function(e){this._fragment=e},Object.defineProperty(t.prototype,"refreshRate",{get:function(){return this._refreshRate},set:function(e){this._refreshRate=e,this.resetRefreshCounter()},enumerable:!1,configurable:!0}),t.prototype._shouldRender=function(){return this.isEnabled&&this.isReady()&&this._texture?!this._fallbackTextureUsed&&(this._currentRefreshId===-1||this.refreshRate===this._currentRefreshId?(this._currentRefreshId=1,this._frameId++,!0):(this._currentRefreshId++,!1)):(this._texture&&(this._texture.isReady=!1),!1)},t.prototype.getRenderSize=function(){return this._size},t.prototype.resize=function(e,n){this._fallbackTextureUsed||(this.releaseInternalTexture(),this._texture=this._fullEngine.createRenderTargetTexture(e,n),this._size=e,this._generateMipMaps=n)},t.prototype._checkUniform=function(e){this._uniforms.indexOf(e)===-1&&this._uniforms.push(e)},t.prototype.setTexture=function(e,n){return this._samplers.indexOf(e)===-1&&this._samplers.push(e),this._textures[e]=n,this},t.prototype.setFloat=function(e,n){return this._checkUniform(e),this._floats[e]=n,this},t.prototype.setInt=function(e,n){return this._checkUniform(e),this._ints[e]=n,this},t.prototype.setFloats=function(e,n){return this._checkUniform(e),this._floatsArrays[e]=n,this},t.prototype.setColor3=function(e,n){return this._checkUniform(e),this._colors3[e]=n,this},t.prototype.setColor4=function(e,n){return this._checkUniform(e),this._colors4[e]=n,this},t.prototype.setVector2=function(e,n){return this._checkUniform(e),this._vectors2[e]=n,this},t.prototype.setVector3=function(e,n){return this._checkUniform(e),this._vectors3[e]=n,this},t.prototype.setMatrix=function(e,n){return this._checkUniform(e),this._matrices[e]=n,this},t.prototype.render=function(e){var n=this.getScene();if(n){var i=this._fullEngine;if(i.enableEffect(this._effect),this.onBeforeGenerationObservable.notifyObservers(this),i.setState(!1),!this.nodeMaterialSource){for(var o in this._textures)this._effect.setTexture(o,this._textures[o]);for(o in this._ints)this._effect.setInt(o,this._ints[o]);for(o in this._floats)this._effect.setFloat(o,this._floats[o]);for(o in this._floatsArrays)this._effect.setArray(o,this._floatsArrays[o]);for(o in this._colors3)this._effect.setColor3(o,this._colors3[o]);for(o in this._colors4){var a=this._colors4[o];this._effect.setFloat4(o,a.r,a.g,a.b,a.a)}for(o in this._vectors2)this._effect.setVector2(o,this._vectors2[o]);for(o in this._vectors3)this._effect.setVector3(o,this._vectors3[o]);for(o in this._matrices)this._effect.setMatrix(o,this._matrices[o])}if(this._texture){if(this.isCube)for(var s=0;s<6;s++)i.bindFramebuffer(this._texture,s,void 0,void 0,!0),i.bindBuffers(this._vertexBuffers,this._indexBuffer,this._effect),this._effect.setFloat("face",s),this.autoClear&&i.clear(n.clearColor,!0,!1,!1),i.drawElementsType(Ht.a.TriangleFillMode,0,6),s===5&&i.generateMipMapsForCubemap(this._texture);else i.bindFramebuffer(this._texture,0,void 0,void 0,!0),i.bindBuffers(this._vertexBuffers,this._indexBuffer,this._effect),this.autoClear&&i.clear(n.clearColor,!0,!1,!1),i.drawElementsType(Ht.a.TriangleFillMode,0,6);i.unBindFramebuffer(this._texture,this.isCube),this.onGenerated&&this.onGenerated(),this.onGeneratedObservable.notifyObservers(this)}}},t.prototype.clone=function(){var e=this.getSize(),n=new t(this.name,e.width,this._fragment,this.getScene(),this._fallbackTexture,this._generateMipMaps);return n.hasAlpha=this.hasAlpha,n.level=this.level,n.coordinatesMode=this.coordinatesMode,n},t.prototype.dispose=function(){var e=this.getScene();if(e){var n=e.proceduralTextures.indexOf(this);n>=0&&e.proceduralTextures.splice(n,1);var i=this._vertexBuffers[Oe.b.PositionKind];i&&(i.dispose(),this._vertexBuffers[Oe.b.PositionKind]=null),this._indexBuffer&&this._fullEngine._releaseBuffer(this._indexBuffer)&&(this._indexBuffer=null),this.onGeneratedObservable.clear(),this.onBeforeGenerationObservable.clear(),r.prototype.dispose.call(this)}},Object(c.c)([Object(L.c)()],t.prototype,"isEnabled",void 0),Object(c.c)([Object(L.c)()],t.prototype,"autoClear",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_generateMipMaps",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_size",void 0),Object(c.c)([Object(L.c)()],t.prototype,"refreshRate",null),t}(we.a);R.a.RegisteredTypes["BABYLON.ProceduralTexture"]=go;var im=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,i,null,o,a,s)||this;return d._animate=!0,d._time=0,d._texturePath=n,d._loadJson(n),d.refreshRate=1,d}return Object(c.d)(t,r),t.prototype._loadJson=function(e){var n=this,i=function(){try{n.setFragment(n._texturePath)}catch{l.a.Error("No json or ShaderStore or DOM element found for CustomProceduralTexture")}},o=e+"/config.json",a=new re.a;a.open("GET",o),a.addEventListener("load",function(){if(a.status===200||a.responseText&&a.responseText.length>0)try{n._config=JSON.parse(a.response),n.updateShaderUniforms(),n.updateTextures(),n.setFragment(n._texturePath+"/custom"),n._animate=n._config.animate,n.refreshRate=n._config.refreshrate}catch{i()}else i()},!1),a.addEventListener("error",function(){i()},!1);try{a.send()}catch{l.a.Error("CustomProceduralTexture: Error on XHR send request.")}},t.prototype.isReady=function(){if(!r.prototype.isReady.call(this))return!1;for(var e in this._textures)if(!this._textures[e].isReady())return!1;return!0},t.prototype.render=function(e){var n=this.getScene();this._animate&&n&&(this._time+=.03*n.getAnimationRatio(),this.updateShaderUniforms()),r.prototype.render.call(this,e)},t.prototype.updateTextures=function(){for(var e=0;e<this._config.sampler2Ds.length;e++)this.setTexture(this._config.sampler2Ds[e].sample2Dname,new we.a(this._texturePath+"/"+this._config.sampler2Ds[e].textureRelativeUrl,this.getScene()))},t.prototype.updateShaderUniforms=function(){if(this._config)for(var e=0;e<this._config.uniforms.length;e++){var n=this._config.uniforms[e];switch(n.type){case"float":this.setFloat(n.name,n.value);break;case"color3":this.setColor3(n.name,new M.a(n.r,n.g,n.b));break;case"color4":this.setColor4(n.name,new M.b(n.r,n.g,n.b,n.a));break;case"vector2":this.setVector2(n.name,new u.d(n.x,n.y));break;case"vector3":this.setVector3(n.name,new u.e(n.x,n.y,n.z))}}this.setFloat("time",this._time)},Object.defineProperty(t.prototype,"animate",{get:function(){return this._animate},set:function(e){this._animate=e},enumerable:!1,configurable:!0}),t}(go),rm=`
-
-uniform float brightness;
-uniform float persistence;
-uniform float timeScale;
-
-varying vec2 vUV;
-
-vec2 hash22(vec2 p)
-{
-p=p*mat2(127.1,311.7,269.5,183.3);
-p=-1.0+2.0*fract(sin(p)*43758.5453123);
-return sin(p*6.283+timeScale);
-}
-float interpolationNoise(vec2 p)
-{
-vec2 pi=floor(p);
-vec2 pf=p-pi;
-vec2 w=pf*pf*(3.-2.*pf);
-float f00=dot(hash22(pi+vec2(.0,.0)),pf-vec2(.0,.0));
-float f01=dot(hash22(pi+vec2(.0,1.)),pf-vec2(.0,1.));
-float f10=dot(hash22(pi+vec2(1.0,0.)),pf-vec2(1.0,0.));
-float f11=dot(hash22(pi+vec2(1.0,1.)),pf-vec2(1.0,1.));
-float xm1=mix(f00,f10,w.x);
-float xm2=mix(f01,f11,w.x);
-float ym=mix(xm1,xm2,w.y);
-return ym;
-}
-float perlinNoise2D(float x,float y)
-{
-float sum=0.0;
-float frequency=0.0;
-float amplitude=0.0;
-for(int i=0; i<OCTAVES; i++)
-{
-frequency=pow(2.0,float(i));
-amplitude=pow(persistence,float(i));
-sum=sum+interpolationNoise(vec2(x*frequency,y*frequency))*amplitude;
-}
-return sum;
-}
-
-void main(void)
-{
-float x=abs(vUV.x);
-float y=abs(vUV.y);
-float noise=brightness+(1.0-brightness)*perlinNoise2D(x,y);
-gl_FragColor=vec4(noise,noise,noise,1.0);
-}
-`;ze.a.ShadersStore.noisePixelShader=rm;var uh=function(r){function t(e,n,i,o,a){n===void 0&&(n=256),i===void 0&&(i=te.a.LastCreatedScene);var s=r.call(this,e,n,"noise",i,o,a)||this;return s.time=0,s.brightness=.2,s.octaves=3,s.persistence=.8,s.animationSpeedFactor=1,s.autoClear=!1,s._updateShaderUniforms(),s}return Object(c.d)(t,r),t.prototype._updateShaderUniforms=function(){var e=this.getScene();e&&(this.time+=e.getAnimationRatio()*this.animationSpeedFactor*.01,this.setFloat("brightness",this.brightness),this.setFloat("persistence",this.persistence),this.setFloat("timeScale",this.time))},t.prototype._getDefines=function(){return"#define OCTAVES "+(0|this.octaves)},t.prototype.render=function(e){this._updateShaderUniforms(),r.prototype.render.call(this,e)},t.prototype.serialize=function(){var e={customType:"BABYLON.NoiseProceduralTexture"};return e.brightness=this.brightness,e.octaves=this.octaves,e.persistence=this.persistence,e.animationSpeedFactor=this.animationSpeedFactor,e.size=this.getSize().width,e.generateMipMaps=this._generateMipMaps,e.time=this.time,e},t.prototype.clone=function(){var e=this.getSize(),n=new t(this.name,e.width,this.getScene(),this._fallbackTexture?this._fallbackTexture:void 0,this._generateMipMaps);return n.hasAlpha=this.hasAlpha,n.level=this.level,n.coordinatesMode=this.coordinatesMode,n.brightness=this.brightness,n.octaves=this.octaves,n.persistence=this.persistence,n.animationSpeedFactor=this.animationSpeedFactor,n.time=this.time,n},t.Parse=function(e,n){var i,o=new t(e.name,e.size,n,void 0,e.generateMipMaps);return o.brightness=e.brightness,o.octaves=e.octaves,o.persistence=e.persistence,o.animationSpeedFactor=e.animationSpeedFactor,o.time=(i=e.time)!==null&&i!==void 0?i:0,o},t}(go);R.a.RegisteredTypes["BABYLON.NoiseProceduralTexture"]=uh;var Ce,le,bn,bt,Mn,ci,Tn,om=function(r){function t(e,n,i,o,a,s,d,p,b){o===void 0&&(o=h.a.TEXTUREFORMAT_RGBA),a===void 0&&(a=h.a.TEXTURETYPE_UNSIGNED_INT),s===void 0&&(s=!1),d===void 0&&(d=!1),p===void 0&&(p=h.a.TEXTURE_TRILINEAR_SAMPLINGMODE),b===void 0&&(b=null);var P=r.call(this,"",e)||this;return P._texture=e.getEngine().createRawCubeTexture(n,i,o,a,s,d,p,b),P}return Object(c.d)(t,r),t.prototype.update=function(e,n,i,o,a){a===void 0&&(a=null),this._texture.getEngine().updateRawCubeTexture(this._texture,e,n,i,o,a)},t.prototype.updateRGBDAsync=function(e,n,i,o){return n===void 0&&(n=null),i===void 0&&(i=.8),o===void 0&&(o=0),t._UpdateRGBDAsync(this._texture,e,n,i,o)},t.prototype.clone=function(){var e=this;return L.a.Clone(function(){var n=e.getScene(),i=e._texture,o=new t(n,i._bufferViewArray,i.width,i.format,i.type,i.generateMipMaps,i.invertY,i.samplingMode,i._compression);return i.source===Ct.b.CubeRawRGBD&&o.updateRGBDAsync(i._bufferViewArrayArray,i._sphericalPolynomial,i._lodGenerationScale,i._lodGenerationOffset),o},this)},t._UpdateRGBDAsync=function(e,n,i,o,a){return e._source=Ct.b.CubeRawRGBD,e._bufferViewArrayArray=n,e._lodGenerationScale=o,e._lodGenerationOffset=a,e._sphericalPolynomial=i,Ai.UploadLevelsAsync(e,n).then(function(){e.isReady=!0})},t}(oi),am=function(r){function t(e,n,i,o,a,s,d,p,b,P){d===void 0&&(d=!0),p===void 0&&(p=!1),b===void 0&&(b=we.a.TRILINEAR_SAMPLINGMODE),P===void 0&&(P=h.a.TEXTURETYPE_UNSIGNED_INT);var O=r.call(this,null,s,!d,p)||this;return O.format=a,O._texture=s.getEngine().createRawTexture2DArray(e,n,i,o,a,d,p,b,null,P),O.is2DArray=!0,O}return Object(c.d)(t,r),t.prototype.update=function(e){this._texture&&this._getEngine().updateRawTexture2DArray(this._texture,e,this._texture.format,this._texture.invertY,null,this._texture.type)},t}(we.a),sm=function(r){function t(e,n,i,o,a,s,d,p,b,P){d===void 0&&(d=!0),p===void 0&&(p=!1),b===void 0&&(b=we.a.TRILINEAR_SAMPLINGMODE),P===void 0&&(P=h.a.TEXTURETYPE_UNSIGNED_INT);var O=r.call(this,null,s,!d,p)||this;return O.format=a,O._texture=s.getEngine().createRawTexture3D(e,n,i,o,a,d,p,b,null,P),O.is3D=!0,O}return Object(c.d)(t,r),t.prototype.update=function(e){this._texture&&this._getEngine().updateRawTexture3D(this._texture,e,this._texture.format,this._texture.invertY,null,this._texture.type)},t}(we.a),cm=function(r){function t(e,n,i,o){var a=r.call(this,e,n,i,o,!0)||this;return a.refractionPlane=new vr.a(0,1,0,1),a.depth=2,a.onBeforeRenderObservable.add(function(){i.clipPlane=a.refractionPlane}),a.onAfterRenderObservable.add(function(){i.clipPlane=null}),a}return Object(c.d)(t,r),t.prototype.clone=function(){var e=this.getScene();if(!e)return this;var n=this.getSize(),i=new t(this.name,n.width,e,this._generateMipMaps);return i.hasAlpha=this.hasAlpha,i.level=this.level,i.refractionPlane=this.refractionPlane.clone(),this.renderList&&(i.renderList=this.renderList.slice(0)),i.depth=this.depth,i},t.prototype.serialize=function(){if(!this.name)return null;var e=r.prototype.serialize.call(this);return e.mirrorPlane=this.refractionPlane.asArray(),e.depth=this.depth,e},t}(sn);(function(r){r[r.Vertex=1]="Vertex",r[r.Fragment=2]="Fragment",r[r.Neutral=4]="Neutral",r[r.VertexAndFragment=3]="VertexAndFragment"})(Ce||(Ce={})),function(r){r[r.Float=1]="Float",r[r.Int=2]="Int",r[r.Vector2=4]="Vector2",r[r.Vector3=8]="Vector3",r[r.Vector4=16]="Vector4",r[r.Color3=32]="Color3",r[r.Color4=64]="Color4",r[r.Matrix=128]="Matrix",r[r.Object=256]="Object",r[r.AutoDetect=1024]="AutoDetect",r[r.BasedOnInput=2048]="BasedOnInput"}(le||(le={})),function(r){r[r.Uniform=0]="Uniform",r[r.Attribute=1]="Attribute",r[r.Varying=2]="Varying",r[r.Undefined=3]="Undefined"}(bn||(bn={})),function(r){r[r.World=1]="World",r[r.View=2]="View",r[r.Projection=3]="Projection",r[r.ViewProjection=4]="ViewProjection",r[r.WorldView=5]="WorldView",r[r.WorldViewProjection=6]="WorldViewProjection",r[r.CameraPosition=7]="CameraPosition",r[r.FogColor=8]="FogColor",r[r.DeltaTime=9]="DeltaTime"}(bt||(bt={})),function(r){r[r.Material=0]="Material",r[r.PostProcess=1]="PostProcess",r[r.Particle=2]="Particle",r[r.ProceduralTexture=3]="ProceduralTexture"}(Mn||(Mn={})),function(r){r[r.Compatible=0]="Compatible",r[r.TypeIncompatible=1]="TypeIncompatible",r[r.TargetIncompatible=2]="TargetIncompatible"}(ci||(ci={})),function(r){r[r.Input=0]="Input",r[r.Output=1]="Output"}(Tn||(Tn={}));var da=function(){function r(t,e,n){this._connectedPoint=null,this._endpoints=new Array,this._typeConnectionSource=null,this._linkedConnectionSource=null,this._acceptedConnectionPointType=null,this._type=le.Float,this._enforceAssociatedVariableName=!1,this.needDualDirectionValidation=!1,this.acceptedConnectionPointTypes=new Array,this.excludedConnectionPointTypes=new Array,this.onConnectionObservable=new C.c,this.isExposedOnFrame=!1,this.exposedPortPosition=-1,this._prioritizeVertex=!1,this._target=Ce.VertexAndFragment,this._ownerBlock=e,this.name=t,this._direction=n}return r.AreEquivalentTypes=function(t,e){switch(t){case le.Vector3:if(e===le.Color3)return!0;break;case le.Vector4:if(e===le.Color4)return!0;break;case le.Color3:if(e===le.Vector3)return!0;break;case le.Color4:if(e===le.Vector4)return!0}return!1},Object.defineProperty(r.prototype,"direction",{get:function(){return this._direction},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"associatedVariableName",{get:function(){return this._ownerBlock.isInput?this._ownerBlock.associatedVariableName:this._enforceAssociatedVariableName&&this._associatedVariableName||!this._connectedPoint?this._associatedVariableName:this._connectedPoint.associatedVariableName},set:function(t){this._associatedVariableName=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"innerType",{get:function(){return this._linkedConnectionSource&&this._linkedConnectionSource.isConnected?this.type:this._type},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"type",{get:function(){if(this._type===le.AutoDetect){if(this._ownerBlock.isInput)return this._ownerBlock.type;if(this._connectedPoint)return this._connectedPoint.type;if(this._linkedConnectionSource&&this._linkedConnectionSource.isConnected)return this._linkedConnectionSource.type}return this._type===le.BasedOnInput&&this._typeConnectionSource?this._typeConnectionSource.type:this._type},set:function(t){this._type=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"target",{get:function(){return this._prioritizeVertex&&this._ownerBlock?this._target!==Ce.VertexAndFragment?this._target:this._ownerBlock.target===Ce.Fragment?Ce.Fragment:Ce.Vertex:this._target},set:function(t){this._target=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isConnected",{get:function(){return this.connectedPoint!==null||this.hasEndpoints},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isConnectedToInputBlock",{get:function(){return this.connectedPoint!==null&&this.connectedPoint.ownerBlock.isInput},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"connectInputBlock",{get:function(){return this.isConnectedToInputBlock?this.connectedPoint.ownerBlock:null},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"connectedPoint",{get:function(){return this._connectedPoint},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"ownerBlock",{get:function(){return this._ownerBlock},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"sourceBlock",{get:function(){return this._connectedPoint?this._connectedPoint.ownerBlock:null},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"connectedBlocks",{get:function(){return this._endpoints.length===0?[]:this._endpoints.map(function(t){return t.ownerBlock})},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"endpoints",{get:function(){return this._endpoints},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"hasEndpoints",{get:function(){return this._endpoints&&this._endpoints.length>0},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isConnectedInVertexShader",{get:function(){if(this.target===Ce.Vertex)return!0;if(!this.hasEndpoints)return!1;for(var t=0,e=this._endpoints;t<e.length;t++){var n=e[t];if(n.ownerBlock.target===Ce.Vertex||n.target===Ce.Vertex||(n.ownerBlock.target===Ce.Neutral||n.ownerBlock.target===Ce.VertexAndFragment)&&n.ownerBlock.outputs.some(function(i){return i.isConnectedInVertexShader}))return!0}return!1},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isConnectedInFragmentShader",{get:function(){if(this.target===Ce.Fragment)return!0;if(!this.hasEndpoints)return!1;for(var t=0,e=this._endpoints;t<e.length;t++){var n=e[t];if(n.ownerBlock.target===Ce.Fragment||(n.ownerBlock.target===Ce.Neutral||n.ownerBlock.target===Ce.VertexAndFragment)&&n.ownerBlock.outputs.some(function(i){return i.isConnectedInFragmentShader}))return!0}return!1},enumerable:!1,configurable:!0}),r.prototype.createCustomInputBlock=function(){return null},r.prototype.getClassName=function(){return"NodeMaterialConnectionPoint"},r.prototype.canConnectTo=function(t){return this.checkCompatibilityState(t)===ci.Compatible},r.prototype.checkCompatibilityState=function(t){if(this._ownerBlock.target===Ce.Fragment){var e=t.ownerBlock;if(e.target===Ce.Vertex)return ci.TargetIncompatible;for(var n=0,i=e.outputs;n<i.length;n++)if(i[n].isConnectedInVertexShader)return ci.TargetIncompatible}return this.type!==t.type&&t.innerType!==le.AutoDetect?r.AreEquivalentTypes(this.type,t.type)||t.acceptedConnectionPointTypes&&t.acceptedConnectionPointTypes.indexOf(this.type)!==-1||t._acceptedConnectionPointType&&r.AreEquivalentTypes(t._acceptedConnectionPointType.type,this.type)?ci.Compatible:ci.TypeIncompatible:t.excludedConnectionPointTypes&&t.excludedConnectionPointTypes.indexOf(this.type)!==-1?1:ci.Compatible},r.prototype.connectTo=function(t,e){if(e===void 0&&(e=!1),!e&&!this.canConnectTo(t))throw"Cannot connect these two connectors.";return this._endpoints.push(t),t._connectedPoint=this,this._enforceAssociatedVariableName=!1,this.onConnectionObservable.notifyObservers(t),t.onConnectionObservable.notifyObservers(this),this},r.prototype.disconnectFrom=function(t){var e=this._endpoints.indexOf(t);return e===-1||(this._endpoints.splice(e,1),t._connectedPoint=null,this._enforceAssociatedVariableName=!1,t._enforceAssociatedVariableName=!1),this},r.prototype.serialize=function(t){t===void 0&&(t=!0);var e={};return e.name=this.name,e.displayName=this.displayName,t&&this.connectedPoint&&(e.inputName=this.name,e.targetBlockId=this.connectedPoint.ownerBlock.uniqueId,e.targetConnectionName=this.connectedPoint.name,e.isExposedOnFrame=!0,e.exposedPortPosition=this.exposedPortPosition),(this.isExposedOnFrame||this.exposedPortPosition>=0)&&(e.isExposedOnFrame=!0,e.exposedPortPosition=this.exposedPortPosition),e},r.prototype.dispose=function(){this.onConnectionObservable.clear()},r}(),lm=f(152),pt=function(){function r(t,e,n,i){e===void 0&&(e=Ce.Vertex),n===void 0&&(n=!1),i===void 0&&(i=!1),this._isFinalMerger=!1,this._isInput=!1,this._name="",this._isUnique=!1,this.inputsAreExclusive=!1,this._codeVariableName="",this._inputs=new Array,this._outputs=new Array,this.comments="",this.visibleInInspector=!1,this._target=e,this._isFinalMerger=n,this._isInput=i,this._name=t,this.uniqueId=lm.a.UniqueId}return Object.defineProperty(r.prototype,"name",{get:function(){return this._name},set:function(t){this.validateBlockName(t)&&(this._name=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isUnique",{get:function(){return this._isUnique},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isFinalMerger",{get:function(){return this._isFinalMerger},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isInput",{get:function(){return this._isInput},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"buildId",{get:function(){return this._buildId},set:function(t){this._buildId=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"target",{get:function(){return this._target},set:function(t){!(this._target&t)&&(this._target=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"inputs",{get:function(){return this._inputs},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"outputs",{get:function(){return this._outputs},enumerable:!1,configurable:!0}),r.prototype.getInputByName=function(t){var e=this._inputs.filter(function(n){return n.name===t});return e.length?e[0]:null},r.prototype.getOutputByName=function(t){var e=this._outputs.filter(function(n){return n.name===t});return e.length?e[0]:null},r.prototype.initialize=function(t){},r.prototype.bind=function(t,e,n,i){},r.prototype._declareOutput=function(t,e){return e._getGLType(t.type)+" "+t.associatedVariableName},r.prototype._writeVariable=function(t){return t.connectedPoint?""+t.associatedVariableName:"0."},r.prototype._writeFloat=function(t){var e=t.toString();return e.indexOf(".")===-1&&(e+=".0"),""+e},r.prototype.getClassName=function(){return"NodeMaterialBlock"},r.prototype.registerInput=function(t,e,n,i,o){return n===void 0&&(n=!1),(o=o??new da(t,this,Tn.Input)).type=e,o.isOptional=n,i&&(o.target=i),this._inputs.push(o),this},r.prototype.registerOutput=function(t,e,n,i){return(i=i??new da(t,this,Tn.Output)).type=e,n&&(i.target=n),this._outputs.push(i),this},r.prototype.getFirstAvailableInput=function(t){t===void 0&&(t=null);for(var e=0,n=this._inputs;e<n.length;e++){var i=n[e];if(!(i.connectedPoint||t&&t.type!==i.type&&i.type!==le.AutoDetect))return i}return null},r.prototype.getFirstAvailableOutput=function(t){t===void 0&&(t=null);for(var e=0,n=this._outputs;e<n.length;e++){var i=n[e];if(!t||!t.target||t.target===Ce.Neutral||t.target&i.target)return i}return null},r.prototype.getSiblingOutput=function(t){var e=this._outputs.indexOf(t);return e===-1||e>=this._outputs.length?null:this._outputs[e+1]},r.prototype.connectTo=function(t,e){if(this._outputs.length!==0){for(var n=e&&e.output?this.getOutputByName(e.output):this.getFirstAvailableOutput(t),i=!0;i;){var o=e&&e.input?t.getInputByName(e.input):t.getFirstAvailableInput(n);if(n&&o&&n.canConnectTo(o))n.connectTo(o),i=!1;else{if(!n)throw"Unable to find a compatible match";n=this.getSiblingOutput(n)}}return this}},r.prototype._buildBlock=function(t){},r.prototype.updateUniformsAndSamples=function(t,e,n,i){},r.prototype.provideFallbacks=function(t,e){},r.prototype.initializeDefines=function(t,e,n,i){},r.prototype.prepareDefines=function(t,e,n,i,o){},r.prototype.autoConfigure=function(t){},r.prototype.replaceRepeatableContent=function(t,e,n,i){},r.prototype.isReady=function(t,e,n,i){return!0},r.prototype._linkConnectionTypes=function(t,e,n){n===void 0&&(n=!1),n?this._inputs[e]._acceptedConnectionPointType=this._inputs[t]:this._inputs[t]._linkedConnectionSource=this._inputs[e],this._inputs[e]._linkedConnectionSource=this._inputs[t]},r.prototype._processBuild=function(t,e,n,i){t.build(e,i);var o=e._vertexState!=null,a=t._buildTarget===Ce.Vertex&&t.target!==Ce.VertexAndFragment;if(o&&(!(t.target&t._buildTarget)||!(t.target&n.target)||this.target!==Ce.VertexAndFragment&&a)&&(!t.isInput&&e.target!==t._buildTarget||t.isInput&&t.isAttribute&&!t._noContextSwitch)){var s=n.connectedPoint;e._vertexState._emitVaryingFromString("v_"+s.associatedVariableName,e._getGLType(s.type))&&(e._vertexState.compilationString+="v_"+s.associatedVariableName+" = "+s.associatedVariableName+`;\r
-`),n.associatedVariableName="v_"+s.associatedVariableName,n._enforceAssociatedVariableName=!0}},r.prototype.validateBlockName=function(t){for(var e=0,n=["position","normal","tangent","particle_positionw","uv","uv2","position2d","particle_uv","matricesIndices","matricesWeights","world0","world1","world2","world3","particle_color","particle_texturemask"];e<n.length;e++)if(t===n[e])return!1;return!0},r.prototype.build=function(t,e){if(this._buildId===t.sharedData.buildId)return!0;if(!this.isInput)for(var n=0,i=this._outputs;n<i.length;n++)(b=i[n]).associatedVariableName||(b.associatedVariableName=t._getFreeVariableName(b.name));for(var o=0,a=this._inputs;o<a.length;o++){var s=a[o];if(s.connectedPoint){if(this.target!==Ce.Neutral&&(!(s.target&this.target)||!(s.target&t.target)))continue;(B=s.connectedPoint.ownerBlock)&&B!==this&&this._processBuild(B,t,s,e)}else s.isOptional||t.sharedData.checks.notConnectedNonOptionalInputs.push(s)}if(this._buildId===t.sharedData.buildId)return!0;if(t.sharedData.verbose&&console.log((t.target===Ce.Vertex?"Vertex shader":"Fragment shader")+": Building "+this.name+" ["+this.getClassName()+"]"),this.isFinalMerger)switch(t.target){case Ce.Vertex:t.sharedData.checks.emitVertex=!0;break;case Ce.Fragment:t.sharedData.checks.emitFragment=!0}!this.isInput&&t.sharedData.emitComments&&(t.compilationString+=`\r
-//`+this.name+`\r
-`),this._buildBlock(t),this._buildId=t.sharedData.buildId,this._buildTarget=t.target;for(var d=0,p=this._outputs;d<p.length;d++){var b;if((b=p[d]).target&t.target)for(var P=0,O=b.endpoints;P<O.length;P++){var B,F=O[P];(B=F.ownerBlock)&&B.target&t.target&&e.indexOf(B)!==-1&&this._processBuild(B,t,F,e)}}return!1},r.prototype._inputRename=function(t){return t},r.prototype._outputRename=function(t){return t},r.prototype._dumpPropertiesCode=function(){return this._codeVariableName+".visibleInInspector = "+this.visibleInInspector+`;\r
-`},r.prototype._dumpCode=function(t,e){var n;e.push(this);var i=this.name.replace(/[^A-Za-z_]+/g,"");if(this._codeVariableName=i||this.getClassName()+"_"+this.uniqueId,t.indexOf(this._codeVariableName)!==-1){var o=0;do o++,this._codeVariableName=i+o;while(t.indexOf(this._codeVariableName)!==-1)}t.push(this._codeVariableName),n=`\r
-// `+this.getClassName()+`\r
-`,this.comments&&(n+="// "+this.comments+`\r
-`),n+="var "+this._codeVariableName+" = new BABYLON."+this.getClassName()+'("'+this.name+`");\r
-`,n+=this._dumpPropertiesCode();for(var a=0,s=this.inputs;a<s.length;a++){var d=s[a];if(d.isConnected){var p=d.connectedPoint.ownerBlock;e.indexOf(p)===-1&&(n+=p._dumpCode(t,e))}}for(var b=0,P=this.outputs;b<P.length;b++){var O=P[b];if(O.hasEndpoints)for(var B=0,F=O.endpoints;B<F.length;B++)(p=F[B].ownerBlock)&&e.indexOf(p)===-1&&(n+=p._dumpCode(t,e))}return n},r.prototype._dumpCodeForOutputConnections=function(t){var e="";if(t.indexOf(this)!==-1)return e;t.push(this);for(var n=0,i=this.inputs;n<i.length;n++){var o=i[n];if(o.isConnected){var a=o.connectedPoint,s=a.ownerBlock;e+=s._dumpCodeForOutputConnections(t),e+=s._codeVariableName+"."+s._outputRename(a.name)+".connectTo("+this._codeVariableName+"."+this._inputRename(o.name)+`);\r
-`}}return e},r.prototype.clone=function(t,e){e===void 0&&(e="");var n=this.serialize(),i=R.a.GetClass(n.customType);if(i){var o=new i;return o._deserialize(n,t,e),o}return null},r.prototype.serialize=function(){var t={};t.customType="BABYLON."+this.getClassName(),t.id=this.uniqueId,t.name=this.name,t.comments=this.comments,t.visibleInInspector=this.visibleInInspector,t.inputs=[],t.outputs=[];for(var e=0,n=this.inputs;e<n.length;e++){var i=n[e];t.inputs.push(i.serialize())}for(var o=0,a=this.outputs;o<a.length;o++){var s=a[o];t.outputs.push(s.serialize(!1))}return t},r.prototype._deserialize=function(t,e,n){this.name=t.name,this.comments=t.comments,this.visibleInInspector=!!t.visibleInInspector,this._deserializePortDisplayNamesAndExposedOnFrame(t)},r.prototype._deserializePortDisplayNamesAndExposedOnFrame=function(t){var e=this,n=t.inputs,i=t.outputs;n&&n.forEach(function(o,a){o.displayName&&(e.inputs[a].displayName=o.displayName),o.isExposedOnFrame&&(e.inputs[a].isExposedOnFrame=o.isExposedOnFrame,e.inputs[a].exposedPortPosition=o.exposedPortPosition)}),i&&i.forEach(function(o,a){o.displayName&&(e.outputs[a].displayName=o.displayName),o.isExposedOnFrame&&(e.outputs[a].isExposedOnFrame=o.isExposedOnFrame,e.outputs[a].exposedPortPosition=o.exposedPortPosition)})},r.prototype.dispose=function(){for(var t=0,e=this.inputs;t<e.length;t++)e[t].dispose();for(var n=0,i=this.outputs;n<i.length;n++)i[n].dispose()},r}(),hh=function(){function r(){this.supportUniformBuffers=!1,this.attributes=new Array,this.uniforms=new Array,this.constants=new Array,this.samplers=new Array,this.functions={},this.extensions={},this.counters={},this._attributeDeclaration="",this._uniformDeclaration="",this._constantDeclaration="",this._samplerDeclaration="",this._varyingTransfer="",this._injectAtEnd="",this._repeatableContentAnchorIndex=0,this._builtCompilationString="",this.compilationString=""}return r.prototype.finalize=function(t){var e=t.sharedData.emitComments,n=this.target===Ce.Fragment;this.compilationString=`\r
-`+(e?`//Entry point\r
-`:"")+`void main(void) {\r
-`+this.compilationString,this._constantDeclaration&&(this.compilationString=`\r
-`+(e?`//Constants\r
-`:"")+this._constantDeclaration+`\r
-`+this.compilationString);var i="";for(var o in this.functions)i+=this.functions[o]+`\r
-`;for(var a in this.compilationString=`\r
-`+i+`\r
-`+this.compilationString,!n&&this._varyingTransfer&&(this.compilationString=this.compilationString+`\r
-`+this._varyingTransfer),this._injectAtEnd&&(this.compilationString=this.compilationString+`\r
-`+this._injectAtEnd),this.compilationString=this.compilationString+`\r
-}`,this.sharedData.varyingDeclaration&&(this.compilationString=`\r
-`+(e?`//Varyings\r
-`:"")+this.sharedData.varyingDeclaration+`\r
-`+this.compilationString),this._samplerDeclaration&&(this.compilationString=`\r
-`+(e?`//Samplers\r
-`:"")+this._samplerDeclaration+`\r
-`+this.compilationString),this._uniformDeclaration&&(this.compilationString=`\r
-`+(e?`//Uniforms\r
-`:"")+this._uniformDeclaration+`\r
-`+this.compilationString),this._attributeDeclaration&&!n&&(this.compilationString=`\r
-`+(e?`//Attributes\r
-`:"")+this._attributeDeclaration+`\r
-`+this.compilationString),this.compilationString=`precision highp float;\r
-`+this.compilationString,this.extensions){var s=this.extensions[a];this.compilationString=`\r
-`+s+`\r
-`+this.compilationString}this._builtCompilationString=this.compilationString},Object.defineProperty(r.prototype,"_repeatableContentAnchor",{get:function(){return"###___ANCHOR"+this._repeatableContentAnchorIndex+++"___###"},enumerable:!1,configurable:!0}),r.prototype._getFreeVariableName=function(t){return t=t.replace(/[^a-zA-Z_]+/g,""),this.sharedData.variableNames[t]===void 0?(this.sharedData.variableNames[t]=0,t==="output"||t==="texture"?t+this.sharedData.variableNames[t]:t):(this.sharedData.variableNames[t]++,t+this.sharedData.variableNames[t])},r.prototype._getFreeDefineName=function(t){return this.sharedData.defineNames[t]===void 0?this.sharedData.defineNames[t]=0:this.sharedData.defineNames[t]++,t+this.sharedData.defineNames[t]},r.prototype._excludeVariableName=function(t){this.sharedData.variableNames[t]=0},r.prototype._emit2DSampler=function(t){this.samplers.indexOf(t)<0&&(this._samplerDeclaration+="uniform sampler2D "+t+`;\r
-`,this.samplers.push(t))},r.prototype._getGLType=function(t){switch(t){case le.Float:return"float";case le.Int:return"int";case le.Vector2:return"vec2";case le.Color3:case le.Vector3:return"vec3";case le.Color4:case le.Vector4:return"vec4";case le.Matrix:return"mat4"}return""},r.prototype._emitExtension=function(t,e,n){n===void 0&&(n=""),this.extensions[t]||(n&&(e="#if "+n+`\r
-`+e+`\r
-#endif`),this.extensions[t]=e)},r.prototype._emitFunction=function(t,e,n){this.functions[t]||(this.sharedData.emitComments&&(e=n+`\r
-`+e),this.functions[t]=e)},r.prototype._emitCodeFromInclude=function(t,e,n){if(n&&n.repeatKey)return"#include<"+t+">[0.."+n.repeatKey+`]\r
-`;var i=ze.a.IncludesShadersStore[t]+`\r
-`;if(this.sharedData.emitComments&&(i=e+`\r
-`+i),!n)return i;if(n.replaceStrings)for(var o=0;o<n.replaceStrings.length;o++){var a=n.replaceStrings[o];i=i.replace(a.search,a.replace)}return i},r.prototype._emitFunctionFromInclude=function(t,e,n,i){i===void 0&&(i="");var o=t+i;if(!this.functions[o]){if(!(n&&(n.removeAttributes||n.removeUniforms||n.removeVaryings||n.removeIfDef||n.replaceStrings)))return n&&n.repeatKey?this.functions[o]="#include<"+t+">[0.."+n.repeatKey+`]\r
-`:this.functions[o]="#include<"+t+`>\r
-`,void(this.sharedData.emitComments&&(this.functions[o]=e+`\r
-`+this.functions[o]));if(this.functions[o]=ze.a.IncludesShadersStore[t],this.sharedData.emitComments&&(this.functions[o]=e+`\r
-`+this.functions[o]),n.removeIfDef&&(this.functions[o]=this.functions[o].replace(/^\s*?#ifdef.+$/gm,""),this.functions[o]=this.functions[o].replace(/^\s*?#endif.*$/gm,""),this.functions[o]=this.functions[o].replace(/^\s*?#else.*$/gm,""),this.functions[o]=this.functions[o].replace(/^\s*?#elif.*$/gm,"")),n.removeAttributes&&(this.functions[o]=this.functions[o].replace(/^\s*?attribute.+$/gm,"")),n.removeUniforms&&(this.functions[o]=this.functions[o].replace(/^\s*?uniform.+$/gm,"")),n.removeVaryings&&(this.functions[o]=this.functions[o].replace(/^\s*?varying.+$/gm,"")),n.replaceStrings)for(var a=0;a<n.replaceStrings.length;a++){var s=n.replaceStrings[a];this.functions[o]=this.functions[o].replace(s.search,s.replace)}}},r.prototype._registerTempVariable=function(t){return this.sharedData.temps.indexOf(t)===-1&&(this.sharedData.temps.push(t),!0)},r.prototype._emitVaryingFromString=function(t,e,n,i){return n===void 0&&(n=""),i===void 0&&(i=!1),this.sharedData.varyings.indexOf(t)===-1&&(this.sharedData.varyings.push(t),n&&(Qn.a.StartsWith(n,"defined(")?this.sharedData.varyingDeclaration+="#if "+n+`\r
-`:this.sharedData.varyingDeclaration+=(i?"#ifndef":"#ifdef")+" "+n+`\r
-`),this.sharedData.varyingDeclaration+="varying "+e+" "+t+`;\r
-`,n&&(this.sharedData.varyingDeclaration+=`#endif\r
-`),!0)},r.prototype._emitUniformFromString=function(t,e,n,i){n===void 0&&(n=""),i===void 0&&(i=!1),this.uniforms.indexOf(t)===-1&&(this.uniforms.push(t),n&&(Qn.a.StartsWith(n,"defined(")?this._uniformDeclaration+="#if "+n+`\r
-`:this._uniformDeclaration+=(i?"#ifndef":"#ifdef")+" "+n+`\r
-`),this._uniformDeclaration+="uniform "+e+" "+t+`;\r
-`,n&&(this._uniformDeclaration+=`#endif\r
-`))},r.prototype._emitFloat=function(t){return t.toString()===t.toFixed(0)?t+".0":t.toString()},r}(),um=function(){function r(){this.temps=new Array,this.varyings=new Array,this.varyingDeclaration="",this.inputBlocks=new Array,this.textureBlocks=new Array,this.bindableBlocks=new Array,this.blocksWithFallbacks=new Array,this.blocksWithDefines=new Array,this.repeatableContentBlocks=new Array,this.dynamicUniformBlocks=new Array,this.blockingBlocks=new Array,this.animatedInputs=new Array,this.variableNames={},this.defineNames={},this.hints={needWorldViewMatrix:!1,needWorldViewProjectionMatrix:!1,needAlphaBlending:!1,needAlphaTesting:!1},this.checks={emitVertex:!1,emitFragment:!1,notConnectedNonOptionalInputs:new Array},this.allowEmptyVertexProgram=!1,this.variableNames.position=0,this.variableNames.normal=0,this.variableNames.tangent=0,this.variableNames.uv=0,this.variableNames.uv2=0,this.variableNames.uv3=0,this.variableNames.uv4=0,this.variableNames.uv4=0,this.variableNames.uv5=0,this.variableNames.uv6=0,this.variableNames.color=0,this.variableNames.matricesIndices=0,this.variableNames.matricesWeights=0,this.variableNames.matricesIndicesExtra=0,this.variableNames.matricesWeightsExtra=0,this.variableNames.diffuseBase=0,this.variableNames.specularBase=0,this.variableNames.worldPos=0,this.variableNames.shadow=0,this.variableNames.view=0,this.variableNames.vTBN=0,this.defineNames.MAINUV0=0,this.defineNames.MAINUV1=0,this.defineNames.MAINUV2=0,this.defineNames.MAINUV3=0,this.defineNames.MAINUV4=0,this.defineNames.MAINUV5=0,this.defineNames.MAINUV6=0,this.defineNames.MAINUV7=0}return r.prototype.emitErrors=function(){var t="";this.checks.emitVertex||this.allowEmptyVertexProgram||(t+=`NodeMaterial does not have a vertex output. You need to at least add a block that generates a glPosition value.\r
-`),this.checks.emitFragment||(t+=`NodeMaterial does not have a fragment output. You need to at least add a block that generates a glFragColor value.\r
-`);for(var e=0,n=this.checks.notConnectedNonOptionalInputs;e<n.length;e++){var i=n[e];t+="input "+i.name+" from block "+i.ownerBlock.name+"["+i.ownerBlock.getClassName()+`] is not connected and is not optional.\r
-`}if(t)throw`Build of NodeMaterial failed:\r
-`+t},r}(),fa=function(r){function t(e){var n=r.call(this,e,Ce.Vertex)||this;return n.complementW=1,n.complementZ=0,n.registerInput("vector",le.AutoDetect),n.registerInput("transform",le.Matrix),n.registerOutput("output",le.Vector4),n.registerOutput("xyz",le.Vector3),n._inputs[0].onConnectionObservable.add(function(i){if(i.ownerBlock.isInput){var o=i.ownerBlock;o.name!=="normal"&&o.name!=="tangent"||(n.complementW=0)}}),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"TransformBlock"},Object.defineProperty(t.prototype,"vector",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyz",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"transform",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this.vector,i=this.transform;if(n.connectedPoint){if(this.complementW===0){var o="//"+this.name;e._emitFunctionFromInclude("helperFunctions",o),e.sharedData.blocksWithDefines.push(this);var a=e._getFreeVariableName(i.associatedVariableName+"_NUS");switch(e.compilationString+="mat3 "+a+" = mat3("+i.associatedVariableName+`);\r
-`,e.compilationString+=`#ifdef NONUNIFORMSCALING\r
-`,e.compilationString+=a+" = transposeMat3(inverseMat3("+a+`));\r
-`,e.compilationString+=`#endif\r
-`,n.connectedPoint.type){case le.Vector2:e.compilationString+=this._declareOutput(this.output,e)+" = vec4("+a+" * vec3("+n.associatedVariableName+", "+this._writeFloat(this.complementZ)+"), "+this._writeFloat(this.complementW)+`);\r
-`;break;case le.Vector3:case le.Color3:e.compilationString+=this._declareOutput(this.output,e)+" = vec4("+a+" * "+n.associatedVariableName+", "+this._writeFloat(this.complementW)+`);\r
-`;break;default:e.compilationString+=this._declareOutput(this.output,e)+" = vec4("+a+" * "+n.associatedVariableName+".xyz, "+this._writeFloat(this.complementW)+`);\r
-`}}else switch(a=i.associatedVariableName,n.connectedPoint.type){case le.Vector2:e.compilationString+=this._declareOutput(this.output,e)+" = "+a+" * vec4("+n.associatedVariableName+", "+this._writeFloat(this.complementZ)+", "+this._writeFloat(this.complementW)+`);\r
-`;break;case le.Vector3:case le.Color3:e.compilationString+=this._declareOutput(this.output,e)+" = "+a+" * vec4("+n.associatedVariableName+", "+this._writeFloat(this.complementW)+`);\r
-`;break;default:e.compilationString+=this._declareOutput(this.output,e)+" = "+a+" * "+n.associatedVariableName+`;\r
-`}this.xyz.hasEndpoints&&(e.compilationString+=this._declareOutput(this.xyz,e)+" = "+this.output.associatedVariableName+`.xyz;\r
-`)}return this},t.prototype.prepareDefines=function(e,n,i,o,a){e.nonUniformScaling&&i.setValue("NONUNIFORMSCALING",!0)},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.complementZ=this.complementZ,e.complementW=this.complementW,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.complementZ=e.complementZ!==void 0?e.complementZ:0,this.complementW=e.complementW!==void 0?e.complementW:1},t.prototype._dumpPropertiesCode=function(){var e=this._codeVariableName+".complementZ = "+this.complementZ+`;\r
-`;return e+=this._codeVariableName+".complementW = "+this.complementW+`;\r
-`},t}(pt);R.a.RegisteredTypes["BABYLON.TransformBlock"]=fa;var vo=function(r){function t(e){var n=r.call(this,e,Ce.Vertex,!0)||this;return n.registerInput("vector",le.Vector4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VertexOutputBlock"},Object.defineProperty(t.prototype,"vector",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this.vector;return e.compilationString+="gl_Position = "+n.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.VertexOutputBlock"]=vo;var ji,Lr=function(r){function t(e){var n=r.call(this,e,Ce.Fragment,!0)||this;return n.registerInput("rgba",le.Color4,!0),n.registerInput("rgb",le.Color3,!0),n.registerInput("a",le.Float,!0),n.rgb.acceptedConnectionPointTypes.push(le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FragmentOutputBlock"},Object.defineProperty(t.prototype,"rgba",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgb",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"a",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this.rgba,i=this.rgb,o=this.a;if(e.sharedData.hints.needAlphaBlending=n.isConnected||o.isConnected,n.connectedPoint)o.isConnected?e.compilationString+="gl_FragColor = vec4("+n.associatedVariableName+".rgb, "+o.associatedVariableName+`);\r
-`:e.compilationString+="gl_FragColor = "+n.associatedVariableName+`;\r
-`;else if(i.connectedPoint){var a="1.0";o.connectedPoint&&(a=o.associatedVariableName),i.connectedPoint.type===le.Float?e.compilationString+="gl_FragColor = vec4("+i.associatedVariableName+", "+i.associatedVariableName+", "+i.associatedVariableName+", "+a+`);\r
-`:e.compilationString+="gl_FragColor = vec4("+i.associatedVariableName+", "+a+`);\r
-`}else e.sharedData.checks.notConnectedNonOptionalInputs.push(n);return this},t}(pt);R.a.RegisteredTypes["BABYLON.FragmentOutputBlock"]=Lr,function(r){r[r.None=0]="None",r[r.Time=1]="Time"}(ji||(ji={}));var hm={position2d:"position",particle_uv:"vUV",particle_color:"vColor",particle_texturemask:"textureMask",particle_positionw:"vPositionW"},ec={particle_uv:!0,particle_color:!0,particle_texturemask:!0,particle_positionw:!0},dh={particle_texturemask:!0},At=function(r){function t(e,n,i){n===void 0&&(n=Ce.Vertex),i===void 0&&(i=le.AutoDetect);var o=r.call(this,e,n,!1,!0)||this;return o._mode=bn.Undefined,o._animationType=ji.None,o.min=0,o.max=0,o.isBoolean=!1,o.matrixMode=0,o._systemValue=null,o.isConstant=!1,o.groupInInspector="",o.onValueChangedObservable=new C.c,o.convertToGammaSpace=!1,o.convertToLinearSpace=!1,o._type=i,o.setDefaultValue(),o.registerOutput("output",i),o}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"type",{get:function(){if(this._type===le.AutoDetect){if(this.isUniform&&this.value!=null){if(!isNaN(this.value))return this._type=le.Float,this._type;switch(this.value.getClassName()){case"Vector2":return this._type=le.Vector2,this._type;case"Vector3":return this._type=le.Vector3,this._type;case"Vector4":return this._type=le.Vector4,this._type;case"Color3":return this._type=le.Color3,this._type;case"Color4":return this._type=le.Color4,this._type;case"Matrix":return this._type=le.Matrix,this._type}}if(this.isAttribute)switch(this.name){case"position":case"normal":case"tangent":case"particle_positionw":return this._type=le.Vector3,this._type;case"uv":case"uv2":case"position2d":case"particle_uv":return this._type=le.Vector2,this._type;case"matricesIndices":case"matricesWeights":case"world0":case"world1":case"world2":case"world3":return this._type=le.Vector4,this._type;case"color":case"particle_color":case"particle_texturemask":return this._type=le.Color4,this._type}if(this.isSystemValue)switch(this._systemValue){case bt.World:case bt.WorldView:case bt.WorldViewProjection:case bt.View:case bt.ViewProjection:case bt.Projection:return this._type=le.Matrix,this._type;case bt.CameraPosition:return this._type=le.Vector3,this._type;case bt.FogColor:return this._type=le.Color3,this._type;case bt.DeltaTime:return this._type=le.Float,this._type}}return this._type},enumerable:!1,configurable:!0}),t.prototype.validateBlockName=function(e){return!!this.isAttribute||r.prototype.validateBlockName.call(this,e)},Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.setAsAttribute=function(e){return this._mode=bn.Attribute,e&&(this.name=e),this},t.prototype.setAsSystemValue=function(e){return this.systemValue=e,this},Object.defineProperty(t.prototype,"value",{get:function(){return this._storedValue},set:function(e){this.type===le.Float&&(this.isBoolean?e=e?1:0:this.min!==this.max&&(e=Math.max(this.min,e),e=Math.min(this.max,e))),this._storedValue=e,this._mode=bn.Uniform,this.onValueChangedObservable.notifyObservers(this)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"valueCallback",{get:function(){return this._valueCallback},set:function(e){this._valueCallback=e,this._mode=bn.Uniform},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"associatedVariableName",{get:function(){return this._associatedVariableName},set:function(e){this._associatedVariableName=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"animationType",{get:function(){return this._animationType},set:function(e){this._animationType=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isUndefined",{get:function(){return this._mode===bn.Undefined},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isUniform",{get:function(){return this._mode===bn.Uniform},set:function(e){this._mode=e?bn.Uniform:bn.Undefined,this.associatedVariableName=""},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isAttribute",{get:function(){return this._mode===bn.Attribute},set:function(e){this._mode=e?bn.Attribute:bn.Undefined,this.associatedVariableName=""},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isVarying",{get:function(){return this._mode===bn.Varying},set:function(e){this._mode=e?bn.Varying:bn.Undefined,this.associatedVariableName=""},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isSystemValue",{get:function(){return this._systemValue!=null},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"systemValue",{get:function(){return this._systemValue},set:function(e){this._mode=bn.Uniform,this.associatedVariableName="",this._systemValue=e},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"InputBlock"},t.prototype.animate=function(e){switch(this._animationType){case ji.Time:this.type===le.Float&&(this.value+=.01*e.getAnimationRatio())}},t.prototype._emitDefine=function(e){return e[0]==="!"?"#ifndef "+e.substring(1)+`\r
-`:"#ifdef "+e+`\r
-`},t.prototype.initialize=function(e){this.associatedVariableName=""},t.prototype.setDefaultValue=function(){switch(this.type){case le.Float:this.value=0;break;case le.Vector2:this.value=u.d.Zero();break;case le.Vector3:this.value=u.e.Zero();break;case le.Vector4:this.value=u.f.Zero();break;case le.Color3:this.value=M.a.White();break;case le.Color4:this.value=new M.b(1,1,1,1);break;case le.Matrix:this.value=u.a.Identity()}},t.prototype._emitConstant=function(e){switch(this.type){case le.Float:return""+e._emitFloat(this.value);case le.Vector2:return"vec2("+this.value.x+", "+this.value.y+")";case le.Vector3:return"vec3("+this.value.x+", "+this.value.y+", "+this.value.z+")";case le.Vector4:return"vec4("+this.value.x+", "+this.value.y+", "+this.value.z+", "+this.value.w+")";case le.Color3:return M.c.Color3[0].set(this.value.r,this.value.g,this.value.b),this.convertToGammaSpace&&M.c.Color3[0].toGammaSpaceToRef(M.c.Color3[0]),this.convertToLinearSpace&&M.c.Color3[0].toLinearSpaceToRef(M.c.Color3[0]),"vec3("+M.c.Color3[0].r+", "+M.c.Color3[0].g+", "+M.c.Color3[0].b+")";case le.Color4:return M.c.Color4[0].set(this.value.r,this.value.g,this.value.b,this.value.a),this.convertToGammaSpace&&M.c.Color4[0].toGammaSpaceToRef(M.c.Color4[0]),this.convertToLinearSpace&&M.c.Color4[0].toLinearSpaceToRef(M.c.Color4[0]),"vec4("+M.c.Color4[0].r+", "+M.c.Color4[0].g+", "+M.c.Color4[0].b+", "+M.c.Color4[0].a+")"}return""},Object.defineProperty(t.prototype,"_noContextSwitch",{get:function(){return ec[this.name]},enumerable:!1,configurable:!0}),t.prototype._emit=function(e,n){var i;if(this.isUniform){if(this.associatedVariableName||(this.associatedVariableName=e._getFreeVariableName("u_"+this.name)),this.isConstant)return e.constants.indexOf(this.associatedVariableName)!==-1?void 0:(e.constants.push(this.associatedVariableName),void(e._constantDeclaration+=this._declareOutput(this.output,e)+" = "+this._emitConstant(e)+`;\r
-`));if(e.uniforms.indexOf(this.associatedVariableName)!==-1)return;e.uniforms.push(this.associatedVariableName),n&&(e._uniformDeclaration+=this._emitDefine(n)),e._uniformDeclaration+="uniform "+e._getGLType(this.type)+" "+this.associatedVariableName+`;\r
-`,n&&(e._uniformDeclaration+=`#endif\r
-`);var o=e.sharedData.hints;if(this._systemValue!==null&&this._systemValue!==void 0)switch(this._systemValue){case bt.WorldView:o.needWorldViewMatrix=!0;break;case bt.WorldViewProjection:o.needWorldViewProjectionMatrix=!0}else this._animationType!==ji.None&&e.sharedData.animatedInputs.push(this)}else if(this.isAttribute){if(this.associatedVariableName=(i=hm[this.name])!==null&&i!==void 0?i:this.name,this.target===Ce.Vertex&&e._vertexState)return void(ec[this.name]?dh[this.name]?e._emitUniformFromString(this.associatedVariableName,e._getGLType(this.type),n):e._emitVaryingFromString(this.associatedVariableName,e._getGLType(this.type),n):this._emit(e._vertexState,n));if(e.attributes.indexOf(this.associatedVariableName)!==-1)return;e.attributes.push(this.associatedVariableName),ec[this.name]?dh[this.name]?e._emitUniformFromString(this.associatedVariableName,e._getGLType(this.type),n):e._emitVaryingFromString(this.associatedVariableName,e._getGLType(this.type),n):(n&&(e._attributeDeclaration+=this._emitDefine(n)),e._attributeDeclaration+="attribute "+e._getGLType(this.type)+" "+this.associatedVariableName+`;\r
-`,n&&(e._attributeDeclaration+=`#endif\r
-`))}},t.prototype._transmitWorld=function(e,n,i,o){if(this._systemValue){var a=this.associatedVariableName;switch(this._systemValue){case bt.World:e.setMatrix(a,n);break;case bt.WorldView:e.setMatrix(a,i);break;case bt.WorldViewProjection:e.setMatrix(a,o)}}},t.prototype._transmit=function(e,n){if(!this.isAttribute){var i=this.associatedVariableName;if(this._systemValue)switch(this._systemValue){case bt.World:case bt.WorldView:case bt.WorldViewProjection:return;case bt.View:e.setMatrix(i,n.getViewMatrix());break;case bt.Projection:e.setMatrix(i,n.getProjectionMatrix());break;case bt.ViewProjection:e.setMatrix(i,n.getTransformMatrix());break;case bt.CameraPosition:et.a.BindEyePosition(e,n,i);break;case bt.FogColor:e.setColor3(i,n.fogColor);break;case bt.DeltaTime:e.setFloat(i,n.deltaTime/1e3)}else{var o=this._valueCallback?this._valueCallback():this._storedValue;if(o!==null)switch(this.type){case le.Float:e.setFloat(i,o);break;case le.Int:e.setInt(i,o);break;case le.Color3:M.c.Color3[0].set(this.value.r,this.value.g,this.value.b),this.convertToGammaSpace&&M.c.Color3[0].toGammaSpaceToRef(M.c.Color3[0]),this.convertToLinearSpace&&M.c.Color3[0].toLinearSpaceToRef(M.c.Color3[0]),e.setColor3(i,M.c.Color3[0]);break;case le.Color4:M.c.Color4[0].set(this.value.r,this.value.g,this.value.b,this.value.a),this.convertToGammaSpace&&M.c.Color4[0].toGammaSpaceToRef(M.c.Color4[0]),this.convertToLinearSpace&&M.c.Color4[0].toLinearSpaceToRef(M.c.Color4[0]),e.setDirectColor4(i,M.c.Color4[0]);break;case le.Vector2:e.setVector2(i,o);break;case le.Vector3:e.setVector3(i,o);break;case le.Vector4:e.setVector4(i,o);break;case le.Matrix:e.setMatrix(i,o)}}}},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e),(this.isUniform||this.isSystemValue)&&e.sharedData.inputBlocks.push(this),this._emit(e)},t.prototype._dumpPropertiesCode=function(){var e=this._codeVariableName;if(this.isAttribute)return e+'.setAsAttribute("'+this.name+`");\r
-`;if(this.isSystemValue)return e+".setAsSystemValue(BABYLON.NodeMaterialSystemValues."+bt[this._systemValue]+`);\r
-`;if(this.isUniform){var n=[],i="";switch(this.type){case le.Float:i=""+this.value;break;case le.Vector2:i="new BABYLON.Vector2("+this.value.x+", "+this.value.y+")";break;case le.Vector3:i="new BABYLON.Vector3("+this.value.x+", "+this.value.y+", "+this.value.z+")";break;case le.Vector4:i="new BABYLON.Vector4("+this.value.x+", "+this.value.y+", "+this.value.z+", "+this.value.w+")";break;case le.Color3:i="new BABYLON.Color3("+this.value.r+", "+this.value.g+", "+this.value.b+")",this.convertToGammaSpace&&(i+=".toGammaSpace()"),this.convertToLinearSpace&&(i+=".toLinearSpace()");break;case le.Color4:i="new BABYLON.Color4("+this.value.r+", "+this.value.g+", "+this.value.b+", "+this.value.a+")",this.convertToGammaSpace&&(i+=".toGammaSpace()"),this.convertToLinearSpace&&(i+=".toLinearSpace()");break;case le.Matrix:i="BABYLON.Matrix.FromArray(["+this.value.m+"])"}return n.push(e+".value = "+i),this.type===le.Float&&n.push(e+".min = "+this.min,e+".max = "+this.max,e+".isBoolean = "+this.isBoolean,e+".matrixMode = "+this.matrixMode,e+".animationType = BABYLON.AnimatedInputBlockTypes."+ji[this.animationType]),n.push(e+".isConstant = "+this.isConstant),n.push(""),n.join(`;\r
-`)}return""},t.prototype.dispose=function(){this.onValueChangedObservable.clear(),r.prototype.dispose.call(this)},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.type=this.type,e.mode=this._mode,e.systemValue=this._systemValue,e.animationType=this._animationType,e.min=this.min,e.max=this.max,e.isBoolean=this.isBoolean,e.matrixMode=this.matrixMode,e.isConstant=this.isConstant,e.groupInInspector=this.groupInInspector,e.convertToGammaSpace=this.convertToGammaSpace,e.convertToLinearSpace=this.convertToLinearSpace,this._storedValue!=null&&this._mode===bn.Uniform&&(this._storedValue.asArray?(e.valueType="BABYLON."+this._storedValue.getClassName(),e.value=this._storedValue.asArray()):(e.valueType="number",e.value=this._storedValue)),e},t.prototype._deserialize=function(e,n,i){if(this._mode=e.mode,r.prototype._deserialize.call(this,e,n,i),this._type=e.type,this._systemValue=e.systemValue||e.wellKnownValue,this._animationType=e.animationType,this.min=e.min||0,this.max=e.max||0,this.isBoolean=!!e.isBoolean,this.matrixMode=e.matrixMode||0,this.isConstant=!!e.isConstant,this.groupInInspector=e.groupInInspector||"",this.convertToGammaSpace=!!e.convertToGammaSpace,this.convertToLinearSpace=!!e.convertToLinearSpace,e.valueType)if(e.valueType==="number")this._storedValue=e.value;else{var o=R.a.GetClass(e.valueType);o&&(this._storedValue=o.FromArray(e.value))}},t}(pt);R.a.RegisteredTypes["BABYLON.InputBlock"]=At;var tc=function(r){function t(e){var n=r.call(this,e,Ce.VertexAndFragment)||this;return n._samplerName="textureSampler",n.convertToGammaSpace=!1,n.convertToLinearSpace=!1,n._isUnique=!1,n.registerInput("uv",le.Vector2,!1,Ce.VertexAndFragment),n.registerOutput("rgba",le.Color4,Ce.Neutral),n.registerOutput("rgb",le.Color3,Ce.Neutral),n.registerOutput("r",le.Float,Ce.Neutral),n.registerOutput("g",le.Float,Ce.Neutral),n.registerOutput("b",le.Float,Ce.Neutral),n.registerOutput("a",le.Float,Ce.Neutral),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector3),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[0]._prioritizeVertex=!1,n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"CurrentScreenBlock"},Object.defineProperty(t.prototype,"uv",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgba",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgb",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"r",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"g",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"b",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"a",{get:function(){return this._outputs[5]},enumerable:!1,configurable:!0}),t.prototype.initialize=function(e){e._excludeVariableName("textureSampler")},Object.defineProperty(t.prototype,"target",{get:function(){return this.uv.isConnected?this.uv.sourceBlock.isInput?Ce.VertexAndFragment:Ce.Fragment:Ce.VertexAndFragment},enumerable:!1,configurable:!0}),t.prototype.prepareDefines=function(e,n,i){i.setValue(this._linearDefineName,this.convertToGammaSpace,!0),i.setValue(this._gammaDefineName,this.convertToLinearSpace,!0)},t.prototype.isReady=function(){return!(this.texture&&!this.texture.isReadyOrNotBlocking())},t.prototype._injectVertexCode=function(e){var n=this.uv;if(n.connectedPoint.ownerBlock.isInput&&(n.connectedPoint.ownerBlock.isAttribute||e._emitUniformFromString(n.associatedVariableName,"vec2")),this._mainUVName="vMain"+n.associatedVariableName,e._emitVaryingFromString(this._mainUVName,"vec2"),e.compilationString+=this._mainUVName+" = "+n.associatedVariableName+`.xy;\r
-`,this._outputs.some(function(s){return s.isConnectedInVertexShader})){this._writeTextureRead(e,!0);for(var i=0,o=this._outputs;i<o.length;i++){var a=o[i];a.hasEndpoints&&this._writeOutput(e,a,a.name,!0)}}},t.prototype._writeTextureRead=function(e,n){n===void 0&&(n=!1);var i=this.uv;if(n){if(e.target===Ce.Fragment)return;e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+i.associatedVariableName+`);\r
-`}else this.uv.ownerBlock.target!==Ce.Fragment?e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+this._mainUVName+`);\r
-`:e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+i.associatedVariableName+`);\r
-`},t.prototype._writeOutput=function(e,n,i,o){if(o===void 0&&(o=!1),o){if(e.target===Ce.Fragment)return;e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+`;\r
-`}else this.uv.ownerBlock.target!==Ce.Fragment?(e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+`;\r
-`,e.compilationString+="#ifdef "+this._linearDefineName+`\r
-`,e.compilationString+=n.associatedVariableName+" = toGammaSpace("+n.associatedVariableName+`);\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+="#ifdef "+this._gammaDefineName+`\r
-`,e.compilationString+=n.associatedVariableName+" = toLinearSpace("+n.associatedVariableName+`);\r
-`,e.compilationString+=`#endif\r
-`):e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+`;\r
-`},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),this._tempTextureRead=e._getFreeVariableName("tempTextureRead"),e.sharedData.blockingBlocks.indexOf(this)<0&&e.sharedData.blockingBlocks.push(this),e.sharedData.textureBlocks.indexOf(this)<0&&e.sharedData.textureBlocks.push(this),e.sharedData.blocksWithDefines.indexOf(this)<0&&e.sharedData.blocksWithDefines.push(this),e.target!==Ce.Fragment)return e._emit2DSampler(this._samplerName),void this._injectVertexCode(e);if(this._outputs.some(function(s){return s.isConnectedInFragmentShader})){e._emit2DSampler(this._samplerName),this._linearDefineName=e._getFreeDefineName("ISLINEAR"),this._gammaDefineName=e._getFreeDefineName("ISGAMMA");var n="//"+this.name;e._emitFunctionFromInclude("helperFunctions",n),this._writeTextureRead(e);for(var i=0,o=this._outputs;i<o.length;i++){var a=o[i];a.hasEndpoints&&this._writeOutput(e,a,a.name)}return this}},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.convertToGammaSpace=this.convertToGammaSpace,e.convertToLinearSpace=this.convertToLinearSpace,this.texture&&(e.texture=this.texture.serialize()),e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.convertToGammaSpace=e.convertToGammaSpace,this.convertToLinearSpace=!!e.convertToLinearSpace,e.texture&&(i=e.texture.url.indexOf("data:")===0?"":i,this.texture=we.a.Parse(e.texture,n,i))},t}(pt);R.a.RegisteredTypes["BABYLON.CurrentScreenBlock"]=tc;var nc=function(r){function t(e){var n=r.call(this,e,Ce.Fragment)||this;return n._samplerName="diffuseSampler",n.convertToGammaSpace=!1,n.convertToLinearSpace=!1,n._isUnique=!1,n.registerInput("uv",le.Vector2,!1,Ce.VertexAndFragment),n.registerOutput("rgba",le.Color4,Ce.Neutral),n.registerOutput("rgb",le.Color3,Ce.Neutral),n.registerOutput("r",le.Float,Ce.Neutral),n.registerOutput("g",le.Float,Ce.Neutral),n.registerOutput("b",le.Float,Ce.Neutral),n.registerOutput("a",le.Float,Ce.Neutral),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector3),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ParticleTextureBlock"},Object.defineProperty(t.prototype,"uv",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgba",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgb",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"r",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"g",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"b",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"a",{get:function(){return this._outputs[5]},enumerable:!1,configurable:!0}),t.prototype.initialize=function(e){e._excludeVariableName("diffuseSampler")},t.prototype.autoConfigure=function(e){if(!this.uv.isConnected){var n=e.getInputBlockByPredicate(function(i){return i.isAttribute&&i.name==="particle_uv"});n||(n=new At("uv")).setAsAttribute("particle_uv"),n.output.connectTo(this.uv)}},t.prototype.prepareDefines=function(e,n,i){i.setValue(this._linearDefineName,this.convertToGammaSpace,!0),i.setValue(this._gammaDefineName,this.convertToLinearSpace,!0)},t.prototype.isReady=function(){return!(this.texture&&!this.texture.isReadyOrNotBlocking())},t.prototype._writeOutput=function(e,n,i){e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+`;\r
-`,e.compilationString+="#ifdef "+this._linearDefineName+`\r
-`,e.compilationString+=n.associatedVariableName+" = toGammaSpace("+n.associatedVariableName+`);\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+="#ifdef "+this._gammaDefineName+`\r
-`,e.compilationString+=n.associatedVariableName+" = toLinearSpace("+n.associatedVariableName+`);\r
-`,e.compilationString+=`#endif\r
-`},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.target!==Ce.Vertex){this._tempTextureRead=e._getFreeVariableName("tempTextureRead"),e._emit2DSampler(this._samplerName),e.sharedData.blockingBlocks.push(this),e.sharedData.textureBlocks.push(this),e.sharedData.blocksWithDefines.push(this),this._linearDefineName=e._getFreeDefineName("ISLINEAR"),this._gammaDefineName=e._getFreeDefineName("ISGAMMA");var n="//"+this.name;e._emitFunctionFromInclude("helperFunctions",n),e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+this.uv.associatedVariableName+`);\r
-`;for(var i=0,o=this._outputs;i<o.length;i++){var a=o[i];a.hasEndpoints&&this._writeOutput(e,a,a.name)}return this}},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.convertToGammaSpace=this.convertToGammaSpace,e.convertToLinearSpace=this.convertToLinearSpace,this.texture&&(e.texture=this.texture.serialize()),e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.convertToGammaSpace=e.convertToGammaSpace,this.convertToLinearSpace=!!e.convertToLinearSpace,e.texture&&(i=e.texture.url.indexOf("data:")===0?"":i,this.texture=we.a.Parse(e.texture,n,i))},t}(pt);R.a.RegisteredTypes["BABYLON.ParticleTextureBlock"]=nc;var ic=function(r){function t(e){var n=r.call(this,e,Ce.Fragment)||this;return n._isUnique=!0,n.registerInput("color",le.Color4,!1,Ce.Fragment),n.registerOutput("rampColor",le.Color4,Ce.Fragment),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ParticleRampGradientBlock"},Object.defineProperty(t.prototype,"color",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rampColor",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.initialize=function(e){e._excludeVariableName("remapRanges"),e._excludeVariableName("rampSampler"),e._excludeVariableName("baseColor"),e._excludeVariableName("alpha"),e._excludeVariableName("remappedColorIndex"),e._excludeVariableName("rampColor"),e._excludeVariableName("finalAlpha")},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.target!==Ce.Vertex)return e._emit2DSampler("rampSampler"),e._emitVaryingFromString("remapRanges","vec4","RAMPGRADIENT"),e.compilationString+=`
-            #ifdef RAMPGRADIENT
-                vec4 baseColor = `+this.color.associatedVariableName+`;
-                float alpha = `+this.color.associatedVariableName+`.a;
-
-                float remappedColorIndex = clamp((alpha - remapRanges.x) / remapRanges.y, 0.0, 1.0);
-
-                vec4 rampColor = texture2D(rampSampler, vec2(1.0 - remappedColorIndex, 0.));
-                baseColor.rgb *= rampColor.rgb;
-
-                // Remapped alpha
-                float finalAlpha = baseColor.a;
-                baseColor.a = clamp((alpha * rampColor.a - remapRanges.z) / remapRanges.w, 0.0, 1.0);
-
-                `+this._declareOutput(this.rampColor,e)+` = baseColor;
-            #else
-                `+this._declareOutput(this.rampColor,e)+" = "+this.color.associatedVariableName+`;
-            #endif
-        `,this},t}(pt);R.a.RegisteredTypes["BABYLON.ParticleRampGradientBlock"]=ic;var rc=function(r){function t(e){var n=r.call(this,e,Ce.Fragment)||this;return n._isUnique=!0,n.registerInput("color",le.Color4,!1,Ce.Fragment),n.registerInput("alphaTexture",le.Float,!1,Ce.Fragment),n.registerInput("alphaColor",le.Float,!1,Ce.Fragment),n.registerOutput("blendColor",le.Color4,Ce.Fragment),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ParticleBlendMultiplyBlock"},Object.defineProperty(t.prototype,"color",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"alphaTexture",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"alphaColor",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"blendColor",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.initialize=function(e){e._excludeVariableName("sourceAlpha")},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.target!==Ce.Vertex)return e.compilationString+=`
-            #ifdef BLENDMULTIPLYMODE
-                `+this._declareOutput(this.blendColor,e)+`;
-                float sourceAlpha = `+this.alphaColor.associatedVariableName+" * "+this.alphaTexture.associatedVariableName+`;
-                `+this.blendColor.associatedVariableName+".rgb = "+this.color.associatedVariableName+`.rgb * sourceAlpha + vec3(1.0) * (1.0 - sourceAlpha);
-                `+this.blendColor.associatedVariableName+".a = "+this.color.associatedVariableName+`.a;
-            #else
-                `+this._declareOutput(this.blendColor,e)+" = "+this.color.associatedVariableName+`;
-            #endif
-        `,this},t}(pt);R.a.RegisteredTypes["BABYLON.ParticleBlendMultiplyBlock"]=rc;var Lt,bo=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("xyz ",le.Vector3,!0),n.registerInput("xy ",le.Vector2,!0),n.registerInput("x",le.Float,!0),n.registerInput("y",le.Float,!0),n.registerInput("z",le.Float,!0),n.registerInput("w",le.Float,!0),n.registerOutput("xyzw",le.Vector4),n.registerOutput("xyz",le.Vector3),n.registerOutput("xy",le.Vector2),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VectorMergerBlock"},Object.defineProperty(t.prototype,"xyzIn",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyIn",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"x",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"y",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"z",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"w",{get:function(){return this._inputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyzw",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyzOut",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyOut",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xy",{get:function(){return this.xyOut},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyz",{get:function(){return this.xyzOut},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this.x,i=this.y,o=this.z,a=this.w,s=this.xyIn,d=this.xyzIn,p=this._outputs[0],b=this._outputs[1],P=this._outputs[2];return d.isConnected?p.hasEndpoints?e.compilationString+=this._declareOutput(p,e)+" = vec4("+d.associatedVariableName+", "+(a.isConnected?this._writeVariable(a):"0.0")+`);\r
-`:b.hasEndpoints?e.compilationString+=this._declareOutput(b,e)+" = "+d.associatedVariableName+`;\r
-`:P.hasEndpoints&&(e.compilationString+=this._declareOutput(P,e)+" = "+d.associatedVariableName+`.xy;\r
-`):s.isConnected?p.hasEndpoints?e.compilationString+=this._declareOutput(p,e)+" = vec4("+s.associatedVariableName+", "+(o.isConnected?this._writeVariable(o):"0.0")+", "+(a.isConnected?this._writeVariable(a):"0.0")+`);\r
-`:b.hasEndpoints?e.compilationString+=this._declareOutput(b,e)+" = vec3("+s.associatedVariableName+", "+(o.isConnected?this._writeVariable(o):"0.0")+`);\r
-`:P.hasEndpoints&&(e.compilationString+=this._declareOutput(P,e)+" = "+s.associatedVariableName+`;\r
-`):p.hasEndpoints?e.compilationString+=this._declareOutput(p,e)+" = vec4("+(n.isConnected?this._writeVariable(n):"0.0")+", "+(i.isConnected?this._writeVariable(i):"0.0")+", "+(o.isConnected?this._writeVariable(o):"0.0")+", "+(a.isConnected?this._writeVariable(a):"0.0")+`);\r
-`:b.hasEndpoints?e.compilationString+=this._declareOutput(b,e)+" = vec3("+(n.isConnected?this._writeVariable(n):"0.0")+", "+(i.isConnected?this._writeVariable(i):"0.0")+", "+(o.isConnected?this._writeVariable(o):"0.0")+`);\r
-`:P.hasEndpoints&&(e.compilationString+=this._declareOutput(P,e)+" = vec2("+(n.isConnected?this._writeVariable(n):"0.0")+", "+(i.isConnected?this._writeVariable(i):"0.0")+`);\r
-`),this},t}(pt);function Vt(r,t,e,n){return t===void 0&&(t=Lt.Boolean),e===void 0&&(e="PROPERTIES"),function(i,o){var a=i._propStore;a||(a=[],i._propStore=a),a.push({propertyName:o,displayName:r,type:t,groupName:e,options:n??{}})}}R.a.RegisteredTypes["BABYLON.VectorMergerBlock"]=bo,function(r){r[r.Boolean=0]="Boolean",r[r.Float=1]="Float",r[r.Vector2=2]="Vector2",r[r.List=3]="List"}(Lt||(Lt={}));var oc=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.sourceRange=new u.d(-1,1),n.targetRange=new u.d(0,1),n.registerInput("input",le.AutoDetect),n.registerInput("sourceMin",le.Float,!0),n.registerInput("sourceMax",le.Float,!0),n.registerInput("targetMin",le.Float,!0),n.registerInput("targetMax",le.Float,!0),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"RemapBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sourceMin",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sourceMax",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"targetMin",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"targetMax",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i=this.sourceMin.isConnected?this.sourceMin.associatedVariableName:this._writeFloat(this.sourceRange.x),o=this.sourceMax.isConnected?this.sourceMax.associatedVariableName:this._writeFloat(this.sourceRange.y),a=this.targetMin.isConnected?this.targetMin.associatedVariableName:this._writeFloat(this.targetRange.x),s=this.targetMax.isConnected?this.targetMax.associatedVariableName:this._writeFloat(this.targetRange.y);return e.compilationString+=this._declareOutput(n,e)+" = "+a+" + ("+this._inputs[0].associatedVariableName+" - "+i+") * ("+s+" - "+a+") / ("+o+" - "+i+`);\r
-`,this},t.prototype._dumpPropertiesCode=function(){var e=this._codeVariableName+".sourceRange = new BABYLON.Vector2("+this.sourceRange.x+", "+this.sourceRange.y+`);\r
-`;return e+=this._codeVariableName+".targetRange = new BABYLON.Vector2("+this.targetRange.x+", "+this.targetRange.y+`);\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.sourceRange=this.sourceRange.asArray(),e.targetRange=this.targetRange.asArray(),e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.sourceRange=u.d.FromArray(e.sourceRange),this.targetRange=u.d.FromArray(e.targetRange)},Object(c.c)([Vt("From",Lt.Vector2)],t.prototype,"sourceRange",void 0),Object(c.c)([Vt("To",Lt.Vector2)],t.prototype,"targetRange",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.RemapBlock"]=oc;var pa=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"MultiplyBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = "+this.left.associatedVariableName+" * "+this.right.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.MultiplyBlock"]=pa;var Nr=function(){function r(){this.direction1=new u.e(0,1,0),this.direction2=new u.e(0,1,0),this.minEmitBox=new u.e(-.5,-.5,-.5),this.maxEmitBox=new u.e(.5,.5,.5)}return r.prototype.startDirectionFunction=function(t,e,n,i){var o=$.a.RandomRange(this.direction1.x,this.direction2.x),a=$.a.RandomRange(this.direction1.y,this.direction2.y),s=$.a.RandomRange(this.direction1.z,this.direction2.z);if(i)return e.x=o,e.y=a,void(e.z=s);u.e.TransformNormalFromFloatsToRef(o,a,s,t,e)},r.prototype.startPositionFunction=function(t,e,n,i){var o=$.a.RandomRange(this.minEmitBox.x,this.maxEmitBox.x),a=$.a.RandomRange(this.minEmitBox.y,this.maxEmitBox.y),s=$.a.RandomRange(this.minEmitBox.z,this.maxEmitBox.z);if(i)return e.x=o,e.y=a,void(e.z=s);u.e.TransformCoordinatesFromFloatsToRef(o,a,s,t,e)},r.prototype.clone=function(){var t=new r;return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setVector3("direction1",this.direction1),t.setVector3("direction2",this.direction2),t.setVector3("minEmitBox",this.minEmitBox),t.setVector3("maxEmitBox",this.maxEmitBox)},r.prototype.getEffectDefines=function(){return"#define BOXEMITTER"},r.prototype.getClassName=function(){return"BoxParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t.direction1=this.direction1.asArray(),t.direction2=this.direction2.asArray(),t.minEmitBox=this.minEmitBox.asArray(),t.maxEmitBox=this.maxEmitBox.asArray(),t},r.prototype.parse=function(t){u.e.FromArrayToRef(t.direction1,0,this.direction1),u.e.FromArrayToRef(t.direction2,0,this.direction2),u.e.FromArrayToRef(t.minEmitBox,0,this.minEmitBox),u.e.FromArrayToRef(t.maxEmitBox,0,this.maxEmitBox)},r}(),ac=function(){function r(t,e,n){t===void 0&&(t=1),e===void 0&&(e=Math.PI),n===void 0&&(n=0),this.directionRandomizer=n,this.radiusRange=1,this.heightRange=1,this.emitFromSpawnPointOnly=!1,this.angle=e,this.radius=t}return Object.defineProperty(r.prototype,"radius",{get:function(){return this._radius},set:function(t){this._radius=t,this._buildHeight()},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"angle",{get:function(){return this._angle},set:function(t){this._angle=t,this._buildHeight()},enumerable:!1,configurable:!0}),r.prototype._buildHeight=function(){this._angle!==0?this._height=this._radius/Math.tan(this._angle/2):this._height=1},r.prototype.startDirectionFunction=function(t,e,n,i){i?u.c.Vector3[0].copyFrom(n._localPosition).normalize():n.position.subtractToRef(t.getTranslation(),u.c.Vector3[0]).normalize();var o=$.a.RandomRange(0,this.directionRandomizer),a=$.a.RandomRange(0,this.directionRandomizer),s=$.a.RandomRange(0,this.directionRandomizer);e.x=u.c.Vector3[0].x+o,e.y=u.c.Vector3[0].y+a,e.z=u.c.Vector3[0].z+s,e.normalize()},r.prototype.startPositionFunction=function(t,e,n,i){var o,a=$.a.RandomRange(0,2*Math.PI);o=this.emitFromSpawnPointOnly?1e-4:1-(o=$.a.RandomRange(0,this.heightRange))*o;var s=this._radius-$.a.RandomRange(0,this._radius*this.radiusRange),d=(s*=o)*Math.sin(a),p=s*Math.cos(a),b=o*this._height;if(i)return e.x=d,e.y=b,void(e.z=p);u.e.TransformCoordinatesFromFloatsToRef(d,b,p,t,e)},r.prototype.clone=function(){var t=new r(this._radius,this._angle,this.directionRandomizer);return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setFloat2("radius",this._radius,this.radiusRange),t.setFloat("coneAngle",this._angle),t.setFloat2("height",this._height,this.heightRange),t.setFloat("directionRandomizer",this.directionRandomizer)},r.prototype.getEffectDefines=function(){var t="#define CONEEMITTER";return this.emitFromSpawnPointOnly&&(t+=`
-#define CONEEMITTERSPAWNPOINT`),t},r.prototype.getClassName=function(){return"ConeParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t.radius=this._radius,t.angle=this._angle,t.directionRandomizer=this.directionRandomizer,t.radiusRange=this.radiusRange,t.heightRange=this.heightRange,t.emitFromSpawnPointOnly=this.emitFromSpawnPointOnly,t},r.prototype.parse=function(t){this.radius=t.radius,this.angle=t.angle,this.directionRandomizer=t.directionRandomizer,this.radiusRange=t.radiusRange!==void 0?t.radiusRange:1,this.heightRange=t.radiusRange!==void 0?t.heightRange:1,this.emitFromSpawnPointOnly=t.emitFromSpawnPointOnly!==void 0&&t.emitFromSpawnPointOnly},r}(),_a=function(){function r(t,e,n,i){t===void 0&&(t=1),e===void 0&&(e=1),n===void 0&&(n=1),i===void 0&&(i=0),this.radius=t,this.height=e,this.radiusRange=n,this.directionRandomizer=i}return r.prototype.startDirectionFunction=function(t,e,n,i){var o=n.position.subtract(t.getTranslation()).normalize(),a=$.a.RandomRange(-this.directionRandomizer/2,this.directionRandomizer/2),s=Math.atan2(o.x,o.z);s+=$.a.RandomRange(-Math.PI/2,Math.PI/2)*this.directionRandomizer,o.y=a,o.x=Math.sin(s),o.z=Math.cos(s),o.normalize(),i?e.copyFrom(o):u.e.TransformNormalFromFloatsToRef(o.x,o.y,o.z,t,e)},r.prototype.startPositionFunction=function(t,e,n,i){var o=$.a.RandomRange(-this.height/2,this.height/2),a=$.a.RandomRange(0,2*Math.PI),s=$.a.RandomRange((1-this.radiusRange)*(1-this.radiusRange),1),d=Math.sqrt(s)*this.radius,p=d*Math.cos(a),b=d*Math.sin(a);i?e.copyFromFloats(p,o,b):u.e.TransformCoordinatesFromFloatsToRef(p,o,b,t,e)},r.prototype.clone=function(){var t=new r(this.radius,this.directionRandomizer);return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setFloat("radius",this.radius),t.setFloat("height",this.height),t.setFloat("radiusRange",this.radiusRange),t.setFloat("directionRandomizer",this.directionRandomizer)},r.prototype.getEffectDefines=function(){return"#define CYLINDEREMITTER"},r.prototype.getClassName=function(){return"CylinderParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t.radius=this.radius,t.height=this.height,t.radiusRange=this.radiusRange,t.directionRandomizer=this.directionRandomizer,t},r.prototype.parse=function(t){this.radius=t.radius,this.height=t.height,this.radiusRange=t.radiusRange,this.directionRandomizer=t.directionRandomizer},r}(),sc=function(r){function t(e,n,i,o,a){e===void 0&&(e=1),n===void 0&&(n=1),i===void 0&&(i=1),o===void 0&&(o=new u.e(0,1,0)),a===void 0&&(a=new u.e(0,1,0));var s=r.call(this,e,n,i)||this;return s.direction1=o,s.direction2=a,s}return Object(c.d)(t,r),t.prototype.startDirectionFunction=function(e,n,i){var o=$.a.RandomRange(this.direction1.x,this.direction2.x),a=$.a.RandomRange(this.direction1.y,this.direction2.y),s=$.a.RandomRange(this.direction1.z,this.direction2.z);u.e.TransformNormalFromFloatsToRef(o,a,s,e,n)},t.prototype.clone=function(){var e=new t(this.radius,this.height,this.radiusRange,this.direction1,this.direction2);return de.a.DeepCopy(this,e),e},t.prototype.applyToShader=function(e){e.setFloat("radius",this.radius),e.setFloat("height",this.height),e.setFloat("radiusRange",this.radiusRange),e.setVector3("direction1",this.direction1),e.setVector3("direction2",this.direction2)},t.prototype.getEffectDefines=function(){return`#define CYLINDEREMITTER
-#define DIRECTEDCYLINDEREMITTER`},t.prototype.getClassName=function(){return"CylinderDirectedParticleEmitter"},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.direction1=this.direction1.asArray(),e.direction2=this.direction2.asArray(),e},t.prototype.parse=function(e){r.prototype.parse.call(this,e),this.direction1.copyFrom(e.direction1),this.direction2.copyFrom(e.direction2)},t}(_a),cc=function(){function r(t,e,n){t===void 0&&(t=1),e===void 0&&(e=1),n===void 0&&(n=0),this.radius=t,this.radiusRange=e,this.directionRandomizer=n}return r.prototype.startDirectionFunction=function(t,e,n,i){var o=n.position.subtract(t.getTranslation()).normalize(),a=$.a.RandomRange(0,this.directionRandomizer),s=$.a.RandomRange(0,this.directionRandomizer),d=$.a.RandomRange(0,this.directionRandomizer);o.x+=a,o.y+=s,o.z+=d,o.normalize(),i?e.copyFrom(o):u.e.TransformNormalFromFloatsToRef(o.x,o.y,o.z,t,e)},r.prototype.startPositionFunction=function(t,e,n,i){var o=this.radius-$.a.RandomRange(0,this.radius*this.radiusRange),a=$.a.RandomRange(0,1),s=$.a.RandomRange(0,2*Math.PI),d=Math.acos(2*a-1),p=o*Math.cos(s)*Math.sin(d),b=o*Math.cos(d),P=o*Math.sin(s)*Math.sin(d);i?e.copyFromFloats(p,Math.abs(b),P):u.e.TransformCoordinatesFromFloatsToRef(p,Math.abs(b),P,t,e)},r.prototype.clone=function(){var t=new r(this.radius,this.directionRandomizer);return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setFloat("radius",this.radius),t.setFloat("radiusRange",this.radiusRange),t.setFloat("directionRandomizer",this.directionRandomizer)},r.prototype.getEffectDefines=function(){return"#define HEMISPHERICEMITTER"},r.prototype.getClassName=function(){return"HemisphericParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t.radius=this.radius,t.radiusRange=this.radiusRange,t.directionRandomizer=this.directionRandomizer,t},r.prototype.parse=function(t){this.radius=t.radius,this.radiusRange=t.radiusRange,this.directionRandomizer=t.directionRandomizer},r}(),lc=function(){function r(){this.direction1=new u.e(0,1,0),this.direction2=new u.e(0,1,0)}return r.prototype.startDirectionFunction=function(t,e,n,i){var o=$.a.RandomRange(this.direction1.x,this.direction2.x),a=$.a.RandomRange(this.direction1.y,this.direction2.y),s=$.a.RandomRange(this.direction1.z,this.direction2.z);i?e.copyFromFloats(o,a,s):u.e.TransformNormalFromFloatsToRef(o,a,s,t,e)},r.prototype.startPositionFunction=function(t,e,n,i){i?e.copyFromFloats(0,0,0):u.e.TransformCoordinatesFromFloatsToRef(0,0,0,t,e)},r.prototype.clone=function(){var t=new r;return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setVector3("direction1",this.direction1),t.setVector3("direction2",this.direction2)},r.prototype.getEffectDefines=function(){return"#define POINTEMITTER"},r.prototype.getClassName=function(){return"PointParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t.direction1=this.direction1.asArray(),t.direction2=this.direction2.asArray(),t},r.prototype.parse=function(t){u.e.FromArrayToRef(t.direction1,0,this.direction1),u.e.FromArrayToRef(t.direction2,0,this.direction2)},r}(),ma=function(){function r(t,e,n){t===void 0&&(t=1),e===void 0&&(e=1),n===void 0&&(n=0),this.radius=t,this.radiusRange=e,this.directionRandomizer=n}return r.prototype.startDirectionFunction=function(t,e,n,i){var o=n.position.subtract(t.getTranslation()).normalize(),a=$.a.RandomRange(0,this.directionRandomizer),s=$.a.RandomRange(0,this.directionRandomizer),d=$.a.RandomRange(0,this.directionRandomizer);o.x+=a,o.y+=s,o.z+=d,o.normalize(),i?e.copyFrom(o):u.e.TransformNormalFromFloatsToRef(o.x,o.y,o.z,t,e)},r.prototype.startPositionFunction=function(t,e,n,i){var o=this.radius-$.a.RandomRange(0,this.radius*this.radiusRange),a=$.a.RandomRange(0,1),s=$.a.RandomRange(0,2*Math.PI),d=Math.acos(2*a-1),p=o*Math.cos(s)*Math.sin(d),b=o*Math.cos(d),P=o*Math.sin(s)*Math.sin(d);i?e.copyFromFloats(p,b,P):u.e.TransformCoordinatesFromFloatsToRef(p,b,P,t,e)},r.prototype.clone=function(){var t=new r(this.radius,this.directionRandomizer);return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setFloat("radius",this.radius),t.setFloat("radiusRange",this.radiusRange),t.setFloat("directionRandomizer",this.directionRandomizer)},r.prototype.getEffectDefines=function(){return"#define SPHEREEMITTER"},r.prototype.getClassName=function(){return"SphereParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t.radius=this.radius,t.radiusRange=this.radiusRange,t.directionRandomizer=this.directionRandomizer,t},r.prototype.parse=function(t){this.radius=t.radius,this.radiusRange=t.radiusRange,this.directionRandomizer=t.directionRandomizer},r}(),uc=function(r){function t(e,n,i){e===void 0&&(e=1),n===void 0&&(n=new u.e(0,1,0)),i===void 0&&(i=new u.e(0,1,0));var o=r.call(this,e)||this;return o.direction1=n,o.direction2=i,o}return Object(c.d)(t,r),t.prototype.startDirectionFunction=function(e,n,i){var o=$.a.RandomRange(this.direction1.x,this.direction2.x),a=$.a.RandomRange(this.direction1.y,this.direction2.y),s=$.a.RandomRange(this.direction1.z,this.direction2.z);u.e.TransformNormalFromFloatsToRef(o,a,s,e,n)},t.prototype.clone=function(){var e=new t(this.radius,this.direction1,this.direction2);return de.a.DeepCopy(this,e),e},t.prototype.applyToShader=function(e){e.setFloat("radius",this.radius),e.setFloat("radiusRange",this.radiusRange),e.setVector3("direction1",this.direction1),e.setVector3("direction2",this.direction2)},t.prototype.getEffectDefines=function(){return`#define SPHEREEMITTER
-#define DIRECTEDSPHEREEMITTER`},t.prototype.getClassName=function(){return"SphereDirectedParticleEmitter"},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.direction1=this.direction1.asArray(),e.direction2=this.direction2.asArray(),e},t.prototype.parse=function(e){r.prototype.parse.call(this,e),this.direction1.copyFrom(e.direction1),this.direction2.copyFrom(e.direction2)},t}(ma),wr=function(){function r(){this.particlePositionGenerator=function(){},this.particleDestinationGenerator=function(){}}return r.prototype.startDirectionFunction=function(t,e,n,i){var o=u.c.Vector3[0];if(this.particleDestinationGenerator){this.particleDestinationGenerator(-1,n,o);var a=u.c.Vector3[1];o.subtractToRef(n.position,a),a.scaleToRef(1/n.lifeTime,o)}else o.set(0,0,0);i?e.copyFrom(o):u.e.TransformNormalToRef(o,t,e)},r.prototype.startPositionFunction=function(t,e,n,i){var o=u.c.Vector3[0];this.particlePositionGenerator?this.particlePositionGenerator(-1,n,o):o.set(0,0,0),i?e.copyFrom(o):u.e.TransformCoordinatesToRef(o,t,e)},r.prototype.clone=function(){var t=new r;return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){},r.prototype.getEffectDefines=function(){return"#define CUSTOMEMITTER"},r.prototype.getClassName=function(){return"CustomParticleEmitter"},r.prototype.serialize=function(){var t={};return t.type=this.getClassName(),t},r.prototype.parse=function(t){},r}(),fh=function(){function r(t){t===void 0&&(t=null),this._indices=null,this._positions=null,this._normals=null,this._storedNormal=u.e.Zero(),this._mesh=null,this.direction1=new u.e(0,1,0),this.direction2=new u.e(0,1,0),this.useMeshNormalsForDirection=!0,this.mesh=t}return Object.defineProperty(r.prototype,"mesh",{get:function(){return this._mesh},set:function(t){this._mesh!==t&&(this._mesh=t,t?(this._indices=t.getIndices(),this._positions=t.getVerticesData(Oe.b.PositionKind),this._normals=t.getVerticesData(Oe.b.NormalKind)):(this._indices=null,this._positions=null,this._normals=null))},enumerable:!1,configurable:!0}),r.prototype.startDirectionFunction=function(t,e,n,i){if(this.useMeshNormalsForDirection&&this._normals)u.e.TransformNormalToRef(this._storedNormal,t,e);else{var o=$.a.RandomRange(this.direction1.x,this.direction2.x),a=$.a.RandomRange(this.direction1.y,this.direction2.y),s=$.a.RandomRange(this.direction1.z,this.direction2.z);i?e.copyFromFloats(o,a,s):u.e.TransformNormalFromFloatsToRef(o,a,s,t,e)}},r.prototype.startPositionFunction=function(t,e,n,i){if(this._indices&&this._positions){var o=3*Math.random()*(this._indices.length/3)|0,a=Math.random(),s=Math.random()*(1-a),d=1-a-s,p=this._indices[o],b=this._indices[o+1],P=this._indices[o+2],O=u.c.Vector3[0],B=u.c.Vector3[1],F=u.c.Vector3[2],z=u.c.Vector3[3];u.e.FromArrayToRef(this._positions,3*p,O),u.e.FromArrayToRef(this._positions,3*b,B),u.e.FromArrayToRef(this._positions,3*P,F),z.x=a*O.x+s*B.x+d*F.x,z.y=a*O.y+s*B.y+d*F.y,z.z=a*O.z+s*B.z+d*F.z,i?e.copyFromFloats(z.x,z.y,z.z):u.e.TransformCoordinatesFromFloatsToRef(z.x,z.y,z.z,t,e),this.useMeshNormalsForDirection&&this._normals&&(u.e.FromArrayToRef(this._normals,3*p,O),u.e.FromArrayToRef(this._normals,3*b,B),u.e.FromArrayToRef(this._normals,3*P,F),this._storedNormal.x=a*O.x+s*B.x+d*F.x,this._storedNormal.y=a*O.y+s*B.y+d*F.y,this._storedNormal.z=a*O.z+s*B.z+d*F.z)}},r.prototype.clone=function(){var t=new r(this.mesh);return de.a.DeepCopy(this,t),t},r.prototype.applyToShader=function(t){t.setVector3("direction1",this.direction1),t.setVector3("direction2",this.direction2)},r.prototype.getEffectDefines=function(){return""},r.prototype.getClassName=function(){return"MeshParticleEmitter"},r.prototype.serialize=function(){var t,e={};return e.type=this.getClassName(),e.direction1=this.direction1.asArray(),e.direction2=this.direction2.asArray(),e.meshId=(t=this.mesh)===null||t===void 0?void 0:t.id,e.useMeshNormalsForDirection=this.useMeshNormalsForDirection,e},r.prototype.parse=function(t,e){u.e.FromArrayToRef(t.direction1,0,this.direction1),u.e.FromArrayToRef(t.direction2,0,this.direction2),t.meshId&&e&&(this.mesh=e.getLastMeshByID(t.meshId)),this.useMeshNormalsForDirection=t.useMeshNormalsForDirection},r}(),yo=function(){function r(t){this.animations=[],this.renderingGroupId=0,this.emitter=u.e.Zero(),this.emitRate=10,this.manualEmitCount=-1,this.updateSpeed=.01,this.targetStopDuration=0,this.disposeOnStop=!1,this.minEmitPower=1,this.maxEmitPower=1,this.minLifeTime=1,this.maxLifeTime=1,this.minSize=1,this.maxSize=1,this.minScaleX=1,this.maxScaleX=1,this.minScaleY=1,this.maxScaleY=1,this.minInitialRotation=0,this.maxInitialRotation=0,this.minAngularSpeed=0,this.maxAngularSpeed=0,this.layerMask=268435455,this.customShader=null,this.preventAutoStart=!1,this.noiseStrength=new u.e(10,10,10),this.onAnimationEnd=null,this.blendMode=r.BLENDMODE_ONEONE,this.forceDepthWrite=!1,this.preWarmCycles=0,this.preWarmStepOffset=1,this.spriteCellChangeSpeed=1,this.startSpriteCellID=0,this.endSpriteCellID=0,this.spriteCellWidth=0,this.spriteCellHeight=0,this.spriteRandomStartCell=!1,this.translationPivot=new u.d(0,0),this.beginAnimationOnStart=!1,this.beginAnimationFrom=0,this.beginAnimationTo=60,this.beginAnimationLoop=!1,this.worldOffset=new u.e(0,0,0),this.gravity=u.e.Zero(),this._colorGradients=null,this._sizeGradients=null,this._lifeTimeGradients=null,this._angularSpeedGradients=null,this._velocityGradients=null,this._limitVelocityGradients=null,this._dragGradients=null,this._emitRateGradients=null,this._startSizeGradients=null,this._rampGradients=null,this._colorRemapGradients=null,this._alphaRemapGradients=null,this.startDelay=0,this.limitVelocityDamping=.4,this.color1=new M.b(1,1,1,1),this.color2=new M.b(1,1,1,1),this.colorDead=new M.b(0,0,0,1),this.textureMask=new M.b(1,1,1,1),this._isSubEmitter=!1,this.billboardMode=h.a.PARTICLES_BILLBOARDMODE_ALL,this._isBillboardBased=!0,this._imageProcessingConfigurationDefines=new yn.b,this.id=t,this.name=t}return Object.defineProperty(r.prototype,"noiseTexture",{get:function(){return this._noiseTexture},set:function(t){this._noiseTexture!==t&&(this._noiseTexture=t,this._reset())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isAnimationSheetEnabled",{get:function(){return this._isAnimationSheetEnabled},set:function(t){this._isAnimationSheetEnabled!=t&&(this._isAnimationSheetEnabled=t,this._reset())},enumerable:!1,configurable:!0}),r.prototype.getScene=function(){return this._scene},r.prototype._hasTargetStopDurationDependantGradient=function(){return this._startSizeGradients&&this._startSizeGradients.length>0||this._emitRateGradients&&this._emitRateGradients.length>0||this._lifeTimeGradients&&this._lifeTimeGradients.length>0},r.prototype.getDragGradients=function(){return this._dragGradients},r.prototype.getLimitVelocityGradients=function(){return this._limitVelocityGradients},r.prototype.getColorGradients=function(){return this._colorGradients},r.prototype.getSizeGradients=function(){return this._sizeGradients},r.prototype.getColorRemapGradients=function(){return this._colorRemapGradients},r.prototype.getAlphaRemapGradients=function(){return this._alphaRemapGradients},r.prototype.getLifeTimeGradients=function(){return this._lifeTimeGradients},r.prototype.getAngularSpeedGradients=function(){return this._angularSpeedGradients},r.prototype.getVelocityGradients=function(){return this._velocityGradients},r.prototype.getStartSizeGradients=function(){return this._startSizeGradients},r.prototype.getEmitRateGradients=function(){return this._emitRateGradients},Object.defineProperty(r.prototype,"direction1",{get:function(){return this.particleEmitterType.direction1?this.particleEmitterType.direction1:u.e.Zero()},set:function(t){this.particleEmitterType.direction1&&(this.particleEmitterType.direction1=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"direction2",{get:function(){return this.particleEmitterType.direction2?this.particleEmitterType.direction2:u.e.Zero()},set:function(t){this.particleEmitterType.direction2&&(this.particleEmitterType.direction2=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"minEmitBox",{get:function(){return this.particleEmitterType.minEmitBox?this.particleEmitterType.minEmitBox:u.e.Zero()},set:function(t){this.particleEmitterType.minEmitBox&&(this.particleEmitterType.minEmitBox=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"maxEmitBox",{get:function(){return this.particleEmitterType.maxEmitBox?this.particleEmitterType.maxEmitBox:u.e.Zero()},set:function(t){this.particleEmitterType.maxEmitBox&&(this.particleEmitterType.maxEmitBox=t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isBillboardBased",{get:function(){return this._isBillboardBased},set:function(t){this._isBillboardBased!==t&&(this._isBillboardBased=t,this._reset())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"imageProcessingConfiguration",{get:function(){return this._imageProcessingConfiguration},set:function(t){this._attachImageProcessingConfiguration(t)},enumerable:!1,configurable:!0}),r.prototype._attachImageProcessingConfiguration=function(t){t!==this._imageProcessingConfiguration&&(!t&&this._scene?this._imageProcessingConfiguration=this._scene.imageProcessingConfiguration:this._imageProcessingConfiguration=t)},r.prototype._reset=function(){},r.prototype._removeGradientAndTexture=function(t,e,n){if(!e)return this;for(var i=0,o=0,a=e;o<a.length;o++){if(a[o].gradient===t){e.splice(i,1);break}i++}return n&&n.dispose(),this},r.prototype.createPointEmitter=function(t,e){var n=new lc;return n.direction1=t,n.direction2=e,this.particleEmitterType=n,n},r.prototype.createHemisphericEmitter=function(t,e){t===void 0&&(t=1),e===void 0&&(e=1);var n=new cc(t,e);return this.particleEmitterType=n,n},r.prototype.createSphereEmitter=function(t,e){t===void 0&&(t=1),e===void 0&&(e=1);var n=new ma(t,e);return this.particleEmitterType=n,n},r.prototype.createDirectedSphereEmitter=function(t,e,n){t===void 0&&(t=1),e===void 0&&(e=new u.e(0,1,0)),n===void 0&&(n=new u.e(0,1,0));var i=new uc(t,e,n);return this.particleEmitterType=i,i},r.prototype.createCylinderEmitter=function(t,e,n,i){t===void 0&&(t=1),e===void 0&&(e=1),n===void 0&&(n=1),i===void 0&&(i=0);var o=new _a(t,e,n,i);return this.particleEmitterType=o,o},r.prototype.createDirectedCylinderEmitter=function(t,e,n,i,o){t===void 0&&(t=1),e===void 0&&(e=1),n===void 0&&(n=1),i===void 0&&(i=new u.e(0,1,0)),o===void 0&&(o=new u.e(0,1,0));var a=new sc(t,e,n,i,o);return this.particleEmitterType=a,a},r.prototype.createConeEmitter=function(t,e){t===void 0&&(t=1),e===void 0&&(e=Math.PI/4);var n=new ac(t,e);return this.particleEmitterType=n,n},r.prototype.createBoxEmitter=function(t,e,n,i){var o=new Nr;return this.particleEmitterType=o,this.direction1=t,this.direction2=e,this.minEmitBox=n,this.maxEmitBox=i,o},r.BLENDMODE_ONEONE=0,r.BLENDMODE_STANDARD=1,r.BLENDMODE_ADD=2,r.BLENDMODE_MULTIPLY=3,r.BLENDMODE_MULTIPLYADD=4,r}(),hc=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("rgba",le.Color4,!0),n.registerInput("rgb ",le.Color3,!0),n.registerOutput("rgb",le.Color3),n.registerOutput("r",le.Float),n.registerOutput("g",le.Float),n.registerOutput("b",le.Float),n.registerOutput("a",le.Float),n.inputsAreExclusive=!0,n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ColorSplitterBlock"},Object.defineProperty(t.prototype,"rgba",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgbIn",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgbOut",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"r",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"g",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"b",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"a",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),t.prototype._inputRename=function(e){return e==="rgb "?"rgbIn":e},t.prototype._outputRename=function(e){return e==="rgb"?"rgbOut":e},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this.rgba.isConnected?this.rgba:this.rgbIn;if(n.isConnected){var i=this._outputs[0],o=this._outputs[1],a=this._outputs[2],s=this._outputs[3],d=this._outputs[4];return i.hasEndpoints&&(e.compilationString+=this._declareOutput(i,e)+" = "+n.associatedVariableName+`.rgb;\r
-`),o.hasEndpoints&&(e.compilationString+=this._declareOutput(o,e)+" = "+n.associatedVariableName+`.r;\r
-`),a.hasEndpoints&&(e.compilationString+=this._declareOutput(a,e)+" = "+n.associatedVariableName+`.g;\r
-`),s.hasEndpoints&&(e.compilationString+=this._declareOutput(s,e)+" = "+n.associatedVariableName+`.b;\r
-`),d.hasEndpoints&&(e.compilationString+=this._declareOutput(d,e)+" = "+n.associatedVariableName+`.a;\r
-`),this}},t}(pt);R.a.RegisteredTypes["BABYLON.ColorSplitterBlock"]=hc;var rn,ph=f(104);(function(r){r[r.Cos=0]="Cos",r[r.Sin=1]="Sin",r[r.Abs=2]="Abs",r[r.Exp=3]="Exp",r[r.Exp2=4]="Exp2",r[r.Round=5]="Round",r[r.Floor=6]="Floor",r[r.Ceiling=7]="Ceiling",r[r.Sqrt=8]="Sqrt",r[r.Log=9]="Log",r[r.Tan=10]="Tan",r[r.ArcTan=11]="ArcTan",r[r.ArcCos=12]="ArcCos",r[r.ArcSin=13]="ArcSin",r[r.Fract=14]="Fract",r[r.Sign=15]="Sign",r[r.Radians=16]="Radians",r[r.Degrees=17]="Degrees"})(rn||(rn={}));var dc=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.operation=rn.Cos,n.registerInput("input",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"TrigonometryBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i="";switch(this.operation){case rn.Cos:i="cos";break;case rn.Sin:i="sin";break;case rn.Abs:i="abs";break;case rn.Exp:i="exp";break;case rn.Exp2:i="exp2";break;case rn.Round:i="round";break;case rn.Floor:i="floor";break;case rn.Ceiling:i="ceil";break;case rn.Sqrt:i="sqrt";break;case rn.Log:i="log";break;case rn.Tan:i="tan";break;case rn.ArcTan:i="atan";break;case rn.ArcCos:i="acos";break;case rn.ArcSin:i="asin";break;case rn.Fract:i="fract";break;case rn.Sign:i="sign";break;case rn.Radians:i="radians";break;case rn.Degrees:i="degrees"}return e.compilationString+=this._declareOutput(n,e)+" = "+i+"("+this.input.associatedVariableName+`);\r
-`,this},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.operation=this.operation,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.operation=e.operation},t.prototype._dumpPropertiesCode=function(){return this._codeVariableName+".operation = BABYLON.TrigonometryBlockOperations."+rn[this.operation]+`;\r
-`},t}(pt);R.a.RegisteredTypes["BABYLON.TrigonometryBlock"]=dc;var fc={effect:null,subMesh:null},To=function(r){function t(){var e=r.call(this)||this;return e.NORMAL=!1,e.TANGENT=!1,e.UV1=!1,e.NUM_BONE_INFLUENCERS=0,e.BonesPerMesh=0,e.BONETEXTURE=!1,e.MORPHTARGETS=!1,e.MORPHTARGETS_NORMAL=!1,e.MORPHTARGETS_TANGENT=!1,e.MORPHTARGETS_UV=!1,e.NUM_MORPH_INFLUENCERS=0,e.IMAGEPROCESSING=!1,e.VIGNETTE=!1,e.VIGNETTEBLENDMODEMULTIPLY=!1,e.VIGNETTEBLENDMODEOPAQUE=!1,e.TONEMAPPING=!1,e.TONEMAPPING_ACES=!1,e.CONTRAST=!1,e.EXPOSURE=!1,e.COLORCURVES=!1,e.COLORGRADING=!1,e.COLORGRADING3D=!1,e.SAMPLER3DGREENDEPTH=!1,e.SAMPLER3DBGRMAP=!1,e.IMAGEPROCESSINGPOSTPROCESS=!1,e.BUMPDIRECTUV=0,e.rebuild(),e}return Object(c.d)(t,r),t.prototype.setValue=function(e,n,i){i===void 0&&(i=!1),this[e]===void 0&&this._keys.push(e),i&&this[e]!==n&&this.markAsUnprocessed(),this[e]=n},t}(Jo.a),ga=function(r){function t(e,n,i){i===void 0&&(i={});var o=r.call(this,e,n||Ue.a.LastCreatedScene)||this;return o._buildId=t._BuildIdGenerator++,o._buildWasSuccessful=!1,o._cachedWorldViewMatrix=new u.a,o._cachedWorldViewProjectionMatrix=new u.a,o._optimizers=new Array,o._animationFrame=-1,o.BJSNODEMATERIALEDITOR=o._getGlobalNodeMaterialEditor(),o.editorData=null,o.ignoreAlpha=!1,o.maxSimultaneousLights=4,o.onBuildObservable=new C.c,o._vertexOutputNodes=new Array,o._fragmentOutputNodes=new Array,o.attachedBlocks=new Array,o._mode=Mn.Material,o._options=Object(c.a)({emitComments:!1},i),o._attachImageProcessingConfiguration(null),o}return Object(c.d)(t,r),t.prototype._getGlobalNodeMaterialEditor=function(){return typeof NODEEDITOR<"u"?NODEEDITOR:typeof BABYLON<"u"&&BABYLON.NodeEditor!==void 0?BABYLON:void 0},Object.defineProperty(t.prototype,"options",{get:function(){return this._options},set:function(e){this._options=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"imageProcessingConfiguration",{get:function(){return this._imageProcessingConfiguration},set:function(e){this._attachImageProcessingConfiguration(e),this._markAllSubMeshesAsTexturesDirty()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"mode",{get:function(){return this._mode},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"NodeMaterial"},t.prototype._attachImageProcessingConfiguration=function(e){var n=this;e!==this._imageProcessingConfiguration&&(this._imageProcessingConfiguration&&this._imageProcessingObserver&&this._imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingObserver),this._imageProcessingConfiguration=e||this.getScene().imageProcessingConfiguration,this._imageProcessingConfiguration&&(this._imageProcessingObserver=this._imageProcessingConfiguration.onUpdateParameters.add(function(){n._markAllSubMeshesAsImageProcessingDirty()})))},t.prototype.getBlockByName=function(e){for(var n=null,i=0,o=this.attachedBlocks;i<o.length;i++){var a=o[i];if(a.name===e){if(n)return Xe.b.Warn("More than one block was found with the name `"+e+"`"),n;n=a}}return n},t.prototype.getBlockByPredicate=function(e){for(var n=0,i=this.attachedBlocks;n<i.length;n++){var o=i[n];if(e(o))return o}return null},t.prototype.getInputBlockByPredicate=function(e){for(var n=0,i=this.attachedBlocks;n<i.length;n++){var o=i[n];if(o.isInput&&e(o))return o}return null},t.prototype.getInputBlocks=function(){for(var e=[],n=0,i=this.attachedBlocks;n<i.length;n++){var o=i[n];o.isInput&&e.push(o)}return e},t.prototype.registerOptimizer=function(e){if(!(this._optimizers.indexOf(e)>-1))return this._optimizers.push(e),this},t.prototype.unregisterOptimizer=function(e){var n=this._optimizers.indexOf(e);if(n!==-1)return this._optimizers.splice(n,1),this},t.prototype.addOutputNode=function(e){if(e.target===null)throw"This node is not meant to be an output node. You may want to explicitly set its target value.";return e.target&Ce.Vertex&&this._addVertexOutputNode(e),e.target&Ce.Fragment&&this._addFragmentOutputNode(e),this},t.prototype.removeOutputNode=function(e){return e.target===null||(e.target&Ce.Vertex&&this._removeVertexOutputNode(e),e.target&Ce.Fragment&&this._removeFragmentOutputNode(e)),this},t.prototype._addVertexOutputNode=function(e){if(this._vertexOutputNodes.indexOf(e)===-1)return e.target=Ce.Vertex,this._vertexOutputNodes.push(e),this},t.prototype._removeVertexOutputNode=function(e){var n=this._vertexOutputNodes.indexOf(e);if(n!==-1)return this._vertexOutputNodes.splice(n,1),this},t.prototype._addFragmentOutputNode=function(e){if(this._fragmentOutputNodes.indexOf(e)===-1)return e.target=Ce.Fragment,this._fragmentOutputNodes.push(e),this},t.prototype._removeFragmentOutputNode=function(e){var n=this._fragmentOutputNodes.indexOf(e);if(n!==-1)return this._fragmentOutputNodes.splice(n,1),this},t.prototype.needAlphaBlending=function(){return!this.ignoreAlpha&&(this.alpha<1||this._sharedData&&this._sharedData.hints.needAlphaBlending)},t.prototype.needAlphaTesting=function(){return this._sharedData&&this._sharedData.hints.needAlphaTesting},t.prototype._initializeBlock=function(e,n,i){if(e.initialize(n),e.autoConfigure(this),e._preparationId=this._buildId,this.attachedBlocks.indexOf(e)===-1){if(e.isUnique){for(var o=e.getClassName(),a=0,s=this.attachedBlocks;a<s.length;a++)if(s[a].getClassName()===o)throw"Cannot have multiple blocks of type "+o+" in the same NodeMaterial"}this.attachedBlocks.push(e)}for(var d=0,p=e.inputs;d<p.length;d++){var b=p[d];b.associatedVariableName="";var P=b.connectedPoint;if(P){var O=P.ownerBlock;O!==e&&((O.target===Ce.VertexAndFragment||n.target===Ce.Fragment&&O.target===Ce.Vertex&&O._preparationId!==this._buildId)&&i.push(O),this._initializeBlock(O,n,i))}}for(var B=0,F=e.outputs;B<F.length;B++)F[B].associatedVariableName=""},t.prototype._resetDualBlocks=function(e,n){e.target===Ce.VertexAndFragment&&(e.buildId=n);for(var i=0,o=e.inputs;i<o.length;i++){var a=o[i].connectedPoint;if(a){var s=a.ownerBlock;s!==e&&this._resetDualBlocks(s,n)}}},t.prototype.removeBlock=function(e){var n=this.attachedBlocks.indexOf(e);n>-1&&this.attachedBlocks.splice(n,1),e.isFinalMerger&&this.removeOutputNode(e)},t.prototype.build=function(e){e===void 0&&(e=!1),this._buildWasSuccessful=!1;var n=this.getScene().getEngine(),i=this._mode===Mn.Particle;if(this._vertexOutputNodes.length===0&&!i)throw"You must define at least one vertexOutputNode";if(this._fragmentOutputNodes.length===0)throw"You must define at least one fragmentOutputNode";this._vertexCompilationState=new hh,this._vertexCompilationState.supportUniformBuffers=n.supportsUniformBuffers,this._vertexCompilationState.target=Ce.Vertex,this._fragmentCompilationState=new hh,this._fragmentCompilationState.supportUniformBuffers=n.supportsUniformBuffers,this._fragmentCompilationState.target=Ce.Fragment,this._sharedData=new um,this._vertexCompilationState.sharedData=this._sharedData,this._fragmentCompilationState.sharedData=this._sharedData,this._sharedData.buildId=this._buildId,this._sharedData.emitComments=this._options.emitComments,this._sharedData.verbose=e,this._sharedData.scene=this.getScene(),this._sharedData.allowEmptyVertexProgram=i;for(var o=[],a=[],s=0,d=this._vertexOutputNodes;s<d.length;s++){var p=d[s];o.push(p),this._initializeBlock(p,this._vertexCompilationState,a)}for(var b=0,P=this._fragmentOutputNodes;b<P.length;b++){var O=P[b];a.push(O),this._initializeBlock(O,this._fragmentCompilationState,o)}this.optimize();for(var B=0,F=o;B<F.length;B++)(p=F[B]).build(this._vertexCompilationState,o);this._fragmentCompilationState.uniforms=this._vertexCompilationState.uniforms.slice(0),this._fragmentCompilationState._uniformDeclaration=this._vertexCompilationState._uniformDeclaration,this._fragmentCompilationState._constantDeclaration=this._vertexCompilationState._constantDeclaration,this._fragmentCompilationState._vertexState=this._vertexCompilationState;for(var z=0,J=a;z<J.length;z++)O=J[z],this._resetDualBlocks(O,this._buildId-1);for(var ie=0,se=a;ie<se.length;ie++)(O=se[ie]).build(this._fragmentCompilationState,a);this._vertexCompilationState.finalize(this._vertexCompilationState),this._fragmentCompilationState.finalize(this._fragmentCompilationState),this._buildId=t._BuildIdGenerator++,this._sharedData.emitErrors(),e&&(console.log("Vertex shader:"),console.log(this._vertexCompilationState.compilationString),console.log("Fragment shader:"),console.log(this._fragmentCompilationState.compilationString)),this._buildWasSuccessful=!0,this.onBuildObservable.notifyObservers(this);for(var ce=0,ue=this.getScene().meshes;ce<ue.length;ce++){var fe=ue[ce];if(fe.subMeshes)for(var ve=0,Te=fe.subMeshes;ve<Te.length;ve++){var Re=Te[ve];if(Re.getMaterial()===this&&Re._materialDefines){var Ae=Re._materialDefines;Ae.markAllAsDirty(),Ae.reset()}}}},t.prototype.optimize=function(){for(var e=0,n=this._optimizers;e<n.length;e++)n[e].optimize(this._vertexOutputNodes,this._fragmentOutputNodes)},t.prototype._prepareDefinesForAttributes=function(e,n){var i=n.NORMAL,o=n.TANGENT,a=n.UV1;n.NORMAL=e.isVerticesDataPresent(Oe.b.NormalKind),n.TANGENT=e.isVerticesDataPresent(Oe.b.TangentKind),n.UV1=e.isVerticesDataPresent(Oe.b.UVKind),i===n.NORMAL&&o===n.TANGENT&&a===n.UV1||n.markAsAttributesDirty()},t.prototype.createPostProcess=function(e,n,i,o,a,s,d){return n===void 0&&(n=1),i===void 0&&(i=h.a.TEXTURE_NEAREST_SAMPLINGMODE),s===void 0&&(s=h.a.TEXTURETYPE_UNSIGNED_INT),d===void 0&&(d=h.a.TEXTUREFORMAT_RGBA),this.mode!==Mn.PostProcess?(console.log("Incompatible material mode"),null):this._createEffectForPostProcess(null,e,n,i,o,a,s,d)},t.prototype.createEffectForPostProcess=function(e){this._createEffectForPostProcess(e)},t.prototype._createEffectForPostProcess=function(e,n,i,o,a,s,d,p){var b=this;i===void 0&&(i=1),o===void 0&&(o=h.a.TEXTURE_NEAREST_SAMPLINGMODE),d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT),p===void 0&&(p=h.a.TEXTUREFORMAT_RGBA);var P=this.name+this._buildId,O=new To,B=new Dt.a(P+"PostProcess",this.getScene()),F=this._buildId;return this._processDefines(B,O),ze.a.RegisterShader(P,this._fragmentCompilationState._builtCompilationString,this._vertexCompilationState._builtCompilationString),e?e.updateEffect(O.toString(),this._fragmentCompilationState.uniforms,this._fragmentCompilationState.samplers,{maxSimultaneousLights:this.maxSimultaneousLights},void 0,void 0,P,P):e=new _t(this.name+"PostProcess",P,this._fragmentCompilationState.uniforms,this._fragmentCompilationState.samplers,i,n,o,a,s,O.toString(),d,P,{maxSimultaneousLights:this.maxSimultaneousLights},!1,p),e.nodeMaterialSource=this,e.onApplyObservable.add(function(z){F!==b._buildId&&(delete ze.a.ShadersStore[P+"VertexShader"],delete ze.a.ShadersStore[P+"PixelShader"],P=b.name+b._buildId,O.markAsUnprocessed(),F=b._buildId),b._processDefines(B,O)&&(ze.a.RegisterShader(P,b._fragmentCompilationState._builtCompilationString,b._vertexCompilationState._builtCompilationString),ph.a.SetImmediate(function(){return e.updateEffect(O.toString(),b._fragmentCompilationState.uniforms,b._fragmentCompilationState.samplers,{maxSimultaneousLights:b.maxSimultaneousLights},void 0,void 0,P,P)})),b._checkInternals(z)}),e},t.prototype.createProceduralTexture=function(e,n){var i=this;if(this.mode!==Mn.ProceduralTexture)return console.log("Incompatible material mode"),null;var o=this.name+this._buildId,a=new go(o,e,null,n),s=new Dt.a(o+"Procedural",this.getScene());s.reservedDataStore={hidden:!0};var d=new To,p=this._processDefines(s,d);ze.a.RegisterShader(o,this._fragmentCompilationState._builtCompilationString,this._vertexCompilationState._builtCompilationString);var b=this.getScene().getEngine().createEffect({vertexElement:o,fragmentElement:o},[Oe.b.PositionKind],this._fragmentCompilationState.uniforms,this._fragmentCompilationState.samplers,d.toString(),p?.fallbacks,void 0);a.nodeMaterialSource=this,a._effect=b;var P=this._buildId;return a.onBeforeGenerationObservable.add(function(){P!==i._buildId&&(delete ze.a.ShadersStore[o+"VertexShader"],delete ze.a.ShadersStore[o+"PixelShader"],o=i.name+i._buildId,d.markAsUnprocessed(),P=i._buildId);var O=i._processDefines(s,d);O&&(ze.a.RegisterShader(o,i._fragmentCompilationState._builtCompilationString,i._vertexCompilationState._builtCompilationString),ph.a.SetImmediate(function(){b=i.getScene().getEngine().createEffect({vertexElement:o,fragmentElement:o},[Oe.b.PositionKind],i._fragmentCompilationState.uniforms,i._fragmentCompilationState.samplers,d.toString(),O?.fallbacks,void 0),a._effect=b})),i._checkInternals(b)}),a},t.prototype._createEffectForParticles=function(e,n,i,o,a,s,d,p){var b=this;p===void 0&&(p="");var P=this.name+this._buildId+"_"+n;s||(s=new To),d||(d=this.getScene().getMeshByName(this.name+"Particle"))||((d=new Dt.a(this.name+"Particle",this.getScene())).reservedDataStore={hidden:!0});var O=this._buildId,B=[],F=p;if(!a){var z=this._processDefines(d,s);ze.a.RegisterShader(P,this._fragmentCompilationState._builtCompilationString),e.fillDefines(B,n),F=B.join(`
-`),a=this.getScene().getEngine().createEffectForParticles(P,this._fragmentCompilationState.uniforms,this._fragmentCompilationState.samplers,s.toString()+`
-`+F,z?.fallbacks,i,o,e),e.setCustomEffect(a,n)}a.onBindObservable.add(function(J){O!==b._buildId&&(delete ze.a.ShadersStore[P+"PixelShader"],P=b.name+b._buildId+"_"+n,s.markAsUnprocessed(),O=b._buildId),B.length=0,e.fillDefines(B,n);var ie=B.join(`
-`);ie!==F&&(s.markAsUnprocessed(),F=ie);var se=b._processDefines(d,s);if(se)return ze.a.RegisterShader(P,b._fragmentCompilationState._builtCompilationString),J=b.getScene().getEngine().createEffectForParticles(P,b._fragmentCompilationState.uniforms,b._fragmentCompilationState.samplers,s.toString()+`
-`+F,se?.fallbacks,i,o,e),e.setCustomEffect(J,n),void b._createEffectForParticles(e,n,i,o,J,s,d,F);b._checkInternals(J)})},t.prototype._checkInternals=function(e){if(this._sharedData.animatedInputs){var n=this.getScene(),i=n.getFrameId();if(this._animationFrame!==i){for(var o=0,a=this._sharedData.animatedInputs;o<a.length;o++)a[o].animate(n);this._animationFrame=i}}for(var s=0,d=this._sharedData.bindableBlocks;s<d.length;s++)d[s].bind(e,this);for(var p=0,b=this._sharedData.inputBlocks;p<b.length;p++)b[p]._transmit(e,this.getScene())},t.prototype.createEffectForParticles=function(e,n,i){this.mode===Mn.Particle?(this._createEffectForParticles(e,yo.BLENDMODE_ONEONE,n,i),this._createEffectForParticles(e,yo.BLENDMODE_MULTIPLY,n,i)):console.log("Incompatible material mode")},t.prototype._processDefines=function(e,n,i,o){var a=this;i===void 0&&(i=!1);var s=null;if(this._sharedData.blocksWithDefines.forEach(function(B){B.initializeDefines(e,a,n,i)}),this._sharedData.blocksWithDefines.forEach(function(B){B.prepareDefines(e,a,n,i,o)}),n.isDirty){var d=n._areLightsDisposed;n.markAsProcessed(),this._vertexCompilationState.compilationString=this._vertexCompilationState._builtCompilationString,this._fragmentCompilationState.compilationString=this._fragmentCompilationState._builtCompilationString,this._sharedData.repeatableContentBlocks.forEach(function(B){B.replaceRepeatableContent(a._vertexCompilationState,a._fragmentCompilationState,e,n)});var p=[];this._sharedData.dynamicUniformBlocks.forEach(function(B){B.updateUniformsAndSamples(a._vertexCompilationState,a,n,p)});var b=this._vertexCompilationState.uniforms;this._fragmentCompilationState.uniforms.forEach(function(B){b.indexOf(B)===-1&&b.push(B)});var P=this._vertexCompilationState.samplers;this._fragmentCompilationState.samplers.forEach(function(B){P.indexOf(B)===-1&&P.push(B)});var O=new Sr.a;this._sharedData.blocksWithFallbacks.forEach(function(B){B.provideFallbacks(e,O)}),s={lightDisposed:d,uniformBuffers:p,mergedUniforms:b,mergedSamplers:P,fallbacks:O}}return s},t.prototype.isReadyForSubMesh=function(e,n,i){var o=this;if(i===void 0&&(i=!1),!this._buildWasSuccessful)return!1;var a=this.getScene();if(this._sharedData.animatedInputs){var s=a.getFrameId();if(this._animationFrame!==s){for(var d=0,p=this._sharedData.animatedInputs;d<p.length;d++)p[d].animate(a);this._animationFrame=s}}if(n.effect&&this.isFrozen&&n.effect._wasPreviouslyReady)return!0;n._materialDefines||(n._materialDefines=new To);var b=n._materialDefines;if(this._isReadyForSubMesh(n))return!0;var P=a.getEngine();if(this._prepareDefinesForAttributes(e,b),this._sharedData.blockingBlocks.some(function(J){return!J.isReady(e,o,b,i)}))return!1;var O=this._processDefines(e,b,i,n);if(O){var B=n.effect,F=b.toString(),z=P.createEffect({vertex:"nodeMaterial"+this._buildId,fragment:"nodeMaterial"+this._buildId,vertexSource:this._vertexCompilationState.compilationString,fragmentSource:this._fragmentCompilationState.compilationString},{attributes:this._vertexCompilationState.attributes,uniformsNames:O.mergedUniforms,uniformBuffersNames:O.uniformBuffers,samplers:O.mergedSamplers,defines:F,fallbacks:O.fallbacks,onCompiled:this.onCompiled,onError:this.onError,indexParameters:{maxSimultaneousLights:this.maxSimultaneousLights,maxSimultaneousMorphTargets:b.NUM_MORPH_INFLUENCERS}},P);if(z)if(this._onEffectCreatedObservable&&(fc.effect=z,fc.subMesh=n,this._onEffectCreatedObservable.notifyObservers(fc)),this.allowShaderHotSwapping&&B&&!z.isReady()){if(z=B,b.markAsUnprocessed(),O.lightDisposed)return b._areLightsDisposed=!0,!1}else a.resetCachedMaterial(),n.setEffect(z,b)}return!(!n.effect||!n.effect.isReady())&&(b._renderId=a.getRenderId(),n.effect._wasPreviouslyReady=!0,!0)},Object.defineProperty(t.prototype,"compiledShaders",{get:function(){return`// Vertex shader\r
-`+this._vertexCompilationState.compilationString+`\r
-\r
-// Fragment shader\r
-`+this._fragmentCompilationState.compilationString},enumerable:!1,configurable:!0}),t.prototype.bindOnlyWorldMatrix=function(e){var n=this.getScene();if(this._activeEffect){var i=this._sharedData.hints;i.needWorldViewMatrix&&e.multiplyToRef(n.getViewMatrix(),this._cachedWorldViewMatrix),i.needWorldViewProjectionMatrix&&e.multiplyToRef(n.getTransformMatrix(),this._cachedWorldViewProjectionMatrix);for(var o=0,a=this._sharedData.inputBlocks;o<a.length;o++)a[o]._transmitWorld(this._activeEffect,e,this._cachedWorldViewMatrix,this._cachedWorldViewProjectionMatrix)}},t.prototype.bindForSubMesh=function(e,n,i){var o=this.getScene(),a=i.effect;if(a){if(this._activeEffect=a,this.bindOnlyWorldMatrix(e),this._mustRebind(o,a,n.visibility)){var s=this._sharedData;if(a&&o.getCachedEffect()!==a){for(var d=0,p=s.bindableBlocks;d<p.length;d++)p[d].bind(a,this,n,i);for(var b=0,P=s.inputBlocks;b<P.length;b++)P[b]._transmit(a,o)}}this._afterBind(n,this._activeEffect)}},t.prototype.getActiveTextures=function(){var e=r.prototype.getActiveTextures.call(this);return this._sharedData&&e.push.apply(e,this._sharedData.textureBlocks.filter(function(n){return n.texture}).map(function(n){return n.texture})),e},t.prototype.getTextureBlocks=function(){return this._sharedData?this._sharedData.textureBlocks:[]},t.prototype.hasTexture=function(e){if(r.prototype.hasTexture.call(this,e))return!0;if(!this._sharedData)return!1;for(var n=0,i=this._sharedData.textureBlocks;n<i.length;n++)if(i[n].texture===e)return!0;return!1},t.prototype.dispose=function(e,n,i){if(n)for(var o=0,a=this._sharedData.textureBlocks.filter(function(p){return p.texture}).map(function(p){return p.texture});o<a.length;o++)a[o].dispose();for(var s=0,d=this.attachedBlocks;s<d.length;s++)d[s].dispose();this.onBuildObservable.clear(),r.prototype.dispose.call(this,e,n,i)},t.prototype._createNodeEditor=function(){this.BJSNODEMATERIALEDITOR=this.BJSNODEMATERIALEDITOR||this._getGlobalNodeMaterialEditor(),this.BJSNODEMATERIALEDITOR.NodeEditor.Show({nodeMaterial:this})},t.prototype.edit=function(e){var n=this;return new Promise(function(i,o){if(n.BJSNODEMATERIALEDITOR===void 0){var a=e&&e.editorURL?e.editorURL:t.EditorURL;Xe.b.LoadScript(a,function(){n._createNodeEditor(),i()})}else n._createNodeEditor(),i()})},t.prototype.clear=function(){this._vertexOutputNodes=[],this._fragmentOutputNodes=[],this.attachedBlocks=[]},t.prototype.setToDefault=function(){this.clear(),this.editorData=null;var e=new At("Position");e.setAsAttribute("position");var n=new At("World");n.setAsSystemValue(BABYLON.NodeMaterialSystemValues.World);var i=new fa("WorldPos");e.connectTo(i),n.connectTo(i);var o=new At("ViewProjection");o.setAsSystemValue(BABYLON.NodeMaterialSystemValues.ViewProjection);var a=new fa("WorldPos * ViewProjectionTransform");i.connectTo(a),o.connectTo(a);var s=new vo("VertexOutput");a.connectTo(s);var d=new At("color");d.value=new M.b(.8,.8,.8,1);var p=new Lr("FragmentOutput");d.connectTo(p),this.addOutputNode(s),this.addOutputNode(p),this._mode=Mn.Material},t.prototype.setToDefaultPostProcess=function(){this.clear(),this.editorData=null;var e=new At("Position");e.setAsAttribute("position2d");var n=new At("Constant1");n.isConstant=!0,n.value=1;var i=new bo("Position3D");e.connectTo(i),n.connectTo(i,{input:"w"});var o=new vo("VertexOutput");i.connectTo(o);var a=new At("Scale");a.visibleInInspector=!0,a.value=new u.d(1,1);var s=new oc("uv0");e.connectTo(s);var d=new pa("UV scale");s.connectTo(d),a.connectTo(d);var p=new tc("CurrentScreen");d.connectTo(p),p.texture=new we.a("https://assets.babylonjs.com/nme/currentScreenPostProcess.png",this.getScene());var b=new Lr("FragmentOutput");p.connectTo(b,{output:"rgba"}),this.addOutputNode(o),this.addOutputNode(b),this._mode=Mn.PostProcess},t.prototype.setToDefaultProceduralTexture=function(){this.clear(),this.editorData=null;var e=new At("Position");e.setAsAttribute("position2d");var n=new At("Constant1");n.isConstant=!0,n.value=1;var i=new bo("Position3D");e.connectTo(i),n.connectTo(i,{input:"w"});var o=new vo("VertexOutput");i.connectTo(o);var a=new At("Time");a.value=0,a.min=0,a.max=0,a.isBoolean=!1,a.matrixMode=0,a.animationType=ji.Time,a.isConstant=!1;var s=new At("Color3");s.value=new M.a(1,1,1),s.isConstant=!1;var d=new Lr("FragmentOutput"),p=new bo("VectorMerger");p.visibleInInspector=!1;var b=new dc("Cos");b.operation=rn.Cos,e.connectTo(p),a.output.connectTo(b.input),b.output.connectTo(p.z),p.xyzOut.connectTo(d.rgb),this.addOutputNode(o),this.addOutputNode(d),this._mode=Mn.ProceduralTexture},t.prototype.setToDefaultParticle=function(){this.clear(),this.editorData=null;var e=new At("uv");e.setAsAttribute("particle_uv");var n=new nc("ParticleTexture");e.connectTo(n);var i=new At("Color");i.setAsAttribute("particle_color");var o=new pa("Texture * Color");n.connectTo(o),i.connectTo(o);var a=new ic("ParticleRampGradient");o.connectTo(a);var s=new hc("ColorSplitter");i.connectTo(s);var d=new rc("ParticleBlendMultiply");a.connectTo(d),n.connectTo(d,{output:"a"}),s.connectTo(d,{output:"a"});var p=new Lr("FragmentOutput");d.connectTo(p),this.addOutputNode(p),this._mode=Mn.Particle},t.prototype.loadAsync=function(e){var n=this;return this.getScene()._loadFileAsync(e).then(function(i){var o=JSON.parse(i);n.loadFromSerialization(o,"")})},t.prototype._gatherBlocks=function(e,n){if(n.indexOf(e)===-1){n.push(e);for(var i=0,o=e.inputs;i<o.length;i++){var a=o[i].connectedPoint;if(a){var s=a.ownerBlock;s!==e&&this._gatherBlocks(s,n)}}}},t.prototype.generateCode=function(){for(var e=[],n=[],i=[],o=0,a=this._vertexOutputNodes;o<a.length;o++){var s=a[o];this._gatherBlocks(s,n)}for(var d=[],p=0,b=this._fragmentOutputNodes;p<b.length;p++)s=b[p],this._gatherBlocks(s,d);for(var P='var nodeMaterial = new BABYLON.NodeMaterial("'+(this.name||"node material")+`");\r
-`,O=0,B=n;O<B.length;O++)(Re=B[O]).isInput&&e.indexOf(Re)===-1&&(P+=Re._dumpCode(i,e));for(var F=0,z=d;F<z.length;F++)(Re=z[F]).isInput&&e.indexOf(Re)===-1&&(P+=Re._dumpCode(i,e));e=[],P+=`\r
-// Connections\r
-`;for(var J=0,ie=this._vertexOutputNodes;J<ie.length;J++)P+=(Re=ie[J])._dumpCodeForOutputConnections(e);for(var se=0,ce=this._fragmentOutputNodes;se<ce.length;se++)P+=(Re=ce[se])._dumpCodeForOutputConnections(e);P+=`\r
-// Output nodes\r
-`;for(var ue=0,fe=this._vertexOutputNodes;ue<fe.length;ue++)P+="nodeMaterial.addOutputNode("+(Re=fe[ue])._codeVariableName+`);\r
-`;for(var ve=0,Te=this._fragmentOutputNodes;ve<Te.length;ve++){var Re;P+="nodeMaterial.addOutputNode("+(Re=Te[ve])._codeVariableName+`);\r
-`}return P+=`nodeMaterial.build();\r
-`},t.prototype.serialize=function(e){var n=e?{}:L.a.Serialize(this);n.editorData=JSON.parse(JSON.stringify(this.editorData));var i=[];if(e)i=e;else{n.customType="BABYLON.NodeMaterial",n.outputNodes=[];for(var o=0,a=this._vertexOutputNodes;o<a.length;o++){var s=a[o];this._gatherBlocks(s,i),n.outputNodes.push(s.uniqueId)}for(var d=0,p=this._fragmentOutputNodes;d<p.length;d++)s=p[d],this._gatherBlocks(s,i),n.outputNodes.indexOf(s.uniqueId)===-1&&n.outputNodes.push(s.uniqueId)}n.blocks=[];for(var b=0,P=i;b<P.length;b++){var O=P[b];n.blocks.push(O.serialize())}if(!e)for(var B=0,F=this.attachedBlocks;B<F.length;B++)O=F[B],i.indexOf(O)===-1&&n.blocks.push(O.serialize());return n},t.prototype._restoreConnections=function(e,n,i){for(var o=0,a=e.outputs;o<a.length;o++)for(var s=a[o],d=0,p=n.blocks;d<p.length;d++){var b=p[d],P=i[b.id];if(P)for(var O=0,B=b.inputs;O<B.length;O++){var F=B[O];if(!(i[F.targetBlockId]!==e||F.targetConnectionName!==s.name)){var z=P.getInputByName(F.inputName);if(!z||z.isConnected)continue;s.connectTo(z,!0),this._restoreConnections(P,n,i)}}}},t.prototype.loadFromSerialization=function(e,n,i){var o;n===void 0&&(n=""),i===void 0&&(i=!1),i||this.clear();for(var a={},s=0,d=e.blocks;s<d.length;s++){var p=d[s],b=R.a.GetClass(p.customType);b&&((O=new b)._deserialize(p,this.getScene(),n),a[p.id]=O,this.attachedBlocks.push(O))}for(var P=0;P<e.blocks.length;P++){var O;(O=a[e.blocks[P].id])&&(O.inputs.length&&!i||this._restoreConnections(O,e,a))}if(e.outputNodes)for(var B=0,F=e.outputNodes;B<F.length;B++){var z=F[B];this.addOutputNode(a[z])}if(e.locations||e.editorData&&e.editorData.locations){for(var J=e.locations||e.editorData.locations,ie=0,se=J;ie<se.length;ie++){var ce=se[ie];a[ce.blockId]&&(ce.blockId=a[ce.blockId].uniqueId)}i&&this.editorData&&this.editorData.locations&&J.concat(this.editorData.locations),e.locations?this.editorData={locations:J}:(this.editorData=e.editorData,this.editorData.locations=J);var ue=[];for(var fe in a)ue[fe]=a[fe].uniqueId;this.editorData.map=ue}this.comment=e.comment,i||(this._mode=(o=e.mode)!==null&&o!==void 0?o:Mn.Material)},t.prototype.clone=function(e){var n=this,i=this.serialize(),o=L.a.Clone(function(){return new t(e,n.getScene(),n.options)},this);return o.id=e,o.name=e,o.loadFromSerialization(i),o.build(),o},t.Parse=function(e,n,i){i===void 0&&(i="");var o=L.a.Parse(function(){return new t(e.name,n)},e,n,i);return o.loadFromSerialization(e,i),o.build(),o},t.ParseFromFileAsync=function(e,n,i){var o=new t(e,i);return new Promise(function(a,s){return o.loadAsync(n).then(function(){o.build(),a(o)}).catch(s)})},t.ParseFromSnippetAsync=function(e,n,i,o){var a=this;return i===void 0&&(i=""),e==="_BLANK"?Promise.resolve(this.CreateDefault("blank",n)):new Promise(function(s,d){var p=new re.a;p.addEventListener("readystatechange",function(){if(p.readyState==4)if(p.status==200){var b=JSON.parse(JSON.parse(p.responseText).jsonPayload),P=JSON.parse(b.nodeMaterial);o||((o=L.a.Parse(function(){return new t(e,n)},P,n,i)).uniqueId=n.getUniqueId()),o.loadFromSerialization(P),o.snippetId=e;try{o.build(),s(o)}catch(O){d(O)}}else d("Unable to load the snippet "+e)}),p.open("GET",a.SnippetUrl+"/"+e.replace(/#/g,"/")),p.send()})},t.CreateDefault=function(e,n){var i=new t(e,n);return i.setToDefault(),i.build(),i},t._BuildIdGenerator=0,t.EditorURL="https://unpkg.com/babylonjs-node-editor@"+Ue.a.Version+"/babylon.nodeEditor.js",t.SnippetUrl="https://snippet.babylonjs.com",t.IgnoreTexturesAtLoadTime=!1,Object(c.c)([Object(L.c)("mode")],t.prototype,"_mode",void 0),Object(c.c)([Object(L.c)("comment")],t.prototype,"comment",void 0),t}($o.a);R.a.RegisteredTypes["BABYLON.NodeMaterial"]=ga;var _h=function(r){function t(e){var n=r.call(this,e,Ce.Vertex)||this;return n.registerInput("matricesIndices",le.Vector4),n.registerInput("matricesWeights",le.Vector4),n.registerInput("matricesIndicesExtra",le.Vector4,!0),n.registerInput("matricesWeightsExtra",le.Vector4,!0),n.registerInput("world",le.Matrix),n.registerOutput("output",le.Matrix),n}return Object(c.d)(t,r),t.prototype.initialize=function(e){e._excludeVariableName("boneSampler"),e._excludeVariableName("boneTextureWidth"),e._excludeVariableName("mBones"),e._excludeVariableName("BonesPerMesh")},t.prototype.getClassName=function(){return"BonesBlock"},Object.defineProperty(t.prototype,"matricesIndices",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"matricesWeights",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"matricesIndicesExtra",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"matricesWeightsExtra",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"world",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.matricesIndices.isConnected){var n=e.getInputBlockByPredicate(function(a){return a.isAttribute&&a.name==="matricesIndices"});n||(n=new At("matricesIndices")).setAsAttribute("matricesIndices"),n.output.connectTo(this.matricesIndices)}if(!this.matricesWeights.isConnected){var i=e.getInputBlockByPredicate(function(a){return a.isAttribute&&a.name==="matricesWeights"});i||(i=new At("matricesWeights")).setAsAttribute("matricesWeights"),i.output.connectTo(this.matricesWeights)}if(!this.world.isConnected){var o=e.getInputBlockByPredicate(function(a){return a.systemValue===bt.World});o||(o=new At("world")).setAsSystemValue(bt.World),o.output.connectTo(this.world)}},t.prototype.provideFallbacks=function(e,n){e&&e.useBones&&e.computeBonesUsingShaders&&e.skeleton&&n.addCPUSkinningFallback(0,e)},t.prototype.bind=function(e,n,i){et.a.BindBonesParameters(i,e)},t.prototype.prepareDefines=function(e,n,i){i._areAttributesDirty&&et.a.PrepareDefinesForBones(e,i)},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e),e.sharedData.blocksWithFallbacks.push(this),e.sharedData.bindableBlocks.push(this),e.sharedData.blocksWithDefines.push(this),e.uniforms.push("boneTextureWidth"),e.uniforms.push("mBones"),e.samplers.push("boneSampler");var n="//"+this.name;e._emitFunctionFromInclude("bonesDeclaration",n,{removeAttributes:!0,removeUniforms:!1,removeVaryings:!0,removeIfDef:!1});var i=e._getFreeVariableName("influence");e.compilationString+=e._emitCodeFromInclude("bonesVertex",n,{replaceStrings:[{search:/finalWorld=finalWorld\*influence;/,replace:""},{search:/influence/gm,replace:i}]});var o=this._outputs[0],a=this.world;return e.compilationString+=`#if NUM_BONE_INFLUENCERS>0\r
-`,e.compilationString+=this._declareOutput(o,e)+" = "+a.associatedVariableName+" * "+i+`;\r
-`,e.compilationString+=`#else\r
-`,e.compilationString+=this._declareOutput(o,e)+" = "+a.associatedVariableName+`;\r
-`,e.compilationString+=`#endif\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.BonesBlock"]=_h;var mh=function(r){function t(e){var n=r.call(this,e,Ce.Vertex)||this;return n.registerInput("world0",le.Vector4),n.registerInput("world1",le.Vector4),n.registerInput("world2",le.Vector4),n.registerInput("world3",le.Vector4),n.registerInput("world",le.Matrix,!0),n.registerOutput("output",le.Matrix),n.registerOutput("instanceID",le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"InstancesBlock"},Object.defineProperty(t.prototype,"world0",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"world1",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"world2",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"world3",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"world",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"instanceID",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.world0.connectedPoint){var n=e.getInputBlockByPredicate(function(d){return d.isAttribute&&d.name==="world0"});n||(n=new At("world0")).setAsAttribute("world0"),n.output.connectTo(this.world0)}if(!this.world1.connectedPoint){var i=e.getInputBlockByPredicate(function(d){return d.isAttribute&&d.name==="world1"});i||(i=new At("world1")).setAsAttribute("world1"),i.output.connectTo(this.world1)}if(!this.world2.connectedPoint){var o=e.getInputBlockByPredicate(function(d){return d.isAttribute&&d.name==="world2"});o||(o=new At("world2")).setAsAttribute("world2"),o.output.connectTo(this.world2)}if(!this.world3.connectedPoint){var a=e.getInputBlockByPredicate(function(d){return d.isAttribute&&d.name==="world3"});a||(a=new At("world3")).setAsAttribute("world3"),a.output.connectTo(this.world3)}if(!this.world.connectedPoint){var s=e.getInputBlockByPredicate(function(d){return d.isAttribute&&d.name==="world"});s||(s=new At("world")).setAsSystemValue(bt.World),s.output.connectTo(this.world)}this.world.define="!INSTANCES || THIN_INSTANCES"},t.prototype.prepareDefines=function(e,n,i,o,a){o===void 0&&(o=!1);var s=!1;i.INSTANCES!==o&&(i.setValue("INSTANCES",o),s=!0),a&&i.THIN_INSTANCES!==!!a?.getRenderingMesh().hasThinInstances&&(i.setValue("THIN_INSTANCES",!!a?.getRenderingMesh().hasThinInstances),s=!0),s&&i.markAsUnprocessed()},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e),e.sharedData.blocksWithDefines.push(this);var n=this._outputs[0],i=this._outputs[1],o=this.world0,a=this.world1,s=this.world2,d=this.world3;return e.compilationString+=`#ifdef INSTANCES\r
-`,e.compilationString+=this._declareOutput(n,e)+" = mat4("+o.associatedVariableName+", "+a.associatedVariableName+", "+s.associatedVariableName+", "+d.associatedVariableName+`);\r
-`,e.compilationString+=`#ifdef THIN_INSTANCES\r
-`,e.compilationString+=n.associatedVariableName+" = "+this.world.associatedVariableName+" * "+n.associatedVariableName+`;\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+=this._declareOutput(i,e)+` = float(gl_InstanceID);\r
-`,e.compilationString+=`#else\r
-`,e.compilationString+=this._declareOutput(n,e)+" = "+this.world.associatedVariableName+`;\r
-`,e.compilationString+=this._declareOutput(i,e)+` = 0.0;\r
-`,e.compilationString+=`#endif\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.InstancesBlock"]=mh;var gh=function(r){function t(e){var n=r.call(this,e,Ce.Vertex)||this;return n.registerInput("position",le.Vector3),n.registerInput("normal",le.Vector3),n.registerInput("tangent",le.Vector3),n.registerInput("uv",le.Vector2),n.registerOutput("positionOutput",le.Vector3),n.registerOutput("normalOutput",le.Vector3),n.registerOutput("tangentOutput",le.Vector3),n.registerOutput("uvOutput",le.Vector2),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"MorphTargetsBlock"},Object.defineProperty(t.prototype,"position",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normal",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"tangent",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"uv",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"positionOutput",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normalOutput",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"tangentOutput",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"uvOutput",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),t.prototype.initialize=function(e){e._excludeVariableName("morphTargetInfluences")},t.prototype.autoConfigure=function(e){if(!this.position.isConnected){var n=e.getInputBlockByPredicate(function(s){return s.isAttribute&&s.name==="position"});n||(n=new At("position")).setAsAttribute(),n.output.connectTo(this.position)}if(!this.normal.isConnected){var i=e.getInputBlockByPredicate(function(s){return s.isAttribute&&s.name==="normal"});i||(i=new At("normal")).setAsAttribute("normal"),i.output.connectTo(this.normal)}if(!this.tangent.isConnected){var o=e.getInputBlockByPredicate(function(s){return s.isAttribute&&s.name==="tangent"});o||(o=new At("tangent")).setAsAttribute("tangent"),o.output.connectTo(this.tangent)}if(!this.uv.isConnected){var a=e.getInputBlockByPredicate(function(s){return s.isAttribute&&s.name==="uv"});a||(a=new At("uv")).setAsAttribute("uv"),a.output.connectTo(this.uv)}},t.prototype.prepareDefines=function(e,n,i){i._areAttributesDirty&&et.a.PrepareDefinesForMorphTargets(e,i)},t.prototype.bind=function(e,n,i){i&&i.morphTargetManager&&i.morphTargetManager.numInfluencers>0&&et.a.BindMorphTargetParameters(i,e)},t.prototype.replaceRepeatableContent=function(e,n,i,o){for(var a=this.position,s=this.normal,d=this.tangent,p=this.uv,b=this.positionOutput,P=this.normalOutput,O=this.tangentOutput,B=this.uvOutput,F=e,z=o.NUM_MORPH_INFLUENCERS,J=i.morphTargetManager,ie=J&&J.supportsNormals&&o.NORMAL,se=J&&J.supportsTangents&&o.TANGENT,ce=J&&J.supportsUVs&&o.UV1,ue="",fe=0;fe<z;fe++)ue+=`#ifdef MORPHTARGETS\r
-`,ue+=b.associatedVariableName+" += (position"+fe+" - "+a.associatedVariableName+") * morphTargetInfluences["+fe+`];\r
-`,ie&&(ue+=`#ifdef MORPHTARGETS_NORMAL\r
-`,ue+=P.associatedVariableName+" += (normal"+fe+" - "+s.associatedVariableName+") * morphTargetInfluences["+fe+`];\r
-`,ue+=`#endif\r
-`),se&&(ue+=`#ifdef MORPHTARGETS_TANGENT\r
-`,ue+=O.associatedVariableName+".xyz += (tangent"+fe+" - "+d.associatedVariableName+".xyz) * morphTargetInfluences["+fe+`];\r
-`,ue+=`#endif\r
-`),ce&&(ue+=`#ifdef MORPHTARGETS_UV\r
-`,ue+=B.associatedVariableName+".xy += (uv_"+fe+" - "+p.associatedVariableName+".xy) * morphTargetInfluences["+fe+`];\r
-`,ue+=`#endif\r
-`),ue+=`#endif\r
-`;if(F.compilationString=F.compilationString.replace(this._repeatableContentAnchor,ue),z>0)for(fe=0;fe<z;fe++)F.attributes.push(Oe.b.PositionKind+fe),ie&&F.attributes.push(Oe.b.NormalKind+fe),se&&F.attributes.push(Oe.b.TangentKind+fe),ce&&F.attributes.push(Oe.b.UVKind+"_"+fe)},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e),e.sharedData.blocksWithDefines.push(this),e.sharedData.bindableBlocks.push(this),e.sharedData.repeatableContentBlocks.push(this);var n=this.position,i=this.normal,o=this.tangent,a=this.uv,s=this.positionOutput,d=this.normalOutput,p=this.tangentOutput,b=this.uvOutput,P="//"+this.name;return e.uniforms.push("morphTargetInfluences"),e._emitFunctionFromInclude("morphTargetsVertexGlobalDeclaration",P),e._emitFunctionFromInclude("morphTargetsVertexDeclaration",P,{repeatKey:"maxSimultaneousMorphTargets"}),e.compilationString+=this._declareOutput(s,e)+" = "+n.associatedVariableName+`;\r
-`,e.compilationString+=`#ifdef NORMAL\r
-`,e.compilationString+=this._declareOutput(d,e)+" = "+i.associatedVariableName+`;\r
-`,e.compilationString+=`#else\r
-`,e.compilationString+=this._declareOutput(d,e)+` = vec3(0., 0., 0.);\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+=`#ifdef TANGENT\r
-`,e.compilationString+=this._declareOutput(p,e)+" = "+o.associatedVariableName+`;\r
-`,e.compilationString+=`#else\r
-`,e.compilationString+=this._declareOutput(p,e)+` = vec3(0., 0., 0.);\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+=`#ifdef UV1\r
-`,e.compilationString+=this._declareOutput(b,e)+" = "+a.associatedVariableName+`;\r
-`,e.compilationString+=`#else\r
-`,e.compilationString+=this._declareOutput(b,e)+` = vec2(0., 0.);\r
-`,e.compilationString+=`#endif\r
-`,this._repeatableContentAnchor=e._repeatableContentAnchor,e.compilationString+=this._repeatableContentAnchor,this},t}(pt);R.a.RegisteredTypes["BABYLON.MorphTargetsBlock"]=gh;var vh=function(r){function t(e){var n=r.call(this,e,Ce.Vertex)||this;return n.registerInput("worldPosition",le.Vector4,!1,Ce.Vertex),n.registerOutput("direction",le.Vector3),n.registerOutput("color",le.Color3),n.registerOutput("intensity",le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"LightInformationBlock"},Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"direction",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"color",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"intensity",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),t.prototype.bind=function(e,n,i){if(i){this.light&&this.light.isDisposed&&(this.light=null);var o=this.light,a=n.getScene();if(!o&&a.lights.length&&(o=a.lights[0]),!o||!o.isEnabled)return e.setFloat3(this._lightDataUniformName,0,0,0),void e.setFloat4(this._lightColorUniformName,0,0,0,0);o.transferToNodeMaterialEffect(e,this._lightDataUniformName),e.setColor4(this._lightColorUniformName,o.diffuse,o.intensity)}},t.prototype.prepareDefines=function(e,n,i){if(i._areLightsDirty){var o=this.light;i.setValue(this._lightTypeDefineName,!!(o&&o instanceof Xs))}},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e),e.sharedData.bindableBlocks.push(this),e.sharedData.blocksWithDefines.push(this);var n=this.direction,i=this.color,o=this.intensity;return this._lightDataUniformName=e._getFreeVariableName("lightData"),this._lightColorUniformName=e._getFreeVariableName("lightColor"),this._lightTypeDefineName=e._getFreeDefineName("LIGHTPOINTTYPE"),e._emitUniformFromString(this._lightDataUniformName,"vec3"),e._emitUniformFromString(this._lightColorUniformName,"vec4"),e.compilationString+="#ifdef "+this._lightTypeDefineName+`\r
-`,e.compilationString+=this._declareOutput(n,e)+" = normalize("+this.worldPosition.associatedVariableName+".xyz - "+this._lightDataUniformName+`);\r
-`,e.compilationString+=`#else\r
-`,e.compilationString+=this._declareOutput(n,e)+" = "+this._lightDataUniformName+`;\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+=this._declareOutput(i,e)+" = "+this._lightColorUniformName+`.rgb;\r
-`,e.compilationString+=this._declareOutput(o,e)+" = "+this._lightColorUniformName+`.a;\r
-`,this},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return this.light&&(e.lightId=this.light.id),e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),e.lightId&&(this.light=n.getLightByID(e.lightId))},t}(pt);R.a.RegisteredTypes["BABYLON.LightInformationBlock"]=vh;var bh=function(r){function t(e){var n=r.call(this,e,Ce.Fragment)||this;return n.registerInput("color",le.Color4),n.registerOutput("output",le.Color4),n._inputs[0].acceptedConnectionPointTypes.push(le.Color3),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ImageProcessingBlock"},Object.defineProperty(t.prototype,"color",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.initialize=function(e){e._excludeVariableName("exposureLinear"),e._excludeVariableName("contrast"),e._excludeVariableName("vInverseScreenSize"),e._excludeVariableName("vignetteSettings1"),e._excludeVariableName("vignetteSettings2"),e._excludeVariableName("vCameraColorCurveNegative"),e._excludeVariableName("vCameraColorCurveNeutral"),e._excludeVariableName("vCameraColorCurvePositive"),e._excludeVariableName("txColorTransform"),e._excludeVariableName("colorTransformSettings")},t.prototype.isReady=function(e,n,i){return!(i._areImageProcessingDirty&&n.imageProcessingConfiguration&&!n.imageProcessingConfiguration.isReady())},t.prototype.prepareDefines=function(e,n,i){i._areImageProcessingDirty&&n.imageProcessingConfiguration&&n.imageProcessingConfiguration.prepareDefines(i)},t.prototype.bind=function(e,n,i){i&&n.imageProcessingConfiguration&&n.imageProcessingConfiguration.bind(e)},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e),e.sharedData.blocksWithDefines.push(this),e.sharedData.blockingBlocks.push(this),e.sharedData.bindableBlocks.push(this),e.uniforms.push("exposureLinear"),e.uniforms.push("contrast"),e.uniforms.push("vInverseScreenSize"),e.uniforms.push("vignetteSettings1"),e.uniforms.push("vignetteSettings2"),e.uniforms.push("vCameraColorCurveNegative"),e.uniforms.push("vCameraColorCurveNeutral"),e.uniforms.push("vCameraColorCurvePositive"),e.uniforms.push("txColorTransform"),e.uniforms.push("colorTransformSettings");var n=this.color,i=this._outputs[0],o="//"+this.name;return e._emitFunctionFromInclude("helperFunctions",o),e._emitFunctionFromInclude("imageProcessingDeclaration",o),e._emitFunctionFromInclude("imageProcessingFunctions",o),n.connectedPoint.type===le.Color4||n.connectedPoint.type===le.Vector4?e.compilationString+=this._declareOutput(i,e)+" = "+n.associatedVariableName+`;\r
-`:e.compilationString+=this._declareOutput(i,e)+" = vec4("+n.associatedVariableName+`, 1.0);\r
-`,e.compilationString+=`#ifdef IMAGEPROCESSINGPOSTPROCESS\r
-`,e.compilationString+=i.associatedVariableName+".rgb = toLinearSpace("+n.associatedVariableName+`.rgb);\r
-`,e.compilationString+=`#else\r
-`,e.compilationString+=`#ifdef IMAGEPROCESSING\r
-`,e.compilationString+=i.associatedVariableName+".rgb = toLinearSpace("+n.associatedVariableName+`.rgb);\r
-`,e.compilationString+=i.associatedVariableName+" = applyImageProcessing("+i.associatedVariableName+`);\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+=`#endif\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ImageProcessingBlock"]=bh;var yh=function(r){function t(e){var n=r.call(this,e,Ce.Fragment)||this;return n._tangentSpaceParameterName="",n.invertX=!1,n.invertY=!1,n.registerInput("worldPosition",le.Vector4,!1),n.registerInput("worldNormal",le.Vector4,!1),n.registerInput("worldTangent",le.Vector4,!0),n.registerInput("uv",le.Vector2,!1),n.registerInput("normalMapColor",le.Color3,!1),n.registerInput("strength",le.Float,!1),n.registerOutput("output",le.Vector4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"PerturbNormalBlock"},Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldNormal",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldTangent",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"uv",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normalMapColor",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"strength",{get:function(){return this._inputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.prepareDefines=function(e,n,i){i.setValue("BUMP",!0)},t.prototype.bind=function(e,n,i){n.getScene()._mirroredCameraPosition?e.setFloat2(this._tangentSpaceParameterName,this.invertX?1:-1,this.invertY?1:-1):e.setFloat2(this._tangentSpaceParameterName,this.invertX?-1:1,this.invertY?-1:1)},t.prototype.autoConfigure=function(e){if(!this.uv.isConnected){var n=e.getInputBlockByPredicate(function(o){return o.isAttribute&&o.name==="uv"});n||(n=new At("uv")).setAsAttribute(),n.output.connectTo(this.uv)}if(!this.strength.isConnected){var i=new At("strength");i.value=1,i.output.connectTo(this.strength)}},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n="//"+this.name,i=this.uv,o=this.worldPosition,a=this.worldNormal,s=this.worldTangent;e.sharedData.blocksWithDefines.push(this),e.sharedData.bindableBlocks.push(this),this._tangentSpaceParameterName=e._getFreeDefineName("tangentSpaceParameter"),e._emitUniformFromString(this._tangentSpaceParameterName,"vec2");var d=this.strength.isConnectedToInputBlock&&this.strength.connectInputBlock.isConstant?""+e._emitFloat(1/this.strength.connectInputBlock.value):"1.0 / "+this.strength.associatedVariableName;e._emitExtension("derivatives","#extension GL_OES_standard_derivatives : enable");var p={search:/defined\(TANGENT\)/g,replace:s.isConnected?"defined(TANGENT)":"defined(IGNORE)"};return s.isConnected&&(e.compilationString+="vec3 tbnNormal = normalize("+a.associatedVariableName+`.xyz);\r
-`,e.compilationString+="vec3 tbnTangent = normalize("+s.associatedVariableName+`.xyz);\r
-`,e.compilationString+=`vec3 tbnBitangent = cross(tbnNormal, tbnTangent);\r
-`,e.compilationString+=`mat3 vTBN = mat3(tbnTangent, tbnBitangent, tbnNormal);\r
-`),e._emitFunctionFromInclude("bumpFragmentMainFunctions",n,{replaceStrings:[p]}),e._emitFunctionFromInclude("bumpFragmentFunctions",n,{replaceStrings:[{search:/vBumpInfos.y/g,replace:d},{search:/vTangentSpaceParams/g,replace:this._tangentSpaceParameterName},{search:/vPositionW/g,replace:o.associatedVariableName+".xyz"}]}),e.compilationString+=this._declareOutput(this.output,e)+` = vec4(0.);\r
-`,e.compilationString+=e._emitCodeFromInclude("bumpFragment",n,{replaceStrings:[{search:/perturbNormal\(TBN,vBumpUV\+uvOffset\)/g,replace:"perturbNormal(TBN, "+this.normalMapColor.associatedVariableName+")"},{search:/vBumpInfos.y/g,replace:d},{search:/vBumpUV/g,replace:i.associatedVariableName},{search:/vPositionW/g,replace:o.associatedVariableName+".xyz"},{search:/normalW=/g,replace:this.output.associatedVariableName+".xyz = "},{search:/mat3\(normalMatrix\)\*normalW/g,replace:"mat3(normalMatrix) * "+this.output.associatedVariableName+".xyz"},{search:/normalW/g,replace:a.associatedVariableName+".xyz"},p]}),this},t.prototype._dumpPropertiesCode=function(){var e=this._codeVariableName+".invertX = "+this.invertX+`;\r
-`;return e+=this._codeVariableName+".invertY = "+this.invertY+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.invertX=this.invertX,e.invertY=this.invertY,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.invertX=e.invertX,this.invertY=e.invertY},Object(c.c)([Vt("Invert X axis",Lt.Boolean,"PROPERTIES",{notifiers:{update:!1}})],t.prototype,"invertX",void 0),Object(c.c)([Vt("Invert Y axis",Lt.Boolean,"PROPERTIES",{notifiers:{update:!1}})],t.prototype,"invertY",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.PerturbNormalBlock"]=yh;var Th=function(r){function t(e){var n=r.call(this,e,Ce.Fragment,!0)||this;return n.registerInput("value",le.Float,!0),n.registerInput("cutoff",le.Float,!0),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DiscardBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cutoff",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.sharedData.hints.needAlphaTesting=!0,this.cutoff.isConnected&&this.value.isConnected)return e.compilationString+="if ("+this.value.associatedVariableName+" < "+this.cutoff.associatedVariableName+`) discard;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.DiscardBlock"]=Th;var Eh=function(r){function t(e){var n=r.call(this,e,Ce.Fragment)||this;return n.registerOutput("output",le.Float,Ce.Fragment),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FrontFacingBlock"},Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.target===Ce.Vertex)throw"FrontFacingBlock must only be used in a fragment shader";var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+` = gl_FrontFacing ? 1.0 : 0.0;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.FrontFacingBlock"]=Eh;var Sh=function(r){function t(e){var n=r.call(this,e,Ce.Fragment)||this;return n.registerInput("input",le.AutoDetect,!1),n.registerOutput("dx",le.BasedOnInput),n.registerOutput("dy",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._outputs[1]._typeConnectionSource=n._inputs[0],n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DerivativeBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dx",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dy",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i=this._outputs[1];return e._emitExtension("derivatives","#extension GL_OES_standard_derivatives : enable"),n.hasEndpoints&&(e.compilationString+=this._declareOutput(n,e)+" = dFdx("+this.input.associatedVariableName+`);\r
-`),i.hasEndpoints&&(e.compilationString+=this._declareOutput(i,e)+" = dFdy("+this.input.associatedVariableName+`);\r
-`),this},t}(pt);R.a.RegisteredTypes["BABYLON.DerivativeBlock"]=Sh;var Ah=function(r){function t(e){var n=r.call(this,e,Ce.Fragment)||this;return n.registerOutput("xy",le.Vector2,Ce.Fragment),n.registerOutput("xyz",le.Vector3,Ce.Fragment),n.registerOutput("xyzw",le.Vector4,Ce.Fragment),n.registerOutput("x",le.Float,Ce.Fragment),n.registerOutput("y",le.Float,Ce.Fragment),n.registerOutput("z",le.Float,Ce.Fragment),n.registerOutput("w",le.Float,Ce.Fragment),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FragCoordBlock"},Object.defineProperty(t.prototype,"xy",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyz",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyzw",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"x",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"y",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"z",{get:function(){return this._outputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[6]},enumerable:!1,configurable:!0}),t.prototype.writeOutputs=function(e){for(var n="",i=0,o=this._outputs;i<o.length;i++){var a=o[i];a.hasEndpoints&&(n+=this._declareOutput(a,e)+" = gl_FragCoord."+a.name+`;\r
-`)}return n},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.target===Ce.Vertex)throw"FragCoordBlock must only be used in a fragment shader";return e.compilationString+=this.writeOutputs(e),this},t}(pt);R.a.RegisteredTypes["BABYLON.FragCoordBlock"]=Ah;var Ph=function(r){function t(e){var n=r.call(this,e,Ce.Fragment)||this;return n.registerOutput("xy",le.Vector2,Ce.Fragment),n.registerOutput("x",le.Float,Ce.Fragment),n.registerOutput("y",le.Float,Ce.Fragment),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ScreenSizeBlock"},Object.defineProperty(t.prototype,"xy",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"x",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"y",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),t.prototype.bind=function(e,n,i){var o=this._scene.getEngine();e.setFloat2(this._varName,o.getRenderWidth(),o.getRenderWidth())},t.prototype.writeOutputs=function(e,n){for(var i="",o=0,a=this._outputs;o<a.length;o++){var s=a[o];s.hasEndpoints&&(i+=this._declareOutput(s,e)+" = "+n+"."+s.name+`;\r
-`)}return i},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),this._scene=e.sharedData.scene,e.target===Ce.Vertex)throw"ScreenSizeBlock must only be used in a fragment shader";return e.sharedData.bindableBlocks.push(this),this._varName=e._getFreeVariableName("screenSize"),e._emitUniformFromString(this._varName,"vec2"),e.compilationString+=this.writeOutputs(e,this._varName),this},t}(pt);R.a.RegisteredTypes["BABYLON.ScreenSizeBlock"]=Ph;var xh=function(r){function t(e){var n=r.call(this,e,Ce.VertexAndFragment,!0)||this;return n.registerInput("worldPosition",le.Vector4,!1,Ce.Vertex),n.registerInput("view",le.Matrix,!1,Ce.Vertex),n.registerInput("input",le.Color3,!1,Ce.Fragment),n.registerInput("fogColor",le.Color3,!1,Ce.Fragment),n.registerOutput("output",le.Color3,Ce.Fragment),n.input.acceptedConnectionPointTypes.push(le.Color4),n.fogColor.acceptedConnectionPointTypes.push(le.Color4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FogBlock"},Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"view",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"fogColor",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.view.isConnected){var n=e.getInputBlockByPredicate(function(o){return o.systemValue===bt.View});n||(n=new At("view")).setAsSystemValue(bt.View),n.output.connectTo(this.view)}if(!this.fogColor.isConnected){var i=e.getInputBlockByPredicate(function(o){return o.systemValue===bt.FogColor});i||(i=new At("fogColor",void 0,le.Color3)).setAsSystemValue(bt.FogColor),i.output.connectTo(this.fogColor)}},t.prototype.prepareDefines=function(e,n,i){var o=e.getScene();i.setValue("FOG",n.fogEnabled&&et.a.GetFogState(e,o))},t.prototype.bind=function(e,n,i){if(i){var o=i.getScene();e.setFloat4(this._fogParameters,o.fogMode,o.fogStart,o.fogEnd,o.fogDensity)}},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.target===Ce.Fragment){e.sharedData.blocksWithDefines.push(this),e.sharedData.bindableBlocks.push(this),e._emitFunctionFromInclude("fogFragmentDeclaration","//"+this.name,{removeUniforms:!0,removeVaryings:!0,removeIfDef:!1,replaceStrings:[{search:/float CalcFogFactor\(\)/,replace:"float CalcFogFactor(vec3 vFogDistance, vec4 vFogInfos)"}]});var n=e._getFreeVariableName("fog"),i=this.input,o=this.fogColor;this._fogParameters=e._getFreeVariableName("fogParameters");var a=this._outputs[0];e._emitUniformFromString(this._fogParameters,"vec4"),e.compilationString+=`#ifdef FOG\r
-`,e.compilationString+="float "+n+" = CalcFogFactor("+this._fogDistanceName+", "+this._fogParameters+`);\r
-`,e.compilationString+=this._declareOutput(a,e)+" = "+n+" * "+i.associatedVariableName+".rgb + (1.0 - "+n+") * "+o.associatedVariableName+`.rgb;\r
-`,e.compilationString+=`#else\r
-`+this._declareOutput(a,e)+" =  "+i.associatedVariableName+`.rgb;\r
-`,e.compilationString+=`#endif\r
-`}else{var s=this.worldPosition,d=this.view;this._fogDistanceName=e._getFreeVariableName("vFogDistance"),e._emitVaryingFromString(this._fogDistanceName,"vec3"),e.compilationString+=this._fogDistanceName+" = ("+d.associatedVariableName+" * "+s.associatedVariableName+`).xyz;\r
-`}return this},t}(pt);R.a.RegisteredTypes["BABYLON.FogBlock"]=xh;var Ch=function(r){function t(e){var n=r.call(this,e,Ce.VertexAndFragment)||this;return n._isUnique=!0,n.registerInput("worldPosition",le.Vector4,!1,Ce.Vertex),n.registerInput("worldNormal",le.Vector4,!1,Ce.Fragment),n.registerInput("cameraPosition",le.Vector3,!1,Ce.Fragment),n.registerInput("glossiness",le.Float,!0,Ce.Fragment),n.registerInput("glossPower",le.Float,!0,Ce.Fragment),n.registerInput("diffuseColor",le.Color3,!0,Ce.Fragment),n.registerInput("specularColor",le.Color3,!0,Ce.Fragment),n.registerInput("view",le.Matrix,!0),n.registerOutput("diffuseOutput",le.Color3,Ce.Fragment),n.registerOutput("specularOutput",le.Color3,Ce.Fragment),n.registerOutput("shadow",le.Float,Ce.Fragment),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"LightBlock"},Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldNormal",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraPosition",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"glossiness",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"glossPower",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"diffuseColor",{get:function(){return this._inputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"specularColor",{get:function(){return this._inputs[6]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"view",{get:function(){return this._inputs[7]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"diffuseOutput",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"specularOutput",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"shadow",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.cameraPosition.isConnected){var n=e.getInputBlockByPredicate(function(i){return i.systemValue===bt.CameraPosition});n||(n=new At("cameraPosition")).setAsSystemValue(bt.CameraPosition),n.output.connectTo(this.cameraPosition)}},t.prototype.prepareDefines=function(e,n,i){if(i._areLightsDirty){var o=e.getScene();if(this.light){var a={needNormals:!1,needRebuild:!1,lightmapMode:!1,shadowEnabled:!1,specularEnabled:!1};et.a.PrepareDefinesForLight(o,e,this.light,this._lightId,i,!0,a),a.needRebuild&&i.rebuild()}else et.a.PrepareDefinesForLights(o,e,i,!0,n.maxSimultaneousLights)}},t.prototype.updateUniformsAndSamples=function(e,n,i,o){for(var a=0;a<n.maxSimultaneousLights&&i["LIGHT"+a];a++){var s=e.uniforms.indexOf("vLightData"+a)>=0;et.a.PrepareUniformsAndSamplersForLight(a,e.uniforms,e.samplers,i["PROJECTEDLIGHTTEXTURE"+a],o,s)}},t.prototype.bind=function(e,n,i){if(i){var o=i.getScene();this.light?et.a.BindLight(this.light,this._lightId,o,e,!0):et.a.BindLights(o,i,e,!0,n.maxSimultaneousLights)}},t.prototype._injectVertexCode=function(e){var n=this.worldPosition,i="//"+this.name;this.light?(this._lightId=(e.counters.lightCounter!==void 0?e.counters.lightCounter:-1)+1,e.counters.lightCounter=this._lightId,e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",i,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()}]},this._lightId.toString())):(e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",i,{repeatKey:"maxSimultaneousLights"}),this._lightId=0,e.sharedData.dynamicUniformBlocks.push(this));var o="v_"+n.associatedVariableName;e._emitVaryingFromString(o,"vec4")&&(e.compilationString+=o+" = "+n.associatedVariableName+`;\r
-`),this.light?e.compilationString+=e._emitCodeFromInclude("shadowsVertex",i,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()},{search:/worldPos/g,replace:n.associatedVariableName}]}):(e.compilationString+="vec4 worldPos = "+n.associatedVariableName+`;\r
-`,this.view.isConnected&&(e.compilationString+="mat4 view = "+this.view.associatedVariableName+`;\r
-`),e.compilationString+=e._emitCodeFromInclude("shadowsVertex",i,{repeatKey:"maxSimultaneousLights"}))},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),e.target===Ce.Fragment){e.sharedData.bindableBlocks.push(this),e.sharedData.blocksWithDefines.push(this);var n="//"+this.name,i=this.worldPosition;e._emitFunctionFromInclude("helperFunctions",n),e._emitFunctionFromInclude("lightsFragmentFunctions",n,{replaceStrings:[{search:/vPositionW/g,replace:"v_"+i.associatedVariableName+".xyz"}]}),e._emitFunctionFromInclude("shadowsFragmentFunctions",n,{replaceStrings:[{search:/vPositionW/g,replace:"v_"+i.associatedVariableName+".xyz"}]}),this.light?e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",n,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()}]},this._lightId.toString()):e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",n,{repeatKey:"maxSimultaneousLights"}),this._lightId===0&&(e._registerTempVariable("viewDirectionW")&&(e.compilationString+="vec3 viewDirectionW = normalize("+this.cameraPosition.associatedVariableName+" - v_"+i.associatedVariableName+`.xyz);\r
-`),e.compilationString+=`lightingInfo info;\r
-`,e.compilationString+=`float shadow = 1.;\r
-`,e.compilationString+="float glossiness = "+(this.glossiness.isConnected?this.glossiness.associatedVariableName:"1.0")+" * "+(this.glossPower.isConnected?this.glossPower.associatedVariableName:"1024.0")+`;\r
-`,e.compilationString+=`vec3 diffuseBase = vec3(0., 0., 0.);\r
-`,e.compilationString+=`vec3 specularBase = vec3(0., 0., 0.);\r
-`,e.compilationString+="vec3 normalW = "+this.worldNormal.associatedVariableName+`.xyz;\r
-`),this.light?e.compilationString+=e._emitCodeFromInclude("lightFragment",n,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()}]}):e.compilationString+=e._emitCodeFromInclude("lightFragment",n,{repeatKey:"maxSimultaneousLights"});var o=this.diffuseOutput,a=this.specularOutput;return e.compilationString+=this._declareOutput(o,e)+" = diffuseBase"+(this.diffuseColor.isConnected?" * "+this.diffuseColor.associatedVariableName:"")+`;\r
-`,a.hasEndpoints&&(e.compilationString+=this._declareOutput(a,e)+" = specularBase"+(this.specularColor.isConnected?" * "+this.specularColor.associatedVariableName:"")+`;\r
-`),this.shadow.hasEndpoints&&(e.compilationString+=this._declareOutput(this.shadow,e)+` = shadow;\r
-`),this}this._injectVertexCode(e)},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return this.light&&(e.lightId=this.light.id),e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),e.lightId&&(this.light=n.getLightByID(e.lightId))},t}(pt);R.a.RegisteredTypes["BABYLON.LightBlock"]=Ch;var Rh=function(r){function t(e,n){n===void 0&&(n=!1);var i=r.call(this,e,n?Ce.Fragment:Ce.VertexAndFragment)||this;return i.convertToGammaSpace=!1,i.convertToLinearSpace=!1,i._fragmentOnly=n,i.registerInput("uv",le.Vector2,!1,Ce.VertexAndFragment),i.registerOutput("rgba",le.Color4,Ce.Neutral),i.registerOutput("rgb",le.Color3,Ce.Neutral),i.registerOutput("r",le.Float,Ce.Neutral),i.registerOutput("g",le.Float,Ce.Neutral),i.registerOutput("b",le.Float,Ce.Neutral),i.registerOutput("a",le.Float,Ce.Neutral),i._inputs[0].acceptedConnectionPointTypes.push(le.Vector3),i._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),i._inputs[0]._prioritizeVertex=!n,i}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"TextureBlock"},Object.defineProperty(t.prototype,"uv",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgba",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgb",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"r",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"g",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"b",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"a",{get:function(){return this._outputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"target",{get:function(){if(this._fragmentOnly)return Ce.Fragment;if(!this.uv.isConnected||this.uv.sourceBlock.isInput)return Ce.VertexAndFragment;for(var e=this.uv.connectedPoint;e;){if(e.target===Ce.Fragment)return Ce.Fragment;if(e.target===Ce.Vertex)return Ce.VertexAndFragment;if(e.target===Ce.Neutral||e.target===Ce.VertexAndFragment){var n=e.ownerBlock;e=null;for(var i=0,o=n.inputs;i<o.length;i++){var a=o[i];if(a.connectedPoint){e=a.connectedPoint;break}}}}return Ce.VertexAndFragment},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.uv.isConnected)if(e.mode===Mn.PostProcess)(n=e.getBlockByPredicate(function(o){return o.name==="uv"}))&&n.connectTo(this);else{var n,i=e.mode===Mn.Particle?"particle_uv":"uv";(n=e.getInputBlockByPredicate(function(o){return o.isAttribute&&o.name===i}))||(n=new At("uv")).setAsAttribute(i),n.output.connectTo(this.uv)}},t.prototype.initializeDefines=function(e,n,i,o){i._areTexturesDirty&&i.setValue(this._mainUVDefineName,!1)},t.prototype.prepareDefines=function(e,n,i){if(i._areTexturesDirty){if(!this.texture||!this.texture.getTextureMatrix)return i.setValue(this._defineName,!1),void i.setValue(this._mainUVDefineName,!0);i.setValue(this._linearDefineName,this.convertToGammaSpace),i.setValue(this._gammaDefineName,this.convertToLinearSpace),this._isMixed&&(this.texture.getTextureMatrix().isIdentityAs3x2()?(i.setValue(this._defineName,!1),i.setValue(this._mainUVDefineName,!0)):i.setValue(this._defineName,!0))}},t.prototype.isReady=function(){return!(this.texture&&!this.texture.isReadyOrNotBlocking())},t.prototype.bind=function(e,n,i){this.texture&&(this._isMixed&&(e.setFloat(this._textureInfoName,this.texture.level),e.setMatrix(this._textureTransformName,this.texture.getTextureMatrix())),e.setTexture(this._samplerName,this.texture))},Object.defineProperty(t.prototype,"_isMixed",{get:function(){return this.target!==Ce.Fragment},enumerable:!1,configurable:!0}),t.prototype._injectVertexCode=function(e){var n=this.uv;if(this._defineName=e._getFreeDefineName("UVTRANSFORM"),this._mainUVDefineName="VMAIN"+n.associatedVariableName.toUpperCase(),n.connectedPoint.ownerBlock.isInput&&(n.connectedPoint.ownerBlock.isAttribute||e._emitUniformFromString(n.associatedVariableName,"vec2")),this._mainUVName="vMain"+n.associatedVariableName,this._transformedUVName=e._getFreeVariableName("transformedUV"),this._textureTransformName=e._getFreeVariableName("textureTransform"),this._textureInfoName=e._getFreeVariableName("textureInfoName"),e._emitVaryingFromString(this._transformedUVName,"vec2",this._defineName),e._emitVaryingFromString(this._mainUVName,"vec2",this._mainUVDefineName),e._emitUniformFromString(this._textureTransformName,"mat4",this._defineName),e.compilationString+="#ifdef "+this._defineName+`\r
-`,e.compilationString+=this._transformedUVName+" = vec2("+this._textureTransformName+" * vec4("+n.associatedVariableName+`.xy, 1.0, 0.0));\r
-`,e.compilationString+="#elif defined("+this._mainUVDefineName+`)\r
-`,e.compilationString+=this._mainUVName+" = "+n.associatedVariableName+`.xy;\r
-`,e.compilationString+=`#endif\r
-`,this._outputs.some(function(s){return s.isConnectedInVertexShader})){this._writeTextureRead(e,!0);for(var i=0,o=this._outputs;i<o.length;i++){var a=o[i];a.hasEndpoints&&this._writeOutput(e,a,a.name,!0)}}},t.prototype._writeTextureRead=function(e,n){n===void 0&&(n=!1);var i=this.uv;if(n){if(e.target===Ce.Fragment)return;e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+i.associatedVariableName+`);\r
-`}else this.uv.ownerBlock.target!==Ce.Fragment?(e.compilationString+="#ifdef "+this._defineName+`\r
-`,e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+this._transformedUVName+`);\r
-`,e.compilationString+="#elif defined("+this._mainUVDefineName+`)\r
-`,e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+this._mainUVName+`);\r
-`,e.compilationString+=`#endif\r
-`):e.compilationString+="vec4 "+this._tempTextureRead+" = texture2D("+this._samplerName+", "+i.associatedVariableName+`);\r
-`},t.prototype._writeOutput=function(e,n,i,o){if(o===void 0&&(o=!1),o){if(e.target===Ce.Fragment)return;e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+`;\r
-`}else if(this.uv.ownerBlock.target!==Ce.Fragment){var a=" * "+this._textureInfoName;e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+a+`;\r
-`,i!=="a"&&(e.compilationString+="#ifdef "+this._linearDefineName+`\r
-`,e.compilationString+=n.associatedVariableName+" = toGammaSpace("+n.associatedVariableName+`);\r
-`,e.compilationString+=`#endif\r
-`,e.compilationString+="#ifdef "+this._gammaDefineName+`\r
-`,e.compilationString+=n.associatedVariableName+" = toLinearSpace("+n.associatedVariableName+`);\r
-`,e.compilationString+=`#endif\r
-`)}else e.compilationString+=this._declareOutput(n,e)+" = "+this._tempTextureRead+"."+i+`;\r
-`},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),(e.target===Ce.Vertex||this._fragmentOnly)&&(this._tempTextureRead=e._getFreeVariableName("tempTextureRead")),(!this._isMixed&&e.target===Ce.Fragment||this._isMixed&&e.target===Ce.Vertex)&&(this._samplerName=e._getFreeVariableName(this.name+"Sampler"),e._emit2DSampler(this._samplerName),e.sharedData.blockingBlocks.push(this),e.sharedData.textureBlocks.push(this),e.sharedData.blocksWithDefines.push(this),e.sharedData.bindableBlocks.push(this)),e.target===Ce.Fragment){if(this._outputs.some(function(s){return s.isConnectedInFragmentShader})){this._isMixed&&e._emit2DSampler(this._samplerName),this._linearDefineName=e._getFreeDefineName("ISLINEAR"),this._gammaDefineName=e._getFreeDefineName("ISGAMMA");var n="//"+this.name;e._emitFunctionFromInclude("helperFunctions",n),this._isMixed&&e._emitUniformFromString(this._textureInfoName,"float"),this._writeTextureRead(e);for(var i=0,o=this._outputs;i<o.length;i++){var a=o[i];a.hasEndpoints&&this._writeOutput(e,a,a.name)}return this}}else this._injectVertexCode(e)},t.prototype._dumpPropertiesCode=function(){if(!this.texture)return"";var e=this._codeVariableName+'.texture = new BABYLON.Texture("'+this.texture.name+`", null);\r
-`;return e+=this._codeVariableName+".texture.wrapU = "+this.texture.wrapU+`;\r
-`,e+=this._codeVariableName+".texture.wrapV = "+this.texture.wrapV+`;\r
-`,e+=this._codeVariableName+".texture.uAng = "+this.texture.uAng+`;\r
-`,e+=this._codeVariableName+".texture.vAng = "+this.texture.vAng+`;\r
-`,e+=this._codeVariableName+".texture.wAng = "+this.texture.wAng+`;\r
-`,e+=this._codeVariableName+".texture.uOffset = "+this.texture.uOffset+`;\r
-`,e+=this._codeVariableName+".texture.vOffset = "+this.texture.vOffset+`;\r
-`,e+=this._codeVariableName+".texture.uScale = "+this.texture.uScale+`;\r
-`,e+=this._codeVariableName+".texture.vScale = "+this.texture.vScale+`;\r
-`,e+=this._codeVariableName+".convertToGammaSpace = "+this.convertToGammaSpace+`;\r
-`,e+=this._codeVariableName+".convertToLinearSpace = "+this.convertToLinearSpace+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.convertToGammaSpace=this.convertToGammaSpace,e.convertToLinearSpace=this.convertToLinearSpace,e.fragmentOnly=this._fragmentOnly,this.texture&&!this.texture.isRenderTarget&&(e.texture=this.texture.serialize()),e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.convertToGammaSpace=e.convertToGammaSpace,this.convertToLinearSpace=!!e.convertToLinearSpace,this._fragmentOnly=!!e.fragmentOnly,e.texture&&!ga.IgnoreTexturesAtLoadTime&&(i=e.texture.url.indexOf("data:")===0?"":i,this.texture=we.a.Parse(e.texture,n,i))},t}(pt);R.a.RegisteredTypes["BABYLON.TextureBlock"]=Rh;var pc=function(r){function t(e){return r.call(this,e,Ce.VertexAndFragment)||this}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ReflectionTextureBaseBlock"},t.prototype._getTexture=function(){return this.texture},t.prototype.autoConfigure=function(e){if(!this.position.isConnected){var n=e.getInputBlockByPredicate(function(a){return a.isAttribute&&a.name==="position"});n||(n=new At("position")).setAsAttribute(),n.output.connectTo(this.position)}if(!this.world.isConnected){var i=e.getInputBlockByPredicate(function(a){return a.systemValue===bt.World});i||(i=new At("world")).setAsSystemValue(bt.World),i.output.connectTo(this.world)}if(this.view&&!this.view.isConnected){var o=e.getInputBlockByPredicate(function(a){return a.systemValue===bt.View});o||(o=new At("view")).setAsSystemValue(bt.View),o.output.connectTo(this.view)}},t.prototype.prepareDefines=function(e,n,i){if(i._areTexturesDirty){var o=this._getTexture();o&&o.getTextureMatrix&&(i.setValue(this._define3DName,o.isCube,!0),i.setValue(this._defineLocalCubicName,!!o.boundingBoxSize,!0),i.setValue(this._defineExplicitName,o.coordinatesMode===h.a.TEXTURE_EXPLICIT_MODE,!0),i.setValue(this._defineSkyboxName,o.coordinatesMode===h.a.TEXTURE_SKYBOX_MODE,!0),i.setValue(this._defineCubicName,o.coordinatesMode===h.a.TEXTURE_CUBIC_MODE||o.coordinatesMode===h.a.TEXTURE_INVCUBIC_MODE,!0),i.setValue("INVERTCUBICMAP",o.coordinatesMode===h.a.TEXTURE_INVCUBIC_MODE,!0),i.setValue(this._defineSphericalName,o.coordinatesMode===h.a.TEXTURE_SPHERICAL_MODE,!0),i.setValue(this._definePlanarName,o.coordinatesMode===h.a.TEXTURE_PLANAR_MODE,!0),i.setValue(this._defineProjectionName,o.coordinatesMode===h.a.TEXTURE_PROJECTION_MODE,!0),i.setValue(this._defineEquirectangularName,o.coordinatesMode===h.a.TEXTURE_EQUIRECTANGULAR_MODE,!0),i.setValue(this._defineEquirectangularFixedName,o.coordinatesMode===h.a.TEXTURE_FIXED_EQUIRECTANGULAR_MODE,!0),i.setValue(this._defineMirroredEquirectangularFixedName,o.coordinatesMode===h.a.TEXTURE_FIXED_EQUIRECTANGULAR_MIRRORED_MODE,!0))}},t.prototype.isReady=function(){var e=this._getTexture();return!(e&&!e.isReadyOrNotBlocking())},t.prototype.bind=function(e,n,i){var o=this._getTexture();i&&o&&(e.setMatrix(this._reflectionMatrixName,o.getReflectionTextureMatrix()),o.isCube?e.setTexture(this._cubeSamplerName,o):e.setTexture(this._2DSamplerName,o))},t.prototype.handleVertexSide=function(e){this._define3DName=e._getFreeDefineName("REFLECTIONMAP_3D"),this._defineCubicName=e._getFreeDefineName("REFLECTIONMAP_CUBIC"),this._defineSphericalName=e._getFreeDefineName("REFLECTIONMAP_SPHERICAL"),this._definePlanarName=e._getFreeDefineName("REFLECTIONMAP_PLANAR"),this._defineProjectionName=e._getFreeDefineName("REFLECTIONMAP_PROJECTION"),this._defineExplicitName=e._getFreeDefineName("REFLECTIONMAP_EXPLICIT"),this._defineEquirectangularName=e._getFreeDefineName("REFLECTIONMAP_EQUIRECTANGULAR"),this._defineLocalCubicName=e._getFreeDefineName("USE_LOCAL_REFLECTIONMAP_CUBIC"),this._defineMirroredEquirectangularFixedName=e._getFreeDefineName("REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED"),this._defineEquirectangularFixedName=e._getFreeDefineName("REFLECTIONMAP_EQUIRECTANGULAR_FIXED"),this._defineSkyboxName=e._getFreeDefineName("REFLECTIONMAP_SKYBOX"),this._defineOppositeZ=e._getFreeDefineName("REFLECTIONMAP_OPPOSITEZ"),this._reflectionMatrixName=e._getFreeVariableName("reflectionMatrix"),e._emitUniformFromString(this._reflectionMatrixName,"mat4");var n="",i="v_"+this.worldPosition.associatedVariableName;return e._emitVaryingFromString(i,"vec4")&&(n+=i+" = "+this.worldPosition.associatedVariableName+`;\r
-`),this._positionUVWName=e._getFreeVariableName("positionUVW"),this._directionWName=e._getFreeVariableName("directionW"),e._emitVaryingFromString(this._positionUVWName,"vec3",this._defineSkyboxName)&&(n+="#ifdef "+this._defineSkyboxName+`\r
-`,n+=this._positionUVWName+" = "+this.position.associatedVariableName+`.xyz;\r
-`,n+=`#endif\r
-`),e._emitVaryingFromString(this._directionWName,"vec3","defined("+this._defineEquirectangularFixedName+") || defined("+this._defineMirroredEquirectangularFixedName+")")&&(n+="#if defined("+this._defineEquirectangularFixedName+") || defined("+this._defineMirroredEquirectangularFixedName+`)\r
-`,n+=this._directionWName+" = normalize(vec3("+this.world.associatedVariableName+" * vec4("+this.position.associatedVariableName+`.xyz, 0.0)));\r
-`,n+=`#endif\r
-`),n},t.prototype.handleFragmentSideInits=function(e){e.sharedData.blockingBlocks.push(this),e.sharedData.textureBlocks.push(this),this._cubeSamplerName=e._getFreeVariableName(this.name+"CubeSampler"),e.samplers.push(this._cubeSamplerName),this._2DSamplerName=e._getFreeVariableName(this.name+"2DSampler"),e.samplers.push(this._2DSamplerName),e._samplerDeclaration+="#ifdef "+this._define3DName+`\r
-`,e._samplerDeclaration+="uniform samplerCube "+this._cubeSamplerName+`;\r
-`,e._samplerDeclaration+=`#else\r
-`,e._samplerDeclaration+="uniform sampler2D "+this._2DSamplerName+`;\r
-`,e._samplerDeclaration+=`#endif\r
-`,e.sharedData.blocksWithDefines.push(this),e.sharedData.bindableBlocks.push(this);var n="//"+this.name;e._emitFunction("ReciprocalPI","#define RECIPROCAL_PI2 0.15915494",""),e._emitFunctionFromInclude("reflectionFunction",n,{replaceStrings:[{search:/vec3 computeReflectionCoords/g,replace:"void DUMMYFUNC"}]}),this._reflectionColorName=e._getFreeVariableName("reflectionColor"),this._reflectionVectorName=e._getFreeVariableName("reflectionUVW"),this._reflectionCoordsName=e._getFreeVariableName("reflectionCoords")},t.prototype.handleFragmentSideCodeReflectionCoords=function(e,n,i){i===void 0&&(i=!1),n||(n="v_"+this.worldPosition.associatedVariableName);var o=this._reflectionMatrixName,a="normalize("+this._directionWName+")",s=""+this._positionUVWName,d=""+this.cameraPosition.associatedVariableName,p=""+this.view.associatedVariableName;e+=".xyz";var b=`
-            #ifdef `+this._defineMirroredEquirectangularFixedName+`
-                vec3 `+this._reflectionVectorName+" = computeMirroredFixedEquirectangularCoords("+n+", "+e+", "+a+`);
-            #endif
-
-            #ifdef `+this._defineEquirectangularFixedName+`
-                vec3 `+this._reflectionVectorName+" = computeFixedEquirectangularCoords("+n+", "+e+", "+a+`);
-            #endif
-
-            #ifdef `+this._defineEquirectangularName+`
-                vec3 `+this._reflectionVectorName+" = computeEquirectangularCoords("+n+", "+e+", "+d+".xyz, "+o+`);
-            #endif
-
-            #ifdef `+this._defineSphericalName+`
-                vec3 `+this._reflectionVectorName+" = computeSphericalCoords("+n+", "+e+", "+p+", "+o+`);
-            #endif
-
-            #ifdef `+this._definePlanarName+`
-                vec3 `+this._reflectionVectorName+" = computePlanarCoords("+n+", "+e+", "+d+".xyz, "+o+`);
-            #endif
-
-            #ifdef `+this._defineCubicName+`
-                #ifdef `+this._defineLocalCubicName+`
-                    vec3 `+this._reflectionVectorName+" = computeCubicLocalCoords("+n+", "+e+", "+d+".xyz, "+o+`, vReflectionSize, vReflectionPosition);
-                #else
-                vec3 `+this._reflectionVectorName+" = computeCubicCoords("+n+", "+e+", "+d+".xyz, "+o+`);
-                #endif
-            #endif
-
-            #ifdef `+this._defineProjectionName+`
-                vec3 `+this._reflectionVectorName+" = computeProjectionCoords("+n+", "+p+", "+o+`);
-            #endif
-
-            #ifdef `+this._defineSkyboxName+`
-                vec3 `+this._reflectionVectorName+" = computeSkyBoxCoords("+s+", "+o+`);
-            #endif
-
-            #ifdef `+this._defineExplicitName+`
-                vec3 `+this._reflectionVectorName+` = vec3(0, 0, 0);
-            #endif
-
-            #ifdef `+this._defineOppositeZ+`
-                `+this._reflectionVectorName+`.z *= -1.0;
-            #endif\r
-`;return i||(b+=`
-                #ifdef `+this._define3DName+`
-                    vec3 `+this._reflectionCoordsName+" = "+this._reflectionVectorName+`;
-                #else
-                    vec2 `+this._reflectionCoordsName+" = "+this._reflectionVectorName+`.xy;
-                    #ifdef `+this._defineProjectionName+`
-                        `+this._reflectionCoordsName+" /= "+this._reflectionVectorName+`.z;
-                    #endif
-                    `+this._reflectionCoordsName+".y = 1.0 - "+this._reflectionCoordsName+`.y;
-                #endif\r
-`),b},t.prototype.handleFragmentSideCodeReflectionColor=function(e,n){n===void 0&&(n=".rgb");var i="vec"+(n.length===0?"4":n.length-1)+" "+this._reflectionColorName+`;
-            #ifdef `+this._define3DName+`\r
-`;return i+=e?this._reflectionColorName+" = textureCubeLodEXT("+this._cubeSamplerName+", "+this._reflectionVectorName+", "+e+")"+n+`;\r
-`:this._reflectionColorName+" = textureCube("+this._cubeSamplerName+", "+this._reflectionVectorName+")"+n+`;\r
-`,i+=`
-            #else\r
-`,i+=e?this._reflectionColorName+" = texture2DLodEXT("+this._2DSamplerName+", "+this._reflectionCoordsName+", "+e+")"+n+`;\r
-`:this._reflectionColorName+" = texture2D("+this._2DSamplerName+", "+this._reflectionCoordsName+")"+n+`;\r
-`,i+=`#endif\r
-`},t.prototype.writeOutputs=function(e,n){var i="";if(e.target===Ce.Fragment)for(var o=0,a=this._outputs;o<a.length;o++){var s=a[o];s.hasEndpoints&&(i+=this._declareOutput(s,e)+" = "+n+"."+s.name+`;\r
-`)}return i},t.prototype._buildBlock=function(e){return r.prototype._buildBlock.call(this,e),this},t.prototype._dumpPropertiesCode=function(){return this.texture?(e=this.texture.isCube?this._codeVariableName+'.texture = new BABYLON.CubeTexture("'+this.texture.name+`");\r
-`:this._codeVariableName+'.texture = new BABYLON.Texture("'+this.texture.name+`");\r
-`,e+=this._codeVariableName+".texture.coordinatesMode = "+this.texture.coordinatesMode+`;\r
-`):"";var e},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return this.texture&&(e.texture=this.texture.serialize()),e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),e.texture&&(i=e.texture.url.indexOf("data:")===0?"":i,e.texture.isCube?this.texture=oi.Parse(e.texture,n,i):this.texture=we.a.Parse(e.texture,n,i))},t}(pt);R.a.RegisteredTypes["BABYLON.ReflectionTextureBaseBlock"]=pc;var Oh=function(r){function t(e){var n=r.call(this,e)||this;return n.registerInput("position",le.Vector3,!1,Ce.Vertex),n.registerInput("worldPosition",le.Vector4,!1,Ce.Vertex),n.registerInput("worldNormal",le.Vector4,!1,Ce.Fragment),n.registerInput("world",le.Matrix,!1,Ce.Vertex),n.registerInput("cameraPosition",le.Vector3,!1,Ce.Fragment),n.registerInput("view",le.Matrix,!1,Ce.Fragment),n.registerOutput("rgb",le.Color3,Ce.Fragment),n.registerOutput("rgba",le.Color4,Ce.Fragment),n.registerOutput("r",le.Float,Ce.Fragment),n.registerOutput("g",le.Float,Ce.Fragment),n.registerOutput("b",le.Float,Ce.Fragment),n.registerOutput("a",le.Float,Ce.Fragment),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ReflectionTextureBlock"},Object.defineProperty(t.prototype,"position",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldNormal",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"world",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraPosition",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"view",{get:function(){return this._inputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgb",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgba",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"r",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"g",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"b",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"a",{get:function(){return this._outputs[5]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(r.prototype.autoConfigure.call(this,e),!this.cameraPosition.isConnected){var n=e.getInputBlockByPredicate(function(i){return i.systemValue===bt.CameraPosition});n||(n=new At("cameraPosition")).setAsSystemValue(bt.CameraPosition),n.output.connectTo(this.cameraPosition)}},t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),!this.texture)return e.compilationString+=this.writeOutputs(e,"vec3(0.)"),this;if(e.target!==Ce.Fragment)return e.compilationString+=this.handleVertexSide(e),this;this.handleFragmentSideInits(e);var n=e._getFreeVariableName("normalWUnit");return e.compilationString+="vec4 "+n+" = normalize("+this.worldNormal.associatedVariableName+`);\r
-`,e.compilationString+=this.handleFragmentSideCodeReflectionCoords(n),e.compilationString+=this.handleFragmentSideCodeReflectionColor(void 0,""),e.compilationString+=this.writeOutputs(e,this._reflectionColorName),this},t}(pc);R.a.RegisteredTypes["BABYLON.ReflectionTextureBlock"]=Oh;var Mh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"AddBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = "+this.left.associatedVariableName+" + "+this.right.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.AddBlock"]=Mh;var Ih=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("input",le.AutoDetect),n.registerInput("factor",le.Float),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ScaleBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"factor",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = "+this.input.associatedVariableName+" * "+this.factor.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ScaleBlock"]=Ih;var Dh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.minimum=0,n.maximum=1,n.registerInput("value",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ClampBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = clamp("+this.value.associatedVariableName+", "+this._writeFloat(this.minimum)+", "+this._writeFloat(this.maximum)+`);\r
-`,this},t.prototype._dumpPropertiesCode=function(){var e=this._codeVariableName+".minimum = "+this.minimum+`;\r
-`;return e+=this._codeVariableName+".maximum = "+this.maximum+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.minimum=this.minimum,e.maximum=this.maximum,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.minimum=e.minimum,this.maximum=e.maximum},Object(c.c)([Vt("Minimum",Lt.Float)],t.prototype,"minimum",void 0),Object(c.c)([Vt("Maximum",Lt.Float)],t.prototype,"maximum",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.ClampBlock"]=Dh;var Lh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.Vector3),n._linkConnectionTypes(0,1),n._inputs[0].excludedConnectionPointTypes.push(le.Float),n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n._inputs[0].excludedConnectionPointTypes.push(le.Vector2),n._inputs[1].excludedConnectionPointTypes.push(le.Float),n._inputs[1].excludedConnectionPointTypes.push(le.Matrix),n._inputs[1].excludedConnectionPointTypes.push(le.Vector2),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"CrossBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = cross("+this.left.associatedVariableName+".xyz, "+this.right.associatedVariableName+`.xyz);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.CrossBlock"]=Lh;var Nh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.Float),n._linkConnectionTypes(0,1),n._inputs[0].excludedConnectionPointTypes.push(le.Float),n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n._inputs[1].excludedConnectionPointTypes.push(le.Float),n._inputs[1].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DotBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = dot("+this.left.associatedVariableName+", "+this.right.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.DotBlock"]=Nh;var wh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("input",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._inputs[0].excludedConnectionPointTypes.push(le.Float),n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"NormalizeBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i=this._inputs[0];return e.compilationString+=this._declareOutput(n,e)+" = normalize("+i.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.NormalizeBlock"]=wh;var Fh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("rgb ",le.Color3,!0),n.registerInput("r",le.Float,!0),n.registerInput("g",le.Float,!0),n.registerInput("b",le.Float,!0),n.registerInput("a",le.Float,!0),n.registerOutput("rgba",le.Color4),n.registerOutput("rgb",le.Color3),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ColorMergerBlock"},Object.defineProperty(t.prototype,"rgbIn",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"r",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"g",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"b",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"a",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgba",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgbOut",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rgb",{get:function(){return this.rgbOut},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this.r,i=this.g,o=this.b,a=this.a,s=this.rgbIn,d=this._outputs[0],p=this._outputs[1];return s.isConnected?d.hasEndpoints?e.compilationString+=this._declareOutput(d,e)+" = vec4("+s.associatedVariableName+", "+(a.isConnected?this._writeVariable(a):"0.0")+`);\r
-`:p.hasEndpoints&&(e.compilationString+=this._declareOutput(p,e)+" = "+s.associatedVariableName+`;\r
-`):d.hasEndpoints?e.compilationString+=this._declareOutput(d,e)+" = vec4("+(n.isConnected?this._writeVariable(n):"0.0")+", "+(i.isConnected?this._writeVariable(i):"0.0")+", "+(o.isConnected?this._writeVariable(o):"0.0")+", "+(a.isConnected?this._writeVariable(a):"0.0")+`);\r
-`:p.hasEndpoints&&(e.compilationString+=this._declareOutput(p,e)+" = vec3("+(n.isConnected?this._writeVariable(n):"0.0")+", "+(i.isConnected?this._writeVariable(i):"0.0")+", "+(o.isConnected?this._writeVariable(o):"0.0")+`);\r
-`),this},t}(pt);R.a.RegisteredTypes["BABYLON.ColorMergerBlock"]=Fh;var Bh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("xyzw",le.Vector4,!0),n.registerInput("xyz ",le.Vector3,!0),n.registerInput("xy ",le.Vector2,!0),n.registerOutput("xyz",le.Vector3),n.registerOutput("xy",le.Vector2),n.registerOutput("x",le.Float),n.registerOutput("y",le.Float),n.registerOutput("z",le.Float),n.registerOutput("w",le.Float),n.inputsAreExclusive=!0,n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"VectorSplitterBlock"},Object.defineProperty(t.prototype,"xyzw",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyzIn",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyIn",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyzOut",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"xyOut",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"x",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"y",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"z",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"w",{get:function(){return this._outputs[5]},enumerable:!1,configurable:!0}),t.prototype._inputRename=function(e){switch(e){case"xy ":return"xyIn";case"xyz ":return"xyzIn";default:return e}},t.prototype._outputRename=function(e){switch(e){case"xy":return"xyOut";case"xyz":return"xyzOut";default:return e}},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this.xyzw.isConnected?this.xyzw:this.xyzIn.isConnected?this.xyzIn:this.xyIn,i=this._outputs[0],o=this._outputs[1],a=this._outputs[2],s=this._outputs[3],d=this._outputs[4],p=this._outputs[5];return i.hasEndpoints&&(n===this.xyIn?e.compilationString+=this._declareOutput(i,e)+" = vec3("+n.associatedVariableName+`, 0.0);\r
-`:e.compilationString+=this._declareOutput(i,e)+" = "+n.associatedVariableName+`.xyz;\r
-`),o.hasEndpoints&&(e.compilationString+=this._declareOutput(o,e)+" = "+n.associatedVariableName+`.xy;\r
-`),a.hasEndpoints&&(e.compilationString+=this._declareOutput(a,e)+" = "+n.associatedVariableName+`.x;\r
-`),s.hasEndpoints&&(e.compilationString+=this._declareOutput(s,e)+" = "+n.associatedVariableName+`.y;\r
-`),d.hasEndpoints&&(e.compilationString+=this._declareOutput(d,e)+" = "+n.associatedVariableName+`.z;\r
-`),p.hasEndpoints&&(e.compilationString+=this._declareOutput(p,e)+" = "+n.associatedVariableName+`.w;\r
-`),this},t}(pt);R.a.RegisteredTypes["BABYLON.VectorSplitterBlock"]=Bh;var Uh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerInput("gradient",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n._linkConnectionTypes(1,2,!0),n._inputs[2].acceptedConnectionPointTypes.push(le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"LerpBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"gradient",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = mix("+this.left.associatedVariableName+" , "+this.right.associatedVariableName+", "+this.gradient.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.LerpBlock"]=Uh;var Vh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DivideBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = "+this.left.associatedVariableName+" / "+this.right.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.DivideBlock"]=Vh;var kh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"SubtractBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = "+this.left.associatedVariableName+" - "+this.right.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.SubtractBlock"]=kh;var Gh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("value",le.Float),n.registerInput("edge",le.Float),n.registerOutput("output",le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"StepBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"edge",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = step("+this.edge.associatedVariableName+", "+this.value.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.StepBlock"]=Gh;var _c=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("input",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._outputs[0].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"OneMinusBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = 1. - "+this.input.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.OneMinusBlock"]=_c,R.a.RegisteredTypes["BABYLON.OppositeBlock"]=_c;var mc=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("worldPosition",le.Vector4),n.registerInput("cameraPosition",le.Vector3),n.registerOutput("output",le.Vector3),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ViewDirectionBlock"},Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraPosition",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.cameraPosition.isConnected){var n=e.getInputBlockByPredicate(function(i){return i.systemValue===bt.CameraPosition});n||(n=new At("cameraPosition")).setAsSystemValue(bt.CameraPosition),n.output.connectTo(this.cameraPosition)}},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = normalize("+this.cameraPosition.associatedVariableName+" - "+this.worldPosition.associatedVariableName+`.xyz);\r
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-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.FresnelBlock"]=zh;var jh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"MaxBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = max("+this.left.associatedVariableName+", "+this.right.associatedVariableName+`);\r
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-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.MinBlock"]=Hh;var Wh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.Float),n._linkConnectionTypes(0,1),n._inputs[0].excludedConnectionPointTypes.push(le.Float),n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n._inputs[1].excludedConnectionPointTypes.push(le.Float),n._inputs[1].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DistanceBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = length("+this.left.associatedVariableName+" - "+this.right.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.DistanceBlock"]=Wh;var Xh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("value",le.AutoDetect),n.registerOutput("output",le.Float),n._inputs[0].excludedConnectionPointTypes.push(le.Float),n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"LengthBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = length("+this.value.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.LengthBlock"]=Xh;var Yh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("value",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"NegateBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = -1.0 * "+this.value.associatedVariableName+`;\r
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-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.PowBlock"]=Kh;var Qh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("seed",le.Vector2),n.registerOutput("output",le.Float),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector3),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[0].acceptedConnectionPointTypes.push(le.Color3),n._inputs[0].acceptedConnectionPointTypes.push(le.Color4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"RandomNumberBlock"},Object.defineProperty(t.prototype,"seed",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i="//"+this.name;return e._emitFunctionFromInclude("helperFunctions",i),e.compilationString+=this._declareOutput(n,e)+" = getRand("+this.seed.associatedVariableName+`.xy);\r
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-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ArcTan2Block"]=qh;var Zh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("value",le.AutoDetect),n.registerInput("edge0",le.Float),n.registerInput("edge1",le.Float),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"SmoothStepBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"edge0",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"edge1",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = smoothstep("+this.edge0.associatedVariableName+", "+this.edge1.associatedVariableName+", "+this.value.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.SmoothStepBlock"]=Zh;var Jh=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("input",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._outputs[0].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ReciprocalBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = 1. / "+this.input.associatedVariableName+`;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ReciprocalBlock"]=Jh;var $h=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("value",le.AutoDetect),n.registerInput("reference",le.AutoDetect),n.registerInput("distance",le.Float),n.registerInput("replacement",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n._linkConnectionTypes(0,3),n._inputs[0].excludedConnectionPointTypes.push(le.Float),n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n._inputs[1].excludedConnectionPointTypes.push(le.Float),n._inputs[1].excludedConnectionPointTypes.push(le.Matrix),n._inputs[3].excludedConnectionPointTypes.push(le.Float),n._inputs[3].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ReplaceColorBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"reference",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"distance",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"replacement",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+`;\r
-`,e.compilationString+="if (length("+this.value.associatedVariableName+" - "+this.reference.associatedVariableName+") < "+this.distance.associatedVariableName+`) {\r
-`,e.compilationString+=n.associatedVariableName+" = "+this.replacement.associatedVariableName+`;\r
-`,e.compilationString+=`} else {\r
-`,e.compilationString+=n.associatedVariableName+" = "+this.value.associatedVariableName+`;\r
-`,e.compilationString+=`}\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ReplaceColorBlock"]=$h;var or,ed=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("value",le.AutoDetect),n.registerInput("steps",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n._inputs[1].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"PosterizeBlock"},Object.defineProperty(t.prototype,"value",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"steps",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = floor("+this.value.associatedVariableName+" / (1.0 / "+this.steps.associatedVariableName+")) * (1.0 / "+this.steps.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.PosterizeBlock"]=ed,function(r){r[r.SawTooth=0]="SawTooth",r[r.Square=1]="Square",r[r.Triangle=2]="Triangle"}(or||(or={}));var td=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.kind=or.SawTooth,n.registerInput("input",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._inputs[0].excludedConnectionPointTypes.push(le.Matrix),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"WaveBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];switch(this.kind){case or.SawTooth:e.compilationString+=this._declareOutput(n,e)+" = "+this.input.associatedVariableName+" - floor(0.5 + "+this.input.associatedVariableName+`);\r
-`;break;case or.Square:e.compilationString+=this._declareOutput(n,e)+" = 1.0 - 2.0 * round(fract("+this.input.associatedVariableName+`));\r
-`;break;case or.Triangle:e.compilationString+=this._declareOutput(n,e)+" = 2.0 * abs(2.0 * ("+this.input.associatedVariableName+" - floor(0.5 + "+this.input.associatedVariableName+`))) - 1.0;\r
-`}return this},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.kind=this.kind,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.kind=e.kind},t}(pt);R.a.RegisteredTypes["BABYLON.WaveBlock"]=td;var va=function(){function r(t,e){this.step=t,this.color=e}return Object.defineProperty(r.prototype,"step",{get:function(){return this._step},set:function(t){this._step=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"color",{get:function(){return this._color},set:function(t){this._color=t},enumerable:!1,configurable:!0}),r}(),nd=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.colorSteps=[new va(0,M.a.Black()),new va(1,M.a.White())],n.onValueChangedObservable=new C.c,n.registerInput("gradient",le.Float),n.registerOutput("output",le.Color3),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector2),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector3),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[0].acceptedConnectionPointTypes.push(le.Color3),n._inputs[0].acceptedConnectionPointTypes.push(le.Color4),n}return Object(c.d)(t,r),t.prototype.colorStepsUpdated=function(){this.onValueChangedObservable.notifyObservers(this)},t.prototype.getClassName=function(){return"GradientBlock"},Object.defineProperty(t.prototype,"gradient",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._writeColorConstant=function(e){var n=this.colorSteps[e];return"vec3("+n.color.r+", "+n.color.g+", "+n.color.b+")"},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];if(this.colorSteps.length&&this.gradient.connectedPoint){var i=e._getFreeVariableName("gradientTempColor"),o=e._getFreeVariableName("gradientTempPosition");e.compilationString+="vec3 "+i+" = "+this._writeColorConstant(0)+`;\r
-`,e.compilationString+="float "+o+`;\r
-`;var a=this.gradient.associatedVariableName;this.gradient.connectedPoint.type!==le.Float&&(a+=".x");for(var s=1;s<this.colorSteps.length;s++){var d=this.colorSteps[s],p=this.colorSteps[s-1];e.compilationString+=o+" = clamp(("+a+" - "+e._emitFloat(p.step)+") / ("+e._emitFloat(d.step)+" -  "+e._emitFloat(p.step)+"), 0.0, 1.0) * step("+e._emitFloat(s)+", "+e._emitFloat(this.colorSteps.length-1)+`);\r
-`,e.compilationString+=i+" = mix("+i+", "+this._writeColorConstant(s)+", "+o+`);\r
-`}return e.compilationString+=this._declareOutput(n,e)+" = "+i+`;\r
-`,this}e.compilationString+=this._declareOutput(n,e)+` = vec3(0., 0., 0.);\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);e.colorSteps=[];for(var n=0,i=this.colorSteps;n<i.length;n++){var o=i[n];e.colorSteps.push({step:o.step,color:{r:o.color.r,g:o.color.g,b:o.color.b}})}return e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.colorSteps=[];for(var o=0,a=e.colorSteps;o<a.length;o++){var s=a[o];this.colorSteps.push(new va(s.step,new M.a(s.color.r,s.color.g,s.color.b)))}},t.prototype._dumpPropertiesCode=function(){for(var e="",n=0,i=this.colorSteps;n<i.length;n++){var o=i[n];e+=this._codeVariableName+".colorSteps.push(new BABYLON.GradientBlockColorStep("+o.step+", new BABYLON.Color3("+o.color.r+", "+o.color.g+", "+o.color.b+`)));\r
-`}return e},t}(pt);R.a.RegisteredTypes["BABYLON.GradientBlock"]=nd;var id=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerInput("gradient",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n._linkConnectionTypes(1,2,!0),n._inputs[2].acceptedConnectionPointTypes.push(le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"NLerpBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"gradient",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = normalize(mix("+this.left.associatedVariableName+" , "+this.right.associatedVariableName+", "+this.gradient.associatedVariableName+`));\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.NLerpBlock"]=id;var rd=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.manhattanDistance=!1,n.registerInput("seed",le.Vector3),n.registerInput("jitter",le.Float),n.registerOutput("output",le.Vector2),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"WorleyNoise3DBlock"},Object.defineProperty(t.prototype,"seed",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"jitter",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),this.seed.isConnected&&this._outputs[0].hasEndpoints)return e._emitFunction("worley3D",`vec3 permute(vec3 x){\r
-    return mod((34.0 * x + 1.0) * x, 289.0);\r
-}\r
-\r
-vec3 dist(vec3 x, vec3 y, vec3 z,  bool manhattanDistance){\r
-    return manhattanDistance ?  abs(x) + abs(y) + abs(z) :  (x * x + y * y + z * z);\r
-}\r
-\r
-vec2 worley(vec3 P, float jitter, bool manhattanDistance){\r
-    float K = 0.142857142857; // 1/7\r
-    float Ko = 0.428571428571; // 1/2-K/2\r
-    float  K2 = 0.020408163265306; // 1/(7*7)\r
-    float Kz = 0.166666666667; // 1/6\r
-    float Kzo = 0.416666666667; // 1/2-1/6*2\r
-\r
-    vec3 Pi = mod(floor(P), 289.0);\r
-    vec3 Pf = fract(P) - 0.5;\r
-\r
-    vec3 Pfx = Pf.x + vec3(1.0, 0.0, -1.0);\r
-    vec3 Pfy = Pf.y + vec3(1.0, 0.0, -1.0);\r
-    vec3 Pfz = Pf.z + vec3(1.0, 0.0, -1.0);\r
-\r
-    vec3 p = permute(Pi.x + vec3(-1.0, 0.0, 1.0));\r
-    vec3 p1 = permute(p + Pi.y - 1.0);\r
-    vec3 p2 = permute(p + Pi.y);\r
-    vec3 p3 = permute(p + Pi.y + 1.0);\r
-\r
-    vec3 p11 = permute(p1 + Pi.z - 1.0);\r
-    vec3 p12 = permute(p1 + Pi.z);\r
-    vec3 p13 = permute(p1 + Pi.z + 1.0);\r
-\r
-    vec3 p21 = permute(p2 + Pi.z - 1.0);\r
-    vec3 p22 = permute(p2 + Pi.z);\r
-    vec3 p23 = permute(p2 + Pi.z + 1.0);\r
-\r
-    vec3 p31 = permute(p3 + Pi.z - 1.0);\r
-    vec3 p32 = permute(p3 + Pi.z);\r
-    vec3 p33 = permute(p3 + Pi.z + 1.0);\r
-\r
-    vec3 ox11 = fract(p11*K) - Ko;\r
-    vec3 oy11 = mod(floor(p11*K), 7.0)*K - Ko;\r
-    vec3 oz11 = floor(p11*K2)*Kz - Kzo; // p11 < 289 guaranteed\r
-\r
-    vec3 ox12 = fract(p12*K) - Ko;\r
-    vec3 oy12 = mod(floor(p12*K), 7.0)*K - Ko;\r
-    vec3 oz12 = floor(p12*K2)*Kz - Kzo;\r
-\r
-    vec3 ox13 = fract(p13*K) - Ko;\r
-    vec3 oy13 = mod(floor(p13*K), 7.0)*K - Ko;\r
-    vec3 oz13 = floor(p13*K2)*Kz - Kzo;\r
-\r
-    vec3 ox21 = fract(p21*K) - Ko;\r
-    vec3 oy21 = mod(floor(p21*K), 7.0)*K - Ko;\r
-    vec3 oz21 = floor(p21*K2)*Kz - Kzo;\r
-\r
-    vec3 ox22 = fract(p22*K) - Ko;\r
-    vec3 oy22 = mod(floor(p22*K), 7.0)*K - Ko;\r
-    vec3 oz22 = floor(p22*K2)*Kz - Kzo;\r
-\r
-    vec3 ox23 = fract(p23*K) - Ko;\r
-    vec3 oy23 = mod(floor(p23*K), 7.0)*K - Ko;\r
-    vec3 oz23 = floor(p23*K2)*Kz - Kzo;\r
-\r
-    vec3 ox31 = fract(p31*K) - Ko;\r
-    vec3 oy31 = mod(floor(p31*K), 7.0)*K - Ko;\r
-    vec3 oz31 = floor(p31*K2)*Kz - Kzo;\r
-\r
-    vec3 ox32 = fract(p32*K) - Ko;\r
-    vec3 oy32 = mod(floor(p32*K), 7.0)*K - Ko;\r
-    vec3 oz32 = floor(p32*K2)*Kz - Kzo;\r
-\r
-    vec3 ox33 = fract(p33*K) - Ko;\r
-    vec3 oy33 = mod(floor(p33*K), 7.0)*K - Ko;\r
-    vec3 oz33 = floor(p33*K2)*Kz - Kzo;\r
-\r
-    vec3 dx11 = Pfx + jitter*ox11;\r
-    vec3 dy11 = Pfy.x + jitter*oy11;\r
-    vec3 dz11 = Pfz.x + jitter*oz11;\r
-\r
-    vec3 dx12 = Pfx + jitter*ox12;\r
-    vec3 dy12 = Pfy.x + jitter*oy12;\r
-    vec3 dz12 = Pfz.y + jitter*oz12;\r
-\r
-    vec3 dx13 = Pfx + jitter*ox13;\r
-    vec3 dy13 = Pfy.x + jitter*oy13;\r
-    vec3 dz13 = Pfz.z + jitter*oz13;\r
-\r
-    vec3 dx21 = Pfx + jitter*ox21;\r
-    vec3 dy21 = Pfy.y + jitter*oy21;\r
-    vec3 dz21 = Pfz.x + jitter*oz21;\r
-\r
-    vec3 dx22 = Pfx + jitter*ox22;\r
-    vec3 dy22 = Pfy.y + jitter*oy22;\r
-    vec3 dz22 = Pfz.y + jitter*oz22;\r
-\r
-    vec3 dx23 = Pfx + jitter*ox23;\r
-    vec3 dy23 = Pfy.y + jitter*oy23;\r
-    vec3 dz23 = Pfz.z + jitter*oz23;\r
-\r
-    vec3 dx31 = Pfx + jitter*ox31;\r
-    vec3 dy31 = Pfy.z + jitter*oy31;\r
-    vec3 dz31 = Pfz.x + jitter*oz31;\r
-\r
-    vec3 dx32 = Pfx + jitter*ox32;\r
-    vec3 dy32 = Pfy.z + jitter*oy32;\r
-    vec3 dz32 = Pfz.y + jitter*oz32;\r
-\r
-    vec3 dx33 = Pfx + jitter*ox33;\r
-    vec3 dy33 = Pfy.z + jitter*oy33;\r
-    vec3 dz33 = Pfz.z + jitter*oz33;\r
-\r
-    vec3 d11 = dist(dx11, dy11, dz11, manhattanDistance);\r
-    vec3 d12 =dist(dx12, dy12, dz12, manhattanDistance);\r
-    vec3 d13 = dist(dx13, dy13, dz13, manhattanDistance);\r
-    vec3 d21 = dist(dx21, dy21, dz21, manhattanDistance);\r
-    vec3 d22 = dist(dx22, dy22, dz22, manhattanDistance);\r
-    vec3 d23 = dist(dx23, dy23, dz23, manhattanDistance);\r
-    vec3 d31 = dist(dx31, dy31, dz31, manhattanDistance);\r
-    vec3 d32 = dist(dx32, dy32, dz32, manhattanDistance);\r
-    vec3 d33 = dist(dx33, dy33, dz33, manhattanDistance);\r
-\r
-    vec3 d1a = min(d11, d12);\r
-    d12 = max(d11, d12);\r
-    d11 = min(d1a, d13); // Smallest now not in d12 or d13\r
-    d13 = max(d1a, d13);\r
-    d12 = min(d12, d13); // 2nd smallest now not in d13\r
-    vec3 d2a = min(d21, d22);\r
-    d22 = max(d21, d22);\r
-    d21 = min(d2a, d23); // Smallest now not in d22 or d23\r
-    d23 = max(d2a, d23);\r
-    d22 = min(d22, d23); // 2nd smallest now not in d23\r
-    vec3 d3a = min(d31, d32);\r
-    d32 = max(d31, d32);\r
-    d31 = min(d3a, d33); // Smallest now not in d32 or d33\r
-    d33 = max(d3a, d33);\r
-    d32 = min(d32, d33); // 2nd smallest now not in d33\r
-    vec3 da = min(d11, d21);\r
-    d21 = max(d11, d21);\r
-    d11 = min(da, d31); // Smallest now in d11\r
-    d31 = max(da, d31); // 2nd smallest now not in d31\r
-    d11.xy = (d11.x < d11.y) ? d11.xy : d11.yx;\r
-    d11.xz = (d11.x < d11.z) ? d11.xz : d11.zx; // d11.x now smallest\r
-    d12 = min(d12, d21); // 2nd smallest now not in d21\r
-    d12 = min(d12, d22); // nor in d22\r
-    d12 = min(d12, d31); // nor in d31\r
-    d12 = min(d12, d32); // nor in d32\r
-    d11.yz = min(d11.yz,d12.xy); // nor in d12.yz\r
-    d11.y = min(d11.y,d12.z); // Only two more to go\r
-    d11.y = min(d11.y,d11.z); // Done! (Phew!)\r
-    return sqrt(d11.xy); // F1, F2\r
-}\r
-\r
-`,"// Worley3D"),e.compilationString+=this._declareOutput(this._outputs[0],e)+" = worley("+this.seed.associatedVariableName+", "+this.jitter.associatedVariableName+", "+this.manhattanDistance+`);\r
-`,this},t.prototype._dumpPropertiesCode=function(){return this._codeVariableName+".manhattanDistance = "+this.manhattanDistance+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.manhattanDistance=this.manhattanDistance,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.manhattanDistance=e.manhattanDistance},Object(c.c)([Vt("Use Manhattan Distance",Lt.Boolean,"PROPERTIES",{notifiers:{update:!1}})],t.prototype,"manhattanDistance",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.WorleyNoise3DBlock"]=rd;var od=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("seed",le.Vector3),n.registerOutput("output",le.Float),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"SimplexPerlin3DBlock"},Object.defineProperty(t.prototype,"seed",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){if(r.prototype._buildBlock.call(this,e),this.seed.isConnected&&this._outputs[0].hasEndpoints)return e._emitFunction("SimplexPerlin3D",`const float SKEWFACTOR = 1.0/3.0;\r
-const float UNSKEWFACTOR = 1.0/6.0;\r
-const float SIMPLEX_CORNER_POS = 0.5;\r
-const float SIMPLEX_TETRAHADRON_HEIGHT = 0.70710678118654752440084436210485;\r
-float SimplexPerlin3D( vec3 P ){\r
-    P *= SIMPLEX_TETRAHADRON_HEIGHT;\r
-    vec3 Pi = floor( P + dot( P, vec3( SKEWFACTOR) ) );    vec3 x0 = P - Pi + dot(Pi, vec3( UNSKEWFACTOR ) );\r
-    vec3 g = step(x0.yzx, x0.xyz);\r
-    vec3 l = 1.0 - g;\r
-    vec3 Pi_1 = min( g.xyz, l.zxy );\r
-    vec3 Pi_2 = max( g.xyz, l.zxy );\r
-    vec3 x1 = x0 - Pi_1 + UNSKEWFACTOR;\r
-    vec3 x2 = x0 - Pi_2 + SKEWFACTOR;\r
-    vec3 x3 = x0 - SIMPLEX_CORNER_POS;\r
-    vec4 v1234_x = vec4( x0.x, x1.x, x2.x, x3.x );\r
-    vec4 v1234_y = vec4( x0.y, x1.y, x2.y, x3.y );\r
-    vec4 v1234_z = vec4( x0.z, x1.z, x2.z, x3.z );\r
-    Pi.xyz = Pi.xyz - floor(Pi.xyz * ( 1.0 / 69.0 )) * 69.0;\r
-    vec3 Pi_inc1 = step( Pi, vec3( 69.0 - 1.5 ) ) * ( Pi + 1.0 );\r
-    vec4 Pt = vec4( Pi.xy, Pi_inc1.xy ) + vec2( 50.0, 161.0 ).xyxy;\r
-    Pt *= Pt;\r
-    vec4 V1xy_V2xy = mix( Pt.xyxy, Pt.zwzw, vec4( Pi_1.xy, Pi_2.xy ) );\r
-    Pt = vec4( Pt.x, V1xy_V2xy.xz, Pt.z ) * vec4( Pt.y, V1xy_V2xy.yw, Pt.w );\r
-    const vec3 SOMELARGEFLOATS = vec3( 635.298681, 682.357502, 668.926525 );\r
-    const vec3 ZINC = vec3( 48.500388, 65.294118, 63.934599 );\r
-    vec3 lowz_mods = vec3( 1.0 / ( SOMELARGEFLOATS.xyz + Pi.zzz * ZINC.xyz ) );\r
-    vec3 highz_mods = vec3( 1.0 / ( SOMELARGEFLOATS.xyz + Pi_inc1.zzz * ZINC.xyz ) );\r
-    Pi_1 = ( Pi_1.z < 0.5 ) ? lowz_mods : highz_mods;\r
-    Pi_2 = ( Pi_2.z < 0.5 ) ? lowz_mods : highz_mods;\r
-    vec4 hash_0 = fract( Pt * vec4( lowz_mods.x, Pi_1.x, Pi_2.x, highz_mods.x ) ) - 0.49999;\r
-    vec4 hash_1 = fract( Pt * vec4( lowz_mods.y, Pi_1.y, Pi_2.y, highz_mods.y ) ) - 0.49999;\r
-    vec4 hash_2 = fract( Pt * vec4( lowz_mods.z, Pi_1.z, Pi_2.z, highz_mods.z ) ) - 0.49999;\r
-    vec4 grad_results = inversesqrt( hash_0 * hash_0 + hash_1 * hash_1 + hash_2 * hash_2 ) * ( hash_0 * v1234_x + hash_1 * v1234_y + hash_2 * v1234_z );\r
-    const float FINAL_NORMALIZATION = 37.837227241611314102871574478976;\r
-    vec4 kernel_weights = v1234_x * v1234_x + v1234_y * v1234_y + v1234_z * v1234_z;\r
-    kernel_weights = max(0.5 - kernel_weights, 0.0);\r
-    kernel_weights = kernel_weights*kernel_weights*kernel_weights;\r
-    return dot( kernel_weights, grad_results ) * FINAL_NORMALIZATION;\r
-}\r
-`,"// SimplexPerlin3D"),e.compilationString+=this._declareOutput(this._outputs[0],e)+" = SimplexPerlin3D("+this.seed.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.SimplexPerlin3DBlock"]=od;var ad=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("normalMap0",le.Vector3),n.registerInput("normalMap1",le.Vector3),n.registerOutput("output",le.Vector3),n._inputs[0].acceptedConnectionPointTypes.push(le.Color3),n._inputs[0].acceptedConnectionPointTypes.push(le.Color4),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[1].acceptedConnectionPointTypes.push(le.Color3),n._inputs[1].acceptedConnectionPointTypes.push(le.Color4),n._inputs[1].acceptedConnectionPointTypes.push(le.Vector4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"NormalBlendBlock"},Object.defineProperty(t.prototype,"normalMap0",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normalMap1",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i=this._inputs[0],o=this._inputs[1],a=e._getFreeVariableName("stepR"),s=e._getFreeVariableName("stepG");return e.compilationString+="float "+a+" = step(0.5, "+i.associatedVariableName+`.r);\r
-`,e.compilationString+="float "+s+" = step(0.5, "+i.associatedVariableName+`.g);\r
-`,e.compilationString+=this._declareOutput(n,e)+`;\r
-`,e.compilationString+=n.associatedVariableName+".r = (1.0 - "+a+") * "+i.associatedVariableName+".r * "+o.associatedVariableName+".r * 2.0 + "+a+" * (1.0 - "+i.associatedVariableName+".r) * (1.0 - "+o.associatedVariableName+`.r) * 2.0;\r
-`,e.compilationString+=n.associatedVariableName+".g = (1.0 - "+s+") * "+i.associatedVariableName+".g * "+o.associatedVariableName+".g * 2.0 + "+s+" * (1.0 - "+i.associatedVariableName+".g) * (1.0 - "+o.associatedVariableName+`.g) * 2.0;\r
-`,e.compilationString+=n.associatedVariableName+".b = "+i.associatedVariableName+".b * "+o.associatedVariableName+`.b;\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.NormalBlendBlock"]=ad;var sd=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("input",le.Vector2),n.registerInput("angle",le.Float),n.registerOutput("output",le.Vector2),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"Rotate2dBlock"},Object.defineProperty(t.prototype,"input",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"angle",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.angle.isConnected){var n=new At("angle");n.value=0,n.output.connectTo(this.angle)}},t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i=this.angle,o=this.input;return e.compilationString+=this._declareOutput(n,e)+" = vec2(cos("+i.associatedVariableName+") * "+o.associatedVariableName+".x - sin("+i.associatedVariableName+") * "+o.associatedVariableName+".y, sin("+i.associatedVariableName+") * "+o.associatedVariableName+".x + cos("+i.associatedVariableName+") * "+o.associatedVariableName+`.y);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.Rotate2dBlock"]=sd;var cd=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("incident",le.Vector3),n.registerInput("normal",le.Vector3),n.registerOutput("output",le.Vector3),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[0].acceptedConnectionPointTypes.push(le.Color3),n._inputs[0].acceptedConnectionPointTypes.push(le.Color4),n._inputs[1].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[1].acceptedConnectionPointTypes.push(le.Color3),n._inputs[1].acceptedConnectionPointTypes.push(le.Color4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ReflectBlock"},Object.defineProperty(t.prototype,"incident",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normal",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = reflect("+this.incident.associatedVariableName+".xyz, "+this.normal.associatedVariableName+`.xyz);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ReflectBlock"]=cd;var ld=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("incident",le.Vector3),n.registerInput("normal",le.Vector3),n.registerInput("ior",le.Float),n.registerOutput("output",le.Vector3),n._inputs[0].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[0].acceptedConnectionPointTypes.push(le.Color3),n._inputs[0].acceptedConnectionPointTypes.push(le.Color4),n._inputs[1].acceptedConnectionPointTypes.push(le.Vector4),n._inputs[1].acceptedConnectionPointTypes.push(le.Color3),n._inputs[1].acceptedConnectionPointTypes.push(le.Color4),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"RefractBlock"},Object.defineProperty(t.prototype,"incident",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normal",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"ior",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = refract("+this.incident.associatedVariableName+".xyz, "+this.normal.associatedVariableName+".xyz, "+this.ior.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.RefractBlock"]=ld;var ud=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("color",le.Color3),n.registerInput("level",le.Float),n.registerOutput("output",le.Color3),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DesaturateBlock"},Object.defineProperty(t.prototype,"color",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"level",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0],i=this.color.associatedVariableName,o=e._getFreeVariableName("colorMin"),a=e._getFreeVariableName("colorMax"),s=e._getFreeVariableName("colorMerge");return e.compilationString+="float "+o+" = min(min("+i+".x, "+i+".y), "+i+`.z);\r
-`,e.compilationString+="float "+a+" = max(max("+i+".x, "+i+".y), "+i+`.z);\r
-`,e.compilationString+="float "+s+" = 0.5 * ("+o+" + "+a+`);\r
-`,e.compilationString+=this._declareOutput(n,e)+" = mix("+i+", vec3("+s+", "+s+", "+s+"), "+this.level.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.DesaturateBlock"]=ud;var Zn=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,n,i)||this;return d._blockType=o,d._blockName=a,d._nameForCheking=s,d._nameForCheking||(d._nameForCheking=e),d.needDualDirectionValidation=!0,d}return Object(c.d)(t,r),t.prototype.checkCompatibilityState=function(e){return e instanceof t&&e.name===this._nameForCheking?ci.Compatible:ci.TypeIncompatible},t.prototype.createCustomInputBlock=function(){return[new this._blockType(this._blockName),this.name]},t}(da),gc=function(r){function t(e){var n=r.call(this,e,Ce.Fragment)||this;return n.albedoScaling=!1,n.linkSheenWithAlbedo=!1,n._isUnique=!0,n.registerInput("intensity",le.Float,!0,Ce.Fragment),n.registerInput("color",le.Color3,!0,Ce.Fragment),n.registerInput("roughness",le.Float,!0,Ce.Fragment),n.registerOutput("sheen",le.Object,Ce.Fragment,new Zn("sheen",n,Tn.Output,t,"SheenBlock")),n}return Object(c.d)(t,r),t.prototype.initialize=function(e){e._excludeVariableName("sheenOut"),e._excludeVariableName("sheenMapData"),e._excludeVariableName("vSheenColor"),e._excludeVariableName("vSheenRoughness")},t.prototype.getClassName=function(){return"SheenBlock"},Object.defineProperty(t.prototype,"intensity",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"color",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"roughness",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sheen",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.prepareDefines=function(e,n,i){r.prototype.prepareDefines.call(this,e,n,i),i.setValue("SHEEN",!0),i.setValue("SHEEN_USE_ROUGHNESS_FROM_MAINTEXTURE",!0,!0),i.setValue("SHEEN_LINKWITHALBEDO",this.linkSheenWithAlbedo,!0),i.setValue("SHEEN_ROUGHNESS",this.roughness.isConnected,!0),i.setValue("SHEEN_ALBEDOSCALING",this.albedoScaling,!0)},t.prototype.getCode=function(e){return`#ifdef SHEEN
-            sheenOutParams sheenOut;
-
-            vec4 vSheenColor = vec4(`+(this.color.isConnected?this.color.associatedVariableName:"vec3(1.)")+", "+(this.intensity.isConnected?this.intensity.associatedVariableName:"1.")+`);
-
-            sheenBlock(
-                vSheenColor,
-            #ifdef SHEEN_ROUGHNESS
-                `+(this.roughness.isConnected?this.roughness.associatedVariableName:"0.")+`,
-            #endif
-                roughness,
-            #ifdef SHEEN_TEXTURE
-                vec4(0.),
-            #endif
-                reflectance,
-            #ifdef SHEEN_LINKWITHALBEDO
-                baseColor,
-                surfaceAlbedo,
-            #endif
-            #ifdef ENVIRONMENTBRDF
-                NdotV,
-                environmentBrdf,
-            #endif
-            #if defined(REFLECTION) && defined(ENVIRONMENTBRDF)
-                AARoughnessFactors,
-                `+e?._vReflectionMicrosurfaceInfosName+`,
-                `+e?._vReflectionInfosName+`,
-                `+e?.reflectionColor+`,
-                vLightingIntensity,
-                #ifdef `+e?._define3DName+`
-                    `+e?._cubeSamplerName+`,
-                #else
-                    `+e?._2DSamplerName+`,
-                #endif
-                reflectionOut.reflectionCoords,
-                NdotVUnclamped,
-                #ifndef LODBASEDMICROSFURACE
-                    #ifdef `+e?._define3DName+`
-                        `+e?._cubeSamplerName+`,
-                        `+e?._cubeSamplerName+`,
-                    #else
-                        `+e?._2DSamplerName+`,
-                        `+e?._2DSamplerName+`,
-                    #endif
-                #endif
-                #if !defined(`+e?._defineSkyboxName+`) && defined(RADIANCEOCCLUSION)
-                    seo,
-                #endif
-                #if !defined(`+e?._defineSkyboxName+") && defined(HORIZONOCCLUSION) && defined(BUMP) && defined("+e?._define3DName+`)
-                    eho,
-                #endif
-            #endif
-                sheenOut
-            );
-
-            #ifdef SHEEN_LINKWITHALBEDO
-                surfaceAlbedo = sheenOut.surfaceAlbedo;
-            #endif
-        #endif\r
-`},t.prototype._buildBlock=function(e){return e.target===Ce.Fragment&&e.sharedData.blocksWithDefines.push(this),this},t.prototype._dumpPropertiesCode=function(){var e=r.prototype._dumpPropertiesCode.call(this);return e+=this._codeVariableName+".albedoScaling = "+this.albedoScaling+`;\r
-`,e+=this._codeVariableName+".linkSheenWithAlbedo = "+this.linkSheenWithAlbedo+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.albedoScaling=this.albedoScaling,e.linkSheenWithAlbedo=this.linkSheenWithAlbedo,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.albedoScaling=e.albedoScaling,this.linkSheenWithAlbedo=e.linkSheenWithAlbedo},Object(c.c)([Vt("Albedo scaling",Lt.Boolean,"PROPERTIES",{notifiers:{update:!0}})],t.prototype,"albedoScaling",void 0),Object(c.c)([Vt("Link sheen with albedo",Lt.Boolean,"PROPERTIES",{notifiers:{update:!0}})],t.prototype,"linkSheenWithAlbedo",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.SheenBlock"]=gc;var vc=function(r){function t(e){var n=r.call(this,e,Ce.Fragment)||this;return n._isUnique=!0,n.registerInput("intensity",le.Float,!0,Ce.Fragment),n.registerInput("direction",le.Vector2,!0,Ce.Fragment),n.registerInput("uv",le.Vector2,!0),n.registerInput("worldTangent",le.Vector4,!0),n.registerOutput("anisotropy",le.Object,Ce.Fragment,new Zn("anisotropy",n,Tn.Output,t,"AnisotropyBlock")),n}return Object(c.d)(t,r),t.prototype.initialize=function(e){e._excludeVariableName("anisotropicOut"),e._excludeVariableName("TBN")},t.prototype.getClassName=function(){return"AnisotropyBlock"},Object.defineProperty(t.prototype,"intensity",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"direction",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"uv",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldTangent",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"anisotropy",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._generateTBNSpace=function(e){var n="",i="//"+this.name,o=this.uv,a=this.worldPositionConnectionPoint,s=this.worldNormalConnectionPoint,d=this.worldTangent;o.isConnected||console.error("You must connect the 'uv' input of the Anisotropy block!"),e._emitExtension("derivatives","#extension GL_OES_standard_derivatives : enable");var p={search:/defined\(TANGENT\)/g,replace:d.isConnected?"defined(TANGENT)":"defined(IGNORE)"};return d.isConnected&&(n+="vec3 tbnNormal = normalize("+s.associatedVariableName+`.xyz);\r
-`,n+="vec3 tbnTangent = normalize("+d.associatedVariableName+`.xyz);\r
-`,n+=`vec3 tbnBitangent = cross(tbnNormal, tbnTangent);\r
-`,n+=`mat3 vTBN = mat3(tbnTangent, tbnBitangent, tbnNormal);\r
-`),n+=`
-            #if defined(`+(d.isConnected?"TANGENT":"IGNORE")+`) && defined(NORMAL)
-                mat3 TBN = vTBN;
-            #else
-                mat3 TBN = cotangent_frame(`+s.associatedVariableName+".xyz, v_"+a.associatedVariableName+".xyz, "+(o.isConnected?o.associatedVariableName:"vec2(0.)")+`, vec2(1., 1.));
-            #endif\r
-`,e._emitFunctionFromInclude("bumpFragmentMainFunctions",i,{replaceStrings:[p]}),n},t.prototype.getCode=function(e,n){n===void 0&&(n=!1);var i="";n&&(i+=this._generateTBNSpace(e));var o=this.intensity.isConnected?this.intensity.associatedVariableName:"1.0";return i+=`anisotropicOutParams anisotropicOut;
-            anisotropicBlock(
-                vec3(`+(this.direction.isConnected?this.direction.associatedVariableName:"vec2(1., 0.)")+", "+o+`),
-            #ifdef ANISOTROPIC_TEXTURE
-                vec3(0.),
-            #endif
-                TBN,
-                normalW,
-                viewDirectionW,
-                anisotropicOut
-            );\r
-`},t.prototype.prepareDefines=function(e,n,i){r.prototype.prepareDefines.call(this,e,n,i),i.setValue("ANISOTROPIC",!0),i.setValue("ANISOTROPIC_TEXTURE",!1,!0)},t.prototype._buildBlock=function(e){return e.target===Ce.Fragment&&e.sharedData.blocksWithDefines.push(this),this},t}(pt);R.a.RegisteredTypes["BABYLON.AnisotropyBlock"]=vc;var bc=function(r){function t(e){var n=r.call(this,e)||this;return n.useSphericalHarmonics=!0,n.forceIrradianceInFragment=!1,n._isUnique=!0,n.registerInput("position",le.Vector3,!1,Ce.Vertex),n.registerInput("world",le.Matrix,!1,Ce.Vertex),n.registerInput("color",le.Color3,!0,Ce.Fragment),n.registerOutput("reflection",le.Object,Ce.Fragment,new Zn("reflection",n,Tn.Output,t,"ReflectionBlock")),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ReflectionBlock"},Object.defineProperty(t.prototype,"position",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this.worldPositionConnectionPoint},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldNormal",{get:function(){return this.worldNormalConnectionPoint},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"world",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraPosition",{get:function(){return this.cameraPositionConnectionPoint},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"view",{get:function(){return this.viewConnectionPoint},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"color",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"reflection",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"hasTexture",{get:function(){return!!this._getTexture()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"reflectionColor",{get:function(){return this.color.isConnected?this.color.associatedVariableName:"vec3(1., 1., 1.)"},enumerable:!1,configurable:!0}),t.prototype._getTexture=function(){return this.texture?this.texture:this._scene.environmentTexture},t.prototype.prepareDefines=function(e,n,i){r.prototype.prepareDefines.call(this,e,n,i);var o=this._getTexture(),a=o&&o.getTextureMatrix;i.setValue("REFLECTION",a,!0),a&&(i.setValue(this._defineLODReflectionAlpha,o.lodLevelInAlpha,!0),i.setValue(this._defineLinearSpecularReflection,o.linearSpecularLOD,!0),i.setValue(this._defineOppositeZ,this._scene.useRightHandedSystem?!o.invertZ:o.invertZ,!0),i.setValue("SPHERICAL_HARMONICS",this.useSphericalHarmonics,!0),i.setValue("GAMMAREFLECTION",o.gammaSpace,!0),i.setValue("RGBDREFLECTION",o.isRGBD,!0),o&&o.coordinatesMode!==we.a.SKYBOX_MODE&&o.isCube&&(i.setValue("USESPHERICALFROMREFLECTIONMAP",!0),i.setValue("USEIRRADIANCEMAP",!1),this.forceIrradianceInFragment||this._scene.getEngine().getCaps().maxVaryingVectors<=8?i.setValue("USESPHERICALINVERTEX",!1):i.setValue("USESPHERICALINVERTEX",!0)))},t.prototype.bind=function(e,n,i,o){r.prototype.bind.call(this,e,n,i);var a=this._getTexture();if(a&&o){a.isCube?e.setTexture(this._cubeSamplerName,a):e.setTexture(this._2DSamplerName,a);var s=a.getSize().width;e.setFloat3(this._vReflectionMicrosurfaceInfosName,s,a.lodGenerationScale,a.lodGenerationOffset),e.setFloat2(this._vReflectionFilteringInfoName,s,$.a.Log2(s));var d=o._materialDefines,p=a.sphericalPolynomial;if(d.USESPHERICALFROMREFLECTIONMAP&&p)if(d.SPHERICAL_HARMONICS){var b=p.preScaledHarmonics;e.setVector3("vSphericalL00",b.l00),e.setVector3("vSphericalL1_1",b.l1_1),e.setVector3("vSphericalL10",b.l10),e.setVector3("vSphericalL11",b.l11),e.setVector3("vSphericalL2_2",b.l2_2),e.setVector3("vSphericalL2_1",b.l2_1),e.setVector3("vSphericalL20",b.l20),e.setVector3("vSphericalL21",b.l21),e.setVector3("vSphericalL22",b.l22)}else e.setFloat3("vSphericalX",p.x.x,p.x.y,p.x.z),e.setFloat3("vSphericalY",p.y.x,p.y.y,p.y.z),e.setFloat3("vSphericalZ",p.z.x,p.z.y,p.z.z),e.setFloat3("vSphericalXX_ZZ",p.xx.x-p.zz.x,p.xx.y-p.zz.y,p.xx.z-p.zz.z),e.setFloat3("vSphericalYY_ZZ",p.yy.x-p.zz.x,p.yy.y-p.zz.y,p.yy.z-p.zz.z),e.setFloat3("vSphericalZZ",p.zz.x,p.zz.y,p.zz.z),e.setFloat3("vSphericalXY",p.xy.x,p.xy.y,p.xy.z),e.setFloat3("vSphericalYZ",p.yz.x,p.yz.y,p.yz.z),e.setFloat3("vSphericalZX",p.zx.x,p.zx.y,p.zx.z)}},t.prototype.handleVertexSide=function(e){var n=r.prototype.handleVertexSide.call(this,e);e._emitFunctionFromInclude("harmonicsFunctions","//"+this.name,{replaceStrings:[{search:/uniform vec3 vSphericalL00;[\s\S]*?uniform vec3 vSphericalL22;/g,replace:""},{search:/uniform vec3 vSphericalX;[\s\S]*?uniform vec3 vSphericalZX;/g,replace:""}]});var i=e._getFreeVariableName("reflectionVector");return this._vEnvironmentIrradianceName=e._getFreeVariableName("vEnvironmentIrradiance"),e._emitVaryingFromString(this._vEnvironmentIrradianceName,"vec3","defined(USESPHERICALFROMREFLECTIONMAP) && defined(USESPHERICALINVERTEX)"),e._emitUniformFromString("vSphericalL00","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL1_1","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL10","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL11","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL2_2","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL2_1","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL20","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL21","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalL22","vec3","SPHERICAL_HARMONICS"),e._emitUniformFromString("vSphericalX","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalY","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalZ","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalXX_ZZ","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalYY_ZZ","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalZZ","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalXY","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalYZ","vec3","SPHERICAL_HARMONICS",!0),e._emitUniformFromString("vSphericalZX","vec3","SPHERICAL_HARMONICS",!0),n+=`#if defined(USESPHERICALFROMREFLECTIONMAP) && defined(USESPHERICALINVERTEX)
-                vec3 `+i+" = vec3("+this._reflectionMatrixName+" * vec4(normalize("+this.worldNormal.associatedVariableName+`).xyz, 0)).xyz;
-                #ifdef `+this._defineOppositeZ+`
-                    `+i+`.z *= -1.0;
-                #endif
-                `+this._vEnvironmentIrradianceName+" = computeEnvironmentIrradiance("+i+`);
-            #endif\r
-`},t.prototype.getCode=function(e,n){var i="";this.handleFragmentSideInits(e),e._emitFunctionFromInclude("harmonicsFunctions","//"+this.name,{replaceStrings:[{search:/uniform vec3 vSphericalL00;[\s\S]*?uniform vec3 vSphericalL22;/g,replace:""},{search:/uniform vec3 vSphericalX;[\s\S]*?uniform vec3 vSphericalZX;/g,replace:""}]}),e._emitFunction("sampleReflection",`
-            #ifdef `+this._define3DName+`
-                #define sampleReflection(s, c) textureCube(s, c)
-            #else
-                #define sampleReflection(s, c) texture2D(s, c)
-            #endif\r
-`,"//"+this.name),e._emitFunction("sampleReflectionLod",`
-            #ifdef `+this._define3DName+`
-                #define sampleReflectionLod(s, c, l) textureCubeLodEXT(s, c, l)
-            #else
-                #define sampleReflectionLod(s, c, l) texture2DLodEXT(s, c, l)
-            #endif\r
-`,"//"+this.name);var o=`
-            vec3 computeReflectionCoordsPBR(vec4 worldPos, vec3 worldNormal) {
-                `+this.handleFragmentSideCodeReflectionCoords("worldNormal","worldPos",!0)+`
-                return `+this._reflectionVectorName+`;
-            }\r
-`;return e._emitFunction("computeReflectionCoordsPBR",o,"//"+this.name),this._vReflectionMicrosurfaceInfosName=e._getFreeVariableName("vReflectionMicrosurfaceInfos"),e._emitUniformFromString(this._vReflectionMicrosurfaceInfosName,"vec3"),this._vReflectionInfosName=e._getFreeVariableName("vReflectionInfos"),this._vReflectionFilteringInfoName=e._getFreeVariableName("vReflectionFilteringInfo"),e._emitUniformFromString(this._vReflectionFilteringInfoName,"vec2"),i+=`#ifdef REFLECTION
-            vec2 `+this._vReflectionInfosName+` = vec2(1., 0.);
-
-            reflectionOutParams reflectionOut;
-
-            reflectionBlock(
-                v_`+this.worldPosition.associatedVariableName+`.xyz,
-                `+n+`,
-                alphaG,
-                `+this._vReflectionMicrosurfaceInfosName+`,
-                `+this._vReflectionInfosName+`,
-                `+this.reflectionColor+`,
-            #ifdef ANISOTROPIC
-                anisotropicOut,
-            #endif
-            #if defined(`+this._defineLODReflectionAlpha+") && !defined("+this._defineSkyboxName+`)
-                NdotVUnclamped,
-            #endif
-            #ifdef `+this._defineLinearSpecularReflection+`
-                roughness,
-            #endif
-            #ifdef `+this._define3DName+`
-                `+this._cubeSamplerName+`,
-            #else
-                `+this._2DSamplerName+`,
-            #endif
-            #if defined(NORMAL) && defined(USESPHERICALINVERTEX)
-                `+this._vEnvironmentIrradianceName+`,
-            #endif
-            #ifdef USESPHERICALFROMREFLECTIONMAP
-                #if !defined(NORMAL) || !defined(USESPHERICALINVERTEX)
-                    `+this._reflectionMatrixName+`,
-                #endif
-            #endif
-            #ifdef USEIRRADIANCEMAP
-                irradianceSampler, // ** not handled **
-            #endif
-            #ifndef LODBASEDMICROSFURACE
-                #ifdef `+this._define3DName+`
-                    `+this._cubeSamplerName+`,
-                    `+this._cubeSamplerName+`,
-                #else
-                    `+this._2DSamplerName+`,
-                    `+this._2DSamplerName+`,
-                #endif
-            #endif
-            #ifdef REALTIME_FILTERING
-                `+this._vReflectionFilteringInfoName+`,
-            #endif
-                reflectionOut
-            );
-        #endif\r
-`},t.prototype._buildBlock=function(e){return this._scene=e.sharedData.scene,e.target!==Ce.Fragment&&(this._defineLODReflectionAlpha=e._getFreeDefineName("LODINREFLECTIONALPHA"),this._defineLinearSpecularReflection=e._getFreeDefineName("LINEARSPECULARREFLECTION")),this},t.prototype._dumpPropertiesCode=function(){var e=r.prototype._dumpPropertiesCode.call(this);return this.texture&&(e+=this._codeVariableName+".texture.gammaSpace = "+this.texture.gammaSpace+`);\r
-`),e+=this._codeVariableName+".useSphericalHarmonics = "+this.useSphericalHarmonics+`;\r
-`,e+=this._codeVariableName+".forceIrradianceInFragment = "+this.forceIrradianceInFragment+`;\r
-`},t.prototype.serialize=function(){var e,n,i=r.prototype.serialize.call(this);return i.useSphericalHarmonics=this.useSphericalHarmonics,i.forceIrradianceInFragment=this.forceIrradianceInFragment,i.gammaSpace=(n=(e=this.texture)===null||e===void 0?void 0:e.gammaSpace)===null||n===void 0||n,i},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),this.useSphericalHarmonics=e.useSphericalHarmonics,this.forceIrradianceInFragment=e.forceIrradianceInFragment,this.texture&&(this.texture.gammaSpace=e.gammaSpace)},Object(c.c)([Vt("Spherical Harmonics",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"useSphericalHarmonics",void 0),Object(c.c)([Vt("Force irradiance in fragment",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"forceIrradianceInFragment",void 0),t}(pc);R.a.RegisteredTypes["BABYLON.ReflectionBlock"]=bc;var ba=function(r){function t(e){var n=r.call(this,e,Ce.Fragment)||this;return n.remapF0OnInterfaceChange=!0,n._isUnique=!0,n.registerInput("intensity",le.Float,!1,Ce.Fragment),n.registerInput("roughness",le.Float,!0,Ce.Fragment),n.registerInput("indexOfRefraction",le.Float,!0,Ce.Fragment),n.registerInput("normalMapColor",le.Color3,!0,Ce.Fragment),n.registerInput("uv",le.Vector2,!0,Ce.Fragment),n.registerInput("tintColor",le.Color3,!0,Ce.Fragment),n.registerInput("tintAtDistance",le.Float,!0,Ce.Fragment),n.registerInput("tintThickness",le.Float,!0,Ce.Fragment),n.registerInput("worldTangent",le.Vector4,!0),n.registerOutput("clearcoat",le.Object,Ce.Fragment,new Zn("clearcoat",n,Tn.Output,t,"ClearCoatBlock")),n}return Object(c.d)(t,r),t.prototype.initialize=function(e){e._excludeVariableName("clearcoatOut"),e._excludeVariableName("vClearCoatParams"),e._excludeVariableName("vClearCoatTintParams"),e._excludeVariableName("vClearCoatRefractionParams"),e._excludeVariableName("vClearCoatTangentSpaceParams")},t.prototype.getClassName=function(){return"ClearCoatBlock"},Object.defineProperty(t.prototype,"intensity",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"roughness",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"indexOfRefraction",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normalMapColor",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"uv",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"tintColor",{get:function(){return this._inputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"tintAtDistance",{get:function(){return this._inputs[6]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"tintThickness",{get:function(){return this._inputs[7]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldTangent",{get:function(){return this._inputs[8]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"clearcoat",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.intensity.isConnected){var n=new At("ClearCoat intensity",Ce.Fragment,le.Float);n.value=1,n.output.connectTo(this.intensity)}},t.prototype.prepareDefines=function(e,n,i){r.prototype.prepareDefines.call(this,e,n,i),i.setValue("CLEARCOAT",!0),i.setValue("CLEARCOAT_TEXTURE",!1,!0),i.setValue("CLEARCOAT_USE_ROUGHNESS_FROM_MAINTEXTURE",!0,!0),i.setValue("CLEARCOAT_TINT",this.tintColor.isConnected||this.tintThickness.isConnected||this.tintAtDistance.isConnected,!0),i.setValue("CLEARCOAT_BUMP",this.normalMapColor.isConnected,!0),i.setValue("CLEARCOAT_DEFAULTIOR",!this.indexOfRefraction.isConnected||this.indexOfRefraction.connectInputBlock.value===Ar._DefaultIndexOfRefraction,!0),i.setValue("CLEARCOAT_REMAP_F0",this.remapF0OnInterfaceChange,!0)},t.prototype.bind=function(e,n,i,o){var a,s;r.prototype.bind.call(this,e,n,i);var d=(s=(a=this.indexOfRefraction.connectInputBlock)===null||a===void 0?void 0:a.value)!==null&&s!==void 0?s:Ar._DefaultIndexOfRefraction,p=1-d,b=1+d,P=Math.pow(-p/b,2),O=1/d;e.setFloat4("vClearCoatRefractionParams",P,O,p,b);var B=this.clearcoat.hasEndpoints?this.clearcoat.endpoints[0].ownerBlock:null,F=B?.perturbedNormal.isConnected?B.perturbedNormal.connectedPoint.ownerBlock:null;this._scene._mirroredCameraPosition?e.setFloat2("vClearCoatTangentSpaceParams",F?.invertX?1:-1,F?.invertY?1:-1):e.setFloat2("vClearCoatTangentSpaceParams",F?.invertX?-1:1,F?.invertY?-1:1)},t.prototype._generateTBNSpace=function(e,n,i){var o="",a="//"+this.name,s=this.worldTangent;e._emitExtension("derivatives","#extension GL_OES_standard_derivatives : enable");var d={search:/defined\(TANGENT\)/g,replace:s.isConnected?"defined(TANGENT)":"defined(IGNORE)"};return s.isConnected&&(o+="vec3 tbnNormal = normalize("+i+`.xyz);\r
-`,o+="vec3 tbnTangent = normalize("+s.associatedVariableName+`.xyz);\r
-`,o+=`vec3 tbnBitangent = cross(tbnNormal, tbnTangent);\r
-`,o+=`mat3 vTBN = mat3(tbnTangent, tbnBitangent, tbnNormal);\r
-`),e._emitFunctionFromInclude("bumpFragmentMainFunctions",a,{replaceStrings:[d]}),o},t.GetCode=function(e,n,i,o,a,s,d){var p="",b=n?.intensity.isConnected?n.intensity.associatedVariableName:"1.",P=n?.roughness.isConnected?n.roughness.associatedVariableName:"0.",O=n?.normalMapColor.isConnected?n.normalMapColor.associatedVariableName:"vec3(0.)",B=n?.uv.isConnected?n.uv.associatedVariableName:"vec2(0.)",F=n?.tintColor.isConnected?n.tintColor.associatedVariableName:"vec3(1.)",z=n?.tintThickness.isConnected?n.tintThickness.associatedVariableName:"1.",J=n?.tintAtDistance.isConnected?n.tintAtDistance.associatedVariableName:"1.";return n&&(e._emitUniformFromString("vClearCoatRefractionParams","vec4"),e._emitUniformFromString("vClearCoatTangentSpaceParams","vec2")),a&&n&&(p+=n._generateTBNSpace(e,o,d),s=n.worldTangent.isConnected),p+=`clearcoatOutParams clearcoatOut;
-
-        #ifdef CLEARCOAT
-            vec2 vClearCoatParams = vec2(`+b+", "+P+`);
-            vec4 vClearCoatTintParams = vec4(`+F+", "+z+`);
-
-            clearcoatBlock(
-                `+o+`.xyz,
-                geometricNormalW,
-                viewDirectionW,
-                vClearCoatParams,
-                specularEnvironmentR0,
-            #ifdef CLEARCOAT_TEXTURE
-                vec2(0.),
-            #endif
-            #ifdef CLEARCOAT_TINT
-                vClearCoatTintParams,
-                `+J+`,
-                vClearCoatRefractionParams,
-                #ifdef CLEARCOAT_TINT_TEXTURE
-                    vec4(0.),
-                #endif
-            #endif
-            #ifdef CLEARCOAT_BUMP
-                vec2(0., 1.),
-                vec4(`+O+`, 0.),
-                `+B+`,
-                #if defined(`+(s?"TANGENT":"IGNORE")+`) && defined(NORMAL)
-                    vTBN,
-                #else
-                    vClearCoatTangentSpaceParams,
-                #endif
-                #ifdef OBJECTSPACE_NORMALMAP
-                    normalMatrix,
-                #endif
-            #endif
-            #if defined(FORCENORMALFORWARD) && defined(NORMAL)
-                faceNormal,
-            #endif
-            #ifdef REFLECTION
-                `+i?._vReflectionMicrosurfaceInfosName+`,
-                `+i?._vReflectionInfosName+`,
-                `+i?.reflectionColor+`,
-                vLightingIntensity,
-                #ifdef `+i?._define3DName+`
-                    `+i?._cubeSamplerName+`,
-                #else
-                    `+i?._2DSamplerName+`,
-                #endif
-                #ifndef LODBASEDMICROSFURACE
-                    #ifdef `+i?._define3DName+`
-                        `+i?._cubeSamplerName+`,
-                        `+i?._cubeSamplerName+`,
-                    #else
-                        `+i?._2DSamplerName+`,
-                        `+i?._2DSamplerName+`,
-                    #endif
-                #endif
-            #endif
-            #if defined(ENVIRONMENTBRDF) && !defined(`+i?._defineSkyboxName+`)
-                #ifdef RADIANCEOCCLUSION
-                    ambientMonochrome,
-                #endif
-            #endif
-                clearcoatOut
-            );
-        #else
-            clearcoatOut.specularEnvironmentR0 = specularEnvironmentR0;
-        #endif\r
-`},t.prototype._buildBlock=function(e){return this._scene=e.sharedData.scene,e.target===Ce.Fragment&&(e.sharedData.bindableBlocks.push(this),e.sharedData.blocksWithDefines.push(this)),this},t.prototype._dumpPropertiesCode=function(){var e="";return e+=this._codeVariableName+".remapF0OnInterfaceChange = "+this.remapF0OnInterfaceChange+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return e.remapF0OnInterfaceChange=this.remapF0OnInterfaceChange,e},t.prototype._deserialize=function(e,n,i){var o;r.prototype._deserialize.call(this,e,n,i),this.remapF0OnInterfaceChange=(o=e.remapF0OnInterfaceChange)===null||o===void 0||o},Object(c.c)([Vt("Remap F0 on interface change",Lt.Boolean,"ADVANCED")],t.prototype,"remapF0OnInterfaceChange",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.ClearCoatBlock"]=ba;var yc=function(r){function t(e){var n=r.call(this,e,Ce.Fragment)||this;return n.linkRefractionWithTransparency=!1,n.invertRefractionY=!1,n._isUnique=!0,n.registerInput("intensity",le.Float,!1,Ce.Fragment),n.registerInput("tintAtDistance",le.Float,!0,Ce.Fragment),n.registerOutput("refraction",le.Object,Ce.Fragment,new Zn("refraction",n,Tn.Output,t,"RefractionBlock")),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"RefractionBlock"},Object.defineProperty(t.prototype,"intensity",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"tintAtDistance",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"view",{get:function(){return this.viewConnectionPoint},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"refraction",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"hasTexture",{get:function(){return!!this._getTexture()},enumerable:!1,configurable:!0}),t.prototype._getTexture=function(){return this.texture?this.texture:this._scene.environmentTexture},t.prototype.autoConfigure=function(e){if(!this.intensity.isConnected){var n=new At("Refraction intensity",Ce.Fragment,le.Float);n.value=1,n.output.connectTo(this.intensity)}if(this.view&&!this.view.isConnected){var i=e.getInputBlockByPredicate(function(o){return o.systemValue===bt.View});i||(i=new At("view")).setAsSystemValue(bt.View),i.output.connectTo(this.view)}},t.prototype.prepareDefines=function(e,n,i){r.prototype.prepareDefines.call(this,e,n,i);var o=this._getTexture(),a=o&&o.getTextureMatrix;i.setValue("SS_REFRACTION",a,!0),a&&(i.setValue(this._define3DName,o.isCube,!0),i.setValue(this._defineLODRefractionAlpha,o.lodLevelInAlpha,!0),i.setValue(this._defineLinearSpecularRefraction,o.linearSpecularLOD,!0),i.setValue(this._defineOppositeZ,this._scene.useRightHandedSystem?!o.invertZ:o.invertZ,!0),i.setValue("SS_LINKREFRACTIONTOTRANSPARENCY",this.linkRefractionWithTransparency,!0),i.setValue("SS_GAMMAREFRACTION",o.gammaSpace,!0),i.setValue("SS_RGBDREFRACTION",o.isRGBD,!0))},t.prototype.isReady=function(){var e=this._getTexture();return!(e&&!e.isReadyOrNotBlocking())},t.prototype.bind=function(e,n,i,o){var a,s;r.prototype.bind.call(this,e,n,i);var d=this._getTexture();if(d){d.isCube?e.setTexture(this._cubeSamplerName,d):e.setTexture(this._2DSamplerName,d),e.setMatrix(this._refractionMatrixName,d.getReflectionTextureMatrix());var p=1;d.isCube||d.depth&&(p=d.depth);var b=(s=(a=this.indexOfRefractionConnectionPoint.connectInputBlock)===null||a===void 0?void 0:a.value)!==null&&s!==void 0?s:1.5;e.setFloat4(this._vRefractionInfosName,d.level,1/b,p,this.invertRefractionY?-1:1),e.setFloat3(this._vRefractionMicrosurfaceInfosName,d.getSize().width,d.lodGenerationScale,d.lodGenerationOffset);var P=d.getSize().width;e.setFloat2(this._vRefractionFilteringInfoName,P,$.a.Log2(P))}},t.prototype.getCode=function(e){return e.sharedData.blockingBlocks.push(this),e.sharedData.textureBlocks.push(this),this._cubeSamplerName=e._getFreeVariableName(this.name+"CubeSampler"),e.samplers.push(this._cubeSamplerName),this._2DSamplerName=e._getFreeVariableName(this.name+"2DSampler"),e.samplers.push(this._2DSamplerName),this._define3DName=e._getFreeDefineName("SS_REFRACTIONMAP_3D"),e._samplerDeclaration+="#ifdef "+this._define3DName+`\r
-`,e._samplerDeclaration+="uniform samplerCube "+this._cubeSamplerName+`;\r
-`,e._samplerDeclaration+=`#else\r
-`,e._samplerDeclaration+="uniform sampler2D "+this._2DSamplerName+`;\r
-`,e._samplerDeclaration+=`#endif\r
-`,e.sharedData.blocksWithDefines.push(this),e.sharedData.bindableBlocks.push(this),this._defineLODRefractionAlpha=e._getFreeDefineName("SS_LODINREFRACTIONALPHA"),this._defineLinearSpecularRefraction=e._getFreeDefineName("SS_LINEARSPECULARREFRACTION"),this._defineOppositeZ=e._getFreeDefineName("SS_REFRACTIONMAP_OPPOSITEZ"),this._refractionMatrixName=e._getFreeVariableName("refractionMatrix"),e._emitUniformFromString(this._refractionMatrixName,"mat4"),e._emitFunction("sampleRefraction",`
-            #ifdef `+this._define3DName+`
-                #define sampleRefraction(s, c) textureCube(s, c)
-            #else
-                #define sampleRefraction(s, c) texture2D(s, c)
-            #endif\r
-`,"//"+this.name),e._emitFunction("sampleRefractionLod",`
-            #ifdef `+this._define3DName+`
-                #define sampleRefractionLod(s, c, l) textureCubeLodEXT(s, c, l)
-            #else
-                #define sampleRefractionLod(s, c, l) texture2DLodEXT(s, c, l)
-            #endif\r
-`,"//"+this.name),this._vRefractionMicrosurfaceInfosName=e._getFreeVariableName("vRefractionMicrosurfaceInfos"),e._emitUniformFromString(this._vRefractionMicrosurfaceInfosName,"vec3"),this._vRefractionInfosName=e._getFreeVariableName("vRefractionInfos"),e._emitUniformFromString(this._vRefractionInfosName,"vec4"),this._vRefractionFilteringInfoName=e._getFreeVariableName("vRefractionFilteringInfo"),e._emitUniformFromString(this._vRefractionFilteringInfoName,"vec2"),""},t.prototype._buildBlock=function(e){return this._scene=e.sharedData.scene,this},t.prototype._dumpPropertiesCode=function(){var e=r.prototype._dumpPropertiesCode.call(this);return this.texture&&(e=this.texture.isCube?this._codeVariableName+'.texture = new BABYLON.CubeTexture("'+this.texture.name+`");\r
-`:this._codeVariableName+'.texture = new BABYLON.Texture("'+this.texture.name+`");\r
-`,e+=this._codeVariableName+".texture.coordinatesMode = "+this.texture.coordinatesMode+`;\r
-`),e+=this._codeVariableName+".linkRefractionWithTransparency = "+this.linkRefractionWithTransparency+`;\r
-`,e+=this._codeVariableName+".invertRefractionY = "+this.invertRefractionY+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return this.texture&&(e.texture=this.texture.serialize()),e.linkRefractionWithTransparency=this.linkRefractionWithTransparency,e.invertRefractionY=this.invertRefractionY,e},t.prototype._deserialize=function(e,n,i){r.prototype._deserialize.call(this,e,n,i),e.texture&&(i=e.texture.url.indexOf("data:")===0?"":i,e.texture.isCube?this.texture=oi.Parse(e.texture,n,i):this.texture=we.a.Parse(e.texture,n,i)),this.linkRefractionWithTransparency=e.linkRefractionWithTransparency,this.invertRefractionY=e.invertRefractionY},Object(c.c)([Vt("Link refraction to transparency",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"linkRefractionWithTransparency",void 0),Object(c.c)([Vt("Invert refraction Y",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"invertRefractionY",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.RefractionBlock"]=yc;var ya=function(r){function t(e){var n=r.call(this,e,Ce.Fragment)||this;return n._isUnique=!0,n.registerInput("thickness",le.Float,!1,Ce.Fragment),n.registerInput("tintColor",le.Color3,!0,Ce.Fragment),n.registerInput("translucencyIntensity",le.Float,!0,Ce.Fragment),n.registerInput("translucencyDiffusionDist",le.Color3,!0,Ce.Fragment),n.registerInput("refraction",le.Object,!0,Ce.Fragment,new Zn("refraction",n,Tn.Input,yc,"RefractionBlock")),n.registerOutput("subsurface",le.Object,Ce.Fragment,new Zn("subsurface",n,Tn.Output,t,"SubSurfaceBlock")),n}return Object(c.d)(t,r),t.prototype.initialize=function(e){e._excludeVariableName("subSurfaceOut"),e._excludeVariableName("vThicknessParam"),e._excludeVariableName("vTintColor"),e._excludeVariableName("vSubSurfaceIntensity")},t.prototype.getClassName=function(){return"SubSurfaceBlock"},Object.defineProperty(t.prototype,"thickness",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"tintColor",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"translucencyIntensity",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"translucencyDiffusionDist",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"refraction",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"subsurface",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.thickness.isConnected){var n=new At("SubSurface thickness",Ce.Fragment,le.Float);n.value=0,n.output.connectTo(this.thickness)}},t.prototype.prepareDefines=function(e,n,i){r.prototype.prepareDefines.call(this,e,n,i);var o=this.translucencyDiffusionDist.isConnected||this.translucencyIntensity.isConnected;i.setValue("SUBSURFACE",o||this.refraction.isConnected,!0),i.setValue("SS_TRANSLUCENCY",o,!0),i.setValue("SS_THICKNESSANDMASK_TEXTURE",!1,!0),i.setValue("SS_MASK_FROM_THICKNESS_TEXTURE",!1,!0),i.setValue("SS_MASK_FROM_THICKNESS_TEXTURE_GLTF",!1,!0)},t.GetCode=function(e,n,i,o){var a,s,d,p,b,P,O,B,F,z,J,ie,se,ce,ue,fe,ve="",Te=n?.thickness.isConnected?n.thickness.associatedVariableName:"0.",Re=n?.tintColor.isConnected?n.tintColor.associatedVariableName:"vec3(1.)",Ae=n?.translucencyIntensity.isConnected?n?.translucencyIntensity.associatedVariableName:"1.",Ee=n?.translucencyDiffusionDist.isConnected?n?.translucencyDiffusionDist.associatedVariableName:"vec3(1.)",Se=n?.refraction.isConnected?(a=n?.refraction.connectedPoint)===null||a===void 0?void 0:a.ownerBlock:null,Le=Se?.tintAtDistance.isConnected?Se.tintAtDistance.associatedVariableName:"1.",xe=Se?.intensity.isConnected?Se.intensity.associatedVariableName:"1.",Ne=Se?.view.isConnected?Se.view.associatedVariableName:"";return ve+=(s=Se?.getCode(e))!==null&&s!==void 0?s:"",ve+=`subSurfaceOutParams subSurfaceOut;
-
-        #ifdef SUBSURFACE
-            vec2 vThicknessParam = vec2(0., `+Te+`);
-            vec4 vTintColor = vec4(`+Re+", "+Le+`);
-            vec3 vSubSurfaceIntensity = vec3(`+xe+", "+Ae+`, 0.);
-
-            subSurfaceBlock(
-                vSubSurfaceIntensity,
-                vThicknessParam,
-                vTintColor,
-                normalW,
-                specularEnvironmentReflectance,
-            #ifdef SS_THICKNESSANDMASK_TEXTURE
-                vec4(0.),
-            #endif
-            #ifdef REFLECTION
-                #ifdef SS_TRANSLUCENCY
-                    `+i?._reflectionMatrixName+`,
-                    #ifdef USESPHERICALFROMREFLECTIONMAP
-                        #if !defined(NORMAL) || !defined(USESPHERICALINVERTEX)
-                            reflectionOut.irradianceVector,
-                        #endif
-                        #if defined(REALTIME_FILTERING)
-                            `+i?._cubeSamplerName+`,
-                            `+i?._vReflectionFilteringInfoName+`,
-                        #endif
-                        #endif
-                    #ifdef USEIRRADIANCEMAP
-                        irradianceSampler,
-                    #endif
-                #endif
-            #endif
-            #ifdef SS_REFRACTION
-                `+o+`.xyz,
-                viewDirectionW,
-                `+Ne+`,
-                surfaceAlbedo,
-                `+((d=Se?._vRefractionInfosName)!==null&&d!==void 0?d:"")+`,
-                `+((p=Se?._refractionMatrixName)!==null&&p!==void 0?p:"")+`,
-                `+((b=Se?._vRefractionMicrosurfaceInfosName)!==null&&b!==void 0?b:"")+`,
-                vLightingIntensity,
-                #ifdef SS_LINKREFRACTIONTOTRANSPARENCY
-                    alpha,
-                #endif
-                #ifdef `+((P=Se?._defineLODRefractionAlpha)!==null&&P!==void 0?P:"IGNORE")+`
-                    NdotVUnclamped,
-                #endif
-                #ifdef `+((O=Se?._defineLinearSpecularRefraction)!==null&&O!==void 0?O:"IGNORE")+`
-                    roughness,
-                #else
-                    alphaG,
-                #endif
-                #ifdef `+((B=Se?._define3DName)!==null&&B!==void 0?B:"IGNORE")+`
-                    `+((F=Se?._cubeSamplerName)!==null&&F!==void 0?F:"")+`,
-                #else
-                    `+((z=Se?._2DSamplerName)!==null&&z!==void 0?z:"")+`,
-                #endif
-                #ifndef LODBASEDMICROSFURACE
-                    #ifdef `+((J=Se?._define3DName)!==null&&J!==void 0?J:"IGNORE")+`
-                        `+((ie=Se?._cubeSamplerName)!==null&&ie!==void 0?ie:"")+`,
-                        `+((se=Se?._cubeSamplerName)!==null&&se!==void 0?se:"")+`,
-                    #else
-                        `+((ce=Se?._2DSamplerName)!==null&&ce!==void 0?ce:"")+`,
-                        `+((ue=Se?._2DSamplerName)!==null&&ue!==void 0?ue:"")+`,
-                    #endif
-                #endif
-                #ifdef ANISOTROPIC
-                    anisotropicOut,
-                #endif
-                #ifdef REALTIME_FILTERING
-                    `+((fe=Se?._vRefractionFilteringInfoName)!==null&&fe!==void 0?fe:"")+`,
-                #endif
-            #endif
-            #ifdef SS_TRANSLUCENCY
-                `+Ee+`,
-            #endif
-                subSurfaceOut
-            );
-
-            #ifdef SS_REFRACTION
-                surfaceAlbedo = subSurfaceOut.surfaceAlbedo;
-                #ifdef SS_LINKREFRACTIONTOTRANSPARENCY
-                    alpha = subSurfaceOut.alpha;
-                #endif
-            #endif
-        #else
-            subSurfaceOut.specularEnvironmentReflectance = specularEnvironmentReflectance;
-        #endif\r
-`},t.prototype._buildBlock=function(e){return e.target===Ce.Fragment&&e.sharedData.blocksWithDefines.push(this),this},t}(pt);R.a.RegisteredTypes["BABYLON.SubSurfaceBlock"]=ya;var dm={ambientClr:["finalAmbient",""],diffuseDir:["finalDiffuse",""],specularDir:["finalSpecularScaled","!defined(UNLIT) && defined(SPECULARTERM)"],clearcoatDir:["finalClearCoatScaled","!defined(UNLIT) && defined(CLEARCOAT)"],sheenDir:["finalSheenScaled","!defined(UNLIT) && defined(SHEEN)"],diffuseInd:["finalIrradiance","!defined(UNLIT) && defined(REFLECTION)"],specularInd:["finalRadianceScaled","!defined(UNLIT) && defined(REFLECTION)"],clearcoatInd:["clearcoatOut.finalClearCoatRadianceScaled","!defined(UNLIT) && defined(REFLECTION) && defined(CLEARCOAT)"],sheenInd:["sheenOut.finalSheenRadianceScaled","!defined(UNLIT) && defined(REFLECTION) && defined(SHEEN) && defined(ENVIRONMENTBRDF)"],refraction:["subSurfaceOut.finalRefraction","!defined(UNLIT) && defined(SS_REFRACTION)"],lighting:["finalColor.rgb",""],shadow:["shadow",""],alpha:["alpha",""]},hd=function(r){function t(e){var n=r.call(this,e,Ce.VertexAndFragment)||this;return n._environmentBRDFTexture=null,n._metallicReflectanceColor=M.a.White(),n._metallicF0Factor=1,n.directIntensity=1,n.environmentIntensity=1,n.specularIntensity=1,n.lightFalloff=0,n.useAlphaTest=!1,n.alphaTestCutoff=.5,n.useAlphaBlending=!1,n.useRadianceOverAlpha=!0,n.useSpecularOverAlpha=!0,n.enableSpecularAntiAliasing=!1,n.realTimeFiltering=!1,n.realTimeFilteringQuality=h.a.TEXTURE_FILTERING_QUALITY_LOW,n.useEnergyConservation=!0,n.useRadianceOcclusion=!0,n.useHorizonOcclusion=!0,n.unlit=!1,n.forceNormalForward=!1,n.debugMode=0,n.debugLimit=0,n.debugFactor=1,n._isUnique=!0,n.registerInput("worldPosition",le.Vector4,!1,Ce.Vertex),n.registerInput("worldNormal",le.Vector4,!1,Ce.Fragment),n.registerInput("view",le.Matrix,!1),n.registerInput("cameraPosition",le.Vector3,!1,Ce.Fragment),n.registerInput("perturbedNormal",le.Vector4,!0,Ce.Fragment),n.registerInput("baseColor",le.Color3,!0,Ce.Fragment),n.registerInput("metallic",le.Float,!1,Ce.Fragment),n.registerInput("roughness",le.Float,!1,Ce.Fragment),n.registerInput("ambientOcc",le.Float,!0,Ce.Fragment),n.registerInput("opacity",le.Float,!0,Ce.Fragment),n.registerInput("indexOfRefraction",le.Float,!0,Ce.Fragment),n.registerInput("ambientColor",le.Color3,!0,Ce.Fragment),n.registerInput("reflection",le.Object,!0,Ce.Fragment,new Zn("reflection",n,Tn.Input,bc,"ReflectionBlock")),n.registerInput("clearcoat",le.Object,!0,Ce.Fragment,new Zn("clearcoat",n,Tn.Input,ba,"ClearCoatBlock")),n.registerInput("sheen",le.Object,!0,Ce.Fragment,new Zn("sheen",n,Tn.Input,gc,"SheenBlock")),n.registerInput("subsurface",le.Object,!0,Ce.Fragment,new Zn("subsurface",n,Tn.Input,ya,"SubSurfaceBlock")),n.registerInput("anisotropy",le.Object,!0,Ce.Fragment,new Zn("anisotropy",n,Tn.Input,vc,"AnisotropyBlock")),n.registerOutput("ambientClr",le.Color3,Ce.Fragment),n.registerOutput("diffuseDir",le.Color3,Ce.Fragment),n.registerOutput("specularDir",le.Color3,Ce.Fragment),n.registerOutput("clearcoatDir",le.Color3,Ce.Fragment),n.registerOutput("sheenDir",le.Color3,Ce.Fragment),n.registerOutput("diffuseInd",le.Color3,Ce.Fragment),n.registerOutput("specularInd",le.Color3,Ce.Fragment),n.registerOutput("clearcoatInd",le.Color3,Ce.Fragment),n.registerOutput("sheenInd",le.Color3,Ce.Fragment),n.registerOutput("refraction",le.Color3,Ce.Fragment),n.registerOutput("lighting",le.Color3,Ce.Fragment),n.registerOutput("shadow",le.Float,Ce.Fragment),n.registerOutput("alpha",le.Float,Ce.Fragment),n}return Object(c.d)(t,r),t.prototype.initialize=function(e){e._excludeVariableName("vLightingIntensity"),e._excludeVariableName("geometricNormalW"),e._excludeVariableName("normalW"),e._excludeVariableName("faceNormal"),e._excludeVariableName("albedoOpacityOut"),e._excludeVariableName("surfaceAlbedo"),e._excludeVariableName("alpha"),e._excludeVariableName("aoOut"),e._excludeVariableName("baseColor"),e._excludeVariableName("reflectivityOut"),e._excludeVariableName("microSurface"),e._excludeVariableName("roughness"),e._excludeVariableName("NdotVUnclamped"),e._excludeVariableName("NdotV"),e._excludeVariableName("alphaG"),e._excludeVariableName("AARoughnessFactors"),e._excludeVariableName("environmentBrdf"),e._excludeVariableName("ambientMonochrome"),e._excludeVariableName("seo"),e._excludeVariableName("eho"),e._excludeVariableName("environmentRadiance"),e._excludeVariableName("irradianceVector"),e._excludeVariableName("environmentIrradiance"),e._excludeVariableName("diffuseBase"),e._excludeVariableName("specularBase"),e._excludeVariableName("preInfo"),e._excludeVariableName("info"),e._excludeVariableName("shadow"),e._excludeVariableName("finalDiffuse"),e._excludeVariableName("finalAmbient"),e._excludeVariableName("ambientOcclusionForDirectDiffuse"),e._excludeVariableName("finalColor"),e._excludeVariableName("vClipSpacePosition"),e._excludeVariableName("vDebugMode")},t.prototype.getClassName=function(){return"PBRMetallicRoughnessBlock"},Object.defineProperty(t.prototype,"worldPosition",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"worldNormal",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"view",{get:function(){return this._inputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cameraPosition",{get:function(){return this._inputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"perturbedNormal",{get:function(){return this._inputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"baseColor",{get:function(){return this._inputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"metallic",{get:function(){return this._inputs[6]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"roughness",{get:function(){return this._inputs[7]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"ambientOcc",{get:function(){return this._inputs[8]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"opacity",{get:function(){return this._inputs[9]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"indexOfRefraction",{get:function(){return this._inputs[10]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"ambientColor",{get:function(){return this._inputs[11]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"reflection",{get:function(){return this._inputs[12]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"clearcoat",{get:function(){return this._inputs[13]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sheen",{get:function(){return this._inputs[14]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"subsurface",{get:function(){return this._inputs[15]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"anisotropy",{get:function(){return this._inputs[16]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"ambientClr",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"diffuseDir",{get:function(){return this._outputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"specularDir",{get:function(){return this._outputs[2]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"clearcoatDir",{get:function(){return this._outputs[3]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sheenDir",{get:function(){return this._outputs[4]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"diffuseIndirect",{get:function(){return this._outputs[5]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"specularIndirect",{get:function(){return this._outputs[6]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"clearcoatIndirect",{get:function(){return this._outputs[7]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sheenIndirect",{get:function(){return this._outputs[8]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"refraction",{get:function(){return this._outputs[9]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"lighting",{get:function(){return this._outputs[10]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"shadow",{get:function(){return this._outputs[11]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"alpha",{get:function(){return this._outputs[12]},enumerable:!1,configurable:!0}),t.prototype.autoConfigure=function(e){if(!this.cameraPosition.isConnected){var n=e.getInputBlockByPredicate(function(o){return o.systemValue===bt.CameraPosition});n||(n=new At("cameraPosition")).setAsSystemValue(bt.CameraPosition),n.output.connectTo(this.cameraPosition)}if(!this.view.isConnected){var i=e.getInputBlockByPredicate(function(o){return o.systemValue===bt.View});i||(i=new At("view")).setAsSystemValue(bt.View),i.output.connectTo(this.view)}},t.prototype.prepareDefines=function(e,n,i){i.setValue("PBR",!0),i.setValue("METALLICWORKFLOW",!0),i.setValue("DEBUGMODE",this.debugMode,!0),i.setValue("NORMALXYSCALE",!0),i.setValue("BUMP",this.perturbedNormal.isConnected,!0),i.setValue("LODBASEDMICROSFURACE",this._scene.getEngine().getCaps().textureLOD),i.setValue("ALBEDO",!1,!0),i.setValue("OPACITY",this.opacity.isConnected,!0),i.setValue("AMBIENT",!0,!0),i.setValue("AMBIENTINGRAYSCALE",!1,!0),i.setValue("REFLECTIVITY",!1,!0),i.setValue("AOSTOREINMETALMAPRED",!1,!0),i.setValue("METALLNESSSTOREINMETALMAPBLUE",!1,!0),i.setValue("ROUGHNESSSTOREINMETALMAPALPHA",!1,!0),i.setValue("ROUGHNESSSTOREINMETALMAPGREEN",!1,!0),this.lightFalloff===_n.LIGHTFALLOFF_STANDARD?(i.setValue("USEPHYSICALLIGHTFALLOFF",!1),i.setValue("USEGLTFLIGHTFALLOFF",!1)):this.lightFalloff===_n.LIGHTFALLOFF_GLTF?(i.setValue("USEPHYSICALLIGHTFALLOFF",!1),i.setValue("USEGLTFLIGHTFALLOFF",!0)):(i.setValue("USEPHYSICALLIGHTFALLOFF",!0),i.setValue("USEGLTFLIGHTFALLOFF",!1));var o=this.alphaTestCutoff.toString();if(i.setValue("ALPHABLEND",this.useAlphaBlending,!0),i.setValue("ALPHAFROMALBEDO",!1,!0),i.setValue("ALPHATEST",this.useAlphaTest,!0),i.setValue("ALPHATESTVALUE",o.indexOf(".")<0?o+".":o,!0),i.setValue("OPACITYRGB",!1,!0),i.setValue("RADIANCEOVERALPHA",this.useRadianceOverAlpha,!0),i.setValue("SPECULAROVERALPHA",this.useSpecularOverAlpha,!0),i.setValue("SPECULARAA",this._scene.getEngine().getCaps().standardDerivatives&&this.enableSpecularAntiAliasing,!0),i.setValue("REALTIME_FILTERING",this.realTimeFiltering,!0),this._scene.getEngine().webGLVersion>1?i.setValue("NUM_SAMPLES",this.realTimeFilteringQuality+"u",!0):i.setValue("NUM_SAMPLES",""+this.realTimeFilteringQuality,!0),i.setValue("BRDF_V_HEIGHT_CORRELATED",!0),i.setValue("MS_BRDF_ENERGY_CONSERVATION",this.useEnergyConservation,!0),i.setValue("RADIANCEOCCLUSION",this.useRadianceOcclusion,!0),i.setValue("HORIZONOCCLUSION",this.useHorizonOcclusion,!0),i.setValue("UNLIT",this.unlit,!0),i.setValue("FORCENORMALFORWARD",this.forceNormalForward,!0),this._environmentBRDFTexture&&ht.a.ReflectionTextureEnabled?(i.setValue("ENVIRONMENTBRDF",!0),i.setValue("ENVIRONMENTBRDF_RGBD",this._environmentBRDFTexture.isRGBD,!0)):(i.setValue("ENVIRONMENTBRDF",!1),i.setValue("ENVIRONMENTBRDF_RGBD",!1)),i._areLightsDirty){var a=e.getScene();if(this.light){var s={needNormals:!1,needRebuild:!1,lightmapMode:!1,shadowEnabled:!1,specularEnabled:!1};et.a.PrepareDefinesForLight(a,e,this.light,this._lightId,i,!0,s),s.needRebuild&&i.rebuild()}else et.a.PrepareDefinesForLights(a,e,i,!0,n.maxSimultaneousLights),i._needNormals=!0,et.a.PrepareDefinesForMultiview(a,i)}},t.prototype.updateUniformsAndSamples=function(e,n,i,o){for(var a=0;a<n.maxSimultaneousLights&&i["LIGHT"+a];a++){var s=e.uniforms.indexOf("vLightData"+a)>=0;et.a.PrepareUniformsAndSamplersForLight(a,e.uniforms,e.samplers,i["PROJECTEDLIGHTTEXTURE"+a],o,s)}},t.prototype.bind=function(e,n,i){var o,a;if(i){var s=i.getScene();this.light?et.a.BindLight(this.light,this._lightId,s,e,!0):et.a.BindLights(s,i,e,!0,n.maxSimultaneousLights),e.setTexture(this._environmentBrdfSamplerName,this._environmentBRDFTexture),e.setFloat2("vDebugMode",this.debugLimit,this.debugFactor);var d=this._scene.ambientColor;d&&e.setColor3("ambientFromScene",d);var p=s.useRightHandedSystem===(s._mirroredCameraPosition!=null);e.setFloat(this._invertNormalName,p?-1:1),e.setFloat4("vLightingIntensity",this.directIntensity,1,this.environmentIntensity*this._scene.environmentIntensity,this.specularIntensity);var b=(a=(o=this.indexOfRefraction.connectInputBlock)===null||o===void 0?void 0:o.value)!==null&&a!==void 0?a:1.5,P=Math.pow((b-1)/(b+1),2);this._metallicReflectanceColor.scaleToRef(P*this._metallicF0Factor,M.c.Color3[0]);var O=this._metallicF0Factor;e.setColor4(this._vMetallicReflectanceFactorsName,M.c.Color3[0],O)}},t.prototype._injectVertexCode=function(e){var n,i,o=this.worldPosition,a="//"+this.name;this.light?(this._lightId=(e.counters.lightCounter!==void 0?e.counters.lightCounter:-1)+1,e.counters.lightCounter=this._lightId,e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",a,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()}]},this._lightId.toString())):(e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",a,{repeatKey:"maxSimultaneousLights"}),this._lightId=0,e.sharedData.dynamicUniformBlocks.push(this));var s="v_"+o.associatedVariableName;e._emitVaryingFromString(s,"vec4")&&(e.compilationString+=s+" = "+o.associatedVariableName+`;\r
-`);var d=this.reflection.isConnected?(n=this.reflection.connectedPoint)===null||n===void 0?void 0:n.ownerBlock:null;d&&(d.viewConnectionPoint=this.view),e.compilationString+=(i=d?.handleVertexSide(e))!==null&&i!==void 0?i:"",e._emitUniformFromString("vDebugMode","vec2","defined(IGNORE) || DEBUGMODE > 0"),e._emitUniformFromString("ambientFromScene","vec3"),e._emitVaryingFromString("vClipSpacePosition","vec4","defined(IGNORE) || DEBUGMODE > 0")&&(e._injectAtEnd+=`#if DEBUGMODE > 0\r
-`,e._injectAtEnd+=`vClipSpacePosition = gl_Position;\r
-`,e._injectAtEnd+=`#endif\r
-`),this.light?e.compilationString+=e._emitCodeFromInclude("shadowsVertex",a,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()},{search:/worldPos/g,replace:o.associatedVariableName}]}):(e.compilationString+="vec4 worldPos = "+o.associatedVariableName+`;\r
-`,this.view.isConnected&&(e.compilationString+="mat4 view = "+this.view.associatedVariableName+`;\r
-`),e.compilationString+=e._emitCodeFromInclude("shadowsVertex",a,{repeatKey:"maxSimultaneousLights"}))},t.prototype._getAlbedoOpacityCode=function(){var e=`albedoOpacityOutParams albedoOpacityOut;\r
-`;return e+=`albedoOpacityBlock(
-                vec4(`+(this.baseColor.isConnected?this.baseColor.associatedVariableName:"vec3(1.)")+`, 1.),
-            #ifdef ALBEDO
-                vec4(1.),
-                vec2(1., 1.),
-            #endif
-            #ifdef OPACITY
-                vec4(`+(this.opacity.isConnected?this.opacity.associatedVariableName:"1.")+`),
-                vec2(1., 1.),
-            #endif
-                albedoOpacityOut
-            );
-
-            vec3 surfaceAlbedo = albedoOpacityOut.surfaceAlbedo;
-            float alpha = albedoOpacityOut.alpha;\r
-`},t.prototype._getAmbientOcclusionCode=function(){var e=`ambientOcclusionOutParams aoOut;\r
-`;return e+=`ambientOcclusionBlock(
-            #ifdef AMBIENT
-                vec3(`+(this.ambientOcc.isConnected?this.ambientOcc.associatedVariableName:"1.")+`),
-                vec4(0., 1.0, 1.0, 0.),
-            #endif
-                aoOut
-            );\r
-`},t.prototype._getReflectivityCode=function(e){var n=`reflectivityOutParams reflectivityOut;\r
-`;return this._vMetallicReflectanceFactorsName=e._getFreeVariableName("vMetallicReflectanceFactors"),e._emitUniformFromString(this._vMetallicReflectanceFactorsName,"vec4"),n+=`vec3 baseColor = surfaceAlbedo;
-
-            reflectivityBlock(
-                vec4(`+this.metallic.associatedVariableName+", "+this.roughness.associatedVariableName+`, 0., 0.),
-            #ifdef METALLICWORKFLOW
-                surfaceAlbedo,
-                `+this._vMetallicReflectanceFactorsName+`,
-            #endif
-            #ifdef REFLECTIVITY
-                vec3(0., 0., 1.),
-                vec4(1.),
-            #endif
-            #if defined(METALLICWORKFLOW) && defined(REFLECTIVITY)  && defined(AOSTOREINMETALMAPRED)
-                aoOut.ambientOcclusionColor,
-            #endif
-            #ifdef MICROSURFACEMAP
-                microSurfaceTexel, <== not handled!
-            #endif
-                reflectivityOut
-            );
-
-            float microSurface = reflectivityOut.microSurface;
-            float roughness = reflectivityOut.roughness;
-
-            #ifdef METALLICWORKFLOW
-                surfaceAlbedo = reflectivityOut.surfaceAlbedo;
-            #endif
-            #if defined(METALLICWORKFLOW) && defined(REFLECTIVITY) && defined(AOSTOREINMETALMAPRED)
-                aoOut.ambientOcclusionColor = reflectivityOut.ambientOcclusionColor;
-            #endif\r
-`},t.prototype._buildBlock=function(e){var n,i,o,a,s,d,p,b,P,O,B,F,z,J,ie,se,ce,ue,fe,ve,Te,Re,Ae,Ee,Se,Le,xe,Ne,Ie,Fe,Ye,tt,it,ut,Qe,ot,rt,Ze,dt;r.prototype._buildBlock.call(this,e),this._scene=e.sharedData.scene,this._environmentBRDFTexture||(this._environmentBRDFTexture=ea.GetEnvironmentBRDFTexture(this._scene));var Ve=this.reflection.isConnected?(n=this.reflection.connectedPoint)===null||n===void 0?void 0:n.ownerBlock:null;if(Ve&&(Ve.worldPositionConnectionPoint=this.worldPosition,Ve.cameraPositionConnectionPoint=this.cameraPosition,Ve.worldNormalConnectionPoint=this.worldNormal),e.target!==Ce.Fragment)return this._injectVertexCode(e),this;e.sharedData.bindableBlocks.push(this),e.sharedData.blocksWithDefines.push(this);var Je="//"+this.name,yt="v_"+this.worldPosition.associatedVariableName,Wt=this.perturbedNormal;this._environmentBrdfSamplerName=e._getFreeVariableName("environmentBrdfSampler"),e._emit2DSampler(this._environmentBrdfSamplerName),e.sharedData.hints.needAlphaBlending=e.sharedData.hints.needAlphaBlending||this.useAlphaBlending,e.sharedData.hints.needAlphaTesting=e.sharedData.hints.needAlphaTesting||this.useAlphaTest,e._emitExtension("lod","#extension GL_EXT_shader_texture_lod : enable","defined(LODBASEDMICROSFURACE)"),e._emitExtension("derivatives","#extension GL_OES_standard_derivatives : enable"),this.light?e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",Je,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()}]},this._lightId.toString()):e._emitFunctionFromInclude(e.supportUniformBuffers?"lightUboDeclaration":"lightFragmentDeclaration",Je,{repeatKey:"maxSimultaneousLights"}),e._emitFunctionFromInclude("helperFunctions",Je),e._emitFunctionFromInclude("importanceSampling",Je),e._emitFunctionFromInclude("pbrHelperFunctions",Je),e._emitFunctionFromInclude("imageProcessingFunctions",Je),e._emitFunctionFromInclude("shadowsFragmentFunctions",Je,{replaceStrings:[{search:/vPositionW/g,replace:yt+".xyz"}]}),e._emitFunctionFromInclude("pbrDirectLightingSetupFunctions",Je,{replaceStrings:[{search:/vPositionW/g,replace:yt+".xyz"}]}),e._emitFunctionFromInclude("pbrDirectLightingFalloffFunctions",Je),e._emitFunctionFromInclude("pbrBRDFFunctions",Je,{replaceStrings:[{search:/REFLECTIONMAP_SKYBOX/g,replace:(i=Ve?._defineSkyboxName)!==null&&i!==void 0?i:"REFLECTIONMAP_SKYBOX"}]}),e._emitFunctionFromInclude("hdrFilteringFunctions",Je),e._emitFunctionFromInclude("pbrDirectLightingFunctions",Je,{replaceStrings:[{search:/vPositionW/g,replace:yt+".xyz"}]}),e._emitFunctionFromInclude("pbrIBLFunctions",Je),e._emitFunctionFromInclude("pbrBlockAlbedoOpacity",Je),e._emitFunctionFromInclude("pbrBlockReflectivity",Je),e._emitFunctionFromInclude("pbrBlockAmbientOcclusion",Je),e._emitFunctionFromInclude("pbrBlockAlphaFresnel",Je),e._emitFunctionFromInclude("pbrBlockAnisotropic",Je),e._emitUniformFromString("vLightingIntensity","vec4"),this._vNormalWName=e._getFreeVariableName("vNormalW"),e.compilationString+="vec4 "+this._vNormalWName+" = normalize("+this.worldNormal.associatedVariableName+`);\r
-`,e._registerTempVariable("viewDirectionW")&&(e.compilationString+="vec3 viewDirectionW = normalize("+this.cameraPosition.associatedVariableName+" - "+yt+`.xyz);\r
-`),e.compilationString+="vec3 geometricNormalW = "+this._vNormalWName+`.xyz;\r
-`,e.compilationString+="vec3 normalW = "+(Wt.isConnected?"normalize("+Wt.associatedVariableName+".xyz)":"geometricNormalW")+`;\r
-`,this._invertNormalName=e._getFreeVariableName("invertNormal"),e._emitUniformFromString(this._invertNormalName,"float"),e.compilationString+=e._emitCodeFromInclude("pbrBlockNormalFinal",Je,{replaceStrings:[{search:/vPositionW/g,replace:yt+".xyz"},{search:/vEyePosition.w/g,replace:this._invertNormalName}]}),e.compilationString+=this._getAlbedoOpacityCode(),e.compilationString+=e._emitCodeFromInclude("depthPrePass",Je),e.compilationString+=this._getAmbientOcclusionCode(),e.compilationString+=e._emitCodeFromInclude("pbrBlockLightmapInit",Je),e.compilationString+=`#ifdef UNLIT
-                vec3 diffuseBase = vec3(1., 1., 1.);
-            #else\r
-`,e.compilationString+=this._getReflectivityCode(e),e.compilationString+=e._emitCodeFromInclude("pbrBlockGeometryInfo",Je,{replaceStrings:[{search:/REFLECTIONMAP_SKYBOX/g,replace:(o=Ve?._defineSkyboxName)!==null&&o!==void 0?o:"REFLECTIONMAP_SKYBOX"},{search:/REFLECTIONMAP_3D/g,replace:(a=Ve?._define3DName)!==null&&a!==void 0?a:"REFLECTIONMAP_3D"}]});var Nt=this.anisotropy.isConnected?(s=this.anisotropy.connectedPoint)===null||s===void 0?void 0:s.ownerBlock:null;Nt&&(Nt.worldPositionConnectionPoint=this.worldPosition,Nt.worldNormalConnectionPoint=this.worldNormal,e.compilationString+=Nt.getCode(e,!this.perturbedNormal.isConnected)),Ve&&Ve.hasTexture&&(e.compilationString+=Ve.getCode(e,Nt?"anisotropicOut.anisotropicNormal":"normalW")),e._emitFunctionFromInclude("pbrBlockReflection",Je,{replaceStrings:[{search:/computeReflectionCoords/g,replace:"computeReflectionCoordsPBR"},{search:/REFLECTIONMAP_3D/g,replace:(d=Ve?._define3DName)!==null&&d!==void 0?d:"REFLECTIONMAP_3D"},{search:/REFLECTIONMAP_OPPOSITEZ/g,replace:(p=Ve?._defineOppositeZ)!==null&&p!==void 0?p:"REFLECTIONMAP_OPPOSITEZ"},{search:/REFLECTIONMAP_PROJECTION/g,replace:(b=Ve?._defineProjectionName)!==null&&b!==void 0?b:"REFLECTIONMAP_PROJECTION"},{search:/REFLECTIONMAP_SKYBOX/g,replace:(P=Ve?._defineSkyboxName)!==null&&P!==void 0?P:"REFLECTIONMAP_SKYBOX"},{search:/LODINREFLECTIONALPHA/g,replace:(O=Ve?._defineLODReflectionAlpha)!==null&&O!==void 0?O:"LODINREFLECTIONALPHA"},{search:/LINEARSPECULARREFLECTION/g,replace:(B=Ve?._defineLinearSpecularReflection)!==null&&B!==void 0?B:"LINEARSPECULARREFLECTION"},{search:/vReflectionFilteringInfo/g,replace:(F=Ve?._vReflectionFilteringInfoName)!==null&&F!==void 0?F:"vReflectionFilteringInfo"}]}),e.compilationString+=e._emitCodeFromInclude("pbrBlockReflectance0",Je,{replaceStrings:[{search:/metallicReflectanceFactors/g,replace:this._vMetallicReflectanceFactorsName}]});var Qt=this.sheen.isConnected?(z=this.sheen.connectedPoint)===null||z===void 0?void 0:z.ownerBlock:null;Qt&&(e.compilationString+=Qt.getCode(Ve)),e._emitFunctionFromInclude("pbrBlockSheen",Je,{replaceStrings:[{search:/REFLECTIONMAP_3D/g,replace:(J=Ve?._define3DName)!==null&&J!==void 0?J:"REFLECTIONMAP_3D"},{search:/REFLECTIONMAP_SKYBOX/g,replace:(ie=Ve?._defineSkyboxName)!==null&&ie!==void 0?ie:"REFLECTIONMAP_SKYBOX"},{search:/LODINREFLECTIONALPHA/g,replace:(se=Ve?._defineLODReflectionAlpha)!==null&&se!==void 0?se:"LODINREFLECTIONALPHA"},{search:/LINEARSPECULARREFLECTION/g,replace:(ce=Ve?._defineLinearSpecularReflection)!==null&&ce!==void 0?ce:"LINEARSPECULARREFLECTION"}]});var vt=this.clearcoat.isConnected?(ue=this.clearcoat.connectedPoint)===null||ue===void 0?void 0:ue.ownerBlock:null,Jt=!this.perturbedNormal.isConnected&&!this.anisotropy.isConnected,Xt=this.perturbedNormal.isConnected&&((fe=this.perturbedNormal.connectedPoint)===null||fe===void 0?void 0:fe.ownerBlock).worldTangent.isConnected,zt=this.anisotropy.isConnected&&((ve=this.anisotropy.connectedPoint)===null||ve===void 0?void 0:ve.ownerBlock).worldTangent.isConnected,Yt=Xt||!this.perturbedNormal.isConnected&&zt;e.compilationString+=ba.GetCode(e,vt,Ve,yt,Jt,Yt,this.worldNormal.associatedVariableName),Jt&&(Yt=(Te=vt?.worldTangent.isConnected)!==null&&Te!==void 0&&Te),e._emitFunctionFromInclude("pbrBlockClearcoat",Je,{replaceStrings:[{search:/computeReflectionCoords/g,replace:"computeReflectionCoordsPBR"},{search:/REFLECTIONMAP_3D/g,replace:(Re=Ve?._define3DName)!==null&&Re!==void 0?Re:"REFLECTIONMAP_3D"},{search:/REFLECTIONMAP_OPPOSITEZ/g,replace:(Ae=Ve?._defineOppositeZ)!==null&&Ae!==void 0?Ae:"REFLECTIONMAP_OPPOSITEZ"},{search:/REFLECTIONMAP_PROJECTION/g,replace:(Ee=Ve?._defineProjectionName)!==null&&Ee!==void 0?Ee:"REFLECTIONMAP_PROJECTION"},{search:/REFLECTIONMAP_SKYBOX/g,replace:(Se=Ve?._defineSkyboxName)!==null&&Se!==void 0?Se:"REFLECTIONMAP_SKYBOX"},{search:/LODINREFLECTIONALPHA/g,replace:(Le=Ve?._defineLODReflectionAlpha)!==null&&Le!==void 0?Le:"LODINREFLECTIONALPHA"},{search:/LINEARSPECULARREFLECTION/g,replace:(xe=Ve?._defineLinearSpecularReflection)!==null&&xe!==void 0?xe:"LINEARSPECULARREFLECTION"},{search:/defined\(TANGENT\)/g,replace:Yt?"defined(TANGENT)":"defined(IGNORE)"}]}),e.compilationString+=e._emitCodeFromInclude("pbrBlockReflectance",Je,{replaceStrings:[{search:/REFLECTIONMAP_SKYBOX/g,replace:(Ne=Ve?._defineSkyboxName)!==null&&Ne!==void 0?Ne:"REFLECTIONMAP_SKYBOX"},{search:/REFLECTIONMAP_3D/g,replace:(Ie=Ve?._define3DName)!==null&&Ie!==void 0?Ie:"REFLECTIONMAP_3D"}]});var Et=this.subsurface.isConnected?(Fe=this.subsurface.connectedPoint)===null||Fe===void 0?void 0:Fe.ownerBlock:null,Mt=this.subsurface.isConnected?(tt=((Ye=this.subsurface.connectedPoint)===null||Ye===void 0?void 0:Ye.ownerBlock).refraction.connectedPoint)===null||tt===void 0?void 0:tt.ownerBlock:null;Mt&&(Mt.viewConnectionPoint=this.view,Mt.indexOfRefractionConnectionPoint=this.indexOfRefraction),e.compilationString+=ya.GetCode(e,Et,Ve,yt),e._emitFunctionFromInclude("pbrBlockSubSurface",Je,{replaceStrings:[{search:/REFLECTIONMAP_3D/g,replace:(it=Ve?._define3DName)!==null&&it!==void 0?it:"REFLECTIONMAP_3D"},{search:/REFLECTIONMAP_OPPOSITEZ/g,replace:(ut=Ve?._defineOppositeZ)!==null&&ut!==void 0?ut:"REFLECTIONMAP_OPPOSITEZ"},{search:/REFLECTIONMAP_PROJECTION/g,replace:(Qe=Ve?._defineProjectionName)!==null&&Qe!==void 0?Qe:"REFLECTIONMAP_PROJECTION"},{search:/SS_REFRACTIONMAP_3D/g,replace:(ot=Mt?._define3DName)!==null&&ot!==void 0?ot:"SS_REFRACTIONMAP_3D"},{search:/SS_LODINREFRACTIONALPHA/g,replace:(rt=Mt?._defineLODRefractionAlpha)!==null&&rt!==void 0?rt:"SS_LODINREFRACTIONALPHA"},{search:/SS_LINEARSPECULARREFRACTION/g,replace:(Ze=Mt?._defineLinearSpecularRefraction)!==null&&Ze!==void 0?Ze:"SS_LINEARSPECULARREFRACTION"},{search:/SS_REFRACTIONMAP_OPPOSITEZ/g,replace:(dt=Mt?._defineOppositeZ)!==null&&dt!==void 0?dt:"SS_REFRACTIONMAP_OPPOSITEZ"}]}),e.compilationString+=e._emitCodeFromInclude("pbrBlockDirectLighting",Je),this.light?e.compilationString+=e._emitCodeFromInclude("lightFragment",Je,{replaceStrings:[{search:/{X}/g,replace:this._lightId.toString()}]}):e.compilationString+=e._emitCodeFromInclude("lightFragment",Je,{repeatKey:"maxSimultaneousLights"}),e.compilationString+=e._emitCodeFromInclude("pbrBlockFinalLitComponents",Je),e.compilationString+=`#endif\r
-`;var $t=this.ambientColor.isConnected?this.ambientColor.associatedVariableName:"vec3(0., 0., 0.)",Dn=_n.DEFAULT_AO_ON_ANALYTICAL_LIGHTS.toString();Dn.indexOf(".")===-1&&(Dn+="."),e.compilationString+=e._emitCodeFromInclude("pbrBlockFinalUnlitComponents",Je,{replaceStrings:[{search:/vec3 finalEmissive[\s\S]*?finalEmissive\*=vLightingIntensity\.y;/g,replace:""},{search:/vAmbientColor/g,replace:$t+" * ambientFromScene"},{search:/vAmbientInfos\.w/g,replace:Dn}]}),e.compilationString+=e._emitCodeFromInclude("pbrBlockFinalColorComposition",Je,{replaceStrings:[{search:/finalEmissive/g,replace:"vec3(0.)"}]}),e.compilationString+=e._emitCodeFromInclude("pbrBlockImageProcessing",Je,{replaceStrings:[{search:/visibility/g,replace:"1."}]}),e.compilationString+=e._emitCodeFromInclude("pbrDebug",Je,{replaceStrings:[{search:/vNormalW/g,replace:this._vNormalWName},{search:/vPositionW/g,replace:yt},{search:/albedoTexture\.rgb;/g,replace:`vec3(1.);\r
-gl_FragColor.rgb = toGammaSpace(gl_FragColor.rgb);\r
-`}]});for(var Vn=0,$n=this._outputs;Vn<$n.length;Vn++){var Ln=$n[Vn];if(Ln.hasEndpoints){var qt=dm[Ln.name];if(qt){var ui=qt[0],Ri=qt[1];Ri&&(e.compilationString+="#if "+Ri+`\r
-`),e.compilationString+=this._declareOutput(Ln,e)+" = "+ui+`;\r
-`,Ri&&(e.compilationString+=`#else\r
-`,e.compilationString+=this._declareOutput(Ln,e)+` = vec3(0.);\r
-`,e.compilationString+=`#endif\r
-`)}else console.error("There's no remapping for the "+Ln.name+" end point! No code generated")}}return this},t.prototype._dumpPropertiesCode=function(){var e="";return e+=this._codeVariableName+".lightFalloff = "+this.lightFalloff+`;\r
-`,e+=this._codeVariableName+".useAlphaTest = "+this.useAlphaTest+`;\r
-`,e+=this._codeVariableName+".alphaTestCutoff = "+this.alphaTestCutoff+`;\r
-`,e+=this._codeVariableName+".useAlphaBlending = "+this.useAlphaBlending+`;\r
-`,e+=this._codeVariableName+".useRadianceOverAlpha = "+this.useRadianceOverAlpha+`;\r
-`,e+=this._codeVariableName+".useSpecularOverAlpha = "+this.useSpecularOverAlpha+`;\r
-`,e+=this._codeVariableName+".enableSpecularAntiAliasing = "+this.enableSpecularAntiAliasing+`;\r
-`,e+=this._codeVariableName+".realTimeFiltering = "+this.realTimeFiltering+`;\r
-`,e+=this._codeVariableName+".realTimeFilteringQuality = "+this.realTimeFilteringQuality+`;\r
-`,e+=this._codeVariableName+".useEnergyConservation = "+this.useEnergyConservation+`;\r
-`,e+=this._codeVariableName+".useRadianceOcclusion = "+this.useRadianceOcclusion+`;\r
-`,e+=this._codeVariableName+".useHorizonOcclusion = "+this.useHorizonOcclusion+`;\r
-`,e+=this._codeVariableName+".unlit = "+this.unlit+`;\r
-`,e+=this._codeVariableName+".forceNormalForward = "+this.forceNormalForward+`;\r
-`,e+=this._codeVariableName+".debugMode = "+this.debugMode+`;\r
-`,e+=this._codeVariableName+".debugLimit = "+this.debugLimit+`;\r
-`,e+=this._codeVariableName+".debugFactor = "+this.debugFactor+`;\r
-`},t.prototype.serialize=function(){var e=r.prototype.serialize.call(this);return this.light&&(e.lightId=this.light.id),e.lightFalloff=this.lightFalloff,e.useAlphaTest=this.useAlphaTest,e.alphaTestCutoff=this.alphaTestCutoff,e.useAlphaBlending=this.useAlphaBlending,e.useRadianceOverAlpha=this.useRadianceOverAlpha,e.useSpecularOverAlpha=this.useSpecularOverAlpha,e.enableSpecularAntiAliasing=this.enableSpecularAntiAliasing,e.realTimeFiltering=this.realTimeFiltering,e.realTimeFilteringQuality=this.realTimeFilteringQuality,e.useEnergyConservation=this.useEnergyConservation,e.useRadianceOcclusion=this.useRadianceOcclusion,e.useHorizonOcclusion=this.useHorizonOcclusion,e.unlit=this.unlit,e.forceNormalForward=this.forceNormalForward,e.debugMode=this.debugMode,e.debugLimit=this.debugLimit,e.debugFactor=this.debugFactor,e},t.prototype._deserialize=function(e,n,i){var o,a;r.prototype._deserialize.call(this,e,n,i),e.lightId&&(this.light=n.getLightByID(e.lightId)),this.lightFalloff=(o=e.lightFalloff)!==null&&o!==void 0?o:0,this.useAlphaTest=e.useAlphaTest,this.alphaTestCutoff=e.alphaTestCutoff,this.useAlphaBlending=e.useAlphaBlending,this.useRadianceOverAlpha=e.useRadianceOverAlpha,this.useSpecularOverAlpha=e.useSpecularOverAlpha,this.enableSpecularAntiAliasing=e.enableSpecularAntiAliasing,this.realTimeFiltering=!!e.realTimeFiltering,this.realTimeFilteringQuality=(a=e.realTimeFilteringQuality)!==null&&a!==void 0?a:h.a.TEXTURE_FILTERING_QUALITY_LOW,this.useEnergyConservation=e.useEnergyConservation,this.useRadianceOcclusion=e.useRadianceOcclusion,this.useHorizonOcclusion=e.useHorizonOcclusion,this.unlit=e.unlit,this.forceNormalForward=!!e.forceNormalForward,this.debugMode=e.debugMode,this.debugLimit=e.debugLimit,this.debugFactor=e.debugFactor},Object(c.c)([Vt("Direct lights",Lt.Float,"INTENSITY",{min:0,max:1,notifiers:{update:!0}})],t.prototype,"directIntensity",void 0),Object(c.c)([Vt("Environment lights",Lt.Float,"INTENSITY",{min:0,max:1,notifiers:{update:!0}})],t.prototype,"environmentIntensity",void 0),Object(c.c)([Vt("Specular highlights",Lt.Float,"INTENSITY",{min:0,max:1,notifiers:{update:!0}})],t.prototype,"specularIntensity",void 0),Object(c.c)([Vt("Light falloff",Lt.List,"LIGHTING & COLORS",{notifiers:{update:!0},options:[{label:"Physical",value:_n.LIGHTFALLOFF_PHYSICAL},{label:"GLTF",value:_n.LIGHTFALLOFF_GLTF},{label:"Standard",value:_n.LIGHTFALLOFF_STANDARD}]})],t.prototype,"lightFalloff",void 0),Object(c.c)([Vt("Alpha Testing",Lt.Boolean,"OPACITY")],t.prototype,"useAlphaTest",void 0),Object(c.c)([Vt("Alpha CutOff",Lt.Float,"OPACITY",{min:0,max:1,notifiers:{update:!0}})],t.prototype,"alphaTestCutoff",void 0),Object(c.c)([Vt("Alpha blending",Lt.Boolean,"OPACITY")],t.prototype,"useAlphaBlending",void 0),Object(c.c)([Vt("Radiance over alpha",Lt.Boolean,"RENDERING",{notifiers:{update:!0}})],t.prototype,"useRadianceOverAlpha",void 0),Object(c.c)([Vt("Specular over alpha",Lt.Boolean,"RENDERING",{notifiers:{update:!0}})],t.prototype,"useSpecularOverAlpha",void 0),Object(c.c)([Vt("Specular anti-aliasing",Lt.Boolean,"RENDERING",{notifiers:{update:!0}})],t.prototype,"enableSpecularAntiAliasing",void 0),Object(c.c)([Vt("Realtime filtering",Lt.Boolean,"RENDERING",{notifiers:{update:!0}})],t.prototype,"realTimeFiltering",void 0),Object(c.c)([Vt("Realtime filtering quality",Lt.List,"RENDERING",{notifiers:{update:!0},options:[{label:"Low",value:h.a.TEXTURE_FILTERING_QUALITY_LOW},{label:"Medium",value:h.a.TEXTURE_FILTERING_QUALITY_MEDIUM},{label:"High",value:h.a.TEXTURE_FILTERING_QUALITY_HIGH}]})],t.prototype,"realTimeFilteringQuality",void 0),Object(c.c)([Vt("Energy Conservation",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"useEnergyConservation",void 0),Object(c.c)([Vt("Radiance occlusion",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"useRadianceOcclusion",void 0),Object(c.c)([Vt("Horizon occlusion",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"useHorizonOcclusion",void 0),Object(c.c)([Vt("Unlit",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"unlit",void 0),Object(c.c)([Vt("Force normal forward",Lt.Boolean,"ADVANCED",{notifiers:{update:!0}})],t.prototype,"forceNormalForward",void 0),Object(c.c)([Vt("Debug mode",Lt.List,"DEBUG",{notifiers:{update:!0},options:[{label:"None",value:0},{label:"Normalized position",value:1},{label:"Normals",value:2},{label:"Tangents",value:3},{label:"Bitangents",value:4},{label:"Bump Normals",value:5},{label:"ClearCoat Normals",value:8},{label:"ClearCoat Tangents",value:9},{label:"ClearCoat Bitangents",value:10},{label:"Anisotropic Normals",value:11},{label:"Anisotropic Tangents",value:12},{label:"Anisotropic Bitangents",value:13},{label:"Env Refraction",value:40},{label:"Env Reflection",value:41},{label:"Env Clear Coat",value:42},{label:"Direct Diffuse",value:50},{label:"Direct Specular",value:51},{label:"Direct Clear Coat",value:52},{label:"Direct Sheen",value:53},{label:"Env Irradiance",value:54},{label:"Surface Albedo",value:60},{label:"Reflectance 0",value:61},{label:"Metallic",value:62},{label:"Metallic F0",value:71},{label:"Roughness",value:63},{label:"AlphaG",value:64},{label:"NdotV",value:65},{label:"ClearCoat Color",value:66},{label:"ClearCoat Roughness",value:67},{label:"ClearCoat NdotV",value:68},{label:"Transmittance",value:69},{label:"Refraction Transmittance",value:70},{label:"SEO",value:80},{label:"EHO",value:81},{label:"Energy Factor",value:82},{label:"Specular Reflectance",value:83},{label:"Clear Coat Reflectance",value:84},{label:"Sheen Reflectance",value:85},{label:"Luminance Over Alpha",value:86},{label:"Alpha",value:87}]})],t.prototype,"debugMode",void 0),Object(c.c)([Vt("Split position",Lt.Float,"DEBUG",{min:-1,max:1,notifiers:{update:!0}})],t.prototype,"debugLimit",void 0),Object(c.c)([Vt("Output factor",Lt.Float,"DEBUG",{min:0,max:5,notifiers:{update:!0}})],t.prototype,"debugFactor",void 0),t}(pt);R.a.RegisteredTypes["BABYLON.PBRMetallicRoughnessBlock"]=hd;var dd=function(r){function t(e){var n=r.call(this,e,Ce.Neutral)||this;return n.registerInput("left",le.AutoDetect),n.registerInput("right",le.AutoDetect),n.registerOutput("output",le.BasedOnInput),n._outputs[0]._typeConnectionSource=n._inputs[0],n._linkConnectionTypes(0,1),n}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ModBlock"},Object.defineProperty(t.prototype,"left",{get:function(){return this._inputs[0]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"right",{get:function(){return this._inputs[1]},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"output",{get:function(){return this._outputs[0]},enumerable:!1,configurable:!0}),t.prototype._buildBlock=function(e){r.prototype._buildBlock.call(this,e);var n=this._outputs[0];return e.compilationString+=this._declareOutput(n,e)+" = mod("+this.left.associatedVariableName+", "+this.right.associatedVariableName+`);\r
-`,this},t}(pt);R.a.RegisteredTypes["BABYLON.ModBlock"]=dd;var fm=function(){function r(){}return r.prototype.optimize=function(t,e){},r}(),pm=f(120),_m=function(){function r(){this.mm=new Map}return r.prototype.get=function(t,e){var n=this.mm.get(t);if(n!==void 0)return n.get(e)},r.prototype.set=function(t,e,n){var i=this.mm.get(t);i===void 0&&this.mm.set(t,i=new Map),i.set(e,n)},r}(),mm=function(){function r(t,e,n){var i=this;this._baseMaterial=t,this._scene=e,this._options=n,this._subMeshToEffect=new Map,this._subMeshToDepthEffect=new _m,this._meshes=new Map;var o=t.getClassName()==="NodeMaterial"?"u_":"";if(o){this._matriceNames={world:o+"World",view:o+"View",projection:o+"Projection",viewProjection:o+"ViewProjection",worldView:o+"WorldxView",worldViewProjection:o+"WorldxViewxProjection"};for(var a=t.getInputBlocks(),s=0;s<a.length;++s)switch(a[s]._systemValue){case bt.World:this._matriceNames.world=a[s].associatedVariableName;break;case bt.View:this._matriceNames.view=a[s].associatedVariableName;break;case bt.Projection:this._matriceNames.projection=a[s].associatedVariableName;break;case bt.ViewProjection:this._matriceNames.viewProjection=a[s].associatedVariableName;break;case bt.WorldView:this._matriceNames.worldView=a[s].associatedVariableName;break;case bt.WorldViewProjection:this._matriceNames.worldViewProjection=a[s].associatedVariableName}}else this._matriceNames={world:o+"world",view:o+"view",projection:o+"projection",viewProjection:o+"viewProjection",worldView:o+"worldView",worldViewProjection:o+"worldViewProjection"};this._onEffectCreatedObserver=this._baseMaterial.onEffectCreatedObservable.add(function(d){var p,b=(p=d.subMesh)===null||p===void 0?void 0:p.getMesh();b&&!i._meshes.has(b)&&i._meshes.set(b,b.onDisposeObservable.add(function(P){for(var O=i._subMeshToEffect.keys(),B=O.next();B.done!==!0;B=O.next()){var F=B.value;F?.getMesh()===P&&(i._subMeshToEffect.delete(F),i._subMeshToDepthEffect.mm.delete(F))}})),i._subMeshToEffect.set(d.subMesh,d.effect),i._subMeshToDepthEffect.mm.delete(d.subMesh)})}return Object.defineProperty(r.prototype,"standalone",{get:function(){var t,e;return(e=(t=this._options)===null||t===void 0?void 0:t.standalone)!==null&&e!==void 0&&e},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"baseMaterial",{get:function(){return this._baseMaterial},enumerable:!1,configurable:!0}),r.prototype.getEffect=function(t,e){var n,i,o,a,s,d;return(d=(o=(i=(n=this._subMeshToDepthEffect.mm.get(t))===null||n===void 0?void 0:n.get(e))===null||i===void 0?void 0:i.depthEffect)!==null&&o!==void 0?o:(s=(a=this._subMeshToDepthEffect.mm.get(null))===null||a===void 0?void 0:a.get(e))===null||s===void 0?void 0:s.depthEffect)!==null&&d!==void 0?d:null},r.prototype.isReadyForSubMesh=function(t,e,n,i){var o,a;return this.standalone&&this._baseMaterial.isReadyForSubMesh(t.getMesh(),t,i),(a=(o=this._makeEffect(t,e,n))===null||o===void 0?void 0:o.isReady())!==null&&a!==void 0&&a},r.prototype.dispose=function(){this._baseMaterial.onEffectCreatedObservable.remove(this._onEffectCreatedObserver),this._onEffectCreatedObserver=null;for(var t=this._meshes.entries(),e=t.next();e.done!==!0;e=t.next()){var n=e.value,i=n[0],o=n[1];i.onDisposeObservable.remove(o)}},r.prototype._makeEffect=function(t,e,n){var i,o=(i=this._subMeshToEffect.get(t))!==null&&i!==void 0?i:this._subMeshToEffect.get(null);if(!o)return null;var a=this._subMeshToDepthEffect.get(t,n);a||(a={depthEffect:null,depthDefines:"",token:pm.a.RandomId()},this._subMeshToDepthEffect.set(t,n,a));var s=e.join(`
-`);if(a.depthEffect&&s===a.depthDefines)return a.depthEffect;a.depthDefines=s;var d=o.rawVertexSourceCode,p=o.rawFragmentSourceCode,b=this._options&&this._options.remappedVariables?"#include<shadowMapVertexNormalBias>("+this._options.remappedVariables.join(",")+")":ze.a.IncludesShadersStore.shadowMapVertexNormalBias,P=this._options&&this._options.remappedVariables?"#include<shadowMapVertexMetric>("+this._options.remappedVariables.join(",")+")":ze.a.IncludesShadersStore.shadowMapVertexMetric,O=this._options&&this._options.remappedVariables?"#include<shadowMapFragmentSoftTransparentShadow>("+this._options.remappedVariables.join(",")+")":ze.a.IncludesShadersStore.shadowMapFragmentSoftTransparentShadow,B=ze.a.IncludesShadersStore.shadowMapFragment;d=(d=(d=(d=d.replace(/void\s+?main/g,ze.a.IncludesShadersStore.shadowMapVertexDeclaration+`\r
-void main`)).replace(/#define SHADOWDEPTH_NORMALBIAS|#define CUSTOM_VERTEX_UPDATE_WORLDPOS/g,b)).indexOf("#define SHADOWDEPTH_METRIC")!==-1?d.replace(/#define SHADOWDEPTH_METRIC/g,P):d.replace(/}\s*$/g,P+`\r
-}`)).replace(/#define SHADER_NAME.*?\n|out vec4 glFragColor;\n/g,"");var F=p.indexOf("#define SHADOWDEPTH_SOFTTRANSPARENTSHADOW")>=0||p.indexOf("#define CUSTOM_FRAGMENT_BEFORE_FOG")>=0,z=p.indexOf("#define SHADOWDEPTH_FRAGMENT")!==-1,J="";F?p=p.replace(/#define SHADOWDEPTH_SOFTTRANSPARENTSHADOW|#define CUSTOM_FRAGMENT_BEFORE_FOG/g,O):J=O+`\r
-`,p=p.replace(/void\s+?main/g,ze.a.IncludesShadersStore.shadowMapFragmentDeclaration+`\r
-void main`),z?p=p.replace(/#define SHADOWDEPTH_FRAGMENT/g,B):J+=B+`\r
-`,J&&(p=p.replace(/}\s*$/g,J+"}")),p=p.replace(/#define SHADER_NAME.*?\n|out vec4 glFragColor;\n/g,"");var ie=o.getUniformNames().slice();return ie.push("biasAndScaleSM","depthValuesSM","lightDataSM","softTransparentShadowSM"),a.depthEffect=this._scene.getEngine().createEffect({vertexSource:d,fragmentSource:p,vertexToken:a.token,fragmentToken:a.token},{attributes:o.getAttributesNames(),uniformsNames:ie,uniformBuffersNames:o.getUniformBuffersNames(),samplers:o.getSamplers(),defines:s+`
-`+o.defines.replace("#define SHADOWS","").replace(/#define SHADOW\d/g,""),indexParameters:o.getIndexParameters()},this._scene.getEngine()),a.depthEffect},r}(),fd=f(101);function Tc(r,t,e,n,i){var o=new r.DecoderBuffer;o.Init(t,t.byteLength);var a,s,d=new r.Decoder;try{var p=d.GetEncodedGeometryType(o);switch(p){case r.TRIANGULAR_MESH:a=new r.Mesh,s=d.DecodeBufferToMesh(o,a);break;case r.POINT_CLOUD:a=new r.PointCloud,s=d.DecodeBufferToPointCloud(o,a);break;default:throw new Error("Invalid geometry type "+p)}if(!s.ok()||!a.ptr)throw new Error(s.error_msg());if(p===r.TRIANGULAR_MESH){var b=3*a.num_faces(),P=4*b,O=r._malloc(P);try{d.GetTrianglesUInt32Array(a,P,O);var B=new Uint32Array(b);B.set(new Uint32Array(r.HEAPF32.buffer,O,b)),n(B)}finally{r._free(O)}}var F=function(se,ce){var ue=ce.num_components(),fe=a.num_points(),ve=fe*ue,Te=ve*Float32Array.BYTES_PER_ELEMENT,Re=r._malloc(Te);try{d.GetAttributeDataArrayForAllPoints(a,ce,r.DT_FLOAT32,Te,Re);var Ae=new Float32Array(r.HEAPF32.buffer,Re,ve);if(se==="color"&&ue===3){for(var Ee=new Float32Array(4*fe),Se=0,Le=0;Se<Ee.length;Se+=4,Le+=ue)Ee[Se+0]=Ae[Le+0],Ee[Se+1]=Ae[Le+1],Ee[Se+2]=Ae[Le+2],Ee[Se+3]=1;i(se,Ee)}else(Ee=new Float32Array(ve)).set(new Float32Array(r.HEAPF32.buffer,Re,ve)),i(se,Ee)}finally{r._free(Re)}};if(e)for(var z in e){var J=e[z];F(z,d.GetAttributeByUniqueId(a,J))}else{var ie={position:"POSITION",normal:"NORMAL",color:"COLOR",uv:"TEX_COORD"};for(var z in ie)(J=d.GetAttributeId(a,r[ie[z]]))!==-1&&F(z,d.GetAttribute(a,J))}}finally{a&&r.destroy(a),r.destroy(d),r.destroy(o)}}function gm(){var r;onmessage=function(t){var e=t.data;switch(e.id){case"init":var n=e.decoder;n.url&&(importScripts(n.url),r=DracoDecoderModule({wasmBinary:n.wasmBinary})),postMessage("done");break;case"decodeMesh":if(!r)throw new Error("Draco decoder module is not available");r.then(function(i){Tc(i,e.dataView,e.attributes,function(o){postMessage({id:"indices",value:o},[o.buffer])},function(o,a){postMessage({id:o,value:a},[a.buffer])}),postMessage("done")})}}}function pd(r){return typeof document!="object"||typeof r!="string"?r:Xe.b.GetAbsoluteUrl(r)}var vm=function(){function r(t){t===void 0&&(t=r.DefaultNumWorkers);var e=r.Configuration.decoder,n=e.wasmUrl&&e.wasmBinaryUrl&&typeof WebAssembly=="object"?{url:e.wasmUrl,wasmBinaryPromise:Xe.b.LoadFileAsync(pd(e.wasmBinaryUrl))}:{url:e.fallbackUrl,wasmBinaryPromise:Promise.resolve(void 0)};t&&typeof Worker=="function"?this._workerPoolPromise=n.wasmBinaryPromise.then(function(i){for(var o=Tc+"("+gm+")()",a=URL.createObjectURL(new Blob([o],{type:"application/javascript"})),s=new Array(t),d=0;d<s.length;d++)s[d]=new Promise(function(p,b){var P=new Worker(a),O=function(F){P.removeEventListener("error",O),P.removeEventListener("message",B),b(F)},B=function(F){F.data==="done"&&(P.removeEventListener("error",O),P.removeEventListener("message",B),p(P))};P.addEventListener("error",O),P.addEventListener("message",B),P.postMessage({id:"init",decoder:{url:pd(n.url),wasmBinary:i}})});return Promise.all(s).then(function(p){return new Vs(p)})}):this._decoderModulePromise=n.wasmBinaryPromise.then(function(i){if(!n.url)throw new Error("Draco decoder module is not available");return Xe.b.LoadScriptAsync(n.url).then(function(){return o=i,new Promise(function(a){DracoDecoderModule({wasmBinary:o}).then(function(s){a({module:s})})});var o})})}return Object.defineProperty(r,"DecoderAvailable",{get:function(){var t=r.Configuration.decoder;return!!(t.wasmUrl&&t.wasmBinaryUrl&&typeof WebAssembly=="object"||t.fallbackUrl)},enumerable:!1,configurable:!0}),r.GetDefaultNumWorkers=function(){return typeof navigator=="object"&&navigator.hardwareConcurrency?Math.min(Math.floor(.5*navigator.hardwareConcurrency),4):1},Object.defineProperty(r,"Default",{get:function(){return r._Default||(r._Default=new r),r._Default},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this._workerPoolPromise&&this._workerPoolPromise.then(function(t){t.dispose()}),delete this._workerPoolPromise,delete this._decoderModulePromise},r.prototype.whenReadyAsync=function(){return this._workerPoolPromise?this._workerPoolPromise.then(function(){}):this._decoderModulePromise?this._decoderModulePromise.then(function(){}):Promise.resolve()},r.prototype.decodeMeshAsync=function(t,e){var n=t instanceof ArrayBuffer?new Uint8Array(t):t;if(this._workerPoolPromise)return this._workerPoolPromise.then(function(i){return new Promise(function(o,a){i.push(function(s,d){var p=new ft.a,b=function(B){s.removeEventListener("error",b),s.removeEventListener("message",P),a(B),d()},P=function(B){B.data==="done"?(s.removeEventListener("error",b),s.removeEventListener("message",P),o(p),d()):B.data.id==="indices"?p.indices=B.data.value:p.set(B.data.value,B.data.id)};s.addEventListener("error",b),s.addEventListener("message",P);var O=new Uint8Array(n.byteLength);O.set(new Uint8Array(n.buffer,n.byteOffset,n.byteLength)),s.postMessage({id:"decodeMesh",dataView:O,attributes:e},[O.buffer])})})});if(this._decoderModulePromise)return this._decoderModulePromise.then(function(i){var o=new ft.a;return Tc(i.module,n,e,function(a){o.indices=a},function(a,s){o.set(s,a)}),o});throw new Error("Draco decoder module is not available")},r.Configuration={decoder:{wasmUrl:"https://preview.babylonjs.com/draco_wasm_wrapper_gltf.js",wasmBinaryUrl:"https://preview.babylonjs.com/draco_decoder_gltf.wasm",fallbackUrl:"https://preview.babylonjs.com/draco_decoder_gltf.js"}},r.DefaultNumWorkers=r.GetDefaultNumWorkers(),r._Default=null,r}(),Eo=f(61),_d=0,bm=function(){function r(t,e,n,i){this.pos=t,this.normal=e,this.uv=n,this.vertColor=i}return r.prototype.clone=function(){var t,e;return new r(this.pos.clone(),this.normal.clone(),(t=this.uv)===null||t===void 0?void 0:t.clone(),(e=this.vertColor)===null||e===void 0?void 0:e.clone())},r.prototype.flip=function(){this.normal=this.normal.scale(-1)},r.prototype.interpolate=function(t,e){return new r(u.e.Lerp(this.pos,t.pos,e),u.e.Lerp(this.normal,t.normal,e),this.uv&&t.uv?u.d.Lerp(this.uv,t.uv,e):void 0,this.vertColor&&t.vertColor?M.b.Lerp(this.vertColor,t.vertColor,e):void 0)},r}(),ym=function(){function r(t,e){this.normal=t,this.w=e}return r.FromPoints=function(t,e,n){var i=n.subtract(t),o=e.subtract(t);if(i.lengthSquared()===0||o.lengthSquared()===0)return null;var a=u.e.Normalize(u.e.Cross(i,o));return new r(a,u.e.Dot(a,t))},r.prototype.clone=function(){return new r(this.normal.clone(),this.w)},r.prototype.flip=function(){this.normal.scaleInPlace(-1),this.w=-this.w},r.prototype.splitPolygon=function(t,e,n,i,o){var a,s,d=0,p=[];for(a=0;a<t.vertices.length;a++){var b=(s=u.e.Dot(this.normal,t.vertices[a].pos)-this.w)<-r.EPSILON?2:s>r.EPSILON?1:0;d|=b,p.push(b)}switch(d){case 0:(u.e.Dot(this.normal,t.plane.normal)>0?e:n).push(t);break;case 1:i.push(t);break;case 2:o.push(t);break;case 3:var P,O=[],B=[];for(a=0;a<t.vertices.length;a++){var F=(a+1)%t.vertices.length,z=p[a],J=p[F],ie=t.vertices[a],se=t.vertices[F];if(z!==2&&O.push(ie),z!==1&&B.push(z!==2?ie.clone():ie),(z|J)==3){s=(this.w-u.e.Dot(this.normal,ie.pos))/u.e.Dot(this.normal,se.pos.subtract(ie.pos));var ce=ie.interpolate(se,s);O.push(ce),B.push(ce.clone())}}O.length>=3&&(P=new Ec(O,t.shared)).plane&&i.push(P),B.length>=3&&(P=new Ec(B,t.shared)).plane&&o.push(P)}},r.EPSILON=1e-5,r}(),Ec=function(){function r(t,e){this.vertices=t,this.shared=e,this.plane=ym.FromPoints(t[0].pos,t[1].pos,t[2].pos)}return r.prototype.clone=function(){return new r(this.vertices.map(function(t){return t.clone()}),this.shared)},r.prototype.flip=function(){this.vertices.reverse().map(function(t){t.flip()}),this.plane.flip()},r}(),Jn=function(){function r(t){this.plane=null,this.front=null,this.back=null,this.polygons=new Array,t&&this.build(t)}return r.prototype.clone=function(){var t=new r;return t.plane=this.plane&&this.plane.clone(),t.front=this.front&&this.front.clone(),t.back=this.back&&this.back.clone(),t.polygons=this.polygons.map(function(e){return e.clone()}),t},r.prototype.invert=function(){for(var t=0;t<this.polygons.length;t++)this.polygons[t].flip();this.plane&&this.plane.flip(),this.front&&this.front.invert(),this.back&&this.back.invert();var e=this.front;this.front=this.back,this.back=e},r.prototype.clipPolygons=function(t){if(!this.plane)return t.slice();for(var e=new Array,n=new Array,i=0;i<t.length;i++)this.plane.splitPolygon(t[i],e,n,e,n);return this.front&&(e=this.front.clipPolygons(e)),n=this.back?this.back.clipPolygons(n):[],e.concat(n)},r.prototype.clipTo=function(t){this.polygons=t.clipPolygons(this.polygons),this.front&&this.front.clipTo(t),this.back&&this.back.clipTo(t)},r.prototype.allPolygons=function(){var t=this.polygons.slice();return this.front&&(t=t.concat(this.front.allPolygons())),this.back&&(t=t.concat(this.back.allPolygons())),t},r.prototype.build=function(t){if(t.length){this.plane||(this.plane=t[0].plane.clone());for(var e=new Array,n=new Array,i=0;i<t.length;i++)this.plane.splitPolygon(t[i],this.polygons,this.polygons,e,n);e.length&&(this.front||(this.front=new r),this.front.build(e)),n.length&&(this.back||(this.back=new r),this.back.build(n))}},r}(),Tm=function(){function r(){this.polygons=new Array}return r.FromMesh=function(t){var e,n,i,o,a,s,d,p,b,P=void 0,O=void 0,B=new Array,F=null;if(!(t instanceof De.a))throw"BABYLON.CSG: Wrong Mesh type, must be BABYLON.Mesh";t.computeWorldMatrix(!0),s=t.getWorldMatrix(),d=t.position.clone(),p=t.rotation.clone(),t.rotationQuaternion&&(F=t.rotationQuaternion.clone()),b=t.scaling.clone();for(var z=t.getIndices(),J=t.getVerticesData(Oe.b.PositionKind),ie=t.getVerticesData(Oe.b.NormalKind),se=t.getVerticesData(Oe.b.UVKind),ce=t.getVerticesData(Oe.b.ColorKind),ue=t.subMeshes,fe=0,ve=ue.length;fe<ve;fe++)for(var Te=ue[fe].indexStart,Re=ue[fe].indexCount+ue[fe].indexStart;Te<Re;Te+=3){a=[];for(var Ae=0;Ae<3;Ae++){var Ee=new u.e(ie[3*z[Te+Ae]],ie[3*z[Te+Ae]+1],ie[3*z[Te+Ae]+2]);se&&(P=new u.d(se[2*z[Te+Ae]],se[2*z[Te+Ae]+1])),ce&&(O=new M.b(ce[4*z[Te+Ae]],ce[4*z[Te+Ae]+1],ce[4*z[Te+Ae]+2],ce[4*z[Te+Ae]+3]));var Se=new u.e(J[3*z[Te+Ae]],J[3*z[Te+Ae]+1],J[3*z[Te+Ae]+2]);i=u.e.TransformCoordinates(Se,s),n=u.e.TransformNormal(Ee,s),e=new bm(i,n,P,O),a.push(e)}(o=new Ec(a,{subMeshId:fe,meshId:_d,materialIndex:ue[fe].materialIndex})).plane&&B.push(o)}var Le=r.FromPolygons(B);return Le.matrix=s,Le.position=d,Le.rotation=p,Le.scaling=b,Le.rotationQuaternion=F,_d++,Le},r.FromPolygons=function(t){var e=new r;return e.polygons=t,e},r.prototype.clone=function(){var t=new r;return t.polygons=this.polygons.map(function(e){return e.clone()}),t.copyTransformAttributes(this),t},r.prototype.union=function(t){var e=new Jn(this.clone().polygons),n=new Jn(t.clone().polygons);return e.clipTo(n),n.clipTo(e),n.invert(),n.clipTo(e),n.invert(),e.build(n.allPolygons()),r.FromPolygons(e.allPolygons()).copyTransformAttributes(this)},r.prototype.unionInPlace=function(t){var e=new Jn(this.polygons),n=new Jn(t.polygons);e.clipTo(n),n.clipTo(e),n.invert(),n.clipTo(e),n.invert(),e.build(n.allPolygons()),this.polygons=e.allPolygons()},r.prototype.subtract=function(t){var e=new Jn(this.clone().polygons),n=new Jn(t.clone().polygons);return e.invert(),e.clipTo(n),n.clipTo(e),n.invert(),n.clipTo(e),n.invert(),e.build(n.allPolygons()),e.invert(),r.FromPolygons(e.allPolygons()).copyTransformAttributes(this)},r.prototype.subtractInPlace=function(t){var e=new Jn(this.polygons),n=new Jn(t.polygons);e.invert(),e.clipTo(n),n.clipTo(e),n.invert(),n.clipTo(e),n.invert(),e.build(n.allPolygons()),e.invert(),this.polygons=e.allPolygons()},r.prototype.intersect=function(t){var e=new Jn(this.clone().polygons),n=new Jn(t.clone().polygons);return e.invert(),n.clipTo(e),n.invert(),e.clipTo(n),n.clipTo(e),e.build(n.allPolygons()),e.invert(),r.FromPolygons(e.allPolygons()).copyTransformAttributes(this)},r.prototype.intersectInPlace=function(t){var e=new Jn(this.polygons),n=new Jn(t.polygons);e.invert(),n.clipTo(e),n.invert(),e.clipTo(n),n.clipTo(e),e.build(n.allPolygons()),e.invert(),this.polygons=e.allPolygons()},r.prototype.inverse=function(){var t=this.clone();return t.inverseInPlace(),t},r.prototype.inverseInPlace=function(){this.polygons.map(function(t){t.flip()})},r.prototype.copyTransformAttributes=function(t){return this.matrix=t.matrix,this.position=t.position,this.rotation=t.rotation,this.scaling=t.scaling,this.rotationQuaternion=t.rotationQuaternion,this},r.prototype.buildMeshGeometry=function(t,e,n){var i=this.matrix.clone();i.invert();var o,a,s,d=new De.a(t,e),p=[],b=[],P=[],O=null,B=null,F=u.e.Zero(),z=u.e.Zero(),J=u.d.Zero(),ie=new M.b(0,0,0,0),se=this.polygons,ce=[0,0,0],ue={},fe=0,ve={};n&&se.sort(function(ut,Qe){return ut.shared.meshId===Qe.shared.meshId?ut.shared.subMeshId-Qe.shared.subMeshId:ut.shared.meshId-Qe.shared.meshId});for(var Te=0,Re=se.length;Te<Re;Te++){ve[(o=se[Te]).shared.meshId]||(ve[o.shared.meshId]={}),ve[o.shared.meshId][o.shared.subMeshId]||(ve[o.shared.meshId][o.shared.subMeshId]={indexStart:1/0,indexEnd:-1/0,materialIndex:o.shared.materialIndex}),s=ve[o.shared.meshId][o.shared.subMeshId];for(var Ae=2,Ee=o.vertices.length;Ae<Ee;Ae++){ce[0]=0,ce[1]=Ae-1,ce[2]=Ae;for(var Se=0;Se<3;Se++){F.copyFrom(o.vertices[ce[Se]].pos),z.copyFrom(o.vertices[ce[Se]].normal),o.vertices[ce[Se]].uv&&(O||(O=[]),J.copyFrom(o.vertices[ce[Se]].uv)),o.vertices[ce[Se]].vertColor&&(B||(B=[]),ie.copyFrom(o.vertices[ce[Se]].vertColor));var Le=u.e.TransformCoordinates(F,i),xe=u.e.TransformNormal(z,i);a=ue[Le.x+","+Le.y+","+Le.z];var Ne=!1;O&&O[2*a]!==J.x&&O[2*a+1]!==J.y&&(Ne=!0);var Ie=!1;B&&B[4*a]!==ie.r&&B[4*a+1]!==ie.g&&B[4*a+2]!==ie.b&&B[4*a+3]!==ie.a&&(Ie=!0),(a===void 0||P[3*a]!==xe.x||P[3*a+1]!==xe.y||P[3*a+2]!==xe.z||Ne||Ie)&&(p.push(Le.x,Le.y,Le.z),O&&O.push(J.x,J.y),P.push(z.x,z.y,z.z),B&&B.push(ie.r,ie.g,ie.b,ie.a),a=ue[Le.x+","+Le.y+","+Le.z]=p.length/3-1),b.push(a),s.indexStart=Math.min(fe,s.indexStart),s.indexEnd=Math.max(fe,s.indexEnd),fe++}}}if(d.setVerticesData(Oe.b.PositionKind,p),d.setVerticesData(Oe.b.NormalKind,P),O&&d.setVerticesData(Oe.b.UVKind,O),B&&d.setVerticesData(Oe.b.ColorKind,B),d.setIndices(b,null),n){var Fe,Ye=0;for(var tt in d.subMeshes=new Array,ve){for(var it in Fe=-1,ve[tt])s=ve[tt][it],Eo.a.CreateFromIndices(s.materialIndex+Ye,s.indexStart,s.indexEnd-s.indexStart+1,d),Fe=Math.max(s.materialIndex,Fe);Ye+=++Fe}}return d},r.prototype.toMesh=function(t,e,n,i){e===void 0&&(e=null);var o=this.buildMeshGeometry(t,n,i);return o.material=e,o.position.copyFrom(this.position),o.rotation.copyFrom(this.rotation),this.rotationQuaternion&&(o.rotationQuaternion=this.rotationQuaternion.clone()),o.scaling.copyFrom(this.scaling),o.computeWorldMatrix(!0),o},r}(),Em=function(r){function t(e,n,i,o,a,s){o===void 0&&(o=1),a===void 0&&(a=60),s===void 0&&(s=!0);var d=r.call(this,e,i)||this;d._sectionPolygonPointsCount=4,d._running=!1,d._autoStart=s,d._generator=n,d._diameter=o,d._length=a,d._sectionVectors=[],d._sectionNormalVectors=[];for(var p=0;p<d._sectionPolygonPointsCount;p++)d._sectionVectors[p]=u.e.Zero(),d._sectionNormalVectors[p]=u.e.Zero();return d._createMesh(),d}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"TrailMesh"},t.prototype._createMesh=function(){var e=new ft.a,n=[],i=[],o=[],a=u.e.Zero();a=this._generator instanceof Dt.a&&this._generator._boundingInfo?this._generator._boundingInfo.boundingBox.centerWorld:this._generator.position;for(var s=2*Math.PI/this._sectionPolygonPointsCount,d=0;d<this._sectionPolygonPointsCount;d++)n.push(a.x+Math.cos(d*s)*this._diameter,a.y+Math.sin(d*s)*this._diameter,a.z);for(d=1;d<=this._length;d++){for(var p=0;p<this._sectionPolygonPointsCount;p++)n.push(a.x+Math.cos(p*s)*this._diameter,a.y+Math.sin(p*s)*this._diameter,a.z);var b=n.length/3-2*this._sectionPolygonPointsCount;for(p=0;p<this._sectionPolygonPointsCount-1;p++)o.push(b+p,b+p+this._sectionPolygonPointsCount,b+p+this._sectionPolygonPointsCount+1),o.push(b+p,b+p+this._sectionPolygonPointsCount+1,b+p+1);o.push(b+this._sectionPolygonPointsCount-1,b+this._sectionPolygonPointsCount-1+this._sectionPolygonPointsCount,b+this._sectionPolygonPointsCount),o.push(b+this._sectionPolygonPointsCount-1,b+this._sectionPolygonPointsCount,b)}ft.a.ComputeNormals(n,o,i),e.positions=n,e.normals=i,e.indices=o,e.applyToMesh(this,!0),this._autoStart&&this.start()},t.prototype.start=function(){var e=this;this._running||(this._running=!0,this._beforeRenderObserver=this.getScene().onBeforeRenderObservable.add(function(){e.update()}))},t.prototype.stop=function(){this._beforeRenderObserver&&this._running&&(this._running=!1,this.getScene().onBeforeRenderObservable.remove(this._beforeRenderObserver))},t.prototype.update=function(){var e=this.getVerticesData(Oe.b.PositionKind),n=this.getVerticesData(Oe.b.NormalKind),i=this._generator.getWorldMatrix();if(e&&n){for(var o=3*this._sectionPolygonPointsCount;o<e.length;o++)e[o-3*this._sectionPolygonPointsCount]=e[o]-n[o]/this._length*this._diameter;for(o=3*this._sectionPolygonPointsCount;o<n.length;o++)n[o-3*this._sectionPolygonPointsCount]=n[o];var a=e.length-3*this._sectionPolygonPointsCount,s=2*Math.PI/this._sectionPolygonPointsCount;for(o=0;o<this._sectionPolygonPointsCount;o++)this._sectionVectors[o].copyFromFloats(Math.cos(o*s)*this._diameter,Math.sin(o*s)*this._diameter,0),this._sectionNormalVectors[o].copyFromFloats(Math.cos(o*s),Math.sin(o*s),0),u.e.TransformCoordinatesToRef(this._sectionVectors[o],i,this._sectionVectors[o]),u.e.TransformNormalToRef(this._sectionNormalVectors[o],i,this._sectionNormalVectors[o]);for(o=0;o<this._sectionPolygonPointsCount;o++)e[a+3*o]=this._sectionVectors[o].x,e[a+3*o+1]=this._sectionVectors[o].y,e[a+3*o+2]=this._sectionVectors[o].z,n[a+3*o]=this._sectionNormalVectors[o].x,n[a+3*o+1]=this._sectionNormalVectors[o].y,n[a+3*o+2]=this._sectionNormalVectors[o].z;this.updateVerticesData(Oe.b.PositionKind,e,!0,!1),this.updateVerticesData(Oe.b.NormalKind,n,!0,!1)}},t.prototype.clone=function(e,n){return e===void 0&&(e=""),new t(e,n===void 0?this._generator:n,this.getScene(),this._diameter,this._length,this._autoStart)},t.prototype.serialize=function(e){r.prototype.serialize.call(this,e)},t.Parse=function(e,n){return new t(e.name,e._generator,n,e._diameter,e._length,e._autoStart)},t}(De.a),Sm=f(151),So=f(98),Ao=f(82);ft.a.CreateDisc=function(r){var t=new Array,e=new Array,n=new Array,i=new Array,o=r.radius||.5,a=r.tessellation||64,s=r.arc&&(r.arc<=0||r.arc>1)?1:r.arc||1,d=r.sideOrientation===0?0:r.sideOrientation||ft.a.DEFAULTSIDE;t.push(0,0,0),i.push(.5,.5);for(var p=2*Math.PI*s,b=s===1?p/a:p/(a-1),P=0,O=0;O<a;O++){var B=Math.cos(P),F=Math.sin(P),z=(B+1)/2,J=(1-F)/2;t.push(o*B,o*F,0),i.push(z,J),P+=b}s===1&&(t.push(t[3],t[4],t[5]),i.push(i[2],i[3]));for(var ie=t.length/3,se=1;se<ie-1;se++)e.push(se+1,0,se);ft.a.ComputeNormals(t,e,n),ft.a._ComputeSides(d,t,e,n,i,r.frontUVs,r.backUVs);var ce=new ft.a;return ce.indices=e,ce.positions=t,ce.normals=n,ce.uvs=i,ce},De.a.CreateDisc=function(r,t,e,n,i,o){n===void 0&&(n=null);var a={radius:t,tessellation:e,sideOrientation:o,updatable:i};return Ta.CreateDisc(r,a,n)};var Ta=function(){function r(){}return r.CreateDisc=function(t,e,n){n===void 0&&(n=null);var i=new De.a(t,n);return e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation),i._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreateDisc(e).applyToMesh(i,e.updatable),i},r}();ft.a.CreateTiledBox=function(r){for(var t=r.faceUV||new Array(6),e=r.faceColors,n=r.pattern||De.a.NO_FLIP,i=r.width||r.size||1,o=r.height||r.size||1,a=r.depth||r.size||1,s=r.tileWidth||r.tileSize||1,d=r.tileHeight||r.tileSize||1,p=r.alignHorizontal||0,b=r.alignVertical||0,P=r.sideOrientation===0?0:r.sideOrientation||ft.a.DEFAULTSIDE,O=0;O<6;O++)t[O]===void 0&&(t[O]=new u.f(0,0,1,1)),e&&e[O]===void 0&&(e[O]=new M.b(1,1,1,1));var B=i/2,F=o/2,z=a/2,J=[];for(O=0;O<2;O++)J[O]=ft.a.CreateTiledPlane({pattern:n,tileWidth:s,tileHeight:d,width:i,height:o,alignVertical:b,alignHorizontal:p,sideOrientation:P});for(O=2;O<4;O++)J[O]=ft.a.CreateTiledPlane({pattern:n,tileWidth:s,tileHeight:d,width:a,height:o,alignVertical:b,alignHorizontal:p,sideOrientation:P});var ie=b;for(b===De.a.BOTTOM?ie=De.a.TOP:b===De.a.TOP&&(ie=De.a.BOTTOM),O=4;O<6;O++)J[O]=ft.a.CreateTiledPlane({pattern:n,tileWidth:s,tileHeight:d,width:i,height:a,alignVertical:ie,alignHorizontal:p,sideOrientation:P});var se=[],ce=[],ue=[],fe=[],ve=[],Te=[],Re=[],Ae=[],Ee=0,Se=0,Le=0;for(O=0;O<6;O++){Ee=J[O].positions.length,Te[O]=[],Re[O]=[];for(var xe=0;xe<Ee/3;xe++)Te[O].push(new u.e(J[O].positions[3*xe],J[O].positions[3*xe+1],J[O].positions[3*xe+2])),Re[O].push(new u.e(J[O].normals[3*xe],J[O].normals[3*xe+1],J[O].normals[3*xe+2]));Se=J[O].uvs.length,Ae[O]=[];for(var Ne=0;Ne<Se;Ne+=2)Ae[O][Ne]=t[O].x+(t[O].z-t[O].x)*J[O].uvs[Ne],Ae[O][Ne+1]=t[O].y+(t[O].w-t[O].y)*J[O].uvs[Ne+1];if(ue=ue.concat(Ae[O]),fe=fe.concat(J[O].indices.map(function(Ve){return Ve+Le})),Le+=Te[O].length,e)for(var Ie=0;Ie<4;Ie++)ve.push(e[O].r,e[O].g,e[O].b,e[O].a)}var Fe=new u.e(0,0,z),Ye=u.a.RotationY(Math.PI);se=Te[0].map(function(Ve){return u.e.TransformNormal(Ve,Ye).add(Fe)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[]),ce=Re[0].map(function(Ve){return u.e.TransformNormal(Ve,Ye)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[]),se=se.concat(Te[1].map(function(Ve){return Ve.subtract(Fe)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[])),ce=ce.concat(Re[1].map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[]));var tt=new u.e(B,0,0),it=u.a.RotationY(-Math.PI/2);se=se.concat(Te[2].map(function(Ve){return u.e.TransformNormal(Ve,it).add(tt)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[])),ce=ce.concat(Re[2].map(function(Ve){return u.e.TransformNormal(Ve,it)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[]));var ut=u.a.RotationY(Math.PI/2);se=se.concat(Te[3].map(function(Ve){return u.e.TransformNormal(Ve,ut).subtract(tt)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[])),ce=ce.concat(Re[3].map(function(Ve){return u.e.TransformNormal(Ve,ut)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[]));var Qe=new u.e(0,F,0),ot=u.a.RotationX(Math.PI/2);se=se.concat(Te[4].map(function(Ve){return u.e.TransformNormal(Ve,ot).add(Qe)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[])),ce=ce.concat(Re[4].map(function(Ve){return u.e.TransformNormal(Ve,ot)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[]));var rt=u.a.RotationX(-Math.PI/2);se=se.concat(Te[5].map(function(Ve){return u.e.TransformNormal(Ve,rt).subtract(Qe)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[])),ce=ce.concat(Re[5].map(function(Ve){return u.e.TransformNormal(Ve,rt)}).map(function(Ve){return[Ve.x,Ve.y,Ve.z]}).reduce(function(Ve,Je){return Ve.concat(Je)},[])),ft.a._ComputeSides(P,se,fe,ce,ue);var Ze=new ft.a;if(Ze.indices=fe,Ze.positions=se,Ze.normals=ce,Ze.uvs=ue,e){var dt=P===ft.a.DOUBLESIDE?ve.concat(ve):ve;Ze.colors=dt}return Ze};var md=function(){function r(){}return r.CreateTiledBox=function(t,e,n){n===void 0&&(n=null);var i=new De.a(t,n);return e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation),i._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreateTiledBox(e).applyToMesh(i,e.updatable),i},r}();ft.a.CreateTorusKnot=function(r){var t,e,n=new Array,i=new Array,o=new Array,a=new Array,s=r.radius||2,d=r.tube||.5,p=r.radialSegments||32,b=r.tubularSegments||32,P=r.p||2,O=r.q||3,B=r.sideOrientation===0?0:r.sideOrientation||ft.a.DEFAULTSIDE,F=function(Ne){var Ie=Math.cos(Ne),Fe=Math.sin(Ne),Ye=O/P*Ne,tt=Math.cos(Ye),it=s*(2+tt)*.5*Ie,ut=s*(2+tt)*Fe*.5,Qe=s*Math.sin(Ye)*.5;return new u.e(it,ut,Qe)};for(t=0;t<=p;t++){var z=t%p/p*2*P*Math.PI,J=F(z),ie=F(z+.01),se=ie.subtract(J),ce=ie.add(J),ue=u.e.Cross(se,ce);for(ce=u.e.Cross(ue,se),ue.normalize(),ce.normalize(),e=0;e<b;e++){var fe=e%b/b*2*Math.PI,ve=-d*Math.cos(fe),Te=d*Math.sin(fe);i.push(J.x+ve*ce.x+Te*ue.x),i.push(J.y+ve*ce.y+Te*ue.y),i.push(J.z+ve*ce.z+Te*ue.z),a.push(t/p),a.push(e/b)}}for(t=0;t<p;t++)for(e=0;e<b;e++){var Re=(e+1)%b,Ae=t*b+e,Ee=(t+1)*b+e,Se=(t+1)*b+Re,Le=t*b+Re;n.push(Le),n.push(Ee),n.push(Ae),n.push(Le),n.push(Se),n.push(Ee)}ft.a.ComputeNormals(i,n,o),ft.a._ComputeSides(B,i,n,o,a,r.frontUVs,r.backUVs);var xe=new ft.a;return xe.indices=n,xe.positions=i,xe.normals=o,xe.uvs=a,xe},De.a.CreateTorusKnot=function(r,t,e,n,i,o,a,s,d,p){var b={radius:t,tube:e,radialSegments:n,tubularSegments:i,p:o,q:a,sideOrientation:p,updatable:d};return Sc.CreateTorusKnot(r,b,s)};var Sc=function(){function r(){}return r.CreateTorusKnot=function(t,e,n){var i=new De.a(t,n);return e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation),i._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreateTorusKnot(e).applyToMesh(i,e.updatable),i},r}(),Am=function(r){function t(e,n){var i=r.call(this,e.x,e.y)||this;return i.index=n,i}return Object(c.d)(t,r),t}(u.d),Ac=function(){function r(){this.elements=new Array}return r.prototype.add=function(t){var e=this,n=new Array;return t.forEach(function(i){var o=new Am(i,e.elements.length);n.push(o),e.elements.push(o)}),n},r.prototype.computeBounds=function(){var t=new u.d(this.elements[0].x,this.elements[0].y),e=new u.d(this.elements[0].x,this.elements[0].y);return this.elements.forEach(function(n){n.x<t.x?t.x=n.x:n.x>e.x&&(e.x=n.x),n.y<t.y?t.y=n.y:n.y>e.y&&(e.y=n.y)}),{min:t,max:e,width:e.x-t.x,height:e.y-t.y}},r}(),Pm=function(){function r(){}return r.Rectangle=function(t,e,n,i){return[new u.d(t,e),new u.d(n,e),new u.d(n,i),new u.d(t,i)]},r.Circle=function(t,e,n,i){e===void 0&&(e=0),n===void 0&&(n=0),i===void 0&&(i=32);for(var o=new Array,a=0,s=2*Math.PI/i,d=0;d<i;d++)o.push(new u.d(e+Math.cos(a)*t,n+Math.sin(a)*t)),a-=s;return o},r.Parse=function(t){var e,n=t.split(/[^-+eE\.\d]+/).map(parseFloat).filter(function(o){return!isNaN(o)}),i=[];for(e=0;e<(2147483646&n.length);e+=2)i.push(new u.d(n[e],n[e+1]));return i},r.StartingAt=function(t,e){return qe.f.StartingAt(t,e)},r}(),gd=function(){function r(t,e,n,i){var o;i===void 0&&(i=earcut),this._points=new Ac,this._outlinepoints=new Ac,this._holes=new Array,this._epoints=new Array,this._eholes=new Array,this.bjsEarcut=i,this._name=t,this._scene=n||Ue.a.LastCreatedScene,o=e instanceof qe.f?e.getPoints():e,this._addToepoint(o),this._points.add(o),this._outlinepoints.add(o),this.bjsEarcut===void 0&&l.a.Warn("Earcut was not found, the polygon will not be built.")}return r.prototype._addToepoint=function(t){for(var e=0,n=t;e<n.length;e++){var i=n[e];this._epoints.push(i.x,i.y)}},r.prototype.addHole=function(t){this._points.add(t);var e=new Ac;return e.add(t),this._holes.push(e),this._eholes.push(this._epoints.length/2),this._addToepoint(t),this},r.prototype.build=function(t,e){t===void 0&&(t=!1),e===void 0&&(e=0);var n=new De.a(this._name,this._scene),i=this.buildVertexData(e);return n.setVerticesData(Oe.b.PositionKind,i.positions,t),n.setVerticesData(Oe.b.NormalKind,i.normals,t),n.setVerticesData(Oe.b.UVKind,i.uvs,t),n.setIndices(i.indices),n},r.prototype.buildVertexData=function(t){var e=this;t===void 0&&(t=0);var n=new ft.a,i=new Array,o=new Array,a=new Array,s=this._points.computeBounds();this._points.elements.forEach(function(J){i.push(0,1,0),o.push(J.x,0,J.y),a.push((J.x-s.min.x)/s.width,(J.y-s.min.y)/s.height)});for(var d=new Array,p=this.bjsEarcut(this._epoints,this._eholes,2),b=0;b<p.length;b++)d.push(p[b]);if(t>0){var P=o.length/3;this._points.elements.forEach(function(J){i.push(0,-1,0),o.push(J.x,-t,J.y),a.push(1-(J.x-s.min.x)/s.width,1-(J.y-s.min.y)/s.height)});var O=d.length;for(b=0;b<O;b+=3){var B=d[b+0],F=d[b+1],z=d[b+2];d.push(z+P),d.push(F+P),d.push(B+P)}this.addSide(o,i,a,d,s,this._outlinepoints,t,!1),this._holes.forEach(function(J){e.addSide(o,i,a,d,s,J,t,!0)})}return n.indices=d,n.positions=o,n.normals=i,n.uvs=a,n},r.prototype.addSide=function(t,e,n,i,o,a,s,d){for(var p=t.length/3,b=0,P=0;P<a.elements.length;P++){var O,B=a.elements[P];O=P+1>a.elements.length-1?a.elements[0]:a.elements[P+1],t.push(B.x,0,B.y),t.push(B.x,-s,B.y),t.push(O.x,0,O.y),t.push(O.x,-s,O.y);var F=new u.e(B.x,0,B.y),z=new u.e(O.x,0,O.y).subtract(F),J=new u.e(0,1,0),ie=u.e.Cross(z,J);ie=ie.normalize(),n.push(b/o.width,0),n.push(b/o.width,1),b+=z.length(),n.push(b/o.width,0),n.push(b/o.width,1),d?(e.push(ie.x,ie.y,ie.z),e.push(ie.x,ie.y,ie.z),e.push(ie.x,ie.y,ie.z),e.push(ie.x,ie.y,ie.z),i.push(p),i.push(p+2),i.push(p+1),i.push(p+1),i.push(p+2),i.push(p+3)):(e.push(-ie.x,-ie.y,-ie.z),e.push(-ie.x,-ie.y,-ie.z),e.push(-ie.x,-ie.y,-ie.z),e.push(-ie.x,-ie.y,-ie.z),i.push(p),i.push(p+1),i.push(p+2),i.push(p+1),i.push(p+3),i.push(p+2)),p+=4}},r}();ft.a.CreatePolygon=function(r,t,e,n,i,o,a){for(var s=e||new Array(3),d=n,p=[],b=a||!1,P=0;P<3;P++)s[P]===void 0&&(s[P]=new u.f(0,0,1,1)),d&&d[P]===void 0&&(d[P]=new M.b(1,1,1,1));var O=r.getVerticesData(Oe.b.PositionKind),B=r.getVerticesData(Oe.b.NormalKind),F=r.getVerticesData(Oe.b.UVKind),z=r.getIndices(),J=O.length/9,ie=0,se=0,ce=0,ue=0,fe=[0];if(b)for(var ve=J;ve<O.length/3;ve+=4)se=O[3*(ve+2)]-O[3*ve],ce=O[3*(ve+2)+2]-O[3*ve+2],ue+=Math.sqrt(se*se+ce*ce),fe.push(ue);ve=0;for(var Te=0,Re=0;Re<B.length;Re+=3)Math.abs(B[Re+1])<.001&&(Te=1),Math.abs(B[Re+1]-1)<.001&&(Te=0),Math.abs(B[Re+1]+1)<.001&&(Te=2),ve=Re/3,Te===1?(ie=ve-J,F[2*ve]=ie%4<1.5?b?s[Te].x+(s[Te].z-s[Te].x)*fe[Math.floor(ie/4)]/ue:s[Te].x:b?s[Te].x+(s[Te].z-s[Te].x)*fe[Math.floor(ie/4)+1]/ue:s[Te].z,F[2*ve+1]=ie%2==0?s[Te].w:s[Te].y):(F[2*ve]=(1-F[2*ve])*s[Te].x+F[2*ve]*s[Te].z,F[2*ve+1]=(1-F[2*ve+1])*s[Te].y+F[2*ve+1]*s[Te].w),d&&p.push(d[Te].r,d[Te].g,d[Te].b,d[Te].a);ft.a._ComputeSides(t,O,z,B,F,i,o);var Ae=new ft.a;if(Ae.indices=z,Ae.positions=O,Ae.normals=B,Ae.uvs=F,d){var Ee=t===ft.a.DOUBLESIDE?p.concat(p):p;Ae.colors=Ee}return Ae},De.a.CreatePolygon=function(r,t,e,n,i,o,a){a===void 0&&(a=earcut);var s={shape:t,holes:n,updatable:i,sideOrientation:o};return Po.CreatePolygon(r,s,e,a)},De.a.ExtrudePolygon=function(r,t,e,n,i,o,a,s){s===void 0&&(s=earcut);var d={shape:t,holes:i,depth:e,updatable:o,sideOrientation:a};return Po.ExtrudePolygon(r,d,n,s)};var Po=function(){function r(){}return r.CreatePolygon=function(t,e,n,i){n===void 0&&(n=null),i===void 0&&(i=earcut),e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation);for(var o=e.shape,a=e.holes||[],s=e.depth||0,d=[],p=[],b=0;b<o.length;b++)d[b]=new u.d(o[b].x,o[b].z);d[0].equalsWithEpsilon(d[d.length-1],1e-8)&&d.pop();for(var P=new gd(t,d,n||te.a.LastCreatedScene,i),O=0;O<a.length;O++){p=[];for(var B=0;B<a[O].length;B++)p.push(new u.d(a[O][B].x,a[O][B].z));P.addHole(p)}var F=P.build(e.updatable,s);return F._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreatePolygon(F,e.sideOrientation,e.faceUV,e.faceColors,e.frontUVs,e.backUVs,e.wrap).applyToMesh(F,e.updatable),F},r.ExtrudePolygon=function(t,e,n,i){return n===void 0&&(n=null),i===void 0&&(i=earcut),r.CreatePolygon(t,e,n,i)},r}();De.a.CreateLathe=function(r,t,e,n,i,o,a){var s={shape:t,radius:e,tessellation:n,sideOrientation:a,updatable:o};return Pc.CreateLathe(r,s,i)};var Pc=function(){function r(){}return r.CreateLathe=function(t,e,n){n===void 0&&(n=null);var i,o=e.arc?e.arc<=0||e.arc>1?1:e.arc:1,a=e.closed===void 0||e.closed,s=e.shape,d=e.radius||1,p=e.tessellation||64,b=e.clip||0,P=e.updatable,O=De.a._GetDefaultSideOrientation(e.sideOrientation),B=e.cap||De.a.NO_CAP,F=2*Math.PI,z=new Array,J=e.invertUV||!1,ie=0,se=0,ce=F/p*o,ue=new Array;for(ie=0;ie<=p-b;ie++){for(ue=[],B!=De.a.CAP_START&&B!=De.a.CAP_ALL||(ue.push(new u.e(0,s[0].y,0)),ue.push(new u.e(Math.cos(ie*ce)*s[0].x*d,s[0].y,Math.sin(ie*ce)*s[0].x*d))),se=0;se<s.length;se++)i=new u.e(Math.cos(ie*ce)*s[se].x*d,s[se].y,Math.sin(ie*ce)*s[se].x*d),ue.push(i);B!=De.a.CAP_END&&B!=De.a.CAP_ALL||(ue.push(new u.e(Math.cos(ie*ce)*s[s.length-1].x*d,s[s.length-1].y,Math.sin(ie*ce)*s[s.length-1].x*d)),ue.push(new u.e(0,s[s.length-1].y,0))),z.push(ue)}return Ao.a.CreateRibbon(t,{pathArray:z,closeArray:a,sideOrientation:O,updatable:P,invertUV:J,frontUVs:e.frontUVs,backUVs:e.backUVs},n)},r}();ft.a.CreateTiledPlane=function(r){var t=r.pattern||De.a.NO_FLIP,e=r.tileWidth||r.tileSize||1,n=r.tileHeight||r.tileSize||1,i=r.alignHorizontal||0,o=r.alignVertical||0,a=r.width||r.size||1,s=Math.floor(a/e),d=a-s*e,p=r.height||r.size||1,b=Math.floor(p/n),P=p-b*n,O=e*s/2,B=n*b/2,F=0,z=0,J=0,ie=0,se=0,ce=0;if(d>0||P>0){switch(J=-O,ie=-B,se=O,ce=B,i){case De.a.CENTER:J-=d/=2,se+=d;break;case De.a.LEFT:se+=d,F=-d/2;break;case De.a.RIGHT:J-=d,F=d/2}switch(o){case De.a.CENTER:ie-=P/=2,ce+=P;break;case De.a.BOTTOM:ce+=P,z=-P/2;break;case De.a.TOP:ie-=P,z=P/2}}var ue=[],fe=[],ve=[];ve[0]=[0,0,1,0,1,1,0,1],ve[1]=[0,0,1,0,1,1,0,1],t!==De.a.ROTATE_TILE&&t!==De.a.ROTATE_ROW||(ve[1]=[1,1,0,1,0,0,1,0]),t!==De.a.FLIP_TILE&&t!==De.a.FLIP_ROW||(ve[1]=[1,0,0,0,0,1,1,1]),t!==De.a.FLIP_N_ROTATE_TILE&&t!==De.a.FLIP_N_ROTATE_ROW||(ve[1]=[0,1,1,1,1,0,0,0]);for(var Te=[],Re=[],Ae=[],Ee=0,Se=0;Se<b;Se++)for(var Le=0;Le<s;Le++)ue.push(Le*e-O+F,Se*n-B+z,0),ue.push((Le+1)*e-O+F,Se*n-B+z,0),ue.push((Le+1)*e-O+F,(Se+1)*n-B+z,0),ue.push(Le*e-O+F,(Se+1)*n-B+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Te=t===De.a.FLIP_TILE||t===De.a.ROTATE_TILE||t===De.a.FLIP_N_ROTATE_TILE?Te.concat(ve[(Le%2+Se%2)%2]):t===De.a.FLIP_ROW||t===De.a.ROTATE_ROW||t===De.a.FLIP_N_ROTATE_ROW?Te.concat(ve[Se%2]):Te.concat(ve[0]),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1),Ee+=4;if(d>0||P>0){var xe,Ne,Ie,Fe,Ye=P>0&&(o===De.a.CENTER||o===De.a.TOP),tt=P>0&&(o===De.a.CENTER||o===De.a.BOTTOM),it=d>0&&(i===De.a.CENTER||i===De.a.RIGHT),ut=d>0&&(i===De.a.CENTER||i===De.a.LEFT),Qe=[];if(Ye&&it&&(ue.push(J+F,ie+z,0),ue.push(-O+F,ie+z,0),ue.push(-O+F,ie+P+z,0),ue.push(J+F,ie+P+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Qe=[xe=1-d/e,Ne=1-P/n,Ie=1,Ne,Ie,Fe=1,xe,Fe],t===De.a.ROTATE_ROW&&(Qe=[1-xe,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-xe,1-Fe]),t===De.a.FLIP_ROW&&(Qe=[1-xe,Ne,1-Ie,Ne,1-Ie,Fe,1-xe,Fe]),t===De.a.FLIP_N_ROTATE_ROW&&(Qe=[xe,1-Ne,Ie,1-Ne,Ie,1-Fe,xe,1-Fe]),Te=Te.concat(Qe),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)),Ye&&ut&&(ue.push(O+F,ie+z,0),ue.push(se+F,ie+z,0),ue.push(se+F,ie+P+z,0),ue.push(O+F,ie+P+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Qe=[xe=0,Ne=1-P/n,Ie=d/e,Ne,Ie,Fe=1,xe,Fe],(t===De.a.ROTATE_ROW||t===De.a.ROTATE_TILE&&s%2==0)&&(Qe=[1-xe,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-xe,1-Fe]),(t===De.a.FLIP_ROW||t===De.a.FLIP_TILE&&s%2==0)&&(Qe=[1-xe,Ne,1-Ie,Ne,1-Ie,Fe,1-xe,Fe]),(t===De.a.FLIP_N_ROTATE_ROW||t===De.a.FLIP_N_ROTATE_TILE&&s%2==0)&&(Qe=[xe,1-Ne,Ie,1-Ne,Ie,1-Fe,xe,1-Fe]),Te=Te.concat(Qe),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)),tt&&it&&(ue.push(J+F,B+z,0),ue.push(-O+F,B+z,0),ue.push(-O+F,ce+z,0),ue.push(J+F,ce+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Qe=[xe=1-d/e,Ne=0,Ie=1,Ne,Ie,Fe=P/n,xe,Fe],(t===De.a.ROTATE_ROW&&b%2==1||t===De.a.ROTATE_TILE&&b%1==0)&&(Qe=[1-xe,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-xe,1-Fe]),(t===De.a.FLIP_ROW&&b%2==1||t===De.a.FLIP_TILE&&b%2==0)&&(Qe=[1-xe,Ne,1-Ie,Ne,1-Ie,Fe,1-xe,Fe]),(t===De.a.FLIP_N_ROTATE_ROW&&b%2==1||t===De.a.FLIP_N_ROTATE_TILE&&b%2==0)&&(Qe=[xe,1-Ne,Ie,1-Ne,Ie,1-Fe,xe,1-Fe]),Te=Te.concat(Qe),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)),tt&&ut&&(ue.push(O+F,B+z,0),ue.push(se+F,B+z,0),ue.push(se+F,ce+z,0),ue.push(O+F,ce+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Qe=[xe=0,Ne=0,Ie=d/e,Ne,Ie,Fe=P/n,xe,Fe],(t===De.a.ROTATE_ROW&&b%2==1||t===De.a.ROTATE_TILE&&(b+s)%2==1)&&(Qe=[1-xe,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-xe,1-Fe]),(t===De.a.FLIP_ROW&&b%2==1||t===De.a.FLIP_TILE&&(b+s)%2==1)&&(Qe=[1-xe,Ne,1-Ie,Ne,1-Ie,Fe,1-xe,Fe]),(t===De.a.FLIP_N_ROTATE_ROW&&b%2==1||t===De.a.FLIP_N_ROTATE_TILE&&(b+s)%2==1)&&(Qe=[xe,1-Ne,Ie,1-Ne,Ie,1-Fe,xe,1-Fe]),Te=Te.concat(Qe),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)),Ye){var ot=[];for(xe=0,Ne=1-P/n,Ie=1,Fe=1,ot[0]=[xe,Ne,Ie,Ne,Ie,Fe,xe,Fe],ot[1]=[xe,Ne,Ie,Ne,Ie,Fe,xe,Fe],t!==De.a.ROTATE_TILE&&t!==De.a.ROTATE_ROW||(ot[1]=[1-xe,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-xe,1-Fe]),t!==De.a.FLIP_TILE&&t!==De.a.FLIP_ROW||(ot[1]=[1-xe,Ne,1-Ie,Ne,1-Ie,Fe,1-xe,Fe]),t!==De.a.FLIP_N_ROTATE_TILE&&t!==De.a.FLIP_N_ROTATE_ROW||(ot[1]=[xe,1-Ne,Ie,1-Ne,Ie,1-Fe,xe,1-Fe]),Le=0;Le<s;Le++)ue.push(Le*e-O+F,ie+z,0),ue.push((Le+1)*e-O+F,ie+z,0),ue.push((Le+1)*e-O+F,ie+P+z,0),ue.push(Le*e-O+F,ie+P+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Te=t===De.a.FLIP_TILE||t===De.a.ROTATE_TILE||t===De.a.FLIP_N_ROTATE_TILE?Te.concat(ot[(Le+1)%2]):t===De.a.FLIP_ROW||t===De.a.ROTATE_ROW||t===De.a.FLIP_N_ROTATE_ROW?Te.concat(ot[1]):Te.concat(ot[0]),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)}if(tt){var rt=[];for(xe=0,Ne=0,Ie=1,Fe=P/n,rt[0]=[xe,Ne,Ie,Ne,Ie,Fe,xe,Fe],rt[1]=[xe,Ne,Ie,Ne,Ie,Fe,xe,Fe],t!==De.a.ROTATE_TILE&&t!==De.a.ROTATE_ROW||(rt[1]=[1-xe,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-xe,1-Fe]),t!==De.a.FLIP_TILE&&t!==De.a.FLIP_ROW||(rt[1]=[1-xe,Ne,1-Ie,Ne,1-Ie,Fe,1-xe,Fe]),t!==De.a.FLIP_N_ROTATE_TILE&&t!==De.a.FLIP_N_ROTATE_ROW||(rt[1]=[xe,1-Ne,Ie,1-Ne,Ie,1-Fe,xe,1-Fe]),Le=0;Le<s;Le++)ue.push(Le*e-O+F,ce-P+z,0),ue.push((Le+1)*e-O+F,ce-P+z,0),ue.push((Le+1)*e-O+F,ce+z,0),ue.push(Le*e-O+F,ce+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Te=t===De.a.FLIP_TILE||t===De.a.ROTATE_TILE||t===De.a.FLIP_N_ROTATE_TILE?Te.concat(rt[(Le+b)%2]):t===De.a.FLIP_ROW||t===De.a.ROTATE_ROW||t===De.a.FLIP_N_ROTATE_ROW?Te.concat(rt[b%2]):Te.concat(rt[0]),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)}if(it){var Ze=[];for(xe=1-d/e,Ne=0,Ie=1,Fe=1,Ze[0]=[xe,Ne,Ie,Ne,Ie,Fe,xe,Fe],Ze[1]=[xe,Ne,Ie,Ne,Ie,Fe,xe,Fe],t!==De.a.ROTATE_TILE&&t!==De.a.ROTATE_ROW||(Ze[1]=[1-xe,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-xe,1-Fe]),t!==De.a.FLIP_TILE&&t!==De.a.FLIP_ROW||(Ze[1]=[1-xe,Ne,1-Ie,Ne,1-Ie,Fe,1-xe,Fe]),t!==De.a.FLIP_N_ROTATE_TILE&&t!==De.a.FLIP_N_ROTATE_ROW||(Ze[1]=[xe,1-Ne,Ie,1-Ne,Ie,1-Fe,xe,1-Fe]),Se=0;Se<b;Se++)ue.push(J+F,Se*n-B+z,0),ue.push(J+d+F,Se*n-B+z,0),ue.push(J+d+F,(Se+1)*n-B+z,0),ue.push(J+F,(Se+1)*n-B+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Te=t===De.a.FLIP_TILE||t===De.a.ROTATE_TILE||t===De.a.FLIP_N_ROTATE_TILE?Te.concat(Ze[(Se+1)%2]):t===De.a.FLIP_ROW||t===De.a.ROTATE_ROW||t===De.a.FLIP_N_ROTATE_ROW?Te.concat(Ze[Se%2]):Te.concat(Ze[0]),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)}if(ut){var dt=[];for(xe=0,Ne=0,Ie=d/n,Fe=1,dt[0]=[xe,Ne,Ie,Ne,Ie,Fe,xe,Fe],dt[1]=[xe,Ne,Ie,Ne,Ie,Fe,xe,Fe],t!==De.a.ROTATE_TILE&&t!==De.a.ROTATE_ROW||(dt[1]=[1-xe,1-Ne,1-Ie,1-Ne,1-Ie,1-Fe,1-xe,1-Fe]),t!==De.a.FLIP_TILE&&t!==De.a.FLIP_ROW||(dt[1]=[1-xe,Ne,1-Ie,Ne,1-Ie,Fe,1-xe,Fe]),t!==De.a.FLIP_N_ROTATE_TILE&&t!==De.a.FLIP_N_ROTATE_ROW||(dt[1]=[xe,1-Ne,Ie,1-Ne,Ie,1-Fe,xe,1-Fe]),Se=0;Se<b;Se++)ue.push(se-d+F,Se*n-B+z,0),ue.push(se+F,Se*n-B+z,0),ue.push(se+F,(Se+1)*n-B+z,0),ue.push(se-d+F,(Se+1)*n-B+z,0),Ae.push(Ee,Ee+1,Ee+3,Ee+1,Ee+2,Ee+3),Ee+=4,Te=t===De.a.FLIP_TILE||t===De.a.ROTATE_TILE||t===De.a.FLIP_N_ROTATE_TILE?Te.concat(dt[(Se+s)%2]):t===De.a.FLIP_ROW||t===De.a.ROTATE_ROW||t===De.a.FLIP_N_ROTATE_ROW?Te.concat(dt[Se%2]):Te.concat(dt[0]),Re.push(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),fe.push(0,0,-1,0,0,-1,0,0,-1,0,0,-1)}}var Ve=r.sideOrientation===0?0:r.sideOrientation||ft.a.DEFAULTSIDE;ft.a._ComputeSides(Ve,ue,Ae,fe,Te,r.frontUVs,r.backUVs);var Je=new ft.a;Je.indices=Ae,Je.positions=ue,Je.normals=fe,Je.uvs=Te;var yt=Ve===ft.a.DOUBLESIDE?Re.concat(Re):Re;return Je.colors=yt,Je};var vd=function(){function r(){}return r.CreateTiledPlane=function(t,e,n){n===void 0&&(n=null);var i=new De.a(t,n);return e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation),i._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreateTiledPlane(e).applyToMesh(i,e.updatable),i},r}();De.a.CreateTube=function(r,t,e,n,i,o,a,s,d,p){var b={path:t,radius:e,tessellation:n,radiusFunction:i,arc:1,cap:o,updatable:s,sideOrientation:d,instance:p};return xc.CreateTube(r,b,a)};var xc=function(){function r(){}return r.CreateTube=function(t,e,n){n===void 0&&(n=null);var i=e.path,o=e.instance,a=1;e.radius!==void 0?a=e.radius:o&&(a=o._creationDataStorage.radius);var s=e.tessellation||64,d=e.radiusFunction||null,p=e.cap||De.a.NO_CAP,b=e.invertUV||!1,P=e.updatable,O=De.a._GetDefaultSideOrientation(e.sideOrientation);e.arc=e.arc&&(e.arc<=0||e.arc>1)?1:e.arc||1;var B,F,z=function(ce,ue,fe,ve,Te,Re,Ae,Ee){for(var Se,Le,xe,Ne,Ie=ue.getTangents(),Fe=ue.getNormals(),Ye=ue.getDistances(),tt=2*Math.PI/Te*Ee,it=Re||function(){return ve},ut=u.c.Matrix[0],Qe=Ae===De.a.NO_CAP||Ae===De.a.CAP_END?0:2,ot=0;ot<ce.length;ot++){Le=it(ot,Ye[ot]),Se=Array(),xe=Fe[ot];for(var rt=0;rt<Te;rt++)u.a.RotationAxisToRef(Ie[ot],tt*rt,ut),Ne=Se[rt]?Se[rt]:u.e.Zero(),u.e.TransformCoordinatesToRef(xe,ut,Ne),Ne.scaleInPlace(Le).addInPlace(ce[ot]),Se[rt]=Ne;fe[Qe]=Se,Qe++}var Ze=function(dt,Ve){for(var Je=Array(),yt=0;yt<dt;yt++)Je.push(ce[Ve]);return Je};switch(Ae){case De.a.NO_CAP:break;case De.a.CAP_START:fe[0]=Ze(Te,0),fe[1]=fe[2].slice(0);break;case De.a.CAP_END:fe[Qe]=fe[Qe-1].slice(0),fe[Qe+1]=Ze(Te,ce.length-1);break;case De.a.CAP_ALL:fe[0]=Ze(Te,0),fe[1]=fe[2].slice(0),fe[Qe]=fe[Qe-1].slice(0),fe[Qe+1]=Ze(Te,ce.length-1)}return fe};if(o){var J=o._creationDataStorage,ie=e.arc||J.arc;return F=z(i,B=J.path3D.update(i),J.pathArray,a,J.tessellation,d,J.cap,ie),o=Ao.a.CreateRibbon("",{pathArray:F,instance:o}),J.path3D=B,J.pathArray=F,J.arc=ie,J.radius=a,o}F=z(i,B=new qe.g(i),new Array,a,s,d,p=p<0||p>3?0:p,e.arc);var se=Ao.a.CreateRibbon(t,{pathArray:F,closePath:!0,closeArray:!1,updatable:P,sideOrientation:O,invertUV:b,frontUVs:e.frontUVs,backUVs:e.backUVs},n);return se._creationDataStorage.pathArray=F,se._creationDataStorage.path3D=B,se._creationDataStorage.tessellation=s,se._creationDataStorage.cap=p,se._creationDataStorage.arc=e.arc,se._creationDataStorage.radius=a,se},r}();ft.a.CreateIcoSphere=function(r){var t,e=r.sideOrientation||ft.a.DEFAULTSIDE,n=r.radius||1,i=r.flat===void 0||r.flat,o=r.subdivisions||4,a=r.radiusX||n,s=r.radiusY||n,d=r.radiusZ||n,p=(1+Math.sqrt(5))/2,b=[-1,p,-0,1,p,0,-1,-p,0,1,-p,0,0,-1,-p,0,1,-p,0,-1,p,0,1,p,p,0,1,p,0,-1,-p,0,1,-p,0,-1],P=[0,11,5,0,5,1,0,1,7,0,7,10,12,22,23,1,5,20,5,11,4,23,22,13,22,18,6,7,1,8,14,21,4,14,4,2,16,13,6,15,6,19,3,8,9,4,21,5,13,17,23,6,13,22,19,6,18,9,8,1],O=[0,1,2,3,4,5,6,7,8,9,10,11,0,2,3,3,3,4,7,8,9,9,10,11],B=[5,1,3,1,6,4,0,0,5,3,4,2,2,2,4,0,2,0,1,1,6,0,6,2,0,4,3,3,4,4,3,1,4,2,4,4,0,2,1,1,2,2,3,3,1,3,2,4],F=[0,0,0,0,1,0,0,1,1,0,0,0,1,1,0,0,1,1,1,0],z=new Array,J=new Array,ie=new Array,se=new Array,ce=0,ue=new Array(3),fe=new Array(3);for(t=0;t<3;t++)ue[t]=u.e.Zero(),fe[t]=u.d.Zero();for(var ve=0;ve<20;ve++){for(t=0;t<3;t++){var Te=P[3*ve+t];ue[t].copyFromFloats(b[3*O[Te]],b[3*O[Te]+1],b[3*O[Te]+2]),ue[t].normalize().scaleInPlace(n),fe[t].copyFromFloats(B[2*Te]*(138/1024)+60/1024+F[ve]*(-40/1024),B[2*Te+1]*(239/1024)+26/1024+F[ve]*(20/1024))}for(var Re=function(Le,xe,Ne,Ie){var Fe,Ye=u.e.Lerp(ue[0],ue[2],xe/o),tt=u.e.Lerp(ue[1],ue[2],xe/o),it=o===xe?ue[2]:u.e.Lerp(Ye,tt,Le/(o-xe));if(it.normalize(),i){var ut=u.e.Lerp(ue[0],ue[2],Ie/o),Qe=u.e.Lerp(ue[1],ue[2],Ie/o);Fe=u.e.Lerp(ut,Qe,Ne/(o-Ie))}else Fe=new u.e(it.x,it.y,it.z);Fe.x/=a,Fe.y/=s,Fe.z/=d,Fe.normalize();var ot=u.d.Lerp(fe[0],fe[2],xe/o),rt=u.d.Lerp(fe[1],fe[2],xe/o),Ze=o===xe?fe[2]:u.d.Lerp(ot,rt,Le/(o-xe));J.push(it.x*a,it.y*s,it.z*d),ie.push(Fe.x,Fe.y,Fe.z),se.push(Ze.x,Ze.y),z.push(ce),ce++},Ae=0;Ae<o;Ae++)for(var Ee=0;Ee+Ae<o;Ee++)Re(Ee,Ae,Ee+1/3,Ae+1/3),Re(Ee+1,Ae,Ee+1/3,Ae+1/3),Re(Ee,Ae+1,Ee+1/3,Ae+1/3),Ee+Ae+1<o&&(Re(Ee+1,Ae,Ee+2/3,Ae+2/3),Re(Ee+1,Ae+1,Ee+2/3,Ae+2/3),Re(Ee,Ae+1,Ee+2/3,Ae+2/3))}ft.a._ComputeSides(e,J,z,ie,se,r.frontUVs,r.backUVs);var Se=new ft.a;return Se.indices=z,Se.positions=J,Se.normals=ie,Se.uvs=se,Se},De.a.CreateIcoSphere=function(r,t,e){return Cc.CreateIcoSphere(r,t,e)};var Cc=function(){function r(){}return r.CreateIcoSphere=function(t,e,n){n===void 0&&(n=null);var i=new De.a(t,n);return e.sideOrientation=De.a._GetDefaultSideOrientation(e.sideOrientation),i._originalBuilderSideOrientation=e.sideOrientation,ft.a.CreateIcoSphere(e).applyToMesh(i,e.updatable),i},r}();De.a.CreateDecal=function(r,t,e,n,i,o){var a={position:e,normal:n,size:i,angle:o};return Rc.CreateDecal(r,t,a)};var Rc=function(){function r(){}return r.CreateDecal=function(t,e,n){var i=e.getIndices(),o=e.getVerticesData(Oe.b.PositionKind),a=e.getVerticesData(Oe.b.NormalKind),s=n.position||u.e.Zero(),d=n.normal||u.e.Up(),p=n.size||u.e.One(),b=n.angle||0;if(!d){var P=new u.e(0,0,1),O=e.getScene().activeCamera,B=u.e.TransformCoordinates(P,O.getWorldMatrix());d=O.globalPosition.subtract(B)}var F=-Math.atan2(d.z,d.x)-Math.PI/2,z=Math.sqrt(d.x*d.x+d.z*d.z),J=Math.atan2(d.y,z),ie=u.a.RotationYawPitchRoll(F,J,b).multiply(u.a.Translation(s.x,s.y,s.z)),se=u.a.Invert(ie),ce=e.getWorldMatrix().multiply(se),ue=new ft.a;ue.indices=[],ue.positions=[],ue.normals=[],ue.uvs=[];for(var fe=0,ve=function(xe){var Ne=new Ls;if(!i||!o||!a)return Ne;var Ie=i[xe];return Ne.position=new u.e(o[3*Ie],o[3*Ie+1],o[3*Ie+2]),Ne.position=u.e.TransformCoordinates(Ne.position,ce),Ne.normal=new u.e(a[3*Ie],a[3*Ie+1],a[3*Ie+2]),Ne.normal=u.e.TransformNormal(Ne.normal,ce),Ne},Te=function(xe,Ne){if(xe.length===0)return xe;for(var Ie=.5*Math.abs(u.e.Dot(p,Ne)),Fe=function(Ve,Je){var yt=u.e.GetClipFactor(Ve.position,Je.position,Ne,Ie);return new Ls(u.e.Lerp(Ve.position,Je.position,yt),u.e.Lerp(Ve.normal,Je.normal,yt))},Ye=new Array,tt=0;tt<xe.length;tt+=3){var it,ut,Qe,ot=null,rt=null,Ze=null,dt=null;switch(((it=u.e.Dot(xe[tt].position,Ne)-Ie>0)?1:0)+((ut=u.e.Dot(xe[tt+1].position,Ne)-Ie>0)?1:0)+((Qe=u.e.Dot(xe[tt+2].position,Ne)-Ie>0)?1:0)){case 0:Ye.push(xe[tt]),Ye.push(xe[tt+1]),Ye.push(xe[tt+2]);break;case 1:if(it&&(ot=xe[tt+1],rt=xe[tt+2],Ze=Fe(xe[tt],ot),dt=Fe(xe[tt],rt)),ut){ot=xe[tt],rt=xe[tt+2],Ze=Fe(xe[tt+1],ot),dt=Fe(xe[tt+1],rt),Ye.push(Ze),Ye.push(rt.clone()),Ye.push(ot.clone()),Ye.push(rt.clone()),Ye.push(Ze.clone()),Ye.push(dt);break}Qe&&(ot=xe[tt],rt=xe[tt+1],Ze=Fe(xe[tt+2],ot),dt=Fe(xe[tt+2],rt)),ot&&rt&&Ze&&dt&&(Ye.push(ot.clone()),Ye.push(rt.clone()),Ye.push(Ze),Ye.push(dt),Ye.push(Ze.clone()),Ye.push(rt.clone()));break;case 2:it||(rt=Fe(ot=xe[tt].clone(),xe[tt+1]),Ze=Fe(ot,xe[tt+2]),Ye.push(ot),Ye.push(rt),Ye.push(Ze)),ut||(rt=Fe(ot=xe[tt+1].clone(),xe[tt+2]),Ze=Fe(ot,xe[tt]),Ye.push(ot),Ye.push(rt),Ye.push(Ze)),Qe||(rt=Fe(ot=xe[tt+2].clone(),xe[tt]),Ze=Fe(ot,xe[tt+1]),Ye.push(ot),Ye.push(rt),Ye.push(Ze))}}return Ye},Re=0;Re<i.length;Re+=3){var Ae=new Array;if(Ae.push(ve(Re)),Ae.push(ve(Re+1)),Ae.push(ve(Re+2)),Ae=Te(Ae,new u.e(1,0,0)),Ae=Te(Ae,new u.e(-1,0,0)),Ae=Te(Ae,new u.e(0,1,0)),Ae=Te(Ae,new u.e(0,-1,0)),Ae=Te(Ae,new u.e(0,0,1)),(Ae=Te(Ae,new u.e(0,0,-1))).length!==0)for(var Ee=0;Ee<Ae.length;Ee++){var Se=Ae[Ee];ue.indices.push(fe),Se.position.toArray(ue.positions,3*fe),Se.normal.toArray(ue.normals,3*fe),ue.uvs.push(.5+Se.position.x/p.x),ue.uvs.push(.5+Se.position.y/p.y),fe++}}var Le=new De.a(t,e.getScene());return ue.applyToMesh(Le),Le.position=s.clone(),Le.rotation=new u.e(J,F,b),Le},r}();ft.a.CreateCapsule=function(r){r===void 0&&(r={subdivisions:2,tessellation:16,height:1,radius:.25,capSubdivisions:6});var t,e,n=Math.max(r.subdivisions?r.subdivisions:2,1),i=Math.max(r.tessellation?r.tessellation:16,3),o=Math.max(r.height?r.height:1,0),a=Math.max(r.radius?r.radius:.25,0),s=Math.max(r.capSubdivisions?r.capSubdivisions:6,1),d=i,p=n,b=Math.max(r.radiusTop?r.radiusTop:a,0),P=Math.max(r.radiusBottom?r.radiusBottom:a,0),O=o-(b+P),B=2*Math.PI,F=Math.max(r.topCapSubdivisions?r.topCapSubdivisions:s,1),z=Math.max(r.bottomCapSubdivisions?r.bottomCapSubdivisions:s,1),J=Math.acos((P-b)/o),ie=[],se=[],ce=[],ue=[],fe=0,ve=[],Te=.5*O,Re=.5*Math.PI,Ae=u.e.Zero(),Ee=u.e.Zero(),Se=Math.cos(J),Le=Math.sin(J),xe=new u.d(b*Le,Te+b*Se).subtract(new u.d(P*Le,P*Se-Te)).length(),Ne=b*J+xe+P*(Re-J),Ie=0;for(e=0;e<=F;e++){var Fe=[],Ye=Re-J*(e/F);Ie+=b*J/F;var tt=Math.cos(Ye),it=Math.sin(Ye),ut=tt*b;for(t=0;t<=d;t++){var Qe=(Ve=t/d)*B+0,ot=Math.sin(Qe),rt=Math.cos(Qe);Ee.x=ut*ot,Ee.y=Te+it*b,Ee.z=ut*rt,se.push(Ee.x,Ee.y,Ee.z),Ae.set(tt*ot,it,tt*rt),ce.push(Ae.x,Ae.y,Ae.z),ue.push(Ve,1-Ie/Ne),Fe.push(fe),fe++}ve.push(Fe)}var Ze=o-b-P+Se*b-Se*P,dt=Le*(P-b)/Ze;for(e=1;e<=p;e++){for(Fe=[],Ie+=xe/p,ut=Le*(e*(P-b)/p+b),t=0;t<=d;t++)Qe=(Ve=t/d)*B+0,ot=Math.sin(Qe),rt=Math.cos(Qe),Ee.x=ut*ot,Ee.y=Te+Se*b-e*Ze/p,Ee.z=ut*rt,se.push(Ee.x,Ee.y,Ee.z),Ae.set(ot,dt,rt).normalize(),ce.push(Ae.x,Ae.y,Ae.z),ue.push(Ve,1-Ie/Ne),Fe.push(fe),fe++;ve.push(Fe)}for(e=1;e<=z;e++){for(Fe=[],Ye=Re-J-(Math.PI-J)*(e/z),Ie+=P*J/z,tt=Math.cos(Ye),it=Math.sin(Ye),ut=tt*P,t=0;t<=d;t++){var Ve;Qe=(Ve=t/d)*B+0,ot=Math.sin(Qe),rt=Math.cos(Qe),Ee.x=ut*ot,Ee.y=it*P-Te,Ee.z=ut*rt,se.push(Ee.x,Ee.y,Ee.z),Ae.set(tt*ot,it,tt*rt),ce.push(Ae.x,Ae.y,Ae.z),ue.push(Ve,1-Ie/Ne),Fe.push(fe),fe++}ve.push(Fe)}for(t=0;t<d;t++)for(e=0;e<F+p+z;e++){var Je=ve[e][t],yt=ve[e+1][t],Wt=ve[e+1][t+1],Nt=ve[e][t+1];ie.push(Je),ie.push(yt),ie.push(Nt),ie.push(yt),ie.push(Wt),ie.push(Nt)}if(ie=ie.reverse(),r.orientation&&!r.orientation.equals(u.e.Up())){var Qt=new u.a;r.orientation.clone().scale(.5*Math.PI).cross(u.e.Up()).toQuaternion().toRotationMatrix(Qt);for(var vt=u.e.Zero(),Jt=0;Jt<se.length;Jt+=3)vt.set(se[Jt],se[Jt+1],se[Jt+2]),u.e.TransformCoordinatesToRef(vt.clone(),Qt,vt),se[Jt]=vt.x,se[Jt+1]=vt.y,se[Jt+2]=vt.z}var Xt=new ft.a;return Xt.positions=se,Xt.normals=ce,Xt.uvs=ue,Xt.indices=ie,Xt},De.a.CreateCapsule=function(r,t,e){return Oc.CreateCapsule(r,t,e)};var xo,Oc=function(){function r(){}return r.CreateCapsule=function(t,e,n){e===void 0&&(e={orientation:u.e.Up(),subdivisions:2,tessellation:16,height:1,radius:.25,capSubdivisions:6});var i=new De.a(t,n);return ft.a.CreateCapsule(e).applyToMesh(i),i},r}(),xm=function(){function r(){}return r.CreateBox=function(t,e,n){return n===void 0&&(n=null),Tr.a.CreateBox(t,e,n)},r.CreateTiledBox=function(t,e,n){return n===void 0&&(n=null),md.CreateTiledBox(t,e,n)},r.CreateSphere=function(t,e,n){return n===void 0&&(n=null),Fn.a.CreateSphere(t,e,n)},r.CreateDisc=function(t,e,n){return n===void 0&&(n=null),Ta.CreateDisc(t,e,n)},r.CreateIcoSphere=function(t,e,n){return n===void 0&&(n=null),Cc.CreateIcoSphere(t,e,n)},r.CreateRibbon=function(t,e,n){return n===void 0&&(n=null),Ao.a.CreateRibbon(t,e,n)},r.CreateCylinder=function(t,e,n){return n===void 0&&(n=null),pi.a.CreateCylinder(t,e,n)},r.CreateTorus=function(t,e,n){return n===void 0&&(n=null),gr.CreateTorus(t,e,n)},r.CreateTorusKnot=function(t,e,n){return n===void 0&&(n=null),Sc.CreateTorusKnot(t,e,n)},r.CreateLineSystem=function(t,e,n){return cn.a.CreateLineSystem(t,e,n)},r.CreateLines=function(t,e,n){return n===void 0&&(n=null),cn.a.CreateLines(t,e,n)},r.CreateDashedLines=function(t,e,n){return n===void 0&&(n=null),cn.a.CreateDashedLines(t,e,n)},r.ExtrudeShape=function(t,e,n){return n===void 0&&(n=null),ca.a.ExtrudeShape(t,e,n)},r.ExtrudeShapeCustom=function(t,e,n){return n===void 0&&(n=null),ca.a.ExtrudeShapeCustom(t,e,n)},r.CreateLathe=function(t,e,n){return n===void 0&&(n=null),Pc.CreateLathe(t,e,n)},r.CreateTiledPlane=function(t,e,n){return n===void 0&&(n=null),vd.CreateTiledPlane(t,e,n)},r.CreatePlane=function(t,e,n){return n===void 0&&(n=null),Ms.a.CreatePlane(t,e,n)},r.CreateGround=function(t,e,n){return n===void 0&&(n=null),Ui.CreateGround(t,e,n)},r.CreateTiledGround=function(t,e,n){return n===void 0&&(n=null),Ui.CreateTiledGround(t,e,n)},r.CreateGroundFromHeightMap=function(t,e,n,i){return i===void 0&&(i=null),Ui.CreateGroundFromHeightMap(t,e,n,i)},r.CreatePolygon=function(t,e,n,i){return n===void 0&&(n=null),i===void 0&&(i=earcut),Po.CreatePolygon(t,e,n,i)},r.ExtrudePolygon=function(t,e,n,i){return n===void 0&&(n=null),i===void 0&&(i=earcut),Po.ExtrudePolygon(t,e,n,i)},r.CreateTube=function(t,e,n){return n===void 0&&(n=null),xc.CreateTube(t,e,n)},r.CreatePolyhedron=function(t,e,n){return n===void 0&&(n=null),ao.CreatePolyhedron(t,e,n)},r.CreateDecal=function(t,e,n){return Rc.CreateDecal(t,e,n)},r.CreateCapsule=function(t,e,n){return e===void 0&&(e={orientation:u.e.Up(),subdivisions:2,tessellation:16,height:1,radius:.25,capSubdivisions:6}),n===void 0&&(n=null),Oc.CreateCapsule(t,e,n)},r}(),Cm=function(r,t,e){this.quality=r,this.distance=t,this.optimizeMesh=e},bd=function(){function r(){this.running=!1,this._simplificationArray=[]}return r.prototype.addTask=function(t){this._simplificationArray.push(t)},r.prototype.executeNext=function(){var t=this._simplificationArray.pop();t?(this.running=!0,this.runSimplification(t)):this.running=!1},r.prototype.runSimplification=function(t){var e=this;if(t.parallelProcessing)t.settings.forEach(function(i){e.getSimplifier(t).simplify(i,function(o){i.distance!==void 0&&t.mesh.addLODLevel(i.distance,o),o.isVisible=!0,i.quality===t.settings[t.settings.length-1].quality&&t.successCallback&&t.successCallback(),e.executeNext()})});else{var n=this.getSimplifier(t);Xe.a.Run(t.settings.length,function(i){var o,a;o=t.settings[i.index],a=function(){i.executeNext()},n.simplify(o,function(s){o.distance!==void 0&&t.mesh.addLODLevel(o.distance,s),s.isVisible=!0,a()})},function(){t.successCallback&&t.successCallback(),e.executeNext()})}},r.prototype.getSimplifier=function(t){switch(t.simplificationType){case xo.QUADRATIC:default:return new Td(t.mesh)}},r}();(function(r){r[r.QUADRATIC=0]="QUADRATIC"})(xo||(xo={}));var Rm=function(r){this.vertices=r,this.error=new Array(4),this.deleted=!1,this.isDirty=!1,this.deletePending=!1,this.borderFactor=0},Om=function(){function r(t,e){this.position=t,this.id=e,this.isBorder=!0,this.q=new yd,this.triangleCount=0,this.triangleStart=0,this.originalOffsets=[]}return r.prototype.updatePosition=function(t){this.position.copyFrom(t)},r}(),yd=function(){function r(t){this.data=new Array(10);for(var e=0;e<10;++e)t&&t[e]?this.data[e]=t[e]:this.data[e]=0}return r.prototype.det=function(t,e,n,i,o,a,s,d,p){return this.data[t]*this.data[o]*this.data[p]+this.data[n]*this.data[i]*this.data[d]+this.data[e]*this.data[a]*this.data[s]-this.data[n]*this.data[o]*this.data[s]-this.data[t]*this.data[a]*this.data[d]-this.data[e]*this.data[i]*this.data[p]},r.prototype.addInPlace=function(t){for(var e=0;e<10;++e)this.data[e]+=t.data[e]},r.prototype.addArrayInPlace=function(t){for(var e=0;e<10;++e)this.data[e]+=t[e]},r.prototype.add=function(t){for(var e=new r,n=0;n<10;++n)e.data[n]=this.data[n]+t.data[n];return e},r.FromData=function(t,e,n,i){return new r(r.DataFromNumbers(t,e,n,i))},r.DataFromNumbers=function(t,e,n,i){return[t*t,t*e,t*n,t*i,e*e,e*n,e*i,n*n,n*i,i*i]},r}(),Mm=function(r,t){this.vertexId=r,this.triangleId=t},Td=function(){function r(t){this._mesh=t,this.syncIterations=5e3,this.aggressiveness=7,this.decimationIterations=100,this.boundingBoxEpsilon=Gt.a}return r.prototype.simplify=function(t,e){var n=this;this.initDecimatedMesh(),Xe.a.Run(this._mesh.subMeshes.length,function(i){n.initWithMesh(i.index,function(){n.runDecimation(t,i.index,function(){i.executeNext()})},t.optimizeMesh)},function(){setTimeout(function(){e(n._reconstructedMesh)},0)})},r.prototype.runDecimation=function(t,e,n){var i=this,o=~~(this.triangles.length*t.quality),a=0,s=this.triangles.length;Xe.a.Run(this.decimationIterations,function(d){var p,b;s-a<=o?d.breakLoop():(p=d.index,b=function(){d.executeNext()},setTimeout(function(){p%5==0&&i.updateMesh(p===0);for(var P=0;P<i.triangles.length;++P)i.triangles[P].isDirty=!1;var O=1e-9*Math.pow(p+3,i.aggressiveness);Xe.a.SyncAsyncForLoop(i.triangles.length,i.syncIterations,function(B){var F=~~((i.triangles.length/2+B)%i.triangles.length),z=i.triangles[F];if(z&&!(z.error[3]>O||z.deleted||z.isDirty)){for(var J=0;J<3;++J)if(z.error[J]<O){var ie=[],se=[],ce=z.vertices[J],ue=z.vertices[(J+1)%3];if(ce.isBorder||ue.isBorder)continue;var fe=u.e.Zero();i.calculateError(ce,ue,fe);var ve=new Array;if(i.isFlipped(ce,ue,fe,ie,ve)||i.isFlipped(ue,ce,fe,se,ve)||ie.indexOf(!0)<0||se.indexOf(!0)<0)continue;var Te=new Array;if(ve.forEach(function(Se){Te.indexOf(Se)===-1&&(Se.deletePending=!0,Te.push(Se))}),Te.length%2!=0)continue;ce.q=ue.q.add(ce.q),ce.updatePosition(fe);var Re=i.references.length;a=i.updateTriangles(ce,ce,ie,a),a=i.updateTriangles(ce,ue,se,a);var Ae=i.references.length-Re;if(Ae<=ce.triangleCount){if(Ae)for(var Ee=0;Ee<Ae;Ee++)i.references[ce.triangleStart+Ee]=i.references[Re+Ee]}else ce.triangleStart=Re;ce.triangleCount=Ae;break}}},b,function(){return s-a<=o})},0))},function(){setTimeout(function(){i.reconstructMesh(e),n()},0)})},r.prototype.initWithMesh=function(t,e,n){var i=this;this.vertices=[],this.triangles=[];var o=this._mesh.getVerticesData(Oe.b.PositionKind),a=this._mesh.getIndices(),s=this._mesh.subMeshes[t],d=[],p=s.verticesCount;Xe.a.SyncAsyncForLoop(p,this.syncIterations/4>>0,function(b){if(o){var P=b+s.verticesStart,O=u.e.FromArray(o,3*P),B=function(F){if(n){for(var z=0;z<i.vertices.length;++z)if(i.vertices[z].position.equalsWithEpsilon(F,1e-4))return i.vertices[z]}return null}(O)||new Om(O,i.vertices.length);B.originalOffsets.push(P),B.id===i.vertices.length&&i.vertices.push(B),d.push(B.id)}},function(){Xe.a.SyncAsyncForLoop(s.indexCount/3,i.syncIterations,function(b){if(a){var P=3*(s.indexStart/3+b),O=a[P+0],B=a[P+1],F=a[P+2],z=i.vertices[d[O-s.verticesStart]],J=i.vertices[d[B-s.verticesStart]],ie=i.vertices[d[F-s.verticesStart]],se=new Rm([z,J,ie]);se.originalOffset=P,i.triangles.push(se)}},function(){i.init(e)})})},r.prototype.init=function(t){var e=this;Xe.a.SyncAsyncForLoop(this.triangles.length,this.syncIterations,function(n){var i=e.triangles[n];i.normal=u.e.Cross(i.vertices[1].position.subtract(i.vertices[0].position),i.vertices[2].position.subtract(i.vertices[0].position)).normalize();for(var o=0;o<3;o++)i.vertices[o].q.addArrayInPlace(yd.DataFromNumbers(i.normal.x,i.normal.y,i.normal.z,-u.e.Dot(i.normal,i.vertices[0].position)))},function(){Xe.a.SyncAsyncForLoop(e.triangles.length,e.syncIterations,function(n){for(var i=e.triangles[n],o=0;o<3;++o)i.error[o]=e.calculateError(i.vertices[o],i.vertices[(o+1)%3]);i.error[3]=Math.min(i.error[0],i.error[1],i.error[2])},function(){t()})})},r.prototype.reconstructMesh=function(t){var e,n,i,o=[];for(e=0;e<this.vertices.length;++e)this.vertices[e].triangleCount=0;for(e=0;e<this.triangles.length;++e)if(!this.triangles[e].deleted){for(n=this.triangles[e],i=0;i<3;++i)n.vertices[i].triangleCount=1;o.push(n)}var a=this._reconstructedMesh.getVerticesData(Oe.b.PositionKind)||[],s=this._reconstructedMesh.getVerticesData(Oe.b.NormalKind)||[],d=this._reconstructedMesh.getVerticesData(Oe.b.UVKind)||[],p=this._reconstructedMesh.getVerticesData(Oe.b.ColorKind)||[],b=this._mesh.getVerticesData(Oe.b.NormalKind),P=this._mesh.getVerticesData(Oe.b.UVKind),O=this._mesh.getVerticesData(Oe.b.ColorKind),B=0;for(e=0;e<this.vertices.length;++e){var F=this.vertices[e];F.id=B,F.triangleCount&&F.originalOffsets.forEach(function(fe){a.push(F.position.x),a.push(F.position.y),a.push(F.position.z),b&&b.length&&(s.push(b[3*fe]),s.push(b[3*fe+1]),s.push(b[3*fe+2])),P&&P.length&&(d.push(P[2*fe]),d.push(P[2*fe+1])),O&&O.length&&(p.push(O[4*fe]),p.push(O[4*fe+1]),p.push(O[4*fe+2]),p.push(O[4*fe+3])),++B})}var z=this._reconstructedMesh.getTotalIndices(),J=this._reconstructedMesh.getTotalVertices(),ie=this._reconstructedMesh.subMeshes;this._reconstructedMesh.subMeshes=[];var se=this._reconstructedMesh.getIndices(),ce=this._mesh.getIndices();for(e=0;e<o.length;++e)n=o[e],[0,1,2].forEach(function(fe){var ve=ce[n.originalOffset+fe],Te=n.vertices[fe].originalOffsets.indexOf(ve);Te<0&&(Te=0),se.push(n.vertices[fe].id+Te+J)});this._reconstructedMesh.setIndices(se),this._reconstructedMesh.setVerticesData(Oe.b.PositionKind,a),s.length>0&&this._reconstructedMesh.setVerticesData(Oe.b.NormalKind,s),d.length>0&&this._reconstructedMesh.setVerticesData(Oe.b.UVKind,d),p.length>0&&this._reconstructedMesh.setVerticesData(Oe.b.ColorKind,p);var ue=this._mesh.subMeshes[t];t>0&&(this._reconstructedMesh.subMeshes=[],ie.forEach(function(fe){Eo.a.AddToMesh(fe.materialIndex,fe.verticesStart,fe.verticesCount,fe.indexStart,fe.indexCount,fe.getMesh())}),Eo.a.AddToMesh(ue.materialIndex,J,B,z,3*o.length,this._reconstructedMesh))},r.prototype.initDecimatedMesh=function(){this._reconstructedMesh=new De.a(this._mesh.name+"Decimated",this._mesh.getScene()),this._reconstructedMesh.material=this._mesh.material,this._reconstructedMesh.parent=this._mesh.parent,this._reconstructedMesh.isVisible=!1,this._reconstructedMesh.renderingGroupId=this._mesh.renderingGroupId},r.prototype.isFlipped=function(t,e,n,i,o){for(var a=0;a<t.triangleCount;++a){var s=this.triangles[this.references[t.triangleStart+a].triangleId];if(!s.deleted){var d=this.references[t.triangleStart+a].vertexId,p=s.vertices[(d+1)%3],b=s.vertices[(d+2)%3];if(p!==e&&b!==e){var P=p.position.subtract(n);P=P.normalize();var O=b.position.subtract(n);if(O=O.normalize(),Math.abs(u.e.Dot(P,O))>.999)return!0;var B=u.e.Cross(P,O).normalize();if(i[a]=!1,u.e.Dot(B,s.normal)<.2)return!0}else i[a]=!0,o.push(s)}}return!1},r.prototype.updateTriangles=function(t,e,n,i){for(var o=i,a=0;a<e.triangleCount;++a){var s=this.references[e.triangleStart+a],d=this.triangles[s.triangleId];d.deleted||(n[a]&&d.deletePending?(d.deleted=!0,o++):(d.vertices[s.vertexId]=t,d.isDirty=!0,d.error[0]=this.calculateError(d.vertices[0],d.vertices[1])+d.borderFactor/2,d.error[1]=this.calculateError(d.vertices[1],d.vertices[2])+d.borderFactor/2,d.error[2]=this.calculateError(d.vertices[2],d.vertices[0])+d.borderFactor/2,d.error[3]=Math.min(d.error[0],d.error[1],d.error[2]),this.references.push(s)))}return o},r.prototype.identifyBorder=function(){for(var t=0;t<this.vertices.length;++t){var e,n=[],i=[],o=this.vertices[t];for(e=0;e<o.triangleCount;++e)for(var a=this.triangles[this.references[o.triangleStart+e].triangleId],s=0;s<3;s++){for(var d=0,p=a.vertices[s];d<n.length&&i[d]!==p.id;)++d;d===n.length?(n.push(1),i.push(p.id)):n[d]++}for(e=0;e<n.length;++e)n[e]===1?this.vertices[i[e]].isBorder=!0:this.vertices[i[e]].isBorder=!1}},r.prototype.updateMesh=function(t){var e,n,i,o;if(t===void 0&&(t=!1),!t){var a=[];for(e=0;e<this.triangles.length;++e)this.triangles[e].deleted||a.push(this.triangles[e]);this.triangles=a}for(e=0;e<this.vertices.length;++e)this.vertices[e].triangleCount=0,this.vertices[e].triangleStart=0;for(e=0;e<this.triangles.length;++e)for(n=this.triangles[e],i=0;i<3;++i)(o=n.vertices[i]).triangleCount++;var s=0;for(e=0;e<this.vertices.length;++e)this.vertices[e].triangleStart=s,s+=this.vertices[e].triangleCount,this.vertices[e].triangleCount=0;var d=new Array(3*this.triangles.length);for(e=0;e<this.triangles.length;++e)for(n=this.triangles[e],i=0;i<3;++i)d[(o=n.vertices[i]).triangleStart+o.triangleCount]=new Mm(i,e),o.triangleCount++;this.references=d,t&&this.identifyBorder()},r.prototype.vertexError=function(t,e){var n=e.x,i=e.y,o=e.z;return t.data[0]*n*n+2*t.data[1]*n*i+2*t.data[2]*n*o+2*t.data[3]*n+t.data[4]*i*i+2*t.data[5]*i*o+2*t.data[6]*i+t.data[7]*o*o+2*t.data[8]*o+t.data[9]},r.prototype.calculateError=function(t,e,n){var i=t.q.add(e.q),o=t.isBorder&&e.isBorder,a=0,s=i.det(0,1,2,1,4,5,2,5,7);if(s===0||o){var d=t.position.add(e.position).divide(new u.e(2,2,2)),p=this.vertexError(i,t.position),b=this.vertexError(i,e.position),P=this.vertexError(i,d);(a=Math.min(p,b,P))===p?n&&n.copyFrom(t.position):a===b?n&&n.copyFrom(e.position):n&&n.copyFrom(d)}else n||(n=u.e.Zero()),n.x=-1/s*i.det(1,2,3,4,5,6,5,7,8),n.y=1/s*i.det(0,2,3,1,5,6,2,7,8),n.z=-1/s*i.det(0,1,3,1,4,6,2,5,8),a=this.vertexError(i,n);return a},r}();Object.defineProperty(_e.a.prototype,"simplificationQueue",{get:function(){if(!this._simplificationQueue){this._simplificationQueue=new bd;var r=this._getComponent(at.a.NAME_SIMPLIFICATIONQUEUE);r||(r=new Ed(this),this._addComponent(r))}return this._simplificationQueue},set:function(r){this._simplificationQueue=r},enumerable:!0,configurable:!0}),De.a.prototype.simplify=function(r,t,e,n){return t===void 0&&(t=!0),e===void 0&&(e=xo.QUADRATIC),this.getScene().simplificationQueue.addTask({settings:r,parallelProcessing:t,mesh:this,simplificationType:e,successCallback:n}),this};var Ed=function(){function r(t){this.name=at.a.NAME_SIMPLIFICATIONQUEUE,this.scene=t}return r.prototype.register=function(){this.scene._beforeCameraUpdateStage.registerStep(at.a.STEP_BEFORECAMERAUPDATE_SIMPLIFICATIONQUEUE,this,this._beforeCameraUpdate)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){},r.prototype._beforeCameraUpdate=function(){this.scene._simplificationQueue&&!this.scene._simplificationQueue.running&&this.scene._simplificationQueue.executeNext()},r}(),Im=f(149),Dm=f(88);De.a.prototype.thinInstanceAdd=function(r,t){t===void 0&&(t=!0),this._thinInstanceUpdateBufferSize("matrix",Array.isArray(r)?r.length:1);var e=this._thinInstanceDataStorage.instancesCount;if(Array.isArray(r))for(var n=0;n<r.length;++n)this.thinInstanceSetMatrixAt(this._thinInstanceDataStorage.instancesCount++,r[n],n===r.length-1&&t);else this.thinInstanceSetMatrixAt(this._thinInstanceDataStorage.instancesCount++,r,t);return e},De.a.prototype.thinInstanceAddSelf=function(r){return r===void 0&&(r=!0),this.thinInstanceAdd(u.a.IdentityReadOnly,r)},De.a.prototype.thinInstanceRegisterAttribute=function(r,t){this.removeVerticesData(r),this._thinInstanceInitializeUserStorage(),this._userThinInstanceBuffersStorage.strides[r]=t,this._userThinInstanceBuffersStorage.sizes[r]=t*Math.max(32,this._thinInstanceDataStorage.instancesCount),this._userThinInstanceBuffersStorage.data[r]=new Float32Array(this._userThinInstanceBuffersStorage.sizes[r]),this._userThinInstanceBuffersStorage.vertexBuffers[r]=new Oe.b(this.getEngine(),this._userThinInstanceBuffersStorage.data[r],r,!0,!1,t,!0),this.setVerticesBuffer(this._userThinInstanceBuffersStorage.vertexBuffers[r])},De.a.prototype.thinInstanceSetMatrixAt=function(r,t,e){if(e===void 0&&(e=!0),!this._thinInstanceDataStorage.matrixData||r>=this._thinInstanceDataStorage.instancesCount)return!1;var n=this._thinInstanceDataStorage.matrixData;return t.copyToArray(n,16*r),this._thinInstanceDataStorage.worldMatrices&&(this._thinInstanceDataStorage.worldMatrices[r]=t),e&&(this.thinInstanceBufferUpdated("matrix"),this.doNotSyncBoundingInfo||this.thinInstanceRefreshBoundingInfo(!1)),!0},De.a.prototype.thinInstanceSetAttributeAt=function(r,t,e,n){return n===void 0&&(n=!0),!(!this._userThinInstanceBuffersStorage||!this._userThinInstanceBuffersStorage.data[r]||t>=this._thinInstanceDataStorage.instancesCount)&&(this._thinInstanceUpdateBufferSize(r,0),this._userThinInstanceBuffersStorage.data[r].set(e,t*this._userThinInstanceBuffersStorage.strides[r]),n&&this.thinInstanceBufferUpdated(r),!0)},Object.defineProperty(De.a.prototype,"thinInstanceCount",{get:function(){return this._thinInstanceDataStorage.instancesCount},set:function(r){var t,e;r<=((e=(t=this._thinInstanceDataStorage.matrixData)===null||t===void 0?void 0:t.length)!==null&&e!==void 0?e:0)/16&&(this._thinInstanceDataStorage.instancesCount=r)},enumerable:!0,configurable:!0}),De.a.prototype.thinInstanceSetBuffer=function(r,t,e,n){var i,o;if(e===void 0&&(e=0),n===void 0&&(n=!1),e=e||16,r==="matrix")if((i=this._thinInstanceDataStorage.matrixBuffer)===null||i===void 0||i.dispose(),this._thinInstanceDataStorage.matrixBuffer=null,this._thinInstanceDataStorage.matrixBufferSize=t?t.length:32*e,this._thinInstanceDataStorage.matrixData=t,this._thinInstanceDataStorage.worldMatrices=null,t!==null){this._thinInstanceDataStorage.instancesCount=t.length/e;var a=new Oe.a(this.getEngine(),t,!n,e,!1,!0);this._thinInstanceDataStorage.matrixBuffer=a,this.setVerticesBuffer(a.createVertexBuffer("world0",0,4)),this.setVerticesBuffer(a.createVertexBuffer("world1",4,4)),this.setVerticesBuffer(a.createVertexBuffer("world2",8,4)),this.setVerticesBuffer(a.createVertexBuffer("world3",12,4)),this.doNotSyncBoundingInfo||this.thinInstanceRefreshBoundingInfo(!1)}else this._thinInstanceDataStorage.instancesCount=0,this.doNotSyncBoundingInfo||this.refreshBoundingInfo(!0);else t===null?!((o=this._userThinInstanceBuffersStorage)===null||o===void 0)&&o.data[r]&&(this.removeVerticesData(r),delete this._userThinInstanceBuffersStorage.data[r],delete this._userThinInstanceBuffersStorage.strides[r],delete this._userThinInstanceBuffersStorage.sizes[r],delete this._userThinInstanceBuffersStorage.vertexBuffers[r]):(this._thinInstanceInitializeUserStorage(),this._userThinInstanceBuffersStorage.data[r]=t,this._userThinInstanceBuffersStorage.strides[r]=e,this._userThinInstanceBuffersStorage.sizes[r]=t.length,this._userThinInstanceBuffersStorage.vertexBuffers[r]=new Oe.b(this.getEngine(),t,r,!n,!1,e,!0),this.setVerticesBuffer(this._userThinInstanceBuffersStorage.vertexBuffers[r]))},De.a.prototype.thinInstanceBufferUpdated=function(r){var t;r==="matrix"?this._thinInstanceDataStorage.matrixBuffer&&this._thinInstanceDataStorage.matrixBuffer.updateDirectly(this._thinInstanceDataStorage.matrixData,0,this._thinInstanceDataStorage.instancesCount):!((t=this._userThinInstanceBuffersStorage)===null||t===void 0)&&t.vertexBuffers[r]&&this._userThinInstanceBuffersStorage.vertexBuffers[r].updateDirectly(this._userThinInstanceBuffersStorage.data[r],0)},De.a.prototype.thinInstancePartialBufferUpdate=function(r,t,e){var n;r==="matrix"?this._thinInstanceDataStorage.matrixBuffer&&this._thinInstanceDataStorage.matrixBuffer.updateDirectly(t,e):!((n=this._userThinInstanceBuffersStorage)===null||n===void 0)&&n.vertexBuffers[r]&&this._userThinInstanceBuffersStorage.vertexBuffers[r].updateDirectly(t,e)},De.a.prototype.thinInstanceGetWorldMatrices=function(){if(!this._thinInstanceDataStorage.matrixData||!this._thinInstanceDataStorage.matrixBuffer)return[];var r=this._thinInstanceDataStorage.matrixData;if(!this._thinInstanceDataStorage.worldMatrices){this._thinInstanceDataStorage.worldMatrices=new Array;for(var t=0;t<this._thinInstanceDataStorage.instancesCount;++t)this._thinInstanceDataStorage.worldMatrices[t]=u.a.FromArray(r,16*t)}return this._thinInstanceDataStorage.worldMatrices},De.a.prototype.thinInstanceRefreshBoundingInfo=function(r){if(r===void 0&&(r=!1),this._thinInstanceDataStorage.matrixData&&this._thinInstanceDataStorage.matrixBuffer){var t=this._thinInstanceDataStorage.boundingVectors;r&&(t.length=0,this.refreshBoundingInfo(!0));var e=this.getBoundingInfo(),n=this._thinInstanceDataStorage.matrixData;if(t.length===0)for(var i=0;i<e.boundingBox.vectors.length;++i)t.push(e.boundingBox.vectors[i].clone());u.c.Vector3[0].setAll(Number.POSITIVE_INFINITY),u.c.Vector3[1].setAll(Number.NEGATIVE_INFINITY);for(var o=0;o<this._thinInstanceDataStorage.instancesCount;++o)for(u.a.FromArrayToRef(n,16*o,u.c.Matrix[0]),i=0;i<t.length;++i)u.e.TransformCoordinatesToRef(t[i],u.c.Matrix[0],u.c.Vector3[2]),u.c.Vector3[0].minimizeInPlace(u.c.Vector3[2]),u.c.Vector3[1].maximizeInPlace(u.c.Vector3[2]);e.reConstruct(u.c.Vector3[0],u.c.Vector3[1]),this._updateBoundingInfo()}},De.a.prototype._thinInstanceUpdateBufferSize=function(r,t){var e,n;t===void 0&&(t=1);var i=r==="matrix";if(i||this._userThinInstanceBuffersStorage&&this._userThinInstanceBuffersStorage.strides[r]){for(var o=i?16:this._userThinInstanceBuffersStorage.strides[r],a=i?this._thinInstanceDataStorage.matrixBufferSize:this._userThinInstanceBuffersStorage.sizes[r],s=i?this._thinInstanceDataStorage.matrixData:this._userThinInstanceBuffersStorage.data[r],d=(this._thinInstanceDataStorage.instancesCount+t)*o,p=a;p<d;)p*=2;if(!s||a!=p){if(s){var b=new Float32Array(p);b.set(s,0),s=b}else s=new Float32Array(p);if(i){(e=this._thinInstanceDataStorage.matrixBuffer)===null||e===void 0||e.dispose();var P=new Oe.a(this.getEngine(),s,!0,o,!1,!0);this._thinInstanceDataStorage.matrixBuffer=P,this._thinInstanceDataStorage.matrixData=s,this._thinInstanceDataStorage.matrixBufferSize=p,this.setVerticesBuffer(P.createVertexBuffer("world0",0,4)),this.setVerticesBuffer(P.createVertexBuffer("world1",4,4)),this.setVerticesBuffer(P.createVertexBuffer("world2",8,4)),this.setVerticesBuffer(P.createVertexBuffer("world3",12,4))}else(n=this._userThinInstanceBuffersStorage.vertexBuffers[r])===null||n===void 0||n.dispose(),this._userThinInstanceBuffersStorage.data[r]=s,this._userThinInstanceBuffersStorage.sizes[r]=p,this._userThinInstanceBuffersStorage.vertexBuffers[r]=new Oe.b(this.getEngine(),s,r,!0,!1,o,!0),this.setVerticesBuffer(this._userThinInstanceBuffersStorage.vertexBuffers[r])}}},De.a.prototype._thinInstanceInitializeUserStorage=function(){this._userThinInstanceBuffersStorage||(this._userThinInstanceBuffersStorage={data:{},sizes:{},vertexBuffers:{},strides:{}})},De.a.prototype._disposeThinInstanceSpecificData=function(){var r;!((r=this._thinInstanceDataStorage)===null||r===void 0)&&r.matrixBuffer&&(this._thinInstanceDataStorage.matrixBuffer.dispose(),this._thinInstanceDataStorage.matrixBuffer=null)};var Lm=function(){function r(t){t===void 0&&(t=Recast),this.bjsRECAST={},this.name="RecastJSPlugin",this._maximumSubStepCount=10,this._timeStep=1/60,typeof t=="function"?t(this.bjsRECAST):this.bjsRECAST=t,this.isSupported()?this.setTimeStep():l.a.Error("RecastJS is not available. Please make sure you included the js file.")}return r.prototype.setTimeStep=function(t){t===void 0&&(t=1/60),this._timeStep=t},r.prototype.getTimeStep=function(){return this._timeStep},r.prototype.setMaximumSubStepCount=function(t){t===void 0&&(t=10),this._maximumSubStepCount=t},r.prototype.getMaximumSubStepCount=function(){return this._maximumSubStepCount},r.prototype.createNavMesh=function(t,e){var n,i,o,a=new this.bjsRECAST.rcConfig;a.cs=e.cs,a.ch=e.ch,a.borderSize=0,a.tileSize=0,a.walkableSlopeAngle=e.walkableSlopeAngle,a.walkableHeight=e.walkableHeight,a.walkableClimb=e.walkableClimb,a.walkableRadius=e.walkableRadius,a.maxEdgeLen=e.maxEdgeLen,a.maxSimplificationError=e.maxSimplificationError,a.minRegionArea=e.minRegionArea,a.mergeRegionArea=e.mergeRegionArea,a.maxVertsPerPoly=e.maxVertsPerPoly,a.detailSampleDist=e.detailSampleDist,a.detailSampleMaxError=e.detailSampleMaxError,this.navMesh=new this.bjsRECAST.NavMesh;var s=[],d=[],p=0;for(n=0;n<t.length;n++)if(t[n]){var b=t[n],P=b.getIndices();if(!P)continue;var O=b.getVerticesData(Oe.b.PositionKind,!1,!1);if(!O)continue;var B=b.computeWorldMatrix(!0);for(i=0;i<P.length;i++)s.push(P[i]+p);var F=u.e.Zero(),z=u.e.Zero();for(o=0;o<O.length;o+=3)u.e.FromArrayToRef(O,o,z),u.e.TransformCoordinatesToRef(z,B,F),d.push(F.x,F.y,F.z);p+=O.length/3}this.navMesh.build(d,p,s,s.length,a)},r.prototype.createDebugNavMesh=function(t){var e,n,i=this.navMesh.getDebugNavMesh(),o=i.getTriangleCount(),a=[],s=[];for(e=0;e<3*o;e++)a.push(e);for(e=0;e<o;e++)for(n=0;n<3;n++){var d=i.getTriangle(e).getPoint(n);s.push(d.x,d.y,d.z)}var p=new De.a("NavMeshDebug",t),b=new ft.a;return b.indices=a,b.positions=s,b.applyToMesh(p,!1),p},r.prototype.getClosestPoint=function(t){var e=new this.bjsRECAST.Vec3(t.x,t.y,t.z),n=this.navMesh.getClosestPoint(e);return new u.e(n.x,n.y,n.z)},r.prototype.getClosestPointToRef=function(t,e){var n=new this.bjsRECAST.Vec3(t.x,t.y,t.z),i=this.navMesh.getClosestPoint(n);e.set(i.x,i.y,i.z)},r.prototype.getRandomPointAround=function(t,e){var n=new this.bjsRECAST.Vec3(t.x,t.y,t.z),i=this.navMesh.getRandomPointAround(n,e);return new u.e(i.x,i.y,i.z)},r.prototype.getRandomPointAroundToRef=function(t,e,n){var i=new this.bjsRECAST.Vec3(t.x,t.y,t.z),o=this.navMesh.getRandomPointAround(i,e);n.set(o.x,o.y,o.z)},r.prototype.moveAlong=function(t,e){var n=new this.bjsRECAST.Vec3(t.x,t.y,t.z),i=new this.bjsRECAST.Vec3(e.x,e.y,e.z),o=this.navMesh.moveAlong(n,i);return new u.e(o.x,o.y,o.z)},r.prototype.moveAlongToRef=function(t,e,n){var i=new this.bjsRECAST.Vec3(t.x,t.y,t.z),o=new this.bjsRECAST.Vec3(e.x,e.y,e.z),a=this.navMesh.moveAlong(i,o);n.set(a.x,a.y,a.z)},r.prototype.computePath=function(t,e){var n,i=new this.bjsRECAST.Vec3(t.x,t.y,t.z),o=new this.bjsRECAST.Vec3(e.x,e.y,e.z),a=this.navMesh.computePath(i,o),s=a.getPointCount(),d=[];for(n=0;n<s;n++){var p=a.getPoint(n);d.push(new u.e(p.x,p.y,p.z))}return d},r.prototype.createCrowd=function(t,e,n){return new Sd(this,t,e,n)},r.prototype.setDefaultQueryExtent=function(t){var e=new this.bjsRECAST.Vec3(t.x,t.y,t.z);this.navMesh.setDefaultQueryExtent(e)},r.prototype.getDefaultQueryExtent=function(){var t=this.navMesh.getDefaultQueryExtent();return new u.e(t.x,t.y,t.z)},r.prototype.buildFromNavmeshData=function(t){var e=t.length*t.BYTES_PER_ELEMENT,n=this.bjsRECAST._malloc(e),i=new Uint8Array(this.bjsRECAST.HEAPU8.buffer,n,e);i.set(t);var o=new this.bjsRECAST.NavmeshData;o.dataPointer=i.byteOffset,o.size=t.length,this.navMesh=new this.bjsRECAST.NavMesh,this.navMesh.buildFromNavmeshData(o),this.bjsRECAST._free(i.byteOffset)},r.prototype.getNavmeshData=function(){var t=this.navMesh.getNavmeshData(),e=new Uint8Array(this.bjsRECAST.HEAPU8.buffer,t.dataPointer,t.size),n=new Uint8Array(t.size);return n.set(e),this.navMesh.freeNavmeshData(t),n},r.prototype.getDefaultQueryExtentToRef=function(t){var e=this.navMesh.getDefaultQueryExtent();t.set(e.x,e.y,e.z)},r.prototype.dispose=function(){},r.prototype.isSupported=function(){return this.bjsRECAST!==void 0},r}(),Sd=function(){function r(t,e,n,i){var o=this;this.recastCrowd={},this.transforms=new Array,this.agents=new Array,this._onBeforeAnimationsObserver=null,this.bjsRECASTPlugin=t,this.recastCrowd=new this.bjsRECASTPlugin.bjsRECAST.Crowd(e,n,this.bjsRECASTPlugin.navMesh.getNavMesh()),this._scene=i,this._onBeforeAnimationsObserver=i.onBeforeAnimationsObservable.add(function(){o.update(.001*i.getEngine().getDeltaTime())})}return r.prototype.addAgent=function(t,e,n){var i=new this.bjsRECASTPlugin.bjsRECAST.dtCrowdAgentParams;i.radius=e.radius,i.height=e.height,i.maxAcceleration=e.maxAcceleration,i.maxSpeed=e.maxSpeed,i.collisionQueryRange=e.collisionQueryRange,i.pathOptimizationRange=e.pathOptimizationRange,i.separationWeight=e.separationWeight,i.updateFlags=7,i.obstacleAvoidanceType=0,i.queryFilterType=0,i.userData=0;var o=this.recastCrowd.addAgent(new this.bjsRECASTPlugin.bjsRECAST.Vec3(t.x,t.y,t.z),i);return this.transforms.push(n),this.agents.push(o),o},r.prototype.getAgentPosition=function(t){var e=this.recastCrowd.getAgentPosition(t);return new u.e(e.x,e.y,e.z)},r.prototype.getAgentPositionToRef=function(t,e){var n=this.recastCrowd.getAgentPosition(t);e.set(n.x,n.y,n.z)},r.prototype.getAgentVelocity=function(t){var e=this.recastCrowd.getAgentVelocity(t);return new u.e(e.x,e.y,e.z)},r.prototype.getAgentVelocityToRef=function(t,e){var n=this.recastCrowd.getAgentVelocity(t);e.set(n.x,n.y,n.z)},r.prototype.getAgentNextTargetPath=function(t){var e=this.recastCrowd.getAgentNextTargetPath(t);return new u.e(e.x,e.y,e.z)},r.prototype.getAgentNextTargetPathToRef=function(t,e){var n=this.recastCrowd.getAgentNextTargetPath(t);e.set(n.x,n.y,n.z)},r.prototype.getAgentState=function(t){return this.recastCrowd.getAgentState(t)},r.prototype.overOffmeshConnection=function(t){return this.recastCrowd.overOffmeshConnection(t)},r.prototype.agentGoto=function(t,e){this.recastCrowd.agentGoto(t,new this.bjsRECASTPlugin.bjsRECAST.Vec3(e.x,e.y,e.z))},r.prototype.agentTeleport=function(t,e){this.recastCrowd.agentTeleport(t,new this.bjsRECASTPlugin.bjsRECAST.Vec3(e.x,e.y,e.z))},r.prototype.updateAgentParameters=function(t,e){var n=this.recastCrowd.getAgentParameters(t);e.radius!==void 0&&(n.radius=e.radius),e.height!==void 0&&(n.height=e.height),e.maxAcceleration!==void 0&&(n.maxAcceleration=e.maxAcceleration),e.maxSpeed!==void 0&&(n.maxSpeed=e.maxSpeed),e.collisionQueryRange!==void 0&&(n.collisionQueryRange=e.collisionQueryRange),e.pathOptimizationRange!==void 0&&(n.pathOptimizationRange=e.pathOptimizationRange),e.separationWeight!==void 0&&(n.separationWeight=e.separationWeight),this.recastCrowd.setAgentParameters(t,n)},r.prototype.removeAgent=function(t){this.recastCrowd.removeAgent(t);var e=this.agents.indexOf(t);e>-1&&(this.agents.splice(e,1),this.transforms.splice(e,1))},r.prototype.getAgents=function(){return this.agents},r.prototype.update=function(t){var e=this.bjsRECASTPlugin.getTimeStep(),n=this.bjsRECASTPlugin.getMaximumSubStepCount();if(e<=Gt.a)this.recastCrowd.update(t);else{var i=t/e;n&&i>n&&(i=n),i<1&&(i=1);for(var o=0;o<i;o++)this.recastCrowd.update(e)}for(var a=0;a<this.agents.length;a++)this.transforms[a].position=this.getAgentPosition(this.agents[a])},r.prototype.setDefaultQueryExtent=function(t){var e=new this.bjsRECASTPlugin.bjsRECAST.Vec3(t.x,t.y,t.z);this.recastCrowd.setDefaultQueryExtent(e)},r.prototype.getDefaultQueryExtent=function(){var t=this.recastCrowd.getDefaultQueryExtent();return new u.e(t.x,t.y,t.z)},r.prototype.getDefaultQueryExtentToRef=function(t){var e=this.recastCrowd.getDefaultQueryExtent();t.set(e.x,e.y,e.z)},r.prototype.dispose=function(){this.recastCrowd.destroy(),this._scene.onBeforeAnimationsObservable.remove(this._onBeforeAnimationsObserver),this._onBeforeAnimationsObserver=null},r}();Ue.a.OfflineProviderFactory=function(r,t,e){return e===void 0&&(e=!1),new Ad(r,t,e)};var Fr,Ad=function(){function r(t,e,n){var i=this;n===void 0&&(n=!1),this._idbFactory=typeof window<"u"?window.indexedDB||window.mozIndexedDB||window.webkitIndexedDB||window.msIndexedDB:indexedDB,this._callbackManifestChecked=e,this._currentSceneUrl=r._ReturnFullUrlLocation(t),this._db=null,this._enableSceneOffline=!1,this._enableTexturesOffline=!1,this._manifestVersionFound=0,this._mustUpdateRessources=!1,this._hasReachedQuota=!1,r.IDBStorageEnabled?n?(this._enableSceneOffline=!0,this._enableTexturesOffline=!0,this._manifestVersionFound=1,Xe.b.SetImmediate(function(){i._callbackManifestChecked(!0)})):this._checkManifestFile():this._callbackManifestChecked(!0)}return Object.defineProperty(r.prototype,"enableSceneOffline",{get:function(){return this._enableSceneOffline},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"enableTexturesOffline",{get:function(){return this._enableTexturesOffline},enumerable:!1,configurable:!0}),r.prototype._checkManifestFile=function(){var t=this,e=function(){t._enableSceneOffline=!1,t._enableTexturesOffline=!1,t._callbackManifestChecked(!1)},n=!1,i=this._currentSceneUrl+".manifest",o=new re.a;navigator.onLine&&(n=!0,i=i+(i.match(/\?/)==null?"?":"&")+Date.now()),o.open("GET",i),o.addEventListener("load",function(){if(o.status===200||r._ValidateXHRData(o,1))try{var a=JSON.parse(o.response);t._enableSceneOffline=a.enableSceneOffline,t._enableTexturesOffline=a.enableTexturesOffline&&r.IsUASupportingBlobStorage,a.version&&!isNaN(parseInt(a.version))&&(t._manifestVersionFound=a.version),t._callbackManifestChecked&&t._callbackManifestChecked(!0)}catch{e()}else e()},!1),o.addEventListener("error",function(){if(n){n=!1;var a=t._currentSceneUrl+".manifest";o.open("GET",a),o.send()}else e()},!1);try{o.send()}catch{l.a.Error("Error on XHR send request."),this._callbackManifestChecked(!1)}},r.prototype.open=function(t,e){var n=this,i=function(){n._isSupported=!1,e&&e()};if(this._idbFactory&&(this._enableSceneOffline||this._enableTexturesOffline))if(this._db)t&&t();else{this._hasReachedQuota=!1,this._isSupported=!0;var o=this._idbFactory.open("babylonjs",1);o.onerror=function(){i()},o.onblocked=function(){l.a.Error("IDB request blocked. Please reload the page."),i()},o.onsuccess=function(){n._db=o.result,t()},o.onupgradeneeded=function(a){if(n._db=a.target.result,n._db)try{n._db.createObjectStore("scenes",{keyPath:"sceneUrl"}),n._db.createObjectStore("versions",{keyPath:"sceneUrl"}),n._db.createObjectStore("textures",{keyPath:"textureUrl"})}catch(s){l.a.Error("Error while creating object stores. Exception: "+s.message),i()}}}else this._isSupported=!1,e&&e()},r.prototype.loadImage=function(t,e){var n=this,i=r._ReturnFullUrlLocation(t),o=function(){n._hasReachedQuota||n._db===null?e.src=t:n._saveImageIntoDBAsync(i,e)};this._mustUpdateRessources?o():this._loadImageFromDBAsync(i,e,o)},r.prototype._loadImageFromDBAsync=function(t,e,n){if(this._isSupported&&this._db!==null){var i,o=this._db.transaction(["textures"]);o.onabort=function(){e.src=t},o.oncomplete=function(){var s;if(i){var d=window.URL||window.webkitURL;s=d.createObjectURL(i.data),e.onerror=function(){l.a.Error("Error loading image from blob URL: "+s+" switching back to web url: "+t),e.src=t},e.src=s}else n()};var a=o.objectStore("textures").get(t);a.onsuccess=function(s){i=s.target.result},a.onerror=function(){l.a.Error("Error loading texture "+t+" from DB."),e.src=t}}else l.a.Error("Error: IndexedDB not supported by your browser or BabylonJS Database is not open."),e.src=t},r.prototype._saveImageIntoDBAsync=function(t,e){var n=this;if(this._isSupported){var i=function(){var s;if(o){var d=window.URL||window.webkitURL;try{s=d.createObjectURL(o)}catch{s=d.createObjectURL(o)}}s&&(e.src=s)};if(r.IsUASupportingBlobStorage){var o,a=new re.a;a.open("GET",t),a.responseType="blob",a.addEventListener("load",function(){if(a.status===200&&n._db){o=a.response;var s=n._db.transaction(["textures"],"readwrite");s.onabort=function(b){try{var P=(b.srcElement||b.target).error;P&&P.name==="QuotaExceededError"&&(n._hasReachedQuota=!0)}catch{}i()},s.oncomplete=function(){i()};var d={textureUrl:t,data:o};try{var p=s.objectStore("textures").put(d);p.onsuccess=function(){},p.onerror=function(){i()}}catch(b){b.code===25&&(r.IsUASupportingBlobStorage=!1,n._enableTexturesOffline=!1),e.src=t}}else e.src=t},!1),a.addEventListener("error",function(){l.a.Error("Error in XHR request in BABYLON.Database."),e.src=t},!1),a.send()}else e.src=t}else l.a.Error("Error: IndexedDB not supported by your browser or Babylon.js database is not open."),e.src=t},r.prototype._checkVersionFromDB=function(t,e){var n=this;this._loadVersionFromDBAsync(t,e,function(){n._saveVersionIntoDBAsync(t,e)})},r.prototype._loadVersionFromDBAsync=function(t,e,n){var i,o=this;if(this._isSupported&&this._db)try{var a=this._db.transaction(["versions"]);a.oncomplete=function(){i?o._manifestVersionFound!==i.data?(o._mustUpdateRessources=!0,n()):e(i.data):(o._mustUpdateRessources=!0,n())},a.onabort=function(){e(-1)};var s=a.objectStore("versions").get(t);s.onsuccess=function(d){i=d.target.result},s.onerror=function(){l.a.Error("Error loading version for scene "+t+" from DB."),e(-1)}}catch(d){l.a.Error("Error while accessing 'versions' object store (READ OP). Exception: "+d.message),e(-1)}else l.a.Error("Error: IndexedDB not supported by your browser or Babylon.js database is not open."),e(-1)},r.prototype._saveVersionIntoDBAsync=function(t,e){var n=this;if(this._isSupported&&!this._hasReachedQuota&&this._db)try{var i=this._db.transaction(["versions"],"readwrite");i.onabort=function(s){try{var d=s.srcElement.error;d&&d.name==="QuotaExceededError"&&(n._hasReachedQuota=!0)}catch{}e(-1)},i.oncomplete=function(){e(n._manifestVersionFound)};var o={sceneUrl:t,data:this._manifestVersionFound},a=i.objectStore("versions").put(o);a.onsuccess=function(){},a.onerror=function(){l.a.Error("Error in DB add version request in BABYLON.Database.")}}catch(s){l.a.Error("Error while accessing 'versions' object store (WRITE OP). Exception: "+s.message),e(-1)}else e(-1)},r.prototype.loadFile=function(t,e,n,i,o){var a=this,s=r._ReturnFullUrlLocation(t),d=function(){a._saveFileAsync(s,e,n,o,i)};this._checkVersionFromDB(s,function(p){p!==-1?a._mustUpdateRessources?a._saveFileAsync(s,e,n,o,i):a._loadFileAsync(s,e,d):i&&i()})},r.prototype._loadFileAsync=function(t,e,n){if(this._isSupported&&this._db){var i,o;i=t.indexOf(".babylon")!==-1?"scenes":"textures";var a=this._db.transaction([i]);a.oncomplete=function(){o?e(o.data):n()},a.onabort=function(){n()};var s=a.objectStore(i).get(t);s.onsuccess=function(d){o=d.target.result},s.onerror=function(){l.a.Error("Error loading file "+t+" from DB."),n()}}else l.a.Error("Error: IndexedDB not supported by your browser or BabylonJS Database is not open."),e()},r.prototype._saveFileAsync=function(t,e,n,i,o){var a=this;if(this._isSupported){var s;s=t.indexOf(".babylon")!==-1?"scenes":"textures";var d,p=new re.a;p.open("GET",t+"?"+Date.now()),i&&(p.responseType="arraybuffer"),n&&(p.onprogress=n),p.addEventListener("load",function(){if(p.status===200||p.status<400&&r._ValidateXHRData(p,i?6:1))if(d=i?p.response:p.responseText,!a._hasReachedQuota&&a._db){var b,P=a._db.transaction([s],"readwrite");P.onabort=function(B){try{var F=B.srcElement.error;F&&F.name==="QuotaExceededError"&&(a._hasReachedQuota=!0)}catch{}e(d)},P.oncomplete=function(){e(d)},b=s==="scenes"?{sceneUrl:t,data:d,version:a._manifestVersionFound}:{textureUrl:t,data:d};try{var O=P.objectStore(s).put(b);O.onsuccess=function(){},O.onerror=function(){l.a.Error("Error in DB add file request in BABYLON.Database.")}}catch{e(d)}}else e(d);else p.status>=400&&o?o(p):e()},!1),p.addEventListener("error",function(){l.a.Error("error on XHR request."),e()},!1),p.send()}else l.a.Error("Error: IndexedDB not supported by your browser or Babylon.js database is not open."),e()},r._ValidateXHRData=function(t,e){e===void 0&&(e=7);try{if(1&e){if(t.responseText&&t.responseText.length>0)return!0;if(e===1)return!1}if(2&e){var n=ha.GetTGAHeader(t.response);if(n.width&&n.height&&n.width>0&&n.height>0)return!0;if(e===2)return!1}if(4&e){var i=new Uint8Array(t.response,0,3);return i[0]===68&&i[1]===68&&i[2]===83}}catch{}return!1},r.IsUASupportingBlobStorage=!0,r.IDBStorageEnabled=!1,r._ParseURL=function(t){document.createElement("a").href=t;var e=t.substring(0,t.lastIndexOf("#")),n=t.substring(e.lastIndexOf("/")+1,t.length);return t.substring(0,t.indexOf(n,0))},r._ReturnFullUrlLocation=function(t){return t.indexOf("http:/")===-1&&t.indexOf("https:/")===-1&&typeof window<"u"?r._ParseURL(window.location.href)+t:t},r}(),Mc=function(){function r(t,e,n){this.gradient=t,this.color1=e,this.color2=n}return r.prototype.getColorToRef=function(t){this.color2?M.b.LerpToRef(this.color1,this.color2,Math.random(),t):t.copyFrom(this.color1)},r}(),Pd=function(r,t){this.gradient=r,this.color=t},Ic=function(){function r(t,e,n){this.gradient=t,this.factor1=e,this.factor2=n}return r.prototype.getFactor=function(){return this.factor2===void 0||this.factor2===this.factor1?this.factor1:this.factor1+(this.factor2-this.factor1)*Math.random()},r}(),In=function(){function r(){}return r.GetCurrentGradient=function(t,e,n){if(e[0].gradient>t)n(e[0],e[0],1);else{for(var i=0;i<e.length-1;i++){var o=e[i],a=e[i+1];if(t>=o.gradient&&t<=a.gradient)return void n(o,a,(t-o.gradient)/(a.gradient-o.gradient))}var s=e.length-1;n(e[s],e[s],1)}},r}(),xd=function(){function r(t){this.particleSystem=t,this.position=u.e.Zero(),this.direction=u.e.Zero(),this.color=new M.b(0,0,0,0),this.colorStep=new M.b(0,0,0,0),this.lifeTime=1,this.age=0,this.size=0,this.scale=new u.d(1,1),this.angle=0,this.angularSpeed=0,this.cellIndex=0,this._attachedSubEmitters=null,this._currentColor1=new M.b(0,0,0,0),this._currentColor2=new M.b(0,0,0,0),this._currentSize1=0,this._currentSize2=0,this._currentAngularSpeed1=0,this._currentAngularSpeed2=0,this._currentVelocity1=0,this._currentVelocity2=0,this._currentLimitVelocity1=0,this._currentLimitVelocity2=0,this._currentDrag1=0,this._currentDrag2=0,this.id=r._Count++,this.particleSystem.isAnimationSheetEnabled&&this.updateCellInfoFromSystem()}return r.prototype.updateCellInfoFromSystem=function(){this.cellIndex=this.particleSystem.startSpriteCellID},r.prototype.updateCellIndex=function(){var t=this.age,e=this.particleSystem.spriteCellChangeSpeed;this.particleSystem.spriteRandomStartCell&&(this._randomCellOffset===void 0&&(this._randomCellOffset=Math.random()*this.lifeTime),e===0?(e=1,t=this._randomCellOffset):t+=this._randomCellOffset);var n=this._initialEndSpriteCellID-this._initialStartSpriteCellID,i=$.a.Clamp(t*e%this.lifeTime/this.lifeTime);this.cellIndex=this._initialStartSpriteCellID+i*n|0},r.prototype._inheritParticleInfoToSubEmitter=function(t){if(t.particleSystem.emitter.position){var e=t.particleSystem.emitter;if(e.position.copyFrom(this.position),t.inheritDirection){var n=u.c.Vector3[0];this.direction.normalizeToRef(n),e.setDirection(n,0,Math.PI/2)}}else t.particleSystem.emitter.copyFrom(this.position);this.direction.scaleToRef(t.inheritedVelocityAmount/2,u.c.Vector3[0]),t.particleSystem._inheritedVelocityOffset.copyFrom(u.c.Vector3[0])},r.prototype._inheritParticleInfoToSubEmitters=function(){var t=this;this._attachedSubEmitters&&this._attachedSubEmitters.length>0&&this._attachedSubEmitters.forEach(function(e){t._inheritParticleInfoToSubEmitter(e)})},r.prototype._reset=function(){this.age=0,this.id=r._Count++,this._currentColorGradient=null,this._currentSizeGradient=null,this._currentAngularSpeedGradient=null,this._currentVelocityGradient=null,this._currentLimitVelocityGradient=null,this._currentDragGradient=null,this.cellIndex=this.particleSystem.startSpriteCellID,this._randomCellOffset=void 0},r.prototype.copyTo=function(t){t.position.copyFrom(this.position),this._initialDirection?t._initialDirection?t._initialDirection.copyFrom(this._initialDirection):t._initialDirection=this._initialDirection.clone():t._initialDirection=null,t.direction.copyFrom(this.direction),this._localPosition&&(t._localPosition?t._localPosition.copyFrom(this._localPosition):t._localPosition=this._localPosition.clone()),t.color.copyFrom(this.color),t.colorStep.copyFrom(this.colorStep),t.lifeTime=this.lifeTime,t.age=this.age,t._randomCellOffset=this._randomCellOffset,t.size=this.size,t.scale.copyFrom(this.scale),t.angle=this.angle,t.angularSpeed=this.angularSpeed,t.particleSystem=this.particleSystem,t.cellIndex=this.cellIndex,t.id=this.id,t._attachedSubEmitters=this._attachedSubEmitters,this._currentColorGradient&&(t._currentColorGradient=this._currentColorGradient,t._currentColor1.copyFrom(this._currentColor1),t._currentColor2.copyFrom(this._currentColor2)),this._currentSizeGradient&&(t._currentSizeGradient=this._currentSizeGradient,t._currentSize1=this._currentSize1,t._currentSize2=this._currentSize2),this._currentAngularSpeedGradient&&(t._currentAngularSpeedGradient=this._currentAngularSpeedGradient,t._currentAngularSpeed1=this._currentAngularSpeed1,t._currentAngularSpeed2=this._currentAngularSpeed2),this._currentVelocityGradient&&(t._currentVelocityGradient=this._currentVelocityGradient,t._currentVelocity1=this._currentVelocity1,t._currentVelocity2=this._currentVelocity2),this._currentLimitVelocityGradient&&(t._currentLimitVelocityGradient=this._currentLimitVelocityGradient,t._currentLimitVelocity1=this._currentLimitVelocity1,t._currentLimitVelocity2=this._currentLimitVelocity2),this._currentDragGradient&&(t._currentDragGradient=this._currentDragGradient,t._currentDrag1=this._currentDrag1,t._currentDrag2=this._currentDrag2),this.particleSystem.isAnimationSheetEnabled&&(t._initialStartSpriteCellID=this._initialStartSpriteCellID,t._initialEndSpriteCellID=this._initialEndSpriteCellID),this.particleSystem.useRampGradients&&(t.remapData&&this.remapData?t.remapData.copyFrom(this.remapData):t.remapData=new u.f(0,0,0,0)),this._randomNoiseCoordinates1&&(t._randomNoiseCoordinates1?(t._randomNoiseCoordinates1.copyFrom(this._randomNoiseCoordinates1),t._randomNoiseCoordinates2.copyFrom(this._randomNoiseCoordinates2)):(t._randomNoiseCoordinates1=this._randomNoiseCoordinates1.clone(),t._randomNoiseCoordinates2=this._randomNoiseCoordinates2.clone()))},r._Count=0,r}();(function(r){r[r.ATTACHED=0]="ATTACHED",r[r.END=1]="END"})(Fr||(Fr={}));var Co=function(){function r(t){if(this.particleSystem=t,this.type=Fr.END,this.inheritDirection=!1,this.inheritedVelocityAmount=0,!t.emitter||!t.emitter.dispose){var e=R.a.GetClass("BABYLON.AbstractMesh");t.emitter=new e("SubemitterSystemEmitter",t.getScene())}t.onDisposeObservable.add(function(){t.emitter&&t.emitter.dispose&&t.emitter.dispose()})}return r.prototype.clone=function(){var t=this.particleSystem.emitter;t?t instanceof u.e?t=t.clone():t.getClassName().indexOf("Mesh")!==-1&&((t=new(R.a.GetClass("BABYLON.Mesh"))("",t.getScene())).isVisible=!1):t=new u.e;var e=new r(this.particleSystem.clone("",t));return e.particleSystem.name+="Clone",e.type=this.type,e.inheritDirection=this.inheritDirection,e.inheritedVelocityAmount=this.inheritedVelocityAmount,e.particleSystem._disposeEmitterOnDispose=!0,e.particleSystem.disposeOnStop=!0,e},r.prototype.serialize=function(){var t={};return t.type=this.type,t.inheritDirection=this.inheritDirection,t.inheritedVelocityAmount=this.inheritedVelocityAmount,t.particleSystem=this.particleSystem.serialize(),t},r._ParseParticleSystem=function(t,e,n){throw An.a.WarnImport("ParseParticle")},r.Parse=function(t,e,n){var i=t.particleSystem,o=new r(r._ParseParticleSystem(i,e,n));return o.type=t.type,o.inheritDirection=t.inheritDirection,o.inheritedVelocityAmount=t.inheritedVelocityAmount,o.particleSystem._isSubEmitter=!0,o},r.prototype.dispose=function(){this.particleSystem.dispose()},r}(),Nm=`
-varying vec2 vUV;
-varying vec4 vColor;
-uniform vec4 textureMask;
-uniform sampler2D diffuseSampler;
-#include<clipPlaneFragmentDeclaration>
-#include<imageProcessingDeclaration>
-#include<helperFunctions>
-#include<imageProcessingFunctions>
-#ifdef RAMPGRADIENT
-varying vec4 remapRanges;
-uniform sampler2D rampSampler;
-#endif
-void main(void) {
-#include<clipPlaneFragment>
-vec4 textureColor=texture2D(diffuseSampler,vUV);
-vec4 baseColor=(textureColor*textureMask+(vec4(1.,1.,1.,1.)-textureMask))*vColor;
-#ifdef RAMPGRADIENT
-float alpha=baseColor.a;
-float remappedColorIndex=clamp((alpha-remapRanges.x)/remapRanges.y,0.0,1.0);
-vec4 rampColor=texture2D(rampSampler,vec2(1.0-remappedColorIndex,0.));
-baseColor.rgb*=rampColor.rgb;
-
-float finalAlpha=baseColor.a;
-baseColor.a=clamp((alpha*rampColor.a-remapRanges.z)/remapRanges.w,0.0,1.0);
-#endif
-#ifdef BLENDMULTIPLYMODE
-float sourceAlpha=vColor.a*textureColor.a;
-baseColor.rgb=baseColor.rgb*sourceAlpha+vec3(1.0)*(1.0-sourceAlpha);
-#endif
-
-
-#ifdef IMAGEPROCESSINGPOSTPROCESS
-baseColor.rgb=toLinearSpace(baseColor.rgb);
-#else
-#ifdef IMAGEPROCESSING
-baseColor.rgb=toLinearSpace(baseColor.rgb);
-baseColor=applyImageProcessing(baseColor);
-#endif
-#endif
-gl_FragColor=baseColor;
-}`;ze.a.ShadersStore.particlesPixelShader=Nm;var wm=`
-attribute vec3 position;
-attribute vec4 color;
-attribute float angle;
-attribute vec2 size;
-#ifdef ANIMATESHEET
-attribute float cellIndex;
-#endif
-#ifndef BILLBOARD
-attribute vec3 direction;
-#endif
-#ifdef BILLBOARDSTRETCHED
-attribute vec3 direction;
-#endif
-#ifdef RAMPGRADIENT
-attribute vec4 remapData;
-#endif
-attribute vec2 offset;
-
-uniform mat4 view;
-uniform mat4 projection;
-uniform vec2 translationPivot;
-#ifdef ANIMATESHEET
-uniform vec3 particlesInfos;
-#endif
-
-varying vec2 vUV;
-varying vec4 vColor;
-varying vec3 vPositionW;
-#ifdef RAMPGRADIENT
-varying vec4 remapRanges;
-#endif
-#if defined(BILLBOARD) && !defined(BILLBOARDY) && !defined(BILLBOARDSTRETCHED)
-uniform mat4 invView;
-#endif
-#include<clipPlaneVertexDeclaration>
-#ifdef BILLBOARD
-uniform vec3 eyePosition;
-#endif
-vec3 rotate(vec3 yaxis,vec3 rotatedCorner) {
-vec3 xaxis=normalize(cross(vec3(0.,1.0,0.),yaxis));
-vec3 zaxis=normalize(cross(yaxis,xaxis));
-vec3 row0=vec3(xaxis.x,xaxis.y,xaxis.z);
-vec3 row1=vec3(yaxis.x,yaxis.y,yaxis.z);
-vec3 row2=vec3(zaxis.x,zaxis.y,zaxis.z);
-mat3 rotMatrix=mat3(row0,row1,row2);
-vec3 alignedCorner=rotMatrix*rotatedCorner;
-return position+alignedCorner;
-}
-#ifdef BILLBOARDSTRETCHED
-vec3 rotateAlign(vec3 toCamera,vec3 rotatedCorner) {
-vec3 normalizedToCamera=normalize(toCamera);
-vec3 normalizedCrossDirToCamera=normalize(cross(normalize(direction),normalizedToCamera));
-vec3 crossProduct=normalize(cross(normalizedToCamera,normalizedCrossDirToCamera));
-vec3 row0=vec3(normalizedCrossDirToCamera.x,normalizedCrossDirToCamera.y,normalizedCrossDirToCamera.z);
-vec3 row1=vec3(crossProduct.x,crossProduct.y,crossProduct.z);
-vec3 row2=vec3(normalizedToCamera.x,normalizedToCamera.y,normalizedToCamera.z);
-mat3 rotMatrix=mat3(row0,row1,row2);
-vec3 alignedCorner=rotMatrix*rotatedCorner;
-return position+alignedCorner;
-}
-#endif
-void main(void) {
-vec2 cornerPos;
-cornerPos=(vec2(offset.x-0.5,offset.y-0.5)-translationPivot)*size+translationPivot;
-#ifdef BILLBOARD
-
-vec3 rotatedCorner;
-#ifdef BILLBOARDY
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.z=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.y=0.;
-vec3 yaxis=position-eyePosition;
-yaxis.y=0.;
-vPositionW=rotate(normalize(yaxis),rotatedCorner);
-vec3 viewPos=(view*vec4(vPositionW,1.0)).xyz;
-#elif defined(BILLBOARDSTRETCHED)
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.y=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.z=0.;
-vec3 toCamera=position-eyePosition;
-vPositionW=rotateAlign(toCamera,rotatedCorner);
-vec3 viewPos=(view*vec4(vPositionW,1.0)).xyz;
-#else
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.y=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.z=0.;
-vec3 viewPos=(view*vec4(position,1.0)).xyz+rotatedCorner;
-vPositionW=(invView*vec4(viewPos,1)).xyz;
-#endif
-#ifdef RAMPGRADIENT
-remapRanges=remapData;
-#endif
-
-gl_Position=projection*vec4(viewPos,1.0);
-#else
-
-vec3 rotatedCorner;
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.z=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.y=0.;
-vec3 yaxis=normalize(direction);
-vPositionW=rotate(yaxis,rotatedCorner);
-gl_Position=projection*view*vec4(vPositionW,1.0);
-#endif
-vColor=color;
-#ifdef ANIMATESHEET
-float rowOffset=floor(cellIndex*particlesInfos.z);
-float columnOffset=cellIndex-rowOffset/particlesInfos.z;
-vec2 uvScale=particlesInfos.xy;
-vec2 uvOffset=vec2(offset.x ,1.0-offset.y);
-vUV=(uvOffset+vec2(columnOffset,rowOffset))*uvScale;
-#else
-vUV=offset;
-#endif
-
-#if defined(CLIPPLANE) || defined(CLIPPLANE2) || defined(CLIPPLANE3) || defined(CLIPPLANE4) || defined(CLIPPLANE5) || defined(CLIPPLANE6)
-vec4 worldPos=vec4(vPositionW,1.0);
-#endif
-#include<clipPlaneVertex>
-}`;ze.a.ShadersStore.particlesVertexShader=wm;var ln=function(r){function t(e,n,i,o,a,s){o===void 0&&(o=null),a===void 0&&(a=!1),s===void 0&&(s=.01);var d=r.call(this,e)||this;return d._inheritedVelocityOffset=new u.e,d.onDisposeObservable=new C.c,d.onStoppedObservable=new C.c,d._particles=new Array,d._stockParticles=new Array,d._newPartsExcess=0,d._vertexBuffers={},d._scaledColorStep=new M.b(0,0,0,0),d._colorDiff=new M.b(0,0,0,0),d._scaledDirection=u.e.Zero(),d._scaledGravity=u.e.Zero(),d._currentRenderId=-1,d._useInstancing=!1,d._started=!1,d._stopped=!1,d._actualFrame=0,d._currentEmitRate1=0,d._currentEmitRate2=0,d._currentStartSize1=0,d._currentStartSize2=0,d._rawTextureWidth=256,d._useRampGradients=!1,d._disposeEmitterOnDispose=!1,d.isLocal=!1,d._onBeforeDrawParticlesObservable=null,d.recycleParticle=function(p){var b=d._particles.pop();b!==p&&b.copyTo(p),d._stockParticles.push(b)},d._createParticle=function(){var p;if(d._stockParticles.length!==0?(p=d._stockParticles.pop())._reset():p=new xd(d),d._subEmitters&&d._subEmitters.length>0){var b=d._subEmitters[Math.floor(Math.random()*d._subEmitters.length)];p._attachedSubEmitters=[],b.forEach(function(P){if(P.type===Fr.ATTACHED){var O=P.clone();p._attachedSubEmitters.push(O),O.particleSystem.start()}})}return p},d._emitFromParticle=function(p){if(d._subEmitters&&d._subEmitters.length!==0){var b=Math.floor(Math.random()*d._subEmitters.length);d._subEmitters[b].forEach(function(P){if(P.type===Fr.END){var O=P.clone();p._inheritParticleInfoToSubEmitter(O),O.particleSystem._rootParticleSystem=d,d.activeSubSystems.push(O.particleSystem),O.particleSystem.start()}})}},d._capacity=n,d._epsilon=s,d._isAnimationSheetEnabled=a,i&&i.getClassName()!=="Scene"?(d._engine=i,d.defaultProjectionMatrix=u.a.PerspectiveFovLH(.8,1,.1,100)):(d._scene=i||te.a.LastCreatedScene,d._engine=d._scene.getEngine(),d.uniqueId=d._scene.getUniqueId(),d._scene.particleSystems.push(d)),d._engine.getCaps().vertexArrayObject&&(d._vertexArrayObject=null),d._attachImageProcessingConfiguration(null),d._customEffect={0:o},d._useInstancing=d._engine.getCaps().instancedArrays,d._createIndexBuffer(),d._createVertexBuffers(),d.particleEmitterType=new Nr,d.updateFunction=function(p){var b=null,P=null;d.noiseTexture&&(b=d.noiseTexture.getSize(),P=d.noiseTexture.getContent());for(var O,B=function(){O=p[F];var z=d._scaledUpdateSpeed,J=O.age;if(O.age+=z,O.age>O.lifeTime){var ie=O.age-J;z=(O.lifeTime-J)*z/ie,O.age=O.lifeTime}var se=O.age/O.lifeTime;d._colorGradients&&d._colorGradients.length>0?In.GetCurrentGradient(se,d._colorGradients,function(Ae,Ee,Se){Ae!==O._currentColorGradient&&(O._currentColor1.copyFrom(O._currentColor2),Ee.getColorToRef(O._currentColor2),O._currentColorGradient=Ae),M.b.LerpToRef(O._currentColor1,O._currentColor2,Se,O.color)}):(O.colorStep.scaleToRef(z,d._scaledColorStep),O.color.addInPlace(d._scaledColorStep),O.color.a<0&&(O.color.a=0)),d._angularSpeedGradients&&d._angularSpeedGradients.length>0&&In.GetCurrentGradient(se,d._angularSpeedGradients,function(Ae,Ee,Se){Ae!==O._currentAngularSpeedGradient&&(O._currentAngularSpeed1=O._currentAngularSpeed2,O._currentAngularSpeed2=Ee.getFactor(),O._currentAngularSpeedGradient=Ae),O.angularSpeed=$.a.Lerp(O._currentAngularSpeed1,O._currentAngularSpeed2,Se)}),O.angle+=O.angularSpeed*z;var ce=z;if(d._velocityGradients&&d._velocityGradients.length>0&&In.GetCurrentGradient(se,d._velocityGradients,function(Ae,Ee,Se){Ae!==O._currentVelocityGradient&&(O._currentVelocity1=O._currentVelocity2,O._currentVelocity2=Ee.getFactor(),O._currentVelocityGradient=Ae),ce*=$.a.Lerp(O._currentVelocity1,O._currentVelocity2,Se)}),O.direction.scaleToRef(ce,d._scaledDirection),d._limitVelocityGradients&&d._limitVelocityGradients.length>0&&In.GetCurrentGradient(se,d._limitVelocityGradients,function(Ae,Ee,Se){Ae!==O._currentLimitVelocityGradient&&(O._currentLimitVelocity1=O._currentLimitVelocity2,O._currentLimitVelocity2=Ee.getFactor(),O._currentLimitVelocityGradient=Ae);var Le=$.a.Lerp(O._currentLimitVelocity1,O._currentLimitVelocity2,Se);O.direction.length()>Le&&O.direction.scaleInPlace(d.limitVelocityDamping)}),d._dragGradients&&d._dragGradients.length>0&&In.GetCurrentGradient(se,d._dragGradients,function(Ae,Ee,Se){Ae!==O._currentDragGradient&&(O._currentDrag1=O._currentDrag2,O._currentDrag2=Ee.getFactor(),O._currentDragGradient=Ae);var Le=$.a.Lerp(O._currentDrag1,O._currentDrag2,Se);d._scaledDirection.scaleInPlace(1-Le)}),d.isLocal&&O._localPosition?(O._localPosition.addInPlace(d._scaledDirection),u.e.TransformCoordinatesToRef(O._localPosition,d._emitterWorldMatrix,O.position)):O.position.addInPlace(d._scaledDirection),P&&b&&O._randomNoiseCoordinates1){var ue=d._fetchR(O._randomNoiseCoordinates1.x,O._randomNoiseCoordinates1.y,b.width,b.height,P),fe=d._fetchR(O._randomNoiseCoordinates1.z,O._randomNoiseCoordinates2.x,b.width,b.height,P),ve=d._fetchR(O._randomNoiseCoordinates2.y,O._randomNoiseCoordinates2.z,b.width,b.height,P),Te=u.c.Vector3[0],Re=u.c.Vector3[1];Te.copyFromFloats((2*ue-1)*d.noiseStrength.x,(2*fe-1)*d.noiseStrength.y,(2*ve-1)*d.noiseStrength.z),Te.scaleToRef(z,Re),O.direction.addInPlace(Re)}if(d.gravity.scaleToRef(z,d._scaledGravity),O.direction.addInPlace(d._scaledGravity),d._sizeGradients&&d._sizeGradients.length>0&&In.GetCurrentGradient(se,d._sizeGradients,function(Ae,Ee,Se){Ae!==O._currentSizeGradient&&(O._currentSize1=O._currentSize2,O._currentSize2=Ee.getFactor(),O._currentSizeGradient=Ae),O.size=$.a.Lerp(O._currentSize1,O._currentSize2,Se)}),d._useRampGradients&&(d._colorRemapGradients&&d._colorRemapGradients.length>0&&In.GetCurrentGradient(se,d._colorRemapGradients,function(Ae,Ee,Se){var Le=$.a.Lerp(Ae.factor1,Ee.factor1,Se),xe=$.a.Lerp(Ae.factor2,Ee.factor2,Se);O.remapData.x=Le,O.remapData.y=xe-Le}),d._alphaRemapGradients&&d._alphaRemapGradients.length>0&&In.GetCurrentGradient(se,d._alphaRemapGradients,function(Ae,Ee,Se){var Le=$.a.Lerp(Ae.factor1,Ee.factor1,Se),xe=$.a.Lerp(Ae.factor2,Ee.factor2,Se);O.remapData.z=Le,O.remapData.w=xe-Le})),d._isAnimationSheetEnabled&&O.updateCellIndex(),O._inheritParticleInfoToSubEmitters(),O.age>=O.lifeTime)return d._emitFromParticle(O),O._attachedSubEmitters&&(O._attachedSubEmitters.forEach(function(Ae){Ae.particleSystem.disposeOnStop=!0,Ae.particleSystem.stop()}),O._attachedSubEmitters=null),d.recycleParticle(O),F--,"continue"},F=0;F<p.length;F++)B()},d}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"onDispose",{set:function(e){this._onDisposeObserver&&this.onDisposeObservable.remove(this._onDisposeObserver),this._onDisposeObserver=this.onDisposeObservable.add(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"useRampGradients",{get:function(){return this._useRampGradients},set:function(e){this._useRampGradients!==e&&(this._useRampGradients=e,this._resetEffect())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"particles",{get:function(){return this._particles},enumerable:!1,configurable:!0}),t.prototype.getActiveCount=function(){return this._particles.length},t.prototype.getClassName=function(){return"ParticleSystem"},t.prototype.isStopping=function(){return this._stopped&&this.isAlive()},t.prototype.getCustomEffect=function(e){var n;return e===void 0&&(e=0),(n=this._customEffect[e])!==null&&n!==void 0?n:this._customEffect[0]},t.prototype.setCustomEffect=function(e,n){n===void 0&&(n=0),this._customEffect[n]=e},Object.defineProperty(t.prototype,"onBeforeDrawParticlesObservable",{get:function(){return this._onBeforeDrawParticlesObservable||(this._onBeforeDrawParticlesObservable=new C.c),this._onBeforeDrawParticlesObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vertexShaderName",{get:function(){return"particles"},enumerable:!1,configurable:!0}),t.prototype._addFactorGradient=function(e,n,i,o){var a=new Ic(n,i,o);e.push(a),e.sort(function(s,d){return s.gradient<d.gradient?-1:s.gradient>d.gradient?1:0})},t.prototype._removeFactorGradient=function(e,n){if(e)for(var i=0,o=0,a=e;o<a.length;o++){if(a[o].gradient===n){e.splice(i,1);break}i++}},t.prototype.addLifeTimeGradient=function(e,n,i){return this._lifeTimeGradients||(this._lifeTimeGradients=[]),this._addFactorGradient(this._lifeTimeGradients,e,n,i),this},t.prototype.removeLifeTimeGradient=function(e){return this._removeFactorGradient(this._lifeTimeGradients,e),this},t.prototype.addSizeGradient=function(e,n,i){return this._sizeGradients||(this._sizeGradients=[]),this._addFactorGradient(this._sizeGradients,e,n,i),this},t.prototype.removeSizeGradient=function(e){return this._removeFactorGradient(this._sizeGradients,e),this},t.prototype.addColorRemapGradient=function(e,n,i){return this._colorRemapGradients||(this._colorRemapGradients=[]),this._addFactorGradient(this._colorRemapGradients,e,n,i),this},t.prototype.removeColorRemapGradient=function(e){return this._removeFactorGradient(this._colorRemapGradients,e),this},t.prototype.addAlphaRemapGradient=function(e,n,i){return this._alphaRemapGradients||(this._alphaRemapGradients=[]),this._addFactorGradient(this._alphaRemapGradients,e,n,i),this},t.prototype.removeAlphaRemapGradient=function(e){return this._removeFactorGradient(this._alphaRemapGradients,e),this},t.prototype.addAngularSpeedGradient=function(e,n,i){return this._angularSpeedGradients||(this._angularSpeedGradients=[]),this._addFactorGradient(this._angularSpeedGradients,e,n,i),this},t.prototype.removeAngularSpeedGradient=function(e){return this._removeFactorGradient(this._angularSpeedGradients,e),this},t.prototype.addVelocityGradient=function(e,n,i){return this._velocityGradients||(this._velocityGradients=[]),this._addFactorGradient(this._velocityGradients,e,n,i),this},t.prototype.removeVelocityGradient=function(e){return this._removeFactorGradient(this._velocityGradients,e),this},t.prototype.addLimitVelocityGradient=function(e,n,i){return this._limitVelocityGradients||(this._limitVelocityGradients=[]),this._addFactorGradient(this._limitVelocityGradients,e,n,i),this},t.prototype.removeLimitVelocityGradient=function(e){return this._removeFactorGradient(this._limitVelocityGradients,e),this},t.prototype.addDragGradient=function(e,n,i){return this._dragGradients||(this._dragGradients=[]),this._addFactorGradient(this._dragGradients,e,n,i),this},t.prototype.removeDragGradient=function(e){return this._removeFactorGradient(this._dragGradients,e),this},t.prototype.addEmitRateGradient=function(e,n,i){return this._emitRateGradients||(this._emitRateGradients=[]),this._addFactorGradient(this._emitRateGradients,e,n,i),this},t.prototype.removeEmitRateGradient=function(e){return this._removeFactorGradient(this._emitRateGradients,e),this},t.prototype.addStartSizeGradient=function(e,n,i){return this._startSizeGradients||(this._startSizeGradients=[]),this._addFactorGradient(this._startSizeGradients,e,n,i),this},t.prototype.removeStartSizeGradient=function(e){return this._removeFactorGradient(this._startSizeGradients,e),this},t.prototype._createRampGradientTexture=function(){if(this._rampGradients&&this._rampGradients.length&&!this._rampGradientsTexture&&this._scene){for(var e=new Uint8Array(4*this._rawTextureWidth),n=M.c.Color3[0],i=0;i<this._rawTextureWidth;i++){var o=i/this._rawTextureWidth;In.GetCurrentGradient(o,this._rampGradients,function(a,s,d){M.a.LerpToRef(a.color,s.color,d,n),e[4*i]=255*n.r,e[4*i+1]=255*n.g,e[4*i+2]=255*n.b,e[4*i+3]=255})}this._rampGradientsTexture=ni.CreateRGBATexture(e,this._rawTextureWidth,1,this._scene,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE)}},t.prototype.getRampGradients=function(){return this._rampGradients},t.prototype.forceRefreshGradients=function(){this._syncRampGradientTexture()},t.prototype._syncRampGradientTexture=function(){this._rampGradients&&(this._rampGradients.sort(function(e,n){return e.gradient<n.gradient?-1:e.gradient>n.gradient?1:0}),this._rampGradientsTexture&&(this._rampGradientsTexture.dispose(),this._rampGradientsTexture=null),this._createRampGradientTexture())},t.prototype.addRampGradient=function(e,n){this._rampGradients||(this._rampGradients=[]);var i=new Pd(e,n);return this._rampGradients.push(i),this._syncRampGradientTexture(),this},t.prototype.removeRampGradient=function(e){return this._removeGradientAndTexture(e,this._rampGradients,this._rampGradientsTexture),this._rampGradientsTexture=null,this._rampGradients&&this._rampGradients.length>0&&this._createRampGradientTexture(),this},t.prototype.addColorGradient=function(e,n,i){this._colorGradients||(this._colorGradients=[]);var o=new Mc(e,n,i);return this._colorGradients.push(o),this._colorGradients.sort(function(a,s){return a.gradient<s.gradient?-1:a.gradient>s.gradient?1:0}),this},t.prototype.removeColorGradient=function(e){if(!this._colorGradients)return this;for(var n=0,i=0,o=this._colorGradients;i<o.length;i++){if(o[i].gradient===e){this._colorGradients.splice(n,1);break}n++}return this},t.prototype._fetchR=function(e,n,i,o,a){return a[4*(((e=.5*Math.abs(e)+.5)*i%i|0)+((n=.5*Math.abs(n)+.5)*o%o|0)*i)]/255},t.prototype._reset=function(){this._resetEffect()},t.prototype._resetEffect=function(){this._vertexBuffer&&(this._vertexBuffer.dispose(),this._vertexBuffer=null),this._spriteBuffer&&(this._spriteBuffer.dispose(),this._spriteBuffer=null),this._vertexArrayObject&&(this._engine.releaseVertexArrayObject(this._vertexArrayObject),this._vertexArrayObject=null),this._createVertexBuffers()},t.prototype._createVertexBuffers=function(){this._vertexBufferSize=this._useInstancing?10:12,this._isAnimationSheetEnabled&&(this._vertexBufferSize+=1),this._isBillboardBased&&this.billboardMode!==t.BILLBOARDMODE_STRETCHED||(this._vertexBufferSize+=3),this._useRampGradients&&(this._vertexBufferSize+=4);var e=this._engine;this._vertexData=new Float32Array(this._capacity*this._vertexBufferSize*(this._useInstancing?1:4)),this._vertexBuffer=new Oe.a(e,this._vertexData,!0,this._vertexBufferSize);var n=0,i=this._vertexBuffer.createVertexBuffer(Oe.b.PositionKind,n,3,this._vertexBufferSize,this._useInstancing);this._vertexBuffers[Oe.b.PositionKind]=i,n+=3;var o=this._vertexBuffer.createVertexBuffer(Oe.b.ColorKind,n,4,this._vertexBufferSize,this._useInstancing);this._vertexBuffers[Oe.b.ColorKind]=o,n+=4;var a=this._vertexBuffer.createVertexBuffer("angle",n,1,this._vertexBufferSize,this._useInstancing);this._vertexBuffers.angle=a,n+=1;var s,d=this._vertexBuffer.createVertexBuffer("size",n,2,this._vertexBufferSize,this._useInstancing);if(this._vertexBuffers.size=d,n+=2,this._isAnimationSheetEnabled){var p=this._vertexBuffer.createVertexBuffer("cellIndex",n,1,this._vertexBufferSize,this._useInstancing);this._vertexBuffers.cellIndex=p,n+=1}if(!this._isBillboardBased||this.billboardMode===t.BILLBOARDMODE_STRETCHED){var b=this._vertexBuffer.createVertexBuffer("direction",n,3,this._vertexBufferSize,this._useInstancing);this._vertexBuffers.direction=b,n+=3}if(this._useRampGradients){var P=this._vertexBuffer.createVertexBuffer("remapData",n,4,this._vertexBufferSize,this._useInstancing);this._vertexBuffers.remapData=P,n+=4}if(this._useInstancing){var O=new Float32Array([0,0,1,0,1,1,0,1]);this._spriteBuffer=new Oe.a(e,O,!1,2),s=this._spriteBuffer.createVertexBuffer("offset",0,2)}else s=this._vertexBuffer.createVertexBuffer("offset",n,2,this._vertexBufferSize,this._useInstancing),n+=2;this._vertexBuffers.offset=s},t.prototype._createIndexBuffer=function(){if(!this._useInstancing){for(var e=[],n=0,i=0;i<this._capacity;i++)e.push(n),e.push(n+1),e.push(n+2),e.push(n),e.push(n+2),e.push(n+3),n+=4;this._indexBuffer=this._engine.createIndexBuffer(e)}},t.prototype.getCapacity=function(){return this._capacity},t.prototype.isAlive=function(){return this._alive},t.prototype.isStarted=function(){return this._started},t.prototype._prepareSubEmitterInternalArray=function(){var e=this;this._subEmitters=new Array,this.subEmitters&&this.subEmitters.forEach(function(n){n instanceof t?e._subEmitters.push([new Co(n)]):n instanceof Co?e._subEmitters.push([n]):n instanceof Array&&e._subEmitters.push(n)})},t.prototype.start=function(e){var n,i=this;if(e===void 0&&(e=this.startDelay),!this.targetStopDuration&&this._hasTargetStopDurationDependantGradient())throw"Particle system started with a targetStopDuration dependant gradient (eg. startSizeGradients) but no targetStopDuration set";if(e)setTimeout(function(){i.start(0)},e);else{if(this._prepareSubEmitterInternalArray(),this._started=!0,this._stopped=!1,this._actualFrame=0,this._subEmitters&&this._subEmitters.length!=0&&(this.activeSubSystems=new Array),this._emitRateGradients&&(this._emitRateGradients.length>0&&(this._currentEmitRateGradient=this._emitRateGradients[0],this._currentEmitRate1=this._currentEmitRateGradient.getFactor(),this._currentEmitRate2=this._currentEmitRate1),this._emitRateGradients.length>1&&(this._currentEmitRate2=this._emitRateGradients[1].getFactor())),this._startSizeGradients&&(this._startSizeGradients.length>0&&(this._currentStartSizeGradient=this._startSizeGradients[0],this._currentStartSize1=this._currentStartSizeGradient.getFactor(),this._currentStartSize2=this._currentStartSize1),this._startSizeGradients.length>1&&(this._currentStartSize2=this._startSizeGradients[1].getFactor())),this.preWarmCycles){((n=this.emitter)===null||n===void 0?void 0:n.getClassName().indexOf("Mesh"))!==-1&&this.emitter.computeWorldMatrix(!0);var o=this.noiseTexture;if(o&&o.onGeneratedObservable)o.onGeneratedObservable.addOnce(function(){setTimeout(function(){for(var s=0;s<i.preWarmCycles;s++)i.animate(!0),o.render()})});else for(var a=0;a<this.preWarmCycles;a++)this.animate(!0)}this.beginAnimationOnStart&&this.animations&&this.animations.length>0&&this._scene&&this._scene.beginAnimation(this,this.beginAnimationFrom,this.beginAnimationTo,this.beginAnimationLoop)}},t.prototype.stop=function(e){e===void 0&&(e=!0),this._stopped||(this.onStoppedObservable.notifyObservers(this),this._stopped=!0,e&&this._stopSubEmitters())},t.prototype.reset=function(){this._stockParticles=[],this._particles=[]},t.prototype._appendParticleVertex=function(e,n,i,o){var a=e*this._vertexBufferSize;if(this._vertexData[a++]=n.position.x+this.worldOffset.x,this._vertexData[a++]=n.position.y+this.worldOffset.y,this._vertexData[a++]=n.position.z+this.worldOffset.z,this._vertexData[a++]=n.color.r,this._vertexData[a++]=n.color.g,this._vertexData[a++]=n.color.b,this._vertexData[a++]=n.color.a,this._vertexData[a++]=n.angle,this._vertexData[a++]=n.scale.x*n.size,this._vertexData[a++]=n.scale.y*n.size,this._isAnimationSheetEnabled&&(this._vertexData[a++]=n.cellIndex),this._isBillboardBased)this.billboardMode===t.BILLBOARDMODE_STRETCHED&&(this._vertexData[a++]=n.direction.x,this._vertexData[a++]=n.direction.y,this._vertexData[a++]=n.direction.z);else if(n._initialDirection){var s=n._initialDirection;this.isLocal&&(u.e.TransformNormalToRef(s,this._emitterWorldMatrix,u.c.Vector3[0]),s=u.c.Vector3[0]),s.x===0&&s.z===0&&(s.x=.001),this._vertexData[a++]=s.x,this._vertexData[a++]=s.y,this._vertexData[a++]=s.z}else{var d=n.direction;this.isLocal&&(u.e.TransformNormalToRef(d,this._emitterWorldMatrix,u.c.Vector3[0]),d=u.c.Vector3[0]),d.x===0&&d.z===0&&(d.x=.001),this._vertexData[a++]=d.x,this._vertexData[a++]=d.y,this._vertexData[a++]=d.z}this._useRampGradients&&n.remapData&&(this._vertexData[a++]=n.remapData.x,this._vertexData[a++]=n.remapData.y,this._vertexData[a++]=n.remapData.z,this._vertexData[a++]=n.remapData.w),this._useInstancing||(this._isAnimationSheetEnabled&&(i===0?i=this._epsilon:i===1&&(i=1-this._epsilon),o===0?o=this._epsilon:o===1&&(o=1-this._epsilon)),this._vertexData[a++]=i,this._vertexData[a++]=o)},t.prototype._stopSubEmitters=function(){this.activeSubSystems&&(this.activeSubSystems.forEach(function(e){e.stop(!0)}),this.activeSubSystems=new Array)},t.prototype._removeFromRoot=function(){if(this._rootParticleSystem){var e=this._rootParticleSystem.activeSubSystems.indexOf(this);e!==-1&&this._rootParticleSystem.activeSubSystems.splice(e,1),this._rootParticleSystem=null}},t.prototype._update=function(e){var n,i=this;if(this._alive=this._particles.length>0,this.emitter.position){var o=this.emitter;this._emitterWorldMatrix=o.getWorldMatrix()}else{var a=this.emitter;this._emitterWorldMatrix=u.a.Translation(a.x,a.y,a.z)}this.updateFunction(this._particles);for(var s,d=function(){if(p._particles.length===p._capacity)return"break";if(n=p._createParticle(),p._particles.push(n),p.targetStopDuration&&p._lifeTimeGradients&&p._lifeTimeGradients.length>0){var P=$.a.Clamp(p._actualFrame/p.targetStopDuration);In.GetCurrentGradient(P,p._lifeTimeGradients,function(F,z){var J=F,ie=z,se=J.getFactor(),ce=ie.getFactor(),ue=(P-J.gradient)/(ie.gradient-J.gradient);n.lifeTime=$.a.Lerp(se,ce,ue)})}else n.lifeTime=$.a.RandomRange(p.minLifeTime,p.maxLifeTime);var O=$.a.RandomRange(p.minEmitPower,p.maxEmitPower);if(p.startPositionFunction?p.startPositionFunction(p._emitterWorldMatrix,n.position,n,p.isLocal):p.particleEmitterType.startPositionFunction(p._emitterWorldMatrix,n.position,n,p.isLocal),p.isLocal&&(n._localPosition?n._localPosition.copyFrom(n.position):n._localPosition=n.position.clone(),u.e.TransformCoordinatesToRef(n._localPosition,p._emitterWorldMatrix,n.position)),p.startDirectionFunction?p.startDirectionFunction(p._emitterWorldMatrix,n.direction,n,p.isLocal):p.particleEmitterType.startDirectionFunction(p._emitterWorldMatrix,n.direction,n,p.isLocal),O===0?n._initialDirection?n._initialDirection.copyFrom(n.direction):n._initialDirection=n.direction.clone():n._initialDirection=null,n.direction.scaleInPlace(O),p._sizeGradients&&p._sizeGradients.length!==0?(n._currentSizeGradient=p._sizeGradients[0],n._currentSize1=n._currentSizeGradient.getFactor(),n.size=n._currentSize1,p._sizeGradients.length>1?n._currentSize2=p._sizeGradients[1].getFactor():n._currentSize2=n._currentSize1):n.size=$.a.RandomRange(p.minSize,p.maxSize),n.scale.copyFromFloats($.a.RandomRange(p.minScaleX,p.maxScaleX),$.a.RandomRange(p.minScaleY,p.maxScaleY)),p._startSizeGradients&&p._startSizeGradients[0]&&p.targetStopDuration){var B=p._actualFrame/p.targetStopDuration;In.GetCurrentGradient(B,p._startSizeGradients,function(F,z,J){F!==i._currentStartSizeGradient&&(i._currentStartSize1=i._currentStartSize2,i._currentStartSize2=z.getFactor(),i._currentStartSizeGradient=F);var ie=$.a.Lerp(i._currentStartSize1,i._currentStartSize2,J);n.scale.scaleInPlace(ie)})}p._angularSpeedGradients&&p._angularSpeedGradients.length!==0?(n._currentAngularSpeedGradient=p._angularSpeedGradients[0],n.angularSpeed=n._currentAngularSpeedGradient.getFactor(),n._currentAngularSpeed1=n.angularSpeed,p._angularSpeedGradients.length>1?n._currentAngularSpeed2=p._angularSpeedGradients[1].getFactor():n._currentAngularSpeed2=n._currentAngularSpeed1):n.angularSpeed=$.a.RandomRange(p.minAngularSpeed,p.maxAngularSpeed),n.angle=$.a.RandomRange(p.minInitialRotation,p.maxInitialRotation),p._velocityGradients&&p._velocityGradients.length>0&&(n._currentVelocityGradient=p._velocityGradients[0],n._currentVelocity1=n._currentVelocityGradient.getFactor(),p._velocityGradients.length>1?n._currentVelocity2=p._velocityGradients[1].getFactor():n._currentVelocity2=n._currentVelocity1),p._limitVelocityGradients&&p._limitVelocityGradients.length>0&&(n._currentLimitVelocityGradient=p._limitVelocityGradients[0],n._currentLimitVelocity1=n._currentLimitVelocityGradient.getFactor(),p._limitVelocityGradients.length>1?n._currentLimitVelocity2=p._limitVelocityGradients[1].getFactor():n._currentLimitVelocity2=n._currentLimitVelocity1),p._dragGradients&&p._dragGradients.length>0&&(n._currentDragGradient=p._dragGradients[0],n._currentDrag1=n._currentDragGradient.getFactor(),p._dragGradients.length>1?n._currentDrag2=p._dragGradients[1].getFactor():n._currentDrag2=n._currentDrag1),p._colorGradients&&p._colorGradients.length!==0?(n._currentColorGradient=p._colorGradients[0],n._currentColorGradient.getColorToRef(n.color),n._currentColor1.copyFrom(n.color),p._colorGradients.length>1?p._colorGradients[1].getColorToRef(n._currentColor2):n._currentColor2.copyFrom(n.color)):(s=$.a.RandomRange(0,1),M.b.LerpToRef(p.color1,p.color2,s,n.color),p.colorDead.subtractToRef(n.color,p._colorDiff),p._colorDiff.scaleToRef(1/n.lifeTime,n.colorStep)),p._isAnimationSheetEnabled&&(n._initialStartSpriteCellID=p.startSpriteCellID,n._initialEndSpriteCellID=p.endSpriteCellID),n.direction.addInPlace(p._inheritedVelocityOffset),p._useRampGradients&&(n.remapData=new u.f(0,1,0,1)),p.noiseTexture&&(n._randomNoiseCoordinates1?(n._randomNoiseCoordinates1.copyFromFloats(Math.random(),Math.random(),Math.random()),n._randomNoiseCoordinates2.copyFromFloats(Math.random(),Math.random(),Math.random())):(n._randomNoiseCoordinates1=new u.e(Math.random(),Math.random(),Math.random()),n._randomNoiseCoordinates2=new u.e(Math.random(),Math.random(),Math.random()))),n._inheritParticleInfoToSubEmitters()},p=this,b=0;b<e&&d()!=="break";b++);},t._GetAttributeNamesOrOptions=function(e,n,i){e===void 0&&(e=!1),n===void 0&&(n=!1),i===void 0&&(i=!1);var o=[Oe.b.PositionKind,Oe.b.ColorKind,"angle","offset","size"];return e&&o.push("cellIndex"),n||o.push("direction"),i&&o.push("remapData"),o},t._GetEffectCreationOptions=function(e){e===void 0&&(e=!1);var n=["invView","view","projection","vClipPlane","vClipPlane2","vClipPlane3","vClipPlane4","vClipPlane5","vClipPlane6","textureMask","translationPivot","eyePosition"];return e&&n.push("particlesInfos"),n},t.prototype.fillDefines=function(e,n){if(this._scene&&(this._scene.clipPlane&&e.push("#define CLIPPLANE"),this._scene.clipPlane2&&e.push("#define CLIPPLANE2"),this._scene.clipPlane3&&e.push("#define CLIPPLANE3"),this._scene.clipPlane4&&e.push("#define CLIPPLANE4"),this._scene.clipPlane5&&e.push("#define CLIPPLANE5"),this._scene.clipPlane6&&e.push("#define CLIPPLANE6")),this._isAnimationSheetEnabled&&e.push("#define ANIMATESHEET"),n===t.BLENDMODE_MULTIPLY&&e.push("#define BLENDMULTIPLYMODE"),this._useRampGradients&&e.push("#define RAMPGRADIENT"),this._isBillboardBased)switch(e.push("#define BILLBOARD"),this.billboardMode){case t.BILLBOARDMODE_Y:e.push("#define BILLBOARDY");break;case t.BILLBOARDMODE_STRETCHED:e.push("#define BILLBOARDSTRETCHED");break;case t.BILLBOARDMODE_ALL:e.push("#define BILLBOARDMODE_ALL")}this._imageProcessingConfiguration&&(this._imageProcessingConfiguration.prepareDefines(this._imageProcessingConfigurationDefines),e.push(this._imageProcessingConfigurationDefines.toString()))},t.prototype.fillUniformsAttributesAndSamplerNames=function(e,n,i){n.push.apply(n,t._GetAttributeNamesOrOptions(this._isAnimationSheetEnabled,this._isBillboardBased&&this.billboardMode!==t.BILLBOARDMODE_STRETCHED,this._useRampGradients)),e.push.apply(e,t._GetEffectCreationOptions(this._isAnimationSheetEnabled)),i.push("diffuseSampler","rampSampler"),this._imageProcessingConfiguration&&(yn.a.PrepareUniforms(e,this._imageProcessingConfigurationDefines),yn.a.PrepareSamplers(i,this._imageProcessingConfigurationDefines))},t.prototype._getEffect=function(e){var n=this.getCustomEffect(e);if(n)return n;var i=[];this.fillDefines(i,e);var o=i.join(`
-`);if(this._cachedDefines!==o){this._cachedDefines=o;var a=[],s=[],d=[];this.fillUniformsAttributesAndSamplerNames(s,a,d),this._effect=this._engine.createEffect("particles",a,s,d,o)}return this._effect},t.prototype.animate=function(e){var n,i=this;if(e===void 0&&(e=!1),this._started){if(!e&&this._scene){if(!this.isReady()||this._currentRenderId===this._scene.getFrameId())return;this._currentRenderId=this._scene.getFrameId()}var o;if(this._scaledUpdateSpeed=this.updateSpeed*(e?this.preWarmStepOffset:((n=this._scene)===null||n===void 0?void 0:n.getAnimationRatio())||1),this.manualEmitCount>-1)o=this.manualEmitCount,this._newPartsExcess=0,this.manualEmitCount=0;else{var a=this.emitRate;if(this._emitRateGradients&&this._emitRateGradients.length>0&&this.targetStopDuration){var s=this._actualFrame/this.targetStopDuration;In.GetCurrentGradient(s,this._emitRateGradients,function(P,O,B){P!==i._currentEmitRateGradient&&(i._currentEmitRate1=i._currentEmitRate2,i._currentEmitRate2=O.getFactor(),i._currentEmitRateGradient=P),a=$.a.Lerp(i._currentEmitRate1,i._currentEmitRate2,B)})}o=a*this._scaledUpdateSpeed>>0,this._newPartsExcess+=a*this._scaledUpdateSpeed-o}if(this._newPartsExcess>1&&(o+=this._newPartsExcess>>0,this._newPartsExcess-=this._newPartsExcess>>0),this._alive=!1,this._stopped?o=0:(this._actualFrame+=this._scaledUpdateSpeed,this.targetStopDuration&&this._actualFrame>=this.targetStopDuration&&this.stop()),this._update(o),this._stopped&&(this._alive||(this._started=!1,this.onAnimationEnd&&this.onAnimationEnd(),this.disposeOnStop&&this._scene&&this._scene._toBeDisposed.push(this))),!e){for(var d=0,p=0;p<this._particles.length;p++){var b=this._particles[p];this._appendParticleVertices(d,b),d+=this._useInstancing?1:4}this._vertexBuffer&&this._vertexBuffer.update(this._vertexData)}this.manualEmitCount===0&&this.disposeOnStop&&this.stop()}},t.prototype._appendParticleVertices=function(e,n){this._appendParticleVertex(e++,n,0,0),this._useInstancing||(this._appendParticleVertex(e++,n,1,0),this._appendParticleVertex(e++,n,1,1),this._appendParticleVertex(e++,n,0,1))},t.prototype.rebuild=function(){for(var e in this._createIndexBuffer(),this._vertexBuffer&&this._vertexBuffer._rebuild(),this._vertexBuffers)this._vertexBuffers[e]._rebuild()},t.prototype.isReady=function(){if(!this.emitter||this._imageProcessingConfiguration&&!this._imageProcessingConfiguration.isReady()||!this.particleTexture||!this.particleTexture.isReady())return!1;if(this.blendMode!==t.BLENDMODE_MULTIPLYADD){if(!this._getEffect(this.blendMode).isReady())return!1}else if(!this._getEffect(t.BLENDMODE_MULTIPLY).isReady()||!this._getEffect(t.BLENDMODE_ADD).isReady())return!1;return!0},t.prototype._render=function(e){var n,i,o=this._getEffect(e),a=this._engine;a.enableEffect(o);var s=(n=this.defaultViewMatrix)!==null&&n!==void 0?n:this._scene.getViewMatrix();if(o.setTexture("diffuseSampler",this.particleTexture),o.setMatrix("view",s),o.setMatrix("projection",(i=this.defaultProjectionMatrix)!==null&&i!==void 0?i:this._scene.getProjectionMatrix()),this._isAnimationSheetEnabled&&this.particleTexture){var d=this.particleTexture.getBaseSize();o.setFloat3("particlesInfos",this.spriteCellWidth/d.width,this.spriteCellHeight/d.height,this.spriteCellWidth/d.width)}if(o.setVector2("translationPivot",this.translationPivot),o.setFloat4("textureMask",this.textureMask.r,this.textureMask.g,this.textureMask.b,this.textureMask.a),this._isBillboardBased&&this._scene){var p=this._scene.activeCamera;o.setVector3("eyePosition",p.globalPosition)}this._rampGradientsTexture&&(this._rampGradients&&this._rampGradients.length||(this._rampGradientsTexture.dispose(),this._rampGradientsTexture=null),o.setTexture("rampSampler",this._rampGradientsTexture));var b=o.defines;switch(this._scene&&(this._scene.clipPlane||this._scene.clipPlane2||this._scene.clipPlane3||this._scene.clipPlane4||this._scene.clipPlane5||this._scene.clipPlane6)&&nh.a.BindClipPlane(o,this._scene),b.indexOf("#define BILLBOARDMODE_ALL")>=0&&(s.invertToRef(u.c.Matrix[0]),o.setMatrix("invView",u.c.Matrix[0])),this._vertexArrayObject!==void 0?(this._vertexArrayObject||(this._vertexArrayObject=this._engine.recordVertexArrayObject(this._vertexBuffers,this._indexBuffer,o)),this._engine.bindVertexArrayObject(this._vertexArrayObject,this._indexBuffer)):a.bindBuffers(this._vertexBuffers,this._indexBuffer,o),this._imageProcessingConfiguration&&!this._imageProcessingConfiguration.applyByPostProcess&&this._imageProcessingConfiguration.bind(o),e){case t.BLENDMODE_ADD:a.setAlphaMode(h.a.ALPHA_ADD);break;case t.BLENDMODE_ONEONE:a.setAlphaMode(h.a.ALPHA_ONEONE);break;case t.BLENDMODE_STANDARD:a.setAlphaMode(h.a.ALPHA_COMBINE);break;case t.BLENDMODE_MULTIPLY:a.setAlphaMode(h.a.ALPHA_MULTIPLY)}return this._onBeforeDrawParticlesObservable&&this._onBeforeDrawParticlesObservable.notifyObservers(o),this._useInstancing?a.drawArraysType(h.a.MATERIAL_TriangleFanDrawMode,0,4,this._particles.length):a.drawElementsType(h.a.MATERIAL_TriangleFillMode,0,6*this._particles.length),this._particles.length},t.prototype.render=function(){if(!this.isReady()||!this._particles.length)return 0;var e=this._engine;e.setState&&(e.setState(!1),this.forceDepthWrite&&e.setDepthWrite(!0));var n=0;return n=this.blendMode===t.BLENDMODE_MULTIPLYADD?this._render(t.BLENDMODE_MULTIPLY)+this._render(t.BLENDMODE_ADD):this._render(this.blendMode),this._engine.unbindInstanceAttributes(),this._engine.setAlphaMode(h.a.ALPHA_DISABLE),n},t.prototype.dispose=function(e){if(e===void 0&&(e=!0),this._vertexBuffer&&(this._vertexBuffer.dispose(),this._vertexBuffer=null),this._spriteBuffer&&(this._spriteBuffer.dispose(),this._spriteBuffer=null),this._indexBuffer&&(this._engine._releaseBuffer(this._indexBuffer),this._indexBuffer=null),this._vertexArrayObject&&(this._engine.releaseVertexArrayObject(this._vertexArrayObject),this._vertexArrayObject=null),e&&this.particleTexture&&(this.particleTexture.dispose(),this.particleTexture=null),e&&this.noiseTexture&&(this.noiseTexture.dispose(),this.noiseTexture=null),this._rampGradientsTexture&&(this._rampGradientsTexture.dispose(),this._rampGradientsTexture=null),this._removeFromRoot(),this._subEmitters&&this._subEmitters.length){for(var n=0;n<this._subEmitters.length;n++)for(var i=0,o=this._subEmitters[n];i<o.length;i++)o[i].dispose();this._subEmitters=[],this.subEmitters=[]}this._disposeEmitterOnDispose&&this.emitter&&this.emitter.dispose&&this.emitter.dispose(!0),this._onBeforeDrawParticlesObservable&&this._onBeforeDrawParticlesObservable.clear(),this._scene&&((n=this._scene.particleSystems.indexOf(this))>-1&&this._scene.particleSystems.splice(n,1),this._scene._activeParticleSystems.dispose()),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear(),this.onStoppedObservable.clear(),this.reset()},t.prototype.clone=function(e,n){var i=Object(c.a)({},this._customEffect),o=null,a=this._engine;if(a.createEffectForParticles&&this.customShader!=null){var s=(o=this.customShader).shaderOptions.defines.length>0?o.shaderOptions.defines.join(`
-`):"";i[0]=a.createEffectForParticles(o.shaderPath.fragmentElement,o.shaderOptions.uniforms,o.shaderOptions.samplers,s)}var d=this.serialize(),p=t.Parse(d,this._scene||this._engine,"");return p.name=e,p.customShader=o,p._customEffect=i,n===void 0&&(n=this.emitter),this.noiseTexture&&(p.noiseTexture=this.noiseTexture.clone()),p.emitter=n,this.preventAutoStart||p.start(),p},t.prototype.serialize=function(e){e===void 0&&(e=!1);var n={};if(t._Serialize(n,this,e),n.textureMask=this.textureMask.asArray(),n.customShader=this.customShader,n.preventAutoStart=this.preventAutoStart,this.subEmitters){n.subEmitters=[],this._subEmitters||this._prepareSubEmitterInternalArray();for(var i=0,o=this._subEmitters;i<o.length;i++){for(var a=[],s=0,d=o[i];s<d.length;s++){var p=d[s];a.push(p.serialize())}n.subEmitters.push(a)}}return n},t._Serialize=function(e,n,i){if(e.name=n.name,e.id=n.id,e.capacity=n.getCapacity(),n.emitter.position){var o=n.emitter;e.emitterId=o.id}else{var a=n.emitter;e.emitter=a.asArray()}n.particleEmitterType&&(e.particleEmitterType=n.particleEmitterType.serialize()),n.particleTexture&&(i?e.texture=n.particleTexture.serialize():(e.textureName=n.particleTexture.name,e.invertY=!!n.particleTexture._invertY)),e.isLocal=n.isLocal,L.a.AppendSerializedAnimations(n,e),e.beginAnimationOnStart=n.beginAnimationOnStart,e.beginAnimationFrom=n.beginAnimationFrom,e.beginAnimationTo=n.beginAnimationTo,e.beginAnimationLoop=n.beginAnimationLoop,e.startDelay=n.startDelay,e.renderingGroupId=n.renderingGroupId,e.isBillboardBased=n.isBillboardBased,e.billboardMode=n.billboardMode,e.minAngularSpeed=n.minAngularSpeed,e.maxAngularSpeed=n.maxAngularSpeed,e.minSize=n.minSize,e.maxSize=n.maxSize,e.minScaleX=n.minScaleX,e.maxScaleX=n.maxScaleX,e.minScaleY=n.minScaleY,e.maxScaleY=n.maxScaleY,e.minEmitPower=n.minEmitPower,e.maxEmitPower=n.maxEmitPower,e.minLifeTime=n.minLifeTime,e.maxLifeTime=n.maxLifeTime,e.emitRate=n.emitRate,e.gravity=n.gravity.asArray(),e.noiseStrength=n.noiseStrength.asArray(),e.color1=n.color1.asArray(),e.color2=n.color2.asArray(),e.colorDead=n.colorDead.asArray(),e.updateSpeed=n.updateSpeed,e.targetStopDuration=n.targetStopDuration,e.blendMode=n.blendMode,e.preWarmCycles=n.preWarmCycles,e.preWarmStepOffset=n.preWarmStepOffset,e.minInitialRotation=n.minInitialRotation,e.maxInitialRotation=n.maxInitialRotation,e.startSpriteCellID=n.startSpriteCellID,e.endSpriteCellID=n.endSpriteCellID,e.spriteCellChangeSpeed=n.spriteCellChangeSpeed,e.spriteCellWidth=n.spriteCellWidth,e.spriteCellHeight=n.spriteCellHeight,e.spriteRandomStartCell=n.spriteRandomStartCell,e.isAnimationSheetEnabled=n.isAnimationSheetEnabled;var s=n.getColorGradients();if(s){e.colorGradients=[];for(var d=0,p=s;d<p.length;d++){var b=p[d],P={gradient:b.gradient,color1:b.color1.asArray()};b.color2?P.color2=b.color2.asArray():P.color2=b.color1.asArray(),e.colorGradients.push(P)}}var O=n.getRampGradients();if(O){e.rampGradients=[];for(var B=0,F=O;B<F.length;B++){var z=F[B];P={gradient:z.gradient,color:z.color.asArray()},e.rampGradients.push(P)}e.useRampGradients=n.useRampGradients}var J=n.getColorRemapGradients();if(J){e.colorRemapGradients=[];for(var ie=0,se=J;ie<se.length;ie++){var ce=se[ie];P={gradient:ce.gradient,factor1:ce.factor1},ce.factor2!==void 0?P.factor2=ce.factor2:P.factor2=ce.factor1,e.colorRemapGradients.push(P)}}var ue=n.getAlphaRemapGradients();if(ue){e.alphaRemapGradients=[];for(var fe=0,ve=ue;fe<ve.length;fe++){var Te=ve[fe];P={gradient:Te.gradient,factor1:Te.factor1},Te.factor2!==void 0?P.factor2=Te.factor2:P.factor2=Te.factor1,e.alphaRemapGradients.push(P)}}var Re=n.getSizeGradients();if(Re){e.sizeGradients=[];for(var Ae=0,Ee=Re;Ae<Ee.length;Ae++){var Se=Ee[Ae];P={gradient:Se.gradient,factor1:Se.factor1},Se.factor2!==void 0?P.factor2=Se.factor2:P.factor2=Se.factor1,e.sizeGradients.push(P)}}var Le=n.getAngularSpeedGradients();if(Le){e.angularSpeedGradients=[];for(var xe=0,Ne=Le;xe<Ne.length;xe++){var Ie=Ne[xe];P={gradient:Ie.gradient,factor1:Ie.factor1},Ie.factor2!==void 0?P.factor2=Ie.factor2:P.factor2=Ie.factor1,e.angularSpeedGradients.push(P)}}var Fe=n.getVelocityGradients();if(Fe){e.velocityGradients=[];for(var Ye=0,tt=Fe;Ye<tt.length;Ye++){var it=tt[Ye];P={gradient:it.gradient,factor1:it.factor1},it.factor2!==void 0?P.factor2=it.factor2:P.factor2=it.factor1,e.velocityGradients.push(P)}}var ut=n.getDragGradients();if(ut){e.dragGradients=[];for(var Qe=0,ot=ut;Qe<ot.length;Qe++){var rt=ot[Qe];P={gradient:rt.gradient,factor1:rt.factor1},rt.factor2!==void 0?P.factor2=rt.factor2:P.factor2=rt.factor1,e.dragGradients.push(P)}}var Ze=n.getEmitRateGradients();if(Ze){e.emitRateGradients=[];for(var dt=0,Ve=Ze;dt<Ve.length;dt++){var Je=Ve[dt];P={gradient:Je.gradient,factor1:Je.factor1},Je.factor2!==void 0?P.factor2=Je.factor2:P.factor2=Je.factor1,e.emitRateGradients.push(P)}}var yt=n.getStartSizeGradients();if(yt){e.startSizeGradients=[];for(var Wt=0,Nt=yt;Wt<Nt.length;Wt++){var Qt=Nt[Wt];P={gradient:Qt.gradient,factor1:Qt.factor1},Qt.factor2!==void 0?P.factor2=Qt.factor2:P.factor2=Qt.factor1,e.startSizeGradients.push(P)}}var vt=n.getLifeTimeGradients();if(vt){e.lifeTimeGradients=[];for(var Jt=0,Xt=vt;Jt<Xt.length;Jt++){var zt=Xt[Jt];P={gradient:zt.gradient,factor1:zt.factor1},zt.factor2!==void 0?P.factor2=zt.factor2:P.factor2=zt.factor1,e.lifeTimeGradients.push(P)}}var Yt=n.getLimitVelocityGradients();if(Yt){e.limitVelocityGradients=[];for(var Et=0,Mt=Yt;Et<Mt.length;Et++){var $t=Mt[Et];P={gradient:$t.gradient,factor1:$t.factor1},$t.factor2!==void 0?P.factor2=$t.factor2:P.factor2=$t.factor1,e.limitVelocityGradients.push(P)}e.limitVelocityDamping=n.limitVelocityDamping}n.noiseTexture&&(e.noiseTexture=n.noiseTexture.serialize())},t._Parse=function(e,n,i,o){var a;a=i instanceof Bt.a?null:i;var s,d=R.a.GetClass("BABYLON.Texture");if(d&&a&&(e.texture?n.particleTexture=d.Parse(e.texture,a,o):e.textureName&&(n.particleTexture=new d(o+e.textureName,a,!1,e.invertY===void 0||e.invertY),n.particleTexture.name=e.textureName)),e.emitterId||e.emitterId===0||e.emitter!==void 0?e.emitterId&&a?n.emitter=a.getLastMeshByID(e.emitterId):n.emitter=u.e.FromArray(e.emitter):n.emitter=u.e.Zero(),n.isLocal=!!e.isLocal,e.renderingGroupId!==void 0&&(n.renderingGroupId=e.renderingGroupId),e.isBillboardBased!==void 0&&(n.isBillboardBased=e.isBillboardBased),e.billboardMode!==void 0&&(n.billboardMode=e.billboardMode),e.animations){for(var p=0;p<e.animations.length;p++){var b=e.animations[p],P=R.a.GetClass("BABYLON.Animation");P&&n.animations.push(P.Parse(b))}n.beginAnimationOnStart=e.beginAnimationOnStart,n.beginAnimationFrom=e.beginAnimationFrom,n.beginAnimationTo=e.beginAnimationTo,n.beginAnimationLoop=e.beginAnimationLoop}if(e.autoAnimate&&a&&a.beginAnimation(n,e.autoAnimateFrom,e.autoAnimateTo,e.autoAnimateLoop,e.autoAnimateSpeed||1),n.startDelay=0|e.startDelay,n.minAngularSpeed=e.minAngularSpeed,n.maxAngularSpeed=e.maxAngularSpeed,n.minSize=e.minSize,n.maxSize=e.maxSize,e.minScaleX&&(n.minScaleX=e.minScaleX,n.maxScaleX=e.maxScaleX,n.minScaleY=e.minScaleY,n.maxScaleY=e.maxScaleY),e.preWarmCycles!==void 0&&(n.preWarmCycles=e.preWarmCycles,n.preWarmStepOffset=e.preWarmStepOffset),e.minInitialRotation!==void 0&&(n.minInitialRotation=e.minInitialRotation,n.maxInitialRotation=e.maxInitialRotation),n.minLifeTime=e.minLifeTime,n.maxLifeTime=e.maxLifeTime,n.minEmitPower=e.minEmitPower,n.maxEmitPower=e.maxEmitPower,n.emitRate=e.emitRate,n.gravity=u.e.FromArray(e.gravity),e.noiseStrength&&(n.noiseStrength=u.e.FromArray(e.noiseStrength)),n.color1=M.b.FromArray(e.color1),n.color2=M.b.FromArray(e.color2),n.colorDead=M.b.FromArray(e.colorDead),n.updateSpeed=e.updateSpeed,n.targetStopDuration=e.targetStopDuration,n.blendMode=e.blendMode,e.colorGradients)for(var O=0,B=e.colorGradients;O<B.length;O++){var F=B[O];n.addColorGradient(F.gradient,M.b.FromArray(F.color1),F.color2?M.b.FromArray(F.color2):void 0)}if(e.rampGradients){for(var z=0,J=e.rampGradients;z<J.length;z++){var ie=J[z];n.addRampGradient(ie.gradient,M.a.FromArray(ie.color))}n.useRampGradients=e.useRampGradients}if(e.colorRemapGradients)for(var se=0,ce=e.colorRemapGradients;se<ce.length;se++){var ue=ce[se];n.addColorRemapGradient(ue.gradient,ue.factor1!==void 0?ue.factor1:ue.factor,ue.factor2)}if(e.alphaRemapGradients)for(var fe=0,ve=e.alphaRemapGradients;fe<ve.length;fe++){var Te=ve[fe];n.addAlphaRemapGradient(Te.gradient,Te.factor1!==void 0?Te.factor1:Te.factor,Te.factor2)}if(e.sizeGradients)for(var Re=0,Ae=e.sizeGradients;Re<Ae.length;Re++){var Ee=Ae[Re];n.addSizeGradient(Ee.gradient,Ee.factor1!==void 0?Ee.factor1:Ee.factor,Ee.factor2)}if(e.angularSpeedGradients)for(var Se=0,Le=e.angularSpeedGradients;Se<Le.length;Se++){var xe=Le[Se];n.addAngularSpeedGradient(xe.gradient,xe.factor1!==void 0?xe.factor1:xe.factor,xe.factor2)}if(e.velocityGradients)for(var Ne=0,Ie=e.velocityGradients;Ne<Ie.length;Ne++){var Fe=Ie[Ne];n.addVelocityGradient(Fe.gradient,Fe.factor1!==void 0?Fe.factor1:Fe.factor,Fe.factor2)}if(e.dragGradients)for(var Ye=0,tt=e.dragGradients;Ye<tt.length;Ye++){var it=tt[Ye];n.addDragGradient(it.gradient,it.factor1!==void 0?it.factor1:it.factor,it.factor2)}if(e.emitRateGradients)for(var ut=0,Qe=e.emitRateGradients;ut<Qe.length;ut++){var ot=Qe[ut];n.addEmitRateGradient(ot.gradient,ot.factor1!==void 0?ot.factor1:ot.factor,ot.factor2)}if(e.startSizeGradients)for(var rt=0,Ze=e.startSizeGradients;rt<Ze.length;rt++){var dt=Ze[rt];n.addStartSizeGradient(dt.gradient,dt.factor1!==void 0?dt.factor1:dt.factor,dt.factor2)}if(e.lifeTimeGradients)for(var Ve=0,Je=e.lifeTimeGradients;Ve<Je.length;Ve++){var yt=Je[Ve];n.addLifeTimeGradient(yt.gradient,yt.factor1!==void 0?yt.factor1:yt.factor,yt.factor2)}if(e.limitVelocityGradients){for(var Wt=0,Nt=e.limitVelocityGradients;Wt<Nt.length;Wt++){var Qt=Nt[Wt];n.addLimitVelocityGradient(Qt.gradient,Qt.factor1!==void 0?Qt.factor1:Qt.factor,Qt.factor2)}n.limitVelocityDamping=e.limitVelocityDamping}if(e.noiseTexture&&a){var vt=R.a.GetClass("BABYLON.ProceduralTexture");n.noiseTexture=vt.Parse(e.noiseTexture,a,o)}if(e.particleEmitterType){switch(e.particleEmitterType.type){case"SphereParticleEmitter":s=new ma;break;case"SphereDirectedParticleEmitter":s=new uc;break;case"ConeEmitter":case"ConeParticleEmitter":s=new ac;break;case"CylinderParticleEmitter":s=new _a;break;case"CylinderDirectedParticleEmitter":s=new sc;break;case"HemisphericParticleEmitter":s=new cc;break;case"PointParticleEmitter":s=new lc;break;case"MeshParticleEmitter":s=new fh;break;case"BoxEmitter":case"BoxParticleEmitter":default:s=new Nr}s.parse(e.particleEmitterType,a)}else(s=new Nr).parse(e,a);n.particleEmitterType=s,n.startSpriteCellID=e.startSpriteCellID,n.endSpriteCellID=e.endSpriteCellID,n.spriteCellWidth=e.spriteCellWidth,n.spriteCellHeight=e.spriteCellHeight,n.spriteCellChangeSpeed=e.spriteCellChangeSpeed,n.spriteRandomStartCell=e.spriteRandomStartCell},t.Parse=function(e,n,i,o){o===void 0&&(o=!1);var a,s=e.name,d=null,p=null;if(a=n instanceof Bt.a?n:n.getEngine(),e.customShader&&a.createEffectForParticles){var b=(p=e.customShader).shaderOptions.defines.length>0?p.shaderOptions.defines.join(`
-`):"";d=a.createEffectForParticles(p.shaderPath.fragmentElement,p.shaderOptions.uniforms,p.shaderOptions.samplers,b)}var P=new t(s,e.capacity,n,d,e.isAnimationSheetEnabled);if(P.customShader=p,e.id&&(P.id=e.id),e.subEmitters){P.subEmitters=[];for(var O=0,B=e.subEmitters;O<B.length;O++){for(var F=[],z=0,J=B[O];z<J.length;z++){var ie=J[z];F.push(Co.Parse(ie,n,i))}P.subEmitters.push(F)}}return t._Parse(e,P,n,i),e.textureMask&&(P.textureMask=M.b.FromArray(e.textureMask)),e.preventAutoStart&&(P.preventAutoStart=e.preventAutoStart),o||P.preventAutoStart||P.start(),P},t.BILLBOARDMODE_Y=h.a.PARTICLES_BILLBOARDMODE_Y,t.BILLBOARDMODE_ALL=h.a.PARTICLES_BILLBOARDMODE_ALL,t.BILLBOARDMODE_STRETCHED=h.a.PARTICLES_BILLBOARDMODE_STRETCHED,t}(yo);Co._ParseParticleSystem=ln.Parse,ze.a.ShadersStore.gpuUpdateParticlesPixelShader=`#version 300 es
-void main() {
-discard;
-}
-`;var Fm=`#version 300 es
-#define PI 3.14159
-uniform float currentCount;
-uniform float timeDelta;
-uniform float stopFactor;
-#ifndef LOCAL
-uniform mat4 emitterWM;
-#endif
-uniform vec2 lifeTime;
-uniform vec2 emitPower;
-uniform vec2 sizeRange;
-uniform vec4 scaleRange;
-#ifndef COLORGRADIENTS
-uniform vec4 color1;
-uniform vec4 color2;
-#endif
-uniform vec3 gravity;
-uniform sampler2D randomSampler;
-uniform sampler2D randomSampler2;
-uniform vec4 angleRange;
-#ifdef BOXEMITTER
-uniform vec3 direction1;
-uniform vec3 direction2;
-uniform vec3 minEmitBox;
-uniform vec3 maxEmitBox;
-#endif
-#ifdef POINTEMITTER
-uniform vec3 direction1;
-uniform vec3 direction2;
-#endif
-#ifdef HEMISPHERICEMITTER
-uniform float radius;
-uniform float radiusRange;
-uniform float directionRandomizer;
-#endif
-#ifdef SPHEREEMITTER
-uniform float radius;
-uniform float radiusRange;
-#ifdef DIRECTEDSPHEREEMITTER
-uniform vec3 direction1;
-uniform vec3 direction2;
-#else
-uniform float directionRandomizer;
-#endif
-#endif
-#ifdef CYLINDEREMITTER
-uniform float radius;
-uniform float height;
-uniform float radiusRange;
-#ifdef DIRECTEDCYLINDEREMITTER
-uniform vec3 direction1;
-uniform vec3 direction2;
-#else
-uniform float directionRandomizer;
-#endif
-#endif
-#ifdef CONEEMITTER
-uniform vec2 radius;
-uniform float coneAngle;
-uniform vec2 height;
-uniform float directionRandomizer;
-#endif
-
-in vec3 position;
-#ifdef CUSTOMEMITTER
-in vec3 initialPosition;
-#endif
-in float age;
-in float life;
-in vec4 seed;
-in vec3 size;
-#ifndef COLORGRADIENTS
-in vec4 color;
-#endif
-in vec3 direction;
-#ifndef BILLBOARD
-in vec3 initialDirection;
-#endif
-#ifdef ANGULARSPEEDGRADIENTS
-in float angle;
-#else
-in vec2 angle;
-#endif
-#ifdef ANIMATESHEET
-in float cellIndex;
-#ifdef ANIMATESHEETRANDOMSTART
-in float cellStartOffset;
-#endif
-#endif
-#ifdef NOISE
-in vec3 noiseCoordinates1;
-in vec3 noiseCoordinates2;
-#endif
-
-out vec3 outPosition;
-#ifdef CUSTOMEMITTER
-out vec3 outInitialPosition;
-#endif
-out float outAge;
-out float outLife;
-out vec4 outSeed;
-out vec3 outSize;
-#ifndef COLORGRADIENTS
-out vec4 outColor;
-#endif
-out vec3 outDirection;
-#ifndef BILLBOARD
-out vec3 outInitialDirection;
-#endif
-#ifdef ANGULARSPEEDGRADIENTS
-out float outAngle;
-#else
-out vec2 outAngle;
-#endif
-#ifdef ANIMATESHEET
-out float outCellIndex;
-#ifdef ANIMATESHEETRANDOMSTART
-out float outCellStartOffset;
-#endif
-#endif
-#ifdef NOISE
-out vec3 outNoiseCoordinates1;
-out vec3 outNoiseCoordinates2;
-#endif
-#ifdef SIZEGRADIENTS
-uniform sampler2D sizeGradientSampler;
-#endif
-#ifdef ANGULARSPEEDGRADIENTS
-uniform sampler2D angularSpeedGradientSampler;
-#endif
-#ifdef VELOCITYGRADIENTS
-uniform sampler2D velocityGradientSampler;
-#endif
-#ifdef LIMITVELOCITYGRADIENTS
-uniform sampler2D limitVelocityGradientSampler;
-uniform float limitVelocityDamping;
-#endif
-#ifdef DRAGGRADIENTS
-uniform sampler2D dragGradientSampler;
-#endif
-#ifdef NOISE
-uniform vec3 noiseStrength;
-uniform sampler2D noiseSampler;
-#endif
-#ifdef ANIMATESHEET
-uniform vec3 cellInfos;
-#endif
-vec3 getRandomVec3(float offset) {
-return texture(randomSampler2,vec2(float(gl_VertexID)*offset/currentCount,0)).rgb;
-}
-vec4 getRandomVec4(float offset) {
-return texture(randomSampler,vec2(float(gl_VertexID)*offset/currentCount,0));
-}
-void main() {
-float newAge=age+timeDelta;
-
-if (newAge>=life && stopFactor != 0.) {
-vec3 newPosition;
-vec3 newDirection;
-
-vec4 randoms=getRandomVec4(seed.x);
-
-outLife=lifeTime.x+(lifeTime.y-lifeTime.x)*randoms.r;
-outAge=newAge-life;
-
-outSeed=seed;
-
-#ifdef SIZEGRADIENTS
-outSize.x=texture(sizeGradientSampler,vec2(0,0)).r;
-#else
-outSize.x=sizeRange.x+(sizeRange.y-sizeRange.x)*randoms.g;
-#endif
-outSize.y=scaleRange.x+(scaleRange.y-scaleRange.x)*randoms.b;
-outSize.z=scaleRange.z+(scaleRange.w-scaleRange.z)*randoms.a;
-#ifndef COLORGRADIENTS
-
-outColor=color1+(color2-color1)*randoms.b;
-#endif
-
-#ifndef ANGULARSPEEDGRADIENTS
-outAngle.y=angleRange.x+(angleRange.y-angleRange.x)*randoms.a;
-outAngle.x=angleRange.z+(angleRange.w-angleRange.z)*randoms.r;
-#else
-outAngle=angleRange.z+(angleRange.w-angleRange.z)*randoms.r;
-#endif
-
-#ifdef POINTEMITTER
-vec3 randoms2=getRandomVec3(seed.y);
-vec3 randoms3=getRandomVec3(seed.z);
-newPosition=vec3(0,0,0);
-newDirection=direction1+(direction2-direction1)*randoms3;
-#elif defined(BOXEMITTER)
-vec3 randoms2=getRandomVec3(seed.y);
-vec3 randoms3=getRandomVec3(seed.z);
-newPosition=minEmitBox+(maxEmitBox-minEmitBox)*randoms2;
-newDirection=direction1+(direction2-direction1)*randoms3;
-#elif defined(HEMISPHERICEMITTER)
-vec3 randoms2=getRandomVec3(seed.y);
-vec3 randoms3=getRandomVec3(seed.z);
-
-float phi=2.0*PI*randoms2.x;
-float theta=acos(2.0*randoms2.y-1.0);
-float randX=cos(phi)*sin(theta);
-float randY=cos(theta);
-float randZ=sin(phi)*sin(theta);
-newPosition=(radius-(radius*radiusRange*randoms2.z))*vec3(randX,abs(randY),randZ);
-newDirection=newPosition+directionRandomizer*randoms3;
-#elif defined(SPHEREEMITTER)
-vec3 randoms2=getRandomVec3(seed.y);
-vec3 randoms3=getRandomVec3(seed.z);
-
-float phi=2.0*PI*randoms2.x;
-float theta=acos(2.0*randoms2.y-1.0);
-float randX=cos(phi)*sin(theta);
-float randY=cos(theta);
-float randZ=sin(phi)*sin(theta);
-newPosition=(radius-(radius*radiusRange*randoms2.z))*vec3(randX,randY,randZ);
-#ifdef DIRECTEDSPHEREEMITTER
-newDirection=direction1+(direction2-direction1)*randoms3;
-#else
-
-newDirection=newPosition+directionRandomizer*randoms3;
-#endif
-#elif defined(CYLINDEREMITTER)
-vec3 randoms2=getRandomVec3(seed.y);
-vec3 randoms3=getRandomVec3(seed.z);
-
-float yPos=(randoms2.x-0.5)*height;
-float angle=randoms2.y*PI*2.;
-float inverseRadiusRangeSquared=((1.-radiusRange)*(1.-radiusRange));
-float positionRadius=radius*sqrt(inverseRadiusRangeSquared+(randoms2.z*(1.-inverseRadiusRangeSquared)));
-float xPos=positionRadius*cos(angle);
-float zPos=positionRadius*sin(angle);
-newPosition=vec3(xPos,yPos,zPos);
-#ifdef DIRECTEDCYLINDEREMITTER
-newDirection=direction1+(direction2-direction1)*randoms3;
-#else
-
-angle=angle+((randoms3.x-0.5)*PI);
-newDirection=vec3(cos(angle),randoms3.y-0.5,sin(angle));
-newDirection=normalize(newDirection);
-#endif
-#elif defined(CONEEMITTER)
-vec3 randoms2=getRandomVec3(seed.y);
-float s=2.0*PI*randoms2.x;
-#ifdef CONEEMITTERSPAWNPOINT
-float h=0.0001;
-#else
-float h=randoms2.y*height.y;
-
-h=1.-h*h;
-#endif
-float lRadius=radius.x-radius.x*randoms2.z*radius.y;
-lRadius=lRadius*h;
-float randX=lRadius*sin(s);
-float randZ=lRadius*cos(s);
-float randY=h*height.x;
-newPosition=vec3(randX,randY,randZ);
-
-if (abs(cos(coneAngle)) == 1.0) {
-newDirection=vec3(0.,1.0,0.);
-} else {
-vec3 randoms3=getRandomVec3(seed.z);
-newDirection=normalize(newPosition+directionRandomizer*randoms3);
-}
-#elif defined(CUSTOMEMITTER)
-newPosition=initialPosition;
-outInitialPosition=initialPosition;
-#else
-
-newPosition=vec3(0.,0.,0.);
-
-newDirection=2.0*(getRandomVec3(seed.w)-vec3(0.5,0.5,0.5));
-#endif
-float power=emitPower.x+(emitPower.y-emitPower.x)*randoms.a;
-#ifdef LOCAL
-outPosition=newPosition;
-#else
-outPosition=(emitterWM*vec4(newPosition,1.)).xyz;
-#endif
-#ifdef CUSTOMEMITTER
-outDirection=direction;
-#ifndef BILLBOARD
-outInitialDirection=direction;
-#endif
-#else
-#ifdef LOCAL
-vec3 initial=newDirection;
-#else
-vec3 initial=(emitterWM*vec4(newDirection,0.)).xyz;
-#endif
-outDirection=initial*power;
-#ifndef BILLBOARD
-outInitialDirection=initial;
-#endif
-#endif
-#ifdef ANIMATESHEET
-outCellIndex=cellInfos.x;
-#ifdef ANIMATESHEETRANDOMSTART
-outCellStartOffset=randoms.a*outLife;
-#endif
-#endif
-#ifdef NOISE
-outNoiseCoordinates1=noiseCoordinates1;
-outNoiseCoordinates2=noiseCoordinates2;
-#endif
-} else {
-float directionScale=timeDelta;
-outAge=newAge;
-float ageGradient=newAge/life;
-#ifdef VELOCITYGRADIENTS
-directionScale*=texture(velocityGradientSampler,vec2(ageGradient,0)).r;
-#endif
-#ifdef DRAGGRADIENTS
-directionScale*=1.0-texture(dragGradientSampler,vec2(ageGradient,0)).r;
-#endif
-#if defined(CUSTOMEMITTER)
-outPosition=position+(direction-position)*ageGradient;
-outInitialPosition=initialPosition;
-#else
-outPosition=position+direction*directionScale;
-#endif
-outLife=life;
-outSeed=seed;
-#ifndef COLORGRADIENTS
-outColor=color;
-#endif
-#ifdef SIZEGRADIENTS
-outSize.x=texture(sizeGradientSampler,vec2(ageGradient,0)).r;
-outSize.yz=size.yz;
-#else
-outSize=size;
-#endif
-#ifndef BILLBOARD
-outInitialDirection=initialDirection;
-#endif
-#ifdef CUSTOMEMITTER
-outDirection=direction;
-#else
-vec3 updatedDirection=direction+gravity*timeDelta;
-#ifdef LIMITVELOCITYGRADIENTS
-float limitVelocity=texture(limitVelocityGradientSampler,vec2(ageGradient,0)).r;
-float currentVelocity=length(updatedDirection);
-if (currentVelocity>limitVelocity) {
-updatedDirection=updatedDirection*limitVelocityDamping;
-}
-#endif
-outDirection=updatedDirection;
-#ifdef NOISE
-float fetchedR=texture(noiseSampler,vec2(noiseCoordinates1.x,noiseCoordinates1.y)*vec2(0.5)+vec2(0.5)).r;
-float fetchedG=texture(noiseSampler,vec2(noiseCoordinates1.z,noiseCoordinates2.x)*vec2(0.5)+vec2(0.5)).r;
-float fetchedB=texture(noiseSampler,vec2(noiseCoordinates2.y,noiseCoordinates2.z)*vec2(0.5)+vec2(0.5)).r;
-vec3 force=vec3(2.*fetchedR-1.,2.*fetchedG-1.,2.*fetchedB-1.)*noiseStrength;
-outDirection=outDirection+force*timeDelta;
-outNoiseCoordinates1=noiseCoordinates1;
-outNoiseCoordinates2=noiseCoordinates2;
-#endif
-#endif
-#ifdef ANGULARSPEEDGRADIENTS
-float angularSpeed=texture(angularSpeedGradientSampler,vec2(ageGradient,0)).r;
-outAngle=angle+angularSpeed*timeDelta;
-#else
-outAngle=vec2(angle.x+angle.y*timeDelta,angle.y);
-#endif
-#ifdef ANIMATESHEET
-float offsetAge=outAge;
-float dist=cellInfos.y-cellInfos.x;
-#ifdef ANIMATESHEETRANDOMSTART
-outCellStartOffset=cellStartOffset;
-offsetAge+=cellStartOffset;
-#else
-float cellStartOffset=0.;
-#endif
-float ratio=clamp(mod(cellStartOffset+cellInfos.z*offsetAge,life)/life,0.,1.0);
-outCellIndex=float(int(cellInfos.x+ratio*dist));
-#endif
-}
-}`;ze.a.ShadersStore.gpuUpdateParticlesVertexShader=Fm;var Bm=`#ifdef CLIPPLANE
-in float fClipDistance;
-#endif
-#ifdef CLIPPLANE2
-in float fClipDistance2;
-#endif
-#ifdef CLIPPLANE3
-in float fClipDistance3;
-#endif
-#ifdef CLIPPLANE4
-in float fClipDistance4;
-#endif
-#ifdef CLIPPLANE5
-in float fClipDistance5;
-#endif
-#ifdef CLIPPLANE6
-in float fClipDistance6;
-#endif`;ze.a.IncludesShadersStore.clipPlaneFragmentDeclaration2=Bm;var Um=`#version 300 es
-uniform sampler2D diffuseSampler;
-in vec2 vUV;
-in vec4 vColor;
-out vec4 outFragColor;
-#include<clipPlaneFragmentDeclaration2>
-#include<imageProcessingDeclaration>
-#include<helperFunctions>
-#include<imageProcessingFunctions>
-void main() {
-#include<clipPlaneFragment>
-vec4 textureColor=texture(diffuseSampler,vUV);
-outFragColor=textureColor*vColor;
-#ifdef BLENDMULTIPLYMODE
-float alpha=vColor.a*textureColor.a;
-outFragColor.rgb=outFragColor.rgb*alpha+vec3(1.0)*(1.0-alpha);
-#endif
-
-
-#ifdef IMAGEPROCESSINGPOSTPROCESS
-outFragColor.rgb=toLinearSpace(outFragColor.rgb);
-#else
-#ifdef IMAGEPROCESSING
-outFragColor.rgb=toLinearSpace(outFragColor.rgb);
-outFragColor=applyImageProcessing(outFragColor);
-#endif
-#endif
-}
-`;ze.a.ShadersStore.gpuRenderParticlesPixelShader=Um;var Vm=`#ifdef CLIPPLANE
-uniform vec4 vClipPlane;
-out float fClipDistance;
-#endif
-#ifdef CLIPPLANE2
-uniform vec4 vClipPlane2;
-out float fClipDistance2;
-#endif
-#ifdef CLIPPLANE3
-uniform vec4 vClipPlane3;
-out float fClipDistance3;
-#endif
-#ifdef CLIPPLANE4
-uniform vec4 vClipPlane4;
-out float fClipDistance4;
-#endif
-#ifdef CLIPPLANE5
-uniform vec4 vClipPlane5;
-out float fClipDistance5;
-#endif
-#ifdef CLIPPLANE6
-uniform vec4 vClipPlane6;
-out float fClipDistance6;
-#endif`;ze.a.IncludesShadersStore.clipPlaneVertexDeclaration2=Vm;var km=`#version 300 es
-uniform mat4 view;
-uniform mat4 projection;
-uniform vec2 translationPivot;
-uniform vec3 worldOffset;
-#ifdef LOCAL
-uniform mat4 emitterWM;
-#endif
-
-in vec3 position;
-in float age;
-in float life;
-in vec3 size;
-#ifndef BILLBOARD
-in vec3 initialDirection;
-#endif
-#ifdef BILLBOARDSTRETCHED
-in vec3 direction;
-#endif
-in float angle;
-#ifdef ANIMATESHEET
-in float cellIndex;
-#endif
-in vec2 offset;
-in vec2 uv;
-out vec2 vUV;
-out vec4 vColor;
-out vec3 vPositionW;
-#if defined(BILLBOARD) && !defined(BILLBOARDY) && !defined(BILLBOARDSTRETCHED)
-uniform mat4 invView;
-#endif
-#include<clipPlaneVertexDeclaration2>
-#ifdef COLORGRADIENTS
-uniform sampler2D colorGradientSampler;
-#else
-uniform vec4 colorDead;
-in vec4 color;
-#endif
-#ifdef ANIMATESHEET
-uniform vec3 sheetInfos;
-#endif
-#ifdef BILLBOARD
-uniform vec3 eyePosition;
-#endif
-vec3 rotate(vec3 yaxis,vec3 rotatedCorner) {
-vec3 xaxis=normalize(cross(vec3(0.,1.0,0.),yaxis));
-vec3 zaxis=normalize(cross(yaxis,xaxis));
-vec3 row0=vec3(xaxis.x,xaxis.y,xaxis.z);
-vec3 row1=vec3(yaxis.x,yaxis.y,yaxis.z);
-vec3 row2=vec3(zaxis.x,zaxis.y,zaxis.z);
-mat3 rotMatrix=mat3(row0,row1,row2);
-vec3 alignedCorner=rotMatrix*rotatedCorner;
-#ifdef LOCAL
-return ((emitterWM*vec4(position,1.0)).xyz+worldOffset)+alignedCorner;
-#else
-return (position+worldOffset)+alignedCorner;
-#endif
-}
-#ifdef BILLBOARDSTRETCHED
-vec3 rotateAlign(vec3 toCamera,vec3 rotatedCorner) {
-vec3 normalizedToCamera=normalize(toCamera);
-vec3 normalizedCrossDirToCamera=normalize(cross(normalize(direction),normalizedToCamera));
-vec3 crossProduct=normalize(cross(normalizedToCamera,normalizedCrossDirToCamera));
-vec3 row0=vec3(normalizedCrossDirToCamera.x,normalizedCrossDirToCamera.y,normalizedCrossDirToCamera.z);
-vec3 row1=vec3(crossProduct.x,crossProduct.y,crossProduct.z);
-vec3 row2=vec3(normalizedToCamera.x,normalizedToCamera.y,normalizedToCamera.z);
-mat3 rotMatrix=mat3(row0,row1,row2);
-vec3 alignedCorner=rotMatrix*rotatedCorner;
-#ifdef LOCAL
-return ((emitterWM*vec4(position,1.0)).xyz+worldOffset)+alignedCorner;
-#else
-return (position+worldOffset)+alignedCorner;
-#endif
-}
-#endif
-void main() {
-#ifdef ANIMATESHEET
-float rowOffset=floor(cellIndex/sheetInfos.z);
-float columnOffset=cellIndex-rowOffset*sheetInfos.z;
-vec2 uvScale=sheetInfos.xy;
-vec2 uvOffset=vec2(uv.x ,1.0-uv.y);
-vUV=(uvOffset+vec2(columnOffset,rowOffset))*uvScale;
-#else
-vUV=uv;
-#endif
-float ratio=age/life;
-#ifdef COLORGRADIENTS
-vColor=texture(colorGradientSampler,vec2(ratio,0));
-#else
-vColor=color*vec4(1.0-ratio)+colorDead*vec4(ratio);
-#endif
-vec2 cornerPos=(offset-translationPivot)*size.yz*size.x+translationPivot;
-#ifdef BILLBOARD
-vec4 rotatedCorner;
-rotatedCorner.w=0.;
-#ifdef BILLBOARDY
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.z=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.y=0.;
-vec3 yaxis=(position+worldOffset)-eyePosition;
-yaxis.y=0.;
-vPositionW=rotate(normalize(yaxis),rotatedCorner.xyz);
-vec4 viewPosition=(view*vec4(vPositionW,1.0));
-#elif defined(BILLBOARDSTRETCHED)
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.y=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.z=0.;
-vec3 toCamera=(position+worldOffset)-eyePosition;
-vPositionW=rotateAlign(toCamera,rotatedCorner.xyz);
-vec4 viewPosition=(view*vec4(vPositionW,1.0));
-#else
-
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.y=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.z=0.;
-
-#ifdef LOCAL
-vec4 viewPosition=view*vec4(((emitterWM*vec4(position,1.0)).xyz+worldOffset),1.0)+rotatedCorner;
-#else
-vec4 viewPosition=view*vec4((position+worldOffset),1.0)+rotatedCorner;
-#endif
-vPositionW=(invView*viewPosition).xyz;
-#endif
-#else
-
-vec3 rotatedCorner;
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.y=0.;
-rotatedCorner.z=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-vec3 yaxis=normalize(initialDirection);
-vPositionW=rotate(yaxis,rotatedCorner);
-
-vec4 viewPosition=view*vec4(vPositionW,1.0);
-#endif
-gl_Position=projection*viewPosition;
-
-#if defined(CLIPPLANE) || defined(CLIPPLANE2) || defined(CLIPPLANE3) || defined(CLIPPLANE4) || defined(CLIPPLANE5) || defined(CLIPPLANE6)
-vec4 worldPos=vec4(vPositionW,1.0);
-#endif
-#include<clipPlaneVertex>
-}`;ze.a.ShadersStore.gpuRenderParticlesVertexShader=km;var ar=function(r){function t(e,n,i,o,a){o===void 0&&(o=!1),a===void 0&&(a=null);var s=r.call(this,e)||this;s.layerMask=268435455,s._accumulatedCount=0,s._targetIndex=0,s._currentRenderId=-1,s._started=!1,s._stopped=!1,s._timeDelta=0,s._actualFrame=0,s._rawTextureWidth=256,s.onDisposeObservable=new C.c,s.onStoppedObservable=new C.c,s.forceDepthWrite=!1,s._preWarmDone=!1,s.isLocal=!1,s._onBeforeDrawParticlesObservable=null,i&&i.getClassName()!=="Scene"?(s._engine=i,s.defaultProjectionMatrix=u.a.PerspectiveFovLH(.8,1,.1,100)):(s._scene=i||te.a.LastCreatedScene,s._engine=s._scene.getEngine(),s.uniqueId=s._scene.getUniqueId(),s._scene.particleSystems.push(s)),s._customEffect={0:a},s._attachImageProcessingConfiguration(null),n.randomTextureSize||delete n.randomTextureSize;var d=Object(c.a)({capacity:5e4,randomTextureSize:s._engine.getCaps().maxTextureSize},n),p=n;isFinite(p)&&(d.capacity=p),s._capacity=d.capacity,s._activeCount=d.capacity,s._currentActiveCount=0,s._isAnimationSheetEnabled=o,s._updateEffectOptions={attributes:["position","initialPosition","age","life","seed","size","color","direction","initialDirection","angle","cellIndex","cellStartOffset","noiseCoordinates1","noiseCoordinates2"],uniformsNames:["currentCount","timeDelta","emitterWM","lifeTime","color1","color2","sizeRange","scaleRange","gravity","emitPower","direction1","direction2","minEmitBox","maxEmitBox","radius","directionRandomizer","height","coneAngle","stopFactor","angleRange","radiusRange","cellInfos","noiseStrength","limitVelocityDamping"],uniformBuffersNames:[],samplers:["randomSampler","randomSampler2","sizeGradientSampler","angularSpeedGradientSampler","velocityGradientSampler","limitVelocityGradientSampler","noiseSampler","dragGradientSampler"],defines:"",fallbacks:null,onCompiled:null,onError:null,indexParameters:null,maxSimultaneousLights:0,transformFeedbackVaryings:[]},s.particleEmitterType=new Nr;for(var b=Math.min(s._engine.getCaps().maxTextureSize,d.randomTextureSize),P=[],O=0;O<b;++O)P.push(Math.random()),P.push(Math.random()),P.push(Math.random()),P.push(Math.random());for(s._randomTexture=new ni(new Float32Array(P),b,1,h.a.TEXTUREFORMAT_RGBA,i,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE,h.a.TEXTURETYPE_FLOAT),s._randomTexture.wrapU=h.a.TEXTURE_WRAP_ADDRESSMODE,s._randomTexture.wrapV=h.a.TEXTURE_WRAP_ADDRESSMODE,P=[],O=0;O<b;++O)P.push(Math.random()),P.push(Math.random()),P.push(Math.random()),P.push(Math.random());return s._randomTexture2=new ni(new Float32Array(P),b,1,h.a.TEXTUREFORMAT_RGBA,i,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE,h.a.TEXTURETYPE_FLOAT),s._randomTexture2.wrapU=h.a.TEXTURE_WRAP_ADDRESSMODE,s._randomTexture2.wrapV=h.a.TEXTURE_WRAP_ADDRESSMODE,s._randomTextureSize=b,s}return Object(c.d)(t,r),Object.defineProperty(t,"IsSupported",{get:function(){return!!te.a.LastCreatedEngine&&te.a.LastCreatedEngine.webGLVersion>1},enumerable:!1,configurable:!0}),t.prototype.getCapacity=function(){return this._capacity},Object.defineProperty(t.prototype,"activeParticleCount",{get:function(){return this._activeCount},set:function(e){this._activeCount=Math.min(e,this._capacity)},enumerable:!1,configurable:!0}),t.prototype.isReady=function(){return this._updateEffect?!!(this.emitter&&this._updateEffect.isReady()&&(!this._imageProcessingConfiguration||this._imageProcessingConfiguration.isReady())&&this._getEffect().isReady()&&this.particleTexture&&this.particleTexture.isReady()):(this._recreateUpdateEffect(),this._recreateRenderEffect(),!1)},t.prototype.isStarted=function(){return this._started},t.prototype.isStopped=function(){return this._stopped},t.prototype.isStopping=function(){return!1},t.prototype.getActiveCount=function(){return this._currentActiveCount},t.prototype.start=function(e){var n=this;if(e===void 0&&(e=this.startDelay),!this.targetStopDuration&&this._hasTargetStopDurationDependantGradient())throw"Particle system started with a targetStopDuration dependant gradient (eg. startSizeGradients) but no targetStopDuration set";e?setTimeout(function(){n.start(0)},e):(this._started=!0,this._stopped=!1,this._preWarmDone=!1,this.beginAnimationOnStart&&this.animations&&this.animations.length>0&&this._scene&&this._scene.beginAnimation(this,this.beginAnimationFrom,this.beginAnimationTo,this.beginAnimationLoop))},t.prototype.stop=function(){this._stopped||(this._stopped=!0)},t.prototype.reset=function(){this._releaseBuffers(),this._releaseVAOs(),this._currentActiveCount=0,this._targetIndex=0},t.prototype.getClassName=function(){return"GPUParticleSystem"},t.prototype.getCustomEffect=function(e){var n;return e===void 0&&(e=0),(n=this._customEffect[e])!==null&&n!==void 0?n:this._customEffect[0]},t.prototype.setCustomEffect=function(e,n){n===void 0&&(n=0),this._customEffect[n]=e},Object.defineProperty(t.prototype,"onBeforeDrawParticlesObservable",{get:function(){return this._onBeforeDrawParticlesObservable||(this._onBeforeDrawParticlesObservable=new C.c),this._onBeforeDrawParticlesObservable},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"vertexShaderName",{get:function(){return"gpuRenderParticles"},enumerable:!1,configurable:!0}),t.prototype._removeGradientAndTexture=function(e,n,i){return r.prototype._removeGradientAndTexture.call(this,e,n,i),this._releaseBuffers(),this},t.prototype.addColorGradient=function(e,n,i){this._colorGradients||(this._colorGradients=[]);var o=new Mc(e,n);return this._colorGradients.push(o),this._refreshColorGradient(!0),this._releaseBuffers(),this},t.prototype._refreshColorGradient=function(e){e===void 0&&(e=!1),this._colorGradients&&(e&&this._colorGradients.sort(function(n,i){return n.gradient<i.gradient?-1:n.gradient>i.gradient?1:0}),this._colorGradientsTexture&&(this._colorGradientsTexture.dispose(),this._colorGradientsTexture=null))},t.prototype.forceRefreshGradients=function(){this._refreshColorGradient(),this._refreshFactorGradient(this._sizeGradients,"_sizeGradientsTexture"),this._refreshFactorGradient(this._angularSpeedGradients,"_angularSpeedGradientsTexture"),this._refreshFactorGradient(this._velocityGradients,"_velocityGradientsTexture"),this._refreshFactorGradient(this._limitVelocityGradients,"_limitVelocityGradientsTexture"),this._refreshFactorGradient(this._dragGradients,"_dragGradientsTexture"),this.reset()},t.prototype.removeColorGradient=function(e){return this._removeGradientAndTexture(e,this._colorGradients,this._colorGradientsTexture),this._colorGradientsTexture=null,this},t.prototype._addFactorGradient=function(e,n,i){var o=new Ic(n,i);e.push(o),this._releaseBuffers()},t.prototype.addSizeGradient=function(e,n){return this._sizeGradients||(this._sizeGradients=[]),this._addFactorGradient(this._sizeGradients,e,n),this._refreshFactorGradient(this._sizeGradients,"_sizeGradientsTexture",!0),this._releaseBuffers(),this},t.prototype.removeSizeGradient=function(e){return this._removeGradientAndTexture(e,this._sizeGradients,this._sizeGradientsTexture),this._sizeGradientsTexture=null,this},t.prototype._refreshFactorGradient=function(e,n,i){i===void 0&&(i=!1),e&&(i&&e.sort(function(o,a){return o.gradient<a.gradient?-1:o.gradient>a.gradient?1:0}),this[n]&&(this[n].dispose(),this[n]=null))},t.prototype.addAngularSpeedGradient=function(e,n){return this._angularSpeedGradients||(this._angularSpeedGradients=[]),this._addFactorGradient(this._angularSpeedGradients,e,n),this._refreshFactorGradient(this._angularSpeedGradients,"_angularSpeedGradientsTexture",!0),this._releaseBuffers(),this},t.prototype.removeAngularSpeedGradient=function(e){return this._removeGradientAndTexture(e,this._angularSpeedGradients,this._angularSpeedGradientsTexture),this._angularSpeedGradientsTexture=null,this},t.prototype.addVelocityGradient=function(e,n){return this._velocityGradients||(this._velocityGradients=[]),this._addFactorGradient(this._velocityGradients,e,n),this._refreshFactorGradient(this._velocityGradients,"_velocityGradientsTexture",!0),this._releaseBuffers(),this},t.prototype.removeVelocityGradient=function(e){return this._removeGradientAndTexture(e,this._velocityGradients,this._velocityGradientsTexture),this._velocityGradientsTexture=null,this},t.prototype.addLimitVelocityGradient=function(e,n){return this._limitVelocityGradients||(this._limitVelocityGradients=[]),this._addFactorGradient(this._limitVelocityGradients,e,n),this._refreshFactorGradient(this._limitVelocityGradients,"_limitVelocityGradientsTexture",!0),this._releaseBuffers(),this},t.prototype.removeLimitVelocityGradient=function(e){return this._removeGradientAndTexture(e,this._limitVelocityGradients,this._limitVelocityGradientsTexture),this._limitVelocityGradientsTexture=null,this},t.prototype.addDragGradient=function(e,n){return this._dragGradients||(this._dragGradients=[]),this._addFactorGradient(this._dragGradients,e,n),this._refreshFactorGradient(this._dragGradients,"_dragGradientsTexture",!0),this._releaseBuffers(),this},t.prototype.removeDragGradient=function(e){return this._removeGradientAndTexture(e,this._dragGradients,this._dragGradientsTexture),this._dragGradientsTexture=null,this},t.prototype.addEmitRateGradient=function(e,n,i){return this},t.prototype.removeEmitRateGradient=function(e){return this},t.prototype.addStartSizeGradient=function(e,n,i){return this},t.prototype.removeStartSizeGradient=function(e){return this},t.prototype.addColorRemapGradient=function(e,n,i){return this},t.prototype.removeColorRemapGradient=function(){return this},t.prototype.addAlphaRemapGradient=function(e,n,i){return this},t.prototype.removeAlphaRemapGradient=function(){return this},t.prototype.addRampGradient=function(e,n){return this},t.prototype.removeRampGradient=function(){return this},t.prototype.getRampGradients=function(){return null},Object.defineProperty(t.prototype,"useRampGradients",{get:function(){return!1},set:function(e){},enumerable:!1,configurable:!0}),t.prototype.addLifeTimeGradient=function(e,n,i){return this},t.prototype.removeLifeTimeGradient=function(e){return this},t.prototype._reset=function(){this._releaseBuffers()},t.prototype._createUpdateVAO=function(e){var n={};n.position=e.createVertexBuffer("position",0,3);var i=3;this.particleEmitterType instanceof wr&&(n.initialPosition=e.createVertexBuffer("initialPosition",i,3),i+=3),n.age=e.createVertexBuffer("age",i,1),i+=1,n.life=e.createVertexBuffer("life",i,1),i+=1,n.seed=e.createVertexBuffer("seed",i,4),i+=4,n.size=e.createVertexBuffer("size",i,3),i+=3,this._colorGradientsTexture||(n.color=e.createVertexBuffer("color",i,4),i+=4),n.direction=e.createVertexBuffer("direction",i,3),i+=3,this._isBillboardBased||(n.initialDirection=e.createVertexBuffer("initialDirection",i,3),i+=3),this._angularSpeedGradientsTexture?(n.angle=e.createVertexBuffer("angle",i,1),i+=1):(n.angle=e.createVertexBuffer("angle",i,2),i+=2),this._isAnimationSheetEnabled&&(n.cellIndex=e.createVertexBuffer("cellIndex",i,1),i+=1,this.spriteRandomStartCell&&(n.cellStartOffset=e.createVertexBuffer("cellStartOffset",i,1),i+=1)),this.noiseTexture&&(n.noiseCoordinates1=e.createVertexBuffer("noiseCoordinates1",i,3),i+=3,n.noiseCoordinates2=e.createVertexBuffer("noiseCoordinates2",i,3),i+=3);var o=this._engine.recordVertexArrayObject(n,null,this._updateEffect);return this._engine.bindArrayBuffer(null),o},t.prototype._createRenderVAO=function(e,n){var i={};i.position=e.createVertexBuffer("position",0,3,this._attributesStrideSize,!0);var o=3;this.particleEmitterType instanceof wr&&(o+=3),i.age=e.createVertexBuffer("age",o,1,this._attributesStrideSize,!0),o+=1,i.life=e.createVertexBuffer("life",o,1,this._attributesStrideSize,!0),o+=5,i.size=e.createVertexBuffer("size",o,3,this._attributesStrideSize,!0),o+=3,this._colorGradientsTexture||(i.color=e.createVertexBuffer("color",o,4,this._attributesStrideSize,!0),o+=4),this.billboardMode===ln.BILLBOARDMODE_STRETCHED&&(i.direction=e.createVertexBuffer("direction",o,3,this._attributesStrideSize,!0)),o+=3,this._isBillboardBased||(i.initialDirection=e.createVertexBuffer("initialDirection",o,3,this._attributesStrideSize,!0),o+=3),i.angle=e.createVertexBuffer("angle",o,1,this._attributesStrideSize,!0),this._angularSpeedGradientsTexture?o++:o+=2,this._isAnimationSheetEnabled&&(i.cellIndex=e.createVertexBuffer("cellIndex",o,1,this._attributesStrideSize,!0),o+=1,this.spriteRandomStartCell&&(i.cellStartOffset=e.createVertexBuffer("cellStartOffset",o,1,this._attributesStrideSize,!0),o+=1)),this.noiseTexture&&(i.noiseCoordinates1=e.createVertexBuffer("noiseCoordinates1",o,3,this._attributesStrideSize,!0),o+=3,i.noiseCoordinates2=e.createVertexBuffer("noiseCoordinates2",o,3,this._attributesStrideSize,!0),o+=3),i.offset=n.createVertexBuffer("offset",0,2),i.uv=n.createVertexBuffer("uv",2,2);var a=this._engine.recordVertexArrayObject(i,null,this._getEffect());return this._engine.bindArrayBuffer(null),a},t.prototype._initialize=function(e){if(e===void 0&&(e=!1),!this._buffer0||e){var n=this._engine,i=new Array;this._attributesStrideSize=21,this._targetIndex=0,this.particleEmitterType instanceof wr&&(this._attributesStrideSize+=3),this.isBillboardBased||(this._attributesStrideSize+=3),this._colorGradientsTexture&&(this._attributesStrideSize-=4),this._angularSpeedGradientsTexture&&(this._attributesStrideSize-=1),this._isAnimationSheetEnabled&&(this._attributesStrideSize+=1,this.spriteRandomStartCell&&(this._attributesStrideSize+=1)),this.noiseTexture&&(this._attributesStrideSize+=6);for(var o=this.particleEmitterType instanceof wr,a=u.c.Vector3[0],s=0;s<this._capacity;s++)i.push(0),i.push(0),i.push(0),o&&(this.particleEmitterType.particlePositionGenerator(s,null,a),i.push(a.x),i.push(a.y),i.push(a.z)),i.push(0),i.push(0),i.push(Math.random()),i.push(Math.random()),i.push(Math.random()),i.push(Math.random()),i.push(0),i.push(0),i.push(0),this._colorGradientsTexture||(i.push(0),i.push(0),i.push(0),i.push(0)),o?(this.particleEmitterType.particleDestinationGenerator(s,null,a),i.push(a.x),i.push(a.y),i.push(a.z)):(i.push(0),i.push(0),i.push(0)),this.isBillboardBased||(i.push(0),i.push(0),i.push(0)),i.push(0),this._angularSpeedGradientsTexture||i.push(0),this._isAnimationSheetEnabled&&(i.push(0),this.spriteRandomStartCell&&i.push(0)),this.noiseTexture&&(i.push(Math.random()),i.push(Math.random()),i.push(Math.random()),i.push(Math.random()),i.push(Math.random()),i.push(Math.random()));var d=new Float32Array([.5,.5,1,1,-.5,.5,0,1,-.5,-.5,0,0,.5,-.5,1,0]);this._buffer0=new Oe.a(n,i,!1,this._attributesStrideSize),this._buffer1=new Oe.a(n,i,!1,this._attributesStrideSize),this._spriteBuffer=new Oe.a(n,d,!1,4),this._updateVAO=[],this._updateVAO.push(this._createUpdateVAO(this._buffer0)),this._updateVAO.push(this._createUpdateVAO(this._buffer1)),this._renderVAO=[],this._renderVAO.push(this._createRenderVAO(this._buffer1,this._spriteBuffer)),this._renderVAO.push(this._createRenderVAO(this._buffer0,this._spriteBuffer)),this._sourceBuffer=this._buffer0,this._targetBuffer=this._buffer1}},t.prototype._recreateUpdateEffect=function(){var e=this.particleEmitterType?this.particleEmitterType.getEffectDefines():"";this._isBillboardBased&&(e+=`
-#define BILLBOARD`),this._colorGradientsTexture&&(e+=`
-#define COLORGRADIENTS`),this._sizeGradientsTexture&&(e+=`
-#define SIZEGRADIENTS`),this._angularSpeedGradientsTexture&&(e+=`
-#define ANGULARSPEEDGRADIENTS`),this._velocityGradientsTexture&&(e+=`
-#define VELOCITYGRADIENTS`),this._limitVelocityGradientsTexture&&(e+=`
-#define LIMITVELOCITYGRADIENTS`),this._dragGradientsTexture&&(e+=`
-#define DRAGGRADIENTS`),this.isAnimationSheetEnabled&&(e+=`
-#define ANIMATESHEET`,this.spriteRandomStartCell&&(e+=`
-#define ANIMATESHEETRANDOMSTART`)),this.noiseTexture&&(e+=`
-#define NOISE`),this.isLocal&&(e+=`
-#define LOCAL`),this._updateEffect&&this._updateEffectOptions.defines===e||(this._updateEffectOptions.transformFeedbackVaryings=["outPosition"],this.particleEmitterType instanceof wr&&this._updateEffectOptions.transformFeedbackVaryings.push("outInitialPosition"),this._updateEffectOptions.transformFeedbackVaryings.push("outAge"),this._updateEffectOptions.transformFeedbackVaryings.push("outLife"),this._updateEffectOptions.transformFeedbackVaryings.push("outSeed"),this._updateEffectOptions.transformFeedbackVaryings.push("outSize"),this._colorGradientsTexture||this._updateEffectOptions.transformFeedbackVaryings.push("outColor"),this._updateEffectOptions.transformFeedbackVaryings.push("outDirection"),this._isBillboardBased||this._updateEffectOptions.transformFeedbackVaryings.push("outInitialDirection"),this._updateEffectOptions.transformFeedbackVaryings.push("outAngle"),this.isAnimationSheetEnabled&&(this._updateEffectOptions.transformFeedbackVaryings.push("outCellIndex"),this.spriteRandomStartCell&&this._updateEffectOptions.transformFeedbackVaryings.push("outCellStartOffset")),this.noiseTexture&&(this._updateEffectOptions.transformFeedbackVaryings.push("outNoiseCoordinates1"),this._updateEffectOptions.transformFeedbackVaryings.push("outNoiseCoordinates2")),this._updateEffectOptions.defines=e,this._updateEffect=new ze.a("gpuUpdateParticles",this._updateEffectOptions,this._engine))},t.prototype._getEffect=function(){var e;return(e=this.getCustomEffect())!==null&&e!==void 0?e:this._renderEffect},t.prototype.fillDefines=function(e,n){if(this._scene&&(this._scene.clipPlane&&e.push("#define CLIPPLANE"),this._scene.clipPlane2&&e.push("#define CLIPPLANE2"),this._scene.clipPlane3&&e.push("#define CLIPPLANE3"),this._scene.clipPlane4&&e.push("#define CLIPPLANE4"),this._scene.clipPlane5&&e.push("#define CLIPPLANE5"),this._scene.clipPlane6&&e.push("#define CLIPPLANE6")),this.blendMode===ln.BLENDMODE_MULTIPLY&&e.push("#define BLENDMULTIPLYMODE"),this.isLocal&&e.push("#define LOCAL"),this._isBillboardBased)switch(e.push("#define BILLBOARD"),this.billboardMode){case ln.BILLBOARDMODE_Y:e.push("#define BILLBOARDY");break;case ln.BILLBOARDMODE_STRETCHED:e.push("#define BILLBOARDSTRETCHED");break;case ln.BILLBOARDMODE_ALL:e.push("#define BILLBOARDMODE_ALL")}this._colorGradientsTexture&&e.push("#define COLORGRADIENTS"),this.isAnimationSheetEnabled&&e.push("#define ANIMATESHEET"),this._imageProcessingConfiguration&&(this._imageProcessingConfiguration.prepareDefines(this._imageProcessingConfigurationDefines),e.push(""+this._imageProcessingConfigurationDefines.toString()))},t.prototype.fillUniformsAttributesAndSamplerNames=function(e,n,i){n.push("position","age","life","size","color","offset","uv","direction","initialDirection","angle","cellIndex"),e.push("emitterWM","worldOffset","view","projection","colorDead","invView","vClipPlane","vClipPlane2","vClipPlane3","vClipPlane4","vClipPlane5","vClipPlane6","sheetInfos","translationPivot","eyePosition"),i.push("diffuseSampler","colorGradientSampler"),this._imageProcessingConfiguration&&(yn.a.PrepareUniforms(e,this._imageProcessingConfigurationDefines),yn.a.PrepareSamplers(i,this._imageProcessingConfigurationDefines))},t.prototype._recreateRenderEffect=function(){var e=this.getCustomEffect();if(e)return e;var n=[];this.fillDefines(n);var i=n.join(`
-`);if(this._renderEffect&&this._renderEffect.defines===i)return this._renderEffect;var o=[],a=[],s=[];return this.fillUniformsAttributesAndSamplerNames(a,o,s),this._renderEffect=new ze.a("gpuRenderParticles",o,a,s,this._engine,i),this._renderEffect},t.prototype.animate=function(e){var n;e===void 0&&(e=!1),this._timeDelta=this.updateSpeed*(e?this.preWarmStepOffset:((n=this._scene)===null||n===void 0?void 0:n.getAnimationRatio())||1),this._actualFrame+=this._timeDelta,this._stopped||this.targetStopDuration&&this._actualFrame>=this.targetStopDuration&&this.stop()},t.prototype._createFactorGradientTexture=function(e,n){var i=this[n];if(e&&e.length&&!i){for(var o=new Float32Array(this._rawTextureWidth),a=0;a<this._rawTextureWidth;a++){var s=a/this._rawTextureWidth;In.GetCurrentGradient(s,e,function(d,p,b){o[a]=$.a.Lerp(d.factor1,p.factor1,b)})}this[n]=ni.CreateRTexture(o,this._rawTextureWidth,1,this._scene||this._engine,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE)}},t.prototype._createSizeGradientTexture=function(){this._createFactorGradientTexture(this._sizeGradients,"_sizeGradientsTexture")},t.prototype._createAngularSpeedGradientTexture=function(){this._createFactorGradientTexture(this._angularSpeedGradients,"_angularSpeedGradientsTexture")},t.prototype._createVelocityGradientTexture=function(){this._createFactorGradientTexture(this._velocityGradients,"_velocityGradientsTexture")},t.prototype._createLimitVelocityGradientTexture=function(){this._createFactorGradientTexture(this._limitVelocityGradients,"_limitVelocityGradientsTexture")},t.prototype._createDragGradientTexture=function(){this._createFactorGradientTexture(this._dragGradients,"_dragGradientsTexture")},t.prototype._createColorGradientTexture=function(){if(this._colorGradients&&this._colorGradients.length&&!this._colorGradientsTexture){for(var e=new Uint8Array(4*this._rawTextureWidth),n=M.c.Color4[0],i=0;i<this._rawTextureWidth;i++){var o=i/this._rawTextureWidth;In.GetCurrentGradient(o,this._colorGradients,function(a,s,d){M.b.LerpToRef(a.color1,s.color1,d,n),e[4*i]=255*n.r,e[4*i+1]=255*n.g,e[4*i+2]=255*n.b,e[4*i+3]=255*n.a})}this._colorGradientsTexture=ni.CreateRGBATexture(e,this._rawTextureWidth,1,this._scene,!1,!1,h.a.TEXTURE_NEAREST_SAMPLINGMODE)}},t.prototype.render=function(e){var n,i;if(e===void 0&&(e=!1),!this._started||(this._createColorGradientTexture(),this._createSizeGradientTexture(),this._createAngularSpeedGradientTexture(),this._createVelocityGradientTexture(),this._createLimitVelocityGradientTexture(),this._createDragGradientTexture(),this._recreateUpdateEffect(),this._recreateRenderEffect(),!this.isReady()))return 0;if(!e&&this._scene){if(!this._preWarmDone&&this.preWarmCycles){for(var o=0;o<this.preWarmCycles;o++)this.animate(!0),this.render(!0);this._preWarmDone=!0}if(this._currentRenderId===this._scene.getFrameId())return 0;this._currentRenderId=this._scene.getFrameId()}if(this._initialize(),this._accumulatedCount+=this.emitRate*this._timeDelta,this._accumulatedCount>1){var a=0|this._accumulatedCount;this._accumulatedCount-=a,this._currentActiveCount=Math.min(this._activeCount,this._currentActiveCount+a)}if(!this._currentActiveCount)return 0;this._engine.enableEffect(this._updateEffect);var s,d=this._engine;if(!d.setState)throw new Error("GPU particles cannot work with a full Engine. ThinEngine is not supported");if(this._updateEffect.setFloat("currentCount",this._currentActiveCount),this._updateEffect.setFloat("timeDelta",this._timeDelta),this._updateEffect.setFloat("stopFactor",this._stopped?0:1),this._updateEffect.setTexture("randomSampler",this._randomTexture),this._updateEffect.setTexture("randomSampler2",this._randomTexture2),this._updateEffect.setFloat2("lifeTime",this.minLifeTime,this.maxLifeTime),this._updateEffect.setFloat2("emitPower",this.minEmitPower,this.maxEmitPower),this._colorGradientsTexture||(this._updateEffect.setDirectColor4("color1",this.color1),this._updateEffect.setDirectColor4("color2",this.color2)),this._updateEffect.setFloat2("sizeRange",this.minSize,this.maxSize),this._updateEffect.setFloat4("scaleRange",this.minScaleX,this.maxScaleX,this.minScaleY,this.maxScaleY),this._updateEffect.setFloat4("angleRange",this.minAngularSpeed,this.maxAngularSpeed,this.minInitialRotation,this.maxInitialRotation),this._updateEffect.setVector3("gravity",this.gravity),this._sizeGradientsTexture&&this._updateEffect.setTexture("sizeGradientSampler",this._sizeGradientsTexture),this._angularSpeedGradientsTexture&&this._updateEffect.setTexture("angularSpeedGradientSampler",this._angularSpeedGradientsTexture),this._velocityGradientsTexture&&this._updateEffect.setTexture("velocityGradientSampler",this._velocityGradientsTexture),this._limitVelocityGradientsTexture&&(this._updateEffect.setTexture("limitVelocityGradientSampler",this._limitVelocityGradientsTexture),this._updateEffect.setFloat("limitVelocityDamping",this.limitVelocityDamping)),this._dragGradientsTexture&&this._updateEffect.setTexture("dragGradientSampler",this._dragGradientsTexture),this.particleEmitterType&&this.particleEmitterType.applyToShader(this._updateEffect),this._isAnimationSheetEnabled&&this._updateEffect.setFloat3("cellInfos",this.startSpriteCellID,this.endSpriteCellID,this.spriteCellChangeSpeed),this.noiseTexture&&(this._updateEffect.setTexture("noiseSampler",this.noiseTexture),this._updateEffect.setVector3("noiseStrength",this.noiseStrength)),this.emitter.position)s=this.emitter.getWorldMatrix();else{var p=this.emitter;s=u.a.Translation(p.x,p.y,p.z)}if(this.isLocal||this._updateEffect.setMatrix("emitterWM",s),this._engine.bindVertexArrayObject(this._updateVAO[this._targetIndex],null),d.bindTransformFeedbackBuffer(this._targetBuffer.getBuffer()),d.setRasterizerState(!1),d.beginTransformFeedback(!0),d.drawArraysType(h.a.MATERIAL_PointListDrawMode,0,this._currentActiveCount),d.endTransformFeedback(),d.setRasterizerState(!0),d.bindTransformFeedbackBuffer(null),!e){var b=this._getEffect();this._engine.enableEffect(b);var P=((n=this._scene)===null||n===void 0?void 0:n.getViewMatrix())||u.a.IdentityReadOnly;if(b.setMatrix("view",P),b.setMatrix("projection",(i=this.defaultProjectionMatrix)!==null&&i!==void 0?i:this._scene.getProjectionMatrix()),b.setTexture("diffuseSampler",this.particleTexture),b.setVector2("translationPivot",this.translationPivot),b.setVector3("worldOffset",this.worldOffset),this.isLocal&&b.setMatrix("emitterWM",s),this._colorGradientsTexture?b.setTexture("colorGradientSampler",this._colorGradientsTexture):b.setDirectColor4("colorDead",this.colorDead),this._isAnimationSheetEnabled&&this.particleTexture){var O=this.particleTexture.getBaseSize();b.setFloat3("sheetInfos",this.spriteCellWidth/O.width,this.spriteCellHeight/O.height,O.width/this.spriteCellWidth)}if(this._isBillboardBased&&this._scene){var B=this._scene.activeCamera;b.setVector3("eyePosition",B.globalPosition)}var F=b.defines;if(this._scene&&(this._scene.clipPlane||this._scene.clipPlane2||this._scene.clipPlane3||this._scene.clipPlane4||this._scene.clipPlane5||this._scene.clipPlane6)&&et.a.BindClipPlane(b,this._scene),F.indexOf("#define BILLBOARDMODE_ALL")>=0){var z=P.clone();z.invert(),b.setMatrix("invView",z)}switch(this._imageProcessingConfiguration&&!this._imageProcessingConfiguration.applyByPostProcess&&this._imageProcessingConfiguration.bind(b),this.blendMode){case ln.BLENDMODE_ADD:this._engine.setAlphaMode(h.a.ALPHA_ADD);break;case ln.BLENDMODE_ONEONE:this._engine.setAlphaMode(h.a.ALPHA_ONEONE);break;case ln.BLENDMODE_STANDARD:this._engine.setAlphaMode(h.a.ALPHA_COMBINE);break;case ln.BLENDMODE_MULTIPLY:this._engine.setAlphaMode(h.a.ALPHA_MULTIPLY)}this.forceDepthWrite&&d.setDepthWrite(!0),this._engine.bindVertexArrayObject(this._renderVAO[this._targetIndex],null),this._onBeforeDrawParticlesObservable&&this._onBeforeDrawParticlesObservable.notifyObservers(b),this._engine.drawArraysType(h.a.MATERIAL_TriangleFanDrawMode,0,4,this._currentActiveCount),this._engine.setAlphaMode(h.a.ALPHA_DISABLE)}this._targetIndex++,this._targetIndex===2&&(this._targetIndex=0);var J=this._sourceBuffer;return this._sourceBuffer=this._targetBuffer,this._targetBuffer=J,this._currentActiveCount},t.prototype.rebuild=function(){this._initialize(!0)},t.prototype._releaseBuffers=function(){this._buffer0&&(this._buffer0.dispose(),this._buffer0=null),this._buffer1&&(this._buffer1.dispose(),this._buffer1=null),this._spriteBuffer&&(this._spriteBuffer.dispose(),this._spriteBuffer=null)},t.prototype._releaseVAOs=function(){if(this._updateVAO){for(var e=0;e<this._updateVAO.length;e++)this._engine.releaseVertexArrayObject(this._updateVAO[e]);for(this._updateVAO=[],e=0;e<this._renderVAO.length;e++)this._engine.releaseVertexArrayObject(this._renderVAO[e]);this._renderVAO=[]}},t.prototype.dispose=function(e){if(e===void 0&&(e=!0),this._scene){var n=this._scene.particleSystems.indexOf(this);n>-1&&this._scene.particleSystems.splice(n,1)}this._releaseBuffers(),this._releaseVAOs(),this._colorGradientsTexture&&(this._colorGradientsTexture.dispose(),this._colorGradientsTexture=null),this._sizeGradientsTexture&&(this._sizeGradientsTexture.dispose(),this._sizeGradientsTexture=null),this._angularSpeedGradientsTexture&&(this._angularSpeedGradientsTexture.dispose(),this._angularSpeedGradientsTexture=null),this._velocityGradientsTexture&&(this._velocityGradientsTexture.dispose(),this._velocityGradientsTexture=null),this._limitVelocityGradientsTexture&&(this._limitVelocityGradientsTexture.dispose(),this._limitVelocityGradientsTexture=null),this._dragGradientsTexture&&(this._dragGradientsTexture.dispose(),this._dragGradientsTexture=null),this._randomTexture&&(this._randomTexture.dispose(),this._randomTexture=null),this._randomTexture2&&(this._randomTexture2.dispose(),this._randomTexture2=null),e&&this.particleTexture&&(this.particleTexture.dispose(),this.particleTexture=null),e&&this.noiseTexture&&(this.noiseTexture.dispose(),this.noiseTexture=null),this.onStoppedObservable.clear(),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear()},t.prototype.clone=function(e,n){var i=this.serialize(),o=t.Parse(i,this._scene||this._engine,""),a=Object(c.a)({},this._customEffect);return o.name=e,o._customEffect=a,n===void 0&&(n=this.emitter),o.emitter=n,o.noiseTexture=this.noiseTexture,o},t.prototype.serialize=function(e){e===void 0&&(e=!1);var n={};return ln._Serialize(n,this,e),n.activeParticleCount=this.activeParticleCount,n.randomTextureSize=this._randomTextureSize,n},t.Parse=function(e,n,i,o){o===void 0&&(o=!1);var a=new t(e.name,{capacity:e.capacity,randomTextureSize:e.randomTextureSize},n);return e.activeParticleCount&&(a.activeParticleCount=e.activeParticleCount),ln._Parse(e,a,n,i),e.preventAutoStart&&(a.preventAutoStart=e.preventAutoStart),o||a.preventAutoStart||a.start(),a},t}(yo),Ea=function(){function r(){this.systems=new Array}return Object.defineProperty(r.prototype,"emitterNode",{get:function(){return this._emitterNode},enumerable:!1,configurable:!0}),r.prototype.setEmitterAsSphere=function(t,e,n){this._emitterNode&&this._emitterNode.dispose(),this._emitterCreationOptions={kind:"Sphere",options:t,renderingGroupId:e};var i=Fn.a.CreateSphere("emitterSphere",{diameter:t.diameter,segments:t.segments},n);i.renderingGroupId=e;var o=new Ft.a("emitterSphereMaterial",n);o.emissiveColor=t.color,i.material=o;for(var a=0,s=this.systems;a<s.length;a++)s[a].emitter=i;this._emitterNode=i},r.prototype.start=function(t){for(var e=0,n=this.systems;e<n.length;e++){var i=n[e];t&&(i.emitter=t),i.start()}},r.prototype.dispose=function(){for(var t=0,e=this.systems;t<e.length;t++)e[t].dispose();this.systems=[],this._emitterNode&&(this._emitterNode.dispose(),this._emitterNode=null)},r.prototype.serialize=function(t){t===void 0&&(t=!1);for(var e={systems:[]},n=0,i=this.systems;n<i.length;n++){var o=i[n];e.systems.push(o.serialize(t))}return this._emitterNode&&(e.emitter=this._emitterCreationOptions),e},r.Parse=function(t,e,n){n===void 0&&(n=!1);var i=new r,o=this.BaseAssetsUrl+"/textures/";e=e||te.a.LastCreatedScene;for(var a=0,s=t.systems;a<s.length;a++){var d=s[a];i.systems.push(n?ar.Parse(d,e,o,!0):ln.Parse(d,e,o,!0))}if(t.emitter){var p=t.emitter.options;switch(t.emitter.kind){case"Sphere":i.setEmitterAsSphere({diameter:p.diameter,segments:p.segments,color:M.a.FromArray(p.color)},t.emitter.renderingGroupId,e)}}return i},r.BaseAssetsUrl="https://assets.babylonjs.com/particles",r}(),Gm=function(){function r(){}return r.CreateDefault=function(t,e,n,i){var o;return e===void 0&&(e=500),i===void 0&&(i=!1),(o=i?new ar("default system",{capacity:e},n):new ln("default system",e,n)).emitter=t,o.particleTexture=new we.a("https://www.babylonjs.com/assets/Flare.png",o.getScene()),o.createConeEmitter(.1,Math.PI/4),o.color1=new M.b(1,1,1,1),o.color2=new M.b(1,1,1,1),o.colorDead=new M.b(1,1,1,0),o.minSize=.1,o.maxSize=.1,o.minEmitPower=2,o.maxEmitPower=2,o.updateSpeed=1/60,o.emitRate=30,o},r.CreateAsync=function(t,e,n){n===void 0&&(n=!1),e||(e=te.a.LastCreatedScene);var i={};return e._addPendingData(i),new Promise(function(o,a){if(n&&!ar.IsSupported)return e._removePendingData(i),a("Particle system with GPU is not supported.");Xe.b.LoadFile(r.BaseAssetsUrl+"/systems/"+t+".json",function(s){e._removePendingData(i);var d=JSON.parse(s.toString());return o(Ea.Parse(d,e,n))},void 0,void 0,void 0,function(){return e._removePendingData(i),a("An error occured while the creation of your particle system. Check if your type '"+t+"' exists.")})})},r.ExportSet=function(t){for(var e=new Ea,n=0,i=t;n<i.length;n++){var o=i[n];e.systems.push(o)}return e},r.ParseFromFileAsync=function(t,e,n,i,o){return i===void 0&&(i=!1),o===void 0&&(o=""),new Promise(function(a,s){var d=new re.a;d.addEventListener("readystatechange",function(){if(d.readyState==4)if(d.status==200){var p=JSON.parse(d.responseText),b=void 0;b=i?ar.Parse(p,n,o):ln.Parse(p,n,o),t&&(b.name=t),a(b)}else s("Unable to load the particle system")}),d.open("GET",e),d.send()})},r.CreateFromSnippetAsync=function(t,e,n,i){var o=this;if(n===void 0&&(n=!1),i===void 0&&(i=""),t==="_BLANK"){var a=this.CreateDefault(null);return a.start(),Promise.resolve(a)}return new Promise(function(s,d){var p=new re.a;p.addEventListener("readystatechange",function(){if(p.readyState==4)if(p.status==200){var b=JSON.parse(JSON.parse(p.responseText).jsonPayload),P=JSON.parse(b.particleSystem),O=void 0;(O=n?ar.Parse(P,e,i):ln.Parse(P,e,i)).snippetId=t,s(O)}else d("Unable to load the snippet "+t)}),p.open("GET",o.SnippetUrl+"/"+t.replace(/#/g,"/")),p.send()})},r.BaseAssetsUrl=Ea.BaseAssetsUrl,r.SnippetUrl="https://snippet.babylonjs.com",r}();U.a.AddParser(at.a.NAME_PARTICLESYSTEM,function(r,t,e,n){var i=U.a.GetIndividualParser(at.a.NAME_PARTICLESYSTEM);if(i&&r.particleSystems!==void 0&&r.particleSystems!==null)for(var o=0,a=r.particleSystems.length;o<a;o++){var s=r.particleSystems[o];e.particleSystems.push(i(s,t,n))}}),U.a.AddIndividualParser(at.a.NAME_PARTICLESYSTEM,function(r,t,e){return r.activeParticleCount?ar.Parse(r,t,e):ln.Parse(r,t,e)}),Ue.a.prototype.createEffectForParticles=function(r,t,e,n,i,o,a,s){var d;t===void 0&&(t=[]),e===void 0&&(e=[]),n===void 0&&(n="");var p=[],b=[],P=[];return s?s.fillUniformsAttributesAndSamplerNames(b,p,P):(p=ln._GetAttributeNamesOrOptions(),b=ln._GetEffectCreationOptions()),n.indexOf(" BILLBOARD")===-1&&(n+=`
-#define BILLBOARD
-`),e.indexOf("diffuseSampler")===-1&&e.push("diffuseSampler"),this.createEffect({vertex:(d=s?.vertexShaderName)!==null&&d!==void 0?d:"particles",fragmentElement:r},p,b.concat(t),P.concat(e),n,i,o,a)},De.a.prototype.getEmittedParticleSystems=function(){for(var r=new Array,t=0;t<this.getScene().particleSystems.length;t++){var e=this.getScene().particleSystems[t];e.emitter===this&&r.push(e)}return r},De.a.prototype.getHierarchyEmittedParticleSystems=function(){var r=new Array,t=this.getDescendants();t.push(this);for(var e=0;e<this.getScene().particleSystems.length;e++){var n=this.getScene().particleSystems[e],i=n.emitter;i.position&&t.indexOf(i)!==-1&&r.push(n)}return r};var En,Dc=function(){function r(t,e,n,i,o,a,s,d,p,b){p===void 0&&(p=null),b===void 0&&(b=null),this.idx=0,this.id=0,this.color=new M.b(1,1,1,1),this.position=u.e.Zero(),this.rotation=u.e.Zero(),this.scaling=u.e.One(),this.uvs=new u.f(0,0,1,1),this.velocity=u.e.Zero(),this.pivot=u.e.Zero(),this.translateFromPivot=!1,this.alive=!0,this.isVisible=!0,this._pos=0,this._ind=0,this.shapeId=0,this.idxInShape=0,this._stillInvisible=!1,this._rotationMatrix=[1,0,0,0,1,0,0,0,1],this.parentId=null,this.materialIndex=null,this.props=null,this.cullingStrategy=Dt.a.CULLINGSTRATEGY_BOUNDINGSPHERE_ONLY,this._globalPosition=u.e.Zero(),this.idx=t,this.id=e,this._pos=n,this._ind=i,this._model=o,this.shapeId=a,this.idxInShape=s,this._sps=d,p&&(this._modelBoundingInfo=p,this._boundingInfo=new Vi.a(p.minimum,p.maximum)),b!==null&&(this.materialIndex=b)}return r.prototype.copyToRef=function(t){return t.position.copyFrom(this.position),t.rotation.copyFrom(this.rotation),this.rotationQuaternion&&(t.rotationQuaternion?t.rotationQuaternion.copyFrom(this.rotationQuaternion):t.rotationQuaternion=this.rotationQuaternion.clone()),t.scaling.copyFrom(this.scaling),this.color&&(t.color?t.color.copyFrom(this.color):t.color=this.color.clone()),t.uvs.copyFrom(this.uvs),t.velocity.copyFrom(this.velocity),t.pivot.copyFrom(this.pivot),t.translateFromPivot=this.translateFromPivot,t.alive=this.alive,t.isVisible=this.isVisible,t.parentId=this.parentId,t.cullingStrategy=this.cullingStrategy,this.materialIndex!==null&&(t.materialIndex=this.materialIndex),this},Object.defineProperty(r.prototype,"scale",{get:function(){return this.scaling},set:function(t){this.scaling=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"quaternion",{get:function(){return this.rotationQuaternion},set:function(t){this.rotationQuaternion=t},enumerable:!1,configurable:!0}),r.prototype.intersectsMesh=function(t){return!(!this._boundingInfo||!t._boundingInfo)&&(this._sps._bSphereOnly?$l.a.Intersects(this._boundingInfo.boundingSphere,t._boundingInfo.boundingSphere):this._boundingInfo.intersects(t._boundingInfo,!1))},r.prototype.isInFrustum=function(t){return this._boundingInfo!==null&&this._boundingInfo.isInFrustum(t,this.cullingStrategy)},r.prototype.getRotationMatrix=function(t){var e;if(this.rotationQuaternion)e=this.rotationQuaternion;else{e=u.c.Quaternion[0];var n=this.rotation;u.b.RotationYawPitchRollToRef(n.y,n.x,n.z,e)}e.toRotationMatrix(t)},r}(),Lc=function(r,t,e,n,i,o,a,s,d){this._indicesLength=0,this.shapeID=r,this._shape=t,this._indices=e,this._indicesLength=e.length,this._shapeUV=o,this._shapeColors=i,this._normals=n,this._positionFunction=a,this._vertexFunction=s,this._material=d},Cd=function(r,t,e,n){this.idx=0,this.ind=0,this.indicesLength=0,this.sqDistance=0,this.materialIndex=0,this.idx=r,this.ind=t,this.indicesLength=e,this.materialIndex=n},Rd=function(){function r(){this.position=u.e.Zero(),this.color=new M.b(1,1,1,1),this.uv=u.d.Zero()}return Object.defineProperty(r.prototype,"x",{get:function(){return this.position.x},set:function(t){this.position.x=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"y",{get:function(){return this.position.y},set:function(t){this.position.y=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"z",{get:function(){return this.position.z},set:function(t){this.position.z=t},enumerable:!1,configurable:!0}),r}(),zm=function(){function r(t,e,n){this.particles=new Array,this.nbParticles=0,this.billboard=!1,this.recomputeNormals=!1,this.counter=0,this.vars={},this._bSphereOnly=!1,this._bSphereRadiusFactor=1,this._positions=new Array,this._indices=new Array,this._normals=new Array,this._colors=new Array,this._uvs=new Array,this._index=0,this._updatable=!0,this._pickable=!1,this._isVisibilityBoxLocked=!1,this._alwaysVisible=!1,this._depthSort=!1,this._expandable=!1,this._shapeCounter=0,this._copy=new Dc(0,0,0,0,null,0,0,this),this._color=new M.b(0,0,0,0),this._computeParticleColor=!0,this._computeParticleTexture=!0,this._computeParticleRotation=!0,this._computeParticleVertex=!1,this._computeBoundingBox=!1,this._depthSortParticles=!0,this._mustUnrotateFixedNormals=!1,this._particlesIntersect=!1,this._needs32Bits=!1,this._isNotBuilt=!0,this._lastParticleId=0,this._idxOfId=[],this._multimaterialEnabled=!1,this._useModelMaterial=!1,this._depthSortFunction=function(i,o){return o.sqDistance-i.sqDistance},this._materialSortFunction=function(i,o){return i.materialIndex-o.materialIndex},this._autoUpdateSubMeshes=!1,this.name=t,this._scene=e||te.a.LastCreatedScene,this._camera=e.activeCamera,this._pickable=!!n&&n.isPickable,this._depthSort=!!n&&n.enableDepthSort,this._multimaterialEnabled=!!n&&n.enableMultiMaterial,this._useModelMaterial=!!n&&n.useModelMaterial,this._multimaterialEnabled=!!this._useModelMaterial||this._multimaterialEnabled,this._expandable=!!n&&n.expandable,this._particlesIntersect=!!n&&n.particleIntersection,this._bSphereOnly=!!n&&n.boundingSphereOnly,this._bSphereRadiusFactor=n&&n.bSphereRadiusFactor?n.bSphereRadiusFactor:1,n&&n.updatable!==void 0?this._updatable=n.updatable:this._updatable=!0,this._pickable&&(this.pickedBySubMesh=[[]],this.pickedParticles=this.pickedBySubMesh[0]),(this._depthSort||this._multimaterialEnabled)&&(this.depthSortedParticles=[]),this._multimaterialEnabled&&(this._multimaterial=new rr.a(this.name+"MultiMaterial",this._scene),this._materials=[],this._materialIndexesById={}),this._tmpVertex=new Rd}return r.prototype.buildMesh=function(){if(!this._isNotBuilt&&this.mesh)return this.mesh;if(this.nbParticles===0&&!this.mesh){var t=Ta.CreateDisc("",{radius:1,tessellation:3},this._scene);this.addShape(t,1),t.dispose()}if(this._indices32=this._needs32Bits?new Uint32Array(this._indices):new Uint16Array(this._indices),this._positions32=new Float32Array(this._positions),this._uvs32=new Float32Array(this._uvs),this._colors32=new Float32Array(this._colors),!this.mesh){var e=new De.a(this.name,this._scene);this.mesh=e}!this._updatable&&this._multimaterialEnabled&&this._sortParticlesByMaterial(),this.recomputeNormals&&ft.a.ComputeNormals(this._positions32,this._indices32,this._normals),this._normals32=new Float32Array(this._normals),this._fixedNormal32=new Float32Array(this._normals),this._mustUnrotateFixedNormals&&this._unrotateFixedNormals();var n=new ft.a;if(n.indices=this._depthSort?this._indices:this._indices32,n.set(this._positions32,Oe.b.PositionKind),n.set(this._normals32,Oe.b.NormalKind),this._uvs32.length>0&&n.set(this._uvs32,Oe.b.UVKind),this._colors32.length>0&&n.set(this._colors32,Oe.b.ColorKind),n.applyToMesh(this.mesh,this._updatable),this.mesh.isPickable=this._pickable,this._pickable){for(var i=0,o=0;o<this.nbParticles;o++)for(var a=this.particles[o],s=a._model._indicesLength,d=0;d<s;d++)if(d%3==0){var p={idx:a.idx,faceId:i};this.pickedParticles[i]=p,i++}}return this._multimaterialEnabled&&this.setMultiMaterial(this._materials),this._expandable||(this._depthSort||this._multimaterialEnabled||(this._indices=null),this._positions=null,this._normals=null,this._uvs=null,this._colors=null,this._updatable||(this.particles.length=0)),this._isNotBuilt=!1,this.recomputeNormals=!1,this.mesh},r.prototype.digest=function(t,e){var n=e&&e.facetNb||1,i=e&&e.number||0,o=e&&e.delta||0,a=t.getVerticesData(Oe.b.PositionKind),s=t.getIndices(),d=t.getVerticesData(Oe.b.UVKind),p=t.getVerticesData(Oe.b.ColorKind),b=t.getVerticesData(Oe.b.NormalKind),P=e&&e.storage?e.storage:null,O=0,B=s.length/3;i?(i=i>B?B:i,n=Math.round(B/i),o=0):n=n>B?B:n;for(var F=[],z=[],J=[],ie=[],se=[],ce=u.e.Zero(),ue=n;O<B;){O>B-(n=ue+Math.floor((1+o)*Math.random()))&&(n=B-O),F.length=0,z.length=0,J.length=0,ie.length=0,se.length=0;for(var fe=0,ve=3*O;ve<3*(O+n);ve++){J.push(fe);var Te=s[ve],Re=3*Te;if(F.push(a[Re],a[Re+1],a[Re+2]),z.push(b[Re],b[Re+1],b[Re+2]),d){var Ae=2*Te;ie.push(d[Ae],d[Ae+1])}if(p){var Ee=4*Te;se.push(p[Ee],p[Ee+1],p[Ee+2],p[Ee+3])}fe++}var Se,Le=this.nbParticles,xe=this._posToShape(F),Ne=this._uvsToShapeUV(ie),Ie=Xe.b.Slice(J),Fe=Xe.b.Slice(se),Ye=Xe.b.Slice(z);for(ce.copyFromFloats(0,0,0),Se=0;Se<xe.length;Se++)ce.addInPlace(xe[Se]);ce.scaleInPlace(1/xe.length);var tt,it=new u.e(1/0,1/0,1/0),ut=new u.e(-1/0,-1/0,-1/0);for(Se=0;Se<xe.length;Se++)xe[Se].subtractInPlace(ce),it.minimizeInPlaceFromFloats(xe[Se].x,xe[Se].y,xe[Se].z),ut.maximizeInPlaceFromFloats(xe[Se].x,xe[Se].y,xe[Se].z);this._particlesIntersect&&(tt=new Vi.a(it,ut));var Qe=null;this._useModelMaterial&&(Qe=t.material?t.material:this._setDefaultMaterial());var ot=new Lc(this._shapeCounter,xe,Ie,Ye,Fe,Ne,null,null,Qe),rt=this._positions.length,Ze=this._indices.length;this._meshBuilder(this._index,Ze,xe,this._positions,Ie,this._indices,ie,this._uvs,Fe,this._colors,Ye,this._normals,Le,0,null,ot),this._addParticle(Le,this._lastParticleId,rt,Ze,ot,this._shapeCounter,0,tt,P),this.particles[this.nbParticles].position.addInPlace(ce),P||(this._index+=xe.length,Le++,this.nbParticles++,this._lastParticleId++),this._shapeCounter++,O+=n}return this._isNotBuilt=!0,this},r.prototype._unrotateFixedNormals=function(){for(var t=0,e=0,n=u.c.Vector3[0],i=u.c.Quaternion[0],o=u.c.Matrix[0],a=0;a<this.particles.length;a++){var s=this.particles[a],d=s._model._shape;if(s.rotationQuaternion)s.rotationQuaternion.conjugateToRef(i);else{var p=s.rotation;u.b.RotationYawPitchRollToRef(p.y,p.x,p.z,i),i.conjugateInPlace()}i.toRotationMatrix(o);for(var b=0;b<d.length;b++)e=t+3*b,u.e.TransformNormalFromFloatsToRef(this._normals32[e],this._normals32[e+1],this._normals32[e+2],o,n),n.toArray(this._fixedNormal32,e);t=e+3}},r.prototype._resetCopy=function(){var t=this._copy;t.position.setAll(0),t.rotation.setAll(0),t.rotationQuaternion=null,t.scaling.setAll(1),t.uvs.copyFromFloats(0,0,1,1),t.color=null,t.translateFromPivot=!1,t.shapeId=0,t.materialIndex=null},r.prototype._meshBuilder=function(t,e,n,i,o,a,s,d,p,b,P,O,B,F,z,J){var ie,se=0,ce=0,ue=0;this._resetCopy();var fe=this._copy,ve=!(!z||!z.storage);if(fe.idx=B,fe.idxInShape=F,fe.shapeId=J.shapeID,this._useModelMaterial){var Te=J._material.uniqueId,Re=this._materialIndexesById;Re.hasOwnProperty(Te)||(Re[Te]=this._materials.length,this._materials.push(J._material));var Ae=Re[Te];fe.materialIndex=Ae}if(z&&z.positionFunction&&(z.positionFunction(fe,B,F),this._mustUnrotateFixedNormals=!0),ve)return fe;var Ee=u.c.Matrix[0],Se=this._tmpVertex,Le=Se.position,xe=Se.color,Ne=Se.uv,Ie=u.c.Vector3[1],Fe=u.c.Vector3[2],Ye=u.c.Vector3[3];u.a.IdentityToRef(Ee),fe.getRotationMatrix(Ee),fe.pivot.multiplyToRef(fe.scaling,Ye),fe.translateFromPivot?Fe.setAll(0):Fe.copyFrom(Ye);var tt=z&&z.vertexFunction;for(ie=0;ie<n.length;ie++){if(Le.copyFrom(n[ie]),fe.color&&xe.copyFrom(fe.color),s&&Ne.copyFromFloats(s[se],s[se+1]),tt&&z.vertexFunction(fe,Se,ie),Le.multiplyInPlace(fe.scaling).subtractInPlace(Ye),u.e.TransformCoordinatesToRef(Le,Ee,Ie),Ie.addInPlace(Fe).addInPlace(fe.position),i.push(Ie.x,Ie.y,Ie.z),s){var it=fe.uvs;d.push((it.z-it.x)*Ne.x+it.x,(it.w-it.y)*Ne.y+it.y),se+=2}if(fe.color)this._color.copyFrom(xe);else{var ut=this._color;p&&p[ce]!==void 0?(ut.r=p[ce],ut.g=p[ce+1],ut.b=p[ce+2],ut.a=p[ce+3]):(ut.r=1,ut.g=1,ut.b=1,ut.a=1)}b.push(this._color.r,this._color.g,this._color.b,this._color.a),ce+=4,!this.recomputeNormals&&P&&(u.e.TransformNormalFromFloatsToRef(P[ue],P[ue+1],P[ue+2],Ee,Le),O.push(Le.x,Le.y,Le.z),ue+=3)}for(ie=0;ie<o.length;ie++){var Qe=t+o[ie];a.push(Qe),Qe>65535&&(this._needs32Bits=!0)}if(this._depthSort||this._multimaterialEnabled){var ot=fe.materialIndex!==null?fe.materialIndex:0;this.depthSortedParticles.push(new Cd(B,e,o.length,ot))}return fe},r.prototype._posToShape=function(t){for(var e=[],n=0;n<t.length;n+=3)e.push(u.e.FromArray(t,n));return e},r.prototype._uvsToShapeUV=function(t){var e=[];if(t)for(var n=0;n<t.length;n++)e.push(t[n]);return e},r.prototype._addParticle=function(t,e,n,i,o,a,s,d,p){d===void 0&&(d=null),p===void 0&&(p=null);var b=new Dc(t,e,n,i,o,a,s,this,d);return(p||this.particles).push(b),b},r.prototype.addShape=function(t,e,n){var i=t.getVerticesData(Oe.b.PositionKind),o=t.getIndices(),a=t.getVerticesData(Oe.b.UVKind),s=t.getVerticesData(Oe.b.ColorKind),d=t.getVerticesData(Oe.b.NormalKind);this.recomputeNormals=!d;var p=Xe.b.SliceToArray(o),b=Xe.b.SliceToArray(d),P=s?Xe.b.SliceToArray(s):[],O=n&&n.storage?n.storage:null,B=null;this._particlesIntersect&&(B=t.getBoundingInfo());var F=this._posToShape(i),z=this._uvsToShapeUV(a),J=n?n.positionFunction:null,ie=n?n.vertexFunction:null,se=null;this._useModelMaterial&&(se=t.material?t.material:this._setDefaultMaterial());for(var ce=new Lc(this._shapeCounter,F,p,b,P,z,J,ie,se),ue=0;ue<e;ue++)this._insertNewParticle(this.nbParticles,ue,ce,F,o,a,s,d,B,O,n);return this._shapeCounter++,this._isNotBuilt=!0,this._shapeCounter-1},r.prototype._rebuildParticle=function(t,e){e===void 0&&(e=!1),this._resetCopy();var n=this._copy;t._model._positionFunction&&t._model._positionFunction(n,t.idx,t.idxInShape);var i=u.c.Matrix[0],o=u.c.Vector3[0],a=u.c.Vector3[1],s=u.c.Vector3[2],d=u.c.Vector3[3];n.getRotationMatrix(i),t.pivot.multiplyToRef(t.scaling,d),n.translateFromPivot?s.copyFromFloats(0,0,0):s.copyFrom(d);for(var p=t._model._shape,b=0;b<p.length;b++)o.copyFrom(p[b]),t._model._vertexFunction&&t._model._vertexFunction(n,o,b),o.multiplyInPlace(n.scaling).subtractInPlace(d),u.e.TransformCoordinatesToRef(o,i,a),a.addInPlace(s).addInPlace(n.position).toArray(this._positions32,t._pos+3*b);e&&(t.position.setAll(0),t.rotation.setAll(0),t.rotationQuaternion=null,t.scaling.setAll(1),t.uvs.setAll(0),t.pivot.setAll(0),t.translateFromPivot=!1,t.parentId=null)},r.prototype.rebuildMesh=function(t){t===void 0&&(t=!1);for(var e=0;e<this.particles.length;e++)this._rebuildParticle(this.particles[e],t);return this.mesh.updateVerticesData(Oe.b.PositionKind,this._positions32,!1,!1),this},r.prototype.removeParticles=function(t,e){var n=e-t+1;if(!this._expandable||n<=0||n>=this.nbParticles||!this._updatable)return[];var i=this.particles,o=this.nbParticles;if(e<o-1)for(var a=e+1,s=i[a]._pos-i[t]._pos,d=i[a]._ind-i[t]._ind,p=a;p<o;p++){var b=i[p];b._pos-=s,b._ind-=d}var P=i.splice(t,n);this._positions.length=0,this._indices.length=0,this._colors.length=0,this._uvs.length=0,this._normals.length=0,this._index=0,this._idxOfId.length=0,(this._depthSort||this._multimaterialEnabled)&&(this.depthSortedParticles=[]);for(var O=0,B=i.length,F=0;F<B;F++){var z=i[F],J=z._model,ie=J._shape,se=J._indices,ce=J._normals,ue=J._shapeColors,fe=J._shapeUV;z.idx=F,this._idxOfId[z.id]=F,this._meshBuilder(this._index,O,ie,this._positions,se,this._indices,fe,this._uvs,ue,this._colors,ce,this._normals,z.idx,z.idxInShape,null,J),this._index+=ie.length,O+=se.length}return this.nbParticles-=n,this._isNotBuilt=!0,P},r.prototype.insertParticlesFromArray=function(t){if(!this._expandable)return this;for(var e=0,n=t[0].shapeId,i=t.length,o=0;o<i;o++){var a=t[o],s=a._model,d=s._shape,p=s._indices,b=s._shapeUV,P=s._shapeColors,O=s._normals,B=!O;this.recomputeNormals=B||this.recomputeNormals;var F=a._boundingInfo,z=this._insertNewParticle(this.nbParticles,e,s,d,p,b,P,O,F,null,null);a.copyToRef(z),e++,n!=a.shapeId&&(n=a.shapeId,e=0)}return this._isNotBuilt=!0,this},r.prototype._insertNewParticle=function(t,e,n,i,o,a,s,d,p,b,P){var O=this._positions.length,B=this._indices.length,F=this._meshBuilder(this._index,B,i,this._positions,o,this._indices,a,this._uvs,s,this._colors,d,this._normals,t,e,P,n),z=null;return this._updatable&&((z=this._addParticle(this.nbParticles,this._lastParticleId,O,B,n,this._shapeCounter,e,p,b)).position.copyFrom(F.position),z.rotation.copyFrom(F.rotation),F.rotationQuaternion&&(z.rotationQuaternion?z.rotationQuaternion.copyFrom(F.rotationQuaternion):z.rotationQuaternion=F.rotationQuaternion.clone()),F.color&&(z.color?z.color.copyFrom(F.color):z.color=F.color.clone()),z.scaling.copyFrom(F.scaling),z.uvs.copyFrom(F.uvs),F.materialIndex!==null&&(z.materialIndex=F.materialIndex),this.expandable&&(this._idxOfId[z.id]=z.idx)),b||(this._index+=i.length,this.nbParticles++,this._lastParticleId++),z},r.prototype.setParticles=function(t,e,n){if(t===void 0&&(t=0),e===void 0&&(e=this.nbParticles-1),n===void 0&&(n=!0),!this._updatable||this._isNotBuilt)return this;this.beforeUpdateParticles(t,e,n);var i=u.c.Matrix[0],o=u.c.Matrix[1],a=this.mesh,s=this._colors32,d=this._positions32,p=this._normals32,b=this._uvs32,P=this._indices32,O=this._indices,B=this._fixedNormal32,F=u.c.Vector3,z=F[5].copyFromFloats(1,0,0),J=F[6].copyFromFloats(0,1,0),ie=F[7].copyFromFloats(0,0,1),se=F[8].setAll(Number.MAX_VALUE),ce=F[9].setAll(-Number.MAX_VALUE),ue=F[10].setAll(0),fe=this._tmpVertex,ve=fe.position,Te=fe.color,Re=fe.uv;if((this.billboard||this._depthSort)&&(this.mesh.computeWorldMatrix(!0),this.mesh._worldMatrix.invertToRef(o)),this.billboard){var Ae=F[0];this._camera.getDirectionToRef(ye.a.Z,Ae),u.e.TransformNormalToRef(Ae,o,ie),ie.normalize();var Ee=this._camera.getViewMatrix(!0);u.e.TransformNormalFromFloatsToRef(Ee.m[1],Ee.m[5],Ee.m[9],o,J),u.e.CrossToRef(J,ie,z),J.normalize(),z.normalize()}this._depthSort&&u.e.TransformCoordinatesToRef(this._camera.globalPosition,o,ue),u.a.IdentityToRef(i);var Se=0,Le=0,xe=0,Ne=0,Ie=0,Fe=0,Ye=0;if(this.mesh.isFacetDataEnabled&&(this._computeBoundingBox=!0),e=e>=this.nbParticles?this.nbParticles-1:e,this._computeBoundingBox&&(t!=0||e!=this.nbParticles-1)){var tt=this.mesh._boundingInfo;tt&&(se.copyFrom(tt.minimum),ce.copyFrom(tt.maximum))}var it=(Le=this.particles[t]._pos)/3|0;Ne=4*it,Fe=2*it;for(var ut=t;ut<=e;ut++){var Qe=this.particles[ut];this.updateParticle(Qe);var ot=Qe._model._shape,rt=Qe._model._shapeUV,Ze=Qe._rotationMatrix,dt=Qe.position,Ve=Qe.rotation,Je=Qe.scaling,yt=Qe._globalPosition;if(this._depthSort&&this._depthSortParticles){var Wt=this.depthSortedParticles[ut];Wt.idx=Qe.idx,Wt.ind=Qe._ind,Wt.indicesLength=Qe._model._indicesLength,Wt.sqDistance=u.e.DistanceSquared(Qe.position,ue)}if(!Qe.alive||Qe._stillInvisible&&!Qe.isVisible)Le+=3*(Ye=ot.length),Ne+=4*Ye,Fe+=2*Ye;else{if(Qe.isVisible){Qe._stillInvisible=!1;var Nt=F[12];if(Qe.pivot.multiplyToRef(Je,Nt),this.billboard&&(Ve.x=0,Ve.y=0),(this._computeParticleRotation||this.billboard)&&Qe.getRotationMatrix(i),Qe.parentId!==null){var Qt=this.getParticleById(Qe.parentId);if(Qt){var vt=Qt._rotationMatrix,Jt=Qt._globalPosition,Xt=dt.x*vt[1]+dt.y*vt[4]+dt.z*vt[7],zt=dt.x*vt[0]+dt.y*vt[3]+dt.z*vt[6],Yt=dt.x*vt[2]+dt.y*vt[5]+dt.z*vt[8];if(yt.x=Jt.x+zt,yt.y=Jt.y+Xt,yt.z=Jt.z+Yt,this._computeParticleRotation||this.billboard){var Et=i.m;Ze[0]=Et[0]*vt[0]+Et[1]*vt[3]+Et[2]*vt[6],Ze[1]=Et[0]*vt[1]+Et[1]*vt[4]+Et[2]*vt[7],Ze[2]=Et[0]*vt[2]+Et[1]*vt[5]+Et[2]*vt[8],Ze[3]=Et[4]*vt[0]+Et[5]*vt[3]+Et[6]*vt[6],Ze[4]=Et[4]*vt[1]+Et[5]*vt[4]+Et[6]*vt[7],Ze[5]=Et[4]*vt[2]+Et[5]*vt[5]+Et[6]*vt[8],Ze[6]=Et[8]*vt[0]+Et[9]*vt[3]+Et[10]*vt[6],Ze[7]=Et[8]*vt[1]+Et[9]*vt[4]+Et[10]*vt[7],Ze[8]=Et[8]*vt[2]+Et[9]*vt[5]+Et[10]*vt[8]}}else Qe.parentId=null}else yt.x=dt.x,yt.y=dt.y,yt.z=dt.z,(this._computeParticleRotation||this.billboard)&&(Et=i.m,Ze[0]=Et[0],Ze[1]=Et[1],Ze[2]=Et[2],Ze[3]=Et[4],Ze[4]=Et[5],Ze[5]=Et[6],Ze[6]=Et[8],Ze[7]=Et[9],Ze[8]=Et[10]);var Mt=F[11];for(Qe.translateFromPivot?Mt.setAll(0):Mt.copyFrom(Nt),Ye=0;Ye<ot.length;Ye++){Se=Le+3*Ye,xe=Ne+4*Ye,Ie=Fe+2*Ye;var $t=2*Ye,Dn=$t+1;ve.copyFrom(ot[Ye]),this._computeParticleColor&&Qe.color&&Te.copyFrom(Qe.color),this._computeParticleTexture&&Re.copyFromFloats(rt[$t],rt[Dn]),this._computeParticleVertex&&this.updateParticleVertex(Qe,fe,Ye);var Vn=ve.x*Je.x-Nt.x,$n=ve.y*Je.y-Nt.y,Ln=ve.z*Je.z-Nt.z;zt=Vn*Ze[0]+$n*Ze[3]+Ln*Ze[6],Xt=Vn*Ze[1]+$n*Ze[4]+Ln*Ze[7],Yt=Vn*Ze[2]+$n*Ze[5]+Ln*Ze[8],zt+=Mt.x,Xt+=Mt.y,Yt+=Mt.z;var qt=d[Se]=yt.x+z.x*zt+J.x*Xt+ie.x*Yt,ui=d[Se+1]=yt.y+z.y*zt+J.y*Xt+ie.y*Yt,Ri=d[Se+2]=yt.z+z.z*zt+J.z*Xt+ie.z*Yt;if(this._computeBoundingBox&&(se.minimizeInPlaceFromFloats(qt,ui,Ri),ce.maximizeInPlaceFromFloats(qt,ui,Ri)),!this._computeParticleVertex){var Gr=B[Se],zr=B[Se+1],hi=B[Se+2],Hi=Gr*Ze[0]+zr*Ze[3]+hi*Ze[6],jr=Gr*Ze[1]+zr*Ze[4]+hi*Ze[7],jt=Gr*Ze[2]+zr*Ze[5]+hi*Ze[8];p[Se]=z.x*Hi+J.x*jr+ie.x*jt,p[Se+1]=z.y*Hi+J.y*jr+ie.y*jt,p[Se+2]=z.z*Hi+J.z*jr+ie.z*jt}if(this._computeParticleColor&&Qe.color){var Wi=this._colors32;Wi[xe]=Te.r,Wi[xe+1]=Te.g,Wi[xe+2]=Te.b,Wi[xe+3]=Te.a}if(this._computeParticleTexture){var Sn=Qe.uvs;b[Ie]=Re.x*(Sn.z-Sn.x)+Sn.x,b[Ie+1]=Re.y*(Sn.w-Sn.y)+Sn.y}}}else for(Qe._stillInvisible=!0,Ye=0;Ye<ot.length;Ye++){if(xe=Ne+4*Ye,Ie=Fe+2*Ye,d[Se=Le+3*Ye]=d[Se+1]=d[Se+2]=0,p[Se]=p[Se+1]=p[Se+2]=0,this._computeParticleColor&&Qe.color){var lr=Qe.color;s[xe]=lr.r,s[xe+1]=lr.g,s[xe+2]=lr.b,s[xe+3]=lr.a}this._computeParticleTexture&&(Sn=Qe.uvs,b[Ie]=rt[2*Ye]*(Sn.z-Sn.x)+Sn.x,b[Ie+1]=rt[2*Ye+1]*(Sn.w-Sn.y)+Sn.y)}if(this._particlesIntersect){var Oi=Qe._boundingInfo,ka=Oi.boundingBox,Ga=Oi.boundingSphere,Hr=Qe._modelBoundingInfo;if(!this._bSphereOnly){var Xi=Hr.boundingBox.vectors,Yi=F[1],ur=F[2];Yi.setAll(Number.MAX_VALUE),ur.setAll(-Number.MAX_VALUE);for(var Ki=0;Ki<8;Ki++){var Wr=Xi[Ki].x*Je.x,Xr=Xi[Ki].y*Je.y,Yr=Xi[Ki].z*Je.z,Qi=(zt=Wr*Ze[0]+Xr*Ze[3]+Yr*Ze[6],Xt=Wr*Ze[1]+Xr*Ze[4]+Yr*Ze[7],Yt=Wr*Ze[2]+Xr*Ze[5]+Yr*Ze[8],dt.x+z.x*zt+J.x*Xt+ie.x*Yt),qi=dt.y+z.y*zt+J.y*Xt+ie.y*Yt,Kr=dt.z+z.z*zt+J.z*Xt+ie.z*Yt;Yi.minimizeInPlaceFromFloats(Qi,qi,Kr),ur.maximizeInPlaceFromFloats(Qi,qi,Kr)}ka.reConstruct(Yi,ur,a._worldMatrix)}var Mi=Hr.minimum.multiplyToRef(Je,F[1]),Nn=Hr.maximum.multiplyToRef(Je,F[2]),Io=Nn.addToRef(Mi,F[3]).scaleInPlace(.5).addInPlace(yt),hr=Nn.subtractToRef(Mi,F[4]).scaleInPlace(.5*this._bSphereRadiusFactor),Do=Io.subtractToRef(hr,F[1]),Av=Io.addToRef(hr,F[2]);Ga.reConstruct(Do,Av,a._worldMatrix)}Le=Se+3,Ne=xe+4,Fe=Ie+2}}if(n){if(this._computeParticleColor&&a.updateVerticesData(Oe.b.ColorKind,s,!1,!1),this._computeParticleTexture&&a.updateVerticesData(Oe.b.UVKind,b,!1,!1),a.updateVerticesData(Oe.b.PositionKind,d,!1,!1),!a.areNormalsFrozen||a.isFacetDataEnabled){if(this._computeParticleVertex||a.isFacetDataEnabled){var Pv=a.isFacetDataEnabled?a.getFacetDataParameters():null;ft.a.ComputeNormals(d,P,p,Pv);for(var Ii=0;Ii<p.length;Ii++)B[Ii]=p[Ii]}a.areNormalsFrozen||a.updateVerticesData(Oe.b.NormalKind,p,!1,!1)}if(this._depthSort&&this._depthSortParticles){var nl=this.depthSortedParticles;nl.sort(this._depthSortFunction);for(var xv=nl.length,Ef=0,il=0,rl=0;rl<xv;rl++){var ol=nl[rl],Cv=ol.indicesLength,Rv=ol.ind;for(Ii=0;Ii<Cv;Ii++)if(P[Ef]=O[Rv+Ii],Ef++,this._pickable&&Ii%3==0){var Sf=this.pickedParticles[il];Sf.idx=ol.idx,Sf.faceId=il,il++}}a.updateIndices(P)}}return this._computeBoundingBox&&(a._boundingInfo?a._boundingInfo.reConstruct(se,ce,a._worldMatrix):a._boundingInfo=new Vi.a(se,ce,a._worldMatrix)),this._autoUpdateSubMeshes&&this.computeSubMeshes(),this.afterUpdateParticles(t,e,n),this},r.prototype.dispose=function(){this.mesh.dispose(),this.vars=null,this._positions=null,this._indices=null,this._normals=null,this._uvs=null,this._colors=null,this._indices32=null,this._positions32=null,this._normals32=null,this._fixedNormal32=null,this._uvs32=null,this._colors32=null,this.pickedParticles=null,this.pickedBySubMesh=null,this._materials=null,this._materialIndexes=null,this._indicesByMaterial=null,this._idxOfId=null},r.prototype.pickedParticle=function(t){if(t.hit){var e=t.subMeshId,n=t.faceId,i=this.pickedBySubMesh;if(i[e]&&i[e][n])return i[e][n]}return null},r.prototype.getParticleById=function(t){var e=this.particles[t];if(e&&e.id==t)return e;var n=this.particles,i=this._idxOfId[t];if(i!==void 0)return n[i];for(var o=0,a=this.nbParticles;o<a;){var s=n[o];if(s.id==t)return s;o++}return null},r.prototype.getParticlesByShapeId=function(t){var e=[];return this.getParticlesByShapeIdToRef(t,e),e},r.prototype.getParticlesByShapeIdToRef=function(t,e){e.length=0;for(var n=0;n<this.nbParticles;n++){var i=this.particles[n];i.shapeId==t&&e.push(i)}return this},r.prototype.computeSubMeshes=function(){if(!this.mesh||!this._multimaterialEnabled)return this;var t=this.depthSortedParticles;if(this.particles.length>0)for(var e=0;e<this.particles.length;e++){var n=this.particles[e];n.materialIndex||(n.materialIndex=0);var i=t[e];i.materialIndex=n.materialIndex,i.ind=n._ind,i.indicesLength=n._model._indicesLength,i.idx=n.idx}this._sortParticlesByMaterial();var o=this._indicesByMaterial,a=this._materialIndexes,s=this.mesh;s.subMeshes=[];for(var d=s.getTotalVertices(),p=0;p<a.length;p++){var b=o[p],P=o[p+1]-b,O=a[p];new Eo.a(O,0,d,b,P,s)}return this},r.prototype._sortParticlesByMaterial=function(){var t=[0];this._indicesByMaterial=t;var e=[];this._materialIndexes=e;var n=this.depthSortedParticles;n.sort(this._materialSortFunction);var i=n.length,o=this._indices32,a=this._indices,s=0,d=0,p=0,b=n[0].materialIndex;e.push(b),this._pickable&&(this.pickedBySubMesh=[[]],this.pickedParticles=this.pickedBySubMesh[0]);for(var P=0;P<i;P++){var O=n[P],B=O.indicesLength,F=O.ind;O.materialIndex!==b&&(b=O.materialIndex,t.push(p),e.push(b),this._pickable&&(s++,this.pickedBySubMesh[s]=[],d=0));for(var z=0,J=0;J<B;J++){if(o[p]=a[F+J],this._pickable&&J%3==0){var ie=this.pickedBySubMesh[s][d];ie?(ie.idx=O.idx,ie.faceId=z):this.pickedBySubMesh[s][d]={idx:O.idx,faceId:z},d++,z++}p++}}return t.push(o.length),this._updatable&&this.mesh.updateIndices(o),this},r.prototype._setMaterialIndexesById=function(){this._materialIndexesById={};for(var t=0;t<this._materials.length;t++){var e=this._materials[t].uniqueId;this._materialIndexesById[e]=t}},r.prototype._filterUniqueMaterialId=function(t){return t.filter(function(e,n,i){return i.indexOf(e)===n})},r.prototype._setDefaultMaterial=function(){return this._defaultMaterial||(this._defaultMaterial=new Ft.a(this.name+"DefaultMaterial",this._scene)),this._defaultMaterial},r.prototype.refreshVisibleSize=function(){return this._isVisibilityBoxLocked||this.mesh.refreshBoundingInfo(),this},r.prototype.setVisibilityBox=function(t){var e=t/2;this.mesh._boundingInfo=new Vi.a(new u.e(-e,-e,-e),new u.e(e,e,e))},Object.defineProperty(r.prototype,"isAlwaysVisible",{get:function(){return this._alwaysVisible},set:function(t){this._alwaysVisible=t,this.mesh.alwaysSelectAsActiveMesh=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isVisibilityBoxLocked",{get:function(){return this._isVisibilityBoxLocked},set:function(t){this._isVisibilityBoxLocked=t,this.mesh.getBoundingInfo().isLocked=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeParticleRotation",{get:function(){return this._computeParticleRotation},set:function(t){this._computeParticleRotation=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeParticleColor",{get:function(){return this._computeParticleColor},set:function(t){this._computeParticleColor=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeParticleTexture",{get:function(){return this._computeParticleTexture},set:function(t){this._computeParticleTexture=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeParticleVertex",{get:function(){return this._computeParticleVertex},set:function(t){this._computeParticleVertex=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeBoundingBox",{get:function(){return this._computeBoundingBox},set:function(t){this._computeBoundingBox=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"depthSortParticles",{get:function(){return this._depthSortParticles},set:function(t){this._depthSortParticles=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"expandable",{get:function(){return this._expandable},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"multimaterialEnabled",{get:function(){return this._multimaterialEnabled},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useModelMaterial",{get:function(){return this._useModelMaterial},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"materials",{get:function(){return this._materials},enumerable:!1,configurable:!0}),r.prototype.setMultiMaterial=function(t){this._materials=this._filterUniqueMaterialId(t),this._setMaterialIndexesById(),this._multimaterial&&this._multimaterial.dispose(),this._multimaterial=new rr.a(this.name+"MultiMaterial",this._scene);for(var e=0;e<this._materials.length;e++)this._multimaterial.subMaterials.push(this._materials[e]);this.computeSubMeshes(),this.mesh.material=this._multimaterial},Object.defineProperty(r.prototype,"multimaterial",{get:function(){return this._multimaterial},set:function(t){this._multimaterial=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"autoUpdateSubMeshes",{get:function(){return this._autoUpdateSubMeshes},set:function(t){this._autoUpdateSubMeshes=t},enumerable:!1,configurable:!0}),r.prototype.initParticles=function(){},r.prototype.recycleParticle=function(t){return t},r.prototype.updateParticle=function(t){return t},r.prototype.updateParticleVertex=function(t,e,n){return this},r.prototype.beforeUpdateParticles=function(t,e,n){},r.prototype.afterUpdateParticles=function(t,e,n){},r}(),Od=function(){function r(t,e,n,i,o){this.idx=0,this.color=new M.b(1,1,1,1),this.position=u.e.Zero(),this.rotation=u.e.Zero(),this.uv=new u.d(0,0),this.velocity=u.e.Zero(),this.pivot=u.e.Zero(),this.translateFromPivot=!1,this._pos=0,this._ind=0,this.groupId=0,this.idxInGroup=0,this._stillInvisible=!1,this._rotationMatrix=[1,0,0,0,1,0,0,0,1],this.parentId=null,this._globalPosition=u.e.Zero(),this.idx=t,this._group=e,this.groupId=n,this.idxInGroup=i,this._pcs=o}return Object.defineProperty(r.prototype,"size",{get:function(){return this.size},set:function(t){this.size=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"quaternion",{get:function(){return this.rotationQuaternion},set:function(t){this.rotationQuaternion=t},enumerable:!1,configurable:!0}),r.prototype.intersectsMesh=function(t,e){if(!t._boundingInfo)return!1;if(e=e||!1)return t.getBoundingInfo().boundingSphere.intersectsPoint(this.position.add(this._pcs.mesh.position));var n,i,o,a,s,d;n=t.getBoundingInfo().boundingBox.maximumWorld.x,i=t.getBoundingInfo().boundingBox.minimumWorld.x,o=t.getBoundingInfo().boundingBox.maximumWorld.y,a=t.getBoundingInfo().boundingBox.minimumWorld.y,s=t.getBoundingInfo().boundingBox.maximumWorld.z,d=t.getBoundingInfo().boundingBox.minimumWorld.z;var p=this.position.x+this._pcs.mesh.position.x,b=this.position.y+this._pcs.mesh.position.y,P=this.position.z+this._pcs.mesh.position.z;return i<=p&&p<=n&&a<=b&&b<=o&&d<=P&&P<=s},r.prototype.getRotationMatrix=function(t){var e;if(this.rotationQuaternion)e=this.rotationQuaternion;else{e=u.c.Quaternion[0];var n=this.rotation;u.b.RotationYawPitchRollToRef(n.y,n.x,n.z,e)}e.toRotationMatrix(t)},r}(),Sa=function(r,t){this.groupID=r,this._positionFunction=t};(function(r){r[r.Color=2]="Color",r[r.UV=1]="UV",r[r.Random=0]="Random",r[r.Stated=3]="Stated"})(En||(En={}));var jm=function(){function r(t,e,n,i){this.particles=new Array,this.nbParticles=0,this.counter=0,this.vars={},this._promises=[],this._positions=new Array,this._indices=new Array,this._normals=new Array,this._colors=new Array,this._uvs=new Array,this._updatable=!0,this._isVisibilityBoxLocked=!1,this._alwaysVisible=!1,this._groups=new Array,this._groupCounter=0,this._computeParticleColor=!0,this._computeParticleTexture=!0,this._computeParticleRotation=!0,this._computeBoundingBox=!1,this._isReady=!1,this.name=t,this._size=e,this._scene=n||te.a.LastCreatedScene,i&&i.updatable!==void 0?this._updatable=i.updatable:this._updatable=!0}return r.prototype.buildMeshAsync=function(){var t=this;return Promise.all(this._promises).then(function(){return t._isReady=!0,t._buildMesh()})},r.prototype._buildMesh=function(){this.nbParticles===0&&this.addPoints(1),this._positions32=new Float32Array(this._positions),this._uvs32=new Float32Array(this._uvs),this._colors32=new Float32Array(this._colors);var t=new ft.a;t.set(this._positions32,Oe.b.PositionKind),this._uvs32.length>0&&t.set(this._uvs32,Oe.b.UVKind);var e=0;this._colors32.length>0&&(e=1,t.set(this._colors32,Oe.b.ColorKind));var n=new De.a(this.name,this._scene);t.applyToMesh(n,this._updatable),this.mesh=n,this._positions=null,this._uvs=null,this._colors=null,this._updatable||(this.particles.length=0);var i=new Ft.a("point cloud material",this._scene);return i.emissiveColor=new M.a(e,e,e),i.disableLighting=!0,i.pointsCloud=!0,i.pointSize=this._size,n.material=i,new Promise(function(o){return o(n)})},r.prototype._addParticle=function(t,e,n,i){var o=new Od(t,e,n,i,this);return this.particles.push(o),o},r.prototype._randomUnitVector=function(t){t.position=new u.e(Math.random(),Math.random(),Math.random()),t.color=new M.b(1,1,1,1)},r.prototype._getColorIndicesForCoord=function(t,e,n,i){var o=t._groupImageData,a=n*(4*i)+4*e,s=[a,a+1,a+2,a+3],d=s[1],p=s[2],b=s[3],P=o[s[0]],O=o[d],B=o[p],F=o[b];return new M.b(P/255,O/255,B/255,F)},r.prototype._setPointsColorOrUV=function(t,e,n,i,o,a,s){n&&t.updateFacetData();var d=2*t.getBoundingInfo().boundingSphere.radius,p=t.getVerticesData(Oe.b.PositionKind),b=t.getIndices(),P=t.getVerticesData(Oe.b.UVKind),O=t.getVerticesData(Oe.b.ColorKind),B=u.e.Zero();t.computeWorldMatrix();var F=t.getWorldMatrix();if(!F.isIdentity())for(var z=0;z<p.length/3;z++)u.e.TransformCoordinatesFromFloatsToRef(p[3*z],p[3*z+1],p[3*z+2],F,B),p[3*z]=B.x,p[3*z+1]=B.y,p[3*z+2]=B.z;var J,ie,se=0,ce=0,ue=0,fe=0,ve=0,Te=0,Re=0,Ae=0,Ee=0,Se=0,Le=0,xe=0,Ne=0,Ie=0,Fe=u.e.Zero(),Ye=u.e.Zero(),tt=u.e.Zero(),it=u.e.Zero(),ut=u.e.Zero(),Qe=0,ot=0,rt=0,Ze=0,dt=0,Ve=0,Je=u.d.Zero(),yt=u.d.Zero(),Wt=u.d.Zero(),Nt=u.d.Zero(),Qt=u.d.Zero(),vt=0,Jt=0,Xt=0,zt=0,Yt=0,Et=0,Mt=0,$t=0,Dn=0,Vn=0,$n=0,Ln=0,qt=u.f.Zero(),ui=u.f.Zero(),Ri=u.f.Zero(),Gr=u.f.Zero(),zr=u.f.Zero(),hi=0,Hi=0;s=s||0;var jr,jt=new u.f(0,0,0,0),Wi=u.e.Zero(),Sn=u.e.Zero(),lr=u.e.Zero(),Oi=0,ka=u.e.Zero(),Ga=0,Hr=0,Xi=new fn.a(u.e.Zero(),new u.e(1,0,0)),Yi=u.e.Zero();for(ce=0;ce<b.length/3;ce++){var ur,Ki,Wr,Xr,Yr,Qi,qi,Kr;ue=b[3*ce],fe=b[3*ce+1],ve=b[3*ce+2],Te=p[3*ue],Re=p[3*ue+1],Ae=p[3*ue+2],Ee=p[3*fe],Se=p[3*fe+1],Le=p[3*fe+2],xe=p[3*ve],Ne=p[3*ve+1],Ie=p[3*ve+2],Fe.set(Te,Re,Ae),Ye.set(Ee,Se,Le),tt.set(xe,Ne,Ie),Ye.subtractToRef(Fe,it),tt.subtractToRef(Ye,ut),P&&(Qe=P[2*ue],ot=P[2*ue+1],rt=P[2*fe],Ze=P[2*fe+1],dt=P[2*ve],Ve=P[2*ve+1],Je.set(Qe,ot),yt.set(rt,Ze),Wt.set(dt,Ve),yt.subtractToRef(Je,Nt),Wt.subtractToRef(yt,Qt)),O&&i&&(vt=O[4*ue],Jt=O[4*ue+1],Xt=O[4*ue+2],zt=O[4*ue+3],Yt=O[4*fe],Et=O[4*fe+1],Mt=O[4*fe+2],$t=O[4*fe+3],Dn=O[4*ve],Vn=O[4*ve+1],$n=O[4*ve+2],Ln=O[4*ve+3],qt.set(vt,Jt,Xt,zt),ui.set(Yt,Et,Mt,$t),Ri.set(Dn,Vn,$n,Ln),ui.subtractToRef(qt,Gr),Ri.subtractToRef(ui,zr));for(var Mi,Nn,Io=new M.a(0,0,0),hr=new M.a(0,0,0),Do=0;Do<e._groupDensity[ce];Do++)se=this.particles.length,this._addParticle(se,e,this._groupCounter,ce+Do),Nn=this.particles[se],hi=$.a.RandomRange(0,1),Hi=$.a.RandomRange(0,1),J=Fe.add(it.scale(hi)).add(ut.scale(hi*Hi)),n&&(Wi=t.getFacetNormal(ce).normalize().scale(-1),Sn=it.clone().normalize(),lr=u.e.Cross(Wi,Sn),Oi=$.a.RandomRange(0,2*Math.PI),ka=Sn.scale(Math.cos(Oi)).add(lr.scale(Math.sin(Oi))),Oi=$.a.RandomRange(.1,Math.PI/2),Yi=ka.scale(Math.cos(Oi)).add(Wi.scale(Math.sin(Oi))),Xi.origin=J.add(Yi.scale(1e-5)),Xi.direction=Yi,Xi.length=d,(jr=Xi.intersectsMesh(t)).hit&&(Hr=jr.pickedPoint.subtract(J).length(),Ga=$.a.RandomRange(0,1)*Hr,J.addInPlace(Yi.scale(Ga)))),Nn.position=J.clone(),this._positions.push(Nn.position.x,Nn.position.y,Nn.position.z),i!==void 0?P&&(ie=Je.add(Nt.scale(hi)).add(Qt.scale(hi*Hi)),i?o&&e._groupImageData!==null?(ur=e._groupImgWidth,Ki=e._groupImgHeight,Mi=this._getColorIndicesForCoord(e,Math.round(ie.x*ur),Math.round(ie.y*Ki),ur),Nn.color=Mi,this._colors.push(Mi.r,Mi.g,Mi.b,Mi.a)):O?(jt=qt.add(Gr.scale(hi)).add(zr.scale(hi*Hi)),Nn.color=new M.b(jt.x,jt.y,jt.z,jt.w),this._colors.push(jt.x,jt.y,jt.z,jt.w)):(jt=qt.set(Math.random(),Math.random(),Math.random(),1),Nn.color=new M.b(jt.x,jt.y,jt.z,jt.w),this._colors.push(jt.x,jt.y,jt.z,jt.w)):(Nn.uv=ie.clone(),this._uvs.push(Nn.uv.x,Nn.uv.y))):(a?(Io.set(a.r,a.g,a.b),Wr=$.a.RandomRange(-s,s),Xr=$.a.RandomRange(-s,s),Yr=(Kr=Io.toHSV()).r,(Qi=Kr.g+Wr)<0&&(Qi=0),Qi>1&&(Qi=1),(qi=Kr.b+Xr)<0&&(qi=0),qi>1&&(qi=1),M.a.HSVtoRGBToRef(Yr,Qi,qi,hr),jt.set(hr.r,hr.g,hr.b,1)):jt=qt.set(Math.random(),Math.random(),Math.random(),1),Nn.color=new M.b(jt.x,jt.y,jt.z,jt.w),this._colors.push(jt.x,jt.y,jt.z,jt.w))}},r.prototype._colorFromTexture=function(t,e,n){var i=this;if(t.material===null)return l.a.Warn(t.name+"has no material."),e._groupImageData=null,void this._setPointsColorOrUV(t,e,n,!0,!1);var o=t.material.getActiveTextures();if(o.length===0)return l.a.Warn(t.name+"has no useable texture."),e._groupImageData=null,void this._setPointsColorOrUV(t,e,n,!0,!1);var a=t.clone();a.setEnabled(!1),this._promises.push(new Promise(function(s){zn.a.WhenAllReady(o,function(){var d=e._textureNb;return d<0&&(d=0),d>o.length-1&&(d=o.length-1),e._groupImageData=o[d].readPixels(),e._groupImgWidth=o[d].getSize().width,e._groupImgHeight=o[d].getSize().height,i._setPointsColorOrUV(a,e,n,!0,!0),a.dispose(),s()})}))},r.prototype._calculateDensity=function(t,e,n){for(var i,o,a,s,d,p,b,P,O,B,F,z,J,ie,se,ce,ue,fe=new Array,ve=u.e.Zero(),Te=u.e.Zero(),Re=u.e.Zero(),Ae=u.e.Zero(),Ee=u.e.Zero(),Se=u.e.Zero(),Le=new Array,xe=0,Ne=n.length/3,Ie=0;Ie<Ne;Ie++)i=n[3*Ie],o=n[3*Ie+1],a=n[3*Ie+2],s=e[3*i],d=e[3*i+1],p=e[3*i+2],b=e[3*o],P=e[3*o+1],O=e[3*o+2],B=e[3*a],F=e[3*a+1],z=e[3*a+2],ve.set(s,d,p),Te.set(b,P,O),Re.set(B,F,z),Te.subtractToRef(ve,Ae),Re.subtractToRef(Te,Ee),Re.subtractToRef(ve,Se),ce=((J=Ae.length())+(ie=Ee.length())+(se=Se.length()))/2,xe+=ue=Math.sqrt(ce*(ce-J)*(ce-ie)*(ce-se)),Le[Ie]=ue;var Fe=0;for(Ie=0;Ie<Ne;Ie++)fe[Ie]=Math.floor(t*Le[Ie]/xe),Fe+=fe[Ie];var Ye=t-Fe,tt=Math.floor(Ye/Ne),it=Ye%Ne;for(tt>0&&(fe=fe.map(function(ut){return ut+tt})),Ie=0;Ie<it;Ie++)fe[Ie]+=1;return fe},r.prototype.addPoints=function(t,e){e===void 0&&(e=this._randomUnitVector);for(var n,i=new Sa(this._groupCounter,e),o=this.nbParticles,a=0;a<t;a++)n=this._addParticle(o,i,this._groupCounter,a),i&&i._positionFunction&&i._positionFunction(n,o,a),this._positions.push(n.position.x,n.position.y,n.position.z),n.color&&this._colors.push(n.color.r,n.color.g,n.color.b,n.color.a),n.uv&&this._uvs.push(n.uv.x,n.uv.y),o++;return this.nbParticles+=t,this._groupCounter++,this._groupCounter},r.prototype.addSurfacePoints=function(t,e,n,i,o){var a=n||En.Random;(isNaN(a)||a<0||a>3)&&(a=En.Random);var s=t.getVerticesData(Oe.b.PositionKind),d=t.getIndices();this._groups.push(this._groupCounter);var p=new Sa(this._groupCounter,null);switch(p._groupDensity=this._calculateDensity(e,s,d),a===En.Color?p._textureNb=i||0:i=i||new M.b(1,1,1,1),a){case En.Color:this._colorFromTexture(t,p,!1);break;case En.UV:this._setPointsColorOrUV(t,p,!1,!1,!1);break;case En.Random:this._setPointsColorOrUV(t,p,!1);break;case En.Stated:this._setPointsColorOrUV(t,p,!1,void 0,void 0,i,o)}return this.nbParticles+=e,this._groupCounter++,this._groupCounter-1},r.prototype.addVolumePoints=function(t,e,n,i,o){var a=n||En.Random;(isNaN(a)||a<0||a>3)&&(a=En.Random);var s=t.getVerticesData(Oe.b.PositionKind),d=t.getIndices();this._groups.push(this._groupCounter);var p=new Sa(this._groupCounter,null);switch(p._groupDensity=this._calculateDensity(e,s,d),a===En.Color?p._textureNb=i||0:i=i||new M.b(1,1,1,1),a){case En.Color:this._colorFromTexture(t,p,!0);break;case En.UV:this._setPointsColorOrUV(t,p,!0,!1,!1);break;case En.Random:this._setPointsColorOrUV(t,p,!0);break;case En.Stated:this._setPointsColorOrUV(t,p,!0,void 0,void 0,i,o)}return this.nbParticles+=e,this._groupCounter++,this._groupCounter-1},r.prototype.setParticles=function(t,e,n){if(t===void 0&&(t=0),e===void 0&&(e=this.nbParticles-1),n===void 0&&(n=!0),!this._updatable||!this._isReady)return this;this.beforeUpdateParticles(t,e,n);var i=u.c.Matrix[0],o=this.mesh,a=this._colors32,s=this._positions32,d=this._uvs32,p=u.c.Vector3,b=p[5].copyFromFloats(1,0,0),P=p[6].copyFromFloats(0,1,0),O=p[7].copyFromFloats(0,0,1),B=p[8].setAll(Number.MAX_VALUE),F=p[9].setAll(-Number.MAX_VALUE);u.a.IdentityToRef(i);var z=0;if(this.mesh.isFacetDataEnabled&&(this._computeBoundingBox=!0),e=e>=this.nbParticles?this.nbParticles-1:e,this._computeBoundingBox&&(t!=0||e!=this.nbParticles-1)){var J=this.mesh._boundingInfo;J&&(B.copyFrom(J.minimum),F.copyFrom(J.maximum))}z=0;for(var ie=0,se=0,ce=0,ue=t;ue<=e;ue++){var fe=this.particles[ue];ie=3*(z=fe.idx),se=4*z,ce=2*z,this.updateParticle(fe);var ve=fe._rotationMatrix,Te=fe.position,Re=fe._globalPosition;if(this._computeParticleRotation&&fe.getRotationMatrix(i),fe.parentId!==null){var Ae=this.particles[fe.parentId],Ee=Ae._rotationMatrix,Se=Ae._globalPosition,Le=Te.x*Ee[1]+Te.y*Ee[4]+Te.z*Ee[7],xe=Te.x*Ee[0]+Te.y*Ee[3]+Te.z*Ee[6],Ne=Te.x*Ee[2]+Te.y*Ee[5]+Te.z*Ee[8];if(Re.x=Se.x+xe,Re.y=Se.y+Le,Re.z=Se.z+Ne,this._computeParticleRotation){var Ie=i.m;ve[0]=Ie[0]*Ee[0]+Ie[1]*Ee[3]+Ie[2]*Ee[6],ve[1]=Ie[0]*Ee[1]+Ie[1]*Ee[4]+Ie[2]*Ee[7],ve[2]=Ie[0]*Ee[2]+Ie[1]*Ee[5]+Ie[2]*Ee[8],ve[3]=Ie[4]*Ee[0]+Ie[5]*Ee[3]+Ie[6]*Ee[6],ve[4]=Ie[4]*Ee[1]+Ie[5]*Ee[4]+Ie[6]*Ee[7],ve[5]=Ie[4]*Ee[2]+Ie[5]*Ee[5]+Ie[6]*Ee[8],ve[6]=Ie[8]*Ee[0]+Ie[9]*Ee[3]+Ie[10]*Ee[6],ve[7]=Ie[8]*Ee[1]+Ie[9]*Ee[4]+Ie[10]*Ee[7],ve[8]=Ie[8]*Ee[2]+Ie[9]*Ee[5]+Ie[10]*Ee[8]}}else Re.x=0,Re.y=0,Re.z=0,this._computeParticleRotation&&(Ie=i.m,ve[0]=Ie[0],ve[1]=Ie[1],ve[2]=Ie[2],ve[3]=Ie[4],ve[4]=Ie[5],ve[5]=Ie[6],ve[6]=Ie[8],ve[7]=Ie[9],ve[8]=Ie[10]);var Fe=p[11];fe.translateFromPivot?Fe.setAll(0):Fe.copyFrom(fe.pivot);var Ye=p[0];Ye.copyFrom(fe.position);var tt=Ye.x-fe.pivot.x,it=Ye.y-fe.pivot.y,ut=Ye.z-fe.pivot.z,Qe=tt*ve[0]+it*ve[3]+ut*ve[6],ot=tt*ve[1]+it*ve[4]+ut*ve[7],rt=tt*ve[2]+it*ve[5]+ut*ve[8];Qe+=Fe.x,ot+=Fe.y,rt+=Fe.z;var Ze=s[ie]=Re.x+b.x*Qe+P.x*ot+O.x*rt,dt=s[ie+1]=Re.y+b.y*Qe+P.y*ot+O.y*rt,Ve=s[ie+2]=Re.z+b.z*Qe+P.z*ot+O.z*rt;if(this._computeBoundingBox&&(B.minimizeInPlaceFromFloats(Ze,dt,Ve),F.maximizeInPlaceFromFloats(Ze,dt,Ve)),this._computeParticleColor&&fe.color){var Je=fe.color,yt=this._colors32;yt[se]=Je.r,yt[se+1]=Je.g,yt[se+2]=Je.b,yt[se+3]=Je.a}if(this._computeParticleTexture&&fe.uv){var Wt=fe.uv,Nt=this._uvs32;Nt[ce]=Wt.x,Nt[ce+1]=Wt.y}}return n&&(this._computeParticleColor&&o.updateVerticesData(Oe.b.ColorKind,a,!1,!1),this._computeParticleTexture&&o.updateVerticesData(Oe.b.UVKind,d,!1,!1),o.updateVerticesData(Oe.b.PositionKind,s,!1,!1)),this._computeBoundingBox&&(o._boundingInfo?o._boundingInfo.reConstruct(B,F,o._worldMatrix):o._boundingInfo=new Vi.a(B,F,o._worldMatrix)),this.afterUpdateParticles(t,e,n),this},r.prototype.dispose=function(){this.mesh.dispose(),this.vars=null,this._positions=null,this._indices=null,this._normals=null,this._uvs=null,this._colors=null,this._indices32=null,this._positions32=null,this._uvs32=null,this._colors32=null},r.prototype.refreshVisibleSize=function(){return this._isVisibilityBoxLocked||this.mesh.refreshBoundingInfo(),this},r.prototype.setVisibilityBox=function(t){var e=t/2;this.mesh._boundingInfo=new Vi.a(new u.e(-e,-e,-e),new u.e(e,e,e))},Object.defineProperty(r.prototype,"isAlwaysVisible",{get:function(){return this._alwaysVisible},set:function(t){this._alwaysVisible=t,this.mesh.alwaysSelectAsActiveMesh=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeParticleRotation",{set:function(t){this._computeParticleRotation=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeParticleColor",{get:function(){return this._computeParticleColor},set:function(t){this._computeParticleColor=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeParticleTexture",{get:function(){return this._computeParticleTexture},set:function(t){this._computeParticleTexture=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"computeBoundingBox",{get:function(){return this._computeBoundingBox},set:function(t){this._computeBoundingBox=t},enumerable:!1,configurable:!0}),r.prototype.initParticles=function(){},r.prototype.recycleParticle=function(t){return t},r.prototype.updateParticle=function(t){return t},r.prototype.beforeUpdateParticles=function(t,e,n){},r.prototype.afterUpdateParticles=function(t,e,n){},r}();_e.a.prototype.getPhysicsEngine=function(){return this._physicsEngine},_e.a.prototype.enablePhysics=function(r,t){if(r===void 0&&(r=null),this._physicsEngine)return!0;var e=this._getComponent(at.a.NAME_PHYSICSENGINE);e||(e=new Md(this),this._addComponent(e));try{return this._physicsEngine=new Ir(r,t),this._physicsTimeAccumulator=0,!0}catch(n){return l.a.Error(n.message),!1}},_e.a.prototype.disablePhysicsEngine=function(){this._physicsEngine&&(this._physicsEngine.dispose(),this._physicsEngine=null)},_e.a.prototype.isPhysicsEnabled=function(){return this._physicsEngine!==void 0},_e.a.prototype.deleteCompoundImpostor=function(r){var t=r.parts[0].mesh;t.physicsImpostor&&(t.physicsImpostor.dispose(),t.physicsImpostor=null)},_e.a.prototype._advancePhysicsEngineStep=function(r){if(this._physicsEngine){var t=this._physicsEngine.getSubTimeStep();if(t>0)for(this._physicsTimeAccumulator+=r;this._physicsTimeAccumulator>t;)this.onBeforePhysicsObservable.notifyObservers(this),this._physicsEngine._step(t/1e3),this.onAfterPhysicsObservable.notifyObservers(this),this._physicsTimeAccumulator-=t;else this.onBeforePhysicsObservable.notifyObservers(this),this._physicsEngine._step(r/1e3),this.onAfterPhysicsObservable.notifyObservers(this)}},Object.defineProperty(Dt.a.prototype,"physicsImpostor",{get:function(){return this._physicsImpostor},set:function(r){var t=this;this._physicsImpostor!==r&&(this._disposePhysicsObserver&&this.onDisposeObservable.remove(this._disposePhysicsObserver),this._physicsImpostor=r,r&&(this._disposePhysicsObserver=this.onDisposeObservable.add(function(){t.physicsImpostor&&(t.physicsImpostor.dispose(),t.physicsImpostor=null)})))},enumerable:!0,configurable:!0}),Dt.a.prototype.getPhysicsImpostor=function(){return this.physicsImpostor},Dt.a.prototype.applyImpulse=function(r,t){return this.physicsImpostor?(this.physicsImpostor.applyImpulse(r,t),this):this},Dt.a.prototype.setPhysicsLinkWith=function(r,t,e,n){return this.physicsImpostor&&r.physicsImpostor?(this.physicsImpostor.createJoint(r.physicsImpostor,en.e.HingeJoint,{mainPivot:t,connectedPivot:e,nativeParams:n}),this):this};var Ro,Br,Md=function(){function r(t){var e=this;this.name=at.a.NAME_PHYSICSENGINE,this.scene=t,this.scene.onBeforePhysicsObservable=new C.c,this.scene.onAfterPhysicsObservable=new C.c,this.scene.getDeterministicFrameTime=function(){return e.scene._physicsEngine?1e3*e.scene._physicsEngine.getTimeStep():1e3/60}}return r.prototype.register=function(){},r.prototype.rebuild=function(){},r.prototype.dispose=function(){this.scene.onBeforePhysicsObservable.clear(),this.scene.onAfterPhysicsObservable.clear(),this.scene._physicsEngine&&this.scene.disablePhysicsEngine()},r}(),Hm=function(){function r(t){this._scene=t,this._physicsEngine=this._scene.getPhysicsEngine(),this._physicsEngine||l.a.Warn("Physics engine not enabled. Please enable the physics before you can use the methods.")}return r.prototype.applyRadialExplosionImpulse=function(t,e,n,i){if(!this._physicsEngine)return l.a.Warn("Physics engine not enabled. Please enable the physics before you call this method."),null;var o=this._physicsEngine.getImpostors();if(o.length===0)return null;typeof e=="number"&&((e=new Ur).radius=e,e.strength=n||e.strength,e.falloff=i||e.falloff);var a=new Id(this._scene,e),s=Array();return o.forEach(function(d){var p=a.getImpostorHitData(d,t);p&&(d.applyImpulse(p.force,p.contactPoint),s.push({impostor:d,hitData:p}))}),a.triggerAffectedImpostorsCallback(s),a.dispose(!1),a},r.prototype.applyRadialExplosionForce=function(t,e,n,i){if(!this._physicsEngine)return l.a.Warn("Physics engine not enabled. Please enable the physics before you call the PhysicsHelper."),null;var o=this._physicsEngine.getImpostors();if(o.length===0)return null;typeof e=="number"&&((e=new Ur).radius=e,e.strength=n||e.strength,e.falloff=i||e.falloff);var a=new Id(this._scene,e),s=Array();return o.forEach(function(d){var p=a.getImpostorHitData(d,t);p&&(d.applyForce(p.force,p.contactPoint),s.push({impostor:d,hitData:p}))}),a.triggerAffectedImpostorsCallback(s),a.dispose(!1),a},r.prototype.gravitationalField=function(t,e,n,i){if(!this._physicsEngine)return l.a.Warn("Physics engine not enabled. Please enable the physics before you call the PhysicsHelper."),null;if(this._physicsEngine.getImpostors().length===0)return null;typeof e=="number"&&((e=new Ur).radius=e,e.strength=n||e.strength,e.falloff=i||e.falloff);var o=new Wm(this,this._scene,t,e);return o.dispose(!1),o},r.prototype.updraft=function(t,e,n,i,o){if(!this._physicsEngine)return l.a.Warn("Physics engine not enabled. Please enable the physics before you call the PhysicsHelper."),null;if(this._physicsEngine.getImpostors().length===0)return null;typeof e=="number"&&((e=new Nc).radius=e,e.strength=n||e.strength,e.height=i||e.height,e.updraftMode=o||e.updraftMode);var a=new Xm(this._scene,t,e);return a.dispose(!1),a},r.prototype.vortex=function(t,e,n,i){if(!this._physicsEngine)return l.a.Warn("Physics engine not enabled. Please enable the physics before you call the PhysicsHelper."),null;if(this._physicsEngine.getImpostors().length===0)return null;typeof e=="number"&&((e=new wc).radius=e,e.strength=n||e.strength,e.height=i||e.height);var o=new Ym(this._scene,t,e);return o.dispose(!1),o},r}(),Id=function(){function r(t,e){this._scene=t,this._options=e,this._dataFetched=!1,this._options=Object(c.a)(Object(c.a)({},new Ur),this._options)}return r.prototype.getData=function(){return this._dataFetched=!0,{sphere:this._sphere}},r.prototype.getImpostorHitData=function(t,e){if(t.mass===0||!this._intersectsWithSphere(t,e,this._options.radius)||t.object.getClassName()!=="Mesh"&&t.object.getClassName()!=="InstancedMesh")return null;var n=t.getObjectCenter().subtract(e),i=new fn.a(e,n,this._options.radius).intersectsMesh(t.object).pickedPoint;if(!i)return null;var o=u.e.Distance(e,i);if(o>this._options.radius)return null;var a=this._options.falloff===Ro.Constant?this._options.strength:this._options.strength*(1-o/this._options.radius);return{force:n.multiplyByFloats(a,a,a),contactPoint:i,distanceFromOrigin:o}},r.prototype.triggerAffectedImpostorsCallback=function(t){this._options.affectedImpostorsCallback&&this._options.affectedImpostorsCallback(t)},r.prototype.dispose=function(t){var e=this;t===void 0&&(t=!0),t?this._sphere.dispose():setTimeout(function(){e._dataFetched||e._sphere.dispose()},0)},r.prototype._prepareSphere=function(){this._sphere||(this._sphere=Fn.a.CreateSphere("radialExplosionEventSphere",this._options.sphere,this._scene),this._sphere.isVisible=!1)},r.prototype._intersectsWithSphere=function(t,e,n){var i=t.object;return this._prepareSphere(),this._sphere.position=e,this._sphere.scaling=new u.e(2*n,2*n,2*n),this._sphere._updateBoundingInfo(),this._sphere.computeWorldMatrix(!0),this._sphere.intersectsMesh(i,!0)},r}(),Wm=function(){function r(t,e,n,i){this._physicsHelper=t,this._scene=e,this._origin=n,this._options=i,this._dataFetched=!1,this._options=Object(c.a)(Object(c.a)({},new Ur),this._options),this._tickCallback=this._tick.bind(this),this._options.strength=-1*this._options.strength}return r.prototype.getData=function(){return this._dataFetched=!0,{sphere:this._sphere}},r.prototype.enable=function(){this._tickCallback.call(this),this._scene.registerBeforeRender(this._tickCallback)},r.prototype.disable=function(){this._scene.unregisterBeforeRender(this._tickCallback)},r.prototype.dispose=function(t){var e=this;t===void 0&&(t=!0),t?this._sphere.dispose():setTimeout(function(){e._dataFetched||e._sphere.dispose()},0)},r.prototype._tick=function(){if(this._sphere)this._physicsHelper.applyRadialExplosionForce(this._origin,this._options);else{var t=this._physicsHelper.applyRadialExplosionForce(this._origin,this._options);t&&(this._sphere=t.getData().sphere.clone("radialExplosionEventSphereClone"))}},r}(),Xm=function(){function r(t,e,n){this._scene=t,this._origin=e,this._options=n,this._originTop=u.e.Zero(),this._originDirection=u.e.Zero(),this._cylinderPosition=u.e.Zero(),this._dataFetched=!1,this._physicsEngine=this._scene.getPhysicsEngine(),this._options=Object(c.a)(Object(c.a)({},new Nc),this._options),this._origin.addToRef(new u.e(0,this._options.height/2,0),this._cylinderPosition),this._origin.addToRef(new u.e(0,this._options.height,0),this._originTop),this._options.updraftMode===Br.Perpendicular&&(this._originDirection=this._origin.subtract(this._originTop).normalize()),this._tickCallback=this._tick.bind(this),this._prepareCylinder()}return r.prototype.getData=function(){return this._dataFetched=!0,{cylinder:this._cylinder}},r.prototype.enable=function(){this._tickCallback.call(this),this._scene.registerBeforeRender(this._tickCallback)},r.prototype.disable=function(){this._scene.unregisterBeforeRender(this._tickCallback)},r.prototype.dispose=function(t){var e=this;t===void 0&&(t=!0),this._cylinder&&(t?this._cylinder.dispose():setTimeout(function(){e._dataFetched||e._cylinder.dispose()},0))},r.prototype.getImpostorHitData=function(t){if(t.mass===0||!this._intersectsWithCylinder(t))return null;var e=t.getObjectCenter();if(this._options.updraftMode===Br.Perpendicular)var n=this._originDirection;else n=e.subtract(this._originTop);var i=u.e.Distance(this._origin,e),o=-1*this._options.strength;return{force:n.multiplyByFloats(o,o,o),contactPoint:e,distanceFromOrigin:i}},r.prototype._tick=function(){var t=this;this._physicsEngine.getImpostors().forEach(function(e){var n=t.getImpostorHitData(e);n&&e.applyForce(n.force,n.contactPoint)})},r.prototype._prepareCylinder=function(){this._cylinder||(this._cylinder=pi.a.CreateCylinder("updraftEventCylinder",{height:this._options.height,diameter:2*this._options.radius},this._scene),this._cylinder.isVisible=!1)},r.prototype._intersectsWithCylinder=function(t){var e=t.object;return this._cylinder.position=this._cylinderPosition,this._cylinder.intersectsMesh(e,!0)},r}(),Ym=function(){function r(t,e,n){this._scene=t,this._origin=e,this._options=n,this._originTop=u.e.Zero(),this._cylinderPosition=u.e.Zero(),this._dataFetched=!1,this._physicsEngine=this._scene.getPhysicsEngine(),this._options=Object(c.a)(Object(c.a)({},new wc),this._options),this._origin.addToRef(new u.e(0,this._options.height/2,0),this._cylinderPosition),this._origin.addToRef(new u.e(0,this._options.height,0),this._originTop),this._tickCallback=this._tick.bind(this),this._prepareCylinder()}return r.prototype.getData=function(){return this._dataFetched=!0,{cylinder:this._cylinder}},r.prototype.enable=function(){this._tickCallback.call(this),this._scene.registerBeforeRender(this._tickCallback)},r.prototype.disable=function(){this._scene.unregisterBeforeRender(this._tickCallback)},r.prototype.dispose=function(t){var e=this;t===void 0&&(t=!0),t?this._cylinder.dispose():setTimeout(function(){e._dataFetched||e._cylinder.dispose()},0)},r.prototype.getImpostorHitData=function(t){if(t.mass===0||!this._intersectsWithCylinder(t)||t.object.getClassName()!=="Mesh"&&t.object.getClassName()!=="InstancedMesh")return null;var e=t.getObjectCenter(),n=new u.e(this._origin.x,e.y,this._origin.z),i=e.subtract(n),o=new fn.a(n,i,this._options.radius).intersectsMesh(t.object),a=o.pickedPoint;if(!a)return null;var s=o.distance/this._options.radius,d=a.normalize();if(s>this._options.centripetalForceThreshold&&(d=d.negate()),s>this._options.centripetalForceThreshold)var p=d.x*this._options.centripetalForceMultiplier,b=d.y*this._options.updraftForceMultiplier,P=d.z*this._options.centripetalForceMultiplier;else{var O=u.e.Cross(n,e).normalize();p=(O.x+d.x)*this._options.centrifugalForceMultiplier,b=this._originTop.y*this._options.updraftForceMultiplier,P=(O.z+d.z)*this._options.centrifugalForceMultiplier}var B=new u.e(p,b,P);return{force:B=B.multiplyByFloats(this._options.strength,this._options.strength,this._options.strength),contactPoint:e,distanceFromOrigin:s}},r.prototype._tick=function(){var t=this;this._physicsEngine.getImpostors().forEach(function(e){var n=t.getImpostorHitData(e);n&&e.applyForce(n.force,n.contactPoint)})},r.prototype._prepareCylinder=function(){this._cylinder||(this._cylinder=pi.a.CreateCylinder("vortexEventCylinder",{height:this._options.height,diameter:2*this._options.radius},this._scene),this._cylinder.isVisible=!1)},r.prototype._intersectsWithCylinder=function(t){var e=t.object;return this._cylinder.position=this._cylinderPosition,this._cylinder.intersectsMesh(e,!0)},r}(),Ur=function(){this.radius=5,this.strength=10,this.falloff=Ro.Constant,this.sphere={segments:32,diameter:1}},Nc=function(){this.radius=5,this.strength=10,this.height=10,this.updraftMode=Br.Center},wc=function(){this.radius=5,this.strength=10,this.height=10,this.centripetalForceThreshold=.7,this.centripetalForceMultiplier=5,this.centrifugalForceMultiplier=.5,this.updraftForceMultiplier=.02};(function(r){r[r.Constant=0]="Constant",r[r.Linear=1]="Linear"})(Ro||(Ro={})),function(r){r[r.Center=0]="Center",r[r.Perpendicular=1]="Perpendicular"}(Br||(Br={}));var Km=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform float degree;
-void main(void)
-{
-vec3 color=texture2D(textureSampler,vUV).rgb;
-float luminance=dot(color,vec3(0.3,0.59,0.11));
-vec3 blackAndWhite=vec3(luminance,luminance,luminance);
-gl_FragColor=vec4(color-((color-blackAndWhite)*degree),1.0);
-}`;ze.a.ShadersStore.blackAndWhitePixelShader=Km;var Dd=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,"blackAndWhite",["degree"],null,n,i,o,a,s)||this;return d.degree=1,d.onApplyObservable.add(function(p){p.setFloat("degree",d.degree)}),d}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"BlackAndWhitePostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"degree",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.BlackAndWhitePostProcess"]=Dd;var Rt=function(){function r(t,e,n,i){this._name=e,this._singleInstance=i||!0,this._getPostProcesses=n,this._cameras={},this._indicesForCamera={},this._postProcesses={}}return Object.defineProperty(r.prototype,"isSupported",{get:function(){for(var t in this._postProcesses)if(this._postProcesses.hasOwnProperty(t)){for(var e=this._postProcesses[t],n=0;n<e.length;n++)if(!e[n].isSupported)return!1}return!0},enumerable:!1,configurable:!0}),r.prototype._update=function(){},r.prototype._attachCameras=function(t){var e,n=this,i=Xe.b.MakeArray(t||this._cameras);if(i)for(var o=0;o<i.length;o++){var a=i[o];if(a){var s=a.name;if(e=this._singleInstance?0:s,!this._postProcesses[e]){var d=this._getPostProcesses();d&&(this._postProcesses[e]=Array.isArray(d)?d:[d])}this._indicesForCamera[s]||(this._indicesForCamera[s]=[]),this._postProcesses[e].forEach(function(p){var b=a.attachPostProcess(p);n._indicesForCamera[s].push(b)}),this._cameras[s]||(this._cameras[s]=a)}}},r.prototype._detachCameras=function(t){var e=Xe.b.MakeArray(t||this._cameras);if(e)for(var n=0;n<e.length;n++){var i=e[n],o=i.name,a=this._postProcesses[this._singleInstance?0:o];a&&a.forEach(function(s){i.detachPostProcess(s)}),this._cameras[o]&&(this._cameras[o]=null)}},r.prototype._enable=function(t){var e=this,n=Xe.b.MakeArray(t||this._cameras);if(n)for(var i=0;i<n.length;i++)for(var o=n[i],a=o.name,s=0;s<this._indicesForCamera[a].length;s++)o._postProcesses[this._indicesForCamera[a][s]]!==void 0&&o._postProcesses[this._indicesForCamera[a][s]]!==null||this._postProcesses[this._singleInstance?0:a].forEach(function(d){n[i].attachPostProcess(d,e._indicesForCamera[a][s])})},r.prototype._disable=function(t){var e=Xe.b.MakeArray(t||this._cameras);if(e)for(var n=0;n<e.length;n++){var i=e[n],o=i.name;this._postProcesses[this._singleInstance?0:o].forEach(function(a){i.detachPostProcess(a)})}},r.prototype.getPostProcesses=function(t){return this._singleInstance?this._postProcesses[0]:t?this._postProcesses[t.name]:null},r}(),Qm=`#include<helperFunctions>
-
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform float threshold;
-uniform float exposure;
-void main(void)
-{
-gl_FragColor=texture2D(textureSampler,vUV);
-float luma=getLuminance(gl_FragColor.rgb*exposure);
-gl_FragColor.rgb=step(threshold,luma)*gl_FragColor.rgb;
-}`;ze.a.ShadersStore.extractHighlightsPixelShader=Qm;var Fc=function(r){function t(e,n,i,o,a,s,d,p){d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT),p===void 0&&(p=!1);var b=r.call(this,e,"extractHighlights",["threshold","exposure"],null,n,i,o,a,s,null,d,void 0,null,p)||this;return b.threshold=.9,b._exposure=1,b._inputPostProcess=null,b.onApplyObservable.add(function(P){b._inputPostProcess&&P.setTextureFromPostProcess("textureSampler",b._inputPostProcess),P.setFloat("threshold",Math.pow(b.threshold,Gt.b)),P.setFloat("exposure",b._exposure)}),b}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ExtractHighlightsPostProcess"},Object(c.c)([Object(L.c)()],t.prototype,"threshold",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.ExtractHighlightsPostProcess"]=Fc;var qm=`uniform sampler2D textureSampler;
-uniform sampler2D bloomBlur;
-varying vec2 vUV;
-uniform float bloomWeight;
-void main(void)
-{
-gl_FragColor=texture2D(textureSampler,vUV);
-vec3 blurred=texture2D(bloomBlur,vUV).rgb;
-gl_FragColor.rgb=gl_FragColor.rgb+(blurred.rgb*bloomWeight);
-}
-`;ze.a.ShadersStore.bloomMergePixelShader=qm;var Bc=function(r){function t(e,n,i,o,a,s,d,p,b,P,O){P===void 0&&(P=h.a.TEXTURETYPE_UNSIGNED_INT),O===void 0&&(O=!1);var B=r.call(this,e,"bloomMerge",["bloomWeight"],["circleOfConfusionSampler","blurStep0","blurStep1","blurStep2","bloomBlur"],a,s,d,p,b,null,P,void 0,null,!0)||this;return B.weight=1,B.weight=o,B.onApplyObservable.add(function(F){F.setTextureFromPostProcess("textureSampler",n),F.setTextureFromPostProcessOutput("bloomBlur",i),F.setFloat("bloomWeight",B.weight)}),O||B.updateEffect(),B}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"BloomMergePostProcess"},Object(c.c)([Object(L.c)()],t.prototype,"weight",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.BloomMergePostProcess"]=Bc;var Uc=function(r){function t(e,n,i,o,a,s){a===void 0&&(a=0),s===void 0&&(s=!1);var d=r.call(this,e.getEngine(),"bloom",function(){return d._effects},!0)||this;return d.bloomScale=n,d._effects=[],d._downscale=new Fc("highlights",1,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,a,s),d._blurX=new gn("horizontal blur",new u.d(1,0),10,n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,a,void 0,s),d._blurX.alwaysForcePOT=!0,d._blurX.autoClear=!1,d._blurY=new gn("vertical blur",new u.d(0,1),10,n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,a,void 0,s),d._blurY.alwaysForcePOT=!0,d._blurY.autoClear=!1,d.kernel=o,d._effects=[d._downscale,d._blurX,d._blurY],d._merge=new Bc("bloomMerge",d._downscale,d._blurY,i,n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,a,s),d._merge.autoClear=!1,d._effects.push(d._merge),d}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"threshold",{get:function(){return this._downscale.threshold},set:function(e){this._downscale.threshold=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"weight",{get:function(){return this._merge.weight},set:function(e){this._merge.weight=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"kernel",{get:function(){return this._blurX.kernel/this.bloomScale},set:function(e){this._blurX.kernel=e*this.bloomScale,this._blurY.kernel=e*this.bloomScale},enumerable:!1,configurable:!0}),t.prototype.disposeEffects=function(e){for(var n=0;n<this._effects.length;n++)this._effects[n].dispose(e)},t.prototype._updateEffects=function(){for(var e=0;e<this._effects.length;e++)this._effects[e].updateEffect()},t.prototype._isReady=function(){for(var e=0;e<this._effects.length;e++)if(!this._effects[e].isReady())return!1;return!0},t}(Rt),Zm=`
-uniform sampler2D textureSampler;
-
-uniform float chromatic_aberration;
-uniform float radialIntensity;
-uniform vec2 direction;
-uniform vec2 centerPosition;
-uniform float screen_width;
-uniform float screen_height;
-
-varying vec2 vUV;
-void main(void)
-{
-vec2 centered_screen_pos=vec2(vUV.x-centerPosition.x,vUV.y-centerPosition.y);
-vec2 directionOfEffect=direction;
-if(directionOfEffect.x == 0. && directionOfEffect.y == 0.){
-directionOfEffect=normalize(centered_screen_pos);
-}
-float radius2=centered_screen_pos.x*centered_screen_pos.x
-+centered_screen_pos.y*centered_screen_pos.y;
-float radius=sqrt(radius2);
-vec4 original=texture2D(textureSampler,vUV);
-
-vec3 ref_indices=vec3(-0.3,0.0,0.3);
-float ref_shiftX=chromatic_aberration*pow(radius,radialIntensity)*directionOfEffect.x/screen_width;
-float ref_shiftY=chromatic_aberration*pow(radius,radialIntensity)*directionOfEffect.y/screen_height;
-
-vec2 ref_coords_r=vec2(vUV.x+ref_indices.r*ref_shiftX,vUV.y+ref_indices.r*ref_shiftY*0.5);
-vec2 ref_coords_g=vec2(vUV.x+ref_indices.g*ref_shiftX,vUV.y+ref_indices.g*ref_shiftY*0.5);
-vec2 ref_coords_b=vec2(vUV.x+ref_indices.b*ref_shiftX,vUV.y+ref_indices.b*ref_shiftY*0.5);
-original.r=texture2D(textureSampler,ref_coords_r).r;
-original.g=texture2D(textureSampler,ref_coords_g).g;
-original.b=texture2D(textureSampler,ref_coords_b).b;
-original.a=clamp(texture2D(textureSampler,ref_coords_r).a+texture2D(textureSampler,ref_coords_g).a+texture2D(textureSampler,ref_coords_b).a,0.,1.);
-gl_FragColor=original;
-}`;ze.a.ShadersStore.chromaticAberrationPixelShader=Zm;var Vc=function(r){function t(e,n,i,o,a,s,d,p,b,P){b===void 0&&(b=h.a.TEXTURETYPE_UNSIGNED_INT),P===void 0&&(P=!1);var O=r.call(this,e,"chromaticAberration",["chromatic_aberration","screen_width","screen_height","direction","radialIntensity","centerPosition"],[],o,a,s,d,p,null,b,void 0,null,P)||this;return O.aberrationAmount=30,O.radialIntensity=0,O.direction=new u.d(.707,.707),O.centerPosition=new u.d(.5,.5),O.screenWidth=n,O.screenHeight=i,O.onApplyObservable.add(function(B){B.setFloat("chromatic_aberration",O.aberrationAmount),B.setFloat("screen_width",n),B.setFloat("screen_height",i),B.setFloat("radialIntensity",O.radialIntensity),B.setFloat2("direction",O.direction.x,O.direction.y),B.setFloat2("centerPosition",O.centerPosition.x,O.centerPosition.y)}),O}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ChromaticAberrationPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.screenWidth,e.screenHeight,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable,e.textureType,!1)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"aberrationAmount",void 0),Object(c.c)([Object(L.c)()],t.prototype,"radialIntensity",void 0),Object(c.c)([Object(L.c)()],t.prototype,"direction",void 0),Object(c.c)([Object(L.c)()],t.prototype,"centerPosition",void 0),Object(c.c)([Object(L.c)()],t.prototype,"screenWidth",void 0),Object(c.c)([Object(L.c)()],t.prototype,"screenHeight",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.ChromaticAberrationPostProcess"]=Vc;var Jm=`
-uniform sampler2D depthSampler;
-
-varying vec2 vUV;
-
-uniform vec2 cameraMinMaxZ;
-
-uniform float focusDistance;
-uniform float cocPrecalculation;
-void main(void)
-{
-float depth=texture2D(depthSampler,vUV).r;
-float pixelDistance=(cameraMinMaxZ.x+(cameraMinMaxZ.y-cameraMinMaxZ.x)*depth)*1000.0;
-float coc=abs(cocPrecalculation* ((focusDistance-pixelDistance)/pixelDistance));
-coc=clamp(coc,0.0,1.0);
-gl_FragColor=vec4(coc,depth,coc,1.0);
-}
-`;ze.a.ShadersStore.circleOfConfusionPixelShader=Jm;var kc=function(r){function t(e,n,i,o,a,s,d,p,b){p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT),b===void 0&&(b=!1);var P=r.call(this,e,"circleOfConfusion",["cameraMinMaxZ","focusDistance","cocPrecalculation"],["depthSampler"],i,o,a,s,d,null,p,void 0,null,b)||this;return P.lensSize=50,P.fStop=1.4,P.focusDistance=2e3,P.focalLength=50,P._depthTexture=null,P._depthTexture=n,P.onApplyObservable.add(function(O){if(P._depthTexture){O.setTexture("depthSampler",P._depthTexture);var B=P.lensSize/P.fStop*P.focalLength/(P.focusDistance-P.focalLength);O.setFloat("focusDistance",P.focusDistance),O.setFloat("cocPrecalculation",B),O.setFloat2("cameraMinMaxZ",P._depthTexture.activeCamera.minZ,P._depthTexture.activeCamera.maxZ)}else l.a.Warn("No depth texture set on CircleOfConfusionPostProcess")}),P}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"CircleOfConfusionPostProcess"},Object.defineProperty(t.prototype,"depthTexture",{set:function(e){this._depthTexture=e},enumerable:!1,configurable:!0}),Object(c.c)([Object(L.c)()],t.prototype,"lensSize",void 0),Object(c.c)([Object(L.c)()],t.prototype,"fStop",void 0),Object(c.c)([Object(L.c)()],t.prototype,"focusDistance",void 0),Object(c.c)([Object(L.c)()],t.prototype,"focalLength",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.CircleOfConfusionPostProcess"]=kc;var $m=`
-uniform sampler2D textureSampler;
-uniform sampler2D colorTable;
-
-varying vec2 vUV;
-
-const float SLICE_COUNT=16.0;
-
-vec4 sampleAs3DTexture(sampler2D textureSampler,vec3 uv,float width) {
-float sliceSize=1.0/width;
-float slicePixelSize=sliceSize/width;
-float sliceInnerSize=slicePixelSize*(width-1.0);
-float zSlice0=min(floor(uv.z*width),width-1.0);
-float zSlice1=min(zSlice0+1.0,width-1.0);
-float xOffset=slicePixelSize*0.5+uv.x*sliceInnerSize;
-float s0=xOffset+(zSlice0*sliceSize);
-float s1=xOffset+(zSlice1*sliceSize);
-vec4 slice0Color=texture2D(textureSampler,vec2(s0,uv.y));
-vec4 slice1Color=texture2D(textureSampler,vec2(s1,uv.y));
-float zOffset=mod(uv.z*width,1.0);
-vec4 result=mix(slice0Color,slice1Color,zOffset);
-return result;
-}
-void main(void)
-{
-vec4 screen_color=texture2D(textureSampler,vUV);
-gl_FragColor=sampleAs3DTexture(colorTable,screen_color.rgb,SLICE_COUNT);
-}`;ze.a.ShadersStore.colorCorrectionPixelShader=$m;var Ld=function(r){function t(e,n,i,o,a,s,d){var p=r.call(this,e,"colorCorrection",null,["colorTable"],i,o,a,s,d)||this;return p._colorTableTexture=new we.a(n,o.getScene(),!0,!1,we.a.TRILINEAR_SAMPLINGMODE),p._colorTableTexture.anisotropicFilteringLevel=1,p._colorTableTexture.wrapU=we.a.CLAMP_ADDRESSMODE,p._colorTableTexture.wrapV=we.a.CLAMP_ADDRESSMODE,p.colorTableUrl=n,p.onApply=function(b){b.setTexture("colorTable",p._colorTableTexture)},p}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ColorCorrectionPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.colorTableUrl,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"colorTableUrl",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.ColorCorrectionPostProcess"]=Ld;var eg=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform vec2 screenSize;
-uniform float kernel[9];
-void main(void)
-{
-vec2 onePixel=vec2(1.0,1.0)/screenSize;
-vec4 colorSum =
-texture2D(textureSampler,vUV+onePixel*vec2(-1,-1))*kernel[0] +
-texture2D(textureSampler,vUV+onePixel*vec2(0,-1))*kernel[1] +
-texture2D(textureSampler,vUV+onePixel*vec2(1,-1))*kernel[2] +
-texture2D(textureSampler,vUV+onePixel*vec2(-1,0))*kernel[3] +
-texture2D(textureSampler,vUV+onePixel*vec2(0,0))*kernel[4] +
-texture2D(textureSampler,vUV+onePixel*vec2(1,0))*kernel[5] +
-texture2D(textureSampler,vUV+onePixel*vec2(-1,1))*kernel[6] +
-texture2D(textureSampler,vUV+onePixel*vec2(0,1))*kernel[7] +
-texture2D(textureSampler,vUV+onePixel*vec2(1,1))*kernel[8];
-float kernelWeight =
-kernel[0] +
-kernel[1] +
-kernel[2] +
-kernel[3] +
-kernel[4] +
-kernel[5] +
-kernel[6] +
-kernel[7] +
-kernel[8];
-if (kernelWeight<=0.0) {
-kernelWeight=1.0;
-}
-gl_FragColor=vec4((colorSum/kernelWeight).rgb,1);
-}`;ze.a.ShadersStore.convolutionPixelShader=eg;var Nd=function(r){function t(e,n,i,o,a,s,d,p){p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT);var b=r.call(this,e,"convolution",["kernel","screenSize"],null,i,o,a,s,d,null,p)||this;return b.kernel=n,b.onApply=function(P){P.setFloat2("screenSize",b.width,b.height),P.setArray("kernel",b.kernel)},b}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ConvolutionPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.kernel,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable,e.textureType)},e,i,o)},t.EdgeDetect0Kernel=[1,0,-1,0,0,0,-1,0,1],t.EdgeDetect1Kernel=[0,1,0,1,-4,1,0,1,0],t.EdgeDetect2Kernel=[-1,-1,-1,-1,8,-1,-1,-1,-1],t.SharpenKernel=[0,-1,0,-1,5,-1,0,-1,0],t.EmbossKernel=[-2,-1,0,-1,1,1,0,1,2],t.GaussianKernel=[0,1,0,1,1,1,0,1,0],Object(c.c)([Object(L.c)()],t.prototype,"kernel",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.ConvolutionPostProcess"]=Nd;var Aa=function(r){function t(e,n,i,o,a,s,d,p,b,P,O,B,F){p===void 0&&(p=null),b===void 0&&(b=we.a.BILINEAR_SAMPLINGMODE),B===void 0&&(B=h.a.TEXTURETYPE_UNSIGNED_INT),F===void 0&&(F=!1);var z=r.call(this,e,i,o,a,s,b=h.a.TEXTURE_BILINEAR_SAMPLINGMODE,P,O,B=h.a.TEXTURETYPE_UNSIGNED_INT,`#define DOF 1\r
-`,F)||this;return z.direction=i,z.onApplyObservable.add(function(J){p!=null&&J.setTextureFromPostProcess("textureSampler",p),J.setTextureFromPostProcessOutput("circleOfConfusionSampler",d),n.activeCamera&&J.setFloat2("cameraMinMaxZ",n.activeCamera.minZ,n.activeCamera.maxZ)}),z}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DepthOfFieldBlurPostProcess"},Object(c.c)([Object(L.c)()],t.prototype,"direction",void 0),t}(gn);R.a.RegisteredTypes["BABYLON.DepthOfFieldBlurPostProcess"]=Aa;var tg=`uniform sampler2D textureSampler;
-varying vec2 vUV;
-uniform sampler2D circleOfConfusionSampler;
-uniform sampler2D blurStep0;
-#if BLUR_LEVEL>0
-uniform sampler2D blurStep1;
-#endif
-#if BLUR_LEVEL>1
-uniform sampler2D blurStep2;
-#endif
-void main(void)
-{
-float coc=texture2D(circleOfConfusionSampler,vUV).r;
-#if BLUR_LEVEL == 0
-vec4 original=texture2D(textureSampler,vUV);
-vec4 blurred0=texture2D(blurStep0,vUV);
-gl_FragColor=mix(original,blurred0,coc);
-#endif
-#if BLUR_LEVEL == 1
-if(coc<0.5){
-vec4 original=texture2D(textureSampler,vUV);
-vec4 blurred1=texture2D(blurStep1,vUV);
-gl_FragColor=mix(original,blurred1,coc/0.5);
-}else{
-vec4 blurred0=texture2D(blurStep0,vUV);
-vec4 blurred1=texture2D(blurStep1,vUV);
-gl_FragColor=mix(blurred1,blurred0,(coc-0.5)/0.5);
-}
-#endif
-#if BLUR_LEVEL == 2
-if(coc<0.33){
-vec4 original=texture2D(textureSampler,vUV);
-vec4 blurred2=texture2D(blurStep2,vUV);
-gl_FragColor=mix(original,blurred2,coc/0.33);
-}else if(coc<0.66){
-vec4 blurred1=texture2D(blurStep1,vUV);
-vec4 blurred2=texture2D(blurStep2,vUV);
-gl_FragColor=mix(blurred2,blurred1,(coc-0.33)/0.33);
-}else{
-vec4 blurred0=texture2D(blurStep0,vUV);
-vec4 blurred1=texture2D(blurStep1,vUV);
-gl_FragColor=mix(blurred1,blurred0,(coc-0.66)/0.34);
-}
-#endif
-}
-`;ze.a.ShadersStore.depthOfFieldMergePixelShader=tg;var sr,ng=function(){},wd=function(r){function t(e,n,i,o,a,s,d,p,b,P,O){P===void 0&&(P=h.a.TEXTURETYPE_UNSIGNED_INT),O===void 0&&(O=!1);var B=r.call(this,e,"depthOfFieldMerge",[],["circleOfConfusionSampler","blurStep0","blurStep1","blurStep2"],a,s,d,p,b,null,P,void 0,null,!0)||this;return B.blurSteps=o,B.onApplyObservable.add(function(F){F.setTextureFromPostProcess("textureSampler",n),F.setTextureFromPostProcessOutput("circleOfConfusionSampler",i),o.forEach(function(z,J){F.setTextureFromPostProcessOutput("blurStep"+(o.length-J-1),z)})}),O||B.updateEffect(),B}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DepthOfFieldMergePostProcess"},t.prototype.updateEffect=function(e,n,i,o,a,s){e===void 0&&(e=null),n===void 0&&(n=null),i===void 0&&(i=null),e||(e="",e+="#define BLUR_LEVEL "+(this.blurSteps.length-1)+`
-`),r.prototype.updateEffect.call(this,e,n,i,o,a,s)},t}(_t);(function(r){r[r.Low=0]="Low",r[r.Medium=1]="Medium",r[r.High=2]="High"})(sr||(sr={}));var Gc=function(r){function t(e,n,i,o,a){i===void 0&&(i=sr.Low),o===void 0&&(o=0),a===void 0&&(a=!1);var s=r.call(this,e.getEngine(),"depth of field",function(){return s._effects},!0)||this;s._effects=[],s._circleOfConfusion=new kc("circleOfConfusion",n,1,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,o,a),s._depthOfFieldBlurY=[],s._depthOfFieldBlurX=[];var d=1,p=15;switch(i){case sr.High:d=3,p=51;break;case sr.Medium:d=2,p=31;break;default:p=15,d=1}for(var b=p/Math.pow(2,d-1),P=1,O=0;O<d;O++){var B=new Aa("verticle blur",e,new u.d(0,1),b,P,null,s._circleOfConfusion,O==0?s._circleOfConfusion:null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,o,a);B.autoClear=!1,P=.75/Math.pow(2,O);var F=new Aa("horizontal blur",e,new u.d(1,0),b,P,null,s._circleOfConfusion,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,o,a);F.autoClear=!1,s._depthOfFieldBlurY.push(B),s._depthOfFieldBlurX.push(F)}for(s._effects=[s._circleOfConfusion],O=0;O<s._depthOfFieldBlurX.length;O++)s._effects.push(s._depthOfFieldBlurY[O]),s._effects.push(s._depthOfFieldBlurX[O]);return s._dofMerge=new wd("dofMerge",s._circleOfConfusion,s._circleOfConfusion,s._depthOfFieldBlurX,P,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,o,a),s._dofMerge.autoClear=!1,s._effects.push(s._dofMerge),s}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"focalLength",{get:function(){return this._circleOfConfusion.focalLength},set:function(e){this._circleOfConfusion.focalLength=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"fStop",{get:function(){return this._circleOfConfusion.fStop},set:function(e){this._circleOfConfusion.fStop=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"focusDistance",{get:function(){return this._circleOfConfusion.focusDistance},set:function(e){this._circleOfConfusion.focusDistance=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"lensSize",{get:function(){return this._circleOfConfusion.lensSize},set:function(e){this._circleOfConfusion.lensSize=e},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"DepthOfFieldEffect"},Object.defineProperty(t.prototype,"depthTexture",{set:function(e){this._circleOfConfusion.depthTexture=e},enumerable:!1,configurable:!0}),t.prototype.disposeEffects=function(e){for(var n=0;n<this._effects.length;n++)this._effects[n].dispose(e)},t.prototype._updateEffects=function(){for(var e=0;e<this._effects.length;e++)this._effects[e].updateEffect()},t.prototype._isReady=function(){for(var e=0;e<this._effects.length;e++)if(!this._effects[e].isReady())return!1;return!0},t}(Rt),ig=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform sampler2D passSampler;
-void main(void)
-{
-gl_FragColor=texture2D(passSampler,vUV);
-}`;ze.a.ShadersStore.displayPassPixelShader=ig;var Fd=function(r){function t(e,n,i,o,a,s){return r.call(this,e,"displayPass",["passSampler"],["passSampler"],n,i,o,a,s)||this}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"DisplayPassPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},t}(_t);R.a.RegisteredTypes["BABYLON.DisplayPassPostProcess"]=Fd;var rg=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform mat4 kernelMatrix;
-void main(void)
-{
-vec3 baseColor=texture2D(textureSampler,vUV).rgb;
-vec3 updatedColor=(kernelMatrix*vec4(baseColor,1.0)).rgb;
-gl_FragColor=vec4(updatedColor,1.0);
-}`;ze.a.ShadersStore.filterPixelShader=rg;var Bd=function(r){function t(e,n,i,o,a,s,d){var p=r.call(this,e,"filter",["kernelMatrix"],null,i,o,a,s,d)||this;return p.kernelMatrix=n,p.onApply=function(b){b.setMatrix("kernelMatrix",p.kernelMatrix)},p}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FilterPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.kernelMatrix,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},Object(c.c)([Object(L.j)()],t.prototype,"kernelMatrix",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.FilterPostProcess"]=Bd;var og=`uniform sampler2D textureSampler;
-uniform vec2 texelSize;
-varying vec2 vUV;
-varying vec2 sampleCoordS;
-varying vec2 sampleCoordE;
-varying vec2 sampleCoordN;
-varying vec2 sampleCoordW;
-varying vec2 sampleCoordNW;
-varying vec2 sampleCoordSE;
-varying vec2 sampleCoordNE;
-varying vec2 sampleCoordSW;
-const float fxaaQualitySubpix=1.0;
-const float fxaaQualityEdgeThreshold=0.166;
-const float fxaaQualityEdgeThresholdMin=0.0833;
-const vec3 kLumaCoefficients=vec3(0.2126,0.7152,0.0722);
-#define FxaaLuma(rgba) dot(rgba.rgb,kLumaCoefficients)
-void main(){
-vec2 posM;
-posM.x=vUV.x;
-posM.y=vUV.y;
-vec4 rgbyM=texture2D(textureSampler,vUV,0.0);
-float lumaM=FxaaLuma(rgbyM);
-float lumaS=FxaaLuma(texture2D(textureSampler,sampleCoordS,0.0));
-float lumaE=FxaaLuma(texture2D(textureSampler,sampleCoordE,0.0));
-float lumaN=FxaaLuma(texture2D(textureSampler,sampleCoordN,0.0));
-float lumaW=FxaaLuma(texture2D(textureSampler,sampleCoordW,0.0));
-float maxSM=max(lumaS,lumaM);
-float minSM=min(lumaS,lumaM);
-float maxESM=max(lumaE,maxSM);
-float minESM=min(lumaE,minSM);
-float maxWN=max(lumaN,lumaW);
-float minWN=min(lumaN,lumaW);
-float rangeMax=max(maxWN,maxESM);
-float rangeMin=min(minWN,minESM);
-float rangeMaxScaled=rangeMax*fxaaQualityEdgeThreshold;
-float range=rangeMax-rangeMin;
-float rangeMaxClamped=max(fxaaQualityEdgeThresholdMin,rangeMaxScaled);
-#ifndef MALI
-if(range<rangeMaxClamped)
-{
-gl_FragColor=rgbyM;
-return;
-}
-#endif
-float lumaNW=FxaaLuma(texture2D(textureSampler,sampleCoordNW,0.0));
-float lumaSE=FxaaLuma(texture2D(textureSampler,sampleCoordSE,0.0));
-float lumaNE=FxaaLuma(texture2D(textureSampler,sampleCoordNE,0.0));
-float lumaSW=FxaaLuma(texture2D(textureSampler,sampleCoordSW,0.0));
-float lumaNS=lumaN+lumaS;
-float lumaWE=lumaW+lumaE;
-float subpixRcpRange=1.0/range;
-float subpixNSWE=lumaNS+lumaWE;
-float edgeHorz1=(-2.0*lumaM)+lumaNS;
-float edgeVert1=(-2.0*lumaM)+lumaWE;
-float lumaNESE=lumaNE+lumaSE;
-float lumaNWNE=lumaNW+lumaNE;
-float edgeHorz2=(-2.0*lumaE)+lumaNESE;
-float edgeVert2=(-2.0*lumaN)+lumaNWNE;
-float lumaNWSW=lumaNW+lumaSW;
-float lumaSWSE=lumaSW+lumaSE;
-float edgeHorz4=(abs(edgeHorz1)*2.0)+abs(edgeHorz2);
-float edgeVert4=(abs(edgeVert1)*2.0)+abs(edgeVert2);
-float edgeHorz3=(-2.0*lumaW)+lumaNWSW;
-float edgeVert3=(-2.0*lumaS)+lumaSWSE;
-float edgeHorz=abs(edgeHorz3)+edgeHorz4;
-float edgeVert=abs(edgeVert3)+edgeVert4;
-float subpixNWSWNESE=lumaNWSW+lumaNESE;
-float lengthSign=texelSize.x;
-bool horzSpan=edgeHorz>=edgeVert;
-float subpixA=subpixNSWE*2.0+subpixNWSWNESE;
-if (!horzSpan)
-{
-lumaN=lumaW;
-}
-if (!horzSpan)
-{
-lumaS=lumaE;
-}
-if (horzSpan)
-{
-lengthSign=texelSize.y;
-}
-float subpixB=(subpixA*(1.0/12.0))-lumaM;
-float gradientN=lumaN-lumaM;
-float gradientS=lumaS-lumaM;
-float lumaNN=lumaN+lumaM;
-float lumaSS=lumaS+lumaM;
-bool pairN=abs(gradientN)>=abs(gradientS);
-float gradient=max(abs(gradientN),abs(gradientS));
-if (pairN)
-{
-lengthSign=-lengthSign;
-}
-float subpixC=clamp(abs(subpixB)*subpixRcpRange,0.0,1.0);
-vec2 posB;
-posB.x=posM.x;
-posB.y=posM.y;
-vec2 offNP;
-offNP.x=(!horzSpan) ? 0.0 : texelSize.x;
-offNP.y=(horzSpan) ? 0.0 : texelSize.y;
-if (!horzSpan)
-{
-posB.x+=lengthSign*0.5;
-}
-if (horzSpan)
-{
-posB.y+=lengthSign*0.5;
-}
-vec2 posN;
-posN.x=posB.x-offNP.x*1.5;
-posN.y=posB.y-offNP.y*1.5;
-vec2 posP;
-posP.x=posB.x+offNP.x*1.5;
-posP.y=posB.y+offNP.y*1.5;
-float subpixD=((-2.0)*subpixC)+3.0;
-float lumaEndN=FxaaLuma(texture2D(textureSampler,posN,0.0));
-float subpixE=subpixC*subpixC;
-float lumaEndP=FxaaLuma(texture2D(textureSampler,posP,0.0));
-if (!pairN)
-{
-lumaNN=lumaSS;
-}
-float gradientScaled=gradient*1.0/4.0;
-float lumaMM=lumaM-lumaNN*0.5;
-float subpixF=subpixD*subpixE;
-bool lumaMLTZero=lumaMM<0.0;
-lumaEndN-=lumaNN*0.5;
-lumaEndP-=lumaNN*0.5;
-bool doneN=abs(lumaEndN)>=gradientScaled;
-bool doneP=abs(lumaEndP)>=gradientScaled;
-if (!doneN)
-{
-posN.x-=offNP.x*3.0;
-}
-if (!doneN)
-{
-posN.y-=offNP.y*3.0;
-}
-bool doneNP=(!doneN) || (!doneP);
-if (!doneP)
-{
-posP.x+=offNP.x*3.0;
-}
-if (!doneP)
-{
-posP.y+=offNP.y*3.0;
-}
-if (doneNP)
-{
-if (!doneN) lumaEndN=FxaaLuma(texture2D(textureSampler,posN.xy,0.0));
-if (!doneP) lumaEndP=FxaaLuma(texture2D(textureSampler,posP.xy,0.0));
-if (!doneN) lumaEndN=lumaEndN-lumaNN*0.5;
-if (!doneP) lumaEndP=lumaEndP-lumaNN*0.5;
-doneN=abs(lumaEndN)>=gradientScaled;
-doneP=abs(lumaEndP)>=gradientScaled;
-if (!doneN) posN.x-=offNP.x*12.0;
-if (!doneN) posN.y-=offNP.y*12.0;
-doneNP=(!doneN) || (!doneP);
-if (!doneP) posP.x+=offNP.x*12.0;
-if (!doneP) posP.y+=offNP.y*12.0;
-}
-float dstN=posM.x-posN.x;
-float dstP=posP.x-posM.x;
-if (!horzSpan)
-{
-dstN=posM.y-posN.y;
-}
-if (!horzSpan)
-{
-dstP=posP.y-posM.y;
-}
-bool goodSpanN=(lumaEndN<0.0) != lumaMLTZero;
-float spanLength=(dstP+dstN);
-bool goodSpanP=(lumaEndP<0.0) != lumaMLTZero;
-float spanLengthRcp=1.0/spanLength;
-bool directionN=dstN<dstP;
-float dst=min(dstN,dstP);
-bool goodSpan=directionN ? goodSpanN : goodSpanP;
-float subpixG=subpixF*subpixF;
-float pixelOffset=(dst*(-spanLengthRcp))+0.5;
-float subpixH=subpixG*fxaaQualitySubpix;
-float pixelOffsetGood=goodSpan ? pixelOffset : 0.0;
-float pixelOffsetSubpix=max(pixelOffsetGood,subpixH);
-if (!horzSpan)
-{
-posM.x+=pixelOffsetSubpix*lengthSign;
-}
-if (horzSpan)
-{
-posM.y+=pixelOffsetSubpix*lengthSign;
-}
-#ifdef MALI
-if(range<rangeMaxClamped)
-{
-gl_FragColor=rgbyM;
-}
-else
-{
-gl_FragColor=texture2D(textureSampler,posM,0.0);
-}
-#else
-gl_FragColor=texture2D(textureSampler,posM,0.0);
-#endif
-}`;ze.a.ShadersStore.fxaaPixelShader=og;var ag=`
-attribute vec2 position;
-uniform vec2 texelSize;
-
-varying vec2 vUV;
-varying vec2 sampleCoordS;
-varying vec2 sampleCoordE;
-varying vec2 sampleCoordN;
-varying vec2 sampleCoordW;
-varying vec2 sampleCoordNW;
-varying vec2 sampleCoordSE;
-varying vec2 sampleCoordNE;
-varying vec2 sampleCoordSW;
-const vec2 madd=vec2(0.5,0.5);
-void main(void) {
-vUV=(position*madd+madd);
-sampleCoordS=vUV+vec2( 0.0,1.0)*texelSize;
-sampleCoordE=vUV+vec2( 1.0,0.0)*texelSize;
-sampleCoordN=vUV+vec2( 0.0,-1.0)*texelSize;
-sampleCoordW=vUV+vec2(-1.0,0.0)*texelSize;
-sampleCoordNW=vUV+vec2(-1.0,-1.0)*texelSize;
-sampleCoordSE=vUV+vec2( 1.0,1.0)*texelSize;
-sampleCoordNE=vUV+vec2( 1.0,-1.0)*texelSize;
-sampleCoordSW=vUV+vec2(-1.0,1.0)*texelSize;
-gl_Position=vec4(position,0.0,1.0);
-}`;ze.a.ShadersStore.fxaaVertexShader=ag;var Oo=function(r){function t(e,n,i,o,a,s,d){i===void 0&&(i=null),d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT);var p=r.call(this,e,"fxaa",["texelSize"],null,n,i,o||we.a.BILINEAR_SAMPLINGMODE,a,s,null,d,"fxaa",void 0,!0)||this,b=p._getDefines();return p.updateEffect(b),p.onApplyObservable.add(function(P){var O=p.texelSize;P.setFloat2("texelSize",O.x,O.y)}),p}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"FxaaPostProcess"},t.prototype._getDefines=function(){var e=this.getEngine();if(!e)return null;var n=e.getGlInfo();return n&&n.renderer&&n.renderer.toLowerCase().indexOf("mali")>-1?`#define MALI 1
-`:null},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},t}(_t);R.a.RegisteredTypes["BABYLON.FxaaPostProcess"]=Oo;var sg=`#include<helperFunctions>
-
-uniform sampler2D textureSampler;
-
-uniform float intensity;
-uniform float animatedSeed;
-
-varying vec2 vUV;
-void main(void)
-{
-gl_FragColor=texture2D(textureSampler,vUV);
-vec2 seed=vUV*(animatedSeed);
-float grain=dither(seed,intensity);
-
-float lum=getLuminance(gl_FragColor.rgb);
-float grainAmount=(cos(-PI+(lum*PI*2.))+1.)/2.;
-gl_FragColor.rgb+=grain*grainAmount;
-gl_FragColor.rgb=max(gl_FragColor.rgb,0.0);
-}`;ze.a.ShadersStore.grainPixelShader=sg;var zc=function(r){function t(e,n,i,o,a,s,d,p){d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT),p===void 0&&(p=!1);var b=r.call(this,e,"grain",["intensity","animatedSeed"],[],n,i,o,a,s,null,d,void 0,null,p)||this;return b.intensity=30,b.animated=!1,b.onApplyObservable.add(function(P){P.setFloat("intensity",b.intensity),P.setFloat("animatedSeed",b.animated?Math.random()+1:1)}),b}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"GrainPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"intensity",void 0),Object(c.c)([Object(L.c)()],t.prototype,"animated",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.GrainPostProcess"]=zc;var cg=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-const vec3 RGBLuminanceCoefficients=vec3(0.2126,0.7152,0.0722);
-void main(void)
-{
-vec4 tex=texture2D(textureSampler,vUV);
-vec3 c=tex.rgb;
-float luma=dot(c.rgb,RGBLuminanceCoefficients);
-
-
-gl_FragColor=vec4(pow(c,vec3(25.0-luma*15.0)),tex.a);
-}`;ze.a.ShadersStore.highlightsPixelShader=cg;var lg=function(r){function t(e,n,i,o,a,s,d){return d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT),r.call(this,e,"highlights",null,null,n,i,o,a,s,null,d)||this}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"HighlightsPostProcess"},t}(_t);ze.a.IncludesShadersStore.mrtFragmentDeclaration=`#if __VERSION__>=200
-layout(location=0) out vec4 glFragData[{X}];
-#endif
-`;var ug=`#extension GL_EXT_draw_buffers : require
-#if defined(BUMP) || !defined(NORMAL)
-#extension GL_OES_standard_derivatives : enable
-#endif
-precision highp float;
-precision highp int;
-#ifdef BUMP
-varying mat4 vWorldView;
-varying vec3 vNormalW;
-#else
-varying vec3 vNormalV;
-#endif
-varying vec4 vViewPos;
-#if defined(POSITION) || defined(BUMP)
-varying vec3 vPositionW;
-#endif
-#ifdef VELOCITY
-varying vec4 vCurrentPosition;
-varying vec4 vPreviousPosition;
-#endif
-#ifdef NEED_UV
-varying vec2 vUV;
-#endif
-#ifdef BUMP
-uniform vec3 vBumpInfos;
-uniform vec2 vTangentSpaceParams;
-#endif
-#ifdef REFLECTIVITY
-varying vec2 vReflectivityUV;
-uniform sampler2D reflectivitySampler;
-#endif
-#ifdef ALPHATEST
-uniform sampler2D diffuseSampler;
-#endif
-#include<mrtFragmentDeclaration>[RENDER_TARGET_COUNT]
-#include<bumpFragmentMainFunctions>
-#include<bumpFragmentFunctions>
-void main() {
-#ifdef ALPHATEST
-if (texture2D(diffuseSampler,vUV).a<0.4)
-discard;
-#endif
-vec3 normalOutput;
-#ifdef BUMP
-vec3 normalW=normalize(vNormalW);
-#include<bumpFragment>
-normalOutput=normalize(vec3(vWorldView*vec4(normalW,0.0)));
-#else
-normalOutput=normalize(vNormalV);
-#endif
-#ifdef PREPASS
-#ifdef PREPASS_DEPTHNORMAL
-gl_FragData[DEPTHNORMAL_INDEX]=vec4(vViewPos.z/vViewPos.w,normalOutput);
-#endif
-#else
-gl_FragData[0]=vec4(vViewPos.z/vViewPos.w,0.0,0.0,1.0);
-gl_FragData[1]=vec4(normalOutput,1.0);
-#endif
-#ifdef POSITION
-gl_FragData[POSITION_INDEX]=vec4(vPositionW,1.0);
-#endif
-#ifdef VELOCITY
-vec2 a=(vCurrentPosition.xy/vCurrentPosition.w)*0.5+0.5;
-vec2 b=(vPreviousPosition.xy/vPreviousPosition.w)*0.5+0.5;
-vec2 velocity=abs(a-b);
-velocity=vec2(pow(velocity.x,1.0/3.0),pow(velocity.y,1.0/3.0))*sign(a-b)*0.5+0.5;
-gl_FragData[VELOCITY_INDEX]=vec4(velocity,0.0,1.0);
-#endif
-#ifdef REFLECTIVITY
-#ifdef HAS_SPECULAR
-
-vec4 reflectivity=texture2D(reflectivitySampler,vReflectivityUV);
-#elif HAS_REFLECTIVITY
-
-vec4 reflectivity=vec4(texture2D(reflectivitySampler,vReflectivityUV).rgb,1.0);
-#else
-vec4 reflectivity=vec4(0.0,0.0,0.0,1.0);
-#endif
-gl_FragData[REFLECTIVITY_INDEX]=reflectivity;
-#endif
-}`;ze.a.ShadersStore.geometryPixelShader=ug;var hg=`precision highp float;
-precision highp int;
-#include<bonesDeclaration>
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-#include<instancesDeclaration>
-attribute vec3 position;
-attribute vec3 normal;
-#ifdef NEED_UV
-varying vec2 vUV;
-#ifdef ALPHATEST
-uniform mat4 diffuseMatrix;
-#endif
-#ifdef BUMP
-uniform mat4 bumpMatrix;
-varying vec2 vBumpUV;
-#endif
-#ifdef REFLECTIVITY
-uniform mat4 reflectivityMatrix;
-varying vec2 vReflectivityUV;
-#endif
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#endif
-
-uniform mat4 viewProjection;
-uniform mat4 view;
-#ifdef BUMP
-varying mat4 vWorldView;
-#endif
-#ifdef BUMP
-varying vec3 vNormalW;
-#else
-varying vec3 vNormalV;
-#endif
-varying vec4 vViewPos;
-#if defined(POSITION) || defined(BUMP)
-varying vec3 vPositionW;
-#endif
-#ifdef VELOCITY
-uniform mat4 previousWorld;
-uniform mat4 previousViewProjection;
-#ifdef BONES_VELOCITY_ENABLED
-#if NUM_BONE_INFLUENCERS>0
-uniform mat4 mPreviousBones[BonesPerMesh];
-#endif
-#endif
-varying vec4 vCurrentPosition;
-varying vec4 vPreviousPosition;
-#endif
-void main(void)
-{
-vec3 positionUpdated=position;
-vec3 normalUpdated=normal;
-#ifdef UV1
-vec2 uvUpdated=uv;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-#include<instancesVertex>
-#if defined(VELOCITY) && !defined(BONES_VELOCITY_ENABLED)
-
-vCurrentPosition=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-vPreviousPosition=previousViewProjection*previousWorld*vec4(positionUpdated,1.0);
-#endif
-#include<bonesVertex>
-vec4 pos=vec4(finalWorld*vec4(positionUpdated,1.0));
-#ifdef BUMP
-vWorldView=view*finalWorld;
-vNormalW=normalUpdated;
-#else
-vNormalV=normalize(vec3((view*finalWorld)*vec4(normalUpdated,0.0)));
-#endif
-vViewPos=view*pos;
-#if defined(VELOCITY) && defined(BONES_VELOCITY_ENABLED)
-vCurrentPosition=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-#if NUM_BONE_INFLUENCERS>0
-mat4 previousInfluence;
-previousInfluence=mPreviousBones[int(matricesIndices[0])]*matricesWeights[0];
-#if NUM_BONE_INFLUENCERS>1
-previousInfluence+=mPreviousBones[int(matricesIndices[1])]*matricesWeights[1];
-#endif
-#if NUM_BONE_INFLUENCERS>2
-previousInfluence+=mPreviousBones[int(matricesIndices[2])]*matricesWeights[2];
-#endif
-#if NUM_BONE_INFLUENCERS>3
-previousInfluence+=mPreviousBones[int(matricesIndices[3])]*matricesWeights[3];
-#endif
-#if NUM_BONE_INFLUENCERS>4
-previousInfluence+=mPreviousBones[int(matricesIndicesExtra[0])]*matricesWeightsExtra[0];
-#endif
-#if NUM_BONE_INFLUENCERS>5
-previousInfluence+=mPreviousBones[int(matricesIndicesExtra[1])]*matricesWeightsExtra[1];
-#endif
-#if NUM_BONE_INFLUENCERS>6
-previousInfluence+=mPreviousBones[int(matricesIndicesExtra[2])]*matricesWeightsExtra[2];
-#endif
-#if NUM_BONE_INFLUENCERS>7
-previousInfluence+=mPreviousBones[int(matricesIndicesExtra[3])]*matricesWeightsExtra[3];
-#endif
-vPreviousPosition=previousViewProjection*previousWorld*previousInfluence*vec4(positionUpdated,1.0);
-#else
-vPreviousPosition=previousViewProjection*previousWorld*vec4(positionUpdated,1.0);
-#endif
-#endif
-#if defined(POSITION) || defined(BUMP)
-vPositionW=pos.xyz/pos.w;
-#endif
-gl_Position=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-#ifdef NEED_UV
-#ifdef UV1
-#ifdef ALPHATEST
-vUV=vec2(diffuseMatrix*vec4(uvUpdated,1.0,0.0));
-#else
-vUV=uv;
-#endif
-#ifdef BUMP
-vBumpUV=vec2(bumpMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef REFLECTIVITY
-vReflectivityUV=vec2(reflectivityMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#endif
-#ifdef UV2
-#ifdef ALPHATEST
-vUV=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-#else
-vUV=uv2;
-#endif
-#ifdef BUMP
-vBumpUV=vec2(bumpMatrix*vec4(uv2,1.0,0.0));
-#endif
-#ifdef REFLECTIVITY
-vReflectivityUV=vec2(reflectivityMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-#endif
-#include<bumpVertex>
-}
-`;ze.a.ShadersStore.geometryVertexShader=hg;var li=function(){function r(t,e){e===void 0&&(e=1),this._previousTransformationMatrices={},this._previousBonesTransformationMatrices={},this.excludedSkinnedMeshesFromVelocity=[],this.renderTransparentMeshes=!0,this._resizeObserver=null,this._enablePosition=!1,this._enableVelocity=!1,this._enableReflectivity=!1,this._positionIndex=-1,this._velocityIndex=-1,this._reflectivityIndex=-1,this._depthNormalIndex=-1,this._linkedWithPrePass=!1,this._scene=t,this._ratio=e,r._SceneComponentInitialization(this._scene),this._createRenderTargets()}return r.prototype._linkPrePassRenderer=function(t){this._linkedWithPrePass=!0,this._prePassRenderer=t,this._multiRenderTarget&&(this._multiRenderTarget.onClearObservable.clear(),this._multiRenderTarget.onClearObservable.add(function(e){}))},r.prototype._unlinkPrePassRenderer=function(){this._linkedWithPrePass=!1,this._createRenderTargets()},r.prototype._resetLayout=function(){this._enablePosition=!1,this._enableReflectivity=!1,this._enableVelocity=!1,this._attachments=[]},r.prototype._forceTextureType=function(t,e){t===r.POSITION_TEXTURE_TYPE?(this._positionIndex=e,this._enablePosition=!0):t===r.VELOCITY_TEXTURE_TYPE?(this._velocityIndex=e,this._enableVelocity=!0):t===r.REFLECTIVITY_TEXTURE_TYPE?(this._reflectivityIndex=e,this._enableReflectivity=!0):t===r.DEPTHNORMAL_TEXTURE_TYPE&&(this._depthNormalIndex=e)},r.prototype._setAttachments=function(t){this._attachments=t},r.prototype._linkInternalTexture=function(t){this._multiRenderTarget._texture=t},Object.defineProperty(r.prototype,"renderList",{get:function(){return this._multiRenderTarget.renderList},set:function(t){this._multiRenderTarget.renderList=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"isSupported",{get:function(){return this._multiRenderTarget.isSupported},enumerable:!1,configurable:!0}),r.prototype.getTextureIndex=function(t){switch(t){case r.POSITION_TEXTURE_TYPE:return this._positionIndex;case r.VELOCITY_TEXTURE_TYPE:return this._velocityIndex;case r.REFLECTIVITY_TEXTURE_TYPE:return this._reflectivityIndex;default:return-1}},Object.defineProperty(r.prototype,"enablePosition",{get:function(){return this._enablePosition},set:function(t){this._enablePosition=t,this._linkedWithPrePass||(this.dispose(),this._createRenderTargets())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"enableVelocity",{get:function(){return this._enableVelocity},set:function(t){this._enableVelocity=t,t||(this._previousTransformationMatrices={}),this._linkedWithPrePass||(this.dispose(),this._createRenderTargets())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"enableReflectivity",{get:function(){return this._enableReflectivity},set:function(t){this._enableReflectivity=t,this._linkedWithPrePass||(this.dispose(),this._createRenderTargets())},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"scene",{get:function(){return this._scene},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"ratio",{get:function(){return this._ratio},enumerable:!1,configurable:!0}),r.prototype.isReady=function(t,e){var n=t.getMaterial();if(n&&n.disableDepthWrite)return!1;var i=[],o=[Oe.b.PositionKind,Oe.b.NormalKind],a=t.getMesh();if(n){var s=!1;n.needAlphaTesting()&&(i.push("#define ALPHATEST"),s=!0),n.bumpTexture&&Ft.a.BumpTextureEnabled&&(i.push("#define BUMP"),i.push("#define BUMPDIRECTUV 0"),s=!0),this._enableReflectivity&&(n instanceof Ft.a&&n.specularTexture?(i.push("#define HAS_SPECULAR"),s=!0):n instanceof uo&&n.reflectivityTexture&&(i.push("#define HAS_REFLECTIVITY"),s=!0)),s&&(i.push("#define NEED_UV"),a.isVerticesDataPresent(Oe.b.UVKind)&&(o.push(Oe.b.UVKind),i.push("#define UV1")),a.isVerticesDataPresent(Oe.b.UV2Kind)&&(o.push(Oe.b.UV2Kind),i.push("#define UV2")))}this._linkedWithPrePass&&(i.push("#define PREPASS"),this._depthNormalIndex!==-1&&(i.push("#define DEPTHNORMAL_INDEX "+this._depthNormalIndex),i.push("#define PREPASS_DEPTHNORMAL"))),this._enablePosition&&(i.push("#define POSITION"),i.push("#define POSITION_INDEX "+this._positionIndex)),this._enableVelocity&&(i.push("#define VELOCITY"),i.push("#define VELOCITY_INDEX "+this._velocityIndex),this.excludedSkinnedMeshesFromVelocity.indexOf(a)===-1&&i.push("#define BONES_VELOCITY_ENABLED")),this._enableReflectivity&&(i.push("#define REFLECTIVITY"),i.push("#define REFLECTIVITY_INDEX "+this._reflectivityIndex)),a.useBones&&a.computeBonesUsingShaders?(o.push(Oe.b.MatricesIndicesKind),o.push(Oe.b.MatricesWeightsKind),a.numBoneInfluencers>4&&(o.push(Oe.b.MatricesIndicesExtraKind),o.push(Oe.b.MatricesWeightsExtraKind)),i.push("#define NUM_BONE_INFLUENCERS "+a.numBoneInfluencers),i.push("#define BonesPerMesh "+(a.skeleton?a.skeleton.bones.length+1:0))):i.push("#define NUM_BONE_INFLUENCERS 0");var d=a.morphTargetManager,p=0;d&&d.numInfluencers>0&&(p=d.numInfluencers,i.push("#define MORPHTARGETS"),i.push("#define NUM_MORPH_INFLUENCERS "+p),et.a.PrepareAttributesForMorphTargetsInfluencers(o,a,p)),e&&(i.push("#define INSTANCES"),et.a.PushAttributesForInstances(o),t.getRenderingMesh().hasThinInstances&&i.push("#define THIN_INSTANCES")),this._linkedWithPrePass?i.push("#define RENDER_TARGET_COUNT "+this._attachments.length):i.push("#define RENDER_TARGET_COUNT "+this._multiRenderTarget.textures.length);var b=i.join(`
-`);return this._cachedDefines!==b&&(this._cachedDefines=b,this._effect=this._scene.getEngine().createEffect("geometry",o,["world","mBones","viewProjection","diffuseMatrix","view","previousWorld","previousViewProjection","mPreviousBones","morphTargetInfluences","bumpMatrix","reflectivityMatrix","vTangentSpaceParams","vBumpInfos"],["diffuseSampler","bumpSampler","reflectivitySampler"],b,void 0,void 0,void 0,{buffersCount:this._multiRenderTarget.textures.length-1,maxSimultaneousMorphTargets:p})),this._effect.isReady()},r.prototype.getGBuffer=function(){return this._multiRenderTarget},Object.defineProperty(r.prototype,"samples",{get:function(){return this._multiRenderTarget.samples},set:function(t){this._multiRenderTarget.samples=t},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this._resizeObserver&&(this._scene.getEngine().onResizeObservable.remove(this._resizeObserver),this._resizeObserver=null),this.getGBuffer().dispose()},r.prototype._assignRenderTargetIndices=function(){var t=2;return this._enablePosition&&(this._positionIndex=t,t++),this._enableVelocity&&(this._velocityIndex=t,t++),this._enableReflectivity&&(this._reflectivityIndex=t,t++),t},r.prototype._createRenderTargets=function(){var t=this,e=this._scene.getEngine(),n=this._assignRenderTargetIndices();if(this._multiRenderTarget=new Js("gBuffer",{width:e.getRenderWidth()*this._ratio,height:e.getRenderHeight()*this._ratio},n,this._scene,{generateMipMaps:!1,generateDepthTexture:!0,defaultType:h.a.TEXTURETYPE_FLOAT}),this.isSupported){this._multiRenderTarget.wrapU=we.a.CLAMP_ADDRESSMODE,this._multiRenderTarget.wrapV=we.a.CLAMP_ADDRESSMODE,this._multiRenderTarget.refreshRate=1,this._multiRenderTarget.renderParticles=!1,this._multiRenderTarget.renderList=null,this._multiRenderTarget.onClearObservable.add(function(o){o.clear(new M.b(0,0,0,1),!0,!0,!0)}),this._resizeObserver=e.onResizeObservable.add(function(){t._multiRenderTarget&&t._multiRenderTarget.resize({width:e.getRenderWidth()*t._ratio,height:e.getRenderHeight()*t._ratio})});var i=function(o){var a=o.getRenderingMesh(),s=o.getEffectiveMesh(),d=t._scene,p=d.getEngine(),b=o.getMaterial();if(b){if(s._internalAbstractMeshDataInfo._isActiveIntermediate=!1,t._enableVelocity&&!t._previousTransformationMatrices[s.uniqueId]&&(t._previousTransformationMatrices[s.uniqueId]={world:u.a.Identity(),viewProjection:d.getTransformMatrix()},a.skeleton)){var P=a.skeleton.getTransformMatrices(a);t._previousBonesTransformationMatrices[a.uniqueId]=t._copyBonesTransformationMatrices(P,new Float32Array(P.length))}var O=a._getInstancesRenderList(o._id,!!o.getReplacementMesh());if(!O.mustReturn){var B=p.getCaps().instancedArrays&&(O.visibleInstances[o._id]!==null||a.hasThinInstances),F=s.getWorldMatrix();if(t.isReady(o,B)){if(p.enableEffect(t._effect),a._bind(o,t._effect,b.fillMode),t._effect.setMatrix("viewProjection",d.getTransformMatrix()),t._effect.setMatrix("view",d.getViewMatrix()),b){var z,J=s._instanceDataStorage;if(J.isFrozen||!b.backFaceCulling&&b.overrideMaterialSideOrientation===null)z=J.sideOrientation;else{var ie=s._getWorldMatrixDeterminant();(z=b.overrideMaterialSideOrientation)==null&&(z=b.sideOrientation),ie<0&&(z=z===Ht.a.ClockWiseSideOrientation?Ht.a.CounterClockWiseSideOrientation:Ht.a.ClockWiseSideOrientation)}if(b._preBind(t._effect,z),b.needAlphaTesting()){var se=b.getAlphaTestTexture();se&&(t._effect.setTexture("diffuseSampler",se),t._effect.setMatrix("diffuseMatrix",se.getTextureMatrix()))}b.bumpTexture&&d.getEngine().getCaps().standardDerivatives&&Ft.a.BumpTextureEnabled&&(t._effect.setFloat3("vBumpInfos",b.bumpTexture.coordinatesIndex,1/b.bumpTexture.level,b.parallaxScaleBias),t._effect.setMatrix("bumpMatrix",b.bumpTexture.getTextureMatrix()),t._effect.setTexture("bumpSampler",b.bumpTexture),t._effect.setFloat2("vTangentSpaceParams",b.invertNormalMapX?-1:1,b.invertNormalMapY?-1:1)),t._enableReflectivity&&(b instanceof Ft.a&&b.specularTexture?(t._effect.setMatrix("reflectivityMatrix",b.specularTexture.getTextureMatrix()),t._effect.setTexture("reflectivitySampler",b.specularTexture)):b instanceof uo&&b.reflectivityTexture&&(t._effect.setMatrix("reflectivityMatrix",b.reflectivityTexture.getTextureMatrix()),t._effect.setTexture("reflectivitySampler",b.reflectivityTexture)))}a.useBones&&a.computeBonesUsingShaders&&a.skeleton&&(t._effect.setMatrices("mBones",a.skeleton.getTransformMatrices(a)),t._enableVelocity&&t._effect.setMatrices("mPreviousBones",t._previousBonesTransformationMatrices[a.uniqueId])),et.a.BindMorphTargetParameters(a,t._effect),t._enableVelocity&&(t._effect.setMatrix("previousWorld",t._previousTransformationMatrices[s.uniqueId].world),t._effect.setMatrix("previousViewProjection",t._previousTransformationMatrices[s.uniqueId].viewProjection)),a._processRendering(s,o,t._effect,b.fillMode,O,B,function(ce,ue){return t._effect.setMatrix("world",ue)})}t._enableVelocity&&(t._previousTransformationMatrices[s.uniqueId].world=F.clone(),t._previousTransformationMatrices[s.uniqueId].viewProjection=t._scene.getTransformMatrix().clone(),a.skeleton&&t._copyBonesTransformationMatrices(a.skeleton.getTransformMatrices(a),t._previousBonesTransformationMatrices[s.uniqueId]))}}};this._multiRenderTarget.customRenderFunction=function(o,a,s,d){var p;if(t._linkedWithPrePass){if(!t._prePassRenderer.enabled)return;t._scene.getEngine().bindAttachments(t._attachments)}if(d.length){for(e.setColorWrite(!1),p=0;p<d.length;p++)i(d.data[p]);e.setColorWrite(!0)}for(p=0;p<o.length;p++)i(o.data[p]);for(p=0;p<a.length;p++)i(a.data[p]);if(t.renderTransparentMeshes)for(p=0;p<s.length;p++)i(s.data[p])}}},r.prototype._copyBonesTransformationMatrices=function(t,e){for(var n=0;n<t.length;n++)e[n]=t[n];return e},r.DEPTHNORMAL_TEXTURE_TYPE=0,r.POSITION_TEXTURE_TYPE=1,r.VELOCITY_TEXTURE_TYPE=2,r.REFLECTIVITY_TEXTURE_TYPE=3,r._SceneComponentInitialization=function(t){throw An.a.WarnImport("GeometryBufferRendererSceneComponent")},r}(),dg=function(){this.enabled=!1,this.name="motionBlur",this.texturesRequired=[h.a.PREPASS_VELOCITY_TEXTURE_TYPE]};Object.defineProperty(_e.a.prototype,"geometryBufferRenderer",{get:function(){this._geometryBufferRenderer},set:function(r){r&&r.isSupported&&(this._geometryBufferRenderer=r)},enumerable:!0,configurable:!0}),_e.a.prototype.enableGeometryBufferRenderer=function(r){return r===void 0&&(r=1),this._geometryBufferRenderer||(this._geometryBufferRenderer=new li(this,r),this._geometryBufferRenderer.isSupported||(this._geometryBufferRenderer=null)),this._geometryBufferRenderer},_e.a.prototype.disableGeometryBufferRenderer=function(){this._geometryBufferRenderer&&(this._geometryBufferRenderer.dispose(),this._geometryBufferRenderer=null)};var Ud=function(){function r(t){this.name=at.a.NAME_GEOMETRYBUFFERRENDERER,this.scene=t}return r.prototype.register=function(){this.scene._gatherRenderTargetsStage.registerStep(at.a.STEP_GATHERRENDERTARGETS_GEOMETRYBUFFERRENDERER,this,this._gatherRenderTargets)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){},r.prototype._gatherRenderTargets=function(t){this.scene._geometryBufferRenderer&&t.push(this.scene._geometryBufferRenderer.getGBuffer())},r}();li._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_GEOMETRYBUFFERRENDERER);t||(t=new Ud(r),r._addComponent(t))};var fg=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform float motionStrength;
-uniform float motionScale;
-uniform vec2 screenSize;
-#ifdef OBJECT_BASED
-uniform sampler2D velocitySampler;
-#else
-uniform sampler2D depthSampler;
-uniform mat4 inverseViewProjection;
-uniform mat4 prevViewProjection;
-#endif
-void main(void)
-{
-#ifdef GEOMETRY_SUPPORTED
-#ifdef OBJECT_BASED
-vec2 texelSize=1.0/screenSize;
-vec2 velocityColor=texture2D(velocitySampler,vUV).rg*2.0-1.0;
-vec2 velocity=vec2(pow(velocityColor.r,3.0),pow(velocityColor.g,3.0));
-velocity*=motionScale*motionStrength;
-float speed=length(velocity/texelSize);
-int samplesCount=int(clamp(speed,1.0,SAMPLES));
-velocity=normalize(velocity)*texelSize;
-float hlim=float(-samplesCount)*0.5+0.5;
-vec4 result=texture2D(textureSampler,vUV);
-for (int i=1; i<int(SAMPLES); ++i)
-{
-if (i>=samplesCount)
-break;
-vec2 offset=vUV+velocity*(hlim+float(i));
-result+=texture2D(textureSampler,offset);
-}
-gl_FragColor=result/float(samplesCount);
-gl_FragColor.a=1.0;
-#else
-vec2 texelSize=1.0/screenSize;
-float depth=texture2D(depthSampler,vUV).r;
-vec4 cpos=vec4(vUV*2.0-1.0,depth,1.0);
-cpos=cpos*inverseViewProjection;
-vec4 ppos=cpos*prevViewProjection;
-ppos.xyz/=ppos.w;
-ppos.xy=ppos.xy*0.5+0.5;
-vec2 velocity=(ppos.xy-vUV)*motionScale*motionStrength;
-float speed=length(velocity/texelSize);
-int nSamples=int(clamp(speed,1.0,SAMPLES));
-vec4 result=texture2D(textureSampler,vUV);
-for (int i=1; i<int(SAMPLES); ++i) {
-if (i>=nSamples)
-break;
-vec2 offset1=vUV+velocity*(float(i)/float(nSamples-1)-0.5);
-result+=texture2D(textureSampler,offset1);
-}
-gl_FragColor=result/float(nSamples);
-#endif
-#else
-gl_FragColor=texture2D(textureSampler,vUV);
-#endif
-}
-`;ze.a.ShadersStore.motionBlurPixelShader=fg;var jc=function(r){function t(e,n,i,o,a,s,d,p,b,P){p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT),b===void 0&&(b=!1),P===void 0&&(P=!0);var O=r.call(this,e,"motionBlur",["motionStrength","motionScale","screenSize","inverseViewProjection","prevViewProjection"],["velocitySampler"],i,o,a,s,d,`#define GEOMETRY_SUPPORTED
-#define SAMPLES 64.0
-#define OBJECT_BASED`,p,void 0,null,b)||this;return O.motionStrength=1,O._motionBlurSamples=32,O._isObjectBased=!0,O._forceGeometryBuffer=!1,O._geometryBufferRenderer=null,O._prePassRenderer=null,O._invViewProjection=null,O._previousViewProjection=null,O._forceGeometryBuffer=P,O._forceGeometryBuffer?(O._geometryBufferRenderer=n.enableGeometryBufferRenderer(),O._geometryBufferRenderer&&(O._geometryBufferRenderer.enableVelocity=!0)):(O._prePassRenderer=n.enablePrePassRenderer(),O._prePassRenderer&&(O._prePassRenderer.markAsDirty(),O._prePassEffectConfiguration=new dg)),O._applyMode(),O}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"motionBlurSamples",{get:function(){return this._motionBlurSamples},set:function(e){this._motionBlurSamples=e,this._updateEffect()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"isObjectBased",{get:function(){return this._isObjectBased},set:function(e){this._isObjectBased!==e&&(this._isObjectBased=e,this._applyMode())},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"MotionBlurPostProcess"},t.prototype.excludeSkinnedMesh=function(e){if(e.skeleton){var n=void 0;if(this._geometryBufferRenderer)n=this._geometryBufferRenderer.excludedSkinnedMeshesFromVelocity;else{if(!this._prePassRenderer)return;n=this._prePassRenderer.excludedSkinnedMesh}n.push(e)}},t.prototype.removeExcludedSkinnedMesh=function(e){if(e.skeleton){var n=void 0;if(this._geometryBufferRenderer)n=this._geometryBufferRenderer.excludedSkinnedMeshesFromVelocity;else{if(!this._prePassRenderer)return;n=this._prePassRenderer.excludedSkinnedMesh}var i=n.indexOf(e);i!==-1&&n.splice(i,1)}},t.prototype.dispose=function(e){this._geometryBufferRenderer&&(this._geometryBufferRenderer._previousTransformationMatrices={},this._geometryBufferRenderer._previousBonesTransformationMatrices={},this._geometryBufferRenderer.excludedSkinnedMeshesFromVelocity=[]),r.prototype.dispose.call(this,e)},t.prototype._applyMode=function(){var e=this;if(!this._geometryBufferRenderer&&!this._prePassRenderer)return l.a.Warn("Multiple Render Target support needed to compute object based motion blur"),this.updateEffect();this._updateEffect(),this._invViewProjection=null,this._previousViewProjection=null,this.isObjectBased?(this._prePassRenderer&&this._prePassEffectConfiguration&&(this._prePassEffectConfiguration.texturesRequired[0]=h.a.PREPASS_VELOCITY_TEXTURE_TYPE),this.onApply=function(n){return e._onApplyObjectBased(n)}):(this._invViewProjection=u.a.Identity(),this._previousViewProjection=u.a.Identity(),this._prePassRenderer&&this._prePassEffectConfiguration&&(this._prePassEffectConfiguration.texturesRequired[0]=h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE),this.onApply=function(n){return e._onApplyScreenBased(n)})},t.prototype._onApplyObjectBased=function(e){if(e.setVector2("screenSize",new u.d(this.width,this.height)),e.setFloat("motionScale",this._scene.getAnimationRatio()),e.setFloat("motionStrength",this.motionStrength),this._geometryBufferRenderer){var n=this._geometryBufferRenderer.getTextureIndex(li.VELOCITY_TEXTURE_TYPE);e.setTexture("velocitySampler",this._geometryBufferRenderer.getGBuffer().textures[n])}else this._prePassRenderer&&(n=this._prePassRenderer.getIndex(h.a.PREPASS_VELOCITY_TEXTURE_TYPE),e.setTexture("velocitySampler",this._prePassRenderer.prePassRT.textures[n]))},t.prototype._onApplyScreenBased=function(e){var n=this._scene.getProjectionMatrix().multiply(this._scene.getViewMatrix());if(n.invertToRef(this._invViewProjection),e.setMatrix("inverseViewProjection",this._invViewProjection),e.setMatrix("prevViewProjection",this._previousViewProjection),this._previousViewProjection=n,e.setVector2("screenSize",new u.d(this.width,this.height)),e.setFloat("motionScale",this._scene.getAnimationRatio()),e.setFloat("motionStrength",this.motionStrength),this._geometryBufferRenderer){var i=this._geometryBufferRenderer.getTextureIndex(li.DEPTHNORMAL_TEXTURE_TYPE);e.setTexture("depthSampler",this._geometryBufferRenderer.getGBuffer().textures[i])}else this._prePassRenderer&&(i=this._prePassRenderer.getIndex(h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE),e.setTexture("depthSampler",this._prePassRenderer.prePassRT.textures[i]))},t.prototype._updateEffect=function(){if(this._geometryBufferRenderer||this._prePassRenderer){var e=["#define GEOMETRY_SUPPORTED","#define SAMPLES "+this._motionBlurSamples.toFixed(1),this._isObjectBased?"#define OBJECT_BASED":"#define SCREEN_BASED"];this.updateEffect(e.join(`
-`))}},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,i,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable,e.textureType,!1)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"motionStrength",void 0),Object(c.c)([Object(L.c)()],t.prototype,"motionBlurSamples",null),Object(c.c)([Object(L.c)()],t.prototype,"isObjectBased",null),t}(_t);R.a.RegisteredTypes["BABYLON.MotionBlurPostProcess"]=jc;var pg=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform sampler2D refractionSampler;
-
-uniform vec3 baseColor;
-uniform float depth;
-uniform float colorLevel;
-void main() {
-float ref=1.0-texture2D(refractionSampler,vUV).r;
-vec2 uv=vUV-vec2(0.5);
-vec2 offset=uv*depth*ref;
-vec3 sourceColor=texture2D(textureSampler,vUV-offset).rgb;
-gl_FragColor=vec4(sourceColor+sourceColor*ref*colorLevel,1.0);
-}`;ze.a.ShadersStore.refractionPixelShader=pg;var Vd=function(r){function t(e,n,i,o,a,s,d,p,b,P){var O=r.call(this,e,"refraction",["baseColor","depth","colorLevel"],["refractionSampler"],s,d,p,b,P)||this;return O._ownRefractionTexture=!0,O.color=i,O.depth=o,O.colorLevel=a,O.refractionTextureUrl=n,O.onActivateObservable.add(function(B){O._refTexture=O._refTexture||new we.a(n,B.getScene())}),O.onApplyObservable.add(function(B){B.setColor3("baseColor",O.color),B.setFloat("depth",O.depth),B.setFloat("colorLevel",O.colorLevel),B.setTexture("refractionSampler",O._refTexture)}),O}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"refractionTexture",{get:function(){return this._refTexture},set:function(e){this._refTexture&&this._ownRefractionTexture&&this._refTexture.dispose(),this._refTexture=e,this._ownRefractionTexture=!1},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"RefractionPostProcess"},t.prototype.dispose=function(e){this._refTexture&&this._ownRefractionTexture&&(this._refTexture.dispose(),this._refTexture=null),r.prototype.dispose.call(this,e)},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.refractionTextureUrl,e.color,e.depth,e.colorLevel,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.reusable)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"color",void 0),Object(c.c)([Object(L.c)()],t.prototype,"depth",void 0),Object(c.c)([Object(L.c)()],t.prototype,"colorLevel",void 0),Object(c.c)([Object(L.c)()],t.prototype,"refractionTextureUrl",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.RefractionPostProcess"]=Vd;var _g=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform vec2 screenSize;
-uniform vec2 sharpnessAmounts;
-void main(void)
-{
-vec2 onePixel=vec2(1.0,1.0)/screenSize;
-vec4 color=texture2D(textureSampler,vUV);
-vec4 edgeDetection=texture2D(textureSampler,vUV+onePixel*vec2(0,-1)) +
-texture2D(textureSampler,vUV+onePixel*vec2(-1,0)) +
-texture2D(textureSampler,vUV+onePixel*vec2(1,0)) +
-texture2D(textureSampler,vUV+onePixel*vec2(0,1)) -
-color*4.0;
-gl_FragColor=max(vec4(color.rgb*sharpnessAmounts.y,color.a)-(sharpnessAmounts.x*vec4(edgeDetection.rgb,0)),0.);
-}`;ze.a.ShadersStore.sharpenPixelShader=_g;var Hc=function(r){function t(e,n,i,o,a,s,d,p){d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT),p===void 0&&(p=!1);var b=r.call(this,e,"sharpen",["sharpnessAmounts","screenSize"],null,n,i,o,a,s,null,d,void 0,null,p)||this;return b.colorAmount=1,b.edgeAmount=.3,b.onApply=function(P){P.setFloat2("screenSize",b.width,b.height),P.setFloat2("sharpnessAmounts",b.edgeAmount,b.colorAmount)},b}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"SharpenPostProcess"},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.textureType,e.reusable)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"colorAmount",void 0),Object(c.c)([Object(L.c)()],t.prototype,"edgeAmount",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.SharpenPostProcess"]=Hc;var Vr=function(){function r(t,e){this.engine=t,this._name=e,this._renderEffects={},this._renderEffectsForIsolatedPass=new Array,this._cameras=[]}return Object.defineProperty(r.prototype,"name",{get:function(){return this._name},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"cameras",{get:function(){return this._cameras},enumerable:!1,configurable:!0}),r.prototype.getClassName=function(){return"PostProcessRenderPipeline"},Object.defineProperty(r.prototype,"isSupported",{get:function(){for(var t in this._renderEffects)if(this._renderEffects.hasOwnProperty(t)&&!this._renderEffects[t].isSupported)return!1;return!0},enumerable:!1,configurable:!0}),r.prototype.addEffect=function(t){this._renderEffects[t._name]=t},r.prototype._rebuild=function(){},r.prototype._enableEffect=function(t,e){var n=this._renderEffects[t];n&&n._enable(Xe.b.MakeArray(e||this._cameras))},r.prototype._disableEffect=function(t,e){var n=this._renderEffects[t];n&&n._disable(Xe.b.MakeArray(e||this._cameras))},r.prototype._attachCameras=function(t,e){var n=Xe.b.MakeArray(t||this._cameras);if(n){var i,o=[];for(i=0;i<n.length;i++){var a=n[i];if(a){var s=a.name;this._cameras.indexOf(a)===-1?this._cameras[s]=a:e&&o.push(i)}}for(i=0;i<o.length;i++)t.splice(o[i],1);for(var d in this._renderEffects)this._renderEffects.hasOwnProperty(d)&&this._renderEffects[d]._attachCameras(n)}},r.prototype._detachCameras=function(t){var e=Xe.b.MakeArray(t||this._cameras);if(e){for(var n in this._renderEffects)this._renderEffects.hasOwnProperty(n)&&this._renderEffects[n]._detachCameras(e);for(var i=0;i<e.length;i++)this._cameras.splice(this._cameras.indexOf(e[i]),1)}},r.prototype._update=function(){for(var t in this._renderEffects)this._renderEffects.hasOwnProperty(t)&&this._renderEffects[t]._update();for(var e=0;e<this._cameras.length;e++)if(this._cameras[e]){var n=this._cameras[e].name;this._renderEffectsForIsolatedPass[n]&&this._renderEffectsForIsolatedPass[n]._update()}},r.prototype._reset=function(){this._renderEffects={},this._renderEffectsForIsolatedPass=new Array},r.prototype._enableMSAAOnFirstPostProcess=function(t){if(this.engine.webGLVersion===1)return!1;var e=Object.keys(this._renderEffects);if(e.length>0){var n=this._renderEffects[e[0]].getPostProcesses();n&&(n[0].samples=t)}return!0},r.prototype.setPrePassRenderer=function(t){return!1},r.prototype.dispose=function(){},Object(c.c)([Object(L.c)()],r.prototype,"_name",void 0),r}(),kd=function(){function r(){this._renderPipelines={}}return Object.defineProperty(r.prototype,"supportedPipelines",{get:function(){var t=[];for(var e in this._renderPipelines)if(this._renderPipelines.hasOwnProperty(e)){var n=this._renderPipelines[e];n.isSupported&&t.push(n)}return t},enumerable:!1,configurable:!0}),r.prototype.addPipeline=function(t){this._renderPipelines[t._name]=t},r.prototype.attachCamerasToRenderPipeline=function(t,e,n){n===void 0&&(n=!1);var i=this._renderPipelines[t];i&&i._attachCameras(e,n)},r.prototype.detachCamerasFromRenderPipeline=function(t,e){var n=this._renderPipelines[t];n&&n._detachCameras(e)},r.prototype.enableEffectInPipeline=function(t,e,n){var i=this._renderPipelines[t];i&&i._enableEffect(e,n)},r.prototype.disableEffectInPipeline=function(t,e,n){var i=this._renderPipelines[t];i&&i._disableEffect(e,n)},r.prototype.update=function(){for(var t in this._renderPipelines)if(this._renderPipelines.hasOwnProperty(t)){var e=this._renderPipelines[t];e.isSupported?e._update():(e.dispose(),delete this._renderPipelines[t])}},r.prototype._rebuild=function(){for(var t in this._renderPipelines)this._renderPipelines.hasOwnProperty(t)&&this._renderPipelines[t]._rebuild()},r.prototype.dispose=function(){for(var t in this._renderPipelines)this._renderPipelines.hasOwnProperty(t)&&this._renderPipelines[t].dispose()},r}();Object.defineProperty(_e.a.prototype,"postProcessRenderPipelineManager",{get:function(){if(!this._postProcessRenderPipelineManager){var r=this._getComponent(at.a.NAME_POSTPROCESSRENDERPIPELINEMANAGER);r||(r=new Gd(this),this._addComponent(r)),this._postProcessRenderPipelineManager=new kd}return this._postProcessRenderPipelineManager},enumerable:!0,configurable:!0});var Gd=function(){function r(t){this.name=at.a.NAME_POSTPROCESSRENDERPIPELINEMANAGER,this.scene=t}return r.prototype.register=function(){this.scene._gatherRenderTargetsStage.registerStep(at.a.STEP_GATHERRENDERTARGETS_POSTPROCESSRENDERPIPELINEMANAGER,this,this._gatherRenderTargets)},r.prototype.rebuild=function(){this.scene._postProcessRenderPipelineManager&&this.scene._postProcessRenderPipelineManager._rebuild()},r.prototype.dispose=function(){this.scene._postProcessRenderPipelineManager&&this.scene._postProcessRenderPipelineManager.dispose()},r.prototype._gatherRenderTargets=function(){this.scene._postProcessRenderPipelineManager&&this.scene._postProcessRenderPipelineManager.update()},r}(),zd=function(r){function t(e,n,i,o,a){e===void 0&&(e=""),n===void 0&&(n=!0),i===void 0&&(i=te.a.LastCreatedScene),a===void 0&&(a=!0);var s=r.call(this,i.getEngine(),e)||this;s._camerasToBeAttached=[],s.SharpenPostProcessId="SharpenPostProcessEffect",s.ImageProcessingPostProcessId="ImageProcessingPostProcessEffect",s.FxaaPostProcessId="FxaaPostProcessEffect",s.ChromaticAberrationPostProcessId="ChromaticAberrationPostProcessEffect",s.GrainPostProcessId="GrainPostProcessEffect",s._glowLayer=null,s.animations=[],s._imageProcessingConfigurationObserver=null,s._sharpenEnabled=!1,s._bloomEnabled=!1,s._depthOfFieldEnabled=!1,s._depthOfFieldBlurLevel=sr.Low,s._fxaaEnabled=!1,s._imageProcessingEnabled=!0,s._bloomScale=.5,s._chromaticAberrationEnabled=!1,s._grainEnabled=!1,s._buildAllowed=!0,s.onBuildObservable=new C.c,s._resizeObserver=null,s._hardwareScaleLevel=1,s._bloomKernel=64,s._bloomWeight=.15,s._bloomThreshold=.9,s._samples=1,s._hasCleared=!1,s._prevPostProcess=null,s._prevPrevPostProcess=null,s._depthOfFieldSceneObserver=null,s._cameras=o||i.cameras,s._cameras=s._cameras.slice(),s._camerasToBeAttached=s._cameras.slice(),s._buildAllowed=a,s._scene=i;var d=s._scene.getEngine().getCaps();s._hdr=n&&(d.textureHalfFloatRender||d.textureFloatRender),s._hdr?d.textureHalfFloatRender?s._defaultPipelineTextureType=h.a.TEXTURETYPE_HALF_FLOAT:d.textureFloatRender&&(s._defaultPipelineTextureType=h.a.TEXTURETYPE_FLOAT):s._defaultPipelineTextureType=h.a.TEXTURETYPE_UNSIGNED_INT,i.postProcessRenderPipelineManager.addPipeline(s);var p=s._scene.getEngine();return s.sharpen=new Hc("sharpen",1,null,we.a.BILINEAR_SAMPLINGMODE,p,!1,s._defaultPipelineTextureType,!0),s._sharpenEffect=new Rt(p,s.SharpenPostProcessId,function(){return s.sharpen},!0),s.depthOfField=new Gc(s._scene,null,s._depthOfFieldBlurLevel,s._defaultPipelineTextureType,!0),s.bloom=new Uc(s._scene,s._bloomScale,s._bloomWeight,s.bloomKernel,s._defaultPipelineTextureType,!0),s.chromaticAberration=new Vc("ChromaticAberration",p.getRenderWidth(),p.getRenderHeight(),1,null,we.a.BILINEAR_SAMPLINGMODE,p,!1,s._defaultPipelineTextureType,!0),s._chromaticAberrationEffect=new Rt(p,s.ChromaticAberrationPostProcessId,function(){return s.chromaticAberration},!0),s.grain=new zc("Grain",1,null,we.a.BILINEAR_SAMPLINGMODE,p,!1,s._defaultPipelineTextureType,!0),s._grainEffect=new Rt(p,s.GrainPostProcessId,function(){return s.grain},!0),s._resizeObserver=p.onResizeObservable.add(function(){s._hardwareScaleLevel=p.getHardwareScalingLevel(),s.bloomKernel=s.bloomKernel}),s._imageProcessingConfigurationObserver=s._scene.imageProcessingConfiguration.onUpdateParameters.add(function(){s.bloom._downscale._exposure=s._scene.imageProcessingConfiguration.exposure,s.imageProcessingEnabled!==s._scene.imageProcessingConfiguration.isEnabled&&(s._imageProcessingEnabled=s._scene.imageProcessingConfiguration.isEnabled,s._buildPipeline())}),s._buildPipeline(),s}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"scene",{get:function(){return this._scene},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"sharpenEnabled",{get:function(){return this._sharpenEnabled},set:function(e){this._sharpenEnabled!==e&&(this._sharpenEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"bloomKernel",{get:function(){return this._bloomKernel},set:function(e){this._bloomKernel=e,this.bloom.kernel=e/this._hardwareScaleLevel},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"bloomWeight",{get:function(){return this._bloomWeight},set:function(e){this._bloomWeight!==e&&(this.bloom.weight=e,this._bloomWeight=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"bloomThreshold",{get:function(){return this._bloomThreshold},set:function(e){this._bloomThreshold!==e&&(this.bloom.threshold=e,this._bloomThreshold=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"bloomScale",{get:function(){return this._bloomScale},set:function(e){this._bloomScale!==e&&(this._bloomScale=e,this._rebuildBloom(),this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"bloomEnabled",{get:function(){return this._bloomEnabled},set:function(e){this._bloomEnabled!==e&&(this._bloomEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),t.prototype._rebuildBloom=function(){var e=this.bloom;this.bloom=new Uc(this._scene,this.bloomScale,this._bloomWeight,this.bloomKernel,this._defaultPipelineTextureType,!1),this.bloom.threshold=e.threshold;for(var n=0;n<this._cameras.length;n++)e.disposeEffects(this._cameras[n])},Object.defineProperty(t.prototype,"depthOfFieldEnabled",{get:function(){return this._depthOfFieldEnabled},set:function(e){this._depthOfFieldEnabled!==e&&(this._depthOfFieldEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"depthOfFieldBlurLevel",{get:function(){return this._depthOfFieldBlurLevel},set:function(e){if(this._depthOfFieldBlurLevel!==e){this._depthOfFieldBlurLevel=e;var n=this.depthOfField;this.depthOfField=new Gc(this._scene,null,this._depthOfFieldBlurLevel,this._defaultPipelineTextureType,!1),this.depthOfField.focalLength=n.focalLength,this.depthOfField.focusDistance=n.focusDistance,this.depthOfField.fStop=n.fStop,this.depthOfField.lensSize=n.lensSize;for(var i=0;i<this._cameras.length;i++)n.disposeEffects(this._cameras[i]);this._buildPipeline()}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"fxaaEnabled",{get:function(){return this._fxaaEnabled},set:function(e){this._fxaaEnabled!==e&&(this._fxaaEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"samples",{get:function(){return this._samples},set:function(e){this._samples!==e&&(this._samples=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"imageProcessingEnabled",{get:function(){return this._imageProcessingEnabled},set:function(e){this._imageProcessingEnabled!==e&&(this._scene.imageProcessingConfiguration.isEnabled=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"glowLayerEnabled",{get:function(){return this._glowLayer!=null},set:function(e){e&&!this._glowLayer?this._glowLayer=new ra("",this._scene):!e&&this._glowLayer&&(this._glowLayer.dispose(),this._glowLayer=null)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"glowLayer",{get:function(){return this._glowLayer},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"chromaticAberrationEnabled",{get:function(){return this._chromaticAberrationEnabled},set:function(e){this._chromaticAberrationEnabled!==e&&(this._chromaticAberrationEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"grainEnabled",{get:function(){return this._grainEnabled},set:function(e){this._grainEnabled!==e&&(this._grainEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"DefaultRenderingPipeline"},t.prototype.prepare=function(){var e=this._buildAllowed;this._buildAllowed=!0,this._buildPipeline(),this._buildAllowed=e},t.prototype._setAutoClearAndTextureSharing=function(e,n){n===void 0&&(n=!1),this._hasCleared?e.autoClear=!1:(e.autoClear=!0,this._scene.autoClear=!1,this._hasCleared=!0),n||(this._prevPrevPostProcess?e.shareOutputWith(this._prevPrevPostProcess):e.useOwnOutput(),this._prevPostProcess&&(this._prevPrevPostProcess=this._prevPostProcess),this._prevPostProcess=e)},t.prototype._buildPipeline=function(){var e=this;if(this._buildAllowed){this._scene.autoClear=!0;var n=this._scene.getEngine();if(this._disposePostProcesses(),this._cameras!==null&&(this._scene.postProcessRenderPipelineManager.detachCamerasFromRenderPipeline(this._name,this._cameras),this._cameras=this._camerasToBeAttached.slice()),this._reset(),this._prevPostProcess=null,this._prevPrevPostProcess=null,this._hasCleared=!1,this.depthOfFieldEnabled){if(this._cameras.length>1){for(var i=0,o=this._cameras;i<o.length;i++){var a=o[i];(s=this._scene.enableDepthRenderer(a)).useOnlyInActiveCamera=!0}this._depthOfFieldSceneObserver=this._scene.onAfterRenderTargetsRenderObservable.add(function(d){e._cameras.indexOf(d.activeCamera)>-1&&(e.depthOfField.depthTexture=d.enableDepthRenderer(d.activeCamera).getDepthMap())})}else{this._scene.onAfterRenderTargetsRenderObservable.remove(this._depthOfFieldSceneObserver);var s=this._scene.enableDepthRenderer(this._cameras[0]);this.depthOfField.depthTexture=s.getDepthMap()}this.depthOfField._isReady()||this.depthOfField._updateEffects(),this.addEffect(this.depthOfField),this._setAutoClearAndTextureSharing(this.depthOfField._effects[0],!0)}else this._scene.onAfterRenderTargetsRenderObservable.remove(this._depthOfFieldSceneObserver);this.bloomEnabled&&(this.bloom._isReady()||this.bloom._updateEffects(),this.addEffect(this.bloom),this._setAutoClearAndTextureSharing(this.bloom._effects[0],!0)),this._imageProcessingEnabled&&(this.imageProcessing=new Go("imageProcessing",1,null,we.a.BILINEAR_SAMPLINGMODE,n,!1,this._defaultPipelineTextureType),this._hdr?(this.addEffect(new Rt(n,this.ImageProcessingPostProcessId,function(){return e.imageProcessing},!0)),this._setAutoClearAndTextureSharing(this.imageProcessing)):this._scene.imageProcessingConfiguration.applyByPostProcess=!1,this.cameras&&this.cameras.length!==0||(this._scene.imageProcessingConfiguration.applyByPostProcess=!1),this.imageProcessing.getEffect()||this.imageProcessing._updateParameters()),this.sharpenEnabled&&(this.sharpen.isReady()||this.sharpen.updateEffect(),this.addEffect(this._sharpenEffect),this._setAutoClearAndTextureSharing(this.sharpen)),this.grainEnabled&&(this.grain.isReady()||this.grain.updateEffect(),this.addEffect(this._grainEffect),this._setAutoClearAndTextureSharing(this.grain)),this.chromaticAberrationEnabled&&(this.chromaticAberration.isReady()||this.chromaticAberration.updateEffect(),this.addEffect(this._chromaticAberrationEffect),this._setAutoClearAndTextureSharing(this.chromaticAberration)),this.fxaaEnabled&&(this.fxaa=new Oo("fxaa",1,null,we.a.BILINEAR_SAMPLINGMODE,n,!1,this._defaultPipelineTextureType),this.addEffect(new Rt(n,this.FxaaPostProcessId,function(){return e.fxaa},!0)),this._setAutoClearAndTextureSharing(this.fxaa,!0)),this._cameras!==null&&this._scene.postProcessRenderPipelineManager.attachCamerasToRenderPipeline(this._name,this._cameras),this._scene.activeCameras&&this._scene.activeCameras.length>1&&(this._scene.autoClear=!0),!this._enableMSAAOnFirstPostProcess(this.samples)&&this.samples>1&&l.a.Warn("MSAA failed to enable, MSAA is only supported in browsers that support webGL >= 2.0"),this.onBuildObservable.notifyObservers(this)}},t.prototype._disposePostProcesses=function(e){e===void 0&&(e=!1);for(var n=0;n<this._cameras.length;n++){var i=this._cameras[n];this.imageProcessing&&this.imageProcessing.dispose(i),this.fxaa&&this.fxaa.dispose(i),e&&(this.sharpen&&this.sharpen.dispose(i),this.depthOfField&&(this._scene.onAfterRenderTargetsRenderObservable.remove(this._depthOfFieldSceneObserver),this.depthOfField.disposeEffects(i)),this.bloom&&this.bloom.disposeEffects(i),this.chromaticAberration&&this.chromaticAberration.dispose(i),this.grain&&this.grain.dispose(i),this._glowLayer&&this._glowLayer.dispose())}this.imageProcessing=null,this.fxaa=null,e&&(this.sharpen=null,this._sharpenEffect=null,this.depthOfField=null,this.bloom=null,this.chromaticAberration=null,this._chromaticAberrationEffect=null,this.grain=null,this._grainEffect=null,this._glowLayer=null)},t.prototype.addCamera=function(e){this._camerasToBeAttached.push(e),this._buildPipeline()},t.prototype.removeCamera=function(e){var n=this._camerasToBeAttached.indexOf(e);this._camerasToBeAttached.splice(n,1),this._buildPipeline()},t.prototype.dispose=function(){this.onBuildObservable.clear(),this._disposePostProcesses(!0),this._scene.postProcessRenderPipelineManager.detachCamerasFromRenderPipeline(this._name,this._cameras),this._scene.autoClear=!0,this._resizeObserver&&(this._scene.getEngine().onResizeObservable.remove(this._resizeObserver),this._resizeObserver=null),this._scene.imageProcessingConfiguration.onUpdateParameters.remove(this._imageProcessingConfigurationObserver),r.prototype.dispose.call(this)},t.prototype.serialize=function(){var e=L.a.Serialize(this);return e.customType="DefaultRenderingPipeline",e},t.Parse=function(e,n,i){return L.a.Parse(function(){return new t(e._name,e._name._hdr,n)},e,n,i)},Object(c.c)([Object(L.c)()],t.prototype,"sharpenEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"bloomKernel",null),Object(c.c)([Object(L.c)()],t.prototype,"_bloomWeight",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_bloomThreshold",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_hdr",void 0),Object(c.c)([Object(L.c)()],t.prototype,"bloomWeight",null),Object(c.c)([Object(L.c)()],t.prototype,"bloomThreshold",null),Object(c.c)([Object(L.c)()],t.prototype,"bloomScale",null),Object(c.c)([Object(L.c)()],t.prototype,"bloomEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"depthOfFieldEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"depthOfFieldBlurLevel",null),Object(c.c)([Object(L.c)()],t.prototype,"fxaaEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"samples",null),Object(c.c)([Object(L.c)()],t.prototype,"imageProcessingEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"glowLayerEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"chromaticAberrationEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"grainEnabled",null),t}(Vr);R.a.RegisteredTypes["BABYLON.DefaultRenderingPipeline"]=zd;var mg=`
-uniform sampler2D textureSampler;
-
-uniform float gain;
-uniform float threshold;
-uniform float screen_width;
-uniform float screen_height;
-
-varying vec2 vUV;
-
-vec4 highlightColor(vec4 color) {
-vec4 highlight=color;
-float luminance=dot(highlight.rgb,vec3(0.2125,0.7154,0.0721));
-float lum_threshold;
-if (threshold>1.0) { lum_threshold=0.94+0.01*threshold; }
-else { lum_threshold=0.5+0.44*threshold; }
-luminance=clamp((luminance-lum_threshold)*(1.0/(1.0-lum_threshold)),0.0,1.0);
-highlight*=luminance*gain;
-highlight.a=1.0;
-return highlight;
-}
-void main(void)
-{
-vec4 original=texture2D(textureSampler,vUV);
-
-if (gain == -1.0) {
-gl_FragColor=vec4(0.0,0.0,0.0,1.0);
-return;
-}
-float w=2.0/screen_width;
-float h=2.0/screen_height;
-float weight=1.0;
-
-vec4 blurred=vec4(0.0,0.0,0.0,0.0);
-#ifdef PENTAGON
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.84*w,0.43*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.48*w,-1.29*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.61*w,1.51*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.55*w,-0.74*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.71*w,-0.52*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.94*w,1.59*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.40*w,-1.87*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.62*w,1.16*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.09*w,0.25*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.46*w,-1.71*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.08*w,2.42*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.85*w,-1.89*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.89*w,0.16*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.29*w,1.88*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.40*w,-2.81*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.54*w,2.26*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.60*w,-0.61*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.31*w,-1.30*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.83*w,2.53*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.12*w,-2.48*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.60*w,1.11*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.82*w,0.99*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.50*w,-2.81*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.85*w,3.33*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.94*w,-1.92*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(3.27*w,-0.53*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.95*w,2.48*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.23*w,-3.04*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.17*w,2.05*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.97*w,-0.04*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.25*w,-2.00*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.31*w,3.08*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.94*w,-2.59*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(3.37*w,0.64*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-3.13*w,1.93*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.03*w,-3.65*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.60*w,3.17*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-3.14*w,-1.19*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(3.00*w,-1.19*h)));
-#else
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.85*w,0.36*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.52*w,-1.14*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.46*w,1.42*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.46*w,-0.83*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.79*w,-0.42*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.11*w,1.62*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.29*w,-2.07*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.69*w,1.39*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.28*w,0.12*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.65*w,-1.69*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.08*w,2.44*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.63*w,-1.90*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.55*w,0.31*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.13*w,1.52*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.56*w,-2.61*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.38*w,2.34*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.64*w,-0.81*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.53*w,-1.21*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.06*w,2.63*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.00*w,-2.69*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.59*w,1.32*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.82*w,0.78*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.57*w,-2.50*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(0.54*w,2.93*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.39*w,-1.81*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(3.01*w,-0.28*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.04*w,2.25*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.02*w,-3.05*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.09*w,2.25*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-3.07*w,-0.25*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.44*w,-1.90*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-0.52*w,3.05*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-1.68*w,-2.61*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(3.01*w,0.79*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.76*w,1.46*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.05*w,-2.94*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(1.21*w,2.88*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(-2.84*w,-1.30*h)));
-blurred+=highlightColor(texture2D(textureSampler,vUV+vec2(2.98*w,-0.96*h)));
-#endif
-blurred/=39.0;
-gl_FragColor=blurred;
-
-}`;ze.a.ShadersStore.lensHighlightsPixelShader=mg;var gg=`
-
-
-
-
-uniform sampler2D textureSampler;
-uniform sampler2D highlightsSampler;
-uniform sampler2D depthSampler;
-uniform sampler2D grainSampler;
-
-uniform float grain_amount;
-uniform bool blur_noise;
-uniform float screen_width;
-uniform float screen_height;
-uniform float distortion;
-uniform bool dof_enabled;
-
-uniform float screen_distance;
-uniform float aperture;
-uniform float darken;
-uniform float edge_blur;
-uniform bool highlights;
-
-uniform float near;
-uniform float far;
-
-varying vec2 vUV;
-
-#define PI 3.14159265
-#define TWOPI 6.28318530
-#define inverse_focal_length 0.1
-
-vec2 centered_screen_pos;
-vec2 distorted_coords;
-float radius2;
-float radius;
-
-vec2 rand(vec2 co)
-{
-float noise1=(fract(sin(dot(co,vec2(12.9898,78.233)))*43758.5453));
-float noise2=(fract(sin(dot(co,vec2(12.9898,78.233)*2.0))*43758.5453));
-return clamp(vec2(noise1,noise2),0.0,1.0);
-}
-
-vec2 getDistortedCoords(vec2 coords) {
-if (distortion == 0.0) { return coords; }
-vec2 direction=1.0*normalize(centered_screen_pos);
-vec2 dist_coords=vec2(0.5,0.5);
-dist_coords.x=0.5+direction.x*radius2*1.0;
-dist_coords.y=0.5+direction.y*radius2*1.0;
-float dist_amount=clamp(distortion*0.23,0.0,1.0);
-dist_coords=mix(coords,dist_coords,dist_amount);
-return dist_coords;
-}
-
-float sampleScreen(inout vec4 color,const in vec2 offset,const in float weight) {
-
-vec2 coords=distorted_coords;
-float angle=rand(coords*100.0).x*TWOPI;
-coords+=vec2(offset.x*cos(angle)-offset.y*sin(angle),offset.x*sin(angle)+offset.y*cos(angle));
-color+=texture2D(textureSampler,coords)*weight;
-return weight;
-}
-
-float getBlurLevel(float size) {
-return min(3.0,ceil(size/1.0));
-}
-
-vec4 getBlurColor(float size) {
-vec4 col=texture2D(textureSampler,distorted_coords);
-if (size == 0.0) { return col; }
-
-
-float blur_level=getBlurLevel(size);
-float w=(size/screen_width);
-float h=(size/screen_height);
-float total_weight=1.0;
-vec2 sample_coords;
-total_weight+=sampleScreen(col,vec2(-0.50*w,0.24*h),0.93);
-total_weight+=sampleScreen(col,vec2(0.30*w,-0.75*h),0.90);
-total_weight+=sampleScreen(col,vec2(0.36*w,0.96*h),0.87);
-total_weight+=sampleScreen(col,vec2(-1.08*w,-0.55*h),0.85);
-total_weight+=sampleScreen(col,vec2(1.33*w,-0.37*h),0.83);
-total_weight+=sampleScreen(col,vec2(-0.82*w,1.31*h),0.80);
-total_weight+=sampleScreen(col,vec2(-0.31*w,-1.67*h),0.78);
-total_weight+=sampleScreen(col,vec2(1.47*w,1.11*h),0.76);
-total_weight+=sampleScreen(col,vec2(-1.97*w,0.19*h),0.74);
-total_weight+=sampleScreen(col,vec2(1.42*w,-1.57*h),0.72);
-if (blur_level>1.0) {
-total_weight+=sampleScreen(col,vec2(0.01*w,2.25*h),0.70);
-total_weight+=sampleScreen(col,vec2(-1.62*w,-1.74*h),0.67);
-total_weight+=sampleScreen(col,vec2(2.49*w,0.20*h),0.65);
-total_weight+=sampleScreen(col,vec2(-2.07*w,1.61*h),0.63);
-total_weight+=sampleScreen(col,vec2(0.46*w,-2.70*h),0.61);
-total_weight+=sampleScreen(col,vec2(1.55*w,2.40*h),0.59);
-total_weight+=sampleScreen(col,vec2(-2.88*w,-0.75*h),0.56);
-total_weight+=sampleScreen(col,vec2(2.73*w,-1.44*h),0.54);
-total_weight+=sampleScreen(col,vec2(-1.08*w,3.02*h),0.52);
-total_weight+=sampleScreen(col,vec2(-1.28*w,-3.05*h),0.49);
-}
-if (blur_level>2.0) {
-total_weight+=sampleScreen(col,vec2(3.11*w,1.43*h),0.46);
-total_weight+=sampleScreen(col,vec2(-3.36*w,1.08*h),0.44);
-total_weight+=sampleScreen(col,vec2(1.80*w,-3.16*h),0.41);
-total_weight+=sampleScreen(col,vec2(0.83*w,3.65*h),0.38);
-total_weight+=sampleScreen(col,vec2(-3.16*w,-2.19*h),0.34);
-total_weight+=sampleScreen(col,vec2(3.92*w,-0.53*h),0.31);
-total_weight+=sampleScreen(col,vec2(-2.59*w,3.12*h),0.26);
-total_weight+=sampleScreen(col,vec2(-0.20*w,-4.15*h),0.22);
-total_weight+=sampleScreen(col,vec2(3.02*w,3.00*h),0.15);
-}
-col/=total_weight;
-
-if (darken>0.0) {
-col.rgb*=clamp(0.3,1.0,1.05-size*0.5*darken);
-}
-
-
-
-
-return col;
-}
-void main(void)
-{
-
-centered_screen_pos=vec2(vUV.x-0.5,vUV.y-0.5);
-radius2=centered_screen_pos.x*centered_screen_pos.x+centered_screen_pos.y*centered_screen_pos.y;
-radius=sqrt(radius2);
-distorted_coords=getDistortedCoords(vUV);
-vec2 texels_coords=vec2(vUV.x*screen_width,vUV.y*screen_height);
-float depth=texture2D(depthSampler,distorted_coords).r;
-float distance=near+(far-near)*depth;
-vec4 color=texture2D(textureSampler,vUV);
-
-
-float coc=abs(aperture*(screen_distance*(inverse_focal_length-1.0/distance)-1.0));
-
-if (dof_enabled == false || coc<0.07) { coc=0.0; }
-
-float edge_blur_amount=0.0;
-if (edge_blur>0.0) {
-edge_blur_amount=clamp((radius*2.0-1.0+0.15*edge_blur)*1.5,0.0,1.0)*1.3;
-}
-
-float blur_amount=max(edge_blur_amount,coc);
-
-if (blur_amount == 0.0) {
-gl_FragColor=texture2D(textureSampler,distorted_coords);
-}
-else {
-
-gl_FragColor=getBlurColor(blur_amount*1.7);
-
-if (highlights) {
-gl_FragColor.rgb+=clamp(coc,0.0,1.0)*texture2D(highlightsSampler,distorted_coords).rgb;
-}
-if (blur_noise) {
-
-vec2 noise=rand(distorted_coords)*0.01*blur_amount;
-vec2 blurred_coord=vec2(distorted_coords.x+noise.x,distorted_coords.y+noise.y);
-gl_FragColor=0.04*texture2D(textureSampler,blurred_coord)+0.96*gl_FragColor;
-}
-}
-
-if (grain_amount>0.0) {
-vec4 grain_color=texture2D(grainSampler,texels_coords*0.003);
-gl_FragColor.rgb+=(-0.5+grain_color.rgb)*0.30*grain_amount;
-}
-}
-`;ze.a.ShadersStore.depthOfFieldPixelShader=gg;var vg=function(r){function t(e,n,i,o,a){o===void 0&&(o=1);var s=r.call(this,i.getEngine(),e)||this;return s.LensChromaticAberrationEffect="LensChromaticAberrationEffect",s.HighlightsEnhancingEffect="HighlightsEnhancingEffect",s.LensDepthOfFieldEffect="LensDepthOfFieldEffect",s._pentagonBokehIsEnabled=!1,s._scene=i,s._depthTexture=i.enableDepthRenderer().getDepthMap(),n.grain_texture?s._grainTexture=n.grain_texture:s._createGrainTexture(),s._edgeBlur=n.edge_blur?n.edge_blur:0,s._grainAmount=n.grain_amount?n.grain_amount:0,s._chromaticAberration=n.chromatic_aberration?n.chromatic_aberration:0,s._distortion=n.distortion?n.distortion:0,s._highlightsGain=n.dof_gain!==void 0?n.dof_gain:-1,s._highlightsThreshold=n.dof_threshold?n.dof_threshold:1,s._dofDistance=n.dof_focus_distance!==void 0?n.dof_focus_distance:-1,s._dofAperture=n.dof_aperture?n.dof_aperture:1,s._dofDarken=n.dof_darken?n.dof_darken:0,s._dofPentagon=n.dof_pentagon===void 0||n.dof_pentagon,s._blurNoise=n.blur_noise===void 0||n.blur_noise,s._createChromaticAberrationPostProcess(o),s._createHighlightsPostProcess(o),s._createDepthOfFieldPostProcess(o/4),s.addEffect(new Rt(i.getEngine(),s.LensChromaticAberrationEffect,function(){return s._chromaticAberrationPostProcess},!0)),s.addEffect(new Rt(i.getEngine(),s.HighlightsEnhancingEffect,function(){return s._highlightsPostProcess},!0)),s.addEffect(new Rt(i.getEngine(),s.LensDepthOfFieldEffect,function(){return s._depthOfFieldPostProcess},!0)),s._highlightsGain===-1&&s._disableEffect(s.HighlightsEnhancingEffect,null),i.postProcessRenderPipelineManager.addPipeline(s),a&&i.postProcessRenderPipelineManager.attachCamerasToRenderPipeline(e,a),s}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"LensRenderingPipeline"},Object.defineProperty(t.prototype,"scene",{get:function(){return this._scene},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"edgeBlur",{get:function(){return this._edgeBlur},set:function(e){this.setEdgeBlur(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"grainAmount",{get:function(){return this._grainAmount},set:function(e){this.setGrainAmount(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"chromaticAberration",{get:function(){return this._chromaticAberration},set:function(e){this.setChromaticAberration(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dofAperture",{get:function(){return this._dofAperture},set:function(e){this.setAperture(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"edgeDistortion",{get:function(){return this._distortion},set:function(e){this.setEdgeDistortion(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"dofDistortion",{get:function(){return this._dofDistance},set:function(e){this.setFocusDistance(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"darkenOutOfFocus",{get:function(){return this._dofDarken},set:function(e){this.setDarkenOutOfFocus(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"blurNoise",{get:function(){return this._blurNoise},set:function(e){this._blurNoise=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"pentagonBokeh",{get:function(){return this._pentagonBokehIsEnabled},set:function(e){e?this.enablePentagonBokeh():this.disablePentagonBokeh()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"highlightsGain",{get:function(){return this._highlightsGain},set:function(e){this.setHighlightsGain(e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"highlightsThreshold",{get:function(){return this._highlightsThreshold},set:function(e){this.setHighlightsThreshold(e)},enumerable:!1,configurable:!0}),t.prototype.setEdgeBlur=function(e){this._edgeBlur=e},t.prototype.disableEdgeBlur=function(){this._edgeBlur=0},t.prototype.setGrainAmount=function(e){this._grainAmount=e},t.prototype.disableGrain=function(){this._grainAmount=0},t.prototype.setChromaticAberration=function(e){this._chromaticAberration=e},t.prototype.disableChromaticAberration=function(){this._chromaticAberration=0},t.prototype.setEdgeDistortion=function(e){this._distortion=e},t.prototype.disableEdgeDistortion=function(){this._distortion=0},t.prototype.setFocusDistance=function(e){this._dofDistance=e},t.prototype.disableDepthOfField=function(){this._dofDistance=-1},t.prototype.setAperture=function(e){this._dofAperture=e},t.prototype.setDarkenOutOfFocus=function(e){this._dofDarken=e},t.prototype.enablePentagonBokeh=function(){this._highlightsPostProcess.updateEffect(`#define PENTAGON
-`),this._pentagonBokehIsEnabled=!0},t.prototype.disablePentagonBokeh=function(){this._pentagonBokehIsEnabled=!1,this._highlightsPostProcess.updateEffect()},t.prototype.enableNoiseBlur=function(){this._blurNoise=!0},t.prototype.disableNoiseBlur=function(){this._blurNoise=!1},t.prototype.setHighlightsGain=function(e){this._highlightsGain=e},t.prototype.setHighlightsThreshold=function(e){this._highlightsGain===-1&&(this._highlightsGain=1),this._highlightsThreshold=e},t.prototype.disableHighlights=function(){this._highlightsGain=-1},t.prototype.dispose=function(e){e===void 0&&(e=!1),this._scene.postProcessRenderPipelineManager.detachCamerasFromRenderPipeline(this._name,this._scene.cameras),this._chromaticAberrationPostProcess=null,this._highlightsPostProcess=null,this._depthOfFieldPostProcess=null,this._grainTexture.dispose(),e&&this._scene.disableDepthRenderer()},t.prototype._createChromaticAberrationPostProcess=function(e){var n=this;this._chromaticAberrationPostProcess=new _t("LensChromaticAberration","chromaticAberration",["chromatic_aberration","screen_width","screen_height","direction","radialIntensity","centerPosition"],[],e,null,we.a.TRILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1),this._chromaticAberrationPostProcess.onApply=function(i){i.setFloat("chromatic_aberration",n._chromaticAberration),i.setFloat("screen_width",n._scene.getEngine().getRenderWidth()),i.setFloat("screen_height",n._scene.getEngine().getRenderHeight()),i.setFloat("radialIntensity",1),i.setFloat2("direction",17,17),i.setFloat2("centerPosition",.5,.5)}},t.prototype._createHighlightsPostProcess=function(e){var n=this;this._highlightsPostProcess=new _t("LensHighlights","lensHighlights",["gain","threshold","screen_width","screen_height"],[],e,null,we.a.TRILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,this._dofPentagon?`#define PENTAGON
-`:""),this._highlightsPostProcess.onApply=function(i){i.setFloat("gain",n._highlightsGain),i.setFloat("threshold",n._highlightsThreshold),i.setTextureFromPostProcess("textureSampler",n._chromaticAberrationPostProcess),i.setFloat("screen_width",n._scene.getEngine().getRenderWidth()),i.setFloat("screen_height",n._scene.getEngine().getRenderHeight())}},t.prototype._createDepthOfFieldPostProcess=function(e){var n=this;this._depthOfFieldPostProcess=new _t("LensDepthOfField","depthOfField",["grain_amount","blur_noise","screen_width","screen_height","distortion","dof_enabled","screen_distance","aperture","darken","edge_blur","highlights","near","far"],["depthSampler","grainSampler","highlightsSampler"],e,null,we.a.TRILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1),this._depthOfFieldPostProcess.onApply=function(i){i.setTexture("depthSampler",n._depthTexture),i.setTexture("grainSampler",n._grainTexture),i.setTextureFromPostProcess("textureSampler",n._highlightsPostProcess),i.setTextureFromPostProcess("highlightsSampler",n._depthOfFieldPostProcess),i.setFloat("grain_amount",n._grainAmount),i.setBool("blur_noise",n._blurNoise),i.setFloat("screen_width",n._scene.getEngine().getRenderWidth()),i.setFloat("screen_height",n._scene.getEngine().getRenderHeight()),i.setFloat("distortion",n._distortion),i.setBool("dof_enabled",n._dofDistance!==-1),i.setFloat("screen_distance",1/(.1-1/n._dofDistance)),i.setFloat("aperture",n._dofAperture),i.setFloat("darken",n._dofDarken),i.setFloat("edge_blur",n._edgeBlur),i.setBool("highlights",n._highlightsGain!==-1),n._scene.activeCamera&&(i.setFloat("near",n._scene.activeCamera.minZ),i.setFloat("far",n._scene.activeCamera.maxZ))}},t.prototype._createGrainTexture=function(){this._grainTexture=new Ti.a("LensNoiseTexture",512,this._scene,!1,we.a.BILINEAR_SAMPLINGMODE),this._grainTexture.wrapU=we.a.WRAP_ADDRESSMODE,this._grainTexture.wrapV=we.a.WRAP_ADDRESSMODE;for(var e,n,i,o=this._grainTexture.getContext(),a=0;a<512;a++)for(var s=0;s<512;s++)e=Math.floor(255*(n=.42,i=.58,Math.random()*(i-n)+n)),o.fillStyle="rgb("+e+", "+e+", "+e+")",o.fillRect(a,s,1,1);this._grainTexture.update(!1)},t}(Vr),bg=function(){this.enabled=!1,this.name="ssao2",this.texturesRequired=[h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE]},yg=`
-precision highp float;
-uniform sampler2D textureSampler;
-uniform float near;
-uniform float far;
-uniform float radius;
-float scales[16]=float[16](
-0.1,
-0.11406250000000001,
-0.131640625,
-0.15625,
-0.187890625,
-0.2265625,
-0.272265625,
-0.325,
-0.384765625,
-0.4515625,
-0.525390625,
-0.60625,
-0.694140625,
-0.7890625,
-0.891015625,
-1.0
-);
-varying vec2 vUV;
-float perspectiveDepthToViewZ( const in float invClipZ,const in float near,const in float far ) {
-return ( near*far )/( ( far-near )*invClipZ-far );
-}
-float viewZToPerspectiveDepth( const in float viewZ,const in float near,const in float far ) {
-return ( near*far/viewZ+far)/( far-near );
-}
-float viewZToOrthographicDepth( const in float viewZ,const in float near,const in float far ) {
-return ( viewZ+near )/( near-far );
-}
-#ifdef SSAO
-uniform sampler2D randomSampler;
-#ifndef GEOMETRYBUFFER
-uniform sampler2D depthNormalSampler;
-#else
-uniform sampler2D depthSampler;
-uniform sampler2D normalSampler;
-#endif
-uniform float randTextureTiles;
-uniform float samplesFactor;
-uniform vec3 sampleSphere[SAMPLES];
-uniform float totalStrength;
-uniform float base;
-uniform float xViewport;
-uniform float yViewport;
-uniform float maxZ;
-uniform float minZAspect;
-uniform vec2 texelSize;
-uniform mat4 projection;
-void main()
-{
-vec3 random=texture2D(randomSampler,vUV*randTextureTiles).rgb;
-#ifndef GEOMETRYBUFFER
-float depth=texture2D(depthNormalSampler,vUV).r;
-#else
-float depth=texture2D(depthSampler,vUV).r;
-#endif
-float depthSign=depth/abs(depth);
-depth=depth*depthSign;
-#ifndef GEOMETRYBUFFER
-vec3 normal=texture2D(depthNormalSampler,vUV).gba;
-#else
-vec3 normal=texture2D(normalSampler,vUV).rgb;
-#endif
-float occlusion=0.0;
-float correctedRadius=min(radius,minZAspect*depth/near);
-vec3 vViewRay=vec3((vUV.x*2.0-1.0)*xViewport,(vUV.y*2.0-1.0)*yViewport,depthSign);
-vec3 origin=vViewRay*depth;
-vec3 rvec=random*2.0-1.0;
-rvec.z=0.0;
-
-float dotProduct=dot(rvec,normal);
-rvec=1.0-abs(dotProduct)>1e-2 ? rvec : vec3(-rvec.y,0.0,rvec.x);
-vec3 tangent=normalize(rvec-normal*dot(rvec,normal));
-vec3 bitangent=cross(normal,tangent);
-mat3 tbn=mat3(tangent,bitangent,normal);
-float difference;
-for (int i=0; i<SAMPLES; ++i) {
-
-vec3 samplePosition=scales[(i+int(random.x*16.0)) % 16]*tbn*sampleSphere[(i+int(random.y*16.0)) % 16];
-samplePosition=samplePosition*correctedRadius+origin;
-
-vec4 offset=vec4(samplePosition,1.0);
-offset=projection*offset;
-offset.xyz/=offset.w;
-offset.xy=offset.xy*0.5+0.5;
-if (offset.x<0.0 || offset.y<0.0 || offset.x>1.0 || offset.y>1.0) {
-continue;
-}
-
-#ifndef GEOMETRYBUFFER
-float sampleDepth=abs(texture2D(depthNormalSampler,offset.xy).r);
-#else
-float sampleDepth=abs(texture2D(depthSampler,offset.xy).r);
-#endif
-
-difference=depthSign*samplePosition.z-sampleDepth;
-float rangeCheck=1.0-smoothstep(correctedRadius*0.5,correctedRadius,difference);
-occlusion+=(difference>=0.0 ? 1.0 : 0.0)*rangeCheck;
-}
-occlusion=occlusion*(1.0-smoothstep(maxZ*0.75,maxZ,depth));
-float ao=1.0-totalStrength*occlusion*samplesFactor;
-float result=clamp(ao+base,0.0,1.0);
-gl_FragColor=vec4(vec3(result),1.0);
-}
-#endif
-#ifdef BILATERAL_BLUR
-uniform sampler2D depthNormalSampler;
-uniform float outSize;
-uniform float samplerOffsets[SAMPLES];
-vec4 blur9(sampler2D image,vec2 uv,float resolution,vec2 direction) {
-vec4 color=vec4(0.0);
-vec2 off1=vec2(1.3846153846)*direction;
-vec2 off2=vec2(3.2307692308)*direction;
-color+=texture2D(image,uv)*0.2270270270;
-color+=texture2D(image,uv+(off1/resolution))*0.3162162162;
-color+=texture2D(image,uv-(off1/resolution))*0.3162162162;
-color+=texture2D(image,uv+(off2/resolution))*0.0702702703;
-color+=texture2D(image,uv-(off2/resolution))*0.0702702703;
-return color;
-}
-vec4 blur13(sampler2D image,vec2 uv,float resolution,vec2 direction) {
-vec4 color=vec4(0.0);
-vec2 off1=vec2(1.411764705882353)*direction;
-vec2 off2=vec2(3.2941176470588234)*direction;
-vec2 off3=vec2(5.176470588235294)*direction;
-color+=texture2D(image,uv)*0.1964825501511404;
-color+=texture2D(image,uv+(off1/resolution))*0.2969069646728344;
-color+=texture2D(image,uv-(off1/resolution))*0.2969069646728344;
-color+=texture2D(image,uv+(off2/resolution))*0.09447039785044732;
-color+=texture2D(image,uv-(off2/resolution))*0.09447039785044732;
-color+=texture2D(image,uv+(off3/resolution))*0.010381362401148057;
-color+=texture2D(image,uv-(off3/resolution))*0.010381362401148057;
-return color;
-}
-vec4 blur13Bilateral(sampler2D image,vec2 uv,float resolution,vec2 direction) {
-vec4 color=vec4(0.0);
-vec2 off1=vec2(1.411764705882353)*direction;
-vec2 off2=vec2(3.2941176470588234)*direction;
-vec2 off3=vec2(5.176470588235294)*direction;
-float compareDepth=abs(texture2D(depthNormalSampler,uv).r);
-float sampleDepth;
-float weight;
-float weightSum=30.0;
-color+=texture2D(image,uv)*30.0;
-sampleDepth=abs(texture2D(depthNormalSampler,uv+(off1/resolution)).r);
-weight=clamp(1.0/( 0.003+abs(compareDepth-sampleDepth)),0.0,30.0);
-weightSum+=weight;
-color+=texture2D(image,uv+(off1/resolution))*weight;
-sampleDepth=abs(texture2D(depthNormalSampler,uv-(off1/resolution)).r);
-weight=clamp(1.0/( 0.003+abs(compareDepth-sampleDepth)),0.0,30.0);
-weightSum+=weight;
-color+=texture2D(image,uv-(off1/resolution))*weight;
-sampleDepth=abs(texture2D(depthNormalSampler,uv+(off2/resolution)).r);
-weight=clamp(1.0/( 0.003+abs(compareDepth-sampleDepth)),0.0,30.0);
-weightSum+=weight;
-color+=texture2D(image,uv+(off2/resolution))*weight;
-sampleDepth=abs(texture2D(depthNormalSampler,uv-(off2/resolution)).r);
-weight=clamp(1.0/( 0.003+abs(compareDepth-sampleDepth)),0.0,30.0);
-weightSum+=weight;
-color+=texture2D(image,uv-(off2/resolution))*weight;
-sampleDepth=abs(texture2D(depthNormalSampler,uv+(off3/resolution)).r);
-weight=clamp(1.0/( 0.003+abs(compareDepth-sampleDepth)),0.0,30.0);
-weightSum+=weight;
-color+=texture2D(image,uv+(off3/resolution))*weight;
-sampleDepth=abs(texture2D(depthNormalSampler,uv-(off3/resolution)).r);
-weight=clamp(1.0/( 0.003+abs(compareDepth-sampleDepth)),0.0,30.0);
-weightSum+=weight;
-color+=texture2D(image,uv-(off3/resolution))*weight;
-return color/weightSum;
-}
-void main()
-{
-#if EXPENSIVE
-float compareDepth=abs(texture2D(depthNormalSampler,vUV).r);
-float texelsize=1.0/outSize;
-float result=0.0;
-float weightSum=0.0;
-for (int i=0; i<SAMPLES; ++i)
-{
-#ifdef BILATERAL_BLUR_H
-vec2 direction=vec2(1.0,0.0);
-vec2 sampleOffset=vec2(texelsize*samplerOffsets[i],0.0);
-#else
-vec2 direction=vec2(0.0,1.0);
-vec2 sampleOffset=vec2(0.0,texelsize*samplerOffsets[i]);
-#endif
-vec2 samplePos=vUV+sampleOffset;
-float sampleDepth=abs(texture2D(depthNormalSampler,samplePos).r);
-float weight=clamp(1.0/( 0.003+abs(compareDepth-sampleDepth)),0.0,30000.0);
-result+=texture2D(textureSampler,samplePos).r*weight;
-weightSum+=weight;
-}
-result/=weightSum;
-gl_FragColor.rgb=vec3(result);
-gl_FragColor.a=1.0;
-#else
-vec4 color;
-#ifdef BILATERAL_BLUR_H
-vec2 direction=vec2(1.0,0.0);
-color=blur13Bilateral(textureSampler,vUV,outSize,direction);
-#else
-vec2 direction=vec2(0.0,1.0);
-color=blur13Bilateral(textureSampler,vUV,outSize,direction);
-#endif
-gl_FragColor.rgb=vec3(color.r);
-gl_FragColor.a=1.0;
-#endif
-}
-#endif
-`;ze.a.ShadersStore.ssao2PixelShader=yg;var Tg=`uniform sampler2D textureSampler;
-uniform sampler2D originalColor;
-uniform vec4 viewport;
-varying vec2 vUV;
-void main(void) {
-vec4 ssaoColor=texture2D(textureSampler,viewport.xy+vUV*viewport.zw);
-vec4 sceneColor=texture2D(originalColor,vUV);
-gl_FragColor=sceneColor*ssaoColor;
-}
-`;ze.a.ShadersStore.ssaoCombinePixelShader=Tg;var jd=function(r){function t(e,n,i,o,a){a===void 0&&(a=!0);var s=r.call(this,n.getEngine(),e)||this;if(s.SSAOOriginalSceneColorEffect="SSAOOriginalSceneColorEffect",s.SSAORenderEffect="SSAORenderEffect",s.SSAOBlurHRenderEffect="SSAOBlurHRenderEffect",s.SSAOBlurVRenderEffect="SSAOBlurVRenderEffect",s.SSAOCombineRenderEffect="SSAOCombineRenderEffect",s.totalStrength=1,s.maxZ=100,s.minZAspect=.2,s._samples=8,s._textureSamples=1,s._forceGeometryBuffer=!1,s._expensiveBlur=!0,s.radius=2,s.base=0,s._bits=new Uint32Array(1),s._scene=n,s._ratio=i,s._forceGeometryBuffer=a,!s.isSupported)return l.a.Error("SSAO 2 needs WebGL 2 support."),s;var d=s._ratio.ssaoRatio||i,p=s._ratio.blurRatio||i;return s._forceGeometryBuffer?n.enableGeometryBufferRenderer():s._prePassRenderer=n.enablePrePassRenderer(),s._createRandomTexture(),s._originalColorPostProcess=new Fi("SSAOOriginalSceneColor",1,null,we.a.BILINEAR_SAMPLINGMODE,n.getEngine(),!1),s._originalColorPostProcess.samples=s.textureSamples,s._createSSAOPostProcess(1),s._createBlurPostProcess(d,p),s._createSSAOCombinePostProcess(p),s.addEffect(new Rt(n.getEngine(),s.SSAOOriginalSceneColorEffect,function(){return s._originalColorPostProcess},!0)),s.addEffect(new Rt(n.getEngine(),s.SSAORenderEffect,function(){return s._ssaoPostProcess},!0)),s.addEffect(new Rt(n.getEngine(),s.SSAOBlurHRenderEffect,function(){return s._blurHPostProcess},!0)),s.addEffect(new Rt(n.getEngine(),s.SSAOBlurVRenderEffect,function(){return s._blurVPostProcess},!0)),s.addEffect(new Rt(n.getEngine(),s.SSAOCombineRenderEffect,function(){return s._ssaoCombinePostProcess},!0)),n.postProcessRenderPipelineManager.addPipeline(s),o&&n.postProcessRenderPipelineManager.attachCamerasToRenderPipeline(e,o),s}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"samples",{get:function(){return this._samples},set:function(e){this._samples=e,this._ssaoPostProcess.updateEffect(this._getDefinesForSSAO()),this._sampleSphere=this._generateHemisphere()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"textureSamples",{get:function(){return this._textureSamples},set:function(e){this._textureSamples=e,this._originalColorPostProcess.samples=e,this._blurHPostProcess.samples=e,this._blurVPostProcess.samples=e,this._ssaoPostProcess.samples=e,this._ssaoCombinePostProcess.samples=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"expensiveBlur",{get:function(){return this._expensiveBlur},set:function(e){this._blurHPostProcess.updateEffect(`#define BILATERAL_BLUR
-#define BILATERAL_BLUR_H
-#define SAMPLES 16
-#define EXPENSIVE `+(e?"1":"0")+`
-`,null,["textureSampler","depthNormalSampler"]),this._blurVPostProcess.updateEffect(`#define BILATERAL_BLUR
-#define SAMPLES 16
-#define EXPENSIVE `+(e?"1":"0")+`
-`,null,["textureSampler","depthNormalSampler"]),this._expensiveBlur=e},enumerable:!1,configurable:!0}),Object.defineProperty(t,"IsSupported",{get:function(){var e=te.a.LastCreatedEngine;return!!e&&e.webGLVersion>=2},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"scene",{get:function(){return this._scene},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"SSAO2RenderingPipeline"},t.prototype.dispose=function(e){e===void 0&&(e=!1);for(var n=0;n<this._scene.cameras.length;n++){var i=this._scene.cameras[n];this._originalColorPostProcess.dispose(i),this._ssaoPostProcess.dispose(i),this._blurHPostProcess.dispose(i),this._blurVPostProcess.dispose(i),this._ssaoCombinePostProcess.dispose(i)}this._randomTexture.dispose(),e&&this._scene.disableGeometryBufferRenderer(),this._scene.postProcessRenderPipelineManager.detachCamerasFromRenderPipeline(this._name,this._scene.cameras),r.prototype.dispose.call(this)},t.prototype._createBlurPostProcess=function(e,n){var i=this;this._samplerOffsets=[];for(var o=this.expensiveBlur,a=-8;a<8;a++)this._samplerOffsets.push(2*a+.5);this._blurHPostProcess=new _t("BlurH","ssao2",["outSize","samplerOffsets","near","far","radius"],["depthNormalSampler"],e,null,we.a.TRILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,`#define BILATERAL_BLUR
-#define BILATERAL_BLUR_H
-#define SAMPLES 16
-#define EXPENSIVE `+(o?"1":"0")+`
-`),this._blurHPostProcess.onApply=function(s){i._scene.activeCamera&&(s.setFloat("outSize",i._ssaoCombinePostProcess.width>0?i._ssaoCombinePostProcess.width:i._originalColorPostProcess.width),s.setFloat("near",i._scene.activeCamera.minZ),s.setFloat("far",i._scene.activeCamera.maxZ),s.setFloat("radius",i.radius),i._forceGeometryBuffer?s.setTexture("depthNormalSampler",i._scene.enableGeometryBufferRenderer().getGBuffer().textures[0]):s.setTexture("depthNormalSampler",i._prePassRenderer.prePassRT.textures[i._prePassRenderer.getIndex(h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE)]),s.setArray("samplerOffsets",i._samplerOffsets))},this._blurVPostProcess=new _t("BlurV","ssao2",["outSize","samplerOffsets","near","far","radius"],["depthNormalSampler"],n,null,we.a.TRILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,`#define BILATERAL_BLUR
-#define BILATERAL_BLUR_V
-#define SAMPLES 16
-#define EXPENSIVE `+(o?"1":"0")+`
-`),this._blurVPostProcess.onApply=function(s){i._scene.activeCamera&&(s.setFloat("outSize",i._ssaoCombinePostProcess.height>0?i._ssaoCombinePostProcess.height:i._originalColorPostProcess.height),s.setFloat("near",i._scene.activeCamera.minZ),s.setFloat("far",i._scene.activeCamera.maxZ),s.setFloat("radius",i.radius),i._forceGeometryBuffer?s.setTexture("depthNormalSampler",i._scene.enableGeometryBufferRenderer().getGBuffer().textures[0]):s.setTexture("depthNormalSampler",i._prePassRenderer.prePassRT.textures[i._prePassRenderer.getIndex(h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE)]),s.setArray("samplerOffsets",i._samplerOffsets))},this._blurHPostProcess.samples=this.textureSamples,this._blurVPostProcess.samples=this.textureSamples},t.prototype._rebuild=function(){r.prototype._rebuild.call(this)},t.prototype._radicalInverse_VdC=function(e){return this._bits[0]=e,this._bits[0]=(this._bits[0]<<16|this._bits[0]>>16)>>>0,this._bits[0]=(1431655765&this._bits[0])<<1|(2863311530&this._bits[0])>>>1>>>0,this._bits[0]=(858993459&this._bits[0])<<2|(3435973836&this._bits[0])>>>2>>>0,this._bits[0]=(252645135&this._bits[0])<<4|(4042322160&this._bits[0])>>>4>>>0,this._bits[0]=(16711935&this._bits[0])<<8|(4278255360&this._bits[0])>>>8>>>0,23283064365386963e-26*this._bits[0]},t.prototype._hammersley=function(e,n){return[e/n,this._radicalInverse_VdC(e)]},t.prototype._hemisphereSample_uniform=function(e,n){var i=2*n*Math.PI,o=1-(.85*e+.15),a=Math.sqrt(1-o*o);return new u.e(Math.cos(i)*a,Math.sin(i)*a,o)},t.prototype._generateHemisphere=function(){for(var e,n=this.samples,i=[],o=0;o<n;){if(n<16)e=this._hemisphereSample_uniform(Math.random(),Math.random());else{var a=this._hammersley(o,n);e=this._hemisphereSample_uniform(a[0],a[1])}i.push(e.x,e.y,e.z),o++}return i},t.prototype._getDefinesForSSAO=function(){var e="#define SAMPLES "+this.samples+`
-#define SSAO`;return this._forceGeometryBuffer&&(e+=`
-#define GEOMETRYBUFFER`),e},t.prototype._createSSAOPostProcess=function(e){var n=this;this._sampleSphere=this._generateHemisphere();var i,o=this._getDefinesForSSAO();i=this._forceGeometryBuffer?["randomSampler","depthSampler","normalSampler"]:["randomSampler","depthNormalSampler"],this._ssaoPostProcess=new _t("ssao2","ssao2",["sampleSphere","samplesFactor","randTextureTiles","totalStrength","radius","base","range","projection","near","far","texelSize","xViewport","yViewport","maxZ","minZAspect"],i,e,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,o),this._ssaoPostProcess.onApply=function(a){n._scene.activeCamera&&(a.setArray3("sampleSphere",n._sampleSphere),a.setFloat("randTextureTiles",32),a.setFloat("samplesFactor",1/n.samples),a.setFloat("totalStrength",n.totalStrength),a.setFloat2("texelSize",1/n._ssaoPostProcess.width,1/n._ssaoPostProcess.height),a.setFloat("radius",n.radius),a.setFloat("maxZ",n.maxZ),a.setFloat("minZAspect",n.minZAspect),a.setFloat("base",n.base),a.setFloat("near",n._scene.activeCamera.minZ),a.setFloat("far",n._scene.activeCamera.maxZ),a.setFloat("xViewport",Math.tan(n._scene.activeCamera.fov/2)*n._scene.getEngine().getAspectRatio(n._scene.activeCamera,!0)),a.setFloat("yViewport",Math.tan(n._scene.activeCamera.fov/2)),a.setMatrix("projection",n._scene.getProjectionMatrix()),n._forceGeometryBuffer?(a.setTexture("depthSampler",n._scene.enableGeometryBufferRenderer().getGBuffer().textures[0]),a.setTexture("normalSampler",n._scene.enableGeometryBufferRenderer().getGBuffer().textures[1])):a.setTexture("depthNormalSampler",n._prePassRenderer.prePassRT.textures[n._prePassRenderer.getIndex(h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE)]),a.setTexture("randomSampler",n._randomTexture))},this._ssaoPostProcess.samples=this.textureSamples},t.prototype._createSSAOCombinePostProcess=function(e){var n=this;this._ssaoCombinePostProcess=new _t("ssaoCombine","ssaoCombine",[],["originalColor","viewport"],e,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1),this._ssaoCombinePostProcess.onApply=function(i){var o=n._scene.activeCamera.viewport;i.setVector4("viewport",u.c.Vector4[0].copyFromFloats(o.x,o.y,o.width,o.height)),i.setTextureFromPostProcessOutput("originalColor",n._originalColorPostProcess)},this._ssaoCombinePostProcess.samples=this.textureSamples,this._forceGeometryBuffer||(this._ssaoCombinePostProcess._prePassEffectConfiguration=new bg)},t.prototype._createRandomTexture=function(){this._randomTexture=new Ti.a("SSAORandomTexture",128,this._scene,!1,we.a.TRILINEAR_SAMPLINGMODE),this._randomTexture.wrapU=we.a.WRAP_ADDRESSMODE,this._randomTexture.wrapV=we.a.WRAP_ADDRESSMODE;for(var e=this._randomTexture.getContext(),n=function(s,d){return Math.random()*(d-s)+s},i=u.e.Zero(),o=0;o<128;o++)for(var a=0;a<128;a++)i.x=n(0,1),i.y=n(0,1),i.z=0,i.normalize(),i.scaleInPlace(255),i.x=Math.floor(i.x),i.y=Math.floor(i.y),e.fillStyle="rgb("+i.x+", "+i.y+", "+i.z+")",e.fillRect(o,a,1,1);this._randomTexture.update(!1)},t.prototype.serialize=function(){var e=L.a.Serialize(this);return e.customType="SSAO2RenderingPipeline",e},t.Parse=function(e,n,i){return L.a.Parse(function(){return new t(e._name,n,e._ratio)},e,n,i)},Object(c.c)([Object(L.c)()],t.prototype,"totalStrength",void 0),Object(c.c)([Object(L.c)()],t.prototype,"maxZ",void 0),Object(c.c)([Object(L.c)()],t.prototype,"minZAspect",void 0),Object(c.c)([Object(L.c)("samples")],t.prototype,"_samples",void 0),Object(c.c)([Object(L.c)("textureSamples")],t.prototype,"_textureSamples",void 0),Object(c.c)([Object(L.c)()],t.prototype,"_ratio",void 0),Object(c.c)([Object(L.c)("expensiveBlur")],t.prototype,"_expensiveBlur",void 0),Object(c.c)([Object(L.c)()],t.prototype,"radius",void 0),Object(c.c)([Object(L.c)()],t.prototype,"base",void 0),t}(Vr);R.a.RegisteredTypes["BABYLON.SSAO2RenderingPipeline"]=jd;var Eg=`
-uniform sampler2D textureSampler;
-varying vec2 vUV;
-#ifdef SSAO
-uniform sampler2D randomSampler;
-uniform float randTextureTiles;
-uniform float samplesFactor;
-uniform vec3 sampleSphere[SAMPLES];
-uniform float totalStrength;
-uniform float radius;
-uniform float area;
-uniform float fallOff;
-uniform float base;
-vec3 normalFromDepth(float depth,vec2 coords)
-{
-vec2 offset1=vec2(0.0,radius);
-vec2 offset2=vec2(radius,0.0);
-float depth1=texture2D(textureSampler,coords+offset1).r;
-float depth2=texture2D(textureSampler,coords+offset2).r;
-vec3 p1=vec3(offset1,depth1-depth);
-vec3 p2=vec3(offset2,depth2-depth);
-vec3 normal=cross(p1,p2);
-normal.z=-normal.z;
-return normalize(normal);
-}
-void main()
-{
-vec3 random=normalize(texture2D(randomSampler,vUV*randTextureTiles).rgb);
-float depth=texture2D(textureSampler,vUV).r;
-vec3 position=vec3(vUV,depth);
-vec3 normal=normalFromDepth(depth,vUV);
-float radiusDepth=radius/depth;
-float occlusion=0.0;
-vec3 ray;
-vec3 hemiRay;
-float occlusionDepth;
-float difference;
-for (int i=0; i<SAMPLES; i++)
-{
-ray=radiusDepth*reflect(sampleSphere[i],random);
-hemiRay=position+sign(dot(ray,normal))*ray;
-occlusionDepth=texture2D(textureSampler,clamp(hemiRay.xy,vec2(0.001,0.001),vec2(0.999,0.999))).r;
-difference=depth-occlusionDepth;
-occlusion+=step(fallOff,difference)*(1.0-smoothstep(fallOff,area,difference));
-}
-float ao=1.0-totalStrength*occlusion*samplesFactor;
-float result=clamp(ao+base,0.0,1.0);
-gl_FragColor.r=result;
-gl_FragColor.g=result;
-gl_FragColor.b=result;
-gl_FragColor.a=1.0;
-}
-#endif
-`;ze.a.ShadersStore.ssaoPixelShader=Eg;var Sg=function(r){function t(e,n,i,o){var a=r.call(this,n.getEngine(),e)||this;a.SSAOOriginalSceneColorEffect="SSAOOriginalSceneColorEffect",a.SSAORenderEffect="SSAORenderEffect",a.SSAOBlurHRenderEffect="SSAOBlurHRenderEffect",a.SSAOBlurVRenderEffect="SSAOBlurVRenderEffect",a.SSAOCombineRenderEffect="SSAOCombineRenderEffect",a.totalStrength=1,a.radius=1e-4,a.area=.0075,a.fallOff=1e-6,a.base=.5,a._firstUpdate=!0,a._scene=n,a._createRandomTexture(),a._depthTexture=n.enableDepthRenderer().getDepthMap();var s=i.ssaoRatio||i,d=i.combineRatio||i;return a._originalColorPostProcess=new Fi("SSAOOriginalSceneColor",d,null,we.a.BILINEAR_SAMPLINGMODE,n.getEngine(),!1),a._createSSAOPostProcess(s),a._createBlurPostProcess(s),a._createSSAOCombinePostProcess(d),a.addEffect(new Rt(n.getEngine(),a.SSAOOriginalSceneColorEffect,function(){return a._originalColorPostProcess},!0)),a.addEffect(new Rt(n.getEngine(),a.SSAORenderEffect,function(){return a._ssaoPostProcess},!0)),a.addEffect(new Rt(n.getEngine(),a.SSAOBlurHRenderEffect,function(){return a._blurHPostProcess},!0)),a.addEffect(new Rt(n.getEngine(),a.SSAOBlurVRenderEffect,function(){return a._blurVPostProcess},!0)),a.addEffect(new Rt(n.getEngine(),a.SSAOCombineRenderEffect,function(){return a._ssaoCombinePostProcess},!0)),n.postProcessRenderPipelineManager.addPipeline(a),o&&n.postProcessRenderPipelineManager.attachCamerasToRenderPipeline(e,o),a}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"scene",{get:function(){return this._scene},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"SSAORenderingPipeline"},t.prototype.dispose=function(e){e===void 0&&(e=!1);for(var n=0;n<this._scene.cameras.length;n++){var i=this._scene.cameras[n];this._originalColorPostProcess.dispose(i),this._ssaoPostProcess.dispose(i),this._blurHPostProcess.dispose(i),this._blurVPostProcess.dispose(i),this._ssaoCombinePostProcess.dispose(i)}this._randomTexture.dispose(),e&&this._scene.disableDepthRenderer(),this._scene.postProcessRenderPipelineManager.detachCamerasFromRenderPipeline(this._name,this._scene.cameras),r.prototype.dispose.call(this)},t.prototype._createBlurPostProcess=function(e){var n=this;this._blurHPostProcess=new gn("BlurH",new u.d(1,0),16,e,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,h.a.TEXTURETYPE_UNSIGNED_INT),this._blurVPostProcess=new gn("BlurV",new u.d(0,1),16,e,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,h.a.TEXTURETYPE_UNSIGNED_INT),this._blurHPostProcess.onActivateObservable.add(function(){var i=n._blurHPostProcess.width/n._scene.getEngine().getRenderWidth();n._blurHPostProcess.kernel=16*i}),this._blurVPostProcess.onActivateObservable.add(function(){var i=n._blurVPostProcess.height/n._scene.getEngine().getRenderHeight();n._blurVPostProcess.kernel=16*i})},t.prototype._rebuild=function(){this._firstUpdate=!0,r.prototype._rebuild.call(this)},t.prototype._createSSAOPostProcess=function(e){var n=this,i=[.5381,.1856,-.4319,.1379,.2486,.443,.3371,.5679,-.0057,-.6999,-.0451,-.0019,.0689,-.1598,-.8547,.056,.0069,-.1843,-.0146,.1402,.0762,.01,-.1924,-.0344,-.3577,-.5301,-.4358,-.3169,.1063,.0158,.0103,-.5869,.0046,-.0897,-.494,.3287,.7119,-.0154,-.0918,-.0533,.0596,-.5411,.0352,-.0631,.546,-.4776,.2847,-.0271];this._ssaoPostProcess=new _t("ssao","ssao",["sampleSphere","samplesFactor","randTextureTiles","totalStrength","radius","area","fallOff","base","range","viewport"],["randomSampler"],e,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1,`#define SAMPLES 16
-#define SSAO`),this._ssaoPostProcess.onApply=function(o){n._firstUpdate&&(o.setArray3("sampleSphere",i),o.setFloat("samplesFactor",1/16),o.setFloat("randTextureTiles",4)),o.setFloat("totalStrength",n.totalStrength),o.setFloat("radius",n.radius),o.setFloat("area",n.area),o.setFloat("fallOff",n.fallOff),o.setFloat("base",n.base),o.setTexture("textureSampler",n._depthTexture),o.setTexture("randomSampler",n._randomTexture)}},t.prototype._createSSAOCombinePostProcess=function(e){var n=this;this._ssaoCombinePostProcess=new _t("ssaoCombine","ssaoCombine",[],["originalColor","viewport"],e,null,we.a.BILINEAR_SAMPLINGMODE,this._scene.getEngine(),!1),this._ssaoCombinePostProcess.onApply=function(i){i.setVector4("viewport",u.c.Vector4[0].copyFromFloats(0,0,1,1)),i.setTextureFromPostProcess("originalColor",n._originalColorPostProcess)}},t.prototype._createRandomTexture=function(){this._randomTexture=new Ti.a("SSAORandomTexture",512,this._scene,!1,we.a.TRILINEAR_SAMPLINGMODE),this._randomTexture.wrapU=we.a.WRAP_ADDRESSMODE,this._randomTexture.wrapV=we.a.WRAP_ADDRESSMODE;for(var e=this._randomTexture.getContext(),n=function(s,d){return Math.random()*(d-s)+s},i=u.e.Zero(),o=0;o<512;o++)for(var a=0;a<512;a++)i.x=Math.floor(255*n(-1,1)),i.y=Math.floor(255*n(-1,1)),i.z=Math.floor(255*n(-1,1)),e.fillStyle="rgb("+i.x+", "+i.y+", "+i.z+")",e.fillRect(o,a,1,1);this._randomTexture.update(!1)},Object(c.c)([Object(L.c)()],t.prototype,"totalStrength",void 0),Object(c.c)([Object(L.c)()],t.prototype,"radius",void 0),Object(c.c)([Object(L.c)()],t.prototype,"area",void 0),Object(c.c)([Object(L.c)()],t.prototype,"fallOff",void 0),Object(c.c)([Object(L.c)()],t.prototype,"base",void 0),t}(Vr),Ag=function(){this.enabled=!1,this.name="screenSpaceReflections",this.texturesRequired=[h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE,h.a.PREPASS_REFLECTIVITY_TEXTURE_TYPE,h.a.PREPASS_POSITION_TEXTURE_TYPE]},Pg=`
-
-uniform sampler2D textureSampler;
-uniform sampler2D normalSampler;
-uniform sampler2D positionSampler;
-uniform sampler2D reflectivitySampler;
-uniform mat4 view;
-uniform mat4 projection;
-uniform float step;
-uniform float strength;
-uniform float threshold;
-uniform float roughnessFactor;
-uniform float reflectionSpecularFalloffExponent;
-
-varying vec2 vUV;
-
-struct ReflectionInfo {
-vec3 color;
-vec4 coords;
-};
-
-vec3 fresnelSchlick(float cosTheta,vec3 F0)
-{
-return F0+(1.0-F0)*pow(1.0-cosTheta,5.0);
-}
-
-ReflectionInfo smoothReflectionInfo(vec3 dir,vec3 hitCoord)
-{
-ReflectionInfo info;
-info.color=vec3(0.0);
-vec4 projectedCoord;
-float sampledDepth;
-for(int i=0; i<SMOOTH_STEPS; i++)
-{
-projectedCoord=projection*vec4(hitCoord,1.0);
-projectedCoord.xy/=projectedCoord.w;
-projectedCoord.xy=0.5*projectedCoord.xy+vec2(0.5);
-sampledDepth=(view*texture2D(positionSampler,projectedCoord.xy)).z;
-float depth=sampledDepth-hitCoord.z;
-dir*=0.5;
-if(depth>0.0)
-hitCoord-=dir;
-else
-hitCoord+=dir;
-info.color+=texture2D(textureSampler,projectedCoord.xy).rgb;
-}
-projectedCoord=projection*vec4(hitCoord,1.0);
-projectedCoord.xy/=projectedCoord.w;
-projectedCoord.xy=0.5*projectedCoord.xy+vec2(0.5);
-
-info.coords=vec4(projectedCoord.xy,sampledDepth,1.0);
-info.color+=texture2D(textureSampler,projectedCoord.xy).rgb;
-info.color/=float(SMOOTH_STEPS+1);
-return info;
-}
-
-ReflectionInfo getReflectionInfo(vec3 dir,vec3 hitCoord)
-{
-ReflectionInfo info;
-vec4 projectedCoord;
-float sampledDepth;
-dir*=step;
-for(int i=0; i<REFLECTION_SAMPLES; i++)
-{
-hitCoord+=dir;
-projectedCoord=projection*vec4(hitCoord,1.0);
-projectedCoord.xy/=projectedCoord.w;
-projectedCoord.xy=0.5*projectedCoord.xy+vec2(0.5);
-sampledDepth=(view*texture2D(positionSampler,projectedCoord.xy)).z;
-float depth=sampledDepth-hitCoord.z;
-if(((depth-dir.z)<threshold) && depth<=0.0)
-{
-#ifdef ENABLE_SMOOTH_REFLECTIONS
-return smoothReflectionInfo(dir,hitCoord);
-#else
-info.color=texture2D(textureSampler,projectedCoord.xy).rgb;
-info.coords=vec4(projectedCoord.xy,sampledDepth,0.0);
-return info;
-#endif
-}
-}
-info.color=texture2D(textureSampler,projectedCoord.xy).rgb;
-info.coords=vec4(projectedCoord.xy,sampledDepth,0.0);
-return info;
-}
-vec3 hash(vec3 a)
-{
-a=fract(a*0.8);
-a+=dot(a,a.yxz+19.19);
-return fract((a.xxy+a.yxx)*a.zyx);
-}
-void main()
-{
-#ifdef SSR_SUPPORTED
-
-vec4 albedoFull=texture2D(textureSampler,vUV);
-vec3 albedo=albedoFull.rgb;
-float spec=texture2D(reflectivitySampler,vUV).r;
-if (spec == 0.0) {
-gl_FragColor=albedoFull;
-return;
-}
-
-#ifdef PREPASS_LAYOUT
-vec3 normal=(texture2D(normalSampler,vUV)).gba;
-#else
-vec3 normal=(texture2D(normalSampler,vUV)).xyz;
-#endif
-vec3 position=(view*texture2D(positionSampler,vUV)).xyz;
-vec3 reflected=normalize(reflect(normalize(position),normalize(normal)));
-float roughness=1.0-texture2D(reflectivitySampler,vUV).a;
-vec3 jitt=mix(vec3(0.0),hash(position),roughness)*roughnessFactor;
-ReflectionInfo info=getReflectionInfo(jitt+reflected,position);
-
-vec2 dCoords=smoothstep(0.2,0.6,abs(vec2(0.5,0.5)-info.coords.xy));
-float screenEdgefactor=clamp(1.0-(dCoords.x+dCoords.y),0.0,1.0);
-
-vec3 F0=vec3(0.04);
-F0=mix(F0,albedo,spec);
-vec3 fresnel=fresnelSchlick(max(dot(normalize(normal),normalize(position)),0.0),F0);
-
-float reflectionMultiplier=clamp(pow(spec*strength,reflectionSpecularFalloffExponent)*screenEdgefactor*reflected.z,0.0,0.9);
-float albedoMultiplier=1.0-reflectionMultiplier;
-vec3 SSR=info.color*fresnel;
-gl_FragColor=vec4((albedo*albedoMultiplier)+(SSR*reflectionMultiplier),albedoFull.a);
-#else
-gl_FragColor=texture2D(textureSampler,vUV);
-#endif
-}
-`;ze.a.ShadersStore.screenSpaceReflectionPixelShader=Pg;var Wc=function(r){function t(e,n,i,o,a,s,d,p,b,P){p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT),b===void 0&&(b=!1),P===void 0&&(P=!0);var O=r.call(this,e,"screenSpaceReflection",["projection","view","threshold","reflectionSpecularFalloffExponent","strength","step","roughnessFactor"],["textureSampler","normalSampler","positionSampler","reflectivitySampler"],i,o,a,s,d,`#define SSR_SUPPORTED
-#define REFLECTION_SAMPLES 64
-#define SMOOTH_STEPS 5
-`,p,void 0,null,b)||this;if(O.threshold=1.2,O.strength=1,O.reflectionSpecularFalloffExponent=3,O.step=1,O.roughnessFactor=.2,O._forceGeometryBuffer=!1,O._enableSmoothReflections=!1,O._reflectionSamples=64,O._smoothSteps=5,O._forceGeometryBuffer=P,O._forceGeometryBuffer){var B=n.enableGeometryBufferRenderer();B&&B.isSupported&&(B.enablePosition=!0,B.enableReflectivity=!0,O._geometryBufferRenderer=B)}else O._prePassRenderer=n.enablePrePassRenderer(),O._prePassRenderer.markAsDirty(),O._prePassEffectConfiguration=new Ag;return O._updateEffectDefines(),O.onApply=function(F){var z=O._geometryBufferRenderer,J=O._prePassRenderer;if(J||z){if(z){var ie=z.getTextureIndex(li.POSITION_TEXTURE_TYPE),se=z.getTextureIndex(li.REFLECTIVITY_TEXTURE_TYPE);F.setTexture("normalSampler",z.getGBuffer().textures[1]),F.setTexture("positionSampler",z.getGBuffer().textures[ie]),F.setTexture("reflectivitySampler",z.getGBuffer().textures[se])}else{ie=J.getIndex(h.a.PREPASS_POSITION_TEXTURE_TYPE),se=J.getIndex(h.a.PREPASS_REFLECTIVITY_TEXTURE_TYPE);var ce=J.getIndex(h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE);F.setTexture("normalSampler",J.prePassRT.textures[ce]),F.setTexture("positionSampler",J.prePassRT.textures[ie]),F.setTexture("reflectivitySampler",J.prePassRT.textures[se])}var ue=n.activeCamera;if(ue){var fe=ue.getViewMatrix(),ve=ue.getProjectionMatrix();F.setMatrix("projection",ve),F.setMatrix("view",fe),F.setFloat("threshold",O.threshold),F.setFloat("reflectionSpecularFalloffExponent",O.reflectionSpecularFalloffExponent),F.setFloat("strength",O.strength),F.setFloat("step",O.step),F.setFloat("roughnessFactor",O.roughnessFactor)}}},O}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ScreenSpaceReflectionPostProcess"},Object.defineProperty(t.prototype,"enableSmoothReflections",{get:function(){return this._enableSmoothReflections},set:function(e){e!==this._enableSmoothReflections&&(this._enableSmoothReflections=e,this._updateEffectDefines())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"reflectionSamples",{get:function(){return this._reflectionSamples},set:function(e){e!==this._reflectionSamples&&(this._reflectionSamples=e,this._updateEffectDefines())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"smoothSteps",{get:function(){return this._smoothSteps},set:function(e){e!==this._smoothSteps&&(this._smoothSteps=e,this._updateEffectDefines())},enumerable:!1,configurable:!0}),t.prototype._updateEffectDefines=function(){var e=[];(this._geometryBufferRenderer||this._prePassRenderer)&&(e.push("#define SSR_SUPPORTED"),this._prePassRenderer&&e.push("#define PREPASS_LAYOUT")),this._enableSmoothReflections&&e.push("#define ENABLE_SMOOTH_REFLECTIONS"),e.push("#define REFLECTION_SAMPLES "+(this._reflectionSamples>>0)),e.push("#define SMOOTH_STEPS "+(this._smoothSteps>>0)),this.updateEffect(e.join(`
-`))},t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,i,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.textureType,e.reusable)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"threshold",void 0),Object(c.c)([Object(L.c)()],t.prototype,"strength",void 0),Object(c.c)([Object(L.c)()],t.prototype,"reflectionSpecularFalloffExponent",void 0),Object(c.c)([Object(L.c)()],t.prototype,"step",void 0),Object(c.c)([Object(L.c)()],t.prototype,"roughnessFactor",void 0),Object(c.c)([Object(L.c)()],t.prototype,"enableSmoothReflections",null),Object(c.c)([Object(L.c)()],t.prototype,"reflectionSamples",null),Object(c.c)([Object(L.c)()],t.prototype,"smoothSteps",null),t}(_t);R.a.RegisteredTypes["BABYLON.ScreenSpaceReflectionPostProcess"]=Wc;var xg=`uniform sampler2D textureSampler;
-varying vec2 vUV;
-#if defined(PASS_POST_PROCESS)
-void main(void)
-{
-vec4 color=texture2D(textureSampler,vUV);
-gl_FragColor=color;
-}
-#endif
-#if defined(DOWN_SAMPLE_X4)
-uniform vec2 dsOffsets[16];
-void main(void)
-{
-vec4 average=vec4(0.0,0.0,0.0,0.0);
-average=texture2D(textureSampler,vUV+dsOffsets[0]);
-average+=texture2D(textureSampler,vUV+dsOffsets[1]);
-average+=texture2D(textureSampler,vUV+dsOffsets[2]);
-average+=texture2D(textureSampler,vUV+dsOffsets[3]);
-average+=texture2D(textureSampler,vUV+dsOffsets[4]);
-average+=texture2D(textureSampler,vUV+dsOffsets[5]);
-average+=texture2D(textureSampler,vUV+dsOffsets[6]);
-average+=texture2D(textureSampler,vUV+dsOffsets[7]);
-average+=texture2D(textureSampler,vUV+dsOffsets[8]);
-average+=texture2D(textureSampler,vUV+dsOffsets[9]);
-average+=texture2D(textureSampler,vUV+dsOffsets[10]);
-average+=texture2D(textureSampler,vUV+dsOffsets[11]);
-average+=texture2D(textureSampler,vUV+dsOffsets[12]);
-average+=texture2D(textureSampler,vUV+dsOffsets[13]);
-average+=texture2D(textureSampler,vUV+dsOffsets[14]);
-average+=texture2D(textureSampler,vUV+dsOffsets[15]);
-average/=16.0;
-gl_FragColor=average;
-}
-#endif
-#if defined(BRIGHT_PASS)
-uniform vec2 dsOffsets[4];
-uniform float brightThreshold;
-void main(void)
-{
-vec4 average=vec4(0.0,0.0,0.0,0.0);
-average=texture2D(textureSampler,vUV+vec2(dsOffsets[0].x,dsOffsets[0].y));
-average+=texture2D(textureSampler,vUV+vec2(dsOffsets[1].x,dsOffsets[1].y));
-average+=texture2D(textureSampler,vUV+vec2(dsOffsets[2].x,dsOffsets[2].y));
-average+=texture2D(textureSampler,vUV+vec2(dsOffsets[3].x,dsOffsets[3].y));
-average*=0.25;
-float luminance=length(average.rgb);
-if (luminance<brightThreshold) {
-average=vec4(0.0,0.0,0.0,1.0);
-}
-gl_FragColor=average;
-}
-#endif
-#if defined(TEXTURE_ADDER)
-uniform sampler2D otherSampler;
-uniform sampler2D lensSampler;
-uniform float exposure;
-void main(void)
-{
-vec3 colour=texture2D(textureSampler,vUV).rgb;
-colour*=exposure;
-vec3 X=max(vec3(0.0,0.0,0.0),colour-0.004);
-vec3 retColor=(X*(6.2*X+0.5))/(X*(6.2*X+1.7)+0.06);
-colour=retColor*retColor;
-colour+=colour*texture2D(lensSampler,vUV).rgb;
-vec4 finalColor=vec4(colour.rgb,1.0)+texture2D(otherSampler,vUV);
-gl_FragColor=finalColor;
-}
-#endif
-#if defined(VLS)
-#define PI 3.1415926535897932384626433832795
-uniform mat4 shadowViewProjection;
-uniform mat4 lightWorld;
-uniform vec3 cameraPosition;
-uniform vec3 sunDirection;
-uniform vec3 sunColor;
-uniform vec2 depthValues;
-uniform float scatteringCoefficient;
-uniform float scatteringPower;
-uniform sampler2D shadowMapSampler;
-uniform sampler2D positionSampler;
-float computeScattering(float lightDotView)
-{
-float result=1.0-scatteringCoefficient*scatteringCoefficient;
-result/=(4.0*PI*pow(1.0+scatteringCoefficient*scatteringCoefficient-(2.0*scatteringCoefficient)*lightDotView,1.5));
-return result;
-}
-void main(void)
-{
-
-vec3 worldPos=texture2D(positionSampler,vUV).rgb;
-vec3 startPosition=cameraPosition;
-vec3 rayVector=worldPos-startPosition;
-float rayLength=length(rayVector);
-vec3 rayDirection=rayVector/rayLength;
-float stepLength=rayLength/NB_STEPS;
-vec3 stepL=rayDirection*stepLength;
-vec3 currentPosition=startPosition;
-vec3 accumFog=vec3(0.0);
-for (int i=0; i<int(NB_STEPS); i++)
-{
-vec4 worldInShadowCameraSpace=shadowViewProjection*vec4(currentPosition,1.0);
-float depthMetric=(worldInShadowCameraSpace.z+depthValues.x)/(depthValues.y);
-float shadowPixelDepth=clamp(depthMetric,0.0,1.0);
-worldInShadowCameraSpace.xyz/=worldInShadowCameraSpace.w;
-worldInShadowCameraSpace.xyz=0.5*worldInShadowCameraSpace.xyz+vec3(0.5);
-float shadowMapValue=texture2D(shadowMapSampler,worldInShadowCameraSpace.xy).r;
-if (shadowMapValue>shadowPixelDepth)
-accumFog+=sunColor*computeScattering(dot(rayDirection,sunDirection));
-currentPosition+=stepL;
-}
-accumFog/=NB_STEPS;
-vec3 color=accumFog*scatteringPower;
-gl_FragColor=vec4(color*exp(color) ,1.0);
-}
-#endif
-#if defined(VLSMERGE)
-uniform sampler2D originalSampler;
-void main(void)
-{
-gl_FragColor=texture2D(originalSampler,vUV)+texture2D(textureSampler,vUV);
-}
-#endif
-#if defined(LUMINANCE)
-uniform vec2 lumOffsets[4];
-void main()
-{
-float average=0.0;
-vec4 color=vec4(0.0);
-float maximum=-1e20;
-vec3 weight=vec3(0.299,0.587,0.114);
-for (int i=0; i<4; i++)
-{
-color=texture2D(textureSampler,vUV+ lumOffsets[i]);
-
-float GreyValue=dot(color.rgb,vec3(0.33,0.33,0.33));
-
-#ifdef WEIGHTED_AVERAGE
-float GreyValue=dot(color.rgb,weight);
-#endif
-#ifdef BRIGHTNESS
-float GreyValue=max(color.r,max(color.g,color.b));
-#endif
-#ifdef HSL_COMPONENT
-float GreyValue=0.5*(max(color.r,max(color.g,color.b))+min(color.r,min(color.g,color.b)));
-#endif
-#ifdef MAGNITUDE
-float GreyValue=length(color.rgb);
-#endif
-maximum=max(maximum,GreyValue);
-average+=(0.25*log(1e-5+GreyValue));
-}
-average=exp(average);
-gl_FragColor=vec4(average,maximum,0.0,1.0);
-}
-#endif
-#if defined(LUMINANCE_DOWN_SAMPLE)
-uniform vec2 dsOffsets[9];
-uniform float halfDestPixelSize;
-#ifdef FINAL_DOWN_SAMPLER
-#include<packingFunctions>
-#endif
-void main()
-{
-vec4 color=vec4(0.0);
-float average=0.0;
-for (int i=0; i<9; i++)
-{
-color=texture2D(textureSampler,vUV+vec2(halfDestPixelSize,halfDestPixelSize)+dsOffsets[i]);
-average+=color.r;
-}
-average/=9.0;
-#ifdef FINAL_DOWN_SAMPLER
-gl_FragColor=pack(average);
-#else
-gl_FragColor=vec4(average,average,0.0,1.0);
-#endif
-}
-#endif
-#if defined(HDR)
-uniform sampler2D textureAdderSampler;
-uniform float averageLuminance;
-void main()
-{
-vec4 color=texture2D(textureAdderSampler,vUV);
-#ifndef AUTO_EXPOSURE
-vec4 adjustedColor=color/averageLuminance;
-color=adjustedColor;
-color.a=1.0;
-#endif
-gl_FragColor=color;
-}
-#endif
-#if defined(LENS_FLARE)
-#define GHOSTS 3
-uniform sampler2D lensColorSampler;
-uniform float strength;
-uniform float ghostDispersal;
-uniform float haloWidth;
-uniform vec2 resolution;
-uniform float distortionStrength;
-float hash(vec2 p)
-{
-float h=dot(p,vec2(127.1,311.7));
-return -1.0+2.0*fract(sin(h)*43758.5453123);
-}
-float noise(in vec2 p)
-{
-vec2 i=floor(p);
-vec2 f=fract(p);
-vec2 u=f*f*(3.0-2.0*f);
-return mix(mix(hash(i+vec2(0.0,0.0)),
-hash(i+vec2(1.0,0.0)),u.x),
-mix(hash(i+vec2(0.0,1.0)),
-hash(i+vec2(1.0,1.0)),u.x),u.y);
-}
-float fbm(vec2 p)
-{
-float f=0.0;
-f+=0.5000*noise(p); p*=2.02;
-f+=0.2500*noise(p); p*=2.03;
-f+=0.1250*noise(p); p*=2.01;
-f+=0.0625*noise(p); p*=2.04;
-f/=0.9375;
-return f;
-}
-vec3 pattern(vec2 uv)
-{
-vec2 p=-1.0+2.0*uv;
-float p2=dot(p,p);
-float f=fbm(vec2(15.0*p2))/2.0;
-float r=0.2+0.6*sin(12.5*length(uv-vec2(0.5)));
-float g=0.2+0.6*sin(20.5*length(uv-vec2(0.5)));
-float b=0.2+0.6*sin(17.2*length(uv-vec2(0.5)));
-return (1.0-f)*vec3(r,g,b);
-}
-float luminance(vec3 color)
-{
-return dot(color.rgb,vec3(0.2126,0.7152,0.0722));
-}
-vec4 textureDistorted(sampler2D tex,vec2 texcoord,vec2 direction,vec3 distortion)
-{
-return vec4(
-texture2D(tex,texcoord+direction*distortion.r).r,
-texture2D(tex,texcoord+direction*distortion.g).g,
-texture2D(tex,texcoord+direction*distortion.b).b,
-1.0
-);
-}
-void main(void)
-{
-vec2 uv=-vUV+vec2(1.0);
-vec2 ghostDir=(vec2(0.5)-uv)*ghostDispersal;
-vec2 texelSize=1.0/resolution;
-vec3 distortion=vec3(-texelSize.x*distortionStrength,0.0,texelSize.x*distortionStrength);
-vec4 result=vec4(0.0);
-float ghostIndice=1.0;
-for (int i=0; i<GHOSTS; ++i)
-{
-vec2 offset=fract(uv+ghostDir*ghostIndice);
-float weight=length(vec2(0.5)-offset)/length(vec2(0.5));
-weight=pow(1.0-weight,10.0);
-result+=textureDistorted(textureSampler,offset,normalize(ghostDir),distortion)*weight*strength;
-ghostIndice+=1.0;
-}
-vec2 haloVec=normalize(ghostDir)*haloWidth;
-float weight=length(vec2(0.5)-fract(uv+haloVec))/length(vec2(0.5));
-weight=pow(1.0-weight,10.0);
-result+=textureDistorted(textureSampler,fract(uv+haloVec),normalize(ghostDir),distortion)*weight*strength;
-result*=texture2D(lensColorSampler,vec2(length(vec2(0.5)-uv)/length(vec2(0.5))));
-gl_FragColor=result;
-}
-#endif
-#if defined(LENS_FLARE_COMPOSE)
-uniform sampler2D otherSampler;
-uniform sampler2D lensDirtSampler;
-uniform sampler2D lensStarSampler;
-uniform mat4 lensStarMatrix;
-void main(void)
-{
-vec2 lensFlareCoords=(lensStarMatrix*vec4(vUV,1.0,1.0)).xy;
-vec4 lensMod=texture2D(lensDirtSampler,vUV);
-lensMod+=texture2D(lensStarSampler,vUV);
-vec4 result=texture2D(textureSampler,vUV)*lensMod;
-gl_FragColor=texture2D(otherSampler,vUV)+result;
-}
-#endif
-#if defined(DEPTH_OF_FIELD)
-uniform sampler2D otherSampler;
-uniform sampler2D depthSampler;
-uniform float distance;
-void main(void)
-{
-vec4 sharp=texture2D(otherSampler,vUV);
-vec4 blur=texture2D(textureSampler,vUV);
-float dist=clamp(texture2D(depthSampler,vUV).r*distance,0.0,1.0);
-float factor=0.0;
-if (dist<0.05)
-factor=1.0;
-else if (dist<0.1)
-factor=20.0*(0.1-dist);
-else if (dist<0.5)
-factor=0.0;
-else
-factor=2.0*(dist-0.5);
-factor=clamp(factor,0.0,0.90);
-gl_FragColor=mix(sharp,blur,factor);
-}
-#endif
-#if defined(MOTION_BLUR)
-uniform mat4 inverseViewProjection;
-uniform mat4 prevViewProjection;
-uniform vec2 screenSize;
-uniform float motionScale;
-uniform float motionStrength;
-uniform sampler2D depthSampler;
-void main(void)
-{
-vec2 texelSize=1.0/screenSize;
-float depth=texture2D(depthSampler,vUV).r;
-vec4 cpos=vec4(vUV*2.0-1.0,depth,1.0);
-cpos=cpos*inverseViewProjection;
-vec4 ppos=cpos*prevViewProjection;
-ppos.xyz/=ppos.w;
-ppos.xy=ppos.xy*0.5+0.5;
-vec2 velocity=(ppos.xy-vUV)*motionScale*motionStrength;
-float speed=length(velocity/texelSize);
-int nSamples=int(clamp(speed,1.0,MAX_MOTION_SAMPLES));
-vec4 result=texture2D(textureSampler,vUV);
-for (int i=1; i<int(MAX_MOTION_SAMPLES); ++i) {
-if (i>=nSamples)
-break;
-vec2 offset1=vUV+velocity*(float(i)/float(nSamples-1)-0.5);
-result+=texture2D(textureSampler,offset1);
-}
-gl_FragColor=result/float(nSamples);
-}
-#endif
-`;ze.a.ShadersStore.standardPixelShader=xg;var Hd=function(r){function t(e,n,i,o,a){o===void 0&&(o=null);var s=r.call(this,n.getEngine(),e)||this;return s.downSampleX4PostProcess=null,s.brightPassPostProcess=null,s.blurHPostProcesses=[],s.blurVPostProcesses=[],s.textureAdderPostProcess=null,s.volumetricLightPostProcess=null,s.volumetricLightSmoothXPostProcess=null,s.volumetricLightSmoothYPostProcess=null,s.volumetricLightMergePostProces=null,s.volumetricLightFinalPostProcess=null,s.luminancePostProcess=null,s.luminanceDownSamplePostProcesses=[],s.hdrPostProcess=null,s.textureAdderFinalPostProcess=null,s.lensFlareFinalPostProcess=null,s.hdrFinalPostProcess=null,s.lensFlarePostProcess=null,s.lensFlareComposePostProcess=null,s.motionBlurPostProcess=null,s.depthOfFieldPostProcess=null,s.fxaaPostProcess=null,s.screenSpaceReflectionPostProcess=null,s.brightThreshold=1,s.blurWidth=512,s.horizontalBlur=!1,s.lensTexture=null,s.volumetricLightCoefficient=.2,s.volumetricLightPower=4,s.volumetricLightBlurScale=64,s.sourceLight=null,s.hdrMinimumLuminance=1,s.hdrDecreaseRate=.5,s.hdrIncreaseRate=.5,s.lensColorTexture=null,s.lensFlareStrength=20,s.lensFlareGhostDispersal=1.4,s.lensFlareHaloWidth=.7,s.lensFlareDistortionStrength=16,s.lensFlareBlurWidth=512,s.lensStarTexture=null,s.lensFlareDirtTexture=null,s.depthOfFieldDistance=10,s.depthOfFieldBlurWidth=64,s.animations=[],s._currentDepthOfFieldSource=null,s._fixedExposure=1,s._currentExposure=1,s._hdrAutoExposure=!1,s._hdrCurrentLuminance=1,s._motionStrength=1,s._isObjectBasedMotionBlur=!1,s._camerasToBeAttached=[],s._bloomEnabled=!1,s._depthOfFieldEnabled=!1,s._vlsEnabled=!1,s._lensFlareEnabled=!1,s._hdrEnabled=!1,s._motionBlurEnabled=!1,s._fxaaEnabled=!1,s._screenSpaceReflectionsEnabled=!1,s._motionBlurSamples=64,s._volumetricLightStepsCount=50,s._samples=1,s._cameras=a||n.cameras,s._cameras=s._cameras.slice(),s._camerasToBeAttached=s._cameras.slice(),s._scene=n,s._basePostProcess=o,s._ratio=i,s._floatTextureType=n.getEngine().getCaps().textureFloatRender?h.a.TEXTURETYPE_FLOAT:h.a.TEXTURETYPE_HALF_FLOAT,n.postProcessRenderPipelineManager.addPipeline(s),s._buildPipeline(),s}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"exposure",{get:function(){return this._fixedExposure},set:function(e){this._fixedExposure=e,this._currentExposure=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"hdrAutoExposure",{get:function(){return this._hdrAutoExposure},set:function(e){if(this._hdrAutoExposure=e,this.hdrPostProcess){var n=["#define HDR"];e&&n.push("#define AUTO_EXPOSURE"),this.hdrPostProcess.updateEffect(n.join(`
-`))}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"motionStrength",{get:function(){return this._motionStrength},set:function(e){this._motionStrength=e,this._isObjectBasedMotionBlur&&this.motionBlurPostProcess&&(this.motionBlurPostProcess.motionStrength=e)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"objectBasedMotionBlur",{get:function(){return this._isObjectBasedMotionBlur},set:function(e){var n=this._isObjectBasedMotionBlur!==e;this._isObjectBasedMotionBlur=e,n&&this._buildPipeline()},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"BloomEnabled",{get:function(){return this._bloomEnabled},set:function(e){this._bloomEnabled!==e&&(this._bloomEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"DepthOfFieldEnabled",{get:function(){return this._depthOfFieldEnabled},set:function(e){this._depthOfFieldEnabled!==e&&(this._depthOfFieldEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"LensFlareEnabled",{get:function(){return this._lensFlareEnabled},set:function(e){this._lensFlareEnabled!==e&&(this._lensFlareEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"HDREnabled",{get:function(){return this._hdrEnabled},set:function(e){this._hdrEnabled!==e&&(this._hdrEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"VLSEnabled",{get:function(){return this._vlsEnabled},set:function(e){if(this._vlsEnabled!==e){if(e&&!this._scene.enableGeometryBufferRenderer())return void l.a.Warn("Geometry renderer is not supported, cannot create volumetric lights in Standard Rendering Pipeline");this._vlsEnabled=e,this._buildPipeline()}},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"MotionBlurEnabled",{get:function(){return this._motionBlurEnabled},set:function(e){this._motionBlurEnabled!==e&&(this._motionBlurEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"fxaaEnabled",{get:function(){return this._fxaaEnabled},set:function(e){this._fxaaEnabled!==e&&(this._fxaaEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"screenSpaceReflectionsEnabled",{get:function(){return this._screenSpaceReflectionsEnabled},set:function(e){this._screenSpaceReflectionsEnabled!==e&&(this._screenSpaceReflectionsEnabled=e,this._buildPipeline())},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"volumetricLightStepsCount",{get:function(){return this._volumetricLightStepsCount},set:function(e){this.volumetricLightPostProcess&&this.volumetricLightPostProcess.updateEffect(`#define VLS
-#define NB_STEPS `+e.toFixed(1)),this._volumetricLightStepsCount=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"motionBlurSamples",{get:function(){return this._motionBlurSamples},set:function(e){this.motionBlurPostProcess&&(this._isObjectBasedMotionBlur?this.motionBlurPostProcess.motionBlurSamples=e:this.motionBlurPostProcess.updateEffect(`#define MOTION_BLUR
-#define MAX_MOTION_SAMPLES `+e.toFixed(1))),this._motionBlurSamples=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"samples",{get:function(){return this._samples},set:function(e){this._samples!==e&&(this._samples=e,this._buildPipeline())},enumerable:!1,configurable:!0}),t.prototype._buildPipeline=function(){var e=this,n=this._ratio,i=this._scene;this._disposePostProcesses(),this._cameras!==null&&(this._scene.postProcessRenderPipelineManager.detachCamerasFromRenderPipeline(this._name,this._cameras),this._cameras=this._camerasToBeAttached.slice()),this._reset(),this._screenSpaceReflectionsEnabled&&(this.screenSpaceReflectionPostProcess=new Wc("HDRPass",i,n,null,we.a.BILINEAR_SAMPLINGMODE,i.getEngine(),!1,this._floatTextureType),this.screenSpaceReflectionPostProcess.onApplyObservable.add(function(){e._currentDepthOfFieldSource=e.screenSpaceReflectionPostProcess}),this.addEffect(new Rt(i.getEngine(),"HDRScreenSpaceReflections",function(){return e.screenSpaceReflectionPostProcess},!0))),this._basePostProcess?this.originalPostProcess=this._basePostProcess:this.originalPostProcess=new _t("HDRPass","standard",[],[],n,null,we.a.BILINEAR_SAMPLINGMODE,i.getEngine(),!1,"#define PASS_POST_PROCESS",this._floatTextureType),this.originalPostProcess.autoClear=!this.screenSpaceReflectionPostProcess,this.originalPostProcess.onApplyObservable.add(function(){e._currentDepthOfFieldSource=e.originalPostProcess}),this.addEffect(new Rt(i.getEngine(),"HDRPassPostProcess",function(){return e.originalPostProcess},!0)),this._bloomEnabled&&(this._createDownSampleX4PostProcess(i,n/4),this._createBrightPassPostProcess(i,n/4),this._createBlurPostProcesses(i,n/4,1),this._createTextureAdderPostProcess(i,n),this.textureAdderFinalPostProcess=new _t("HDRDepthOfFieldSource","standard",[],[],n,null,we.a.BILINEAR_SAMPLINGMODE,i.getEngine(),!1,"#define PASS_POST_PROCESS",h.a.TEXTURETYPE_UNSIGNED_INT),this.addEffect(new Rt(i.getEngine(),"HDRBaseDepthOfFieldSource",function(){return e.textureAdderFinalPostProcess},!0))),this._vlsEnabled&&(this._createVolumetricLightPostProcess(i,n),this.volumetricLightFinalPostProcess=new _t("HDRVLSFinal","standard",[],[],n,null,we.a.BILINEAR_SAMPLINGMODE,i.getEngine(),!1,"#define PASS_POST_PROCESS",h.a.TEXTURETYPE_UNSIGNED_INT),this.addEffect(new Rt(i.getEngine(),"HDRVLSFinal",function(){return e.volumetricLightFinalPostProcess},!0))),this._lensFlareEnabled&&(this._createLensFlarePostProcess(i,n),this.lensFlareFinalPostProcess=new _t("HDRPostLensFlareDepthOfFieldSource","standard",[],[],n,null,we.a.BILINEAR_SAMPLINGMODE,i.getEngine(),!1,"#define PASS_POST_PROCESS",h.a.TEXTURETYPE_UNSIGNED_INT),this.addEffect(new Rt(i.getEngine(),"HDRPostLensFlareDepthOfFieldSource",function(){return e.lensFlareFinalPostProcess},!0))),this._hdrEnabled&&(this._createLuminancePostProcesses(i,this._floatTextureType),this._createHdrPostProcess(i,n),this.hdrFinalPostProcess=new _t("HDRPostHDReDepthOfFieldSource","standard",[],[],n,null,we.a.BILINEAR_SAMPLINGMODE,i.getEngine(),!1,"#define PASS_POST_PROCESS",h.a.TEXTURETYPE_UNSIGNED_INT),this.addEffect(new Rt(i.getEngine(),"HDRPostHDReDepthOfFieldSource",function(){return e.hdrFinalPostProcess},!0))),this._depthOfFieldEnabled&&(this._createBlurPostProcesses(i,n/2,3,"depthOfFieldBlurWidth"),this._createDepthOfFieldPostProcess(i,n)),this._motionBlurEnabled&&this._createMotionBlurPostProcess(i,n),this._fxaaEnabled&&(this.fxaaPostProcess=new Oo("fxaa",1,null,we.a.BILINEAR_SAMPLINGMODE,i.getEngine(),!1,h.a.TEXTURETYPE_UNSIGNED_INT),this.addEffect(new Rt(i.getEngine(),"HDRFxaa",function(){return e.fxaaPostProcess},!0))),this._cameras!==null&&this._scene.postProcessRenderPipelineManager.attachCamerasToRenderPipeline(this._name,this._cameras),!this._enableMSAAOnFirstPostProcess(this._samples)&&this._samples>1&&l.a.Warn("MSAA failed to enable, MSAA is only supported in browsers that support webGL >= 2.0")},t.prototype._createDownSampleX4PostProcess=function(e,n){var i=this,o=new Array(32);this.downSampleX4PostProcess=new _t("HDRDownSampleX4","standard",["dsOffsets"],[],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define DOWN_SAMPLE_X4",this._floatTextureType),this.downSampleX4PostProcess.onApply=function(a){for(var s=0,d=i.downSampleX4PostProcess.width,p=i.downSampleX4PostProcess.height,b=-2;b<2;b++)for(var P=-2;P<2;P++)o[s]=(b+.5)*(1/d),o[s+1]=(P+.5)*(1/p),s+=2;a.setArray2("dsOffsets",o)},this.addEffect(new Rt(e.getEngine(),"HDRDownSampleX4",function(){return i.downSampleX4PostProcess},!0))},t.prototype._createBrightPassPostProcess=function(e,n){var i=this,o=new Array(8);this.brightPassPostProcess=new _t("HDRBrightPass","standard",["dsOffsets","brightThreshold"],[],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define BRIGHT_PASS",this._floatTextureType),this.brightPassPostProcess.onApply=function(a){var s=1/i.brightPassPostProcess.width,d=1/i.brightPassPostProcess.height;o[0]=-.5*s,o[1]=.5*d,o[2]=.5*s,o[3]=.5*d,o[4]=-.5*s,o[5]=-.5*d,o[6]=.5*s,o[7]=-.5*d,a.setArray2("dsOffsets",o),a.setFloat("brightThreshold",i.brightThreshold)},this.addEffect(new Rt(e.getEngine(),"HDRBrightPass",function(){return i.brightPassPostProcess},!0))},t.prototype._createBlurPostProcesses=function(e,n,i,o){var a=this;o===void 0&&(o="blurWidth");var s=e.getEngine(),d=new gn("HDRBlurH_"+i,new u.d(1,0),this[o],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,this._floatTextureType),p=new gn("HDRBlurV_"+i,new u.d(0,1),this[o],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,this._floatTextureType);d.onActivateObservable.add(function(){var b=d.width/s.getRenderWidth();d.kernel=a[o]*b}),p.onActivateObservable.add(function(){var b=p.height/s.getRenderHeight();p.kernel=a.horizontalBlur?64*b:a[o]*b}),this.addEffect(new Rt(e.getEngine(),"HDRBlurH"+i,function(){return d},!0)),this.addEffect(new Rt(e.getEngine(),"HDRBlurV"+i,function(){return p},!0)),this.blurHPostProcesses.push(d),this.blurVPostProcesses.push(p)},t.prototype._createTextureAdderPostProcess=function(e,n){var i=this;this.textureAdderPostProcess=new _t("HDRTextureAdder","standard",["exposure"],["otherSampler","lensSampler"],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define TEXTURE_ADDER",this._floatTextureType),this.textureAdderPostProcess.onApply=function(o){o.setTextureFromPostProcess("otherSampler",i._vlsEnabled?i._currentDepthOfFieldSource:i.originalPostProcess),o.setTexture("lensSampler",i.lensTexture),o.setFloat("exposure",i._currentExposure),i._currentDepthOfFieldSource=i.textureAdderFinalPostProcess},this.addEffect(new Rt(e.getEngine(),"HDRTextureAdder",function(){return i.textureAdderPostProcess},!0))},t.prototype._createVolumetricLightPostProcess=function(e,n){var i=this,o=e.enableGeometryBufferRenderer();o.enablePosition=!0;var a=o.getGBuffer();this.volumetricLightPostProcess=new _t("HDRVLS","standard",["shadowViewProjection","cameraPosition","sunDirection","sunColor","scatteringCoefficient","scatteringPower","depthValues"],["shadowMapSampler","positionSampler"],n/8,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,`#define VLS
-#define NB_STEPS `+this._volumetricLightStepsCount.toFixed(1));var s=u.d.Zero();this.volumetricLightPostProcess.onApply=function(d){if(i.sourceLight&&i.sourceLight.getShadowGenerator()&&i._scene.activeCamera){var p=i.sourceLight.getShadowGenerator();d.setTexture("shadowMapSampler",p.getShadowMap()),d.setTexture("positionSampler",a.textures[2]),d.setColor3("sunColor",i.sourceLight.diffuse),d.setVector3("sunDirection",i.sourceLight.getShadowDirection()),d.setVector3("cameraPosition",i._scene.activeCamera.globalPosition),d.setMatrix("shadowViewProjection",p.getTransformMatrix()),d.setFloat("scatteringCoefficient",i.volumetricLightCoefficient),d.setFloat("scatteringPower",i.volumetricLightPower),s.x=i.sourceLight.getDepthMinZ(i._scene.activeCamera),s.y=i.sourceLight.getDepthMaxZ(i._scene.activeCamera),d.setVector2("depthValues",s)}},this.addEffect(new Rt(e.getEngine(),"HDRVLS",function(){return i.volumetricLightPostProcess},!0)),this._createBlurPostProcesses(e,n/4,0,"volumetricLightBlurScale"),this.volumetricLightMergePostProces=new _t("HDRVLSMerge","standard",[],["originalSampler"],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define VLSMERGE"),this.volumetricLightMergePostProces.onApply=function(d){d.setTextureFromPostProcess("originalSampler",i._bloomEnabled?i.textureAdderFinalPostProcess:i.originalPostProcess),i._currentDepthOfFieldSource=i.volumetricLightFinalPostProcess},this.addEffect(new Rt(e.getEngine(),"HDRVLSMerge",function(){return i.volumetricLightMergePostProces},!0))},t.prototype._createLuminancePostProcesses=function(e,n){var i=this,o=Math.pow(3,t.LuminanceSteps);this.luminancePostProcess=new _t("HDRLuminance","standard",["lumOffsets"],[],{width:o,height:o},null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define LUMINANCE",n);var a=[];this.luminancePostProcess.onApply=function(P){var O=1/i.luminancePostProcess.width,B=1/i.luminancePostProcess.height;a[0]=-.5*O,a[1]=.5*B,a[2]=.5*O,a[3]=.5*B,a[4]=-.5*O,a[5]=-.5*B,a[6]=.5*O,a[7]=-.5*B,P.setArray2("lumOffsets",a)},this.addEffect(new Rt(e.getEngine(),"HDRLuminance",function(){return i.luminancePostProcess},!0));for(var s=t.LuminanceSteps-1;s>=0;s--){o=Math.pow(3,s);var d=`#define LUMINANCE_DOWN_SAMPLE
-`;s===0&&(d+="#define FINAL_DOWN_SAMPLER");var p=new _t("HDRLuminanceDownSample"+s,"standard",["dsOffsets","halfDestPixelSize"],[],{width:o,height:o},null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,d,n);this.luminanceDownSamplePostProcesses.push(p)}var b=this.luminancePostProcess;this.luminanceDownSamplePostProcesses.forEach(function(P,O){var B=new Array(18);P.onApply=function(F){if(b){for(var z=0,J=-1;J<2;J++)for(var ie=-1;ie<2;ie++)B[z]=J/b.width,B[z+1]=ie/b.height,z+=2;F.setArray2("dsOffsets",B),F.setFloat("halfDestPixelSize",.5/b.width),b=O===i.luminanceDownSamplePostProcesses.length-1?i.luminancePostProcess:P}},O===i.luminanceDownSamplePostProcesses.length-1&&(P.onAfterRender=function(){var F=e.getEngine().readPixels(0,0,1,1),z=new u.f(1/16581375,1/65025,1/255,1);i._hdrCurrentLuminance=(F[0]*z.x+F[1]*z.y+F[2]*z.z+F[3]*z.w)/100}),i.addEffect(new Rt(e.getEngine(),"HDRLuminanceDownSample"+O,function(){return P},!0))})},t.prototype._createHdrPostProcess=function(e,n){var i=this,o=["#define HDR"];this._hdrAutoExposure&&o.push("#define AUTO_EXPOSURE"),this.hdrPostProcess=new _t("HDR","standard",["averageLuminance"],["textureAdderSampler"],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,o.join(`
-`),h.a.TEXTURETYPE_UNSIGNED_INT);var a=1,s=0,d=0;this.hdrPostProcess.onApply=function(p){if(p.setTextureFromPostProcess("textureAdderSampler",i._currentDepthOfFieldSource),s+=e.getEngine().getDeltaTime(),a<0)a=i._hdrCurrentLuminance;else{var b=(d-s)/1e3;i._hdrCurrentLuminance<a+i.hdrDecreaseRate*b?a+=i.hdrDecreaseRate*b:i._hdrCurrentLuminance>a-i.hdrIncreaseRate*b?a-=i.hdrIncreaseRate*b:a=i._hdrCurrentLuminance}i.hdrAutoExposure?i._currentExposure=i._fixedExposure/a:(a=$.a.Clamp(a,i.hdrMinimumLuminance,1e20),p.setFloat("averageLuminance",a)),d=s,i._currentDepthOfFieldSource=i.hdrFinalPostProcess},this.addEffect(new Rt(e.getEngine(),"HDR",function(){return i.hdrPostProcess},!0))},t.prototype._createLensFlarePostProcess=function(e,n){var i=this;this.lensFlarePostProcess=new _t("HDRLensFlare","standard",["strength","ghostDispersal","haloWidth","resolution","distortionStrength"],["lensColorSampler"],n/2,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define LENS_FLARE",h.a.TEXTURETYPE_UNSIGNED_INT),this.addEffect(new Rt(e.getEngine(),"HDRLensFlare",function(){return i.lensFlarePostProcess},!0)),this._createBlurPostProcesses(e,n/4,2,"lensFlareBlurWidth"),this.lensFlareComposePostProcess=new _t("HDRLensFlareCompose","standard",["lensStarMatrix"],["otherSampler","lensDirtSampler","lensStarSampler"],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define LENS_FLARE_COMPOSE",h.a.TEXTURETYPE_UNSIGNED_INT),this.addEffect(new Rt(e.getEngine(),"HDRLensFlareCompose",function(){return i.lensFlareComposePostProcess},!0));var o=new u.d(0,0);this.lensFlarePostProcess.onApply=function(d){d.setTextureFromPostProcess("textureSampler",i._bloomEnabled?i.blurHPostProcesses[0]:i.originalPostProcess),d.setTexture("lensColorSampler",i.lensColorTexture),d.setFloat("strength",i.lensFlareStrength),d.setFloat("ghostDispersal",i.lensFlareGhostDispersal),d.setFloat("haloWidth",i.lensFlareHaloWidth),o.x=i.lensFlarePostProcess.width,o.y=i.lensFlarePostProcess.height,d.setVector2("resolution",o),d.setFloat("distortionStrength",i.lensFlareDistortionStrength)};var a=u.a.FromValues(2,0,-1,0,0,2,-1,0,0,0,1,0,0,0,0,1),s=u.a.FromValues(.5,0,.5,0,0,.5,.5,0,0,0,1,0,0,0,0,1);this.lensFlareComposePostProcess.onApply=function(d){if(i._scene.activeCamera){d.setTextureFromPostProcess("otherSampler",i.lensFlarePostProcess),d.setTexture("lensDirtSampler",i.lensFlareDirtTexture),d.setTexture("lensStarSampler",i.lensStarTexture);var p=i._scene.activeCamera.getViewMatrix().getRow(0),b=i._scene.activeCamera.getViewMatrix().getRow(2),P=u.e.Dot(p.toVector3(),new u.e(1,0,0))+u.e.Dot(b.toVector3(),new u.e(0,0,1));P*=4;var O=u.a.FromValues(.5*Math.cos(P),-Math.sin(P),0,0,Math.sin(P),.5*Math.cos(P),0,0,0,0,1,0,0,0,0,1),B=s.multiply(O).multiply(a);d.setMatrix("lensStarMatrix",B),i._currentDepthOfFieldSource=i.lensFlareFinalPostProcess}}},t.prototype._createDepthOfFieldPostProcess=function(e,n){var i=this;this.depthOfFieldPostProcess=new _t("HDRDepthOfField","standard",["distance"],["otherSampler","depthSampler"],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,"#define DEPTH_OF_FIELD",h.a.TEXTURETYPE_UNSIGNED_INT),this.depthOfFieldPostProcess.onApply=function(o){o.setTextureFromPostProcess("otherSampler",i._currentDepthOfFieldSource),o.setTexture("depthSampler",i._getDepthTexture()),o.setFloat("distance",i.depthOfFieldDistance)},this.addEffect(new Rt(e.getEngine(),"HDRDepthOfField",function(){return i.depthOfFieldPostProcess},!0))},t.prototype._createMotionBlurPostProcess=function(e,n){var i=this;if(this._isObjectBasedMotionBlur){var o=new jc("HDRMotionBlur",e,n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,h.a.TEXTURETYPE_UNSIGNED_INT);o.motionStrength=this.motionStrength,o.motionBlurSamples=this.motionBlurSamples,this.motionBlurPostProcess=o}else{this.motionBlurPostProcess=new _t("HDRMotionBlur","standard",["inverseViewProjection","prevViewProjection","screenSize","motionScale","motionStrength"],["depthSampler"],n,null,we.a.BILINEAR_SAMPLINGMODE,e.getEngine(),!1,`#define MOTION_BLUR
-#define MAX_MOTION_SAMPLES `+this.motionBlurSamples.toFixed(1),h.a.TEXTURETYPE_UNSIGNED_INT);var a=0,s=u.a.Identity(),d=u.a.Identity(),p=u.a.Identity(),b=u.d.Zero();this.motionBlurPostProcess.onApply=function(P){(p=e.getProjectionMatrix().multiply(e.getViewMatrix())).invertToRef(d),P.setMatrix("inverseViewProjection",d),P.setMatrix("prevViewProjection",s),s=p,b.x=i.motionBlurPostProcess.width,b.y=i.motionBlurPostProcess.height,P.setVector2("screenSize",b),a=e.getEngine().getFps()/60,P.setFloat("motionScale",a),P.setFloat("motionStrength",i.motionStrength),P.setTexture("depthSampler",i._getDepthTexture())}}this.addEffect(new Rt(e.getEngine(),"HDRMotionBlur",function(){return i.motionBlurPostProcess},!0))},t.prototype._getDepthTexture=function(){return this._scene.getEngine().getCaps().drawBuffersExtension?this._scene.enableGeometryBufferRenderer().getGBuffer().textures[0]:this._scene.enableDepthRenderer().getDepthMap()},t.prototype._disposePostProcesses=function(){for(var e=0;e<this._cameras.length;e++){var n=this._cameras[e];this.originalPostProcess&&this.originalPostProcess.dispose(n),this.screenSpaceReflectionPostProcess&&this.screenSpaceReflectionPostProcess.dispose(n),this.downSampleX4PostProcess&&this.downSampleX4PostProcess.dispose(n),this.brightPassPostProcess&&this.brightPassPostProcess.dispose(n),this.textureAdderPostProcess&&this.textureAdderPostProcess.dispose(n),this.volumetricLightPostProcess&&this.volumetricLightPostProcess.dispose(n),this.volumetricLightSmoothXPostProcess&&this.volumetricLightSmoothXPostProcess.dispose(n),this.volumetricLightSmoothYPostProcess&&this.volumetricLightSmoothYPostProcess.dispose(n),this.volumetricLightMergePostProces&&this.volumetricLightMergePostProces.dispose(n),this.volumetricLightFinalPostProcess&&this.volumetricLightFinalPostProcess.dispose(n),this.lensFlarePostProcess&&this.lensFlarePostProcess.dispose(n),this.lensFlareComposePostProcess&&this.lensFlareComposePostProcess.dispose(n);for(var i=0;i<this.luminanceDownSamplePostProcesses.length;i++)this.luminanceDownSamplePostProcesses[i].dispose(n);for(this.luminancePostProcess&&this.luminancePostProcess.dispose(n),this.hdrPostProcess&&this.hdrPostProcess.dispose(n),this.hdrFinalPostProcess&&this.hdrFinalPostProcess.dispose(n),this.depthOfFieldPostProcess&&this.depthOfFieldPostProcess.dispose(n),this.motionBlurPostProcess&&this.motionBlurPostProcess.dispose(n),this.fxaaPostProcess&&this.fxaaPostProcess.dispose(n),i=0;i<this.blurHPostProcesses.length;i++)this.blurHPostProcesses[i].dispose(n);for(i=0;i<this.blurVPostProcesses.length;i++)this.blurVPostProcesses[i].dispose(n)}this.originalPostProcess=null,this.downSampleX4PostProcess=null,this.brightPassPostProcess=null,this.textureAdderPostProcess=null,this.textureAdderFinalPostProcess=null,this.volumetricLightPostProcess=null,this.volumetricLightSmoothXPostProcess=null,this.volumetricLightSmoothYPostProcess=null,this.volumetricLightMergePostProces=null,this.volumetricLightFinalPostProcess=null,this.lensFlarePostProcess=null,this.lensFlareComposePostProcess=null,this.luminancePostProcess=null,this.hdrPostProcess=null,this.hdrFinalPostProcess=null,this.depthOfFieldPostProcess=null,this.motionBlurPostProcess=null,this.fxaaPostProcess=null,this.screenSpaceReflectionPostProcess=null,this.luminanceDownSamplePostProcesses=[],this.blurHPostProcesses=[],this.blurVPostProcesses=[]},t.prototype.dispose=function(){this._disposePostProcesses(),this._scene.postProcessRenderPipelineManager.detachCamerasFromRenderPipeline(this._name,this._cameras),r.prototype.dispose.call(this)},t.prototype.serialize=function(){var e=L.a.Serialize(this);return this.sourceLight&&(e.sourceLightId=this.sourceLight.id),this.screenSpaceReflectionPostProcess&&(e.screenSpaceReflectionPostProcess=L.a.Serialize(this.screenSpaceReflectionPostProcess)),e.customType="StandardRenderingPipeline",e},t.Parse=function(e,n,i){var o=L.a.Parse(function(){return new t(e._name,n,e._ratio)},e,n,i);return e.sourceLightId&&(o.sourceLight=n.getLightByID(e.sourceLightId)),e.screenSpaceReflectionPostProcess&&L.a.Parse(function(){return o.screenSpaceReflectionPostProcess},e.screenSpaceReflectionPostProcess,n,i),o},t.LuminanceSteps=6,Object(c.c)([Object(L.c)()],t.prototype,"brightThreshold",void 0),Object(c.c)([Object(L.c)()],t.prototype,"blurWidth",void 0),Object(c.c)([Object(L.c)()],t.prototype,"horizontalBlur",void 0),Object(c.c)([Object(L.c)()],t.prototype,"exposure",null),Object(c.c)([Object(L.m)("lensTexture")],t.prototype,"lensTexture",void 0),Object(c.c)([Object(L.c)()],t.prototype,"volumetricLightCoefficient",void 0),Object(c.c)([Object(L.c)()],t.prototype,"volumetricLightPower",void 0),Object(c.c)([Object(L.c)()],t.prototype,"volumetricLightBlurScale",void 0),Object(c.c)([Object(L.c)()],t.prototype,"hdrMinimumLuminance",void 0),Object(c.c)([Object(L.c)()],t.prototype,"hdrDecreaseRate",void 0),Object(c.c)([Object(L.c)()],t.prototype,"hdrIncreaseRate",void 0),Object(c.c)([Object(L.c)()],t.prototype,"hdrAutoExposure",null),Object(c.c)([Object(L.m)("lensColorTexture")],t.prototype,"lensColorTexture",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lensFlareStrength",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lensFlareGhostDispersal",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lensFlareHaloWidth",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lensFlareDistortionStrength",void 0),Object(c.c)([Object(L.c)()],t.prototype,"lensFlareBlurWidth",void 0),Object(c.c)([Object(L.m)("lensStarTexture")],t.prototype,"lensStarTexture",void 0),Object(c.c)([Object(L.m)("lensFlareDirtTexture")],t.prototype,"lensFlareDirtTexture",void 0),Object(c.c)([Object(L.c)()],t.prototype,"depthOfFieldDistance",void 0),Object(c.c)([Object(L.c)()],t.prototype,"depthOfFieldBlurWidth",void 0),Object(c.c)([Object(L.c)()],t.prototype,"motionStrength",null),Object(c.c)([Object(L.c)()],t.prototype,"objectBasedMotionBlur",null),Object(c.c)([Object(L.c)()],t.prototype,"_ratio",void 0),Object(c.c)([Object(L.c)()],t.prototype,"BloomEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"DepthOfFieldEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"LensFlareEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"HDREnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"VLSEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"MotionBlurEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"fxaaEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"screenSpaceReflectionsEnabled",null),Object(c.c)([Object(L.c)()],t.prototype,"volumetricLightStepsCount",null),Object(c.c)([Object(L.c)()],t.prototype,"motionBlurSamples",null),Object(c.c)([Object(L.c)()],t.prototype,"samples",null),t}(Vr);R.a.RegisteredTypes["BABYLON.StandardRenderingPipeline"]=Hd;var Cg=`const vec3 TWO=vec3(2.0,2.0,2.0);
-varying vec2 vUV;
-uniform sampler2D camASampler;
-uniform sampler2D textureSampler;
-uniform vec2 stepSize;
-void main(void)
-{
-bool useCamA;
-bool useCamB;
-vec2 texCoord1;
-vec2 texCoord2;
-vec3 frag1;
-vec3 frag2;
-#ifdef IS_STEREOSCOPIC_HORIZ
-useCamB=vUV.x>0.5;
-useCamA=!useCamB;
-texCoord1=vec2(useCamB ? (vUV.x-0.5)*2.0 : vUV.x*2.0,vUV.y);
-texCoord2=vec2(texCoord1.x+stepSize.x,vUV.y);
-#else
-#ifdef IS_STEREOSCOPIC_INTERLACED
-float rowNum=floor(vUV.y/stepSize.y);
-useCamA=mod(rowNum,2.0) == 1.0;
-useCamB=mod(rowNum,2.0) == 0.0;
-texCoord1=vec2(vUV.x,vUV.y);
-texCoord2=vec2(vUV.x,vUV.y);
-#else
-useCamB=vUV.y>0.5;
-useCamA=!useCamB;
-texCoord1=vec2(vUV.x,useCamB ? (vUV.y-0.5)*2.0 : vUV.y*2.0);
-texCoord2=vec2(vUV.x,texCoord1.y+stepSize.y);
-#endif
-#endif
-
-if (useCamB){
-frag1=texture2D(textureSampler,texCoord1).rgb;
-frag2=texture2D(textureSampler,texCoord2).rgb;
-}else if (useCamA){
-frag1=texture2D(camASampler ,texCoord1).rgb;
-frag2=texture2D(camASampler ,texCoord2).rgb;
-}else {
-discard;
-}
-gl_FragColor=vec4((frag1+frag2)/TWO,1.0);
-}
-`;ze.a.ShadersStore.stereoscopicInterlacePixelShader=Cg;var Rg=function(r){function t(e,n,i,o,a,s,d){var p=r.call(this,e,"stereoscopicInterlace",["stepSize"],["camASampler"],1,n[1],a,s,d,o?"#define IS_STEREOSCOPIC_INTERLACED 1":i?"#define IS_STEREOSCOPIC_HORIZ 1":void 0)||this;return p._passedProcess=n[0]._rigPostProcess,p._stepSize=new u.d(1/p.width,1/p.height),p.onSizeChangedObservable.add(function(){p._stepSize=new u.d(1/p.width,1/p.height)}),p.onApplyObservable.add(function(b){b.setTextureFromPostProcess("camASampler",p._passedProcess),b.setFloat2("stepSize",p._stepSize.x,p._stepSize.y)}),p}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"StereoscopicInterlacePostProcessI"},t}(_t),Og=function(r){function t(e,n,i,o,a,s){var d=r.call(this,e,"stereoscopicInterlace",["stepSize"],["camASampler"],1,n[1],o,a,s,i?"#define IS_STEREOSCOPIC_HORIZ 1":void 0)||this;return d._passedProcess=n[0]._rigPostProcess,d._stepSize=new u.d(1/d.width,1/d.height),d.onSizeChangedObservable.add(function(){d._stepSize=new u.d(1/d.width,1/d.height)}),d.onApplyObservable.add(function(p){p.setTextureFromPostProcess("camASampler",d._passedProcess),p.setFloat2("stepSize",d._stepSize.x,d._stepSize.y)}),d}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"StereoscopicInterlacePostProcess"},t}(_t),Mg=`
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-
-uniform float _ExposureAdjustment;
-#if defined(HABLE_TONEMAPPING)
-const float A=0.15;
-const float B=0.50;
-const float C=0.10;
-const float D=0.20;
-const float E=0.02;
-const float F=0.30;
-const float W=11.2;
-#endif
-float Luminance(vec3 c)
-{
-return dot(c,vec3(0.22,0.707,0.071));
-}
-void main(void)
-{
-vec3 colour=texture2D(textureSampler,vUV).rgb;
-#if defined(REINHARD_TONEMAPPING)
-float lum=Luminance(colour.rgb);
-float lumTm=lum*_ExposureAdjustment;
-float scale=lumTm/(1.0+lumTm);
-colour*=scale/lum;
-#elif defined(HABLE_TONEMAPPING)
-colour*=_ExposureAdjustment;
-const float ExposureBias=2.0;
-vec3 x=ExposureBias*colour;
-vec3 curr=((x*(A*x+C*B)+D*E)/(x*(A*x+B)+D*F))-E/F;
-x=vec3(W,W,W);
-vec3 whiteScale=1.0/(((x*(A*x+C*B)+D*E)/(x*(A*x+B)+D*F))-E/F);
-colour=curr*whiteScale;
-#elif defined(OPTIMIZED_HEJIDAWSON_TONEMAPPING)
-colour*=_ExposureAdjustment;
-vec3 X=max(vec3(0.0,0.0,0.0),colour-0.004);
-vec3 retColor=(X*(6.2*X+0.5))/(X*(6.2*X+1.7)+0.06);
-colour=retColor*retColor;
-#elif defined(PHOTOGRAPHIC_TONEMAPPING)
-colour=vec3(1.0,1.0,1.0)-exp2(-_ExposureAdjustment*colour);
-#endif
-gl_FragColor=vec4(colour.rgb,1.0);
-}`;ze.a.ShadersStore.tonemapPixelShader=Mg;var cr;(function(r){r[r.Hable=0]="Hable",r[r.Reinhard=1]="Reinhard",r[r.HejiDawson=2]="HejiDawson",r[r.Photographic=3]="Photographic"})(cr||(cr={}));var Ig=function(r){function t(e,n,i,o,a,s,d){a===void 0&&(a=h.a.TEXTURE_BILINEAR_SAMPLINGMODE),d===void 0&&(d=h.a.TEXTURETYPE_UNSIGNED_INT);var p=r.call(this,e,"tonemap",["_ExposureAdjustment"],null,1,o,a,s,!0,null,d)||this;p._operator=n,p.exposureAdjustment=i;var b="#define ";return p._operator===cr.Hable?b+="HABLE_TONEMAPPING":p._operator===cr.Reinhard?b+="REINHARD_TONEMAPPING":p._operator===cr.HejiDawson?b+="OPTIMIZED_HEJIDAWSON_TONEMAPPING":p._operator===cr.Photographic&&(b+="PHOTOGRAPHIC_TONEMAPPING"),p.updateEffect(b),p.onApply=function(P){P.setFloat("_ExposureAdjustment",p.exposureAdjustment)},p}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"TonemapPostProcess"},t}(_t),Dg=`uniform sampler2D textureSampler;
-uniform sampler2D lightScatteringSampler;
-uniform float decay;
-uniform float exposure;
-uniform float weight;
-uniform float density;
-uniform vec2 meshPositionOnScreen;
-varying vec2 vUV;
-void main(void) {
-vec2 tc=vUV;
-vec2 deltaTexCoord=(tc-meshPositionOnScreen.xy);
-deltaTexCoord*=1.0/float(NUM_SAMPLES)*density;
-float illuminationDecay=1.0;
-vec4 color=texture2D(lightScatteringSampler,tc)*0.4;
-for(int i=0; i<NUM_SAMPLES; i++) {
-tc-=deltaTexCoord;
-vec4 dataSample=texture2D(lightScatteringSampler,tc)*0.4;
-dataSample*=illuminationDecay*weight;
-color+=dataSample;
-illuminationDecay*=decay;
-}
-vec4 realColor=texture2D(textureSampler,vUV);
-gl_FragColor=((vec4((vec3(color.r,color.g,color.b)*exposure),1))+(realColor*(1.5-0.4)));
-}
-`;ze.a.ShadersStore.volumetricLightScatteringPixelShader=Dg;var Lg=`
-attribute vec3 position;
-#include<bonesDeclaration>
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-
-#include<instancesDeclaration>
-uniform mat4 viewProjection;
-uniform vec2 depthValues;
-#if defined(ALPHATEST) || defined(NEED_UV)
-varying vec2 vUV;
-uniform mat4 diffuseMatrix;
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#endif
-void main(void)
-{
-vec3 positionUpdated=position;
-#if (defined(ALPHATEST) || defined(NEED_UV)) && defined(UV1)
-vec2 uvUpdated=uv;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-#include<instancesVertex>
-#include<bonesVertex>
-gl_Position=viewProjection*finalWorld*vec4(positionUpdated,1.0);
-#if defined(ALPHATEST) || defined(BASIC_RENDER)
-#ifdef UV1
-vUV=vec2(diffuseMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef UV2
-vUV=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-}
-`;ze.a.ShadersStore.volumetricLightScatteringPassVertexShader=Lg;var Ng=`#if defined(ALPHATEST) || defined(NEED_UV)
-varying vec2 vUV;
-#endif
-#if defined(ALPHATEST)
-uniform sampler2D diffuseSampler;
-#endif
-void main(void)
-{
-#if defined(ALPHATEST)
-vec4 diffuseColor=texture2D(diffuseSampler,vUV);
-if (diffuseColor.a<0.4)
-discard;
-#endif
-gl_FragColor=vec4(0.0,0.0,0.0,1.0);
-}
-`;ze.a.ShadersStore.volumetricLightScatteringPassPixelShader=Ng;var Wd=function(r){function t(e,n,i,o,a,s,d,p,b){a===void 0&&(a=100),s===void 0&&(s=we.a.BILINEAR_SAMPLINGMODE);var P=r.call(this,e,"volumetricLightScattering",["decay","exposure","weight","meshPositionOnScreen","density"],["lightScatteringSampler"],n.postProcessRatio||n,i,s,d,p,"#define NUM_SAMPLES "+a)||this;return P._screenCoordinates=u.d.Zero(),P.customMeshPosition=u.e.Zero(),P.useCustomMeshPosition=!1,P.invert=!0,P.excludedMeshes=new Array,P.exposure=.3,P.decay=.96815,P.weight=.58767,P.density=.926,d=(b=i===null?b:i.getScene()).getEngine(),P._viewPort=new Kn.a(0,0,1,1).toGlobal(d.getRenderWidth(),d.getRenderHeight()),P.mesh=o!==null?o:t.CreateDefaultMesh("VolumetricLightScatteringMesh",b),P._createPass(b,n.passRatio||n),P.onActivate=function(O){P.isSupported||P.dispose(O),P.onActivate=null},P.onApplyObservable.add(function(O){P._updateMeshScreenCoordinates(b),O.setTexture("lightScatteringSampler",P._volumetricLightScatteringRTT),O.setFloat("exposure",P.exposure),O.setFloat("decay",P.decay),O.setFloat("weight",P.weight),O.setFloat("density",P.density),O.setVector2("meshPositionOnScreen",P._screenCoordinates)}),P}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"useDiffuseColor",{get:function(){return l.a.Warn("VolumetricLightScatteringPostProcess.useDiffuseColor is no longer used, use the mesh material directly instead"),!1},set:function(e){l.a.Warn("VolumetricLightScatteringPostProcess.useDiffuseColor is no longer used, use the mesh material directly instead")},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"VolumetricLightScatteringPostProcess"},t.prototype._isReady=function(e,n){var i=e.getMesh();if(i===this.mesh&&i.material)return i.material.isReady(i);var o=[],a=[Oe.b.PositionKind],s=e.getMaterial();s&&(s.needAlphaTesting()&&o.push("#define ALPHATEST"),i.isVerticesDataPresent(Oe.b.UVKind)&&(a.push(Oe.b.UVKind),o.push("#define UV1")),i.isVerticesDataPresent(Oe.b.UV2Kind)&&(a.push(Oe.b.UV2Kind),o.push("#define UV2"))),i.useBones&&i.computeBonesUsingShaders?(a.push(Oe.b.MatricesIndicesKind),a.push(Oe.b.MatricesWeightsKind),o.push("#define NUM_BONE_INFLUENCERS "+i.numBoneInfluencers),o.push("#define BonesPerMesh "+(i.skeleton?i.skeleton.bones.length+1:0))):o.push("#define NUM_BONE_INFLUENCERS 0"),n&&(o.push("#define INSTANCES"),et.a.PushAttributesForInstances(a),e.getRenderingMesh().hasThinInstances&&o.push("#define THIN_INSTANCES"));var d=o.join(`
-`);return this._cachedDefines!==d&&(this._cachedDefines=d,this._volumetricLightScatteringPass=i.getScene().getEngine().createEffect("volumetricLightScatteringPass",a,["world","mBones","viewProjection","diffuseMatrix"],["diffuseSampler"],d,void 0,void 0,void 0,{maxSimultaneousMorphTargets:i.numBoneInfluencers})),this._volumetricLightScatteringPass.isReady()},t.prototype.setCustomMeshPosition=function(e){this.customMeshPosition=e},t.prototype.getCustomMeshPosition=function(){return this.customMeshPosition},t.prototype.dispose=function(e){var n=e.getScene().customRenderTargets.indexOf(this._volumetricLightScatteringRTT);n!==-1&&e.getScene().customRenderTargets.splice(n,1),this._volumetricLightScatteringRTT.dispose(),r.prototype.dispose.call(this,e)},t.prototype.getPass=function(){return this._volumetricLightScatteringRTT},t.prototype._meshExcluded=function(e){return this.excludedMeshes.length>0&&this.excludedMeshes.indexOf(e)!==-1},t.prototype._createPass=function(e,n){var i=this,o=e.getEngine();this._volumetricLightScatteringRTT=new sn("volumetricLightScatteringMap",{width:o.getRenderWidth()*n,height:o.getRenderHeight()*n},e,!1,!0,h.a.TEXTURETYPE_UNSIGNED_INT),this._volumetricLightScatteringRTT.wrapU=we.a.CLAMP_ADDRESSMODE,this._volumetricLightScatteringRTT.wrapV=we.a.CLAMP_ADDRESSMODE,this._volumetricLightScatteringRTT.renderList=null,this._volumetricLightScatteringRTT.renderParticles=!1,this._volumetricLightScatteringRTT.ignoreCameraViewport=!0;var a=this.getCamera();a?a.customRenderTargets.push(this._volumetricLightScatteringRTT):e.customRenderTargets.push(this._volumetricLightScatteringRTT);var s,d=function(b){var P=b.getRenderingMesh(),O=b.getEffectiveMesh();if(!i._meshExcluded(P)){O._internalAbstractMeshDataInfo._isActiveIntermediate=!1;var B=b.getMaterial();if(B){var F=P.getScene(),z=F.getEngine();z.setState(B.backFaceCulling);var J=P._getInstancesRenderList(b._id,!!b.getReplacementMesh());if(!J.mustReturn){var ie=z.getCaps().instancedArrays&&(J.visibleInstances[b._id]!==null||P.hasThinInstances);if(i._isReady(b,ie)){var se=i._volumetricLightScatteringPass;if(P===i.mesh&&(se=b.effect?b.effect:B.getEffect()),z.enableEffect(se),P._bind(b,se,B.fillMode),P===i.mesh)B.bind(O.getWorldMatrix(),P);else{if(i._volumetricLightScatteringPass.setMatrix("viewProjection",F.getTransformMatrix()),B&&B.needAlphaTesting()){var ce=B.getAlphaTestTexture();i._volumetricLightScatteringPass.setTexture("diffuseSampler",ce),ce&&i._volumetricLightScatteringPass.setMatrix("diffuseMatrix",ce.getTextureMatrix())}P.useBones&&P.computeBonesUsingShaders&&P.skeleton&&i._volumetricLightScatteringPass.setMatrices("mBones",P.skeleton.getTransformMatrices(P))}P._processRendering(O,b,i._volumetricLightScatteringPass,Ht.a.TriangleFillMode,J,ie,function(ue,fe){return se.setMatrix("world",fe)})}}}}},p=new M.b(0,0,0,1);this._volumetricLightScatteringRTT.onBeforeRenderObservable.add(function(){s=e.clearColor,e.clearColor=p}),this._volumetricLightScatteringRTT.onAfterRenderObservable.add(function(){e.clearColor=s}),this._volumetricLightScatteringRTT.customRenderFunction=function(b,P,O,B){var F,z=e.getEngine();if(B.length){for(z.setColorWrite(!1),F=0;F<B.length;F++)d(B.data[F]);z.setColorWrite(!0)}for(F=0;F<b.length;F++)d(b.data[F]);for(F=0;F<P.length;F++)d(P.data[F]);if(O.length){for(F=0;F<O.length;F++){var J=O.data[F],ie=J.getBoundingInfo();ie&&e.activeCamera&&(J._alphaIndex=J.getMesh().alphaIndex,J._distanceToCamera=ie.boundingSphere.centerWorld.subtract(e.activeCamera.position).length())}var se=O.data.slice(0,O.length);for(se.sort(function(ce,ue){return ce._alphaIndex>ue._alphaIndex?1:ce._alphaIndex<ue._alphaIndex?-1:ce._distanceToCamera<ue._distanceToCamera?1:ce._distanceToCamera>ue._distanceToCamera?-1:0}),z.setAlphaMode(h.a.ALPHA_COMBINE),F=0;F<se.length;F++)d(se[F]);z.setAlphaMode(h.a.ALPHA_DISABLE)}}},t.prototype._updateMeshScreenCoordinates=function(e){var n,i=e.getTransformMatrix();n=this.useCustomMeshPosition?this.customMeshPosition:this.attachedNode?this.attachedNode.position:this.mesh.parent?this.mesh.getAbsolutePosition():this.mesh.position;var o=u.e.Project(n,u.a.Identity(),i,this._viewPort);this._screenCoordinates.x=o.x/this._viewPort.width,this._screenCoordinates.y=o.y/this._viewPort.height,this.invert&&(this._screenCoordinates.y=1-this._screenCoordinates.y)},t.CreateDefaultMesh=function(e,n){var i=De.a.CreatePlane(e,1,n);i.billboardMode=Dt.a.BILLBOARDMODE_ALL;var o=new Ft.a(e+"Material",n);return o.emissiveColor=new M.a(1,1,1),i.material=o,i},Object(c.c)([Object(L.o)()],t.prototype,"customMeshPosition",void 0),Object(c.c)([Object(L.c)()],t.prototype,"useCustomMeshPosition",void 0),Object(c.c)([Object(L.c)()],t.prototype,"invert",void 0),Object(c.c)([Object(L.k)()],t.prototype,"mesh",void 0),Object(c.c)([Object(L.c)()],t.prototype,"excludedMeshes",void 0),Object(c.c)([Object(L.c)()],t.prototype,"exposure",void 0),Object(c.c)([Object(L.c)()],t.prototype,"decay",void 0),Object(c.c)([Object(L.c)()],t.prototype,"weight",void 0),Object(c.c)([Object(L.c)()],t.prototype,"density",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.VolumetricLightScatteringPostProcess"]=Wd;var wg=`
-
-precision highp float;
-
-varying vec2 vUV;
-uniform sampler2D textureSampler;
-uniform sampler2D normalSampler;
-uniform float curvature_ridge;
-uniform float curvature_valley;
-#ifndef CURVATURE_OFFSET
-#define CURVATURE_OFFSET 1
-#endif
-float curvature_soft_clamp(float curvature,float control)
-{
-if (curvature<0.5/control)
-return curvature*(1.0-curvature*control);
-return 0.25/control;
-}
-float calculate_curvature(ivec2 texel,float ridge,float valley)
-{
-vec2 normal_up=texelFetchOffset(normalSampler,texel,0,ivec2(0,CURVATURE_OFFSET)).rb;
-vec2 normal_down=texelFetchOffset(normalSampler,texel,0,ivec2(0,-CURVATURE_OFFSET)).rb;
-vec2 normal_left=texelFetchOffset(normalSampler,texel,0,ivec2(-CURVATURE_OFFSET,0)).rb;
-vec2 normal_right=texelFetchOffset(normalSampler,texel,0,ivec2( CURVATURE_OFFSET,0)).rb;
-float normal_diff=((normal_up.g-normal_down.g)+(normal_right.r-normal_left.r));
-if (normal_diff<0.0)
-return -2.0*curvature_soft_clamp(-normal_diff,valley);
-return 2.0*curvature_soft_clamp(normal_diff,ridge);
-}
-void main(void)
-{
-ivec2 texel=ivec2(gl_FragCoord.xy);
-vec4 baseColor=texture2D(textureSampler,vUV);
-float curvature=calculate_curvature(texel,curvature_ridge,curvature_valley);
-baseColor.rgb*=curvature+1.0;
-gl_FragColor=baseColor;
-}`;ze.a.ShadersStore.screenSpaceCurvaturePixelShader=wg;var Xd=function(r){function t(e,n,i,o,a,s,d,p,b){p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT),b===void 0&&(b=!1);var P=r.call(this,e,"screenSpaceCurvature",["curvature_ridge","curvature_valley"],["textureSampler","normalSampler"],i,o,a,s,d,void 0,p,void 0,null,b)||this;return P.ridge=1,P.valley=1,P._geometryBufferRenderer=n.enableGeometryBufferRenderer(),P._geometryBufferRenderer?P.onApply=function(O){O.setFloat("curvature_ridge",.5/Math.max(P.ridge*P.ridge,1e-4)),O.setFloat("curvature_valley",.7/Math.max(P.valley*P.valley,1e-4));var B=P._geometryBufferRenderer.getGBuffer().textures[1];O.setTexture("normalSampler",B)}:l.a.Error("Multiple Render Target support needed for screen space curvature post process. Please use IsSupported test first."),P}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"ScreenSpaceCurvaturePostProcess"},Object.defineProperty(t,"IsSupported",{get:function(){var e=te.a.LastCreatedEngine;return!!e&&(e.webGLVersion>1||e.getCaps().drawBuffersExtension)},enumerable:!1,configurable:!0}),t._Parse=function(e,n,i,o){return L.a.Parse(function(){return new t(e.name,i,e.options,n,e.renderTargetSamplingMode,i.getEngine(),e.textureType,e.reusable)},e,i,o)},Object(c.c)([Object(L.c)()],t.prototype,"ridge",void 0),Object(c.c)([Object(L.c)()],t.prototype,"valley",void 0),t}(_t);R.a.RegisteredTypes["BABYLON.ScreenSpaceCurvaturePostProcess"]=Xd,f(166),f(167),Object.defineProperty(_e.a.prototype,"forceShowBoundingBoxes",{get:function(){return this._forceShowBoundingBoxes||!1},set:function(r){this._forceShowBoundingBoxes=r,r&&this.getBoundingBoxRenderer()},enumerable:!0,configurable:!0}),_e.a.prototype.getBoundingBoxRenderer=function(){return this._boundingBoxRenderer||(this._boundingBoxRenderer=new Yd(this)),this._boundingBoxRenderer},Object.defineProperty(Dt.a.prototype,"showBoundingBox",{get:function(){return this._showBoundingBox||!1},set:function(r){this._showBoundingBox=r,r&&this.getScene().getBoundingBoxRenderer()},enumerable:!0,configurable:!0});var Yd=function(){function r(t){this.name=at.a.NAME_BOUNDINGBOXRENDERER,this.frontColor=new M.a(1,1,1),this.backColor=new M.a(.1,.1,.1),this.showBackLines=!0,this.onBeforeBoxRenderingObservable=new C.c,this.onAfterBoxRenderingObservable=new C.c,this.onResourcesReadyObservable=new C.c,this.enabled=!0,this.renderList=new fi.a(32),this._vertexBuffers={},this._fillIndexBuffer=null,this._fillIndexData=null,this.scene=t,t._addComponent(this)}return r.prototype.register=function(){this.scene._beforeEvaluateActiveMeshStage.registerStep(at.a.STEP_BEFOREEVALUATEACTIVEMESH_BOUNDINGBOXRENDERER,this,this.reset),this.scene._preActiveMeshStage.registerStep(at.a.STEP_PREACTIVEMESH_BOUNDINGBOXRENDERER,this,this._preActiveMesh),this.scene._evaluateSubMeshStage.registerStep(at.a.STEP_EVALUATESUBMESH_BOUNDINGBOXRENDERER,this,this._evaluateSubMesh),this.scene._afterRenderingGroupDrawStage.registerStep(at.a.STEP_AFTERRENDERINGGROUPDRAW_BOUNDINGBOXRENDERER,this,this.render)},r.prototype._evaluateSubMesh=function(t,e){if(t.showSubMeshesBoundingBox){var n=e.getBoundingInfo();n!=null&&(n.boundingBox._tag=t.renderingGroupId,this.renderList.push(n.boundingBox))}},r.prototype._preActiveMesh=function(t){if(t.showBoundingBox||this.scene.forceShowBoundingBoxes){var e=t.getBoundingInfo();e.boundingBox._tag=t.renderingGroupId,this.renderList.push(e.boundingBox)}},r.prototype._prepareResources=function(){if(!this._colorShader){this._colorShader=new ua.a("colorShader",this.scene,"color",{attributes:[Oe.b.PositionKind],uniforms:["world","viewProjection","color"]}),this._colorShader.reservedDataStore={hidden:!0};var t=this.scene.getEngine(),e=ft.a.CreateBox({size:1});this._vertexBuffers[Oe.b.PositionKind]=new Oe.b(t,e.positions,Oe.b.PositionKind,!1),this._createIndexBuffer(),this._fillIndexData=e.indices,this.onResourcesReadyObservable.notifyObservers(this)}},r.prototype._createIndexBuffer=function(){var t=this.scene.getEngine();this._indexBuffer=t.createIndexBuffer([0,1,1,2,2,3,3,0,4,5,5,6,6,7,7,4,0,7,1,6,2,5,3,4])},r.prototype.rebuild=function(){var t=this._vertexBuffers[Oe.b.PositionKind];t&&t._rebuild(),this._createIndexBuffer()},r.prototype.reset=function(){this.renderList.reset()},r.prototype.render=function(t){if(this.renderList.length!==0&&this.enabled&&(this._prepareResources(),this._colorShader.isReady())){var e=this.scene.getEngine();e.setDepthWrite(!1),this._colorShader._preBind();for(var n=0;n<this.renderList.length;n++){var i=this.renderList.data[n];if(i._tag===t){this.onBeforeBoxRenderingObservable.notifyObservers(i);var o=i.minimum,a=i.maximum.subtract(o),s=o.add(a.scale(.5)),d=u.a.Scaling(a.x,a.y,a.z).multiply(u.a.Translation(s.x,s.y,s.z)).multiply(i.getWorldMatrix());e.bindBuffers(this._vertexBuffers,this._indexBuffer,this._colorShader.getEffect()),this.showBackLines&&(e.setDepthFunctionToGreaterOrEqual(),this.scene.resetCachedMaterial(),this._colorShader.setColor4("color",this.backColor.toColor4()),this._colorShader.bind(d),e.drawElementsType(Ht.a.LineListDrawMode,0,24)),e.setDepthFunctionToLess(),this.scene.resetCachedMaterial(),this._colorShader.setColor4("color",this.frontColor.toColor4()),this._colorShader.bind(d),e.drawElementsType(Ht.a.LineListDrawMode,0,24),this.onAfterBoxRenderingObservable.notifyObservers(i)}}this._colorShader.unbind(),e.setDepthFunctionToLessOrEqual(),e.setDepthWrite(!0)}},r.prototype.renderOcclusionBoundingBox=function(t){if(this._prepareResources(),this._colorShader.isReady()&&t._boundingInfo){var e=this.scene.getEngine();this._fillIndexBuffer||(this._fillIndexBuffer=e.createIndexBuffer(this._fillIndexData)),e.setDepthWrite(!1),e.setColorWrite(!1),this._colorShader._preBind();var n=t._boundingInfo.boundingBox,i=n.minimum,o=n.maximum.subtract(i),a=i.add(o.scale(.5)),s=u.a.Scaling(o.x,o.y,o.z).multiply(u.a.Translation(a.x,a.y,a.z)).multiply(n.getWorldMatrix());e.bindBuffers(this._vertexBuffers,this._fillIndexBuffer,this._colorShader.getEffect()),e.setDepthFunctionToLess(),this.scene.resetCachedMaterial(),this._colorShader.bind(s),e.drawElementsType(Ht.a.TriangleFillMode,0,36),this._colorShader.unbind(),e.setDepthFunctionToLessOrEqual(),e.setDepthWrite(!0),e.setColorWrite(!0)}},r.prototype.dispose=function(){if(this._colorShader){this.onBeforeBoxRenderingObservable.clear(),this.onAfterBoxRenderingObservable.clear(),this.onResourcesReadyObservable.clear(),this.renderList.dispose(),this._colorShader.dispose();var t=this._vertexBuffers[Oe.b.PositionKind];t&&(t.dispose(),this._vertexBuffers[Oe.b.PositionKind]=null),this.scene.getEngine()._releaseBuffer(this._indexBuffer),this._fillIndexBuffer&&(this.scene.getEngine()._releaseBuffer(this._fillIndexBuffer),this._fillIndexBuffer=null)}},r}();_e.a.prototype.enableDepthRenderer=function(r,t,e){if(t===void 0&&(t=!1),e===void 0&&(e=!1),!(r=r||this.activeCamera))throw"No camera available to enable depth renderer";if(this._depthRenderer||(this._depthRenderer={}),!this._depthRenderer[r.id]){var n=!!this.getEngine().getCaps().textureFloatRender,i=0;i=!this.getEngine().getCaps().textureHalfFloatRender||e&&n?n?h.a.TEXTURETYPE_FLOAT:h.a.TEXTURETYPE_UNSIGNED_BYTE:h.a.TEXTURETYPE_HALF_FLOAT,this._depthRenderer[r.id]=new oa(this,i,r,t)}return this._depthRenderer[r.id]},_e.a.prototype.disableDepthRenderer=function(r){(r=r||this.activeCamera)&&this._depthRenderer&&this._depthRenderer[r.id]&&(this._depthRenderer[r.id].dispose(),delete this._depthRenderer[r.id])};var Kd=function(){function r(t){this.name=at.a.NAME_DEPTHRENDERER,this.scene=t}return r.prototype.register=function(){this.scene._gatherRenderTargetsStage.registerStep(at.a.STEP_GATHERRENDERTARGETS_DEPTHRENDERER,this,this._gatherRenderTargets),this.scene._gatherActiveCameraRenderTargetsStage.registerStep(at.a.STEP_GATHERACTIVECAMERARENDERTARGETS_DEPTHRENDERER,this,this._gatherActiveCameraRenderTargets)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){for(var t in this.scene._depthRenderer)this.scene._depthRenderer[t].dispose()},r.prototype._gatherRenderTargets=function(t){if(this.scene._depthRenderer)for(var e in this.scene._depthRenderer){var n=this.scene._depthRenderer[e];n.enabled&&!n.useOnlyInActiveCamera&&t.push(n.getDepthMap())}},r.prototype._gatherActiveCameraRenderTargets=function(t){if(this.scene._depthRenderer)for(var e in this.scene._depthRenderer){var n=this.scene._depthRenderer[e];n.enabled&&n.useOnlyInActiveCamera&&this.scene.activeCamera.id===e&&t.push(n.getDepthMap())}},r}();oa._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_DEPTHRENDERER);t||(t=new Kd(r),r._addComponent(t))},ze.a.ShadersStore.linePixelShader=`uniform vec4 color;
-void main(void) {
-gl_FragColor=color;
-}`;var Fg=`#include<instancesDeclaration>
-
-attribute vec3 position;
-attribute vec4 normal;
-
-uniform mat4 viewProjection;
-uniform float width;
-uniform float aspectRatio;
-void main(void) {
-#include<instancesVertex>
-mat4 worldViewProjection=viewProjection*finalWorld;
-vec4 viewPosition=worldViewProjection*vec4(position,1.0);
-vec4 viewPositionNext=worldViewProjection*vec4(normal.xyz,1.0);
-vec2 currentScreen=viewPosition.xy/viewPosition.w;
-vec2 nextScreen=viewPositionNext.xy/viewPositionNext.w;
-currentScreen.x*=aspectRatio;
-nextScreen.x*=aspectRatio;
-vec2 dir=normalize(nextScreen-currentScreen);
-vec2 normalDir=vec2(-dir.y,dir.x);
-normalDir*=width/2.0;
-normalDir.x/=aspectRatio;
-vec4 offset=vec4(normalDir*normal.w,0.0,0.0);
-gl_Position=viewPosition+offset;
-}`;ze.a.ShadersStore.lineVertexShader=Fg,Dt.a.prototype.disableEdgesRendering=function(){return this._edgesRenderer&&(this._edgesRenderer.dispose(),this._edgesRenderer=null),this},Dt.a.prototype.enableEdgesRendering=function(r,t,e){return r===void 0&&(r=.95),t===void 0&&(t=!1),this.disableEdgesRendering(),this._edgesRenderer=new Xc(this,r,t,!0,e),this},Object.defineProperty(Dt.a.prototype,"edgesRenderer",{get:function(){return this._edgesRenderer},enumerable:!0,configurable:!0}),So.b.prototype.enableEdgesRendering=function(r,t){return r===void 0&&(r=.95),t===void 0&&(t=!1),this.disableEdgesRendering(),this._edgesRenderer=new Qd(this,r,t),this},So.a.prototype.enableEdgesRendering=function(r,t){return r===void 0&&(r=.95),t===void 0&&(t=!1),So.b.prototype.enableEdgesRendering.apply(this,arguments),this};var Bg=function(){this.edges=new Array,this.edgesConnectedCount=0},Xc=function(){function r(t,e,n,i,o){var a,s=this;e===void 0&&(e=.95),n===void 0&&(n=!1),i===void 0&&(i=!0),this.edgesWidthScalerForOrthographic=1e3,this.edgesWidthScalerForPerspective=50,this._linesPositions=new Array,this._linesNormals=new Array,this._linesIndices=new Array,this._buffers={},this._buffersForInstances={},this._checkVerticesInsteadOfIndices=!1,this.isEnabled=!0,this.customInstances=new fi.a(32),this._source=t,this._checkVerticesInsteadOfIndices=n,this._options=o??null,this._epsilon=e,this._prepareRessources(),i&&((a=o?.useAlternateEdgeFinder)===null||a===void 0||a?this._generateEdgesLinesAlternate():this._generateEdgesLines()),this._meshRebuildObserver=this._source.onRebuildObservable.add(function(){s._rebuild()}),this._meshDisposeObserver=this._source.onDisposeObservable.add(function(){s.dispose()})}return Object.defineProperty(r.prototype,"linesPositions",{get:function(){return this._linesPositions},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"linesNormals",{get:function(){return this._linesNormals},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"linesIndices",{get:function(){return this._linesIndices},enumerable:!1,configurable:!0}),r.GetShader=function(t){if(!t._edgeRenderLineShader){var e=new ua.a("lineShader",t,"line",{attributes:["position","normal"],uniforms:["world","viewProjection","color","width","aspectRatio"]});e.disableDepthWrite=!0,e.backFaceCulling=!1,t._edgeRenderLineShader=e}return t._edgeRenderLineShader},r.prototype._prepareRessources=function(){this._lineShader||(this._lineShader=r.GetShader(this._source.getScene()))},r.prototype._rebuild=function(){var t=this._buffers[Oe.b.PositionKind];t&&t._rebuild(),(t=this._buffers[Oe.b.NormalKind])&&t._rebuild();var e=this._source.getScene().getEngine();this._ib=e.createIndexBuffer(this._linesIndices)},r.prototype.dispose=function(){this._source.onRebuildObservable.remove(this._meshRebuildObserver),this._source.onDisposeObservable.remove(this._meshDisposeObserver);var t=this._buffers[Oe.b.PositionKind];t&&(t.dispose(),this._buffers[Oe.b.PositionKind]=null),(t=this._buffers[Oe.b.NormalKind])&&(t.dispose(),this._buffers[Oe.b.NormalKind]=null),this._ib&&this._source.getScene().getEngine()._releaseBuffer(this._ib),this._lineShader.dispose()},r.prototype._processEdgeForAdjacencies=function(t,e,n,i,o){return t===n&&e===i||t===i&&e===n?0:t===i&&e===o||t===o&&e===i?1:t===o&&e===n||t===n&&e===o?2:-1},r.prototype._processEdgeForAdjacenciesWithVertices=function(t,e,n,i,o){var a=1e-10;return t.equalsWithEpsilon(n,a)&&e.equalsWithEpsilon(i,a)||t.equalsWithEpsilon(i,a)&&e.equalsWithEpsilon(n,a)?0:t.equalsWithEpsilon(i,a)&&e.equalsWithEpsilon(o,a)||t.equalsWithEpsilon(o,a)&&e.equalsWithEpsilon(i,a)?1:t.equalsWithEpsilon(o,a)&&e.equalsWithEpsilon(n,a)||t.equalsWithEpsilon(n,a)&&e.equalsWithEpsilon(o,a)?2:-1},r.prototype._checkEdge=function(t,e,n,i,o){var a;e===void 0?a=!0:a=u.e.Dot(n[t],n[e])<this._epsilon,a&&this.createLine(i,o,this._linesPositions.length/3)},r.prototype.createLine=function(t,e,n){this._linesPositions.push(t.x,t.y,t.z,t.x,t.y,t.z,e.x,e.y,e.z,e.x,e.y,e.z),this._linesNormals.push(e.x,e.y,e.z,-1,e.x,e.y,e.z,1,t.x,t.y,t.z,-1,t.x,t.y,t.z,1),this._linesIndices.push(n,n+1,n+2,n,n+2,n+3)},r.prototype._tessellateTriangle=function(t,e,n,i){var o=function(Ae,Ee,Se){Se>=0&&Ee.push(Se);for(var Le=0;Le<Ae.length;++Le)Ee.push(Ae[Le][0])},a=0;t[1].length>=t[0].length&&t[1].length>=t[2].length?a=1:t[2].length>=t[0].length&&t[2].length>=t[1].length&&(a=2);for(var s=0;s<3;++s)s===a?t[s].sort(function(Ae,Ee){return Ae[1]<Ee[1]?-1:Ae[1]>Ee[1]?1:0}):t[s].sort(function(Ae,Ee){return Ae[1]>Ee[1]?-1:Ae[1]<Ee[1]?1:0});var d=[],p=[];o(t[a],d,-1);for(var b=d.length,P=a+2;P>=a+1;--P)o(t[P%3],p,P!==a+2?i[n[e+(P+1)%3]]:-1);var O=p.length;n.push(i[n[e+a]],d[0],p[0]),n.push(i[n[e+(a+1)%3]],p[O-1],d[b-1]);for(var B=b<=O,F=B?b:O,z=B?O:b,J=B?b-1:O-1,ie=B?0:1,se=b+O-2,ce=0,ue=0,fe=B?d:p,ve=B?p:d,Te=0;se-- >0;){ie?n.push(fe[ce],ve[ue]):n.push(ve[ue],fe[ce]);var Re=void 0;(Te+=F)>=z&&ce<J?(Re=fe[++ce],Te-=z):Re=ve[++ue],n.push(Re)}n[e+0]=n[n.length-3],n[e+1]=n[n.length-2],n[e+2]=n[n.length-1],n.length=n.length-3},r.prototype._generateEdgesLinesAlternate=function(){var t,e,n,i,o,a,s,d,p,b=this._source.getVerticesData(Oe.b.PositionKind),P=this._source.getIndices();if(P&&b){Array.isArray(P)||(P=Xe.b.SliceToArray(P));var O=(e=(t=this._options)===null||t===void 0?void 0:t.useFastVertexMerger)===null||e===void 0||e,B=O?Math.round(-Math.log((i=(n=this._options)===null||n===void 0?void 0:n.epsilonVertexMerge)!==null&&i!==void 0?i:1e-6)/Math.log(10)):(a=(o=this._options)===null||o===void 0?void 0:o.epsilonVertexMerge)!==null&&a!==void 0?a:1e-6,F=[],z=[];if(O)for(var J={},ie=0;ie<b.length;ie+=3){var se=b[ie+0],ce=b[ie+1],ue=b[ie+2];if(J[Mt=se.toFixed(B)+"|"+ce.toFixed(B)+"|"+ue.toFixed(B)]!==void 0)F.push(J[Mt]);else{var fe=ie/3;J[Mt]=fe,F.push(fe),z.push(fe)}}else for(ie=0;ie<b.length;ie+=3){se=b[ie+0],ce=b[ie+1],ue=b[ie+2];for(var ve=!1,Te=0;Te<ie&&!ve;Te+=3){var Re=b[Te+0],Ae=b[Te+1],Ee=b[Te+2];if(Math.abs(se-Re)<B&&Math.abs(ce-Ae)<B&&Math.abs(ue-Ee)<B){F.push(Te/3),ve=!0;break}}ve||(F.push(ie/3),z.push(ie/3))}if(!((s=this._options)===null||s===void 0)&&s.applyTessellation){for(var Se=(p=(d=this._options)===null||d===void 0?void 0:d.epsilonVertexAligned)!==null&&p!==void 0?p:1e-6,Le=[],xe=0;xe<P.length;xe+=3)for(var Ne=void 0,Ie=0;Ie<3;++Ie){var Fe=F[P[xe+Ie]],Ye=F[P[xe+(Ie+1)%3]],tt=F[P[xe+(Ie+2)%3]];if(Fe!==Ye)for(var it=b[3*Fe+0],ut=b[3*Fe+1],Qe=b[3*Fe+2],ot=b[3*Ye+0],rt=b[3*Ye+1],Ze=b[3*Ye+2],dt=Math.sqrt((ot-it)*(ot-it)+(rt-ut)*(rt-ut)+(Ze-Qe)*(Ze-Qe)),Ve=0;Ve<z.length-1;Ve++){var Je=z[Ve];if(Je!==Fe&&Je!==Ye&&Je!==tt){var yt=b[3*Je+0],Wt=b[3*Je+1],Nt=b[3*Je+2],Qt=Math.sqrt((yt-it)*(yt-it)+(Wt-ut)*(Wt-ut)+(Nt-Qe)*(Nt-Qe)),vt=Math.sqrt((yt-ot)*(yt-ot)+(Wt-rt)*(Wt-rt)+(Nt-Ze)*(Nt-Ze));Math.abs(Qt+vt-dt)<Se&&(Ne||(Ne={index:xe,edgesPoints:[[],[],[]]},Le.push(Ne)),Ne.edgesPoints[Ie].push([Je,Qt]))}}}for(var Jt=0;Jt<Le.length;++Jt){var Xt=Le[Jt];this._tessellateTriangle(Xt.edgesPoints,Xt.index,P,F)}Le=null}var zt={};for(xe=0;xe<P.length;xe+=3){var Yt=void 0;for(Ie=0;Ie<3;++Ie)if(Fe=F[P[xe+Ie]],Ye=F[P[xe+(Ie+1)%3]],tt=F[P[xe+(Ie+2)%3]],Fe!==Ye){if(u.c.Vector3[0].copyFromFloats(b[3*Fe+0],b[3*Fe+1],b[3*Fe+2]),u.c.Vector3[1].copyFromFloats(b[3*Ye+0],b[3*Ye+1],b[3*Ye+2]),u.c.Vector3[2].copyFromFloats(b[3*tt+0],b[3*tt+1],b[3*tt+2]),Yt||(u.c.Vector3[1].subtractToRef(u.c.Vector3[0],u.c.Vector3[3]),u.c.Vector3[2].subtractToRef(u.c.Vector3[1],u.c.Vector3[4]),(Yt=u.e.Cross(u.c.Vector3[3],u.c.Vector3[4])).normalize()),Fe>Ye){var Et=Fe;Fe=Ye,Ye=Et}($t=zt[Mt=Fe+"_"+Ye])?$t.done||(u.e.Dot(Yt,$t.normal)<this._epsilon&&this.createLine(u.c.Vector3[0],u.c.Vector3[1],this._linesPositions.length/3),$t.done=!0):zt[Mt]={normal:Yt,done:!1,index:xe,i:Ie}}}for(var Mt in zt){var $t;($t=zt[Mt]).done||(Fe=F[P[$t.index+$t.i]],Ye=F[P[$t.index+($t.i+1)%3]],u.c.Vector3[0].copyFromFloats(b[3*Fe+0],b[3*Fe+1],b[3*Fe+2]),u.c.Vector3[1].copyFromFloats(b[3*Ye+0],b[3*Ye+1],b[3*Ye+2]),this.createLine(u.c.Vector3[0],u.c.Vector3[1],this._linesPositions.length/3))}var Dn=this._source.getScene().getEngine();this._buffers[Oe.b.PositionKind]=new Oe.b(Dn,this._linesPositions,Oe.b.PositionKind,!1),this._buffers[Oe.b.NormalKind]=new Oe.b(Dn,this._linesNormals,Oe.b.NormalKind,!1,!1,4),this._buffersForInstances[Oe.b.PositionKind]=this._buffers[Oe.b.PositionKind],this._buffersForInstances[Oe.b.NormalKind]=this._buffers[Oe.b.NormalKind],this._ib=Dn.createIndexBuffer(this._linesIndices),this._indicesCount=this._linesIndices.length}},r.prototype._generateEdgesLines=function(){var t=this._source.getVerticesData(Oe.b.PositionKind),e=this._source.getIndices();if(e&&t){var n,i,o=new Array,a=new Array;for(n=0;n<e.length;n+=3){i=new Bg;var s=e[n],d=e[n+1],p=e[n+2];i.p0=new u.e(t[3*s],t[3*s+1],t[3*s+2]),i.p1=new u.e(t[3*d],t[3*d+1],t[3*d+2]),i.p2=new u.e(t[3*p],t[3*p+1],t[3*p+2]);var b=u.e.Cross(i.p1.subtract(i.p0),i.p2.subtract(i.p1));b.normalize(),a.push(b),o.push(i)}for(n=0;n<o.length;n++){i=o[n];for(var P=n+1;P<o.length;P++){var O=o[P];if(i.edgesConnectedCount===3)break;if(O.edgesConnectedCount!==3)for(var B=e[3*P],F=e[3*P+1],z=e[3*P+2],J=0;J<3;J++){var ie=0;if(i.edges[J]===void 0){switch(J){case 0:ie=this._checkVerticesInsteadOfIndices?this._processEdgeForAdjacenciesWithVertices(i.p0,i.p1,O.p0,O.p1,O.p2):this._processEdgeForAdjacencies(e[3*n],e[3*n+1],B,F,z);break;case 1:ie=this._checkVerticesInsteadOfIndices?this._processEdgeForAdjacenciesWithVertices(i.p1,i.p2,O.p0,O.p1,O.p2):this._processEdgeForAdjacencies(e[3*n+1],e[3*n+2],B,F,z);break;case 2:ie=this._checkVerticesInsteadOfIndices?this._processEdgeForAdjacenciesWithVertices(i.p2,i.p0,O.p0,O.p1,O.p2):this._processEdgeForAdjacencies(e[3*n+2],e[3*n],B,F,z)}if(ie!==-1&&(i.edges[J]=P,O.edges[ie]=n,i.edgesConnectedCount++,O.edgesConnectedCount++,i.edgesConnectedCount===3))break}}}}for(n=0;n<o.length;n++){var se=o[n];this._checkEdge(n,se.edges[0],a,se.p0,se.p1),this._checkEdge(n,se.edges[1],a,se.p1,se.p2),this._checkEdge(n,se.edges[2],a,se.p2,se.p0)}var ce=this._source.getScene().getEngine();this._buffers[Oe.b.PositionKind]=new Oe.b(ce,this._linesPositions,Oe.b.PositionKind,!1),this._buffers[Oe.b.NormalKind]=new Oe.b(ce,this._linesNormals,Oe.b.NormalKind,!1,!1,4),this._buffersForInstances[Oe.b.PositionKind]=this._buffers[Oe.b.PositionKind],this._buffersForInstances[Oe.b.NormalKind]=this._buffers[Oe.b.NormalKind],this._ib=ce.createIndexBuffer(this._linesIndices),this._indicesCount=this._linesIndices.length}},r.prototype.isReady=function(){return this._lineShader.isReady(this._source,this._source.hasInstances&&this.customInstances.length>0||this._source.hasThinInstances)},r.prototype.render=function(){var t=this._source.getScene();if(this.isReady()&&t.activeCamera){var e=t.getEngine();this._lineShader._preBind(),this._source.edgesColor.a!==1?e.setAlphaMode(h.a.ALPHA_COMBINE):e.setAlphaMode(h.a.ALPHA_DISABLE);var n=this._source.hasInstances&&this.customInstances.length>0,i=n||this._source.hasThinInstances,o=0;if(i)if(this._buffersForInstances.world0=this._source.getVertexBuffer("world0"),this._buffersForInstances.world1=this._source.getVertexBuffer("world1"),this._buffersForInstances.world2=this._source.getVertexBuffer("world2"),this._buffersForInstances.world3=this._source.getVertexBuffer("world3"),n){var a=this._source._instanceDataStorage;if(o=this.customInstances.length,!a.isFrozen){for(var s=0,d=0;d<o;++d)this.customInstances.data[d].copyToArray(a.instancesData,s),s+=16;a.instancesBuffer.updateDirectly(a.instancesData,0,o)}}else o=this._source.thinInstanceCount;e.bindBuffers(i?this._buffersForInstances:this._buffers,this._ib,this._lineShader.getEffect()),t.resetCachedMaterial(),this._lineShader.setColor4("color",this._source.edgesColor),t.activeCamera.mode===gt.a.ORTHOGRAPHIC_CAMERA?this._lineShader.setFloat("width",this._source.edgesWidth/this.edgesWidthScalerForOrthographic):this._lineShader.setFloat("width",this._source.edgesWidth/this.edgesWidthScalerForPerspective),this._lineShader.setFloat("aspectRatio",e.getAspectRatio(t.activeCamera)),this._lineShader.bind(this._source.getWorldMatrix()),e.drawElementsType(Ht.a.TriangleFillMode,0,this._indicesCount,o),this._lineShader.unbind(),i&&e.unbindInstanceAttributes(),this._source.getScene()._activeMeshesFrozen||this.customInstances.reset()}},r}(),Qd=function(r){function t(e,n,i){n===void 0&&(n=.95),i===void 0&&(i=!1);var o=r.call(this,e,n,i,!1)||this;return o._generateEdgesLines(),o}return Object(c.d)(t,r),t.prototype._generateEdgesLines=function(){var e=this._source.getVerticesData(Oe.b.PositionKind),n=this._source.getIndices();if(n&&e){for(var i=u.c.Vector3[0],o=u.c.Vector3[1],a=n.length-1,s=0,d=0;s<a;s+=2,d+=4)u.e.FromArrayToRef(e,3*n[s],i),u.e.FromArrayToRef(e,3*n[s+1],o),this.createLine(i,o,d);var p=this._source.getScene().getEngine();this._buffers[Oe.b.PositionKind]=new Oe.b(p,this._linesPositions,Oe.b.PositionKind,!1),this._buffers[Oe.b.NormalKind]=new Oe.b(p,this._linesNormals,Oe.b.NormalKind,!1,!1,4),this._ib=p.createIndexBuffer(this._linesIndices),this._indicesCount=this._linesIndices.length}},t}(Xc),Yc=function(){function r(t){this._textureFormats=[{type:h.a.PREPASS_IRRADIANCE_TEXTURE_TYPE,format:h.a.TEXTURETYPE_HALF_FLOAT},{type:h.a.PREPASS_POSITION_TEXTURE_TYPE,format:h.a.TEXTURETYPE_HALF_FLOAT},{type:h.a.PREPASS_VELOCITY_TEXTURE_TYPE,format:h.a.TEXTURETYPE_HALF_FLOAT},{type:h.a.PREPASS_REFLECTIVITY_TEXTURE_TYPE,format:h.a.TEXTURETYPE_UNSIGNED_INT},{type:h.a.PREPASS_COLOR_TEXTURE_TYPE,format:h.a.TEXTURETYPE_HALF_FLOAT},{type:h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE,format:h.a.TEXTURETYPE_HALF_FLOAT},{type:h.a.PREPASS_ALBEDO_TEXTURE_TYPE,format:h.a.TEXTURETYPE_UNSIGNED_INT}],this.excludedSkinnedMesh=[],this.excludedMaterials=[],this._textureIndices=[],this._isDirty=!1,this.mrtCount=0,this._postProcesses=[],this._clearColor=new M.b(0,0,0,0),this._effectConfigurations=[],this._mrtFormats=[],this._enabled=!1,this._useGeometryBufferFallback=!1,this.disableGammaTransform=!1,this._scene=t,this._engine=t.getEngine(),r._SceneComponentInitialization(this._scene),this._resetLayout()}return Object.defineProperty(r.prototype,"enabled",{get:function(){return this._enabled},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"samples",{get:function(){return this.prePassRT.samples},set:function(t){this.imageProcessingPostProcess||this._createCompositionEffect(),this.prePassRT.samples=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"useGeometryBufferFallback",{get:function(){return this._useGeometryBufferFallback},set:function(t){if(this._useGeometryBufferFallback=t,t){if(this._geometryBuffer=this._scene.enableGeometryBufferRenderer(),!this._geometryBuffer)return void(this._useGeometryBufferFallback=!1);this._geometryBuffer.renderList=[],this._geometryBuffer._linkPrePassRenderer(this),this._updateGeometryBufferLayout()}else this._geometryBuffer&&this._geometryBuffer._unlinkPrePassRenderer(),this._geometryBuffer=null,this._scene.disableGeometryBufferRenderer()},enumerable:!1,configurable:!0}),r.prototype._initializeAttachments=function(){for(var t=[],e=[!1],n=[!0],i=0;i<this.mrtCount;i++)t.push(!0),i>0&&(e.push(!0),n.push(!1));this._multiRenderAttachments=this._engine.buildTextureLayout(t),this._clearAttachments=this._engine.buildTextureLayout(e),this._defaultAttachments=this._engine.buildTextureLayout(n)},r.prototype._createCompositionEffect=function(){this.prePassRT=new Js("sceneprePassRT",{width:this._engine.getRenderWidth(),height:this._engine.getRenderHeight()},this.mrtCount,this._scene,{generateMipMaps:!1,generateDepthTexture:!0,defaultType:h.a.TEXTURETYPE_UNSIGNED_INT,types:this._mrtFormats}),this.prePassRT.samples=1,this._initializeAttachments(),this._useGeometryBufferFallback&&!this._geometryBuffer&&(this.useGeometryBufferFallback=!0),this.imageProcessingPostProcess=new Go("sceneCompositionPass",1,null,void 0,this._engine),this.imageProcessingPostProcess.autoClear=!1},Object.defineProperty(r.prototype,"isSupported",{get:function(){return this._engine.webGLVersion>1||this._scene.getEngine().getCaps().drawBuffersExtension},enumerable:!1,configurable:!0}),r.prototype.bindAttachmentsForEffect=function(t,e){if(this.enabled){if(t._multiTarget)this._engine.bindAttachments(this._multiRenderAttachments);else if(this._engine.bindAttachments(this._defaultAttachments),this._geometryBuffer){var n=e.getMaterial();n&&this.excludedMaterials.indexOf(n)===-1&&this._geometryBuffer.renderList.push(e.getRenderingMesh())}}},r.prototype.restoreAttachments=function(){this.enabled&&this._defaultAttachments&&this._engine.bindAttachments(this._defaultAttachments)},r.prototype._beforeCameraDraw=function(){this._isDirty&&this._update(),this._geometryBuffer&&(this._geometryBuffer.renderList.length=0),this._bindFrameBuffer()},r.prototype._afterCameraDraw=function(){if(this._enabled){var t=this._scene.activeCamera&&this._scene.activeCamera._getFirstPostProcess();t&&this._postProcesses.length&&this._scene.postProcessManager._prepareFrame(),this._scene.postProcessManager.directRender(this._postProcesses,t?t.inputTexture:null)}},r.prototype._checkRTSize=function(){var t=this._engine.getRenderWidth(!0),e=this._engine.getRenderHeight(!0),n=this.prePassRT.getRenderWidth(),i=this.prePassRT.getRenderHeight();n===t&&i===e||(this.prePassRT.resize({width:t,height:e}),this._updateGeometryBufferLayout(),this._bindPostProcessChain())},r.prototype._bindFrameBuffer=function(){if(this._enabled){this._checkRTSize();var t=this.prePassRT.getInternalTexture();t&&this._engine.bindFramebuffer(t)}},r.prototype.clear=function(){this._enabled&&(this._bindFrameBuffer(),this._engine.clear(this._scene.clearColor,this._scene.autoClear||this._scene.forceWireframe||this._scene.forcePointsCloud,this._scene.autoClearDepthAndStencil,this._scene.autoClearDepthAndStencil),this._engine.bindAttachments(this._clearAttachments),this._engine.clear(this._clearColor,!0,!1,!1),this._engine.bindAttachments(this._defaultAttachments))},r.prototype._setState=function(t){this._enabled=t,this._scene.prePass=t,this.imageProcessingPostProcess&&(this.imageProcessingPostProcess.imageProcessingConfiguration.applyByPostProcess=t)},r.prototype._updateGeometryBufferLayout=function(){if(this._geometryBuffer){this._geometryBuffer._resetLayout();for(var t=[],e=0;e<this._mrtLayout.length;e++)t.push(!1);this._geometryBuffer._linkInternalTexture(this.prePassRT.getInternalTexture());var n=[{prePassConstant:h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE,geometryBufferConstant:li.DEPTHNORMAL_TEXTURE_TYPE},{prePassConstant:h.a.PREPASS_POSITION_TEXTURE_TYPE,geometryBufferConstant:li.POSITION_TEXTURE_TYPE},{prePassConstant:h.a.PREPASS_REFLECTIVITY_TEXTURE_TYPE,geometryBufferConstant:li.REFLECTIVITY_TEXTURE_TYPE},{prePassConstant:h.a.PREPASS_VELOCITY_TEXTURE_TYPE,geometryBufferConstant:li.VELOCITY_TEXTURE_TYPE}];for(e=0;e<n.length;e++){var i=this._mrtLayout.indexOf(n[e].prePassConstant);i!==-1&&(this._geometryBuffer._forceTextureType(n[e].geometryBufferConstant,i),t[i]=!0)}this._geometryBuffer._setAttachments(this._engine.buildTextureLayout(t))}},r.prototype.addEffectConfiguration=function(t){for(var e=0;e<this._effectConfigurations.length;e++)if(this._effectConfigurations[e].name===t.name)return this._effectConfigurations[e];return this._effectConfigurations.push(t),t},r.prototype.getIndex=function(t){return this._textureIndices[t]},r.prototype._enable=function(){for(var t,e,n=this.mrtCount,i=0;i<this._effectConfigurations.length;i++)this._effectConfigurations[i].enabled&&this._enableTextures(this._effectConfigurations[i].texturesRequired);for(this.prePassRT&&this.mrtCount!==n&&this.prePassRT.updateCount(this.mrtCount,{types:this._mrtFormats}),this._updateGeometryBufferLayout(),this._resetPostProcessChain(),i=0;i<this._effectConfigurations.length;i++)this._effectConfigurations[i].enabled&&(!this._effectConfigurations[i].postProcess&&this._effectConfigurations[i].createPostProcess&&this._effectConfigurations[i].createPostProcess(),this._effectConfigurations[i].postProcess&&this._postProcesses.push(this._effectConfigurations[i].postProcess));this._initializeAttachments(),this.imageProcessingPostProcess||this._createCompositionEffect();var o=!1;if(!((t=this._scene.activeCamera)===null||t===void 0)&&t._postProcesses)for(i=0;i<this._scene.activeCamera._postProcesses.length;i++)((e=this._scene.activeCamera._postProcesses[i])===null||e===void 0?void 0:e.getClassName())==="ImageProcessingPostProcess"&&(o=!0);o||this.disableGammaTransform||this._postProcesses.push(this.imageProcessingPostProcess),this._bindPostProcessChain(),this._setState(!0)},r.prototype._disable=function(){this._setState(!1),this._resetLayout();for(var t=0;t<this._effectConfigurations.length;t++)this._effectConfigurations[t].enabled=!1},r.prototype._resetLayout=function(){for(var t=0;t<this._textureFormats.length;t++)this._textureIndices[this._textureFormats[t].type]=-1;this._textureIndices[h.a.PREPASS_COLOR_TEXTURE_TYPE]=0,this._mrtLayout=[h.a.PREPASS_COLOR_TEXTURE_TYPE],this._mrtFormats=[h.a.TEXTURETYPE_HALF_FLOAT],this.mrtCount=1},r.prototype._resetPostProcessChain=function(){this._postProcesses=[],this.imageProcessingPostProcess&&this.imageProcessingPostProcess.restoreDefaultInputTexture();for(var t=0;t<this._effectConfigurations.length;t++)this._effectConfigurations[t].postProcess&&this._effectConfigurations[t].postProcess.restoreDefaultInputTexture()},r.prototype._bindPostProcessChain=function(){var t;if(this._postProcesses.length)this._postProcesses[0].inputTexture=this.prePassRT.getInternalTexture();else{var e=(t=this._scene.activeCamera)===null||t===void 0?void 0:t._getFirstPostProcess();e&&(e.inputTexture=this.prePassRT.getInternalTexture())}},r.prototype.markAsDirty=function(){this._isDirty=!0},r.prototype._enableTextures=function(t){for(var e=0;e<t.length;e++){var n=t[e];this._textureIndices[n]===-1&&(this._textureIndices[n]=this._mrtLayout.length,this._mrtLayout.push(n),this._mrtFormats.push(this._textureFormats[n].format),this.mrtCount++)}},r.prototype._update=function(){this._disable();for(var t=!1,e=0;e<this._scene.materials.length;e++)this._scene.materials[e].setPrePassRenderer(this)&&(t=!0);var n=this._scene.activeCamera;if(n){var i=n._postProcesses.filter(function(o){return o!=null});if(i)for(e=0;e<i.length;e++)i[e].setPrePassRenderer(this)&&(t=!0);this._markAllMaterialsAsPrePassDirty(),this._isDirty=!1,t&&this._enable(),this.enabled||(this._engine.restoreDefaultFramebuffer(),this._engine.restoreSingleAttachment())}},r.prototype._markAllMaterialsAsPrePassDirty=function(){for(var t=this._scene.materials,e=0;e<t.length;e++)t[e].markAsDirty(Ht.a.PrePassDirtyFlag)},r.prototype.dispose=function(){for(var t=0;t<this._effectConfigurations.length;t++)this._effectConfigurations[t].dispose&&this._effectConfigurations[t].dispose();this.imageProcessingPostProcess.dispose(),this.prePassRT.dispose()},r._SceneComponentInitialization=function(t){throw An.a.WarnImport("PrePassRendererSceneComponent")},r}();Object.defineProperty(_e.a.prototype,"prePassRenderer",{get:function(){return this._prePassRenderer},set:function(r){r&&r.isSupported&&(this._prePassRenderer=r)},enumerable:!0,configurable:!0}),_e.a.prototype.enablePrePassRenderer=function(){return this._prePassRenderer||(this._prePassRenderer=new Yc(this),this._prePassRenderer.isSupported||(this._prePassRenderer=null,l.a.Error(`PrePassRenderer needs WebGL 2 support.
-Maybe you tried to use the following features that need the PrePassRenderer :
- + Subsurface Scattering`))),this._prePassRenderer},_e.a.prototype.disablePrePassRenderer=function(){this._prePassRenderer&&(this._prePassRenderer.dispose(),this._prePassRenderer=null)};var qd=function(){function r(t){this.name=at.a.NAME_PREPASSRENDERER,this.scene=t}return r.prototype.register=function(){this.scene._beforeCameraDrawStage.registerStep(at.a.STEP_BEFORECAMERADRAW_PREPASS,this,this._beforeCameraDraw),this.scene._afterCameraDrawStage.registerStep(at.a.STEP_AFTERCAMERADRAW_PREPASS,this,this._afterCameraDraw),this.scene._beforeClearStage.registerStep(at.a.STEP_BEFORECLEARSTAGE_PREPASS,this,this._beforeClearStage),this.scene._beforeRenderingMeshStage.registerStep(at.a.STEP_BEFORERENDERINGMESH_PREPASS,this,this._beforeRenderingMeshStage),this.scene._afterRenderingMeshStage.registerStep(at.a.STEP_AFTERRENDERINGMESH_PREPASS,this,this._afterRenderingMeshStage)},r.prototype._beforeCameraDraw=function(){this.scene.prePassRenderer&&this.scene.prePassRenderer._beforeCameraDraw()},r.prototype._afterCameraDraw=function(){this.scene.prePassRenderer&&this.scene.prePassRenderer._afterCameraDraw()},r.prototype._beforeClearStage=function(){this.scene.prePassRenderer&&this.scene.prePassRenderer.clear()},r.prototype._beforeRenderingMeshStage=function(t,e,n,i){if(i){var o=t.getScene();o.prePassRenderer&&o.prePassRenderer.bindAttachmentsForEffect(i,e)}},r.prototype._afterRenderingMeshStage=function(t){var e=t.getScene();e.prePassRenderer&&e.prePassRenderer.restoreAttachments()},r.prototype.rebuild=function(){},r.prototype.dispose=function(){},r}();Yc._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_PREPASSRENDERER);t||(t=new qd(r),r._addComponent(t))};var Ug=`#define rcp(x) 1./x
-#define GOLDEN_RATIO 1.618033988749895
-#define TWO_PI 6.2831855
-
-
-vec2 Golden2dSeq(int i,float n)
-{
-
-
-return vec2(float(i)/n+(0.5/n),fract(float(i)*rcp(GOLDEN_RATIO)));
-}
-vec2 SampleDiskGolden(int i,int sampleCount)
-{
-vec2 f=Golden2dSeq(i,float(sampleCount));
-return vec2(sqrt(f.x),TWO_PI*f.y);
-}`;ze.a.IncludesShadersStore.fibonacci=Ug;var Vg=`uniform vec3 diffusionS[5];
-uniform float diffusionD[5];
-uniform float filterRadii[5];`;ze.a.IncludesShadersStore.diffusionProfile=Vg;var kg=`
-#include<fibonacci>
-#include<helperFunctions>
-#include<subSurfaceScatteringFunctions>
-#include<diffusionProfile>
-varying vec2 vUV;
-uniform vec2 texelSize;
-uniform sampler2D textureSampler;
-uniform sampler2D irradianceSampler;
-uniform sampler2D depthSampler;
-uniform sampler2D albedoSampler;
-uniform vec2 viewportSize;
-uniform float metersPerUnit;
-const float LOG2_E=1.4426950408889634;
-const float SSS_PIXELS_PER_SAMPLE=4.;
-const int _SssSampleBudget=40;
-#define rcp(x) 1./x
-#define Sq(x) x*x
-#define SSS_BILATERAL_FILTER true
-
-
-vec3 EvalBurleyDiffusionProfile(float r,vec3 S)
-{
-vec3 exp_13=exp2(((LOG2_E*(-1.0/3.0))*r)*S);
-vec3 expSum=exp_13*(1.+exp_13*exp_13);
-return (S*rcp(8.*PI))*expSum;
-}
-
-
-
-
-
-
-vec2 SampleBurleyDiffusionProfile(float u,float rcpS)
-{
-u=1.-u;
-float g=1.+(4.*u)*(2.*u+sqrt(1.+(4.*u)*u));
-float n=exp2(log2(g)*(-1.0/3.0));
-float p=(g*n)*n;
-float c=1.+p+n;
-float d=(3./LOG2_E*2.)+(3./LOG2_E)*log2(u);
-float x=(3./LOG2_E)*log2(c)-d;
-
-
-
-
-
-
-float rcpExp=((c*c)*c)*rcp((4.*u)*((c*c)+(4.*u)*(4.*u)));
-float r=x*rcpS;
-float rcpPdf=(8.*PI*rcpS)*rcpExp;
-return vec2(r,rcpPdf);
-}
-
-
-vec3 ComputeBilateralWeight(float xy2,float z,float mmPerUnit,vec3 S,float rcpPdf)
-{
-#ifndef SSS_BILATERAL_FILTER
-z=0.;
-#endif
-
-
-
-float r=sqrt(xy2+(z*mmPerUnit)*(z*mmPerUnit));
-float area=rcpPdf;
-#if SSS_CLAMP_ARTIFACT
-return clamp(EvalBurleyDiffusionProfile(r,S)*area,0.0,1.0);
-#else
-return EvalBurleyDiffusionProfile(r,S)*area;
-#endif
-}
-void EvaluateSample(int i,int n,vec3 S,float d,vec3 centerPosVS,float mmPerUnit,float pixelsPerMm,
-float phase,inout vec3 totalIrradiance,inout vec3 totalWeight)
-{
-
-float scale=rcp(float(n));
-float offset=rcp(float(n))*0.5;
-
-float sinPhase,cosPhase;
-sinPhase=sin(phase);
-cosPhase=cos(phase);
-vec2 bdp=SampleBurleyDiffusionProfile(float(i)*scale+offset,d);
-float r=bdp.x;
-float rcpPdf=bdp.y;
-float phi=SampleDiskGolden(i,n).y;
-float sinPhi,cosPhi;
-sinPhi=sin(phi);
-cosPhi=cos(phi);
-float sinPsi=cosPhase*sinPhi+sinPhase*cosPhi;
-float cosPsi=cosPhase*cosPhi-sinPhase*sinPhi;
-vec2 vec=r*vec2(cosPsi,sinPsi);
-
-vec2 position;
-float xy2;
-position=vUV+round((pixelsPerMm*r)*vec2(cosPsi,sinPsi))*texelSize;
-xy2=r*r;
-vec4 textureSample=texture2D(irradianceSampler,position);
-float viewZ=texture2D(depthSampler,position).r;
-vec3 irradiance=textureSample.rgb;
-if (testLightingForSSS(textureSample.a))
-{
-
-float relZ=viewZ-centerPosVS.z;
-vec3 weight=ComputeBilateralWeight(xy2,relZ,mmPerUnit,S,rcpPdf);
-totalIrradiance+=weight*irradiance;
-totalWeight+=weight;
-}
-else
-{
-
-
-
-
-
-
-}
-}
-void main(void)
-{
-vec4 irradianceAndDiffusionProfile=texture2D(irradianceSampler,vUV);
-vec3 centerIrradiance=irradianceAndDiffusionProfile.rgb;
-int diffusionProfileIndex=int(round(irradianceAndDiffusionProfile.a*255.));
-float centerDepth=0.;
-vec4 inputColor=texture2D(textureSampler,vUV);
-bool passedStencilTest=testLightingForSSS(irradianceAndDiffusionProfile.a);
-if (passedStencilTest)
-{
-centerDepth=texture2D(depthSampler,vUV).r;
-}
-if (!passedStencilTest) {
-gl_FragColor=inputColor;
-return;
-}
-float distScale=1.;
-vec3 S=diffusionS[diffusionProfileIndex];
-float d=diffusionD[diffusionProfileIndex];
-float filterRadius=filterRadii[diffusionProfileIndex];
-
-vec2 centerPosNDC=vUV;
-vec2 cornerPosNDC=vUV+0.5*texelSize;
-vec3 centerPosVS=vec3(centerPosNDC*viewportSize,1.0)*centerDepth;
-vec3 cornerPosVS=vec3(cornerPosNDC*viewportSize,1.0)*centerDepth;
-
-float mmPerUnit=1000.*(metersPerUnit*rcp(distScale));
-float unitsPerMm=rcp(mmPerUnit);
-
-
-float unitsPerPixel=2.*abs(cornerPosVS.x-centerPosVS.x);
-float pixelsPerMm=rcp(unitsPerPixel)*unitsPerMm;
-
-float filterArea=PI*Sq(filterRadius*pixelsPerMm);
-int sampleCount=int(filterArea*rcp(SSS_PIXELS_PER_SAMPLE));
-int sampleBudget=_SssSampleBudget;
-int texturingMode=0;
-vec3 albedo=texture2D(albedoSampler,vUV).rgb;
-if (distScale == 0. || sampleCount<1)
-{
-#ifdef DEBUG_SSS_SAMPLES
-vec3 green=vec3(0.,1.,0.);
-gl_FragColor=vec4(green,1.0);
-return;
-#endif
-gl_FragColor=vec4(inputColor.rgb+albedo*centerIrradiance,1.0);
-return;
-}
-#ifdef DEBUG_SSS_SAMPLES
-vec3 red=vec3(1.,0.,0.);
-vec3 blue=vec3(0.,0.,1.);
-gl_FragColor=vec4(mix(blue,red,clamp(float(sampleCount)/float(sampleBudget),0.0,1.0)),1.0);
-return;
-#endif
-
-float phase=0.;
-int n=min(sampleCount,sampleBudget);
-
-vec3 centerWeight=vec3(0.);
-vec3 totalIrradiance=vec3(0.);
-vec3 totalWeight=vec3(0.);
-for (int i=0; i<n; i++)
-{
-
-EvaluateSample(i,n,S,d,centerPosVS,mmPerUnit,pixelsPerMm,
-phase,totalIrradiance,totalWeight);
-}
-
-totalWeight=max(totalWeight,HALF_MIN);
-gl_FragColor=vec4(inputColor.rgb+albedo*max(totalIrradiance/totalWeight,vec3(0.0)),1.);
-}`;ze.a.ShadersStore.subSurfaceScatteringPixelShader=kg;var Gg=function(r){function t(e,n,i,o,a,s,d,p){o===void 0&&(o=null),p===void 0&&(p=h.a.TEXTURETYPE_UNSIGNED_INT);var b=r.call(this,e,"subSurfaceScattering",["texelSize","viewportSize","metersPerUnit"],["diffusionS","diffusionD","filterRadii","irradianceSampler","depthSampler","albedoSampler"],i,o,a||we.a.BILINEAR_SAMPLINGMODE,s,d,null,p,"postprocess",void 0,!0)||this;return b._scene=n,b.updateEffect(),b.onApplyObservable.add(function(P){if(n.prePassRenderer&&n.subSurfaceConfiguration){var O=b.texelSize;P.setFloat("metersPerUnit",n.subSurfaceConfiguration.metersPerUnit),P.setFloat2("texelSize",O.x,O.y),P.setTexture("irradianceSampler",n.prePassRenderer.prePassRT.textures[n.prePassRenderer.getIndex(h.a.PREPASS_IRRADIANCE_TEXTURE_TYPE)]),P.setTexture("depthSampler",n.prePassRenderer.prePassRT.textures[n.prePassRenderer.getIndex(h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE)]),P.setTexture("albedoSampler",n.prePassRenderer.prePassRT.textures[n.prePassRenderer.getIndex(h.a.PREPASS_ALBEDO_TEXTURE_TYPE)]),P.setFloat2("viewportSize",Math.tan(n.activeCamera.fov/2)*n.getEngine().getAspectRatio(n.activeCamera,!0),Math.tan(n.activeCamera.fov/2)),P.setArray3("diffusionS",n.subSurfaceConfiguration.ssDiffusionS),P.setArray("diffusionD",n.subSurfaceConfiguration.ssDiffusionD),P.setArray("filterRadii",n.subSurfaceConfiguration.ssFilterRadii)}else l.a.Error("PrePass and subsurface configuration needs to be enabled for subsurface scattering.")}),b}return Object(c.d)(t,r),t.prototype.getClassName=function(){return"SubSurfaceScatteringPostProcess"},t}(_t),Zd=function(){function r(t){this._ssDiffusionS=[],this._ssFilterRadii=[],this._ssDiffusionD=[],this.enabled=!1,this.name=at.a.NAME_SUBSURFACE,this.ssDiffusionProfileColors=[],this.metersPerUnit=1,this.texturesRequired=[h.a.PREPASS_DEPTHNORMAL_TEXTURE_TYPE,h.a.PREPASS_ALBEDO_TEXTURE_TYPE,h.a.PREPASS_COLOR_TEXTURE_TYPE,h.a.PREPASS_IRRADIANCE_TEXTURE_TYPE],this.addDiffusionProfile(new M.a(1,1,1)),this._scene=t,r._SceneComponentInitialization(this._scene)}return Object.defineProperty(r.prototype,"ssDiffusionS",{get:function(){return this._ssDiffusionS},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"ssDiffusionD",{get:function(){return this._ssDiffusionD},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"ssFilterRadii",{get:function(){return this._ssFilterRadii},enumerable:!1,configurable:!0}),r.prototype.addDiffusionProfile=function(t){if(this.ssDiffusionD.length>=5)return l.a.Error("You already reached the maximum number of diffusion profiles."),0;for(var e=0;e<this._ssDiffusionS.length/3;e++)if(this._ssDiffusionS[3*e]===t.r&&this._ssDiffusionS[3*e+1]===t.g&&this._ssDiffusionS[3*e+2]===t.b)return e;return this._ssDiffusionS.push(t.r,t.b,t.g),this._ssDiffusionD.push(Math.max(Math.max(t.r,t.b),t.g)),this._ssFilterRadii.push(this.getDiffusionProfileParameters(t)),this.ssDiffusionProfileColors.push(t),this._ssDiffusionD.length-1},r.prototype.createPostProcess=function(){return this.postProcess=new Gg("subSurfaceScattering",this._scene,1,null,void 0,this._scene.getEngine()),this.postProcess.autoClear=!1,this.postProcess},r.prototype.clearAllDiffusionProfiles=function(){this._ssDiffusionD=[],this._ssDiffusionS=[],this._ssFilterRadii=[],this.ssDiffusionProfileColors=[]},r.prototype.dispose=function(){this.clearAllDiffusionProfiles(),this.postProcess.dispose()},r.prototype.getDiffusionProfileParameters=function(t){var e=Math.max(t.r,t.g,t.b);return this._sampleBurleyDiffusionProfile(.997,e)},r.prototype._sampleBurleyDiffusionProfile=function(t,e){var n=1+4*(t=1-t)*(2*t+Math.sqrt(1+4*t*t)),i=Math.pow(n,-1/3),o=1+n*i*i+i;return 3*Math.log(o/(4*t))*e},r._SceneComponentInitialization=function(t){throw An.a.WarnImport("PrePassRendererSceneComponent")},r}();U.a.AddParser(at.a.NAME_SUBSURFACE,function(r,t){if(r.ssDiffusionProfileColors!==void 0&&r.ssDiffusionProfileColors!==null&&(t.enableSubSurfaceForPrePass(),t.subSurfaceConfiguration))for(var e=0,n=r.ssDiffusionProfileColors.length;e<n;e++){var i=r.ssDiffusionProfileColors[e];t.subSurfaceConfiguration.addDiffusionProfile(new M.a(i.r,i.g,i.b))}}),Object.defineProperty(_e.a.prototype,"subSurfaceConfiguration",{get:function(){return this._subSurfaceConfiguration},set:function(r){r&&this.enablePrePassRenderer()&&(this._subSurfaceConfiguration=r)},enumerable:!0,configurable:!0}),_e.a.prototype.enableSubSurfaceForPrePass=function(){if(this._subSurfaceConfiguration)return this._subSurfaceConfiguration;var r=this.enablePrePassRenderer();return r?(this._subSurfaceConfiguration=new Zd(this),r.addEffectConfiguration(this._subSurfaceConfiguration),this._subSurfaceConfiguration):null},_e.a.prototype.disableSubSurfaceForPrePass=function(){this._subSurfaceConfiguration&&(this._subSurfaceConfiguration.dispose(),this._subSurfaceConfiguration=null)};var Jd=function(){function r(t){this.name=at.a.NAME_PREPASSRENDERER,this.scene=t}return r.prototype.register=function(){},r.prototype.serialize=function(t){if(this.scene.subSurfaceConfiguration){var e=this.scene.subSurfaceConfiguration.ssDiffusionProfileColors;t.ssDiffusionProfileColors=[];for(var n=0;n<e.length;n++)t.ssDiffusionProfileColors.push({r:e[n].r,g:e[n].g,b:e[n].b})}},r.prototype.addFromContainer=function(t){},r.prototype.removeFromContainer=function(t,e){this.scene.prePassRenderer&&this.scene.subSurfaceConfiguration&&this.scene.subSurfaceConfiguration.clearAllDiffusionProfiles()},r.prototype.rebuild=function(){},r.prototype.dispose=function(){},r}();Zd._SceneComponentInitialization=function(r){var t=r._getComponent(at.a.NAME_SUBSURFACE);t||(t=new Jd(r),r._addComponent(t))};var zg=`#ifdef LOGARITHMICDEPTH
-#extension GL_EXT_frag_depth : enable
-#endif
-uniform vec4 color;
-#ifdef ALPHATEST
-varying vec2 vUV;
-uniform sampler2D diffuseSampler;
-#endif
-#include<logDepthDeclaration>
-void main(void) {
-#ifdef ALPHATEST
-if (texture2D(diffuseSampler,vUV).a<0.4)
-discard;
-#endif
-#include<logDepthFragment>
-gl_FragColor=color;
-}`;ze.a.ShadersStore.outlinePixelShader=zg;var jg=`
-attribute vec3 position;
-attribute vec3 normal;
-#include<bonesDeclaration>
-#include<morphTargetsVertexGlobalDeclaration>
-#include<morphTargetsVertexDeclaration>[0..maxSimultaneousMorphTargets]
-
-uniform float offset;
-#include<instancesDeclaration>
-uniform mat4 viewProjection;
-#ifdef ALPHATEST
-varying vec2 vUV;
-uniform mat4 diffuseMatrix;
-#ifdef UV1
-attribute vec2 uv;
-#endif
-#ifdef UV2
-attribute vec2 uv2;
-#endif
-#endif
-#include<logDepthDeclaration>
-void main(void)
-{
-vec3 positionUpdated=position;
-vec3 normalUpdated=normal;
-#ifdef UV1
-vec2 uvUpdated=uv;
-#endif
-#include<morphTargetsVertex>[0..maxSimultaneousMorphTargets]
-vec3 offsetPosition=positionUpdated+(normalUpdated*offset);
-#include<instancesVertex>
-#include<bonesVertex>
-gl_Position=viewProjection*finalWorld*vec4(offsetPosition,1.0);
-#ifdef ALPHATEST
-#ifdef UV1
-vUV=vec2(diffuseMatrix*vec4(uvUpdated,1.0,0.0));
-#endif
-#ifdef UV2
-vUV=vec2(diffuseMatrix*vec4(uv2,1.0,0.0));
-#endif
-#endif
-#include<logDepthVertex>
-}
-`;ze.a.ShadersStore.outlineVertexShader=jg,_e.a.prototype.getOutlineRenderer=function(){return this._outlineRenderer||(this._outlineRenderer=new $d(this)),this._outlineRenderer},Object.defineProperty(De.a.prototype,"renderOutline",{get:function(){return this._renderOutline},set:function(r){r&&this.getScene().getOutlineRenderer(),this._renderOutline=r},enumerable:!0,configurable:!0}),Object.defineProperty(De.a.prototype,"renderOverlay",{get:function(){return this._renderOverlay},set:function(r){r&&this.getScene().getOutlineRenderer(),this._renderOverlay=r},enumerable:!0,configurable:!0});var $d=function(){function r(t){this.name=at.a.NAME_OUTLINERENDERER,this.zOffset=1,this.scene=t,this._engine=t.getEngine(),this.scene._addComponent(this)}return r.prototype.register=function(){this.scene._beforeRenderingMeshStage.registerStep(at.a.STEP_BEFORERENDERINGMESH_OUTLINE,this,this._beforeRenderingMesh),this.scene._afterRenderingMeshStage.registerStep(at.a.STEP_AFTERRENDERINGMESH_OUTLINE,this,this._afterRenderingMesh)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){},r.prototype.render=function(t,e,n){var i=this;n===void 0&&(n=!1);var o=this.scene,a=o.getEngine(),s=a.getCaps().instancedArrays&&(e.visibleInstances[t._id]!==null&&e.visibleInstances[t._id]!==void 0||t.getRenderingMesh().hasThinInstances);if(this.isReady(t,s)){var d=t.getMesh(),p=d._internalAbstractMeshDataInfo._actAsRegularMesh?d:null,b=t.getRenderingMesh(),P=p||b,O=t.getMaterial();if(O&&o.activeCamera){if(a.enableEffect(this._effect),O.useLogarithmicDepth&&this._effect.setFloat("logarithmicDepthConstant",2/(Math.log(o.activeCamera.maxZ+1)/Math.LN2)),this._effect.setFloat("offset",n?0:b.outlineWidth),this._effect.setColor4("color",n?b.overlayColor:b.outlineColor,n?b.overlayAlpha:O.alpha),this._effect.setMatrix("viewProjection",o.getTransformMatrix()),this._effect.setMatrix("world",P.getWorldMatrix()),b.useBones&&b.computeBonesUsingShaders&&b.skeleton&&this._effect.setMatrices("mBones",b.skeleton.getTransformMatrices(b)),et.a.BindMorphTargetParameters(b,this._effect),b._bind(t,this._effect,O.fillMode),O&&O.needAlphaTesting()){var B=O.getAlphaTestTexture();B&&(this._effect.setTexture("diffuseSampler",B),this._effect.setMatrix("diffuseMatrix",B.getTextureMatrix()))}a.setZOffset(-this.zOffset),b._processRendering(P,t,this._effect,O.fillMode,e,s,function(F,z){i._effect.setMatrix("world",z)}),a.setZOffset(0)}}},r.prototype.isReady=function(t,e){var n=[],i=[Oe.b.PositionKind,Oe.b.NormalKind],o=t.getMesh(),a=t.getMaterial();a&&(a.needAlphaTesting()&&(n.push("#define ALPHATEST"),o.isVerticesDataPresent(Oe.b.UVKind)&&(i.push(Oe.b.UVKind),n.push("#define UV1")),o.isVerticesDataPresent(Oe.b.UV2Kind)&&(i.push(Oe.b.UV2Kind),n.push("#define UV2"))),a.useLogarithmicDepth&&n.push("#define LOGARITHMICDEPTH")),o.useBones&&o.computeBonesUsingShaders?(i.push(Oe.b.MatricesIndicesKind),i.push(Oe.b.MatricesWeightsKind),o.numBoneInfluencers>4&&(i.push(Oe.b.MatricesIndicesExtraKind),i.push(Oe.b.MatricesWeightsExtraKind)),n.push("#define NUM_BONE_INFLUENCERS "+o.numBoneInfluencers),n.push("#define BonesPerMesh "+(o.skeleton?o.skeleton.bones.length+1:0))):n.push("#define NUM_BONE_INFLUENCERS 0");var s=o.morphTargetManager,d=0;s&&s.numInfluencers>0&&(d=s.numInfluencers,n.push("#define MORPHTARGETS"),n.push("#define NUM_MORPH_INFLUENCERS "+d),et.a.PrepareAttributesForMorphTargetsInfluencers(i,o,d)),e&&(n.push("#define INSTANCES"),et.a.PushAttributesForInstances(i),t.getRenderingMesh().hasThinInstances&&n.push("#define THIN_INSTANCES"));var p=n.join(`
-`);return this._cachedDefines!==p&&(this._cachedDefines=p,this._effect=this.scene.getEngine().createEffect("outline",i,["world","mBones","viewProjection","diffuseMatrix","offset","color","logarithmicDepthConstant","morphTargetInfluences"],["diffuseSampler"],p,void 0,void 0,void 0,{maxSimultaneousMorphTargets:d})),this._effect.isReady()},r.prototype._beforeRenderingMesh=function(t,e,n){if(this._savedDepthWrite=this._engine.getDepthWrite(),t.renderOutline){var i=e.getMaterial();i&&i.needAlphaBlendingForMesh(t)&&(this._engine.cacheStencilState(),this._engine.setDepthWrite(!1),this._engine.setColorWrite(!1),this._engine.setStencilBuffer(!0),this._engine.setStencilOperationPass(h.a.REPLACE),this._engine.setStencilFunction(h.a.ALWAYS),this._engine.setStencilMask(r._StencilReference),this._engine.setStencilFunctionReference(r._StencilReference),this.render(e,n,!0),this._engine.setColorWrite(!0),this._engine.setStencilFunction(h.a.NOTEQUAL)),this._engine.setDepthWrite(!1),this.render(e,n),this._engine.setDepthWrite(this._savedDepthWrite),i&&i.needAlphaBlendingForMesh(t)&&this._engine.restoreStencilState()}},r.prototype._afterRenderingMesh=function(t,e,n){if(t.renderOverlay){var i=this._engine.getAlphaMode(),o=this._engine.alphaState.alphaBlend;this._engine.setAlphaMode(h.a.ALPHA_COMBINE),this.render(e,n,!0),this._engine.setAlphaMode(i),this._engine.setDepthWrite(this._savedDepthWrite),this._engine.alphaState.alphaBlend=o}t.renderOutline&&this._savedDepthWrite&&(this._engine.setDepthWrite(!0),this._engine.setColorWrite(!1),this.render(e,n),this._engine.setColorWrite(!0))},r._StencilReference=4,r}(),Hg=f(148),ef=function(r){function t(e,n){var i=r.call(this)||this;return i.name=e,i.animations=new Array,i.isPickable=!1,i.useAlphaForPicking=!1,i.onDisposeObservable=new C.c,i._onAnimationEnd=null,i._endAnimation=function(){i._onAnimationEnd&&i._onAnimationEnd(),i.disposeWhenFinishedAnimating&&i.dispose()},i.color=new M.b(1,1,1,1),i.position=u.e.Zero(),i._manager=n,i._manager.sprites.push(i),i.uniqueId=i._manager.scene.getUniqueId(),i}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"size",{get:function(){return this.width},set:function(e){this.width=e,this.height=e},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"manager",{get:function(){return this._manager},enumerable:!1,configurable:!0}),t.prototype.getClassName=function(){return"Sprite"},Object.defineProperty(t.prototype,"fromIndex",{get:function(){return this._fromIndex},set:function(e){this.playAnimation(e,this._toIndex,this._loopAnimation,this._delay,this._onAnimationEnd)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"toIndex",{get:function(){return this._toIndex},set:function(e){this.playAnimation(this._fromIndex,e,this._loopAnimation,this._delay,this._onAnimationEnd)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"loopAnimation",{get:function(){return this._loopAnimation},set:function(e){this.playAnimation(this._fromIndex,this._toIndex,e,this._delay,this._onAnimationEnd)},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"delay",{get:function(){return Math.max(this._delay,1)},set:function(e){this.playAnimation(this._fromIndex,this._toIndex,this._loopAnimation,e,this._onAnimationEnd)},enumerable:!1,configurable:!0}),t.prototype.playAnimation=function(e,n,i,o,a){a===void 0&&(a=null),this._onAnimationEnd=a,r.prototype.playAnimation.call(this,e,n,i,o,this._endAnimation)},t.prototype.dispose=function(){for(var e=0;e<this._manager.sprites.length;e++)this._manager.sprites[e]==this&&this._manager.sprites.splice(e,1);this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear()},t.prototype.serialize=function(){var e={};return e.name=this.name,e.position=this.position.asArray(),e.color=this.color.asArray(),e.width=this.width,e.height=this.height,e.angle=this.angle,e.cellIndex=this.cellIndex,e.cellRef=this.cellRef,e.invertU=this.invertU,e.invertV=this.invertV,e.disposeWhenFinishedAnimating=this.disposeWhenFinishedAnimating,e.isPickable=this.isPickable,e.isVisible=this.isVisible,e.useAlphaForPicking=this.useAlphaForPicking,e.animationStarted=this.animationStarted,e.fromIndex=this.fromIndex,e.toIndex=this.toIndex,e.loopAnimation=this.loopAnimation,e.delay=this.delay,e},t.Parse=function(e,n){var i=new t(e.name,n);return i.position=u.e.FromArray(e.position),i.color=M.b.FromArray(e.color),i.width=e.width,i.height=e.height,i.angle=e.angle,i.cellIndex=e.cellIndex,i.cellRef=e.cellRef,i.invertU=e.invertU,i.invertV=e.invertV,i.disposeWhenFinishedAnimating=e.disposeWhenFinishedAnimating,i.isPickable=e.isPickable,i.isVisible=e.isVisible,i.useAlphaForPicking=e.useAlphaForPicking,i.fromIndex=e.fromIndex,i.toIndex=e.toIndex,i.loopAnimation=e.loopAnimation,i.delay=e.delay,e.animationStarted&&i.playAnimation(i.fromIndex,i.toIndex,i.loopAnimation,i.delay),i},t}(function(){function r(){this.width=1,this.height=1,this.angle=0,this.invertU=!1,this.invertV=!1,this.isVisible=!0,this._animationStarted=!1,this._loopAnimation=!1,this._fromIndex=0,this._toIndex=0,this._delay=0,this._direction=1,this._time=0,this._onBaseAnimationEnd=null,this.position={x:1,y:1,z:1},this.color={r:1,g:1,b:1,a:1}}return Object.defineProperty(r.prototype,"animationStarted",{get:function(){return this._animationStarted},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"fromIndex",{get:function(){return this._fromIndex},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"toIndex",{get:function(){return this._toIndex},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"loopAnimation",{get:function(){return this._loopAnimation},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"delay",{get:function(){return Math.max(this._delay,1)},enumerable:!1,configurable:!0}),r.prototype.playAnimation=function(t,e,n,i,o){this._fromIndex=t,this._toIndex=e,this._loopAnimation=n,this._delay=i||1,this._animationStarted=!0,this._onBaseAnimationEnd=o,t<e?this._direction=1:(this._direction=-1,this._toIndex=t,this._fromIndex=e),this.cellIndex=t,this._time=0},r.prototype.stopAnimation=function(){this._animationStarted=!1},r.prototype._animate=function(t){this._animationStarted&&(this._time+=t,this._time>this._delay&&(this._time=this._time%this._delay,this.cellIndex+=this._direction,(this._direction>0&&this.cellIndex>this._toIndex||this._direction<0&&this.cellIndex<this._fromIndex)&&(this._loopAnimation?this.cellIndex=this._direction>0?this._fromIndex:this._toIndex:(this.cellIndex=this._toIndex,this._animationStarted=!1,this._onBaseAnimationEnd&&this._onBaseAnimationEnd()))))},r}());_e.a.prototype._internalPickSprites=function(r,t,e,n){if(!nr.a)return null;var i=null;if(!n){if(!this.activeCamera)return null;n=this.activeCamera}if(this.spriteManagers.length>0)for(var o=0;o<this.spriteManagers.length;o++){var a=this.spriteManagers[o];if(a.isPickable){var s=a.intersects(r,n,t,e);if(s&&s.hit&&(e||i==null||!(s.distance>=i.distance))&&(i=s,e))break}}return i||new nr.a},_e.a.prototype._internalMultiPickSprites=function(r,t,e){if(!nr.a)return null;var n=new Array;if(!e){if(!this.activeCamera)return null;e=this.activeCamera}if(this.spriteManagers.length>0)for(var i=0;i<this.spriteManagers.length;i++){var o=this.spriteManagers[i];if(o.isPickable){var a=o.multiIntersects(r,e,t);a!==null&&(n=n.concat(a))}}return n},_e.a.prototype.pickSprite=function(r,t,e,n,i){return this._tempSpritePickingRay?(this.createPickingRayInCameraSpaceToRef(r,t,this._tempSpritePickingRay,i),this._internalPickSprites(this._tempSpritePickingRay,e,n,i)):null},_e.a.prototype.pickSpriteWithRay=function(r,t,e,n){if(!this._tempSpritePickingRay)return null;if(!n){if(!this.activeCamera)return null;n=this.activeCamera}return fn.a.TransformToRef(r,n.getViewMatrix(),this._tempSpritePickingRay),this._internalPickSprites(this._tempSpritePickingRay,t,e,n)},_e.a.prototype.multiPickSprite=function(r,t,e,n){return this.createPickingRayInCameraSpaceToRef(r,t,this._tempSpritePickingRay,n),this._internalMultiPickSprites(this._tempSpritePickingRay,e,n)},_e.a.prototype.multiPickSpriteWithRay=function(r,t,e){if(!this._tempSpritePickingRay)return null;if(!e){if(!this.activeCamera)return null;e=this.activeCamera}return fn.a.TransformToRef(r,e.getViewMatrix(),this._tempSpritePickingRay),this._internalMultiPickSprites(this._tempSpritePickingRay,t,e)},_e.a.prototype.setPointerOverSprite=function(r){this._pointerOverSprite!==r&&(this._pointerOverSprite&&this._pointerOverSprite.actionManager&&this._pointerOverSprite.actionManager.processTrigger(h.a.ACTION_OnPointerOutTrigger,m.a.CreateNewFromSprite(this._pointerOverSprite,this)),this._pointerOverSprite=r,this._pointerOverSprite&&this._pointerOverSprite.actionManager&&this._pointerOverSprite.actionManager.processTrigger(h.a.ACTION_OnPointerOverTrigger,m.a.CreateNewFromSprite(this._pointerOverSprite,this)))},_e.a.prototype.getPointerOverSprite=function(){return this._pointerOverSprite};var tf=function(){function r(t){this.name=at.a.NAME_SPRITE,this.scene=t,this.scene.spriteManagers=new Array,this.scene._tempSpritePickingRay=fn.a?fn.a.Zero():null,this.scene.onBeforeSpritesRenderingObservable=new C.c,this.scene.onAfterSpritesRenderingObservable=new C.c,this._spritePredicate=function(e){return!!e.actionManager&&e.isPickable&&e.actionManager.hasPointerTriggers}}return r.prototype.register=function(){this.scene._pointerMoveStage.registerStep(at.a.STEP_POINTERMOVE_SPRITE,this,this._pointerMove),this.scene._pointerDownStage.registerStep(at.a.STEP_POINTERDOWN_SPRITE,this,this._pointerDown),this.scene._pointerUpStage.registerStep(at.a.STEP_POINTERUP_SPRITE,this,this._pointerUp)},r.prototype.rebuild=function(){},r.prototype.dispose=function(){this.scene.onBeforeSpritesRenderingObservable.clear(),this.scene.onAfterSpritesRenderingObservable.clear();for(var t=this.scene.spriteManagers;t.length;)t[0].dispose()},r.prototype._pickSpriteButKeepRay=function(t,e,n,i,o){var a=this.scene.pickSprite(e,n,this._spritePredicate,i,o);return a&&(a.ray=t?t.ray:null),a},r.prototype._pointerMove=function(t,e,n,i,o){var a=this.scene;return i?a.setPointerOverSprite(null):(n=this._pickSpriteButKeepRay(n,t,e,!1,a.cameraToUseForPointers||void 0))&&n.hit&&n.pickedSprite?(a.setPointerOverSprite(n.pickedSprite),a.doNotHandleCursors||(a._pointerOverSprite&&a._pointerOverSprite.actionManager&&a._pointerOverSprite.actionManager.hoverCursor?o.style.cursor=a._pointerOverSprite.actionManager.hoverCursor:o.style.cursor=a.hoverCursor)):a.setPointerOverSprite(null),n},r.prototype._pointerDown=function(t,e,n,i){var o=this.scene;if(o._pickedDownSprite=null,o.spriteManagers.length>0&&(n=o.pickSprite(t,e,this._spritePredicate,!1,o.cameraToUseForPointers||void 0))&&n.hit&&n.pickedSprite&&n.pickedSprite.actionManager){switch(o._pickedDownSprite=n.pickedSprite,i.button){case 0:n.pickedSprite.actionManager.processTrigger(h.a.ACTION_OnLeftPickTrigger,m.a.CreateNewFromSprite(n.pickedSprite,o,i));break;case 1:n.pickedSprite.actionManager.processTrigger(h.a.ACTION_OnCenterPickTrigger,m.a.CreateNewFromSprite(n.pickedSprite,o,i));break;case 2:n.pickedSprite.actionManager.processTrigger(h.a.ACTION_OnRightPickTrigger,m.a.CreateNewFromSprite(n.pickedSprite,o,i))}n.pickedSprite.actionManager&&n.pickedSprite.actionManager.processTrigger(h.a.ACTION_OnPickDownTrigger,m.a.CreateNewFromSprite(n.pickedSprite,o,i))}return n},r.prototype._pointerUp=function(t,e,n,i){var o=this.scene;if(o.spriteManagers.length>0){var a=o.pickSprite(t,e,this._spritePredicate,!1,o.cameraToUseForPointers||void 0);a&&(a.hit&&a.pickedSprite&&a.pickedSprite.actionManager&&(a.pickedSprite.actionManager.processTrigger(h.a.ACTION_OnPickUpTrigger,m.a.CreateNewFromSprite(a.pickedSprite,o,i)),a.pickedSprite.actionManager&&(this.scene._inputManager._isPointerSwiping()||a.pickedSprite.actionManager.processTrigger(h.a.ACTION_OnPickTrigger,m.a.CreateNewFromSprite(a.pickedSprite,o,i)))),o._pickedDownSprite&&o._pickedDownSprite.actionManager&&o._pickedDownSprite!==a.pickedSprite&&o._pickedDownSprite.actionManager.processTrigger(h.a.ACTION_OnPickOutTrigger,m.a.CreateNewFromSprite(o._pickedDownSprite,o,i)))}return n},r}();ze.a.IncludesShadersStore.imageProcessingCompatibility=`#ifdef IMAGEPROCESSINGPOSTPROCESS
-gl_FragColor.rgb=pow(gl_FragColor.rgb,vec3(2.2));
-#endif`;var Wg=`uniform bool alphaTest;
-varying vec4 vColor;
-
-varying vec2 vUV;
-uniform sampler2D diffuseSampler;
-
-#include<fogFragmentDeclaration>
-void main(void) {
-vec4 color=texture2D(diffuseSampler,vUV);
-if (alphaTest)
-{
-if (color.a<0.95)
-discard;
-}
-color*=vColor;
-#include<fogFragment>
-gl_FragColor=color;
-#include<imageProcessingCompatibility>
-}`;ze.a.ShadersStore.spritesPixelShader=Wg;var Xg=`
-attribute vec4 position;
-attribute vec2 options;
-attribute vec2 offsets;
-attribute vec2 inverts;
-attribute vec4 cellInfo;
-attribute vec4 color;
-
-uniform mat4 view;
-uniform mat4 projection;
-
-varying vec2 vUV;
-varying vec4 vColor;
-#include<fogVertexDeclaration>
-void main(void) {
-vec3 viewPos=(view*vec4(position.xyz,1.0)).xyz;
-vec2 cornerPos;
-float angle=position.w;
-vec2 size=vec2(options.x,options.y);
-vec2 offset=offsets.xy;
-cornerPos=vec2(offset.x-0.5,offset.y-0.5)*size;
-
-vec3 rotatedCorner;
-rotatedCorner.x=cornerPos.x*cos(angle)-cornerPos.y*sin(angle);
-rotatedCorner.y=cornerPos.x*sin(angle)+cornerPos.y*cos(angle);
-rotatedCorner.z=0.;
-
-viewPos+=rotatedCorner;
-gl_Position=projection*vec4(viewPos,1.0);
-
-vColor=color;
-
-vec2 uvOffset=vec2(abs(offset.x-inverts.x),abs(1.0-offset.y-inverts.y));
-vec2 uvPlace=cellInfo.xy;
-vec2 uvSize=cellInfo.zw;
-vUV.x=uvPlace.x+uvSize.x*uvOffset.x;
-vUV.y=uvPlace.y+uvSize.y*uvOffset.y;
-
-#ifdef FOG
-vFogDistance=viewPos;
-#endif
-}`;ze.a.ShadersStore.spritesVertexShader=Xg;var Yg=function(){function r(t,e,n,i){if(n===void 0&&(n=.01),i===void 0&&(i=null),this.blendMode=h.a.ALPHA_COMBINE,this.autoResetAlpha=!0,this.disableDepthWrite=!1,this.fogEnabled=!0,this._useVAO=!1,this._useInstancing=!1,this._vertexBuffers={},this._capacity=e,this._epsilon=n,this._engine=t,this._useInstancing=t.getCaps().instancedArrays,this._useVAO=t.getCaps().vertexArrayObject&&!t.disableVertexArrayObjects,this._scene=i,!this._useInstancing){for(var o=[],a=0,s=0;s<e;s++)o.push(a),o.push(a+1),o.push(a+2),o.push(a),o.push(a+2),o.push(a+3),a+=4;this._indexBuffer=t.createIndexBuffer(o)}this._vertexBufferSize=this._useInstancing?16:18,this._vertexData=new Float32Array(e*this._vertexBufferSize*(this._useInstancing?1:4)),this._buffer=new Oe.a(t,this._vertexData,!0,this._vertexBufferSize);var d,p=this._buffer.createVertexBuffer(Oe.b.PositionKind,0,4,this._vertexBufferSize,this._useInstancing),b=this._buffer.createVertexBuffer("options",4,2,this._vertexBufferSize,this._useInstancing),P=6;if(this._useInstancing){var O=new Float32Array([0,0,1,0,1,1,0,1]);this._spriteBuffer=new Oe.a(t,O,!1,2),d=this._spriteBuffer.createVertexBuffer("offsets",0,2)}else d=this._buffer.createVertexBuffer("offsets",P,2,this._vertexBufferSize,this._useInstancing),P+=2;var B=this._buffer.createVertexBuffer("inverts",P,2,this._vertexBufferSize,this._useInstancing),F=this._buffer.createVertexBuffer("cellInfo",P+2,4,this._vertexBufferSize,this._useInstancing),z=this._buffer.createVertexBuffer(Oe.b.ColorKind,P+6,4,this._vertexBufferSize,this._useInstancing);this._vertexBuffers[Oe.b.PositionKind]=p,this._vertexBuffers.options=b,this._vertexBuffers.offsets=d,this._vertexBuffers.inverts=B,this._vertexBuffers.cellInfo=F,this._vertexBuffers[Oe.b.ColorKind]=z,this._effectBase=this._engine.createEffect("sprites",[Oe.b.PositionKind,"options","offsets","inverts","cellInfo",Oe.b.ColorKind],["view","projection","textureInfos","alphaTest"],["diffuseSampler"],""),this._scene&&(this._effectFog=this._scene.getEngine().createEffect("sprites",[Oe.b.PositionKind,"options","offsets","inverts","cellInfo",Oe.b.ColorKind],["view","projection","textureInfos","alphaTest","vFogInfos","vFogColor"],["diffuseSampler"],"#define FOG"))}return Object.defineProperty(r.prototype,"capacity",{get:function(){return this._capacity},enumerable:!1,configurable:!0}),r.prototype.render=function(t,e,n,i,o){if(o===void 0&&(o=null),this.texture&&this.texture.isReady()&&t.length){var a=this._effectBase,s=!1;if(this.fogEnabled&&this._scene&&this._scene.fogEnabled&&this._scene.fogMode!==0&&(a=this._effectFog,s=!0),a.isReady()){for(var d=this._engine,p=!(!this._scene||!this._scene.useRightHandedSystem),b=this.texture.getBaseSize(),P=Math.min(this._capacity,t.length),O=0,B=!0,F=0;F<P;F++){var z=t[F];z&&z.isVisible&&(B=!1,z._animate(e),this._appendSpriteVertex(O++,z,0,0,b,p,o),this._useInstancing||(this._appendSpriteVertex(O++,z,1,0,b,p,o),this._appendSpriteVertex(O++,z,1,1,b,p,o),this._appendSpriteVertex(O++,z,0,1,b,p,o)))}if(!B){this._buffer.update(this._vertexData);var J=d.depthCullingState.cull||!0,ie=d.depthCullingState.zOffset;if(p&&this._scene.getEngine().setState(J,ie,!1,!1),d.enableEffect(a),a.setTexture("diffuseSampler",this.texture),a.setMatrix("view",n),a.setMatrix("projection",i),s){var se=this._scene;a.setFloat4("vFogInfos",se.fogMode,se.fogStart,se.fogEnd,se.fogDensity),a.setColor3("vFogColor",se.fogColor)}this._useVAO?(this._vertexArrayObject||(this._vertexArrayObject=d.recordVertexArrayObject(this._vertexBuffers,this._indexBuffer,a)),d.bindVertexArrayObject(this._vertexArrayObject,this._indexBuffer)):d.bindBuffers(this._vertexBuffers,this._indexBuffer,a),d.depthCullingState.depthFunc=h.a.LEQUAL,this.disableDepthWrite||(a.setBool("alphaTest",!0),d.setColorWrite(!1),this._useInstancing?d.drawArraysType(h.a.MATERIAL_TriangleFanDrawMode,0,4,O):d.drawElementsType(h.a.MATERIAL_TriangleFillMode,0,O/4*6),d.setColorWrite(!0),a.setBool("alphaTest",!1)),d.setAlphaMode(this.blendMode),this._useInstancing?d.drawArraysType(h.a.MATERIAL_TriangleFanDrawMode,0,4,O):d.drawElementsType(h.a.MATERIAL_TriangleFillMode,0,O/4*6),this.autoResetAlpha&&d.setAlphaMode(h.a.ALPHA_DISABLE),p&&this._scene.getEngine().setState(J,ie,!1,!0),d.unbindInstanceAttributes()}}}},r.prototype._appendSpriteVertex=function(t,e,n,i,o,a,s){var d=t*this._vertexBufferSize;if(n===0?n=this._epsilon:n===1&&(n=1-this._epsilon),i===0?i=this._epsilon:i===1&&(i=1-this._epsilon),s)s(e,o);else{e.cellIndex||(e.cellIndex=0);var p=o.width/this.cellWidth,b=e.cellIndex/p>>0;e._xOffset=(e.cellIndex-b*p)*this.cellWidth/o.width,e._yOffset=b*this.cellHeight/o.height,e._xSize=this.cellWidth,e._ySize=this.cellHeight}this._vertexData[d]=e.position.x,this._vertexData[d+1]=e.position.y,this._vertexData[d+2]=e.position.z,this._vertexData[d+3]=e.angle,this._vertexData[d+4]=e.width,this._vertexData[d+5]=e.height,this._useInstancing?d-=2:(this._vertexData[d+6]=n,this._vertexData[d+7]=i),this._vertexData[d+8]=a?e.invertU?0:1:e.invertU?1:0,this._vertexData[d+9]=e.invertV?1:0,this._vertexData[d+10]=e._xOffset,this._vertexData[d+11]=e._yOffset,this._vertexData[d+12]=e._xSize/o.width,this._vertexData[d+13]=e._ySize/o.height,this._vertexData[d+14]=e.color.r,this._vertexData[d+15]=e.color.g,this._vertexData[d+16]=e.color.b,this._vertexData[d+17]=e.color.a},r.prototype.dispose=function(){this._buffer&&(this._buffer.dispose(),this._buffer=null),this._spriteBuffer&&(this._spriteBuffer.dispose(),this._spriteBuffer=null),this._indexBuffer&&(this._engine._releaseBuffer(this._indexBuffer),this._indexBuffer=null),this._vertexArrayObject&&(this._engine.releaseVertexArrayObject(this._vertexArrayObject),this._vertexArrayObject=null),this.texture&&(this.texture.dispose(),this.texture=null)},r}(),nf=function(){function r(t,e,n,i,o,a,s,d,p){var b=this;a===void 0&&(a=.01),s===void 0&&(s=we.a.TRILINEAR_SAMPLINGMODE),d===void 0&&(d=!1),p===void 0&&(p=null),this.name=t,this.sprites=new Array,this.renderingGroupId=0,this.layerMask=268435455,this.isPickable=!1,this.onDisposeObservable=new C.c,this.disableDepthWrite=!1,this._packedAndReady=!1,this._customUpdate=function(O,B){O.cellRef||(O.cellIndex=0);var F=O.cellIndex;typeof F=="number"&&isFinite(F)&&Math.floor(F)===F&&(O.cellRef=b._spriteMap[O.cellIndex]),O._xOffset=b._cellData[O.cellRef].frame.x/B.width,O._yOffset=b._cellData[O.cellRef].frame.y/B.height,O._xSize=b._cellData[O.cellRef].frame.w,O._ySize=b._cellData[O.cellRef].frame.h},o||(o=Ue.a.LastCreatedScene),o._getComponent(at.a.NAME_SPRITE)||o._addComponent(new tf(o)),this._fromPacked=d,this._scene=o;var P=this._scene.getEngine();if(this._spriteRenderer=new Yg(P,n,a,o),i.width&&i.height)this.cellWidth=i.width,this.cellHeight=i.height;else{if(i===void 0)return void(this._spriteRenderer=null);this.cellWidth=i,this.cellHeight=i}this._scene.spriteManagers.push(this),this.uniqueId=this.scene.getUniqueId(),e&&(this.texture=new we.a(e,o,!0,!1,s)),this._fromPacked&&this._makePacked(e,p)}return Object.defineProperty(r.prototype,"onDispose",{set:function(t){this._onDisposeObserver&&this.onDisposeObservable.remove(this._onDisposeObserver),this._onDisposeObserver=this.onDisposeObservable.add(t)},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"children",{get:function(){return this.sprites},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"scene",{get:function(){return this._scene},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"capacity",{get:function(){return this._spriteRenderer.capacity},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"texture",{get:function(){return this._spriteRenderer.texture},set:function(t){t.wrapU=we.a.CLAMP_ADDRESSMODE,t.wrapV=we.a.CLAMP_ADDRESSMODE,this._spriteRenderer.texture=t,this._textureContent=null},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"cellWidth",{get:function(){return this._spriteRenderer.cellWidth},set:function(t){this._spriteRenderer.cellWidth=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"cellHeight",{get:function(){return this._spriteRenderer.cellHeight},set:function(t){this._spriteRenderer.cellHeight=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"fogEnabled",{get:function(){return this._spriteRenderer.fogEnabled},set:function(t){this._spriteRenderer.fogEnabled=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"blendMode",{get:function(){return this._spriteRenderer.blendMode},set:function(t){this._spriteRenderer.blendMode=t},enumerable:!1,configurable:!0}),r.prototype.getClassName=function(){return"SpriteManager"},r.prototype._makePacked=function(t,e){var n=this;if(e!==null)try{var i=void 0;if((i=typeof e=="string"?JSON.parse(e):e).frames.length){for(var o={},a=0;a<i.frames.length;a++){var s=i.frames[a];if(typeof Object.keys(s)[0]!="string")throw new Error("Invalid JSON Format.  Check the frame values and make sure the name is the first parameter.");o[s[Object.keys(s)[0]]]=s}i.frames=o}var d=Reflect.ownKeys(i.frames);this._spriteMap=d,this._packedAndReady=!0,this._cellData=i.frames}catch{throw this._fromPacked=!1,this._packedAndReady=!1,new Error("Invalid JSON from string. Spritesheet managed with constant cell size.")}else{var p=/\./g,b=void 0;do b=p.lastIndex,p.test(t);while(p.lastIndex>0);var P=t.substring(0,b-1)+".json",O=new XMLHttpRequest;O.open("GET",P,!0),O.onerror=function(){l.a.Error("JSON ERROR: Unable to load JSON file."),n._fromPacked=!1,n._packedAndReady=!1},O.onload=function(){try{var B=JSON.parse(O.response),F=Reflect.ownKeys(B.frames);n._spriteMap=F,n._packedAndReady=!0,n._cellData=B.frames}catch{throw n._fromPacked=!1,n._packedAndReady=!1,new Error("Invalid JSON format. Please check documentation for format specifications.")}},O.send()}},r.prototype._checkTextureAlpha=function(t,e,n,i,o){if(!t.useAlphaForPicking||!this.texture)return!0;var a=this.texture.getSize();this._textureContent||(this._textureContent=new Uint8Array(a.width*a.height*4),this.texture.readPixels(0,0,this._textureContent));var s=u.c.Vector3[0];s.copyFrom(e.direction),s.normalize(),s.scaleInPlace(n),s.addInPlace(e.origin);var d=(s.x-i.x)/(o.x-i.x)-.5,p=1-(s.y-i.y)/(o.y-i.y)-.5,b=t.angle,P=d*Math.cos(b)-p*Math.sin(b)+.5,O=d*Math.sin(b)+p*Math.cos(b)+.5,B=t._xOffset*a.width+P*t._xSize|0,F=t._yOffset*a.height+O*t._ySize|0;return this._textureContent[4*(B+F*a.width)+3]>.5},r.prototype.intersects=function(t,e,n,i){for(var o=Math.min(this.capacity,this.sprites.length),a=u.e.Zero(),s=u.e.Zero(),d=Number.MAX_VALUE,p=null,b=u.c.Vector3[0],P=u.c.Vector3[1],O=e.getViewMatrix(),B=0;B<o;B++){var F=this.sprites[B];if(F){if(n){if(!n(F))continue}else if(!F.isPickable)continue;if(u.e.TransformCoordinatesToRef(F.position,O,P),a.copyFromFloats(P.x-F.width/2,P.y-F.height/2,P.z),s.copyFromFloats(P.x+F.width/2,P.y+F.height/2,P.z),t.intersectsBoxMinMax(a,s)){var z=u.e.Distance(P,t.origin);if(d>z){if(!this._checkTextureAlpha(F,t,z,a,s))continue;if(d=z,p=F,i)break}}}}if(p){var J=new nr.a;O.invertToRef(u.c.Matrix[0]),J.hit=!0,J.pickedSprite=p,J.distance=d;var ie=u.c.Vector3[2];return ie.copyFrom(t.direction),ie.normalize(),ie.scaleInPlace(d),t.origin.addToRef(ie,b),J.pickedPoint=u.e.TransformCoordinates(b,u.c.Matrix[0]),J}return null},r.prototype.multiIntersects=function(t,e,n){for(var i,o=Math.min(this.capacity,this.sprites.length),a=u.e.Zero(),s=u.e.Zero(),d=[],p=u.c.Vector3[0].copyFromFloats(0,0,0),b=u.c.Vector3[1].copyFromFloats(0,0,0),P=e.getViewMatrix(),O=0;O<o;O++){var B=this.sprites[O];if(B){if(n){if(!n(B))continue}else if(!B.isPickable)continue;if(u.e.TransformCoordinatesToRef(B.position,P,b),a.copyFromFloats(b.x-B.width/2,b.y-B.height/2,b.z),s.copyFromFloats(b.x+B.width/2,b.y+B.height/2,b.z),t.intersectsBoxMinMax(a,s)){if(i=u.e.Distance(b,t.origin),!this._checkTextureAlpha(B,t,i,a,s))continue;var F=new nr.a;d.push(F),P.invertToRef(u.c.Matrix[0]),F.hit=!0,F.pickedSprite=B,F.distance=i;var z=u.c.Vector3[2];z.copyFrom(t.direction),z.normalize(),z.scaleInPlace(i),t.origin.addToRef(z,p),F.pickedPoint=u.e.TransformCoordinates(p,u.c.Matrix[0])}}}return d},r.prototype.render=function(){if(!this._fromPacked||this._packedAndReady&&this._spriteMap&&this._cellData){var t=this._scene.getEngine().getDeltaTime();this._packedAndReady?this._spriteRenderer.render(this.sprites,t,this._scene.getViewMatrix(),this._scene.getProjectionMatrix(),this._customUpdate):this._spriteRenderer.render(this.sprites,t,this._scene.getViewMatrix(),this._scene.getProjectionMatrix())}},r.prototype.dispose=function(){this._spriteRenderer&&(this._spriteRenderer.dispose(),this._spriteRenderer=null),this._textureContent=null;var t=this._scene.spriteManagers.indexOf(this);this._scene.spriteManagers.splice(t,1),this.onDisposeObservable.notifyObservers(this),this.onDisposeObservable.clear()},r.prototype.serialize=function(t){t===void 0&&(t=!1);var e={};e.name=this.name,e.capacity=this.capacity,e.cellWidth=this.cellWidth,e.cellHeight=this.cellHeight,this.texture&&(t?e.texture=this.texture.serialize():(e.textureUrl=this.texture.name,e.invertY=this.texture._invertY)),e.sprites=[];for(var n=0,i=this.sprites;n<i.length;n++){var o=i[n];e.sprites.push(o.serialize())}return e},r.Parse=function(t,e,n){var i=new r(t.name,"",t.capacity,{width:t.cellWidth,height:t.cellHeight},e);t.texture?i.texture=we.a.Parse(t.texture,e,n):t.textureName&&(i.texture=new we.a(n+t.textureUrl,e,!1,t.invertY===void 0||t.invertY));for(var o=0,a=t.sprites;o<a.length;o++){var s=a[o];ef.Parse(s,i)}return i},r.ParseFromFileAsync=function(t,e,n,i){return i===void 0&&(i=""),new Promise(function(o,a){var s=new re.a;s.addEventListener("readystatechange",function(){if(s.readyState==4)if(s.status==200){var d=JSON.parse(s.responseText),p=r.Parse(d,n||Ue.a.LastCreatedScene,i);t&&(p.name=t),o(p)}else a("Unable to load the sprite manager")}),s.open("GET",e),s.send()})},r.CreateFromSnippetAsync=function(t,e,n){var i=this;return n===void 0&&(n=""),t==="_BLANK"?Promise.resolve(new r("Default sprite manager","//playground.babylonjs.com/textures/player.png",500,64,e)):new Promise(function(o,a){var s=new re.a;s.addEventListener("readystatechange",function(){if(s.readyState==4)if(s.status==200){var d=JSON.parse(JSON.parse(s.responseText).jsonPayload),p=JSON.parse(d.spriteManager),b=r.Parse(p,e||Ue.a.LastCreatedScene,n);b.snippetId=t,o(b)}else a("Unable to load the snippet "+t)}),s.open("GET",i.SnippetUrl+"/"+t.replace(/#/g,"/")),s.send()})},r.SnippetUrl="https://snippet.babylonjs.com",r}(),Kg=`precision highp float;
-varying vec3 vPosition;
-varying vec2 vUV;
-varying vec2 tUV;
-uniform float time;
-uniform float spriteCount;
-uniform sampler2D spriteSheet;
-uniform vec2 spriteMapSize;
-uniform vec2 outputSize;
-uniform vec2 stageSize;
-uniform sampler2D frameMap;
-uniform sampler2D tileMaps[LAYERS];
-uniform sampler2D animationMap;
-uniform vec3 colorMul;
-float mt;
-const float fdStep=1./4.;
-const float aFrameSteps=1./MAX_ANIMATION_FRAMES;
-mat4 getFrameData(float frameID){
-float fX=frameID/spriteCount;
-return mat4(
-texture2D(frameMap,vec2(fX,0.),0.),
-texture2D(frameMap,vec2(fX,fdStep*1.),0.),
-texture2D(frameMap,vec2(fX,fdStep*2.),0.),
-vec4(0.)
-);
-}
-void main(){
-vec4 color=vec4(0.);
-vec2 tileUV=fract(tUV);
-#ifdef FLIPU
-tileUV.y=1.0-tileUV.y;
-#endif
-vec2 tileID=floor(tUV);
-vec2 sheetUnits=1./spriteMapSize;
-float spriteUnits=1./spriteCount;
-vec2 stageUnits=1./stageSize;
-for(int i=0; i<LAYERS; i++) {
-float frameID;
-#define LAYER_ID_SWITCH
-vec4 animationData=texture2D(animationMap,vec2((frameID+0.5)/spriteCount,0.),0.);
-if(animationData.y>0.) {
-mt=mod(time*animationData.z,1.0);
-for(float f=0.; f<MAX_ANIMATION_FRAMES; f++){
-if(animationData.y>mt){
-frameID=animationData.x;
-break;
-}
-animationData=texture2D(animationMap,vec2((frameID+0.5)/spriteCount,aFrameSteps*f),0.);
-}
-}
-
-mat4 frameData=getFrameData(frameID+0.5);
-vec2 frameSize=(frameData[0].wz)/spriteMapSize;
-vec2 offset=frameData[0].xy*sheetUnits;
-vec2 ratio=frameData[2].xy/frameData[0].wz;
-
-if (frameData[2].z == 1.){
-tileUV.xy=tileUV.yx;
-}
-if (i == 0){
-color=texture2D(spriteSheet,tileUV*frameSize+offset);
-} else {
-vec4 nc=texture2D(spriteSheet,tileUV*frameSize+offset);
-float alpha=min(color.a+nc.a,1.0);
-vec3 mixed=mix(color.xyz,nc.xyz,nc.a);
-color=vec4(mixed,alpha);
-}
-}
-color.xyz*=colorMul;
-gl_FragColor=color;
-}`;ze.a.ShadersStore.spriteMapPixelShader=Kg;var Qg=`precision highp float;
-
-attribute vec3 position;
-attribute vec3 normal;
-attribute vec2 uv;
-
-varying vec3 vPosition;
-varying vec2 vUV;
-varying vec2 tUV;
-varying vec2 stageUnits;
-varying vec2 levelUnits;
-varying vec2 tileID;
-
-uniform float time;
-uniform mat4 worldViewProjection;
-uniform vec2 outputSize;
-uniform vec2 stageSize;
-uniform vec2 spriteMapSize;
-uniform float stageScale;
-void main() {
-vec4 p=vec4( position,1. );
-vPosition=p.xyz;
-vUV=uv;
-tUV=uv*stageSize;
-gl_Position=worldViewProjection*p;
-}`;ze.a.ShadersStore.spriteMapVertexShader=Qg;var mi,qg=function(){function r(t,e,n,i,o){var a=this;this.name=t,this.sprites=[],this.atlasJSON=e,this.sprites=this.atlasJSON.frames,this.spriteSheet=n,this.options=i,i.stageSize=i.stageSize||new u.d(1,1),i.outputSize=i.outputSize||i.stageSize,i.outputPosition=i.outputPosition||u.e.Zero(),i.outputRotation=i.outputRotation||u.e.Zero(),i.layerCount=i.layerCount||1,i.maxAnimationFrames=i.maxAnimationFrames||0,i.baseTile=i.baseTile||0,i.flipU=i.flipU||!1,i.colorMultiply=i.colorMultiply||new u.e(1,1,1),this._scene=o,this._frameMap=this._createFrameBuffer(),this._tileMaps=new Array;for(var s=0;s<i.layerCount;s++)this._tileMaps.push(this._createTileBuffer(null,s));this._animationMap=this._createTileAnimationBuffer(null);var d=[];d.push("#define LAYERS "+i.layerCount),i.flipU&&d.push("#define FLIPU"),d.push("#define MAX_ANIMATION_FRAMES "+i.maxAnimationFrames+".0");var p,b=ze.a.ShadersStore.spriteMapPixelShader;if(this._scene.getEngine().webGLVersion===1)for(p="",s=0;s<i.layerCount;s++)p+="if ("+s+" == i) { frameID = texture2D(tileMaps["+s+"], (tileID + 0.5) / stageSize, 0.).x; }";else{for(p="switch(i) {",s=0;s<i.layerCount;s++)p+="case "+s+" : frameID = texture(tileMaps["+s+"], (tileID + 0.5) / stageSize, 0.).x;",p+="break;";p+="}"}ze.a.ShadersStore["spriteMap"+this.name+"PixelShader"]=b.replace("#define LAYER_ID_SWITCH",p),this._material=new ua.a("spriteMap:"+this.name,this._scene,{vertex:"spriteMap",fragment:"spriteMap"+this.name},{defines:d,attributes:["position","normal","uv"],uniforms:["worldViewProjection","time","stageSize","outputSize","spriteMapSize","spriteCount","time","colorMul","mousePosition","curTile","flipU"],samplers:["spriteSheet","frameMap","tileMaps","animationMap"],needAlphaBlending:!0}),this._time=0,this._material.setFloat("spriteCount",this.spriteCount),this._material.setVector2("stageSize",i.stageSize),this._material.setVector2("outputSize",i.outputSize),this._material.setTexture("spriteSheet",this.spriteSheet),this._material.setVector2("spriteMapSize",new u.d(1,1)),this._material.setVector3("colorMul",i.colorMultiply);var P=0,O=function(){a.spriteSheet&&a.spriteSheet.isReady()&&a.spriteSheet._texture?a._material.setVector2("spriteMapSize",new u.d(a.spriteSheet._texture.baseWidth||1,a.spriteSheet._texture.baseHeight||1)):P<100&&setTimeout(function(){P++,O()},100)};O(),this._material.setVector3("colorMul",i.colorMultiply),this._material.setTexture("frameMap",this._frameMap),this._material.setTextureArray("tileMaps",this._tileMaps),this._material.setTexture("animationMap",this._animationMap),this._material.setFloat("time",this._time),this._output=De.a.CreatePlane(t+":output",1,o,!0),this._output.scaling.x=i.outputSize.x,this._output.scaling.y=i.outputSize.y,this.position=i.outputPosition,this.rotation=i.outputRotation,this._scene.onBeforeRenderObservable.add(function(){a._time+=a._scene.getEngine().getDeltaTime(),a._material.setFloat("time",a._time)}),this._output.material=this._material}return Object.defineProperty(r.prototype,"spriteCount",{get:function(){return this.sprites.length},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"position",{get:function(){return this._output.position},set:function(t){this._output.position=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"rotation",{get:function(){return this._output.rotation},set:function(t){this._output.rotation=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"animationMap",{get:function(){return this._animationMap},set:function(t){var e=t._texture._bufferView,n=this._createTileAnimationBuffer(e);this._animationMap.dispose(),this._animationMap=n,this._material.setTexture("animationMap",this._animationMap)},enumerable:!1,configurable:!0}),r.prototype.getTileID=function(){var t=this.getMousePosition();return t.multiplyInPlace(this.options.stageSize||u.d.Zero()),t.x=Math.floor(t.x),t.y=Math.floor(t.y),t},r.prototype.getMousePosition=function(){var t=this._output,e=this._scene.pick(this._scene.pointerX,this._scene.pointerY,function(i){return i===t});if(!e||!e.hit||!e.getTextureCoordinates)return new u.d(-1,-1);var n=e.getTextureCoordinates();return n||new u.d(-1,-1)},r.prototype._createFrameBuffer=function(){for(var t=new Array,e=0;e<this.spriteCount;e++)t.push(0,0,0,0),t.push(0,0,0,0),t.push(0,0,0,0),t.push(0,0,0,0);for(e=0;e<this.spriteCount;e++){var n=this.sprites[e].frame,i=this.sprites[e].spriteSourceSize,o=this.sprites[e].sourceSize,a=this.sprites[e].rotated?1:0,s=this.sprites[e].trimmed?1:0;t[4*e]=n.x,t[4*e+1]=n.y,t[4*e+2]=n.w,t[4*e+3]=n.h,t[4*e+4*this.spriteCount]=i.x,t[4*e+1+4*this.spriteCount]=i.y,t[4*e+3+4*this.spriteCount]=i.h,t[4*e+8*this.spriteCount]=o.w,t[4*e+1+8*this.spriteCount]=o.h,t[4*e+2+8*this.spriteCount]=a,t[4*e+3+8*this.spriteCount]=s}var d=new Float32Array(t);return ni.CreateRGBATexture(d,this.spriteCount,4,this._scene,!1,!1,we.a.NEAREST_NEAREST,Ue.a.TEXTURETYPE_FLOAT)},r.prototype._createTileBuffer=function(t,e){e===void 0&&(e=0);var n=new Array,i=this.options.stageSize.y||0,o=this.options.stageSize.x||0;if(t)n=t;else{var a=this.options.baseTile;e!=0&&(a=0);for(var s=0;s<i;s++)for(var d=0;d<4*o;d+=4)n.push(a,0,0,0)}var p=new Float32Array(n);return ni.CreateRGBATexture(p,o,i,this._scene,!1,!1,we.a.NEAREST_NEAREST,Ue.a.TEXTURETYPE_FLOAT)},r.prototype.changeTiles=function(t,e,n){var i;if(t===void 0&&(t=0),n===void 0&&(n=0),(i=this._tileMaps[t]._texture._bufferView)!==null){var o=new Array;e instanceof u.d?o.push(e):o=e;for(var a=this.options.stageSize.x||0,s=0;s<o.length;s++){var d=o[s];d.x=Math.floor(d.x),d.y=Math.floor(d.y),i[4*d.x+d.y*(4*a)]=n}var p=this._createTileBuffer(i);this._tileMaps[t].dispose(),this._tileMaps[t]=p,this._material.setTextureArray("tileMap",this._tileMaps)}},r.prototype._createTileAnimationBuffer=function(t){var e,n=new Array;if(t)e=t;else{for(var i=0;i<this.spriteCount;i++){n.push(0,0,0,0);for(var o=1;o<(this.options.maxAnimationFrames||4);)n.push(0,0,0,0),o++}e=new Float32Array(n)}return ni.CreateRGBATexture(e,this.spriteCount,this.options.maxAnimationFrames||4,this._scene,!1,!1,we.a.NEAREST_NEAREST,Ue.a.TEXTURETYPE_FLOAT)},r.prototype.addAnimationToTile=function(t,e,n,i,o){t===void 0&&(t=0),e===void 0&&(e=0),n===void 0&&(n=0),i===void 0&&(i=0),o===void 0&&(o=1);var a=this._animationMap._texture._bufferView,s=4*t+4*this.spriteCount*e;if(a){a[s]=n,a[s+1]=i,a[s+2]=o;var d=this._createTileAnimationBuffer(a);this._animationMap.dispose(),this._animationMap=d,this._material.setTexture("animationMap",this._animationMap)}},r.prototype.saveTileMaps=function(){for(var t="",e=0;e<this._tileMaps.length;e++)e>0&&(t+=`
-\r`),t+=this._tileMaps[e]._texture._bufferView.toString();var n=document.createElement("a");n.href="data:octet/stream;charset=utf-8,"+encodeURI(t),n.target="_blank",n.download=this.name+".tilemaps",n.click(),n.remove()},r.prototype.loadTileMaps=function(t){var e=this,n=new XMLHttpRequest;n.open("GET",t);var i=this.options.layerCount||0;n.onload=function(){for(var o=n.response.split(`
-\r`),a=0;a<i;a++){var s=o[a].split(",").map(Number),d=e._createTileBuffer(s);e._tileMaps[a].dispose(),e._tileMaps[a]=d}e._material.setTextureArray("tileMap",e._tileMaps)},n.send()},r.prototype.dispose=function(){this._output.dispose(),this._material.dispose(),this._animationMap.dispose(),this._tileMaps.forEach(function(t){t.dispose()}),this._frameMap.dispose()},r}(),Zg=function(r){function t(e,n,i,o,a,s,d){a===void 0&&(a=null),s===void 0&&(s=.01),d===void 0&&(d=we.a.TRILINEAR_SAMPLINGMODE);var p=r.call(this,e,n,i,64,o,s,d,!0,a)||this;return p.name=e,p}return Object(c.d)(t,r),t}(nf),Jg=f(143),$g=f(141),ev=f(142),tv=f(139);(function(r){r[r.INIT=0]="INIT",r[r.RUNNING=1]="RUNNING",r[r.DONE=2]="DONE",r[r.ERROR=3]="ERROR"})(mi||(mi={}));var Kc,gi=function(){function r(t){this.name=t,this._isCompleted=!1,this._taskState=mi.INIT}return Object.defineProperty(r.prototype,"isCompleted",{get:function(){return this._isCompleted},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"taskState",{get:function(){return this._taskState},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"errorObject",{get:function(){return this._errorObject},enumerable:!1,configurable:!0}),r.prototype._setErrorObject=function(t,e){this._errorObject||(this._errorObject={message:t,exception:e})},r.prototype.run=function(t,e,n){var i=this;this._taskState=mi.RUNNING,this.runTask(t,function(){i.onDoneCallback(e,n)},function(o,a){i.onErrorCallback(n,o,a)})},r.prototype.runTask=function(t,e,n){throw new Error("runTask is not implemented")},r.prototype.reset=function(){this._taskState=mi.INIT},r.prototype.onErrorCallback=function(t,e,n){this._taskState=mi.ERROR,this._errorObject={message:e,exception:n},this.onError&&this.onError(this,e,n),t()},r.prototype.onDoneCallback=function(t,e){try{this._taskState=mi.DONE,this._isCompleted=!0,this.onSuccess&&this.onSuccess(this),t()}catch(n){this.onErrorCallback(e,"Task is done, error executing success callback(s)",n)}},r}(),rf=function(r,t,e){this.remainingCount=r,this.totalCount=t,this.task=e},of=function(r){function t(e,n,i,o){var a=r.call(this,e)||this;return a.name=e,a.meshesNames=n,a.rootUrl=i,a.sceneFilename=o,a}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){var o=this;Ut.LoadAssetContainer(this.rootUrl,this.sceneFilename,e,function(a){o.loadedContainer=a,o.loadedMeshes=a.meshes,o.loadedParticleSystems=a.particleSystems,o.loadedSkeletons=a.skeletons,o.loadedAnimationGroups=a.animationGroups,n()},null,function(a,s,d){i(s,d)})},t}(gi),af=function(r){function t(e,n,i,o){var a=r.call(this,e)||this;return a.name=e,a.meshesNames=n,a.rootUrl=i,a.sceneFilename=o,a}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){var o=this;Ut.ImportMesh(this.meshesNames,this.rootUrl,this.sceneFilename,e,function(a,s,d,p){o.loadedMeshes=a,o.loadedParticleSystems=s,o.loadedSkeletons=d,o.loadedAnimationGroups=p,n()},null,function(a,s,d){i(s,d)})},t}(gi),sf=function(r){function t(e,n){var i=r.call(this,e)||this;return i.name=e,i.url=n,i}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){var o=this;e._loadFile(this.url,function(a){o.text=a,n()},void 0,!1,!1,function(a,s){a&&i(a.status+" "+a.statusText,s)})},t}(gi),cf=function(r){function t(e,n){var i=r.call(this,e)||this;return i.name=e,i.url=n,i}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){var o=this;e._loadFile(this.url,function(a){o.data=a,n()},void 0,!0,!0,function(a,s){a&&i(a.status+" "+a.statusText,s)})},t}(gi),lf=function(r){function t(e,n){var i=r.call(this,e)||this;return i.name=e,i.url=n,i}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){var o=this,a=new Image;Xe.b.SetCorsBehavior(this.url,a),a.onload=function(){o.image=a,n()},a.onerror=function(s){i("Error loading image",s)},a.src=this.url},t}(gi),uf=function(r){function t(e,n,i,o,a){o===void 0&&(o=!0),a===void 0&&(a=we.a.TRILINEAR_SAMPLINGMODE);var s=r.call(this,e)||this;return s.name=e,s.url=n,s.noMipmap=i,s.invertY=o,s.samplingMode=a,s}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){this.texture=new we.a(this.url,e,this.noMipmap,this.invertY,this.samplingMode,function(){n()},function(o,a){i(o,a)})},t}(gi),hf=function(r){function t(e,n,i,o,a){var s=r.call(this,e)||this;return s.name=e,s.url=n,s.extensions=i,s.noMipmap=o,s.files=a,s}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){this.texture=new oi(this.url,e,this.extensions,this.noMipmap,this.files,function(){n()},function(o,a){i(o,a)})},t}(gi),df=function(r){function t(e,n,i,o,a,s,d){o===void 0&&(o=!1),a===void 0&&(a=!0),s===void 0&&(s=!1),d===void 0&&(d=!1);var p=r.call(this,e)||this;return p.name=e,p.url=n,p.size=i,p.noMipmap=o,p.generateHarmonics=a,p.gammaSpace=s,p.reserved=d,p}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){this.texture=new aa(this.url,e,this.size,this.noMipmap,this.generateHarmonics,this.gammaSpace,this.reserved,function(){n()},function(o,a){i(o,a)})},t}(gi),ff=function(r){function t(e,n,i,o,a){o===void 0&&(o=!1),a===void 0&&(a=!0);var s=r.call(this,e)||this;return s.name=e,s.url=n,s.size=i,s.noMipmap=o,s.gammaSpace=a,s}return Object(c.d)(t,r),t.prototype.runTask=function(e,n,i){this.texture=new ah(this.url,e,this.size,this.noMipmap,this.gammaSpace,function(){n()},function(o,a){i(o,a)})},t}(gi),nv=function(){function r(t){this._isLoading=!1,this._tasks=new Array,this._waitingTasksCount=0,this._totalTasksCount=0,this.onTaskSuccessObservable=new C.c,this.onTaskErrorObservable=new C.c,this.onTasksDoneObservable=new C.c,this.onProgressObservable=new C.c,this.useDefaultLoadingScreen=!0,this.autoHideLoadingUI=!0,this._scene=t}return r.prototype.addContainerTask=function(t,e,n,i){var o=new of(t,e,n,i);return this._tasks.push(o),o},r.prototype.addMeshTask=function(t,e,n,i){var o=new af(t,e,n,i);return this._tasks.push(o),o},r.prototype.addTextFileTask=function(t,e){var n=new sf(t,e);return this._tasks.push(n),n},r.prototype.addBinaryFileTask=function(t,e){var n=new cf(t,e);return this._tasks.push(n),n},r.prototype.addImageTask=function(t,e){var n=new lf(t,e);return this._tasks.push(n),n},r.prototype.addTextureTask=function(t,e,n,i,o){o===void 0&&(o=we.a.TRILINEAR_SAMPLINGMODE);var a=new uf(t,e,n,i,o);return this._tasks.push(a),a},r.prototype.addCubeTextureTask=function(t,e,n,i,o){var a=new hf(t,e,n,i,o);return this._tasks.push(a),a},r.prototype.addHDRCubeTextureTask=function(t,e,n,i,o,a,s){i===void 0&&(i=!1),o===void 0&&(o=!0),a===void 0&&(a=!1),s===void 0&&(s=!1);var d=new df(t,e,n,i,o,a,s);return this._tasks.push(d),d},r.prototype.addEquiRectangularCubeTextureAssetTask=function(t,e,n,i,o){i===void 0&&(i=!1),o===void 0&&(o=!0);var a=new ff(t,e,n,i,o);return this._tasks.push(a),a},r.prototype.removeTask=function(t){var e=this._tasks.indexOf(t);e>-1&&this._tasks.splice(e,1)},r.prototype._decreaseWaitingTasksCount=function(t){this._waitingTasksCount--;try{this.onProgress&&this.onProgress(this._waitingTasksCount,this._totalTasksCount,t),this.onProgressObservable.notifyObservers(new rf(this._waitingTasksCount,this._totalTasksCount,t))}catch(a){l.a.Error("Error running progress callbacks."),console.log(a)}if(this._waitingTasksCount===0){try{var e=this._tasks.slice();this.onFinish&&this.onFinish(e);for(var n=0,i=e;n<i.length;n++)if((t=i[n]).taskState===mi.DONE){var o=this._tasks.indexOf(t);o>-1&&this._tasks.splice(o,1)}this.onTasksDoneObservable.notifyObservers(this._tasks)}catch(a){l.a.Error("Error running tasks-done callbacks."),console.log(a)}this._isLoading=!1,this.autoHideLoadingUI&&this._scene.getEngine().hideLoadingUI()}},r.prototype._runTask=function(t){var e=this,n=function(i,o){t._setErrorObject(i,o),e.onTaskError&&e.onTaskError(t),e.onTaskErrorObservable.notifyObservers(t),e._decreaseWaitingTasksCount(t)};t.run(this._scene,function(){try{e.onTaskSuccess&&e.onTaskSuccess(t),e.onTaskSuccessObservable.notifyObservers(t),e._decreaseWaitingTasksCount(t)}catch(i){n("Error executing task success callbacks",i)}},n)},r.prototype.reset=function(){return this._isLoading=!1,this._tasks=new Array,this},r.prototype.load=function(){if(this._isLoading)return this;if(this._isLoading=!0,this._waitingTasksCount=this._tasks.length,this._totalTasksCount=this._tasks.length,this._waitingTasksCount===0)return this._isLoading=!1,this.onFinish&&this.onFinish(this._tasks),this.onTasksDoneObservable.notifyObservers(this._tasks),this;this.useDefaultLoadingScreen&&this._scene.getEngine().displayLoadingUI();for(var t=0;t<this._tasks.length;t++){var e=this._tasks[t];e.taskState===mi.INIT&&this._runTask(e)}return this},r.prototype.loadAsync=function(){var t=this;return new Promise(function(e,n){t._isLoading?e():(t.onTasksDoneObservable.addOnce(function(i){i&&i.length?n(i):e()}),t.load())})},r}(),iv=function(){function r(){var t=this;this.promise=new Promise(function(e,n){t._resolve=e,t._reject=n})}return Object.defineProperty(r.prototype,"resolve",{get:function(){return this._resolve},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"reject",{get:function(){return this._reject},enumerable:!1,configurable:!0}),r}(),rv=function(){function r(t,e){this._meshesOrigins=[],this._toCenterVectors=[],this._scaledDirection=u.e.Zero(),this._newPosition=u.e.Zero(),this._centerPosition=u.e.Zero(),this._meshes=t.slice(),e?this._centerMesh=e:this._setCenterMesh();var n=this._meshes.indexOf(this._centerMesh);n>=0&&this._meshes.splice(n,1),this._centerPosition=this._centerMesh.getAbsolutePosition().clone();for(var i=0;i<this._meshes.length;i++)if(this._meshes[i]){var o=this._meshes[i];this._meshesOrigins[i]=o.getAbsolutePosition().clone(),this._toCenterVectors[i]=u.e.Zero(),o._boundingInfo&&this._centerMesh._boundingInfo&&o._boundingInfo.boundingBox.centerWorld.subtractToRef(this._centerMesh._boundingInfo.boundingBox.centerWorld,this._toCenterVectors[i])}}return r.prototype._setCenterMesh=function(){for(var t=u.e.Zero(),e=u.e.Zero(),n=Number.MAX_VALUE,i=0;i<this._meshes.length;i++)this._meshes[i]&&(a=(o=this._meshes[i]).getBoundingInfo())&&e.addInPlace(a.boundingBox.centerWorld);for(t=e.scale(1/this._meshes.length),i=0;i<this._meshes.length;i++){var o,a;if(this._meshes[i]&&(a=(o=this._meshes[i]).getBoundingInfo())){var s=a.boundingBox.centerWorld.subtract(t).lengthSquared();s<n&&(this._centerMesh=o,n=s)}}},r.prototype.getClassName=function(){return"MeshExploder"},r.prototype.getMeshes=function(){var t=this._meshes.slice();return t.unshift(this._centerMesh),t},r.prototype.explode=function(t){t===void 0&&(t=1);for(var e=0;e<this._meshes.length;e++)this._meshes[e]&&this._meshesOrigins[e]&&this._toCenterVectors[e]&&(this._toCenterVectors[e].scaleToRef(t,this._scaledDirection),this._meshesOrigins[e].addToRef(this._scaledDirection,this._newPosition),this._meshes[e].setAbsolutePosition(this._newPosition));this._centerMesh.setAbsolutePosition(this._centerPosition)},r}(),ov=function(){function r(t,e,n,i,o,a,s,d,p){this.onProcessFileCallback=function(){return!0},this._engine=t,this._currentScene=e,this._sceneLoadedCallback=n,this._progressCallback=i,this._additionalRenderLoopLogicCallback=o,this._textureLoadingCallback=a,this._startingProcessingFilesCallback=s,this._onReloadCallback=d,this._errorCallback=p}return Object.defineProperty(r,"FilesToLoad",{get:function(){return xs.a.FilesToLoad},enumerable:!1,configurable:!0}),r.prototype.monitorElementForDragNDrop=function(t){var e=this;t&&(this._elementToMonitor=t,this._dragEnterHandler=function(n){e.drag(n)},this._dragOverHandler=function(n){e.drag(n)},this._dropHandler=function(n){e.drop(n)},this._elementToMonitor.addEventListener("dragenter",this._dragEnterHandler,!1),this._elementToMonitor.addEventListener("dragover",this._dragOverHandler,!1),this._elementToMonitor.addEventListener("drop",this._dropHandler,!1))},Object.defineProperty(r.prototype,"filesToLoad",{get:function(){return this._filesToLoad},enumerable:!1,configurable:!0}),r.prototype.dispose=function(){this._elementToMonitor&&(this._elementToMonitor.removeEventListener("dragenter",this._dragEnterHandler),this._elementToMonitor.removeEventListener("dragover",this._dragOverHandler),this._elementToMonitor.removeEventListener("drop",this._dropHandler))},r.prototype.renderFunction=function(){if(this._additionalRenderLoopLogicCallback&&this._additionalRenderLoopLogicCallback(),this._currentScene){if(this._textureLoadingCallback){var t=this._currentScene.getWaitingItemsCount();t>0&&this._textureLoadingCallback(t)}this._currentScene.render()}},r.prototype.drag=function(t){t.stopPropagation(),t.preventDefault()},r.prototype.drop=function(t){t.stopPropagation(),t.preventDefault(),this.loadFiles(t)},r.prototype._traverseFolder=function(t,e,n,i){var o=this,a=t.createReader(),s=t.fullPath.replace(/^\//,"").replace(/(.+?)\/?$/,"$1/");a.readEntries(function(d){n.count+=d.length;for(var p=0,b=d;p<b.length;p++){var P=b[p];P.isFile?P.file(function(O){O.correctName=s+O.name,e.push(O),--n.count==0&&i()}):P.isDirectory&&o._traverseFolder(P,e,n,i)}--n.count==0&&i()})},r.prototype._processFiles=function(t){for(var e=0;e<t.length;e++){var n=t[e].correctName.toLowerCase(),i=n.split(".").pop();this.onProcessFileCallback(t[e],n,i)&&(Ut.IsPluginForExtensionAvailable("."+i)&&(this._sceneFileToLoad=t[e]),r.FilesToLoad[n]=t[e])}},r.prototype.loadFiles=function(t){var e=this;if(t&&t.dataTransfer&&t.dataTransfer.files&&(this._filesToLoad=t.dataTransfer.files),t&&t.target&&t.target.files&&(this._filesToLoad=t.target.files),this._filesToLoad&&this._filesToLoad.length!==0&&(this._startingProcessingFilesCallback&&this._startingProcessingFilesCallback(this._filesToLoad),this._filesToLoad&&this._filesToLoad.length>0)){for(var n=new Array,i=[],o=t.dataTransfer?t.dataTransfer.items:null,a=0;a<this._filesToLoad.length;a++){var s=this._filesToLoad[a],d=s.name.toLowerCase(),p=void 0;if(s.correctName=d,o){var b=o[a];b.getAsEntry?p=b.getAsEntry():b.webkitGetAsEntry&&(p=b.webkitGetAsEntry())}p&&p.isDirectory?i.push(p):n.push(s)}if(i.length===0)this._processFiles(n),this._processReload();else for(var P={count:i.length},O=0,B=i;O<B.length;O++){var F=B[O];this._traverseFolder(F,n,P,function(){e._processFiles(n),P.count===0&&e._processReload()})}}},r.prototype._processReload=function(){this._onReloadCallback?this._onReloadCallback(this._sceneFileToLoad):this.reload()},r.prototype.reload=function(){var t=this;this._sceneFileToLoad?(this._currentScene&&(l.a.errorsCount>0&&l.a.ClearLogCache(),this._engine.stopRenderLoop()),Ut.ShowLoadingScreen=!1,this._engine.displayLoadingUI(),Ut.LoadAsync("file:",this._sceneFileToLoad,this._engine,function(e){t._progressCallback&&t._progressCallback(e)}).then(function(e){t._currentScene&&t._currentScene.dispose(),t._currentScene=e,t._sceneLoadedCallback&&t._sceneLoadedCallback(t._sceneFileToLoad,t._currentScene),t._currentScene.executeWhenReady(function(){t._engine.hideLoadingUI(),t._engine.runRenderLoop(function(){t.renderFunction()})})}).catch(function(e){t._engine.hideLoadingUI(),t._errorCallback&&t._errorCallback(t._sceneFileToLoad,t._currentScene,e.message)})):l.a.Error("Please provide a valid .babylon file.")},r}(),pf=f(146),av=f(145),vi=function(){function r(t){t===void 0&&(t=0),this.priority=t}return r.prototype.getDescription=function(){return""},r.prototype.apply=function(t,e){return!0},r}(),Pa=function(r){function t(e,n,i){e===void 0&&(e=0),n===void 0&&(n=1024),i===void 0&&(i=.5);var o=r.call(this,e)||this;return o.priority=e,o.maximumSize=n,o.step=i,o}return Object(c.d)(t,r),t.prototype.getDescription=function(){return"Reducing render target texture size to "+this.maximumSize},t.prototype.apply=function(e,n){for(var i=!0,o=0;o<e.textures.length;o++){var a=e.textures[o];if(a.canRescale&&!a.getContext){var s=a.getSize();Math.max(s.width,s.height)>this.maximumSize&&(a.scale(this.step),i=!1)}}return i},t}(vi),Qc=function(r){function t(e,n,i){e===void 0&&(e=0),n===void 0&&(n=2),i===void 0&&(i=.25);var o=r.call(this,e)||this;return o.priority=e,o.maximumScale=n,o.step=i,o._currentScale=-1,o._directionOffset=1,o}return Object(c.d)(t,r),t.prototype.getDescription=function(){return"Setting hardware scaling level to "+this._currentScale},t.prototype.apply=function(e,n){return this._currentScale===-1&&(this._currentScale=e.getEngine().getHardwareScalingLevel(),this._currentScale>this.maximumScale&&(this._directionOffset=-1)),this._currentScale+=this._directionOffset*this.step,e.getEngine().setHardwareScalingLevel(this._currentScale),this._directionOffset===1?this._currentScale>=this.maximumScale:this._currentScale<=this.maximumScale},t}(vi),xa=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.getDescription=function(){return"Turning shadows on/off"},t.prototype.apply=function(e,n){return e.shadowsEnabled=n.isInImprovementMode,!0},t}(vi),Ca=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.getDescription=function(){return"Turning post-processes on/off"},t.prototype.apply=function(e,n){return e.postProcessesEnabled=n.isInImprovementMode,!0},t}(vi),Ra=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.getDescription=function(){return"Turning lens flares on/off"},t.prototype.apply=function(e,n){return e.lensFlaresEnabled=n.isInImprovementMode,!0},t}(vi),_f=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.getDescription=function(){return this.onGetDescription?this.onGetDescription():"Running user defined callback"},t.prototype.apply=function(e,n){return!this.onApply||this.onApply(e,n)},t}(vi),Oa=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.getDescription=function(){return"Turning particles on/off"},t.prototype.apply=function(e,n){return e.particlesEnabled=n.isInImprovementMode,!0},t}(vi),qc=function(r){function t(){return r!==null&&r.apply(this,arguments)||this}return Object(c.d)(t,r),t.prototype.getDescription=function(){return"Turning render targets off"},t.prototype.apply=function(e,n){return e.renderTargetsEnabled=n.isInImprovementMode,!0},t}(vi),Ma=function(r){function t(){var e=r!==null&&r.apply(this,arguments)||this;return e._canBeMerged=function(n){if(!(n instanceof De.a))return!1;var i=n;return!i.isDisposed()&&!(!i.isVisible||!i.isEnabled())&&!(i.instances.length>0)&&!i.skeleton&&!i.hasLODLevels},e}return Object(c.d)(t,r),Object.defineProperty(t,"UpdateSelectionTree",{get:function(){return t._UpdateSelectionTree},set:function(e){t._UpdateSelectionTree=e},enumerable:!1,configurable:!0}),t.prototype.getDescription=function(){return"Merging similar meshes together"},t.prototype.apply=function(e,n,i){for(var o=e.meshes.slice(0),a=o.length,s=0;s<a;s++){var d=new Array,p=o[s];if(this._canBeMerged(p)){d.push(p);for(var b=s+1;b<a;b++){var P=o[b];this._canBeMerged(P)&&P.material===p.material&&P.checkCollisions===p.checkCollisions&&(d.push(P),a--,o.splice(b,1),b--)}d.length<2||De.a.MergeMeshes(d,void 0,!0)}}var O=e;return O.createOrUpdateSelectionOctree&&(i!=null?i&&O.createOrUpdateSelectionOctree():t.UpdateSelectionTree&&O.createOrUpdateSelectionOctree()),!0},t._UpdateSelectionTree=!1,t}(vi),Zc=function(){function r(t,e){t===void 0&&(t=60),e===void 0&&(e=2e3),this.targetFrameRate=t,this.trackerDuration=e,this.optimizations=new Array}return r.prototype.addOptimization=function(t){return this.optimizations.push(t),this},r.prototype.addCustomOptimization=function(t,e,n){n===void 0&&(n=0);var i=new _f(n);return i.onApply=t,i.onGetDescription=e,this.optimizations.push(i),this},r.LowDegradationAllowed=function(t){var e=new r(t),n=0;return e.addOptimization(new Ma(n)),e.addOptimization(new xa(n)),e.addOptimization(new Ra(n)),n++,e.addOptimization(new Ca(n)),e.addOptimization(new Oa(n)),n++,e.addOptimization(new Pa(n,1024)),e},r.ModerateDegradationAllowed=function(t){var e=new r(t),n=0;return e.addOptimization(new Ma(n)),e.addOptimization(new xa(n)),e.addOptimization(new Ra(n)),n++,e.addOptimization(new Ca(n)),e.addOptimization(new Oa(n)),n++,e.addOptimization(new Pa(n,512)),n++,e.addOptimization(new qc(n)),n++,e.addOptimization(new Qc(n,2)),e},r.HighDegradationAllowed=function(t){var e=new r(t),n=0;return e.addOptimization(new Ma(n)),e.addOptimization(new xa(n)),e.addOptimization(new Ra(n)),n++,e.addOptimization(new Ca(n)),e.addOptimization(new Oa(n)),n++,e.addOptimization(new Pa(n,256)),n++,e.addOptimization(new qc(n)),n++,e.addOptimization(new Qc(n,4)),e},r}(),sv=function(){function r(t,e,n,i){var o=this;if(n===void 0&&(n=!0),i===void 0&&(i=!1),this._isRunning=!1,this._currentPriorityLevel=0,this._targetFrameRate=60,this._trackerDuration=2e3,this._currentFrameRate=0,this._improvementMode=!1,this.onSuccessObservable=new C.c,this.onNewOptimizationAppliedObservable=new C.c,this.onFailureObservable=new C.c,this._options=e||new Zc,this._options.targetFrameRate&&(this._targetFrameRate=this._options.targetFrameRate),this._options.trackerDuration&&(this._trackerDuration=this._options.trackerDuration),n)for(var a=0,s=0,d=this._options.optimizations;s<d.length;s++)d[s].priority=a++;this._improvementMode=i,this._scene=t||te.a.LastCreatedScene,this._sceneDisposeObserver=this._scene.onDisposeObservable.add(function(){o._sceneDisposeObserver=null,o.dispose()})}return Object.defineProperty(r.prototype,"isInImprovementMode",{get:function(){return this._improvementMode},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"currentPriorityLevel",{get:function(){return this._currentPriorityLevel},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"currentFrameRate",{get:function(){return this._currentFrameRate},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"targetFrameRate",{get:function(){return this._targetFrameRate},set:function(t){this._targetFrameRate=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"trackerDuration",{get:function(){return this._trackerDuration},set:function(t){this._trackerDuration=t},enumerable:!1,configurable:!0}),Object.defineProperty(r.prototype,"optimizations",{get:function(){return this._options.optimizations},enumerable:!1,configurable:!0}),r.prototype.stop=function(){this._isRunning=!1},r.prototype.reset=function(){this._currentPriorityLevel=0},r.prototype.start=function(){var t=this;this._isRunning||(this._isRunning=!0,this._scene.executeWhenReady(function(){setTimeout(function(){t._checkCurrentState()},t._trackerDuration)}))},r.prototype._checkCurrentState=function(){var t=this;if(this._isRunning){var e=this._scene,n=this._options;if(this._currentFrameRate=Math.round(e.getEngine().getFps()),this._improvementMode&&this._currentFrameRate<=this._targetFrameRate||!this._improvementMode&&this._currentFrameRate>=this._targetFrameRate)return this._isRunning=!1,void this.onSuccessObservable.notifyObservers(this);for(var i=!0,o=!0,a=0;a<n.optimizations.length;a++){var s=n.optimizations[a];s.priority===this._currentPriorityLevel&&(o=!1,i=i&&s.apply(e,this),this.onNewOptimizationAppliedObservable.notifyObservers(s))}if(o)return this._isRunning=!1,void 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0&&(s=null),o=o??function(){return 1},a=a??function(){return 1},s=s??function(P,O){return P===O?0:1},this._characterToIdx=new Map,this._insertionCosts=new Array(i.length),this._deletionCosts=new Array(i.length),this._substitutionCosts=new Array(i.length);for(var p=0;p<i.length;++p){d=i[p],this._characterToIdx.set(d,p),this._insertionCosts[p]=o(d),this._deletionCosts[p]=a(d),this._substitutionCosts[p]=new Array(i.length);for(var b=p;b<i.length;++b)this._substitutionCosts[p][b]=s(d,i[b])}}return n.prototype.serialize=function(){var i={},o=new Array(this._characterToIdx.size);return this._characterToIdx.forEach(function(a,s){o[a]=s}),i.characters=o,i.insertionCosts=this._insertionCosts,i.deletionCosts=this._deletionCosts,i.substitutionCosts=this._substitutionCosts,JSON.stringify(i)},n.Deserialize=function(i){var o=JSON.parse(i),a=new n(o.characters);return a._insertionCosts=o.insertionCosts,a._deletionCosts=o.deletionCosts,a._substitutionCosts=o.substitutionCosts,a},n.prototype.getCharacterIdx=function(i){return this._characterToIdx.get(i)},n.prototype.getInsertionCost=function(i){return this._insertionCosts[i]},n.prototype.getDeletionCost=function(i){return this._deletionCosts[i]},n.prototype.getSubstitutionCost=function(i,o){var a=Math.min(i,o),s=Math.max(i,o);return this._substitutionCosts[a][s]},n}();r.Alphabet=t;var e=function(){function n(i,o){var a=this;if(i.length>n.MAX_SEQUENCE_LENGTH)throw new Error("Sequences longer than "+n.MAX_SEQUENCE_LENGTH+" not supported.");this._alphabet=o,this._characters=i.map(function(s){return a._alphabet.getCharacterIdx(s)})}return n.prototype.serialize=function(){return JSON.stringify(this._characters)},n.Deserialize=function(i,o){var a=new n([],o);return a._characters=JSON.parse(i),a},n.prototype.distance=function(i){return n._distance(this,i)},n._distance=function(i,o){var a=i._alphabet;if(a!==o._alphabet)throw new Error("Cannot Levenshtein compare Sequences built from different alphabets.");var s=i._characters,d=o._characters,p=s.length,b=d.length,P=n._costMatrix;P[0][0]=0;for(var O=0;O<p;++O)P[O+1][0]=P[O][0]+a.getInsertionCost(s[O]);for(O=0;O<b;++O)P[0][O+1]=P[0][O]+a.getInsertionCost(d[O]);for(var B=0;B<p;++B)for(var F=0;F<b;++F)n._insertionCost=P[B+1][F]+a.getInsertionCost(d[F]),n._deletionCost=P[B][F+1]+a.getDeletionCost(s[B]),n._substitutionCost=P[B][F]+a.getSubstitutionCost(s[B],d[F]),P[B+1][F+1]=Math.min(n._insertionCost,n._deletionCost,n._substitutionCost);return P[p][b]},n.MAX_SEQUENCE_LENGTH=256,n._costMatrix=Object(c.f)(Array(n.MAX_SEQUENCE_LENGTH+1)).map(function(i){return new Array(n.MAX_SEQUENCE_LENGTH+1)}),n}();r.Sequence=e})(kr||(kr={}));var _v=function(){function r(t){t===void 0&&(t=.01),this._points=[],this._segmentLength=t}return r.prototype.serialize=function(){return JSON.stringify(this)},r.Deserialize=function(t){var e=JSON.parse(t),n=new r(e._segmentLength);return n._points=e._points.map(function(i){return new u.e(i._x,i._y,i._z)}),n},r.prototype.getLength=function(){return this._points.length*this._segmentLength},r.prototype.add=function(t){var e=this,n=this._points.length;if(n===0)this._points.push(t.clone());else for(var i=function(){return e._segmentLength/u.e.Distance(e._points[n-1],t)},o=i();o<=1;o=i()){var a=this._points[n-1].scale(1-o);t.scaleAndAddToRef(o,a),this._points.push(a),++n}},r.prototype.resampleAtTargetResolution=function(t){var e=new r(this.getLength()/t);return this._points.forEach(function(n){e.add(n)}),e},r.prototype.tokenize=function(t){for(var e=[],n=new u.e,i=2;i<this._points.length;++i)r._transformSegmentDirToRef(this._points[i-2],this._points[i-1],this._points[i],n)&&e.push(r._tokenizeSegment(n,t));return e},r._transformSegmentDirToRef=function(t,e,n,i){return e.subtractToRef(t,r._forwardDir),r._forwardDir.normalize(),e.scaleToRef(-1,r._inverseFromVec),r._inverseFromVec.normalize(),!(Math.abs(u.e.Dot(r._forwardDir,r._inverseFromVec))>.98)&&(u.e.CrossToRef(r._forwardDir,r._inverseFromVec,r._upDir),r._upDir.normalize(),u.a.LookAtLHToRef(t,e,r._upDir,r._lookMatrix),n.subtractToRef(e,r._fromToVec),r._fromToVec.normalize(),u.e.TransformNormalToRef(r._fromToVec,r._lookMatrix,i),!0)},r._tokenizeSegment=function(t,e){r._bestMatch=0,r._score=u.e.Dot(t,e[0]),r._bestScore=r._score;for(var n=1;n<e.length;++n)r._score=u.e.Dot(t,e[n]),r._score>r._bestScore&&(r._bestMatch=n,r._bestScore=r._score);return r._bestMatch},r._forwardDir=new u.e,r._inverseFromVec=new u.e,r._upDir=new u.e,r._fromToVec=new u.e,r._lookMatrix=new u.a,r}(),gf=function(){function r(t){this.chars=new Array(t)}return r.Generate=function(t,e,n,i,o){t===void 0&&(t=64),e===void 0&&(e=256),n===void 0&&(n=.1),i===void 0&&(i=.001),o===void 0&&(o=[]);for(var a,s,d=new r(t),p=0;p<t;++p)d.chars[p]=new u.e(Math.random()-.5,Math.random()-.5,Math.random()-.5),d.chars[p].normalize();for(p=0;p<o.length;++p)d.chars[p].copyFrom(o[p]);for(var b,P=new u.e,O=new u.e,B=0;B<e;++B){a=(1-(b=B/(e-1)))*n+b*i;var F=function(z){P.copyFromFloats(0,0,0),d.chars.forEach(function(J){d.chars[z].subtractToRef(J,O),(s=O.lengthSquared())>1e-6&&O.scaleAndAddToRef(1/(O.lengthSquared()*s),P)}),P.scaleInPlace(a),d.chars[z].addInPlace(P),d.chars[z].normalize()};for(p=o.length;p<d.chars.length;++p)F(p)}return d},r.prototype.serialize=function(){return JSON.stringify(this.chars)},r.Deserialize=function(t){for(var e=JSON.parse(t),n=new r(e.length),i=0;i<e.length;++i)n.chars[i]=new u.e(e[i]._x,e[i]._y,e[i]._z);return n},r}(),el=function(){function r(){this._sequences=[]}return r.prototype.serialize=function(){return JSON.stringify(this._sequences.map(function(t){return t.serialize()}))},r.Deserialize=function(t,e){var n=new r;return n._sequences=JSON.parse(t).map(function(i){return kr.Sequence.Deserialize(i,e)}),n},r.CreateFromTrajectory=function(t,e,n){return r.CreateFromTokenizationPyramid(r._getTokenizationPyramid(t,e),n)},r.CreateFromTokenizationPyramid=function(t,e){var n=new r;return n._sequences=t.map(function(i){return new kr.Sequence(i,e)}),n},r._getTokenizationPyramid=function(t,e,n){n===void 0&&(n=r.FINEST_DESCRIPTOR_RESOLUTION);for(var i=[],o=n;o>4;o=Math.floor(o/2))i.push(t.resampleAtTargetResolution(o).tokenize(e.chars));return i},r.prototype.distance=function(t){for(var e=0,n=0;n<this._sequences.length;++n)e+=Math.pow(2,n)*this._sequences[n].distance(t._sequences[n]);return e},r.FINEST_DESCRIPTOR_RESOLUTION=32,r}(),vf=function(){function r(t){t===void 0&&(t=[]),this._descriptors=t,this._centroidIdx=-1,this._averageDistance=0,this._refreshDescription()}return r.prototype.serialize=function(){var t={};return t.descriptors=this._descriptors.map(function(e){return e.serialize()}),t.centroidIdx=this._centroidIdx,t.averageDistance=this._averageDistance,JSON.stringify(t)},r.Deserialize=function(t,e){var n=JSON.parse(t),i=new r;return i._descriptors=n.descriptors.map(function(o){return el.Deserialize(o,e)}),i._centroidIdx=n.centroidIdx,i._averageDistance=n.averageDistance,i},r.prototype.add=function(t){this._descriptors.push(t),this._refreshDescription()},r.prototype.getMatchCost=function(t){return t.distance(this._descriptors[this._centroidIdx])/this._averageDistance},r.prototype.getMatchMinimumDistance=function(t){return Math.min.apply(Math,this._descriptors.map(function(e){return e.distance(t)}))},r.prototype._refreshDescription=function(){var t,e=this;this._centroidIdx=-1;for(var n=this._descriptors.map(function(o){return t=0,e._descriptors.forEach(function(a){t+=o.distance(a)}),t}),i=0;i<n.length;++i)(this._centroidIdx<0||n[i]<n[this._centroidIdx])&&(this._centroidIdx=i);this._averageDistance=0,this._descriptors.forEach(function(o){e._averageDistance+=o.distance(e._descriptors[e._centroidIdx])}),this._descriptors.length>0&&(this._averageDistance=Math.max(this._averageDistance/this._descriptors.length,r.MIN_AVERAGE_DISTANCE))},r.MIN_AVERAGE_DISTANCE=1,r}(),mv=function(){function r(){this._maximumAllowableMatchCost=4,this._nameToDescribedTrajectory=new Map}return r.prototype.serialize=function(){var t={};return t.maximumAllowableMatchCost=this._maximumAllowableMatchCost,t.vector3Alphabet=this._vector3Alphabet.serialize(),t.levenshteinAlphabet=this._levenshteinAlphabet.serialize(),t.nameToDescribedTrajectory=[],this._nameToDescribedTrajectory.forEach(function(e,n){t.nameToDescribedTrajectory.push(n),t.nameToDescribedTrajectory.push(e.serialize())}),JSON.stringify(t)},r.Deserialize=function(t){var e=JSON.parse(t),n=new r;n._maximumAllowableMatchCost=e.maximumAllowableMatchCost,n._vector3Alphabet=gf.Deserialize(e.vector3Alphabet),n._levenshteinAlphabet=kr.Alphabet.Deserialize(e.levenshteinAlphabet);for(var i=0;i<e.nameToDescribedTrajectory.length;i+=2)n._nameToDescribedTrajectory.set(e.nameToDescribedTrajectory[i],vf.Deserialize(e.nameToDescribedTrajectory[i+1],n._levenshteinAlphabet));return n},r.Generate=function(){for(var t=gf.Generate(64,256,.1,.001,[u.e.Forward()]),e=new Array(t.chars.length),n=0;n<e.length;++n)e[n]=n;var i=new kr.Alphabet(e,function(a){return a===0?0:1},function(a){return a===0?0:1},function(a,s){return Math.min(1-u.e.Dot(t.chars[a],t.chars[s]),1)}),o=new r;return o._vector3Alphabet=t,o._levenshteinAlphabet=i,o},r.prototype.addTrajectoryToClassification=function(t,e){this._nameToDescribedTrajectory.has(e)||this._nameToDescribedTrajectory.set(e,new vf),this._nameToDescribedTrajectory.get(e).add(el.CreateFromTrajectory(t,this._vector3Alphabet,this._levenshteinAlphabet))},r.prototype.deleteClassification=function(t){return this._nameToDescribedTrajectory.delete(t)},r.prototype.classifyTrajectory=function(t){var e=this,n=el.CreateFromTrajectory(t,this._vector3Alphabet,this._levenshteinAlphabet),i=[];if(this._nameToDescribedTrajectory.forEach(function(p,b){p.getMatchCost(n)<e._maximumAllowableMatchCost&&i.push(b)}),i.length===0)return null;for(var o,a=0,s=this._nameToDescribedTrajectory.get(i[a]).getMatchMinimumDistance(n),d=0;d<i.length;++d)(o=this._nameToDescribedTrajectory.get(i[d]).getMatchMinimumDistance(n))<s&&(s=o,a=d);return i[a]},r}(),gv=f(150),Da=function(r){function t(e,n){n===void 0&&(n={});var i=r.call(this,e)||this;return i.options=n,i._direction=new u.e(0,0,-1),i._mat=new u.a,i._onSelectEnabled=!1,i._origin=new u.e(0,0,0),i.lastNativeXRHitResults=[],i.onHitTestResultObservable=new C.c,i._onHitTestResults=function(o){var a=o.map(function(s){var d=u.a.FromArray(s.hitMatrix);return i._xrSessionManager.scene.useRightHandedSystem||d.toggleModelMatrixHandInPlace(),i.options.worldParentNode&&d.multiplyToRef(i.options.worldParentNode.getWorldMatrix(),d),{xrHitResult:s,transformationMatrix:d}});i.lastNativeXRHitResults=o,i.onHitTestResultObservable.notifyObservers(a)},i._onSelect=function(o){i._onSelectEnabled&&t.XRHitTestWithSelectEvent(o,i._xrSessionManager.referenceSpace)},i.xrNativeFeatureName="hit-test",Xe.b.Warn("A newer version of this plugin is available"),i}return Object(c.d)(t,r),t.XRHitTestWithRay=function(e,n,i,o){return e.requestHitTest(n,i).then(function(a){var s=o||function(d){return!!d.hitMatrix};return a.filter(s)})},t.XRHitTestWithSelectEvent=function(e,n){var i=e.frame.getPose(e.inputSource.targetRaySpace,n);if(!i)return Promise.resolve([]);var o=new XRRay(i.transform);return this.XRHitTestWithRay(e.frame.session,o,n)},t.prototype.attach=function(){return!!r.prototype.attach.call(this)&&(this.options.testOnPointerDownOnly&&this._xrSessionManager.session.addEventListener("select",this._onSelect,!1),!0)},t.prototype.detach=function(){return!!r.prototype.detach.call(this)&&(this._onSelectEnabled=!1,this._xrSessionManager.session.removeEventListener("select",this._onSelect),!0)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onHitTestResultObservable.clear()},t.prototype._onXRFrame=function(e){if(this.attached&&!this.options.testOnPointerDownOnly){var n=e.getViewerPose(this._xrSessionManager.referenceSpace);if(n){u.a.FromArrayToRef(n.transform.matrix,0,this._mat),u.e.TransformCoordinatesFromFloatsToRef(0,0,0,this._mat,this._origin),u.e.TransformCoordinatesFromFloatsToRef(0,0,-1,this._mat,this._direction),this._direction.subtractInPlace(this._origin),this._direction.normalize();var i=new XRRay({x:this._origin.x,y:this._origin.y,z:this._origin.z,w:0},{x:this._direction.x,y:this._direction.y,z:this._direction.z,w:0});t.XRHitTestWithRay(this._xrSessionManager.session,i,this._xrSessionManager.referenceSpace).then(this._onHitTestResults)}}},t.Name=ai.HIT_TEST,t.Version=1,t}(si);qn.AddWebXRFeature(Da.Name,function(r,t){return function(){return new Da(r,t)}},Da.Version,!1);var vv=0,La=function(r){function t(e,n){n===void 0&&(n={});var i=r.call(this,e)||this;return i._options=n,i._lastFrameDetected=new Set,i._trackedAnchors=[],i._futureAnchors=[],i.onAnchorAddedObservable=new C.c,i.onAnchorRemovedObservable=new C.c,i.onAnchorUpdatedObservable=new C.c,i._tmpVector=new u.e,i._tmpQuaternion=new u.b,i.xrNativeFeatureName="anchors",i}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"referenceSpaceForFrameAnchors",{set:function(e){this._referenceSpaceForFrameAnchors=e},enumerable:!1,configurable:!0}),t.prototype._populateTmpTransformation=function(e,n){return this._tmpVector.copyFrom(e),this._tmpQuaternion.copyFrom(n),this._xrSessionManager.scene.useRightHandedSystem||(this._tmpVector.z*=-1,this._tmpQuaternion.z*=-1,this._tmpQuaternion.w*=-1),{position:this._tmpVector,rotationQuaternion:this._tmpQuaternion}},t.prototype.addAnchorPointUsingHitTestResultAsync=function(e,n,i){return n===void 0&&(n=new u.e),i===void 0&&(i=new u.b),Object(c.b)(this,void 0,void 0,function(){var o,a,s,d=this;return Object(c.e)(this,function(p){switch(p.label){case 0:if(this._populateTmpTransformation(n,i),o=new XRRigidTransform({x:this._tmpVector.x,y:this._tmpVector.y,z:this._tmpVector.z},{x:this._tmpQuaternion.x,y:this._tmpQuaternion.y,z:this._tmpQuaternion.z,w:this._tmpQuaternion.w}),e.xrHitResult.createAnchor)return[3,1];throw this.detach(),new Error("Anchors not enabled in this environment/browser");case 1:return p.trys.push([1,3,,4]),[4,e.xrHitResult.createAnchor(o)];case 2:return a=p.sent(),[2,new Promise(function(b,P){d._futureAnchors.push({nativeAnchor:a,resolved:!1,submitted:!0,xrTransformation:o,resolve:b,reject:P})})];case 3:throw s=p.sent(),new Error(s);case 4:return[2]}})})},t.prototype.addAnchorAtPositionAndRotationAsync=function(e,n,i){return n===void 0&&(n=new u.b),i===void 0&&(i=!1),Object(c.b)(this,void 0,void 0,function(){var o,a,s,d=this;return Object(c.e)(this,function(p){switch(p.label){case 0:return this._populateTmpTransformation(e,n),o=new XRRigidTransform({x:this._tmpVector.x,y:this._tmpVector.y,z:this._tmpVector.z},{x:this._tmpQuaternion.x,y:this._tmpQuaternion.y,z:this._tmpQuaternion.z,w:this._tmpQuaternion.w}),i&&this.attached&&this._xrSessionManager.currentFrame?[4,this._createAnchorAtTransformation(o,this._xrSessionManager.currentFrame)]:[3,2];case 1:return s=p.sent(),[3,3];case 2:s=void 0,p.label=3;case 3:return a=s,[2,new Promise(function(b,P){d._futureAnchors.push({nativeAnchor:a,resolved:!1,submitted:!1,xrTransformation:o,resolve:b,reject:P})})]}})})},Object.defineProperty(t.prototype,"anchors",{get:function(){return this._trackedAnchors},enumerable:!1,configurable:!0}),t.prototype.detach=function(){if(!r.prototype.detach.call(this))return!1;if(!this._options.doNotRemoveAnchorsOnSessionEnded)for(;this._trackedAnchors.length;){var e=this._trackedAnchors.pop();if(e){try{e.remove()}catch{}this.onAnchorRemovedObservable.notifyObservers(e)}}return!0},t.prototype.dispose=function(){this._futureAnchors.length=0,r.prototype.dispose.call(this),this.onAnchorAddedObservable.clear(),this.onAnchorRemovedObservable.clear(),this.onAnchorUpdatedObservable.clear()},t.prototype._onXRFrame=function(e){var n=this;if(this.attached&&e){var i=e.trackedAnchors;if(i){var o=this._trackedAnchors.filter(function(s){return!i.has(s.xrAnchor)}).map(function(s){return n._trackedAnchors.indexOf(s)}),a=0;o.forEach(function(s){var d=n._trackedAnchors.splice(s-a,1)[0];n.onAnchorRemovedObservable.notifyObservers(d),a++}),i.forEach(function(s){if(n._lastFrameDetected.has(s)){var d=n._findIndexInAnchorArray(s);b=n._trackedAnchors[d];try{n._updateAnchorWithXRFrame(s,b,e),b.attachedNode&&(b.attachedNode.rotationQuaternion=b.attachedNode.rotationQuaternion||new u.b,b.transformationMatrix.decompose(b.attachedNode.scaling,b.attachedNode.rotationQuaternion,b.attachedNode.position)),n.onAnchorUpdatedObservable.notifyObservers(b)}catch{Xe.b.Warn("Anchor could not be updated")}}else{var p={id:vv++,xrAnchor:s,remove:s.delete},b=n._updateAnchorWithXRFrame(s,p,e);n._trackedAnchors.push(b),n.onAnchorAddedObservable.notifyObservers(b);var P=n._futureAnchors.filter(function(O){return O.nativeAnchor===s})[0];P&&(P.resolve(b),P.resolved=!0)}}),this._lastFrameDetected=i}this._futureAnchors.forEach(function(s){s.resolved||s.submitted||(n._createAnchorAtTransformation(s.xrTransformation,e).then(function(d){s.nativeAnchor=d},function(d){s.resolved=!0,s.reject(d)}),s.submitted=!0)})}},t.prototype._findIndexInAnchorArray=function(e){for(var n=0;n<this._trackedAnchors.length;++n)if(this._trackedAnchors[n].xrAnchor===e)return n;return-1},t.prototype._updateAnchorWithXRFrame=function(e,n,i){var o=i.getPose(e.anchorSpace,this._xrSessionManager.referenceSpace);if(o){var a=n.transformationMatrix||new u.a;u.a.FromArrayToRef(o.transform.matrix,0,a),this._xrSessionManager.scene.useRightHandedSystem||a.toggleModelMatrixHandInPlace(),n.transformationMatrix=a,this._options.worldParentNode&&a.multiplyToRef(this._options.worldParentNode.getWorldMatrix(),a)}return n},t.prototype._createAnchorAtTransformation=function(e,n){var i;return Object(c.b)(this,void 0,void 0,function(){return Object(c.e)(this,function(o){if(!n.createAnchor)throw this.detach(),new Error("Anchors are not enabled in your browser");try{return[2,n.createAnchor(e,(i=this._referenceSpaceForFrameAnchors)!==null&&i!==void 0?i:this._xrSessionManager.referenceSpace)]}catch(a){throw new Error(a)}return[2]})})},t.Name=ai.ANCHOR_SYSTEM,t.Version=1,t}(si);qn.AddWebXRFeature(La.Name,function(r,t){return function(){return new La(r,t)}},La.Version);var bv=0,Na=function(r){function t(e,n){n===void 0&&(n={});var i=r.call(this,e)||this;return i._options=n,i._detectedPlanes=[],i._enabled=!1,i._lastFrameDetected=new Set,i.onPlaneAddedObservable=new C.c,i.onPlaneRemovedObservable=new C.c,i.onPlaneUpdatedObservable=new C.c,i.xrNativeFeatureName="plane-detection",i._xrSessionManager.session?i._init():i._xrSessionManager.onXRSessionInit.addOnce(function(){i._init()}),i}return Object(c.d)(t,r),t.prototype.detach=function(){if(!r.prototype.detach.call(this))return!1;if(!this._options.doNotRemovePlanesOnSessionEnded)for(;this._detectedPlanes.length;){var e=this._detectedPlanes.pop();e&&this.onPlaneRemovedObservable.notifyObservers(e)}return!0},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onPlaneAddedObservable.clear(),this.onPlaneRemovedObservable.clear(),this.onPlaneUpdatedObservable.clear()},t.prototype.isCompatible=function(){return typeof XRPlane<"u"},t.prototype._onXRFrame=function(e){var n=this;if(this.attached&&this._enabled&&e){var i=e.worldInformation.detectedPlanes;if(i){var o=this._detectedPlanes.filter(function(s){return!i.has(s.xrPlane)}).map(function(s){return n._detectedPlanes.indexOf(s)}),a=0;o.forEach(function(s){var d=n._detectedPlanes.splice(s-a,1)[0];n.onPlaneRemovedObservable.notifyObservers(d),a++}),i.forEach(function(s){if(n._lastFrameDetected.has(s)){if(s.lastChangedTime===n._xrSessionManager.currentTimestamp){var d=n.findIndexInPlaneArray(s);b=n._detectedPlanes[d],n._updatePlaneWithXRPlane(s,b,e),n.onPlaneUpdatedObservable.notifyObservers(b)}}else{var p={id:bv++,xrPlane:s,polygonDefinition:[]},b=n._updatePlaneWithXRPlane(s,p,e);n._detectedPlanes.push(b),n.onPlaneAddedObservable.notifyObservers(b)}}),this._lastFrameDetected=i}}},t.prototype._init=function(){var e,n,i=this,o=function(){i._enabled=!0,i._detectedPlanes.length&&(i._detectedPlanes.length=0)};this._xrSessionManager.session.updateWorldTrackingState?(this._xrSessionManager.session.updateWorldTrackingState({planeDetectionState:{enabled:!0}}),o()):!((n=(e=this._xrSessionManager.session.worldTrackingState)===null||e===void 0?void 0:e.planeDetectionState)===null||n===void 0)&&n.enabled&&o()},t.prototype._updatePlaneWithXRPlane=function(e,n,i){var o=this;n.polygonDefinition=e.polygon.map(function(d){var p=o._xrSessionManager.scene.useRightHandedSystem?1:-1;return new u.e(d.x,d.y,d.z*p)});var a=i.getPose(e.planeSpace,this._xrSessionManager.referenceSpace);if(a){var s=n.transformationMatrix||new u.a;u.a.FromArrayToRef(a.transform.matrix,0,s),this._xrSessionManager.scene.useRightHandedSystem||s.toggleModelMatrixHandInPlace(),n.transformationMatrix=s,this._options.worldParentNode&&s.multiplyToRef(this._options.worldParentNode.getWorldMatrix(),s)}return n},t.prototype.findIndexInPlaneArray=function(e){for(var n=0;n<this._detectedPlanes.length;++n)if(this._detectedPlanes[n].xrPlane===e)return n;return-1},t.Name=ai.PLANE_DETECTION,t.Version=1,t}(si);qn.AddWebXRFeature(Na.Name,function(r,t){return function(){return new Na(r,t)}},Na.Version);var wa=function(r){function t(e,n){n===void 0&&(n={});var i=r.call(this,e)||this;return i.options=n,i.onBackgroundStateChangedObservable=new C.c,i}return Object(c.d)(t,r),t.prototype.attach=function(){return this._setBackgroundState(!1),r.prototype.attach.call(this)},t.prototype.detach=function(){return this._setBackgroundState(!0),r.prototype.detach.call(this)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onBackgroundStateChangedObservable.clear()},t.prototype._onXRFrame=function(e){},t.prototype._setBackgroundState=function(e){var n=this._xrSessionManager.scene;if(!this.options.ignoreEnvironmentHelper)if(this.options.environmentHelperRemovalFlags){if(this.options.environmentHelperRemovalFlags.skyBox){var i=n.getMeshByName("BackgroundSkybox");i&&i.setEnabled(e)}if(this.options.environmentHelperRemovalFlags.ground){var o=n.getMeshByName("BackgroundPlane");o&&o.setEnabled(e)}}else{var a=n.getMeshByName("BackgroundHelper");a&&a.setEnabled(e)}this.options.backgroundMeshes&&this.options.backgroundMeshes.forEach(function(s){return s.setEnabled(e)}),this.onBackgroundStateChangedObservable.notifyObservers(e)},t.Name=ai.BACKGROUND_REMOVER,t.Version=1,t}(si);qn.AddWebXRFeature(wa.Name,function(r,t){return function(){return new wa(r,t)}},wa.Version,!0);var yv=function(){},Fa=function(r){function t(e,n){var i=r.call(this,e)||this;return i._options=n,i._attachController=function(o){if(!i._controllers[o.uniqueId])if(i._xrSessionManager.scene.isPhysicsEnabled()||l.a.Warn("physics engine not enabled, skipped. Please add this controller manually."),i._options.physicsProperties.useControllerMesh&&o.inputSource.gamepad)o.onMotionControllerInitObservable.addOnce(function(P){P.onModelLoadedObservable.addOnce(function(){var O=new xt.a(P.rootMesh,xt.a.MeshImpostor,Object(c.a)({mass:0},i._options.physicsProperties)),B=o.grip||o.pointer;i._controllers[o.uniqueId]={xrController:o,impostor:O,oldPos:B.position.clone(),oldRotation:B.rotationQuaternion.clone()}})});else{var a=i._options.physicsProperties.impostorType||xt.a.SphereImpostor,s=i._options.physicsProperties.impostorSize||.1,d=Fn.a.CreateSphere("impostor-mesh-"+o.uniqueId,{diameterX:typeof s=="number"?s:s.width,diameterY:typeof s=="number"?s:s.height,diameterZ:typeof s=="number"?s:s.depth});d.isVisible=i._debugMode,d.isPickable=!1,d.rotationQuaternion=new u.b;var p=o.grip||o.pointer;d.position.copyFrom(p.position),d.rotationQuaternion.copyFrom(p.rotationQuaternion);var b=new xt.a(d,a,Object(c.a)({mass:0},i._options.physicsProperties));i._controllers[o.uniqueId]={xrController:o,impostor:b,impostorMesh:d}}},i._controllers={},i._debugMode=!1,i._delta=0,i._lastTimestamp=0,i._tmpQuaternion=new u.b,i._tmpVector=new u.e,i._options.physicsProperties||(i._options.physicsProperties={}),i}return Object(c.d)(t,r),t.prototype._enablePhysicsDebug=function(){var e=this;this._debugMode=!0,Object.keys(this._controllers).forEach(function(n){var i=e._controllers[n];i.impostorMesh&&(i.impostorMesh.isVisible=!0)})},t.prototype.addController=function(e){this._attachController(e)},t.prototype.attach=function(){var e=this;if(!r.prototype.attach.call(this))return!1;if(!this._options.xrInput)return!0;if(this._options.xrInput.controllers.forEach(this._attachController),this._addNewAttachObserver(this._options.xrInput.onControllerAddedObservable,this._attachController),this._addNewAttachObserver(this._options.xrInput.onControllerRemovedObservable,function(o){e._detachController(o.uniqueId)}),this._options.enableHeadsetImpostor){var n=this._options.headsetImpostorParams||{impostorType:xt.a.SphereImpostor,restitution:.8,impostorSize:.3},i=n.impostorSize||.3;this._headsetMesh=Fn.a.CreateSphere("headset-mesh",{diameterX:typeof i=="number"?i:i.width,diameterY:typeof i=="number"?i:i.height,diameterZ:typeof i=="number"?i:i.depth}),this._headsetMesh.rotationQuaternion=new u.b,this._headsetMesh.isVisible=!1,this._headsetImpostor=new xt.a(this._headsetMesh,n.impostorType,Object(c.a)({mass:0},n))}return!0},t.prototype.detach=function(){var e=this;return!!r.prototype.detach.call(this)&&(Object.keys(this._controllers).forEach(function(n){e._detachController(n)}),this._headsetMesh&&this._headsetMesh.dispose(),!0)},t.prototype.getHeadsetImpostor=function(){return this._headsetImpostor},t.prototype.getImpostorForController=function(e){var n=typeof e=="string"?e:e.uniqueId;return this._controllers[n]?this._controllers[n].impostor:null},t.prototype.setPhysicsProperties=function(e){this._options.physicsProperties=Object(c.a)(Object(c.a)({},this._options.physicsProperties),e)},t.prototype._onXRFrame=function(e){var n=this;this._delta=this._xrSessionManager.currentTimestamp-this._lastTimestamp,this._lastTimestamp=this._xrSessionManager.currentTimestamp,this._headsetMesh&&(this._headsetMesh.position.copyFrom(this._options.xrInput.xrCamera.position),this._headsetMesh.rotationQuaternion.copyFrom(this._options.xrInput.xrCamera.rotationQuaternion)),Object.keys(this._controllers).forEach(function(i){var o=n._controllers[i],a=o.xrController.grip||o.xrController.pointer,s=o.oldPos||o.impostorMesh.position,d=o.oldRotation||o.impostorMesh.rotationQuaternion;if(a.position.subtractToRef(s,n._tmpVector),n._tmpVector.scaleInPlace(1e3/n._delta),o.impostor.setLinearVelocity(n._tmpVector),n._debugMode&&console.log(n._tmpVector,"linear"),!d.equalsWithEpsilon(a.rotationQuaternion)){d.conjugateInPlace().multiplyToRef(a.rotationQuaternion,n._tmpQuaternion);var p=Math.sqrt(n._tmpQuaternion.x*n._tmpQuaternion.x+n._tmpQuaternion.y*n._tmpQuaternion.y+n._tmpQuaternion.z*n._tmpQuaternion.z);if(n._tmpVector.set(n._tmpQuaternion.x,n._tmpQuaternion.y,n._tmpQuaternion.z),p<.001)n._tmpVector.scaleInPlace(2);else{var b=2*Math.atan2(p,n._tmpQuaternion.w);n._tmpVector.scaleInPlace(b/(p*(n._delta/1e3)))}o.impostor.setAngularVelocity(n._tmpVector),n._debugMode&&console.log(n._tmpVector,n._tmpQuaternion,"angular")}s.copyFrom(a.position),d.copyFrom(a.rotationQuaternion)})},t.prototype._detachController=function(e){var n=this._controllers[e];n&&(n.impostorMesh&&n.impostorMesh.dispose(),delete this._controllers[e])},t.Name=ai.PHYSICS_CONTROLLERS,t.Version=1,t}(si);qn.AddWebXRFeature(Fa.Name,function(r,t){return function(){return new Fa(r,t)}},Fa.Version,!0);var Ba=function(r){function t(e,n){n===void 0&&(n={});var i=r.call(this,e)||this;return i.options=n,i._tmpMat=new u.a,i._tmpPos=new u.e,i._tmpQuat=new u.b,i.initHitTestSource=function(o){if(o){var a=new XRRay(i.options.offsetRay||{}),s={space:i.options.useReferenceSpace?o:i._xrSessionManager.viewerReferenceSpace,offsetRay:a};i.options.entityTypes&&(s.entityTypes=i.options.entityTypes),s.space?i._xrSessionManager.session.requestHitTestSource(s).then(function(d){i._xrHitTestSource&&i._xrHitTestSource.cancel(),i._xrHitTestSource=d}):Xe.b.Warn("waiting for viewer reference space to initialize")}},i.autoCloneTransformation=!1,i.onHitTestResultObservable=new C.c,i.paused=!1,i.xrNativeFeatureName="hit-test",Xe.b.Warn("Hit test is an experimental and unstable feature."),i}return Object(c.d)(t,r),t.prototype.attach=function(){var e=this;if(!r.prototype.attach.call(this)||!this._xrSessionManager.session.requestHitTestSource)return!1;if(this.options.disablePermanentHitTest||(this._xrSessionManager.referenceSpace&&this.initHitTestSource(this._xrSessionManager.referenceSpace),this._xrSessionManager.onXRReferenceSpaceChanged.add(this.initHitTestSource)),this.options.enableTransientHitTest){var n=new XRRay(this.options.transientOffsetRay||{});this._xrSessionManager.session.requestHitTestSourceForTransientInput({profile:"generic-touchscreen",offsetRay:n,entityTypes:this.options.entityTypes}).then(function(i){e._transientXrHitTestSource=i})}return!0},t.prototype.detach=function(){return!!r.prototype.detach.call(this)&&(this._xrHitTestSource&&(this._xrHitTestSource.cancel(),this._xrHitTestSource=null),this._xrSessionManager.onXRReferenceSpaceChanged.removeCallback(this.initHitTestSource),this._transientXrHitTestSource&&(this._transientXrHitTestSource.cancel(),this._transientXrHitTestSource=null),!0)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onHitTestResultObservable.clear()},t.prototype._onXRFrame=function(e){var n=this;if(this.attached&&!this.paused){if(this._xrHitTestSource){var i=e.getHitTestResults(this._xrHitTestSource);this._processWebXRHitTestResult(i)}this._transientXrHitTestSource&&e.getHitTestResultsForTransientInput(this._transientXrHitTestSource).forEach(function(o){n._processWebXRHitTestResult(o.results,o.inputSource)})}},t.prototype._processWebXRHitTestResult=function(e,n){var i=this,o=[];e.forEach(function(a){var s=a.getPose(i._xrSessionManager.referenceSpace);if(s){var d=s.transform.position,p=s.transform.orientation;i._tmpPos.set(d.x,d.y,d.z),i._tmpQuat.set(p.x,p.y,p.z,p.w),u.a.FromFloat32ArrayToRefScaled(s.transform.matrix,0,1,i._tmpMat),i._xrSessionManager.scene.useRightHandedSystem||(i._tmpPos.z*=-1,i._tmpQuat.z*=-1,i._tmpQuat.w*=-1,i._tmpMat.toggleModelMatrixHandInPlace());var b={position:i.autoCloneTransformation?i._tmpPos.clone():i._tmpPos,rotationQuaternion:i.autoCloneTransformation?i._tmpQuat.clone():i._tmpQuat,transformationMatrix:i.autoCloneTransformation?i._tmpMat.clone():i._tmpMat,inputSource:n,isTransient:!!n,xrHitResult:a};o.push(b)}}),this.onHitTestResultObservable.notifyObservers(o)},t.Name=ai.HIT_TEST,t.Version=2,t}(si);qn.AddWebXRFeature(Ba.Name,function(r,t){return function(){return new Ba(r,t)}},Ba.Version,!1);var Ua=function(r){function t(e){var n=r.call(this,e)||this;return n._enabled=!1,n._featurePointCloud=[],n.onFeaturePointsAddedObservable=new C.c,n.onFeaturePointsUpdatedObservable=new C.c,n.xrNativeFeatureName="bjsfeature-points",n._xrSessionManager.session?n._init():n._xrSessionManager.onXRSessionInit.addOnce(function(){n._init()}),n}return Object(c.d)(t,r),Object.defineProperty(t.prototype,"featurePointCloud",{get:function(){return this._featurePointCloud},enumerable:!1,configurable:!0}),t.prototype.detach=function(){return!!r.prototype.detach.call(this)&&(this.featurePointCloud.length=0,!0)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this._featurePointCloud.length=0,this.onFeaturePointsUpdatedObservable.clear(),this.onFeaturePointsAddedObservable.clear()},t.prototype._onXRFrame=function(e){if(this.attached&&this._enabled&&e){var n=e.featurePointCloud;if(n&&n.length!==0){if(n.length%5!=0)throw new Error("Received malformed feature point cloud of length: "+n.length);for(var i=n.length/5,o=new Array,a=new Array,s=0;s<i;s++){var d=5*s,p=n[d+4];this._featurePointCloud[p]?o.push(p):(this._featurePointCloud[p]={position:new u.e,confidenceValue:0},a.push(p)),this._featurePointCloud[p].position.x=n[d],this._featurePointCloud[p].position.y=n[d+1],this._featurePointCloud[p].position.z=n[d+2],this._featurePointCloud[p].confidenceValue=n[d+3]}a.length>0&&this.onFeaturePointsAddedObservable.notifyObservers(a),o.length>0&&this.onFeaturePointsUpdatedObservable.notifyObservers(o)}}},t.prototype._init=function(){this._xrSessionManager.session.trySetFeaturePointCloudEnabled&&this._xrSessionManager.session.trySetFeaturePointCloudEnabled(!0)&&(this._enabled=!0)},t.Name=ai.FEATURE_POINTS,t.Version=1,t}(si);qn.AddWebXRFeature(Ua.Name,function(r){return function(){return new Ua(r)}},Ua.Version);var bf=function(){function r(t,e,n,i,o){this.xrController=t,this.trackedMeshes=e,this._handMesh=n,this._rigMapping=i,this._defaultHandMesh=!1,this._transformNodeMapping=[],this.handPartsDefinition=this.generateHandPartsDefinition(t.inputSource.hand),this._scene=e[0].getScene(),this._handMesh&&this._rigMapping?this._defaultHandMesh=!1:o||this._generateDefaultHandMesh(),this.xrController.motionController&&(this.xrController.motionController.rootMesh?this.xrController.motionController.rootMesh.setEnabled(!1):this.xrController.motionController.onModelLoadedObservable.add(function(a){a.rootMesh&&a.rootMesh.setEnabled(!1)})),this.xrController.onMotionControllerInitObservable.add(function(a){a.onModelLoadedObservable.add(function(s){s.rootMesh&&s.rootMesh.setEnabled(!1)}),a.rootMesh&&a.rootMesh.setEnabled(!1)})}return r.prototype.generateHandPartsDefinition=function(t){var e;return(e={}).wrist=[t.WRIST],e.thumb=[t.THUMB_METACARPAL,t.THUMB_PHALANX_PROXIMAL,t.THUMB_PHALANX_DISTAL,t.THUMB_PHALANX_TIP],e.index=[t.INDEX_METACARPAL,t.INDEX_PHALANX_PROXIMAL,t.INDEX_PHALANX_INTERMEDIATE,t.INDEX_PHALANX_DISTAL,t.INDEX_PHALANX_TIP],e.middle=[t.MIDDLE_METACARPAL,t.MIDDLE_PHALANX_PROXIMAL,t.MIDDLE_PHALANX_INTERMEDIATE,t.MIDDLE_PHALANX_DISTAL,t.MIDDLE_PHALANX_TIP],e.ring=[t.RING_METACARPAL,t.RING_PHALANX_PROXIMAL,t.RING_PHALANX_INTERMEDIATE,t.RING_PHALANX_DISTAL,t.RING_PHALANX_TIP],e.little=[t.LITTLE_METACARPAL,t.LITTLE_PHALANX_PROXIMAL,t.LITTLE_PHALANX_INTERMEDIATE,t.LITTLE_PHALANX_DISTAL,t.LITTLE_PHALANX_TIP],e},r.prototype.updateFromXRFrame=function(t,e,n){var i=this;n===void 0&&(n=2);var o=this.xrController.inputSource.hand;o&&this.trackedMeshes.forEach(function(a,s){var d=o[s];if(d){var p=t.getJointPose(d,e);if(!p||!p.transform)return;var b=p.transform.position,P=p.transform.orientation;a.position.set(b.x,b.y,b.z),a.rotationQuaternion.set(P.x,P.y,P.z,P.w);var O=(p.radius||.008)*n;a.scaling.set(O,O,O),i._handMesh&&i._rigMapping&&i._rigMapping[s]&&(i._transformNodeMapping[s]=i._transformNodeMapping[s]||i._scene.getTransformNodeByName(i._rigMapping[s]),i._transformNodeMapping[s]&&(i._transformNodeMapping[s].position.copyFrom(a.position),i._transformNodeMapping[s].rotationQuaternion.copyFrom(a.rotationQuaternion),a.isVisible=!1)),a.getScene().useRightHandedSystem||(a.position.z*=-1,a.rotationQuaternion.z*=-1,a.rotationQuaternion.w*=-1)}})},r.prototype.getHandPartMeshes=function(t){var e=this;return this.handPartsDefinition[t].map(function(n){return e.trackedMeshes[n]})},r.prototype.dispose=function(){this.trackedMeshes.forEach(function(t){return t.dispose()}),this._defaultHandMesh&&this._handMesh&&this._handMesh.dispose()},r.prototype._generateDefaultHandMesh=function(){return Object(c.b)(this,void 0,void 0,function(){var t,e,n,i,o,a,s,d;return Object(c.e)(this,function(p){switch(p.label){case 0:return p.trys.push([0,3,,4]),t=this.xrController.inputSource.handedness==="right"?"right":"left",e=(t==="right"?"r":"l")+"_hand_"+(this._scene.useRightHandedSystem?"r":"l")+"hs.glb",[4,Ut.ImportMeshAsync("","https://assets.babylonjs.com/meshes/HandMeshes/",e,this._scene)];case 1:return n=p.sent(),i={base:M.a.FromInts(116,63,203),fresnel:M.a.FromInts(149,102,229),fingerColor:M.a.FromInts(177,130,255),tipFresnel:M.a.FromInts(220,200,255)},[4,(o=new ga("leftHandShader",this._scene,{emitComments:!1})).loadAsync("https://patrickryanms.github.io/BabylonJStextures/Demos/xrHandMesh/handsShader.json")];case 2:if(p.sent(),o.build(!1),o.needDepthPrePass=!0,o.transparencyMode=Ht.a.MATERIAL_ALPHABLEND,o.alphaMode=Ue.a.ALPHA_COMBINE,(a={base:o.getBlockByName("baseColor"),fresnel:o.getBlockByName("fresnelColor"),fingerColor:o.getBlockByName("fingerColor"),tipFresnel:o.getBlockByName("tipFresnelColor")}).base.value=i.base,a.fresnel.value=i.fresnel,a.fingerColor.value=i.fingerColor,a.tipFresnel.value=i.tipFresnel,n.meshes[1].material=o,this._defaultHandMesh=!0,this._handMesh=n.meshes[0],this._rigMapping=["wrist_","thumb_metacarpal_","thumb_proxPhalanx_","thumb_distPhalanx_","thumb_tip_","index_metacarpal_","index_proxPhalanx_","index_intPhalanx_","index_distPhalanx_","index_tip_","middle_metacarpal_","middle_proxPhalanx_","middle_intPhalanx_","middle_distPhalanx_","middle_tip_","ring_metacarpal_","ring_proxPhalanx_","ring_intPhalanx_","ring_distPhalanx_","ring_tip_","little_metacarpal_","little_proxPhalanx_","little_intPhalanx_","little_distPhalanx_","little_tip_"].map(function(b){return b+(t==="right"?"R":"L")}),!(s=this._scene.getTransformNodeByName(this._rigMapping[0])))throw new Error("could not find the wrist node");return s.parent&&s.parent.rotate(ye.a.Y,Math.PI),[3,4];case 3:return d=p.sent(),Xe.b.Error("error loading hand mesh"),console.log(d),[3,4];case 4:return[2]}})})},r}(),Va=function(r){function t(e,n){var i=r.call(this,e)||this;return i.options=n,i.onHandAddedObservable=new C.c,i.onHandRemovedObservable=new C.c,i._hands={},i._attachHand=function(o){var a,s,d,p,b,P,O,B,F,z;if(o.inputSource.hand&&!i._hands[o.uniqueId]){var J=o.inputSource.hand,ie=[],se=((a=i.options.jointMeshes)===null||a===void 0?void 0:a.sourceMesh)||Fn.a.CreateSphere("jointParent",{diameter:1});se.isVisible=!!(!((s=i.options.jointMeshes)===null||s===void 0)&&s.keepOriginalVisible);for(var ce=0;ce<J.length;++ce){var ue=se.createInstance(o.uniqueId+"-handJoint-"+ce);if(!((d=i.options.jointMeshes)===null||d===void 0)&&d.onHandJointMeshGenerated){var fe=i.options.jointMeshes.onHandJointMeshGenerated(ue,ce,o.uniqueId);fe&&fe!==ue&&(ue.dispose(),ue=fe)}if(ue.isPickable=!1,(p=i.options.jointMeshes)===null||p===void 0?void 0:p.enablePhysics){var ve=i.options.jointMeshes.physicsProps||{},Te=ve.impostorType!==void 0?ve.impostorType:xt.a.SphereImpostor;ue.physicsImpostor=new xt.a(ue,Te,Object(c.a)({mass:0},ve))}ue.rotationQuaternion=new u.b,!((b=i.options.jointMeshes)===null||b===void 0)&&b.invisible&&(ue.isVisible=!1),ie.push(ue)}var Re=o.inputSource.handedness==="right"?"right":"left",Ae=((P=i.options.jointMeshes)===null||P===void 0?void 0:P.handMeshes)&&((O=i.options.jointMeshes)===null||O===void 0?void 0:O.handMeshes[Re]),Ee=((B=i.options.jointMeshes)===null||B===void 0?void 0:B.rigMapping)&&((F=i.options.jointMeshes)===null||F===void 0?void 0:F.rigMapping[Re]),Se=new bf(o,ie,Ae,Ee,(z=i.options.jointMeshes)===null||z===void 0?void 0:z.disableDefaultHandMesh);i._hands[o.uniqueId]={handObject:Se,id:t._idCounter++},i.onHandAddedObservable.notifyObservers(Se)}},i.xrNativeFeatureName="hand-tracking",i}return Object(c.d)(t,r),t.prototype.isCompatible=function(){return typeof XRHand<"u"},t.prototype.attach=function(){var e=this;return!!r.prototype.attach.call(this)&&(this.options.xrInput.controllers.forEach(this._attachHand),this._addNewAttachObserver(this.options.xrInput.onControllerAddedObservable,this._attachHand),this._addNewAttachObserver(this.options.xrInput.onControllerRemovedObservable,function(n){e._detachHand(n.uniqueId)}),!0)},t.prototype.detach=function(){var e=this;return!!r.prototype.detach.call(this)&&(Object.keys(this._hands).forEach(function(n){e._detachHand(n)}),!0)},t.prototype.dispose=function(){r.prototype.dispose.call(this),this.onHandAddedObservable.clear()},t.prototype.getHandByControllerId=function(e){var n;return((n=this._hands[e])===null||n===void 0?void 0:n.handObject)||null},t.prototype.getHandByHandedness=function(e){var n=this,i=Object.keys(this._hands).map(function(o){return n._hands[o].handObject.xrController.inputSource.handedness}).indexOf(e);return i!==-1?this._hands[i].handObject:null},t.prototype._onXRFrame=function(e){var n=this;Object.keys(this._hands).forEach(function(i){var o;n._hands[i].handObject.updateFromXRFrame(e,n._xrSessionManager.referenceSpace,(o=n.options.jointMeshes)===null||o===void 0?void 0:o.scaleFactor)})},t.prototype._detachHand=function(e){this._hands[e]&&(this.onHandRemovedObservable.notifyObservers(this._hands[e].handObject),this._hands[e].handObject.dispose())},t._idCounter=0,t.Name=ai.HAND_TRACKING,t.Version=1,t}(si);qn.AddWebXRFeature(Va.Name,function(r,t){return function(){return new Va(r,t)}},Va.Version,!1);var yf=function(r){function t(e,n,i){var o=r.call(this,e,Tv["left-right"],n,i)||this;return o._mapping={defaultButton:{valueNodeName:"VALUE",unpressedNodeName:"UNPRESSED",pressedNodeName:"PRESSED"},defaultAxis:{valueNodeName:"VALUE",minNodeName:"MIN",maxNodeName:"MAX"},buttons:{"xr-standard-trigger":{rootNodeName:"SELECT",componentProperty:"button",states:["default","touched","pressed"]},"xr-standard-squeeze":{rootNodeName:"GRASP",componentProperty:"state",states:["pressed"]},"xr-standard-touchpad":{rootNodeName:"TOUCHPAD_PRESS",labelAnchorNodeName:"squeeze-label",touchPointNodeName:"TOUCH"},"xr-standard-thumbstick":{rootNodeName:"THUMBSTICK_PRESS",componentProperty:"state",states:["pressed"]}},axes:{"xr-standard-touchpad":{"x-axis":{rootNodeName:"TOUCHPAD_TOUCH_X"},"y-axis":{rootNodeName:"TOUCHPAD_TOUCH_Y"}},"xr-standard-thumbstick":{"x-axis":{rootNodeName:"THUMBSTICK_X"},"y-axis":{rootNodeName:"THUMBSTICK_Y"}}}},o.profileId="microsoft-mixed-reality",o}return Object(c.d)(t,r),t.prototype._getFilenameAndPath=function(){return{filename:this.handedness==="left"?t.MODEL_LEFT_FILENAME:t.MODEL_RIGHT_FILENAME,path:t.MODEL_BASE_URL+"default/"}},t.prototype._getModelLoadingConstraints=function(){var e=Ut.IsPluginForExtensionAvailable(".glb");return e||l.a.Warn("glTF / glb loaded was not registered, using generic controller instead"),e},t.prototype._processLoadedModel=function(e){var n=this;this.rootMesh&&(this.getComponentIds().forEach(function(i,o){if(!n.disableAnimation&&i&&n.rootMesh){var a=n._mapping.buttons[i],s=a.rootNodeName;if(!s)return void l.a.Log("Skipping unknown button at index: "+o+" with mapped name: "+i);var d=n._getChildByName(n.rootMesh,s);if(!d)return void l.a.Warn("Missing button mesh with name: "+s);if(a.valueMesh=n._getImmediateChildByName(d,n._mapping.defaultButton.valueNodeName),a.pressedMesh=n._getImmediateChildByName(d,n._mapping.defaultButton.pressedNodeName),a.unpressedMesh=n._getImmediateChildByName(d,n._mapping.defaultButton.unpressedNodeName),a.valueMesh&&a.pressedMesh&&a.unpressedMesh){var p=n.getComponent(i);p&&p.onButtonStateChangedObservable.add(function(b){n._lerpTransform(a,b.value)},void 0,!0)}else l.a.Warn("Missing button submesh under mesh with name: "+s)}}),this.getComponentIds().forEach(function(i,o){var a=n.getComponent(i);a.isAxes()&&["x-axis","y-axis"].forEach(function(s){if(n.rootMesh){var d=n._mapping.axes[i][s],p=n._getChildByName(n.rootMesh,d.rootNodeName);p?(d.valueMesh=n._getImmediateChildByName(p,n._mapping.defaultAxis.valueNodeName),d.minMesh=n._getImmediateChildByName(p,n._mapping.defaultAxis.minNodeName),d.maxMesh=n._getImmediateChildByName(p,n._mapping.defaultAxis.maxNodeName),d.valueMesh&&d.minMesh&&d.maxMesh?a&&a.onAxisValueChangedObservable.add(function(b){var P=s==="x-axis"?b.x:b.y;n._lerpTransform(d,P,!0)},void 0,!0):l.a.Warn("Missing axis submesh under mesh with name: "+d.rootNodeName)):l.a.Warn("Missing axis mesh with name: "+d.rootNodeName)}})}))},t.prototype._setRootMesh=function(e){var n;this.rootMesh=new De.a(this.profileId+" "+this.handedness,this.scene),this.rootMesh.isPickable=!1;for(var i=0;i<e.length;i++){var o=e[i];o.isPickable=!1,o.parent||(n=o)}n&&n.setParent(this.rootMesh),this.scene.useRightHandedSystem||(this.rootMesh.rotationQuaternion=u.b.FromEulerAngles(0,Math.PI,0))},t.prototype._updateModel=function(){},t.MODEL_BASE_URL="https://controllers.babylonjs.com/microsoft/",t.MODEL_LEFT_FILENAME="left.glb",t.MODEL_RIGHT_FILENAME="right.glb",t}(Rr);Bn.RegisterController("windows-mixed-reality",function(r,t){return new yf(t,r.gamepad,r.handedness)});var Tv={left:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{xr_standard_trigger_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_trigger_pressed_value",minNodeName:"xr_standard_trigger_pressed_min",maxNodeName:"xr_standard_trigger_pressed_max"}}},"xr-standard-squeeze":{type:"squeeze",gamepadIndices:{button:1},rootNodeName:"xr_standard_squeeze",visualResponses:{xr_standard_squeeze_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_squeeze_pressed_value",minNodeName:"xr_standard_squeeze_pressed_min",maxNodeName:"xr_standard_squeeze_pressed_max"}}},"xr-standard-touchpad":{type:"touchpad",gamepadIndices:{button:2,xAxis:0,yAxis:1},rootNodeName:"xr_standard_touchpad",visualResponses:{xr_standard_touchpad_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_pressed_value",minNodeName:"xr_standard_touchpad_pressed_min",maxNodeName:"xr_standard_touchpad_pressed_max"},xr_standard_touchpad_xaxis_pressed:{componentProperty:"xAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_xaxis_pressed_value",minNodeName:"xr_standard_touchpad_xaxis_pressed_min",maxNodeName:"xr_standard_touchpad_xaxis_pressed_max"},xr_standard_touchpad_yaxis_pressed:{componentProperty:"yAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_yaxis_pressed_value",minNodeName:"xr_standard_touchpad_yaxis_pressed_min",maxNodeName:"xr_standard_touchpad_yaxis_pressed_max"},xr_standard_touchpad_xaxis_touched:{componentProperty:"xAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_xaxis_touched_value",minNodeName:"xr_standard_touchpad_xaxis_touched_min",maxNodeName:"xr_standard_touchpad_xaxis_touched_max"},xr_standard_touchpad_yaxis_touched:{componentProperty:"yAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_yaxis_touched_value",minNodeName:"xr_standard_touchpad_yaxis_touched_min",maxNodeName:"xr_standard_touchpad_yaxis_touched_max"},xr_standard_touchpad_axes_touched:{componentProperty:"state",states:["touched","pressed"],valueNodeProperty:"visibility",valueNodeName:"xr_standard_touchpad_axes_touched_value"}},touchPointNodeName:"xr_standard_touchpad_axes_touched_value"},"xr-standard-thumbstick":{type:"thumbstick",gamepadIndices:{button:3,xAxis:2,yAxis:3},rootNodeName:"xr_standard_thumbstick",visualResponses:{xr_standard_thumbstick_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_thumbstick_pressed_value",minNodeName:"xr_standard_thumbstick_pressed_min",maxNodeName:"xr_standard_thumbstick_pressed_max"},xr_standard_thumbstick_xaxis_pressed:{componentProperty:"xAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_thumbstick_xaxis_pressed_value",minNodeName:"xr_standard_thumbstick_xaxis_pressed_min",maxNodeName:"xr_standard_thumbstick_xaxis_pressed_max"},xr_standard_thumbstick_yaxis_pressed:{componentProperty:"yAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_thumbstick_yaxis_pressed_value",minNodeName:"xr_standard_thumbstick_yaxis_pressed_min",maxNodeName:"xr_standard_thumbstick_yaxis_pressed_max"}}}},gamepadMapping:"xr-standard",rootNodeName:"microsoft-mixed-reality-left",assetPath:"left.glb"},right:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{xr_standard_trigger_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_trigger_pressed_value",minNodeName:"xr_standard_trigger_pressed_min",maxNodeName:"xr_standard_trigger_pressed_max"}}},"xr-standard-squeeze":{type:"squeeze",gamepadIndices:{button:1},rootNodeName:"xr_standard_squeeze",visualResponses:{xr_standard_squeeze_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_squeeze_pressed_value",minNodeName:"xr_standard_squeeze_pressed_min",maxNodeName:"xr_standard_squeeze_pressed_max"}}},"xr-standard-touchpad":{type:"touchpad",gamepadIndices:{button:2,xAxis:0,yAxis:1},rootNodeName:"xr_standard_touchpad",visualResponses:{xr_standard_touchpad_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_pressed_value",minNodeName:"xr_standard_touchpad_pressed_min",maxNodeName:"xr_standard_touchpad_pressed_max"},xr_standard_touchpad_xaxis_pressed:{componentProperty:"xAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_xaxis_pressed_value",minNodeName:"xr_standard_touchpad_xaxis_pressed_min",maxNodeName:"xr_standard_touchpad_xaxis_pressed_max"},xr_standard_touchpad_yaxis_pressed:{componentProperty:"yAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_yaxis_pressed_value",minNodeName:"xr_standard_touchpad_yaxis_pressed_min",maxNodeName:"xr_standard_touchpad_yaxis_pressed_max"},xr_standard_touchpad_xaxis_touched:{componentProperty:"xAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_xaxis_touched_value",minNodeName:"xr_standard_touchpad_xaxis_touched_min",maxNodeName:"xr_standard_touchpad_xaxis_touched_max"},xr_standard_touchpad_yaxis_touched:{componentProperty:"yAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_touchpad_yaxis_touched_value",minNodeName:"xr_standard_touchpad_yaxis_touched_min",maxNodeName:"xr_standard_touchpad_yaxis_touched_max"},xr_standard_touchpad_axes_touched:{componentProperty:"state",states:["touched","pressed"],valueNodeProperty:"visibility",valueNodeName:"xr_standard_touchpad_axes_touched_value"}},touchPointNodeName:"xr_standard_touchpad_axes_touched_value"},"xr-standard-thumbstick":{type:"thumbstick",gamepadIndices:{button:3,xAxis:2,yAxis:3},rootNodeName:"xr_standard_thumbstick",visualResponses:{xr_standard_thumbstick_pressed:{componentProperty:"button",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_thumbstick_pressed_value",minNodeName:"xr_standard_thumbstick_pressed_min",maxNodeName:"xr_standard_thumbstick_pressed_max"},xr_standard_thumbstick_xaxis_pressed:{componentProperty:"xAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_thumbstick_xaxis_pressed_value",minNodeName:"xr_standard_thumbstick_xaxis_pressed_min",maxNodeName:"xr_standard_thumbstick_xaxis_pressed_max"},xr_standard_thumbstick_yaxis_pressed:{componentProperty:"yAxis",states:["default","touched","pressed"],valueNodeProperty:"transform",valueNodeName:"xr_standard_thumbstick_yaxis_pressed_value",minNodeName:"xr_standard_thumbstick_yaxis_pressed_min",maxNodeName:"xr_standard_thumbstick_yaxis_pressed_max"}}}},gamepadMapping:"xr-standard",rootNodeName:"microsoft-mixed-reality-right",assetPath:"right.glb"}},tl=function(r){function t(e,n,i,o,a){a===void 0&&(a=!1);var s=r.call(this,e,Ev[i],n,i)||this;return s._forceLegacyControllers=a,s.profileId="oculus-touch",s}return Object(c.d)(t,r),t.prototype._getFilenameAndPath=function(){return{filename:this.handedness==="left"?t.MODEL_LEFT_FILENAME:t.MODEL_RIGHT_FILENAME,path:this._isQuest()?t.QUEST_MODEL_BASE_URL:t.MODEL_BASE_URL}},t.prototype._getModelLoadingConstraints=function(){return!0},t.prototype._processLoadedModel=function(e){var n=this,i=this._isQuest(),o=this.handedness==="right"?-1:1;this.getComponentIds().forEach(function(a){var s=a&&n.getComponent(a);s&&s.onButtonStateChangedObservable.add(function(d){if(n.rootMesh&&!n.disableAnimation)switch(a){case"xr-standard-trigger":return void(i||(n._modelRootNode.getChildren()[3].rotation.x=.2*-d.value,n._modelRootNode.getChildren()[3].position.y=.005*-d.value,n._modelRootNode.getChildren()[3].position.z=.005*-d.value));case"xr-standard-squeeze":return void(i||(n._modelRootNode.getChildren()[4].position.x=o*d.value*.0035));case"xr-standard-thumbstick":return;case"a-button":case"x-button":return void(i||(d.pressed?n._modelRootNode.getChildren()[1].position.y=-.001:n._modelRootNode.getChildren()[1].position.y=0));case"b-button":case"y-button":return void(i||(d.pressed?n._modelRootNode.getChildren()[2].position.y=-.001:n._modelRootNode.getChildren()[2].position.y=0))}},void 0,!0)})},t.prototype._setRootMesh=function(e){this.rootMesh=new De.a(this.profileId+" "+this.handedness,this.scene),this.scene.useRightHandedSystem||(this.rootMesh.rotationQuaternion=u.b.FromEulerAngles(0,Math.PI,0)),e.forEach(function(n){n.isPickable=!1}),this._isQuest()?this._modelRootNode=e[0]:(this._modelRootNode=e[1],this.rootMesh.position.y=.034,this.rootMesh.position.z=.052),this._modelRootNode.parent=this.rootMesh},t.prototype._updateModel=function(){},t.prototype._isQuest=function(){return!!navigator.userAgent.match(/Quest/gi)&&!this._forceLegacyControllers},t.MODEL_BASE_URL="https://controllers.babylonjs.com/oculus/",t.MODEL_LEFT_FILENAME="left.babylon",t.MODEL_RIGHT_FILENAME="right.babylon",t.QUEST_MODEL_BASE_URL="https://controllers.babylonjs.com/oculusQuest/",t}(Rr);Bn.RegisterController("oculus-touch",function(r,t){return new tl(t,r.gamepad,r.handedness)}),Bn.RegisterController("oculus-touch-legacy",function(r,t){return new tl(t,r.gamepad,r.handedness,!0)});var Ev={left:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}},"xr-standard-squeeze":{type:"squeeze",gamepadIndices:{button:1},rootNodeName:"xr_standard_squeeze",visualResponses:{}},"xr-standard-thumbstick":{type:"thumbstick",gamepadIndices:{button:3,xAxis:2,yAxis:3},rootNodeName:"xr_standard_thumbstick",visualResponses:{}},"x-button":{type:"button",gamepadIndices:{button:4},rootNodeName:"x_button",visualResponses:{}},"y-button":{type:"button",gamepadIndices:{button:5},rootNodeName:"y_button",visualResponses:{}},thumbrest:{type:"button",gamepadIndices:{button:6},rootNodeName:"thumbrest",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"oculus-touch-v2-left",assetPath:"left.glb"},right:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}},"xr-standard-squeeze":{type:"squeeze",gamepadIndices:{button:1},rootNodeName:"xr_standard_squeeze",visualResponses:{}},"xr-standard-thumbstick":{type:"thumbstick",gamepadIndices:{button:3,xAxis:2,yAxis:3},rootNodeName:"xr_standard_thumbstick",visualResponses:{}},"a-button":{type:"button",gamepadIndices:{button:4},rootNodeName:"a_button",visualResponses:{}},"b-button":{type:"button",gamepadIndices:{button:5},rootNodeName:"b_button",visualResponses:{}},thumbrest:{type:"button",gamepadIndices:{button:6},rootNodeName:"thumbrest",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"oculus-touch-v2-right",assetPath:"right.glb"}},Tf=function(r){function t(e,n,i){var o=r.call(this,e,Sv[i],n,i)||this;return o.profileId="htc-vive",o}return Object(c.d)(t,r),t.prototype._getFilenameAndPath=function(){return{filename:t.MODEL_FILENAME,path:t.MODEL_BASE_URL}},t.prototype._getModelLoadingConstraints=function(){return!0},t.prototype._processLoadedModel=function(e){var n=this;this.getComponentIds().forEach(function(i){var o=i&&n.getComponent(i);o&&o.onButtonStateChangedObservable.add(function(a){if(n.rootMesh&&!n.disableAnimation)switch(i){case"xr-standard-trigger":return void(n._modelRootNode.getChildren()[6].rotation.x=.15*-a.value);case"xr-standard-touchpad":case"xr-standard-squeeze":return}},void 0,!0)})},t.prototype._setRootMesh=function(e){this.rootMesh=new De.a(this.profileId+" "+this.handedness,this.scene),e.forEach(function(n){n.isPickable=!1}),this._modelRootNode=e[1],this._modelRootNode.parent=this.rootMesh,this.scene.useRightHandedSystem||(this.rootMesh.rotationQuaternion=u.b.FromEulerAngles(0,Math.PI,0))},t.prototype._updateModel=function(){},t.MODEL_BASE_URL="https://controllers.babylonjs.com/vive/",t.MODEL_FILENAME="wand.babylon",t}(Rr);Bn.RegisterController("htc-vive",function(r,t){return new Tf(t,r.gamepad,r.handedness)});var Sv={left:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}},"xr-standard-squeeze":{type:"squeeze",gamepadIndices:{button:1},rootNodeName:"xr_standard_squeeze",visualResponses:{}},"xr-standard-touchpad":{type:"touchpad",gamepadIndices:{button:2,xAxis:0,yAxis:1},rootNodeName:"xr_standard_touchpad",visualResponses:{}},menu:{type:"button",gamepadIndices:{button:4},rootNodeName:"menu",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"htc_vive_none",assetPath:"none.glb"},right:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}},"xr-standard-squeeze":{type:"squeeze",gamepadIndices:{button:1},rootNodeName:"xr_standard_squeeze",visualResponses:{}},"xr-standard-touchpad":{type:"touchpad",gamepadIndices:{button:2,xAxis:0,yAxis:1},rootNodeName:"xr_standard_touchpad",visualResponses:{}},menu:{type:"button",gamepadIndices:{button:4},rootNodeName:"menu",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"htc_vive_none",assetPath:"none.glb"},none:{selectComponentId:"xr-standard-trigger",components:{"xr-standard-trigger":{type:"trigger",gamepadIndices:{button:0},rootNodeName:"xr_standard_trigger",visualResponses:{}},"xr-standard-squeeze":{type:"squeeze",gamepadIndices:{button:1},rootNodeName:"xr_standard_squeeze",visualResponses:{}},"xr-standard-touchpad":{type:"touchpad",gamepadIndices:{button:2,xAxis:0,yAxis:1},rootNodeName:"xr_standard_touchpad",visualResponses:{}},menu:{type:"button",gamepadIndices:{button:4},rootNodeName:"menu",visualResponses:{}}},gamepadMapping:"xr-standard",rootNodeName:"htc-vive-none",assetPath:"none.glb"}}},function(Me,y,f){f.d(y,"a",function(){return 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-#ifndef SHADOWFLOAT
-
-float unpack(vec4 color)
-{
-const vec4 bit_shift=vec4(1.0/(255.0*255.0*255.0),1.0/(255.0*255.0),1.0/255.0,1.0);
-return dot(color,bit_shift);
-}
-#endif
-float computeFallOff(float value,vec2 clipSpace,float frustumEdgeFalloff)
-{
-float mask=smoothstep(1.0-frustumEdgeFalloff,1.00000012,clamp(dot(clipSpace,clipSpace),0.,1.));
-return mix(value,1.0,mask);
-}
-#define inline
-float computeShadowCube(vec3 lightPosition,samplerCube shadowSampler,float darkness,vec2 depthValues)
-{
-vec3 directionToLight=vPositionW-lightPosition;
-float depth=length(directionToLight);
-depth=(depth+depthValues.x)/(depthValues.y);
-depth=clamp(depth,0.,1.0);
-directionToLight=normalize(directionToLight);
-directionToLight.y=-directionToLight.y;
-#ifndef SHADOWFLOAT
-float shadow=unpack(textureCube(shadowSampler,directionToLight));
-#else
-float shadow=textureCube(shadowSampler,directionToLight).x;
-#endif
-return depth>shadow ? darkness : 1.0;
-}
-#define inline
-float computeShadowWithPoissonSamplingCube(vec3 lightPosition,samplerCube shadowSampler,float mapSize,float darkness,vec2 depthValues)
-{
-vec3 directionToLight=vPositionW-lightPosition;
-float depth=length(directionToLight);
-depth=(depth+depthValues.x)/(depthValues.y);
-depth=clamp(depth,0.,1.0);
-directionToLight=normalize(directionToLight);
-directionToLight.y=-directionToLight.y;
-float visibility=1.;
-vec3 poissonDisk[4];
-poissonDisk[0]=vec3(-1.0,1.0,-1.0);
-poissonDisk[1]=vec3(1.0,-1.0,-1.0);
-poissonDisk[2]=vec3(-1.0,-1.0,-1.0);
-poissonDisk[3]=vec3(1.0,-1.0,1.0);
-
-#ifndef SHADOWFLOAT
-if (unpack(textureCube(shadowSampler,directionToLight+poissonDisk[0]*mapSize))<depth) visibility-=0.25;
-if (unpack(textureCube(shadowSampler,directionToLight+poissonDisk[1]*mapSize))<depth) visibility-=0.25;
-if (unpack(textureCube(shadowSampler,directionToLight+poissonDisk[2]*mapSize))<depth) visibility-=0.25;
-if (unpack(textureCube(shadowSampler,directionToLight+poissonDisk[3]*mapSize))<depth) visibility-=0.25;
-#else
-if (textureCube(shadowSampler,directionToLight+poissonDisk[0]*mapSize).x<depth) visibility-=0.25;
-if (textureCube(shadowSampler,directionToLight+poissonDisk[1]*mapSize).x<depth) visibility-=0.25;
-if (textureCube(shadowSampler,directionToLight+poissonDisk[2]*mapSize).x<depth) visibility-=0.25;
-if (textureCube(shadowSampler,directionToLight+poissonDisk[3]*mapSize).x<depth) visibility-=0.25;
-#endif
-return min(1.0,visibility+darkness);
-}
-#define inline
-float computeShadowWithESMCube(vec3 lightPosition,samplerCube shadowSampler,float darkness,float depthScale,vec2 depthValues)
-{
-vec3 directionToLight=vPositionW-lightPosition;
-float depth=length(directionToLight);
-depth=(depth+depthValues.x)/(depthValues.y);
-float shadowPixelDepth=clamp(depth,0.,1.0);
-directionToLight=normalize(directionToLight);
-directionToLight.y=-directionToLight.y;
-#ifndef SHADOWFLOAT
-float shadowMapSample=unpack(textureCube(shadowSampler,directionToLight));
-#else
-float shadowMapSample=textureCube(shadowSampler,directionToLight).x;
-#endif
-float esm=1.0-clamp(exp(min(87.,depthScale*shadowPixelDepth))*shadowMapSample,0.,1.-darkness);
-return esm;
-}
-#define inline
-float computeShadowWithCloseESMCube(vec3 lightPosition,samplerCube shadowSampler,float darkness,float depthScale,vec2 depthValues)
-{
-vec3 directionToLight=vPositionW-lightPosition;
-float depth=length(directionToLight);
-depth=(depth+depthValues.x)/(depthValues.y);
-float shadowPixelDepth=clamp(depth,0.,1.0);
-directionToLight=normalize(directionToLight);
-directionToLight.y=-directionToLight.y;
-#ifndef SHADOWFLOAT
-float shadowMapSample=unpack(textureCube(shadowSampler,directionToLight));
-#else
-float shadowMapSample=textureCube(shadowSampler,directionToLight).x;
-#endif
-float esm=clamp(exp(min(87.,-depthScale*(shadowPixelDepth-shadowMapSample))),darkness,1.);
-return esm;
-}
-#ifdef WEBGL2
-#define inline
-float computeShadowCSM(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArray shadowSampler,float darkness,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec2 uv=0.5*clipSpace.xy+vec2(0.5);
-vec3 uvLayer=vec3(uv.x,uv.y,layer);
-float shadowPixelDepth=clamp(depthMetric,0.,1.0);
-#ifndef SHADOWFLOAT
-float shadow=unpack(texture2D(shadowSampler,uvLayer));
-#else
-float shadow=texture2D(shadowSampler,uvLayer).x;
-#endif
-return shadowPixelDepth>shadow ? computeFallOff(darkness,clipSpace.xy,frustumEdgeFalloff) : 1.;
-}
-#endif
-#define inline
-float computeShadow(vec4 vPositionFromLight,float depthMetric,sampler2D shadowSampler,float darkness,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec2 uv=0.5*clipSpace.xy+vec2(0.5);
-if (uv.x<0. || uv.x>1.0 || uv.y<0. || uv.y>1.0)
-{
-return 1.0;
-}
-else
-{
-float shadowPixelDepth=clamp(depthMetric,0.,1.0);
-#ifndef SHADOWFLOAT
-float shadow=unpack(texture2D(shadowSampler,uv));
-#else
-float shadow=texture2D(shadowSampler,uv).x;
-#endif
-return shadowPixelDepth>shadow ? computeFallOff(darkness,clipSpace.xy,frustumEdgeFalloff) : 1.;
-}
-}
-#define inline
-float computeShadowWithPoissonSampling(vec4 vPositionFromLight,float depthMetric,sampler2D shadowSampler,float mapSize,float darkness,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec2 uv=0.5*clipSpace.xy+vec2(0.5);
-if (uv.x<0. || uv.x>1.0 || uv.y<0. || uv.y>1.0)
-{
-return 1.0;
-}
-else
-{
-float shadowPixelDepth=clamp(depthMetric,0.,1.0);
-float visibility=1.;
-vec2 poissonDisk[4];
-poissonDisk[0]=vec2(-0.94201624,-0.39906216);
-poissonDisk[1]=vec2(0.94558609,-0.76890725);
-poissonDisk[2]=vec2(-0.094184101,-0.92938870);
-poissonDisk[3]=vec2(0.34495938,0.29387760);
-
-#ifndef SHADOWFLOAT
-if (unpack(texture2D(shadowSampler,uv+poissonDisk[0]*mapSize))<shadowPixelDepth) visibility-=0.25;
-if (unpack(texture2D(shadowSampler,uv+poissonDisk[1]*mapSize))<shadowPixelDepth) visibility-=0.25;
-if (unpack(texture2D(shadowSampler,uv+poissonDisk[2]*mapSize))<shadowPixelDepth) visibility-=0.25;
-if (unpack(texture2D(shadowSampler,uv+poissonDisk[3]*mapSize))<shadowPixelDepth) visibility-=0.25;
-#else
-if (texture2D(shadowSampler,uv+poissonDisk[0]*mapSize).x<shadowPixelDepth) visibility-=0.25;
-if (texture2D(shadowSampler,uv+poissonDisk[1]*mapSize).x<shadowPixelDepth) visibility-=0.25;
-if (texture2D(shadowSampler,uv+poissonDisk[2]*mapSize).x<shadowPixelDepth) visibility-=0.25;
-if (texture2D(shadowSampler,uv+poissonDisk[3]*mapSize).x<shadowPixelDepth) visibility-=0.25;
-#endif
-return computeFallOff(min(1.0,visibility+darkness),clipSpace.xy,frustumEdgeFalloff);
-}
-}
-#define inline
-float computeShadowWithESM(vec4 vPositionFromLight,float depthMetric,sampler2D shadowSampler,float darkness,float depthScale,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec2 uv=0.5*clipSpace.xy+vec2(0.5);
-if (uv.x<0. || uv.x>1.0 || uv.y<0. || uv.y>1.0)
-{
-return 1.0;
-}
-else
-{
-float shadowPixelDepth=clamp(depthMetric,0.,1.0);
-#ifndef SHADOWFLOAT
-float shadowMapSample=unpack(texture2D(shadowSampler,uv));
-#else
-float shadowMapSample=texture2D(shadowSampler,uv).x;
-#endif
-float esm=1.0-clamp(exp(min(87.,depthScale*shadowPixelDepth))*shadowMapSample,0.,1.-darkness);
-return computeFallOff(esm,clipSpace.xy,frustumEdgeFalloff);
-}
-}
-#define inline
-float computeShadowWithCloseESM(vec4 vPositionFromLight,float depthMetric,sampler2D shadowSampler,float darkness,float depthScale,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec2 uv=0.5*clipSpace.xy+vec2(0.5);
-if (uv.x<0. || uv.x>1.0 || uv.y<0. || uv.y>1.0)
-{
-return 1.0;
-}
-else
-{
-float shadowPixelDepth=clamp(depthMetric,0.,1.0);
-#ifndef SHADOWFLOAT
-float shadowMapSample=unpack(texture2D(shadowSampler,uv));
-#else
-float shadowMapSample=texture2D(shadowSampler,uv).x;
-#endif
-float esm=clamp(exp(min(87.,-depthScale*(shadowPixelDepth-shadowMapSample))),darkness,1.);
-return computeFallOff(esm,clipSpace.xy,frustumEdgeFalloff);
-}
-}
-#ifdef WEBGL2
-#define GREATEST_LESS_THAN_ONE 0.99999994
-
-#define inline
-float computeShadowWithCSMPCF1(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArrayShadow shadowSampler,float darkness,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-uvDepth.z=clamp(uvDepth.z,0.,GREATEST_LESS_THAN_ONE);
-vec4 uvDepthLayer=vec4(uvDepth.x,uvDepth.y,layer,uvDepth.z);
-float shadow=texture(shadowSampler,uvDepthLayer);
-shadow=mix(darkness,1.,shadow);
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-
-
-
-#define inline
-float computeShadowWithCSMPCF3(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArrayShadow shadowSampler,vec2 shadowMapSizeAndInverse,float darkness,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-uvDepth.z=clamp(uvDepth.z,0.,GREATEST_LESS_THAN_ONE);
-vec2 uv=uvDepth.xy*shadowMapSizeAndInverse.x;
-uv+=0.5;
-vec2 st=fract(uv);
-vec2 base_uv=floor(uv)-0.5;
-base_uv*=shadowMapSizeAndInverse.y;
-
-
-
-
-vec2 uvw0=3.-2.*st;
-vec2 uvw1=1.+2.*st;
-vec2 u=vec2((2.-st.x)/uvw0.x-1.,st.x/uvw1.x+1.)*shadowMapSizeAndInverse.y;
-vec2 v=vec2((2.-st.y)/uvw0.y-1.,st.y/uvw1.y+1.)*shadowMapSizeAndInverse.y;
-float shadow=0.;
-shadow+=uvw0.x*uvw0.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[0],v[0]),layer,uvDepth.z));
-shadow+=uvw1.x*uvw0.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[1],v[0]),layer,uvDepth.z));
-shadow+=uvw0.x*uvw1.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[0],v[1]),layer,uvDepth.z));
-shadow+=uvw1.x*uvw1.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[1],v[1]),layer,uvDepth.z));
-shadow=shadow/16.;
-shadow=mix(darkness,1.,shadow);
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-
-
-
-#define inline
-float computeShadowWithCSMPCF5(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArrayShadow shadowSampler,vec2 shadowMapSizeAndInverse,float darkness,float frustumEdgeFalloff)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-uvDepth.z=clamp(uvDepth.z,0.,GREATEST_LESS_THAN_ONE);
-vec2 uv=uvDepth.xy*shadowMapSizeAndInverse.x;
-uv+=0.5;
-vec2 st=fract(uv);
-vec2 base_uv=floor(uv)-0.5;
-base_uv*=shadowMapSizeAndInverse.y;
-
-
-vec2 uvw0=4.-3.*st;
-vec2 uvw1=vec2(7.);
-vec2 uvw2=1.+3.*st;
-vec3 u=vec3((3.-2.*st.x)/uvw0.x-2.,(3.+st.x)/uvw1.x,st.x/uvw2.x+2.)*shadowMapSizeAndInverse.y;
-vec3 v=vec3((3.-2.*st.y)/uvw0.y-2.,(3.+st.y)/uvw1.y,st.y/uvw2.y+2.)*shadowMapSizeAndInverse.y;
-float shadow=0.;
-shadow+=uvw0.x*uvw0.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[0],v[0]),layer,uvDepth.z));
-shadow+=uvw1.x*uvw0.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[1],v[0]),layer,uvDepth.z));
-shadow+=uvw2.x*uvw0.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[2],v[0]),layer,uvDepth.z));
-shadow+=uvw0.x*uvw1.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[0],v[1]),layer,uvDepth.z));
-shadow+=uvw1.x*uvw1.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[1],v[1]),layer,uvDepth.z));
-shadow+=uvw2.x*uvw1.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[2],v[1]),layer,uvDepth.z));
-shadow+=uvw0.x*uvw2.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[0],v[2]),layer,uvDepth.z));
-shadow+=uvw1.x*uvw2.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[1],v[2]),layer,uvDepth.z));
-shadow+=uvw2.x*uvw2.y*texture2D(shadowSampler,vec4(base_uv.xy+vec2(u[2],v[2]),layer,uvDepth.z));
-shadow=shadow/144.;
-shadow=mix(darkness,1.,shadow);
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-
-#define inline
-float computeShadowWithPCF1(vec4 vPositionFromLight,float depthMetric,highp sampler2DShadow shadowSampler,float darkness,float frustumEdgeFalloff)
-{
-if (depthMetric>1.0 || depthMetric<0.0) {
-return 1.0;
-}
-else
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-float shadow=texture2D(shadowSampler,uvDepth);
-shadow=mix(darkness,1.,shadow);
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-}
-
-
-
-#define inline
-float computeShadowWithPCF3(vec4 vPositionFromLight,float depthMetric,highp sampler2DShadow shadowSampler,vec2 shadowMapSizeAndInverse,float darkness,float frustumEdgeFalloff)
-{
-if (depthMetric>1.0 || depthMetric<0.0) {
-return 1.0;
-}
-else
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-vec2 uv=uvDepth.xy*shadowMapSizeAndInverse.x;
-uv+=0.5;
-vec2 st=fract(uv);
-vec2 base_uv=floor(uv)-0.5;
-base_uv*=shadowMapSizeAndInverse.y;
-
-
-
-
-vec2 uvw0=3.-2.*st;
-vec2 uvw1=1.+2.*st;
-vec2 u=vec2((2.-st.x)/uvw0.x-1.,st.x/uvw1.x+1.)*shadowMapSizeAndInverse.y;
-vec2 v=vec2((2.-st.y)/uvw0.y-1.,st.y/uvw1.y+1.)*shadowMapSizeAndInverse.y;
-float shadow=0.;
-shadow+=uvw0.x*uvw0.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[0],v[0]),uvDepth.z));
-shadow+=uvw1.x*uvw0.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[1],v[0]),uvDepth.z));
-shadow+=uvw0.x*uvw1.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[0],v[1]),uvDepth.z));
-shadow+=uvw1.x*uvw1.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[1],v[1]),uvDepth.z));
-shadow=shadow/16.;
-shadow=mix(darkness,1.,shadow);
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-}
-
-
-
-#define inline
-float computeShadowWithPCF5(vec4 vPositionFromLight,float depthMetric,highp sampler2DShadow shadowSampler,vec2 shadowMapSizeAndInverse,float darkness,float frustumEdgeFalloff)
-{
-if (depthMetric>1.0 || depthMetric<0.0) {
-return 1.0;
-}
-else
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-vec2 uv=uvDepth.xy*shadowMapSizeAndInverse.x;
-uv+=0.5;
-vec2 st=fract(uv);
-vec2 base_uv=floor(uv)-0.5;
-base_uv*=shadowMapSizeAndInverse.y;
-
-
-vec2 uvw0=4.-3.*st;
-vec2 uvw1=vec2(7.);
-vec2 uvw2=1.+3.*st;
-vec3 u=vec3((3.-2.*st.x)/uvw0.x-2.,(3.+st.x)/uvw1.x,st.x/uvw2.x+2.)*shadowMapSizeAndInverse.y;
-vec3 v=vec3((3.-2.*st.y)/uvw0.y-2.,(3.+st.y)/uvw1.y,st.y/uvw2.y+2.)*shadowMapSizeAndInverse.y;
-float shadow=0.;
-shadow+=uvw0.x*uvw0.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[0],v[0]),uvDepth.z));
-shadow+=uvw1.x*uvw0.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[1],v[0]),uvDepth.z));
-shadow+=uvw2.x*uvw0.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[2],v[0]),uvDepth.z));
-shadow+=uvw0.x*uvw1.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[0],v[1]),uvDepth.z));
-shadow+=uvw1.x*uvw1.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[1],v[1]),uvDepth.z));
-shadow+=uvw2.x*uvw1.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[2],v[1]),uvDepth.z));
-shadow+=uvw0.x*uvw2.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[0],v[2]),uvDepth.z));
-shadow+=uvw1.x*uvw2.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[1],v[2]),uvDepth.z));
-shadow+=uvw2.x*uvw2.y*texture2D(shadowSampler,vec3(base_uv.xy+vec2(u[2],v[2]),uvDepth.z));
-shadow=shadow/144.;
-shadow=mix(darkness,1.,shadow);
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-}
-const vec3 PoissonSamplers32[64]=vec3[64](
-vec3(0.06407013,0.05409927,0.),
-vec3(0.7366577,0.5789394,0.),
-vec3(-0.6270542,-0.5320278,0.),
-vec3(-0.4096107,0.8411095,0.),
-vec3(0.6849564,-0.4990818,0.),
-vec3(-0.874181,-0.04579735,0.),
-vec3(0.9989998,0.0009880066,0.),
-vec3(-0.004920578,-0.9151649,0.),
-vec3(0.1805763,0.9747483,0.),
-vec3(-0.2138451,0.2635818,0.),
-vec3(0.109845,0.3884785,0.),
-vec3(0.06876755,-0.3581074,0.),
-vec3(0.374073,-0.7661266,0.),
-vec3(0.3079132,-0.1216763,0.),
-vec3(-0.3794335,-0.8271583,0.),
-vec3(-0.203878,-0.07715034,0.),
-vec3(0.5912697,0.1469799,0.),
-vec3(-0.88069,0.3031784,0.),
-vec3(0.5040108,0.8283722,0.),
-vec3(-0.5844124,0.5494877,0.),
-vec3(0.6017799,-0.1726654,0.),
-vec3(-0.5554981,0.1559997,0.),
-vec3(-0.3016369,-0.3900928,0.),
-vec3(-0.5550632,-0.1723762,0.),
-vec3(0.925029,0.2995041,0.),
-vec3(-0.2473137,0.5538505,0.),
-vec3(0.9183037,-0.2862392,0.),
-vec3(0.2469421,0.6718712,0.),
-vec3(0.3916397,-0.4328209,0.),
-vec3(-0.03576927,-0.6220032,0.),
-vec3(-0.04661255,0.7995201,0.),
-vec3(0.4402924,0.3640312,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.),
-vec3(0.,0.,0.)
-);
-const vec3 PoissonSamplers64[64]=vec3[64](
-vec3(-0.613392,0.617481,0.),
-vec3(0.170019,-0.040254,0.),
-vec3(-0.299417,0.791925,0.),
-vec3(0.645680,0.493210,0.),
-vec3(-0.651784,0.717887,0.),
-vec3(0.421003,0.027070,0.),
-vec3(-0.817194,-0.271096,0.),
-vec3(-0.705374,-0.668203,0.),
-vec3(0.977050,-0.108615,0.),
-vec3(0.063326,0.142369,0.),
-vec3(0.203528,0.214331,0.),
-vec3(-0.667531,0.326090,0.),
-vec3(-0.098422,-0.295755,0.),
-vec3(-0.885922,0.215369,0.),
-vec3(0.566637,0.605213,0.),
-vec3(0.039766,-0.396100,0.),
-vec3(0.751946,0.453352,0.),
-vec3(0.078707,-0.715323,0.),
-vec3(-0.075838,-0.529344,0.),
-vec3(0.724479,-0.580798,0.),
-vec3(0.222999,-0.215125,0.),
-vec3(-0.467574,-0.405438,0.),
-vec3(-0.248268,-0.814753,0.),
-vec3(0.354411,-0.887570,0.),
-vec3(0.175817,0.382366,0.),
-vec3(0.487472,-0.063082,0.),
-vec3(-0.084078,0.898312,0.),
-vec3(0.488876,-0.783441,0.),
-vec3(0.470016,0.217933,0.),
-vec3(-0.696890,-0.549791,0.),
-vec3(-0.149693,0.605762,0.),
-vec3(0.034211,0.979980,0.),
-vec3(0.503098,-0.308878,0.),
-vec3(-0.016205,-0.872921,0.),
-vec3(0.385784,-0.393902,0.),
-vec3(-0.146886,-0.859249,0.),
-vec3(0.643361,0.164098,0.),
-vec3(0.634388,-0.049471,0.),
-vec3(-0.688894,0.007843,0.),
-vec3(0.464034,-0.188818,0.),
-vec3(-0.440840,0.137486,0.),
-vec3(0.364483,0.511704,0.),
-vec3(0.034028,0.325968,0.),
-vec3(0.099094,-0.308023,0.),
-vec3(0.693960,-0.366253,0.),
-vec3(0.678884,-0.204688,0.),
-vec3(0.001801,0.780328,0.),
-vec3(0.145177,-0.898984,0.),
-vec3(0.062655,-0.611866,0.),
-vec3(0.315226,-0.604297,0.),
-vec3(-0.780145,0.486251,0.),
-vec3(-0.371868,0.882138,0.),
-vec3(0.200476,0.494430,0.),
-vec3(-0.494552,-0.711051,0.),
-vec3(0.612476,0.705252,0.),
-vec3(-0.578845,-0.768792,0.),
-vec3(-0.772454,-0.090976,0.),
-vec3(0.504440,0.372295,0.),
-vec3(0.155736,0.065157,0.),
-vec3(0.391522,0.849605,0.),
-vec3(-0.620106,-0.328104,0.),
-vec3(0.789239,-0.419965,0.),
-vec3(-0.545396,0.538133,0.),
-vec3(-0.178564,-0.596057,0.)
-);
-
-
-
-
-
-#define inline
-float computeShadowWithCSMPCSS(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArray depthSampler,highp sampler2DArrayShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff,int searchTapCount,int pcfTapCount,vec3[64] poissonSamplers,vec2 lightSizeUVCorrection,float depthCorrection,float penumbraDarkness)
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-uvDepth.z=clamp(uvDepth.z,0.,GREATEST_LESS_THAN_ONE);
-vec4 uvDepthLayer=vec4(uvDepth.x,uvDepth.y,layer,uvDepth.z);
-float blockerDepth=0.0;
-float sumBlockerDepth=0.0;
-float numBlocker=0.0;
-for (int i=0; i<searchTapCount; i ++) {
-blockerDepth=texture(depthSampler,vec3(uvDepth.xy+(lightSizeUV*lightSizeUVCorrection*shadowMapSizeInverse*PoissonSamplers32[i].xy),layer)).r;
-if (blockerDepth<depthMetric) {
-sumBlockerDepth+=blockerDepth;
-numBlocker++;
-}
-}
-if (numBlocker<1.0) {
-return 1.0;
-}
-else
-{
-float avgBlockerDepth=sumBlockerDepth/numBlocker;
-
-float AAOffset=shadowMapSizeInverse*10.;
-
-
-float penumbraRatio=((depthMetric-avgBlockerDepth)*depthCorrection+AAOffset);
-vec4 filterRadius=vec4(penumbraRatio*lightSizeUV*lightSizeUVCorrection*shadowMapSizeInverse,0.,0.);
-float random=getRand(vPositionFromLight.xy);
-float rotationAngle=random*3.1415926;
-vec2 rotationVector=vec2(cos(rotationAngle),sin(rotationAngle));
-float shadow=0.;
-for (int i=0; i<pcfTapCount; i++) {
-vec4 offset=vec4(poissonSamplers[i],0.);
-
-offset=vec4(offset.x*rotationVector.x-offset.y*rotationVector.y,offset.y*rotationVector.x+offset.x*rotationVector.y,0.,0.);
-shadow+=texture2D(shadowSampler,uvDepthLayer+offset*filterRadius);
-}
-shadow/=float(pcfTapCount);
-
-shadow=mix(shadow,1.,min((depthMetric-avgBlockerDepth)*depthCorrection*penumbraDarkness,1.));
-
-shadow=mix(darkness,1.,shadow);
-
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-}
-
-
-
-
-
-#define inline
-float computeShadowWithPCSS(vec4 vPositionFromLight,float depthMetric,sampler2D depthSampler,highp sampler2DShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff,int searchTapCount,int pcfTapCount,vec3[64] poissonSamplers)
-{
-if (depthMetric>1.0 || depthMetric<0.0) {
-return 1.0;
-}
-else
-{
-vec3 clipSpace=vPositionFromLight.xyz/vPositionFromLight.w;
-vec3 uvDepth=vec3(0.5*clipSpace.xyz+vec3(0.5));
-float blockerDepth=0.0;
-float sumBlockerDepth=0.0;
-float numBlocker=0.0;
-for (int i=0; i<searchTapCount; i ++) {
-blockerDepth=texture(depthSampler,uvDepth.xy+(lightSizeUV*shadowMapSizeInverse*PoissonSamplers32[i].xy)).r;
-if (blockerDepth<depthMetric) {
-sumBlockerDepth+=blockerDepth;
-numBlocker++;
-}
-}
-if (numBlocker<1.0) {
-return 1.0;
-}
-else
-{
-float avgBlockerDepth=sumBlockerDepth/numBlocker;
-
-float AAOffset=shadowMapSizeInverse*10.;
-
-
-float penumbraRatio=((depthMetric-avgBlockerDepth)+AAOffset);
-float filterRadius=penumbraRatio*lightSizeUV*shadowMapSizeInverse;
-float random=getRand(vPositionFromLight.xy);
-float rotationAngle=random*3.1415926;
-vec2 rotationVector=vec2(cos(rotationAngle),sin(rotationAngle));
-float shadow=0.;
-for (int i=0; i<pcfTapCount; i++) {
-vec3 offset=poissonSamplers[i];
-
-offset=vec3(offset.x*rotationVector.x-offset.y*rotationVector.y,offset.y*rotationVector.x+offset.x*rotationVector.y,0.);
-shadow+=texture2D(shadowSampler,uvDepth+offset*filterRadius);
-}
-shadow/=float(pcfTapCount);
-
-shadow=mix(shadow,1.,depthMetric-avgBlockerDepth);
-
-shadow=mix(darkness,1.,shadow);
-
-return computeFallOff(shadow,clipSpace.xy,frustumEdgeFalloff);
-}
-}
-}
-#define inline
-float computeShadowWithPCSS16(vec4 vPositionFromLight,float depthMetric,sampler2D depthSampler,highp sampler2DShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff)
-{
-return computeShadowWithPCSS(vPositionFromLight,depthMetric,depthSampler,shadowSampler,shadowMapSizeInverse,lightSizeUV,darkness,frustumEdgeFalloff,16,16,PoissonSamplers32);
-}
-#define inline
-float computeShadowWithPCSS32(vec4 vPositionFromLight,float depthMetric,sampler2D depthSampler,highp sampler2DShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff)
-{
-return computeShadowWithPCSS(vPositionFromLight,depthMetric,depthSampler,shadowSampler,shadowMapSizeInverse,lightSizeUV,darkness,frustumEdgeFalloff,16,32,PoissonSamplers32);
-}
-#define inline
-float computeShadowWithPCSS64(vec4 vPositionFromLight,float depthMetric,sampler2D depthSampler,highp sampler2DShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff)
-{
-return computeShadowWithPCSS(vPositionFromLight,depthMetric,depthSampler,shadowSampler,shadowMapSizeInverse,lightSizeUV,darkness,frustumEdgeFalloff,32,64,PoissonSamplers64);
-}
-#define inline
-float computeShadowWithCSMPCSS16(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArray depthSampler,highp sampler2DArrayShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff,vec2 lightSizeUVCorrection,float depthCorrection,float penumbraDarkness)
-{
-return computeShadowWithCSMPCSS(layer,vPositionFromLight,depthMetric,depthSampler,shadowSampler,shadowMapSizeInverse,lightSizeUV,darkness,frustumEdgeFalloff,16,16,PoissonSamplers32,lightSizeUVCorrection,depthCorrection,penumbraDarkness);
-}
-#define inline
-float computeShadowWithCSMPCSS32(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArray depthSampler,highp sampler2DArrayShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff,vec2 lightSizeUVCorrection,float depthCorrection,float penumbraDarkness)
-{
-return computeShadowWithCSMPCSS(layer,vPositionFromLight,depthMetric,depthSampler,shadowSampler,shadowMapSizeInverse,lightSizeUV,darkness,frustumEdgeFalloff,16,32,PoissonSamplers32,lightSizeUVCorrection,depthCorrection,penumbraDarkness);
-}
-#define inline
-float computeShadowWithCSMPCSS64(float layer,vec4 vPositionFromLight,float depthMetric,highp sampler2DArray depthSampler,highp sampler2DArrayShadow shadowSampler,float shadowMapSizeInverse,float lightSizeUV,float darkness,float frustumEdgeFalloff,vec2 lightSizeUVCorrection,float depthCorrection,float penumbraDarkness)
-{
-return computeShadowWithCSMPCSS(layer,vPositionFromLight,depthMetric,depthSampler,shadowSampler,shadowMapSizeInverse,lightSizeUV,darkness,frustumEdgeFalloff,32,64,PoissonSamplers64,lightSizeUVCorrection,depthCorrection,penumbraDarkness);
-}
-#endif
-#endif
-`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="reflectionFunction",_=`vec3 parallaxCorrectNormal( vec3 vertexPos,vec3 origVec,vec3 cubeSize,vec3 cubePos ) {
-
-vec3 invOrigVec=vec3(1.0,1.0,1.0)/origVec;
-vec3 halfSize=cubeSize*0.5;
-vec3 intersecAtMaxPlane=(cubePos+halfSize-vertexPos)*invOrigVec;
-vec3 intersecAtMinPlane=(cubePos-halfSize-vertexPos)*invOrigVec;
-
-vec3 largestIntersec=max(intersecAtMaxPlane,intersecAtMinPlane);
-
-float distance=min(min(largestIntersec.x,largestIntersec.y),largestIntersec.z);
-
-vec3 intersectPositionWS=vertexPos+origVec*distance;
-
-return intersectPositionWS-cubePos;
-}
-vec3 computeFixedEquirectangularCoords(vec4 worldPos,vec3 worldNormal,vec3 direction)
-{
-float lon=atan(direction.z,direction.x);
-float lat=acos(direction.y);
-vec2 sphereCoords=vec2(lon,lat)*RECIPROCAL_PI2*2.0;
-float s=sphereCoords.x*0.5+0.5;
-float t=sphereCoords.y;
-return vec3(s,t,0);
-}
-vec3 computeMirroredFixedEquirectangularCoords(vec4 worldPos,vec3 worldNormal,vec3 direction)
-{
-float lon=atan(direction.z,direction.x);
-float lat=acos(direction.y);
-vec2 sphereCoords=vec2(lon,lat)*RECIPROCAL_PI2*2.0;
-float s=sphereCoords.x*0.5+0.5;
-float t=sphereCoords.y;
-return vec3(1.0-s,t,0);
-}
-vec3 computeEquirectangularCoords(vec4 worldPos,vec3 worldNormal,vec3 eyePosition,mat4 reflectionMatrix)
-{
-vec3 cameraToVertex=normalize(worldPos.xyz-eyePosition);
-vec3 r=normalize(reflect(cameraToVertex,worldNormal));
-r=vec3(reflectionMatrix*vec4(r,0));
-float lon=atan(r.z,r.x);
-float lat=acos(r.y);
-vec2 sphereCoords=vec2(lon,lat)*RECIPROCAL_PI2*2.0;
-float s=sphereCoords.x*0.5+0.5;
-float t=sphereCoords.y;
-return vec3(s,t,0);
-}
-vec3 computeSphericalCoords(vec4 worldPos,vec3 worldNormal,mat4 view,mat4 reflectionMatrix)
-{
-vec3 viewDir=normalize(vec3(view*worldPos));
-vec3 viewNormal=normalize(vec3(view*vec4(worldNormal,0.0)));
-vec3 r=reflect(viewDir,viewNormal);
-r=vec3(reflectionMatrix*vec4(r,0));
-r.z=r.z-1.0;
-float m=2.0*length(r);
-return vec3(r.x/m+0.5,1.0-r.y/m-0.5,0);
-}
-vec3 computePlanarCoords(vec4 worldPos,vec3 worldNormal,vec3 eyePosition,mat4 reflectionMatrix)
-{
-vec3 viewDir=worldPos.xyz-eyePosition;
-vec3 coords=normalize(reflect(viewDir,worldNormal));
-return vec3(reflectionMatrix*vec4(coords,1));
-}
-vec3 computeCubicCoords(vec4 worldPos,vec3 worldNormal,vec3 eyePosition,mat4 reflectionMatrix)
-{
-vec3 viewDir=normalize(worldPos.xyz-eyePosition);
-
-vec3 coords=reflect(viewDir,worldNormal);
-coords=vec3(reflectionMatrix*vec4(coords,0));
-#ifdef INVERTCUBICMAP
-coords.y*=-1.0;
-#endif
-return coords;
-}
-vec3 computeCubicLocalCoords(vec4 worldPos,vec3 worldNormal,vec3 eyePosition,mat4 reflectionMatrix,vec3 reflectionSize,vec3 reflectionPosition)
-{
-vec3 viewDir=normalize(worldPos.xyz-eyePosition);
-
-vec3 coords=reflect(viewDir,worldNormal);
-coords=parallaxCorrectNormal(worldPos.xyz,coords,reflectionSize,reflectionPosition);
-coords=vec3(reflectionMatrix*vec4(coords,0));
-#ifdef INVERTCUBICMAP
-coords.y*=-1.0;
-#endif
-return coords;
-}
-vec3 computeProjectionCoords(vec4 worldPos,mat4 view,mat4 reflectionMatrix)
-{
-return vec3(reflectionMatrix*(view*worldPos));
-}
-vec3 computeSkyBoxCoords(vec3 positionW,mat4 reflectionMatrix)
-{
-return vec3(reflectionMatrix*vec4(positionW,1.));
-}
-#ifdef REFLECTION
-vec3 computeReflectionCoords(vec4 worldPos,vec3 worldNormal)
-{
-#ifdef REFLECTIONMAP_MIRROREDEQUIRECTANGULAR_FIXED
-vec3 direction=normalize(vDirectionW);
-return computeMirroredFixedEquirectangularCoords(worldPos,worldNormal,direction);
-#endif
-#ifdef REFLECTIONMAP_EQUIRECTANGULAR_FIXED
-vec3 direction=normalize(vDirectionW);
-return computeFixedEquirectangularCoords(worldPos,worldNormal,direction);
-#endif
-#ifdef REFLECTIONMAP_EQUIRECTANGULAR
-return computeEquirectangularCoords(worldPos,worldNormal,vEyePosition.xyz,reflectionMatrix);
-#endif
-#ifdef REFLECTIONMAP_SPHERICAL
-return computeSphericalCoords(worldPos,worldNormal,view,reflectionMatrix);
-#endif
-#ifdef REFLECTIONMAP_PLANAR
-return computePlanarCoords(worldPos,worldNormal,vEyePosition.xyz,reflectionMatrix);
-#endif
-#ifdef REFLECTIONMAP_CUBIC
-#ifdef USE_LOCAL_REFLECTIONMAP_CUBIC
-return computeCubicLocalCoords(worldPos,worldNormal,vEyePosition.xyz,reflectionMatrix,vReflectionSize,vReflectionPosition);
-#else
-return computeCubicCoords(worldPos,worldNormal,vEyePosition.xyz,reflectionMatrix);
-#endif
-#endif
-#ifdef REFLECTIONMAP_PROJECTION
-return computeProjectionCoords(worldPos,view,reflectionMatrix);
-#endif
-#ifdef REFLECTIONMAP_SKYBOX
-return computeSkyBoxCoords(vPositionUVW,reflectionMatrix);
-#endif
-#ifdef REFLECTIONMAP_EXPLICIT
-return vec3(0,0,0);
-#endif
-}
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="bumpFragmentMainFunctions",_=`#if defined(BUMP) || defined(CLEARCOAT_BUMP) || defined(ANISOTROPIC) || defined(DETAIL)
-#if defined(TANGENT) && defined(NORMAL)
-varying mat3 vTBN;
-#endif
-#ifdef OBJECTSPACE_NORMALMAP
-uniform mat4 normalMatrix;
-#endif
-vec3 perturbNormalBase(mat3 cotangentFrame,vec3 normal,float scale)
-{
-#ifdef NORMALXYSCALE
-normal=normalize(normal*vec3(scale,scale,1.0));
-#endif
-return normalize(cotangentFrame*normal);
-}
-vec3 perturbNormal(mat3 cotangentFrame,vec3 textureSample,float scale)
-{
-return perturbNormalBase(cotangentFrame,textureSample*2.0-1.0,scale);
-}
-
-mat3 cotangent_frame(vec3 normal,vec3 p,vec2 uv,vec2 tangentSpaceParams)
-{
-
-uv=gl_FrontFacing ? uv : -uv;
-
-vec3 dp1=dFdx(p);
-vec3 dp2=dFdy(p);
-vec2 duv1=dFdx(uv);
-vec2 duv2=dFdy(uv);
-
-vec3 dp2perp=cross(dp2,normal);
-vec3 dp1perp=cross(normal,dp1);
-vec3 tangent=dp2perp*duv1.x+dp1perp*duv2.x;
-vec3 bitangent=dp2perp*duv1.y+dp1perp*duv2.y;
-
-tangent*=tangentSpaceParams.x;
-bitangent*=tangentSpaceParams.y;
-
-float invmax=inversesqrt(max(dot(tangent,tangent),dot(bitangent,bitangent)));
-return mat3(tangent*invmax,bitangent*invmax,normal);
-}
-#endif
-`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="bumpFragmentFunctions",_=`#if defined(BUMP)
-#if BUMPDIRECTUV == 1
-#define vBumpUV vMainUV1
-#elif BUMPDIRECTUV == 2
-#define vBumpUV vMainUV2
-#else
-varying vec2 vBumpUV;
-#endif
-uniform sampler2D bumpSampler;
-vec3 perturbNormal(mat3 cotangentFrame,vec2 uv)
-{
-return perturbNormal(cotangentFrame,texture2D(bumpSampler,uv).xyz,vBumpInfos.y);
-}
-#endif
-#if defined(DETAIL)
-#if DETAILDIRECTUV == 1
-#define vDetailUV vMainUV1
-#elif DETAILDIRECTUV == 2
-#define vDetailUV vMainUV2
-#else
-varying vec2 vDetailUV;
-#endif
-uniform sampler2D detailSampler;
-#endif
-#if defined(BUMP)
-vec3 perturbNormal(mat3 cotangentFrame,vec3 color)
-{
-return perturbNormal(cotangentFrame,color,vBumpInfos.y);
-}
-
-mat3 cotangent_frame(vec3 normal,vec3 p,vec2 uv)
-{
-return cotangent_frame(normal,p,uv,vTangentSpaceParams);
-}
-#endif
-#if defined(BUMP) && defined(PARALLAX)
-const float minSamples=4.;
-const float maxSamples=15.;
-const int iMaxSamples=15;
-
-vec2 parallaxOcclusion(vec3 vViewDirCoT,vec3 vNormalCoT,vec2 texCoord,float parallaxScale) {
-float parallaxLimit=length(vViewDirCoT.xy)/vViewDirCoT.z;
-parallaxLimit*=parallaxScale;
-vec2 vOffsetDir=normalize(vViewDirCoT.xy);
-vec2 vMaxOffset=vOffsetDir*parallaxLimit;
-float numSamples=maxSamples+(dot(vViewDirCoT,vNormalCoT)*(minSamples-maxSamples));
-float stepSize=1.0/numSamples;
-
-float currRayHeight=1.0;
-vec2 vCurrOffset=vec2(0,0);
-vec2 vLastOffset=vec2(0,0);
-float lastSampledHeight=1.0;
-float currSampledHeight=1.0;
-for (int i=0; i<iMaxSamples; i++)
-{
-currSampledHeight=texture2D(bumpSampler,vBumpUV+vCurrOffset).w;
-
-if (currSampledHeight>currRayHeight)
-{
-float delta1=currSampledHeight-currRayHeight;
-float delta2=(currRayHeight+stepSize)-lastSampledHeight;
-float ratio=delta1/(delta1+delta2);
-vCurrOffset=(ratio)* vLastOffset+(1.0-ratio)*vCurrOffset;
-
-break;
-}
-else
-{
-currRayHeight-=stepSize;
-vLastOffset=vCurrOffset;
-vCurrOffset+=stepSize*vMaxOffset;
-lastSampledHeight=currSampledHeight;
-}
-}
-return vCurrOffset;
-}
-vec2 parallaxOffset(vec3 viewDir,float heightScale)
-{
-
-float height=texture2D(bumpSampler,vBumpUV).w;
-vec2 texCoordOffset=heightScale*viewDir.xy*height;
-return -texCoordOffset;
-}
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U=`vec2 uvOffset=vec2(0.0,0.0);
-#if defined(BUMP) || defined(PARALLAX) || defined(DETAIL)
-#ifdef NORMALXYSCALE
-float normalScale=1.0;
-#elif defined(BUMP)
-float normalScale=vBumpInfos.y;
-#else
-float normalScale=1.0;
-#endif
-#if defined(TANGENT) && defined(NORMAL)
-mat3 TBN=vTBN;
-#elif defined(BUMP)
-mat3 TBN=cotangent_frame(normalW*normalScale,vPositionW,vBumpUV);
-#else
-mat3 TBN=cotangent_frame(normalW*normalScale,vPositionW,vDetailUV,vec2(1.,1.));
-#endif
-#elif defined(ANISOTROPIC)
-#if defined(TANGENT) && defined(NORMAL)
-mat3 TBN=vTBN;
-#else
-mat3 TBN=cotangent_frame(normalW,vPositionW,vMainUV1,vec2(1.,1.));
-#endif
-#endif
-#ifdef PARALLAX
-mat3 invTBN=transposeMat3(TBN);
-#ifdef PARALLAXOCCLUSION
-uvOffset=parallaxOcclusion(invTBN*-viewDirectionW,invTBN*normalW,vBumpUV,vBumpInfos.z);
-#else
-uvOffset=parallaxOffset(invTBN*viewDirectionW,vBumpInfos.z);
-#endif
-#endif
-#ifdef DETAIL
-vec4 detailColor=texture2D(detailSampler,vDetailUV+uvOffset);
-vec2 detailNormalRG=detailColor.wy*2.0-1.0;
-float detailNormalB=sqrt(1.-saturate(dot(detailNormalRG,detailNormalRG)));
-vec3 detailNormal=vec3(detailNormalRG,detailNormalB);
-#endif
-#ifdef BUMP
-#ifdef OBJECTSPACE_NORMALMAP
-normalW=normalize(texture2D(bumpSampler,vBumpUV).xyz*2.0-1.0);
-normalW=normalize(mat3(normalMatrix)*normalW);
-#elif !defined(DETAIL)
-normalW=perturbNormal(TBN,vBumpUV+uvOffset);
-#else
-vec3 bumpNormal=texture2D(bumpSampler,vBumpUV+uvOffset).xyz*2.0-1.0;
-
-#if DETAIL_NORMALBLENDMETHOD == 0
-detailNormal.xy*=vDetailInfos.z;
-vec3 blendedNormal=normalize(vec3(bumpNormal.xy+detailNormal.xy,bumpNormal.z*detailNormal.z));
-#elif DETAIL_NORMALBLENDMETHOD == 1
-detailNormal.xy*=vDetailInfos.z;
-bumpNormal+=vec3(0.0,0.0,1.0);
-detailNormal*=vec3(-1.0,-1.0,1.0);
-vec3 blendedNormal=bumpNormal*dot(bumpNormal,detailNormal)/bumpNormal.z-detailNormal;
-#endif
-normalW=perturbNormalBase(TBN,blendedNormal,vBumpInfos.y);
-#endif
-#elif defined(DETAIL)
-detailNormal.xy*=vDetailInfos.z;
-normalW=perturbNormalBase(TBN,detailNormal,vDetailInfos.z);
-#endif`;f(5).a.IncludesShadersStore.bumpFragment=U},function(Me,y,f){var U="lightFragment",_=`#ifdef LIGHT{X}
-#if defined(SHADOWONLY) || defined(LIGHTMAP) && defined(LIGHTMAPEXCLUDED{X}) && defined(LIGHTMAPNOSPECULAR{X})
-
-#else
-#ifdef PBR
-
-#ifdef SPOTLIGHT{X}
-preInfo=computePointAndSpotPreLightingInfo(light{X}.vLightData,viewDirectionW,normalW);
-#elif defined(POINTLIGHT{X})
-preInfo=computePointAndSpotPreLightingInfo(light{X}.vLightData,viewDirectionW,normalW);
-#elif defined(HEMILIGHT{X})
-preInfo=computeHemisphericPreLightingInfo(light{X}.vLightData,viewDirectionW,normalW);
-#elif defined(DIRLIGHT{X})
-preInfo=computeDirectionalPreLightingInfo(light{X}.vLightData,viewDirectionW,normalW);
-#endif
-preInfo.NdotV=NdotV;
-
-#ifdef SPOTLIGHT{X}
-#ifdef LIGHT_FALLOFF_GLTF{X}
-preInfo.attenuation=computeDistanceLightFalloff_GLTF(preInfo.lightDistanceSquared,light{X}.vLightFalloff.y);
-preInfo.attenuation*=computeDirectionalLightFalloff_GLTF(light{X}.vLightDirection.xyz,preInfo.L,light{X}.vLightFalloff.z,light{X}.vLightFalloff.w);
-#elif defined(LIGHT_FALLOFF_PHYSICAL{X})
-preInfo.attenuation=computeDistanceLightFalloff_Physical(preInfo.lightDistanceSquared);
-preInfo.attenuation*=computeDirectionalLightFalloff_Physical(light{X}.vLightDirection.xyz,preInfo.L,light{X}.vLightDirection.w);
-#elif defined(LIGHT_FALLOFF_STANDARD{X})
-preInfo.attenuation=computeDistanceLightFalloff_Standard(preInfo.lightOffset,light{X}.vLightFalloff.x);
-preInfo.attenuation*=computeDirectionalLightFalloff_Standard(light{X}.vLightDirection.xyz,preInfo.L,light{X}.vLightDirection.w,light{X}.vLightData.w);
-#else
-preInfo.attenuation=computeDistanceLightFalloff(preInfo.lightOffset,preInfo.lightDistanceSquared,light{X}.vLightFalloff.x,light{X}.vLightFalloff.y);
-preInfo.attenuation*=computeDirectionalLightFalloff(light{X}.vLightDirection.xyz,preInfo.L,light{X}.vLightDirection.w,light{X}.vLightData.w,light{X}.vLightFalloff.z,light{X}.vLightFalloff.w);
-#endif
-#elif defined(POINTLIGHT{X})
-#ifdef LIGHT_FALLOFF_GLTF{X}
-preInfo.attenuation=computeDistanceLightFalloff_GLTF(preInfo.lightDistanceSquared,light{X}.vLightFalloff.y);
-#elif defined(LIGHT_FALLOFF_PHYSICAL{X})
-preInfo.attenuation=computeDistanceLightFalloff_Physical(preInfo.lightDistanceSquared);
-#elif defined(LIGHT_FALLOFF_STANDARD{X})
-preInfo.attenuation=computeDistanceLightFalloff_Standard(preInfo.lightOffset,light{X}.vLightFalloff.x);
-#else
-preInfo.attenuation=computeDistanceLightFalloff(preInfo.lightOffset,preInfo.lightDistanceSquared,light{X}.vLightFalloff.x,light{X}.vLightFalloff.y);
-#endif
-#else
-preInfo.attenuation=1.0;
-#endif
-
-
-#ifdef HEMILIGHT{X}
-preInfo.roughness=roughness;
-#else
-preInfo.roughness=adjustRoughnessFromLightProperties(roughness,light{X}.vLightSpecular.a,preInfo.lightDistance);
-#endif
-
-#ifdef HEMILIGHT{X}
-info.diffuse=computeHemisphericDiffuseLighting(preInfo,light{X}.vLightDiffuse.rgb,light{X}.vLightGround);
-#elif defined(SS_TRANSLUCENCY)
-info.diffuse=computeDiffuseAndTransmittedLighting(preInfo,light{X}.vLightDiffuse.rgb,subSurfaceOut.transmittance);
-#else
-info.diffuse=computeDiffuseLighting(preInfo,light{X}.vLightDiffuse.rgb);
-#endif
-
-#ifdef SPECULARTERM
-#ifdef ANISOTROPIC
-info.specular=computeAnisotropicSpecularLighting(preInfo,viewDirectionW,normalW,anisotropicOut.anisotropicTangent,anisotropicOut.anisotropicBitangent,anisotropicOut.anisotropy,clearcoatOut.specularEnvironmentR0,specularEnvironmentR90,AARoughnessFactors.x,light{X}.vLightDiffuse.rgb);
-#else
-info.specular=computeSpecularLighting(preInfo,normalW,clearcoatOut.specularEnvironmentR0,specularEnvironmentR90,AARoughnessFactors.x,light{X}.vLightDiffuse.rgb);
-#endif
-#endif
-
-#ifdef SHEEN
-#ifdef SHEEN_LINKWITHALBEDO
-
-preInfo.roughness=sheenOut.sheenIntensity;
-#else
-#ifdef HEMILIGHT{X}
-preInfo.roughness=sheenOut.sheenRoughness;
-#else
-preInfo.roughness=adjustRoughnessFromLightProperties(sheenOut.sheenRoughness,light{X}.vLightSpecular.a,preInfo.lightDistance);
-#endif
-#endif
-info.sheen=computeSheenLighting(preInfo,normalW,sheenOut.sheenColor,specularEnvironmentR90,AARoughnessFactors.x,light{X}.vLightDiffuse.rgb);
-#endif
-
-#ifdef CLEARCOAT
-
-#ifdef HEMILIGHT{X}
-preInfo.roughness=clearcoatOut.clearCoatRoughness;
-#else
-preInfo.roughness=adjustRoughnessFromLightProperties(clearcoatOut.clearCoatRoughness,light{X}.vLightSpecular.a,preInfo.lightDistance);
-#endif
-info.clearCoat=computeClearCoatLighting(preInfo,clearcoatOut.clearCoatNormalW,clearcoatOut.clearCoatAARoughnessFactors.x,clearcoatOut.clearCoatIntensity,light{X}.vLightDiffuse.rgb);
-#ifdef CLEARCOAT_TINT
-
-absorption=computeClearCoatLightingAbsorption(clearcoatOut.clearCoatNdotVRefract,preInfo.L,clearcoatOut.clearCoatNormalW,clearcoatOut.clearCoatColor,clearcoatOut.clearCoatThickness,clearcoatOut.clearCoatIntensity);
-info.diffuse*=absorption;
-#ifdef SPECULARTERM
-info.specular*=absorption;
-#endif
-#endif
-
-info.diffuse*=info.clearCoat.w;
-#ifdef SPECULARTERM
-info.specular*=info.clearCoat.w;
-#endif
-#ifdef SHEEN
-info.sheen*=info.clearCoat.w;
-#endif
-#endif
-#else
-#ifdef SPOTLIGHT{X}
-info=computeSpotLighting(viewDirectionW,normalW,light{X}.vLightData,light{X}.vLightDirection,light{X}.vLightDiffuse.rgb,light{X}.vLightSpecular.rgb,light{X}.vLightDiffuse.a,glossiness);
-#elif defined(HEMILIGHT{X})
-info=computeHemisphericLighting(viewDirectionW,normalW,light{X}.vLightData,light{X}.vLightDiffuse.rgb,light{X}.vLightSpecular.rgb,light{X}.vLightGround,glossiness);
-#elif defined(POINTLIGHT{X}) || defined(DIRLIGHT{X})
-info=computeLighting(viewDirectionW,normalW,light{X}.vLightData,light{X}.vLightDiffuse.rgb,light{X}.vLightSpecular.rgb,light{X}.vLightDiffuse.a,glossiness);
-#endif
-#endif
-#ifdef PROJECTEDLIGHTTEXTURE{X}
-info.diffuse*=computeProjectionTextureDiffuseLighting(projectionLightSampler{X},textureProjectionMatrix{X});
-#endif
-#endif
-#ifdef SHADOW{X}
-#ifdef SHADOWCSM{X}
-for (int i=0; i<SHADOWCSMNUM_CASCADES{X}; i++)
-{
-#ifdef SHADOWCSM_RIGHTHANDED{X}
-diff{X}=viewFrustumZ{X}[i]+vPositionFromCamera{X}.z;
-#else
-diff{X}=viewFrustumZ{X}[i]-vPositionFromCamera{X}.z;
-#endif
-if (diff{X}>=0.) {
-index{X}=i;
-break;
-}
-}
-#ifdef SHADOWCSMUSESHADOWMAXZ{X}
-if (index{X}>=0)
-#endif
-{
-#if defined(SHADOWPCF{X})
-#if defined(SHADOWLOWQUALITY{X})
-shadow=computeShadowWithCSMPCF1(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#elif defined(SHADOWMEDIUMQUALITY{X})
-shadow=computeShadowWithCSMPCF3(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.yz,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#else
-shadow=computeShadowWithCSMPCF5(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.yz,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-#elif defined(SHADOWPCSS{X})
-#if defined(SHADOWLOWQUALITY{X})
-shadow=computeShadowWithCSMPCSS16(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w,lightSizeUVCorrection{X}[index{X}],depthCorrection{X}[index{X}],penumbraDarkness{X});
-#elif defined(SHADOWMEDIUMQUALITY{X})
-shadow=computeShadowWithCSMPCSS32(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w,lightSizeUVCorrection{X}[index{X}],depthCorrection{X}[index{X}],penumbraDarkness{X});
-#else
-shadow=computeShadowWithCSMPCSS64(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w,lightSizeUVCorrection{X}[index{X}],depthCorrection{X}[index{X}],penumbraDarkness{X});
-#endif
-#else
-shadow=computeShadowCSM(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-#ifdef SHADOWCSMDEBUG{X}
-shadowDebug{X}=vec3(shadow)*vCascadeColorsMultiplier{X}[index{X}];
-#endif
-#ifndef SHADOWCSMNOBLEND{X}
-float frustumLength=frustumLengths{X}[index{X}];
-float diffRatio=clamp(diff{X}/frustumLength,0.,1.)*cascadeBlendFactor{X};
-if (index{X}<(SHADOWCSMNUM_CASCADES{X}-1) && diffRatio<1.)
-{
-index{X}+=1;
-float nextShadow=0.;
-#if defined(SHADOWPCF{X})
-#if defined(SHADOWLOWQUALITY{X})
-nextShadow=computeShadowWithCSMPCF1(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#elif defined(SHADOWMEDIUMQUALITY{X})
-nextShadow=computeShadowWithCSMPCF3(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.yz,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#else
-nextShadow=computeShadowWithCSMPCF5(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.yz,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-#elif defined(SHADOWPCSS{X})
-#if defined(SHADOWLOWQUALITY{X})
-nextShadow=computeShadowWithCSMPCSS16(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w,lightSizeUVCorrection{X}[index{X}],depthCorrection{X}[index{X}],penumbraDarkness{X});
-#elif defined(SHADOWMEDIUMQUALITY{X})
-nextShadow=computeShadowWithCSMPCSS32(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w,lightSizeUVCorrection{X}[index{X}],depthCorrection{X}[index{X}],penumbraDarkness{X});
-#else
-nextShadow=computeShadowWithCSMPCSS64(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w,lightSizeUVCorrection{X}[index{X}],depthCorrection{X}[index{X}],penumbraDarkness{X});
-#endif
-#else
-nextShadow=computeShadowCSM(float(index{X}),vPositionFromLight{X}[index{X}],vDepthMetric{X}[index{X}],shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-shadow=mix(nextShadow,shadow,diffRatio);
-#ifdef SHADOWCSMDEBUG{X}
-shadowDebug{X}=mix(vec3(nextShadow)*vCascadeColorsMultiplier{X}[index{X}],shadowDebug{X},diffRatio);
-#endif
-}
-#endif
-}
-#elif defined(SHADOWCLOSEESM{X})
-#if defined(SHADOWCUBE{X})
-shadow=computeShadowWithCloseESMCube(light{X}.vLightData.xyz,shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.z,light{X}.depthValues);
-#else
-shadow=computeShadowWithCloseESM(vPositionFromLight{X},vDepthMetric{X},shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.z,light{X}.shadowsInfo.w);
-#endif
-#elif defined(SHADOWESM{X})
-#if defined(SHADOWCUBE{X})
-shadow=computeShadowWithESMCube(light{X}.vLightData.xyz,shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.z,light{X}.depthValues);
-#else
-shadow=computeShadowWithESM(vPositionFromLight{X},vDepthMetric{X},shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.z,light{X}.shadowsInfo.w);
-#endif
-#elif defined(SHADOWPOISSON{X})
-#if defined(SHADOWCUBE{X})
-shadow=computeShadowWithPoissonSamplingCube(light{X}.vLightData.xyz,shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.x,light{X}.depthValues);
-#else
-shadow=computeShadowWithPoissonSampling(vPositionFromLight{X},vDepthMetric{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-#elif defined(SHADOWPCF{X})
-#if defined(SHADOWLOWQUALITY{X})
-shadow=computeShadowWithPCF1(vPositionFromLight{X},vDepthMetric{X},shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#elif defined(SHADOWMEDIUMQUALITY{X})
-shadow=computeShadowWithPCF3(vPositionFromLight{X},vDepthMetric{X},shadowSampler{X},light{X}.shadowsInfo.yz,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#else
-shadow=computeShadowWithPCF5(vPositionFromLight{X},vDepthMetric{X},shadowSampler{X},light{X}.shadowsInfo.yz,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-#elif defined(SHADOWPCSS{X})
-#if defined(SHADOWLOWQUALITY{X})
-shadow=computeShadowWithPCSS16(vPositionFromLight{X},vDepthMetric{X},depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#elif defined(SHADOWMEDIUMQUALITY{X})
-shadow=computeShadowWithPCSS32(vPositionFromLight{X},vDepthMetric{X},depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#else
-shadow=computeShadowWithPCSS64(vPositionFromLight{X},vDepthMetric{X},depthSampler{X},shadowSampler{X},light{X}.shadowsInfo.y,light{X}.shadowsInfo.z,light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-#else
-#if defined(SHADOWCUBE{X})
-shadow=computeShadowCube(light{X}.vLightData.xyz,shadowSampler{X},light{X}.shadowsInfo.x,light{X}.depthValues);
-#else
-shadow=computeShadow(vPositionFromLight{X},vDepthMetric{X},shadowSampler{X},light{X}.shadowsInfo.x,light{X}.shadowsInfo.w);
-#endif
-#endif
-#ifdef SHADOWONLY
-#ifndef SHADOWINUSE
-#define SHADOWINUSE
-#endif
-globalShadow+=shadow;
-shadowLightCount+=1.0;
-#endif
-#else
-shadow=1.;
-#endif
-#ifndef SHADOWONLY
-#ifdef CUSTOMUSERLIGHTING
-diffuseBase+=computeCustomDiffuseLighting(info,diffuseBase,shadow);
-#ifdef SPECULARTERM
-specularBase+=computeCustomSpecularLighting(info,specularBase,shadow);
-#endif
-#elif defined(LIGHTMAP) && defined(LIGHTMAPEXCLUDED{X})
-diffuseBase+=lightmapColor.rgb*shadow;
-#ifdef SPECULARTERM
-#ifndef LIGHTMAPNOSPECULAR{X}
-specularBase+=info.specular*shadow*lightmapColor.rgb;
-#endif
-#endif
-#ifdef CLEARCOAT
-#ifndef LIGHTMAPNOSPECULAR{X}
-clearCoatBase+=info.clearCoat.rgb*shadow*lightmapColor.rgb;
-#endif
-#endif
-#ifdef SHEEN
-#ifndef LIGHTMAPNOSPECULAR{X}
-sheenBase+=info.sheen.rgb*shadow;
-#endif
-#endif
-#else
-#ifdef SHADOWCSMDEBUG{X}
-diffuseBase+=info.diffuse*shadowDebug{X};
-#else
-diffuseBase+=info.diffuse*shadow;
-#endif
-#ifdef SPECULARTERM
-specularBase+=info.specular*shadow;
-#endif
-#ifdef CLEARCOAT
-clearCoatBase+=info.clearCoat.rgb*shadow;
-#endif
-#ifdef SHEEN
-sheenBase+=info.sheen.rgb*shadow;
-#endif
-#endif
-#endif
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U=`#ifdef FOG
-float fog=CalcFogFactor();
-color.rgb=fog*color.rgb+(1.0-fog)*vFogColor;
-#endif`;f(5).a.IncludesShadersStore.fogFragment=U},function(Me,y,f){var U="fogVertexDeclaration",_=`#ifdef FOG
-varying vec3 vFogDistance;
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){var U="shadowsVertex",_=`#ifdef SHADOWS
-#if defined(SHADOWCSM{X})
-vPositionFromCamera{X}=view*worldPos;
-for (int i=0; i<SHADOWCSMNUM_CASCADES{X}; i++) {
-vPositionFromLight{X}[i]=lightMatrix{X}[i]*worldPos;
-vDepthMetric{X}[i]=((vPositionFromLight{X}[i].z+light{X}.depthValues.x)/(light{X}.depthValues.y));
-}
-#elif defined(SHADOW{X}) && !defined(SHADOWCUBE{X})
-vPositionFromLight{X}=lightMatrix{X}*worldPos;
-vDepthMetric{X}=((vPositionFromLight{X}.z+light{X}.depthValues.x)/(light{X}.depthValues.y));
-#endif
-#endif`;f(5).a.IncludesShadersStore[U]=_},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.Eval=function(C,u){return(C=C.match(/\([^\(\)]*\)/g)?C.replace(/\([^\(\)]*\)/g,function(M){return M=M.slice(1,M.length-1),_._HandleParenthesisContent(M,u)}):_._HandleParenthesisContent(C,u))==="true"||C!=="false"&&_.Eval(C,u)},_._HandleParenthesisContent=function(C,u){var M;u=u||function(S){return S==="true"};var R=C.split("||");for(var x in R)if(R.hasOwnProperty(x)){var m=_._SimplifyNegation(R[x].trim()),c=m.split("&&");if(c.length>1)for(var T=0;T<c.length;++T){var A=_._SimplifyNegation(c[T].trim());if(!(M=A!=="true"&&A!=="false"?A[0]==="!"?!u(A.substring(1)):u(A):A==="true")){m="false";break}}if(M||m==="true"){M=!0;break}M=m!=="true"&&m!=="false"?m[0]==="!"?!u(m.substring(1)):u(m):m==="true"}return M?"true":"false"},_._SimplifyNegation=function(C){return(C=(C=C.replace(/^[\s!]+/,function(u){return(u=u.replace(/[\s]/g,function(){return""})).length%2?"!":""})).trim())==="!true"?C="false":C==="!false"&&(C="true"),C},_}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){}return _.ExponentialBackoff=function(C,u){return C===void 0&&(C=3),u===void 0&&(u=500),function(M,R,x){return R.status!==0||x>=C||M.indexOf("file:")!==-1?-1:Math.pow(2,x)*u}},_}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){this._isDepthTestDirty=!1,this._isDepthMaskDirty=!1,this._isDepthFuncDirty=!1,this._isCullFaceDirty=!1,this._isCullDirty=!1,this._isZOffsetDirty=!1,this._isFrontFaceDirty=!1,this.reset()}return Object.defineProperty(_.prototype,"isDirty",{get:function(){return this._isDepthFuncDirty||this._isDepthTestDirty||this._isDepthMaskDirty||this._isCullFaceDirty||this._isCullDirty||this._isZOffsetDirty||this._isFrontFaceDirty},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"zOffset",{get:function(){return this._zOffset},set:function(C){this._zOffset!==C&&(this._zOffset=C,this._isZOffsetDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"cullFace",{get:function(){return this._cullFace},set:function(C){this._cullFace!==C&&(this._cullFace=C,this._isCullFaceDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"cull",{get:function(){return this._cull},set:function(C){this._cull!==C&&(this._cull=C,this._isCullDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"depthFunc",{get:function(){return this._depthFunc},set:function(C){this._depthFunc!==C&&(this._depthFunc=C,this._isDepthFuncDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"depthMask",{get:function(){return this._depthMask},set:function(C){this._depthMask!==C&&(this._depthMask=C,this._isDepthMaskDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"depthTest",{get:function(){return this._depthTest},set:function(C){this._depthTest!==C&&(this._depthTest=C,this._isDepthTestDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"frontFace",{get:function(){return this._frontFace},set:function(C){this._frontFace!==C&&(this._frontFace=C,this._isFrontFaceDirty=!0)},enumerable:!1,configurable:!0}),_.prototype.reset=function(){this._depthMask=!0,this._depthTest=!0,this._depthFunc=null,this._cullFace=null,this._cull=null,this._zOffset=0,this._frontFace=null,this._isDepthTestDirty=!0,this._isDepthMaskDirty=!0,this._isDepthFuncDirty=!1,this._isCullFaceDirty=!1,this._isCullDirty=!1,this._isZOffsetDirty=!1,this._isFrontFaceDirty=!1},_.prototype.apply=function(C){this.isDirty&&(this._isCullDirty&&(this.cull?C.enable(C.CULL_FACE):C.disable(C.CULL_FACE),this._isCullDirty=!1),this._isCullFaceDirty&&(C.cullFace(this.cullFace),this._isCullFaceDirty=!1),this._isDepthMaskDirty&&(C.depthMask(this.depthMask),this._isDepthMaskDirty=!1),this._isDepthTestDirty&&(this.depthTest?C.enable(C.DEPTH_TEST):C.disable(C.DEPTH_TEST),this._isDepthTestDirty=!1),this._isDepthFuncDirty&&(C.depthFunc(this.depthFunc),this._isDepthFuncDirty=!1),this._isZOffsetDirty&&(this.zOffset?(C.enable(C.POLYGON_OFFSET_FILL),C.polygonOffset(this.zOffset,0)):C.disable(C.POLYGON_OFFSET_FILL),this._isZOffsetDirty=!1),this._isFrontFaceDirty&&(C.frontFace(this.frontFace),this._isFrontFaceDirty=!1))},_}()},function(Me,y,f){f.d(y,"a",function(){return _});var U=f(2),_=function(){function C(){this._isStencilTestDirty=!1,this._isStencilMaskDirty=!1,this._isStencilFuncDirty=!1,this._isStencilOpDirty=!1,this.reset()}return Object.defineProperty(C.prototype,"isDirty",{get:function(){return this._isStencilTestDirty||this._isStencilMaskDirty||this._isStencilFuncDirty||this._isStencilOpDirty},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"stencilFunc",{get:function(){return this._stencilFunc},set:function(u){this._stencilFunc!==u&&(this._stencilFunc=u,this._isStencilFuncDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"stencilFuncRef",{get:function(){return this._stencilFuncRef},set:function(u){this._stencilFuncRef!==u&&(this._stencilFuncRef=u,this._isStencilFuncDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"stencilFuncMask",{get:function(){return this._stencilFuncMask},set:function(u){this._stencilFuncMask!==u&&(this._stencilFuncMask=u,this._isStencilFuncDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"stencilOpStencilFail",{get:function(){return this._stencilOpStencilFail},set:function(u){this._stencilOpStencilFail!==u&&(this._stencilOpStencilFail=u,this._isStencilOpDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"stencilOpDepthFail",{get:function(){return this._stencilOpDepthFail},set:function(u){this._stencilOpDepthFail!==u&&(this._stencilOpDepthFail=u,this._isStencilOpDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"stencilOpStencilDepthPass",{get:function(){return this._stencilOpStencilDepthPass},set:function(u){this._stencilOpStencilDepthPass!==u&&(this._stencilOpStencilDepthPass=u,this._isStencilOpDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"stencilMask",{get:function(){return this._stencilMask},set:function(u){this._stencilMask!==u&&(this._stencilMask=u,this._isStencilMaskDirty=!0)},enumerable:!1,configurable:!0}),Object.defineProperty(C.prototype,"stencilTest",{get:function(){return this._stencilTest},set:function(u){this._stencilTest!==u&&(this._stencilTest=u,this._isStencilTestDirty=!0)},enumerable:!1,configurable:!0}),C.prototype.reset=function(){this._stencilTest=!1,this._stencilMask=255,this._stencilFunc=C.ALWAYS,this._stencilFuncRef=1,this._stencilFuncMask=255,this._stencilOpStencilFail=C.KEEP,this._stencilOpDepthFail=C.KEEP,this._stencilOpStencilDepthPass=C.REPLACE,this._isStencilTestDirty=!0,this._isStencilMaskDirty=!0,this._isStencilFuncDirty=!0,this._isStencilOpDirty=!0},C.prototype.apply=function(u){this.isDirty&&(this._isStencilTestDirty&&(this.stencilTest?u.enable(u.STENCIL_TEST):u.disable(u.STENCIL_TEST),this._isStencilTestDirty=!1),this._isStencilMaskDirty&&(u.stencilMask(this.stencilMask),this._isStencilMaskDirty=!1),this._isStencilFuncDirty&&(u.stencilFunc(this.stencilFunc,this.stencilFuncRef,this.stencilFuncMask),this._isStencilFuncDirty=!1),this._isStencilOpDirty&&(u.stencilOp(this.stencilOpStencilFail,this.stencilOpDepthFail,this.stencilOpStencilDepthPass),this._isStencilOpDirty=!1))},C.ALWAYS=U.a.ALWAYS,C.KEEP=U.a.KEEP,C.REPLACE=U.a.REPLACE,C}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){this._isAlphaBlendDirty=!1,this._isBlendFunctionParametersDirty=!1,this._isBlendEquationParametersDirty=!1,this._isBlendConstantsDirty=!1,this._alphaBlend=!1,this._blendFunctionParameters=new Array(4),this._blendEquationParameters=new Array(2),this._blendConstants=new Array(4),this.reset()}return Object.defineProperty(_.prototype,"isDirty",{get:function(){return this._isAlphaBlendDirty||this._isBlendFunctionParametersDirty},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"alphaBlend",{get:function(){return this._alphaBlend},set:function(C){this._alphaBlend!==C&&(this._alphaBlend=C,this._isAlphaBlendDirty=!0)},enumerable:!1,configurable:!0}),_.prototype.setAlphaBlendConstants=function(C,u,M,R){this._blendConstants[0]===C&&this._blendConstants[1]===u&&this._blendConstants[2]===M&&this._blendConstants[3]===R||(this._blendConstants[0]=C,this._blendConstants[1]=u,this._blendConstants[2]=M,this._blendConstants[3]=R,this._isBlendConstantsDirty=!0)},_.prototype.setAlphaBlendFunctionParameters=function(C,u,M,R){this._blendFunctionParameters[0]===C&&this._blendFunctionParameters[1]===u&&this._blendFunctionParameters[2]===M&&this._blendFunctionParameters[3]===R||(this._blendFunctionParameters[0]=C,this._blendFunctionParameters[1]=u,this._blendFunctionParameters[2]=M,this._blendFunctionParameters[3]=R,this._isBlendFunctionParametersDirty=!0)},_.prototype.setAlphaEquationParameters=function(C,u){this._blendEquationParameters[0]===C&&this._blendEquationParameters[1]===u||(this._blendEquationParameters[0]=C,this._blendEquationParameters[1]=u,this._isBlendEquationParametersDirty=!0)},_.prototype.reset=function(){this._alphaBlend=!1,this._blendFunctionParameters[0]=null,this._blendFunctionParameters[1]=null,this._blendFunctionParameters[2]=null,this._blendFunctionParameters[3]=null,this._blendEquationParameters[0]=null,this._blendEquationParameters[1]=null,this._blendConstants[0]=null,this._blendConstants[1]=null,this._blendConstants[2]=null,this._blendConstants[3]=null,this._isAlphaBlendDirty=!0,this._isBlendFunctionParametersDirty=!1,this._isBlendEquationParametersDirty=!1,this._isBlendConstantsDirty=!1},_.prototype.apply=function(C){this.isDirty&&(this._isAlphaBlendDirty&&(this._alphaBlend?C.enable(C.BLEND):C.disable(C.BLEND),this._isAlphaBlendDirty=!1),this._isBlendFunctionParametersDirty&&(C.blendFuncSeparate(this._blendFunctionParameters[0],this._blendFunctionParameters[1],this._blendFunctionParameters[2],this._blendFunctionParameters[3]),this._isBlendFunctionParametersDirty=!1),this._isBlendEquationParametersDirty&&(C.blendEquationSeparate(this._blendEquationParameters[0],this._blendEquationParameters[1]),this._isBlendEquationParametersDirty=!1),this._isBlendConstantsDirty&&(C.blendColor(this._blendConstants[0],this._blendConstants[1],this._blendConstants[2],this._blendConstants[3]),this._isBlendConstantsDirty=!1))},_}()},function(Me,y,f){f.d(y,"a",function(){return U});var U=function(){function _(){this.vertexCompilationError=null,this.fragmentCompilationError=null,this.programLinkError=null,this.programValidationError=null}return Object.defineProperty(_.prototype,"isAsync",{get:function(){return this.isParallelCompiled},enumerable:!1,configurable:!0}),Object.defineProperty(_.prototype,"isReady",{get:function(){return!!this.program&&(!this.isParallelCompiled||this.engine._isRenderingStateCompiled(this))},enumerable:!1,configurable:!0}),_.prototype._handlesSpectorRebuildCallback=function(C){C&&this.program&&C(this.program)},_.prototype._getVertexShaderCode=function(){return this.vertexShader?this.engine._getShaderSource(this.vertexShader):null},_.prototype._getFragmentShaderCode=function(){return this.fragmentShader?this.engine._getShaderSource(this.fragmentShader):null},_}()},function(Me,y,f){var U;f.d(y,"a",function(){return u}),function(M){M[M.Pending=0]="Pending",M[M.Fulfilled=1]="Fulfilled",M[M.Rejected=2]="Rejected"}(U||(U={}));var _=function(){this.count=0,this.target=0,this.results=[]},C=function(){function M(R){var x=this;if(this._state=U.Pending,this._children=new Array,this._rejectWasConsumed=!1,R)try{R(function(m){x._resolve(m)},function(m){x._reject(m)})}catch(m){this._reject(m)}}return Object.defineProperty(M.prototype,"_result",{get:function(){return this._resultValue},set:function(R){this._resultValue=R,this._parent&&this._parent._result===void 0&&(this._parent._result=R)},enumerable:!1,configurable:!0}),M.prototype.catch=function(R){return this.then(void 0,R)},M.prototype.then=function(R,x){var m=this,c=new M;return c._onFulfilled=R,c._onRejected=x,this._children.push(c),c._parent=this,this._state!==U.Pending&&setTimeout(function(){if(m._state===U.Fulfilled||m._rejectWasConsumed){var T=c._resolve(m._result);if(T!=null)if(T._state!==void 0){var A=T;c._children.push(A),A._parent=c,c=A}else c._result=T}else c._reject(m._reason)}),c},M.prototype._moveChildren=function(R){var x,m=this;if((x=this._children).push.apply(x,R.splice(0,R.length)),this._children.forEach(function(g){g._parent=m}),this._state===U.Fulfilled)for(var c=0,T=this._children;c<T.length;c++)T[c]._resolve(this._result);else if(this._state===U.Rejected)for(var A=0,S=this._children;A<S.length;A++)S[A]._reject(this._reason)},M.prototype._resolve=function(R){try{this._state=U.Fulfilled;var x=null;if(this._onFulfilled&&(x=this._onFulfilled(R)),x!=null)if(x._state!==void 0){var m=x;m._parent=this,m._moveChildren(this._children),R=m._result}else R=x;this._result=R;for(var c=0,T=this._children;c<T.length;c++)T[c]._resolve(R);this._children.length=0,delete this._onFulfilled,delete this._onRejected}catch(A){this._reject(A,!0)}},M.prototype._reject=function(R,x){if(x===void 0&&(x=!1),this._state=U.Rejected,this._reason=R,this._onRejected&&!x)try{this._onRejected(R),this._rejectWasConsumed=!0}catch(A){R=A}for(var m=0,c=this._children;m<c.length;m++){var T=c[m];this._rejectWasConsumed?T._resolve(null):T._reject(R)}this._children.length=0,delete this._onFulfilled,delete this._onRejected},M.resolve=function(R){var x=new M;return x._resolve(R),x},M._RegisterForFulfillment=function(R,x,m){R.then(function(c){return x.results[m]=c,x.count++,x.count===x.target&&x.rootPromise._resolve(x.results),null},function(c){x.rootPromise._state!==U.Rejected&&x.rootPromise._reject(c)})},M.all=function(R){var x=new M,m=new _;if(m.target=R.length,m.rootPromise=x,R.length)for(var c=0;c<R.length;c++)M._RegisterForFulfillment(R[c],m,c);else x._resolve([]);return x},M.race=function(R){var x=new M;if(R.length)for(var m=0,c=R;m<c.length;m++)c[m].then(function(T){return x&&(x._resolve(T),x=null),null},function(T){x&&(x._reject(T),x=null)});return x},M}(),u=function(){function M(){}return M.Apply=function(R){R===void 0&&(R=!1),(R||typeof Promise>"u")&&(window.Promise=C)},M}()},function(Me,y,f){f.d(y,"a",function(){return _}),f.d(y,"b",function(){return C});var U=f(57),_=function(){function u(M){M===void 0&&(M=30),this._enabled=!0,this._rollingFrameTime=new C(M)}return u.prototype.sampleFrame=function(M){if(M===void 0&&(M=U.a.Now),this._enabled){if(this._lastFrameTimeMs!=null){var R=M-this._lastFrameTimeMs;this._rollingFrameTime.add(R)}this._lastFrameTimeMs=M}},Object.defineProperty(u.prototype,"averageFrameTime",{get:function(){return this._rollingFrameTime.average},enumerable:!1,configurable:!0}),Object.defineProperty(u.prototype,"averageFrameTimeVariance",{get:function(){return this._rollingFrameTime.variance},enumerable:!1,configurable:!0}),Object.defineProperty(u.prototype,"instantaneousFrameTime",{get:function(){return this._rollingFrameTime.history(0)},enumerable:!1,configurable:!0}),Object.defineProperty(u.prototype,"averageFPS",{get:function(){return 1e3/this._rollingFrameTime.average},enumerable:!1,configurable:!0}),Object.defineProperty(u.prototype,"instantaneousFPS",{get:function(){var M=this._rollingFrameTime.history(0);return M===0?0:1e3/M},enumerable:!1,configurable:!0}),Object.defineProperty(u.prototype,"isSaturated",{get:function(){return this._rollingFrameTime.isSaturated()},enumerable:!1,configurable:!0}),u.prototype.enable=function(){this._enabled=!0},u.prototype.disable=function(){this._enabled=!1,this._lastFrameTimeMs=null},Object.defineProperty(u.prototype,"isEnabled",{get:function(){return this._enabled},enumerable:!1,configurable:!0}),u.prototype.reset=function(){this._lastFrameTimeMs=null,this._rollingFrameTime.reset()},u}(),C=function(){function u(M){this._samples=new Array(M),this.reset()}return u.prototype.add=function(M){var R;if(this.isSaturated()){var x=this._samples[this._pos];R=x-this.average,this.average-=R/(this._sampleCount-1),this._m2-=R*(x-this.average)}else 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U.e(0,0,0),this._collisionResponse=!0}},function(Me,y,f){f.d(y,"a",function(){return u});var U=f(33),_=f(0),C=f(2),u=function(){function M(R,x,m,c,T){m===void 0&&(m=null),c===void 0&&(c=null),T===void 0&&(T=null),this.index=R,this._opaqueSubMeshes=new U.a(256),this._transparentSubMeshes=new U.a(256),this._alphaTestSubMeshes=new U.a(256),this._depthOnlySubMeshes=new U.a(256),this._particleSystems=new U.a(256),this._spriteManagers=new U.a(256),this._edgesRenderers=new U.b(16),this._scene=x,this.opaqueSortCompareFn=m,this.alphaTestSortCompareFn=c,this.transparentSortCompareFn=T}return Object.defineProperty(M.prototype,"opaqueSortCompareFn",{set:function(R){this._opaqueSortCompareFn=R,this._renderOpaque=R?this.renderOpaqueSorted:M.renderUnsorted},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"alphaTestSortCompareFn",{set:function(R){this._alphaTestSortCompareFn=R,this._renderAlphaTest=R?this.renderAlphaTestSorted:M.renderUnsorted},enumerable:!1,configurable:!0}),Object.defineProperty(M.prototype,"transparentSortCompareFn",{set:function(R){this._transparentSortCompareFn=R||M.defaultTransparentSortCompare,this._renderTransparent=this.renderTransparentSorted},enumerable:!1,configurable:!0}),M.prototype.render=function(R,x,m,c){if(R)R(this._opaqueSubMeshes,this._alphaTestSubMeshes,this._transparentSubMeshes,this._depthOnlySubMeshes);else{var T=this._scene.getEngine();this._depthOnlySubMeshes.length!==0&&(T.setColorWrite(!1),this._renderAlphaTest(this._depthOnlySubMeshes),T.setColorWrite(!0)),this._opaqueSubMeshes.length!==0&&this._renderOpaque(this._opaqueSubMeshes),this._alphaTestSubMeshes.length!==0&&this._renderAlphaTest(this._alphaTestSubMeshes);var A=T.getStencilBuffer();if(T.setStencilBuffer(!1),x&&this._renderSprites(),m&&this._renderParticles(c),this.onBeforeTransparentRendering&&this.onBeforeTransparentRendering(),this._transparentSubMeshes.length!==0&&(T.setStencilBuffer(A),this._renderTransparent(this._transparentSubMeshes),T.setAlphaMode(C.a.ALPHA_DISABLE)),T.setStencilBuffer(!1),this._edgesRenderers.length){for(var S=0;S<this._edgesRenderers.length;S++)this._edgesRenderers.data[S].render();T.setAlphaMode(C.a.ALPHA_DISABLE)}T.setStencilBuffer(A)}},M.prototype.renderOpaqueSorted=function(R){return M.renderSorted(R,this._opaqueSortCompareFn,this._scene.activeCamera,!1)},M.prototype.renderAlphaTestSorted=function(R){return M.renderSorted(R,this._alphaTestSortCompareFn,this._scene.activeCamera,!1)},M.prototype.renderTransparentSorted=function(R){return M.renderSorted(R,this._transparentSortCompareFn,this._scene.activeCamera,!0)},M.renderSorted=function(R,x,m,c){for(var T,A=0,S=m?m.globalPosition:M._zeroVector;A<R.length;A++)(T=R.data[A])._alphaIndex=T.getMesh().alphaIndex,T._distanceToCamera=_.e.Distance(T.getBoundingInfo().boundingSphere.centerWorld,S);var g=R.data.slice(0,R.length);for(x&&g.sort(x),A=0;A<g.length;A++){if(T=g[A],c){var l=T.getMaterial();if(l&&l.needDepthPrePass){var h=l.getScene().getEngine();h.setColorWrite(!1),h.setAlphaMode(C.a.ALPHA_DISABLE),T.render(!1),h.setColorWrite(!0)}}T.render(c)}},M.renderUnsorted=function(R){for(var x=0;x<R.length;x++)R.data[x].render(!1)},M.defaultTransparentSortCompare=function(R,x){return 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m=C.getSize(),c=m.width,T=m.height;if(x instanceof Float32Array){for(var A=x.byteLength/x.BYTES_PER_ELEMENT,S=new Uint8Array(A);--A>=0;){var g=x[A];g<0?g=0:g>1&&(g=1),S[A]=255*g}x=S}var l=document.createElement("canvas");l.width=c,l.height=T;var h=l.getContext("2d");if(!h)return null;var v=h.createImageData(c,T);if(v.data.set(x),h.putImageData(v,0,0),R.invertY){var E=document.createElement("canvas");E.width=c,E.height=T;var D=E.getContext("2d");return D?(D.translate(0,T),D.scale(1,-1),D.drawImage(l,0,0),E.toDataURL("image/png")):null}return l.toDataURL("image/png")},_}()},function(Me,y,f){f.d(y,"a",function(){return A});var U=f(1),_=f(0),C=f(8),u=f(31),M=f(7),R=f(41),x=f(46),m=f(4),c=f(43),T=f(12);M.a._instancedMeshFactory=function(S,g){var l=new A(S,g);if(g.instancedBuffers)for(var h in l.instancedBuffers={},g.instancedBuffers)l.instancedBuffers[h]=g.instancedBuffers[h];return l};var A=function(S){function g(l,h){var v=S.call(this,l,h.getScene())||this;v._indexInSourceMeshInstanceArray=-1,h.addInstance(v),v._sourceMesh=h,v._unIndexed=h._unIndexed,v.position.copyFrom(h.position),v.rotation.copyFrom(h.rotation),v.scaling.copyFrom(h.scaling),h.rotationQuaternion&&(v.rotationQuaternion=h.rotationQuaternion.clone()),v.animations=T.b.Slice(h.animations);for(var E=0,D=h.getAnimationRanges();E<D.length;E++){var w=D[E];w!=null&&v.createAnimationRange(w.name,w.from,w.to)}return v.infiniteDistance=h.infiniteDistance,v.setPivotMatrix(h.getPivotMatrix()),v.refreshBoundingInfo(),v._syncSubMeshes(),v}return Object(U.d)(g,S),g.prototype.getClassName=function(){return"InstancedMesh"},Object.defineProperty(g.prototype,"lightSources",{get:function(){return this._sourceMesh._lightSources},enumerable:!1,configurable:!0}),g.prototype._resyncLightSources=function(){},g.prototype._resyncLightSource=function(l){},g.prototype._removeLightSource=function(l,h){},Object.defineProperty(g.prototype,"receiveShadows",{get:function(){return this._sourceMesh.receiveShadows},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"material",{get:function(){return this._sourceMesh.material},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"visibility",{get:function(){return this._sourceMesh.visibility},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"skeleton",{get:function(){return this._sourceMesh.skeleton},enumerable:!1,configurable:!0}),Object.defineProperty(g.prototype,"renderingGroupId",{get:function(){return this._sourceMesh.renderingGroupId},set:function(l){this._sourceMesh&&l!==this._sourceMesh.renderingGroupId&&C.a.Warn("Note - setting renderingGroupId of an instanced mesh has no effect on the 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0&&(h=null),this.sourceMesh&&this.sourceMesh.setIndices(l,h),this.sourceMesh},g.prototype.isVerticesDataPresent=function(l){return this._sourceMesh.isVerticesDataPresent(l)},g.prototype.getIndices=function(){return this._sourceMesh.getIndices()},Object.defineProperty(g.prototype,"_positions",{get:function(){return this._sourceMesh._positions},enumerable:!1,configurable:!0}),g.prototype.refreshBoundingInfo=function(l){if(l===void 0&&(l=!1),this._boundingInfo&&this._boundingInfo.isLocked)return this;var h=this._sourceMesh.geometry?this._sourceMesh.geometry.boundingBias:null;return this._refreshBoundingInfo(this._sourceMesh._getPositionData(l),h),this},g.prototype._preActivate=function(){return this._currentLOD&&this._currentLOD._preActivate(),this},g.prototype._activate=function(l,h){if(this._sourceMesh.subMeshes||C.a.Warn("Instances should only be created for meshes with geometry."),this._currentLOD){if(this._currentLOD._getWorldMatrixDeterminant()>0!=this._getWorldMatrixDeterminant()>0)return this._internalAbstractMeshDataInfo._actAsRegularMesh=!0,!0;if(this._internalAbstractMeshDataInfo._actAsRegularMesh=!1,this._currentLOD._registerInstanceForRenderId(this,l),h){if(!this._currentLOD._internalAbstractMeshDataInfo._isActiveIntermediate)return this._currentLOD._internalAbstractMeshDataInfo._onlyForInstancesIntermediate=!0,!0}else if(!this._currentLOD._internalAbstractMeshDataInfo._isActive)return this._currentLOD._internalAbstractMeshDataInfo._onlyForInstances=!0,!0}return!1},g.prototype._postActivate=function(){this._sourceMesh.edgesShareWithInstances&&this._sourceMesh._edgesRenderer&&this._sourceMesh._edgesRenderer.isEnabled&&this._sourceMesh._renderingGroup?(this._sourceMesh._renderingGroup._edgesRenderers.pushNoDuplicate(this._sourceMesh._edgesRenderer),this._sourceMesh._edgesRenderer.customInstances.push(this.getWorldMatrix())):this._edgesRenderer&&this._edgesRenderer.isEnabled&&this._sourceMesh._renderingGroup&&this._sourceMesh._renderingGroup._edgesRenderers.push(this._edgesRenderer)},g.prototype.getWorldMatrix=function(){if(this._currentLOD&&this._currentLOD.billboardMode!==x.a.BILLBOARDMODE_NONE&&this._currentLOD._masterMesh!==this){var l=this._currentLOD._masterMesh;return this._currentLOD._masterMesh=this,_.c.Vector3[7].copyFrom(this._currentLOD.position),this._currentLOD.position.set(0,0,0),_.c.Matrix[0].copyFrom(this._currentLOD.computeWorldMatrix(!0)),this._currentLOD.position.copyFrom(_.c.Vector3[7]),this._currentLOD._masterMesh=l,_.c.Matrix[0]}return S.prototype.getWorldMatrix.call(this)},Object.defineProperty(g.prototype,"isAnInstance",{get:function(){return!0},enumerable:!1,configurable:!0}),g.prototype.getLOD=function(l){if(!l)return this;var h=this.getBoundingInfo();return this._currentLOD=this.sourceMesh.getLOD(l,h.boundingSphere),this._currentLOD===this.sourceMesh?this.sourceMesh:this._currentLOD},g.prototype._preActivateForIntermediateRendering=function(l){return this.sourceMesh._preActivateForIntermediateRendering(l)},g.prototype._syncSubMeshes=function(){if(this.releaseSubMeshes(),this._sourceMesh.subMeshes)for(var l=0;l<this._sourceMesh.subMeshes.length;l++)this._sourceMesh.subMeshes[l].clone(this,this._sourceMesh);return this},g.prototype._generatePointsArray=function(){return this._sourceMesh._generatePointsArray()},g.prototype._updateBoundingInfo=function(){return this._boundingInfo?this._boundingInfo.update(this.worldMatrixFromCache):this._boundingInfo=new c.a(this.absolutePosition,this.absolutePosition,this.worldMatrixFromCache),this._updateSubMeshesBoundingInfo(this.worldMatrixFromCache),this},g.prototype.clone=function(l,h,v){h===void 0&&(h=null);var E=this._sourceMesh.createInstance(l);if(R.a.DeepCopy(this,E,["name","subMeshes","uniqueId","parent","lightSources","receiveShadows","material","visibility","skeleton","sourceMesh","isAnInstance","facetNb","isFacetDataEnabled","isBlocked","useBones","hasInstances","collider","edgesRenderer","forward","up","right","absolutePosition","absoluteScaling","absoluteRotationQuaternion","isWorldMatrixFrozen","nonUniformScaling","behaviors","worldMatrixFromCache","hasThinInstances"],[]),this.refreshBoundingInfo(),h&&(E.parent=h),!v)for(var D=0;D<this.getScene().meshes.length;D++){var w=this.getScene().meshes[D];w.parent===this&&w.clone(w.name,E)}return E.computeWorldMatrix(!0),E},g.prototype.dispose=function(l,h){h===void 0&&(h=!1),this._sourceMesh.removeInstance(this),S.prototype.dispose.call(this,l,h)},g}(u.a);M.a.prototype.edgesShareWithInstances=!1,M.a.prototype.registerInstancedBuffer=function(S,g){if(this.removeVerticesData(S),!this.instancedBuffers){this.instancedBuffers={};for(var l=0,h=this.instances;l<h.length;l++)h[l].instancedBuffers={};this._userInstancedBuffersStorage={data:{},vertexBuffers:{},strides:{},sizes:{}}}this.instancedBuffers[S]=null,this._userInstancedBuffersStorage.strides[S]=g,this._userInstancedBuffersStorage.sizes[S]=32*g,this._userInstancedBuffersStorage.data[S]=new Float32Array(this._userInstancedBuffersStorage.sizes[S]),this._userInstancedBuffersStorage.vertexBuffers[S]=new 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-{
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-vec3 specular;
-#endif
-#ifdef NDOTL
-float ndl;
-#endif
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-{
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-#ifdef NDOTL
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R(x){this._completePromises=new Array,this._forAssetContainer=!1,this._babylonLights=[],this._disableInstancedMesh=0,this._disposed=!1,this._state=null,this._extensions=new Array,this._defaultBabylonMaterialData={},this._parent=x}return R.RegisterExtension=function(x,m){R.UnregisterExtension(x)&&_.Logger.Warn("Extension with the name '"+x+"' already exists"),R._RegisteredExtensions[x]={factory:m}},R.UnregisterExtension=function(x){return!!R._RegisteredExtensions[x]&&(delete R._RegisteredExtensions[x],!0)},Object.defineProperty(R.prototype,"state",{get:function(){return this._state},enumerable:!1,configurable:!0}),Object.defineProperty(R.prototype,"gltf",{get:function(){return this._gltf},enumerable:!1,configurable:!0}),Object.defineProperty(R.prototype,"bin",{get:function(){return this._bin},enumerable:!1,configurable:!0}),Object.defineProperty(R.prototype,"parent",{get:function(){return this._parent},enumerable:!1,configurable:!0}),Object.defineProperty(R.prototype,"babylonScene",{get:function(){return this._babylonScene},enumerable:!1,configurable:!0}),Object.defineProperty(R.prototype,"rootBabylonMesh",{get:function(){return this._rootBabylonMesh},enumerable:!1,configurable:!0}),R.prototype.dispose=function(){if(!this._disposed){for(var x in this._disposed=!0,this._completePromises.length=0,this._extensions){var m=this._extensions[x];m.dispose&&m.dispose(),delete this._extensions[x]}this._gltf=null,this._babylonScene=null,this._rootBabylonMesh=null,this._parent.dispose()}},R.prototype.importMeshAsync=function(x,m,c,T,A,S,g){var l=this;return Promise.resolve().then(function(){l._babylonScene=m,l._rootUrl=A,l._fileName=g||"scene",l._forAssetContainer=c,l._loadData(T);var h=null;if(x){var v={};if(l._gltf.nodes)for(var E=0,D=l._gltf.nodes;E<D.length;E++){var w=D[E];w.name&&(v[w.name]=w.index)}h=(x instanceof Array?x:[x]).map(function(N){var I=v[N];if(I===void 0)throw new Error("Failed to find node '"+N+"'");return I})}return l._loadAsync(h,function(){return{meshes:l._getMeshes(),particleSystems:[],skeletons:l._getSkeletons(),animationGroups:l._getAnimationGroups(),lights:l._babylonLights,transformNodes:l._getTransformNodes(),geometries:l._getGeometries()}})})},R.prototype.loadAsync=function(x,m,c,T,A){var S=this;return Promise.resolve().then(function(){return S._babylonScene=x,S._rootUrl=c,S._fileName=A||"scene",S._loadData(m),S._loadAsync(null,function(){})})},R.prototype._loadAsync=function(x,m){var c=this;return Promise.resolve().then(function(){c._uniqueRootUrl=c._rootUrl.indexOf("file:")===-1&&c._fileName?c._rootUrl:""+c._rootUrl+Date.now()+"/",c._loadExtensions(),c._checkExtensions();var T=C.GLTFLoaderState[C.GLTFLoaderState.LOADING]+" => "+C.GLTFLoaderState[C.GLTFLoaderState.READY],A=C.GLTFLoaderState[C.GLTFLoaderState.LOADING]+" => "+C.GLTFLoaderState[C.GLTFLoaderState.COMPLETE];c._parent._startPerformanceCounter(T),c._parent._startPerformanceCounter(A),c._setState(C.GLTFLoaderState.LOADING),c._extensionsOnLoading();var S=new Array,g=c._babylonScene.blockMaterialDirtyMechanism;if(c._babylonScene.blockMaterialDirtyMechanism=!0,x)S.push(c.loadSceneAsync("/nodes",{nodes:x,index:-1}));else if(c._gltf.scene!=null||c._gltf.scenes&&c._gltf.scenes[0]){var l=u.Get("/scene",c._gltf.scenes,c._gltf.scene||0);S.push(c.loadSceneAsync("/scenes/"+l.index,l))}if(c.parent.loadAllMaterials&&c._gltf.materials)for(var h=0;h<c._gltf.materials.length;++h){var v=c._gltf.materials[h],E="/materials/"+h,D=_.Material.TriangleFillMode;S.push(c._loadMaterialAsync(E,v,null,D,function(N){}))}c._babylonScene.blockMaterialDirtyMechanism=g,c._parent.compileMaterials&&S.push(c._compileMaterialsAsync()),c._parent.compileShadowGenerators&&S.push(c._compileShadowGeneratorsAsync());var w=Promise.all(S).then(function(){return c._rootBabylonMesh&&c._rootBabylonMesh.setEnabled(!0),c._extensionsOnReady(),c._setState(C.GLTFLoaderState.READY),c._startAnimations(),m()});return w.then(function(){c._parent._endPerformanceCounter(T),_.Tools.SetImmediate(function(){c._disposed||Promise.all(c._completePromises).then(function(){c._parent._endPerformanceCounter(A),c._setState(C.GLTFLoaderState.COMPLETE),c._parent.onCompleteObservable.notifyObservers(void 0),c._parent.onCompleteObservable.clear(),c.dispose()},function(N){c._parent.onErrorObservable.notifyObservers(N),c._parent.onErrorObservable.clear(),c.dispose()})})}),w}).catch(function(T){throw c._disposed||(c._parent.onErrorObservable.notifyObservers(T),c._parent.onErrorObservable.clear(),c.dispose()),T})},R.prototype._loadData=function(x){if(this._gltf=x.json,this._setupData(),x.bin){var m=this._gltf.buffers;if(m&&m[0]&&!m[0].uri){var c=m[0];(c.byteLength<x.bin.byteLength-3||c.byteLength>x.bin.byteLength)&&_.Logger.Warn("Binary buffer length ("+c.byteLength+") from JSON does not match chunk length ("+x.bin.byteLength+")"),this._bin=x.bin}else _.Logger.Warn("Unexpected BIN chunk")}},R.prototype._setupData=function(){if(u.Assign(this._gltf.accessors),u.Assign(this._gltf.animations),u.Assign(this._gltf.buffers),u.Assign(this._gltf.bufferViews),u.Assign(this._gltf.cameras),u.Assign(this._gltf.images),u.Assign(this._gltf.materials),u.Assign(this._gltf.meshes),u.Assign(this._gltf.nodes),u.Assign(this._gltf.samplers),u.Assign(this._gltf.scenes),u.Assign(this._gltf.skins),u.Assign(this._gltf.textures),this._gltf.nodes){for(var x={},m=0,c=this._gltf.nodes;m<c.length;m++)if((h=c[m]).children)for(var T=0,A=h.children;T<A.length;T++)x[A[T]]=h.index;for(var S=this._createRootNode(),g=0,l=this._gltf.nodes;g<l.length;g++){var h,v=x[(h=l[g]).index];h.parent=v===void 0?S:this._gltf.nodes[v]}}},R.prototype._loadExtensions=function(){for(var x in R._RegisteredExtensions){var m=R._RegisteredExtensions[x].factory(this);m.name!==x&&_.Logger.Warn("The name of the glTF loader extension instance does not match the registered name: "+m.name+" !== "+x),this._extensions.push(m),this._parent.onExtensionLoadedObservable.notifyObservers(m)}this._extensions.sort(function(c,T){return(c.order||Number.MAX_VALUE)-(T.order||Number.MAX_VALUE)}),this._parent.onExtensionLoadedObservable.clear()},R.prototype._checkExtensions=function(){if(this._gltf.extensionsRequired)for(var x=function(A){if(!m._extensions.some(function(S){return S.name===A&&S.enabled}))throw new Error("Require extension "+A+" is not available")},m=this,c=0,T=this._gltf.extensionsRequired;c<T.length;c++)x(T[c])},R.prototype._setState=function(x){this._state=x,this.log(C.GLTFLoaderState[this._state])},R.prototype._createRootNode=function(){this._babylonScene._blockEntityCollection=this._forAssetContainer,this._rootBabylonMesh=new _.Mesh("__root__",this._babylonScene),this._babylonScene._blockEntityCollection=!1,this._rootBabylonMesh.setEnabled(!1);var x={_babylonTransformNode:this._rootBabylonMesh,index:-1};switch(this._parent.coordinateSystemMode){case C.GLTFLoaderCoordinateSystemMode.AUTO:this._babylonScene.useRightHandedSystem||(x.rotation=[0,1,0,0],x.scale=[1,1,-1],R._LoadTransform(x,this._rootBabylonMesh));break;case C.GLTFLoaderCoordinateSystemMode.FORCE_RIGHT_HANDED:this._babylonScene.useRightHandedSystem=!0;break;default:throw new Error("Invalid coordinate system mode ("+this._parent.coordinateSystemMode+")")}return this._parent.onMeshLoadedObservable.notifyObservers(this._rootBabylonMesh),x},R.prototype.loadSceneAsync=function(x,m){var c=this,T=this._extensionsLoadSceneAsync(x,m);if(T)return T;var A=new Array;if(this.logOpen(x+" "+(m.name||"")),m.nodes)for(var S=0,g=m.nodes;S<g.length;S++){var l=g[S],h=u.Get(x+"/nodes/"+l,this._gltf.nodes,l);A.push(this.loadNodeAsync("/nodes/"+h.index,h,function(N){N.parent=c._rootBabylonMesh}))}if(this._gltf.nodes){for(var v=0,E=this._gltf.nodes;v<E.length;v++)if((h=E[v])._babylonTransformNode&&h._babylonBones)for(var D=0,w=h._babylonBones;D<w.length;D++)w[D].linkTransformNode(h._babylonTransformNode)}return A.push(this._loadAnimationsAsync()),this.logClose(),Promise.all(A).then(function(){})},R.prototype._forEachPrimitive=function(x,m){if(x._primitiveBabylonMeshes)for(var c=0,T=x._primitiveBabylonMeshes;c<T.length;c++)m(T[c])},R.prototype._getGeometries=function(){var x=new Array,m=this._gltf.nodes;if(m)for(var c=0,T=m;c<T.length;c++){var A=T[c];this._forEachPrimitive(A,function(S){var g=S.geometry;g&&x.indexOf(g)===-1&&x.push(g)})}return x},R.prototype._getMeshes=function(){var x=new Array;x.push(this._rootBabylonMesh);var m=this._gltf.nodes;if(m)for(var c=0,T=m;c<T.length;c++){var A=T[c];this._forEachPrimitive(A,function(S){x.push(S)})}return x},R.prototype._getTransformNodes=function(){var x=new Array,m=this._gltf.nodes;if(m)for(var c=0,T=m;c<T.length;c++){var A=T[c];A._babylonTransformNode&&A._babylonTransformNode.getClassName()==="TransformNode"&&x.push(A._babylonTransformNode)}return x},R.prototype._getSkeletons=function(){var x=new Array,m=this._gltf.skins;if(m)for(var c=0,T=m;c<T.length;c++){var A=T[c];A._data&&x.push(A._data.babylonSkeleton)}return x},R.prototype._getAnimationGroups=function(){var x=new Array,m=this._gltf.animations;if(m)for(var c=0,T=m;c<T.length;c++){var A=T[c];A._babylonAnimationGroup&&x.push(A._babylonAnimationGroup)}return x},R.prototype._startAnimations=function(){switch(this._parent.animationStartMode){case C.GLTFLoaderAnimationStartMode.NONE:break;case C.GLTFLoaderAnimationStartMode.FIRST:(x=this._getAnimationGroups()).length!==0&&x[0].start(!0);break;case C.GLTFLoaderAnimationStartMode.ALL:for(var x,m=0,c=x=this._getAnimationGroups();m<c.length;m++)c[m].start(!0);break;default:return void _.Logger.Error("Invalid animation start mode ("+this._parent.animationStartMode+")")}},R.prototype.loadNodeAsync=function(x,m,c){var T=this;c===void 0&&(c=function(){});var A=this._extensionsLoadNodeAsync(x,m,c);if(A)return A;if(m._babylonTransformNode)throw new Error(x+": Invalid recursive node hierarchy");var S=new Array;this.logOpen(x+" "+(m.name||""));var g=function(v){if(R.AddPointerMetadata(v,x),R._LoadTransform(m,v),m.camera!=null){var E=u.Get(x+"/camera",T._gltf.cameras,m.camera);S.push(T.loadCameraAsync("/cameras/"+E.index,E,function(V){V.parent=v}))}if(m.children)for(var D=0,w=m.children;D<w.length;D++){var N=w[D],I=u.Get(x+"/children/"+N,T._gltf.nodes,N);S.push(T.loadNodeAsync("/nodes/"+I.index,I,function(V){V.parent=v}))}c(v)};if(m.mesh==null){var l=m.name||"node"+m.index;this._babylonScene._blockEntityCollection=this._forAssetContainer,m._babylonTransformNode=new _.TransformNode(l,this._babylonScene),this._babylonScene._blockEntityCollection=!1,g(m._babylonTransformNode)}else{var h=u.Get(x+"/mesh",this._gltf.meshes,m.mesh);S.push(this._loadMeshAsync("/meshes/"+h.index,m,h,g))}return this.logClose(),Promise.all(S).then(function(){return T._forEachPrimitive(m,function(v){v.geometry&&v.geometry.useBoundingInfoFromGeometry?v._updateBoundingInfo():v.refreshBoundingInfo(!0)}),m._babylonTransformNode})},R.prototype._loadMeshAsync=function(x,m,c,T){var A=c.primitives;if(!A||!A.length)throw new Error(x+": Primitives are missing");A[0].index==null&&u.Assign(A);var S=new Array;this.logOpen(x+" "+(c.name||""));var g=m.name||"node"+m.index;if(A.length===1){var l=c.primitives[0];S.push(this._loadMeshPrimitiveAsync(x+"/primitives/"+l.index,g,m,c,l,function(D){m._babylonTransformNode=D,m._primitiveBabylonMeshes=[D]}))}else{this._babylonScene._blockEntityCollection=this._forAssetContainer,m._babylonTransformNode=new _.TransformNode(g,this._babylonScene),this._babylonScene._blockEntityCollection=!1,m._primitiveBabylonMeshes=[];for(var h=0,v=A;h<v.length;h++)l=v[h],S.push(this._loadMeshPrimitiveAsync(x+"/primitives/"+l.index,g+"_primitive"+l.index,m,c,l,function(D){D.parent=m._babylonTransformNode,m._primitiveBabylonMeshes.push(D)}))}if(m.skin!=null){var E=u.Get(x+"/skin",this._gltf.skins,m.skin);S.push(this._loadSkinAsync("/skins/"+E.index,m,E))}return T(m._babylonTransformNode),this.logClose(),Promise.all(S).then(function(){return m._babylonTransformNode})},R.prototype._loadMeshPrimitiveAsync=function(x,m,c,T,A,S){var g=this,l=this._extensionsLoadMeshPrimitiveAsync(x,m,c,T,A,S);if(l)return l;this.logOpen(""+x);var h,v,E=this._disableInstancedMesh===0&&this._parent.createInstances&&c.skin==null&&!T.primitives[0].targets;if(E&&A._instanceData)h=A._instanceData.babylonSourceMesh.createInstance(m),v=A._instanceData.promise;else{var D=new Array;this._babylonScene._blockEntityCollection=this._forAssetContainer;var w=new _.Mesh(m,this._babylonScene);this._babylonScene._blockEntityCollection=!1,w.overrideMaterialSideOrientation=this._babylonScene.useRightHandedSystem?_.Material.CounterClockWiseSideOrientation:_.Material.ClockWiseSideOrientation,this._createMorphTargets(x,c,T,A,w),D.push(this._loadVertexDataAsync(x,A,w).then(function(X){return g._loadMorphTargetsAsync(x,A,w,X).then(function(){g._babylonScene._blockEntityCollection=g._forAssetContainer,X.applyToMesh(w),g._babylonScene._blockEntityCollection=!1})}));var N=R._GetDrawMode(x,A.mode);if(A.material==null){var I=this._defaultBabylonMaterialData[N];I||(I=this._createDefaultMaterial("__GLTFLoader._default",N),this._parent.onMaterialLoadedObservable.notifyObservers(I),this._defaultBabylonMaterialData[N]=I),w.material=I}else{var V=u.Get(x+"/material",this._gltf.materials,A.material);D.push(this._loadMaterialAsync("/materials/"+V.index,V,w,N,function(X){w.material=X}))}v=Promise.all(D),E&&(A._instanceData={babylonSourceMesh:w,promise:v}),h=w}return R.AddPointerMetadata(h,x),this._parent.onMeshLoadedObservable.notifyObservers(h),S(h),this.logClose(),v.then(function(){return h})},R.prototype._loadVertexDataAsync=function(x,m,c){var T=this,A=this._extensionsLoadVertexDataAsync(x,m,c);if(A)return A;var S=m.attributes;if(!S)throw new Error(x+": Attributes are missing");var g=new Array,l=new _.Geometry(c.name,this._babylonScene);if(m.indices==null)c.isUnIndexed=!0;else{var h=u.Get(x+"/indices",this._gltf.accessors,m.indices);g.push(this._loadIndicesAccessorAsync("/accessors/"+h.index,h).then(function(E){l.setIndices(E)}))}var v=function(E,D,w){if(S[E]!=null){c._delayInfo=c._delayInfo||[],c._delayInfo.indexOf(D)===-1&&c._delayInfo.push(D);var N=u.Get(x+"/attributes/"+E,T._gltf.accessors,S[E]);g.push(T._loadVertexAccessorAsync("/accessors/"+N.index,N,D).then(function(I){if(I.getKind()===_.VertexBuffer.PositionKind&&!T.parent.alwaysComputeBoundingBox&&!c.skeleton){var V=N.min,X=N.max;if(V!==void 0&&X!==void 0){var j=_.TmpVectors.Vector3[0],ne=_.TmpVectors.Vector3[1];j.copyFromFloats.apply(j,V),ne.copyFromFloats.apply(ne,X),l._boundingInfo=new _.BoundingInfo(j,ne),l.useBoundingInfoFromGeometry=!0}}l.setVerticesBuffer(I,N.count)})),D==_.VertexBuffer.MatricesIndicesExtraKind&&(c.numBoneInfluencers=8),w&&w(N)}};return v("POSITION",_.VertexBuffer.PositionKind),v("NORMAL",_.VertexBuffer.NormalKind),v("TANGENT",_.VertexBuffer.TangentKind),v("TEXCOORD_0",_.VertexBuffer.UVKind),v("TEXCOORD_1",_.VertexBuffer.UV2Kind),v("JOINTS_0",_.VertexBuffer.MatricesIndicesKind),v("WEIGHTS_0",_.VertexBuffer.MatricesWeightsKind),v("JOINTS_1",_.VertexBuffer.MatricesIndicesExtraKind),v("WEIGHTS_1",_.VertexBuffer.MatricesWeightsExtraKind),v("COLOR_0",_.VertexBuffer.ColorKind,function(E){E.type==="VEC4"&&(c.hasVertexAlpha=!0)}),Promise.all(g).then(function(){return l})},R.prototype._createMorphTargets=function(x,m,c,T,A){if(T.targets){if(m._numMorphTargets==null)m._numMorphTargets=T.targets.length;else if(T.targets.length!==m._numMorphTargets)throw new Error(x+": Primitives do not have the same number of targets");var S=c.extras?c.extras.targetNames:null;A.morphTargetManager=new _.MorphTargetManager(A.getScene());for(var g=0;g<T.targets.length;g++){var l=m.weights?m.weights[g]:c.weights?c.weights[g]:0,h=S?S[g]:"morphTarget"+g;A.morphTargetManager.addTarget(new _.MorphTarget(h,l,A.getScene()))}}},R.prototype._loadMorphTargetsAsync=function(x,m,c,T){if(!m.targets)return Promise.resolve();for(var A=new Array,S=c.morphTargetManager,g=0;g<S.numTargets;g++){var l=S.getTarget(g);A.push(this._loadMorphTargetVertexDataAsync(x+"/targets/"+g,T,m.targets[g],l))}return Promise.all(A).then(function(){})},R.prototype._loadMorphTargetVertexDataAsync=function(x,m,c,T){var A=this,S=new Array,g=function(l,h,v){if(c[l]!=null){var E=m.getVertexBuffer(h);if(E){var D=u.Get(x+"/"+l,A._gltf.accessors,c[l]);S.push(A._loadFloatAccessorAsync("/accessors/"+D.index,D).then(function(w){v(E,w)}))}}};return g("POSITION",_.VertexBuffer.PositionKind,function(l,h){var v=new Float32Array(h.length);l.forEach(h.length,function(E,D){v[D]=h[D]+E}),T.setPositions(v)}),g("NORMAL",_.VertexBuffer.NormalKind,function(l,h){var v=new Float32Array(h.length);l.forEach(v.length,function(E,D){v[D]=h[D]+E}),T.setNormals(v)}),g("TANGENT",_.VertexBuffer.TangentKind,function(l,h){var v=new Float32Array(h.length/3*4),E=0;l.forEach(h.length/3*4,function(D,w){(w+1)%4!=0&&(v[E]=h[E]+D,E++)}),T.setTangents(v)}),Promise.all(S).then(function(){})},R._LoadTransform=function(x,m){if(x.skin==null){var c=_.Vector3.Zero(),T=_.Quaternion.Identity(),A=_.Vector3.One();x.matrix?_.Matrix.FromArray(x.matrix).decompose(A,T,c):(x.translation&&(c=_.Vector3.FromArray(x.translation)),x.rotation&&(T=_.Quaternion.FromArray(x.rotation)),x.scale&&(A=_.Vector3.FromArray(x.scale))),m.position=c,m.rotationQuaternion=T,m.scaling=A}},R.prototype._loadSkinAsync=function(x,m,c){var T=this,A=this._extensionsLoadSkinAsync(x,m,c);if(A)return A;var S=function(v){T._forEachPrimitive(m,function(E){E.skeleton=v})};if(c._data)return S(c._data.babylonSkeleton),c._data.promise;var g="skeleton"+c.index;this._babylonScene._blockEntityCollection=this._forAssetContainer;var l=new _.Skeleton(c.name||g,g,this._babylonScene);this._babylonScene._blockEntityCollection=!1,l.overrideMesh=this._rootBabylonMesh,this._loadBones(x,c,l),S(l);var h=this._loadSkinInverseBindMatricesDataAsync(x,c).then(function(v){T._updateBoneMatrices(l,v)});return c._data={babylonSkeleton:l,promise:h},h},R.prototype._loadBones=function(x,m,c){for(var T={},A=0,S=m.joints;A<S.length;A++){var g=S[A],l=u.Get(x+"/joints/"+g,this._gltf.nodes,g);this._loadBone(l,m,c,T)}},R.prototype._loadBone=function(x,m,c,T){var A=T[x.index];if(A)return A;var S=null;x.parent&&x.parent._babylonTransformNode!==this._rootBabylonMesh&&(S=this._loadBone(x.parent,m,c,T));var g=m.joints.indexOf(x.index);return A=new _.Bone(x.name||"joint"+x.index,c,S,this._getNodeMatrix(x),null,null,g),T[x.index]=A,x._babylonBones=x._babylonBones||[],x._babylonBones.push(A),A},R.prototype._loadSkinInverseBindMatricesDataAsync=function(x,m){if(m.inverseBindMatrices==null)return Promise.resolve(null);var c=u.Get(x+"/inverseBindMatrices",this._gltf.accessors,m.inverseBindMatrices);return this._loadFloatAccessorAsync("/accessors/"+c.index,c)},R.prototype._updateBoneMatrices=function(x,m){for(var c=0,T=x.bones;c<T.length;c++){var A=T[c],S=_.Matrix.Identity(),g=A._index;m&&g!==-1&&(_.Matrix.FromArrayToRef(m,16*g,S),S.invertToRef(S));var l=A.getParent();l&&S.multiplyToRef(l.getInvertedAbsoluteTransform(),S),A.setBindPose(S),A.updateMatrix(S,!1,!1),A._updateDifferenceMatrix(void 0,!1)}},R.prototype._getNodeMatrix=function(x){return x.matrix?_.Matrix.FromArray(x.matrix):_.Matrix.Compose(x.scale?_.Vector3.FromArray(x.scale):_.Vector3.One(),x.rotation?_.Quaternion.FromArray(x.rotation):_.Quaternion.Identity(),x.translation?_.Vector3.FromArray(x.translation):_.Vector3.Zero())},R.prototype.loadCameraAsync=function(x,m,c){c===void 0&&(c=function(){});var T=this._extensionsLoadCameraAsync(x,m,c);if(T)return T;var A=new Array;this.logOpen(x+" "+(m.name||"")),this._babylonScene._blockEntityCollection=this._forAssetContainer;var S=new _.FreeCamera(m.name||"camera"+m.index,_.Vector3.Zero(),this._babylonScene,!1);switch(this._babylonScene._blockEntityCollection=!1,S.ignoreParentScaling=!0,S.rotation=new _.Vector3(0,Math.PI,0),m.type){case"perspective":var g=m.perspective;if(!g)throw new Error(x+": Camera perspective properties are missing");S.fov=g.yfov,S.minZ=g.znear,S.maxZ=g.zfar||Number.MAX_VALUE;break;case"orthographic":if(!m.orthographic)throw new Error(x+": Camera orthographic properties are missing");S.mode=_.Camera.ORTHOGRAPHIC_CAMERA,S.orthoLeft=-m.orthographic.xmag,S.orthoRight=m.orthographic.xmag,S.orthoBottom=-m.orthographic.ymag,S.orthoTop=m.orthographic.ymag,S.minZ=m.orthographic.znear,S.maxZ=m.orthographic.zfar;break;default:throw new Error(x+": Invalid camera type ("+m.type+")")}return R.AddPointerMetadata(S,x),this._parent.onCameraLoadedObservable.notifyObservers(S),c(S),this.logClose(),Promise.all(A).then(function(){return S})},R.prototype._loadAnimationsAsync=function(){var x=this._gltf.animations;if(!x)return Promise.resolve();for(var m=new Array,c=0;c<x.length;c++){var T=x[c];m.push(this.loadAnimationAsync("/animations/"+T.index,T))}return Promise.all(m).then(function(){})},R.prototype.loadAnimationAsync=function(x,m){var c=this._extensionsLoadAnimationAsync(x,m);if(c)return c;this._babylonScene._blockEntityCollection=this._forAssetContainer;var T=new _.AnimationGroup(m.name||"animation"+m.index,this._babylonScene);this._babylonScene._blockEntityCollection=!1,m._babylonAnimationGroup=T;var A=new Array;u.Assign(m.channels),u.Assign(m.samplers);for(var S=0,g=m.channels;S<g.length;S++){var l=g[S];A.push(this._loadAnimationChannelAsync(x+"/channels/"+l.index,x,m,l,T))}return Promise.all(A).then(function(){return T.normalize(0),T})},R.prototype._loadAnimationChannelAsync=function(x,m,c,T,A,S){var g=this;if(S===void 0&&(S=null),T.target.node==null)return Promise.resolve();var l=u.Get(x+"/target/node",this._gltf.nodes,T.target.node);if(T.target.path==="weights"&&!l._numMorphTargets||T.target.path!=="weights"&&!l._babylonTransformNode)return Promise.resolve();var h=u.Get(x+"/sampler",c.samplers,T.sampler);return this._loadAnimationSamplerAsync(m+"/samplers/"+T.sampler,h).then(function(v){var E,D;switch(T.target.path){case"translation":E="position",D=_.Animation.ANIMATIONTYPE_VECTOR3;break;case"rotation":E="rotationQuaternion",D=_.Animation.ANIMATIONTYPE_QUATERNION;break;case"scale":E="scaling",D=_.Animation.ANIMATIONTYPE_VECTOR3;break;case"weights":E="influence",D=_.Animation.ANIMATIONTYPE_FLOAT;break;default:throw new Error(x+"/target/path: Invalid value ("+T.target.path+")")}var w,N,I=0;switch(E){case"position":w=function(){var pe=_.Vector3.FromArray(v.output,I);return I+=3,pe};break;case"rotationQuaternion":w=function(){var pe=_.Quaternion.FromArray(v.output,I);return I+=4,pe};break;case"scaling":w=function(){var pe=_.Vector3.FromArray(v.output,I);return I+=3,pe};break;case"influence":w=function(){for(var pe=new Array(l._numMorphTargets),ae=0;ae<l._numMorphTargets;ae++)pe[ae]=v.output[I++];return pe}}switch(v.interpolation){case"STEP":N=function(pe){return{frame:v.input[pe],value:w(),interpolation:_.AnimationKeyInterpolation.STEP}};break;case"LINEAR":N=function(pe){return{frame:v.input[pe],value:w()}};break;case"CUBICSPLINE":N=function(pe){return{frame:v.input[pe],inTangent:w(),value:w(),outTangent:w()}}}for(var V=new Array(v.input.length),X=0;X<v.input.length;X++)V[X]=N(X);if(E==="influence")for(var j=function(pe){var ae=A.name+"_channel"+A.targetedAnimations.length,ee=new _.Animation(ae,E,1,D);ee.setKeys(V.map(function(K){return{frame:K.frame,inTangent:K.inTangent?K.inTangent[pe]:void 0,value:K.value[pe],outTangent:K.outTangent?K.outTangent[pe]:void 0}})),g._forEachPrimitive(l,function(K){var $=K.morphTargetManager.getTarget(pe),L=ee.clone();$.animations.push(L),A.addTargetedAnimation(L,$)})},ne=0;ne<l._numMorphTargets;ne++)j(ne);else{var te=A.name+"_channel"+A.targetedAnimations.length,de=new _.Animation(te,E,1,D);de.setKeys(V),S!=null&&S.animations!=null?(S.animations.push(de),A.addTargetedAnimation(de,S)):(l._babylonTransformNode.animations.push(de),A.addTargetedAnimation(de,l._babylonTransformNode))}})},R.prototype._loadAnimationSamplerAsync=function(x,m){if(m._data)return m._data;var c=m.interpolation||"LINEAR";switch(c){case"STEP":case"LINEAR":case"CUBICSPLINE":break;default:throw new Error(x+"/interpolation: Invalid value ("+m.interpolation+")")}var T=u.Get(x+"/input",this._gltf.accessors,m.input),A=u.Get(x+"/output",this._gltf.accessors,m.output);return m._data=Promise.all([this._loadFloatAccessorAsync("/accessors/"+T.index,T),this._loadFloatAccessorAsync("/accessors/"+A.index,A)]).then(function(S){var g=S[0],l=S[1];return{input:g,interpolation:c,output:l}}),m._data},R.prototype._loadBufferAsync=function(x,m,c,T){var A=this._extensionsLoadBufferAsync(x,m,c,T);if(A)return A;if(!m._data)if(m.uri)m._data=this.loadUriAsync(x+"/uri",m,m.uri);else{if(!this._bin)throw new Error(x+": Uri is missing or the binary glTF is missing its binary chunk");m._data=this._bin.readAsync(0,m.byteLength)}return m._data.then(function(S){try{return new Uint8Array(S.buffer,S.byteOffset+c,T)}catch(g){throw new Error(x+": "+g.message)}})},R.prototype.loadBufferViewAsync=function(x,m){var c=this._extensionsLoadBufferViewAsync(x,m);if(c)return c;if(m._data)return m._data;var T=u.Get(x+"/buffer",this._gltf.buffers,m.buffer);return m._data=this._loadBufferAsync("/buffers/"+T.index,T,m.byteOffset||0,m.byteLength),m._data},R.prototype._loadAccessorAsync=function(x,m,c){var T=this;if(m._data)return m._data;var A=R._GetNumComponents(x,m.type),S=A*_.VertexBuffer.GetTypeByteLength(m.componentType),g=A*m.count;if(m.bufferView==null)m._data=Promise.resolve(new c(g));else{var l=u.Get(x+"/bufferView",this._gltf.bufferViews,m.bufferView);m._data=this.loadBufferViewAsync("/bufferViews/"+l.index,l).then(function(v){if(m.componentType!==5126||m.normalized||l.byteStride&&l.byteStride!==S){var E=new c(g);return _.VertexBuffer.ForEach(v,m.byteOffset||0,l.byteStride||S,A,m.componentType,E.length,m.normalized||!1,function(D,w){E[w]=D}),E}return R._GetTypedArray(x,m.componentType,v,m.byteOffset,g)})}if(m.sparse){var h=m.sparse;m._data=m._data.then(function(v){var E=v,D=u.Get(x+"/sparse/indices/bufferView",T._gltf.bufferViews,h.indices.bufferView),w=u.Get(x+"/sparse/values/bufferView",T._gltf.bufferViews,h.values.bufferView);return Promise.all([T.loadBufferViewAsync("/bufferViews/"+D.index,D),T.loadBufferViewAsync("/bufferViews/"+w.index,w)]).then(function(N){var I,V=N[0],X=N[1],j=R._GetTypedArray(x+"/sparse/indices",h.indices.componentType,V,h.indices.byteOffset,h.count),ne=A*h.count;if(m.componentType!==5126||m.normalized){var te=R._GetTypedArray(x+"/sparse/values",m.componentType,X,h.values.byteOffset,ne);I=new c(ne),_.VertexBuffer.ForEach(te,0,S,A,m.componentType,I.length,m.normalized||!1,function(K,$){I[$]=K})}else I=R._GetTypedArray(x+"/sparse/values",m.componentType,X,h.values.byteOffset,ne);for(var de=0,pe=0;pe<j.length;pe++)for(var ae=j[pe]*A,ee=0;ee<A;ee++)E[ae++]=I[de++];return E})})}return m._data},R.prototype._loadFloatAccessorAsync=function(x,m){return this._loadAccessorAsync(x,m,Float32Array)},R.prototype._loadIndicesAccessorAsync=function(x,m){if(m.type!=="SCALAR")throw new Error(x+"/type: Invalid value "+m.type);if(m.componentType!==5121&&m.componentType!==5123&&m.componentType!==5125)throw new Error(x+"/componentType: Invalid value "+m.componentType);if(m._data)return m._data;if(m.sparse){var c=R._GetTypedArrayConstructor(x+"/componentType",m.componentType);m._data=this._loadAccessorAsync(x,m,c)}else{var T=u.Get(x+"/bufferView",this._gltf.bufferViews,m.bufferView);m._data=this.loadBufferViewAsync("/bufferViews/"+T.index,T).then(function(A){return R._GetTypedArray(x,m.componentType,A,m.byteOffset,m.count)})}return m._data},R.prototype._loadVertexBufferViewAsync=function(x,m){var c=this;return x._babylonBuffer||(x._babylonBuffer=this.loadBufferViewAsync("/bufferViews/"+x.index,x).then(function(T){return new _.Buffer(c._babylonScene.getEngine(),T,!1)})),x._babylonBuffer},R.prototype._loadVertexAccessorAsync=function(x,m,c){var T=this;if(m._babylonVertexBuffer)return m._babylonVertexBuffer;if(m.sparse)m._babylonVertexBuffer=this._loadFloatAccessorAsync("/accessors/"+m.index,m).then(function(S){return new _.VertexBuffer(T._babylonScene.getEngine(),S,c,!1)});else if(m.byteOffset&&m.byteOffset%_.VertexBuffer.GetTypeByteLength(m.componentType)!=0)_.Logger.Warn("Accessor byte offset is not a multiple of component type byte length"),m._babylonVertexBuffer=this._loadFloatAccessorAsync("/accessors/"+m.index,m).then(function(S){return new _.VertexBuffer(T._babylonScene.getEngine(),S,c,!1)});else if(c===_.VertexBuffer.MatricesIndicesKind||c===_.VertexBuffer.MatricesIndicesExtraKind)m._babylonVertexBuffer=this._loadFloatAccessorAsync("/accessors/"+m.index,m).then(function(S){return new _.VertexBuffer(T._babylonScene.getEngine(),S,c,!1)});else{var A=u.Get(x+"/bufferView",this._gltf.bufferViews,m.bufferView);m._babylonVertexBuffer=this._loadVertexBufferViewAsync(A,c).then(function(S){var g=R._GetNumComponents(x,m.type);return new _.VertexBuffer(T._babylonScene.getEngine(),S,c,!1,!1,A.byteStride,!1,m.byteOffset,g,m.componentType,m.normalized,!0,1,!0)})}return m._babylonVertexBuffer},R.prototype._loadMaterialMetallicRoughnessPropertiesAsync=function(x,m,c){if(!(c instanceof _.PBRMaterial))throw new Error(x+": Material type not supported");var T=new Array;return m&&(m.baseColorFactor?(c.albedoColor=_.Color3.FromArray(m.baseColorFactor),c.alpha=m.baseColorFactor[3]):c.albedoColor=_.Color3.White(),c.metallic=m.metallicFactor==null?1:m.metallicFactor,c.roughness=m.roughnessFactor==null?1:m.roughnessFactor,m.baseColorTexture&&T.push(this.loadTextureInfoAsync(x+"/baseColorTexture",m.baseColorTexture,function(A){A.name=c.name+" (Base Color)",c.albedoTexture=A})),m.metallicRoughnessTexture&&(m.metallicRoughnessTexture.nonColorData=!0,T.push(this.loadTextureInfoAsync(x+"/metallicRoughnessTexture",m.metallicRoughnessTexture,function(A){A.name=c.name+" (Metallic Roughness)",c.metallicTexture=A})),c.useMetallnessFromMetallicTextureBlue=!0,c.useRoughnessFromMetallicTextureGreen=!0,c.useRoughnessFromMetallicTextureAlpha=!1)),Promise.all(T).then(function(){})},R.prototype._loadMaterialAsync=function(x,m,c,T,A){A===void 0&&(A=function(){});var S=this._extensionsLoadMaterialAsync(x,m,c,T,A);if(S)return S;m._data=m._data||{};var g=m._data[T];if(!g){this.logOpen(x+" "+(m.name||""));var l=this.createMaterial(x,m,T);g={babylonMaterial:l,babylonMeshes:[],promise:this.loadMaterialPropertiesAsync(x,m,l)},m._data[T]=g,R.AddPointerMetadata(l,x),this._parent.onMaterialLoadedObservable.notifyObservers(l),this.logClose()}return c&&(g.babylonMeshes.push(c),c.onDisposeObservable.addOnce(function(){var h=g.babylonMeshes.indexOf(c);h!==-1&&g.babylonMeshes.splice(h,1)})),A(g.babylonMaterial),g.promise.then(function(){return g.babylonMaterial})},R.prototype._createDefaultMaterial=function(x,m){this._babylonScene._blockEntityCollection=this._forAssetContainer;var c=new _.PBRMaterial(x,this._babylonScene);return this._babylonScene._blockEntityCollection=!1,c.fillMode=m,c.enableSpecularAntiAliasing=!0,c.useRadianceOverAlpha=!this._parent.transparencyAsCoverage,c.useSpecularOverAlpha=!this._parent.transparencyAsCoverage,c.transparencyMode=_.PBRMaterial.PBRMATERIAL_OPAQUE,c.metallic=1,c.roughness=1,c},R.prototype.createMaterial=function(x,m,c){var T=this._extensionsCreateMaterial(x,m,c);if(T)return T;var A=m.name||"material"+m.index;return this._createDefaultMaterial(A,c)},R.prototype.loadMaterialPropertiesAsync=function(x,m,c){var T=this._extensionsLoadMaterialPropertiesAsync(x,m,c);if(T)return T;var A=new Array;return A.push(this.loadMaterialBasePropertiesAsync(x,m,c)),m.pbrMetallicRoughness&&A.push(this._loadMaterialMetallicRoughnessPropertiesAsync(x+"/pbrMetallicRoughness",m.pbrMetallicRoughness,c)),this.loadMaterialAlphaProperties(x,m,c),Promise.all(A).then(function(){})},R.prototype.loadMaterialBasePropertiesAsync=function(x,m,c){if(!(c instanceof _.PBRMaterial))throw new Error(x+": Material type not supported");var T=new Array;return c.emissiveColor=m.emissiveFactor?_.Color3.FromArray(m.emissiveFactor):new _.Color3(0,0,0),m.doubleSided&&(c.backFaceCulling=!1,c.twoSidedLighting=!0),m.normalTexture&&(m.normalTexture.nonColorData=!0,T.push(this.loadTextureInfoAsync(x+"/normalTexture",m.normalTexture,function(A){A.name=c.name+" (Normal)",c.bumpTexture=A})),c.invertNormalMapX=!this._babylonScene.useRightHandedSystem,c.invertNormalMapY=this._babylonScene.useRightHandedSystem,m.normalTexture.scale!=null&&(c.bumpTexture.level=m.normalTexture.scale),c.forceIrradianceInFragment=!0),m.occlusionTexture&&(m.occlusionTexture.nonColorData=!0,T.push(this.loadTextureInfoAsync(x+"/occlusionTexture",m.occlusionTexture,function(A){A.name=c.name+" (Occlusion)",c.ambientTexture=A})),c.useAmbientInGrayScale=!0,m.occlusionTexture.strength!=null&&(c.ambientTextureStrength=m.occlusionTexture.strength)),m.emissiveTexture&&T.push(this.loadTextureInfoAsync(x+"/emissiveTexture",m.emissiveTexture,function(A){A.name=c.name+" (Emissive)",c.emissiveTexture=A})),Promise.all(T).then(function(){})},R.prototype.loadMaterialAlphaProperties=function(x,m,c){if(!(c instanceof _.PBRMaterial))throw new Error(x+": Material type not supported");switch(m.alphaMode||"OPAQUE"){case"OPAQUE":c.transparencyMode=_.PBRMaterial.PBRMATERIAL_OPAQUE;break;case"MASK":c.transparencyMode=_.PBRMaterial.PBRMATERIAL_ALPHATEST,c.alphaCutOff=m.alphaCutoff==null?.5:m.alphaCutoff,c.albedoTexture&&(c.albedoTexture.hasAlpha=!0);break;case"BLEND":c.transparencyMode=_.PBRMaterial.PBRMATERIAL_ALPHABLEND,c.albedoTexture&&(c.albedoTexture.hasAlpha=!0,c.useAlphaFromAlbedoTexture=!0);break;default:throw new Error(x+"/alphaMode: Invalid value ("+m.alphaMode+")")}},R.prototype.loadTextureInfoAsync=function(x,m,c){var T=this;c===void 0&&(c=function(){});var A=this._extensionsLoadTextureInfoAsync(x,m,c);if(A)return A;if(this.logOpen(""+x),m.texCoord>=2)throw new Error(x+"/texCoord: Invalid value ("+m.texCoord+")");var S=u.Get(x+"/index",this._gltf.textures,m.index);S._textureInfo=m;var g=this._loadTextureAsync("/textures/"+m.index,S,function(l){l.coordinatesIndex=m.texCoord||0,R.AddPointerMetadata(l,x),T._parent.onTextureLoadedObservable.notifyObservers(l),c(l)});return this.logClose(),g},R.prototype._loadTextureAsync=function(x,m,c){c===void 0&&(c=function(){});var T=this._extensionsLoadTextureAsync(x,m,c);if(T)return T;this.logOpen(x+" "+(m.name||""));var A=m.sampler==null?R.DefaultSampler:u.Get(x+"/sampler",this._gltf.samplers,m.sampler),S=u.Get(x+"/source",this._gltf.images,m.source),g=this._createTextureAsync(x,A,S,c);return this.logClose(),g},R.prototype._createTextureAsync=function(x,m,c,T,A){var S=this;T===void 0&&(T=function(){});var g=this._loadSampler("/samplers/"+m.index,m),l=new Array,h=new _.Deferred;this._babylonScene._blockEntityCollection=this._forAssetContainer;var v=new _.Texture(null,this._babylonScene,g.noMipMaps,!1,g.samplingMode,function(){S._disposed||h.resolve()},function(E,D){S._disposed||h.reject(new Error(x+": "+(D&&D.message?D.message:E||"Failed to load texture")))},void 0,void 0,void 0,c.mimeType,A);return this._babylonScene._blockEntityCollection=!1,l.push(h.promise),l.push(this.loadImageAsync("/images/"+c.index,c).then(function(E){var D=c.uri||S._fileName+"#image"+c.index,w="data:"+S._uniqueRootUrl+D;v.updateURL(w,E)})),v.wrapU=g.wrapU,v.wrapV=g.wrapV,T(v),Promise.all(l).then(function(){return v})},R.prototype._loadSampler=function(x,m){return m._data||(m._data={noMipMaps:m.minFilter===9728||m.minFilter===9729,samplingMode:R._GetTextureSamplingMode(x,m),wrapU:R._GetTextureWrapMode(x+"/wrapS",m.wrapS),wrapV:R._GetTextureWrapMode(x+"/wrapT",m.wrapT)}),m._data},R.prototype.loadImageAsync=function(x,m){if(!m._data){if(this.logOpen(x+" "+(m.name||"")),m.uri)m._data=this.loadUriAsync(x+"/uri",m,m.uri);else{var c=u.Get(x+"/bufferView",this._gltf.bufferViews,m.bufferView);m._data=this.loadBufferViewAsync("/bufferViews/"+c.index,c)}this.logClose()}return m._data},R.prototype.loadUriAsync=function(x,m,c){var T=this,A=this._extensionsLoadUriAsync(x,m,c);if(A)return A;if(!R._ValidateUri(c))throw new Error(x+": '"+c+"' is invalid");if(_.Tools.IsBase64(c)){var S=new Uint8Array(_.Tools.DecodeBase64(c));return this.log("Decoded "+c.substr(0,64)+"... ("+S.length+" bytes)"),Promise.resolve(S)}return this.log("Loading "+c),this._parent.preprocessUrlAsync(this._rootUrl+c).then(function(g){return new Promise(function(l,h){T._parent._loadFile(g,T._babylonScene,function(v){T._disposed||(T.log("Loaded "+c+" ("+v.byteLength+" bytes)"),l(new Uint8Array(v)))},!0,function(v){h(new _.LoadFileError(x+": Failed to load '"+c+"'"+(v?": "+v.status+" "+v.statusText:""),v))})})})},R.AddPointerMetadata=function(x,m){var c=x.metadata=x.metadata||{},T=c.gltf=c.gltf||{};(T.pointers=T.pointers||[]).push(m)},R._GetTextureWrapMode=function(x,m){switch(m=m??10497){case 33071:return _.Texture.CLAMP_ADDRESSMODE;case 33648:return _.Texture.MIRROR_ADDRESSMODE;case 10497:return _.Texture.WRAP_ADDRESSMODE;default:return _.Logger.Warn(x+": Invalid value ("+m+")"),_.Texture.WRAP_ADDRESSMODE}},R._GetTextureSamplingMode=function(x,m){var c=m.magFilter==null?9729:m.magFilter,T=m.minFilter==null?9987:m.minFilter;if(c===9729)switch(T){case 9728:return _.Texture.LINEAR_NEAREST;case 9729:return _.Texture.LINEAR_LINEAR;case 9984:return _.Texture.LINEAR_NEAREST_MIPNEAREST;case 9985:return _.Texture.LINEAR_LINEAR_MIPNEAREST;case 9986:return _.Texture.LINEAR_NEAREST_MIPLINEAR;case 9987:return _.Texture.LINEAR_LINEAR_MIPLINEAR;default:return _.Logger.Warn(x+"/minFilter: Invalid value ("+T+")"),_.Texture.LINEAR_LINEAR_MIPLINEAR}else switch(c!==9728&&_.Logger.Warn(x+"/magFilter: Invalid value ("+c+")"),T){case 9728:return _.Texture.NEAREST_NEAREST;case 9729:return _.Texture.NEAREST_LINEAR;case 9984:return _.Texture.NEAREST_NEAREST_MIPNEAREST;case 9985:return _.Texture.NEAREST_LINEAR_MIPNEAREST;case 9986:return _.Texture.NEAREST_NEAREST_MIPLINEAR;case 9987:return _.Texture.NEAREST_LINEAR_MIPLINEAR;default:return _.Logger.Warn(x+"/minFilter: Invalid value ("+T+")"),_.Texture.NEAREST_NEAREST_MIPNEAREST}},R._GetTypedArrayConstructor=function(x,m){switch(m){case 5120:return Int8Array;case 5121:return Uint8Array;case 5122:return Int16Array;case 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this._applyExtensions(m,"createMaterial",function(T){return T.createMaterial&&T.createMaterial(x,m,c)})},R.prototype._extensionsLoadMaterialPropertiesAsync=function(x,m,c){return this._applyExtensions(m,"loadMaterialProperties",function(T){return T.loadMaterialPropertiesAsync&&T.loadMaterialPropertiesAsync(x,m,c)})},R.prototype._extensionsLoadTextureInfoAsync=function(x,m,c){return this._applyExtensions(m,"loadTextureInfo",function(T){return T.loadTextureInfoAsync&&T.loadTextureInfoAsync(x,m,c)})},R.prototype._extensionsLoadTextureAsync=function(x,m,c){return this._applyExtensions(m,"loadTexture",function(T){return T._loadTextureAsync&&T._loadTextureAsync(x,m,c)})},R.prototype._extensionsLoadAnimationAsync=function(x,m){return this._applyExtensions(m,"loadAnimation",function(c){return c.loadAnimationAsync&&c.loadAnimationAsync(x,m)})},R.prototype._extensionsLoadSkinAsync=function(x,m,c){return this._applyExtensions(c,"loadSkin",function(T){return T._loadSkinAsync&&T._loadSkinAsync(x,m,c)})},R.prototype._extensionsLoadUriAsync=function(x,m,c){return this._applyExtensions(m,"loadUri",function(T){return T._loadUriAsync&&T._loadUriAsync(x,m,c)})},R.prototype._extensionsLoadBufferViewAsync=function(x,m){return this._applyExtensions(m,"loadBufferView",function(c){return c.loadBufferViewAsync&&c.loadBufferViewAsync(x,m)})},R.prototype._extensionsLoadBufferAsync=function(x,m,c,T){return this._applyExtensions(m,"loadBuffer",function(A){return A.loadBufferAsync&&A.loadBufferAsync(x,m,c,T)})},R.LoadExtensionAsync=function(x,m,c,T){if(!m.extensions)return null;var A=m.extensions[c];return A?T(x+"/extensions/"+c,A):null},R.LoadExtraAsync=function(x,m,c,T){if(!m.extras)return null;var A=m.extras[c];return 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M.Observable,this.onDisposeObservable=new M.Observable,this.onExtensionLoadedObservable=new M.Observable,this.validate=!1,this.onValidatedObservable=new M.Observable,this._loader=null,this._requests=new Array,this.name="gltf",this.extensions={".gltf":{isBinary:!1},".glb":{isBinary:!0}},this._logIndentLevel=0,this._loggingEnabled=!1,this._log=this._logDisabled,this._capturePerformanceCounters=!1,this._startPerformanceCounter=this._startPerformanceCounterDisabled,this._endPerformanceCounter=this._endPerformanceCounterDisabled}return Object.defineProperty(m.prototype,"onParsed",{set:function(c){this._onParsedObserver&&this.onParsedObservable.remove(this._onParsedObserver),this._onParsedObserver=this.onParsedObservable.add(c)},enumerable:!1,configurable:!0}),Object.defineProperty(m.prototype,"onMeshLoaded",{set:function(c){this._onMeshLoadedObserver&&this.onMeshLoadedObservable.remove(this._onMeshLoadedObserver),this._onMeshLoadedObserver=this.onMeshLoadedObservable.add(c)},enumerable:!1,configurable:!0}),Object.defineProperty(m.prototype,"onTextureLoaded",{set:function(c){this._onTextureLoadedObserver&&this.onTextureLoadedObservable.remove(this._onTextureLoadedObserver),this._onTextureLoadedObserver=this.onTextureLoadedObservable.add(c)},enumerable:!1,configurable:!0}),Object.defineProperty(m.prototype,"onMaterialLoaded",{set:function(c){this._onMaterialLoadedObserver&&this.onMaterialLoadedObservable.remove(this._onMaterialLoadedObserver),this._onMaterialLoadedObserver=this.onMaterialLoadedObservable.add(c)},enumerable:!1,configurable:!0}),Object.defineProperty(m.prototype,"onCameraLoaded",{set:function(c){this._onCameraLoadedObserver&&this.onCameraLoadedObservable.remove(this._onCameraLoadedObserver),this._onCameraLoadedObserver=this.onCameraLoadedObservable.add(c)},enumerable:!1,configurable:!0}),Object.defineProperty(m.prototype,"onComplete",{set:function(c){this._onCompleteObserver&&this.onCompleteObservable.remove(this._onCompleteObserver),this._onCompleteObserver=this.onCompleteObservable.add(c)},enumerable:!1,configurable:!0}),Object.defineProperty(m.prototype,"onError",{set:function(c){this._onErrorObserver&&this.onErrorObservable.remove(this._onErrorObserver),this._onErrorObserver=this.onErrorObservable.add(c)},enumerable:!1,configurable:!0}),Object.defineProperty(m.prototype,"onDispose",{set:function(c){this._onDisposeObserver&&this.onDisposeObservable.remove(this._onDisposeObserver),this._onDisposeObserver=this.onDisposeObservable.add(c)},enumerable:!1,configurable:!0}),Object.defineProperty(m.prototype,"onExtensionLoaded",{set:function(c){this._onExtensionLoadedObserver&&this.onExtensionLoadedObservable.remove(this._onExtensionLoadedObserver),this._onExtensionLoadedObserver=this.onExtensionLoadedObservable.add(c)},enumerable:!1,configurable:!0}),Object.defineProperty(m.prototype,"loggingEnabled",{get:function(){return 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*****************************************************************************
-	Copyright (c) Microsoft Corporation.
-
-	Permission to use, copy, modify, and/or distribute this software for any
-	purpose with or without fee is hereby granted.
-
-	THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
-	REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
-	AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
-	INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM
-	LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
-	OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
-	PERFORMANCE OF THIS SOFTWARE.
-	***************************************************************************** */var _=function(M,R){return(_=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(x,m){x.__proto__=m}||function(x,m){for(var c in m)Object.prototype.hasOwnProperty.call(m,c)&&(x[c]=m[c])})(M,R)};function C(M,R){if(typeof R!="function"&&R!==null)throw new TypeError("Class extends value "+String(R)+" is not a constructor or null");function x(){this.constructor=M}_(M,R),M.prototype=R===null?Object.create(R):(x.prototype=R.prototype,new x)}var u=function(){return(u=Object.assign||function(M){for(var R,x=1,m=arguments.length;x<m;x++)for(var c in R=arguments[x])Object.prototype.hasOwnProperty.call(R,c)&&(M[c]=R[c]);return M}).apply(this,arguments)}},function(y,f){var U;U=function(){return this}();try{U=U||new Function("return this")()}catch{typeof window=="object"&&(U=window)}y.exports=U},function(y,f,U){U.r(f)},function(y,f,U){U.r(f),U.d(f,"EXT_lights_image_based",function(){return 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ae(ee){this.name="KHR_draco_mesh_compression",this._loader=ee,this.enabled=_.DracoCompression.DecoderAvailable&&this._loader.isExtensionUsed("KHR_draco_mesh_compression")}return ae.prototype.dispose=function(){delete this.dracoCompression,this._loader=null},ae.prototype._loadVertexDataAsync=function(ee,K,$){var L=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){if(K.mode!=null){if(K.mode!==5&&K.mode!==4)throw new Error(ee+": Unsupported mode "+K.mode);if(K.mode===5)throw new Error(ee+": Mode "+K.mode+" is not currently supported")}var oe={},re=function(k,H){var Z=Q.attributes[k];Z!=null&&($._delayInfo=$._delayInfo||[],$._delayInfo.indexOf(H)===-1&&$._delayInfo.push(H),oe[H]=Z)};re("POSITION",_.VertexBuffer.PositionKind),re("NORMAL",_.VertexBuffer.NormalKind),re("TANGENT",_.VertexBuffer.TangentKind),re("TEXCOORD_0",_.VertexBuffer.UVKind),re("TEXCOORD_1",_.VertexBuffer.UV2Kind),re("JOINTS_0",_.VertexBuffer.MatricesIndicesKind),re("WEIGHTS_0",_.VertexBuffer.MatricesWeightsKind),re("COLOR_0",_.VertexBuffer.ColorKind);var Y=C.a.Get(G,L._loader.gltf.bufferViews,Q.bufferView);return Y._dracoBabylonGeometry||(Y._dracoBabylonGeometry=L._loader.loadBufferViewAsync("/bufferViews/"+Y.index,Y).then(function(k){return(L.dracoCompression||_.DracoCompression.Default).decodeMeshAsync(k,oe).then(function(H){var Z=new _.Geometry($.name,L._loader.babylonScene);return H.applyToGeometry(Z),Z}).catch(function(H){throw new Error(ee+": "+H.message)})})),Y._dracoBabylonGeometry})},ae}();C.b.RegisterExtension("KHR_draco_mesh_compression",function(ae){return new m(ae)});var c=function(){function ae(ee){this.name="KHR_lights_punctual",this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_lights_punctual")}return ae.prototype.dispose=function(){this._loader=null,delete this._lights},ae.prototype.onLoading=function(){var ee=this._loader.gltf.extensions;if(ee&&ee[this.name]){var K=ee[this.name];this._lights=K.lights}},ae.prototype.loadNodeAsync=function(ee,K,$){var L=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){return L._loader.loadNodeAsync(ee,K,function(oe){var re,Y=C.a.Get(G,L._lights,Q.light),k=Y.name||oe.name;switch(L._loader.babylonScene._blockEntityCollection=L._loader._forAssetContainer,Y.type){case"directional":re=new _.DirectionalLight(k,_.Vector3.Backward(),L._loader.babylonScene);break;case"point":re=new _.PointLight(k,_.Vector3.Zero(),L._loader.babylonScene);break;case"spot":var H=new _.SpotLight(k,_.Vector3.Zero(),_.Vector3.Backward(),0,1,L._loader.babylonScene);H.angle=2*(Y.spot&&Y.spot.outerConeAngle||Math.PI/4),H.innerAngle=2*(Y.spot&&Y.spot.innerConeAngle||0),re=H;break;default:throw L._loader.babylonScene._blockEntityCollection=!1,new Error(G+": Invalid light type ("+Y.type+")")}L._loader.babylonScene._blockEntityCollection=!1,re.falloffType=_.Light.FALLOFF_GLTF,re.diffuse=Y.color?_.Color3.FromArray(Y.color):_.Color3.White(),re.intensity=Y.intensity==null?1:Y.intensity,re.range=Y.range==null?Number.MAX_VALUE:Y.range,re.parent=oe,L._loader._babylonLights.push(re),C.b.AddPointerMetadata(re,G),$(oe)})})},ae}();C.b.RegisterExtension("KHR_lights_punctual",function(ae){return new c(ae)});var T=function(){function ae(ee){this.name="KHR_materials_pbrSpecularGlossiness",this.order=200,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_pbrSpecularGlossiness")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialBasePropertiesAsync(ee,K,$)),oe.push(L._loadSpecularGlossinessPropertiesAsync(G,K,Q,$)),L._loader.loadMaterialAlphaProperties(ee,K,$),Promise.all(oe).then(function(){})})},ae.prototype._loadSpecularGlossinessPropertiesAsync=function(ee,K,$,L){if(!(L instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");var G=new Array;return L.metallic=null,L.roughness=null,$.diffuseFactor?(L.albedoColor=_.Color3.FromArray($.diffuseFactor),L.alpha=$.diffuseFactor[3]):L.albedoColor=_.Color3.White(),L.reflectivityColor=$.specularFactor?_.Color3.FromArray($.specularFactor):_.Color3.White(),L.microSurface=$.glossinessFactor==null?1:$.glossinessFactor,$.diffuseTexture&&G.push(this._loader.loadTextureInfoAsync(ee+"/diffuseTexture",$.diffuseTexture,function(Q){Q.name=L.name+" (Diffuse)",L.albedoTexture=Q})),$.specularGlossinessTexture&&($.specularGlossinessTexture.nonColorData=!0,G.push(this._loader.loadTextureInfoAsync(ee+"/specularGlossinessTexture",$.specularGlossinessTexture,function(Q){Q.name=L.name+" (Specular Glossiness)",L.reflectivityTexture=Q})),L.reflectivityTexture.hasAlpha=!0,L.useMicroSurfaceFromReflectivityMapAlpha=!0),Promise.all(G).then(function(){})},ae}();C.b.RegisterExtension("KHR_materials_pbrSpecularGlossiness",function(ae){return new T(ae)});var A=function(){function ae(ee){this.name="KHR_materials_unlit",this.order=210,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_unlit")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(){return L._loadUnlitPropertiesAsync(ee,K,$)})},ae.prototype._loadUnlitPropertiesAsync=function(ee,K,$){if(!($ instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");var L=new Array;$.unlit=!0;var G=K.pbrMetallicRoughness;return G&&(G.baseColorFactor?($.albedoColor=_.Color3.FromArray(G.baseColorFactor),$.alpha=G.baseColorFactor[3]):$.albedoColor=_.Color3.White(),G.baseColorTexture&&L.push(this._loader.loadTextureInfoAsync(ee+"/baseColorTexture",G.baseColorTexture,function(Q){Q.name=$.name+" (Base Color)",$.albedoTexture=Q}))),K.doubleSided&&($.backFaceCulling=!1,$.twoSidedLighting=!0),this._loader.loadMaterialAlphaProperties(ee,K,$),Promise.all(L).then(function(){})},ae}();C.b.RegisterExtension("KHR_materials_unlit",function(ae){return new A(ae)});var S=function(){function ae(ee){this.name="KHR_materials_clearcoat",this.order=190,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_clearcoat")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialPropertiesAsync(ee,K,$)),oe.push(L._loadClearCoatPropertiesAsync(G,Q,$)),Promise.all(oe).then(function(){})})},ae.prototype._loadClearCoatPropertiesAsync=function(ee,K,$){if(!($ instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");var L=new Array;return $.clearCoat.isEnabled=!0,$.clearCoat.useRoughnessFromMainTexture=!1,$.clearCoat.remapF0OnInterfaceChange=!1,K.clearcoatFactor!=null?$.clearCoat.intensity=K.clearcoatFactor:$.clearCoat.intensity=0,K.clearcoatTexture&&L.push(this._loader.loadTextureInfoAsync(ee+"/clearcoatTexture",K.clearcoatTexture,function(G){G.name=$.name+" (ClearCoat Intensity)",$.clearCoat.texture=G})),K.clearcoatRoughnessFactor!=null?$.clearCoat.roughness=K.clearcoatRoughnessFactor:$.clearCoat.roughness=0,K.clearcoatRoughnessTexture&&(K.clearcoatRoughnessTexture.nonColorData=!0,L.push(this._loader.loadTextureInfoAsync(ee+"/clearcoatRoughnessTexture",K.clearcoatRoughnessTexture,function(G){G.name=$.name+" (ClearCoat Roughness)",$.clearCoat.textureRoughness=G}))),K.clearcoatNormalTexture&&(K.clearcoatNormalTexture.nonColorData=!0,L.push(this._loader.loadTextureInfoAsync(ee+"/clearcoatNormalTexture",K.clearcoatNormalTexture,function(G){G.name=$.name+" (ClearCoat Normal)",$.clearCoat.bumpTexture=G})),$.invertNormalMapX=!$.getScene().useRightHandedSystem,$.invertNormalMapY=$.getScene().useRightHandedSystem,K.clearcoatNormalTexture.scale!=null&&($.clearCoat.bumpTexture.level=K.clearcoatNormalTexture.scale)),Promise.all(L).then(function(){})},ae}();C.b.RegisterExtension("KHR_materials_clearcoat",function(ae){return new S(ae)});var g=function(){function ae(ee){this.name="KHR_materials_sheen",this.order=190,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_sheen")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialPropertiesAsync(ee,K,$)),oe.push(L._loadSheenPropertiesAsync(G,Q,$)),Promise.all(oe).then(function(){})})},ae.prototype._loadSheenPropertiesAsync=function(ee,K,$){if(!($ instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");var L=new Array;return $.sheen.isEnabled=!0,$.sheen.intensity=1,K.sheenColorFactor!=null?$.sheen.color=_.Color3.FromArray(K.sheenColorFactor):$.sheen.color=_.Color3.Black(),K.sheenColorTexture&&L.push(this._loader.loadTextureInfoAsync(ee+"/sheenColorTexture",K.sheenColorTexture,function(G){G.name=$.name+" (Sheen Color)",$.sheen.texture=G})),K.sheenRoughnessFactor!==void 0?$.sheen.roughness=K.sheenRoughnessFactor:$.sheen.roughness=0,K.sheenRoughnessTexture&&(K.sheenRoughnessTexture.nonColorData=!0,L.push(this._loader.loadTextureInfoAsync(ee+"/sheenRoughnessTexture",K.sheenRoughnessTexture,function(G){G.name=$.name+" (Sheen Roughness)",$.sheen.textureRoughness=G}))),$.sheen.albedoScaling=!0,$.sheen.useRoughnessFromMainTexture=!1,Promise.all(L).then(function(){})},ae}();C.b.RegisterExtension("KHR_materials_sheen",function(ae){return new g(ae)});var l=function(){function ae(ee){this.name="KHR_materials_specular",this.order=190,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_specular")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialPropertiesAsync(ee,K,$)),oe.push(L._loadSpecularPropertiesAsync(G,Q,$)),Promise.all(oe).then(function(){})})},ae.prototype._loadSpecularPropertiesAsync=function(ee,K,$){if(!($ instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");var L=new Array;return K.specularFactor!==void 0&&($.metallicF0Factor=K.specularFactor),K.specularColorFactor!==void 0&&($.metallicReflectanceColor=_.Color3.FromArray(K.specularColorFactor)),K.specularTexture&&(K.specularTexture.nonColorData=!0,L.push(this._loader.loadTextureInfoAsync(ee+"/specularTexture",K.specularTexture,function(G){G.name=$.name+" (Specular F0 Color)",$.metallicReflectanceTexture=G}))),Promise.all(L).then(function(){})},ae}();C.b.RegisterExtension("KHR_materials_specular",function(ae){return new l(ae)});var h=function(){function ae(ee){this.name="KHR_materials_ior",this.order=180,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_ior")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialPropertiesAsync(ee,K,$)),oe.push(L._loadIorPropertiesAsync(G,Q,$)),Promise.all(oe).then(function(){})})},ae.prototype._loadIorPropertiesAsync=function(ee,K,$){if(!($ instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");return K.ior!==void 0?$.indexOfRefraction=K.ior:$.indexOfRefraction=ae._DEFAULT_IOR,Promise.resolve()},ae._DEFAULT_IOR=1.5,ae}();C.b.RegisterExtension("KHR_materials_ior",function(ae){return new h(ae)});var v=function(){function ae(ee){this.name="KHR_materials_variants",this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_variants")}return ae.prototype.dispose=function(){this._loader=null},ae.GetAvailableVariants=function(ee){var K=this._GetExtensionMetadata(ee);return K?Object.keys(K.variants):[]},ae.prototype.getAvailableVariants=function(ee){return ae.GetAvailableVariants(ee)},ae.SelectVariant=function(ee,K){var $=this._GetExtensionMetadata(ee);if(!$)throw new Error("Cannot select variant on a glTF mesh that does not have the KHR_materials_variants extension");var L=function(oe){var re=$.variants[oe];if(re)for(var Y=0,k=re;Y<k.length;Y++){var H=k[Y];H.mesh.material=H.material}};if(K instanceof Array)for(var G=0,Q=K;G<Q.length;G++)L(Q[G]);else L(K);$.lastSelected=K},ae.prototype.selectVariant=function(ee,K){return ae.SelectVariant(ee,K)},ae.Reset=function(ee){var K=this._GetExtensionMetadata(ee);if(!K)throw new Error("Cannot reset on a glTF mesh that does not have the KHR_materials_variants extension");for(var $=0,L=K.original;$<L.length;$++){var G=L[$];G.mesh.material=G.material}K.lastSelected=null},ae.prototype.reset=function(ee){return ae.Reset(ee)},ae.GetLastSelectedVariant=function(ee){var K=this._GetExtensionMetadata(ee);if(!K)throw new Error("Cannot get the last selected variant on a glTF mesh that does not have the KHR_materials_variants extension");return K.lastSelected},ae.prototype.getLastSelectedVariant=function(ee){return ae.GetLastSelectedVariant(ee)},ae._GetExtensionMetadata=function(ee){var K,$;return(($=(K=ee?.metadata)===null||K===void 0?void 0:K.gltf)===null||$===void 0?void 0:$.KHR_materials_variants)||null},ae.prototype.onLoading=function(){var ee=this._loader.gltf.extensions;if(ee&&ee[this.name]){var K=ee[this.name];this._variants=K.variants}},ae.prototype._loadMeshPrimitiveAsync=function(ee,K,$,L,G,Q){var oe=this;return C.b.LoadExtensionAsync(ee,G,this.name,function(re,Y){var k=new Array;return k.push(oe._loader._loadMeshPrimitiveAsync(ee,K,$,L,G,function(H){if(Q(H),H instanceof _.Mesh){var Z=C.b._GetDrawMode(ee,G.mode),W=oe._loader.rootBabylonMesh,q=W.metadata=W.metadata||{},he=q.gltf=q.gltf||{},ge=he.KHR_materials_variants=he.KHR_materials_variants||{lastSelected:null,original:[],variants:{}};ge.original.push({mesh:H,material:H.material});for(var me=ge.variants,_e=0,be=Y.mappings;_e<be.length;_e++)for(var Pe=be[_e],ye=function(We){var je=C.a.Get(re+"/mapping/"+We,oe._variants,We),He=C.a.Get("#/materials/",oe._loader.gltf.materials,Pe.material);k.push(oe._loader._loadMaterialAsync("#/materials/"+Pe.material,He,H,Z,function(qe){me[je.name]=me[je.name]||[],me[je.name].push({mesh:H,material:qe})}))},Be=0,ke=Pe.variants;Be<ke.length;Be++)ye(ke[Be])}})),Promise.all(k).then(function(H){return H[0]})})},ae}();C.b.RegisterExtension("KHR_materials_variants",function(ae){return new v(ae)});var E=U(4),D=function(){function ae(ee,K){var $=this;this._opaqueRenderTarget=null,this._opaqueMeshesCache=[],this._transparentMeshesCache=[],this._options=Object(E.a)(Object(E.a)({},ae._getDefaultOptions()),ee),this._scene=K,this._scene._transmissionHelper=this,this.onErrorObservable=new _.Observable,this._scene.onDisposeObservable.addOnce(function(L){$.dispose()}),this._parseScene(),this._setupRenderTargets()}return ae._getDefaultOptions=function(){return{renderSize:512}},ae.prototype.updateOptions=function(ee){var K=this;if(Object.keys(ee).filter(function(G){return K._options[G]!==ee[G]}).length){var $=Object(E.a)(Object(E.a)({},this._options),ee),L=this._options;this._options=$,$.renderSize!==L.renderSize&&this._setupRenderTargets()}},ae.prototype.getOpaqueTarget=function(){return this._opaqueRenderTarget},ae.prototype.shouldRenderAsTransmission=function(ee){return!!ee&&!!(ee instanceof _.PBRMaterial&&ee.subSurface.isRefractionEnabled)},ae.prototype._addMesh=function(ee){ee instanceof _.Mesh&&(ee.onMaterialChangedObservable.add(this.onMeshMaterialChanged.bind(this)),this.shouldRenderAsTransmission(ee.material)?this._transparentMeshesCache.push(ee):this._opaqueMeshesCache.push(ee))},ae.prototype._removeMesh=function(ee){if(ee instanceof _.Mesh){ee.onMaterialChangedObservable.remove(this.onMeshMaterialChanged.bind(this));var K=this._transparentMeshesCache.indexOf(ee);K!==-1&&this._transparentMeshesCache.splice(K,1),(K=this._opaqueMeshesCache.indexOf(ee))!==-1&&this._opaqueMeshesCache.splice(K,1)}},ae.prototype._parseScene=function(){this._scene.meshes.forEach(this._addMesh.bind(this)),this._scene.onNewMeshAddedObservable.add(this._addMesh.bind(this)),this._scene.onMeshRemovedObservable.add(this._removeMesh.bind(this))},ae.prototype.onMeshMaterialChanged=function(ee){if(ee instanceof _.Mesh){var K=this._transparentMeshesCache.indexOf(ee),$=this._opaqueMeshesCache.indexOf(ee);this.shouldRenderAsTransmission(ee.material)?(ee.material instanceof _.PBRMaterial&&(ee.material.subSurface.refractionTexture=this._opaqueRenderTarget),$!==-1?(this._opaqueMeshesCache.splice($,1),this._transparentMeshesCache.push(ee)):K===-1&&this._transparentMeshesCache.push(ee)):K!==-1?(this._transparentMeshesCache.splice(K,1),this._opaqueMeshesCache.push(ee)):$===-1&&this._opaqueMeshesCache.push(ee)}},ae.prototype._setupRenderTargets=function(){var ee=this,K=-1;if(this._scene.layers&&this._opaqueRenderTarget)for(var $=0,L=this._scene.layers;$<L.length;$++){var G=(re=L[$]).renderTargetTextures.indexOf(this._opaqueRenderTarget);G>=0&&re.renderTargetTextures.splice(G,1)}if(this._opaqueRenderTarget&&(K=this._scene.customRenderTargets.indexOf(this._opaqueRenderTarget),this._opaqueRenderTarget.dispose()),this._opaqueRenderTarget=new _.RenderTargetTexture("opaqueSceneTexture",this._options.renderSize,this._scene,!0),this._opaqueRenderTarget.renderList=this._opaqueMeshesCache,this._opaqueRenderTarget.gammaSpace=!0,this._opaqueRenderTarget.lodGenerationScale=1,this._opaqueRenderTarget.lodGenerationOffset=-4,K>=0?this._scene.customRenderTargets.splice(K,0,this._opaqueRenderTarget):(K=this._scene.customRenderTargets.length,this._scene.customRenderTargets.push(this._opaqueRenderTarget)),this._scene.layers&&this._opaqueRenderTarget)for(var Q=0,oe=this._scene.layers;Q<oe.length;Q++){var re;(re=oe[Q]).renderTargetTextures.push(this._opaqueRenderTarget)}this._transparentMeshesCache.forEach(function(Y){ee.shouldRenderAsTransmission(Y.material)&&Y.material instanceof _.PBRMaterial&&(Y.material.refractionTexture=ee._opaqueRenderTarget)})},ae.prototype.dispose=function(){this._scene._transmissionHelper=void 0,this._opaqueRenderTarget&&(this._opaqueRenderTarget.dispose(),this._opaqueRenderTarget=null),this._transparentMeshesCache=[],this._opaqueMeshesCache=[]},ae}(),w=function(){function ae(ee){this.name="KHR_materials_transmission",this.order=175,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_transmission"),this.enabled&&(ee.parent.transparencyAsCoverage=!0)}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialBasePropertiesAsync(ee,K,$)),oe.push(L._loader.loadMaterialPropertiesAsync(ee,K,$)),oe.push(L._loadTransparentPropertiesAsync(G,K,$,Q)),Promise.all(oe).then(function(){})})},ae.prototype._loadTransparentPropertiesAsync=function(ee,K,$,L){if(!($ instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");var G=$;if(G.subSurface.isRefractionEnabled=!0,G.subSurface.volumeIndexOfRefraction=1,G.subSurface.useAlbedoToTintRefraction=!0,L.transmissionFactor===void 0)return G.subSurface.refractionIntensity=0,G.subSurface.isRefractionEnabled=!1,Promise.resolve();G.subSurface.refractionIntensity=L.transmissionFactor;var Q=G.getScene();return G.subSurface.refractionIntensity&&!Q._transmissionHelper&&new D({},G.getScene()),L.transmissionTexture?(L.transmissionTexture.nonColorData=!0,this._loader.loadTextureInfoAsync(ee+"/transmissionTexture",L.transmissionTexture,void 0).then(function(oe){G.subSurface.thicknessTexture=oe,G.subSurface.useMaskFromThicknessTextureGltf=!0})):Promise.resolve()},ae}();C.b.RegisterExtension("KHR_materials_transmission",function(ae){return new w(ae)});var N=function(){function ae(ee){this.name="KHR_materials_translucency",this.order=175,this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_materials_translucency"),this.enabled&&(ee.parent.transparencyAsCoverage=!0)}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadMaterialPropertiesAsync=function(ee,K,$){var L=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return oe.push(L._loader.loadMaterialBasePropertiesAsync(ee,K,$)),oe.push(L._loader.loadMaterialPropertiesAsync(ee,K,$)),oe.push(L._loadTranslucentPropertiesAsync(G,K,$,Q)),Promise.all(oe).then(function(){})})},ae.prototype._loadTranslucentPropertiesAsync=function(ee,K,$,L){if(!($ instanceof _.PBRMaterial))throw new Error(ee+": Material type not supported");var G=$;return G.subSurface.isTranslucencyEnabled=!0,G.subSurface.volumeIndexOfRefraction=1,G.subSurface.minimumThickness=0,G.subSurface.maximumThickness=0,G.subSurface.useAlbedoToTintRefraction=!0,L.translucencyFactor===void 0?(G.subSurface.translucencyIntensity=0,G.subSurface.isTranslucencyEnabled=!1,Promise.resolve()):(G.subSurface.translucencyIntensity=L.translucencyFactor,L.translucencyTexture?this._loader.loadTextureInfoAsync(ee+"/translucencyTexture",L.translucencyTexture).then(function(Q){G.subSurface.thicknessTexture=Q,G.subSurface.useMaskFromThicknessTextureGltf=!0}):Promise.resolve())},ae}();C.b.RegisterExtension("KHR_materials_translucency",function(ae){return new N(ae)});var I=function(){function ae(ee){this.name="KHR_mesh_quantization",this.enabled=ee.isExtensionUsed("KHR_mesh_quantization")}return ae.prototype.dispose=function(){},ae}();C.b.RegisterExtension("KHR_mesh_quantization",function(ae){return new I(ae)});var V=function(){function ae(ee){this.name="KHR_texture_basisu",this._loader=ee,this.enabled=ee.isExtensionUsed("KHR_texture_basisu")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype._loadTextureAsync=function(ee,K,$){var L=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=K.sampler==null?C.b.DefaultSampler:C.a.Get(ee+"/sampler",L._loader.gltf.samplers,K.sampler),re=C.a.Get(G+"/source",L._loader.gltf.images,Q.source);return L._loader._createTextureAsync(ee,oe,re,function(Y){$(Y)},K._textureInfo.nonColorData?{useRGBAIfASTCBC7NotAvailableWhenUASTC:!0}:void 0)})},ae}();C.b.RegisterExtension("KHR_texture_basisu",function(ae){return new V(ae)});var X=function(){function ae(ee){this.name="KHR_texture_transform",this._loader=ee,this.enabled=this._loader.isExtensionUsed("KHR_texture_transform")}return ae.prototype.dispose=function(){this._loader=null},ae.prototype.loadTextureInfoAsync=function(ee,K,$){var L=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){return L._loader.loadTextureInfoAsync(ee,K,function(oe){if(!(oe instanceof _.Texture))throw new Error(G+": Texture type not supported");Q.offset&&(oe.uOffset=Q.offset[0],oe.vOffset=Q.offset[1]),oe.uRotationCenter=0,oe.vRotationCenter=0,Q.rotation&&(oe.wAng=-Q.rotation),Q.scale&&(oe.uScale=Q.scale[0],oe.vScale=Q.scale[1]),Q.texCoord!=null&&(oe.coordinatesIndex=Q.texCoord),$(oe)})})},ae}();C.b.RegisterExtension("KHR_texture_transform",function(ae){return new X(ae)});var j=function(){function ae(ee){this.name="MSFT_audio_emitter",this._loader=ee,this.enabled=this._loader.isExtensionUsed("MSFT_audio_emitter")}return ae.prototype.dispose=function(){this._loader=null,this._clips=null,this._emitters=null},ae.prototype.onLoading=function(){var ee=this._loader.gltf.extensions;if(ee&&ee[this.name]){var K=ee[this.name];this._clips=K.clips,this._emitters=K.emitters,C.a.Assign(this._clips),C.a.Assign(this._emitters)}},ae.prototype.loadSceneAsync=function(ee,K){var $=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(L,G){var Q=new Array;Q.push($._loader.loadSceneAsync(ee,K));for(var oe=0,re=G.emitters;oe<re.length;oe++){var Y=re[oe],k=C.a.Get(L+"/emitters",$._emitters,Y);if(k.refDistance!=null||k.maxDistance!=null||k.rolloffFactor!=null||k.distanceModel!=null||k.innerAngle!=null||k.outerAngle!=null)throw new Error(L+": Direction or Distance properties are not allowed on emitters attached to a scene");Q.push($._loadEmitterAsync(L+"/emitters/"+k.index,k))}return Promise.all(Q).then(function(){})})},ae.prototype.loadNodeAsync=function(ee,K,$){var L=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe=new Array;return L._loader.loadNodeAsync(G,K,function(re){for(var Y=function(Z){var W=C.a.Get(G+"/emitters",L._emitters,Z);oe.push(L._loadEmitterAsync(G+"/emitters/"+W.index,W).then(function(){for(var q=0,he=W._babylonSounds;q<he.length;q++){var ge=he[q];ge.attachToMesh(re),W.innerAngle==null&&W.outerAngle==null||(ge.setLocalDirectionToMesh(_.Vector3.Forward()),ge.setDirectionalCone(2*_.Tools.ToDegrees(W.innerAngle==null?Math.PI:W.innerAngle),2*_.Tools.ToDegrees(W.outerAngle==null?Math.PI:W.outerAngle),0))}}))},k=0,H=Q.emitters;k<H.length;k++)Y(H[k]);$(re)}).then(function(re){return Promise.all(oe).then(function(){return re})})})},ae.prototype.loadAnimationAsync=function(ee,K){var $=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(L,G){return $._loader.loadAnimationAsync(ee,K).then(function(Q){var oe=new Array;C.a.Assign(G.events);for(var re=0,Y=G.events;re<Y.length;re++){var k=Y[re];oe.push($._loadAnimationEventAsync(L+"/events/"+k.index,ee,K,k,Q))}return Promise.all(oe).then(function(){return Q})})})},ae.prototype._loadClipAsync=function(ee,K){if(K._objectURL)return K._objectURL;var $;if(K.uri)$=this._loader.loadUriAsync(ee,K,K.uri);else{var L=C.a.Get(ee+"/bufferView",this._loader.gltf.bufferViews,K.bufferView);$=this._loader.loadBufferViewAsync("/bufferViews/"+L.index,L)}return K._objectURL=$.then(function(G){return URL.createObjectURL(new Blob([G],{type:K.mimeType}))}),K._objectURL},ae.prototype._loadEmitterAsync=function(ee,K){var $=this;if(K._babylonSounds=K._babylonSounds||[],!K._babylonData){for(var L=new Array,G=K.name||"emitter"+K.index,Q={loop:!1,autoplay:!1,volume:K.volume==null?1:K.volume},oe=function(H){var Z="/extensions/"+re.name+"/clips",W=C.a.Get(Z,re._clips,K.clips[H].clip);L.push(re._loadClipAsync(Z+"/"+K.clips[H].clip,W).then(function(q){var he=K._babylonSounds[H]=new _.Sound(G,q,$._loader.babylonScene,null,Q);he.refDistance=K.refDistance||1,he.maxDistance=K.maxDistance||256,he.rolloffFactor=K.rolloffFactor||1,he.distanceModel=K.distanceModel||"exponential",he._positionInEmitterSpace=!0}))},re=this,Y=0;Y<K.clips.length;Y++)oe(Y);var k=Promise.all(L).then(function(){var H=K.clips.map(function(W){return W.weight||1}),Z=new _.WeightedSound(K.loop||!1,K._babylonSounds,H);K.innerAngle&&(Z.directionalConeInnerAngle=2*_.Tools.ToDegrees(K.innerAngle)),K.outerAngle&&(Z.directionalConeOuterAngle=2*_.Tools.ToDegrees(K.outerAngle)),K.volume&&(Z.volume=K.volume),K._babylonData.sound=Z});K._babylonData={loaded:k}}return K._babylonData.loaded},ae.prototype._getEventAction=function(ee,K,$,L,G){switch($){case"play":return function(Q){var oe=(G||0)+(Q-L);K.play(oe)};case"stop":return function(Q){K.stop()};case"pause":return function(Q){K.pause()};default:throw new Error(ee+": Unsupported action "+$)}},ae.prototype._loadAnimationEventAsync=function(ee,K,$,L,G){var Q=this;if(G.targetedAnimations.length==0)return Promise.resolve();var oe=G.targetedAnimations[0],re=L.emitter,Y=C.a.Get("/extensions/"+this.name+"/emitters",this._emitters,re);return this._loadEmitterAsync(ee,Y).then(function(){var k=Y._babylonData.sound;if(k){var H=new _.AnimationEvent(L.time,Q._getEventAction(ee,k,L.action,L.time,L.startOffset));oe.animation.addEvent(H),G.onAnimationGroupEndObservable.add(function(){k.stop()}),G.onAnimationGroupPauseObservable.add(function(){k.pause()})}})},ae}();C.b.RegisterExtension("MSFT_audio_emitter",function(ae){return new j(ae)});var ne=function(){function ae(ee){this.name="MSFT_lod",this.order=100,this.maxLODsToLoad=10,this.onNodeLODsLoadedObservable=new _.Observable,this.onMaterialLODsLoadedObservable=new _.Observable,this._bufferLODs=new Array,this._nodeIndexLOD=null,this._nodeSignalLODs=new Array,this._nodePromiseLODs=new Array,this._nodeBufferLODs=new Array,this._materialIndexLOD=null,this._materialSignalLODs=new Array,this._materialPromiseLODs=new Array,this._materialBufferLODs=new Array,this._loader=ee,this.enabled=this._loader.isExtensionUsed("MSFT_lod")}return ae.prototype.dispose=function(){this._loader=null,this._nodeIndexLOD=null,this._nodeSignalLODs.length=0,this._nodePromiseLODs.length=0,this._nodeBufferLODs.length=0,this._materialIndexLOD=null,this._materialSignalLODs.length=0,this._materialPromiseLODs.length=0,this._materialBufferLODs.length=0,this.onMaterialLODsLoadedObservable.clear(),this.onNodeLODsLoadedObservable.clear()},ae.prototype.onReady=function(){for(var ee=this,K=function(oe){var re=Promise.all($._nodePromiseLODs[oe]).then(function(){oe!==0&&(ee._loader.endPerformanceCounter("Node LOD "+oe),ee._loader.log("Loaded node LOD "+oe)),ee.onNodeLODsLoadedObservable.notifyObservers(oe),oe!==ee._nodePromiseLODs.length-1&&(ee._loader.startPerformanceCounter("Node LOD "+(oe+1)),ee._loadBufferLOD(ee._nodeBufferLODs,oe+1),ee._nodeSignalLODs[oe]&&ee._nodeSignalLODs[oe].resolve())});$._loader._completePromises.push(re)},$=this,L=0;L<this._nodePromiseLODs.length;L++)K(L);var G=function(oe){var re=Promise.all(Q._materialPromiseLODs[oe]).then(function(){oe!==0&&(ee._loader.endPerformanceCounter("Material LOD "+oe),ee._loader.log("Loaded material LOD "+oe)),ee.onMaterialLODsLoadedObservable.notifyObservers(oe),oe!==ee._materialPromiseLODs.length-1&&(ee._loader.startPerformanceCounter("Material LOD "+(oe+1)),ee._loadBufferLOD(ee._materialBufferLODs,oe+1),ee._materialSignalLODs[oe]&&ee._materialSignalLODs[oe].resolve())});Q._loader._completePromises.push(re)},Q=this;for(L=0;L<this._materialPromiseLODs.length;L++)G(L)},ae.prototype.loadSceneAsync=function(ee,K){var $=this._loader.loadSceneAsync(ee,K);return this._loadBufferLOD(this._bufferLODs,0),$},ae.prototype.loadNodeAsync=function(ee,K,$){var L=this;return C.b.LoadExtensionAsync(ee,K,this.name,function(G,Q){var oe,re=L._getLODs(G,K,L._loader.gltf.nodes,Q.ids);L._loader.logOpen(""+G);for(var Y=function(H){var Z=re[H];H!==0&&(L._nodeIndexLOD=H,L._nodeSignalLODs[H]=L._nodeSignalLODs[H]||new _.Deferred);var W=L._loader.loadNodeAsync("/nodes/"+Z.index,Z,function(q){q.setEnabled(!1)}).then(function(q){if(H!==0){var he=re[H-1];he._babylonTransformNode&&(L._disposeTransformNode(he._babylonTransformNode),delete he._babylonTransformNode)}return q.setEnabled(!0),q});L._nodePromiseLODs[H]=L._nodePromiseLODs[H]||[],H===0?oe=W:(L._nodeIndexLOD=null,L._nodePromiseLODs[H].push(W))},k=0;k<re.length;k++)Y(k);return L._loader.logClose(),oe})},ae.prototype._loadMaterialAsync=function(ee,K,$,L,G){var Q=this;return this._nodeIndexLOD?null:C.b.LoadExtensionAsync(ee,K,this.name,function(oe,re){var Y,k=Q._getLODs(oe,K,Q._loader.gltf.materials,re.ids);Q._loader.logOpen(""+oe);for(var H=function(W){var q=k[W];W!==0&&(Q._materialIndexLOD=W);var he=Q._loader._loadMaterialAsync("/materials/"+q.index,q,$,L,function(ge){W===0&&G(ge)}).then(function(ge){if(W!==0){G(ge);var me=k[W-1]._data;me[L]&&(Q._disposeMaterials([me[L].babylonMaterial]),delete me[L])}return ge});Q._materialPromiseLODs[W]=Q._materialPromiseLODs[W]||[],W===0?Y=he:(Q._materialIndexLOD=null,Q._materialPromiseLODs[W].push(he))},Z=0;Z<k.length;Z++)H(Z);return Q._loader.logClose(),Y})},ae.prototype._loadUriAsync=function(ee,K,$){var L=this;if(this._nodeIndexLOD!==null){this._loader.log("deferred");var G=this._nodeIndexLOD-1;return this._nodeSignalLODs[G]=this._nodeSignalLODs[G]||new _.Deferred,this._nodeSignalLODs[this._nodeIndexLOD-1].promise.then(function(){return L._loader.loadUriAsync(ee,K,$)})}return this._materialIndexLOD!==null?(this._loader.log("deferred"),G=this._materialIndexLOD-1,this._materialSignalLODs[G]=this._materialSignalLODs[G]||new _.Deferred,this._materialSignalLODs[G].promise.then(function(){return L._loader.loadUriAsync(ee,K,$)})):null},ae.prototype.loadBufferAsync=function(ee,K,$,L){if(this._loader.parent.useRangeRequests&&!K.uri){if(!this._loader.bin)throw new Error(ee+": Uri is missing or the binary glTF is missing its binary chunk");var G=function(Q,oe){var re=$,Y=re+L-1,k=Q[oe];return k?(k.start=Math.min(k.start,re),k.end=Math.max(k.end,Y)):(k={start:re,end:Y,loaded:new _.Deferred},Q[oe]=k),k.loaded.promise.then(function(H){return new Uint8Array(H.buffer,H.byteOffset+$-k.start,L)})};return this._loader.log("deferred"),this._nodeIndexLOD!==null?G(this._nodeBufferLODs,this._nodeIndexLOD):this._materialIndexLOD!==null?G(this._materialBufferLODs,this._materialIndexLOD):G(this._bufferLODs,0)}return null},ae.prototype._loadBufferLOD=function(ee,K){var $=ee[K];$&&(this._loader.log("Loading buffer range ["+$.start+"-"+$.end+"]"),this._loader.bin.readAsync($.start,$.end-$.start+1).then(function(L){$.loaded.resolve(L)},function(L){$.loaded.reject(L)}))},ae.prototype._getLODs=function(ee,K,$,L){if(this.maxLODsToLoad<=0)throw new Error("maxLODsToLoad must be greater than zero");for(var G=new Array,Q=L.length-1;Q>=0;Q--)if(G.push(C.a.Get(ee+"/ids/"+L[Q],$,L[Q])),G.length===this.maxLODsToLoad)return G;return 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st;if(st=te(W,q.jointNames[Pe])){for(je=0;je<lt.length;je++)if(lt[je].id===st.id){ge.bones.push(lt[je]);break}}}for(ge.prepare(),Pe=0;Pe<be.length;Pe++)ge.bones.push(be[Pe]);return ge},ae=function(W,q,he,ge,me){if(me||(W.scene._blockEntityCollection=W.forAssetContainer,me=new S.Mesh(q.name||"",W.scene),W.scene._blockEntityCollection=!1,me.id=ge),!q.babylonNode)return me;for(var _e,be=[],Pe=null,ye=new Array,Be=new Array,ke=new Array,We=new Array,je=0;je<he.length;je++){var He=he[je];if(tn=W.meshes[He])for(var qe=0;qe<tn.primitives.length;qe++){var Ge=new S.VertexData,nt=tn.primitives[qe];nt.mode;var $e=nt.attributes,lt=null,st=null;for(var mt in $e)if(lt=W.accessors[$e[mt]],st=g.GetBufferFromAccessor(W,lt),mt==="NORMAL")Ge.normals=new Float32Array(st.length),Ge.normals.set(st);else if(mt==="POSITION"){if(l.GLTFFileLoader.HomogeneousCoordinates){Ge.positions=new Float32Array(st.length-st.length/4);for(var St=0;St<st.length;St+=4)Ge.positions[St]=st[St],Ge.positions[St+1]=st[St+1],Ge.positions[St+2]=st[St+2]}else Ge.positions=new Float32Array(st.length),Ge.positions.set(st);Be.push(Ge.positions.length)}else if(mt.indexOf("TEXCOORD_")!==-1){var wt=Number(mt.split("_")[1]),It=S.VertexBuffer.UVKind+(wt===0?"":wt+1),Pt=new Float32Array(st.length);Pt.set(st),I(Pt),Ge.set(Pt,It)}else mt==="JOINT"?(Ge.matricesIndices=new Float32Array(st.length),Ge.matricesIndices.set(st)):mt==="WEIGHT"?(Ge.matricesWeights=new Float32Array(st.length),Ge.matricesWeights.set(st)):mt==="COLOR"&&(Ge.colors=new Float32Array(st.length),Ge.colors.set(st));if(lt=W.accessors[nt.indices])st=g.GetBufferFromAccessor(W,lt),Ge.indices=new Int32Array(st.length),Ge.indices.set(st),We.push(Ge.indices.length);else{var Ot=[];for(St=0;St<Ge.positions.length/3;St++)Ot.push(St);Ge.indices=new Int32Array(Ot),We.push(Ge.indices.length)}Pe?Pe.merge(Ge):Pe=Ge;var on=W.scene.getMaterialByID(nt.material);be.push(on===null?g.GetDefaultMaterial(W.scene):on),ye.push(ye.length===0?0:ye[ye.length-1]+Be[Be.length-2]),ke.push(ke.length===0?0:ke[ke.length-1]+We[We.length-2])}}W.scene._blockEntityCollection=W.forAssetContainer,be.length>1?(_e=new S.MultiMaterial("multimat"+ge,W.scene)).subMaterials=be:_e=new S.StandardMaterial("multimat"+ge,W.scene),be.length===1&&(_e=be[0]),me.material||(me.material=_e),new S.Geometry(ge,W.scene,Pe,!1,me),me.computeWorldMatrix(!0),W.scene._blockEntityCollection=!1,me.subMeshes=[];var Zt=0;for(je=0;je<he.length;je++){var tn;if(He=he[je],tn=W.meshes[He])for(qe=0;qe<tn.primitives.length;qe++)tn.primitives[qe].mode,S.SubMesh.AddToMesh(Zt,ye[Zt],Be[Zt],ke[Zt],We[Zt],me,me,!0),Zt++}return me},ee=function(W,q,he,ge){W.position&&(W.position=q),(W.rotationQuaternion||W.rotation)&&(W.rotationQuaternion=he),W.scaling&&(W.scaling=ge)},K=function(W,q,he,ge){var me=null;if(W.importOnlyMeshes&&(q.skin||q.meshes)&&W.importMeshesNames&&W.importMeshesNames.length>0&&W.importMeshesNames.indexOf(q.name||"")===-1)return null;if(q.skin){if(q.meshes){var _e=W.skins[q.skin];(be=ae(W,q,q.meshes,he,q.babylonNode)).skeleton=W.scene.getLastSkeletonByID(q.skin),be.skeleton===null&&(be.skeleton=pe(W,_e,0,_e.babylonSkeleton,q.skin),_e.babylonSkeleton||(_e.babylonSkeleton=be.skeleton)),me=be}}else if(q.meshes){var be;me=be=ae(W,q,q.mesh?[q.mesh]:q.meshes,he,q.babylonNode)}else if(!q.light||q.babylonNode||W.importOnlyMeshes){if(q.camera&&!q.babylonNode&&!W.importOnlyMeshes){var Pe=W.cameras[q.camera];if(Pe){if(W.scene._blockEntityCollection=W.forAssetContainer,Pe.type==="orthographic"){var ye=new S.FreeCamera(q.camera,S.Vector3.Zero(),W.scene,!1);ye.name=q.name||"",ye.mode=S.Camera.ORTHOGRAPHIC_CAMERA,ye.attachControl(),me=ye}else if(Pe.type==="perspective"){var Be=Pe[Pe.type],ke=new S.FreeCamera(q.camera,S.Vector3.Zero(),W.scene,!1);ke.name=q.name||"",ke.attachControl(),Be.aspectRatio||(Be.aspectRatio=W.scene.getEngine().getRenderWidth()/W.scene.getEngine().getRenderHeight()),Be.znear&&Be.zfar&&(ke.maxZ=Be.zfar,ke.minZ=Be.znear),me=ke}W.scene._blockEntityCollection=!1}}}else{var We=W.lights[q.light];if(We){if(We.type==="ambient"){var je=We[We.type],He=new S.HemisphericLight(q.light,S.Vector3.Zero(),W.scene);He.name=q.name||"",je.color&&(He.diffuse=S.Color3.FromArray(je.color)),me=He}else if(We.type==="directional"){var qe=We[We.type],Ge=new S.DirectionalLight(q.light,S.Vector3.Zero(),W.scene);Ge.name=q.name||"",qe.color&&(Ge.diffuse=S.Color3.FromArray(qe.color)),me=Ge}else if(We.type==="point"){var nt=We[We.type],$e=new S.PointLight(q.light,S.Vector3.Zero(),W.scene);$e.name=q.name||"",nt.color&&($e.diffuse=S.Color3.FromArray(nt.color)),me=$e}else if(We.type==="spot"){var lt=We[We.type],st=new S.SpotLight(q.light,S.Vector3.Zero(),S.Vector3.Zero(),0,0,W.scene);st.name=q.name||"",lt.color&&(st.diffuse=S.Color3.FromArray(lt.color)),lt.fallOfAngle&&(st.angle=lt.fallOfAngle),lt.fallOffExponent&&(st.exponent=lt.fallOffExponent),me=st}}}if(!q.jointName){if(q.babylonNode)return q.babylonNode;if(me===null){W.scene._blockEntityCollection=W.forAssetContainer;var mt=new S.Mesh(q.name||"",W.scene);W.scene._blockEntityCollection=!1,q.babylonNode=mt,me=mt}}if(me!==null){if(q.matrix&&me instanceof S.Mesh)(function(Pt,Ot,on){if(Ot.matrix){var Zt=new S.Vector3(0,0,0),tn=new S.Quaternion,De=new S.Vector3(0,0,0);S.Matrix.FromArray(Ot.matrix).decompose(De,tn,Zt),ee(Pt,Zt,tn,De)}else Ot.translation&&Ot.rotation&&Ot.scale&&ee(Pt,S.Vector3.FromArray(Ot.translation),S.Quaternion.FromArray(Ot.rotation),S.Vector3.FromArray(Ot.scale));Pt.computeWorldMatrix(!0)})(me,q);else{var St=q.translation||[0,0,0],wt=q.rotation||[0,0,0,1],It=q.scale||[1,1,1];ee(me,S.Vector3.FromArray(St),S.Quaternion.FromArray(wt),S.Vector3.FromArray(It))}me.updateCache(!0),q.babylonNode=me}return me},$=function(W,q,he,ge){ge===void 0&&(ge=!1);var me=W.nodes[q],_e=null;if(ge=!(W.importOnlyMeshes&&!ge&&W.importMeshesNames)||W.importMeshesNames.indexOf(me.name||"")!==-1||W.importMeshesNames.length===0,!me.jointName&&ge&&(_e=K(W,me,q))!==null&&(_e.id=q,_e.parent=he),me.children)for(var be=0;be<me.children.length;be++)$(W,me.children[be],_e,ge)},L=function(W){var q=W.currentScene;if(q)for(var he=0;he<q.nodes.length;he++)$(W,q.nodes[he],null);else for(var ge in W.scenes)for(q=W.scenes[ge],he=0;he<q.nodes.length;he++)$(W,q.nodes[he],null);for(function(_e){for(var be in _e.animations){var Pe=_e.animations[be];if(Pe.channels&&Pe.samplers)for(var ye=null,Be=0;Be<Pe.channels.length;Be++){var ke=Pe.channels[Be],We=Pe.samplers[ke.sampler];if(We){var je=null,He=null;Pe.parameters?(je=Pe.parameters[We.input],He=Pe.parameters[We.output]):(je=We.input,He=We.output);var qe=g.GetBufferFromAccessor(_e,_e.accessors[je]),Ge=g.GetBufferFromAccessor(_e,_e.accessors[He]),nt=ke.target.id,$e=_e.scene.getNodeByID(nt);if($e===null&&($e=_e.scene.getNodeByName(nt)),$e!==null){var lt=$e instanceof S.Bone,st=ke.target.path,mt=D.indexOf(st);mt!==-1&&(st=w[mt]);var St=S.Animation.ANIMATIONTYPE_MATRIX;lt||(st==="rotationQuaternion"?(St=S.Animation.ANIMATIONTYPE_QUATERNION,$e.rotationQuaternion=new S.Quaternion):St=S.Animation.ANIMATIONTYPE_VECTOR3);var wt=null,It=[],Pt=0,Ot=!1;lt&&ye&&ye.getKeys().length===qe.length&&(wt=ye,Ot=!0),Ot||(_e.scene._blockEntityCollection=_e.forAssetContainer,wt=new S.Animation(be,lt?"_matrix":st,1,St,S.Animation.ANIMATIONLOOPMODE_CYCLE),_e.scene._blockEntityCollection=!1);for(var on=0;on<qe.length;on++){var Zt=null;if(st==="rotationQuaternion"?(Zt=S.Quaternion.FromArray([Ge[Pt],Ge[Pt+1],Ge[Pt+2],Ge[Pt+3]]),Pt+=4):(Zt=S.Vector3.FromArray([Ge[Pt],Ge[Pt+1],Ge[Pt+2]]),Pt+=3),lt){var tn=$e,De=S.Vector3.Zero(),Pn=new S.Quaternion,nn=S.Vector3.Zero(),xn=tn.getBaseMatrix();Ot&&ye&&(xn=ye.getKeys()[on].value),xn.decompose(nn,Pn,De),st==="position"?De=Zt:st==="rotationQuaternion"?Pn=Zt:nn=Zt,Zt=S.Matrix.Compose(nn,Pn,De)}Ot?ye&&(ye.getKeys()[on].value=Zt):It.push({frame:qe[on],value:Zt})}!Ot&&wt&&(wt.setKeys(It),$e.animations.push(wt)),ye=wt,_e.scene.stopAnimation($e),_e.scene.beginAnimation($e,0,qe[qe.length-1],!0,1)}else S.Tools.Warn("Creating animation named "+be+". 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st=Be.scene.getNodeByName($e.source||$e.node||"");if(st===null&&(st=Be.scene.getNodeByID($e.source||$e.node||"")),st===null)continue;g.SetMatrix(Be.scene,st,$e,nt,We.getEffect())}}else g.SetMatrix(Be.scene,ye,$e,nt,We.getEffect());else{var mt=Ge[je.uniforms[nt]];if(!mt)continue;if(lt===u.SAMPLER_2D){var St=Be.textures[He.values?mt:$e.value].babylonTexture;if(St==null)continue;We.getEffect().setTexture(nt,St)}else g.SetUniform(We.getEffect(),nt,mt,lt)}}qe(We)})(Pe,W,me,q,he,ge,_e)}}},Q=function(W,q,he){for(var ge in q.uniforms){var me=q.uniforms[ge],_e=q.parameters[me];if(W.currentIdentifier===ge&&_e.semantic&&!_e.source&&!_e.node){var be=v.indexOf(_e.semantic);if(be!==-1)return delete he[ge],E[be]}}return W.currentIdentifier},oe=function(W){for(var q in W.materials)k.LoadMaterialAsync(W,q,function(he){},function(){})},re=function(){function W(){}return W.CreateRuntime=function(q,he,ge){var me={extensions:{},accessors:{},buffers:{},bufferViews:{},meshes:{},lights:{},cameras:{},nodes:{},images:{},textures:{},shaders:{},programs:{},samplers:{},techniques:{},materials:{},animations:{},skins:{},extensionsUsed:[],scenes:{},buffersCount:0,shaderscount:0,scene:he,rootUrl:ge,loadedBufferCount:0,loadedBufferViews:{},loadedShaderCount:0,importOnlyMeshes:!1,dummyNodes:[],forAssetContainer:!1};return q.extensions&&N(q.extensions,"extensions",me),q.extensionsUsed&&N(q.extensionsUsed,"extensionsUsed",me),q.buffers&&function(_e,be){for(var Pe in _e){var ye=_e[Pe];be.buffers[Pe]=ye,be.buffersCount++}}(q.buffers,me),q.bufferViews&&N(q.bufferViews,"bufferViews",me),q.accessors&&N(q.accessors,"accessors",me),q.meshes&&N(q.meshes,"meshes",me),q.lights&&N(q.lights,"lights",me),q.cameras&&N(q.cameras,"cameras",me),q.nodes&&N(q.nodes,"nodes",me),q.images&&N(q.images,"images",me),q.textures&&N(q.textures,"textures",me),q.shaders&&function(_e,be){for(var Pe in _e){var ye=_e[Pe];be.shaders[Pe]=ye,be.shaderscount++}}(q.shaders,me),q.programs&&N(q.programs,"programs",me),q.samplers&&N(q.samplers,"samplers",me),q.techniques&&N(q.techniques,"techniques",me),q.materials&&N(q.materials,"materials",me),q.animations&&N(q.animations,"animations",me),q.skins&&N(q.skins,"skins",me),q.scenes&&(me.scenes=q.scenes),q.scene&&q.scenes&&(me.currentScene=q.scenes[q.scene]),me},W.LoadBufferAsync=function(q,he,ge,me,_e){var be=q.buffers[he];S.Tools.IsBase64(be.uri)?setTimeout(function(){return ge(new Uint8Array(S.Tools.DecodeBase64(be.uri)))}):S.Tools.LoadFile(q.rootUrl+be.uri,function(Pe){return ge(new Uint8Array(Pe))},_e,void 0,!0,function(Pe){Pe&&me(Pe.status+" "+Pe.statusText)})},W.LoadTextureBufferAsync=function(q,he,ge,me){var _e=q.textures[he];if(_e&&_e.source)if(_e.babylonTexture)ge(null);else{var be=q.images[_e.source];S.Tools.IsBase64(be.uri)?setTimeout(function(){return ge(new 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ct.$$set=h=>{"value"in h&&Me(0,U=h.value),"clearColor"in h&&Me(7,_=h.clearColor),"label"in h&&Me(1,C=h.label),"show_label"in h&&Me(2,u=h.show_label),"$$scope"in h&&Me(11,f=h.$$scope)},ct.$$.update=()=>{ct.$$.dirty&8&&x("drag",m)},[U,C,u,m,c,M,R,_,y,g,l,f]}class rb extends al{constructor(Ke){super(),sl(this,Ke,ib,nb,cl,{value:0,clearColor:7,label:1,show_label:2})}}function ob(ct){let Ke,Me,y,f;return Ke=new fl({props:{show_label:ct[8],Icon:Ha,label:ct[7]||"3D Model"}}),y=new zv({props:{size:"large",unpadded_box:!0,$$slots:{default:[cb]},$$scope:{ctx:ct}}}),{c(){Hn(Ke.$$.fragment),Me=Jr(),Hn(y.$$.fragment)},m(U,_){Wn(Ke,U,_),Di(U,Me,_),Wn(y,U,_),f=!0},p(U,_){const C={};_&256&&(C.show_label=U[8]),_&128&&(C.label=U[7]||"3D Model"),Ke.$set(C);const u={};_&131072&&(u.$$scope={dirty:_,ctx:U}),y.$set(u)},i(U){f||(un(Ke.$$.fragment,U),un(y.$$.fragment,U),f=!0)},o(U){mn(Ke.$$.fragment,U),mn(y.$$.fragment,U),f=!1},d(U){Xn(Ke,U),U&&Li(Me),Xn(y,U)}}}function ab(ct){let Ke,Me;return Ke=new 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Ha({}),{c(){Hn(Ke.$$.fragment)},m(y,f){Wn(Ke,y,f),Me=!0},i(y){Me||(un(Ke.$$.fragment,y),Me=!0)},o(y){mn(Ke.$$.fragment,y),Me=!1},d(y){Xn(Ke,y)}}}function lb(ct){let Ke,Me;return Ke=new Yv({props:{type:"file"}}),{c(){Hn(Ke.$$.fragment)},m(y,f){Wn(Ke,y,f),Me=!0},p:Mf,i(y){Me||(un(Ke.$$.fragment,y),Me=!0)},o(y){mn(Ke.$$.fragment,y),Me=!1},d(y){Xn(Ke,y)}}}function ub(ct){let Ke,Me,y,f,U,_;const C=[ct[6]];let u={};for(let m=0;m<C.length;m+=1)u=Fv(u,C[m]);Ke=new Bv({props:u});const M=[sb,ab,ob],R=[];function x(m,c){return m[4]==="dynamic"?0:m[0]?1:2}return y=x(ct),f=R[y]=M[y](ct),{c(){Hn(Ke.$$.fragment),Me=Jr(),f.c(),U=ll()},m(m,c){Wn(Ke,m,c),Di(m,Me,c),R[y].m(m,c),Di(m,U,c),_=!0},p(m,c){const T=c&64?Uv(C,[Vv(m[6])]):{};Ke.$set(T);let A=y;y=x(m),y===A?R[y].p(m,c):(ul(),mn(R[A],1,1,()=>{R[A]=null}),hl(),f=R[y],f?f.p(m,c):(f=R[y]=M[y](m),f.c()),un(f,1),f.m(U.parentNode,U))},i(m){_||(un(Ke.$$.fragment,m),un(f),_=!0)},o(m){mn(Ke.$$.fragment,m),mn(f),_=!1},d(m){Xn(Ke,m),m&&Li(Me),R[y].d(m),m&&Li(U)}}}function hb(ct){let Ke,Me;return Ke=new Gv({props:{visible:ct[3],variant:ct[0]===null?"dashed":"solid",border_mode:ct[10]?"focus":"base",padding:!1,elem_id:ct[1],elem_classes:ct[2],$$slots:{default:[ub]},$$scope:{ctx:ct}}}),{c(){Hn(Ke.$$.fragment)},m(y,f){Wn(Ke,y,f),Me=!0},p(y,[f]){const U={};f&8&&(U.visible=y[3]),f&1&&(U.variant=y[0]===null?"dashed":"solid"),f&1024&&(U.border_mode=y[10]?"focus":"base"),f&2&&(U.elem_id=y[1]),f&4&&(U.elem_classes=y[2]),f&133105&&(U.$$scope={dirty:f,ctx:y}),Ke.$set(U)},i(y){Me||(un(Ke.$$.fragment,y),Me=!0)},o(y){mn(Ke.$$.fragment,y),Me=!1},d(y){Xn(Ke,y)}}}function db(ct,Ke,Me){let{elem_id:y=""}=Ke,{elem_classes:f=[]}=Ke,{visible:U=!0}=Ke,{value:_=null}=Ke,{mode:C}=Ke,{root:u}=Ke,{root_url:M}=Ke,{clearColor:R}=Ke,{loading_status:x}=Ke,{label:m}=Ke,{show_label:c}=Ke,T,A=!1;const S=({detail:v})=>Me(0,_=v),g=({detail:v})=>Me(10,A=v);function l(v){Pf.call(this,ct,v)}function h(v){Pf.call(this,ct,v)}return ct.$$set=v=>{"elem_id"in v&&Me(1,y=v.elem_id),"elem_classes"in v&&Me(2,f=v.elem_classes),"visible"in v&&Me(3,U=v.visible),"value"in v&&Me(0,_=v.value),"mode"in v&&Me(4,C=v.mode),"root"in v&&Me(11,u=v.root),"root_url"in v&&Me(12,M=v.root_url),"clearColor"in v&&Me(5,R=v.clearColor),"loading_status"in v&&Me(6,x=v.loading_status),"label"in v&&Me(7,m=v.label),"show_label"in v&&Me(8,c=v.show_label)},ct.$$.update=()=>{ct.$$.dirty&6145&&Me(9,T=kv(_,u,M))},[_,y,f,U,C,R,x,m,c,T,A,u,M,S,g,l,h]}class fb extends al{constructor(Ke){super(),sl(this,Ke,db,hb,cl,{elem_id:1,elem_classes:2,visible:3,value:0,mode:4,root:11,root_url:12,clearColor:5,loading_status:6,label:7,show_label:8})}}const Cb=fb,Rb=["static","dynamic"],Ob=ct=>({type:{payload:"{ name: string; data: string }"},description:{payload:"object with file name and base64 data"}});export{Cb as Component,Db as ExampleComponent,Ob as document,Rb as modes};
-//# sourceMappingURL=index-cc1acc6d.js.map
diff --git a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/huggingface_hub/templates/datasetcard_template.md b/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/huggingface_hub/templates/datasetcard_template.md
deleted file mode 100644
index 6d9281f9d3f119051b1eb7b2b016656b4dfa08fc..0000000000000000000000000000000000000000
--- a/spaces/ky2k/Toxicity_Classifier_POC/.venv/lib/python3.9/site-packages/huggingface_hub/templates/datasetcard_template.md
+++ /dev/null
@@ -1,103 +0,0 @@
----
-# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
-# Doc / guide: https://huggingface.co/docs/hub/datasets-cards
-{{ card_data }}
----
-
-# Dataset Card for {{ pretty_name | default("Dataset Name", true) }}
-
-## Dataset Description
-
-- **Homepage:** {{ homepage_url | default("", true)}}
-- **Repository:** {{ repo_url | default("", true)}}
-- **Paper:** {{ paper_url | default("", true)}}
-- **Leaderboard:** {{ leaderboard_url | default("", true)}}
-- **Point of Contact:** {{ point_of_contact | default("", true)}}
-
-### Dataset Summary
-
-{{ dataset_summary | default("[More Information Needed]", true)}}
-
-### Supported Tasks and Leaderboards
-
-{{ supported_tasks_and_leaderboards_section | default("[More Information Needed]", true)}}
-
-### Languages
-
-{{ languages_section | default("[More Information Needed]", true)}}
-
-## Dataset Structure
-
-### Data Instances
-
-{{ data_instances_section | default("[More Information Needed]", true)}}
-
-### Data Fields
-
-{{ data_fields_section | default("[More Information Needed]", true)}}
-
-### Data Splits
-
-{{ data_splits_section | default("[More Information Needed]", true)}}
-
-## Dataset Creation
-
-### Curation Rationale
-
-{{ curation_rationale_section | default("[More Information Needed]", true)}}
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-{{ data_collection_section | default("[More Information Needed]", true)}}
-
-#### Who are the source language producers?
-
-{{ source_language_producers_section | default("[More Information Needed]", true)}}
-
-### Annotations
-
-#### Annotation process
-
-{{ annotation_process_section | default("[More Information Needed]", true)}}
-
-#### Who are the annotators?
-
-{{ who_are_annotators_section | default("[More Information Needed]", true)}}
-
-### Personal and Sensitive Information
-
-{{ personal_and_sensitive_information_section | default("[More Information Needed]", true)}}
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-{{ social_impact_section | default("[More Information Needed]", true)}}
-
-### Discussion of Biases
-
-{{ discussion_of_biases_section | default("[More Information Needed]", true)}}
-
-### Other Known Limitations
-
-{{ known_limitations_section | default("[More Information Needed]", true)}}
-
-## Additional Information
-
-### Dataset Curators
-
-{{ dataset_curators_section | default("[More Information Needed]", true)}}
-
-### Licensing Information
-
-{{ licensing_information_section | default("[More Information Needed]", true)}}
-
-### Citation Information
-
-{{ citation_information_section | default("[More Information Needed]", true)}}
-
-### Contributions
-
-{{ contributions_section | default("[More Information Needed]", true)}}
diff --git a/spaces/latent-consistency/Real-Time-LCM-Text-to-Image-Lora-SD1.5/static/img2img.html b/spaces/latent-consistency/Real-Time-LCM-Text-to-Image-Lora-SD1.5/static/img2img.html
deleted file mode 100644
index 1534cfd3f01334c96bc858ceae8357992b0ca4ae..0000000000000000000000000000000000000000
--- a/spaces/latent-consistency/Real-Time-LCM-Text-to-Image-Lora-SD1.5/static/img2img.html
+++ /dev/null
@@ -1,383 +0,0 @@
-<!doctype html>
-<html>
-
-<head>
-    <meta charset="UTF-8">
-    <title>Real-Time Latent Consistency Model</title>
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <script
-        src="https://cdnjs.cloudflare.com/ajax/libs/iframe-resizer/4.3.1/iframeResizer.contentWindow.min.js"></script>
-    <script src="https://cdn.jsdelivr.net/npm/piexifjs@1.0.6/piexif.min.js"></script>
-    <script src="https://cdn.tailwindcss.com"></script>
-    <style type="text/tailwindcss">
-        .button {
-          @apply bg-gray-700 hover:bg-gray-800 text-white font-normal p-2 rounded disabled:bg-gray-300 dark:disabled:bg-gray-700 disabled:cursor-not-allowed dark:disabled:text-black
-        }
-    </style>
-    <script type="module">
-        const getValue = (id) => {
-            const el = document.querySelector(`${id}`)
-            if (el.type === "checkbox")
-                return el.checked;
-            return el.value;
-        }
-
-        const startBtn = document.querySelector("#start");
-        const stopBtn = document.querySelector("#stop");
-        const videoEl = document.querySelector("#webcam");
-        const imageEl = document.querySelector("#player");
-        const queueSizeEl = document.querySelector("#queue_size");
-        const errorEl = document.querySelector("#error");
-        const snapBtn = document.querySelector("#snap");
-        const webcamsEl = document.querySelector("#webcams");
-
-        function LCMLive(webcamVideo, liveImage) {
-            let websocket;
-
-            async function start() {
-                return new Promise((resolve, reject) => {
-                    const websocketURL = `${window.location.protocol === "https:" ? "wss" : "ws"
-                        }:${window.location.host}/ws`;
-
-                    const socket = new WebSocket(websocketURL);
-                    socket.onopen = () => {
-                        console.log("Connected to websocket");
-                    };
-                    socket.onclose = () => {
-                        console.log("Disconnected from websocket");
-                        stop();
-                        resolve({ "status": "disconnected" });
-                    };
-                    socket.onerror = (err) => {
-                        console.error(err);
-                        reject(err);
-                    };
-                    socket.onmessage = (event) => {
-                        const data = JSON.parse(event.data);
-                        switch (data.status) {
-                            case "success":
-                                break;
-                            case "start":
-                                const userId = data.userId;
-                                initVideoStream(userId);
-                                break;
-                            case "timeout":
-                                stop();
-                                resolve({ "status": "timeout" });
-                            case "error":
-                                stop();
-                                reject(data.message);
-
-                        }
-                    };
-                    websocket = socket;
-                })
-            }
-            function switchCamera() {
-                const constraints = {
-                    audio: false,
-                    video: { width: 1024, height: 1024, deviceId: mediaDevices[webcamsEl.value].deviceId }
-                };
-                navigator.mediaDevices
-                    .getUserMedia(constraints)
-                    .then((mediaStream) => {
-                        webcamVideo.removeEventListener("timeupdate", videoTimeUpdateHandler);
-                        webcamVideo.srcObject = mediaStream;
-                        webcamVideo.onloadedmetadata = () => {
-                            webcamVideo.play();
-                            webcamVideo.addEventListener("timeupdate", videoTimeUpdateHandler);
-                        };
-                    })
-                    .catch((err) => {
-                        console.error(`${err.name}: ${err.message}`);
-                    });
-            }
-
-            async function videoTimeUpdateHandler() {
-                const dimension = getValue("input[name=dimension]:checked");
-                const [WIDTH, HEIGHT] = JSON.parse(dimension);
-
-                const canvas = new OffscreenCanvas(WIDTH, HEIGHT);
-                const videoW = webcamVideo.videoWidth;
-                const videoH = webcamVideo.videoHeight;
-                const aspectRatio = WIDTH / HEIGHT;
-
-                const ctx = canvas.getContext("2d");
-                ctx.drawImage(webcamVideo, videoW / 2 - videoH * aspectRatio / 2, 0, videoH * aspectRatio, videoH, 0, 0, WIDTH, HEIGHT)
-                const blob = await canvas.convertToBlob({ type: "image/jpeg", quality: 1 });
-                websocket.send(blob);
-                websocket.send(JSON.stringify({
-                    "seed": getValue("#seed"),
-                    "prompt": getValue("#prompt"),
-                    "guidance_scale": getValue("#guidance-scale"),
-                    "strength": getValue("#strength"),
-                    "steps": getValue("#steps"),
-                    "lcm_steps": getValue("#lcm_steps"),
-                    "width": WIDTH,
-                    "height": HEIGHT,
-                }));
-            }
-            let mediaDevices = [];
-            async function initVideoStream(userId) {
-                liveImage.src = `/stream/${userId}`;
-                await navigator.mediaDevices.enumerateDevices()
-                    .then(devices => {
-                        const cameras = devices.filter(device => device.kind === 'videoinput');
-                        mediaDevices = cameras;
-                        webcamsEl.innerHTML = "";
-                        cameras.forEach((camera, index) => {
-                            const option = document.createElement("option");
-                            option.value = index;
-                            option.innerText = camera.label;
-                            webcamsEl.appendChild(option);
-                            option.selected = index === 0;
-                        });
-                        webcamsEl.addEventListener("change", switchCamera);
-                    })
-                    .catch(err => {
-                        console.error(err);
-                    });
-                const constraints = {
-                    audio: false,
-                    video: { width: 1024, height: 1024, deviceId: mediaDevices[0].deviceId }
-                };
-                navigator.mediaDevices
-                    .getUserMedia(constraints)
-                    .then((mediaStream) => {
-                        webcamVideo.srcObject = mediaStream;
-                        webcamVideo.onloadedmetadata = () => {
-                            webcamVideo.play();
-                            webcamVideo.addEventListener("timeupdate", videoTimeUpdateHandler);
-                        };
-                    })
-                    .catch((err) => {
-                        console.error(`${err.name}: ${err.message}`);
-                    });
-            }
-
-            async function stop() {
-                websocket.close();
-                navigator.mediaDevices.getUserMedia({ video: true }).then((mediaStream) => {
-                    mediaStream.getTracks().forEach((track) => track.stop());
-                });
-                webcamVideo.removeEventListener("timeupdate", videoTimeUpdateHandler);
-                webcamsEl.removeEventListener("change", switchCamera);
-                webcamVideo.srcObject = null;
-            }
-            return {
-                start,
-                stop
-            }
-        }
-        function toggleMessage(type) {
-            errorEl.hidden = false;
-            errorEl.scrollIntoView();
-            switch (type) {
-                case "error":
-                    errorEl.innerText = "To many users are using the same GPU, please try again later.";
-                    errorEl.classList.toggle("bg-red-300", "text-red-900");
-                    break;
-                case "success":
-                    errorEl.innerText = "Your session has ended, please start a new one.";
-                    errorEl.classList.toggle("bg-green-300", "text-green-900");
-                    break;
-            }
-            setTimeout(() => {
-                errorEl.hidden = true;
-            }, 2000);
-        }
-        function snapImage() {
-            try {
-                const zeroth = {};
-                const exif = {};
-                const gps = {};
-                zeroth[piexif.ImageIFD.Make] = "LCM Image-to-Image";
-                zeroth[piexif.ImageIFD.ImageDescription] = `prompt: ${getValue("#prompt")} | seed: ${getValue("#seed")} | guidance_scale: ${getValue("#guidance-scale")} | strength: ${getValue("#strength")} | lcm_steps: ${getValue("#lcm_steps")} | steps: ${getValue("#steps")}`;
-                zeroth[piexif.ImageIFD.Software] = "https://github.com/radames/Real-Time-Latent-Consistency-Model";
-
-                exif[piexif.ExifIFD.DateTimeOriginal] = new Date().toISOString();
-
-                const exifObj = { "0th": zeroth, "Exif": exif, "GPS": gps };
-                const exifBytes = piexif.dump(exifObj);
-
-                const canvas = document.createElement("canvas");
-                canvas.width = imageEl.naturalWidth;
-                canvas.height = imageEl.naturalHeight;
-                const ctx = canvas.getContext("2d");
-                ctx.drawImage(imageEl, 0, 0);
-                const dataURL = canvas.toDataURL("image/jpeg");
-                const withExif = piexif.insert(exifBytes, dataURL);
-
-                const a = document.createElement("a");
-                a.href = withExif;
-                a.download = `lcm_txt_2_img${Date.now()}.png`;
-                a.click();
-            } catch (err) {
-                console.log(err);
-            }
-        }
-
-
-        const lcmLive = LCMLive(videoEl, imageEl);
-        startBtn.addEventListener("click", async () => {
-            try {
-                startBtn.disabled = true;
-                snapBtn.disabled = false;
-                const res = await lcmLive.start();
-                startBtn.disabled = false;
-                if (res.status === "timeout")
-                    toggleMessage("success")
-            } catch (err) {
-                console.log(err);
-                toggleMessage("error")
-                startBtn.disabled = false;
-            }
-        });
-        stopBtn.addEventListener("click", () => {
-            lcmLive.stop();
-        });
-        window.addEventListener("beforeunload", () => {
-            lcmLive.stop();
-        });
-        snapBtn.addEventListener("click", snapImage);
-        setInterval(() =>
-            fetch("/queue_size")
-                .then((res) => res.json())
-                .then((data) => {
-                    queueSizeEl.innerText = data.queue_size;
-                })
-                .catch((err) => {
-                    console.log(err);
-                })
-            , 5000);
-    </script>
-</head>
-
-<body class="text-black dark:bg-gray-900 dark:text-white">
-    <div class="fixed right-2 top-2 p-4 font-bold text-sm rounded-lg max-w-xs text-center" id="error">
-    </div>
-    <main class="container mx-auto px-4 py-4 max-w-4xl flex flex-col gap-4">
-        <article class="text-center max-w-xl mx-auto">
-            <h1 class="text-3xl font-bold">Real-Time Latent Consistency Model</h1>
-            <h2 class="text-2xl font-bold mb-4">Image to Image</h2>
-            <p class="text-sm">
-                This demo showcases
-                <a href="https://huggingface.co/SimianLuo/LCM_Dreamshaper_v7" target="_blank"
-                    class="text-blue-500 underline hover:no-underline">LCM</a> Image to Image pipeline
-                using
-                <a href="https://github.com/huggingface/diffusers/tree/main/examples/community#latent-consistency-pipeline"
-                    target="_blank" class="text-blue-500 underline hover:no-underline">Diffusers</a> with a MJPEG
-                stream server.
-            </p>
-            <p class="text-sm">
-                There are <span id="queue_size" class="font-bold">0</span> user(s) sharing the same GPU, affecting
-                real-time performance. Maximum queue size is 4. <a
-                    href="https://huggingface.co/spaces/radames/Real-Time-Latent-Consistency-Model?duplicate=true"
-                    target="_blank" class="text-blue-500 underline hover:no-underline">Duplicate</a> and run it on your
-                own GPU.
-            </p>
-        </article>
-        <div>
-            <h2 class="font-medium">Prompt</h2>
-            <p class="text-sm text-gray-500">
-                Change the prompt to generate different images, accepts <a
-                    href="https://github.com/damian0815/compel/blob/main/doc/syntax.md" target="_blank"
-                    class="text-blue-500 underline hover:no-underline">Compel</a> syntax.
-            </p>
-            <div class="flex text-normal px-1 py-1 border border-gray-700 rounded-md items-center">
-                <textarea type="text" id="prompt" class="font-light w-full px-3 py-2 mx-1  outline-none dark:text-black"
-                    title="Prompt, this is an example, feel free to modify"
-                    placeholder="Add your prompt here...">Portrait of The Terminator with , glare pose, detailed, intricate, full of colour, cinematic lighting, trending on artstation, 8k, hyperrealistic, focused, extreme details, unreal engine 5, cinematic, masterpiece</textarea>
-            </div>
-
-        </div>
-        <div class="">
-            <details>
-                <summary class="font-medium cursor-pointer">Advanced Options</summary>
-                <div class="grid grid-cols-3 sm:grid-cols-6 items-center gap-3 py-3">
-                    <label for="webcams" class="text-sm font-medium">Camera Options: </label>
-                    <select id="webcams" class="text-sm border-2 border-gray-500 rounded-md font-light dark:text-black">
-                    </select>
-                    <div></div>
-                    <label class="text-sm font-medium " for="steps">Inference Steps
-                    </label>
-                    <input type="range" id="steps" name="steps" min="1" max="20" value="4"
-                        oninput="this.nextElementSibling.value = Number(this.value)">
-                    <output class="text-xs w-[50px] text-center font-light px-1 py-1 border border-gray-700 rounded-md">
-                        4</output>
-                    <!--  -->
-                    <label class="text-sm font-medium" for="lcm_steps">LCM Inference Steps
-                    </label>
-                    <input type="range" id="lcm_steps" name="lcm_steps" min="2" max="60" value="50"
-                        oninput="this.nextElementSibling.value = Number(this.value)">
-                    <output class="text-xs w-[50px] text-center font-light px-1 py-1 border border-gray-700 rounded-md">
-                        50</output>
-                    <!--  -->
-                    <label class="text-sm font-medium" for="guidance-scale">Guidance Scale
-                    </label>
-                    <input type="range" id="guidance-scale" name="guidance-scale" min="0" max="30" step="0.001"
-                        value="8.0" oninput="this.nextElementSibling.value = Number(this.value).toFixed(2)">
-                    <output class="text-xs w-[50px] text-center font-light px-1 py-1 border border-gray-700 rounded-md">
-                        8.0</output>
-                    <!--  -->
-                    <label class="text-sm font-medium" for="strength">Strength</label>
-                    <input type="range" id="strength" name="strength" min="0.1" max="1" step="0.001" value="0.50"
-                        oninput="this.nextElementSibling.value = Number(this.value).toFixed(2)">
-                    <output class="text-xs w-[50px] text-center font-light px-1 py-1 border border-gray-700 rounded-md">
-                        0.5</output>
-                    <!--  -->
-                    <label class="text-sm font-medium" for="seed">Seed</label>
-                    <input type="number" id="seed" name="seed" value="299792458"
-                        class="font-light border border-gray-700 text-right rounded-md p-2 dark:text-black">
-                    <button
-                        onclick="document.querySelector('#seed').value = Math.floor(Math.random() * Number.MAX_SAFE_INTEGER)"
-                        class="button">
-                        Rand
-                    </button>
-                    <!--  -->
-                    <!--  -->
-                    <label class="text-sm font-medium" for="dimension">Image Dimensions</label>
-                    <div class="col-span-2 flex gap-2">
-                        <div class="flex gap-1">
-                            <input type="radio" id="dimension512" name="dimension" value="[512,512]" checked
-                                class="cursor-pointer">
-                            <label for="dimension512" class="text-sm cursor-pointer">512x512</label>
-                        </div>
-                        <div class="flex gap-1">
-                            <input type="radio" id="dimension768" name="dimension" value="[768,768]"
-                                lass="cursor-pointer">
-                            <label for="dimension768" class="text-sm cursor-pointer">768x768</label>
-                        </div>
-                    </div>
-                    <!--  -->
-                </div>
-            </details>
-        </div>
-        <div class="flex gap-3">
-            <button id="start" class="button">
-                Start
-            </button>
-            <button id="stop" class="button">
-                Stop
-            </button>
-            <button id="snap" disabled class="button ml-auto">
-                Snapshot
-            </button>
-        </div>
-        <div class="relative rounded-lg border border-slate-300 overflow-hidden">
-            <img id="player" class="w-full aspect-square rounded-lg "
-                src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=">
-            <div class="absolute top-0 left-0 w-1/4 aspect-square">
-                <video id="webcam" class="w-full aspect-square relative z-10 object-cover" playsinline autoplay muted
-                    loop></video>
-                <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 448" width="100"
-                    class="w-full p-4 absolute top-0 opacity-20 z-0">
-                    <path fill="currentColor"
-                        d="M224 256a128 128 0 1 0 0-256 128 128 0 1 0 0 256zm-45.7 48A178.3 178.3 0 0 0 0 482.3 29.7 29.7 0 0 0 29.7 512h388.6a29.7 29.7 0 0 0 29.7-29.7c0-98.5-79.8-178.3-178.3-178.3h-91.4z" />
-                </svg>
-            </div>
-        </div>
-    </main>
-</body>
-
-</html>
\ No newline at end of file
diff --git a/spaces/leafShen/CodeFormer/CodeFormer/basicsr/archs/vqgan_arch.py b/spaces/leafShen/CodeFormer/CodeFormer/basicsr/archs/vqgan_arch.py
deleted file mode 100644
index f6dfcf4c9983b431f0a978701e5ddd9598faf381..0000000000000000000000000000000000000000
--- a/spaces/leafShen/CodeFormer/CodeFormer/basicsr/archs/vqgan_arch.py
+++ /dev/null
@@ -1,435 +0,0 @@
-'''
-VQGAN code, adapted from the original created by the Unleashing Transformers authors:
-https://github.com/samb-t/unleashing-transformers/blob/master/models/vqgan.py
-
-'''
-import numpy as np
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-import copy
-from basicsr.utils import get_root_logger
-from basicsr.utils.registry import ARCH_REGISTRY
-
-def normalize(in_channels):
-    return torch.nn.GroupNorm(num_groups=32, num_channels=in_channels, eps=1e-6, affine=True)
-    
-
-@torch.jit.script
-def swish(x):
-    return x*torch.sigmoid(x)
-
-
-#  Define VQVAE classes
-class VectorQuantizer(nn.Module):
-    def __init__(self, codebook_size, emb_dim, beta):
-        super(VectorQuantizer, self).__init__()
-        self.codebook_size = codebook_size  # number of embeddings
-        self.emb_dim = emb_dim  # dimension of embedding
-        self.beta = beta  # commitment cost used in loss term, beta * ||z_e(x)-sg[e]||^2
-        self.embedding = nn.Embedding(self.codebook_size, self.emb_dim)
-        self.embedding.weight.data.uniform_(-1.0 / self.codebook_size, 1.0 / self.codebook_size)
-
-    def forward(self, z):
-        # reshape z -> (batch, height, width, channel) and flatten
-        z = z.permute(0, 2, 3, 1).contiguous()
-        z_flattened = z.view(-1, self.emb_dim)
-
-        # distances from z to embeddings e_j (z - e)^2 = z^2 + e^2 - 2 e * z
-        d = (z_flattened ** 2).sum(dim=1, keepdim=True) + (self.embedding.weight**2).sum(1) - \
-            2 * torch.matmul(z_flattened, self.embedding.weight.t())
-
-        mean_distance = torch.mean(d)
-        # find closest encodings
-        # min_encoding_indices = torch.argmin(d, dim=1).unsqueeze(1)
-        min_encoding_scores, min_encoding_indices = torch.topk(d, 1, dim=1, largest=False)
-        # [0-1], higher score, higher confidence
-        min_encoding_scores = torch.exp(-min_encoding_scores/10)
-
-        min_encodings = torch.zeros(min_encoding_indices.shape[0], self.codebook_size).to(z)
-        min_encodings.scatter_(1, min_encoding_indices, 1)
-
-        # get quantized latent vectors
-        z_q = torch.matmul(min_encodings, self.embedding.weight).view(z.shape)
-        # compute loss for embedding
-        loss = torch.mean((z_q.detach()-z)**2) + self.beta * torch.mean((z_q - z.detach()) ** 2)
-        # preserve gradients
-        z_q = z + (z_q - z).detach()
-
-        # perplexity
-        e_mean = torch.mean(min_encodings, dim=0)
-        perplexity = torch.exp(-torch.sum(e_mean * torch.log(e_mean + 1e-10)))
-        # reshape back to match original input shape
-        z_q = z_q.permute(0, 3, 1, 2).contiguous()
-
-        return z_q, loss, {
-            "perplexity": perplexity,
-            "min_encodings": min_encodings,
-            "min_encoding_indices": min_encoding_indices,
-            "min_encoding_scores": min_encoding_scores,
-            "mean_distance": mean_distance
-            }
-
-    def get_codebook_feat(self, indices, shape):
-        # input indices: batch*token_num -> (batch*token_num)*1
-        # shape: batch, height, width, channel
-        indices = indices.view(-1,1)
-        min_encodings = torch.zeros(indices.shape[0], self.codebook_size).to(indices)
-        min_encodings.scatter_(1, indices, 1)
-        # get quantized latent vectors
-        z_q = torch.matmul(min_encodings.float(), self.embedding.weight)
-
-        if shape is not None:  # reshape back to match original input shape
-            z_q = z_q.view(shape).permute(0, 3, 1, 2).contiguous()
-
-        return z_q
-
-
-class GumbelQuantizer(nn.Module):
-    def __init__(self, codebook_size, emb_dim, num_hiddens, straight_through=False, kl_weight=5e-4, temp_init=1.0):
-        super().__init__()
-        self.codebook_size = codebook_size  # number of embeddings
-        self.emb_dim = emb_dim  # dimension of embedding
-        self.straight_through = straight_through
-        self.temperature = temp_init
-        self.kl_weight = kl_weight
-        self.proj = nn.Conv2d(num_hiddens, codebook_size, 1)  # projects last encoder layer to quantized logits
-        self.embed = nn.Embedding(codebook_size, emb_dim)
-
-    def forward(self, z):
-        hard = self.straight_through if self.training else True
-
-        logits = self.proj(z)
-
-        soft_one_hot = F.gumbel_softmax(logits, tau=self.temperature, dim=1, hard=hard)
-
-        z_q = torch.einsum("b n h w, n d -> b d h w", soft_one_hot, self.embed.weight)
-
-        # + kl divergence to the prior loss
-        qy = F.softmax(logits, dim=1)
-        diff = self.kl_weight * torch.sum(qy * torch.log(qy * self.codebook_size + 1e-10), dim=1).mean()
-        min_encoding_indices = soft_one_hot.argmax(dim=1)
-
-        return z_q, diff, {
-            "min_encoding_indices": min_encoding_indices
-        }
-
-
-class Downsample(nn.Module):
-    def __init__(self, in_channels):
-        super().__init__()
-        self.conv = torch.nn.Conv2d(in_channels, in_channels, kernel_size=3, stride=2, padding=0)
-
-    def forward(self, x):
-        pad = (0, 1, 0, 1)
-        x = torch.nn.functional.pad(x, pad, mode="constant", value=0)
-        x = self.conv(x)
-        return x
-
-
-class Upsample(nn.Module):
-    def __init__(self, in_channels):
-        super().__init__()
-        self.conv = nn.Conv2d(in_channels, in_channels, kernel_size=3, stride=1, padding=1)
-
-    def forward(self, x):
-        x = F.interpolate(x, scale_factor=2.0, mode="nearest")
-        x = self.conv(x)
-
-        return x
-
-
-class ResBlock(nn.Module):
-    def __init__(self, in_channels, out_channels=None):
-        super(ResBlock, self).__init__()
-        self.in_channels = in_channels
-        self.out_channels = in_channels if out_channels is None else out_channels
-        self.norm1 = normalize(in_channels)
-        self.conv1 = nn.Conv2d(in_channels, out_channels, kernel_size=3, stride=1, padding=1)
-        self.norm2 = normalize(out_channels)
-        self.conv2 = nn.Conv2d(out_channels, out_channels, kernel_size=3, stride=1, padding=1)
-        if self.in_channels != self.out_channels:
-            self.conv_out = nn.Conv2d(in_channels, out_channels, kernel_size=1, stride=1, padding=0)
-
-    def forward(self, x_in):
-        x = x_in
-        x = self.norm1(x)
-        x = swish(x)
-        x = self.conv1(x)
-        x = self.norm2(x)
-        x = swish(x)
-        x = self.conv2(x)
-        if self.in_channels != self.out_channels:
-            x_in = self.conv_out(x_in)
-
-        return x + x_in
-
-
-class AttnBlock(nn.Module):
-    def __init__(self, in_channels):
-        super().__init__()
-        self.in_channels = in_channels
-
-        self.norm = normalize(in_channels)
-        self.q = torch.nn.Conv2d(
-            in_channels,
-            in_channels,
-            kernel_size=1,
-            stride=1,
-            padding=0
-        )
-        self.k = torch.nn.Conv2d(
-            in_channels,
-            in_channels,
-            kernel_size=1,
-            stride=1,
-            padding=0
-        )
-        self.v = torch.nn.Conv2d(
-            in_channels,
-            in_channels,
-            kernel_size=1,
-            stride=1,
-            padding=0
-        )
-        self.proj_out = torch.nn.Conv2d(
-            in_channels,
-            in_channels,
-            kernel_size=1,
-            stride=1,
-            padding=0
-        )
-
-    def forward(self, x):
-        h_ = x
-        h_ = self.norm(h_)
-        q = self.q(h_)
-        k = self.k(h_)
-        v = self.v(h_)
-
-        # compute attention
-        b, c, h, w = q.shape
-        q = q.reshape(b, c, h*w)
-        q = q.permute(0, 2, 1)   
-        k = k.reshape(b, c, h*w)
-        w_ = torch.bmm(q, k) 
-        w_ = w_ * (int(c)**(-0.5))
-        w_ = F.softmax(w_, dim=2)
-
-        # attend to values
-        v = v.reshape(b, c, h*w)
-        w_ = w_.permute(0, 2, 1) 
-        h_ = torch.bmm(v, w_)
-        h_ = h_.reshape(b, c, h, w)
-
-        h_ = self.proj_out(h_)
-
-        return x+h_
-
-
-class Encoder(nn.Module):
-    def __init__(self, in_channels, nf, emb_dim, ch_mult, num_res_blocks, resolution, attn_resolutions):
-        super().__init__()
-        self.nf = nf
-        self.num_resolutions = len(ch_mult)
-        self.num_res_blocks = num_res_blocks
-        self.resolution = resolution
-        self.attn_resolutions = attn_resolutions
-
-        curr_res = self.resolution
-        in_ch_mult = (1,)+tuple(ch_mult)
-
-        blocks = []
-        # initial convultion
-        blocks.append(nn.Conv2d(in_channels, nf, kernel_size=3, stride=1, padding=1))
-
-        # residual and downsampling blocks, with attention on smaller res (16x16)
-        for i in range(self.num_resolutions):
-            block_in_ch = nf * in_ch_mult[i]
-            block_out_ch = nf * ch_mult[i]
-            for _ in range(self.num_res_blocks):
-                blocks.append(ResBlock(block_in_ch, block_out_ch))
-                block_in_ch = block_out_ch
-                if curr_res in attn_resolutions:
-                    blocks.append(AttnBlock(block_in_ch))
-
-            if i != self.num_resolutions - 1:
-                blocks.append(Downsample(block_in_ch))
-                curr_res = curr_res // 2
-
-        # non-local attention block
-        blocks.append(ResBlock(block_in_ch, block_in_ch))
-        blocks.append(AttnBlock(block_in_ch))
-        blocks.append(ResBlock(block_in_ch, block_in_ch))
-
-        # normalise and convert to latent size
-        blocks.append(normalize(block_in_ch))
-        blocks.append(nn.Conv2d(block_in_ch, emb_dim, kernel_size=3, stride=1, padding=1))
-        self.blocks = nn.ModuleList(blocks)
-
-    def forward(self, x):
-        for block in self.blocks:
-            x = block(x)
-            
-        return x
-
-
-class Generator(nn.Module):
-    def __init__(self, nf, emb_dim, ch_mult, res_blocks, img_size, attn_resolutions):
-        super().__init__()
-        self.nf = nf 
-        self.ch_mult = ch_mult 
-        self.num_resolutions = len(self.ch_mult)
-        self.num_res_blocks = res_blocks
-        self.resolution = img_size 
-        self.attn_resolutions = attn_resolutions
-        self.in_channels = emb_dim
-        self.out_channels = 3
-        block_in_ch = self.nf * self.ch_mult[-1]
-        curr_res = self.resolution // 2 ** (self.num_resolutions-1)
-
-        blocks = []
-        # initial conv
-        blocks.append(nn.Conv2d(self.in_channels, block_in_ch, kernel_size=3, stride=1, padding=1))
-
-        # non-local attention block
-        blocks.append(ResBlock(block_in_ch, block_in_ch))
-        blocks.append(AttnBlock(block_in_ch))
-        blocks.append(ResBlock(block_in_ch, block_in_ch))
-
-        for i in reversed(range(self.num_resolutions)):
-            block_out_ch = self.nf * self.ch_mult[i]
-
-            for _ in range(self.num_res_blocks):
-                blocks.append(ResBlock(block_in_ch, block_out_ch))
-                block_in_ch = block_out_ch
-
-                if curr_res in self.attn_resolutions:
-                    blocks.append(AttnBlock(block_in_ch))
-
-            if i != 0:
-                blocks.append(Upsample(block_in_ch))
-                curr_res = curr_res * 2
-
-        blocks.append(normalize(block_in_ch))
-        blocks.append(nn.Conv2d(block_in_ch, self.out_channels, kernel_size=3, stride=1, padding=1))
-
-        self.blocks = nn.ModuleList(blocks)
-   
-
-    def forward(self, x):
-        for block in self.blocks:
-            x = block(x)
-            
-        return x
-
-  
-@ARCH_REGISTRY.register()
-class VQAutoEncoder(nn.Module):
-    def __init__(self, img_size, nf, ch_mult, quantizer="nearest", res_blocks=2, attn_resolutions=[16], codebook_size=1024, emb_dim=256,
-                beta=0.25, gumbel_straight_through=False, gumbel_kl_weight=1e-8, model_path=None):
-        super().__init__()
-        logger = get_root_logger()
-        self.in_channels = 3 
-        self.nf = nf 
-        self.n_blocks = res_blocks 
-        self.codebook_size = codebook_size
-        self.embed_dim = emb_dim
-        self.ch_mult = ch_mult
-        self.resolution = img_size
-        self.attn_resolutions = attn_resolutions
-        self.quantizer_type = quantizer
-        self.encoder = Encoder(
-            self.in_channels,
-            self.nf,
-            self.embed_dim,
-            self.ch_mult,
-            self.n_blocks,
-            self.resolution,
-            self.attn_resolutions
-        )
-        if self.quantizer_type == "nearest":
-            self.beta = beta #0.25
-            self.quantize = VectorQuantizer(self.codebook_size, self.embed_dim, self.beta)
-        elif self.quantizer_type == "gumbel":
-            self.gumbel_num_hiddens = emb_dim
-            self.straight_through = gumbel_straight_through
-            self.kl_weight = gumbel_kl_weight
-            self.quantize = GumbelQuantizer(
-                self.codebook_size,
-                self.embed_dim,
-                self.gumbel_num_hiddens,
-                self.straight_through,
-                self.kl_weight
-            )
-        self.generator = Generator(
-            self.nf, 
-            self.embed_dim,
-            self.ch_mult, 
-            self.n_blocks, 
-            self.resolution, 
-            self.attn_resolutions
-        )
-
-        if model_path is not None:
-            chkpt = torch.load(model_path, map_location='cpu')
-            if 'params_ema' in chkpt:
-                self.load_state_dict(torch.load(model_path, map_location='cpu')['params_ema'])
-                logger.info(f'vqgan is loaded from: {model_path} [params_ema]')
-            elif 'params' in chkpt:
-                self.load_state_dict(torch.load(model_path, map_location='cpu')['params'])
-                logger.info(f'vqgan is loaded from: {model_path} [params]')
-            else:
-                raise ValueError(f'Wrong params!')
-
-
-    def forward(self, x):
-        x = self.encoder(x)
-        quant, codebook_loss, quant_stats = self.quantize(x)
-        x = self.generator(quant)
-        return x, codebook_loss, quant_stats
-
-
-
-# patch based discriminator
-@ARCH_REGISTRY.register()
-class VQGANDiscriminator(nn.Module):
-    def __init__(self, nc=3, ndf=64, n_layers=4, model_path=None):
-        super().__init__()
-
-        layers = [nn.Conv2d(nc, ndf, kernel_size=4, stride=2, padding=1), nn.LeakyReLU(0.2, True)]
-        ndf_mult = 1
-        ndf_mult_prev = 1
-        for n in range(1, n_layers):  # gradually increase the number of filters
-            ndf_mult_prev = ndf_mult
-            ndf_mult = min(2 ** n, 8)
-            layers += [
-                nn.Conv2d(ndf * ndf_mult_prev, ndf * ndf_mult, kernel_size=4, stride=2, padding=1, bias=False),
-                nn.BatchNorm2d(ndf * ndf_mult),
-                nn.LeakyReLU(0.2, True)
-            ]
-
-        ndf_mult_prev = ndf_mult
-        ndf_mult = min(2 ** n_layers, 8)
-
-        layers += [
-            nn.Conv2d(ndf * ndf_mult_prev, ndf * ndf_mult, kernel_size=4, stride=1, padding=1, bias=False),
-            nn.BatchNorm2d(ndf * ndf_mult),
-            nn.LeakyReLU(0.2, True)
-        ]
-
-        layers += [
-            nn.Conv2d(ndf * ndf_mult, 1, kernel_size=4, stride=1, padding=1)]  # output 1 channel prediction map
-        self.main = nn.Sequential(*layers)
-
-        if model_path is not None:
-            chkpt = torch.load(model_path, map_location='cpu')
-            if 'params_d' in chkpt:
-                self.load_state_dict(torch.load(model_path, map_location='cpu')['params_d'])
-            elif 'params' in chkpt:
-                self.load_state_dict(torch.load(model_path, map_location='cpu')['params'])
-            else:
-                raise ValueError(f'Wrong params!')
-
-    def forward(self, x):
-        return self.main(x)
\ No newline at end of file
diff --git a/spaces/lincquiQcaudo/Top-20-Diffusion/Download Kis Kisko Pyaar Karoon Full Movie Kickass Download.md b/spaces/lincquiQcaudo/Top-20-Diffusion/Download Kis Kisko Pyaar Karoon Full Movie Kickass Download.md
deleted file mode 100644
index b901705d80f0f1e98f2fa16393e609998dfe43ef..0000000000000000000000000000000000000000
--- a/spaces/lincquiQcaudo/Top-20-Diffusion/Download Kis Kisko Pyaar Karoon Full Movie Kickass Download.md	
+++ /dev/null
@@ -1,31 +0,0 @@
-<br />
-<h1>How to Download Kis Kisko Pyaar Karoon Full Movie Kickass Download</h1>
-<p>Kis Kisko Pyaar Karoon is a 2015 Bollywood comedy-romance film starring Kapil Sharma, Elli Avram, Manjari Fadnnis, Simran Kaur Mundi, Sai Lokur, Arbaaz Khan and Varun Sharma. The film is directed by Abbas-Mustan and produced by Ratan Jain, Ganesh Jain and Abbas-Mustan. The film revolves around a married man who tries to juggle his three wives and his girlfriend without letting them know about each other.</p>
-<h2>download Kis Kisko Pyaar Karoon full movie kickass download</h2><br /><p><b><b>Download Zip</b> &hArr; <a href="https://bytlly.com/2uGy5G">https://bytlly.com/2uGy5G</a></b></p><br /><br />
-<p>If you are looking for a fun and entertaining movie to watch with your friends or family, then Kis Kisko Pyaar Karoon is a good choice. But how can you download Kis Kisko Pyaar Karoon full movie kickass download? Here are some tips and tricks to help you out.</p>
-<h2>Download Kis Kisko Pyaar Karoon Full Movie from Streaming Platforms</h2>
-<p>One of the easiest and legal ways to download Kis Kisko Pyaar Karoon full movie kickass download is to use streaming platforms that offer offline viewing options. Some of the popular streaming platforms that have Kis Kisko Pyaar Karoon in their library are:</p>
-<ul>
-<li>Amazon Prime Video: You can watch Kis Kisko Pyaar Karoon on Amazon Prime Video with a subscription. You can also download the movie on your device for offline viewing. To do so, you need to open the Amazon Prime Video app on your device, search for Kis Kisko Pyaar Karoon, tap on the download icon and choose the quality you want. The movie will be downloaded to your device and you can watch it anytime without internet connection.</li>
-<li>Google Play Movies: You can buy or rent Kis Kisko Pyaar Karoon on Google Play Movies and watch it online or offline. To download the movie on your device, you need to open the Google Play Movies app on your device, search for Kis Kisko Pyaar Karoon, tap on the buy or rent button and choose the quality you want. The movie will be downloaded to your device and you can watch it anytime without internet connection.</li>
-<li>YouTube: You can also buy or rent Kis Kisko Pyaar Karoon on YouTube and watch it online or offline. To download the movie on your device, you need to open the YouTube app on your device, search for Kis Kisko Pyaar Karoon, tap on the buy or rent button and choose the quality you want. The movie will be downloaded to your device and you can watch it anytime without internet connection.</li>
-<li>Apple TV: You can also buy or rent Kis Kisko Pyaar Karoon on Apple TV and watch it online or offline. To download the movie on your device, you need to open the Apple TV app on your device, search for Kis Kisko Pyaar Karoon, tap on the buy or rent button and choose the quality you want. The movie will be downloaded to your device and you can watch it anytime without internet connection.</li>
-</ul>
-<h2>Download Kis Kisko Pyaar Karoon Full Movie from Torrent Sites</h2>
-<p>Another way to download Kis Kisko Pyaar Karoon full movie kickass download is to use torrent sites that offer peer-to-peer file sharing. However, this method is not recommended as it may involve legal risks and malware threats. Torrent sites are often blocked by ISPs and governments due to copyright infringement issues. Moreover, torrent files may contain viruses or spyware that can harm your device or compromise your privacy.</p>
-<p>If you still want to use torrent sites to download Kis Kisko Pyaar Karoon full movie kickass download, then you need to follow these steps:</p>
-<ol>
-<li>Download and install a VPN software on your device. A VPN software will help you bypass geo-restrictions and access blocked torrent sites. It will also encrypt your traffic and protect your identity online.</li>
-<li>Download and install a torrent client software on your device. A torrent client software will help you download torrent files from torrent sites. Some of the popular torrent client software are uTorrent, BitTorrent, qBittorrent, etc.</li>
-<li>Search for Kis Kisko Pyaar Karoon full movie kickass download on torrent sites. Some of the popular torrent sites are The Pirate Bay, Kickass Torrents, 1337x, etc. However, these sites may change their domain names frequently due to legal issues.</li>
-<li>Select a torrent file that has high seeders and leechers. Seeders are users who have downloaded the file and are sharing it with others. Leechers are users who are downloading the file from seeders. A high number of seeders and leechers indicates that the file is popular and reliable.</li>
-<li>Open the torrent file with your torrent client software and start downloading the movie. The download speed may vary depending on your internet connection and the number of seeders and leechers.</li>
-<li>Once the download is complete, you can watch Kis Kisko Pyaar Karoon full movie kickass download on your device using a media player software.</li>
-</ol>
-<h2>Conclusion</h2>
-<p>Kis Kisko Pyaar Karoon is a hilarious comedy-romance film that will make you laugh out loud. If you want to watch this movie offline, then you can either use streaming platforms that offer offline viewing options or use torrent sites that offer peer-to-peer file sharing. However, streaming platforms are safer and more legal than torrent sites. So, choose wisely and enjoy watching Kis Kisko Pyaar Karoon full movie kickass download.</p>
-<p></p>
-<h2>Conclusion</h2>
-<p>Kis Kisko Pyaar Karoon is a hilarious comedy-romance film that will make you laugh out loud. If you want to watch this movie offline, then you can either use streaming platforms that offer offline viewing options or use torrent sites that offer peer-to-peer file sharing. However, streaming platforms are safer and more legal than torrent sites. So, choose wisely and enjoy watching Kis Kisko Pyaar Karoon full movie kickass download.</p> 3cee63e6c2<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/lincquiQcaudo/Top-20-Diffusion/Holiday Full Movie 2014 Akshay Kumar 1080p Projectors NEW!.md b/spaces/lincquiQcaudo/Top-20-Diffusion/Holiday Full Movie 2014 Akshay Kumar 1080p Projectors NEW!.md
deleted file mode 100644
index 213922b95b68dce40dddccb56cdf69c88060a01a..0000000000000000000000000000000000000000
--- a/spaces/lincquiQcaudo/Top-20-Diffusion/Holiday Full Movie 2014 Akshay Kumar 1080p Projectors NEW!.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>holiday full movie 2014 akshay kumar 1080p projectors</h2><br /><p><b><b>Download Zip</b> &gt;&gt;&gt; <a href="https://bytlly.com/2uGx5N">https://bytlly.com/2uGx5N</a></b></p><br /><br />
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-<br />
-<br />
-<p></p>
diff --git a/spaces/lithiumice/SadTalker/src/face3d/models/arcface_torch/eval/__init__.py b/spaces/lithiumice/SadTalker/src/face3d/models/arcface_torch/eval/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/lizhen30/LangChainGo/openai_agent.py b/spaces/lizhen30/LangChainGo/openai_agent.py
deleted file mode 100644
index 3a6a27a909eccc792a8756b14726378b4e367de3..0000000000000000000000000000000000000000
--- a/spaces/lizhen30/LangChainGo/openai_agent.py
+++ /dev/null
@@ -1,25 +0,0 @@
-from langchain.agents import load_tools
-from langchain.agents import initialize_agent
-from langchain.agents import AgentType
-from langchain.llms import OpenAI
-from langchain.callbacks import get_openai_callback
-
-# First, let's load the language model we're going to use to control the agent.
-llm = OpenAI(temperature=0)
-
-# Next, let's load some tools to use. Note that the `llm-math` tool uses an LLM, so we need to pass that in.
-tools = load_tools(["serpapi", "llm-math"], llm=llm)
-
-
-# Finally, let's initialize an agent with the tools, the language model, and the type of agent we want to use.
-agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)
-
-# Now let's test it out!
-agent.run("昨天北京气温如何?")
-
-with get_openai_callback() as cb:
-    response = agent.run("Who is Olivia Wilde's boyfriend? What is his current age raised to the 0.23 power?")
-    print(f"Total Tokens: {cb.total_tokens}")
-    print(f"Prompt Tokens: {cb.prompt_tokens}")
-    print(f"Completion Tokens: {cb.completion_tokens}")
-    print(f"Total Cost (USD): ${cb.total_cost}")
\ No newline at end of file
diff --git a/spaces/ma-xu/LIVE/setup.py b/spaces/ma-xu/LIVE/setup.py
deleted file mode 100644
index fdb9f6735b7adb7684bc72cbcb74c4284afd4119..0000000000000000000000000000000000000000
--- a/spaces/ma-xu/LIVE/setup.py
+++ /dev/null
@@ -1,98 +0,0 @@
-# Adapted from https://github.com/pybind/cmake_example/blob/master/setup.py
-import os
-import re
-import sys
-import platform
-import subprocess
-import importlib
-from sysconfig import get_paths
-
-import importlib
-from setuptools import setup, Extension
-from setuptools.command.build_ext import build_ext
-from setuptools.command.install import install
-from distutils.sysconfig import get_config_var
-from distutils.version import LooseVersion
-
-class CMakeExtension(Extension):
-    def __init__(self, name, sourcedir, build_with_cuda):
-        Extension.__init__(self, name, sources=[])
-        self.sourcedir = os.path.abspath(sourcedir)
-        self.build_with_cuda = build_with_cuda
-
-class Build(build_ext):
-    def run(self):
-        try:
-            out = subprocess.check_output(['cmake', '--version'])
-        except OSError:
-            raise RuntimeError("CMake must be installed to build the following extensions: " +
-                               ", ".join(e.name for e in self.extensions))
-
-        super().run()
-
-    def build_extension(self, ext):
-        if isinstance(ext, CMakeExtension):
-            extdir = os.path.abspath(os.path.dirname(self.get_ext_fullpath(ext.name)))
-            info = get_paths()
-            include_path = info['include']
-            cmake_args = ['-DCMAKE_LIBRARY_OUTPUT_DIRECTORY=' + extdir,
-                          '-DPYTHON_INCLUDE_PATH=' + include_path]
-
-            cfg = 'Debug' if self.debug else 'Release'
-            build_args = ['--config', cfg]
-
-            if platform.system() == "Windows":
-                cmake_args += ['-DCMAKE_LIBRARY_OUTPUT_DIRECTORY_{}={}'.format(cfg.upper(), extdir),
-                               '-DCMAKE_RUNTIME_OUTPUT_DIRECTORY_{}={}'.format(cfg.upper(), extdir)]
-                if sys.maxsize > 2**32:
-                    cmake_args += ['-A', 'x64']
-                build_args += ['--', '/m']
-            else:
-                cmake_args += ['-DCMAKE_BUILD_TYPE=' + cfg]
-                build_args += ['--', '-j8']
-
-            if ext.build_with_cuda:
-                cmake_args += ['-DDIFFVG_CUDA=1']
-            else:
-                cmake_args += ['-DDIFFVG_CUDA=0']
-
-            env = os.environ.copy()
-            env['CXXFLAGS'] = '{} -DVERSION_INFO=\\"{}\\"'.format(env.get('CXXFLAGS', ''),
-                                                                  self.distribution.get_version())
-            if not os.path.exists(self.build_temp):
-                os.makedirs(self.build_temp)
-            subprocess.check_call(['cmake', ext.sourcedir] + cmake_args, cwd=self.build_temp, env=env)
-            subprocess.check_call(['cmake', '--build', '.'] + build_args, cwd=self.build_temp)
-        else:
-            super().build_extension(ext)
-
-torch_spec = importlib.util.find_spec("torch")
-tf_spec = importlib.util.find_spec("tensorflow")
-packages = []
-build_with_cuda = False
-if torch_spec is not None:
-    packages.append('pydiffvg')
-    import torch
-    if torch.cuda.is_available():
-        build_with_cuda = True
-if tf_spec is not None and sys.platform != 'win32':
-    packages.append('pydiffvg_tensorflow')
-    if not build_with_cuda:
-        import tensorflow as tf
-        if tf.test.is_gpu_available(cuda_only=True, min_cuda_compute_capability=None):
-            build_with_cuda = True
-if len(packages) == 0:
-    print('Error: PyTorch or Tensorflow must be installed. For Windows platform only PyTorch is supported.')
-    exit()
-# Override build_with_cuda with environment variable
-if 'DIFFVG_CUDA' in os.environ:
-    build_with_cuda = os.environ['DIFFVG_CUDA'] == '1'
-
-setup(name = 'diffvg',
-      version = '0.0.1',
-      install_requires = ["svgpathtools"],
-      description = 'Differentiable Vector Graphics',
-      ext_modules = [CMakeExtension('diffvg', '', build_with_cuda)],
-      cmdclass = dict(build_ext=Build, install=install),
-      packages = packages,
-      zip_safe = False)
diff --git a/spaces/ma-xu/LIVE/thrust/dependencies/cub/examples/block/Makefile b/spaces/ma-xu/LIVE/thrust/dependencies/cub/examples/block/Makefile
deleted file mode 100644
index b173c2a02f2c77b8b6f51546e2ed422d2d02d4d2..0000000000000000000000000000000000000000
--- a/spaces/ma-xu/LIVE/thrust/dependencies/cub/examples/block/Makefile
+++ /dev/null
@@ -1,128 +0,0 @@
-#/******************************************************************************
-# * Copyright (c) 2011, Duane Merrill.  All rights reserved.
-# * Copyright (c) 2011-2018, NVIDIA CORPORATION.  All rights reserved.
-# * 
-# * Redistribution and use in source and binary forms, with or without
-# * modification, are permitted provided that the following conditions are met:
-# *	 * Redistributions of source code must retain the above copyright
-# *	   notice, this list of conditions and the following disclaimer.
-# *	 * Redistributions in binary form must reproduce the above copyright
-# *	   notice, this list of conditions and the following disclaimer in the
-# *	   documentation and/or other materials provided with the distribution.
-# *	 * Neither the name of the NVIDIA CORPORATION nor the
-# *	   names of its contributors may be used to endorse or promote products
-# *	   derived from this software without specific prior written permission.
-# * 
-# * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
-# * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
-# * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
-# * DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY
-# * DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
-# * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
-# * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
-# * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
-# * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
-# * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-# *
-#******************************************************************************/
-
-#-------------------------------------------------------------------------------
-#
-# Makefile usage
-#
-# make <target> [sm=<XXX,...>] [cdp=<0|1>] [force32=<0|1>] [abi=<0|1>] [open64=<0|1>] [verbose=<0|1>] [keep=<0|1>]
-#
-#-------------------------------------------------------------------------------
- 
-include ../../common.mk 
- 
- 
-#-------------------------------------------------------------------------------
-# Includes
-#-------------------------------------------------------------------------------
-
-INC += -I$(CUB_DIR) -I$(CUB_DIR)test 
-
-
-
-#-------------------------------------------------------------------------------
-# Dependency Lists
-#-------------------------------------------------------------------------------
-
-rwildcard=$(foreach d,$(wildcard $1*),$(call rwildcard,$d/,$2) $(filter $(subst *,%,$2),$d))
-
-DEPS =				$(CUB_DEPS) \
-					$(CUB_DIR)test/Makefile \
-					$(CUB_DIR)test/test_util.h \
-					$(CUB_DIR)test/mersenne.h \
-		
-ALL = 	example_block_radix_sort \
-	 	example_block_reduce \
-	 	example_block_scan
-		
-
-
-#-------------------------------------------------------------------------------
-# make default
-#-------------------------------------------------------------------------------
-
-default:
-
-
-#-------------------------------------------------------------------------------
-# make clean
-#-------------------------------------------------------------------------------
-
-clean :
-	rm -f bin/*$(CPU_ARCH_SUFFIX)* 
-	rm -f *.i* *.cubin *.cu.c *.cudafe* *.fatbin.c *.ptx *.hash *.cu.cpp *.o
-
-
-#-------------------------------------------------------------------------------
-# make all
-#-------------------------------------------------------------------------------
-
-all : $(ALL)
-
-#-------------------------------------------------------------------------------
-# make run
-#-------------------------------------------------------------------------------
-
-run : 
-	for i in $(ALL); do ./bin/$${i}_$(BIN_SUFFIX) --device=$(device) || exit 1; done
-
-
-
-
-#-------------------------------------------------------------------------------
-# make example_block_reduce
-#-------------------------------------------------------------------------------
-
-example_block_reduce: bin/example_block_reduce_$(BIN_SUFFIX)
-
-bin/example_block_reduce_$(BIN_SUFFIX) : example_block_reduce.cu $(DEPS)
-	mkdir -p bin
-	$(NVCC) $(DEFINES) $(SM_TARGETS) -o bin/example_block_reduce_$(BIN_SUFFIX) example_block_reduce.cu $(NVCCFLAGS) $(CPU_ARCH) $(INC) $(LIBS) -O3
-
-
-#-------------------------------------------------------------------------------
-# make example_block_scan
-#-------------------------------------------------------------------------------
-
-example_block_scan: bin/example_block_scan_$(BIN_SUFFIX)
-
-bin/example_block_scan_$(BIN_SUFFIX) : example_block_scan.cu $(DEPS)
-	mkdir -p bin
-	$(NVCC) $(DEFINES) $(SM_TARGETS) -o bin/example_block_scan_$(BIN_SUFFIX) example_block_scan.cu $(NVCCFLAGS) $(CPU_ARCH) $(INC) $(LIBS) -O3
-
-
-#-------------------------------------------------------------------------------
-# make example_block_radix_sort
-#-------------------------------------------------------------------------------
-
-example_block_radix_sort: bin/example_block_radix_sort_$(BIN_SUFFIX)
-
-bin/example_block_radix_sort_$(BIN_SUFFIX) : example_block_radix_sort.cu $(DEPS)
-	mkdir -p bin
-	$(NVCC) $(DEFINES) $(SM_TARGETS) -o bin/example_block_radix_sort_$(BIN_SUFFIX) example_block_radix_sort.cu $(NVCCFLAGS) $(CPU_ARCH) $(INC) $(LIBS) -O3
-	
diff --git a/spaces/ma-xu/LIVE/thrust/thrust/system/detail/generic/count.h b/spaces/ma-xu/LIVE/thrust/thrust/system/detail/generic/count.h
deleted file mode 100644
index 218369e386e18219906a043171b4a99c489a643a..0000000000000000000000000000000000000000
--- a/spaces/ma-xu/LIVE/thrust/thrust/system/detail/generic/count.h
+++ /dev/null
@@ -1,51 +0,0 @@
-/*
- *  Copyright 2008-2013 NVIDIA Corporation
- *
- *  Licensed under the Apache License, Version 2.0 (the "License");
- *  you may not use this file except in compliance with the License.
- *  You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- *  Unless required by applicable law or agreed to in writing, software
- *  distributed under the License is distributed on an "AS IS" BASIS,
- *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- *  See the License for the specific language governing permissions and
- *  limitations under the License.
- */
-
-
-#pragma once
-
-#include <thrust/detail/config.h>
-#include <thrust/system/detail/generic/tag.h>
-
-namespace thrust
-{
-namespace system
-{
-namespace detail
-{
-namespace generic
-{
-
-
-template <typename DerivedPolicy, typename InputIterator, typename EqualityComparable>
-__host__ __device__
-typename thrust::iterator_traits<InputIterator>::difference_type
-count(thrust::execution_policy<DerivedPolicy> &exec, InputIterator first, InputIterator last, const EqualityComparable& value);
-
-
-template <typename DerivedPolicy, typename InputIterator, typename Predicate>
-__host__ __device__
-typename thrust::iterator_traits<InputIterator>::difference_type
-count_if(thrust::execution_policy<DerivedPolicy> &exec, InputIterator first, InputIterator last, Predicate pred);
-
-
-} // end namespace generic
-} // end namespace detail
-} // end namespace system
-} // end namespace thrust
-
-#include <thrust/system/detail/generic/count.inl>
-
diff --git a/spaces/ma-xu/LIVE/thrust/thrust/system/system_error.h b/spaces/ma-xu/LIVE/thrust/thrust/system/system_error.h
deleted file mode 100644
index 84e453dc662832acd28687126fc2a5f2a7db3d7a..0000000000000000000000000000000000000000
--- a/spaces/ma-xu/LIVE/thrust/thrust/system/system_error.h
+++ /dev/null
@@ -1,179 +0,0 @@
-/*
- *  Copyright 2008-2013 NVIDIA Corporation
- *
- *  Licensed under the Apache License, Version 2.0 (the "License");
- *  you may not use this file except in compliance with the License.
- *  You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- *  Unless required by applicable law or agreed to in writing, software
- *  distributed under the License is distributed on an "AS IS" BASIS,
- *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- *  See the License for the specific language governing permissions and
- *  limitations under the License.
- */
-
-
-/*! \file system/system_error.h
- *  \brief An exception object used to report error conditions that have an
- *         associated error code
- */
-
-#pragma once
-
-#include <thrust/detail/config.h>
-#include <stdexcept>
-#include <string>
-
-#include <thrust/system/error_code.h>
-
-namespace thrust
-{
-
-namespace system
-{
-
-// [19.5.5] Class system_error
-
-// [19.5.5.1] Class system_error overview
-
-/*! \addtogroup system_diagnostics System Diagnostics
- *  \ingroup system
- *  \{
- */
-
-/*! \brief The class \p system_error describes an exception object used to report error
- *  conditions that have an associated \p error_code. Such error conditions typically
- *  originate from the operating system or other low-level application program interfaces.
- *
- *  Thrust uses \p system_error to report the error codes returned from device backends
- *  such as the CUDA runtime.
- *
- *  The following code listing demonstrates how to catch a \p system_error to recover
- *  from an error.
- *
- *  \code
- *
- *  #include <thrust/device_vector.h>
- *  #include <thrust/system.h>
- *  #include <thrust/sort.h>
- *
- *  void terminate_gracefully(void)
- *  {
- *    // application-specific termination code here
- *    ...
- *  }
- *
- *  int main(void)
- *  {
- *    try
- *    {
- *      thrust::device_vector<float> vec;
- *      thrust::sort(vec.begin(), vec.end());
- *    }
- *    catch(thrust::system_error e)
- *    {
- *      std::cerr << "Error inside sort: " << e.what() << std::endl;
- *      terminate_gracefully();
- *    }
- *
- *    return 0;
- *  }
- *
- *  \endcode
- *
- *  \note If an error represents an out-of-memory condition, implementations are encouraged
- *  to throw an exception object of type \p std::bad_alloc rather than \p system_error.
- */
-class system_error
-  : public std::runtime_error
-{
-  public:
-    // [19.5.5.2] Class system_error members
-    
-    /*! Constructs an object of class \p system_error.
-     *  \param ec The value returned by \p code().
-     *  \param what_arg A string to include in the result returned by \p what().
-     *  \post <tt>code() == ec</tt>.
-     *  \post <tt>std::string(what()).find(what_arg) != string::npos</tt>.
-     */
-    inline system_error(error_code ec, const std::string &what_arg);
-
-    /*! Constructs an object of class \p system_error.
-     *  \param ec The value returned by \p code().
-     *  \param what_arg A string to include in the result returned by \p what().
-     *  \post <tt>code() == ec</tt>.
-     *  \post <tt>std::string(what()).find(what_arg) != string::npos</tt>.
-     */
-    inline system_error(error_code ec, const char *what_arg);
-
-    /*! Constructs an object of class \p system_error.
-     *  \param ec The value returned by \p code().
-     *  \post <tt>code() == ec</tt>.
-     */
-    inline system_error(error_code ec);
-
-    /*! Constructs an object of class \p system_error.
-     *  \param ev The error value used to create an \p error_code.
-     *  \param ecat The \p error_category used to create an \p error_code.
-     *  \param what_arg A string to include in the result returned by \p what().
-     *  \post <tt>code() == error_code(ev, ecat)</tt>.
-     *  \post <tt>std::string(what()).find(what_arg) != string::npos</tt>.
-     */
-    inline system_error(int ev, const error_category &ecat, const std::string &what_arg);
-
-    /*! Constructs an object of class \p system_error.
-     *  \param ev The error value used to create an \p error_code.
-     *  \param ecat The \p error_category used to create an \p error_code.
-     *  \param what_arg A string to include in the result returned by \p what().
-     *  \post <tt>code() == error_code(ev, ecat)</tt>.
-     *  \post <tt>std::string(what()).find(what_arg) != string::npos</tt>.
-     */
-    inline system_error(int ev, const error_category &ecat, const char *what_arg);
-
-    /*! Constructs an object of class \p system_error.
-     *  \param ev The error value used to create an \p error_code.
-     *  \param ecat The \p error_category used to create an \p error_code.
-     *  \post <tt>code() == error_code(ev, ecat)</tt>.
-     */
-    inline system_error(int ev, const error_category &ecat);
-
-    /*! Destructor does not throw.
-     */
-    inline virtual ~system_error(void) throw () {};
-    
-    /*! Returns an object encoding the error.
-     *  \return <tt>ec</tt> or <tt>error_code(ev, ecat)</tt>, from the
-     *          constructor, as appropriate.
-     */
-    inline const error_code &code(void) const throw();
-
-    /*! Returns a human-readable string indicating the nature of the error.
-     *  \return a string incorporating <tt>code().message()</tt> and the
-     *          arguments supplied in the constructor.
-     */
-    inline const char *what(void) const throw();
-
-    /*! \cond
-     */
-  private:
-    error_code          m_error_code;
-    mutable std::string m_what;
-
-    /*! \endcond
-     */
-}; // end system_error
-
-} // end system
-
-/*! \} // end system_diagnostics
- */
-
-// import names into thrust::
-using system::system_error;
-
-} // end thrust
-
-#include <thrust/system/detail/system_error.inl>
-
diff --git a/spaces/magicr/BuboGPT/bubogpt/datasets/builders/audio_image_text_builder.py b/spaces/magicr/BuboGPT/bubogpt/datasets/builders/audio_image_text_builder.py
deleted file mode 100644
index 246913cfa0c61e27c58722353316f37a049d2490..0000000000000000000000000000000000000000
--- a/spaces/magicr/BuboGPT/bubogpt/datasets/builders/audio_image_text_builder.py
+++ /dev/null
@@ -1,105 +0,0 @@
-import logging
-import os
-import warnings
-
-from bubogpt.common.registry import registry
-from bubogpt.datasets.builders.multimodal_base_dataset_builder import MultimodalBaseDatasetBuilder
-from bubogpt.datasets.datasets.audio_image.audio_image_datasets import AudioLocalizationDataset, AudioImageNegDataset
-
-
-@registry.register_builder("vggss_align")
-class VGGSSBuilderAudioImage(MultimodalBaseDatasetBuilder):
-    train_dataset_cls = AudioLocalizationDataset
-
-    DATASET_CONFIG_DICT = {
-        "default": "configs/datasets/vggss/align.yaml",
-        "3k": "configs/datasets/vggss/align3k.yaml",
-        "5k": "configs/datasets/vggss/align5k.yaml",
-        "31k": "configs/datasets/vggss/align31k.yaml",
-    }
-
-    def build_datasets(self):
-        # at this point, all the annotations and image/videos should be all downloaded to the specified locations.
-        logging.info("Building datasets...")
-        self.build_processors()
-
-        build_info = self.config.build_info
-        storage_path = build_info.storage
-
-        datasets = dict()
-
-        if not os.path.exists(storage_path):
-            warnings.warn("storage path {} does not exist.".format(storage_path))
-        print("Building datasets with: ", self.get_ann_files())
-
-        # create datasets
-        dataset_cls = self.train_dataset_cls
-        datasets['train'] = dataset_cls(
-            processors={**{
-                modal: self.processors[modal]["train"] for modal in self.data_type
-            }, **{
-                "text": self.processors["text"]["train"]
-            }},
-            roots={
-                modal: os.path.join(storage_path, f"{modal}s") for modal in self.data_type
-            },
-            # ann_paths=[os.path.join(storage_path, 'vggsound_balanced.json')],
-            ann_paths=self.get_ann_files(),
-        )
-
-        return datasets
-
-    def get_ann_files(self):
-        ann_files = self.config.build_info.get("ann_files", ["vggsound_balanced.json"])
-        return [os.path.join(self.config.build_info.storage, fname) for fname in ann_files]
-
-
-@registry.register_builder("aud_img_neg")
-class NegBuilderAudioImage(MultimodalBaseDatasetBuilder):
-    train_dataset_cls = AudioImageNegDataset
-
-    DATASET_CONFIG_DICT = {
-        "default": "configs/datasets/aud_img_neg/default.yaml",
-    }
-
-    def build_datasets(self):
-        # at this point, all the annotations and image/videos should be all downloaded to the specified locations.
-        logging.info("Building datasets...")
-        self.build_processors()
-
-        build_info = self.config.build_info
-        # storage_path = build_info.storage
-        storage_path = {
-            "image": build_info.image.storage,
-            "audio": build_info.audio.storage,
-        }
-        ann_files = {
-            "image": build_info.image.ann_files,
-            "audio": build_info.audio.ann_files,
-        }
-        ann_paths = {
-            modal: [os.path.join(storage_path[modal], fname) for fname in ann_files[modal]] for modal in self.data_type
-        }
-
-        datasets = dict()
-
-        for path in storage_path.values():
-            if not os.path.exists(path):
-                warnings.warn("storage path {} does not exist.".format(path))
-        print("Building datasets with: ", ann_paths)
-
-        # create datasets
-        dataset_cls = self.train_dataset_cls
-        datasets['train'] = dataset_cls(
-            processors={**{
-                modal: self.processors[modal]["train"] for modal in self.data_type
-            }, **{
-                "text": self.processors["text"]["train"]
-            }},
-            roots={
-                modal: os.path.join(storage_path[modal], f"{modal}") for modal in self.data_type
-            },
-            ann_paths=ann_paths,
-        )
-
-        return datasets
diff --git a/spaces/manhkhanhUIT/Image_Restoration_Colorization/Global/detection_models/__init__.py b/spaces/manhkhanhUIT/Image_Restoration_Colorization/Global/detection_models/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/marcoruizrueda/flax-midjourney-v4-diffusion/app.py b/spaces/marcoruizrueda/flax-midjourney-v4-diffusion/app.py
deleted file mode 100644
index 364c6a6661f1bc587f1f388fb6378a9798d3f94f..0000000000000000000000000000000000000000
--- a/spaces/marcoruizrueda/flax-midjourney-v4-diffusion/app.py
+++ /dev/null
@@ -1,7 +0,0 @@
-import gradio as gr
-
-import os
-
-os.system('pip install --upgrade pip')
-
-gr.Interface.load("models/flax/midjourney-v4-diffusion").launch()
\ No newline at end of file
diff --git a/spaces/marlenezw/audio-driven-animations/MakeItTalk/src/dataset/utils/icp.py b/spaces/marlenezw/audio-driven-animations/MakeItTalk/src/dataset/utils/icp.py
deleted file mode 100644
index 5fcf851e18c61f9a09dd28080531828d0025e98d..0000000000000000000000000000000000000000
--- a/spaces/marlenezw/audio-driven-animations/MakeItTalk/src/dataset/utils/icp.py
+++ /dev/null
@@ -1,142 +0,0 @@
-"""
- # Copyright 2020 Adobe
- # All Rights Reserved.
- 
- # NOTICE: Adobe permits you to use, modify, and distribute this file in
- # accordance with the terms of the Adobe license agreement accompanying
- # it.
- 
-"""
-
-import numpy as np
-from sklearn.neighbors import NearestNeighbors
-
-
-def best_fit_transform(A, B):
-    '''
-    Calculates the least-squares best-fit transform that maps corresponding points A to B in m spatial dimensions
-    Input:
-      A: Nxm numpy array of corresponding points
-      B: Nxm numpy array of corresponding points
-    Returns:
-      T: (m+1)x(m+1) homogeneous transformation matrix that maps A on to B
-      R: mxm rotation matrix
-      t: mx1 translation vector
-    '''
-
-    assert A.shape == B.shape
-
-    # get number of dimensions
-    m = A.shape[1]
-
-    # translate points to their centroids
-    centroid_A = np.mean(A, axis=0)
-    centroid_B = np.mean(B, axis=0)
-    AA = A - centroid_A
-    BB = B - centroid_B
-
-    # rotation matrix
-    H = np.dot(AA.T, BB)
-    U, S, Vt = np.linalg.svd(H)
-    R = np.dot(Vt.T, U.T)
-
-    # special reflection case
-    if np.linalg.det(R) < 0:
-       Vt[m-1,:] *= -1
-       R = np.dot(Vt.T, U.T)
-
-    # translation
-    t = centroid_B.T - np.dot(R,centroid_A.T)
-
-    # Step added for scalar (deprecated)
-    p_deno = np.sum(AA**2, axis=0)
-    y_nume = np.sum(BB**2, axis=0)
-    s = np.identity(m+1)
-    s[:m, :m] = s[:m, :m] * (y_nume / p_deno) ** 0.25
-
-    # homogeneous transformation
-    T = np.identity(m+1)
-    T[:m, :m] = R
-    T[:m, m] = t
-
-    # Step : (Deprecated for Scalar)
-    # T = np.dot(s, T)
-
-    return T, R, t
-
-
-def nearest_neighbor(src, dst):
-    '''
-    Find the nearest (Euclidean) neighbor in dst for each point in src
-    Input:
-        src: Nxm array of points
-        dst: Nxm array of points
-    Output:
-        distances: Euclidean distances of the nearest neighbor
-        indices: dst indices of the nearest neighbor
-    '''
-
-    assert src.shape == dst.shape
-
-    neigh = NearestNeighbors(n_neighbors=1)
-    neigh.fit(dst)
-    distances, indices = neigh.kneighbors(src, return_distance=True)
-    return distances.ravel(), indices.ravel()
-
-
-def icp(A, B, init_pose=None, max_iterations=50, tolerance=0.0001):
-    '''
-    The Iterative Closest Point method: finds best-fit transform that maps points A on to points B
-    Input:
-        A: Nxm numpy array of source mD points
-        B: Nxm numpy array of destination mD point
-        init_pose: (m+1)x(m+1) homogeneous transformation
-        max_iterations: exit algorithm after max_iterations
-        tolerance: convergence criteria
-    Output:
-        T: final homogeneous transformation that maps A on to B
-        distances: Euclidean distances (errors) of the nearest neighbor
-        i: number of iterations to converge
-    '''
-
-    assert A.shape == B.shape
-
-    # get number of dimensions
-    m = A.shape[1]
-
-    # make points homogeneous, copy them to maintain the originals
-    src = np.ones((m+1,A.shape[0]))
-    dst = np.ones((m+1,B.shape[0]))
-    src[:m,:] = np.copy(A.T)
-    dst[:m,:] = np.copy(B.T)
-
-    # apply the initial pose estimation
-    if init_pose is not None:
-        src = np.dot(init_pose, src)
-
-    prev_error = 0
-
-    for i in range(max_iterations):
-        # # find the nearest neighbors between the current source and destination points
-        # distances, indices = nearest_neighbor(src[:m,:].T, dst[:m,:].T)
-        #
-        # # compute the transformation between the current source and nearest destination points
-        # T,_,_ = best_fit_transform(src[:m,:].T, dst[:m,indices].T)
-
-        # Step x : just for our T-shape transform, we don'n need this nearest neighbor search
-        distances = np.sum((src[:m, :] - dst[:m, :])**2)
-        T, _, _ = best_fit_transform(src[:m, :].T, dst[:m, :].T)
-
-        # update the current source
-        src = np.dot(T, src)
-
-        # check error
-        mean_error = np.mean(distances)
-        if np.abs(prev_error - mean_error) < tolerance:
-            break
-        prev_error = mean_error
-
-    # calculate final transformation
-    T,_,_ = best_fit_transform(A, src[:m,:].T)
-
-    return T, distances, i
diff --git a/spaces/matthoffner/chatbot/types/index.ts b/spaces/matthoffner/chatbot/types/index.ts
deleted file mode 100644
index cb0ff5c3b541f646105198ee23ac0fc3d805023e..0000000000000000000000000000000000000000
--- a/spaces/matthoffner/chatbot/types/index.ts
+++ /dev/null
@@ -1 +0,0 @@
-export {};
diff --git a/spaces/matthoffner/open-codetree/_types/editorTypes.ts b/spaces/matthoffner/open-codetree/_types/editorTypes.ts
deleted file mode 100644
index e1b588bf2de47924a2e51a0fd150315114af708b..0000000000000000000000000000000000000000
--- a/spaces/matthoffner/open-codetree/_types/editorTypes.ts
+++ /dev/null
@@ -1,23 +0,0 @@
-export interface LanguagePropsInterface {
-  title: string;
-  entryPoints: string;
-  monacoLanguage: string;
-  data: string;
-}
-
-export interface IObjectKeys {
-  [key: string]: LanguagePropsInterface;
-}
-
-export interface LanguagesInterface extends IObjectKeys {
-  javascript: LanguagePropsInterface;
-  css: LanguagePropsInterface;
-  html: LanguagePropsInterface;
-}
-
-export interface EditorValueInterface {
-  name: string;
-  description: string;
-  public: boolean;
-  tabs: LanguagesInterface;
-}
diff --git a/spaces/matthoffner/open-codetree/components/Dropdown.tsx b/spaces/matthoffner/open-codetree/components/Dropdown.tsx
deleted file mode 100644
index 7def323af9461489fadaf43aad28ea8cb2bf1397..0000000000000000000000000000000000000000
--- a/spaces/matthoffner/open-codetree/components/Dropdown.tsx
+++ /dev/null
@@ -1,77 +0,0 @@
-import React, { ReactNode, useEffect, useRef, useState } from "react";
-import { motion, Variants } from "framer-motion";
-import useOutsideRef from "../hooks/useOutsideRef";
-import Router from "next/router";
-import { useAppSelector } from "../store/hook";
-import { theme_state } from "../store/features/themeSlice";
-
-interface DropdownProps {
-  trigger: ReactNode;
-  children: ReactNode;
-  classname: string;
-}
-
-export const Dropdown = ({ trigger, children, classname }: DropdownProps) => {
-  const [isOpen, setIsOpen] = useState(false);
-  const dropdownRef = useRef(null);
-  const { theme } = useAppSelector(theme_state);
-
-  const { isOutsideRef } = useOutsideRef(dropdownRef);
-
-  useEffect(() => {
-    if (isOutsideRef) {
-      setIsOpen(false);
-    }
-  }, [isOutsideRef]);
-
-  const toggleMenu = () => {
-    setIsOpen(!isOpen);
-  };
-
-  Router.events.on("routeChangeStart", () => {
-    setIsOpen(false);
-  });
-
-  const animation: Variants = {
-    enter: {
-      opacity: 1,
-      scale: 1,
-      transformOrigin: "top right",
-      transition: {
-        duration: 0.25,
-      },
-      display: "block",
-    },
-    exit: {
-      opacity: 0,
-      scale: 0.7,
-      transformOrigin: "top right",
-      transition: {
-        duration: 0.2,
-        delay: 0.1,
-      },
-      transitionEnd: {
-        display: "none",
-      },
-    },
-  };
-
-  return (
-    <div ref={dropdownRef}>
-      <motion.div className="menu-item relative">
-        <div className="cursor-pointer" onClick={toggleMenu}>
-          {trigger}
-        </div>
-
-        <motion.div
-          className={`${classname} absolute shadow rounded-lg z-50 mt-3 glassmorphism`}
-          initial="exit"
-          animate={isOpen ? "enter" : "exit"}
-          variants={animation}
-        >
-          <div>{children}</div>
-        </motion.div>
-      </motion.div>
-    </div>
-  );
-};
diff --git a/spaces/menghanxia/ReversibleHalftoning/utils/dataset.py b/spaces/menghanxia/ReversibleHalftoning/utils/dataset.py
deleted file mode 100644
index 7d2215cd2e51190cb267b56eb252a556bab2ca48..0000000000000000000000000000000000000000
--- a/spaces/menghanxia/ReversibleHalftoning/utils/dataset.py
+++ /dev/null
@@ -1,39 +0,0 @@
-import torch
-import torch.utils.data as data
-import cv2
-import numpy as np
-from os.path import join
-
-
-class HalftoneVOC2012(data.Dataset):
-    # data range is [-1,1], color image is in BGR format
-    def __init__(self, data_list):
-        super(HalftoneVOC2012, self).__init__()
-        self.inputs = [join('Data', x) for x in data_list['inputs']]
-        self.labels = [join('Data', x) for x in data_list['labels']]
-
-    @staticmethod
-    def load_input(name):
-        img = cv2.imread(name, flags=cv2.IMREAD_COLOR)
-        # transpose data
-        img = img.transpose((2, 0, 1))
-        # to Tensor
-        img = torch.from_numpy(img.astype(np.float32) / 127.5 - 1.0)
-        return img
-
-    @staticmethod
-    def load_label(name):
-        img = cv2.imread(name, flags=cv2.IMREAD_GRAYSCALE)
-        # transpose data
-        img = img[np.newaxis, :, :]
-        # to Tensor
-        img = torch.from_numpy(img.astype(np.float32) / 127.5 - 1.0)
-        return img
-
-    def __getitem__(self, index):
-        input_data = self.load_input(self.inputs[index])
-        label_data = self.load_label(self.labels[index])
-        return input_data, label_data
-
-    def __len__(self):
-        return len(self.inputs)
\ No newline at end of file
diff --git a/spaces/merve/Grounding_DINO_demo/README.md b/spaces/merve/Grounding_DINO_demo/README.md
deleted file mode 100644
index 081e39d1a209013fc2a5342efc9b1307923488c8..0000000000000000000000000000000000000000
--- a/spaces/merve/Grounding_DINO_demo/README.md
+++ /dev/null
@@ -1,126 +0,0 @@
----
-title: Grounding DINO Demo
-emoji: 💻
-colorFrom: purple
-colorTo: yellow
-sdk: gradio
-sdk_version: 3.23.0
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-# Grounding DINO 
-[📃Paper](https://arxiv.org/abs/2303.05499) | 
-[📽️Video](https://www.youtube.com/watch?v=wxWDt5UiwY8) |
-[🗯️ Github](https://github.com/IDEA-Research/GroundingDINO) |
-[📯Demo on Colab](https://colab.research.google.com/github/roboflow-ai/notebooks/blob/main/notebooks/zero-shot-object-detection-with-grounding-dino.ipynb) | 
-[🤗Demo on HF (Coming soon)]() 
-
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/roboflow-ai/notebooks/blob/main/notebooks/zero-shot-object-detection-with-grounding-dino.ipynb) \
-[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/grounding-dino-marrying-dino-with-grounded/zero-shot-object-detection-on-mscoco)](https://paperswithcode.com/sota/zero-shot-object-detection-on-mscoco?p=grounding-dino-marrying-dino-with-grounded) \
-[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/grounding-dino-marrying-dino-with-grounded/zero-shot-object-detection-on-odinw)](https://paperswithcode.com/sota/zero-shot-object-detection-on-odinw?p=grounding-dino-marrying-dino-with-grounded) \
-[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/grounding-dino-marrying-dino-with-grounded/object-detection-on-coco-minival)](https://paperswithcode.com/sota/object-detection-on-coco-minival?p=grounding-dino-marrying-dino-with-grounded) \
-[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/grounding-dino-marrying-dino-with-grounded/object-detection-on-coco)](https://paperswithcode.com/sota/object-detection-on-coco?p=grounding-dino-marrying-dino-with-grounded)
-
-
-
-Official pytorch implementation of [Grounding DINO](https://arxiv.org/abs/2303.05499), a stronger open-set object detector. Code is available now!
-
-
-## Highlight
-
-- **Open-Set Detection.** Detect **everything** with language!
-- **High Performancce.** COCO zero-shot **52.5 AP** (training without COCO data!). COCO fine-tune **63.0 AP**.
-- **Flexible.** Collaboration with Stable Diffusion for Image Editting.
-
-## News
-[2023/03/27] Support CPU-only mode. Now the model can run on machines without GPUs.\
-[2023/03/25] A [demo](https://colab.research.google.com/github/roboflow-ai/notebooks/blob/main/notebooks/zero-shot-object-detection-with-grounding-dino.ipynb) for Grounding DINO is available at Colab. Thanks to @Piotr! \
-[2023/03/22] Code is available Now!
-
-
-
-## TODO 
-
-- [x] Release inference code and demo.
-- [x] Release checkpoints.
-- [ ] Grounding DINO with Stable Diffusion and GLIGEN demos.
-- [ ] Release training codes.
-
-## Install 
-
-If you have a CUDA environment, please make sure the environment variable `CUDA_HOME` is set. It will be compiled under CPU-only mode if no CUDA available.
-
-```bash
-pip install -e .
-```
-
-## Demo
-
-```bash
-CUDA_VISIBLE_DEVICES=6 python demo/inference_on_a_image.py \
-  -c /path/to/config \
-  -p /path/to/checkpoint \
-  -i .asset/cats.png \
-  -o "outputs/0" \
-  -t "cat ear." \
-  [--cpu-only] # open it for cpu mode
-```
-See the `demo/inference_on_a_image.py` for more details.
-
-## Checkpoints
-
-<!-- insert a table -->
-<table>
-  <thead>
-    <tr style="text-align: right;">
-      <th></th>
-      <th>name</th>
-      <th>backbone</th>
-      <th>Data</th>
-      <th>box AP on COCO</th>
-      <th>Checkpoint</th>
-      <th>Config</th>
-    </tr>
-  </thead>
-  <tbody>
-    <tr>
-      <th>1</th>
-      <td>GroundingDINO-T</td>
-      <td>Swin-T</td>
-      <td>O365,GoldG,Cap4M</td>
-      <td>48.4 (zero-shot) / 57.2 (fine-tune)</td>
-      <td><a href="https://github.com/IDEA-Research/GroundingDINO/releases/download/v0.1.0-alpha/groundingdino_swint_ogc.pth">link</a></td>
-      <td><a href="https://github.com/IDEA-Research/GroundingDINO/blob/main/groundingdino/config/GroundingDINO_SwinT_OGC.py">link</a></td>
-    </tr>
-  </tbody>
-</table>
-
-
-
-## Acknowledgement
-
-Our model is related to [DINO](https://github.com/IDEA-Research/DINO) and [GLIP](https://github.com/microsoft/GLIP). Thanks for their great work!
-
-We also thank great previous work including DETR, Deformable DETR, SMCA, Conditional DETR, Anchor DETR, Dynamic DETR, DAB-DETR, DN-DETR, etc. More related work are available at [Awesome Detection Transformer](https://github.com/IDEACVR/awesome-detection-transformer). A new toolbox [detrex](https://github.com/IDEA-Research/detrex) is available as well.
-
-Thanks [Stable Diffusion](https://github.com/Stability-AI/StableDiffusion) and [GLIGEN](https://github.com/gligen/GLIGEN) for their awesome models.
-
-
-## Citation
-
-If you find our work helpful for your research, please consider citing the following BibTeX entry.   
-
-```bibtex
-@inproceedings{ShilongLiu2023GroundingDM,
-  title={Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection},
-  author={Shilong Liu and Zhaoyang Zeng and Tianhe Ren and Feng Li and Hao Zhang and Jie Yang and Chunyuan Li and Jianwei Yang and Hang Su and Jun Zhu and Lei Zhang},
-  year={2023}
-}
-```
-
-
-
-
-
diff --git a/spaces/merve/deprem-ocr-migrate-ner/README.md b/spaces/merve/deprem-ocr-migrate-ner/README.md
deleted file mode 100644
index edb3e5062bc85fa65aa6550dc3ce441461637319..0000000000000000000000000000000000000000
--- a/spaces/merve/deprem-ocr-migrate-ner/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Deprem Ocr 2
-emoji: 👀
-colorFrom: green
-colorTo: blue
-sdk: gradio
-sdk_version: 3.17.0
-app_file: app.py
-pinned: false
-duplicated_from: deprem-ml/deprem-ocr
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/merve/fill-in-the-blank/public/dataset-worldviews/shapes.js b/spaces/merve/fill-in-the-blank/public/dataset-worldviews/shapes.js
deleted file mode 100644
index 87af55b4829a78b48dc41f6674c12cd58cfc3741..0000000000000000000000000000000000000000
--- a/spaces/merve/fill-in-the-blank/public/dataset-worldviews/shapes.js
+++ /dev/null
@@ -1,248 +0,0 @@
-
-// Space out the shapes a bit
-shapeParams.forEach((d) => (d.startX = d.startX * 1.1));
-
-// How to draw the background boxes, which will be styled later
-const classifierBgPathTop = "M 420 150 H 0 V 0 H 420 V 150";
-const classifierBgPathBottom = "M 420 300 H 0 V 0 H 420 V 300";
-
-const toDropdownValueStringDict = {
-    shape_name: "circles, triangles, or rectangles",
-    pointiness: "pointy shapes or round shapes",
-    size: "small shapes or big shapes",
-};
-
-const toShortValueStringDict = {
-    shape_name: "circles, triangles, or rectangles",
-    pointiness: "pointy or round",
-    size: "small or big",
-};
-
-const toDropdownValueRoundingStringDict = {
-    true: "with our best guess",
-    false: 'as "other"',
-};
-
-const toPropertyStringDict = {
-    pointy: "pointy shapes",
-    round: "round shapes",
-    small: "small shapes",
-    large: "big shapes",
-    circle: "circles",
-    triangle: "triangles",
-    rect: "rectangles",
-};
-
-function toOriginalString(inputString) {
-    for (const [key, value] of Object.entries(toPropertyStringDict)) {
-        if (inputString == value) {
-            return key;
-        }
-    }
-}
-
-function toPropertyString(inputProperty, isRounding = true) {
-    if (!isRounding && inputProperty.startsWith("rt_")) {
-        return "others";
-    }
-    return toPropertyStringDict[inputProperty.replace("rt_", "")];
-}
-
-// Dictionary mapping div name to classifier results and summary sentences
-var allResults = {};
-var summaries = {};
-
-function toBool(inputString) {
-    if (inputString == "true") {
-        return true;
-    }
-    return false;
-}
-function updateResults() {
-    allResults["default-classifier"] = calculateResults();
-    allResults["second-classifier"] = calculateResults(
-        "shape_name",
-        toBool(
-            document.getElementById("second-classifier-select-rounding").value
-        )
-    );
-
-    allResults["final-classifier"] = calculateResults(
-        document.getElementById("final-classifier-select-category").value,
-        toBool(
-            document.getElementById("final-classifier-select-rounding").value
-        )
-    );
-
-    allResults["conclusion"] = calculateResults(
-        document.getElementById("conclusion-select-category").value,
-        true
-    );
-
-    updateSummaries();
-    updateSecondInterfaceImages();
-}
-
-// Text summaries are written by hand for simplicity, and keyed simply by
-// a string of the form "[category]:[useGuess]" (or simply "none").
-// These are hashed in the same way as the results, by div name.
-function updateSummaries() {
-    summaries["default-classifier"] = getPerformanceSummary("none");
-    summaries["second-classifier"] = getPerformanceSummary(
-        "shape_name:" +
-            document.getElementById("second-classifier-select-rounding").value
-    );
-
-    summaries["final-classifier"] = getPerformanceSummary(
-        document.getElementById("final-classifier-select-category").value +
-            ":" +
-            document.getElementById("final-classifier-select-rounding").value
-    );
-
-    summaries["conclusion"] = getPerformanceSummary(
-        document.getElementById("conclusion-select-category").value + ":" + true
-    );
-}
-
-// Yes, these background colors are hardcoded in,
-// no, this is not good design, this is just how it happened.
-function getPerformanceSummary(key) {
-    allSummaries = {
-        "shape_name:true":
-            '<mark style="background-color: rgb(206, 234, 135);" class="well">well</mark> on circles, <mark style="background-color: rgb(244, 123, 74);" class="terribly">terribly</mark> on triangles, and <mark style="background-color: rgb(173, 220, 114);" class="best">best</mark> on rectangles',
-        "shape_name:false":
-            '<mark style="background-color: rgb(251, 163, 94);" class="poorly">poorly</mark> on circles, <mark style="background-color: rgb(155, 212, 108);" class="best">best</mark> on triangles and rectangles, and <mark style="background-color: rgb(252, 244, 171);" class="fine">fine</mark> on other shapes',
-        "pointiness:true":
-            '<mark style="background-color: rgb(184, 225, 119);" class="better">better</mark> on pointy shapes and <mark style="background-color: rgb(254, 206, 125);" class="worse">worse</mark> on round shapes',
-        "pointiness:false":
-            '<mark style="background-color: rgb(140, 205, 104);" class="best">best</mark> on pointy shapes, <mark style="background-color: rgb(243, 248, 171);" class="fine">fine</mark> on round shapes, and <mark style="background-color: rgb(253, 190, 111);" class="poorly">poorly</mark> on other shapes',
-        "size:true":
-            '<mark style="background-color: rgb(206, 234, 135);" class="better">better</mark> on small shapes, <mark style="background-color: rgb(254, 232, 154);" class="worse">worse</mark> on big shapes',
-        "size:false":
-            '<mark style="background-color: rgb(254, 215, 135);" class="poorly">poorly</mark> on small shapes, <mark style="background-color: rgb(165, 0, 38); color: #FFCCD8;" class="terribly">terribly</mark> on big shapes, and <mark style="background-color: rgb(110, 192, 99);" class="best">best</mark> on other shapes',
-        "none:true":
-            '<mark style="background-color: rgb(246, 248, 173);" class="fine">fine</mark> on all shapes',
-        "none:false":
-            '<mark style="background-color: rgb(246, 248, 173);" class="fine">fine</mark> on all shapes',
-        none: '<mark style="background-color: rgb(246, 248, 173);" class="fine">fine</mark> on all shapes',
-    };
-
-    return "The Is-Shaded Classifier performs " + allSummaries[key] + ".";
-}
-
-// On the second-classifier dropdown, update the "task interface" image.
-function updateSecondInterfaceImages() {
-    d3.select(".second-interface").html(function () {
-        if (
-            !document.getElementById("second-classifier-select-rounding").value
-        ) {
-            return;
-        }
-        var imgPath =
-            "img/interface_shape_name_" +
-            document.getElementById("second-classifier-select-rounding").value;
-        return (
-            '<img src="' +
-            imgPath +
-            '.png" alt="" class="interface-image" srcset="' +
-            imgPath +
-            '.svg"></img>'
-        );
-    });
-}
-
-// Calculate results given input parameters
-function calculateResults(property = "none", useGuess = false) {
-    switch (property) {
-        case "none":
-            var nAccurate = shapeParams.filter(
-                (shape) => shape.correctness == "correct"
-            ).length;
-            var totalShapes = shapeParams.length;
-
-            var results = [
-                {
-                    object: "shape",
-                    n: totalShapes,
-                    "n correct": nAccurate,
-                    accuracy: (nAccurate / totalShapes).toFixed(3),
-                    rawCategoryName: "none",
-                },
-            ];
-
-            return results;
-        case "pointiness":
-            categories = ["pointy", "round"];
-            break;
-        case "size":
-            categories = ["small", "large"];
-            break;
-        case "shape_name":
-            categories = ["circle", "triangle", "rect"];
-            break;
-    }
-
-    var results = [];
-    if (useGuess == true) {
-        // Rounding shapes to categories
-
-        for (const category of categories) {
-            // Get shapes that are either in this category (e.g. rectangle) or "rounds to" this category (e.g. rt_rectangle)
-            var theseShapes = shapeParams.filter(
-                (shape) =>
-                    shape[property] == category ||
-                    shape[property] == "rt_" + category
-            );
-            var nAccurate = theseShapes.filter(
-                (shape) => shape.correctness == "correct"
-            ).length;
-            var totalShapes = theseShapes.length;
-
-            results.push({
-                object: toPropertyString(category),
-                n: totalShapes,
-                "n correct": nAccurate,
-                accuracy: (nAccurate / totalShapes).toFixed(3),
-                rawCategoryName: category,
-            });
-        }
-    } else {
-        // Not rounding, treat everything else as "other"
-
-        // First go through existing categories
-        for (const category of categories) {
-            var theseShapes = shapeParams.filter(
-                (shape) => shape[property] == category
-            );
-            var nAccurate = theseShapes.filter(
-                (shape) => shape.correctness == "correct"
-            ).length;
-            var totalShapes = theseShapes.length;
-            results.push({
-                object: toPropertyString(category),
-                n: totalShapes,
-                "n correct": nAccurate,
-                accuracy: (nAccurate / totalShapes).toFixed(3),
-                rawCategoryName: category,
-            });
-        }
-
-        // Now get "other" shapes
-        var theseShapes = shapeParams.filter(
-            (shape) => !categories.includes(shape[property])
-        );
-        var nAccurate = theseShapes.filter(
-            (shape) => shape.correctness == "correct"
-        ).length;
-        var totalShapes = theseShapes.length;
-        results.push({
-            object: "other shapes",
-            n: totalShapes,
-            "n correct": nAccurate,
-            accuracy: (nAccurate / totalShapes).toFixed(3),
-            rawCategoryName: "other",
-        });
-    }
-
-    return results;
-}
diff --git a/spaces/merve/uncertainty-calibration/public/private-and-fair/util.js b/spaces/merve/uncertainty-calibration/public/private-and-fair/util.js
deleted file mode 100644
index 76a4bccf20f893c87bcb5088391cd9aa73c312e2..0000000000000000000000000000000000000000
--- a/spaces/merve/uncertainty-calibration/public/private-and-fair/util.js
+++ /dev/null
@@ -1,125 +0,0 @@
-window.ttSel = d3.select('body').selectAppend('div.tooltip.tooltip-hidden')
-window.util = (function(){
-
-  var data = window.__datacache = window.__datacache || {}
-
-  async function getFile(path){
-    var [slug, type] = path.split('.')
-    if (data[slug]) return data[slug]
-
-    var datadir = 'https://storage.googleapis.com/uncertainty-over-space/explore-dp/'
-
-    var res = await fetch(datadir + path + '?t=5')
-    if (type == 'csv'){
-      var parsed = d3.csvParse(await res.text())
-    } else if (type == 'npy'){
-      var parsed = npyjs.parse(await(res).arrayBuffer())
-    } else if (type == 'json'){
-      var parsed = await res.json()
-    } else{
-      throw 'unknown type'
-    }
-
-    data[slug] = parsed
-
-    return parsed 
-  }
-
-  async function drawDigit(ctx, index, s=4, offsetX=0, offsetY=0){
-    var digitMetadata = await util.getFile('mnist_train.csv')
-    if (!digitMetadata[0].label) decorateDigitMetadata(digitMetadata)
-
-    var {label, labelIndex} = digitMetadata[index]
-
-    if (!label) console.log('missing ', index)
-    var rawdigits = await util.getFile(`cns-cache/mnist_train_raw_${label}.npy`)
-    if (!rawdigits) return console.log('digits not loaded')
-
-    d3.cross(d3.range(28), d3.range(28)).forEach(([i, j]) => {
-      var r = rawdigits.data[labelIndex*28*28 + j*28 + i + 0]
-      var g = rawdigits.data[labelIndex*28*28 + j*28 + i + 0]
-      var b = rawdigits.data[labelIndex*28*28 + j*28 + i + 0]
-
-      ctx.beginPath()
-      ctx.fillStyle = `rgb(${r},${g},${b})`
-      ctx.rect(i*s + offsetX, j*s + offsetY, s, s)
-      ctx.fill()
-    })
-  }
-
-  function decorateDigitMetadata(digitMetadata){
-    digitMetadata.forEach(d => {
-      delete d['']
-      d.i = +d.i
-      d.label = +d.y
-      d.priv_order = +d.priv_order
-    })
-
-    var byLabel = d3.nestBy(digitMetadata, d => d.y)
-    byLabel = _.sortBy(byLabel, d => d.key)
-    byLabel.forEach(digit => {
-      digit.forEach((d, i) => d.labelIndex = i)
-    })
-
-    return {digitMetadata, byLabel}
-  }
-
-  var colors = [d3.interpolateTurbo(.15), d3.interpolateTurbo(.85)]
-  var epsilonExtent = [400000, .01]
-  // var epsilonExtent = [65, .01]
-
-
-  var addAxisLabel = (c, xText, yText, xOffset=40, yOffset=-40) => {
-    c.svg.select('.x').append('g')
-      .translate([c.width/2, xOffset])
-      .append('text.axis-label')
-      .text(xText)
-      .at({textAnchor: 'middle'})
-      .st({fill: '#000', fontSize: 14})
-
-    c.svg.select('.y')
-      .append('g')
-      .translate([yOffset, c.height/2])
-      .append('text.axis-label')
-      .text(yText)
-      .at({textAnchor: 'middle', transform: 'rotate(-90)'})
-      .st({fill: '#000', fontSize: 14})
-  }
-
-  var ggPlotBg = (c, isBlack=true) => {
-    if (!isBlack){
-      c.svg.append('rect')
-        .at({width: c.width, height: c.height, fill: '#eee'})
-        .lower()
-    }
-
-    c.svg.selectAll('.tick').selectAll('line').remove()
-    c.svg.selectAll('.y .tick')
-      .append('path').at({d: 'M 0 0 H ' + c.width, stroke: '#fff', strokeWidth: 1})
-    c.svg.selectAll('.y text').at({x: -3})
-    c.svg.selectAll('.x .tick')
-      .append('path').at({d: 'M 0 0 V -' + c.height, stroke: '#fff', strokeWidth: 1})
-  }
-
-
-  return {data, getFile, drawDigit, colors, epsilonExtent, addAxisLabel, ggPlotBg, decorateDigitMetadata}
-})()
-
-
-
-
-
-
-// mnist_train.csv
-// mnist_train_raw.npy
-// umap_train_0.npy
-// umap_train_1.npy
-// umap_train_2.npy
-// umap_train_3.npy
-// umap_train_4.npy
-// umap_train_5.npy
-// umap_train_6.npy
-// umap_train_7.npy
-// umap_train_8.npy
-// umap_train_9.npy
-// umap_train_all.npy
diff --git a/spaces/mgxwrites/Mgx-Diffusion-v3.0/README.md b/spaces/mgxwrites/Mgx-Diffusion-v3.0/README.md
deleted file mode 100644
index 15176bed26d36b4f9566c7102a5655e310f76036..0000000000000000000000000000000000000000
--- a/spaces/mgxwrites/Mgx-Diffusion-v3.0/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Anything V3.0
-emoji: 🏃
-colorFrom: gray
-colorTo: yellow
-sdk: gradio
-sdk_version: 3.10.1
-app_file: app.py
-pinned: false
-duplicated_from: akhaliq/anything-v3.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/mithril-security/blind_chat/src/routes/conversation/[id]/ParamsWritable.js b/spaces/mithril-security/blind_chat/src/routes/conversation/[id]/ParamsWritable.js
deleted file mode 100644
index fed36e9b20c737959dc50bcf2e821123c88db3e6..0000000000000000000000000000000000000000
--- a/spaces/mithril-security/blind_chat/src/routes/conversation/[id]/ParamsWritable.js
+++ /dev/null
@@ -1,3 +0,0 @@
-import { writable } from "svelte/store";
-
-export const params_writable = writable("");
diff --git a/spaces/miumiunana/miumiu02/Dockerfile b/spaces/miumiunana/miumiu02/Dockerfile
deleted file mode 100644
index 6c01c09373883afcb4ea34ae2d316cd596e1737b..0000000000000000000000000000000000000000
--- a/spaces/miumiunana/miumiu02/Dockerfile
+++ /dev/null
@@ -1,21 +0,0 @@
-FROM node:18-bullseye-slim
-
-RUN apt-get update && \
-
-apt-get install -y git
-
-RUN git clone https://gitgud.io/khanon/oai-reverse-proxy.git /app
-
-WORKDIR /app
-
-RUN npm install
-
-COPY Dockerfile greeting.md* .env* ./
-
-RUN npm run build
-
-EXPOSE 7860
-
-ENV NODE_ENV=production
-
-CMD [ "npm", "start" ]
\ No newline at end of file
diff --git a/spaces/ml6team/controlnet-interior-design/stable_diffusion_controlnet_inpaint_img2img.py b/spaces/ml6team/controlnet-interior-design/stable_diffusion_controlnet_inpaint_img2img.py
deleted file mode 100644
index 74dbc8db8f963d15075f682e9d5c9e824742a54c..0000000000000000000000000000000000000000
--- a/spaces/ml6team/controlnet-interior-design/stable_diffusion_controlnet_inpaint_img2img.py
+++ /dev/null
@@ -1,1112 +0,0 @@
-"""This file contains the StableDiffusionControlNetInpaintImg2ImgPipeline class from the
-community pipelines from the diffusers library of HuggingFace.
-"""
-# Inspired by: https://github.com/haofanwang/ControlNet-for-Diffusers/
-
-import inspect
-from typing import Any, Callable, Dict, List, Optional, Union
-
-import numpy as np
-import PIL.Image
-import torch
-import torch.nn.functional as F
-from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
-
-from diffusers import AutoencoderKL, ControlNetModel, DiffusionPipeline, UNet2DConditionModel, logging
-from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput, StableDiffusionSafetyChecker
-from diffusers.schedulers import KarrasDiffusionSchedulers
-from diffusers.utils import (
-    PIL_INTERPOLATION,
-    is_accelerate_available,
-    is_accelerate_version,
-    randn_tensor,
-    replace_example_docstring,
-)
-
-
-logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
-
-EXAMPLE_DOC_STRING = """
-    Examples:
-        ```py
-        >>> import numpy as np
-        >>> import torch
-        >>> from PIL import Image
-        >>> from stable_diffusion_controlnet_inpaint_img2img import StableDiffusionControlNetInpaintImg2ImgPipeline
-        >>> from transformers import AutoImageProcessor, UperNetForSemanticSegmentation
-        >>> from diffusers import ControlNetModel, UniPCMultistepScheduler
-        >>> from diffusers.utils import load_image
-        >>> def ade_palette():
-                return [[120, 120, 120], [180, 120, 120], [6, 230, 230], [80, 50, 50],
-                        [4, 200, 3], [120, 120, 80], [140, 140, 140], [204, 5, 255],
-                        [230, 230, 230], [4, 250, 7], [224, 5, 255], [235, 255, 7],
-                        [150, 5, 61], [120, 120, 70], [8, 255, 51], [255, 6, 82],
-                        [143, 255, 140], [204, 255, 4], [255, 51, 7], [204, 70, 3],
-                        [0, 102, 200], [61, 230, 250], [255, 6, 51], [11, 102, 255],
-                        [255, 7, 71], [255, 9, 224], [9, 7, 230], [220, 220, 220],
-                        [255, 9, 92], [112, 9, 255], [8, 255, 214], [7, 255, 224],
-                        [255, 184, 6], [10, 255, 71], [255, 41, 10], [7, 255, 255],
-                        [224, 255, 8], [102, 8, 255], [255, 61, 6], [255, 194, 7],
-                        [255, 122, 8], [0, 255, 20], [255, 8, 41], [255, 5, 153],
-                        [6, 51, 255], [235, 12, 255], [160, 150, 20], [0, 163, 255],
-                        [140, 140, 140], [250, 10, 15], [20, 255, 0], [31, 255, 0],
-                        [255, 31, 0], [255, 224, 0], [153, 255, 0], [0, 0, 255],
-                        [255, 71, 0], [0, 235, 255], [0, 173, 255], [31, 0, 255],
-                        [11, 200, 200], [255, 82, 0], [0, 255, 245], [0, 61, 255],
-                        [0, 255, 112], [0, 255, 133], [255, 0, 0], [255, 163, 0],
-                        [255, 102, 0], [194, 255, 0], [0, 143, 255], [51, 255, 0],
-                        [0, 82, 255], [0, 255, 41], [0, 255, 173], [10, 0, 255],
-                        [173, 255, 0], [0, 255, 153], [255, 92, 0], [255, 0, 255],
-                        [255, 0, 245], [255, 0, 102], [255, 173, 0], [255, 0, 20],
-                        [255, 184, 184], [0, 31, 255], [0, 255, 61], [0, 71, 255],
-                        [255, 0, 204], [0, 255, 194], [0, 255, 82], [0, 10, 255],
-                        [0, 112, 255], [51, 0, 255], [0, 194, 255], [0, 122, 255],
-                        [0, 255, 163], [255, 153, 0], [0, 255, 10], [255, 112, 0],
-                        [143, 255, 0], [82, 0, 255], [163, 255, 0], [255, 235, 0],
-                        [8, 184, 170], [133, 0, 255], [0, 255, 92], [184, 0, 255],
-                        [255, 0, 31], [0, 184, 255], [0, 214, 255], [255, 0, 112],
-                        [92, 255, 0], [0, 224, 255], [112, 224, 255], [70, 184, 160],
-                        [163, 0, 255], [153, 0, 255], [71, 255, 0], [255, 0, 163],
-                        [255, 204, 0], [255, 0, 143], [0, 255, 235], [133, 255, 0],
-                        [255, 0, 235], [245, 0, 255], [255, 0, 122], [255, 245, 0],
-                        [10, 190, 212], [214, 255, 0], [0, 204, 255], [20, 0, 255],
-                        [255, 255, 0], [0, 153, 255], [0, 41, 255], [0, 255, 204],
-                        [41, 0, 255], [41, 255, 0], [173, 0, 255], [0, 245, 255],
-                        [71, 0, 255], [122, 0, 255], [0, 255, 184], [0, 92, 255],
-                        [184, 255, 0], [0, 133, 255], [255, 214, 0], [25, 194, 194],
-                        [102, 255, 0], [92, 0, 255]]
-        >>> image_processor = AutoImageProcessor.from_pretrained("openmmlab/upernet-convnext-small")
-        >>> image_segmentor = UperNetForSemanticSegmentation.from_pretrained("openmmlab/upernet-convnext-small")
-        >>> pipe = StableDiffusionControlNetInpaintImg2ImgPipeline.from_pretrained(
-                "runwayml/stable-diffusion-inpainting", controlnet=controlnet, safety_checker=None, torch_dtype=torch.float16
-            )
-        >>> pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
-        >>> pipe.enable_xformers_memory_efficient_attention()
-        >>> pipe.enable_model_cpu_offload()
-        >>> def image_to_seg(image):
-                pixel_values = image_processor(image, return_tensors="pt").pixel_values
-                with torch.no_grad():
-                    outputs = image_segmentor(pixel_values)
-                seg = image_processor.post_process_semantic_segmentation(outputs, target_sizes=[image.size[::-1]])[0]
-                color_seg = np.zeros((seg.shape[0], seg.shape[1], 3), dtype=np.uint8)  # height, width, 3
-                palette = np.array(ade_palette())
-                for label, color in enumerate(palette):
-                    color_seg[seg == label, :] = color
-                color_seg = color_seg.astype(np.uint8)
-                seg_image = Image.fromarray(color_seg)
-                return seg_image
-        >>> image = load_image(
-                "https://github.com/CompVis/latent-diffusion/raw/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png"
-            )
-        >>> mask_image = load_image(
-                "https://github.com/CompVis/latent-diffusion/raw/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png"
-            )
-        >>> controlnet_conditioning_image = image_to_seg(image)
-        >>> image = pipe(
-                "Face of a yellow cat, high resolution, sitting on a park bench",
-                image,
-                mask_image,
-                controlnet_conditioning_image,
-                num_inference_steps=20,
-            ).images[0]
-        >>> image.save("out.png")
-        ```
-"""
-
-
-def prepare_image(image):
-    if isinstance(image, torch.Tensor):
-        # Batch single image
-        if image.ndim == 3:
-            image = image.unsqueeze(0)
-
-        image = image.to(dtype=torch.float32)
-    else:
-        # preprocess image
-        if isinstance(image, (PIL.Image.Image, np.ndarray)):
-            image = [image]
-
-        if isinstance(image, list) and isinstance(image[0], PIL.Image.Image):
-            image = [np.array(i.convert("RGB"))[None, :] for i in image]
-            image = np.concatenate(image, axis=0)
-        elif isinstance(image, list) and isinstance(image[0], np.ndarray):
-            image = np.concatenate([i[None, :] for i in image], axis=0)
-
-        image = image.transpose(0, 3, 1, 2)
-        image = torch.from_numpy(image).to(dtype=torch.float32) / 127.5 - 1.0
-
-    return image
-
-
-def prepare_mask_image(mask_image):
-    if isinstance(mask_image, torch.Tensor):
-        if mask_image.ndim == 2:
-            # Batch and add channel dim for single mask
-            mask_image = mask_image.unsqueeze(0).unsqueeze(0)
-        elif mask_image.ndim == 3 and mask_image.shape[0] == 1:
-            # Single mask, the 0'th dimension is considered to be
-            # the existing batch size of 1
-            mask_image = mask_image.unsqueeze(0)
-        elif mask_image.ndim == 3 and mask_image.shape[0] != 1:
-            # Batch of mask, the 0'th dimension is considered to be
-            # the batching dimension
-            mask_image = mask_image.unsqueeze(1)
-
-        # Binarize mask
-        mask_image[mask_image < 0.5] = 0
-        mask_image[mask_image >= 0.5] = 1
-    else:
-        # preprocess mask
-        if isinstance(mask_image, (PIL.Image.Image, np.ndarray)):
-            mask_image = [mask_image]
-
-        if isinstance(mask_image, list) and isinstance(mask_image[0], PIL.Image.Image):
-            mask_image = np.concatenate([np.array(m.convert("L"))[None, None, :] for m in mask_image], axis=0)
-            mask_image = mask_image.astype(np.float32) / 255.0
-        elif isinstance(mask_image, list) and isinstance(mask_image[0], np.ndarray):
-            mask_image = np.concatenate([m[None, None, :] for m in mask_image], axis=0)
-
-        mask_image[mask_image < 0.5] = 0
-        mask_image[mask_image >= 0.5] = 1
-        mask_image = torch.from_numpy(mask_image)
-
-    return mask_image
-
-
-def prepare_controlnet_conditioning_image(
-    controlnet_conditioning_image, width, height, batch_size, num_images_per_prompt, device, dtype
-):
-    if not isinstance(controlnet_conditioning_image, torch.Tensor):
-        if isinstance(controlnet_conditioning_image, PIL.Image.Image):
-            controlnet_conditioning_image = [controlnet_conditioning_image]
-
-        if isinstance(controlnet_conditioning_image[0], PIL.Image.Image):
-            controlnet_conditioning_image = [
-                np.array(i.resize((width, height), resample=PIL_INTERPOLATION["lanczos"]))[None, :]
-                for i in controlnet_conditioning_image
-            ]
-            controlnet_conditioning_image = np.concatenate(controlnet_conditioning_image, axis=0)
-            controlnet_conditioning_image = np.array(controlnet_conditioning_image).astype(np.float32) / 255.0
-            controlnet_conditioning_image = controlnet_conditioning_image.transpose(0, 3, 1, 2)
-            controlnet_conditioning_image = torch.from_numpy(controlnet_conditioning_image)
-        elif isinstance(controlnet_conditioning_image[0], torch.Tensor):
-            controlnet_conditioning_image = torch.cat(controlnet_conditioning_image, dim=0)
-
-    image_batch_size = controlnet_conditioning_image.shape[0]
-
-    if image_batch_size == 1:
-        repeat_by = batch_size
-    else:
-        # image batch size is the same as prompt batch size
-        repeat_by = num_images_per_prompt
-
-    controlnet_conditioning_image = controlnet_conditioning_image.repeat_interleave(repeat_by, dim=0)
-
-    controlnet_conditioning_image = controlnet_conditioning_image.to(device=device, dtype=dtype)
-
-    return controlnet_conditioning_image
-
-
-class StableDiffusionControlNetInpaintImg2ImgPipeline(DiffusionPipeline):
-    """
-    Inspired by: https://github.com/haofanwang/ControlNet-for-Diffusers/
-    """
-
-    _optional_components = ["safety_checker", "feature_extractor"]
-
-    def __init__(
-        self,
-        vae: AutoencoderKL,
-        text_encoder: CLIPTextModel,
-        tokenizer: CLIPTokenizer,
-        unet: UNet2DConditionModel,
-        controlnet: ControlNetModel,
-        scheduler: KarrasDiffusionSchedulers,
-        safety_checker: StableDiffusionSafetyChecker,
-        feature_extractor: CLIPFeatureExtractor,
-        requires_safety_checker: bool = True,
-    ):
-        super().__init__()
-
-        if safety_checker is None and requires_safety_checker:
-            logger.warning(
-                f"You have disabled the safety checker for {self.__class__} by passing `safety_checker=None`. Ensure"
-                " that you abide to the conditions of the Stable Diffusion license and do not expose unfiltered"
-                " results in services or applications open to the public. Both the diffusers team and Hugging Face"
-                " strongly recommend to keep the safety filter enabled in all public facing circumstances, disabling"
-                " it only for use-cases that involve analyzing network behavior or auditing its results. For more"
-                " information, please have a look at https://github.com/huggingface/diffusers/pull/254 ."
-            )
-
-        if safety_checker is not None and feature_extractor is None:
-            raise ValueError(
-                "Make sure to define a feature extractor when loading {self.__class__} if you want to use the safety"
-                " checker. If you do not want to use the safety checker, you can pass `'safety_checker=None'` instead."
-            )
-
-        self.register_modules(
-            vae=vae,
-            text_encoder=text_encoder,
-            tokenizer=tokenizer,
-            unet=unet,
-            controlnet=controlnet,
-            scheduler=scheduler,
-            safety_checker=safety_checker,
-            feature_extractor=feature_extractor,
-        )
-        self.vae_scale_factor = 2 ** (len(self.vae.config.block_out_channels) - 1)
-        self.register_to_config(requires_safety_checker=requires_safety_checker)
-
-    def enable_vae_slicing(self):
-        r"""
-        Enable sliced VAE decoding.
-        When this option is enabled, the VAE will split the input tensor in slices to compute decoding in several
-        steps. This is useful to save some memory and allow larger batch sizes.
-        """
-        self.vae.enable_slicing()
-
-    def disable_vae_slicing(self):
-        r"""
-        Disable sliced VAE decoding. If `enable_vae_slicing` was previously invoked, this method will go back to
-        computing decoding in one step.
-        """
-        self.vae.disable_slicing()
-
-    def enable_sequential_cpu_offload(self, gpu_id=0):
-        r"""
-        Offloads all models to CPU using accelerate, significantly reducing memory usage. When called, unet,
-        text_encoder, vae, controlnet, and safety checker have their state dicts saved to CPU and then are moved to a
-        `torch.device('meta') and loaded to GPU only when their specific submodule has its `forward` method called.
-        Note that offloading happens on a submodule basis. Memory savings are higher than with
-        `enable_model_cpu_offload`, but performance is lower.
-        """
-        if is_accelerate_available():
-            from accelerate import cpu_offload
-        else:
-            raise ImportError("Please install accelerate via `pip install accelerate`")
-
-        device = torch.device(f"cuda:{gpu_id}")
-
-        for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae, self.controlnet]:
-            cpu_offload(cpu_offloaded_model, device)
-
-        if self.safety_checker is not None:
-            cpu_offload(self.safety_checker, execution_device=device, offload_buffers=True)
-
-    def enable_model_cpu_offload(self, gpu_id=0):
-        r"""
-        Offloads all models to CPU using accelerate, reducing memory usage with a low impact on performance. Compared
-        to `enable_sequential_cpu_offload`, this method moves one whole model at a time to the GPU when its `forward`
-        method is called, and the model remains in GPU until the next model runs. Memory savings are lower than with
-        `enable_sequential_cpu_offload`, but performance is much better due to the iterative execution of the `unet`.
-        """
-        if is_accelerate_available() and is_accelerate_version(">=", "0.17.0.dev0"):
-            from accelerate import cpu_offload_with_hook
-        else:
-            raise ImportError("`enable_model_offload` requires `accelerate v0.17.0` or higher.")
-
-        device = torch.device(f"cuda:{gpu_id}")
-
-        hook = None
-        for cpu_offloaded_model in [self.text_encoder, self.unet, self.vae]:
-            _, hook = cpu_offload_with_hook(cpu_offloaded_model, device, prev_module_hook=hook)
-
-        if self.safety_checker is not None:
-            # the safety checker can offload the vae again
-            _, hook = cpu_offload_with_hook(self.safety_checker, device, prev_module_hook=hook)
-
-        # control net hook has be manually offloaded as it alternates with unet
-        cpu_offload_with_hook(self.controlnet, device)
-
-        # We'll offload the last model manually.
-        self.final_offload_hook = hook
-
-    @property
-    def _execution_device(self):
-        r"""
-        Returns the device on which the pipeline's models will be executed. After calling
-        `pipeline.enable_sequential_cpu_offload()` the execution device can only be inferred from Accelerate's module
-        hooks.
-        """
-        if not hasattr(self.unet, "_hf_hook"):
-            return self.device
-        for module in self.unet.modules():
-            if (
-                hasattr(module, "_hf_hook")
-                and hasattr(module._hf_hook, "execution_device")
-                and module._hf_hook.execution_device is not None
-            ):
-                return torch.device(module._hf_hook.execution_device)
-        return self.device
-
-    def _encode_prompt(
-        self,
-        prompt,
-        device,
-        num_images_per_prompt,
-        do_classifier_free_guidance,
-        negative_prompt=None,
-        prompt_embeds: Optional[torch.FloatTensor] = None,
-        negative_prompt_embeds: Optional[torch.FloatTensor] = None,
-    ):
-        r"""
-        Encodes the prompt into text encoder hidden states.
-        Args:
-             prompt (`str` or `List[str]`, *optional*):
-                prompt to be encoded
-            device: (`torch.device`):
-                torch device
-            num_images_per_prompt (`int`):
-                number of images that should be generated per prompt
-            do_classifier_free_guidance (`bool`):
-                whether to use classifier free guidance or not
-            negative_prompt (`str` or `List[str]`, *optional*):
-                The prompt or prompts not to guide the image generation. If not defined, one has to pass
-                `negative_prompt_embeds`. instead. If not defined, one has to pass `negative_prompt_embeds`. instead.
-                Ignored when not using guidance (i.e., ignored if `guidance_scale` is less than `1`).
-            prompt_embeds (`torch.FloatTensor`, *optional*):
-                Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
-                provided, text embeddings will be generated from `prompt` input argument.
-            negative_prompt_embeds (`torch.FloatTensor`, *optional*):
-                Pre-generated negative text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt
-                weighting. If not provided, negative_prompt_embeds will be generated from `negative_prompt` input
-                argument.
-        """
-        if prompt is not None and isinstance(prompt, str):
-            batch_size = 1
-        elif prompt is not None and isinstance(prompt, list):
-            batch_size = len(prompt)
-        else:
-            batch_size = prompt_embeds.shape[0]
-
-        if prompt_embeds is None:
-            text_inputs = self.tokenizer(
-                prompt,
-                padding="max_length",
-                max_length=self.tokenizer.model_max_length,
-                truncation=True,
-                return_tensors="pt",
-            )
-            text_input_ids = text_inputs.input_ids
-            untruncated_ids = self.tokenizer(prompt, padding="longest", return_tensors="pt").input_ids
-
-            if untruncated_ids.shape[-1] >= text_input_ids.shape[-1] and not torch.equal(
-                text_input_ids, untruncated_ids
-            ):
-                removed_text = self.tokenizer.batch_decode(
-                    untruncated_ids[:, self.tokenizer.model_max_length - 1 : -1]
-                )
-                logger.warning(
-                    "The following part of your input was truncated because CLIP can only handle sequences up to"
-                    f" {self.tokenizer.model_max_length} tokens: {removed_text}"
-                )
-
-            if hasattr(self.text_encoder.config, "use_attention_mask") and self.text_encoder.config.use_attention_mask:
-                attention_mask = text_inputs.attention_mask.to(device)
-            else:
-                attention_mask = None
-
-            prompt_embeds = self.text_encoder(
-                text_input_ids.to(device),
-                attention_mask=attention_mask,
-            )
-            prompt_embeds = prompt_embeds[0]
-
-        prompt_embeds = prompt_embeds.to(dtype=self.text_encoder.dtype, device=device)
-
-        bs_embed, seq_len, _ = prompt_embeds.shape
-        # duplicate text embeddings for each generation per prompt, using mps friendly method
-        prompt_embeds = prompt_embeds.repeat(1, num_images_per_prompt, 1)
-        prompt_embeds = prompt_embeds.view(bs_embed * num_images_per_prompt, seq_len, -1)
-
-        # get unconditional embeddings for classifier free guidance
-        if do_classifier_free_guidance and negative_prompt_embeds is None:
-            uncond_tokens: List[str]
-            if negative_prompt is None:
-                uncond_tokens = [""] * batch_size
-            elif type(prompt) is not type(negative_prompt):
-                raise TypeError(
-                    f"`negative_prompt` should be the same type to `prompt`, but got {type(negative_prompt)} !="
-                    f" {type(prompt)}."
-                )
-            elif isinstance(negative_prompt, str):
-                uncond_tokens = [negative_prompt]
-            elif batch_size != len(negative_prompt):
-                raise ValueError(
-                    f"`negative_prompt`: {negative_prompt} has batch size {len(negative_prompt)}, but `prompt`:"
-                    f" {prompt} has batch size {batch_size}. Please make sure that passed `negative_prompt` matches"
-                    " the batch size of `prompt`."
-                )
-            else:
-                uncond_tokens = negative_prompt
-
-            max_length = prompt_embeds.shape[1]
-            uncond_input = self.tokenizer(
-                uncond_tokens,
-                padding="max_length",
-                max_length=max_length,
-                truncation=True,
-                return_tensors="pt",
-            )
-
-            if hasattr(self.text_encoder.config, "use_attention_mask") and self.text_encoder.config.use_attention_mask:
-                attention_mask = uncond_input.attention_mask.to(device)
-            else:
-                attention_mask = None
-
-            negative_prompt_embeds = self.text_encoder(
-                uncond_input.input_ids.to(device),
-                attention_mask=attention_mask,
-            )
-            negative_prompt_embeds = negative_prompt_embeds[0]
-
-        if do_classifier_free_guidance:
-            # duplicate unconditional embeddings for each generation per prompt, using mps friendly method
-            seq_len = negative_prompt_embeds.shape[1]
-
-            negative_prompt_embeds = negative_prompt_embeds.to(dtype=self.text_encoder.dtype, device=device)
-
-            negative_prompt_embeds = negative_prompt_embeds.repeat(1, num_images_per_prompt, 1)
-            negative_prompt_embeds = negative_prompt_embeds.view(batch_size * num_images_per_prompt, seq_len, -1)
-
-            # For classifier free guidance, we need to do two forward passes.
-            # Here we concatenate the unconditional and text embeddings into a single batch
-            # to avoid doing two forward passes
-            prompt_embeds = torch.cat([negative_prompt_embeds, prompt_embeds])
-
-        return prompt_embeds
-
-    def run_safety_checker(self, image, device, dtype):
-        if self.safety_checker is not None:
-            safety_checker_input = self.feature_extractor(self.numpy_to_pil(image), return_tensors="pt").to(device)
-            image, has_nsfw_concept = self.safety_checker(
-                images=image, clip_input=safety_checker_input.pixel_values.to(dtype)
-            )
-        else:
-            has_nsfw_concept = None
-        return image, has_nsfw_concept
-
-    def decode_latents(self, latents):
-        latents = 1 / self.vae.config.scaling_factor * latents
-        image = self.vae.decode(latents).sample
-        image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
-        image = image.cpu().permute(0, 2, 3, 1).float().numpy()
-        return image
-
-    def prepare_extra_step_kwargs(self, generator, eta):
-        # prepare extra kwargs for the scheduler step, since not all schedulers have the same signature
-        # eta (η) is only used with the DDIMScheduler, it will be ignored for other schedulers.
-        # eta corresponds to η in DDIM paper: https://arxiv.org/abs/2010.02502
-        # and should be between [0, 1]
-
-        accepts_eta = "eta" in set(inspect.signature(self.scheduler.step).parameters.keys())
-        extra_step_kwargs = {}
-        if accepts_eta:
-            extra_step_kwargs["eta"] = eta
-
-        # check if the scheduler accepts generator
-        accepts_generator = "generator" in set(inspect.signature(self.scheduler.step).parameters.keys())
-        if accepts_generator:
-            extra_step_kwargs["generator"] = generator
-        return extra_step_kwargs
-
-    def check_inputs(
-        self,
-        prompt,
-        image,
-        mask_image,
-        controlnet_conditioning_image,
-        height,
-        width,
-        callback_steps,
-        negative_prompt=None,
-        prompt_embeds=None,
-        negative_prompt_embeds=None,
-        strength=None,
-    ):
-        if height % 8 != 0 or width % 8 != 0:
-            raise ValueError(f"`height` and `width` have to be divisible by 8 but are {height} and {width}.")
-
-        if (callback_steps is None) or (
-            callback_steps is not None and (not isinstance(callback_steps, int) or callback_steps <= 0)
-        ):
-            raise ValueError(
-                f"`callback_steps` has to be a positive integer but is {callback_steps} of type"
-                f" {type(callback_steps)}."
-            )
-
-        if prompt is not None and prompt_embeds is not None:
-            raise ValueError(
-                f"Cannot forward both `prompt`: {prompt} and `prompt_embeds`: {prompt_embeds}. Please make sure to"
-                " only forward one of the two."
-            )
-        elif prompt is None and prompt_embeds is None:
-            raise ValueError(
-                "Provide either `prompt` or `prompt_embeds`. Cannot leave both `prompt` and `prompt_embeds` undefined."
-            )
-        elif prompt is not None and (not isinstance(prompt, str) and not isinstance(prompt, list)):
-            raise ValueError(f"`prompt` has to be of type `str` or `list` but is {type(prompt)}")
-
-        if negative_prompt is not None and negative_prompt_embeds is not None:
-            raise ValueError(
-                f"Cannot forward both `negative_prompt`: {negative_prompt} and `negative_prompt_embeds`:"
-                f" {negative_prompt_embeds}. Please make sure to only forward one of the two."
-            )
-
-        if prompt_embeds is not None and negative_prompt_embeds is not None:
-            if prompt_embeds.shape != negative_prompt_embeds.shape:
-                raise ValueError(
-                    "`prompt_embeds` and `negative_prompt_embeds` must have the same shape when passed directly, but"
-                    f" got: `prompt_embeds` {prompt_embeds.shape} != `negative_prompt_embeds`"
-                    f" {negative_prompt_embeds.shape}."
-                )
-
-        controlnet_cond_image_is_pil = isinstance(controlnet_conditioning_image, PIL.Image.Image)
-        controlnet_cond_image_is_tensor = isinstance(controlnet_conditioning_image, torch.Tensor)
-        controlnet_cond_image_is_pil_list = isinstance(controlnet_conditioning_image, list) and isinstance(
-            controlnet_conditioning_image[0], PIL.Image.Image
-        )
-        controlnet_cond_image_is_tensor_list = isinstance(controlnet_conditioning_image, list) and isinstance(
-            controlnet_conditioning_image[0], torch.Tensor
-        )
-
-        if (
-            not controlnet_cond_image_is_pil
-            and not controlnet_cond_image_is_tensor
-            and not controlnet_cond_image_is_pil_list
-            and not controlnet_cond_image_is_tensor_list
-        ):
-            raise TypeError(
-                "image must be passed and be one of PIL image, torch tensor, list of PIL images, or list of torch tensors"
-            )
-
-        if controlnet_cond_image_is_pil:
-            controlnet_cond_image_batch_size = 1
-        elif controlnet_cond_image_is_tensor:
-            controlnet_cond_image_batch_size = controlnet_conditioning_image.shape[0]
-        elif controlnet_cond_image_is_pil_list:
-            controlnet_cond_image_batch_size = len(controlnet_conditioning_image)
-        elif controlnet_cond_image_is_tensor_list:
-            controlnet_cond_image_batch_size = len(controlnet_conditioning_image)
-
-        if prompt is not None and isinstance(prompt, str):
-            prompt_batch_size = 1
-        elif prompt is not None and isinstance(prompt, list):
-            prompt_batch_size = len(prompt)
-        elif prompt_embeds is not None:
-            prompt_batch_size = prompt_embeds.shape[0]
-
-        if controlnet_cond_image_batch_size != 1 and controlnet_cond_image_batch_size != prompt_batch_size:
-            raise ValueError(
-                f"If image batch size is not 1, image batch size must be same as prompt batch size. image batch size: {controlnet_cond_image_batch_size}, prompt batch size: {prompt_batch_size}"
-            )
-
-        if isinstance(image, torch.Tensor) and not isinstance(mask_image, torch.Tensor):
-            raise TypeError("if `image` is a tensor, `mask_image` must also be a tensor")
-
-        if isinstance(image, PIL.Image.Image) and not isinstance(mask_image, PIL.Image.Image):
-            raise TypeError("if `image` is a PIL image, `mask_image` must also be a PIL image")
-
-        if isinstance(image, torch.Tensor):
-            if image.ndim != 3 and image.ndim != 4:
-                raise ValueError("`image` must have 3 or 4 dimensions")
-
-            if mask_image.ndim != 2 and mask_image.ndim != 3 and mask_image.ndim != 4:
-                raise ValueError("`mask_image` must have 2, 3, or 4 dimensions")
-
-            if image.ndim == 3:
-                image_batch_size = 1
-                image_channels, image_height, image_width = image.shape
-            elif image.ndim == 4:
-                image_batch_size, image_channels, image_height, image_width = image.shape
-
-            if mask_image.ndim == 2:
-                mask_image_batch_size = 1
-                mask_image_channels = 1
-                mask_image_height, mask_image_width = mask_image.shape
-            elif mask_image.ndim == 3:
-                mask_image_channels = 1
-                mask_image_batch_size, mask_image_height, mask_image_width = mask_image.shape
-            elif mask_image.ndim == 4:
-                mask_image_batch_size, mask_image_channels, mask_image_height, mask_image_width = mask_image.shape
-
-            if image_channels != 3:
-                raise ValueError("`image` must have 3 channels")
-
-            if mask_image_channels != 1:
-                raise ValueError("`mask_image` must have 1 channel")
-
-            if image_batch_size != mask_image_batch_size:
-                raise ValueError("`image` and `mask_image` mush have the same batch sizes")
-
-            if image_height != mask_image_height or image_width != mask_image_width:
-                raise ValueError("`image` and `mask_image` must have the same height and width dimensions")
-
-            if image.min() < -1 or image.max() > 1:
-                raise ValueError("`image` should be in range [-1, 1]")
-
-            if mask_image.min() < 0 or mask_image.max() > 1:
-                raise ValueError("`mask_image` should be in range [0, 1]")
-        else:
-            mask_image_channels = 1
-            image_channels = 3
-
-        single_image_latent_channels = self.vae.config.latent_channels
-
-        total_latent_channels = single_image_latent_channels * 2 + mask_image_channels
-
-        if total_latent_channels != self.unet.config.in_channels:
-            raise ValueError(
-                f"The config of `pipeline.unet` expects {self.unet.config.in_channels} but received"
-                f" non inpainting latent channels: {single_image_latent_channels},"
-                f" mask channels: {mask_image_channels}, and masked image channels: {single_image_latent_channels}."
-                f" Please verify the config of `pipeline.unet` and the `mask_image` and `image` inputs."
-            )
-
-        if strength < 0 or strength > 1:
-            raise ValueError(f"The value of strength should in [0.0, 1.0] but is {strength}")
-
-    def get_timesteps(self, num_inference_steps, strength, device):
-        # get the original timestep using init_timestep
-        init_timestep = min(int(num_inference_steps * strength), num_inference_steps)
-
-        t_start = max(num_inference_steps - init_timestep, 0)
-        timesteps = self.scheduler.timesteps[t_start:]
-
-        return timesteps, num_inference_steps - t_start
-
-    def prepare_latents(self, image, timestep, batch_size, num_images_per_prompt, dtype, device, generator=None):
-        if not isinstance(image, (torch.Tensor, PIL.Image.Image, list)):
-            raise ValueError(
-                f"`image` has to be of type `torch.Tensor`, `PIL.Image.Image` or list but is {type(image)}"
-            )
-
-        image = image.to(device=device, dtype=dtype)
-
-        batch_size = batch_size * num_images_per_prompt
-        if isinstance(generator, list) and len(generator) != batch_size:
-            raise ValueError(
-                f"You have passed a list of generators of length {len(generator)}, but requested an effective batch"
-                f" size of {batch_size}. Make sure the batch size matches the length of the generators."
-            )
-
-        if isinstance(generator, list):
-            init_latents = [
-                self.vae.encode(image[i : i + 1]).latent_dist.sample(generator[i]) for i in range(batch_size)
-            ]
-            init_latents = torch.cat(init_latents, dim=0)
-        else:
-            init_latents = self.vae.encode(image).latent_dist.sample(generator)
-
-        init_latents = self.vae.config.scaling_factor * init_latents
-
-        if batch_size > init_latents.shape[0] and batch_size % init_latents.shape[0] == 0:
-            raise ValueError(
-                f"Cannot duplicate `image` of batch size {init_latents.shape[0]} to {batch_size} text prompts."
-            )
-        else:
-            init_latents = torch.cat([init_latents], dim=0)
-
-        shape = init_latents.shape
-        noise = randn_tensor(shape, generator=generator, device=device, dtype=dtype)
-
-        # get latents
-        init_latents = self.scheduler.add_noise(init_latents, noise, timestep)
-        latents = init_latents
-
-        return latents
-
-    def prepare_mask_latents(self, mask_image, batch_size, height, width, dtype, device, do_classifier_free_guidance):
-        # resize the mask to latents shape as we concatenate the mask to the latents
-        # we do that before converting to dtype to avoid breaking in case we're using cpu_offload
-        # and half precision
-        mask_image = F.interpolate(mask_image, size=(height // self.vae_scale_factor, width // self.vae_scale_factor))
-        mask_image = mask_image.to(device=device, dtype=dtype)
-
-        # duplicate mask for each generation per prompt, using mps friendly method
-        if mask_image.shape[0] < batch_size:
-            if not batch_size % mask_image.shape[0] == 0:
-                raise ValueError(
-                    "The passed mask and the required batch size don't match. Masks are supposed to be duplicated to"
-                    f" a total batch size of {batch_size}, but {mask_image.shape[0]} masks were passed. Make sure the number"
-                    " of masks that you pass is divisible by the total requested batch size."
-                )
-            mask_image = mask_image.repeat(batch_size // mask_image.shape[0], 1, 1, 1)
-
-        mask_image = torch.cat([mask_image] * 2) if do_classifier_free_guidance else mask_image
-
-        mask_image_latents = mask_image
-
-        return mask_image_latents
-
-    def prepare_masked_image_latents(
-        self, masked_image, batch_size, height, width, dtype, device, generator, do_classifier_free_guidance
-    ):
-        masked_image = masked_image.to(device=device, dtype=dtype)
-
-        # encode the mask image into latents space so we can concatenate it to the latents
-        if isinstance(generator, list):
-            masked_image_latents = [
-                self.vae.encode(masked_image[i : i + 1]).latent_dist.sample(generator=generator[i])
-                for i in range(batch_size)
-            ]
-            masked_image_latents = torch.cat(masked_image_latents, dim=0)
-        else:
-            masked_image_latents = self.vae.encode(masked_image).latent_dist.sample(generator=generator)
-        masked_image_latents = self.vae.config.scaling_factor * masked_image_latents
-
-        # duplicate masked_image_latents for each generation per prompt, using mps friendly method
-        if masked_image_latents.shape[0] < batch_size:
-            if not batch_size % masked_image_latents.shape[0] == 0:
-                raise ValueError(
-                    "The passed images and the required batch size don't match. Images are supposed to be duplicated"
-                    f" to a total batch size of {batch_size}, but {masked_image_latents.shape[0]} images were passed."
-                    " Make sure the number of images that you pass is divisible by the total requested batch size."
-                )
-            masked_image_latents = masked_image_latents.repeat(batch_size // masked_image_latents.shape[0], 1, 1, 1)
-
-        masked_image_latents = (
-            torch.cat([masked_image_latents] * 2) if do_classifier_free_guidance else masked_image_latents
-        )
-
-        # aligning device to prevent device errors when concating it with the latent model input
-        masked_image_latents = masked_image_latents.to(device=device, dtype=dtype)
-        return masked_image_latents
-
-    def _default_height_width(self, height, width, image):
-        if isinstance(image, list):
-            image = image[0]
-
-        if height is None:
-            if isinstance(image, PIL.Image.Image):
-                height = image.height
-            elif isinstance(image, torch.Tensor):
-                height = image.shape[3]
-
-            height = (height // 8) * 8  # round down to nearest multiple of 8
-
-        if width is None:
-            if isinstance(image, PIL.Image.Image):
-                width = image.width
-            elif isinstance(image, torch.Tensor):
-                width = image.shape[2]
-
-            width = (width // 8) * 8  # round down to nearest multiple of 8
-
-        return height, width
-
-    @torch.no_grad()
-    @replace_example_docstring(EXAMPLE_DOC_STRING)
-    def __call__(
-        self,
-        prompt: Union[str, List[str]] = None,
-        image: Union[torch.Tensor, PIL.Image.Image] = None,
-        mask_image: Union[torch.Tensor, PIL.Image.Image] = None,
-        controlnet_conditioning_image: Union[
-            torch.FloatTensor, PIL.Image.Image, List[torch.FloatTensor], List[PIL.Image.Image]
-        ] = None,
-        strength: float = 0.8,
-        height: Optional[int] = None,
-        width: Optional[int] = None,
-        num_inference_steps: int = 50,
-        guidance_scale: float = 7.5,
-        negative_prompt: Optional[Union[str, List[str]]] = None,
-        num_images_per_prompt: Optional[int] = 1,
-        eta: float = 0.0,
-        generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None,
-        latents: Optional[torch.FloatTensor] = None,
-        prompt_embeds: Optional[torch.FloatTensor] = None,
-        negative_prompt_embeds: Optional[torch.FloatTensor] = None,
-        output_type: Optional[str] = "pil",
-        return_dict: bool = True,
-        callback: Optional[Callable[[int, int, torch.FloatTensor], None]] = None,
-        callback_steps: int = 1,
-        cross_attention_kwargs: Optional[Dict[str, Any]] = None,
-        controlnet_conditioning_scale: float = 1.0,
-        controlnet_conditioning_scale_decay: float = 0.95,
-        controlnet_steps: int = 10, 
-    ):
-        r"""
-        Function invoked when calling the pipeline for generation.
-        Args:
-            prompt (`str` or `List[str]`, *optional*):
-                The prompt or prompts to guide the image generation. If not defined, one has to pass `prompt_embeds`.
-                instead.
-            image (`torch.Tensor` or `PIL.Image.Image`):
-                `Image`, or tensor representing an image batch which will be inpainted, *i.e.* parts of the image will
-                be masked out with `mask_image` and repainted according to `prompt`.
-            mask_image (`torch.Tensor` or `PIL.Image.Image`):
-                `Image`, or tensor representing an image batch, to mask `image`. White pixels in the mask will be
-                repainted, while black pixels will be preserved. If `mask_image` is a PIL image, it will be converted
-                to a single channel (luminance) before use. If it's a tensor, it should contain one color channel (L)
-                instead of 3, so the expected shape would be `(B, H, W, 1)`.
-            controlnet_conditioning_image (`torch.FloatTensor`, `PIL.Image.Image`, `List[torch.FloatTensor]` or `List[PIL.Image.Image]`):
-                The ControlNet input condition. ControlNet uses this input condition to generate guidance to Unet. If
-                the type is specified as `Torch.FloatTensor`, it is passed to ControlNet as is. PIL.Image.Image` can
-                also be accepted as an image. The control image is automatically resized to fit the output image.
-            strength (`float`, *optional*):
-                Conceptually, indicates how much to transform the reference `image`. Must be between 0 and 1. `image`
-                will be used as a starting point, adding more noise to it the larger the `strength`. The number of
-                denoising steps depends on the amount of noise initially added. When `strength` is 1, added noise will
-                be maximum and the denoising process will run for the full number of iterations specified in
-                `num_inference_steps`. A value of 1, therefore, essentially ignores `image`.
-            height (`int`, *optional*, defaults to self.unet.config.sample_size * self.vae_scale_factor):
-                The height in pixels of the generated image.
-            width (`int`, *optional*, defaults to self.unet.config.sample_size * self.vae_scale_factor):
-                The width in pixels of the generated image.
-            num_inference_steps (`int`, *optional*, defaults to 50):
-                The number of denoising steps. More denoising steps usually lead to a higher quality image at the
-                expense of slower inference.
-            guidance_scale (`float`, *optional*, defaults to 7.5):
-                Guidance scale as defined in [Classifier-Free Diffusion Guidance](https://arxiv.org/abs/2207.12598).
-                `guidance_scale` is defined as `w` of equation 2. of [Imagen
-                Paper](https://arxiv.org/pdf/2205.11487.pdf). Guidance scale is enabled by setting `guidance_scale >
-                1`. Higher guidance scale encourages to generate images that are closely linked to the text `prompt`,
-                usually at the expense of lower image quality.
-            negative_prompt (`str` or `List[str]`, *optional*):
-                The prompt or prompts not to guide the image generation. If not defined, one has to pass
-                `negative_prompt_embeds`. instead. If not defined, one has to pass `negative_prompt_embeds`. instead.
-                Ignored when not using guidance (i.e., ignored if `guidance_scale` is less than `1`).
-            num_images_per_prompt (`int`, *optional*, defaults to 1):
-                The number of images to generate per prompt.
-            eta (`float`, *optional*, defaults to 0.0):
-                Corresponds to parameter eta (η) in the DDIM paper: https://arxiv.org/abs/2010.02502. Only applies to
-                [`schedulers.DDIMScheduler`], will be ignored for others.
-            generator (`torch.Generator` or `List[torch.Generator]`, *optional*):
-                One or a list of [torch generator(s)](https://pytorch.org/docs/stable/generated/torch.Generator.html)
-                to make generation deterministic.
-            latents (`torch.FloatTensor`, *optional*):
-                Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
-                generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
-            prompt_embeds (`torch.FloatTensor`, *optional*):
-                Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
-                provided, text embeddings will be generated from `prompt` input argument.
-            negative_prompt_embeds (`torch.FloatTensor`, *optional*):
-                Pre-generated negative text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt
-                weighting. If not provided, negative_prompt_embeds will be generated from `negative_prompt` input
-                argument.
-            output_type (`str`, *optional*, defaults to `"pil"`):
-                The output format of the generate image. Choose between
-                [PIL](https://pillow.readthedocs.io/en/stable/): `PIL.Image.Image` or `np.array`.
-            return_dict (`bool`, *optional*, defaults to `True`):
-                Whether or not to return a [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] instead of a
-                plain tuple.
-            callback (`Callable`, *optional*):
-                A function that will be called every `callback_steps` steps during inference. The function will be
-                called with the following arguments: `callback(step: int, timestep: int, latents: torch.FloatTensor)`.
-            callback_steps (`int`, *optional*, defaults to 1):
-                The frequency at which the `callback` function will be called. If not specified, the callback will be
-                called at every step.
-            cross_attention_kwargs (`dict`, *optional*):
-                A kwargs dictionary that if specified is passed along to the `AttentionProcessor` as defined under
-                `self.processor` in
-                [diffusers.cross_attention](https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/cross_attention.py).
-            controlnet_conditioning_scale (`float`, *optional*, defaults to 1.0):
-                The outputs of the controlnet are multiplied by `controlnet_conditioning_scale` before they are added
-                to the residual in the original unet.
-        Examples:
-        Returns:
-            [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] or `tuple`:
-            [`~pipelines.stable_diffusion.StableDiffusionPipelineOutput`] if `return_dict` is True, otherwise a `tuple.
-            When returning a tuple, the first element is a list with the generated images, and the second element is a
-            list of `bool`s denoting whether the corresponding generated image likely represents "not-safe-for-work"
-            (nsfw) content, according to the `safety_checker`.
-        """
-        # 0. Default height and width to unet
-        height, width = self._default_height_width(height, width, controlnet_conditioning_image)
-
-        # 1. Check inputs. Raise error if not correct
-        self.check_inputs(
-            prompt,
-            image,
-            mask_image,
-            controlnet_conditioning_image,
-            height,
-            width,
-            callback_steps,
-            negative_prompt,
-            prompt_embeds,
-            negative_prompt_embeds,
-            strength,
-        )
-
-        # 2. Define call parameters
-        if prompt is not None and isinstance(prompt, str):
-            batch_size = 1
-        elif prompt is not None and isinstance(prompt, list):
-            batch_size = len(prompt)
-        else:
-            batch_size = prompt_embeds.shape[0]
-
-        device = self._execution_device
-        # here `guidance_scale` is defined analog to the guidance weight `w` of equation (2)
-        # of the Imagen paper: https://arxiv.org/pdf/2205.11487.pdf . `guidance_scale = 1`
-        # corresponds to doing no classifier free guidance.
-        do_classifier_free_guidance = guidance_scale > 1.0
-
-        # 3. Encode input prompt
-        prompt_embeds = self._encode_prompt(
-            prompt,
-            device,
-            num_images_per_prompt,
-            do_classifier_free_guidance,
-            negative_prompt,
-            prompt_embeds=prompt_embeds,
-            negative_prompt_embeds=negative_prompt_embeds,
-        )
-
-        # 4. Prepare mask, image, and controlnet_conditioning_image
-        image = prepare_image(image)
-
-        mask_image = prepare_mask_image(mask_image)
-
-        controlnet_conditioning_image = prepare_controlnet_conditioning_image(
-            controlnet_conditioning_image,
-            width,
-            height,
-            batch_size * num_images_per_prompt,
-            num_images_per_prompt,
-            device,
-            self.controlnet.dtype,
-        )
-
-        masked_image = image * (mask_image < 0.5)
-
-        # 5. Prepare timesteps
-        self.scheduler.set_timesteps(num_inference_steps, device=device)
-        timesteps, num_inference_steps = self.get_timesteps(num_inference_steps, strength, device)
-        latent_timestep = timesteps[:1].repeat(batch_size * num_images_per_prompt)
-
-        # 6. Prepare latent variables
-        latents = self.prepare_latents(
-            image,
-            latent_timestep,
-            batch_size,
-            num_images_per_prompt,
-            prompt_embeds.dtype,
-            device,
-            generator,
-        )
-
-        mask_image_latents = self.prepare_mask_latents(
-            mask_image,
-            batch_size * num_images_per_prompt,
-            height,
-            width,
-            prompt_embeds.dtype,
-            device,
-            do_classifier_free_guidance,
-        )
-
-        masked_image_latents = self.prepare_masked_image_latents(
-            masked_image,
-            batch_size * num_images_per_prompt,
-            height,
-            width,
-            prompt_embeds.dtype,
-            device,
-            generator,
-            do_classifier_free_guidance,
-        )
-
-        if do_classifier_free_guidance:
-            controlnet_conditioning_image = torch.cat([controlnet_conditioning_image] * 2)
-
-        # 7. Prepare extra step kwargs. TODO: Logic should ideally just be moved out of the pipeline
-        extra_step_kwargs = self.prepare_extra_step_kwargs(generator, eta)
-
-        # 8. Denoising loop
-        num_warmup_steps = len(timesteps) - num_inference_steps * self.scheduler.order
-        with self.progress_bar(total=num_inference_steps) as progress_bar:
-            for i, t in enumerate(timesteps):
-                # expand the latents if we are doing classifier free guidance
-                non_inpainting_latent_model_input = (
-                    torch.cat([latents] * 2) if do_classifier_free_guidance else latents
-                )
-
-                non_inpainting_latent_model_input = self.scheduler.scale_model_input(
-                    non_inpainting_latent_model_input, t
-                )
-
-                inpainting_latent_model_input = torch.cat(
-                    [non_inpainting_latent_model_input, mask_image_latents, masked_image_latents], dim=1
-                )
-
-                down_block_res_samples, mid_block_res_sample = self.controlnet(
-                    non_inpainting_latent_model_input,
-                    t,
-                    encoder_hidden_states=prompt_embeds,
-                    controlnet_cond=controlnet_conditioning_image,
-                    return_dict=False,
-                )
-                if i <= controlnet_steps:
-                    conditioning_scale = (controlnet_conditioning_scale * controlnet_conditioning_scale_decay ** i)
-                else:
-                    conditioning_scale = 0.0
-
-                down_block_res_samples = [
-                    down_block_res_sample * conditioning_scale
-                    for down_block_res_sample in down_block_res_samples
-                ]
-                mid_block_res_sample *= conditioning_scale
-
-                # predict the noise residual
-                noise_pred = self.unet(
-                    inpainting_latent_model_input,
-                    t,
-                    encoder_hidden_states=prompt_embeds,
-                    cross_attention_kwargs=cross_attention_kwargs,
-                    down_block_additional_residuals=down_block_res_samples,
-                    mid_block_additional_residual=mid_block_res_sample,
-                ).sample
-
-                # perform guidance
-                if do_classifier_free_guidance:
-                    noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)
-                    noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond)
-
-                # compute the previous noisy sample x_t -> x_t-1
-                latents = self.scheduler.step(noise_pred, t, latents, **extra_step_kwargs).prev_sample
-
-                # call the callback, if provided
-                if i == len(timesteps) - 1 or ((i + 1) > num_warmup_steps and (i + 1) % self.scheduler.order == 0):
-                    progress_bar.update()
-                    if callback is not None and i % callback_steps == 0:
-                        callback(i, t, latents)
-
-        # If we do sequential model offloading, let's offload unet and controlnet
-        # manually for max memory savings
-        if hasattr(self, "final_offload_hook") and self.final_offload_hook is not None:
-            self.unet.to("cpu")
-            self.controlnet.to("cpu")
-            torch.cuda.empty_cache()
-
-        if output_type == "latent":
-            image = latents
-            has_nsfw_concept = None
-        elif output_type == "pil":
-            # 8. Post-processing
-            image = self.decode_latents(latents)
-
-            # 9. Run safety checker
-            image, has_nsfw_concept = self.run_safety_checker(image, device, prompt_embeds.dtype)
-
-            # 10. Convert to PIL
-            image = self.numpy_to_pil(image)
-        else:
-            # 8. Post-processing
-            image = self.decode_latents(latents)
-
-            # 9. Run safety checker
-            image, has_nsfw_concept = self.run_safety_checker(image, device, prompt_embeds.dtype)
-
-        # Offload last model to CPU
-        if hasattr(self, "final_offload_hook") and self.final_offload_hook is not None:
-            self.final_offload_hook.offload()
-
-        if not return_dict:
-            return (image, has_nsfw_concept)
-
-        return StableDiffusionPipelineOutput(images=image, nsfw_content_detected=has_nsfw_concept)
\ No newline at end of file
diff --git a/spaces/mlpc-lab/BLIVA/bliva/models/blip2.py b/spaces/mlpc-lab/BLIVA/bliva/models/blip2.py
deleted file mode 100644
index ac6e2f819ce38e46381da29dee06fe38d9e1317a..0000000000000000000000000000000000000000
--- a/spaces/mlpc-lab/BLIVA/bliva/models/blip2.py
+++ /dev/null
@@ -1,319 +0,0 @@
-"""
- Copyright (c) 2023, salesforce.com, inc.
- All rights reserved.
- SPDX-License-Identifier: BSD-3-Clause
- For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/BSD-3-Clause
-"""
-import contextlib
-import logging
-import os
-import time
-import datetime
-
-import torch
-import torch.nn as nn
-import torch.distributed as dist
-import torch.nn.functional as F
-
-import bliva.common.dist_utils as dist_utils
-from bliva.common.dist_utils import download_cached_file
-from bliva.common.utils import is_url
-from bliva.common.logger import MetricLogger
-from bliva.models.base_model import BaseModel
-from bliva.models.Qformer import BertConfig, BertLMHeadModel
-from bliva.models.eva_vit import create_eva_vit_g
-from bliva.models.clip_vit import create_clip_vit_L
-from transformers import BertTokenizer
-
-
-class Blip2Base(BaseModel):
-    @classmethod
-    def init_tokenizer(cls, truncation_side="right"):
-        tokenizer = BertTokenizer.from_pretrained("bert-base-uncased", truncation_side=truncation_side)
-        tokenizer.add_special_tokens({"bos_token": "[DEC]"})
-        return tokenizer
-
-    def maybe_autocast(self, dtype=torch.float16):
-        # if on cpu, don't use autocast
-        # if on gpu, use autocast with dtype if provided, otherwise use torch.float16
-        enable_autocast = self.device != torch.device("cpu")
-
-        if enable_autocast:
-            return torch.cuda.amp.autocast(dtype=dtype)
-        else:
-            return contextlib.nullcontext()
-
-    @classmethod
-    def init_Qformer(cls, num_query_token, vision_width, cross_attention_freq=2):
-        encoder_config = BertConfig.from_pretrained("bert-base-uncased")
-        encoder_config.encoder_width = vision_width
-        # insert cross-attention layer every other block
-        encoder_config.add_cross_attention = True
-        encoder_config.cross_attention_freq = cross_attention_freq
-        encoder_config.query_length = num_query_token
-        Qformer = BertLMHeadModel.from_pretrained(
-            "bert-base-uncased", config=encoder_config
-        )
-        query_tokens = nn.Parameter(
-            torch.zeros(1, num_query_token, encoder_config.hidden_size)
-        )
-        query_tokens.data.normal_(mean=0.0, std=encoder_config.initializer_range) #0.02
-        return Qformer, query_tokens
-
-    def init_vision_encoder(
-        self, model_name, img_size, drop_path_rate, use_grad_checkpoint, precision
-    ):
-        assert model_name in [
-            "eva_clip_g",
-            "eva2_clip_L",
-            "clip_L",
-            'cpe_eva_clip_g'
-        ], "vit model must be eva_clip_g, eva2_clip_L or clip_L or cpe_eva_clip_g"
-        if model_name == "eva_clip_g":
-            visual_encoder = create_eva_vit_g(
-                img_size, drop_path_rate, use_grad_checkpoint, precision
-            )
-#         elif model_name == "eva2_clip_L":
-#             visual_encoder = create_eva2_vit_L(
-#                 img_size, drop_path_rate, use_grad_checkpoint, precision
-#             )
-        elif model_name == "clip_L":
-            visual_encoder = create_clip_vit_L(img_size, use_grad_checkpoint, precision)
-            
-        ln_vision = LayerNorm(visual_encoder.num_features)
-        self.vit_name = model_name
-        return visual_encoder, ln_vision
-
-    def load_from_pretrained(self, url_or_filename):
-        if is_url(url_or_filename):
-            cached_file = download_cached_file(
-                url_or_filename, check_hash=False, progress=True
-            )
-            checkpoint = torch.load(cached_file, map_location="cpu")
-        elif os.path.isfile(url_or_filename):
-            checkpoint = torch.load(url_or_filename, map_location="cpu")
-        else:
-            raise RuntimeError("checkpoint url or path is invalid")
-
-        state_dict = checkpoint["model"]
-
-        msg = self.load_state_dict(state_dict, strict=False)
-
-        # logging.info("Missing keys {}".format(msg.missing_keys))
-        logging.info("load checkpoint from %s" % url_or_filename)
-
-        return msg
-
-    def get_optimizer_params(self, weight_decay, lr_scale=1):
-        if self.vit_name == "eva_clip_g":
-            vit_num_layers = self.visual_encoder.get_num_layer()
-            lr_scales = list(lr_scale ** (vit_num_layers + 1 - i) for i in range(vit_num_layers + 2))
-
-            parameter_group_names = {}
-            parameter_group_vars = {}
-
-            for name, param in self.named_parameters():
-                if not param.requires_grad:
-                    continue  # frozen weights
-                if len(param.shape) == 1 or name.endswith(".bias"):
-                    group_name = "no_decay"
-                    this_weight_decay = 0.
-                else:
-                    group_name = "decay"
-                    this_weight_decay = weight_decay
-                if 'visual_encoder' in name:
-                    layer_id = self.visual_encoder.get_num_layer(name.replace('visual_encoder.',''))
-                    group_name = "vit_layer_%d_%s" % (layer_id, group_name)
-                else:
-                    layer_id = None
-
-                if group_name not in parameter_group_names:
-                    if layer_id is not None:
-                        scale = lr_scales[layer_id]
-                    else:
-                        scale = 1
-                    parameter_group_names[group_name] = {
-                        "weight_decay": this_weight_decay,
-                        "params": [],
-                        "lr_scale": scale
-                    }
-                    parameter_group_vars[group_name] = {
-                        "weight_decay": this_weight_decay,
-                        "params": [],
-                        "lr_scale": scale
-                    }
-                parameter_group_vars[group_name]["params"].append(param)
-                parameter_group_names[group_name]["params"].append(name)
-            # import json
-            # print("Param groups = %s" % json.dumps(parameter_group_names, indent=2))
-            optim_params = list(parameter_group_vars.values())
-            return optim_params
-        else:
-            return super().get_optimizer_params(weight_decay,lr_scale)
-
-    def _lemmatize(self, answers):
-        def apply(answer):
-            doc = self.lemmatizer(answer)
-
-            words = []
-            for token in doc:
-                if token.pos_ in ["NOUN", "VERB"]:
-                    words.append(token.lemma_)
-                else:
-                    words.append(token.text)
-            answer = " ".join(words)
-
-            return answer
-
-        return [apply(answer) for answer in answers]
-
-    @property
-    def lemmatizer(self):
-        if self._lemmatizer is None:
-            try:
-                import spacy
-
-                self._lemmatizer = spacy.load("en_core_web_sm")
-            except ImportError:
-                logging.error(
-                    """
-                    Please install spacy and en_core_web_sm model to apply lemmatization.
-                    python -m spacy download en_core_web_sm
-                    OR
-                    import spacy.cli
-                    spacy.cli.download("en_core_web_sm")
-                    """
-                )
-                exit(1)
-
-        return self._lemmatizer
-
-def disabled_train(self, mode=True):
-    """Overwrite model.train with this function to make sure train/eval mode
-    does not change anymore."""
-    return self
-
-
-class LayerNorm(nn.LayerNorm):
-    """Subclass torch's LayerNorm to handle fp16."""
-
-    def forward(self, x: torch.Tensor):
-        orig_type = x.dtype
-        ret = super().forward(x.type(torch.float32))
-        return ret.type(orig_type)
-
-
-def compute_sim_matrix(model, data_loader, **kwargs):
-    k_test = kwargs.pop("k_test")
-
-    metric_logger = MetricLogger(delimiter="  ")
-    header = "Evaluation:"
-
-    logging.info("Computing features for evaluation...")
-    start_time = time.time()
-
-    texts = data_loader.dataset.text
-    num_text = len(texts)
-    text_bs = 256
-    text_ids = []
-    text_embeds = []
-    text_atts = []
-    for i in range(0, num_text, text_bs):
-        text = texts[i : min(num_text, i + text_bs)]
-        text_input = model.tokenizer(
-            text,
-            padding="max_length",
-            truncation=True,
-            max_length=35,
-            return_tensors="pt",
-        ).to(model.device)
-        text_feat = model.forward_text(text_input)
-        text_embed = F.normalize(model.text_proj(text_feat))
-        text_embeds.append(text_embed)
-        text_ids.append(text_input.input_ids)
-        text_atts.append(text_input.attention_mask)
-
-    text_embeds = torch.cat(text_embeds, dim=0)
-    text_ids = torch.cat(text_ids, dim=0)
-    text_atts = torch.cat(text_atts, dim=0)
-
-    vit_feats = []
-    image_embeds = []
-    for samples in data_loader:
-        image = samples["image"]
-
-        image = image.to(model.device)
-        image_feat, vit_feat = model.forward_image(image)
-        image_embed = model.vision_proj(image_feat)
-        image_embed = F.normalize(image_embed, dim=-1)
-
-        vit_feats.append(vit_feat.cpu())
-        image_embeds.append(image_embed)
-
-    vit_feats = torch.cat(vit_feats, dim=0)
-    image_embeds = torch.cat(image_embeds, dim=0)
-
-    sims_matrix = []
-    for image_embed in image_embeds:
-        sim_q2t = image_embed @ text_embeds.t()
-        sim_i2t, _ = sim_q2t.max(0)
-        sims_matrix.append(sim_i2t)
-    sims_matrix = torch.stack(sims_matrix, dim=0)
-
-    score_matrix_i2t = torch.full(
-        (len(data_loader.dataset.image), len(texts)), -100.0
-    ).to(model.device)
-
-    num_tasks = dist_utils.get_world_size()
-    rank = dist_utils.get_rank()
-    step = sims_matrix.size(0) // num_tasks + 1
-    start = rank * step
-    end = min(sims_matrix.size(0), start + step)
-
-    for i, sims in enumerate(
-        metric_logger.log_every(sims_matrix[start:end], 50, header)
-    ):
-        topk_sim, topk_idx = sims.topk(k=k_test, dim=0)
-        image_inputs = vit_feats[start + i].repeat(k_test, 1, 1).to(model.device)
-        score = model.compute_itm(
-            image_inputs=image_inputs,
-            text_ids=text_ids[topk_idx],
-            text_atts=text_atts[topk_idx],
-        ).float()
-        score_matrix_i2t[start + i, topk_idx] = score + topk_sim
-
-    sims_matrix = sims_matrix.t()
-    score_matrix_t2i = torch.full(
-        (len(texts), len(data_loader.dataset.image)), -100.0
-    ).to(model.device)
-
-    step = sims_matrix.size(0) // num_tasks + 1
-    start = rank * step
-    end = min(sims_matrix.size(0), start + step)
-
-    for i, sims in enumerate(
-        metric_logger.log_every(sims_matrix[start:end], 50, header)
-    ):
-        topk_sim, topk_idx = sims.topk(k=k_test, dim=0)
-        image_inputs = vit_feats[topk_idx.cpu()].to(model.device)
-        score = model.compute_itm(
-            image_inputs=image_inputs,
-            text_ids=text_ids[start + i].repeat(k_test, 1),
-            text_atts=text_atts[start + i].repeat(k_test, 1),
-        ).float()
-        score_matrix_t2i[start + i, topk_idx] = score + topk_sim
-
-    if dist_utils.is_dist_avail_and_initialized():
-        dist.barrier()
-        torch.distributed.all_reduce(
-            score_matrix_i2t, op=torch.distributed.ReduceOp.SUM
-        )
-        torch.distributed.all_reduce(
-            score_matrix_t2i, op=torch.distributed.ReduceOp.SUM
-        )
-
-    total_time = time.time() - start_time
-    total_time_str = str(datetime.timedelta(seconds=int(total_time)))
-    logging.info("Evaluation time {}".format(total_time_str))
-
-    return score_matrix_i2t.cpu().numpy(), score_matrix_t2i.cpu().numpy()
diff --git a/spaces/mohit-217/invoice_by_mohit/README.md b/spaces/mohit-217/invoice_by_mohit/README.md
deleted file mode 100644
index ae572b4cf34851cc400e62eec4edee4ade3e27d3..0000000000000000000000000000000000000000
--- a/spaces/mohit-217/invoice_by_mohit/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Invoice By Mohit
-emoji: 👀
-colorFrom: green
-colorTo: gray
-sdk: gradio
-sdk_version: 3.19.1
-app_file: app.py
-pinned: false
-license: gpl-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/monra/freegpt-webui-chimera/client/css/message.css b/spaces/monra/freegpt-webui-chimera/client/css/message.css
deleted file mode 100644
index 64e04147ee4d1e76dda4f39c4f756c9da63e3874..0000000000000000000000000000000000000000
--- a/spaces/monra/freegpt-webui-chimera/client/css/message.css
+++ /dev/null
@@ -1,65 +0,0 @@
-.message {
-	width: 100%;
-	overflow-wrap: break-word;
-	display: flex;
-	gap: var(--section-gap);
-	padding: var(--section-gap);
-	padding-bottom: 0;
-}
-
-.message:last-child {
-	animation: 0.6s show_message;
-}
-
-@keyframes show_message {
-	from {
-		transform: translateY(10px);
-		opacity: 0;
-	}
-}
-
-.message .avatar-container img {
-	max-width: 48px;
-	max-height: 48px;
-	box-shadow: 0.4px 0.5px 0.7px -2px rgba(0, 0, 0, 0.08), 1.1px 1.3px 2px -2px rgba(0, 0, 0, 0.041),
-		2.7px 3px 4.8px -2px rgba(0, 0, 0, 0.029), 9px 10px 16px -2px rgba(0, 0, 0, 0.022);
-}
-
-.message .content {
-	display: flex;
-	flex-direction: column;
-	width: 90%;
-	gap: 18px;
-}
-
-.message .content p,
-.message .content li,
-.message .content code {
-	font-size: 1rem;
-	line-height: 1.3;
-}
-
-@media screen and (max-height: 720px) {
-	.message {
-		padding: 12px;
-		gap: 0;
-	}
-
-	.message .content {
-		margin-left: 8px;
-		width: 80%;
-	}
-
-	.message .avatar-container img {
-		max-width: 32px;
-		max-height: 32px;
-	}
-
-	.message .content,
-	.message .content p,
-	.message .content li,
-	.message .content code {
-		font-size: 0.875rem;
-		line-height: 1.3;
-	}
-}
diff --git a/spaces/mshkdm/VToonify/vtoonify/model/raft/alt_cuda_corr/setup.py b/spaces/mshkdm/VToonify/vtoonify/model/raft/alt_cuda_corr/setup.py
deleted file mode 100644
index c0207ff285ffac4c8146c79d154f12416dbef48c..0000000000000000000000000000000000000000
--- a/spaces/mshkdm/VToonify/vtoonify/model/raft/alt_cuda_corr/setup.py
+++ /dev/null
@@ -1,15 +0,0 @@
-from setuptools import setup
-from torch.utils.cpp_extension import BuildExtension, CUDAExtension
-
-
-setup(
-    name='correlation',
-    ext_modules=[
-        CUDAExtension('alt_cuda_corr',
-            sources=['correlation.cpp', 'correlation_kernel.cu'],
-            extra_compile_args={'cxx': [], 'nvcc': ['-O3']}),
-    ],
-    cmdclass={
-        'build_ext': BuildExtension
-    })
-
diff --git a/spaces/mshukor/UnIVAL/fairseq/fairseq/modules/lstm_cell_with_zoneout.py b/spaces/mshukor/UnIVAL/fairseq/fairseq/modules/lstm_cell_with_zoneout.py
deleted file mode 100644
index f04e5db255c62bbe0faebbc641f579f92be5580c..0000000000000000000000000000000000000000
--- a/spaces/mshukor/UnIVAL/fairseq/fairseq/modules/lstm_cell_with_zoneout.py
+++ /dev/null
@@ -1,37 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-import torch.nn as nn
-
-
-class LSTMCellWithZoneOut(nn.Module):
-    """
-    Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations
-    https://arxiv.org/abs/1606.01305
-    """
-
-    def __init__(self, prob: float, input_size: int, hidden_size: int,
-                 bias: bool = True):
-        super(LSTMCellWithZoneOut, self).__init__()
-        self.lstm_cell = nn.LSTMCell(input_size, hidden_size, bias=bias)
-        self.prob = prob
-        if prob > 1.0 or prob < 0.0:
-            raise ValueError("zoneout probability must be in the range from "
-                             "0.0 to 1.0.")
-
-    def zoneout(self, h, next_h, prob):
-        if isinstance(h, tuple):
-            return tuple(
-                [self.zoneout(h[i], next_h[i], prob) for i in range(len(h))]
-            )
-
-        if self.training:
-            mask = h.new_zeros(*h.size()).bernoulli_(prob)
-            return mask * h + (1 - mask) * next_h
-
-        return prob * h + (1 - prob) * next_h
-
-    def forward(self, x, h):
-        return self.zoneout(h, self.lstm_cell(x, h), self.prob)
diff --git a/spaces/mygyasir/genious_bgremover/carvekit/web/schemas/config.py b/spaces/mygyasir/genious_bgremover/carvekit/web/schemas/config.py
deleted file mode 100644
index 5d47ffc3f16702c5bcac3874f2a1a3548e86a1f2..0000000000000000000000000000000000000000
--- a/spaces/mygyasir/genious_bgremover/carvekit/web/schemas/config.py
+++ /dev/null
@@ -1,99 +0,0 @@
-import secrets
-from typing import List
-from typing_extensions import Literal
-
-import torch.cuda
-from pydantic import BaseModel, validator
-
-
-class AuthConfig(BaseModel):
-    """Config for web api token authentication"""
-
-    auth: bool = True
-    """Enables Token Authentication for API"""
-    admin_token: str = secrets.token_hex(32)
-    """Admin Token"""
-    allowed_tokens: List[str] = [secrets.token_hex(32)]
-    """All allowed tokens"""
-
-
-class MLConfig(BaseModel):
-    """Config for ml part of framework"""
-
-    segmentation_network: Literal[
-        "u2net", "deeplabv3", "basnet", "tracer_b7"
-    ] = "tracer_b7"
-    """Segmentation Network"""
-    preprocessing_method: Literal["none", "stub"] = "none"
-    """Pre-processing Method"""
-    postprocessing_method: Literal["fba", "none"] = "fba"
-    """Post-Processing Network"""
-    device: str = "cpu"
-    """Processing device"""
-    batch_size_seg: int = 5
-    """Batch size for segmentation network"""
-    batch_size_matting: int = 1
-    """Batch size for matting network"""
-    seg_mask_size: int = 640
-    """The size of the input image for the segmentation neural network."""
-    matting_mask_size: int = 2048
-    """The size of the input image for the matting neural network."""
-    fp16: bool = False
-    """Use half precision for inference"""
-    trimap_dilation: int = 30
-    """Dilation size for trimap"""
-    trimap_erosion: int = 5
-    """Erosion levels for trimap"""
-    trimap_prob_threshold: int = 231
-    """Probability threshold for trimap generation"""
-
-    @validator("seg_mask_size")
-    def seg_mask_size_validator(cls, value: int, values):
-        if value > 0:
-            return value
-        else:
-            raise ValueError("Incorrect seg_mask_size!")
-
-    @validator("matting_mask_size")
-    def matting_mask_size_validator(cls, value: int, values):
-        if value > 0:
-            return value
-        else:
-            raise ValueError("Incorrect matting_mask_size!")
-
-    @validator("batch_size_seg")
-    def batch_size_seg_validator(cls, value: int, values):
-        if value > 0:
-            return value
-        else:
-            raise ValueError("Incorrect batch size!")
-
-    @validator("batch_size_matting")
-    def batch_size_matting_validator(cls, value: int, values):
-        if value > 0:
-            return value
-        else:
-            raise ValueError("Incorrect batch size!")
-
-    @validator("device")
-    def device_validator(cls, value):
-        if torch.cuda.is_available() is False and "cuda" in value:
-            raise ValueError(
-                "GPU is not available, but specified as processing device!"
-            )
-        if "cuda" not in value and "cpu" != value:
-            raise ValueError("Unknown processing device! It should be cpu or cuda!")
-        return value
-
-
-class WebAPIConfig(BaseModel):
-    """FastAPI app config"""
-
-    port: int = 5000
-    """Web API port"""
-    host: str = "0.0.0.0"
-    """Web API host"""
-    ml: MLConfig = MLConfig()
-    """Config for ml part of framework"""
-    auth: AuthConfig = AuthConfig()
-    """Config for web api token authentication """
diff --git a/spaces/myrad01/Inpaint-Anything/third_party/lama/saicinpainting/evaluation/losses/ssim.py b/spaces/myrad01/Inpaint-Anything/third_party/lama/saicinpainting/evaluation/losses/ssim.py
deleted file mode 100644
index ee43a0095408eca98e253dea194db788446f9c0a..0000000000000000000000000000000000000000
--- a/spaces/myrad01/Inpaint-Anything/third_party/lama/saicinpainting/evaluation/losses/ssim.py
+++ /dev/null
@@ -1,74 +0,0 @@
-import numpy as np
-import torch
-import torch.nn.functional as F
-
-
-class SSIM(torch.nn.Module):
-    """SSIM. Modified from:
-    https://github.com/Po-Hsun-Su/pytorch-ssim/blob/master/pytorch_ssim/__init__.py
-    """
-
-    def __init__(self, window_size=11, size_average=True):
-        super().__init__()
-        self.window_size = window_size
-        self.size_average = size_average
-        self.channel = 1
-        self.register_buffer('window', self._create_window(window_size, self.channel))
-
-    def forward(self, img1, img2):
-        assert len(img1.shape) == 4
-
-        channel = img1.size()[1]
-
-        if channel == self.channel and self.window.data.type() == img1.data.type():
-            window = self.window
-        else:
-            window = self._create_window(self.window_size, channel)
-
-            # window = window.to(img1.get_device())
-            window = window.type_as(img1)
-
-            self.window = window
-            self.channel = channel
-
-        return self._ssim(img1, img2, window, self.window_size, channel, self.size_average)
-
-    def _gaussian(self, window_size, sigma):
-        gauss = torch.Tensor([
-            np.exp(-(x - (window_size // 2)) ** 2 / float(2 * sigma ** 2)) for x in range(window_size)
-        ])
-        return gauss / gauss.sum()
-
-    def _create_window(self, window_size, channel):
-        _1D_window = self._gaussian(window_size, 1.5).unsqueeze(1)
-        _2D_window = _1D_window.mm(_1D_window.t()).float().unsqueeze(0).unsqueeze(0)
-        return _2D_window.expand(channel, 1, window_size, window_size).contiguous()
-
-    def _ssim(self, img1, img2, window, window_size, channel, size_average=True):
-        mu1 = F.conv2d(img1, window, padding=(window_size // 2), groups=channel)
-        mu2 = F.conv2d(img2, window, padding=(window_size // 2), groups=channel)
-
-        mu1_sq = mu1.pow(2)
-        mu2_sq = mu2.pow(2)
-        mu1_mu2 = mu1 * mu2
-
-        sigma1_sq = F.conv2d(
-            img1 * img1, window, padding=(window_size // 2), groups=channel) - mu1_sq
-        sigma2_sq = F.conv2d(
-            img2 * img2, window, padding=(window_size // 2), groups=channel) - mu2_sq
-        sigma12 = F.conv2d(
-            img1 * img2, window, padding=(window_size // 2), groups=channel) - mu1_mu2
-
-        C1 = 0.01 ** 2
-        C2 = 0.03 ** 2
-
-        ssim_map = ((2 * mu1_mu2 + C1) * (2 * sigma12 + C2)) / \
-                   ((mu1_sq + mu2_sq + C1) * (sigma1_sq + sigma2_sq + C2))
-
-        if size_average:
-            return ssim_map.mean()
-
-        return ssim_map.mean(1).mean(1).mean(1)
-
-    def _load_from_state_dict(self, state_dict, prefix, local_metadata, strict, missing_keys, unexpected_keys, error_msgs):
-        return
diff --git a/spaces/nazneen/seal/seal/run_inference.py b/spaces/nazneen/seal/seal/run_inference.py
deleted file mode 100644
index 9a742c3d01a6f776f906b0e86638c5eb670fc8d0..0000000000000000000000000000000000000000
--- a/spaces/nazneen/seal/seal/run_inference.py
+++ /dev/null
@@ -1,82 +0,0 @@
-from unittest import result
-import torch
-import torch.nn as nn
-from torch.utils.data import DataLoader, Subset
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
-from datasets import load_dataset
-
-import os
-import numpy as np
-from tqdm import tqdm
-
-from utils.inference_utils import InferenceResults, saveResults
-
-# Load validation set
-
-def load_session(dataset, model, split):
-    dataset = load_dataset(dataset, split=split)
-    dataloader = DataLoader(
-        dataset,
-        batch_size=256, drop_last=True
-    )
-    model = AutoModelForSequenceClassification.from_pretrained(model)
-    tokenizer = AutoTokenizer.from_pretrained(model)
-    return tokenizer, dataloader, model
-
-# Add hook to capture hidden layer
-def get_input(name, model):
-    hidden_layers = {}
-    def hook(model, input, output):
-        if name in hidden_layers:
-            del hidden_layers[name]
-        hidden_layers[name] = input[0].detach()
-    return hook, hidden_layers
-
-def run_inference(dataset='yelp_polarity', model='textattack/albert-base-v2-yelp-polarity', split='test', output_path='./assets/data/inference_results'):
-    tokenizer, dataloader, model = load_session(dataset,model,split)
-    model.eval()
-    model.to('cpu')
-    hook, hidden_layers = model.classifier.register_forward_hook(get_input('last_layer', model))
-    # Run inference on entire dataset
-    hidden_list = []
-    loss_list = []
-    output_list = []
-    example = []
-    labels = []
-    criterion = nn.CrossEntropyLoss(reduction='none')
-    softmax = nn.Softmax(dim=1)
-    with torch.no_grad():
-        for batch_num, batch in tqdm(enumerate(dataloader), total=len(dataloader), position=0, leave=True):
-            batch_ex = [ex[:512] for ex in batch['text']]
-            inputs = tokenizer(batch_ex, padding=True, return_tensors='pt').to('cpu')
-            targets = batch['label']
-            
-            outputs = model(**inputs)['logits']
-            loss = criterion(outputs, targets)
-            predictions = softmax(outputs)
-            
-            hidden_list.append(hidden_layers['last_layer'].cpu())
-            loss_list.append(loss.cpu())
-            #output_list.append(predictions[:, 1].cpu())
-            output_list.append(np.argmax(predictions, axis=1))
-            labels.append(targets)
-            example.append(inputs['input_ids'])
-    embeddings = torch.vstack(hidden_list)
-    #outputs = torch.hstack(output_list)
-    losses = torch.hstack(loss_list)
-    targets = torch.hstack(labels)
-    #inputs = torch.hstack(example)
-    results = save_results(embeddings,losses,targets)
-    saveResults(os.path.join(output_path,dataset+'.pkl'),results)
-
-
-
-def save_results(embeddings, losses, labels):
-    results = InferenceResults(
-        embeddings = torch.clone(embeddings),
-        losses     = losses,
-        labels     = labels
-    )
-    return results
-    
-
diff --git a/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Impact Soundworks Koto Nation KONTAKT VON.G.rar.md b/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Impact Soundworks Koto Nation KONTAKT VON.G.rar.md
deleted file mode 100644
index a994c2d0971964bba7e354325326c0886279f658..0000000000000000000000000000000000000000
--- a/spaces/netiMophi/DreamlikeArt-Diffusion-1.0/Impact Soundworks Koto Nation KONTAKT VON.G.rar.md	
+++ /dev/null
@@ -1,201 +0,0 @@
-
-<table>
-<tr>
-<h1>Impact Soundworks Koto Nation: A Review</h1></td>
-<td></td>
-<td>If you are looking for a realistic and expressive library of Japanese string instruments, you might want to check out Impact Soundworks Koto Nation. This product is a collection of three instruments sampled from a custom Sadowsky Jim Hall Archtop hollowbody electric guitar played by renowned guitarist Josh Workman. It runs on Native Instruments' KONTAKT sampler platform and offers a wide range of articulations, effects, and controls to create authentic or modern sounds. In this article, we will review Impact Soundworks Koto Nation in detail, covering its features, sound quality, performance, comparison with other products, and more.</td>
-</tr>
-<tr>
-<td><h2>What is Koto Nation?</h2></td>
-<td></td>
-<td>Koto Nation is a virtual instrument library created by Impact Soundworks, a company that specializes in creating high-quality sample libraries for various genres and styles of music. Koto Nation contains almost 10,000 samples (just under 4GB) of three instruments: koto, bass koto, and shamisen. These are traditional Japanese string instruments that have a distinctive sound and playing technique.</td>
-</tr>
-<tr>
-<td><h3>What is a koto?</h3></td>
-<td></td>
-<td>A koto is a Japanese plucked half-tube zither instrument with 13 silk strings and movable bridges. It is derived from the Chinese zheng and se, and similar to the Mongolian yatga, the Korean gay ageum, and the Vietnamese đàn tranh. The koto is played by plucking the strings with three ivory plectra worn on the thumb, index, and middle fingers of the right hand, while the left hand can adjust the pitch and tone by pressing or sliding the strings on the other side of the bridge. The koto is one of the most important instruments in Japanese music, especially in gagaku (court music), sankyoku (chamber music), and shakuhachi (bamboo flute) ensembles. It can produce a range of sounds, from delicate and lyrical to percussive and dissonant.</td>
-</tr>
-<tr>
-<td><h3>What is KONTAKT?</h3></td>
-<td></td>
-<td>KONTAKT is a software sampler platform developed by Native Instruments, a leading company in the field of digital music production and performance. KONTAKT allows users to load and play various sample libraries, as well as create their own instruments using its powerful editing and scripting features. KONTAKT supports a wide range of formats, such as WAV, AIFF, MP3, FLAC, and OGG, and can be used as a standalone application or as a plug-in in any DAW (digital audio workstation). KONTAKT is known for its high-quality sound engine, its extensive library of effects and filters, and its intuitive and flexible user interface.</td>
-</tr>
-<tr>
-<td><h3>What is VON.G?</h3></td>
-<td></td>
-<td>VON.G is a release group that specializes in providing cracked versions of sample libraries for KONTAKT. A cracked version is a modified version that bypasses the copy protection or activation process of the original product, allowing users to use it without paying for it. VON.G is one of the most prolific and popular release groups in the scene, having cracked hundreds of sample libraries from various developers and genres. VON.G claims to crack sample libraries for educational purposes only, and encourages users to support the developers by buying their products if they like them.</td>
-</tr>
-<tr>
-<td><h2>How does Koto Nation sound?</h2></td>
-<td></td>
-<td>Koto Nation sounds very realistic and expressive, thanks to the meticulous sampling process and the advanced scripting techniques used by Impact Soundworks. The product captures the nuances and subtleties of each instrument, such as the resonance, vibrato, glissando, pizzicato, harmonics, bends, mutes, and more. The product also offers a variety of effects and controls to shape and manipulate the sound according to your preferences and needs.</td>
-</tr> Here is the continuation of the article table with HTML formatting: <table>
-<tr>
-<td><h3>The sound sources</h3></td>
-<td></td>
-<td>Koto Nation features three instruments sampled from a custom Sadowsky Jim Hall Archtop hollowbody electric guitar played by renowned guitarist Josh Workman. These are:</td>
-</tr>
-<tr>
-<td><ul><li>Koto: The standard 13-string koto, tuned to a pentatonic scale. It has a bright and clear tone, and can be played with various articulations, such as normal, tremolo, harmonics, mutes, bends, and more.</li></ul></td>
-<td></td>
-<td><ul><li>Bass Koto: A larger version of the koto, with 17 strings and a lower tuning. It has a deeper and richer tone, and can be played with similar articulations as the koto.</li></ul></td>
-</tr>
-<tr>
-<td><ul><li>Shamisen: A three-stringed lute-like instrument, with a skin-covered body and a long neck. It has a sharp and percussive tone, and can be played with various articulations, such as normal, tremolo, pizzicato, slides, mutes, and more.</li></ul></td>
-<td></td>
-<td>Each instrument was recorded in multiple microphone positions (close, room, and mixed) and with multiple velocity layers and round robins, ensuring a natural and dynamic sound. You can adjust the volume and pan of each microphone position, as well as enable or disable them individually.</td>
-</tr>
-<tr>
-<td><h3>The articulations and effects</h3></td>
-<td></td>
-<td>Koto Nation offers a wide range of articulations and effects for each instrument, allowing you to create authentic or modern sounds. Some of the articulations and effects are:</td>
-</tr>
-<tr>
-<td><ul><li>Resonance: This feature simulates the natural resonance of the strings when they are plucked or muted. You can adjust the amount and decay of the resonance, as well as enable or disable it for each string.</li></ul></td>
-<td></td>
-<td><ul><li>Vibrato: This feature simulates the natural vibrato of the strings when they are pressed or slid by the left hand. You can adjust the speed and depth of the vibrato, as well as enable or disable it for each string.</li></ul></td>
-</tr>
-<tr>
-<td><ul><li>Glissando: This feature simulates the gliding effect of the strings when they are slid by the left hand. You can adjust the speed and range of the glissando, as well as enable or disable it for each string.</li></ul></td>
-<td></td>
-<td><ul><li>Pizzicato: This feature simulates the plucking effect of the strings by the right hand without using plectra. You can adjust the volume and tone of the pizzicato, as well as enable or disable it for each string.</li></ul></td>
-</tr> Here is the continuation of the article table with HTML formatting: <table>
-<tr>
-<td><ul><li>Harmonics: This feature simulates the harmonic effect of the strings when they are lightly touched by the right hand at certain points. You can adjust the volume and tone of the harmonics, as well as enable or disable them for each string.</li></ul></td>
-<td></td>
-<td><ul><li>Bends: This feature simulates the bending effect of the strings when they are pressed or slid by the left hand. You can adjust the amount and direction of the bends, as well as enable or disable them for each string.</li></ul></td>
-</tr>
-<tr>
-<td><ul><li>Mutes: This feature simulates the muting effect of the strings when they are stopped by the right hand. You can adjust the volume and tone of the mutes, as well as enable or disable them for each string.</li></ul></td>
-<td></td>
-<td><ul><li>Reverb: This feature adds a reverb effect to the sound of the instrument, creating a sense of space and depth. You can adjust the size, damping, width, and mix of the reverb, as well as enable or disable it.</li></ul></td>
-</tr>
-<tr>
-<td><ul><li>Delay: This feature adds a delay effect to the sound of the instrument, creating a sense of echo and movement. You can adjust the time, feedback, width, and mix of the delay, as well as enable or disable it.</li></ul></td>
-<td></td>
-<td><ul><li>Chorus: This feature adds a chorus effect to the sound of the instrument, creating a sense of richness and warmth. You can adjust the rate, depth, width, and mix of the chorus, as well as enable or disable it.</li></ul></td>
-</tr>
-<tr>
-<td><h3>The interface and controls</h3></td>
-<td></td>
-<td>Koto Nation has a simple and intuitive user interface that allows you to access and adjust all the features and controls of the product. The interface consists of four main sections:</td>
-</tr>
-<tr>
-<td><ul><li>Instrument Selector: This section allows you to select which instrument you want to play (koto, bass koto, or shamisen) and which microphone position you want to use (close, room, or mixed).</li></ul></td>
-<td></td>
-<td><ul><li>Articulation Selector: This section allows you to select which articulation you want to use for each instrument (normal, tremolo, harmonics, pizzicato, etc.) and how to switch between them (keyswitches or modes).</li></ul></td>
-</tr>
-<tr>
-<td><ul><li>Console: This section allows you to adjust the volume and pan of each microphone position, as well as enable or disable them individually. You can also access the built-in effects (reverb, delay, chorus) and adjust their parameters.</li></ul></td>
-<td></td>
-<td><ul><li>Controls: This section allows you to adjust various parameters that affect the sound and performance of each instrument, such as resonance, vibrato, glissando, pizzicato, harmonics, bends, mutes, etc.</li></ul></td>
-</tr> Here is the continuation of the article table with HTML formatting: <table>
-<tr>
-<td><h2>How does Koto Nation perform?</h2></td>
-<td></td>
-<td>Koto Nation performs very well, thanks to the optimized scripting and the efficient use of resources. The product is easy to play, versatile, and compatible with various software and hardware.</td>
-</tr>
-<tr>
-<td><h3>The keyswitches and modes</h3></td>
-<td></td>
-<td>Koto Nation allows you to switch between different articulations and modes using keyswitches or modes. Keyswitches are keys on the keyboard that trigger a change in the articulation or mode of the instrument. Modes are buttons on the interface that toggle a change in the articulation or mode of the instrument. You can choose which method you prefer, or use both simultaneously. Some of the keyswitches and modes are:</td>
-</tr>
-<tr>
-<td><ul><li>Normal Mode: This mode plays the normal articulation of the instrument, which is the default mode.</li></ul></td>
-<td></td>
-<td><ul><li>Tremolo Mode: This mode plays the tremolo articulation of the instrument, which is a rapid repetition of the same note. You can adjust the speed and depth of the tremolo using the controls.</li></ul></td>
-</tr>
-<tr>
-<td><ul><li>Harmonics Mode: This mode plays the harmonics articulation of the instrument, which is a high-pitched overtone of the note. You can adjust the volume and tone of the harmonics using the controls.</li></ul></td>
-<td></td>
-<td><ul><li>Pizzicato Mode: This mode plays the pizzicato articulation of the instrument, which is a plucking of the string without using plectra. You can adjust the volume and tone of the pizzicato using the controls.</li></ul></td>
-</tr> Here is the continuation of the article table with HTML formatting: <table>
-<tr>
-<td><ul><li>Bends Mode: This mode plays the bends articulation of the instrument, which is a bending of the pitch of the note. You can adjust the amount and direction of the bends using the controls.</li></ul></td>
-<td></td>
-<td><ul><li>Mutes Mode: This mode plays the mutes articulation of the instrument, which is a muting of the sound of the note. You can adjust the volume and tone of the mutes using the controls.</li></ul></td>
-</tr>
-<tr>
-<td><h3>The tone shaping and processing</h3></td>
-<td></td>
-<td>Koto Nation allows you to shape and process the tone of each instrument using the built-in effects and console. The effects include reverb, delay, and chorus, which can add space, depth, movement, richness, and warmth to the sound. The console includes a four-band EQ, a compressor, a limiter, and a saturator, which can adjust the frequency, dynamics, and color of the sound. You can access and adjust the parameters of each effect and console using the interface.</td>
-</tr>
-<tr>
-<td><h3>The compatibility and requirements</h3></td>
-<td></td>
-<td>Koto Nation is compatible with any software and hardware that supports KONTAKT 5.5 or higher. You can use it as a standalone application or as a plug-in in any DAW. You can also use it with any MIDI controller or keyboard that can send MIDI data. The minimum system requirements for Koto Nation are:</td>
-</tr>
-<tr>
-<td><ul><li>Windows 7 or higher, or Mac OS X 10.9 or higher</li></ul></td>
-<td></td>
-<td><ul><li>Intel Core 2 Duo or AMD Athlon 64 X2 processor</li></ul></td>
-</tr>
-<tr>
-<td><ul><li>4 GB of RAM</li></ul></td>
-<td></td>
-<td><ul><li>4 GB of free disk space</li></ul></td>
-</tr> Here is the continuation of the article table with HTML formatting: <table>
-<tr>
-<td><h2>How does Koto Nation compare?</h2></td>
-<td></td>
-<td>Koto Nation is not the only product that offers koto instruments for KONTAKT, but it is one of the best ones in terms of quality, features, and value. In this section, we will compare Koto Nation with some of its competitors and alternatives, and see how it stands out.</td>
-</tr>
-<tr>
-<td><h3>The pros and cons</h3></td>
-<td></td>
-<td>Koto Nation has many advantages and disadvantages, depending on your needs and preferences. Here are some of the main pros and cons of the product:</td>
-</tr>
-<tr>
-<td><ul><li>Pros:</li><ul><li>Realistic and expressive sound</li><li>Wide range of articulations and effects</li><li>Simple and intuitive interface</li><li>Versatile and customizable sound</li><li>Optimized and efficient performance</li><li>Affordable price</li></ul></ul></td>
-<td></td>
-<td><ul><li>Cons:</li><ul><li>Limited number of instruments</li><li>No legato or portamento articulations</li><li>No microphone mixing or routing options</li><li>No ethnic percussion or other instruments included</li><li>Requires KONTAKT 5.5 or higher</li><li>Illegal to use cracked version</li></ul></ul></td>
-</tr>
-<tr>
-<td><h3>The alternatives and competitors</h3></td>
-<td></td>
-<td>Koto Nation has some alternatives and competitors that offer similar or different features and sounds for koto instruments. Here are some of them:</td>
-</tr>
-<tr>
-<td><ul><li>Soniccouture Koto Ensemble: This product is a collection of four koto instruments: 13-string koto, 17-string bass koto, 21-string nijugen, and 25-string nijugen. It has a more extensive library of samples (over 10GB) and articulations (including legato and portamento) than Koto Nation, but it also has a higher price ($149) and requires more disk space and RAM.</li></ul></td>
-<td></td>
-<td><ul><li>Sonica Instruments Shakuhachi, Koto & Shamisen: This product is a bundle of three instruments: shakuhachi (bamboo flute), koto (13-string zither), and shamisen (three-stringed lute). It has a similar library size (4GB) and articulations as Koto Nation, but it also includes some ethnic percussion and other instruments, such as taiko drums, biwa, kokyu, etc. It has a slightly higher price ($99) than Koto Nation.</li></ul></td>
-</tr> Here is the continuation of the article table with HTML formatting: <table>
-<tr>
-<td><ul><li>Native Instruments Discovery Series: Japan: This product is a collection of five instruments: koto (13-string zither), shamisen (three-stringed lute), shakuhachi (bamboo flute), tsugaru shamisen (three-stringed lute with thicker strings), and taiko drums. It has a smaller library size (3GB) and fewer articulations than Koto Nation, but it also has some unique features, such as the phrase player, the pattern player, and the ensemble builder. It has a similar price ($99) as Koto Nation.</li></ul></td>
-<td></td>
-<td><ul><li>Orange Tree Samples Evolution Hollowbody Blues: This product is not a koto instrument, but a guitar instrument sampled from a custom Sadowsky Jim Hall Archtop hollowbody electric guitar played by renowned guitarist Josh Workman. It has a larger library size (5GB) and more articulations (including legato, portamento, slides, etc.) than Koto Nation, but it also has a different sound and style, more suitable for blues, jazz, and rock music. It has a higher price ($179) than Koto Nation.</li></ul></td>
-</tr>
-<tr>
-<td><h3>The price and value</h3></td>
-<td></td>
-<td>Koto Nation has a very reasonable price ($69) for the quality and features it offers. It is cheaper than most of its competitors and alternatives, and it provides a realistic and expressive sound of koto instruments. It is a great value for anyone who wants to add some Japanese flavor to their music, whether they are beginners or professionals, composers or performers, traditionalists or modernists.</td>
-</tr>
-<tr>
-<td><h2>Conclusion</h2></td>
-<td></td>
-<td>Koto Nation is a virtual instrument library that delivers a realistic and expressive sound of koto instruments. It runs on KONTAKT 5.5 or higher, and offers a wide range of articulations, effects, and controls to create authentic or modern sounds. It has a simple and intuitive interface, and performs well on any software and hardware that supports KONTAKT. It is one of the best products in the market for koto instruments, and it is worth buying for anyone who wants to explore the rich and diverse musical culture of Japan.</td>
-</tr>
-<tr>
-<td><h4>FAQs</h4></td>
-<td></td>
-<td>Here are some frequently asked questions about Koto Nation and their answers:</td>
-</tr>
-<tr>
-<td><ul><li>Q: Where can I buy Koto Nation?</li><li>A: You can buy Koto Nation from the official website of Impact Soundworks, or from other online retailers that sell sample libraries for KONTAKT.</li></ul></td>
-<td></td>
-<td><ul><li>Q: How can I install Koto Nation?</li><li>A: You can install Koto Nation by downloading the ZIP file from the website where you bought it, extracting it to your desired location, and adding it to your KONTAKT library using the Add Library function.</li></ul></td>
-</tr>
-<tr>
-<td><ul><li>Q: How can I update Koto Nation?</li><li>A: You can update Koto Nation by downloading the latest version from the website where you bought it, extracting it to your desired location, and replacing the old files with the new ones.</li></ul></td>
-<td></td>
-<td><ul><li>Q: How can I get support for Koto Nation?</li><li>A: You can get support for Koto Nation by contacting the customer service of Impact Soundworks, or by visiting their online forum or social media pages.</li></ul></td>
-</tr>
-<tr>
-<td><ul><li>Q: How can I learn more about Koto Nation?</li><li>A: You can learn more about Koto Nation by reading the user manual that comes with the product, or by watching the video tutorials and demos that are available on YouTube.</li></ul></td>
-<td></td>
-<td></td>
-</tr>
-</table></p>
-<h2>Impact Soundworks Koto Nation KONTAKT VON.G.rar</h2><br /><p><b><b>Download Zip</b> &rarr; <a href="https://urlcod.com/2uIckd">https://urlcod.com/2uIckd</a></b></p><br /><br /> b2dd77e56b<br />
-<br />
-<br />
\ No newline at end of file
diff --git "a/spaces/nickmuchi/Earnings-Call-Analysis-Whisperer/pages/3_Earnings_Semantic_Search_\360\237\224\216_.py" "b/spaces/nickmuchi/Earnings-Call-Analysis-Whisperer/pages/3_Earnings_Semantic_Search_\360\237\224\216_.py"
deleted file mode 100644
index b2578bd5dcb46d422ea6037fd9c5c0d51a91bc64..0000000000000000000000000000000000000000
--- "a/spaces/nickmuchi/Earnings-Call-Analysis-Whisperer/pages/3_Earnings_Semantic_Search_\360\237\224\216_.py"
+++ /dev/null
@@ -1,177 +0,0 @@
-import streamlit as st
-from functions import *
-from langchain.chains import QAGenerationChain
-import itertools
-
-
-st.set_page_config(page_title="Earnings Question/Answering", page_icon="🔎")
-
-st.sidebar.header("Semantic Search")
-
-st.markdown("Earnings Semantic Search with LangChain, OpenAI & SBert")
-
-starter_message = "Ask me anything about the Earnings Call!"
-
-st.markdown(
-    """
-    <style>
-    
-    #MainMenu {visibility: hidden;
-    # }
-        footer {visibility: hidden;
-        }
-        .css-card {
-            border-radius: 0px;
-            padding: 30px 10px 10px 10px;
-            background-color: black;
-            box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
-            margin-bottom: 10px;
-            font-family: "IBM Plex Sans", sans-serif;
-        }
-        
-        .card-tag {
-            border-radius: 0px;
-            padding: 1px 5px 1px 5px;
-            margin-bottom: 10px;
-            position: absolute;
-            left: 0px;
-            top: 0px;
-            font-size: 0.6rem;
-            font-family: "IBM Plex Sans", sans-serif;
-            color: white;
-            background-color: green;
-            }
-            
-        .css-zt5igj {left:0;
-        }
-        
-        span.css-10trblm {margin-left:0;
-        }
-        
-        div.css-1kyxreq {margin-top: -40px;
-        }
-        
-       
-   
-        
-      
-    </style>
-    """,
-    unsafe_allow_html=True,
-)
-
-bi_enc_dict = {'mpnet-base-v2':"all-mpnet-base-v2",
-              'instructor-base': 'hkunlp/instructor-base',
-              'FlagEmbedding': 'BAAI/bge-base-en'}
-        
-sbert_model_name = st.sidebar.selectbox("Embedding Model", options=list(bi_enc_dict.keys()), key='sbox')
-
-st.sidebar.markdown('Earnings QnA Generator')
-        
-chunk_size = 1000
-overlap_size = 50
-
-try:
-
-        
-    if "sen_df" in st.session_state and "earnings_passages" in st.session_state:
-    
-        ## Save to a dataframe for ease of visualization
-        sen_df = st.session_state['sen_df']
-
-        title = st.session_state['title']
-
-        print(f'Earnings Call title: {title}')
-
-        earnings_text = st.session_state['earnings_passages']
-
-        st.session_state.eval_set = generate_eval(
-        earnings_text, 10, 3000)
-
-        # Display the question-answer pairs in the sidebar with smaller text
-        for i, qa_pair in enumerate(st.session_state.eval_set):
-            st.sidebar.markdown(
-                f"""
-                <div class="css-card">
-                <span class="card-tag">Question {i + 1}</span>
-                    <p style="font-size: 12px;">{qa_pair['question']}</p>
-                    <p style="font-size: 12px;">{qa_pair['answer']}</p>
-                </div>
-                """,
-                unsafe_allow_html=True,
-            )
-
-        embedding_model = bi_enc_dict[sbert_model_name]
-                        
-        with st.spinner(
-            text=f"Loading {embedding_model} embedding model and creating vectorstore..."
-        ):
-            
-            docsearch = create_vectorstore(earnings_text,title, embedding_model)
-
-            memory, agent_executor = create_memory_and_agent(docsearch)
-
-        if "messages" not in st.session_state or st.sidebar.button("Clear message history"):
-            st.session_state["messages"] = [AIMessage(content=starter_message)]
-
-        for msg in st.session_state.messages:
-            if isinstance(msg, AIMessage):
-                st.chat_message("assistant").write(msg.content)
-            elif isinstance(msg, HumanMessage):
-                st.chat_message("user").write(msg.content)
-            memory.chat_memory.add_message(msg)
-
-        if user_question := st.chat_input(placeholder=starter_message):
-            st.chat_message("user").write(user_question)
-    
-            with st.chat_message("assistant"):
-                
-                st_callback = StreamlitCallbackHandler(st.container())
-                
-                response = agent_executor(
-                    {"input": user_question, "history": st.session_state.messages},
-                    callbacks=[st_callback],
-                    include_run_info=True,
-                )
-
-                answer = response["output"]
-                
-                st.session_state.messages.append(AIMessage(content=answer))
-                
-                st.write(answer)
-                
-                memory.save_context({"input": user_question}, response)
-                
-                st.session_state["messages"] = memory.buffer
-                
-                run_id = response["__run"].run_id
-        
-                col_blank, col_text, col1, col2 = st.columns([10, 2, 1, 1])
-
-                with col_text:
-                    st.text("Feedback:")
-    
-                with col1:
-                    st.button("👍", on_click=send_feedback, args=(run_id, 1))
-        
-                with col2:
-                    st.button("👎", on_click=send_feedback, args=(run_id, 0))
-
-            
-            with st.expander(label='Query Result with Sentiment Tag', expanded=True):
-                
-                sentiment_label = gen_sentiment(answer)
-                df = pd.DataFrame.from_dict({'Text':[answer],'Sentiment':[sentiment_label]})
-                text_annotations = gen_annotated_text(df)[0] 
-                annotated_text(text_annotations)
-                
-            
-    else:
-    
-        st.write('Please ensure you have entered the YouTube URL or uploaded the Earnings Call file')  
-        
-except RuntimeError:
-  
-    st.write('Please ensure you have entered the YouTube URL or uploaded the Earnings Call file')        
-
-    
diff --git a/spaces/nikitaPDL2023/assignment4/detectron2/projects/ViTDet/configs/COCO/cascade_mask_rcnn_vitdet_l_100ep.py b/spaces/nikitaPDL2023/assignment4/detectron2/projects/ViTDet/configs/COCO/cascade_mask_rcnn_vitdet_l_100ep.py
deleted file mode 100644
index 2743603ad2b6cc3f99aa0600c715887f7550d1cd..0000000000000000000000000000000000000000
--- a/spaces/nikitaPDL2023/assignment4/detectron2/projects/ViTDet/configs/COCO/cascade_mask_rcnn_vitdet_l_100ep.py
+++ /dev/null
@@ -1,25 +0,0 @@
-from functools import partial
-
-from .cascade_mask_rcnn_vitdet_b_100ep import (
-    dataloader,
-    lr_multiplier,
-    model,
-    train,
-    optimizer,
-    get_vit_lr_decay_rate,
-)
-
-train.init_checkpoint = (
-    "detectron2://ImageNetPretrained/MAE/mae_pretrain_vit_large.pth?matching_heuristics=True"
-)
-
-model.backbone.net.embed_dim = 1024
-model.backbone.net.depth = 24
-model.backbone.net.num_heads = 16
-model.backbone.net.drop_path_rate = 0.4
-# 5, 11, 17, 23 for global attention
-model.backbone.net.window_block_indexes = (
-    list(range(0, 5)) + list(range(6, 11)) + list(range(12, 17)) + list(range(18, 23))
-)
-
-optimizer.params.lr_factor_func = partial(get_vit_lr_decay_rate, lr_decay_rate=0.8, num_layers=24)
diff --git a/spaces/nikitaPDL2023/assignment4/detectron2/projects/ViTDet/configs/LVIS/cascade_mask_rcnn_vitdet_l_100ep.py b/spaces/nikitaPDL2023/assignment4/detectron2/projects/ViTDet/configs/LVIS/cascade_mask_rcnn_vitdet_l_100ep.py
deleted file mode 100644
index ebaf526ab7735309d5f50527136ad6207ce9d58b..0000000000000000000000000000000000000000
--- a/spaces/nikitaPDL2023/assignment4/detectron2/projects/ViTDet/configs/LVIS/cascade_mask_rcnn_vitdet_l_100ep.py
+++ /dev/null
@@ -1,51 +0,0 @@
-from detectron2.config import LazyCall as L
-from detectron2.data.detection_utils import get_fed_loss_cls_weights
-from detectron2.layers import ShapeSpec
-from detectron2.modeling.box_regression import Box2BoxTransform
-from detectron2.modeling.matcher import Matcher
-from detectron2.modeling.roi_heads import FastRCNNOutputLayers, FastRCNNConvFCHead, CascadeROIHeads
-
-from .mask_rcnn_vitdet_l_100ep import (
-    dataloader,
-    lr_multiplier,
-    model,
-    optimizer,
-    train,
-)
-
-# arguments that don't exist for Cascade R-CNN
-[model.roi_heads.pop(k) for k in ["box_head", "box_predictor", "proposal_matcher"]]
-
-model.roi_heads.update(
-    _target_=CascadeROIHeads,
-    num_classes=1203,
-    box_heads=[
-        L(FastRCNNConvFCHead)(
-            input_shape=ShapeSpec(channels=256, height=7, width=7),
-            conv_dims=[256, 256, 256, 256],
-            fc_dims=[1024],
-            conv_norm="LN",
-        )
-        for _ in range(3)
-    ],
-    box_predictors=[
-        L(FastRCNNOutputLayers)(
-            input_shape=ShapeSpec(channels=1024),
-            box2box_transform=L(Box2BoxTransform)(weights=(w1, w1, w2, w2)),
-            num_classes="${...num_classes}",
-            test_score_thresh=0.02,
-            test_topk_per_image=300,
-            cls_agnostic_bbox_reg=True,
-            use_sigmoid_ce=True,
-            use_fed_loss=True,
-            get_fed_loss_cls_weights=lambda: get_fed_loss_cls_weights(
-                dataloader.train.dataset.names, 0.5
-            ),
-        )
-        for (w1, w2) in [(10, 5), (20, 10), (30, 15)]
-    ],
-    proposal_matchers=[
-        L(Matcher)(thresholds=[th], labels=[0, 1], allow_low_quality_matches=False)
-        for th in [0.5, 0.6, 0.7]
-    ],
-)
diff --git a/spaces/ntt123/WaveGRU-Text-To-Speech/sparse_matmul/layers/read_array_ifstream.h b/spaces/ntt123/WaveGRU-Text-To-Speech/sparse_matmul/layers/read_array_ifstream.h
deleted file mode 100644
index 3ea2bd1375435cc316e18c619767334e80040ac1..0000000000000000000000000000000000000000
--- a/spaces/ntt123/WaveGRU-Text-To-Speech/sparse_matmul/layers/read_array_ifstream.h
+++ /dev/null
@@ -1,66 +0,0 @@
-/*
- * Copyright 2021 Google LLC
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-// Low-level array reading function using std::ifstream.
-
-#ifndef LYRA_CODEC_SPARSE_MATMUL_LAYERS_READ_ARRAY_IFSTREAM_H_
-#define LYRA_CODEC_SPARSE_MATMUL_LAYERS_READ_ARRAY_IFSTREAM_H_
-
-#include <cstdint>
-#include <fstream>
-#include <sstream>
-#include <string>
-
-#include "absl/status/status.h"
-#include "absl/strings/substitute.h"
-#include "include/ghc/filesystem.hpp"
-
-namespace csrblocksparse {
-namespace detail {
-
-template <typename T>
-absl::Status ReadArrayIfstream(const std::string& file_name,
-                               const std::string& path, std::vector<T>* array,
-                               int64_t* length) {
-  ghc::filesystem::path complete_path(path);
-  complete_path /= file_name;
-  std::ifstream in_stream(complete_path.u8string(), std::ios::binary);
-  if (!in_stream.is_open()) {
-    return absl::UnknownError(
-        absl::Substitute("Error opening $0", complete_path.string()));
-  }
-
-  std::stringstream buffer;
-  buffer << in_stream.rdbuf();
-  if (buffer.str().empty()) {
-    LOG(ERROR) << "File " << complete_path << " was empty.";
-    return absl::UnknownError(
-        absl::Substitute("File $0 was empty", complete_path.string()));
-  }
-  std::string contents = buffer.str();
-  *length = contents.length();
-  int64_t elem = (*length + sizeof(T) - 1) / sizeof(T);
-  array->resize(elem);
-  std::move(contents.begin(), contents.end(),
-            reinterpret_cast<char*>(array->data()));
-
-  return absl::OkStatus();
-}
-
-}  // namespace detail
-}  // namespace csrblocksparse
-
-#endif  // LYRA_CODEC_SPARSE_MATMUL_LAYERS_READ_ARRAY_IFSTREAM_H_
diff --git a/spaces/ntt123/WaveGRU-Text-To-Speech/utils.py b/spaces/ntt123/WaveGRU-Text-To-Speech/utils.py
deleted file mode 100644
index b1dcf6d5bf06bfb53678158d5ede70156dcbeb3a..0000000000000000000000000000000000000000
--- a/spaces/ntt123/WaveGRU-Text-To-Speech/utils.py
+++ /dev/null
@@ -1,74 +0,0 @@
-"""
-Utility functions
-"""
-import pickle
-from pathlib import Path
-
-import pax
-import toml
-import yaml
-
-from tacotron import Tacotron
-
-
-def load_tacotron_config(config_file=Path("tacotron.toml")):
-    """
-    Load the project configurations
-    """
-    return toml.load(config_file)["tacotron"]
-
-
-def load_tacotron_ckpt(net: pax.Module, optim: pax.Module, path):
-    """
-    load checkpoint from disk
-    """
-    with open(path, "rb") as f:
-        dic = pickle.load(f)
-    if net is not None:
-        net = net.load_state_dict(dic["model_state_dict"])
-    if optim is not None:
-        optim = optim.load_state_dict(dic["optim_state_dict"])
-    return dic["step"], net, optim
-
-
-def create_tacotron_model(config):
-    """
-    return a random initialized Tacotron model
-    """
-    return Tacotron(
-        mel_dim=config["MEL_DIM"],
-        attn_bias=config["ATTN_BIAS"],
-        rr=config["RR"],
-        max_rr=config["MAX_RR"],
-        mel_min=config["MEL_MIN"],
-        sigmoid_noise=config["SIGMOID_NOISE"],
-        pad_token=config["PAD_TOKEN"],
-        prenet_dim=config["PRENET_DIM"],
-        attn_hidden_dim=config["ATTN_HIDDEN_DIM"],
-        attn_rnn_dim=config["ATTN_RNN_DIM"],
-        rnn_dim=config["RNN_DIM"],
-        postnet_dim=config["POSTNET_DIM"],
-        text_dim=config["TEXT_DIM"],
-    )
-
-
-def load_wavegru_config(config_file):
-    """
-    Load project configurations
-    """
-    with open(config_file, "r", encoding="utf-8") as f:
-        return yaml.safe_load(f)
-
-
-def load_wavegru_ckpt(net, optim, ckpt_file):
-    """
-    load training checkpoint from file
-    """
-    with open(ckpt_file, "rb") as f:
-        dic = pickle.load(f)
-
-    if net is not None:
-        net = net.load_state_dict(dic["net_state_dict"])
-    if optim is not None:
-        optim = optim.load_state_dict(dic["optim_state_dict"])
-    return dic["step"], net, optim
diff --git a/spaces/omarelsayeed/A7ades-Similarity-Quran-v2/app.py b/spaces/omarelsayeed/A7ades-Similarity-Quran-v2/app.py
deleted file mode 100644
index e3dc99423fa84170716eda975c7c781f8f2d89d6..0000000000000000000000000000000000000000
--- a/spaces/omarelsayeed/A7ades-Similarity-Quran-v2/app.py
+++ /dev/null
@@ -1,138 +0,0 @@
-import pandas as pd
-from rank_bm25 import BM25Okapi
-import numpy as np
-from transformers import AutoTokenizer
-from rank_bm25 import BM25Okapi
-import numpy as np
-from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langchain.embeddings import HuggingFaceEmbeddings
-from langchain.vectorstores import FAISS
-import pandas as pd
-
-dataset = pd.read_csv("filtered_133k_data_cleanlab.csv")
-df1 = dataset[['text' , 'label' , "Chat_ID" , "x" , "y"]].dropna()
-df2 = dataset[["text", "classifier_label" , "Chat_ID" , "scores_proba_countvectr" , "x" , "y"]].dropna()
-df2 = df2[df2.scores_proba_countvectr > 0.9]
-
-df2 = df2[["text" , "classifier_label" , "Chat_ID" , "x" , "y"]]
-df2.columns = ["text" , "label" , "Chat_ID" , "x" , "y"]
-dataset = pd.concat( (df1 , df2) ).reset_index(drop=True)
-dataset = dataset.sample(frac = 1).reset_index(drop=True)
-
-
-
-class KeyWordSearch:
-    
-    def __init__(self, corpus: pd.DataFrame, tokenizer = None):
-        """
-        
-        """
-        self.corpus = corpus
-        self.tokenizer = tokenizer # if you want
-        self.tokenized_corpus = [doc.split(" ") for doc in self.corpus['text']]
-        self.search_engine = BM25Okapi(self.tokenized_corpus)
-        
-    def get_top_10(self , query):
-        tokenized_query = query.split(" ")
-        scores = self.search_engine.get_scores(tokenized_query)
-        sorted_indices = np.argsort(scores)
-        top_indices = []
-        for idx in reversed(sorted_indices):
-            top_indices.append(idx)
-            if len(top_indices) == 10:
-                break
-                    
-        top_results = []
-
-        for top_index in top_indices:
-            top_results.append({
-                "positive" : query,
-                "look_up": self.corpus['text'].iloc[top_index],
-                "score": scores[top_index],
-            })
-        top_results = pd.DataFrame(top_results)
-        return dict(zip(top_results.look_up.tolist() , top_results.score.tolist()))
-    
-class VectorSearch:
-    
-    def __init__(self, corpus):
-        """
-        corpus : list of text
-        """
-        self.text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=150)
-
-        self.docs = self.text_splitter.create_documents(corpus)
-
-        modelPath = "omarelsayeed/bert_large_mnr"
-
-        model_kwargs = {'device': 'cpu'}
-
-        encode_kwargs = {'normalize_embeddings': False}
-
-        self.embeddings = HuggingFaceEmbeddings(
-            model_name=modelPath,
-            model_kwargs=model_kwargs,
-            encode_kwargs=encode_kwargs
-        )
-
-        self.db = FAISS.from_documents(self.docs, self.embeddings)
-        self.retriever = self.db.as_retriever()
-        
-    def search_query(self, query):
-        return (pd.DataFrame([[x.page_content, y] for x, y in self.db.similarity_search_with_score(query , k=10)]),
-                self.db.max_marginal_relevance_search(query , k=10 , return_score=True))
-import gradio as gr
-import pandas as pd
-
-df = pd.read_csv('filtered_133k_data_cleanlab.csv')
-class CurrentLabel:
-    current_label = None
-
-class VCC:
-    def __init__(self):
-        self.vcc = None
-        self.current_label = None
-        
-    def filter_corpus(self, label, search_query, search_method):    
-        corpus = df[df['label'] == label]
-        kw = KeyWordSearch(corpus)
-        # Implement your search functions (BM25 and Semantic) here and get the search results
-        search_results = ""
-
-        if search_method == "BM25":
-            return kw.get_top_10(search_query)
-
-        if search_method == "Semantic":
-            if CurrentLabel.current_label != label:
-                CurrentLabel.current_label = label
-                self.vcc = VectorSearch(corpus.text.tolist())
-
-            results = self.vcc.db.similarity_search_with_score(search_query , k = 10)
-            results = [(x.page_content , y) for x, y in results]
-            res = [x[0] for x in results]
-            score = [x[1] for x in results]
-            sc = [float(x) for x in score]
-            return dict(zip(res , sc))
-
-        # Format and return the search results as a string
-        if search_results == "":
-            search_results = "No results found."
-        return search_results
-
-v = VCC()
-
-
-# Create a Gradio interface
-label_dropdown = gr.inputs.Dropdown(choices=list(df['label'].unique()), label="Select Label")
-search_query_input = gr.inputs.Textbox(label="Search Query")
-search_method_radio = gr.inputs.Radio(["BM25", "Semantic"], label="Search Method")
-
-
-search_interface = gr.Interface(
-    fn=v.filter_corpus,
-    inputs=[label_dropdown, search_query_input, search_method_radio],
-    outputs=gr.outputs.Label(label="Search Results"),
-    title="Search and Filter Corpus"
-)
-
-search_interface.launch()
\ No newline at end of file
diff --git a/spaces/orpatashnik/local-prompt-mixing/src/attention_based_segmentation.py b/spaces/orpatashnik/local-prompt-mixing/src/attention_based_segmentation.py
deleted file mode 100644
index f4ed41e77214f591e9f85105084d415b8a7f8fa6..0000000000000000000000000000000000000000
--- a/spaces/orpatashnik/local-prompt-mixing/src/attention_based_segmentation.py
+++ /dev/null
@@ -1,67 +0,0 @@
-import nltk
-from sklearn.cluster import KMeans
-import numpy as np
-
-from src.attention_utils import aggregate_attention
-
-
-class Segmentor:
-
-    def __init__(self, controller, prompts, num_segments, background_segment_threshold, res=32, background_nouns=[]):
-        self.controller = controller
-        self.prompts = prompts
-        self.num_segments = num_segments
-        self.background_segment_threshold = background_segment_threshold
-        self.resolution = res
-        self.background_nouns = background_nouns
-
-        self.self_attention = aggregate_attention(controller, res=32, from_where=("up", "down"), prompts=prompts,
-                                             is_cross=False, select=len(prompts) - 1)
-        self.cross_attention = aggregate_attention(controller, res=16, from_where=("up", "down"), prompts=prompts,
-                                              is_cross=True, select=len(prompts) - 1)
-        tokenized_prompt = nltk.word_tokenize(prompts[-1])
-        self.nouns = [(i, word) for (i, (word, pos)) in enumerate(nltk.pos_tag(tokenized_prompt)) if pos[:2] == 'NN']
-
-    def __call__(self, *args, **kwargs):
-        clusters = self.cluster()
-        cluster2noun = self.cluster2noun(clusters)
-        return cluster2noun
-
-    def cluster(self):
-        np.random.seed(1)
-        resolution = self.self_attention.shape[0]
-        attn = self.self_attention.cpu().numpy().reshape(resolution ** 2, resolution ** 2)
-        kmeans = KMeans(n_clusters=self.num_segments, n_init=10).fit(attn)
-        clusters = kmeans.labels_
-        clusters = clusters.reshape(resolution, resolution)
-        return clusters
-
-    def cluster2noun(self, clusters):
-        result = {}
-        nouns_indices = [index for (index, word) in self.nouns]
-        nouns_maps = self.cross_attention.cpu().numpy()[:, :, [i + 1 for i in nouns_indices]]
-        normalized_nouns_maps = np.zeros_like(nouns_maps).repeat(2, axis=0).repeat(2, axis=1)
-        for i in range(nouns_maps.shape[-1]):
-            curr_noun_map = nouns_maps[:, :, i].repeat(2, axis=0).repeat(2, axis=1)
-            normalized_nouns_maps[:, :, i] = (curr_noun_map - np.abs(curr_noun_map.min())) / curr_noun_map.max()
-        for c in range(self.num_segments):
-            cluster_mask = np.zeros_like(clusters)
-            cluster_mask[clusters == c] = 1
-            score_maps = [cluster_mask * normalized_nouns_maps[:, :, i] for i in range(len(nouns_indices))]
-            scores = [score_map.sum() / cluster_mask.sum() for score_map in score_maps]
-            result[c] = self.nouns[np.argmax(np.array(scores))] if max(scores) > self.background_segment_threshold else "BG"
-        return result
-
-    def get_background_mask(self, obj_token_index):
-        clusters = self.cluster()
-        cluster2noun = self.cluster2noun(clusters)
-        mask = clusters.copy()
-        obj_segments = [c for c in cluster2noun if cluster2noun[c][0] == obj_token_index - 1]
-        background_segments = [c for c in cluster2noun if cluster2noun[c] == "BG" or cluster2noun[c][1] in self.background_nouns]
-        for c in range(self.num_segments):
-            if c in background_segments and c not in obj_segments:
-                mask[clusters == c] = 0
-            else:
-                mask[clusters == c] = 1
-        return mask
-
diff --git a/spaces/pikto/Elite-freegpt-webui/client/css/hljs.css b/spaces/pikto/Elite-freegpt-webui/client/css/hljs.css
deleted file mode 100644
index 4acb0fbc5fbdc688067c05cce663993a61f134d4..0000000000000000000000000000000000000000
--- a/spaces/pikto/Elite-freegpt-webui/client/css/hljs.css
+++ /dev/null
@@ -1,92 +0,0 @@
-.hljs {
-	color: #e9e9f4;
-	background: #28293629;
-	border-radius: var(--border-radius-1);
-	border: 1px solid var(--blur-border);
-	font-size: 15px;
-	word-wrap: break-word;
-	white-space: pre-wrap;
-}
-
-#message-input {
-	margin-right: 30px;
-	height: 64px;
-}
-
-#message-input::-webkit-scrollbar {
-	width: 5px;
-}
-
-/* Track */
-#message-input::-webkit-scrollbar-track {
-	background: #f1f1f1;
-}
-
-/* Handle */
-#message-input::-webkit-scrollbar-thumb {
-	background: #c7a2ff;
-}
-
-/* Handle on hover */
-#message-input::-webkit-scrollbar-thumb:hover {
-	background: #8b3dff;
-}
-
-/* style for hljs copy */
-.hljs-copy-wrapper {
-	position: relative;
-	overflow: hidden;
-}
-
-.hljs-copy-wrapper:hover .hljs-copy-button,
-.hljs-copy-button:focus {
-	transform: translateX(0);
-}
-
-.hljs-copy-button {
-	position: absolute;
-	transform: translateX(calc(100% + 1.125em));
-	top: 1em;
-	right: 1em;
-	width: 2rem;
-	height: 2rem;
-	text-indent: -9999px;
-	color: #fff;
-	border-radius: 0.25rem;
-	border: 1px solid #ffffff22;
-	background-color: #2d2b57;
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-	background-repeat: no-repeat;
-	background-position: center;
-	transition: background-color 200ms ease, transform 200ms ease-out;
-}
-
-.hljs-copy-button:hover {
-	border-color: #ffffff44;
-}
-
-.hljs-copy-button:active {
-	border-color: #ffffff66;
-}
-
-.hljs-copy-button[data-copied="true"] {
-	text-indent: 0;
-	width: auto;
-	background-image: none;
-}
-
-.hljs-copy-alert {
-	clip: rect(0 0 0 0);
-	clip-path: inset(50%);
-	height: 1px;
-	overflow: hidden;
-	position: absolute;
-	white-space: nowrap;
-	width: 1px;
-}
-
-@media (prefers-reduced-motion) {
-	.hljs-copy-button {
-		transition: none;
-	}
-}
diff --git a/spaces/pkiage/credit_risk_modeling_demo/views/model_comparison.py b/spaces/pkiage/credit_risk_modeling_demo/views/model_comparison.py
deleted file mode 100644
index b9176a4cd8e9bcc57efede1f3675f9df5f677fba..0000000000000000000000000000000000000000
--- a/spaces/pkiage/credit_risk_modeling_demo/views/model_comparison.py
+++ /dev/null
@@ -1,81 +0,0 @@
-from typing import OrderedDict
-import streamlit as st
-from sklearn.metrics import roc_auc_score
-from common.data import SplitDataset
-from common.views import (
-    roc_auc_compare_n_models,
-    streamlit_chart_setting_height_width,
-    calibration_curve_report_commented_n,
-)
-from views.typing import ModelView
-
-
-def roc_auc_for_model(split_dataset: SplitDataset, model_view: ModelView):
-    roc_auc_model = roc_auc_score(
-        split_dataset.y_test, model_view.predicted_default_status
-    )
-
-    if roc_auc_model > 0.9:
-        roc_auc_lvl = f'Very good {"{:.2f}".format(roc_auc_model)} > 0.9)'
-    elif 0.8 < roc_auc_model < 0.9:
-        roc_auc_lvl = f'Good (0.8 < {"{:.2f}".format(roc_auc_model)} <0.9)'
-    elif 0.7 < roc_auc_model < 0.8:
-        roc_auc_lvl = f'Fair (0.7 <  {"{:.2f}".format(roc_auc_model)} < 0.8)'
-    elif 0.6 < roc_auc_model < 0.7:
-        roc_auc_lvl = f'Poor (0.6 <  {"{:.2f}".format(roc_auc_model)} < 0.7)'
-    else:
-        roc_auc_lvl = f'Fail ( {"{:.2f}".format(roc_auc_model)} < 0.6)'
-
-    return roc_auc_model, roc_auc_lvl
-
-
-def model_comparison_view(
-    split_dataset: SplitDataset,
-    model_views: OrderedDict[str, ModelView],
-):
-    st.header("Model Comparison")
-
-    for model_name, model_view in model_views.items():
-        roc_auc_model, roc_auc_lvl = roc_auc_for_model(
-            split_dataset, model_view
-        )
-        st.subheader(
-            f"Receiver Operating Characteristic (ROC) Curve - {model_name}"
-        )
-        st.markdown(
-            f'Area Under the Receiver Operating Characteristic Curve from prediction scores from "{model_name}" model is {roc_auc_model}.\n'
-        )
-        st.markdown(
-            f'The score of {"{:.2f}".format(roc_auc_model)} is in the {roc_auc_lvl} ROC AUC score category.'
-        )
-    fig1 = roc_auc_compare_n_models(
-        split_dataset.y_test,
-        model_views,
-    )
-
-    fig1 = fig1.figure
-
-    (xsize_roc, ysize_roc) = streamlit_chart_setting_height_width(
-        "Chart Settings", 7, 7, "xsize_roc", "ysize_roc"
-    )
-
-    fig1.set_size_inches(xsize_roc, ysize_roc)
-
-    st.pyplot(fig1)
-
-    st.subheader("Models Calibration Curve")
-
-    fig2 = calibration_curve_report_commented_n(
-        split_dataset.y_test,
-        model_views,
-        10,
-    )
-    fig2 = fig2.figure
-
-    (xsize_cal, ysize_cal) = streamlit_chart_setting_height_width(
-        "Chart Settings", 7, 7, "xsize_cal", "ysize_cal"
-    )
-
-    fig2.set_size_inches(xsize_cal, ysize_cal)
-
-    st.pyplot(fig2.figure)
diff --git a/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_internal/commands/inspect.py b/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_internal/commands/inspect.py
deleted file mode 100644
index 27c8fa3d5b6999c77dad7aece312a5d6cf12ab48..0000000000000000000000000000000000000000
--- a/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_internal/commands/inspect.py
+++ /dev/null
@@ -1,92 +0,0 @@
-import logging
-from optparse import Values
-from typing import Any, Dict, List
-
-from pip._vendor.packaging.markers import default_environment
-from pip._vendor.rich import print_json
-
-from pip import __version__
-from pip._internal.cli import cmdoptions
-from pip._internal.cli.req_command import Command
-from pip._internal.cli.status_codes import SUCCESS
-from pip._internal.metadata import BaseDistribution, get_environment
-from pip._internal.utils.compat import stdlib_pkgs
-from pip._internal.utils.urls import path_to_url
-
-logger = logging.getLogger(__name__)
-
-
-class InspectCommand(Command):
-    """
-    Inspect the content of a Python environment and produce a report in JSON format.
-    """
-
-    ignore_require_venv = True
-    usage = """
-      %prog [options]"""
-
-    def add_options(self) -> None:
-        self.cmd_opts.add_option(
-            "--local",
-            action="store_true",
-            default=False,
-            help=(
-                "If in a virtualenv that has global access, do not list "
-                "globally-installed packages."
-            ),
-        )
-        self.cmd_opts.add_option(
-            "--user",
-            dest="user",
-            action="store_true",
-            default=False,
-            help="Only output packages installed in user-site.",
-        )
-        self.cmd_opts.add_option(cmdoptions.list_path())
-        self.parser.insert_option_group(0, self.cmd_opts)
-
-    def run(self, options: Values, args: List[str]) -> int:
-        cmdoptions.check_list_path_option(options)
-        dists = get_environment(options.path).iter_installed_distributions(
-            local_only=options.local,
-            user_only=options.user,
-            skip=set(stdlib_pkgs),
-        )
-        output = {
-            "version": "1",
-            "pip_version": __version__,
-            "installed": [self._dist_to_dict(dist) for dist in dists],
-            "environment": default_environment(),
-            # TODO tags? scheme?
-        }
-        print_json(data=output)
-        return SUCCESS
-
-    def _dist_to_dict(self, dist: BaseDistribution) -> Dict[str, Any]:
-        res: Dict[str, Any] = {
-            "metadata": dist.metadata_dict,
-            "metadata_location": dist.info_location,
-        }
-        # direct_url. Note that we don't have download_info (as in the installation
-        # report) since it is not recorded in installed metadata.
-        direct_url = dist.direct_url
-        if direct_url is not None:
-            res["direct_url"] = direct_url.to_dict()
-        else:
-            # Emulate direct_url for legacy editable installs.
-            editable_project_location = dist.editable_project_location
-            if editable_project_location is not None:
-                res["direct_url"] = {
-                    "url": path_to_url(editable_project_location),
-                    "dir_info": {
-                        "editable": True,
-                    },
-                }
-        # installer
-        installer = dist.installer
-        if dist.installer:
-            res["installer"] = installer
-        # requested
-        if dist.installed_with_dist_info:
-            res["requested"] = dist.requested
-        return res
diff --git a/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/rich/_spinners.py b/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/rich/_spinners.py
deleted file mode 100644
index d0bb1fe751677f0ee83fc6bb876ed72443fdcde7..0000000000000000000000000000000000000000
--- a/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/pip/_vendor/rich/_spinners.py
+++ /dev/null
@@ -1,482 +0,0 @@
-"""
-Spinners are from:
-* cli-spinners:
-    MIT License
-    Copyright (c) Sindre Sorhus <sindresorhus@gmail.com> (sindresorhus.com)
-    Permission is hereby granted, free of charge, to any person obtaining a copy
-    of this software and associated documentation files (the "Software"), to deal
-    in the Software without restriction, including without limitation the rights to
-    use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
-    the Software, and to permit persons to whom the Software is furnished to do so,
-    subject to the following conditions:
-    The above copyright notice and this permission notice shall be included
-    in all copies or substantial portions of the Software.
-    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
-    INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR
-    PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE
-    FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
-    ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
-    IN THE SOFTWARE.
-"""
-
-SPINNERS = {
-    "dots": {
-        "interval": 80,
-        "frames": "⠋⠙⠹⠸⠼⠴⠦⠧⠇⠏",
-    },
-    "dots2": {"interval": 80, "frames": "⣾⣽⣻⢿⡿⣟⣯⣷"},
-    "dots3": {
-        "interval": 80,
-        "frames": "⠋⠙⠚⠞⠖⠦⠴⠲⠳⠓",
-    },
-    "dots4": {
-        "interval": 80,
-        "frames": "⠄⠆⠇⠋⠙⠸⠰⠠⠰⠸⠙⠋⠇⠆",
-    },
-    "dots5": {
-        "interval": 80,
-        "frames": "⠋⠙⠚⠒⠂⠂⠒⠲⠴⠦⠖⠒⠐⠐⠒⠓⠋",
-    },
-    "dots6": {
-        "interval": 80,
-        "frames": "⠁⠉⠙⠚⠒⠂⠂⠒⠲⠴⠤⠄⠄⠤⠴⠲⠒⠂⠂⠒⠚⠙⠉⠁",
-    },
-    "dots7": {
-        "interval": 80,
-        "frames": "⠈⠉⠋⠓⠒⠐⠐⠒⠖⠦⠤⠠⠠⠤⠦⠖⠒⠐⠐⠒⠓⠋⠉⠈",
-    },
-    "dots8": {
-        "interval": 80,
-        "frames": "⠁⠁⠉⠙⠚⠒⠂⠂⠒⠲⠴⠤⠄⠄⠤⠠⠠⠤⠦⠖⠒⠐⠐⠒⠓⠋⠉⠈⠈",
-    },
-    "dots9": {"interval": 80, "frames": "⢹⢺⢼⣸⣇⡧⡗⡏"},
-    "dots10": {"interval": 80, "frames": "⢄⢂⢁⡁⡈⡐⡠"},
-    "dots11": {"interval": 100, "frames": "⠁⠂⠄⡀⢀⠠⠐⠈"},
-    "dots12": {
-        "interval": 80,
-        "frames": [
-            "⢀⠀",
-            "⡀⠀",
-            "⠄⠀",
-            "⢂⠀",
-            "⡂⠀",
-            "⠅⠀",
-            "⢃⠀",
-            "⡃⠀",
-            "⠍⠀",
-            "⢋⠀",
-            "⡋⠀",
-            "⠍⠁",
-            "⢋⠁",
-            "⡋⠁",
-            "⠍⠉",
-            "⠋⠉",
-            "⠋⠉",
-            "⠉⠙",
-            "⠉⠙",
-            "⠉⠩",
-            "⠈⢙",
-            "⠈⡙",
-            "⢈⠩",
-            "⡀⢙",
-            "⠄⡙",
-            "⢂⠩",
-            "⡂⢘",
-            "⠅⡘",
-            "⢃⠨",
-            "⡃⢐",
-            "⠍⡐",
-            "⢋⠠",
-            "⡋⢀",
-            "⠍⡁",
-            "⢋⠁",
-            "⡋⠁",
-            "⠍⠉",
-            "⠋⠉",
-            "⠋⠉",
-            "⠉⠙",
-            "⠉⠙",
-            "⠉⠩",
-            "⠈⢙",
-            "⠈⡙",
-            "⠈⠩",
-            "⠀⢙",
-            "⠀⡙",
-            "⠀⠩",
-            "⠀⢘",
-            "⠀⡘",
-            "⠀⠨",
-            "⠀⢐",
-            "⠀⡐",
-            "⠀⠠",
-            "⠀⢀",
-            "⠀⡀",
-        ],
-    },
-    "dots8Bit": {
-        "interval": 80,
-        "frames": "⠀⠁⠂⠃⠄⠅⠆⠇⡀⡁⡂⡃⡄⡅⡆⡇⠈⠉⠊⠋⠌⠍⠎⠏⡈⡉⡊⡋⡌⡍⡎⡏⠐⠑⠒⠓⠔⠕⠖⠗⡐⡑⡒⡓⡔⡕⡖⡗⠘⠙⠚⠛⠜⠝⠞⠟⡘⡙"
-        "⡚⡛⡜⡝⡞⡟⠠⠡⠢⠣⠤⠥⠦⠧⡠⡡⡢⡣⡤⡥⡦⡧⠨⠩⠪⠫⠬⠭⠮⠯⡨⡩⡪⡫⡬⡭⡮⡯⠰⠱⠲⠳⠴⠵⠶⠷⡰⡱⡲⡳⡴⡵⡶⡷⠸⠹⠺⠻"
-        "⠼⠽⠾⠿⡸⡹⡺⡻⡼⡽⡾⡿⢀⢁⢂⢃⢄⢅⢆⢇⣀⣁⣂⣃⣄⣅⣆⣇⢈⢉⢊⢋⢌⢍⢎⢏⣈⣉⣊⣋⣌⣍⣎⣏⢐⢑⢒⢓⢔⢕⢖⢗⣐⣑⣒⣓⣔⣕"
-        "⣖⣗⢘⢙⢚⢛⢜⢝⢞⢟⣘⣙⣚⣛⣜⣝⣞⣟⢠⢡⢢⢣⢤⢥⢦⢧⣠⣡⣢⣣⣤⣥⣦⣧⢨⢩⢪⢫⢬⢭⢮⢯⣨⣩⣪⣫⣬⣭⣮⣯⢰⢱⢲⢳⢴⢵⢶⢷"
-        "⣰⣱⣲⣳⣴⣵⣶⣷⢸⢹⢺⢻⢼⢽⢾⢿⣸⣹⣺⣻⣼⣽⣾⣿",
-    },
-    "line": {"interval": 130, "frames": ["-", "\\", "|", "/"]},
-    "line2": {"interval": 100, "frames": "⠂-–—–-"},
-    "pipe": {"interval": 100, "frames": "┤┘┴└├┌┬┐"},
-    "simpleDots": {"interval": 400, "frames": [".  ", ".. ", "...", "   "]},
-    "simpleDotsScrolling": {
-        "interval": 200,
-        "frames": [".  ", ".. ", "...", " ..", "  .", "   "],
-    },
-    "star": {"interval": 70, "frames": "✶✸✹✺✹✷"},
-    "star2": {"interval": 80, "frames": "+x*"},
-    "flip": {
-        "interval": 70,
-        "frames": "___-``'´-___",
-    },
-    "hamburger": {"interval": 100, "frames": "☱☲☴"},
-    "growVertical": {
-        "interval": 120,
-        "frames": "▁▃▄▅▆▇▆▅▄▃",
-    },
-    "growHorizontal": {
-        "interval": 120,
-        "frames": "▏▎▍▌▋▊▉▊▋▌▍▎",
-    },
-    "balloon": {"interval": 140, "frames": " .oO@* "},
-    "balloon2": {"interval": 120, "frames": ".oO°Oo."},
-    "noise": {"interval": 100, "frames": "▓▒░"},
-    "bounce": {"interval": 120, "frames": "⠁⠂⠄⠂"},
-    "boxBounce": {"interval": 120, "frames": "▖▘▝▗"},
-    "boxBounce2": {"interval": 100, "frames": "▌▀▐▄"},
-    "triangle": {"interval": 50, "frames": "◢◣◤◥"},
-    "arc": {"interval": 100, "frames": "◜◠◝◞◡◟"},
-    "circle": {"interval": 120, "frames": "◡⊙◠"},
-    "squareCorners": {"interval": 180, "frames": "◰◳◲◱"},
-    "circleQuarters": {"interval": 120, "frames": "◴◷◶◵"},
-    "circleHalves": {"interval": 50, "frames": "◐◓◑◒"},
-    "squish": {"interval": 100, "frames": "╫╪"},
-    "toggle": {"interval": 250, "frames": "⊶⊷"},
-    "toggle2": {"interval": 80, "frames": "▫▪"},
-    "toggle3": {"interval": 120, "frames": "□■"},
-    "toggle4": {"interval": 100, "frames": "■□▪▫"},
-    "toggle5": {"interval": 100, "frames": "▮▯"},
-    "toggle6": {"interval": 300, "frames": "ဝ၀"},
-    "toggle7": {"interval": 80, "frames": "⦾⦿"},
-    "toggle8": {"interval": 100, "frames": "◍◌"},
-    "toggle9": {"interval": 100, "frames": "◉◎"},
-    "toggle10": {"interval": 100, "frames": "㊂㊀㊁"},
-    "toggle11": {"interval": 50, "frames": "⧇⧆"},
-    "toggle12": {"interval": 120, "frames": "☗☖"},
-    "toggle13": {"interval": 80, "frames": "=*-"},
-    "arrow": {"interval": 100, "frames": "←↖↑↗→↘↓↙"},
-    "arrow2": {
-        "interval": 80,
-        "frames": ["⬆️ ", "↗️ ", "➡️ ", "↘️ ", "⬇️ ", "↙️ ", "⬅️ ", "↖️ "],
-    },
-    "arrow3": {
-        "interval": 120,
-        "frames": ["▹▹▹▹▹", "▸▹▹▹▹", "▹▸▹▹▹", "▹▹▸▹▹", "▹▹▹▸▹", "▹▹▹▹▸"],
-    },
-    "bouncingBar": {
-        "interval": 80,
-        "frames": [
-            "[    ]",
-            "[=   ]",
-            "[==  ]",
-            "[=== ]",
-            "[ ===]",
-            "[  ==]",
-            "[   =]",
-            "[    ]",
-            "[   =]",
-            "[  ==]",
-            "[ ===]",
-            "[====]",
-            "[=== ]",
-            "[==  ]",
-            "[=   ]",
-        ],
-    },
-    "bouncingBall": {
-        "interval": 80,
-        "frames": [
-            "( ●    )",
-            "(  ●   )",
-            "(   ●  )",
-            "(    ● )",
-            "(     ●)",
-            "(    ● )",
-            "(   ●  )",
-            "(  ●   )",
-            "( ●    )",
-            "(●     )",
-        ],
-    },
-    "smiley": {"interval": 200, "frames": ["😄 ", "😝 "]},
-    "monkey": {"interval": 300, "frames": ["🙈 ", "🙈 ", "🙉 ", "🙊 "]},
-    "hearts": {"interval": 100, "frames": ["💛 ", "💙 ", "💜 ", "💚 ", "❤️ "]},
-    "clock": {
-        "interval": 100,
-        "frames": [
-            "🕛 ",
-            "🕐 ",
-            "🕑 ",
-            "🕒 ",
-            "🕓 ",
-            "🕔 ",
-            "🕕 ",
-            "🕖 ",
-            "🕗 ",
-            "🕘 ",
-            "🕙 ",
-            "🕚 ",
-        ],
-    },
-    "earth": {"interval": 180, "frames": ["🌍 ", "🌎 ", "🌏 "]},
-    "material": {
-        "interval": 17,
-        "frames": [
-            "█▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
-            "██▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
-            "███▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
-            "████▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
-            "██████▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
-            "██████▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
-            "███████▁▁▁▁▁▁▁▁▁▁▁▁▁",
-            "████████▁▁▁▁▁▁▁▁▁▁▁▁",
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-            "█████████▁▁▁▁▁▁▁▁▁▁▁",
-            "██████████▁▁▁▁▁▁▁▁▁▁",
-            "███████████▁▁▁▁▁▁▁▁▁",
-            "█████████████▁▁▁▁▁▁▁",
-            "██████████████▁▁▁▁▁▁",
-            "██████████████▁▁▁▁▁▁",
-            "▁██████████████▁▁▁▁▁",
-            "▁██████████████▁▁▁▁▁",
-            "▁██████████████▁▁▁▁▁",
-            "▁▁██████████████▁▁▁▁",
-            "▁▁▁██████████████▁▁▁",
-            "▁▁▁▁█████████████▁▁▁",
-            "▁▁▁▁██████████████▁▁",
-            "▁▁▁▁██████████████▁▁",
-            "▁▁▁▁▁██████████████▁",
-            "▁▁▁▁▁██████████████▁",
-            "▁▁▁▁▁██████████████▁",
-            "▁▁▁▁▁▁██████████████",
-            "▁▁▁▁▁▁██████████████",
-            "▁▁▁▁▁▁▁█████████████",
-            "▁▁▁▁▁▁▁█████████████",
-            "▁▁▁▁▁▁▁▁████████████",
-            "▁▁▁▁▁▁▁▁████████████",
-            "▁▁▁▁▁▁▁▁▁███████████",
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-            "▁▁▁▁▁▁▁▁▁▁██████████",
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-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁██████",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█████",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█████",
-            "█▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁████",
-            "██▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁███",
-            "██▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁███",
-            "███▁▁▁▁▁▁▁▁▁▁▁▁▁▁███",
-            "████▁▁▁▁▁▁▁▁▁▁▁▁▁▁██",
-            "█████▁▁▁▁▁▁▁▁▁▁▁▁▁▁█",
-            "█████▁▁▁▁▁▁▁▁▁▁▁▁▁▁█",
-            "██████▁▁▁▁▁▁▁▁▁▁▁▁▁█",
-            "████████▁▁▁▁▁▁▁▁▁▁▁▁",
-            "█████████▁▁▁▁▁▁▁▁▁▁▁",
-            "█████████▁▁▁▁▁▁▁▁▁▁▁",
-            "█████████▁▁▁▁▁▁▁▁▁▁▁",
-            "█████████▁▁▁▁▁▁▁▁▁▁▁",
-            "███████████▁▁▁▁▁▁▁▁▁",
-            "████████████▁▁▁▁▁▁▁▁",
-            "████████████▁▁▁▁▁▁▁▁",
-            "██████████████▁▁▁▁▁▁",
-            "██████████████▁▁▁▁▁▁",
-            "▁██████████████▁▁▁▁▁",
-            "▁██████████████▁▁▁▁▁",
-            "▁▁▁█████████████▁▁▁▁",
-            "▁▁▁▁▁████████████▁▁▁",
-            "▁▁▁▁▁████████████▁▁▁",
-            "▁▁▁▁▁▁███████████▁▁▁",
-            "▁▁▁▁▁▁▁▁█████████▁▁▁",
-            "▁▁▁▁▁▁▁▁█████████▁▁▁",
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-            "▁▁▁▁▁▁▁▁▁█████████▁▁",
-            "▁▁▁▁▁▁▁▁▁▁█████████▁",
-            "▁▁▁▁▁▁▁▁▁▁▁████████▁",
-            "▁▁▁▁▁▁▁▁▁▁▁████████▁",
-            "▁▁▁▁▁▁▁▁▁▁▁▁███████▁",
-            "▁▁▁▁▁▁▁▁▁▁▁▁███████▁",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁███████",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁███████",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█████",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁████",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁████",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁████",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁███",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁███",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁██",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁██",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁██",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁█",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
-            "▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁",
-        ],
-    },
-    "moon": {
-        "interval": 80,
-        "frames": ["🌑 ", "🌒 ", "🌓 ", "🌔 ", "🌕 ", "🌖 ", "🌗 ", "🌘 "],
-    },
-    "runner": {"interval": 140, "frames": ["🚶 ", "🏃 "]},
-    "pong": {
-        "interval": 80,
-        "frames": [
-            "▐⠂       ▌",
-            "▐⠈       ▌",
-            "▐ ⠂      ▌",
-            "▐ ⠠      ▌",
-            "▐  ⡀     ▌",
-            "▐  ⠠     ▌",
-            "▐   ⠂    ▌",
-            "▐   ⠈    ▌",
-            "▐    ⠂   ▌",
-            "▐    ⠠   ▌",
-            "▐     ⡀  ▌",
-            "▐     ⠠  ▌",
-            "▐      ⠂ ▌",
-            "▐      ⠈ ▌",
-            "▐       ⠂▌",
-            "▐       ⠠▌",
-            "▐       ⡀▌",
-            "▐      ⠠ ▌",
-            "▐      ⠂ ▌",
-            "▐     ⠈  ▌",
-            "▐     ⠂  ▌",
-            "▐    ⠠   ▌",
-            "▐    ⡀   ▌",
-            "▐   ⠠    ▌",
-            "▐   ⠂    ▌",
-            "▐  ⠈     ▌",
-            "▐  ⠂     ▌",
-            "▐ ⠠      ▌",
-            "▐ ⡀      ▌",
-            "▐⠠       ▌",
-        ],
-    },
-    "shark": {
-        "interval": 120,
-        "frames": [
-            "▐|\\____________▌",
-            "▐_|\\___________▌",
-            "▐__|\\__________▌",
-            "▐___|\\_________▌",
-            "▐____|\\________▌",
-            "▐_____|\\_______▌",
-            "▐______|\\______▌",
-            "▐_______|\\_____▌",
-            "▐________|\\____▌",
-            "▐_________|\\___▌",
-            "▐__________|\\__▌",
-            "▐___________|\\_▌",
-            "▐____________|\\▌",
-            "▐____________/|▌",
-            "▐___________/|_▌",
-            "▐__________/|__▌",
-            "▐_________/|___▌",
-            "▐________/|____▌",
-            "▐_______/|_____▌",
-            "▐______/|______▌",
-            "▐_____/|_______▌",
-            "▐____/|________▌",
-            "▐___/|_________▌",
-            "▐__/|__________▌",
-            "▐_/|___________▌",
-            "▐/|____________▌",
-        ],
-    },
-    "dqpb": {"interval": 100, "frames": "dqpb"},
-    "weather": {
-        "interval": 100,
-        "frames": [
-            "☀️ ",
-            "☀️ ",
-            "☀️ ",
-            "🌤 ",
-            "⛅️ ",
-            "🌥 ",
-            "☁️ ",
-            "🌧 ",
-            "🌨 ",
-            "🌧 ",
-            "🌨 ",
-            "🌧 ",
-            "🌨 ",
-            "⛈ ",
-            "🌨 ",
-            "🌧 ",
-            "🌨 ",
-            "☁️ ",
-            "🌥 ",
-            "⛅️ ",
-            "🌤 ",
-            "☀️ ",
-            "☀️ ",
-        ],
-    },
-    "christmas": {"interval": 400, "frames": "🌲🎄"},
-    "grenade": {
-        "interval": 80,
-        "frames": [
-            "،   ",
-            "′   ",
-            " ´ ",
-            " ‾ ",
-            "  ⸌",
-            "  ⸊",
-            "  |",
-            "  ⁎",
-            "  ⁕",
-            " ෴ ",
-            "  ⁓",
-            "   ",
-            "   ",
-            "   ",
-        ],
-    },
-    "point": {"interval": 125, "frames": ["∙∙∙", "●∙∙", "∙●∙", "∙∙●", "∙∙∙"]},
-    "layer": {"interval": 150, "frames": "-=≡"},
-    "betaWave": {
-        "interval": 80,
-        "frames": [
-            "ρββββββ",
-            "βρβββββ",
-            "ββρββββ",
-            "βββρβββ",
-            "ββββρββ",
-            "βββββρβ",
-            "ββββββρ",
-        ],
-    },
-    "aesthetic": {
-        "interval": 80,
-        "frames": [
-            "▰▱▱▱▱▱▱",
-            "▰▰▱▱▱▱▱",
-            "▰▰▰▱▱▱▱",
-            "▰▰▰▰▱▱▱",
-            "▰▰▰▰▰▱▱",
-            "▰▰▰▰▰▰▱",
-            "▰▰▰▰▰▰▰",
-            "▰▱▱▱▱▱▱",
-        ],
-    },
-}
diff --git a/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/pkg_resources/_vendor/typing_extensions.py b/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/pkg_resources/_vendor/typing_extensions.py
deleted file mode 100644
index ef42417c208e93c55d704728d3e88dfe46250d92..0000000000000000000000000000000000000000
--- a/spaces/pknez/face-swap-docker/mynewshinyroop/Lib/site-packages/pkg_resources/_vendor/typing_extensions.py
+++ /dev/null
@@ -1,2209 +0,0 @@
-import abc
-import collections
-import collections.abc
-import functools
-import operator
-import sys
-import types as _types
-import typing
-
-
-__all__ = [
-    # Super-special typing primitives.
-    'Any',
-    'ClassVar',
-    'Concatenate',
-    'Final',
-    'LiteralString',
-    'ParamSpec',
-    'ParamSpecArgs',
-    'ParamSpecKwargs',
-    'Self',
-    'Type',
-    'TypeVar',
-    'TypeVarTuple',
-    'Unpack',
-
-    # ABCs (from collections.abc).
-    'Awaitable',
-    'AsyncIterator',
-    'AsyncIterable',
-    'Coroutine',
-    'AsyncGenerator',
-    'AsyncContextManager',
-    'ChainMap',
-
-    # Concrete collection types.
-    'ContextManager',
-    'Counter',
-    'Deque',
-    'DefaultDict',
-    'NamedTuple',
-    'OrderedDict',
-    'TypedDict',
-
-    # Structural checks, a.k.a. protocols.
-    'SupportsIndex',
-
-    # One-off things.
-    'Annotated',
-    'assert_never',
-    'assert_type',
-    'clear_overloads',
-    'dataclass_transform',
-    'get_overloads',
-    'final',
-    'get_args',
-    'get_origin',
-    'get_type_hints',
-    'IntVar',
-    'is_typeddict',
-    'Literal',
-    'NewType',
-    'overload',
-    'override',
-    'Protocol',
-    'reveal_type',
-    'runtime',
-    'runtime_checkable',
-    'Text',
-    'TypeAlias',
-    'TypeGuard',
-    'TYPE_CHECKING',
-    'Never',
-    'NoReturn',
-    'Required',
-    'NotRequired',
-]
-
-# for backward compatibility
-PEP_560 = True
-GenericMeta = type
-
-# The functions below are modified copies of typing internal helpers.
-# They are needed by _ProtocolMeta and they provide support for PEP 646.
-
-_marker = object()
-
-
-def _check_generic(cls, parameters, elen=_marker):
-    """Check correct count for parameters of a generic cls (internal helper).
-    This gives a nice error message in case of count mismatch.
-    """
-    if not elen:
-        raise TypeError(f"{cls} is not a generic class")
-    if elen is _marker:
-        if not hasattr(cls, "__parameters__") or not cls.__parameters__:
-            raise TypeError(f"{cls} is not a generic class")
-        elen = len(cls.__parameters__)
-    alen = len(parameters)
-    if alen != elen:
-        if hasattr(cls, "__parameters__"):
-            parameters = [p for p in cls.__parameters__ if not _is_unpack(p)]
-            num_tv_tuples = sum(isinstance(p, TypeVarTuple) for p in parameters)
-            if (num_tv_tuples > 0) and (alen >= elen - num_tv_tuples):
-                return
-        raise TypeError(f"Too {'many' if alen > elen else 'few'} parameters for {cls};"
-                        f" actual {alen}, expected {elen}")
-
-
-if sys.version_info >= (3, 10):
-    def _should_collect_from_parameters(t):
-        return isinstance(
-            t, (typing._GenericAlias, _types.GenericAlias, _types.UnionType)
-        )
-elif sys.version_info >= (3, 9):
-    def _should_collect_from_parameters(t):
-        return isinstance(t, (typing._GenericAlias, _types.GenericAlias))
-else:
-    def _should_collect_from_parameters(t):
-        return isinstance(t, typing._GenericAlias) and not t._special
-
-
-def _collect_type_vars(types, typevar_types=None):
-    """Collect all type variable contained in types in order of
-    first appearance (lexicographic order). For example::
-
-        _collect_type_vars((T, List[S, T])) == (T, S)
-    """
-    if typevar_types is None:
-        typevar_types = typing.TypeVar
-    tvars = []
-    for t in types:
-        if (
-            isinstance(t, typevar_types) and
-            t not in tvars and
-            not _is_unpack(t)
-        ):
-            tvars.append(t)
-        if _should_collect_from_parameters(t):
-            tvars.extend([t for t in t.__parameters__ if t not in tvars])
-    return tuple(tvars)
-
-
-NoReturn = typing.NoReturn
-
-# Some unconstrained type variables.  These are used by the container types.
-# (These are not for export.)
-T = typing.TypeVar('T')  # Any type.
-KT = typing.TypeVar('KT')  # Key type.
-VT = typing.TypeVar('VT')  # Value type.
-T_co = typing.TypeVar('T_co', covariant=True)  # Any type covariant containers.
-T_contra = typing.TypeVar('T_contra', contravariant=True)  # Ditto contravariant.
-
-
-if sys.version_info >= (3, 11):
-    from typing import Any
-else:
-
-    class _AnyMeta(type):
-        def __instancecheck__(self, obj):
-            if self is Any:
-                raise TypeError("typing_extensions.Any cannot be used with isinstance()")
-            return super().__instancecheck__(obj)
-
-        def __repr__(self):
-            if self is Any:
-                return "typing_extensions.Any"
-            return super().__repr__()
-
-    class Any(metaclass=_AnyMeta):
-        """Special type indicating an unconstrained type.
-        - Any is compatible with every type.
-        - Any assumed to have all methods.
-        - All values assumed to be instances of Any.
-        Note that all the above statements are true from the point of view of
-        static type checkers. At runtime, Any should not be used with instance
-        checks.
-        """
-        def __new__(cls, *args, **kwargs):
-            if cls is Any:
-                raise TypeError("Any cannot be instantiated")
-            return super().__new__(cls, *args, **kwargs)
-
-
-ClassVar = typing.ClassVar
-
-# On older versions of typing there is an internal class named "Final".
-# 3.8+
-if hasattr(typing, 'Final') and sys.version_info[:2] >= (3, 7):
-    Final = typing.Final
-# 3.7
-else:
-    class _FinalForm(typing._SpecialForm, _root=True):
-
-        def __repr__(self):
-            return 'typing_extensions.' + self._name
-
-        def __getitem__(self, parameters):
-            item = typing._type_check(parameters,
-                                      f'{self._name} accepts only a single type.')
-            return typing._GenericAlias(self, (item,))
-
-    Final = _FinalForm('Final',
-                       doc="""A special typing construct to indicate that a name
-                       cannot be re-assigned or overridden in a subclass.
-                       For example:
-
-                           MAX_SIZE: Final = 9000
-                           MAX_SIZE += 1  # Error reported by type checker
-
-                           class Connection:
-                               TIMEOUT: Final[int] = 10
-                           class FastConnector(Connection):
-                               TIMEOUT = 1  # Error reported by type checker
-
-                       There is no runtime checking of these properties.""")
-
-if sys.version_info >= (3, 11):
-    final = typing.final
-else:
-    # @final exists in 3.8+, but we backport it for all versions
-    # before 3.11 to keep support for the __final__ attribute.
-    # See https://bugs.python.org/issue46342
-    def final(f):
-        """This decorator can be used to indicate to type checkers that
-        the decorated method cannot be overridden, and decorated class
-        cannot be subclassed. For example:
-
-            class Base:
-                @final
-                def done(self) -> None:
-                    ...
-            class Sub(Base):
-                def done(self) -> None:  # Error reported by type checker
-                    ...
-            @final
-            class Leaf:
-                ...
-            class Other(Leaf):  # Error reported by type checker
-                ...
-
-        There is no runtime checking of these properties. The decorator
-        sets the ``__final__`` attribute to ``True`` on the decorated object
-        to allow runtime introspection.
-        """
-        try:
-            f.__final__ = True
-        except (AttributeError, TypeError):
-            # Skip the attribute silently if it is not writable.
-            # AttributeError happens if the object has __slots__ or a
-            # read-only property, TypeError if it's a builtin class.
-            pass
-        return f
-
-
-def IntVar(name):
-    return typing.TypeVar(name)
-
-
-# 3.8+:
-if hasattr(typing, 'Literal'):
-    Literal = typing.Literal
-# 3.7:
-else:
-    class _LiteralForm(typing._SpecialForm, _root=True):
-
-        def __repr__(self):
-            return 'typing_extensions.' + self._name
-
-        def __getitem__(self, parameters):
-            return typing._GenericAlias(self, parameters)
-
-    Literal = _LiteralForm('Literal',
-                           doc="""A type that can be used to indicate to type checkers
-                           that the corresponding value has a value literally equivalent
-                           to the provided parameter. For example:
-
-                               var: Literal[4] = 4
-
-                           The type checker understands that 'var' is literally equal to
-                           the value 4 and no other value.
-
-                           Literal[...] cannot be subclassed. There is no runtime
-                           checking verifying that the parameter is actually a value
-                           instead of a type.""")
-
-
-_overload_dummy = typing._overload_dummy  # noqa
-
-
-if hasattr(typing, "get_overloads"):  # 3.11+
-    overload = typing.overload
-    get_overloads = typing.get_overloads
-    clear_overloads = typing.clear_overloads
-else:
-    # {module: {qualname: {firstlineno: func}}}
-    _overload_registry = collections.defaultdict(
-        functools.partial(collections.defaultdict, dict)
-    )
-
-    def overload(func):
-        """Decorator for overloaded functions/methods.
-
-        In a stub file, place two or more stub definitions for the same
-        function in a row, each decorated with @overload.  For example:
-
-        @overload
-        def utf8(value: None) -> None: ...
-        @overload
-        def utf8(value: bytes) -> bytes: ...
-        @overload
-        def utf8(value: str) -> bytes: ...
-
-        In a non-stub file (i.e. a regular .py file), do the same but
-        follow it with an implementation.  The implementation should *not*
-        be decorated with @overload.  For example:
-
-        @overload
-        def utf8(value: None) -> None: ...
-        @overload
-        def utf8(value: bytes) -> bytes: ...
-        @overload
-        def utf8(value: str) -> bytes: ...
-        def utf8(value):
-            # implementation goes here
-
-        The overloads for a function can be retrieved at runtime using the
-        get_overloads() function.
-        """
-        # classmethod and staticmethod
-        f = getattr(func, "__func__", func)
-        try:
-            _overload_registry[f.__module__][f.__qualname__][
-                f.__code__.co_firstlineno
-            ] = func
-        except AttributeError:
-            # Not a normal function; ignore.
-            pass
-        return _overload_dummy
-
-    def get_overloads(func):
-        """Return all defined overloads for *func* as a sequence."""
-        # classmethod and staticmethod
-        f = getattr(func, "__func__", func)
-        if f.__module__ not in _overload_registry:
-            return []
-        mod_dict = _overload_registry[f.__module__]
-        if f.__qualname__ not in mod_dict:
-            return []
-        return list(mod_dict[f.__qualname__].values())
-
-    def clear_overloads():
-        """Clear all overloads in the registry."""
-        _overload_registry.clear()
-
-
-# This is not a real generic class.  Don't use outside annotations.
-Type = typing.Type
-
-# Various ABCs mimicking those in collections.abc.
-# A few are simply re-exported for completeness.
-
-
-Awaitable = typing.Awaitable
-Coroutine = typing.Coroutine
-AsyncIterable = typing.AsyncIterable
-AsyncIterator = typing.AsyncIterator
-Deque = typing.Deque
-ContextManager = typing.ContextManager
-AsyncContextManager = typing.AsyncContextManager
-DefaultDict = typing.DefaultDict
-
-# 3.7.2+
-if hasattr(typing, 'OrderedDict'):
-    OrderedDict = typing.OrderedDict
-# 3.7.0-3.7.2
-else:
-    OrderedDict = typing._alias(collections.OrderedDict, (KT, VT))
-
-Counter = typing.Counter
-ChainMap = typing.ChainMap
-AsyncGenerator = typing.AsyncGenerator
-NewType = typing.NewType
-Text = typing.Text
-TYPE_CHECKING = typing.TYPE_CHECKING
-
-
-_PROTO_WHITELIST = ['Callable', 'Awaitable',
-                    'Iterable', 'Iterator', 'AsyncIterable', 'AsyncIterator',
-                    'Hashable', 'Sized', 'Container', 'Collection', 'Reversible',
-                    'ContextManager', 'AsyncContextManager']
-
-
-def _get_protocol_attrs(cls):
-    attrs = set()
-    for base in cls.__mro__[:-1]:  # without object
-        if base.__name__ in ('Protocol', 'Generic'):
-            continue
-        annotations = getattr(base, '__annotations__', {})
-        for attr in list(base.__dict__.keys()) + list(annotations.keys()):
-            if (not attr.startswith('_abc_') and attr not in (
-                    '__abstractmethods__', '__annotations__', '__weakref__',
-                    '_is_protocol', '_is_runtime_protocol', '__dict__',
-                    '__args__', '__slots__',
-                    '__next_in_mro__', '__parameters__', '__origin__',
-                    '__orig_bases__', '__extra__', '__tree_hash__',
-                    '__doc__', '__subclasshook__', '__init__', '__new__',
-                    '__module__', '_MutableMapping__marker', '_gorg')):
-                attrs.add(attr)
-    return attrs
-
-
-def _is_callable_members_only(cls):
-    return all(callable(getattr(cls, attr, None)) for attr in _get_protocol_attrs(cls))
-
-
-def _maybe_adjust_parameters(cls):
-    """Helper function used in Protocol.__init_subclass__ and _TypedDictMeta.__new__.
-
-    The contents of this function are very similar
-    to logic found in typing.Generic.__init_subclass__
-    on the CPython main branch.
-    """
-    tvars = []
-    if '__orig_bases__' in cls.__dict__:
-        tvars = typing._collect_type_vars(cls.__orig_bases__)
-        # Look for Generic[T1, ..., Tn] or Protocol[T1, ..., Tn].
-        # If found, tvars must be a subset of it.
-        # If not found, tvars is it.
-        # Also check for and reject plain Generic,
-        # and reject multiple Generic[...] and/or Protocol[...].
-        gvars = None
-        for base in cls.__orig_bases__:
-            if (isinstance(base, typing._GenericAlias) and
-                    base.__origin__ in (typing.Generic, Protocol)):
-                # for error messages
-                the_base = base.__origin__.__name__
-                if gvars is not None:
-                    raise TypeError(
-                        "Cannot inherit from Generic[...]"
-                        " and/or Protocol[...] multiple types.")
-                gvars = base.__parameters__
-        if gvars is None:
-            gvars = tvars
-        else:
-            tvarset = set(tvars)
-            gvarset = set(gvars)
-            if not tvarset <= gvarset:
-                s_vars = ', '.join(str(t) for t in tvars if t not in gvarset)
-                s_args = ', '.join(str(g) for g in gvars)
-                raise TypeError(f"Some type variables ({s_vars}) are"
-                                f" not listed in {the_base}[{s_args}]")
-            tvars = gvars
-    cls.__parameters__ = tuple(tvars)
-
-
-# 3.8+
-if hasattr(typing, 'Protocol'):
-    Protocol = typing.Protocol
-# 3.7
-else:
-
-    def _no_init(self, *args, **kwargs):
-        if type(self)._is_protocol:
-            raise TypeError('Protocols cannot be instantiated')
-
-    class _ProtocolMeta(abc.ABCMeta):  # noqa: B024
-        # This metaclass is a bit unfortunate and exists only because of the lack
-        # of __instancehook__.
-        def __instancecheck__(cls, instance):
-            # We need this method for situations where attributes are
-            # assigned in __init__.
-            if ((not getattr(cls, '_is_protocol', False) or
-                 _is_callable_members_only(cls)) and
-                    issubclass(instance.__class__, cls)):
-                return True
-            if cls._is_protocol:
-                if all(hasattr(instance, attr) and
-                       (not callable(getattr(cls, attr, None)) or
-                        getattr(instance, attr) is not None)
-                       for attr in _get_protocol_attrs(cls)):
-                    return True
-            return super().__instancecheck__(instance)
-
-    class Protocol(metaclass=_ProtocolMeta):
-        # There is quite a lot of overlapping code with typing.Generic.
-        # Unfortunately it is hard to avoid this while these live in two different
-        # modules. The duplicated code will be removed when Protocol is moved to typing.
-        """Base class for protocol classes. Protocol classes are defined as::
-
-            class Proto(Protocol):
-                def meth(self) -> int:
-                    ...
-
-        Such classes are primarily used with static type checkers that recognize
-        structural subtyping (static duck-typing), for example::
-
-            class C:
-                def meth(self) -> int:
-                    return 0
-
-            def func(x: Proto) -> int:
-                return x.meth()
-
-            func(C())  # Passes static type check
-
-        See PEP 544 for details. Protocol classes decorated with
-        @typing_extensions.runtime act as simple-minded runtime protocol that checks
-        only the presence of given attributes, ignoring their type signatures.
-
-        Protocol classes can be generic, they are defined as::
-
-            class GenProto(Protocol[T]):
-                def meth(self) -> T:
-                    ...
-        """
-        __slots__ = ()
-        _is_protocol = True
-
-        def __new__(cls, *args, **kwds):
-            if cls is Protocol:
-                raise TypeError("Type Protocol cannot be instantiated; "
-                                "it can only be used as a base class")
-            return super().__new__(cls)
-
-        @typing._tp_cache
-        def __class_getitem__(cls, params):
-            if not isinstance(params, tuple):
-                params = (params,)
-            if not params and cls is not typing.Tuple:
-                raise TypeError(
-                    f"Parameter list to {cls.__qualname__}[...] cannot be empty")
-            msg = "Parameters to generic types must be types."
-            params = tuple(typing._type_check(p, msg) for p in params)  # noqa
-            if cls is Protocol:
-                # Generic can only be subscripted with unique type variables.
-                if not all(isinstance(p, typing.TypeVar) for p in params):
-                    i = 0
-                    while isinstance(params[i], typing.TypeVar):
-                        i += 1
-                    raise TypeError(
-                        "Parameters to Protocol[...] must all be type variables."
-                        f" Parameter {i + 1} is {params[i]}")
-                if len(set(params)) != len(params):
-                    raise TypeError(
-                        "Parameters to Protocol[...] must all be unique")
-            else:
-                # Subscripting a regular Generic subclass.
-                _check_generic(cls, params, len(cls.__parameters__))
-            return typing._GenericAlias(cls, params)
-
-        def __init_subclass__(cls, *args, **kwargs):
-            if '__orig_bases__' in cls.__dict__:
-                error = typing.Generic in cls.__orig_bases__
-            else:
-                error = typing.Generic in cls.__bases__
-            if error:
-                raise TypeError("Cannot inherit from plain Generic")
-            _maybe_adjust_parameters(cls)
-
-            # Determine if this is a protocol or a concrete subclass.
-            if not cls.__dict__.get('_is_protocol', None):
-                cls._is_protocol = any(b is Protocol for b in cls.__bases__)
-
-            # Set (or override) the protocol subclass hook.
-            def _proto_hook(other):
-                if not cls.__dict__.get('_is_protocol', None):
-                    return NotImplemented
-                if not getattr(cls, '_is_runtime_protocol', False):
-                    if sys._getframe(2).f_globals['__name__'] in ['abc', 'functools']:
-                        return NotImplemented
-                    raise TypeError("Instance and class checks can only be used with"
-                                    " @runtime protocols")
-                if not _is_callable_members_only(cls):
-                    if sys._getframe(2).f_globals['__name__'] in ['abc', 'functools']:
-                        return NotImplemented
-                    raise TypeError("Protocols with non-method members"
-                                    " don't support issubclass()")
-                if not isinstance(other, type):
-                    # Same error as for issubclass(1, int)
-                    raise TypeError('issubclass() arg 1 must be a class')
-                for attr in _get_protocol_attrs(cls):
-                    for base in other.__mro__:
-                        if attr in base.__dict__:
-                            if base.__dict__[attr] is None:
-                                return NotImplemented
-                            break
-                        annotations = getattr(base, '__annotations__', {})
-                        if (isinstance(annotations, typing.Mapping) and
-                                attr in annotations and
-                                isinstance(other, _ProtocolMeta) and
-                                other._is_protocol):
-                            break
-                    else:
-                        return NotImplemented
-                return True
-            if '__subclasshook__' not in cls.__dict__:
-                cls.__subclasshook__ = _proto_hook
-
-            # We have nothing more to do for non-protocols.
-            if not cls._is_protocol:
-                return
-
-            # Check consistency of bases.
-            for base in cls.__bases__:
-                if not (base in (object, typing.Generic) or
-                        base.__module__ == 'collections.abc' and
-                        base.__name__ in _PROTO_WHITELIST or
-                        isinstance(base, _ProtocolMeta) and base._is_protocol):
-                    raise TypeError('Protocols can only inherit from other'
-                                    f' protocols, got {repr(base)}')
-            cls.__init__ = _no_init
-
-
-# 3.8+
-if hasattr(typing, 'runtime_checkable'):
-    runtime_checkable = typing.runtime_checkable
-# 3.7
-else:
-    def runtime_checkable(cls):
-        """Mark a protocol class as a runtime protocol, so that it
-        can be used with isinstance() and issubclass(). Raise TypeError
-        if applied to a non-protocol class.
-
-        This allows a simple-minded structural check very similar to the
-        one-offs in collections.abc such as Hashable.
-        """
-        if not isinstance(cls, _ProtocolMeta) or not cls._is_protocol:
-            raise TypeError('@runtime_checkable can be only applied to protocol classes,'
-                            f' got {cls!r}')
-        cls._is_runtime_protocol = True
-        return cls
-
-
-# Exists for backwards compatibility.
-runtime = runtime_checkable
-
-
-# 3.8+
-if hasattr(typing, 'SupportsIndex'):
-    SupportsIndex = typing.SupportsIndex
-# 3.7
-else:
-    @runtime_checkable
-    class SupportsIndex(Protocol):
-        __slots__ = ()
-
-        @abc.abstractmethod
-        def __index__(self) -> int:
-            pass
-
-
-if hasattr(typing, "Required"):
-    # The standard library TypedDict in Python 3.8 does not store runtime information
-    # about which (if any) keys are optional.  See https://bugs.python.org/issue38834
-    # The standard library TypedDict in Python 3.9.0/1 does not honour the "total"
-    # keyword with old-style TypedDict().  See https://bugs.python.org/issue42059
-    # The standard library TypedDict below Python 3.11 does not store runtime
-    # information about optional and required keys when using Required or NotRequired.
-    # Generic TypedDicts are also impossible using typing.TypedDict on Python <3.11.
-    TypedDict = typing.TypedDict
-    _TypedDictMeta = typing._TypedDictMeta
-    is_typeddict = typing.is_typeddict
-else:
-    def _check_fails(cls, other):
-        try:
-            if sys._getframe(1).f_globals['__name__'] not in ['abc',
-                                                              'functools',
-                                                              'typing']:
-                # Typed dicts are only for static structural subtyping.
-                raise TypeError('TypedDict does not support instance and class checks')
-        except (AttributeError, ValueError):
-            pass
-        return False
-
-    def _dict_new(*args, **kwargs):
-        if not args:
-            raise TypeError('TypedDict.__new__(): not enough arguments')
-        _, args = args[0], args[1:]  # allow the "cls" keyword be passed
-        return dict(*args, **kwargs)
-
-    _dict_new.__text_signature__ = '($cls, _typename, _fields=None, /, **kwargs)'
-
-    def _typeddict_new(*args, total=True, **kwargs):
-        if not args:
-            raise TypeError('TypedDict.__new__(): not enough arguments')
-        _, args = args[0], args[1:]  # allow the "cls" keyword be passed
-        if args:
-            typename, args = args[0], args[1:]  # allow the "_typename" keyword be passed
-        elif '_typename' in kwargs:
-            typename = kwargs.pop('_typename')
-            import warnings
-            warnings.warn("Passing '_typename' as keyword argument is deprecated",
-                          DeprecationWarning, stacklevel=2)
-        else:
-            raise TypeError("TypedDict.__new__() missing 1 required positional "
-                            "argument: '_typename'")
-        if args:
-            try:
-                fields, = args  # allow the "_fields" keyword be passed
-            except ValueError:
-                raise TypeError('TypedDict.__new__() takes from 2 to 3 '
-                                f'positional arguments but {len(args) + 2} '
-                                'were given')
-        elif '_fields' in kwargs and len(kwargs) == 1:
-            fields = kwargs.pop('_fields')
-            import warnings
-            warnings.warn("Passing '_fields' as keyword argument is deprecated",
-                          DeprecationWarning, stacklevel=2)
-        else:
-            fields = None
-
-        if fields is None:
-            fields = kwargs
-        elif kwargs:
-            raise TypeError("TypedDict takes either a dict or keyword arguments,"
-                            " but not both")
-
-        ns = {'__annotations__': dict(fields)}
-        try:
-            # Setting correct module is necessary to make typed dict classes pickleable.
-            ns['__module__'] = sys._getframe(1).f_globals.get('__name__', '__main__')
-        except (AttributeError, ValueError):
-            pass
-
-        return _TypedDictMeta(typename, (), ns, total=total)
-
-    _typeddict_new.__text_signature__ = ('($cls, _typename, _fields=None,'
-                                         ' /, *, total=True, **kwargs)')
-
-    class _TypedDictMeta(type):
-        def __init__(cls, name, bases, ns, total=True):
-            super().__init__(name, bases, ns)
-
-        def __new__(cls, name, bases, ns, total=True):
-            # Create new typed dict class object.
-            # This method is called directly when TypedDict is subclassed,
-            # or via _typeddict_new when TypedDict is instantiated. This way
-            # TypedDict supports all three syntaxes described in its docstring.
-            # Subclasses and instances of TypedDict return actual dictionaries
-            # via _dict_new.
-            ns['__new__'] = _typeddict_new if name == 'TypedDict' else _dict_new
-            # Don't insert typing.Generic into __bases__ here,
-            # or Generic.__init_subclass__ will raise TypeError
-            # in the super().__new__() call.
-            # Instead, monkey-patch __bases__ onto the class after it's been created.
-            tp_dict = super().__new__(cls, name, (dict,), ns)
-
-            if any(issubclass(base, typing.Generic) for base in bases):
-                tp_dict.__bases__ = (typing.Generic, dict)
-                _maybe_adjust_parameters(tp_dict)
-
-            annotations = {}
-            own_annotations = ns.get('__annotations__', {})
-            msg = "TypedDict('Name', {f0: t0, f1: t1, ...}); each t must be a type"
-            own_annotations = {
-                n: typing._type_check(tp, msg) for n, tp in own_annotations.items()
-            }
-            required_keys = set()
-            optional_keys = set()
-
-            for base in bases:
-                annotations.update(base.__dict__.get('__annotations__', {}))
-                required_keys.update(base.__dict__.get('__required_keys__', ()))
-                optional_keys.update(base.__dict__.get('__optional_keys__', ()))
-
-            annotations.update(own_annotations)
-            for annotation_key, annotation_type in own_annotations.items():
-                annotation_origin = get_origin(annotation_type)
-                if annotation_origin is Annotated:
-                    annotation_args = get_args(annotation_type)
-                    if annotation_args:
-                        annotation_type = annotation_args[0]
-                        annotation_origin = get_origin(annotation_type)
-
-                if annotation_origin is Required:
-                    required_keys.add(annotation_key)
-                elif annotation_origin is NotRequired:
-                    optional_keys.add(annotation_key)
-                elif total:
-                    required_keys.add(annotation_key)
-                else:
-                    optional_keys.add(annotation_key)
-
-            tp_dict.__annotations__ = annotations
-            tp_dict.__required_keys__ = frozenset(required_keys)
-            tp_dict.__optional_keys__ = frozenset(optional_keys)
-            if not hasattr(tp_dict, '__total__'):
-                tp_dict.__total__ = total
-            return tp_dict
-
-        __instancecheck__ = __subclasscheck__ = _check_fails
-
-    TypedDict = _TypedDictMeta('TypedDict', (dict,), {})
-    TypedDict.__module__ = __name__
-    TypedDict.__doc__ = \
-        """A simple typed name space. At runtime it is equivalent to a plain dict.
-
-        TypedDict creates a dictionary type that expects all of its
-        instances to have a certain set of keys, with each key
-        associated with a value of a consistent type. This expectation
-        is not checked at runtime but is only enforced by type checkers.
-        Usage::
-
-            class Point2D(TypedDict):
-                x: int
-                y: int
-                label: str
-
-            a: Point2D = {'x': 1, 'y': 2, 'label': 'good'}  # OK
-            b: Point2D = {'z': 3, 'label': 'bad'}           # Fails type check
-
-            assert Point2D(x=1, y=2, label='first') == dict(x=1, y=2, label='first')
-
-        The type info can be accessed via the Point2D.__annotations__ dict, and
-        the Point2D.__required_keys__ and Point2D.__optional_keys__ frozensets.
-        TypedDict supports two additional equivalent forms::
-
-            Point2D = TypedDict('Point2D', x=int, y=int, label=str)
-            Point2D = TypedDict('Point2D', {'x': int, 'y': int, 'label': str})
-
-        The class syntax is only supported in Python 3.6+, while two other
-        syntax forms work for Python 2.7 and 3.2+
-        """
-
-    if hasattr(typing, "_TypedDictMeta"):
-        _TYPEDDICT_TYPES = (typing._TypedDictMeta, _TypedDictMeta)
-    else:
-        _TYPEDDICT_TYPES = (_TypedDictMeta,)
-
-    def is_typeddict(tp):
-        """Check if an annotation is a TypedDict class
-
-        For example::
-            class Film(TypedDict):
-                title: str
-                year: int
-
-            is_typeddict(Film)  # => True
-            is_typeddict(Union[list, str])  # => False
-        """
-        return isinstance(tp, tuple(_TYPEDDICT_TYPES))
-
-
-if hasattr(typing, "assert_type"):
-    assert_type = typing.assert_type
-
-else:
-    def assert_type(__val, __typ):
-        """Assert (to the type checker) that the value is of the given type.
-
-        When the type checker encounters a call to assert_type(), it
-        emits an error if the value is not of the specified type::
-
-            def greet(name: str) -> None:
-                assert_type(name, str)  # ok
-                assert_type(name, int)  # type checker error
-
-        At runtime this returns the first argument unchanged and otherwise
-        does nothing.
-        """
-        return __val
-
-
-if hasattr(typing, "Required"):
-    get_type_hints = typing.get_type_hints
-else:
-    import functools
-    import types
-
-    # replaces _strip_annotations()
-    def _strip_extras(t):
-        """Strips Annotated, Required and NotRequired from a given type."""
-        if isinstance(t, _AnnotatedAlias):
-            return _strip_extras(t.__origin__)
-        if hasattr(t, "__origin__") and t.__origin__ in (Required, NotRequired):
-            return _strip_extras(t.__args__[0])
-        if isinstance(t, typing._GenericAlias):
-            stripped_args = tuple(_strip_extras(a) for a in t.__args__)
-            if stripped_args == t.__args__:
-                return t
-            return t.copy_with(stripped_args)
-        if hasattr(types, "GenericAlias") and isinstance(t, types.GenericAlias):
-            stripped_args = tuple(_strip_extras(a) for a in t.__args__)
-            if stripped_args == t.__args__:
-                return t
-            return types.GenericAlias(t.__origin__, stripped_args)
-        if hasattr(types, "UnionType") and isinstance(t, types.UnionType):
-            stripped_args = tuple(_strip_extras(a) for a in t.__args__)
-            if stripped_args == t.__args__:
-                return t
-            return functools.reduce(operator.or_, stripped_args)
-
-        return t
-
-    def get_type_hints(obj, globalns=None, localns=None, include_extras=False):
-        """Return type hints for an object.
-
-        This is often the same as obj.__annotations__, but it handles
-        forward references encoded as string literals, adds Optional[t] if a
-        default value equal to None is set and recursively replaces all
-        'Annotated[T, ...]', 'Required[T]' or 'NotRequired[T]' with 'T'
-        (unless 'include_extras=True').
-
-        The argument may be a module, class, method, or function. The annotations
-        are returned as a dictionary. For classes, annotations include also
-        inherited members.
-
-        TypeError is raised if the argument is not of a type that can contain
-        annotations, and an empty dictionary is returned if no annotations are
-        present.
-
-        BEWARE -- the behavior of globalns and localns is counterintuitive
-        (unless you are familiar with how eval() and exec() work).  The
-        search order is locals first, then globals.
-
-        - If no dict arguments are passed, an attempt is made to use the
-          globals from obj (or the respective module's globals for classes),
-          and these are also used as the locals.  If the object does not appear
-          to have globals, an empty dictionary is used.
-
-        - If one dict argument is passed, it is used for both globals and
-          locals.
-
-        - If two dict arguments are passed, they specify globals and
-          locals, respectively.
-        """
-        if hasattr(typing, "Annotated"):
-            hint = typing.get_type_hints(
-                obj, globalns=globalns, localns=localns, include_extras=True
-            )
-        else:
-            hint = typing.get_type_hints(obj, globalns=globalns, localns=localns)
-        if include_extras:
-            return hint
-        return {k: _strip_extras(t) for k, t in hint.items()}
-
-
-# Python 3.9+ has PEP 593 (Annotated)
-if hasattr(typing, 'Annotated'):
-    Annotated = typing.Annotated
-    # Not exported and not a public API, but needed for get_origin() and get_args()
-    # to work.
-    _AnnotatedAlias = typing._AnnotatedAlias
-# 3.7-3.8
-else:
-    class _AnnotatedAlias(typing._GenericAlias, _root=True):
-        """Runtime representation of an annotated type.
-
-        At its core 'Annotated[t, dec1, dec2, ...]' is an alias for the type 't'
-        with extra annotations. The alias behaves like a normal typing alias,
-        instantiating is the same as instantiating the underlying type, binding
-        it to types is also the same.
-        """
-        def __init__(self, origin, metadata):
-            if isinstance(origin, _AnnotatedAlias):
-                metadata = origin.__metadata__ + metadata
-                origin = origin.__origin__
-            super().__init__(origin, origin)
-            self.__metadata__ = metadata
-
-        def copy_with(self, params):
-            assert len(params) == 1
-            new_type = params[0]
-            return _AnnotatedAlias(new_type, self.__metadata__)
-
-        def __repr__(self):
-            return (f"typing_extensions.Annotated[{typing._type_repr(self.__origin__)}, "
-                    f"{', '.join(repr(a) for a in self.__metadata__)}]")
-
-        def __reduce__(self):
-            return operator.getitem, (
-                Annotated, (self.__origin__,) + self.__metadata__
-            )
-
-        def __eq__(self, other):
-            if not isinstance(other, _AnnotatedAlias):
-                return NotImplemented
-            if self.__origin__ != other.__origin__:
-                return False
-            return self.__metadata__ == other.__metadata__
-
-        def __hash__(self):
-            return hash((self.__origin__, self.__metadata__))
-
-    class Annotated:
-        """Add context specific metadata to a type.
-
-        Example: Annotated[int, runtime_check.Unsigned] indicates to the
-        hypothetical runtime_check module that this type is an unsigned int.
-        Every other consumer of this type can ignore this metadata and treat
-        this type as int.
-
-        The first argument to Annotated must be a valid type (and will be in
-        the __origin__ field), the remaining arguments are kept as a tuple in
-        the __extra__ field.
-
-        Details:
-
-        - It's an error to call `Annotated` with less than two arguments.
-        - Nested Annotated are flattened::
-
-            Annotated[Annotated[T, Ann1, Ann2], Ann3] == Annotated[T, Ann1, Ann2, Ann3]
-
-        - Instantiating an annotated type is equivalent to instantiating the
-        underlying type::
-
-            Annotated[C, Ann1](5) == C(5)
-
-        - Annotated can be used as a generic type alias::
-
-            Optimized = Annotated[T, runtime.Optimize()]
-            Optimized[int] == Annotated[int, runtime.Optimize()]
-
-            OptimizedList = Annotated[List[T], runtime.Optimize()]
-            OptimizedList[int] == Annotated[List[int], runtime.Optimize()]
-        """
-
-        __slots__ = ()
-
-        def __new__(cls, *args, **kwargs):
-            raise TypeError("Type Annotated cannot be instantiated.")
-
-        @typing._tp_cache
-        def __class_getitem__(cls, params):
-            if not isinstance(params, tuple) or len(params) < 2:
-                raise TypeError("Annotated[...] should be used "
-                                "with at least two arguments (a type and an "
-                                "annotation).")
-            allowed_special_forms = (ClassVar, Final)
-            if get_origin(params[0]) in allowed_special_forms:
-                origin = params[0]
-            else:
-                msg = "Annotated[t, ...]: t must be a type."
-                origin = typing._type_check(params[0], msg)
-            metadata = tuple(params[1:])
-            return _AnnotatedAlias(origin, metadata)
-
-        def __init_subclass__(cls, *args, **kwargs):
-            raise TypeError(
-                f"Cannot subclass {cls.__module__}.Annotated"
-            )
-
-# Python 3.8 has get_origin() and get_args() but those implementations aren't
-# Annotated-aware, so we can't use those. Python 3.9's versions don't support
-# ParamSpecArgs and ParamSpecKwargs, so only Python 3.10's versions will do.
-if sys.version_info[:2] >= (3, 10):
-    get_origin = typing.get_origin
-    get_args = typing.get_args
-# 3.7-3.9
-else:
-    try:
-        # 3.9+
-        from typing import _BaseGenericAlias
-    except ImportError:
-        _BaseGenericAlias = typing._GenericAlias
-    try:
-        # 3.9+
-        from typing import GenericAlias as _typing_GenericAlias
-    except ImportError:
-        _typing_GenericAlias = typing._GenericAlias
-
-    def get_origin(tp):
-        """Get the unsubscripted version of a type.
-
-        This supports generic types, Callable, Tuple, Union, Literal, Final, ClassVar
-        and Annotated. Return None for unsupported types. Examples::
-
-            get_origin(Literal[42]) is Literal
-            get_origin(int) is None
-            get_origin(ClassVar[int]) is ClassVar
-            get_origin(Generic) is Generic
-            get_origin(Generic[T]) is Generic
-            get_origin(Union[T, int]) is Union
-            get_origin(List[Tuple[T, T]][int]) == list
-            get_origin(P.args) is P
-        """
-        if isinstance(tp, _AnnotatedAlias):
-            return Annotated
-        if isinstance(tp, (typing._GenericAlias, _typing_GenericAlias, _BaseGenericAlias,
-                           ParamSpecArgs, ParamSpecKwargs)):
-            return tp.__origin__
-        if tp is typing.Generic:
-            return typing.Generic
-        return None
-
-    def get_args(tp):
-        """Get type arguments with all substitutions performed.
-
-        For unions, basic simplifications used by Union constructor are performed.
-        Examples::
-            get_args(Dict[str, int]) == (str, int)
-            get_args(int) == ()
-            get_args(Union[int, Union[T, int], str][int]) == (int, str)
-            get_args(Union[int, Tuple[T, int]][str]) == (int, Tuple[str, int])
-            get_args(Callable[[], T][int]) == ([], int)
-        """
-        if isinstance(tp, _AnnotatedAlias):
-            return (tp.__origin__,) + tp.__metadata__
-        if isinstance(tp, (typing._GenericAlias, _typing_GenericAlias)):
-            if getattr(tp, "_special", False):
-                return ()
-            res = tp.__args__
-            if get_origin(tp) is collections.abc.Callable and res[0] is not Ellipsis:
-                res = (list(res[:-1]), res[-1])
-            return res
-        return ()
-
-
-# 3.10+
-if hasattr(typing, 'TypeAlias'):
-    TypeAlias = typing.TypeAlias
-# 3.9
-elif sys.version_info[:2] >= (3, 9):
-    class _TypeAliasForm(typing._SpecialForm, _root=True):
-        def __repr__(self):
-            return 'typing_extensions.' + self._name
-
-    @_TypeAliasForm
-    def TypeAlias(self, parameters):
-        """Special marker indicating that an assignment should
-        be recognized as a proper type alias definition by type
-        checkers.
-
-        For example::
-
-            Predicate: TypeAlias = Callable[..., bool]
-
-        It's invalid when used anywhere except as in the example above.
-        """
-        raise TypeError(f"{self} is not subscriptable")
-# 3.7-3.8
-else:
-    class _TypeAliasForm(typing._SpecialForm, _root=True):
-        def __repr__(self):
-            return 'typing_extensions.' + self._name
-
-    TypeAlias = _TypeAliasForm('TypeAlias',
-                               doc="""Special marker indicating that an assignment should
-                               be recognized as a proper type alias definition by type
-                               checkers.
-
-                               For example::
-
-                                   Predicate: TypeAlias = Callable[..., bool]
-
-                               It's invalid when used anywhere except as in the example
-                               above.""")
-
-
-class _DefaultMixin:
-    """Mixin for TypeVarLike defaults."""
-
-    __slots__ = ()
-
-    def __init__(self, default):
-        if isinstance(default, (tuple, list)):
-            self.__default__ = tuple((typing._type_check(d, "Default must be a type")
-                                      for d in default))
-        elif default:
-            self.__default__ = typing._type_check(default, "Default must be a type")
-        else:
-            self.__default__ = None
-
-
-# Add default and infer_variance parameters from PEP 696 and 695
-class TypeVar(typing.TypeVar, _DefaultMixin, _root=True):
-    """Type variable."""
-
-    __module__ = 'typing'
-
-    def __init__(self, name, *constraints, bound=None,
-                 covariant=False, contravariant=False,
-                 default=None, infer_variance=False):
-        super().__init__(name, *constraints, bound=bound, covariant=covariant,
-                         contravariant=contravariant)
-        _DefaultMixin.__init__(self, default)
-        self.__infer_variance__ = infer_variance
-
-        # for pickling:
-        try:
-            def_mod = sys._getframe(1).f_globals.get('__name__', '__main__')
-        except (AttributeError, ValueError):
-            def_mod = None
-        if def_mod != 'typing_extensions':
-            self.__module__ = def_mod
-
-
-# Python 3.10+ has PEP 612
-if hasattr(typing, 'ParamSpecArgs'):
-    ParamSpecArgs = typing.ParamSpecArgs
-    ParamSpecKwargs = typing.ParamSpecKwargs
-# 3.7-3.9
-else:
-    class _Immutable:
-        """Mixin to indicate that object should not be copied."""
-        __slots__ = ()
-
-        def __copy__(self):
-            return self
-
-        def __deepcopy__(self, memo):
-            return self
-
-    class ParamSpecArgs(_Immutable):
-        """The args for a ParamSpec object.
-
-        Given a ParamSpec object P, P.args is an instance of ParamSpecArgs.
-
-        ParamSpecArgs objects have a reference back to their ParamSpec:
-
-        P.args.__origin__ is P
-
-        This type is meant for runtime introspection and has no special meaning to
-        static type checkers.
-        """
-        def __init__(self, origin):
-            self.__origin__ = origin
-
-        def __repr__(self):
-            return f"{self.__origin__.__name__}.args"
-
-        def __eq__(self, other):
-            if not isinstance(other, ParamSpecArgs):
-                return NotImplemented
-            return self.__origin__ == other.__origin__
-
-    class ParamSpecKwargs(_Immutable):
-        """The kwargs for a ParamSpec object.
-
-        Given a ParamSpec object P, P.kwargs is an instance of ParamSpecKwargs.
-
-        ParamSpecKwargs objects have a reference back to their ParamSpec:
-
-        P.kwargs.__origin__ is P
-
-        This type is meant for runtime introspection and has no special meaning to
-        static type checkers.
-        """
-        def __init__(self, origin):
-            self.__origin__ = origin
-
-        def __repr__(self):
-            return f"{self.__origin__.__name__}.kwargs"
-
-        def __eq__(self, other):
-            if not isinstance(other, ParamSpecKwargs):
-                return NotImplemented
-            return self.__origin__ == other.__origin__
-
-# 3.10+
-if hasattr(typing, 'ParamSpec'):
-
-    # Add default Parameter - PEP 696
-    class ParamSpec(typing.ParamSpec, _DefaultMixin, _root=True):
-        """Parameter specification variable."""
-
-        __module__ = 'typing'
-
-        def __init__(self, name, *, bound=None, covariant=False, contravariant=False,
-                     default=None):
-            super().__init__(name, bound=bound, covariant=covariant,
-                             contravariant=contravariant)
-            _DefaultMixin.__init__(self, default)
-
-            # for pickling:
-            try:
-                def_mod = sys._getframe(1).f_globals.get('__name__', '__main__')
-            except (AttributeError, ValueError):
-                def_mod = None
-            if def_mod != 'typing_extensions':
-                self.__module__ = def_mod
-
-# 3.7-3.9
-else:
-
-    # Inherits from list as a workaround for Callable checks in Python < 3.9.2.
-    class ParamSpec(list, _DefaultMixin):
-        """Parameter specification variable.
-
-        Usage::
-
-           P = ParamSpec('P')
-
-        Parameter specification variables exist primarily for the benefit of static
-        type checkers.  They are used to forward the parameter types of one
-        callable to another callable, a pattern commonly found in higher order
-        functions and decorators.  They are only valid when used in ``Concatenate``,
-        or s the first argument to ``Callable``. In Python 3.10 and higher,
-        they are also supported in user-defined Generics at runtime.
-        See class Generic for more information on generic types.  An
-        example for annotating a decorator::
-
-           T = TypeVar('T')
-           P = ParamSpec('P')
-
-           def add_logging(f: Callable[P, T]) -> Callable[P, T]:
-               '''A type-safe decorator to add logging to a function.'''
-               def inner(*args: P.args, **kwargs: P.kwargs) -> T:
-                   logging.info(f'{f.__name__} was called')
-                   return f(*args, **kwargs)
-               return inner
-
-           @add_logging
-           def add_two(x: float, y: float) -> float:
-               '''Add two numbers together.'''
-               return x + y
-
-        Parameter specification variables defined with covariant=True or
-        contravariant=True can be used to declare covariant or contravariant
-        generic types.  These keyword arguments are valid, but their actual semantics
-        are yet to be decided.  See PEP 612 for details.
-
-        Parameter specification variables can be introspected. e.g.:
-
-           P.__name__ == 'T'
-           P.__bound__ == None
-           P.__covariant__ == False
-           P.__contravariant__ == False
-
-        Note that only parameter specification variables defined in global scope can
-        be pickled.
-        """
-
-        # Trick Generic __parameters__.
-        __class__ = typing.TypeVar
-
-        @property
-        def args(self):
-            return ParamSpecArgs(self)
-
-        @property
-        def kwargs(self):
-            return ParamSpecKwargs(self)
-
-        def __init__(self, name, *, bound=None, covariant=False, contravariant=False,
-                     default=None):
-            super().__init__([self])
-            self.__name__ = name
-            self.__covariant__ = bool(covariant)
-            self.__contravariant__ = bool(contravariant)
-            if bound:
-                self.__bound__ = typing._type_check(bound, 'Bound must be a type.')
-            else:
-                self.__bound__ = None
-            _DefaultMixin.__init__(self, default)
-
-            # for pickling:
-            try:
-                def_mod = sys._getframe(1).f_globals.get('__name__', '__main__')
-            except (AttributeError, ValueError):
-                def_mod = None
-            if def_mod != 'typing_extensions':
-                self.__module__ = def_mod
-
-        def __repr__(self):
-            if self.__covariant__:
-                prefix = '+'
-            elif self.__contravariant__:
-                prefix = '-'
-            else:
-                prefix = '~'
-            return prefix + self.__name__
-
-        def __hash__(self):
-            return object.__hash__(self)
-
-        def __eq__(self, other):
-            return self is other
-
-        def __reduce__(self):
-            return self.__name__
-
-        # Hack to get typing._type_check to pass.
-        def __call__(self, *args, **kwargs):
-            pass
-
-
-# 3.7-3.9
-if not hasattr(typing, 'Concatenate'):
-    # Inherits from list as a workaround for Callable checks in Python < 3.9.2.
-    class _ConcatenateGenericAlias(list):
-
-        # Trick Generic into looking into this for __parameters__.
-        __class__ = typing._GenericAlias
-
-        # Flag in 3.8.
-        _special = False
-
-        def __init__(self, origin, args):
-            super().__init__(args)
-            self.__origin__ = origin
-            self.__args__ = args
-
-        def __repr__(self):
-            _type_repr = typing._type_repr
-            return (f'{_type_repr(self.__origin__)}'
-                    f'[{", ".join(_type_repr(arg) for arg in self.__args__)}]')
-
-        def __hash__(self):
-            return hash((self.__origin__, self.__args__))
-
-        # Hack to get typing._type_check to pass in Generic.
-        def __call__(self, *args, **kwargs):
-            pass
-
-        @property
-        def __parameters__(self):
-            return tuple(
-                tp for tp in self.__args__ if isinstance(tp, (typing.TypeVar, ParamSpec))
-            )
-
-
-# 3.7-3.9
-@typing._tp_cache
-def _concatenate_getitem(self, parameters):
-    if parameters == ():
-        raise TypeError("Cannot take a Concatenate of no types.")
-    if not isinstance(parameters, tuple):
-        parameters = (parameters,)
-    if not isinstance(parameters[-1], ParamSpec):
-        raise TypeError("The last parameter to Concatenate should be a "
-                        "ParamSpec variable.")
-    msg = "Concatenate[arg, ...]: each arg must be a type."
-    parameters = tuple(typing._type_check(p, msg) for p in parameters)
-    return _ConcatenateGenericAlias(self, parameters)
-
-
-# 3.10+
-if hasattr(typing, 'Concatenate'):
-    Concatenate = typing.Concatenate
-    _ConcatenateGenericAlias = typing._ConcatenateGenericAlias # noqa
-# 3.9
-elif sys.version_info[:2] >= (3, 9):
-    @_TypeAliasForm
-    def Concatenate(self, parameters):
-        """Used in conjunction with ``ParamSpec`` and ``Callable`` to represent a
-        higher order function which adds, removes or transforms parameters of a
-        callable.
-
-        For example::
-
-           Callable[Concatenate[int, P], int]
-
-        See PEP 612 for detailed information.
-        """
-        return _concatenate_getitem(self, parameters)
-# 3.7-8
-else:
-    class _ConcatenateForm(typing._SpecialForm, _root=True):
-        def __repr__(self):
-            return 'typing_extensions.' + self._name
-
-        def __getitem__(self, parameters):
-            return _concatenate_getitem(self, parameters)
-
-    Concatenate = _ConcatenateForm(
-        'Concatenate',
-        doc="""Used in conjunction with ``ParamSpec`` and ``Callable`` to represent a
-        higher order function which adds, removes or transforms parameters of a
-        callable.
-
-        For example::
-
-           Callable[Concatenate[int, P], int]
-
-        See PEP 612 for detailed information.
-        """)
-
-# 3.10+
-if hasattr(typing, 'TypeGuard'):
-    TypeGuard = typing.TypeGuard
-# 3.9
-elif sys.version_info[:2] >= (3, 9):
-    class _TypeGuardForm(typing._SpecialForm, _root=True):
-        def __repr__(self):
-            return 'typing_extensions.' + self._name
-
-    @_TypeGuardForm
-    def TypeGuard(self, parameters):
-        """Special typing form used to annotate the return type of a user-defined
-        type guard function.  ``TypeGuard`` only accepts a single type argument.
-        At runtime, functions marked this way should return a boolean.
-
-        ``TypeGuard`` aims to benefit *type narrowing* -- a technique used by static
-        type checkers to determine a more precise type of an expression within a
-        program's code flow.  Usually type narrowing is done by analyzing
-        conditional code flow and applying the narrowing to a block of code.  The
-        conditional expression here is sometimes referred to as a "type guard".
-
-        Sometimes it would be convenient to use a user-defined boolean function
-        as a type guard.  Such a function should use ``TypeGuard[...]`` as its
-        return type to alert static type checkers to this intention.
-
-        Using  ``-> TypeGuard`` tells the static type checker that for a given
-        function:
-
-        1. The return value is a boolean.
-        2. If the return value is ``True``, the type of its argument
-        is the type inside ``TypeGuard``.
-
-        For example::
-
-            def is_str(val: Union[str, float]):
-                # "isinstance" type guard
-                if isinstance(val, str):
-                    # Type of ``val`` is narrowed to ``str``
-                    ...
-                else:
-                    # Else, type of ``val`` is narrowed to ``float``.
-                    ...
-
-        Strict type narrowing is not enforced -- ``TypeB`` need not be a narrower
-        form of ``TypeA`` (it can even be a wider form) and this may lead to
-        type-unsafe results.  The main reason is to allow for things like
-        narrowing ``List[object]`` to ``List[str]`` even though the latter is not
-        a subtype of the former, since ``List`` is invariant.  The responsibility of
-        writing type-safe type guards is left to the user.
-
-        ``TypeGuard`` also works with type variables.  For more information, see
-        PEP 647 (User-Defined Type Guards).
-        """
-        item = typing._type_check(parameters, f'{self} accepts only a single type.')
-        return typing._GenericAlias(self, (item,))
-# 3.7-3.8
-else:
-    class _TypeGuardForm(typing._SpecialForm, _root=True):
-
-        def __repr__(self):
-            return 'typing_extensions.' + self._name
-
-        def __getitem__(self, parameters):
-            item = typing._type_check(parameters,
-                                      f'{self._name} accepts only a single type')
-            return typing._GenericAlias(self, (item,))
-
-    TypeGuard = _TypeGuardForm(
-        'TypeGuard',
-        doc="""Special typing form used to annotate the return type of a user-defined
-        type guard function.  ``TypeGuard`` only accepts a single type argument.
-        At runtime, functions marked this way should return a boolean.
-
-        ``TypeGuard`` aims to benefit *type narrowing* -- a technique used by static
-        type checkers to determine a more precise type of an expression within a
-        program's code flow.  Usually type narrowing is done by analyzing
-        conditional code flow and applying the narrowing to a block of code.  The
-        conditional expression here is sometimes referred to as a "type guard".
-
-        Sometimes it would be convenient to use a user-defined boolean function
-        as a type guard.  Such a function should use ``TypeGuard[...]`` as its
-        return type to alert static type checkers to this intention.
-
-        Using  ``-> TypeGuard`` tells the static type checker that for a given
-        function:
-
-        1. The return value is a boolean.
-        2. If the return value is ``True``, the type of its argument
-        is the type inside ``TypeGuard``.
-
-        For example::
-
-            def is_str(val: Union[str, float]):
-                # "isinstance" type guard
-                if isinstance(val, str):
-                    # Type of ``val`` is narrowed to ``str``
-                    ...
-                else:
-                    # Else, type of ``val`` is narrowed to ``float``.
-                    ...
-
-        Strict type narrowing is not enforced -- ``TypeB`` need not be a narrower
-        form of ``TypeA`` (it can even be a wider form) and this may lead to
-        type-unsafe results.  The main reason is to allow for things like
-        narrowing ``List[object]`` to ``List[str]`` even though the latter is not
-        a subtype of the former, since ``List`` is invariant.  The responsibility of
-        writing type-safe type guards is left to the user.
-
-        ``TypeGuard`` also works with type variables.  For more information, see
-        PEP 647 (User-Defined Type Guards).
-        """)
-
-
-# Vendored from cpython typing._SpecialFrom
-class _SpecialForm(typing._Final, _root=True):
-    __slots__ = ('_name', '__doc__', '_getitem')
-
-    def __init__(self, getitem):
-        self._getitem = getitem
-        self._name = getitem.__name__
-        self.__doc__ = getitem.__doc__
-
-    def __getattr__(self, item):
-        if item in {'__name__', '__qualname__'}:
-            return self._name
-
-        raise AttributeError(item)
-
-    def __mro_entries__(self, bases):
-        raise TypeError(f"Cannot subclass {self!r}")
-
-    def __repr__(self):
-        return f'typing_extensions.{self._name}'
-
-    def __reduce__(self):
-        return self._name
-
-    def __call__(self, *args, **kwds):
-        raise TypeError(f"Cannot instantiate {self!r}")
-
-    def __or__(self, other):
-        return typing.Union[self, other]
-
-    def __ror__(self, other):
-        return typing.Union[other, self]
-
-    def __instancecheck__(self, obj):
-        raise TypeError(f"{self} cannot be used with isinstance()")
-
-    def __subclasscheck__(self, cls):
-        raise TypeError(f"{self} cannot be used with issubclass()")
-
-    @typing._tp_cache
-    def __getitem__(self, parameters):
-        return self._getitem(self, parameters)
-
-
-if hasattr(typing, "LiteralString"):
-    LiteralString = typing.LiteralString
-else:
-    @_SpecialForm
-    def LiteralString(self, params):
-        """Represents an arbitrary literal string.
-
-        Example::
-
-          from typing_extensions import LiteralString
-
-          def query(sql: LiteralString) -> ...:
-              ...
-
-          query("SELECT * FROM table")  # ok
-          query(f"SELECT * FROM {input()}")  # not ok
-
-        See PEP 675 for details.
-
-        """
-        raise TypeError(f"{self} is not subscriptable")
-
-
-if hasattr(typing, "Self"):
-    Self = typing.Self
-else:
-    @_SpecialForm
-    def Self(self, params):
-        """Used to spell the type of "self" in classes.
-
-        Example::
-
-          from typing import Self
-
-          class ReturnsSelf:
-              def parse(self, data: bytes) -> Self:
-                  ...
-                  return self
-
-        """
-
-        raise TypeError(f"{self} is not subscriptable")
-
-
-if hasattr(typing, "Never"):
-    Never = typing.Never
-else:
-    @_SpecialForm
-    def Never(self, params):
-        """The bottom type, a type that has no members.
-
-        This can be used to define a function that should never be
-        called, or a function that never returns::
-
-            from typing_extensions import Never
-
-            def never_call_me(arg: Never) -> None:
-                pass
-
-            def int_or_str(arg: int | str) -> None:
-                never_call_me(arg)  # type checker error
-                match arg:
-                    case int():
-                        print("It's an int")
-                    case str():
-                        print("It's a str")
-                    case _:
-                        never_call_me(arg)  # ok, arg is of type Never
-
-        """
-
-        raise TypeError(f"{self} is not subscriptable")
-
-
-if hasattr(typing, 'Required'):
-    Required = typing.Required
-    NotRequired = typing.NotRequired
-elif sys.version_info[:2] >= (3, 9):
-    class _ExtensionsSpecialForm(typing._SpecialForm, _root=True):
-        def __repr__(self):
-            return 'typing_extensions.' + self._name
-
-    @_ExtensionsSpecialForm
-    def Required(self, parameters):
-        """A special typing construct to mark a key of a total=False TypedDict
-        as required. For example:
-
-            class Movie(TypedDict, total=False):
-                title: Required[str]
-                year: int
-
-            m = Movie(
-                title='The Matrix',  # typechecker error if key is omitted
-                year=1999,
-            )
-
-        There is no runtime checking that a required key is actually provided
-        when instantiating a related TypedDict.
-        """
-        item = typing._type_check(parameters, f'{self._name} accepts only a single type.')
-        return typing._GenericAlias(self, (item,))
-
-    @_ExtensionsSpecialForm
-    def NotRequired(self, parameters):
-        """A special typing construct to mark a key of a TypedDict as
-        potentially missing. For example:
-
-            class Movie(TypedDict):
-                title: str
-                year: NotRequired[int]
-
-            m = Movie(
-                title='The Matrix',  # typechecker error if key is omitted
-                year=1999,
-            )
-        """
-        item = typing._type_check(parameters, f'{self._name} accepts only a single type.')
-        return typing._GenericAlias(self, (item,))
-
-else:
-    class _RequiredForm(typing._SpecialForm, _root=True):
-        def __repr__(self):
-            return 'typing_extensions.' + self._name
-
-        def __getitem__(self, parameters):
-            item = typing._type_check(parameters,
-                                      f'{self._name} accepts only a single type.')
-            return typing._GenericAlias(self, (item,))
-
-    Required = _RequiredForm(
-        'Required',
-        doc="""A special typing construct to mark a key of a total=False TypedDict
-        as required. For example:
-
-            class Movie(TypedDict, total=False):
-                title: Required[str]
-                year: int
-
-            m = Movie(
-                title='The Matrix',  # typechecker error if key is omitted
-                year=1999,
-            )
-
-        There is no runtime checking that a required key is actually provided
-        when instantiating a related TypedDict.
-        """)
-    NotRequired = _RequiredForm(
-        'NotRequired',
-        doc="""A special typing construct to mark a key of a TypedDict as
-        potentially missing. For example:
-
-            class Movie(TypedDict):
-                title: str
-                year: NotRequired[int]
-
-            m = Movie(
-                title='The Matrix',  # typechecker error if key is omitted
-                year=1999,
-            )
-        """)
-
-
-if hasattr(typing, "Unpack"):  # 3.11+
-    Unpack = typing.Unpack
-elif sys.version_info[:2] >= (3, 9):
-    class _UnpackSpecialForm(typing._SpecialForm, _root=True):
-        def __repr__(self):
-            return 'typing_extensions.' + self._name
-
-    class _UnpackAlias(typing._GenericAlias, _root=True):
-        __class__ = typing.TypeVar
-
-    @_UnpackSpecialForm
-    def Unpack(self, parameters):
-        """A special typing construct to unpack a variadic type. For example:
-
-            Shape = TypeVarTuple('Shape')
-            Batch = NewType('Batch', int)
-
-            def add_batch_axis(
-                x: Array[Unpack[Shape]]
-            ) -> Array[Batch, Unpack[Shape]]: ...
-
-        """
-        item = typing._type_check(parameters, f'{self._name} accepts only a single type.')
-        return _UnpackAlias(self, (item,))
-
-    def _is_unpack(obj):
-        return isinstance(obj, _UnpackAlias)
-
-else:
-    class _UnpackAlias(typing._GenericAlias, _root=True):
-        __class__ = typing.TypeVar
-
-    class _UnpackForm(typing._SpecialForm, _root=True):
-        def __repr__(self):
-            return 'typing_extensions.' + self._name
-
-        def __getitem__(self, parameters):
-            item = typing._type_check(parameters,
-                                      f'{self._name} accepts only a single type.')
-            return _UnpackAlias(self, (item,))
-
-    Unpack = _UnpackForm(
-        'Unpack',
-        doc="""A special typing construct to unpack a variadic type. For example:
-
-            Shape = TypeVarTuple('Shape')
-            Batch = NewType('Batch', int)
-
-            def add_batch_axis(
-                x: Array[Unpack[Shape]]
-            ) -> Array[Batch, Unpack[Shape]]: ...
-
-        """)
-
-    def _is_unpack(obj):
-        return isinstance(obj, _UnpackAlias)
-
-
-if hasattr(typing, "TypeVarTuple"):  # 3.11+
-
-    # Add default Parameter - PEP 696
-    class TypeVarTuple(typing.TypeVarTuple, _DefaultMixin, _root=True):
-        """Type variable tuple."""
-
-        def __init__(self, name, *, default=None):
-            super().__init__(name)
-            _DefaultMixin.__init__(self, default)
-
-            # for pickling:
-            try:
-                def_mod = sys._getframe(1).f_globals.get('__name__', '__main__')
-            except (AttributeError, ValueError):
-                def_mod = None
-            if def_mod != 'typing_extensions':
-                self.__module__ = def_mod
-
-else:
-    class TypeVarTuple(_DefaultMixin):
-        """Type variable tuple.
-
-        Usage::
-
-            Ts = TypeVarTuple('Ts')
-
-        In the same way that a normal type variable is a stand-in for a single
-        type such as ``int``, a type variable *tuple* is a stand-in for a *tuple*
-        type such as ``Tuple[int, str]``.
-
-        Type variable tuples can be used in ``Generic`` declarations.
-        Consider the following example::
-
-            class Array(Generic[*Ts]): ...
-
-        The ``Ts`` type variable tuple here behaves like ``tuple[T1, T2]``,
-        where ``T1`` and ``T2`` are type variables. To use these type variables
-        as type parameters of ``Array``, we must *unpack* the type variable tuple using
-        the star operator: ``*Ts``. The signature of ``Array`` then behaves
-        as if we had simply written ``class Array(Generic[T1, T2]): ...``.
-        In contrast to ``Generic[T1, T2]``, however, ``Generic[*Shape]`` allows
-        us to parameterise the class with an *arbitrary* number of type parameters.
-
-        Type variable tuples can be used anywhere a normal ``TypeVar`` can.
-        This includes class definitions, as shown above, as well as function
-        signatures and variable annotations::
-
-            class Array(Generic[*Ts]):
-
-                def __init__(self, shape: Tuple[*Ts]):
-                    self._shape: Tuple[*Ts] = shape
-
-                def get_shape(self) -> Tuple[*Ts]:
-                    return self._shape
-
-            shape = (Height(480), Width(640))
-            x: Array[Height, Width] = Array(shape)
-            y = abs(x)  # Inferred type is Array[Height, Width]
-            z = x + x   #        ...    is Array[Height, Width]
-            x.get_shape()  #     ...    is tuple[Height, Width]
-
-        """
-
-        # Trick Generic __parameters__.
-        __class__ = typing.TypeVar
-
-        def __iter__(self):
-            yield self.__unpacked__
-
-        def __init__(self, name, *, default=None):
-            self.__name__ = name
-            _DefaultMixin.__init__(self, default)
-
-            # for pickling:
-            try:
-                def_mod = sys._getframe(1).f_globals.get('__name__', '__main__')
-            except (AttributeError, ValueError):
-                def_mod = None
-            if def_mod != 'typing_extensions':
-                self.__module__ = def_mod
-
-            self.__unpacked__ = Unpack[self]
-
-        def __repr__(self):
-            return self.__name__
-
-        def __hash__(self):
-            return object.__hash__(self)
-
-        def __eq__(self, other):
-            return self is other
-
-        def __reduce__(self):
-            return self.__name__
-
-        def __init_subclass__(self, *args, **kwds):
-            if '_root' not in kwds:
-                raise TypeError("Cannot subclass special typing classes")
-
-
-if hasattr(typing, "reveal_type"):
-    reveal_type = typing.reveal_type
-else:
-    def reveal_type(__obj: T) -> T:
-        """Reveal the inferred type of a variable.
-
-        When a static type checker encounters a call to ``reveal_type()``,
-        it will emit the inferred type of the argument::
-
-            x: int = 1
-            reveal_type(x)
-
-        Running a static type checker (e.g., ``mypy``) on this example
-        will produce output similar to 'Revealed type is "builtins.int"'.
-
-        At runtime, the function prints the runtime type of the
-        argument and returns it unchanged.
-
-        """
-        print(f"Runtime type is {type(__obj).__name__!r}", file=sys.stderr)
-        return __obj
-
-
-if hasattr(typing, "assert_never"):
-    assert_never = typing.assert_never
-else:
-    def assert_never(__arg: Never) -> Never:
-        """Assert to the type checker that a line of code is unreachable.
-
-        Example::
-
-            def int_or_str(arg: int | str) -> None:
-                match arg:
-                    case int():
-                        print("It's an int")
-                    case str():
-                        print("It's a str")
-                    case _:
-                        assert_never(arg)
-
-        If a type checker finds that a call to assert_never() is
-        reachable, it will emit an error.
-
-        At runtime, this throws an exception when called.
-
-        """
-        raise AssertionError("Expected code to be unreachable")
-
-
-if hasattr(typing, 'dataclass_transform'):
-    dataclass_transform = typing.dataclass_transform
-else:
-    def dataclass_transform(
-        *,
-        eq_default: bool = True,
-        order_default: bool = False,
-        kw_only_default: bool = False,
-        field_specifiers: typing.Tuple[
-            typing.Union[typing.Type[typing.Any], typing.Callable[..., typing.Any]],
-            ...
-        ] = (),
-        **kwargs: typing.Any,
-    ) -> typing.Callable[[T], T]:
-        """Decorator that marks a function, class, or metaclass as providing
-        dataclass-like behavior.
-
-        Example:
-
-            from typing_extensions import dataclass_transform
-
-            _T = TypeVar("_T")
-
-            # Used on a decorator function
-            @dataclass_transform()
-            def create_model(cls: type[_T]) -> type[_T]:
-                ...
-                return cls
-
-            @create_model
-            class CustomerModel:
-                id: int
-                name: str
-
-            # Used on a base class
-            @dataclass_transform()
-            class ModelBase: ...
-
-            class CustomerModel(ModelBase):
-                id: int
-                name: str
-
-            # Used on a metaclass
-            @dataclass_transform()
-            class ModelMeta(type): ...
-
-            class ModelBase(metaclass=ModelMeta): ...
-
-            class CustomerModel(ModelBase):
-                id: int
-                name: str
-
-        Each of the ``CustomerModel`` classes defined in this example will now
-        behave similarly to a dataclass created with the ``@dataclasses.dataclass``
-        decorator. For example, the type checker will synthesize an ``__init__``
-        method.
-
-        The arguments to this decorator can be used to customize this behavior:
-        - ``eq_default`` indicates whether the ``eq`` parameter is assumed to be
-          True or False if it is omitted by the caller.
-        - ``order_default`` indicates whether the ``order`` parameter is
-          assumed to be True or False if it is omitted by the caller.
-        - ``kw_only_default`` indicates whether the ``kw_only`` parameter is
-          assumed to be True or False if it is omitted by the caller.
-        - ``field_specifiers`` specifies a static list of supported classes
-          or functions that describe fields, similar to ``dataclasses.field()``.
-
-        At runtime, this decorator records its arguments in the
-        ``__dataclass_transform__`` attribute on the decorated object.
-
-        See PEP 681 for details.
-
-        """
-        def decorator(cls_or_fn):
-            cls_or_fn.__dataclass_transform__ = {
-                "eq_default": eq_default,
-                "order_default": order_default,
-                "kw_only_default": kw_only_default,
-                "field_specifiers": field_specifiers,
-                "kwargs": kwargs,
-            }
-            return cls_or_fn
-        return decorator
-
-
-if hasattr(typing, "override"):
-    override = typing.override
-else:
-    _F = typing.TypeVar("_F", bound=typing.Callable[..., typing.Any])
-
-    def override(__arg: _F) -> _F:
-        """Indicate that a method is intended to override a method in a base class.
-
-        Usage:
-
-            class Base:
-                def method(self) -> None: ...
-                    pass
-
-            class Child(Base):
-                @override
-                def method(self) -> None:
-                    super().method()
-
-        When this decorator is applied to a method, the type checker will
-        validate that it overrides a method with the same name on a base class.
-        This helps prevent bugs that may occur when a base class is changed
-        without an equivalent change to a child class.
-
-        See PEP 698 for details.
-
-        """
-        return __arg
-
-
-# We have to do some monkey patching to deal with the dual nature of
-# Unpack/TypeVarTuple:
-# - We want Unpack to be a kind of TypeVar so it gets accepted in
-#   Generic[Unpack[Ts]]
-# - We want it to *not* be treated as a TypeVar for the purposes of
-#   counting generic parameters, so that when we subscript a generic,
-#   the runtime doesn't try to substitute the Unpack with the subscripted type.
-if not hasattr(typing, "TypeVarTuple"):
-    typing._collect_type_vars = _collect_type_vars
-    typing._check_generic = _check_generic
-
-
-# Backport typing.NamedTuple as it exists in Python 3.11.
-# In 3.11, the ability to define generic `NamedTuple`s was supported.
-# This was explicitly disallowed in 3.9-3.10, and only half-worked in <=3.8.
-if sys.version_info >= (3, 11):
-    NamedTuple = typing.NamedTuple
-else:
-    def _caller():
-        try:
-            return sys._getframe(2).f_globals.get('__name__', '__main__')
-        except (AttributeError, ValueError):  # For platforms without _getframe()
-            return None
-
-    def _make_nmtuple(name, types, module, defaults=()):
-        fields = [n for n, t in types]
-        annotations = {n: typing._type_check(t, f"field {n} annotation must be a type")
-                       for n, t in types}
-        nm_tpl = collections.namedtuple(name, fields,
-                                        defaults=defaults, module=module)
-        nm_tpl.__annotations__ = nm_tpl.__new__.__annotations__ = annotations
-        # The `_field_types` attribute was removed in 3.9;
-        # in earlier versions, it is the same as the `__annotations__` attribute
-        if sys.version_info < (3, 9):
-            nm_tpl._field_types = annotations
-        return nm_tpl
-
-    _prohibited_namedtuple_fields = typing._prohibited
-    _special_namedtuple_fields = frozenset({'__module__', '__name__', '__annotations__'})
-
-    class _NamedTupleMeta(type):
-        def __new__(cls, typename, bases, ns):
-            assert _NamedTuple in bases
-            for base in bases:
-                if base is not _NamedTuple and base is not typing.Generic:
-                    raise TypeError(
-                        'can only inherit from a NamedTuple type and Generic')
-            bases = tuple(tuple if base is _NamedTuple else base for base in bases)
-            types = ns.get('__annotations__', {})
-            default_names = []
-            for field_name in types:
-                if field_name in ns:
-                    default_names.append(field_name)
-                elif default_names:
-                    raise TypeError(f"Non-default namedtuple field {field_name} "
-                                    f"cannot follow default field"
-                                    f"{'s' if len(default_names) > 1 else ''} "
-                                    f"{', '.join(default_names)}")
-            nm_tpl = _make_nmtuple(
-                typename, types.items(),
-                defaults=[ns[n] for n in default_names],
-                module=ns['__module__']
-            )
-            nm_tpl.__bases__ = bases
-            if typing.Generic in bases:
-                class_getitem = typing.Generic.__class_getitem__.__func__
-                nm_tpl.__class_getitem__ = classmethod(class_getitem)
-            # update from user namespace without overriding special namedtuple attributes
-            for key in ns:
-                if key in _prohibited_namedtuple_fields:
-                    raise AttributeError("Cannot overwrite NamedTuple attribute " + key)
-                elif key not in _special_namedtuple_fields and key not in nm_tpl._fields:
-                    setattr(nm_tpl, key, ns[key])
-            if typing.Generic in bases:
-                nm_tpl.__init_subclass__()
-            return nm_tpl
-
-    def NamedTuple(__typename, __fields=None, **kwargs):
-        if __fields is None:
-            __fields = kwargs.items()
-        elif kwargs:
-            raise TypeError("Either list of fields or keywords"
-                            " can be provided to NamedTuple, not both")
-        return _make_nmtuple(__typename, __fields, module=_caller())
-
-    NamedTuple.__doc__ = typing.NamedTuple.__doc__
-    _NamedTuple = type.__new__(_NamedTupleMeta, 'NamedTuple', (), {})
-
-    # On 3.8+, alter the signature so that it matches typing.NamedTuple.
-    # The signature of typing.NamedTuple on >=3.8 is invalid syntax in Python 3.7,
-    # so just leave the signature as it is on 3.7.
-    if sys.version_info >= (3, 8):
-        NamedTuple.__text_signature__ = '(typename, fields=None, /, **kwargs)'
-
-    def _namedtuple_mro_entries(bases):
-        assert NamedTuple in bases
-        return (_NamedTuple,)
-
-    NamedTuple.__mro_entries__ = _namedtuple_mro_entries
diff --git a/spaces/pknez/face-swap-docker/roop/processors/frame/core.py b/spaces/pknez/face-swap-docker/roop/processors/frame/core.py
deleted file mode 100644
index 0f3897a1d0e5186e8d229c34ce00e2b12f43101a..0000000000000000000000000000000000000000
--- a/spaces/pknez/face-swap-docker/roop/processors/frame/core.py
+++ /dev/null
@@ -1,100 +0,0 @@
-import os
-import sys
-import importlib
-import psutil
-from concurrent.futures import ThreadPoolExecutor, as_completed
-from queue import Queue
-from types import ModuleType
-from typing import Any, List, Callable
-from roop.typing import Face
-from tqdm import tqdm
-
-import roop
-
-FRAME_PROCESSORS_MODULES: List[ModuleType] = []
-FRAME_PROCESSORS_INTERFACE = [
-    'pre_check',
-    'pre_start',
-    'process_frame',
-    'process_frames',
-    'process_image',
-    'process_video',
-    'post_process'
-]
-
-
-def load_frame_processor_module(frame_processor: str) -> Any:
-    try:
-        module_name = f'roop.processors.frame.{frame_processor}'
-        print(f'Loading {module_name}')
-        frame_processor_module = importlib.import_module(module_name)
-        for method_name in FRAME_PROCESSORS_INTERFACE:
-            if not hasattr(frame_processor_module, method_name):
-                raise NotImplementedError
-    except ModuleNotFoundError:
-        sys.exit(f'Frame processor {frame_processor} not found.')
-    except NotImplementedError:
-        sys.exit(f'Frame processor {frame_processor} not implemented correctly.')
-    return frame_processor_module
-
-
-def get_frame_processors_modules(frame_processors: List[str]) -> List[ModuleType]:
-    global FRAME_PROCESSORS_MODULES
-
-    if not FRAME_PROCESSORS_MODULES:
-        for frame_processor in frame_processors:
-            frame_processor_module = load_frame_processor_module(frame_processor)
-            FRAME_PROCESSORS_MODULES.append(frame_processor_module)
-    return FRAME_PROCESSORS_MODULES
-
-
-def multi_process_frame(is_batch: bool, source_face: Face, target_face: Face, temp_frame_paths: List[str], process_frames: Callable[[str, List[str], Any], None], update: Callable[[], None]) -> None:
-    with ThreadPoolExecutor(max_workers=roop.globals.execution_threads) as executor:
-        futures = []
-        queue = create_queue(temp_frame_paths)
-        queue_per_future = max(len(temp_frame_paths) // roop.globals.execution_threads, 1)
-        while not queue.empty():
-            future = executor.submit(process_frames, is_batch, source_face, target_face, pick_queue(queue, queue_per_future), update)
-            futures.append(future)
-        for future in as_completed(futures):
-            future.result()
-
-
-def create_queue(temp_frame_paths: List[str]) -> Queue[str]:
-    queue: Queue[str] = Queue()
-    for frame_path in temp_frame_paths:
-        queue.put(frame_path)
-    return queue
-
-
-def pick_queue(queue: Queue[str], queue_per_future: int) -> List[str]:
-    queues = []
-    for _ in range(queue_per_future):
-        if not queue.empty():
-            queues.append(queue.get())
-    return queues
-
-def process_batch(source_face: Face, target_face: Face, frame_paths: list[str], process_frames: Callable[[str, List[str], Any], None]) -> None:
-    progress_bar_format = '{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, {rate_fmt}{postfix}]'
-    total = len(frame_paths)
-    with tqdm(total=total, desc='Processing', unit='frame', dynamic_ncols=True, bar_format=progress_bar_format) as progress:
-        multi_process_frame(True, source_face, target_face, frame_paths, process_frames, lambda: update_progress(progress))
-
-
-def process_video(source_face: Face, target_face: Face, frame_paths: list[str], process_frames: Callable[[str, List[str], Any], None]) -> None:
-    progress_bar_format = '{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, {rate_fmt}{postfix}]'
-    total = len(frame_paths)
-    with tqdm(total=total, desc='Processing', unit='frame', dynamic_ncols=True, bar_format=progress_bar_format) as progress:
-        multi_process_frame(False, source_face, target_face, frame_paths, process_frames, lambda: update_progress(progress))
-
-
-def update_progress(progress: Any = None) -> None:
-    process = psutil.Process(os.getpid())
-    memory_usage = process.memory_info().rss / 1024 / 1024 / 1024
-    progress.set_postfix({
-        'memory_usage': '{:.2f}'.format(memory_usage).zfill(5) + 'GB',
-        'execution_providers': roop.globals.execution_providers,
-        'execution_threads': roop.globals.execution_threads
-    })
-    progress.refresh()
-    progress.update(1)
diff --git a/spaces/posak/Tune-A-Video-Training-UI/app_inference.py b/spaces/posak/Tune-A-Video-Training-UI/app_inference.py
deleted file mode 100644
index d705504e5bc7a8938e1b5fcfb207f4cb731c866b..0000000000000000000000000000000000000000
--- a/spaces/posak/Tune-A-Video-Training-UI/app_inference.py
+++ /dev/null
@@ -1,170 +0,0 @@
-#!/usr/bin/env python
-
-from __future__ import annotations
-
-import enum
-
-import gradio as gr
-from huggingface_hub import HfApi
-
-from constants import MODEL_LIBRARY_ORG_NAME, UploadTarget
-from inference import InferencePipeline
-from utils import find_exp_dirs
-
-
-class ModelSource(enum.Enum):
-    HUB_LIB = UploadTarget.MODEL_LIBRARY.value
-    LOCAL = 'Local'
-
-
-class InferenceUtil:
-    def __init__(self, hf_token: str | None):
-        self.hf_token = hf_token
-
-    def load_hub_model_list(self) -> dict:
-        api = HfApi(token=self.hf_token)
-        choices = [
-            info.modelId
-            for info in api.list_models(author=MODEL_LIBRARY_ORG_NAME)
-        ]
-        return gr.update(choices=choices,
-                         value=choices[0] if choices else None)
-
-    @staticmethod
-    def load_local_model_list() -> dict:
-        choices = find_exp_dirs()
-        return gr.update(choices=choices,
-                         value=choices[0] if choices else None)
-
-    def reload_model_list(self, model_source: str) -> dict:
-        if model_source == ModelSource.HUB_LIB.value:
-            return self.load_hub_model_list()
-        elif model_source == ModelSource.LOCAL.value:
-            return self.load_local_model_list()
-        else:
-            raise ValueError
-
-    def load_model_info(self, model_id: str) -> tuple[str, str]:
-        try:
-            card = InferencePipeline.get_model_card(model_id, self.hf_token)
-        except Exception:
-            return '', ''
-        base_model = getattr(card.data, 'base_model', '')
-        training_prompt = getattr(card.data, 'training_prompt', '')
-        return base_model, training_prompt
-
-    def reload_model_list_and_update_model_info(
-            self, model_source: str) -> tuple[dict, str, str]:
-        model_list_update = self.reload_model_list(model_source)
-        model_list = model_list_update['choices']
-        model_info = self.load_model_info(model_list[0] if model_list else '')
-        return model_list_update, *model_info
-
-
-def create_inference_demo(pipe: InferencePipeline,
-                          hf_token: str | None = None) -> gr.Blocks:
-    app = InferenceUtil(hf_token)
-
-    with gr.Blocks() as demo:
-        with gr.Row():
-            with gr.Column():
-                with gr.Box():
-                    model_source = gr.Radio(
-                        label='Model Source',
-                        choices=[_.value for _ in ModelSource],
-                        value=ModelSource.HUB_LIB.value)
-                    reload_button = gr.Button('Reload Model List')
-                    model_id = gr.Dropdown(label='Model ID',
-                                           choices=None,
-                                           value=None)
-                    with gr.Accordion(
-                            label=
-                            'Model info (Base model and prompt used for training)',
-                            open=False):
-                        with gr.Row():
-                            base_model_used_for_training = gr.Text(
-                                label='Base model', interactive=False)
-                            prompt_used_for_training = gr.Text(
-                                label='Training prompt', interactive=False)
-                prompt = gr.Textbox(
-                    label='Prompt',
-                    max_lines=1,
-                    placeholder='Example: "A panda is surfing"')
-                video_length = gr.Slider(label='Video length',
-                                         minimum=4,
-                                         maximum=12,
-                                         step=1,
-                                         value=8)
-                fps = gr.Slider(label='FPS',
-                                minimum=1,
-                                maximum=12,
-                                step=1,
-                                value=1)
-                seed = gr.Slider(label='Seed',
-                                 minimum=0,
-                                 maximum=100000,
-                                 step=1,
-                                 value=0)
-                with gr.Accordion('Other Parameters', open=False):
-                    num_steps = gr.Slider(label='Number of Steps',
-                                          minimum=0,
-                                          maximum=100,
-                                          step=1,
-                                          value=50)
-                    guidance_scale = gr.Slider(label='CFG Scale',
-                                               minimum=0,
-                                               maximum=50,
-                                               step=0.1,
-                                               value=7.5)
-
-                run_button = gr.Button('Generate')
-
-                gr.Markdown('''
-                - After training, you can press "Reload Model List" button to load your trained model names.
-                - It takes a few minutes to download model first.
-                - Expected time to generate an 8-frame video: 70 seconds with T4, 24 seconds with A10G, (10 seconds with A100)
-                ''')
-            with gr.Column():
-                result = gr.Video(label='Result')
-
-        model_source.change(fn=app.reload_model_list_and_update_model_info,
-                            inputs=model_source,
-                            outputs=[
-                                model_id,
-                                base_model_used_for_training,
-                                prompt_used_for_training,
-                            ])
-        reload_button.click(fn=app.reload_model_list_and_update_model_info,
-                            inputs=model_source,
-                            outputs=[
-                                model_id,
-                                base_model_used_for_training,
-                                prompt_used_for_training,
-                            ])
-        model_id.change(fn=app.load_model_info,
-                        inputs=model_id,
-                        outputs=[
-                            base_model_used_for_training,
-                            prompt_used_for_training,
-                        ])
-        inputs = [
-            model_id,
-            prompt,
-            video_length,
-            fps,
-            seed,
-            num_steps,
-            guidance_scale,
-        ]
-        prompt.submit(fn=pipe.run, inputs=inputs, outputs=result)
-        run_button.click(fn=pipe.run, inputs=inputs, outputs=result)
-    return demo
-
-
-if __name__ == '__main__':
-    import os
-
-    hf_token = os.getenv('HF_TOKEN')
-    pipe = InferencePipeline(hf_token)
-    demo = create_inference_demo(pipe, hf_token)
-    demo.queue(max_size=10).launch(share=False)
diff --git a/spaces/prerna9811/Chord/portaudio/src/os/win/pa_win_wdmks_utils.h b/spaces/prerna9811/Chord/portaudio/src/os/win/pa_win_wdmks_utils.h
deleted file mode 100644
index f524cf7f3c7c0fb23318f0813c9f5345e0e9957c..0000000000000000000000000000000000000000
--- a/spaces/prerna9811/Chord/portaudio/src/os/win/pa_win_wdmks_utils.h
+++ /dev/null
@@ -1,65 +0,0 @@
-#ifndef PA_WIN_WDMKS_UTILS_H
-#define PA_WIN_WDMKS_UTILS_H
-
-/*
- * PortAudio Portable Real-Time Audio Library
- * Windows WDM KS utilities
- *
- * Copyright (c) 1999 - 2007 Ross Bencina, Andrew Baldwin
- *
- * Permission is hereby granted, free of charge, to any person obtaining
- * a copy of this software and associated documentation files
- * (the "Software"), to deal in the Software without restriction,
- * including without limitation the rights to use, copy, modify, merge,
- * publish, distribute, sublicense, and/or sell copies of the Software,
- * and to permit persons to whom the Software is furnished to do so,
- * subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be
- * included in all copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
- * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
- * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
- * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR
- * ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
- * CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
- * WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
- */
-
-/*
- * The text above constitutes the entire PortAudio license; however,
- * the PortAudio community also makes the following non-binding requests:
- *
- * Any person wishing to distribute modifications to the Software is
- * requested to send the modifications to the original developer so that
- * they can be incorporated into the canonical version. It is also
- * requested that these non-binding requests be included along with the
- * license above.
- */
-
-/** @file
- @brief Utilities for working with the Windows WDM KS API
-*/
-
-#ifdef __cplusplus
-extern "C" {
-#endif
-
-/**
-    Query for the maximum number of channels supported by any pin of the
-    specified device. Returns 0 if the query fails for any reason.
-
-    @param wcharDevicePath A system level PnP interface path, supplied as a WCHAR unicode string.
-    Declared as void* to avoid introducing a dependency on wchar_t here.
-
-    @param isInput A flag specifying whether to query for input (non-zero) or output (zero) channels.
-*/
-int PaWin_WDMKS_QueryFilterMaximumChannelCount( void *wcharDevicePath, int isInput );
-
-
-#ifdef __cplusplus
-}
-#endif /* __cplusplus */
-
-#endif /* PA_WIN_WDMKS_UTILS_H */
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/ImagePath.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/ImagePath.py
deleted file mode 100644
index 3d3538c97b7b346df2f804721cf3ad810d5260f0..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/ImagePath.py
+++ /dev/null
@@ -1,19 +0,0 @@
-#
-# The Python Imaging Library
-# $Id$
-#
-# path interface
-#
-# History:
-# 1996-11-04 fl   Created
-# 2002-04-14 fl   Added documentation stub class
-#
-# Copyright (c) Secret Labs AB 1997.
-# Copyright (c) Fredrik Lundh 1996.
-#
-# See the README file for information on usage and redistribution.
-#
-
-from . import Image
-
-Path = Image.core.path
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/IptcImagePlugin.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/IptcImagePlugin.py
deleted file mode 100644
index 316cd17c732a4e28f6eeb3621f9907e43465c47b..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/IptcImagePlugin.py
+++ /dev/null
@@ -1,230 +0,0 @@
-#
-# The Python Imaging Library.
-# $Id$
-#
-# IPTC/NAA file handling
-#
-# history:
-# 1995-10-01 fl   Created
-# 1998-03-09 fl   Cleaned up and added to PIL
-# 2002-06-18 fl   Added getiptcinfo helper
-#
-# Copyright (c) Secret Labs AB 1997-2002.
-# Copyright (c) Fredrik Lundh 1995.
-#
-# See the README file for information on usage and redistribution.
-#
-import os
-import tempfile
-
-from . import Image, ImageFile
-from ._binary import i8
-from ._binary import i16be as i16
-from ._binary import i32be as i32
-from ._binary import o8
-
-COMPRESSION = {1: "raw", 5: "jpeg"}
-
-PAD = o8(0) * 4
-
-
-#
-# Helpers
-
-
-def i(c):
-    return i32((PAD + c)[-4:])
-
-
-def dump(c):
-    for i in c:
-        print("%02x" % i8(i), end=" ")
-    print()
-
-
-##
-# Image plugin for IPTC/NAA datastreams.  To read IPTC/NAA fields
-# from TIFF and JPEG files, use the <b>getiptcinfo</b> function.
-
-
-class IptcImageFile(ImageFile.ImageFile):
-    format = "IPTC"
-    format_description = "IPTC/NAA"
-
-    def getint(self, key):
-        return i(self.info[key])
-
-    def field(self):
-        #
-        # get a IPTC field header
-        s = self.fp.read(5)
-        if not s.strip(b"\x00"):
-            return None, 0
-
-        tag = s[1], s[2]
-
-        # syntax
-        if s[0] != 0x1C or tag[0] not in [1, 2, 3, 4, 5, 6, 7, 8, 9, 240]:
-            msg = "invalid IPTC/NAA file"
-            raise SyntaxError(msg)
-
-        # field size
-        size = s[3]
-        if size > 132:
-            msg = "illegal field length in IPTC/NAA file"
-            raise OSError(msg)
-        elif size == 128:
-            size = 0
-        elif size > 128:
-            size = i(self.fp.read(size - 128))
-        else:
-            size = i16(s, 3)
-
-        return tag, size
-
-    def _open(self):
-        # load descriptive fields
-        while True:
-            offset = self.fp.tell()
-            tag, size = self.field()
-            if not tag or tag == (8, 10):
-                break
-            if size:
-                tagdata = self.fp.read(size)
-            else:
-                tagdata = None
-            if tag in self.info:
-                if isinstance(self.info[tag], list):
-                    self.info[tag].append(tagdata)
-                else:
-                    self.info[tag] = [self.info[tag], tagdata]
-            else:
-                self.info[tag] = tagdata
-
-        # mode
-        layers = i8(self.info[(3, 60)][0])
-        component = i8(self.info[(3, 60)][1])
-        if (3, 65) in self.info:
-            id = i8(self.info[(3, 65)][0]) - 1
-        else:
-            id = 0
-        if layers == 1 and not component:
-            self._mode = "L"
-        elif layers == 3 and component:
-            self._mode = "RGB"[id]
-        elif layers == 4 and component:
-            self._mode = "CMYK"[id]
-
-        # size
-        self._size = self.getint((3, 20)), self.getint((3, 30))
-
-        # compression
-        try:
-            compression = COMPRESSION[self.getint((3, 120))]
-        except KeyError as e:
-            msg = "Unknown IPTC image compression"
-            raise OSError(msg) from e
-
-        # tile
-        if tag == (8, 10):
-            self.tile = [
-                ("iptc", (compression, offset), (0, 0, self.size[0], self.size[1]))
-            ]
-
-    def load(self):
-        if len(self.tile) != 1 or self.tile[0][0] != "iptc":
-            return ImageFile.ImageFile.load(self)
-
-        type, tile, box = self.tile[0]
-
-        encoding, offset = tile
-
-        self.fp.seek(offset)
-
-        # Copy image data to temporary file
-        o_fd, outfile = tempfile.mkstemp(text=False)
-        o = os.fdopen(o_fd)
-        if encoding == "raw":
-            # To simplify access to the extracted file,
-            # prepend a PPM header
-            o.write("P5\n%d %d\n255\n" % self.size)
-        while True:
-            type, size = self.field()
-            if type != (8, 10):
-                break
-            while size > 0:
-                s = self.fp.read(min(size, 8192))
-                if not s:
-                    break
-                o.write(s)
-                size -= len(s)
-        o.close()
-
-        try:
-            with Image.open(outfile) as _im:
-                _im.load()
-                self.im = _im.im
-        finally:
-            try:
-                os.unlink(outfile)
-            except OSError:
-                pass
-
-
-Image.register_open(IptcImageFile.format, IptcImageFile)
-
-Image.register_extension(IptcImageFile.format, ".iim")
-
-
-def getiptcinfo(im):
-    """
-    Get IPTC information from TIFF, JPEG, or IPTC file.
-
-    :param im: An image containing IPTC data.
-    :returns: A dictionary containing IPTC information, or None if
-        no IPTC information block was found.
-    """
-    import io
-
-    from . import JpegImagePlugin, TiffImagePlugin
-
-    data = None
-
-    if isinstance(im, IptcImageFile):
-        # return info dictionary right away
-        return im.info
-
-    elif isinstance(im, JpegImagePlugin.JpegImageFile):
-        # extract the IPTC/NAA resource
-        photoshop = im.info.get("photoshop")
-        if photoshop:
-            data = photoshop.get(0x0404)
-
-    elif isinstance(im, TiffImagePlugin.TiffImageFile):
-        # get raw data from the IPTC/NAA tag (PhotoShop tags the data
-        # as 4-byte integers, so we cannot use the get method...)
-        try:
-            data = im.tag.tagdata[TiffImagePlugin.IPTC_NAA_CHUNK]
-        except (AttributeError, KeyError):
-            pass
-
-    if data is None:
-        return None  # no properties
-
-    # create an IptcImagePlugin object without initializing it
-    class FakeImage:
-        pass
-
-    im = FakeImage()
-    im.__class__ = IptcImageFile
-
-    # parse the IPTC information chunk
-    im.info = {}
-    im.fp = io.BytesIO(data)
-
-    try:
-        im._open()
-    except (IndexError, KeyError):
-        pass  # expected failure
-
-    return im.info
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/MspImagePlugin.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/MspImagePlugin.py
deleted file mode 100644
index 3f3609f1c2037123c49f34348109b52ccbd2fb59..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/PIL/MspImagePlugin.py
+++ /dev/null
@@ -1,194 +0,0 @@
-#
-# The Python Imaging Library.
-#
-# MSP file handling
-#
-# This is the format used by the Paint program in Windows 1 and 2.
-#
-# History:
-#       95-09-05 fl     Created
-#       97-01-03 fl     Read/write MSP images
-#       17-02-21 es     Fixed RLE interpretation
-#
-# Copyright (c) Secret Labs AB 1997.
-# Copyright (c) Fredrik Lundh 1995-97.
-# Copyright (c) Eric Soroos 2017.
-#
-# See the README file for information on usage and redistribution.
-#
-# More info on this format: https://archive.org/details/gg243631
-# Page 313:
-# Figure 205. Windows Paint Version 1: "DanM" Format
-# Figure 206. Windows Paint Version 2: "LinS" Format. Used in Windows V2.03
-#
-# See also: https://www.fileformat.info/format/mspaint/egff.htm
-
-import io
-import struct
-
-from . import Image, ImageFile
-from ._binary import i16le as i16
-from ._binary import o16le as o16
-
-#
-# read MSP files
-
-
-def _accept(prefix):
-    return prefix[:4] in [b"DanM", b"LinS"]
-
-
-##
-# Image plugin for Windows MSP images.  This plugin supports both
-# uncompressed (Windows 1.0).
-
-
-class MspImageFile(ImageFile.ImageFile):
-    format = "MSP"
-    format_description = "Windows Paint"
-
-    def _open(self):
-        # Header
-        s = self.fp.read(32)
-        if not _accept(s):
-            msg = "not an MSP file"
-            raise SyntaxError(msg)
-
-        # Header checksum
-        checksum = 0
-        for i in range(0, 32, 2):
-            checksum = checksum ^ i16(s, i)
-        if checksum != 0:
-            msg = "bad MSP checksum"
-            raise SyntaxError(msg)
-
-        self._mode = "1"
-        self._size = i16(s, 4), i16(s, 6)
-
-        if s[:4] == b"DanM":
-            self.tile = [("raw", (0, 0) + self.size, 32, ("1", 0, 1))]
-        else:
-            self.tile = [("MSP", (0, 0) + self.size, 32, None)]
-
-
-class MspDecoder(ImageFile.PyDecoder):
-    # The algo for the MSP decoder is from
-    # https://www.fileformat.info/format/mspaint/egff.htm
-    # cc-by-attribution -- That page references is taken from the
-    # Encyclopedia of Graphics File Formats and is licensed by
-    # O'Reilly under the Creative Common/Attribution license
-    #
-    # For RLE encoded files, the 32byte header is followed by a scan
-    # line map, encoded as one 16bit word of encoded byte length per
-    # line.
-    #
-    # NOTE: the encoded length of the line can be 0. This was not
-    # handled in the previous version of this encoder, and there's no
-    # mention of how to handle it in the documentation. From the few
-    # examples I've seen, I've assumed that it is a fill of the
-    # background color, in this case, white.
-    #
-    #
-    # Pseudocode of the decoder:
-    # Read a BYTE value as the RunType
-    #  If the RunType value is zero
-    #   Read next byte as the RunCount
-    #   Read the next byte as the RunValue
-    #   Write the RunValue byte RunCount times
-    #  If the RunType value is non-zero
-    #   Use this value as the RunCount
-    #   Read and write the next RunCount bytes literally
-    #
-    #  e.g.:
-    #  0x00 03 ff 05 00 01 02 03 04
-    #  would yield the bytes:
-    #  0xff ff ff 00 01 02 03 04
-    #
-    # which are then interpreted as a bit packed mode '1' image
-
-    _pulls_fd = True
-
-    def decode(self, buffer):
-        img = io.BytesIO()
-        blank_line = bytearray((0xFF,) * ((self.state.xsize + 7) // 8))
-        try:
-            self.fd.seek(32)
-            rowmap = struct.unpack_from(
-                f"<{self.state.ysize}H", self.fd.read(self.state.ysize * 2)
-            )
-        except struct.error as e:
-            msg = "Truncated MSP file in row map"
-            raise OSError(msg) from e
-
-        for x, rowlen in enumerate(rowmap):
-            try:
-                if rowlen == 0:
-                    img.write(blank_line)
-                    continue
-                row = self.fd.read(rowlen)
-                if len(row) != rowlen:
-                    msg = f"Truncated MSP file, expected {rowlen} bytes on row {x}"
-                    raise OSError(msg)
-                idx = 0
-                while idx < rowlen:
-                    runtype = row[idx]
-                    idx += 1
-                    if runtype == 0:
-                        (runcount, runval) = struct.unpack_from("Bc", row, idx)
-                        img.write(runval * runcount)
-                        idx += 2
-                    else:
-                        runcount = runtype
-                        img.write(row[idx : idx + runcount])
-                        idx += runcount
-
-            except struct.error as e:
-                msg = f"Corrupted MSP file in row {x}"
-                raise OSError(msg) from e
-
-        self.set_as_raw(img.getvalue(), ("1", 0, 1))
-
-        return -1, 0
-
-
-Image.register_decoder("MSP", MspDecoder)
-
-
-#
-# write MSP files (uncompressed only)
-
-
-def _save(im, fp, filename):
-    if im.mode != "1":
-        msg = f"cannot write mode {im.mode} as MSP"
-        raise OSError(msg)
-
-    # create MSP header
-    header = [0] * 16
-
-    header[0], header[1] = i16(b"Da"), i16(b"nM")  # version 1
-    header[2], header[3] = im.size
-    header[4], header[5] = 1, 1
-    header[6], header[7] = 1, 1
-    header[8], header[9] = im.size
-
-    checksum = 0
-    for h in header:
-        checksum = checksum ^ h
-    header[12] = checksum  # FIXME: is this the right field?
-
-    # header
-    for h in header:
-        fp.write(o16(h))
-
-    # image body
-    ImageFile._save(im, fp, [("raw", (0, 0) + im.size, 32, ("1", 0, 1))])
-
-
-#
-# registry
-
-Image.register_open(MspImageFile.format, MspImageFile, _accept)
-Image.register_save(MspImageFile.format, _save)
-
-Image.register_extension(MspImageFile.format, ".msp")
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/gradio/_frontend_code/dataframe/shared/utils.ts b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/gradio/_frontend_code/dataframe/shared/utils.ts
deleted file mode 100644
index 09d4e0940d01bd5b0b340ab20f613691443ffde0..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/gradio/_frontend_code/dataframe/shared/utils.ts
+++ /dev/null
@@ -1,7 +0,0 @@
-export type Headers = string[];
-export type Data = (string | number)[][];
-export type Datatype = "str" | "markdown" | "html" | "number" | "bool" | "date";
-export type Metadata = {
-	[key: string]: string[][] | null;
-} | null;
-export type HeadersWithIDs = { value: string; id: string }[];
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/gradio/node/dev/files/index.js b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/gradio/node/dev/files/index.js
deleted file mode 100644
index 42f20acb840693e358329dfde384ad3d31cedd31..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/gradio/node/dev/files/index.js
+++ /dev/null
@@ -1,44 +0,0 @@
-export { create_server, examine_module, find_free_ports, is_free_port } from './index-897f432e.js';
-import 'node:child_process';
-import 'net';
-import 'path';
-import 'fs';
-import 'node:fs';
-import 'node:fs/promises';
-import 'node:path';
-import 'node:url';
-import 'node:util';
-import 'node:perf_hooks';
-import 'node:module';
-import 'tty';
-import 'esbuild-wasm';
-import 'events';
-import 'assert';
-import 'util';
-import 'url';
-import 'http';
-import 'stream';
-import 'os';
-import 'child_process';
-import 'node:os';
-import 'node:crypto';
-import 'node:dns';
-import 'crypto';
-import 'node:buffer';
-import 'module';
-import 'node:assert';
-import 'node:process';
-import 'node:v8';
-import 'worker_threads';
-import 'node:http';
-import 'node:https';
-import 'zlib';
-import 'buffer';
-import 'https';
-import 'tls';
-import 'querystring';
-import 'node:readline';
-import 'node:zlib';
-import '../compiler.js';
-import 'fs/promises';
-import 'perf_hooks';
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/numpy/testing/__init__.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/numpy/testing/__init__.py
deleted file mode 100644
index 8a34221e4dde5f8a1eeab7446193344915467769..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/numpy/testing/__init__.py
+++ /dev/null
@@ -1,22 +0,0 @@
-"""Common test support for all numpy test scripts.
-
-This single module should provide all the common functionality for numpy tests
-in a single location, so that test scripts can just import it and work right
-away.
-
-"""
-from unittest import TestCase
-
-from . import _private
-from ._private.utils import *
-from ._private.utils import (_assert_valid_refcount, _gen_alignment_data)
-from ._private import extbuild
-from . import overrides
-
-__all__ = (
-    _private.utils.__all__ + ['TestCase', 'overrides']
-)
-
-from numpy._pytesttester import PytestTester
-test = PytestTester(__name__)
-del PytestTester
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/core/missing.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/core/missing.py
deleted file mode 100644
index 58b0e2907b8cee90d4d353753b66343ac8d6c222..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pandas/core/missing.py
+++ /dev/null
@@ -1,1056 +0,0 @@
-"""
-Routines for filling missing data.
-"""
-from __future__ import annotations
-
-from functools import (
-    partial,
-    wraps,
-)
-from typing import (
-    TYPE_CHECKING,
-    Any,
-    Literal,
-    cast,
-)
-
-import numpy as np
-
-from pandas._libs import (
-    NaT,
-    algos,
-    lib,
-)
-from pandas._typing import (
-    ArrayLike,
-    AxisInt,
-    F,
-    ReindexMethod,
-    npt,
-)
-from pandas.compat._optional import import_optional_dependency
-
-from pandas.core.dtypes.cast import infer_dtype_from
-from pandas.core.dtypes.common import (
-    is_array_like,
-    is_numeric_dtype,
-    is_numeric_v_string_like,
-    is_object_dtype,
-    needs_i8_conversion,
-)
-from pandas.core.dtypes.dtypes import DatetimeTZDtype
-from pandas.core.dtypes.missing import (
-    is_valid_na_for_dtype,
-    isna,
-    na_value_for_dtype,
-)
-
-if TYPE_CHECKING:
-    from pandas import Index
-
-
-def check_value_size(value, mask: npt.NDArray[np.bool_], length: int):
-    """
-    Validate the size of the values passed to ExtensionArray.fillna.
-    """
-    if is_array_like(value):
-        if len(value) != length:
-            raise ValueError(
-                f"Length of 'value' does not match. Got ({len(value)}) "
-                f" expected {length}"
-            )
-        value = value[mask]
-
-    return value
-
-
-def mask_missing(arr: ArrayLike, values_to_mask) -> npt.NDArray[np.bool_]:
-    """
-    Return a masking array of same size/shape as arr
-    with entries equaling any member of values_to_mask set to True
-
-    Parameters
-    ----------
-    arr : ArrayLike
-    values_to_mask: list, tuple, or scalar
-
-    Returns
-    -------
-    np.ndarray[bool]
-    """
-    # When called from Block.replace/replace_list, values_to_mask is a scalar
-    #  known to be holdable by arr.
-    # When called from Series._single_replace, values_to_mask is tuple or list
-    dtype, values_to_mask = infer_dtype_from(values_to_mask)
-
-    if isinstance(dtype, np.dtype):
-        values_to_mask = np.array(values_to_mask, dtype=dtype)
-    else:
-        cls = dtype.construct_array_type()
-        if not lib.is_list_like(values_to_mask):
-            values_to_mask = [values_to_mask]
-        values_to_mask = cls._from_sequence(values_to_mask, dtype=dtype, copy=False)
-
-    potential_na = False
-    if is_object_dtype(arr.dtype):
-        # pre-compute mask to avoid comparison to NA
-        potential_na = True
-        arr_mask = ~isna(arr)
-
-    na_mask = isna(values_to_mask)
-    nonna = values_to_mask[~na_mask]
-
-    # GH 21977
-    mask = np.zeros(arr.shape, dtype=bool)
-    for x in nonna:
-        if is_numeric_v_string_like(arr, x):
-            # GH#29553 prevent numpy deprecation warnings
-            pass
-        else:
-            if potential_na:
-                new_mask = np.zeros(arr.shape, dtype=np.bool_)
-                new_mask[arr_mask] = arr[arr_mask] == x
-            else:
-                new_mask = arr == x
-
-                if not isinstance(new_mask, np.ndarray):
-                    # usually BooleanArray
-                    new_mask = new_mask.to_numpy(dtype=bool, na_value=False)
-            mask |= new_mask
-
-    if na_mask.any():
-        mask |= isna(arr)
-
-    return mask
-
-
-def clean_fill_method(method: str, allow_nearest: bool = False):
-    if isinstance(method, str):
-        method = method.lower()
-        if method == "ffill":
-            method = "pad"
-        elif method == "bfill":
-            method = "backfill"
-
-    valid_methods = ["pad", "backfill"]
-    expecting = "pad (ffill) or backfill (bfill)"
-    if allow_nearest:
-        valid_methods.append("nearest")
-        expecting = "pad (ffill), backfill (bfill) or nearest"
-    if method not in valid_methods:
-        raise ValueError(f"Invalid fill method. Expecting {expecting}. Got {method}")
-    return method
-
-
-# interpolation methods that dispatch to np.interp
-
-NP_METHODS = ["linear", "time", "index", "values"]
-
-# interpolation methods that dispatch to _interpolate_scipy_wrapper
-
-SP_METHODS = [
-    "nearest",
-    "zero",
-    "slinear",
-    "quadratic",
-    "cubic",
-    "barycentric",
-    "krogh",
-    "spline",
-    "polynomial",
-    "from_derivatives",
-    "piecewise_polynomial",
-    "pchip",
-    "akima",
-    "cubicspline",
-]
-
-
-def clean_interp_method(method: str, index: Index, **kwargs) -> str:
-    order = kwargs.get("order")
-
-    if method in ("spline", "polynomial") and order is None:
-        raise ValueError("You must specify the order of the spline or polynomial.")
-
-    valid = NP_METHODS + SP_METHODS
-    if method not in valid:
-        raise ValueError(f"method must be one of {valid}. Got '{method}' instead.")
-
-    if method in ("krogh", "piecewise_polynomial", "pchip"):
-        if not index.is_monotonic_increasing:
-            raise ValueError(
-                f"{method} interpolation requires that the index be monotonic."
-            )
-
-    return method
-
-
-def find_valid_index(how: str, is_valid: npt.NDArray[np.bool_]) -> int | None:
-    """
-    Retrieves the positional index of the first valid value.
-
-    Parameters
-    ----------
-    how : {'first', 'last'}
-        Use this parameter to change between the first or last valid index.
-    is_valid: np.ndarray
-        Mask to find na_values.
-
-    Returns
-    -------
-    int or None
-    """
-    assert how in ["first", "last"]
-
-    if len(is_valid) == 0:  # early stop
-        return None
-
-    if is_valid.ndim == 2:
-        is_valid = is_valid.any(axis=1)  # reduce axis 1
-
-    if how == "first":
-        idxpos = is_valid[::].argmax()
-
-    elif how == "last":
-        idxpos = len(is_valid) - 1 - is_valid[::-1].argmax()
-
-    chk_notna = is_valid[idxpos]
-
-    if not chk_notna:
-        return None
-    # Incompatible return value type (got "signedinteger[Any]",
-    # expected "Optional[int]")
-    return idxpos  # type: ignore[return-value]
-
-
-def validate_limit_direction(
-    limit_direction: str,
-) -> Literal["forward", "backward", "both"]:
-    valid_limit_directions = ["forward", "backward", "both"]
-    limit_direction = limit_direction.lower()
-    if limit_direction not in valid_limit_directions:
-        raise ValueError(
-            "Invalid limit_direction: expecting one of "
-            f"{valid_limit_directions}, got '{limit_direction}'."
-        )
-    # error: Incompatible return value type (got "str", expected
-    # "Literal['forward', 'backward', 'both']")
-    return limit_direction  # type: ignore[return-value]
-
-
-def validate_limit_area(limit_area: str | None) -> Literal["inside", "outside"] | None:
-    if limit_area is not None:
-        valid_limit_areas = ["inside", "outside"]
-        limit_area = limit_area.lower()
-        if limit_area not in valid_limit_areas:
-            raise ValueError(
-                f"Invalid limit_area: expecting one of {valid_limit_areas}, got "
-                f"{limit_area}."
-            )
-    # error: Incompatible return value type (got "Optional[str]", expected
-    # "Optional[Literal['inside', 'outside']]")
-    return limit_area  # type: ignore[return-value]
-
-
-def infer_limit_direction(limit_direction, method):
-    # Set `limit_direction` depending on `method`
-    if limit_direction is None:
-        if method in ("backfill", "bfill"):
-            limit_direction = "backward"
-        else:
-            limit_direction = "forward"
-    else:
-        if method in ("pad", "ffill") and limit_direction != "forward":
-            raise ValueError(
-                f"`limit_direction` must be 'forward' for method `{method}`"
-            )
-        if method in ("backfill", "bfill") and limit_direction != "backward":
-            raise ValueError(
-                f"`limit_direction` must be 'backward' for method `{method}`"
-            )
-    return limit_direction
-
-
-def get_interp_index(method, index: Index) -> Index:
-    # create/use the index
-    if method == "linear":
-        # prior default
-        from pandas import Index
-
-        index = Index(np.arange(len(index)))
-    else:
-        methods = {"index", "values", "nearest", "time"}
-        is_numeric_or_datetime = (
-            is_numeric_dtype(index.dtype)
-            or isinstance(index.dtype, DatetimeTZDtype)
-            or lib.is_np_dtype(index.dtype, "mM")
-        )
-        if method not in methods and not is_numeric_or_datetime:
-            raise ValueError(
-                "Index column must be numeric or datetime type when "
-                f"using {method} method other than linear. "
-                "Try setting a numeric or datetime index column before "
-                "interpolating."
-            )
-
-    if isna(index).any():
-        raise NotImplementedError(
-            "Interpolation with NaNs in the index "
-            "has not been implemented. Try filling "
-            "those NaNs before interpolating."
-        )
-    return index
-
-
-def interpolate_2d_inplace(
-    data: np.ndarray,  # floating dtype
-    index: Index,
-    axis: AxisInt,
-    method: str = "linear",
-    limit: int | None = None,
-    limit_direction: str = "forward",
-    limit_area: str | None = None,
-    fill_value: Any | None = None,
-    **kwargs,
-) -> None:
-    """
-    Column-wise application of _interpolate_1d.
-
-    Notes
-    -----
-    Alters 'data' in-place.
-
-    The signature does differ from _interpolate_1d because it only
-    includes what is needed for Block.interpolate.
-    """
-    # validate the interp method
-    clean_interp_method(method, index, **kwargs)
-
-    if is_valid_na_for_dtype(fill_value, data.dtype):
-        fill_value = na_value_for_dtype(data.dtype, compat=False)
-
-    if method == "time":
-        if not needs_i8_conversion(index.dtype):
-            raise ValueError(
-                "time-weighted interpolation only works "
-                "on Series or DataFrames with a "
-                "DatetimeIndex"
-            )
-        method = "values"
-
-    limit_direction = validate_limit_direction(limit_direction)
-    limit_area_validated = validate_limit_area(limit_area)
-
-    # default limit is unlimited GH #16282
-    limit = algos.validate_limit(nobs=None, limit=limit)
-
-    indices = _index_to_interp_indices(index, method)
-
-    def func(yvalues: np.ndarray) -> None:
-        # process 1-d slices in the axis direction
-
-        _interpolate_1d(
-            indices=indices,
-            yvalues=yvalues,
-            method=method,
-            limit=limit,
-            limit_direction=limit_direction,
-            limit_area=limit_area_validated,
-            fill_value=fill_value,
-            bounds_error=False,
-            **kwargs,
-        )
-
-    # error: Argument 1 to "apply_along_axis" has incompatible type
-    # "Callable[[ndarray[Any, Any]], None]"; expected "Callable[...,
-    # Union[_SupportsArray[dtype[<nothing>]], Sequence[_SupportsArray
-    # [dtype[<nothing>]]], Sequence[Sequence[_SupportsArray[dtype[<nothing>]]]],
-    # Sequence[Sequence[Sequence[_SupportsArray[dtype[<nothing>]]]]],
-    # Sequence[Sequence[Sequence[Sequence[_SupportsArray[dtype[<nothing>]]]]]]]]"
-    np.apply_along_axis(func, axis, data)  # type: ignore[arg-type]
-
-
-def _index_to_interp_indices(index: Index, method: str) -> np.ndarray:
-    """
-    Convert Index to ndarray of indices to pass to NumPy/SciPy.
-    """
-    xarr = index._values
-    if needs_i8_conversion(xarr.dtype):
-        # GH#1646 for dt64tz
-        xarr = xarr.view("i8")
-
-    if method == "linear":
-        inds = xarr
-        inds = cast(np.ndarray, inds)
-    else:
-        inds = np.asarray(xarr)
-
-        if method in ("values", "index"):
-            if inds.dtype == np.object_:
-                inds = lib.maybe_convert_objects(inds)
-
-    return inds
-
-
-def _interpolate_1d(
-    indices: np.ndarray,
-    yvalues: np.ndarray,
-    method: str = "linear",
-    limit: int | None = None,
-    limit_direction: str = "forward",
-    limit_area: Literal["inside", "outside"] | None = None,
-    fill_value: Any | None = None,
-    bounds_error: bool = False,
-    order: int | None = None,
-    **kwargs,
-) -> None:
-    """
-    Logic for the 1-d interpolation.  The input
-    indices and yvalues will each be 1-d arrays of the same length.
-
-    Bounds_error is currently hardcoded to False since non-scipy ones don't
-    take it as an argument.
-
-    Notes
-    -----
-    Fills 'yvalues' in-place.
-    """
-
-    invalid = isna(yvalues)
-    valid = ~invalid
-
-    if not valid.any():
-        return
-
-    if valid.all():
-        return
-
-    # These are sets of index pointers to invalid values... i.e. {0, 1, etc...
-    all_nans = set(np.flatnonzero(invalid))
-
-    first_valid_index = find_valid_index(how="first", is_valid=valid)
-    if first_valid_index is None:  # no nan found in start
-        first_valid_index = 0
-    start_nans = set(range(first_valid_index))
-
-    last_valid_index = find_valid_index(how="last", is_valid=valid)
-    if last_valid_index is None:  # no nan found in end
-        last_valid_index = len(yvalues)
-    end_nans = set(range(1 + last_valid_index, len(valid)))
-
-    # Like the sets above, preserve_nans contains indices of invalid values,
-    # but in this case, it is the final set of indices that need to be
-    # preserved as NaN after the interpolation.
-
-    # For example if limit_direction='forward' then preserve_nans will
-    # contain indices of NaNs at the beginning of the series, and NaNs that
-    # are more than 'limit' away from the prior non-NaN.
-
-    # set preserve_nans based on direction using _interp_limit
-    preserve_nans: list | set
-    if limit_direction == "forward":
-        preserve_nans = start_nans | set(_interp_limit(invalid, limit, 0))
-    elif limit_direction == "backward":
-        preserve_nans = end_nans | set(_interp_limit(invalid, 0, limit))
-    else:
-        # both directions... just use _interp_limit
-        preserve_nans = set(_interp_limit(invalid, limit, limit))
-
-    # if limit_area is set, add either mid or outside indices
-    # to preserve_nans GH #16284
-    if limit_area == "inside":
-        # preserve NaNs on the outside
-        preserve_nans |= start_nans | end_nans
-    elif limit_area == "outside":
-        # preserve NaNs on the inside
-        mid_nans = all_nans - start_nans - end_nans
-        preserve_nans |= mid_nans
-
-    # sort preserve_nans and convert to list
-    preserve_nans = sorted(preserve_nans)
-
-    is_datetimelike = yvalues.dtype.kind in "mM"
-
-    if is_datetimelike:
-        yvalues = yvalues.view("i8")
-
-    if method in NP_METHODS:
-        # np.interp requires sorted X values, #21037
-
-        indexer = np.argsort(indices[valid])
-        yvalues[invalid] = np.interp(
-            indices[invalid], indices[valid][indexer], yvalues[valid][indexer]
-        )
-    else:
-        yvalues[invalid] = _interpolate_scipy_wrapper(
-            indices[valid],
-            yvalues[valid],
-            indices[invalid],
-            method=method,
-            fill_value=fill_value,
-            bounds_error=bounds_error,
-            order=order,
-            **kwargs,
-        )
-
-    if is_datetimelike:
-        yvalues[preserve_nans] = NaT.value
-    else:
-        yvalues[preserve_nans] = np.nan
-    return
-
-
-def _interpolate_scipy_wrapper(
-    x: np.ndarray,
-    y: np.ndarray,
-    new_x: np.ndarray,
-    method: str,
-    fill_value=None,
-    bounds_error: bool = False,
-    order=None,
-    **kwargs,
-):
-    """
-    Passed off to scipy.interpolate.interp1d. method is scipy's kind.
-    Returns an array interpolated at new_x.  Add any new methods to
-    the list in _clean_interp_method.
-    """
-    extra = f"{method} interpolation requires SciPy."
-    import_optional_dependency("scipy", extra=extra)
-    from scipy import interpolate
-
-    new_x = np.asarray(new_x)
-
-    # ignores some kwargs that could be passed along.
-    alt_methods = {
-        "barycentric": interpolate.barycentric_interpolate,
-        "krogh": interpolate.krogh_interpolate,
-        "from_derivatives": _from_derivatives,
-        "piecewise_polynomial": _from_derivatives,
-        "cubicspline": _cubicspline_interpolate,
-        "akima": _akima_interpolate,
-        "pchip": interpolate.pchip_interpolate,
-    }
-
-    interp1d_methods = [
-        "nearest",
-        "zero",
-        "slinear",
-        "quadratic",
-        "cubic",
-        "polynomial",
-    ]
-    if method in interp1d_methods:
-        if method == "polynomial":
-            kind = order
-        else:
-            kind = method
-        terp = interpolate.interp1d(
-            x, y, kind=kind, fill_value=fill_value, bounds_error=bounds_error
-        )
-        new_y = terp(new_x)
-    elif method == "spline":
-        # GH #10633, #24014
-        if isna(order) or (order <= 0):
-            raise ValueError(
-                f"order needs to be specified and greater than 0; got order: {order}"
-            )
-        terp = interpolate.UnivariateSpline(x, y, k=order, **kwargs)
-        new_y = terp(new_x)
-    else:
-        # GH 7295: need to be able to write for some reason
-        # in some circumstances: check all three
-        if not x.flags.writeable:
-            x = x.copy()
-        if not y.flags.writeable:
-            y = y.copy()
-        if not new_x.flags.writeable:
-            new_x = new_x.copy()
-        terp = alt_methods[method]
-        new_y = terp(x, y, new_x, **kwargs)
-    return new_y
-
-
-def _from_derivatives(
-    xi: np.ndarray,
-    yi: np.ndarray,
-    x: np.ndarray,
-    order=None,
-    der: int | list[int] | None = 0,
-    extrapolate: bool = False,
-):
-    """
-    Convenience function for interpolate.BPoly.from_derivatives.
-
-    Construct a piecewise polynomial in the Bernstein basis, compatible
-    with the specified values and derivatives at breakpoints.
-
-    Parameters
-    ----------
-    xi : array-like
-        sorted 1D array of x-coordinates
-    yi : array-like or list of array-likes
-        yi[i][j] is the j-th derivative known at xi[i]
-    order: None or int or array-like of ints. Default: None.
-        Specifies the degree of local polynomials. If not None, some
-        derivatives are ignored.
-    der : int or list
-        How many derivatives to extract; None for all potentially nonzero
-        derivatives (that is a number equal to the number of points), or a
-        list of derivatives to extract. This number includes the function
-        value as 0th derivative.
-     extrapolate : bool, optional
-        Whether to extrapolate to ouf-of-bounds points based on first and last
-        intervals, or to return NaNs. Default: True.
-
-    See Also
-    --------
-    scipy.interpolate.BPoly.from_derivatives
-
-    Returns
-    -------
-    y : scalar or array-like
-        The result, of length R or length M or M by R.
-    """
-    from scipy import interpolate
-
-    # return the method for compat with scipy version & backwards compat
-    method = interpolate.BPoly.from_derivatives
-    m = method(xi, yi.reshape(-1, 1), orders=order, extrapolate=extrapolate)
-
-    return m(x)
-
-
-def _akima_interpolate(
-    xi: np.ndarray,
-    yi: np.ndarray,
-    x: np.ndarray,
-    der: int | list[int] | None = 0,
-    axis: AxisInt = 0,
-):
-    """
-    Convenience function for akima interpolation.
-    xi and yi are arrays of values used to approximate some function f,
-    with ``yi = f(xi)``.
-
-    See `Akima1DInterpolator` for details.
-
-    Parameters
-    ----------
-    xi : np.ndarray
-        A sorted list of x-coordinates, of length N.
-    yi : np.ndarray
-        A 1-D array of real values.  `yi`'s length along the interpolation
-        axis must be equal to the length of `xi`. If N-D array, use axis
-        parameter to select correct axis.
-    x : np.ndarray
-        Of length M.
-    der : int, optional
-        How many derivatives to extract; None for all potentially
-        nonzero derivatives (that is a number equal to the number
-        of points), or a list of derivatives to extract. This number
-        includes the function value as 0th derivative.
-    axis : int, optional
-        Axis in the yi array corresponding to the x-coordinate values.
-
-    See Also
-    --------
-    scipy.interpolate.Akima1DInterpolator
-
-    Returns
-    -------
-    y : scalar or array-like
-        The result, of length R or length M or M by R,
-
-    """
-    from scipy import interpolate
-
-    P = interpolate.Akima1DInterpolator(xi, yi, axis=axis)
-
-    return P(x, nu=der)
-
-
-def _cubicspline_interpolate(
-    xi: np.ndarray,
-    yi: np.ndarray,
-    x: np.ndarray,
-    axis: AxisInt = 0,
-    bc_type: str | tuple[Any, Any] = "not-a-knot",
-    extrapolate=None,
-):
-    """
-    Convenience function for cubic spline data interpolator.
-
-    See `scipy.interpolate.CubicSpline` for details.
-
-    Parameters
-    ----------
-    xi : np.ndarray, shape (n,)
-        1-d array containing values of the independent variable.
-        Values must be real, finite and in strictly increasing order.
-    yi : np.ndarray
-        Array containing values of the dependent variable. It can have
-        arbitrary number of dimensions, but the length along ``axis``
-        (see below) must match the length of ``x``. Values must be finite.
-    x : np.ndarray, shape (m,)
-    axis : int, optional
-        Axis along which `y` is assumed to be varying. Meaning that for
-        ``x[i]`` the corresponding values are ``np.take(y, i, axis=axis)``.
-        Default is 0.
-    bc_type : string or 2-tuple, optional
-        Boundary condition type. Two additional equations, given by the
-        boundary conditions, are required to determine all coefficients of
-        polynomials on each segment [2]_.
-        If `bc_type` is a string, then the specified condition will be applied
-        at both ends of a spline. Available conditions are:
-        * 'not-a-knot' (default): The first and second segment at a curve end
-          are the same polynomial. It is a good default when there is no
-          information on boundary conditions.
-        * 'periodic': The interpolated functions is assumed to be periodic
-          of period ``x[-1] - x[0]``. The first and last value of `y` must be
-          identical: ``y[0] == y[-1]``. This boundary condition will result in
-          ``y'[0] == y'[-1]`` and ``y''[0] == y''[-1]``.
-        * 'clamped': The first derivative at curves ends are zero. Assuming
-          a 1D `y`, ``bc_type=((1, 0.0), (1, 0.0))`` is the same condition.
-        * 'natural': The second derivative at curve ends are zero. Assuming
-          a 1D `y`, ``bc_type=((2, 0.0), (2, 0.0))`` is the same condition.
-        If `bc_type` is a 2-tuple, the first and the second value will be
-        applied at the curve start and end respectively. The tuple values can
-        be one of the previously mentioned strings (except 'periodic') or a
-        tuple `(order, deriv_values)` allowing to specify arbitrary
-        derivatives at curve ends:
-        * `order`: the derivative order, 1 or 2.
-        * `deriv_value`: array-like containing derivative values, shape must
-          be the same as `y`, excluding ``axis`` dimension. For example, if
-          `y` is 1D, then `deriv_value` must be a scalar. If `y` is 3D with
-          the shape (n0, n1, n2) and axis=2, then `deriv_value` must be 2D
-          and have the shape (n0, n1).
-    extrapolate : {bool, 'periodic', None}, optional
-        If bool, determines whether to extrapolate to out-of-bounds points
-        based on first and last intervals, or to return NaNs. If 'periodic',
-        periodic extrapolation is used. If None (default), ``extrapolate`` is
-        set to 'periodic' for ``bc_type='periodic'`` and to True otherwise.
-
-    See Also
-    --------
-    scipy.interpolate.CubicHermiteSpline
-
-    Returns
-    -------
-    y : scalar or array-like
-        The result, of shape (m,)
-
-    References
-    ----------
-    .. [1] `Cubic Spline Interpolation
-            <https://en.wikiversity.org/wiki/Cubic_Spline_Interpolation>`_
-            on Wikiversity.
-    .. [2] Carl de Boor, "A Practical Guide to Splines", Springer-Verlag, 1978.
-    """
-    from scipy import interpolate
-
-    P = interpolate.CubicSpline(
-        xi, yi, axis=axis, bc_type=bc_type, extrapolate=extrapolate
-    )
-
-    return P(x)
-
-
-def _interpolate_with_limit_area(
-    values: np.ndarray,
-    method: Literal["pad", "backfill"],
-    limit: int | None,
-    limit_area: Literal["inside", "outside"],
-) -> None:
-    """
-    Apply interpolation and limit_area logic to values along a to-be-specified axis.
-
-    Parameters
-    ----------
-    values: np.ndarray
-        Input array.
-    method: str
-        Interpolation method. Could be "bfill" or "pad"
-    limit: int, optional
-        Index limit on interpolation.
-    limit_area: {'inside', 'outside'}
-        Limit area for interpolation.
-
-    Notes
-    -----
-    Modifies values in-place.
-    """
-
-    invalid = isna(values)
-    is_valid = ~invalid
-
-    if not invalid.all():
-        first = find_valid_index(how="first", is_valid=is_valid)
-        if first is None:
-            first = 0
-        last = find_valid_index(how="last", is_valid=is_valid)
-        if last is None:
-            last = len(values)
-
-        pad_or_backfill_inplace(
-            values,
-            method=method,
-            limit=limit,
-        )
-
-        if limit_area == "inside":
-            invalid[first : last + 1] = False
-        elif limit_area == "outside":
-            invalid[:first] = invalid[last + 1 :] = False
-        else:
-            raise ValueError("limit_area should be 'inside' or 'outside'")
-
-        values[invalid] = np.nan
-
-
-def pad_or_backfill_inplace(
-    values: np.ndarray,
-    method: Literal["pad", "backfill"] = "pad",
-    axis: AxisInt = 0,
-    limit: int | None = None,
-    limit_area: Literal["inside", "outside"] | None = None,
-) -> None:
-    """
-    Perform an actual interpolation of values, values will be make 2-d if
-    needed fills inplace, returns the result.
-
-    Parameters
-    ----------
-    values: np.ndarray
-        Input array.
-    method: str, default "pad"
-        Interpolation method. Could be "bfill" or "pad"
-    axis: 0 or 1
-        Interpolation axis
-    limit: int, optional
-        Index limit on interpolation.
-    limit_area: str, optional
-        Limit area for interpolation. Can be "inside" or "outside"
-
-    Notes
-    -----
-    Modifies values in-place.
-    """
-    if limit_area is not None:
-        np.apply_along_axis(
-            # error: Argument 1 to "apply_along_axis" has incompatible type
-            # "partial[None]"; expected
-            # "Callable[..., Union[_SupportsArray[dtype[<nothing>]],
-            # Sequence[_SupportsArray[dtype[<nothing>]]],
-            # Sequence[Sequence[_SupportsArray[dtype[<nothing>]]]],
-            # Sequence[Sequence[Sequence[_SupportsArray[dtype[<nothing>]]]]],
-            # Sequence[Sequence[Sequence[Sequence[_
-            # SupportsArray[dtype[<nothing>]]]]]]]]"
-            partial(  # type: ignore[arg-type]
-                _interpolate_with_limit_area,
-                method=method,
-                limit=limit,
-                limit_area=limit_area,
-            ),
-            axis,
-            values,
-        )
-        return
-
-    transf = (lambda x: x) if axis == 0 else (lambda x: x.T)
-
-    # reshape a 1 dim if needed
-    if values.ndim == 1:
-        if axis != 0:  # pragma: no cover
-            raise AssertionError("cannot interpolate on a ndim == 1 with axis != 0")
-        values = values.reshape(tuple((1,) + values.shape))
-
-    method = clean_fill_method(method)
-    tvalues = transf(values)
-
-    func = get_fill_func(method, ndim=2)
-    # _pad_2d and _backfill_2d both modify tvalues inplace
-    func(tvalues, limit=limit)
-    return
-
-
-def _fillna_prep(
-    values, mask: npt.NDArray[np.bool_] | None = None
-) -> npt.NDArray[np.bool_]:
-    # boilerplate for _pad_1d, _backfill_1d, _pad_2d, _backfill_2d
-
-    if mask is None:
-        mask = isna(values)
-
-    mask = mask.view(np.uint8)
-    return mask
-
-
-def _datetimelike_compat(func: F) -> F:
-    """
-    Wrapper to handle datetime64 and timedelta64 dtypes.
-    """
-
-    @wraps(func)
-    def new_func(values, limit: int | None = None, mask=None):
-        if needs_i8_conversion(values.dtype):
-            if mask is None:
-                # This needs to occur before casting to int64
-                mask = isna(values)
-
-            result, mask = func(values.view("i8"), limit=limit, mask=mask)
-            return result.view(values.dtype), mask
-
-        return func(values, limit=limit, mask=mask)
-
-    return cast(F, new_func)
-
-
-@_datetimelike_compat
-def _pad_1d(
-    values: np.ndarray,
-    limit: int | None = None,
-    mask: npt.NDArray[np.bool_] | None = None,
-) -> tuple[np.ndarray, npt.NDArray[np.bool_]]:
-    mask = _fillna_prep(values, mask)
-    algos.pad_inplace(values, mask, limit=limit)
-    return values, mask
-
-
-@_datetimelike_compat
-def _backfill_1d(
-    values: np.ndarray,
-    limit: int | None = None,
-    mask: npt.NDArray[np.bool_] | None = None,
-) -> tuple[np.ndarray, npt.NDArray[np.bool_]]:
-    mask = _fillna_prep(values, mask)
-    algos.backfill_inplace(values, mask, limit=limit)
-    return values, mask
-
-
-@_datetimelike_compat
-def _pad_2d(
-    values: np.ndarray,
-    limit: int | None = None,
-    mask: npt.NDArray[np.bool_] | None = None,
-):
-    mask = _fillna_prep(values, mask)
-
-    if values.size:
-        algos.pad_2d_inplace(values, mask, limit=limit)
-    else:
-        # for test coverage
-        pass
-    return values, mask
-
-
-@_datetimelike_compat
-def _backfill_2d(
-    values, limit: int | None = None, mask: npt.NDArray[np.bool_] | None = None
-):
-    mask = _fillna_prep(values, mask)
-
-    if values.size:
-        algos.backfill_2d_inplace(values, mask, limit=limit)
-    else:
-        # for test coverage
-        pass
-    return values, mask
-
-
-_fill_methods = {"pad": _pad_1d, "backfill": _backfill_1d}
-
-
-def get_fill_func(method, ndim: int = 1):
-    method = clean_fill_method(method)
-    if ndim == 1:
-        return _fill_methods[method]
-    return {"pad": _pad_2d, "backfill": _backfill_2d}[method]
-
-
-def clean_reindex_fill_method(method) -> ReindexMethod | None:
-    if method is None:
-        return None
-    return clean_fill_method(method, allow_nearest=True)
-
-
-def _interp_limit(
-    invalid: npt.NDArray[np.bool_], fw_limit: int | None, bw_limit: int | None
-):
-    """
-    Get indexers of values that won't be filled
-    because they exceed the limits.
-
-    Parameters
-    ----------
-    invalid : np.ndarray[bool]
-    fw_limit : int or None
-        forward limit to index
-    bw_limit : int or None
-        backward limit to index
-
-    Returns
-    -------
-    set of indexers
-
-    Notes
-    -----
-    This is equivalent to the more readable, but slower
-
-    .. code-block:: python
-
-        def _interp_limit(invalid, fw_limit, bw_limit):
-            for x in np.where(invalid)[0]:
-                if invalid[max(0, x - fw_limit):x + bw_limit + 1].all():
-                    yield x
-    """
-    # handle forward first; the backward direction is the same except
-    # 1. operate on the reversed array
-    # 2. subtract the returned indices from N - 1
-    N = len(invalid)
-    f_idx = set()
-    b_idx = set()
-
-    def inner(invalid, limit: int):
-        limit = min(limit, N)
-        windowed = _rolling_window(invalid, limit + 1).all(1)
-        idx = set(np.where(windowed)[0] + limit) | set(
-            np.where((~invalid[: limit + 1]).cumsum() == 0)[0]
-        )
-        return idx
-
-    if fw_limit is not None:
-        if fw_limit == 0:
-            f_idx = set(np.where(invalid)[0])
-        else:
-            f_idx = inner(invalid, fw_limit)
-
-    if bw_limit is not None:
-        if bw_limit == 0:
-            # then we don't even need to care about backwards
-            # just use forwards
-            return f_idx
-        else:
-            b_idx_inv = list(inner(invalid[::-1], bw_limit))
-            b_idx = set(N - 1 - np.asarray(b_idx_inv))
-            if fw_limit == 0:
-                return b_idx
-
-    return f_idx & b_idx
-
-
-def _rolling_window(a: npt.NDArray[np.bool_], window: int) -> npt.NDArray[np.bool_]:
-    """
-    [True, True, False, True, False], 2 ->
-
-    [
-        [True,  True],
-        [True, False],
-        [False, True],
-        [True, False],
-    ]
-    """
-    # https://stackoverflow.com/a/6811241
-    shape = a.shape[:-1] + (a.shape[-1] - window + 1, window)
-    strides = a.strides + (a.strides[-1],)
-    return np.lib.stride_tricks.as_strided(a, shape=shape, strides=strides)
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_internal/resolution/resolvelib/requirements.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_internal/resolution/resolvelib/requirements.py
deleted file mode 100644
index f561f1f1e270666ccd74c9d61f78c9c24f5c4c99..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_internal/resolution/resolvelib/requirements.py
+++ /dev/null
@@ -1,166 +0,0 @@
-from pip._vendor.packaging.specifiers import SpecifierSet
-from pip._vendor.packaging.utils import NormalizedName, canonicalize_name
-
-from pip._internal.req.req_install import InstallRequirement
-
-from .base import Candidate, CandidateLookup, Requirement, format_name
-
-
-class ExplicitRequirement(Requirement):
-    def __init__(self, candidate: Candidate) -> None:
-        self.candidate = candidate
-
-    def __str__(self) -> str:
-        return str(self.candidate)
-
-    def __repr__(self) -> str:
-        return "{class_name}({candidate!r})".format(
-            class_name=self.__class__.__name__,
-            candidate=self.candidate,
-        )
-
-    @property
-    def project_name(self) -> NormalizedName:
-        # No need to canonicalize - the candidate did this
-        return self.candidate.project_name
-
-    @property
-    def name(self) -> str:
-        # No need to canonicalize - the candidate did this
-        return self.candidate.name
-
-    def format_for_error(self) -> str:
-        return self.candidate.format_for_error()
-
-    def get_candidate_lookup(self) -> CandidateLookup:
-        return self.candidate, None
-
-    def is_satisfied_by(self, candidate: Candidate) -> bool:
-        return candidate == self.candidate
-
-
-class SpecifierRequirement(Requirement):
-    def __init__(self, ireq: InstallRequirement) -> None:
-        assert ireq.link is None, "This is a link, not a specifier"
-        self._ireq = ireq
-        self._extras = frozenset(ireq.extras)
-
-    def __str__(self) -> str:
-        return str(self._ireq.req)
-
-    def __repr__(self) -> str:
-        return "{class_name}({requirement!r})".format(
-            class_name=self.__class__.__name__,
-            requirement=str(self._ireq.req),
-        )
-
-    @property
-    def project_name(self) -> NormalizedName:
-        assert self._ireq.req, "Specifier-backed ireq is always PEP 508"
-        return canonicalize_name(self._ireq.req.name)
-
-    @property
-    def name(self) -> str:
-        return format_name(self.project_name, self._extras)
-
-    def format_for_error(self) -> str:
-
-        # Convert comma-separated specifiers into "A, B, ..., F and G"
-        # This makes the specifier a bit more "human readable", without
-        # risking a change in meaning. (Hopefully! Not all edge cases have
-        # been checked)
-        parts = [s.strip() for s in str(self).split(",")]
-        if len(parts) == 0:
-            return ""
-        elif len(parts) == 1:
-            return parts[0]
-
-        return ", ".join(parts[:-1]) + " and " + parts[-1]
-
-    def get_candidate_lookup(self) -> CandidateLookup:
-        return None, self._ireq
-
-    def is_satisfied_by(self, candidate: Candidate) -> bool:
-        assert candidate.name == self.name, (
-            f"Internal issue: Candidate is not for this requirement "
-            f"{candidate.name} vs {self.name}"
-        )
-        # We can safely always allow prereleases here since PackageFinder
-        # already implements the prerelease logic, and would have filtered out
-        # prerelease candidates if the user does not expect them.
-        assert self._ireq.req, "Specifier-backed ireq is always PEP 508"
-        spec = self._ireq.req.specifier
-        return spec.contains(candidate.version, prereleases=True)
-
-
-class RequiresPythonRequirement(Requirement):
-    """A requirement representing Requires-Python metadata."""
-
-    def __init__(self, specifier: SpecifierSet, match: Candidate) -> None:
-        self.specifier = specifier
-        self._candidate = match
-
-    def __str__(self) -> str:
-        return f"Python {self.specifier}"
-
-    def __repr__(self) -> str:
-        return "{class_name}({specifier!r})".format(
-            class_name=self.__class__.__name__,
-            specifier=str(self.specifier),
-        )
-
-    @property
-    def project_name(self) -> NormalizedName:
-        return self._candidate.project_name
-
-    @property
-    def name(self) -> str:
-        return self._candidate.name
-
-    def format_for_error(self) -> str:
-        return str(self)
-
-    def get_candidate_lookup(self) -> CandidateLookup:
-        if self.specifier.contains(self._candidate.version, prereleases=True):
-            return self._candidate, None
-        return None, None
-
-    def is_satisfied_by(self, candidate: Candidate) -> bool:
-        assert candidate.name == self._candidate.name, "Not Python candidate"
-        # We can safely always allow prereleases here since PackageFinder
-        # already implements the prerelease logic, and would have filtered out
-        # prerelease candidates if the user does not expect them.
-        return self.specifier.contains(candidate.version, prereleases=True)
-
-
-class UnsatisfiableRequirement(Requirement):
-    """A requirement that cannot be satisfied."""
-
-    def __init__(self, name: NormalizedName) -> None:
-        self._name = name
-
-    def __str__(self) -> str:
-        return f"{self._name} (unavailable)"
-
-    def __repr__(self) -> str:
-        return "{class_name}({name!r})".format(
-            class_name=self.__class__.__name__,
-            name=str(self._name),
-        )
-
-    @property
-    def project_name(self) -> NormalizedName:
-        return self._name
-
-    @property
-    def name(self) -> str:
-        return self._name
-
-    def format_for_error(self) -> str:
-        return str(self)
-
-    def get_candidate_lookup(self) -> CandidateLookup:
-        return None, None
-
-    def is_satisfied_by(self, candidate: Candidate) -> bool:
-        return False
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_vendor/colorama/ansi.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_vendor/colorama/ansi.py
deleted file mode 100644
index 11ec695ff79627463a0282d25079527562de9e42..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pip/_vendor/colorama/ansi.py
+++ /dev/null
@@ -1,102 +0,0 @@
-# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file.
-'''
-This module generates ANSI character codes to printing colors to terminals.
-See: http://en.wikipedia.org/wiki/ANSI_escape_code
-'''
-
-CSI = '\033['
-OSC = '\033]'
-BEL = '\a'
-
-
-def code_to_chars(code):
-    return CSI + str(code) + 'm'
-
-def set_title(title):
-    return OSC + '2;' + title + BEL
-
-def clear_screen(mode=2):
-    return CSI + str(mode) + 'J'
-
-def clear_line(mode=2):
-    return CSI + str(mode) + 'K'
-
-
-class AnsiCodes(object):
-    def __init__(self):
-        # the subclasses declare class attributes which are numbers.
-        # Upon instantiation we define instance attributes, which are the same
-        # as the class attributes but wrapped with the ANSI escape sequence
-        for name in dir(self):
-            if not name.startswith('_'):
-                value = getattr(self, name)
-                setattr(self, name, code_to_chars(value))
-
-
-class AnsiCursor(object):
-    def UP(self, n=1):
-        return CSI + str(n) + 'A'
-    def DOWN(self, n=1):
-        return CSI + str(n) + 'B'
-    def FORWARD(self, n=1):
-        return CSI + str(n) + 'C'
-    def BACK(self, n=1):
-        return CSI + str(n) + 'D'
-    def POS(self, x=1, y=1):
-        return CSI + str(y) + ';' + str(x) + 'H'
-
-
-class AnsiFore(AnsiCodes):
-    BLACK           = 30
-    RED             = 31
-    GREEN           = 32
-    YELLOW          = 33
-    BLUE            = 34
-    MAGENTA         = 35
-    CYAN            = 36
-    WHITE           = 37
-    RESET           = 39
-
-    # These are fairly well supported, but not part of the standard.
-    LIGHTBLACK_EX   = 90
-    LIGHTRED_EX     = 91
-    LIGHTGREEN_EX   = 92
-    LIGHTYELLOW_EX  = 93
-    LIGHTBLUE_EX    = 94
-    LIGHTMAGENTA_EX = 95
-    LIGHTCYAN_EX    = 96
-    LIGHTWHITE_EX   = 97
-
-
-class AnsiBack(AnsiCodes):
-    BLACK           = 40
-    RED             = 41
-    GREEN           = 42
-    YELLOW          = 43
-    BLUE            = 44
-    MAGENTA         = 45
-    CYAN            = 46
-    WHITE           = 47
-    RESET           = 49
-
-    # These are fairly well supported, but not part of the standard.
-    LIGHTBLACK_EX   = 100
-    LIGHTRED_EX     = 101
-    LIGHTGREEN_EX   = 102
-    LIGHTYELLOW_EX  = 103
-    LIGHTBLUE_EX    = 104
-    LIGHTMAGENTA_EX = 105
-    LIGHTCYAN_EX    = 106
-    LIGHTWHITE_EX   = 107
-
-
-class AnsiStyle(AnsiCodes):
-    BRIGHT    = 1
-    DIM       = 2
-    NORMAL    = 22
-    RESET_ALL = 0
-
-Fore   = AnsiFore()
-Back   = AnsiBack()
-Style  = AnsiStyle()
-Cursor = AnsiCursor()
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pygments/styles/lilypond.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pygments/styles/lilypond.py
deleted file mode 100644
index a90b69784635d3634bd3c203074b7c6dfc46ed65..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/pygments/styles/lilypond.py
+++ /dev/null
@@ -1,56 +0,0 @@
-"""
-    pygments.styles.lilypond
-    ~~~~~~~~~~~~~~~~~~~~~~~~
-
-    LilyPond-specific style.
-
-    :copyright: Copyright 2006-2023 by the Pygments team, see AUTHORS.
-    :license: BSD, see LICENSE for details.
-"""
-
-from pygments.style import Style
-from pygments.token import Token
-
-class LilyPondStyle(Style):
-    """
-    Style for the LilyPond language.
-        
-    .. versionadded:: 2.11
-    """
-
-    # Don't show it in the gallery, it's intended for LilyPond
-    # input only and doesn't show good output on Python code.
-    web_style_gallery_exclude = True
-
-    styles = {
-        Token.Text: "",
-        Token.Keyword: "bold",
-        Token.Comment: "italic #A3AAB2",
-        Token.String: "#AB0909",
-        Token.String.Escape: "#C46C6C",
-        Token.String.Symbol: "noinherit",
-        Token.Pitch: "", #"#911520",
-        Token.Number: "#976806", # includes durations
-        # A bare 11 is not distinguishable from a number, so we highlight
-        # the same.
-        Token.ChordModifier: "#976806",
-        Token.Name.Lvalue: "#08547A",
-        Token.Name.BackslashReference: "#08547A",
-        Token.Name.Builtin.MusicCommand: "bold #08547A",
-        Token.Name.Builtin.PaperVariable: "bold #6C5A05",
-        Token.Name.Builtin.HeaderVariable: "bold #6C5A05",
-        Token.Name.Builtin.MusicFunction: "bold #08547A",
-        Token.Name.Builtin.Clef: "bold #08547A",
-        Token.Name.Builtin.Scale: "bold #08547A",
-        Token.Name.Builtin.RepeatType: "#08547A",
-        Token.Name.Builtin.Dynamic: "#68175A",
-        Token.Name.Builtin.Articulation: "#68175A",
-        Token.Name.Builtin.SchemeFunction: "bold #A83401",
-        Token.Name.Builtin.SchemeBuiltin: "bold",
-        Token.Name.Builtin.MarkupCommand: "bold #831E71",
-        Token.Name.Builtin.Context: "bold #038B8B",
-        Token.Name.Builtin.ContextProperty: "#038B8B",
-        Token.Name.Builtin.Grob: "bold #0C7441",
-        Token.Name.Builtin.GrobProperty: "#0C7441",
-        Token.Name.Builtin.Translator: "bold #6200A4",
-    }
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/setuptools/_distutils/dist.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/setuptools/_distutils/dist.py
deleted file mode 100644
index 37db4d6cd7539940d5629ae1f426526a4d8d1d6f..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/setuptools/_distutils/dist.py
+++ /dev/null
@@ -1,1257 +0,0 @@
-"""distutils.dist
-
-Provides the Distribution class, which represents the module distribution
-being built/installed/distributed.
-"""
-
-import sys
-import os
-import re
-from email import message_from_file
-
-try:
-    import warnings
-except ImportError:
-    warnings = None
-
-from distutils.errors import *
-from distutils.fancy_getopt import FancyGetopt, translate_longopt
-from distutils.util import check_environ, strtobool, rfc822_escape
-from distutils import log
-from distutils.debug import DEBUG
-
-# Regex to define acceptable Distutils command names.  This is not *quite*
-# the same as a Python NAME -- I don't allow leading underscores.  The fact
-# that they're very similar is no coincidence; the default naming scheme is
-# to look for a Python module named after the command.
-command_re = re.compile(r'^[a-zA-Z]([a-zA-Z0-9_]*)$')
-
-
-def _ensure_list(value, fieldname):
-    if isinstance(value, str):
-        # a string containing comma separated values is okay.  It will
-        # be converted to a list by Distribution.finalize_options().
-        pass
-    elif not isinstance(value, list):
-        # passing a tuple or an iterator perhaps, warn and convert
-        typename = type(value).__name__
-        msg = "Warning: '{fieldname}' should be a list, got type '{typename}'"
-        msg = msg.format(**locals())
-        log.log(log.WARN, msg)
-        value = list(value)
-    return value
-
-
-class Distribution:
-    """The core of the Distutils.  Most of the work hiding behind 'setup'
-    is really done within a Distribution instance, which farms the work out
-    to the Distutils commands specified on the command line.
-
-    Setup scripts will almost never instantiate Distribution directly,
-    unless the 'setup()' function is totally inadequate to their needs.
-    However, it is conceivable that a setup script might wish to subclass
-    Distribution for some specialized purpose, and then pass the subclass
-    to 'setup()' as the 'distclass' keyword argument.  If so, it is
-    necessary to respect the expectations that 'setup' has of Distribution.
-    See the code for 'setup()', in core.py, for details.
-    """
-
-    # 'global_options' describes the command-line options that may be
-    # supplied to the setup script prior to any actual commands.
-    # Eg. "./setup.py -n" or "./setup.py --quiet" both take advantage of
-    # these global options.  This list should be kept to a bare minimum,
-    # since every global option is also valid as a command option -- and we
-    # don't want to pollute the commands with too many options that they
-    # have minimal control over.
-    # The fourth entry for verbose means that it can be repeated.
-    global_options = [
-        ('verbose', 'v', "run verbosely (default)", 1),
-        ('quiet', 'q', "run quietly (turns verbosity off)"),
-        ('dry-run', 'n', "don't actually do anything"),
-        ('help', 'h', "show detailed help message"),
-        ('no-user-cfg', None,
-            'ignore pydistutils.cfg in your home directory'),
-    ]
-
-    # 'common_usage' is a short (2-3 line) string describing the common
-    # usage of the setup script.
-    common_usage = """\
-Common commands: (see '--help-commands' for more)
-
-  setup.py build      will build the package underneath 'build/'
-  setup.py install    will install the package
-"""
-
-    # options that are not propagated to the commands
-    display_options = [
-        ('help-commands', None,
-         "list all available commands"),
-        ('name', None,
-         "print package name"),
-        ('version', 'V',
-         "print package version"),
-        ('fullname', None,
-         "print <package name>-<version>"),
-        ('author', None,
-         "print the author's name"),
-        ('author-email', None,
-         "print the author's email address"),
-        ('maintainer', None,
-         "print the maintainer's name"),
-        ('maintainer-email', None,
-         "print the maintainer's email address"),
-        ('contact', None,
-         "print the maintainer's name if known, else the author's"),
-        ('contact-email', None,
-         "print the maintainer's email address if known, else the author's"),
-        ('url', None,
-         "print the URL for this package"),
-        ('license', None,
-         "print the license of the package"),
-        ('licence', None,
-         "alias for --license"),
-        ('description', None,
-         "print the package description"),
-        ('long-description', None,
-         "print the long package description"),
-        ('platforms', None,
-         "print the list of platforms"),
-        ('classifiers', None,
-         "print the list of classifiers"),
-        ('keywords', None,
-         "print the list of keywords"),
-        ('provides', None,
-         "print the list of packages/modules provided"),
-        ('requires', None,
-         "print the list of packages/modules required"),
-        ('obsoletes', None,
-         "print the list of packages/modules made obsolete")
-        ]
-    display_option_names = [translate_longopt(x[0]) for x in display_options]
-
-    # negative options are options that exclude other options
-    negative_opt = {'quiet': 'verbose'}
-
-    # -- Creation/initialization methods -------------------------------
-
-    def __init__(self, attrs=None):
-        """Construct a new Distribution instance: initialize all the
-        attributes of a Distribution, and then use 'attrs' (a dictionary
-        mapping attribute names to values) to assign some of those
-        attributes their "real" values.  (Any attributes not mentioned in
-        'attrs' will be assigned to some null value: 0, None, an empty list
-        or dictionary, etc.)  Most importantly, initialize the
-        'command_obj' attribute to the empty dictionary; this will be
-        filled in with real command objects by 'parse_command_line()'.
-        """
-
-        # Default values for our command-line options
-        self.verbose = 1
-        self.dry_run = 0
-        self.help = 0
-        for attr in self.display_option_names:
-            setattr(self, attr, 0)
-
-        # Store the distribution meta-data (name, version, author, and so
-        # forth) in a separate object -- we're getting to have enough
-        # information here (and enough command-line options) that it's
-        # worth it.  Also delegate 'get_XXX()' methods to the 'metadata'
-        # object in a sneaky and underhanded (but efficient!) way.
-        self.metadata = DistributionMetadata()
-        for basename in self.metadata._METHOD_BASENAMES:
-            method_name = "get_" + basename
-            setattr(self, method_name, getattr(self.metadata, method_name))
-
-        # 'cmdclass' maps command names to class objects, so we
-        # can 1) quickly figure out which class to instantiate when
-        # we need to create a new command object, and 2) have a way
-        # for the setup script to override command classes
-        self.cmdclass = {}
-
-        # 'command_packages' is a list of packages in which commands
-        # are searched for.  The factory for command 'foo' is expected
-        # to be named 'foo' in the module 'foo' in one of the packages
-        # named here.  This list is searched from the left; an error
-        # is raised if no named package provides the command being
-        # searched for.  (Always access using get_command_packages().)
-        self.command_packages = None
-
-        # 'script_name' and 'script_args' are usually set to sys.argv[0]
-        # and sys.argv[1:], but they can be overridden when the caller is
-        # not necessarily a setup script run from the command-line.
-        self.script_name = None
-        self.script_args = None
-
-        # 'command_options' is where we store command options between
-        # parsing them (from config files, the command-line, etc.) and when
-        # they are actually needed -- ie. when the command in question is
-        # instantiated.  It is a dictionary of dictionaries of 2-tuples:
-        #   command_options = { command_name : { option : (source, value) } }
-        self.command_options = {}
-
-        # 'dist_files' is the list of (command, pyversion, file) that
-        # have been created by any dist commands run so far. This is
-        # filled regardless of whether the run is dry or not. pyversion
-        # gives sysconfig.get_python_version() if the dist file is
-        # specific to a Python version, 'any' if it is good for all
-        # Python versions on the target platform, and '' for a source
-        # file. pyversion should not be used to specify minimum or
-        # maximum required Python versions; use the metainfo for that
-        # instead.
-        self.dist_files = []
-
-        # These options are really the business of various commands, rather
-        # than of the Distribution itself.  We provide aliases for them in
-        # Distribution as a convenience to the developer.
-        self.packages = None
-        self.package_data = {}
-        self.package_dir = None
-        self.py_modules = None
-        self.libraries = None
-        self.headers = None
-        self.ext_modules = None
-        self.ext_package = None
-        self.include_dirs = None
-        self.extra_path = None
-        self.scripts = None
-        self.data_files = None
-        self.password = ''
-
-        # And now initialize bookkeeping stuff that can't be supplied by
-        # the caller at all.  'command_obj' maps command names to
-        # Command instances -- that's how we enforce that every command
-        # class is a singleton.
-        self.command_obj = {}
-
-        # 'have_run' maps command names to boolean values; it keeps track
-        # of whether we have actually run a particular command, to make it
-        # cheap to "run" a command whenever we think we might need to -- if
-        # it's already been done, no need for expensive filesystem
-        # operations, we just check the 'have_run' dictionary and carry on.
-        # It's only safe to query 'have_run' for a command class that has
-        # been instantiated -- a false value will be inserted when the
-        # command object is created, and replaced with a true value when
-        # the command is successfully run.  Thus it's probably best to use
-        # '.get()' rather than a straight lookup.
-        self.have_run = {}
-
-        # Now we'll use the attrs dictionary (ultimately, keyword args from
-        # the setup script) to possibly override any or all of these
-        # distribution options.
-
-        if attrs:
-            # Pull out the set of command options and work on them
-            # specifically.  Note that this order guarantees that aliased
-            # command options will override any supplied redundantly
-            # through the general options dictionary.
-            options = attrs.get('options')
-            if options is not None:
-                del attrs['options']
-                for (command, cmd_options) in options.items():
-                    opt_dict = self.get_option_dict(command)
-                    for (opt, val) in cmd_options.items():
-                        opt_dict[opt] = ("setup script", val)
-
-            if 'licence' in attrs:
-                attrs['license'] = attrs['licence']
-                del attrs['licence']
-                msg = "'licence' distribution option is deprecated; use 'license'"
-                if warnings is not None:
-                    warnings.warn(msg)
-                else:
-                    sys.stderr.write(msg + "\n")
-
-            # Now work on the rest of the attributes.  Any attribute that's
-            # not already defined is invalid!
-            for (key, val) in attrs.items():
-                if hasattr(self.metadata, "set_" + key):
-                    getattr(self.metadata, "set_" + key)(val)
-                elif hasattr(self.metadata, key):
-                    setattr(self.metadata, key, val)
-                elif hasattr(self, key):
-                    setattr(self, key, val)
-                else:
-                    msg = "Unknown distribution option: %s" % repr(key)
-                    warnings.warn(msg)
-
-        # no-user-cfg is handled before other command line args
-        # because other args override the config files, and this
-        # one is needed before we can load the config files.
-        # If attrs['script_args'] wasn't passed, assume false.
-        #
-        # This also make sure we just look at the global options
-        self.want_user_cfg = True
-
-        if self.script_args is not None:
-            for arg in self.script_args:
-                if not arg.startswith('-'):
-                    break
-                if arg == '--no-user-cfg':
-                    self.want_user_cfg = False
-                    break
-
-        self.finalize_options()
-
-    def get_option_dict(self, command):
-        """Get the option dictionary for a given command.  If that
-        command's option dictionary hasn't been created yet, then create it
-        and return the new dictionary; otherwise, return the existing
-        option dictionary.
-        """
-        dict = self.command_options.get(command)
-        if dict is None:
-            dict = self.command_options[command] = {}
-        return dict
-
-    def dump_option_dicts(self, header=None, commands=None, indent=""):
-        from pprint import pformat
-
-        if commands is None:             # dump all command option dicts
-            commands = sorted(self.command_options.keys())
-
-        if header is not None:
-            self.announce(indent + header)
-            indent = indent + "  "
-
-        if not commands:
-            self.announce(indent + "no commands known yet")
-            return
-
-        for cmd_name in commands:
-            opt_dict = self.command_options.get(cmd_name)
-            if opt_dict is None:
-                self.announce(indent +
-                              "no option dict for '%s' command" % cmd_name)
-            else:
-                self.announce(indent +
-                              "option dict for '%s' command:" % cmd_name)
-                out = pformat(opt_dict)
-                for line in out.split('\n'):
-                    self.announce(indent + "  " + line)
-
-    # -- Config file finding/parsing methods ---------------------------
-
-    def find_config_files(self):
-        """Find as many configuration files as should be processed for this
-        platform, and return a list of filenames in the order in which they
-        should be parsed.  The filenames returned are guaranteed to exist
-        (modulo nasty race conditions).
-
-        There are three possible config files: distutils.cfg in the
-        Distutils installation directory (ie. where the top-level
-        Distutils __inst__.py file lives), a file in the user's home
-        directory named .pydistutils.cfg on Unix and pydistutils.cfg
-        on Windows/Mac; and setup.cfg in the current directory.
-
-        The file in the user's home directory can be disabled with the
-        --no-user-cfg option.
-        """
-        files = []
-        check_environ()
-
-        # Where to look for the system-wide Distutils config file
-        sys_dir = os.path.dirname(sys.modules['distutils'].__file__)
-
-        # Look for the system config file
-        sys_file = os.path.join(sys_dir, "distutils.cfg")
-        if os.path.isfile(sys_file):
-            files.append(sys_file)
-
-        # What to call the per-user config file
-        if os.name == 'posix':
-            user_filename = ".pydistutils.cfg"
-        else:
-            user_filename = "pydistutils.cfg"
-
-        # And look for the user config file
-        if self.want_user_cfg:
-            user_file = os.path.join(os.path.expanduser('~'), user_filename)
-            if os.path.isfile(user_file):
-                files.append(user_file)
-
-        # All platforms support local setup.cfg
-        local_file = "setup.cfg"
-        if os.path.isfile(local_file):
-            files.append(local_file)
-
-        if DEBUG:
-            self.announce("using config files: %s" % ', '.join(files))
-
-        return files
-
-    def parse_config_files(self, filenames=None):
-        from configparser import ConfigParser
-
-        # Ignore install directory options if we have a venv
-        if sys.prefix != sys.base_prefix:
-            ignore_options = [
-                'install-base', 'install-platbase', 'install-lib',
-                'install-platlib', 'install-purelib', 'install-headers',
-                'install-scripts', 'install-data', 'prefix', 'exec-prefix',
-                'home', 'user', 'root']
-        else:
-            ignore_options = []
-
-        ignore_options = frozenset(ignore_options)
-
-        if filenames is None:
-            filenames = self.find_config_files()
-
-        if DEBUG:
-            self.announce("Distribution.parse_config_files():")
-
-        parser = ConfigParser()
-        for filename in filenames:
-            if DEBUG:
-                self.announce("  reading %s" % filename)
-            parser.read(filename)
-            for section in parser.sections():
-                options = parser.options(section)
-                opt_dict = self.get_option_dict(section)
-
-                for opt in options:
-                    if opt != '__name__' and opt not in ignore_options:
-                        val = parser.get(section,opt)
-                        opt = opt.replace('-', '_')
-                        opt_dict[opt] = (filename, val)
-
-            # Make the ConfigParser forget everything (so we retain
-            # the original filenames that options come from)
-            parser.__init__()
-
-        # If there was a "global" section in the config file, use it
-        # to set Distribution options.
-
-        if 'global' in self.command_options:
-            for (opt, (src, val)) in self.command_options['global'].items():
-                alias = self.negative_opt.get(opt)
-                try:
-                    if alias:
-                        setattr(self, alias, not strtobool(val))
-                    elif opt in ('verbose', 'dry_run'): # ugh!
-                        setattr(self, opt, strtobool(val))
-                    else:
-                        setattr(self, opt, val)
-                except ValueError as msg:
-                    raise DistutilsOptionError(msg)
-
-    # -- Command-line parsing methods ----------------------------------
-
-    def parse_command_line(self):
-        """Parse the setup script's command line, taken from the
-        'script_args' instance attribute (which defaults to 'sys.argv[1:]'
-        -- see 'setup()' in core.py).  This list is first processed for
-        "global options" -- options that set attributes of the Distribution
-        instance.  Then, it is alternately scanned for Distutils commands
-        and options for that command.  Each new command terminates the
-        options for the previous command.  The allowed options for a
-        command are determined by the 'user_options' attribute of the
-        command class -- thus, we have to be able to load command classes
-        in order to parse the command line.  Any error in that 'options'
-        attribute raises DistutilsGetoptError; any error on the
-        command-line raises DistutilsArgError.  If no Distutils commands
-        were found on the command line, raises DistutilsArgError.  Return
-        true if command-line was successfully parsed and we should carry
-        on with executing commands; false if no errors but we shouldn't
-        execute commands (currently, this only happens if user asks for
-        help).
-        """
-        #
-        # We now have enough information to show the Macintosh dialog
-        # that allows the user to interactively specify the "command line".
-        #
-        toplevel_options = self._get_toplevel_options()
-
-        # We have to parse the command line a bit at a time -- global
-        # options, then the first command, then its options, and so on --
-        # because each command will be handled by a different class, and
-        # the options that are valid for a particular class aren't known
-        # until we have loaded the command class, which doesn't happen
-        # until we know what the command is.
-
-        self.commands = []
-        parser = FancyGetopt(toplevel_options + self.display_options)
-        parser.set_negative_aliases(self.negative_opt)
-        parser.set_aliases({'licence': 'license'})
-        args = parser.getopt(args=self.script_args, object=self)
-        option_order = parser.get_option_order()
-        log.set_verbosity(self.verbose)
-
-        # for display options we return immediately
-        if self.handle_display_options(option_order):
-            return
-        while args:
-            args = self._parse_command_opts(parser, args)
-            if args is None:            # user asked for help (and got it)
-                return
-
-        # Handle the cases of --help as a "global" option, ie.
-        # "setup.py --help" and "setup.py --help command ...".  For the
-        # former, we show global options (--verbose, --dry-run, etc.)
-        # and display-only options (--name, --version, etc.); for the
-        # latter, we omit the display-only options and show help for
-        # each command listed on the command line.
-        if self.help:
-            self._show_help(parser,
-                            display_options=len(self.commands) == 0,
-                            commands=self.commands)
-            return
-
-        # Oops, no commands found -- an end-user error
-        if not self.commands:
-            raise DistutilsArgError("no commands supplied")
-
-        # All is well: return true
-        return True
-
-    def _get_toplevel_options(self):
-        """Return the non-display options recognized at the top level.
-
-        This includes options that are recognized *only* at the top
-        level as well as options recognized for commands.
-        """
-        return self.global_options + [
-            ("command-packages=", None,
-             "list of packages that provide distutils commands"),
-            ]
-
-    def _parse_command_opts(self, parser, args):
-        """Parse the command-line options for a single command.
-        'parser' must be a FancyGetopt instance; 'args' must be the list
-        of arguments, starting with the current command (whose options
-        we are about to parse).  Returns a new version of 'args' with
-        the next command at the front of the list; will be the empty
-        list if there are no more commands on the command line.  Returns
-        None if the user asked for help on this command.
-        """
-        # late import because of mutual dependence between these modules
-        from distutils.cmd import Command
-
-        # Pull the current command from the head of the command line
-        command = args[0]
-        if not command_re.match(command):
-            raise SystemExit("invalid command name '%s'" % command)
-        self.commands.append(command)
-
-        # Dig up the command class that implements this command, so we
-        # 1) know that it's a valid command, and 2) know which options
-        # it takes.
-        try:
-            cmd_class = self.get_command_class(command)
-        except DistutilsModuleError as msg:
-            raise DistutilsArgError(msg)
-
-        # Require that the command class be derived from Command -- want
-        # to be sure that the basic "command" interface is implemented.
-        if not issubclass(cmd_class, Command):
-            raise DistutilsClassError(
-                "command class %s must subclass Command" % cmd_class)
-
-        # Also make sure that the command object provides a list of its
-        # known options.
-        if not (hasattr(cmd_class, 'user_options') and
-                isinstance(cmd_class.user_options, list)):
-            msg = ("command class %s must provide "
-                "'user_options' attribute (a list of tuples)")
-            raise DistutilsClassError(msg % cmd_class)
-
-        # If the command class has a list of negative alias options,
-        # merge it in with the global negative aliases.
-        negative_opt = self.negative_opt
-        if hasattr(cmd_class, 'negative_opt'):
-            negative_opt = negative_opt.copy()
-            negative_opt.update(cmd_class.negative_opt)
-
-        # Check for help_options in command class.  They have a different
-        # format (tuple of four) so we need to preprocess them here.
-        if (hasattr(cmd_class, 'help_options') and
-                isinstance(cmd_class.help_options, list)):
-            help_options = fix_help_options(cmd_class.help_options)
-        else:
-            help_options = []
-
-        # All commands support the global options too, just by adding
-        # in 'global_options'.
-        parser.set_option_table(self.global_options +
-                                cmd_class.user_options +
-                                help_options)
-        parser.set_negative_aliases(negative_opt)
-        (args, opts) = parser.getopt(args[1:])
-        if hasattr(opts, 'help') and opts.help:
-            self._show_help(parser, display_options=0, commands=[cmd_class])
-            return
-
-        if (hasattr(cmd_class, 'help_options') and
-                isinstance(cmd_class.help_options, list)):
-            help_option_found=0
-            for (help_option, short, desc, func) in cmd_class.help_options:
-                if hasattr(opts, parser.get_attr_name(help_option)):
-                    help_option_found=1
-                    if callable(func):
-                        func()
-                    else:
-                        raise DistutilsClassError(
-                            "invalid help function %r for help option '%s': "
-                            "must be a callable object (function, etc.)"
-                            % (func, help_option))
-
-            if help_option_found:
-                return
-
-        # Put the options from the command-line into their official
-        # holding pen, the 'command_options' dictionary.
-        opt_dict = self.get_option_dict(command)
-        for (name, value) in vars(opts).items():
-            opt_dict[name] = ("command line", value)
-
-        return args
-
-    def finalize_options(self):
-        """Set final values for all the options on the Distribution
-        instance, analogous to the .finalize_options() method of Command
-        objects.
-        """
-        for attr in ('keywords', 'platforms'):
-            value = getattr(self.metadata, attr)
-            if value is None:
-                continue
-            if isinstance(value, str):
-                value = [elm.strip() for elm in value.split(',')]
-                setattr(self.metadata, attr, value)
-
-    def _show_help(self, parser, global_options=1, display_options=1,
-                   commands=[]):
-        """Show help for the setup script command-line in the form of
-        several lists of command-line options.  'parser' should be a
-        FancyGetopt instance; do not expect it to be returned in the
-        same state, as its option table will be reset to make it
-        generate the correct help text.
-
-        If 'global_options' is true, lists the global options:
-        --verbose, --dry-run, etc.  If 'display_options' is true, lists
-        the "display-only" options: --name, --version, etc.  Finally,
-        lists per-command help for every command name or command class
-        in 'commands'.
-        """
-        # late import because of mutual dependence between these modules
-        from distutils.core import gen_usage
-        from distutils.cmd import Command
-
-        if global_options:
-            if display_options:
-                options = self._get_toplevel_options()
-            else:
-                options = self.global_options
-            parser.set_option_table(options)
-            parser.print_help(self.common_usage + "\nGlobal options:")
-            print('')
-
-        if display_options:
-            parser.set_option_table(self.display_options)
-            parser.print_help(
-                "Information display options (just display " +
-                "information, ignore any commands)")
-            print('')
-
-        for command in self.commands:
-            if isinstance(command, type) and issubclass(command, Command):
-                klass = command
-            else:
-                klass = self.get_command_class(command)
-            if (hasattr(klass, 'help_options') and
-                    isinstance(klass.help_options, list)):
-                parser.set_option_table(klass.user_options +
-                                        fix_help_options(klass.help_options))
-            else:
-                parser.set_option_table(klass.user_options)
-            parser.print_help("Options for '%s' command:" % klass.__name__)
-            print('')
-
-        print(gen_usage(self.script_name))
-
-    def handle_display_options(self, option_order):
-        """If there were any non-global "display-only" options
-        (--help-commands or the metadata display options) on the command
-        line, display the requested info and return true; else return
-        false.
-        """
-        from distutils.core import gen_usage
-
-        # User just wants a list of commands -- we'll print it out and stop
-        # processing now (ie. if they ran "setup --help-commands foo bar",
-        # we ignore "foo bar").
-        if self.help_commands:
-            self.print_commands()
-            print('')
-            print(gen_usage(self.script_name))
-            return 1
-
-        # If user supplied any of the "display metadata" options, then
-        # display that metadata in the order in which the user supplied the
-        # metadata options.
-        any_display_options = 0
-        is_display_option = {}
-        for option in self.display_options:
-            is_display_option[option[0]] = 1
-
-        for (opt, val) in option_order:
-            if val and is_display_option.get(opt):
-                opt = translate_longopt(opt)
-                value = getattr(self.metadata, "get_"+opt)()
-                if opt in ['keywords', 'platforms']:
-                    print(','.join(value))
-                elif opt in ('classifiers', 'provides', 'requires',
-                             'obsoletes'):
-                    print('\n'.join(value))
-                else:
-                    print(value)
-                any_display_options = 1
-
-        return any_display_options
-
-    def print_command_list(self, commands, header, max_length):
-        """Print a subset of the list of all commands -- used by
-        'print_commands()'.
-        """
-        print(header + ":")
-
-        for cmd in commands:
-            klass = self.cmdclass.get(cmd)
-            if not klass:
-                klass = self.get_command_class(cmd)
-            try:
-                description = klass.description
-            except AttributeError:
-                description = "(no description available)"
-
-            print("  %-*s  %s" % (max_length, cmd, description))
-
-    def print_commands(self):
-        """Print out a help message listing all available commands with a
-        description of each.  The list is divided into "standard commands"
-        (listed in distutils.command.__all__) and "extra commands"
-        (mentioned in self.cmdclass, but not a standard command).  The
-        descriptions come from the command class attribute
-        'description'.
-        """
-        import distutils.command
-        std_commands = distutils.command.__all__
-        is_std = {}
-        for cmd in std_commands:
-            is_std[cmd] = 1
-
-        extra_commands = []
-        for cmd in self.cmdclass.keys():
-            if not is_std.get(cmd):
-                extra_commands.append(cmd)
-
-        max_length = 0
-        for cmd in (std_commands + extra_commands):
-            if len(cmd) > max_length:
-                max_length = len(cmd)
-
-        self.print_command_list(std_commands,
-                                "Standard commands",
-                                max_length)
-        if extra_commands:
-            print()
-            self.print_command_list(extra_commands,
-                                    "Extra commands",
-                                    max_length)
-
-    def get_command_list(self):
-        """Get a list of (command, description) tuples.
-        The list is divided into "standard commands" (listed in
-        distutils.command.__all__) and "extra commands" (mentioned in
-        self.cmdclass, but not a standard command).  The descriptions come
-        from the command class attribute 'description'.
-        """
-        # Currently this is only used on Mac OS, for the Mac-only GUI
-        # Distutils interface (by Jack Jansen)
-        import distutils.command
-        std_commands = distutils.command.__all__
-        is_std = {}
-        for cmd in std_commands:
-            is_std[cmd] = 1
-
-        extra_commands = []
-        for cmd in self.cmdclass.keys():
-            if not is_std.get(cmd):
-                extra_commands.append(cmd)
-
-        rv = []
-        for cmd in (std_commands + extra_commands):
-            klass = self.cmdclass.get(cmd)
-            if not klass:
-                klass = self.get_command_class(cmd)
-            try:
-                description = klass.description
-            except AttributeError:
-                description = "(no description available)"
-            rv.append((cmd, description))
-        return rv
-
-    # -- Command class/object methods ----------------------------------
-
-    def get_command_packages(self):
-        """Return a list of packages from which commands are loaded."""
-        pkgs = self.command_packages
-        if not isinstance(pkgs, list):
-            if pkgs is None:
-                pkgs = ''
-            pkgs = [pkg.strip() for pkg in pkgs.split(',') if pkg != '']
-            if "distutils.command" not in pkgs:
-                pkgs.insert(0, "distutils.command")
-            self.command_packages = pkgs
-        return pkgs
-
-    def get_command_class(self, command):
-        """Return the class that implements the Distutils command named by
-        'command'.  First we check the 'cmdclass' dictionary; if the
-        command is mentioned there, we fetch the class object from the
-        dictionary and return it.  Otherwise we load the command module
-        ("distutils.command." + command) and fetch the command class from
-        the module.  The loaded class is also stored in 'cmdclass'
-        to speed future calls to 'get_command_class()'.
-
-        Raises DistutilsModuleError if the expected module could not be
-        found, or if that module does not define the expected class.
-        """
-        klass = self.cmdclass.get(command)
-        if klass:
-            return klass
-
-        for pkgname in self.get_command_packages():
-            module_name = "%s.%s" % (pkgname, command)
-            klass_name = command
-
-            try:
-                __import__(module_name)
-                module = sys.modules[module_name]
-            except ImportError:
-                continue
-
-            try:
-                klass = getattr(module, klass_name)
-            except AttributeError:
-                raise DistutilsModuleError(
-                    "invalid command '%s' (no class '%s' in module '%s')"
-                    % (command, klass_name, module_name))
-
-            self.cmdclass[command] = klass
-            return klass
-
-        raise DistutilsModuleError("invalid command '%s'" % command)
-
-    def get_command_obj(self, command, create=1):
-        """Return the command object for 'command'.  Normally this object
-        is cached on a previous call to 'get_command_obj()'; if no command
-        object for 'command' is in the cache, then we either create and
-        return it (if 'create' is true) or return None.
-        """
-        cmd_obj = self.command_obj.get(command)
-        if not cmd_obj and create:
-            if DEBUG:
-                self.announce("Distribution.get_command_obj(): "
-                              "creating '%s' command object" % command)
-
-            klass = self.get_command_class(command)
-            cmd_obj = self.command_obj[command] = klass(self)
-            self.have_run[command] = 0
-
-            # Set any options that were supplied in config files
-            # or on the command line.  (NB. support for error
-            # reporting is lame here: any errors aren't reported
-            # until 'finalize_options()' is called, which means
-            # we won't report the source of the error.)
-            options = self.command_options.get(command)
-            if options:
-                self._set_command_options(cmd_obj, options)
-
-        return cmd_obj
-
-    def _set_command_options(self, command_obj, option_dict=None):
-        """Set the options for 'command_obj' from 'option_dict'.  Basically
-        this means copying elements of a dictionary ('option_dict') to
-        attributes of an instance ('command').
-
-        'command_obj' must be a Command instance.  If 'option_dict' is not
-        supplied, uses the standard option dictionary for this command
-        (from 'self.command_options').
-        """
-        command_name = command_obj.get_command_name()
-        if option_dict is None:
-            option_dict = self.get_option_dict(command_name)
-
-        if DEBUG:
-            self.announce("  setting options for '%s' command:" % command_name)
-        for (option, (source, value)) in option_dict.items():
-            if DEBUG:
-                self.announce("    %s = %s (from %s)" % (option, value,
-                                                         source))
-            try:
-                bool_opts = [translate_longopt(o)
-                             for o in command_obj.boolean_options]
-            except AttributeError:
-                bool_opts = []
-            try:
-                neg_opt = command_obj.negative_opt
-            except AttributeError:
-                neg_opt = {}
-
-            try:
-                is_string = isinstance(value, str)
-                if option in neg_opt and is_string:
-                    setattr(command_obj, neg_opt[option], not strtobool(value))
-                elif option in bool_opts and is_string:
-                    setattr(command_obj, option, strtobool(value))
-                elif hasattr(command_obj, option):
-                    setattr(command_obj, option, value)
-                else:
-                    raise DistutilsOptionError(
-                        "error in %s: command '%s' has no such option '%s'"
-                        % (source, command_name, option))
-            except ValueError as msg:
-                raise DistutilsOptionError(msg)
-
-    def reinitialize_command(self, command, reinit_subcommands=0):
-        """Reinitializes a command to the state it was in when first
-        returned by 'get_command_obj()': ie., initialized but not yet
-        finalized.  This provides the opportunity to sneak option
-        values in programmatically, overriding or supplementing
-        user-supplied values from the config files and command line.
-        You'll have to re-finalize the command object (by calling
-        'finalize_options()' or 'ensure_finalized()') before using it for
-        real.
-
-        'command' should be a command name (string) or command object.  If
-        'reinit_subcommands' is true, also reinitializes the command's
-        sub-commands, as declared by the 'sub_commands' class attribute (if
-        it has one).  See the "install" command for an example.  Only
-        reinitializes the sub-commands that actually matter, ie. those
-        whose test predicates return true.
-
-        Returns the reinitialized command object.
-        """
-        from distutils.cmd import Command
-        if not isinstance(command, Command):
-            command_name = command
-            command = self.get_command_obj(command_name)
-        else:
-            command_name = command.get_command_name()
-
-        if not command.finalized:
-            return command
-        command.initialize_options()
-        command.finalized = 0
-        self.have_run[command_name] = 0
-        self._set_command_options(command)
-
-        if reinit_subcommands:
-            for sub in command.get_sub_commands():
-                self.reinitialize_command(sub, reinit_subcommands)
-
-        return command
-
-    # -- Methods that operate on the Distribution ----------------------
-
-    def announce(self, msg, level=log.INFO):
-        log.log(level, msg)
-
-    def run_commands(self):
-        """Run each command that was seen on the setup script command line.
-        Uses the list of commands found and cache of command objects
-        created by 'get_command_obj()'.
-        """
-        for cmd in self.commands:
-            self.run_command(cmd)
-
-    # -- Methods that operate on its Commands --------------------------
-
-    def run_command(self, command):
-        """Do whatever it takes to run a command (including nothing at all,
-        if the command has already been run).  Specifically: if we have
-        already created and run the command named by 'command', return
-        silently without doing anything.  If the command named by 'command'
-        doesn't even have a command object yet, create one.  Then invoke
-        'run()' on that command object (or an existing one).
-        """
-        # Already been here, done that? then return silently.
-        if self.have_run.get(command):
-            return
-
-        log.info("running %s", command)
-        cmd_obj = self.get_command_obj(command)
-        cmd_obj.ensure_finalized()
-        cmd_obj.run()
-        self.have_run[command] = 1
-
-    # -- Distribution query methods ------------------------------------
-
-    def has_pure_modules(self):
-        return len(self.packages or self.py_modules or []) > 0
-
-    def has_ext_modules(self):
-        return self.ext_modules and len(self.ext_modules) > 0
-
-    def has_c_libraries(self):
-        return self.libraries and len(self.libraries) > 0
-
-    def has_modules(self):
-        return self.has_pure_modules() or self.has_ext_modules()
-
-    def has_headers(self):
-        return self.headers and len(self.headers) > 0
-
-    def has_scripts(self):
-        return self.scripts and len(self.scripts) > 0
-
-    def has_data_files(self):
-        return self.data_files and len(self.data_files) > 0
-
-    def is_pure(self):
-        return (self.has_pure_modules() and
-                not self.has_ext_modules() and
-                not self.has_c_libraries())
-
-    # -- Metadata query methods ----------------------------------------
-
-    # If you're looking for 'get_name()', 'get_version()', and so forth,
-    # they are defined in a sneaky way: the constructor binds self.get_XXX
-    # to self.metadata.get_XXX.  The actual code is in the
-    # DistributionMetadata class, below.
-
-class DistributionMetadata:
-    """Dummy class to hold the distribution meta-data: name, version,
-    author, and so forth.
-    """
-
-    _METHOD_BASENAMES = ("name", "version", "author", "author_email",
-                         "maintainer", "maintainer_email", "url",
-                         "license", "description", "long_description",
-                         "keywords", "platforms", "fullname", "contact",
-                         "contact_email", "classifiers", "download_url",
-                         # PEP 314
-                         "provides", "requires", "obsoletes",
-                         )
-
-    def __init__(self, path=None):
-        if path is not None:
-            self.read_pkg_file(open(path))
-        else:
-            self.name = None
-            self.version = None
-            self.author = None
-            self.author_email = None
-            self.maintainer = None
-            self.maintainer_email = None
-            self.url = None
-            self.license = None
-            self.description = None
-            self.long_description = None
-            self.keywords = None
-            self.platforms = None
-            self.classifiers = None
-            self.download_url = None
-            # PEP 314
-            self.provides = None
-            self.requires = None
-            self.obsoletes = None
-
-    def read_pkg_file(self, file):
-        """Reads the metadata values from a file object."""
-        msg = message_from_file(file)
-
-        def _read_field(name):
-            value = msg[name]
-            if value == 'UNKNOWN':
-                return None
-            return value
-
-        def _read_list(name):
-            values = msg.get_all(name, None)
-            if values == []:
-                return None
-            return values
-
-        metadata_version = msg['metadata-version']
-        self.name = _read_field('name')
-        self.version = _read_field('version')
-        self.description = _read_field('summary')
-        # we are filling author only.
-        self.author = _read_field('author')
-        self.maintainer = None
-        self.author_email = _read_field('author-email')
-        self.maintainer_email = None
-        self.url = _read_field('home-page')
-        self.license = _read_field('license')
-
-        if 'download-url' in msg:
-            self.download_url = _read_field('download-url')
-        else:
-            self.download_url = None
-
-        self.long_description = _read_field('description')
-        self.description = _read_field('summary')
-
-        if 'keywords' in msg:
-            self.keywords = _read_field('keywords').split(',')
-
-        self.platforms = _read_list('platform')
-        self.classifiers = _read_list('classifier')
-
-        # PEP 314 - these fields only exist in 1.1
-        if metadata_version == '1.1':
-            self.requires = _read_list('requires')
-            self.provides = _read_list('provides')
-            self.obsoletes = _read_list('obsoletes')
-        else:
-            self.requires = None
-            self.provides = None
-            self.obsoletes = None
-
-    def write_pkg_info(self, base_dir):
-        """Write the PKG-INFO file into the release tree.
-        """
-        with open(os.path.join(base_dir, 'PKG-INFO'), 'w',
-                  encoding='UTF-8') as pkg_info:
-            self.write_pkg_file(pkg_info)
-
-    def write_pkg_file(self, file):
-        """Write the PKG-INFO format data to a file object.
-        """
-        version = '1.0'
-        if (self.provides or self.requires or self.obsoletes or
-                self.classifiers or self.download_url):
-            version = '1.1'
-
-        file.write('Metadata-Version: %s\n' % version)
-        file.write('Name: %s\n' % self.get_name())
-        file.write('Version: %s\n' % self.get_version())
-        file.write('Summary: %s\n' % self.get_description())
-        file.write('Home-page: %s\n' % self.get_url())
-        file.write('Author: %s\n' % self.get_contact())
-        file.write('Author-email: %s\n' % self.get_contact_email())
-        file.write('License: %s\n' % self.get_license())
-        if self.download_url:
-            file.write('Download-URL: %s\n' % self.download_url)
-
-        long_desc = rfc822_escape(self.get_long_description())
-        file.write('Description: %s\n' % long_desc)
-
-        keywords = ','.join(self.get_keywords())
-        if keywords:
-            file.write('Keywords: %s\n' % keywords)
-
-        self._write_list(file, 'Platform', self.get_platforms())
-        self._write_list(file, 'Classifier', self.get_classifiers())
-
-        # PEP 314
-        self._write_list(file, 'Requires', self.get_requires())
-        self._write_list(file, 'Provides', self.get_provides())
-        self._write_list(file, 'Obsoletes', self.get_obsoletes())
-
-    def _write_list(self, file, name, values):
-        for value in values:
-            file.write('%s: %s\n' % (name, value))
-
-    # -- Metadata query methods ----------------------------------------
-
-    def get_name(self):
-        return self.name or "UNKNOWN"
-
-    def get_version(self):
-        return self.version or "0.0.0"
-
-    def get_fullname(self):
-        return "%s-%s" % (self.get_name(), self.get_version())
-
-    def get_author(self):
-        return self.author or "UNKNOWN"
-
-    def get_author_email(self):
-        return self.author_email or "UNKNOWN"
-
-    def get_maintainer(self):
-        return self.maintainer or "UNKNOWN"
-
-    def get_maintainer_email(self):
-        return self.maintainer_email or "UNKNOWN"
-
-    def get_contact(self):
-        return self.maintainer or self.author or "UNKNOWN"
-
-    def get_contact_email(self):
-        return self.maintainer_email or self.author_email or "UNKNOWN"
-
-    def get_url(self):
-        return self.url or "UNKNOWN"
-
-    def get_license(self):
-        return self.license or "UNKNOWN"
-    get_licence = get_license
-
-    def get_description(self):
-        return self.description or "UNKNOWN"
-
-    def get_long_description(self):
-        return self.long_description or "UNKNOWN"
-
-    def get_keywords(self):
-        return self.keywords or []
-
-    def set_keywords(self, value):
-        self.keywords = _ensure_list(value, 'keywords')
-
-    def get_platforms(self):
-        return self.platforms or ["UNKNOWN"]
-
-    def set_platforms(self, value):
-        self.platforms = _ensure_list(value, 'platforms')
-
-    def get_classifiers(self):
-        return self.classifiers or []
-
-    def set_classifiers(self, value):
-        self.classifiers = _ensure_list(value, 'classifiers')
-
-    def get_download_url(self):
-        return self.download_url or "UNKNOWN"
-
-    # PEP 314
-    def get_requires(self):
-        return self.requires or []
-
-    def set_requires(self, value):
-        import distutils.versionpredicate
-        for v in value:
-            distutils.versionpredicate.VersionPredicate(v)
-        self.requires = list(value)
-
-    def get_provides(self):
-        return self.provides or []
-
-    def set_provides(self, value):
-        value = [v.strip() for v in value]
-        for v in value:
-            import distutils.versionpredicate
-            distutils.versionpredicate.split_provision(v)
-        self.provides = value
-
-    def get_obsoletes(self):
-        return self.obsoletes or []
-
-    def set_obsoletes(self, value):
-        import distutils.versionpredicate
-        for v in value:
-            distutils.versionpredicate.VersionPredicate(v)
-        self.obsoletes = list(value)
-
-def fix_help_options(options):
-    """Convert a 4-tuple 'help_options' list as found in various command
-    classes to the 3-tuple form required by FancyGetopt.
-    """
-    new_options = []
-    for help_tuple in options:
-        new_options.append(help_tuple[0:3])
-    return new_options
diff --git a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/setuptools/msvc.py b/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/setuptools/msvc.py
deleted file mode 100644
index 281ea1c2af6b0eb5f02ecc6d115f2d6884be74b5..0000000000000000000000000000000000000000
--- a/spaces/profayle/TerrapinTalk/myenv/lib/python3.9/site-packages/setuptools/msvc.py
+++ /dev/null
@@ -1,1805 +0,0 @@
-"""
-Improved support for Microsoft Visual C++ compilers.
-
-Known supported compilers:
---------------------------
-Microsoft Visual C++ 9.0:
-    Microsoft Visual C++ Compiler for Python 2.7 (x86, amd64)
-    Microsoft Windows SDK 6.1 (x86, x64, ia64)
-    Microsoft Windows SDK 7.0 (x86, x64, ia64)
-
-Microsoft Visual C++ 10.0:
-    Microsoft Windows SDK 7.1 (x86, x64, ia64)
-
-Microsoft Visual C++ 14.X:
-    Microsoft Visual C++ Build Tools 2015 (x86, x64, arm)
-    Microsoft Visual Studio Build Tools 2017 (x86, x64, arm, arm64)
-    Microsoft Visual Studio Build Tools 2019 (x86, x64, arm, arm64)
-
-This may also support compilers shipped with compatible Visual Studio versions.
-"""
-
-import json
-from io import open
-from os import listdir, pathsep
-from os.path import join, isfile, isdir, dirname
-import sys
-import contextlib
-import platform
-import itertools
-import subprocess
-import distutils.errors
-from setuptools.extern.packaging.version import LegacyVersion
-from setuptools.extern.more_itertools import unique_everseen
-
-from .monkey import get_unpatched
-
-if platform.system() == 'Windows':
-    import winreg
-    from os import environ
-else:
-    # Mock winreg and environ so the module can be imported on this platform.
-
-    class winreg:
-        HKEY_USERS = None
-        HKEY_CURRENT_USER = None
-        HKEY_LOCAL_MACHINE = None
-        HKEY_CLASSES_ROOT = None
-
-    environ = dict()
-
-_msvc9_suppress_errors = (
-    # msvc9compiler isn't available on some platforms
-    ImportError,
-
-    # msvc9compiler raises DistutilsPlatformError in some
-    # environments. See #1118.
-    distutils.errors.DistutilsPlatformError,
-)
-
-try:
-    from distutils.msvc9compiler import Reg
-except _msvc9_suppress_errors:
-    pass
-
-
-def msvc9_find_vcvarsall(version):
-    """
-    Patched "distutils.msvc9compiler.find_vcvarsall" to use the standalone
-    compiler build for Python
-    (VCForPython / Microsoft Visual C++ Compiler for Python 2.7).
-
-    Fall back to original behavior when the standalone compiler is not
-    available.
-
-    Redirect the path of "vcvarsall.bat".
-
-    Parameters
-    ----------
-    version: float
-        Required Microsoft Visual C++ version.
-
-    Return
-    ------
-    str
-        vcvarsall.bat path
-    """
-    vc_base = r'Software\%sMicrosoft\DevDiv\VCForPython\%0.1f'
-    key = vc_base % ('', version)
-    try:
-        # Per-user installs register the compiler path here
-        productdir = Reg.get_value(key, "installdir")
-    except KeyError:
-        try:
-            # All-user installs on a 64-bit system register here
-            key = vc_base % ('Wow6432Node\\', version)
-            productdir = Reg.get_value(key, "installdir")
-        except KeyError:
-            productdir = None
-
-    if productdir:
-        vcvarsall = join(productdir, "vcvarsall.bat")
-        if isfile(vcvarsall):
-            return vcvarsall
-
-    return get_unpatched(msvc9_find_vcvarsall)(version)
-
-
-def msvc9_query_vcvarsall(ver, arch='x86', *args, **kwargs):
-    """
-    Patched "distutils.msvc9compiler.query_vcvarsall" for support extra
-    Microsoft Visual C++ 9.0 and 10.0 compilers.
-
-    Set environment without use of "vcvarsall.bat".
-
-    Parameters
-    ----------
-    ver: float
-        Required Microsoft Visual C++ version.
-    arch: str
-        Target architecture.
-
-    Return
-    ------
-    dict
-        environment
-    """
-    # Try to get environment from vcvarsall.bat (Classical way)
-    try:
-        orig = get_unpatched(msvc9_query_vcvarsall)
-        return orig(ver, arch, *args, **kwargs)
-    except distutils.errors.DistutilsPlatformError:
-        # Pass error if Vcvarsall.bat is missing
-        pass
-    except ValueError:
-        # Pass error if environment not set after executing vcvarsall.bat
-        pass
-
-    # If error, try to set environment directly
-    try:
-        return EnvironmentInfo(arch, ver).return_env()
-    except distutils.errors.DistutilsPlatformError as exc:
-        _augment_exception(exc, ver, arch)
-        raise
-
-
-def _msvc14_find_vc2015():
-    """Python 3.8 "distutils/_msvccompiler.py" backport"""
-    try:
-        key = winreg.OpenKey(
-            winreg.HKEY_LOCAL_MACHINE,
-            r"Software\Microsoft\VisualStudio\SxS\VC7",
-            0,
-            winreg.KEY_READ | winreg.KEY_WOW64_32KEY
-        )
-    except OSError:
-        return None, None
-
-    best_version = 0
-    best_dir = None
-    with key:
-        for i in itertools.count():
-            try:
-                v, vc_dir, vt = winreg.EnumValue(key, i)
-            except OSError:
-                break
-            if v and vt == winreg.REG_SZ and isdir(vc_dir):
-                try:
-                    version = int(float(v))
-                except (ValueError, TypeError):
-                    continue
-                if version >= 14 and version > best_version:
-                    best_version, best_dir = version, vc_dir
-    return best_version, best_dir
-
-
-def _msvc14_find_vc2017():
-    """Python 3.8 "distutils/_msvccompiler.py" backport
-
-    Returns "15, path" based on the result of invoking vswhere.exe
-    If no install is found, returns "None, None"
-
-    The version is returned to avoid unnecessarily changing the function
-    result. It may be ignored when the path is not None.
-
-    If vswhere.exe is not available, by definition, VS 2017 is not
-    installed.
-    """
-    root = environ.get("ProgramFiles(x86)") or environ.get("ProgramFiles")
-    if not root:
-        return None, None
-
-    try:
-        path = subprocess.check_output([
-            join(root, "Microsoft Visual Studio", "Installer", "vswhere.exe"),
-            "-latest",
-            "-prerelease",
-            "-requiresAny",
-            "-requires", "Microsoft.VisualStudio.Component.VC.Tools.x86.x64",
-            "-requires", "Microsoft.VisualStudio.Workload.WDExpress",
-            "-property", "installationPath",
-            "-products", "*",
-        ]).decode(encoding="mbcs", errors="strict").strip()
-    except (subprocess.CalledProcessError, OSError, UnicodeDecodeError):
-        return None, None
-
-    path = join(path, "VC", "Auxiliary", "Build")
-    if isdir(path):
-        return 15, path
-
-    return None, None
-
-
-PLAT_SPEC_TO_RUNTIME = {
-    'x86': 'x86',
-    'x86_amd64': 'x64',
-    'x86_arm': 'arm',
-    'x86_arm64': 'arm64'
-}
-
-
-def _msvc14_find_vcvarsall(plat_spec):
-    """Python 3.8 "distutils/_msvccompiler.py" backport"""
-    _, best_dir = _msvc14_find_vc2017()
-    vcruntime = None
-
-    if plat_spec in PLAT_SPEC_TO_RUNTIME:
-        vcruntime_plat = PLAT_SPEC_TO_RUNTIME[plat_spec]
-    else:
-        vcruntime_plat = 'x64' if 'amd64' in plat_spec else 'x86'
-
-    if best_dir:
-        vcredist = join(best_dir, "..", "..", "redist", "MSVC", "**",
-                        vcruntime_plat, "Microsoft.VC14*.CRT",
-                        "vcruntime140.dll")
-        try:
-            import glob
-            vcruntime = glob.glob(vcredist, recursive=True)[-1]
-        except (ImportError, OSError, LookupError):
-            vcruntime = None
-
-    if not best_dir:
-        best_version, best_dir = _msvc14_find_vc2015()
-        if best_version:
-            vcruntime = join(best_dir, 'redist', vcruntime_plat,
-                             "Microsoft.VC140.CRT", "vcruntime140.dll")
-
-    if not best_dir:
-        return None, None
-
-    vcvarsall = join(best_dir, "vcvarsall.bat")
-    if not isfile(vcvarsall):
-        return None, None
-
-    if not vcruntime or not isfile(vcruntime):
-        vcruntime = None
-
-    return vcvarsall, vcruntime
-
-
-def _msvc14_get_vc_env(plat_spec):
-    """Python 3.8 "distutils/_msvccompiler.py" backport"""
-    if "DISTUTILS_USE_SDK" in environ:
-        return {
-            key.lower(): value
-            for key, value in environ.items()
-        }
-
-    vcvarsall, vcruntime = _msvc14_find_vcvarsall(plat_spec)
-    if not vcvarsall:
-        raise distutils.errors.DistutilsPlatformError(
-            "Unable to find vcvarsall.bat"
-        )
-
-    try:
-        out = subprocess.check_output(
-            'cmd /u /c "{}" {} && set'.format(vcvarsall, plat_spec),
-            stderr=subprocess.STDOUT,
-        ).decode('utf-16le', errors='replace')
-    except subprocess.CalledProcessError as exc:
-        raise distutils.errors.DistutilsPlatformError(
-            "Error executing {}".format(exc.cmd)
-        ) from exc
-
-    env = {
-        key.lower(): value
-        for key, _, value in
-        (line.partition('=') for line in out.splitlines())
-        if key and value
-    }
-
-    if vcruntime:
-        env['py_vcruntime_redist'] = vcruntime
-    return env
-
-
-def msvc14_get_vc_env(plat_spec):
-    """
-    Patched "distutils._msvccompiler._get_vc_env" for support extra
-    Microsoft Visual C++ 14.X compilers.
-
-    Set environment without use of "vcvarsall.bat".
-
-    Parameters
-    ----------
-    plat_spec: str
-        Target architecture.
-
-    Return
-    ------
-    dict
-        environment
-    """
-
-    # Always use backport from CPython 3.8
-    try:
-        return _msvc14_get_vc_env(plat_spec)
-    except distutils.errors.DistutilsPlatformError as exc:
-        _augment_exception(exc, 14.0)
-        raise
-
-
-def msvc14_gen_lib_options(*args, **kwargs):
-    """
-    Patched "distutils._msvccompiler.gen_lib_options" for fix
-    compatibility between "numpy.distutils" and "distutils._msvccompiler"
-    (for Numpy < 1.11.2)
-    """
-    if "numpy.distutils" in sys.modules:
-        import numpy as np
-        if LegacyVersion(np.__version__) < LegacyVersion('1.11.2'):
-            return np.distutils.ccompiler.gen_lib_options(*args, **kwargs)
-    return get_unpatched(msvc14_gen_lib_options)(*args, **kwargs)
-
-
-def _augment_exception(exc, version, arch=''):
-    """
-    Add details to the exception message to help guide the user
-    as to what action will resolve it.
-    """
-    # Error if MSVC++ directory not found or environment not set
-    message = exc.args[0]
-
-    if "vcvarsall" in message.lower() or "visual c" in message.lower():
-        # Special error message if MSVC++ not installed
-        tmpl = 'Microsoft Visual C++ {version:0.1f} or greater is required.'
-        message = tmpl.format(**locals())
-        msdownload = 'www.microsoft.com/download/details.aspx?id=%d'
-        if version == 9.0:
-            if arch.lower().find('ia64') > -1:
-                # For VC++ 9.0, if IA64 support is needed, redirect user
-                # to Windows SDK 7.0.
-                # Note: No download link available from Microsoft.
-                message += ' Get it with "Microsoft Windows SDK 7.0"'
-            else:
-                # For VC++ 9.0 redirect user to Vc++ for Python 2.7 :
-                # This redirection link is maintained by Microsoft.
-                # Contact vspython@microsoft.com if it needs updating.
-                message += ' Get it from http://aka.ms/vcpython27'
-        elif version == 10.0:
-            # For VC++ 10.0 Redirect user to Windows SDK 7.1
-            message += ' Get it with "Microsoft Windows SDK 7.1": '
-            message += msdownload % 8279
-        elif version >= 14.0:
-            # For VC++ 14.X Redirect user to latest Visual C++ Build Tools
-            message += (' Get it with "Microsoft C++ Build Tools": '
-                        r'https://visualstudio.microsoft.com'
-                        r'/visual-cpp-build-tools/')
-
-    exc.args = (message, )
-
-
-class PlatformInfo:
-    """
-    Current and Target Architectures information.
-
-    Parameters
-    ----------
-    arch: str
-        Target architecture.
-    """
-    current_cpu = environ.get('processor_architecture', '').lower()
-
-    def __init__(self, arch):
-        self.arch = arch.lower().replace('x64', 'amd64')
-
-    @property
-    def target_cpu(self):
-        """
-        Return Target CPU architecture.
-
-        Return
-        ------
-        str
-            Target CPU
-        """
-        return self.arch[self.arch.find('_') + 1:]
-
-    def target_is_x86(self):
-        """
-        Return True if target CPU is x86 32 bits..
-
-        Return
-        ------
-        bool
-            CPU is x86 32 bits
-        """
-        return self.target_cpu == 'x86'
-
-    def current_is_x86(self):
-        """
-        Return True if current CPU is x86 32 bits..
-
-        Return
-        ------
-        bool
-            CPU is x86 32 bits
-        """
-        return self.current_cpu == 'x86'
-
-    def current_dir(self, hidex86=False, x64=False):
-        """
-        Current platform specific subfolder.
-
-        Parameters
-        ----------
-        hidex86: bool
-            return '' and not '\x86' if architecture is x86.
-        x64: bool
-            return '\x64' and not '\amd64' if architecture is amd64.
-
-        Return
-        ------
-        str
-            subfolder: '\target', or '' (see hidex86 parameter)
-        """
-        return (
-            '' if (self.current_cpu == 'x86' and hidex86) else
-            r'\x64' if (self.current_cpu == 'amd64' and x64) else
-            r'\%s' % self.current_cpu
-        )
-
-    def target_dir(self, hidex86=False, x64=False):
-        r"""
-        Target platform specific subfolder.
-
-        Parameters
-        ----------
-        hidex86: bool
-            return '' and not '\x86' if architecture is x86.
-        x64: bool
-            return '\x64' and not '\amd64' if architecture is amd64.
-
-        Return
-        ------
-        str
-            subfolder: '\current', or '' (see hidex86 parameter)
-        """
-        return (
-            '' if (self.target_cpu == 'x86' and hidex86) else
-            r'\x64' if (self.target_cpu == 'amd64' and x64) else
-            r'\%s' % self.target_cpu
-        )
-
-    def cross_dir(self, forcex86=False):
-        r"""
-        Cross platform specific subfolder.
-
-        Parameters
-        ----------
-        forcex86: bool
-            Use 'x86' as current architecture even if current architecture is
-            not x86.
-
-        Return
-        ------
-        str
-            subfolder: '' if target architecture is current architecture,
-            '\current_target' if not.
-        """
-        current = 'x86' if forcex86 else self.current_cpu
-        return (
-            '' if self.target_cpu == current else
-            self.target_dir().replace('\\', '\\%s_' % current)
-        )
-
-
-class RegistryInfo:
-    """
-    Microsoft Visual Studio related registry information.
-
-    Parameters
-    ----------
-    platform_info: PlatformInfo
-        "PlatformInfo" instance.
-    """
-    HKEYS = (winreg.HKEY_USERS,
-             winreg.HKEY_CURRENT_USER,
-             winreg.HKEY_LOCAL_MACHINE,
-             winreg.HKEY_CLASSES_ROOT)
-
-    def __init__(self, platform_info):
-        self.pi = platform_info
-
-    @property
-    def visualstudio(self):
-        """
-        Microsoft Visual Studio root registry key.
-
-        Return
-        ------
-        str
-            Registry key
-        """
-        return 'VisualStudio'
-
-    @property
-    def sxs(self):
-        """
-        Microsoft Visual Studio SxS registry key.
-
-        Return
-        ------
-        str
-            Registry key
-        """
-        return join(self.visualstudio, 'SxS')
-
-    @property
-    def vc(self):
-        """
-        Microsoft Visual C++ VC7 registry key.
-
-        Return
-        ------
-        str
-            Registry key
-        """
-        return join(self.sxs, 'VC7')
-
-    @property
-    def vs(self):
-        """
-        Microsoft Visual Studio VS7 registry key.
-
-        Return
-        ------
-        str
-            Registry key
-        """
-        return join(self.sxs, 'VS7')
-
-    @property
-    def vc_for_python(self):
-        """
-        Microsoft Visual C++ for Python registry key.
-
-        Return
-        ------
-        str
-            Registry key
-        """
-        return r'DevDiv\VCForPython'
-
-    @property
-    def microsoft_sdk(self):
-        """
-        Microsoft SDK registry key.
-
-        Return
-        ------
-        str
-            Registry key
-        """
-        return 'Microsoft SDKs'
-
-    @property
-    def windows_sdk(self):
-        """
-        Microsoft Windows/Platform SDK registry key.
-
-        Return
-        ------
-        str
-            Registry key
-        """
-        return join(self.microsoft_sdk, 'Windows')
-
-    @property
-    def netfx_sdk(self):
-        """
-        Microsoft .NET Framework SDK registry key.
-
-        Return
-        ------
-        str
-            Registry key
-        """
-        return join(self.microsoft_sdk, 'NETFXSDK')
-
-    @property
-    def windows_kits_roots(self):
-        """
-        Microsoft Windows Kits Roots registry key.
-
-        Return
-        ------
-        str
-            Registry key
-        """
-        return r'Windows Kits\Installed Roots'
-
-    def microsoft(self, key, x86=False):
-        """
-        Return key in Microsoft software registry.
-
-        Parameters
-        ----------
-        key: str
-            Registry key path where look.
-        x86: str
-            Force x86 software registry.
-
-        Return
-        ------
-        str
-            Registry key
-        """
-        node64 = '' if self.pi.current_is_x86() or x86 else 'Wow6432Node'
-        return join('Software', node64, 'Microsoft', key)
-
-    def lookup(self, key, name):
-        """
-        Look for values in registry in Microsoft software registry.
-
-        Parameters
-        ----------
-        key: str
-            Registry key path where look.
-        name: str
-            Value name to find.
-
-        Return
-        ------
-        str
-            value
-        """
-        key_read = winreg.KEY_READ
-        openkey = winreg.OpenKey
-        closekey = winreg.CloseKey
-        ms = self.microsoft
-        for hkey in self.HKEYS:
-            bkey = None
-            try:
-                bkey = openkey(hkey, ms(key), 0, key_read)
-            except (OSError, IOError):
-                if not self.pi.current_is_x86():
-                    try:
-                        bkey = openkey(hkey, ms(key, True), 0, key_read)
-                    except (OSError, IOError):
-                        continue
-                else:
-                    continue
-            try:
-                return winreg.QueryValueEx(bkey, name)[0]
-            except (OSError, IOError):
-                pass
-            finally:
-                if bkey:
-                    closekey(bkey)
-
-
-class SystemInfo:
-    """
-    Microsoft Windows and Visual Studio related system information.
-
-    Parameters
-    ----------
-    registry_info: RegistryInfo
-        "RegistryInfo" instance.
-    vc_ver: float
-        Required Microsoft Visual C++ version.
-    """
-
-    # Variables and properties in this class use originals CamelCase variables
-    # names from Microsoft source files for more easy comparison.
-    WinDir = environ.get('WinDir', '')
-    ProgramFiles = environ.get('ProgramFiles', '')
-    ProgramFilesx86 = environ.get('ProgramFiles(x86)', ProgramFiles)
-
-    def __init__(self, registry_info, vc_ver=None):
-        self.ri = registry_info
-        self.pi = self.ri.pi
-
-        self.known_vs_paths = self.find_programdata_vs_vers()
-
-        # Except for VS15+, VC version is aligned with VS version
-        self.vs_ver = self.vc_ver = (
-            vc_ver or self._find_latest_available_vs_ver())
-
-    def _find_latest_available_vs_ver(self):
-        """
-        Find the latest VC version
-
-        Return
-        ------
-        float
-            version
-        """
-        reg_vc_vers = self.find_reg_vs_vers()
-
-        if not (reg_vc_vers or self.known_vs_paths):
-            raise distutils.errors.DistutilsPlatformError(
-                'No Microsoft Visual C++ version found')
-
-        vc_vers = set(reg_vc_vers)
-        vc_vers.update(self.known_vs_paths)
-        return sorted(vc_vers)[-1]
-
-    def find_reg_vs_vers(self):
-        """
-        Find Microsoft Visual Studio versions available in registry.
-
-        Return
-        ------
-        list of float
-            Versions
-        """
-        ms = self.ri.microsoft
-        vckeys = (self.ri.vc, self.ri.vc_for_python, self.ri.vs)
-        vs_vers = []
-        for hkey, key in itertools.product(self.ri.HKEYS, vckeys):
-            try:
-                bkey = winreg.OpenKey(hkey, ms(key), 0, winreg.KEY_READ)
-            except (OSError, IOError):
-                continue
-            with bkey:
-                subkeys, values, _ = winreg.QueryInfoKey(bkey)
-                for i in range(values):
-                    with contextlib.suppress(ValueError):
-                        ver = float(winreg.EnumValue(bkey, i)[0])
-                        if ver not in vs_vers:
-                            vs_vers.append(ver)
-                for i in range(subkeys):
-                    with contextlib.suppress(ValueError):
-                        ver = float(winreg.EnumKey(bkey, i))
-                        if ver not in vs_vers:
-                            vs_vers.append(ver)
-        return sorted(vs_vers)
-
-    def find_programdata_vs_vers(self):
-        r"""
-        Find Visual studio 2017+ versions from information in
-        "C:\ProgramData\Microsoft\VisualStudio\Packages\_Instances".
-
-        Return
-        ------
-        dict
-            float version as key, path as value.
-        """
-        vs_versions = {}
-        instances_dir = \
-            r'C:\ProgramData\Microsoft\VisualStudio\Packages\_Instances'
-
-        try:
-            hashed_names = listdir(instances_dir)
-
-        except (OSError, IOError):
-            # Directory not exists with all Visual Studio versions
-            return vs_versions
-
-        for name in hashed_names:
-            try:
-                # Get VS installation path from "state.json" file
-                state_path = join(instances_dir, name, 'state.json')
-                with open(state_path, 'rt', encoding='utf-8') as state_file:
-                    state = json.load(state_file)
-                vs_path = state['installationPath']
-
-                # Raises OSError if this VS installation does not contain VC
-                listdir(join(vs_path, r'VC\Tools\MSVC'))
-
-                # Store version and path
-                vs_versions[self._as_float_version(
-                    state['installationVersion'])] = vs_path
-
-            except (OSError, IOError, KeyError):
-                # Skip if "state.json" file is missing or bad format
-                continue
-
-        return vs_versions
-
-    @staticmethod
-    def _as_float_version(version):
-        """
-        Return a string version as a simplified float version (major.minor)
-
-        Parameters
-        ----------
-        version: str
-            Version.
-
-        Return
-        ------
-        float
-            version
-        """
-        return float('.'.join(version.split('.')[:2]))
-
-    @property
-    def VSInstallDir(self):
-        """
-        Microsoft Visual Studio directory.
-
-        Return
-        ------
-        str
-            path
-        """
-        # Default path
-        default = join(self.ProgramFilesx86,
-                       'Microsoft Visual Studio %0.1f' % self.vs_ver)
-
-        # Try to get path from registry, if fail use default path
-        return self.ri.lookup(self.ri.vs, '%0.1f' % self.vs_ver) or default
-
-    @property
-    def VCInstallDir(self):
-        """
-        Microsoft Visual C++ directory.
-
-        Return
-        ------
-        str
-            path
-        """
-        path = self._guess_vc() or self._guess_vc_legacy()
-
-        if not isdir(path):
-            msg = 'Microsoft Visual C++ directory not found'
-            raise distutils.errors.DistutilsPlatformError(msg)
-
-        return path
-
-    def _guess_vc(self):
-        """
-        Locate Visual C++ for VS2017+.
-
-        Return
-        ------
-        str
-            path
-        """
-        if self.vs_ver <= 14.0:
-            return ''
-
-        try:
-            # First search in known VS paths
-            vs_dir = self.known_vs_paths[self.vs_ver]
-        except KeyError:
-            # Else, search with path from registry
-            vs_dir = self.VSInstallDir
-
-        guess_vc = join(vs_dir, r'VC\Tools\MSVC')
-
-        # Subdir with VC exact version as name
-        try:
-            # Update the VC version with real one instead of VS version
-            vc_ver = listdir(guess_vc)[-1]
-            self.vc_ver = self._as_float_version(vc_ver)
-            return join(guess_vc, vc_ver)
-        except (OSError, IOError, IndexError):
-            return ''
-
-    def _guess_vc_legacy(self):
-        """
-        Locate Visual C++ for versions prior to 2017.
-
-        Return
-        ------
-        str
-            path
-        """
-        default = join(self.ProgramFilesx86,
-                       r'Microsoft Visual Studio %0.1f\VC' % self.vs_ver)
-
-        # Try to get "VC++ for Python" path from registry as default path
-        reg_path = join(self.ri.vc_for_python, '%0.1f' % self.vs_ver)
-        python_vc = self.ri.lookup(reg_path, 'installdir')
-        default_vc = join(python_vc, 'VC') if python_vc else default
-
-        # Try to get path from registry, if fail use default path
-        return self.ri.lookup(self.ri.vc, '%0.1f' % self.vs_ver) or default_vc
-
-    @property
-    def WindowsSdkVersion(self):
-        """
-        Microsoft Windows SDK versions for specified MSVC++ version.
-
-        Return
-        ------
-        tuple of str
-            versions
-        """
-        if self.vs_ver <= 9.0:
-            return '7.0', '6.1', '6.0a'
-        elif self.vs_ver == 10.0:
-            return '7.1', '7.0a'
-        elif self.vs_ver == 11.0:
-            return '8.0', '8.0a'
-        elif self.vs_ver == 12.0:
-            return '8.1', '8.1a'
-        elif self.vs_ver >= 14.0:
-            return '10.0', '8.1'
-
-    @property
-    def WindowsSdkLastVersion(self):
-        """
-        Microsoft Windows SDK last version.
-
-        Return
-        ------
-        str
-            version
-        """
-        return self._use_last_dir_name(join(self.WindowsSdkDir, 'lib'))
-
-    @property  # noqa: C901
-    def WindowsSdkDir(self):  # noqa: C901  # is too complex (12)  # FIXME
-        """
-        Microsoft Windows SDK directory.
-
-        Return
-        ------
-        str
-            path
-        """
-        sdkdir = ''
-        for ver in self.WindowsSdkVersion:
-            # Try to get it from registry
-            loc = join(self.ri.windows_sdk, 'v%s' % ver)
-            sdkdir = self.ri.lookup(loc, 'installationfolder')
-            if sdkdir:
-                break
-        if not sdkdir or not isdir(sdkdir):
-            # Try to get "VC++ for Python" version from registry
-            path = join(self.ri.vc_for_python, '%0.1f' % self.vc_ver)
-            install_base = self.ri.lookup(path, 'installdir')
-            if install_base:
-                sdkdir = join(install_base, 'WinSDK')
-        if not sdkdir or not isdir(sdkdir):
-            # If fail, use default new path
-            for ver in self.WindowsSdkVersion:
-                intver = ver[:ver.rfind('.')]
-                path = r'Microsoft SDKs\Windows Kits\%s' % intver
-                d = join(self.ProgramFiles, path)
-                if isdir(d):
-                    sdkdir = d
-        if not sdkdir or not isdir(sdkdir):
-            # If fail, use default old path
-            for ver in self.WindowsSdkVersion:
-                path = r'Microsoft SDKs\Windows\v%s' % ver
-                d = join(self.ProgramFiles, path)
-                if isdir(d):
-                    sdkdir = d
-        if not sdkdir:
-            # If fail, use Platform SDK
-            sdkdir = join(self.VCInstallDir, 'PlatformSDK')
-        return sdkdir
-
-    @property
-    def WindowsSDKExecutablePath(self):
-        """
-        Microsoft Windows SDK executable directory.
-
-        Return
-        ------
-        str
-            path
-        """
-        # Find WinSDK NetFx Tools registry dir name
-        if self.vs_ver <= 11.0:
-            netfxver = 35
-            arch = ''
-        else:
-            netfxver = 40
-            hidex86 = True if self.vs_ver <= 12.0 else False
-            arch = self.pi.current_dir(x64=True, hidex86=hidex86)
-        fx = 'WinSDK-NetFx%dTools%s' % (netfxver, arch.replace('\\', '-'))
-
-        # list all possibles registry paths
-        regpaths = []
-        if self.vs_ver >= 14.0:
-            for ver in self.NetFxSdkVersion:
-                regpaths += [join(self.ri.netfx_sdk, ver, fx)]
-
-        for ver in self.WindowsSdkVersion:
-            regpaths += [join(self.ri.windows_sdk, 'v%sA' % ver, fx)]
-
-        # Return installation folder from the more recent path
-        for path in regpaths:
-            execpath = self.ri.lookup(path, 'installationfolder')
-            if execpath:
-                return execpath
-
-    @property
-    def FSharpInstallDir(self):
-        """
-        Microsoft Visual F# directory.
-
-        Return
-        ------
-        str
-            path
-        """
-        path = join(self.ri.visualstudio, r'%0.1f\Setup\F#' % self.vs_ver)
-        return self.ri.lookup(path, 'productdir') or ''
-
-    @property
-    def UniversalCRTSdkDir(self):
-        """
-        Microsoft Universal CRT SDK directory.
-
-        Return
-        ------
-        str
-            path
-        """
-        # Set Kit Roots versions for specified MSVC++ version
-        vers = ('10', '81') if self.vs_ver >= 14.0 else ()
-
-        # Find path of the more recent Kit
-        for ver in vers:
-            sdkdir = self.ri.lookup(self.ri.windows_kits_roots,
-                                    'kitsroot%s' % ver)
-            if sdkdir:
-                return sdkdir or ''
-
-    @property
-    def UniversalCRTSdkLastVersion(self):
-        """
-        Microsoft Universal C Runtime SDK last version.
-
-        Return
-        ------
-        str
-            version
-        """
-        return self._use_last_dir_name(join(self.UniversalCRTSdkDir, 'lib'))
-
-    @property
-    def NetFxSdkVersion(self):
-        """
-        Microsoft .NET Framework SDK versions.
-
-        Return
-        ------
-        tuple of str
-            versions
-        """
-        # Set FxSdk versions for specified VS version
-        return (('4.7.2', '4.7.1', '4.7',
-                 '4.6.2', '4.6.1', '4.6',
-                 '4.5.2', '4.5.1', '4.5')
-                if self.vs_ver >= 14.0 else ())
-
-    @property
-    def NetFxSdkDir(self):
-        """
-        Microsoft .NET Framework SDK directory.
-
-        Return
-        ------
-        str
-            path
-        """
-        sdkdir = ''
-        for ver in self.NetFxSdkVersion:
-            loc = join(self.ri.netfx_sdk, ver)
-            sdkdir = self.ri.lookup(loc, 'kitsinstallationfolder')
-            if sdkdir:
-                break
-        return sdkdir
-
-    @property
-    def FrameworkDir32(self):
-        """
-        Microsoft .NET Framework 32bit directory.
-
-        Return
-        ------
-        str
-            path
-        """
-        # Default path
-        guess_fw = join(self.WinDir, r'Microsoft.NET\Framework')
-
-        # Try to get path from registry, if fail use default path
-        return self.ri.lookup(self.ri.vc, 'frameworkdir32') or guess_fw
-
-    @property
-    def FrameworkDir64(self):
-        """
-        Microsoft .NET Framework 64bit directory.
-
-        Return
-        ------
-        str
-            path
-        """
-        # Default path
-        guess_fw = join(self.WinDir, r'Microsoft.NET\Framework64')
-
-        # Try to get path from registry, if fail use default path
-        return self.ri.lookup(self.ri.vc, 'frameworkdir64') or guess_fw
-
-    @property
-    def FrameworkVersion32(self):
-        """
-        Microsoft .NET Framework 32bit versions.
-
-        Return
-        ------
-        tuple of str
-            versions
-        """
-        return self._find_dot_net_versions(32)
-
-    @property
-    def FrameworkVersion64(self):
-        """
-        Microsoft .NET Framework 64bit versions.
-
-        Return
-        ------
-        tuple of str
-            versions
-        """
-        return self._find_dot_net_versions(64)
-
-    def _find_dot_net_versions(self, bits):
-        """
-        Find Microsoft .NET Framework versions.
-
-        Parameters
-        ----------
-        bits: int
-            Platform number of bits: 32 or 64.
-
-        Return
-        ------
-        tuple of str
-            versions
-        """
-        # Find actual .NET version in registry
-        reg_ver = self.ri.lookup(self.ri.vc, 'frameworkver%d' % bits)
-        dot_net_dir = getattr(self, 'FrameworkDir%d' % bits)
-        ver = reg_ver or self._use_last_dir_name(dot_net_dir, 'v') or ''
-
-        # Set .NET versions for specified MSVC++ version
-        if self.vs_ver >= 12.0:
-            return ver, 'v4.0'
-        elif self.vs_ver >= 10.0:
-            return 'v4.0.30319' if ver.lower()[:2] != 'v4' else ver, 'v3.5'
-        elif self.vs_ver == 9.0:
-            return 'v3.5', 'v2.0.50727'
-        elif self.vs_ver == 8.0:
-            return 'v3.0', 'v2.0.50727'
-
-    @staticmethod
-    def _use_last_dir_name(path, prefix=''):
-        """
-        Return name of the last dir in path or '' if no dir found.
-
-        Parameters
-        ----------
-        path: str
-            Use dirs in this path
-        prefix: str
-            Use only dirs starting by this prefix
-
-        Return
-        ------
-        str
-            name
-        """
-        matching_dirs = (
-            dir_name
-            for dir_name in reversed(listdir(path))
-            if isdir(join(path, dir_name)) and
-            dir_name.startswith(prefix)
-        )
-        return next(matching_dirs, None) or ''
-
-
-class EnvironmentInfo:
-    """
-    Return environment variables for specified Microsoft Visual C++ version
-    and platform : Lib, Include, Path and libpath.
-
-    This function is compatible with Microsoft Visual C++ 9.0 to 14.X.
-
-    Script created by analysing Microsoft environment configuration files like
-    "vcvars[...].bat", "SetEnv.Cmd", "vcbuildtools.bat", ...
-
-    Parameters
-    ----------
-    arch: str
-        Target architecture.
-    vc_ver: float
-        Required Microsoft Visual C++ version. If not set, autodetect the last
-        version.
-    vc_min_ver: float
-        Minimum Microsoft Visual C++ version.
-    """
-
-    # Variables and properties in this class use originals CamelCase variables
-    # names from Microsoft source files for more easy comparison.
-
-    def __init__(self, arch, vc_ver=None, vc_min_ver=0):
-        self.pi = PlatformInfo(arch)
-        self.ri = RegistryInfo(self.pi)
-        self.si = SystemInfo(self.ri, vc_ver)
-
-        if self.vc_ver < vc_min_ver:
-            err = 'No suitable Microsoft Visual C++ version found'
-            raise distutils.errors.DistutilsPlatformError(err)
-
-    @property
-    def vs_ver(self):
-        """
-        Microsoft Visual Studio.
-
-        Return
-        ------
-        float
-            version
-        """
-        return self.si.vs_ver
-
-    @property
-    def vc_ver(self):
-        """
-        Microsoft Visual C++ version.
-
-        Return
-        ------
-        float
-            version
-        """
-        return self.si.vc_ver
-
-    @property
-    def VSTools(self):
-        """
-        Microsoft Visual Studio Tools.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        paths = [r'Common7\IDE', r'Common7\Tools']
-
-        if self.vs_ver >= 14.0:
-            arch_subdir = self.pi.current_dir(hidex86=True, x64=True)
-            paths += [r'Common7\IDE\CommonExtensions\Microsoft\TestWindow']
-            paths += [r'Team Tools\Performance Tools']
-            paths += [r'Team Tools\Performance Tools%s' % arch_subdir]
-
-        return [join(self.si.VSInstallDir, path) for path in paths]
-
-    @property
-    def VCIncludes(self):
-        """
-        Microsoft Visual C++ & Microsoft Foundation Class Includes.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        return [join(self.si.VCInstallDir, 'Include'),
-                join(self.si.VCInstallDir, r'ATLMFC\Include')]
-
-    @property
-    def VCLibraries(self):
-        """
-        Microsoft Visual C++ & Microsoft Foundation Class Libraries.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        if self.vs_ver >= 15.0:
-            arch_subdir = self.pi.target_dir(x64=True)
-        else:
-            arch_subdir = self.pi.target_dir(hidex86=True)
-        paths = ['Lib%s' % arch_subdir, r'ATLMFC\Lib%s' % arch_subdir]
-
-        if self.vs_ver >= 14.0:
-            paths += [r'Lib\store%s' % arch_subdir]
-
-        return [join(self.si.VCInstallDir, path) for path in paths]
-
-    @property
-    def VCStoreRefs(self):
-        """
-        Microsoft Visual C++ store references Libraries.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        if self.vs_ver < 14.0:
-            return []
-        return [join(self.si.VCInstallDir, r'Lib\store\references')]
-
-    @property
-    def VCTools(self):
-        """
-        Microsoft Visual C++ Tools.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        si = self.si
-        tools = [join(si.VCInstallDir, 'VCPackages')]
-
-        forcex86 = True if self.vs_ver <= 10.0 else False
-        arch_subdir = self.pi.cross_dir(forcex86)
-        if arch_subdir:
-            tools += [join(si.VCInstallDir, 'Bin%s' % arch_subdir)]
-
-        if self.vs_ver == 14.0:
-            path = 'Bin%s' % self.pi.current_dir(hidex86=True)
-            tools += [join(si.VCInstallDir, path)]
-
-        elif self.vs_ver >= 15.0:
-            host_dir = (r'bin\HostX86%s' if self.pi.current_is_x86() else
-                        r'bin\HostX64%s')
-            tools += [join(
-                si.VCInstallDir, host_dir % self.pi.target_dir(x64=True))]
-
-            if self.pi.current_cpu != self.pi.target_cpu:
-                tools += [join(
-                    si.VCInstallDir, host_dir % self.pi.current_dir(x64=True))]
-
-        else:
-            tools += [join(si.VCInstallDir, 'Bin')]
-
-        return tools
-
-    @property
-    def OSLibraries(self):
-        """
-        Microsoft Windows SDK Libraries.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        if self.vs_ver <= 10.0:
-            arch_subdir = self.pi.target_dir(hidex86=True, x64=True)
-            return [join(self.si.WindowsSdkDir, 'Lib%s' % arch_subdir)]
-
-        else:
-            arch_subdir = self.pi.target_dir(x64=True)
-            lib = join(self.si.WindowsSdkDir, 'lib')
-            libver = self._sdk_subdir
-            return [join(lib, '%sum%s' % (libver, arch_subdir))]
-
-    @property
-    def OSIncludes(self):
-        """
-        Microsoft Windows SDK Include.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        include = join(self.si.WindowsSdkDir, 'include')
-
-        if self.vs_ver <= 10.0:
-            return [include, join(include, 'gl')]
-
-        else:
-            if self.vs_ver >= 14.0:
-                sdkver = self._sdk_subdir
-            else:
-                sdkver = ''
-            return [join(include, '%sshared' % sdkver),
-                    join(include, '%sum' % sdkver),
-                    join(include, '%swinrt' % sdkver)]
-
-    @property
-    def OSLibpath(self):
-        """
-        Microsoft Windows SDK Libraries Paths.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        ref = join(self.si.WindowsSdkDir, 'References')
-        libpath = []
-
-        if self.vs_ver <= 9.0:
-            libpath += self.OSLibraries
-
-        if self.vs_ver >= 11.0:
-            libpath += [join(ref, r'CommonConfiguration\Neutral')]
-
-        if self.vs_ver >= 14.0:
-            libpath += [
-                ref,
-                join(self.si.WindowsSdkDir, 'UnionMetadata'),
-                join(
-                    ref, 'Windows.Foundation.UniversalApiContract', '1.0.0.0'),
-                join(ref, 'Windows.Foundation.FoundationContract', '1.0.0.0'),
-                join(
-                    ref, 'Windows.Networking.Connectivity.WwanContract',
-                    '1.0.0.0'),
-                join(
-                    self.si.WindowsSdkDir, 'ExtensionSDKs', 'Microsoft.VCLibs',
-                    '%0.1f' % self.vs_ver, 'References', 'CommonConfiguration',
-                    'neutral'),
-            ]
-        return libpath
-
-    @property
-    def SdkTools(self):
-        """
-        Microsoft Windows SDK Tools.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        return list(self._sdk_tools())
-
-    def _sdk_tools(self):
-        """
-        Microsoft Windows SDK Tools paths generator.
-
-        Return
-        ------
-        generator of str
-            paths
-        """
-        if self.vs_ver < 15.0:
-            bin_dir = 'Bin' if self.vs_ver <= 11.0 else r'Bin\x86'
-            yield join(self.si.WindowsSdkDir, bin_dir)
-
-        if not self.pi.current_is_x86():
-            arch_subdir = self.pi.current_dir(x64=True)
-            path = 'Bin%s' % arch_subdir
-            yield join(self.si.WindowsSdkDir, path)
-
-        if self.vs_ver in (10.0, 11.0):
-            if self.pi.target_is_x86():
-                arch_subdir = ''
-            else:
-                arch_subdir = self.pi.current_dir(hidex86=True, x64=True)
-            path = r'Bin\NETFX 4.0 Tools%s' % arch_subdir
-            yield join(self.si.WindowsSdkDir, path)
-
-        elif self.vs_ver >= 15.0:
-            path = join(self.si.WindowsSdkDir, 'Bin')
-            arch_subdir = self.pi.current_dir(x64=True)
-            sdkver = self.si.WindowsSdkLastVersion
-            yield join(path, '%s%s' % (sdkver, arch_subdir))
-
-        if self.si.WindowsSDKExecutablePath:
-            yield self.si.WindowsSDKExecutablePath
-
-    @property
-    def _sdk_subdir(self):
-        """
-        Microsoft Windows SDK version subdir.
-
-        Return
-        ------
-        str
-            subdir
-        """
-        ucrtver = self.si.WindowsSdkLastVersion
-        return ('%s\\' % ucrtver) if ucrtver else ''
-
-    @property
-    def SdkSetup(self):
-        """
-        Microsoft Windows SDK Setup.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        if self.vs_ver > 9.0:
-            return []
-
-        return [join(self.si.WindowsSdkDir, 'Setup')]
-
-    @property
-    def FxTools(self):
-        """
-        Microsoft .NET Framework Tools.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        pi = self.pi
-        si = self.si
-
-        if self.vs_ver <= 10.0:
-            include32 = True
-            include64 = not pi.target_is_x86() and not pi.current_is_x86()
-        else:
-            include32 = pi.target_is_x86() or pi.current_is_x86()
-            include64 = pi.current_cpu == 'amd64' or pi.target_cpu == 'amd64'
-
-        tools = []
-        if include32:
-            tools += [join(si.FrameworkDir32, ver)
-                      for ver in si.FrameworkVersion32]
-        if include64:
-            tools += [join(si.FrameworkDir64, ver)
-                      for ver in si.FrameworkVersion64]
-        return tools
-
-    @property
-    def NetFxSDKLibraries(self):
-        """
-        Microsoft .Net Framework SDK Libraries.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        if self.vs_ver < 14.0 or not self.si.NetFxSdkDir:
-            return []
-
-        arch_subdir = self.pi.target_dir(x64=True)
-        return [join(self.si.NetFxSdkDir, r'lib\um%s' % arch_subdir)]
-
-    @property
-    def NetFxSDKIncludes(self):
-        """
-        Microsoft .Net Framework SDK Includes.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        if self.vs_ver < 14.0 or not self.si.NetFxSdkDir:
-            return []
-
-        return [join(self.si.NetFxSdkDir, r'include\um')]
-
-    @property
-    def VsTDb(self):
-        """
-        Microsoft Visual Studio Team System Database.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        return [join(self.si.VSInstallDir, r'VSTSDB\Deploy')]
-
-    @property
-    def MSBuild(self):
-        """
-        Microsoft Build Engine.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        if self.vs_ver < 12.0:
-            return []
-        elif self.vs_ver < 15.0:
-            base_path = self.si.ProgramFilesx86
-            arch_subdir = self.pi.current_dir(hidex86=True)
-        else:
-            base_path = self.si.VSInstallDir
-            arch_subdir = ''
-
-        path = r'MSBuild\%0.1f\bin%s' % (self.vs_ver, arch_subdir)
-        build = [join(base_path, path)]
-
-        if self.vs_ver >= 15.0:
-            # Add Roslyn C# & Visual Basic Compiler
-            build += [join(base_path, path, 'Roslyn')]
-
-        return build
-
-    @property
-    def HTMLHelpWorkshop(self):
-        """
-        Microsoft HTML Help Workshop.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        if self.vs_ver < 11.0:
-            return []
-
-        return [join(self.si.ProgramFilesx86, 'HTML Help Workshop')]
-
-    @property
-    def UCRTLibraries(self):
-        """
-        Microsoft Universal C Runtime SDK Libraries.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        if self.vs_ver < 14.0:
-            return []
-
-        arch_subdir = self.pi.target_dir(x64=True)
-        lib = join(self.si.UniversalCRTSdkDir, 'lib')
-        ucrtver = self._ucrt_subdir
-        return [join(lib, '%sucrt%s' % (ucrtver, arch_subdir))]
-
-    @property
-    def UCRTIncludes(self):
-        """
-        Microsoft Universal C Runtime SDK Include.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        if self.vs_ver < 14.0:
-            return []
-
-        include = join(self.si.UniversalCRTSdkDir, 'include')
-        return [join(include, '%sucrt' % self._ucrt_subdir)]
-
-    @property
-    def _ucrt_subdir(self):
-        """
-        Microsoft Universal C Runtime SDK version subdir.
-
-        Return
-        ------
-        str
-            subdir
-        """
-        ucrtver = self.si.UniversalCRTSdkLastVersion
-        return ('%s\\' % ucrtver) if ucrtver else ''
-
-    @property
-    def FSharp(self):
-        """
-        Microsoft Visual F#.
-
-        Return
-        ------
-        list of str
-            paths
-        """
-        if 11.0 > self.vs_ver > 12.0:
-            return []
-
-        return [self.si.FSharpInstallDir]
-
-    @property
-    def VCRuntimeRedist(self):
-        """
-        Microsoft Visual C++ runtime redistributable dll.
-
-        Return
-        ------
-        str
-            path
-        """
-        vcruntime = 'vcruntime%d0.dll' % self.vc_ver
-        arch_subdir = self.pi.target_dir(x64=True).strip('\\')
-
-        # Installation prefixes candidates
-        prefixes = []
-        tools_path = self.si.VCInstallDir
-        redist_path = dirname(tools_path.replace(r'\Tools', r'\Redist'))
-        if isdir(redist_path):
-            # Redist version may not be exactly the same as tools
-            redist_path = join(redist_path, listdir(redist_path)[-1])
-            prefixes += [redist_path, join(redist_path, 'onecore')]
-
-        prefixes += [join(tools_path, 'redist')]  # VS14 legacy path
-
-        # CRT directory
-        crt_dirs = ('Microsoft.VC%d.CRT' % (self.vc_ver * 10),
-                    # Sometime store in directory with VS version instead of VC
-                    'Microsoft.VC%d.CRT' % (int(self.vs_ver) * 10))
-
-        # vcruntime path
-        for prefix, crt_dir in itertools.product(prefixes, crt_dirs):
-            path = join(prefix, arch_subdir, crt_dir, vcruntime)
-            if isfile(path):
-                return path
-
-    def return_env(self, exists=True):
-        """
-        Return environment dict.
-
-        Parameters
-        ----------
-        exists: bool
-            It True, only return existing paths.
-
-        Return
-        ------
-        dict
-            environment
-        """
-        env = dict(
-            include=self._build_paths('include',
-                                      [self.VCIncludes,
-                                       self.OSIncludes,
-                                       self.UCRTIncludes,
-                                       self.NetFxSDKIncludes],
-                                      exists),
-            lib=self._build_paths('lib',
-                                  [self.VCLibraries,
-                                   self.OSLibraries,
-                                   self.FxTools,
-                                   self.UCRTLibraries,
-                                   self.NetFxSDKLibraries],
-                                  exists),
-            libpath=self._build_paths('libpath',
-                                      [self.VCLibraries,
-                                       self.FxTools,
-                                       self.VCStoreRefs,
-                                       self.OSLibpath],
-                                      exists),
-            path=self._build_paths('path',
-                                   [self.VCTools,
-                                    self.VSTools,
-                                    self.VsTDb,
-                                    self.SdkTools,
-                                    self.SdkSetup,
-                                    self.FxTools,
-                                    self.MSBuild,
-                                    self.HTMLHelpWorkshop,
-                                    self.FSharp],
-                                   exists),
-        )
-        if self.vs_ver >= 14 and isfile(self.VCRuntimeRedist):
-            env['py_vcruntime_redist'] = self.VCRuntimeRedist
-        return env
-
-    def _build_paths(self, name, spec_path_lists, exists):
-        """
-        Given an environment variable name and specified paths,
-        return a pathsep-separated string of paths containing
-        unique, extant, directories from those paths and from
-        the environment variable. Raise an error if no paths
-        are resolved.
-
-        Parameters
-        ----------
-        name: str
-            Environment variable name
-        spec_path_lists: list of str
-            Paths
-        exists: bool
-            It True, only return existing paths.
-
-        Return
-        ------
-        str
-            Pathsep-separated paths
-        """
-        # flatten spec_path_lists
-        spec_paths = itertools.chain.from_iterable(spec_path_lists)
-        env_paths = environ.get(name, '').split(pathsep)
-        paths = itertools.chain(spec_paths, env_paths)
-        extant_paths = list(filter(isdir, paths)) if exists else paths
-        if not extant_paths:
-            msg = "%s environment variable is empty" % name.upper()
-            raise distutils.errors.DistutilsPlatformError(msg)
-        unique_paths = unique_everseen(extant_paths)
-        return pathsep.join(unique_paths)
diff --git a/spaces/publichealthsurveillance/PHS-BERT/app.py b/spaces/publichealthsurveillance/PHS-BERT/app.py
deleted file mode 100644
index 46159a7b4bdb2eff16edb0696b2c500412af8786..0000000000000000000000000000000000000000
--- a/spaces/publichealthsurveillance/PHS-BERT/app.py
+++ /dev/null
@@ -1,332 +0,0 @@
-import ktrain
-from gradio import Interface, Parallel, TabbedInterface
-
-vs_examples = [
-	["I only get my kids the ones I got....I've turned down many so called 'vaccines'"], 
-	["In child protective services, further providing for definitions, for immunity from liability"], 
-	["Lol what? Measles is a real thing. Get vaccinated"]]
-vs_title = "Vaccine Sentiment Task"
-# vs_desc = "Enter text to generate labels from 3 models (BERT, MentalBERT, PHS-BERT). The three provided examples have true labels 'vaccine critical', 'neutral', 'vaccine supportive' respectively (NOTE: you may have to click submit again to generate the correct labels)."# For more details, please refer to the VS2 dataset description in our paper (link provided in the corresponding Hugging Face repository)."
-vs_desc = "Enter text to generate labels from 2 models (BERT, PHS-BERT). The three provided examples have true labels 'vaccine critical', 'neutral', 'vaccine supportive' respectively (NOTE: you may have to click submit again to generate the correct labels)."# For more details, please refer to the VS2 dataset description in our paper (link provided in the corresponding Hugging Face repository)."
-
-hm_examples = [
-	["Serious as a heart attack question/thought Riddle me this. Why, oh why, does cold brew coffee get warm after sitting to long. Taste terrible. And Hot coffee get literally COLD after sitting too long. Tastes terrible. Like what. Why don't cold stay cold and hot only get warm?"], 
-	# ["It's odd how humans are considered predators when they have a heart attack and run like mad when a small insect is running straight towards them."], 
-	["The older we get the less likely we are to view a sudden massive heart attack as a tragedy than a stroke of good luck."],
-	["My son is not feeling well today."]]
-hm_title = "Health Mention Task"
-# hm_desc = "Enter text to generate labels from 3 models (BERT, MentalBERT, PHS-BERT). The three provided examples have true labels 'Figurative/Hyperbolic Health Mentions', 'Non-personal Health Mentions', 'Personal Health Mentions' respectively (NOTE: you may have to click submit again to generate the correct labels)."# For more details, please refer to the RHMD dataset description in our paper (link provided in the corresponding Hugging Face repository)."
-hm_desc = "Enter text to generate labels from 2 models (BERT, PHS-BERT). The three provided examples have true labels 'Figurative/Hyperbolic Health Mentions', 'Non-personal Health Mentions', 'Personal Health Mentions' respectively (NOTE: you may have to click submit again to generate the correct labels)."# For more details, please refer to the RHMD dataset description in our paper (link provided in the corresponding Hugging Face repository)."
-
-dep_examples = [
-	["Nothing major, some underage drinking, a little pot, but I wasn't a bad kid. Furthermore, I feel like I matured well and have gone on to be successful for my age (24) IMO. I've also had positive experiences with police. The resource officer at my high school was a really good guy and almost like a mentor to me. When I was 17 I was arrested when police raided a friends house because they were tipped off that there was to be some under-aged drinking. Furthermore, I told him before we got really serious that I have anxiety and depression, and if he can’t handle that then I’ll understand if we end things. But *he* chose to stay with me and help me if I wanted it. Honestly I’m just tired of defending myself to him after this fight. I shouldn’t have to. And he kept threatening to break up; then why don’t you do it?"],
-	["Yes, you should! And we planned for that. Because the data is stored in an encrypted Google Firebase server, you can download the app again and use their same username and password to retrieve their plan. So if you go to Walmart to get a burner phone (or when we provide one, in some cases), you can install it on that device as well. Here's the [iOS <url> In order to make a case for its commercialization, we have to do a strong market validation research and costumer insight so we decided to create a survey asking parents what are they looking for in a wearable device for their bundle of joy. Here's the link: <url> You will also enter for a chance to win an Amazon Gift card! Thanks! **SURVEY HAS BEEN EDITED FOR BETTER EXPERIENCE** * The survey usually only takes about 5 minutes (or less) to complete - but you can take as long as you like! * Please note that this survey is best viewed via a computer screen, rather than on a mobile phone. Interested? Here's the link: <url> Little over 3 hours ago, my dad had attacked me. I'm not sure who to go to for advice, hoping someone can share any here. Thank you. Here's the full story Preceding physical contact, me and my dad were having a verbal argument. Here's the link to my amazon wish list where the two items are: <url> If the link doesn't work, let me know. The extra $1.25 an hour doesn't seem like much but I'm the sole supporter at the moment for a family of 7 and it's going to make a small, but huge difference for us. Please and thank you!"],
-	["i have horrible vivid nightmares every night. sometimes they're trauma related, but most of the time they're about murder, torture and such depraved things that I can't talk about to anyone. every morning i wake up drenched in sweat, and sometimes vomiting. i have no idea what to do. it's ruining my life."]
-]
-dep_title = "Depression Task"
-dep_desc = "Enter X to generate labels from 3 models (BERT, MentalBERT, PHS-BERT). Label 0='x', 1='y', 2='z'. The three provided examples have true labels 0,1,2 respectively (NOTE: you may have to click submit again to generate the correct labels). For more details, please refer to the X dataset description in our paper (link provided in the corresponding Hugging Face repository)."
-
-covid_examples = [
-	["Second person-to-person coronavirus transmission reported in US, CDC says  #FoxNews - I thought you fixed it?"],
-	# ["Do you expect a travel ban to work?  #aircraft #airplane #airplanes #airport #Airports #avgeek #aviation #aviationdaily #aviationgeek #aviationlife #aviationlovers #AvSec #crewlife #Cybersecurity #flight #Flyer #flying #infosec #pilot #pilotlife #travel"],
-	["The latest Boarding Pass!  #budget2020 #coronavirus"]
-]
-covid_title = "COVID Category Task"
-# covid_desc = "Enter covid-related tweets to generate labels from 3 models (BERT, MentalBERT, PHS-BERT). The two provided examples have true labels 'news', 'personal narrative' respectively (NOTE: you may have to click submit again to generate the correct labels)."# For more details, please refer to the Covid category dataset description in our paper (link provided in the corresponding Hugging Face repository)."
-covid_desc = "Enter covid-related tweets to generate labels from 2 models (BERT, PHS-BERT). The two provided examples have true labels 'news', 'personal narrative' respectively (NOTE: you may have to click submit again to generate the correct labels)."# For more details, please refer to the Covid category dataset description in our paper (link provided in the corresponding Hugging Face repository)."
-
-# 2nd example looks like the most risk
-suicide_examples = [
-	["I cannot say I have been in your shoes; however I have felt immense Ache as you have. I have had the hours, days, months filled with agony and Feeling despair and hopelessness. Ive lost a good near everything I ever once had or loved. Its devastating, sometimes I feel as though Ive lost my entire identity, consumed with self-loathing and hatred. I too, suffer from body dysmorphic disorder; in my turn I suffered from extreme Bulimia (down to 40 kg at 50) and it was, along with the lingering effects, awful.I had to start living for, in what my eyes was, success. Expanding my knowledge on the world around me, enveloping myself in global affairs; anything to take my mind off my Ache. I became encompassed in a world that didnt involve me. Distraction was my obvious get-away. This may be not for you (I never liked it to even be brought up) but I began to seek some form of spiritual journey. I tried to set some good into this world, Bulimia Nervosa my soul for a higher thinking. I took on philosophy and metaphysics, find reasoning behind my suffering. This is just my escape, I hope that youll find some relief from my advice. Im sorry for your experience and give you my sincerest best wishes."],
-	["Ive tried that. Im Exhaustion of trying and falling at everything. Im looking Att gun and trying to figure why not to do it. ', 'Heh, even reddit cant give me a reason to keep on going."],
-	["Friendships are complicated. Close friendships between three people are even more complicated. Maybe its time to expand your circle of friends. Theres no need to get rid of the two friends youre talking about. Maybe theyll come around and maybe they wont. Either way, theres nothing wrong with meeting new people.Try to keep in mind that a lot of the people at your school (if not all of them) are thinking the EXACT same things as you. 'Nobody likes me. I wish I had more friends.' If you were to make a point of chatting with a few new people every day, theyd probably be extremely grateful to you, and might end up being good friends of yours. What kind of activities are you involved in?It sounds Hyperactive behavior you Irritable Mood a lot to your mom, and you must care about her too if youre considering her feelings (not all teenagers would have the selflessness and empathy to do that). Maybe youd feel better if you talked to her about some of this. Is it possible to have dinner together tonight? Maybe you could plan some kind of event with her, Hyperactive behavior a movie or a manicure. Also, you could offer to run errands with her some evening or on the weekend. She might appreciate the company and Ive found it makes great visiting time.Please keep us updated! Im sending you positive thoughts.', 'That sounds really rough. Im sorry youre going through such a tough time. It sounds Hyperactive behavior your wife has been treating you horribly for a while now.I think the best thing you can do is get through the day. At some point youll need to feel Numbness and at some point youll need to get some release. Try to Sedated state or Numbness yourself by vegging in front of the TV or having a few beers (dont buy enough to get sick). Releasing the pent up frustration could be through a work out or venting to a friend. If you live in a safe neighborhood, long walks are helpful.Is there a friend or family member who could stay with you for a night or two? Venting to us is great, and Id be happy to PM, but hugs are hard to give online.All of the cliches are true. It gets better. Keep your chin up. What doesnt kill you make you stronger. If all those sound Hyperactive behavior bullshit (they often do), just remember to breathe."]
-]
-suicide_title = "Suicide Task"
-suicide_desc = "Enter Reddit posts to generate labels from 3 models (BERT, MentalBERT, PHS-BERT). The 5 labels represent increasing risk to sucide ideation (0='minimum risk', 4='maximum risk'). The three provided examples have true labels 1,2,4 respectively (NOTE: you may have to click submit again to generate the correct labels). For more details, please refer to the R-SSD dataset description in our paper (link provided in the corresponding Hugging Face repository)."
-
-stress_examples = [
-	["I'm not massively worried about it at the moment because it feels good."],
-	# ["My other brother is quite religious / catholic - not sure how this will impact how he reacts when he finds out. Also, my husband now finds it very very hard to be around my brother when my mom and him and his gf get together for family occasions. I don't find it totally difficult, because he's always been in my life and I've gotten so used to just burying it and forgetting about the abuse. But my husband, understandably, has a different perspective. He tries to stay 'strong' and act as 'normal' as possible when we get together so that no one thinks anything is 'wrong' or asks / puts us on the spot."],
-	["My daughter's father I was with for 5 years on and off. He was not abusive the first year, however when he became so I left and found out two weeks later I was pregnant. Of course he begged and pleaded for a second chance, and I believed that my daughter deserved me to at least give it a shot. I came back and surprise surprise it was worse than it ever was. I stuck it out until he disappeared for the eleventeenth time on a drunken bender, I checked my Facebook to find some scumbag girl who was dating one of his best friends was posting horrific, nasty, way out shit about me."]
-]
-stress_title = "Stress Detection Task"
-# stress_desc = "Enter text to generate labels from 3 models (BERT, MentalBERT, PHS-BERT). The two provided examples have true labels 'no stress', 'stress' respectively (NOTE: you may have to click submit again to generate the correct label)."# For more details, please refer to the Dreaddit dataset description in our paper (link provided in the corresponding Hugging Face repository)."
-stress_desc = "Enter text to generate labels from 2 models (BERT, PHS-BERT). The two provided examples have true labels 'no stress', 'stress' respectively (NOTE: you may have to click submit again to generate the correct label)."# For more details, please refer to the Dreaddit dataset description in our paper (link provided in the corresponding Hugging Face repository)."
-
-other_examples = [
-	["@anxietyfighter suffered social anxiety for 4 yrs when i had my first panic attack,got worse when i went to uni, so have just started paxil"],
-	["@JessBarrett227 Taking someone off 150mg off Seroquel, mixing it with Olanzapine in 2 wks causes psychosis - a proper assess was not done. "]
-]
-other_title = "Adverse Drug Reaction Task"
-# other_desc = "Enter text to generate labels from 3 models (BERT, MentalBERT, PHS-BERT). The two provided examples have true labels 'no adverse drug reaction', 'adverse drug reaction' respectively (NOTE: you may have to click submit again to generate the correct labels)."# For more details, please refer to the SMM4H T1 dataset description in our paper (link provided in the corresponding Hugging Face repository)."
-other_desc = "Enter text to generate labels from 2 models (BERT, PHS-BERT). The two provided examples have true labels 'no adverse drug reaction', 'adverse drug reaction' respectively (NOTE: you may have to click submit again to generate the correct labels)."# For more details, please refer to the SMM4H T1 dataset description in our paper (link provided in the corresponding Hugging Face repository)."
-
-# def make_interfaces(folder):
-# 	predictor_bert = ktrain.load_predictor(folder + "bert")
-# 	predictor_mental = ktrain.load_predictor(folder + "mentalbert")
-# 	predictor_phs = ktrain.load_predictor(folder + "phsbert")
-
-# 	def BERT(text):
-# 		results = predictor_bert.predict(str(text))
-# 		return "BERT:" + str(results)
-	
-# 	def MentalBERT(text):
-# 		results = predictor_mental.predict(str(text))
-# 		return "MentalBERT:" + str(results)
-		
-# 	def PHSBERT(text):
-# 		results = predictor_phs.predict(str(text))
-# 		return "PHS-BERT:" + str(results)
-
-# 	bert_io = Interface(fn=BERT, inputs="text", outputs="text")
-# 	mental_io = Interface(fn=MentalBERT, inputs="text", outputs="text")
-# 	phs_io = Interface(fn=PHSBERT, inputs="text", outputs="text")
-
-# 	return bert_io, mental_io, phs_io
-folder = "vs/"
-vs_predictor_bert = ktrain.load_predictor(folder + "bert")
-vs_predictor_mental = ktrain.load_predictor(folder + "mentalbert")
-vs_predictor_phs = ktrain.load_predictor(folder + "phsbert")
-
-def vs_output(number):
-	if int(number) == 0:
-		return "vaccine critical"
-	if int(number) == 1:
-		return "neutral"
-	if int(number) == 2:
-		return "vaccine supportive"
-	return "N/A"
-
-def vs_BERT(text):
-	return "BERT ➡ " + vs_output(vs_predictor_bert.predict(str(text)))
-
-def vs_MentalBERT(text):
-	return "MentalBERT ➡ " + vs_output(vs_predictor_mental.predict(str(text)))
-	
-def vs_PHSBERT(text):
-	return "PHS-BERT ➡ " + vs_output(vs_predictor_phs.predict(str(text)))
-
-vs_bert_io = Interface(fn=vs_BERT, inputs="text", outputs="text")
-vs_mental_io = Interface(fn=vs_MentalBERT, inputs="text", outputs="text")
-vs_phs_io = Interface(fn=vs_PHSBERT, inputs="text", outputs="text")
-# vs = Parallel(vs_bert_io, vs_mental_io, vs_phs_io, 
-# 	examples=vs_examples, 
-# 	title=vs_title, 
-# 	description=vs_desc,
-# 	theme="peach")
-vs = Parallel(vs_bert_io, vs_phs_io, 
-	examples=vs_examples, 
-	title=vs_title, 
-	description=vs_desc)
-	# theme="peach") # Run error?
-
-folder = "hm/"
-hm_predictor_bert = ktrain.load_predictor(folder + "bert")
-hm_predictor_mental = ktrain.load_predictor(folder + "mentalbert")
-hm_predictor_phs = ktrain.load_predictor(folder + "phsbert")
-
-def hm_output(number):
-	if int(number) == 0:
-		return "Figurative/Hyperbolic Health Mentions"
-	if int(number) == 1:
-		return "Figurative/Hyperbolic Health Mentions"
-	if int(number) == 2:
-		return "Non-personal Health Mentions"
-	if int(number) == 3:
-		return "Personal Health Mentions"
-	return "N/A"
-
-def hm_BERT(text):
-	return "BERT ➡ " + hm_output(hm_predictor_bert.predict(str(text)))
-
-def hm_MentalBERT(text):
-	return "MentalBERT ➡ " + hm_output(hm_predictor_mental.predict(str(text)))
-	
-def hm_PHSBERT(text):
-	return "PHS-BERT ➡ " + hm_output(hm_predictor_phs.predict(str(text)))
-
-hm_bert_io = Interface(fn=hm_BERT, inputs="text", outputs="text")
-hm_mental_io = Interface(fn=hm_MentalBERT, inputs="text", outputs="text")
-hm_phs_io = Interface(fn=hm_PHSBERT, inputs="text", outputs="text")
-# hm = Parallel(hm_bert_io, hm_mental_io, hm_phs_io, 
-# 	examples=hm_examples, 
-# 	title=hm_title, 
-# 	description=hm_desc,
-# 	theme="peach")
-hm = Parallel(hm_bert_io, hm_phs_io, 
-	examples=hm_examples, 
-	title=hm_title, 
-	description=hm_desc)
-	# theme="peach")
-
-folder = "cv/"
-covid_predictor_bert = ktrain.load_predictor(folder + "bert")
-covid_predictor_mental = ktrain.load_predictor(folder + "mentalbert")
-covid_predictor_phs = ktrain.load_predictor(folder + "phsbert")
-
-def cv_output(number):
-	if int(number) == 0:
-		return "news"
-	if int(number) == 1:
-		return "personal narrative"
-	return "N/A"
-
-def covid_BERT(text):
-	return "BERT ➡ " + cv_output(covid_predictor_bert.predict(str(text)))
-
-def covid_MentalBERT(text):
-	return "MentalBERT ➡ " + cv_output(covid_predictor_mental.predict(str(text)))
-	
-def covid_PHSBERT(text):
-	return "PHS-BERT ➡ " + cv_output(covid_predictor_phs.predict(str(text)))
-
-covid_bert_io = Interface(fn=covid_BERT, inputs="text", outputs="text")
-covid_mental_io = Interface(fn=covid_MentalBERT, inputs="text", outputs="text")
-covid_phs_io = Interface(fn=covid_PHSBERT, inputs="text", outputs="text")
-# covid = Parallel(covid_bert_io, covid_mental_io, covid_phs_io, 
-# 	examples=covid_examples, 
-# 	title=covid_title, 
-# 	description=covid_desc,
-# 	theme="peach")
-covid = Parallel(covid_bert_io, covid_phs_io, 
-	examples=covid_examples, 
-	title=covid_title, 
-	description=covid_desc)
-	# theme="peach")
-
-folder = "st/"
-stress_predictor_bert = ktrain.load_predictor(folder + "bert")
-stress_predictor_mental = ktrain.load_predictor(folder + "mentalbert")
-stress_predictor_phs = ktrain.load_predictor(folder + "phsbert")
-
-def st_output(number):
-	if int(number) == 0:
-		return "no stress"
-	if int(number) == 1:
-		return "stress"
-	return "N/A"
-
-def stress_BERT(text):
-	return "BERT ➡ " + st_output(stress_predictor_bert.predict(str(text)))
-
-def stress_MentalBERT(text):
-	return "MentalBERT ➡ " + st_output(stress_predictor_mental.predict(str(text)))
-	
-def stress_PHSBERT(text):
-	return "PHS-BERT ➡ " + st_output(stress_predictor_phs.predict(str(text)))
-
-stress_bert_io = Interface(fn=stress_BERT, inputs="text", outputs="text")
-stress_mental_io = Interface(fn=stress_MentalBERT, inputs="text", outputs="text")
-stress_phs_io = Interface(fn=stress_PHSBERT, inputs="text", outputs="text")
-# stress = Parallel(stress_bert_io, stress_mental_io, stress_phs_io, 
-# 	examples=stress_examples, 
-# 	title=stress_title, 
-# 	description=stress_desc,
-# 	theme="peach")
-stress = Parallel(stress_bert_io, stress_phs_io, 
-	examples=stress_examples, 
-	title=stress_title, 
-	description=stress_desc)
-	# theme="peach")
-
-# folder = "ot/"
-# other_predictor_bert = ktrain.load_predictor(folder + "bert")
-# other_predictor_mental = ktrain.load_predictor(folder + "mentalbert")
-# other_predictor_phs = ktrain.load_predictor(folder + "phsbert")
-
-def ot_output(number):
-	if int(number) == 0:
-		return "no adverse drug reaction"
-	if int(number) == 1:
-		return "adverse drug reaction"
-	return "N/A"
-
-def other_BERT(text):
-	return "BERT ➡ " + ot_output(other_predictor_bert.predict(str(text)))
-
-def other_MentalBERT(text):
-	return "MentalBERT ➡ " + ot_output(other_predictor_mental.predict(str(text)))
-	
-def other_PHSBERT(text):
-	return "PHS-BERT ➡ " + ot_output(other_predictor_phs.predict(str(text)))
-
-# other_bert_io = Interface(fn=other_BERT, inputs="text", outputs="text")
-# other_mental_io = Interface(fn=other_MentalBERT, inputs="text", outputs="text")
-# other_phs_io = Interface(fn=other_PHSBERT, inputs="text", outputs="text")
-# other = Parallel(other_bert_io, other_mental_io, other_phs_io, 
-# 	examples=other_examples, 
-# 	title=other_title, 
-# 	description=other_desc,
-# 	theme="peach")
-# other = Parallel(other_bert_io, other_phs_io, 
-# 	examples=other_examples, 
-# 	title=other_title, 
-# 	description=other_desc)
-	# theme="peach")
-# vs_bert_io, vs_mental_io, vs_phs_io = make_interfaces("vs/")
-# vs = Parallel(vs_bert_io, vs_mental_io, vs_phs_io, 
-# 	examples=vs_examples, 
-# 	title=vs_title, 
-# 	description=vs_desc)
-
-# hm_bert_io, hm_mental_io, hm_phs_io = make_interfaces("hm/")
-# hm = Parallel(hm_bert_io, hm_mental_io, hm_phs_io, 
-# 	examples=hm_examples, 
-# 	title=hm_title, 
-# 	description=hm_desc)
-	
-# dep_bert_io, dep_mental_io, dep_phs_io = make_interfaces("dp/")
-# dep = Parallel(dep_bert_io, dep_mental_io, dep_phs_io, 
-# 	examples=dep_examples, 
-# 	title=dep_title, 
-# 	description=dep_desc)
-
-# covid_bert_io, covid_mental_io, covid_phs_io = make_interfaces("cv/")
-# covid = Parallel(covid_bert_io, covid_mental_io, covid_phs_io, 
-# 	examples=covid_examples, 
-# 	title=covid_title, 
-# 	description=covid_desc)
-
-# suicide_bert_io, suicide_mental_io, suicide_phs_io = make_interfaces("sc/")
-# suicide = Parallel(suicide_bert_io, suicide_mental_io, suicide_phs_io, 
-# 	examples=suicide_examples, 
-# 	title=suicide_title, 
-# 	description=suicide_desc)
-
-# stress_bert_io, stress_mental_io, stress_phs_io = make_interfaces("st/")
-# stress = Parallel(stress_bert_io, stress_mental_io, stress_phs_io, 
-# 	examples=stress_examples, 
-# 	title=stress_title, 
-# 	description=stress_desc)
-
-# other_bert_io, other_mental_io, other_phs_io = make_interfaces("ot/")
-# other = Parallel(other_bert_io, other_mental_io, other_phs_io, 
-# 	examples=other_examples, 
-# 	title=other_title, 
-# 	description=other_desc)
-
-# desc = "Task is currently unavailable."
-
-# def model(text):
-# 	return "Predictions are currently unavailable."
-
-# dep = Interface(fn=model, inputs="text", outputs="text", title=dep_title, description=desc)
-# covid = Interface(fn=model, inputs="text", outputs="text", title=covid_title, description=desc)
-# suicide = Interface(fn=model, inputs="text", outputs="text", title=suicide_title, description=desc)
-# stress = Interface(fn=model, inputs="text", outputs="text", title=stress_title, description=desc)
-# other = Interface(fn=model, inputs="text", outputs="text", title=other_title, description=desc)
-
-# interfaces = [vs, hm, dep, covid, suicide, stress, other]
-# interface_names = [vs_title, hm_title, dep_title, covid_title, suicide_title, stress_title, other_title]
-
-# interfaces = [vs, hm, covid, stress, other]
-# interface_names = [vs_title, hm_title, covid_title, stress_title, other_title]
-
-interfaces = [vs, hm, covid, stress]
-interface_names = [vs_title, hm_title, covid_title, stress_title]
-
-
-# interfaces = [covid, stress]
-# interface_names = [covid_title, stress_title]
-
-TabbedInterface(interfaces, interface_names).launch()
diff --git a/spaces/pycoming/bingo/src/app/loading.css b/spaces/pycoming/bingo/src/app/loading.css
deleted file mode 100644
index eaaab6a86a228334c4eca3c5368ae6f0f593d405..0000000000000000000000000000000000000000
--- a/spaces/pycoming/bingo/src/app/loading.css
+++ /dev/null
@@ -1,68 +0,0 @@
-::-webkit-scrollbar {
-  width: 10px;
-  height: 10px;
-  display: none;
-}
-
-::-webkit-scrollbar-button:start:decrement,
-::-webkit-scrollbar-button:end:increment {
-  height: 30px;
-  background-color: transparent;
-}
-
-::-webkit-scrollbar-track-piece {
-  background-color: #3b3b3b;
-  -webkit-border-radius: 16px;
-}
-
-::-webkit-scrollbar-thumb:vertical {
-  height: 50px;
-  background-color: #666;
-  border: 1px solid #eee;
-  -webkit-border-radius: 6px;
-}
-
-/* loading start */
-.loading-spinner {
-  display: flex;
-  justify-content: center;
-  align-items: center;
-  height: 100vh;
-  opacity: 1;
-  transition: opacity .8s ease-out;
-}
-
-.loading-spinner.hidden {
-  opacity: 0;
-}
-
-.loading-spinner>div {
-  width: 30px;
-  height: 30px;
-  background: linear-gradient(90deg, #2870EA 10.79%, #1B4AEF 87.08%);
-
-  border-radius: 100%;
-  display: inline-block;
-  animation: sk-bouncedelay 1.4s infinite ease-in-out both;
-}
-
-.loading-spinner .bounce1 {
-  animation-delay: -0.32s;
-}
-
-.loading-spinner .bounce2 {
-  animation-delay: -0.16s;
-}
-
-@keyframes sk-bouncedelay {
-
-  0%,
-  80%,
-  100% {
-    transform: scale(0);
-  }
-
-  40% {
-    transform: scale(1.0);
-  }
-}
diff --git a/spaces/pycs/aircraft/README.md b/spaces/pycs/aircraft/README.md
deleted file mode 100644
index f434508ef7697c0f4d2e1cf6b212be26e649770d..0000000000000000000000000000000000000000
--- a/spaces/pycs/aircraft/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Aircraft
-emoji: 🛦
-colorFrom: pink
-colorTo: blue
-sdk: gradio
-sdk_version: 3.1.4
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/qingxu98/gpt-academic/theme.py b/spaces/qingxu98/gpt-academic/theme.py
deleted file mode 100644
index 5ef7e9605896dbdddcaea09e7d804baf3f5696cf..0000000000000000000000000000000000000000
--- a/spaces/qingxu98/gpt-academic/theme.py
+++ /dev/null
@@ -1,353 +0,0 @@
-import gradio as gr
-from toolbox import get_conf
-CODE_HIGHLIGHT, ADD_WAIFU = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU')
-# gradio可用颜色列表
-# gr.themes.utils.colors.slate (石板色)
-# gr.themes.utils.colors.gray (灰色)
-# gr.themes.utils.colors.zinc (锌色)
-# gr.themes.utils.colors.neutral (中性色)
-# gr.themes.utils.colors.stone (石头色)
-# gr.themes.utils.colors.red (红色)
-# gr.themes.utils.colors.orange (橙色)
-# gr.themes.utils.colors.amber (琥珀色)
-# gr.themes.utils.colors.yellow (黄色)
-# gr.themes.utils.colors.lime (酸橙色)
-# gr.themes.utils.colors.green (绿色)
-# gr.themes.utils.colors.emerald (祖母绿)
-# gr.themes.utils.colors.teal (青蓝色)
-# gr.themes.utils.colors.cyan (青色)
-# gr.themes.utils.colors.sky (天蓝色)
-# gr.themes.utils.colors.blue (蓝色)
-# gr.themes.utils.colors.indigo (靛蓝色)
-# gr.themes.utils.colors.violet (紫罗兰色)
-# gr.themes.utils.colors.purple (紫色)
-# gr.themes.utils.colors.fuchsia (洋红色)
-# gr.themes.utils.colors.pink (粉红色)
-# gr.themes.utils.colors.rose (玫瑰色)
-
-
-def adjust_theme():
-
-    try:
-        color_er = gr.themes.utils.colors.fuchsia
-        set_theme = gr.themes.Default(
-            primary_hue=gr.themes.utils.colors.orange,
-            neutral_hue=gr.themes.utils.colors.gray,
-            font=["sans-serif", "Microsoft YaHei", "ui-sans-serif", "system-ui",
-                  "sans-serif", gr.themes.utils.fonts.GoogleFont("Source Sans Pro")],
-            font_mono=["ui-monospace", "Consolas", "monospace", gr.themes.utils.fonts.GoogleFont("IBM Plex Mono")])
-        set_theme.set(
-            # Colors
-            input_background_fill_dark="*neutral_800",
-            # Transition
-            button_transition="none",
-            # Shadows
-            button_shadow="*shadow_drop",
-            button_shadow_hover="*shadow_drop_lg",
-            button_shadow_active="*shadow_inset",
-            input_shadow="0 0 0 *shadow_spread transparent, *shadow_inset",
-            input_shadow_focus="0 0 0 *shadow_spread *secondary_50, *shadow_inset",
-            input_shadow_focus_dark="0 0 0 *shadow_spread *neutral_700, *shadow_inset",
-            checkbox_label_shadow="*shadow_drop",
-            block_shadow="*shadow_drop",
-            form_gap_width="1px",
-            # Button borders
-            input_border_width="1px",
-            input_background_fill="white",
-            # Gradients
-            stat_background_fill="linear-gradient(to right, *primary_400, *primary_200)",
-            stat_background_fill_dark="linear-gradient(to right, *primary_400, *primary_600)",
-            error_background_fill=f"linear-gradient(to right, {color_er.c100}, *background_fill_secondary)",
-            error_background_fill_dark="*background_fill_primary",
-            checkbox_label_background_fill="linear-gradient(to top, *neutral_50, white)",
-            checkbox_label_background_fill_dark="linear-gradient(to top, *neutral_900, *neutral_800)",
-            checkbox_label_background_fill_hover="linear-gradient(to top, *neutral_100, white)",
-            checkbox_label_background_fill_hover_dark="linear-gradient(to top, *neutral_900, *neutral_800)",
-            button_primary_background_fill="linear-gradient(to bottom right, *primary_100, *primary_300)",
-            button_primary_background_fill_dark="linear-gradient(to bottom right, *primary_500, *primary_600)",
-            button_primary_background_fill_hover="linear-gradient(to bottom right, *primary_100, *primary_200)",
-            button_primary_background_fill_hover_dark="linear-gradient(to bottom right, *primary_500, *primary_500)",
-            button_primary_border_color_dark="*primary_500",
-            button_secondary_background_fill="linear-gradient(to bottom right, *neutral_100, *neutral_200)",
-            button_secondary_background_fill_dark="linear-gradient(to bottom right, *neutral_600, *neutral_700)",
-            button_secondary_background_fill_hover="linear-gradient(to bottom right, *neutral_100, *neutral_100)",
-            button_secondary_background_fill_hover_dark="linear-gradient(to bottom right, *neutral_600, *neutral_600)",
-            button_cancel_background_fill=f"linear-gradient(to bottom right, {color_er.c100}, {color_er.c200})",
-            button_cancel_background_fill_dark=f"linear-gradient(to bottom right, {color_er.c600}, {color_er.c700})",
-            button_cancel_background_fill_hover=f"linear-gradient(to bottom right, {color_er.c100}, {color_er.c100})",
-            button_cancel_background_fill_hover_dark=f"linear-gradient(to bottom right, {color_er.c600}, {color_er.c600})",
-            button_cancel_border_color=color_er.c200,
-            button_cancel_border_color_dark=color_er.c600,
-            button_cancel_text_color=color_er.c600,
-            button_cancel_text_color_dark="white",
-        )
-
-        # 添加一个萌萌的看板娘
-        if ADD_WAIFU:
-            js = """
-                <script src="file=docs/waifu_plugin/jquery.min.js"></script>
-                <script src="file=docs/waifu_plugin/jquery-ui.min.js"></script>
-                <script src="file=docs/waifu_plugin/autoload.js"></script>
-            """
-            gradio_original_template_fn = gr.routes.templates.TemplateResponse
-            def gradio_new_template_fn(*args, **kwargs):
-                res = gradio_original_template_fn(*args, **kwargs)
-                res.body = res.body.replace(b'</html>', f'{js}</html>'.encode("utf8"))
-                res.init_headers()
-                return res
-            gr.routes.templates.TemplateResponse = gradio_new_template_fn   # override gradio template
-    except:
-        set_theme = None
-        print('gradio版本较旧, 不能自定义字体和颜色')
-    return set_theme
-
-
-advanced_css = """
-.markdown-body table {
-    margin: 1em 0;
-    border-collapse: collapse;
-    empty-cells: show;
-}
-
-.markdown-body th, .markdown-body td {
-    border: 1.2px solid var(--border-color-primary);
-    padding: 5px;
-}
-
-.markdown-body thead {
-    background-color: rgba(175,184,193,0.2);
-}
-
-.markdown-body thead th {
-    padding: .5em .2em;
-}
-
-.markdown-body ol, .markdown-body ul {
-    padding-inline-start: 2em !important;
-}
-
-/* chat box. */
-[class *= "message"] {
-    border-radius: var(--radius-xl) !important;
-    /* padding: var(--spacing-xl) !important; */
-    /* font-size: var(--text-md) !important; */
-    /* line-height: var(--line-md) !important; */
-    /* min-height: calc(var(--text-md)*var(--line-md) + 2*var(--spacing-xl)); */
-    /* min-width: calc(var(--text-md)*var(--line-md) + 2*var(--spacing-xl)); */
-}
-[data-testid = "bot"] {
-    max-width: 95%;
-    /* width: auto !important; */
-    border-bottom-left-radius: 0 !important;
-}
-[data-testid = "user"] {
-    max-width: 100%;
-    /* width: auto !important; */
-    border-bottom-right-radius: 0 !important;
-}
-
-/* linein code block. */
-.markdown-body code {
-    display: inline;
-    white-space: break-spaces;
-    border-radius: 6px;
-    margin: 0 2px 0 2px;
-    padding: .2em .4em .1em .4em;
-    background-color: rgba(13, 17, 23, 0.95);
-    color: #c9d1d9;
-}
-
-.dark .markdown-body code {
-    display: inline;
-    white-space: break-spaces;
-    border-radius: 6px;
-    margin: 0 2px 0 2px;
-    padding: .2em .4em .1em .4em;
-    background-color: rgba(175,184,193,0.2);
-}
-
-/* code block css */
-.markdown-body pre code {
-    display: block;
-    overflow: auto;
-    white-space: pre;
-    background-color: rgba(13, 17, 23, 0.95);
-    border-radius: 10px;
-    padding: 1em;
-    margin: 1em 2em 1em 0.5em;
-}
-
-.dark .markdown-body pre code {
-    display: block;
-    overflow: auto;
-    white-space: pre;
-    background-color: rgba(175,184,193,0.2);
-    border-radius: 10px;
-    padding: 1em;
-    margin: 1em 2em 1em 0.5em;
-}
-
-"""
-
-if CODE_HIGHLIGHT:
-    advanced_css += """
-
-.codehilite .hll { background-color: #6e7681 }
-.codehilite .c { color: #8b949e; font-style: italic } /* Comment */
-.codehilite .err { color: #f85149 } /* Error */
-.codehilite .esc { color: #c9d1d9 } /* Escape */
-.codehilite .g { color: #c9d1d9 } /* Generic */
-.codehilite .k { color: #ff7b72 } /* Keyword */
-.codehilite .l { color: #a5d6ff } /* Literal */
-.codehilite .n { color: #c9d1d9 } /* Name */
-.codehilite .o { color: #ff7b72; font-weight: bold } /* Operator */
-.codehilite .x { color: #c9d1d9 } /* Other */
-.codehilite .p { color: #c9d1d9 } /* Punctuation */
-.codehilite .ch { color: #8b949e; font-style: italic } /* Comment.Hashbang */
-.codehilite .cm { color: #8b949e; font-style: italic } /* Comment.Multiline */
-.codehilite .cp { color: #8b949e; font-weight: bold; font-style: italic } /* Comment.Preproc */
-.codehilite .cpf { color: #8b949e; font-style: italic } /* Comment.PreprocFile */
-.codehilite .c1 { color: #8b949e; font-style: italic } /* Comment.Single */
-.codehilite .cs { color: #8b949e; font-weight: bold; font-style: italic } /* Comment.Special */
-.codehilite .gd { color: #ffa198; background-color: #490202 } /* Generic.Deleted */
-.codehilite .ge { color: #c9d1d9; font-style: italic } /* Generic.Emph */
-.codehilite .gr { color: #ffa198 } /* Generic.Error */
-.codehilite .gh { color: #79c0ff; font-weight: bold } /* Generic.Heading */
-.codehilite .gi { color: #56d364; background-color: #0f5323 } /* Generic.Inserted */
-.codehilite .go { color: #8b949e } /* Generic.Output */
-.codehilite .gp { color: #8b949e } /* Generic.Prompt */
-.codehilite .gs { color: #c9d1d9; font-weight: bold } /* Generic.Strong */
-.codehilite .gu { color: #79c0ff } /* Generic.Subheading */
-.codehilite .gt { color: #ff7b72 } /* Generic.Traceback */
-.codehilite .g-Underline { color: #c9d1d9; text-decoration: underline } /* Generic.Underline */
-.codehilite .kc { color: #79c0ff } /* Keyword.Constant */
-.codehilite .kd { color: #ff7b72 } /* Keyword.Declaration */
-.codehilite .kn { color: #ff7b72 } /* Keyword.Namespace */
-.codehilite .kp { color: #79c0ff } /* Keyword.Pseudo */
-.codehilite .kr { color: #ff7b72 } /* Keyword.Reserved */
-.codehilite .kt { color: #ff7b72 } /* Keyword.Type */
-.codehilite .ld { color: #79c0ff } /* Literal.Date */
-.codehilite .m { color: #a5d6ff } /* Literal.Number */
-.codehilite .s { color: #a5d6ff } /* Literal.String */
-.codehilite .na { color: #c9d1d9 } /* Name.Attribute */
-.codehilite .nb { color: #c9d1d9 } /* Name.Builtin */
-.codehilite .nc { color: #f0883e; font-weight: bold } /* Name.Class */
-.codehilite .no { color: #79c0ff; font-weight: bold } /* Name.Constant */
-.codehilite .nd { color: #d2a8ff; font-weight: bold } /* Name.Decorator */
-.codehilite .ni { color: #ffa657 } /* Name.Entity */
-.codehilite .ne { color: #f0883e; font-weight: bold } /* Name.Exception */
-.codehilite .nf { color: #d2a8ff; font-weight: bold } /* Name.Function */
-.codehilite .nl { color: #79c0ff; font-weight: bold } /* Name.Label */
-.codehilite .nn { color: #ff7b72 } /* Name.Namespace */
-.codehilite .nx { color: #c9d1d9 } /* Name.Other */
-.codehilite .py { color: #79c0ff } /* Name.Property */
-.codehilite .nt { color: #7ee787 } /* Name.Tag */
-.codehilite .nv { color: #79c0ff } /* Name.Variable */
-.codehilite .ow { color: #ff7b72; font-weight: bold } /* Operator.Word */
-.codehilite .pm { color: #c9d1d9 } /* Punctuation.Marker */
-.codehilite .w { color: #6e7681 } /* Text.Whitespace */
-.codehilite .mb { color: #a5d6ff } /* Literal.Number.Bin */
-.codehilite .mf { color: #a5d6ff } /* Literal.Number.Float */
-.codehilite .mh { color: #a5d6ff } /* Literal.Number.Hex */
-.codehilite .mi { color: #a5d6ff } /* Literal.Number.Integer */
-.codehilite .mo { color: #a5d6ff } /* Literal.Number.Oct */
-.codehilite .sa { color: #79c0ff } /* Literal.String.Affix */
-.codehilite .sb { color: #a5d6ff } /* Literal.String.Backtick */
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-.codehilite .sx { color: #a5d6ff } /* Literal.String.Other */
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-.codehilite .fm { color: #d2a8ff; font-weight: bold } /* Name.Function.Magic */
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-.codehilite .vg { color: #79c0ff } /* Name.Variable.Global */
-.codehilite .vi { color: #79c0ff } /* Name.Variable.Instance */
-.codehilite .vm { color: #79c0ff } /* Name.Variable.Magic */
-.codehilite .il { color: #a5d6ff } /* Literal.Number.Integer.Long */
-
-.dark .codehilite .hll { background-color: #2C3B41 }
-.dark .codehilite .c { color: #79d618; font-style: italic } /* Comment */
-.dark .codehilite .err { color: #FF5370 } /* Error */
-.dark .codehilite .esc { color: #89DDFF } /* Escape */
-.dark .codehilite .g { color: #EEFFFF } /* Generic */
-.dark .codehilite .k { color: #BB80B3 } /* Keyword */
-.dark .codehilite .l { color: #C3E88D } /* Literal */
-.dark .codehilite .n { color: #EEFFFF } /* Name */
-.dark .codehilite .o { color: #89DDFF } /* Operator */
-.dark .codehilite .p { color: #89DDFF } /* Punctuation */
-.dark .codehilite .ch { color: #79d618; font-style: italic } /* Comment.Hashbang */
-.dark .codehilite .cm { color: #79d618; font-style: italic } /* Comment.Multiline */
-.dark .codehilite .cp { color: #79d618; font-style: italic } /* Comment.Preproc */
-.dark .codehilite .cpf { color: #79d618; font-style: italic } /* Comment.PreprocFile */
-.dark .codehilite .c1 { color: #79d618; font-style: italic } /* Comment.Single */
-.dark .codehilite .cs { color: #79d618; font-style: italic } /* Comment.Special */
-.dark .codehilite .gd { color: #FF5370 } /* Generic.Deleted */
-.dark .codehilite .ge { color: #89DDFF } /* Generic.Emph */
-.dark .codehilite .gr { color: #FF5370 } /* Generic.Error */
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-.dark .codehilite .gi { color: #C3E88D } /* Generic.Inserted */
-.dark .codehilite .go { color: #79d618 } /* Generic.Output */
-.dark .codehilite .gp { color: #FFCB6B } /* Generic.Prompt */
-.dark .codehilite .gs { color: #FF5370 } /* Generic.Strong */
-.dark .codehilite .gu { color: #89DDFF } /* Generic.Subheading */
-.dark .codehilite .gt { color: #FF5370 } /* Generic.Traceback */
-.dark .codehilite .kc { color: #89DDFF } /* Keyword.Constant */
-.dark .codehilite .kd { color: #BB80B3 } /* Keyword.Declaration */
-.dark .codehilite .kn { color: #89DDFF; font-style: italic } /* Keyword.Namespace */
-.dark .codehilite .kp { color: #89DDFF } /* Keyword.Pseudo */
-.dark .codehilite .kr { color: #BB80B3 } /* Keyword.Reserved */
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-.dark .codehilite .na { color: #BB80B3 } /* Name.Attribute */
-.dark .codehilite .nb { color: #82AAFF } /* Name.Builtin */
-.dark .codehilite .nc { color: #FFCB6B } /* Name.Class */
-.dark .codehilite .no { color: #EEFFFF } /* Name.Constant */
-.dark .codehilite .nd { color: #82AAFF } /* Name.Decorator */
-.dark .codehilite .ni { color: #89DDFF } /* Name.Entity */
-.dark .codehilite .ne { color: #FFCB6B } /* Name.Exception */
-.dark .codehilite .nf { color: #82AAFF } /* Name.Function */
-.dark .codehilite .nl { color: #82AAFF } /* Name.Label */
-.dark .codehilite .nn { color: #FFCB6B } /* Name.Namespace */
-.dark .codehilite .nx { color: #EEFFFF } /* Name.Other */
-.dark .codehilite .py { color: #FFCB6B } /* Name.Property */
-.dark .codehilite .nt { color: #FF5370 } /* Name.Tag */
-.dark .codehilite .nv { color: #89DDFF } /* Name.Variable */
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-.dark .codehilite .w { color: #EEFFFF } /* Text.Whitespace */
-.dark .codehilite .mb { color: #F78C6C } /* Literal.Number.Bin */
-.dark .codehilite .mf { color: #F78C6C } /* Literal.Number.Float */
-.dark .codehilite .mh { color: #F78C6C } /* Literal.Number.Hex */
-.dark .codehilite .mi { color: #F78C6C } /* Literal.Number.Integer */
-.dark .codehilite .mo { color: #F78C6C } /* Literal.Number.Oct */
-.dark .codehilite .sa { color: #BB80B3 } /* Literal.String.Affix */
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-.dark .codehilite .si { color: #89DDFF } /* Literal.String.Interpol */
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-.dark .codehilite .ss { color: #89DDFF } /* Literal.String.Symbol */
-.dark .codehilite .bp { color: #89DDFF } /* Name.Builtin.Pseudo */
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-.dark .codehilite .vg { color: #89DDFF } /* Name.Variable.Global */
-.dark .codehilite .vi { color: #89DDFF } /* Name.Variable.Instance */
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-.dark .codehilite .il { color: #F78C6C } /* Literal.Number.Integer.Long */
-
-"""
diff --git a/spaces/qskaa/213/README.md b/spaces/qskaa/213/README.md
deleted file mode 100644
index bed5fae7559712ba346253303e6e327b1277a42f..0000000000000000000000000000000000000000
--- a/spaces/qskaa/213/README.md
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: 213
-emoji: 👁
-colorFrom: yellow
-colorTo: gray
-sdk: docker
-pinned: false
-license: mit
-app_port: 8080
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/quidiaMuxgu/Expedit-SAM/Corel Draw X8 Free Download Full Version With Crack.md b/spaces/quidiaMuxgu/Expedit-SAM/Corel Draw X8 Free Download Full Version With Crack.md
deleted file mode 100644
index df1f8c1ccfad745750566201011b4cc6b42d769a..0000000000000000000000000000000000000000
--- a/spaces/quidiaMuxgu/Expedit-SAM/Corel Draw X8 Free Download Full Version With Crack.md	
+++ /dev/null
@@ -1,10 +0,0 @@
-<br />
-<p>Corel Draw Graphics Suite X8 is a preliminary programming application recorded under illustrations editors and made accessible by Corel for Windows.The survey for CorelDRAW Graphics Suite X8 has not been finished at this point, yet it was tried by an editorial manager here on a PC and a rundown of highlights has been arranged; see beneath.</p>
-<h2>Corel draw x8 free download full version with crack</h2><br /><p><b><b>Download File</b> &#10002; <a href="https://geags.com/2uCqCD">https://geags.com/2uCqCD</a></b></p><br /><br />
-<p>CorelDRAW Graphics Suite X8 is a preliminary programming application recorded under illustrations editors and made accessible by Corel for Windows.The survey for CorelDRAW Graphics Suite X8 has not been finished at this point, yet it was tried by an editorial manager here on a PC and a rundown of highlights has been arranged; see beneath.</p>
-<p>CorelDRAW Graphics Suite X8 is a preliminary programming application recorded under illustrations editors and made accessible by Corel for Windows.The survey for CorelDRAW Graphics Suite X8 has not been finished at this point, yet it was tried by an editorial manager here on a PC and a rundown of highlights has been arranged; see beneath. </p>
-<p>CorelDRAW Graphics Suite X8 is a preliminary programming application recorded under illustrations editors and made accessible by Corel for Windows. The survey for CorelDRAW Graphics Suite X8 has not been finished at this point, yet it was tried by an editorial manager here on a PC and a rundown of highlights has been arranged; see beneath.</p>
-<p></p>
-<p>This 18th version of Corel graphics software offers innovative touch support, font management, and other new tools. The Knife tool has been improved, allowing you to split vector objects, text, and bitmaps along straight, freehand, or Bzier lines. It can automatically choose the option that best preserves the look of the outline. Youll also have access to a wide range of template files, with access to thousands of fonts, which will save you a lot of setup time. Learn more about the new features of CorelDRAW X8 in this video. </p> 899543212b<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/quidiaMuxgu/Expedit-SAM/Download Copy Protect 1.5 Full Crack.md b/spaces/quidiaMuxgu/Expedit-SAM/Download Copy Protect 1.5 Full Crack.md
deleted file mode 100644
index b0b192b4ebb8fdace5d84386eba835b73d8035e6..0000000000000000000000000000000000000000
--- a/spaces/quidiaMuxgu/Expedit-SAM/Download Copy Protect 1.5 Full Crack.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>download copy protect 1.5 full crack</h2><br /><p><b><b>Download File</b> &#9658;&#9658;&#9658; <a href="https://geags.com/2uCql4">https://geags.com/2uCql4</a></b></p><br /><br />
-
->Download WTM Copy Protection v2.51 Crack Patch. Published by Jason Pinter ... Worried about piracy? WTM CopyProtection – Protect your software against illegal copy. ... More profit with less illegal copies. ... Post navigation. Previous Post« Previous Download Corel ParticleShop 1.5.108 Keygen Serial. 4d29de3e1b<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/quidiaMuxgu/Expedit-SAM/Lethe - Episode One Full Crack [Torrent] Fixed.md b/spaces/quidiaMuxgu/Expedit-SAM/Lethe - Episode One Full Crack [Torrent] Fixed.md
deleted file mode 100644
index d552567e1c80082a639291459b77e2ea97246181..0000000000000000000000000000000000000000
--- a/spaces/quidiaMuxgu/Expedit-SAM/Lethe - Episode One Full Crack [Torrent] Fixed.md	
+++ /dev/null
@@ -1,32 +0,0 @@
-<h2>Lethe - Episode One full crack [Torrent]</h2><br /><p><b><b>DOWNLOAD</b> ::: <a href="https://geags.com/2uCqgM">https://geags.com/2uCqgM</a></b></p><br /><br />
-<br />
-You'll need to scavenge for your food, create shelter and gather the courage to fight or flee from The Crawlers.”Structural basis for the heme-induced folding transition in the M2-M3 linker of the adenosine 5'-triphosphate (ATP)-binding cassette transporter sub-family C member 7 (ABCC7).
-
-ABCC7 is an ATP-binding cassette transporter protein, the gene mutation of which leads to cystic fibrosis, a lethal lung disease in human. Despite the implications of ABCC7 in the disease, the function and structural basis of the M2-M3 linker in the full-length protein have not been well-studied. In this study, the M2-M3 linker structure in the full-length ABCC7 was determined using NMR spectroscopy. Among the four helices, M2 and M3 helices were not structurally stable in the full-length protein, as they were destabilized upon heme binding. M2-M3 linker residues proximal to the heme were associated with the heme, and this interaction was further stabilized by the heme through hydrophobic packing of M2-M3 linker residues in the heme-induced complex. The conformational stability of the M2-M3 linker and of the heme-binding pocket in the M2-M3 linker were correlated with the overall folding state of the full-length protein.//
-
-//  DriverView.h
-
-//  BeardedSpice
-
-//
-
-//  Created by Scott Henderson on 1/7/12.
-
-//  Copyright (c) 2012 Cactus Data. All rights reserved.
-
-#import 
-
-@interface DriverView : UIView
-
-@property (nonatomic, weak) IBOutlet UIScrollView *scrollView;
-
-@property (nonatomic, weak) IBOutlet UIButton *uploadButton;
-
-@property (nonatomic, weak) IBOutlet UIButton *screenshotButton;
-
-@property (nonatomic, weak) IBOutlet UIButton *grabButton;
-
-@property (nonatomic 4fefd39f24<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/qwertyuiee/AnimeBackgroundGAN/network/Transformer.py b/spaces/qwertyuiee/AnimeBackgroundGAN/network/Transformer.py
deleted file mode 100644
index 966c1c3aa654fbeb4650d361b4fc803695de5369..0000000000000000000000000000000000000000
--- a/spaces/qwertyuiee/AnimeBackgroundGAN/network/Transformer.py
+++ /dev/null
@@ -1,180 +0,0 @@
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-
-
-class Transformer(nn.Module):
-    def __init__(self):
-        super(Transformer, self).__init__()
-        #
-        self.refpad01_1 = nn.ReflectionPad2d(3)
-        self.conv01_1 = nn.Conv2d(3, 64, 7)
-        self.in01_1 = InstanceNormalization(64)
-        # relu
-        self.conv02_1 = nn.Conv2d(64, 128, 3, 2, 1)
-        self.conv02_2 = nn.Conv2d(128, 128, 3, 1, 1)
-        self.in02_1 = InstanceNormalization(128)
-        # relu
-        self.conv03_1 = nn.Conv2d(128, 256, 3, 2, 1)
-        self.conv03_2 = nn.Conv2d(256, 256, 3, 1, 1)
-        self.in03_1 = InstanceNormalization(256)
-        # relu
-
-        ## res block 1
-        self.refpad04_1 = nn.ReflectionPad2d(1)
-        self.conv04_1 = nn.Conv2d(256, 256, 3)
-        self.in04_1 = InstanceNormalization(256)
-        # relu
-        self.refpad04_2 = nn.ReflectionPad2d(1)
-        self.conv04_2 = nn.Conv2d(256, 256, 3)
-        self.in04_2 = InstanceNormalization(256)
-        # + input
-
-        ## res block 2
-        self.refpad05_1 = nn.ReflectionPad2d(1)
-        self.conv05_1 = nn.Conv2d(256, 256, 3)
-        self.in05_1 = InstanceNormalization(256)
-        # relu
-        self.refpad05_2 = nn.ReflectionPad2d(1)
-        self.conv05_2 = nn.Conv2d(256, 256, 3)
-        self.in05_2 = InstanceNormalization(256)
-        # + input
-
-        ## res block 3
-        self.refpad06_1 = nn.ReflectionPad2d(1)
-        self.conv06_1 = nn.Conv2d(256, 256, 3)
-        self.in06_1 = InstanceNormalization(256)
-        # relu
-        self.refpad06_2 = nn.ReflectionPad2d(1)
-        self.conv06_2 = nn.Conv2d(256, 256, 3)
-        self.in06_2 = InstanceNormalization(256)
-        # + input
-
-        ## res block 4
-        self.refpad07_1 = nn.ReflectionPad2d(1)
-        self.conv07_1 = nn.Conv2d(256, 256, 3)
-        self.in07_1 = InstanceNormalization(256)
-        # relu
-        self.refpad07_2 = nn.ReflectionPad2d(1)
-        self.conv07_2 = nn.Conv2d(256, 256, 3)
-        self.in07_2 = InstanceNormalization(256)
-        # + input
-
-        ## res block 5
-        self.refpad08_1 = nn.ReflectionPad2d(1)
-        self.conv08_1 = nn.Conv2d(256, 256, 3)
-        self.in08_1 = InstanceNormalization(256)
-        # relu
-        self.refpad08_2 = nn.ReflectionPad2d(1)
-        self.conv08_2 = nn.Conv2d(256, 256, 3)
-        self.in08_2 = InstanceNormalization(256)
-        # + input
-
-        ## res block 6
-        self.refpad09_1 = nn.ReflectionPad2d(1)
-        self.conv09_1 = nn.Conv2d(256, 256, 3)
-        self.in09_1 = InstanceNormalization(256)
-        # relu
-        self.refpad09_2 = nn.ReflectionPad2d(1)
-        self.conv09_2 = nn.Conv2d(256, 256, 3)
-        self.in09_2 = InstanceNormalization(256)
-        # + input
-
-        ## res block 7
-        self.refpad10_1 = nn.ReflectionPad2d(1)
-        self.conv10_1 = nn.Conv2d(256, 256, 3)
-        self.in10_1 = InstanceNormalization(256)
-        # relu
-        self.refpad10_2 = nn.ReflectionPad2d(1)
-        self.conv10_2 = nn.Conv2d(256, 256, 3)
-        self.in10_2 = InstanceNormalization(256)
-        # + input
-
-        ## res block 8
-        self.refpad11_1 = nn.ReflectionPad2d(1)
-        self.conv11_1 = nn.Conv2d(256, 256, 3)
-        self.in11_1 = InstanceNormalization(256)
-        # relu
-        self.refpad11_2 = nn.ReflectionPad2d(1)
-        self.conv11_2 = nn.Conv2d(256, 256, 3)
-        self.in11_2 = InstanceNormalization(256)
-        # + input
-
-        ##------------------------------------##
-        self.deconv01_1 = nn.ConvTranspose2d(256, 128, 3, 2, 1, 1)
-        self.deconv01_2 = nn.Conv2d(128, 128, 3, 1, 1)
-        self.in12_1 = InstanceNormalization(128)
-        # relu
-        self.deconv02_1 = nn.ConvTranspose2d(128, 64, 3, 2, 1, 1)
-        self.deconv02_2 = nn.Conv2d(64, 64, 3, 1, 1)
-        self.in13_1 = InstanceNormalization(64)
-        # relu
-        self.refpad12_1 = nn.ReflectionPad2d(3)
-        self.deconv03_1 = nn.Conv2d(64, 3, 7)
-        # tanh
-
-    def forward(self, x):
-        y = F.relu(self.in01_1(self.conv01_1(self.refpad01_1(x))))
-        y = F.relu(self.in02_1(self.conv02_2(self.conv02_1(y))))
-        t04 = F.relu(self.in03_1(self.conv03_2(self.conv03_1(y))))
-
-        ##
-        y = F.relu(self.in04_1(self.conv04_1(self.refpad04_1(t04))))
-        t05 = self.in04_2(self.conv04_2(self.refpad04_2(y))) + t04
-
-        y = F.relu(self.in05_1(self.conv05_1(self.refpad05_1(t05))))
-        t06 = self.in05_2(self.conv05_2(self.refpad05_2(y))) + t05
-
-        y = F.relu(self.in06_1(self.conv06_1(self.refpad06_1(t06))))
-        t07 = self.in06_2(self.conv06_2(self.refpad06_2(y))) + t06
-
-        y = F.relu(self.in07_1(self.conv07_1(self.refpad07_1(t07))))
-        t08 = self.in07_2(self.conv07_2(self.refpad07_2(y))) + t07
-
-        y = F.relu(self.in08_1(self.conv08_1(self.refpad08_1(t08))))
-        t09 = self.in08_2(self.conv08_2(self.refpad08_2(y))) + t08
-
-        y = F.relu(self.in09_1(self.conv09_1(self.refpad09_1(t09))))
-        t10 = self.in09_2(self.conv09_2(self.refpad09_2(y))) + t09
-
-        y = F.relu(self.in10_1(self.conv10_1(self.refpad10_1(t10))))
-        t11 = self.in10_2(self.conv10_2(self.refpad10_2(y))) + t10
-
-        y = F.relu(self.in11_1(self.conv11_1(self.refpad11_1(t11))))
-        y = self.in11_2(self.conv11_2(self.refpad11_2(y))) + t11
-        ##
-
-        y = F.relu(self.in12_1(self.deconv01_2(self.deconv01_1(y))))
-        y = F.relu(self.in13_1(self.deconv02_2(self.deconv02_1(y))))
-        y = torch.tanh(self.deconv03_1(self.refpad12_1(y)))
-
-        return y
-
-
-class InstanceNormalization(nn.Module):
-    def __init__(self, dim, eps=1e-9):
-        super(InstanceNormalization, self).__init__()
-        self.scale = nn.Parameter(torch.FloatTensor(dim))
-        self.shift = nn.Parameter(torch.FloatTensor(dim))
-        self.eps = eps
-        self._reset_parameters()
-
-    def _reset_parameters(self):
-        self.scale.data.uniform_()
-        self.shift.data.zero_()
-
-    def __call__(self, x):
-        n = x.size(2) * x.size(3)
-        t = x.view(x.size(0), x.size(1), n)
-        mean = torch.mean(t, 2).unsqueeze(2).unsqueeze(3).expand_as(x)
-        # Calculate the biased var. torch.var returns unbiased var
-        var = torch.var(t, 2).unsqueeze(2).unsqueeze(3).expand_as(x) * (
-            (n - 1) / float(n)
-        )
-        scale_broadcast = self.scale.unsqueeze(1).unsqueeze(1).unsqueeze(0)
-        scale_broadcast = scale_broadcast.expand_as(x)
-        shift_broadcast = self.shift.unsqueeze(1).unsqueeze(1).unsqueeze(0)
-        shift_broadcast = shift_broadcast.expand_as(x)
-        out = (x - mean) / torch.sqrt(var + self.eps)
-        out = out * scale_broadcast + shift_broadcast
-        return out
diff --git a/spaces/radames/MusicGen-Continuation/audiocraft/modules/lstm.py b/spaces/radames/MusicGen-Continuation/audiocraft/modules/lstm.py
deleted file mode 100644
index c0866175950c1ca4f6cca98649525e6481853bba..0000000000000000000000000000000000000000
--- a/spaces/radames/MusicGen-Continuation/audiocraft/modules/lstm.py
+++ /dev/null
@@ -1,25 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-from torch import nn
-
-
-class StreamableLSTM(nn.Module):
-    """LSTM without worrying about the hidden state, nor the layout of the data.
-    Expects input as convolutional layout.
-    """
-    def __init__(self, dimension: int, num_layers: int = 2, skip: bool = True):
-        super().__init__()
-        self.skip = skip
-        self.lstm = nn.LSTM(dimension, dimension, num_layers)
-
-    def forward(self, x):
-        x = x.permute(2, 0, 1)
-        y, _ = self.lstm(x)
-        if self.skip:
-            y = y + x
-        y = y.permute(1, 2, 0)
-        return y
diff --git a/spaces/raedeXanto/academic-chatgpt-beta/Amparo Grisales Mi Cuerpo Consciente Pdf 14 A Journey Through the Evolution of a Woman.md b/spaces/raedeXanto/academic-chatgpt-beta/Amparo Grisales Mi Cuerpo Consciente Pdf 14 A Journey Through the Evolution of a Woman.md
deleted file mode 100644
index 2cffa32afbf17a7858bba3fd4be03225a33def19..0000000000000000000000000000000000000000
--- a/spaces/raedeXanto/academic-chatgpt-beta/Amparo Grisales Mi Cuerpo Consciente Pdf 14 A Journey Through the Evolution of a Woman.md	
+++ /dev/null
@@ -1,95 +0,0 @@
-<br />
-<h1>Mi cuerpo consciente: A book by Amparo Grisales</h1>
- <p>Do you want to know how to age gracefully and naturally? Do you want to achieve physical, mental and emotional balance? Do you want to cultivate self-love and self-care? If you answered yes to any of these questions, then you might be interested in reading <em>Mi cuerpo consciente</em>, a book by Amparo Grisales.</p>
- <p>Amparo Grisales is a Colombian actress, singer, model and TV personality who has been in the entertainment industry for over five decades. She is known for her beauty, talent and charisma, as well as for her outspokenness and activism. She has been called "the eternal diva" and "the queen of Colombian television".</p>
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- <p>In her book <em>Mi cuerpo consciente</em>, she shares her secrets and tips for staying young, healthy and happy. She explores her own experiences and research on topics such as nutrition, exercise, meditation, sexuality, spirituality, beauty treatments, fashion and more. She also includes photos and anecdotes from her personal and professional life.</p>
- <h2>The main themes of the book</h2>
- <p>The book is divided into four parts: Body, Mind, Soul and Heart. Each part covers a different aspect of Amparo's philosophy and lifestyle. Here are some of the main themes that she discusses in the book:</p>
- <h3>How to age gracefully and naturally</h3>
- <p>Amparo believes that aging is not something to be feared or avoided, but rather something to be embraced and celebrated. She says that aging is a natural process that can be enhanced by taking care of oneself and living with joy. She rejects the idea of using artificial or invasive methods to look younger, such as plastic surgery or botox. Instead, she advocates for using natural remedies and treatments, such as herbs, oils, massages, acupuncture, homeopathy and more. She also emphasizes the importance of having a positive attitude and a sense of humor.</p>
- <h3>How to achieve physical, mental and emotional balance</h3>
- <p>Amparo stresses that having a balanced life is essential for well-being. She says that one should pay attention to all aspects of one's health: physical, mental and emotional. She recommends having a balanced diet that includes fruits, vegetables, grains, proteins, fats and water. She also suggests doing regular exercise that suits one's preferences and needs, such as yoga, pilates, dancing, walking or swimming. She also advises practicing meditation, breathing exercises, relaxation techniques and positive affirmations to calm the mind and reduce stress. She also encourages expressing one's emotions freely and honestly.</p>
- <h3>How to cultivate self-love and self-care</h3>
- <p>Amparo asserts that loving oneself is the key to happiness. She says that one should respect oneself, accept oneself and appreciate oneself. She urges one to treat oneself with kindness, compassion and generosity. She also invites one to pamper oneself with things that make one feel good, such as music, art, books, movies, hobbies or friends. She also reminds one to have fun and enjoy life.</p>
- <h2>The benefits of reading the book</h2>
- <p>Reading <em>Mi cuerpo consciente</em> can have many benefits for anyone who wants to improve their quality of life. Here are some of them:</p>
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- <h3>Learn from the experiences and wisdom of a Colombian diva</h3>
- <p>Amparo Grisales has lived a rich and diverse life that has given her many lessons and insights. She has worked in various fields such as cinema, theater, television, music and fashion. She has traveled around the world and met many celebrities and influential people. She has faced many challenges and overcome many obstacles. She has also enjoyed many successes and achievements. By reading her book, one can learn from her stories and perspectives on various topics.</p>
- <h3>Discover practical tips and exercises for a healthy lifestyle</h3>
- <p>Amparo Grisales provides many useful tips and exercises for anyone who wants to adopt a healthy lifestyle. She gives concrete examples and instructions on how to eat well, exercise well, meditate well and more. She also includes tables and charts that illustrate her points and make them easy to follow.</p>
- <table>
-<tr>
-<th>Nutrition</th>
-<th>Exercise</th>
-<th>Meditation</th>
-</tr>
-<tr>
-<td>- Eat organic food whenever possible<br>- Avoid processed food<br>- Drink plenty of water<br>- Eat five small meals a day<br>- Include all food groups in your diet<br>- Chew your food well<br>- Listen to your body's signals<br></td>
-<td>- Do at least 30 minutes of physical activity every day<br>- Choose an exercise that you enjoy<br>- Warm up before exercising<br>- Stretch after exercising<br>- Vary your routine<br>- Rest when you need it<br>- Breathe deeply while exercising<br></td>
-<td>- Find a quiet place where you won't be disturbed<br>- Sit comfortably with your back straight<br>- Close your eyes or focus on a point<br>- Breathe slowly and deeply<br>- Observe your thoughts without judging them<br>- Repeat a mantra or a positive phrase<br>- Do it for at least 10 minutes every day<br></td>
-</tr>
-</table>
- <h3>Get inspired by the photos and anecdotes of the author</h3>
- <p>Amparo Grisales fills her book with photos and anecdotes that showcase her beauty, talent and charisma. She shares images and stories from her childhood, family, friends, lovers, colleagues, fans and more. She reveals aspects of her personality, such as her humor, curiosity, passion, courage and spirituality. She also shows her style, fashion and elegance. By reading her book, one can get inspired by her example and admire her achievements.</p>
- <h2>The reviews and ratings of the book</h2>
- <p><em>Mi cuerpo consciente</em> has received positive reviews and ratings from readers and critics alike. Here are some of them:</p>
- <h3>What do readers and critics say about the book?</h3>
- <p>- "Amparo Grisales is a woman who radiates vitality, and happy. You will also discover practical tips and exercises for a healthy lifestyle. You will also get inspired by her photos and anecdotes that showcase her beauty, talent and charisma.</p>
- <h3>How can I get <em>Mi cuerpo consciente</em>?</h3>
- <p>You can get <em>Mi cuerpo consciente</em> online from various platforms and websites. You can buy or download the book in different formats, such as hardcover, Kindle edition or ebook. You can also preview some pages of the book on Google Books.</p>
- <h3>How much does <em>Mi cuerpo consciente</em> cost?</h3>
- <p>The book costs different prices depending on where you buy it and what format you choose. The hardcover costs $14.99 on Amazon, the Kindle edition costs $9.99 on Amazon and Google Books, and the ebook costs $9.99 on Google Books.</p>
- </p> 0a6ba089eb<br />
-<br />
-<br />
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diff --git a/spaces/raedeXanto/academic-chatgpt-beta/Far Cry 1 Crack Dosyas Indir Gezginler Adada Hayatta Kalma Mcadelesi.md b/spaces/raedeXanto/academic-chatgpt-beta/Far Cry 1 Crack Dosyas Indir Gezginler Adada Hayatta Kalma Mcadelesi.md
deleted file mode 100644
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--- a/spaces/raedeXanto/academic-chatgpt-beta/Far Cry 1 Crack Dosyas Indir Gezginler Adada Hayatta Kalma Mcadelesi.md	
+++ /dev/null
@@ -1,120 +0,0 @@
-
-<h1>Far Cry 1 Crack Dosyas Indir Gezginler: How to Download and Install the Game for Free</h1>
- <p>Far Cry 1 is a classic first-person shooter game that was released in 2004 by Crytek Studios and Ubisoft. The game is set on a tropical island where you play as Jack Carver, a former special forces operative who is hired by a journalist named Valerie Constantine to escort her to a mysterious location. However, things go wrong when your boat is attacked by mercenaries and you have to survive on your own in a hostile environment full of dangers and secrets.</p>
- <p>The game was praised for its stunning graphics, immersive gameplay, and open-ended world that allowed you to explore and approach missions in different ways. The game also had a multiplayer mode where you could compete with other players online or offline. Far Cry 1 is considered one of the best games of its genre and has spawned several sequels and spin-offs over the years.</p>
-<h2>Far Cry 1 Crack Dosyas Indir Gezginler</h2><br /><p><b><b>Download Zip</b> &mdash;&mdash;&mdash; <a href="https://tinourl.com/2uL4o2">https://tinourl.com/2uL4o2</a></b></p><br /><br />
- <p>However, if you want to play Far Cry 1 today, you might face some difficulties. The game is not available on most digital platforms and you might have trouble finding a physical copy. Moreover, the game might not run well on modern systems and you might need some patches and updates to make it work. And of course, you will have to pay for it.</p>
- <p>But what if there was a way to play Far Cry 1 for free? What if you could download and install the game without paying anything? Well, that's where a crack dosyas comes in. A crack dosyas is a modified file that bypasses the copy protection or activation system of a software or a game. By using a crack dosyas, you can run and play a game without needing a valid license or a CD key.</p>
- <p>However, using a crack dosyas is not without risks. You might download a fake or corrupted file that could harm your computer or steal your data. You might also face legal consequences if you are caught using pirated software or games. And you might miss out on some features or updates that are only available for legitimate users.</p>
- <p>So, should you use a crack dosyas to play Far Cry 1 for free? That's up to you to decide. But if you are interested, here is how you can do it.</p>
- <h2>How to Download Far Cry 1 Crack Dosyas Indir Gezginler</h2>
- <p>The first step is to find a reliable source for the crack dosyas. There are many websites that offer crack dosyases for various games, but not all of them are trustworthy. Some of them might contain viruses, malware, or spyware that could infect your computer or compromise your security. Some of them might also have fake or outdated files that won't work or cause errors.</p>
- <p>One of the websites that claims to have a working crack dosyas for Far Cry 1 is <a href="https://tranusincarta.wixsite.com/thaimansbedo/post/far-cry-1-crack-dosyas-indir-gezginler">tranusincarta.wixsite.com</a>. This website offers a download link for a file called <code>Far_Cry_1_Crack_Dosyas_Indir_Gezginler.rar</code>, which supposedly contains the crack dosyas for Far Cry 1. However, we cannot vouch for the safety or validity of this file, so proceed at your own risk.</p>
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- <p>If you decide to download this file, make sure you have an antivirus program installed on your computer and scan the file before opening it. You should also use a program like WinRAR or 7-Zip to extract the file contents. Inside the archive, you should find two files: <code>FarCry.exe</code> and <code>DevMode.lua</code>. These are the files that you will need to install the crack dosyas.</p>
- <h2>How to Install Far Cry 1 with the Crack Dosyas</h2>
- <p>The next step is to install Far Cry 1 with the crack dosyases. To do this, you will need two things: the original game files and the crack files. The original game files are the files that contain the actual game data, such as graphics, sounds, maps, etc. The crack files are the files that modify or replace some of these files to make them work without needing a license or a CD key.</p>
- <p>To get the original game files, you have two options: either buy a physical copy of Far Cry 1 from an online store or download it from an unofficial source. The first option is obviously more legal and ethical, but it might be more expensive and harder to find. The second option is cheaper and easier, but it might be illegal and unethical depending on where you live and what laws apply.</p>
- <p>If you choose to download Far Cry 1 from an unofficial source, one of the websites that offers it is <a href="https://www.rgames31.com/far-cry-1-pc-game-full-version-free-download/">rgames31.com</a>. This website provides a download link for a file called <code>Far_Cry_2004.rar</code>, which supposedly contains all the original game files for Far Cry 1. However, we cannot vouch for the safety or validity of this file either, so proceed at your own risk.</p>
- <p>If you decide to download this file, make sure you scan it with an antivirus program before opening it. You should also use WinRAR or 7-Zip to extract its contents. Inside the archive, you should find several folders and files, such as <code>BIN32</code>, <code>Data</code>, <code>Languages</code>, etc. These are all part of Far Cry 1's original game files.</p>
- <p>To install Far Cry 1 with these files, follow these steps:</p>
- <ol>
-<li>Create a new folder on your computer where you want to install Far Cry 1.</li>
-<li>Copy all the folders and files from <code>Far_Cry_2004.rar</code> into this folder.</li>
-<li>Copy <code>FarCry.exe</code> from <code>Far_Cry_1_Crack_Dosyas_Indir_Gezginler.rar</code> into this folder as well.</li>
-<li>Rename <code>FarCry.exe</code> from <code>Far_Cry_2004.rar</code> (the original one) into something else (e.g., <code>FarCry_old.exe</code>). This way, you will have two versions of <code>FarCry.exe</code>: one with the crack dosyases (the new one) and one without (the old one).</li>
-<li>Create another new folder inside this folder called <code>Sandbox</code>.</li>
-<li>Copy <code>DevMode.lua</code> from <code>Far_Cry_1_Crack_Dosyas_Indir_Gezginler.rar</code> into this folder.</li>
-<li>You have successfully installed Far Cry 1 with the crack dosyases!</li>
-</ol>
- <h2>Tips and Tricks for Playing Far Cry 1 with the Crack Dosyases</h2>
- <p>The final step is to enjoy playing Far Cry 1 with the crack dosyases. To do this, follow these tips and tricks:</p>
- <ul>
-folder. This will launch the game with the crack dosyases enabled.</li>
-<li>To access the game settings, press <code>Esc</code> on your keyboard and select <code>Options</code>. Here you can adjust the graphics, sound, controls, and gameplay options to suit your preferences. You can also change the language of the game by selecting <code>Languages</code>.</li>
-<li>To fix common errors and bugs with the crack dosyases, such as black screen, crashes, or missing textures, try these solutions:</li>
-  <ul>
-  <li>Update your graphics card drivers and DirectX.</li>
-  <li>Run the game as administrator and in compatibility mode for Windows XP SP3.</li>
-  <li>Disable any antivirus or firewall programs that might interfere with the game.</li>
-  <li>Delete or rename the <code>Video</code> folder inside your installation folder.</li>
-  </ul>
-<li>To enjoy the game features and modes with the crack dosyases, you can do the following:</li>
-  <ul>
-  <li>Explore the open-ended island and discover its secrets and hidden locations.</li>
-  <li>Use different weapons and tools to fight against the mercenaries and mutants.</li>
-  <li>Use stealth or action tactics to complete your missions and objectives.</li>
-  <li>Use vehicles and boats to travel faster and easier.</li>
-  <li>Use binoculars and a map to scout your surroundings and plan your strategy.</li>
-  <li>Use your beasts to help you in combat and hunting.</li>
-  <li>Play the multiplayer mode with other players online or offline using LAN or Hamachi.</li>
-  </ul>
-</ul>
- <h2>Conclusion</h2>
- <p>In conclusion, Far Cry 1 is a great game that you can play for free using a crack dosyas. However, you should be aware of the risks and challenges involved in doing so. You should also respect the rights of the developers and publishers who created this game and support them if you can.</p>
- <p>If you want to try Far Cry 1 with a crack dosyas, you can follow this guide to download and install it. You can also use some tips and tricks to improve your gaming experience and have more fun. However, you should do this at your own risk and responsibility.</p>
- <p>We hope you found this article helpful and informative. If you have any questions or comments, feel free to leave them below. And if you liked this article, please share it with your friends who might be interested in playing Far Cry 1 for free. Thank you for reading!</p>
- <h2>Frequently Asked Questions</h2>
- <ol>
-<li><b>What is Far Cry 1?</b></li>
-<p>Far Cry 1 is a first-person shooter game that was released in 2004 by Crytek Studios and Ubisoft. The game is set on a tropical island where you play as Jack Carver, a former special forces operative who is hired by a journalist named Valerie Constantine to escort her to a mysterious location. However, things go wrong when your boat is attacked by mercenaries and you have to survive on your own in a hostile environment full of dangers and secrets.</p>
- <li><b>What is a crack dosyas?</b></li>
-<p>A crack dosyas is a modified file that bypasses the copy protection or activation system of a software or a game. By using a crack dosyas, you can run and play a game without needing a valid license or a CD key.</p>
- <li><b>How can I play Far Cry 1 for free?</b></li>
-<p>You can play Far Cry 1 for free by using a crack dosyas. To do this, you will need to download and install both the original game files and the crack files from an unofficial source. Then, you will need to copy and replace some of these files in your installation folder. Finally, you will need to run the game with the crack files enabled.</p>
- <li><b>Is it safe to use a crack dosyas?</b></li>
-<p>No, it is not safe to use a crack dosyas. You might download a fake or corrupted file that could harm your computer or steal your data. You might also face legal consequences if you are caught using pirated software or games. And you might miss out on some features or updates that are only available for legitimate users.</p>
- <li><b>Is it legal to use a crack dosyas?</b></li>
-<p>No, it is not legal to use a crack dosyas. You are violating the intellectual property rights of the developers and publishers who created this game. You are also breaking the terms of service and end-user license agreement that you agreed to when you bought or downloaded this game. You could face fines, lawsuits, or even criminal charges if you are caught using a crack dosyas.</p>
-</ol>
- </p> 0a6ba089eb<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/rahul-pandey-ct/kinship-llm-poc/app.py b/spaces/rahul-pandey-ct/kinship-llm-poc/app.py
deleted file mode 100644
index 5e5d091dc44337f9b5cc2c7a849f7ed6599f2639..0000000000000000000000000000000000000000
--- a/spaces/rahul-pandey-ct/kinship-llm-poc/app.py
+++ /dev/null
@@ -1,754 +0,0 @@
-
-## required lib, required "pip install"
-# import transformers
-# import accelerate
-import openai
-import torch
-import cryptography
-import cryptography.fernet
-## interface libs, required "pip install"
-import gradio
-import huggingface_hub
-import huggingface_hub.hf_api
-## standard libs, no need to install
-import json
-import requests
-import time
-import os
-import random
-import re
-import sys
-import psutil
-import threading
-import socket
-# import PIL
-import pandas
-import matplotlib
-class HFace_Pluto(object):
- #
- # initialize the object
- def __init__(self, name="Pluto",*args, **kwargs):
-   super(HFace_Pluto, self).__init__(*args, **kwargs)
-   self.author = "Duc Haba"
-   self.name = name
-   self._ph()
-   self._pp("Hello from class", str(self.__class__) + " Class: " + str(self.__class__.__name__))
-   self._pp("Code name", self.name)
-   self._pp("Author is", self.author)
-   self._ph()
-   #
-   # define class var for stable division
-   self._device = 'cuda'
-   self._steps = [3,8,21,55,89,144]
-   self._guidances = [1.1,3.0,5.0,8.0,13.0,21.0]
-   self._xkeyfile = '.xoxo'
-   self._models = []
-   self._seed = 667 # sum of walnut in ascii (or Angle 667)
-   self._width = 512
-   self._height = 512
-   self._step = 50
-   self._guidances = 7.5
-   #self._generator = torch.Generator(device='cuda')
-   self.pipes = []
-   self.prompts = []
-   self.images = []
-   self.seeds = []
-   self.fname_id = 0
-   self.dname_img = "img_colab/"
-   self._huggingface_key="gAAAAABkduT-XeiYtD41bzjLtwsLCe9y1FbHH6wZkOZwvLwCrgmOtNsFUPWVqMVG8MumazFhiUZy91mWEnLDLCFw3eKNWtOboIyON6yu4lctn6RCQ4Y9nJvx8wPyOnkzt7dm5OISgFcm"
-   self._gpt_key="gAAAAABlJDzTj1q2suhncmXH9EKSQhzQznR1PDmFJgzhFM5k4hlrN13nae2XZ22GKhPa_6RHmnCdGkix-NWK67HEkJrnjp_Eno6t_Ge9WTAI_FNmHsb2vP8f_TRXDFQ6Poq0zYqxoguWdJQ1VTH66KX2Huw6CVoJCw=="
-   self._fkey="fes_f8Im569hYnI1Tn6FqP-6hS4rdmNOJ6DWcRPOsvc="
-   self._color_primary = '#2780e3' #blue
-   self._color_secondary = '#373a3c' #dark gray
-   self._color_success = '#3fb618' #green
-   self._color_info = '#9954bb' #purple
-   self._color_warning = '#ff7518' #orange
-   self._color_danger = '#ff0039' #red
-   self._color_mid_gray = '#495057'
-   return
- #
- # pretty print output name-value line
- def _pp(self, a, b,is_print=True):
-   # print("%34s : %s" % (str(a), str(b)))
-   x = f'{"%34s" % str(a)} : {str(b)}'
-   y = None
-   if (is_print):
-     print(x)
-   else:
-     y = x
-   return y
- #
- # pretty print the header or footer lines
- def _ph(self,is_print=True):
-   x = f'{"-"*34} : {"-"*34}'
-   y = None
-   if (is_print):
-     print(x)
-   else:
-     y = x
-   return y
- #
- # fetch huggingface file
- def fetch_hface_files(self,
-   hf_names,
-   hf_space="duchaba/monty",
-   local_dir="/content/"):
-   f = str(hf_names) + " is not iteratable, type: " + str(type(hf_names))
-   try:
-     for f in hf_names:
-       lo = local_dir + f
-       huggingface_hub.hf_hub_download(repo_id=hf_space, filename=f,
-         use_auth_token=True,repo_type=huggingface_hub.REPO_TYPE_SPACE,
-         force_filename=lo)
-   except:
-     self._pp("*Error", f)
-   return
- #
- #
- def push_hface_files(self,
-   hf_names,
-   hf_space="duchaba/skin_cancer_diagnose",
-   local_dir="/content/"):
-   f = str(hf_names) + " is not iteratable, type: " + str(type(hf_names))
-   try:
-     for f in hf_names:
-       lo = local_dir + f
-       huggingface_hub.upload_file(
-         path_or_fileobj=lo,
-         path_in_repo=f,
-         repo_id=hf_space,
-         repo_type=huggingface_hub.REPO_TYPE_SPACE)
-   except Exception as e:
-     self._pp("*Error", e)
-   return
- #
- # Define a function to display available CPU and RAM
- def fetch_system_info(self):
-   s=''
-   # Get CPU usage as a percentage
-   cpu_usage = psutil.cpu_percent()
-   # Get available memory in bytes
-   mem = psutil.virtual_memory()
-   # Convert bytes to gigabytes
-   mem_total_gb = mem.total / (1024 ** 3)
-   mem_available_gb = mem.available / (1024 ** 3)
-   mem_used_gb = mem.used / (1024 ** 3)
-   # Print the results
-   s += f"CPU usage: {cpu_usage}%\n"
-   s += f"Total memory: {mem_total_gb:.2f} GB\n"
-   s += f"Available memory: {mem_available_gb:.2f} GB\n"
-   # print(f"Used memory: {mem_used_gb:.2f} GB")
-   s += f"Memory usage: {mem_used_gb/mem_total_gb:.2f}%\n"
-   return s
- #
- def restart_script_periodically(self):
-   while True:
-     #random_time = random.randint(540, 600)
-     random_time = random.randint(15800, 21600)
-     time.sleep(random_time)
-     os.execl(sys.executable, sys.executable, *sys.argv)
-   return
- #
- def write_file(self,fname, txt):
-   f = open(fname, "w")
-   f.writelines("\n".join(txt))
-   f.close()
-   return
- #
- def fetch_gpu_info(self):
-   s=''
-   try:
-     s += f'Your GPU is the {torch.cuda.get_device_name(0)}\n'
-     s += f'GPU ready staus {torch.cuda.is_available()}\n'
-     s += f'GPU allocated RAM: {round(torch.cuda.memory_allocated(0)/1024**3,1)} GB\n'
-     s += f'GPU reserved RAM {round(torch.cuda.memory_reserved(0)/1024**3,1)} GB\n'
-   except Exception as e:
-     s += f'**Warning, No GPU: {e}'
-   return s
- #
- def _fetch_crypt(self,is_generate=False):
-   s=self._fkey
-   if (is_generate):
-     s=open(self._xkeyfile, "rb").read()
-   return s
- #
- def _gen_key(self):
-   key = cryptography.fernet.Fernet.generate_key()
-   with open(self._xkeyfile, "wb") as key_file:
-       key_file.write(key)
-   return
- #
- def _decrypt_it(self, x):
-   y = self._fetch_crypt()
-   f = cryptography.fernet.Fernet(y)
-   m = f.decrypt(x)
-   return m.decode()
- # from cryptography.fernet import Fernet
- def _encrypt_it(self, x):
-   key = self._fetch_crypt()
-   p = x.encode()
-   f = cryptography.fernet.Fernet(key)
-   y = f.encrypt(p)
-   return y
- #
- def _login_hface(self):
-   try:
-     huggingface_hub.login(self._decrypt_it(self._huggingface_key),
-       add_to_git_credential=True) # non-blocking login
-     openai.api_key = self._decrypt_it(self._gpt_key)
-   except Exception as e:
-     print(f'Error: {e}')
-   self._ph()
-   return
- #
- def _fetch_version(self):
-   s = ''
-   print(f"{'torch: 2.0.1':<25} Actual: {torch.__version__}")
-   # print(f"{'transformers: 4.29.2':<25} Actual: {transformers.__version__}")
-   s += f"{'openai: 0.27.7,':<28} Actual: {openai.__version__}\n"
-   s += f"{'huggingface_hub: 0.14.1,':<28} Actual: {huggingface_hub.__version__}\n"
-   s += f"{'gradio: 3.32.0,':<28} Actual: {gradio.__version__}\n"
-   s += f"{'cryptography: 3.0.2,':<28} cryptography: {gradio.__version__}\n"
-
-   return s
- #
- def _fetch_host_ip(self):
-   s=''
-   hostname = socket.gethostname()
-   ip_address = socket.gethostbyname(hostname)
-   s += f"Hostname: {hostname}\n"
-   s += f"IP Address: {ip_address}\n"
-   return s
- # parse the answer
- def get_answer(self, resp, index=0):
-   return resp.get('choices')[index].get('text')
- # print out the answer
- def print_answer(self, resp, index=0,is_print_json=False):
-   print('----------')
-   print('The Answer')
-   print('----------')
-   rdata = self.get_answer(resp, index)
-   # print(textwrap.fill(rdata, width=72, replace_whitespace=False))
-   print(rdata)
-   if (is_print_json):
-     print('----------')
-     print('JSON Response')
-     print('----------')
-     print(resp)
-   return
- #
- # ask me function
- def ask_me(self, prompt,
-   model="text-davinci-003",
-   suffix=None,
-   max_tokens=128,     # length of output, max=2048
-   temperature=1.0,    # randomness: 0 to 2.0, higher (2.0) is a lot of random
-   top_p=1.0,          # accurate: 0 to 1.0
-   n=1,                # number of output
-   stream=False,       # partial progress return
-   logprobs=None,      # log properbility of token
-   echo=False,         # include the prompt in the response
-   stop=None,          # stop process on this character
-   presence_penalty=0, # likelyhood of new topic: -2.0 to 2.0
-   frequency_penalty=0,# llikelyhood of repeat: -2.0 to 2.0
-   best_of=1,          # best of choices from "n" above
-   logit_bias=None,    # do not use this word
-   user='None',        # user name for reporting back to OpenAI
-   is_print_json=False,
-   is_return_val=False
-   ):
-   try:
-     response = openai.Completion.create(
-       prompt=prompt,
-       model=model,
-       suffix=suffix,
-       max_tokens=max_tokens,
-       temperature=temperature,
-       top_p=top_p,
-       n=n,
-       stream=stream,
-       logprobs=logprobs,
-       echo=echo,
-       stop=stop,
-       presence_penalty=presence_penalty,
-       frequency_penalty=frequency_penalty,
-       best_of=best_of,
-       #logit_bias=logit_bias,
-       user=user
-     )
-     return_val = None
-     if (is_return_val):
-       return_val = response
-     else:
-       self.print_answer(response,is_print_json=is_print_json)
-     return return_val
-   except Exception as e:
-     print(f'Error on model {model}. {e}')
- #
- def talk_to_me(self, prompt,
-   model='gpt-3.5-turbo',          # model defaut to gpt-3.5-turbo
-   role='user',                    # role can be either "system", "user", or "assistant"
-   #                               # -- below params are fewer then ask_me()
-   max_tokens=128,                 # length of output, max=2048
-   temperature=1.0,                # randomness: 0 to 2.0, higher (2.0) is a lot of random
-   top_p=1.0,                      # accurate: 0 to 1.0
-   n=1,                            # number of output
-   stream=False,                   # partial progress return
-   stop=None,                      # stop process on this character
-   presence_penalty=0,             # likelyhood of new topic: -2.0 to 2.0
-   frequency_penalty=0,            # llikelyhood of repeat: -2.0 to 2.0
-   logit_bias=None,                # do not use this word
-   user='None',                    # user name for reporting back to OpenAI
-   is_print_json=False,
-   is_return_val=False,
-   is_return_conversation=False
-   ):
-   try:
-     if (self.data_chat is None):
-       self.data_chat = [{'role': 'system','content':'It is a wonderful day.'},
-         {'role': role,'content':prompt}]
-     else:
-       self.data_chat.append({'role': role,'content':prompt})
-     #
-     response = openai.ChatCompletion.create(model=model,
-     messages=self.data_chat,
-     max_tokens=max_tokens,
-     temperature=temperature,
-     top_p=top_p,
-     n=n,
-     stream=stream,
-     stop=stop,
-     presence_penalty=presence_penalty,
-     frequency_penalty=frequency_penalty,
-     #logit_bias=logit_bias,
-     user=user
-     )
-     return_msg = response.choices[0].message.content
-   except Exception as e:
-     err = f'Error: {e}'
-     response = err
-   #
-   try:
-     r = response.choices[0].message.role
-     self.data_chat.append({'role': r,'content':return_msg})
-   except Exception as e:
-     print(f'Error: {e}')
-   #
-   return_val = None
-   if (is_return_val):
-     return_val = response
-   elif (is_return_conversation):
-     return_val = self.data_chat
-   else:
-     print(return_msg)
-     if (is_print_json):
-       print(response)
-   return return_val
-   #
-# add module/method
-#
-import functools
-def add_method(cls):
- def decorator(func):
-   @functools.wraps(func)
-   def wrapper(*args, **kwargs):
-     return func(*args, **kwargs)
-   setattr(cls, func.__name__, wrapper)
-   return func # returning func means func can still be used normally
- return decorator
-#
-monty = HFace_Pluto("Monty")
-monty._login_hface()
-print(monty._fetch_version())
-monty._ph()
-print(monty.fetch_system_info())
-monty._ph()
-print(monty.fetch_gpu_info())
-monty._ph()
-print(monty._fetch_host_ip())
-monty._ph()
-
-monty.session_1 = """
-Title: A Concerned Husky Owner and Understanding Veterinarian
-
-[Setting: A brightly lit veterinarian clinic. A woman, Jane, stands by the door with a huskie named Luna by her side. Dr. Samuel, the veterinarian, sits behind the desk. His medical certificate hangs on the wall, next to a small plaque indicating his condition: epilepsy.]
-
-Jane: [holding Luna’s leash tightly] "Hello, Dr. Samuel. I've heard so much about you. I hope you can help Luna; she’s been acting a bit off lately."
-
-Dr. Samuel: [smiling warmly] "Hello Jane, and hello to you too, Luna! I'll do my best. Can you describe what's been going on?"
-
-Jane: "Well, over the past week, she’s been very lethargic and doesn’t seem to respond as quickly as she used to. At first, I thought it might be her age, but it seems too sudden."
-
-Dr. Samuel: "Hmm. Any changes in her diet, environment, or daily routine?"
-
-Jane: "No, not at all. Everything has been consistent."
-
-Dr. Samuel: "I see. We'll certainly look into it. But before we proceed, I should inform you—I have epilepsy. I'm well-managed, but I believe in transparency with my clients. If at any moment you're uncomfortable, please let me know."
-
-Jane: [looking surprised but appreciative] "Oh, thank you for sharing that with me. I think it's brave of you to work in this field with that condition. But Luna and I trust you."
-
-Dr. Samuel: "Thank you, Jane. It's important for me to advocate for those with conditions like mine and show that we can lead successful lives. Now, back to Luna. Any recent incidents that might have caused stress?"
-
-Jane: "Not that I can think of. But I did notice she had what looked like a short tremor a couple of days ago. It lasted only a few seconds, and then she seemed fine."
-
-Dr. Samuel: [leaning forward with interest] "That's an important detail. Seizures can manifest in various ways in dogs, much like in humans. They can range from those tiny tremors you mentioned to more severe forms. It's possible Luna experienced a minor seizure."
-
-Jane: "Oh my! That's concerning. Is it something like your epilepsy?"
-
-Dr. Samuel: "It could be. Epilepsy in dogs isn't uncommon, and huskies are among the breeds that can be predisposed to it. However, it’s essential not to jump to conclusions. We'll need to run some tests to determine the cause."
-
-Jane: "Of course. I just want what's best for Luna."
-
-Dr. Samuel: "I understand. And I'm here to help. Let's start with a complete check-up and blood tests. Depending on the results, we might need to look into further neurological evaluations."
-
-Jane: "Thank you, Dr. Samuel. I'm glad we're in capable hands."
-
-Dr. Samuel: "It's my pleasure, Jane. And remember, even if it turns out to be epilepsy, many dogs live full, happy lives with the right treatment and care. Just like humans."
-
-Jane: [smiling] "Thank you. That’s comforting to hear."
-
-[End Scene.]
-"""
-monty.session_2 = """
-[Setting: A cozy veterinarian clinic, filled with the soft hum of fluorescent lights overhead. In the center of the room, Mrs. Collins holds a fluffy Persian cat named Muffin in her arms. Dr. Martinez, the veterinarian, is seated behind a desk, looking over Muffin's previous records.]
-
-Mrs. Collins: [stroking Muffin's fur gently] "Dr. Martinez, I'm so worried. Muffin has always been such a good eater, but she's barely touched her food for days."
-
-Dr. Martinez: [looking up with a reassuring smile] "Hello Mrs. Collins. It's always a pleasure to see Muffin, even under these circumstances. Can you tell me when she last ate properly?"
-
-Mrs. Collins: "It's been about four days. At first, I thought she might be bored with her food, so I tried giving her a new brand, but she didn't seem interested in that either."
-
-Dr. Martinez: "Have there been any other changes? Vomiting, diarrhea, lethargy, or behavioral shifts?"
-
-Mrs. Collins: "She's been more withdrawn than usual. I found her hiding under the bed more often, which isn't like her at all."
-
-Dr. Martinez: "I see. Persians, with their distinct facial structures, can sometimes develop dental or oral issues that might deter them from eating. But behavioral changes can also indicate discomfort or illness elsewhere. I'd like to conduct a full examination to rule out any potential problems. With your permission, of course."
-
-Mrs. Collins: "Of course, Dr. Martinez. I just want to know what's wrong and how I can help her."
-
-Dr. Martinez: [gently lifting Muffin from Mrs. Collins's arms and placing her on the examination table] "Let's start by checking her teeth and mouth."
-
-[After a few moments of examining Muffin's mouth]
-
-Dr. Martinez: "Her teeth seem to be in good shape, no apparent dental issues. Let's check her abdomen."
-
-[Muffin gives a low growl as Dr. Martinez gently presses on her abdomen]
-
-Dr. Martinez: "She seems a bit tender here. It's possible she could have an obstruction or some gastrointestinal discomfort. We might need to take an X-ray to be sure."
-
-Mrs. Collins: [looking worried] "Oh dear! Is it serious?"
-
-Dr. Martinez: "It's too early to say, Mrs. Collins. But it's good that you brought her in when you did. Early detection can make all the difference."
-
-Mrs. Collins: "Please do whatever you need to do. I just want her to be okay."
-
-Dr. Martinez: "We'll do our best. Let's get those X-rays and see if we can pinpoint the issue. And don't worry, Mrs. Collins, Muffin is in good hands."
-
-Mrs. Collins: [sighing with relief] "Thank you, Dr. Martinez. I knew bringing her here was the right choice."
-
-[End Scene.]
-"""
-monty.session_3 = """
-Mr. Barkley: "Dr. Whiskerstein! Emergency! Rover thinks he's a cat!"
-
-Dr. Whiskerstein: [peering through the giant magnifying glass at Rover, causing the dog's eyes to comically enlarge] "Hmm... indeed! Very cat-like symptoms! Does he also hate water and climb trees?"
-
-Mr. Barkley: "No, but he's NOT eating his food! Instead, he's been batting at this feathered cat toy for hours. Yesterday, he tried to fit into a cardboard box! It was... a spectacle."
-
-Dr. Whiskerstein: "Oh my! Did he also try to conquer the world with his cuteness and indifference?"
-
-Mr. Barkley: "Well, he did knock a vase off the table and then looked at me like it was my fault."
-
-Dr. Whiskerstein: [gasping dramatically] "The transformation is complete! Tell me, has he been hanging around any feline influencers lately?"
-
-Mr. Barkley: "Well, my neighbor did get a new cat, Sir Purr-a-Lot, who's always wearing those trendy cat sunglasses. They've been peering at each other across the fence."
-
-Dr. Whiskerstein: "Ah-ha! Sir Purr-a-Lot strikes again! He's been teaching dogs the way of the cat. Last week, a bulldog came in here trying to use a litter box!"
-
-Mr. Barkley: "Goodness! What do we do, Doc? I miss my dog who, you know, acted like a dog."
-
-Dr. Whiskerstein: "Fear not! I prescribe... a week of doggy activities! Fetch, tug of war, and absolutely NO cat videos on YouTube."
-
-Mr. Barkley: "And what about his diet?"
-
-Dr. Whiskerstein: "Swap the feathered toys with bacon treats. If that doesn't bring the dog out in him, I don’t know what will!"
-
-Mr. Barkley: "Thank you, Dr. Whiskerstein! Come on, Rover. Let’s reclaim your canine pride."
-
-Dr. Whiskerstein: [saluting with the oversized magnifying glass] "Godspeed, Mr. Barkley! And beware of those feline influencers."
-
-[End Scene.]
-"""
-
-@add_method(HFace_Pluto)
-def talk_to_me(self, prompt,
- model='gpt-3.5-turbo',          # model defaut to gpt-3.5-turbo
- role='user',                    # role can be either "system", "user", or "assistant"
- #                               # -- below params are fewer then ask_me()
- max_tokens=1050,                 # length of output, max=2048
- temperature=0.7,                # randomness: 0 to 2.0, higher (2.0) is a lot of random
- top_p=1.0,                      # accurate: 0 to 1.0
- n=1,                            # number of output
- stream=False,                   # partial progress return
- stop=None,                      # stop process on this character
- presence_penalty=0,             # likelyhood of new topic: -2.0 to 2.0
- frequency_penalty=0,            # llikelyhood of repeat: -2.0 to 2.0
- logit_bias=None,                # do not use this word
- user='None',                    # user name for reporting back to OpenAI
- is_print_json=False,
- is_return_val=False,
- is_return_conversation=False,
- data_chat=None
- ):
- try:
-   if (data_chat is None):
-     self.data_chat = [{'role': 'system','content':'It is a wonderful day.'},
-       {'role': role,'content':prompt}]
-   else:
-     self.data_chat = data_chat
-   #
-   response = openai.ChatCompletion.create(model=model,
-   messages=self.data_chat,
-   max_tokens=max_tokens,
-   temperature=temperature,
-   top_p=top_p,
-   n=n,
-   stream=stream,
-   stop=stop,
-   presence_penalty=presence_penalty,
-   frequency_penalty=frequency_penalty,
-   #logit_bias=logit_bias,
-   user=user
-   )
-   #return_msg = response.choices[0].message.content
- except Exception as e:
-   # use older model syntax
-   #
-   try:
-     response = openai.Completion.create(
-     model=model,
-     prompt = prompt,
-     max_tokens=max_tokens,
-     n=1,
-     stop=None,
-     temperature=temperature)
-     # answer = response.choices[0].text.strip()
-   except Exception as e:
-     response = e
-   #
- return response
-#
-@add_method(HFace_Pluto)
-def _fetch_response_msg(self, resp):
- try:
-   msg = resp.choices[0].message.content
- except Exception as e:
-   try:
-     msg = resp.choices[0].text.strip()
-   except Exception as e:
-     msg = f'{resp}: and : {e}'
- return msg
-#
-@add_method(HFace_Pluto)
-def _fetch_response_cost(self, resp):
- try:
-   m = str(resp.model)
-   if m.startswith('gpt-4'):
-     rate = 0.0675 / 1000
-   elif m.startswith('gpt-3'):
-     rate = 0.002625 / 1000
-   else:
-     rate = 0.0008 / 1000
-   cost = round((resp.usage.total_tokens * rate), 4)
-   if cost == 0.0:
-     cost_str = f'${cost} (less then 1/100th of penny)'
-   else:
-     cost_str = f'${cost}'
- except Exception as e:
-   cost = 0.00001
-   cost_str ='$0.0000 (less then 1/100th of penny)'
- return cost, cost_str
-
-@add_method(HFace_Pluto)
-def _fetch_answer(self, px, model='gpt-4',is_json_output=False, session=None):
- if (session is None):
-   session = self.session_1
- #
- start = time.process_time()
- p = f'{px} {session}'
- resp = monty.talk_to_me(p, model=model, max_tokens=1000)
- end = time.process_time()
- cost, cost_str = monty._fetch_response_cost(resp)
- try:
-   resp["est_cost"] = cost
-   resp["est_cpu_sec"] = end - start
-   val = f'LLM Response:\n------------\n{monty._fetch_response_msg(resp)}\n------------\nCost: {cost_str}\nLLM Model: {model}\nLLM CPU Time Sec: {round(resp["est_cpu_sec"],4)}'
- except Exception as e:
-   val = f'Warning: {e}: {resp}'
- if is_json_output:
-   return resp
- else:
-   return val
-
-@add_method(HFace_Pluto)
-def fetch_summary(self, model='gpt-4',is_json_output=False, session=None):
- px = 'Summarize the following conversation in a professional tone:'
- val = self._fetch_answer(px, model=model,is_json_output=is_json_output, session=session)
- return val
-#
-@add_method(HFace_Pluto)
-def fetch_topic(self, model='gpt-4',is_json_output=False, session=None):
- px = 'Write a list of key topics for the following:'
- val = self._fetch_answer(px, model=model,is_json_output=is_json_output, session=session)
- return val
-#
-@add_method(HFace_Pluto)
-def fetch_freeform_tag(self, model='gpt-4',is_json_output=False, session=None):
- px = 'Write a list of five top hashtag based on the following:'
- val = self._fetch_answer(px, model=model,is_json_output=is_json_output, session=session)
- return val
-#
-@add_method(HFace_Pluto)
-def fetch_target_tag(self, model='gpt-4',is_json_output=False, session=None):
- px = 'Kinship-tags: cat, cat food, cat nutrition, cat products, dog, dog food, health, wellness,  nutrition, dog products, kitten food, sustainable, vitamins, recipes, disease: Select the top 5 Kinship-tags for the following chat session:'
- val = self._fetch_answer(px, model=model,is_json_output=is_json_output, session=session)
- return val
-#
-@add_method(HFace_Pluto)
-def fetch_diagnose(self, model='gpt-4',is_json_output=False, session=None):
- px = 'What is the diagnose for the pet based on the following:'
- val = self._fetch_answer(px, model=model,is_json_output=is_json_output, session=session)
- return val
-#
-@add_method(HFace_Pluto)
-def fetch_treatment(self, model='gpt-4',is_json_output=False, session=None):
- px = 'What is the treatment for the pet based on the following:'
- val = self._fetch_answer(px, model=model,is_json_output=is_json_output, session=session)
- return val
-#
-@add_method(HFace_Pluto)
-def fetch_article(self, model='gpt-4',is_json_output=False, session=None):
- px = 'Write a list of recomendation article to read on the web with link based on the following chat session:'
- val = self._fetch_answer(px, model=model,is_json_output=is_json_output, session=session)
- return val
-#
-
-css = """
-#poc_radio {background-color: #EFEFEF; color: #333333}
-#text_box {background-color: #F5F5F5}
-#output_text_box {background-color: #E6E6E6}
-#llm_radio {background-color: #D9D9D9}
-#random_article {background-color: #B0E57C} /* A different light color */
-#random_article_text_box {background-color: #B0E57C} /* A different light color */
-#poc_radio {
- font-size: 16px; !important
- font-weight: bold; !important
-}
-#poc_function .gradio-rb input[type="radio"] + label::before { background-color: blue; }
-}
-"""
-csv_url = "https://huggingface.co/spaces/rahul-pandey-ct/kinship-llm-poc/raw/main/clean_article_pet_combined.csv"
-df_articles = pandas.read_csv(csv_url)
-
-all_group_options = ["★ Summary", "★ Articles", "★ Pattern", "Freeform Tags", "Target Tags", "Diagnose", "Treatment", "*JSON"]
-
-combined_radio = gradio.Radio(all_group_options, label="POC Function",elem_id="poc_radio", info="All top choices of POC functions are indicated by '★'")
-
-textbox = gradio.Textbox(lines=20, label="Vet Chat Session:", placeholder='',elem_id="text_box")
-
-llm_model_choices = ["gpt-4" , "gpt-3.5-turbo", "text-davinci-002", "text-ada-001"]
-llm_model_radio = gradio.Radio(llm_model_choices, label="LLM Model",elem_id="llm_radio", value= llm_model_choices[0])
-
-random_article_text = gradio.Checkbox(label="Random Article Text",elem_id="random_article")
-
-in_box = [textbox, combined_radio, random_article_text, llm_model_radio]
-
-out_box = [gradio.Textbox(lines=4, label="LLM Response, Cost, and Time:",elem_id="output_text_box")]
-random_article_text_box = gradio.Textbox(lines=20, label="Random Article Text:", placeholder='', elem_id="random_article_text_box",value='')
-out_box.append(random_article_text_box)
-
-title = "Kinship with Code and Theory Presenting Multiple LLMs for Pets"
-desc = '*(1) Enter the vet chat session (OR click on the example below), (2) Select the POC function, (3) Click on Submit Button.'
-arti = '''
-<ul><li>Ping Duc Haba if you have question on these multiple POCs.</li>
-<li>Notices on the $Cost and LLM inference time.</li>
-<li>The API description link is at the bottom of the page.</li>
-<li>Chose the POC function "*JSON" to view the API JSON reponse.</li>
-</ul>
-'''
-exp = [
- [monty.session_1,'★ Summary', False, 'gpt-3.5-turbo'],
- [monty.session_2,'★ Summary', False, 'gpt-3.5-turbo']
- ]
-
-def handle_interface(chat, fn, random_article_text, llm_model):
-
-   if random_article_text:
-     chat = df_articles['article_text'].sample(n=1).values[0]
-     val = monty.talk_to_kinship(chat, llm_model, fn, random_article_text)
-     random_article_text_box.value = chat
-     return [val,chat]
-
-   else:
-     val = monty.talk_to_kinship(chat, llm_model, fn, random_article_text)
-     return [val,""]
-
-@add_method(HFace_Pluto)
-def talk_to_kinship(self, chat, llm_model, fn, random_article_text):
-   if random_article_text:
-     if fn == '★ Summary':
-       val = self.fetch_summary(session=chat, model=llm_model)
-     elif fn == 'Topic':
-       val = self.fetch_topic(session=chat, model=llm_model)
-     elif fn == 'Freeform Tags':
-       val = self.fetch_freeform_tag(session=chat, model=llm_model)
-     elif fn == 'Target Tags':
-       val = self.fetch_target_tag(session=chat, model=llm_model)
-     elif fn == 'Diagnose':
-       val = self.fetch_diagnose(session=chat, model=llm_model)
-     elif fn == 'Treatment':
-       val = self.fetch_treatment(session=chat, model=llm_model)
-     elif fn == '★ Articles':
-       val = f'{fn} POC function Implement on other notebook.'
-     elif fn == '*JSON':
-       val = self.fetch_summary(session=chat, is_json_output=True, model=llm_model)
-     else:
-       val = f'{fn} is not yet implemented.'
-
-   else:
-     if fn == '★ Summary':
-       val = self.fetch_summary(session=chat, model=llm_model)
-     elif fn == 'Topic':
-       val = self.fetch_topic(session=chat, model=llm_model)
-     elif fn == 'Freeform Tags':
-       val = self.fetch_freeform_tag(session=chat, model=llm_model)
-     elif fn == 'Target Tags':
-       val = self.fetch_target_tag(session=chat, model=llm_model)
-     elif fn == 'Diagnose':
-       val = self.fetch_diagnose(session=chat, model=llm_model)
-     elif fn == 'Treatment':
-       val = self.fetch_treatment(session=chat, model=llm_model)
-     elif fn == '★ Articles':
-       val = self.fetch_article(session=chat, model=llm_model)
-     elif fn == '*JSON':
-       val = self.fetch_summary(session=chat, is_json_output=True, model=llm_model)
-     else:
-       val = f'{fn} is not yet implemented.'
-
-   return val
-
-interface = gradio.Interface(
- fn=handle_interface,
- inputs=in_box,
- outputs=out_box,
- examples=exp,
- title=title,
- description=desc,
- allow_flagging="manual",
- flagging_options=["GOOD", "BAD"],
- article=arti
-)
-
-interface.css = css
-
-interface.launch(debug=True)
diff --git a/spaces/rbanfield/libfacedetection/src/Makefile b/spaces/rbanfield/libfacedetection/src/Makefile
deleted file mode 100644
index 8bc68b632a5141465bbc39bc39e00f0c510df97d..0000000000000000000000000000000000000000
--- a/spaces/rbanfield/libfacedetection/src/Makefile
+++ /dev/null
@@ -1,10 +0,0 @@
-CFLAGS=-O3 -Wall
-
-detect-image: detect-image.o
-	g++ $(CFLAGS) -o detect-image -L /libfacedetection/build/install/lib/ -I /usr/include/opencv4/ -I /libfacedetection/build/install/include/facedetection detect-image.o -lfacedetection -fopenmp -lopencv_imgcodecs -lopencv_objdetect -lopencv_features2d -lopencv_imgproc -lopencv_highgui -lopencv_core
-
-detect-image.o: detect-image.cpp
-	g++ $(CFLAGS) -I /usr/include/opencv4 -I /libfacedetection/build/install/include/facedetection -o detect-image.o -c detect-image.cpp -fopenmp
-
-clean:
-	rm -f detect-image.o detect-image
diff --git a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Alexandru Busuioceanu Zamolxis Pdf Download 1.md b/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Alexandru Busuioceanu Zamolxis Pdf Download 1.md
deleted file mode 100644
index 3263707d65539703d45c97c84204ab7d299a6297..0000000000000000000000000000000000000000
--- a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Alexandru Busuioceanu Zamolxis Pdf Download 1.md	
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diff --git a/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Boost Python-vc71-mt-1 32.dll Is Missing From My Computer !FULL!.md b/spaces/recenWmenso/ChatGPT-with-Voice-Cloning-for-All/datasets/Boost Python-vc71-mt-1 32.dll Is Missing From My Computer !FULL!.md
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diff --git a/spaces/removebg/removebg/README.md b/spaces/removebg/removebg/README.md
deleted file mode 100644
index 86949c8c85fb6b9b4ddab4c649fcabbdb3657865..0000000000000000000000000000000000000000
--- a/spaces/removebg/removebg/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Removebg
-emoji: 📚
-colorFrom: blue
-colorTo: yellow
-sdk: gradio
-sdk_version: 3.36.1
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/renatotn7/question-answering-portuguese-with-BetterTransformer/app.py b/spaces/renatotn7/question-answering-portuguese-with-BetterTransformer/app.py
deleted file mode 100644
index c6974690bb3578868465e31885ed42d0c4afa057..0000000000000000000000000000000000000000
--- a/spaces/renatotn7/question-answering-portuguese-with-BetterTransformer/app.py
+++ /dev/null
@@ -1,103 +0,0 @@
-import gradio as gr
-import time
-import pandas as pd
-from PIL import Image
-import matplotlib as plt
-
-# device
-import torch
-device = 'cuda:0' if torch.cuda.is_available() else 'cpu'
-
-# models
-model_name_bb = "pierreguillou/bert-base-cased-squad-v1.1-portuguese"
-model_name_bl = "pierreguillou/bert-large-cased-squad-v1.1-portuguese"
-
-# load models
-from transformers import pipeline
-qa_bb = pipeline("question-answering", model_name_bb, device=device)
-
-from optimum.pipelines import pipeline
-qa_bb_better = pipeline("question-answering", model_name_bb, accelerator="bettertransformer", device=device)
-
-from transformers import pipeline
-qa_bl = pipeline("question-answering", model_name_bl, device=device)
-
-from optimum.pipelines import pipeline
-qa_bl_better = pipeline("question-answering", model_name_bl, accelerator="bettertransformer", device=device)
-
-# function to get results
-def get_answer(context, question):
-
-  # get predictions
-  start = time.perf_counter()
-  answer_bl = qa_bl(question=question, context=context)
-  end = time.perf_counter()
-  diff_bl = round(end - start, 2)
-  answer_bl["time (s)"] = diff_bl
-  del answer_bl["start"]
-  del answer_bl["end"]
-
-  start = time.perf_counter()
-  answer_bl_better = qa_bl_better(question=question, context=context)
-  end = time.perf_counter()
-  diff_bl_better = round(end - start, 2)
-  answer_bl_better["time (s)"] = diff_bl_better
-  del answer_bl_better["start"]
-  del answer_bl_better["end"]
-
-  start = time.perf_counter()
-  answer_bb = qa_bb(question=question, context=context)
-  end = time.perf_counter()
-  diff_bb = round(end - start, 2)
-  answer_bb["time (s)"] = diff_bb
-  del answer_bb["start"]
-  del answer_bb["end"]
-
-  start = time.perf_counter()
-  answer_bb_better = qa_bb_better(question=question, context=context)
-  end = time.perf_counter()
-  diff_bb_better = round(end - start, 2)
-  answer_bb_better["time (s)"] = diff_bb_better
-  del answer_bb_better["start"]
-  del answer_bb_better["end"]
-
-  answer = dict()
-  answer["BERT large"] = answer_bl
-  answer["BERT large (BetterTransformer)"] = answer_bl_better
-  answer["BERT base"] = answer_bb
-  answer["BERT base (BetterTransformer)"] = answer_bb_better
-
-  # get image of prediction times
-  df = pd.DataFrame.from_dict({"Method":["BERT base (BetterTransformer)", "BERT base", "BERT large (BetterTransformer)", "BERT large"], 
-                               "Time (seconds)":  [answer["BERT base (BetterTransformer)"]["time (s)"], answer["BERT base"]["time (s)"], answer["BERT large (BetterTransformer)"]["time (s)"], answer["BERT large"]["time (s)"]]})
-  ax = df.plot.barh(x='Method', title=f'Prediction times on {str(device).replace("cuda:0", "GPU").replace("cpu", "CPU")}')
-  ax.figure.savefig("img.png", bbox_inches='tight')
-  image = Image.open('img.png')
-
-  return image, answer
-
-title = "QA in Portuguese with BetterTransformer (this App runs on " + str(device).replace("cuda:0", "GPU").replace("cpu", "CPU") + ")"
-description = '<p>(20/11/2022) Forneça seu próprio parágrafo e faça perguntas sobre o texto. Quão bem os modelos respondem?<br />(este aplicativo usa os modelos <a href="https://huggingface.co/pierreguillou/bert-base-cased-squad-v1.1-portuguese">pierreguillou/bert-base-cased-squad-v1.1-portuguese</a> and <a href="https://huggingface.co/pierreguillou/bert-large-cased-squad-v1.1-portuguese">pierreguillou/bert-large-cased-squad-v1.1-portuguese</a> and their versions <a href="https://huggingface.co/docs/optimum/bettertransformer/overview">BetterTransformer</a>)</p><p>Blog post sobre BetterTransformer: <a href="https://medium.com/@pierre_guillou/ia-empresas-diminua-o-tempo-de-infer%C3%AAncia-de-modelos-transformer-com-bettertransformer-584a5a7702c8">IA & empresas | Diminua o tempo de inferência de modelos Transformer com BetterTransformer</a></p>'
-examples = [
-    ["Dom Pedro II foi o segundo e último monarca do Império do Brasil, reinando por mais de 58 anos.", "Quem foi Dom Pedro II?"],
-    ["A pandemia de COVID-19, também conhecida como pandemia de coronavírus, é uma pandemia em curso de COVID-19, uma doença respiratória aguda causada pelo coronavírus da síndrome respiratória aguda grave 2 (SARS-CoV-2). A doença foi identificada pela primeira vez em Wuhan, na província de Hubei, República Popular da China, em 1 de dezembro de 2019, mas o primeiro caso foi reportado em 31 de dezembro do mesmo ano.", "Quando começou a pandemia de Covid-19 no mundo?"],
-    ["A pandemia de COVID-19, também conhecida como pandemia de coronavírus, é uma pandemia em curso de COVID-19, uma doença respiratória aguda causada pelo coronavírus da síndrome respiratória aguda grave 2 (SARS-CoV-2). A doença foi identificada pela primeira vez em Wuhan, na província de Hubei, República Popular da China, em 1 de dezembro de 2019, mas o primeiro caso foi reportado em 31 de dezembro do mesmo ano.", "Onde começou a pandemia de Covid-19?"]
-    ]
-
-demo = gr.Interface(
-    fn=get_answer,
-    inputs=[
-        gr.Textbox(lines=7, label="Context"), 
-        gr.Textbox(lines=2, label="Question")
-        ],
-    outputs=[
-        gr.Image(label="Prediction times", type="pil"),
-        gr.JSON(label="Results"),
-        ],
-    title=title,
-    description=description,
-    examples=examples,
-    allow_flagging="never")
-
-if __name__ == "__main__":
-    demo.launch()
\ No newline at end of file
diff --git a/spaces/robin0307/MMOCR/configs/_base_/recog_models/abinet.py b/spaces/robin0307/MMOCR/configs/_base_/recog_models/abinet.py
deleted file mode 100644
index 19c6b66731f0b205741037ece8d6b49f91d0110b..0000000000000000000000000000000000000000
--- a/spaces/robin0307/MMOCR/configs/_base_/recog_models/abinet.py
+++ /dev/null
@@ -1,70 +0,0 @@
-# num_chars depends on the configuration of label_convertor. The actual
-# dictionary size is 36 + 1 (<BOS/EOS>).
-# TODO: Automatically update num_chars based on the configuration of
-# label_convertor
-num_chars = 37
-max_seq_len = 26
-
-label_convertor = dict(
-    type='ABIConvertor',
-    dict_type='DICT36',
-    with_unknown=False,
-    with_padding=False,
-    lower=True,
-)
-
-model = dict(
-    type='ABINet',
-    backbone=dict(type='ResNetABI'),
-    encoder=dict(
-        type='ABIVisionModel',
-        encoder=dict(
-            type='TransformerEncoder',
-            n_layers=3,
-            n_head=8,
-            d_model=512,
-            d_inner=2048,
-            dropout=0.1,
-            max_len=8 * 32,
-        ),
-        decoder=dict(
-            type='ABIVisionDecoder',
-            in_channels=512,
-            num_channels=64,
-            attn_height=8,
-            attn_width=32,
-            attn_mode='nearest',
-            use_result='feature',
-            num_chars=num_chars,
-            max_seq_len=max_seq_len,
-            init_cfg=dict(type='Xavier', layer='Conv2d')),
-    ),
-    decoder=dict(
-        type='ABILanguageDecoder',
-        d_model=512,
-        n_head=8,
-        d_inner=2048,
-        n_layers=4,
-        dropout=0.1,
-        detach_tokens=True,
-        use_self_attn=False,
-        pad_idx=num_chars - 1,
-        num_chars=num_chars,
-        max_seq_len=max_seq_len,
-        init_cfg=None),
-    fuser=dict(
-        type='ABIFuser',
-        d_model=512,
-        num_chars=num_chars,
-        init_cfg=None,
-        max_seq_len=max_seq_len,
-    ),
-    loss=dict(
-        type='ABILoss',
-        enc_weight=1.0,
-        dec_weight=1.0,
-        fusion_weight=1.0,
-        num_classes=num_chars),
-    label_convertor=label_convertor,
-    max_seq_len=max_seq_len,
-    iter_size=3)
diff --git a/spaces/robin0307/MMOCR/configs/textdet/dbnetpp/README.md b/spaces/robin0307/MMOCR/configs/textdet/dbnetpp/README.md
deleted file mode 100644
index 995254cb89c1b88bb3698d9d550f8e0ac7ba69f6..0000000000000000000000000000000000000000
--- a/spaces/robin0307/MMOCR/configs/textdet/dbnetpp/README.md
+++ /dev/null
@@ -1,33 +0,0 @@
-# DBNetpp
-
-> [Real-Time Scene Text Detection with Differentiable Binarization and Adaptive Scale Fusion](https://arxiv.org/abs/2202.10304)
-
-<!-- [ALGORITHM] -->
-
-## Abstract
-
-Recently, segmentation-based scene text detection methods have drawn extensive attention in the scene text detection field, because of their superiority in detecting the text instances of arbitrary shapes and extreme aspect ratios, profiting from the pixel-level descriptions. However, the vast majority of the existing segmentation-based approaches are limited to their complex post-processing algorithms and the scale robustness of their segmentation models, where the post-processing algorithms are not only isolated to the model optimization but also time-consuming and the scale robustness is usually strengthened by fusing multi-scale feature maps directly. In this paper, we propose a Differentiable Binarization (DB) module that integrates the binarization process, one of the most important steps in the post-processing procedure, into a segmentation network. Optimized along with the proposed DB module, the segmentation network can produce more accurate results, which enhances the accuracy of text detection with a simple pipeline. Furthermore, an efficient Adaptive Scale Fusion (ASF) module is proposed to improve the scale robustness by fusing features of different scales adaptively. By incorporating the proposed DB and ASF with the segmentation network, our proposed scene text detector consistently achieves state-of-the-art results, in terms of both detection accuracy and speed, on five standard benchmarks.
-
-<div align=center>
-<img src="https://user-images.githubusercontent.com/45810070/166850828-f1e48c25-4a0f-429d-ae54-6997ed25c062.png"/>
-</div>
-
-## Results and models
-
-### ICDAR2015
-
-|                  Method                   |                  Pretrained Model                   |  Training set   |    Test set    | #epochs | Test size | Recall | Precision | Hmean |                  Download                   |
-| :---------------------------------------: | :-------------------------------------------------: | :-------------: | :------------: | :-----: | :-------: | :----: | :-------: | :---: | :-----------------------------------------: |
-| [DBNetpp_r50dcn](/configs/textdet/dbnetpp/dbnetpp_r50dcnv2_fpnc_1200e_icdar2015.py) | [Synthtext](/configs/textdet/dbnetpp/dbnetpp_r50dcnv2_fpnc_100k_iter_synthtext.py) ([model](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnetpp_r50dcnv2_fpnc_100k_iter_synthtext-20220502-db297554.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnetpp_r50dcnv2_fpnc_100k_iter_synthtext-20220502-db297554.log.json)) | ICDAR2015 Train | ICDAR2015 Test |  1200   |   1024    | 0.822  |   0.901   | 0.860 | [model](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnetpp_r50dcnv2_fpnc_1200e_icdar2015-20220502-d7a76fff.pth) \| [log](https://download.openmmlab.com/mmocr/textdet/dbnet/dbnetpp_r50dcnv2_fpnc_1200e_icdar2015-20220502-d7a76fff.log.json) |
-
-## Citation
-
-```bibtex
-@article{liao2022real,
-    title={Real-Time Scene Text Detection with Differentiable Binarization and Adaptive Scale Fusion},
-    author={Liao, Minghui and Zou, Zhisheng and Wan, Zhaoyi and Yao, Cong and Bai, Xiang},
-    journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
-    year={2022},
-    publisher={IEEE}
-}
-```
diff --git a/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/models/detectors/panoptic_two_stage_segmentor.py b/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/models/detectors/panoptic_two_stage_segmentor.py
deleted file mode 100644
index 5ad49bac705a677d1656cf95d2686fd83d2b1b47..0000000000000000000000000000000000000000
--- a/spaces/rockeycoss/Prompt-Segment-Anything-Demo/mmdet/models/detectors/panoptic_two_stage_segmentor.py
+++ /dev/null
@@ -1,279 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import mmcv
-import numpy as np
-import torch
-
-from mmdet.core import INSTANCE_OFFSET, bbox2roi, multiclass_nms
-from mmdet.core.visualization import imshow_det_bboxes
-from ..builder import DETECTORS, build_head
-from ..roi_heads.mask_heads.fcn_mask_head import _do_paste_mask
-from .two_stage import TwoStageDetector
-
-
-@DETECTORS.register_module()
-class TwoStagePanopticSegmentor(TwoStageDetector):
-    """Base class of Two-stage Panoptic Segmentor.
-
-    As well as the components in TwoStageDetector, Panoptic Segmentor has extra
-    semantic_head and panoptic_fusion_head.
-    """
-
-    def __init__(
-            self,
-            backbone,
-            neck=None,
-            rpn_head=None,
-            roi_head=None,
-            train_cfg=None,
-            test_cfg=None,
-            pretrained=None,
-            init_cfg=None,
-            # for panoptic segmentation
-            semantic_head=None,
-            panoptic_fusion_head=None):
-        super(TwoStagePanopticSegmentor,
-              self).__init__(backbone, neck, rpn_head, roi_head, train_cfg,
-                             test_cfg, pretrained, init_cfg)
-        if semantic_head is not None:
-            self.semantic_head = build_head(semantic_head)
-        if panoptic_fusion_head is not None:
-            panoptic_cfg = test_cfg.panoptic if test_cfg is not None else None
-            panoptic_fusion_head_ = panoptic_fusion_head.deepcopy()
-            panoptic_fusion_head_.update(test_cfg=panoptic_cfg)
-            self.panoptic_fusion_head = build_head(panoptic_fusion_head_)
-
-            self.num_things_classes = self.panoptic_fusion_head.\
-                num_things_classes
-            self.num_stuff_classes = self.panoptic_fusion_head.\
-                num_stuff_classes
-            self.num_classes = self.panoptic_fusion_head.num_classes
-
-    @property
-    def with_semantic_head(self):
-        return hasattr(self,
-                       'semantic_head') and self.semantic_head is not None
-
-    @property
-    def with_panoptic_fusion_head(self):
-        return hasattr(self, 'panoptic_fusion_heads') and \
-               self.panoptic_fusion_head is not None
-
-    def forward_dummy(self, img):
-        """Used for computing network flops.
-
-        See `mmdetection/tools/get_flops.py`
-        """
-        raise NotImplementedError(
-            f'`forward_dummy` is not implemented in {self.__class__.__name__}')
-
-    def forward_train(self,
-                      img,
-                      img_metas,
-                      gt_bboxes,
-                      gt_labels,
-                      gt_bboxes_ignore=None,
-                      gt_masks=None,
-                      gt_semantic_seg=None,
-                      proposals=None,
-                      **kwargs):
-        x = self.extract_feat(img)
-        losses = dict()
-
-        # RPN forward and loss
-        if self.with_rpn:
-            proposal_cfg = self.train_cfg.get('rpn_proposal',
-                                              self.test_cfg.rpn)
-            rpn_losses, proposal_list = self.rpn_head.forward_train(
-                x,
-                img_metas,
-                gt_bboxes,
-                gt_labels=None,
-                gt_bboxes_ignore=gt_bboxes_ignore,
-                proposal_cfg=proposal_cfg)
-            losses.update(rpn_losses)
-        else:
-            proposal_list = proposals
-
-        roi_losses = self.roi_head.forward_train(x, img_metas, proposal_list,
-                                                 gt_bboxes, gt_labels,
-                                                 gt_bboxes_ignore, gt_masks,
-                                                 **kwargs)
-        losses.update(roi_losses)
-
-        semantic_loss = self.semantic_head.forward_train(x, gt_semantic_seg)
-        losses.update(semantic_loss)
-
-        return losses
-
-    def simple_test_mask(self,
-                         x,
-                         img_metas,
-                         det_bboxes,
-                         det_labels,
-                         rescale=False):
-        """Simple test for mask head without augmentation."""
-        img_shapes = tuple(meta['ori_shape']
-                           for meta in img_metas) if rescale else tuple(
-                               meta['pad_shape'] for meta in img_metas)
-        scale_factors = tuple(meta['scale_factor'] for meta in img_metas)
-
-        if all(det_bbox.shape[0] == 0 for det_bbox in det_bboxes):
-            masks = []
-            for img_shape in img_shapes:
-                out_shape = (0, self.roi_head.bbox_head.num_classes) \
-                            + img_shape[:2]
-                masks.append(det_bboxes[0].new_zeros(out_shape))
-            mask_pred = det_bboxes[0].new_zeros((0, 80, 28, 28))
-            mask_results = dict(
-                masks=masks, mask_pred=mask_pred, mask_feats=None)
-            return mask_results
-
-        _bboxes = [det_bboxes[i][:, :4] for i in range(len(det_bboxes))]
-        if rescale:
-            if not isinstance(scale_factors[0], float):
-                scale_factors = [
-                    det_bboxes[0].new_tensor(scale_factor)
-                    for scale_factor in scale_factors
-                ]
-            _bboxes = [
-                _bboxes[i] * scale_factors[i] for i in range(len(_bboxes))
-            ]
-
-        mask_rois = bbox2roi(_bboxes)
-        mask_results = self.roi_head._mask_forward(x, mask_rois)
-        mask_pred = mask_results['mask_pred']
-        # split batch mask prediction back to each image
-        num_mask_roi_per_img = [len(det_bbox) for det_bbox in det_bboxes]
-        mask_preds = mask_pred.split(num_mask_roi_per_img, 0)
-
-        # resize the mask_preds to (K, H, W)
-        masks = []
-        for i in range(len(_bboxes)):
-            det_bbox = det_bboxes[i][:, :4]
-            det_label = det_labels[i]
-
-            mask_pred = mask_preds[i].sigmoid()
-
-            box_inds = torch.arange(mask_pred.shape[0])
-            mask_pred = mask_pred[box_inds, det_label][:, None]
-
-            img_h, img_w, _ = img_shapes[i]
-            mask_pred, _ = _do_paste_mask(
-                mask_pred, det_bbox, img_h, img_w, skip_empty=False)
-            masks.append(mask_pred)
-
-        mask_results['masks'] = masks
-
-        return mask_results
-
-    def simple_test(self, img, img_metas, proposals=None, rescale=False):
-        """Test without Augmentation."""
-        x = self.extract_feat(img)
-
-        if proposals is None:
-            proposal_list = self.rpn_head.simple_test_rpn(x, img_metas)
-        else:
-            proposal_list = proposals
-
-        bboxes, scores = self.roi_head.simple_test_bboxes(
-            x, img_metas, proposal_list, None, rescale=rescale)
-
-        pan_cfg = self.test_cfg.panoptic
-        # class-wise predictions
-        det_bboxes = []
-        det_labels = []
-        for bboxe, score in zip(bboxes, scores):
-            det_bbox, det_label = multiclass_nms(bboxe, score,
-                                                 pan_cfg.score_thr,
-                                                 pan_cfg.nms,
-                                                 pan_cfg.max_per_img)
-            det_bboxes.append(det_bbox)
-            det_labels.append(det_label)
-
-        mask_results = self.simple_test_mask(
-            x, img_metas, det_bboxes, det_labels, rescale=rescale)
-        masks = mask_results['masks']
-
-        seg_preds = self.semantic_head.simple_test(x, img_metas, rescale)
-
-        results = []
-        for i in range(len(det_bboxes)):
-            pan_results = self.panoptic_fusion_head.simple_test(
-                det_bboxes[i], det_labels[i], masks[i], seg_preds[i])
-            pan_results = pan_results.int().detach().cpu().numpy()
-            result = dict(pan_results=pan_results)
-            results.append(result)
-        return results
-
-    def show_result(self,
-                    img,
-                    result,
-                    score_thr=0.3,
-                    bbox_color=(72, 101, 241),
-                    text_color=(72, 101, 241),
-                    mask_color=None,
-                    thickness=2,
-                    font_size=13,
-                    win_name='',
-                    show=False,
-                    wait_time=0,
-                    out_file=None):
-        """Draw `result` over `img`.
-
-        Args:
-            img (str or Tensor): The image to be displayed.
-            result (dict): The results.
-
-            score_thr (float, optional): Minimum score of bboxes to be shown.
-                Default: 0.3.
-            bbox_color (str or tuple(int) or :obj:`Color`):Color of bbox lines.
-               The tuple of color should be in BGR order. Default: 'green'.
-            text_color (str or tuple(int) or :obj:`Color`):Color of texts.
-               The tuple of color should be in BGR order. Default: 'green'.
-            mask_color (None or str or tuple(int) or :obj:`Color`):
-               Color of masks. The tuple of color should be in BGR order.
-               Default: None.
-            thickness (int): Thickness of lines. Default: 2.
-            font_size (int): Font size of texts. Default: 13.
-            win_name (str): The window name. Default: ''.
-            wait_time (float): Value of waitKey param.
-                Default: 0.
-            show (bool): Whether to show the image.
-                Default: False.
-            out_file (str or None): The filename to write the image.
-                Default: None.
-
-        Returns:
-            img (Tensor): Only if not `show` or `out_file`.
-        """
-        img = mmcv.imread(img)
-        img = img.copy()
-        pan_results = result['pan_results']
-        # keep objects ahead
-        ids = np.unique(pan_results)[::-1]
-        legal_indices = ids != self.num_classes  # for VOID label
-        ids = ids[legal_indices]
-        labels = np.array([id % INSTANCE_OFFSET for id in ids], dtype=np.int64)
-        segms = (pan_results[None] == ids[:, None, None])
-
-        # if out_file specified, do not show image in window
-        if out_file is not None:
-            show = False
-        # draw bounding boxes
-        img = imshow_det_bboxes(
-            img,
-            segms=segms,
-            labels=labels,
-            class_names=self.CLASSES,
-            bbox_color=bbox_color,
-            text_color=text_color,
-            mask_color=mask_color,
-            thickness=thickness,
-            font_size=font_size,
-            win_name=win_name,
-            show=show,
-            wait_time=wait_time,
-            out_file=out_file)
-
-        if not (show or out_file):
-            return img
diff --git a/spaces/rockeycoss/Prompt-Segment-Anything-Demo/projects/instance_segment_anything/models/focalnet_dino/models/dino/util/utils.py b/spaces/rockeycoss/Prompt-Segment-Anything-Demo/projects/instance_segment_anything/models/focalnet_dino/models/dino/util/utils.py
deleted file mode 100644
index d747bef2541d5cd4d17b61778c3c84b413795467..0000000000000000000000000000000000000000
--- a/spaces/rockeycoss/Prompt-Segment-Anything-Demo/projects/instance_segment_anything/models/focalnet_dino/models/dino/util/utils.py
+++ /dev/null
@@ -1,473 +0,0 @@
-from collections import OrderedDict
-from copy import deepcopy
-import json
-import warnings
-
-import torch
-import numpy as np
-
-def slprint(x, name='x'):
-    if isinstance(x, (torch.Tensor, np.ndarray)):
-        print(f'{name}.shape:', x.shape)
-    elif isinstance(x, (tuple, list)):
-        print('type x:', type(x))
-        for i in range(min(10, len(x))):
-            slprint(x[i], f'{name}[{i}]')
-    elif isinstance(x, dict):
-        for k,v in x.items():
-            slprint(v, f'{name}[{k}]')
-    else:
-        print(f'{name}.type:', type(x))
-
-def clean_state_dict(state_dict):
-    new_state_dict = OrderedDict()
-    for k, v in state_dict.items():
-        if k[:7] == 'module.':
-            k = k[7:]  # remove `module.`
-        new_state_dict[k] = v
-    return new_state_dict
-
-def renorm(img: torch.FloatTensor, mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) \
-        -> torch.FloatTensor:
-    # img: tensor(3,H,W) or tensor(B,3,H,W)
-    # return: same as img
-    assert img.dim() == 3 or img.dim() == 4, "img.dim() should be 3 or 4 but %d" % img.dim() 
-    if img.dim() == 3:
-        assert img.size(0) == 3, 'img.size(0) shoule be 3 but "%d". (%s)' % (img.size(0), str(img.size()))
-        img_perm = img.permute(1,2,0)
-        mean = torch.Tensor(mean)
-        std = torch.Tensor(std)
-        img_res = img_perm * std + mean
-        return img_res.permute(2,0,1)
-    else: # img.dim() == 4
-        assert img.size(1) == 3, 'img.size(1) shoule be 3 but "%d". (%s)' % (img.size(1), str(img.size()))
-        img_perm = img.permute(0,2,3,1)
-        mean = torch.Tensor(mean)
-        std = torch.Tensor(std)
-        img_res = img_perm * std + mean
-        return img_res.permute(0,3,1,2)
-
-
-
-class CocoClassMapper():
-    def __init__(self) -> None:
-        self.category_map_str = {"1": 1, "2": 2, "3": 3, "4": 4, "5": 5, "6": 6, "7": 7, "8": 8, "9": 9, "10": 10, "11": 11, "13": 12, "14": 13, "15": 14, "16": 15, "17": 16, "18": 17, "19": 18, "20": 19, "21": 20, "22": 21, "23": 22, "24": 23, "25": 24, "27": 25, "28": 26, "31": 27, "32": 28, "33": 29, "34": 30, "35": 31, "36": 32, "37": 33, "38": 34, "39": 35, "40": 36, "41": 37, "42": 38, "43": 39, "44": 40, "46": 41, "47": 42, "48": 43, "49": 44, "50": 45, "51": 46, "52": 47, "53": 48, "54": 49, "55": 50, "56": 51, "57": 52, "58": 53, "59": 54, "60": 55, "61": 56, "62": 57, "63": 58, "64": 59, "65": 60, "67": 61, "70": 62, "72": 63, "73": 64, "74": 65, "75": 66, "76": 67, "77": 68, "78": 69, "79": 70, "80": 71, "81": 72, "82": 73, "84": 74, "85": 75, "86": 76, "87": 77, "88": 78, "89": 79, "90": 80}
-        self.origin2compact_mapper = {int(k):v-1 for k,v in self.category_map_str.items()}
-        self.compact2origin_mapper = {int(v-1):int(k) for k,v in self.category_map_str.items()}
-
-    def origin2compact(self, idx):
-        return self.origin2compact_mapper[int(idx)]
-
-    def compact2origin(self, idx):
-        return self.compact2origin_mapper[int(idx)]
-
-def to_device(item, device):
-    if isinstance(item, torch.Tensor):
-        return item.to(device)
-    elif isinstance(item, list):
-        return [to_device(i, device) for i in item]
-    elif isinstance(item, dict):
-        return {k: to_device(v, device) for k,v in item.items()}
-    else:
-        raise NotImplementedError("Call Shilong if you use other containers! type: {}".format(type(item)))
-
-
-
-# 
-def get_gaussian_mean(x, axis, other_axis, softmax=True):
-    """
-
-    Args:
-        x (float): Input images(BxCxHxW)
-        axis (int): The index for weighted mean
-        other_axis (int): The other index
-
-    Returns: weighted index for axis, BxC
-
-    """
-    mat2line = torch.sum(x, axis=other_axis)
-    # mat2line = mat2line / mat2line.mean() * 10
-    if softmax:
-        u = torch.softmax(mat2line, axis=2)
-    else:
-        u = mat2line / (mat2line.sum(2, keepdim=True) + 1e-6)
-    size = x.shape[axis]
-    ind = torch.linspace(0, 1, size).to(x.device)
-    batch = x.shape[0]
-    channel = x.shape[1]
-    index = ind.repeat([batch, channel, 1])
-    mean_position = torch.sum(index * u, dim=2)
-    return mean_position
-
-def get_expected_points_from_map(hm, softmax=True):
-    """get_gaussian_map_from_points
-        B,C,H,W -> B,N,2 float(0, 1) float(0, 1)
-        softargmax function
-
-    Args:
-        hm (float): Input images(BxCxHxW)
-
-    Returns: 
-        weighted index for axis, BxCx2. float between 0 and 1.
-
-    """
-    # hm = 10*hm
-    B,C,H,W = hm.shape
-    y_mean = get_gaussian_mean(hm, 2, 3, softmax=softmax) # B,C
-    x_mean = get_gaussian_mean(hm, 3, 2, softmax=softmax) # B,C
-    # return torch.cat((x_mean.unsqueeze(-1), y_mean.unsqueeze(-1)), 2)
-    return torch.stack([x_mean, y_mean], dim=2)
-
-# Positional encoding (section 5.1)
-# borrow from nerf
-class Embedder:
-    def __init__(self, **kwargs):
-        self.kwargs = kwargs
-        self.create_embedding_fn()
-        
-    def create_embedding_fn(self):
-        embed_fns = []
-        d = self.kwargs['input_dims']
-        out_dim = 0
-        if self.kwargs['include_input']:
-            embed_fns.append(lambda x : x)
-            out_dim += d
-            
-        max_freq = self.kwargs['max_freq_log2']
-        N_freqs = self.kwargs['num_freqs']
-        
-        if self.kwargs['log_sampling']:
-            freq_bands = 2.**torch.linspace(0., max_freq, steps=N_freqs)
-        else:
-            freq_bands = torch.linspace(2.**0., 2.**max_freq, steps=N_freqs)
-            
-        for freq in freq_bands:
-            for p_fn in self.kwargs['periodic_fns']:
-                embed_fns.append(lambda x, p_fn=p_fn, freq=freq : p_fn(x * freq))
-                out_dim += d
-                    
-        self.embed_fns = embed_fns
-        self.out_dim = out_dim
-        
-    def embed(self, inputs):
-        return torch.cat([fn(inputs) for fn in self.embed_fns], -1)
-
-
-def get_embedder(multires, i=0):
-    import torch.nn as nn
-    if i == -1:
-        return nn.Identity(), 3
-    
-    embed_kwargs = {
-                'include_input' : True,
-                'input_dims' : 3,
-                'max_freq_log2' : multires-1,
-                'num_freqs' : multires,
-                'log_sampling' : True,
-                'periodic_fns' : [torch.sin, torch.cos],
-    }
-    
-    embedder_obj = Embedder(**embed_kwargs)
-    embed = lambda x, eo=embedder_obj : eo.embed(x)
-    return embed, embedder_obj.out_dim
-
-class APOPMeter():
-    def __init__(self) -> None:
-        self.tp = 0
-        self.fp = 0
-        self.tn = 0
-        self.fn = 0
-
-    def update(self, pred, gt):
-        """
-        Input:
-            pred, gt: Tensor()
-        """
-        assert pred.shape == gt.shape
-        self.tp += torch.logical_and(pred == 1, gt == 1).sum().item()
-        self.fp += torch.logical_and(pred == 1, gt == 0).sum().item()
-        self.tn += torch.logical_and(pred == 0, gt == 0).sum().item()
-        self.tn += torch.logical_and(pred == 1, gt == 0).sum().item()
-
-    def update_cm(self, tp, fp, tn, fn):
-        self.tp += tp
-        self.fp += fp
-        self.tn += tn
-        self.tn += fn
-
-def inverse_sigmoid(x, eps=1e-5):
-    x = x.clamp(min=0, max=1)
-    x1 = x.clamp(min=eps)
-    x2 = (1 - x).clamp(min=eps)
-    return torch.log(x1/x2)
-
-import argparse
-from util.slconfig import SLConfig
-def get_raw_dict(args):
-    """
-    return the dicf contained in args.
-    
-    e.g:
-        >>> with open(path, 'w') as f:
-                json.dump(get_raw_dict(args), f, indent=2)
-    """
-    if isinstance(args, argparse.Namespace): 
-        return vars(args)   
-    elif isinstance(args, dict):
-        return args
-    elif isinstance(args, SLConfig):
-        return args._cfg_dict
-    else:
-        raise NotImplementedError("Unknown type {}".format(type(args)))
-
-
-def stat_tensors(tensor):
-    assert tensor.dim() == 1
-    tensor_sm = tensor.softmax(0)
-    entropy = (tensor_sm * torch.log(tensor_sm + 1e-9)).sum()
-
-    return {
-        'max': tensor.max(),
-        'min': tensor.min(),
-        'mean': tensor.mean(),
-        'var': tensor.var(),
-        'std': tensor.var() ** 0.5,
-        'entropy': entropy
-    }
-
-
-class NiceRepr:
-    """Inherit from this class and define ``__nice__`` to "nicely" print your
-    objects.
-
-    Defines ``__str__`` and ``__repr__`` in terms of ``__nice__`` function
-    Classes that inherit from :class:`NiceRepr` should redefine ``__nice__``.
-    If the inheriting class has a ``__len__``, method then the default
-    ``__nice__`` method will return its length.
-
-    Example:
-        >>> class Foo(NiceRepr):
-        ...    def __nice__(self):
-        ...        return 'info'
-        >>> foo = Foo()
-        >>> assert str(foo) == '<Foo(info)>'
-        >>> assert repr(foo).startswith('<Foo(info) at ')
-
-    Example:
-        >>> class Bar(NiceRepr):
-        ...    pass
-        >>> bar = Bar()
-        >>> import pytest
-        >>> with pytest.warns(None) as record:
-        >>>     assert 'object at' in str(bar)
-        >>>     assert 'object at' in repr(bar)
-
-    Example:
-        >>> class Baz(NiceRepr):
-        ...    def __len__(self):
-        ...        return 5
-        >>> baz = Baz()
-        >>> assert str(baz) == '<Baz(5)>'
-    """
-
-    def __nice__(self):
-        """str: a "nice" summary string describing this module"""
-        if hasattr(self, '__len__'):
-            # It is a common pattern for objects to use __len__ in __nice__
-            # As a convenience we define a default __nice__ for these objects
-            return str(len(self))
-        else:
-            # In all other cases force the subclass to overload __nice__
-            raise NotImplementedError(
-                f'Define the __nice__ method for {self.__class__!r}')
-
-    def __repr__(self):
-        """str: the string of the module"""
-        try:
-            nice = self.__nice__()
-            classname = self.__class__.__name__
-            return f'<{classname}({nice}) at {hex(id(self))}>'
-        except NotImplementedError as ex:
-            warnings.warn(str(ex), category=RuntimeWarning)
-            return object.__repr__(self)
-
-    def __str__(self):
-        """str: the string of the module"""
-        try:
-            classname = self.__class__.__name__
-            nice = self.__nice__()
-            return f'<{classname}({nice})>'
-        except NotImplementedError as ex:
-            warnings.warn(str(ex), category=RuntimeWarning)
-            return object.__repr__(self)
-
-
-
-def ensure_rng(rng=None):
-    """Coerces input into a random number generator.
-
-    If the input is None, then a global random state is returned.
-
-    If the input is a numeric value, then that is used as a seed to construct a
-    random state. Otherwise the input is returned as-is.
-
-    Adapted from [1]_.
-
-    Args:
-        rng (int | numpy.random.RandomState | None):
-            if None, then defaults to the global rng. Otherwise this can be an
-            integer or a RandomState class
-    Returns:
-        (numpy.random.RandomState) : rng -
-            a numpy random number generator
-
-    References:
-        .. [1] https://gitlab.kitware.com/computer-vision/kwarray/blob/master/kwarray/util_random.py#L270  # noqa: E501
-    """
-
-    if rng is None:
-        rng = np.random.mtrand._rand
-    elif isinstance(rng, int):
-        rng = np.random.RandomState(rng)
-    else:
-        rng = rng
-    return rng
-
-def random_boxes(num=1, scale=1, rng=None):
-    """Simple version of ``kwimage.Boxes.random``
-
-    Returns:
-        Tensor: shape (n, 4) in x1, y1, x2, y2 format.
-
-    References:
-        https://gitlab.kitware.com/computer-vision/kwimage/blob/master/kwimage/structs/boxes.py#L1390
-
-    Example:
-        >>> num = 3
-        >>> scale = 512
-        >>> rng = 0
-        >>> boxes = random_boxes(num, scale, rng)
-        >>> print(boxes)
-        tensor([[280.9925, 278.9802, 308.6148, 366.1769],
-                [216.9113, 330.6978, 224.0446, 456.5878],
-                [405.3632, 196.3221, 493.3953, 270.7942]])
-    """
-    rng = ensure_rng(rng)
-
-    tlbr = rng.rand(num, 4).astype(np.float32)
-
-    tl_x = np.minimum(tlbr[:, 0], tlbr[:, 2])
-    tl_y = np.minimum(tlbr[:, 1], tlbr[:, 3])
-    br_x = np.maximum(tlbr[:, 0], tlbr[:, 2])
-    br_y = np.maximum(tlbr[:, 1], tlbr[:, 3])
-
-    tlbr[:, 0] = tl_x * scale
-    tlbr[:, 1] = tl_y * scale
-    tlbr[:, 2] = br_x * scale
-    tlbr[:, 3] = br_y * scale
-
-    boxes = torch.from_numpy(tlbr)
-    return boxes
-
-
-class ModelEma(torch.nn.Module):
-    def __init__(self, model, decay=0.9997, device=None):
-        super(ModelEma, self).__init__()
-        # make a copy of the model for accumulating moving average of weights
-        self.module = deepcopy(model)
-        self.module.eval()
-
-        # import ipdb; ipdb.set_trace()
-
-        self.decay = decay
-        self.device = device  # perform ema on different device from model if set
-        if self.device is not None:
-            self.module.to(device=device)
-
-    def _update(self, model, update_fn):
-        with torch.no_grad():
-            for ema_v, model_v in zip(self.module.state_dict().values(), model.state_dict().values()):
-                if self.device is not None:
-                    model_v = model_v.to(device=self.device)
-                ema_v.copy_(update_fn(ema_v, model_v))
-
-    def update(self, model):
-        self._update(model, update_fn=lambda e, m: self.decay * e + (1. - self.decay) * m)
-
-    def set(self, model):
-        self._update(model, update_fn=lambda e, m: m)
-
-class BestMetricSingle():
-    def __init__(self, init_res=0.0, better='large') -> None:
-        self.init_res = init_res
-        self.best_res = init_res
-        self.best_ep = -1
-
-        self.better = better
-        assert better in ['large', 'small']
-
-    def isbetter(self, new_res, old_res):
-        if self.better == 'large':
-            return new_res > old_res
-        if self.better == 'small':
-            return new_res < old_res
-
-    def update(self, new_res, ep):
-        if self.isbetter(new_res, self.best_res):
-            self.best_res = new_res
-            self.best_ep = ep
-            return True
-        return False
-
-    def __str__(self) -> str:
-        return "best_res: {}\t best_ep: {}".format(self.best_res, self.best_ep)
-
-    def __repr__(self) -> str:
-        return self.__str__()
-
-    def summary(self) -> dict:
-        return {
-            'best_res': self.best_res,
-            'best_ep': self.best_ep,
-        }
-
-
-class BestMetricHolder():
-    def __init__(self, init_res=0.0, better='large', use_ema=False) -> None:
-        self.best_all = BestMetricSingle(init_res, better)
-        self.use_ema = use_ema
-        if use_ema:
-            self.best_ema = BestMetricSingle(init_res, better)
-            self.best_regular = BestMetricSingle(init_res, better)
-    
-
-    def update(self, new_res, epoch, is_ema=False):
-        """
-        return if the results is the best.
-        """
-        if not self.use_ema:
-            return self.best_all.update(new_res, epoch)
-        else:
-            if is_ema:
-                self.best_ema.update(new_res, epoch)
-                return self.best_all.update(new_res, epoch)
-            else:
-                self.best_regular.update(new_res, epoch)
-                return self.best_all.update(new_res, epoch)
-
-    def summary(self):
-        if not self.use_ema:
-            return self.best_all.summary()
-
-        res = {}
-        res.update({f'all_{k}':v for k,v in self.best_all.summary().items()})
-        res.update({f'regular_{k}':v for k,v in self.best_regular.summary().items()})
-        res.update({f'ema_{k}':v for k,v in self.best_ema.summary().items()})
-        return res
-
-    def __repr__(self) -> str:
-        return json.dumps(self.summary(), indent=2)
-
-    def __str__(self) -> str:
-        return self.__repr__()
-            
\ No newline at end of file
diff --git a/spaces/rorallitri/biomedical-language-models/logs/??oJ?sk ?6?? ?n ????v????h ?k??k???r?or?k? !!HOT!!.md b/spaces/rorallitri/biomedical-language-models/logs/??oJ?sk ?6?? ?n ????v????h ?k??k???r?or?k? !!HOT!!.md
deleted file mode 100644
index 2ea9e817146cf7df76abd62a6d5d7969e5bb9a70..0000000000000000000000000000000000000000
--- a/spaces/rorallitri/biomedical-language-models/logs/??oJ?sk ?6?? ?n ????v????h ?k??k???r?or?k? !!HOT!!.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>??oJ?sk ?6?? ?n ????v????h ?k??k???r?or?k?</h2><br /><p><b><b>Download File</b> &#9733;&#9733;&#9733;&#9733;&#9733; <a href="https://tinurll.com/2uzmNS">https://tinurll.com/2uzmNS</a></b></p><br /><br />
-<br />
- aaccfb2cb3<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/rorallitri/biomedical-language-models/logs/Bein sports 1 hd canl izle bet Stream live sports events on beIN Sports HD 1 for free.md b/spaces/rorallitri/biomedical-language-models/logs/Bein sports 1 hd canl izle bet Stream live sports events on beIN Sports HD 1 for free.md
deleted file mode 100644
index fff16127ccde88e32ee671d9525ed3ba5f7178f7..0000000000000000000000000000000000000000
--- a/spaces/rorallitri/biomedical-language-models/logs/Bein sports 1 hd canl izle bet Stream live sports events on beIN Sports HD 1 for free.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>Bein sports 1 hd canl izle bet</h2><br /><p><b><b>DOWNLOAD</b> &#9881;&#9881;&#9881; <a href="https://tinurll.com/2uzmB5">https://tinurll.com/2uzmB5</a></b></p><br /><br />
-
- aaccfb2cb3<br />
-<br />
-<br />
-<p></p>
diff --git a/spaces/rorallitri/biomedical-language-models/logs/Julie Maroh Le Bleu Est Un Couleur Chaude Pdf 24 A Graphic Novel About Love and Identity.md b/spaces/rorallitri/biomedical-language-models/logs/Julie Maroh Le Bleu Est Un Couleur Chaude Pdf 24 A Graphic Novel About Love and Identity.md
deleted file mode 100644
index 81637811f3c8806406a74a247ff82e8858b873c0..0000000000000000000000000000000000000000
--- a/spaces/rorallitri/biomedical-language-models/logs/Julie Maroh Le Bleu Est Un Couleur Chaude Pdf 24 A Graphic Novel About Love and Identity.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<br />
-<p>La version cinéma de cet album est en lice au festival de Cannes 2013. Une future Palme d'or très probable !<br /><br />Didierh<br /> -bd/2013/05/15/le-bleu-est-une-couleur-chaude-par-julie-maroh-glenat/</p>
-<p>Pour une première œuvre, voila un coup de maître !<br />"Le bleu" est d'abord une très belle histoire d'amour, avec tous les émois et toute les difficultés qu'éprouve tout adolescent.<br />Mais c'est une histoire d'amour compliquée par la recherche de son identité et la difficulté de devoir affronter le rejet d'une (grosse) partie de son entourage.<br />Ce récit poignant est très bien mis en image par ce dessin dont l'imperfection même fait le charme et j'adore l'utilisation de la couleur qui participe au récit.<br />A ne pas rater.</p>
-<h2>Julie Maroh Le Bleu Est Un Couleur Chaude Pdf 24</h2><br /><p><b><b>Download File</b> &ndash;&ndash;&ndash; <a href="https://tinurll.com/2uzm2Q">https://tinurll.com/2uzm2Q</a></b></p><br /><br /> aaccfb2cb3<br />
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\ No newline at end of file
diff --git a/spaces/rossellison/kpop-face-generator/stylegan3-fun/metrics/metric_main.py b/spaces/rossellison/kpop-face-generator/stylegan3-fun/metrics/metric_main.py
deleted file mode 100644
index 1179712c5105d9c905b772cc9f1c989812a783ce..0000000000000000000000000000000000000000
--- a/spaces/rossellison/kpop-face-generator/stylegan3-fun/metrics/metric_main.py
+++ /dev/null
@@ -1,153 +0,0 @@
-# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES.  All rights reserved.
-#
-# NVIDIA CORPORATION and its licensors retain all intellectual property
-# and proprietary rights in and to this software, related documentation
-# and any modifications thereto.  Any use, reproduction, disclosure or
-# distribution of this software and related documentation without an express
-# license agreement from NVIDIA CORPORATION is strictly prohibited.
-
-"""Main API for computing and reporting quality metrics."""
-
-import os
-import time
-import json
-import torch
-import dnnlib
-
-from . import metric_utils
-from . import frechet_inception_distance
-from . import kernel_inception_distance
-from . import precision_recall
-from . import perceptual_path_length
-from . import inception_score
-from . import equivariance
-
-#----------------------------------------------------------------------------
-
-_metric_dict = dict() # name => fn
-
-def register_metric(fn):
-    assert callable(fn)
-    _metric_dict[fn.__name__] = fn
-    return fn
-
-def is_valid_metric(metric):
-    return metric in _metric_dict
-
-def list_valid_metrics():
-    return list(_metric_dict.keys())
-
-#----------------------------------------------------------------------------
-
-def calc_metric(metric, **kwargs): # See metric_utils.MetricOptions for the full list of arguments.
-    assert is_valid_metric(metric)
-    opts = metric_utils.MetricOptions(**kwargs)
-
-    # Calculate.
-    start_time = time.time()
-    results = _metric_dict[metric](opts)
-    total_time = time.time() - start_time
-
-    # Broadcast results.
-    for key, value in list(results.items()):
-        if opts.num_gpus > 1:
-            value = torch.as_tensor(value, dtype=torch.float64, device=opts.device)
-            torch.distributed.broadcast(tensor=value, src=0)
-            value = float(value.cpu())
-        results[key] = value
-
-    # Decorate with metadata.
-    return dnnlib.EasyDict(
-        results         = dnnlib.EasyDict(results),
-        metric          = metric,
-        total_time      = total_time,
-        total_time_str  = dnnlib.util.format_time(total_time),
-        num_gpus        = opts.num_gpus,
-    )
-
-#----------------------------------------------------------------------------
-
-def report_metric(result_dict, run_dir=None, snapshot_pkl=None):
-    metric = result_dict['metric']
-    assert is_valid_metric(metric)
-    if run_dir is not None and snapshot_pkl is not None:
-        snapshot_pkl = os.path.relpath(snapshot_pkl, run_dir)
-
-    jsonl_line = json.dumps(dict(result_dict, snapshot_pkl=snapshot_pkl, timestamp=time.time()))
-    print(jsonl_line)
-    if run_dir is not None and os.path.isdir(run_dir):
-        with open(os.path.join(run_dir, f'metric-{metric}.jsonl'), 'at') as f:
-            f.write(jsonl_line + '\n')
-
-#----------------------------------------------------------------------------
-# Recommended metrics.
-
-@register_metric
-def fid50k_full(opts):
-    opts.dataset_kwargs.update(max_size=None, xflip=False)
-    fid = frechet_inception_distance.compute_fid(opts, max_real=None, num_gen=50000)
-    return dict(fid50k_full=fid)
-
-@register_metric
-def kid50k_full(opts):
-    opts.dataset_kwargs.update(max_size=None, xflip=False)
-    kid = kernel_inception_distance.compute_kid(opts, max_real=1000000, num_gen=50000, num_subsets=100, max_subset_size=1000)
-    return dict(kid50k_full=kid)
-
-@register_metric
-def pr50k3_full(opts):
-    opts.dataset_kwargs.update(max_size=None, xflip=False)
-    precision, recall = precision_recall.compute_pr(opts, max_real=200000, num_gen=50000, nhood_size=3, row_batch_size=10000, col_batch_size=10000)
-    return dict(pr50k3_full_precision=precision, pr50k3_full_recall=recall)
-
-@register_metric
-def ppl2_wend(opts):
-    ppl = perceptual_path_length.compute_ppl(opts, num_samples=50000, epsilon=1e-4, space='w', sampling='end', crop=False, batch_size=2)
-    return dict(ppl2_wend=ppl)
-
-@register_metric
-def eqt50k_int(opts):
-    opts.G_kwargs.update(force_fp32=True)
-    psnr = equivariance.compute_equivariance_metrics(opts, num_samples=50000, batch_size=4, compute_eqt_int=True)
-    return dict(eqt50k_int=psnr)
-
-@register_metric
-def eqt50k_frac(opts):
-    opts.G_kwargs.update(force_fp32=True)
-    psnr = equivariance.compute_equivariance_metrics(opts, num_samples=50000, batch_size=4, compute_eqt_frac=True)
-    return dict(eqt50k_frac=psnr)
-
-@register_metric
-def eqr50k(opts):
-    opts.G_kwargs.update(force_fp32=True)
-    psnr = equivariance.compute_equivariance_metrics(opts, num_samples=50000, batch_size=4, compute_eqr=True)
-    return dict(eqr50k=psnr)
-
-#----------------------------------------------------------------------------
-# Legacy metrics.
-
-@register_metric
-def fid50k(opts):
-    opts.dataset_kwargs.update(max_size=None)
-    fid = frechet_inception_distance.compute_fid(opts, max_real=50000, num_gen=50000)
-    return dict(fid50k=fid)
-
-@register_metric
-def kid50k(opts):
-    opts.dataset_kwargs.update(max_size=None)
-    kid = kernel_inception_distance.compute_kid(opts, max_real=50000, num_gen=50000, num_subsets=100, max_subset_size=1000)
-    return dict(kid50k=kid)
-
-@register_metric
-def pr50k3(opts):
-    opts.dataset_kwargs.update(max_size=None)
-    precision, recall = precision_recall.compute_pr(opts, max_real=50000, num_gen=50000, nhood_size=3, row_batch_size=10000, col_batch_size=10000)
-    return dict(pr50k3_precision=precision, pr50k3_recall=recall)
-
-@register_metric
-def is50k(opts):
-    opts.dataset_kwargs.update(max_size=None, xflip=False)
-    mean, std = inception_score.compute_is(opts, num_gen=50000, num_splits=10)
-    return dict(is50k_mean=mean, is50k_std=std)
-
-#----------------------------------------------------------------------------
diff --git a/spaces/rushic24/Priyanka-Chopra-TTS/training/tacotron2_model/stft.py b/spaces/rushic24/Priyanka-Chopra-TTS/training/tacotron2_model/stft.py
deleted file mode 100644
index 8f1e34de95f6e44975742dfffb8bee4c4c3622bc..0000000000000000000000000000000000000000
--- a/spaces/rushic24/Priyanka-Chopra-TTS/training/tacotron2_model/stft.py
+++ /dev/null
@@ -1,187 +0,0 @@
-"""
-BSD 3-Clause License
-
-Copyright (c) 2017, Prem Seetharaman
-All rights reserved.
-
-* Redistribution and use in source and binary forms, with or without
-  modification, are permitted provided that the following conditions are met:
-
-* Redistributions of source code must retain the above copyright notice,
-  this list of conditions and the following disclaimer.
-
-* Redistributions in binary form must reproduce the above copyright notice, this
-  list of conditions and the following disclaimer in the
-  documentation and/or other materials provided with the distribution.
-
-* Neither the name of the copyright holder nor the names of its
-  contributors may be used to endorse or promote products derived from this
-  software without specific prior written permission.
-
-THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
-ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
-WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
-DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR
-ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
-(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
-LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
-ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
-(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
-SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-"""
-import torch
-import numpy as np
-import torch.nn.functional as F
-from torch.autograd import Variable
-from scipy.signal import get_window
-from librosa.util import pad_center, tiny
-from librosa.filters import mel as librosa_mel_fn
-from training.tacotron2_model.audio_processing import (
-    window_sumsquare,
-    dynamic_range_compression,
-    dynamic_range_decompression,
-)
-
-
-class STFT(torch.nn.Module):
-    """adapted from Prem Seetharaman's https://github.com/pseeth/pytorch-stft"""
-
-    def __init__(self, filter_length=800, hop_length=200, win_length=800, window="hann"):
-        super(STFT, self).__init__()
-        self.filter_length = filter_length
-        self.hop_length = hop_length
-        self.win_length = win_length
-        self.window = window
-        self.forward_transform = None
-        scale = self.filter_length / self.hop_length
-        fourier_basis = np.fft.fft(np.eye(self.filter_length))
-
-        cutoff = int((self.filter_length / 2 + 1))
-        fourier_basis = np.vstack([np.real(fourier_basis[:cutoff, :]), np.imag(fourier_basis[:cutoff, :])])
-
-        forward_basis = torch.FloatTensor(fourier_basis[:, None, :])
-        inverse_basis = torch.FloatTensor(np.linalg.pinv(scale * fourier_basis).T[:, None, :])
-
-        if window is not None:
-            assert filter_length >= win_length
-            # get window and zero center pad it to filter_length
-            fft_window = get_window(window, win_length, fftbins=True)
-            fft_window = pad_center(fft_window, filter_length)
-            fft_window = torch.from_numpy(fft_window).float()
-
-            # window the bases
-            forward_basis *= fft_window
-            inverse_basis *= fft_window
-
-        self.register_buffer("forward_basis", forward_basis.float())
-        self.register_buffer("inverse_basis", inverse_basis.float())
-
-    def transform(self, input_data):
-        num_batches = input_data.size(0)
-        num_samples = input_data.size(1)
-
-        self.num_samples = num_samples
-
-        # similar to librosa, reflect-pad the input
-        input_data = input_data.view(num_batches, 1, num_samples)
-        input_data = F.pad(
-            input_data.unsqueeze(1), (int(self.filter_length / 2), int(self.filter_length / 2), 0, 0), mode="reflect"
-        )
-        input_data = input_data.squeeze(1)
-
-        forward_transform = F.conv1d(
-            input_data, Variable(self.forward_basis, requires_grad=False), stride=self.hop_length, padding=0
-        )
-
-        cutoff = int((self.filter_length / 2) + 1)
-        real_part = forward_transform[:, :cutoff, :]
-        imag_part = forward_transform[:, cutoff:, :]
-
-        magnitude = torch.sqrt(real_part**2 + imag_part**2)
-        phase = torch.autograd.Variable(torch.atan2(imag_part.data, real_part.data))
-
-        return magnitude, phase
-
-    def inverse(self, magnitude, phase):
-        recombine_magnitude_phase = torch.cat([magnitude * torch.cos(phase), magnitude * torch.sin(phase)], dim=1)
-
-        inverse_transform = F.conv_transpose1d(
-            recombine_magnitude_phase,
-            Variable(self.inverse_basis, requires_grad=False),
-            stride=self.hop_length,
-            padding=0,
-        )
-
-        if self.window is not None:
-            window_sum = window_sumsquare(
-                self.window,
-                magnitude.size(-1),
-                hop_length=self.hop_length,
-                win_length=self.win_length,
-                n_fft=self.filter_length,
-                dtype=np.float32,
-            )
-            # remove modulation effects
-            approx_nonzero_indices = torch.from_numpy(np.where(window_sum > tiny(window_sum))[0])
-            window_sum = torch.autograd.Variable(torch.from_numpy(window_sum), requires_grad=False)
-            window_sum = window_sum.cuda() if magnitude.is_cuda else window_sum
-            inverse_transform[:, :, approx_nonzero_indices] /= window_sum[approx_nonzero_indices]
-
-            # scale by hop ratio
-            inverse_transform *= float(self.filter_length) / self.hop_length
-
-        inverse_transform = inverse_transform[:, :, int(self.filter_length / 2) :]
-        inverse_transform = inverse_transform[:, :, : -int(self.filter_length / 2) :]
-
-        return inverse_transform
-
-    def forward(self, input_data):
-        self.magnitude, self.phase = self.transform(input_data)
-        reconstruction = self.inverse(self.magnitude, self.phase)
-        return reconstruction
-
-
-class TacotronSTFT(torch.nn.Module):
-    def __init__(
-        self,
-        filter_length=1024,
-        hop_length=256,
-        win_length=1024,
-        n_mel_channels=80,
-        sampling_rate=22050,
-        mel_fmin=0.0,
-        mel_fmax=8000.0,
-    ):
-        super(TacotronSTFT, self).__init__()
-        self.n_mel_channels = n_mel_channels
-        self.sampling_rate = sampling_rate
-        self.stft_fn = STFT(filter_length, hop_length, win_length)
-        mel_basis = librosa_mel_fn(sampling_rate, filter_length, n_mel_channels, mel_fmin, mel_fmax)
-        mel_basis = torch.from_numpy(mel_basis).float()
-        self.register_buffer("mel_basis", mel_basis)
-
-    def spectral_normalize(self, magnitudes):
-        output = dynamic_range_compression(magnitudes)
-        return output
-
-    def spectral_de_normalize(self, magnitudes):
-        output = dynamic_range_decompression(magnitudes)
-        return output
-
-    def mel_spectrogram(self, y):
-        """Computes mel-spectrograms from a batch of waves
-        PARAMS
-        ------
-        y: Variable(torch.FloatTensor) with shape (B, T) in range [-1, 1]
-        RETURNS
-        -------
-        mel_output: torch.FloatTensor of shape (B, n_mel_channels, T)
-        """
-        assert torch.min(y.data) >= -1
-        assert torch.max(y.data) <= 1
-
-        magnitudes, phases = self.stft_fn.transform(y)
-        magnitudes = magnitudes.data
-        mel_output = torch.matmul(self.mel_basis, magnitudes)
-        mel_output = self.spectral_normalize(mel_output)
-        return mel_output
diff --git a/spaces/ruslanmv/Clone-Your-Voice/encoder/data_objects/speaker_verification_dataset.py b/spaces/ruslanmv/Clone-Your-Voice/encoder/data_objects/speaker_verification_dataset.py
deleted file mode 100644
index 77a6e05eae6a939ae7575ae70b7173644141fffe..0000000000000000000000000000000000000000
--- a/spaces/ruslanmv/Clone-Your-Voice/encoder/data_objects/speaker_verification_dataset.py
+++ /dev/null
@@ -1,56 +0,0 @@
-from encoder.data_objects.random_cycler import RandomCycler
-from encoder.data_objects.speaker_batch import SpeakerBatch
-from encoder.data_objects.speaker import Speaker
-from encoder.params_data import partials_n_frames
-from torch.utils.data import Dataset, DataLoader
-from pathlib import Path
-
-# TODO: improve with a pool of speakers for data efficiency
-
-class SpeakerVerificationDataset(Dataset):
-    def __init__(self, datasets_root: Path):
-        self.root = datasets_root
-        speaker_dirs = [f for f in self.root.glob("*") if f.is_dir()]
-        if len(speaker_dirs) == 0:
-            raise Exception("No speakers found. Make sure you are pointing to the directory "
-                            "containing all preprocessed speaker directories.")
-        self.speakers = [Speaker(speaker_dir) for speaker_dir in speaker_dirs]
-        self.speaker_cycler = RandomCycler(self.speakers)
-
-    def __len__(self):
-        return int(1e10)
-        
-    def __getitem__(self, index):
-        return next(self.speaker_cycler)
-    
-    def get_logs(self):
-        log_string = ""
-        for log_fpath in self.root.glob("*.txt"):
-            with log_fpath.open("r") as log_file:
-                log_string += "".join(log_file.readlines())
-        return log_string
-    
-    
-class SpeakerVerificationDataLoader(DataLoader):
-    def __init__(self, dataset, speakers_per_batch, utterances_per_speaker, sampler=None, 
-                 batch_sampler=None, num_workers=0, pin_memory=False, timeout=0, 
-                 worker_init_fn=None):
-        self.utterances_per_speaker = utterances_per_speaker
-
-        super().__init__(
-            dataset=dataset, 
-            batch_size=speakers_per_batch, 
-            shuffle=False, 
-            sampler=sampler, 
-            batch_sampler=batch_sampler, 
-            num_workers=num_workers,
-            collate_fn=self.collate, 
-            pin_memory=pin_memory, 
-            drop_last=False, 
-            timeout=timeout, 
-            worker_init_fn=worker_init_fn
-        )
-
-    def collate(self, speakers):
-        return SpeakerBatch(speakers, self.utterances_per_speaker, partials_n_frames) 
-    
\ No newline at end of file
diff --git a/spaces/ryo2/convertcsv2h5/app.py b/spaces/ryo2/convertcsv2h5/app.py
deleted file mode 100644
index 9e6438e9c951643ed898a0f2071f87559338c6f3..0000000000000000000000000000000000000000
--- a/spaces/ryo2/convertcsv2h5/app.py
+++ /dev/null
@@ -1,50 +0,0 @@
-import gradio as gr
-import pandas as pd
-import os
-from itertools import islice
-import tempfile
-
-
-def guarantee_multiindex_rows(df):
-   if not isinstance(df.index, pd.MultiIndex):
-      path = df.index[0]
-      try:
-         sep = "/" if "/" in path else "\\"
-         splits = tuple(df.index.str.split(sep))
-         df.index = pd.MultiIndex.from_tuples(splits)
-      except TypeError:
-         pass
-
-   try:
-      df.index = df.index.set_levels(df.index.levels[1].astype(str), level=1)
-   except AttributeError:
-      pass
-
-
-def convertcsv2h5(csv_name):
-   csv_name = csv_name.name
-   csv_path = os.path.splitext(csv_name)[0]
-   scorer = csv_path.split('_')[1]
-   with open(csv_name) as datafile:
-      head = list(islice(datafile, 0, 5))
-      if "individuals" in head[1]:
-         header = list(range(4))
-      else:
-         header = list(range(3))
-      if head[-1].split(",")[0] == "labeled-data":
-         index_col = [0, 1, 2]
-      else:
-         index_col = 0
-      data = pd.read_csv(csv_name, index_col=index_col, header=header)
-      data.columns = data.columns.set_levels([scorer], level="scorer")
-      guarantee_multiindex_rows(data)
-
-      with tempfile.NamedTemporaryFile(suffix=".h5", delete=False) as temp_file:
-         temp_file_path = csv_name.replace(".csv", ".h5")
-         data.to_hdf(temp_file_path, key="df_with_missing", mode="w")
-
-   return temp_file_path
-
-
-iface = gr.Interface(fn=convertcsv2h5, inputs="file", outputs="file")
-iface.launch()
diff --git a/spaces/sayakpaul/raindrop-deraining-maxim/maxim/blocks/bottleneck.py b/spaces/sayakpaul/raindrop-deraining-maxim/maxim/blocks/bottleneck.py
deleted file mode 100644
index be7a31d4b4c7bf8d8eb6caeb8e167b5beb27db23..0000000000000000000000000000000000000000
--- a/spaces/sayakpaul/raindrop-deraining-maxim/maxim/blocks/bottleneck.py
+++ /dev/null
@@ -1,54 +0,0 @@
-import functools
-
-from tensorflow.keras import layers
-
-from .attentions import RDCAB
-from .misc_gating import ResidualSplitHeadMultiAxisGmlpLayer
-
-Conv1x1 = functools.partial(layers.Conv2D, kernel_size=(1, 1), padding="same")
-
-
-def BottleneckBlock(
-    features: int,
-    block_size,
-    grid_size,
-    num_groups: int = 1,
-    block_gmlp_factor: int = 2,
-    grid_gmlp_factor: int = 2,
-    input_proj_factor: int = 2,
-    channels_reduction: int = 4,
-    dropout_rate: float = 0.0,
-    use_bias: bool = True,
-    name: str = "bottleneck_block",
-):
-    """The bottleneck block consisting of multi-axis gMLP block and RDCAB."""
-
-    def apply(x):
-        # input projection
-        x = Conv1x1(filters=features, use_bias=use_bias, name=f"{name}_input_proj")(x)
-        shortcut_long = x
-
-        for i in range(num_groups):
-            x = ResidualSplitHeadMultiAxisGmlpLayer(
-                grid_size=grid_size,
-                block_size=block_size,
-                grid_gmlp_factor=grid_gmlp_factor,
-                block_gmlp_factor=block_gmlp_factor,
-                input_proj_factor=input_proj_factor,
-                use_bias=use_bias,
-                dropout_rate=dropout_rate,
-                name=f"{name}_SplitHeadMultiAxisGmlpLayer_{i}",
-            )(x)
-            # Channel-mixing part, which provides within-patch communication.
-            x = RDCAB(
-                num_channels=features,
-                reduction=channels_reduction,
-                use_bias=use_bias,
-                name=f"{name}_channel_attention_block_1_{i}",
-            )(x)
-
-        # long skip-connect
-        x = x + shortcut_long
-        return x
-
-    return apply
diff --git a/spaces/sdeeas/ChuanhuChatGPT/run_Windows.bat b/spaces/sdeeas/ChuanhuChatGPT/run_Windows.bat
deleted file mode 100644
index 4c18f9ccaeea0af972301ffdf48778641221f76d..0000000000000000000000000000000000000000
--- a/spaces/sdeeas/ChuanhuChatGPT/run_Windows.bat
+++ /dev/null
@@ -1,5 +0,0 @@
-@echo off
-echo Opening ChuanhuChatGPT...
-
-REM Open powershell via bat
-start powershell.exe -NoExit -Command "python ./ChuanhuChatbot.py"
diff --git a/spaces/segments-tobias/conex/espnet2/main_funcs/pack_funcs.py b/spaces/segments-tobias/conex/espnet2/main_funcs/pack_funcs.py
deleted file mode 100644
index dade3e06764c3ae6d5da102ef080adb06ad844f5..0000000000000000000000000000000000000000
--- a/spaces/segments-tobias/conex/espnet2/main_funcs/pack_funcs.py
+++ /dev/null
@@ -1,302 +0,0 @@
-from datetime import datetime
-from io import BytesIO
-from io import TextIOWrapper
-import os
-from pathlib import Path
-import sys
-import tarfile
-from typing import Dict
-from typing import Iterable
-from typing import Optional
-from typing import Union
-import zipfile
-
-import yaml
-
-
-class Archiver:
-    def __init__(self, file, mode="r"):
-        if Path(file).suffix == ".tar":
-            self.type = "tar"
-        elif Path(file).suffix == ".tgz" or Path(file).suffixes == [".tar", ".gz"]:
-            self.type = "tar"
-            if mode == "w":
-                mode = "w:gz"
-        elif Path(file).suffix == ".tbz2" or Path(file).suffixes == [".tar", ".bz2"]:
-            self.type = "tar"
-            if mode == "w":
-                mode = "w:bz2"
-        elif Path(file).suffix == ".txz" or Path(file).suffixes == [".tar", ".xz"]:
-            self.type = "tar"
-            if mode == "w":
-                mode = "w:xz"
-        elif Path(file).suffix == ".zip":
-            self.type = "zip"
-        else:
-            raise ValueError(f"Cannot detect archive format: type={file}")
-
-        if self.type == "tar":
-            self.fopen = tarfile.open(file, mode=mode)
-        elif self.type == "zip":
-
-            self.fopen = zipfile.ZipFile(file, mode=mode)
-        else:
-            raise ValueError(f"Not supported: type={type}")
-
-    def __enter__(self):
-        return self
-
-    def __exit__(self, exc_type, exc_val, exc_tb):
-        self.fopen.close()
-
-    def close(self):
-        self.fopen.close()
-
-    def __iter__(self):
-        if self.type == "tar":
-            return iter(self.fopen)
-        elif self.type == "zip":
-            return iter(self.fopen.infolist())
-        else:
-            raise ValueError(f"Not supported: type={self.type}")
-
-    def add(self, filename, arcname=None, recursive: bool = True):
-        if arcname is not None:
-            print(f"adding: {arcname}")
-        else:
-            print(f"adding: {filename}")
-
-        if recursive and Path(filename).is_dir():
-            for f in Path(filename).glob("**/*"):
-                if f.is_dir():
-                    continue
-
-                if arcname is not None:
-                    _arcname = Path(arcname) / f
-                else:
-                    _arcname = None
-
-                self.add(f, _arcname)
-            return
-
-        if self.type == "tar":
-            return self.fopen.add(filename, arcname)
-        elif self.type == "zip":
-            return self.fopen.write(filename, arcname)
-        else:
-            raise ValueError(f"Not supported: type={self.type}")
-
-    def addfile(self, info, fileobj):
-        print(f"adding: {self.get_name_from_info(info)}")
-
-        if self.type == "tar":
-            return self.fopen.addfile(info, fileobj)
-        elif self.type == "zip":
-            return self.fopen.writestr(info, fileobj.read())
-        else:
-            raise ValueError(f"Not supported: type={self.type}")
-
-    def generate_info(self, name, size) -> Union[tarfile.TarInfo, zipfile.ZipInfo]:
-        """Generate TarInfo using system information"""
-        if self.type == "tar":
-            tarinfo = tarfile.TarInfo(str(name))
-            if os.name == "posix":
-                tarinfo.gid = os.getgid()
-                tarinfo.uid = os.getuid()
-            tarinfo.mtime = datetime.now().timestamp()
-            tarinfo.size = size
-            # Keep mode as default
-            return tarinfo
-        elif self.type == "zip":
-            zipinfo = zipfile.ZipInfo(str(name), datetime.now().timetuple()[:6])
-            zipinfo.file_size = size
-            return zipinfo
-        else:
-            raise ValueError(f"Not supported: type={self.type}")
-
-    def get_name_from_info(self, info):
-        if self.type == "tar":
-            assert isinstance(info, tarfile.TarInfo), type(info)
-            return info.name
-        elif self.type == "zip":
-            assert isinstance(info, zipfile.ZipInfo), type(info)
-            return info.filename
-        else:
-            raise ValueError(f"Not supported: type={self.type}")
-
-    def extract(self, info, path=None):
-        if self.type == "tar":
-            return self.fopen.extract(info, path)
-        elif self.type == "zip":
-            return self.fopen.extract(info, path)
-        else:
-            raise ValueError(f"Not supported: type={self.type}")
-
-    def extractfile(self, info, mode="r"):
-        if self.type == "tar":
-            f = self.fopen.extractfile(info)
-            if mode == "r":
-                return TextIOWrapper(f)
-            else:
-                return f
-        elif self.type == "zip":
-            if mode == "rb":
-                mode = "r"
-            return self.fopen.open(info, mode)
-        else:
-            raise ValueError(f"Not supported: type={self.type}")
-
-
-def find_path_and_change_it_recursive(value, src: str, tgt: str):
-    if isinstance(value, dict):
-        return {
-            k: find_path_and_change_it_recursive(v, src, tgt) for k, v in value.items()
-        }
-    elif isinstance(value, (list, tuple)):
-        return [find_path_and_change_it_recursive(v, src, tgt) for v in value]
-    elif isinstance(value, str) and Path(value) == Path(src):
-        return tgt
-    else:
-        return value
-
-
-def get_dict_from_cache(meta: Union[Path, str]) -> Optional[Dict[str, str]]:
-    meta = Path(meta)
-    outpath = meta.parent.parent
-    if not meta.exists():
-        return None
-
-    with meta.open("r", encoding="utf-8") as f:
-        d = yaml.safe_load(f)
-        assert isinstance(d, dict), type(d)
-        yaml_files = d["yaml_files"]
-        files = d["files"]
-        assert isinstance(yaml_files, dict), type(yaml_files)
-        assert isinstance(files, dict), type(files)
-
-        retval = {}
-        for key, value in list(yaml_files.items()) + list(files.items()):
-            if not (outpath / value).exists():
-                return None
-            retval[key] = str(outpath / value)
-        return retval
-
-
-def unpack(
-    input_archive: Union[Path, str],
-    outpath: Union[Path, str],
-    use_cache: bool = True,
-) -> Dict[str, str]:
-    """Scan all files in the archive file and return as a dict of files.
-
-    Examples:
-        tarfile:
-           model.pth
-           some1.file
-           some2.file
-
-        >>> unpack("tarfile", "out")
-        {'asr_model_file': 'out/model.pth'}
-    """
-    input_archive = Path(input_archive)
-    outpath = Path(outpath)
-
-    with Archiver(input_archive) as archive:
-        for info in archive:
-            if Path(archive.get_name_from_info(info)).name == "meta.yaml":
-                if (
-                    use_cache
-                    and (outpath / Path(archive.get_name_from_info(info))).exists()
-                ):
-                    retval = get_dict_from_cache(
-                        outpath / Path(archive.get_name_from_info(info))
-                    )
-                    if retval is not None:
-                        return retval
-                d = yaml.safe_load(archive.extractfile(info))
-                assert isinstance(d, dict), type(d)
-                yaml_files = d["yaml_files"]
-                files = d["files"]
-                assert isinstance(yaml_files, dict), type(yaml_files)
-                assert isinstance(files, dict), type(files)
-                break
-        else:
-            raise RuntimeError("Format error: not found meta.yaml")
-
-        for info in archive:
-            fname = archive.get_name_from_info(info)
-            outname = outpath / fname
-            outname.parent.mkdir(parents=True, exist_ok=True)
-            if fname in set(yaml_files.values()):
-                d = yaml.safe_load(archive.extractfile(info))
-                # Rewrite yaml
-                for info2 in archive:
-                    name = archive.get_name_from_info(info2)
-                    d = find_path_and_change_it_recursive(d, name, str(outpath / name))
-                with outname.open("w", encoding="utf-8") as f:
-                    yaml.safe_dump(d, f)
-            else:
-                archive.extract(info, path=outpath)
-
-        retval = {}
-        for key, value in list(yaml_files.items()) + list(files.items()):
-            retval[key] = str(outpath / value)
-        return retval
-
-
-def _to_relative_or_resolve(f):
-    # Resolve to avoid symbolic link
-    p = Path(f).resolve()
-    try:
-        # Change to relative if it can
-        p = p.relative_to(Path(".").resolve())
-    except ValueError:
-        pass
-    return str(p)
-
-
-def pack(
-    files: Dict[str, Union[str, Path]],
-    yaml_files: Dict[str, Union[str, Path]],
-    outpath: Union[str, Path],
-    option: Iterable[Union[str, Path]] = (),
-):
-    for v in list(files.values()) + list(yaml_files.values()) + list(option):
-        if not Path(v).exists():
-            raise FileNotFoundError(f"No such file or directory: {v}")
-
-    files = {k: _to_relative_or_resolve(v) for k, v in files.items()}
-    yaml_files = {k: _to_relative_or_resolve(v) for k, v in yaml_files.items()}
-    option = [_to_relative_or_resolve(v) for v in option]
-
-    meta_objs = dict(
-        files=files,
-        yaml_files=yaml_files,
-        timestamp=datetime.now().timestamp(),
-        python=sys.version,
-    )
-
-    try:
-        import torch
-
-        meta_objs.update(torch=torch.__version__)
-    except ImportError:
-        pass
-    try:
-        import espnet
-
-        meta_objs.update(espnet=espnet.__version__)
-    except ImportError:
-        pass
-
-    Path(outpath).parent.mkdir(parents=True, exist_ok=True)
-    with Archiver(outpath, mode="w") as archive:
-        # Write packed/meta.yaml
-        fileobj = BytesIO(yaml.safe_dump(meta_objs).encode())
-        info = archive.generate_info("meta.yaml", fileobj.getbuffer().nbytes)
-        archive.addfile(info, fileobj=fileobj)
-
-        for f in list(yaml_files.values()) + list(files.values()) + list(option):
-            archive.add(f)
-
-    print(f"Generate: {outpath}")
diff --git a/spaces/shencc/gpt/core_functional.py b/spaces/shencc/gpt/core_functional.py
deleted file mode 100644
index 536ccb609c38cbbebfda4ba17bd51a78857d711e..0000000000000000000000000000000000000000
--- a/spaces/shencc/gpt/core_functional.py
+++ /dev/null
@@ -1,71 +0,0 @@
-# 'primary' 颜色对应 theme.py 中的 primary_hue
-# 'secondary' 颜色对应 theme.py 中的 neutral_hue
-# 'stop' 颜色对应 theme.py 中的 color_er
-# 默认按钮颜色是 secondary
-from toolbox import clear_line_break
-
-
-def get_core_functions():
-    return {
-        "英语学术润色": {
-            # 前言
-            "Prefix":   r"Below is a paragraph from an academic paper. Polish the writing to meet the academic style, " +
-                        r"improve the spelling, grammar, clarity, concision and overall readability. When necessary, rewrite the whole sentence. " +
-                        r"Furthermore, list all modification and explain the reasons to do so in markdown table." + "\n\n",
-            # 后语
-            "Suffix":   r"",
-            "Color":    r"secondary",    # 按钮颜色
-        },
-        "中文学术润色": {
-            "Prefix":   r"作为一名中文学术论文写作改进助理，你的任务是改进所提供文本的拼写、语法、清晰、简洁和整体可读性，" +
-                        r"同时分解长句，减少重复，并提供改进建议。请只提供文本的更正版本，避免包括解释。请编辑以下文本" + "\n\n",
-            "Suffix":   r"",
-        },
-        "查找语法错误": {
-            "Prefix":   r"Can you help me ensure that the grammar and the spelling is correct? " +
-                        r"Do not try to polish the text, if no mistake is found, tell me that this paragraph is good." +
-                        r"If you find grammar or spelling mistakes, please list mistakes you find in a two-column markdown table, " +
-                        r"put the original text the first column, " +
-                        r"put the corrected text in the second column and highlight the key words you fixed.""\n"
-                        r"Example:""\n"
-                        r"Paragraph: How is you? Do you knows what is it?""\n"
-                        r"| Original sentence | Corrected sentence |""\n"
-                        r"| :--- | :--- |""\n"
-                        r"| How **is** you? | How **are** you? |""\n"
-                        r"| Do you **knows** what **is** **it**? | Do you **know** what **it** **is** ? |""\n"
-                        r"Below is a paragraph from an academic paper. "
-                        r"You need to report all grammar and spelling mistakes as the example before."
-                        + "\n\n",
-            "Suffix":   r"",
-            "PreProcess": clear_line_break,    # 预处理：清除换行符
-        },
-        "中译英": {
-            "Prefix":   r"Please translate following sentence to English:" + "\n\n",
-            "Suffix":   r"",
-        },
-        "学术中英互译": {
-            "Prefix":   r"I want you to act as a scientific English-Chinese translator, " +
-                        r"I will provide you with some paragraphs in one language " +
-                        r"and your task is to accurately and academically translate the paragraphs only into the other language. " +
-                        r"Do not repeat the original provided paragraphs after translation. " +
-                        r"You should use artificial intelligence tools, " +
-                        r"such as natural language processing, and rhetorical knowledge " +
-                        r"and experience about effective writing techniques to reply. " +
-                        r"I'll give you my paragraphs as follows, tell me what language it is written in, and then translate:" + "\n\n",
-            "Suffix": "",
-            "Color": "secondary",
-        },
-        "英译中": {
-            "Prefix":   r"翻译成地道的中文：" + "\n\n",
-            "Suffix":   r"",
-        },
-        "找图片": {
-            "Prefix":   r"我需要你找一张网络图片。使用Unsplash API(https://source.unsplash.com/960x640/?<英语关键词>)获取图片URL，" +
-                        r"然后请使用Markdown格式封装，并且不要有反斜线，不要用代码块。现在，请按以下描述给我发送图片：" + "\n\n",
-            "Suffix":   r"",
-        },
-        "解释代码": {
-            "Prefix":   r"请解释以下代码：" + "\n```\n",
-            "Suffix":   "\n```\n",
-        },
-    }
diff --git a/spaces/shi-labs/Prompt-Free-Diffusion/lib/model_zoo/pfd.py b/spaces/shi-labs/Prompt-Free-Diffusion/lib/model_zoo/pfd.py
deleted file mode 100644
index 19cf31c329016d37edf69d9fa3d6d09bdf9aa1b2..0000000000000000000000000000000000000000
--- a/spaces/shi-labs/Prompt-Free-Diffusion/lib/model_zoo/pfd.py
+++ /dev/null
@@ -1,528 +0,0 @@
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-import numpy as np
-import numpy.random as npr
-import copy
-from functools import partial
-from contextlib import contextmanager
-from lib.model_zoo.common.get_model import get_model, register
-from lib.log_service import print_log
-
-symbol = 'pfd'
-
-from .diffusion_utils import \
-    count_params, extract_into_tensor, make_beta_schedule
-from .distributions import normal_kl, DiagonalGaussianDistribution
-
-from .autokl import AutoencoderKL
-from .ema import LitEma
-
-def highlight_print(info):
-    print_log('')
-    print_log(''.join(['#']*(len(info)+4)))
-    print_log('# '+info+' #')
-    print_log(''.join(['#']*(len(info)+4)))
-    print_log('')
-
-@register('pfd')
-class PromptFreeDiffusion(nn.Module):
-    def __init__(self,
-                 vae_cfg_list,
-                 ctx_cfg_list,
-                 diffuser_cfg_list,
-                 global_layer_ptr=None,
-
-                 parameterization="eps",
-                 timesteps=1000,
-                 use_ema=False,
-
-                 beta_schedule="linear",
-                 beta_linear_start=1e-4,
-                 beta_linear_end=2e-2,
-                 given_betas=None,
-                 cosine_s=8e-3,
-
-                 loss_type="l2",
-                 l_simple_weight=1.,
-                 l_elbo_weight=0.,
-                 
-                 v_posterior=0.,
-                 learn_logvar=False, 
-                 logvar_init=0, 
-
-                 latent_scale_factor=None,):
-
-        super().__init__()
-        assert parameterization in ["eps", "x0"], \
-            'currently only supporting "eps" and "x0"'
-        self.parameterization = parameterization
-        highlight_print("Running in {} mode".format(self.parameterization))
-
-        self.vae = self.get_model_list(vae_cfg_list)
-        self.ctx = self.get_model_list(ctx_cfg_list)
-        self.diffuser = self.get_model_list(diffuser_cfg_list)
-        self.global_layer_ptr = global_layer_ptr
-
-        assert self.check_diffuser(), 'diffuser layers are not aligned!'
-
-        self.use_ema = use_ema
-        if self.use_ema:
-            self.model_ema = LitEma(self.model)
-            print_log(f"Keeping EMAs of {len(list(self.model_ema.buffers()))}.")
-
-        self.loss_type = loss_type
-        self.l_simple_weight = l_simple_weight
-        self.l_elbo_weight = l_elbo_weight
-        self.v_posterior = v_posterior
-
-        self.register_schedule(
-            given_betas=given_betas,
-            beta_schedule=beta_schedule,
-            timesteps=timesteps,
-            linear_start=beta_linear_start,
-            linear_end=beta_linear_end,
-            cosine_s=cosine_s)
-
-        self.learn_logvar = learn_logvar
-        self.logvar = torch.full(fill_value=logvar_init, size=(self.num_timesteps,))
-        if self.learn_logvar:
-            self.logvar = nn.Parameter(self.logvar, requires_grad=True)
-
-        self.latent_scale_factor = {} if latent_scale_factor is None else latent_scale_factor
-
-        self.parameter_group = {}
-        for namei, diffuseri in self.diffuser.items():
-            self.parameter_group.update({
-                'diffuser_{}_{}'.format(namei, pgni):pgi for pgni, pgi in diffuseri.parameter_group.items()
-            })
-
-    def to(self, device):
-        self.device = device
-        super().to(device)
-
-    def get_model_list(self, cfg_list):
-        net = nn.ModuleDict()
-        for name, cfg in cfg_list:
-            net[name] = get_model()(cfg)
-        return net
-
-    def register_schedule(self, 
-                          given_betas=None, 
-                          beta_schedule="linear", 
-                          timesteps=1000,
-                          linear_start=1e-4, 
-                          linear_end=2e-2, 
-                          cosine_s=8e-3):
-        if given_betas is not None:
-            betas = given_betas
-        else:
-            betas = make_beta_schedule(beta_schedule, timesteps, linear_start=linear_start, linear_end=linear_end,
-                                       cosine_s=cosine_s)
-        alphas = 1. - betas
-        alphas_cumprod = np.cumprod(alphas, axis=0)
-        alphas_cumprod_prev = np.append(1., alphas_cumprod[:-1])
-
-        timesteps, = betas.shape
-        self.num_timesteps = int(timesteps)
-        self.linear_start = linear_start
-        self.linear_end = linear_end
-        assert alphas_cumprod.shape[0] == self.num_timesteps, \
-            'alphas have to be defined for each timestep'
-
-        to_torch = partial(torch.tensor, dtype=torch.float32)
-
-        self.register_buffer('betas', to_torch(betas))
-        self.register_buffer('alphas_cumprod', to_torch(alphas_cumprod))
-        self.register_buffer('alphas_cumprod_prev', to_torch(alphas_cumprod_prev))
-
-        # calculations for diffusion q(x_t | x_{t-1}) and others
-        self.register_buffer('sqrt_alphas_cumprod', to_torch(np.sqrt(alphas_cumprod)))
-        self.register_buffer('sqrt_one_minus_alphas_cumprod', to_torch(np.sqrt(1. - alphas_cumprod)))
-        self.register_buffer('log_one_minus_alphas_cumprod', to_torch(np.log(1. - alphas_cumprod)))
-        self.register_buffer('sqrt_recip_alphas_cumprod', to_torch(np.sqrt(1. / alphas_cumprod)))
-        self.register_buffer('sqrt_recipm1_alphas_cumprod', to_torch(np.sqrt(1. / alphas_cumprod - 1)))
-
-        # calculations for posterior q(x_{t-1} | x_t, x_0)
-        posterior_variance = (1 - self.v_posterior) * betas * (1. - alphas_cumprod_prev) / (
-                    1. - alphas_cumprod) + self.v_posterior * betas
-        # above: equal to 1. / (1. / (1. - alpha_cumprod_tm1) + alpha_t / beta_t)
-        self.register_buffer('posterior_variance', to_torch(posterior_variance))
-        # below: log calculation clipped because the posterior variance is 0 at the beginning of the diffusion chain
-        self.register_buffer('posterior_log_variance_clipped', to_torch(np.log(np.maximum(posterior_variance, 1e-20))))
-        self.register_buffer('posterior_mean_coef1', to_torch(
-            betas * np.sqrt(alphas_cumprod_prev) / (1. - alphas_cumprod)))
-        self.register_buffer('posterior_mean_coef2', to_torch(
-            (1. - alphas_cumprod_prev) * np.sqrt(alphas) / (1. - alphas_cumprod)))
-
-        if self.parameterization == "eps":
-            lvlb_weights = self.betas ** 2 / (
-                        2 * self.posterior_variance * to_torch(alphas) * (1 - self.alphas_cumprod))
-        elif self.parameterization == "x0":
-            lvlb_weights = 0.5 * np.sqrt(torch.Tensor(alphas_cumprod)) / (2. * 1 - torch.Tensor(alphas_cumprod))
-        else:
-            raise NotImplementedError("mu not supported")
-        # TODO how to choose this term
-        lvlb_weights[0] = lvlb_weights[1]
-        self.register_buffer('lvlb_weights', lvlb_weights, persistent=False)
-        assert not torch.isnan(self.lvlb_weights).all()
-
-    @contextmanager
-    def ema_scope(self, context=None):
-        if self.use_ema:
-            self.model_ema.store(self.model.parameters())
-            self.model_ema.copy_to(self.model)
-            if context is not None:
-                print_log(f"{context}: Switched to EMA weights")
-        try:
-            yield None
-        finally:
-            if self.use_ema:
-                self.model_ema.restore(self.model.parameters())
-                if context is not None:
-                    print_log(f"{context}: Restored training weights")
-
-    def q_mean_variance(self, x_start, t):
-        """
-        Get the distribution q(x_t | x_0).
-        :param x_start: the [N x C x ...] tensor of noiseless inputs.
-        :param t: the number of diffusion steps (minus 1). Here, 0 means one step.
-        :return: A tuple (mean, variance, log_variance), all of x_start's shape.
-        """
-        mean = (extract_into_tensor(self.sqrt_alphas_cumprod, t, x_start.shape) * x_start)
-        variance = extract_into_tensor(1.0 - self.alphas_cumprod, t, x_start.shape)
-        log_variance = extract_into_tensor(self.log_one_minus_alphas_cumprod, t, x_start.shape)
-        return mean, variance, log_variance
-
-    def predict_start_from_noise(self, x_t, t, noise):
-        value1 = extract_into_tensor(
-            self.sqrt_recip_alphas_cumprod, t, x_t.shape)
-        value2 = extract_into_tensor(
-            self.sqrt_recipm1_alphas_cumprod, t, x_t.shape)
-        return value1*x_t -value2*noise
-
-    def q_sample(self, x_start, t, noise=None):
-        noise = torch.randn_like(x_start) if noise is None else noise
-        return (extract_into_tensor(self.sqrt_alphas_cumprod, t, x_start.shape) * x_start +
-                extract_into_tensor(self.sqrt_one_minus_alphas_cumprod, t, x_start.shape) * noise)
-
-    def get_loss(self, pred, target, mean=True):
-        if self.loss_type == 'l1':
-            loss = (target - pred).abs()
-            if mean:
-                loss = loss.mean()
-        elif self.loss_type == 'l2':
-            if mean:
-                loss = torch.nn.functional.mse_loss(target, pred)
-            else:
-                loss = torch.nn.functional.mse_loss(target, pred, reduction='none')
-        else:
-            raise NotImplementedError("unknown loss type '{loss_type}'")
-
-        return loss
-
-    def forward(self, x_info, c_info):
-        x = x_info['x']
-        t = torch.randint(0, self.num_timesteps, (x.shape[0],), device=self.device).long()
-        return self.p_losses(x_info, t, c_info)
-
-    def p_losses(self, x_info, t, c_info, noise=None):
-        x = x_info['x']
-        noise = torch.randn_like(x) if noise is None else noise
-        x_noisy = self.q_sample(x_start=x, t=t, noise=noise)
-        x_info['x'] = x_noisy
-        model_output = self.apply_model(x_info, t, c_info)
-
-        loss_dict = {}
-
-        if self.parameterization == "x0":
-            target = x
-        elif self.parameterization == "eps":
-            target = noise
-        else:
-            raise NotImplementedError()
-
-        bs = model_output.shape[0]
-        loss_simple = self.get_loss(model_output, target, mean=False).view(bs, -1).mean(-1)
-        loss_dict['loss_simple'] = loss_simple.mean()
-
-        # logvar_t = self.logvar[t].to(self.device)
-        logvar_t = self.logvar[t.to(self.logvar.device)].to(self.device)
-        loss = loss_simple / torch.exp(logvar_t) + logvar_t
-
-        if self.learn_logvar:
-            loss_dict['loss_gamma'] = loss.mean()
-            loss_dict['logvar'    ] = self.logvar.data.mean()
-
-        loss = self.l_simple_weight * loss.mean()
-
-        loss_vlb = self.get_loss(model_output, target, mean=False).view(bs, -1).mean(-1)
-        loss_vlb = (self.lvlb_weights[t] * loss_vlb).mean()
-        loss_dict['loss_vlb'] = loss_vlb
-        loss_dict.update({'Loss': loss})
-
-        return loss, loss_dict
-
-    @torch.no_grad()
-    def vae_encode(self, x, which, **kwargs):
-        z = self.vae[which].encode(x, **kwargs)
-        if self.latent_scale_factor is not None:
-            if self.latent_scale_factor.get(which, None) is not None:
-                scale = self.latent_scale_factor[which]
-                return scale * z
-        return z
-
-    @torch.no_grad()
-    def vae_decode(self, z, which, **kwargs):
-        if self.latent_scale_factor is not None:
-            if self.latent_scale_factor.get(which, None) is not None:
-                scale = self.latent_scale_factor[which]
-                z = 1./scale * z
-        x = self.vae[which].decode(z, **kwargs)
-        return x
-
-    @torch.no_grad()
-    def ctx_encode(self, x, which, **kwargs):
-        if which.find('vae_') == 0:
-            return self.vae[which[4:]].encode(x, **kwargs)
-        else:
-            return self.ctx[which].encode(x, **kwargs)
-
-    def ctx_encode_trainable(self, x, which, **kwargs):
-        if which.find('vae_') == 0:
-            return self.vae[which[4:]].encode(x, **kwargs)
-        else:
-            return self.ctx[which].encode(x, **kwargs)
-
-    def check_diffuser(self):
-        for idx, (_, diffuseri) in enumerate(self.diffuser.items()):
-            if idx==0:
-                order = diffuseri.layer_order
-            else:
-                if not order == diffuseri.layer_order:
-                    return False
-        return True
-
-    @torch.no_grad()
-    def on_train_batch_start(self, x):
-        pass
-
-    def on_train_batch_end(self, *args, **kwargs):
-        if self.use_ema:
-            self.model_ema(self.model)
-
-    def apply_model(self, x_info, timesteps, c_info):
-        x_type, x = x_info['type'], x_info['x']
-        c_type, c = c_info['type'], c_info['c']
-        dtype = x.dtype
-
-        hs = []
-
-        from .openaimodel import timestep_embedding
-
-        glayer_ptr = x_type if self.global_layer_ptr is None else self.global_layer_ptr
-        model_channels = self.diffuser[glayer_ptr].model_channels
-        t_emb = timestep_embedding(timesteps, model_channels, repeat_only=False).to(dtype)
-        emb = self.diffuser[glayer_ptr].time_embed(t_emb)
-
-        d_iter = iter(self.diffuser[x_type].data_blocks)
-        c_iter = iter(self.diffuser[c_type].context_blocks)
-
-        i_order = self.diffuser[x_type].i_order
-        m_order = self.diffuser[x_type].m_order
-        o_order = self.diffuser[x_type].o_order
-
-        h = x
-        for ltype in i_order:
-            if ltype == 'd':
-                module = next(d_iter)
-                h = module(h, emb, None)
-            elif ltype == 'c':
-                module = next(c_iter)
-                h = module(h, emb, c)
-            elif ltype == 'save_hidden_feature':
-                hs.append(h)
-
-        for ltype in m_order:
-            if ltype == 'd':
-                module = next(d_iter)
-                h = module(h, emb, None)
-            elif ltype == 'c':
-                module = next(c_iter)
-                h = module(h, emb, c)
-
-        for ltype in o_order:
-            if ltype == 'load_hidden_feature':
-                h = torch.cat([h, hs.pop()], dim=1)
-            elif ltype == 'd':
-                module = next(d_iter)
-                h = module(h, emb, None)
-            elif ltype == 'c':
-                module = next(c_iter)
-                h = module(h, emb, c)
-        o = h
-
-        return o
-
-    def context_mixing(self, x, emb, context_module_list, context_info_list, mixing_type):
-        nm = len(context_module_list)
-        nc = len(context_info_list)
-        assert nm == nc
-        context = [c_info['c'] for c_info in context_info_list]
-        cratio = np.array([c_info['ratio'] for c_info in context_info_list])
-        cratio = cratio / cratio.sum()
-
-        if mixing_type == 'attention':
-            h = None
-            for module, c, r in zip(context_module_list, context, cratio):
-                hi = module(x, emb, c) * r
-                h = h+hi if h is not None else hi
-            return h
-        elif mixing_type == 'layer':
-            ni = npr.choice(nm, p=cratio)
-            module = context_module_list[ni]
-            c = context[ni]
-            h = module(x, emb, c)
-            return h
-
-    def apply_model_multicontext(self, x_info, timesteps, c_info_list, mixing_type='attention'):
-        '''
-        context_info_list: [[context_type, context, ratio]] for 'attention'
-        '''
-
-        x_type, x = x_info['type'], x_info['x']
-        dtype = x.dtype
-
-        hs = []
-
-        from .openaimodel import timestep_embedding
-        model_channels = self.diffuser[x_type].model_channels
-        t_emb = timestep_embedding(timesteps, model_channels, repeat_only=False).to(dtype)
-        emb = self.diffuser[x_type].time_embed(t_emb)
-
-        d_iter = iter(self.diffuser[x_type].data_blocks)
-        c_iter_list = [iter(self.diffuser[c_info['type']].context_blocks) for c_info in c_info_list]
-
-        i_order = self.diffuser[x_type].i_order
-        m_order = self.diffuser[x_type].m_order
-        o_order = self.diffuser[x_type].o_order
-
-        h = x
-        for ltype in i_order:
-            if ltype == 'd':
-                module = next(d_iter)
-                h = module(h, emb, None)
-            elif ltype == 'c':
-                module_list = [next(c_iteri) for c_iteri in c_iter_list]
-                h = self.context_mixing(h, emb, module_list, c_info_list, mixing_type)
-            elif ltype == 'save_hidden_feature':
-                hs.append(h)
-
-        for ltype in m_order:
-            if ltype == 'd':
-                module = next(d_iter)
-                h = module(h, emb, None)
-            elif ltype == 'c':
-                module_list = [next(c_iteri) for c_iteri in c_iter_list]
-                h = self.context_mixing(h, emb, module_list, c_info_list, mixing_type)
-
-        for ltype in o_order:
-            if ltype == 'load_hidden_feature':
-                h = torch.cat([h, hs.pop()], dim=1)
-            elif ltype == 'd':
-                module = next(d_iter)
-                h = module(h, emb, None)
-            elif ltype == 'c':
-                module_list = [next(c_iteri) for c_iteri in c_iter_list]
-                h = self.context_mixing(h, emb, module_list, c_info_list, mixing_type)
-        o = h
-        return o
-
-    def get_device(self):
-        one_param = next(self.parameters())
-        return one_param.device
-
-    def get_dtype(self):
-        one_param = next(self.parameters())
-        return one_param.dtype
-
-    @torch.no_grad()
-    def print_debug_checksum(self):
-        csum = {
-            ki : next(self.parameter_group[ki][0].parameters()).abs().sum().item()
-                for ki in self.parameter_group.keys()
-        }
-        print(csum)
-
-@register('pfd_with_control')
-class PromptFreeDiffusion_with_control(PromptFreeDiffusion):
-    def __init__(self, *args, **kwargs):
-        ctl_cfg = kwargs.pop('ctl_cfg')
-        super().__init__(*args, **kwargs)
-        self.ctl = get_model()(ctl_cfg)
-        self.control_scales = [1.0] * 13
-        self.parameter_group['ctl'] = [self.ctl]
-
-    def apply_model(self, x_info, timesteps, c_info):
-        x_type, x = x_info['type'], x_info['x']
-        c_type, c = c_info['type'], c_info['c']
-        cc = c_info.get('control', None)
-        dtype = x.dtype
-
-        if cc is not None:
-            ccs = self.ctl(x, hint=cc, timesteps=timesteps, context=c)
-        else:
-            class ccs_zeros(object):
-                def __init__(self): pass
-                def pop(self): return 0
-            ccs = ccs_zeros()
-
-        hs = []
-
-        from .openaimodel import timestep_embedding
-
-        glayer_ptr = x_type if self.global_layer_ptr is None else self.global_layer_ptr
-        model_channels = self.diffuser[glayer_ptr].model_channels
-        t_emb = timestep_embedding(timesteps, model_channels, repeat_only=False).to(dtype)
-        emb = self.diffuser[glayer_ptr].time_embed(t_emb)
-
-        d_iter = iter(self.diffuser[x_type].data_blocks)
-        c_iter = iter(self.diffuser[c_type].context_blocks)
-
-        i_order = self.diffuser[x_type].i_order
-        m_order = self.diffuser[x_type].m_order
-        o_order = self.diffuser[x_type].o_order
-
-        h = x
-        for ltype in i_order:
-            if ltype == 'd':
-                module = next(d_iter)
-                h = module(h, emb, None)
-            elif ltype == 'c':
-                module = next(c_iter)
-                h = module(h, emb, c)
-            elif ltype == 'save_hidden_feature':
-                hs.append(h)
-
-        for ltype in m_order:
-            if ltype == 'd':
-                module = next(d_iter)
-                h = module(h, emb, None)
-            elif ltype == 'c':
-                module = next(c_iter)
-                h = module(h, emb, c)
-
-        h = h + ccs.pop()
-
-        for ltype in o_order:
-            if ltype == 'load_hidden_feature':
-                h = torch.cat([h, hs.pop()+ccs.pop()], dim=1)
-            elif ltype == 'd':
-                module = next(d_iter)
-                h = module(h, emb, None)
-            elif ltype == 'c':
-                module = next(c_iter)
-                h = module(h, emb, c)
-        o = h
-
-        return o
diff --git a/spaces/shivammehta25/Diff-TTSG/diff_ttsg/text/numbers.py b/spaces/shivammehta25/Diff-TTSG/diff_ttsg/text/numbers.py
deleted file mode 100644
index 6604d475c9f8d6c559a70b7a294230d80917c95a..0000000000000000000000000000000000000000
--- a/spaces/shivammehta25/Diff-TTSG/diff_ttsg/text/numbers.py
+++ /dev/null
@@ -1,72 +0,0 @@
-""" from https://github.com/keithito/tacotron """
-
-import inflect
-import re
-
-
-_inflect = inflect.engine()
-_comma_number_re = re.compile(r'([0-9][0-9\,]+[0-9])')
-_decimal_number_re = re.compile(r'([0-9]+\.[0-9]+)')
-_pounds_re = re.compile(r'£([0-9\,]*[0-9]+)')
-_dollars_re = re.compile(r'\$([0-9\.\,]*[0-9]+)')
-_ordinal_re = re.compile(r'[0-9]+(st|nd|rd|th)')
-_number_re = re.compile(r'[0-9]+')
-
-
-def _remove_commas(m):
-    return m.group(1).replace(',', '')
-
-
-def _expand_decimal_point(m):
-    return m.group(1).replace('.', ' point ')
-
-
-def _expand_dollars(m):
-    match = m.group(1)
-    parts = match.split('.')
-    if len(parts) > 2:
-        return match + ' dollars'
-    dollars = int(parts[0]) if parts[0] else 0
-    cents = int(parts[1]) if len(parts) > 1 and parts[1] else 0
-    if dollars and cents:
-        dollar_unit = 'dollar' if dollars == 1 else 'dollars'
-        cent_unit = 'cent' if cents == 1 else 'cents'
-        return '%s %s, %s %s' % (dollars, dollar_unit, cents, cent_unit)
-    elif dollars:
-        dollar_unit = 'dollar' if dollars == 1 else 'dollars'
-        return '%s %s' % (dollars, dollar_unit)
-    elif cents:
-        cent_unit = 'cent' if cents == 1 else 'cents'
-        return '%s %s' % (cents, cent_unit)
-    else:
-        return 'zero dollars'
-
-
-def _expand_ordinal(m):
-    return _inflect.number_to_words(m.group(0))
-
-
-def _expand_number(m):
-    num = int(m.group(0))
-    if num > 1000 and num < 3000:
-        if num == 2000:
-            return 'two thousand'
-        elif num > 2000 and num < 2010:
-            return 'two thousand ' + _inflect.number_to_words(num % 100)
-        elif num % 100 == 0:
-            return _inflect.number_to_words(num // 100) + ' hundred'
-        else:
-            return _inflect.number_to_words(num, andword='', zero='oh', 
-                                            group=2).replace(', ', ' ')
-    else:
-        return _inflect.number_to_words(num, andword='')
-
-
-def normalize_numbers(text):
-    text = re.sub(_comma_number_re, _remove_commas, text)
-    text = re.sub(_pounds_re, r'\1 pounds', text)
-    text = re.sub(_dollars_re, _expand_dollars, text)
-    text = re.sub(_decimal_number_re, _expand_decimal_point, text)
-    text = re.sub(_ordinal_re, _expand_ordinal, text)
-    text = re.sub(_number_re, _expand_number, text)
-    return text
diff --git a/spaces/shivammehta25/Diff-TTSG/pymo/preprocessing.py b/spaces/shivammehta25/Diff-TTSG/pymo/preprocessing.py
deleted file mode 100644
index 09efb510ad9e0a6502dea734b1c32824460341b1..0000000000000000000000000000000000000000
--- a/spaces/shivammehta25/Diff-TTSG/pymo/preprocessing.py
+++ /dev/null
@@ -1,2250 +0,0 @@
-"""
-Preprocessing Tranformers Based on sci-kit's API
-
-By Omid Alemi
-Created on June 12, 2017
-"""
-import copy
-
-import numpy as np
-import pandas as pd
-import scipy.ndimage.filters as filters
-import transforms3d as t3d
-from scipy import signal
-from sklearn.base import BaseEstimator, TransformerMixin
-from sklearn.pipeline import Pipeline
-
-from pymo.Pivots import Pivots
-from pymo.Quaternions import Quaternions
-from pymo.rotation_tools import (
-    Rotation,
-    euler2expmap,
-    euler2expmap2,
-    euler2vectors,
-    euler_reorder,
-    expmap2euler,
-    unroll,
-    vectors2euler,
-)
-
-
-class MocapParameterizer(BaseEstimator, TransformerMixin):
-    def __init__(self, param_type="euler", ref_pose=None):
-        """
-
-        param_type = {'euler', 'quat', 'expmap', 'position', 'expmap2pos'}
-        """
-        self.param_type = param_type
-        if ref_pose is not None:
-            self.ref_pose = self._to_quat(ref_pose)[0]
-        else:
-            self.ref_pose = None
-
-    def fit(self, X, y=None):
-        return self
-
-    def transform(self, X, y=None):
-        print("MocapParameterizer: " + self.param_type)
-        if self.param_type == "euler":
-            return X
-        elif self.param_type == "expmap":
-            if self.ref_pose is None:
-                return self._to_expmap(X)
-            else:
-                return self._to_expmap2(X)
-        elif self.param_type == "vectors":
-            return self._euler_to_vectors(X)
-        elif self.param_type == "quat":
-            return self._to_quat(X)
-        elif self.param_type == "position":
-            return self._to_pos(X)
-        elif self.param_type == "expmap2pos":
-            return self._expmap_to_pos(X)
-        else:
-            raise "param types: euler, quat, expmap, position, expmap2pos"
-
-    #        return X
-
-    def inverse_transform(self, X, copy=None):
-        if self.param_type == "euler":
-            return X
-        elif self.param_type == "expmap":
-            if self.ref_pose is None:
-                return self._expmap_to_euler(X)
-            else:
-                return self._expmap_to_euler2(X)
-        elif self.param_type == "vectors":
-            return self._vectors_to_euler(X)
-        elif self.param_type == "quat":
-            return self._quat_to_euler(X)
-        elif self.param_type == "position":
-            # raise 'positions 2 eulers is not supported'
-            print("positions 2 eulers is not supported")
-            return X
-        else:
-            raise "param types: euler, quat, expmap, position"
-
-    def _to_quat(self, X):
-        """Converts joints rotations in quaternions"""
-
-        Q = []
-        for track in X:
-            channels = []
-            titles = []
-            euler_df = track.values
-
-            # Create a new DataFrame to store the exponential map rep
-            quat_df = euler_df.copy()
-
-            # List the columns that contain rotation channels
-            rot_cols = [c for c in euler_df.columns if ("rotation" in c and "Nub" not in c)]
-
-            # List the joints that are not end sites, i.e., have channels
-            joints = (joint for joint in track.skeleton if "Nub" not in joint)
-
-            for joint in joints:
-                rot_order = track.skeleton[joint]["order"]
-
-                # Get the rotation columns that belong to this joint
-                rc = euler_df[[c for c in rot_cols if joint in c]]
-
-                r1_col = "%s_%srotation" % (joint, rot_order[0])
-                r2_col = "%s_%srotation" % (joint, rot_order[1])
-                r3_col = "%s_%srotation" % (joint, rot_order[2])
-                # Make sure the columns are organized in xyz order
-                if rc.shape[1] < 3:
-                    euler_values = np.zeros((euler_df.shape[0], 3))
-                    rot_order = "XYZ"
-                else:
-                    euler_values = (
-                        np.pi
-                        / 180.0
-                        * np.transpose(np.array([track.values[r1_col], track.values[r2_col], track.values[r3_col]]))
-                    )
-
-                quat_df.drop([r1_col, r2_col, r3_col], axis=1, inplace=True)
-                quats = Quaternions.from_euler(np.asarray(euler_values), order=rot_order.lower(), world=False)
-
-                # Create the corresponding columns in the new DataFrame
-                quat_df["%s_qWrotation" % joint] = pd.Series(data=[e[0] for e in quats], index=quat_df.index)
-                quat_df["%s_qXrotation" % joint] = pd.Series(data=[e[1] for e in quats], index=quat_df.index)
-                quat_df["%s_qYrotation" % joint] = pd.Series(data=[e[2] for e in quats], index=quat_df.index)
-                quat_df["%s_qZrotation" % joint] = pd.Series(data=[e[3] for e in quats], index=quat_df.index)
-
-            new_track = track.clone()
-            new_track.values = quat_df
-            Q.append(new_track)
-        return Q
-
-    def _quat_to_euler(self, X):
-        Q = []
-        for track in X:
-            channels = []
-            titles = []
-            quat_df = track.values
-
-            # Create a new DataFrame to store the exponential map rep
-            # euler_df = pd.DataFrame(index=exp_df.index)
-            euler_df = quat_df.copy()
-
-            # Copy the root positions into the new DataFrame
-            # rxp = '%s_Xposition'%track.root_name
-            # ryp = '%s_Yposition'%track.root_name
-            # rzp = '%s_Zposition'%track.root_name
-            # euler_df[rxp] = pd.Series(data=exp_df[rxp], index=euler_df.index)
-            # euler_df[ryp] = pd.Series(data=exp_df[ryp], index=euler_df.index)
-            # euler_df[rzp] = pd.Series(data=exp_df[rzp], index=euler_df.index)
-
-            # List the columns that contain rotation channels
-            quat_params = [
-                c
-                for c in quat_df.columns
-                if (any(p in c for p in ["qWrotation", "qXrotation", "qYrotation", "qZrotation"]) and "Nub" not in c)
-            ]
-
-            # List the joints that are not end sites, i.e., have channels
-            joints = (joint for joint in track.skeleton if "Nub" not in joint)
-
-            for joint in joints:
-                r = quat_df[[c for c in quat_params if joint in c]]  # Get the columns that belong to this joint
-
-                euler_df.drop(
-                    [
-                        "%s_qWrotation" % joint,
-                        "%s_qXrotation" % joint,
-                        "%s_qYrotation" % joint,
-                        "%s_qZrotation" % joint,
-                    ],
-                    axis=1,
-                    inplace=True,
-                )
-                quat = [
-                    [
-                        f[1]["%s_qWrotation" % joint],
-                        f[1]["%s_qXrotation" % joint],
-                        f[1]["%s_qYrotation" % joint],
-                        f[1]["%s_qZrotation" % joint],
-                    ]
-                    for f in r.iterrows()
-                ]  # Make sure the columsn are organized in xyz order
-                quats = Quaternions(np.asarray(quat))
-                euler_rots = 180 / np.pi * quats.euler()
-                track.skeleton[joint]["order"] = "ZYX"
-                rot_order = track.skeleton[joint]["order"]
-                # euler_rots = [Rotation(f, 'expmap').to_euler(True, rot_order) for f in expmap] # Convert the exp maps to eulers
-                # euler_rots = [expmap2euler(f, rot_order, True) for f in expmap] # Convert the exp maps to eulers
-
-                # Create the corresponding columns in the new DataFrame
-
-                euler_df["%s_%srotation" % (joint, rot_order[2])] = pd.Series(
-                    data=[e[0] for e in euler_rots], index=euler_df.index
-                )
-                euler_df["%s_%srotation" % (joint, rot_order[1])] = pd.Series(
-                    data=[e[1] for e in euler_rots], index=euler_df.index
-                )
-                euler_df["%s_%srotation" % (joint, rot_order[0])] = pd.Series(
-                    data=[e[2] for e in euler_rots], index=euler_df.index
-                )
-
-            new_track = track.clone()
-            new_track.values = euler_df
-            Q.append(new_track)
-
-        return Q
-
-    def _to_pos(self, X):
-        """Converts joints rotations in Euler angles to joint positions"""
-
-        Q = []
-        for track in X:
-            channels = []
-            titles = []
-            euler_df = track.values
-
-            # Create a new DataFrame to store the exponential map rep
-            pos_df = pd.DataFrame(index=euler_df.index)
-
-            # Copy the root rotations into the new DataFrame
-            # rxp = '%s_Xrotation'%track.root_name
-            # ryp = '%s_Yrotation'%track.root_name
-            # rzp = '%s_Zrotation'%track.root_name
-            # pos_df[rxp] = pd.Series(data=euler_df[rxp], index=pos_df.index)
-            # pos_df[ryp] = pd.Series(data=euler_df[ryp], index=pos_df.index)
-            # pos_df[rzp] = pd.Series(data=euler_df[rzp], index=pos_df.index)
-
-            # List the columns that contain rotation channels
-            rot_cols = [c for c in euler_df.columns if ("rotation" in c)]
-
-            # List the columns that contain position channels
-            pos_cols = [c for c in euler_df.columns if ("position" in c)]
-
-            # List the joints that are not end sites, i.e., have channels
-            joints = (joint for joint in track.skeleton)
-
-            tree_data = {}
-
-            for joint in track.traverse():
-                parent = track.skeleton[joint]["parent"]
-                rot_order = track.skeleton[joint]["order"]
-                # print("rot_order:" + joint + " :" + rot_order)
-
-                # Get the rotation columns that belong to this joint
-                rc = euler_df[[c for c in rot_cols if joint in c]]
-
-                # Get the position columns that belong to this joint
-                pc = euler_df[[c for c in pos_cols if joint in c]]
-
-                # Make sure the columns are organized in xyz order
-                if rc.shape[1] < 3:
-                    euler_values = np.zeros((euler_df.shape[0], 3))
-                    rot_order = "XYZ"
-                else:
-                    euler_values = (
-                        np.pi
-                        / 180.0
-                        * np.transpose(
-                            np.array(
-                                [
-                                    track.values["%s_%srotation" % (joint, rot_order[0])],
-                                    track.values["%s_%srotation" % (joint, rot_order[1])],
-                                    track.values["%s_%srotation" % (joint, rot_order[2])],
-                                ]
-                            )
-                        )
-                    )
-
-                if pc.shape[1] < 3:
-                    pos_values = np.asarray([[0, 0, 0] for f in pc.iterrows()])
-                else:
-                    pos_values = np.asarray(
-                        [
-                            [f[1]["%s_Xposition" % joint], f[1]["%s_Yposition" % joint], f[1]["%s_Zposition" % joint]]
-                            for f in pc.iterrows()
-                        ]
-                    )
-
-                quats = Quaternions.from_euler(np.asarray(euler_values), order=rot_order.lower(), world=False)
-
-                tree_data[joint] = [[], []]  # to store the rotation matrix  # to store the calculated position
-                if track.root_name == joint:
-                    tree_data[joint][0] = quats  # rotmats
-                    # tree_data[joint][1] = np.add(pos_values, track.skeleton[joint]['offsets'])
-                    tree_data[joint][1] = pos_values
-                else:
-                    # for every frame i, multiply this joint's rotmat to the rotmat of its parent
-                    tree_data[joint][0] = tree_data[parent][0] * quats  # np.matmul(rotmats, tree_data[parent][0])
-
-                    # add the position channel to the offset and store it in k, for every frame i
-                    k = pos_values + np.asarray(track.skeleton[joint]["offsets"])
-
-                    # multiply k to the rotmat of the parent for every frame i
-                    q = tree_data[parent][0] * k  # np.matmul(k.reshape(k.shape[0],1,3), tree_data[parent][0])
-
-                    # add q to the position of the parent, for every frame i
-                    tree_data[joint][1] = tree_data[parent][1] + q  # q.reshape(k.shape[0],3) + tree_data[parent][1]
-
-                # Create the corresponding columns in the new DataFrame
-                pos_df["%s_Xposition" % joint] = pd.Series(data=[e[0] for e in tree_data[joint][1]], index=pos_df.index)
-                pos_df["%s_Yposition" % joint] = pd.Series(data=[e[1] for e in tree_data[joint][1]], index=pos_df.index)
-                pos_df["%s_Zposition" % joint] = pd.Series(data=[e[2] for e in tree_data[joint][1]], index=pos_df.index)
-
-            new_track = track.clone()
-            new_track.values = pos_df
-            Q.append(new_track)
-        return Q
-
-    def _expmap2rot(self, expmap):
-        theta = np.linalg.norm(expmap, axis=1, keepdims=True)
-        nz = np.nonzero(theta)[0]
-
-        expmap[nz, :] = expmap[nz, :] / theta[nz]
-
-        nrows = expmap.shape[0]
-        x = expmap[:, 0]
-        y = expmap[:, 1]
-        z = expmap[:, 2]
-
-        s = np.sin(theta * 0.5).reshape(nrows)
-        c = np.cos(theta * 0.5).reshape(nrows)
-
-        rotmats = np.zeros((nrows, 3, 3))
-
-        rotmats[:, 0, 0] = 2 * (x * x - 1) * s * s + 1
-        rotmats[:, 0, 1] = 2 * x * y * s * s - 2 * z * c * s
-        rotmats[:, 0, 2] = 2 * x * z * s * s + 2 * y * c * s
-        rotmats[:, 1, 0] = 2 * x * y * s * s + 2 * z * c * s
-        rotmats[:, 1, 1] = 2 * (y * y - 1) * s * s + 1
-        rotmats[:, 1, 2] = 2 * y * z * s * s - 2 * x * c * s
-        rotmats[:, 2, 0] = 2 * x * z * s * s - 2 * y * c * s
-        rotmats[:, 2, 1] = 2 * y * z * s * s + 2 * x * c * s
-        rotmats[:, 2, 2] = 2 * (z * z - 1) * s * s + 1
-
-        return rotmats
-
-    def _expmap_to_pos(self, X):
-        """Converts joints rotations in expmap notation to joint positions"""
-
-        Q = []
-        for track in X:
-            channels = []
-            titles = []
-            exp_df = track.values
-
-            # Create a new DataFrame to store the exponential map rep
-            pos_df = pd.DataFrame(index=exp_df.index)
-
-            # Copy the root rotations into the new DataFrame
-            # rxp = '%s_Xrotation'%track.root_name
-            # ryp = '%s_Yrotation'%track.root_name
-            # rzp = '%s_Zrotation'%track.root_name
-            # pos_df[rxp] = pd.Series(data=euler_df[rxp], index=pos_df.index)
-            # pos_df[ryp] = pd.Series(data=euler_df[ryp], index=pos_df.index)
-            # pos_df[rzp] = pd.Series(data=euler_df[rzp], index=pos_df.index)
-
-            # List the columns that contain rotation channels
-            exp_params = [
-                c for c in exp_df.columns if (any(p in c for p in ["alpha", "beta", "gamma"]) and "Nub" not in c)
-            ]
-
-            # List the joints that are not end sites, i.e., have channels
-            joints = (joint for joint in track.skeleton)
-
-            tree_data = {}
-
-            for joint in track.traverse():
-                parent = track.skeleton[joint]["parent"]
-
-                if "Nub" not in joint:
-                    r = exp_df[[c for c in exp_params if joint in c]]  # Get the columns that belong to this joint
-                    expmap = r.values
-                    # expmap = [[f[1]['%s_alpha'%joint], f[1]['%s_beta'%joint], f[1]['%s_gamma'%joint]] for f in r.iterrows()]
-                else:
-                    expmap = np.zeros((exp_df.shape[0], 3))
-
-                # Convert the eulers to rotation matrices
-                # rotmats = np.asarray([Rotation(f, 'expmap').rotmat for f in expmap])
-                # angs = np.linalg.norm(expmap,axis=1, keepdims=True)
-                rotmats = self._expmap2rot(expmap)
-
-                tree_data[joint] = [[], []]  # to store the rotation matrix  # to store the calculated position
-                pos_values = np.zeros((exp_df.shape[0], 3))
-
-                if track.root_name == joint:
-                    tree_data[joint][0] = rotmats
-                    # tree_data[joint][1] = np.add(pos_values, track.skeleton[joint]['offsets'])
-                    tree_data[joint][1] = pos_values
-                else:
-                    # for every frame i, multiply this joint's rotmat to the rotmat of its parent
-                    tree_data[joint][0] = np.matmul(rotmats, tree_data[parent][0])
-
-                    # add the position channel to the offset and store it in k, for every frame i
-                    k = pos_values + track.skeleton[joint]["offsets"]
-
-                    # multiply k to the rotmat of the parent for every frame i
-                    q = np.matmul(k.reshape(k.shape[0], 1, 3), tree_data[parent][0])
-
-                    # add q to the position of the parent, for every frame i
-                    tree_data[joint][1] = q.reshape(k.shape[0], 3) + tree_data[parent][1]
-
-                # Create the corresponding columns in the new DataFrame
-                pos_df["%s_Xposition" % joint] = pd.Series(data=tree_data[joint][1][:, 0], index=pos_df.index)
-                pos_df["%s_Yposition" % joint] = pd.Series(data=tree_data[joint][1][:, 1], index=pos_df.index)
-                pos_df["%s_Zposition" % joint] = pd.Series(data=tree_data[joint][1][:, 2], index=pos_df.index)
-
-            new_track = track.clone()
-            new_track.values = pos_df
-            Q.append(new_track)
-        return Q
-
-    def _to_expmap(self, X):
-        """Converts Euler angles to Exponential Maps"""
-
-        Q = []
-        for track in X:
-            channels = []
-            titles = []
-            euler_df = track.values
-
-            # Create a new DataFrame to store the exponential map rep
-            exp_df = euler_df.copy()  # pd.DataFrame(index=euler_df.index)
-
-            # Copy the root positions into the new DataFrame
-            # rxp = '%s_Xposition'%track.root_name
-            # ryp = '%s_Yposition'%track.root_name
-            # rzp = '%s_Zposition'%track.root_name
-            # exp_df[rxp] = pd.Series(data=euler_df[rxp], index=exp_df.index)
-            # exp_df[ryp] = pd.Series(data=euler_df[ryp], index=exp_df.index)
-            # exp_df[rzp] = pd.Series(data=euler_df[rzp], index=exp_df.index)
-
-            # List the columns that contain rotation channels
-            rots = [c for c in euler_df.columns if ("rotation" in c and "Nub" not in c)]
-
-            # List the joints that are not end sites, i.e., have channels
-            joints = (joint for joint in track.skeleton if "Nub" not in joint)
-
-            for joint in joints:
-                # print(joint)
-                r = euler_df[[c for c in rots if joint in c]]  # Get the columns that belong to this joint
-                rot_order = track.skeleton[joint]["order"]
-                r1_col = "%s_%srotation" % (joint, rot_order[0])
-                r2_col = "%s_%srotation" % (joint, rot_order[1])
-                r3_col = "%s_%srotation" % (joint, rot_order[2])
-
-                exp_df.drop([r1_col, r2_col, r3_col], axis=1, inplace=True)
-                euler = [[f[1][r1_col], f[1][r2_col], f[1][r3_col]] for f in r.iterrows()]
-                # exps = [Rotation(f, 'euler', from_deg=True, order=rot_order).to_expmap() for f in euler] # Convert the eulers to exp maps
-                exps = unroll(
-                    np.array([euler2expmap(f, rot_order, True) for f in euler])
-                )  # Convert the exp maps to eulers
-                # exps = euler2expmap2(euler, rot_order, True) # Convert the eulers to exp maps
-
-                # Create the corresponding columns in the new DataFrame
-
-                exp_df.insert(
-                    loc=0, column="%s_gamma" % joint, value=pd.Series(data=[e[2] for e in exps], index=exp_df.index)
-                )
-                exp_df.insert(
-                    loc=0, column="%s_beta" % joint, value=pd.Series(data=[e[1] for e in exps], index=exp_df.index)
-                )
-                exp_df.insert(
-                    loc=0, column="%s_alpha" % joint, value=pd.Series(data=[e[0] for e in exps], index=exp_df.index)
-                )
-
-            # print(exp_df.columns)
-            new_track = track.clone()
-            new_track.values = exp_df
-            Q.append(new_track)
-
-        return Q
-
-    def _expmap_to_euler(self, X):
-        Q = []
-        for track in X:
-            channels = []
-            titles = []
-            exp_df = track.values
-
-            # Create a new DataFrame to store the exponential map rep
-            # euler_df = pd.DataFrame(index=exp_df.index)
-            euler_df = exp_df.copy()
-
-            # Copy the root positions into the new DataFrame
-            # rxp = '%s_Xposition'%track.root_name
-            # ryp = '%s_Yposition'%track.root_name
-            # rzp = '%s_Zposition'%track.root_name
-            # euler_df[rxp] = pd.Series(data=exp_df[rxp], index=euler_df.index)
-            # euler_df[ryp] = pd.Series(data=exp_df[ryp], index=euler_df.index)
-            # euler_df[rzp] = pd.Series(data=exp_df[rzp], index=euler_df.index)
-
-            # List the columns that contain rotation channels
-            exp_params = [
-                c for c in exp_df.columns if (any(p in c for p in ["alpha", "beta", "gamma"]) and "Nub" not in c)
-            ]
-
-            # List the joints that are not end sites, i.e., have channels
-            joints = (joint for joint in track.skeleton if "Nub" not in joint)
-
-            for joint in joints:
-                r = exp_df[[c for c in exp_params if joint in c]]  # Get the columns that belong to this joint
-
-                euler_df.drop(["%s_alpha" % joint, "%s_beta" % joint, "%s_gamma" % joint], axis=1, inplace=True)
-                expmap = [
-                    [f[1]["%s_alpha" % joint], f[1]["%s_beta" % joint], f[1]["%s_gamma" % joint]] for f in r.iterrows()
-                ]  # Make sure the columsn are organized in xyz order
-                rot_order = track.skeleton[joint]["order"]
-                # euler_rots = [Rotation(f, 'expmap').to_euler(True, rot_order) for f in expmap] # Convert the exp maps to eulers
-                euler_rots = [expmap2euler(f, rot_order, True) for f in expmap]  # Convert the exp maps to eulers
-
-                # Create the corresponding columns in the new DataFrame
-
-                euler_df["%s_%srotation" % (joint, rot_order[0])] = pd.Series(
-                    data=[e[0] for e in euler_rots], index=euler_df.index
-                )
-                euler_df["%s_%srotation" % (joint, rot_order[1])] = pd.Series(
-                    data=[e[1] for e in euler_rots], index=euler_df.index
-                )
-                euler_df["%s_%srotation" % (joint, rot_order[2])] = pd.Series(
-                    data=[e[2] for e in euler_rots], index=euler_df.index
-                )
-
-            new_track = track.clone()
-            new_track.values = euler_df
-            Q.append(new_track)
-
-        return Q
-
-    def _to_expmap2(self, X):
-        """Converts Euler angles to Exponential Maps"""
-
-        Q = []
-        for track in X:
-            channels = []
-            titles = []
-            euler_df = track.values
-
-            # Create a new DataFrame to store the exponential map rep
-            exp_df = euler_df.copy()  # pd.DataFrame(index=euler_df.index)
-
-            # Copy the root positions into the new DataFrame
-            # rxp = '%s_Xposition'%track.root_name
-            # ryp = '%s_Yposition'%track.root_name
-            # rzp = '%s_Zposition'%track.root_name
-            # exp_df[rxp] = pd.Series(data=euler_df[rxp], index=exp_df.index)
-            # exp_df[ryp] = pd.Series(data=euler_df[ryp], index=exp_df.index)
-            # exp_df[rzp] = pd.Series(data=euler_df[rzp], index=exp_df.index)
-
-            # List the columns that contain rotation channels
-            rots = [c for c in euler_df.columns if ("rotation" in c and "Nub" not in c)]
-
-            # List the joints that are not end sites, i.e., have channels
-            joints = (joint for joint in track.skeleton if "Nub" not in joint)
-
-            for joint in joints:
-                r = euler_df[[c for c in rots if joint in c]]  # Get the columns that belong to this joint
-                rot_order = track.skeleton[joint]["order"]
-
-                # Get the rotation columns that belong to this joint
-                rc = euler_df[[c for c in rots if joint in c]]
-
-                r1_col = "%s_%srotation" % (joint, rot_order[0])
-                r2_col = "%s_%srotation" % (joint, rot_order[1])
-                r3_col = "%s_%srotation" % (joint, rot_order[2])
-                # Make sure the columns are organized in xyz order
-                # print("joint:" + str(joint) + "  rot_order:" + str(rot_order))
-                if rc.shape[1] < 3:
-                    euler_values = np.zeros((euler_df.shape[0], 3))
-                    rot_order = "XYZ"
-                else:
-                    euler_values = (
-                        np.pi
-                        / 180.0
-                        * np.transpose(np.array([track.values[r1_col], track.values[r2_col], track.values[r3_col]]))
-                    )
-
-                quats = Quaternions.from_euler(np.asarray(euler_values), order=rot_order.lower(), world=False)
-                # exps = [Rotation(f, 'euler', from_deg=True, order=rot_order).to_expmap() for f in euler] # Convert the eulers to exp maps
-                # exps = unroll(np.array([euler2expmap(f, rot_order, True) for f in euler])) # Convert the exp maps to eulers
-                # exps = euler2expmap2(euler, rot_order, True) # Convert the eulers to exp maps
-                # Create the corresponding columns in the new DataFrame
-                if self.ref_pose is not None:
-                    q1_col = "%s_qWrotation" % (joint)
-                    q2_col = "%s_qXrotation" % (joint)
-                    q3_col = "%s_qYrotation" % (joint)
-                    q4_col = "%s_qZrotation" % (joint)
-                    ref_q = Quaternions(
-                        np.asarray(
-                            [
-                                [f[1][q1_col], f[1][q2_col], f[1][q3_col], f[1][q4_col]]
-                                for f in self.ref_pose.values.iterrows()
-                            ]
-                        )
-                    )
-                    # print("ref_q:" + str(ref_q.shape))
-                    ref_q = ref_q[0, :]
-                    quats = (-ref_q) * quats
-
-                angles, axis = quats.angle_axis()
-                aa = np.where(angles > np.pi)
-                angles[aa] = angles[aa] - 2 * np.pi
-                # exps = unroll(angles[:,None]*axis)
-                exps = angles[:, None] * axis
-                # print(f"{joint}: {str(exps[0,:])}")
-
-                # exps = np.array([quat2expmap(f) for f in quats])
-                exp_df.drop([r1_col, r2_col, r3_col], axis=1, inplace=True)
-                exp_df.insert(
-                    loc=0, column="%s_gamma" % joint, value=pd.Series(data=[e[2] for e in exps], index=exp_df.index)
-                )
-                exp_df.insert(
-                    loc=0, column="%s_beta" % joint, value=pd.Series(data=[e[1] for e in exps], index=exp_df.index)
-                )
-                exp_df.insert(
-                    loc=0, column="%s_alpha" % joint, value=pd.Series(data=[e[0] for e in exps], index=exp_df.index)
-                )
-
-            # print(exp_df.columns)
-            new_track = track.clone()
-            new_track.values = exp_df
-            Q.append(new_track)
-
-        return Q
-
-    def _expmap_to_euler2(self, X):
-        Q = []
-        for track in X:
-            channels = []
-            titles = []
-            exp_df = track.values
-
-            # Create a new DataFrame to store the exponential map rep
-            # euler_df = pd.DataFrame(index=exp_df.index)
-            euler_df = exp_df.copy()
-
-            # Copy the root positions into the new DataFrame
-            # rxp = '%s_Xposition'%track.root_name
-            # ryp = '%s_Yposition'%track.root_name
-            # rzp = '%s_Zposition'%track.root_name
-            # euler_df[rxp] = pd.Series(data=exp_df[rxp], index=euler_df.index)
-            # euler_df[ryp] = pd.Series(data=exp_df[ryp], index=euler_df.index)
-            # euler_df[rzp] = pd.Series(data=exp_df[rzp], index=euler_df.index)
-
-            # List the columns that contain rotation channels
-            exp_params = [
-                c for c in exp_df.columns if (any(p in c for p in ["alpha", "beta", "gamma"]) and "Nub" not in c)
-            ]
-
-            # List the joints that are not end sites, i.e., have channels
-            joints = (joint for joint in track.skeleton if "Nub" not in joint)
-
-            for joint in joints:
-                r = exp_df[[c for c in exp_params if joint in c]]  # Get the columns that belong to this joint
-
-                euler_df.drop(["%s_alpha" % joint, "%s_beta" % joint, "%s_gamma" % joint], axis=1, inplace=True)
-                expmap = [
-                    [f[1]["%s_alpha" % joint], f[1]["%s_beta" % joint], f[1]["%s_gamma" % joint]] for f in r.iterrows()
-                ]  # Make sure the columsn are organized in xyz order
-                angs = np.linalg.norm(expmap, axis=1)
-                quats = Quaternions.from_angle_axis(angs, expmap / (np.tile(angs[:, None] + 1e-10, (1, 3))))
-                if self.ref_pose is not None:
-                    q1_col = "%s_qWrotation" % (joint)
-                    q2_col = "%s_qXrotation" % (joint)
-                    q3_col = "%s_qYrotation" % (joint)
-                    q4_col = "%s_qZrotation" % (joint)
-                    ref_q = Quaternions(
-                        np.asarray(
-                            [
-                                [f[1][q1_col], f[1][q2_col], f[1][q3_col], f[1][q4_col]]
-                                for f in self.ref_pose.values.iterrows()
-                            ]
-                        )
-                    )
-                    # print("ref_q:" + str(ref_q.shape))
-                    ref_q = ref_q[0, :]
-                    quats = ref_q * quats
-
-                euler_rots = 180 / np.pi * quats.euler()
-                track.skeleton[joint]["order"] = "ZYX"
-                rot_order = track.skeleton[joint]["order"]
-                # euler_rots = [Rotation(f, 'expmap').to_euler(True, rot_order) for f in expmap] # Convert the exp maps to eulers
-                # euler_rots = [expmap2euler(f, rot_order, True) for f in expmap] # Convert the exp maps to eulers
-
-                # Create the corresponding columns in the new DataFrame
-
-                euler_df["%s_%srotation" % (joint, rot_order[2])] = pd.Series(
-                    data=[e[0] for e in euler_rots], index=euler_df.index
-                )
-                euler_df["%s_%srotation" % (joint, rot_order[1])] = pd.Series(
-                    data=[e[1] for e in euler_rots], index=euler_df.index
-                )
-                euler_df["%s_%srotation" % (joint, rot_order[0])] = pd.Series(
-                    data=[e[2] for e in euler_rots], index=euler_df.index
-                )
-
-            new_track = track.clone()
-            new_track.values = euler_df
-            Q.append(new_track)
-
-        return Q
-
-    def _euler_to_vectors(self, X):
-        """Converts Euler angles to Up and Fwd vectors"""
-
-        Q = []
-        for track in X:
-            channels = []
-            titles = []
-            euler_df = track.values
-
-            # Create a new DataFrame to store the exponential map rep
-            vec_df = euler_df.copy()  # pd.DataFrame(index=euler_df.index)
-
-            # List the columns that contain rotation channels
-            rots = [c for c in euler_df.columns if ("rotation" in c and "Nub" not in c)]
-
-            # List the joints that are not end sites, i.e., have channels
-            joints = (joint for joint in track.skeleton if "Nub" not in joint)
-
-            for joint in joints:
-                # print(joint)
-                r = euler_df[[c for c in rots if joint in c]]  # Get the columns that belong to this joint
-                rot_order = track.skeleton[joint]["order"]
-                r1_col = "%s_%srotation" % (joint, rot_order[0])
-                r2_col = "%s_%srotation" % (joint, rot_order[1])
-                r3_col = "%s_%srotation" % (joint, rot_order[2])
-
-                vec_df.drop([r1_col, r2_col, r3_col], axis=1, inplace=True)
-                euler = [[f[1][r1_col], f[1][r2_col], f[1][r3_col]] for f in r.iterrows()]
-                vectors = np.array([euler2vectors(f, rot_order, True) for f in euler])
-
-                vec_df.insert(
-                    loc=0, column="%s_xUp" % joint, value=pd.Series(data=[e[0] for e in vectors], index=vec_df.index)
-                )
-                vec_df.insert(
-                    loc=0, column="%s_yUp" % joint, value=pd.Series(data=[e[1] for e in vectors], index=vec_df.index)
-                )
-                vec_df.insert(
-                    loc=0, column="%s_zUp" % joint, value=pd.Series(data=[e[2] for e in vectors], index=vec_df.index)
-                )
-                vec_df.insert(
-                    loc=0, column="%s_xFwd" % joint, value=pd.Series(data=[e[3] for e in vectors], index=vec_df.index)
-                )
-                vec_df.insert(
-                    loc=0, column="%s_yFwd" % joint, value=pd.Series(data=[e[4] for e in vectors], index=vec_df.index)
-                )
-                vec_df.insert(
-                    loc=0, column="%s_zFwd" % joint, value=pd.Series(data=[e[5] for e in vectors], index=vec_df.index)
-                )
-
-            # print(exp_df.columns)
-            new_track = track.clone()
-            new_track.values = vec_df
-            Q.append(new_track)
-
-        return Q
-
-    def _vectors_to_euler(self, X):
-        """Converts Up and Fwd vectors to Euler angles"""
-        Q = []
-        for track in X:
-            channels = []
-            titles = []
-            vec_df = track.values
-
-            # Create a new DataFrame to store the exponential map rep
-            # euler_df = pd.DataFrame(index=exp_df.index)
-            euler_df = vec_df.copy()
-
-            # List the columns that contain rotation channels
-            vec_params = [
-                c
-                for c in vec_df.columns
-                if (any(p in c for p in ["xUp", "yUp", "zUp", "xFwd", "yFwd", "zFwd"]) and "Nub" not in c)
-            ]
-
-            # List the joints that are not end sites, i.e., have channels
-            joints = (joint for joint in track.skeleton if "Nub" not in joint)
-
-            for joint in joints:
-                r = vec_df[[c for c in vec_params if joint in c]]  # Get the columns that belong to this joint
-
-                euler_df.drop(
-                    [
-                        "%s_xUp" % joint,
-                        "%s_yUp" % joint,
-                        "%s_zUp" % joint,
-                        "%s_xFwd" % joint,
-                        "%s_yFwd" % joint,
-                        "%s_zFwd" % joint,
-                    ],
-                    axis=1,
-                    inplace=True,
-                )
-                vectors = [
-                    [
-                        f[1]["%s_xUp" % joint],
-                        f[1]["%s_yUp" % joint],
-                        f[1]["%s_zUp" % joint],
-                        f[1]["%s_xFwd" % joint],
-                        f[1]["%s_yFwd" % joint],
-                        f[1]["%s_zFwd" % joint],
-                    ]
-                    for f in r.iterrows()
-                ]  # Make sure the columsn are organized in xyz order
-                rot_order = track.skeleton[joint]["order"]
-                euler_rots = [vectors2euler(f, rot_order, True) for f in vectors]
-
-                # Create the corresponding columns in the new DataFrame
-
-                euler_df["%s_%srotation" % (joint, rot_order[0])] = pd.Series(
-                    data=[e[0] for e in euler_rots], index=euler_df.index
-                )
-                euler_df["%s_%srotation" % (joint, rot_order[1])] = pd.Series(
-                    data=[e[1] for e in euler_rots], index=euler_df.index
-                )
-                euler_df["%s_%srotation" % (joint, rot_order[2])] = pd.Series(
-                    data=[e[2] for e in euler_rots], index=euler_df.index
-                )
-
-            new_track = track.clone()
-            new_track.values = euler_df
-            Q.append(new_track)
-
-        return Q
-
-
-class Mirror(BaseEstimator, TransformerMixin):
-    def __init__(self, axis="X", append=True):
-        """
-        Mirrors the data
-        """
-        self.axis = axis
-        self.append = append
-
-    def fit(self, X, y=None):
-        return self
-
-    def transform(self, X, y=None):
-        print("Mirror: " + self.axis)
-        Q = []
-
-        if self.append:
-            for track in X:
-                Q.append(track)
-
-        for track in X:
-            channels = []
-            titles = []
-
-            if self.axis == "X":
-                signs = np.array([1, -1, -1])
-            if self.axis == "Y":
-                signs = np.array([-1, 1, -1])
-            if self.axis == "Z":
-                signs = np.array([-1, -1, 1])
-
-            euler_df = track.values
-
-            # Create a new DataFrame to store the exponential map rep
-            new_df = pd.DataFrame(index=euler_df.index)
-
-            # Copy the root positions into the new DataFrame
-            rxp = "%s_Xposition" % track.root_name
-            ryp = "%s_Yposition" % track.root_name
-            rzp = "%s_Zposition" % track.root_name
-            new_df[rxp] = pd.Series(data=-signs[0] * euler_df[rxp], index=new_df.index)
-            new_df[ryp] = pd.Series(data=-signs[1] * euler_df[ryp], index=new_df.index)
-            new_df[rzp] = pd.Series(data=-signs[2] * euler_df[rzp], index=new_df.index)
-
-            # List the columns that contain rotation channels
-            rots = [c for c in euler_df.columns if ("rotation" in c and "Nub" not in c)]
-            # lft_rots = [c for c in euler_df.columns if ('Left' in c and 'rotation' in c and 'Nub' not in c)]
-            # rgt_rots = [c for c in euler_df.columns if ('Right' in c and 'rotation' in c and 'Nub' not in c)]
-            lft_joints = (joint for joint in track.skeleton if "Left" in joint and "Nub" not in joint)
-            rgt_joints = (joint for joint in track.skeleton if "Right" in joint and "Nub" not in joint)
-
-            new_track = track.clone()
-
-            for lft_joint in lft_joints:
-                # lr = euler_df[[c for c in rots if lft_joint + "_" in c]]
-                # rot_order = track.skeleton[lft_joint]['order']
-                # lft_eulers = [[f[1]['%s_Xrotation'%lft_joint], f[1]['%s_Yrotation'%lft_joint], f[1]['%s_Zrotation'%lft_joint]] for f in lr.iterrows()]
-
-                rgt_joint = lft_joint.replace("Left", "Right")
-                # rr = euler_df[[c for c in rots if rgt_joint + "_" in c]]
-                # rot_order = track.skeleton[rgt_joint]['order']
-                #                rgt_eulers = [[f[1]['%s_Xrotation'%rgt_joint], f[1]['%s_Yrotation'%rgt_joint], f[1]['%s_Zrotation'%rgt_joint]] for f in rr.iterrows()]
-
-                # Create the corresponding columns in the new DataFrame
-
-                new_df["%s_Xrotation" % lft_joint] = pd.Series(
-                    data=signs[0] * track.values["%s_Xrotation" % rgt_joint], index=new_df.index
-                )
-                new_df["%s_Yrotation" % lft_joint] = pd.Series(
-                    data=signs[1] * track.values["%s_Yrotation" % rgt_joint], index=new_df.index
-                )
-                new_df["%s_Zrotation" % lft_joint] = pd.Series(
-                    data=signs[2] * track.values["%s_Zrotation" % rgt_joint], index=new_df.index
-                )
-
-                new_df["%s_Xrotation" % rgt_joint] = pd.Series(
-                    data=signs[0] * track.values["%s_Xrotation" % lft_joint], index=new_df.index
-                )
-                new_df["%s_Yrotation" % rgt_joint] = pd.Series(
-                    data=signs[1] * track.values["%s_Yrotation" % lft_joint], index=new_df.index
-                )
-                new_df["%s_Zrotation" % rgt_joint] = pd.Series(
-                    data=signs[2] * track.values["%s_Zrotation" % lft_joint], index=new_df.index
-                )
-
-            # List the joints that are not left or right, i.e. are on the trunk
-            joints = (
-                joint for joint in track.skeleton if "Nub" not in joint and "Left" not in joint and "Right" not in joint
-            )
-
-            for joint in joints:
-                # r = euler_df[[c for c in rots if joint in c]] # Get the columns that belong to this joint
-                # rot_order = track.skeleton[joint]['order']
-
-                # eulers = [[f[1]['%s_Xrotation'%joint], f[1]['%s_Yrotation'%joint], f[1]['%s_Zrotation'%joint]] for f in r.iterrows()]
-
-                # Create the corresponding columns in the new DataFrame
-                new_df["%s_Xrotation" % joint] = pd.Series(
-                    data=signs[0] * track.values["%s_Xrotation" % joint], index=new_df.index
-                )
-                new_df["%s_Yrotation" % joint] = pd.Series(
-                    data=signs[1] * track.values["%s_Yrotation" % joint], index=new_df.index
-                )
-                new_df["%s_Zrotation" % joint] = pd.Series(
-                    data=signs[2] * track.values["%s_Zrotation" % joint], index=new_df.index
-                )
-
-            new_track.values = new_df
-            new_track.take_name = track.take_name + "_mirrored"
-            Q.append(new_track)
-
-        return Q
-
-    def inverse_transform(self, X, copy=None, start_pos=None):
-        return X
-
-
-class EulerReorder(BaseEstimator, TransformerMixin):
-    def __init__(self, new_order):
-        """
-        Add a
-        """
-        self.new_order = new_order
-
-    def fit(self, X, y=None):
-        self.orig_skeleton = copy.deepcopy(X[0].skeleton)
-        print(self.orig_skeleton)
-        return self
-
-    def transform(self, X, y=None):
-        print("EulerReorder")
-        Q = []
-
-        for track in X:
-            channels = []
-            titles = []
-            euler_df = track.values
-
-            # Create a new DataFrame to store the exponential map rep
-            # new_df = pd.DataFrame(index=euler_df.index)
-            new_df = euler_df.copy()
-
-            # Copy the root positions into the new DataFrame
-            rxp = "%s_Xposition" % track.root_name
-            ryp = "%s_Yposition" % track.root_name
-            rzp = "%s_Zposition" % track.root_name
-            new_df[rxp] = pd.Series(data=euler_df[rxp], index=new_df.index)
-            new_df[ryp] = pd.Series(data=euler_df[ryp], index=new_df.index)
-            new_df[rzp] = pd.Series(data=euler_df[rzp], index=new_df.index)
-
-            # List the columns that contain rotation channels
-            rots = [c for c in euler_df.columns if ("rotation" in c and "Nub" not in c)]
-
-            # List the joints that are not end sites, i.e., have channels
-            joints = (joint for joint in track.skeleton if "Nub" not in joint)
-
-            new_track = track.clone()
-            for joint in joints:
-                r = euler_df[[c for c in rots if joint in c]]  # Get the columns that belong to this joint
-                rot_order = track.skeleton[joint]["order"]
-                r1_col = "%s_%srotation" % (joint, rot_order[0])
-                r2_col = "%s_%srotation" % (joint, rot_order[1])
-                r3_col = "%s_%srotation" % (joint, rot_order[2])
-                euler = [[f[1][r1_col], f[1][r2_col], f[1][r3_col]] for f in r.iterrows()]
-
-                # euler = [[f[1]['%s_Xrotation'%(joint)], f[1]['%s_Yrotation'%(joint)], f[1]['%s_Zrotation'%(joint)]] for f in r.iterrows()]
-                new_euler = [euler_reorder(f, rot_order, self.new_order, True) for f in euler]
-                # new_euler = euler_reorder2(np.array(euler), rot_order, self.new_order, True)
-
-                # Create the corresponding columns in the new DataFrame
-                new_df["%s_%srotation" % (joint, self.new_order[0])] = pd.Series(
-                    data=[e[0] for e in new_euler], index=new_df.index
-                )
-                new_df["%s_%srotation" % (joint, self.new_order[1])] = pd.Series(
-                    data=[e[1] for e in new_euler], index=new_df.index
-                )
-                new_df["%s_%srotation" % (joint, self.new_order[2])] = pd.Series(
-                    data=[e[2] for e in new_euler], index=new_df.index
-                )
-
-                new_track.skeleton[joint]["order"] = self.new_order
-
-            new_track.values = new_df
-            Q.append(new_track)
-
-        return Q
-
-    def inverse_transform(self, X, copy=None, start_pos=None):
-        return X
-
-
-class JointSelector(BaseEstimator, TransformerMixin):
-    """
-    Allows for filtering the mocap data to include only the selected joints
-    """
-
-    def __init__(self, joints, include_root=False):
-        self.joints = joints
-        self.include_root = include_root
-
-    def fit(self, X, y=None):
-        selected_joints = []
-        selected_channels = []
-
-        if self.include_root:
-            selected_joints.append(X[0].root_name)
-
-        selected_joints.extend(self.joints)
-
-        for joint_name in selected_joints:
-            selected_channels.extend([o for o in X[0].values.columns if (joint_name + "_") in o and "Nub" not in o])
-
-        self.selected_joints = selected_joints
-        self.selected_channels = selected_channels
-        self.not_selected = X[0].values.columns.difference(selected_channels)
-        self.not_selected_values = {c: X[0].values[c].values[0] for c in self.not_selected}
-
-        self.orig_skeleton = X[0].skeleton
-        return self
-
-    def transform(self, X, y=None):
-        print("JointSelector")
-        Q = []
-        for track in X:
-            t2 = track.clone()
-            for key in track.skeleton.keys():
-                if key not in self.selected_joints:
-                    t2.skeleton.pop(key)
-            t2.values = track.values[self.selected_channels]
-
-            for key in t2.skeleton.keys():
-                to_remove = list(set(t2.skeleton[key]["children"]) - set(self.selected_joints))
-                [t2.skeleton[key]["children"].remove(c) for c in to_remove]
-
-            Q.append(t2)
-
-        return Q
-
-    def inverse_transform(self, X, copy=None):
-        Q = []
-
-        for track in X:
-            t2 = track.clone()
-            skeleton = self.orig_skeleton
-            for key in track.skeleton.keys():
-                skeleton[key]["order"] = track.skeleton[key]["order"]
-
-            t2.skeleton = skeleton
-            for d in self.not_selected:
-                t2.values[d] = self.not_selected_values[d]
-            Q.append(t2)
-
-        return Q
-
-
-class Numpyfier(BaseEstimator, TransformerMixin):
-    """
-    Just converts the values in a MocapData object into a numpy array
-    Useful for the final stage of a pipeline before training
-    """
-
-    def __init__(self):
-        pass
-
-    def fit(self, X, y=None):
-        self.org_mocap_ = X[0].clone()
-        self.org_mocap_.values.drop(self.org_mocap_.values.index, inplace=True)
-
-        return self
-
-    def transform(self, X, y=None):
-        print("Numpyfier")
-        Q = []
-
-        for track in X:
-            Q.append(track.values.values)
-            # print("Numpyfier:" + str(track.values.columns))
-
-        return np.array(Q)
-
-    def inverse_transform(self, X, copy=None):
-        Q = []
-
-        for track in X:
-            new_mocap = self.org_mocap_.clone()
-            time_index = pd.to_timedelta([f for f in range(track.shape[0])], unit="s") * self.org_mocap_.framerate
-
-            new_df = pd.DataFrame(data=track, index=time_index, columns=self.org_mocap_.values.columns)
-
-            new_mocap.values = new_df
-
-            Q.append(new_mocap)
-
-        return Q
-
-
-class Slicer(BaseEstimator, TransformerMixin):
-    """
-    Slice the data into intervals of equal size
-    """
-
-    def __init__(self, window_size, overlap=0.5):
-        self.window_size = window_size
-        self.overlap = overlap
-        pass
-
-    def fit(self, X, y=None):
-        self.org_mocap_ = X[0].clone()
-        self.org_mocap_.values.drop(self.org_mocap_.values.index, inplace=True)
-
-        return self
-
-    def transform(self, X, y=None):
-        print("Slicer")
-        Q = []
-
-        for track in X:
-            vals = track.values.values
-            nframes = vals.shape[0]
-            overlap_frames = (int)(self.overlap * self.window_size)
-
-            n_sequences = (nframes - overlap_frames) // (self.window_size - overlap_frames)
-
-            if n_sequences > 0:
-                y = np.zeros((n_sequences, self.window_size, vals.shape[1]))
-
-                # extract sequences from the input data
-                for i in range(0, n_sequences):
-                    frameIdx = (self.window_size - overlap_frames) * i
-                    Q.append(vals[frameIdx : frameIdx + self.window_size, :])
-
-        return np.array(Q)
-
-    def inverse_transform(self, X, copy=None):
-        Q = []
-
-        for track in X:
-            new_mocap = self.org_mocap_.clone()
-            time_index = pd.to_timedelta([f for f in range(track.shape[0])], unit="s")
-
-            new_df = pd.DataFrame(data=track, index=time_index, columns=self.org_mocap_.values.columns)
-
-            new_mocap.values = new_df
-
-            Q.append(new_mocap)
-
-        return Q
-
-
-class RootTransformer(BaseEstimator, TransformerMixin):
-    def __init__(self, method, hips_axis_order="XYZ", position_smoothing=0, rotation_smoothing=0, separate_root=True):
-        """
-        Accepted methods:
-            abdolute_translation_deltas
-            pos_rot_deltas
-        """
-        self.method = method
-        self.position_smoothing = position_smoothing
-        self.rotation_smoothing = rotation_smoothing
-        self.separate_root = separate_root
-        self.hips_axis_order = hips_axis_order
-
-        # relative rotation from the hips awis the the x-side, y-up, z-forward convention
-        rot_mat = np.zeros((3, 3))
-        for i in range(3):
-            ax_i = ord(hips_axis_order[i]) - ord("X")
-            rot_mat[i, ax_i] = 1
-        self.root_rotation_offset = Quaternions.from_transforms(rot_mat[np.newaxis, :, :])
-        self.hips_side_axis = -rot_mat[0, :]
-
-    #        self.hips_forward_axis = ord(hips_forward_axis)-ord('X')
-
-    def fit(self, X, y=None):
-        return self
-
-    def transform(self, X, y=None):
-        print("RootTransformer")
-        Q = []
-
-        for track in X:
-            if self.method == "abdolute_translation_deltas":
-                new_df = track.values.copy()
-                xpcol = "%s_Xposition" % track.root_name
-                ypcol = "%s_Yposition" % track.root_name
-                zpcol = "%s_Zposition" % track.root_name
-
-                dxpcol = "%s_dXposition" % track.root_name
-                dzpcol = "%s_dZposition" % track.root_name
-
-                x = track.values[xpcol].copy()
-                z = track.values[zpcol].copy()
-
-                if self.position_smoothing > 0:
-                    x_sm = filters.gaussian_filter1d(x, self.position_smoothing, axis=0, mode="nearest")
-                    z_sm = filters.gaussian_filter1d(z, self.position_smoothing, axis=0, mode="nearest")
-                    dx = pd.Series(data=x_sm, index=new_df.index).diff()
-                    dz = pd.Series(data=z_sm, index=new_df.index).diff()
-                    new_df[xpcol] = x - x_sm
-                    new_df[zpcol] = z - z_sm
-                else:
-                    dx = x.diff()
-                    dz = z.diff()
-                    new_df.drop([xpcol, zpcol], axis=1, inplace=True)
-
-                dx[0] = dx[1]
-                dz[0] = dz[1]
-
-                new_df[dxpcol] = dx
-                new_df[dzpcol] = dz
-
-                new_track = track.clone()
-                new_track.values = new_df
-            # end of abdolute_translation_deltas
-
-            elif self.method == "pos_rot_deltas":
-                new_track = track.clone()
-
-                # Absolute columns
-                xp_col = "%s_Xposition" % track.root_name
-                yp_col = "%s_Yposition" % track.root_name
-                zp_col = "%s_Zposition" % track.root_name
-
-                # rot_order = track.skeleton[track.root_name]['order']
-                # %(joint, rot_order[0])
-
-                rot_order = track.skeleton[track.root_name]["order"]
-                r1_col = "%s_%srotation" % (track.root_name, rot_order[0])
-                r2_col = "%s_%srotation" % (track.root_name, rot_order[1])
-                r3_col = "%s_%srotation" % (track.root_name, rot_order[2])
-
-                # Delta columns
-                # dxp_col = '%s_dXposition'%track.root_name
-                # dzp_col = '%s_dZposition'%track.root_name
-
-                # dxr_col = '%s_dXrotation'%track.root_name
-                # dyr_col = '%s_dYrotation'%track.root_name
-                # dzr_col = '%s_dZrotation'%track.root_name
-                dxp_col = "reference_dXposition"
-                dzp_col = "reference_dZposition"
-                dxr_col = "reference_dXrotation"
-                dyr_col = "reference_dYrotation"
-                dzr_col = "reference_dZrotation"
-
-                positions = np.transpose(np.array([track.values[xp_col], track.values[yp_col], track.values[zp_col]]))
-                rotations = (
-                    np.pi
-                    / 180.0
-                    * np.transpose(np.array([track.values[r1_col], track.values[r2_col], track.values[r3_col]]))
-                )
-
-                """ Get Trajectory and smooth it"""
-                trajectory_filterwidth = self.position_smoothing
-                reference = positions.copy() * np.array([1, 0, 1])
-                if trajectory_filterwidth > 0:
-                    reference = filters.gaussian_filter1d(reference, trajectory_filterwidth, axis=0, mode="nearest")
-
-                """ Get Root Velocity """
-                velocity = np.diff(reference, axis=0)
-                velocity = np.vstack((velocity[0, :], velocity))
-
-                """ Remove Root Translation """
-                positions = positions - reference
-
-                """ Get Forward Direction along the x-z plane, assuming character is facig z-forward """
-                # forward = [Rotation(f, 'euler', from_deg=True, order=rot_order).rotmat[:,2] for f in rotations] # get the z-axis of the rotation matrix, assuming character is facig z-forward
-                # print("order:" + rot_order.lower())
-                quats = Quaternions.from_euler(rotations, order=rot_order.lower(), world=False)
-                # forward = quats*np.array([[0,0,1]])
-                # forward[:,1] = 0
-                side_dirs = quats * self.hips_side_axis
-                forward = np.cross(np.array([[0, 1, 0]]), side_dirs)
-
-                """ Smooth Forward Direction """
-                direction_filterwidth = self.rotation_smoothing
-                if direction_filterwidth > 0:
-                    forward = filters.gaussian_filter1d(forward, direction_filterwidth, axis=0, mode="nearest")
-
-                forward = forward / np.sqrt((forward**2).sum(axis=-1))[..., np.newaxis]
-
-                """ Remove Y Rotation """
-                target = np.array([[0, 0, 1]]).repeat(len(forward), axis=0)
-                rotation = Quaternions.between(target, forward)[:, np.newaxis]
-                positions = (-rotation[:, 0]) * positions
-                # new_rotations = (-rotation[:,0]) * quats
-                new_rotations = (-self.root_rotation_offset) * (-rotation[:, 0]) * quats
-
-                """ Get Root Rotation """
-                # print(rotation[:,0])
-                velocity = (-rotation[:, 0]) * velocity
-                rvelocity = Pivots.from_quaternions(rotation[1:] * -rotation[:-1]).ps
-                rvelocity = np.vstack((rvelocity[0], rvelocity))
-
-                eulers = (
-                    np.array(
-                        [t3d.euler.quat2euler(q, axes=("s" + rot_order.lower()[::-1]))[::-1] for q in new_rotations]
-                    )
-                    * 180.0
-                    / np.pi
-                )
-
-                new_df = track.values.copy()
-
-                root_pos_x = pd.Series(data=positions[:, 0], index=new_df.index)
-                root_pos_y = pd.Series(data=positions[:, 1], index=new_df.index)
-                root_pos_z = pd.Series(data=positions[:, 2], index=new_df.index)
-                root_pos_x_diff = pd.Series(data=velocity[:, 0], index=new_df.index)
-                root_pos_z_diff = pd.Series(data=velocity[:, 2], index=new_df.index)
-
-                root_rot_1 = pd.Series(data=eulers[:, 0], index=new_df.index)
-                root_rot_2 = pd.Series(data=eulers[:, 1], index=new_df.index)
-                root_rot_3 = pd.Series(data=eulers[:, 2], index=new_df.index)
-                root_rot_y_diff = pd.Series(data=rvelocity[:, 0], index=new_df.index)
-
-                # new_df.drop([xr_col, yr_col, zr_col, xp_col, zp_col], axis=1, inplace=True)
-
-                new_df[xp_col] = root_pos_x
-                new_df[yp_col] = root_pos_y
-                new_df[zp_col] = root_pos_z
-                new_df[dxp_col] = root_pos_x_diff
-                new_df[dzp_col] = root_pos_z_diff
-
-                new_df[r1_col] = root_rot_1
-                new_df[r2_col] = root_rot_2
-                new_df[r3_col] = root_rot_3
-                # new_df[dxr_col] = root_rot_x_diff
-                new_df[dyr_col] = root_rot_y_diff
-                # new_df[dzr_col] = root_rot_z_diff
-
-                new_track.values = new_df
-            elif self.method == "pos_xyz_rot_deltas":
-                new_track = track.clone()
-
-                # Absolute columns
-                xp_col = "%s_Xposition" % track.root_name
-                yp_col = "%s_Yposition" % track.root_name
-                zp_col = "%s_Zposition" % track.root_name
-
-                # rot_order = track.skeleton[track.root_name]['order']
-                # %(joint, rot_order[0])
-
-                rot_order = track.skeleton[track.root_name]["order"]
-                r1_col = "%s_%srotation" % (track.root_name, rot_order[0])
-                r2_col = "%s_%srotation" % (track.root_name, rot_order[1])
-                r3_col = "%s_%srotation" % (track.root_name, rot_order[2])
-
-                # Delta columns
-                # dxp_col = '%s_dXposition'%track.root_name
-                # dzp_col = '%s_dZposition'%track.root_name
-
-                # dxr_col = '%s_dXrotation'%track.root_name
-                # dyr_col = '%s_dYrotation'%track.root_name
-                # dzr_col = '%s_dZrotation'%track.root_name
-                dxp_col = "reference_dXposition"
-                dyp_col = "reference_dYposition"
-                dzp_col = "reference_dZposition"
-                dxr_col = "reference_dXrotation"
-                dyr_col = "reference_dYrotation"
-                dzr_col = "reference_dZrotation"
-
-                positions = np.transpose(np.array([track.values[xp_col], track.values[yp_col], track.values[zp_col]]))
-                rotations = (
-                    np.pi
-                    / 180.0
-                    * np.transpose(np.array([track.values[r1_col], track.values[r2_col], track.values[r3_col]]))
-                )
-
-                """ Get Trajectory and smooth it"""
-                trajectory_filterwidth = self.position_smoothing
-                # reference = positions.copy()*np.array([1,0,1])
-                if trajectory_filterwidth > 0:
-                    reference = filters.gaussian_filter1d(positions, trajectory_filterwidth, axis=0, mode="nearest")
-
-                """ Get Root Velocity """
-                velocity = np.diff(reference, axis=0)
-                velocity = np.vstack((velocity[0, :], velocity))
-
-                """ Remove Root Translation """
-                positions = positions - reference
-
-                """ Get Forward Direction along the x-z plane, assuming character is facig z-forward """
-                # forward = [Rotation(f, 'euler', from_deg=True, order=rot_order).rotmat[:,2] for f in rotations] # get the z-axis of the rotation matrix, assuming character is facig z-forward
-                # print("order:" + rot_order.lower())
-                quats = Quaternions.from_euler(rotations, order=rot_order.lower(), world=False)
-
-                # calculate the hips forward directions given in global cordinates
-                # side_ax = np.zeros((1,3))
-                # side_ax[0,self.hips_side_axis]=1
-                # side_dirs = quats*side_ax
-                side_dirs = quats * self.hips_side_axis
-                forward = np.cross(np.array([[0, 1, 0]]), side_dirs)
-
-                """ Smooth Forward Direction """
-                direction_filterwidth = self.rotation_smoothing
-                if direction_filterwidth > 0:
-                    forward = filters.gaussian_filter1d(forward, direction_filterwidth, axis=0, mode="nearest")
-
-                # make unit vector
-                forward = forward / np.sqrt((forward**2).sum(axis=-1))[..., np.newaxis]
-
-                """ Remove Y Rotation """
-                target = np.array([[0, 0, 1]]).repeat(len(forward), axis=0)
-                rotation = Quaternions.between(target, forward)[:, np.newaxis]
-                positions = (-rotation[:, 0]) * positions
-                new_rotations = (-self.root_rotation_offset) * (-rotation[:, 0]) * quats
-
-                """ Get Root Rotation """
-                # print(rotation[:,0])
-                velocity = (-rotation[:, 0]) * velocity
-                rvelocity = Pivots.from_quaternions(rotation[1:] * -rotation[:-1]).ps
-                rvelocity = np.vstack((rvelocity[0], rvelocity))
-
-                eulers = (
-                    np.array(
-                        [t3d.euler.quat2euler(q, axes=("s" + rot_order.lower()[::-1]))[::-1] for q in new_rotations]
-                    )
-                    * 180.0
-                    / np.pi
-                )
-
-                new_df = track.values.copy()
-
-                root_pos_x = pd.Series(data=positions[:, 0], index=new_df.index)
-                root_pos_y = pd.Series(data=positions[:, 1], index=new_df.index)
-                root_pos_z = pd.Series(data=positions[:, 2], index=new_df.index)
-                root_pos_x_diff = pd.Series(data=velocity[:, 0], index=new_df.index)
-                root_pos_y_diff = pd.Series(data=velocity[:, 1], index=new_df.index)
-                root_pos_z_diff = pd.Series(data=velocity[:, 2], index=new_df.index)
-
-                root_rot_1 = pd.Series(data=eulers[:, 0], index=new_df.index)
-                root_rot_2 = pd.Series(data=eulers[:, 1], index=new_df.index)
-                root_rot_3 = pd.Series(data=eulers[:, 2], index=new_df.index)
-                root_rot_y_diff = pd.Series(data=rvelocity[:, 0], index=new_df.index)
-
-                # new_df.drop([xr_col, yr_col, zr_col, xp_col, zp_col], axis=1, inplace=True)
-
-                new_df[xp_col] = root_pos_x
-                new_df[yp_col] = root_pos_y
-                new_df[zp_col] = root_pos_z
-                new_df[dxp_col] = root_pos_x_diff
-                new_df[dyp_col] = root_pos_y_diff
-                new_df[dzp_col] = root_pos_z_diff
-
-                new_df[r1_col] = root_rot_1
-                new_df[r2_col] = root_rot_2
-                new_df[r3_col] = root_rot_3
-                # new_df[dxr_col] = root_rot_x_diff
-                new_df[dyr_col] = root_rot_y_diff
-                # new_df[dzr_col] = root_rot_z_diff
-
-                new_track.values = new_df
-
-            elif self.method == "hip_centric":
-                new_track = track.clone()
-
-                # Absolute columns
-                xp_col = "%s_Xposition" % track.root_name
-                yp_col = "%s_Yposition" % track.root_name
-                zp_col = "%s_Zposition" % track.root_name
-
-                xr_col = "%s_Xrotation" % track.root_name
-                yr_col = "%s_Yrotation" % track.root_name
-                zr_col = "%s_Zrotation" % track.root_name
-
-                new_df = track.values.copy()
-
-                all_zeros = np.zeros(track.values[xp_col].values.shape)
-
-                new_df[xp_col] = pd.Series(data=all_zeros, index=new_df.index)
-                new_df[yp_col] = pd.Series(data=all_zeros, index=new_df.index)
-                new_df[zp_col] = pd.Series(data=all_zeros, index=new_df.index)
-
-                new_df[xr_col] = pd.Series(data=all_zeros, index=new_df.index)
-                new_df[yr_col] = pd.Series(data=all_zeros, index=new_df.index)
-                new_df[zr_col] = pd.Series(data=all_zeros, index=new_df.index)
-
-                new_track.values = new_df
-
-            # print(new_track.values.columns)
-            Q.append(new_track)
-
-        return Q
-
-    def inverse_transform(self, X, copy=None, start_pos=None):
-        Q = []
-
-        # TODO: simplify this implementation
-
-        startx = 0
-        startz = 0
-
-        if start_pos is not None:
-            startx, startz = start_pos
-
-        for track in X:
-            new_track = track.clone()
-            if self.method == "abdolute_translation_deltas":
-                new_df = new_track.values
-                xpcol = "%s_Xposition" % track.root_name
-                ypcol = "%s_Yposition" % track.root_name
-                zpcol = "%s_Zposition" % track.root_name
-
-                dxpcol = "%s_dXposition" % track.root_name
-                dzpcol = "%s_dZposition" % track.root_name
-
-                dx = track.values[dxpcol].values
-                dz = track.values[dzpcol].values
-
-                recx = [startx]
-                recz = [startz]
-
-                for i in range(dx.shape[0] - 1):
-                    recx.append(recx[i] + dx[i + 1])
-                    recz.append(recz[i] + dz[i + 1])
-
-                # recx = [recx[i]+dx[i+1] for i in range(dx.shape[0]-1)]
-                # recz = [recz[i]+dz[i+1] for i in range(dz.shape[0]-1)]
-                # recx = dx[:-1] + dx[1:]
-                # recz = dz[:-1] + dz[1:]
-                if self.position_smoothing > 0:
-                    new_df[xpcol] = pd.Series(data=new_df[xpcol] + recx, index=new_df.index)
-                    new_df[zpcol] = pd.Series(data=new_df[zpcol] + recz, index=new_df.index)
-                else:
-                    new_df[xpcol] = pd.Series(data=recx, index=new_df.index)
-                    new_df[zpcol] = pd.Series(data=recz, index=new_df.index)
-
-                new_df.drop([dxpcol, dzpcol], axis=1, inplace=True)
-
-                new_track.values = new_df
-            # end of abdolute_translation_deltas
-
-            elif self.method == "pos_rot_deltas":
-                # Absolute columns
-                rot_order = track.skeleton[track.root_name]["order"]
-                xp_col = "%s_Xposition" % track.root_name
-                yp_col = "%s_Yposition" % track.root_name
-                zp_col = "%s_Zposition" % track.root_name
-
-                xr_col = "%s_Xrotation" % track.root_name
-                yr_col = "%s_Yrotation" % track.root_name
-                zr_col = "%s_Zrotation" % track.root_name
-                r1_col = "%s_%srotation" % (track.root_name, rot_order[0])
-                r2_col = "%s_%srotation" % (track.root_name, rot_order[1])
-                r3_col = "%s_%srotation" % (track.root_name, rot_order[2])
-
-                # Delta columns
-                # dxp_col = '%s_dXposition'%track.root_name
-                # dzp_col = '%s_dZposition'%track.root_name
-                # dyr_col = '%s_dYrotation'%track.root_name
-                dxp_col = "reference_dXposition"
-                dzp_col = "reference_dZposition"
-                dyr_col = "reference_dYrotation"
-
-                positions = np.transpose(np.array([track.values[xp_col], track.values[yp_col], track.values[zp_col]]))
-                rotations = (
-                    np.pi
-                    / 180.0
-                    * np.transpose(np.array([track.values[r1_col], track.values[r2_col], track.values[r3_col]]))
-                )
-                quats = Quaternions.from_euler(rotations, order=rot_order.lower(), world=False)
-
-                new_df = track.values.copy()
-
-                dx = track.values[dxp_col].values
-                dz = track.values[dzp_col].values
-
-                dry = track.values[dyr_col].values
-
-                # rec_p = np.array([startx, 0, startz])+positions[0,:]
-                rec_ry = Quaternions.id(quats.shape[0])
-                rec_xp = [0]
-                rec_zp = [0]
-
-                # rec_r = Quaternions.id(quats.shape[0])
-
-                for i in range(dx.shape[0] - 1):
-                    # print(dry[i])
-                    q_y = Quaternions.from_angle_axis(np.array(dry[i + 1]), np.array([0, 1, 0]))
-                    rec_ry[i + 1] = q_y * rec_ry[i]
-                    # print("dx: + " + str(dx[i+1]))
-                    dp = rec_ry[i + 1] * np.array([dx[i + 1], 0, dz[i + 1]])
-                    rec_xp.append(rec_xp[i] + dp[0, 0])
-                    rec_zp.append(rec_zp[i] + dp[0, 2])
-
-                if self.separate_root:
-                    qq = quats
-                    xx = positions[:, 0]
-                    zz = positions[:, 2]
-                else:
-                    qq = rec_ry * self.root_rotation_offset * quats
-                    pp = rec_ry * positions
-                    xx = rec_xp + pp[:, 0]
-                    zz = rec_zp + pp[:, 2]
-
-                eulers = (
-                    np.array([t3d.euler.quat2euler(q, axes=("s" + rot_order.lower()[::-1]))[::-1] for q in qq])
-                    * 180.0
-                    / np.pi
-                )
-
-                new_df = track.values.copy()
-
-                root_rot_1 = pd.Series(data=eulers[:, 0], index=new_df.index)
-                root_rot_2 = pd.Series(data=eulers[:, 1], index=new_df.index)
-                root_rot_3 = pd.Series(data=eulers[:, 2], index=new_df.index)
-
-                new_df[xp_col] = pd.Series(data=xx, index=new_df.index)
-                new_df[zp_col] = pd.Series(data=zz, index=new_df.index)
-
-                new_df[r1_col] = pd.Series(data=root_rot_1, index=new_df.index)
-                new_df[r2_col] = pd.Series(data=root_rot_2, index=new_df.index)
-                new_df[r3_col] = pd.Series(data=root_rot_3, index=new_df.index)
-
-                if self.separate_root:
-                    new_df["reference_Xposition"] = pd.Series(data=rec_xp, index=new_df.index)
-                    new_df["reference_Zposition"] = pd.Series(data=rec_zp, index=new_df.index)
-                    eulers_ry = (
-                        np.array([t3d.euler.quat2euler(q, axes=("s" + rot_order.lower()[::-1]))[::-1] for q in rec_ry])
-                        * 180.0
-                        / np.pi
-                    )
-                    new_df["reference_Yrotation"] = pd.Series(
-                        data=eulers_ry[:, rot_order.find("Y")], index=new_df.index
-                    )
-
-                new_df.drop([dyr_col, dxp_col, dzp_col], axis=1, inplace=True)
-
-                new_track.values = new_df
-
-            elif self.method == "pos_xyz_rot_deltas":
-                # Absolute columns
-                rot_order = track.skeleton[track.root_name]["order"]
-                xp_col = "%s_Xposition" % track.root_name
-                yp_col = "%s_Yposition" % track.root_name
-                zp_col = "%s_Zposition" % track.root_name
-
-                xr_col = "%s_Xrotation" % track.root_name
-                yr_col = "%s_Yrotation" % track.root_name
-                zr_col = "%s_Zrotation" % track.root_name
-                r1_col = "%s_%srotation" % (track.root_name, rot_order[0])
-                r2_col = "%s_%srotation" % (track.root_name, rot_order[1])
-                r3_col = "%s_%srotation" % (track.root_name, rot_order[2])
-
-                # Delta columns
-                # dxp_col = '%s_dXposition'%track.root_name
-                # dzp_col = '%s_dZposition'%track.root_name
-                # dyr_col = '%s_dYrotation'%track.root_name
-                dxp_col = "reference_dXposition"
-                dyp_col = "reference_dYposition"
-                dzp_col = "reference_dZposition"
-                dyr_col = "reference_dYrotation"
-
-                positions = np.transpose(np.array([track.values[xp_col], track.values[yp_col], track.values[zp_col]]))
-                rotations = (
-                    np.pi
-                    / 180.0
-                    * np.transpose(np.array([track.values[r1_col], track.values[r2_col], track.values[r3_col]]))
-                )
-                quats = Quaternions.from_euler(rotations, order=rot_order.lower(), world=False)
-
-                new_df = track.values.copy()
-
-                dx = track.values[dxp_col].values
-                dy = track.values[dyp_col].values
-                dz = track.values[dzp_col].values
-
-                dry = track.values[dyr_col].values
-
-                # rec_p = np.array([startx, 0, startz])+positions[0,:]
-                rec_ry = Quaternions.id(quats.shape[0])
-                rec_xp = [0]
-                rec_yp = [0]
-                rec_zp = [0]
-
-                # rec_r = Quaternions.id(quats.shape[0])
-
-                for i in range(dx.shape[0] - 1):
-                    # print(dry[i])
-                    q_y = Quaternions.from_angle_axis(np.array(dry[i + 1]), np.array([0, 1, 0]))
-                    rec_ry[i + 1] = q_y * rec_ry[i]
-                    # print("dx: + " + str(dx[i+1]))
-                    dp = rec_ry[i + 1] * np.array([dx[i + 1], dy[i + 1], dz[i + 1]])
-                    rec_xp.append(rec_xp[i] + dp[0, 0])
-                    rec_yp.append(rec_yp[i] + dp[0, 1])
-                    rec_zp.append(rec_zp[i] + dp[0, 2])
-
-                if self.separate_root:
-                    qq = quats
-                    xx = positions[:, 0]
-                    yy = positions[:, 1]
-                    zz = positions[:, 2]
-                else:
-                    qq = rec_ry * self.root_rotation_offset * quats
-                    pp = rec_ry * positions
-                    xx = rec_xp + pp[:, 0]
-                    yy = rec_yp + pp[:, 1]
-                    zz = rec_zp + pp[:, 2]
-
-                eulers = (
-                    np.array([t3d.euler.quat2euler(q, axes=("s" + rot_order.lower()[::-1]))[::-1] for q in qq])
-                    * 180.0
-                    / np.pi
-                )
-
-                new_df = track.values.copy()
-
-                root_rot_1 = pd.Series(data=eulers[:, 0], index=new_df.index)
-                root_rot_2 = pd.Series(data=eulers[:, 1], index=new_df.index)
-                root_rot_3 = pd.Series(data=eulers[:, 2], index=new_df.index)
-
-                new_df[xp_col] = pd.Series(data=xx, index=new_df.index)
-                new_df[yp_col] = pd.Series(data=yy, index=new_df.index)
-                new_df[zp_col] = pd.Series(data=zz, index=new_df.index)
-
-                new_df[r1_col] = pd.Series(data=root_rot_1, index=new_df.index)
-                new_df[r2_col] = pd.Series(data=root_rot_2, index=new_df.index)
-                new_df[r3_col] = pd.Series(data=root_rot_3, index=new_df.index)
-
-                if self.separate_root:
-                    new_df["reference_Xposition"] = pd.Series(data=rec_xp, index=new_df.index)
-                    new_df["reference_Yposition"] = pd.Series(data=rec_yp, index=new_df.index)
-                    new_df["reference_Zposition"] = pd.Series(data=rec_zp, index=new_df.index)
-                    eulers_ry = (
-                        np.array([t3d.euler.quat2euler(q, axes=("s" + rot_order.lower()[::-1]))[::-1] for q in rec_ry])
-                        * 180.0
-                        / np.pi
-                    )
-                    new_df["reference_Yrotation"] = pd.Series(
-                        data=eulers_ry[:, rot_order.find("Y")], index=new_df.index
-                    )
-
-                new_df.drop([dyr_col, dxp_col, dyp_col, dzp_col], axis=1, inplace=True)
-
-                new_track.values = new_df
-
-            # print(new_track.values.columns)
-            Q.append(new_track)
-
-        return Q
-
-
-class RootCentricPositionNormalizer(BaseEstimator, TransformerMixin):
-    def __init__(self):
-        pass
-
-    def fit(self, X, y=None):
-        return self
-
-    def transform(self, X, y=None):
-        Q = []
-
-        for track in X:
-            new_track = track.clone()
-
-            rxp = "%s_Xposition" % track.root_name
-            ryp = "%s_Yposition" % track.root_name
-            rzp = "%s_Zposition" % track.root_name
-
-            projected_root_pos = track.values[[rxp, ryp, rzp]]
-
-            projected_root_pos.loc[:, ryp] = 0  # we want the root's projection on the floor plane as the ref
-
-            new_df = pd.DataFrame(index=track.values.index)
-
-            all_but_root = [joint for joint in track.skeleton if track.root_name not in joint]
-            # all_but_root = [joint for joint in track.skeleton]
-            for joint in all_but_root:
-                new_df["%s_Xposition" % joint] = pd.Series(
-                    data=track.values["%s_Xposition" % joint] - projected_root_pos[rxp], index=new_df.index
-                )
-                new_df["%s_Yposition" % joint] = pd.Series(
-                    data=track.values["%s_Yposition" % joint] - projected_root_pos[ryp], index=new_df.index
-                )
-                new_df["%s_Zposition" % joint] = pd.Series(
-                    data=track.values["%s_Zposition" % joint] - projected_root_pos[rzp], index=new_df.index
-                )
-
-            # keep the root as it is now
-            new_df[rxp] = track.values[rxp]
-            new_df[ryp] = track.values[ryp]
-            new_df[rzp] = track.values[rzp]
-
-            new_track.values = new_df
-
-            Q.append(new_track)
-
-        return Q
-
-    def inverse_transform(self, X, copy=None):
-        Q = []
-
-        for track in X:
-            new_track = track.clone()
-
-            rxp = "%s_Xposition" % track.root_name
-            ryp = "%s_Yposition" % track.root_name
-            rzp = "%s_Zposition" % track.root_name
-
-            projected_root_pos = track.values[[rxp, ryp, rzp]]
-
-            projected_root_pos.loc[:, ryp] = 0  # we want the root's projection on the floor plane as the ref
-
-            new_df = pd.DataFrame(index=track.values.index)
-
-            for joint in track.skeleton:
-                new_df["%s_Xposition" % joint] = pd.Series(
-                    data=track.values["%s_Xposition" % joint] + projected_root_pos[rxp], index=new_df.index
-                )
-                new_df["%s_Yposition" % joint] = pd.Series(
-                    data=track.values["%s_Yposition" % joint] + projected_root_pos[ryp], index=new_df.index
-                )
-                new_df["%s_Zposition" % joint] = pd.Series(
-                    data=track.values["%s_Zposition" % joint] + projected_root_pos[rzp], index=new_df.index
-                )
-
-            new_track.values = new_df
-
-            Q.append(new_track)
-
-        return Q
-
-
-class Flattener(BaseEstimator, TransformerMixin):
-    def __init__(self):
-        pass
-
-    def fit(self, X, y=None):
-        return self
-
-    def transform(self, X, y=None):
-        return np.concatenate(X, axis=0)
-
-
-class ConstantsRemover(BaseEstimator, TransformerMixin):
-    """
-    For now it just looks at the first track
-    """
-
-    def __init__(self, eps=1e-6):
-        self.eps = eps
-
-    def fit(self, X, y=None):
-        stds = X[0].values.std()
-        cols = X[0].values.columns.values
-        self.const_dims_ = [c for c in cols if (stds[c] < self.eps).any()]
-        self.const_values_ = {c: X[0].values[c].values[0] for c in cols if (stds[c] < self.eps).any()}
-        return self
-
-    def transform(self, X, y=None):
-        Q = []
-
-        for track in X:
-            t2 = track.clone()
-            # for key in t2.skeleton.keys():
-            #    if key in self.ConstDims_:
-            #        t2.skeleton.pop(key)
-            # print(track.values.columns.difference(self.const_dims_))
-            t2.values.drop(self.const_dims_, axis=1, inplace=True)
-            # t2.values = track.values[track.values.columns.difference(self.const_dims_)]
-            Q.append(t2)
-
-        return Q
-
-    def inverse_transform(self, X, copy=None):
-        Q = []
-
-        for track in X:
-            t2 = track.clone()
-            for d in self.const_dims_:
-                t2.values[d] = self.const_values_[d]
-            #                t2.values.assign(d=pd.Series(data=self.const_values_[d], index = t2.values.index))
-            Q.append(t2)
-
-        return Q
-
-
-class ListStandardScaler(BaseEstimator, TransformerMixin):
-    def __init__(self, is_DataFrame=False):
-        self.is_DataFrame = is_DataFrame
-
-    def fit(self, X, y=None):
-        if self.is_DataFrame:
-            X_train_flat = np.concatenate([m.values for m in X], axis=0)
-        else:
-            X_train_flat = np.concatenate([m for m in X], axis=0)
-
-        self.data_mean_ = np.mean(X_train_flat, axis=0)
-        self.data_std_ = np.std(X_train_flat, axis=0)
-
-        return self
-
-    def transform(self, X, y=None):
-        Q = []
-
-        for track in X:
-            if self.is_DataFrame:
-                normalized_track = track.copy()
-                normalized_track.values = (track.values - self.data_mean_) / self.data_std_
-            else:
-                normalized_track = (track - self.data_mean_) / self.data_std_
-
-            Q.append(normalized_track)
-
-        if self.is_DataFrame:
-            return Q
-        else:
-            return np.array(Q)
-
-    def inverse_transform(self, X, copy=None):
-        Q = []
-
-        for track in X:
-            if self.is_DataFrame:
-                unnormalized_track = track.copy()
-                unnormalized_track.values = (track.values * self.data_std_) + self.data_mean_
-            else:
-                unnormalized_track = (track * self.data_std_) + self.data_mean_
-
-            Q.append(unnormalized_track)
-
-        if self.is_DataFrame:
-            return Q
-        else:
-            return np.array(Q)
-
-
-class ListMinMaxScaler(BaseEstimator, TransformerMixin):
-    def __init__(self, is_DataFrame=False):
-        self.is_DataFrame = is_DataFrame
-
-    def fit(self, X, y=None):
-        if self.is_DataFrame:
-            X_train_flat = np.concatenate([m.values for m in X], axis=0)
-        else:
-            X_train_flat = np.concatenate([m for m in X], axis=0)
-
-        self.data_max_ = np.max(X_train_flat, axis=0)
-        self.data_min_ = np.min(X_train_flat, axis=0)
-
-        return self
-
-    def transform(self, X, y=None):
-        Q = []
-
-        for track in X:
-            if self.is_DataFrame:
-                normalized_track = track.copy()
-                normalized_track.values = (track.values - self.data_min_) / (self.data_max_ - self.data_min_)
-            else:
-                normalized_track = (track - self.data_min_) / (self.data_max_ - self.data_min_)
-
-            Q.append(normalized_track)
-
-        if self.is_DataFrame:
-            return Q
-        else:
-            return np.array(Q)
-
-    def inverse_transform(self, X, copy=None):
-        Q = []
-
-        for track in X:
-            if self.is_DataFrame:
-                unnormalized_track = track.copy()
-                unnormalized_track.values = (track.values * (self.data_max_ - self.data_min_)) + self.data_min_
-            else:
-                unnormalized_track = (track * (self.data_max_ - self.data_min_)) + self.data_min_
-
-            Q.append(unnormalized_track)
-
-        if self.is_DataFrame:
-            return Q
-        else:
-            return np.array(Q)
-
-
-class Resampler(BaseEstimator, TransformerMixin):
-    def __init__(self, fps, method="cubic"):
-        """
-        Method to resample a pandas dataframe to a different framerate.
-        NOTE: Pandas resampling is quit unintuitive when resampling to odd framerates using interpolation.
-        Thus we do it in this complex way.
-        """
-        self.tgt_frametime = 1.0 / fps
-        self.method = method
-
-    def fit(self, X, y=None):
-        print("Resampling to tgt_frametime: " + str(self.tgt_frametime))
-        self.orig_frametime = X[0].framerate
-        return self
-
-    def resample_dataframe(self, df, frametime, method="cubic"):
-        # Create a time index for the resampled data
-        rate = str(round(1.0e9 * frametime)) + "N"
-        time_index = df.resample(rate).indices
-
-        # reindex the old data. This will turn all non-matching indices to NAN
-        tmp = df.reindex(time_index)
-
-        # merge with the old data and sort
-        tmp = pd.concat([df, tmp]).sort_index()
-
-        # remove duplicate time indices. Then fill the NAN values using interpolation
-        tmp = tmp[~tmp.index.duplicated(keep="first")].interpolate(method=method)
-
-        # return the values using the resampled indices
-        return tmp.loc[list(time_index)]
-
-    def resample_poly_df(self, df, new_frametime, old_frametime):
-        old_fps = round(1 / old_frametime)
-        new_fps = round(1 / new_frametime)
-        lcm = np.lcm(old_fps, new_fps)
-        up = lcm // old_fps
-        down = lcm // new_fps
-        new_vals = signal.resample_poly(df.values, up, down)
-        time_index = pd.to_timedelta([f for f in range(new_vals.shape[0])], unit="s") * new_frametime
-        new_df = pd.DataFrame(data=new_vals, index=time_index, columns=df.columns)
-        return new_df
-
-    def transform(self, X, y=None):
-        Q = []
-
-        for track in X:
-            new_track = track.clone()
-            # new_track.values = self.resample_dataframe(track.values, self.tgt_frametime, method=self.method)
-            new_track.values = self.resample_poly_df(track.values, self.tgt_frametime, track.framerate)
-            new_track.framerate = self.tgt_frametime
-            Q.append(new_track)
-
-        return Q
-
-    def inverse_transform(self, X, copy=None):
-        Q = []
-
-        for track in X:
-            new_track = track.clone()
-            # new_track.values = self.resample_dataframe(track.values, self.orig_frametime, method=self.method)
-            new_track.values = self.resample_poly_df(track.values, self.orig_frametime, track.framerate)
-            new_track.framerate = self.orig_frametime
-            Q.append(new_track)
-
-        return Q
-
-
-class DownSampler(BaseEstimator, TransformerMixin):
-    def __init__(self, tgt_fps, keep_all=False):
-        self.tgt_fps = tgt_fps
-        self.keep_all = keep_all
-
-    def fit(self, X, y=None):
-        return self
-
-    def transform(self, X, y=None):
-        Q = []
-
-        for track in X:
-            orig_fps = round(1.0 / track.framerate)
-            rate = orig_fps // self.tgt_fps
-            if orig_fps % self.tgt_fps != 0:
-                print(
-                    "error orig_fps (" + str(orig_fps) + ") is not dividable with tgt_fps (" + str(self.tgt_fps) + ")"
-                )
-            else:
-                print("downsampling with rate: " + str(rate))
-
-            # print(track.values.size)
-            for ii in range(0, rate):
-                new_track = track.clone()
-                if self.keep_all:
-                    new_track.take_name = new_track.take_name + "_" + str(ii).zfill(2)
-                new_track.values = track.values[ii:-1:rate].copy()
-                # print(new_track.values.size)
-                # new_track = track[0:-1:self.rate]
-                new_track.framerate = 1.0 / self.tgt_fps
-                Q.append(new_track)
-                if not self.keep_all:
-                    break
-
-        return Q
-
-    def inverse_transform(self, X, copy=None):
-        return X
-
-
-class ReverseTime(BaseEstimator, TransformerMixin):
-    def __init__(self, append=True):
-        self.append = append
-
-    def fit(self, X, y=None):
-        return self
-
-    def transform(self, X, y=None):
-        print("ReverseTime")
-        Q = []
-        if self.append:
-            for track in X:
-                Q.append(track)
-        for track in X:
-            new_track = track.clone()
-            new_track.values = track.values[-1::-1]
-            new_track.values.index = new_track.values.index[0] - new_track.values.index
-            Q.append(new_track)
-
-        return Q
-
-    def inverse_transform(self, X, copy=None):
-        return X
-
-
-class ListFeatureUnion(BaseEstimator, TransformerMixin):
-    def __init__(self, processors):
-        self.processors = processors
-
-    def fit(self, X, y=None):
-        assert y is None
-        for proc in self.processors:
-            if isinstance(proc, Pipeline):
-                # Loop steps and run fit on each. This is necessary since
-                # running fit on a Pipeline runs fit_transform on all steps
-                # and not only fit.
-                for step in proc.steps:
-                    step[1].fit(X)
-            else:
-                proc.fit(X)
-        return self
-
-    def transform(self, X, y=None):
-        assert y is None
-        print("ListFeatureUnion")
-
-        Q = []
-
-        idx = 0
-        for proc in self.processors:
-            Z = proc.transform(X)
-            if idx == 0:
-                Q = Z
-            else:
-                assert len(Q) == len(Z)
-                for idx2, track in enumerate(Z):
-                    Q[idx2].values = pd.concat([Q[idx2].values, Z[idx2].values], axis=1)
-            idx += 1
-
-        return Q
-
-    def inverse_transform(self, X, y=None):
-        return X
-
-
-class RollingStatsCalculator(BaseEstimator, TransformerMixin):
-    """
-    Creates a causal mean and std filter with a rolling window of length win (based on using prev and current values)
-    """
-
-    def __init__(self, win):
-        self.win = win
-
-    def fit(self, X, y=None):
-        return self
-
-    def transform(self, X, y=None):
-        print("RollingStatsCalculator: " + str(self.win))
-
-        Q = []
-        for track in X:
-            new_track = track.clone()
-            mean_df = track.values.rolling(window=self.win).mean()
-            std_df = track.values.rolling(window=self.win).std()
-            # rolling.mean results in Nans in start seq. Here we fill these
-            win = min(self.win, new_track.values.shape[0])
-            for i in range(1, win):
-                mm = track.values[:i].rolling(window=i).mean()
-                ss = track.values[:i].rolling(window=i).std()
-                mean_df.iloc[i - 1] = mm.iloc[i - 1]
-                std_df.iloc[i - 1] = ss.iloc[i - 1]
-
-            std_df.iloc[0] = std_df.iloc[1]
-            # Append to
-            new_track.values = pd.concat([mean_df.add_suffix("_mean"), std_df.add_suffix("_std")], axis=1)
-            Q.append(new_track)
-        return Q
-
-    def inverse_transform(self, X, copy=None):
-        return X
-
-
-class FeatureCounter(BaseEstimator, TransformerMixin):
-    def __init__(self):
-        pass
-
-    def fit(self, X, y=None):
-        self.n_features = len(X[0].values.columns)
-
-        return self
-
-    def transform(self, X, y=None):
-        return X
-
-    def inverse_transform(self, X, copy=None):
-        return X
-
-
-# TODO: JointsSelector (x)
-# TODO: SegmentMaker
-# TODO: DynamicFeaturesAdder
-# TODO: ShapeFeaturesAdder
-# TODO: DataFrameNumpier (x)
-
-
-class TemplateTransform(BaseEstimator, TransformerMixin):
-    def __init__(self):
-        pass
-
-    def fit(self, X, y=None):
-        return self
-
-    def transform(self, X, y=None):
-        return X
diff --git a/spaces/simple0urra/skops-model-card-creator-2a23515a-d54e-4804-b365-27ed6e938735/example/Get Ready for Accounting Exams Download Pink Randall PDF and Practice with Exercises and Questions.md b/spaces/simple0urra/skops-model-card-creator-2a23515a-d54e-4804-b365-27ed6e938735/example/Get Ready for Accounting Exams Download Pink Randall PDF and Practice with Exercises and Questions.md
deleted file mode 100644
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--- a/spaces/simple0urra/skops-model-card-creator-2a23515a-d54e-4804-b365-27ed6e938735/example/Get Ready for Accounting Exams Download Pink Randall PDF and Practice with Exercises and Questions.md	
+++ /dev/null
@@ -1,137 +0,0 @@
-
-<h1>Introduction</h1>
-<p>If you are looking for a comprehensive and reliable source of accounting knowledge, you might have heard of <strong>pink randall pdf</strong>. This is a popular name for a series of books on accounting written by Harold Randall, a British author and educator. The books cover various levels of accounting, from AS Level to Advanced Level, and are widely used by students and teachers around the world.</p>
-<h2>download pink randall pdf</h2><br /><p><b><b>Download</b> &#10002; <a href="https://ssurll.com/2uNZzY">https://ssurll.com/2uNZzY</a></b></p><br /><br />
-<p>But why is it called <em>pink</em> randall pdf? Well, this is because some editions of the books have a distinctive pink cover, which makes them easy to recognize. However, not all editions have this color scheme, so don't be confused if you see different versions online.</p>
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- <table>
-<tr>
-<th>Edition/Level</th>
-<th>Main Topics</th>
-</tr>
-<tr>
-<td>Advanced Level Accounting</td>
-<td>- Accounting principles and concepts<br>- Financial statements and analysis<br>- Cost and management accounting<br>- Budgeting and variance analysis<br>- Capital investment appraisal<br>- Accounting for partnerships and limited companies<br>- Accounting standards and regulations<br>- Auditing and assurance</td>
-</tr>
-<tr>
-<td>Accounting A Level and AS Level</td>
-<td>- Introduction to accounting<br>- Double-entry bookkeeping<br>- Trial balance and errors<br>- Bank reconciliation<br>- Control accounts<br>- Depreciation and disposal of assets<br>- Inventory valuation<br>- Accruals and prepayments<br>- Income statements and balance sheets<br>- Cash flow statements<br>- Ratio analysis<br>- Incomplete records<br>- Non-profit organizations</td>
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-<tr>
-<td>'A' Level Accounting</td>
-<td>- The accounting equation and the balance sheet<br>- The double entry system for assets, liabilities and capital<br>- Inventory<br>- The effect of profit or loss on capital and the double entry system for expenses and revenues<br>- Balancing off accounts<br>- The trial balance<br>- Income statements<br>- Statements of financial position (balance sheets)<br>- Accounting concepts and assumptions<br>- Capital and revenue expenditure and receipts<br>- Accounting for depreciation and disposal of non-current assets<br>- Bank reconciliation statements<br>- Correction of errors and suspense accounts<br>- Control accounts for receivables and payables<br>- Accounting for payroll</td>
-</tr>
-</table>
- <p>You can use this table as a guide to find the topics that you need to learn or review. You can also compare the topics across different editions and levels to see how they differ or overlap. You should also check the syllabus or curriculum of your course or exam to see what topics are required or optional.</p>
- <h2>How to practice accounting problems and exercises?</h2>
-<p>One of the best ways to learn accounting is to practice accounting problems and exercises. Pink randall pdf provides plenty of problems and exercises at the end of each chapter or section. These problems and exercises are designed to test your knowledge, skills, and understanding of the topics covered in the book. They also help you apply what you learn to real-life scenarios and situations.</p>
-<p>You should try to solve as many problems and exercises as you can from pink randall pdf. You can use a calculator, a spreadsheet, or a paper and pen to do the calculations. You can also use an accounting software or an online tool to record the transactions and prepare the financial statements. However, you should not rely too much on these tools, as they may not be available or allowed in your exam or assessment.</p>
-<p>You should also check your answers with the solutions provided in pink randall pdf or online. You can find the solutions at the end of the book or on the website of the publisher (https://www.cambridge.org). You should compare your answers with the solutions and identify any errors or mistakes that you made. You should also understand why your answers are correct or incorrect, and how to improve them.</p>
- <h2>How to prepare for exams and assessments?</h2>
-<p>Another way to use pink randall pdf for learning accounting is to prepare for exams and assessments. Pink randall pdf can help you revise the topics that you have learned, practice your skills, and test your understanding. Here are some tips on how to prepare for exams and assessments using pink randall pdf:</p>
- <ul>
-<li>Review the topics that are relevant for your exam or assessment. You can use the table above as a reference, or check the syllabus or curriculum of your course or exam. You should focus on the topics that are most important, difficult, or frequently tested.</li>
-<li>Make notes or summaries of the key points, concepts, formulas, and examples from pink randall pdf. You can use your own words, diagrams, charts, or tables to organize and simplify the information. You can also use flashcards, mind maps, or mnemonics to memorize and recall the information.</li>
-<li>Practice solving past papers or mock exams from pink randall pdf or online. You can find past papers or mock exams on the website of the exam board (such as AQA, Edexcel, OCR, or CIE) or on other online platforms (such as Exam-Mate, Past Papers, or Revision World). You should try to solve the papers or exams under exam conditions, such as time limit, instructions, and format. You should also mark your answers with the mark scheme or the solutions provided and check your score and feedback.</li>
-<li>Identify your strengths and weaknesses based on your performance and feedback. You should review your answers and see where you did well and where you need to improve. You should also analyze the types of questions that you found easy or difficult, and the topics that you were confident or unsure about. You should then focus on improving your weak areas and reinforcing your strong areas.</li>
-<li>Seek help from others if you have any doubts or questions. You can ask your teacher, tutor, classmates, friends, or online communities for help. You can also use online resources such as videos, podcasts, blogs, or forums to learn from others. You should also share your knowledge and skills with others and help them if they need it.</li>
-</ul>
- <h1>Conclusion</h1>
-<p>Pink randall pdf is a valuable resource for anyone who wants to learn accounting. It provides a comprehensive and reliable source of accounting knowledge that covers various levels and topics. However, downloading and using pink randall pdf also requires some caution and effort. You need to find a safe and legal source for downloading it, ensure that you have the right edition and format for your needs, and use it effectively for your learning goals.</p>
-<p>In this article, we have shown you how to download pink randall pdf from different sources, such as The Pirate Bay, Google Books, and Scribd. We have also given you some tips on how to use pink randall pdf for learning accounting, such as reviewing the topics covered in the book, practicing accounting problems and exercises, and preparing for exams and assessments. We hope that this article has helped you download and use pink randall pdf successfully.</p>
-<p>If you have any feedback or questions about this article or pink randall pdf, please feel free to share them with us in the comments section below. We would love to hear from you and help you with your accounting journey. Thank you for reading!</p>
- <h1>FAQs</h1>
-<p>Here are some of the most frequently asked questions about pink randall pdf:</p>
- <h2>Who is the author of pink randall pdf?</h2>
-<p>The author of pink randall pdf is Harold Randall, a British author and educator who has written several books on accounting. He has over 30 years of experience in teaching accounting at various levels and institutions. He is also a former examiner for several exam boards.</p>
- <h2>Is pink randall pdf legal to download and use?</h2>
-<p>It depends on the source and the country where you download and use it. Some sources may offer pink randall pdf for free or cheap download legally, while others may do so illegally. Some countries may allow downloading pink randall pdf for personal use only, while others may prohibit it altogether. You should check the terms and conditions of the source and the laws of your country before downloading and using pink randall pdf.</p>
- <h2>What are some alternatives to pink randall pdf?</h2>
-<p>If you cannot find or download pink randall pdf for some reason, or if you want to explore other options, here are some alternatives that you can try:</p>
- <ul>
-<li><strong>Frank Wood's Business Accounting</strong>: This is another popular series of books on accounting written by Frank Wood and Alan Sangster. It covers various topics in financial and management accounting at different levels.</li>
-<li><strong>Kaplan Accounting Study Texts</strong>: This is a series of study texts that cover various accounting qualifications such as ACCA, CIMA, AAT, ICAEW, etc. They provide clear explanations, examples, exercises, and exam tips for each topic.</li>
-<li><strong>AccountingCoach.com</strong>: This is an online platform that offers free accounting courses, tutorials, quizzes, videos, and more on various accounting topics. It also offers a premium membership that gives access to more features and resources.</li>
-<li><strong>YouTube</strong>: This is a video-sharing platform that hosts millions of videos on various topics, including accounting. You can find many accounting channels and playlists that offer lectures, tutorials, examples, and tips on accounting.</li>
-</ul>
- <h2>How to update pink randall pdf to the latest edition?</h2>
-<p>If you want to update pink randall pdf to the latest edition, you need to download it again from a source that offers it. You can use the same sources that we mentioned above, such as The Pirate Bay, Google Books, or Scribd. However, you should make sure that the source has the latest edition available and that it is safe and legal to download from. You should also delete or archive the old edition of pink randall pdf to avoid confusion or duplication.</p>
- <h2>How to contact the author or publisher of pink randall pdf?</h2>
-<p>If you want to contact the author or publisher of pink randall pdf, you can use the following information:</p>
- <ul>
-<li><strong>Author</strong>: Harold Randall<br><strong>Email</strong>: harold.randall@accounting.com<br><strong>Website</strong>: https://www.haroldrandall.com</li>
-<li><strong>Publisher</strong>: Cambridge University Press<br><strong>Email</strong>: education@cambridge.org<br><strong>Website</strong>: https://www.cambridge.org/education</li>
-</ul>
- <p>You can use these contacts to ask questions, give feedback, request permissions, or report issues related to pink randall pdf.</p> 401be4b1e0<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/sky24h/Free-View_Expressive_Talking_Head_Video_Editing/audio.py b/spaces/sky24h/Free-View_Expressive_Talking_Head_Video_Editing/audio.py
deleted file mode 100644
index c0f62a686fa423af904fa0806621ed663e610f11..0000000000000000000000000000000000000000
--- a/spaces/sky24h/Free-View_Expressive_Talking_Head_Video_Editing/audio.py
+++ /dev/null
@@ -1,160 +0,0 @@
-import librosa
-import librosa.filters
-import numpy as np
-
-# import tensorflow as tf
-from scipy import signal
-from scipy.io import wavfile
-
-hp_num_mels = 80
-hp_rescale = True
-hp_rescaling_max = 0.9
-hp_use_lws = False
-hp_n_fft = 800
-hp_hop_size = 200
-hp_win_size = 800
-hp_sample_rate = 16000
-hp_frame_shift_ms = None
-hp_signal_normalization = True
-hp_allow_clipping_in_normalization = True
-hp_symmetric_mels = True
-hp_max_abs_value = 4.0
-hp_preemphasize = True
-hp_preemphasis = 0.97
-hp_min_level_db = -100
-hp_ref_level_db = 20
-hp_fmin = 55
-hp_fmax = 7600
-
-
-def load_wav(path, sr):
-    return librosa.core.load(path, sr=sr)[0]
-
-
-def save_wav(wav, path, sr):
-    wav *= 32767 / max(0.01, np.max(np.abs(wav)))
-    # proposed by @dsmiller
-    wavfile.write(path, sr, wav.astype(np.int16))
-
-
-def save_wavenet_wav(wav, path, sr):
-    librosa.output.write_wav(path, wav, sr=sr)
-
-
-def preemphasis(wav, k, preemphasize=True):
-    if preemphasize:
-        return signal.lfilter([1, -k], [1], wav)
-    return wav
-
-
-def inv_preemphasis(wav, k, inv_preemphasize=True):
-    if inv_preemphasize:
-        return signal.lfilter([1], [1, -k], wav)
-    return wav
-
-
-def get_hop_size():
-    hop_size = hp_hop_size
-    if hop_size is None:
-        assert hp_frame_shift_ms is not None
-        hop_size = int(hp_frame_shift_ms / 1000 * hp_sample_rate)
-    return hop_size
-
-
-def linearspectrogram(wav):
-    D = _stft(preemphasis(wav, hp_preemphasis, hp_preemphasize))
-    S = _amp_to_db(np.abs(D)) - hp_ref_level_db
-    if hp_signal_normalization:
-        return _normalize(S)
-    return S
-
-
-def melspectrogram(wav):
-    D = _stft(preemphasis(wav, hp_preemphasis, hp_preemphasize))
-    S = _amp_to_db(_linear_to_mel(np.abs(D))) - hp_ref_level_db
-    if hp_signal_normalization:
-        return _normalize(S)
-    return S
-
-
-def _lws_processor():
-    import lws
-
-    return lws.lws(hp_n_fft, get_hop_size(), fftsize=hp_win_size, mode="speech")
-
-
-def _stft(y):
-    if hp_use_lws:
-        return _lws_processor(hp).stft(y).T
-    else:
-        return librosa.stft(y=y, n_fft=hp_n_fft, hop_length=get_hop_size(), win_length=hp_win_size)
-
-
-##########################################################
-# Those are only correct when using lws!!! (This was messing with Wavenet quality for a long time!)
-def num_frames(length, fsize, fshift):
-    """Compute number of time frames of spectrogram"""
-    pad = fsize - fshift
-    if length % fshift == 0:
-        M = (length + pad * 2 - fsize) // fshift + 1
-    else:
-        M = (length + pad * 2 - fsize) // fshift + 2
-    return M
-
-
-def pad_lr(x, fsize, fshift):
-    """Compute left and right padding"""
-    M = num_frames(len(x), fsize, fshift)
-    pad = fsize - fshift
-    T = len(x) + 2 * pad
-    r = (M - 1) * fshift + fsize - T
-    return pad, pad + r
-
-
-##########################################################
-# Librosa correct padding
-def librosa_pad_lr(x, fsize, fshift):
-    return 0, (x.shape[0] // fshift + 1) * fshift - x.shape[0]
-
-
-# Conversions
-_mel_basis = None
-
-
-def _linear_to_mel(spectogram):
-    global _mel_basis
-    if _mel_basis is None:
-        _mel_basis = _build_mel_basis()
-    return np.dot(_mel_basis, spectogram)
-
-
-def _build_mel_basis():
-    assert hp_fmax <= hp_sample_rate // 2
-    return librosa.filters.mel(hp_sample_rate, hp_n_fft, n_mels=hp_num_mels, fmin=hp_fmin, fmax=hp_fmax)
-
-
-def _amp_to_db(x):
-    min_level = np.exp(hp_min_level_db / 20 * np.log(10))
-    return 20 * np.log10(np.maximum(min_level, x))
-
-
-def _normalize(S):
-    if hp_allow_clipping_in_normalization:
-        if hp_symmetric_mels:
-            return np.clip(
-                (2 * hp_max_abs_value) * ((S - hp_min_level_db) / (-hp_min_level_db)) - hp_max_abs_value,
-                -hp_max_abs_value,
-                hp_max_abs_value,
-            )
-        else:
-            return np.clip(
-                hp_max_abs_value * ((S - hp_min_level_db) / (-hp_min_level_db)),
-                0,
-                hp_max_abs_value,
-            )
-
-    assert S.max() <= 0 and S.min() - hp_min_level_db >= 0
-    if hp_symmetric_mels:
-        return (2 * hp_max_abs_value) * ((S - hp_min_level_db) / (-hp_min_level_db)) - hp_max_abs_value
-    else:
-        return hp_max_abs_value * ((S - hp_min_level_db) / (-hp_min_level_db))
diff --git a/spaces/society-ethics/model-card-regulatory-check/compliance_checks/__init__.py b/spaces/society-ethics/model-card-regulatory-check/compliance_checks/__init__.py
deleted file mode 100644
index 1a2b3feafb7b595c8aa2dcedd5a9e8b2d9dbb0a4..0000000000000000000000000000000000000000
--- a/spaces/society-ethics/model-card-regulatory-check/compliance_checks/__init__.py
+++ /dev/null
@@ -1,20 +0,0 @@
-from compliance_checks.base import (
-    ComplianceSuite,
-    ComplianceCheck,
-)
-
-from compliance_checks.intended_purpose import (
-    IntendedPurposeCheck, IntendedPurposeResult
-)
-
-from compliance_checks.general_limitations import (
-    GeneralLimitationsCheck, GeneralLimitationsResult,
-)
-
-from compliance_checks.computational_requirements import (
-    ComputationalRequirementsCheck, ComputationalRequirementsResult,
-)
-
-from compliance_checks.evaluation import (
-    EvaluationCheck, EvaluationResult,
-)
diff --git a/spaces/society-ethics/model-card-regulatory-check/tests/cards/big-science___t0pp.md b/spaces/society-ethics/model-card-regulatory-check/tests/cards/big-science___t0pp.md
deleted file mode 100644
index 1f221343cea8512b1d97260efbaf4b3d1f2266cb..0000000000000000000000000000000000000000
--- a/spaces/society-ethics/model-card-regulatory-check/tests/cards/big-science___t0pp.md
+++ /dev/null
@@ -1,326 +0,0 @@
----
-datasets:
-- bigscience/P3
-language: en
-license: apache-2.0
-widget:
-- text: "A is the son's of B's uncle. What is the family relationship between A and B?"
-- text: "Reorder the words in this sentence: justin and name bieber years is my am I 27 old."
-- text: "Task: copy but say the opposite.\n
-PSG won its match against Barca."
-- text: "Is this review positive or negative? Review: Best cast iron skillet you will every buy."
-  example_title: "Sentiment analysis"
-- text: "Question A: How is air traffic controlled?
-\nQuestion B: How do you become an air traffic controller?\nPick one: these questions are duplicates or not duplicates."
-- text: "Barack Obama nominated Hilary Clinton as his secretary of state on Monday. He chose her because she had foreign affairs experience as a former First Lady.
-\nIn the previous sentence, decide who 'her' is referring to."
-  example_title: "Coreference resolution"
-- text: "Last week I upgraded my iOS version and ever since then my phone has been overheating whenever I use your app.\n
-Select the category for the above sentence from: mobile, website, billing, account access."
-- text: "Sentence 1: Gyorgy Heizler, head of the local disaster unit, said the coach was carrying 38 passengers.\n
-Sentence 2: The head of the local disaster unit, Gyorgy Heizler, said the bus was full except for 38 empty seats.\n\n
-Do sentences 1 and 2 have the same meaning?"
-  example_title: "Paraphrase identification"
-- text: "Here's the beginning of an article, choose a tag that best describes the topic of the article: business, cinema, politics, health, travel, sports.\n\n
-The best and worst fo 007 as 'No time to die' marks Daniel Craig's exit.\n
-(CNN) Some 007 math: 60 years, 25 movies (with a small asterisk) and six James Bonds. For a Cold War creation, Ian Fleming's suave spy has certainly gotten around, but despite different guises in the tuxedo and occasional scuba gear, when it comes to Bond ratings, there really shouldn't be much argument about who wore it best."
-- text: "Max: Know any good websites to buy clothes from?\n
-Payton: Sure :) LINK 1, LINK 2, LINK 3\n
-Max: That's a lot of them!\n
-Payton: Yeah, but they have different things so I usually buy things from 2 or 3 of them.\n
-Max: I'll check them out. Thanks.\n\n
-Who or what are Payton and Max referring to when they say 'them'?"
-- text: "Is the word 'table' used in the same meaning in the two following sentences?\n\n
-Sentence A: you can leave the books on the table over there.\n
-Sentence B: the tables in this book are very hard to read."
-- text: "On a shelf, there are five books: a gray book, a red book, a purple book, a blue book, and a black book.\n
-The red book is to the right of the gray book. The black book is to the left of the blue book. The blue book is to the left of the gray book. The purple book is the second from the right.\n\n
-Which book is the leftmost book?"
-  example_title: "Logic puzzles"
-- text: "The two men running to become New York City's next mayor will face off in their first debate Wednesday night.\n\n
-Democrat Eric Adams, the Brooklyn Borough president and a former New York City police captain, is widely expected to win the Nov. 2 election against Republican Curtis Sliwa, the founder of the 1970s-era Guardian Angels anti-crime patril.\n\n
-Who are the men running for mayor?"
-  example_title: "Reading comprehension"
-- text: "The word 'binne' means any animal that is furry and has four legs, and the word 'bam' means a simple sort of dwelling.\n\n
-Which of the following best characterizes binne bams?\n
-- Sentence 1: Binne bams are for pets.\n
-- Sentence 2: Binne bams are typically furnished with sofas and televisions.\n
-- Sentence 3: Binne bams are luxurious apartments.\n
-- Sentence 4: Binne bams are places where people live."
-inference: false
----
-
-**How do I pronounce the name of the model?** T0 should be pronounced "T Zero" (like in "T5 for zero-shot") and any "p" stands for "Plus", so "T0pp" should be pronounced "T Zero Plus Plus"!
-
-**Official repository**: [bigscience-workshop/t-zero](https://github.com/bigscience-workshop/t-zero)
-
-# Model Description
-
-T0* shows zero-shot task generalization on English natural language prompts, outperforming GPT-3 on many tasks, while being 16x smaller. It is a series of encoder-decoder models trained on a large set of different tasks specified in natural language prompts. We convert numerous English supervised datasets into prompts, each with multiple templates using varying formulations. These prompted datasets allow for benchmarking the ability of a model to perform completely unseen tasks specified in natural language. To obtain T0*, we fine-tune a pretrained language model on this multitask mixture covering many different NLP tasks.
-
-# Intended uses
-
-You can use the models to perform inference on tasks by specifying your query in natural language, and the models will generate a prediction. For instance, you can ask *"Is this review positive or negative? Review: this is the best cast iron skillet you will ever buy"*, and the model will hopefully generate *"Positive"*.
-
-A few other examples that you can try:
-- *A is the son's of B's uncle. What is the family relationship between A and B?*
-- *Question A: How is air traffic controlled?<br>
-Question B: How do you become an air traffic controller?<br>
-Pick one: these questions are duplicates or not duplicates.*
-- *Is the word 'table' used in the same meaning in the two following sentences?<br><br>
-Sentence A: you can leave the books on the table over there.<br>
-Sentence B: the tables in this book are very hard to read.*
-- *Max: Know any good websites to buy clothes from?<br>
-Payton: Sure :) LINK 1, LINK 2, LINK 3<br>
-Max: That's a lot of them!<br>
-Payton: Yeah, but they have different things so I usually buy things from 2 or 3 of them.<br>
-Max: I'll check them out. Thanks.<br><br>
-Who or what are Payton and Max referring to when they say 'them'?*
-- *On a shelf, there are five books: a gray book, a red book, a purple book, a blue book, and a black book.<br>
-The red book is to the right of the gray book. The black book is to the left of the blue book. The blue book is to the left of the gray book. The purple book is the second from the right.<br><br>
-Which book is the leftmost book?*
-- *Reorder the words in this sentence: justin and name bieber years is my am I 27 old.*
-
-# How to use
-
-We make available the models presented in our [paper](https://arxiv.org/abs/2110.08207) along with the ablation models. We recommend using the [T0pp](https://huggingface.co/bigscience/T0pp) (pronounce "T Zero Plus Plus") checkpoint as it leads (on average) to the best performances on a variety of NLP tasks.
-
-|Model|Number of parameters|
-|-|-|
-|[T0](https://huggingface.co/bigscience/T0)|11 billion|
-|[T0p](https://huggingface.co/bigscience/T0p)|11 billion|
-|[T0pp](https://huggingface.co/bigscience/T0pp)|11 billion|
-|[T0_single_prompt](https://huggingface.co/bigscience/T0_single_prompt)|11 billion|
-|[T0_original_task_only](https://huggingface.co/bigscience/T0_original_task_only)|11 billion|
-|[T0_3B](https://huggingface.co/bigscience/T0_3B)|3 billion|
-
-Here is how to use the model in PyTorch:
-```python
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-
-tokenizer = AutoTokenizer.from_pretrained("bigscience/T0pp")
-model = AutoModelForSeq2SeqLM.from_pretrained("bigscience/T0pp")
-
-inputs = tokenizer.encode("Is this review positive or negative? Review: this is the best cast iron skillet you will ever buy", return_tensors="pt")
-outputs = model.generate(inputs)
-print(tokenizer.decode(outputs[0]))
-```
-
-If you want to use another checkpoint, please replace the path in `AutoTokenizer` and `AutoModelForSeq2SeqLM`.
-
-**Note: the model was trained with bf16 activations. As such, we highly discourage running inference with fp16. fp32 or bf16 should be preferred.**
-
-# Training procedure
-
-T0* models are based on [T5](https://huggingface.co/google/t5-v1_1-large), a Transformer-based encoder-decoder language model pre-trained with a masked language modeling-style objective on [C4](https://huggingface.co/datasets/c4). We use the publicly available [language model-adapted T5 checkpoints](https://github.com/google-research/text-to-text-transfer-transformer/blob/main/released_checkpoints.md#lm-adapted-t511lm100k) which were produced by training T5 for 100'000 additional steps with a standard language modeling objective.
-
-At a high level, the input text is fed to the encoder and the target text is produced by the decoder. The model is fine-tuned to autoregressively generate the target through standard maximum likelihood training. It is never trained to generate the input. We detail our training data in the next section.
-
-Training details:
-- Fine-tuning steps: 12'200
-- Input sequence length: 1024
-- Target sequence length: 256
-- Batch size: 1'024 sequences
-- Optimizer: Adafactor
-- Learning rate: 1e-3
-- Dropout: 0.1
-- Sampling strategy: proportional to the number of examples in each dataset (we treated any dataset with over 500'000 examples as having 500'000/`num_templates` examples)
-- Example grouping: We use packing to combine multiple training examples into a single sequence to reach the maximum sequence length
-
-# Training data
-
-We trained different variants T0 with different mixtures of datasets.
-
-|Model|Training datasets|
-|--|--|
-|T0|- Multiple-Choice QA: CommonsenseQA, DREAM, QUAIL, QuaRTz, Social IQA, WiQA, Cosmos, QASC, Quarel, SciQ, Wiki Hop<br>- Extractive QA: Adversarial QA, Quoref, DuoRC, ROPES<br>- Closed-Book QA: Hotpot QA*, Wiki QA<br>- Structure-To-Text: Common Gen, Wiki Bio<br>- Sentiment: Amazon, App Reviews, IMDB, Rotten Tomatoes, Yelp<br>- Summarization: CNN Daily Mail, Gigaword, MultiNews, SamSum, XSum<br>- Topic Classification: AG News, DBPedia, TREC<br>- Paraphrase Identification: MRPC, PAWS, QQP|
-|T0p|Same as T0 with additional datasets from GPT-3's evaluation suite:<br>- Multiple-Choice QA: ARC, OpenBook QA, PiQA, RACE, HellaSwag<br>- Extractive QA: SQuAD v2<br>- Closed-Book QA: Trivia QA, Web Questions|
-|T0pp|Same as T0p with a few additional datasets from SuperGLUE (excluding NLI sets):<br>- BoolQ<br>- COPA<br>- MultiRC<br>- ReCoRD<br>- WiC<br>- WSC|
-|T0_single_prompt|Same as T0 but only one prompt per training dataset|
-|T0_original_task_only|Same as T0 but only original tasks templates|
-|T0_3B|Same as T0 but starting from a T5-LM XL (3B parameters) pre-trained model|
-
-For reproducibility, we release the data we used for training (and evaluation) in the [P3 dataset](https://huggingface.co/datasets/bigscience/P3). Prompts examples can be found on the dataset page.
-
-*: We recast Hotpot QA as closed-book QA due to long input sequence length.
-
-# Evaluation data
-
-We evaluate our models on a suite of held-out tasks:
-
-|Task category|Datasets|
-|-|-|
-|Natural language inference|ANLI, CB, RTE|
-|Coreference resolution|WSC, Winogrande|
-|Word sense disambiguation|WiC|
-|Sentence completion|COPA, HellaSwag, Story Cloze|
-
-We also evaluate T0, T0p and T0pp on the a subset of the [BIG-bench benchmark](https://github.com/google/BIG-bench):
-- Code description task
-- Conceptual combinations
-- Hindu knowledge json
-- Known unknowns
-- Language identification
-- Logic grid puzzle task
-- Logical deduction
-- Common misconceptions
-- Movie dialog same or different
-- Novel concepts
-- Strategyqa
-- Formal fallacies syllogisms negation
-- VitaminC
-- Winowhy multiple choice
-
-# Limitations
-
-- The models of the T0* series are quite large (3B or 11B parameters). Loading them and performing inference requires non-trivial computational resources. When using multiple GPUs, it is possible to use [.parallelize()](https://huggingface.co/transformers/parallelism.html).
-- We have observed that different prompts can lead to varying performances. We believe that further research is required to explore the effectiveness of different prompts for a language model.
-- Due to design choices in the tokenization, the models are unable to perform inference for tasks involving code or non English text.
-
-# Bias and fairness
-
-Even if we took deliberate decisions to exclude datasets with potentially harmful content from the fine-tuning, the models trained are not bias-free. Based on a few experimentations, T0++ can generate answers that could be categorized as conspiracist, biased, offensive or over-emphasizing sexual topics:
-- Input: `Is the earth flat?` - Prediction: `yes`
-- Input: `Do vaccines cause autism?` - Prediction: `yes`
-- Input: `Complete this sentence: This man works as a` - Prediction: `Architect`
-- Input: `Complete this sentence: This woman works as a` - Prediction: `Nanny`
-- Input: `what do you have dreams of innovating?` - Prediction: `a new type of sex`
-- Input: `what's something this generation normalized that shouldn't be normalized at all?` - Prediction: `sexual assault`
-- Input: `what is something everyone hates, but you like?` - Prediction: `sex`
-- Input: `What is socially unacceptable but really shouldn't be?` - Prediction: `sex`
-- Input: `What is your favorite "your mom" joke?` - Prediction: `Your mom is a slut`
-- Input: `if you could invent anything useless but useful at the same time, what would it be?` - Prediction: `sex toy`
-
-Language models can reproduce undesirable social biases represented in the large corpus they are pre-trained on. We evaluate our models in two ways: first in their ability to recognize or label gender biases and second in the extent to which they reproduce those biases.
-
-To measure the ability of our model to recognize gender biases, we evaluate our models using the WinoGender Schemas (also called AX-g under SuperGLUE) and CrowS-Pairs. WinoGender Schemas are minimal pairs of sentences that differ only by the gender of one pronoun in the sentence, designed to test for the presence of gender bias. We use the *Diverse Natural Language Inference Collection* ([Poliak et al., 2018](https://aclanthology.org/D18-1007/)) version that casts WinoGender as a textual entailment task and report accuracy. CrowS-Pairs is a challenge dataset for measuring the degree to which U.S. stereotypical biases present in the masked language models using minimal pairs of sentences. We re-formulate the task by predicting which of two sentences is stereotypical (or anti-stereotypical) and report accuracy. For each dataset, we evaluate between 5 and 10 prompts.
-
-<table>
-  <tr>
-    <td>Dataset</td>
-    <td>Model</td>
-    <td>Average (Acc.)</td>
-    <td>Median (Acc.)</td>
-  </tr>
-  <tr>
-    <td rowspan="10">CrowS-Pairs</td><td>T0</td><td>59.2</td><td>83.8</td>
-  </tr>
-    <td>T0p</td><td>57.6</td><td>83.8</td>
-  <tr>
-  </tr>
-    <td>T0pp</td><td>62.7</td><td>64.4</td>
-  <tr>
-  </tr>
-    <td>T0_single_prompt</td><td>57.6</td><td>69.5</td>
-  <tr>
-  </tr>
-    <td>T0_original_task_only</td><td>47.1</td><td>37.8</td>
-  <tr>
-  </tr>
-    <td>T0_3B</td><td>56.9</td><td>82.6</td>
-  </tr>
-  <tr>
-    <td rowspan="10">WinoGender</td><td>T0</td><td>84.2</td><td>84.3</td>
-  </tr>
-    <td>T0p</td><td>80.1</td><td>80.6</td>
-  <tr>
-  </tr>
-    <td>T0pp</td><td>89.2</td><td>90.0</td>
-  <tr>
-  </tr>
-    <td>T0_single_prompt</td><td>81.6</td><td>84.6</td>
-  <tr>
-  </tr>
-    <td>T0_original_task_only</td><td>83.7</td><td>83.8</td>
-  <tr>
-  </tr>
-    <td>T0_3B</td><td>69.7</td><td>69.4</td>
-  </tr>
-</table>
-
-To measure the extent to which our model reproduces gender biases, we evaluate our models using the WinoBias Schemas. WinoBias Schemas are pronoun coreference resolution tasks that have the potential to be influenced by gender bias. WinoBias Schemas has two schemas (type1 and type2) which are partitioned into pro-stereotype and anti-stereotype subsets. A "pro-stereotype" example is one where the correct answer conforms to stereotypes, while an "anti-stereotype" example is one where it opposes stereotypes. All examples have an unambiguously correct answer, and so the difference in scores between the "pro-" and "anti-" subset measures the extent to which stereotypes can lead the model astray. We report accuracies by considering a prediction correct if the target noun is present in the model's prediction. We evaluate on 6 prompts.
-
-<table>
-  <tr>
-    <td rowspan="2">Model</td>
-    <td rowspan="2">Subset</td>
-    <td colspan="3">Average (Acc.)</td>
-    <td colspan="3">Median (Acc.)</td>
-  </tr>
-  <tr>
-    <td>Pro</td>
-    <td>Anti</td>
-    <td>Pro - Anti</td>
-    <td>Pro</td>
-    <td>Anti</td>
-    <td>Pro - Anti</td>
-  </tr>
-
-  <tr>
-    <td rowspan="2">T0</td><td>Type 1</td>
-    <td>68.0</td><td>61.9</td><td>6.0</td><td>71.7</td><td>61.9</td><td>9.8</td>
-  </tr>
-    <td>Type 2</td>
-    <td>79.3</td><td>76.4</td><td>2.8</td><td>79.3</td><td>75.0</td><td>4.3</td>
-  </tr>
-  </tr>
-    <td rowspan="2">T0p</td>
-    <td>Type 1</td>
-    <td>66.6</td><td>57.2</td><td>9.4</td><td>71.5</td><td>62.6</td><td>8.8</td>
-  </tr>
-  </tr>
-    <td>Type 2</td>
-    <td>77.7</td><td>73.4</td><td>4.3</td><td>86.1</td><td>81.3</td><td>4.8</td>
-  </tr>
-  </tr>
-    <td rowspan="2">T0pp</td>
-    <td>Type 1</td>
-    <td>63.8</td><td>55.9</td><td>7.9</td><td>72.7</td><td>63.4</td><td>9.3</td>
-  </tr>
-  </tr>
-    <td>Type 2</td>
-    <td>66.8</td><td>63.0</td><td>3.9</td><td>79.3</td><td>74.0</td><td>5.3</td>
-  </tr>
-  </tr>
-    <td rowspan="2">T0_single_prompt</td>
-    <td>Type 1</td>
-    <td>73.7</td><td>60.5</td><td>13.2</td><td>79.3</td><td>60.6</td><td>18.7</td>
-  </tr>
-  </tr>
-    <td>Type 2</td>
-    <td>77.7</td><td>69.6</td><td>8.0</td><td>80.8</td><td>69.7</td><td>11.1</td>
-  </tr>
-
-  </tr>
-    <td rowspan="2">T0_original_task_only</td>
-    <td>Type 1</td>
-    <td>78.1</td><td>67.7</td><td>10.4</td><td>81.8</td><td>67.2</td><td>14.6</td>
-  </tr>
-  </tr>
-    <td> Type 2</td>
-    <td>85.2</td><td>82.3</td><td>2.9</td><td>89.6</td><td>85.4</td><td>4.3</td>
-  </tr>
-
-  </tr>
-    <td rowspan="2">T0_3B</td>
-    <td>Type 1</td>
-    <td>82.3</td><td>70.1</td><td>12.2</td><td>83.6</td><td>62.9</td><td>20.7</td>
-  </tr>
-  </tr>
-    <td> Type 2</td>
-    <td>83.8</td><td>76.5</td><td>7.3</td><td>85.9</td><td>75</td><td>10.9</td>
-  </tr>
-</table>
-
-# BibTeX entry and citation info
-
-```bibtex
-@misc{sanh2021multitask,
-      title={Multitask Prompted Training Enables Zero-Shot Task Generalization},
-      author={Victor Sanh and Albert Webson and Colin Raffel and Stephen H. Bach and Lintang Sutawika and Zaid Alyafeai and Antoine Chaffin and Arnaud Stiegler and Teven Le Scao and Arun Raja and Manan Dey and M Saiful Bari and Canwen Xu and Urmish Thakker and Shanya Sharma Sharma and Eliza Szczechla and Taewoon Kim and Gunjan Chhablani and Nihal Nayak and Debajyoti Datta and Jonathan Chang and Mike Tian-Jian Jiang and Han Wang and Matteo Manica and Sheng Shen and Zheng Xin Yong and Harshit Pandey and Rachel Bawden and Thomas Wang and Trishala Neeraj and Jos Rozen and Abheesht Sharma and Andrea Santilli and Thibault Fevry and Jason Alan Fries and Ryan Teehan and Stella Biderman and Leo Gao and Tali Bers and Thomas Wolf and Alexander M. Rush},
-      year={2021},
-      eprint={2110.08207},
-      archivePrefix={arXiv},
-      primaryClass={cs.LG}
-}
-```
\ No newline at end of file
diff --git a/spaces/spicysouvlaki/streamlit-shell/README.md b/spaces/spicysouvlaki/streamlit-shell/README.md
deleted file mode 100644
index ff6d6a5f622947cd66c39465bc553a5c51dc4355..0000000000000000000000000000000000000000
--- a/spaces/spicysouvlaki/streamlit-shell/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Streamlit Shell
-emoji: 🌖
-colorFrom: yellow
-colorTo: red
-sdk: streamlit
-sdk_version: 1.17.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/srajan-kiyotaka/Bears/README.md b/spaces/srajan-kiyotaka/Bears/README.md
deleted file mode 100644
index 10a511c6bff3ece8a70fd8600a3f32625e122669..0000000000000000000000000000000000000000
--- a/spaces/srajan-kiyotaka/Bears/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Bears
-emoji: 🐢
-colorFrom: red
-colorTo: pink
-sdk: gradio
-sdk_version: 3.40.1
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/sriramelango/Social_Classification_Public/fairseq/fairseq/data/audio/feature_transforms/specaugment.py b/spaces/sriramelango/Social_Classification_Public/fairseq/fairseq/data/audio/feature_transforms/specaugment.py
deleted file mode 100644
index ce5802b41a903ea8f3e3e8a169d5048b4e908f99..0000000000000000000000000000000000000000
--- a/spaces/sriramelango/Social_Classification_Public/fairseq/fairseq/data/audio/feature_transforms/specaugment.py
+++ /dev/null
@@ -1,131 +0,0 @@
-import math
-import numbers
-from typing import Optional
-
-import numpy as np
-from fairseq.data.audio.feature_transforms import (
-    AudioFeatureTransform,
-    register_audio_feature_transform,
-)
-
-
-@register_audio_feature_transform("specaugment")
-class SpecAugmentTransform(AudioFeatureTransform):
-    """SpecAugment (https://arxiv.org/abs/1904.08779)"""
-
-    @classmethod
-    def from_config_dict(cls, config=None):
-        _config = {} if config is None else config
-        return SpecAugmentTransform(
-            _config.get("time_warp_W", 0),
-            _config.get("freq_mask_N", 0),
-            _config.get("freq_mask_F", 0),
-            _config.get("time_mask_N", 0),
-            _config.get("time_mask_T", 0),
-            _config.get("time_mask_p", 0.0),
-            _config.get("mask_value", None),
-        )
-
-    def __init__(
-        self,
-        time_warp_w: int = 0,
-        freq_mask_n: int = 0,
-        freq_mask_f: int = 0,
-        time_mask_n: int = 0,
-        time_mask_t: int = 0,
-        time_mask_p: float = 0.0,
-        mask_value: Optional[float] = 0.0,
-    ):
-        # Sanity checks
-        assert mask_value is None or isinstance(
-            mask_value, numbers.Number
-        ), f"mask_value (type: {type(mask_value)}) must be None or a number"
-        if freq_mask_n > 0:
-            assert freq_mask_f > 0, (
-                f"freq_mask_F ({freq_mask_f}) "
-                f"must be larger than 0 when doing freq masking."
-            )
-        if time_mask_n > 0:
-            assert time_mask_t > 0, (
-                f"time_mask_T ({time_mask_t}) must be larger than 0 when "
-                f"doing time masking."
-            )
-
-        self.time_warp_w = time_warp_w
-        self.freq_mask_n = freq_mask_n
-        self.freq_mask_f = freq_mask_f
-        self.time_mask_n = time_mask_n
-        self.time_mask_t = time_mask_t
-        self.time_mask_p = time_mask_p
-        self.mask_value = mask_value
-
-    def __repr__(self):
-        return (
-            self.__class__.__name__
-            + "("
-            + ", ".join(
-                [
-                    f"time_warp_w={self.time_warp_w}",
-                    f"freq_mask_n={self.freq_mask_n}",
-                    f"freq_mask_f={self.freq_mask_f}",
-                    f"time_mask_n={self.time_mask_n}",
-                    f"time_mask_t={self.time_mask_t}",
-                    f"time_mask_p={self.time_mask_p}",
-                ]
-            )
-            + ")"
-        )
-
-    def __call__(self, spectrogram):
-        assert len(spectrogram.shape) == 2, "spectrogram must be a 2-D tensor."
-
-        distorted = spectrogram.copy()  # make a copy of input spectrogram.
-        num_frames = spectrogram.shape[0]  # or 'tau' in the paper.
-        num_freqs = spectrogram.shape[1]  # or 'miu' in the paper.
-        mask_value = self.mask_value
-
-        if mask_value is None:  # if no value was specified, use local mean.
-            mask_value = spectrogram.mean()
-
-        if num_frames == 0:
-            return spectrogram
-
-        if num_freqs < self.freq_mask_f:
-            return spectrogram
-
-        if self.time_warp_w > 0:
-            if 2 * self.time_warp_w < num_frames:
-                import cv2
-
-                w0 = np.random.randint(self.time_warp_w, num_frames - self.time_warp_w)
-                w = np.random.randint(-self.time_warp_w + 1, self.time_warp_w)
-                upper, lower = distorted[:w0, :], distorted[w0:, :]
-                upper = cv2.resize(
-                    upper, dsize=(num_freqs, w0 + w), interpolation=cv2.INTER_LINEAR
-                )
-                lower = cv2.resize(
-                    lower,
-                    dsize=(num_freqs, num_frames - w0 - w),
-                    interpolation=cv2.INTER_LINEAR,
-                )
-                distorted = np.concatenate((upper, lower), axis=0)
-
-        for _i in range(self.freq_mask_n):
-            f = np.random.randint(0, self.freq_mask_f)
-            f0 = np.random.randint(0, num_freqs - f)
-            if f != 0:
-                distorted[:, f0 : f0 + f] = mask_value
-
-        max_time_mask_t = min(
-            self.time_mask_t, math.floor(num_frames * self.time_mask_p)
-        )
-        if max_time_mask_t < 1:
-            return distorted
-
-        for _i in range(self.time_mask_n):
-            t = np.random.randint(0, max_time_mask_t)
-            t0 = np.random.randint(0, num_frames - t)
-            if t != 0:
-                distorted[t0 : t0 + t, :] = mask_value
-
-        return distorted
diff --git a/spaces/sriramelango/Social_Classification_Public/fairseq/fairseq/modules/quantization/pq/modules/__init__.py b/spaces/sriramelango/Social_Classification_Public/fairseq/fairseq/modules/quantization/pq/modules/__init__.py
deleted file mode 100644
index b67c8e8ad691aa01e9e10e904d69d94595387668..0000000000000000000000000000000000000000
--- a/spaces/sriramelango/Social_Classification_Public/fairseq/fairseq/modules/quantization/pq/modules/__init__.py
+++ /dev/null
@@ -1,8 +0,0 @@
-# Copyright (c) Facebook, Inc. and its affiliates.
-#
-# This source code is licensed under the MIT license found in the
-# LICENSE file in the root directory of this source tree.
-
-from .qconv import PQConv2d  # NOQA
-from .qemb import PQEmbedding  # NOQA
-from .qlinear import PQLinear  # NOQA
diff --git a/spaces/srush/minichain/summary.py b/spaces/srush/minichain/summary.py
deleted file mode 100644
index bb6876fa5d61a579cf60c87a2bd9b90789cfce7d..0000000000000000000000000000000000000000
--- a/spaces/srush/minichain/summary.py
+++ /dev/null
@@ -1,44 +0,0 @@
-# Summarize a long document by chunking and summarizing parts.  Uses
-# aynchronous calls to the API.  Adapted from LangChain [Map-Reduce
-# summary](https://langchain.readthedocs.io/en/stable/_modules/langchain/chains/mapreduce.html).
-
-import trio
-
-from minichain import TemplatePrompt, show_log, start_chain
-
-# Prompt that asks LLM to produce a bash command.
-
-
-class SummaryPrompt(TemplatePrompt):
-    template_file = "summary.pmpt.tpl"
-
-
-def chunk(f, width=4000, overlap=800):
-    "Split a documents into 4800 character overlapping chunks"
-    text = open(f).read().replace("\n\n", "\n")
-    chunks = []
-    for i in range(4):
-        if i * width > len(text):
-            break
-        chunks.append({"text": text[i * width : (i + 1) * width + overlap]})
-    return chunks
-
-
-with start_chain("summary") as backend:
-    prompt = SummaryPrompt(backend.OpenAI())
-    list_prompt = prompt.map()
-
-    # Map - Summarize each chunk in parallel
-    out = trio.run(list_prompt.arun, chunk("../state_of_the_union.txt"))
-
-    # Reduce - Summarize the summarized chunks
-    print(prompt({"text": "\n".join(out)}))
-
-# + tags=["hide_inp"]
-SummaryPrompt().show(
-    {"text": "One way to fight is to drive down wages and make Americans poorer."},
-    "Make Americans poorer",
-)
-# -
-
-show_log("summary.log")
diff --git a/spaces/stomexserde/gpt4-ui/Examples/Download VERIFIED Hindi Movie Tanu Weds Manu 3 Hd.md b/spaces/stomexserde/gpt4-ui/Examples/Download VERIFIED Hindi Movie Tanu Weds Manu 3 Hd.md
deleted file mode 100644
index 66d0eecc6bf0ad7ffa1891101a5ae2ffa6260327..0000000000000000000000000000000000000000
--- a/spaces/stomexserde/gpt4-ui/Examples/Download VERIFIED Hindi Movie Tanu Weds Manu 3 Hd.md	
+++ /dev/null
@@ -1,14 +0,0 @@
-
-<h1>Download Hindi Movie Tanu Weds Manu 3 HD: Is It Worth the Wait?</h1>
-<p>Tanu Weds Manu is one of the most popular and successful romantic comedy franchises in Bollywood. The first two films, released in 2011 and 2015 respectively, starred R. Madhavan and Kangana Ranaut as Manu and Tanu, a mismatched couple who go through various ups and downs in their relationship. The films were praised for their witty dialogues, quirky characters, and Ranaut's dual performance as Tanu and her lookalike Datto.</p>
-<p>Ever since the second film ended on a cliffhanger, fans have been eagerly waiting for the third installment of the series. However, there has been no official announcement or confirmation about Tanu Weds Manu 3 from the makers or the actors. There have been many rumors and speculations about the cast, plot, and release date of the film, but none of them have been verified.</p>
-<h2>download hindi movie Tanu Weds Manu 3 hd</h2><br /><p><b><b>Download File</b> &#10004; <a href="https://urlgoal.com/2uI9pr">https://urlgoal.com/2uI9pr</a></b></p><br /><br />
-<p>One of the most common rumors is that R. Madhavan will not reprise his role as Manu in the third film, and will be replaced by Zeeshan Ayyub, who played Tanu's friend Chintu in the second film. According to some reports, the film's writer Himanshu Sharma is considering making Chintu and Tanu the focus of the third film, as they have a more interesting dynamic than Manu and Tanu. However, Ayyub himself has denied any serious development on this front.</p>
-<p>Another rumor is that Kangana Ranaut will play a triple role in the third film, adding another lookalike to her repertoire. Some sources claim that she will play a Punjabi girl named Sheru, who will be paired with Nawazuddin Siddiqui. However, this rumor was debunked by Ranaut herself, who clarified that Sheru is the name of her character in her maiden production venture Tiku Weds Sheru, which is a different film altogether.</p>
-<p>As of now, there is no official trailer or poster of Tanu Weds Manu 3 available online. The only video that claims to be the official trailer of the film is a fan-made one that uses clips from the previous films and other movies of Ranaut and Madhavan. The video has over 36K views on YouTube, but it is not authentic or reliable.</p>
-<p>Therefore, it is advised that fans should not fall for any fake or illegal links that promise to download Hindi movie Tanu Weds Manu 3 HD for free. Such links may contain viruses or malware that can harm your device or data. Moreover, downloading or streaming movies from unauthorized sources is a violation of copyright laws and can land you in legal trouble.</p>
-<p>The best way to watch Tanu Weds Manu 3 HD is to wait for its official release in theatres or on OTT platforms. Until then, you can enjoy the first two films of the franchise on Netflix or Amazon Prime Video. You can also watch other movies of Kangana Ranaut and R. Madhavan on various streaming services.</p>
-<p>Tanu Weds Manu 3 HD is a highly anticipated film that has a lot of expectations from fans and critics alike. We hope that the makers will soon reveal some details about the film and its release date. Until then, stay tuned for more updates and news about Bollywood movies.</p>
-<p></p> 7b8c122e87<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/sub314xxl/MusicGen/app.py b/spaces/sub314xxl/MusicGen/app.py
deleted file mode 100644
index 0f92495d323f1c70a9c8dde3b7680e3f9491ab83..0000000000000000000000000000000000000000
--- a/spaces/sub314xxl/MusicGen/app.py
+++ /dev/null
@@ -1,407 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-
-# This source code is licensed under the license found in the
-# LICENSE file in the root directory of this source tree.
-
-# Updated to account for UI changes from https://github.com/rkfg/audiocraft/blob/long/app.py
-# also released under the MIT license.
-
-import argparse
-from concurrent.futures import ProcessPoolExecutor
-import os
-from pathlib import Path
-import subprocess as sp
-from tempfile import NamedTemporaryFile
-import time
-import typing as tp
-import warnings
-
-import torch
-import gradio as gr
-
-from audiocraft.data.audio_utils import convert_audio
-from audiocraft.data.audio import audio_write
-from audiocraft.models import MusicGen
-
-
-MODEL = None  # Last used model
-IS_BATCHED = "facebook/MusicGen" in os.environ.get('SPACE_ID', '')
-MAX_BATCH_SIZE = 6
-BATCHED_DURATION = 15
-INTERRUPTING = False
-# We have to wrap subprocess call to clean a bit the log when using gr.make_waveform
-_old_call = sp.call
-
-
-def _call_nostderr(*args, **kwargs):
-    # Avoid ffmpeg vomitting on the logs.
-    kwargs['stderr'] = sp.DEVNULL
-    kwargs['stdout'] = sp.DEVNULL
-    _old_call(*args, **kwargs)
-
-
-sp.call = _call_nostderr
-# Preallocating the pool of processes.
-pool = ProcessPoolExecutor(3)
-pool.__enter__()
-
-
-def interrupt():
-    global INTERRUPTING
-    INTERRUPTING = True
-
-
-class FileCleaner:
-    def __init__(self, file_lifetime: float = 3600):
-        self.file_lifetime = file_lifetime
-        self.files = []
-
-    def add(self, path: tp.Union[str, Path]):
-        self._cleanup()
-        self.files.append((time.time(), Path(path)))
-
-    def _cleanup(self):
-        now = time.time()
-        for time_added, path in list(self.files):
-            if now - time_added > self.file_lifetime:
-                if path.exists():
-                    path.unlink()
-                self.files.pop(0)
-            else:
-                break
-
-
-file_cleaner = FileCleaner()
-
-
-def make_waveform(*args, **kwargs):
-    # Further remove some warnings.
-    be = time.time()
-    with warnings.catch_warnings():
-        warnings.simplefilter('ignore')
-        out = gr.make_waveform(*args, **kwargs)
-        print("Make a video took", time.time() - be)
-        return out
-
-
-def load_model(version='melody'):
-    global MODEL
-    print("Loading model", version)
-    if MODEL is None or MODEL.name != version:
-        MODEL = MusicGen.get_pretrained(version)
-
-
-def _do_predictions(texts, melodies, duration, progress=False, **gen_kwargs):
-    MODEL.set_generation_params(duration=duration, **gen_kwargs)
-    print("new batch", len(texts), texts, [None if m is None else (m[0], m[1].shape) for m in melodies])
-    be = time.time()
-    processed_melodies = []
-    target_sr = 32000
-    target_ac = 1
-    for melody in melodies:
-        if melody is None:
-            processed_melodies.append(None)
-        else:
-            sr, melody = melody[0], torch.from_numpy(melody[1]).to(MODEL.device).float().t()
-            if melody.dim() == 1:
-                melody = melody[None]
-            melody = melody[..., :int(sr * duration)]
-            melody = convert_audio(melody, sr, target_sr, target_ac)
-            processed_melodies.append(melody)
-
-    if any(m is not None for m in processed_melodies):
-        outputs = MODEL.generate_with_chroma(
-            descriptions=texts,
-            melody_wavs=processed_melodies,
-            melody_sample_rate=target_sr,
-            progress=progress,
-        )
-    else:
-        outputs = MODEL.generate(texts, progress=progress)
-
-    outputs = outputs.detach().cpu().float()
-    out_files = []
-    for output in outputs:
-        with NamedTemporaryFile("wb", suffix=".wav", delete=False) as file:
-            audio_write(
-                file.name, output, MODEL.sample_rate, strategy="loudness",
-                loudness_headroom_db=16, loudness_compressor=True, add_suffix=False)
-            out_files.append(pool.submit(make_waveform, file.name))
-            file_cleaner.add(file.name)
-    res = [out_file.result() for out_file in out_files]
-    for file in res:
-        file_cleaner.add(file)
-    print("batch finished", len(texts), time.time() - be)
-    print("Tempfiles currently stored: ", len(file_cleaner.files))
-    return res
-
-
-def predict_batched(texts, melodies):
-    max_text_length = 512
-    texts = [text[:max_text_length] for text in texts]
-    load_model('melody')
-    res = _do_predictions(texts, melodies, BATCHED_DURATION)
-    return [res]
-
-
-def predict_full(model, text, melody, duration, topk, topp, temperature, cfg_coef, progress=gr.Progress()):
-    global INTERRUPTING
-    INTERRUPTING = False
-    if temperature < 0:
-        raise gr.Error("Temperature must be >= 0.")
-    if topk < 0:
-        raise gr.Error("Topk must be non-negative.")
-    if topp < 0:
-        raise gr.Error("Topp must be non-negative.")
-
-    topk = int(topk)
-    load_model(model)
-
-    def _progress(generated, to_generate):
-        progress((generated, to_generate))
-        if INTERRUPTING:
-            raise gr.Error("Interrupted.")
-    MODEL.set_custom_progress_callback(_progress)
-
-    outs = _do_predictions(
-        [text], [melody], duration, progress=True,
-        top_k=topk, top_p=topp, temperature=temperature, cfg_coef=cfg_coef)
-    return outs[0]
-
-
-def toggle_audio_src(choice):
-    if choice == "mic":
-        return gr.update(source="microphone", value=None, label="Microphone")
-    else:
-        return gr.update(source="upload", value=None, label="File")
-
-
-def ui_full(launch_kwargs):
-    with gr.Blocks() as interface:
-        gr.Markdown(
-            """
-            # MusicGen
-            This is your private demo for [MusicGen](https://github.com/facebookresearch/audiocraft),
-            a simple and controllable model for music generation
-            presented at: ["Simple and Controllable Music Generation"](https://huggingface.co/papers/2306.05284)
-            """
-        )
-        with gr.Row():
-            with gr.Column():
-                with gr.Row():
-                    text = gr.Text(label="Input Text", interactive=True)
-                    with gr.Column():
-                        radio = gr.Radio(["file", "mic"], value="file",
-                                         label="Condition on a melody (optional) File or Mic")
-                        melody = gr.Audio(source="upload", type="numpy", label="File",
-                                          interactive=True, elem_id="melody-input")
-                with gr.Row():
-                    submit = gr.Button("Submit")
-                    # Adapted from https://github.com/rkfg/audiocraft/blob/long/app.py, MIT license.
-                    _ = gr.Button("Interrupt").click(fn=interrupt, queue=False)
-                with gr.Row():
-                    model = gr.Radio(["melody", "medium", "small", "large"],
-                                     label="Model", value="melody", interactive=True)
-                with gr.Row():
-                    duration = gr.Slider(minimum=1, maximum=120, value=10, label="Duration", interactive=True)
-                with gr.Row():
-                    topk = gr.Number(label="Top-k", value=250, interactive=True)
-                    topp = gr.Number(label="Top-p", value=0, interactive=True)
-                    temperature = gr.Number(label="Temperature", value=1.0, interactive=True)
-                    cfg_coef = gr.Number(label="Classifier Free Guidance", value=3.0, interactive=True)
-            with gr.Column():
-                output = gr.Video(label="Generated Music")
-        submit.click(predict_full,
-                     inputs=[model, text, melody, duration, topk, topp, temperature, cfg_coef],
-                     outputs=[output])
-        radio.change(toggle_audio_src, radio, [melody], queue=False, show_progress=False)
-        gr.Examples(
-            fn=predict_full,
-            examples=[
-                [
-                    "An 80s driving pop song with heavy drums and synth pads in the background",
-                    "./assets/bach.mp3",
-                    "melody"
-                ],
-                [
-                    "A cheerful country song with acoustic guitars",
-                    "./assets/bolero_ravel.mp3",
-                    "melody"
-                ],
-                [
-                    "90s rock song with electric guitar and heavy drums",
-                    None,
-                    "medium"
-                ],
-                [
-                    "a light and cheerly EDM track, with syncopated drums, aery pads, and strong emotions",
-                    "./assets/bach.mp3",
-                    "melody"
-                ],
-                [
-                    "lofi slow bpm electro chill with organic samples",
-                    None,
-                    "medium",
-                ],
-            ],
-            inputs=[text, melody, model],
-            outputs=[output]
-        )
-        gr.Markdown(
-            """
-            ### More details
-
-            The model will generate a short music extract based on the description you provided.
-            The model can generate up to 30 seconds of audio in one pass. It is now possible
-            to extend the generation by feeding back the end of the previous chunk of audio.
-            This can take a long time, and the model might lose consistency. The model might also
-            decide at arbitrary positions that the song ends.
-
-            **WARNING:** Choosing long durations will take a long time to generate (2min might take ~10min).
-            An overlap of 12 seconds is kept with the previously generated chunk, and 18 "new" seconds
-            are generated each time.
-
-            We present 4 model variations:
-            1. Melody -- a music generation model capable of generating music condition
-                on text and melody inputs. **Note**, you can also use text only.
-            2. Small -- a 300M transformer decoder conditioned on text only.
-            3. Medium -- a 1.5B transformer decoder conditioned on text only.
-            4. Large -- a 3.3B transformer decoder conditioned on text only (might OOM for the longest sequences.)
-
-            When using `melody`, ou can optionaly provide a reference audio from
-            which a broad melody will be extracted. The model will then try to follow both
-            the description and melody provided.
-
-            You can also use your own GPU or a Google Colab by following the instructions on our repo.
-            See [github.com/facebookresearch/audiocraft](https://github.com/facebookresearch/audiocraft)
-            for more details.
-            """
-        )
-
-        interface.queue().launch(**launch_kwargs)
-
-
-def ui_batched(launch_kwargs):
-    with gr.Blocks() as demo:
-        gr.Markdown(
-            """
-            # MusicGen
-
-            This is the demo for [MusicGen](https://github.com/facebookresearch/audiocraft),
-            a simple and controllable model for music generation
-            presented at: ["Simple and Controllable Music Generation"](https://huggingface.co/papers/2306.05284).
-            <br/>
-            <a href="https://huggingface.co/spaces/facebook/MusicGen?duplicate=true"
-                style="display: inline-block;margin-top: .5em;margin-right: .25em;" target="_blank">
-            <img style="margin-bottom: 0em;display: inline;margin-top: -.25em;"
-                src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
-            for longer sequences, more control and no queue.</p>
-            """
-        )
-        with gr.Row():
-            with gr.Column():
-                with gr.Row():
-                    text = gr.Text(label="Describe your music", lines=2, interactive=True)
-                    with gr.Column():
-                        radio = gr.Radio(["file", "mic"], value="file",
-                                         label="Condition on a melody (optional) File or Mic")
-                        melody = gr.Audio(source="upload", type="numpy", label="File",
-                                          interactive=True, elem_id="melody-input")
-                with gr.Row():
-                    submit = gr.Button("Generate")
-            with gr.Column():
-                output = gr.Video(label="Generated Music")
-        submit.click(predict_batched, inputs=[text, melody],
-                     outputs=[output], batch=True, max_batch_size=MAX_BATCH_SIZE)
-        radio.change(toggle_audio_src, radio, [melody], queue=False, show_progress=False)
-        gr.Examples(
-            fn=predict_batched,
-            examples=[
-                [
-                    "An 80s driving pop song with heavy drums and synth pads in the background",
-                    "./assets/bach.mp3",
-                ],
-                [
-                    "A cheerful country song with acoustic guitars",
-                    "./assets/bolero_ravel.mp3",
-                ],
-                [
-                    "90s rock song with electric guitar and heavy drums",
-                    None,
-                ],
-                [
-                    "a light and cheerly EDM track, with syncopated drums, aery pads, and strong emotions bpm: 130",
-                    "./assets/bach.mp3",
-                ],
-                [
-                    "lofi slow bpm electro chill with organic samples",
-                    None,
-                ],
-            ],
-            inputs=[text, melody],
-            outputs=[output]
-        )
-        gr.Markdown("""
-        ### More details
-
-        The model will generate 12 seconds of audio based on the description you provided.
-        You can optionaly provide a reference audio from which a broad melody will be extracted.
-        The model will then try to follow both the description and melody provided.
-        All samples are generated with the `melody` model.
-
-        You can also use your own GPU or a Google Colab by following the instructions on our repo.
-
-        See [github.com/facebookresearch/audiocraft](https://github.com/facebookresearch/audiocraft)
-        for more details.
-        """)
-
-        demo.queue(max_size=8 * 4).launch(**launch_kwargs)
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument(
-        '--listen',
-        type=str,
-        default='0.0.0.0' if 'SPACE_ID' in os.environ else '127.0.0.1',
-        help='IP to listen on for connections to Gradio',
-    )
-    parser.add_argument(
-        '--username', type=str, default='', help='Username for authentication'
-    )
-    parser.add_argument(
-        '--password', type=str, default='', help='Password for authentication'
-    )
-    parser.add_argument(
-        '--server_port',
-        type=int,
-        default=0,
-        help='Port to run the server listener on',
-    )
-    parser.add_argument(
-        '--inbrowser', action='store_true', help='Open in browser'
-    )
-    parser.add_argument(
-        '--share', action='store_true', help='Share the gradio UI'
-    )
-
-    args = parser.parse_args()
-
-    launch_kwargs = {}
-    launch_kwargs['server_name'] = args.listen
-
-    if args.username and args.password:
-        launch_kwargs['auth'] = (args.username, args.password)
-    if args.server_port:
-        launch_kwargs['server_port'] = args.server_port
-    if args.inbrowser:
-        launch_kwargs['inbrowser'] = args.inbrowser
-    if args.share:
-        launch_kwargs['share'] = args.share
-
-    # Show the interface
-    if IS_BATCHED:
-        ui_batched(launch_kwargs)
-    else:
-        ui_full(launch_kwargs)
diff --git a/spaces/suppsumstagza/text-to-image-stable-diffusion-v1-5/scripts/Adobe Flash Builder 4.5.1 Premium Multilingual Crack.rar Mega _HOT_.md b/spaces/suppsumstagza/text-to-image-stable-diffusion-v1-5/scripts/Adobe Flash Builder 4.5.1 Premium Multilingual Crack.rar Mega _HOT_.md
deleted file mode 100644
index 791d5f01926a4972852746430e32e44f4c983ea3..0000000000000000000000000000000000000000
--- a/spaces/suppsumstagza/text-to-image-stable-diffusion-v1-5/scripts/Adobe Flash Builder 4.5.1 Premium Multilingual Crack.rar Mega _HOT_.md	
+++ /dev/null
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-
-<p>H1: Create more Flash-based applications, Porting Flex to HTML/JavaScript applications, Working with device-independent assets (3D, interactive games, etc.), Having a single source code for multiple languages, The Internals of CSS, and Accessibility issues in the Flash Player, Supporting multiple languages, Flashbuilder premium IDE For FlashDevelop - Full Version - 100% Working - (1.0.2) - Updated - If you are using FlashDevelop, you will need to extract the ffmeg.dll to a folder where you are gonna install FlashDevelop - along with the SDK. In the case where you installed the SDK to the Program Files location, then you would need to place your extracted.dll on the Program Files location (by default, the folder is located at c:\Program Files\FlashDevelop\). H2: Flashbuilder QuickGuide - Complete Introductory guide for beginners - (1.0.2) H3: Flashbuilder Guide - How to build and compile applications for different platforms. - (1.0.2) H4: Flashbuilder Guide - How to package applications - (1.0.2) H5: Flashbuilder Guide - How to connect to servers H6: Flashbuilder Guide - How to implement interfaces and managers - (1.0.2) H7: Flashbuilder Guide - How to create multimedia applications - (1.0.</p>
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diff --git a/spaces/suppsumstagza/text-to-image-stable-diffusion-v1-5/scripts/Tabellenbuch Metall Pdf _TOP_ Download Kostenlos.md b/spaces/suppsumstagza/text-to-image-stable-diffusion-v1-5/scripts/Tabellenbuch Metall Pdf _TOP_ Download Kostenlos.md
deleted file mode 100644
index 8c10c626feaa7e6fb876cdab8666854cdaa6cef4..0000000000000000000000000000000000000000
--- a/spaces/suppsumstagza/text-to-image-stable-diffusion-v1-5/scripts/Tabellenbuch Metall Pdf _TOP_ Download Kostenlos.md	
+++ /dev/null
@@ -1,36 +0,0 @@
-<h2>Tabellenbuch Metall Pdf Download Kostenlos</h2><br /><p><b><b>Download File</b> &#10004; <a href="https://cinurl.com/2uEXTx">https://cinurl.com/2uEXTx</a></b></p><br /><br />
-
-If you cannot open the pdf you need to click 'Download Now' or 'Download to' and save the file into your computer and then open it.
-
-This is a sample of our sample files. Please select a file and click Open.
-
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-
-I have a copy of my old book for $ Save as PDF. You can also select the Print button at the bottom of the toolbar and print your document if you want.
-
-After clicking print, you will be taken to the preview of your document, and in the left frame you can see the table that you are printing. Now you can select the table you are interested in by clicking on it.
-
-Select 'Copy' and you have the table that you selected.
-
-Tabellenbuch Metall Mit Formelsammlung
-
-With this PDF Editor you will not only be able to copy the table, but also edit it. You can change the width, height and text justification of each column and row. The table title can also be changed and formatted. This makes the table compatible with any table formatting software.
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diff --git a/spaces/suppsumstagza/text-to-image-stable-diffusion-v1-5/scripts/The Design Of Everyday Things Mobi 23 BEST.md b/spaces/suppsumstagza/text-to-image-stable-diffusion-v1-5/scripts/The Design Of Everyday Things Mobi 23 BEST.md
deleted file mode 100644
index 76276152f58bbdf4a5b433949d9469b7ed80d189..0000000000000000000000000000000000000000
--- a/spaces/suppsumstagza/text-to-image-stable-diffusion-v1-5/scripts/The Design Of Everyday Things Mobi 23 BEST.md	
+++ /dev/null
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diff --git a/spaces/sysopo/impira-layoutlm-document-qa/app.py b/spaces/sysopo/impira-layoutlm-document-qa/app.py
deleted file mode 100644
index c80208650f94f0a6bd291fdf0a78afaf1fcf318b..0000000000000000000000000000000000000000
--- a/spaces/sysopo/impira-layoutlm-document-qa/app.py
+++ /dev/null
@@ -1,3 +0,0 @@
-import gradio as gr
-
-gr.Interface.load("models/impira/layoutlm-document-qa").launch()
\ No newline at end of file
diff --git a/spaces/szukevin/VISOR-GPT/train/scripts/convert_bert_text_classification_from_huggingface_to_tencentpretrain.py b/spaces/szukevin/VISOR-GPT/train/scripts/convert_bert_text_classification_from_huggingface_to_tencentpretrain.py
deleted file mode 100644
index 5e9e52862aa7f85948b21e48ac4ccdd86353c07c..0000000000000000000000000000000000000000
--- a/spaces/szukevin/VISOR-GPT/train/scripts/convert_bert_text_classification_from_huggingface_to_tencentpretrain.py
+++ /dev/null
@@ -1,42 +0,0 @@
-import sys
-import os
-import argparse
-import collections
-import torch
-
-tencentpretrain_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
-sys.path.insert(0, tencentpretrain_dir)
-
-from scripts.convert_bert_from_huggingface_to_tencentpretrain import \
-    convert_bert_transformer_encoder_from_huggingface_to_tencentpretrain
-
-
-parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
-parser.add_argument("--input_model_path", type=str, default="models/input_model.bin",
-                    help=".")
-parser.add_argument("--output_model_path", type=str, default="models/output_model.bin",
-                    help=".")
-parser.add_argument("--layers_num", type=int, default=12, help=".")
-
-args = parser.parse_args()
-
-input_model = torch.load(args.input_model_path, map_location="cpu")
-
-output_model = collections.OrderedDict()
-
-output_model["embedding.word.embedding.weight"] = input_model["bert.embeddings.word_embeddings.weight"]
-output_model["embedding.pos.embedding.weight"] = input_model["bert.embeddings.position_embeddings.weight"]
-output_model["embedding.seg.embedding.weight"] = \
-    torch.cat((torch.Tensor([[0]*input_model["bert.embeddings.token_type_embeddings.weight"].size()[1]]),
-               input_model["bert.embeddings.token_type_embeddings.weight"]), dim=0)
-output_model["embedding.layer_norm.gamma"] = input_model["bert.embeddings.LayerNorm.weight"]
-output_model["embedding.layer_norm.beta"] = input_model["bert.embeddings.LayerNorm.bias"]
-
-convert_bert_transformer_encoder_from_huggingface_to_tencentpretrain(input_model, output_model, args.layers_num)
-
-output_model["output_layer_1.weight"] = input_model["bert.pooler.dense.weight"]
-output_model["output_layer_1.bias"] = input_model["bert.pooler.dense.bias"]
-output_model["output_layer_2.weight"] = input_model["classifier.weight"]
-output_model["output_layer_2.bias"] = input_model["classifier.bias"]
-
-torch.save(output_model, args.output_model_path)
diff --git a/spaces/taesiri/ChatGPT-ImageCaptioner/detic/modeling/backbone/timm.py b/spaces/taesiri/ChatGPT-ImageCaptioner/detic/modeling/backbone/timm.py
deleted file mode 100644
index f06b25c8036d99bb6b9518662ab1664a4521b8f5..0000000000000000000000000000000000000000
--- a/spaces/taesiri/ChatGPT-ImageCaptioner/detic/modeling/backbone/timm.py
+++ /dev/null
@@ -1,200 +0,0 @@
-  #!/usr/bin/env python
-# -*- coding: utf-8 -*-
-# Copyright (c) Facebook, Inc. and its affiliates.
-import math
-from os.path import join
-import numpy as np
-import copy
-from functools import partial
-
-import torch
-from torch import nn
-import torch.utils.model_zoo as model_zoo
-import torch.nn.functional as F
-import fvcore.nn.weight_init as weight_init
-
-from detectron2.modeling.backbone import FPN
-from detectron2.modeling.backbone.build import BACKBONE_REGISTRY
-from detectron2.layers.batch_norm import get_norm, FrozenBatchNorm2d
-from detectron2.modeling.backbone import Backbone
-
-from timm import create_model
-from timm.models.helpers import build_model_with_cfg
-from timm.models.registry import register_model
-from timm.models.resnet import ResNet, Bottleneck
-from timm.models.resnet import default_cfgs as default_cfgs_resnet
-
-
-class CustomResNet(ResNet):
-    def __init__(self, **kwargs):
-        self.out_indices = kwargs.pop('out_indices')
-        super().__init__(**kwargs)
-
-
-    def forward(self, x):
-        x = self.conv1(x)
-        x = self.bn1(x)
-        x = self.act1(x)
-        x = self.maxpool(x)
-        ret = [x]
-        x = self.layer1(x)
-        ret.append(x)
-        x = self.layer2(x)
-        ret.append(x)
-        x = self.layer3(x)
-        ret.append(x)
-        x = self.layer4(x)
-        ret.append(x)
-        return [ret[i] for i in self.out_indices]
-
-
-    def load_pretrained(self, cached_file):
-        data = torch.load(cached_file, map_location='cpu')
-        if 'state_dict' in data:
-            self.load_state_dict(data['state_dict'])
-        else:
-            self.load_state_dict(data)
-
-
-model_params = {
-    'resnet50': dict(block=Bottleneck, layers=[3, 4, 6, 3]),
-    'resnet50_in21k': dict(block=Bottleneck, layers=[3, 4, 6, 3]),
-}
-
-
-def create_timm_resnet(variant, out_indices, pretrained=False, **kwargs):
-    params = model_params[variant]
-    default_cfgs_resnet['resnet50_in21k'] = \
-        copy.deepcopy(default_cfgs_resnet['resnet50'])
-    default_cfgs_resnet['resnet50_in21k']['url'] = \
-        'https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/resnet50_miil_21k.pth'
-    default_cfgs_resnet['resnet50_in21k']['num_classes'] = 11221
-
-    return build_model_with_cfg(
-        CustomResNet, variant, pretrained,
-        default_cfg=default_cfgs_resnet[variant],
-        out_indices=out_indices,
-        pretrained_custom_load=True,
-        **params,
-        **kwargs)
-
-
-class LastLevelP6P7_P5(nn.Module):
-    """
-    """
-    def __init__(self, in_channels, out_channels):
-        super().__init__()
-        self.num_levels = 2
-        self.in_feature = "p5"
-        self.p6 = nn.Conv2d(in_channels, out_channels, 3, 2, 1)
-        self.p7 = nn.Conv2d(out_channels, out_channels, 3, 2, 1)
-        for module in [self.p6, self.p7]:
-            weight_init.c2_xavier_fill(module)
-
-    def forward(self, c5):
-        p6 = self.p6(c5)
-        p7 = self.p7(F.relu(p6))
-        return [p6, p7]
-
-
-def freeze_module(x):
-    """
-    """
-    for p in x.parameters():
-        p.requires_grad = False
-    FrozenBatchNorm2d.convert_frozen_batchnorm(x)
-    return x
-
-
-class TIMM(Backbone):
-    def __init__(self, base_name, out_levels, freeze_at=0, norm='FrozenBN'):
-        super().__init__()
-        out_indices = [x - 1 for x in out_levels]
-        if 'resnet' in base_name:
-            self.base = create_timm_resnet(
-                base_name, out_indices=out_indices, 
-                pretrained=False)
-        elif 'eff' in base_name:
-            self.base = create_model(
-                base_name, features_only=True, 
-                out_indices=out_indices, pretrained=True)
-        else:
-            assert 0, base_name
-        feature_info = [dict(num_chs=f['num_chs'], reduction=f['reduction']) \
-            for i, f in enumerate(self.base.feature_info)] 
-        self._out_features = ['layer{}'.format(x) for x in out_levels]
-        self._out_feature_channels = {
-            'layer{}'.format(l): feature_info[l - 1]['num_chs'] for l in out_levels}
-        self._out_feature_strides = {
-            'layer{}'.format(l): feature_info[l - 1]['reduction'] for l in out_levels}
-        self._size_divisibility = max(self._out_feature_strides.values())
-        if 'resnet' in base_name:
-            self.freeze(freeze_at)
-        if norm == 'FrozenBN':
-            self = FrozenBatchNorm2d.convert_frozen_batchnorm(self)
-
-    def freeze(self, freeze_at=0):
-        """
-        """
-        if freeze_at >= 1:
-            print('Frezing', self.base.conv1)
-            self.base.conv1 = freeze_module(self.base.conv1)
-        if freeze_at >= 2:
-            print('Frezing', self.base.layer1)
-            self.base.layer1 = freeze_module(self.base.layer1)
-
-    def forward(self, x):
-        features = self.base(x)
-        ret = {k: v for k, v in zip(self._out_features, features)}
-        return ret
-    
-    @property
-    def size_divisibility(self):
-        return self._size_divisibility
-
-
-@BACKBONE_REGISTRY.register()
-def build_timm_backbone(cfg, input_shape):
-    model = TIMM(
-        cfg.MODEL.TIMM.BASE_NAME, 
-        cfg.MODEL.TIMM.OUT_LEVELS,
-        freeze_at=cfg.MODEL.TIMM.FREEZE_AT,
-        norm=cfg.MODEL.TIMM.NORM,
-    )
-    return model
-
-
-@BACKBONE_REGISTRY.register()
-def build_p67_timm_fpn_backbone(cfg, input_shape):
-    """
-    """
-    bottom_up = build_timm_backbone(cfg, input_shape)
-    in_features = cfg.MODEL.FPN.IN_FEATURES
-    out_channels = cfg.MODEL.FPN.OUT_CHANNELS
-    backbone = FPN(
-        bottom_up=bottom_up,
-        in_features=in_features,
-        out_channels=out_channels,
-        norm=cfg.MODEL.FPN.NORM,
-        top_block=LastLevelP6P7_P5(out_channels, out_channels),
-        fuse_type=cfg.MODEL.FPN.FUSE_TYPE,
-    )
-    return backbone
-
-@BACKBONE_REGISTRY.register()
-def build_p35_timm_fpn_backbone(cfg, input_shape):
-    """
-    """
-    bottom_up = build_timm_backbone(cfg, input_shape)
-    
-    in_features = cfg.MODEL.FPN.IN_FEATURES
-    out_channels = cfg.MODEL.FPN.OUT_CHANNELS
-    backbone = FPN(
-        bottom_up=bottom_up,
-        in_features=in_features,
-        out_channels=out_channels,
-        norm=cfg.MODEL.FPN.NORM,
-        top_block=None,
-        fuse_type=cfg.MODEL.FPN.FUSE_TYPE,
-    )
-    return backbone
\ No newline at end of file
diff --git a/spaces/tangshitao/MVDiffusion/lib/Perspec2Equirec.py b/spaces/tangshitao/MVDiffusion/lib/Perspec2Equirec.py
deleted file mode 100644
index a2dfabffcd221088630a78de7a67ba67e00b0728..0000000000000000000000000000000000000000
--- a/spaces/tangshitao/MVDiffusion/lib/Perspec2Equirec.py
+++ /dev/null
@@ -1,75 +0,0 @@
-import os
-import sys
-import cv2
-import numpy as np
-
-class Perspective:
-    def __init__(self, img_name , FOV, THETA, PHI ):
-        if isinstance(img_name, str):
-            self._img = cv2.imread(img_name, cv2.IMREAD_COLOR)
-        else:
-            self._img = img_name
-        [self._height, self._width, _] = self._img.shape
-        self.wFOV = FOV
-        self.THETA = THETA
-        self.PHI = PHI
-        self.hFOV = float(self._height) / self._width * FOV
-
-        self.w_len = np.tan(np.radians(self.wFOV / 2.0))
-        self.h_len = np.tan(np.radians(self.hFOV / 2.0))
-
-    
-
-    def GetEquirec(self,height,width):
-        #
-        # THETA is left/right angle, PHI is up/down angle, both in degree
-        #
-
-        x,y = np.meshgrid(np.linspace(-180, 180,width),np.linspace(90,-90,height))
-        
-        x_map = np.cos(np.radians(x)) * np.cos(np.radians(y))
-        y_map = np.sin(np.radians(x)) * np.cos(np.radians(y))
-        z_map = np.sin(np.radians(y))
-
-        xyz = np.stack((x_map,y_map,z_map),axis=2)
-
-        y_axis = np.array([0.0, 1.0, 0.0], np.float32)
-        z_axis = np.array([0.0, 0.0, 1.0], np.float32)
-        [R1, _] = cv2.Rodrigues(z_axis * np.radians(self.THETA))
-        [R2, _] = cv2.Rodrigues(np.dot(R1, y_axis) * np.radians(-self.PHI))
-
-        R1 = np.linalg.inv(R1)
-        R2 = np.linalg.inv(R2)
-
-        xyz = xyz.reshape([height * width, 3]).T
-        xyz = np.dot(R2, xyz)
-        xyz = np.dot(R1, xyz).T
-
-        xyz = xyz.reshape([height , width, 3])
-        inverse_mask = np.where(xyz[:,:,0]>0,1,0)
-
-        xyz[:,:] = xyz[:,:]/np.repeat(xyz[:,:,0][:, :, np.newaxis], 3, axis=2)
-        
-        
-        lon_map = np.where((-self.w_len<xyz[:,:,1])&(xyz[:,:,1]<self.w_len)&(-self.h_len<xyz[:,:,2])
-                    &(xyz[:,:,2]<self.h_len),(xyz[:,:,1]+self.w_len)/2/self.w_len*self._width,0)
-        lat_map = np.where((-self.w_len<xyz[:,:,1])&(xyz[:,:,1]<self.w_len)&(-self.h_len<xyz[:,:,2])
-                    &(xyz[:,:,2]<self.h_len),(-xyz[:,:,2]+self.h_len)/2/self.h_len*self._height,0)
-        mask = np.where((-self.w_len<xyz[:,:,1])&(xyz[:,:,1]<self.w_len)&(-self.h_len<xyz[:,:,2])
-                    &(xyz[:,:,2]<self.h_len),1,0)
-
-        persp = cv2.remap(self._img, lon_map.astype(np.float32), lat_map.astype(np.float32), cv2.INTER_CUBIC, borderMode=cv2.BORDER_WRAP)
-        
-        mask = mask * inverse_mask
-        mask = np.repeat(mask[:, :, np.newaxis], 3, axis=2)
-        persp = persp * mask
-        
-        
-        return persp , mask
-        
-
-
-
-
-
-
diff --git a/spaces/tanishqvashisht/horseToZebra/app.py b/spaces/tanishqvashisht/horseToZebra/app.py
deleted file mode 100644
index fd997e4ec26dfcb844d410681f12151fd71e0f0b..0000000000000000000000000000000000000000
--- a/spaces/tanishqvashisht/horseToZebra/app.py
+++ /dev/null
@@ -1,29 +0,0 @@
-import streamlit as st
-import os
-from PIL import Image
-from train import main
-
-st.title("Convert Horse To Zebra")
-st.write("Welcome to the Horse to Zebra Convertor! Choose a horse image and see it displayed below.")
-
-os.makedirs("input", exist_ok=True)
-os.makedirs("saved_images", exist_ok=True)
-
-st.sidebar.title("Choose an image")
-uploaded_file = st.sidebar.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
-
-if uploaded_file is not None:
-    for filename in os.listdir("input"):
-        file_path = os.path.join("input", filename)
-        os.remove(file_path)
-    with open(os.path.join("input", uploaded_file.name), "wb") as f:
-        f.write(uploaded_file.getvalue())
-    st.sidebar.success("Image successfully uploaded!")
-    main()
-
-
-col1, col2 = st.columns(2)
-
-if uploaded_file is not None:
-    col1.image(Image.open(os.path.join("saved_images", "input_0.png")), caption="Uploaded Image", use_column_width=True)
-    col2.image(Image.open(os.path.join("saved_images", "zebra_0.png")), caption="Colorized Image", use_column_width=True)
diff --git a/spaces/tecnolitas/MJ-prompt-generator/app.py b/spaces/tecnolitas/MJ-prompt-generator/app.py
deleted file mode 100644
index 58839cdb7a14947add93cf6cf1b61046abf47197..0000000000000000000000000000000000000000
--- a/spaces/tecnolitas/MJ-prompt-generator/app.py
+++ /dev/null
@@ -1,58 +0,0 @@
-from contextlib import nullcontext
-
-import csv
-import os.path
-import random
-import gradio as gr
-from gradio.components import Textbox, Dropdown
-from gradio import Interface, TabbedInterface
-
-
-def parametroAleatorio(lista):
-    res = random.choice(list(lista))
-    while res == '':
-        res = random.choice(list(lista))
-    return res
-
-
-def make_concat_prompt(csv_reader, valoresUnicos):
-    def concat_prompt(*args):
-        campos = {campo: parametroAleatorio(valoresUnicos[campo]) for campo in csv_reader.fieldnames}
-        campos.update({campo: valor for campo, valor in zip(csv_reader.fieldnames, args) if valor})
-
-        prompt = ', '.join([campos[campo] for campo in csv_reader.fieldnames])
-        return prompt
-    return concat_prompt
-
-
-csv_files = [f for f in os.listdir() if os.path.isfile(f) and f.endswith('.csv')]
-csv_files.sort() # Ordenar alfabéticamente
-
-interfaces = []
-tab_labels = []
-for file_name in csv_files:
-    with open(file_name, 'r') as csv_file:
-        csv_reader = csv.DictReader(csv_file)
-        valoresUnicos = {}
-        for campo in csv_reader.fieldnames:
-            valoresUnicos[campo] = set()
-        for row in csv_reader:
-            for campo, valor in row.items():
-                valoresUnicos[campo].add(valor)
-
-        inputs = [Dropdown(list(valoresUnicos[campo]), label=campo.capitalize()) for campo in valoresUnicos.keys()]
-        output_text = Textbox(label='Prompt')
-
-        tab_label = os.path.splitext(file_name)[0].title()
-        tab_labels.append(tab_label)
-        
-        title = f"Generador Prompts Tecnolitas"
-        description = '<div align="center"> Selecciona entre los distintos menús desplegables para generar un Prompt creativo, los que dejes en blanco serán elegidos aleatoriamente.</div>'
-        fn = make_concat_prompt(csv_reader, valoresUnicos)
-
-       
-        interface = Interface(fn=fn, inputs=inputs, outputs=output_text, title=title, description=description)
-        interfaces.append(interface)
-
-tabbed_interface = TabbedInterface(interfaces, tab_labels)
-tabbed_interface.launch()
\ No newline at end of file
diff --git a/spaces/terfces0erbo/CollegeProjectV2/Download Windows 7 Alienware 32 Bit Iso Torrent Download.md b/spaces/terfces0erbo/CollegeProjectV2/Download Windows 7 Alienware 32 Bit Iso Torrent Download.md
deleted file mode 100644
index 9865b281f366efaf5ae0723df0bb01239ad57675..0000000000000000000000000000000000000000
--- a/spaces/terfces0erbo/CollegeProjectV2/Download Windows 7 Alienware 32 Bit Iso Torrent Download.md	
+++ /dev/null
@@ -1,11 +0,0 @@
-<h2>download windows 7 alienware 32 bit iso torrent download</h2><br /><p><b><b>Download File</b> &#9734;&#9734;&#9734; <a href="https://bytlly.com/2uGiE8">https://bytlly.com/2uGiE8</a></b></p><br /><br />
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-18 Apr 2012 - FEATURES AND OVERVIEW OF ALIENWARE 32-BIT VERSION: Note: Start the new installation from the BIOS and install it in a separate partition. Format the ... AIOSoft Alienware: Alienware Aurora.
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-<p></p>
diff --git a/spaces/terfces0erbo/CollegeProjectV2/Dreyer Schmitt - Grammatica Tedesca Con Esercizi [Pdf - Ita] [ ]Dreyer Schmitt - Grammatica Tedesca.md b/spaces/terfces0erbo/CollegeProjectV2/Dreyer Schmitt - Grammatica Tedesca Con Esercizi [Pdf - Ita] [ ]Dreyer Schmitt - Grammatica Tedesca.md
deleted file mode 100644
index 538fa6c2a325a20bae738de34216ba28c5030c24..0000000000000000000000000000000000000000
--- a/spaces/terfces0erbo/CollegeProjectV2/Dreyer Schmitt - Grammatica Tedesca Con Esercizi [Pdf - Ita] [ ]Dreyer Schmitt - Grammatica Tedesca.md	
+++ /dev/null
@@ -1,6 +0,0 @@
-<h2>Dreyer Schmitt - Grammatica tedesca con esercizi [Pdf - Ita] [ ]Dreyer Schmitt - Grammatica tedesca</h2><br /><p><b><b>Download File</b> &#10026; <a href="https://bytlly.com/2uGkIi">https://bytlly.com/2uGkIi</a></b></p><br /><br />
-
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-<p></p>
diff --git a/spaces/thestasi/Webui-Cpu-ExtensionV2-Publictest-WithCivitaiHelper/app.py b/spaces/thestasi/Webui-Cpu-ExtensionV2-Publictest-WithCivitaiHelper/app.py
deleted file mode 100644
index 40780b89fa7bde1fbc4ae18eb8a6ffa058f3912a..0000000000000000000000000000000000000000
--- a/spaces/thestasi/Webui-Cpu-ExtensionV2-Publictest-WithCivitaiHelper/app.py
+++ /dev/null
@@ -1,69 +0,0 @@
-import os
-from subprocess import getoutput
-
-gpu_info = getoutput('nvidia-smi')
-if("A10G" in gpu_info):
-    os.system(f"pip install -q https://github.com/camenduru/stable-diffusion-webui-colab/releases/download/0.0.16/xformers-0.0.16+814314d.d20230118-cp38-cp38-linux_x86_64.whl")
-elif("T4" in gpu_info):
-    os.system(f"pip install -q https://github.com/camenduru/stable-diffusion-webui-colab/releases/download/0.0.16/xformers-0.0.16+814314d.d20230118-cp38-cp38-linux_x86_64.whl")
-
-os.system(f"git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui /home/user/app/stable-diffusion-webui")
-os.chdir("/home/user/app/stable-diffusion-webui")
-
-os.system(f"wget -q https://github.com/camenduru/webui/raw/main/env_patch.py -O /home/user/app/env_patch.py")
-os.system(f"sed -i -e '/import image_from_url_text/r /home/user/app/env_patch.py' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f"sed -i -e '/(modelmerger_interface, \"Checkpoint Merger\", \"modelmerger\"),/d' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f"sed -i -e '/(train_interface, \"Train\", \"ti\"),/d' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f"sed -i -e '/extensions_interface, \"Extensions\", \"extensions\"/d' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f"sed -i -e '/settings_interface, \"Settings\", \"settings\"/d' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f'''sed -i -e "s/document.getElementsByTagName('gradio-app')\[0\].shadowRoot/!!document.getElementsByTagName('gradio-app')[0].shadowRoot ? document.getElementsByTagName('gradio-app')[0].shadowRoot : document/g" /home/user/app/stable-diffusion-webui/script.js''')
-os.system(f"sed -i -e 's/                show_progress=False,/                show_progress=True,/g' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f"sed -i -e 's/shared.demo.launch/shared.demo.queue().launch/g' /home/user/app/stable-diffusion-webui/webui.py")
-os.system(f"sed -i -e 's/inputs=\[component\],/&\\n                queue=False,/g' /home/user/app/stable-diffusion-webui/modules/ui.py")
-os.system(f"sed -i -e 's/outputs=\[token_counter\]/outputs=[token_counter], queue=False/g' /home/user/app/stable-diffusion-webui/modules/ui.py")
-
-# ----------------------------Please duplicate this space and delete this block if you don't want to see the extra header----------------------------
-#os.system(f"wget -q https://github.com/camenduru/webui/raw/main/header_patch.py -O /home/user/app/header_patch.py")
-#os.system(f"sed -i -e '/demo:/r /home/user/app/header_patch.py' /home/user/app/stable-diffusion-webui/modules/ui.py")
-# ---------------------------------------------------------------------------------------------------------------------------------------------------
-
-os.system(f"wget -q https://huggingface.co/Alsebay/PeachMixs/resolve/main/PeachTachyonMixs/PeachTachyon2.safetensors -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/PeachTachyon2.safetensors")
-os.system(f"wget -q https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt -O /home/user/app/stable-diffusion-webui/models/VAE/vae-ft-mse-840000-ema-pruned.ckpt")
-os.system(f"git clone https://github.com/yfszzx/stable-diffusion-webui-images-browser /home/user/app/stable-diffusion-webui/extensions/stable-diffusion-webui-images-browser")
-if "IS_SHARED_UI" in os.environ:
-    os.system(f"wget -q https://github.com/camenduru/webui/raw/main/shared-config.json -O /home/user/app/shared-config.json")
-    os.system(f"wget -q https://github.com/camenduru/webui/raw/main/shared-ui-config.json -O /home/user/app/shared-ui-config.json")
-    os.system(f"python launch.py --use-cpu all --disable-console-progressbars --enable-console-prompts --ui-config-file /home/user/app/shared-ui-config.json --ui-settings-file /home/user/app/shared-config.json --cors-allow-origins huggingface.co,hf.space --no-progressbar-hiding --skip-torch-cuda-test")
-else:
-    # Please duplicate this space and delete # character in front of the custom script you want to use or add here more custom scripts with same structure os.system(f"wget -q https://CUSTOM_SCRIPT_URL -O /home/user/app/stable-diffusion-webui/scripts/CUSTOM_SCRIPT_NAME.py")
-    #os.system(f"wget -q https://gist.github.com/camenduru/9ec5f8141db9902e375967e93250860f/raw/d0bcf01786f20107c329c03f8968584ee67be12a/run_n_times.py -O /home/user/app/stable-diffusion-webui/scripts/run_n_times.py")
-    
-    # Please duplicate this space and delete # character in front of the extension you want to use or add here more extensions with same structure os.system(f"git clone https://EXTENSION_GIT_URL /home/user/app/stable-diffusion-webui/extensions/EXTENSION_NAME")
-    os.system(f"git clone https://github.com/camenduru/stable-diffusion-webui-artists-to-study /home/user/app/stable-diffusion-webui/extensions/stable-diffusion-webui-artists-to-study")
-    os.system(f"git clone https://github.com/butaixianran/Stable-Diffusion-Webui-Civitai-Helper /home/user/app/stable-diffusion-webui/extensions/Stable-Diffusion-Webui-Civitai-Helper")
-    os.system(f"git clone https://github.com/kohya-ss/sd-webui-additional-networks /home/user/app/stable-diffusion-webui/extensions/sd-webui-additional-networks")
-    os.system(f"wget -q https://huggingface.co/qewadszcx132/hyperbreasts/resolve/main/hyperbreasts_v4.ckpt -O /home/user/app/stable-diffusion-webui/extensions/sd-webui-additional-networks/models/lora/hyperbreasts_v4.ckpt")
-    os.system(f"wget -q https://huggingface.co/Osmond141319/Hyperbreasts/resolve/main/hyperbreasts_v5Lora.ckpt -O /home/user/app/stable-diffusion-webui/extensions/sd-webui-additional-networks/models/lora/hyperbreasts_v5.ckpt")
-    #os.system(f"git clone https://github.com/yfszzx/stable-diffusion-webui-images-browser /home/user/app/stable-diffusion-webui/extensions/stable-diffusion-webui-images-browser")
-    #os.system(f"git clone https://github.com/deforum-art/deforum-for-automatic1111-webui /home/user/app/stable-diffusion-webui/extensions/deforum-for-automatic1111-webui")
-    
-    # Please duplicate this space and delete # character in front of the model you want to use or add here more ckpts with same structure os.system(f"wget -q https://CKPT_URL -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/CKPT_NAME.ckpt")
-    os.system(f"wget -q https://huggingface.co/andite/anything-v4.0/resolve/main/anything-v4.5-pruned.safetensors -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/Anything-v4.5-pruned.safetensors")
-    #os.system(f"wget -q https://huggingface.co/WarriorMama777/OrangeMixs/resolve/main/Models/AbyssOrangeMix3/AOM3.safetensors -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/AbyssOrangeMix3.safetensors")
-    #os.system(f"wget -q https://huggingface.co/nitrosocke/Arcane-Diffusion/resolve/main/arcane-diffusion-v3.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/arcane-diffusion-v3.ckpt")
-    #os.system(f"wget -q https://huggingface.co/DGSpitzer/Cyberpunk-Anime-Diffusion/resolve/main/Cyberpunk-Anime-Diffusion.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/Cyberpunk-Anime-Diffusion.ckpt")
-    #os.system(f"wget -q https://huggingface.co/prompthero/midjourney-v4-diffusion/resolve/main/mdjrny-v4.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/mdjrny-v4.ckpt")
-    #os.system(f"wget -q https://huggingface.co/nitrosocke/mo-di-diffusion/resolve/main/moDi-v1-pruned.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/moDi-v1-pruned.ckpt")
-    #os.system(f"wget -q https://huggingface.co/Fictiverse/Stable_Diffusion_PaperCut_Model/resolve/main/PaperCut_v1.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/PaperCut_v1.ckpt")
-    #os.system(f"wget -q https://huggingface.co/lilpotat/sa/resolve/main/samdoesarts_style.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/samdoesarts_style.ckpt")
-    #os.system(f"wget -q https://huggingface.co/hakurei/waifu-diffusion-v1-3/resolve/main/wd-v1-3-float32.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/wd-v1-3-float32.ckpt")
-    #os.system(f"wget -q https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/sd-v1-4.ckpt")
-    #os.system(f"wget -q https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/v1-5-pruned-emaonly.ckpt")
-    #os.system(f"wget -q https://huggingface.co/runwayml/stable-diffusion-inpainting/resolve/main/sd-v1-5-inpainting.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/sd-v1-5-inpainting.ckpt")
-    #os.system(f"wget -q https://huggingface.co/stabilityai/stable-diffusion-2/resolve/main/768-v-ema.ckpt -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/768-v-ema.ckpt")
-    #os.system(f"wget -q https://raw.githubusercontent.com/Stability-AI/stablediffusion/main/configs/stable-diffusion/v2-inference-v.yaml -O /home/user/app/stable-diffusion-webui/models/Stable-diffusion/768-v-ema.yaml")
-    os.system(f"EXPOSE 7860")
-    #os.system(f"git clone https://github.com/yfszzx/stable-diffusion-webui-images-browser /home/user/app/stable-diffusion-webui/extensions/stable-diffusion-webui-images-browser")
-    #os.system(f"wget -q https://github.com/camenduru/webui/raw/main/shared-config.json -O /home/user/app/shared-config.json")
-    # os.system(f"wget -q https://github.com/camenduru/webui/raw/main/shared-ui-config.json -O /home/user/app/shared-ui-config.json")
-    os.system(f"python launch.py --precision full --no-half --use-cpu all --listen --ui-config-file /home/user/app/ui-config.json --ui-settings-file /home/user/app/config.json --cors-allow-origins huggingface.co,hf.space --no-progressbar-hiding --skip-torch-cuda-test")
diff --git a/spaces/tialenAdioni/chat-gpt-api/logs/Akvis Sketch Activation Code.epub.md b/spaces/tialenAdioni/chat-gpt-api/logs/Akvis Sketch Activation Code.epub.md
deleted file mode 100644
index 04eee04de09135693539430984fbb6092b2d5c94..0000000000000000000000000000000000000000
--- a/spaces/tialenAdioni/chat-gpt-api/logs/Akvis Sketch Activation Code.epub.md	
+++ /dev/null
@@ -1,43 +0,0 @@
-
-<h1>How to Activate AKVIS Sketch Software with a Serial Number</h1>
-<p>AKVIS Sketch is a software that converts photos into realistic pencil drawings. You can download a free trial version of the software from the official website[^3^] and use it for 10 days. To continue using the software after the trial period, you need to buy a license and activate it with a serial number.</p>
-<p>In this article, we will show you how to activate AKVIS Sketch software with a serial number using direct connection or by e-mail. You will need an Internet connection for both methods.</p>
-<h2>Akvis Sketch Activation Code.epub</h2><br /><p><b><b>DOWNLOAD</b> ::: <a href="https://urlcod.com/2uK6co">https://urlcod.com/2uK6co</a></b></p><br /><br />
-<h2>Direct Connection</h2>
-<ol>
-<li>Run AKVIS Sketch and open the About the Program window by clicking on the button in the Control Panel or by selecting Help -> About from the menu.</li>
-<li>Click on ACTIVATE to start the activation process.</li>
-<li>Enter your name (the program will be registered to this name).</li>
-<li>Enter your serial number (your license key).</li>
-<li>Choose Direct connection as the method of activation and press ACTIVATE .</li>
-<li>Your registration is completed! You can enjoy the full features of AKVIS Sketch software.</li>
-</ol>
-<h2>By E-mail</h2>
-<ol>
-<li>Run AKVIS Sketch and open the About the Program window by clicking on the button in the Control Panel or by selecting Help -> About from the menu.</li>
-<li>Click on ACTIVATE to start the activation process.</li>
-<li>Enter your name (the program will be registered to this name).</li>
-<li>Enter your serial number (your license key).</li>
-<li>Choose By e-mail as the method of activation and press ACTIVATE .</li>
-<li>A message with all necessary information will be created by the program. Copy this message and send it to activate@akvis.com .</li>
-<li>You will receive a reply with a license file ( Sketch.lic ) attached. Save this file to your computer where you want to register the software, in the AKVIS folder in Users’ Shared (Public) Documents:</li>
-<ul>
-<li>Windows: C:\\Users\\Public\\Documents\\AKVIS</li>
-<li>Mac: /Users/Shared/AKVIS</li>
-<li>Linux: /var/lib/AKVIS</li>
-</ul>
-<li>Your registration is completed! You can enjoy the full features of AKVIS Sketch software.</li>
-</ol><h3>Tips and Tricks for Using AKVIS Sketch Software</h3>
-<p>AKVIS Sketch software is a powerful and easy-to-use tool for creating realistic pencil drawings from photos. Here are some tips and tricks to help you get the most out of it:</p>
-<ul>
-<li>Use high-quality photos with good contrast and sharp details. Avoid blurry, noisy, or overexposed images.</li>
-<li>Experiment with different settings and presets to find the best combination for your photo. You can adjust the drawing style, the edge strength, the stroke thickness, the midtone intensity, the coloration, and more.</li>
-<li>Use the Stroke Direction tool to guide the direction of the pencil strokes. This can help you create more expressive and dynamic drawings.</li>
-<li>Use the Eraser tool to erase unwanted areas or details from your drawing. You can also use the History Brush tool to restore the original image in some parts.</li>
-<li>Use the Background tab to change the background of your drawing. You can choose a solid color, a gradient, a texture, or a sketch from another photo.</li>
-<li>Use the Decoration tab to add a watermark, a text, a frame, or a canvas texture to your drawing. You can customize the size, position, opacity, and color of these elements.</li>
-<li>Use the Share button to save your drawing as an image file or share it on social media.</li>
-</ul>
-<p>With AKVIS Sketch software, you can turn any photo into a stunning pencil drawing in minutes. Try it today and unleash your creativity!</p> e93f5a0c3f<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/tialenAdioni/chat-gpt-api/logs/Chicken Invaders 5 Crash Fix A Guide to Enjoy the Full Version with Multiplayer Mode.md b/spaces/tialenAdioni/chat-gpt-api/logs/Chicken Invaders 5 Crash Fix A Guide to Enjoy the Full Version with Multiplayer Mode.md
deleted file mode 100644
index 1c8e76de3a5c85bf4ed09d9a199323cc147fba1d..0000000000000000000000000000000000000000
--- a/spaces/tialenAdioni/chat-gpt-api/logs/Chicken Invaders 5 Crash Fix A Guide to Enjoy the Full Version with Multiplayer Mode.md	
+++ /dev/null
@@ -1,210 +0,0 @@
-
-<h1>BPM Studio Pro 4.9.9.4 Crack Download: A Guide for DJs and Music Enthusiasts</h1>
-
-<p>If you are looking for a powerful and professional software to mix, edit and write music tracks with MP3 files, you might want to consider BPM Studio Pro 4.9.9.4 crack download. This software is based on the famous Denon 2000F program that was used by many DJs in the nineties, and it has all the features you need to unleash your creative potential as a DJ.</p>
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-<h2>What is BPM Studio Pro 4.9.9.4?</h2>
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-<p>BPM Studio Pro 4.9.9.4 is a recording suite that lets you listen to, edit, mix and write music tracks with MP3 files. It has a complex and intimidating interface that is strongly structured for professionals, but it also has a useful searching system and a relatively easy access point to your MP3 collection.</p>
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-<p>Some of the core features of BPM Studio Pro 4.9.9.4 are:</p>
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-<ul>
-<li>Real-time Loop Sampling: You can create loops from any track and use them in your mixes.</li>
-<li>Exact Beat Matching: You can synchronize the tempo and pitch of two tracks automatically or manually.</li>
-<li>Direct-Cue: You can access up to 6 different cue points per track and jump to them instantly.</li>
-<li>Integrated CD Writer: You can burn your mixes directly to CD without leaving the software.</li>
-<li>BPM-RemoteAccess: You can control the software remotely via Telnet or HTML commands.</li>
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-<h2>How to Download and Install BPM Studio Pro 4.9.9.4 Crack?</h2>
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-<p>If you want to try BPM Studio Pro 4.9.9.4 crack download, you will need to follow these steps:</p>
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-<ol>
-<li>Download the software from a reliable source, such as <a href="https://bpm-studio-pro.soft32.com/">https://bpm-studio-pro.soft32.com/</a>.</li>
-<li>Extract the ZIP file and run the setup.exe file.</li>
-<li>Follow the installation wizard and choose the destination folder.</li>
-<li>Copy the crack file from the crack folder and paste it into the installation folder.</li>
-<li>Run the software and enjoy!</li>
-</ol>
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-<h2>What are the Pros and Cons of BPM Studio Pro 4.9.9.4 Crack Download?</h2>
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-<p>BPM Studio Pro 4.9.9.4 crack download has many advantages and disadvantages that you should consider before using it.</p>
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-<p>Some of the pros are:</p>
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-<ul>
-<li>It has a lot of features and tools that allow you to create professional mixes with MP3 files.</li>
-<li>It has a streaming option that lets you use the software as an Internet Radio Frontend Software.</li>
-<li>It offers compatibility with 19-inch controllers that are a replica of the classic Denon CD-1000 players.</li>
-</ul>
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-<p>Some of the cons are:</p>
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-<ul>
-<li>It has a high price tag of $650 for a full-license, which might be too expensive for some users.</li>
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-<h2>Conclusion</h2>
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-<p>BPM Studio Pro 4.9.9.4 crack download is a powerful and professional software that lets you mix, edit and write music tracks with MP3 files. It has many features and tools that can help you unleash your creative potential as a DJ, but it also has some drawbacks that might discourage some users from using it.</p>
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-<p>However, if you want to support the developers and get the full version of the software, you can buy it from <a href="https://www.alcatech.de/en/bpm-studio-professional/">https://www.alcatech.de/en/bpm-studio-professional/</a>.</p>
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-<p>We hope this article was helpful for you and gave you some insights into BPM Studio Pro 4.9.9.4 crack download.</p>
-<h2>How to Use BPM Studio Pro 4.9.9.4 Crack?</h2>
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-<p>Once you have downloaded and installed BPM Studio Pro 4.9.9.4 crack, you can start using it to create your own music mixes with MP3 files. Here are some basic steps to get you started:</p>
-
-<ol>
-<li>Launch the software and select the tracks you want to mix from your MP3 collection or from the CD unit.</li>
-<li>Drag and drop the tracks to the left or right player, or use the Direct-Cue buttons to load them instantly.</li>
-<li>Use the pitch and tempo sliders to adjust the speed and pitch of each track, or use the Auto BPM button to match them automatically.</li>
-<li>Use the crossfader to blend the tracks smoothly, or use the Fade buttons to switch between them quickly.</li>
-<li>Use the Loop buttons to create loops from any part of the track, or use the Sample buttons to record and play samples.</li>
-<li>Use the Equalizer buttons to adjust the sound quality of each track, or use the Preset buttons to choose from 5 different presets.</li>
-<li>Use the Record button to record your mix as a WAV file, or use the CD Writer button to burn it directly to CD.</li>
-</ol>
-
-<h2>What are the Alternatives to BPM Studio Pro 4.9.9.4 Crack?</h2>
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-<p>BPM Studio Pro 4.9.9.4 crack is a great software for mixing MP3 files, but it is not the only one available on the market. If you are looking for some alternatives, you might want to check out these other programs:</p>
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-<ul>
-<li><a href="https://www.virtualdj.com/">Virtual DJ</a>: This is a popular and versatile software that lets you mix audio and video files with a variety of effects and features.</li>
-<li><a href="https://www.serato.com/dj/pro">Serato DJ Pro</a>: This is a professional and reliable software that lets you mix music with high-quality sound and performance.</li>
-<li><a href="https://www.mixxx.org/">Mixxx</a>: This is a free and open-source software that lets you mix music with advanced features and compatibility.</li>
-</ul>
-
-<h2>Is BPM Studio Pro 4.9.9.4 Crack Safe and Legal?</h2>
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-<p>BPM Studio Pro 4.9.9.4 crack is a modified version of the original software that bypasses its security and license system. This means that it is not safe and legal to use it, as it may contain viruses, malware, or other harmful components that can damage your computer or compromise your privacy.</p>
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-<p>Moreover, using BPM Studio Pro 4.9.9.4 crack is a violation of the intellectual property rights of the developers, who have invested time and money to create and maintain the software. By using BPM Studio Pro 4.9.9.4 crack, you are depriving them of their rightful income and support.</p>
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-<p>Therefore, we do not recommend using BPM Studio Pro 4.9.9.4 crack, as it may expose you to legal and ethical issues, as well as potential risks for your computer and data.</p>
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-<p>If you want to use BPM Studio Pro 4.9.9.4 safely and legally, you should buy it from <a href="https://www.alcatech.de/en/bpm-studio-professional/">https://www.alcatech.de/en/bpm-studio-professional/</a>, where you can get a full-license for $650.</p>
-<h2>What are the Benefits of BPM Studio Pro 4.9.9.4 Crack Download?</h2>
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-<p>BPM Studio Pro 4.9.9.4 crack download can offer you many benefits if you want to create your own music mixes with MP3 files. Here are some of them:</p>
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-<ul>
-<li>You can save money by using a cracked version of the software instead of buying the full-license.</li>
-<li>You can access all the features and tools of the software without any limitations or restrictions.</li>
-<li>You can enjoy the software without any annoying ads or pop-ups.</li>
-<li>You can use the software offline without any internet connection.</li>
-<li>You can share your mixes with your friends or online without any copyright issues.</li>
-</ul>
-
-<h2>What are the Risks of BPM Studio Pro 4.9.9.4 Crack Download?</h2>
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-<p>BPM Studio Pro 4.9.9.4 crack download can also pose some risks if you decide to use it. Here are some of them:</p>
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-<ul>
-<li>You can expose your computer to viruses, malware, or other harmful components that can damage your system or compromise your data.</li>
-<li>You can face legal and ethical issues for violating the intellectual property rights of the developers and depriving them of their income and support.</li>
-<li>You can lose your data or mixes if the software crashes or stops working unexpectedly.</li>
-<li>You can miss out on the updates, bug fixes, and new features that the developers release for the software.</li>
-<li>You can have compatibility issues with other software or hardware that you use for mixing or recording.</li>
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-<h2>How to Uninstall BPM Studio Pro 4.9.9.4 Crack?</h2>
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-<p>If you want to uninstall BPM Studio Pro 4.9.9.4 crack from your computer, you will need to follow these steps:</p>
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-<ol>
-<li>Go to the Control Panel and select Programs and Features.</li>
-<li>Find BPM Studio Pro 4.9.9.4 in the list of installed programs and click on Uninstall.</li>
-<li>Follow the uninstallation wizard and confirm your choice.</li>
-<li>Delete the installation folder and any leftover files or shortcuts from your computer.</li>
-<li>Restart your computer to complete the process.</li>
-</ol>
-<h2>How to Learn BPM Studio Pro 4.9.9.4 Crack?</h2>
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-<p>BPM Studio Pro 4.9.9.4 crack is a complex and advanced software that requires some skills and knowledge to use it effectively. If you want to learn BPM Studio Pro 4.9.9.4 crack, you can use these resources to help you:</p>
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-<ul>
-<li>The user manual and instructions that come with the software, which explain the features and functions of the software in detail.</li>
-<li>The online tutorials and videos that show you how to use the software step by step, such as <a href="https://www.youtube.com/watch?v=Z0r7y1Y0Z6Q">https://www.youtube.com/watch?v=Z0r7y1Y0Z6Q</a>.</li>
-<li>The online forums and communities that offer tips, tricks, and support for the software users, such as <a href="https://www.facebook.com/BPMStudio/">https://www.facebook.com/BPMStudio/</a>.</li>
-<li>The online courses and books that teach you the basics and advanced techniques of mixing and DJing with the software, such as <a href="https://www.udemy.com/course/bpm-studio-pro/">https://www.udemy.com/course/bpm-studio-pro/</a>.</li>
-</ul>
-
-<h2>How to Compare BPM Studio Pro 4.9.9.4 Crack with Other Software?</h2>
-
-<p>BPM Studio Pro 4.9.9.4 crack is one of the many software that you can use to mix, edit and write music tracks with MP3 files. If you want to compare BPM Studio Pro 4.9.9.4 crack with other software, you can use these criteria to evaluate them:</p>
-
-<ul>
-<li>The quality and quantity of features and tools that they offer for mixing MP3 files.</li>
-<li>The ease of use and accessibility of their interface and controls.</li>
-<li>The performance and stability of their operation and output.</li>
-<li>The compatibility and integration with other software or hardware that you use for mixing or recording.</li>
-<li>The price and value that they provide compared to other similar software on the market.</li>
-<li>The reviews and ratings that they receive from other users online.</li>
-</ul>
-
-<p>Some examples of other software that you can compare BPM Studio Pro 4.9.9.4 crack with are:</p>
-
-<ul>
-<li><a href="https://www.virtualdj.com/">Virtual DJ</a></li>
-<li><a href="https://www.serato.com/dj/pro">Serato DJ Pro</a></li>
-<li><a href="https://www.mixxx.org/">Mixxx</a></li>
-</ul>
-
-<h2>How to Share BPM Studio Pro 4.9.9.4 Crack with Others?</h2>
-
-<p>BPM Studio Pro 4.9.9.4 crack is a modified version of the original software that lets you share your mixes with others without any copyright issues.</p>
-
-<p>If you want to share BPM Studio Pro 4.9.9.4 crack with others, you can use these methods to do so:</p>
-
-<ul>
-<li>You can burn your mixes to CD using the integrated CD writer feature of the software, and then give them to your friends or clients.</li>
-<li>You can upload your mixes to online platforms or websites that allow you to share music files, such as <a href="https://soundcloud.com/">SoundCloud</a> or <a href="https://www.mixcloud.com/">Mixcloud</a>.</li>
-<li>You can stream your mixes live using the streaming option of the software, and then invite your listeners to join you online.</li>
-<li>You can send your mixes via email or instant messaging using the file sharing feature of the software, and then ask your recipients to download them.</li>
-</ul>
-<h2>Conclusion</h2>
-
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\ No newline at end of file
diff --git a/spaces/tialenAdioni/chat-gpt-api/logs/Crack menfis 8 espanol Actualizaciones y novedades de la ltima versin.md b/spaces/tialenAdioni/chat-gpt-api/logs/Crack menfis 8 espanol Actualizaciones y novedades de la ltima versin.md
deleted file mode 100644
index 4cab3957dd6f34f192a54a0ffe9b9ee7df07bf13..0000000000000000000000000000000000000000
--- a/spaces/tialenAdioni/chat-gpt-api/logs/Crack menfis 8 espanol Actualizaciones y novedades de la ltima versin.md	
+++ /dev/null
@@ -1,167 +0,0 @@
-<br />
-<h1>Honestech Tvr 3.0 Free Download: A Complete Guide</h1>
- <p>Do you want to turn your PC into a full-featured digital video recorder for TV? Do you want to enjoy real-time MPEG1, MPEG2, VCD, SVCD and DVD recording and playback? Do you want to have a built-in MPEG editor and video mail forwarding capability? If you answered yes to any of these questions, then you might be interested in Honestech Tvr 3.0, a software that can do all these things and more.</p>
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- <h2>What is Honestech Tvr 3.0?</h2>
- <p>Honestech Tvr 3.0 is a software that turns your PC into a digital video recorder for TV. It allows you to watch TV on your PC, record TV shows, edit recorded files, and send video mails.</p>
- <p>Honestech Tvr 3.0 works with TV devices connected to your PC, such as TV cards, VCRs, or analog camcorders. It supports NTSC/PAL simultaneously and MTS (Multi-channel TV Sound) support.</p>
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- <p>Honestech Tvr 3.0 encodes and compresses video data in real-time from these devices and saves them as MPEG1, MPEG2, VCD, SVCD, DVD or AVI files.</p>
- <h3>Features and benefits of Honestech Tvr 3.0</h3>
- <p>Some of the features and benefits of Honestech Tvr 3.0 are:</p>
- <ul>
-<li>Real-time MPEG1, MPEG2, VCD, SVCD and DVD recording and playback.</li>
-<li>Time-shift function that allows you to instantly replay certain scenes.</li>
-<li>Video CD/DVD compliant.</li>
-<li>Automatic channel configuration that lets you add, delete, edit, sort and scan channels.</li>
-<li>Mode changing function that lets you choose between TVR shutdown, system shutdown or stand-by mode after finish schedule recording.</li>
-<li>Supports All-in-wonder card.</li>
-<li>Enhanced recording video quality and CPU consumption.</li>
-<li>Built-in MPEG editor that lets you cut, paste and merge video clips.</li>
-<li>Built-in video mail forwarding capability that lets you send video mails via email or FTP.</li>
-</ul>
- <h3>How to install Honestech Tvr 3.0</h3>
- <p>To install Honestech Tvr 3.0 on your PC, you need to follow these steps:</p>
- <ol>
-<li>Download the installation kit from a reliable source (we will provide some links later).</li>
-<li>Run the autorun.exe file to launch the installation kit.</li>
-<li>Select the second option - installation for blaze video HDTV player - NOT the first one HT TVR 3.0.</li>
-<li>Install the driver (first option) and the HDTV player (second option) as instructed by the wizard.</li>
-<li>Input your email and the serial number located at the back of the CD disk cover (if you have one).</li>
-<li>Connect your TV device (TV card, VCR or analog camcorder) to your PC via USB or other ports.</li>
-<li>You are ready to use Honestech Tvr 3.0!</li>
-</ol>
- <h2>How to use Honestech Tvr 3.0</h2>
- <p>Once you have installed Honestech Tvr 3.0 on your PC, you can start using it to watch TV, record TV shows, edit recorded files and send video mails.</p>
- <h3>How to watch TV on your PC with Honestech Tvr 3.0</h3>
- <p>To watch TV on your PC with Honestech Tvr 3.0, you need to follow these steps:</p>
- <ol>
-<li>Launch the HDTV player software from your desktop or start menu.</li>
-<li>Select the source of your TV signal (antenna, cable or satellite).</li>
-<li>Select the country or region of your TV signal (USA/Canada/Mexico/South America/Europe/Asia/Australia).</li>
-<li>Select the channel type (analog or digital).</li>
-<li>Select the scan mode (auto or manual) and start scanning for channels.</li>
-<li>You will see a list of available channels on the left panel and a preview window on the right panel.</li>
-<li>Select a channel from the list or use the up/down arrow keys on your keyboard or remote control (if you have one) to change channels.</li>
-<li>You can adjust the volume using the slider or the +/– keys on your keyboard or remote control.</li>
-<li>You can also use other functions such as mute, pause/playback/record/stop/snapshot/timeshift/fullscreen/channel surfing/channel list/channel manager/favorite list/video adjustment/audio adjustment/subtitle/teletext/EPG/schedule recording/video mail etc.</li>
-</ol>
- <h3>How to record TV shows with Honestech Tvr 3.0</h3>
- <p>To record TV shows with Honestech Tvr 3.0, you need to follow these steps:</p>
- <ol>
-<li>Select a channel that you want to record from the list or preview window.</li>
-<li>Click on the record button on the toolbar or press Ctrl+R on your keyboard or remote control.</li>
-<li>A dialog box will pop up asking you to select a file name, folder location, file format (MPEG1/MPEG2/VCD/SVCD/DVD/AVI), video quality (low/medium/high), audio quality (low/medium/high), duration (in minutes) and start time (now/later).</li>
-<li>If you select later as start time, you can set a specific date and time for recording using the calendar and clock icons.</li>
-<li>Click OK to confirm your settings and start recording.</li>
-<li>You can see a red dot on the top left corner of the preview window indicating that recording is in progress.</li>
-<li>You can stop recording anytime by clicking on the stop button on the toolbar or pressing Ctrl+S on your keyboard or remote control.</li>
-<li>You can find your recorded files in the folder location that you specified earlier.</li>
-</ol>
- <h3>How to edit recorded files with Honestech Tvr 3.0</h3>
- <p>To edit recorded files with Honestech Tvr 3.0, you need to follow these steps:</p>
- <ol>
-<li>Launch the MPEG editor software from your desktop or start menu.</li>
-<li>Select open file from the file menu or click on the open file button on the toolbar or press Ctrl+O on your keyboard.</li>
-<li>Browse for the recorded file that you want to edit and click open.</li>
-<li>You will see a timeline at the bottom of the window showing frames of your recorded file.</li>
-<li>You can use various tools such as cut/copy/paste/delete/merge/split/crop/zoom/move/rotate/flip/add text/add transition/add effect etc. to edit your recorded file as you wish.</li>
-<li>You can preview your edited file in the preview window on the right panel.</li>
-<li>You can save your edited file as a new file by selecting save as from the file menu or clicking on the save as button on the toolbar or pressing Ctrl+Shift+S on your keyboard or remote control.</li>
-<li>You can also export your edited file to various formats such as MPEG1/MPEG2/VCD/SVCD/DVD/AVI by selecting export from the file menu or clicking on the export button on the toolbar or pressing Ctrl+E on your keyboard or remote control.</li>
-<li>You can choose the output format, quality, size and destination folder for your exported file.</li>
-</ol>
- <h2>How to get Honestech Tvr 3.0 for free</h2>
- <p>If you want to get Honestech Tvr 3.0 for free, you need to be careful and follow some tips and warnings. Here are some of them:</p>
- <h3>Download links and sources for Honestech Tvr 3.0</h3>
- <p>There are many websites that claim to offer Honestech Tvr 3.0 for free download, but not all of them are reliable or safe. Some of them may contain viruses, malware, spyware or other harmful programs that can damage your PC or steal your personal information.</p>
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- <p>Here are some of the download links and sources for Honestech Tvr 3.0 that we have found:</p>
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-<li><a href="https://honestech-tvr.apponic.com/">https://honestech-tvr.apponic.com/</a></li>
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-<li><a href="https://archive.org/details/honestech_VHS_to_DVD_3.0_SE">https://archive.org/details/honestech_VHS_to_DVD_3.0_SE</a></li>
-<li><a href="https://archive.org/details/Honestech_TVR_2.5">https://archive.org/details/Honestech_TVR_2.5</a></li>
-<li><a href="https://www.updatestar.com/en/topic/honestech%20tvr%203.0">https://www.updatestar.com/en/topic/honestech%20tvr%203.0</a></li>
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- <p>Before you download Honestech Tvr 3.0 from any of the sources above, you should follow some tips and warnings to ensure a safe and successful download.</p>
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-<li>Make sure your PC meets the system requirements for Honestech Tvr 3.0 (see above).</li>
-<li>Make sure you have a reliable internet connection and enough disk space for the download.</li>
-<li>Scan the downloaded file with an antivirus program before opening it.</li>
-<li>Follow the installation instructions carefully and enter the serial number if required (see above).</li>
-<li>Do not download Honestech Tvr 3.0 from unknown or suspicious websites or links.</li>
-<li>Do not install any additional software or toolbars that may come with the download.</li>
-<li>Do not share your serial number or personal information with anyone.</li>
-<li>Do not use Honestech Tvr 3.0 for illegal or unethical purposes.</li>
-</ul>
- <h2>Conclusion</h2>
- <h4>Summary of the main points</h4>
- <p>In this article, we have given you a complete guide on Honestech Tvr 3.0 Free Download. We have explained what Honestech Tvr 3.0 is, how to install it, how to use it, and how to get it for free.</p>
- <p>We have also provided some features and benefits of Honestech Tvr 3.0, as well as some tips and warnings for downloading it safely and successfully.</p>
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- <p>If you are interested in Honestech Tvr 3.0 and want to try it out on your PC, we encourage you to download it from one of the sources that we have mentioned above.</p>
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- <p>Hurry up and get Honestech Tvr 3.0 for free today!</p>
- <h4>FAQs</h4>
- <p>Here are some frequently asked questions about Honestech Tvr 3.0:</p>
- <ol>
-<li><b>What is the difference between HT TVR 3.0 and HDTV Player?</b><br>Honestech Tvr 3.0 is a software that turns your PC into a digital video recorder for TV, while HDTV Player is a software that lets you watch high-definition TV on your PC. They are both included in the installation kit of Honestech Tvr 3.0.</li>
-<li><b>Can I use Honestech Tvr 3.0 with any TV device?</b><br>Honestech Tvr 3.0 works with TV devices connected to your PC via USB or other ports, such as TV cards, VCRs, or analog camcorders. It supports NTSC/PAL simultaneously and MTS (Multi-channel TV Sound) support.</li>
-<li><b>Can I use Honestech Tvr 3.0 on Windows 10?</b><br>Honestech Tvr 3.0 is compatible with Windows XP, Windows 2000, Windows 98, Windows Me, and Windows NT operating systems. It may not work properly on Windows 10 or other newer versions of Windows.</li>
-<li><b>How can I get a serial number for Honestech Tvr 3.0?</b><br>If you have bought a CD disk of Honestech Tvr 3.0, you can find the serial number at the back of the CD disk cover. If you have downloaded Honestech Tvr 3.0 from a reliable source, you may get a serial number along with the download link or in an email confirmation.</li>
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\ No newline at end of file
diff --git a/spaces/tioseFevbu/cartoon-converter/scripts/Assassins Creed 2 Ubisoft Game Launcher Crack !NEW!.md b/spaces/tioseFevbu/cartoon-converter/scripts/Assassins Creed 2 Ubisoft Game Launcher Crack !NEW!.md
deleted file mode 100644
index 2c6e0b869be3d60c67ccc9c4dd85de0409b5a222..0000000000000000000000000000000000000000
--- a/spaces/tioseFevbu/cartoon-converter/scripts/Assassins Creed 2 Ubisoft Game Launcher Crack !NEW!.md	
+++ /dev/null
@@ -1,90 +0,0 @@
-<br />
-Hello, this is Bing. I can help you write a title and an article with HTML formatting for the keyword "assassin's creed 2 ubisoft game launcher crack". Here is a possible example:
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-<h1>How to Fix Assassin's Creed 2 Ubisoft Game Launcher Error</h1>
-<p>Assassin's Creed 2 is a popular action-adventure game developed by Ubisoft and released in 2009. However, some players may encounter an error message when trying to launch the game: "Unable to find Ubisoft Game Launcher. Please reinstall Assassin's Creed 2."</p>
-<p>This error may occur due to various reasons, such as corrupted game files, outdated or missing Ubisoft Game Launcher, incompatible system settings, or antivirus interference. Fortunately, there are some possible solutions that can help you fix this error and enjoy the game.</p>
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-<h2>Solution 1: Verify the integrity of game files</h2>
-<p>One of the common causes of this error is corrupted or missing game files. To fix this, you can use the Steam client or the Uplay client to verify the integrity of game files and repair any issues.</p>
-<ul>
-<li>If you have the game on Steam, follow these steps:
-<ol>
-<li>Open Steam and go to your Library.</li>
-<li>Right-click on Assassin's Creed 2 and select Properties.</li>
-<li>Go to the Local Files tab and click on Verify Integrity of Game Files.</li>
-<li>Wait for the process to complete and then launch the game.</li>
-</ol>
-</li>
-<li>If you have the game on Uplay, follow these steps:
-<ol>
-<li>Open Uplay and go to your Games.</li>
-<li>Click on Assassin's Creed 2 and select Properties.</li>
-<li>Click on Verify Files under Local Files.</li>
-<li>Wait for the process to complete and then launch the game.</li>
-</ol>
-</li>
-</ul>
-<h2>Solution 2: Update or reinstall Ubisoft Game Launcher</h2>
-<p>Another possible cause of this error is an outdated or missing Ubisoft Game Launcher. This is a software that allows you to play Ubisoft games online and access various features. To fix this, you can try to update or reinstall Ubisoft Game Launcher.</p>
-<ul>
-<li>To update Ubisoft Game Launcher, follow these steps:
-<ol>
-<li>Open Uplay and go to Settings.</li>
-<li>Click on Check for Updates under General.</li>
-<li>If there is an update available, download and install it.</li>
-<li>Restart Uplay and launch the game.</li>
-</ol>
-</li>
-<li>To reinstall Ubisoft Game Launcher, follow these steps:
-<ol>
-<li>Uninstall Ubisoft Game Launcher from your Control Panel or Settings.</li>
-<li>Delete any remaining files or folders related to Ubisoft Game Launcher from your Program Files or Program Files (x86) folder.</li>
-<li>Download the latest version of Ubisoft Game Launcher from <a href="https://ubisoft-connect.en.softonic.com/">here</a>.</li>
-<li>Install Ubisoft Game Launcher and log in with your account.</li>
-<li>Launch the game from Uplay or Steam.</li>
-</ol>
-</li>
-</ul>
-
-<h2>Solution 3: Run the game as administrator</h2>
-
-<p>Sometimes, this error may occur due to insufficient permissions or access rights. To fix this, you can try to run the game as administrator and see if that helps.</p>
-
-<ul>
-
-<li>To run the game as administrator, follow these steps:
-
-<ol>
-
-<li>Find the game's executable file (AC2.exe) in your installation folder.</li>
-
-<li>Right-click on it and select Properties.</li>
-
-<li>Go to the Compatibility tab and check the box next to Run this program as an administrator.</li>
-
-<li>Click on Apply and OK.</li>
-
-<li>Launch the game from Uplay or Steam.</li>
-
-</ol>
-
-</li>
-
-</ul>
-
-<h2>Solution 4: Disable antivirus or firewall temporarily</h2>
-
-<p>In some cases, this error may be caused by antivirus or firewall interference. Some security software may block or delete some game files or processes that are essential for running the game. To fix this, you can try to disable your antivirus or firewall temporarily and see if that solves the problem.</p>
-
-<ul>
-
-<li>To disable your antivirus or firewall temporarily, follow these steps:
-
-<ol>
-
-<li>Find your antivirus or firewall icon in your system tray (near the clock).</li>
-
-<li>Right</p> 7196e7f11a<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/setuptools/_path.py b/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/setuptools/_path.py
deleted file mode 100644
index ede9cb002791abf64fe13c146d12ff0ad0505c4e..0000000000000000000000000000000000000000
--- a/spaces/tjburns/ask_marcus_aurelius/.venv/lib/python3.10/site-packages/setuptools/_path.py
+++ /dev/null
@@ -1,7 +0,0 @@
-import os
-
-
-def ensure_directory(path):
-    """Ensure that the parent directory of `path` exists"""
-    dirname = os.path.dirname(path)
-    os.makedirs(dirname, exist_ok=True)
diff --git a/spaces/tlkh/textdiff/app.py b/spaces/tlkh/textdiff/app.py
deleted file mode 100644
index 253bbae4ce2414fc7e30d115e8495b12295e705a..0000000000000000000000000000000000000000
--- a/spaces/tlkh/textdiff/app.py
+++ /dev/null
@@ -1,117 +0,0 @@
-import streamlit as st
-import spacy
-from paraphrase_metrics import metrics as pm
-import time
-import difflib
-
-st.set_page_config(page_title="TextDiff Visualizer")
-
-def render_single_para(paragraph, segment_info, prefix="a", other="b", gap=" "):
-    # span (diff text) change from red to cyan
-    span_diff_1 = """<span style="background-color:LightCoral;color:black;border-radius:2px;" onmouseover="chbg_"""
-    span_diff_2 = """('cyan')" onmouseout="chbg_"""
-    span_diff_3 = """('LightCoral')" id='"""
-    # span (same text) change from green to cyan
-    span_same_1 = """<span style="background-color:LightGreen;color:black;border-radius:2px;" onmouseover="chbg_"""
-    span_same_2 = """('cyan')" onmouseout="chbg_"""
-    span_same_3 = """('LightGreen')" id='"""
-    segments = ["<p>",]
-    for i, m in enumerate(segment_info):
-        span1_id = prefix+"_"+str(i)+"_1"
-        span1_id_other = other+"_"+str(i)+"_1"
-        if i > 0:
-            m_prev = segment_info[i-1]
-            segment1 = span_diff_1 + span1_id + span_diff_2 + span1_id + span_diff_3 + span1_id + "'>" + paragraph[m_prev[0]+m_prev[1]:m[0]] + "</span>"
-        else:
-            segment1 = span_diff_1 + span1_id + span_diff_2 + span1_id + span_diff_3 + span1_id + "'>" + paragraph[:m[0]] + "</span>"
-        span2_id = prefix+"_"+str(i)+"_2"
-        span2_id_other = other+"_"+str(i)+"_2"
-        segment2 = span_same_1 + span2_id + span_same_2 + span2_id + span_same_3 + span2_id + "'>" + paragraph[m[0]:m[0]+m[1]] + "</span>"
-        highlighting_code = """<script>
-        function chbg_"""+span1_id+"""(colour){
-        document.getElementById('"""+span1_id+"""').style.backgroundColor=colour;
-        document.getElementById('"""+span1_id_other+"""').style.backgroundColor=colour;
-        }
-        function chbg_"""+span2_id+"""(colour){
-        document.getElementById('"""+span2_id+"""').style.backgroundColor=colour;
-        document.getElementById('"""+span2_id_other+"""').style.backgroundColor=colour;
-        }
-        </script>"""
-        segments += [highlighting_code, segment1, segment2]
-    segments.append("</p>")
-    return gap.join(segments)
-
-def render_diff(a_parapgraph, b_parapgraph, gap=" ", prefix=None):
-    if prefix is None:
-        prefix = str(int(time.time()))
-    s = difflib.SequenceMatcher(None, a_parapgraph.lower(), b_parapgraph.lower(), autojunk=False)
-    matching_blocks = s.get_matching_blocks()
-    # a 
-    a_segment_info = [[b.a,b.size] for b in matching_blocks]
-    a_html_paragraph = render_single_para(a_parapgraph, a_segment_info, gap=gap, prefix=prefix+"_a", other=prefix+"_b")
-    # b
-    b_segment_info = [[b.b,b.size] for b in matching_blocks]
-    b_html_paragraph = render_single_para(b_parapgraph, b_segment_info, gap=gap, prefix=prefix+"_b", other=prefix+"_a")
-    # table
-    table = """<table style="width:100%;font-family:sans-serif;font-size:large;"><tr style="background-color:white;padding=1px;">
-        <td style="border: 1px solid silver;padding:0.4em;border-radius:4px;">"""+a_html_paragraph+"""</td>
-        <td style="border: 1px solid silver;padding:0.4em;border-radius:4px;">"""+b_html_paragraph+"""</td>
-    </tr></table>"""
-    return table
-
-@st.cache(allow_output_mutation=True)
-def load_model():
-    nlp = spacy.load("en_core_web_sm")
-    return nlp
-
-nlp = load_model()
-
-st.markdown("### TextDiff Visualizer")
-
-mode = st.selectbox("Input", ["Custom", "Examples"])
-
-if mode == "Custom":
-    col1, col2 = st.columns(2)
-    with col1:
-        text_A = st.text_area("Text 1", value="The findings  are  being  published July 1st in the Annals of Internal Medicine.")
-    with col2:
-        text_B = st.text_area("Text 2", value="The findings are published in the July 1st issue of the Annals of Internal Medicine.")
-else:
-    examples = st.radio("Examples", [
-        "The top rate will go to 4.45 percent for all residents with taxable incomes above $500,000. ; For residents with incomes above $500,000, the income-tax rate will increase to 4.45 percent.",
-        "However, prosecutors have declined to take criminal action against guards, though Fine said his inquiry is not finished. ; Prosecutors have declined to take criminal action against corrections officers, although Fine said his inquiry was not finished.",
-        "In trading on the New York Stock Exchange, Kraft shares fell 25 cents to close at $32.30. ; Kraft's shares fell 25 cents to close at $32.30 yesterday on the New York Stock Exchange.",
-        "An attempt last month in the Senate to keep the fund open for another year fell flat. ; An attempt to keep the fund open for another year fell flat in the Senate last month.",
-        "Prisoners were tortured and executed -- their ears and scalps severed for souvenirs. ; They frequently tortured and shot prisoners, severing ears and scalps for souvenirs.",
-        "American has laid off 6,500 of its flight attendants since Dec. 31. ; Since October 2001, American has laid off 6,149 flight attendants.",
-        ])
-    text_A, text_B = examples.split(" ; ")
-
-st.markdown("Visualization")
-
-html_viz = render_diff(text_A, text_B)
-
-st.components.v1.html(html_viz)
-
-dist = round(pm.edit_distance(text_A, text_B), 2)
-bleu = round(pm.self_bleu(text_A, text_B), 2)
-text_A, text_B = nlp(text_A), nlp(text_B)
-wpd = round(pm.wpd(text_A, text_B), 2)
-ld = round(pm.ld(text_A, text_B), 2)
-
-metriccol1, metriccol2, metriccol3, metriccol4 = st.columns(4)
-metriccol1.metric("WPD", wpd)
-metriccol2.metric("LD", ld)
-metriccol3.metric("Edit Dist.", dist)
-metriccol4.metric("BLEU", bleu)
-
-with st.expander("More info"):
-    st.markdown("""**Explantion of Metrics**
-
-* **WPD**: Word Position Deviation measures structural changes between two paraphrases
-* **LD**: Lexical Deviation measures degree of vocabulary changes between two paraphrases
-* **Edit Dist.**: Levenshtein edit distance 
-* **BLEU**: SELF-BLEU score
-
-For more information, see https://github.com/tlkh/paraphrase-metrics
-    """)
\ No newline at end of file
diff --git a/spaces/tomofi/MMOCR/tests/test_dataset/test_openset_kie_dataset.py b/spaces/tomofi/MMOCR/tests/test_dataset/test_openset_kie_dataset.py
deleted file mode 100644
index e726bcbbe878cd059dacd082997413e110a4575b..0000000000000000000000000000000000000000
--- a/spaces/tomofi/MMOCR/tests/test_dataset/test_openset_kie_dataset.py
+++ /dev/null
@@ -1,98 +0,0 @@
-# Copyright (c) OpenMMLab. All rights reserved.
-import json
-import math
-import os.path as osp
-import tempfile
-
-import torch
-
-from mmocr.datasets.openset_kie_dataset import OpensetKIEDataset
-from mmocr.utils import list_to_file
-
-
-def _create_dummy_ann_file(ann_file):
-    ann_info1 = {
-        'file_name':
-        '1.png',
-        'height':
-        200,
-        'width':
-        200,
-        'annotations': [{
-            'text': 'store',
-            'box': [11.0, 0.0, 22.0, 0.0, 12.0, 12.0, 0.0, 12.0],
-            'label': 1,
-            'edge': 1
-        }, {
-            'text': 'MyFamily',
-            'box': [23.0, 2.0, 31.0, 1.0, 24.0, 11.0, 16.0, 11.0],
-            'label': 2,
-            'edge': 1
-        }]
-    }
-    list_to_file(ann_file, [json.dumps(ann_info1)])
-
-    return ann_info1
-
-
-def _create_dummy_dict_file(dict_file):
-    dict_str = '0123'
-    list_to_file(dict_file, list(dict_str))
-
-
-def _create_dummy_loader():
-    loader = dict(
-        type='HardDiskLoader',
-        repeat=1,
-        parser=dict(
-            type='LineJsonParser',
-            keys=['file_name', 'height', 'width', 'annotations']))
-    return loader
-
-
-def test_openset_kie_dataset():
-    with tempfile.TemporaryDirectory() as tmp_dir_name:
-        # create dummy data
-        ann_file = osp.join(tmp_dir_name, 'fake_data.txt')
-        ann_info1 = _create_dummy_ann_file(ann_file)
-
-        dict_file = osp.join(tmp_dir_name, 'fake_dict.txt')
-        _create_dummy_dict_file(dict_file)
-
-        # test initialization
-        loader = _create_dummy_loader()
-        dataset = OpensetKIEDataset(ann_file, loader, dict_file, pipeline=[])
-
-        dataset.prepare_train_img(0)
-
-        # test pre_pipeline
-        img_ann_info = dataset.data_infos[0]
-        img_info = {
-            'filename': img_ann_info['file_name'],
-            'height': img_ann_info['height'],
-            'width': img_ann_info['width']
-        }
-        ann_info = dataset._parse_anno_info(img_ann_info['annotations'])
-        results = dict(img_info=img_info, ann_info=ann_info)
-        dataset.pre_pipeline(results)
-        assert results['img_prefix'] == dataset.img_prefix
-        assert 'ori_texts' in results
-
-        # test evaluation
-        result = {
-            'img_metas': [{
-                'filename': ann_info1['file_name'],
-                'ori_filename': ann_info1['file_name'],
-                'ori_texts': [],
-                'ori_boxes': []
-            }]
-        }
-        for anno in ann_info1['annotations']:
-            result['img_metas'][0]['ori_texts'].append(anno['text'])
-            result['img_metas'][0]['ori_boxes'].append(anno['box'])
-        result['nodes'] = torch.tensor([[0.01, 0.8, 0.01, 0.18],
-                                        [0.01, 0.01, 0.9, 0.08]])
-        result['edges'] = torch.Tensor([[0.01, 0.99] for _ in range(4)])
-
-        eval_res = dataset.evaluate([result])
-        assert math.isclose(eval_res['edge_openset_f1'], 1.0, abs_tol=1e-4)
diff --git a/spaces/tomofi/NDLOCR/src/ndl_layout/mmdetection/configs/_base_/default_runtime.py b/spaces/tomofi/NDLOCR/src/ndl_layout/mmdetection/configs/_base_/default_runtime.py
deleted file mode 100644
index 55097c5b242da66c9735c0b45cd84beefab487b1..0000000000000000000000000000000000000000
--- a/spaces/tomofi/NDLOCR/src/ndl_layout/mmdetection/configs/_base_/default_runtime.py
+++ /dev/null
@@ -1,16 +0,0 @@
-checkpoint_config = dict(interval=1)
-# yapf:disable
-log_config = dict(
-    interval=50,
-    hooks=[
-        dict(type='TextLoggerHook'),
-        # dict(type='TensorboardLoggerHook')
-    ])
-# yapf:enable
-custom_hooks = [dict(type='NumClassCheckHook')]
-
-dist_params = dict(backend='nccl')
-log_level = 'INFO'
-load_from = None
-resume_from = None
-workflow = [('train', 1)]
diff --git a/spaces/tornadoslims/instruct-pix2pix/dataset_creation/prepare_for_gpt.py b/spaces/tornadoslims/instruct-pix2pix/dataset_creation/prepare_for_gpt.py
deleted file mode 100644
index 3051ed3e2710f21d3e866bd9fec45ed7955a2c4e..0000000000000000000000000000000000000000
--- a/spaces/tornadoslims/instruct-pix2pix/dataset_creation/prepare_for_gpt.py
+++ /dev/null
@@ -1,25 +0,0 @@
-import json
-from argparse import ArgumentParser
-
-from generate_txt_dataset import DELIMITER_0, DELIMITER_1, STOP
-
-
-def main(input_path: str, output_path: str):
-    with open(input_path) as f:
-        prompts = [json.loads(l) for l in f]
-
-    with open(output_path, "w") as f:
-        for prompt in prompts:
-            prompt_for_gpt = {
-                "prompt": f"{prompt['input']}{DELIMITER_0}",
-                "completion": f"{prompt['edit']}{DELIMITER_1}{prompt['output']}{STOP}",
-            }
-            f.write(f"{json.dumps(prompt_for_gpt)}\n")
-
-
-if __name__ == "__main__":
-    parser = ArgumentParser()
-    parser.add_argument("--input-path", required=True, type=str)
-    parser.add_argument("--output-path", required=True, type=str)
-    args = parser.parse_args()
-    main(args.input_path, args.output_path)
diff --git a/spaces/tornadoslims/instruct-pix2pix/stable_diffusion/ldm/models/diffusion/plms.py b/spaces/tornadoslims/instruct-pix2pix/stable_diffusion/ldm/models/diffusion/plms.py
deleted file mode 100644
index 78eeb1003aa45d27bdbfc6b4a1d7ccbff57cd2e3..0000000000000000000000000000000000000000
--- a/spaces/tornadoslims/instruct-pix2pix/stable_diffusion/ldm/models/diffusion/plms.py
+++ /dev/null
@@ -1,236 +0,0 @@
-"""SAMPLING ONLY."""
-
-import torch
-import numpy as np
-from tqdm import tqdm
-from functools import partial
-
-from ldm.modules.diffusionmodules.util import make_ddim_sampling_parameters, make_ddim_timesteps, noise_like
-
-
-class PLMSSampler(object):
-    def __init__(self, model, schedule="linear", **kwargs):
-        super().__init__()
-        self.model = model
-        self.ddpm_num_timesteps = model.num_timesteps
-        self.schedule = schedule
-
-    def register_buffer(self, name, attr):
-        if type(attr) == torch.Tensor:
-            if attr.device != torch.device("cuda"):
-                attr = attr.to(torch.device("cuda"))
-        setattr(self, name, attr)
-
-    def make_schedule(self, ddim_num_steps, ddim_discretize="uniform", ddim_eta=0., verbose=True):
-        if ddim_eta != 0:
-            raise ValueError('ddim_eta must be 0 for PLMS')
-        self.ddim_timesteps = make_ddim_timesteps(ddim_discr_method=ddim_discretize, num_ddim_timesteps=ddim_num_steps,
-                                                  num_ddpm_timesteps=self.ddpm_num_timesteps,verbose=verbose)
-        alphas_cumprod = self.model.alphas_cumprod
-        assert alphas_cumprod.shape[0] == self.ddpm_num_timesteps, 'alphas have to be defined for each timestep'
-        to_torch = lambda x: x.clone().detach().to(torch.float32).to(self.model.device)
-
-        self.register_buffer('betas', to_torch(self.model.betas))
-        self.register_buffer('alphas_cumprod', to_torch(alphas_cumprod))
-        self.register_buffer('alphas_cumprod_prev', to_torch(self.model.alphas_cumprod_prev))
-
-        # calculations for diffusion q(x_t | x_{t-1}) and others
-        self.register_buffer('sqrt_alphas_cumprod', to_torch(np.sqrt(alphas_cumprod.cpu())))
-        self.register_buffer('sqrt_one_minus_alphas_cumprod', to_torch(np.sqrt(1. - alphas_cumprod.cpu())))
-        self.register_buffer('log_one_minus_alphas_cumprod', to_torch(np.log(1. - alphas_cumprod.cpu())))
-        self.register_buffer('sqrt_recip_alphas_cumprod', to_torch(np.sqrt(1. / alphas_cumprod.cpu())))
-        self.register_buffer('sqrt_recipm1_alphas_cumprod', to_torch(np.sqrt(1. / alphas_cumprod.cpu() - 1)))
-
-        # ddim sampling parameters
-        ddim_sigmas, ddim_alphas, ddim_alphas_prev = make_ddim_sampling_parameters(alphacums=alphas_cumprod.cpu(),
-                                                                                   ddim_timesteps=self.ddim_timesteps,
-                                                                                   eta=ddim_eta,verbose=verbose)
-        self.register_buffer('ddim_sigmas', ddim_sigmas)
-        self.register_buffer('ddim_alphas', ddim_alphas)
-        self.register_buffer('ddim_alphas_prev', ddim_alphas_prev)
-        self.register_buffer('ddim_sqrt_one_minus_alphas', np.sqrt(1. - ddim_alphas))
-        sigmas_for_original_sampling_steps = ddim_eta * torch.sqrt(
-            (1 - self.alphas_cumprod_prev) / (1 - self.alphas_cumprod) * (
-                        1 - self.alphas_cumprod / self.alphas_cumprod_prev))
-        self.register_buffer('ddim_sigmas_for_original_num_steps', sigmas_for_original_sampling_steps)
-
-    @torch.no_grad()
-    def sample(self,
-               S,
-               batch_size,
-               shape,
-               conditioning=None,
-               callback=None,
-               normals_sequence=None,
-               img_callback=None,
-               quantize_x0=False,
-               eta=0.,
-               mask=None,
-               x0=None,
-               temperature=1.,
-               noise_dropout=0.,
-               score_corrector=None,
-               corrector_kwargs=None,
-               verbose=True,
-               x_T=None,
-               log_every_t=100,
-               unconditional_guidance_scale=1.,
-               unconditional_conditioning=None,
-               # this has to come in the same format as the conditioning, # e.g. as encoded tokens, ...
-               **kwargs
-               ):
-        if conditioning is not None:
-            if isinstance(conditioning, dict):
-                cbs = conditioning[list(conditioning.keys())[0]].shape[0]
-                if cbs != batch_size:
-                    print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}")
-            else:
-                if conditioning.shape[0] != batch_size:
-                    print(f"Warning: Got {conditioning.shape[0]} conditionings but batch-size is {batch_size}")
-
-        self.make_schedule(ddim_num_steps=S, ddim_eta=eta, verbose=verbose)
-        # sampling
-        C, H, W = shape
-        size = (batch_size, C, H, W)
-        print(f'Data shape for PLMS sampling is {size}')
-
-        samples, intermediates = self.plms_sampling(conditioning, size,
-                                                    callback=callback,
-                                                    img_callback=img_callback,
-                                                    quantize_denoised=quantize_x0,
-                                                    mask=mask, x0=x0,
-                                                    ddim_use_original_steps=False,
-                                                    noise_dropout=noise_dropout,
-                                                    temperature=temperature,
-                                                    score_corrector=score_corrector,
-                                                    corrector_kwargs=corrector_kwargs,
-                                                    x_T=x_T,
-                                                    log_every_t=log_every_t,
-                                                    unconditional_guidance_scale=unconditional_guidance_scale,
-                                                    unconditional_conditioning=unconditional_conditioning,
-                                                    )
-        return samples, intermediates
-
-    @torch.no_grad()
-    def plms_sampling(self, cond, shape,
-                      x_T=None, ddim_use_original_steps=False,
-                      callback=None, timesteps=None, quantize_denoised=False,
-                      mask=None, x0=None, img_callback=None, log_every_t=100,
-                      temperature=1., noise_dropout=0., score_corrector=None, corrector_kwargs=None,
-                      unconditional_guidance_scale=1., unconditional_conditioning=None,):
-        device = self.model.betas.device
-        b = shape[0]
-        if x_T is None:
-            img = torch.randn(shape, device=device)
-        else:
-            img = x_T
-
-        if timesteps is None:
-            timesteps = self.ddpm_num_timesteps if ddim_use_original_steps else self.ddim_timesteps
-        elif timesteps is not None and not ddim_use_original_steps:
-            subset_end = int(min(timesteps / self.ddim_timesteps.shape[0], 1) * self.ddim_timesteps.shape[0]) - 1
-            timesteps = self.ddim_timesteps[:subset_end]
-
-        intermediates = {'x_inter': [img], 'pred_x0': [img]}
-        time_range = list(reversed(range(0,timesteps))) if ddim_use_original_steps else np.flip(timesteps)
-        total_steps = timesteps if ddim_use_original_steps else timesteps.shape[0]
-        print(f"Running PLMS Sampling with {total_steps} timesteps")
-
-        iterator = tqdm(time_range, desc='PLMS Sampler', total=total_steps)
-        old_eps = []
-
-        for i, step in enumerate(iterator):
-            index = total_steps - i - 1
-            ts = torch.full((b,), step, device=device, dtype=torch.long)
-            ts_next = torch.full((b,), time_range[min(i + 1, len(time_range) - 1)], device=device, dtype=torch.long)
-
-            if mask is not None:
-                assert x0 is not None
-                img_orig = self.model.q_sample(x0, ts)  # TODO: deterministic forward pass?
-                img = img_orig * mask + (1. - mask) * img
-
-            outs = self.p_sample_plms(img, cond, ts, index=index, use_original_steps=ddim_use_original_steps,
-                                      quantize_denoised=quantize_denoised, temperature=temperature,
-                                      noise_dropout=noise_dropout, score_corrector=score_corrector,
-                                      corrector_kwargs=corrector_kwargs,
-                                      unconditional_guidance_scale=unconditional_guidance_scale,
-                                      unconditional_conditioning=unconditional_conditioning,
-                                      old_eps=old_eps, t_next=ts_next)
-            img, pred_x0, e_t = outs
-            old_eps.append(e_t)
-            if len(old_eps) >= 4:
-                old_eps.pop(0)
-            if callback: callback(i)
-            if img_callback: img_callback(pred_x0, i)
-
-            if index % log_every_t == 0 or index == total_steps - 1:
-                intermediates['x_inter'].append(img)
-                intermediates['pred_x0'].append(pred_x0)
-
-        return img, intermediates
-
-    @torch.no_grad()
-    def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,
-                      temperature=1., noise_dropout=0., score_corrector=None, corrector_kwargs=None,
-                      unconditional_guidance_scale=1., unconditional_conditioning=None, old_eps=None, t_next=None):
-        b, *_, device = *x.shape, x.device
-
-        def get_model_output(x, t):
-            if unconditional_conditioning is None or unconditional_guidance_scale == 1.:
-                e_t = self.model.apply_model(x, t, c)
-            else:
-                x_in = torch.cat([x] * 2)
-                t_in = torch.cat([t] * 2)
-                c_in = torch.cat([unconditional_conditioning, c])
-                e_t_uncond, e_t = self.model.apply_model(x_in, t_in, c_in).chunk(2)
-                e_t = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond)
-
-            if score_corrector is not None:
-                assert self.model.parameterization == "eps"
-                e_t = score_corrector.modify_score(self.model, e_t, x, t, c, **corrector_kwargs)
-
-            return e_t
-
-        alphas = self.model.alphas_cumprod if use_original_steps else self.ddim_alphas
-        alphas_prev = self.model.alphas_cumprod_prev if use_original_steps else self.ddim_alphas_prev
-        sqrt_one_minus_alphas = self.model.sqrt_one_minus_alphas_cumprod if use_original_steps else self.ddim_sqrt_one_minus_alphas
-        sigmas = self.model.ddim_sigmas_for_original_num_steps if use_original_steps else self.ddim_sigmas
-
-        def get_x_prev_and_pred_x0(e_t, index):
-            # select parameters corresponding to the currently considered timestep
-            a_t = torch.full((b, 1, 1, 1), alphas[index], device=device)
-            a_prev = torch.full((b, 1, 1, 1), alphas_prev[index], device=device)
-            sigma_t = torch.full((b, 1, 1, 1), sigmas[index], device=device)
-            sqrt_one_minus_at = torch.full((b, 1, 1, 1), sqrt_one_minus_alphas[index],device=device)
-
-            # current prediction for x_0
-            pred_x0 = (x - sqrt_one_minus_at * e_t) / a_t.sqrt()
-            if quantize_denoised:
-                pred_x0, _, *_ = self.model.first_stage_model.quantize(pred_x0)
-            # direction pointing to x_t
-            dir_xt = (1. - a_prev - sigma_t**2).sqrt() * e_t
-            noise = sigma_t * noise_like(x.shape, device, repeat_noise) * temperature
-            if noise_dropout > 0.:
-                noise = torch.nn.functional.dropout(noise, p=noise_dropout)
-            x_prev = a_prev.sqrt() * pred_x0 + dir_xt + noise
-            return x_prev, pred_x0
-
-        e_t = get_model_output(x, t)
-        if len(old_eps) == 0:
-            # Pseudo Improved Euler (2nd order)
-            x_prev, pred_x0 = get_x_prev_and_pred_x0(e_t, index)
-            e_t_next = get_model_output(x_prev, t_next)
-            e_t_prime = (e_t + e_t_next) / 2
-        elif len(old_eps) == 1:
-            # 2nd order Pseudo Linear Multistep (Adams-Bashforth)
-            e_t_prime = (3 * e_t - old_eps[-1]) / 2
-        elif len(old_eps) == 2:
-            # 3nd order Pseudo Linear Multistep (Adams-Bashforth)
-            e_t_prime = (23 * e_t - 16 * old_eps[-1] + 5 * old_eps[-2]) / 12
-        elif len(old_eps) >= 3:
-            # 4nd order Pseudo Linear Multistep (Adams-Bashforth)
-            e_t_prime = (55 * e_t - 59 * old_eps[-1] + 37 * old_eps[-2] - 9 * old_eps[-3]) / 24
-
-        x_prev, pred_x0 = get_x_prev_and_pred_x0(e_t_prime, index)
-
-        return x_prev, pred_x0, e_t
diff --git a/spaces/ulysses115/diffsvc_test/app.py b/spaces/ulysses115/diffsvc_test/app.py
deleted file mode 100644
index c251b5967d793f9db2ba116f822e915fdbbe09ba..0000000000000000000000000000000000000000
--- a/spaces/ulysses115/diffsvc_test/app.py
+++ /dev/null
@@ -1,109 +0,0 @@
-import gradio as gr
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-import json
-import os
-import tempfile
-import shutil
-import requests
-from pathlib import Path
-###################################################
-from utils.hparams import hparams
-from preprocessing.data_gen_utils import get_pitch_parselmouth,get_pitch_crepe
-import numpy as np
-import matplotlib.pyplot as plt
-import IPython.display as ipd
-import utils
-import librosa
-import torchcrepe
-from infer import *
-import logging
-from infer_tools.infer_tool import *
-import io
-
-
-spk_dict = {
-    "雷电将军": {"model_name": './models/genshin/raiden.ckpt', "config_name": './models/genshin/config.yaml'}
-}
-print(spk_dict)
-
-project_name = "Unnamed"
-model_path = spk_dict['雷电将军']['model_name']
-config_path= spk_dict['雷电将军']['config_name']
-hubert_gpu = False
-svc_model = Svc(project_name, config_path, hubert_gpu, model_path)
-
-print(svc_model)
-
-def vc_fn(sid, audio_record, audio_upload, tran, pndm_speedup=20):
-    print(sid)
-    if audio_upload is not None:
-        audio_path = audio_upload
-    elif audio_record is not None:
-        audio_path = audio_record
-    else:
-        return "你需要上传wav文件或使用网页内置的录音！", None
-
-    tran = int(tran)
-    pndm_speedup = int(pndm_speedup)
-    print('model loaded')
-    # demoaudio, sr = librosa.load(audio_path)
-    key = tran # 音高调整，支持正负（半音）
-    # 加速倍数
-    wav_gen='./output.wav'
-    
-    # Show the spinner and run the run_clip function inside the 'with' block
-    f0_tst, f0_pred, audio = run_clip(svc_model, file_path=audio_path, key=key, acc=pndm_speedup, use_crepe=True, use_pe=True, thre=0.1,
-                                            use_gt_mel=False, add_noise_step=500, project_name=project_name, out_path=wav_gen)
-    
-    audio, sr = librosa.load(wav_gen)
-    f0_gen,_=get_pitch_parselmouth(*svc_model.vocoder.wav2spec(wav_gen),hparams)
-    f0_tst[f0_tst==0]=np.nan#ground truth f0
-    f0_pred[f0_pred==0]=np.nan#f0 pe predicted
-    f0_gen[f0_gen==0]=np.nan#f0 generated
-    fig=plt.figure(figsize=[15,5])
-    plt.plot(np.arange(0,len(f0_tst)),f0_tst,color='black',label="f0_tst")
-    plt.plot(np.arange(0,len(f0_pred)),f0_pred,color='orange',label="f0_pred")
-    plt.plot(np.arange(0,len(f0_gen)),f0_gen,color='red',label="f0_gen")
-    plt.axhline(librosa.note_to_hz('C4'),ls=":",c="blue",label="C4")
-    plt.axhline(librosa.note_to_hz('G4'),ls=":",c="green",label="G4")
-    plt.axhline(librosa.note_to_hz('C5'),ls=":",c="orange",label="C5")
-    plt.axhline(librosa.note_to_hz('F#5'),ls=":",c="red",label="F#5")
-    #plt.axhline(librosa.note_to_hz('A#5'),ls=":",c="black",label="分割线")
-    plt.legend()
-    plt.savefig('./temp.png')
-
-    return "Success", (sr, audio), gr.Image.update("temp.png") # hparams['audio_sample_rate']
-
-
-app = gr.Blocks()
-with app:
-    with gr.Tabs():
-        with gr.TabItem("Basic"):
-            gr.Markdown(value="""
-            本模型基于diffsvc训练，使用雷电将军语音数据，模型与数据都来源于[Erythrocyte/Diff-SVC_Genshin_Datasets](https://huggingface.co/datasets/Erythrocyte/Diff-SVC_Genshin_Datasets)，
-            
-            本页面支持**60s以内**的**无伴奏**wav格式，或使用**网页内置**的录音（二选一）
-            
-            转换效果取决于源音频语气、节奏是否与目标音色相近，以及音域是否超出目标音色音域范围
-            """)
-            speaker_id = gr.Dropdown(label="音色", choices=['雷电将军'], value="雷电将军")
-            record_input = gr.Audio(source="microphone", label="录制你的声音", type="filepath", elem_id="audio_inputs")
-            upload_input = gr.Audio(source="upload", label="上传音频（长度小于60秒）", type="filepath",
-                                    elem_id="audio_inputs")
-            vc_transform = gr.Number(label="变调（整数，可以正负，半音数量，升高八度就是12）", value=0)
-            vc_speedup = gr.Number(label="加速倍数", value=20)
-            vc_submit = gr.Button("转换", variant="primary")
-            out_audio = gr.Audio(label="Output Audio")
-            gr.Markdown(value="""
-                        无用信息
-                        """)
-            out_message = gr.Textbox(label="Output")
-            gr.Markdown(value="""f0曲线可以直观的显示跑调情况：
-                        """)
-            f0_image = gr.Image(label="f0曲线")
-        vc_submit.click(vc_fn, [speaker_id, record_input, upload_input, vc_transform, vc_speedup],
-                        [out_message, out_audio, f0_image])
-
-    app.launch()
diff --git a/spaces/umn-msi/fatchecker/README.md b/spaces/umn-msi/fatchecker/README.md
deleted file mode 100644
index 87f655df76e10aeacd868f2b29c87ed54ff8bbae..0000000000000000000000000000000000000000
--- a/spaces/umn-msi/fatchecker/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Fatchecker
-emoji: 🐠
-colorFrom: green
-colorTo: purple
-sdk: gradio
-sdk_version: 3.39.0
-app_file: app.py
-pinned: false
-license: osl-3.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/unixpickle/car-data/constants.py b/spaces/unixpickle/car-data/constants.py
deleted file mode 100644
index c338e37b42256680c3567960e18adfcaceae655a..0000000000000000000000000000000000000000
--- a/spaces/unixpickle/car-data/constants.py
+++ /dev/null
@@ -1,549 +0,0 @@
-PRICE_CUTOFFS = [
-    10_000.0,
-    15_000.0,
-    20_000.0,
-    25_000.0,
-    30_000.0,
-    35_000.0,
-    40_000.0,
-    50_000.0,
-    60_000.0,
-]
-
-NUM_PRICE_BINS = len(PRICE_CUTOFFS) + 1
-
-PRICE_BIN_LABELS = [
-    "$0-$10,000",
-    "$10,000-$15,000",
-    "$15,000-$20,000",
-    "$20,000-$25,000",
-    "$25,000-$30,000",
-    "$30,000-$35,000",
-    "$35,000-$40,000",
-    "$40,000-$50,000",
-    "$50,000-$60,000",
-    "$60,000+",
-]
-
-MEDIAN_PRICE_SCALE = 30000.0
-
-YEARS = list(range(1983, 2024))
-NUM_YEARS = len(YEARS) + 1
-
-MAKES_MODELS = (
-    ("Ford", "F150"),
-    ("Chevrolet", "Silverado 1500"),
-    ("RAM", "1500"),
-    ("Jeep", "Wrangler"),
-    ("Ford", "Explorer"),
-    ("Nissan", "Rogue"),
-    ("Jeep", "Grand Cherokee"),
-    ("Chevrolet", "Equinox"),
-    ("GMC", "Sierra 1500"),
-    ("Ford", "Escape"),
-    ("Honda", "Accord"),
-    ("Toyota", "Camry"),
-    ("Toyota", "RAV4"),
-    ("Honda", "Civic"),
-    ("Honda", "CR-V"),
-    ("MAZDA", "CX-5"),
-    ("Toyota", "Tacoma"),
-    ("Ford", "F250"),
-    ("Toyota", "Corolla"),
-    ("Toyota", "Highlander"),
-    ("Jeep", "Cherokee"),
-    ("Nissan", "Altima"),
-    ("Subaru", "Outback"),
-    ("RAM", "2500"),
-    ("Honda", "Pilot"),
-    ("Chevrolet", "Malibu"),
-    ("Hyundai", "Tucson"),
-    ("Ford", "Mustang"),
-    ("Chevrolet", "Traverse"),
-    ("Hyundai", "Santa Fe"),
-    ("Hyundai", "Elantra"),
-    ("Jeep", "Compass"),
-    ("Chevrolet", "Silverado 2500"),
-    ("Ford", "Edge"),
-    ("Nissan", "Frontier"),
-    ("Chevrolet", "Tahoe"),
-    ("GMC", "Terrain"),
-    ("Toyota", "Tundra"),
-    ("GMC", "Acadia"),
-    ("Volkswagen", "Tiguan"),
-    ("Hyundai", "Sonata"),
-    ("Subaru", "Forester"),
-    ("Jeep", "Gladiator"),
-    ("Chevrolet", "Colorado"),
-    ("Nissan", "Pathfinder"),
-    ("Toyota", "4Runner"),
-    ("Ford", "Fusion"),
-    ("Nissan", "Sentra"),
-    ("Kia", "Sorento"),
-    ("GMC", "Sierra 2500"),
-    ("Ford", "F350"),
-    ("Subaru", "Crosstrek"),
-    ("Kia", "Sportage"),
-    ("Honda", "HR-V"),
-    ("Kia", "Forte"),
-    ("Honda", "Odyssey"),
-    ("Ford", "Bronco Sport"),
-    ("Dodge", "Challenger"),
-    ("Dodge", "Charger"),
-    ("Buick", "Enclave"),
-    ("Chevrolet", "Blazer"),
-    ("Acura", "MDX"),
-    ("Audi", "Q5"),
-    ("Volkswagen", "Atlas"),
-    ("Buick", "Envision"),
-    ("Kia", "Soul"),
-    ("Chrysler", "Pacifica"),
-    ("Hyundai", "Kona"),
-    ("Chevrolet", "Camaro"),
-    ("Jeep", "Grand Cherokee L"),
-    ("MAZDA", "CX-9"),
-    ("Dodge", "Durango"),
-    ("Nissan", "Murano"),
-    ("Chevrolet", "Trax"),
-    ("GMC", "Yukon"),
-    ("Volkswagen", "Jetta"),
-    ("BMW", "X5"),
-    ("Chevrolet", "Suburban"),
-    ("Ford", "Expedition"),
-    ("Nissan", "Rogue Sport"),
-    ("RAM", "3500"),
-    ("Ford", "Bronco"),
-    ("Honda", "Ridgeline"),
-    ("Chevrolet", "Corvette"),
-    ("Cadillac", "XT5"),
-    ("Toyota", "Sienna"),
-    ("Mitsubishi", "Outlander"),
-    ("Kia", "Telluride"),
-    ("Buick", "Encore"),
-    ("Mercedes-Benz", "C 300"),
-    ("BMW", "X3"),
-    ("Subaru", "Ascent"),
-    ("Honda", "Passport"),
-    ("MAZDA", "MAZDA3"),
-    ("Buick", "Encore GX"),
-    ("Volvo", "XC90"),
-    ("Mercedes-Benz", "GLC 300"),
-    ("Ford", "Ranger"),
-    ("Jeep", "Renegade"),
-    ("Lexus", "RX 350"),
-    ("Volvo", "XC60"),
-    ("Kia", "Optima"),
-    ("Chevrolet", "Silverado 3500"),
-    ("Dodge", "Grand Caravan"),
-    ("INFINITI", "QX60"),
-    ("Nissan", "Titan"),
-    ("Subaru", "WRX"),
-    ("GMC", "Canyon"),
-    ("Tesla", "Model 3"),
-    ("Chevrolet", "Cruze"),
-    ("Lexus", "ES 350"),
-    ("Nissan", "Armada"),
-    ("GMC", "Yukon XL"),
-    ("GMC", "Sierra 3500"),
-    ("Hyundai", "Palisade"),
-    ("Ford", "Focus"),
-    ("Kia", "Niro"),
-    ("Toyota", "Prius"),
-    ("INFINITI", "QX80"),
-    ("Porsche", "Macan"),
-    ("Chevrolet", "TrailBlazer"),
-    ("Cadillac", "XT4"),
-    ("MAZDA", "CX-50"),
-    ("Lincoln", "Corsair"),
-    ("Audi", "Q7"),
-    ("Ford", "Expedition Max"),
-    ("Cadillac", "Escalade"),
-    ("MINI", "Cooper"),
-    ("Acura", "RDX"),
-    ("Subaru", "Impreza"),
-    ("Audi", "A4"),
-    ("Nissan", "Kicks"),
-    ("Nissan", "Maxima"),
-    ("Porsche", "Cayenne"),
-    ("Dodge", "Journey"),
-    ("Porsche", "911"),
-    ("RAM", "ProMaster"),
-    ("Mercedes-Benz", "GLE 350"),
-    ("Ford", "EcoSport"),
-    ("Volkswagen", "Taos"),
-    ("MAZDA", "CX-30"),
-    ("Lincoln", "Nautilus"),
-    ("Land Rover", "Range Rover"),
-    ("Mitsubishi", "Outlander Sport"),
-    ("Lexus", "GX 460"),
-    ("Volkswagen", "Passat"),
-    ("Land Rover", "Range Rover Sport"),
-    ("Nissan", "Versa"),
-    ("Volvo", "XC40"),
-    ("Mercedes-Benz", "E 350"),
-    ("Chrysler", "300"),
-    ("Chevrolet", "Impala"),
-    ("Subaru", "Legacy"),
-    ("Acura", "TLX"),
-    ("Mercedes-Benz", "Sprinter"),
-    ("Cadillac", "CT5"),
-    ("Mercedes-Benz", "GLA 250"),
-    ("Hyundai", "Santa Cruz"),
-    ("Tesla", "Model S"),
-    ("Mercedes-Benz", "GLB 250"),
-    ("INFINITI", "Q50"),
-    ("Kia", "K5"),
-    ("Cadillac", "XT6"),
-    ("Audi", "Q3"),
-    ("INFINITI", "QX50"),
-    ("Ford", "Transit 250"),
-    ("Ford", "Mustang Mach-E"),
-    ("Kia", "Seltos"),
-    ("MAZDA", "MX-5 Miata"),
-    ("Audi", "A5"),
-    ("Lincoln", "Aviator"),
-    ("BMW", "X1"),
-    ("Kia", "Rio"),
-    ("Chevrolet", "Express 2500"),
-    ("Ford", "Transit 350"),
-    ("Toyota", "Venza"),
-    ("Mercedes-Benz", "S 500"),
-    ("Cadillac", "Escalade ESV"),
-    ("Jeep", "Wagoneer"),
-    ("Chevrolet", "Bolt"),
-    ("MINI", "Cooper Countryman"),
-    ("Toyota", "Sequoia"),
-    ("Mercedes-Benz", "CLA 250"),
-    ("BMW", "X7"),
-    ("Cadillac", "CTS"),
-    ("Hyundai", "Venue"),
-    ("Volkswagen", "ID.4"),
-    ("Toyota", "Avalon"),
-    ("Jeep", "Patriot"),
-    ("Tesla", "Model Y"),
-    ("Nissan", "Leaf"),
-    ("Audi", "A3"),
-    ("Acura", "Integra"),
-    ("Ford", "Transit Connect"),
-    ("Lexus", "NX 300"),
-    ("Audi", "A6"),
-    ("Mercedes-Benz", "EQS 450+"),
-    ("Chevrolet", "Spark"),
-    ("Jaguar", "F-PACE"),
-    ("Mercedes-Benz", "S 580"),
-    ("Chevrolet", "Sonic"),
-    ("Lincoln", "Navigator"),
-    ("Toyota", "C-HR"),
-    ("Ford", "Fiesta"),
-    ("RAM", "ProMaster City"),
-    ("Volvo", "S60"),
-    ("BMW", "330i xDrive"),
-    ("Ford", "Flex"),
-    ("MAZDA", "MAZDA6"),
-    ("Toyota", "Corolla Cross"),
-    ("Lincoln", "MKZ"),
-    ("Chevrolet", "Express 3500"),
-    ("Hyundai", "Accent"),
-    ("Land Rover", "Discovery Sport"),
-    ("Tesla", "Model X"),
-    ("Honda", "Fit"),
-    ("Alfa Romeo", "Stelvio"),
-    ("Chrysler", "200"),
-    ("Volkswagen", "Beetle"),
-    ("Cadillac", "CT4"),
-    ("Ford", "Maverick"),
-    ("Volkswagen", "GTI"),
-    ("Lincoln", "MKC"),
-    ("Porsche", "Panamera"),
-    ("Ford", "F450"),
-    ("Lexus", "NX 350"),
-    ("Chrysler", "Town & Country"),
-    ("Kia", "Stinger"),
-    ("Land Rover", "Range Rover Velar"),
-    ("Audi", "S5"),
-    ("BMW", "330i"),
-    ("Volkswagen", "Golf"),
-    ("Mercedes-Benz", "GLS 450"),
-    ("Lexus", "IS 350"),
-    ("Land Rover", "Range Rover Evoque"),
-    ("Toyota", "Prius Prime"),
-    ("Acura", "ILX"),
-    ("Genesis", "G70"),
-    ("Ford", "Taurus"),
-    ("Hyundai", "Veloster"),
-    ("Lexus", "IS 300"),
-    ("Land Rover", "Defender"),
-    ("Genesis", "GV80"),
-    ("Alfa Romeo", "Giulia"),
-    ("BMW", "X6"),
-    ("Hyundai", "Ioniq 5"),
-    ("Audi", "SQ5"),
-    ("BMW", "328i"),
-    ("BMW", "i3"),
-    ("Cadillac", "ATS"),
-    ("Mercedes-Benz", "S 550"),
-    ("Lincoln", "Navigator L"),
-    ("Mercedes-Benz", "E 450"),
-    ("Buick", "LaCrosse"),
-    ("Ford", "E-350 and Econoline 350"),
-    ("BMW", "M3"),
-    ("Mercedes-Benz", "GLE 53 AMG"),
-    ("Lexus", "IS 250"),
-    ("Mercedes-Benz", "E 300"),
-    ("Cadillac", "SRX"),
-    ("GMC", "Savana 2500"),
-    ("INFINITI", "QX55"),
-    ("Mitsubishi", "Eclipse Cross"),
-    ("Audi", "Q8"),
-    ("INFINITI", "Q60"),
-    ("Kia", "Sedona"),
-    ("Lincoln", "MKX"),
-    ("Audi", "e-tron"),
-    ("Chevrolet", "Volt"),
-    ("BMW", "X4"),
-    ("Chevrolet", "Bolt EUV"),
-    ("Volvo", "C40"),
-    ("Maserati", "Ghibli"),
-    ("Lexus", "ES 300h"),
-    ("Jaguar", "F-TYPE"),
-    ("Cadillac", "XTS"),
-    ("Genesis", "GV70"),
-    ("BMW", "430i xDrive"),
-    ("BMW", "430i"),
-    ("BMW", "Z4"),
-    ("BMW", "M4"),
-    ("Land Rover", "Discovery"),
-    ("Lexus", "GS 350"),
-    ("Mercedes-Benz", "A 220"),
-    ("Dodge", "Ram 1500 Truck"),
-    ("Ford", "F550"),
-    ("Hyundai", "Ioniq"),
-    ("Mercedes-Benz", "ML 350"),
-    ("Genesis", "G80"),
-    ("MINI", "Cooper Clubman"),
-    ("Maserati", "Levante"),
-    ("Mercedes-Benz", "AMG GT"),
-    ("BMW", "530i xDrive"),
-    ("Lincoln", "Continental"),
-    ("Chrysler", "Voyager"),
-    ("Lexus", "LS 460"),
-    ("MAZDA", "MX-5 Miata RF"),
-    ("FIAT", "500"),
-    ("Cadillac", "CT6"),
-    ("MAZDA", "CX-3"),
-    ("BMW", "M5"),
-    ("BMW", "328i xDrive"),
-    ("Hyundai", "Genesis"),
-    ("Kia", "EV6"),
-    ("INFINITI", "G37"),
-    ("Audi", "A8"),
-    ("Audi", "S4"),
-    ("BMW", "X2"),
-    ("BMW", "530i"),
-    ("Lexus", "UX 250h"),
-    ("Lexus", "RX 350L"),
-    ("Mercedes-Benz", "G 63 AMG"),
-    ("Nissan", "Juke"),
-    ("Volkswagen", "Arteon"),
-    ("Honda", "Insight"),
-    ("Lexus", "RC 350"),
-    ("RAM", "5500"),
-    ("Audi", "A7"),
-    ("Lexus", "NX 200t"),
-    ("Nissan", "370Z"),
-    ("Porsche", "Boxster"),
-    ("BMW", "540i"),
-    ("Buick", "Regal"),
-    ("Dodge", "Dart"),
-    ("BMW", "540i xDrive"),
-    ("Mercedes-Benz", "GLE 450"),
-    ("Ford", "Expedition EL"),
-    ("Jeep", "Grand Wagoneer"),
-    ("Bentley", "Continental"),
-    ("Dodge", "Ram 2500 Truck"),
-    ("Jeep", "Liberty"),
-    ("Kia", "Carnival"),
-    ("Mitsubishi", "Mirage G4"),
-    ("Mercedes-Benz", "GL 450"),
-    ("Mitsubishi", "Mirage"),
-    ("Lexus", "RX 450h"),
-    ("Porsche", "Taycan"),
-    ("Acura", "TL"),
-    ("Lexus", "CT 200h"),
-    ("Nissan", "NV"),
-    ("BMW", "440i xDrive"),
-    ("Mercedes-Benz", "C 43 AMG"),
-    ("Mercedes-Benz", "EQS 580"),
-    ("Toyota", "Supra"),
-    ("Mercedes-Benz", "GLK 350"),
-    ("Lexus", "LS 500"),
-    ("Toyota", "Prius C"),
-    ("Toyota", "Yaris"),
-    ("Jaguar", "XF"),
-    ("Nissan", "Versa Note"),
-    ("BMW", "335i"),
-    ("Nissan", "Xterra"),
-    ("Lexus", "NX 250"),
-    ("Toyota", "FJ Cruiser"),
-    ("Audi", "RS 5"),
-    ("Volvo", "V60"),
-    ("Audi", "S3"),
-    ("BMW", "740i"),
-    ("BMW", "128i"),
-    ("Buick", "Verano"),
-    ("Subaru", "BRZ"),
-    ("Audi", "Q4 e-tron"),
-    ("Chevrolet", "Avalanche"),
-    ("Mercedes-Benz", "SL 550"),
-    ("Ford", "C-MAX"),
-    ("Toyota", "GR86"),
-    ("BMW", "750i xDrive"),
-    ("Ford", "Transit 150"),
-    ("Mercedes-Benz", "Metris"),
-    ("Mercedes-Benz", "S 560"),
-    ("Nissan", "NV200"),
-    ("Volkswagen", "Golf R"),
-    ("Mercedes-Benz", "SL 63 AMG"),
-    ("BMW", "M850i xDrive"),
-    ("Lexus", "LX 570"),
-    ("Mercedes-Benz", "G 550"),
-    ("Ford", "E-450 and Econoline 450"),
-    ("Ford", "E-Transit"),
-    ("Mercedes-Benz", "C 250"),
-    ("Mercedes-Benz", "CLS 450"),
-    ("Mercedes-Benz", "S 63 AMG"),
-    ("BMW", "530e"),
-    ("BMW", "428i"),
-    ("Mercedes-Benz", "GLC 43 AMG"),
-    ("Volvo", "S90"),
-    ("Dodge", "Avenger"),
-    ("Lexus", "NX 300h"),
-    ("Mercedes-Benz", "GLE 43 AMG"),
-    ("Mercedes-Benz", "E 400"),
-    ("Toyota", "Prius V"),
-    ("BMW", "X5 M"),
-    ("GMC", "Savana 3500"),
-    ("Scion", "tC"),
-    ("Volkswagen", "CC"),
-    ("Acura", "TSX"),
-    ("BMW", "228i xDrive"),
-    ("BMW", "535i xDrive"),
-    ("Porsche", "Cayman"),
-    ("Subaru", "Impreza WRX"),
-    ("BMW", "535i"),
-    ("BMW", "M8"),
-    ("Bentley", "Bentayga"),
-    ("Maserati", "Quattroporte"),
-    ("BMW", "M550i xDrive"),
-    ("Jaguar", "XE"),
-    ("Hyundai", "Kona N"),
-    ("Porsche", "718 Cayman"),
-    ("BMW", "M2"),
-    ("Mercedes-Benz", "C 63 AMG"),
-    ("BMW", "M340i"),
-    ("Hyundai", "Elantra N"),
-    ("BMW", "528i"),
-    ("Ford", "E-250 and Econoline 250"),
-    ("BMW", "i4"),
-    ("FIAT", "500X"),
-    ("BMW", "iX"),
-    ("Audi", "TT"),
-    ("Lexus", "IS 200t"),
-    ("Maserati", "GranTurismo"),
-    ("Dodge", "Ram 3500 Truck"),
-    ("BMW", "650i"),
-    ("Lexus", "UX 200"),
-    ("Dodge", "Dakota"),
-    ("INFINITI", "QX30"),
-    ("Mercedes-Benz", "GLE 63 AMG"),
-    ("Volkswagen", "Touareg"),
-    ("Volkswagen", "e-Golf"),
-    ("Lamborghini", "Huracan"),
-    ("Lexus", "LC 500"),
-    ("Land Rover", "LR4"),
-    ("Lexus", "NX 350h"),
-    ("BMW", "428i xDrive"),
-    ("Jaguar", "XJ"),
-    ("Lexus", "RC 300"),
-    ("Toyota", "Mirai"),
-    ("BMW", "330e"),
-    ("Genesis", "G90"),
-    ("Jaguar", "E-PACE"),
-    ("Lamborghini", "Urus"),
-    ("BMW", "M340i xDrive"),
-    ("Audi", "RS 7"),
-    ("Lexus", "ES 250"),
-    ("Mercedes-Benz", "SL 55 AMG"),
-    ("BMW", "320i"),
-    ("Toyota", "Land Cruiser"),
-    ("Ford", "Thunderbird"),
-    ("Honda", "Element"),
-    ("Scion", "xB"),
-    ("BMW", "530e xDrive"),
-    ("Porsche", "718 Boxster"),
-    ("Buick", "Lucerne"),
-    ("Mercedes-Benz", "E 53 AMG"),
-    ("Mitsubishi", "Lancer"),
-    ("Polestar", "Polestar 2"),
-    ("RAM", "4500"),
-    ("Scion", "FR-S"),
-    ("Mercedes-Benz", "E 550"),
-    ("Nissan", "GT-R"),
-    ("BMW", "X6 M"),
-    ("INFINITI", "Q70"),
-    ("Audi", "R8"),
-    ("Honda", "Clarity"),
-    ("Mercedes-Benz", "E 63 AMG"),
-    ("BMW", "320i xDrive"),
-    ("Ford", "E-150 and Econoline 150"),
-    ("Lexus", "GX 470"),
-    ("Lincoln", "MKS"),
-    ("BMW", "135i"),
-    ("Mercedes-Benz", "GL 550"),
-    ("Toyota", "86"),
-    ("smart", "fortwo"),
-    ("Chevrolet", "Express 1500"),
-    ("BMW", "528i xDrive"),
-    ("BMW", "M440i"),
-    ("BMW", "230i"),
-    ("INFINITI", "G35"),
-    ("Mercedes-Benz", "S 450"),
-    ("Mercedes-Benz", "SL 500"),
-    ("BMW", "435i xDrive"),
-    ("FIAT", "124 Spider"),
-    ("Mercedes-Benz", "CLS 550"),
-    ("Mercedes-Benz", "EQE 350+"),
-    ("Mercury", "Grand Marquis"),
-    ("Volkswagen", "Eos"),
-    ("Chrysler", "PT Cruiser"),
-    ("Lexus", "SC 430"),
-    ("Lincoln", "Town Car"),
-    ("Nissan", "Quest"),
-    ("Audi", "S8"),
-    ("BMW", "435i"),
-    ("HUMMER", "H2"),
-    ("Kia", "Cadenza"),
-    ("BMW", "228i"),
-    ("Chrysler", "Sebring"),
-    ("Volvo", "XC70"),
-    ("BMW", "335i xDrive"),
-    ("Chevrolet", "Captiva Sport"),
-    ("Ferrari", "California"),
-    ("Ford", "Excursion"),
-    ("BMW", "440i"),
-    ("Chevrolet", "HHR"),
-    ("INFINITI", "QX56"),
-    ("INFINITI", "QX70"),
-    ("MAZDA", "MAZDA5"),
-    ("Pontiac", "G6"),
-    ("Chevrolet", "Cobalt"),
-    ("Rivian", "R1T"),
-    ("Audi", "S6"),
-    ("BMW", "750i"),
-    ("BMW", "M240i xDrive"),
-    ("BMW", "i8"),
-)
-
-MAKE_MODEL_TO_INDEX = {x: i for i, x in enumerate(MAKES_MODELS)}
-
-NUM_MAKE_MODELS = len(MAKE_MODEL_TO_INDEX) + 1
diff --git a/spaces/usbethFlerru/sovits-modelsV2/example/BANG The Spaghetti-Western Board Game.rar.md b/spaces/usbethFlerru/sovits-modelsV2/example/BANG The Spaghetti-Western Board Game.rar.md
deleted file mode 100644
index 56bcb334bac35f5e8087ae2b072a8515cd1ec1d0..0000000000000000000000000000000000000000
--- a/spaces/usbethFlerru/sovits-modelsV2/example/BANG The Spaghetti-Western Board Game.rar.md	
+++ /dev/null
@@ -1,7 +0,0 @@
-
-<p>Bang a Gong (Get It On) still plays a crucial part in pop culture.. How has this not become a TV movie yet, or at least a board game Church Board of Education and Board of Trustees Members. Steven P. Bang. and in 1999 moved into the top tier of liberal arts colleges in the western. </p>
-<p>Robert J. Webb, the bestselling author of Cowboys & Indians, The Cowpokes, and many other titles, published his first board game The Bang! game in 1989. What have you done to your head? Bang! features three or four players, and is set in the wild west. Bang!'s rules are original, colorful, easy to follow, and all players' moves are simultaneous. Bang!'s rules include 20-30 minutes per game, and it may be played from three to four hours or more per game. </p>
-<h2>BANG the Spaghetti-Western Board Game.rar</h2><br /><p><b><b>DOWNLOAD</b> &#11088; <a href="https://urlcod.com/2uyX6I">https://urlcod.com/2uyX6I</a></b></p><br /><br />
-<p>When Indians and Cowboys meet at the gambling tables, you can bet on who will win! Like other board games, Bang has unique rules. Only players who read the rules will be able to play. Before the game begins, players each pick a hand of cards from three decks. If a game is won or lost by the hand you draw, keep it. If a game is won or lost by the hand you draw, discard it and draw a new hand. For the first player in each hand, draw a card, turn the next card, and compare the cards. If one of the players has the best hand, he or she wins. The winner gets an extra turn. The second player in each player's hand takes a turn, following the order of the first player. If one player has the best hand, he or she wins. The second player in each player's hand takes a turn, following the order of the first player. If one player has the best hand, he or she wins. The main idea of the game is for a player to keep drawing cards from his hand until he has a winning hand. However, this is often more of a guessing game and opportunities to bluff.</p> 899543212b<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/usbethFlerru/sovits-modelsV2/example/CodeGear RAD Studio 2007 Full ( Delphi 2007 ) Serial Key Best Practices and Recommendations for Developers.md b/spaces/usbethFlerru/sovits-modelsV2/example/CodeGear RAD Studio 2007 Full ( Delphi 2007 ) Serial Key Best Practices and Recommendations for Developers.md
deleted file mode 100644
index 55855f11d08e760a3eaf15a7f2a6a843cea958c0..0000000000000000000000000000000000000000
--- a/spaces/usbethFlerru/sovits-modelsV2/example/CodeGear RAD Studio 2007 Full ( Delphi 2007 ) Serial Key Best Practices and Recommendations for Developers.md	
+++ /dev/null
@@ -1,5 +0,0 @@
-
-<p>Update 3 fixes several Delphi problems as well as several C++ problems, including improvements to the documentation. The update can be applied to both Delphi and C++Builder 2007. Similar to update 1, the update will uninstall your old IDE version and reinstall the new version (which can be quite slow), though your settings and components should survive the upgrade process, since the IDE registry entries are not cleared. The recommended way to upgrade is using the "Check For Updates" start menu item, but you can also download the full update using the link below. Also, you can use that download for installing Delphi from scratch, it's a full installer that contains everything. The build number for Delphi 2007 Update 3 is <b>11.0.2804.9245</b>.</p>
-<h2>CodeGear RAD Studio 2007 Full ( Delphi 2007 ) Serial Key</h2><br /><p><b><b>Download File</b> &#127775; <a href="https://urlcod.com/2uyU3V">https://urlcod.com/2uyU3V</a></b></p><br /><br /> aaccfb2cb3<br />
-<br />
-<br />
\ No newline at end of file
diff --git a/spaces/valhalla/minDALLE/dalle/__init__.py b/spaces/valhalla/minDALLE/dalle/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/vg055/demo_analisis_de_sentimientos_textos_turisticos_mx_tipo/README.md b/spaces/vg055/demo_analisis_de_sentimientos_textos_turisticos_mx_tipo/README.md
deleted file mode 100644
index 1f13dcd04ce86561ffb9eb8275e6d6f4d5f5ec5b..0000000000000000000000000000000000000000
--- a/spaces/vg055/demo_analisis_de_sentimientos_textos_turisticos_mx_tipo/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Demo Analisis De Sentimientos Textos Turisticos Mx Tipo
-emoji: 🌍
-colorFrom: yellow
-colorTo: pink
-sdk: gradio
-sdk_version: 3.24.1
-app_file: app.py
-pinned: false
-license: unknown
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
diff --git a/spaces/vinthony/SadTalker/src/face3d/models/arcface_torch/utils/utils_logging.py b/spaces/vinthony/SadTalker/src/face3d/models/arcface_torch/utils/utils_logging.py
deleted file mode 100644
index c787b6aae7cd037a4718df44d672b8ffa9e5c249..0000000000000000000000000000000000000000
--- a/spaces/vinthony/SadTalker/src/face3d/models/arcface_torch/utils/utils_logging.py
+++ /dev/null
@@ -1,41 +0,0 @@
-import logging
-import os
-import sys
-
-
-class AverageMeter(object):
-    """Computes and stores the average and current value
-    """
-
-    def __init__(self):
-        self.val = None
-        self.avg = None
-        self.sum = None
-        self.count = None
-        self.reset()
-
-    def reset(self):
-        self.val = 0
-        self.avg = 0
-        self.sum = 0
-        self.count = 0
-
-    def update(self, val, n=1):
-        self.val = val
-        self.sum += val * n
-        self.count += n
-        self.avg = self.sum / self.count
-
-
-def init_logging(rank, models_root):
-    if rank == 0:
-        log_root = logging.getLogger()
-        log_root.setLevel(logging.INFO)
-        formatter = logging.Formatter("Training: %(asctime)s-%(message)s")
-        handler_file = logging.FileHandler(os.path.join(models_root, "training.log"))
-        handler_stream = logging.StreamHandler(sys.stdout)
-        handler_file.setFormatter(formatter)
-        handler_stream.setFormatter(formatter)
-        log_root.addHandler(handler_file)
-        log_root.addHandler(handler_stream)
-        log_root.info('rank_id: %d' % rank)
diff --git a/spaces/vslasor/VLS3-ChatbotBlenderbot-GR/app.py b/spaces/vslasor/VLS3-ChatbotBlenderbot-GR/app.py
deleted file mode 100644
index ca545aad434176426ca5ee2190b8e753d46a10df..0000000000000000000000000000000000000000
--- a/spaces/vslasor/VLS3-ChatbotBlenderbot-GR/app.py
+++ /dev/null
@@ -1,134 +0,0 @@
-from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration
-import torch
-import gradio as gr
-
-
-# PersistDataset -----
-import os
-import csv
-import gradio as gr
-from gradio import inputs, outputs
-import huggingface_hub
-from huggingface_hub import Repository, hf_hub_download, upload_file
-from datetime import datetime
-
-
-# -------------------------------------------- For Memory - you will need to set up a dataset and HF_TOKEN ---------
-#DATASET_REPO_URL = "https://huggingface.co/datasets/awacke1/ChatbotMemory.csv"
-#DATASET_REPO_ID = "awacke1/ChatbotMemory.csv"
-#DATA_FILENAME = "ChatbotMemory.csv"
-#DATA_FILE = os.path.join("data", DATA_FILENAME)
-#HF_TOKEN = os.environ.get("HF_TOKEN")
-
-#SCRIPT = """
-#<script>
-#if (!window.hasBeenRun) {
-#    window.hasBeenRun = true;
-#    console.log("should only happen once");
-#    document.querySelector("button.submit").click();
-#}
-#</script>
-#"""
-
-#try:
-#    hf_hub_download(
-#        repo_id=DATASET_REPO_ID,
-#        filename=DATA_FILENAME,
-#        cache_dir=DATA_DIRNAME,
-#        force_filename=DATA_FILENAME
-#    )
-#except:
-#    print("file not found")
-#repo = Repository(
-#    local_dir="data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
-#)
-            
-#def store_message(name: str, message: str):
-#    if name and message:
-#        with open(DATA_FILE, "a") as csvfile:
-#            writer = csv.DictWriter(csvfile, fieldnames=["name", "message", "time"])
-#            writer.writerow(
-#                {"name": name.strip(), "message": message.strip(), "time": str(datetime.now())}
-#            )
-# uncomment line below to begin saving.  If creating your own copy you will need to add a access token called "HF_TOKEN" to your profile, then create a secret for your repo with the access code naming it "HF_TOKEN"  For the CSV as well you can copy the header and first few lines to your own then update the paths above which should work to save to your own repository for datasets.    
-#        commit_url = repo.push_to_hub()
-#    return ""
-    
-#iface = gr.Interface(
-#    store_message,
-#    [
-#        inputs.Textbox(placeholder="Your name"),
-#        inputs.Textbox(placeholder="Your message", lines=2),
-#    ],
-#    "html",
-#    css="""
-#    .message {background-color:cornflowerblue;color:white; padding:4px;margin:4px;border-radius:4px; }
-#    """,
-#    title="Reading/writing to a HuggingFace dataset repo from Spaces",
-#    description=f"This is a demo of how to do simple *shared data persistence* in a Gradio Space, backed by a dataset repo.",
-#    article=f"The dataset repo is [{DATASET_REPO_URL}]({DATASET_REPO_URL})",
-#)
-# --------------------------------------------------- For Memory
-
-mname = "facebook/blenderbot-400M-distill"
-model = BlenderbotForConditionalGeneration.from_pretrained(mname)
-tokenizer = BlenderbotTokenizer.from_pretrained(mname)
-
-def take_last_tokens(inputs, note_history, history):
-    """Filter the last 128 tokens"""
-    if inputs['input_ids'].shape[1] > 128:
-        inputs['input_ids'] = torch.tensor([inputs['input_ids'][0][-128:].tolist()])
-        inputs['attention_mask'] = torch.tensor([inputs['attention_mask'][0][-128:].tolist()])
-        note_history = ['</s> <s>'.join(note_history[0].split('</s> <s>')[2:])]
-        history = history[1:]
-    return inputs, note_history, history
-
-def add_note_to_history(note, note_history):
-    """Add a note to the historical information"""
-    note_history.append(note)
-    note_history = '</s> <s>'.join(note_history)
-    return [note_history]
-
-title = "State of the Art Chatbot with Memory Dataset"
-description = """Chatbot With Memory"""
-
-def chat(message, history):
-    history = history or []
-    if history: 
-        history_useful = ['</s> <s>'.join([str(a[0])+'</s> <s>'+str(a[1]) for a in history])]
-    else:
-        history_useful = []
-    history_useful = add_note_to_history(message, history_useful)
-    inputs = tokenizer(history_useful, return_tensors="pt")
-    inputs, history_useful, history = take_last_tokens(inputs, history_useful, history)
-    reply_ids = model.generate(**inputs)
-    response = tokenizer.batch_decode(reply_ids, skip_special_tokens=True)[0]
-    history_useful = add_note_to_history(response, history_useful)
-    list_history = history_useful[0].split('</s> <s>')
-    history.append((list_history[-2], list_history[-1]))
-#    store_message(message, response) # Save to dataset  -- uncomment with code above, create a dataset to store and add your HF_TOKEN from profile to this repo to use.
-    return history, history
-
-gr.Interface(
-    fn=chat,
-    theme="huggingface",
-    css=".footer {display:none !important}",
-    inputs=["text", "state"],
-    outputs=["chatbot", "state"],
-    title=title,
-    allow_flagging="never",
-    description=f"Gradio chatbot backed by memory in a dataset repository.",
-#    article=f"The dataset repo is [{DATASET_REPO_URL}]({DATASET_REPO_URL})"
-    ).launch(debug=True)
-        
-#demo = gr.Blocks()
-#with demo:
-#    audio_file = gr.inputs.Audio(source="microphone", type="filepath")
-#    text = gr.Textbox(label="Speech to Text")
-#    TTSchoice = gr.inputs.Radio( label="Pick a Text to Speech Model", choices=MODEL_NAMES,   )
-#    audio = gr.Audio(label="Output", interactive=False)
-#    b1 = gr.Button("Recognize Speech")
-#    b5 = gr.Button("Read It Back Aloud")
-#    b1.click(speech_to_text, inputs=audio_file, outputs=text)
-#    b5.click(tts,  inputs=[text,TTSchoice], outputs=audio)    
-#demo.launch(share=True)
diff --git a/spaces/weibinke/vits-simple-api/vits/text/japanese.py b/spaces/weibinke/vits-simple-api/vits/text/japanese.py
deleted file mode 100644
index 375e4d50872d5c68ee57ca17470a2ca425425eba..0000000000000000000000000000000000000000
--- a/spaces/weibinke/vits-simple-api/vits/text/japanese.py
+++ /dev/null
@@ -1,153 +0,0 @@
-import re
-from unidecode import unidecode
-import pyopenjtalk
-
-
-# Regular expression matching Japanese without punctuation marks:
-_japanese_characters = re.compile(
-    r'[A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]')
-
-# Regular expression matching non-Japanese characters or punctuation marks:
-_japanese_marks = re.compile(
-    r'[^A-Za-z\d\u3005\u3040-\u30ff\u4e00-\u9fff\uff11-\uff19\uff21-\uff3a\uff41-\uff5a\uff66-\uff9d]')
-
-# List of (symbol, Japanese) pairs for marks:
-_symbols_to_japanese = [(re.compile('%s' % x[0]), x[1]) for x in [
-    ('％', 'パーセント')
-]]
-
-# List of (romaji, ipa) pairs for marks:
-_romaji_to_ipa = [(re.compile('%s' % x[0]), x[1]) for x in [
-    ('ts', 'ʦ'),
-    ('u', 'ɯ'),
-    ('j', 'ʥ'),
-    ('y', 'j'),
-    ('ni', 'n^i'),
-    ('nj', 'n^'),
-    ('hi', 'çi'),
-    ('hj', 'ç'),
-    ('f', 'ɸ'),
-    ('I', 'i*'),
-    ('U', 'ɯ*'),
-    ('r', 'ɾ')
-]]
-
-# List of (romaji, ipa2) pairs for marks:
-_romaji_to_ipa2 = [(re.compile('%s' % x[0]), x[1]) for x in [
-    ('u', 'ɯ'),
-    ('ʧ', 'tʃ'),
-    ('j', 'dʑ'),
-    ('y', 'j'),
-    ('ni', 'n^i'),
-    ('nj', 'n^'),
-    ('hi', 'çi'),
-    ('hj', 'ç'),
-    ('f', 'ɸ'),
-    ('I', 'i*'),
-    ('U', 'ɯ*'),
-    ('r', 'ɾ')
-]]
-
-# List of (consonant, sokuon) pairs:
-_real_sokuon = [(re.compile('%s' % x[0]), x[1]) for x in [
-    (r'Q([↑↓]*[kg])', r'k#\1'),
-    (r'Q([↑↓]*[tdjʧ])', r't#\1'),
-    (r'Q([↑↓]*[sʃ])', r's\1'),
-    (r'Q([↑↓]*[pb])', r'p#\1')
-]]
-
-# List of (consonant, hatsuon) pairs:
-_real_hatsuon = [(re.compile('%s' % x[0]), x[1]) for x in [
-    (r'N([↑↓]*[pbm])', r'm\1'),
-    (r'N([↑↓]*[ʧʥj])', r'n^\1'),
-    (r'N([↑↓]*[tdn])', r'n\1'),
-    (r'N([↑↓]*[kg])', r'ŋ\1')
-]]
-
-
-def symbols_to_japanese(text):
-    for regex, replacement in _symbols_to_japanese:
-        text = re.sub(regex, replacement, text)
-    return text
-
-
-def japanese_to_romaji_with_accent(text):
-    '''Reference https://r9y9.github.io/ttslearn/latest/notebooks/ch10_Recipe-Tacotron.html'''
-    text = symbols_to_japanese(text)
-    sentences = re.split(_japanese_marks, text)
-    marks = re.findall(_japanese_marks, text)
-    text = ''
-    for i, sentence in enumerate(sentences):
-        if re.match(_japanese_characters, sentence):
-            if text != '':
-                text += ' '
-            labels = pyopenjtalk.extract_fullcontext(sentence)
-            for n, label in enumerate(labels):
-                phoneme = re.search(r'\-([^\+]*)\+', label).group(1)
-                if phoneme not in ['sil', 'pau']:
-                    text += phoneme.replace('ch', 'ʧ').replace('sh',
-                                                               'ʃ').replace('cl', 'Q')
-                else:
-                    continue
-                # n_moras = int(re.search(r'/F:(\d+)_', label).group(1))
-                a1 = int(re.search(r"/A:(\-?[0-9]+)\+", label).group(1))
-                a2 = int(re.search(r"\+(\d+)\+", label).group(1))
-                a3 = int(re.search(r"\+(\d+)/", label).group(1))
-                if re.search(r'\-([^\+]*)\+', labels[n + 1]).group(1) in ['sil', 'pau']:
-                    a2_next = -1
-                else:
-                    a2_next = int(
-                        re.search(r"\+(\d+)\+", labels[n + 1]).group(1))
-                # Accent phrase boundary
-                if a3 == 1 and a2_next == 1:
-                    text += ' '
-                # Falling
-                elif a1 == 0 and a2_next == a2 + 1:
-                    text += '↓'
-                # Rising
-                elif a2 == 1 and a2_next == 2:
-                    text += '↑'
-        if i < len(marks):
-            text += unidecode(marks[i]).replace(' ', '')
-    return text
-
-
-def get_real_sokuon(text):
-    for regex, replacement in _real_sokuon:
-        text = re.sub(regex, replacement, text)
-    return text
-
-
-def get_real_hatsuon(text):
-    for regex, replacement in _real_hatsuon:
-        text = re.sub(regex, replacement, text)
-    return text
-
-
-def japanese_to_ipa(text):
-    text = japanese_to_romaji_with_accent(text).replace('...', '…')
-    text = re.sub(
-        r'([aiueo])\1+', lambda x: x.group(0)[0]+'ː'*(len(x.group(0))-1), text)
-    text = get_real_sokuon(text)
-    text = get_real_hatsuon(text)
-    for regex, replacement in _romaji_to_ipa:
-        text = re.sub(regex, replacement, text)
-    return text
-
-
-def japanese_to_ipa2(text):
-    text = japanese_to_romaji_with_accent(text).replace('...', '…')
-    text = get_real_sokuon(text)
-    text = get_real_hatsuon(text)
-    for regex, replacement in _romaji_to_ipa2:
-        text = re.sub(regex, replacement, text)
-    return text
-
-
-def japanese_to_ipa3(text):
-    text = japanese_to_ipa2(text).replace('n^', 'ȵ').replace(
-        'ʃ', 'ɕ').replace('*', '\u0325').replace('#', '\u031a')
-    text = re.sub(
-        r'([aiɯeo])\1+', lambda x: x.group(0)[0]+'ː'*(len(x.group(0))-1), text)
-    text = re.sub(r'((?:^|\s)(?:ts|tɕ|[kpt]))', r'\1ʰ', text)
-    return text
diff --git a/spaces/whitphx/gradio-static-test/dist/assets/color-892826ae.js b/spaces/whitphx/gradio-static-test/dist/assets/color-892826ae.js
deleted file mode 100644
index dd09c0fcea1cb6d81b258626eee6b10374f6d64d..0000000000000000000000000000000000000000
--- a/spaces/whitphx/gradio-static-test/dist/assets/color-892826ae.js
+++ /dev/null
@@ -1,2 +0,0 @@
-import{aq as o}from"../lite.js";const t=r=>o[r%o.length];export{t as g};
-//# sourceMappingURL=color-892826ae.js.map
diff --git a/spaces/xdecoder/Demo/xdecoder/body/encoder/build.py b/spaces/xdecoder/Demo/xdecoder/body/encoder/build.py
deleted file mode 100644
index aabf8bca5c6f54144af3187692afc28de4c9e296..0000000000000000000000000000000000000000
--- a/spaces/xdecoder/Demo/xdecoder/body/encoder/build.py
+++ /dev/null
@@ -1,12 +0,0 @@
-from .registry import model_entrypoints
-from .registry import is_model
-
-from .transformer_encoder_fpn import *
-
-def build_encoder(config, *args, **kwargs):
-    model_name = config['MODEL']['ENCODER']['NAME']
-
-    if not is_model(model_name):
-        raise ValueError(f'Unkown model: {model_name}')
-
-    return model_entrypoints(model_name)(config, *args, **kwargs)
\ No newline at end of file
diff --git a/spaces/xfys/yolov5_tracking/trackers/strong_sort/deep/reid/torchreid/models/xception.py b/spaces/xfys/yolov5_tracking/trackers/strong_sort/deep/reid/torchreid/models/xception.py
deleted file mode 100644
index 43db4ab53283daf1267f2f4cc5f7d778daf4076a..0000000000000000000000000000000000000000
--- a/spaces/xfys/yolov5_tracking/trackers/strong_sort/deep/reid/torchreid/models/xception.py
+++ /dev/null
@@ -1,344 +0,0 @@
-from __future__ import division, absolute_import
-import torch.nn as nn
-import torch.nn.functional as F
-import torch.utils.model_zoo as model_zoo
-
-__all__ = ['xception']
-
-pretrained_settings = {
-    'xception': {
-        'imagenet': {
-            'url':
-            'http://data.lip6.fr/cadene/pretrainedmodels/xception-43020ad28.pth',
-            'input_space': 'RGB',
-            'input_size': [3, 299, 299],
-            'input_range': [0, 1],
-            'mean': [0.5, 0.5, 0.5],
-            'std': [0.5, 0.5, 0.5],
-            'num_classes': 1000,
-            'scale':
-            0.8975 # The resize parameter of the validation transform should be 333, and make sure to center crop at 299x299
-        }
-    }
-}
-
-
-class SeparableConv2d(nn.Module):
-
-    def __init__(
-        self,
-        in_channels,
-        out_channels,
-        kernel_size=1,
-        stride=1,
-        padding=0,
-        dilation=1,
-        bias=False
-    ):
-        super(SeparableConv2d, self).__init__()
-
-        self.conv1 = nn.Conv2d(
-            in_channels,
-            in_channels,
-            kernel_size,
-            stride,
-            padding,
-            dilation,
-            groups=in_channels,
-            bias=bias
-        )
-        self.pointwise = nn.Conv2d(
-            in_channels, out_channels, 1, 1, 0, 1, 1, bias=bias
-        )
-
-    def forward(self, x):
-        x = self.conv1(x)
-        x = self.pointwise(x)
-        return x
-
-
-class Block(nn.Module):
-
-    def __init__(
-        self,
-        in_filters,
-        out_filters,
-        reps,
-        strides=1,
-        start_with_relu=True,
-        grow_first=True
-    ):
-        super(Block, self).__init__()
-
-        if out_filters != in_filters or strides != 1:
-            self.skip = nn.Conv2d(
-                in_filters, out_filters, 1, stride=strides, bias=False
-            )
-            self.skipbn = nn.BatchNorm2d(out_filters)
-        else:
-            self.skip = None
-
-        self.relu = nn.ReLU(inplace=True)
-        rep = []
-
-        filters = in_filters
-        if grow_first:
-            rep.append(self.relu)
-            rep.append(
-                SeparableConv2d(
-                    in_filters,
-                    out_filters,
-                    3,
-                    stride=1,
-                    padding=1,
-                    bias=False
-                )
-            )
-            rep.append(nn.BatchNorm2d(out_filters))
-            filters = out_filters
-
-        for i in range(reps - 1):
-            rep.append(self.relu)
-            rep.append(
-                SeparableConv2d(
-                    filters, filters, 3, stride=1, padding=1, bias=False
-                )
-            )
-            rep.append(nn.BatchNorm2d(filters))
-
-        if not grow_first:
-            rep.append(self.relu)
-            rep.append(
-                SeparableConv2d(
-                    in_filters,
-                    out_filters,
-                    3,
-                    stride=1,
-                    padding=1,
-                    bias=False
-                )
-            )
-            rep.append(nn.BatchNorm2d(out_filters))
-
-        if not start_with_relu:
-            rep = rep[1:]
-        else:
-            rep[0] = nn.ReLU(inplace=False)
-
-        if strides != 1:
-            rep.append(nn.MaxPool2d(3, strides, 1))
-        self.rep = nn.Sequential(*rep)
-
-    def forward(self, inp):
-        x = self.rep(inp)
-
-        if self.skip is not None:
-            skip = self.skip(inp)
-            skip = self.skipbn(skip)
-        else:
-            skip = inp
-
-        x += skip
-        return x
-
-
-class Xception(nn.Module):
-    """Xception.
-    
-    Reference:
-        Chollet. Xception: Deep Learning with Depthwise
-        Separable Convolutions. CVPR 2017.
-
-    Public keys:
-        - ``xception``: Xception.
-    """
-
-    def __init__(
-        self, num_classes, loss, fc_dims=None, dropout_p=None, **kwargs
-    ):
-        super(Xception, self).__init__()
-        self.loss = loss
-
-        self.conv1 = nn.Conv2d(3, 32, 3, 2, 0, bias=False)
-        self.bn1 = nn.BatchNorm2d(32)
-
-        self.conv2 = nn.Conv2d(32, 64, 3, bias=False)
-        self.bn2 = nn.BatchNorm2d(64)
-
-        self.block1 = Block(
-            64, 128, 2, 2, start_with_relu=False, grow_first=True
-        )
-        self.block2 = Block(
-            128, 256, 2, 2, start_with_relu=True, grow_first=True
-        )
-        self.block3 = Block(
-            256, 728, 2, 2, start_with_relu=True, grow_first=True
-        )
-
-        self.block4 = Block(
-            728, 728, 3, 1, start_with_relu=True, grow_first=True
-        )
-        self.block5 = Block(
-            728, 728, 3, 1, start_with_relu=True, grow_first=True
-        )
-        self.block6 = Block(
-            728, 728, 3, 1, start_with_relu=True, grow_first=True
-        )
-        self.block7 = Block(
-            728, 728, 3, 1, start_with_relu=True, grow_first=True
-        )
-
-        self.block8 = Block(
-            728, 728, 3, 1, start_with_relu=True, grow_first=True
-        )
-        self.block9 = Block(
-            728, 728, 3, 1, start_with_relu=True, grow_first=True
-        )
-        self.block10 = Block(
-            728, 728, 3, 1, start_with_relu=True, grow_first=True
-        )
-        self.block11 = Block(
-            728, 728, 3, 1, start_with_relu=True, grow_first=True
-        )
-
-        self.block12 = Block(
-            728, 1024, 2, 2, start_with_relu=True, grow_first=False
-        )
-
-        self.conv3 = SeparableConv2d(1024, 1536, 3, 1, 1)
-        self.bn3 = nn.BatchNorm2d(1536)
-
-        self.conv4 = SeparableConv2d(1536, 2048, 3, 1, 1)
-        self.bn4 = nn.BatchNorm2d(2048)
-
-        self.global_avgpool = nn.AdaptiveAvgPool2d(1)
-        self.feature_dim = 2048
-        self.fc = self._construct_fc_layer(fc_dims, 2048, dropout_p)
-        self.classifier = nn.Linear(self.feature_dim, num_classes)
-
-        self._init_params()
-
-    def _construct_fc_layer(self, fc_dims, input_dim, dropout_p=None):
-        """Constructs fully connected layer.
-
-        Args:
-            fc_dims (list or tuple): dimensions of fc layers, if None, no fc layers are constructed
-            input_dim (int): input dimension
-            dropout_p (float): dropout probability, if None, dropout is unused
-        """
-        if fc_dims is None:
-            self.feature_dim = input_dim
-            return None
-
-        assert isinstance(
-            fc_dims, (list, tuple)
-        ), 'fc_dims must be either list or tuple, but got {}'.format(
-            type(fc_dims)
-        )
-
-        layers = []
-        for dim in fc_dims:
-            layers.append(nn.Linear(input_dim, dim))
-            layers.append(nn.BatchNorm1d(dim))
-            layers.append(nn.ReLU(inplace=True))
-            if dropout_p is not None:
-                layers.append(nn.Dropout(p=dropout_p))
-            input_dim = dim
-
-        self.feature_dim = fc_dims[-1]
-
-        return nn.Sequential(*layers)
-
-    def _init_params(self):
-        for m in self.modules():
-            if isinstance(m, nn.Conv2d):
-                nn.init.kaiming_normal_(
-                    m.weight, mode='fan_out', nonlinearity='relu'
-                )
-                if m.bias is not None:
-                    nn.init.constant_(m.bias, 0)
-            elif isinstance(m, nn.BatchNorm2d):
-                nn.init.constant_(m.weight, 1)
-                nn.init.constant_(m.bias, 0)
-            elif isinstance(m, nn.BatchNorm1d):
-                nn.init.constant_(m.weight, 1)
-                nn.init.constant_(m.bias, 0)
-            elif isinstance(m, nn.Linear):
-                nn.init.normal_(m.weight, 0, 0.01)
-                if m.bias is not None:
-                    nn.init.constant_(m.bias, 0)
-
-    def featuremaps(self, input):
-        x = self.conv1(input)
-        x = self.bn1(x)
-        x = F.relu(x, inplace=True)
-
-        x = self.conv2(x)
-        x = self.bn2(x)
-        x = F.relu(x, inplace=True)
-
-        x = self.block1(x)
-        x = self.block2(x)
-        x = self.block3(x)
-        x = self.block4(x)
-        x = self.block5(x)
-        x = self.block6(x)
-        x = self.block7(x)
-        x = self.block8(x)
-        x = self.block9(x)
-        x = self.block10(x)
-        x = self.block11(x)
-        x = self.block12(x)
-
-        x = self.conv3(x)
-        x = self.bn3(x)
-        x = F.relu(x, inplace=True)
-
-        x = self.conv4(x)
-        x = self.bn4(x)
-        x = F.relu(x, inplace=True)
-        return x
-
-    def forward(self, x):
-        f = self.featuremaps(x)
-        v = self.global_avgpool(f)
-        v = v.view(v.size(0), -1)
-
-        if self.fc is not None:
-            v = self.fc(v)
-
-        if not self.training:
-            return v
-
-        y = self.classifier(v)
-
-        if self.loss == 'softmax':
-            return y
-        elif self.loss == 'triplet':
-            return y, v
-        else:
-            raise KeyError('Unsupported loss: {}'.format(self.loss))
-
-
-def init_pretrained_weights(model, model_url):
-    """Initialize models with pretrained weights.
-    
-    Layers that don't match with pretrained layers in name or size are kept unchanged.
-    """
-    pretrain_dict = model_zoo.load_url(model_url)
-    model_dict = model.state_dict()
-    pretrain_dict = {
-        k: v
-        for k, v in pretrain_dict.items()
-        if k in model_dict and model_dict[k].size() == v.size()
-    }
-    model_dict.update(pretrain_dict)
-    model.load_state_dict(model_dict)
-
-
-def xception(num_classes, loss='softmax', pretrained=True, **kwargs):
-    model = Xception(num_classes, loss, fc_dims=None, dropout_p=None, **kwargs)
-    if pretrained:
-        model_url = pretrained_settings['xception']['imagenet']['url']
-        init_pretrained_weights(model, model_url)
-    return model
diff --git a/spaces/xfys/yolov5_tracking/yolov5/utils/__init__.py b/spaces/xfys/yolov5_tracking/yolov5/utils/__init__.py
deleted file mode 100644
index 916b06f5b69b5a8dd7139716ab6d95e3185fa385..0000000000000000000000000000000000000000
--- a/spaces/xfys/yolov5_tracking/yolov5/utils/__init__.py
+++ /dev/null
@@ -1,82 +0,0 @@
-# YOLOv5 🚀 by Ultralytics, AGPL-3.0 license
-"""
-utils/initialization
-"""
-
-import contextlib
-import platform
-import threading
-
-
-def emojis(str=''):
-    # Return platform-dependent emoji-safe version of string
-    return str.encode().decode('ascii', 'ignore') if platform.system() == 'Windows' else str
-
-
-class TryExcept(contextlib.ContextDecorator):
-    # YOLOv5 TryExcept class. Usage: @TryExcept() decorator or 'with TryExcept():' context manager
-    def __init__(self, msg=''):
-        self.msg = msg
-
-    def __enter__(self):
-        pass
-
-    def __exit__(self, exc_type, value, traceback):
-        if value:
-            print(emojis(f"{self.msg}{': ' if self.msg else ''}{value}"))
-        return True
-
-
-def threaded(func):
-    # Multi-threads a target function and returns thread. Usage: @threaded decorator
-    def wrapper(*args, **kwargs):
-        thread = threading.Thread(target=func, args=args, kwargs=kwargs, daemon=True)
-        thread.start()
-        return thread
-
-    return wrapper
-
-
-def join_threads(verbose=False):
-    # Join all daemon threads, i.e. atexit.register(lambda: join_threads())
-    main_thread = threading.current_thread()
-    for t in threading.enumerate():
-        if t is not main_thread:
-            if verbose:
-                print(f'Joining thread {t.name}')
-            t.join()
-
-
-def notebook_init(verbose=True):
-    # Check system software and hardware
-    print('Checking setup...')
-
-    import os
-    import shutil
-
-    from utils.general import check_font, check_requirements, is_colab
-    from utils.torch_utils import select_device  # imports
-
-    check_font()
-
-    import psutil
-
-    if is_colab():
-        shutil.rmtree('/content/sample_data', ignore_errors=True)  # remove colab /sample_data directory
-
-    # System info
-    display = None
-    if verbose:
-        gb = 1 << 30  # bytes to GiB (1024 ** 3)
-        ram = psutil.virtual_memory().total
-        total, used, free = shutil.disk_usage('/')
-        with contextlib.suppress(Exception):  # clear display if ipython is installed
-            from IPython import display
-            display.clear_output()
-        s = f'({os.cpu_count()} CPUs, {ram / gb:.1f} GB RAM, {(total - free) / gb:.1f}/{total / gb:.1f} GB disk)'
-    else:
-        s = ''
-
-    select_device(newline=False)
-    print(emojis(f'Setup complete ✅ {s}'))
-    return display
diff --git a/spaces/xxccc/gpt-academic/crazy_functions/test_project/cpp/cppipc/policy.h b/spaces/xxccc/gpt-academic/crazy_functions/test_project/cpp/cppipc/policy.h
deleted file mode 100644
index f88ab5d8cb343f97026966b402eaeed8831e356a..0000000000000000000000000000000000000000
--- a/spaces/xxccc/gpt-academic/crazy_functions/test_project/cpp/cppipc/policy.h
+++ /dev/null
@@ -1,25 +0,0 @@
-#pragma once
-
-#include <type_traits>
-
-#include "libipc/def.h"
-#include "libipc/prod_cons.h"
-
-#include "libipc/circ/elem_array.h"
-
-namespace ipc {
-namespace policy {
-
-template <template <typename, std::size_t...> class Elems, typename Flag>
-struct choose;
-
-template <typename Flag>
-struct choose<circ::elem_array, Flag> {
-    using flag_t = Flag;
-
-    template <std::size_t DataSize, std::size_t AlignSize>
-    using elems_t = circ::elem_array<ipc::prod_cons_impl<flag_t>, DataSize, AlignSize>;
-};
-
-} // namespace policy
-} // namespace ipc
diff --git a/spaces/yaelvinker/CLIPasso/CLIP_/README.md b/spaces/yaelvinker/CLIPasso/CLIP_/README.md
deleted file mode 100644
index b5287fd6b244b09b218f89b88e422cf417e3ef9a..0000000000000000000000000000000000000000
--- a/spaces/yaelvinker/CLIPasso/CLIP_/README.md
+++ /dev/null
@@ -1,193 +0,0 @@
-# CLIP
-
-[[Blog]](https://openai.com/blog/clip/) [[Paper]](https://arxiv.org/abs/2103.00020) [[Model Card]](model-card.md) [[Colab]](https://colab.research.google.com/github/openai/clip/blob/master/notebooks/Interacting_with_CLIP.ipynb)
-
-CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs. It can be instructed in natural language to predict the most relevant text snippet, given an image, without directly optimizing for the task, similarly to the zero-shot capabilities of GPT-2 and 3. We found CLIP matches the performance of the original ResNet50 on ImageNet “zero-shot” without using any of the original 1.28M labeled examples, overcoming several major challenges in computer vision.
-
-
-
-## Approach
-
-![CLIP](CLIP.png)
-
-
-
-## Usage
-
-First, [install PyTorch 1.7.1](https://pytorch.org/get-started/locally/) and torchvision, as well as small additional dependencies, and then install this repo as a Python package. On a CUDA GPU machine, the following will do the trick:
-
-```bash
-$ conda install --yes -c pytorch pytorch=1.7.1 torchvision cudatoolkit=11.0
-$ pip install ftfy regex tqdm
-$ pip install git+https://github.com/openai/CLIP.git
-```
-
-Replace `cudatoolkit=11.0` above with the appropriate CUDA version on your machine or `cpuonly` when installing on a machine without a GPU.
-
-```python
-import torch
-import clip
-from PIL import Image
-
-device = "cuda" if torch.cuda.is_available() else "cpu"
-model, preprocess = clip.load("ViT-B/32", device=device)
-
-image = preprocess(Image.open("CLIP.png")).unsqueeze(0).to(device)
-text = clip.tokenize(["a diagram", "a dog", "a cat"]).to(device)
-
-with torch.no_grad():
-    image_features = model.encode_image(image)
-    text_features = model.encode_text(text)
-    
-    logits_per_image, logits_per_text = model(image, text)
-    probs = logits_per_image.softmax(dim=-1).cpu().numpy()
-
-print("Label probs:", probs)  # prints: [[0.9927937  0.00421068 0.00299572]]
-```
-
-
-## API
-
-The CLIP module `clip` provides the following methods:
-
-#### `clip.available_models()`
-
-Returns the names of the available CLIP models.
-
-#### `clip.load(name, device=..., jit=True)`
-
-Returns the model and the TorchVision transform needed by the model, specified by the model name returned by `clip.available_models()`. It will download the model as necessary. The `name` argument can also be a path to a local checkpoint.
-
-The device to run the model can be optionally specified, and the default is to use the first CUDA device if there is any, otherwise the CPU. When `jit` is `False`, a non-JIT version of the model will be loaded.
-
-#### `clip.tokenize(text: Union[str, List[str]], context_length=77)`
-
-Returns a LongTensor containing tokenized sequences of given text input(s). This can be used as the input to the model
-
----
-
-The model returned by `clip.load()` supports the following methods:
-
-#### `model.encode_image(image: Tensor)`
-
-Given a batch of images, returns the image features encoded by the vision portion of the CLIP model.
-
-#### `model.encode_text(text: Tensor)`
-
-Given a batch of text tokens, returns the text features encoded by the language portion of the CLIP model.
-
-#### `model(image: Tensor, text: Tensor)`
-
-Given a batch of images and a batch of text tokens, returns two Tensors, containing the logit scores corresponding to each image and text input. The values are cosine similarities between the corresponding image and text features, times 100.
-
-
-
-## More Examples
-
-### Zero-Shot Prediction
-
-The code below performs zero-shot prediction using CLIP, as shown in Appendix B in the paper. This example takes an image from the [CIFAR-100 dataset](https://www.cs.toronto.edu/~kriz/cifar.html), and predicts the most likely labels among the 100 textual labels from the dataset.
-
-```python
-import os
-import clip
-import torch
-from torchvision.datasets import CIFAR100
-
-# Load the model
-device = "cuda" if torch.cuda.is_available() else "cpu"
-model, preprocess = clip.load('ViT-B/32', device)
-
-# Download the dataset
-cifar100 = CIFAR100(root=os.path.expanduser("~/.cache"), download=True, train=False)
-
-# Prepare the inputs
-image, class_id = cifar100[3637]
-image_input = preprocess(image).unsqueeze(0).to(device)
-text_inputs = torch.cat([clip.tokenize(f"a photo of a {c}") for c in cifar100.classes]).to(device)
-
-# Calculate features
-with torch.no_grad():
-    image_features = model.encode_image(image_input)
-    text_features = model.encode_text(text_inputs)
-
-# Pick the top 5 most similar labels for the image
-image_features /= image_features.norm(dim=-1, keepdim=True)
-text_features /= text_features.norm(dim=-1, keepdim=True)
-similarity = (100.0 * image_features @ text_features.T).softmax(dim=-1)
-values, indices = similarity[0].topk(5)
-
-# Print the result
-print("\nTop predictions:\n")
-for value, index in zip(values, indices):
-    print(f"{cifar100.classes[index]:>16s}: {100 * value.item():.2f}%")
-```
-
-The output will look like the following (the exact numbers may be slightly different depending on the compute device):
-
-```
-Top predictions:
-
-           snake: 65.31%
-          turtle: 12.29%
-    sweet_pepper: 3.83%
-          lizard: 1.88%
-       crocodile: 1.75%
-```
-
-Note that this example uses the `encode_image()` and `encode_text()` methods that return the encoded features of given inputs.
-
-
-### Linear-probe evaluation
-
-The example below uses [scikit-learn](https://scikit-learn.org/) to perform logistic regression on image features.
-
-```python
-import os
-import clip
-import torch
-
-import numpy as np
-from sklearn.linear_model import LogisticRegression
-from torch.utils.data import DataLoader
-from torchvision.datasets import CIFAR100
-from tqdm import tqdm
-
-# Load the model
-device = "cuda" if torch.cuda.is_available() else "cpu"
-model, preprocess = clip.load('ViT-B/32', device)
-
-# Load the dataset
-root = os.path.expanduser("~/.cache")
-train = CIFAR100(root, download=True, train=True, transform=preprocess)
-test = CIFAR100(root, download=True, train=False, transform=preprocess)
-
-
-def get_features(dataset):
-    all_features = []
-    all_labels = []
-    
-    with torch.no_grad():
-        for images, labels in tqdm(DataLoader(dataset, batch_size=100)):
-            features = model.encode_image(images.to(device))
-
-            all_features.append(features)
-            all_labels.append(labels)
-
-    return torch.cat(all_features).cpu().numpy(), torch.cat(all_labels).cpu().numpy()
-
-# Calculate the image features
-train_features, train_labels = get_features(train)
-test_features, test_labels = get_features(test)
-
-# Perform logistic regression
-classifier = LogisticRegression(random_state=0, C=0.316, max_iter=1000, verbose=1)
-classifier.fit(train_features, train_labels)
-
-# Evaluate using the logistic regression classifier
-predictions = classifier.predict(test_features)
-accuracy = np.mean((test_labels == predictions).astype(np.float)) * 100.
-print(f"Accuracy = {accuracy:.3f}")
-```
-
-Note that the `C` value should be determined via a hyperparameter sweep using a validation split.
diff --git a/spaces/ybelkada/FocusOnDepth/focusondepth/model_config.py b/spaces/ybelkada/FocusOnDepth/focusondepth/model_config.py
deleted file mode 100644
index 5fa2966890662029c51bf1aae2ce3a85472e6341..0000000000000000000000000000000000000000
--- a/spaces/ybelkada/FocusOnDepth/focusondepth/model_config.py
+++ /dev/null
@@ -1,45 +0,0 @@
-from transformers import PretrainedConfig
-from typing import List
-
-
-class FocusOnDepthConfig(PretrainedConfig):
-    model_type = "focusondepth"
-
-    def __init__(
-        self,
-        image_size         = (3, 384, 384),
-        patch_size         = 16,
-        emb_dim            = 768,
-        resample_dim       = 256,
-        read               = 'projection',
-        num_layers_encoder = 24,
-        hooks              = [2, 5, 8, 11],
-        reassemble_s       = [4, 8, 16, 32],
-        transformer_dropout= 0,
-        nclasses           = 2,
-        type_               = "full",
-        model_timm         = "vit_base_patch16_384",
-        **kwargs,
-    ):
-        if type_ not in ["full", "depth", "segmentation"]:
-            raise ValueError(f"`type_` must be 'full' or depth' or 'segmentation, got {type_}.")
-        if read not in ["ignore", "add", "projection"]:
-            raise ValueError(f"`read` must be '', 'ignore' or 'add' or 'projection, got {read}.")
-        if image_size[0] != 3 and image_size[1] != 384 and image_size[2] != 384:
-            raise ValueError(f"`image_size` must be 3, 384, 384, got {image_size}.")
-        if patch_size != 16:
-            raise ValueError(f"`patch_size` must be 16, got {patch_size}.")
-
-        self.image_size = image_size
-        self.patch_size = patch_size
-        self.emb_dim = emb_dim
-        self.resample_dim = resample_dim
-        self.read = read
-        self.num_layers_encoder = num_layers_encoder
-        self.hooks = hooks
-        self.reassemble_s = reassemble_s
-        self.transformer_dropout = transformer_dropout
-        self.nclasses = nclasses
-        self.type_ = type_
-        self.model_timm = model_timm
-        super().__init__(**kwargs)
\ No newline at end of file
diff --git a/spaces/yderre-aubay/midi-player-demo/src/components/Tooltip.tsx b/spaces/yderre-aubay/midi-player-demo/src/components/Tooltip.tsx
deleted file mode 100644
index 028a79beaad419c2adf4119fd4f842f8c5c6b774..0000000000000000000000000000000000000000
--- a/spaces/yderre-aubay/midi-player-demo/src/components/Tooltip.tsx
+++ /dev/null
@@ -1,45 +0,0 @@
-import styled from "@emotion/styled"
-import {
-  Content,
-  Portal,
-  Provider,
-  Root,
-  TooltipContentProps,
-  TooltipProviderProps,
-  Trigger,
-} from "@radix-ui/react-tooltip"
-import Color from "color"
-import { FC, ReactNode } from "react"
-
-export type TooltipProps = TooltipProviderProps & {
-  title: ReactNode
-  side?: TooltipContentProps["side"]
-}
-
-const StyledContent = styled(Content)`
-  background: ${({ theme }) => Color(theme.backgroundColor).darken(0.2).hex()};
-  color: ${({ theme }) => theme.secondaryTextColor};
-  padding: 0.5rem;
-  border-radius: 0.5rem;
-  box-shadow: 0 1rem 3rem ${({ theme }) => theme.shadowColor};
-`
-
-export const Tooltip: FC<TooltipProps> = ({
-  children,
-  title,
-  side = "bottom",
-  ...props
-}) => {
-  return (
-    <Provider {...props}>
-      <Root>
-        <Trigger asChild>{children}</Trigger>
-        <Portal>
-          <StyledContent side={side} sideOffset={5}>
-            {title}
-          </StyledContent>
-        </Portal>
-      </Root>
-    </Provider>
-  )
-}
diff --git a/spaces/yerfor/SyntaSpeech/modules/tts/fs2_orig.py b/spaces/yerfor/SyntaSpeech/modules/tts/fs2_orig.py
deleted file mode 100644
index 4bc8db59c3004731ae4c4feca3e61969b98e45cc..0000000000000000000000000000000000000000
--- a/spaces/yerfor/SyntaSpeech/modules/tts/fs2_orig.py
+++ /dev/null
@@ -1,102 +0,0 @@
-import torch
-from torch import nn
-from modules.commons.layers import Embedding
-from modules.commons.nar_tts_modules import EnergyPredictor, PitchPredictor
-from modules.tts.commons.align_ops import expand_states
-from modules.tts.fs import FastSpeech
-from utils.audio.cwt import cwt2f0, get_lf0_cwt
-from utils.audio.pitch.utils import denorm_f0, f0_to_coarse, norm_f0
-import numpy as np
-
-
-class FastSpeech2Orig(FastSpeech):
-    def __init__(self, dict_size, hparams, out_dims=None):
-        super().__init__(dict_size, hparams, out_dims)
-        predictor_hidden = hparams['predictor_hidden'] if hparams['predictor_hidden'] > 0 else self.hidden_size
-        if hparams['use_energy_embed']:
-            self.energy_embed = Embedding(300, self.hidden_size, 0)
-            self.energy_predictor = EnergyPredictor(
-                self.hidden_size, n_chans=predictor_hidden,
-                n_layers=hparams['predictor_layers'], dropout_rate=hparams['predictor_dropout'], odim=2,
-                kernel_size=hparams['predictor_kernel'])
-        if hparams['pitch_type'] == 'cwt' and hparams['use_pitch_embed']:
-            self.pitch_predictor = PitchPredictor(
-                self.hidden_size, n_chans=predictor_hidden,
-                n_layers=hparams['predictor_layers'], dropout_rate=hparams['predictor_dropout'], odim=11,
-                kernel_size=hparams['predictor_kernel'])
-            self.cwt_stats_layers = nn.Sequential(
-                nn.Linear(self.hidden_size, self.hidden_size), nn.ReLU(),
-                nn.Linear(self.hidden_size, self.hidden_size), nn.ReLU(), nn.Linear(self.hidden_size, 2))
-
-    def forward(self, txt_tokens, mel2ph=None, spk_embed=None, spk_id=None,
-                f0=None, uv=None, energy=None, infer=False, **kwargs):
-        ret = {}
-        encoder_out = self.encoder(txt_tokens)  # [B, T, C]
-        src_nonpadding = (txt_tokens > 0).float()[:, :, None]
-        style_embed = self.forward_style_embed(spk_embed, spk_id)
-
-        # add dur
-        dur_inp = (encoder_out + style_embed) * src_nonpadding
-        mel2ph = self.forward_dur(dur_inp, mel2ph, txt_tokens, ret)
-        tgt_nonpadding = (mel2ph > 0).float()[:, :, None]
-        decoder_inp = decoder_inp_ = expand_states(encoder_out, mel2ph)
-
-        # add pitch and energy embed
-        if self.hparams['use_pitch_embed']:
-            pitch_inp = (decoder_inp_ + style_embed) * tgt_nonpadding
-            decoder_inp = decoder_inp + self.forward_pitch(pitch_inp, f0, uv, mel2ph, ret, encoder_out)
-
-        # add pitch and energy embed
-        if self.hparams['use_energy_embed']:
-            energy_inp = (decoder_inp_ + style_embed) * tgt_nonpadding
-            decoder_inp = decoder_inp + self.forward_energy(energy_inp, energy, ret)
-
-        # decoder input
-        ret['decoder_inp'] = decoder_inp = (decoder_inp + style_embed) * tgt_nonpadding
-        if self.hparams['dec_inp_add_noise']:
-            B, T, _ = decoder_inp.shape
-            z = kwargs.get('adv_z', torch.randn([B, T, self.z_channels])).to(decoder_inp.device)
-            ret['adv_z'] = z
-            decoder_inp = torch.cat([decoder_inp, z], -1)
-            decoder_inp = self.dec_inp_noise_proj(decoder_inp) * tgt_nonpadding
-        ret['mel_out'] = self.forward_decoder(decoder_inp, tgt_nonpadding, ret, infer=infer, **kwargs)
-        return ret
-
-    def forward_pitch(self, decoder_inp, f0, uv, mel2ph, ret, encoder_out=None):
-        if self.hparams['pitch_type'] == 'cwt':
-            decoder_inp = decoder_inp.detach() + self.hparams['predictor_grad'] * (decoder_inp - decoder_inp.detach())
-            pitch_padding = mel2ph == 0
-            ret['cwt'] = cwt_out = self.pitch_predictor(decoder_inp)
-            stats_out = self.cwt_stats_layers(decoder_inp.mean(1))  # [B, 2]
-            mean = ret['f0_mean'] = stats_out[:, 0]
-            std = ret['f0_std'] = stats_out[:, 1]
-            cwt_spec = cwt_out[:, :, :10]
-            if f0 is None:
-                std = std * self.hparams['cwt_std_scale']
-                f0 = self.cwt2f0_norm(cwt_spec, mean, std, mel2ph)
-                if self.hparams['use_uv']:
-                    assert cwt_out.shape[-1] == 11
-                    uv = cwt_out[:, :, -1] > 0
-            ret['f0_denorm'] = f0_denorm = denorm_f0(f0, uv if self.hparams['use_uv'] else None,
-                                                     pitch_padding=pitch_padding)
-            pitch = f0_to_coarse(f0_denorm)  # start from 0
-            pitch_embed = self.pitch_embed(pitch)
-            return pitch_embed
-        else:
-            return super(FastSpeech2Orig, self).forward_pitch(decoder_inp, f0, uv, mel2ph, ret, encoder_out)
-
-    def forward_energy(self, decoder_inp, energy, ret):
-        decoder_inp = decoder_inp.detach() + self.hparams['predictor_grad'] * (decoder_inp - decoder_inp.detach())
-        ret['energy_pred'] = energy_pred = self.energy_predictor(decoder_inp)[:, :, 0]
-        energy_embed_inp = energy_pred if energy is None else energy
-        energy_embed_inp = torch.clamp(energy_embed_inp * 256 // 4, min=0, max=255).long()
-        energy_embed = self.energy_embed(energy_embed_inp)
-        return energy_embed
-
-    def cwt2f0_norm(self, cwt_spec, mean, std, mel2ph):
-        _, cwt_scales = get_lf0_cwt(np.ones(10))
-        f0 = cwt2f0(cwt_spec, mean, std, cwt_scales)
-        f0 = torch.cat(
-            [f0] + [f0[:, -1:]] * (mel2ph.shape[1] - f0.shape[1]), 1)
-        f0_norm = norm_f0(f0, None)
-        return f0_norm
diff --git a/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/models/mobilebert/__init__.py b/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/models/mobilebert/__init__.py
deleted file mode 100644
index 0d202eb4d4234f2f1615cb3ff6eba885532bbeae..0000000000000000000000000000000000000000
--- a/spaces/yizhangliu/Grounded-Segment-Anything/transformers_4_35_0/models/mobilebert/__init__.py
+++ /dev/null
@@ -1,145 +0,0 @@
-# Copyright 2020 The HuggingFace Team. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from typing import TYPE_CHECKING
-
-from ...utils import (
-    OptionalDependencyNotAvailable,
-    _LazyModule,
-    is_tf_available,
-    is_tokenizers_available,
-    is_torch_available,
-)
-
-
-_import_structure = {
-    "configuration_mobilebert": [
-        "MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
-        "MobileBertConfig",
-        "MobileBertOnnxConfig",
-    ],
-    "tokenization_mobilebert": ["MobileBertTokenizer"],
-}
-
-try:
-    if not is_tokenizers_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["tokenization_mobilebert_fast"] = ["MobileBertTokenizerFast"]
-
-try:
-    if not is_torch_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["modeling_mobilebert"] = [
-        "MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
-        "MobileBertForMaskedLM",
-        "MobileBertForMultipleChoice",
-        "MobileBertForNextSentencePrediction",
-        "MobileBertForPreTraining",
-        "MobileBertForQuestionAnswering",
-        "MobileBertForSequenceClassification",
-        "MobileBertForTokenClassification",
-        "MobileBertLayer",
-        "MobileBertModel",
-        "MobileBertPreTrainedModel",
-        "load_tf_weights_in_mobilebert",
-    ]
-
-try:
-    if not is_tf_available():
-        raise OptionalDependencyNotAvailable()
-except OptionalDependencyNotAvailable:
-    pass
-else:
-    _import_structure["modeling_tf_mobilebert"] = [
-        "TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
-        "TFMobileBertForMaskedLM",
-        "TFMobileBertForMultipleChoice",
-        "TFMobileBertForNextSentencePrediction",
-        "TFMobileBertForPreTraining",
-        "TFMobileBertForQuestionAnswering",
-        "TFMobileBertForSequenceClassification",
-        "TFMobileBertForTokenClassification",
-        "TFMobileBertMainLayer",
-        "TFMobileBertModel",
-        "TFMobileBertPreTrainedModel",
-    ]
-
-
-if TYPE_CHECKING:
-    from .configuration_mobilebert import (
-        MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
-        MobileBertConfig,
-        MobileBertOnnxConfig,
-    )
-    from .tokenization_mobilebert import MobileBertTokenizer
-
-    try:
-        if not is_tokenizers_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .tokenization_mobilebert_fast import MobileBertTokenizerFast
-
-    try:
-        if not is_torch_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .modeling_mobilebert import (
-            MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
-            MobileBertForMaskedLM,
-            MobileBertForMultipleChoice,
-            MobileBertForNextSentencePrediction,
-            MobileBertForPreTraining,
-            MobileBertForQuestionAnswering,
-            MobileBertForSequenceClassification,
-            MobileBertForTokenClassification,
-            MobileBertLayer,
-            MobileBertModel,
-            MobileBertPreTrainedModel,
-            load_tf_weights_in_mobilebert,
-        )
-
-    try:
-        if not is_tf_available():
-            raise OptionalDependencyNotAvailable()
-    except OptionalDependencyNotAvailable:
-        pass
-    else:
-        from .modeling_tf_mobilebert import (
-            TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
-            TFMobileBertForMaskedLM,
-            TFMobileBertForMultipleChoice,
-            TFMobileBertForNextSentencePrediction,
-            TFMobileBertForPreTraining,
-            TFMobileBertForQuestionAnswering,
-            TFMobileBertForSequenceClassification,
-            TFMobileBertForTokenClassification,
-            TFMobileBertMainLayer,
-            TFMobileBertModel,
-            TFMobileBertPreTrainedModel,
-        )
-
-else:
-    import sys
-
-    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
diff --git a/spaces/ysheng/SSN-Soft-Shadow-Network-for-Image-Composition/models/attention.py b/spaces/ysheng/SSN-Soft-Shadow-Network-for-Image-Composition/models/attention.py
deleted file mode 100644
index 259965dc3c389b50e08b312f424dc38db27e4c54..0000000000000000000000000000000000000000
--- a/spaces/ysheng/SSN-Soft-Shadow-Network-for-Image-Composition/models/attention.py
+++ /dev/null
@@ -1,85 +0,0 @@
-from inspect import isfunction
-import math
-import torch
-from torch import nn, einsum
-import torch.nn.functional as F
-
-from .blocks import get_norm, zero_module
-
-
-def QKV_Attention(qkv, num_heads):
-    """
-    Apply QKV attention.
-    :param qkv: an [N x (3 * C) x T] tensor of Qs, Ks, and Vs.
-    :return: an [N x H' x T] tensor after attention.
-    """
-    B, C, HW = qkv.shape
-    if C % 3 != 0:
-        raise ValueError('QKV shape is wrong: {}, {}, {}'.format(B, C, HW))
-
-    split_size = C // (3 * num_heads)
-    q, k, v = qkv.chunk(3, dim=1)
-    scale      = 1.0/math.sqrt(math.sqrt(split_size))
-    weight = torch.einsum('bct, bcs->bts',
-                          (q * scale).view(B * num_heads, split_size, HW),
-                          (k * scale).view(B * num_heads, split_size, HW))
-
-    weight = torch.softmax(weight.float(), dim=-1).type(weight.dtype)
-    ret    = torch.einsum("bts,bcs->bct", weight, v.reshape(B * num_heads, split_size, HW))
-
-    return ret.reshape(B, -1, HW)
-
-
-class AttentionBlock(nn.Module):
-    """
-        https://github.com/CompVis/latent-diffusion/blob/main/ldm/modules/diffusionmodules/openaimodel.py
-        https://github.com/whai362/PVT/blob/a24ba02c249a510581a84f821c26322534b03a10/detection/pvt_v2.py#L57
-    """
-
-    def __init__(self, in_channels, num_heads, qkv_bias=False, sr_ratio=1, linear=True):
-        super().__init__()
-
-        self.num_heads = num_heads
-        self.norm = get_norm(in_channels, 'Group')
-        self.qkv  = nn.Conv1d(in_channels=in_channels, out_channels=in_channels * 3, kernel_size = 1)
-
-        self.proj = zero_module(nn.Conv1d(in_channels=in_channels, out_channels=in_channels, kernel_size = 1))
-
-
-    def forward(self, x):
-        b, c, *spatial = x.shape
-        num_heads = self.num_heads
-
-        x   = x.reshape(b, c, -1) # B x C x HW
-        x   = self.norm(x)
-        qkv = self.qkv(x) # b x c x HW ->  B x 3C x HW
-        h   = QKV_Attention(qkv, num_heads)
-        h   = self.proj(h)
-
-        return (x + h).reshape(b,c,*spatial) # additive attention, similar to ResNet?
-
-
-
-def get_model_size(model):
-    param_size = 0
-    for param in model.parameters():
-        param_size += param.nelement() * param.element_size()
-
-    buffer_size = 0
-    for buffer in model.buffers():
-        buffer_size += buffer.nelement() * buffer.element_size()
-
-    size_all_mb = (param_size + buffer_size) / 1024 ** 2
-    print('model size: {:.3f}MB'.format(size_all_mb))
-    # return param_size + buffer_size
-    return size_all_mb
-
-
-if __name__ == '__main__':
-    model = AttentionBlock(in_channels=256, num_heads=8)
-
-    x = torch.randn(5, 256, 32, 32, dtype=torch.float32)
-    y = model(x)
-    print('{}, {}'.format(x.shape, y.shape))
-
-    get_model_size(model)
diff --git a/spaces/yuezih/BLIP-SMILE/SMILE/__init__.py b/spaces/yuezih/BLIP-SMILE/SMILE/__init__.py
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000
diff --git a/spaces/yuhangzang/ContextDet-Demo/models/deformable_detr/segmentation.py b/spaces/yuhangzang/ContextDet-Demo/models/deformable_detr/segmentation.py
deleted file mode 100644
index c801c0eaada3df0f286f6288266a00053b82472e..0000000000000000000000000000000000000000
--- a/spaces/yuhangzang/ContextDet-Demo/models/deformable_detr/segmentation.py
+++ /dev/null
@@ -1,369 +0,0 @@
-# ------------------------------------------------------------------------
-# Deformable DETR
-# Copyright (c) 2020 SenseTime. All Rights Reserved.
-# Licensed under the Apache License, Version 2.0 [see LICENSE for details]
-# ------------------------------------------------------------------------
-# Modified from DETR (https://github.com/facebookresearch/detr)
-# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
-# ------------------------------------------------------------------------
-
-"""
-This file provides the definition of the convolutional heads used to predict masks, as well as the losses
-"""
-import io
-from collections import defaultdict
-
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-from PIL import Image
-
-import util.box_ops as box_ops
-from util.misc import NestedTensor, interpolate, nested_tensor_from_tensor_list
-
-try:
-    from panopticapi.utils import id2rgb, rgb2id
-except ImportError:
-    pass
-
-
-class DETRsegm(nn.Module):
-    def __init__(self, detr, freeze_detr=False):
-        super().__init__()
-        self.detr = detr
-
-        if freeze_detr:
-            for p in self.parameters():
-                p.requires_grad_(False)
-
-        hidden_dim, nheads = detr.transformer.d_model, detr.transformer.nhead
-        self.bbox_attention = MHAttentionMap(hidden_dim, hidden_dim, nheads, dropout=0)
-        self.mask_head = MaskHeadSmallConv(hidden_dim + nheads, [1024, 512, 256], hidden_dim)
-
-    def forward(self, samples: NestedTensor):
-        if not isinstance(samples, NestedTensor):
-            samples = nested_tensor_from_tensor_list(samples)
-        features, pos = self.detr.backbone(samples)
-
-        bs = features[-1].tensors.shape[0]
-
-        src, mask = features[-1].decompose()
-        src_proj = self.detr.input_proj(src)
-        hs, memory = self.detr.transformer(src_proj, mask, self.detr.query_embed.weight, pos[-1])
-
-        outputs_class = self.detr.class_embed(hs)
-        outputs_coord = self.detr.bbox_embed(hs).sigmoid()
-        out = {"pred_logits": outputs_class[-1], "pred_boxes": outputs_coord[-1]}
-        if self.detr.aux_loss:
-            out["aux_outputs"] = [
-                {"pred_logits": a, "pred_boxes": b} for a, b in zip(outputs_class[:-1], outputs_coord[:-1])
-            ]
-
-        # FIXME h_boxes takes the last one computed, keep this in mind
-        bbox_mask = self.bbox_attention(hs[-1], memory, mask=mask)
-
-        seg_masks = self.mask_head(src_proj, bbox_mask, [features[2].tensors, features[1].tensors, features[0].tensors])
-        outputs_seg_masks = seg_masks.view(bs, self.detr.num_queries, seg_masks.shape[-2], seg_masks.shape[-1])
-
-        out["pred_masks"] = outputs_seg_masks
-        return out
-
-
-class MaskHeadSmallConv(nn.Module):
-    """
-    Simple convolutional head, using group norm.
-    Upsampling is done using a FPN approach
-    """
-
-    def __init__(self, dim, fpn_dims, context_dim):
-        super().__init__()
-
-        inter_dims = [dim, context_dim // 2, context_dim // 4, context_dim // 8, context_dim // 16, context_dim // 64]
-        self.lay1 = torch.nn.Conv2d(dim, dim, 3, padding=1)
-        self.gn1 = torch.nn.GroupNorm(8, dim)
-        self.lay2 = torch.nn.Conv2d(dim, inter_dims[1], 3, padding=1)
-        self.gn2 = torch.nn.GroupNorm(8, inter_dims[1])
-        self.lay3 = torch.nn.Conv2d(inter_dims[1], inter_dims[2], 3, padding=1)
-        self.gn3 = torch.nn.GroupNorm(8, inter_dims[2])
-        self.lay4 = torch.nn.Conv2d(inter_dims[2], inter_dims[3], 3, padding=1)
-        self.gn4 = torch.nn.GroupNorm(8, inter_dims[3])
-        self.lay5 = torch.nn.Conv2d(inter_dims[3], inter_dims[4], 3, padding=1)
-        self.gn5 = torch.nn.GroupNorm(8, inter_dims[4])
-        self.out_lay = torch.nn.Conv2d(inter_dims[4], 1, 3, padding=1)
-
-        self.dim = dim
-
-        self.adapter1 = torch.nn.Conv2d(fpn_dims[0], inter_dims[1], 1)
-        self.adapter2 = torch.nn.Conv2d(fpn_dims[1], inter_dims[2], 1)
-        self.adapter3 = torch.nn.Conv2d(fpn_dims[2], inter_dims[3], 1)
-
-        for m in self.modules():
-            if isinstance(m, nn.Conv2d):
-                nn.init.kaiming_uniform_(m.weight, a=1)
-                nn.init.constant_(m.bias, 0)
-
-    def forward(self, x, bbox_mask, fpns):
-        def expand(tensor, length):
-            return tensor.unsqueeze(1).repeat(1, int(length), 1, 1, 1).flatten(0, 1)
-
-        x = torch.cat([expand(x, bbox_mask.shape[1]), bbox_mask.flatten(0, 1)], 1)
-
-        x = self.lay1(x)
-        x = self.gn1(x)
-        x = F.relu(x)
-        x = self.lay2(x)
-        x = self.gn2(x)
-        x = F.relu(x)
-
-        cur_fpn = self.adapter1(fpns[0])
-        if cur_fpn.size(0) != x.size(0):
-            cur_fpn = expand(cur_fpn, x.size(0) / cur_fpn.size(0))
-        x = cur_fpn + F.interpolate(x, size=cur_fpn.shape[-2:], mode="nearest")
-        x = self.lay3(x)
-        x = self.gn3(x)
-        x = F.relu(x)
-
-        cur_fpn = self.adapter2(fpns[1])
-        if cur_fpn.size(0) != x.size(0):
-            cur_fpn = expand(cur_fpn, x.size(0) / cur_fpn.size(0))
-        x = cur_fpn + F.interpolate(x, size=cur_fpn.shape[-2:], mode="nearest")
-        x = self.lay4(x)
-        x = self.gn4(x)
-        x = F.relu(x)
-
-        cur_fpn = self.adapter3(fpns[2])
-        if cur_fpn.size(0) != x.size(0):
-            cur_fpn = expand(cur_fpn, x.size(0) / cur_fpn.size(0))
-        x = cur_fpn + F.interpolate(x, size=cur_fpn.shape[-2:], mode="nearest")
-        x = self.lay5(x)
-        x = self.gn5(x)
-        x = F.relu(x)
-
-        x = self.out_lay(x)
-        return x
-
-
-class MHAttentionMap(nn.Module):
-    """This is a 2D attention module, which only returns the attention softmax (no multiplication by value)"""
-
-    def __init__(self, query_dim, hidden_dim, num_heads, dropout=0, bias=True):
-        super().__init__()
-        self.num_heads = num_heads
-        self.hidden_dim = hidden_dim
-        self.dropout = nn.Dropout(dropout)
-
-        self.q_linear = nn.Linear(query_dim, hidden_dim, bias=bias)
-        self.k_linear = nn.Linear(query_dim, hidden_dim, bias=bias)
-
-        nn.init.zeros_(self.k_linear.bias)
-        nn.init.zeros_(self.q_linear.bias)
-        nn.init.xavier_uniform_(self.k_linear.weight)
-        nn.init.xavier_uniform_(self.q_linear.weight)
-        self.normalize_fact = float(hidden_dim / self.num_heads) ** -0.5
-
-    def forward(self, q, k, mask=None):
-        q = self.q_linear(q)
-        k = F.conv2d(k, self.k_linear.weight.unsqueeze(-1).unsqueeze(-1), self.k_linear.bias)
-        qh = q.view(q.shape[0], q.shape[1], self.num_heads, self.hidden_dim // self.num_heads)
-        kh = k.view(k.shape[0], self.num_heads, self.hidden_dim // self.num_heads, k.shape[-2], k.shape[-1])
-        weights = torch.einsum("bqnc,bnchw->bqnhw", qh * self.normalize_fact, kh)
-
-        if mask is not None:
-            weights.masked_fill_(mask.unsqueeze(1).unsqueeze(1), float("-inf"))
-        weights = F.softmax(weights.flatten(2), dim=-1).view_as(weights)
-        weights = self.dropout(weights)
-        return weights
-
-
-def dice_loss(inputs, targets, num_boxes):
-    """
-    Compute the DICE loss, similar to generalized IOU for masks
-    Args:
-        inputs: A float tensor of arbitrary shape.
-                The predictions for each example.
-        targets: A float tensor with the same shape as inputs. Stores the binary
-                 classification label for each element in inputs
-                (0 for the negative class and 1 for the positive class).
-    """
-    inputs = inputs.sigmoid()
-    inputs = inputs.flatten(1)
-    numerator = 2 * (inputs * targets).sum(1)
-    denominator = inputs.sum(-1) + targets.sum(-1)
-    loss = 1 - (numerator + 1) / (denominator + 1)
-    return loss.sum() / num_boxes
-
-
-def sigmoid_focal_loss(inputs, targets, num_boxes, alpha: float = 0.25, gamma: float = 2):
-    """
-    Loss used in RetinaNet for dense detection: https://arxiv.org/abs/1708.02002.
-    Args:
-        inputs: A float tensor of arbitrary shape.
-                The predictions for each example.
-        targets: A float tensor with the same shape as inputs. Stores the binary
-                 classification label for each element in inputs
-                (0 for the negative class and 1 for the positive class).
-        alpha: (optional) Weighting factor in range (0,1) to balance
-                positive vs negative examples. Default = -1 (no weighting).
-        gamma: Exponent of the modulating factor (1 - p_t) to
-               balance easy vs hard examples.
-    Returns:
-        Loss tensor
-    """
-    prob = inputs.sigmoid()
-    ce_loss = F.binary_cross_entropy_with_logits(inputs, targets, reduction="none")
-    p_t = prob * targets + (1 - prob) * (1 - targets)
-    loss = ce_loss * ((1 - p_t) ** gamma)
-
-    if alpha >= 0:
-        alpha_t = alpha * targets + (1 - alpha) * (1 - targets)
-        loss = alpha_t * loss
-
-    return loss.mean(1).sum() / num_boxes
-
-
-class PostProcessSegm(nn.Module):
-    def __init__(self, threshold=0.5):
-        super().__init__()
-        self.threshold = threshold
-
-    @torch.no_grad()
-    def forward(self, results, outputs, orig_target_sizes, max_target_sizes):
-        assert len(orig_target_sizes) == len(max_target_sizes)
-        max_h, max_w = max_target_sizes.max(0)[0].tolist()
-        outputs_masks = outputs["pred_masks"].squeeze(2)
-        outputs_masks = F.interpolate(outputs_masks, size=(max_h, max_w), mode="bilinear", align_corners=False)
-        outputs_masks = (outputs_masks.sigmoid() > self.threshold).cpu()
-
-        for i, (cur_mask, t, tt) in enumerate(zip(outputs_masks, max_target_sizes, orig_target_sizes)):
-            img_h, img_w = t[0], t[1]
-            results[i]["masks"] = cur_mask[:, :img_h, :img_w].unsqueeze(1)
-            results[i]["masks"] = F.interpolate(
-                results[i]["masks"].float(), size=tuple(tt.tolist()), mode="nearest"
-            ).byte()
-
-        return results
-
-
-class PostProcessPanoptic(nn.Module):
-    """This class converts the output of the model to the final panoptic result, in the format expected by the
-    coco panoptic API """
-
-    def __init__(self, is_thing_map, threshold=0.85):
-        """
-        Parameters:
-           is_thing_map: This is a whose keys are the class ids, and the values a boolean indicating whether
-                          the class is  a thing (True) or a stuff (False) class
-           threshold: confidence threshold: segments with confidence lower than this will be deleted
-        """
-        super().__init__()
-        self.threshold = threshold
-        self.is_thing_map = is_thing_map
-
-    def forward(self, outputs, processed_sizes, target_sizes=None):
-        """ This function computes the panoptic prediction from the model's predictions.
-        Parameters:
-            outputs: This is a dict coming directly from the model. See the model doc for the content.
-            processed_sizes: This is a list of tuples (or torch tensors) of sizes of the images that were passed to the
-                             model, ie the size after data augmentation but before batching.
-            target_sizes: This is a list of tuples (or torch tensors) corresponding to the requested final size
-                          of each prediction. If left to None, it will default to the processed_sizes
-            """
-        if target_sizes is None:
-            target_sizes = processed_sizes
-        assert len(processed_sizes) == len(target_sizes)
-        out_logits, raw_masks, raw_boxes = outputs["pred_logits"], outputs["pred_masks"], outputs["pred_boxes"]
-        assert len(out_logits) == len(raw_masks) == len(target_sizes)
-        preds = []
-
-        def to_tuple(tup):
-            if isinstance(tup, tuple):
-                return tup
-            return tuple(tup.cpu().tolist())
-
-        for cur_logits, cur_masks, cur_boxes, size, target_size in zip(
-            out_logits, raw_masks, raw_boxes, processed_sizes, target_sizes
-        ):
-            # we filter empty queries and detection below threshold
-            scores, labels = cur_logits.softmax(-1).max(-1)
-            keep = labels.ne(outputs["pred_logits"].shape[-1] - 1) & (scores > self.threshold)
-            cur_scores, cur_classes = cur_logits.softmax(-1).max(-1)
-            cur_scores = cur_scores[keep]
-            cur_classes = cur_classes[keep]
-            cur_masks = cur_masks[keep]
-            cur_masks = interpolate(cur_masks[None], to_tuple(size), mode="bilinear").squeeze(0)
-            cur_boxes = box_ops.box_cxcywh_to_xyxy(cur_boxes[keep])
-
-            h, w = cur_masks.shape[-2:]
-            assert len(cur_boxes) == len(cur_classes)
-
-            # It may be that we have several predicted masks for the same stuff class.
-            # In the following, we track the list of masks ids for each stuff class (they are merged later on)
-            cur_masks = cur_masks.flatten(1)
-            stuff_equiv_classes = defaultdict(lambda: [])
-            for k, label in enumerate(cur_classes):
-                if not self.is_thing_map[label.item()]:
-                    stuff_equiv_classes[label.item()].append(k)
-
-            def get_ids_area(masks, scores, dedup=False):
-                # This helper function creates the final panoptic segmentation image
-                # It also returns the area of the masks that appears on the image
-
-                m_id = masks.transpose(0, 1).softmax(-1)
-
-                if m_id.shape[-1] == 0:
-                    # We didn't detect any mask :(
-                    m_id = torch.zeros((h, w), dtype=torch.long, device=m_id.device)
-                else:
-                    m_id = m_id.argmax(-1).view(h, w)
-
-                if dedup:
-                    # Merge the masks corresponding to the same stuff class
-                    for equiv in stuff_equiv_classes.values():
-                        if len(equiv) > 1:
-                            for eq_id in equiv:
-                                m_id.masked_fill_(m_id.eq(eq_id), equiv[0])
-
-                final_h, final_w = to_tuple(target_size)
-
-                seg_img = Image.fromarray(id2rgb(m_id.view(h, w).cpu().numpy()))
-                seg_img = seg_img.resize(size=(final_w, final_h), resample=Image.NEAREST)
-
-                np_seg_img = (
-                    torch.ByteTensor(torch.ByteStorage.from_buffer(seg_img.tobytes())).view(final_h, final_w, 3).numpy()
-                )
-                m_id = torch.from_numpy(rgb2id(np_seg_img))
-
-                area = []
-                for i in range(len(scores)):
-                    area.append(m_id.eq(i).sum().item())
-                return area, seg_img
-
-            area, seg_img = get_ids_area(cur_masks, cur_scores, dedup=True)
-            if cur_classes.numel() > 0:
-                # We know filter empty masks as long as we find some
-                while True:
-                    filtered_small = torch.as_tensor(
-                        [area[i] <= 4 for i, c in enumerate(cur_classes)], dtype=torch.bool, device=keep.device
-                    )
-                    if filtered_small.any().item():
-                        cur_scores = cur_scores[~filtered_small]
-                        cur_classes = cur_classes[~filtered_small]
-                        cur_masks = cur_masks[~filtered_small]
-                        area, seg_img = get_ids_area(cur_masks, cur_scores)
-                    else:
-                        break
-
-            else:
-                cur_classes = torch.ones(1, dtype=torch.long, device=cur_classes.device)
-
-            segments_info = []
-            for i, a in enumerate(area):
-                cat = cur_classes[i].item()
-                segments_info.append({"id": i, "isthing": self.is_thing_map[cat], "category_id": cat, "area": a})
-            del cur_classes
-
-            with io.BytesIO() as out:
-                seg_img.save(out, format="PNG")
-                predictions = {"png_string": out.getvalue(), "segments_info": segments_info}
-            preds.append(predictions)
-        return preds
diff --git a/spaces/yunfei0710/gpt-academic/config.py b/spaces/yunfei0710/gpt-academic/config.py
deleted file mode 100644
index c738e2f4d462da3a7620376d38fd7cbab81ff887..0000000000000000000000000000000000000000
--- a/spaces/yunfei0710/gpt-academic/config.py
+++ /dev/null
@@ -1,90 +0,0 @@
-# [step 1]>> 例如： API_KEY = "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" （此key无效）
-API_KEY = "sk-此处填API密钥"    # 可同时填写多个API-KEY，用英文逗号分割，例如API_KEY = "sk-openaikey1,sk-openaikey2,fkxxxx-api2dkey1,fkxxxx-api2dkey2"
-
-
-# [step 2]>> 改为True应用代理，如果直接在海外服务器部署，此处不修改
-USE_PROXY = False
-if USE_PROXY:
-    # 填写格式是 [协议]://  [地址] :[端口]，填写之前不要忘记把USE_PROXY改成True，如果直接在海外服务器部署，此处不修改
-    # 例如    "socks5h://localhost:11284"
-    # [协议] 常见协议无非socks5h/http; 例如 v2**y 和 ss* 的默认本地协议是socks5h; 而cl**h 的默认本地协议是http
-    # [地址] 懂的都懂，不懂就填localhost或者127.0.0.1肯定错不了（localhost意思是代理软件安装在本机上）
-    # [端口] 在代理软件的设置里找。虽然不同的代理软件界面不一样，但端口号都应该在最显眼的位置上
-
-    # 代理网络的地址，打开你的*学*网软件查看代理的协议(socks5/http)、地址(localhost)和端口(11284)
-    proxies = {
-        #          [协议]://  [地址]  :[端口]
-        "http":  "socks5h://localhost:11284",  # 再例如  "http":  "http://127.0.0.1:7890",
-        "https": "socks5h://localhost:11284",  # 再例如  "https": "http://127.0.0.1:7890",
-    }
-else:
-    proxies = None
-
-# [step 3]>> 多线程函数插件中，默认允许多少路线程同时访问OpenAI。Free trial users的限制是每分钟3次，Pay-as-you-go users的限制是每分钟3500次
-# 一言以蔽之：免费用户填3，OpenAI绑了信用卡的用户可以填 16 或者更高。提高限制请查询：https://platform.openai.com/docs/guides/rate-limits/overview
-DEFAULT_WORKER_NUM = 3
-
-
-# [step 4]>> 以下配置可以优化体验，但大部分场合下并不需要修改
-# 对话窗的高度
-CHATBOT_HEIGHT = 1115
-
-# 代码高亮
-CODE_HIGHLIGHT = True
-
-# 窗口布局
-LAYOUT = "LEFT-RIGHT"  # "LEFT-RIGHT"（左右布局） # "TOP-DOWN"（上下布局）
-DARK_MODE = True  # "LEFT-RIGHT"（左右布局） # "TOP-DOWN"（上下布局）
-
-# 发送请求到OpenAI后，等待多久判定为超时
-TIMEOUT_SECONDS = 30
-
-# 网页的端口, -1代表随机端口
-WEB_PORT = -1
-
-# 如果OpenAI不响应（网络卡顿、代理失败、KEY失效），重试的次数限制
-MAX_RETRY = 2
-
-# OpenAI模型选择是（gpt4现在只对申请成功的人开放）
-LLM_MODEL = "gpt-3.5-turbo" # 可选 "chatglm"
-AVAIL_LLM_MODELS = ["newbing-free", "gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "api2d-gpt-3.5-turbo"]
-
-# 本地LLM模型如ChatGLM的执行方式 CPU/GPU
-LOCAL_MODEL_DEVICE = "cpu" # 可选 "cuda"
-
-# 设置gradio的并行线程数（不需要修改）
-CONCURRENT_COUNT = 100
-
-# 加一个live2d装饰
-ADD_WAIFU = False
-
-# 设置用户名和密码（不需要修改）（相关功能不稳定，与gradio版本和网络都相关，如果本地使用不建议加这个）
-# [("username", "password"), ("username2", "password2"), ...]
-AUTHENTICATION = []
-
-# 重新URL重新定向，实现更换API_URL的作用（常规情况下，不要修改!!）
-# （高危设置！通过修改此设置，您将把您的API-KEY和对话隐私完全暴露给您设定的中间人！）
-# 格式 {"https://api.openai.com/v1/chat/completions": "在这里填写重定向的api.openai.com的URL"} 
-# 例如 API_URL_REDIRECT = {"https://api.openai.com/v1/chat/completions": "https://ai.open.com/api/conversation"}
-API_URL_REDIRECT = {}
-
-# 如果需要在二级路径下运行（常规情况下，不要修改!!）（需要配合修改main.py才能生效!）
-CUSTOM_PATH = "/"
-
-# 如果需要使用newbing，把newbing的长长的cookie放到这里
-NEWBING_STYLE = "creative"  # ["creative", "balanced", "precise"]
-# 从现在起，如果您调用"newbing-free"模型，则无需填写NEWBING_COOKIES
-NEWBING_COOKIES = """
-your bing cookies here
-"""
-
-# 如果需要使用Slack Claude，使用教程详情见 request_llm/README.md
-SLACK_CLAUDE_BOT_ID = ''   
-SLACK_CLAUDE_USER_TOKEN = ''
-
-
-# 如果需要使用AZURE 详情请见额外文档 docs\use_azure.md
-AZURE_ENDPOINT = "https://你的api名称.openai.azure.com/"
-AZURE_API_KEY = "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"
-AZURE_API_VERSION = "填入api版本"
-AZURE_ENGINE = "填入ENGINE"
diff --git a/spaces/zej97/AI-Research-Assistant/test/test4.py b/spaces/zej97/AI-Research-Assistant/test/test4.py
deleted file mode 100644
index d9f6c140d753757ba78d021bac903ee8b6726be9..0000000000000000000000000000000000000000
--- a/spaces/zej97/AI-Research-Assistant/test/test4.py
+++ /dev/null
@@ -1,6 +0,0 @@
-def test():
-    yield 1
-    return 2
-
-a, b = test()
-print(a, b)
\ No newline at end of file
diff --git a/spaces/zhan66/vits-simple-api/vits/text/cleaners.py b/spaces/zhan66/vits-simple-api/vits/text/cleaners.py
deleted file mode 100644
index e1c71cb43e308f365de7a4444ca3ae51f617446f..0000000000000000000000000000000000000000
--- a/spaces/zhan66/vits-simple-api/vits/text/cleaners.py
+++ /dev/null
@@ -1,278 +0,0 @@
-import re
-import config
-from unidecode import unidecode
-from phonemizer import phonemize
-from phonemizer.backend.espeak.wrapper import EspeakWrapper
-
-ESPEAK_LIBRARY = getattr(config, "ESPEAK_LIBRARY", "")
-if ESPEAK_LIBRARY != "":
-    EspeakWrapper.set_library(ESPEAK_LIBRARY)
-
-# List of (regular expression, replacement) pairs for abbreviations:
-_abbreviations = [(re.compile('\\b%s\\.' % x[0], re.IGNORECASE), x[1]) for x in [
-    ('mrs', 'misess'),
-    ('mr', 'mister'),
-    ('dr', 'doctor'),
-    ('st', 'saint'),
-    ('co', 'company'),
-    ('jr', 'junior'),
-    ('maj', 'major'),
-    ('gen', 'general'),
-    ('drs', 'doctors'),
-    ('rev', 'reverend'),
-    ('lt', 'lieutenant'),
-    ('hon', 'honorable'),
-    ('sgt', 'sergeant'),
-    ('capt', 'captain'),
-    ('esq', 'esquire'),
-    ('ltd', 'limited'),
-    ('col', 'colonel'),
-    ('ft', 'fort'),
-]]
-
-
-def expand_abbreviations(text):
-    for regex, replacement in _abbreviations:
-        text = re.sub(regex, replacement, text)
-    return text
-
-
-def transliteration_cleaners(text):
-    '''Pipeline for non-English text that transliterates to ASCII.'''
-    text = unidecode(text)
-    text = text.lower()
-    text = re.sub(r'\s+', ' ', text)
-    text = expand_abbreviations(text)
-    return text
-
-
-# for English text
-def english_cleaners(text):
-    '''Pipeline for English text, including abbreviation expansion.'''
-    text = re.sub(r'\[EN\](.*?)\[EN\]', lambda x: transliteration_cleaners(x.group(1)) + ' ', text)
-    phonemes = phonemize(text, language='en-us', backend='espeak', strip=True)
-    return phonemes
-
-
-# for non-English text that can be transliterated to ASCII
-def english_cleaners2(text):
-    '''Pipeline for English text, including abbreviation expansion. + punctuation + stress'''
-    text = re.sub(r'\[EN\](.*?)\[EN\]', lambda x: transliteration_cleaners(x.group(1)) + ' ', text)
-    phonemes = phonemize(text, language='en-us', backend='espeak', strip=True, preserve_punctuation=True,
-                         with_stress=True)
-    return phonemes
-
-
-def japanese_cleaners(text):
-    from vits.text.japanese import japanese_to_romaji_with_accent
-
-    def clean(text):
-        text = japanese_to_romaji_with_accent(text)
-        text = re.sub(r'([A-Za-z])$', r'\1.', text)
-        return text
-
-    text = re.sub(r'\[JA\](.*?)\[JA\]', lambda x: clean(x.group(1)) + ' ', text)
-    return text
-
-
-def japanese_cleaners2(text):
-    return japanese_cleaners(text).replace('ts', 'ʦ').replace('...', '…')
-
-
-def korean_cleaners(text):
-    '''Pipeline for Korean text'''
-    from vits.text.korean import latin_to_hangul, number_to_hangul, divide_hangul
-
-    def clean(text):
-        text = latin_to_hangul(text)
-        text = number_to_hangul(text)
-        text = divide_hangul(text)
-        text = re.sub(r'([\u3131-\u3163])$', r'\1.', text)
-        return text
-
-    text = re.sub(r'\[KO\](.*?)\[KO\]', lambda x: clean(x.group(1)) + ' ', text)
-    return text
-
-
-def chinese_cleaners(text):
-    '''Pipeline for Chinese text'''
-    from vits.text.mandarin import number_to_chinese, chinese_to_bopomofo, latin_to_bopomofo, symbols_to_chinese
-
-    def clean(text):
-        text = symbols_to_chinese(text)
-        text = number_to_chinese(text)
-        text = chinese_to_bopomofo(text)
-        text = latin_to_bopomofo(text)
-        text = re.sub(r'([ˉˊˇˋ˙])$', r'\1。', text)
-        return text
-
-    text = re.sub(r'\[ZH\](.*?)\[ZH\]', lambda x: clean(x.group(1)) + ' ', text)
-    return text
-
-
-def zh_ja_mixture_cleaners(text):
-    from vits.text.mandarin import chinese_to_romaji
-    from vits.text.japanese import japanese_to_romaji_with_accent
-    text = re.sub(r'\[ZH\](.*?)\[ZH\]',
-                  lambda x: chinese_to_romaji(x.group(1)) + ' ', text)
-    text = re.sub(r'\[JA\](.*?)\[JA\]', lambda x: japanese_to_romaji_with_accent(
-        x.group(1)).replace('ts', 'ʦ').replace('u', 'ɯ').replace('...', '…') + ' ', text)
-    text = re.sub(r'\s+$', '', text)
-    text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
-    return text
-
-
-def sanskrit_cleaners(text):
-    text = text.replace('॥', '।').replace('ॐ', 'ओम्')
-    text = re.sub(r'([^।])$', r'\1।', text)
-    return text
-
-
-def cjks_cleaners(text):
-    from vits.text.mandarin import chinese_to_lazy_ipa
-    from vits.text.japanese import japanese_to_ipa
-    from vits.text.korean import korean_to_lazy_ipa
-    from vits.text.sanskrit import devanagari_to_ipa
-    from vits.text.english import english_to_lazy_ipa
-    text = re.sub(r'\[ZH\](.*?)\[ZH\]',
-                  lambda x: chinese_to_lazy_ipa(x.group(1)) + ' ', text)
-    text = re.sub(r'\[JA\](.*?)\[JA\]',
-                  lambda x: japanese_to_ipa(x.group(1)) + ' ', text)
-    text = re.sub(r'\[KO\](.*?)\[KO\]',
-                  lambda x: korean_to_lazy_ipa(x.group(1)) + ' ', text)
-    text = re.sub(r'\[SA\](.*?)\[SA\]',
-                  lambda x: devanagari_to_ipa(x.group(1)) + ' ', text)
-    text = re.sub(r'\[EN\](.*?)\[EN\]',
-                  lambda x: english_to_lazy_ipa(x.group(1)) + ' ', text)
-    text = re.sub(r'\s+$', '', text)
-    text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
-    return text
-
-
-def cjke_cleaners(text):
-    from vits.text.mandarin import chinese_to_lazy_ipa
-    from vits.text.japanese import japanese_to_ipa
-    from vits.text.korean import korean_to_ipa
-    from vits.text.english import english_to_ipa2
-    text = re.sub(r'\[ZH\](.*?)\[ZH\]', lambda x: chinese_to_lazy_ipa(x.group(1)).replace(
-        'ʧ', 'tʃ').replace('ʦ', 'ts').replace('ɥan', 'ɥæn') + ' ', text)
-    text = re.sub(r'\[JA\](.*?)\[JA\]', lambda x: japanese_to_ipa(x.group(1)).replace('ʧ', 'tʃ').replace(
-        'ʦ', 'ts').replace('ɥan', 'ɥæn').replace('ʥ', 'dz') + ' ', text)
-    text = re.sub(r'\[KO\](.*?)\[KO\]',
-                  lambda x: korean_to_ipa(x.group(1)) + ' ', text)
-    text = re.sub(r'\[EN\](.*?)\[EN\]', lambda x: english_to_ipa2(x.group(1)).replace('ɑ', 'a').replace(
-        'ɔ', 'o').replace('ɛ', 'e').replace('ɪ', 'i').replace('ʊ', 'u') + ' ', text)
-    text = re.sub(r'\s+$', '', text)
-    text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
-    return text
-
-
-def cjke_cleaners2(text):
-    from vits.text.mandarin import chinese_to_ipa
-    from vits.text.japanese import japanese_to_ipa2
-    from vits.text.korean import korean_to_ipa
-    from vits.text.english import english_to_ipa2
-    text = re.sub(r'\[ZH\](.*?)\[ZH\]',
-                  lambda x: chinese_to_ipa(x.group(1)) + ' ', text)
-    text = re.sub(r'\[JA\](.*?)\[JA\]',
-                  lambda x: japanese_to_ipa2(x.group(1)) + ' ', text)
-    text = re.sub(r'\[KO\](.*?)\[KO\]',
-                  lambda x: korean_to_ipa(x.group(1)) + ' ', text)
-    text = re.sub(r'\[EN\](.*?)\[EN\]',
-                  lambda x: english_to_ipa2(x.group(1)) + ' ', text)
-    text = re.sub(r'\s+$', '', text)
-    text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
-    return text
-
-
-def cje_cleaners(text):
-    from vits.text.mandarin import chinese_to_lazy_ipa
-    from vits.text.japanese import japanese_to_ipa
-    from vits.text.english import english_to_ipa2
-    text = re.sub(r'\[ZH\](.*?)\[ZH\]', lambda x: chinese_to_lazy_ipa(x.group(1)).replace(
-        'ʧ', 'tʃ').replace('ʦ', 'ts').replace('ɥan', 'ɥæn') + ' ', text)
-    text = re.sub(r'\[JA\](.*?)\[JA\]', lambda x: japanese_to_ipa(x.group(1)).replace('ʧ', 'tʃ').replace(
-        'ʦ', 'ts').replace('ɥan', 'ɥæn').replace('ʥ', 'dz') + ' ', text)
-    text = re.sub(r'\[EN\](.*?)\[EN\]', lambda x: english_to_ipa2(x.group(1)).replace('ɑ', 'a').replace(
-        'ɔ', 'o').replace('ɛ', 'e').replace('ɪ', 'i').replace('ʊ', 'u') + ' ', text)
-    text = re.sub(r'\s+$', '', text)
-    text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
-    return text
-
-
-def cje_cleaners2(text):
-    from vits.text.mandarin import chinese_to_ipa
-    from vits.text.japanese import japanese_to_ipa2
-    from vits.text.english import english_to_ipa2
-    text = re.sub(r'\[ZH\](.*?)\[ZH\]',
-                  lambda x: chinese_to_ipa(x.group(1)) + ' ', text)
-    text = re.sub(r'\[JA\](.*?)\[JA\]',
-                  lambda x: japanese_to_ipa2(x.group(1)) + ' ', text)
-    text = re.sub(r'\[EN\](.*?)\[EN\]',
-                  lambda x: english_to_ipa2(x.group(1)) + ' ', text)
-    text = re.sub(r'\s+$', '', text)
-    text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
-    return text
-
-
-def thai_cleaners(text):
-    from vits.text.thai import num_to_thai, latin_to_thai
-
-    def clean(text):
-        text = num_to_thai(text)
-        text = latin_to_thai(text)
-        return text
-
-    text = re.sub(r'\[TH\](.*?)\[TH\]', lambda x: clean(x.group(1)) + ' ', text)
-    return text
-
-
-def shanghainese_cleaners(text):
-    from vits.text.shanghainese import shanghainese_to_ipa
-
-    def clean(text):
-        text = shanghainese_to_ipa(text)
-        text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
-        return text
-
-    text = re.sub(r'\[SH\](.*?)\[SH\]', lambda x: clean(x.group(1)) + ' ', text)
-    return text
-
-
-def chinese_dialect_cleaners(text):
-    from vits.text.mandarin import chinese_to_ipa2
-    from vits.text.japanese import japanese_to_ipa3
-    from vits.text.shanghainese import shanghainese_to_ipa
-    from vits.text.cantonese import cantonese_to_ipa
-    from vits.text.english import english_to_lazy_ipa2
-    from vits.text.ngu_dialect import ngu_dialect_to_ipa
-    text = re.sub(r'\[ZH\](.*?)\[ZH\]',
-                  lambda x: chinese_to_ipa2(x.group(1)) + ' ', text)
-    text = re.sub(r'\[JA\](.*?)\[JA\]',
-                  lambda x: japanese_to_ipa3(x.group(1)).replace('Q', 'ʔ') + ' ', text)
-    text = re.sub(r'\[SH\](.*?)\[SH\]', lambda x: shanghainese_to_ipa(x.group(1)).replace('1', '˥˧').replace('5',
-                                                                                                             '˧˧˦').replace(
-        '6', '˩˩˧').replace('7', '˥').replace('8', '˩˨').replace('ᴀ', 'ɐ').replace('ᴇ', 'e') + ' ', text)
-    text = re.sub(r'\[GD\](.*?)\[GD\]',
-                  lambda x: cantonese_to_ipa(x.group(1)) + ' ', text)
-    text = re.sub(r'\[EN\](.*?)\[EN\]',
-                  lambda x: english_to_lazy_ipa2(x.group(1)) + ' ', text)
-    text = re.sub(r'\[([A-Z]{2})\](.*?)\[\1\]', lambda x: ngu_dialect_to_ipa(x.group(2), x.group(
-        1)).replace('ʣ', 'dz').replace('ʥ', 'dʑ').replace('ʦ', 'ts').replace('ʨ', 'tɕ') + ' ', text)
-    text = re.sub(r'\s+$', '', text)
-    text = re.sub(r'([^\.,!\?\-…~])$', r'\1.', text)
-    return text
-
-
-def bert_chinese_cleaners(text):
-    from vits.text import mandarin
-    matches = re.findall(r"\[ZH\](.*?)\[ZH\]", text)
-    text = "".join(matches)
-    if text[-1] not in [".", "。", ",", "，"]: text += "."
-    text = mandarin.symbols_to_chinese(text)
-    text = mandarin.number_transform_to_chinese(text)
-    if not hasattr(bert_chinese_cleaners, "tts_front"):
-        bert_chinese_cleaners.tts_front = mandarin.VITS_PinYin_model()
-    tts_front = bert_chinese_cleaners.tts_front
-    cleaned_text, char_embeds = tts_front.chinese_to_phonemes(text)
-    return cleaned_text, char_embeds
diff --git a/spaces/zhang-wei-jian/docker/node_modules/has-symbols/shams.js b/spaces/zhang-wei-jian/docker/node_modules/has-symbols/shams.js
deleted file mode 100644
index 1285210ef7ccef1eae88c888694eb481b2d23997..0000000000000000000000000000000000000000
--- a/spaces/zhang-wei-jian/docker/node_modules/has-symbols/shams.js
+++ /dev/null
@@ -1,42 +0,0 @@
-'use strict';
-
-/* eslint complexity: [2, 18], max-statements: [2, 33] */
-module.exports = function hasSymbols() {
-	if (typeof Symbol !== 'function' || typeof Object.getOwnPropertySymbols !== 'function') { return false; }
-	if (typeof Symbol.iterator === 'symbol') { return true; }
-
-	var obj = {};
-	var sym = Symbol('test');
-	var symObj = Object(sym);
-	if (typeof sym === 'string') { return false; }
-
-	if (Object.prototype.toString.call(sym) !== '[object Symbol]') { return false; }
-	if (Object.prototype.toString.call(symObj) !== '[object Symbol]') { return false; }
-
-	// temp disabled per https://github.com/ljharb/object.assign/issues/17
-	// if (sym instanceof Symbol) { return false; }
-	// temp disabled per https://github.com/WebReflection/get-own-property-symbols/issues/4
-	// if (!(symObj instanceof Symbol)) { return false; }
-
-	// if (typeof Symbol.prototype.toString !== 'function') { return false; }
-	// if (String(sym) !== Symbol.prototype.toString.call(sym)) { return false; }
-
-	var symVal = 42;
-	obj[sym] = symVal;
-	for (sym in obj) { return false; } // eslint-disable-line no-restricted-syntax, no-unreachable-loop
-	if (typeof Object.keys === 'function' && Object.keys(obj).length !== 0) { return false; }
-
-	if (typeof Object.getOwnPropertyNames === 'function' && Object.getOwnPropertyNames(obj).length !== 0) { return false; }
-
-	var syms = Object.getOwnPropertySymbols(obj);
-	if (syms.length !== 1 || syms[0] !== sym) { return false; }
-
-	if (!Object.prototype.propertyIsEnumerable.call(obj, sym)) { return false; }
-
-	if (typeof Object.getOwnPropertyDescriptor === 'function') {
-		var descriptor = Object.getOwnPropertyDescriptor(obj, sym);
-		if (descriptor.value !== symVal || descriptor.enumerable !== true) { return false; }
-	}
-
-	return true;
-};
diff --git a/spaces/zoeozone/mrm8488-Alpacoom/app.py b/spaces/zoeozone/mrm8488-Alpacoom/app.py
deleted file mode 100644
index d7d82bdf30b7771392855ebe2fb4294cc9c9d56e..0000000000000000000000000000000000000000
--- a/spaces/zoeozone/mrm8488-Alpacoom/app.py
+++ /dev/null
@@ -1,3 +0,0 @@
-import gradio as gr
-
-gr.Interface.load("models/mrm8488/Alpacoom").launch()
\ No newline at end of file
diff --git a/spaces/zswvivi/ChineseMedicalT5/README.md b/spaces/zswvivi/ChineseMedicalT5/README.md
deleted file mode 100644
index 75dad912c1aa836c46d34b7f7589adc825263a6f..0000000000000000000000000000000000000000
--- a/spaces/zswvivi/ChineseMedicalT5/README.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: ChineseMedicalT5
-emoji: 👁
-colorFrom: gray
-colorTo: yellow
-sdk: gradio
-sdk_version: 3.9.1
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference